axz91 commited on
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Parent(s): 31fb99a
UPDATE
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- puc/10309591.pdf +529 -0
- puc/10334487.pdf +529 -0
- puc/10338377.pdf +529 -0
- puc/10346901.pdf +529 -0
- puc/10359595.pdf +529 -0
- puc/10379198.pdf +529 -0
- puc/10390025.pdf +529 -0
- puc/PMC10000982.txt +307 -0
- puc/PMC10001138.txt +254 -0
- puc/PMC10002489.txt +429 -0
- puc/PMC10003152.txt +225 -0
- puc/PMC10003660.txt +297 -0
- puc/PMC10005707.txt +331 -0
- puc/PMC10017542.txt +308 -0
- puc/PMC10019655.txt +0 -0
- puc/PMC10045348.txt +332 -0
- puc/PMC10045570.txt +350 -0
- puc/PMC10047974.txt +256 -0
- puc/PMC10052724.txt +281 -0
- puc/PMC10055201.txt +349 -0
- puc/PMC10066626.txt +36 -0
- puc/PMC10069774.txt +478 -0
- puc/PMC10071559.txt +233 -0
- puc/PMC10076305.txt +259 -0
- puc/PMC10077699.txt +422 -0
- puc/PMC10078291.txt +0 -0
- puc/PMC10081256.txt +30 -0
- puc/PMC10092757.txt +329 -0
- puc/PMC10093881.txt +230 -0
- puc/PMC10135657.txt +261 -0
- puc/PMC10138341.txt +298 -0
- puc/PMC10138540.txt +227 -0
- puc/PMC10138945.txt +232 -0
- puc/PMC10147829.txt +348 -0
- puc/PMC10149209.txt +308 -0
- puc/PMC10164900.txt +268 -0
- puc/PMC10171860.txt +0 -0
- puc/PMC10172585.txt +220 -0
- puc/PMC10173662.txt +314 -0
- puc/PMC10183792.txt +204 -0
- puc/PMC10202359.txt +314 -0
- puc/PMC10209870.txt +423 -0
- puc/PMC10216179.txt +322 -0
- puc/PMC10216850.txt +264 -0
- puc/PMC10216952.txt +0 -0
- puc/PMC10218173.txt +59 -0
- puc/PMC10232201.txt +320 -0
- puc/PMC10232613.txt +65 -0
- puc/PMC10252591.txt +277 -0
- puc/PMC10253796.txt +271 -0
puc/10309591.pdf
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| 384 |
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| 401 |
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| 402 |
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| 424 |
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| 426 |
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| 427 |
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<p class="address_footer text-white">National Library of Medicine<br>
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| 428 |
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<a href="https://www.google.com/maps/place/8600+Rockville+Pike,+Bethesda,+MD+20894/@38.9959508,-77.101021,17z/data=!3m1!4b1!4m5!3m4!1s0x89b7c95e25765ddb:0x19156f88b27635b8!8m2!3d38.9959508!4d-77.0988323"
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| 430 |
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Bethesda, MD 20894</a></p>
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| 431 |
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| 432 |
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| 433 |
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<p><a href="https://www.nlm.nih.gov/web_policies.html" class="text-white">Web Policies</a><br>
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| 434 |
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| 435 |
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class="text-white">FOIA</a><br>
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| 436 |
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| 437 |
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| 438 |
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<div class="col-lg-3 col-12 centered-lg">
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| 439 |
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| 440 |
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<a href="https://www.nlm.nih.gov/accessibility.html" class="text-white">Accessibility</a><br>
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| 441 |
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<a href="https://www.nlm.nih.gov/careers/careers.html" class="text-white">Careers</a></p>
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| 442 |
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</div>
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| 443 |
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| 444 |
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| 445 |
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| 448 |
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<a class="text-white" href="//www.nlm.nih.gov/">NLM</a>
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| 450 |
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</li>
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| 452 |
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<a class="text-white"
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| 453 |
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href="https://www.nih.gov/">NIH</a>
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| 454 |
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| 455 |
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<li>
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| 456 |
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<a class="text-white" href="https://www.hhs.gov/">HHS</a>
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| 458 |
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| 459 |
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<a
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| 462 |
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| 466 |
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| 469 |
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| 470 |
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| 493 |
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| 494 |
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| 495 |
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| 528 |
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</body>
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| 529 |
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</html>
|
puc/10334487.pdf
ADDED
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|
| 333 |
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</a>
|
| 334 |
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| 335 |
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|
| 336 |
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|
| 337 |
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|
| 338 |
+
<section class="container-fluid bg-primary">
|
| 339 |
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<div class="container pt-5">
|
| 340 |
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<div class="row mt-3">
|
| 341 |
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<div class="col-lg-3 col-12">
|
| 342 |
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<p><a class="text-white" href="https://www.nlm.nih.gov/socialmedia/index.html">Connect with NLM</a></p>
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| 343 |
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<ul class="list-inline social_media">
|
| 344 |
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<li class="list-inline-item"><a href="https://twitter.com/NLM_NIH" aria-label="Twitter"
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| 374 |
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| 375 |
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| 376 |
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| 383 |
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| 384 |
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| 386 |
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| 387 |
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| 388 |
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| 389 |
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| 390 |
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| 392 |
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| 398 |
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| 399 |
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<li class="list-inline-item"><a href="https://www.youtube.com/user/NLMNIH" aria-label="Youtube"
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| 401 |
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| 402 |
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| 403 |
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| 404 |
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<title>SM-Youtube</title>
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| 411 |
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| 421 |
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| 423 |
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| 424 |
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</ul>
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| 425 |
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| 426 |
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<div class="col-lg-3 col-12">
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| 427 |
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<p class="address_footer text-white">National Library of Medicine<br>
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| 428 |
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<a href="https://www.google.com/maps/place/8600+Rockville+Pike,+Bethesda,+MD+20894/@38.9959508,-77.101021,17z/data=!3m1!4b1!4m5!3m4!1s0x89b7c95e25765ddb:0x19156f88b27635b8!8m2!3d38.9959508!4d-77.0988323"
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class="text-white" target="_blank" rel="noopener noreferrer">8600 Rockville Pike<br>
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| 430 |
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Bethesda, MD 20894</a></p>
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| 431 |
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</div>
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| 432 |
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<div class="col-lg-3 col-12 centered-lg">
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| 433 |
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<p><a href="https://www.nlm.nih.gov/web_policies.html" class="text-white">Web Policies</a><br>
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| 434 |
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<a href="https://www.nih.gov/institutes-nih/nih-office-director/office-communications-public-liaison/freedom-information-act-office"
|
| 435 |
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class="text-white">FOIA</a><br>
|
| 436 |
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<a href="https://www.hhs.gov/vulnerability-disclosure-policy/index.html" class="text-white" id="vdp">HHS Vulnerability Disclosure</a></p>
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| 437 |
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</div>
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| 438 |
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<div class="col-lg-3 col-12 centered-lg">
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| 439 |
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|
| 440 |
+
<a href="https://www.nlm.nih.gov/accessibility.html" class="text-white">Accessibility</a><br>
|
| 441 |
+
<a href="https://www.nlm.nih.gov/careers/careers.html" class="text-white">Careers</a></p>
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| 442 |
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</div>
|
| 443 |
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</div>
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| 444 |
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<div class="row">
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| 445 |
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| 446 |
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| 447 |
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<ul class="mt-3">
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| 448 |
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<li>
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| 449 |
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<a class="text-white" href="//www.nlm.nih.gov/">NLM</a>
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| 450 |
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</li>
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<li>
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| 452 |
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<a class="text-white"
|
| 453 |
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href="https://www.nih.gov/">NIH</a>
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| 454 |
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</li>
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| 455 |
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<li>
|
| 456 |
+
<a class="text-white" href="https://www.hhs.gov/">HHS</a>
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| 457 |
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| 458 |
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<li>
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| 459 |
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<a
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| 460 |
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class="text-white" href="https://www.usa.gov/">USA.gov</a>
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| 462 |
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| 464 |
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| 466 |
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| 467 |
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</section>
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| 469 |
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| 470 |
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| 492 |
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| 493 |
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| 494 |
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<!-- JavaScript -->
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| 495 |
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<script src="/pmc/static/CACHE/js/output.0f72d6a64937.js"></script>
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| 497 |
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| 527 |
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| 528 |
+
</body>
|
| 529 |
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</html>
|
puc/10346901.pdf
ADDED
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| 449 |
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<a class="text-white" href="//www.nlm.nih.gov/">NLM</a>
|
| 450 |
+
</li>
|
| 451 |
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<li>
|
| 452 |
+
<a class="text-white"
|
| 453 |
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href="https://www.nih.gov/">NIH</a>
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| 454 |
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|
| 455 |
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<li>
|
| 456 |
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<a class="text-white" href="https://www.hhs.gov/">HHS</a>
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| 457 |
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| 458 |
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<li>
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| 459 |
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<a
|
| 460 |
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class="text-white" href="https://www.usa.gov/">USA.gov</a>
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| 494 |
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puc/10359595.pdf
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|
| 1 |
+
<!DOCTYPE html>
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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<html lang="en" >
|
| 7 |
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<head >
|
| 8 |
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| 9 |
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<p class="address_footer text-white">National Library of Medicine<br>
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<a href="https://www.google.com/maps/place/8600+Rockville+Pike,+Bethesda,+MD+20894/@38.9959508,-77.101021,17z/data=!3m1!4b1!4m5!3m4!1s0x89b7c95e25765ddb:0x19156f88b27635b8!8m2!3d38.9959508!4d-77.0988323"
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puc/10379198.pdf
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<div class="col-lg-3 col-12 centered-lg">
|
| 433 |
+
<p><a href="https://www.nlm.nih.gov/web_policies.html" class="text-white">Web Policies</a><br>
|
| 434 |
+
<a href="https://www.nih.gov/institutes-nih/nih-office-director/office-communications-public-liaison/freedom-information-act-office"
|
| 435 |
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class="text-white">FOIA</a><br>
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| 436 |
+
<a href="https://www.hhs.gov/vulnerability-disclosure-policy/index.html" class="text-white" id="vdp">HHS Vulnerability Disclosure</a></p>
|
| 437 |
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</div>
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| 438 |
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<div class="col-lg-3 col-12 centered-lg">
|
| 439 |
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<p><a class="supportLink text-white" href="https://support.nlm.nih.gov/">Help</a><br>
|
| 440 |
+
<a href="https://www.nlm.nih.gov/accessibility.html" class="text-white">Accessibility</a><br>
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| 441 |
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<a href="https://www.nlm.nih.gov/careers/careers.html" class="text-white">Careers</a></p>
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| 442 |
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</div>
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| 443 |
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| 444 |
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<div class="row">
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| 445 |
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<div class="col-lg-12 centered-lg">
|
| 446 |
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<nav class="bottom-links">
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| 447 |
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<ul class="mt-3">
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| 448 |
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<li>
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| 449 |
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<a class="text-white" href="//www.nlm.nih.gov/">NLM</a>
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| 450 |
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</li>
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| 451 |
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<li>
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| 452 |
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<a class="text-white"
|
| 453 |
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href="https://www.nih.gov/">NIH</a>
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| 454 |
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</li>
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<li>
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| 456 |
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<a class="text-white" href="https://www.hhs.gov/">HHS</a>
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| 458 |
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<li>
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| 459 |
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<a
|
| 460 |
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class="text-white" href="https://www.usa.gov/">USA.gov</a>
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<script type="text/javascript">
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| 495 |
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<script src="/pmc/static/CACHE/js/output.0f72d6a64937.js"></script>
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puc/10390025.pdf
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|
| 1 |
+
<!DOCTYPE html>
|
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|
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<html lang="en" >
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<p class="address_footer text-white">National Library of Medicine<br>
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<a href="https://www.google.com/maps/place/8600+Rockville+Pike,+Bethesda,+MD+20894/@38.9959508,-77.101021,17z/data=!3m1!4b1!4m5!3m4!1s0x89b7c95e25765ddb:0x19156f88b27635b8!8m2!3d38.9959508!4d-77.0988323"
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class="text-white" target="_blank" rel="noopener noreferrer">8600 Rockville Pike<br>
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Bethesda, MD 20894</a></p>
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<a href="https://www.nih.gov/institutes-nih/nih-office-director/office-communications-public-liaison/freedom-information-act-office"
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| 435 |
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class="text-white">FOIA</a><br>
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| 436 |
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<a href="https://www.hhs.gov/vulnerability-disclosure-policy/index.html" class="text-white" id="vdp">HHS Vulnerability Disclosure</a></p>
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| 438 |
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<div class="col-lg-3 col-12 centered-lg">
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<a href="https://www.nlm.nih.gov/accessibility.html" class="text-white">Accessibility</a><br>
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<a class="text-white" href="//www.nlm.nih.gov/">NLM</a>
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<a class="text-white"
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| 456 |
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<a class="text-white" href="https://www.hhs.gov/">HHS</a>
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| 495 |
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| 528 |
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</body>
|
| 529 |
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</html>
|
puc/PMC10000982.txt
ADDED
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Foods
|
| 4 |
+
Foods
|
| 5 |
+
foods
|
| 6 |
+
Foods
|
| 7 |
+
2304-8158
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
10.3390/foods12051014
|
| 11 |
+
foods-12-01014
|
| 12 |
+
Article
|
| 13 |
+
Inhibitory Effect of Isopanduratin A on Adipogenesis: A Study of Possible Mechanisms
|
| 14 |
+
Rungsa Prapenpuksiri Investigation Data curation Writing – original draft 1
|
| 15 |
+
https://orcid.org/0000-0002-3547-1940
|
| 16 |
+
San Htoo Tint Methodology 1
|
| 17 |
+
https://orcid.org/0000-0001-8352-4122
|
| 18 |
+
Sritularak Boonchoo Methodology 12
|
| 19 |
+
Böttcher Chotima Methodology 34
|
| 20 |
+
https://orcid.org/0000-0001-7565-9211
|
| 21 |
+
Prompetchara Eakachai Methodology Software 56
|
| 22 |
+
Chaotham Chatchai Conceptualization Formal analysis Resources Data curation Writing – original draft Writing – review & editing Supervision Project administration Funding acquisition 78*
|
| 23 |
+
https://orcid.org/0000-0002-0861-7617
|
| 24 |
+
Likhitwitayawuid Kittisak Conceptualization Resources Writing – original draft Writing – review & editing Supervision Project administration Funding acquisition 1*
|
| 25 |
+
Castilho Paula C. Academic Editor
|
| 26 |
+
Wang Weiqun Academic Editor
|
| 27 |
+
1 Department of Pharmacognosy and Pharmaceutical Botany, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok 10330, Thailand
|
| 28 |
+
2 Center of Excellence in Natural Products for Ageing and Chronic Diseases, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok 10330, Thailand
|
| 29 |
+
3 Experimental and Clinical Research Center, a Cooperation between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité–Universitätsmedizin Berlin, 13125 Berlin, Germany
|
| 30 |
+
4 Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 13125 Berlin, Germany
|
| 31 |
+
5 Department of Laboratory Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
|
| 32 |
+
6 Center of Excellence in Vaccine Research and Development (Chula Vaccine Research Center), Faculty of Medicine, Chulalongkorn University, Bangkok 10330, Thailand
|
| 33 |
+
7 Department of Biochemistry and Microbiology, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok 10330, Thailand
|
| 34 |
+
8 Preclinical Toxicity and Efficacy Assessment of Medicines and Chemicals Research Unit, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok 10330, Thailand
|
| 35 |
+
* Correspondence: chatchai.c@chula.ac.th (C.C.); kittisak.l@chula.ac.th (K.L.)
|
| 36 |
+
27 2 2023
|
| 37 |
+
3 2023
|
| 38 |
+
12 5 101429 1 2023
|
| 39 |
+
21 2 2023
|
| 40 |
+
25 2 2023
|
| 41 |
+
© 2023 by the authors.
|
| 42 |
+
2023
|
| 43 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 44 |
+
The root of Boesenbergia rotunda, a culinary plant commonly known as fingerroot, has previously been reported to possess anti-obesity activity, with four flavonoids identified as active principles, including pinostrobin, panduratin A, cardamonin, and isopanduratin A. However, the molecular mechanisms underlying the antiadipogenic potential of isopanduratin A remain unknown. In this study, isopanduratin A at non-cytotoxic concentrations (1–10 μM) significantly suppressed lipid accumulation in murine (3T3-L1) and human (PCS-210-010) adipocytes in a dose-dependent manner. Downregulation of adipogenic effectors (FAS, PLIN1, LPL, and adiponectin) and adipogenic transcription factors (SREBP-1c, PPARγ, and C/EBPα) occurred in differentiated 3T3-L1 cells treated with varying concentrations of isopanduratin A. The compound deactivated the upstream regulatory signals of AKT/GSK3β and MAPKs (ERK, JNK, and p38) but stimulated the AMPK-ACC pathway. The inhibitory trend of isopanduratin A was also observed with the proliferation of 3T3-L1 cells. The compound also paused the passage of 3T3-L1 cells by inducing cell cycle arrest at the G0/G1 phase, supported by altered levels of cyclins D1 and D3 and CDK2. Impaired p-ERK/ERK signaling might be responsible for the delay in mitotic clonal expansion. These findings revealed that isopanduratin A is a strong adipogenic suppressor with multi-target mechanisms and contributes significantly to anti-obesogenic activity. These results suggest the potential of fingerroot as a functional food for weight control and obesity prevention.
|
| 45 |
+
|
| 46 |
+
fingerroot
|
| 47 |
+
Boesenbergia rotunda
|
| 48 |
+
obesity
|
| 49 |
+
adipocyte
|
| 50 |
+
isopanduratin A
|
| 51 |
+
AKT/GSK3β
|
| 52 |
+
AMPK-ACC
|
| 53 |
+
MAPKs
|
| 54 |
+
MCE
|
| 55 |
+
the Thailand Science Research and Innovation Fund, Chulalongkorn UniversityCU_FRB65_hea (60)_069_33_13 the Ratchadaphiseksomphot Endowment Fund, Chulalongkorn UniversityRCU_H_64_028_33 This research was funded by the Thailand Science Research and Innovation Fund, Chulalongkorn University (grant number: CU_FRB65_hea (60)_069_33_13), and the Ratchadaphiseksomphot Endowment Fund, Chulalongkorn University (grant number: RCU_H_64_028_33).
|
| 56 |
+
==== Body
|
| 57 |
+
pmc1. Introduction
|
| 58 |
+
|
| 59 |
+
With the steady increase in the number of overweight and obese populations in recent years, obesity has been declared a pandemic disease by the World Health Organization (WHO) [1]. Obesity is the result of an energy imbalance, characterized by excessive fat accumulation in the body. This irregularity, though a non-communicable disorder, is closely associated with several metabolic conditions, such as hyperglycemia, hyperlipidemia, hypertension, cancer, and cardiovascular diseases, all of which have a high mortality rate and can cause a socioeconomic burden, particularly in countries where access to the healthcare system is limited [2].
|
| 60 |
+
|
| 61 |
+
Modulation of the excess mass of adipose tissues due to hyperplasia (excessive adipogenesis) and the hypertrophy of adipocytes is one of the reasonable strategies to regulate lipid homeostasis and obesity. Recently, inhibition of adipogenic differentiation and maturation has become a novel therapeutic approach to treating obesity [3]. Adipogenesis, a multistep process that converts undifferentiated preadipocytes into mature adipocytes, is modulated by a series of biochemical cascades that include coordinated changes in hormone sensitivity and gene expression, together with morphological alterations. Triggered by adipogenic stimulants, preadipocytes undergo mitotic clonal expansion (MCE) to re-enter the cell cycle. Concurrently, the upregulation of adipogenic regulating genes and adipogenic effector proteins leads to adipocyte differentiation and maturation [4,5,6,7].
|
| 62 |
+
|
| 63 |
+
Adipocyte differentiation and development are directed by lipogenesis-related transcription factors such as CCAAT/enhancer-binding protein alpha (C/EBPα), peroxisome proliferator-activated receptor gamma (PPARγ), sterol response element-binding protein-1c (SREBP-1c) [8,9], and the adenosine monophosphate-activated protein kinase (AMPK) and acetyl-CoA carboxylase (ACC) enzymes [10]. AMPK, a serine/threonine kinase, forms a heterotrimeric complex with one catalytic α subunit and two regulatory β and γ subunits [11]. Its roles in cellular lipid metabolism involve the synthesis and degradation of fatty acids. Another upstream regulatory molecule in adipocyte differentiation is protein kinase B (AKT), as its activation strongly links to the upregulation of SREBP-1c and cellular lipogenesis [12]. Subsequent phosphorylation of glycogen synthase kinase 3β (GSK3β) by AKT upregulates C/EBPα and promotes adipocyte maturation [13]. Additionally, mitogen-activated protein kinases (MAPKs), including c-Jun N-terminal kinase (JNK), extracellular signal-regulated kinase (ERK), and stress-activated protein kinase (p38), mediate adipogenesis [14]. Suppression of these signaling molecules efficiently inhibits adipocyte differentiation [15,16]. For example, inhibition of p38 function can hamper adipocyte differentiation by suppressing PPARγ transcription. Modulation of these biomolecules during adipocyte differentiation proved to be a promising strategy to limit cellular lipogenesis and adipocyte differentiation and maturation [17].
|
| 64 |
+
|
| 65 |
+
Recently, a growing body of evidence has revealed medicinal and culinary plants as a rich source of phytochemicals that exert their anti-obesity potential through multi-target mechanisms [18,19,20]. Boesenbergia rotunda (L.) Mansf., also known as Boesenbergia pandurata (Roxb.) Schltr., is commonly called fingerroot. The plant is found in the wild and is widely cultivated in South Asia and Southeast Asia [21,22]. Traditionally, people use its roots as food and flavoring agents. In Thailand, they are the main ingredient in shrimp soup, which is popularly consumed by lactating women to help improve their breast milk supply. Various medicinal values for fingerroot were reported, including anti-inflammatory, antimicrobial, antiviral [21,22,23,24], anti-obesity [25], anti-osteoporosis [26], and anticancer activities [27], as well as aphrodisiac and vasorelaxant effects [28]. The bioactive constituents were characterized as several subclasses of flavonoids [29,30].
|
| 66 |
+
|
| 67 |
+
In a recent study, the anti-obesity activity of fingerroot was demonstrated in mice on a high-fat diet [31]. Our previous phytochemical study of the roots of this plant revealed the presence of several flavonoids, along with a monoterpene alcohol and a styrylpyrone [32]. In a preliminary Oil Red O assay, we found that the flavonoids pinostrobin, panduratin A, isopanduratin A, and cardamonin were strong adipogenic inhibitors, which may be responsible for the anti-obesity activity of fingerroot (see Section 3.1). In our previous study, pinostrobin was shown to inhibit adipogenesis in murine 3T3-L1 preadipocytes by lowering the levels of lipid-metabolism-mediating proteins, such as C/EBPα, PPARγ, and SREBP-1c, and suppressing the signals of MAPKs (p38 and JNK) and AKT (AKT/GSK3β and AKT/AMPKα-ACC) [33]. The other flavonoids, i.e., panduratin A and cardamonin, were previously investigated for the molecular mechanisms underlying their anti-adipogenic effects in 3T3-L1 cells [25,34,35]. In this study, we report the inhibitory effects of isopanduratin A, another fingerroot flavonoid, on adipogenesis in mouse 3T3-L1 and human PCS-210-010 preadipocytes. The relevant molecular mechanisms are also elucidated and addressed.
|
| 68 |
+
|
| 69 |
+
2. Materials and Methods
|
| 70 |
+
|
| 71 |
+
2.1. Chemicals, Reagents, and Culture Media
|
| 72 |
+
|
| 73 |
+
Isopanduratin A and other phytochemicals were isolated and characterized from B. rotunda roots with a protocol described previously [32]. The purity of these phytochemicals was more than 98% (by NMR). Dimethyl sulfoxide (DMSO), Oil Red O, crystal violet, isobutylmethylxanthine (IBMX), dexamethasone, isopropanol, RNase A, and skim milk powder were purchased from Sigma-Aldrich (St. Louis, MO, USA). Ethanol, methanol, formaldehyde, and chloroform were ordered from Merck KgaA (Darmstadt, Germany). Dulbecco’s Modified Eagle Medium (DMEM), fetal bovine serum (FBS), penicillin/streptomycin solution, l-glutamine, and trypsin were bought from Gibco (Gaithersburg, MA, USA). Fibroblast basal medium (FBM) was purchased from the American Type Culture Collection (ATCC; Manassas, VA, USA). Insulin was ordered from Himedia (Mumbai, India). Bicinchoninic acid (BCA) protein assay kit, western chemiluminescent ECL substrate, and radio-immunoprecipitation assay (RIPA) buffer were acquired from Thermo-Fisher (Rockford, IL, USA). A protease inhibitor cocktail was obtained from Roche Applied Science (Indianapolis, IN, USA). Primary antibodies against β-actin (Cat. No. 4970; dilution 1:1000), Cyclin D1 (Cat. No. 2978; dilution 1:1000), Cyclin D3 (Cat. No. 2936; dilution 1:2000), CDK2 (Cat. No. 2546; dilution 1:1000), AKT (Cat. No. 4691; dilution 1:1000), p-AKT (Ser473) (Cat. No. 4060; dilution 1:2000), GSK3β (Cat. No. 12456; dilution 1:1000), p-GSK3β (Ser9) (Cat. No. 9322; dilution 1:1000), AMPKα (Cat. No. 5831; dilution 1:1000), p-AMPKα (Thr172) (Cat. No. 2535; dilution 1:1000), AMPKβ1/2 (Cat. No. 4150; dilution 1:1000), p-AMPKβ1 (Ser182) (Cat. No. 4186; dilution 1:1000), ACC (Cat. No. 3676; dilution 1:1000), p-ACC (Ser79) (Cat. No. 11818; dilution 1:1000), PPARγ (Cat. No. 2435; dilution 1:1000), C/EBPα (Cat. No. 8178; dilution 1:1000), FAS (Cat. No. 3180; dilution 1:1000), PLIN1 (Cat. No. 9349; dilution 1:1000), adiponectin (Cat. No. 2789; dilution 1:1000), ERK1/2 (Cat. No. 9102; dilution 1:1000), p-ERK1/2 (Thr202/Tyr204) (Cat. No. 4695; dilution 1:1000), JNK (Cat. No. 9252; dilution 1:1000), p-JNK (Thr183/Tyr185) (Cat. No. 9251; dilution 1:1000), p38 (Cat. No. 8690; dilution 1:1000), p-p38 (Thr180/Tyr182) (Cat. No. 4511; dilution 1:1000), and horseradish peroxidase (HRP)-linked secondary antibodies (Cat. No. 7074; dilution 1:2000) were purchased from Cell Signaling Technology (Danvers, MA, USA). Specific primary antibodies against SREBP-1c (Cat. No. PA1-337; dilution 1:1000) and LPL (Cat. No. PA5-85126; dilution 1:1000) were acquired from Invitrogen (Waltham, MA, USA).
|
| 74 |
+
|
| 75 |
+
2.2. Cell Culture and Adipocyte Differentiation
|
| 76 |
+
|
| 77 |
+
Human PCS-210-010 preadipocyte and mouse embryonic preadipocyte 3T3-L1 cells obtained from the American Type Culture Collection (ATCC; Manassas, VA, USA) were, respectively, cultured in FBM and DMEM containing 10% FBS, 100 units/mL of penicillin/streptomycin, and 2 mmol/L of l-glutamine under humidified conditions of 5% CO2 at 37 °C. For a differentiation program to convert preadipocytes to adipocytes, preadipocytes growing as monolayers up to 90% confluent for 2 days were exposed to a differentiation medium made of FBM or DMEM containing 10% FBS, 0.5 mM IBMX, 1 μM dexamethasone, and 5 μg/mL insulin for 2 days. At this stage, various concentrations of isopanduratin A were added, while 0.5% (v/v) DMSO was used as vehicle control. The differentiation medium was replaced with culture medium supplemented with 5 μg/mL of insulin. After further incubation for 2 days, cells were maintained in complete medium, which was changed every 2 days until lipid-droplet-containing adipocytes were observed under the microscope. Undifferentiated and differentiated cells were defined as negative control and positive control groups, respectively.
|
| 78 |
+
|
| 79 |
+
2.3. Cytotoxicity Assay
|
| 80 |
+
|
| 81 |
+
Following the recommended course of action, the cytotoxicity of isopanduratin A was evaluated using a crystal violet colorimetric assay [33]. Cells were seeded in a 96-well plate at a density of 1 × 104 cells/well and incubated under humidified 5% CO2 at 37 °C overnight and then exposed for 48 h to isopanduratin A in a range of final concentrations (0–100 μM). A vehicle control (0.5% (v/v) DMSO) was also included. Dead detached cells were removed after washing twice with phosphate buffer saline (PBS; pH 7.4). The adherently viable cells were then stained with crystal violet solution (0.05% w/v) for 30 min at room temperature after being fixed with 10% w/v formic aldehyde for 30 min. The assayed plate was washed twice with deionized water to remove any excess crystal violet solution and then left to dry overnight. The stained cells were treated with 100 μL of methanol prior to absorbance measurement (570 nm) with a microplate reader (Anthros, Durham, NC, USA). The percentage of cell viability was calculated using the absorbance value of each treatment relative to that of the vehicle control.
|
| 82 |
+
|
| 83 |
+
2.4. Cell Proliferation Assay and Cell Cycle Analysis
|
| 84 |
+
|
| 85 |
+
The ability of 3T3-L1 cells to proliferate in the presence of isopanduratin A at its non-cytotoxic doses for 24–72 h was investigated by crystal violet staining [33,36]. 3T3-L1 cells (3.5 × 103 cells/well in a 96-well plate) growing as a monolayer for 2 days were exposed to differentiation medium containing varying concentrations of isopanduratin A (0–10 μM) and incubated for 24, 48, and 72 h. A vehicle (0.5% (v/v) DMSO) was also included. At the end of each incubation period, the crystal violet staining assay was carried out as described previously, and the ability of cells to proliferate was calculated and reported as the percentage of cell proliferation in each treatment relative to that of the vehicle control measured at 24 h.
|
| 86 |
+
|
| 87 |
+
The impact of isopanduratin A on the passage of 3T3-L1 cells through the cell cycle was analyzed by flow cytometry. Cells seeded in a 6-well plate and at 90% confluent of their growth were treated with non-cytotoxic doses of isopanduratin A for 18 h. Undifferentiated or differentiated control cells were established by exposure to 0.5% (v/v) DMSO. Cells in each treatment and control were harvested by centrifugation for 5 min at 2500× g and 4 °C and then fixed overnight in 1 mL of ice-cold 70% (v/v) ethanol at −20 °C. The fixed cells were washed with PBS (pH 7.4), stained with 50 μg/mL PI solution (400 μL) containing 5 μg/mL DNase-free RNase solution for 30 min at room temperature, and kept away from light. DNA content was analyzed by flow cytometry (EMD Millipore, Austin, TX, USA). The percentages of cells in the G0/G1, S, and G2/M phases were then calculated using the FlowJo V10 software trial version (Williamson Way, Ashland, OR, USA).
|
| 88 |
+
|
| 89 |
+
2.5. Assessment of Cellular Lipid Content
|
| 90 |
+
|
| 91 |
+
The impact of isopanduratin A, at varying non-toxic doses, on the formation of lipid droplets in 3T3-L1 and PCS-210-010 adipocytes was evaluated by the Oil Red O staining assay. Both adipocytic cells undergoing the differentiation program, as described previously, were fixed with 10% formaldehyde for 30 min at room temperature, and then the fixed cells were stained with Oil Red O solution (at an Oil Red O:distilled water ratio of 6:4) for 1 h at room temperature. The stained cells were washed twice with 60% (v/v) isopropanol and randomly photographed under an inverted light microscope (Nikon Ts2, Tokyo, Japan). Intracellular Oil Red O-stained lipid droplets were eluted using 100% isopropanol, and their absorbance values at 500 nm wavelength were measured using a microplate reader (Anthros, Durham, NC, USA).
|
| 92 |
+
|
| 93 |
+
The effects of isopanduratin A at varying non-cytotoxic doses on cellular triglyceride and released glycerol levels were also determined, respectively, using triglyceride and glycerol assay kits (Sigma Aldrich, St. Louis, MO, USA), in accordance with the instructions of the manufacturer. Undifferentiated or differentiated cells treated with DMSO (0.5% v/v) functioned as controls for each experiment.
|
| 94 |
+
|
| 95 |
+
2.6. Western Blotting
|
| 96 |
+
|
| 97 |
+
The effects of isopanduratin A (0–10 μM) on the expression of proteins related to adipogenesis after 48 h of incubation were tracked by western blot analysis. Undifferentiated and differentiated 3T3-L1 cells treated with DMSO (0.5% v/v) functioned as controls. Cells were collected and lysed on ice in RIPA buffer supplemented with a protease inhibitor cocktail for 45 min. Cell lysates were quantified for protein concentration using the BCA assay and stored at −80 °C until further use. Equal protein samples (30 μg) were loaded to separate on 10% SDS-PAGE and transferred onto a nitrocellulose membrane (BIO-RAD, Hercules, CA, USA). The membranes were blocked in 5% skim milk for 1 h at room temperature and incubated overnight with primary antibodies at 4 °C. The membranes were then washed (7 min × 3 times) with Tris-buffered saline with 0.1% Tween® 20 (TBST) before incubation with HRP-conjugated secondary antibody for 2 h at room temperature. The membranes were washed 3 times with TBST to remove excess antibodies and detected using western chemiluminescent ECL substrates. The protein expression level was calculated as the ratio of the band intensity of the target protein to that of β-actin—a housekeeping protein.
|
| 98 |
+
|
| 99 |
+
2.7. Reverse Transcription-Quantitative Polymerase Chain Reaction (RT-qPCR)
|
| 100 |
+
|
| 101 |
+
The impact of isopanduratin A on the expression of some proteins involved in the differentiation of 3T3-L1 adipocytes was confirmed at the transcriptional level using the RT-qPCR technique. 3T3-L1 preadipocytes (5 × 104 cells/well in a 6-well plate) with up to 90% confluent were treated with varying non-cytotoxic doses of isopanduratin A for 2 days in differentiation medium. Undifferentiated and differentiated 3T3-L1 cells treated with DMSO (0.5% (v/v) functioned as controls for this study. The medium was removed, and the cells were rinsed thrice with ice-cold PBS (pH 7.4) and extracted for their RNA using the PureLink™ RNA Mini Kit (Invitrogen, Carisbad, CA, USA). An equal amount (1 μg) of total RNA was reverse-transcribed to complementary DNA with a RevertAid first-strand cDNA synthesis kit (Thermo Scientific Pierce, Rockford, IL, USA). The Bio-Rad Luna Universal qPCR master mix (Hercules, CA, USA) was used in the assay reaction, while amplification was performed with the Bio-Rad CFX96 Touch real-time PCR detection system (Hercules, CA, USA), in accordance with the instructions of the manufacturer. The RT-qPCR primers (Table 1) and conditions were previously described elsewhere [36]. The expression level of each target gene was normalized with that of Gapdh—a housekeeping gene. Relative mRNA expression levels were analyzed using the 2−(ave.∆∆CT) method, where CT is the threshold cycle.
|
| 102 |
+
|
| 103 |
+
2.8. Statistical Analysis
|
| 104 |
+
|
| 105 |
+
All experiments were carried out in triplicate, and the results are expressed as mean ± standard deviation (SD). Statistical comparison of means by one-way analysis of variance (ANOVA) with Tukey’s post hoc test was performed using GraphPad Prism 8.0.2 software (San Diego, CA, USA). A p-value of <0.05 was considered statistically significant.
|
| 106 |
+
|
| 107 |
+
3. Results
|
| 108 |
+
|
| 109 |
+
3.1. Effect of Isopanduratin A on Adipogenesis in 3T3-L1 Preadipocytes
|
| 110 |
+
|
| 111 |
+
In this study, murine 3T3-L1 preadipocyte cells, which can differentiate into mature adipocytes under appropriate conditions [4,37], were used. Initially, the toxicity of each test compound was evaluated at 5 μM by a crystal violet assay, as previously described [33]. At this concentration, pinostrobin (1), panduratin A (3), isopanduratin A (4), and cardamonin (6) were all non-toxic and showed a significant reduction in intracellular lipid content in the Oil Red O staining assay (Table 2), suggesting their anti-adipogenic potential. Isopanduratin A showed a drop in the percentage of stained cells to approximately 60%, compared to the vehicle control. The cytotoxic effect of isopanduratin A was then further assessed in a wider range of concentrations (0–100 μM). The highest non-toxic dose was found to be 10 μM, and the half-maximum inhibitory concentration was 28.63 ± 0.70 μM.
|
| 112 |
+
|
| 113 |
+
The dose-dependent effect of isopanduratin A on 3T3-L1 adipocyte differentiation was then further examined by measuring the accumulation of cellular lipid droplets stained with Oil Red O dye (Figure 1a). Figure 1b shows that isopanduratin A at 5 and 10 μM inhibited cell differentiation in a dose-dependent manner, as indicated by the lower percentage of stained lipid droplets. The intracellular triglyceride content in the cells exposed to 1–10 μM isopanduratin A for 48 h decreased significantly, compared to untreated control cells (Figure 1c), although a reduction in cellular lipid droplets by 1 μM isopanduratin A was not clearly observed. Similarly, isopanduratin A at 1–10 μM significantly increased the amount of extracellular glycerol released from differentiated cells (Figure 1d).
|
| 114 |
+
|
| 115 |
+
The expression of proteins related to lipid metabolism as markers of mature adipocytes was further investigated in differentiated cells. Elevated expression levels of FAS, LPL, PLIN, and adiponectin, which play an important role in lipogenesis, were clearly observed in cells cultured with differentiation medium for 8 days (Figure 2a). Intriguingly, 5–10 μM of isopanduratin A significantly suppressed the expression of PLIN (Figure 2c) and adiponectin (Figure 2e) in differentiated cells, while lower levels of FAS (Figure 2b) and LPL (Figure 2d) were observed at as low as 1 μM of isopanduratin A. These results demonstrated that isopanduratin A at non-cytotoxic doses could efficiently limit lipogenesis during cell differentiation.
|
| 116 |
+
|
| 117 |
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3.2. Isopanduratin A Inhibits Mitotic Clonal Expansion during Adipogenesis
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Preadipocytes undergo mitotic clonal expansion (MCE) during the early stage of adipogenesis. Before the beginning of cell differentiation, these growth-arrested preadipocytes usually undergo a few rounds of mitosis. Concurrent reentry into the cell cycle caused by MCE leads to an increased number of adipocytes [7]. MCE is mediated by the activation of cyclin-dependent kinase (CDK) and cyclin family proteins. Following MCE, activated C/EBPβ stimulates C/EBPα, which in turn causes PPARγ to begin transcription [36,38].
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As presented in Figure 3a (see Figure S1), isopanduratin A (1–10 μM) significantly inhibited the proliferation of 3T3-L1 preadipocytes after incubation for 24, 48, and 72 h, compared to differentiated control cells at each time point. The effect of isopanduratin A on cell cycle progression during MCE was further determined. The number of cells at different stages of the cell cycle was assessed after culture in differentiation medium for 18 h in the presence or absence of 1–10 μM of isopanduratin A. The histograms obtained from flow cytometry reveal the entry into the S phase of the cell cycle in differentiated 3T3-L1 cells (Figure 3b). Surprisingly, isopanduratin A significantly hindered the progression of the cell cycle, as indicated by the higher number of cells in the G0/G1 phase, compared to the differentiated control group (Figure 3c).
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Figure 4 shows that isopanduratin A markedly altered the expression of MCE-mediated proteins (cyclins D1 and D3 and CDK2) in differentiated 3T3-L1 cells after 18 h of incubation, as proven by western blot analysis. Cyclin D1 is known to be suppressed, while other cyclin proteins are upregulated, during the initial phase of adipogenesis [39]. Cyclin D1 inhibits adipogenesis by preventing the expression of C/EBPα [40]. In this study, a reduction in cyclin D1 levels was observed in differentiated 3T3-L1 cells, but this downregulation was effectively reversed by isopanduratin A (Figure 4a,b) (See Figure S2). Lower levels of CDK2 (Figure 4c) and cyclin D3 (Figure 4d) were found in cells treated with isopanduratin A (10 μM) in comparison with the differentiated control group. These observations indicate that isopanduratin A delayed cell passage in the cell cycle by modulating MCE-mediated protein expression.
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3.3. Isopanduratin A Downregulates Adipogenic Transcription Factors
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To further elucidate the molecular mechanisms underlying the suppressive effect of isopanduratin A on adipogenesis, the expression of various adipogenic transcription factors was determined at both the mRNA and protein expression levels. Preadipocyte 3T3-L1 cells were collected during the early differentiation stage after 48 h of incubation with or without differentiation medium with isopanduratin A at non-toxic concentrations. Upregulated levels of transcription factor mRNA, including PPARγ, SREBP-1C, and C/EBPα, were observed in cells cultured in differentiation medium for 48 h (Figure 5a) (see Figure S3). Nevertheless, isopanduratin A at 5 and 10 μM significantly decreased the levels of SREBP-1C and PPARγ mRNA, compared to those of the differentiated control cells. It should be noted that the decreased level of C/EBPα mRNA was observed only in the 3T3-L1 cells incubated with isopanduratin A at a high concentration (10 μM). Consistent with the mRNA levels detected by qRT-PCR, western blotting revealed lower expression levels of the SREBP-1C, PPARγ, and C/EBPα proteins in the differentiated 3T3-L1 cells cultured with 5–10 μM of isopanduratin A, compared to differentiated control groups (Figure 5b–d).
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3.4. Upstream Signals from MAPKs Are Modulated by Isopanduratin A
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Mitogen-activated protein kinases (MAPKs), including ERK, p38, and JNK, play an important role during adipogenesis, in which their regulating roles, such as cell proliferation and differentiation, are exerted [37]. Suppression of MAPK signaling molecules efficiently inhibits adipocyte development, and it has been demonstrated that altering these biomolecules during adipocyte differentiation is one of the promising strategies to slow adipogenesis and cellular lipid metabolism [16].
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In the present investigation, a western blot analysis was performed to determine whether isopanduratin A modulates the signaling molecules in the MAPK pathway (Figure 6a). The decreased levels of p-JNK/JNK (Figure 6b) (see Figure S4) and p-ERK/ERK (Figure 6c) were clearly indicated in the 3T3-L1 cells cultured with differentiation medium containing 5–10 μM of isopanduratin A, compared to differentiated control cells. It is worth noting that isopanduratin A at a high concentration (10 μM) dramatically suppressed p-p38/p38 signaling (Figure 6d). Thus, these results indicated that isopanduratin A might attenuate adipogenesis by inhibiting the MAPK pathway.
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3.5. Isopanduratin A Modulates the Crosstalk between AMPK-ACC and AKT/GSK3β Signals
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Several reports suggest that AMP-activated protein kinase (AMPK) regulates the cellular energy balance by inhibiting lipogenesis and promoting lipolysis [41,42]. In this study, isopanduratin A affected AMPK signaling molecules, as illustrated by Western blot analysis (Figure 7a) (see Figures S5 and S6). The activation of the AMPK pathway by this compound was indicated by the highly elevated levels of p-ACC/ACC (Figure 7b), p-AMPKα/AMPKα (Figure 7c), and p-AMPKβ/AMPKβ (Figure 7f) in the differentiated 3T3-L1 cells cultured with 10 μM of isopanduratin A for 48 h.
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Protein kinase B (AKT) is another upstream molecule that plays an important role in adipogenesis. Phosphorylated AKT (p-AKT) suppresses AMPK-ACC signals, resulting in the upregulation of adipogenic transcription factors and promotion of lipogenesis [43]. Additionally, p-GSK3β, which mediates the transcription of adipogenic transcription factors, is also modulated by p-AKT. The AKT/GSK3β cascade is required for the expression of C/EBPβ, C/EBPα, and PPARγ during cell differentiation [44]. Consistent with the elevated expression of AMPK-ACC signals and decreased levels of adipogenic transcription factors, the ratios of p-AKT/AKT (Figure 7d) and p-GSK3β/GSK3β (Figure 7e) were suppressed by isopanduratin A. These results suggest that isopanduratin A modulates the signaling pathways of AKT/GSK3β and AKT/AMPK-ACC to inhibit adipogenesis.
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3.6. Isopanduratin A Suppresses Adipocyte Maturation in Human Preadipocytes
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The antiadipogenic potential of isopanduratin A was further studied in primary human PCS-210-010 preadipocytes. The lipid contents were analyzed by Oil Red O staining (Figure 8a). Treatment with isopanduratin A at 1, 5, and 10 μM decreased the number of cellular lipid droplets by 93.51%, 71.75%, and 49.79%, respectively (Figure 8b). These results suggested that isopanduratin A suppresses adipogenesis in human preadipocytes in a dose-dependent manner.
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4. Discussion
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Obesity is associated with the onset of metabolic syndrome and various degenerative diseases that can cause various chronic health problems and often lead to premature death. During the recent COVID-19 pandemic, obesity increased the risk of hospitalization and admission to intensive care units [45]. The unusual expansion of adipose tissue, a characteristic feature of obesity, depends on adipocyte hypertrophy (an increase in cell size) and/or hyperplasia (an increase in cell number) [46]. It is commonly acknowledged that a long-term regulated lifestyle that involves reducing food intake and increasing physical activity can effectively lower body weight. However, these diet and lifestyle modifications are challenging for many overweight patients. Currently, nutrition intervention is highlighted as an alternative strategy to treat obesity [47].
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In this study, in the Oil Red O staining assay, isopanduratin A at non-toxic concentrations reduced the number of mature, lipid-containing adipocytes in both mouse 3T3-L1 (Figure 1a,b) and human PCS-210-010 (Figure 8) preadipocyte models. These results indicate its anti-adipogenic activity. It should be noted that isopanduratin A at 1 μM could reduce cellular fat accumulation in human preadipocytes more than in murine preadipocytes. Lipid metabolism plays a crucial role in adipocyte differentiation, and its dysregulation is a critical factor in the development of obesity [48]. The decrease in intracellular triglyceride content and the elevated levels of released glycerol (Figure 1c,d) demonstrated the lipolytic effect of isopaduratin A.
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The suppressive effect of isopanduratin A on 3T3-L1 adipogenesis is further evidenced by decreased expression levels of adipogenic effectors, including FAS, PLIN1, LPL, and adiponectin (Figure 2). These lipid-metabolism-modulating proteins are essential for maintaining cellular lipid homeostasis and are associated with various metabolic conditions such as hyperlipidemia, insulin resistance, atherosclerosis, and obesity [9,37,48,49,50,51,52]. Due to its ability to modulate cellular lipid accumulation and interact with these lipid metabolism proteins, isopanduratin A might be a potential nutraceutical candidate for the treatment of several metabolic diseases.
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Mitotic clonal expansion (MCE) is the process in which the number of premature adipocytes increases as a result of cell cycle re-entry and the repeated cycles (two–three cycles) of cell proliferation at the early stage of adipogenesis [7]. Several natural compounds that possess an anti-adipogenic potential exhibit cell cycle arrest in differentiated preadipocytes [37,38,39]. As mentioned above, growth-arrested preadipocytes undergo MCE, which is mediated by the activation of cyclin/CDK complexes [7]. Interestingly, treatment with 1–10 μM of isopanduratin A showed a significant decrease in the percentage of cell proliferation, compared to the differentiation control cells (Figure 3a). Increased cyclin D1 expression in preadipocytes treated with isopanduratin A, with concomitant lowered levels of cyclin D3 and CDK2 (Figure 4), indicated cell cycle arrest in the G0/G1 phase. Similar effects on cyclin D1 levels were reported earlier for other natural polyphenols such as delphinidin and curcumin, both of which are strong anti-adipogenic compounds [53,54]. The increase in cyclin D1 levels may suggest that isopanduratin A also inhibits adipogenesis by activating the Wnt/β-catenin signaling pathway. Consistent with the change in the DNA content analyzed by flow cytometry, the accumulation of G0/G1 cells and the decrease in S phase cells occurred in differentiated preadipocytes cultured with isopanduratin A at 1–10 μM (Figure 3b,c). These results suggested that isopanduratin A inhibited the generation of mature adipocytes from preadipocytes by triggering cell cycle arrest.
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After the MCE period, activation of C/EBPα triggers PPARγ transcription in association with the expression of adipogenesis-regulating proteins [36]. During adipocyte differentiation, transcription factors C/EBPα, PPARγ, and SREBP-1c cross-activate one another to exert their adipogenic functions [38,55]. Previous studies showed that C/EBPα controls the expression of SREBP-1c and that low C/EBPα levels lead to reduced PPARγ activity. In addition, gene expressions related to cellular lipid storage and insulin response are affected by C/EBPα [56,57]. Intriguingly, isopanduratin A suppressed adipogenesis in 3T3-L1 cells by downregulating these transcription factors at both the translation and transcription levels (Figure 5).
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The expression of adipogenic transcription factors is also governed by the opposite correlation between the AKT/GSK3β and the AMPK-ACC pathways. As these two pathways critically mediate the upstream machinery of adipocyte differentiation [58], the regulation of proteins involved in these processes could be another mechanism for suppressing adipogenesis. It is plausible that AMPK and AKT are competitively phosphorylated by an energy balance sensor that controls several metabolic pathways [59]. The AKT/GSK3β cascade is vital for the expressions of C/EBPβ, C/EBPα, and PPARγ during cell differentiation [60].
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Moreover, the AMPK pathway influences the expression of FAS and FABP4, which participate in lipogenesis at the late stage of adipogenesis [57]. In mouse and human mesenchymal cells, upregulated levels of C/EBPα, PPARγ, and SREBP-1c are caused by the downregulation of AMPK, which also affects the activation of ACC [55]. Activation of AMPK (p-AMPK), in association with ACC initiation, hampers triglyceride and fatty acid production by suppressing SREBP-1c and FAS during adipogenesis [47,59]. Therefore, the good correlation between the suppressive effects of isopanduratin A on adipogenic proteins (Figure 4 and Figure 5) and the downregulated levels of p-AKT and p-GSK3β as well as the upregulated levels of p-AMPK and p-ACC (Figure 7) suggests that the compound inhibits adipogenesis and lipogenesis in mature adipocytes through the AKT/AMPK-ACC pathway.
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In general, extracellular stimuli can induce MAPK signaling, which, in turn, activates several intracellular responses through the phosphorylation of specific sites and components, including ERK, JNK, and p38. Studies showed that adipogenic transcription regulators are influenced by proteins in the MAPK family [61]. In this study, isopanduratin A decreased the phosphorylated forms of JNK, ERK, and p38 (Figure 6). Interestingly, isopanduratin A suppressed MAPK signaling concomitantly with a reduction in intracellular lipid accumulation (Figure 1). ERK phosphorylation is known to be essential for cell proliferation and cell cycle progression during the MCE process [62,63,64]. Isopanduratin A prevented MCE, in parallel with the downregulated levels of p-ERK/ERK (Figure 6c). On the other hand, in our previous report, pinostrobin did not suppress MCE, in agreement with its lack of activity on p-ERK/ERK [33]. Panduratin A and cardamonin, the other adipogenic suppressors obtained from fingerroot, have never been reported for MCE interference.
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It is worth noting that the non-theoretical alteration of the upstream regulating molecules (p-AKT, p-GSK3β, p-AMPK, p-ACC, and p-ERK) observed in this study could be the result of late-stage detection. However, isopanduratin A indeed restricts these signaling pathways during adipogenesis. Although more in-depth investigations are needed, the overall results suggest that isopanduratin A suppresses adipogenesis through multi-target mechanisms.
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5. Conclusions
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Fingerroot (Bosenbergia rotunda) possesses pinostrobin, panduratin A, cardamonin, and idopanduratin A as adipogenic inhibitors. Isopanduratin A suppresses adipogenesis by modulating AKT/AMPK-ACC (AKT/GSK3β and AKT/AMPK-ACC) and MAPK (JNK/ERK/p38) signals that correspond to the downregulation of key adipogenic regulators (SREBP-1c, PPARγ, and C/EBPα) and adipogenic effectors (FAS, PLIN1, LPL, and adiponectin) (Figure 9). It is worth noting that isopanduratin A also inhibits MCE by preventing ERK phosphorylation at the early stage of adipogenesis. This property is absent in pinostrobin and has not yet been described for panduratin A or cardamonin. Taken together, our results shed light on the molecular mechanisms underlying the anti-adipogenic activity of isopanduratin A and provide further evidence for the potential use of fingerroot as a functional food against weight gain and obesity. Rigorous preclinical and clinical trials should be performed to establish this hypothesis. As a culinary plant, fingerroot might be consumed directly as a functional food or used as an ingredient in nutraceutical products for body weight control. However, the safety for long-term daily consumption, as well as the stability and bioavailability of the active principles, must be thoroughly investigated before any application can be realized.
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Acknowledgments
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P.R. is grateful to Chulalongkorn University for a C2F (Second Century Fund) postdoctoral fellowship under the supervision of K.L.
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Supplementary Materials
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The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/foods12051014/s1, Figure S1: Original western blot images for Figure 3a; Figure S2: Original western blot images for Figure 4a; Figure S3: Original western blot images for Figure 5a; Figure S4: Original western blot images for Figure 6a; Figure S5: Original western blot images for Figure 7a; Figure S6: Original western blot images for Figure 7a (continued).
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Click here for additional data file.
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Author Contributions
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Conceptualization, K.L. and C.C.; methodology, P.R., H.T.S., B.S., E.P., K.L. and C.C.; soft-ware, E.P. and C.C.; validation, B.S., K.L. and C.C.; formal analysis, P.R., H.T.S. and C.C.; investigation, P.R.; resources, B.S., K.L. and C.C.; data curation, P.R. and C.C.; writing—original draft preparation, P.R.; writing—review and editing, C.B., K.L. and C.C.; review and editing, K.L.; supervision, K.L. and C.C.; funding acquisition, K.L. and C.C. All authors have read and agreed to the published version of the manuscript.
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Data Availability Statement
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Data are contained within the article and Supplementary Material.
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Conflicts of Interest
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The authors declare no conflict of interest.
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Figure 1 Inhibitory effects of isopanduratin A on the accumulation of intracellular lipids in differentiated adipocytes. Mouse preadipocyte 3T3-L1 cells were cultured in differentiation medium in the presence or absence of isopanduratin A at non-toxic concentrations (1–10 μM). (a) The lower number of cellular lipid droplets stained with Oil Red O and (b) the relative absorbance of the eluted Oil Red O dye at 500 nm were noticed in differentiated 3T3-L1 cells treated with 5–10 μM isopanduratin A for 48 h. The altered levels of (c) intracellular triglyceride content and (d) extracellular glycerol were initially detected in differentiated 3T3-L1 cells treated with 1 μM isopanduratin A. Confluent 3T3-L1 cells were cultured in the presence (+) or absence (−) of differentiation medium (MDI) with 0–10 μM isopanduratin A (Iso-PA). Cells treated with dimethyl sulfoxide (0.5% v/v) functioned as the untreated control (0). Bar graphs demonstrating mean ± SD (n = 3) were created using GraphPad Prism. A one-way ANOVA with Tukey’s post hoc test was used to compare the means of treatment and differentiated control groups (* p < 0.05).
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Figure 2 Inhibitory effects of isopanduratin A on the expression of adipogenic effectors in 3T3-L1 adipocytes. Cells were differentiated for 8 days in differentiation medium containing isopanduratin A at non-toxic concentrations. (a) Protein expression was then examined by Western blotting. The expression levels of (b) FAS, (c) PLIN1, (d) LPL, and (e) adiponectin relative to β-actin were measured by the ImageJ program. Confluent 3T3-L1 cells were cultured in the presence (+) or absence (−) of differentiation medium (MDI) with 0–10 μM isopanduratin A (Iso-PA). Cells treated with 0.5% v/v DMSO functioned as untreated control (0). Bar graphs demonstrating mean ± SD (n = 3) were created using GraphPad Prism. A one-way ANOVA with Tukey’s post hoc test was used to compare the means of treatment and the differentiated control groups (* p < 0.05).
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Figure 3 Effects of isopanduratin A on cell proliferation and cell cycle progression of differentiated 3T3-L1 cells. (a) A crystal violet assay was used to track the proliferation of cells cultured in differentiation medium with or without 1–10 μM isopanduratin A for 24 to 72 h. The alteration of the cell cycle in cells treated with isopanduratin A was evaluated by flow cytometry and presented in (b) histograms and (c) cell frequency in each phase. Confluent 3T3-L1 cells were cultured in the presence (+) or absence (−) of differentiation medium (MDI) with 0–10 μM isopanduratin A (Iso-PA). Cells treated with dimethyl sulfoxide (0.5% v/v) functioned as the untreated control (0). Bar graphs demonstrating mean ± SD (n = 3) were created using GraphPad Prism. A one-way ANOVA with Tukey’s post hoc test was used to compare the means of treatment and the differentiated control groups (* p < 0.05).
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Figure 4 Isopanduratin A alters cell-cycle-regulating proteins during differentiation of 3T3-L1 adipocytes. The band intensity of the target protein obtained from (a) Western blot analysis was estimated by comparison with that of β-actin (internal reference) including (b) cyclin D1, (c) CDK 2, and (d) cyclin D3. Confluent 3T3-L1 cells were cultured in the presence (+) or absence (−) of differentiation medium (MDI) with 0–10 μM isopanduratin A (Iso-PA). Cells treated with 0.5% v/v DMSO functioned as untreated control (0). Bar graphs demonstrating mean ± SD (n = 3) were created using GraphPad Prism. A one-way ANOVA with Tukey’s post hoc test was used to compare the means of treatment and differentiated control groups (* p < 0.05).
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Figure 5 Isopanduratin A downregulates adipogenic transcription factors in differentiated 3T3-L1 cells. (a) Relative mRNA levels analyzed via RT-qPCR demonstrated the gene expression of C/ebpa, Pparg, and Srebp-1c. (b) Western blotting was used to evaluate the protein expression level. Treatment with isopanduratin A significantly decreased the levels of (c) SREBP-1c, (d) PPARγ, and (e) C/EBPα proteins in differentiated 3T3-L1 cells. Confluent 3T3-L1 cells were cultured in the presence (+) or absence (−) of differentiation medium (MDI) with 0–10 μM isopanduratin A (Iso-PA). Cells treated with 0.5% v/v DMSO functioned as untreated control (0). Bar graphs demonstrating mean ± SD (n = 3) were created using GraphPad Prism. A one-way ANOVA with Tukey’s post hoc test was used to compare the means of treatment and differentiated control groups (* p < 0.05).
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Figure 6 Isopanduratin A deactivates MAPK signaling molecules in differentiated 3T3-L1 cells. (a) After 48 h of incubation in differentiation medium containing 1–10 μM isopanduratin A, cells were subjected to Western blot analysis. The phosphorylation ratios of (b) p-JNK/JNK, (c) p-ERK/ERK, and (d) p-p38/p38 were significantly lower in cells treated with isopanduratin A, compared to the differentiated control groups. Confluent 3T3-L1 cells were cultured in the presence (+) or absence (−) of differentiation medium (MDI) with 0–10 μM isopanduratin A (Iso-PA). Cells treated with 0.5% v/v DMSO functioned as the untreated control (0). Bar graphs demonstrating mean ± SD (n = 3) were created using GraphPad Prism. A one-way ANOVA with Tukey’s post hoc test was used to compare the means of treatment and differentiated control groups (* p < 0.05).
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Figure 7 Regulatory effects of isopanduratin A on AKT-related signaling pathways. Isopanduratin A activates the AMPK-ACC pathway but deactivates the AKT/GSK3β signaling pathway in differentiating 3T3-L1 cells. The band intensity of each protein obtained from (a) Western blotting was used to analyze the ratio of the phosphorylated to the unphosphorylated form of (b) p-ACC/ACC (c) p-AMPKα/AMPKα, (d) pAKT/AKT, (e) p-GSK3β/GSK3β, and (f) p-AMPK β/AMPK β. Confluent 3T3-L1 cells were cultured in the presence (+) or absence (−) of differentiation medium (MDI) with 0–10 μM isopanduratin A (Iso-PA). Cells treated with 0.5% v/v dimethyl sulfoxide served as the untreated control (0). Bar graphs demonstrating mean ± SD (n = 3) were created using GraphPad Prism. A one-way ANOVA with Tukey’s post hoc test was used to compare the means of treatment and differentiated control groups (* p < 0.05).
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Figure 8 The suppressive effect of isopanduratin A on lipid accumulation in differentiated human PCS-210-010 preadipocytes cultured with isopanduratin A was assessed by Oil Red O staining and represented as percentage of Oil Red O staining. (a) Confluent 3T3-L1 cells were cultured in the presence (+) or absence (−) of differentiation medium (MDI) with 0–10 μM isopanduratin A (Iso-PA). Cells treated with 0.5% v/v DMSO functioned as untreated control (0). (b) Bar graphs demonstrating mean ± SD (n = 3) were created using GraphPad Prism. A one-way ANOVA with Tukey’s post hoc test was used to compare the means of treatment and differentiated control groups (* p < 0.05).
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Figure 9 Proposed regulatory mechanisms of isopanduratin A on the suppression of adipogenesis. Isopanduratin A decreases adipocyte generation and cellular lipid accumulation by downregulating adipogenic effectors (FAS, PLIN1, LPL, and adiponectin) and adipogenic transcription factors (PPARγ, C/EBPα, and SREBP-1c). The multi-target inhibitory properties of isopanduratin A are evidenced by its modulation on mitotic clonal expansion-regulating proteins (CyclinD1, CyclinD3, and CDK2) and AKT (AKT/GSK3β and AKT/AMPK-ACC) and MAPK (JNK, ERK, and p38) signals.
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foods-12-01014-t001_Table 1 Table 1 RT-qPCR primers used in this study.
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Targeted Gene Primer Nucleotide Sequence (5′-3′)
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Pparg PpargF GATTCTCCTRTTGACCCAG
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| 213 |
+
PpargR GAR TGSGAGTGGTCTTCCAT
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| 214 |
+
C/ebpa CebpaF AGTCGGTGGACAAGAACAGC
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| 215 |
+
CebpaR GTGTCCAGTTCRCGGCTCA
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| 216 |
+
Srebp1c Srebp1cF YTGCMGACCCTGGTGAGTG
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| 217 |
+
Srebp1cR GASCGGTAGCGCTTCTCAAT
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| 218 |
+
Gadph GADPHF ACTCCACTCACGGCAAATTC
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| 219 |
+
GADPHR TCTCCATGGTGGTGAAGACA
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foods-12-01014-t002_Table 2 Table 2 List of phytochemicals from Boesenbergia rotunda roots and their effects on lipid content in 3T3-L1 cells determined by Oil Red O staining.
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Tested Chemical a Relative Percentage of Oil Red O Stained Cells (%) b
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Vehicle control c 100.00 ± 0.00
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(1) Pinostrobin [C16H14O4] 66.79 ± 2.34 *
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(2) Geraniol [C10H18O] 106.46 ± 3.34
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(3) Panduratin A [C26H30O4] 76.94 ± 1.14 *
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(4) Isopanduratin A [C26H30O4] 64.04 ± 3.70 *
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(5) Pinocembrin [C15H12O4] 117.31 ± 7.05
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(6) Cardamonin [C16H14O4] 80.89 ± 5.58 *
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(7) Hydroxypanduratin A [C25H28O4] 99.53 ± 0.59
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(8) 5,6-Dehydrokawain [C14H13O3] 115.57 ± 2.89
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(9) Rotundaflavanochalcone [C31H26O8] 115.05 ± 4.31
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(10) 2′,4′,6′-Trihydroxydihydrochalcone [C15H15O4] 99.95 ± 3.92
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(11) Alpinetin [C16H15O4] 108.18 ± 2.28
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(12) Iso-rotundaflavanochalcone [C31H26O8] 86.31 ± 7.20
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a All tested compounds (5 µM) with a purity of >98% were isolated from B. rotunda and identified by nuclear magnetic resonance spectroscopy and mass spectrometry, as previously described [31]. b The Oil Red O staining assay was conducted and reported as the percentage of Oil Red O-stained cells compared to that of the control. c Dimethyl sulfoxide at 0.5% (v/v) was used as a vehicle control. Each experiment was carried out in at least triplicate, and a one-way analysis of the variant-based comparison of means ± SD was carried out. An asterisk refers to the significant difference in means compared to control cells at p < 0.05.
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==== Refs
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puc/PMC10001138.txt
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==== Front
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Cells
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Cells
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cells
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Cells
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2073-4409
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MDPI
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10.3390/cells12050714
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cells-12-00714
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Article
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A Novel Mix of Polyphenols and Micronutrients Reduces Adipogenesis and Promotes White Adipose Tissue Browning via UCP1 Expression and AMPK Activation
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https://orcid.org/0000-0001-9014-7492
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Pacifici Francesca Conceptualization Methodology Validation Formal analysis Investigation Data curation Writing – original draft Writing – review & editing Visualization Supervision Project administration 1†
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Malatesta Gina Methodology Investigation Data curation 1†
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Mammi Caterina Conceptualization Methodology Investigation Data curation Writing – original draft Writing – review & editing Supervision 2
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Pastore Donatella Formal analysis 3
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Marzolla Vincenzo Conceptualization Methodology Formal analysis Data curation Writing – original draft Writing – review & editing Supervision 2
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Ricordi Camillo Validation Supervision 4
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https://orcid.org/0000-0002-6109-3250
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Chiereghin Francesca Formal analysis 3
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https://orcid.org/0000-0003-2032-8735
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Infante Marco Validation 15
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https://orcid.org/0000-0002-2454-5940
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Donadel Giulia Formal analysis 6
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Curcio Francesco Validation 7
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https://orcid.org/0000-0003-1310-3730
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Noce Annalisa Formal analysis 8
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https://orcid.org/0000-0002-3311-486X
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Rovella Valentina Formal analysis 1
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https://orcid.org/0000-0002-8597-4415
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Lauro Davide Validation Visualization 1
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Tesauro Manfredi Visualization 1
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https://orcid.org/0000-0001-7671-0015
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Di Daniele Nicola Visualization 1
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Garaci Enrico Supervision 3
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https://orcid.org/0000-0003-0722-7163
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Caprio Massimiliano Writing – review & editing Supervision 23
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Della-Morte David Conceptualization Validation Investigation Resources Writing – original draft Writing – review & editing Visualization Supervision Project administration 13910*
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Dani Christian Academic Editor
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1 Department of Systems Medicine, University of Rome “Tor Vergata”, 00133 Rome, Italy
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2 Laboratory of Cardiovascular Endocrinology, IRCCS San Raffaele, 00166 Rome, Italy
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3 Department of Human Sciences and Quality of Life Promotion, San Raffaele University, 00166 Rome, Italy
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4 Cell Transplant Center, Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL 33136, USA
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5 Section of Diabetology, UniCamillus, Saint Camillus International University of Health Sciences, Via di Sant’Alessandro 8, 00131 Rome, Italy
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6 Department of Clinical Sciences and Translational Medicine, University of Rome Tor Vergata, 00133 Rome, Italy
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7 Covid Internal Medicine Unit, Department of Translational Medical Sciences, AOU Federico II, University of Naples Federico II, Via S. Pansini, 5, 80131 Naples, Italy
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8 UOC of Internal Medicine-Center of Hypertension and Nephrology Unit, Department of Systems Medicine, University of Rome Tor Vergata, Via Montpellier 1, 00133, Rome, Italy
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9 Department of Neurology, Evelyn F. McKnight Brain Institute, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
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10 Interdisciplinary Center for Advanced Studies on Lab-on-Chip and Organ-on-Chip Applications (ICLOC), University of Rome Tor Vergata, 00133 Rome, Italy
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* Correspondence: david.dellamorte@uniroma2.it; Tel.: +39-06-7259-6893
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† These authors contributed equally to this work.
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24 2 2023
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3 2023
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12 5 71419 10 2022
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17 2 2023
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22 2 2023
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© 2023 by the authors.
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2023
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https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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Background: Obesity is a pandemic disease characterized by excessive severe body comorbidities. Reduction in fat accumulation represents a mechanism of prevention, and the replacement of white adipose tissue (WAT) with brown adipose tissue (BAT) has been proposed as one promising strategy against obesity. In the present study, we sought to investigate the ability of a natural mixture of polyphenols and micronutrients (A5+) to counteract white adipogenesis by promoting WAT browning. Methods: For this study, we employed a murine 3T3-L1 fibroblast cell line treated with A5+, or DMSO as control, during the differentiation in mature adipocytes for 10 days. Cell cycle analysis was performed using propidium iodide staining and cytofluorimetric analysis. Intracellular lipid contents were detected by Oil Red O staining. Inflammation Array, along with qRT-PCR and Western Blot analyses, served to measure the expression of the analyzed markers, such as pro-inflammatory cytokines. Results: A5+ administration significantly reduced lipids’ accumulation in adipocytes when compared to control cells (p < 0.005). Similarly, A5+ inhibited cellular proliferation during the mitotic clonal expansion (MCE), the most relevant stage in adipocytes differentiation (p < 0.0001). We also found that A5+ significantly reduced the release of pro-inflammatory cytokines, such as IL-6 and Leptin (p < 0.005), and promoted fat browning and fatty acid oxidation through increasing expression levels of genes related to BAT, such as UCP1 (p < 0.05). This thermogenic process is mediated via AMPK-ATGL pathway activation. Conclusion: Overall, these results demonstrated that the synergistic effect of compounds contained in A5+ may be able to counteract adipogenesis and then obesity by inducing fat browning.
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polyphenols
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browning
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adipogenesis
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mitotic clonal expansion
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AMPK
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UCP1
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The Evelyn F. McKnight Brain Institute, and partially by the Ministry of Health of Italy (Ricerca Corrente)The activity leading to the present study was founded by The Evelyn F. McKnight Brain Institute, and partially by the Ministry of Health of Italy (Ricerca Corrente).
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==== Body
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pmc1. Introduction
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Obesity is a pandemic health problem [1]. In 2016, the World Health Organization (WHO) estimated that 650 million adults, 340 million adolescents and 39 million children were affected by obesity, and these numbers are growing fast [2]. This condition has been worsened by increased junk food consumption, highly enriched with sugar and fat, that contributes to the development of visceral adiposity, which is strongly associated with cardiovascular diseases (CVD) [3]. Visceral adiposity is primarily composed of white adipose tissue (WAT) and is the main type of adipose tissue serving as energy storage. WAT also acts as an endocrine organ, secreting several pro-inflammatory cytokines, such as tumor necrosis factor (TNF)-α, Interleukin (IL)-6, and leptin, among others [4]. In a state of obesity, the significant increase in WAT and in cytokine levels led to the onset of a pro-inflammatory state typical of this pathological condition and its related disorders (insulin resistance, diabetes mellitus, and CVD).
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Recently, it has been proposed that WAT transdifferentiation into brown adipose tissue (BAT), a phenomenon known as browning, may be a novel approach to counteract obesity [5]. BAT activation enhances energy expenditure and promotes a negative energy balance reducing weight gain in animal models [6,7]. BAT uncouples fatty acid oxidation from adenosine triphosphate (ATP) production, dissipating energy as heat [8]. This beneficial process is primarily mediated by AMP-activated protein kinase (AMPK) that, when triggered by specific impulses, such as cold and/or fasting, induces phosphorylation and activation of adipose triglyceride lipase (ATGL), leading to an increase in lipolysis and fatty acids (FA) release [7,9]. These FA, in turn, bind to the uncoupling protein 1 (UCP1), a protein located in the inner mitochondrial membrane, promoting the dissipation of an electrochemical gradient as heat [9].
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Based on these known mechanisms, several pharmacological and nutritional approaches have been proposed to counteract obesity and fat accumulation [10]. Among nutritional compounds, polyphenols showed a significant anti-obesity effect by regulating lipid metabolism [11]. Resveratrol, the most studied among polyphenols, promotes BAT metabolism by increasing expression of UCP1 in rodents [12]. However, the major limitation in the clinical application of polyphenols, especially resveratrol, is their low bioavailability [13]. To avoid this problem, several resveratrol derivatives with enhanced bioavailability have been proposed and investigated, such as the glycosylated derivate polydatin and the methoxylated derivative pterostilbene [14]. Chronic pterostilbene administration in mice fed with a high fat diet has already been reported to improve lipid metabolism and to promote expression of UCP1 and other factors related to BAT [15]. Recently, we demonstrated that a novel mix of polyphenols and micronutrients, called A5+, was able to protect against inflammation by reducing cytokines-mediated processes in different in vitro experimental models [16,17].
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Based on these findings, the present study aimed to evaluate the effects of A5+ in counteracting adipogenesis by promoting WAT browning in a model of 3T3-L1 murine fibroblasts.
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2. Materials and Methods
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2.1. Cell Culture, Differentiation and Treatments
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A murine 3T3-L1 fibroblast cell line was provided by Prof. Massimiliano Caprio (San Raffaele Open University) and cultured in Dulbecco’s Modified Eagle’s Medium (DMEM, 4.5 g/L glucose) (Gibco, Thermo Fisher Scientific, Waltham, MA, USA), supplemented with 10% Fetal Calf Serum and 1% penicillin/streptomycin (Gibco, Thermo Fisher Scientific, Waltham, MA, USA) at 37 °C in a humidified, 5% CO2 atmosphere.
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To induce differentiation, as previously reported [18], cells were seeded at the desired concentration in the culture medium. When they reached confluence, the medium was changed. The new differentiation medium was composed of DMEM 4.5 g/L glucose supplemented with 10% Fetal Bovine Serum (FBS, Corning, NY, USA), 1% penicillin/streptomycin, 1 µg/mL insulin, 0.5 mM isobutylmethylxanthine (IBMX), and 1 µM dexamethasone, 50 µM A5+ (SirtLIfe srl, Rome), or DMSO (for control cells) (Sigma Aldrich, Saint Louis, MO, USA) for 2 days. On day 2, the differentiation medium was replaced with DMEM (4.5 g/L glucose) containing 10% FBS, 1 µg/mL insulin, and 50 µM A5+, or DMSO (for control cells), until day 10. The medium was changed every 2 days until day 10.
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A5+ is composed of ellagic acid (20%), polydatin (98%), pterostilbene (20%), and honokiol (20%), mixed with recommended doses of zinc, selenium, and chromium. It is dissolved in DMSO at 1 mg/mL, as reported by Pacifici et al. [17].
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2.2. Oil Red O Staining
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Oil Red O staining was performed to quantify the intracellular lipid content as previously described [18]. Briefly, 1 × 105 cells were seeded in a 6-multiwell plate and differentiated as reported in Section 2.1. Then, the cells were washed and fixed with 4% formalin (Sigma Aldrich, Saint Louis, MO, USA). Subsequently, the cells were incubated with 60% isopropanol (Sigma Aldrich, Saint Louis, MO, USA) and then stained with Oil Red O solution (0.5 g/L, Sigma Aldrich, Saint Louis, MO, USA). The dye solution maintained by the cells was dissolved in pure isopropanol and quantified at 490 nm by using the Multiskan FC microplate reader (Thermo Fisher Scientific, Waltham, MA, USA).
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2.3. Proliferation Assay
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For cell proliferation, 2 × 104 cells were plated in a 24-multiwell plate and differentiated as previously reported. At time 0 and at 48 h, the cells were detached using trypsin solution 0.05% (Gibco, Thermo Fisher Scientific, Waltham, MA, USA), then they were centrifuged and the pellet was resuspended in culture medium. Then, 10 µL o cell resuspension was added to 10 µL of trypan blue (Sigma Aldrich, Saint Louis, MO, USA) and analyzed with a Countess Automated Cell Counter (Thermo Fisher Scientific, Waltham, MA, USA).
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2.4. Cell Cycle Analysis
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Cell cycle analysis was performed using Propidium Iodide staining as reported in Pacifici et al. [17]. Briefly, the cells were seeded at 1 × 105 in a 6-multiwell plate and differentiated as reported in Section 2.1. Then, both the supernatants and cells were collected in a FACS collection tube and centrifuged at 1600 rpm for 5 min. Subsequently, the supernatant was discarded, and the pellet was fixed with 70% ethanol for 45 min [19]. Finally, the cells were washed with PBS, stained with PI solution, and analyzed using cytofluorimetric analysis.
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2.5. Inflammatory Array
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Cytokines profile was analyzed in the supernatants of differentiated cells using the Mouse Inflammation Array C1 (Ray-Biotech, Inc., Norcross, GA, USA), as previously reported [17]. Briefly, the cells were treated as described in Section 2.1; at day 10, the supernatants were collected, centrifuged to remove cell debris, and used for the assay. Membranes with 40 spotted cytokine antibodies were blocked with the supplied blocking buffer and then incubated overnight at +4 °C with the supernatants. The next day, the membranes were washed and incubated overnight at +4 °C with a biotinylated antibody cocktail. The next day, the membranes were washed, and HRP-Streptavidin solution was added over night at +4 °C. The following day, the membranes were washed and detected by chemiluminescence. The membranes map is reported in Table 1.
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2.6. Gene Expression Analysis
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For gene expression analysis, total RNA was isolated by using TRIzol reagent (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s protocol. Then, 2.5 µg of total RNA was reverse transcribed into cDNA by using the High-Capacity cDNA Archive Kit (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA). qRT-PCR was performed using the ABI Prism 7500 instrument (Applied Biosystem, Thermo Fisher Scientific, Waltham, MA, USA). cDNA amplification was assessed using a specific primer reported by Marzolla et al. [20] (UCP1, Adbr3, Cidea, DIO2, Cpt1beta, Cpt2, Crat, ACADM, ACADL, Hadha, Aco2, Idh3a Sdhac, Cs), and PowerUp SYBR green dye (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s protocol. All samples were normalized using TATA-box binding protein (TBP) as an internal control; the relative quantification was calculated using the comparative ΔΔCT method, and the values were expressed as 2−ΔΔCT.
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2.7. Western Blot Analysis
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The 3T3-L1 cell pellets were lysed at 4 °C in an HNTG lysis buffer (1% Triton X-100, 50 mM HEPES, 10%glycerol, 150 mM NaCl, 1% sodium deoxycholate) supplemented with Phosphatase Inhibitor Cocktail 2 and 3 (Sigma Aldrich, Milan, Italy) and protease inhibitor cocktail (Sigma Aldrich, Milan, Italy). A clear supernatant was obtained by centrifugation of lysates at 13,000× g for 15 min at 4 °C. Protein concentration was determined using a BCA protein assay kit (Pierce; Thermo Fisher Scientific, Milan, Italy). Protein samples were subjected to sodium dodecylsulfate polyacrilamide gel electrophoresis (SDS-PAGE) using Miniprotean precast gels (BioRad; Segrate, Italy) and electroblotted onto nitrocellulose membranes (Bio-Rad, Segrate, Italy). Membranes were blocked for 1 h at room temperature (RT) with 5% non-fat milk in Tris-Buffered Saline with 0.05% Tween 20 (TBS-T). Incubation with primary specific antibodies was performed in the blocking solution (5% milk or bovine serum albumin in TBS-T) overnight at 4 °C and horseradish peroxidase-conjugated secondary antibodies (in blocking solution) for 1 h at RT. We used antibodies against AMPK-α 1:1000 (Cell Signaling, Danvers, MA, USA), phospho-AMPK-α (Thr172) 1:1000 (Cell Signaling, Danvers, MA), ATGL 1:1000 (Cell Signaling, Danvers, MA), phospho-ATGL (Ser406) 1:1000 (Abcam Cambridge, MA, USA), and UCP1 1:1000 (Abcam Cambridge, MA, USA). The appropriate secondary horseradish peroxidase-conjugated antibodies from Jackson Immunoresearch were used in the blocking solution (1:5000). Immunoreactive bands were visualized by Luminata Forte Western Chemiluminescent HRP substrate (Millipore (Merk); Milan, Italy) using an ImageQuant LAS 4000 (GE Healthcare). Equal samples loading was confirmed using GAPDH 1:30,000 (Sigma Aldrich, Milan, Italy) and bands quantified by densitometry using the ImageQuant TL software from GE Healthcare Life Sciences.
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2.8. Statistical Analysis
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All data were analyzed using GraphPad Prism 9 (La Jolla, CA, USA). An unpaired two-tailed Student’s test was used for statistical analysis and significance. All data were expressed as mean ± SEM. Values of p < 0.05 were considered statistically significant.
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3. Results
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3.1. A5+ Blunts Intracellular Lipid Accumulation
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In order to test whether A5+ was able to reduce intracellular lipid accumulation, we induced 3T3-L1 differentiation into a mature adipocyte phenotype. Then, we stained the differentiated cells with an Oil Red O solution that recognized triglycerides and lipids. As reported in Figure 1, A5+ administration significantly reduced lipid accumulation when compared to control cells, as confirmed by the Oil Red O absorbance at 490 nm (p < 0.005). These results indicated a direct effect of this compound on the mechanisms associated with fat storage. To further validate a reduction in adipogenesis, we also analyzed the mRNA expression of some adipogenic factors (Figure 1, Panels b–d). Accordingly, we observed a significant increase in FAB4 (p < 0.001) and adiponectin expression (p < 0.05) in the A5+-treated cells. Moreover, PPARγ levels were increased following A5+ administration, in agreement with its ability to promote adipogenesis in both white in brown adipose tissue, and to boost the brown-fat characteristics in white adipose tissue [21]. Taken together, these data suggest an involvement of A5+ in reducing white adipocytes maturation.
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3.2. A5+ Inhibits Cell Proliferation by Arresting the Cell Cycle in G2-M Phase
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Mitotic clonal expansion (MCE) is one of the most relevant stages in adipocytes differentiation. MCE is the moment where the cells reentered the cell cycle and promoted the transcription of several genes involved in 3T3-L1 adipocytes differentiation [22]. Based on the importance of MCE, we tested whether A5+ could act at this stage by reducing cell proliferation and thus, the differentiation driving force. Cells were plated at 1 × 105 cells/well in a 6-multiweel plate and differentiation was induced as previously reported. Then, at day 2, cell number and cell cycle were assessed. As expected, while physiological proliferation occurred in control cells, A5+ administration significantly reduced cell proliferation (p < 0.005) (Figure 2, Panel a). We also evaluated the cycle to confirm the cell growth arrest mediated by the selected compound. As reported in Figure 2, Panel b, cells treated with A5+ showed a cell cycle arrest in G2-M phase compared to control cells (p < 0.05). These results were further confirmed by the G2-M cell cycle arrest observed during the follow-up of this process with a peak at day 10 (p < 0.0001) (Figure 2, Panel c).
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3.3. A5+ Administration Blunts Inflammatory Cytokines Release in Adipocytes
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It is well known that mature adipocytes secrete several pro-inflammatory cytokines, thereby contributing to systemic inflammation and complications in obese subjects [23]. In order to evaluate whether this novel compound may impact on inflammation, we tested the secretion levels of several cytokines directly involved in adipocytes maturation and lipid accumulation in a differentiated mature 3T3-L1 adipocytes medium. As shown in Figure 3, A5+ administration significantly reduced the release of BLC, Eotaxin 1, IL-6, Leptin (p < 0.005), the chemokin CXCL9 (p < 0.05), RANTES (p < 0.001), and TIMP1 (p < 0.05) when compared to control cells. These data further highlight the relevant anti-inflammatory effect of polyphenols in general, and A5+ in particular. These findings are also in agreement with our previous data [17].
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3.4. A5+ Promotes Fat Browning
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Recently, a novel strategy to counteract obesity has been reported: it is based on the increase in activity and/or amount of brown adipose tissue (BAT), which, as opposed to WAT, dissipates energy by generating heat and leading to a negative energy balance and weight loss [6]. Based on our previous results, we tested whether reduction in lipid content after A5+ treatment may be attributed to fat browning. Therefore, we differentiated cells and isolated RNA to evaluate gene expression levels of important genes related to BAT. As reported in Figure 4, cells treated with A5+ displayed significantly increased levels of UCP1 (p < 0.05), Adrb3 (p < 0.0001), and Cidea (p < 0.05). A positive but non-significant trend was also shown for DIO2. These data demonstrated that this natural compound was able to promote fat browning, suggesting a potential role in blunting fat accumulation and obesity by triggering the switch from WAT to BAT.
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3.5. A5+ Regulates Lipid Metabolism
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Fatty acid (FA) oxidation is essential to induce UCP1 expression and, thus, to maintain and develop fat browning [24]. Based on our results showing the up-regulation of browning-related genes, we decided to analyze expression levels of genes involved in FA oxidation (Figure 5). As expected, genes involved in mitochondrial FA uptake, in particular Cpt2, significantly increased in A5+-treated cells when compared to control (ctr) cells (p < 0.05) (Figure 5, Panel a). Moreover, following A5+ administration, all analyzed components linked to FA oxidation increased when compared to ctr cells (ACADM: p < 0.05; ACADL: p < 0.005; Hadha: p < 0.05) (Figure 5, Panel b). The Acetyl-Coa derived from FA, metabolized by FAO, enters the TCA cycle to produce the most relevant cofactors essential for mitochondrial respiration [25]. According to the previously shown results genes involved in the TCA cycle were upregulated after treatment (Aco2 and Idh3a: p < 0.005; Sdhac and Cs: p < 0.05) (Figure 5, Panel c). Taken together, these data suggest that A5+ regulates brown fat thermogenesis.
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3.6. A5+ Regulates Cellular Lipid Metabolism in 3T3-L1 via AMPK-ATGL Pathway
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The observation that A5+ treatment increases the expression of thermogenesis-related markers prompted us to investigate the molecular mechanisms underlying the browning of 3T3-L1 adipocytes. 3T3-L1 pre-adipocytes were differentiated, in complete medium, in the presence or absence of A5+ for 10 days. A5+ effects on 3T3-L1 cells were assessed using western blot analysis of UCP-1 protein expression in terminally differentiated 3T3-L1 cells (day 10). A significant increase of UCP-1 protein expression was observed in A5+-treated 3T3-L1 cells when compared with control cells (p < 0.05) (Figure 6, Panel b). Given the well-known role of AMP-activated protein kinase (AMPK) as a sensor of intracellular energy state by regulating FA metabolism and thermogenesis in adipose tissue [26], we investigated whether A5+ was able to activate AMPK. We observed that A5+ administration induced a significant increase of AMPK-α phosphorylation at threonine-172 (Thr172) at day 10 of 3T3-L1 cell differentiation, indicating its capacity to induce AMPK activation (p < 0.001) (Figure 6, Panel b). Adipose triglyceride lipase (ATGL) can be phosphorylated at serine-406 (Ser406) by AMPK to increase its catalytic activity and, in turn, lipolysis in adipocytes [27].Therefore, we examined ATGL phosphorylation at Ser406 in A5+-treated 3T3-L1 cells and observed that it was significantly increased in A5+-treated cells when compared to control cells (p < 0.05) (Figure 6, Panel b).
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4. Discussion
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In the present study, by using a model of a 3T3-L1 fibroblast cell line differentiated into mature adipocytes, we reported, for the first time, that a mix of polyphenols and micronutrients (A5+) may be useful in preventing obesity and its related complications. A5+ administration reduced the accumulation of intracellular lipids and inhibited adipocytes differentiation during MCE, therefore blunting fat accumulation. Moreover, as reported in our previous studies [16,17], A5+ significantly reduced the release of pro-inflammatory cytokines, including leptin. All these beneficial properties of A5+ were primarily linked to its ability to triggering fat browning, or rather switching white adipose tissue to brown adipose tissue, as demonstrated by an increase in the genes linked with this mechanism and with fatty acid oxidation. At a molecular level, overexpression of UCP1 and the activation of AMPK represented the main thermogenic pathways involved.
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Recently, we showed that A5+ significantly blunted inflammation in an in vitro model of Parkinson’s disease [17]. This relevant effect was explained, at least in part, by the synergistic and integrative effect of its components that act in different phases of cellular rescue mechanisms against damage and/or cellular stress. Similarly, in obesity, where a low grade of inflammation plays a pivotal role [28], the components of A5+ may induce a preventive and protective effect. The efficacy of the different polyphenols against obesity has been already largely explored and reported [29]. We previously demonstrated that tyrosol, a major polyphenol found in extra virgin olive oil, inhibited adipogenesis by downregulating several adipogenic factors (leptin and aP2) and transcription factors (C/EBPα, PPARγ, SREBP1c, and Glut4) and by modulating the histone deacetylase sirtuin 1 [18]. A study using the same in vitro model of the present research, showed that phenolic acids, including ellagic acid, inhibited lipid accumulation throughout the whole process of adipogenesis differentiation [30]. However, in this study it was remarked that, despite the similar structure of these compounds, they show interactions with different targets when compared to those reported in the previous study; they also exert distinct effects in adipogenesis [30]. Moreover, polydatin, pterostilbene, and honokiol were not tested. Polydatin was shown to reduce body weight in high fat diet (HFD)-fed mice and to downregulate serum levels of triglyceride, low density lipoprotein (LDL), aspartate aminotransferase (AST), and alanine aminotransferase (ALT), and to upregulate high-density lipoprotein (HDL) [31]. In association with the loss of weight, polydatin also reduced levels of pro-inflammatory factors such as IL-6 [31]. On the other hand, pterostilbene significantly ameliorated free fatty acids (FFA)-induced lipid accumulation in HepG2 cells and activated FA β-oxidation to inhibit FA synthesis in HFD-fed mice via AMPK activation [32]. Again, honokiol supplementation promoted the browning of WAT by upregulation of UCP1 and AMPK expression in HFD mice [33]. All these findings are completely in line with the results of the present study and with our hypothesis of the concomitant and interactive effect of the A5+ compounds on the adipogenesis mechanisms.
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After A5+ treatment, we found a cell cycle arrest in the G2-M phase during adipogenesis, which may be the main cause of the following cascade effect, including reduction in cytokine cellular secretion. Among all pro-inflammatory factors, a significant decrease in leptin release was found. This may have an important consequence since leptin is a primary adipokine linked to mechanisms leading to obesity and its complications regulating body mass via negative feedback between adipose tissue and hypothalamus. [28,34]. In turn, the reduction of IL-6 and CXCL9, that increase the concentration of FFA [35], may drive the regulation of mitochondrial FA metabolism.
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The ultimate protective step of induced by A5+ is the promotion of fat browning. This is a complex process in which gut microbiota also plays an important role [36]. BAT includes several cells, such as pre-adipocytes, stem progenitor cells, and immune cells, and has anti-inflammatory action through the ability to dissipate energy in the form of heat, primarily mediated by UCP1 [8]. In obesity, BAT function is negatively affected by inflammatory mediators, such as high levels of cytokines. For this reason, anti-inflammatory supplementation, even natural, has already been proposed to preserve it [5]. Here we found that treatment with A5+ increases the expression of the main genes involved in fat browning and in FA oxidation. These processes control adipose tissue thermogenesis [8]. UCP1 generates a heat dissipating energy proton gradient from the electron transport chain in mitochondrial respiration [37]. The increase in cellular respiration has favorable effects on other cellular pathways such as AMPK-ATGL, which, in turn, are pivotal to activate central and peripheral beneficial effects of BAT [9]. Here, we demonstrated either an increase of UCP1 and AMPK-ATGL expression after A5+ treatment. Interestingly, AMPK has already been shown to be positively modulated by other polyphenols, such as resveratrol [9].
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The beneficial effect of minerals dissolved in A5+ (zinc, selenium, and chromium) against obesity has been largely demonstrated. Recently, the levels of these elements were found to be significantly reduced when measured in blood serum, hair, and urine of obese adult patients, demonstrating their predictive role in obesity and the helpful impact of their adequate replacement therapy [38].
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5. Conclusions
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In conclusion, in the present article we found that a natural product composed of highly bioavailable polyphenols and minerals may help in preventing some cellular processes associated with obesity, primarily by reducing cellular lipid accumulation and by increasing fat browning through enhancement of mitochondrial respiration and fatty acid oxidation (Figure 7). Further studies in this important field are necessary to understand how to counteract this pandemic disease.
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Author Contributions
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| 165 |
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Conceptualization, F.P., C.M., V.M. and D.D.-M.; methodology, F.P., G.M. and C.M.; validation, F.P., C.R., M.I., F.C. (Francesco Curcio), D.L., M.C. and D.D-M.; formal analysis, F.P., D.P., V.M., F.C. (Francesca Chiereghin), G.D., A.N. and V.R.; investigation, F.P., G.M., C.M. and V.M.; resources, D.D.-M.; data curation, F.P., G.M., C.M. and V.M.; writing—original draft preparation, F.P., C.M., V.M. and D.D.-M.; writing—review and editing, F.P., C.M., V.M., M.C. and D.D.-M.; visualization, D.L., M.T., N.D.D. and D.D.-M.; supervision, F.P., C.M., V.M., C.R., E.G., M.C. and D.D.-M.; project administration, F.P. and D.D.-M.; funding acquisition, D.D.-M. All authors have read and agreed to the published version of the manuscript.
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Institutional Review Board Statement
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Not applicable.
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Informed Consent Statement
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| 172 |
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| 173 |
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Not applicable.
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Data Availability Statement
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The data are contained within the article.
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+
Conflicts of Interest
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C.R. and D.D.-M. are scientific advisors for SirtLife, srl and hold equity in the company that patented and provided A5+.
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+
Figure 1 Oil Red O staining in 3T3-L1 adipocytes. Cells were seeded at a density of 1 × 105 cells/well in a 6-well plate and differentiated with or without A5+. (a) Cells were stained with Oil Red O and lipid droplets were visualized in optical microscopy (20× magnification) and quantified by measuring absorbance. (b–d) Bar graphs illustrating the most relevant adipogenesis-related genes modulated by A5+. Results are expressed as the mean ± SEM. * p < 0.05, ** p < 0,005, *** p < 0.001. Graphs illustrate three different experiments conducted separately. FAB4: Fatty acid-binding protein 4; PPARγ (peroxisome proliferator-activated receptor gamma).
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+
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Figure 2 Cell proliferation and cell cycle analysis. (a) Cell proliferation during MCE; (b) Cell cycle analysis during MCE; (c) Cell cycle analysis at day 10. Results are expressed as the mean ± SEM. * p < 0.05, ** p < 0.005, *** p < 0.001, **** p < 0.0001. Graphs illustrate three different experiments conducted separately.
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Figure 3 A5+ reduced adipocytes induced inflammation. (a) Representative blot assay reporting all cytokines evaluated; (b) Bar graph illustrating the most relevant cytokines modulated by A5+ administration. Data are reported as mean ± SEM (n = 4). (* p < 0.05; ** p < 0.005; *** p < 0.001). ctr: control; BLC: B lymphocyte chemoattractant; IL-6 Interlukin-6; CXCL9: chemokine (C-X-C motif) ligand 9; RANTES: Regulated upon Activation, Normal T Cell Expressed and Secreted; TIMP1: Tissue inhibitor matrix metalloproteinase 1.
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Figure 4 A5+ promotes browning related genes. Bar graph illustrating the most relevant browning-related genes modulated by A5+ administration: (a) UCP1, (b) Adrb3, (c) Cidea, (d) DIO2. Data are reported as mean ± SEM (n = 4). (* p < 0.05; **** p < 0.0001). ctr: control; UCP1: uncoupling protein 1; Adrb3: β3-adrenergic receptor; DIO2: Deiodinase, iodothyronine, type II. ns: not significant.
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Figure 5 A5+-induced lipid metabolism. Bar graph illustrating the most relevant lipid metabolism-related genes modulated by A5+ administration: (a) Genes related to mitochondrial fatty acids (FA) uptake, (b) Genes involved in fatty acid oxidation (FAO), (c) Genes regulating tricarboxylic acid (TCA) cycle. Data are reported as mean ± SEM (n = 4). (* p < 0.05; ** p < 0.005; ns: not significant). ctr: control; Cpt1beta: Carnitine palmitoyltransferase I beta; Cpt2: Carnitine palmitoyltransferase II; Crat: Carnitine acetyltransferase; ACADM: acyl-Coenzyme A dehydrogenase, C-4 to C-12 straight chain; ACADL: Acyl-CoA dehydrogenase, long chain; Hadha: Hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase, alpha subunit; Aco2: aconitase 2; Idh3a: Isocitrate dehydrogenase subunit alpha; Sdhac: Succinate dehydrogenase complex subunit C; Cs: Citrate synthase; TBP: TATA box binding protein.
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Figure 6 A5+ determined activation of AMPK-ATGL pathway in 3T3-L1 adipocytes. (a) Representative immunoblots of UCP1, AMPK, and ATGL activation analysis (n = 6), (b) distribution graphs of the densitometric scanning analyses performed by ImageQuant TL software by using GAPDH as loading control. Phosphorylated forms were normalized in comparison with their total forms. * p < 0.05; *** p < 0.001.
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| 194 |
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| 195 |
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Figure 7 Schematic representation of A5+ effects on adipogenesis and browning. A5+ administration increased the expression levels of several genes involved in FAO, FA uptake and TCA. Moreover, it also promoted the activation of the AMPK-ATGL pathway and increased the expression levels of UCP1, leading to BAT generation and reducing the pro-inflammatory state typical of obesity and white adipogenesis. Created by Bio-Render.com.
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cells-12-00714-t001_Table 1 Table 1 Membrane cytokines array map.
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| 198 |
+
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| 199 |
+
POS POS NEG NEG Blank BLC CD30L Eotaxin Eotaxin-2 Fas L Fractalkine GCSF
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| 200 |
+
POS POS NEG NEG Blank BLC CD30L Eotaxin Eotaxin-2 Fas L Fractalkine GCSF
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| 201 |
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GM-CSF IFNγ IL-1α IL-1β IL-2 IL-3 IL-4 IL-6 IL-9 IL-10 IL-12
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| 202 |
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p40p70 IL-12
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| 203 |
+
p70
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| 204 |
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GM-CSF IFNγ IL-1α IL-1β IL-2 IL-3 IL-4 IL-6 IL-9 IL-10 IL-12
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| 205 |
+
p40p70 IL-12
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| 206 |
+
p70
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| 207 |
+
IL-13 IL-17 I-TAC KC Leptin LIX Lymphotactin MCP-1 MCSF MIG MIP-1α MIP-1γ
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| 208 |
+
IL-13 IL-17 I-TAC KC Leptin LIX Lymphotactin MCP-1 MCSF MIG MIP-1α MIP-1γ
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| 209 |
+
RANTES SDF-1 TCA-3 TECK TIMP-1 TIMP-2 TNF-α sTNF RI sTNF RII Blank Blank POS
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| 210 |
+
RANTES SDF-1 TCA-3 TECK TIMP-1 TIMP-2 TNF-α sTNF RI sTNF RII Blank Blank POS
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| 211 |
+
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| 212 |
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Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
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==== Refs
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puc/PMC10002489.txt
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Int J Mol Sci
|
| 4 |
+
Int J Mol Sci
|
| 5 |
+
ijms
|
| 6 |
+
International Journal of Molecular Sciences
|
| 7 |
+
1422-0067
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
10.3390/ijms24054549
|
| 11 |
+
ijms-24-04549
|
| 12 |
+
Review
|
| 13 |
+
Circular RNA- and microRNA-Mediated Post-Transcriptional Regulation of Preadipocyte Differentiation in Adipogenesis: From Expression Profiling to Signaling Pathway
|
| 14 |
+
Huang Chiu-Jung 1*
|
| 15 |
+
Choo Kong Bung 2*
|
| 16 |
+
Tegeder Irmgard Academic Editor
|
| 17 |
+
1 Department of Animal Science & Graduate Institute of Biotechnology, School of Agriculture, Chinese Culture University, 11114 Taipei, Taiwan
|
| 18 |
+
2 Department of Preclinical Sciences, M Kandiah Faculty of Medicine and Health Sciences, Universiti Tunku Abdul Rahman, 43000 Selangor, Malaysia
|
| 19 |
+
* Correspondence: hqr2@ulive.pccu.edu.tw (C.-J.H.); chookb@utar.edu.my (K.B.C.)
|
| 20 |
+
25 2 2023
|
| 21 |
+
3 2023
|
| 22 |
+
24 5 454909 1 2023
|
| 23 |
+
22 2 2023
|
| 24 |
+
24 2 2023
|
| 25 |
+
© 2023 by the authors.
|
| 26 |
+
2023
|
| 27 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 28 |
+
Adipogenesis is an indispensable cellular process that involves preadipocyte differentiation into mature adipocyte. Dysregulated adipogenesis contributes to obesity, diabetes, vascular conditions and cancer-associated cachexia. This review aims to elucidate the mechanistic details on how circular RNA (circRNA) and microRNA (miRNA) modulate post-transcriptional expression of targeted mRNA and the impacted downstream signaling and biochemical pathways in adipogenesis. Twelve adipocyte circRNA profiling and comparative datasets from seven species are analyzed using bioinformatics tools and interrogations of public circRNA databases. Twenty-three circRNAs are identified in the literature that are common to two or more of the adipose tissue datasets in different species; these are novel circRNAs that have not been reported in the literature in relation to adipogenesis. Four complete circRNA–miRNA-mediated modulatory pathways are constructed via integration of experimentally validated circRNA–miRNA–mRNA interactions and the downstream signaling and biochemical pathways involved in preadipocyte differentiation via the PPARγ/C/EBPα gateway. Despite the diverse mode of modulation, bioinformatics analysis shows that the circRNA–miRNA–mRNA interacting seed sequences are conserved across species, supporting mandatory regulatory functions in adipogenesis. Understanding the diverse modes of post-transcriptional regulation of adipogenesis may contribute to the development of novel diagnostic and therapeutic strategies for adipogenesis-associated diseases and in improving meat quality in the livestock industries.
|
| 29 |
+
|
| 30 |
+
circular RNA
|
| 31 |
+
microRNA
|
| 32 |
+
post-transcriptional regulation
|
| 33 |
+
signaling pathways
|
| 34 |
+
preadipocyte differentiation
|
| 35 |
+
adipogenesis
|
| 36 |
+
species conservation
|
| 37 |
+
This work was self-sponsored without any grant supports.
|
| 38 |
+
==== Body
|
| 39 |
+
pmc1. Introduction
|
| 40 |
+
|
| 41 |
+
1.1. Adipogenesis Is a Crucial Cellular Process
|
| 42 |
+
|
| 43 |
+
Adipose tissue mass may expand via increasing the size of the constituent adipocyte cells. On the other hand, adipogenesis is an adipocyte biogenesis process in which new adipocytes are generated from multipotent progenitor stem cells. Adipogenesis begins with the progenitor cells being committed to become preadipocytes, which undergo growth arrest, followed by preadipocyte differentiation into mature adipocytes [1,2].
|
| 44 |
+
|
| 45 |
+
Adipose tissues are morphologically divided into the white (WAT) and brown adipose tissue (BAT), and the beige adipose tissue, with each type playing a different physiological role. Morphologically, a mature WAT adipocyte carries a large lipid droplet but few mitochondria within the cell. Hence, WAT serves mainly as an energy reservoir; excessive lipids are stored as triglyceride, which is converted, on energy demand, to free fatty acids for circulation [3,4,5]. Dysfunctional WAT is associated with obesity, insulin-resistance in diabetes, cardiovascular disorders and cancers, among other human conditions [6,7,8,9]. On the other hand, small lipid droplets and high numbers of mitochondria are found in BAT adipocytes. Functionally, BAT serves a thermogenic function in producing heat from the lipid droplets, regulating body temperature, in addition to other secretory functions [10,11,12]. While excessive WAT in obesity is unhealthy, BAT is favorable in health in its effects on reducing the accumulation of adipose tissues and in lowering insulin resistance in diabetes patients (reviewed in [13]). Beige adipocytes may be converted from WAT adipocytes, a process dubbed WAT browning. Beige adipocytes possess smaller oil droplets and enriched mitochondria contents; hence, beige adipose tissues share many features and physiological functions with BAT [14]. WAT browning is typically induced by exposure to cold and on demand for heat [15].
|
| 46 |
+
|
| 47 |
+
In term of regulation, a key gateway to adipogenic gene expression that drives preadipocyte differentiation is the peroxisome proliferator-activated receptor (PPAR) family nuclear proteins, particularly the PPARγ isoform [16,17,18,19,20]. In several human clinical conditions, including inflammation, insulin sensitivity, obesity and cancer, PPARγ has been shown to play important causative roles (reviewed in [18]). In thermogenesis, there is also crosstalk between PPARs and thyroid hormone receptors in the adipogenesis process via competing for binding to the heterodimeric partner, retinoid X receptor or other targets [21,22,23]. Hence, adipogenesis, acting through PPARs or otherwise, is a crucial cellular process for human wellbeing and survival.
|
| 48 |
+
|
| 49 |
+
In animal husbandry, studies on adipogenesis are focused on improving the quality and nutritional values of meat of livestock, which are a major source of proteins and lipids for humans. A major factor that affects meat quality is intramuscular fat content, which controls not only meat texture and taste, but also supplements of essential fatty acids [24]. Hence, extrapolations from animals to the human, and vice versa, may rapidly help expand understanding in the regulation of adipogenesis and the adipogenesis-associated proteins across species. The assumption is that if a transcript or protein sequence is highly conserved through evolution, critical biological functions are implied. Interspecies sequence conservation has, indeed, been useful in identifying causes of congenital diseases in humans [25,26]. Based on this supposition, we have previously reviewed possible extrapolation of species-conserved microRNAs (miRNAs) and the miRNA-targeted mRNAs of chicken in adipogenic gene expression in the adipogenesis process [16].
|
| 50 |
+
|
| 51 |
+
1.2. CircRNA- and miRNA-Mediated Post-Transcriptional Regulation of Gene Expression: An Overview
|
| 52 |
+
|
| 53 |
+
Studies have shown that adipogenesis is regulated by a wide array of genes [17]. On reaching the cytoplasm, mature mRNAs may further be modulated post-transcriptionally by regulatory RNA species, including circular RNA (circRNA) and microRNA (miRNA), in deciding “go or no go” in translation into a functional protein (Figure 1). Translation of an mRNA may be blocked by a targeting miRNA, or the mRNA may suffer degradation induced by the targeting miRNA (Figure 1B). The miRNA is, in turn, under the whip of another single-stranded but larger-sized circular RNA (circRNA) via base-pairing resulting in the “sponging” off, i.e., in depleting, of the miRNA pool to free the targeted mRNA for translation (Figure 1C). Subsequently, the translated protein goes into signal transduction or other biochemical pathways to regulate adipogenic gene expression (Figure 1A–C) [16,27]. Clinical studies have indicated that circRNAs and miRNAs may be encapsulated in exosomes, or simply released as free forms into the blood stream of patients to be transported to destination cells, which may or may not express the circRNA or miRNA, to exert gene regulatory functions in the destination cells (Figure 1D) [28].
|
| 54 |
+
|
| 55 |
+
It is noted here in passing that the long noncoding RNAs (lncRNAs) constitute another unique group of noncoding RNAs that interact with other biomolecules, including circular RNAs and microRNAs, to affect biological functions at multiple regulatory levels [29,30,31]. However, lncRNAs are not the focus of this work, and are discussed only in relation to their interactions with the circRNA and miRNA networks being analyzed.
|
| 56 |
+
|
| 57 |
+
The biogenesis of and functions of miRNA have been extensively reviewed [32,33,34,35]. Only a synopsis of key features relevant to this review is given here. Each miRNA is encoded by a single gene, which may occur in clusters; an extensively studied example is the chromosome 19 miRNA cluster, or C19MC, which includes 46 individual miRNA genes [36,37]. Evolutionary transposition has also generated miRNA families, each with multiple family members with identical or highly homologous sequences; a notable example is the let-7 miRNA family [38,39]. It is noteworthy that many miRNA genes are located within the intron sequences of many protein-coding genes, a genomic framework also shaped by evolution [40,41]. In the process of miRNA biogenesis, a hairpin precursor is first formed, which is further processed to generate either or both the 3- or 5-prime (3p or 5p) mature miRNA species with different sequences targeting different mRNAs in action (Figure 1B) [42,43]. Hence, the suffix -3p or -5p is important in designing a specific miRNA to avoid confusion. The soul of the 17–21-nucleotide miRNA is the “seed sequence” of 5–8 nucleotides located at the 5′-end of the short RNA sequence. Members of the same miRNA family share identical seed sequences. In targeting an mRNA, the miRNA seed sequence interacts with a complementary sequence in the 3′-untranslated region (3′-UTR) of the mRNA; the sequences on both sides of the seed regions often show low sequence homology without affecting the mRNA-targeting action of the miRNA.
|
| 58 |
+
|
| 59 |
+
The biogenesis of circRNAs is more elaborate [44]. Unlike miRNA, which each have a specific-gene status, a circRNA is the backsplicing offspring of a pre-mRNA of a specific host gene by stitching together one or more selected exons and/or intron sequences of the pre-mRNA into a circular RNA molecule of assorted sizes (Figure 1C). Backsplicing requires canonical pre-mRNA spliceosomal machinery, recognizing the same consensus intron–exon GU-AG junctions. The process is also modulated by the pairing of intronic repetitive sequences, such as Alu, and contributions by cis complementary sequences and trans-acting protein factors [45,46]. Multiple circRNA species, or isoforms, may be generated from a specific host transcript. Different isoforms carry different sequences and, therefore, sponging off of different miRNA targets. In the literature, the circRNA nomenclature has not been standardized, and is, therefore, rather confusing. A circRNA designation may be provided as: (i) a circBase (http://www.circbase.org, accessed on 20 December 2022) ID, which is specific for each circRNA, but does not provide any hint of the isoform on first sight; (ii) the host gene name but often without indication of the isoform being studied; or (iii) the chromosomal location of the circRNA sequence, which is not reader friendly. In this review, efforts are put into identifying both the circBase ID and the host gene name of the reported circRNAs being discussed.
|
| 60 |
+
|
| 61 |
+
We have previously reviewed the miRNA–mRNA signaling axis that impacts the PPARγ gateway in the adipogenesis process [16]. In this review, we are extending the literature appraisal to include circRNAs in the post-transcriptional regulatory network, focusing on circRNA–miRNA and miRNA–mRNA crosstalk in regulating preadipocyte differentiation. The approach used is integration and analysis of information and datasets harvested from literature scrutiny, interrogation of circRNA and miRNA databases and analysis of the acquired information using bioinformatics and algorithmic tools.
|
| 62 |
+
|
| 63 |
+
2. Whole-Transcriptome Profiling of circRNAs in Preadipocyte Differentiation in Adipogenesis: Connecting the Human and Animal Species
|
| 64 |
+
|
| 65 |
+
2.1. Profiling of Adipogenesis-Associated circRNAs in Different Species: Methodology and Dataset Availability
|
| 66 |
+
|
| 67 |
+
To uncover novel circRNAs associated with adipogenesis, whole-transcriptome profiling has been applied in humans and assorted experimental and domesticated farm animals. Reports of such studies are obtained through searches in the PubMed (https://pubmed.ncbi.nlm.nih.gov, accessed on 20 December 2022) database. Many studies are focused on the critical step of differentiation of preadipocytes into mature adipocytes by examining differential expression (DE) data before and after differentiation induced in vitro (Table 1A). Besides preadipocyte differentiation, comparative studies on subjects relevant to adipogenesis are also presented, e.g., circRNA profiling in adipocytes between obese and lean individuals, and between developmental stages in calf and adult cattle (Table 1B) [47,48]. We also include here a paper that does not have DE data but provides useful datasets on visceral (VAT) and subcutaneous adipose tissues (SAT) in humans and mice (Table 1B, rows B2 and B3) [49]. In total, 11 studies with 12 datasets that encompass the human and six animal and bird species are included in this review (Table 1).
|
| 68 |
+
|
| 69 |
+
In early circRNA profiling studies, a human circRNA microarray platform was used, which generated non-discriminating and not-user-friendly datasets [47,50]. Subsequently, most circRNA profiling works used the high-throughput whole-transcriptome RNA sequencing (RNA-seq) platform. The quality of the profiling datasets obtained are affected by the RNA preparations used in the RNA-seq work. In a study in which total RNA preparations were used in a microarray platform, a high number (4080) of differentially expressed (DE) circRNAs are reported, while the total number of circRNAs was not revealed (Table 1A, row A1) [50]. In most studies, ribosomal RNA-free RNA preparations were used. In a few studies, circRNA was further enriched by RNase R treatment to remove other linear RNA species [47,51,52]. The RNA preparations were then used in constructing unidirectional strand-specific RNA libraries for RNA-seq, followed by data analysis using appropriate algorithms and bioinformatics tools. In most cases, the circRNA expression datasets, after various degrees of annotation and organization, were submitted either as Supplementary Materials for online access on publication of the papers, or were deposited in some public databases, including miRbase (https://www.mirbase.org, accessed on 20 December 2022) and miRDB (https://mirdb.org, accessed on 20 December 2022). In this review, the availability of useful circRNA profiling datasets is indicated (Table 1).
|
| 70 |
+
|
| 71 |
+
For whole-transcriptome profiling, the availability of useful and user-friendly datasets is important for comparative analysis. Many authors provide circRNA names either in the host name nomenclature, e.g., circSAMD4A, or as circBase identification (ID) numbers, e.g., hsa_circ_0004846. However, authors, except Arcinas et al. (2019) [49], often neglect to be more specific when different circRNA isoforms are detected [49]. Other useful circRNA identification information includes the GenBank (https://www.ncbi.nlm.nih.gov/genbank/, accessed on 20 December 2022) accession number of the host gene transcript from which the circRNA is derived, the exons retained in the circRNA and the chromosomal positions of the retained exons [49]. In many circRNA profiling papers, only circBase ID numbers are provided, which make it difficult to prompt the identity of the circRNA concerned. Hence, we have put in efforts in this review on better identifying the specific host genes and translating the circBase ID into the host gene nomenclature whenever is possible. In some works, the supplementary circRNA datasets provided are in chromosomal positions of the predicted retained exons without the putative circRNA IDs or host gene names, which makes cross referencing difficult [53,54]. In some cases, accessible and useful datasets are unavailable (Table 1).
|
| 72 |
+
|
| 73 |
+
2.2. Only a Small Number of circRNAs Are Involved in Preadipocyte Differentiation: Findings from Profiling Studies
|
| 74 |
+
|
| 75 |
+
Discounting the microarray-based work on human by Sun W et al. (2020) [50], the total number of circRNAs expressed in the adipocytes in different species ranges from 2172 in pig to 7203 in yak (Table 1A) [53,54]. On differentiation, the fraction and the number of differentially expressed (DE) circRNAs in the mature adipocytes relative to the preadipocytes before differentiation ranges from 1.09% (41 circRNAs) to 3.02% (117) in the stromal cells of mouse WAT and BAT, respectively (Table 1A, rows A2 and A3). A much higher, but seemingly unrealistic, DE number of 4080 was observed when total RNA was used in the microarray platform [50]. In a study in pig in which lncRNA and mRNA were also included in the analysis [54], a high fraction (13.67%, 297 circRNAs) of DE circRNA was also reported, probably due to the use of different algorithms in analyzing the sequencing datasets. Hence, these two studies are excluded from further analysis.
|
| 76 |
+
|
| 77 |
+
Taken together, the small number of DE circRNAs may indicate that only a small number of circRNAs participate in the preadipocyte differentiation process (Table 1A). Furthermore, DE circRNAs may be up- or downregulated, suggesting that circRNAs may act as positive or negative modulators in modulating downstream adipogenic gene expression.
|
| 78 |
+
|
| 79 |
+
Besides differentiation, four comparative studies, generating six datasets, on adipogenesis-related subjects have been included (Table 1B). In the work comparing human obese vs. lean subjects, 244 DE circRNAs are revealed (Table 1B, row B1) [47]. In comparing two breeds of pig with different fat contents, 275 circRNAs, mostly downregulated, are reported (Table 1B, row B4) [55]. Further examination of the DE circRNAs presented in these two works may contribute to producing slimmer persons in the clinic and leaner farm animals in the meat industry. In development-related adipogenesis, 67 (1.38%) DE circRNAs are reported between young and old rats and 307 (7.08%) in calf and adult cattle (Table 1B, rows B5 and B6) [48,56].
|
| 80 |
+
|
| 81 |
+
2.3. Preadipocyte Differentiation-Associated circRNAs in the Adipose Tissue: Extrapolating Animal Data to the Human
|
| 82 |
+
|
| 83 |
+
A comprehensive and informative profiling work on preadipocyte differentiation in mouse WAT-1 is presented by Zhang P.P. et al. (2021) [51] (Table 1A, row A2). In the study, 28 circRNAs are identified as upregulated and 13 as downregulated on differentiation, including four circRNAs, each with two isoforms (Table 2, row 1). Based on the log2fold changes of these 41 DE circRNAs provided in this work, comparative assessments are made with other WAT and BAT circRNA datasets in mouse, human and yak, reported by other authors (Table 2, rows 2–5; Supplementary Table S1). When compared with the mouse WAT-2 dataset of Arcinas et al. (2019) [49], only 25 (61.0%) of the 41 circRNAs in the Zhang P.P. et al. (2021) [51] dataset are found in both mouse datasets, including 20 up- and 5 downregulated in expression on differentiation (Table 2, rows 1 and 2; Supplementary Table S1). The 25 circRNAs may be considered as validated circRNAs that are involved in preadipocyte differentiation in the mouse WAT. Interestingly, PubMed interrogations indicate that none of these circRNAs have been reported before in relation to adipogenesis, indicating that they are novel circRNAs awaiting further investigation into their regulatory role in adipogenesis. These circRNAs are not further discussed here.
|
| 84 |
+
|
| 85 |
+
In the human and yak WAT, 23 (56.1%) and 19 (46.3%) circRNAs are in common in the mouse WAT-1 dataset, respectively (Table 2, rows 3 and 4; Supplementary Table S1). The common circRNAs that appear in the WAT datasets of mouse, human and yak may be interpreted as that these circRNAs that are conserved in mandatory functions in modulating preadipocyte differentiation in different species. Thirty-two (78.0%) circRNAs, including three isoforms, are commonly expressed in WAT and BAT differentiation in the different species analyzed (Table 2, row 5; Supplementary Table S1), indicating common circRNA regulatory pathways in WAT and BAT differentiation. It is also noted that 9 of the 41 mouse WAT-1 circRNAs are WAT-specific and are not detected in mouse BAT (Supplementary Table S1), suggesting that some regulatory pathways are exclusive to WAT differentiation. The nine circRNAs are chr17:34877211-34956589, Cacna1d and Fancl in the upregulated group and Rad18, Megf8, Trpc6, Zfp532, Dcbld2, Zfx in the downregulated group. The comparative analysis presented here is based on a limited number of datasets and species analyzed. The predictions made should be taken with caution pending further confirmation of their involvement in adipogenesis differentiation.
|
| 86 |
+
|
| 87 |
+
3. Cross-Species Conservation of the circRNA–miRNA and miRNA–mRNA Interacting Sequences in Adipogenesis Differentiation
|
| 88 |
+
|
| 89 |
+
In two RNAseq profiling studies (Table 1B, rows B1 and B5), the circRNA–miRNA–mRNA trio association, validated in luciferase assays, are reported: circSAMD4A-miR-138-5p-EZH2 mRNA in the human and the circFUT10-let-7c-5p-PGC1β/PPARGC1B in the cattle; circRNA-mediated preadipocyte differentiation was also demonstrated in both cases (Table 3) [47,48]. Further PubMed searches were conducted using the stringent criteria of validation of circRNA–miRNA and miRNA–mRNA interactions by luciferase and mutational or pulldown analysis. Two other circRNAs are identified: the bovine bta_circ_Pparγ and bta_circ_Flt1 (Table 3). Taken together, four circRNAs with established circRNA–miRNA–mRNA connections are found in one or more of the general WAT and BAT circRNA datasets of human, mouse and yak presented in Table 1 and Table 2 above (Table 3). However, they are not among the list of 41 differentially expressed circRNAs in the mouse dataset, most likely because of the imposed criteria constraints in the identification of these circRNAs, and possibly because of species differences. The basic molecular features of the four selected circRNAs, including the exons of the host transcript, retained, size, transcript ID of the host transcript and chromosomal positions are shown in Supplementary Table S2. It is noted that circPPARγ- and circFLT1-modulated miR-92a-3p and miR-93-5p affect more than one mRNA species and, therefore, different cellular processes, and that two long noncoding RNAs also participate in the circFLT1-miR-93-5p regulation (Table 3; see below).
|
| 90 |
+
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| 91 |
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3.1. miRNA Conservation
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| 92 |
+
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Sequence conservation in modulatory RNAs across species is a good indicator of the importance of the regulated cellular functions. If found highly conserved, similar action and function may be predicted across species [16]. Since miRNA plays a central role in connecting circRNA to mRNA, the miRNAs in the validated interactions described above are first examined (Table 3). It is first noted that each of the four miRNAs belongs to a specific miRNA family, and that the genes of miR-92a-3p and miR-138-5p are found in two different chromosomal clusters (Table 3; Supplementary Figure S1). Since members of the same family share identical seed sequences, family members may target the same transcript and share regulatory functions. On the other hand, appearance in chromosomal clusters is an indication of active sequence evolutionary histories [63,64].
|
| 94 |
+
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| 95 |
+
The miRNA sequences of the human, mouse, rat, pig, bovine and chicken obtained through miRBase and TargetScan (https://www.targetscan.org, accessed on 20 December 2022) interrogations are aligned (Figure 2A and Table 4). Except for the unavailability of the pig and chicken miR-93-5p sequences, the 6–7-nucleotide seed sequences of all four adipogenesis-associated miRNAs are identical in the six species analyzed, including the avian chicken. Moreover, the non-seed sequences of the miRNAs are also highly conserved (Figure 2A). The observed miRNA sequence conservation supports the proposition that these miRNAs play crucial functional roles in adipogenesis across species.
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| 96 |
+
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3.2. Conservation in circRNA–miRNA Interactions
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CircRNA sponging of miRNA kickstarts the regulatory role of circRNA in modulating mRNA translation and the subsequent cellular functions. For circRNA–miRNA alignments, circRNA sequences in human, mouse and bovine are obtained from the circBase and circBank (http://www.circbank.cn, accessed on 20 December 2022) databases. The analysis shows that the miRNA seed sequences align perfectly with the targeted sequences of the circRNAs (Table 4), allowing for the rare wobble G-U base-paring in the RNA species (Figure 2B(i,ii), underlined nucleotides). However, a single mismatch in the circFLT1-miR-93-5p pair and two mismatches in circFUT10-let-7c-5p in the seed sequences in the mouse are noted (Figure 2B(ii,iii), in black letters). Furthermore, the circRNA sequences outside the seed regions also show a high degree of sequence homology in the three species, further supporting species conservation of the circRNA and miRNA interactions.
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| 100 |
+
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3.3. Conservation in miRNA–mRNA Interactions
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| 102 |
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+
Literature scrutiny has revealed that miR-92a-3p targets the C/EBPα (CCAAT Enhancer-Binding Protein alpha) and p130/Rb2 (Retinoblastoma 2/p130) transcripts and miR-93-5p targets SIRT7 (Sirtuin-7) and TBX3 (T-Box Transcription factor 3) (Table 3). On alignment of the miRNA and mRNA sequences of interaction, all seven to eight nucleotides of the miRNA seed sequences are found to align perfectly with the complementary targeted sites in the 3′-UTR (3′-untranslated region) of the mRNAs in most cases, with only rare single-nucleotide disparity in some cases, particularly in chicken (Figure 2C; Table 4, last column). Furthermore, two miRNA target sites are found in the 3′-UTR of PGC1β/PPARGC1B (PPARγ Coactivator 1-β) mRNAs of all species analyzed, both of which are also fully conserved in the let-7c-5p seed sequence (Figure 2C(iii)). The interaction of miR-138-5p-EZH2 (Enhancer of Zeste Homolog 2) is also perfectly aligned (Figure 2C(iv)). Taken together, the high degree of miRNA seed sequence conservation in the miRNA–mRNA interactions between species predicts conservation of the modulation mechanism of adipogenesis across species.
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4. Selected circRNA- and miRNA-Mediated Post-Transcriptional Regulation of Signaling and Biochemical Pathways in Preadipocyte Differentiation
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| 106 |
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+
In this section, the four selected circRNAs and the associated miRNAs and mRNAs that modulate preadipocyte differentiation are individually discussed. The salient molecular features of the four circRNAs are shown in Supplementary Table S2. Emphasis in our discussion is on the molecular events controlled by the proteins, the translation of which is regulated by the circRNAs and miRNAs. We have shown above that the circRNAs, miRNAs and mRNAs concerned are highly conserved in the interacting sequences (Table 4; Figure 3). Hence, the events are discussed in general without species specification. However, the human or animal species of the RNAs investigated in the cited studies is specified.
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4.1. CircPPARγ Sponges miR-92a-3p to Regulate C/EBPα and p130/Rb2
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On induced differentiation of bovine adipocytes, bta_circ_Pparγ (bta_circ_0010660) inhibits adipocyte apoptosis and proliferation while promoting adipocyte differentiation via the sponging of miR-92a-3p [57]. However, the authors did not identify the mRNA targeted by miR-92a-3p.
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+
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In an early study, the whole of the miR-17/92 cluster, amongst which is miR-92a (Supplementary Figure S1), was used in preadipocyte differentiation studies in mouse 3T3L1 preadipocyte cells [58]. Upregulated expression of members of the miR-17-92 cluster is shown to promote the clonal expansion stage of adipocyte differentiation via targeting p130/RB2 (Retinoblastoma 2), echoing a previous report [65], and supported by our seed sequence analysis that miR-92a-3p targets a 3′-UTR sequence of the p130 mRNA, and the seed sequence is conserved in different species (Figure 2C(i); Table 4). Before terminal differentiation, differentiating preadipocytes are arrested in growth when re-entry of the cell cycle is blocked [66]. circPPARγ-induced downregulation of miR-92a-3p results in increased p130 levels to enhance p130/E2F dimerization [67] and association with the transcription factor DP-1 [66,68]. The consequence is the exit of the cell cycle, growth arrest and terminal differentiation to form mature adipocytes. In uncommitted human bone marrow adipose tissue-derived stromal cells, absence of p130 has, indeed, been shown to hamper terminal adipocyte differentiation [69]. Hence, targeting p130 is the first route by which circPPARγ exerts its influence on adipogenesis via miR-92a-3p by influencing cell cycle, growth arrest leading to terminal differentiation (Figure 3A, left panel, route I).
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It has also been reported that C/EBPα, when induced in mouse 3T3-L1 preadipocytes in the early stage of differentiation, prompts p130/E2F association via p21 upregulation [59]. In this way, C/EBPα may also regulate E2F availability in the activation of the cell cycle in the clonal expansion stage, leading to terminal differentiation and formation of mature adipocytes (Figure 3A, left panel, route II).
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| 116 |
+
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| 117 |
+
In a different study, chronic myeloid leukemia (CML)-derived exosomes that harbor human miR-92a-3p are shown to promote adipogenesis of adipose-derived mesenchymal stem cells [60]. Our analysis supports that the seed sequence of miR-92a-3p perfectly complements a specific sequence of the 3′-UTR of the C/EBPα transcript, and that the seed sequence is conserved (Figure 2C(i); Table 4). In the same CML-exosome study, in vitro studies show that miR-92a-3p suppresses PPARγ and C/EBPα expression and, consequently, the expression of the adipogenic genes, FABP4 (Fatty Acid Binding Protein 4) and AdipoQ (Adipocyte, C1q And Collagen Domain-Containing Protein) (Figure 3A, right panel, route III) [60]. The results are consistent with a previous report that high C/EBPα levels trigger preadipocyte differentiation and WAT development [70]. The C/EBPα-C/EBPβ heterodimer often acts in concert with PPARγ to form a gateway to adipogenic expression and the maintenance of the differentiated state of adipocytes (Figure 3A, right panel, route III) [16,71,72,73]. Importantly, CML-derived exosomal miR-92a-3p is linked to induction of loss of bodyweight via WAT browning and increased energy expenses in cancer-associated cachexia [8].
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| 118 |
+
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| 119 |
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4.2. CircFLT1 Sponges miR-93-5p to Regulate SIRT-7 and TBX3
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| 120 |
+
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| 121 |
+
In induced differentiation of bovine preadipocytes, miR-93, which should be miR-93-5p, is identified as the top expressing miRNA [61]. Through TargetScan analysis and luciferase assays, circFLT1 (bta_circ_002673) and the long noncoding RNAs, lncCCPG1 and lncSLC30A9, are shown to bind competitively to miR-93-5p. On the other hand, circFLT1 and lncCCPG1 also compete to deplete miRNA-93-5p from binding to lncSLC30A9 to offset the lncSLC30A9 action in inducing upregulated expression of PPARγ, C/EBPα and FABP4, leading to preadipocyte differentiation (Figure 3B, route I). The mechanism proposed by the authors is that lncSLC30A9 binds to and transports c-Fos into the nucleus to activate the PPARγ promoter, leading to differentiation (Figure 3B, route I) [61,74].
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| 122 |
+
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| 123 |
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MiR-93 is a member of the miR-106b/25 cluster (Supplementary Figure S1). In another study using miR-106b/25-knockout mice, miR-93-5p is shown to target SIRT-7 (Sirtuin-7) [62]. SIRT-7 is a NAD-dependent deacetylase of histones that induces transcriptional repression [75]. Since SIRT-7-knockout mice have less visceral fat, the gene is linked to adipogenesis [76]. In knockout mice, SIRT-7 is shown to deacetylate and, hence, activate another SIRT protein, SIRT-1, in the preadipocyte differentiation process (Figure 3B, route II) [77]. On the other hand, FOXO1 (Forkhead Box O1), previously inactivated upstream by being acetylated and also phosphorylated by AKT signaling, is now being re-activated by deacetylation by SIRT-1 and dephosphorylation by PP2A (protein phosphatase 2). Subsequently, the activated FOXO1 protein binds to the PPARγ promoter to block PPARγ expression in cis, or interacts with PPARγ in trans, to deplete PPARγ for utilization in adipogenesis (Figure 3B, route II) [16,78,79,80,81]. When miR-93-5p is sponged by circFlt-1, expression of SIRT-7 is upregulated, suppressing SIRT-1 expression to prevent deacetylation and re-activation of FOXO1, thus, allowing PPARγ to participate in adipogenesis.
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| 124 |
+
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| 125 |
+
In the same study, miR-93-5p targeting of TBX3 (T-Box Transcription Factor 3) is demonstrated, which results in suppression of self-renewal in adipocyte precursors before commitment to differentiation in the very early stage of adipogenesis (Figure 3B, route III) [62]. TBX3 has previously been shown to contribute to osteogenic differentiation of human adipose stroma cells and in maintaining pluripotency via targeting the promoter of Oct-4, one of crucial pluripotency inducers in precursor stem cells [82,83].
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| 126 |
+
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| 127 |
+
4.3. The circFUT10-let-7c-5p-PCG1β Regulatory Pathway
|
| 128 |
+
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| 129 |
+
In RNAseq analysis, one of top differentially expressing circRNAs in adipose tissues of both young and adult cattle is circFUT10 (Table 1, row B6) [48]. In cattle, circFUT10 (circRNA ID not available) is further shown to promote adipocyte proliferation by increasing the number of adipocytes in the S and G2 phases of the cell cycle, while suppressing adipocyte differentiation in in vitro assays in bovine adipocyte cells. CircFUT10 sponges let-7c, which we show is let-7c-5p, and that let-7c-5p targets PGC1β/PPARGC1B (PPARγ coactivator 1-β) (Figure 3C). PPARγ acts in collaboration with retinoid X receptor (RXR) to bind to PPARγ response elements in the promoters’ PPARγ-modulated genes in the adipogenesis process [84,85]. PGC1β also associates with PPARγ to induce further PPARγ interactions with other transcription factors in various processes, including tumorigenesis [86,87]. In adipogenesis, however, PGC1β acts as a PPARγ repressor in adipocyte differentiation [88,89]. It is also noteworthy that PGC1β has been shown to be activated, at least in part, by PRDM16 (PR/SET Domain 16 Protein) in the earlier fate determination of brown fat adipogenesis [90]. Whether PRDM16 also activates PGC1β in preadipocyte differentiation remains to be shown.
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| 130 |
+
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| 131 |
+
4.4. The circSAMD4A-miR-138-5p-EZH2 Pathway
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| 132 |
+
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| 133 |
+
In a circRNA profiling work on adipose tissues in obese and lean human individuals, one of the top-expressing circRNAs in preadipocytes is circSAMD4A (hsa_circ_0004846). CircSAMD4A expression levels are correlated with bodyweight (Table 1, row B1) [47]. Knockdown of circSAMD4A downregulates expression of PPARγ and C/EBPα and inhibits preadipocyte differentiation via sponging of miR-138-5p, which releases EZH2 (Enhancer of Zeste Homolog 2) mRNA from miR-138-5p translational suppression (Figure 3D, top portion). miR-138-5p has, indeed, been shown earlier to be a negative modulator of adipogenic differentiation of human adipose-derived mesenchymal stem cells [91].
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| 134 |
+
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| 135 |
+
EZH2 is a histone methyltransferase that epigenetically regulates gene expression through methylation of the histone H3K27, resulting in chromatin changes [92,93,94]. Under normal circumstances, methylated H3K27 binds to the WNT promoter, thereby suppressing WNT expression [95]. Involvement of the EZH2-WNT signaling in adipogenesis has been independently reported by several laboratories [95,96,97]. The WNT-1 protein, on entering the nucleus of preadipocyte cells, downregulates expression of PPARγ and C/EBPα through β-catenin association with other transcription factors to consequently suppress preadipocyte differentiation [16,98]. In short, circSAMD4A upregulates EZH2 expression via sponging miR-138-5p to boost H3K27 histone methylation, thereby suppressing canonical WNT/β-catenin signaling and activating the PPARγ-C/EBPα gateway to advance adipogenesis (Figure 3D).
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| 136 |
+
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| 137 |
+
It is noteworthy that miR-138-5p and EZH2 are hot subjects in cancer research. circSAMD4A also sponges another miRNA, viz. miR-1244, which targets the transcript of ubiquitin protein ligase MDM2 in promoting proliferation and enhancement of stem cell characteristics of osteosarcoma cells [99]. Besides circSAMD4A, miR-138-5p is also targeted by lncHCP5, lncSNHG7 and lncDSCAM-AS1 in promoting tumor growth in various cancers, all of which also act through EZH2 [100,101,102]. Furthermore, besides the WNT/β-catenin signaling in adipogenesis, the miR-138-5p and EZH2 act in concert to affect other signaling pathways in the tumorigenesis process [103,104,105]. All such observations further support that there exist cross talks between adipogenesis and tumorigenesis.
|
| 138 |
+
|
| 139 |
+
5. Concluding Remarks
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| 140 |
+
|
| 141 |
+
In this review, we have identified and elucidated the regulatory role of sets of circRNAs and miRNAs that modulate post-transcriptional expression of proteins directing chemical signals to the PPARγ-C/EBPα gateway and other entry points to activate adipogenic gene expression in preadipocyte differentiation. A summary of the pathway of analysis and the major findings of the four complete circRNA- and miRNA-mediated regulatory pathways leading to adipogenesis is shown in Figure 4. Part (I) involves dissection of circRNA profiling datasets, which leads to the identification of 32 novel WAT and BAT differentiation-associated circRNAs that await elucidation in their regulatory roles in adipogenesis. In part (II) of our analysis, four circRNAs and the respective interacting miRNAs and mRNAs are identified and the downstream signaling and biochemical pathways are analyzed.
|
| 142 |
+
|
| 143 |
+
A salient finding is conservation in the seed sequence of interactions in the circRNA–miRNA and miRNA–mRNA pairs, supporting that these circRNAs and miRNAs play crucial roles in post-transcriptional regulation in preadipocyte differentiation in the adipogenesis process. Sequence conservation may also justify extrapolations and projections of data between the human and animal species, pending more direct demonstration cross species, but speeding up clinical studies in the human in adipogenesis-associated diseases. No less important, elucidation of regulatory circRNAs and miRNAs in adipogenesis may also have impacts on improving meat quality in the livestock industry.
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| 144 |
+
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| 145 |
+
Acknowledgments
|
| 146 |
+
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| 147 |
+
K.B.C. would like to thank Emeritus Soon Keng Cheong, Dean of MK Faculty of Medicine and Health Sciences, UTAR, Malaysia, for the adjunct appointment on K.B.C.’s retirement from full-time teaching. With this position, the authors were able to continue to access library resources to complete this work, and to continue to serve the research community.
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| 149 |
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Supplementary Materials
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| 150 |
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+
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms24054549/s1.
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Click here for additional data file.
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Author Contributions
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| 156 |
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| 157 |
+
C.-J.H. and K.B.C. both conceived the idea, developed the structure and wrote the manuscript, contributing equally. All authors have read and agreed to the published version of the manuscript.
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+
Institutional Review Board Statement
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Not applicable.
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Informed Consent Statement
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Not applicable.
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| 167 |
+
Data Availability Statement
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Not applicable.
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| 171 |
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Conflicts of Interest
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| 172 |
+
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| 173 |
+
The authors declare no conflict of interest in relation to the content of this article.
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| 174 |
+
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| 175 |
+
Abbreviations
|
| 176 |
+
|
| 177 |
+
3′-UTR: 3′-untranslated region; AdipoQ, Adipocyte C1q and Collagen Domain-Containing Protein; AKT, proto-oncogene Akt; BAT, brown adipose tissue; βα, CCAAT-enhancer-binding protein alpha; C19MC, chromosome 19 miRNA cluster; circRNA, circular RNA; CML, chronic myeloid leukemia; DE, differential expression; DP-1, transcription factor DP-1; EZH2, enhancer of zeste homolog 2; FADP4, fatty acid binding protein 4; FOXO1, forkhead box O1; GC, gastric cancer; lncRNA, long noncoding RNA; miRNA, microRNA; PGC1β/PPARGC1B, PPARγ coactivator 1-β; PP2A, protein phosphatase 2; PPAR, peroxisome proliferator-activated receptor; p130/RB2, Retinoblastoma-like protein 2; RNA-seq, whole transcriptome RNA sequencing; RXR, retinoid X receptor; SAT, subcutaneous adipose tissue; SIRT-7, sirtuin-7; TBX3, T-Box transcription factor 3; VAT, visceral adipose tissue; WAT, white adipose tissue; WNT, proto-oncogene Wnt.
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+
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| 179 |
+
Figure 1 The circRNA- and miRNA-mediated post-transcriptional regulation of gene expression: an overview. (A–C) Basic mechanisms of biogenesis of mRNA (A), miRNA (B) and circRNA (C), and interactions between the various RNA species. Notably, the transcript of a miRNA gene first forms a precursor pre-miRNA, which matures into single-stranded 5p and/or 3p miRNA species to bind to the 3′-UTR of the targeted mRNA to induce mRNA degradation or to block translation. A mature circRNA, formed via backsplicing of the pre-mRNA of a host gene, sponges to deplete the targeted miRNA, unblocking mRNA translation by the miRNA. (D) CircRNA and miRNA may also be released into the blood stream encapsulated in exosomes, or as free forms, to reach a distant destination cell to exert their post-transcriptional regulatory functions.
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| 180 |
+
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| 181 |
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Figure 2 Cross-species alignment and conservation of the circRNA–miRNA and miRNA–mRNA interacting sequences in adipogenesis differentiation. (A) miRNA conservation among different species. (B) circRNA–miRNA interactions. (C) miRNA–mRNA interactions. circRNA sequences are derived from circBase (http://www.circbase.org) and circBank (http://www.circbank.cn); miRNA sequences are derived from miRbase; 3′-UTR of mRNA is derived from TargetScan (https://www.targetscan.org). Seed sequences are shown in the red box; homologous seed nucleotides are shown in red letters and mismatches are shown in black letters in the seed sequence box. “-” indicates a gap in the sequence. In the circRNA–miRNA alignments in (B), G–U wobbles are underlined. NA, not available in databases.
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| 182 |
+
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| 183 |
+
Figure 3 Selected circRNA- and miRNA-mediated post-transcriptional regulation of signaling and biochemical pathways in preadipocyte differentiation. (A) CircPPARγ sponges miR-92a-3p to regulate C/EBPα and p130/Rb2. Depicted are the impacts of circPPARγ sponging of miR-92a-3p on adipogenesis via p130 (left panel, route I) and C/EBPα (left panel, routes I and II). Cancer-associated cachexia in chronic myeloid leukemia (CML) through adipogenesis is also shown (right panel, route III). (B) CircFLT1 sponges miR-93-5p to regulate SIRT-7 and TBX3. Route (I) involves lncCCPG1 and lncSLC30A9 and the c-Fos protein; route (II) depicts SIRT-1 and -7 and the FOXO1 pathway targeting PPARγ; route (III) illustrates TBX3 regulation of precursor renewal prior to differentiation in the early stage of adipogenesis. (C) The circFUT10-let-7c-5p-PCG1β regulatory pathway. Negative modulation of preadipocyte differentiation by circFUT10 is shown. (D) The circSAMD4A-miR-138-5p-EZH2 pathway. In this pathway, circSAMD4A sponges miR-138-5p to modulate EZH2-induced histone methylation. See text for further description and for sources based on which the schemes are constructed. In all subfigures, thin and blunted arrows indicate positive and negative regulation, respectively, in normal cells; thick upward-pointing green and red downward-pointing arrows indicate the modulatory effects of the circRNAs on the proteins in the pathway accumulating to the modulation of preadipocyte differentiation in adipogenesis; arrowheads with dashed lines indicate other multi-step pathways, the details of which are not indicated.
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| 184 |
+
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| 185 |
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Figure 4 Pathway of analysis in the identification of circRNAs, miRNAs, proteins and modulated pathways leading preadipocyte differentiation in adipogenesis. Part (I): Identification of circRNAs using 12 datasets derived in circRNA profiling and comparative studies in different species. Twenty-three circRNAs common to two or more WATs and BATs in different species are identified, none of which has not been reported in adipogenesis studies. Part (II): Identification of selected circRNAs, which are validated in circRNA–miRNA–mRNA interactions, and which show species conservation in the RNA interacting sequences. The circRNA/miRNA-mediated signaling and biochemical pathways leading to adipogenesis differentiation are also analyzed. See text for details.
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| 186 |
+
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| 187 |
+
ijms-24-04549-t001_Table 1 Table 1 Adipocyte circRNA profiling papers and datasets in relation to preadipocyte differentiation and comparative studies.
|
| 188 |
+
|
| 189 |
+
No. Species Adipose Tissue Profiled Platform a
|
| 190 |
+
(RNA Prep’n) Profiling Dataset Availability Number in circRNA Reference
|
| 191 |
+
Total DE (Up/Down) on Different’n/Comparison
|
| 192 |
+
(A) Preadipocyte Differentiation Studies
|
| 193 |
+
A1 Human VAT circRNA microarray
|
| 194 |
+
(total RNA) Yes NA 4080
|
| 195 |
+
(2215/1865) [50]
|
| 196 |
+
A2 Mouse WAT
|
| 197 |
+
(stromal cells) RNA-seq
|
| 198 |
+
(circRNA-enriched) Yes 3771 41 (1.09%)
|
| 199 |
+
(28/13) [51]
|
| 200 |
+
A3 Mouse BAT
|
| 201 |
+
(stromal cells) RNA-seq
|
| 202 |
+
(circRNA-enriched) Yes 3869 117 (3.02%)
|
| 203 |
+
(77/40) [52]
|
| 204 |
+
A4 Yak SAT RNA-seq
|
| 205 |
+
(circRNA-enriched) Yes 7203 136 (1.89%)
|
| 206 |
+
(92/44) [53]
|
| 207 |
+
A5 Pig SAT RNA-seq Yes
|
| 208 |
+
(chrom’l sites only) 2172 297 (13.67%)
|
| 209 |
+
(Also, lncRNA and mRNA) [54]
|
| 210 |
+
(B) Differentiation and Comparative Studies
|
| 211 |
+
B1 Human VAT circRNA microarray
|
| 212 |
+
(circRNA-enriched) Yes NA Obese vs. lean:
|
| 213 |
+
244 (143/101) [47]
|
| 214 |
+
B2 Human VAT and SAT RNA-seq Yes 6925 NA [49]
|
| 215 |
+
B3 Mouse Epididymal and inguinal fat (WAT) RNA-seq Yes 2380 NA [49]
|
| 216 |
+
B4 Pig SAT RNA-seq
|
| 217 |
+
(circRNA-enriched) No 29,763
|
| 218 |
+
(combined) Two breeds:
|
| 219 |
+
275
|
| 220 |
+
(70/205) [55]
|
| 221 |
+
B5 Rat SAT
|
| 222 |
+
(stromal cells) RNA-seq No Young: 4860
|
| 223 |
+
Old: 4952 Young vs. old:
|
| 224 |
+
67 (1.38%)
|
| 225 |
+
(33/34) [56]
|
| 226 |
+
B6 Cattle SAT RNA-seq No Calf: 4337
|
| 227 |
+
Adult: 5465 Calf vs. adult:
|
| 228 |
+
307 (7.08%)
|
| 229 |
+
(156/151) [48]
|
| 230 |
+
a RNA-seq, whole transcriptome RNA sequencing. The RNA preparations used were either rRNA-free, or “circRNA-enriched” RNA preparations in which both rRNA and linear RNA species were depleted. VAT and SAT, visceral and subcutaneous adipose tissues; WAT and BAT, white and brown adipose tissues; DE, differential expression; NA, not available.
|
| 231 |
+
|
| 232 |
+
ijms-24-04549-t002_Table 2 Table 2 Common circRNAs in WAT and BAT profiling datasets of different species.
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| 233 |
+
|
| 234 |
+
Dataset No. Dataset a No. of DE circRNAs No. of Overlapping
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| 235 |
+
circRNAs in WAT-1 (Percentage) a Reference
|
| 236 |
+
Upregulated Downregulated
|
| 237 |
+
1 Mouse WAT-1 28 13 41 (100%) [51]
|
| 238 |
+
2 Mouse WAT-2 20 5 25 (61.0%) [49]
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| 239 |
+
3 Human WAT 18 5 23 (56.1%) [49]
|
| 240 |
+
4 Yak WAT 14 5 19 (46.3%) [53]
|
| 241 |
+
5 Mouse BAT 25 7 32 (78.0%) [52]
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| 242 |
+
a The mouse WAT dataset 1 of reference [51] is used as the reference for comparison with other datasets. See Supplementary Table S1 for more details on the circRNAs identified.
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| 243 |
+
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| 244 |
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ijms-24-04549-t003_Table 3 Table 3 Validated circRNA–miRNA–mRNA connections in preadipocyte differentiation.
|
| 245 |
+
|
| 246 |
+
CircRNA Presence in WAT/BAT Dataset a miRNA
|
| 247 |
+
(Family) mRNA (Gene Symbol) Reference
|
| 248 |
+
Host Gene CircRNA
|
| 249 |
+
(circBase ID)
|
| 250 |
+
(Species) Exons
|
| 251 |
+
PPARγ(Peroxisome Proliferator-Activated Receptor-gamma) bta_circ_Pparγ
|
| 252 |
+
(bta_circ_0010660)
|
| 253 |
+
(Bovine) 3-5 h, m, y miR-92a-3p/(mir-25) p130/Rb2RB (Transcriptional Corepressor Like 2)
|
| 254 |
+
|
| 255 |
+
C/EBPα (CCAAT Enhancer Binding Protein Alpha)
|
| 256 |
+
|
| 257 |
+
[57,58,59,60]
|
| 258 |
+
FLT1(Fms-Related Receptor Tyrosine Kinase 1 bta_circ_Flt1
|
| 259 |
+
(bta_circ_002673)
|
| 260 |
+
(Bovine) 2-3 y miR-93-5p (mir-17) (and lncCCPG1 and lncSL30A9) SIRT7 (Sirtuin 7)
|
| 261 |
+
|
| 262 |
+
TBX3 (T-Box Transcription Factor 3)
|
| 263 |
+
|
| 264 |
+
[61,62]
|
| 265 |
+
FUT10(Fucosyltransferase 10) bta_circ_Fut10
|
| 266 |
+
(NA)
|
| 267 |
+
(Bovine) 2 h, y let-7c-5p (let-7) PGC1β/PPARGC1B (PPARγ Coactivator 1-β)
|
| 268 |
+
|
| 269 |
+
[48]
|
| 270 |
+
SAMD4A(Sterile Alpha Motif Domain Containing 4A) hsa_circ_SAMD4A
|
| 271 |
+
(hsa_circ_0004846)
|
| 272 |
+
(Human) 3 h, m, y miR-138-5p (mir-138) E2H2 (Enhancer of Zeste 2 Polycomb Repressive Complex 2)
|
| 273 |
+
|
| 274 |
+
[47]
|
| 275 |
+
a h, human, m, mouse, y, yak. The datasets are as in Table 2.
|
| 276 |
+
|
| 277 |
+
ijms-24-04549-t004_Table 4 Table 4 Species conservation of miRNA seed sequences and in circRNA–miRNA and miRNA–mRNA interactions.
|
| 278 |
+
|
| 279 |
+
circRNA miRNA mRNA miRNA Seed Sequence Conservation
|
| 280 |
+
miRNA in Different Species a cirRNA–miRNA
|
| 281 |
+
Interaction b miRNA–mRNA
|
| 282 |
+
Interaction a
|
| 283 |
+
circPPARγ miR-92a-3p C/EBPα
|
| 284 |
+
|
| 285 |
+
p130/RB2
|
| 286 |
+
|
| 287 |
+
All 7/7 All 7/7 C/EBPα: All 7/7
|
| 288 |
+
|
| 289 |
+
except chicken: 6/7
|
| 290 |
+
|
| 291 |
+
p130/RB2: All 7/7
|
| 292 |
+
|
| 293 |
+
except rat: 6/7
|
| 294 |
+
|
| 295 |
+
|
| 296 |
+
circFLT1 miR-93-5p SIRT7
|
| 297 |
+
|
| 298 |
+
TBX3
|
| 299 |
+
|
| 300 |
+
All 7/7
|
| 301 |
+
(NA for pig and chicken) All 7/7
|
| 302 |
+
except mouse: 6/7 SIRT7: All 8/8
|
| 303 |
+
|
| 304 |
+
except rat: 7/8 (NA for chicken)
|
| 305 |
+
|
| 306 |
+
TBX3: All 8/8
|
| 307 |
+
|
| 308 |
+
|
| 309 |
+
circFUT10 let-7c-5p PGC1β All 6/6 All 6/6
|
| 310 |
+
except mouse: 4/6 Seed I: All 7/7
|
| 311 |
+
|
| 312 |
+
Seed II: All 7/7, except pig: 6/7
|
| 313 |
+
|
| 314 |
+
|
| 315 |
+
circSAMD4A miR-138-5p EZH2 All 7/7 All 6/6 All 7/7, except chicken: 6/7
|
| 316 |
+
|
| 317 |
+
|
| 318 |
+
Details of seed sequence alignments are as shown in Figure 2. Seed sequences are compared in a human, mouse, rat, pig, cow and chicken, or in b human, mouse and bovine. NA, not available.
|
| 319 |
+
|
| 320 |
+
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
|
| 321 |
+
==== Refs
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| 429 |
+
|
puc/PMC10003152.txt
ADDED
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Int J Mol Sci
|
| 4 |
+
Int J Mol Sci
|
| 5 |
+
ijms
|
| 6 |
+
International Journal of Molecular Sciences
|
| 7 |
+
1422-0067
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
10.3390/ijms24054752
|
| 11 |
+
ijms-24-04752
|
| 12 |
+
Article
|
| 13 |
+
Inhibitory Effects of Loganin on Adipogenesis In Vitro and In Vivo
|
| 14 |
+
Jeon Hyoju Methodology Investigation Writing – original draft 12†
|
| 15 |
+
https://orcid.org/0000-0002-2031-0802
|
| 16 |
+
Lee Chang-Gun Methodology Writing – original draft Funding acquisition 12†‡
|
| 17 |
+
Jeong Hyesoo Software Validation Resources 3
|
| 18 |
+
Yun Seong-Hoon Validation Investigation Data curation 3
|
| 19 |
+
https://orcid.org/0000-0002-9497-9779
|
| 20 |
+
Kim Jeonghyun Conceptualization Investigation 12
|
| 21 |
+
https://orcid.org/0000-0002-6687-1293
|
| 22 |
+
Uprety Laxmi Prasad Validation Resources 12
|
| 23 |
+
https://orcid.org/0000-0001-7787-7394
|
| 24 |
+
Oh Kang-Il Validation Formal analysis 12
|
| 25 |
+
Singh Shivani Software Data curation 12
|
| 26 |
+
Yoo Jisu Data curation 12
|
| 27 |
+
https://orcid.org/0000-0002-1928-5531
|
| 28 |
+
Park Eunkuk Conceptualization Writing – review & editing Funding acquisition 12*
|
| 29 |
+
https://orcid.org/0000-0002-0625-3530
|
| 30 |
+
Jeong Seon-Yong Conceptualization Writing – review & editing Funding acquisition 123*
|
| 31 |
+
Gomez-Muñoz Antonio Academic Editor
|
| 32 |
+
1 Department of Medical Genetics, Ajou University School of Medicine, Suwon 16499, Republic of Korea
|
| 33 |
+
2 Department of Biomedical Sciences, Ajou University School of Medicine, Suwon 16499, Republic of Korea
|
| 34 |
+
3 Nine B Co., Ltd., Daejeon 34121, Republic of Korea
|
| 35 |
+
* Correspondence: jude0815@ajou.ac.kr (E.P.); jeongsy@ajou.ac.kr (S.-Y.J.); Tel.: +82-31-219-4520 (E.P. & S.-Y.J.); Fax: +82-31-219-4521 (E.P. & S.-Y.J.)
|
| 36 |
+
† These authors contributed equally to this work.
|
| 37 |
+
|
| 38 |
+
‡ Current address: Department of Biomedical Laboratory Science, College of Software and Digital Healthcare Convergence, Yonsei University MIRAE Campus, Wonju 26493, Republic of Korea.
|
| 39 |
+
|
| 40 |
+
01 3 2023
|
| 41 |
+
3 2023
|
| 42 |
+
24 5 475229 12 2022
|
| 43 |
+
18 2 2023
|
| 44 |
+
25 2 2023
|
| 45 |
+
© 2023 by the authors.
|
| 46 |
+
2023
|
| 47 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 48 |
+
Obesity is characterized by the excessive accumulation of mature adipocytes that store surplus energy in the form of lipids. In this study, we investigated the inhibitory effects of loganin on adipogenesis in mouse preadipocyte 3T3-L1 cells and primary cultured adipose-derived stem cells (ADSCs) in vitro and in mice with ovariectomy (OVX)- and high-fat diet (HFD)-induced obesity in vivo. For an in vitro study, loganin was co-incubated during adipogenesis in both 3T3-L1 cells and ADSCs, lipid droplets were evaluated by oil red O staining, and adipogenesis-related factors were assessed by qRT-PCR. For in vivo studies, mouse models of OVX- and HFD-induced obesity were orally administered with loganin, body weight was measured, and hepatic steatosis and development of excessive fat were evaluated by histological analysis. Loganin treatment reduced adipocyte differentiation by accumulating lipid droplets through the downregulation of adipogenesis-related factors, including peroxisome proliferator-activated receptor γ (Pparg), CCAAT/enhancer-binding protein α (Cebpa), perilipin 2 (Plin2), fatty acid synthase (Fasn), and sterol regulatory element binding transcription protein 1 (Srebp1). Loganin administration prevented weight gain in mouse models of obesity induced by OVX and HFD. Further, loganin inhibited metabolic abnormalities, such as hepatic steatosis and adipocyte enlargement, and increased the serum levels of leptin and insulin in both OVX- and HFD-induced obesity models. These results suggest that loganin is a potential candidate for preventing and treating obesity.
|
| 49 |
+
|
| 50 |
+
loganin
|
| 51 |
+
anti-adipogenic effect
|
| 52 |
+
ovariectomized mice
|
| 53 |
+
high-fat diet mice
|
| 54 |
+
Korea Industrial Technology Association (KOITA)Ministry of Science and ICT (MSIT)KOITA-RND2-2022-1 Korea Health Industry Development Institute (KHIDI)Ministry of Health & Welfare, Republic of KoreaHR22C1734 Ministry of SMEs and StartupsS3263796 National Research Foundation (NRF)Korean Ministry of EducationNRF-2021R1F1A1062311 This research was funded by the Korea Industrial Technology Association (KOITA) funded by the Ministry of Science and ICT (MSIT) in the Korean government (grant number: KOITA-RND2-2022-1), the Korea Health Technology R&D project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HR22C1734), the Technology Development Program of the Ministry of SMEs and Startups (grant number: S3263796), and the Basic Science Research Program through the National Research Foundation (NRF) funded by the Korean Ministry of Education (grant number: NRF-2021R1F1A1062311).
|
| 55 |
+
==== Body
|
| 56 |
+
pmc1. Introduction
|
| 57 |
+
|
| 58 |
+
Obesity is a crucial health problem worldwide, and it is caused by hormonal abnormalities, genetic factors, and an imbalance between food intake and energy consumption [1]. Body mass index (BMI), calculated by dividing body weight by the square of height, is the most commonly used diagnostic indicator of obesity [2]. According to the World Health Organization (WHO) guidelines, a BMI of 25–30 and > 30 kg/m2 are considered overweight and obese, respectively [3]. In 2016, 1.9 billion and 650 million adults above 18 years of age were reported to be overweight and obese, respectively [4].
|
| 59 |
+
|
| 60 |
+
Obesity is characterized by the abnormal deposition of fat in the body, leading to metabolic abnormalities, including fatty liver, elevated plasma insulin/leptin levels, and dyslipidemia [5]. Liver steatosis is caused by an increase in liver fat, which can promote inflammatory signaling pathways that trigger oxidative stress in hepatocytes and produce proinflammatory cytokine. This can lead to the development of non-alcoholic steatohepatitis and macrophage infiltration, which cause liver damage [6,7]. Moreover, excessive fat accumulation alters two main endocrine factors: insulin and leptin [8]. Insulin is a hormone secreted from pancreatic β cells when large amounts of energy are consumed. Insulin regulates energy metabolism by converting glucose into fat. In obese individuals, elevated plasma insulin levels have been observed, in which insulin sensitivity is reduced in insulin-targeted organs such as the liver and adipose tissues, which results in excessive insulin production [9]. Excessive differentiated adipocytes trigger excessive fat accumulation, which leads to an increase in the number or the size of adipocytes (hypertrophy), resulting in a high risk of obesity [10,11].
|
| 61 |
+
|
| 62 |
+
Adipogenesis is a process in which surplus energy is stored in adipocytes in the form of lipids [12]. Adipogenesis is the process of differentiation of mesenchymal stem cells (MSCs) into adipocytes [13]. MSCs are differentiated by a complex cascade of adipocyte-specific transcription factors, such as peroxisome proliferator-activated receptor γ (Pparg), CCAAT/enhancer-binding protein α (Cebpa), perilipin 2 (Plin2), fatty acid synthase (Fasn), and sterol regulatory element binding transcription protein 1 (Srebp1) [14,15,16]. These genes are essential adipogenesis-related markers regulating adipocyte differentiation [15,16]. Excessive differentiated adipocytes trigger immoderate fat accumulation, which leads to an increase in the number of adipocytes (hyperplasia) or the size of adipocytes (hypertrophy), resulting in a high risk of obesity [17]. Despite having a relatively short life in plasma, adipocytokines such as leptin and adiponectin play a crucial role in regulating fat accumulation, which influences insulin sensitivity [18].
|
| 63 |
+
|
| 64 |
+
Overweightness is generally caused by abnormal eating behavior (i.e., calorie-rich food intake, irregular eating habits, and snacking after a meal), insufficient exercise, and inadequate sleep time [19]. Recently, pharmacological therapies, including liraglutide (suppressing appetite) and orlistat (decreasing fat absorption) for managing and preventing obesity, have seen an increase in patients with obesity. However, some medications have serious adverse effects and long-term safety limitations, such as vomiting, nausea, satiety, and oily evacuation [20].
|
| 65 |
+
|
| 66 |
+
Medicinal herbs have been widely considered as alternative conventional therapeutics in the treatment and prevention of various diseases, owing to their long-term safety and fewer adverse effects [21]. A study has demonstrated that single bioactive components derived from herbal products have beneficial therapeutic effects as natural medicines [22]. In addition, studies have shown that several plants containing the iridoid glycoside bioactive compound loganin alleviated hepatic steatosis in a non-alcoholic fatty liver disease mouse model [23], exhibit antidiabetic activities in obese diabetic rats [24] and inhibit adipocyte differentiation and proliferation in rat preadipocytes [25]. Further, loganin prevents inflammatory responses in mouse 3T3-L1 preadipocyte cells and in Tyloxapol-induced mice [26] resulting in decreased body weight gain via improved glucolipid metabolism [25]. Although several beneficial effects of loganin are known, the specific anti-obesity effects of loganin on adipogenesis remain unclear.
|
| 67 |
+
|
| 68 |
+
Therefore, this study aimed to investigate the inhibitory effects of loganin in 3T3-L1 mouse preadipocytes and adipose-derived stem cells (ADSCs) in vitro and in ovariectomy (OVX) and high-fat diet (HFD)-induced mice in vivo.
|
| 69 |
+
|
| 70 |
+
2. Results
|
| 71 |
+
|
| 72 |
+
2.1. Loganin Inhibits Adipocyte Differentiation in Mouse Preadipocytes and ADSCs
|
| 73 |
+
|
| 74 |
+
We first examined whether loganin inhibits adipogenesis in 3T3-L1 mouse preadipocyte cells. Cells were induced to differentiate into adipocytes and were co-incubated with different concentrations of loganin (2, 5, and 10 μM) for 8 d. After the induction of adipocyte differentiation, mRNA expression levels of adipogenic-related markers such as Pparg and Cebpa for adipogenesis, Plin2 for mature adipocytes, and Fasn and Srebp1 for upstream activator of adipogenesis were examined using quantitative reverse transcription polymerase chain reaction (qRT-PCR), and accumulated lipid droplets were visualized using oil Red O staining. Loganin significantly decreased the mRNA expression levels of Pparg, Cebpa, Plin2, Fasn, and Srebp1 in a dose-dependent manner, and treatment with 10 μM loganin showed the greatest inhibitory effect on adipocyte differentiation (Figure 1A). Loganin treatment decreased the number of oil Red O-positive cells (Figure 1B). Further, the cellular viability test showed that loganin did not affect cellular viability in 3T3-L1 cells (Supplementary Figure S1). These results indicate that loganin prevents adipocyte differentiation by reducing expressions of Pparγ, Cebpa, Plin2, Fasn, and Srebp1.
|
| 75 |
+
|
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We further confirmed the anti-adipogenic effects of loganin on ADSCs isolated from mouse adipose tissues. ADSCs were induced to differentiate into adipocytes and were co-cultured with loganin (2, 5, and 10 μM) for 8 d. Consistent with the results obtained in the preadipocyte cell line, mRNA expression levels of adipogenic-related markers, including Pparγ, Cebpa, Plin2, Fasn, and Srebp1 were reduced by loganin treatment (Figure 2A), and the number of oil Red O-positive cells was also decreased (Figure 2B). These results suggest that loganin inhibits adipocyte differentiation by downregulating adipogenic-related markers (Pparγ, Cebpa, Plin2, Fasn, and Srebp1) in both 3T3-L1 mouse preadipocytes and ADSCs.
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2.2. Loganin Prevents OVX- and HFD-Induced Weight gain in Mice
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To examine the anti-adipogenic effect of loganin in vivo, we used two different animal models of obesity in mice, i.e., OVX- and HFD-induced obesity. We used the 17β-estradiol (E2; 0.03 μg/kg/d) administration as a positive control for anti-obesity, and strontium chloride (SrCl2; 10 mg/kg/d) administration as a negative control. E2 is a well-known reagent for treating menopausal obesity and SrCl2 is an anti-osteoporotic compound used for treating menopause. As expected, OVX-induced obese mice showed weight gain compared to sham-operated mice because of estrogen deficiency, further hepatic steatosis, and adipose tissue enlargement were observed. Administration of 17β-estradiol (E2), the active form of estrogen, restored OVX-induced estrogen deficiency, resulting in the prevention of weight gain, whereas the negative control group administered with the anti-osteoporotic reagent, strontium chloride (SrCl2), did not show any change in body weight compared to that of OVX-induced obese mice (Figure 3A). However, loganin administration prevented OVX-induced weight gain and reduced hepatic steatosis and adipose tissue enlargement (Figure 3A,B).
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We further investigated the anti-adipogenic effects of loganin in a mouse model of HFD-induced obesity. Six-week-old mice were fed an HFD, and loganin treatment (2 and 10 mg/kg/d) was orally administered for 12 wk. As expected, HFD increased mouse body weight compared to the normal diet (ND) (Figure 4A), and histological analysis of the HFD-induced animals showed hepatic steatosis and adipocyte enlargement (Figure 4B). However, loganin treatment prevented HFD-induced weight gain and reduced hepatic steatosis and adipocyte expansion (Figure 4A,B). Collectively, these results suggest that loganin administration inhibits OVX- and HFD-induced weight gain, hepatic steatosis, and adipocyte enlargement.
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2.3. Loganin Reduced Plasma Leptin and Insulin Levels in OVX- and HFD-Induced Obese Mice
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Finally, we evaluated the effects of loganin on the plasma levels of leptin and insulin in OVX- and HFD-induced obese mice. OVX- and HFD-induced obese mice showed a significant increase in plasma leptin and insulin levels compared to those in the sham-operated and ND groups. However, loganin administration resulted in decreased plasma leptin and insulin levels in both OVX- and HFD-induced obese mice (Figure 5). These results indicate that loganin ameliorated the OVX- and HFD-induced increase in plasma leptin and insulin levels in mice, resulting in anti-adipogenic effects in mouse models of obesity in vivo.
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3. Discussion
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Adipogenesis promotes fat accumulation in mature adipocytes during preadipocyte differentiation, and excessive fat accumulation leads to overweightness and obesity. Regarding excessive adipogenesis initiating obesity, understanding adipocyte differentiation is important to prevent obesity-related diseases [27]. This study examined the inhibitory effects of loganin in a preadipocyte 3T3-L1 mouse cell line and in primary cultured ADSCs in vitro as well as in OVX- and HFD-induced mice in vivo.
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Preadipocyte 3T3-L1 cells derived from a mouse embryonic fibroblast cell line have been widely used in biological research on adipogenesis [28]. Further, ADSCs are MSCs isolated from white adipose tissue that are most likely to recapitulate adipogenesis during adipose tissue development [29]. Complete differentiation of adipocytes is represented by the formation of lipid droplets, which are visualized using oil Red O staining [30]. In this study, 3T3-L1 preadipocytes and ADSCs induced for adipocyte differentiation and evaluated using oil Red O staining showed that loganin treatment inhibited the accumulation of lipid droplets and decreased the number of oil Red O-positive cells, indicating reduced adipocyte differentiation.
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Adipocyte differentiation is regulated by various transcription factors, including Pparγ, Cebpa, Plin2, Fasn, and Srebp1 [14,15,16]. Pparγ is considered to be a master regulator of adipogenesis and plays a central role in maintaining insulin sensitivity [31]. Cebpa binds to the Pparγ promoter and induces the expression of Pparγ isoform 2, thus enhancing adipogenesis [32]. Plin2, also known as an adipose differentiation-related protein, is a cytoplasmic lipid droplet-binding protein required for storing neutral lipids within lipid droplets in mature adipocytes [33,34]. Further, Fasn stimulates the formation of long-chain fatty acids [35,36], and Srebp1 regulates lipogenesis and fatty acid metabolism in adipocytes [37]. In this study, we examined the mRNA expression of adipogenesis-related genes using qRT-PCR. After the induction of adipocyte differentiation, increased expression of Pparγ, Cebpa, Plin2, Fasn, and Srebp1 was observed. However, loganin treatment inhibited the mRNA expression of adipogenic inducible genes in 3T3-L1 stable cells and primary ADSCs. Collectively, the in vitro results suggest that loganin treatment prevents adipocyte differentiation through the decreased accumulation of lipid droplets and downregulation of adipogenesis-related factors.
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Mouse models of obesity are widely used to investigate fat development induced by HFD and OVX in mice [38,39]. The HFD contains high amounts of calories from fat and is an appropriate method to trigger excessive fat development in an in vivo obesity model [40,41]. OVX-induced obese mice lack estradiol owing to ovary removal and mimic human menopause with increased susceptibility to gain weight [39]. Based on the in vitro results, we confirmed the attenuating effects of loganin on adipogenesis in HFD- and OVX-induced obese mice. Persistent inappropriate weight gain is strongly associated with metabolic abnormalities, such as hepatic steatosis, adipocyte hypertrophy, and hyperlipidemia [42,43,44]. Liver steatosis and adipocyte enlargement are commonly reported symptoms following excessive fat deposition [45]. A recent study suggested that loganin prevented inflammatory-associated diseases by inhibiting hepatic steatosis [46]. Furthermore, excessively elevated insulin levels inhibit hormone-sensitive lipase, an essential enzyme for lipid digestion [47]. Leptin plays a major role in regulating lipid metabolism through changes in food consumption [48]. In this study, loganin treatment inhibited HFD- and OVX-induced weight gain and fat deposition reduced metabolic abnormalities, such as hepatic steatosis and adipocyte expansion, and increased the plasma levels of insulin and leptin. The results indicated that the protective effects of loganin on metabolic abnormalities induced by HFD and OVX are probably due to anti-obesity effects rather than phytoestrogen activity. Our results thus showed that loganin reduced the total body weight along with adipogenic-associated abnormalities in two mouse models of obesity.
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Collectively, loganin promoted the reduction of adipocyte differentiation and accumulation of lipid droplets in 3T3-L1 preadipocytes and ADSCs and alleviated obesity-related phenotypes induced by OVX and HFD in vivo.
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4. Materials and Methods
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4.1. Reagents, Cell Culture and Induction of Mature Adipocytes
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Loganin was purchased from Chengdu Biopurify Phytochemicals Ltd., (Sichuan, China) and was completely dissolved in deionized water. The mouse fibroblast cell line, 3T3-L1, was obtained from the Korean Cell Line Bank (KCLB No. 10092.1). 3T3-L1 cells were maintained in high-glucose Dulbecco’s modified Eagle’s medium (DMEM; Invitrogen, Carlsbad, CA, USA) containing 10% bovine calf serum (BCS; Invitrogen, Carlsbad, CA, USA) and 1% antibiotic-antimycotic (AA; Invitrogen, Carlsbad, CA, USA). For adipogenic induction, cells (1×106 cells) were seeded in 6-well plates (SPL Life Sciences, Pocheon, Republic of Korea) and maintained until the cells reached 100% confluent. Then, the cells were replaced with DMEM containing 10% fetal bovine serum (FBS; Invitrogen, Carlsbad, CA, USA), 1% AA, 1 μM dexamethasone, 0.5 mM 3-isobutyl-1-methylxanthine, and 10 μg/mL insulin for 3 days. The medium was then incubated with DMEM containing 10% FBS, 1% AA, and 10 μg/mL insulin for 5 days. Insulin was changed every 2 days, and loganin was replaced every time the media was switched. ADSCs were isolated using the stromal vascular fraction, as previously described [49]. Briefly, 9-week-old mouse epidydimal adipose tissue was digested with collagenase type II for 1 h. The digestive solution was neutralized with low-glucose DMEM containing 10% FBS, followed by filtration using a 100 μm cell strainer (Corning, NY, USA). The cells were then centrifuged at 2500 rpm for 10 min and maintained in low-glucose DMEM containing 10% FBS and 1% AA. For the adipogenic induction of ADSCs, cells were incubated with Mesencult™ Adipogenic Differentiation Medium (STEMCELL Technologies, Vancouver, BC, Canada) for 8 d. The “Control” indicates non-treated cells, and the “Mock” indicates adipogenic induction medium-treated cells. To examine cellular viability tests, 3T3-L1 cells were incubated with loganin in cultured media for 8 d and cellular viability was assessed using D-Plus™ CCK cell viability kit (Dongin Biotech, Seoul, Republic of Korea) in absorbance at 450 nm by iMark™ Microplate Absorbance Reader (Bio-Rad, Hercules, CA, USA).
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4.2. Oil Red O Staining
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The cells were fixed with 4% paraformaldehyde (BIOSESANG, Seongnam, Republic of Korea) for 15 min and then with 70% isopropanol for 1 min. Thereafter, the cells were incubated with oil Red O (Sigma-Aldrich, St. Louis, MO, USA) for 1 h. Representative images were obtained using a light microscope (Leica Microsystems; Wetzlar, Germany). For quantification of oil Red O-positive cells, cells were destained with 100% isopropanol, and absorbance at 490 nm was measured using a microplate reader (Bio-Rad, Hercules, CA, USA). The values were normalized to the “Mock” sample (1.0) and expressed as relative values for the other samples.
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4.3. Quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR)
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Total RNA was isolated using the QIAzol Lysis Reagent (QIAGEN, Hilden, Germany), according to the manufacturer’s instructions. RNA was reverse-transcribed using the RevertAid™ H Minus First Strand cDNA synthesis kit (Fermentas, Hanover, NH, USA) under the following conditions: 2 U of Dnase Ⅰ for 30 min at 37 °C, 50 mM EDTA for 10 min at 65 °C, 1:1 ratio of Random Hexamer and Oilgo (dT) 18 primers for 5 min at 65 °C and 10 mM of dNTP mix, 20 U of RNase Inhibitor, and 200 U of RevertAid H Minus Reverse Transcriptase for 5 min at 25 °C, 1 h at 42 °C and 5 min at 70 °C. qRT-PCR was performed using the SYBR Green I qPCR kit (Takara, Shiga, Japan). The gene-specific primers used in this study were as follows: forward 5′-GCG GGA ACG CAA CAA CAT C-3′ and reverse 5′-GTC ACT GGT CAA CTC CAG CAC-3′ for mouse Cebpa, forward 5′-AAG ATG TAC CCG TCC GTG TC-3′ and reverse 5′-TGA AGG CAG GCT CGA GTA AC-3′ for mouse Srebp1, forward 5′-GGA AGA CCA CTC GCA TTC CTT-3′ and reverse 5′-GTA ATC AGC AAC CAT TGG GTC-3′ for mouse Pparg, forward 5′-GAC CTT GTG TCC TCC GCT TAT-3′ and reverse 5′-CAA CCG CAA TTT GTG GCT C-3′ for mouse Plin2, forward 5′-GGA GGT GGT GAT AGC CGG TAT-3′ and reverse 5′-TGG GTA ATC CAT AGA GCC CAG-3′ for mouse Fasn, and forward 5′-AGC TGA AGC AAA GGA AGA GTC GGA-3′ and reverse 5′-ACT TGG TTG CTT TGG CGG GAT TAG-3′ for mouse Arbp. Relative mRNA expression levels were normalized to those of mouse Arbp (ribosomal protein large P0, also known as Rplp0) expression, and fold change was determined using the 2−ΔΔCt method. The values presented in this study were expressed using “Mock” as a standard (1.0), while other values were expressed as relative values.
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4.4. Animal Study
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All animal experiments performed in this study were approved by the Institutional Animal Care and Use Committee (IACUC) of Ajou University School of Medicine (2022-0064). Mice were maintained under specific-pathogen-free conditions at the Animal Care Center at Ajou University School of Medicine and provided with standard food pellets (Feedlab Co., Ltd., Hanam, Republic of Korea) and distilled water ad libitum. The OVX- or HFD-induced obese mice were used as previously described [50,51]. For OVX-induced obese mice, sham-operated (n = 5) and OVX-induced ddY mice (n = 25) were purchased from Shizuoka Laboratory Center Inc. (Hamamatsu, Japan). OVX-induced obese mice were divided into five groups: OVX only, OVX plus β-estradiol (E2; 0.03 μg/kg/day, Sigma-Aldrich), OVX plus strontium chloride (SrCl2; 10 mg/kg/day, Sigma-Aldrich), OVX plus loganin (2 mg/kg/day), and OVX plus loganin (10 mg/kg/day). For HFD-induced obese mice, 4-week-old mice were divided into four groups (n = 5 per group): ND, HFD, HFD plus loganin (2 mg/kg/day), and HFD plus loganin (10 mg/kg/day). The total body weights of the mice were measured using a Micro Weighing Scale (CAS Corporation, Yangju, Republic of Korea) after 4, 8, and 12 weeks of the experiment. E2, SrCl2, and loganin were administered through oral gavage. At the end of the experiment, mice were euthanized using CO2, and tissue samples, including liver and fat, were fixed in 4% paraformaldehyde (BIOSESANG, Seongnam, Republic of Korea).
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4.5. Histological Analysis
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Formalin-fixed tissue samples were dehydrated and embedded in paraffin. The paraffin blocks were sectioned using a rotary microtome (3 μm; Leica Microsystems, Wetzler, Germany). The tissue slides were stained with hematoxylin and eosin (H&E; SSN Solutions, London, UK). Briefly, the sectioned slides were deparaffinized using xylene and rehydrated using sequentially treated ethanol (100%, 95%, and 70%). Slides were stained with Harris hematoxylin solution and differentiated using 1% acid alcohol. Bluing was performed using 0.2% ammonia water and counterstained with eosin Y solution. The slides were then dehydrated using sequentially treated ethanol (70%, 95%, and 100%), cleared with xylene, and mounted using mounting medium (Leica Microsystems, Wetzler, Germany). Slide scanning was performed using an Axioscan Z1 slide scanner (Carl Zeiss).
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4.6. Plasma Analysis
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At the end of the experiment, blood samples were obtained from mice using cardiac puncture, collected in EDTA tubes, and stored at −80 °C until use. Plasma leptin and insulin levels were determined using a customized MILLIPLEX® Mouse Adipokine Magnetic Bead Panel (MADKMAG-71K; Millipore, Billerica, MA, USA) and a MAGPIX® multiplex analyzer (Luminex, Austin, TX, USA).
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4.7. Statistical Analysis
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Data in bar graphs are expressed as mean ± standard error of the mean (SEM) using GraphPad Prism 9.2.0 software (GraphPad Software, San Diego, CA, USA). Statistical significance was determined using one-way analysis of variance (ANOVA), followed by Tukey’s honest post hoc test using the professional Statistical Package software (SPSS 25.0 for Windows, SPSS Inc., Chicago, IL, USA).
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5. Conclusions
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This study revealed the inhibitory effects of loganin on adipogenesis in 3T3-L1 preadipocytes, ADSCs, and on OVX- and HFD-induced obesity models in mice. Loganin treatment decreased adipocyte differentiation and lipid droplet accumulation by reducing the mRNA expression of adipogenesis-related factors. In OVX- and HFD-induced obese mice, loganin attenuated the representative obesity phenotypes, including hepatic steatosis, adipocyte hypertrophy, and increased plasma levels of leptin and insulin. These findings indicate the strong potential of loganin as a therapeutic agent for treating and preventing obesity.
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Supplementary Materials
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The supporting information can be downloaded at https://www.mdpi.com/article/10.3390/ijms24054752/s1.
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Click here for additional data file.
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Author Contributions
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Conceptualization, S.-Y.J. and E.P.; methodology, E.P.; investigation, H.J. (Hyoju Jeon), C.-G.L., H.J. (Hyesoo Jeong), S.-H.Y., J.K., L.P.U., K.-I.O., S.S. and J.Y.; data curation, C.-G.L.; writing—original draft preparation, H.J. (Hyoju Jeon), C.-G.L., H.J. (Hyesoo Jeong) and S.-H.Y.; writing—review and editing, S.-Y.J. and E.P.; supervision, S.-Y.J.; funding acquisition, S.-Y.J. All authors have read and agreed to the published version of the manuscript.
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Institutional Review Board Statement
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The animal study performed in this study was approved by the Institutional Animal Care and Use Committee (IACUC) of the Ajou University School of Medicine (2022-0064) and the experiments were processed according to the guidelines of the committee.
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Informed Consent Statement
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Not applicable.
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Data Availability Statement
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The data presented in this research is available on request from the corresponding author.
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Conflicts of Interest
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The authors declare no conflict of interest. Nine B Co., Ltd. collaboratively participated in this study funded by the Korea Industrial Technology Association funded by the Ministry of Science and ICT in the Korean government (grant number: KOITA-RND2-2022-1). H.J. and S.-H.Y are employed by Nine B Co., Ltd. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.
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Figure 1 Inhibitory effects of loganin on mouse preadipocyte differentiation. Notably, 3T3-L1 cells underwent adipogenesis after being treated with MDI (3-isobutyl-1-methylxanthine, dexamethasone, and insulin) for 3 days, followed by insulin treatment for 5 days. During the 8 days of the adipogenesis period, loganin was administered at various concentrations (2, 5, and 10 μM). (A) mRNA expression levels of Pparg, Cebpa, Plin2, Fasn, and Srebp1 were examined using qRT-PCR. (B) Oil Red O-positive cells were visualized using a light microscope (left), and stained cells were quantified by relative absorbance at 490 nm (right) using microplate reader. * p < 0.05 vs. Induction, # p < 0.05 vs. Lo 2. $ p < 0.05 vs. Lo 5. Lo; Loganin.
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Figure 2 Inhibitory effects of loganin on mouse primary adipocyte differentiation. ADSCs were induced for adipocyte differentiation and co-treated with loganin (2, 5, and 10 μM) for 8 d. (A) mRNA expression levels of Pparg, Cebpa, Plin2, Fasn and Srebp1 were examined using qRT-PCR. (B) Oil Red O-positive cells were visualized using a light microscope. * p < 0.05 vs. Induction, # p < 0.05 vs. Lo 2, $ p < 0.05 vs. Lo 5. Lo, Loganin.
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Figure 3 Ameliorative effects of loganin on OVX-induced mouse gain weight. OVX-induced obese mice were administered E2, SrCl2, or loganin (2 and 10 mg/kg/day) for 12 weeks. (A) Body weight changes during the 12 weeks of the experiment. n = 5 per group. (B) Representative images of H&E-stained mouse liver and fat tissue sections. * p < 0.05 vs. OVX, # p < 0.05 vs. SrCl2, $ p < 0.05 vs. Lo 2. Sham, sham-operated mice; OVX, ovariectomized mice; Lo, loganin.
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Figure 4 Anti-obesity effects of loganin on HFD-induced obese mice. Mice were administered with ND, HFD, or HFD with different concentrations of loganin (2 and 10 mg/kg) for 12 weeks. (A) Body weight changes throughout 12 weeks of the experiment. n = 5 per group. (B) Representative images of H&E-stained mouse liver and fat tissue sections. * p < 0.05 vs. HFD, $ p < 0.05 vs. Lo 2. ND, normal diet; HFD, high-fat diet; Lo, loganin.
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Figure 5 Effects of loganin on plasma levels of leptin and insulin in obese mice. (A) OVX-induced obese mice were administered E2, SrCl2, or loganin (2 and 10 mg/kg/day) for 12 weeks. (B) Mice were administered with ND, HFD, or HFD with different concentrations of loganin (2 and 10 mg/kg) for 12 weeks. Plasma leptin (left) and insulin (right) levels were examined using ELISA. * p < 0.05 vs. OVX or HFD, # p < 0.05 vs. SrCl2, $ p < 0.05 vs. Lo 2. Sham, sham-operated mice; OVX, ovariectomized mice; ND, normal diet; HFD, high-fat diet; Lo, loganin.
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| 225 |
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|
puc/PMC10003660.txt
ADDED
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Int J Mol Sci
|
| 4 |
+
Int J Mol Sci
|
| 5 |
+
ijms
|
| 6 |
+
International Journal of Molecular Sciences
|
| 7 |
+
1422-0067
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
10.3390/ijms24054561
|
| 11 |
+
ijms-24-04561
|
| 12 |
+
Article
|
| 13 |
+
Skeletal Muscle-Derived Exosomal miR-146a-5p Inhibits Adipogenesis by Mediating Muscle-Fat Axis and Targeting GDF5-PPARγ Signaling
|
| 14 |
+
https://orcid.org/0000-0001-5990-6550
|
| 15 |
+
Qin Mengran Methodology Software Formal analysis Investigation Data curation Writing – original draft Writing – review & editing 1†
|
| 16 |
+
Xing Lipeng Validation Investigation Writing – review & editing 1†
|
| 17 |
+
Wu Jiahan Investigation 1
|
| 18 |
+
Wen Shulei Investigation 1
|
| 19 |
+
Luo Junyi Investigation Writing – review & editing 1
|
| 20 |
+
Chen Ting Investigation 1
|
| 21 |
+
Fan Yaotian Investigation 1
|
| 22 |
+
Zhu Jiahao Investigation 1
|
| 23 |
+
Yang Lekai Validation 1
|
| 24 |
+
https://orcid.org/0000-0002-5028-8589
|
| 25 |
+
Liu Jie Investigation 1
|
| 26 |
+
Xiong Jiali Investigation 1
|
| 27 |
+
Chen Xingping Validation 2
|
| 28 |
+
Zhu Canjun Validation 1
|
| 29 |
+
https://orcid.org/0000-0001-9190-9401
|
| 30 |
+
Wang Songbo Investigation 1
|
| 31 |
+
https://orcid.org/0000-0001-8133-3349
|
| 32 |
+
Wang Lina Investigation 1
|
| 33 |
+
Shu Gang Investigation 1
|
| 34 |
+
Jiang Qingyan Investigation 1
|
| 35 |
+
Zhang Yongliang Investigation Project administration Funding acquisition 1
|
| 36 |
+
https://orcid.org/0000-0003-1992-154X
|
| 37 |
+
Sun Jiajie Investigation Writing – review & editing Project administration Funding acquisition 1*
|
| 38 |
+
Xi Qianyun Investigation Writing – review & editing Visualization Project administration Funding acquisition 1*
|
| 39 |
+
Gomez-Muñoz Antonio Academic Editor
|
| 40 |
+
1 Guangdong Provincial Key Laboratory of Animal Nutrition Control, State Key Laboratory of Livestock and Poultry Breeding, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, No. 483 Wushan Road, Guangzhou 510642, China
|
| 41 |
+
2 Jiangxi Province Key Laboratory of Animal Nutrition, College of Animal Science and Technology, Jiangxi Agricultural University, Nanchang 330045, China
|
| 42 |
+
* Correspondence: jiajiesun@scau.edu.cn (J.S.); xqy0228@scau.edu.cn (Q.X.)
|
| 43 |
+
† These authors contributed equally to this work.
|
| 44 |
+
|
| 45 |
+
25 2 2023
|
| 46 |
+
3 2023
|
| 47 |
+
24 5 456124 1 2023
|
| 48 |
+
13 2 2023
|
| 49 |
+
22 2 2023
|
| 50 |
+
© 2023 by the authors.
|
| 51 |
+
2023
|
| 52 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 53 |
+
Skeletal muscle-fat interaction is essential for maintaining organismal energy homeostasis and managing obesity by secreting cytokines and exosomes, but the role of the latter as a new mediator in inter-tissue communication remains unclear. Recently, we discovered that miR-146a-5p was mainly enriched in skeletal muscle-derived exosomes (SKM-Exos), 50-fold higher than in fat exosomes. Here, we investigated the role of skeletal muscle-derived exosomes regulating lipid metabolism in adipose tissue by delivering miR-146a-5p. The results showed that skeletal muscle cell-derived exosomes significantly inhibited the differentiation of preadipocytes and their adipogenesis. When the skeletal muscle-derived exosomes co-treated adipocytes with miR-146a-5p inhibitor, this inhibition was reversed. Additionally, skeletal muscle-specific knockout miR-146a-5p (mKO) mice significantly increased body weight gain and decreased oxidative metabolism. On the other hand, the internalization of this miRNA into the mKO mice by injecting skeletal muscle-derived exosomes from the Flox mice (Flox-Exos) resulted in significant phenotypic reversion, including down-regulation of genes and proteins involved in adipogenesis. Mechanistically, miR-146a-5p has also been demonstrated to function as a negative regulator of peroxisome proliferator-activated receptor γ (PPARγ) signaling by directly targeting growth and differentiation factor 5 (GDF5) gene to mediate adipogenesis and fatty acid absorption. Taken together, these data provide new insights into the role of miR-146a-5p as a novel myokine involved in the regulation of adipogenesis and obesity via mediating the skeletal muscle-fat signaling axis, which may serve as a target for the development of therapies against metabolic diseases, such as obesity.
|
| 54 |
+
|
| 55 |
+
skeletal muscle
|
| 56 |
+
exosomes
|
| 57 |
+
miR-146a-5p
|
| 58 |
+
adipogenesis
|
| 59 |
+
GDF5
|
| 60 |
+
crosstalk
|
| 61 |
+
PPARγ
|
| 62 |
+
Natural Science Foundation of China32072814 32072812 32072714 Project of Guangdong Provincial Nature Science Foundation2023A1515012511 2019A15150117734 2021A1515011310 This research was funded by the Natural Science Foundation of China (32072814, 32072812, and 32072714) and the Project of Guangdong Provincial Nature Science Foundation (2023A1515012511, 2019A15150117734 and 2021A1515011310).
|
| 63 |
+
==== Body
|
| 64 |
+
pmc1. Introduction
|
| 65 |
+
|
| 66 |
+
Adipose tissue and skeletal muscle are highly heterogeneous endocrine organs that secrete several hormones, with myokines and adipokines participating in local autocrine/paracrine interactions and crosstalk with other tissues [1]. Myokines and adipokines are essential for the maintenance of body muscle and fat levels and modulation of the body composition [2]. Irisin stimulates uncoupling protein 1 (UCP1) expression on white adipose cells in vitro and in vivo, which results in brown-fat-like development, while muscle-specific expression of PPARγ coactivator-1 α (PGC1α) drives browning of subcutaneous white adipose tissue [3]. As reported, the muscle interleukin-6 (IL-6) influences the main neuropeptides for energy homeostasis in a sex-specific manner [4]. The hormone myostatin inhibits myogenesis and promotes adipogenic differentiation of mesenchymal cells [5]. Prolyl hydroxylase 3 (PHD3) losses during endurance exercise challenges improve exercise capacity [6]. In mice with GR mKOs in the skeletal muscle, muscle mass is increased, while fat tissue is smaller [7]. The present study demonstrated that exercise induces myokines to counteract the negative effects of pro-inflammatory adipokines [8]. In recent years, there has been increased interest in investigating the effects of exercise training on adipose tissue [9].
|
| 67 |
+
|
| 68 |
+
Exosomes are small extracellular vesicles with a diameter of 50–150 nm, which are formed when multivesicular endosomes fuse with the plasma membrane and contained biologically active substances, such as proteins, RNA, DNA, cholesterol, etc. [10,11]. Secreted exosomes are taken up by and deliver their content to the recipient cells, thus representing a novel intercellular communication pathway [12]. Muscle and adipose exosomes can act as a mediator of intercellular communication to exert their physiological regulatory functions. There is increasing evidence that exosomes released by myogenic cells can transport their proteins, mRNAs, and miRNAs to recipient cells and regulate myocyte function in an autocrine or paracrine manner [13]. They can also enter the circulatory system, such as the blood, and may act on distant tissues [14,15]. The incorporation of muscle exosomes into various tissues in vivo, including the pancreas and liver, suggests that skeletal muscle (SKM) could transfer specific signals via the exosomal route to key metabolic tissues [16]. Endocytosis, membrane fusions, and receptor-mediated internalization are the mechanisms by which exosomes are absorbed intracellularly [17]. These variable internalization mechanisms and the signaling molecules presenting in exosomes are the reason why exosomes are widely accepted as important players of intercellular communication in the microenvironment and worthy of investigation [18].
|
| 69 |
+
|
| 70 |
+
The miRNA gene family adds a new layer of regulation and fine-tuning to gene expression that may affect a wide range of cellular functions, including metabolism, and numerous studies indicate that miRNAs play important roles in diverse aspects of signaling and metabolism, despite their unknown functions [19]. miR-27a released from adipocytes of high-fat diet-fed C57BL/6J mice was associated with a triglyceride accumulation. Exosomal miR-27a derived from adipocytes induces insulin resistance in C2C12 muscle cells through miR-27a-mediated repression of PPARγ and downstream genes involved in obesity [20]. miR-130b’s circulation could act as a metabolic mediator in adipose-muscle crosstalk, as well as a potential contributor to obesity-associated metabolic diseases [21]. MiR-124 secreted by adipose-derived stem cells has been implicated in skin wound healing, possibly by targeting MALAT1 and activating Wnt/catenin signaling pathways [22]. Accumulating evidence indicates that miR-146a-5p is a multifunctional miRNA that can act as a multidirectional target to regulate body metabolism. Mechanistically, miR-146a-5p attenuates TGF-β signaling by directly targeting SMAD family member 4 (SMAD4), thereby inhibiting cell proliferation, and attenuates AKT/mTORC1 signaling by targeting TNF receptor-associated factor 6 (TRAF6) to inhibit the differentiation of intramuscular preadipocytes [23]. Further studies revealed that hepatic miR-146a-5p overexpression significantly improved glucose and insulin tolerance as well as lipid accumulation in the liver by targeting the mediator complex subunit 1 gene (MED1) to promote the oxidative metabolism of fatty acids [24]. In long-living Ame’s dwarf (df/df) mice, miR-146a-5p mimetic treatment increased cellular senescence and inflammation and decreased pro-apoptotic factors in visceral adipose tissue [25]. Furthermore, the miR-146a gene might be a powerful target for preventing age-related bone dysfunctions such as the formation of bone marrow adiposity and osteoporosis [26]. However, whether skeletal muscle-derived exosomes by transferring miRNAs and then affects adipogenesis associated signaling pathways remains elusive.
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Recently, we compared the expression profiles of miRNA between exosomes derived from skeletal muscle and adipose tissue [27]. The findings showed that the content of miR-146a-5p in skeletal muscle-derived exosomes was more than 50 times higher than that in fat-derived exosomes, indicating that the miR-146a-5p may play a crucial role in regulating the skeletal muscle-fat axis. In this study, we intend to explore the connection between skeletal muscle and adipose tissue via the mediation of exosomes, especially, miR-146a-5p from skeletal muscle-derived exosomes mediating crosstalk between skeletal muscle and adipose tissue. Through transwell assay, gain-of-function and loss-of-function strategies in cell models, and skeletal muscle-specific miR-146a-5p knockout animal models, in vitro and in vivo studies have gradually revealed the exosomal miR-146a-5p released from skeletal muscle as a new myokine involved in the regulation of adipogenesis via mediating the skeletal muscle-fat signaling axis.
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2. Results
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2.1. Transwell Co-Culture of C2C12 Cells Inhibits the Adipogenesis of 3T3-L1 Cells
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To further determine whether muscle cells can regulate adipocyte differentiation and lipid deposition via secreted exosomes, we used the transwell co-culture experiments with C2C12 cells and 3T3-L1 cells to test this possibility (Figure 1a). C2C12 myoblasts during proliferation (Pro) were cultured in vitro and induced to differentiate into mature myofibroblasts (Diff) (Figure 1b). The result showed that the differentiated C2C12 cells promoted the deposition of lipid droplets (Figure 1c), and significantly increased the content of TG in 3T3-L1 cells (Figure 1d). Next, we extracted the exosomes from the proliferation stage (Pro-Exos) and differentiation stage (Diff-Exos), respectively, and determined the morphology of Pro-Exos and Diff-Exos by electron microscopy (Figure 1e); nanoparticle tracking analysis (NTA) showed that the exosomes were mainly concentrated at 130–150 nm (Figure 1f), and the exosome marker proteins such as apoptosis-linked gene 2-interacting protein X (Alix), tumor susceptibility gene 101 (TSG101), CD9, and CD63 were mainly enriched in Pro-Exos and Diff-Exos, while the endoplasmic reticulum marker protein Calexin was mainly enriched in cells (Figure 1g), indicating that the exosomes were successfully extracted. Interestingly, we found that the expression of miR-146a-5p in the C2C12 cells’ proliferation stage was significantly higher than that in the differentiation stage of C2C12 cells, and the same expression level of miR-146a-5p also existed in the secreted exosomes (Pro-Exos and Diff-Exos) (Figure 1h). Then, 3T3-L1 cells were treated with Pro-Exos and Diff-Exos and induced to differentiate. RT-qPCR showed that Pro-Exos inhibited the mRNA levels of adipogenesis-related transcriptional factors PPARγ and C/EBPα (Figure 1i–j), and fatty acid synthesis-related genes CD36 and FABP4 (Figure 1k–l), on the contrary, the results of Diff-Exos treatment are reversed. These results suggest that the co-culture of C2C12 cells can inhibit adipogenesis of 3T3-L1 cells, and the reason may be related to exosomal miR-146a-5p secreted by C2C12 cells.
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2.2. C2C12 Cells-Derived Exosomes Affect Glucose and Fatty Acid Uptake in 3T3-L1 Cells via Transferring of miR-146a-5p
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To further explore whether skeletal muscle-derived exosomes are involved in regulating adipogenesis and metabolism, especially via miR-146a-5p, we cultured 3T3-L1 adipose precursor cells in vitro to induce their maturation. The results showed that the deposition of lipid droplets and the content of TG in the Pro-Exos treated group was significantly smaller than that of the Diff-Exos group. However, Pro-Exos + i group the miR-146a-5p inhibitor co-treated with Pro-Exos 3T3-L1 cells obtained a similar phenotype to Diff-Exos, indicating that the downregulation of muscle exosomal miR-146a-5p can improve adipogenesis. Similarly, after co-treatment of Diff-Exos with miR-146a-5p mimics (Diff-Exos + m), lipid droplet phenotype and TG content are similar to that of Pro-Exos (Figure 2a,b). Subsequently, the expressions of adipogenesis-related proteins GDF5, PPARγ, C/EBPα, and fatty acid synthesis-related proteins FABP4 and FASN were detected in 3T3-L1 cells of each group. The expression of these proteins was found to be significantly lower in the Pro-Exos and Diff-Exos + m treated groups than in the Diff-Exos and Pro-Exos + i treated groups (Figure 2c,d). To further explore whether skeletal muscle-derived exosomes can affect adipogenesis by affecting glucose and fatty acid uptake in adipocytes, we used fluorescently labeled glucose (2-NBDG) and fatty acids (Bodipy-FA) to observe glycolipid absorption. The amount of glucose absorbed by 3T3-L1 cells in the Pro-Exos treatment group was significantly smaller than that in the Diff-Exos treatment group for the same period. In the Pro-Exos + i group, the glucose uptake of 3T3-L1 cells was significantly greater than that in the Pro-Exos group, and in the Diff-Exos + m group, the absorption of glucose by 3T3-L1 cells was significantly lower than that in the Diff-Exos group (Figure 2e,f). Pro-Exos and Diff-Exos + m treated 3T3-L1 cells had significantly less uptake of free fatty acids than Diff-Exos and Pro-Exos + i treated groups (Figure 2g,h). Experiments showed that C2C12 cells-derived Pro-Exos can inhibit glucose and fatty acid uptake in 3T3-L1 cells, while Diff-Exos can promote glucose and fatty acid uptake in 3T3-L1 cells. Adding the inhibitor and mimics of miR-146a-5p to pro-Exos and diff-Exos, respectively, could reverse the effects of exosomal treatment alone on adipogenesis and glycolipid transport metabolism in 3T3-L1 cells. In summary, the above results highlight the important roles of exosomal miR-146a-5p in mediating the interactions between skeletal muscle cells and the adipocytes’ microenvironment.
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2.3. miR-146a-5p Significantly Inhibits Adipogenesis, Glucose Uptake and Fatty Acid Absorption in 3T3-L1 Cells
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+
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To further determine the role of skeletal muscle-derived exosomes in affecting adipogenesis mediated through miR-146a-5p, 3T3-L1 cells were transfected with miR-146a-5p mimics (Mimics) and miR-146a-5p inhibitor (Inhibitor) and induced to mature. The transfection efficiency of miR-146a-5p was quantitatively analyzed first. The expression of miR-146a-5p in 3T3-L1 cells transfected with miR-146a-5p mimics increased 166 times. However, the expression of miR-146a-5p in the miR-146a-5p inhibitor transfected group was also reduced by 33%, and both reached a statistically significant level (Figure 3a). For TG content in each group, it was significantly decreased for miR-146a-5p mimics and significantly increased for miR-146a-5p inhibitor (Figure 3b). At the same time, the results of Oil Red O staining showed that miR-146a-5p mimics could significantly reduce lipid droplet synthesis, while there is a significant increase in miR-146a-5p inhibitor (Figure 3c). To confirm the effect of skeletal muscle-derived exosomes on adipocyte glucose uptake and fatty acid absorption is mediated by miR-146a-5p, we used 2-NBDG and Bodipy-FA to examine the efficiency of glycolipid uptake in 3T3-L1 cells. The 3T3-L1 cells with miR-146a-5p inhibitor treatment significantly increased the uptake of glucose and the absorption of free fatty acids, while miR-146a-5p mimics treatment significantly reduced glucose uptake and free fatty acid uptake (Figure 3d–g). It was found by qPCR that miR-146a-5p mimics could significantly reduce the expression of adipogenesis-related genes PPARγ, C/EBPα, and fatty acid synthesis-related genes CD36, FABP4, and FASN, while miR-146a-5p inhibitor significantly increased the expression levels of these genes (Figure 3h). Western blot results were consistent with the quantitative results that miR-146a-5p mimics significantly decreased the expression of adipogenesis-related proteins PPARγ, C/EBPα, and fatty acid synthesis-related proteins CD36, FABP4, and FASN, while miR-146a-5p inhibitor significantly increased the expression of these proteins (Figure 3i–j). The results showed that miR-146a-5p significantly inhibited the differentiation, glucose uptake, and fatty acid absorption of 3T3-L1 preadipocytes.
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2.4. miR-146a-5p as a Negative Regulator of PPARγ Signaling by Directly Targeting GDF5 to Inhibit Adipogenesis
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To determine the targeting mechanism of miR-146a-5p inhibiting adipogenesis, the bioinformatics database miRDB was used to identify putative target genes for miR-146a-5p given the above adipogenesis-related genes and found that miR-146a-5p has a target interaction with the 3′UTR of GDF5 (Figure 4a). Subsequently, the relationship between miR-146a-5p and GDF5 was verified by dual luciferase and miR-146a-5p targeted the 3′UTR of GDF5 and reduced dual-luciferase expression (Figure 4b). In addition, we examined the protein and gene expression changes of GDF5 after miR-146a-5p overexpression and knockdown. As expected, miR-146a-5p overexpression decreased GDF5 protein expression, whereas miR-146a-5p knockdown increased GDF5 protein expression (Figure 4c,d). At the same time, overexpression of miR-146a-5p reduced GDF5 gene expression, and knockdown of miR-146a-5p increased GDF5 gene expression (Figure 4e), which is in line with the trend of miRNA regulation of target genes, and also indicated that miR-146a-5p targeted GDF5. To verify that miR-146a-5p regulates the PPARγ signaling pathway by targeting GDF5, three siRNAs against GDF5 were designed. First, the protein knockdown efficiency of GDF5 siRNA were verified, and GDF5 siRNA-3 significantly reduced GDF5 protein expression (Figure 4f,g). 3T3-L1 cells were transfected with different miR-146a-5p nucleic acid analogs and siRNA (NC, GDF5 siRNA, miR-146a-5p inhibitor + GDF5 siRNA), and the cells were cultured until mature. In 3T3-L1 cells treated with GDF5 siRNA, the expression levels of adipogenesis-related genes GDF5, PPARγ, C/EBPα and fatty acid synthesis-related genes CD36, FABP4 and FASN were significantly decreased, while in those co-treated with GDF5 siRNA and miR-146a-5p inhibitor, the gene expressions of adipogenesis-related genes GDF5, PPARγ, C/EBPα and fatty acid synthesis-related genes CD36, FABP4 and FASN were significantly increased compared with just GDF5 siRNA treatment (Figure 4h). Western blotting results further verified that 3T3-L1 cells transfected GDF5 siRNA significantly reduced the expressions of adipogenesis-related proteins GDF5, PPARγ, C/EBPα, and fatty acid synthesis-related proteins CD36, FABP4, and FASN, while in those co-transfected with miR-146a-5p inhibitor and GDF5 siRNA, the expressions of adipogenesis-related proteins GDF5, PPARγ, C/EBPα and fatty acid synthesis-related proteins CD36, FABP4, and FASN were significantly increased (Figure 4i–j). We found that the content of TG and lipid droplets in the GDF5 siRNA treatment group were significantly lower than NC group, while the co-treatment of GDF5 siRNA and miR-146a-5p inhibitor significantly increased TG and lipid droplet content (Figure 4k–l). Co-immunoprecipitation (co-IP) test further showed that GDF5 has a protein-protein interaction relationship with PPARγ, C/EBPα, CD36, and FASN (Figure 4m). These results suggested that GDF5 participated in adipogenesis by regulating the PPARγ signaling pathway, indicating that miR-146a-5p regulated the PPARγ signaling pathway by targeting GDF5.
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2.5. Skeletal Muscle-Specific Knockout miR-146a-5p Significantly Increased Body Weight Gain and Decreased Oxidative Metabolism in Mice
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| 93 |
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| 94 |
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To further explore the function of miR-146a-5p, we constructed a skeletal muscle-specific knockout mouse model of miR-146a-5p. Through Sanger sequencing and genotyping results, we confirmed that the mKO mice were successfully constructed (Figure 5a,b). By qPCR, the expression of miR-146a-5p was significantly knocked down in the gastrocnemius (GAS) and tibialis anterior (TA) of mKO mice compared with Flox mice (Figure 5c). Flox and mKO mice were induced with a high-fat diet (HFD) to observe the effect on the growth and metabolism of the mice. During the experiment, it was found that the HFD induction significantly increased the body weight gain of the mKO mice (Figure 5d). We found a significant decrease in muscle mass in both GAS and TA in mKO mice (Figure 5e). However, there was no difference in feed intake (Figure 5f). The skeletal muscle had no significant effect on insulin resistance in miR-146a-5p knockout mice (Figure 5g), but significantly improved glucose tolerance (Figure 5h). In terms of respiratory metabolism, O2 inhalation and CO2 exhalation in the skeletal muscle of miR-146a-5p knockout mice (mKO) were significantly lower than those in the Flox mice (control group) (Figure 5i–l). To a certain extent, O2 inhalation and CO2 exhalation reflect the energy metabolism level of the body. Therefore, the experiment showed that the skeletal muscle-specific miR-146a-5p knockout could increase body weight gain and reduce oxidative metabolism in mice.
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+
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| 96 |
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2.6. Skeletal Muscle-Specific Knockout miR-146a-5p Significantly Increased Adipogenesis in Mice by Up-Regulating GDF5 and PPARγ
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| 97 |
+
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| 98 |
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To further explore how miR-146a-5p knockdown in the skeletal muscle regulates adipogenesis in vivo, the body composition and body imaging of the mice were observed, and the lean mass content of mKO mice was significantly reduced; interestingly, the fat mass content and fat enrichment increased instead, which successfully confirmed the crosstalk in the skeletal muscle and fat axis (Figure 6a,b). For further verification, the tissue weights of inguinal white adipose tissue (IngWAT) and epididymal white adipose tissue (EpiWAT) in mKO mice were found to be significantly higher than those in Flox mice (Figure 6c). At the same time, the HE-stained sections of IngWAT and EpiWAT tissues intuitively revealed that the adipocytes in mKO mice were larger and plumper (Figure 6d). qPCR analysis of adipogenesis-related gene expression showed that the expressions of GDF5, PPARγ, C/EBPα, and fatty acid synthesis-related genes CD36, FABP4, FASN in IngWAT of mKO mice were significantly increased compared with that of Flox mice (Figure 6e). Consistent with the quantitative results, the proteins of these genes were also more highly expressed in the IngWAT tissues of mKO mice (Figure 6f,g). Similarly, in the EpiWAT tissue of mKO mice, the expression of GDF5, PPARγ, C/EBPα, and fatty acid synthesis-related genes CD36, FABP4, FASN was significantly higher than that of Flox mice (Figure 6h), and the protein expressions of these genes were also significantly higher than those of Flox mice (Figure 6i–j). These results suggested that skeletal muscle miR-146a-5p knockout significantly increased adipogenesis in mice.
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| 100 |
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2.7. The Internalization of miR-146a-5p into the mKO Mice by Injecting Flox-Exos Inhibits Adipogenesis
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| 101 |
+
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| 102 |
+
To further explore the function of skeletal muscle-derived exosomes, two different skeletal muscle-derived exosomes (Flox-Exos, mKO-Exos) were extracted and identified (Supplementary Figure S1a–c), and the expression level of miR-146a-5p was detected (Figure 7a). The skeletal muscle-derived exosomes were labeled with PKH67 and injected into mice via the tail vein, which was distributed in different organs after 24 h. Interestingly, imaging showed that PKH67-labeled exosomes were mainly distributed in IngWAT, EpiWAT, visceral adipose tissue (VAT), brown adipose tissue (BAT), GAS, TA, liver, lung, kidney (with a small enrichment in extensor digitorum longus (EDL)), soleus (SOL), heart, and spleen (Figure 7b). This indicated that skeletal muscle-derived exosomal miR-146a-5p could be specifically taken up into the fat tissues through humoral circulation (Figure 7c). When mice were continuously injected with skeletal muscle-derived exosomes for 3 weeks (Figure 7d), the body weight gain of Flox-Exos injected mice was significantly reduced at 2 weeks (Figure 7e), and the body weight was also different at 3 weeks (Figure 7f), but there was no difference in feed intake (Figure 7g). After aKO mice were injected with Flox-Exos, IngWAT and EpiWAT tissue weight in mice was significantly reduced (Figure 7h), and the fat mass in body composition decreased significantly, while the lean content showed an increasing trend (Figure 7i), and in vivo imaging also showed fat enrichment was decreased compared to injected with mKO-Exos (Figure 7j). In tissue sections, we found decreased accumulation of lipid droplets in the adipose tissue of mice injected with Flox-Exos (Figure 7k,o). Further studies found that IngWAT adipogenesis and fatty acid synthesis-related mRNA levels were significantly reduced in Flox-Exos-injected mice (Figure 7l), and protein levels were also significantly reduced (Figure 7m,n). Similar results were seen for EpiWAT adipogenesis and fatty acid synthesis-related mRNA and protein levels (Figure 7p–r). These results suggested that miR-146a-5p in skeletal muscle-derived exosomes can be specifically enriched in the adipose tissue, further affecting adipogenesis. Taken together, SKM-Exos-mediated intercellular miR-146a-5p has great potential for the prevention and treatment of obesity.
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3. Discussion
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By binding the 3′UTR of mRNA, miRNAs regulate metabolic homeostasis by repressing or degrading the translation of target mRNA [28]. miR-146a is lowered in obese and type 2 diabetic patients, and mice fed a high-fat diet (HFD) show exaggerated weight gain, increased adiposity, hepatosteatosis, and dysregulated blood glucose levels compared to wild-type controls [29]. miR-146a may be involved in the regulation of inflammation in orbital fibroblasts, contributing to GO pathogenesis [30]. Exosomes derived from miR-146a-modified ADSCs reduced acute myocardial infarction (AMI)-induced myocardial damage by downregulating early growth response factor 1 (EGR1) [31]. Both in vitro and in vivo, miR-146a negatively regulates osteogenesis and bone regeneration in ADSCs [32]. In WAT, miR-146a may contribute to the regulation of inflammatory processes and prevent an overreaction to inflammation [33]. However, some studies suggest that miR-146a deficiency increases inflammation in the liver tissue without affecting lipid deposition in the liver [34]. Our findings indicate that low-abundance miR-146a-5p skeletal muscle-derived exosomes could be circulated to adipose tissue and increase adipogenesis. This indicates that miR-146a-5p plays different roles in different organs.
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The interaction between skeletal muscle and fat is dynamic, in which excessive accumulation of fat can cause skeletal muscle atrophy that in turn increases fat differentiation [35]. Adipose tissue is an important fuel reservoir for animal bodies, providing energy for energy-consuming tissues such as the skeletal muscle and ensuring the normal energy operation of the body. The exosome is a natural vehicle for intercellular communication that can penetrate tissues, and diffuse into the blood [36]. These exosomes carry proteins, mRNA, and miRNA for mediating intercellular communication and regulating the function of the recipient cells [37,38]. Previous studies have shown that miR-146a-5p mimics inhibit the proliferation and differentiation of porcine intramuscular adipocyte precursor cells, whereas miR-146a-5p inhibitors promote cell proliferation and adipogenic differentiation of adipogenic precursor cells [23]. After miR-146a-/- systemic knockout, mice were fed a high-fat diet, and their body weight gain was significantly higher; additionally, the sliced cells in the adipose tissue of the mice were significantly larger than those of the control group [39], which is consistent with the phenotype of muscle-specific miR-146a knockout mice in this study. Our study demonstrated that after knocking out miR-146a-5p in mouse skeletal muscle tissue, the adipose tissue showed a promotion effect the same as a miR-146a-5p inhibitor on adipogenic formation, revealing that the skeletal muscle tissue has a potential regulatory effect on adipose development, and the skeletal muscle-derived exosome is the bridge between the two tissues. Thus, the miR-146a-5p is critical for regulating the balance between normal skeletal muscle development and adipogenesis.
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In this study, the target gene of miR-146a-5p, GDF5, is a member of the TGF-β superfamily. GDF5 is mainly expressed in developing joints and lateral edges of joints and is a key regulator of cartilage and bone formation [40,41,42]. In addition, GDF5 also plays a key role in embryogenesis, limb development, and connective tissue repair [43]. Overexpression of GDF5 promotes brown adipocyte development in a transgenic mouse model [44]. PPARγ is the main regulatory gene of adipocyte proliferation and differentiation, which promotes adipocyte differentiation and increases the expression of lipid metabolism-related genes. As an important marker gene of adipose differentiation, PPARγ is of great significance to study the regulation of miRNAs. Up to now, a large number of studies have reported that miRNAs can directly or indirectly target the PPARγ signaling pathway to regulate lipid metabolism [45,46]. Subsequent studies found that there is a positive correlation between the gene and protein expressions of GDF5 and PPARγ during the differentiation of 3T3-L1 cells [47]. As research continues, the types of miRNAs found that regulate the expression of PPARγ have increased, and their regulatory mechanisms are gradually explored, providing more selectivity for future applications such as obesity treatment. The present study thus shows that miR-146a-5p internalization plays a critical role in SKM-Exos-mediated of adipogenesis, although other signaling pathways being regulated by GDF5/PPARγ-related cannot be completely excluded.
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4. Materials and Methods
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4.1. Animals
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The mice were housed under a 12 h light/12 h dark cycle at a constant temperature (23 ± 2 °C) with free access to food and water. The animals were fed ad libitum with standard mouse chow (18% protein, 4.5% fat, and 58% carbohydrate, purchased from Guangdong Medical Science Experiment Center, Guangzhou, Guangdong, China) for the first 8 weeks and high-fat chow (60 kcal% Fat from Research Diets, Cat No. D12492) from 8 to 20 weeks. All animal experiments used female mice aged 20 weeks at the time when they were sacrificed. The miR-146a-5p flox/flox (miR-146aflox+/+) and Myf5-Cre mice using CRISPR/Cas9/Cre method were generated (Cyagen, Suzhou, China) and maintained on a C57BL/6 background. They were used to study the metabolic effects of long-term HFD supplementation. To generate skeletal muscle-specific miR-146a-5p knockout (mKO) mice, miR-146aflox+/+ mice were first crossed with Myf5-Cre mice to obtain F1(miR-146aflox+/−,Cre+/−). Then the F1 mice mated with miR-146aflox+/+ mice to produce the mKO mice (miR-146aflox+/+,Cre+/−). The primer sequence of mouse genotype identification is shown in Table S1. The care of all animals and procedures at South China Agricultural University complies with “The Instructive Notions with Respect to Caring for Laboratory Animals” issued by the Ministry of Science and Technology of the People’s Republic of China and approved by the Animal Subjects Committee of South China Agricultural University.
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4.2. NMR Analysis of the Whole-Body Composition
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Body composition of mice was determined using quantitative magnetic resonance (QMR, Niumag Corporation, Shanghai, China).
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4.3. IPITT and IPGTT
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Before the intraperitoneal glucose tolerance test (IPGTT), mice fasted for 12 h. By using a blood glucose meter, blood glucose levels were measured at 0, 15, 30, 60, and 120 min after glucose (1 g∙kg−1) was injected intraperitoneally. In the intraperitoneal insulin tolerance test (IPITT), mice fasted for 6 h prior to the experiment. Insulin (0.7 U∙kg−1) was injected, and blood glucose levels were measured at 0, 15, 30, 60, and 120 min after injection.
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4.4. In Vivo Oxygen Consumption Assay
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Utilizing the promotion metabolism measurement system (Sable Systems International, North Las Vegas, NV, USA), we analyzed O2 consumption (VO2) and CO2 production (VCO2) in HFD.
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4.5. Imaging Experiments
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The tissue distribution of PKH67 (Sigma-Aldrich) labeled exosomes were visualized using fluorescence parameters as detected by the IVIS Lumina LT SeriesIII®® imaging system after injection of PKH67-labeled exosomes into the tail vein. We isolated all tissue samples within a 1-h post-mortem, rinsed them in cold PBS to remove blood, and observed them. Exosomes labeled with PKH67 (Sigma-Aldrich, St. Louis, MI, USA) were measured at 490 nm and 520 nm.
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4.6. HE Staining
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Briefly, an aliquot of IngWAT (inguinal white adipose tissue) and EpiWAT (epididymal white adipose tissue) was fixed with 10% formalin and embedded with paraffin. Then, fixed IngWAT and EpiWAT were sectioned and stained with hematoxylin-eosin (HE).
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4.7. Cell Lines, Culture Conditions, Transfection
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The 3T3-L1 cells were grown in high-glucose Dulbecco’s Modified Eagle Medium (DMEM, Gibco) with 10% fetal bovine serum (FBS, Gibco) and 1% penicillin-streptomycin (P/S, Gibco) in a 5% CO2 atmosphere at 37 °C. The differentiation was induced by incubating confluent cells (in 12-well plates) for 2 days in differentiation media, which was comprised of DMEM supplemented with 10% FBS, 0.5 mM 3-isobutyl-1-methylxanthine (IBMX), 1 μM dexamethasone, and 10 μg/mL of insulin. Then the cells were cultured with 10 μg/mL insulin in 10% FBS medium by changing the medium every 2 days until a mature lipid droplet appeared. For miR-146a-5p mimics or miR-146a-5p inhibitor (40 nM) (GenePharma, Shanghai, China) or si-GDF5 (50 nM) (Tsingke, Beijing, China) or exosome (10 μg/mL) transfection, 3T3-L1 cells were plated in 12-well dishes at a density of 1.0 × 105 per well and lipofectamine 2000 (Thermo Fisher, Waltham, MA, USA) transfection started at the cell density reached 60 to 70%. The sequence of siRNA transfected by 3T3L-1 cells is shown in Table S2.
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4.8. Cell Co-Culture
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Transwell chambers (BIOFIL, TCS016012) were used to construct the co-culture systems. At the beginning of the test, the upper layer of the cell chamber was inoculated with 3T3-L1 cells (2.0 × 104 cells per well), and the lower layer with C2C12 cells (8.0 × 104 cells per well). They were cultured separately, co-cultured, and contacted for 48 h to detect indicators.
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| 146 |
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4.9. Collection of C2C12 Cell Culture Medium Supernatant
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The C2C12 cells were seeded in 75 cm2 cell culture flasks (1.0 × 106 cells/flasks) (Corning, Corning, NY, USA) exosome-free 10% FBS DMEM and grown for 48 h. Then, the cellular supernatant was collected. The C2C12 cells were plated in 12-well plates (Corning, 3513), seeded with 8.0 × 104 cells per well in DMEM supplemented with 10% FBS and 1% P/S. By adding 2% horse serum (HS, Gibco) after reaching 80% confluency, C2C12 cells became myotubes for 4 days. The supernatant was collected by contacting the cells with 2% exosome-free HS DMEM for 48 h.
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4.10. Collection of Skeletal Muscle Tissue Culture Medium Supernatant
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In order to obtain the mice skeletal muscle tissue-derived exosomes, the mice’s were first identified by genotype. After identification, Flox mice and mKO mice were sacrificed by cervical dislocation and immersed in a beaker of 75% alcohol and isolated in a sterile environment. The skeletal muscle tissue of mice was removed, washed with PBS (containing 1% P/S), and placed in a medium containing exosome-free 10% FBS DMEM. Then, the skeletal muscle tissue was carefully cut into 1 mm3 pieces with fine scissors for 10 min and washed with PBS 3 times. Then, they were placed in a petri dish and kept in an incubator of a 5% CO2 atmosphere at 37 °C for 24 h to collect the medium supernatant. The exosomes were named Flox-Exos and mKO-Exos, respectively.
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4.11. Exosome Isolation
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Isolation of exosomes in culture supernatant by ultracentrifugation. The specific steps were as follows. After centrifuging the culture supernatant at 2000× g for 10 min and 12,000× g for 30 min, large debris and dead cells were removed. An ultracentrifuge of 100,000× g for 70 min was performed on the supernatant. Finally, the cells were rinsed in 38 mL PBS and ultracentrifuged for 70 min at 100,000× g. We resuspended the pellets in 100 μL of PBS and stored them at −80 °C.
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4.12. Transmission Electron Microscopy Analysis
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Exosomes of 10 μL were placed on copper grids coated with formvar, incubated for 5 min, and excess liquid was discarded. Uranyl acetate was added to the grid for negative stain for 1 min, and excess liquid was discarded. At 100 kV, samples were examined using transmission electron microscopy.
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4.13. Dual-Luciferase Reporter Experiments
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We seeded HEK293T cells in 96-well plates (Corning) at 2.5 × 104 cells per well and grew them overnight to 70–80% confluence. The dual-luciferase reporter plasmids were co-transfected with miRNA into HEK293T cells and the dosage of miR-146a-5p NC/mimic and wild-type/mutation/deletion dual-luciferase gene reporter vector per well was 3 pmol and 100 ng, respectively. The Dual-Luciferase Reporter Assay System (Promega) was used to detect luciferase activity after 48 h.
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4.14. Nanoparticle Tracking Analysis
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The exosomes were diluted to appropriate concentrations with PBS. The size of exosomes derived from cells or skeletal muscle tissue was measured by nanoparticle tracking analysis (NTA). Refer to the manual for the specific use of the instrument, including sample loading, photo-taking, and result statistics in brief.
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4.15. Co-IP Experiment
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The specific steps are shown in the instructions. In short, Pierce™ Protein A/G Magnetic Beads (88803, Thermo Scientific, Waltham, MA, USA) were used to bind GDF5 antibody and added to the lysed samples. The magnetic beads were pulled down with a magnet, and the resulting precipitate was detected using a western blot to confirm whether the target protein exists, and the sample lysate was directly used as the Input group control to detect the target protein.
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4.16. Oil Red O Staining
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After being treated and induced to mature, 3T3-L1 cells (24-well plates, Corning) were washed 3 times with PBS buffer, fixed in 4% formaldehyde for 30 min at room temperature, washed 3 times with PBS for 5 min each, and then stained with oil red O (Sigma-Aldrich, Shanghai, China) for 1 h. To create a working solution, oil red O was first diluted with water (3:2) and filtered through filter paper. After staining the cells, the plates were washed 3 times in PBS for 5 min each and then photographed under a microscope (TE2000-E; Nikon, Japan).
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4.17. Triglyceride Accumulation
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Triglyceride (TG) content was determined using a colorimetric/fluorometric assay kit (Biovision, Milpitas, CA, USA). 3T3-L1 cells were seeded into a 96-well plate and differentiated with CTE (500–1000 µg/mL) until they became mature adipocytes. A lipid droplet was then extracted by extraction buffer and converted by lipase to glycerol and fatty acid. A wavelength of 570 nm was used to measure the released glycerol.
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4.18. Fatty Acid and Glucose Uptake Assay
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Fatty acid and glucose uptake assays were carried out using Bodipy-FA (Invitrogen Cat No. D3835) and 2-NBDG (Sigma Cat No. 186689-07-6), which are fluorescent tracers.
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4.19. Quantitative Real-Time PCR
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We extracted the total RNA using TRIzol (Thermo Fisher). 1 µg of RNA was converted into complementary deoxyribonucleic acid (cDNA) using Color Reverse Transcription Kit (EZBioscience, Roseville, MN, USA, Cat No. A0010CGQ). We performed quantitative real-time PCR (qPCR) using a QuantStudio Real-Time PCR System (Bio-Rad C1000 Touch) using 2 × RealStar Fast SYBR qPCR Mix (GenStar, Cat No. A301). The mRNA and miRNA internal references were GAPDH and U6. Quantitative real-time PCR primer sequence is shown in Table S3, and reverse transcription primer sequences are shown in Table S4.
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4.20. Protein Extraction and Western Blot Analysis
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Radioimmunoprecipitation assay (RIPA) buffer containing protease and phosphatase inhibitors (BestBio Cat No. BB-3101) was used to extract proteins. The protein concentration was assessed using the Rapid Gold BCA Protein Assay Kit (Thermo Fisher). Western blotting analysis was performed by loading 15 µg of lysate onto sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gels, transferring the gels to polyvinylidene difluoride (PVDF) membranes (Millipore), and incubated with rabbit anti-GDF5 (1:1000, #A13167; ABclonal), rabbit anti-PPARγ (1:1000, #2443; CST), rabbit anti-FASN (1:1000, #D262701; Sangon Biotech), rabbit anti-C/EBPα (1:1000, #2295; CST), rabbit anti-FABP4 (1:1000, #2120; CST), rabbit anti-CD36 (1:1000, #ab1336-25; Abcam), rabbit anti-GAPDH (1:5000, #BS65529; Bioworld), rabbit anti-CD9 (1:1000, #AP68-965-100; Abcepta), rabbit anti-CD63 (1:2000, #D160973; Sangon Biotech), rabbit anti-TSG101 (1:2000, #381538; ZEN BIO), rabbit anti-Alix (1:1000, #D262028; Sangon Biotech) or rabbit anti-Calnexin (1:1000, #D262986; Sangon Biotech). Afterward, goat anti-rabbit secondary antibody (1:50000, # BS13278, Bioworld) conjugated with HRP was used. GAPDH levels served as the loading control. The amount of protein was measured using ImageJ software.
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4.21. Statistical Analysis
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SPSS 25 and Graphpad prism 9.0 were used for one-way ANOVA and stand-alone sample t-test analysis and plotting. The results were presented as mean ± standard error of the mean (SEM). The significance of the difference was judged by a level of * p < 0.05 or ** p < 0.01. The letters a, b, and c represent the level of statistical significance of the difference between the groups. Different letters mean a significant difference, and the same letters mean the difference is not significant.
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5. Conclusions
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In conclusion, our results suggest that high levels of miR-146a-5p in mice are inversely correlated with adipogenesis. Skeletal muscle secreted large quantities of exosomes containing abundant proteins, mRNA, and miRNAs. Additionally, there were notably high levels of miR-146a-5p. Under the uptake of adipocytes to skeletal muscle-derived exosomes, the skeletal muscle exosomal miR-146a-5p inhibits the synthesis of lipid droplets and adipocyte differentiation by down-regulating the expression of GDF5 in adipocytes and repressing the PPARγ signaling pathway. In addition, miR-146a-5p blocked fatty acid uptake by decreasing CD36 expression. miR-146a-5p-specific knockout in skeletal muscle can improve the body weight, fat ratio, and glucose tolerance, and reduce the body’s oxidative respiratory metabolism in mice. Our study provides new insights into the role of miR-146a-5p as a novel myokine in the cross-talk between skeletal muscle and fat tissue and contributes to the prevention and improvement of obesity by maintaining an appropriate ratio of skeletal muscle to fat.
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Supplementary Materials
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The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms24054561/s1.
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Click here for additional data file.
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Author Contributions
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Data curation, M.Q.; formal analysis, M.Q.; funding acquisition, T.C.,Y.Z., J.S. and Q.X.; investigation, M.Q., L.X., J.W., S.W. (Shulei Wen), J.L. (Junyi Luo), T.C., Y.F., J.Z., L.Y., J.L. (Jie Liu), J.X., X.C., C.Z., S.W. (Songbo Wang), L.W., G.S., Q.J., Y.Z., J.S. and Q.X.; methodology, M.Q.; project administration Q.J., Y.Z., J.S. and Q.X.; software, M.Q.; supervision, Q.X.; validation, L.X.; visualization, M.Q.; writing—original draft, M.Q.; writing—review & editing, M.Q., L.X., J.L. (Junyi Luo), J.S. and Q.X. All authors have read and agreed to the published version of the manuscript.
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Institutional Review Board Statement
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All of the experimental protocols and methods were approved by the College of Animal Science, South China Agricultural University (Ethical code number: SCAU-AEC-2015–0527). All of the experiments were conducted following the “The Instructive Notions with Respect to Caring for Laboratory Animals” issued by the Ministry of Science and Technology of the People’s Republic of China.
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Informed Consent Statement
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Not applicable.
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Data Availability Statement
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Not applicable.
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Conflicts of Interest
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The authors declare no conflict of interest.
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Abbreviations
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CD36: Cluster of differentiation 36 receptor; C/EBPα: CCAAT/enhancer binding protein alpha; EpiWAT: Epididymal white adipose tissue; Exos: Exosomes; FABP4: Fatty acid binding proteins4; Flox-Exos: Skeletal muscle-derived exosomes from the Flox mice; GDF5: Growth and differentiation factor 5; HE: Hematoxylin-eosin; IngWAT: Inguinal white adipose tissue; IPGTT: Intraperitoneal glucose tolerance test; IPITT: Intraperitoneal insulin tolerance test; miRNAs: microRNAs; mKO: skeletal muscle-specific knockout miR-146a-5p; NTA: Nanoparticle tracking analysis; PPARγ: Peroxisome proliferator-activated receptor γ; SKM: Skeletal muscle; SKM-Exos: Skeletal muscle-derived exosomes; TG: triglyceride.
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Figure 1 Effects of skeletal muscle-derived exosomes on adipogenesis in 3T3-L1 cells. (a) C2C12 cells were co-cultured with 3T3-L1 cells, and the cells were grown in a transwell. (b) The morphology of C2C12 cells before and after differentiation was observed under a microscope (scale bar = 100 μm). (c) During co-culture, differentiated 3T3-L1 adipogenic precursor cells were induced to mature, and oil red O staining was performed. (d) During co-culture, the differentiation of 3T3-L1 adipocyte precursor cells was induced to mature to examine TG content (n = 6). (e) Electron microscopy photographs of C2C12 cells-derived exosomes proliferation (Pro-Exos) and differentiation (Diff-Exos) (scale bar = 200 nm). (f) Nanoparticle tracking analysis (NTA) was used to determine the size distribution and concentration of exosomes. (g) Marker proteins Alix, TSG101, CD9, and CD63 in exosomes extracted from C2C12 cells, and the Western Blot detection bands of endoplasmic reticulum marker protein Calnexin. (h) The expression of miR-146a-5p in C2C12 cells proliferation and differentiation (n = 6), and the expression of miR-146a-5p in C2C12 cells-derived exosomes of the proliferation and differentiation (n = 4). (i–l) After treatment with skeletal muscle-derived exosomes (Pro-Exos, Diff-Exos), adipogenesis-related genes PPARγ and C/EBPα, and fatty acid synthesis-related genes CD36 and FABP4, were detected by real-time quantitative PCR after induced differentiation in 3T3-L1 preadipocytes (n = 6). Values are presented as means ± SEM, * p < 0.05, and ** p < 0.01, according to the non-paired Student’s t-test or one-way ANOVA between individual groups. Different letters mean significant difference (p < 0.05), and the same letters mean no significant difference (p > 0.05).
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Figure 2 miR-146a-5p reversed the effect of skeletal muscle-derived exosomes on adipogenesis, glucose uptake, and fatty acid absorption in 3T3-L1 cells. (a) After treatment of exosomes (Pro-Exos, Diff-Exos) and transfections of miR-146a-5p mimics and miR-146a-5p inhibitor, 3T3-L1 adipogenic precursor cells were induced to mature, and oil red O staining was performed (scale bar = 50 μm). (b) After treatment with exosomes (Pro-Exos, Diff-Exos) and transfecting miR-146a-5p mimics (mimics) and miR-146a-5p inhibitor (inhibitor), 3T3-L1 adipocytes were induced to mature, and TG content was assayed (n = 6). (c,d) After treatment of exosomes (Pro-Exos, Diff-Exos) and transfections of mimics and inhibitor, adipogenesis-related proteins and fatty acid synthesis-related protein bands were detected by Western Blot in mature 3T3-L1 cells (n = 4). (e) 2-NBDG fluorescence profile of 3T3-L1 cells after treatment of exosomes (Pro-Exos, Diff-Exos) and transfections of mimics and inhibitor for 24 h (scale bar = 50 μm). (f) 2-NBDG fluorescence values of 3T3-L1 cell after treatment of exosomes (Pro-Exos, Diff-Exos) and transfections of mimics and inhibitor for 24h (n = 6). (g) Bodipy-FA fluorescence image of 3T3-L1 cells after treatment with exosomes (Pro-Exos, Diff-Exos) and transfections of mimics and inhibitor for 24 h (scale bar = 50 μm). (h) Bodipy-FA for 4 h, 3T3-L1 cell fluorescence values after treatment of exosomes (Pro-Exos, Diff-Exos) and transfections of mimics and inhibitor for 24 h (n = 6). Values are presented as means ± SEM, according to the non-paired Student’s t-test or one-way ANOVA between individual groups. Different letters mean significant difference (p < 0.05), and the same letters mean no significant difference (p > 0.05).
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Figure 3 miR-146a-5p was associated with adipogenesis and glucose uptake and fatty acid absorption. (a) miR-146a-5p gene expressions in 3T3-L1 adipose mature cells after transfections of miR-146a-5p mimics (Mimics) and miR-146a-5p inhibitor (Inhibitor) (n = 6). (b) TG content in 3T3-L1 adipose mature cells after transfections of mimics and inhibitor (n = 6). (c) Oil red O staining photographs in 3T3-L1 adipose mature cells after transfections of mimics and inhibitor (scale bar = 50 μm). (d) Fluorescence image of 3T3-L1 cells treated with glucose analog 2-NBDG for 1 h after transfections of mimics and inhibitor for 24 h (bar = 50 μm). (e) Statistical graph of fluorescence value of 3T3-L1 cells treated with glucose analog 2-NBDG (n = 4). (f) Fluorescence image of 3T3-L1 cells treated with free fatty acid analog Bodipy-FA for 4 h after transfections of mimics and inhibitor for 24 h (bar = 50 μm). (g) Statistical graph of fluorescence value of 3T3-L1 cells treated with free fatty acid analog Bodipy-FA (n = 4). (h) After transfection of mimics and inhibitor adipogenesis-related genes PPARγ, C/EBPα, and fatty acid synthesis-related genes CD36, FABP4, and FASN were detected by real-time quantitative PCR in mature 3T3-L1 (n = 6). (i,j) After transfection of mimics and inhibitor, adipogenesis-related proteins PPARγ, C/EBPα, and fatty acid synthesis-related proteins CD36, FABP4, and FASN were detected by Western Blot (n = 6). Values are presented as means ± SEM, * p < 0.05, and ** p < 0.01, according to the non-paired Student’s t-test or one-way ANOVA between individual groups.
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Figure 4 miR-146a-5p regulated PPARγ signaling pathway by targeting GDF5. (a) miR-146a-5p has a target interaction with the 3′UTR of GDF5. (b) Statistical chart of miR-146a-5p and GDF5 dual luciferase validation fluorescence values (n = 8). (c,d) After transfections of miR-146a-5p mimics (Mimics) and miR-146a-5p inhibitor (Inhibitor), GDF5 was detected by Western Blot in mature 3T3-L1 cells (n = 6). (e) After transfections of mimics and inhibitor, GDF5 gene expression was detected by real-time quantitative PCR (n = 6). (f,g) 3T3-L1 cells were transfected with GDF5 siRNA for 48 h, and GDF5 was detected by Western Blot (n = 6). (h) After transfection (NC, GDF5 siRNA, miR-146a-5p inhibitor + GDF5 siRNA), GDF5, PPARγ C/EBPα, CD36, FABP4 and FASN expressions were detected by real-time quantitative PCR (n = 6). (i,j) After transfection (NC, GDF5 siRNA, miR-146a-5p inhibitor + GDF5 siRNA), proteins GDF5, PPARγ C/EBPα, CD36, FABP4 and FASN were detected by Western Blot (n = 6). (k) After transfection (NC, GDF5 siRNA, miR-146a-5p inhibitor + GDF5 siRNA), TG content was assayed (n = 6). (l) After transfection (NC, GDF5 siRNA, miR-146a-5p inhibitor + GDF5 siRNA), oil red O staining was performed (scale bar = 50 μm). (k) Oil Red O readings (n = 6). (m) Immunoprecipitation assay revealed enrichment of PPARγ C/EBPα, CD36, FABP4, and FASN when introduced with GDF5. Values are presented as means ± SEM, * p < 0.05, and ** p < 0.01, according to the non-paired Student’s t-test or one-way ANOVA between individual groups.
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Figure 5 Regulations of growth and metabolism in transgenic mice. (a) Mice breeding atlas. (b) Sequence alignment of skeletal muscle-specific miR-146a-5p knockout (mKO) and Flox. (c) The expression of miR-146a-5p in GAS and TA of mKO mice was detected by quantitative PCR (n = 4). (d) Body weight change curve of Flox and mKO mice fed a high-fat diet (n = 4). (e) The muscle weight for GAS and TA of Flox and mKO mice fed a high-fat diet (n = 4). (f) Accumulate feed intake of Flox and mKO fed HFD (n = 4). (g) IPITT blood glucose changes in Flox and mKO mice (n = 4). (h) IPGTT blood glucose changes in Flox and mKO mice (n = 4). (i,j) Oxygen consumption (n = 4). (k,l) CO2 release (n = 4). Values are presented as means ± SEM, * p < 0.05, and ** p < 0.01, according to the non-paired Student’s t-test or one-way ANOVA between individual groups.
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Figure 6 Effects of skeletal muscle-specific miR-146a-5p knockout on adipogenesis in mice. (a) Body composition of Flox and mKO mice. (b) Body imaging of Flox and mKO mice. (c) Tissue weight (IngWAT and EpiWAT) of Flox and mKO mice after feeding with a high-fat diet (HFD) (n = 4). (d) HE staining image of IngWAT and EpiWAT in Flox and mKO mice fed with HFD (scale bar = 50 μm). (e) Fluorescence quantitative PCR detection of adipogenesis-related genes GDF5, PPARγ, C/EBPα, and fatty acid synthesis-related genes CD36, FABP4, FASN in IngWAT of Flox and mKO mice (n = 4). (f,g) Western Blot detection of adipogenesis-related proteins GDF5, PPARγ, C/EBPα, and fatty acid synthesis-related proteins CD36, FABP4, and FASN in IngWAT of Flox and mKO mice (n = 4). (h) Fluorescence quantitative PCR detection of adipogenesis-related genes GDF5, PPARγ, C/EBPα, and fatty acid synthesis-related genes CD36, FABP4, FASN in EpiWAT of Flox and mKO mice (n = 4). (i,j) Western Blot detection of adipogenesis-related proteins GDF5, PPARγ, C/EBPα, and fatty acid synthesis-related proteins CD36, FABP4, FASN in EpiWAT of Flox and mKO mice (n = 4). Values are presented as means ± SEM, * p < 0.05, and ** p < 0.01, according to the non-paired Student’s t-test or one-way ANOVA between individual groups.
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Figure 7 The intravenous injection of Flox-Exos into mKO mice reversed the inhibition of adipogenesis. (a) Expressions of miR-146a-5p were determined in skeletal muscle-derived exosomes from mKO and Flox mice (n = 6). (b) The fluorescence signal of skeletal muscle-derived exosomes in isolated mKO mice organs 24 h after tail vein injection. The isolated organs from left to right are as follows: heart, liver, spleen, lung, kidney, BAT, IngWAT, EpiWAT, whole intestine, TA, EDL, GAS, SOL. (c) In vivo imaging of mKO mice 24h after tail vein injection of PKH67-labeled skeletal muscle-derived exosomes. (d) Schematic diagram of tail-vein injections of Flox-Exos and mKO-Exos administered to HFD-fed mKO mice at the age of 6 weeks. (e) Body weight gain in mKO mice (n = 3). (f) Body weight of mKO mice (n = 3). (g) Accumulate feed intake of mKO mice fed HFD (n = 3). (h) Tissue weight (IngWAT and EpiWAT) of mKO mice (n = 3). (i) Body Composition of mKO mice (n = 3). (j) Body imaging of mKO mice. (k) IngWAT HE staining image of mKO mice. (l) Expression of adipogenesis and fatty acid synthesis-related genes 21 days after exosome injection in IngWAT (n = 3). (m,n) Expression of adipogenesis and fatty acid synthesis-related proteins in IngWAT (n = 3). (o) EpiWAT HE staining image of mKO mice. (p) Expression of adipogenesis and fatty acid synthesis-related genes 21 days after exosome injection in EpiWAT (n = 3). (q,r) Expression of adipogenesis and fatty acid synthesis-related proteins in EpiWAT (n = 3). Values are presented as means ± SEM, * p < 0.05, and ** p < 0.01, according to the non-paired Student’s t-test or one-way ANOVA between individual groups.
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==== Refs
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|
| 297 |
+
|
puc/PMC10005707.txt
ADDED
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Nutrients
|
| 4 |
+
Nutrients
|
| 5 |
+
nutrients
|
| 6 |
+
Nutrients
|
| 7 |
+
2072-6643
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
10.3390/nu15051252
|
| 11 |
+
nutrients-15-01252
|
| 12 |
+
Article
|
| 13 |
+
Macauba (Acrocomia aculeata) Pulp Oil Prevents Adipogenesis, Inflammation and Oxidative Stress in Mice Fed a High-Fat Diet
|
| 14 |
+
Sant’ Ana Cíntia Tomaz 1
|
| 15 |
+
Agrizzi Verediano Thaísa 2
|
| 16 |
+
Grancieri Mariana Methodology Formal analysis 2
|
| 17 |
+
Toledo Renata Celi Lopes Methodology Formal analysis 2
|
| 18 |
+
Tako Elad Writing – review & editing 3*
|
| 19 |
+
Costa Neuza Maria Brunoro Writing – review & editing Supervision 4
|
| 20 |
+
Martino Hércia Stampini Duarte Conceptualization Writing – review & editing Supervision Project administration 2
|
| 21 |
+
https://orcid.org/0000-0001-7300-8773
|
| 22 |
+
de Barros Frederico Augusto Ribeiro 1
|
| 23 |
+
Sureda Antoni Academic Editor
|
| 24 |
+
1 Department of Food Technology, Federal University of Viçosa, Viçosa 36570-900, MG, Brazil
|
| 25 |
+
2 Department of Nutrition and Health, Federal University of Viçosa, Viçosa 36570-900, MG, Brazil
|
| 26 |
+
3 Department of Food Science, Cornell University, Stocking Hall, Ithaca, NY 14850, USA
|
| 27 |
+
4 Department of Pharmacy and Nutrition, Federal University of Espírito Santo, Alegre 29500-000, ES, Brazil
|
| 28 |
+
* Correspondence: et79@cornell.edu
|
| 29 |
+
02 3 2023
|
| 30 |
+
3 2023
|
| 31 |
+
15 5 125203 2 2023
|
| 32 |
+
23 2 2023
|
| 33 |
+
28 2 2023
|
| 34 |
+
© 2023 by the authors.
|
| 35 |
+
2023
|
| 36 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 37 |
+
Macauba is a palm tree native to Brazil, which fruits are rich in oil. Macauba pulp oil has high contents of oleic acid, carotenoids, and tocopherol, but its effect on health is unknown. We hypothesized that macauba pulp oil would prevent adipogenesis and inflammation in mice. Thus, the purpose of this study was to evaluate the effects of macauba pulp oil on the metabolic changes in C57Bl/6 mice fed a high-fat diet. Three experimental groups were used (n = 10): control diet (CD), high-fat diet (HFD), and high-fat diet with macauba pulp oil (HFM). The HFM reduced malondialdehyde and increased SOD activity and antioxidant capacity (TAC), showing high positive correlations between total tocopherol, oleic acid, and carotenoid intakes and SOD activity (r = 0.9642, r = 0.8770, and r = 0.8585, respectively). The animals fed the HFM had lower levels of PPAR-γ and NF-κB, which were negatively correlated with oleic acid intake (r = −0.7809 and r = −0.7831, respectively). Moreover, the consumption of macauba pulp oil reduced inflammatory infiltrate, adipocyte number and length, (mRNA) TNF-α, and (mRNA) SREBP-1c in the adipose tissue, and it increased (mRNA) Adiponectin. Therefore, macauba pulp oil prevents oxidative stress, inflammation, and adipogenesis and increases antioxidant capacity; these results highlight its potential against metabolic changes induced by an HFD.
|
| 38 |
+
|
| 39 |
+
bioactive compounds
|
| 40 |
+
metabolic changes
|
| 41 |
+
oleic acid
|
| 42 |
+
carotenoid
|
| 43 |
+
tocopherol
|
| 44 |
+
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, Brazil)23/2028-DAI/CNPq This work was supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, Brazil). Cíntia Tomaz Sant’ Ana was a recipient of a scholarship from CNPq (call # 23/2028-DAI/CNPq).
|
| 45 |
+
==== Body
|
| 46 |
+
pmc1. Introduction
|
| 47 |
+
|
| 48 |
+
Current eating habits characterized by elevated consumption of saturated fats and simple carbohydrates and low vitamins are one of the most important causes for the emergence of chronic non-communicable diseases, such as obesity and nonalcoholic fatty liver disease [1,2]. Obesity is characterized by adipogenesis, which favors the induction of metabolic changes, including changes in cytokine concentrations, activation of inflammatory pathways, and lipotoxic effects in tissues such as the liver. As a consequence of these changes, reactive oxygen species (ROS) production may increase and may, thus, result in an exacerbation of inflammation, oxidative stress, and cell alterations [3].
|
| 49 |
+
|
| 50 |
+
Regulation and control of adipogenesis and metabolic changes are performed by specific transcriptional regulators, such as peroxisome proliferator-activated receptor gamma (PPAR-γ), sterol regulatory element-binding protein 1 (SREBP-1), and nuclear factor kappa B (NF-κB) [4]. SREBP-1 controls fatty acid biosynthesis by favoring the transcription of specific enzymes and activating PPAR-γ, which controls the expression of genes that regulate adipocyte differentiation. NF-κB controls the expression of inflammatory genes. In obesity, there is an increase in these transcription factors, resulting in increased lipogenesis, which leads to an increase in triacylglycerol and a reduction in lipolysis, thereby favoring the development of inflammation and oxidative stress [3,4]. As such, research studies that demonstrate new dietary strategies with the purpose of preventing or controlling obesity and metabolic alterations become very important, and dietary fatty acid composition demonstrates a significant impact on disease development [5]. Thus, nutritional strategies that aim to treat or prevent these metabolic alterations are of great importance.
|
| 51 |
+
|
| 52 |
+
Macauba (Acrocomia aculeata) is a palm tree that is naturally present in almost all Brazilian territories, and it is considered a promising alternative to vegetable oil for fuel and for the cosmetic and food industries due to its high oil production and specific characteristics [6]. Two types of oils are obtained from macauba: pulp and kernel oils. Both have important chemical and economical characteristics, highlighting their nutritional action and applications in the food industry [7]. Similar to olive oil, macauba pulp oil is rich in oleic acid [6]. Oleic acid has been shown to reduce the expression of transcription factors related to the adipogenesis signaling pathway, such as PPAR-γ, and reduce oxidative stress markers [8]. Moreover, macauba pulp oil has a high content of carotenoids, which can act to reduce inflammation through NF-κB modulation [6,9]. Additionally, this oil contains tocopherol, which is an important antioxidant that has been shown to improve inflammation and oxidative stress [10]. Thus, macauba pulp oil consumption may result in an improvement in metabolic changes, which is associated with the bioactive compounds in its composition [6].
|
| 53 |
+
|
| 54 |
+
We hypothesized that macauba pulp oil would prevent adipogenesis and inflammation in mice. However, to the best of our knowledge, no research has been performed to provide evidence of the health benefits of macauba pulp oil. Thus, the objective of this work was to evaluate the effect of macauba pulp oil on the adipogenesis pathways and metabolic changes in mice fed a high-fat diet. This study is the first to explore the health benefits of this promising vegetable oil.
|
| 55 |
+
|
| 56 |
+
2. Material and Methods
|
| 57 |
+
|
| 58 |
+
2.1. Materials
|
| 59 |
+
|
| 60 |
+
Macauba fruits were harvested in Araponga, Minas Gerais (Brazil), in the mature stage, and then they were peeled and pulped to obtain the macauba pulp. The pulp was dried at 65 °C (CIENLAB CE220, Brazil) for 15 h. Oil was extracted using a manual hydraulic press (Laboratory Press, Fred S. Carver Inc., Summit, NJ, USA), centrifuged (5000 rpm/20 min), and then placed in a freezer (−80 °C).
|
| 61 |
+
|
| 62 |
+
2.2. Chemical Characterization of Macauba Pulp Oil
|
| 63 |
+
|
| 64 |
+
The fatty acid profile of the macauba pulp oil was determined using a gas chromatography equipped with a flame ionization detector (GC-FID) (Shimadzu, GC-2010, Kyoto, Japan) and a capillary column of 100 m × 0.25 mm (SP-2560, Sigma-Aldrich, San Luis, MO, USA) [11]. Helium gas was used as the dragging gas and maintained at a constant flow rate of 363 kPa. Fatty acid methyl esters (FAMEs) were separated using a linear heating ramp from 100 °C to 270 °C, at a heating rate of 20 °C mim−1 and with a high linear velocity for better peak resolution. Peak identification was confirmed by comparison with the standard FAME mix (Supelco 37 FAME mix, Sigma-Aldrich, San Luis, MO, USA). Moreover, the oleic acid content (mg/g) of the oil was also determined using a standard (Sigma-Aldrich).
|
| 65 |
+
|
| 66 |
+
Carotenoid analysis was carried out by a high-performance liquid chromatography (HPLC) with detection at 450 nm, using the following chromatographic conditions: a HPLC system (Shimadzu, SCL 10AT VP, Kyoto, Japan) and a chromatographic column Phenomenex Gemini RP-18 (250 mm × 4.6 mm, 5 mm) fitted with a guard column RP-18 Phenomenex ODS column (4 mm × 3 mm). The mobile phase consisted of methanol:ethylacetate:acetonitrile (70:20:10, v/v/v) with a flow rate of 2.0 mL·min−1 and a run time of 15 min. Total carotenoid content (μg/g) was expressed as the sum of the major carotenoids present in the macauba pulp oil [12].
|
| 67 |
+
|
| 68 |
+
Total tocopherol content was determined following the AOCS method, using a HPLC with fluorescence detection at 450 nm and the following chromatographic conditions: a silica column of 4.6 × 250 mm with a pore of 5 μm, a flow rate of 1.0 mL min−1, and as the mobile phase, a mixture of 99.5% of n-hexane and 0.5% of isopropanol. The concentration of total tocopherols (μg/g) was expressed as the sum of the major tocopherols present in the macauba pulp oil [13].
|
| 69 |
+
|
| 70 |
+
2.3. Animals and Experimental Design
|
| 71 |
+
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+
Black male mice C57Bl/6 (30 animals), which were 8 weeks old and had an average weight of 24.34 ± 0.18 g, were allocated into 3 groups, with 10 animals in each group, based on the homogeneity of body weight. The sample calculation equation determined how many animals should be in each group, using the following variables: α-error type I = 1.96, α-level = 5%, and data of fat mass mean reported by Schoemaker et al. in 2017 [14,15]. Individual stainless steel cages were used to keep the animals in a temperature-controlled room (light–dark cycles of 12 h and temperature of 22 ± 2 °C). Water and the respective experimental diets were supplied ad libitum.
|
| 73 |
+
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| 74 |
+
The experimental diets were formulated according to AIN-93M and high-fat diet, using lard in the high-fat diet [16]. Each experimental group consumed the following diet: control diet—AIN93M (CD); high-fat diet (HFD); high-fat diet with macauba pulp oil (HFM). In the HFM, macauba pulp oil was added in a proportion of 40 g/kg (4%), replacing the soybean oil used in the AIN-93M diet (Table 1). The objective was to verify the effect of macauba pulp oil as a replacement of soybean oil, which is commonly used in control diets, and not as a supplementation. The formulated diets were stored at a low temperature (−20 °C) and offered to the animals every day.
|
| 75 |
+
|
| 76 |
+
At the end of the 8 weeks, the animals were anesthetized after 12 h of fasting using isoflurane (Isoforine, Cristália), in accordance with the bodyweight of the mice. Using the methodology of cardiac puncture, blood was collected and centrifuged (4 °C at 800× g for 10 min using Fanem-204, São Paulo, Brazil), and the serum was collected and stored at −80 °C. The liver and adipose (epididymal and subcutaneous) tissues were extracted and stored at (−80 °C) until analysis, and another part was fixed in formaldehyde (10%) for the analysis of histological markers. Bodyweight gain and feed consumption were measured on a weekly basis throughout the experiment to calculate the feed efficiency ratio (weight gain/consumption × 100), and the percentage of adiposity was measured based on the weight of the adipose tissue (g) in relation to the total body weight. Body mass index (BMI) was measured using the ratio between weight and naso-anal length (cm) squared [17]. The hepatosomatic index was also determined (liver weight/body weight × 100) [18]. Carotenoid, oleic acid, and tocopherol intakes were determined by the total amount of diet consumed by the mice. Ethical principles for animal experimentation were implemented for all processes performed on the animals [19]. The Ethics Committee of the Federal University of Viçosa approved this research (Protocol 09/2019; date of approval: 28 May 2019).
|
| 77 |
+
|
| 78 |
+
2.4. Biochemical Analysis
|
| 79 |
+
|
| 80 |
+
The biochemical parameters were determined using the serum. Glucose concentration, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), triacylglycerides (TGL), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) were determined based on the colorimetric method using commercial kits (Bioclin®, Belo Horizonte, Brazil).
|
| 81 |
+
|
| 82 |
+
2.5. Homogenate Preparation and Oxidative Stress Levels
|
| 83 |
+
|
| 84 |
+
Liver homogenate was prepared with 200 mg of the liver. The liver was mixed with 1 mM of EDTA (pH 7.4) and 1000 μL of phosphate buffer (50 mM). The content was macerated and centrifuged (1200× g/8 min/4 °C), and the supernatant was collected for the analysis of antioxidant enzymes.
|
| 85 |
+
|
| 86 |
+
For the quantification of the enzyme superoxide dismutase (SOD), 249 μL of 50 mM of Tris-HCl buffer (pH 8.2) (1 mM of EDTA, 6 μL of MTT (1.25 mM), 15 μL of pyrogallol (10 mM), and 279 μL of buffer) was mixed into the aliquoted homogenate. To determine the blank, 6 μL of MTT and 294 μL of buffer were added to the wells, which were incubated for 5 min at 37 °C, and the reading was performed on a spectrophotometer at 570 nm (Thermo Scientific Multiskan GO, Waltham, MA, USA). The SOD quantification was expressed as units of SOD/mg protein [20].
|
| 87 |
+
|
| 88 |
+
Malondialdehyde (MDA) was determined using the samples of the homogenate. A total of 400 μL of trichloroacetic acid solution (15%) and thiobarbituric acid (0.375%) was added into 400 μL of the sample. It was placed in a water bath (90 °C/40 min) and 600 μL of n-Butanol was added; then, the mixture was centrifuged (3500 rpm/ 5 min). The supernatant was removed, and the absorbance was read at 535 nm (Multiskan GO—Thermo Scientific). The MDA level was expressed as MDA/mg protein [21].
|
| 89 |
+
|
| 90 |
+
Catalase was performed on the samples of the homogenate as described above. At 0, 30, and 60 s after the reaction was initiated, the absorbance was determined at 240 nm (T70 + UV/VIS Spectrometer). Enzyme activity was reported as μmol per mL of sample, and the data were expressed in U of catalase/mg protein. Catalase activity was calculated according to the Beer–Lambert law [22].
|
| 91 |
+
|
| 92 |
+
For the quantification of nitric oxide, 50 μL of the homogenate was used. Then, 1% sulfanilamide solution and 0.1% nafityl ethylene amide dihydrochloride were added. A 0.025 M sodium nitrite standard curve was used, and the absorbance was determined at 570 nm (Multiskan GO—Thermo Scientific) [23].
|
| 93 |
+
|
| 94 |
+
2.6. Total Antioxidant Capacity of Serum and Liver
|
| 95 |
+
|
| 96 |
+
The total antioxidant capacity (TAC) of the serum and the liver was determined with an antioxidant assay kit (Cayman Chem Corp, Ann Arbor, MI, USA) Sigma Aldrich®. The absorbance reading was performed at 405 nm (Multiskan GO—Thermo Scientific).
|
| 97 |
+
|
| 98 |
+
2.7. PPAR-γ, PPAR-α, NF-κB, and TLR-4 Quantification
|
| 99 |
+
|
| 100 |
+
The adipose tissue and liver samples were homogenized using the NE-PER™ Nuclear and Cytoplasmic Extraction Kit reagents (Thermo Scientific Fisher, Waltham, MA, USA). The nuclear fractions were analyzed using an immunoassay with the Mouse PPAR-γ (Peroxisome Proliferator-Activated Receptor Gamma—E-EL-M0893, Elabscience, Houston, TX, USA), Mouse NF-κB p65 (Factor Nuclear Kappa B—E-EL-M0838, Elabscience, Houston, TX, USA), Rat PPAR-α (Peroxisome Proliferator-Activated Receptor Alfa—E-EL-R0725, Elabscience, Houston, TX, USA), Rat NF-κB p65 (Factor Nuclear Kappa B—E-EL-R0674, Elabscience, USA) and Rat TLR-4 (Toll-like Receptor 4—E-EL-R0990, Elabscience, USA) ELISA kits, respectively. The microplates were, respectively, precoated with anti-PPAR-γ, anti-NF-κB p65, anti-PPAR-α, and anti-TLR-4 antibodies. The concentrations were calculated by comparison to the corresponding standard curves.
|
| 101 |
+
|
| 102 |
+
2.8. Determination of Gene Expression in Adipose Tissue and Liver by Reverse Transcriptase Quantitative Polymerase Chain Reaction (RT-qPCR)
|
| 103 |
+
|
| 104 |
+
TRIzol reagent (Invitrogen, CA, USA) was used to extract total RNA from the liver, and a specific kit (mirVana™ miRNA Isolation Kit, Life Technologies, Carlsbad, CA, USA) was used to extract RNA from the adipose tissue, according to the manufacturer’s protocols. RNA concentration and purity were evaluated using a Microdrop plate spectrophotometer Multiskan™ GO (Thermo Scientific, Waltham, MA, USA). To create cDNA synthesis, the M-MLV Reverse Transcriptase Kit (Invitrogen, CA, USA) was used. RT-qPCR was used for the gene expression relative quantification using the AB StepOne Real-Time PCR System equipment and Fast SYBR Green Master Mix (Applied Biosystems, Carlsbad, CA, USA) reagent. The initial parameters used were 20 s at 95 °C and then 40 cycles at 95 °C (3 s), 60 °C (30 s), followed by the melting curve analysis. A melting point analysis was performed to improve the specificity and sensitivity of the amplification reactions detected. All primers were designed by using the Primer 3 Plus program and obtained from Sigma-Aldrich Brazil Ltda. (Table 2). The 2-Delta-Delta C (T) method was used to calculate the gene expression, by using GAPDH and β-actin as the references and the high-fat diet group as the control, which was normalized to 1 [24].
|
| 105 |
+
|
| 106 |
+
2.9. Histomorphometric Analysis of Adipose and Liver Tissues
|
| 107 |
+
|
| 108 |
+
Paraffin was used to fix the samples of adipose tissue and liver. Ten cuts per animal were performed (3 μm thick), and the samples were mounted on glass slides and stained with hematoxylin and eosin. Analyses were performed under a light microscope (Leica DM750®). The histological sections of the images were captured in a 20× objective. Inflammatory infiltrate number and length of adipocytes were evaluated using the adipose tissue (Image-Pro Plus® 4.5). Liver cellular components (fat vesicles, inflammatory infiltrate, cytoplasm, and nucleus), for 10 histological fields per animal, were analyzed using a test system with 266 points, obtaining 2660 total points for each animal analyzed (Image J®, Wayne Rasband). The following formula was used to calculate the parameters: Vv = Pp/PT (Pp = number of points located on the structure of interest, and PT = total test points in the histological area) [25]. The steatosis degree was determined semi-quantitatively according to a 5° scale and the fat percentage: degree 0 (<5%), grade 1 (≥5% and <25%), grade 2 (≥25% and <50%), grade 3 (≥50% and <75%), grade 4 (≥75%) [26].
|
| 109 |
+
|
| 110 |
+
2.10. Statistical Analyses
|
| 111 |
+
|
| 112 |
+
Kolmogorov–Smirnov normality test was initially applied, and then an analysis of variance (ANOVA) test was performed, followed by the Newman–Keuls test for parametric variables. For the correlation analysis, Pearson’s correlation was used. The results with a p-value ≤ 0.05 were considered statistically significant. The statistical analyses were performed using the GraphPad Prism® version 8.0 (GraphPad Software, San Diego, CA, USA).
|
| 113 |
+
|
| 114 |
+
3. Results
|
| 115 |
+
|
| 116 |
+
3.1. Chemical Characterization of Macauba Pulp Oil
|
| 117 |
+
|
| 118 |
+
The macauba pulp oil shows a high content of monounsaturated fatty acids (55%), with significant oleic acid content (49.32%), as shown in Table 3. In addition, it has high contents of carotenoids and tocopherol (Table 3).
|
| 119 |
+
|
| 120 |
+
3.2. Effects of Macauba Pulp Oil on Biometric Measures, Food Intake, and Lipid Profile
|
| 121 |
+
|
| 122 |
+
Weight gain, body mass index (BMI), and food efficiency ratio (FER) did not differ among the experimental groups (p > 0.05; Table 4). The CD group had higher food consumption compared to the HFD and HFM groups, which was associated with the reduced caloric density of the AIN93M diet (p < 0.0001; Table 4). The CD group had a lower percentage of adiposity compared to the HFD and HFM groups (p = 0.0018; Table 4).
|
| 123 |
+
|
| 124 |
+
The group that consumed macauba pulp oil (HFM) did not differ from the HFD group in terms of glucose, triglyceride, TC, LDL, and HDL values, as well as hepatic enzymes AST and ALT, and hepatosomatic index (p > 0.05; Table 4).
|
| 125 |
+
|
| 126 |
+
3.3. Total Antioxidant Capacity and Oxidative Stress Marker Levels in Mice
|
| 127 |
+
|
| 128 |
+
The HFM group had a high SOD activity (p = 0.0078; Figure 1A) and showed a positive correlation with carotenoid (r = 0.8585, p = 0.004), oleic acid (r = 0.8770, p = 0.009) and tocopherol (r = 0.9642, p < 0.0001) intakes (Figure 1B–D). Macauba pulp oil decreased malondialdehyde (p = 0.0057; Figure 1E), showing a negative correlation between this parameter and oleic acid (r = −0.9401, p < 0.001) and tocopherol (r = −0.9021, p = 0.0004) (Figure 1G,H). Catalase and nitric oxide did not differ among the groups (p > 0.05; Figure 1M,N).
|
| 129 |
+
|
| 130 |
+
The HFM group had a higher serum TAC compared to the HFD and CD groups (p = 0.0058; Figure 1I), showing a positive correlation between serum TAC and oleic acid (r = 0.8967, p = 0.005) intake from macauba pulp oil (Figure 1K). Liver TAC did not differ among the experimental groups (p > 0.05; Figure 1O).
|
| 131 |
+
|
| 132 |
+
3.4. Effects of Macauba Pulp Oil on NF-κB, TLR-4, and PPAR-(α, γ) Quantification
|
| 133 |
+
|
| 134 |
+
The HFM group had a lower nuclear quantification of NF-κB in the adipose tissue compared to the HFD and CD groups (p = 0.0179; Figure 2A), showing a negative correlation with oleic acid (r = −0.7831, p = 0.037) and tocopherol (r = −0.8134, p = 0.0261) intakes (Figure 2C,D). Macauba pulp oil reduced the PPAR-γ quantification (p = 0.056; Figure 2E), showing a negative correlation with carotenoid (r = −0.7301, p = 0.021) and oleic acid (r = −0.7809, p = 0.022) (Figure 2F,G).
|
| 135 |
+
|
| 136 |
+
NF-κB, PPAR-α, and TLR-4, as present in the nuclear fraction in the liver, did not differ among the experimental groups (p > 0.05; Figure 2I–K).
|
| 137 |
+
|
| 138 |
+
3.5. Effects of Macauba Pulp Oil on Gene Expression in Adipose and Hepatic Tissues
|
| 139 |
+
|
| 140 |
+
In the liver, in the HFM group, the mRNA expression of SREBP-1c was significantly increased compared to the control and HFD groups (p < 0.0001; Figure 3A), whereas (mRNA) CPT-1α was decreased (p = 0.0031; Figure 3B). The mRNA expression of ACC-1α and AdipoR2 did not differ from the HFD group (p > 0.05; Figure 3C,D).
|
| 141 |
+
|
| 142 |
+
In the adipose tissue, in the HFM group, the mRNA expression of SREBP-1c (p < 0.0001; Figure 3E) and (mRNA) TNF-α (p < 0.0001; Figure 3H) were significantly decreased compared to the HFD group, and the mRNA expression of Adiponectin was similar between the HFM and CD groups (p > 0.05; Figure 3G). The mRNA expression of LPL was similar among the groups (p > 0.05; Figure 3F). The correlation analysis showed a negative correlation between mRNA SREBP-1c and carotenoid intake (r = −0.8991, p = 0.012), a positive correlation between mRNA Adiponectin and carotenoid intake (r = 0.9130, p < 0.001), and negative correlation between mRNA TNF-α and oleic acid intake (r = −0.9057, p = 0.0009).
|
| 143 |
+
|
| 144 |
+
3.6. Effects of Macauba Pulp Oil on Histological Morphometrics of Liver and Adipose Tissues
|
| 145 |
+
|
| 146 |
+
The percentage of the nucleus, cytoplasm, inflammatory infiltrate, and fat deposition in the hepatocytes did not differ among the groups (p > 0.05, Figure 4A). The control group was identified as steatosis grade 0, whereas the HFD and HFM groups increased the steatosis to grade 1 and had similar values between them (Figure 4B). The HFM group had lower inflammatory infiltrate (p < 0.0001) and adipocyte number (p = 0.0027) and length (p = 0.0088) in the adipose tissue compared to the HFD group, but its values were similar to the CD group (Figure 4C,D).
|
| 147 |
+
|
| 148 |
+
4. Discussion
|
| 149 |
+
|
| 150 |
+
This is the first work that evaluated the influence of macauba pulp oil on undesirable metabolic changes in mice fed a high-fat diet. The present research focused on the effects of macauba pulp oil since there is evidence that oleic acid, carotenoid, and tocopherol present in this oil would trigger anti-inflammatory, anti-obesity, and antioxidant effects [27,28]. In this study, macauba pulp oil intake prevented the adipogenesis pathway, inflammation, and oxidative stress in mice fed a high-fat diet. In order to stimulate metabolic changes in animals, high-saturated fat diet consumption is extensively applied. The time to verify the effect of a specific food or compound on metabolic changes usually begins after seven or eight weeks of receiving the diet. In a different way, in our study, to determine the effects of macauba pulp oil as a preventive treatment, macauba pulp oil was added in the diet since the beginning of the experiment, along with the high-fat diet, to examine its mechanism of action and metabolic alterations.
|
| 151 |
+
|
| 152 |
+
In the present study, the consumption of macauba pulp oil reflected a higher total antioxidant capacity (TAC), which might be associated with the oleic acid content, and this was confirmed by the correlation analysis, which demonstrated a significant positive correlation between this compound consumption and TAC. Oleic acid is well documented for its anti-inflammatory properties, possibly associated with its chemical configuration with a double bond, thereby causing less chance of oxidation and resulting in the antioxidant property against a high oxidative load [10,29]. In addition, higher SOD activity and lower malondialdehyde levels were observed with the macauba pulp oil consumption. SODs are oxidoreductase enzymes that have a role in protecting cells against superoxide anions, performing the dismutation of O2•− into oxygen and H2O2, and providing antioxidant defense for the organism, while malondialdehyde is an important marker of lipid peroxidation [30,31]. it is shown that macauba pulp oil consumption can improve antioxidant defenses, with these results being attributed to the oleic acid, carotenoids, and tocopherol present in macauba pulp oil, as demonstrated in other studies that examined the relationship between these components and the improvement of the body’s antioxidant defenses [32,33,34]. Additionally, there was a positive correlation between SOD and these compounds and a negative correlation between MDA and oleic acid and tocopherol.
|
| 153 |
+
|
| 154 |
+
The consumption of macauba pulp oil prevented the adipogenesis pathway by decreasing the expression of PPAR-γ and (mRNA) SREBP-1c and increasing the expression of (mRNA) Adiponectin in the adipose tissue. This effect was confirmed by the result of the histomorphometric analysis, which demonstrated that the animals that consumed the macauba pulp oil had smaller adipocyte number and length even with a high-fat diet consumption, that is, the macauba pulp oil caused less hypertrophy and hyperplasia of the adipocytes. Thus, the lower translocation of PPAR-γ in the present research could be associated with the high content of oleic acid and carotenoids in the macauba pulp oil and was confirmed by the significant negative correlation between the consumption of these compounds and PPAR-γ quantification. Oleic acid has been shown to act in PPAR-γ repression, resulting in less differentiation of pre-adipocytes into mature adipocytes and reducing adipogenesis [3,35]. Similar to our results, a previous study found a relationship between oleic acid consumption and reduction in PPAR-γ and (mRNA) SREBP-1c in an obese animal model [35]. Research shows that carotenoids can affect adipocyte function through the interaction with PPAR-γ, thereby interfering with adipocyte differentiation, as demonstrated in a study using experimental animals, which found an association between carotenoids and lower adipose tissue gain related to lower PPAR-γ expression [36]. Still, this result is related to the increased expression of adiponectin since PPAR-γ is tightly regulated by adiponectin [37]. Moreover, the observed results of a reduction in the genes related to the adipogenesis pathway, with a concomitant reduction in the histological markers of adipose tissue, could be related to the presence of β-carotene, which was the main carotenoid found in the macauba pulp oil that could suppress PPAR-γ, resulting in lower total lipid in adipocytes [38,39].
|
| 155 |
+
|
| 156 |
+
Related to this, macauba pulp oil was efficient in reducing inflammation in the adipose tissue since it reduced NF-κB in the nuclear fraction, and this indicates a reduction in the inflammation cascade, leading to a significant reduction in (mRNA) TNF-α gene expression. Corroborating this result, the histomorphometric analysis of the adipose tissue showed less inflammatory infiltrate with the consumption of macauba pulp oil. A hypertrophy of adipose tissue initiates the emission of chemotactic signals that recruit immune cells and lead to the infiltration of macrophages into the adipose tissue, contributing to systemic subclinical inflammation [3]. This result may be associated with a lower amount of PPAR-γ and higher adiponectin since PPAR-γ interferes with the differentiation of adipocytes and is consequently related to the inflammatory process. Obesity is an inflammatory condition: one of the complications related to obesity is the development of reactive oxygen species (ROS), and adiponectin is an anti-inflammatory adipokine with a negative correlation between the degree of obesity and the level of this adipokine [40,41]. These results were supported by the present study since there was a positive correlation between carotenoid consumption and an increase in the expression of adiponectin, indicating that the macauba pulp oil, which is high in carotenoids, may contribute to the reduction of inflammation. Additionally, there was a significant negative correlation between oleic acid and tocopherol and NF-κB, that is, an increase in oleic acid and tocopherol consumption was correlated with a decrease in the quantification of NF-κB. The study by Rosillo et al., with a mouse model, also demonstrated that the administration of oleic acid is able to suppress NF-κB activation [42]. Oleic acid is able to activate PGC-1α by forming a dimer with the protein called c-MAF, migrate to the nucleus, and then transcribe the gene responsible for IL-10, which dismantles the activation signaling of NF-κB due to its potent anti-inflammatory action [43]. Tocopherol can block NF-kB activation through its action on enzymes that regulate the NF-kB signaling pathway [44]. Despite the lack of a correlation between the reduction in NF-κB and the consumption of carotenoids in the present study, this compound presents interference with the NF-κB pathway, resulting in the modulation of their interacting proteins and interacting with the cysteine residues of IκB kinase, thereby suppressing NF-κB activation or inhibiting IκBα degradation [45,46].
|
| 157 |
+
|
| 158 |
+
Although macauba pulp oil prevented the adipogenesis pathway and inflammation in the adipose tissue, significant effects in the hepatic markers were not observed after eight weeks of the high-fat diet. The current study was carried out as a prevention model, and for this reason, it might not be able to verify alterations in the liver. Thus, in the current research, the consumption of the diets for eight weeks, even with a high concentration of saturated fats, was not able to cause metabolic changes in the liver. These results were confirmed by histomorphometric analyses, which showed that there was no alteration of the cellular components evaluated, such as fat and inflammation in the liver.
|
| 159 |
+
|
| 160 |
+
Despite the decreased expression of (mRNA) CPT-1α gene, the quantification of PPAR-α did not change with the consumption of macauba pulp oil, which might be because ADIPOR2 did not change either. The increase in the sensitization of ADIPOR2 receptor triggers the activation of PPAR-α, which regulates fatty acid oxidation [47]. Moreover, the high traffic of free fatty acids due to a high-fat diet has the ability to trigger SREBP-1c, which controls the expression of enzymes essential in triacylglycerol synthesis and storage, and restricts lipogenic genes, such as ACC-1, that are responsible for the transformation of ACC-1 to malonyl CoA [48]. However, despite the overexpression of this gene in the fatty acid synthesis pathway, there was no change in the proportion of fat and steatosis degree in the liver. This might be due to the increased antioxidant capacity, which decreased the expression of this gene in relation to fatty acid synthesis.
|
| 161 |
+
|
| 162 |
+
The strain of mice used in this study was chosen since they are prone to metabolic disturbances generated by a high-fat diet. However, it is known that experiments with mice do not fully reflect the effects in humans due to differences in the organs and metabolism of these two species. However, taking into account the macauba pulp oil intake per animal weight, a human with 70 kg needs a consumption of a small amount per day (approximately 8 g/day of macauba pulp oil—similar to one teaspoon) to have the same improvements observed in this research in the prevention of metabolic changes. Thus, further studies are needed to verify the real effects of macauba pulp oil in human.
|
| 163 |
+
|
| 164 |
+
The influence of a high-fat diet on the body and the mechanism of macauba pulp oil, which was demonstrated in our study, are summarized in Figure 5. The consumption of macauba pulp oil prevents inflammation and adipogenesis, as demonstrated by a reduction in the expression of PPAR-γ, (mRNA) SREBP-1c, NF-κB, and (mRNA) TNF-α, and an increase in adiponectin in adipose tissue. In the liver, despite triggering the SREBP-1c expression and a lower (mRNA) CPT-1α level, it does not lead to liver changes, according to the histomorphometric analysis, due to an increased antioxidant capacity. These modes of action may be related to macauba pulp oil, which has a good composition of carotenoids, oleic acid, and tocopherol and improves the total antioxidant capacity, resulting in adipogenesis even with a high level of saturated fat consumption.
|
| 165 |
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|
| 166 |
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5. Conclusions
|
| 167 |
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|
| 168 |
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Consumption of macauba pulp oil increases antioxidant capacity and prevents oxidative stress, inflammation, and the adipogenesis pathway. Therefore, macauba pulp oil has a great potential for inclusion in human foods to improve health, assisting in the prevention of risk factors for chronic non-communicable diseases.
|
| 169 |
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|
| 170 |
+
Acknowledgments
|
| 171 |
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|
| 172 |
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We gratefully acknowledge the Soleá Brasil Óleos Vegetais Ltd.a (Brazil) for providing the macauba used in this study and financial support, and Ceres Mattos Della Lucia (Federal University of Viçosa, Brazil) for her assistance with the quantification of tocopherols and carotenoids.
|
| 173 |
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|
| 174 |
+
Author Contributions
|
| 175 |
+
|
| 176 |
+
C.T.S.A.: data curation, formal analysis, methodology, investigation, validation, writing—original draft, and writing—review and editing. T.A.V.: formal analysis and methodology. M.G.: formal analysis and methodology. R.C.L.T.: formal analysis and methodology. E.T.: writing—review and editing. N.M.B.C.: supervision and writing—review and editing. H.S.D.M.: conceptualization, project administration, supervision, and writing—review and editing. F.A.R.d.B.: conceptualization, funding acquisition, project administration, supervision, and writing—review and editing. All authors have read and agreed to the published version of the manuscript.
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|
| 178 |
+
Institutional Review Board Statement
|
| 179 |
+
|
| 180 |
+
This study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the Federal University of Viçosa (protocol code 09/2019 and date of approval 28 May 2019).
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| 182 |
+
Informed Consent Statement
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|
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Not applicable.
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Data Availability Statement
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+
Data are contained within the article.
|
| 189 |
+
|
| 190 |
+
Conflicts of Interest
|
| 191 |
+
|
| 192 |
+
The authors declare no conflict of interest.
|
| 193 |
+
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| 194 |
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Figure 1 Oxidative stress level and antioxidant capacity of mice after consuming the experimental diets for 8 weeks, and correlation with carotenoid, oleic acid, and tocopherol intakes. (A) Superoxide dismutase level. (B) Correlation between SOD level and carotenoid intake. (C) Correlation between SOD level and oleic acid intake. (D) Correlation between SOD level and tocopherol intake. (E) Malondialdehyde level. (F) Correlation between MDA level and carotenoid intake. (G) Correlation between MDA level and oleic acid intake. (H) Correlation between MDA level and tocopherol intake. (I) Serum total antioxidant capacity level. (J) Correlation between serum TAC level and carotenoid intake. (K) Correlation between serum TAC level and oleic acid intake. (L) Correlation between serum TAC level and tocopherol intake. (M) Catalase level. (N) Nitric oxide level. (O) Liver total antioxidant capacity level. Data are expressed as mean ± standard deviation (n = 10). Different letters indicate a statistical difference based on the Newman–Keuls test (p ≤ 0.05). CD: control diet—AIN93M; HFD: high-fat diet; HFM: high-fat diet with macauba pulp oil; SOD: superoxide dismutase; MDA: malondialdehyde; TAC: total antioxidant capacity.
|
| 195 |
+
|
| 196 |
+
Figure 2 Levels of proteins in the adipose tissue (A–H) and liver (I–K) of mice after consuming the experimental diets for 8 weeks, and correlation with carotenoid, oleic acid, and tocopherol intakes. Data are expressed as mean ± standard deviation (n = 8). Different letters indicate a statistical difference based on the Newman–Keuls test (p ≤ 0.05). CD: control diet—AIN93M; HFD: high-fat diet; HFM: high-fat diet with macauba pulp oil; NF-κB p65: nuclear factor kappa B subunit p65; PPAR-α: peroxisome proliferator-activated receptor alpha; PPAR-γ: peroxisome proliferator-activated receptor gamma; TLR-4: toll-like receptor 4.
|
| 197 |
+
|
| 198 |
+
Figure 3 Gene expression in the liver (A–D) and adipose tissue (E–H) of mice after consuming the experimental diets for 8 weeks. Data are expressed as mean ± standard deviation (n = 8). Different letters indicate a statistical difference based on the Newman–Keuls test (p ≤ 0.05). CD: control diet—AIN93M; HFD: high-fat diet; HFM: high-fat diet with macauba pulp oil; SREBP-1c: sterol regulatory element-binding proteins 1c; ADIPOR2: adiponectin receptor 2; ACC-1: acetyl CoA carboxilase 1; CPT-1α: carnitine palmitoyl transferase 1 alpha; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; LPL: lipoprotein lipase; TNF-α: tumor necrosis factor alpha.
|
| 199 |
+
|
| 200 |
+
Figure 4 Cellular components: percentage in hepatic tissue (A), steatosis degree (B), number and length of adipocyte (C), and inflammatory infiltrate (D). The black arrows represent the following: z: cytoplasm, f: fat vesicles, n: nucleus, p: inflammatory infiltrate, and r: adiposity. Data are expressed as mean ± standard deviation (n = 10). Different letters indicate a statistical difference based on the Newman–Keuls test (p ≤ 0.05). CD: control diet; HFD: high-fat diet; HFM: high-fat diet with macauba pulp oil.
|
| 201 |
+
|
| 202 |
+
Figure 5 Effects of a high-fat diet on the adipose tissue and liver and potential action mechanism of macauba pulp oil. TLR-4: toll-like receptor 4; NF-κB: nuclear factor kappa B; SREBP-1c: sterol regulatory element-binding protein; ACC-1: acetyl-CoA carboxylase 1; ADIPOR2: adiponectin receptor 2; CPT-1α: carnitine palmitoyl transferase 1 alpha; PPAR-γ: peroxisome proliferator-activated receptor gamma; PPAR-α: peroxisome proliferator-activated receptor alpha; LPL: lipoprotein lipase; TNF-α: tumor necrosis factor alpha; Ikk: IkB kinase complex; IkBα nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor alpha; Malonil-CoA: malonyl coenzyme A; FA: fatty acid.
|
| 203 |
+
|
| 204 |
+
nutrients-15-01252-t001_Table 1 Table 1 Composition of experimental diets (g/kg of diet).
|
| 205 |
+
|
| 206 |
+
Ingredients (g/kg) CD HFD HFM
|
| 207 |
+
Albumin * 179.71 179.71 179.71
|
| 208 |
+
Dextrinized starch 155 155 155
|
| 209 |
+
Sucrose 100 100 100
|
| 210 |
+
Soybean oil 40 40 -
|
| 211 |
+
Lard 0 312 312
|
| 212 |
+
Cellulose 50 50 50
|
| 213 |
+
Mineral mix 35 35 35
|
| 214 |
+
Vitamin mix 10 10 10
|
| 215 |
+
L-cystine 1.8 1.8 1.8
|
| 216 |
+
Choline bitartrate 2.5 2.5 2.5
|
| 217 |
+
Corn starch 425.99 113.99 113.99
|
| 218 |
+
Macauba pulp oil - - 40
|
| 219 |
+
Carbohydrate (%) 76.9 44.1 44.1
|
| 220 |
+
Protein (%) 18.9 18.9 18.9
|
| 221 |
+
Lipids (%) 4.20 37 37
|
| 222 |
+
Caloric density (kcal g−1) 3.85 5.41 5.41
|
| 223 |
+
* Purity of 78%. CD: control diet (AIN93M); HFD: high-fat diet; HFM: high-fat diet with macauba pulp oil.
|
| 224 |
+
|
| 225 |
+
nutrients-15-01252-t002_Table 2 Table 2 Sequence of primers used in the RT-qPCR analyses.
|
| 226 |
+
|
| 227 |
+
Genes Forward Reverse
|
| 228 |
+
SREBP-1c CGC TAC CGT TCC TCT ATC AAT GAC AGT TTC TGG TTG CTG TGC TGT AAG
|
| 229 |
+
ADIPOR2 CAT GTT TGC CAC CCC TCA GTA ATG CAA GGT AGG GAT TCC A
|
| 230 |
+
ACC-1 TCA AGA CGG CTC AGG TCA TCA AGG CGC CAA ACT TCA GCA TC
|
| 231 |
+
CPT-1α GTA AGG CCA CTG ATG AAG GAA GA ATT TGG GTC CGA GGT TGA CA
|
| 232 |
+
LPL TCA ACC ACA GCA GCA AGA CCG ATA CAA CCA GTC TAC TAC AA
|
| 233 |
+
Adiponectin ATG AGT ACC AGA CTA ATG AGA C GGC AGG ATT AAG AGG AAC A
|
| 234 |
+
TNF-α TAT GGC TCA GGG TCC AAC TC GCT CCA GTG AAT TCG GAA AG
|
| 235 |
+
SREBP-1c GCC GAG ATG TGC GAA CTG GGA AGT CAC TGT CTT GGT TGT T
|
| 236 |
+
β-actin TTC GTT GCC GGT CCA CC GCT TTG CAC ATG CCG GAG CC
|
| 237 |
+
GAPDH AGG TTG TCT CCT GTC ACT TC CTG TTG CTG TAG CCA TAT TC
|
| 238 |
+
SREBP-1c: Sterol regulatory element-binding proteins 1c; ADIPOR2: adiponectin receptor 2; ACC-1: acetyl CoA carboxylase 1; CPT-1α: carnitine palmitoyl transferase 1 alpha; LPL: Lipoprotein lipase; TNF-α: Tumor necrosis factor alpha; GAPDH: Glyceraldehyde-3-phosphate dehydrogenase.
|
| 239 |
+
|
| 240 |
+
nutrients-15-01252-t003_Table 3 Table 3 Fatty acid profile, carotenoids, and tocopherol contents in macauba pulp oil.
|
| 241 |
+
|
| 242 |
+
Components
|
| 243 |
+
Palmitic (C16:0) 22.84%
|
| 244 |
+
Palmitoleic (C16:1) 5.93%
|
| 245 |
+
Stearic (C18:0) 1.23%
|
| 246 |
+
Oleic (C18:1n9c) 49.32%
|
| 247 |
+
Linoleic (C18:2n6c) 19.63%
|
| 248 |
+
Linolenic (C18:3n6c) 1.05%
|
| 249 |
+
Oleic acid (mg/g) 199.00
|
| 250 |
+
Tocopherol (μg/g) 40.80
|
| 251 |
+
Total carotenoids (μg/g) 207.52
|
| 252 |
+
β-carotene (μg/g) 163.63
|
| 253 |
+
α-carotene (μg/g) 21.03
|
| 254 |
+
Lutein (μg/g) 8.75
|
| 255 |
+
Lycopene (μg/g) 14.11
|
| 256 |
+
Caprylic, capric, lauric, and myristic acids are not detected.
|
| 257 |
+
|
| 258 |
+
nutrients-15-01252-t004_Table 4 Table 4 Biometric measures, food intake, and serum biochemical values of the mice after consuming the experimental diets for 8 weeks.
|
| 259 |
+
|
| 260 |
+
CD HFD HFM
|
| 261 |
+
Weight gain (g) 4.01 ± 1.74 a 4.14 ± 2.23 a 3.66 ± 2.23 a
|
| 262 |
+
BMI (g/cm2) 0.34 ± 0.02 a 0.33 ± 0.01 a 0.33 ± 0.02 a
|
| 263 |
+
Adiposity (%) 0.71 ± 0.24 b 2.43 ± 1.28 a 2.26 ± 1.25 a
|
| 264 |
+
Food consumption (g/day) 4.07 ± 0.16 a 2.53 ± 0.41 b 2.63 ± 0.42 b
|
| 265 |
+
Food efficiency (%) 1.69 ± 0.60 b 2.67 ± 1.46 a 2.42 ± 1.55 a
|
| 266 |
+
Hepatosomatic index (%) 3.61 ± 0.29 a 3.72 ± 0.28 a 3.48 ± 0.29 a
|
| 267 |
+
Oleic acid intake (mg/day) - - 0.52 ± 0.08
|
| 268 |
+
Carotenoid intake (µg/day) - - 21.96 ± 4.11
|
| 269 |
+
Tocopherol intake (mg/day) 0.46 ± 0.01 a 0.29 ± 0.03 b 0.31 ± 0.03 b
|
| 270 |
+
Total cholesterol (mg dL−1) 151.48 ± 13.79 b 166.49 ± 15.51 a 179.91 ± 6.87 a
|
| 271 |
+
Total triglycerides (mg dL−1) 79.91 ± 4.71 a 84.83 ± 5.63 a 83.06 ± 5.09 a
|
| 272 |
+
HDL-c (mg dL−1) 38.13 ± 4.29 a 37.35 ± 5.79 a 43.07 ± 5.64 a
|
| 273 |
+
LDL-c (mg dL−1) 12.80 ± 2.11 b 20.64 ± 5.25 a 20.80 ± 5.20 a
|
| 274 |
+
Glucose (mg dL−1) 160.67 ± 44.23 a 182.58 ± 30.09 a 197.31 ± 36.68 a
|
| 275 |
+
AST (mg dL−1) 88.14 ± 21.88 a 71.66 ± 21.30 a 73.39 ± 19.04 a
|
| 276 |
+
ALT (mg dL−1) 18.74 ± 9.88 a 15.71 ± 5.63 a 18.84 ± 9.26 a
|
| 277 |
+
Data are expressed as mean ± standard deviation (n = 10). Different lowercase letters in the same row indicate a statistical difference based on the Newman–Keuls test (p ≤ 0.05). CD: control diet—AIN93M; HFD: high-fat diet; HFM: high-fat diet with macauba pulp oil; BMI: body mass index; HDL-c: high-density lipoprotein; LDL-c: low-density lipoprotein; ALT: alanine aminotransferase; AST: aspartate aminotransferase.
|
| 278 |
+
|
| 279 |
+
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
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| 280 |
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Front Cardiovasc Med
|
| 4 |
+
Front Cardiovasc Med
|
| 5 |
+
Front. Cardiovasc. Med.
|
| 6 |
+
Frontiers in Cardiovascular Medicine
|
| 7 |
+
2297-055X
|
| 8 |
+
Frontiers Media S.A.
|
| 9 |
+
|
| 10 |
+
10.3389/fcvm.2023.1118738
|
| 11 |
+
Cardiovascular Medicine
|
| 12 |
+
Original Research
|
| 13 |
+
Muscle progenitor cells are required for skeletal muscle regeneration and prevention of adipogenesis after limb ischemia
|
| 14 |
+
Abbas Hasan 1 2 3
|
| 15 |
+
|
| 16 |
+
Olivere Lindsey A. 4
|
| 17 |
+
|
| 18 |
+
Padgett Michael E. 3
|
| 19 |
+
Schmidt Cameron A. 5 6
|
| 20 |
+
|
| 21 |
+
Gilmore Brian F. 7
|
| 22 |
+
McCord Timothy J. 8
|
| 23 |
+
Southerland Kevin W. 7
|
| 24 |
+
|
| 25 |
+
McClung Joseph M. 5 6 9
|
| 26 |
+
|
| 27 |
+
Kontos Christopher D. 1 3 4 *
|
| 28 |
+
|
| 29 |
+
1Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC, United States
|
| 30 |
+
2Duke-NUS Medical School, Singapore, Singapore
|
| 31 |
+
3Department of Medicine, Division of Cardiology, Duke University Medical Center, Durham, NC, United States
|
| 32 |
+
4Duke University School of Medicine, Durham, NC, United States
|
| 33 |
+
5Department of Physiology, Brody School of Medicine, East Carolina University, Greenville, NC, United States
|
| 34 |
+
6Brody School of Medicine, East Carolina Diabetes and Obesity Institute, East Carolina University, Greenville, NC, United States
|
| 35 |
+
7Department of Surgery, Duke University Medical Center, Durham, NC, United States
|
| 36 |
+
8Department of Cell Biology, Duke University School of Medicine, Durham, NC, United States
|
| 37 |
+
9Brody School of Medicine, East Carolina Heart Institute, East Carolina University, Greenville, NC, United States
|
| 38 |
+
Edited by: Roberto Vazquez-Padron, University of Miami, United States
|
| 39 |
+
|
| 40 |
+
Reviewed by: Xiaoguang Liu, Guangzhou Sport University, China; Vihang Narkar, The University of Texas Health Science Center at Houston, United States
|
| 41 |
+
|
| 42 |
+
*Correspondence: Christopher D. Kontos, cdkontos@duke.edu
|
| 43 |
+
This article was submitted to Atherosclerosis and Vascular Medicine, a section of the journal Frontiers in Cardiovascular Medicine
|
| 44 |
+
|
| 45 |
+
02 3 2023
|
| 46 |
+
2023
|
| 47 |
+
10 111873807 12 2022
|
| 48 |
+
08 2 2023
|
| 49 |
+
Copyright © 2023 Abbas, Olivere, Padgett, Schmidt, Gilmore, McCord, Southerland, McClung and Kontos.
|
| 50 |
+
2023
|
| 51 |
+
Abbas, Olivere, Padgett, Schmidt, Gilmore, McCord, Southerland, McClung and Kontos
|
| 52 |
+
https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
|
| 53 |
+
Skeletal muscle injury in peripheral artery disease (PAD) has been attributed to vascular insufficiency, however evidence has demonstrated that muscle cell responses play a role in determining outcomes in limb ischemia. Here, we demonstrate that genetic ablation of Pax7+ muscle progenitor cells (MPCs) in a model of hindlimb ischemia (HLI) inhibited muscle regeneration following ischemic injury, despite a lack of morphological or physiological changes in resting muscle. Compared to control mice (Pax7WT), the ischemic limb of Pax7-deficient mice (Pax7Δ) was unable to generate significant force 7 or 28 days after HLI. A significant increase in adipose was observed in the ischemic limb 28 days after HLI in Pax7Δ mice, which replaced functional muscle. Adipogenesis in Pax7Δ mice corresponded with a significant increase in PDGFRα+ fibro/adipogenic progenitors (FAPs). Inhibition of FAPs with batimastat decreased muscle adipose but increased fibrosis. In vitro, Pax7Δ MPCs failed to form myotubes but displayed increased adipogenesis. Skeletal muscle from patients with critical limb threatening ischemia displayed increased adipose in more ischemic regions of muscle, which corresponded with fewer satellite cells. Collectively, these data demonstrate that Pax7+ MPCs are required for muscle regeneration after ischemia and suggest that muscle regeneration may be an important therapeutic target in PAD.
|
| 54 |
+
|
| 55 |
+
peripheral artery disease
|
| 56 |
+
critical limb threatening ischemia
|
| 57 |
+
muscle progenitor cells
|
| 58 |
+
skeletal muscle regeneration
|
| 59 |
+
fibro/adipogenic progenitor cells
|
| 60 |
+
hind limb ischemia
|
| 61 |
+
adipogenesis
|
| 62 |
+
==== Body
|
| 63 |
+
pmc1. Introduction
|
| 64 |
+
|
| 65 |
+
Peripheral artery disease (PAD) is caused by atherosclerosis of the peripheral arteries, most commonly the legs. PAD affects over 200 million individuals globally, and it is a major contributor to disease burden in both developing and developed countries (1, 2). Current treatment options are limited to surgical and percutaneous revascularization approaches (3), both of which have minimal impact on long-term morbidity and mortality (4, 5). The clinical course of PAD ranges from the milder manifestation of intermittent claudication (IC), resulting in pain with ambulation that resolves with rest, to the more severe critical limb threatening ischemia (CLTI), characterized by pain at rest, either with or without tissue necrosis (3). Although CLTI affects only 10–15% of patients with PAD, it results in a substantial burden on the health care system, as these patients often progress to limb amputation and have significantly greater morbidity and mortality (6, 7). Although therapeutic approaches to PAD primarily target revascularization and tissue perfusion, it has been observed that patients with similar degrees of atherosclerotic vascular occlusion often present with markedly different severity of disease (8, 9), suggesting that blood flow alone may not determine clinical outcomes.
|
| 66 |
+
|
| 67 |
+
Recent evidence from our group and others supports the idea that skeletal muscle responses to tissue ischemia, and not solely the vascular supply, play an important role in determining the muscle response to limb ischemia (9–12). In mice subjected to hind limb ischemia (HLI), a model of PAD, the genetic background strongly influences outcomes. For example, C57BL/6 mice display not only robust angiogenesis but also a muscle regenerative response that typically leads to full recovery from HLI. In stark contrast, HLI in BALB/c mice typically results in muscle degeneration and auto-amputation, and even muscle that does survive fails to recover function, i.e., force generation (9). Although this genetic difference was previously attributed to differences in collateral vessel density (13–16), muscle progenitor cells (MPCs) isolated from these strains of mice display markedly different responses to experimental ischemia in vitro, independent of blood supply. This finding is consistent with the differential responses observed in vivo and it suggests muscle cell-specific determinants of the response to ischemia. Although the mechanisms by which skeletal muscle responds to ischemia remain poorly understood, a genetic variant in at least one gene, Bag3, has been linked to this differential ischemic response in mice (12). However, it is not known whether these effects are at the level of mature muscle cells or MPCs.
|
| 68 |
+
|
| 69 |
+
MPCs, commonly known as satellite cells, lie between the basal lamina and plasma membrane of skeletal muscle cells and are critical regulators of postnatal myofiber regeneration (17, 18). MPCs are defined by expression of the Pax3 homolog Pax7, and they serve as a unipotent stem cell population for myogenesis following injury (19). However, these cells have a limited capacity for self-renewal, and repeated replication cycles may result in depletion of the satellite cell pool (20). The development of genetically modified mouse models to ablate MPCs has allowed investigation of the role of Pax7+ MPCs in various disease states. In particular, mice inducibly expressing Diphtheria toxin A (DTA) only in Pax7+ cells have been used to demonstrate a requirement for these MPCs in muscle regeneration in a variety of conditions. Most of these studies have been performed using cytotoxic injury models, such as cardiotoxin, freeze injury, or BaCl2 injury (21). However, it is known that different modes of injury have unique characteristics. For example, glycerol injury results in a more adipogenic phenotype compared to other modes of injury (22). Although we and others have characterized the skeletal muscle response to ischemia (9, 10, 12, 23, 24), the role of MPCs in this process remains unexplored.
|
| 70 |
+
|
| 71 |
+
In addition to MPCs, the discovery of a novel subpopulation of fibro/adipogenic progenitors (FAPs) in mature skeletal muscle (25) has led to considerable focus on the role of these cells in pathological skeletal muscle conditions. Histologically and functionally, these cells can be identified in skeletal muscle by their expression of platelet-derived growth factor receptor alpha (PDGFRα) and signaling by this receptor in pathophysiology (26–28). FAPs isolated from skeletal muscle were able to cause white fat infiltration in diseased but not in healthy muscle because myofibers have a significant inhibitory effect on the differentiation of FAPs (29). This observation suggests an environmental contribution to FAP cell fate. FAP expansion has also been shown to regulate the MPC pool during muscle regeneration in addition to playing a critical role in skeletal muscle homeostasis (27).
|
| 72 |
+
|
| 73 |
+
Here, we used genetically modified mouse models to explore the role of Pax7+ MPCs in the skeletal muscle response to hind limb ischemia. We demonstrate a near complete absence of skeletal muscle regeneration after HLI in mice following ablation of Pax7+ satellite cells. Furthermore, ischemic, Pax7-deficient muscle displayed a dramatic increase in adipogenesis that was driven at least in part by FAPs. Consistent with these findings in mice, decreased MPC numbers and increased adipogenesis were observed in more ischemic regions of skeletal muscle of CLTI patients. These findings demonstrate the requirement for Pax7+ MPCs in ischemic skeletal muscle regeneration, and they provide important new insights into the pathogenesis of PAD.
|
| 74 |
+
|
| 75 |
+
2. Materials and methods
|
| 76 |
+
|
| 77 |
+
2.1. Mouse lines and tamoxifen treatment
|
| 78 |
+
|
| 79 |
+
For satellite cell genetic ablation experiments, Pax7-CreERT2 mice (Jackson Labs Stock: 017763, B6.Cg-Pax7tm1(cre/ERT2)Gaka/J) were crossed to ROSA26DTA mice (Jackson Labs Stock: 009669, C.129P2(B6)-Gt(ROSA)26Sortm1(DTA)Lky/J). Both lines of mice had been backcrossed to C57BL/6 J mice for at least 8 generations at the time of these studies. Mice were given sterile-filtered tamoxifen (Sigma T5648) or corn oil at 75 mg/kg body weight via an intraperitoneal route for 5 days. Following this initial treatment, mice were given tamoxifen (Envigo Teklad Tamoxifen Diet TD.130855) or a control-matched diet (Envigo Teklad global 16% protein diet 2016S) to continue treatment at a lower dose of 50 mg/kg body weight. All mice were used at 8–12 weeks of age unless stated otherwise.
|
| 80 |
+
|
| 81 |
+
2.2. Hindlimb ischemia surgery and perfusion imaging
|
| 82 |
+
|
| 83 |
+
Hindlimb Ischemia surgery was performed as described previously (10, 30). Briefly, mice were anaesthetized on a heated pad with inhaled isoflurane (1–3%) in oxygen (1.5 L/min). Prior to surgery, the mice were scanned with a Laser Doppler Perfusion Imager (LDPI, Moor Instruments United States) to quantify baseline perfusion in the hindlimbs. Using sterile surgical instruments (sterilized by autoclaving), a 1-cm incision was made just below the inguinal ligament. Subcutaneous fat was removed and the femoral artery was separated from the neurovascular bundle, taking care not to perforate the femoral vein. A 7–0 silk non-absorbable suture (Sharpoint) was used to ligate the femoral artery above the bifurcation of the lateral circumflex femoral artery, and a ligature was also made below the superficial caudal epigastric artery but above the bifurcation of the popliteal artery. The wound was then closed using an absorbable Vicryl 5–0 suture (Ethicon). A post-operative LDPI scan was then performed to verify complete occlusion of the artery. Mice were provided appropriate pain relief and monitored after surgery to ensure animal welfare.
|
| 84 |
+
|
| 85 |
+
2.3. Tissue collection and muscle processing
|
| 86 |
+
|
| 87 |
+
Mice were deeply anesthetized with inhaled isoflurane as described above, and the tibialis anterior (TA) and extensor digitorum longus (EDL) muscles were isolated and frozen on liquid nitrogen in Optimal Cutting Temperature (OCT) medium, while the gastrocnemius muscles were flash frozen in liquid nitrogen and stored at −80°C for later tissue analysis. Mice were euthanized by exsanguination or bilateral thoracotomy while still under anesthesia. Tissue sections (8 μm or 30 μm) were cut on a Leica 3150S cryostat at −21° to −25°C and stored on Superfrost Slides.
|
| 88 |
+
|
| 89 |
+
2.4. Immunofluorescence microscopy and image analysis
|
| 90 |
+
|
| 91 |
+
Tissue sections were fixed in 4% paraformaldehyde (PFA) followed by permeabilization in 0.2% Triton X-100 in Phosphate-Buffered Saline (PBS). After washes in PBS, slides were blocked with 5% normal goat serum (NGS) in PBS for 1 h. Dilutions of antibodies used for immunostaining are listed in the Table 1. For Pax7 immunofluorescence staining, a goat anti-mouse IgG blocking antibody (Jackson Immunoresearch 115–007-003) was used in blocking buffer, and an antigen retrieval step was performed by heating slides in a Cuisinart CPC-6001000-watt pressure cooker at high setting in 10 mM sodium citrate, 0.05% Tween 20, pH 6.0, and allowed to return to room temperature over 20 min prior to incubation with the primary antibody. Slides were incubated overnight at 4°C with antibodies of interest at the dilutions listed in Table 1. The following day, sections were washes 3 times in PBS, followed by incubation at room temperature for 1 h with appropriate Alexa Fluor-conjugated secondary antibody. Slides were then washed 3 times with PBS or PBST followed by a 5-min incubation with a nuclear stain (DAPI or Hoechst) as indicated. After a final PBS rinse, slides were mounted in either Vectashield Antifade Mounting Medium (H1000) or Prolong Gold Antifade Mountant (Invitrogen P36962) and allowed to cure overnight. Brightfield microscopy and epifluorescence microscopy were both performed on a Zeiss Upright AxioImager, while all confocal microscopy was performed on the Zeiss 780 or Zeiss 880 Inverted Confocal Microscope. All image analysis was performed in Zeiss Zen software, IMARIS, or ImageJ with identical thresholds and blinding performed for all signal quantification.
|
| 92 |
+
|
| 93 |
+
Table 1 Commercially available antibodies used for immunofluorescence microscopy.
|
| 94 |
+
|
| 95 |
+
Antibody Manufacturer Catalog Number Dilution Species
|
| 96 |
+
Pax7 DSHB Pax7 1:50 Mouse IgG1
|
| 97 |
+
Dystrophin Thermo RB-9024 1:100 Rabbit
|
| 98 |
+
Type IIa fibers DSHB SC-71 1:100 Mouse IgG1
|
| 99 |
+
Type I fibers DSHB BA-F8 1:100 Mouse IgG2b
|
| 100 |
+
Type IIb fibers DSHB BF-F3 1:100 Mouse IgM
|
| 101 |
+
Embryonic myosin heavy chain DSHB F1.652 1:50 Mouse IgG1
|
| 102 |
+
CD31 BioRad MCA2388 1:200 Rat
|
| 103 |
+
Dystrophin Abcam ab3149 (discontinued) 1:100 Mouse IgG1
|
| 104 |
+
Perilipin Cell Signaling Technologies 9349S 1:200 Rabbit
|
| 105 |
+
PDGFRα Cell Signaling Technologies 3174S 1:800 Rabbit
|
| 106 |
+
Myogenin DSHB F5D 1:50 Mouse IgG1
|
| 107 |
+
Myosin heavy chain DSHB A4.1025 1:200 Mouse IgG2a
|
| 108 |
+
|
| 109 |
+
2.5. Hematoxylin and eosin staining
|
| 110 |
+
|
| 111 |
+
Sections were brought to room temperature, then fixed for 10 min in 10% Neutral Buffered Formalin (NBF). The slides were washed with distilled water followed by staining of nuclei with Meyer’s hematoxylin for 4 min. Slides were rinsed under running tap water for 10 min and then differentiated with 0.3% acid-alcohol. An additional rinse with tap water and Scott’s tap water substitute was used to further enhance coloration of the nuclei. Samples were then briefly incubated in 90% ethanol (EtOH) and then stained with alcoholic eosin for 30 s. Slides were then dehydrated in 100% EtOH followed by 2 rinses in xylene or xylene substitute for 2 min each before mounting with Cytoseal resin-based mounting medium. The slides were then allowed to cure overnight prior to imaging.
|
| 112 |
+
|
| 113 |
+
2.6. Muscle contractile measurements
|
| 114 |
+
|
| 115 |
+
Contractile muscle force was measured as described previously (31). Briefly, single EDL muscles were isolated and ligated with a 5–0 silk suture at each tendon and maintained in a physiological saline solution (pH 7.6) containing 119 mM NaCl, 5 mM KCl, 1 mM MgSO4, 5 mM NaHCO3, 1.25 mM CaCl2, 1 mM KH2PO4, 10 mM HEPES, and 10 mM dextrose at 30°C under aeration with 95% O2/5% CO2 throughout the experiment. Muscles were mounted in a bath within the force transducer (Aurora 300B-LR) operated in isometric mode. A 5-min equilibration was performed, during which single twitches were elicited every 30 s with 0.5 msec electrical pulses. Isometric tension was evaluated by 250 msec trains of pulses delivered at 10, 20, 40, 60, 80, 100 and 120 Hz. After the experimental protocol, muscle length was determined with a digital caliper and muscle mass was measured after removing liquid. The cross-sectional area for each muscle was measured, and muscle density was determined as the muscle mass (g) divided by the product of its length (Lo, mm) and cross-sectional area (mm2), expressed in g/mm3. Muscle output was then expressed as isometric tension (N/cm2) determined by dividing the developed tension (N) by the muscle cross-sectional area. In the case of atrophied muscle, absolute tension was used as the measure of force because the cross-sectional muscle area is no longer a reliable measure due to change in muscle density.
|
| 116 |
+
|
| 117 |
+
2.7. Oil red O staining
|
| 118 |
+
|
| 119 |
+
Tissue sections were fixed in 10% NBF for 4 min and briefly washed under running tap water for 1 to 10 min. After rinsing with 60% isopropanol, samples were stained with freshly prepared and filtered oil red O working solution (Oil Red O powder [Sigma] in 60% isopropanol) for 15 min, then rinsed again with 60% isopropanol. The samples were then lightly stained with Meyer’s hematoxylin and rinsed with distilled water. Slides were mounted in aqueous glycerine jelly and imaged within 2 h.
|
| 120 |
+
|
| 121 |
+
2.8. BODIPY staining
|
| 122 |
+
|
| 123 |
+
Frozen sections were fixed with 4% PFA in PBS for 10 min followed by 2 washes with PBST for 5 min each. The slides were then incubated for 60 min with 1 μg/ml BODIPY 493/503 (Invitrogen D3922) in PBST. Following incubation, the slides were washed twice with PBST for 5 min each, then twice with PBS for 5 min each. Slides were finally mounted with Prolong Diamond Antifade Mountant with DAPI (Invitrogen P36962) and imaged immediately.
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2.9. MicroCT/DiceCT
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EDLs were isolated from hindlimbs of mice and fixed immediately in 10% NBF solution overnight. Muscles were then stained using the diceCT protocol, as described previously (32). Briefly, muscles were incubated in Lugol’s Iodine for 2 nights. The muscles were then scanned in a fixed container at low power in a Nikon XTH 225 ST microCT scanner at a 10-μm or 14-μm resolution. Images were then reconstructed using Nikon automated reconstruction software and analyzed using Avizo to delineate soft tissue densities in false colors.
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2.10. Batimastat treatment
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Pax7-CreERT2; ROSA26DTA mice were all given tamoxifen (75 mg/kg body weight) via i.p. injection for 5 days prior to surgery. 1 day prior to surgery, half the mice were given batimastat (30 mg/kg body weight) as a 3 mg/ml suspension in sterile-filtered PBS with 0.01% Tween-80 via i.p. injection, and the other half were injected with vehicle only. Batimastat injections were given daily until muscle was isolated. Following surgery, the mice were switched to a tamoxifen diet and the muscle was harvested 7 days post-operatively.
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2.11. Fast Green/Sirius Red staining
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Samples were placed in 0.04% Fast Green (Sigma) for 15 min then washed with distilled water. Sections were then incubated in 0.1% Fast Green and 0.04% Sirius Red (Sigma) in saturated picric acid for 30 min. Samples were dehydrated through serial 70, 90, and 100% Ethanol washes and cleared in xylene for 2 min before mounting using Cytoseal mounting medium. Positive and negative controls were run simultaneously to validate the specificity of this assay for collagen.
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2.12. Myoblast isolation
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Hindlimb muscles from mice were dissected, rinsed briefly in sterile PBS, and placed in a 10-cm dish containing DMEM +1% penicillin/streptomycin (pen/strep). Thereafter, all steps were performed in a biosafety cabinet under sterile conditions. Muscles were cleaned of excess connective tissue and tendons and transferred to a new 10-cm dish containing 5 mL DMEM +1% pen/strep. The muscle was minced with razor blades for >10 min then transferred to a 50-ml centrifuge tube using a wide-bore pipet. Samples were centrifuged in a tabletop centrifuge for 2 min at 800× g. The medium was aspirated, cells were resuspended in 18 mL DMEM + pen/strep, and 2 ml pronase (1% solution) was added and the mixture was digested for 1 h at 37°C on a Nutator. The cells were then centrifuged for 3 min at 800 × g and the medium was aspirated. Muscle was then suspended in 10 mL DMEM +10% FBS + pen/strep and triturated 20 times to loosen cells. The supernatant was filtered through a Steriflip 100-μm vacuum filter and washed with 5 ml DMEM with 10% FBS + pen/strep. The cells were then centrifuged 5 min at 1,000× g and resuspended in 10 mL of growth medium (Ham’s F10 with 20% FBS + pen/strep) and plated on collagen-coated plates.
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2.13. In vitro myogenic and adipogenic differentiation
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Differentiation of isolated myoblasts was stimulated by plating the cells on entactin-collagen-laminin-coated plates in differentiation medium (DMEM supplemented with 2% horse serum, 1% pen/strep, 0.2% amphotericin B, and 0.01% human insulin/transferrin/selenium). Effects of hypoxia were determined by placing cells in a hypoxia chamber (Billups-Rothenberg) at 0% O2 (95% N2, 5% CO2). Control cells were maintained in normoxia (21% O2, 5% CO2). Medium was changed daily to ensure cell viability. Adipogenic differentiation was induced by incubating cells for 48 h in medium containing 10% FBS, 0.5 mM isobuylmethylxanthine, 125 nM indomethacin, 1 μM dexamethosone, 850 nM insulin, 1 nM T3 with or without 1 μM rosiglitazone. After 48 h, cells were switched to medium containing 10% FBS, 850 nM insulin, 1 nM T3, and 1 μM rosiglitazone. Cells were placed in either normoxic or hypoxic conditions as described above, and medium was changed every other day to ensure cell viability.
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2.14. Human skeletal muscle acquisition
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Critical limb threatening ischemia (CLTI) patients undergoing above-or below-knee amputations were consented according to an Institutional Review Board (IRB)-approved protocol to donate skeletal muscle tissue from the amputated limb. Muscle samples were collected under sterile conditions in the operating room from both the proximal and distal ends of the gastrocnemius muscle and oriented cross-sectionally in OCT and frozen on liquid nitrogen. The samples were then sectioned in a cryostat and stored at −80°C for subsequent analysis.
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2.15. Statistical analysis
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For each of the analyses, a script was used to blind the reviewer to either the images or the animal treatments to ensure no bias in the analysis. For a comparison of 2 groups, a two-way Student’s t-test was performed in GraphPad Prism, and statistical significance was established at p < 0.05. For multiple group comparisons, an ANOVA was first performed to determine whether an effect was present, followed by a t-test for multiple groups with a correction for multiple group testing in GraphPad Prism. Significance was once again established by a corrected p value <0.05.
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3. Results
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To study the role of Pax7+ MPCs in a mouse model of PAD, we crossed Pax7-CreERT2 mice to ROSA26DTA mice. To ablate satellite cells, we injected tamoxifen (Pax7Δ) or corn oil as a control (Pax7WT) for 5 days, followed by femoral artery ligation to induce HLI. Perfusion imaging demonstrated an identical injury and similar perfusion of the ischemic hind limb up to 28 days after HLI surgery in both groups (Supplementary Figure S1C). To maintain MPC ablation, mice were fed a diet supplemented with either corn oil or tamoxifen. To validate the model, muscle sections from the non-ischemic tibialis anterior (TA) muscle were stained for the satellite cell marker Pax7, and in the tamoxifen-treated mice there was a complete absence of satellite cells (Supplementary Figures S1A,B), demonstrating successful ablation of all satellite cells within skeletal muscle.
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3.1. Satellite cell ablation does not alter resting muscle morphology or physiology
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To examine whether satellite cell ablation resulted in changes in resting muscle, we isolated the TA muscle from the contralateral, non-ischemic limbs of Pax7Δ and Pax7WT mice after HLI and compared the skeletal muscle histologically by H&E staining. Muscle morphology and architecture appeared similar in Pax7Δ and Pax7WT mice (Figure 1A), although total cross-sectional area of the TA muscle was significantly reduced in Pax7Δ mice (4.48 ± 0.24 mm2 vs. 5.49 ± 0.07 mm2, p = 0.0043), possibly due to greater muscle hypertrophy in Pax7WT mice after disuse of the ischemic limb. Importantly, however, ex vivo force generation of extensor digitorum longus (EDL) muscle did not differ between Pax7Δ and Pax7WT mice (Figure 1B), demonstrating that absence of satellite cells does not alter resting muscle physiology. Lastly, we examined whether deletion of the endogenous skeletal muscle progenitor cell pool affects muscle fiber type distribution. Staining and quantification of both slow-twitch type 1 fibers, which are highly oxidative, and more glycolytic type IIa, IIb, and IId/x fibers (which are more abundant in TA muscle) demonstrated no differences between the groups, demonstrating that loss of Pax7+ MPCs does not cause a shift in myofiber metabolism at rest (Figures 1C,D).
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Figure 1 Pax7+ MPC ablation does not alter resting muscle morphology 1 week after ischemia. (A) H&E stains of skeletal muscle from mice with ablated satellite cells are not distinguishable from those with intact satellite cells (n = 3–4 per group). (B) EDL muscles from mice (n = 5 per group) were isolated, and their ability to generate force was measured on a force transducer. Ablation of satellite cells did not impair the ability of resting skeletal muscle to generate force. Data shown are means +/− SEM. (C) Representative immunostains of type I, IIa, and IIb myofibers in non-ischemic limbs of Pax7WT and Pax7Δ mice. (D) Quantification of relative percentages of each myofiber type in non-ischemic muscle of Pax7WT and Pax7Δ mice. Pax7+ MPC ablation did not alter non-ischemic resting muscle fiber type distribution 1 week after ischemia (n = 3–4 per group). Type IId/x myofibers were quantified by lack of staining for the other three markers. All data shown are means +/− SEM; p = ns for all comparisons. Scale bar = 100 μm.
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3.2. Satellite cell ablation in ischemic muscle results in complete absence of regeneration 1 week after ischemia
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To determine the effect of MPC ablation after ischemia, Pax7Δ and Pax7WT mice were subjected to unilateral HLI and examined 7 days later. Following ablation of satellite cells, markers of skeletal muscle regeneration (embryonic myosin heavy chain expression and centralized myonuclei) were absent in the ischemic limb of Pax7Δ mice (Figures 2A–C). To exclude the possibility that genetic ablation of MPCs with DTA had a non-specific effect on the vasculature, muscle sections were stained for the endothelial cell marker PECAM (CD31). Not only was the endothelium intact, but the total endothelial area relative to the muscle area was in fact increased in Pax7Δ mice (Figure 2D), suggesting a possible vascular compensation for the muscle loss. Satellite cell activation and proliferation normally occur after muscle injury in general and are observed after limb ischemia as well. 1 week after HLI, Pax7WT mice displayed a significant increase in the number of Pax7+ cells in ischemic TA muscle in contrast to the contralateral, non-ischemic limb, confirming normal satellite cell activation in this model (Figures 2E,F). As expected, this activation was absent in Pax7Δ mice lacking satellite cells, consistent with their inability to regenerate muscle following ischemic injury (Figures 2E,F).
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Figure 2 Ablation of Pax7+ MPCs in mice results in a complete lack of a muscle regenerative response 1 week after HLI. (A) Muscle regeneration was examined by staining for embryonic myosin heavy chain (eMHC, red) and endothelial cells (CD31, green), top, and for centralized myonuclei by H&E, bottom. (B–D) Quantification of centralized myonuclei (B) and eMHC (C) demonstrates a complete lack of regenerative response to ischemia. Quantification of CD31 area (D) demonstrates an increase in endothelial area relative to muscle area in Pax7Δ mice (n = 3–4 per group). (E,F) 1 week after HLI surgery, there was a significant increase in the number of Pax7+ cells per high power field in the ischemic TA of Pax7WT mice but not in muscle of Pax7Δ mice. Compared to resting muscle, there was a 10-15-fold increase in the number of Pax7+ cells in injured Pax7WT muscle, consistent with activation of satellite cells following injury (n = 3 per group). Scale bar = 100 μm. All data shown are means +/− SEM. **p < 0.01; ***p < 0.001, by 2-sided t-test.
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3.3. Chronic satellite cell ablation in ischemic muscle results in complete absence of regeneration 1 month after ischemia
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To investigate the effects of satellite cell ablation on long-term muscle recovery from ischemia, Pax7Δ and Pax7WT mice were subjected to HLI and followed for 14 and 30 days after surgery. Consistent with responses observed in parental C57BL/6 mice, ischemic Pax7WT mice displayed improved muscle architecture at day 14 post-HLI. Expression of eMHC had resolved by this time point, although there were still centralized myonuclei, and an inflammatory infiltrate was still present in the interstitial spaces between muscle fibers (Figure 3A). These features were further improved by day 30, with near compete resolution of inflammation (Figure 3B). In contrast, Pax7Δ mice displayed a persistent absence of muscle regeneration with an accompanying increase in cellularity characteristic of ongoing inflammation (Figures 3A,B). Strikingly, muscle of late stage ischemic Pax7Δ mice displayed a dramatic increase in adipose observed both histologically and by microCT (Figure 3A,B; Supplementary Figure S2), which was also evidenced grossly by the inability of whole muscle tissue to sink in aqueous solution (Supplementary Figure S2A). Whereas distinct, individual myofibers were visualized by microCT in control muscle (Supplementary Figure S2B), EDL muscle from Pax7Δ mice was markedly atrophied and displayed significant soft tissue adipogenic changes (Supplementary Figure S2B). These findings suggested that the chronic absence of satellite cells after ischemic injury resulted not only in a loss of muscle regeneration but also a shift in the cellular makeup of injured muscle. Persistent satellite cell ablation in Pax7Δ mice 30 days after HLI was verified by Pax7 immunostaining (Figures 3C,D). In the non-ischemic limb of Pax7WT mice, satellite cell numbers were similar to the day 7 timepoint, whereas satellite cell number diminished significantly in the ischemic limb by day 30 (~4/hpf compared to ~35/hpf on day 7 post-HLI) and was only slightly higher than in the non-ischemic limb at this stage (Figures 3C,D).
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Figure 3 Sustained deletion of satellite cells results in long-term prevention of muscle regeneration after HLI. (A,B) H&E staining and quantification of regenerating fibers, demonstrated by myofibers with centralized myonuclei, of the ischemic TA muscle at 14 days (A) and 30 days (B) after ischemia demonstrated a complete lack of regeneration (n = 3–4 per group). (C,D) 30 days after HLI Pax7+ cells per high power field were significantly increased (2-fold) in the ischemic relative to the non-ischemic TA muscle of Pax7WT mice, although their numbers were diminished compared to 7 days post-HLI. Pax7+ cells were persistently absent in Pax7Δ mice (n = 4 per group). Scale bar = 100 μm. All data shown are means +/− SEM. ***p < 0.001, ****p < 0.0001 by 2-sided t-test.
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3.4. Long-term satellite cell ablation in ischemic muscle results in impaired force generation
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Because long-term satellite cell ablation resulted in markedly abnormal muscle tissue morphology, we tested ex vivo muscle force generation to determine the functional effects of this injury. Force generation in Pax7Δ and Pax7WT mice correlated with histological findings, as there was a significant impairment in both maximal force generation and the time-tension force integral in EDL muscle of Pax7Δ mice compared to that of Pax7WT mice 30 days after ischemia (Figures 4A,B). In stark contrast, force generation in the non-ischemic EDL mirrored that observed on day 7 post-HLI (Figures 4C,D), confirming that resting skeletal muscle is unaffected by satellite cell ablation even after 30 days.
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Figure 4 Pax7+ MPC ablation impairs force generation 30 days after HLI. (A) The maximum force generated by the ischemic EDL muscle was significantly lower (p < 0.0001 by 2-way ANOVA) in Pax7Δ mice. (B) Maximum force was unchanged in the non-ischemic limb of Pax7Δ mice. (C,D) The time-tension integral, a measure of work done in a single contraction, of muscle 30 days after HLI mirrored the maximum force data in both ischemic (C) and non-ischemic TA muscle (D) (n = 4–5 per group).
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3.5. Ablation of Pax7+ MPCs in mice results in marked fat infiltration of skeletal muscle following ischemia
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A key feature of muscle injury is that different modes of injury can result in varying regenerative responses. For example, unlike cardiotoxin-mediated injury, glycerol injection induces a more adipogenic change to the muscle (22). In contrast, the mdx mouse, a genetic model of muscular dystrophy, fails to accurately recapitulate many of the adipogenic changes observed in patients with muscular dystrophy. The lipid deposition seen in Pax7Δ mice 30 days after HLI is reminiscent not only of that of patients with muscular dystrophy but also of patients with CLTI (33). To investigate the adipogenic changes that occur in skeletal muscle following ischemic injury, we used two different complementary lipid stains, oil red O and BODIPY 493/503, to examine fatty changes 7 days after HLI. Oil red O staining showed a small amount of fat deposition in the control Pax7WT TA muscle, which was significantly increased in Pax7Δ muscle (Figure 5A), and these findings were mirrored by the BODIPY staining (data not shown). The increased fat deposition in Pax7Δ muscle after long-term injury resulted in the need to cut thicker tissue (~30 μm) sections, which also resulted in what appeared to be increased non-specific oil red O (Figure 5A) and BODIPY staining (data not shown). To overcome this issue, we immunostained for perilipin, which is selectively localized to the periphery of lipid droplets and thus specifically marks adipose accumulation. Perilipin staining also revealed a significant increase in adipogenesis in Pax7Δ TA muscle compared to that of Pax7WT mice at 7 and 14 days post-HLI (Figures 5A,B), and this difference persisted out to day 30 post-HLI (Figure 5C). These findings demonstrate that the lack of Pax7+ MPCs results in aberrant lipid accumulation, which may contribute to the pathogenesis of PAD.
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Figure 5 Ablation of Pax7+ MPCs in mice results in marked fat infiltration within skeletal muscle following ischemia. (A) Oil red O (top) and Perilipin (bottom) staining of the ischemic TA muscle demonstrated significantly increased lipid staining in Pax7Δ mice compared to Pax7WT 7 days after HLI surgery (n = 3–4 per group). (B,C) Perilipin staining and quantification of adipose in the ischemic TA muscle 14 days (B) and 30 days (C) after HLI surgery demonstrated increased lipid staining in Pax7Δ mice compared to Pax7WT (n = 3–4 per group). Scale bars = 1 mm. All data shown are means +/-SEM. * represents p < 0.05, **p < 0.01; ***p < 0.001 by 2-sided t-test.
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3.6. Fibro/adipogenic progenitors are significantly increased in Pax7Δ mice after ischemia
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To begin to elucidate the origins of the adipogenic changes observed after ischemia in Pax7Δ mice, we explored the potential contribution of fibro/adipogenic progenitor cells (FAPs) to the phenotype. FAPs have been shown to induce adipogenic changes in skeletal muscle in limb girdle muscular dystrophy type II (33) and in other pathological conditions (22). Additionally, FAPs have been shown to drive adipogenic changes in a variety of metabolic and cardiovascular disorders (26, 27, 34). Staining ischemic muscle from Pax7Δ and Pax7WT mice for the FAP marker PDGFRα (35–37) demonstrated a significant increase in FAPs in Pax7Δ mice that progressively increased over time after ischemia (Figures 6A–C), consistent with the observed temporal increase in adipogenesis (Figure 5). In contrast, PDGFRα+ area was unchanged in Pax7WT muscle at all timepoints after ischemia. These findings suggest that increased ischemic skeletal muscle adipogenesis following MPC ablation is driven by FAPs.
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Figure 6 Ablation of Pax7+ MPCs in mice results in a significant increase in FAPs in skeletal muscle following ischemia. (A-C) PDGFRα staining of the ischemic TA muscle demonstrated significantly increased FAP staining in Pax7Δ mice compared to Pax7WT 7 days (A), 14 days (B), and 30 days (C) after HLI surgery (n = 3–5 per group). Scale bars = 1 mm. All data shown are means +/-SEM. *p < 0.05; **p < 0.01; ***p < 0.001 by 2-sided t-test.
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3.7. Batimastat, an FAP inhibitor, limits adipogenesis and promotes fibrosis after ischemia in the absence of satellite cells
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Batimastat is a non-specific MMP inhibitor that has been shown to prevent adipogenesis both in isolated FAP cells in vitro and in skeletal muscle in vivo (22, 33). We reasoned that if FAPs contribute to adipogenesis after HLI in the absence of satellite cells, then treating ischemic mice with batimastat should limit the amount of lipid deposition. Indeed, treatment of Pax7Δ mice with batimastat during recovery from HLI resulted in a significant decrease in oil red O+ and perilipin+ area compared to that observed in vehicle-treated Pax7Δ mice (Figure 7A). Notably, this change was accompanied by a corresponding increase in fibrosis (Figure 7B). Despite this clear difference in phenotype, batimastat did not alter the number of FAPs, as indicated by the lack of a difference in PDGFRα staining (Supplementary Figure S3), consistent with previous reports (33). Collectively, these findings suggest that in the absence of satellite cells, ischemia drives FAPs to promote adipogenesis, which may play an important role in the pathophysiology of PAD.
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Figure 7 Inhibiting FAPs with batimastat reduces adipogenesis and increases fibrosis after HLI in the absence of satellite cells. (A) Batimastat treatment significantly decreased total fat in Pax7Δ ischemic TA muscle as determined by oil red O and perilipin staining 7 days after HLI surgery. (B) Fast Green/Sirius Red staining demonstrated a corresponding significant increase in collagen content in Pax7Δ ischemic TA muscle, consistent with a switch from adipogenesis to fibrosis after inhibition of FAPs (n = 4–6 per group). Scale bars = 100 μm. All data shown are normalized means +/− SEM. **p < 0.01; ***p < 0.001 by 2-sided t-test.
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3.8. Isolation and differentiation of myoblasts following satellite cell ablation in vivo results in defective myogenesis and increased adipogenesis in vitro
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It is well known that myoblasts isolated from whole muscle tissue retain their ability to differentiate and fuse into mature skeletal myotubes in vitro. Pax7+ satellite cells comprise a small percentage (<10%) of the mononuclear cells isolated from muscle tissue that have the potential to differentiate into muscle (i.e., MPCs). Once MPCs are isolated and plated in vitro, satellite cells rapidly lose expression of Pax7 and differentiate into MyoD-expressing committed myoblasts (38). Prior studies have demonstrated that deletion of Pax7+ satellite cells in vitro, after plating, does not impair myoblast differentiation (39). To our knowledge, however, no studies have examined the effect of in vivo ablation of Pax7+ cells on subsequent myoblast differentiation in vitro and whether this might influence isolated myoblasts to differentiate toward an adipogenic lineage. To test this, mice were treated with either tamoxifen or corn oil for 5 days to ablate Pax7+ cells in vivo, then muscle was harvested and mononuclear cells/myoblasts were isolated and plated in vitro. When cultured in muscle differentiation medium, only cells from Pax7WT mice were able to form mature myotubes, as evidenced by expression of the myogenic regulatory factor myogenin and myosin heavy chain (MHC) (Figure 8A). To determine whether MPCs isolated from Pax7WT or Pax7Δ mice have an increased propensity to differentiate into adipocytes, cells were plated in adipogenic medium. Because increased adipogenesis in Pax7Δ mice was observed in vivo in the setting of ischemia, cells were incubated for 12 days under hypoxic conditions to simulate ischemia. Compared to cells from Pax7WT mice, cells isolated from Pax7Δ mice had an increased propensity to form adipocytes, as demonstrated by oil red O staining (Figure 8B). These findings suggest that in the absence of Pax7+ cells, Pax7− cells with the potential to fuse and differentiate into muscle are driven toward an adipocyte lineage, although it is unclear whether these cells are FAPs or if they are derived from some other progenitor cell population.
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Figure 8 Myoblasts isolated from Pax7-depleted muscle fail to differentiate under hypoxic conditions and display increased adipogenesis. (A) Pax7WT myoblasts in differentiation medium expressed myosin heavy chain (MHC) under hypoxia whereas Pax7Δ cells failed to fuse and did not express the early differentiation marker myogenin or MHC. (B) When grown in adipogenic medium, Pax7Δ myoblasts had a higher propensity to form oil red O+ lipid droplets. Similar results were observed in three independent experiments. Scale bars = 100 μm.
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3.9. Critical limb ischemia patients have increased adipogenesis and fewer satellite cells in regions of greater ischemia
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To examine whether the adipogenic changes observed in our preclinical model are also seen clinically, we obtained skeletal muscle tissue from CLTI patients undergoing limb amputation. In this setting, tissue that is farthest from the amputation site (distal) is typically the most ischemic, whereas proximal tissue, closer to the amputation site is less ischemic and often relatively healthy. Paired proximal and distal gastrocnemius muscle samples were obtained from 10 CLTI patients undergoing amputation, and adipose area was determined by perilipin staining. Distal, more ischemic muscle displayed significantly greater adipose area (Figure 9A). Because the increase in adipogenic area in our preclinical model was caused by the ablation of satellite cells prior to ischemia, we investigated whether the increased adipogenesis in the regions of greater ischemia corresponded with a loss or reduction in the number of Pax7+ cells. Immunostaining for Pax7 was performed on paired proximal and distal skeletal muscle sections from each subject. Although Pax7+ cells were still present in all subjects’ distal muscle, we observed significantly fewer Pax7+ cells in distal vs. proximal tissue (Figure 9B). These findings support the possibility that chronic limb ischemia results in loss of satellite cell number and/or satellite cell dysfunction, which leads to increased skeletal muscle adipogenesis and may contribute to the pathogenesis of PAD in general and CLTI in particular.
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Figure 9 CLTI patients have increased adipogenesis in more ischemic muscle regions that correspond with decreased Pax7+ cell numbers. (A) Perilipin staining in the gastrocnemius muscle of CLTI patients (n = 10) revealed significantly greater fat deposition in more distal ischemic regions. Scale bar = 1 mm (B) More ischemic distal regions of the same patients in panel (A) had significantly fewer Pax7+ cells. Scale bar = 100 μm. All data shown are paired values from the same patient. **p < 0.01 by a 2-sided ratio paired t-test.
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4. Discussion
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Although surgical and endovascular approaches to revascularization represent the primary strategy to treat PAD, outcomes remain poor, particularly in CLTI, which results in high rates of subsequent amputation (40, 41). Moreover, while experimental pro-angiogenic approaches to improve limb perfusion have shown great promise in preclinical models of hindlimb ischemia, they have proven suboptimal in clinical experience (42, 43). We hypothesized that these poor outcomes might be explained, at least in part, by non-vascular etiologies of CLTI. Our prior results supported this hypothesis by demonstrating that skeletal muscle cell responses to ischemia are independent of blood supply and are strongly influenced by genetic background. However, the role of skeletal muscle regeneration in the response to ischemia and, in particular, the role of muscle progenitor cells in this process, remained unknown. Here, we have demonstrated an absolute requirement for Pax7+ skeletal muscle satellite cells in muscle regeneration following ischemic injury. Furthermore, by continuously feeding mice a tamoxifen-containing diet over 30 days post-HLI, we ensured that there was no repopulation of the satellite cell pool (39), and we demonstrated that the regenerative response to ischemia was entirely muscle-dependent. Although one prior study raised the possibility that, following a critical juvenile period, satellite cells were dispensable for regeneration in the postnatal phase, our results are consistent with studies that demonstrate an absolute requirement for satellite cells during regeneration (44, 45), in our case following ischemia-induced muscle injury. Our data demonstrate that complete recovery from ischemia follows a similar time course as skeletal muscle injuries that are cytotoxic and cryogenic in nature (21, 23).
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Staining for endothelial cells in mice lacking satellite cells verified that vascular cells were not targeted non-specifically by DTA after tamoxifen treatment and, therefore, that the observed injury was not likely due to loss of vascular supply. Somewhat surprisingly, we found that capillary density was in fact increased in Pax7Δ mice. Although the mechanisms responsible for this effect are not clear, it is possible that capillary proliferation occurred as a compensatory response to the increased tissue destruction (46). One caveat in interpreting this result is that decreased muscle area due to atrophy could have falsely increased apparent vascular density. Future studies will be necessary to fully elucidate the nature of the endothelial response during this process, including examination of endothelial cell proliferation, angiogenesis, and collateralization, which are known to occur in the setting of hindlimb ischemia (47).
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Using several complementary approaches (oil red O, BODIPY, perilipin), we demonstrated the novel and important finding that in the absence of Pax7+ satellite cells, ischemia induces marked lipid deposition within skeletal muscle. This observation distinguishes the injury in this model from that seen in murine models of muscular dystrophy and cardiotoxin injury, which lack similar adipogenesis. Although the mdx mouse model lacks the extreme fat deposition that is observed in DMD patients (29), a “humanized” mdx model with shortened telomeres and mitochondrial defects did show greater adipogenic changes (48). These lipid deposits are presumed to be pathogenic, because many skeletal muscle diseases are characterized by increased adipogenesis (49). Notably, the adipose deposition observed after complete loss of satellite cells in Pax7Δ mice recapitulated findings seen in muscle tissue samples of CLTI patients, who displayed increased adipogenesis in more ischemic, distal regions of the amputated limb. The mice used in this study were on a C57BL/6 background, a strain in which the skeletal muscle is known to be relatively resistant to ischemic injury (10). Strikingly, the absence of satellite cells completely abrogated the protective effect conferred by C57BL/6 genetic factors, suggesting that satellite cell loss or dysfunction contributes to the CLTI phenotype. Consistent with this observation, we found that more ischemic distal regions of CLTI muscle had significantly fewer Pax7+ satellite cells. It is important to note that the mouse phenotype was induced by the complete ablation of satellite cells after tamoxifen treatment, although it is unclear whether partial loss of Pax7+ cells would result in a similar phenotype. Although satellite cells were still present in more ischemic regions of CLTI tissue, it is possible that they were dysfunctional and unable to contribute to regeneration. Satellite cell dysfunction may not manifest as a decrease in absolute number, but there may instead be epigenetic, post-transcriptional, and/or post-translational alterations that affect satellite cells’ ability to effectively promote regeneration in CLTI patients. Alternatively, the reduction in Pax7+ cell number with ischemia in CLTI may result from a loss due to satellite cell exhaustion reminiscent of phenotypes seen in DMD patients. Future experiments will be necessary to elucidate the exact role that satellite cells play in the pathogenesis of PAD. Gene expression profiling of satellite cells in PAD patients with claudication or CLTI may identify a specific genetic signature that defines the pathophysiology of satellite cells in these conditions. The observed correlation between preclinical and clinical adipose deposition in the setting of limb ischemia supports the biological and clinical relevance of these findings.
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FAPs have been shown to play a role in obesity-associated skeletal muscle dysfunction as well as in denervated skeletal muscle (34, 50). We hypothesized that FAPs were responsible for the increased adipogenesis after ischemia in Pax7Δ mice. To explore this possibility, we treated ischemic Pax7Δ mice with batimastat, a small molecule inhibitor of fibroblast activation protein, a dual specificity serine protease. Batimastat has been shown to inhibit adipogenesis resulting from FAP cell differentiation into adipocytes in both isolated FAPs in culture and skeletal muscle in vivo in a model of limb girdle muscular dystrophy (33). Indeed, we observed a decrease in the degree of adiposity after batimastat treatment, and this was accompanied by a corresponding increase in fibrosis, supporting the possibility that FAP differentiation into adipocytes was responsible for the observed ischemic lipid deposition. Future studies, such as lineage tracing using an FAP marker like PDGFRα (25), will be necessary to conclusively determine whether FAPs or other progenitor cell types contribute to this fat infiltration. Definitively establishing that FAPs are responsible for the increased skeletal muscle adiposity in the setting of ischemia would likely require a genetic approach, such as ablation of PDGFRα+ FAPs. However, ablation of both Pax7+ cells and PDGFRα+ cells would likely have complex effects that may be difficult to interpret.
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Several important questions arise regarding the mechanisms responsible for both the adipogenesis and the switch to a fibrotic phenotype after batimastat treatment. First, what are the paracrine signaling pathways between satellite cells and other muscle progenitor cells, including FAPs, that drive normal myogenesis? Pax7+ cells account for a small percentage of total cells in muscle tissue, yet in typical muscle cell isolates, a number of mononuclear cell types have the capacity to fuse and differentiate into myotubes in vitro, suggesting that the presence of satellite cells confers on other MPCs (e.g., myoblasts, pericytes, FAPs) the ability to differentiate into functional muscle. This likely involves paracrine signaling mechanisms that remain to be fully elucidated, although PDGF-BB and DLL4 have been implicated in driving pericytes toward a myogenic lineage (51). Second, what are the mechanisms that drive the increased adipogenesis in the absence of satellite cells? Does a suppressive signal from satellite cells to FAPs normally prevent adipogenesis, or does the absence of satellite cells activate another pathway to drive adipogenesis? Third, and equally important, does ischemia contribute to these processes, since adipogenesis does not occur in the non-ischemic limb, or are these pathways driven by aberrant regeneration? Future studies will be necessary to elucidate these mechanisms, and it is hoped that such information would lead to the eventual development of therapies for diseases of aberrant muscle stem cell number and/or function, such as CLTI and DMD. Batimastat provides a potential starting point for development of drugs to inhibit adipogenic changes in skeletal muscle. Although an increase in fibrosis in CLTI in place of adipose tissue may not translate into optimal clinical outcomes, it provides an initial strategy to redirect aberrant MPC differentiation and possibly prevent pathological adipogenesis.
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Data availability statement
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The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
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Ethics statement
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The studies involving human participants were reviewed and approved by Duke University Institutional Review Board. The patients/participants provided their written informed consent to participate in this study. The animal study was reviewed and approved by Duke University Institutional Animal Care and Use Committee.
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Author contributions
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HA and CK designed the research study. HA conducted all in vivo and in vitro experiments and performed data analysis. LO, BG, and KS isolated human skeletal muscle and assisted in human muscle staining and experiments. MP performed animal husbandry, genotyping and HLI surgeries. TM performed histological data analysis and assisted with editing the manuscript. CS and JM conducted muscle force generation experiments. HA wrote the manuscript, and CK co-wrote and edited the manuscript. All authors contributed to the article and approved the submitted version.
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Funding
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This study was supported in part by NIH grants HL124444, HL118661, and HL156009 to CK, HL125695 to JM, and by a grant from the Duke University School of Medicine to CK for microCT studies through the Shared Materials Instrumentation Facility. BG was supported by grant F32 HL136125 from the NIH. KS was supported in part by a KL2 award through the Duke Clinical and Translational Science Award TR002553 from the NIH. LO was the recipient of a Eugene A. Stead Student Research Scholarship and a Poindexter Scholars in Basic Sciences Award from the Duke University School of Medicine.
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Conflict of interest
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The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Publisher’s note
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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The authors wish to thank the Light Microscopy Core Facility at Duke University for the use of their microscopes and assistance in image acquisition; the Shared Materials Instrumentation Facility for the use of the microCT scanner and assistance in data acquisition and analysis; Mitchell Cox, Cynthia Shortell, Chandler Long, and the Division of Vascular Surgery in the Department of Surgery for their assistance in acquiring human skeletal muscle samples; and Jianbin Li for assistance with animal husbandry.
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Supplementary material
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The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcvm.2023.1118738/full#supplementary-material
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Click here for additional data file.
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==== Refs
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Antioxidants (Basel)
|
| 4 |
+
Antioxidants (Basel)
|
| 5 |
+
antioxidants
|
| 6 |
+
Antioxidants
|
| 7 |
+
2076-3921
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
10.3390/antiox12030542
|
| 11 |
+
antioxidants-12-00542
|
| 12 |
+
Article
|
| 13 |
+
Prenylcysteine Oxidase 1 Is a Key Regulator of Adipogenesis
|
| 14 |
+
https://orcid.org/0000-0003-3346-9879
|
| 15 |
+
Banfi Cristina 1*
|
| 16 |
+
https://orcid.org/0000-0002-7088-9074
|
| 17 |
+
Mallia Alice 12
|
| 18 |
+
Ghilardi Stefania 1
|
| 19 |
+
Brioschi Maura 1
|
| 20 |
+
https://orcid.org/0000-0003-2370-947X
|
| 21 |
+
Gianazza Erica 1
|
| 22 |
+
https://orcid.org/0000-0002-5507-6737
|
| 23 |
+
Eligini Sonia 1
|
| 24 |
+
https://orcid.org/0000-0001-6943-9618
|
| 25 |
+
Sahlén Pelin 3
|
| 26 |
+
https://orcid.org/0000-0001-7190-4638
|
| 27 |
+
Baetta Roberta 1
|
| 28 |
+
González-Domínguez Raúl Academic Editor
|
| 29 |
+
Gonzalez-Dominguez Alvaro Academic Editor
|
| 30 |
+
1 Centro Cardiologico Monzino IRCCS, Unit of Functional Proteomics, Metabolomics, and Network Analysis, 20138 Milan, Italy
|
| 31 |
+
2 Dipartimento di Biologia e Biotecnologie “Lazzaro Spallanzani”, Università di Pavia, 27100 Pavia, Italy
|
| 32 |
+
3 Science for Life Laboratory, KTH—Royal Institute of Technology, Tomtebodavägen 23A, 17165 Solna, Sweden
|
| 33 |
+
* Correspondence: cristina.banfi@cardiologicomonzino.it
|
| 34 |
+
21 2 2023
|
| 35 |
+
3 2023
|
| 36 |
+
12 3 54206 2 2023
|
| 37 |
+
18 2 2023
|
| 38 |
+
19 2 2023
|
| 39 |
+
© 2023 by the authors.
|
| 40 |
+
2023
|
| 41 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 42 |
+
The process of adipogenesis involves the differentiation of preadipocytes into mature adipocytes. Excessive adipogenesis promotes obesity, a condition that increasingly threatens global health and contributes to the rapid rise of obesity-related diseases. We have recently shown that prenylcysteine oxidase 1 (PCYOX1) is a regulator of atherosclerosis-disease mechanisms, which acts through mechanisms not exclusively related to its pro-oxidant activity. To address the role of PCYOX1 in the adipogenic process, we extended our previous observations confirming that Pcyox1−/−/Apoe−/− mice fed a high-fat diet for 8 or 12 weeks showed significantly lower body weight, when compared to Pcyox1+/+/Apoe−/− mice, due to an evident reduction in visceral adipose content. We herein assessed the role of PCYOX1 in adipogenesis. Here, we found that PCYOX1 is expressed in adipose tissue, and, independently from its pro-oxidant enzymatic activity, is critical for adipogenesis. Pcyox1 gene silencing completely prevented the differentiation of 3T3-L1 preadipocytes, by acting as an upstream regulator of several key players, such as FABP4, PPARγ, C/EBPα. Proteomic analysis, performed by quantitative label-free mass spectrometry, further strengthened the role of PCYOX1 in adipogenesis by expanding the list of its downstream targets. Finally, the absence of Pcyox1 reduces the inflammatory markers in adipose tissue. These findings render PCYOX1 a novel adipogenic factor with possible pathophysiological or therapeutic potential.
|
| 43 |
+
|
| 44 |
+
adipogenesis
|
| 45 |
+
prenylcysteine oxidase 1
|
| 46 |
+
adipose tissue
|
| 47 |
+
adipogenic factors
|
| 48 |
+
oxidation
|
| 49 |
+
Italian Ministry of Health, Italy, Ricerca Corrente 2021, Centro Cardiologico Monzino IRCCSThis work was supported by the Italian Ministry of Health, Italy, Ricerca Corrente 2021, Centro Cardiologico Monzino IRCCS.
|
| 50 |
+
==== Body
|
| 51 |
+
pmc1. Introduction
|
| 52 |
+
|
| 53 |
+
Adipose tissue plays an important role in energy homeostasis through its capacity to store energy, mobilize stored lipids for fuel, and secrete hormones and cytokines [1]. Cardiovascular diseases, type 2 diabetes, and metabolic syndrome are all associated with excess fat accumulation in white adipose tissue (WAT) [2]. Understanding the molecular events that regulate adipocyte differentiation is an essential step towards preventing obesity and metabolic diseases because adipocyte differentiation determines adipose tissue mass.
|
| 54 |
+
|
| 55 |
+
Adipocyte differentiation involves hormonal stimulators and the induction of a network of transcription factors that induce changes in gene expression and cell morphology. At the top of this transcriptional hierarchy are the basic region/leucine zipper proteins CCAAT-enhancer binding protein (C/EBP)δ, C/EBPβ, C/EBPα, and the nuclear receptor peroxisome proliferator-activated receptor (PPAR)γ [3]. These transcription factors are induced in a sequential and tightly regulated manner, and all are essential for normal adipogenesis. However, several important unanswered questions remain, and a more complete understanding of the developmental origin as well as the cellular and molecular components of adipose tissue is necessary to further illuminate how excess adiposity contributes to the onset and/or progression of metabolic disorders.
|
| 56 |
+
|
| 57 |
+
We have recently shown that prenylcysteine oxidase 1 (PCYOX1) deficiency in apolipoprotein E deficient mice (Apoe−/−) is associated with reduced body weight and adipose tissue deposits [4], but the role of PCYOX1 in adipogenesis has never been addressed since its discovery in 1997 by Casey’s group in studies related to the metabolism of prenylated proteins [5,6].
|
| 58 |
+
|
| 59 |
+
To substantiate the contribution of PCYOX1 in the adipogenic process, we investigated its role in vitro and in vivo, taking advantage of a complementary approach based on gene silencing and label-free quantitative proteomics.
|
| 60 |
+
|
| 61 |
+
Here we describe for the first time the role of PCYOX1 as a novel regulator of adipogenesis. Employing proteomics and gene expression analysis in Pcyox1 silenced cells, we show that it acts upstream of the key factors that control the adipogenic process, while the in vivo absence of the Pcyox1 gene in mice is associated with reduced adipose deposits, and related adipose tissue inflammation. Overall, these data identify PCYOX1 as a master regulator and potential therapeutic target in obesity-related diseases.
|
| 62 |
+
|
| 63 |
+
2. Materials and Methods
|
| 64 |
+
|
| 65 |
+
2.1. Cell Culture and Induction of Differentiation
|
| 66 |
+
|
| 67 |
+
3T3-L1 preadipocytes (American Type Culture Collection, Manassas, VA, USA) were maintained in Dulbecco’s Modified Eagle Medium (DMEM) (Gibco; Thermo Fisher Scientific, Milan, Italy) with 4500 mg/L glucose supplemented with 10% fetal bovine serum (EuroClone, Milan, Italy). To induce differentiation, 2 days after reaching confluence (day 0), cells were exposed to a cocktail of 0.5 mmol/L 3-isobutyl-1-methyl-xanthine (Sigma-Aldrich, Milan, Italy), 0.25 µmol/L dexamethasone (Sigma-Aldrich, Milan, Italy) and 1 µg/mL insulin (Sigma-Aldrich, Milan, Italy) for 48 h, followed by exposure to insulin 1 µg/mL alone for additional 3 days. After this period, the medium was replaced every 2 days with DMEM containing 10% fetal bovine serum until the ninth day.
|
| 68 |
+
|
| 69 |
+
2.2. PCYOX1 Overexpression in CHO Cells
|
| 70 |
+
|
| 71 |
+
CHO cells overexpressing PCYOX1 were generated as previously described [4]. Briefly, an empty pcDNA5/FRT vector and a custom pcDNA5/FRT:PCYOX1 (Invitrogen; Thermo Fisher Scientific, Milan, Italy) were transfected into Flp-In-CHO cells (R758-07, Invitrogen; Thermo Fisher Scientific, Milan, Italy) using a pOG44 expression vector (V6005-20, Invitrogen; Thermo Fisher Scientific, Milan, Italy). The selection of PCYOX1-expressing clones was performed according to the Flip-In System protocol (K6010-01, Invitrogen; Thermo Fisher Scientific, Milan, Italy).
|
| 72 |
+
|
| 73 |
+
2.3. Stable Transfection with Short Hairpin RNA (shRNA)
|
| 74 |
+
|
| 75 |
+
Stable gene silencing of Pcyox1 and Cebpb in 3T3-L1 cells was achieved using shRNA plasmids (Santa Cruz Biotechnology, Dallas, TX, USA), a pool of 3 target-specific lentiviral vector plasmids each encoding 19–25 nt (plus hairpin) shRNAs designed to knock down Pcyox1 and Cebpb gene expression. A shRNA plasmid encoding a scrambled shRNA sequence that does not induce the degradation of any cellular message was taken as negative control (control cells, shNEG). Cells at 50–70% confluency were transfected for 24 h with a multiplicity of infection (MOI) of 5 for Pcyox1 shRNA and 7.5 for Cebpb shRNA lentiviral particles, and 5 µg/mL of Polybrene (Santa Cruz Biotechnology, Dallas, TX, USA) for each well of a 12 well/plate and cultured in complete medium containing 2 µg/mL puromycin to allow selection.
|
| 76 |
+
|
| 77 |
+
2.4. Oil Red O Staining
|
| 78 |
+
|
| 79 |
+
Cells were washed with phosphate-buffered saline (PBS) and fixed with formalin (4%) for 1 h. After washing with water, cells were treated with 60% isopropanol for 5 min, and then stained with Oil Red O working solution prepared according to the manufacturer’s instructions (Sigma-Aldrich, Milan, Italy).
|
| 80 |
+
|
| 81 |
+
2.5. Real-Time Quantitative Reverse Transcriptase PCR (qRT-PCR)
|
| 82 |
+
|
| 83 |
+
Cells were harvested in the lysis buffer, and RNA was extracted with the Total RNA Purification Kit (Norgen Biotek Corp., Thorold, ON, Canada). Adipose tissues were homogenized by means of TissueLyser II (QIAGEN, Milan, Italy) before RNA extraction with the Fatty Tissue RNA Purification Kit (Norgen Biotek Corp., Thorold, Ontario, Canada) and reverse transcribed (1 μg) as described [7]. The quality of cellular and tissue RNA was checked by the Agilent 2100 Bioanalyzer system (Agilent Technologies, Santa Clara, CA, USA). Real-time qRT-PCR was performed in triplicate with 2.5 μL of cDNA incubated in 22.5 μL IQ Supermix containing primers and SYBRGreen fluorescence dye (Bio-Rad Laboratories, Milan, Italy) using the iCycler Optical System (Bio-Rad Laboratories, Milan, Italy) with an initial denaturation for 3.3 min at 95 °C, followed by 50 cycles of amplification (15 s at 95 °C and 60 °C for 1 min), and by melting curve. The sequences of the primers used are listed in Supplementary Table S1. The other specific primers were purchased from QIAGEN (Milan, Italy): Pcyox1, Pparg, Fabp4, Cebpa, Cebpb, Lipe, Car3, Plin1, Agpat2, Ces1f, Gpd1, Emr1, Itgam, Itgax, Lgals3, and Saa3, and summarized in Table S2. Expression levels were calculated by Ct values normalized to the housekeeping 18s rRNA or Gapdh genes using the 2−ΔΔCT data analysis method. Pcyox1 amplicons (120 bp) were analysed by electrophoresis in agarose gel 2% w/v containing GelRed (Biotium, Fremont, CA, USA) and visualized with Gel doc (Bio-Rad Laboratories, Milan, Italy).
|
| 84 |
+
|
| 85 |
+
2.6. Oxidized Low Density Lipoprotein (oxLDL) Assay
|
| 86 |
+
|
| 87 |
+
The quantitation of oxLDL in the cell culture medium was performed by a quantitative immunoenzymatic assay according to the manufacturer’s instructions (MyBioSource, Inc., San Diego, CA, USA). Briefly, shNEG and shPcyox1 silenced cells were induced to differentiate for 9 days. After this period, medium was collected and oxLDL levels were measured.
|
| 88 |
+
|
| 89 |
+
2.7. PCOYX1 Activity Assay
|
| 90 |
+
|
| 91 |
+
PCYOX1 activity was assessed as previously described [4]. Briefly, H2O2 produced in cells by the PCYOX1 reaction was measured using the Amplex Red Kit (Life Technologies, Milan, Italy). In the presence of peroxidase, the Amplex Red reagent is converted by H2O2 into the red-fluorescent oxidation product resorufin. The resorufin produced was measured following the fluorescence emission in a microplate reader Infinite 200 (TECAN, Mannedorf, Switzerland), equipped for excitation at 530 nm and fluorescence emission detection at 590 nm. Results are expressed as picomoles of H2O2 /µg protein.
|
| 92 |
+
|
| 93 |
+
2.8. Label-Free Mass Spectrometry (LC-MSE) Analysis
|
| 94 |
+
|
| 95 |
+
Cell pellets were dissolved in 25 mmol/L NH4HCO3 containing 0.1% RapiGest (Waters Corporation, Milford, MA, USA), sonicated, and centrifuged at 13,000× g for 10 min. After 15 min of incubation at 80 °C, proteins were reduced with 5 mmol/L dithiothreitol (DTT) at 60 °C for 15 min, and carbamidomethylated with 10 mmol/L iodoacetamide for 30 min at room temperature in darkness. Digestion was performed with sequencing grade trypsin (Promega, Milan, Italy) (1 µg every 20 µg of proteins) overnight at 37 °C. After digestion, 2% trifluoroacetic acid (TFA) was added to hydrolyze RapiGest and inactivated trypsin. Tryptic peptides were used for label-free mass spectrometry analysis, LC-MSE, performed on a hybrid quadrupole-time of flight mass spectrometer (SYNAPT-XS, Waters Corporation, Milford, MA, USA) coupled with a UPLC Mclass system and equipped with a nano-source (Waters Corporation, Milford, MA, USA), as previously described [8,9]. Statistical analysis was performed by means of Progenesis QIP v 4.1 (Nonlinear Dynamics) using a Uniprot mouse protein sequence database (v2020). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [10] partner repository with the dataset identifier PXD039943 and 10.6019/PXD039943.
|
| 96 |
+
|
| 97 |
+
2.9. GO Analysis
|
| 98 |
+
|
| 99 |
+
The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING 10.5) database [11] was used to identify enriched Gene Ontology (GO) terms in the biological process, molecular function, or cellular component categories, as previously described [12]. The enrichment function of STRING, which calculates an enrichment p value based on a hypergeometric test using the method of Benjamini and Hochberg for correction of multiple testing (p value cut-off < 0.05), was used.
|
| 100 |
+
|
| 101 |
+
2.10. Mass Spectrometry-Based Quantification of PCYOX1
|
| 102 |
+
|
| 103 |
+
Tryptic peptides (0.5 μg/uL), obtained as described above, were added with the stable isotope labelled proteotipic PCYOX1 peptide (CPSIILHD(R) from Thermofisher Scientific (Milan, Italy), desalted with ZipTip C18 (Millipore, Burlington, MA, USA) according to the manufacturer’s instruction, and then dissolved in water with 0.1% formic acid before mass spectrometry analysis. Two microliters of each sample, containing 10 fmol/μL of labelled heavy peptide, were injected into a Xevo TQ-S micro triple quadrupole mass spectrometer coupled to a Waters ACQUITY ultra-performance liquid chromatography (UPLC) M-Class system through an ionKey source (Waters Corporation, Milford, MA, USA), and analysed as previously described [13].
|
| 104 |
+
|
| 105 |
+
2.11. Mice and Diets
|
| 106 |
+
|
| 107 |
+
Pcyox1−/− mice were bred with Apoe−/− mice (B6.129P2-Apoetm1Unc/J, stock 002052, JAX™ Mice Strain) as previously described [4]. Intercrosses of resulting Apoe−/−/Pcyox1+/− mice generated offspring that entered the study. All procedures were approved by the Institutional Animal Care and Ethics Committee of the University of Milan and by the Ministry of Health DGSAF (N. 782-2020; approval 10 August 2020). Mice were housed in an air-conditioned room at 22 ± 0.5 °C with a 12-h lighting cycle and free access to food and water. For experiments, double knockout mice (Pcyox1−/−/Apoe−/−) and control mice (Pcyox1+/+/Apoe−/−) were fed ad libitum with a high fat diet (HFD) containing 0.2% cholesterol, 21.2% fat (42% kcal), and 17.5% protein by weight (Teklad diet TD.88137; Envigo, Milan, Italy), starting at 11 weeks of age and continuing for 8 or 12 weeks. After the indicated period of HFD, mice were anesthetized by intraperitoneal injection of ketamine hydrochloride (75 mg/kg) and medetomidine (1 mg/kg) prior to visceral fat harvest. Abdominal visceral adipose tissue (VAT) was rapidly removed, weighed, and snap frozen for RNA and mass spectrometry analyses. Each experimental session included animals of both genotypes (Pcyox+/+/Apoe−/− n = 23; Pcyox−/−/Apoe−/− n = 19), with animals being assigned to the experimental groups according to genotype, and with the investigators blinded to group assignment during all experimental stages and when evaluating outcome measures.
|
| 108 |
+
|
| 109 |
+
2.12. Statistical Analysis
|
| 110 |
+
|
| 111 |
+
Data analysis was performed with GraphPad Prism 9.3 software (GraphPad Software Inc., San Diego, CA, USA). All data sets were tested for normality of distribution and analysed using the Student t test or analysis of variance (ANOVA) for multiple comparison followed by Dunnett’s or Tukey’s post hoc test as indicated. Statistical significance level was accepted at p < 0.05.
|
| 112 |
+
|
| 113 |
+
3. Results
|
| 114 |
+
|
| 115 |
+
3.1. Pcyox1−/− Mice Have Decreased Adiposity
|
| 116 |
+
|
| 117 |
+
Pcyox1−/−/Apoe−/− mice fed an HFD for 8 or 12 weeks showed 16.3% and 20.2% lower body weight, respectively, when compared to Pcyox1+/+/Apoe−/− mice (Figure 1A), due to a 40% and 52.5% reduction in visceral adipose content (Figure 1B), thus confirming preliminary observations [4]. Pcyox1 mRNA and protein, measured by quantitative mass spectrometry, were both present in the VAT of Pcyox1+/+/Apoe−/− mice fed an HFD for 8 weeks (Figure 1C,D). As previously demonstrated, serum analysis in Pcyox1−/−/Apoe−/− mice showed significantly decreased triglycerides, free fatty acid, and cholesterol concentrations, without any effects attributable to differences in food intake [4]. Overall, these data suggest that PCYOX1 may play a role in promoting in vivo adipogenesis. To address this, we explored the role of PCYOX1 in adipogenesis in in vitro differentiating cells.
|
| 118 |
+
|
| 119 |
+
3.2. PCYOX1 Expression Is Induced during Adipocyte Differentiation In Vitro
|
| 120 |
+
|
| 121 |
+
Pcyox1 mRNA expression is significantly increased when 3T3-L1 are fully differentiated to adipocyte-like cells after 9 days from the beginning of the differentiation protocol (Figure 2A). This occurs concomitantly with a rising expression of Pparg, a nuclear receptor critically involved in adipocyte differentiation, and Fabp4, a downstream target of PPARγ, which is a terminal marker of adipocyte differentiation (Figure 2B,C).
|
| 122 |
+
|
| 123 |
+
To explore the determinants of PCYOX1 induction during adipogenesis, we analysed the effects of the three components of the cocktail used to induce differentiation: insulin, dexamethasone (DEX), and the phosphodiesterase inhibitor 3-isobutyl-1-methylxanthine (IBMX). Insulin minimally perturbed Pcyox1 expression (Figure 3A), whereas IBMX and dexamethasone strongly increased Pcyox1 gene expression (Figure 3B,C). Because IBMX and DEX are each necessary for maximal and sustained expression of the pro-adipogenic transcription factor CCAAT/enhancer binding protein β (C/EBPβ) [14], we evaluate its mRNA modulation in the initial stages of differentiation (Figure 3D).
|
| 124 |
+
|
| 125 |
+
3.3. PCYOX1 Is Critical for Adipogenesis In Vitro
|
| 126 |
+
|
| 127 |
+
To examine the role of PCYOX1 in adipogenesis, short-hairpin shRNA retroviral constructs targeting three regions of the Pcyox1 mRNA were generated, and stably transfected into 3T3-L1 preadipocytes. The control and knockdown cell lines were then induced to differentiate for 9 days. Before the induction of differentiation, Pcyox1 mRNA levels were reduced in silenced cells (−92.8 ± 1.1% with respect to control cells, n = 5, p < 0.001), and remained significantly reduced until day 9 (−86.4 ± 2.5%, n = 8, p < 0.001 versus control cells). Similarly, treatment of 3T3-L1 cells with the Pcyox1 shRNA reduced endogenous PCYOX1 protein levels by 79.1 ± 6%, as assessed by mass spectrometry (n = 3; p < 0.0002). The shPcyox1-treated 3T3-L1 were also examined for their ability to differentiate into adipocytes compared to control cells. In response to adipogenic inducers, control cells underwent efficient morphological differentiation into lipid droplet-containing adipocytes. By contrast, Pcyox1-depleted 3T3-L1 preadipocytes accumulated fewer lipid droplets when induced to undergo differentiation (Figure 4A).
|
| 128 |
+
|
| 129 |
+
The mRNA expression of Fabp4, a terminal marker of adipogenesis (Figure 4B), was found to be significantly reduced in Pcyox1-silenced cells compared to control cells at the end of differentiation.
|
| 130 |
+
|
| 131 |
+
To identify the developmental stage regulated by PCYOX1, we harvested control and Pcyox1-depleted 3T3-L1 cells at 0, 1, and 9 days after the addition of adipogenic inducers in order to evaluate the expression of known transcriptional factors involved in adipogenesis. Pparg (Figure 4C) and Cebpa (Figure 4D) were significantly lower in Pcyox1-silenced cells compared to controls at day 9. Importantly, the earlier induction of Cebpb was unaffected by the loss of PCYOX1 in 3T3-L1 cells, being induced to the same extent in control and Pcyox1-silenced cells 24 h after the addition of the adipogenic cocktail (Figure 4E), suggesting that PCYOX1 acts downstream of C/EBPβ to promote the adipogenic program.
|
| 132 |
+
|
| 133 |
+
To assess whether C/EBPβ can directly regulate PCYOX1, we silenced cells for Cebpb. Although there was a significantly lower expression of Cebpb (−54 ± 6% in silenced cells with respect to control cells treated with a negative construct, n = 3, p < 0.002) and the known C/EBPβ downstream targets Pparg and Cebpa, Pcyox1 expression was unaffected (Figure 5).
|
| 134 |
+
|
| 135 |
+
3.4. The Effects of PCYOX1 in Adipogenesis Are Independent of Its Pro-Oxidant Activity
|
| 136 |
+
|
| 137 |
+
We previously demonstrated that PCYOX1 is able to generate H2O2, which in turn induces the formation of oxLDL [4], a known activator of PPARγ because a variety of oxLDL components act as PPARγ ligands [15]. Therefore, we assessed whether PCYOX1 could induce the formation of oxLDL during adipogenesis. First, we measured PCYOX1 activity in control and Pcyox1-silenced cells, in comparison with CHO cells overexpressing PCYOX1. The results obtained indicated that, in differentiated adipocytes, PCYOX1 is expressed but is not active (1.4 pmol H2O2/µg protein in CHO cells overexpressing PCYOX1, undetectable in differentiated adipocytes, n = 3). Furthermore, the levels of oxLDL, as assessed by immunoenzymatic assay, were not different between control cells and Pcyox1-silenced cells (1.1 ± 0.3 ng/mL and 1.0 ± 0.2 ng/mL, respectively, n = 6).
|
| 138 |
+
|
| 139 |
+
3.5. PCYOX1 Significantly Affects the Cell Proteome
|
| 140 |
+
|
| 141 |
+
The impact of PCYOX1 deletion on adipogenesis was further investigated by proteomics. Label-free quantitative mass spectrometry revealed that 43 proteins were significantly less abundant in the Pcyox1-deficient cells, and only two were more abundant in the Pcyox1-deficient cells compared to control cells (Table 1).
|
| 142 |
+
|
| 143 |
+
The GO analysis of proteins that were less abundant after Pcyox1 silencing (Figure 6 and Supplementary Table S3) revealed the enrichment of GO terms related to the lipid metabolic process (n = 18, p = 5.79e−10, i.e., hormone-sensitive lipase +(Lipe), fatty acid-binding protein (Fabp4), perilipin-1 (Plin1)), fatty acids β-oxidation (n = 7, p = 2.01e−8, i.e., enoyl-CoA hydratase), tricarboxylic acid cycle (n = 6, p = 4.21e−8, i.e., malate dehydrogenase 2, citrate synthase), gluconeogenesis (n = 3, p = 0.0069, i.e., glycerol-3-phosphate dehydrogenase), and oxidation reaction process (n = 26, p = 1.26e−20).
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Furthermore, the results from the proteomic analysis were validated in independent experiments by assessing the mRNA levels of the less abundant proteins: hormone-sensitive lipase (Lipe), carbonic anhydrase 3 (Car3), perilipin-1 (Plin1), 1-acyl-sn-glycerol-3-phosphate acyltransferase (Agpat2), carboxylesterase (Ces1f), platelet glycoprotein 4 (Cd36), and glycerol-3-phosphate dehydrogenase (Gpd1) (Figure 7A–G).
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We then evaluated gene expression in the VAT of mice fed an HFD for 8 weeks. As shown in Figure 8, Pcyox1 deficiency was associated with a significant reduction in the expression of the genes involved in adipogenesis, such as Cd36, Pparg, Lpl, and Ldlr (Figure 8).
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To determine the effect of the ablation of Pcyox1 on adipose tissue inflammation, we examined the expression of inflammatory markers serum amiloyd A3 (SAA3), MAC2, CD11b, CD11c, and EMR1. All of them were decreased in the VAT of Pcyox1−/−/Apoe−/− mice versus Pcyox1+/+/Apoe−/− mice after 8 weeks on HFD (Figure 9).
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4. Discussion
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New treatments that directly target adipose tissue accumulation may be possible if we understand all the factors necessary for normal adipogenesis. To the list of these factors, we add PCYOX1 as a novel regulator of adipogenesis. Our results demonstrate that PCYOX1 is expressed in adipose tissue, and that its deficiency results in reduced fat deposits. In agreement with these findings, in vitro experiments revealed that PCYOX1 is necessary for adipogenesis. PCYOX1 first emerged at the end of the 1990s as a lysosomal enzyme involved in the catabolism of prenylated proteins acting as a flavin adenine dinucleotide (FAD)-dependent thioether oxidase able to generate a stoichiometric amount of H2O2 [5,16]. Afterwards, thanks to the advent of proteomics, the knowledge of PCYOX1 was extended to the finding that this protein belongs to the proteome of lipoproteins, in which it contributes to their oxidative modifications [17]. Furthermore, Pcyox1 silencing in vitro was found to affect the cellular proteome by influencing multiple functions related to inflammation, oxidative stress, and platelet adhesion [4,13]. We also showed that Pcyox1 deficiency in Apoe−/− mice on C57/BL6J background mice (B6.129P2-Apoetm1Unc/J) retards atheroprogression, is associated with decreased features of lesion vulnerability and lower levels of lipid peroxidation, and reduces plasma lipid levels and inflammation, thus highlighting for the first time the role of PCYOX1 in vivo. Indeed, the pioneering study of Beigneux et al. [18] showed the absence of any histologic abnormalities in a survey of >30 tissues from Pcyox1-deficient mice on a mixed C57BL/6-129/SvJae genetic background. The observation that Pcyox1 deficiency in Apoe−/− mice fed with HFD, a model of obesity-accelerated atherosclerosis accompanied by development of a metabolic syndrome phenotype [19], have less adipose tissue depots, led us to further investigate the role of PCYOX1 in adipogenesis.
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The differentiation of preadipocytes into adipocytes is regulated by an elaborate network of transcription factors that coordinate the expression of hundreds of proteins responsible for establishing the mature fat-cell phenotype. At the center of this network are the two principal adipogenic factors, PPARγ and C/EBPα, which oversee the entire terminal differentiation process. PPARγ in particular is considered the master regulator of adipogenesis; without it, precursor cells are incapable of expressing any known aspect of the adipocyte phenotype [20].
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We found that the knockdown of Pcyox1 in 3T3-L1 preadipocytes renders them defective in inducing markers of terminal differentiation such as C/EBPα, PPARγ, and FABP4 and in accumulating fat, suggesting that PCYOX1 plays a pivotal role during the early events of the process. In this process, we ruled out the reciprocal regulation between PCYOX1 and C/EBPβ, suggesting that PCYOX1 acts independently from this crucial transcription factor. In an attempt to define the sequence of events leading to terminal adipogenesis, it was proposed that C/EBPβ and C/EBPδ simultaneously control the expression of both PPARγ and C/EBPα. Alternatively, some investigators have suggested that C/EBPβ induces C/EBPα and that, together, these factors regulate PPARγ expression [21]. The precise role of C/EBPβ and C/EBPδ in regulating this cascade of factors has been questioned, however, in knockout mice. Specifically, Tanaka et al. [22] demonstrated that adipocyte differentiation in vitro proceeds according to the proposed transcriptional regulatory cascade in which adipogenic transcription factors such as C/EBP family members and PPARs are activated sequentially. However, in vivo, C/EBPα and PPARγ can be induced without expression of C/EBPβ and C/EBPδ. These data suggest that there is some redundancy in the early steps of adipogenesis in vivo where alternative pathways operate to ensure the expression of PPARγ and C/EBPα. Over the last few years, many studies suggested that many additional transcription factors are potential components of this complex network of factors responsible for inducing adipogenic gene expression [23,24,25]. It is likely that additional factors of parallel pathways are induced early and converge on PPARγ at a stage downstream of C/EBPβ and C/EBPδ [21,25].
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The evidence that PCYOX1 generates H2O2, which in turn leads to the oxidative modifications of lipoproteins [4], suggested that it might be involved in the synthesis of PPARγ ligands. Indeed, it has been reported that oxLDL induces PPARγ activation, and that 9-hydroxyoctadecadienoic acid (9-HODE), 13-hydroxyoctadecadienoic acid (13-HODE), and oxidized phospholipids, which are components of oxLDL, are involved in oxLDL-induced PPARγ activation [15]. However, our findings excluded that PCYOX1 might contribute to the adipogenic process by providing a ligand for PPARγ, as far as oxLDL is concerned.
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| 160 |
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| 161 |
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Furthermore, a peak of expression of PCYOX1 at later stages of 3T3-L1 differentiation highlights an additional role in terminal differentiation. Inactivation of Pcyox1 blocked the expression of several mediators involved in adipogenesis, including, among others, Perilipin-1 (Plin1), 1-acyl-sn-glycerol-3-phosphate acyltransferase beta (Agpat2), Carboxylesterase 1 (Ces1), Hormone-sensitive lipase (Lipe), and Carbonic anhydrase 3 (Car3).
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Importantly, Perilipin-1 is abundantly expressed in mature adipocytes, phosphorylated in a cAMP-dependent manner, and localized to lipid droplet surfaces during differentiation of 3T3-L1 adipocytes into lipid-accumulating mature adipocytes. Plin1-knockout (KO) mice exhibited striking phenotypes [26,27], being lean, with microscopically reduced lipid droplet sizes in adipose tissues, increased glucose tolerance and resistance to diet-induced obesity [28]. In addition, the high lipolytic activities in the WAT of Plin1-KO mice prevent the accumulation of triglycerides, suggesting that Perilipin-1 exerts essential roles in lipid droplet formation and triglyceride metabolism in vivo.
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| 165 |
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Additionally, isoform 2 of the 1-acyl-sn-glycerol-3-phosphate acyltransferases (Agpat2) is a key enzyme involved in lipid synthesis, which is highly expressed in adipose tissue. It catalyses the acylation of lyso-phospatidic acid (LPA) to produce phosphatidic acid (PA), which will subsequently enter triglyceride or phospholipid synthesis. Cellular studies have supported that Agpat2 is necessary for adipocyte differentiation, suggesting that the absence of WAT in Agpat2 KO was the result of altered adipogenesis [29,30]. Furthermore, decreased levels of LPC in Agpat2 KO could lead to reduced synthesis of LPA, which has been previously shown to be a physiological PPARγ ligand [31].
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Recent advances in research have shown the relevance of carboxylesterases to metabolic diseases such as obesity and fatty liver disease [32]. Expression of Ces1 was induced during 3T3-L1 adipocyte differentiation [33], and administration of Ces1 inhibitors to HFD fed mice or db/db mice protected from weight gain reduced plasma lipids, ameliorated liver steatosis, and improved glucose tolerance [34]. Furthermore, in the adipose tissue of obese and type 2 diabetic patients, the activity of Ces1 is elevated, which is consistent with other studies showing that Ces1 expression is higher in adipose tissue from obese patients compared to lean subjects [35,36].
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| 168 |
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| 169 |
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Hormone-sensitive lipase (Lipe) is rate-limiting for diacylglycerol and cholesteryl ester hydrolysis in adipose tissue and essential for complete hormone-stimulated lipolysis [37]. Gene expression profiling in Lipe−/− mice suggests that it is important for modulating adipogenesis and adipose metabolism. In vitro studies showed that Lipe increases during differentiation [38], likely providing ligands for the activation of PPARγ.
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PCYOX1 also modulates Car3, which belongs to the family of carbonic anhydrases, enzymes involved in the promotion of fatty acid synthesis in adipocytes and the liver [39]. Car3 is highly abundant in tissues that can store lipids [40,41], and increases in rodents fed Western-type high-fat diets [42], becoming one of the most abundant transcripts in both human [43] and rodent [44] adipose tissues, accounting for up to 2% of the total mRNA. Moreover, Car3 constitutes the most abundant protein in mature adipocytes, comprising up to 24% of the total soluble protein fraction [40].
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| 172 |
+
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| 173 |
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Overall, the modulation of a plethora of genes involved in adipogenesis supports the hypothesis that PCYOX1 not only acts at early stages of adipogenesis, but also may account for the persistent expression of genes relevant for terminal adipogenic differentiation.
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| 175 |
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Importantly, PCYOX1 deficiency abrogated, in vitro and in vivo, the expression of CD36, a multifunctional immuno-metabolic receptor that is involved in many physiological and pathological processes [45]. Compared to wild-type mice, CD36 deficient mice with an HFD exhibited reduced adipose tissue inflammation, as evidenced by decreased pro-inflammatory cytokine levels in adipose tissue, and less macrophage and T-cell accumulation in adipose tissue [46,47].
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| 176 |
+
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| 177 |
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Consistent with the role of PCYOX1 in the regulation of adipose tissue inflammation is the finding that SAA3, one of the members of the acute-phase proteins serum amyloid A family, is also downregulated in Pcyox1−/−/Apoe−/− mice. Furthermore, SAA3 has been recently utilized for monitoring the adipose inflammatory state, possibly serving as an index of the number of infiltrated macrophages in adipose tissue [48]. In support of this hypothesis, we also found that the macrophage markers Mac2, Cd11b, Cd11c, and Emr1 were all decreased in the adipose tissue of Pcyox1 deficient mice, thus substantiating the hypothesis of a crosstalk between adipocytes and infiltrated macrophages as an important pathological phenomenon leading to adipose tissue inflammation.
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5. Conclusions
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| 180 |
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In summary, we report here that PCYOX1 is a novel regulator of adipogenesis, which acts upstream of known transcription factors and genes involved in lipogenesis, lipid droplet formation as well as lipid binding, and inflammation. These novel findings expand our knowledge on PCYOX1 biology and functions beyond its role in the metabolism of prenylated proteins [5,6,18,49]. Indeed, PCYOX1 is emerging as a multifunctional protein with a relevant role in atherogenesis by modulating lipid metabolism, inflammation and lipid peroxidation [4,17], in thrombosis by likely regulating circulating coagulant and inflammatory factors [13], and lastly, in adipogenesis. How PCYOX1 can modulate such different processes, which might not be restricted to its enzymatic pro-oxidant activity, is under investigation. Understanding the biology and mechanisms of all functions of this unique enzyme will help to provide additional therapeutic opportunities in addressing such conditions.
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Acknowledgments
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| 184 |
+
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| 185 |
+
Authors warmly thank Patrick Casey (Duke-NUS Medical School, Singapore and, Duke University Medical Center, NC, USA) and Stephen G. Young (UCLA Department of Medicine/Division of Cardiology, Los Angeles, CA, USA) for the generous support in the resuscitation of the Pcyox1 knockout mice.
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Supplementary Materials
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+
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| 189 |
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The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/antiox12030542/s1, Table S1: Primers used for qRT-PCR; Table S2: Primers purchased from Qiagen; Table S3: List of eEnriched GO terms in the biological process category considering all the proteins modulated by Pcyox1 silencing.
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Click here for additional data file.
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Author Contributions
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| 194 |
+
|
| 195 |
+
Conceptualization: C.B. and R.B.; methodology, A.M., S.G., M.B., E.G., S.E. and R.B.; validation, A.M., S.G., M.B., E.G. and S.E.; formal analysis, A.M. and M.B.; investigation, A.M., S.G., M.B., E.G., S.E., P.S. and R.B.; resources, C.B.; data curation, A.M., S.G., M.B., E.G. and P.S.; writing—original draft preparation, A.M. and M.B.; writing—review and editing, A.M., S.G., M.B., E.G., S.E., P.S., R.B. and C.B.; visualization, A.M., S.G. and M.B.; supervision, C.B.; project administration, C.B.; funding acquisition, C.B. All authors have read and agreed to the published version of the manuscript.
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Institutional Review Board Statement
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| 198 |
+
|
| 199 |
+
The animal study protocol was approved by the Ethics Committee of Centro Cardiologico Monzino IRCCS (protocol code 394/2015-PR, approved 20/05/2015).
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| 200 |
+
|
| 201 |
+
Data Availability Statement
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| 202 |
+
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| 203 |
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Data collected in the study will be made available using the data repository Zenodo (https://zenodo.org accessed on 22 February 2023) with restricted access upon request to direzione.scientifica@ccfm.it. Proteomic data are available via ProeomeXchange with identifier PXD039943. Any remaining information can be obtained from the corresponding Author upon reasonable request.
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+
|
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Conflicts of Interest
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| 206 |
+
|
| 207 |
+
We disclose the following European Patent application, under examination, EP15817414.4 entitled “Prenylcysteine oxidase 1 inhibitors for the prevention and/or treatment of oxidative stress-related degenerative diseases and prenylcysteine oxidase 1 as diagnostic marker”, applicant Centro Cardiologico Monzino IRCCS, with no financial competing interest. The remaining authors declare no competing interest.
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Figure 1 Effect of Pcyox1 deficiency on (A) body weight and (B) visceral adipose tissue (VAT) content evaluated in male Pcyox1+/+/Apoe−/− and Pcyox1−/−/Apoe−/− mice fed an HFD for 8 weeks (Pcyox1+/+/Apoe−/− n = 10; Pcyox1−/−/Apoe−/− n = 10) and 12 weeks (Pcyox1+/+/Apoe−/− n = 13; Pcyox1−/−/Apoe−/− n = 9). (C) Representative gel image of Pcyox1 mRNA expression, and (D) PCYOX1 protein level in VAT from wild-type mice evaluated by mass spectrometry (n = 3). Data are presented as circle plot, with each circle representing an individual mouse and bars showing the mean value ± SEM. VAT is expressed as percentage on body weight. HFD, high fat diet. Statistical significance calculated by Student’s t test, * p < 0.05 vs. Pcyox1+/+/Apoe−/−.
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| 210 |
+
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| 211 |
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Figure 2 Pcyox1 mRNA expression during 3T3-L1 in vitro differentiation. (A) Pcyox1, (B) Pparg, and (C) Fabp4 mRNA levels during 3T3-L1 differentiation. 18s mRNA was used as a housekeeping gene; n = 5–11 different experiments. * p < 0.05, *** p < 0.001 vs. day 0 with ANOVA and Dunnett’s post-hoc test.
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Figure 3 Pcyox1 mRNA levels in 3T3-L1 during adipogenic differentiation in the presence of (A) insulin 1 µg/mL, (B), dexamethasone 0.25 µmol/L (DEX) and (C) the phosphodiesterase inhibitor 3-isobutyl-1-methylxanthine 0.5 mmol/L (IBMX). (D) mRNA levels of Cebpb during 3T3-L1 differentiation. 18s mRNA was used as a housekeeping gene; n = 3–4 different experiments. * p < 0.05, ** p < 0.01, *** p < 0.001 vs. day 0 with ANOVA and Dunnett’s post-hoc test.
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Figure 4 Effects of Pcyox1 silencing on 3T3-L1 differentiation towards adipocyte-like cells. Control cells were treated with lentiviral particles containing negative shRNA constructs (shNEG), while specific shPcyox1 constructs were used to silence Pcyox1. (A) Lipid droplets were visualized by Oil Red O staining after 9 days of differentiation. Representative images of n= 3 different experiments were acquired with 20× magnification. (B–F): effects of Pcyox1 silencing on mRNA levels of (B) Fabp4, (C) Pparg, (D) Lpl, (E) Cebpa, and (F) Cebpb. 18s mRNA was used as a housekeeping gene; n = 3–7 different experiments. **** p < 0.0001 vs. shNEG day 0; §§§§ p < 0.0001 vs. shPcyox1 day 9; ‡‡‡‡ p < 0.0001 vs. shPcyox1 day 0; ‡‡‡ p < 0.001 vs. shPcyox1 day 0; ‡ p < 0.05 vs. shPcyox1 day 0 with ANOVA and Tukey’s post-hoc test.
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+
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Figure 5 Effects of Cebpb silencing on Cebpa, Pparg, and Pcyox1 expression during 3T3-L1 differentiation. 18s mRNA was used as a housekeeping gene; n = 6 different experiments. **** p < 0.0001 vs. shNEG day 0; §§§§ p < 0.0001 vs. shCebpb; ‡‡‡‡ p < 0.0001 vs. shCebpb day 0 with ANOVA and Tukey’s post-hoc test.
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| 218 |
+
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| 219 |
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Figure 6 GO analysis of proteins modulated by Pcyox1 silencing. Enriched GO terms in the biological process category are highlighted in different colors: red, lipid metabolic processes; violet, oxidation-reduction processes; blue, fatty acid β-oxidation; green, tricarboxylic acid cycle; yellow, gluconeogenesis.
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+
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Figure 7 mRNA levels of the differently expressed proteins in Pcyox1 silenced cells. mRNA levels were evaluated in control (shNEG) and Pcyox1-silenced (shPcyox1) 3T3-L1 cells after 9 days of adipocyte differentiation. (A) Hormone-sensitive lipase (Lipe), (B) Carbonic anhydrase 3 (Car3), (C) Perilipin-1 (Plin1), (D) 1-acyl-sn-glycerol-3-phosphate acyltransferase beta (Agpat2), (E) Carboxylesterase 1F (Ces1f), (F) Platelet glycoprotein 4 (Cd36) and (G) Glycerol-3-phosphate dehydrogenase [NAD(+)] cytoplasmic (Gpd1); 18s mRNA was used as a housekeeping gene; n = 4 different experiments. Statistical significance calculated with Student’s t test.
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Figure 8 mRNA levels of Cd36, Pparg, Lpl and Ldlr in Pcyox1−/−/ApoE−/− (n = 9) mice fed with HFD for 8 weeks compared with Pcyox1+/+/Apoe−/− (n = 9); 18s mRNA was used as a housekeeping gene. Data are presented as circle plot, with each circle representing an individual mouse and bars showing the mean value ± SEM, n = 9. Statistical significance calculated by Student’s t test.
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| 224 |
+
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| 225 |
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Figure 9 Changes in mRNA of Emr1, Itgam (CD11b), Itgax (CD11c), Lgals3 (MAC2) and Saa3 in Pcyox1−/−/Apoe−/− mice (n = 4) fed with HFD for 8 weeks compared with Pcyox1+/+/Apoe−/− (n = 4); 18s mRNA was used as a housekeeping gene. Data are presented as circle plot, with each circle representing an individual mouse and bars showing the mean value ± SEM. Statistical significance calculated by Student’s t test.
|
| 226 |
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antioxidants-12-00542-t001_Table 1 Table 1 List of differentially expressed proteins in the proteome of differentiated 3T3-L1 cells after Pcyox1 silencing with respect to control cells, treated with a negative construct.
|
| 228 |
+
|
| 229 |
+
Accession Unique Peptides q Value Max Fold Change Highest Mean
|
| 230 |
+
Condition Description
|
| 231 |
+
Reduced in Pcyox1 silenced cells
|
| 232 |
+
P54310 3 0.003 7.07 NEG Hormone-sensitive lipase OS = Mus musculus GN = Lipe
|
| 233 |
+
Q9CQF9 2 0.001 4.84 NEG Prenylcysteine oxidase OS = Mus musculus GN = Pcyox1
|
| 234 |
+
P16015 5 0.001 4.73 NEG Carbonic anhydrase 3 OS = Mus musculus GN = Car3
|
| 235 |
+
P04117 5 0.003 3.51 NEG Fatty acid-binding protein_ adipocyte OS = Mus musculus GN = Fabp4
|
| 236 |
+
Q8CGN5 5 0.001 3.34 NEG Perilipin-1 OS = Mus musculus GN = Plin1
|
| 237 |
+
Q8K3K7 3 0.003 2.91 NEG 1-acyl-sn-glycerol-3-phosphate acyltransferase beta OS = Mus musculus GN = Agpat2
|
| 238 |
+
Q91WU0 2 0.006 2.77 NEG Carboxylesterase 1F OS = Mus musculus GN = Ces1f
|
| 239 |
+
Q08857 2 0.012 2.32 NEG Platelet glycoprotein 4 OS = Mus musculus GN = Cd36
|
| 240 |
+
P13707 9 0.006 2.32 NEG Glycerol-3-phosphate dehydrogenase [NAD(+)]_ cytoplasmic OS = Mus musculus GN = Gpd1
|
| 241 |
+
P28271 3 0.004 2.18 NEG Cytoplasmic aconitate hydratase OS = Mus musculus GN = Aco1
|
| 242 |
+
P16125 2 0.011 2.03 NEG L-lactate dehydrogenase B chain OS = Mus musculus GN = Ldhb P
|
| 243 |
+
P24270 2 0.004 1.92 NEG Catalase OS = Mus musculus GN = Cat
|
| 244 |
+
Q63918 4 0.001 1.92 NEG Serum deprivation-response protein OS = Mus musculus GN = Sdpr
|
| 245 |
+
Q05920 18 0.001 1.88 NEG Pyruvate carboxylase_ mitochondrial OS = Mus musculus GN = Pc
|
| 246 |
+
P31786 2 0.021 1.87 NEG Acyl-CoA-binding protein OS = Mus musculus GN = Dbi
|
| 247 |
+
O88492 3 0.019 1.86 NEG Perilipin-4 OS = Mus musculus GN = Plin4
|
| 248 |
+
P45952 3 0.006 1.81 NEG Medium-chain specific acyl-CoA dehydrogenase_ mitochondrial OS = Mus musculus GN = Acadm
|
| 249 |
+
Q8BMS1 13 0.007 1.80 NEG Trifunctional enzyme subunit alpha_ mitochondrial OS = Mus musculus GN = Hadha
|
| 250 |
+
P97807 6 0.004 1.79 NEG Fumarate hydratase_ mitochondrial OS = Mus musculus GN = Fh
|
| 251 |
+
Q8BH95 3 0.037 1.70 NEG Enoyl-CoA hydratase_ mitochondrial OS = Mus musculus GN = Echs1
|
| 252 |
+
Q9WTP7 2 0.007 1.68 NEG GTP:AMP phosphotransferase AK3_ mitochondrial OS = Mus musculus GN = Ak3
|
| 253 |
+
P49817 2 0.016 1.53 NEG Caveolin-1 OS = Mus musculus GN = Cav1
|
| 254 |
+
Q9CZU6 4 0.017 1.51 NEG Citrate synthase_ mitochondrial OS = Mus musculus GN = Cs
|
| 255 |
+
P62897 2 0.005 1.49 NEG Cytochrome c_ somatic OS = Mus musculus GN = Cycs
|
| 256 |
+
Q9EQ20 3 0.001 1.48 NEG Methylmalonate-semialdehyde dehydrogenase [acylating]_ mitochondrial OS = Mus musculus GN = Aldh6a1
|
| 257 |
+
Q9JHI5 2 0.007 1.48 NEG Isovaleryl-CoA dehydrogenase_ mitochondrial OS = Mus musculus GN = Ivd
|
| 258 |
+
Q9CZ13 3 0.009 1.47 NEG Cytochrome b-c1 complex subunit 1_ mitochondrial OS = Mus musculus GN = Uqcrc1
|
| 259 |
+
O54724 6 0.001 1.47 NEG Polymerase I and transcript release factor OS = Mus musculus GN = Ptrf
|
| 260 |
+
Q8BH64 8 0.003 1.46 NEG EH domain-containing protein 2 OS = Mus musculus GN = Ehd2
|
| 261 |
+
P17751 9 0.001 1.46 NEG Triosephosphate isomerase OS = Mus musculus GN = Tpi1
|
| 262 |
+
Q9D3D9 2 0.010 1.46 NEG ATP synthase subunit delta_ mitochondrial OS = Mus musculus GN = Atp5d
|
| 263 |
+
Q8BMF4 5 0.011 1.45 NEG Dihydrolipoyllysine-residue acetyltransferase component of pyruvate dehydrogenase complex_ mitochondrial OS = Mus musculus GN = Dlat
|
| 264 |
+
Q60597 4 0.022 1.44 NEG 2-oxoglutarate dehydrogenase_ mitochondrial OS = Mus musculus GN = Ogdh
|
| 265 |
+
Q9DB77 7 0.014 1.43 NEG Cytochrome b-c1 complex subunit 2_ mitochondrial OS = Mus musculus GN = Uqcrc2
|
| 266 |
+
Q99L13 3 0.003 1.42 NEG 3-hydroxyisobutyrate dehydrogenase_ mitochondrial OS = Mus musculus GN = Hibadh
|
| 267 |
+
P08249 13 0.019 1.42 NEG Malate dehydrogenase_ mitochondrial OS = Mus musculus GN = Mdh2
|
| 268 |
+
Q9DCW4 4 0.017 1.42 NEG Electron transfer flavoprotein subunit beta OS = Mus musculus GN = Etfb
|
| 269 |
+
Q99LC5 9 0.011 1.42 NEG Electron transfer flavoprotein subunit alpha_ mitochondrial OS = Mus musculus GN = Etfa
|
| 270 |
+
Q9CR62 2 0.003 1.41 NEG Mitochondrial 2-oxoglutarate/malate carrier protein OS = Mus musculus GN = Slc25a11
|
| 271 |
+
P00405 4 0.046 1.41 NEG Cytochrome c oxidase subunit 2 OS = Mus musculus GN = Mtco2
|
| 272 |
+
Q922Q1 2 0.034 1.41 NEG Mitochondrial amidoxime reducing component 2 OS = Mus musculus GN = Marc2
|
| 273 |
+
P47738 8 0.016 1.40 NEG Aldehyde dehydrogenase_ mitochondrial OS = Mus musculus GN = Aldh2
|
| 274 |
+
Q9D9V3 4 0.022 1.40 NEG Ethylmalonyl-CoA decarboxylase OS = Mus musculus GN = Echdc1
|
| 275 |
+
Increased in Pcyox1 silenced cells
|
| 276 |
+
Q60847 4 0.001 1.99 shPCYOX1 Collagen alpha-1(XII) chain OS = Mus musculus GN = Col12a1
|
| 277 |
+
P37889 16 0.004 1.42 shPCYOX1 Fibulin-2 OS = Mus musculus GN = Fbln2
|
| 278 |
+
|
| 279 |
+
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| 280 |
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|
puc/PMC10045570.txt
ADDED
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
PLoS One
|
| 4 |
+
PLoS One
|
| 5 |
+
plos
|
| 6 |
+
PLOS ONE
|
| 7 |
+
1932-6203
|
| 8 |
+
Public Library of Science San Francisco, CA USA
|
| 9 |
+
|
| 10 |
+
36735680
|
| 11 |
+
10.1371/journal.pone.0281240
|
| 12 |
+
PONE-D-22-30790
|
| 13 |
+
Research Article
|
| 14 |
+
Biology and life sciences
|
| 15 |
+
Biochemistry
|
| 16 |
+
Nucleic acids
|
| 17 |
+
RNA
|
| 18 |
+
Non-coding RNA
|
| 19 |
+
Long non-coding RNA
|
| 20 |
+
Biology and Life Sciences
|
| 21 |
+
Anatomy
|
| 22 |
+
Biological Tissue
|
| 23 |
+
Connective Tissue
|
| 24 |
+
Adipose Tissue
|
| 25 |
+
Medicine and Health Sciences
|
| 26 |
+
Anatomy
|
| 27 |
+
Biological Tissue
|
| 28 |
+
Connective Tissue
|
| 29 |
+
Adipose Tissue
|
| 30 |
+
Biology and Life Sciences
|
| 31 |
+
Physiology
|
| 32 |
+
Physiological Parameters
|
| 33 |
+
Body Weight
|
| 34 |
+
Obesity
|
| 35 |
+
Biology and life sciences
|
| 36 |
+
Cell biology
|
| 37 |
+
Chromosome biology
|
| 38 |
+
Chromatin
|
| 39 |
+
Chromatin modification
|
| 40 |
+
DNA methylation
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Biology and life sciences
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Genetics
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Epigenetics
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Chromatin
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Chromatin modification
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DNA methylation
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Biology and life sciences
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Genetics
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Gene expression
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Chromatin
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Chromatin modification
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DNA methylation
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Biology and life sciences
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Genetics
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DNA
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DNA modification
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DNA methylation
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Biology and life sciences
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Biochemistry
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Nucleic acids
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DNA
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DNA modification
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DNA methylation
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Biology and life sciences
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Genetics
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Epigenetics
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DNA modification
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DNA methylation
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Biology and life sciences
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Genetics
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Gene expression
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DNA modification
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DNA methylation
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Biology and Life Sciences
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Genetics
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Gene Expression
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Biology and Life Sciences
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Genetics
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Epigenetics
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Biology and Life Sciences
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Biochemistry
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Metabolism
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Carbohydrate Metabolism
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Glucose Metabolism
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Biology and Life Sciences
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Genetics
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Gene Expression
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Gene Regulation
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Co-expression analysis of lncRNA and mRNA identifies potential adipogenesis regulatory non-coding RNAs involved in the transgenerational effects of tributyltin
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Regulation of adipogenesis by lncRNAs after ancestral exposure to tributyltin
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https://orcid.org/0000-0001-9123-9452
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Lopes Maria Fernanda da Silva Conceptualization Formal analysis Investigation Methodology Project administration Resources Software Visualization Writing – original draft Writing – review & editing 1
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https://orcid.org/0000-0002-8635-1674
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Felix Juliana de Souza Methodology 1
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https://orcid.org/0000-0003-4071-5935
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Scaramele Natália Francisco Methodology 1
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https://orcid.org/0000-0003-4371-1446
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Almeida Mariana Cordeiro Methodology 1
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https://orcid.org/0000-0002-6467-590X
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Furlan Amanda de Oliveira Methodology 1
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Troiano Jéssica Antonini Methodology 1 2
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de Athayde Flávia Regina Florêncio Methodology 1
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https://orcid.org/0000-0002-3173-3712
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Lopes Flávia Lombardi Supervision 1 *
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1 Department of Animal Production and Health, School of Veterinary Medicine, São Paulo State University Júlio de Mesquita Filho (Unesp), Araçatuba, Brazil
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2 Faculdades de Dracena (UNIFADRA–Fundec), Dracena, São Paulo, Brazil
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Shioda Toshi Editor
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Massachusetts General Hospital, UNITED STATES
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Competing Interests: The authors have declared that no competing interests exist.
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* E-mail: flavia.lopes@unesp.br
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3 2 2023
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2023
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18 2 e02812408 11 2022
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18 1 2023
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© 2023 Lopes et al
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2023
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Lopes et al
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https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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The obesity epidemic is considered a global public health crisis, with an increase in caloric intake, sedentary lifestyles and/or genetic predispositions as contributing factors. Although the positive energy balance is one of the most significant causes of obesity, recent research has linked early exposure to Endocrine-Disrupting Chemicals (EDCs) such as the obesogen tributyltin (TBT) to the disease epidemic. In addition to their actions on the hormonal profile, EDCs can induce long-term changes in gene expression, possibly due to changes in epigenetic patterns. Long non-coding RNAs (lncRNAs) are epigenetic mediators that play important regulatory roles in several biological processes, through regulation of gene transcription and/or translation. In this study, we explored the differential expression of lncRNAs in gonadal white adipose tissue samples from adult male C57BL/6J F4 generation, female C57BL/6J offspring exposed (F0 generation) to 50 nM TBT or 0.1% DMSO (control of vehicle) via drinking water provided during pregnancy and lactation, analyzing RNA-seq data from a publicly available dataset (GSE105051). A total of 74 lncRNAs were differentially expressed (DE), 22 were up-regulated and 52 were down-regulated in the group whose F4 ancestor was exposed in utero to 50nM TBT when compared to those exposed to 0.1% DMSO (control). Regulation of DE lncRNAs and their potential partner genes in gonadal white adipose tissue of mice ancestrally exposed to EDC TBT may be related to the control of adipogenesis, as pathway enrichment analyses showed that these gene partners are mainly involved in the metabolism of lipids and glucose and in insulin-related pathways, which are essential for obesity onset and control.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) https://orcid.org/0000-0001-9123-9452
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Lopes Maria Fernanda da Silva FLL is a PQ2 CNPQ scholar. MFSL, JSF, NFS, MCA, AOF and FRFA has a scholarship supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Data AvailabilityAll relevant data are within the paper and its Supporting Information files.
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Data Availability
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All relevant data are within the paper and its Supporting Information files.
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==== Body
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pmcIntroduction
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Exposure to environmental factors during embryonic development has been linked to increased risk of diseases such as obesity and type 2 diabetes mellitus later in life. The obesity epidemic is considered a global public health crisis, having as contributing factors increased caloric intake, sedentary lifestyles and/or genetic predispositions. Although the positive energy balance is one of the most significant causes of obesity, recent research has linked early exposure to endocrine disrupting chemicals (EDCs) to the disease [1].
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EDCs are chemical compounds that interfere with production, release, transport, metabolism, action or elimination of endogenous hormones responsible for maintaining homeostasis and regulating developmental processes [2]. Obesogenic substances comprise a subset of EDCs, which can lead to accumulation of lipids through inadequate adipogenesis, hypertrophy or hyperplasia of adipocytes, or by affecting hormonal regulation of metabolism, appetite and satiety [3]. There is growing evidence suggesting that exposure to these chemicals during intrauterine development or lactation can strongly influence the offspring’s predisposition to obesity in adulthood [4].
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The germline transmission of epigenetic information between generations in the absence of direct exposures to environmental factors is defined as transgenerational epigenetic inheritance. Exposure of the pregnant mother (F0), linked with the developing fetus (F1), to environmental insults (e.g. endocrine disruptors, toxics, malnutrition), causes epimutations that are transmitted to the F2 and F3 generation. The transgenerational epigenetic inheritance caused by the environment has significant consequences in the etiology of diseases, inheritance of phenotypic variation and in evolutionary biology [5]. Studies show that transgenerational effects obtained through exposure to environmental factors is associated with epimutations in DNA methylation patterns and in histone retention patterns, which are promoted specifically through the germline [6–8].
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Transgenerational effects have been observed with some types of EDCs, such as bisphenol A (BPA), dichlorodiphenyltrichloroethane (DDT), dibutyl phthalate (DBP), triphenyltin (TPT) and tributyltin (TBT). Egusquiza and Blumberg [9] reported that TBT induces obesity by promoting the differentiation of adipocytes in the body while stimulating the activity of the RXR-PPARγ complex, and that the obesogenic effects of TBT exposure are propagated transgenerationally to unexposed offspring through epigenetic changes. Shoucri et al. [10] have demonstrated that exposure to TBT in mesenchymal stem cell culture is related to greater accumulation of lipids during subsequent adipose differentiation. In addition to their actions on the hormonal profile, EDCs can induce long-term changes in gene expression, possibly due to changes in epigenetic patterns [11]. Epigenetic mechanisms play essential roles in the processes that determine adult phenotypes through epigenetic programming. Numerous studies over the last two decades have shown that maternal nutrition can cause changes in the fetal epigenome, i.e., DNA methylation profile, post-translational histone modifications, and regulation of and by non-coding RNAs (ncRNAs), which can lead to permanent phenotypic changes in the offspring, as reviewed by Greco et al. [12].
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LncRNAs are non-coding transcripts composed of more than 200 nucleotides, and play an important role in the transcriptional, post-transcriptional and epigenetic regulation of gene expression, thus being able to silence or activate specific genes or loci [13]. The mechanisms by which lncRNAs regulate their targets genes depend on specific features of primary sequence, secondary structure and genomic positioning of lncRNA transcripts. LncRNAs can act by recruiting different protein components of the chromatin remodeling complex to change chromatin organizational patterns; they can function as ’sponges’ by base pairing with complementary miRNAs, thus reducing their effects; they can play scaffolding roles by providing docking sites for proteins that function together in the same biological pathway; lncRNAs can activate transcription of certain genes by guiding transcription factors to their promoters, or suppress transcription by sequestering transcription factors; and they can also modulate mRNA by base pairing with them to inhibit translation, alter splicing patterns or affect degradation [14].
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Considering the importance of maternal nutrition for epigenetic patterning on the offspring (and transgenerationally on their descendants), the diverse roles that lncRNAs play on gene expression control, and the previously demonstrated effects of TBT on the expression of genes relevant to fat metabolism [1], we aimed to evaluate the effects of ancestral exposure to obesogenic substances on the expression of lncRNAs, and to correlate their expression to those of their possible biological targets in the white adipose tissue (WAT) of mice.
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In this study, we identified lncRNA expression profiles in the WAT of F4 mice transgenerationally exposed to 50nM TBT or 0.1% DMSO (control). Differentially expressed lncRNAs were then used to predict putative cis- and trans-target genes which were then integrated with differentially expressed mRNA data to improve the accuracy of the target prediction. Putative target mRNAs of lncRNAs in cis and trans were then used to build lncRNA-mRNA correlation networks affected transgenerationally in F4, following exposure of F0 generation to the obesogen TBT.
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Methods
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RNA-seq datasets
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RNA-seq data were previously generated by Chamorro-Garcia et al. [1], and obtained from the Gene Expression Omnibus (GEO) public database (www.ncbi.nlm.nih.gov/geo/) under the bioproject PRJNA414476, with accession number GSE105051. Briefly, 7 week-old female C57BL/6 J mice (generation F0) were exposed to 50 nM TBT or 0.1% DMSO (vehicle control) via drinking water provided during pregnancy and lactation. To form subsequent generations (F2-F4), non-sibling mice were randomly assigned from litters within the same experimental groups. Only animals from the F0 generation were directly exposed to 50 nM TBT (exposed to the TBT) or 0.1% DMSO (control).
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Mice were kept on low-fat chow (standard diet, SD—13.2% KCal of fat) throughout the experimentation period (F0-F4). To assess interaction between TBT exposure and dietary fat levels, F4 descendants (n = 4 for each experimental group) of TBT or DMSO F0 females were switched to a high-fat diet (HFD—21.2% KCal of fat) at week 19. These F4 animals were kept in the HFD for 6 weeks, then returned to SD for 8 weeks until 33 weeks of age. To assess the effect of ancestral exposure to TBT on fat mobilization, one week before euthanasia (week 32), animals were submitted to overnight fasting (16h). In total, 8 samples of gonadal WAT (gWAT) were used for RNA-Seq, consisting of 4 samples from the 50 nM TBT exposed group (exposed to TBT in the F0 generation) and 4 samples from the 0.1% DMSO group (not exposed to TBT in the F0 generation).
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Bioinformatic identification of lncRNAs in RNA-seq datasets
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Quality of the extracted RNA-seq readings was evaluated with FastQC available at the public server www.usegalaxy.org [15]. Data were aligned to the latest mouse genome reference sequence (GRCm38.p6, as provided by GENCODE) (https://www.gencodegenes.org/) using HISAT2 version 2.1.0+galaxy5 [16] with the Burrows-Wheeler Transformation (BWT) and the Ferragina-Manzini (FM) indexing algorithms. The resulting BAM file was then processed with FeatureCounts version 1.6.4+galaxy1 [17] to perform read counts using the GENCODE M25 (mouse) annotation as reference (https://www.gencodegenes.org/). Quality control of all steps was carried out using MultiQC. Next, DESeq2 (version 2.11.40.6 + galaxy1) was used to perform statistical analyses of differential expression of lncRNAs and mRNAs between samples from the TBT and control (DMSO) groups. This tool estimates the average variance in read counts and tests the differential expression using a binomial distribution model as basis and Wald test [18].
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The Biomart tool was used to classify the transcripts according to their biotype. Biotypes are classified according to HAVANA gene biotype (http://www.ensembl.org/info/genome/genebuild/biotypes.html) and grouped into 3 classes: protein-coding genes, long non-coding RNA (lncRNAs) genes and small non-coding RNA genes. In the lncRNAs class, the following descriptions were considered: "processed_transcript", "pseudogene", "To be Experimentally Confirmed (TEC)", "lincRNA", "3prime_overlapping_ncrna", "antisense", "sense_intronic" and sense_overlapping".
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Differently expressed (DE) LncRNAs (p < 0.05) and coding proteins (p < 0.05 and log2(FC) ≥ ± 0.5) were clustered with the heatmap3 package in R using the “complete linkage” method and the Euclidean distance as parameters (https://www.rdocumentation.org/packages/heatmap3/versions/1.1.7/topics/heatmap3).
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Prediction analysis of putative lncRNAs with cis-and trans action
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Differentially expressed lncRNAs were used for the prediction of the putative cis- and trans-target genes. First, using normalized counts of differentially expressed lncRNAs and mRNAs, we performed correlation analysis by means of Pearson’s correlation coefficient. A lncRNA-mRNA interaction was considered significant when Pearson`s correlation |r| ≥ 0.80 and p<0.05. From the total correlation matrix, we performed two analyses to identify and classify the interactions and possible actions of lncRNAs (cis and/or trans) in relation to their target gene. To check potential lncRNA-mRNA interactions, LncTar (http://www.cuilab.cn/lnctar) [19] was used to predict lncRNA targets (normalized dG (ndG) was set to -0.10) and those with significant correlation, as identified by Pearson’s correlation (as described above), were maintained. Classification of DE lncRNAs was performed using the program FEELnc (Flexible Extraction of Long non-coding RNAs) (v.0.1.1) (https://github.com/tderrien/FEELnc) [20]. Based on locus analysis, lncRNA-mRNA interactions that had the target mRNA within a window of 100 kbps upstream or downstream of the lncRNA location were classified as cis-acting, and interactions outside the established window of 100 kbps and that also had a binding potential (ndG≤ -0.10) were classified as trans-acting.
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Only DE lncRNAs with correlation and binding potential within the parameters and their corresponding cis- and trans-target genes were used to construct lncRNA-gene interaction networks using the Cytoscape 3.9.0 program (https://cytoscape.org/). Also, Cytoscape was used to identify nodes from the co-expression modules. The top five nodes were ranked according to interaction number of the lncRNAs and their targets.
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To gather as much information as possible on all lncRNAs, we performed orthology analysis of all DE lncRNAs with humans using the Orthology Predictions Search tool, available at https://www.genenames.org/tools/hcop/#!/. Subsequently, the NcPath tool (http://ncpath.pianlab.cn/#/Home) was employed to compare the predict targets of the orthologous lncRNA to experimentally-verified lncRNA targets in humans.
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Gene ontology and pathway enrichment analysis
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We used the g:GOSt (Function Profiling) tool within gProfiler (https://biit.cs.ut.ee/gprofiler/gost) for analysis of the Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG Pathways) of all significant lncRNAs and partner mRNA pairs (https://biit.cs.ut.ee/gprofiler/gost). All p-values were adjusted using the Benjamini-Hochberg (FDR) method (adjusted p-value <0.05).
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A schematic overview of the lncRNA analysis and identification pipeline can be seen in Fig 1.
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10.1371/journal.pone.0281240.g001 Fig 1 Workflow of lncRNA analysis and functional predictions.
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The workflow describes the step-by-step bioinformatics analyzes performed in our study. (A) Raw reads were extracted from the GEO database. (B) The bioinformatics analyzes (quality, alignment, counting and differential expression) of these readings were performed on the Galaxy platform. (C) Classification of transcripts was performed on the Ensembl Biomart platform. (D) Correlation between differentially expressed lncRNAs-mRNAs. (E) Classification of the action of lncRNAs and their target mRNAs. (F) Functional enrichment analysis.
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MBD-seq data analysis
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To evaluate the methylation profile of the regions of interest (DE lncRNAs), MBD-seq data, generated with the same model described for RNA-Seq (Chamorro-Garcia et al. [1]) and previously analyzed by the authors, was employed (GSE105051).
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Results
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Identification differential expression of lncRNA
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Out of 818 differentially expressed transcripts, 708 (86.5%) matched to protein coding and 74 (~9%) were considered to have a lncRNA biotype, according to the HAVANA gene biotype classification, available on the Ensembl Biomart tool. Long intergenic non-coding RNAs (lincRNAs) accounted for 39.2% of all DE lncRNAs, followed by antisense transcripts (27%). The remaining non-coding transcript types were TEC (18.9%), processed_transcripts (8.1%), bidirectional promoter lncRNA (5.4%), and sense_intronic transcripts (1.4%).
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Of these 74 DE lncRNAs in the contrast of the groups exposed to 50 nM TBT or exposed to 0.1% DMSO (S1A and S1B Table), 22 showed increased expression in the group in which F0 was exposed to 50 nM TBT when compared to that exposed to 0.1%DMSO. The other 52 lncRNAs were downregulated in the group ancestrally (F4) exposed to 50 nM TBT (Fig 2).
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10.1371/journal.pone.0281240.g002 Fig 2 Heatmap of 74 differentially expressed lncRNAs between samples of gWAT ancestrally exposed to EDC TBT and samples of the control group (DMSO).
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Expression of lncRNA is represented according to the color scale shown at the top, corresponding to the z-score. Red represents higher expression, and green represents lower expression.
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Correlation of expression and classification of trans and cis acting lncRNAs
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To assess the influence of lncRNAs on the expression of mRNAs and their biological functions, we obtained a correlation matrix of 6595 significant interactions between DE lncRNA and mRNA (Pearson correlation r ≥ |0.80|; p-value <0.05) (S2 Table). Of these, we observed that a total of 1191 lncRNA-mRNA interactions presented significant binding potential, suggesting trans-action potential (normalized deltaG analysis in LncTar tool (ndG < -0.10)) (S3 Table).
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In the prediction analysis of cis lncRNAs-mRNAs pairs (performed in the FEELnc tool), we obtained 11 DE lncRNAs linked to 11 genes close to DE, and of these 2 lncRNA-mRNA interactions showed significant correlation (Pearson correlation r ≥ |0.80 |; p-value <0.05) (S4 Table). As a cis-acting transcript, lncRNA Gm26704 could affect Fzd6 pre-transcriptionally, in addition to presenting binding potential (LncTar) with the Fzd6 mRNA. The lncRNA Gm10603 is a cis-partner of the Ucp gene.
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Following orthology analysis of our 74 differentially expressed lncRNAs, only 2 lncRNAs had human orthologous, namely Rian (MEG8—human) and Ftx (FTX—human). Of these, Rian was the only one with predicted targets in mice that were also experimentally-verified targets in humans (Shank2 and Inhba).
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Biological function analysis
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For gene ontology and KEGG pathway analyses, DE mRNAs and lncRNAs that showed significant correlation (Pearson correlation r ≥ |0.80 |; p-value <0.05) and binding potential (ndG < -0.10) were used. Therefore, 479 target genes identified from the 61 lncRNAs were used to obtain information about biological functions. KEGG analysis revealed 27 pathways (Fig 3) with 100 of our identified partner mRNAs, which in turn were potentially regulated by 50 DE lncRNAs. The enriched pathways were mainly related to lipid and glucose metabolism.
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10.1371/journal.pone.0281240.g003 Fig 3 KEGG pathways enriched for co-expressed mRNAs in Cytoscape network.
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KEGG pathway enrichment analysis was performed in gProfiler. The y-axis represents the KEGG pathways and the x-axis represents the number of genes participating in each pathway. The numbers in front of the bars represent the adjusted p-value of the respective route.
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Next, we constructed co-expression networks to better visualize the five major interactions between lncRNAs and their targets (Fig 4). Using the analyze network tool in Cytoscape, the top five lncRNAs were identified based on the number of interactions with mRNA partners (Table 1 and S5 Table).
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10.1371/journal.pone.0281240.g004 Fig 4 Network analysis of the top 5 network analysis of the top 5 lncRNAs based on the number of interactions with mRNAs.
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Hexagons represent mRNAs, and triangles represent lncRNAs. Light blue nodes represent KEGG pathways. Expression of lncRNA and mRNA are represented according to the colors red and green, corresponding to up and down-regulated transcripts, respectively.
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10.1371/journal.pone.0281240.t001 Table 1 Top 5 lncRNAs based on the number of interactions with mRNAs.
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Name Interactions
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Rian 33
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Gm10804 32
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Rmst 16
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Gm13067 14
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Gm53 13
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Identification of DE lncRNAs in DMRs
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Next, we used the MBD-Seq data obtained by Chamorro-Garcia et al. [1] in order to verify the location of Differentially Methylated Regions (DMR) in relation to our identified DE lncRNAs. In the study, the authors classified the regions according to the distance of the DMRs from the transcription start site (TSS), as well the number of DMRs present. Region I was comprised of genes with at least one DMR in close proximity (between -1500 bp and +500 bp) to the transcription start site (TSS). Region II indicates genes that overlap or flank at least one DMR, regardless of their distance from the TSS. Finally, region III represents genes located in iso-differentially methylated blocks (isoDMBs). Our results show that 35 of our DE lncRNAs were located within regions II and III, as classified by Chamorro-Garcia et al. [1], 9 of which were down-regulated in hypermethylated regions and 10 were up-regulated in hypomethylated regions (Table 2) suggesting that global changes in DNA methylation, resulting from ancestral exposure to the endocrine disruptor TBT, can alter the expression of lncRNAs and mRNAs involved in the adipogenesis process.
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10.1371/journal.pone.0281240.t002 Table 2 LncRNAs associated to genomic structures defined using TBT-dependent DNA methylome.
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Gene symbol Up/Down Direction of change DMR subset DMR structure
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1700018A04Rik down Hypermethylated II mDMR
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2810013P06Rik down Hypermethylated III isoDMB
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3300002A11Rik down Hypermethylated III isoDMB
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Arhgap27os1 down Hypermethylated III isoDMB
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| 237 |
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B130024G19Rik down Hypermethylated II mDMR
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| 238 |
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BE692007 down Hypermethylated III isoDMB
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| 239 |
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E430024I08Rik down Hypermethylated III isoDMB
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| 240 |
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Gm10804 down Hypermethylated II mDMR
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| 241 |
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Gm37464 down Hypermethylated II mDMR
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| 242 |
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1700047G03Rik up Hypomethylated III isoDMB
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| 243 |
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B430119L08Rik up Hypomethylated II mDMR
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Gm10370 up Hypomethylated II mDMR
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| 245 |
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Gm10603 up Hypomethylated III isoDMB
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| 246 |
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Gm13067 up Hypomethylated II mDMR
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| 247 |
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Gm13375 up Hypomethylated II mDMR
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| 248 |
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Gm42917 up Hypomethylated III isoDMB
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| 249 |
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Gm43050 up Hypomethylated III isoDMB
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| 250 |
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Gm5144 up Hypomethylated III isoDMB
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Gm5627 up Hypomethylated III isoDMB
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Discussion
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Exposure to endocrine-disrupting chemicals has been linked to transgenerational effects, including a predisposition to unfavorable phenotypic traits and the development of diseases, including obesity and other associated comorbidities [21]. In the present study, we analyzed the expression profiles of lncRNAs in the gWAT of F4 mice ancestrally exposed in F0 to obesogenic substances. Previous evidence indicates that epigenetic mechanisms, e.g. DNA methylation, histone methylation, histone retention and the expression of non-coding RNAs may be involved in transgenerational inheritance under the effects of endocrine disruptors [1, 22]. With a particular interest in ncRNA regulation of phenotypes, we used the RNA-Seq data elegantly generated by Chamorro-Garcia et al. [1], and identified a total of 74 differentially expressed lncRNAs in F4 mice ancestrally exposed in F0 to the EDC TBT, and analyzed the expression correlation with their presumptive partner genes, as lncRNAs are known to regulate protein-coding genes [23]. Among the many regulatory roles of lncRNAs [24], the use of transcriptome data affords the investigation of direct effects of lncRNAs on coding transcripts, through the use of target sequence-based prediction and coexpression analyses. In order to investigate the biological functions of these lncRNAs and their gene partners, we performed GO term analysis and pathway enrichment analysis. Pathway analysis showed that some of our DE lncRNAs and their partner genes are primarily involved in glucose and lipid metabolism and in insulin-related pathways, essential in regulating adipogenesis and obesity [25].
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LncRNA Gm6277, upregulated in the TBT group, is correlated with the coding transcript for Slc2a4 (Solute Carrier Family 2 Member 4), also upregulated in the TBT group. Slc2a4 is a member of the solute transporter 2 (facilitated glucose transporter) family and encodes the main glucose transporter present in skeletal and cardiac muscles and adipose tissue, GLUT4. Expression of Slc2a4/GLUT4 is majorly involved in glucose removal from tissues and, consequently, in glycemic homeostasis, playing an important role in the pathophysiology of diseases such as Type 1 and 2 Diabetes Mellitus and Obesity [26]. Downregulation of GLUT4 in obesity is an important factor contributing to impaired insulin-stimulated glucose transport in adipocytes [27]. As reviewed by Yohannes Tsegyie Wondmkun [28], defective insulin receptor signaling is a major component of obesity-associated insulin resistance in humans. Bazhan et al. [29] reported that levels of the gene responsible for glucose uptake in white adipose tissue in mice, Slc2a4, were subject to age-related changes, with Slc2a4 expression increasing from young age to early adulthood and decreasing with age from adulthood onwards. Progression from early to late adulthood is commonly accompanied by an impaired glucose metabolism, including increased plasma insulin levels and impaired glucose tolerance. In agreement, Carvalho et al. [30] showed, also in mice, that reduced expression of Slc2a4 in white adipose tissue is associated with the development of impaired glucose tolerance and insulin resistance, while its overexpression is linked to insulin sensitivity. Insulin stimulates the transport of glucose and the synthesis of triglycerides (lipogenesis), in addition to inhibiting lipolysis, which may be responsible for excessive accumulation of adipose tissue. Thus, insulin resistance in obesity is exhibited by reduced insulin-stimulated glucose transport and metabolism in adipocytes, and by impaired suppression of hepatic glucose production [31]. Kamstra et al. [32] showed in 3T3-L1 cells, that exposure to endocrine disruptors (e.g. EDC BDE-47) increases the expression of specific adipogenesis markers such as Slc2a4, through activation of peroxisome proliferator-activated receptor (PPARγ). We observed that the expression of Slc2a4, a differentiated adipocyte marker gene [33], is potentially regulated by lncRNA Gm6277, and its high expression can be explained by exposure to endocrine disruptors, as described above. Endocrine disrupting chemicals promote adipogenesis by altering fat cell development and/or increasing energy storage in adipose tissue [34], which, in turn, can be inherited by subsequent non-exposed generations, as demonstrated by Chamorro-Garcia et al. [35]. We suggest that regulation of lncRNAs and their gene-partners in the white gonadal adipose tissue of mice ancestrally exposed to the EDC TBT may be related to the control of adipogenesis, suggesting that this regulation may be epigenetically inherited.
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The second lncRNA with the highest number of mRNA targets, the TBT-downregulated Gm10804. Recently, Li and colleagues [36] reported that low expression of Gm10804 improves glucose and lipid metabolism disorders in hepatocytes from mice exposed to high glucose, which is of importance as the liver plays a key role in adjusting glucose levels, in turn affecting energy homeostasis in other tissues [37]. One of the correlated target mRNAs of this lncRNA is the TBT-downregulated Slc27a2 mRNA, also known as FATP2. Slc27a2 plays a key role in lipid metabolism through fatty acid transport and/or activation of very long-chain fatty acids and is linked with activation and/or inhibition of the transcription factors PPARγ (in adipocytes), PPARα (liver) and PPARβ (adipocytes), regulating the expression of several genes involved in lipid metabolism [38]. Further, Choi and colleagues [39] reported in C57BL/6 J mice, that reduced expression of genes involved in lipolysis and uptake and transport of fatty acids (such as Slc27a2) in response to a high-fat diet (HFD) can reduce β-oxidation, resulting in excessive fat accumulation. Chamorro-Garcia et al. [35] have previously demonstrated that exposure of pregnant F0 mice to TBT led to transgenerational effects on the accumulation of lipids in white adipose tissue and liver, and to the increase in expression of hepatic genes involved in the storage/transport of lipids, in all future generations evaluated. Early exposure to endocrine-disrupting chemicals may alter metabolic homeostasis points, predisposing exposed individuals and their offspring to store more fat [40]. Here in our study, we used the RNA-Seq data produced by Chamorro-Garcia et al. [1], from gonadal adipose tissue samples from F4 mice transgenerationally exposed to EDC TBT in F0, which were subjected to a high fat diet challenge (HDF– 21.2% Kcal from fat) for 6 weeks, to assess the interaction between EDC TBT and fat accumulation. Our results suggest that low expression and the positive correlation of the mRNA Slc27a2 with the lncRNA Gm10804 in the gonadal white adipose tissue of mice ancestrally exposed to the obesogenic substance TBT, may alter lipogenic and lipolytic pathways, reflecting in increased fat storage as well as decreased fat mobilization, as observed in these mice. This corroborates previous reports of association of lncRNAs with several metabolic conditions such as obesity, type 1 diabetes mellitus, type 2 diabetes mellitus and non-alcoholic fatty liver disease [41].
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LncRNA Rian, which is orthologous with the lncRNA MEG8 in humans, was down-regulated in our study. One of the correlated target mRNAs of this lncRNA is the TBT-downregulated Inhba, also known as activin A. Activin A is a secreted adipokine composed of two subunits of inhibin βA (INHBA) and is highly expressed in the adipose tissue of obese patients when compared to lean individuals. INHBA is a member of the transforming growth factor-β superfamily and regulates a number of cellular events, including regulation of cancer cell growth and metastasis, apoptosis and, primarily, proliferation and differentiation of human embryonic stem cells. Zaragosi and colleagues [42] analyzed the transcriptome of human adipose tissue-derived stem cells (hMADS) and identified that activin A is expressed in adipose progenitors of various human fat depots and is dramatically downregulated as these progenitor cells undergo adipogenesis. Thus, we suggest that downregulation of mRNA Inhba, positively correlated with the lncRNA Rian, may be associated to excessive accumulation of adipose tissue resulting from exposure to the endocrine disruptor tributyltin and adipogenic pathways.
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Evidence shows that in many complex diseases (e.g. cancer, obesity, diabetes), expression levels of lncRNAs and mRNAs can be significantly altered through DNA methylation, which plays a vital role as an epigenetic regulator [43]. Hernando-Herraez et al. [44] reported that methylation of lncRNA promoters is involved in a variety of biological processes and can lead to silencing or activating their expression. Dysregulation of lncRNA expression, by means of promoter methylation, can directly affect expression of their target mRNAs, or indirectly affect mRNAs controlled by miRNAs that are targets of competing endogenous lncRNAs [45]. Methylation in the promoter region of genes and lncRNAs is a major component of epigenetic regulation, however much less is known about DNA methylation outside of proximal promoters [46]. Albeit less investigated, methylation of regulatory regions outside of promoters are also able to regulate gene expression, as reviewed by Ordoñez and contributors [47]. Chamorro-Garcia et al. [1] analyzed differentially methylated regions (DMRs) and isoDMB regions (genomic regions containing differentially methylated DNA blocks with similar methylation profile) and associated to differentially expressed genes related to metabolism. Using their methylation data, we found DE lncRNAs and mRNAs in regions classified by the authors as regions II and III (Chamorro-Garcia et al., [1]), with 11 lncRNAs and 183 mRNAs that were downregulated by TBT located in hypermethylated regions, and 9 lncRNAs and 58 mRNAs that were TBT-upregulated located in hypomethylated regions. Similar to the findings of Chamorro-Garcia et al. [1], these target mRNAs encode proteins that participate in pathways involved in fatty acid metabolism, such as β-oxidation, citric acid cycle and glycolysis, such as the Slc27a4 mRNA. Our results support and extend the findings of Chamorro-Garcia et al. [1] and suggest that some of the altered expression profiles of mRNAs and lncRNAs, observed transgenerationally following exposure to TBT, could be directly related and partly explained by alterations in methylation profile.
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Conclusions
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Our analyses showed that ancestral exposure to obesogenic substances seems to play an important role in the low and/or high expression of mRNAs, potentially regulated by lncRNAs, which act in the glucose and lipid metabolism pathways, which are directly related to the adipogenesis process. Therefore, further studies are needed on the molecular and biological roles of lncRNAs as potential regulators of white adipose tissue functions.
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Supporting information
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S1 Table (A and B) lncRNAs differentially expressed in contrast to EDC TBT and DMSO control groups.
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(XLSX)
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Click here for additional data file.
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S2 Table Interactions between DE lncRNA and mRNA (Pearson`s correlation r ≥ |0.80|; p-value <0.05).
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(XLSX)
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Click here for additional data file.
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S3 Table lncRNA-mRNA interactions presented significant binding potential (normalized deltaG analysis in LncTar tool (ndG < -0.10)).
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(XLSX)
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Click here for additional data file.
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S4 Table Results of cis lncRNAs-mRNAs pair prediction analysis (performed in the FEELnc tool).
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(XLSX)
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Click here for additional data file.
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S5 Table KEGGs pathways of the top 5 differentially expressed lncRNAs based on their mRNA interaction.
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(XLSX)
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Click here for additional data file.
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==== Refs
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References
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|
| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Genes (Basel)
|
| 4 |
+
Genes (Basel)
|
| 5 |
+
genes
|
| 6 |
+
Genes
|
| 7 |
+
2073-4425
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
10.3390/genes14030683
|
| 11 |
+
genes-14-00683
|
| 12 |
+
Communication
|
| 13 |
+
Droplet Digital PCR Quantification of Selected Intracellular and Extracellular microRNAs Reveals Changes in Their Expression Pattern during Porcine In Vitro Adipogenesis
|
| 14 |
+
Bilinska Adrianna
|
| 15 |
+
https://orcid.org/0000-0003-2833-5083
|
| 16 |
+
Pszczola Marcin
|
| 17 |
+
https://orcid.org/0000-0003-3485-1359
|
| 18 |
+
Stachowiak Monika
|
| 19 |
+
Stachecka Joanna
|
| 20 |
+
Garbacz Franciszek
|
| 21 |
+
https://orcid.org/0000-0002-3789-7937
|
| 22 |
+
Aksoy Mehmet Onur
|
| 23 |
+
https://orcid.org/0000-0002-4238-0414
|
| 24 |
+
Szczerbal Izabela *
|
| 25 |
+
Piórkowska Katarzyna Academic Editor
|
| 26 |
+
Ropka-Molik Katarzyna Academic Editor
|
| 27 |
+
Graphodatsky Alexander S. Academic Editor
|
| 28 |
+
Department of Genetics and Animal Breeding, Poznan University of Life Sciences, 60-637 Poznan, Poland
|
| 29 |
+
* Correspondence: izabela.szczerbal@up.poznan.pl
|
| 30 |
+
09 3 2023
|
| 31 |
+
3 2023
|
| 32 |
+
14 3 68315 12 2022
|
| 33 |
+
27 1 2023
|
| 34 |
+
08 3 2023
|
| 35 |
+
© 2023 by the authors.
|
| 36 |
+
2023
|
| 37 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 38 |
+
Extracellular miRNAs have attracted considerable interest because of their role in intercellular communication, as well as because of their potential use as diagnostic and prognostic biomarkers for many diseases. It has been shown that miRNAs secreted by adipose tissue can contribute to the pathophysiology of obesity. Detailed knowledge of the expression of intracellular and extracellular microRNAs in adipocytes is thus urgently required. The system of in vitro differentiation of mesenchymal stem cells (MSCs) into adipocytes offers a good model for such an analysis. The aim of this study was to quantify eight intracellular and extracellular miRNAs (miR-21a, miR-26b, miR-30a, miR-92a, miR-146a, miR-148a, miR-199, and miR-383a) during porcine in vitro adipogenesis using droplet digital PCR (ddPCR), a highly sensitive method. It was found that only some miRNAs associated with the inflammatory process (miR-21a, miR-92a) were highly expressed in differentiated adipocytes and were also secreted by cells. All miRNAs associated with adipocyte differentiation were highly abundant in both the studied cells and in the cell culture medium. Those miRNAs showed a characteristic expression profile with upregulation during differentiation.
|
| 39 |
+
|
| 40 |
+
adipocytes
|
| 41 |
+
ddPCR
|
| 42 |
+
ECmiRNAs
|
| 43 |
+
mesenchymal stem cells
|
| 44 |
+
pig
|
| 45 |
+
Department of Genetics and Animal Breeding, Faculty of Veterinary Medicine and Animal Science, Poznan University of Life Sciences506.534.09.00 This research was funded by the statutory fund of the Department of Genetics and Animal Breeding, Faculty of Veterinary Medicine and Animal Science, Poznan University of Life Sciences, Poland (no. 506.534.09.00).
|
| 46 |
+
==== Body
|
| 47 |
+
pmc1. Introduction
|
| 48 |
+
|
| 49 |
+
MicroRNAs (miRNAs) are a well-known class of small, noncoding RNAs that regulate post-transcriptional gene expression through mRNA destabilization or inhibition of translation [1]. To date, over 2500 miRNAs have been discovered in the human genome, and it is estimated that they regulate over 60% of protein-coding genes [2]. miRNAs thus play an essential role in all biological processes, including cell differentiation and development [3]. Changes in miRNA expression have been reported in altered physiological conditions and various diseases, so these molecules have been treated as promising therapeutic targets. miRNA-based therapies involve correcting altered miRNA expression levels using mimics or inhibitors [4]. Moreover, miRNAs can be used as biomarkers of pathophysiological conditions [5]. In particular, extracellular miRNAs (ECmiRNAs) can serve as good diagnostic markers due to their stability and ease of sample collection. ECmiRNAs have been detected in cell-free conditions, including cell culture media and biological fluids, such as serum, plasma, saliva, tears, urine, breast milk, etc. [6].
|
| 50 |
+
|
| 51 |
+
The role of miRNAs has been extensively studied in the context of the development of obesity. It has been shown that miRNAs are involved in the control of a range of processes, including adipogenesis, insulin resistance, and inflammation in adipose tissue [7].
|
| 52 |
+
|
| 53 |
+
Dysregulation of many miRNAs has been identified in the adipose tissue of obese individuals [8,9,10]. The presence of adipocyte-related miRNAs in adipocyte-derived microvesicles indicates their involvement in intercellular communication in both paracrine and endocrine manners [10,11,12]. Studies of miRNA in adipocyte tissue have also been conducted on the domestic pig (Sus scrofa), an important animal model for human obesity and also a major livestock species [13]. There are a number of reports on the functioning of individual miRNAs during the formation of fat tissue in the pig (summarized by Song et al. [14]). High-throughput miRNA profiling of porcine adipocyte tissue has also allowed the detection of a complex microRNA–mRNA regulatory network related to fat deposition in pigs [15,16,17,18]. A recent study of the identification of miRNAs in porcine adipose-derived and muscle-derived exosomes showed some miRNAs to be involved in skeletal muscle–adipose crosstalk [19].
|
| 54 |
+
|
| 55 |
+
Most of the research on porcine miRNAs has been carried out on adipose tissues, while studies on in vitro models of adipogenesis are scarce [20]. Due to the heterogeneous nature of adipose tissue—which is composed of several cell types, including adipocytes, preadipocytes, stem cells, endothelial cells, and various blood cells [21]—cultured adipocytes represent a good system for studying molecular events that occur during adipogenesis, including the secretion of miRNA by adipocytes [22]. The aim of this study was thus to quantify eight miRNAs (miR-21a, miR-26b, miR-30a, miR-92a, miR-146a, miR-148a, miR-199a, and miR-383) during porcine in vitro differentiation of mesenchymal stem cells (MSCs) into adipocytes. These miRNAs were selected on the basis of their role in differentiation and inflammation processes (Table 1). The expression of intracellular and extracellular microRNAs was evaluated using droplet digital PCR (ddPCR), a highly sensitive method.
|
| 56 |
+
|
| 57 |
+
2. Materials and Methods
|
| 58 |
+
|
| 59 |
+
2.1. Mesenchymal Stem Cell Culture
|
| 60 |
+
|
| 61 |
+
Mesenchymal stem cells were derived from the adipose tissue (AD-MSCs) of a three-month-old female Polish Large White pig. Tissue sample collection was approved by the Local Ethical Commission for Experiments on Animals at Poznan University of Life Sciences, Poznan, Poland (approval no. 57/2012). Following Stachecka et al. [39], the AD-MSCs were cultured in Advanced DMEM (Gibco, Life Technologies, Grand Island, NY, USA) supplemented with 10% FBS (v/v) (Sigma-Aldrich, St. Louis, MO, USA), 5 ng/mL FGF-2 (PromoCell GmbH, Heidelberg Germany), 2 mM L-glutamine (Gibco), 1 mM 2-mercaptoethanol (Sigma-Aldrich), 1 × antibiotic antimycotic solution (Sigma-Aldrich), and 1 × MEM NEAA (Gibco) at 37 °C in 5% CO2. To avoid the possible influence of FBS-derived miRNAs on obtained results, the same part of filtered FBS was used during the whole cell culture experiment. The AD-MSCs were propagated by passaging using standard cell culture procedures, and their stemness was confirmed by staining for positive (CD44, CD90, CD105) and negative (CD45) markers (Abcam, Cambridge, UK).
|
| 62 |
+
|
| 63 |
+
2.2. Adipogenic Differentiation
|
| 64 |
+
|
| 65 |
+
Adipogenesis was induced by culturing early-passage MSCs in an adipogenic differentiation medium composed of Advanced DMEM (Gibco), 10% FBS (Sigma-Aldrich), 1 × antibiotic antimycotic solution (Sigma-Aldrich), 1 × MEM NEAA (Gibco), 5 ng/mL FGF-2 (PromoCell GmbH), 1 × linoleic acid albumin, 1 × ITS, 1 µm dexamethasone (Sigma-Aldrich), 100 µm indomethacin (Sigma-Aldrich), and 50 mM IBMX (Sigma-Aldrich). The cells were cultured for ten days. Adipogenic differentiation was monitored using visual examination of lipid droplet formation under a phase-contrast microscope (Nikon TS100 Eclipse, Melville, NY, USA) and BODIPY staining. Cells were fixed with 4% paraformaldehyde in PBS (w/v) for ten minutes at room temperature and washed thrice with PBS. The cells were then incubated with BODIPY 493/503 (Thermo Fisher, Waltham, MA, USA) in PBS (3 µg/mL) and washed thrice in PBS. The nuclei were counterstained with DAPI in Vectashield medium (Vector Laboratories, Newark, CA, USA) and examined under a fluorescence microscope (Nikon E600 Eclipse, Melville, NY, USA). Each measurement was performed in triplicate.
|
| 66 |
+
|
| 67 |
+
2.3. RNA Extraction from Cells and Culture Medium
|
| 68 |
+
|
| 69 |
+
Total RNA extraction from cells (approximately 2 × 106 in number) and the cell culture medium (200 µL) was performed on days 0, 2, 4, 6, 8, and 10 of adipogenesis using the miRNeasy Micro Kit (Qiagen, Hilden, Germany), following the manufacturer’s protocol. The RNA samples isolated from cell culture medium were enriched in the fraction of miRNAs, both exosomal and non-exosomal ECmiRNAs. All samples were analyzed in duplicate. The RNA concentrations and quality were assessed using a NanoDrop 2000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA) and Qubit RNA HS Assay Kit (Thermo Fisher Scientific) on a Qubit 2.0 Fluorometer (Thermo Fisher Scientific).
|
| 70 |
+
|
| 71 |
+
2.4. Real-Time PCR
|
| 72 |
+
|
| 73 |
+
One microgram of RNA was reversely transcribed using a Transcriptor High Fidelity cDNA Synthesis kit (Roche Diagnostic, Mannheim, Germany). Primer sets for quantitative real-time PCR for selected protein-coding marker and reference genes (Table S1) were designed using the PRIMER 3 software (http://simgene.com/Primer3 (accessed on 12 May 2022)). The relative transcript levels were assessed using a LightCycler 480 SYBR Green I Master kit (Roche Diagnostic) with a LightCycler 480 II (Roche Life Science). All samples were analyzed in triplicate. Standard curves were designed as tenfold dilutions of the PCR products. Relative transcript levels of the studied genes were calculated after normalization with the transcript level of a reference gene, ribosomal protein L27 (RPL27), which has shown stability during adipogenic differentiation [40,41].
|
| 74 |
+
|
| 75 |
+
2.5. miRNA-Specific Reverse Transcription
|
| 76 |
+
|
| 77 |
+
Reverse transcription was performed with 10 ng of total RNA using a TaqMan MicroRNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA, USA). Reverse transcription reactions were conducted with the use of an RT primer specific to each tested miRNA. The following TaqMan MicroRNA Assays (Applied Biosystems) were employed: miR-21a-5p, (Assay ID: 000397), miR-26b-5p (Assay ID: 000406), miR-30a-5p (Assay ID: 000417), miR-92a-3p (Assay ID: 000431), miR-146a (Assay ID: 005896), miR-148a-3p (Assay ID: 000470), miR-199a-3p (Assay ID: 002304), and miR-383-5p (Assay ID: 000573). RNU6b (Assay ID: 001093) was used as the reference for normalizing the ddPCR results [42]. The reverse transcription reactions were performed following the manufacturers’ recommendations.
|
| 78 |
+
|
| 79 |
+
2.6. Droplet Digital PCR (ddPCR)
|
| 80 |
+
|
| 81 |
+
miRNA quantification was performed using droplet digital PCR (ddPCR). All samples were analyzed in duplicate. Each PCR reaction consisted of 1 µL cDNA, 11 µL of 2 × ddPCR SuperMix for Probes (Bio-Rad, Hercules, CA, USA), 9 µL of H2O, and 1 µL of TaqMan primers and probe from the corresponding TaqMan MicroRNA Assay (Applied Biosystems). The reaction mixtures were divided into approximately 20,000 droplets using a QX200 droplet generator (Bio-Rad) followed by PCR performed on a T100 Thermal Cycler (Bio-Rad) using the following conditions (ramp rate of 2 °C/s): initial denaturation at 95 °C for 10 min, 40 cycles at 94 °C for 30s, followed by 60 °C for 1 min and denaturation at 98 °C for 10 min. A QX200 droplet reader (Bio-Rad) was used to detect fluorescence, and the results were analyzed using QuantaSoft software (Bio-Rad). The fraction of positive droplets was quantified using the Poisson distribution.
|
| 82 |
+
|
| 83 |
+
Since cell culture media may carry miRNAs derived from supplements such as fetal bovine serum (FBS) [43], an experiment on the expression level of the investigated miRNAs in the pure cell culture medium, supplemented with 10% of FBS, was performed. Expression of miR-92a, miR-146a, and miR-26b was not observed, while expression of miR-21a, miR-383, miR-30a, miR-148a, and miR-199a was on very low level (Table S2), which was about 1% of the average expression level of extracellular miRNAs (Table S6). Thus, an additional normalization step was abandoned.
|
| 84 |
+
|
| 85 |
+
2.7. Statistical Analysis
|
| 86 |
+
|
| 87 |
+
Differences between expression levels were assessed separately for each miRNA and for each medium. To give the analyzed variables a normal distribution, the expression levels were transformed by taking the natural logarithm of the original values. The following model was then used to assess the differences between the expression levels on each day:log (Exp) ij = µ + DAY j + sampleID i + error ij,
|
| 88 |
+
|
| 89 |
+
where log (Exp) is the natural logarithm of the expression level recorded on the jth DAY for the ith sampleID. DAY was a categorical variable with six levels (0, 2, 4, 6, 8, 10). The sampleID and error were random terms. The sampleID was treated as random term to account for repeated observations of the sample on following days. The analyses were performed using the R environment [44]. The effects of the model were estimated using the lme4 package [45] and the significance of the differences between days was assessed using the lmerTest [46] and emmeans packages [47], making use of Satterthwaite’s method [48] for approximating degrees of freedom. The p-values for comparing expression levels on particular days were adjusted for multiple comparisons using Tukey’s method for comparing six estimates.
|
| 90 |
+
|
| 91 |
+
To assess whether there was a relationship between the expression level in the medium and cells, the previously used model was updated to include the log-transformed expression in the medium log (Expmedium). The following model was thus used: log (Exp) ij = µ + log (Expmedium) ij + DAY j + sampleID i + error ij.
|
| 92 |
+
|
| 93 |
+
The regression line was obtained by applying the locally weighted scatterplot smoothing method available from the ggplot2 package [49].
|
| 94 |
+
|
| 95 |
+
3. Results
|
| 96 |
+
|
| 97 |
+
Eight miRNAs associated with inflammatory processes (miR-21a, miR-92a, miR-146a, miR-383) and adipocyte differentiation processes (miR-26b, miR-30a, miR-148a, miR-199a) were included in this study (Table 1). The abundances of these miRNAs were determined in cells and in cell culture medium over ten days of adipogenic differentiation (Figure 1).
|
| 98 |
+
|
| 99 |
+
The differentiation process was monitored by evaluating the accumulation of lipid droplets using BODIPY staining (Figure 1 and Figure 2A, Table S3). On day 4, individual cells with lipid droplets were seen, while lipid accumulation was highly abundant from day 6. Adipocyte differentiation was also confirmed by the upregulation of expression of three marker genes: CEBPA, FABP4, and PPARG (Figure 2B, Table S3).
|
| 100 |
+
|
| 101 |
+
The expression of all the miRNAs was successfully detected with the ddPCR method (Figure 3).
|
| 102 |
+
|
| 103 |
+
It was found that, of the miRNAs associated with the inflammatory process, miR-21a showed the highest expression in differentiated adipocytes and was also highly secreted by these cells (Figure 4A,B; Tables S4 and S5). Both intracellular and extracellular miR-21a levels were upregulated during adipogenesis. miR-92a was also highly expressed by adipocytes, reaching its highest level on day 10 of differentiation. The abundance of extracellular miR-92a initially decreased on days 2–4, returned to its original level after day 6, and then decreased (Figure 4C,D; Tables S4 and S5). The expression of miR-146a in the studied differentiation system was quite low (Figure 4E,F; Tables S4 and S5). Cellular miR-146a was upregulated during adipogenesis, but was not secreted by the differentiated cells. The lowest expression level was found for miR-383, and this was comparable in the cells and in the cell culture medium (Figure 4G,H; Tables S4 and S5).
|
| 104 |
+
|
| 105 |
+
In terms of miRNAs associated with adipogenesis, all the molecules we examined here were highly expressed during differentiation (Figure 5; Tables S4 and S5). The highest expression in cells was found for miR-26b, next to miR-199a, miR-148a, and miR-30a. Of these, miR-26b, miR-148a, and miR-30a had the highest expression levels at the end of differentiation (day 10), while for miR-199a this occurred on day 4 of adipogenesis. All extracellular miRNAs had similar expression profiles, reaching the highest level on day 6 of differentiation. miR-199a, miR-30a, and miR-148a were secreted at comparable levels, while the amount of miR-26b was lower.
|
| 106 |
+
|
| 107 |
+
Comparing the expression levels of intracellular and extracellular miRNAs showed higher expression in cells than in the medium for all the studied miRNAs except miR-383 (Table S6). No relationship was found between the expression level of intracellular and extracellular miRNAs (Table S7).
|
| 108 |
+
|
| 109 |
+
4. Discussion
|
| 110 |
+
|
| 111 |
+
To better understand the role of miRNA in adipocyte formation, we examined the expression of the selected intracellular and extracellular miRNAs during adipogenesis, using the domestic pig as a model organism. We employed ddPCR, as a robust method for absolute quantification of miRNAs [50]. This method has proven to be especially useful for quantifying extracellular miRNAs [51,52]. Here, we showed the usefulness of ddPCR for detecting less abundant ECmiRNAs in adipogenic spent medium.
|
| 112 |
+
|
| 113 |
+
We found that, of the studied miRNAs, miR-21a showed the highest expression in differentiated cells, and its expression was very high in the cell culture medium. It has been reported that miR-21 is frequently upregulated in many chronic diseases, including obesity [25]. It plays a pivotal role in the functioning of adipose tissue through its regulation of many biological processes, such as thermogenesis, browning of adipose tissue, angiogenesis, apoptosis, and adipogenesis [53]. A previous study of MSCs isolated from human adipose tissue showed that miR-21 expression increased in the early stages of adipogenic differentiation and gradually decreased after day 3 [24]; in our differentiation system, miR-21a was upregulated throughout the entire differentiation period. Studies of miR-21 mimics and inhibitors as therapeutic agents in obesity treatment have also provided varying results [53,54]. miR-21 has also been depicted as secreted by macrophages of adipose tissue [10], while in this study we confirmed its secretion by adipocytes. Further studies, including of both the intracellular and extracellular form of miR-21a, are thus needed.
|
| 114 |
+
|
| 115 |
+
To date, little has been learned about the role of miR-92a in adipogenesis. There are reports of its involvement in brown adipocyte differentiation [55]. Exosomal miR-92a abundance has also been observed in human serum after cold-induced brown adipose tissue activity [56]. In 3T3L1 cells, the miR-17–92 cluster accelerated adipocyte differentiation by negatively regulating the tumor suppressor Rb2/p130 during the early stages of adipogenesis [57]. Here, we provide evidence that miR-92a alone is upregulated during porcine adipogenesis and is secreted by adipocytes.
|
| 116 |
+
|
| 117 |
+
Recently, miR-146a has been recognized as a potential regulator of porcine intramuscular preadipocytes [58]. The authors reporting this observed that miR-146a-5p mimics inhibited preadipocyte proliferation and differentiation, while the miR-146a-5p inhibitors promoted cell proliferation and adipogenic differentiation. Both that study and our present one found a similar expression pattern for these miRNAs, with the expression peaking in the early stages of adipogenesis (on days 2 or 4 of differentiation, respectively). Interestingly, miR-146a was one of the studied miRNAs that was not secreted by differentiated cells (as was miR-383).
|
| 118 |
+
|
| 119 |
+
Of the studied miRNAs, miR-26b, miR-30a, miR-148a, and miR-199a have been reported as involved in adipocyte formation through their promotion or acceleration of adipogenesis, which they achieve by regulating numerous target genes [27,28,34,59]. Their expression was found to gradually increase after the induction of adipocyte differentiation, as in our study. Only miR-199a reached its highest expression at day 4 of adipogenesis, and its expression then decreased, as confirmed by its function in the proliferation and differentiation of porcine preadipocytes [60]. This miRNA was highly expressed in cells and also secreted more. It seems that this molecule has a comprehensive set of functions and plays a role in a range of different processes, such as angiogenesis, aging, apoptosis, proliferation, and myogenic differentiation [61,62].
|
| 120 |
+
|
| 121 |
+
All the extracellular miR-26b, miR-30a, miR-148a, miR-199a, and miR-92a showed the same expression profiles, with their expression peaking on day 6 of differentiation. It was previously reported that exosomal miRNAs are secreted from hypertrophic adipocytes and transferred to small adipocytes to promote lipogenesis and hypertrophy of emerging adipocytes [63,64]. This may be one reason why high expression of these extracellular miRNAs is observed in the intermediate days of differentiation, when new adipocytes arise at an intense rate. As we found no strong correlation between the expression of intracellular and extracellular miRNAs, it can be anticipated that the secretion of miRNA is an independent process regulated by other mechanisms, such as the formation of extracellular vesicles such as exosomes or transportation via protein–miRNA complexes [65,66].
|
| 122 |
+
|
| 123 |
+
Our study revealed relatively high intercellular variation of miRNA expression (Tables S4–S6, which may be related to the heterogeneity of cell populations in terms of differentiation timing. It has been shown in previous studies that a high standard deviation is found for low-expressed miRNA [67]. Application of new methods, such as single-cell microRNA–mRNA co-sequencing, revealed that microRNA expression variability might be responsible alone for non-genetic cell-to-cell heterogeneity [68]. The authors found that miRNAs with low expression levels showed inherently large standard deviations, while the variation of high-abundance miRNAs gradually decreased as the expression level increased.
|
| 124 |
+
|
| 125 |
+
It has been shown that the miRNA expression profile can serve as a signature of cell identity, through the expression of a unique miRNA. However, this would seem to be difficult to apply to adipose tissue, as it expresses a wide range of miRNAs [65,69]. Our study of cultured adipocytes allowed us to obtain more detailed knowledge of the relationship between the intracellular and extracellular microRNAs that are expressed during the formation of adipocyte cells. Taking into account the fact that miRNAs from adipose tissue participate in intercellular and interorgan communications, and that their aberrant expression may lead to pathological conditions, further comprehensive studies of extracellular and intracellular miRNAs are needed.
|
| 126 |
+
|
| 127 |
+
5. Conclusions
|
| 128 |
+
|
| 129 |
+
We showed that miRNAs associated with adipogenesis and inflammation processes are expressed by differentiated adipocytes. Both intracellular and extracellular miRNAs have characteristic expression profiles during porcine adipogenesis. We found that there is no relationship between the expression level of intracellular miRNAs and the levels of extracellular miRNAs. ddPCR proved a useful method of quantifying miRNAs during in vitro adipogenesis, especially for less abundant extracellular miRNAs.
|
| 130 |
+
|
| 131 |
+
Acknowledgments
|
| 132 |
+
|
| 133 |
+
We wish to thank Magdalena Noak for her technical assistance.
|
| 134 |
+
|
| 135 |
+
Supplementary Materials
|
| 136 |
+
|
| 137 |
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The following supporting information can be downloaded from https://www.mdpi.com/article/10.3390/genes14030683/s1. Table S1: PCR primers used to study the expression level of adipocyte differentiation marker genes. Table S2: Expression levels of miRNAs in cell culture medium supplemented with 10% of fetal bovine serum (FBS). SE—standard error; Table S3: Lipid droplet content and relative gene expression of CEBPA, FABP4, and PPARG genes across the consecutive days of experiment (supplementary to Figure 2). The regression slope and p-values were obtained using the locally weighted scatterplot smoothing method of the ggplot2 package. Table S4: Expression levels of intracellular miRNAs over the course of differentiation. The comparisons were made between days of the experiment for one miRNA at a time, and so the table should be read column by column. The same letters indicate an absence of significant difference (at the 0.05 level) between the expression levels; Table S5: Expression levels of extracellular miRNAs over the course of differentiation. The comparisons were made between days of the experiment for one miRNA at the time, so the table should be read column by column. The same letters indicate an absence of significant difference (at the 0.05 level) between the expression levels; Table S6: Expression levels of intracellular and extracellular miRNAs. The comparisons were made between miRNAs, so the table should be read row by row. The same letters indicate an absence of significant difference (at the 0.05 level) between the expression levels; Table S7: Relationship between the expression in the medium and cells based on regression slopes for the log-transformed expression in the medium on the log-transformed expression in cells for different miRNA.
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Click here for additional data file.
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Author Contributions
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Conceptualization: I.S., M.P. and M.S.; methodology: A.B., M.P., M.S., J.S. and I.S.; formal analysis: A.B., M.P., M.S., J.S. and I.S.; investigation: A.B., M.P., M.S., J.S., F.G., M.O.A. and I.S.; writing—original draft preparation: I.S., M.P., M.S. and A.B.; writing—review and editing: I.S.; visualization: A.B., M.P., M.S., J.S., F.G., M.O.A. and I.S.; supervision: I.S.; project administration: I.S.; funding acquisition: I.S. All authors have read and agreed to the published version of the manuscript.
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Institutional Review Board Statement
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Not applicable.
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Informed Consent Statement
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Not applicable.
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Data Availability Statement
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The data supporting the findings of the study are available from the corresponding author (I.S.), upon reasonable request.
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Conflicts of Interest
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The authors declare no conflict of interest.
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Figure 1 The adipocyte differentiation experiment. Mesenchymal stem cells (MSCs, day 0 of differentiation) were treated with adipogenic hormonal inducers and were cultured for ten days. Cells and media were collected for total RNA isolation on days 0 (A), 2 (B), 4 (C), 6 (D), 8 (E), and 10 (F). Representative images were taken after staining the lipid droplets with BODIPY 493/503 (green); the nuclei were counterstained with DAPI (blue). Scale bar: 50 µm.
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Figure 2 Monitoring of adipocyte differentiation. (A) Lipid droplet accumulation was quantified by measuring BODIPY 493/503/DAPI fluorescent intensity. Error bars show SDs. The error bars represent standard deviations. (B) Measurements of the relative transcript level of three genes: CEBPA, FABP4, and PPARG. Each dot represents relative expression (mean of 3 repeats). The line is simple linear regression based on the collected data points and the gray area represents the 0.95 confidence interval for the regression line.
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Figure 3 Examples of the detection of miRNAs using the ddPCR method. Absolute quantification (concentration in copies/µL) of miR-148a in cells (A) and cell culture medium (B) at days 0 (d0), 2 (d2), 4 (d4), 6 (d6), 8 (d8), and 10 (d10). NC: negative control (sample without cDNA template). Error bars indicate the Poisson 95% confidence intervals.
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Figure 4 Relative expression levels of extracellular and intracellular miRNAs related to inflammation during the ten days of adipocyte differentiation. The expression of miR-21a (A,B), miR-92a (C,D), miR-146a (E,F), and miR-383 (G,H) was normalized using RNU6B. Dots represent the actual measurements, the line is a local regression based on the collected data points, and the gray area represents the 0.95 confidence interval for the regression line.
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Figure 5 Relative expression levels of extracellular and intracellular miRNAs related to adipogenesis during the ten days of adipocyte differentiation. The expression of miR-26b (A,B), miR-30a (C,D), miR-199a (E,F), miR-148a (G,H) was normalized using RNU6B. Dots represent the actual measurements, the line is a local regression based on the collected data points, and the gray area represents the 0.95 confidence interval for the regression line.
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genes-14-00683-t001_Table 1 Table 1 Characteristics of the analyzed miRNAs.
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microRNA Function Reference
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miR-21a modulates inflammation, regulates adipogenic differentiation, and is upregulated in obesity [23,24,25]
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miR-26b mediates the multiple differentiation of MSCs and promotes adipocyte differentiation [26,27]
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miR-30a accelerates adipogenesis and promotes fatty acid and glucose metabolism in adipocytes [28,29]
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miR-92a controls inflammatory response and inhibits adipose browning [30,31]
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miR-146a plays a role in inflammatory process in various disorders and is upregulated in obesity [32,33]
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miR-148a regulates MSC differentiation into adipocytes, a biomarker of obesity [34,35]
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miR-199a regulates adipocyte differentiation and fatty acid composition during adipogenesis [36,37]
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miR-383 its expression correlates with various inflammatory diseases [38]
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Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
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==== Refs
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
J Funct Biomater
|
| 4 |
+
J Funct Biomater
|
| 5 |
+
jfb
|
| 6 |
+
Journal of Functional Biomaterials
|
| 7 |
+
2079-4983
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
36976086
|
| 11 |
+
10.3390/jfb14030162
|
| 12 |
+
jfb-14-00162
|
| 13 |
+
Article
|
| 14 |
+
Adipogenesis-Related Metabolic Condition Affects Shear-Stressed Endothelial Cells Activity Responding to Titanium
|
| 15 |
+
Pinto Thaís Silva Methodology Validation Investigation Writing – review & editing
|
| 16 |
+
Gomes Anderson Moreira Methodology Formal analysis Investigation Writing – original draft
|
| 17 |
+
de Morais Paula Bertin
|
| 18 |
+
https://orcid.org/0000-0002-4149-5965
|
| 19 |
+
Zambuzzi Willian F. Writing – original draft Supervision Project administration Funding acquisition *
|
| 20 |
+
Nakai Masaaki Academic Editor
|
| 21 |
+
Lab. of Bioassays and Cellular Dynamics, Department of Chemical and Biological Sciences, Institute of Biosciences, UNESP—São Paulo State University, Botucatu 18618-970, SP, Brazil
|
| 22 |
+
* Correspondence: w.zambuzzi@unesp.br
|
| 23 |
+
17 3 2023
|
| 24 |
+
3 2023
|
| 25 |
+
14 3 16219 1 2023
|
| 26 |
+
14 3 2023
|
| 27 |
+
16 3 2023
|
| 28 |
+
© 2023 by the authors.
|
| 29 |
+
2023
|
| 30 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 31 |
+
Purpose: Obesity has increased around the world. Obese individuals need to be better assisted, with special attention given to dental and medical specialties. Among obesity-related complications, the osseointegration of dental implants has raised concerns. This mechanism depends on healthy angiogenesis surrounding the implanted devices. As an experimental analysis able to mimic this issue is currently lacking, we address this issue by proposing an in vitro high-adipogenesis model using differentiated adipocytes to further investigate their endocrine and synergic effect in endothelial cells responding to titanium. Materials and methods: Firstly, adipocytes (3T3-L1 cell line) were differentiated under two experimental conditions: Ctrl (normal glucose concentration) and High-Glucose Medium (50 mM of glucose), which was validated using Oil Red O Staining and inflammatory markers gene expression by qPCR. Further, the adipocyte-conditioned medium was enriched by two types of titanium-related surfaces: Dual Acid-Etching (DAE) and Nano-Hydroxyapatite blasted surfaces (nHA) for up to 24 h. Finally, the endothelial cells (ECs) were exposed in those conditioned media under shear stress mimicking blood flow. Important genes related to angiogenesis were then evaluated by using RT-qPCR and Western blot. Results: Firstly, the high-adipogenicity model using 3T3-L1 adipocytes was validated presenting an increase in the oxidative stress markers, concomitantly with an increase in intracellular fat droplets, pro-inflammatory-related gene expressions, and also the ECM remodeling, as well as modulating mitogen-activated protein kinases (MAPKs). Additionally, Src was evaluated by Western blot, and its modulation can be related to EC survival signaling. Conclusion: Our study provides an experimental model of high adipogenesis in vitro by establishing a pro-inflammatory environment and intracellular fat droplets. Additionally, the efficacy of this model to evaluate the EC response to titanium-enriched mediums under adipogenicity-related metabolic conditions was analyzed, revealing significant interference with EC performance. Altogether, these data gather valuable findings on understanding the reasons for the higher percentage of implant failures in obese individuals.
|
| 32 |
+
|
| 33 |
+
bone
|
| 34 |
+
wound healing
|
| 35 |
+
adipogenesis
|
| 36 |
+
obese
|
| 37 |
+
dental implants
|
| 38 |
+
titanium
|
| 39 |
+
failure
|
| 40 |
+
angiogenesis
|
| 41 |
+
Fundação de Amparo à Pesquisa do Estado de São Paulo-FAPESP2019/26854-2 2014/22689-3 Conselho Nacional de Desenvolvimento Científico e Tecnológico314166/2021-1 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes)code 1 Fundação de Amparo à Pesquisa do Estado de São Paulo-FAPESP (FAPESP: 2019/26854-2; 2014/22689-3), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq–Bolsa Produtividade em Pesquisa, 314166/2021-1), and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Capes), code 1.
|
| 42 |
+
==== Body
|
| 43 |
+
pmc1. Introduction
|
| 44 |
+
|
| 45 |
+
Physiological changes in obese patients are widely studied due to their systemic complications. The comorbidities known to be associated with obesity include cardiovascular, pulmonary, renal, endocrine, and musculoskeletal problems (e.g., arthrosis, osteoarthritis, back and joint pain), as well as impaired wound healing [1]. It is known that the adipose tissue develops endocrine activity by secreting bioactive substances, named adipokines, that can reach all systems and develop important roles in metabolism [2]. In obese individuals there is a dysfunction of the adipose tissue, presenting higher adipogenesis (high number and size of adipocytes, as well as intracellular fat droplets) that directly affects the profiles of released adipokines, including an increase in proinflammatory interleukin secretion, which triggers different responses systemically, including in the cardiovascular system and vasculature [3].
|
| 46 |
+
|
| 47 |
+
The vasculature exerts an important function in supplying blood to the whole body, delivering oxygen, nutrients, and essential factors to ensure adequate physiologic and metabolic functioning, also guaranteeing adequate tissue regeneration and repair in cases of injuries, when the vasculature also provides undifferentiated cells [4]. In this context, the endothelial cells (ECs), present along the luminal surface of the blood vessels, develop a central role in vascular activity by perceiving and responding to the changes in chemical and mechanical factors in the blood [5,6,7,8]. It is important to mention that angiogenesis is a decisive event during tissue healing [9] and it has been shown that ECs differently respond to metallic implantable medical devices, such as titanium alloys [10,11,12].
|
| 48 |
+
|
| 49 |
+
Titanium is commonly used as a biomaterial in several dental and medical fields, e.g., implantology, orthopedics, cardiology, and gastroenterology [13]. This metallic alloy is considered the gold standard for these purposes because it possesses important properties such as mechanical and corrosion resistance and proper biocompatibility [14]. After biomaterial implantation, the reactional tissue surrounding the implants suffers adaptation processes that require blood supplements through the blood vessels, highlighting the importance of EC activities and angiogenesis [15]. In addition, studies have revealed that angiogenesis and osteogenesis are coupled processes, and shown that better osseointegration occurs by interfering with the process of appositional new bone growth [16]. This coupling between cells seems to be affected in specific metabolic conditions, such as diabetes and obesity.
|
| 50 |
+
|
| 51 |
+
In fact, obesity is related to severe complications in the process of bone healing and osseointegration, likely because it provokes a burst of pro-inflammatory involvement, and an increased risk of bone loss [17]. The explanation for the obesity-related tissue regeneration complications lies in the effects of the unbalanced adipose-derived proinflammatory cytokines and adipokines [18], however, the biology involved in this context is barely known.
|
| 52 |
+
|
| 53 |
+
Thus, studies exploring the metabolic effects of high adipogenicity on different systems are needed, as well as strategies and alternative technologies and methodologies to study these conditions and predict biological responses. In this context, in vitro methods and analyses, such as cell culture, have the relevant advantages, despite presenting a huge set of limitations in comparison to in vivo protocols arising from age, genetics, environments, habits, hormones, etc. Furthermore, many in vitro methodologies capable of mimicking or closely addressing scenarios in biological systems, as well as in the presence of pathologies, have been proposed and used to guide preclinical experiments.
|
| 54 |
+
|
| 55 |
+
Using in vitro methodologies, we investigated the potential crosstalk between adipogenicity-related metabolic conditions and ECs responding to a titanium-enriched medium. Specifically, we demonstrate the proof of concept of the creation of the high-adipogenicity model using an adipocyte cell line, and observed its interference with EC activity. Altogether, these data gather new findings to understand the higher rate of failure of implants in obese individuals.
|
| 56 |
+
|
| 57 |
+
2. Methods
|
| 58 |
+
|
| 59 |
+
2.1. Implants
|
| 60 |
+
|
| 61 |
+
This experimental workflow was performed using two titanium surfaces, as follows: Dual Acid-Etched (DAE) and nanohydroxyapatite-coated surfaces (nHA). Both set of titanium discs were kindly provided by S.I.N.—Sistema Nacional de Implantes (Sao Paulo, SP, Brazil). The nHA titanium surface is described in more detail elsewhere by Gottlander et al. (1997) and Meirelles et al. (2008) [19,20].
|
| 62 |
+
|
| 63 |
+
2.2. Reagents
|
| 64 |
+
|
| 65 |
+
Dulbecco’s modified Eagle’s medium (DMEM), Fetal Bovine Serum (FBS), trypsin, penicillin, and streptomycin (antibiotics) were obtained from Nutricell (Campinas, Sao Paulo, Brazil). Trypan Blue (T6146), acetic acid glacial (695092), (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) (MTT) (M2128), ethanol (459844), Oil Red O (O0625), 3-isobutyl-1-methylxanthine (IBMX) (I5879), Dexamethasone (D1756), β-glycerophosphate (G9422), glucose (G-5400) and insulin (I2643) were obtained from Sigma Chemical Co. (St. Louis, MO, USA). The antibodies #9102, #8690, #3700, and #2109 were obtained from Cell Signaling Technology (Beverly, MA, USA). TRIzol™ reagent (15596026), DNase I (18068015), and the High-Capacity cDNA Reverse Transcription Kit (4368814) were purchased from Thermo Fisher Scientific Inc. (Waltham, MA, USA). GoTaq qPCR Master Mix (A6002) was obtained from PROMEGA (Madison, WI, USA). Oligonucleotides for gene expression were purchased from Exxtend (Campinas, São Paulo, Brazil).
|
| 66 |
+
|
| 67 |
+
2.3. Cell Culture
|
| 68 |
+
|
| 69 |
+
Two cell lines were used in this study: both 3T3-L1 preadipocytes (passage < 10) and Human Umbilical Vein Endothelial Cells (HUVECs; ECs) (ATCC; CRL1730; passage < 10) were cultured in Dulbecco’s modified Eagle’s medium (DMEM—Nutricell, Campinas, Brazil) containing penicillin 100 U/mL, streptomycin 100 mg/mL, and 10% fetal bovine serum (FBS). The adipocyte differentiation is described below. Importantly, ECs were cultured subjected to a shear stress model, as is described in detail below. In all experiments, the cells were maintained at 37 °C with a 5% CO2 and 95% humidity environment.
|
| 70 |
+
|
| 71 |
+
2.4. Adipocyte Differentiation
|
| 72 |
+
|
| 73 |
+
The 3T3-L1 adipocyte cultures were maintained in 100 mm culture dishes in DMEM supplemented with 10% FBS and 1% penicillin/streptomycin at 37 °C, 5% CO2, and 95% humidity until reaching proper confluence. Then, adipocyte differentiation was induced by supplementing the cell culture medium with insulin (1 mg/mL), dexamethasone (1 mM), and 3-isobutyl-1-methylxanthine (IBMX) (0.5 mM), which was used to expose the cells for 3 days. The medium was changed to maintenance DMEM containing 10% FBS and insulin (1 mg/mL) for an additional 7 days (completing 10 days in toto), being changed every 2 days in the meantime. This differentiation process was followed under 2 separate experimental conditions; one under normal conditions (Ctrl), and the other subjected to a high-glucose medium (HGM) to induce higher adipogenesis, reaching a final glucose concentration of 50 mM. The cultures were maintained up to 10 days, at which point the cells were harvested and the conditioned medium collected to further expose ECs.
|
| 74 |
+
|
| 75 |
+
2.5. Shear Stress Model
|
| 76 |
+
|
| 77 |
+
ECs were seeded in the peripheral area of previously modified 100 mm culture dishes (Figure 1). The modification in the 100 mm culture dishes was made by using medical silicone to bond a 60 mm culture dish at the center-bottom of the 100 mm culture dishes. Thereafter, the modified dishes were sterilized using UV light for 30 min. To perform the model, the ECs were exposed to the tension forces induced by the circuit of shear stress triggered by the rotations of an orbital shaker (Scilogex, Rocky Hill, CT, USA) placed in the cell culture incubator, as in other experiments [21,22]. We calculated the maximal wall shear stress of ~3 Pa (physiological arterial shear stress = ~1–4 Pa) by using this equation: τmax = α√ρη(2πʄ)3. This equation encompasses the τmax that is the shear stress (Pascal), α is the radius of orbital rotation (12 cm), ρ is the density of the cell culture medium (937.5 kg/m3), η is the viscosity of the cell culture medium (7.5 × 10−4 Pa s), and ʄ is the frequency of rotation.
|
| 78 |
+
|
| 79 |
+
2.6. Cell Viability Assay
|
| 80 |
+
|
| 81 |
+
The high-glucose medium was prepared previously at 50 mM final concentration. Concomitantly, the 3T3-L1 adipocytes were maintained on 96-well plates (5 × 104 cells/mL) and later incubated for up to 24 h. One group of cells was treated with the HGM to evaluate whether the high glucose concentration would affect cell viability. The control group contained cells under normal cell culture conditions. The cells were maintained in both treatments (Ctrl and HGM 50 mM) for up to 72 h, after which the cell viability was measured by adding 1 mg/mL of 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) to evaluate the mitochondrial dehydrogenase activity through the MTT reduction reaction after 3 h in a CO2 incubator. During this reaction, the yellow-colored water-soluble tetrazolium salt MTT becomes the purple-colored soluble compound formazan proportional to mitochondrial activity. The dye of formazan was later dissolved in DMSO, and the absorbance was measured at 570 nm (Synergy II; BioTek Instruments, Winooski, VT, USA).
|
| 82 |
+
|
| 83 |
+
2.7. Oil Red O Staining
|
| 84 |
+
|
| 85 |
+
Previously, Oil Red O solution was obtained by dissolving the Oil Red O dye in propylene glycol (0.5%; w/v) in a heater at 95 °C. By using a 0.45 μm syringe filter the Oil Red O solution was filtered to eliminate residual particulates from the solution and later used to stain the adipocytes. Adipocytes were differentiated for 10 days using a 24-well plate. At the end of differentiation, the medium was removed, the cells were washed with warm PBS, fixed in 4% paraformaldehyde for 10 min at room temperature, washed twice in deionized water, and then maintained in absolute propylene glycol for 5 min. The cells were stained in Oil Red O solution 0.5% up to 30 min at room temperature, then washed in 85% propylene glycol solution for 3 min. Finally, 3T3-L1 was washed twice in deionized water. Images were acquired using an inverted microscope (Axio Vert.A1, Carl Zeiss microscopy GMBH, Göttingen, Germany).
|
| 86 |
+
|
| 87 |
+
2.8. Titanium-Enriched Medium Obtaining
|
| 88 |
+
|
| 89 |
+
Adipocyte-related conditioned medium was later used to incubate both types of titanium disc for 24 h: DAE and nHA, in accordance with ISO 10993:2016 (0.2 g/mL w/v) with slight modification as suggested by Zambuzzi et al. [23,24,25,26]. The final conditioned medium was later used to expose ECs for 3 days under shear stress to mimic blood flow.
|
| 90 |
+
|
| 91 |
+
2.9. Western Blot
|
| 92 |
+
|
| 93 |
+
Both adipocytes and ECs were harvested using lysis buffer [Lysis Cocktail (50 mM Tris [tris(hydroxymethyl)aminomethane]–HCl [pH 7.4], 1% Tween 20, 0.25% sodium deoxycholate, 150 mM NaCl, 1 mM EGTA (ethylene glycol tetraacetic acid), 1 mM O-Vanadate, 1 mM NaF, and protease inhibitors [1 μg/mL aprotinin, 10 μg/mL leupeptin, and 1 mM 4-(2-amino-ethyl)-benzolsulfonylfluorid-hydrochloride])] for 2 h, after which the samples were cleared by centrifugation, and the protein concentration was measured using the Lowry method [27]. An equal volume of 2x sodium dodecyl sulfate (SDS) gel loading buffer (100 mM Tris-HCl [pH 6.8], 200 mM dithiothreitol [DTT], 4% SDS, 0.1% bromophenol blue, and 20% glycerol) was added to the samples and boiled for 5 min. Aliquots of protein extracts were resolved into SDS-PAGE (10 or 12%) and transferred to PVDF membranes (Millipore, Burlington, MA, USA). Membranes were blocked with either 5% fat-free dried milk dissolved in Tris-buffered saline (TBS)–Tween 20 (0.05%) and incubated overnight at 4° C with appropriate primary antibody at 1:1000 dilutions. After washing 3x TBS-Tween 20 (0.05%), those membranes were incubated with horseradish peroxidase-conjugated secondary IgGs antibodies, at 1:5000 dilutions, in a blocking buffer for 1 h. Thereafter, the bands were detected by enhanced chemiluminescence (ECL), or by fluorescence (ODYSSEY® CLx Infrared Imaging System).
|
| 94 |
+
|
| 95 |
+
2.10. Quantitative PCR Assay (qPCR)
|
| 96 |
+
|
| 97 |
+
The same experimental workflow was performed and the cells were harvested now in Ambion TRIzol Reagent (Life Sciences—Fisher Scientific Inc, Waltham, MA, USA), and treated with DNase I (Invitrogen, Carlsband, CA, USA). cDNA synthesis was performed using High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA, USA) following the manufacturer’s instructions. qPCR was performed on a total of 10 μL, containing PowerUp™ SYBR™ Green Master Mix 2x (5 μL) (Applied Biosystems, Foster City, CA, USA), 0.4 μM of each primer, and 50 ng of cDNA and nuclease-free H2O. Data were expressed as relative amounts of each target gene normalized considering the expression of 18SrRNA and Gapdh genes, here used as housekeeping genes, using the cycle threshold (Ct) method. Specific primers and running details are described in Table 1.
|
| 98 |
+
|
| 99 |
+
2.11. Oxidative Stress Markers
|
| 100 |
+
|
| 101 |
+
After obtaining adipocytes, the cells were harvested in PBS and sonicated. Protein carbonylation (CBO) was measured by using DNPH (2,4-dinitrophenyl hydrazine) as derivatizing agent [28]. The experiment was performed in a dark chamber to prevent the light. Firstly, the samples (10 µL of the lysed cells) were incubated with DNPH 10 mM (100 µL) for 10 min, after which 50 µL of 6 M NaOH (sodium hydroxide) was added. The reaction was interrupted after 10 min. The CBO was estimated by reading the final solution coloration spectrophotometrically at 450 nm. Finally, the results were calculated using the molar extinction coefficient (22,000 M−1 cm−1) of DNPH and expressed as nmol/mg protein.
|
| 102 |
+
|
| 103 |
+
2.12. Matrix Metalloproteinases (MMPs) Activities by Zymography
|
| 104 |
+
|
| 105 |
+
Differentiating adipocyte cell culture medium was collected to measure the activity of matrix metalloproteinases (MMPs). The conditioned medium was centrifuged at 14,000 rpm for 15 min to avoid cell debris, and the protein concentration was determined using the Lowry method [27]. The same concentration of protein was resolved into a 12% polyacrylamide gel containing 4% gelatin. The gelatinolytic activity of MMPs was determined in the resolved proteins (bands). The proteins’ structures were renatured in Triton X-100 aqueous solution (2% w/v) for 40 min, followed by incubation for 18 h in proteolysis buffer (Tris-CaCl2) at 37 °C, when the gels were stained using Coomassie Blue R-250 dye solution 0.05% for 3 h. Thereafter, the stained gels were washed in a 30% methanol (v/v) and 10% glacial acetic acid solution (v/v). The opposite staining (clear bands) was obtained in the gels exactly where there was the gelatinolytic activity (bands) of MMP2 (~62 kDa) and MMP9 (~84 kDa), and then they were analyzed using the software ImageJ (Bethesda, MD, USA), as previously proposed [29].
|
| 106 |
+
|
| 107 |
+
2.13. Statistical Analysis
|
| 108 |
+
|
| 109 |
+
Data were expressed as mean ± standard error of the mean (SEM) of the replicates of each experiment (n = 3). The samples assumed a normal distribution, and they were subjected to Student’s t-test (two-tailed) with p < 0.05 considered statistically significant. In the experiment where there were more than two groups, the statistical analyses were performed using either analysis of variance (one-way ANOVA) combined with appropriate Bonferroni’s correction post-test, or nonparametric analysis. A p < 0.05 was considered to be statistically significant. The software used was GraphPad Prism 7 (GraphPad Software, La Jolla, CA, USA).
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3. Results
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To better evaluate the molecular mechanism underlying EC response to high-adipogenesis conditions concomitant to a titanium-enriched medium, we proposed an in vitro experimental model subjecting adipocyte cells to differentiation under two conditions: Control cultures (Ctrl) and high-glucose treated cells (H_Adip). Furthermore, the adipocyte-obtained medium was enriched by titanium and then used to expose semiconfluent EC cultures dynamically responding to mechanotransduction mimicking blood flow [22]. Additionally, the titanium-enriched medium was obtained using two different titanium-modified surfaces: DAE, in which the discs were subjected to dual acid-etching, and nHA, in which DAE surfaces were covered by nano-hydroxyapatite [11,30,31], as we have shown previously.
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3.1. Validation of the High-Adipogenesis Model
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To validate the proposed high-adipogenesis model, we first analyzed classical biomarkers of adipocyte phenotype in cells responding to high-glucose exposition, which did not affect their viability (Figure 2A). Oxidative stress markers and fat droplet staining were analyzed and correlated with inflammatory profile and adipogenesis. Reactive oxygen species and concomitant oxidative stress in adipocytes was better investigated by evaluating the protein carbonylation profile. Our data show that this parameter was significantly affected in cells responding to the high-glucose exposure, with higher values than the conventional condition (Ctrl) (Figure 2B). Images acquired by using light microscopy show that adipocytes responding to the high-glucose medium presented a higher number of bigger-sized intracellular fat droplets stained by Oil Red O dye (Figure 2C).
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Adipocyte differentiation and inflammation signaling pathways are widely studied regarding obesity concerns. Herein, the gene expression was evaluated by investigating the behavior of the interleukins IL-1β, IL-6, IL-13, IL-18, and IL-33 genes. They were significantly higher in cells responding to the adipogenesis model where pre-adipocytes were exposed to the high-glucose medium (HGM) (Figure 3A–E), as well as considering TNF-α gene expression (Figure 3G). Importantly, the expression activity of the PPAR-γ gene was also investigated in this study. It was significantly higher in cells responding to HGM (Figure 3J), while both Myd88 and IL1 receptor genes expression were lower in the HGM group (Figure 3F,I), and NFkB remains unchanged (Figure 3H).
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We also investigated the behavior of mitogen-activated protein kinase (MAPKs) genes to infer about cell survival signaling in differentiated adipocytes. Our data show that there is a higher profile of MAPK-ERK proteins in cells responding to HGM (Figure 4A,B), while the MAPK-P38 protein remains unchanged (Figure 4C,D). Finally, the perspective of extracellular matrix (ECM) remodeling was investigated by analyzing the activities of matrix metalloproteinases (MMPs) through gelatin-based proteolysis assay. Our data show that there is higher activity of both MMP2 and 9 in differentiated adipocytes (Figure 4E–J).
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3.2. Angiogenesis-Related Genes Were Evaluated in ECs Responding to High Adipogenesis and Titanium
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To analyze the behavior of ECs responding to high-adipogenesis and titanium-enriched mediums, we first evaluated angiogenesis-related genes and viability. The Ctrl group now refers to the adipocyte-conditioned medium subjected to normal conditions, while the H_Adip group refers to the adipocyte-conditioned medium chronically responding to high glucose concentrations (50 mM); furthermore, the DAE and nHA refer to the adipocyte-conditioned medium previously used to incubate titanium discs with respect to the difference on their surfaces: H_Adip + DAE and H_Adip + nHA. The VEGF gene remains unchanged when compared to Ctrl or when the cells were treated with either of the titanium-enriched mediums (Figure 5A). In this way, the VEGFr1 gene remains unchanged when compared to the Ctrl group, but significantly decreases in response to both nHA and H_Adip + nHA groups when compared to H_Adip (Figure 5B).
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3.3. Proliferation and Survival-Related Genes in ECs
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The protein kinase B (AKT), cyclin-dependent kinase 2 (CDK2), and CDK4 genes were significantly higher in ECs exposed to adipocyte-conditioned medium (H_Adip) (Figure 6A–C). Thereafter, our data show that there is a significant involvement of the AKT gene in the coupling of adipogenicity and titanium-enriched medium (Figure 6A). Thereafter, the CDK genes presented a very similar profile between DAE and nHA, with CDK2 being higher in nHA (Figure 6B), and CDK4 expressing a very similar profile (Figure 6C).
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MAPK genes were also investigated in ECs. Figure 7 shows there is a significant modulation in response to the coupling between high-adipogenicity and titanium-enriched medium. The titanium DAE-enriched medium increased the expression of the MAPK-ERK gene independently of normal or high-adipogenicity conditions (Figure 7A). ECs required MAPK-JNK gene expression when they were exposed to the DAE-enriched medium under normal adipogenesis conditions (DAE) when compared to H_Adip group, but without difference in the H_Adip + DAE group, while cells responding to nHA and H_Adip + nHA remain unchanged (Figure 7B). The MAPK-P38 gene showed involvement but without statistically significant changes when the groups were compared to the Ctrl group, showing an increase only in the DAE group when compared to H_Adip (Figure 7C).
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As c-Src kinase is related to the survival mechanism governing the viability of eukaryotic cells, we decided to evaluate whether this protein was involved in response to the titanium-enriched medium under normal and high-adipogenesis conditions. Additionally, our data show that c-Src seems to be required in high-adipogenesis conditions regardless of the presence of the titanium DAE-enriched medium as it remained higher in the group H_Adip + DAE (Figure 8A,B). Moreover, in the titanium nHA-enriched medium, the cells under high adipogenesis showed a significant difference when compared with Ctrl (Figure 8).
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3.4. Endothelial Cell Appears to Be Important in Inflammatory Gene Microenvironment
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The interleukins IL-6 and IL1-β genes were evaluated using RT-qPCR technology. This revealed an important modulation in ECs responding to different treatments. The IL-6 gene was significantly higher when ECs were treated with titanium DAE and nHA under the high-adipogenesis condition (Figure 9A). The IL-1β gene was also significantly higher in the high-adipogenesis condition, a situation that seems to be controlled in the presence of the titanium-enriched medium, whether considering DAE or nHA (Figure 9B).
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4. Discussion
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The experimental model proposed in this study permits the evaluation of the effect of high adipogenesis in the ECs responding to a titanium-enriched medium. The adipocyte differentiation under high-glucose conditions has been used as a tool in vitro to understand obesity-related metabolic dysfunctions [32], once the glucose enhances lipid accumulation and adipogenesis [33]. Regarding the validation of this alternative model, the adipocyte exposed to high glucose concentrations in our model significantly modulated specific interleukin gene expression as well as the PPAR-γ gene activation. These genes are related to adipocyte differentiation [34]. Taken together, this validates our biological model for obtaining functional adipocytes. Importantly, the increase in protein carbonylation in obtained adipocytes can be correlated with the high oxidative stress expected in differentiated adipocytes. In general, our proposed adipogenesis model promotes an increase in the intracellular fat droplets during the pre-adipocyte differentiation concomitantly with the increase in the pro-inflammatory profile, as expected in adipocytes [32,35]. Additionally, MAPK and PPAR are also both involved with adipocyte metabolism [33], which corroborates with our findings. Additionally, we have also shown significant morphological changes in adipocytes and which can explain the higher activities of MMPs and is expected to modulate the ECM remodeling. Considering in vitro studies, this experimental model presents limitations, such as evaluating the crosstalk between cells of different origins, however, it can be overcome by the evolutionarily conserved structure and functions of proteins and genes over 80%.
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Although some progress has been made on the way to understanding the etiology of systemic and metabolic dysfunctions such as diabetes and obesity, their relevance to bone-healing peri-implants, which might explain the higher failure of implants in obese patients [36], is barely understood. In fact, it has been hypothesized that angiogenesis is compromised in obese and diabetic individuals. Thus, we have applied an experimental model to better evaluate the impact on ECs responding to a titanium-enriched medium which plays crucial roles during the osseointegration mechanism of angiogenesis, such as interacting with osteoblasts [37,38]. There are important similarities between osseointegration and wound healing, a situation that is harmful in patients with compromised metabolism [39]. To advance with this proposal, we have investigated the effect of two titanium-modified surfaces. Firstly, genes related to the phenotype of endothelial cells were investigated. While VEGF seemed not to be affected, its receptor, VEGFR1, was higher in ECs responding to the titanium-enriched medium. This might be explained by a correlation with its ligand and suggests an autocrine loop in this condition. The increase in the intracellular signaling upon VEGFR1 activation requires the involvement of MAPK upstream, modulating cell survival and proliferative phenotype. This explains the capacity of those cells to involve p38 and CDKs [40]. Additionally, the VEGFR1-related intracellular cascade seems to require Src kinase in this context, and also might be correlated with ECM remodeling by regulating MMP activity.
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Lastly, the gene expression of interleukins IL-6 and IL-1β was shown to be sensitive to the response to titanium in an adipogenesis-related metabolic condition once both DAE and nHA promoted their higher expression. It is important that the IL-related cascade also requires the activation of MAPKs and Src. An important aspect is that IL-1β effectively and rapidly induces human mesenchymal stem cells differentiation into osteoblasts [41]. This might be an important axis coupling angiogenesis and osteogenesis during the osseointegration mechanism, meaning nHA is able to improve the capacity of ECs to drive bone healing in obese patients.
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5. Conclusions
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Taking our data into consideration, it is possible to suggest that nHA-coated surface favor biological events related to angiogenesis and might be an alternative strategy in adipogenesis-related metabolic conditions where usually the percentage of dental implant failure is higher. Altogether, this study gathers valuable information on understanding the higher failure of dental implants in obese individuals.
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Author Contributions
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Methodology, T.S.P., A.M.G. and P.B.d.M.; Validation, T.S.P.; Formal analysis, A.M.G. and P.B.d.M.; Investigation, T.S.P., A.M.G. and P.B.d.M.; Data curation, P.B.d.M.; Writing—original draft, A.M.G. and W.F.Z.; Writing—review & editing, T.S.P. and P.B.d.M.; Supervision, W.F.Z.; Project administration, W.F.Z.; Funding acquisition, W.F.Z. All authors have read and agreed to the published version of the manuscript.
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Institutional Review Board Statement
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Not applicable.
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Informed Consent Statement
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Not applicable.
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Data Availability Statement
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The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Conflicts of Interest
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The authors declare no conflict of interest.
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Figure 1 Outline and workflow. To evaluate the ECs behavior in response to titanium-enriched medium in concomitance with high adipogenesis conditions arising from 3T3-L1 adipocytes, we collected the medium conditioned by the adipocytes during their differentiation, which was later enriched with titanium for up to 24 h, as recommended by ISO 10993:2016. This conditioned medium was also further used to expose ECs for 72 h under shear stress mimicking blood flow, at which point the samples were collected to allow the molecular analysis.
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Figure 2 High-glucose medium affects adipocyte differentiation. The 50 mM high-glucose medium was used to expose pre-adipocyte cells for stimulation to differentiation. Firstly, cytotoxicity was measured by using an MTT assay (A). Thereafter, oxidative stress was measured by evaluating the protein carbonylation (nmol/mg protein) by performing a method using DNPH (2,4-dinitrophenylhydrazine derivatizing agent) (B). The data are plotted respecting mean ± SD (n = 3), and the significance was shown using Student’s t-test, ** p = 0.0058. Intracellular fat droplets of the pre-adipocytes were acquired using a light microscope (40× magnification) thereafter stained by using Oil Red O Staining (C). HGM: high-glucose medium.
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Figure 3 Adipogenesis model recapitulates the inflammation microenvironment and requires PPAR-γ. Pre-adipocytes were differentiated for 10 days using classical model when the cells were harvested and the biological samples forwarded to perform the qPCR technology. A significantly higher expression of IL-1β (A), IL-6 (B), IL-13 (C), IL-18 (D), IL-33 (E), TNF-α (G), and PPAR-γ (J) genes were observed in the adipocytes responding to HGM (50 mM). The graphs bring the n-fold change of the profile of gene expression normalized to the GAPDH gene (housekeeping gene). Significant differences were considered when * p < 0.05, and ** p < 0.01, *** p < 0.001. HGM: high glucose medium.
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Figure 4 Adipocytes require MAPK and MMP activity. Adipocytes require MAPK-ERK (A,B), while the MAPK-P38 protein remains unchanged (C,D). β-Actin was used as the protein loading control. Additionally, higher activities of MMP9 (F–H) and MMP2 (I,J) were found in adipocytes responding to HGM. Data are plotted as means ± standard deviations (n = 3). Significant differences were considered when * p < 0.05, and ** p < 0.01. HGM: high glucose medium.
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Figure 5 VEGF and VEGFR1 genes are modulated in response to titanium-based surfaces. Both genes are related to EC phenotype as well as to angiogenesis. Their response to H_Adip and the titanium-enriched medium seems to be relevant to the lower angiogenesis profile in adipogenesis. The VEGF gene presented a low expression profile in ECs responding to DAE, while there was no significance when considering the other groups (A). Additionally, the VEGFR1 gene presented a low profile of expression in ECs responding to nHA (B). The data show the n-fold changes in the profile of transcripts normalized to the 18 S gene (housekeeping gene). Differences were considered statistically significant when * p < 0.05, and *** p < 0.001, represented by red * when compared to the H_Adip group.
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Figure 6 Both survival and cell proliferation progress were investigated in ECs. ECs require an increase in survival and cell cycle-related gene expression even more responding to high-adipogenesis condition, observing the behavior of AKT (A), CDK2 (B), and CDK4 (C). Differences were considered statistically when * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001, represented by black * when compared to the Ctrl group, by red * when compared to the H_Adip group, and by green * when compared between the groups with nHA.
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Figure 7 MAPK-related genes were modulated in EC responding to adipogenesis. qPCR shows different modulations of the MAPKs genes in ECs: the MAPK-ERK gene was higher in cells responding to the DAE group, and even higher in the H_Adip + DAE group. However, there was no difference in the H_Adip + nHA group when compared to Ctrl (A). The JNK was down-regulated in the H_Adip group when compared to Ctrl, and higher in response to DAE treatment when compared to H_Adip. Data are reported as means ± standard deviations (n = 3). Comparison by one-way ANOVA. Statistical differences were considered when * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001, represented by black * when compared to the Ctrl group, by red * when compared to the H_Adip group, and by green * when compared between the groups with DAE.
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Figure 8 c-Src involvement. After exposing the ECs to different shear-stress treatments for 72 h, the samples were obtained to perform the Western blotting assay and evaluate SRC protein content (A,B). The high adipogenesis condition increased the content of SRC in ECs, significantly in the H_Adip + DAE group, and less significantly in the H_Adip + nHA group. β-Actin was considered the protein loading control. Differences were considered significant when * p < 0.05, and *** p < 0.001, represented by black * when compared to the Ctrl group, and by red * when compared to the H_Adip group.
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Figure 9 IL6 and IL1B gene expression changed in response to conditioned mediums. The samples were harvested as described earlier and the gene expression was measured using qPCR. To address the inflammatory effect of different conditions on ECs, we evaluated IL-6 (A) and IL-1β (B) genes. The 18SrRNA gene was considered the housekeeping gene and used to normalize the expression values. Data are reported in means ± standard deviations (n = 3). Differences were considered significant when * p < 0.05, *** p < 0.001, and **** p < 0.0001, represented by black * when compared to the Ctrl group, by red * when compared to the H_Adip group, and by green * when compared between the groups with DAE or between the groups with nHA. DAE = titanium with Dual Acid-Etching; nHA = titanium with nano-Hydroxyapatite-coated surface.
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jfb-14-00162-t001_Table 1 Table 1 Sequences of the primers and conditions of the quantitative polymerase chain reaction cycle.
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| 190 |
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| 191 |
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Genes Primers 5′-3′ Sequences Reaction’s Conditions
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| 192 |
+
H-AKT Forward CAG CGC GGC CCG AAG GAC 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 193 |
+
Reverse GAC GCT CAC GCG CTC CTC TC
|
| 194 |
+
H-CDK2 Forward CTT TGC TGA GAT GGT GAC TCG 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 195 |
+
Reverse GCC TCC CAG ATT CCT CAT GC
|
| 196 |
+
H-CDK4 Forward CTC TCT AGC TTG CGG CCT G 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 197 |
+
Reverse GCA GGG ATA CAT CTC GAG GC
|
| 198 |
+
H-ERK Forward GCA GCG CCT CCC TTG CTA GA 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 199 |
+
Reverse AAC AGC CTC TGG CCC ACC CAT
|
| 200 |
+
H-IL1B Forward GGA GAA TGA CCT GAG CAC CT 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 201 |
+
Reverse GGA GGT GGA GAG CTT TCA GT
|
| 202 |
+
H-IL6 Forward AGT CCT GAT CCA GTT CCT GC 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 203 |
+
Reverse CTA CAT TTG CCG AAG AGC CC
|
| 204 |
+
H-JNK Forward AAA GGT GGT GTT TTG TTC CCA GGT 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 205 |
+
Reverse TGA TGA TGG ATG CTG AGA GCC ATT G
|
| 206 |
+
H-P38 Forward GAG AAC TGC GGT TAC TTA 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 207 |
+
Reverse ATG GGT CAC CAG ATA CAC AT
|
| 208 |
+
H-VEGF Forward TGC AGA TTA TGC GGA TCA AAC C 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 209 |
+
Reverse TGC ATT CAC ATT TGT TGT GCT GTA G
|
| 210 |
+
H-VEGFr1 Forward CAG GCC CAG TTT CTG CCA TT 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 211 |
+
Reverse TTC CAG CTC AGC GTG GTC GTA
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| 212 |
+
M-Gapdh Forward AGG CCG GTG CTG AGT ATG TC 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 213 |
+
Reverse TGC CTG CTT CAC CAC CTT CT
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| 214 |
+
M-Il13 Forward CAG TCC TGG CTC TTG CTT G 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 215 |
+
Reverse CCA GGT CCA CAC TCC ATA CC
|
| 216 |
+
M-Il18 Forward ACT TTG GCC GAC TTC ACT GT 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 217 |
+
Reverse GGG TTC ACT GGC ACT TTG AT
|
| 218 |
+
M-Il1b Forward GAC CTT CCA GGA TGA GGA CA 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 219 |
+
Reverse AGC TCA TAT GGG TCC GAC AG
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| 220 |
+
M-Il1r Forward ACC CCC ATA TCA GCG GAG CG 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 221 |
+
Reverse TTG CTT CCC CCG GAA CGT AT
|
| 222 |
+
M-Il33 Forward CCT TCT CGC TGA TTT CCA AG 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 223 |
+
Reverse CCG TTA CGG ATA TGG TGG TC
|
| 224 |
+
M-Il6 Forward AGT TGC CTT CTT GGG ACT GA 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 225 |
+
Reverse CAG AAT TGC CAT TGC ACA AC
|
| 226 |
+
M-Myd88 Forward ATG GTG GTG GTT GTT TCT GAC GA 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 227 |
+
Reverse GCA AGG GTT GGT ATA GTC GCA TAT A
|
| 228 |
+
M-Nfkb Forward CAC CTG TTC CAA AGA GCA CC 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 229 |
+
Reverse GGT TCA GGA GCT GCT GAA AC
|
| 230 |
+
M-Pparg Forward TTT TCA AGG GTG CCA GTT TC 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 231 |
+
Reverse AAT CCT TGG CCC TCT GAG AT
|
| 232 |
+
M-Tnf Forward CCA CAT CTC CCT CCA GAA AA 95 °C, 3 s; 55 °C, 8 s; 72 °C, 20 s
|
| 233 |
+
Reverse AGG GTC TGG GCC ATA GAA CT
|
| 234 |
+
Note: H = Human; M = Mice.
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| 235 |
+
|
| 236 |
+
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
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==== Refs
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References
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14. Coelho P.G. Granjeiro J.M. Romanos G.E. Suzuki M. Silva N.R.F. Cardaropoli G. Thompson V.P. Lemons J.E. Basic research methods and current trends of dental implant surfaces J. Biomed. Mater. Res. B Appl. Biomater. 2009 88 579 596 10.1002/jbm.b.31264 18973274
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15. Rademakers T. Horvath J.M. van Blitterswijk C.A. LaPointe V.L.S. Oxygen and nutrient delivery in tissue engineering: Approaches to graft vascularization J. Tissue Eng. Regen. Med. 2019 13 1815 1829 10.1002/term.2932 31310055
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| 281 |
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puc/PMC10055201.txt
ADDED
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
bioRxiv
|
| 4 |
+
BIORXIV
|
| 5 |
+
bioRxiv
|
| 6 |
+
Cold Spring Harbor Laboratory
|
| 7 |
+
|
| 8 |
+
36993336
|
| 9 |
+
10.1101/2023.03.20.533514
|
| 10 |
+
preprint
|
| 11 |
+
1
|
| 12 |
+
Article
|
| 13 |
+
Aging impairs cold-induced beige adipogenesis and adipocyte metabolic reprogramming
|
| 14 |
+
Holman Corey D. responsible for conceptualization and data analysis responsible for writing of the manuscript conducted the majority of the experiments 12
|
| 15 |
+
Sakers Alexander P. responsible for conceptualization and data analysis conducted the majority of the experiments 12
|
| 16 |
+
Calhoun Ryan P. responsible for conceptualization and data analysis performed bioinformatics analyses 12
|
| 17 |
+
Cheng Lan processed tissue sections for histology and performed immunostaining 12
|
| 18 |
+
Fein Ethan C. performed bioinformatics analyses 12
|
| 19 |
+
Jacobs Christopher performed and processed the snRNA-seq experiment 34
|
| 20 |
+
Tsai Linus performed and processed the snRNA-seq experiment 345
|
| 21 |
+
Rosen Evan D. performed and processed the snRNA-seq experiment 345
|
| 22 |
+
Seale Patrick responsible for conceptualization and data analysis responsible for writing of the manuscript 12*
|
| 23 |
+
1 Institute for Diabetes, Obesity & Metabolism; Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
|
| 24 |
+
2 Department of Cell and Developmental Biology; Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
|
| 25 |
+
3 Division of Endocrinology, Diabetes, and Metabolism, Beth Israel Deaconess Medical Center, Boston, MA, USA
|
| 26 |
+
4 Broad Institute of MIT and Harvard, Cambridge, MA, USA
|
| 27 |
+
5 Harvard Medical School, Boston, MA, USA
|
| 28 |
+
* Correspondence should be addressed to: Patrick Seale, Perelman School of Medicine, University of Pennsylvania, Smilow Center for Translational Research, 3400 Civic Center Blvd, Rm. 12-105, Philadelphia, PA, 19104. USA, Tel: 215-573-8856, sealep@pennmedicine.upenn.edu
|
| 29 |
+
23 3 2023
|
| 30 |
+
2023.03.20.533514https://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License, which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
|
| 31 |
+
nihpp-2023.03.20.533514.pdf
|
| 32 |
+
The energy-burning capability of beige adipose tissue is a potential therapeutic tool for reducing obesity and metabolic disease, but this capacity is decreased by aging. Here, we evaluate the impact of aging on the profile and activity of adipocyte stem and progenitor cells (ASPCs) and adipocytes during the beiging process. We found that aging increases the expression of Cd9 and other fibrogenic genes in fibroblastic ASPCs and blocks their differentiation into beige adipocytes. Fibroblastic ASPC populations from young and aged mice were equally competent for beige differentiation in vitro, suggesting that environmental factors suppress adipogenesis in vivo. Examination of adipocytes by single nucleus RNA-sequencing identified compositional and transcriptional differences in adipocyte populations with age and cold exposure. Notably, cold exposure induced an adipocyte population expressing high levels of de novo lipogenesis (DNL) genes, and this response was severely blunted in aged animals. We further identified natriuretic peptide clearance receptor Npr3, a beige fat repressor, as a marker gene for a subset of white adipocytes and an aging-upregulated gene in adipocytes. In summary, this study indicates that aging blocks beige adipogenesis and dysregulates adipocyte responses to cold exposure and provides a unique resource for identifying cold and/or aging-regulated pathways in adipose tissue.
|
| 33 |
+
|
| 34 |
+
NIHDK120982 DK121801 T32 HD083185 T32 DK007314 RC2 DK116691
|
| 35 |
+
==== Body
|
| 36 |
+
pmcIntroduction
|
| 37 |
+
|
| 38 |
+
Brown and beige fat cells are specialized to burn calories for heat production in response to certain stimuli and have the capacity to reduce obesity and metabolic disease. Brown adipocytes are localized in dedicated brown adipose tissue (BAT) depots, whereas beige adipocytes develop in white adipose tissue (WAT) in response to cold exposure, and other stimuli (W. Wang & Seale, 2016). Adult humans possess thermogenic adipose depots that resemble rodent beige adipose tissue (Jespersen et al., 2013; Wu et al., 2012). Brown and beige adipocytes share similar cellular features such as abundant mitochondria, multilocular lipid droplets, and expression of thermogenic genes like Uncoupling Protein-1 (UCP1). UCP1, when activated, dissipates the mitochondrial proton gradient, leading to high levels of substrate oxidation and heat production (Cannon & Nedergaard, 2004). Brown and beige adipocytes can also produce heat via several other UCP1-independent futile cycles (Chouchani, Kazak, & Spiegelman, 2019).
|
| 39 |
+
|
| 40 |
+
Increasing beige fat development in mice reduces obesity and improves insulin sensitivity, whereas ablation of beige fat in mice causes metabolic dysfunction (Cederberg et al., 2001; Cohen et al., 2014; Seale et al., 2011; Shao et al., 2016; Stine et al., 2016). Furthermore, transplantation of human beige adipocytes into obese mice reduces liver steatosis and improves metabolic health (Min et al 2016). Beige adipocytes develop via the de novo differentiation of adipocyte precursor cells (ASPCs) or through induction of the thermogenic program in adipocytes (Ferrero, Rainer, & Deplancke, 2020; Sakers, De Siqueira, Seale, & Villanueva, 2022; Shao et al., 2019).
|
| 41 |
+
|
| 42 |
+
Human and mouse thermogenic adipose tissue activity declines with aging, predisposing to cardiometabolic disease and limiting the potential of brown/beige fat targeted therapies (Becher et al., 2021; Berry et al., 2017; Cypess et al., 2012; Rogers, Landa, Park, & Smith, 2012; W. Wang et al., 2019; Yoneshiro et al., 2011). In mice, beige adipose tissue is reduced by ‘middle-age’ (i.e., 1-year-old), preceding many of the damaging effects of old age on organ function (Berry et al., 2017; Goncalves et al., 2017; Rogers et al., 2012). The aging-associated decline in beige fat activity can occur independently of increases in body weight (Rogers et al., 2012; St-Onge, 2005). A variety of processes and pathways have been linked to the aging-induced deficit in beige fat formation, including diminished proliferation and cellular senescence of ASPCs (Berry et al., 2017), increased fibrosis (W. Wang et al., 2019), increased inflammation (Amiya Kumar Ghosh, 2019), accumulation of anti-adipogenic regulatory cells (Nguyen et al., 2021), and reduced adrenergic tone (Rogers et al., 2012). However, a detailed understanding of how cold exposure and aging affect ASPC identity, adipogenesis, and adipocyte phenotypic switching remains elusive.
|
| 43 |
+
|
| 44 |
+
We applied ASPC lineage tracing, along with unbiased single-cell and single-nucleus RNA sequencing (scRNA-seq; snRNA-seq) to comprehensively profile the beiging process and evaluated the impact of aging on this process. We found that aging modulates the gene program of multiple fibroblastic ASPC populations and blocks the differentiation of these cells into beige adipocytes in vivo. snRNA-seq analysis revealed four types of adipocytes defined by different responses to cold exposure and aging: beige, Npr3-high, de novo lipogenesis (DNL)-low, and DNL-high. Notably, DNL-high adipocytes were defined by the marked induction of DNL genes during cold exposure in young compared to aged animals. A white adipocyte subpopulation in young mice were marked by expression of Natriuretic peptide receptor-3 (Npr3), which was also increased in multiple adipocyte populations of aged mice. Altogether, this study shows that aging blocks cold-stimulated adipocyte reprogramming and ASPC adipogenesis and implicates suppression of natriuretic peptide signaling and DNL in contributing to the aging-mediated decline in beige fat formation.
|
| 45 |
+
|
| 46 |
+
Results
|
| 47 |
+
|
| 48 |
+
Aging impairs iWAT beiging
|
| 49 |
+
|
| 50 |
+
To study the impact of aging on beige adipose tissue development, we exposed young (9-week-old) and middle aged (57-week-old) C57BL/6 mice to 6°C for either 3 or 14 days. All mouse groups were first acclimated to 30°C (thermoneutrality [TN]) for 3 weeks to reduce beige adipose tissue to baseline (low) levels. Following acclimation, TN-housed mice remained at 30°C; acute cold mice (3D) were transitioned to 6°C after 11 days for the final 3 days; and chronic cold mice (14D) were moved to 6°C for two weeks (Figure 1A). As expected, the aged mice weighed more and had larger iWAT depots than the young mice (Figure S1A,B). Cold exposure greatly and progressively increased the expression levels of thermogenic genes Ucp1, Cidea, Dio2 and Ppargc1a in young iWAT, but the activation of these genes was significantly blunted in aged mice, especially at the 3D timepoint (Figure 1B). Immunofluorescence staining showed a robust induction of UCP1 protein in multilocular adipocytes of young iWAT at 3D of cold exposure, which was further increased at 14D. The induction of UCP1+ beige adipocytes was severely reduced in aged animals, with strikingly few UCP1+ adipocytes detected at. At 14D, the beige adipocytes in young and aged look morphologically similar, although there are fewer in aged. (Figure 1C). Beige adipocytes in young and aged were most prominent in the inguinal region (versus dorsolumbar) of iWAT, consistent with other reports (Barreau et al., 2016; Chi et al., 2018; Dichamp et al., 2019) and beiging was largely absent in the dorsolumbar region of aged mice (Figure S1C–D). To determine if the beiging response is delayed in aged mice, we exposed young and aged mice at 6°C for 6 weeks. At this time point, the iWAT of aged mice exhibited a larger deficit in thermogenic gene expression compared to young animals (Figure 1D). Thermogenic gene levels in interscapular BAT were similar between young and aged mice, at TN and after cold exposure, indicating that the inhibitory effects of aging were selective to WAT (Figure S1E).
|
| 51 |
+
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+
Next, we examined beige fat formation in young and aged animals upon treatment with the β3-selective adrenergic agonist CL-316,243 (CL). CL acts in an adipose tissue autonomous manner to stimulate beige fat biogenesis, bypassing the central nervous system pathways that mediate the response to cold exposure. Acute CL treatment for only 1 hour increased iWAT Ucp1 expression in young mice to a much greater extent than in aged mice (Figure 1E). Chronic CL exposure for 5 days also induced much higher expression levels of Ucp1 and Cidea in iWAT of young compared to aged mice (Figure 1F). Taken together, these results demonstrate that beige adipose tissue induction is severely impaired in middle aged mice.
|
| 53 |
+
|
| 54 |
+
Aging blocks beige adipogenesis from Pdgfra+ ASPCs
|
| 55 |
+
|
| 56 |
+
To determine the contribution of fibroblastic ASPCs to beige adipocytes during cold exposure, we performed lineage tracing using Pdgfra-CreERT2;R26RtdTomato reporter mice. Pdgfra expression marks multiple ASPC populations, including preadipocytes (Merrick et al., 2019; Sakers et al., 2022). Young and aged reporter mice were treated with tamoxifen for 5 days at TN (30°C; “pulse”) to activate Cre and induce tdTomato expression in Pdgfra+ cells. Following a 9 day washout period, mice were transferred to 6°C (cold) for two weeks (“chase”) (Figure 2A). We observed near complete and specific labeling of ASPCs during the pulse period, with ~95% of PDGFRα+ cells in iWAT from young and aged mice displaying tdTomato expression (Figures 2B, S2A). No tdTomato-expressing adipocytes were observed after the pulse (Figure S2B). After 14 days of cold exposure, we detected many newly developed beige adipocytes from ASPCs in young mice (visible as tdTomato+/UCP1+ multilocular adipocytes). By contrast, very few ASPC-derived (tdTomato+) were detected in the beige fat areas of aged iWAT at day 14 (Figures 2C). Quantifying across the entire length of iWAT pads revealed that most beige adipogenesis occurred in the inguinal region and was ~12-fold lower in aged than in young (Figure 2D,E). However, the overall contribution of Pdgfra+ ASPCs to beige adipocytes was relatively low, even in young animals, with <20% of beige adipocytes expressing tdTomato.
|
| 57 |
+
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| 58 |
+
Single cell expression profiling of ASPCs
|
| 59 |
+
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| 60 |
+
We previously identified three main fibroblastic ASPC populations in iWAT: DPP4+ interstitial cells, ICAM1+ preadipocytes, and CD142+ cells. All these cell types express Pdgfra and have the capacity to undergo adipogenic differentiation (Merrick et al., 2019). We hypothesized that the aging-related impairment of beige adipogenesis was caused by dysregulation of these ASPC types. To investigate this, we performed scRNA-seq on stromal vascular cells from iWAT of young and aged animals, maintained at TN, or following transition to cold for 3 or 14 days (Figure 1A). ASPCs were enriched by removing immune (CD45+) cells using fluorescence activated cell sorting (FACS). We integrated the datasets from all conditions together and performed clustering analysis. The following cell populations were annotated based on their expression of cell type-specific marker genes: four fibroblast populations (Dpp4+; Icam1+ preadipocytes; Cd142+, Spp1+), two populations of endothelial cells (Pecam1+); smooth muscle cells/pericytes (Myh11+, Pdgfrb+); Schwann cells (Mpz+); and residual immune cells (Ptprc+) (Figures 3A–C). Aging or cold exposure did not promote the emergence of any specific cell populations. In this regard, we did not identify ‘aging-dependent regulatory cells (ARCs)’, which were previously defined as ASPCs expressing Lgals3 and other inflammatory genes (Figure S3A) (Nguyen et al., 2021). The expression levels of identity markers of the ASPC populations were not modulated during cold exposure or aging (Figure S3B).
|
| 61 |
+
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| 62 |
+
Differential gene expression analyses identified aging-modulated genes in the ASPC populations (Figure 3D). Notably, expression of Cd9, previously identified as a fibrogenic marker, was upregulated with age in Dpp4+ cells and preadipocytes (Marcelin et al., 2017). Pltp and Gpnmb were also elevated by aging across all ASPC populations and temperature conditions. Genes downregulated by aging in all ASPC populations included Meg3, Itm2a and Gpc3 and Postn. Of note, Postn encodes an extracellular matrix protein that was previously reported to regulate adipose tissue expansion and decrease in expression during aging (Graja et al., 2018).
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| 63 |
+
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| 64 |
+
ASPCs from aged mice are competent for beige adipogenesis ex vivo
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| 65 |
+
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| 66 |
+
We next evaluated if ASPCs from young and aged animals exhibit cell-autonomous differences in adipogenic differentiation capacity. We FACS-purified the three ASPC populations, DPP4+, ICAM1+ and CD142+ cells, from the iWAT of young and aged mice, plated them in culture and induced adipocyte differentiation. Using a minimal differentiation stimulus consisting of insulin only (MIN), ICAM1+ and CD142+ cells underwent more efficient differentiation into lipid droplet-containing adipocytes, and expressed higher levels of adipocyte genes (Adipoq and Fabp4) than DPP4+ cells, consistent with prior work (Figures 4A,B) (Merrick et al., 2019). DPP4+ and CD142+ cells from young and aged mice underwent adipocyte differentiation and induced adipocyte genes with equivalent efficiency. Unexpectedly, aged ICAM1+ cells exhibited greater differentiation capacity than young ICAM1+ cells, as evidenced by higher expression levels of Adipoq and Fabp4 (Figures 4A,B). Maximal stimulation with a full cocktail of adipogenic inducers (MAX), produced similar and robust differentiation in all ASPC populations from young or aged mice (Figures 4C,D). To assess whether young and aged precursor cells behave differently when cultured as a mixed heterogeneous population, we isolated the stromal vascular fraction (SVF) for adipogenesis assays. Again, SVF cell cultures from both young and aged mice displayed similar adipogenic differentiation capacity with either MIN or MAX stimulation (Figures 4E,F). Finally, we stimulated cell cultures with the pan-adrenergic agonist isoproterenol for 4 hours to evaluate thermogenic gene activation (i.e., beiging). Basal levels of Ucp1 expression appear to be lower in DPP4+ cells compared to other ASPC types, but all three ASPC populations activated Ucp1 expression to high and similar levels in response to stimulation and did not differ by age (Figure 4G). We also did not observe an aging-related difference in the levels of Ucp1 induction in SVF-derived adipocyte cultures stimulated with either MAX or MIN cocktail, and as expected, MAX differentiated cells demonstrated greater stimulated capacity (Figure 4H). Together, these data suggest that the beige adipogenic capacity of ASPCs is not intrinsically compromised in aged mice, and therefore the in vivo deficit in beige adipogenesis could be due to non-ASPC-autonomous effects.
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| 67 |
+
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| 68 |
+
Single nucleus RNA sequencing uncovers adipocyte heterogeneity
|
| 69 |
+
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+
To determine the effects of aging and cold exposure on adipocyte gene profiles, we performed snRNA-seq analyses of iWAT samples using the same experimental paradigm described above (Figure 1A). We integrated all the conditions together for analyses from two separate runs. Similar cell types were captured as with scRNA-seq (Figure 3A), but with the addition of mature adipocyte populations (Figure 5A). This dataset has increased representation from immune cells since there was no negative selection against CD45+ cells. As with the single-cell data set, we did not identify any aging-specific cell populations (Figure S4A). However, we observed striking differences in the adipocyte cluster across age and temperature. Most obvious was the emergence and expansion of a distinct beige adipocyte population, marked by expression of Ucp1 and other thermogenic genes, during cold exposure (Figure 5B).
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| 71 |
+
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| 72 |
+
To focus on adipocyte responses, we reintegrated the snRNA-seq data using only the adipocytes, which revealed four main clusters (Figures 5D–F). Beige adipocytes, marked by high expression of many thermogenic genes (i.e., Ppargc1a, Esrrg, Cidea, Gk and Ucp1), were the most distinctive cluster and were largely absent at TN in young and aged mice, but they began to appear in young mice after 3 days of cold exposure, and were further increased at 14 days. By contrast, in aged mice, beige cells were barely detectable at 3 days of cold exposure and were present at greatly reduced numbers than in young mice at 14 days (Figure 5E). This analysis also revealed three sub-populations of ‘white’ adipocytes. ‘Npr3-high’ adipocytes were enriched for expression of Npr3, Synpo2, Prr16, and Tshr, expressed higher levels of canonical white fat marker genes Leptin (Lep) and Nnat, and exhibited the lowest expression levels of thermogenic (beige) genes. Two additional white adipocyte clusters were designated as ‘de novo lipogenesis (DNL)-low’ and ‘DNL-high’ cells, both of which expressed lower levels of Npr3 and shared selective expression of Fgf14. DNL-high cells uniquely expressed Ces1f and Gsta3, and activated high levels of DNL pathway genes (i.e., Fasn, Acss2 and Acly) upon cold exposure (Figure 5F). Quantification of adipocyte nuclei from this data set showed that the proportions of Npr3-high and DNL-high adipocytes remain stable across temperature, with aged mice having more Npr3-high adipocytes. The proportion of beige adipocytes increased dramatically during cold exposure selectively in young animals, as expected, while DNL-low adipocytes decreased with cold exposure in both young and aged mice (Figure 5G).
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| 73 |
+
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| 74 |
+
Aging dysregulates gene programming in adipocyte populations
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| 75 |
+
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| 76 |
+
To evaluate the global effects of cold exposure and aging on adipocytes, we performed differential gene expression analysis between young and aged adipocytes within each cluster. DNL-high and beige adipocytes exhibited the most dramatic expression changes between young and aged animals (Figures 6A–B, S4B–C). At TN, DNL-high cells from aged animals expressed lower levels of several genes, including Fkbp5, Spon1 and Adam12. Interestingly, Npr3, in addition to marking Npr3-high cells, was increased by aging in DNL-high adipocytes and to a lesser extent in other adipocyte populations (Figure 6C,D). In young animals, Npr3 expression was downregulated by cold exposure in the three white adipocyte populations, and this downregulation was blunted in aged animals (Figure 6D). Gene expression analysis of whole iWAT pads confirmed that Npr3 mRNA levels are progressively decreased by cold exposure and elevated in aged versus young mice under all temperature conditions (Figure 6E). Npr3 expression levels were also increased in isolated primary adipocytes from aged relative to young mice (Figure 6F). Expression levels of the G-protein coupled NP receptors Npr1 or Npr2 were not modulated by cold or aging in iWAT or iWAT adipocytes (Figure S4D,E).
|
| 77 |
+
|
| 78 |
+
We also observed a striking activation of the DNL and related gene programs (Acly, Fasn, Acaca, Scd1, etc.) in DNL-high and beige adipocytes during cold exposure (Figures 6G,H). The induction of these genes during cold exposure, exemplified by Acly expression, was a cluster-defining attribute of DNL-high cells, which did not express beige genes like Ucp1 even after 14 days of cold exposure. Of note, we found two types of beige (UCP1+) adipocytes, distinguished by the presence vs. absence of high DNL gene levels (i.e., UCP1+; DNL+ and UCP1+;DNL(−)), with the latter arising first during cold exposure (3D vs. 14D) (Figures 6G, S4F,G). Importantly, the induction of DNL genes was nearly completely blocked in DNL-high cells and reduced in beige cells of aged animals (Figure 6G). Indeed, the top aging downregulated genes in adipocytes from cold exposed mice correspond to DNL and related pathways, especially in DNL-high cells (Figure S4I). Lastly, at the whole tissue level, we observed robust induction of Acly in iWAT of young relative to aged mice with increasing duration of cold exposure (Figure S4H). Taken together, these results implicate the suppression of natriuretic peptide signaling and DNL in contributing to the aging-related impairment of beige fat formation.
|
| 79 |
+
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| 80 |
+
Discussion
|
| 81 |
+
|
| 82 |
+
Thermogenic adipose tissue activity declines during aging of mice and humans, correlating with increases in fat mass and susceptibility to cardiometabolic diseases (Berry et al., 2017; Cypess et al., 2009; Pfannenberg et al., 2010; Rogers et al., 2012; Saito et al., 2009; W. Wang et al., 2019; Yoneshiro et al., 2011). Our study provides a comprehensive unbiased profile of the adipose tissue beiging process and reveals pathways dysregulated by aging in ASPCs and adipocytes during this process.
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| 83 |
+
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| 84 |
+
Beige adipocytes develop via the de novo differentiation of ASPCs or through activation of the thermogenic gene program in mature adipocytes. Previous studies defined three populations of fibroblastic ASPCs in iWAT, namely Dpp4+ interstitial cells, Icam1+ preadipocytes, and Cd142+ cells (Burl et al., 2018; Merrick et al., 2019). Aging or cold exposure did not induce dramatic shifts in either the proportions, or gene expression signatures of any of these ASPC types, suggesting that these cell populations are stably maintained across a range of conditions. In support of this, aging did not diminish the cell-intrinsic adipogenic capacities of these ASPC populations, when isolated and subjected to adipogenesis assays ex vivo. Notably, we did not observe the emergence of aging-dependent regulatory cells (ARCs), previously described as modulated ASPCs co-expressing ASPC and immune marker genes, which have the capacity to suppress adipocyte differentiation (Nguyen et al., 2021). However, we did observe the induction of ARC-selective gene markers (i.e., Lgals3, Cd36) specifically in immune cells (Ptprc+, Adgre1+) from aged mice in both our scRNA-seq and snRNA-seq datasets. This Lgals3/Cd36 gene signature has also been described in Lin+ macrophages and CD45+ lipid-associated (LAM) macrophages (Burl et al., 2018; Jaitin et al., 2019). Overall, our results suggest that aging-induced alterations to the systemic milieu or adipose tissue environment are responsible for the block in beige adipogenesis.
|
| 85 |
+
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| 86 |
+
Gene expression analyses identified several genes that were altered by aging across multiple ASPC types and temperature conditions. The top aging-upregulated gene was Cd9, which was previously identified as a marker of fibrogenic (fibrosis-generating) progenitor cells (Marcelin et al., 2017). Cd9 encodes for a tetraspanin protein implicated in various processes that could affect adipogenesis, including extracellular vesicle production, cell adhesion, inflammation, and platelet activation (Brosseau, Colas, Magnan, & Brouard, 2018). Aging also upregulated the expression of Pltp and Gpnmb, which are both linked to the regulation of inflammation and fibrosis (Prabata, Ikeda, Rahardini, Hirata, & Emoto, 2021; Saade, Araujo de Souza, Scavone, & Kinoshita, 2021). Conversely, Meg3, Itm2a and Postn were consistently downregulated across all ASPC populations from aged versus young mice. Of note, Periostin (Postn) is an extracellular matrix protein that regulates adipose tissue lipid storage, and its levels were previously shown to decrease in several adipose tissue depots during aging (Graja et al., 2018).
|
| 87 |
+
|
| 88 |
+
We were surprised by the limited (<20%) contribution of fibroblastic (Pdgfra+) ASPCs, (which includes Pparg-expressing preadipocytes), to beige adipocytes during cold exposure. Previous studies in mice using an adipocyte fate tracking system show that a high proportion of beige adipocytes arise via the de novo differentiation of ASPCs (Q. A. Wang, Tao, Gupta, & Scherer, 2013). However, the relative contribution from ASPC differentiation and direct adipocyte conversion to the formation of beige adipocytes depends highly on the experimental conditions, especially cold exposure history (Shao et al., 2019). Mice housed at TN from birth undergo high rates of de novo beige adipogenesis upon first cold exposure, whereas mice reared at room temperature acquire many ‘dormant’ beige adipocytes that can be re-activated by cold exposure (Rosenwald, Perdikari, Rulicke, & Wolfrum, 2013; Shao et al., 2019). Based on these findings, we presume that mature (dormant beige) adipocytes serve as the major source of beige adipocytes in our cold-exposure paradigm. However, long-term cold exposure also recruits smooth muscle cells to differentiate into beige adipocytes; a process that we did not investigate here (Berry, Jiang, & Graff, 2016; Long et al., 2014; McDonald et al., 2015; Shamsi et al., 2021).
|
| 89 |
+
|
| 90 |
+
The beiging process is associated with a dramatic remodeling of adipose tissue structure and metabolic function. We applied snRNA-seq analysis to investigate the cold response of iWAT adipocytes in young and aged animals, leading us to identify four adipocyte clusters: beige adipocytes and three “white” subsets: Npr3-high, DNL-low and DNL-high adipocytes. Npr3-high adipocytes were enriched for expression of white fat-selective genes and exhibit the lowest levels of thermogenic genes (Rosell et al., 2014; Ussar et al., 2014). Interestingly, Npr3 also upregulated by aging in all white adipocytes. Previous studies show that obesity also increases Npr3 levels in adipose tissue of mice and humans (Gentili et al., 2017; Kovacova et al., 2016). NPR3 represses beige fat development and adipocyte thermogenesis by functioning as a clearance receptor for natriuretic peptides (NPs), thereby reducing their lipolytic and thermogenic effects (Bordicchia et al., 2012; Coue et al., 2018; Moro et al., 2004; Sengenès, Berlan, Glisezinski, Lafontan, & Galitzky, 2000; Sengenes et al., 2003). Together, these results suggest that Npr3-high adipocytes may impede beige fat development in a cell non-autonomous manner by reducing NP signaling. Moreover, high NPR3 levels in aged animals could contribute to the block in beige fat development, and targeting this pathway may be a promising avenue to elevate beige fat activity.
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| 91 |
+
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| 92 |
+
We were also intrigued by the dramatic induction of lipogenesis genes in both beige adipocytes and DNL-high cells during cold exposure. Previous work established that cold stimulates opposing pathways of lipid oxidation and lipogenesis in thermogenic fat tissue (Mottillo et al., 2014; Sanchez-Gurmaches et al., 2018; Yu, Lewin, Forrest, & Adams, 2002). The cooccurrence of these two processes is unusual and may provide a mechanism to ensure the continued availability of fatty acids to fuel thermogenesis and/or provide critical metabolic intermediates, such as acetyl-CoA. The Granneman lab demonstrated that high expression of the lipid catabolic enzyme MCAD and lipogenic enzyme FAS occurred in separate populations of iWAT adipocytes upon stimulation with a β3-adrenergic agonist for 3–7 days (Lee, Kim, Kwon, & Granneman, 2017). We identified two subsets of UCP1+ beige adipocytes, distinguished by the presence vs. absence of high levels of DNL genes (i.e., UCP1+; DNL-high and UCP1+; DNL-low). Interestingly, the UCP1+; DNL-high cells accumulated later during cold exposure (14D), suggesting that fully cold-adapted beige adipocytes express both pathways simultaneously. Of note, the induction of Acly and other lipogenic genes was very severely impaired in aged animals. Related to this point, Martinez Calejman and colleagues showed that Acly deficiency in brown adipocytes caused a whitened phenotype, coupled with an unexpected and unexplained reduction in Ucp1 expression (Martinez Calejman et al., 2020). We speculate that high levels of ACLY may be required to support thermogenic gene transcription by supplying and efficiently shuttling acetyl-CoA for acetylation of histones or other factors.
|
| 93 |
+
|
| 94 |
+
In summary, this work shows that aging impairs beige adipogenesis through non-cell-autonomous effects on adipose tissue precursors and by disrupting adipocyte responses to environmental cold exposure. Expression profiling at the single-cell level reveals adipocyte heterogeneity, including two different types of UCP1+ beige adipocytes. Finally, aging-dysregulated pathways, including natriuretic peptide signaling and lipogenesis, may provide promising targets for unlocking beige adipocyte development.
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Materials and Methods
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| 97 |
+
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Mice
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+
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| 100 |
+
All animal procedures were approved and performed under the guidance of the University of Pennsylvania Institutional Animal Care and Use Committee. Young (4 weeks) and aged (52 weeks) C57BL/6 male mice were obtained from the National Institute of Aging (C57BL/6JN) or Jackson Laboratories (C57BL/6J, stock number 000664). Mice were housed at 30°C for 3 weeks, then were either: maintained at 30°C for 2 weeks (TN); kept at 30°C for 11 more days before moving to 6°C for 3 days (3D cold) or moved to 6°C for 14 days (14D cold). Mice were single housed during the final two week temperature treatment and provided with a nestlet and shepherd shack. For experiments with CL316,243 (CL, Sigma-C5976), mice were housed at 30°C for 5 weeks, followed by intraperitoneal (IP) injection of 1 mg/kg/d CL either 1 hour prior to tissue harvest or for 5 days. PdgfraCreERT2 mice were obtained from Dr. Brigid Hogan (Duke University) (Chung, Bujnis, Barkauskas, Kobayashi, & Hogan, 2018) and crossed with Rosa26tdTomato (strain: B6.Cg-Gt(ROSA)26Sortm14(CAG-tdTomato)Hze/J, stock no. 007914). To induce Cre activity, tamoxifen (Sigma, T5648) dissolved in corn oil (Sigma, C8267) was injected intraperitonially (IP) into mice at a dose of 100 mg/kg/d for 5 days. For all iWAT processing other than histology, the inguinal lymph node was removed.
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| 101 |
+
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| 102 |
+
Histology and Immunofluorescence
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| 103 |
+
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| 104 |
+
Tissues were fixed overnight in 4% paraformaldehyde, washed with PBS, dehydrated in ethanol, paraffin-embedded and sectioned. Following deparaffinization, slides were subjected to heat antigen retrieval in a pressure cooker with Bulls Eye Decloaking buffer (Biocare), unless otherwise noted. Slides were incubated in primary antibody overnight and secondary antibody conjugated to peroxidase and then developed using Tyramide Signal Amplification (TSA, Akoya Biosciences). Samples were stained with the following antibodies: anti-red fluorescent protein (RFP) (rabbit; 1:500; Rockland #600–401-379), anti-UCP1 (rabbit, 1:2000, AstraZeneca), and anti-PLIN1 (rabbit, 1:200 Cell Signaling #3470). Slides were imaged on an inverted fluorescence microscope (Keyence BZ-X710). For quantification of tdTomato-expressing adipocytes, full-length iWAT slices were tile imaged, stitched, exported as a BigTiff, and quantified using the Count Tool in Photoshop (Adobe).
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| 105 |
+
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| 106 |
+
Isolation of stromal vascular cells (SCVs) and adipocytes
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| 107 |
+
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| 108 |
+
SVCs.
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| 109 |
+
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| 110 |
+
As previously described (Merrick et al 2019, Wang et al 2019), iWAT tissue was dissected, minced gently and digested with Collagenase Type I (1.5 units/ml; Worthington) and Dispase II (2.4 units/ml; Roche) in DMEM/F12 containing 1% fatty acid-free bovine serum albumin (Gold Biotechnology) in a gentleMACS dissociator (Miltenyi Biotec) on program “37 MR ATDK-1.” The digestion was quenched with DMEM/F12 containing 10% FBS, and the dissociated cells were passed through a 100 μm filter and spun at 400 × g for 4 mins. The pellet was resuspended in red blood cell lysis buffer (BioLegend), incubated for 4 mins at RT, then quenched with DMEM/F12 containing 10% serum. Cells were passed through a 70 μm filter, spun, resuspended, then passed through a final 40 μm filter, spun at 400 × g for 4 minutes and plated or underwent further processing for FACS. Mice were not pooled unless indicated.
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| 111 |
+
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| 112 |
+
Adipocytes.
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| 113 |
+
|
| 114 |
+
Tissue went through the same process as above, except after digestion and quenching, adipocyte/SVF slurry was filtered through a 200 μm filter and centrifuged at 50 × g for 3 mins at RT. Using a 20 mL syringe and 1.5-inch, 25G needle, media containing the SVCs was removed from below the adipocytes (and saved if concurrently isolating SVCs), leaving only the adipocytes in the tube. Adipocytes were washed twice with the same media as quenching, transferred to 2 mL tubes, spun a final time, media was removed from below the adipocytes again, and TRIzol was added for RNA extraction. Mice were not pooled.
|
| 115 |
+
|
| 116 |
+
FACS
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| 117 |
+
|
| 118 |
+
DPP4+, ICAM1+, and CD142+ cells were isolated as previously described (Merrick et al 2019). Briefly, SVCs from the subcutaneous adipose of mice (n= 2–5) were pooled and resuspended in FACS buffer (HBSS containing 3% FBS; Fisher), then incubated for 1 hr at 4°C with the following antibodies: CD26 (DPP4)-fluorescein isothiocyanate (FITC) (Biolegend, 137806; 1:200), anti-mouse ICAM1-phycoerythrin (PE)/Cy7 (Biolegend, 116122; 1:100), anti-mouse CD45-allophycocyanin (APC)/Cy7 (Biolegend, 103116; 1:1000), anti-mouse CD31-APC-Fire (Biolegend, 102528; 1:1000), and anti-mouse CD142 (Sino Biological, 50413-R001, 1:100; or R&D Systems, AF3178, 1:50). Anti-mouse CD142 antibodies were conjugated with Biotium Mix-n-Stain CF647 (Sigma, MX647S100). For lineage tracing pulse analysis, SVCs were isolated from individual mice without pooling. SVCs were stained with anti-mouse CD31, anti-mouse CD45, and anti-mouse CD140a (PDGFRΑ) (PE/Cy7) (Biolegend, 135912; 1:100). In all FACS experiments, cells were stained with 4′,6-diamidino-2-phenylindole (DAPI) (Roche, 10236276001; 1:10,000) for 5 minutes, then washed three times with FACS buffer to remove unbound antibodies. Cells were sorted with a BD FACS Aria cell sorter (BD Biosciences) equipped with a 100 μm nozzle and the following lasers and filters: DAPI, 405 and 450/50 nm; FITC, 488 and 515/20 nm; mTomato, 532 and 610/20 nm; PE/Cy7, 532 and 780/60 nm; CF647, 640 and 660/20 nm; and APC/Cy7 and APC-Fire, 640 and 780/60 nm. All compensation was performed at the time of acquisition in Diva software by using compensation beads (BioLegend, A10497) for single-color staining and SVCs for negative staining and fluorescence (DAPI and tdTomato).
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+
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Cell culture and differentiation
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| 121 |
+
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| 122 |
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Adipocyte precursor cells.
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| 123 |
+
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| 124 |
+
All cells were cultured in DMEM/F12 containing 10% FBS and Primocin (50 ng/ml) (InvivoGen, ant-pm-1). DPP4+, ICAM1+, and CD142+ populations were FACS purified, plated on CellBind 384-well plates (Corning) at 15–25K cells/well, and incubated for 48 (25K cells) to 72 hours (15K cells) to facilitate attachment before the induction of adipogenic differentiation. For whole SVF, SVCs were isolated and plated in a 48 well CellBind plate (Corning) at a high confluency of one mouse per 18 wells. No cells were passaged after plating to maintain adipogenic competency. Differentiation was carried out with either maximum adipogenic cocktail, max: 500 μM isobutylmethylxanthine (Sigma, I7018), 10 μM dexamethasone (Sigma, D4902), 125 μM indomethacin (Sigma, I8280), 1 μM rosiglitazone (Cayman Chemical, 11884), 1 nM T3 (Sigma, T6397), and 20 nM insulin (Novolin) or a minimal adipogenic cocktail, min: 20 nM insulin. For the max adipogenic cocktail induction, cells were incubated with cocktail for 2 days and then transferred to adipogenic maintenance medium for the remaining 6 days (1 μM rosiglitazone, 1 nM T3, and 20 nM insulin). For all conditions, medium was changed every 2 days, and cells were harvested on day 8 of differentiation. For drug treatments, cells were treated for 4 hrs on day 8 with 1 μM isoproterenol (Sigma, I6504). Adipogenesis was assessed by staining with Biodipy 493/503 (Invitrogen, D3922) for lipid droplet accumulation and Hoechst 33342 (Thermo Fisher, 62249) for nuclei number. The cells were imaged on a Keyence inverted fluorescence microscope (BZ-X710) by using DAPI (excitation, 360/40 nm; emission, 460/50 nm) and green fluorescent protein (excitation, 470/40 nm; emission, 525/50 nm) filters. Individual wells were imaged in their entirety at 4x magnification, and at 20x to see morphology. 384-well plates were not stained and imaged in brightfield due to low cell number recovery from FACS prior to RNA extraction.
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| 125 |
+
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| 126 |
+
RNA Extraction, qRT-PCR and RNA Sequencing
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| 127 |
+
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| 128 |
+
RNA Extraction.
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| 129 |
+
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| 130 |
+
Total RNA was extracted using TRIzol (Invitrogen) combined with PureLink RNA Mini columns (Thermo Fisher, 12183025) for tissue and SVC cells or by PicoPure RNA Isolation Kit (Applied Biosystems, KIT0204) for 384-well plate populations and adipocytes. Prior to the addition of chloroform, all tissue and primary adipocytes in TRIzol included an extra spin at max speed for 10 minutes at RT, then TRIzol was removed from below the lipid layer to avoid lipid contamination disrupting the subsequent phase separation with chloroform. Chloroform was added to the lipid-free TRIzol, spun for 15 mins at 12,000 × g and the aqueous layer was removed and added to columns. mRNA was quantified using a Nanodrop and reverse transcribed to cDNA using the ABI High-Capacity cDNA Synthesis kit (ABI, 4368813). Real-time PCR was performed on a QuantStudio5 qPCR machine using SYBR green fluorescent dye (Applied Biosystems). Fold changes were calculated using the ddCT method, with TATA binding Protein (Tbp) mRNA serving as a normalization control.
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| 131 |
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| 132 |
+
Single Cell RNA-seq Samples.
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| 133 |
+
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| 134 |
+
Cells were flow sorted to isolate live (DAPI−) cells and remove debris. We enriched non-immune cells by sorting out CD45+ cells. Next-generation sequencing libraries were prepared using the Chromium Next GEM Single Cell 3’ Reagent kit v3.1 (10x Genomics, 1000121) per manufacturer’s instructions. Libraries were uniquely indexed using the Chromium Single Index Kit T Set A, pooled, and sequenced on an Illumina NovaSeq 6000 sequencer in a paired-end, dual indexing run by the CHOP Center for Applied Genomics at the University of Pennsylvania. Sequencing for each library targeted 20,000 mean reads per cell.
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| 135 |
+
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| 136 |
+
Single Nucleus RNA-seq Samples.
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| 137 |
+
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| 138 |
+
Nuclei were isolated from frozen mouse iWAT samples as previously described, with the following modifications to integrate hash multiplexing and FANS-assisted nuclear quality thresholding and sample pooling (Drokhlyansky et al., 2020; Slyper et al., 2020). Briefly, 300 mg of flash-frozen adipose samples were held on dry ice until immediately before nuclei isolation, and all sample handling steps were performed on ice. Each sample was placed into a gentleMACS C tube (Miltenyi Biotec, 130–093-237) with 2 mL freshly prepared TST buffer (0.03% Tween 20 (Bio-Rad), 0.01% Molecular Grade BSA (New England Biolabs), 146 mM NaCl (ThermoFisher Scientific), 1 mM CaCl2 (VWR International), 21 mM MgCl2 (Sigma Aldrich), and 10 mM Tris-HCl pH 7.5 (ThermoFisher Scientific) in ultrapure water (ThermoFisher Scientific)) with 0.2 U/μL of Protector RNase Inhibitor (Sigma Aldrich, RNAINH-RO). gentleMACS C tubes were then placed on the gentleMACS Dissociator (Miltenyi Biotec) and tissue was dissociated by running the program “mr_adipose_01” three times, and then incubated on ice for 10 minutes. Lysate was passed through a 40 μm nylon filter (CellTreat) and collected into a 50 mL conical tube (Corning). Filter was rinsed with 3 mL of freshly prepared ST buffer (146 mM NaCl, 1 mM CaCl2, 21 mM MgCl2; 10 mM Tris-HCl pH 7.5) with 0.2 U/μL RNase Inhibitor, and collected into the same tube. Flow-through was passed through a 20 μm pre-separation filter (Miltenyi Biotec) set on top of a 5 mL FACS tube (Corning) and collected into the same tube. Suspension was centrifuged in a swinging-bucket centrifuge (Eppendorf) at 500 × g for 5 minutes at 4°C with brake set to low. Following centrifugation, supernatant was removed and 5 mL of PBS pH 7.4 (ThermoFisher Scientific) with 0.02% BSA and 0.2 U/μL RNase Inhibitor was added without resuspending the nuclear pellet. Sample was centrifuged again at 500 × g for 5 minutes at 4°C with brake set to low. Following centrifugation, supernatant was removed, and the nuclear pellet was resuspended in 1 mL PBS-0.02% BSA with 0.2 U/μL RNase Inhibitor. Each sample was split into two 500 μL aliquots and transferred to new 5 mL FACS tubes for subsequent hashing. Each aliquot of resuspended nuclei was stained with NucBlue (ThermoFisher, R37605 ), labeled with 1 μg of a unique TotalSeq anti-Nuclear Pore Complex Proteins Hashtag Antibody (Biolegend), and then incubated on ice for 30 minutes. Suspension was centrifuged at 500 × g for 5 minutes at 4°C with brake set to low. Following centrifugation, 450 μL of supernatant was removed and the nuclear pellet was resuspended in 450 μL PBS-0.02% BSA with 0.2 U/μL RNase Inhibitor. For nuclear quality thresholding, fluorescence-activated nuclear sorting (FANS) was implemented to collect 4,000–4,300 nuclei from hashtagged aliquots directly into a shared well of a 96-well PCR plate (Thermo Scientific) containing 24.6 μL of 10X RT Reagent B with 1U/uL RNase Inhibitor on a Beckman Coulter MoFlo AstriosEQ fitted with a 70 μm nozzle. High-quality nuclei were selected by initial gating at 360 nm with laser filter 405–448/59 followed by SSC-H and FSC-H to remove doublets and unlysed cells. Once all sample aliquots were FANS-sorted, the pool of 43,000 nuclei was loaded on the 10x Chromium controller (10x Genomics) according to the manufacturer’s protocol. cDNA and gene expression libraries were generated according to the manufacturer’s instructions (10x Genomics). Libraries of hashtag oligo fractions were generated according to the manufacturer’s instructions (Biolegend). cDNA and gene expression library fragment sizes were assessed with a DNA High Sensitivity Bioanalyzer Chip (Agilent). cDNA and gene expression libraries were quantified using the Qubit dsDNA High Sensitivity assay kit (ThermoFisher, Q32854). Gene expression libraries were multiplexed and sequenced on the Nextseq 500 (Illumina) using a 75-cycle kit and the following read structure: Read 1: 28 cycles, Read 2: 55 cycles, Index Read 1: 8 cycles.
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| 139 |
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| 140 |
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Bioinformatics analysis
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| 141 |
+
|
| 142 |
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Single Cell RNA Sequencing
|
| 143 |
+
|
| 144 |
+
Data was processed using the Cell Ranger pipeline (10x Genomics, v.3.1.0) for demultiplexing and alignment of sequencing reads to the mm10 transcriptome and creation of feature-barcode matrices. The cell ranger output files were read into R (version 4.1.1) and processed utilizing the standard Seurat CCA integrated workflow (version 4.3.0). Each of the six samples went through a first phase of filtering, where only cells that recorded more than 200 features and only features present in a minimum of 3 cells were kept. Each sample was filtered prior to downstream analysis on nCount_RNA, nFeature_RNA, and mitochondrial percentages. Samples were then normalized using a LogNormalization method with a scaling factor of 10000 followed by FindVariableFeatures using Variance Stabilization Transformation with the top 6000 features to be returned. The samples were scored on their cell cycle phases which would be used in the regression later. The FindIntegrationAnchors function using the CCA reduction method and IntegrateData was utilized to integrate the data together. The integrated data-set was then scaled in which mitochondrial percentage and cell cycle state was regressed out. A principal component analysis was performed and the top 15 dimensions were kept. Uniform Manifold and Projection (UMAP) was run on the dataset, in addition to FindNeighbors and FindClusters. Differential gene expression between clusters was performed using the FindMarkers function with the Wilocox test in Seurat. Violin plots and individual UMAP plots were all generated using the Seurat toolkit VlnPlot and FeaturePlot functions, respectively. Heatmaps were generated utilizing the pheatmap package (version 1.0.12).
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| 145 |
+
|
| 146 |
+
Single Nucleus RNA Sequencing
|
| 147 |
+
|
| 148 |
+
Raw sequencing reads were demultiplexed to FASTQ format files using bcl2fastq (Illumina; version 2.20.0). Digital expression matrices were generated from the FASTQ files using Cell Ranger (Zheng et al., 2017)(version 6.1.2) with the option to include intronic reads (--include-introns). Reads were aligned against the GRCm38 mouse genome assembly and gene counts were obtained, per-droplet, by summarizing exonic and intronic UMIs that overlapped with the GENCODE mouse annotation (release 24) for each gene symbol. In order to adjust for downstream effects of ambient RNA expression within mouse nuclei, we used the “remove-background” module from CellBender (Fleming et al., 2022) (version 0.2.0) to remove counts due to ambient RNA molecules from the count matrices and to estimate the true cells. Genes were subsequently filtered such that only genes detected in two or more cells and with at least 6 total counts (across all cells) were retained. Sample demultiplexing via hashtag oligonucleotide sequences (HTOs) was performed with the Cumulus sc/snRNA-Seq processing pipeline (Li et al., 2020). Specifically, HTO quantification was performed with the Cumulus Tool on Feature Barcoding, which provided a cell-by-HTO count matrix. This HTO count matrix, along with the gene count matrices generated via Cell Ranger (above) were used to assign each cell to their respective sample(s) with the demuxEM program. Only cells that were identified as singlets were retained (i.e. no cells identified as a multiplet or unassignable) in the per-sample CellBender-ed gene count matrices.
|
| 149 |
+
|
| 150 |
+
Cellbender output files were read into R (version 4.1.1) and processed utilizing the standard Seurat CCA and later RPCA integration workflows (version 4.3.0). Each of the hashed samples (24 in total) were merged with their respective pair to have a total of twelve samples consisting of six different groups. Each sample was filtered prior to downstream analysis based on their nCount_RNA, nFeature_RNA, and mitochondrial percentages. Samples were then normalized using a LogNormalization method with a scaling factor of 10000 followed by FindVariableFeatures using a Variance-Stabilizing Transformation as the method with the top 2000 features to be returned. The FindIntegrationAnchors function using the CCA reduction method and IntegrateData was utilized to integrate the data together. The integrated data-set was then scaled on which mitochondrial percentage was regressed. A principal component analysis was performed in which only the top 18 dimensions were retained. Uniform Manifold and Projection (UMAP), FindNeighbors, and FindClusters with a resolution of 0.4 was performed on the dataset. To remove doublets in the dataset, we used the package scDblFinder (1.8.0) and their function scDblFinder with the parameters of samples set to our twelve samples, dbr set to NULL, dbr.sd set to 1, clusters set to FALSE, and multiSampleMode set to split. The object was then subsetted to only contain expected singlets. Differential gene expression between clusters was performed using the FindMarkers function with the Wilocox test in Seurat. Violin plots and individual UMAP plots were all generated using the Seurat toolkit VlnPlot and FeaturePlot functions, respectively. Heatmaps were generated utilizing the dittoSeq package (1.9.1) and pheatmap package (version 1.0.12).
|
| 151 |
+
|
| 152 |
+
After identifying the adipocyte population, we subsetted our object on that population, extracting the raw RNA counts on the cells for each of the six samples (YTN, OTN, Y3D, O3D, Y14D, O14D) (Y is young, O is “Old” or as referred to in this paper, Aged). These samples were then integrated together using the standard RPCA integration workflow. There was no further filtering done on the reintegrated adipocyte population. Samples were normalized using a LogNormalization method with a scaling factor of 10000 followed by FindvariableFeatures using a Variance-Stabilizing Transformation as the method with the top 2000 features to be returned. The function SelectIntegrationFeatures was performed on the dataset where it was then scaled on which mitochondrial percentage was regressed, and principal components were found using the ScaleData and RunPCA functions. The FindIntegrationAnchors function using the ROCA reduction method and a k.anchors of 20 and IntegrateData was utilized to integrate the data together. After integration, the dataset was then scaled in which mitochondrial percentage was regressed on again. A principal component analysis was performed in which only the top 18 dimensions were retained. Uniform Manifold and Projection (UMAP), FindNeighbors, and FindClusters with a resolution of 0.2 was performed on the dataset. Differential gene expression between clusters was performed using the FindMarkers function with a Wilcoxon signed-rank test as the method in Seurat. Violin plots and individual UMAP plots were all generated using the Seurat toolkit VlnPlot and FeaturePlot functions, respectively. Heatmaps were generated utilizing the dittoSeq package (1.9.1) and pheatmap package (version 1.0.12).
|
| 153 |
+
|
| 154 |
+
Enrichment analysis was performed on the positively expressed genes with a log2 fold change (LFC) > 0.25 and a P adjusted value < 0.01 on comparison of the young 14 days cold and old 14 days cold groups in the DNL high cluster. The generated gene list, which was in order of significance, was fed into g:Profiler (version 0.2.1) using default parameters except with modifications to query as an ordered query against the ‘mmusculus’ database, a gSCS correction method for multiple testing, with domain scope set to annotated, and sources set to the Reactome database. The top six enriched pathways yielded from the database were taken and displayed in order of P adjusted value.
|
| 155 |
+
|
| 156 |
+
Statistical methods
|
| 157 |
+
|
| 158 |
+
All bar graphs represent the mean ± SE. A Student’s t-test was used when 2 groups were compared. Where multiple conditions were compared, we applied a Holm-Šidák correction for multiple comparisons. p values are indicated by asterisks and defined as *p < 0.05, **p < 0.01 and ***p < 0.001. All statistics were calculated with GraphPad Prism Version 9.5.0.
|
| 159 |
+
|
| 160 |
+
Supplementary Material
|
| 161 |
+
|
| 162 |
+
Supplement 1
|
| 163 |
+
|
| 164 |
+
Acknowledgements
|
| 165 |
+
|
| 166 |
+
We thank members of the Seale lab for helpful advice and discussions.
|
| 167 |
+
|
| 168 |
+
Funding:
|
| 169 |
+
|
| 170 |
+
NIH grants DK120982 and DK121801 to P.S.; T32 HD083185 to C.D.H; T32 DK007314 to E.F.; RC2 DK116691 to E.D.R.
|
| 171 |
+
|
| 172 |
+
Data and materials availability:
|
| 173 |
+
|
| 174 |
+
scRNA-seq and snRNA-seq datasets are deposited in the Gene Expression Omnibus (GEO) under the super series accession number GSE227441. Data analysis pipelines used for processing of raw sequencing data, integration and clustering can be obtained from: https://github.com/calhounr/Aging-impairs-cold-induced-beige-adipogenesis-and-adipocyte-metabolic-reprogramming
|
| 175 |
+
|
| 176 |
+
Figure 1. Aged mice exhibit decreased iWAT beiging in response to cold exposure or β3-agonist treatment.
|
| 177 |
+
|
| 178 |
+
(A) Young (9-week-old) and aged (57-week-old) C57BL/6 mice were acclimated to 30°C for 3 weeks, followed by two additional weeks remaining at 30°C (TN, thermoneutral controls), spending the last 3 days at 6°C (3D, acute cold) or last 14 days at 6°C (14D, chronic cold). (B) Relative mRNA levels of thermogenic marker genes in mouse iWAT from (A), n=5. (C) Immunofluorescence analysis of UCP1 (green) and DAPI (blue) in iWAT sections from mice in (A), LN = lymph node. Scale bar 100 μm. (D-F) Relative mRNA levels of Ucp1 and Cidea in iWAT from young and aged mice that were either: exposed to 6°C cold for 6 weeks (D), treated with CL-316,243 for 1 hour (E) or treated with CL 316,243 for 5 days (F). Data represent mean ± SEM, points represent biological replicates, 2 groups analyzed using a Student’s t-test, and multiple conditions analyzed with a Holm-Šidák correction for multiple comparisons. Significance: not significant, P > 0.05; * P < 0.05 ** P < 0.01; *** P < 0.001.
|
| 179 |
+
|
| 180 |
+
Figure 2. Aging blocks beige adipogenesis from fibroblastic ASPCs.
|
| 181 |
+
|
| 182 |
+
(A) Schematic of PdgfraCreERT2;R26RtdTomato reporter mouse model and lineage tracing paradigm. (B) Flow cytometry-based quantification showing proportion of tdTomato-expressing PDGFRα+cells (as % of total Live, Lin-, PDGFRα+ cells) in iWAT from young and aged Cre+ and Cre− (control) mice. n=6 young, 5 aged (Circles represent male mice, triangles represent female mice). (C) Immunofluorescence analysis of tdTomato (red), UCP1 (green), PLIN1 (white) and DAPI (blue) in iWAT from young and aged reporter mice after 14 days of 6°C cold exposure (chase). Scale bar 100 μm. (D) Representative stitched images of full length iWAT histology slices from samples in (C) showing quantification of traced tdTomato+;UCP1+ multilocular (beige) adipocytes (blue numbers). LN= lymph node, scale bar 500 μm. (E) Quantification of traced beige adipocytes from (D) presented as total cell number (left) or proportion of PLIN1+ area (right), n=7 (young), n=5 (aged). Data represent mean ± SEM, points represent biological replicates, 2 groups analyzed using a Student’s t-test, and multiple conditions analyzed with a Holm-Šidák correction for multiple comparisons. Significance: not significant, P > 0.05; * P < 0.05 ** P < 0.01; *** P < 0.001.
|
| 183 |
+
|
| 184 |
+
Figure 3. Single cell expression profiling of ASPCs during iWAT beiging.
|
| 185 |
+
|
| 186 |
+
(A) Fully integrated UMAP of gene expression in 54,987 stromal vascular cells (FACS depleted of CD45+ immune cells) from young and aged mouse groups detailed in Figure 1A. (B) UMAPs split by condition. (C) Violin plots showing the expression levels of representative marker genes for various cell clusters. y-axis = log-scale normalized read count. (D) Expression heatmap of the top differentially expressed genes in young vs. aged fibroblastic ASPCs (combined Dpp4+, preadipocytes and Cd142+ cells). Table shows expression of these genes in ASPC populations across temperature conditions (TN, cold 3D, cold 14D) from young and aged mice.
|
| 187 |
+
|
| 188 |
+
Figure 4. ASPCs from young and aged mice display similar beige adipogenic activity ex vivo.
|
| 189 |
+
|
| 190 |
+
(A, C) Phase contrast images of DPP4+, ICAM1+ and CD142+ cells from iWAT of young and aged mice that were induced to undergo adipocyte differentiation with minimal (MIN, A) or maximal (MAX, C) induction cocktail for 8 days. Scale bar 200 μm. (B, D) mRNA levels of adipocyte marker genes Adipoq and Fabp4 in cultures from (A, C). Data points represent separate wells, sorted from a pool of 5 mice (A) or sorted from two pools of 2–3 mice (C). (E) Stromal vascular fraction (SVF) cell cultures from the iWAT of young and aged mice were induced to differentiate for 8 days with MIN or MAX cocktail, followed by Bodipy (green) staining of lipid droplets and DAPI (blue) staining of nuclei. Scale bar 100 μm. (F) Relative mRNA levels of Adipoq and Fabp4 in cultures from (E). Data points represent wells from individual mice, n = 5. (G, H) Relative mRNA levels of Ucp1 in adipocyte cultures from (C, E) with or without treatment with isoproterenol for 4 hours. Data points represent wells sorted from two pools of 2–3 mice (G) or wells from individual mice, n=5 (H). Data represent mean ± SEM, 2 groups analyzed using a Student’s t-test, and multiple conditions analyzed with a Holm-Šidák correction for multiple comparisons. Significance: not significant, P > 0.05; * P < 0.05 ** P < 0.01; *** P < 0.001.
|
| 191 |
+
|
| 192 |
+
Figure 5. Single nucleus expression profiling of adipocytes during the beiging process in young and aged mice.
|
| 193 |
+
|
| 194 |
+
(A) Fully integrated UMAP of mRNA levels in 11,905 nuclei from iWAT of mouse groups detailed in Figure 1A, n=2 mice per condition. (B) UMAPs split by condition. (C) Violin plots showing expression patterns of cell cluster-selective marker genes, Y-axis = log-scale normalized read count. (D) UMAP of gene expression in re-integrated adipocyte clusters including 4,937 nuclei from (A) identifying four populations: Npr3-high, beige, DNL-low, and DNL-high. (E) Adipocyte UMAPs split by condition. (F) Violin plots showing expression patterns of selected genes in adipocyte populations, Y-axis = log-scale normalized read count. (G) Adipocyte nuclei numbers in each sample, plotted as percent of total adipocytes captured for that sample.
|
| 195 |
+
|
| 196 |
+
Figure 6. Aging blocks activation of the lipogenic gene program in adipocytes
|
| 197 |
+
|
| 198 |
+
(A) Expression heatmap of the top aging-regulated genes in DNL-high adipocytes at TN (left) and after 14 days of cold exposure (right). (B) Expression heatmap of the top aging-regulated genes in beige adipocytes after 14 days of cold exposure. (C) UMAP of Npr3 mRNA levels in adipocyte populations (from Figure 5D). (D) Violin plot showing Npr3 mRNA levels in adipocyte populations, Y-axis = log-scale normalized read count, first bar in beige is ‘Young 3D’. (E) Npr3 mRNA levels in iWAT from mouse groups described in Figure 1A, n=5. (F) Npr3 mRNA levels in isolated adipocytes from TN- acclimated young and aged mice, n=6. (G) UMAPs of Ucp1, Acly, and co-expression mRNA levels in adipocyte populations from all young and aged mice. (H) Heatmap showing average expression of lipogenic genes in all nuclei from DNL-high and beige adipocytes per condition indicated in the top table. Data represent mean ± SEM, points represent biological replicates, 2 groups analyzed using a Student’s t-test, and multiple conditions analyzed with a Holm-Šidák correction for multiple comparisons. Significance: not significant, P > 0.05; * P < 0.05 ** P < 0.01; *** P < 0.001.
|
| 199 |
+
|
| 200 |
+
Key Resources Table Reagent type (species) or resource Designation Source or reference Identifiers Additional information
|
| 201 |
+
genetic reagent (M. musculus) C57BL/6J The Jackson Laboratory, Bar Harbor, ME RRID:IMSR_JAX:000664
|
| 202 |
+
genetic reagent (M. musculus) C57BL/6JN NIA, Bethesda, MD NA
|
| 203 |
+
genetic reagent (M. musculus) Rosa26 loxp-stop-loxp tdTomato Reporter (Ai14) The Jackson Laboratory, Bar Harbor, ME RRID:IMSR_JAX:007914
|
| 204 |
+
genetic reagent (M. musculus) PdgfraCreERT2 The Jackson Laboratory, Bar Harbor, ME RRID:IMSR_JAX:032770
|
| 205 |
+
antibody Rabbit anti–red fluorescent protein (RFP) Rockland, Pottstown, PA 600-401-379, RRID:AB_2209751 1:500
|
| 206 |
+
antibody Rabbit anti-Perilipin (D418) Cell Signaling, Denvers, MA 3470, RRID:AB_2167268 1:200
|
| 207 |
+
antibody Rabbit anti- UCP1 Specially made by AstraZeneca, Cambridge, UK NA 1:2000
|
| 208 |
+
antibody Anti-mouse CD142 Sino Biological, Chesterbrook, PA 50413- R001 1:100
|
| 209 |
+
antibody Anti-mouse CD142 R & D Systems, Minneapolis, MN AF3178, RRID:AB_2278143 1:50
|
| 210 |
+
antibody Anti-mouse CD140a-(PDGFRα)-PECy7 Biolegend, San Diego, CA 135912, RRID:AB_2715974 1:100
|
| 211 |
+
antibody Anti-mouse-CD31 (APC-Fire) Biolegend, San Diego, CA 102528, RRID:AB_2721491 1:1000
|
| 212 |
+
antibody Anti-mouse CD45-allophycocyanin (APC/Cy7) Biolegend, San Diego, CA 103116, RRID:AB_312981 1:1000
|
| 213 |
+
antibody Anti-mouse ICAM1-phycoerythrin (PE/Cy7) Biolegend, San Diego, CA 116122, RRID:AB_2715950 1:100
|
| 214 |
+
antibody Anti-mouse CD26 (DPP-4)-fluorescein isothiocyanate (FITC) Biolegend, San Diego, CA 137806, RRID:AB_10663402 1:200
|
| 215 |
+
sequence-based reagent mTbp PMID: 24703692 NA F-GAAGCTGCGGTACAATTCCAG
|
| 216 |
+
R-CCCCTTGTACCCTTCACCAAT
|
| 217 |
+
sequence-based reagent mAdipoq PMID: 24703692 NA F-GCACTGGCAAGTTCTACTGCAA
|
| 218 |
+
R-GTAGGTGAAGAGAACGGCCTTGT
|
| 219 |
+
sequence-based reagent mFabp4 PMID: 24703692 NA F-ACACCGAGATTTCCTTCAAACTG
|
| 220 |
+
R-CCATCTAGGGTTATGATGCTCTTCA
|
| 221 |
+
sequence-based reagent mCidea PMID: 24703692 NA F-TGCTCTTCTGTATCGCCCAGT
|
| 222 |
+
R-GCCGTGTTAAGGAATCTGCTG
|
| 223 |
+
sequence-based reagent mPgc1a PMID: 24703692 NA F-CCCTGCCATTGTTAAGACC
|
| 224 |
+
R-TGCTGCTGTTCCTGTTTTC
|
| 225 |
+
sequence-based reagent mUcp1 PMID: 24703692 NA F-ACTGCCACACCTCCAGTCATT
|
| 226 |
+
R-CTTTGCCTCACTCAGGATTGG
|
| 227 |
+
sequence-based reagent mDio2 PMID: 24703692 NA F-CAGTGTGGTGCACGTCTCCAATC
|
| 228 |
+
R-TGAACCAAAGTTGACCACCAG
|
| 229 |
+
sequence-based reagent mAcly PMID: 31141698 NA F-GAGTGCTATTGCGCTTCCC
|
| 230 |
+
R-GGTTGCCGAAGTCACAGGT
|
| 231 |
+
sequence-based reagent mNpr3 This Paper NA F-TTTTCAGGAGGAGGGGTTGC
|
| 232 |
+
R-ACACATGATCACCACTCGCT
|
| 233 |
+
sequence-based reagent mNpr1 MGH PrimerBank Primer Bank ID: 113930717c1 F-GCTTGTGCTCTATGCAGATCG
|
| 234 |
+
R-CCTCGACGAACTCCTGGTG
|
| 235 |
+
sequence-based reagent mNpr2 MGH PrimerBank Primer Bank ID: 118129825c2 F-CATGACCCCGACCTTCTGTTG
|
| 236 |
+
R-CGAACCAGGGTACGATAATGCT
|
| 237 |
+
commercial assay or kit ABI High-Capacity cDNA Synthesis kit Applied Biosystems, Waltham, MA 4368813
|
| 238 |
+
commercial assay or kit Purelink RNA Mini columns Invitrogen, Waltham, MA LT-12183018
|
| 239 |
+
commercial assay or kit TSA TMR Tyramide Reagent Pack Akoya Biosciences, Marlborough, MA NEL742001KT
|
| 240 |
+
commercial assay or kit TSA Fluorescein Tyramide Reagent Pack Akoya Biosciences, Marlborough, MA NEL741001KT
|
| 241 |
+
commercial assay or kit Bulls Eye Decloaking Buffer Biocare, Pacheco, CA BULL1000 MX
|
| 242 |
+
commercial assay or kit AbC Total Antibody Compensation Bead Kit BioLegend,San Diego, CA A10497
|
| 243 |
+
commercial assay or kit Biotium Mix-n-Stain CF647 Sigma, Burlington, MA MX647S100
|
| 244 |
+
commercial assay or kit PicoPure RNA Isolation Kit Invitrogen, Waltham, MA KIT0204
|
| 245 |
+
commercial assay or kit Qubit dsDNA High Sensitivity assay kit ThermoFisher, Waltham, MA Q32851
|
| 246 |
+
commercial assay or kit DNA High Sensitivity Bioanalyzer Chip (Agilent) Agilent, Santa Clara, CA 5067-4626
|
| 247 |
+
software, algorithm Graphpad Prism Graphpad, San Diego, CA RRID:SCR_002798
|
| 248 |
+
software, algorithm Adobe Illustrator Adobe, San Jose, CA RRID:SCR_010279
|
| 249 |
+
software, algorithm Adobe Photoshop Adobe, San Jose, CA RRID:SCR_014199
|
| 250 |
+
software, algorithm Image J PMID: 22743772 RRID:SCR_003070
|
| 251 |
+
software, algorithm Cell Ranger 10x Genomics RRID:SCR_017344
|
| 252 |
+
software, algorithm Seurat PMID: 34062119 RRID:SCR_016341
|
| 253 |
+
software, algorithm bcl2fastq Illumina RRID:SCR_015058
|
| 254 |
+
software, algorithm Cumulus PMID: 32719530 RRID:SCR_021644
|
| 255 |
+
software, algorithm FACSDiva Softward Becton Dickinson, Franklin Lakes, NJ RRID:SCR_001456
|
| 256 |
+
other Tamoxifen (Free Base) Sigma, Burlington, MA T5648
|
| 257 |
+
other Corn Oil Sigma, Burlington, MA C8267
|
| 258 |
+
other 16% Paraformaldehyde EMS, Hatfield, PA 15710
|
| 259 |
+
other TRIzol Invitrogen, Waltham, MA 15596018
|
| 260 |
+
other CL-316,243 Sigma, Burlington, MA C5976
|
| 261 |
+
other 4’,6-Diamidine-2’-phenylindole dihydrochloride (DAPI), 1:10,000 Roche, Basel, Switzerland 10236276001
|
| 262 |
+
other Bovine Serum Albumin, fraction V, fatty-acid free Gold Biotechnology, St. Louis, MO A-421-250
|
| 263 |
+
other DMEM/F12 Fisher Scientific, Waltham, MA 11320033
|
| 264 |
+
other Fetal Bovine Serum Omega Scientific, Tarzana, CA FB-11, Lot 401714
|
| 265 |
+
other Primocin InvivoGen, San Diego, CA ant-pm-2
|
| 266 |
+
other PCR Master Mix, Power SYBR Green Applied Biosystems, Waltham, MA 4367659
|
| 267 |
+
other HBSS, 1X Fisher Scientific, Waltham, MA 14175079
|
| 268 |
+
other Dispase II Roche, Basel, Switzerland 4942078001
|
| 269 |
+
other Collagenase, Type 1 Worthington, Lakewood, NJ LS004197
|
| 270 |
+
other Red Blood Cell Lysis Buffer, 10x BioLegend, San Diego, CA 420302
|
| 271 |
+
other Human Insulin, Novolin Novo Nordisk, Bagsvaerd, Denmark 183311
|
| 272 |
+
other Dexamethasone Sigma-Aldrich, Burlington, VT D4902
|
| 273 |
+
other 3-isobutyl-1-methylxanthine (IBMX) Sigma-Aldrich, Burlington, VT I7018
|
| 274 |
+
other Rosiglitazone Cayman Chemical, Ann Arbor, MI 11884
|
| 275 |
+
other Indomethacin Sigma-Aldrich, Burlington, VT I8280
|
| 276 |
+
other 3,30,5-Triiodo-L-thyronine sodium salt (T3) Sigma-Aldrich, Burlington, VT T6397
|
| 277 |
+
other isoproterenol Sigma-Aldrich, Burlington, VT I6504
|
| 278 |
+
other Biodipy 493/503 Invitrogen, Waltham, MA D3922
|
| 279 |
+
other Hoechst 33342 Thermo Fisher, Waltham, MA 62249
|
| 280 |
+
other Protector RNase Inhibitor Roche, Basel, Switzerland 3335399001
|
| 281 |
+
|
| 282 |
+
Competing Interests: The authors declare no competing interests.
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| 283 |
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==== Front
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Drug Des Devel Ther
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Drug Des Devel Ther
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dddt
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Drug Design, Development and Therapy
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1177-8881
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Dove
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414031
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10.2147/DDDT.S414031
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Retraction
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Orcinol Glucoside Facilitates the Shift of MSC Fate to Osteoblast and Prevents Adipogenesis via Wnt/β-Catenin Signaling Pathway [Retraction]
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Zhou et al
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Zhou et al
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28 3 2023
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28 3 2023
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17 959960
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© 2023 Dove Medical Press.
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2023
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Dove Medical Press.
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https://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
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==== Body
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pmcZhou X, Liu Z, Huang B, et al. Drug Des Devel Ther. 2019;13:2703–2713.
|
| 28 |
+
|
| 29 |
+
The Editor and Publisher of Drug Design, Development and Therapy wish to retract the published article. Concerns were raised regarding the alleged duplication of Oil Red O images in Figures 4 and Figure 6. Specifically, Figure 4C, Oil Red O, Ctrl, appears to have been duplicated with the same image for Figure 6D, Oil Red O, OG+ICG-001.
|
| 30 |
+
|
| 31 |
+
The authors cooperated with the investigation and provided data associated with the study. However, despite the authors’ assistance, it was still not clear how the images came to be duplicated, and, as we cannot verify the validity of the published work, we are therefore retracting the article and the authors agree with this decision.
|
| 32 |
+
|
| 33 |
+
We have been informed in our decision-making by our policy on publishing ethics and integrity and the COPE guidelines on retractions.
|
| 34 |
+
|
| 35 |
+
The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as “Retracted”.
|
| 36 |
+
|
puc/PMC10069774.txt
ADDED
|
@@ -0,0 +1,478 @@
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|
| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
PLoS Biol
|
| 4 |
+
PLoS Biol
|
| 5 |
+
plos
|
| 6 |
+
PLOS Biology
|
| 7 |
+
1544-9173
|
| 8 |
+
1545-7885
|
| 9 |
+
Public Library of Science San Francisco, CA USA
|
| 10 |
+
|
| 11 |
+
36947563
|
| 12 |
+
10.1371/journal.pbio.3002050
|
| 13 |
+
PBIOLOGY-D-22-00947
|
| 14 |
+
Research Article
|
| 15 |
+
Biology and Life Sciences
|
| 16 |
+
Anatomy
|
| 17 |
+
Biological Tissue
|
| 18 |
+
Connective Tissue
|
| 19 |
+
Adipose Tissue
|
| 20 |
+
Medicine and Health Sciences
|
| 21 |
+
Anatomy
|
| 22 |
+
Biological Tissue
|
| 23 |
+
Connective Tissue
|
| 24 |
+
Adipose Tissue
|
| 25 |
+
Biology and Life Sciences
|
| 26 |
+
Biochemistry
|
| 27 |
+
Lipids
|
| 28 |
+
Fats
|
| 29 |
+
Biology and Life Sciences
|
| 30 |
+
Anatomy
|
| 31 |
+
Abdomen
|
| 32 |
+
Medicine and Health Sciences
|
| 33 |
+
Anatomy
|
| 34 |
+
Abdomen
|
| 35 |
+
Biology and Life Sciences
|
| 36 |
+
Anatomy
|
| 37 |
+
Biological Tissue
|
| 38 |
+
Connective Tissue
|
| 39 |
+
Adipose Tissue
|
| 40 |
+
Adipocytes
|
| 41 |
+
Medicine and Health Sciences
|
| 42 |
+
Anatomy
|
| 43 |
+
Biological Tissue
|
| 44 |
+
Connective Tissue
|
| 45 |
+
Adipose Tissue
|
| 46 |
+
Adipocytes
|
| 47 |
+
Biology and Life Sciences
|
| 48 |
+
Cell Biology
|
| 49 |
+
Cellular Types
|
| 50 |
+
Animal Cells
|
| 51 |
+
Connective Tissue Cells
|
| 52 |
+
Adipocytes
|
| 53 |
+
Biology and Life Sciences
|
| 54 |
+
Anatomy
|
| 55 |
+
Biological Tissue
|
| 56 |
+
Connective Tissue
|
| 57 |
+
Connective Tissue Cells
|
| 58 |
+
Adipocytes
|
| 59 |
+
Medicine and Health Sciences
|
| 60 |
+
Anatomy
|
| 61 |
+
Biological Tissue
|
| 62 |
+
Connective Tissue
|
| 63 |
+
Connective Tissue Cells
|
| 64 |
+
Adipocytes
|
| 65 |
+
Biology and Life Sciences
|
| 66 |
+
Developmental Biology
|
| 67 |
+
Life Cycles
|
| 68 |
+
Larvae
|
| 69 |
+
Biology and Life Sciences
|
| 70 |
+
Cell Biology
|
| 71 |
+
Cellular Types
|
| 72 |
+
Animal Cells
|
| 73 |
+
Precursor Cells
|
| 74 |
+
Research and analysis methods
|
| 75 |
+
Specimen preparation and treatment
|
| 76 |
+
Staining
|
| 77 |
+
Nuclear staining
|
| 78 |
+
DAPI staining
|
| 79 |
+
Biology and Life Sciences
|
| 80 |
+
Developmental Biology
|
| 81 |
+
Metamorphosis
|
| 82 |
+
FGF signaling promotes spreading of fat body precursors necessary for adult adipogenesis in Drosophila
|
| 83 |
+
Origin and development of the adult adipose tissue in flies
|
| 84 |
+
Lei Yuting Conceptualization Formal analysis Investigation Visualization Writing – review & editing 1
|
| 85 |
+
Huang Yuwei Conceptualization Formal analysis Investigation Visualization Writing – review & editing 1
|
| 86 |
+
Yang Ke Formal analysis Investigation Visualization Writing – review & editing 1
|
| 87 |
+
Cao Xueya Formal analysis Investigation Writing – review & editing 1
|
| 88 |
+
Song Yuzhao Investigation Writing – review & editing 1
|
| 89 |
+
Martín-Blanco Enrique Investigation Resources Writing – review & editing 2
|
| 90 |
+
https://orcid.org/0000-0002-3823-4473
|
| 91 |
+
Pastor-Pareja José Carlos Conceptualization Formal analysis Funding acquisition Investigation Supervision Visualization Writing – original draft Writing – review & editing 1 3 4 *
|
| 92 |
+
1 School of Life Sciences, Tsinghua University, Beijing, China
|
| 93 |
+
2 Instituto de Biología Molecular de Barcelona, Consejo Superior de Investigaciones Científicas, Parc Científic de Barcelona, Barcelona, Spain
|
| 94 |
+
3 Tsinghua-Peking Center for Life Sciences, Beijing, China
|
| 95 |
+
4 Institute of Neurosciences, Consejo Superior de Investigaciones Científicas-Universidad Miguel Hernández, San Juan de Alicante, Spain
|
| 96 |
+
Schweisguth François Academic Editor
|
| 97 |
+
Institut Pasteur, FRANCE
|
| 98 |
+
The authors have declared that no competing interests exist.
|
| 99 |
+
|
| 100 |
+
* E-mail: jose.pastorp@umh.es
|
| 101 |
+
22 3 2023
|
| 102 |
+
3 2023
|
| 103 |
+
22 3 2023
|
| 104 |
+
21 3 e300205026 4 2022
|
| 105 |
+
24 2 2023
|
| 106 |
+
© 2023 Lei et al
|
| 107 |
+
2023
|
| 108 |
+
Lei et al
|
| 109 |
+
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
|
| 110 |
+
|
| 111 |
+
Knowledge of adipogenetic mechanisms is essential to understand and treat conditions affecting organismal metabolism and adipose tissue health. In Drosophila, mature adipose tissue (fat body) exists in larvae and adults. In contrast to the well-known development of the larval fat body from the embryonic mesoderm, adult adipogenesis has remained mysterious. Furthermore, conclusive proof of its physiological significance is lacking. Here, we show that the adult fat body originates from a pool of undifferentiated mesodermal precursors that migrate from the thorax into the abdomen during metamorphosis. Through in vivo imaging, we found that these precursors spread from the ventral midline and cover the inner surface of the abdomen in a process strikingly reminiscent of embryonic mesoderm migration, requiring fibroblast growth factor (FGF) signaling as well. FGF signaling guides migration dorsally and regulates adhesion to the substrate. After spreading is complete, precursor differentiation involves fat accumulation and cell fusion that produces mature binucleate and tetranucleate adipocytes. Finally, we show that flies where adult adipogenesis is impaired by knock down of FGF receptor Heartless or transcription factor Serpent display ectopic fat accumulation in oenocytes and decreased resistance to starvation. Our results reveal that adult adipogenesis occurs de novo during metamorphosis and demonstrate its crucial physiological role.
|
| 112 |
+
|
| 113 |
+
This study shows that during fly metamorphosis, the adipose tissue of the adult is assembled from proliferating adipocyte precursors that spread from the ventral midline in a process that recapitulates embryonic mesoderm migration.
|
| 114 |
+
|
| 115 |
+
http://dx.doi.org/10.13039/501100001809 National Natural Science Foundation of China 32150710524, 91854207 https://orcid.org/0000-0002-3823-4473
|
| 116 |
+
Pastor-Pareja José Carlos http://dx.doi.org/10.13039/501100004837 Ministerio de Ciencia e Innovación PID2021-122119NB-I00 https://orcid.org/0000-0002-3823-4473
|
| 117 |
+
Pastor-Pareja José Carlos http://dx.doi.org/10.13039/501100004837 Ministerio de Ciencia e Innovación CEX2021-001165-S https://orcid.org/0000-0002-3823-4473
|
| 118 |
+
Pastor-Pareja José Carlos This work was funded by grants 32150710524 and 91854207 from the National Natural Science Foundation of China (https://nsfc.gov.cn) and grant PID2021-122119NB-I00 from Ministerio de Ciencia e Innovación (https://www.ciencia.gob.es), all to J.C.P.-P. J.C.P.-P. was also funded by the “Severo Ochoa” Program for Centers of Excellence (CEX2021-001165-S) from Ministerio de Ciencia e Innovación. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. PLOS Publication Stagevor-update-to-uncorrected-proof
|
| 119 |
+
Publication Update2023-04-03
|
| 120 |
+
Data AvailabilityAll relevant data are within the paper and its Supporting information files.
|
| 121 |
+
Data Availability
|
| 122 |
+
|
| 123 |
+
All relevant data are within the paper and its Supporting information files.
|
| 124 |
+
==== Body
|
| 125 |
+
pmcIntroduction
|
| 126 |
+
|
| 127 |
+
Eukaryotic cells can efficiently store energy in the form of fat inside lipid droplets. Lipid droplets are ER outgrowths consisting of a core of neutral lipids surrounded by a phospholipid monolayer [1]. Many unicellular eukaryotes and certain cell types in multicellular ones possess the ability to produce lipid droplets. However, in the animal kingdom, both vertebrates and arthropods have concentrated lipid storage and release functions in large specialized cells called adipocytes. Differentiated adipocytes associate into adipose tissues and display giant lipid droplets that occupy most of their cytoplasm. In vertebrates, histogenesis of adipose tissue (adipogenesis) is quite complex. Vertebrate adipocytes are generally believed to be of mesodermal origin, but specific populations have been found to derive instead from the neural crest [2]. In addition to fully differentiated adipocytes, mammalian adipose tissues contain stem cell precursors capable of producing new adipocytes [3,4]. Adipose tissue remodeling through formation of new adipocytes (hyperplasia) is a healthy response to caloric excess, whereas expansion of existing adipocytes through increased fat storage (hypertrophy) stresses those cells and associates with metabolic disease [5]. In contrast to adipocyte hyperplasia or hypertrophy, lipodystrophies are a group of congenital and acquired disorders characterized by the absence of functional adipocytes, causing insulin resistance, hyperlipidemia, and other metabolic complications [6]. Better knowledge of basic adipogenetic mechanisms, therefore, is essential to understand and treat conditions affecting adipose tissue health.
|
| 128 |
+
|
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Besides vertebrates, the existence of true adipocytes and adipose tissue is documented in arthropods. The adipose tissue of arthropods, called fat body, has been extensively studied in insects, but is also present in crustaceans, chelicerates (spiders, scorpions, and mites), and myriapods [7]. Within insects, research in the fruit fly Drosophila melanogaster has described the presence of mature fat body in 2 stages of the life cycle of the animal: the larva and the adult. The development of the larval fat body, known to originate from the embryonic mesoderm, is well characterized. Shortly after gastrulation, different groups of mesodermal cells become specified within each segment to give rise to segmental populations of precursors for the somatic musculature, visceral musculature, heart mesoderm, gonadal mesoderm or fat body, depending on antero-posterior and dorso-ventral positional cues provided in part by the overlying ectoderm/epidermis to which they attach [8,9]. Precursors of the larval fat body, in particular, arise at lateral positions inside the domain of expression of segmentation gene eve [9,10]. The earliest sign of fat body differentiation is the expression at stage 10 of the transcription factor Serpent (Srp), required for fat body development [9,11,12]. During the larval stages, after segmental precursors have joined into a continuous larval adipose tissue, larval fat body adipocytes increase their cell size and ploidy through nutrition-dependent endoreplication [13]. Later, the larval fat body undergoes cell dissociation and histolysis during metamorphosis [14,15]. Isolated larval fat body cells are found inside the adult abdomen until 2 days after eclosion. However, in addition to the disappearing larval adipocytes, the eclosed adult displays segmental plates of adult fat body lining the abdomen (Fig 1A), with lesser amounts found in the head, thorax, and female gonads. In contrast to the well-known development of the larval fat body, adult fat body adipogenesis has remained mysterious to this date [16–18]. Clonal analysis shows that the adult fat body, like the larval fat body, is mesodermal in origin [19]. A possible relation between the larval and adult adipose tissues has been a matter of speculation and discussion for long time. Two alternative mechanisms for adult adipogenesis have been proposed: partial reassociation of the dissociated larval fat body [20] or de novo adipogenesis from undifferentiated precursors [21]. Many functional studies support a crucial involvement of the larval fat body in energy storage and metabolic regulation in the fast-feeding larva. Fewer studies, however, have tried to address the role of the adipose tissue in mature adult flies. Furthermore, due to insufficient knowledge of the development of the adult fat body and the lack of genetic tools to specifically image and manipulate it, conclusive proof of its physiological significance has been lacking.
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In this study, we set out to investigate the development of the adult fat body in Drosophila. Through in vivo imaging, we found that the adult fat body originates from a pool of precursors that migrate from the thorax into the abdomen during metamorphosis. These precursors spread from the ventral midline in a process strikingly reminiscent of embryonic mesoderm migration, requiring fibroblast growth factor (FGF) signaling as well. In addition, we show that flies in which adult fat body development is impaired display decreased resistance to starvation.
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Results
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Adult fat body precursors migrate into the abdomen during metamorphosis
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Searching for tools that could help investigate the development of the adult fat body (Fig 1A), we came across OK6-GAL4, a GAL4 enhancer trap insertion in the second chromosome [22]. When we crossed OK6-GAL4 to UAS-GFP flies, we observed expression of GFP in the pupal abdomen during metamorphosis. At 72 h APF (after puparium formation), OK6-driven GFP did not label the cells of the dissociated larval fat body, but was visible in segmental plates of tissue reminiscent of the morphology of the adult fat body (Fig 1B). Staining with the neutral lipid dye BODIPY showed that OK6-positive cells contained lipid droplets, consistent with their identity as developing adipocytes (Fig 1C). Furthermore, these OK6-positive cells were distinct from the dissociated larval adipocytes, which were larger and did not express OK6-GAL4 (Fig 1D). Because at earlier stages of metamorphosis OK6-driven GFP was expressed in single cells attached to the abdominal epidermis, we hypothesized that these were the precursors of the adult fat body. Time-lapse imaging of the pupa (see Materials and methods) revealed that OK6-positive cells started arriving from the thorax at around 15 h APF, migrating and proliferating on the ventral epidermis of the abdomen (Fig 1E and S1 Video). To investigate the origin of these cells, we performed lineage tracing experiments. In these, GAL4-driven expression of the recombinase Flp, together with a flip-out cassette and thermosensitive GAL4 repressor GAL80ts, labeled the progeny of cells expressing at a given stage twi-GAL4 (embryonic mesoderm) and Mef2-GAL4 (myoblasts and muscles) (see Methods). Lineage tracing with twi-GAL4 in the embryo labeled adult adipocytes (Fig 1F), confirming their mesodermal origin [19]. Remarkably, Mef2-GAL4 tracing in larva 1 (L1) stage labeled adult (but not larval) adipocytes and adult muscles (Fig 1G). This result shows that adult and larval adipocyte lineages have diverged at the L1 stage and additionally suggests that adult adipocytes and muscles may descend from a common larval population of progenitors. Altogether, our data show that the adult fat body derives from a population of undifferentiated mesodermal precursors that migrate from the thorax into the abdomen during metamorphosis.
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10.1371/journal.pbio.3002050.g001 Fig 1 Adult fat body precursors migrate into the abdomen during metamorphosis.
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(A) Schematic cartoon depicting the adipose tissue (fat body) in Drosophila larvae and adults. The larval fat body, originating from embryonic mesoderm, disintegrates during metamorphosis. It is not known if the adult fat body is built from larval fat body remnants or assembled de novo from an alternate source of adipocytes. (B) Expression of GFP (green) driven by OK6-GAL4 in pupal abdomens dissected and mounted flat at 50 and 72 h APF (after puparium formation). Abdominal segments A1 to A5 are indicated. (C) Adult fat body marked with OK6-GAL4-driven myr-RFP (magenta) at 72 h APF. Nuclei stained with DAPI (cyan, left) and neutral lipids with BODIPY (green, right). (D) Detail of a 72 h APF abdomen stained with BODIPY (green) showing together adult fat body (OK6>myr-RFP, magenta) and dissociated larval adipocytes. Note the large size of these highly polyploid cells and of their nuclei (blue arrowheads). (E) Still images from a time-lapse recording of an OK6>GFP pupa (ventral view). To image the ventral abdomen, legs were gently displaced anteriorly. Blue lines outline wings, thorax, and abdomen. Yellow dashed lines surround the growing population of OK6-positive cells migrating into the abdomen and proliferating there. Images are maximum intensity projections of 61 confocal sections. See S1 Video. (F) Summary of GAL4 expression patterns, indicating the presence (+) or absence (-) of GFP expression under control of OK6-GAL4, Cg-GAL4, ppl-GAL4, twi-GAL4, and Mef2-GAL4 in different mesodermal derivatives. Shown as well are the results of lineage tracing experiments in which the progeny of all cells that express twi-GAL4 or Mef2-GAL4 at a given stage become permanently labeled (see Methods). (G) Abdomen of a pupa dissected 90 h APF in which cells that have expressed Mef2-GAL4 up to the L1 stage are labeled with GFP (green). Summarized genotype: Mef2-GAL4 + tub-GAL80ts > UAS-Flp > act-y+-GAL4 > UAS-GFP. Nuclei stained with DAPI (blue).
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The GATA transcription factor Serpent is required for early amplification of adult fat body precursors
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Expression of the transcription factor Serpent (Srp) marks the precursors of the larval fat body in the embryo [11]. Furthermore, srp mutant embryos lack fat body, indicating that Srp is essential for correct development of the larval fat body [12]. We stained pupal abdomens with anti-Srp antibody and found that Srp was expressed in the adult fat body precursors, labeled with OK6-GAL4-driven GFP expression, and localized to their nuclei (Fig 2A), hinting an involvement of Srp in adult fat body formation as well. In order to test this, we knocked down the expression of srp in the precursors of the adult fat body using OK6-GAL4-driven transgenic RNAi (S1A Fig). In the abdomen of both wild-type and OK6>srpi adults dissected 2 days after eclosion, BODIPY staining revealed the presence of some fat body tissue. However, compared to wild-type, OK6>wi and OK6>yi control adults, the fat body of OK6>srpi adults was severely reduced (Fig 2B and 2C). To investigate the genesis of this phenotype, we imaged the adult fat body precursors using OK6-GAL4-driven GFP expression. We found that precursors were present in the ventral abdomen of OK6>srpi pupae at 30 h APF (Fig 2D). However, in contrast to the fast proliferation of these cells observed in the wild type, the number of precursors had increased less when we analyzed the same animal 6 h later at 36 h APF (Fig 2E). Counting of cell division events in live recordings lasting 6 h (S1B Fig and S2 Video) showed 132 mitosis/385 initial cells in wild type (0.342 mitosis/cell), and 29 mitosis/172 initial cells in OK6>srpi (0.168 mitosis/cell), indicating a strong difference in proliferation rates. To additionally explore the contribution of apoptosis to the reduction of the adult fat body upon srp knock down, we performed TUNEL staining and found occasional apoptosis in OK6>srpi precursors (S1E and S1F Fig). Because we never observed apoptosis in wild-type precursors, this result, while not statistically different from the wild type, led us to further test the effect of apoptosis. To do that, we expressed apoptosis inhibitor p35 while knocking down expression of srp. This, however, failed to rescue or modify OK6>srpi adult fat body reduction (S1G and S1H Fig), suggesting that precursor apoptosis played a minor role in this reduction.
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10.1371/journal.pbio.3002050.g002 Fig 2 The GATA transcription factor Serpent is required for amplification of adult fat body precursors.
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(A) Adult fat body precursors (OK6-GAL4-driven GFP, green) from an abdomen dissected 72 h APF and stained with anti-Srp antibody (magenta). Nuclei stained with DAPI (cyan). (B) Adult abdomens from a wild-type fly and flies in which srp was knocked down with 3 different RNAi transgenes under OK6-GAL4 control (OK6>srpi). Controls knocking down genes white (OK6>wi) and yellow (OK6>yi) are shown as well. Abdomens were dissected 2 days after eclosion and mounted flat after staining with DAPI (nuclei, blue) and BODIPY (neutral lipids, green). (C) Quantification of adult fat body reduction upon srp knock down. Graph represents the coverage of adult fat body measured in images like those in (B) in at least 5 individuals per genotype, with the height of the bar indicating mean value. Significance of comparisons with the wild type in unpaired t tests reported as follows: n.s.: p > 0.05; ****: p < 0.0001. (D) Adult fat body precursors (OK6-GAL4-driven GFP, white) imaged in vivo in the abdomen (ventral view) of wild-type (top) and OK6>srpi (bottom) pupae at 30 (left) and 36 (right) h APF. Images are maximum intensity projections of 65 confocal sections. (E) Graph representing number of adult fat body precursors at 30 and 36 h APF in 3 wild-type and 3 OK6>srpi animals. Cells were counted in images like those in (D). The data underlying the graphs in the figure can be found in S1 Data.
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To further probe the role of Srp in adult fat body development, we used the Flp/FRT system to generate adipocyte precursors homozygous mutant for srp01459, an srp null mutant allele [23]. To do that, we drove expression of recombinase Flp in precursors under control of OK6-GAL4 and assessed mitotic recombination in the FRT82B site by the loss of the marker Ub-GFP (Fig 3A). Control wild-type clones, negatively labeled by the lack of GFP, represented 42.8% ±3.6 SD of the fat body in pupal abdomens dissected 70 h APF, indicating high efficiency of clone induction (Fig 3B). Homozygous srp01459 nuclei, in contrast, were 23.6% ±6.7 SD of the adult fat body nuclei at 70 h APF, evidencing a growth disadvantage of these cells. Nonetheless, mutant precursors seemed well integrated and displayed lipid droplets (S1I Fig). From these results, we conclude that Srp expression in adult fat body precursors is necessary for the amplification of their numbers during the early phases of adult adipogenesis. Our results additionally suggest that Srp may not be involved in their correct specification and differentiation into adipocytes.
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10.1371/journal.pbio.3002050.g003 Fig 3 srp mutant clones are underrepresented in the adult fat body.
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(A) Adult fat body containing wild-type control (left) or srp mutant (right) mitotic recombination clones induced by expression of recombinase Flp under control of OK6-GAL4. Clones (outlined) are negatively labeled by the absence of Ub-GFP (green) in abdomens dissected at 70 h APF (upper row) or 2 days after eclosion (lower row). OK6-GAL4-driven myr-RFP in magenta. Nuclei stained with DAPI (white). (B) Graph representing the percentage of GFP-negative nuclei (wild-type control or srp mutant clones) in adult fat body dissected at 70 h APF or 2 days after eclosion. Each dot represents a measurement of that percentage in a different individual. The height of the black columns marks mean values. Differences between wild-type and mutant clones are significant in unpaired t tests. **: 0.01 > p > 0.001; ***: 0.001 > p > 0.0001. The data underlying the graphs in the figure can be found in S1 Data.
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Adult fat body precursors spread from the ventral midline
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To further investigate adult adipogenesis, we recorded and analyzed the behavior of adult fat body precursors after the initial migration that brings them to the abdomen. Time-lapse imaging of OK6>GFP animals from 30 h APF showed that precursors in the ventral abdomen quickly converge towards the ventral midline at about 32 h APF (Fig 4A and S3 Video). This convergent movement is coincident with the time when the expanding nests of histoblasts (adult epidermal cells) push and replace the contracting ventral epidermis of the larva [24]. After this ventral contraction, adult fat body precursors spread on the abdominal epidermis, first laterally (Fig 4A and S3 Video) and then dorsally (Fig 4B and S3 Video), as they continue to increase their numbers through cell proliferation. Once the spreading precursors reach the dorsal side, they converge towards the dorsal midline from left and right (Fig 4C and S3 Video). Tracking of cell trajectories showed that adult fat body precursors experienced frequent changes of direction and repulsive interactions during their spreading when they contacted or collided with each other (Fig 4D and S3 Video). At the same time, analysis of the direction of migration with a 4-min resolution (the recording interval of our movies) revealed a tendency towards displacements in the dorsal direction (Fig 4E). Consistent with both contact inhibition and guided migration governing precursor movement, the observed long-term displacement of precursors is less dorsally oriented than predicted by applying the observed 4-min directional bias in simulations of a biased random walk model (Fig 4E; see S1 File and Materials and methods for details of the model). In all, our time-lapse recordings show that adult fat body precursors spread throughout the abdomen from the ventral midline (Fig 4F). In addition, our analysis of their trajectories indicates that a directional component guiding migration dorsally is operative besides mutual repulsion.
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10.1371/journal.pbio.3002050.g004 Fig 4 Adult fat body precursors spread from the ventral midline.
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(A) Still images from a time-lapse recording of adult fat body precursors (OK6>GFP, white) in the ventral abdomen of the pupa (30–40 h APF). Images are standard deviation projections of 62 confocal sections. See S3 Video. (B) Still images from a time-lapse recording of adult fat body precursors (OK6>GFP, white) imaged laterally in the abdomen of the pupa (35–45 h APF; dorsal up, anterior left). Images are maximum intensity projections of 62 confocal sections. See S3 Video. (C) Still images from a time-lapse recording of adult fat body precursors (OK6>GFP, white) in the dorsal abdomen of the pupa (48–56 h APF). Images are maximum intensity projections of 62 confocal sections. See S3 Video. (D) Trajectories of the adult fat body precursors imaged in (B). On the left, complete migration paths are represented (a stack of images for each time point was acquired every 4 min). Total precursor displacement for the 10 h duration of recording is represented as well. See S3 Video. (E) Graph representing the angle of migration of precursors in (B) with respect to the anterior-posterior axis. The angle of a fully dorsal displacement is 90° [see schematic representation in (D)]. For the 4-min interval angle distribution, n = 22,831. For the 10 h angle distribution, n = 485. Predicted distributions based on the assumption that migration is governed solely by dorsal displacement bias (no repulsion) are the result of 100 simulations in a biased random walk model. In this model, cells migrate with constant speed and change direction every 4 min, with probabilities for the new migration angle given by the observed 4-min interval angle distribution (see Materials and methods and S1 File). (F) Schematic illustration of the migration of adult fat body precursors in the abdomen during metamorphosis. Precursors spread laterally and dorsally from the ventral midline. The data underlying the graphs in the figure can be found in S1 Data.
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FGF signaling is required for adult adipogenesis
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The spreading of adult fat body precursors from the ventral midline during metamorphosis, our live imaging showed, is very reminiscent of the migration of embryonic mesodermal cells during gastrulation, taking place after ventral furrow ingression [25]. Mesoderm migration in the embryo depends on FGF signaling. We therefore decided to test the involvement of FGF signaling in the adult fat body formation as well. Embryonic mesoderm cells express the FGF receptor Heartless (Htl) [26,27], whereas the overlying ectoderm expresses its FGF ligands Pyramus (Pyr) and Thisbe (Ths) [28,29]). Knock down of htl under control of OK6-GAL4 in adult fat body precursors produced adults lacking most fat body tissue in their abdomens (Fig 5A, 5B, and 5E). Expression of a dominant negative version of Htl (HtlDN) similarly caused a large reduction in adult fat body tissue (Fig 5C and 5E). Expression of a constitutively active Htl (HtlCA), in contrast, did not cause any apparent defect (Fig 5D and 5E). Consistent with a requirement of htl in the formation of the adult fat body, an htl-GAL4 reporter showed expression in the adult fat body precursors (Fig 5F and S4 Video). We next knocked down the expression of Htl-binding ligands Ths and Pyr (Fig 5G) under control of strong, ubiquitous driver act-GAL4. Knock down of ths strongly reduced the amount of fat body tissue in the adult abdomen (Fig 5H and 5E; control in S2A Fig). Knock down of pyr, in contrast, did not show such effect (Fig 5I). Consistent with a requirement of ths in the formation of the adult fat body, a ths-GAL4 reporter was expressed in the dorsal epidermis of the pupal abdomen (Fig 5K and 5L). Furthermore, adults where ths had been knocked down under control of dorsal epidermal driver pnr-GAL4 presented a wide gap devoid of adult fat body around the dorsal midline (Fig 5J and 5E; control in S2A Fig). Finally, overexpression of Ths in the wing epidermis under control of rn-GAL4 caused the appearance of adult fat body between the dorsal and ventral surfaces of the wing (Fig 5M and 5N). Broadly complementary to ths-GAL4, a pyr-GAL4 reporter showed expression in the ventral epidermis of the pupal abdomen (S2B and S2C Fig) despite a seeming lack of phenotype in act>pyri flies. In all, these data evidence that expression of FGF receptor Htl in adult fat body precursors and FGF ligand Ths in the epidermis are needed for correct formation of the adult fat body and suggest a role of Ths in directing the migration of adult adipocyte precursors.
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10.1371/journal.pbio.3002050.g005 Fig 5 FGF signaling is required for adult adipogenesis.
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(A) Adult abdomen from a wild-type fly dissected 2 days after eclosion and mounted flat after staining with DAPI (nuclei, blue) and BODIPY (neutral lipids, green). (B) Adult abdomens from flies in which htl was knocked down under control of OK6-GAL4 (OK6>htli) using 2 different RNAi transgenes. DAPI (blue) and BODIPY (green) stainings are shown. (C) Adult abdomen from a fly expressing dominant negative Htl (OK6>htlDN). DAPI (blue) and BODIPY (green) stainings are shown. (D) Adult abdomen from a fly expressing a constitutively active Htl (OK6>htlCA). DAPI (blue) and BODIPY (green) stainings are shown. (E) Quantification of adult fat body coverage measured in at least 5 individuals of the indicated genotypes, with the height of the bar indicating mean value. Significance of comparisons with the wild type in unpaired t tests reported as follows: n.s.: p > 0.05; ****: p < 0.0001. (F) Expression of GFP (white) under control of htl-GAL4 in motile fat body precursors imaged in vivo 30 h APF in the abdomen (ventral view). Images are maximum intensity projections of 60 confocal sections. See S4 Video. (G) Cartoon representing the receptor Heartless (htl) and its 2 known FGF-like ligands Thisbe (Ths) and Pyramus (Pyr). (H) Adult abdomens from flies in which ths was knocked down under control of act-GAL4 (act>htli) using 2 different RNAi transgenes. DAPI (blue) and BODIPY (green) stainings are shown. (I) Adult abdomen from a fly in which pyr was knocked down under control of act-GAL4 (act>pyri). DAPI (blue) and BODIPY (green) stainings are shown. (J) Adult abdomens from flies in which ths was knocked down in the dorsal epidermis under control of pnr-GAL4 (pnr>thsi) using 2 different RNAi transgenes. DAPI (blue) and BODIPY (green) stainings are shown. (K) Expression of GFP (white) under control of ths-GAL4 in the dorsal epidermis of the abdomen (lateral view) at 50 and 72 h APF. Images are maximum intensity projections of 60 confocal sections. (L) Z-section of an abdomen expressing GFP (green) under control of ths-GAL4, dissected 72 h APF and stained with F-actin dye phalloidin (magenta). GFP-positive cells are the outermost cells and display actin-rich apical trichomes (arrowheads). Nuclei stained with DAPI (blue). (M) Late pupal wings dissected from a wild-type pupa (left) and a pupa overexpressing Ths under control of rn-GAL4 in the wing blade (rn>thsOE, right), stained with BODIPY (green) and DAPI (blue). (N) Confocal sections of the region of the rn>thsOE wing indicated by the white square in (M), taken on surface (left, dorsal wing epidermis) and 10 μm depth (right, space between dorsal and ventral wing epidermal layers). BODIPY in green and DAPI in blue. Note that the small size of the fat body nuclei identifies these as adult adipocytes, not larval ones (see Fig 1D). The data underlying the graphs in the figure can be found in S1 Data.
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FGF signaling confers directionality and substrate adherence during precursor spreading
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We next tried to ascertain in more detail the role of FGF signaling in adult adipogenesis. To that end, we imaged and analyzed the migration of adult fat body precursors in conditions of loss of FGF signaling (expressing HtlDN, Fig 6A) and excess FGF signaling (expressing HtlCA, Fig 6B). In both cases, live imaging showed precursors spreading (Fig 6A–6C and S5 Video). Analysis of their direction of migration (4-min interval), however, revealed that expression of either HtlDN or HtlCA markedly reduced their tendency to displace dorsally (Fig 6D). This result is highly consistent with a role of dorsally expressed Ths in guiding the migration of Htl-expressing precursors as a chemoattractant cue. However, as previously noted, expression of HtlCA in precursors produced a seemingly normal adult fat body (see Fig 5D), unlike HtlDN (Fig 5C), hinting FGF roles additional or alternative to chemoattraction that might explain this discrepancy. To solve this, we further analyzed the spreading of OK6>htlDN and OK6>htlCA adult fat body precursors, and found that expression of HtlCA, but not HtlDN, reduced their migration speed (Fig 6E). Furthermore, counting of precursors in lateral view recordings from 48 to 58 h APF revealed that the number of precursors expressing HtlDN decreased over time (Fig 6F), instead of increasing as a result of proliferation and income of new cells from the ventral side. Upon close observation, we discovered that precursors expressing HtlDN frequently detached from the abdominal epidermis and abandoned the plane of view to disappear into the body cavity (Fig 6G and S6 Video). Altogether, our analysis of htl loss and gain of function phenotypes is consistent with a function of FGF signaling in both directing migration dorsally and increasing adhesion to the substrate.
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10.1371/journal.pbio.3002050.g006 Fig 6 FGF signaling confers directionality and substrate adherence during precursor spreading.
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(A) Still images from a time-lapse recording of OK6>htlDN adult fat body precursors (OK6>GFP, white) imaged laterally in the abdomen of the pupa (48–58 h APF; dorsal up, anterior left). Images are maximum intensity projections of 60 confocal sections. See S5 Video. (B) Still images from a time-lapse recording of OK6>htlCA adult fat body precursors (OK6>GFP, white) imaged laterally in the abdomen of the pupa (48–58 h APF; dorsal up, anterior left). Images are maximum intensity projections of 60 confocal sections. See S5 Video. (C) Trajectories of the adult fat body precursors imaged in (A) and (B). Complete migration paths are represented (a stack of images for each time point was acquired every 4 min). See S5 Video. (D) Angle of migration (4-min interval) with respect to the anterior-posterior axis of wild type, OK6>htlDN and OK6>htlCA precursors imaged laterally 52–54 h APF. Three recordings were analyzed for each genotype. Error bars represent SD. (E) Average migration velocity (4-min interval) of wild type, OK6>htlDN and OK6>htlCA precursors imaged laterally 52–54 h APF. Three recordings were analyzed for each genotype. Error bars represent SD. Significance of differences with the wild type in two-way ANOVA tests reported in graph as follows: ****: p < 0.0001; n.s.: p > 0.05. (F) Evolution of precursor numbers with time in wild type, OK6>htlDN and OK6>htlCA abdomens imaged laterally 48–58 h APF. Notice stationary/decreasing number of OK6>htlDN precursors. (G) Still images from a time-lapse recording of OK6>htlDN adult fat body precursors (OK6>GFP, white) imaged laterally in the abdomen of the pupa (dorsal up, anterior left) at 53:04 (center panel) and 55:16 h APF. Initial position, trajectory, and final position before detachment of 4 precursors are represented in the left panel. Images are maximum intensity projections of 60 confocal sections. See S6 Video. The data underlying the graphs in the figure can be found in S1 Data.
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Adult fat body adipocytes are formed by fusion of precursors after spreading
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As a result of spreading and continued proliferation, adult fat body precursors end up covering most of the inner surface of the abdominal epidermis, stop migrating and become confluent at about 65 h APF, giving rise to a tissue monolayer (Fig 7A). Soon after becoming confluent, precursors start accumulating fat in the form of lipid droplets, suggesting a process of gradual differentiation into mature adipocytes, complete at day 2 after eclosion of the adult (Fig 7B). During this differentiation process, we noticed the progressive appearance of adipocytes containing 2 and 4 nuclei (Fig 7B), consistent with the observation of binucleate and tetranucleate adipocytes in the adult by others [30]. Indeed, our counts showed that the adult fat body consists entirely of binucleate and tetranucleate cells in proportions that do not seem to change after eclosion (Fig 7C). To ascertain the mechanism by which adult adipocytes become multinucleate, we imaged their late metamorphic development and documented multiple instances of cells merging through disappearance of the intervening plasma membranes (Fig 7D and S7 Video). These observations indicate that adult adipocytes become multinucleate not through mitosis followed by incomplete cytokinesis, as is the case in the mammalian liver [31], but as a result of cell fusion. In these binucleate and tetranucleate adipocytes, in addition, we found that the DNA content of nuclei in adults was 4C in average (Fig 7E). Furthermore, adult adipocyte nuclei were surrounded by a cortex of perinuclear microtubules (Fig 7F), typical of polyploid nuclei [32]. This suggests that adult adipocyte nuclei have switched to an endoreplicative cell cycle and, therefore, are tetraploid rather than diploid stalled in G2. Consistent with this, monitoring of the cell cycle with the FUCCI system [33] revealed that all nuclei in the mature adult fat body are found in G1 (S3 Fig). In summary, our data show that adult fat body precursors during late metamorphosis give rise through cell fusion to large binucleate and tetranucleate adipocytes whose nuclei are in turn tetraploid (Fig 7G).
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10.1371/journal.pbio.3002050.g007 Fig 7 Adult fat body adipocytes are formed by fusion of precursors after spreading.
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(A) Adult fat body precursors (OK6>GFP, green) imaged at indicated times. Notice the presence of dividing cells. (B) Images showing the differentiation of adult precursors into mature adipocytes at indicated times. Eclosion of the adult takes place at about 96 h APF. Stainings with phalloidin (actin cell cortex, magenta, upper and lower row), BODIPY (neutral lipids, green, upper row) and DAPI (nuclei, cyan, lower row) are shown. Notice gradual fat accumulation, cell size increase and appearance of binucleate and tetranucleate cells until day 2 of eclosion. (C) Proportion of cells containing 1, 2, and 4 nuclei at indicated times. Counts in 3 individuals per time point are represented. At least 100 cells were analyzed per individual at 70 and 75 h APF, 40 cells at 80 and 85 h APF, and 30 cells in adults. (D) Still images from a time-lapse recording of the fusion of 2 adult fat body precursors at indicated times (75:40–76:15 h APF). Plasma membrane is labeled with mCD8-RFP (magenta) and nuclei with nls-GFP (green), both driven by OK6-GAL4. Arrowheads point to the disappearing membrane separating the 2 cells. Asterisks mark their nuclei. See S6 Video. (E) Ploidy in nuclei of adult adipocytes at indicated times. Ploidy was estimated from confocal stacks by measuring the amount of DAPI signal through the entire nuclear volume (see Methods). Blood cells were used as a diploid reference (2n, 2C). Each point represents a measurement in a single nucleus. Horizontal lines mark the average value. (F) Microtubule organization in adult adipocytes at 75 h APF (upper row) and 2 days after eclosion (lower row). Microtubules are marked with αTub-GFP (green) driven by OK6-GAL4 and Cg-GAL4, respectively. Nuclei stained with DAPI (cyan). Notice perinuclear microtubule organization in 2 day adult nuclei. (G) Cartoon depicting the maturation of adult fat body precursors into adipocytes. Migrating adult fat body precursors migrate and divide until reaching confluence, when they start accumulating lipid droplets and fusing, giving rise to binucleate and tetranucleate adipocytes. During or after the cell fusion period, nuclei undergo 1 additional round of DNA replication and become tetraploid. The data underlying the graphs in the figure can be found in S1 Data.
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The adult fat body buffers fat levels and provides resistance to starvation
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After studying the morphogenesis of the adult fat body during metamorphosis, we sought to get insights into its function and evidence of its physiological importance. To this end, we analyzed adult flies in which the adult fat body was missing or severely reduced due to knock down of srp or htl under OK6-GAL4 control. In these flies, we found that neutral lipids ectopically accumulated in oenocytes (Fig 8A), a cell type involved like the fat body in lipid metabolism [34]. This result suggests a central role for the adult fat body in storing away fat and buffering its circulation levels in the animal. Further proof of an essential storage role for the adult fat body, its fat content decreased when we subjected adults to starvation for 3 days and recovered normal levels when flies thus starved were refed for 1 day (Fig 8B and 8C). Reduction of fat levels upon starvation was accompanied by autophagy, as evidenced by the presence of vesicles positive for autophagy marker Atg8, reversible upon refeeding as well (Fig 8D and 8E). These results strongly argue that the adult fat body acts as an energy reserve to be mobilized upon starvation. To finally probe the importance of this reserve, we recorded the survival after starvation of wild-type flies and flies in which adult adipogenesis was impaired due to srp or htl knock down. We conducted these starvation experiments in the presence of elav-GAL80, inhibiting GAL4 expression in neurons, to avoid a possible influence of the expression of OK6-GAL4 in motoneurons [22]. Compared to control flies, survival of flies in which srp or htl had been knocked under OK6-GAL4 control was reduced (Fig 8F), showing that the adult fat body reserve provides increased resistance to starvation. In summary, we conclude that the adult fat body, formed de novo during metamorphosis, accomplishes a fat storage role crucial in the physiology of the adult.
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10.1371/journal.pbio.3002050.g008 Fig 8 The adult fat body buffers fat levels and provides resistance to starvation.
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(A) Oenocytes (outlined) from adult wild type, OK6>wi and OK6>yi control, OK6>srpi and OK6>htli abdomens dissected 2 days after eclosion, stained with BODIPY (green) and DAPI (cyan). Notice the accumulation of lipid droplets in OK6>srpi and OK6>htli oenocytes. (B) Adult fat body stained with BODIPY (green) in control flies (5-day adult, left panel), starved flies (2-day adult starved for 3 days, center panel) and refed flies (2-day adult starved for 3 days and refed for 1 day, right panel). Nuclei stained with DAPI (cyan). (C) Quantification of BODIPY staining in the experiment in (B). Each dot represents BODIPY signal intensity measured in 1 cell, with the horizontal bar indicating mean value. Significance of comparisons in Mann–Whitney tests as follows: n.s.: p > 0.05; ****: p < 0.0001. (D) Adult fat body expressing autophagy marker Atg8a-mCherry (driven by BM-40-SPARC-GAL4, magenta) in control flies (5-day adult, left panel), starved flies (2-day adult starved for 3 days, center panel) and refed flies (2-day adult starved for 3 days and refed for 1 day, right panel). Areas inside dashed squares are magnified in upper right corner insets. Nuclei stained with DAPI (cyan). (E) Quantification of autophagy induction in the experiment in (D). Each dot represents number of Atg8a-mCherry-positive puncta counted in 1 cell, with the horizontal bar indicating mean value. Significance of comparisons in Mann–Whitney tests reported as follows: n.s.: p > 0.05; ****: p < 0.0001. (F) Graphs representing survival of control, OK6>srpi and OK6>htli adult male (upper graphs) and female (lower graphs) flies subjected to starvation starting 12 h (left), 2 days (center), and 5 days (right) after eclosion. elav-GAL80, repressing GAL4 activity in neurons, was included in genotypes to prevent a possible influence of OK6-GAL4 expression in larval motoneurons [22]. Three repeats were carried out per genotype and sex, each with at least 85 flies. Error bars represent SD. In all cases, differences with the control were significant in Mantel–Cox tests (****; p < 0.0001). The data underlying the graphs in the figure can be found in S1 Data.
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Discussion
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In this study, we found that adult Drosophila adipocytes do not originate in the larval adipose tissue. Instead, de novo adipogenesis takes place during metamorphosis, when the adult fat body assembles from undifferentiated mesodermal precursors. Through in vivo imaging, we observed that fast-proliferating adult fat body precursors migrate from the thorax into the abdomen, accumulate at the abdominal ventral midline and spread laterally and dorsally on the inner surface of the abdominal epidermis. The migration of these precursors is, therefore, strikingly reminiscent of mesoderm migration during gastrulation in the embryo [25,35,36]. During gastrulation, the cells that give rise to the mesoderm invaginate at the ventral midline, undergo epithelial-to-mesenchymal transition and migrate dorsally along the ectoderm. In light of the similarities between embryonic mesoderm migration and adult adipogenesis, we propose that the formation of the adult fat body in Drosophila is, in essence, a recapitulation of gastrulation that partially reenacts during metamorphosis that earlier process. Outside of insects, a form of secondary gastrulation has been reported during metamorphosis of the jellyfish Aurelia [37]. Another metamorphic process in Drosophila with a clear counterpart in embryonic development is thorax closure at the dorsal midline, reminiscent of embryonic dorsal closure and driven as well by JNK activity in an epidermal edge [38,39]. The extent to which metamorphosis recapitulates key morphogenetic processes of embryonic development is worth exploring. Indeed, comparisons among different Drosophila species revealed reduced transcriptome divergence during both mid-embryogenesis [40] and metamorphosis [41], suggesting intense developmental constraints shared by both stages.
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Supporting the notion that adult adipogenesis recapitulates embryonic mesoderm formation, we found that FGF signaling, required for mesoderm migration, is critical also for adult fat body formation. In both processes, epidermal FGF ligands seem to activate FGF receptor Htl in motile precursors. In the embryo, FGF signaling mutants fail to spread their mesoderm from the ventral midline. Different roles have been attributed to FGF to explain this defect, such as promoting epithelial-to-mesenchymal transition, regulating proliferation and guiding migration as a chemoattractant cue [35,42]. According to our results, FGF may not affect precursor proliferation or differentiation during adult adipogenesis. However, our findings show that FGF acts as a chemoattractant cue that influences the direction of migration, since both loss and gain of htl function makes precursor displacements less dorsally directed. In agreement with such a guidance role, a GAL4 expression reporter for FGF Ths is expressed in the dorsal epidermis and knock down under control of dorsal epidermal driver pnr-GAL4 produced fat body reduction. It would be convenient, however, to confirm this expression pattern through other means. Similarly, our assessment of htl and pyr expression, in adult adipocyte precursors and ventral epidermis, respectively, is based as well on GAL4 reporters.
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Our analysis reveals that a second effect of FGF signaling, potentially more important for adult adipogenesis, is to enhance adhesion between precursors and the epidermis on which they migrate. This conclusion is based on (1) the behavior of htlDN precursors, which frequently detach and disappear into the body cavity; (2) the decreased migration speed of htlCA precursors; and (3) the fact that htlCA precursors give rise to an apparently normal adult fat body despite decreased motility and directionality. In this light, mutual repulsion and contact inhibition of locomotion, similar to the dispersion of embryonic blood cells [43], may be sufficient to ensure spreading of htlCA precursors, although at a slower pace. In embryonic mesoderm spreading, one of the defects reported in htl mutants is reduced expression of mys, encoding a β subunit of the extracellular matrix receptor integrin [44]. Reduced integrin adhesion could explain the detachment of HtlDN precursors, but does not fit well their normal velocity, as loss of integrin should reduce migration speed. A recently described process in which FGF may predominantly regulate adhesion instead of acting as a guidance cue is the wrapping of olfactory glomeruli expressing Ths by Htl-expressing ensheathing glia [45]. In these and other processes, the mechanisms by which FGF signaling regulates substrate adherence are unclear. To address this, migration of adult adipocyte precursors, suitable for long-term live imaging of large numbers of migrating cells and complex genetic manipulations, could be a useful system to elucidate the effects of FGF signaling on migration and the specificity of the roles of ligands Ths and Pyr, still not well understood in the embryo. In this regard, the complementary expression in the pupal abdomen of ths-GAL4 (dorsal) and pyr-GAL4 (ventral) is reminiscent of the situation in the embryonic epidermis, where both Ths and Pyr, complementarily expressed as well, are required for correct mesoderm migration, which warrants further examination of the role of pyr in adipocyte migration despite a seeming lack of effect in act>pyri flies.
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Another point for future clarification is the exact origin of adult fat body precursors and their location prior to migration into the abdomen. This, however, will require additional markers and better knowledge of adult fat body specification. OK6-GAL4, an insertion into the promoter of the gene RapGAP1 [22], allowed us to follow the development of adult fat body precursors into adult adipocytes during metamorphosis. However, OK6-GAL4 expression in these cells does not start until around 12 h APF. Furthermore, a previous study reported that null mutants for RapGAP1, encoding a GTPase activating protein for small GTPase Rap1, were viable and showed no detectable phenotypic abnormalities [46], suggesting that this gene may not have a role in the specification of these cells as adipocyte precursors. Our experiments do not support a role for Srp in adult adipocyte specification either, since null mutant srp precursors seem to be capable of correctly differentiating. Our results, however, evidence reduced rates of cell division in precursors upon srp knock down, indicating a role of Srp in the proliferation of these cells, and probably also in their survival, as suggested by the occasional observation of apoptotic precursors in this condition. It would be interesting to test, in addition, whether Srp is required to establish or maintain htl expression, given that precursor migration is visibly impaired in live recordings of OK6>srpi animals.
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Lineage tracing experiments with Mef2-GAL4 suggest a common lineage with the myoblast precursors of adult muscles. It has been proposed that adult fat body cells derive from adepithelial cells [18]. These are populations of cells in the larval imaginal discs that contain large numbers of adult muscle precursors. According to the images in the reference, however, the putative precursor cells are not adepithelial cells, but differentiated blood cells that typically attach to other regions of the imaginal discs such as the wing pleura or the antenna. Despite this, we consider imaginal disc-associated adepithelial cells a possible source of adult adipocyte precursors. Similar to the adipogenic precursors, adepithelial myoblasts express Htl and respond to the expression of FGF ligands in the epidermis [47–49]. Further suggesting similarity between fat body and muscle precursors is production of syncitia through cell fusion. Adipocyte fusion, however, seems homotypical, unlike myoblast fusion, in which a founder asymmetrically instructs other cells to fuse with it [50]. It will be interesting to investigate in the future how the temporal window of adipocyte cell fusion is determined (70 to 96 h APF) and whether the conserved machinery by which myoblasts fuse to produce muscle fibers is acting in adipocyte fusion as well.
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The consequences and potential advantages for the function of adipocytes of their status as binucleate and tetranucleate polyploid cells is an additional topic of interest stemming from our findings. Human and rodent hepatocytes are frequently binucleate, but this is due to abortive cytokinesis rather than cell fusion [31]. Moreover, in the human liver endoreplication produces tetraploid and octaploid nuclei, giving rise to a mixture of mononucleate 2n, 4n, 8n and binucleate 2x2n, 2x4n cells [51]. Faster attainment of large cell volumes is often adduced to explain polyploidy in the larval fat body and other endoreplicating larval tissues [52], a purpose cell fusion could serve as well. Alternatively, it has been proposed that polyploidy confers protection to human hepatocytes against genotoxic damage. Under this lens, acquiring multiple genome copies could buffer the effects of mutations caused by DNA damaging agents [53]. Regardless of the reasons behind multinucleation/polyploidy in the adult fat body, a possible consequence, our results suggest, is limited tissue plasticity. We did not observe after eclosion mitotic cells, nor any variation in nuclei number, DNA content (4C) or proportions of binucleate/tetranucleate cells. Starvation did not seem to induce changes in these features either. Starvation and refeeding, however, did decrease and increase cell size, respectively. It is likely, therefore, that adult fat body remodeling can take place only through changes in cell size, not in cell or nuclear number. However, further experiments should test the possibility that stimuli such as excess nutrition, damage, or traumatic tissue loss might induce remodeling or regrowth through endoreplication, polyploid mitosis, depolyploidizing divisions, or reactivation of cell fusion. Additionally, in light of the possibly low plasticity of the adult fat body, an interesting question to ask is whether the diet of the larva could imprint the metabolic status of the adult by affecting adult fat body development, for instance, by influencing the initial number of precursors or their proliferative potential.
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Despite our data showing that adult adipocytes do not derive from larval adipocytes, functional relations between these 2 separate adipocyte populations during the time they coexist is an interesting topic deserving of further investigation. We observed that adult adipocytes increase their size from 0 to 2 days after eclosion, consistent with previous reports [54] and coincident with the final disappearance of the dissociated larval adipocytes, suggesting a transfer of their fat content to the adult fat body. Indeed, a role in resistance of the adult to starvation has been postulated for these larval adipocytes persisting in the body cavity in the eclosed adult [55]. This is based on experiments where survival of starved flies was reduced in older adults with respect to younger ones starved since eclosion. Our own starvation experiments, however, did not find such effect, as flies starved since day 5 after eclosion were no less resistant than those starved from day 2 or day 1. Alternatively, dissection of the influence of the larval fat body on adult fat body development or adult physiology could come from experiments in which the elimination of larval adipocytes is prevented. We were, however, unsuccessful in delaying the disappearance of the larval fat body beyond day 2 through expression of p35 or DIAP1, inconsistent as well with a previous report [55].
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Besides characterizing adult fat body development, we importantly provide evidence of its physiological significance, for which conclusive prove had remained elusive. We found that flies where the adult fat body was missing or reduced (upon srp or htl knock down) displayed accumulation of neutral lipids in oenocytes and decreased viability upon starvation, demonstrating an essential role of the adult fat body as a lipid store and energy reserve. Consistent with this, starvation induced adult adipocyte autophagy and reduction in fat content, both reversible upon refeeding. By generating flies specifically lacking adult fat body, finally, our study opens new avenues to systematically research adipocyte function in the adult, including roles beyond storage and metabolic regulation, for instance, in endocrine signaling, matrix production, detoxification, immune responses, reproduction, and mating and feeding behaviors.
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Methods
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Drosophila genetics
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Standard fly husbandry and genetic methodologies were used to obtain the required genotypes for each experiment (see S1 Table for a detailed list of experimental genotypes). Fly strains and genetic crosses were maintained on standard medium prepared in our laboratory with yeast (24.5 g/L), cornmeal (50 g/L), agar (10 g/L), white granulated sugar (7.25 g/L), brown granulated sugar (30 g/L), propionic acid (4 mL/L), methyl-4-hydroxybenzoate (1.75 g/L), and absolute alcohol (17.5 mL/L). Pupae were staged by collection at the white pupa stage (0 h APF). Adults were staged by collection of newly eclosed animals from vials emptied at least 4 h before (day 0 adult). Only males were imaged and analyzed, except for the survival experiment in Fig 8F, in which both males and females were separately subjected to starvation. The GAL4-UAS system was employed to drive UAS transgene expression under the control of GAL4 drivers. Crosses were maintained at 25 °C except for lineage tracing experiments involving tub-GAL80ts, in which cultures were maintained at 18 °C until transferred to 30 °C to initiate GAL4-driven gene expression. In lineage tracing experiments, expression of the yeast recombinase Flp driven by twi-GAL4 or Mef2-GAL4 excises an FRT-flanked sequence in a GAL4 flip-out cassette [56], turning on permanent, inheritable GAL4 expression in the affected cells and their progeny even after twi-GAL4 or Mef-GAL4 have ceased to be expressed in them. The time of labeling was additionally controlled with thermosensitive GAL4 repressor tub-GAL80ts by staging and transferring animals from 18 °C to 30 °C at L1, L2, L3, or white pupa stage (0 h APF). Negatively labeled mitotic recombination clones (Figs 3 and S1G) were generated through the Flp/FRT system [57]. The following strains were used:
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w; OK6-GAL4 (BDSC, 64199),
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+
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| 223 |
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w; UAS-GFP.S65T (BDSC, 1521),
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| 224 |
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| 225 |
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w; UAS-myr-RFP / TM6B (BDSC, 7119),
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| 226 |
+
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| 227 |
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w; Cg-GAL4 (BDSC, 7011),
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| 228 |
+
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| 229 |
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ppl-GAL4 (Gift from Pierre Leopold),
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| 231 |
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w twi-GAL4 (BDSC, 914),
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| 232 |
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| 233 |
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y w; ay-GAL4 UAS-GFP.S65T / CyO (BDSC, 4411),
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| 234 |
+
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| 235 |
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w; Sco / CyO; tub-GAL80ts (BDSC, 7018),
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| 236 |
+
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| 237 |
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y w; Mef2-GAL4 (BDSC, 27390),
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+
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| 239 |
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w1118 (BDSC, 3506),
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+
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| 241 |
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y v sc sev; UAS-w.RNAiTRiP.HMS00017 (THFC, THU0558),
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| 242 |
+
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y v sc sev; UAS-y.RNAiTH03319.N (THFC, TH03319.N),
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| 244 |
+
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| 245 |
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y v sc sev; UAS-srp.RNAiTRiP.HMS01298 (THFC, THU1529),
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| 246 |
+
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| 247 |
+
y v sc sev; UAS-srp.RNAiTRiP.HMS01083 (BDSC, 34080),
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| 248 |
+
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| 249 |
+
w; UAS-srp.RNAiVDRC.v35578 (VDRC, v35578),
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| 250 |
+
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| 251 |
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w; FRT82B Ubi-GFP (BDSC, 5188),
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| 252 |
+
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| 253 |
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y w; FRT82B (gift from Tian Xu),
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| 254 |
+
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| 255 |
+
y w; UAS-Flp / CyO (BDSC, 4539),
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| 256 |
+
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| 257 |
+
srp01549 / TM3, Sb (BDSC, 11538),
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| 258 |
+
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| 259 |
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w; UAS-htl.RNAiVDRC.v6692 (VDRC, v6692),
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| 260 |
+
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| 261 |
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w; UAS-htl.RNAiVDRC.v27180 (VDRC, v27180),
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| 262 |
+
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| 263 |
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y w; UAS-htl.DN.M; UAS-htl.DN.M (BDSC, 5366),
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| 264 |
+
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| 265 |
+
w; UAS-htl.lambda.M (BDSC, 5367),
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| 266 |
+
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| 267 |
+
w; GMR93H07-GAL4 (BDSC, 40669),
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| 268 |
+
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| 269 |
+
y w; act5C-GAL4 / TM6B (BDSC, 3954),
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| 270 |
+
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| 271 |
+
w; UAS-ths.RNAiVDRC.v24536 / TM3 (VDRC, v24536),
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| 272 |
+
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| 273 |
+
y w; UAS-ths.RNAiVDRC.v102441 (VDRC, v102441),
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| 274 |
+
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| 275 |
+
y v; UAS-pyr.RNAiTRiP.HMJ30113 / CyO (BDSC, 63547),
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| 276 |
+
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| 277 |
+
y w; pnr-GAL4 / TM3,Ser (BDSC, 3039),
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| 278 |
+
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| 279 |
+
w; thsMI07139-TG4.1 / CyO; MKRS / TM6B (BDSC, 77475),
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| 280 |
+
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| 281 |
+
w; rn-GAL4 / TM3,Sb (BDSC, 7405),
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| 282 |
+
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| 283 |
+
w; UAS-ths.S (BDSC, 93874),
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| 284 |
+
|
| 285 |
+
y w; UAS-mCD8-GFP (BDSC, 5137),
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| 286 |
+
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| 287 |
+
w; UAS-GFP.nls (BDSC, 4776),
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| 288 |
+
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| 289 |
+
w; UAS-mCD8-RFP (BDSC, 32219),
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| 290 |
+
|
| 291 |
+
w; UAS-GFPS65C.αTub84B / CyO (BDSC, 7374),
|
| 292 |
+
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| 293 |
+
BM-40-SPARC-GAL4 (gift from Hugo Bellen),
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| 294 |
+
|
| 295 |
+
y w; UAS-mCherry.Atg8a (BDSC, 37750),
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| 296 |
+
|
| 297 |
+
w; elav-GAL80 (gift from Bing Zhou),
|
| 298 |
+
|
| 299 |
+
w; UAS-GFP.E2F1.1–230 UAS-NLS.CycB.1-266 / CyO; MKRS / TM6B (BDSC, 55110),
|
| 300 |
+
|
| 301 |
+
y w; pyrCR01744-TG4.2 / SM6a (BDSC, 91292).
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| 302 |
+
|
| 303 |
+
Tissue dissections
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| 304 |
+
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| 305 |
+
To dissect pupal abdomens, we attached pupae to glass slides through their ventral sides using double-sided sticky tape. Then, we proceeded to open and peel the pupal case with fine tip forceps, pull out the animal carefully, and transfer it to a Sylgard plate filled with PBS for dissection. Using dissection scissors, we separated the abdomen from the thorax and cut open the abdomen on its ventral side. Afterwards, we removed guts, gonads, larval fat body, and other inner tissues using forceps. Abdomens were then fixed in 4% PFA for 15 min and washed twice in PBS for 15 min. After this, abdomens were either further processed for tissue staining (see below) or mounted flat for direct observation with their inside surface up on a glass slide in a drop of DAPI-Vectashield (Vector Laboratories). A similar strategy was used for dissecting adult abdomens, only flies were immobilized by anesthetization with CO2, not stuck to a glass slide wit tape.
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| 306 |
+
|
| 307 |
+
Tissue stainings
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| 308 |
+
|
| 309 |
+
For neutral lipid stainings, fixed pupal and adult abdomens were stained in BODIPY 493/503 (1:3,000 dilution of a 1 mg/mL stock, Life Technologies) in PBS for 1 h at room temperature and washed twice in PBS for 10 min before mounting in DAPI-Vectashield. For double staining of neutral lipids and actin cortex (Fig 7B), we stained fixed pupal and adult abdomens with Texas-Red phalloidin (1:100, Life Technologies) and BODIPY 493/503 (1:3,000 dilution of a 1 mg/mL stock, Life Technologies) in PBT (PBS containing 0.1% Triton X) for 2 h at room temperature, followed by PBS washes (3 × 20 min). For single phalloidin stainings (Figs 5L and S2C), we stained fixed pupal abdomens with Texas-Red phalloidin (1:100, Life Technologies) in PBT for 2 h at room temperature, followed by PBS washes (3 × 20 min). For anti-Srp antibody staining (Figs 2A and S1A), fixed samples were blocked in PBT-BSA (PBS containing 0.2% Triton X-100 detergent, 1% BSA, and 250 mM NaCl) for 1 h, incubated overnight with anti-Srp primary antibody (1:200) in PBT-BSA at 4 °C, washed in PBT-BSA (3 × 20 min), incubated for 2 h in anti-rabbit IgG conjugated to Alexa-555 (1:200, Life Technologies) in PBT-BSA at room temperature, and washed in PBS (3 × 10 min). For staining of apoptotic adult fat body precursors (S1C Fig), fixed pupal abdomens were permeabilized overnight in PBT-BSA at 4 °C, incubated in TUNEL mixture (One Step TUNEL Apoptosis Assay Kit, red fluorescence, Beyotime Biotechnology) for 1 h at 37 °C and washed in PBT-BSA (3 × 10 min). All samples were finally mounted in DAPI-Vectashield.
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| 310 |
+
|
| 311 |
+
Imaging of fixed tissues and analysis
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| 312 |
+
|
| 313 |
+
Images of fixed adult abdomens stained with BODIPY in Figs 2B, 5A–5D, 5H–5J, S1E, and S2B were acquired in a Zeiss Axio Imager D.2 epifluorescence microscope using a 10 × / NA 0.3 objective. Other images of fixed pupal and adult abdomens were acquired with a Zeiss LSM780 confocal microscope using 10 × / NA 0.3, 20 × / NA 0.8, 40 × / NA 1.2 (water), or 63 × / NA 1.4 (oil) objectives. Nuclear counts in Fig 7C were performed using the Multi-point tool in ImageJ-FIJI software. These counts were conducted on confocal stacks of images showing nuclear DAPI signal and plasma membrane OK6>mCD8-GFP (pupae) or phalloidin (adults). Three individuals were analyzed for each developmental time point. For nuclear ploidy estimation in Fig 7E, confocal stacks of DAPI images were outlined and labeled with the Surface function in Imaris 9.8.1 software (Bitplane) and total DAPI signal inside the nucleus was computed. Ploidy was calculated with reference to the average DAPI fluorescence value of diploid (2n, 2C) blood cells. For quantification of BODIPY in Fig 8C, signal intensity was measured in individual cells using ImageJ-FIJI in 3 images per condition. For quantification of autophagy in Fig 8E, the number of cytoplasmic Atg8a-mCherry puncta in cells was manually counted using the Multi-point tool of ImageJ-FIJI in 3 images per condition.
|
| 314 |
+
|
| 315 |
+
Live imaging and analysis
|
| 316 |
+
|
| 317 |
+
For live imaging of adult fat body formation during metamorphosis, pupae were removed completely from the pupal case with forceps and deposited on a glass-bottomed dish with a small drop of halocarbon oil 700 (Sigma) placed between the glass and the area to image. At the time of imaging, the glass-bottomed plate was inverted, leaving the animal hanging from the glass, attached to it by the surface tension of the oil. To maintain humidity, a piece of paper tissue soaked with water was located inside the dish. Imaging was conducted at a room temperature of 23 °C in a Zeiss LSM780 confocal microscope using a 10 × / NA 0.3 objective for recordings of precursor migration (S1–S6 Videos), counting of OK6>srpi precursors (Fig 2D) and documentation of htl, ths, and pyr expression (Figs 5F, 5K, and S2B). For quantification of adult fat body reduction (Figs 2C, 5E, and S1F), we measured the area covered by fat body in images like those in Figs 2B, 5A–5D, 5H–5J, and S1E in at least 5 individuals per genotype. Number of precursors at 30 h APF and 36 h APF in wild type and OK6>srpi animals were counted using the Multi-point tool in ImageJ-FIJI software. A 40 × / NA 0.95 (air) objective was used for recordings of precursor fusion (S7 Video). From confocal stacks, maximum intensity projections or standard deviation projections were obtained using Zeiss Zen software. In recordings of precursor migration, 60 to 65 confocal sections were acquired per time point with a z-step of 1.7 to 2.0 μm at intervals of 4 min. In ventral view recordings and imaging in vivo (Figs 1E, 2D, 4A, and 5F), the legs were carefully displaced anteriorly, out of the imaging frame. For recordings of precursor fusion, 16 confocal sections were acquired per time point with a z-step of 1.2 μm at intervals of 5 min.
|
| 318 |
+
|
| 319 |
+
Videos of maximum intensity or standard deviation projections were imported into Imaris 9.8 software to analyze precursor migration. The Spots tool was used to track cells and generate trajectories with the following parameters: 20 μm maximum distance between successive time points, 2 time points maximum gap size, and 10 time points minimum track duration. Raw data for cell position was exported from Imaris into Excel, where we obtained displacement angles and speed through basic trigonometric calculations.
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| 320 |
+
|
| 321 |
+
Biased random walk simulation
|
| 322 |
+
|
| 323 |
+
To simulate paths of cell migration and predict 1-h and 10-h distribution of displacement angles in Fig 4E, we devised a simple biased random walk model, implemented through an Excel formula contained in S1 File. In this model, cells migrate with a constant speed of 1 au/4 min and change their migration angle every 4 min, with the probabilities of the new angle given by the 4-min distribution of displacement angles observed in live recordings (also in Fig 4E). Plotted predicted distributions correspond to 100 simulations.
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| 324 |
+
|
| 325 |
+
Starvation assays
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| 326 |
+
|
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Starvation/refeeding experiments in Fig 8B and 8D were conducted by placing 12-h, 2-day and 5-day-old male adults on starvation medium (2% agar medium) for 3 days before dissection. For refeeding, animals starved as above were transferred back to standard medium and then dissected. For survival tests in Fig 8F, 2-day adults were placed on starvation medium and the number of surviving flies were counted at 12 h intervals. Three replicates of the experiment were performed separately for males and females, each replicate consisting of 2 vials containing 15 to 20 animals. Significance of differences with the control was tested through Mantel–Cox tests using GraphPad Prism 8. All differences were significant (****; p < 0.0001).
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The numerical data used in all figures are included in S1 Data.
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Supporting information
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S1 Fig Srp is required for amplification of adult fat body precursors (related to Figs 2 and 3).
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(A) Adult fat body precursors (OK6-GAL4-driven GFP, green) in wild-type control (left) and OK6>srpi (right) abdomens dissected 72 h APF and stained with anti-Srp antibody (magenta). (B) Still images from movies recorded between 30 and 36 h APF showing examples of cell division in adult fat body precursors (OK6-GAL4-driven GFP, white) from wild-type control and OK6>srpi animals. See also S2 Video. (C) TUNEL apoptosis staining (magenta) of adult fat body precursors (OK6-GAL4-driven GFP, green) from wild type, OK6>srpi and OK6>htli abdomens dissected 36 h APF. Apoptotic precursors (arrowheads) were observed in 3 out of 10 OK6>srpi. (D) Quantification of TUNEL-positive apoptotic adult fat body precursors in abdomens dissected 36 h APF of the indicated genotypes. Each dot represents the percentage of TUNEL positive precursors in 1 individual. Between 40 and 241 precursors were scored per individual. (E) Adult abdomens from control, OK6>srpi and OK6>htli flies, all expressing apoptosis inhibitor p35 under OK6-GAL4 control. Tissues stained with DAPI (nuclei, blue) and BODIPY (neutral lipids, green). (F) Coverage of adult fat body measured in images like those in (E) in at least 5 individuals per genotype, with the height of the bar indicating mean value. p35 expression shows no significant effect on OK6>srpi and OK6>htli phenotypes (unpaired t tests; n.s.: p > 0.05). Data for OK6>srpi and OK6>htli from Figs 2C and 5E, respectively. (G) High magnification view of srp01549 homozygous adult adipocytes generated in wild-type animals through mitotic recombination (see Fig 3). Mutant cells are negatively labeled by loss of Ub-GFP (green). OK6-GAL4-driven myr-RFP in magenta. Nuclei stained with DAPI (white). Asterisks mark circular spaces in the cytoplasm indicative of lipid droplets. The data underlying the graphs in the figure can be found in S1 Data.
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(TIF)
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Click here for additional data file.
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S2 Fig RNAi controls and pyr-GAL4 expression (related to Fig 5).
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(A) Adult abdomens from control flies in which yellow was knocked down under control of act-GAL4 (act>yi) and pnr-GAL4 (pnr>yi). DAPI (blue) and BODIPY (green) stainings are shown. (B) Expression of GFP (white) under control of pyr-GAL4 in the ventral epidermis of the abdomen (lateral view) at 50 and 72 h APF. Images are maximum intensity projections of 60 confocal sections. (C) Z-section of an abdomen expressing GFP (green) under control of pyr-GAL4, dissected 72 h APF and stained with F-actin dye phalloidin (magenta). GFP-positive cells are the outermost cells and display actin-rich apical trichomes (arrowheads). Nuclei stained with DAPI (blue).
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(TIF)
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Click here for additional data file.
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S3 Fig FUCCI monitoring of cell cycle stage in adult fat body precursors and mature adult adipocytes (related to Fig 7).
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Adult fat body precursors (30 h APF and 60 h APF) and mature adipocytes (2 days after eclosion) expressing FUCCI system of cell cycle monitoring components [33] E2F-GFP (green) and CycB-RFP (magenta) under control of OK6-GAL4 (precursors) and Cg-GAL4 (mature adipocytes). In the adult, mature adipocytes are all found in G1 (accumulation of E2F-GFP in absence of CycB-RFP). CycB-RFP separately shown below.
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(TIF)
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Click here for additional data file.
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S1 Video Migration of adult fat body precursors into the abdomen.
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(MP4)
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Click here for additional data file.
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S2 Video Proliferation of early adult fat body precursors.
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(MP4)
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Click here for additional data file.
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S3 Video Spreading of adult fat body precursors.
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S4 Video Expression of htl-GAL4 in adult fat body precursors.
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(MP4)
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S5 Video Spreading of htlDN and htlCA adult fat body precursors.
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(MP4)
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Click here for additional data file.
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S6 Video Detachment of htlDN adult fat body precursors.
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(MP4)
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Click here for additional data file.
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S7 Video Fusion of adult fat body precursors.
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(MP4)
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Click here for additional data file.
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S1 Table Detailed genotypes.
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(XLSX)
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Click here for additional data file.
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S1 File Biased random walk model.
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(XLSX)
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Click here for additional data file.
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S1 Data Numerical data.
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(XLSX)
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We thank Deborah Keiko-Hoshizaki for anti-Srp antibody. We also thank the Bloomington Drosophila Stock Center (BDSC); Vienna Drosophila RNAi Center (VDRC); Tsinghua Fly Center (THFC); Junhai Han, Yulong Li, and Bing Zhou for providing fly strains; and José Martos-Marqués for technical advice on time-lapse imaging.
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==== Refs
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| 1 |
+
LICENSE: This file is available for text mining. It may also be used consistent with the principles of fair use under the copyright law.
|
| 2 |
+
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| 3 |
+
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| 4 |
+
8213295
|
| 5 |
+
1156
|
| 6 |
+
Biomed Pharmacother
|
| 7 |
+
Biomed Pharmacother
|
| 8 |
+
Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
|
| 9 |
+
0753-3322
|
| 10 |
+
1950-6007
|
| 11 |
+
|
| 12 |
+
36921534
|
| 13 |
+
10071559
|
| 14 |
+
10.1016/j.biopha.2023.114514
|
| 15 |
+
NIHMS1886748
|
| 16 |
+
Article
|
| 17 |
+
Piceatannol induces regulatory T cells and modulates the inflammatory response and adipogenesis
|
| 18 |
+
Rakib Ahmed a1
|
| 19 |
+
Mandal Mousumi a1
|
| 20 |
+
Showkat Anaum a
|
| 21 |
+
Kiran Sonia a
|
| 22 |
+
Mazumdar Soumi b
|
| 23 |
+
Singla Bhupesh a
|
| 24 |
+
Bajwa Aman cd
|
| 25 |
+
Kumar Santosh a
|
| 26 |
+
Park Frank a
|
| 27 |
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Singh Udai P. a*
|
| 28 |
+
a Department of Pharmaceutical Sciences, College of Pharmacy, The University of Tennessee Health Science Center, Memphis, TN, USA
|
| 29 |
+
b Department of Physiology, College of Medicine, The University of Tennessee Health Science Center, Memphis, TN, USA
|
| 30 |
+
c Transplant Research Institute, James D. Eason Transplant Institute, Department of Surgery, College of Medicine, The University of Tennessee Health Science Center, Memphis, TN, USA
|
| 31 |
+
d Department of Genetics, Genomics, and Informatics, College of Medicine, The University of Tennessee Health Science Center, Memphis, TN, USA
|
| 32 |
+
1 These authors contributed equally to this manuscript
|
| 33 |
+
|
| 34 |
+
* Corresponding author.: usingh1@uthsc.edu (U.P. Singh).
|
| 35 |
+
29 3 2023
|
| 36 |
+
5 2023
|
| 37 |
+
13 3 2023
|
| 38 |
+
01 5 2023
|
| 39 |
+
161 114514114514
|
| 40 |
+
This file is available for text mining. It may also be used consistent with the principles of fair use under the copyright law.
|
| 41 |
+
The beneficial effects of the polyphenolic compound piceatannol (PC) has been reported for metabolic diseases, antiproliferative, antioxidant, and anti-cancer properties. Despite its beneficial effects on inflammatory diseases, little is known about how PC regulates inflammatory responses and adipogenesis. Therefore, this study was designed to determine the effects of PC on the inflammatory response and adipogenesis. The effect of PC on splenocytes, 3T3-L1 adipocytes, and RAW264.7 macrophages was analyzed by flow cytometry, qRT-PCR, morphometry, and western blot analysis. PC induced apoptosis in activated T cells in a dose-dependent manner using stimulated splenocytes and reduced the activation of T cells, altered T cell frequency, and interestingly induced the frequency of regulatory T (Treg) cells as compared to controls. PC suppressed the expression of TNF-α, iNOS, IL-6R, and NF-κB activation in RAW264.7 macrophages after lipopolysaccharides (LPS)-induction as compared to the control. Interestingly, PC altered the cell morphology of 3T3-L1 adipocytes with a concomitant decrease in cell volume, lipid deposition, and TNF-α expression, but upregulation of leptin and IL-1β. Our findings suggested that PC induced apoptosis in activated T cells, decreased immune cell activation and inflammatory response, and hindered adipogenesis. This new set of data provides promising hope as a new therapeutic to treat both inflammatory disease and obesity.
|
| 42 |
+
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| 43 |
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Piceatannol (PC)
|
| 44 |
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Regulatory T (Treg) cells
|
| 45 |
+
Inflammation
|
| 46 |
+
Macrophage
|
| 47 |
+
Adipogenesis
|
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+
|
| 49 |
+
pmc1. Introduction
|
| 50 |
+
|
| 51 |
+
Piceatannol (PC) (3,4′,3′,5-trans-trihydroxystilbene) is a stilbene and a resveratrol analog, which is commonly found in red grapes, wines, passion fruit, Japanese knotweed, and Asian legumes [1,2]. Although resveratrol has beneficial effects on chronic diseases, it has poor bioavailability and rapid metabolism [3]. To overcome this issue, several analogs of resveratrol, including PC, have been studied to determine their effect on inflammatory diseases. Studies have reported that PC has exhibited anti-cancer, anti-inflammatory, and antioxidant activities [2,4,5], but the mechanism is not clear. In addition to this, it has been reported that PC mediates tumor necrosis factor-α (TNF-α) mediated inflammation and inhibits the production of prostaglandin 2 (PGE2), and nitric oxide (NO) by modulating transcription factor nuclear factor kappa B (NF-κB) and CCAAT-enhancer-binding proteins (C/EBP) in RAW264.7 macrophage cell lines [6]. Recently, it was shown that PC exerts anti-obesity effects in mice through modulating adipogenic proteins and gut microbiota [7]. Further, PC inhibits adipogenesis by modulating mitotic clonal expansion and insulin-dependent signaling in the early phase of adipocyte differentiation [8]. However, the mechanism of how PC exerts its anti-inflammatory effects and modulates adipogenesis remains to be fully determined.
|
| 52 |
+
|
| 53 |
+
Inflammation is considered a protective mechnism of the body, in which the immune system defends the body from harmful agents like bacteria and viruses. If inflammation persists for a long time, it causes chronic inflammation and is related to the production and secretion of several pro-inflammatory mediators. These mediators are associated with abnormal perturbation of the native immune response from normal homeostasis and play a crucial role in promoting various types of organ injuries and diseases [9]. Chronic inflammation leads to many autoimmune diseases such as inflammatory bowel disease (IBD), Type 1 Diabetes (T1D), and obesity and is currently a growing health concern around the world. Thereby, chronic inflammation should be controlled appropriately in time to protect from various diseases. To date, available drugs that suppress inflammation have limited efficacy with many side effects, thereby identifying new natural anti-inflammatory agents for the treatment of inflammatory disorders is a provocative area of therapeutic need. Towards achieving this goal, PC possesses various pharmacological attributes, including anti-inflammatory properties, and it has been used for the treatment of several disease conditions including cancer, liver injury, and skin diseases [3,10,11].
|
| 54 |
+
|
| 55 |
+
Various immune cells, including T cells and macrophages play a key role in the regulation of inflammation as well as being responsible for controlling autoimmune diseases. Towards this end, macrophages are one of the most dominant and widely distributed inflammatory cells associated with the initiation and regulation of acute and chronic inflammatory responses [12]. Lipopolysaccharide (LPS), which is the major component of the outer membrane of Gram-negative bacteria, are important for triggering a cascade of processes related to inflammatory immune responses mediated by toll-like receptor (TLR) signaling. A previous study demonstrated that PC treatment suppressed the secretion of proinflammatory cytokines and NO synthesis in RAW264.7 macrophage cells after LPS induction [13].
|
| 56 |
+
|
| 57 |
+
The transcriptional factor NF-κB is regarded as a master regulator of several inflammatory genes [14]. After activation, NF-κB initiates the expression of pro-inflammatory genes and further extremely accumulates various pro-inflammatory mediators, including TNF-α, interleukin (IL)-1β, IL-6, and NO [15,16]. Inhibiting the activities of NF-κB can effectively attenuate inflammatory conditions and decreases the progression of the disease. Further, TNF-α secreted from macrophages and T cells infiltrate adipose tissue, thereby increase the risk factors for obesity-related metabolic disorders [6]. However, a study reported that PC significantly suppressed the expression of both TNF-α and IL-6 in NIH3T3-L1 cells [13]. Further, PC represents anti-lipolytic function, which is crucial since obesity is related to the potential increase in basal lipolysis [17,18]. Despite numerous beneficial effects, little is known about how PC affects the inflammatory response and adipogenesis.
|
| 58 |
+
|
| 59 |
+
In this present study, we investigated the effects of PC on the inflammatory response and modulation of adipocyte function using splenocytes, RAW264.7 macrophages, and NIH3T3-L1 cells by in vitro analysis.
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| 60 |
+
|
| 61 |
+
2. Materials and methods
|
| 62 |
+
|
| 63 |
+
2.1. Splenocyte single cell isolation and PC treatment
|
| 64 |
+
|
| 65 |
+
Wild-type C57BL/6J male mice (7 weeks of age) were purchased from Jackson Laboratories (Bar Harbor, ME) and housed in the animal facility at the University of Tennessee Health Science Center (UTHSC). The mice were kept with a normal 12:12 h light/dark cycle with ad libitum access to food and water for a week to acclimate them to the animal facility under humidity and temperature-controlled conditions. Experiments were performed under an approved protocol (# 20–0169) by the University of Tennessee Health Science Centre (UTHSC) Institutional Animal Care and Use Committee (IACUC). After euthanization, spleens were collected from the mouse and dissociated by a Stomacher (Seward Stomacher® 80) to make single-cell suspensions. Red blood cells (RBCs) were removed by RBC lysis buffer (Cat. No. 00–4333–57, Invitrogen, Waltham, MA). After RBC lysis, cells were centrifuged at 300 × g for 8 min, the supernatant was discarded, and the cells were suspended in Roswell Park Memorial Institute (RPMI)‒1640 medium (Cat. No. 10–041-CV, Corning, NY) containing 10 % fetal bovine serum (FBS) (Cat. No. 25–550 H, Genesee Scientific, San Diego, CA). Initially, a day before the experiment, individual 6-well plates were coated with anti-CD3 antibody (5 μg/mL; clone: 145–2C11, Catalog No. 100360, BioLegend, San Diego, CA) and kept overnight at 4°C. In the experiment, single-cell suspensions of splenocytes were seeded in each well of the 6-well plates (1.5 × 106 cells/well). The cells were treated with an anti-CD28 antibody (1 μg/mL; Clone: 37.51, Cat. No. 102116, BioLegend, San Diego, CA) along with 10 μM PC (Cat. No. 1554/10; R&D Systems, Minneapolis, MN) or without (control) and incubated for 72 h at 37°C, 5 % CO2 incubator. PC is safe and we did not notice any cytotoxicity in our in vitro experiments.
|
| 66 |
+
|
| 67 |
+
2.2. RAW264.7 and NIH3T3-L1 cell culture and treatment
|
| 68 |
+
|
| 69 |
+
RAW264.7 mouse macrophage cells (ATCC TIB-71) were cultured in Dulbecco’s modified essential medium (DMEM) (Cat. No. 8921008. Corning, NY) media supplemented with 10 % heat-inactivated FBS, penicillin/streptomycin (100 U/mL/100 μg/mL) (Cat. No. 15140–122, Gibco, Waltham, MA) and maintained at 37°C, in 5 % CO2 incubator. Media was replaced every 48 h for the duration of the experiment. In all experiments, RAW264.7 macrophages were treated in the presence or absence (control) of 10 μM PC added with 100 ng/mL lipopolysaccharide (Cat. No. L4391, Sigma, St. Louis, MO) for 24 h.
|
| 70 |
+
|
| 71 |
+
3T3-L1 (ATCC-CL-173) preadipocyte cells were cultured and maintained in DMEM supplemented with L-glutamine (2 mM) (Cat. No. 25030–081, Gibco, Waltham, MA), sodium pyruvate (1 mM) (Cat. No. 11360–070, Gibco, Waltham, MA), penicillin/streptomycin (100 U/mL/100 μg/mL), and 10 % fetal calf serum (FCS) (Cat. No. 26010–066, Gibco, Waltham, MA). Preadipocytes were passaged upon reaching 70 % confluence. For differentiation into adipocytes, 3T3-L1 cells were grown to confluency, at this point media was replaced with DMEM supplemented with, L-glutamine (2 mM), sodium pyruvate (1 mM), penicillin/streptomycin (100 U/mL/100 μg/mL), 10 % FBS and a cocktail of insulin (10 μg/mL) (Cat. No. I0516, Sigma-Aldrich, St. Louis, MO), 3-isobutyl-1-methylxanthine (IBMX) (500 μM) (Cat. No. PHZ1124, Invitrogen, Waltham, MA), and dexamethasone (1 μM) (Cat No. AAA1759003, Thermo Fisher Scientific, USA). After 48 h, the media was replaced with DMEM with L-glutamine, sodium pyruvate, penicillin/streptomycin, and 10 % FBS as used as differentiation media and insulin (10 μg/mL) for another 48 h. The media was further replaced and the cells were maintained in DMEM supplemented with L-glutamine, sodium pyruvate, penicillin/streptomycin, and FBS as in the previous concentration and insulin (2.5 μg/mL) until full differentiation. At day 7, the adipocytes were treated with 10 μM PC or without (control). Cell morphology and accumulation of lipid droplets inside the cells were documented with an AMG EVOS FL inverted microscope from Life Technologies. Cell morphological parameters including cell area, perimeter, and circularity were quantified from phase contrast images by ImageJ software (NIH) (Number of cells, n = 45 in each dish).
|
| 72 |
+
|
| 73 |
+
2.3. Annexin V/PI apoptosis assay
|
| 74 |
+
|
| 75 |
+
Splenocytes were pretreated with PC (10 μM or 50 μM) for 72 h after anti-CD3 and anti-CD28 stimulation as described above. For detection of apoptosis, stimulated splenocytes (1 ×106) were stained with annexin V-conjugated to Alexa Fluor 488 and propidium iodide (PI) by using annexin V/dead cell apoptosis kit (Cat. No. V13242, Invitrogen, Waltham, MA). Briefly, cells were suspended in 100 μL of annexin-binding buffer and incubated with 5 μL of annexin V and 1 μL of 100 μg/mL PI working solution for 15 min at room temperature RT. After incubation, 400 μL of annexin-binding buffer was added and the stained cells were analyzed by Novocyte flow cytometer (Agilent Technologies, Santa Clara, CA).
|
| 76 |
+
|
| 77 |
+
2.4. Flow cytometry
|
| 78 |
+
|
| 79 |
+
Compensation beads, isotype controls, and fluorescence-conjugated antibodies were purchased from either BD Bioscience (San Diego, CA) or Biolegend (San Diego, CA). For each experimental study, freshly isolated cells were pelleted and resuspended in 80 μL of ice-cold flow cytometry staining buffer (FACS buffer), PBS (Cat. No. 10010–031, Gibco, Waltham, MA) containing 1 % fetal bovine serum (FBS). Later, the cells from each well in triplicate were stained with 5 μL of the manufacturer’s recommended dilutions of either respective fluorescence-conjugated antibodies or their respective controls at 4°C for 40 min. We used the following fluorescently labeled mouse monoclonal antibodies for flow cytometry: APC-conjugated anti-CD4 (clone: GK1.5), FITC-conjugated anti-CD8 (clone: 53–6.7), PE-conjugated anti-CXCR3 (clone: CXCR3–173), PE-conjugated anti-FoxP3 (clone: MF-14), APC-conjugated anti-IL-6R (clone: D7715A7), PE-conjugated anti-iNOS (clone: W16030C), APC-conjugated anti-TNF-α (clone: MP6-XT22). For intracellular staining (ICS) of FoxP3, IL-6R, iNOS, and TNF-α, the cells were re-suspended in BD Cytofix/Cytoperm solution for 20 min. The cells were again washed with BD perm/wash solution after storage at 4°C for 10 min. Intracellular staining, incubation, and analysis of IL-6R, FoxP3, iNOS, and TNF-α were performed according to the manufacturer’s protocol at RT (dark) for 30 min. Afterward, cells were washed with FACS buffer and resuspended in 300 μL of FACS buffer. The quantification of fluorescent signals was measured using a Novocyte flow cytometer (Agilent Technologies, Santa Clara, CA), and expressed relative to isotype controls.
|
| 80 |
+
|
| 81 |
+
2.5. Western blot analysis
|
| 82 |
+
|
| 83 |
+
RAW264.7 cells were seeded into (0.5 × 106 cells/well) 6-well plates and incubated at 37°C along with 5 % CO2. After 24 h, cells were treated with 100 ng/mL LPS and with or without 10 μM PC. After 24 h of treatment, cells were washed twice with ice-cold PBS and lysed in RIPA buffer (Cat. No. J63306, Alfa Aesar, Haverhill, MA) with protease and phosphatase inhibitors. The cell lysate was centrifuged to collect the supernatant and protein concentration was measured using a BCA protein assay kit (Cat. No. 23225, Thermo Fisher Scientific, Waltham, MA). 20 μg of protein from each group were mixed with 4X laemmli buffer (Cat. No. #1610747, Bio-Rad, Hercules, CA) and 2-β-mercaptoethanol (Cat. No. A15890, Alfa Aesar, Haverhill, MA), then heated at 95°C for 5 min. The protein samples were resolved and separated by 10 % sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) (Bio-Rad, Hercules, CA). Proteins were transferred from the gel to polyvinylidene fluoride (PVDF) membranes (Cat. No. # 1620174, Bio-Rad, Hercules, CA) by using a trans-blot turbo instrument (Bio-Rad, Hercules, CA). Membranes were blocked with intercept blocking buffer (# 92760001, LI-COR Biosciences, Lincoln, NE) at RT for 2 h and were incubated with anti-NF-κB p50 (1:100, # 8414, Santa Cruz Biotechnology, Dallas, TX) and anti-β-actin (1:5000, LI-COR Biosciences, Lincoln, NE) primary antibodies overnight at 4°C with continuous shaking. Afterward, the membranes were washed with TBS containing 0.2 % Tween 20 (Cat. No. 28360, Thermo Scientific Fisher, Waltham, MA) 3 times for 5 min. Then, the membranes were incubated with IRDye® 800CW-labeled goat anti-mouse IgG (# 926–32210, LI-COR Biosciences, Lincoln, NE), IRDye® 680RD-labeled goat anti-mouse IgG (# 925–68070, LI-COR Biosciences, Lincoln, NE), or goat anti-rabbit IgG (# 926–32211, LI-COR Biosciences, Lincoln, NE) secondary antibodies (1:5000) at RT for 1 h. Images were taken with an LI-COR Odyssey® DLX imaging system (LI-COR Biosciences, Lincoln, NE) and densitometry analyses were performed with LI-COR Image Studio Software (LI-COR Biosciences, Lincoln, NE).
|
| 84 |
+
|
| 85 |
+
2.6. Oil red O staining and imaging with quantification
|
| 86 |
+
|
| 87 |
+
Untreated and 24 h PC-treated differentiated NIH3T3-L1 adipocytes were washed twice with PBS and fixed with 4 % paraformaldehyde for 15 min at RT. Cells were washed with PBS. The fixed cells were stained with freshly diluted Oil Red O (Cat no. 00625, Sigma Aldrich) solution for 45 min at RT, followed by washing thrice with distilled water. Cells were counterstained with Hematoxylin (Cat no. MAK 194 D, Sigma) and mounted. Microphotographs were captured with an Olympus BX43 bright field microscope. The greyscale mean intensity of oil red O stain of oil droplets inside the cell was quantified by ImageJ (number of an oil droplet, n = 75). The intensity was normalized by the respective background.
|
| 88 |
+
|
| 89 |
+
2.7. Total RNA isolation and quantitative real-time polymerase chain reaction
|
| 90 |
+
|
| 91 |
+
Differentiated NIH3T3-L1 cells were treated with or without 10 μM PC. Total RNA was extracted using Qiazol (QIAGEN, Germantown, MD) following the manufacturer’s instructions. The concentration and purity of the total RNA were determined by NanoDrop (Thermo Fisher Scientific, Waltham, MA). Total RNA (1 μg) was converted into cDNA by iScript cDNA synthesis kit (Bio-Rad, Hercules, CA) according to the manufacturer’s procedure. The mRNA expression of targeted genes including leptin (Forward sequence: GCA GTG CCT ATC CAG AAA GTC C, Reverse sequence: GGA ATG AAG TCC AAG CCA GTG AC, IDT, Coralville, IA), IL-1β (Forward sequence: TGG ACC TTC CAG GAT GAG GAC A, Reverse sequence: GTT CAT CTC GGA GCC TGT AGT G, IDT, Coralville, IA), TNF-α (Forward sequence: GGT GCC TAT GTC TCA GCC TCT T, Reverse sequence: GCC ATA GAA CTG ATG AGA GGG AG, IDT, Coralville, IA) was measured by quantitative PCR (qPCR) using the appropriate primers and iTaq Universal SYBR Green Supermix (Bio-Rad, Hercules, CA) with a CFX96 Touch™ Real-Time PCR Detection System (Bio-Rad, Hercules, CA). GAPDH (QIAGEN, Germantown, MD) was used as a reference gene.
|
| 92 |
+
|
| 93 |
+
2.8. Statistical analysis
|
| 94 |
+
|
| 95 |
+
Data are expressed as the means ± standard error of the mean (SEM) for all the experiments. Statistical significance was calculated compared to control groups and determined either by one-way ANOVA or by Student’s t-tests. p < 0.05 was considered significant. The experiments were repeated three times in triplicate.
|
| 96 |
+
|
| 97 |
+
3. Results
|
| 98 |
+
|
| 99 |
+
3.1. PC alters the frequency and activation of T cells
|
| 100 |
+
|
| 101 |
+
It has been shown that activated T cells increased significantly during inflammation and contribute to an inflammatory response by releasing several proinflammatory cytokines [19]. Further, CD8 T cells secrete proinflammatory cytokines due to the abundance of interferon-γ producing effector cells [20]. During preliminary studies, we used various doses (1, 5, 10, 50, and 100 μM PC) and determined that the 10 μM dose is the most effective and used in this study (data not shown). However, 50 μM dose that does not produce toxicity was also used for a few experiments in this study. Since naïve, activated, and effector T cells regulate inflammation by different mechanisms, we sought to analyze the effect of PC on the frequency of stimulated splenocytes. The frequency of both CD4 and CD8 decreased after 10 μM PC treatment as compared to the control (Fig. 1A and C). However, we noticed a significant reduction in the CD8 frequency after PC treatment as compared to stimulation alone (13.9 % vs 9.22 %) (Fig. 1A). These results suggest that PC effectively reduces the activation of both T cells with a stronger effect in CD8 T cells.
|
| 102 |
+
|
| 103 |
+
CXCR3, a chemokine receptor facilitates T-cell differentiation and is increased in inflamed conditions [21]. We further investigated the frequency of CXCR3 after PC treatment. Our results indicated that the frequency of CD8+CXCR3+ was decreased after PC treatment as compared with that of stimulated splenocytes alone (Fig. 1B and C). These findings indicate that PC reduces the expression of CD8+CXCR3+ after T-cell activation.
|
| 104 |
+
|
| 105 |
+
3.2. PC induces the frequency of regulatory T cells (Tregs) and apoptosis in activated T cells
|
| 106 |
+
|
| 107 |
+
The increased frequency and function of Tregs during inflammation plays a pivotal role in controlling inflammation and evidence suggests that Tregs suppress inflammation by suppressing immune response [22]. Thus, we analyzed the frequency of Tregs in the splenocytes after PC treatment using flow cytometry. The stimulated splenocytes showed an increase in the frequency of Tregs as compared with the control group (Fig. 2A). Interestingly, we also noticed that PC further induces the frequency of Tregs as compared to the stimulated group alone. We also used a higher dose of 50 μM PC and noticed that Tregs were even more increased after PC treatment (Fig. 2A). These results suggest that PC might be used for the inhibitory effect on inflammation through the induction of Tregs.
|
| 108 |
+
|
| 109 |
+
Apoptosis is a key step in reducing the inflammatory immune response, and the number of activated T cells decreases significantly during the suppression of inflammation [23]. Thus, we also analyzed the effect of PC on apoptosis in activated T cells by flow cytometry. We noticed an increase in stimulated T-cell apoptosis after PC treatment as compared to the control. We noticed 13.5 % apoptotic cells increased to 28.1 % in the 50 μM PC treated as compared to the stimulated group alone (Fig. 2B). After treatment with PC, the frequency of apoptotic cells was dramatically increased in a dose-dependent manner. These data indicated that PC successfully induces apoptosis in activated T cells as compared to control.
|
| 110 |
+
|
| 111 |
+
3.3. PC reduces the inflammatory response in LPS-induced RAW264.7 macrophage
|
| 112 |
+
|
| 113 |
+
Inflammation is a complex response and mounting evidence suggests that TNF-α, IL-6, and inducible nitric oxide synthase (iNOS) are over-produced and secreted during a variety of inflammatory disorders [24]. Hence, we determined whether PC treatment reduces these cytokines in the LPS-induced RAW264.7 macrophage. Our results delineated that after LPS treatment, the frequency of TNF-α, iNOS, and IL-6R increased percentages of 46.45 %, 24.52 %, and 7.23 % respectively (Fig. 3A). PC treatment decreased the frequency of TNF-α, iNOS, and IL-6R in the LPS-induced RAW264.7 cell line to 30.39 %, 7.52 %, and 4.29 % respectively (Fig. 3A). Thus, PC treatment was able to decrease the responses of inflammatory cytokines in the LPS-induced RAW264.7 macrophages.
|
| 114 |
+
|
| 115 |
+
3.4. PC reduces the expression of cytokines and NF-κB in LPS-induced RAW264.7 macrophage
|
| 116 |
+
|
| 117 |
+
LPS induction in macrophages leads to the production of several proinflammatory markers, including IL-1β, TNF-α, and IL-6 [25]. We analyzed the LPS-induced morphological changes in response to PC treatment and noticed an increase in size as well as obvious proliferation and several irregular pseudopods, which indicates that LPS-induced inflammation leads to abnormal proliferation of RAW264.7 macrophages (Fig. 4A). However, PC treatment resulted in the reduction of cell density and attenuated the abnormal proliferation (Fig. 4A). These results suggest that PC treatment altered the morphology of RAW264.7 macrophages after LPS induction.
|
| 118 |
+
|
| 119 |
+
NF-κB is considered a ubiquitous transcription factor and regulates the expression of a large array of genes that are involved in different processes related to immune as well as inflammatory responses [26]. Further, it has been shown that activation of NF-κB by LPS induces plenty of proinflammatory mediators [27]. Thus, we investigated the possible suppressive effects of PC on the activation of NF-κB in LPS-induced RAW264.7 macrophages. LPS treatment significantly increased the expression of NF-κB compared to the control group (Fig. 4B and C). On the other hand, PC treatment caused a reduction in the protein expression of NF-κB when compared with the LPS-alone group (Fig. 4B and C). These results suggested that the inhibition of translocation of NF-κB by PC might be the mechanism that leads to the suppression of several proinflammatory mediators, including TNF-α, IL-6, and iNOS.
|
| 120 |
+
|
| 121 |
+
3.5. PC alters NIH3T3-L1 cell morphology, lipid accumulation, and gene expression
|
| 122 |
+
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To assess the effect of PC on adipocytes, we evaluated and compared the cell morphology, lipid deposition, and the expression of IL-1β, TNF-α, and leptin in NIH3T3-L1 adipocytes. After treating these cells with PC, the cell size was reduced in the PC-treated group which was reflected in cell area and perimeter (Fig. 5A and B). Interestingly, PC-treated cells became morphologically more round in shape compared to the control group because the circularity parameter increased (circularity is the ratio of area to the perimeter). Furthermore, in the PC-treated group, the oil droplets were dispersed in the cytoplasm whereas the oil droplets are very densely packed and covered the whole cytoplasm in the control group (Fig. 5A red and yellow arrows). This difference is further validated by measuring the intensity of oil red O on stained bright field images (40X). There was a significant reduction in the intensity of oil droplets in the treated cell compared to the control (Fig. 5B). Furthermore, the expression of TNF-α was reduced significantly (Fig. 5C). However, the gene expression for leptin was increased after PC administration and IL-1β also showed a similar pattern (Fig. 5C). The results suggested that PC reduced the hypertrophy of adipocytes and also decreased inflammation, which may indicate that PC has an anti-adipogenic effect.
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4. Discussion
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Drug discovery using natural products remains an area of huge opportunity, as there are centuries of historical knowledge describing the benefits of nature providing considerable remedial and synergistic effects. However, new strategies need to be explored to identify new moieties in these compounds and their mechanism of action to promote their therapeutic effects. Normally, these natural compounds are safe, have minimal toxicity, and are without any adverse side effects. One example is resveratrol, which is widely considered an anticancer, anti-oxidant, and anti-inflammatory, but represents low bioavailability and rapid metabolism [28]. To overcome this issue, PC, a derivative of resveratrol has been reported to have great potential to suppress inflammation [29]. However, the mechanism of the suppressive properties of PC is not clear. In this study, we demonstrated that PC exhibited multifactorial effects. First, PC increased the frequency of Tregs and T cell apoptosis. Second, PC reduced the expression of CXCR3 on T cells, and the levels of TNF-α, IL-6R, NF-κB, and iNOS in RAW264.7 macrophages. Third, PC decreased the hypertrophy of adipocytes in 3T3-L1 adipocytes.
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Inflammation is considered a pathological cause of various diseases and seriously endangers human health around the globe. Immune cells play a key role in maintaining the regulation of inflammation and are the mediator for the progression of disease symptoms. Both CD4 and CD8 T cells are recruited to the sites of inflammation during inflammatory diseases [30]. In the present in vitro study, we noticed that PC reduces the frequency of T cells in anti-CD3 and anti-CD28 stimulated splenocytes. These findings corroborated the results from a previous study where PC inhibited the activation markers in both CD4 and CD8 T cells [31]. It has been shown that type 1 helper (Th1) cells are elevated during chronic inflammation [32], and CXCR3-expressing T cells mediate Th1 inflammatory lymphocytes [33]. We also observed that PC decreased the frequency of CXCR3-expressing CD8 T cells, which may have resulted from the inhibition of activated T cells. Prior work has demonstrated that Tregs were immunosuppressors and suppressed the activation of various immune cells, including T and B cells, natural killers, and dendritic cells. Further, an increase in Tregs is considered a key regulator of several types of immune response [34]. In our study, PC treatment increased the frequency of Tregs, which confirms a previous finding that increased Tregs mediate the apoptosis of T cells [35]. Furthermore, the decrease in CXCR3+ T cells is also plausible by indirectly inducing Tregs, which is associated with the suppression of inflammatory responses to maintain immune homeostasis [36]. We also demonstrated that PC induces apoptosis in the activated T cells and further influences the functional sub-type of T cell response.
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When considering other immune cells, LPS-stimulated RAW264.7 macrophages are used as the model for inflammation [37,38]. Inflammation-induced by activated macrophages makes both NO and iNOS an important markers for inflammatory response [39]. Our findings would suggest that the loss of iNOS expression following exposure to PC in the LPS-treated RAW264.7 macrophages may explain the anti-inflammatory effects of PC. In this study, we noticed that LPS increased the expression of iNOS in RAW264.7 macrophages as compared to the control. Treatment with PC drastically decreased the iNOS expression. Additionally, it has been shown that proinflammatory cytokines, such as TNF-α and IL-6R, are responsible for various inflammatory disorders [40]. In confirmation of these prior observations, we detected a reduction in both TNF-α and IL-6R in RAW264.7 macrophages treated with PC. Taken together, our results corroborate that PC reduces the proinflammatory markers during the LPS-induced inflammatory response. Additionally, these findings corroborated previous studies that demonstrated the role of PC in decreased expression of proinflammatory markers [13,41].
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NF-κB is a transcription factor associated with the regulation of several proinflammatory genes, including TNF-α, iNOS, IL-6, and IL-1β [42]. Hence, modulation of NF-κB activity is considered a crucial target for developing an anti-inflammatory drug. Growing evidence suggested that macrophage-mediated inflammatory responses also include the NF-κB signaling pathway [43]. In this study, LPS-stimulated macrophages showed a marked increase in the expression of NF-κB, as well as a significant increase in the level of proinflammatory cytokines, including TNF-α, iNOS, and IL-6R. Conversely, concomitant treatment of PC represented an anti-inflammatory effect by decreasing the expression of NF-κB and inflammatory markers. In addition, the anti-inflammatory effect of PC has been reported in previous studies, thereby providing significant hints regarding the role of PC as an anti-inflammatory therapeutic agent [26,44,45].
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Adipose tissue stores lipids by enlarging existing adipocytes as well as recruitment of new adipocytes so that it can accommodate excess lipids, known as hypertrophy and hyperplasia respectively [46]. It has been shown that the anti-adipogenic effect of PC is more significant compared to resveratrol [47]. Moreover, the effect of PC in inhibiting adipogenesis followed dose-dependently in NIH3T3-L1 adipocytes [8]. One reason for the protective effect of PC for negatively regulating adipogenesis is that it reduces various proinflammatory markers. In the present study, we demonstrated that PC significantly reduced the cell size, oil droplet density, deposition, TNF-α expression. Nonetheless, previous studies showed that leptin is directly associated with the inhibition of lipogenesis and promotes lipolysis by acting directly on adipocytes [48]. This leptin activity might be due to the suppression of the inhibitory action of adenylyl cyclase [49]. Previous studies suggested that PC regulates adipocyte differentiation [8,13,17]. By contrast, our study investigated the effect of PC after adipocyte differentiation. Interestingly, the outcomes depicted that PC diminishes the hypertrophy of mature adipocytes, lipid accumulation inside the cell and minimizes the and expression of the proinflammatory gene. Additionally, PC alters the adipocyte shape from elongated to a more-round shape which might indicate the role of PC on any mechanosensory receptors on mature adipocytes. It has been shown that various mechanosensory proteins regulate cell morphology [50]. However, we need further investigation to make a definitive conclusion on how PC alters adipocytes after differentiation.
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5. Conclusion
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Our findings strongly demonstrate that PC induces the frequency of Tregs and apoptosis in the activated splenocytes. PC also decreases the expression of several proinflammatory mediators in immune cells as well as in adipocytes. Additionally, PC regulates adipocyte shape, size, and lipid deposition. Taken together, our study reveals the anti-inflammatory, anti-adipogenic, and apoptotic activities of PC. This provides a suitable scope for subsequent in vivo investigation of PC to confirm its potential health benefits and utility as a treatment modality in various inflammatory diseases and obesity.
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Acknowledgments
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This study was supported by grants from National Institute of Allergy and Infectious Diseases, USA (NIAID R01 AI140405) to the U.S., and the Intramural Research Program, UTHSC in Memphis, TN.
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Data availability
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Data will be made available on request.
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Fig. 1. PC alters the T cell frequency and reduces activated T cells.
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Flow cytometry analysis of control stimulated, and 10 μM PC treated spleen cells stained with phenotypic markers for T cells (CD4 and CD8) and T cell activation markers CXCR3. Panel A represents the percentages of CD4+ T cells (Panel A, lower right quadrant), CD8+ T cells (Panel A, upper left quadrant), and CD4+CD8+ T cells (Panel A, upper right quadrant). Panel B shows representative experiments for both CD4 +CXCR3 and CD8 +CXCR3 populations. Panel C represents the percentages of CD4+CD8+ T cells and CXCR3 cells that were gated on the CD8 T cell population. Data are representative of one of the three biological experiments run in triplicate. The values are shown as mean ± SEM; * *p ≤ 0.01 (compared to control vs stimulated); * **p ≤ 0.001 (compared to stimulated vs PC).
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Fig. 2. PC induces regulatory T cells (Tregs) and induces apoptosis in activated T cells.
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Flow cytometry analysis of control, stimulated, 10 μM & 50 μM PC treated spleen cells, respectively, and stained for CD4, FoxP3 antibodies for Tregs and Annexin V/PI staining for apoptosis analysis. Panel A represents the changes in the frequency of FoxP3+ cells gated on CD4 T cells. Panel B shows the apoptosis analysis by Annexin V/PI staining. Data are representative of one of the three biological experiments run in triplicate.
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Fig. 3. Effect of PC on inflammatory mediators in RAW264.7 macrophages.
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RAW264.7 macrophages were treated with 10 μM PC and control in presence of LPS stimulation. Cells were intracellularly stained with TNF-α, iNOS, and IL-6R antibodies. Panel A shows the changes in the frequency of TNF-α, iNOS, and IL-6R in control, LPS, and LPS treated with 10 μM PC. Panel B shows the percentages of cells in each group for TNF-α, iNOS, and IL-6R. Data are representative of one of the three biological experiments run in triplicate. The values are shown as mean ± SEM; ***p ≤ 0.001(compared to control vs stimulated vs PC).
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Fig. 4. PC alters the morphology and expression of NF-κB in LPS-induced RAW264.7 macrophages.Panel
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A represents the altered morphology in RAW264.7 cells stimulated with LPS and 10 μM PC treatment. Panel B shows the expression of NF-κB in RAW264.7 macrophages treated with 10 μM PC or control in presence of LPS induction. Panel C delineates the relative protein expression of NF-κB normalized with β-actin. Data are representative of one of the three biological experiments run in triplicate. The values are shown as mean ± SEM; * **p ≤ 0.001(compared to control vs stimulated vs PC).
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Fig. 5. Representation of the alteration in morphology, lipid accumulation, and gene expression of 3T3-L1 cells treated with PC.
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A) microphotograph (100X) of cell morphology in phase contrast microscope and microphotograph (100X and 400X) of oil red O-stained cells in bright field microscope, red color represents the lipid accumulation portion inside the cells (Red and yellow arrowheads indicate the difference in lipid deposition between control and treated group in different microscopic modes). B) Graphical illustration of morphometric analysis such as cellular area, perimeter, and circularity (n = 45) and oil red O staining intensity (n = 75). C) Relative gene expression of TNF-α, leptin, and IL-1β. Data are representative of one of the three biological experiments run in triplicate. The values are shown as mean ± SEM; not significant (ns) p > 0.05, *p ≤ 0.05, **p ≤ 0.01; ***p ≤ 0.001.
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Conflict of Interest Statement
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The all authors declare that they do not have any competing interests that might influence this study and have had no involvement with study sponsors.
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Ethics Statement
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All animal experimentation was performed under a protocol number (UPS 20–0169) approved by the University of Tennessee Health Science Center (UTHSC) Institutional Animal Care and Use Committee (IACUC). All animal handling and experimental procedures involving animals were performed to minimize pain and discomfort.
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CRediT authorship contribution statement
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Ahmed Rakib, Mousumi Mandal, Anaum Showkat, Sonia Kiran, and Soumi Mazumdar: Data curation, performed the majority of the experiments, and data analysis. Ahmed Rakib, Mousumi Mandal: wrote the first draft of the manuscript and made all the figures. Aman Bajwa, and Bhupesh Singla: provided the cell lines, helped with data analysis, and critically edited the manuscript. Santosh Kumar and Frank Park: Assisted with editing the manuscript. Udai Singh: Conceived the idea, review and edited the manuscript.
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Sci Rep
|
| 4 |
+
Sci Rep
|
| 5 |
+
Scientific Reports
|
| 6 |
+
2045-2322
|
| 7 |
+
Nature Publishing Group UK London
|
| 8 |
+
|
| 9 |
+
37020143
|
| 10 |
+
32868
|
| 11 |
+
10.1038/s41598-023-32868-y
|
| 12 |
+
Article
|
| 13 |
+
Microfibrillar-associated protein 5 suppresses adipogenesis by inhibiting essential coactivator of PPARγ
|
| 14 |
+
Zhang Tianlong 13
|
| 15 |
+
Li Haoran 12
|
| 16 |
+
Sun Shiwei 13
|
| 17 |
+
Zhou Wuling 13
|
| 18 |
+
Zhang Tieqi 13
|
| 19 |
+
Yu Yueming 13
|
| 20 |
+
Wang Qiang wqwyj81@163.com
|
| 21 |
+
|
| 22 |
+
13
|
| 23 |
+
Wang Minghai wangminghai@5thhospital.com
|
| 24 |
+
|
| 25 |
+
13
|
| 26 |
+
1 grid.8547.e 0000 0001 0125 2443 Department of Orthopedics, Shanghai Fifth People’s Hospital, Fudan University, No128. Ruili Road, Minhang District, Shanghai, 200240 China
|
| 27 |
+
2 grid.7737.4 0000 0004 0410 2071 Department of Anatomy and Stem Cells and Metabolism Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
|
| 28 |
+
3 grid.8547.e 0000 0001 0125 2443 Center of Community-Based Health Research, Fudan University, Shanghai, China
|
| 29 |
+
5 4 2023
|
| 30 |
+
5 4 2023
|
| 31 |
+
2023
|
| 32 |
+
13 558912 1 2023
|
| 33 |
+
4 4 2023
|
| 34 |
+
© The Author(s) 2023
|
| 35 |
+
https://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
|
| 36 |
+
Femoral head necrosis is responsible for severe pain and its incidence is increasing. Abnormal adipogenic differentiation and fat cell hypertrophy of bone marrow mesenchymal stem cells increase intramedullary cavity pressure, leading to osteonecrosis. By analyzing gene expression before and after adipogenic differentiation, we found that Microfibril-Associated Protein 5 (MFAP5) is significantly down-regulated in adipogenesis whilst the mechanism of MFAP5 in regulating the differentiation of bone marrow mesenchymal stem cells is unknown. The purpose of this study was to clarify the role of MAFP5 in adipogenesis and therefore provide a theoretical basis for future therapeutic options of osteonecrosis. By knockdown or overexpression of MFAP5 in C3H10 and 3T3-L1 cells, we found that MFAP5 was significantly down-regulated as a key regulator of adipogenic differentiation, and identified the underlying downstream molecular mechanism. MFAP5 directly bound to and inhibited the expression of Staphylococcal Nuclease And Tudor Domain Containing 1, an essential coactivator of PPARγ, exerting an important regulatory role in adipogenesis.
|
| 37 |
+
|
| 38 |
+
Subject terms
|
| 39 |
+
|
| 40 |
+
Cell biology
|
| 41 |
+
Molecular biology
|
| 42 |
+
Stem cells
|
| 43 |
+
Natural Science Foundation of Shanghai22ZR1448900 Natural Science Foundation of Minhang District Shanghai2021MHZ081 the Key Department of Minhang District Shanghai2020MWTZB03 the Key Department of the Fifth People's Hospital of Shanghai2020WYZDZK03 the Fifth People's Hospital of Shanghai, Fudan University2018WYZT01 the Minhang District Leading Talent Development Fundsissue-copyright-statement© The Author(s) 2023
|
| 44 |
+
==== Body
|
| 45 |
+
pmcIntroduction
|
| 46 |
+
|
| 47 |
+
Steroid-induced osteonecrosis of the femoral head (SONFH) is a common orthopedic disease with a high disability rate1. Long-term use of glucocorticoids induces necrosis of trabecular bone and bone marrow, eventually leading to hip dysfunction2. The pathogenesis of SONFH involves increased adipogenesis and fat cell hypertrophy in marrow, increasing intraosseous pressure and inducing avascular necrosis3. However, there are no effective methods to prevent and treat SONFH, which thus necessitates hip replacement, the main treatment of end-stage SONFH at the present time. However, hip replacement is costly and causes marked trauma. Reversing the disorders of lipid metabolism, such as inhibiting adipogenesis of bone marrow mesenchymal stem cells (BMSCs), might improve SONFH treatment.
|
| 48 |
+
|
| 49 |
+
Fat cells in bone marrow are mainly derived from BMSCs4. The differentiation and maturation of adipocytes is complex and involves multiple signaling pathways, such as Erk, Wnt, BMP, and hedgehog pathways5–7. These affect the transcriptional activity of key factors, such as peroxisome proliferator-activated receptor-g (PPARγ), and CCAAT/enhancer binding protein alpha (CEBPα), which promote the initiation and maturation of adipogenesis8,9. These mechanisms maintain normal adipogenic differentiation by complex mutual regulation. Among them, the PPARγ signaling pathway is important in adipogenic differentiation and maturation10. A hormonal adipogenic stimulus triggers expression of CCAAT/enhancer-binding proteins, inducing the expression of PPARγ and initiating a series of downstream adjustment processes11. Transcriptional activation of PPARγ and other nuclear hormone receptors regulates the participation of co-activators or co-repressors that link nuclear receptors with the basal transcription machinery. Previous studies indicated the special role of PPARγ in SONFH. Pravastatin was found to prevent SONFH by suppressing the expression of PPARγ and activating Wnt pathway at both the mRNA and protein levels12,13, and Huogu I formula has been specifically shown to inhibit fat formation-related gene expression and the occurrence of SONFH by inhibiting the expression of the PPARγ gene14. SND1 (Staphylococcal Nuclease And Tudor Domain Containing 1), also known as Tudor staphylococcal nuclease (Tudor-SN) or p100, is a co-activator of PPARγ, which, by directly binding PPARγ, promotes the transcription of downstream factors and adipogenic differentiation15.
|
| 50 |
+
|
| 51 |
+
MFAP5, also known as Microfibril-Associated Glycoprotein 2 (MAGP2), is a 25 kDa glycoprotein, present in the stroma and extracellular matrix of all tissues. MFAP5 secreted by mesenchymal stromal cells plays a key role in the hematopoietic and immune systems16,17. Mutation of MFAP5 is associated with the pathology of thoracic aortic aneurysm and dissection in human18. Moreover, MFAP5 regulates the progression of ovarian cancer, breast cancer, and tongue cancer19–21. Previously, our research group found that MFAP5 promoted osteogenic differentiation of MSCs by activating the Wnt/β-catenin and AMPK signaling pathways22. However, the function of MFAP5 in regulating the differentiation of BMSCs remains unclear. By analyzing the data of adipogenic precursor cells and mature adipocytes, we found that the expression of MFAP5 was significantly down-regulated, implicating MFAP5 in adipogenesis. We verified the sequencing results and confirmed the function of MFAP5 in adipogenesis by silencing and overexpressing. In addition, we validated the mechanism of its regulation of BMSC differentiation. MFAP5 directly bound to and inhibited the expression of SND1, a novel coactivator of peroxisome PPARγ, suppressing the expression of downstream molecules of PPARγ including CD36 and Adipsin23,24. In summary, MFAP5 is involved in the regulation of adipogenic differentiation, and has potential as a therapeutic target for diseases caused by adipogenic over-differentiation, such as SONFH.
|
| 52 |
+
|
| 53 |
+
Materials and methods
|
| 54 |
+
|
| 55 |
+
Microarray data
|
| 56 |
+
|
| 57 |
+
The gene expression profiles of undifferentiated and differentiated adipocytes, including GSE20696, GSE40565, and GSE119593, were acquired from the GEO database (https://www.ncbi.nlm.nih.gov/). The GEO2R web tool was used to identify differentially expressed genes with screening criteria of an adjusted P < 0.05 and an absolute logFC value of > 1.5 after eliminating invalid and duplicate values. Next, the intersection of the differentially expressed genes was found and the top 30 (ranked by the mean of the absolute value of logFC) differentially expressed genes were visualized.
|
| 58 |
+
|
| 59 |
+
Reagents and drug preparation
|
| 60 |
+
|
| 61 |
+
Dexamethasone (DXMS, D4902), L-Ascorbic acid (AA, A4403), β-Glycerophosphate (β-GP, G9422), Isobutylmethylxanthine (IBMX, I5879) and Indomethacin (ID, I7378) were purchased from Sigma Aldrich, USA. The antibody to MFAP5(DF13146) was from Affinity, USA. Antibodies to SND1(A5874), IgG (AC005), PPARγ(A19676), CD36(A19016), Adipsin (A8117), and β-actin(AC026) were from ABclonal, CHN. Goat anti-rabbit(7074) and -mouse(4410) antibodies from CST, USA were used as secondary antibodies.
|
| 62 |
+
|
| 63 |
+
Cell culture and differentiation
|
| 64 |
+
|
| 65 |
+
The 293 T (for lentivirus packaging), 3T3-L1, and C3H10 cell lines were purchased from the Cell Bank of the Chinese Academy of Sciences, Shanghai, and placed in high-glucose DMEM containing 10% FBS; the medium was exchanged every 3 days. 3T3-L1 and C3H10T1/2 cells were induced to differentiate when they reached 100% confluence in differentiation medium, (500 mM IBMX, 200 mM indomethacin, 1 μM dexamethasone, and 10 μM insulin in growth medium). The differentiation medium was renewed every 2 days.
|
| 66 |
+
|
| 67 |
+
Plasmids and viral infection
|
| 68 |
+
|
| 69 |
+
Three plasmids (psPAX2, pLKO.1-EGFP-puromycin, and pMD2.G) were purchased from GeneChem, China. Three shRNA sequences targeting mouse MFAP5 were designed for knockdown of MFAP5 expression (shRNA1: 5′-CCGGCGGGATGAGAAGTTTGCTTGTCTCGAGACAAGCAAACTTCTCATCCCGTTTTTTG-3′; shRNA2: 5′-CCGGGAGATGATGTGCCTGAGACATCTCGAGATGTCTCAGGCACATCATCTCTTTTTTG-3′; shRNA3: 5′-AAAACACCAGTTTACGACGTATGTATTCGTACATACGTCGTAAACTGGTGC-3′) and 3 to SND1 (shRNA1: 5′-CCGGGAAGGCATGAGAGCTAATAATCTCGAGATTATTAGCTCTCATGCCTTCTTTTTG-3′; shRNA2: 5′-CCGGTGTGGCTCCCACAGCTAATTTCTCGAGAAATTAGCTGTGGGAGCCACATTTTG-3′; shRNA3: 5′-CCGGTCTCGTCTCAAACTCAAACTCTATTTGCTCGAGCAAATAGAGTTTGAGACGAGATTTTG-3′).
|
| 70 |
+
|
| 71 |
+
The full-length coding sequence of mouse MFAP5 was amplified and inserted into a lentiviral vector CMV-MCS-EGFP-SV40-Puro to overexpress MFAP5 in C3H10 and 3T3-L1 cells. To produce lentiviruses, a lentiviral vector (pLKO.1-puro or pCDHCMV-MCS-EF1-Puro), psPAX2, pMD2.G, and Lipofectamine2000 (Invitrogen) were mixed and added to 293 T cells in high-glucose DMEM without FBS. The cell density was about 80%. At 12 h after transfection, the medium was changed to high-glucose DMEM with 10% FBS. Two days later, the supernatants were collected and filtered through a 0.45 μm membrane (Millipore). Cells were infected with lentivirus using 6 μg/mL polybrene. Next, puromycin was used to screen for stably transfected cells at a concentration of 3 μg/mL for 3 days and 1 μg/mL for 1 week.
|
| 72 |
+
|
| 73 |
+
Oil red O staining
|
| 74 |
+
|
| 75 |
+
Oil red O staining was performed to assay lipid accumulation. Differentiated cells were rinsed with PBS three times and fixed in 4% formaldehyde for 25 min at 21 °C. Saturated Oil red O stain (0.5% in isopropanol) was diluted 60% with ddH2O and added to wells for 1 h at 21 °C. The cells were rinsed in 75% ethanol to remove residual Oil red O stain, and stained cells were observed and photographed.
|
| 76 |
+
|
| 77 |
+
Quantitative real-time PCR
|
| 78 |
+
|
| 79 |
+
RNAiso Plus (9108, TaKaRa) was used to extract total RNA according to the manufacturer's instructions. RNA samples (500 ng) were reverse transcribed into cDNA with Primescript™ RT Master Mix (RR036A, TaKaRa). Quantitative real-time PCR reactions were implemented in a total volume of 10 μL, comprising 5 μL of 2 × SYBR Premix Ex Taq, 1 μL of diluted cDNA, and 0.2 μM primers. The amplification program was as follows: 95 °C for 10 min, followed by 40 cycles of 15 s at 95 °C and 34 s at 55 °C, then melting curve analysis for 15 s at 95 °C, 1 min at 55 °C, 15 s at 95 °C and 15 s at 60 °C. Each sample was established three holes and detected in three times independently. The 2−ΔΔCT method was used to analyze the data. β-actin was set as the internal reference to normalize gene expression between samples. The primers used for qRT-PCR were from PrimerBank (https://pga.mgh.harvard.edu/primerbank/) and are listed in Supplemental File 1.
|
| 80 |
+
|
| 81 |
+
Western blotting
|
| 82 |
+
|
| 83 |
+
Culture medium was removed, and adherent cells were washed twice with cold PBS. Next, 60 μL of RIPA (p0013b, Beyotime) buffer with 1% PMSF (st506, Beyotime) were added to 60 mm dishes and the cells were scraped into EP tubes. Lysates were vortexed for 10 s every 5 min for 30 min at 0 °C and centrifuged at 12,000 rpm at 4 °C for 10 min to harvest supernatant. A BCA kit (P0010, Beyotime) was used to determine the total protein concentration. Protein samples were subjected to SDS-gel electrophoresis and transferred to PVDF membranes (Millipore), which were blocked using 5% non-fat milk for 2 h at room temperature. According to the molecular weight of different proteins, the blots were cut from the membranes into a single strip, and put into a 15 ml centrifuge tube containing primary antibody for incubation. Following incubation with the primary antibodies at 4 °C overnight, the PVDF membranes were rinsed with TBST three times for 10 min each and probed with a goat anti-rabbit or -mouse secondary antibody (7074 and 4410, CST) at room temperature for 2 h, followed by detection using an ECL Kit (Share-bio, China). Images were analyzed using the Fluor Chem E system (Proteinsimple) and results were quantified using ImageJ software (https://imagej.nih.gov/ij/).
|
| 84 |
+
|
| 85 |
+
Co-immunoprecipitation
|
| 86 |
+
|
| 87 |
+
Cells were harvested at the indicated time points during differentiation. After washing twice with cold PBS, 300 μL of RIPA (p0013d, Beyotime) buffer with 1% PMSF (st506, Beyotime) were added to a 100 mm dish. Next, 1 mL syringes were used to pump cells for 10 min. Next, 40 μL of Protein L Magnetic Beads (HY-K0205, MCE) were incubated with the corresponding antibody for 30 min at room temperature and washed four times in PBST. Protein samples and treated magnetic beads were incubated for 1 h at room temperature on a rotator. The magnetic beads were collected and rinsed four times in PBST, and eluted with 20ul loading buffer at 100 °C for 10 min.
|
| 88 |
+
|
| 89 |
+
Statistical analysis
|
| 90 |
+
|
| 91 |
+
Statistical analysis was performed using GraphPad Prism 8.0 software for Windows. Numerical data are means ± SD from at least three replicates. The independent two-tailed Student’s t-test was used to compare two groups, and one-way ANOVA for more than two groups. P < 0.05 indicated a significant difference.
|
| 92 |
+
|
| 93 |
+
Results
|
| 94 |
+
|
| 95 |
+
MFAP5 was down-regulated during adipogenesis
|
| 96 |
+
|
| 97 |
+
As shown in Fig. 1A, 57 differentially expressed genes were at the intersection of GSE20696, GSE40565, and GSE119593; the top 30 genes were shown in Fig. 1B. MFAP5 expression was consistently down-regulated. The adipogenic cell lines C3H10 and 3T3-L1 were used in adipogenic differentiation research25–27. Oil red O staining and analyzing the mRNA levels of CEBPα, FABP4, and SREB1 at 0, 3, 7, and 10 d of adipogenic induction showed that C3H10 and 3T3-L1 had good adipogenic differentiation potential (Fig. 1C, F and G). As shown in Fig. 1D and E, MFAP5 expression was stable in C3H10 and 3T3-L1 cells, and the MFAP5 protein and mRNA levels decreased gradually as adipogenic differentiation progressed, consistent with the bioinformatics data. The above results indicated a negative correlation between MFAP5 and adipogenic differentiation.Figure 1 Association of MFAP5 with adipogenic differentiation. (A) Fifty-seven genes were at the intersection of three sequencing datasets before and after adipogenic differentiation. (B) Radar chart of 25 genes with the highest differential expression. Blue and red, down- and up-regulated during adipogenesis, respectively. Multiples of gene expression in each database are indicated by different colors. (C) Oil red O staining of C3H10 and 3T3-L1 cells. (D) Endogenous expression and expression pattern during adipogenesis of MFAP5 in C3H10 and 3T3-L1 cells. (E–G) Relative mRNA levels of MFAP5, CEBPα, FABP4, and SREB1 during adipogenesis. n = 3, the experiment was repeated 3 times. Values are means ± SD. *P < 0.05, **P < 0.01 and ***P < 0.001.
|
| 98 |
+
|
| 99 |
+
Establishment of MFAP5-knockdown cell lines
|
| 100 |
+
|
| 101 |
+
An siRNA was used to knockdown expression of MFAP5 in C3H10 and 3T3-L1 cells. To enhance knockdown, three shRNA sequences were designed and used in combination with a lentivirus transfection system to establish stable expression cell lines. Western blotting (Fig. 2A-C) and qRT-PCR (Fig. 2D and E) showed that MFAP5 expression was most significantly silenced in the MFAP5-shRNA2 group in both cell lines.Figure 2 Establishment of MFAP5-knockdown C3H10 and 3T3-L1 cells and the role of MFAP5 in adipogenesis. (A) Western blotting of MFAP5 protein levels in the blank, control, and MFAP5-shRNA1-3 groups of C3H10 and 3T3-L1 cells. (B–C) Quantification of protein levels using ImageJ software in the blank, control, and MFAP5-shRNA1-3 groups of C3H10 and 3T3-L1 cells, respectively. (D–E) qRT-PCR of MFAP5 mRNA levels in the blank, control, and MFAP5 -shRNA1-3 groups of C3H10 and 3T3-L1 cells. (F) Lipid droplets accumulation determined by Oil red O staining. (G) Absorbance at 510 nm of Oil red O-stained cells. (H–J) Expression of CEBPα, FABP4, and SREB1 during adipogenesis was suppressed in MFAP5-knockdown cells. n = 3, the experiment was repeated 3 times. Values are means ± SD. *P < 0.05, **P < 0.01, and ***P < 0.001.
|
| 102 |
+
|
| 103 |
+
MFAP5 knockdown promoted adipogenesis and expression of adipogenic biomarkers
|
| 104 |
+
|
| 105 |
+
We evaluated the role of MFAP5 in adipogenesis by Oil red O staining (Fig. 2F) and by measuring absorbance (Fig. 2G). MFAP5 knockdown facilitated differentiation of C3H10 and 3T3-L1 cells from day 3 onward, as indicated by the presence of more lipid accumulating cells. During adipogenic differentiation, the mRNA levels of CEBPα, FABP4, and SREB1 increased compared with the control (Fig. 2H-J), consistent with the results of Oil red O staining. Collectively, these findings suggested that knockdown of MFAP5 significantly promoted adipogenic differentiation.
|
| 106 |
+
|
| 107 |
+
MFAP5 suppressed adipogenesis by inhibiting SND1, a coactivator of PPARγ
|
| 108 |
+
|
| 109 |
+
After ensuring the effect of MFAP5 on adipogenic differentiation, we further explored the underlying exact mechanism. Adipogenic differentiation involves complex pathway regulation. PPARγ requires auxiliary factors to regulate its downstream molecular transcription and trigger lipid accumulation, resulting in fat differentiation and maturation. Duan et al. reported that SND1 was an essential coactivator of PPARγ15. As shown in Fig. 3A and B, co-immunoprecipitation showed that MFAP5 directly bound SND1 in both cell lines. Furthermore, in MFAP5-knockdown cells, the expression of SND1 was significantly up-regulated (Fig. 3C). Therefore, MFAP5 directly bound to and inhibited the expression of SND1. To determine whether inhibition of SND1 mediated MFAP5-induced inhibition of adipogenic differentiation, we performed co-immunoprecipitation. The expression of SND1 increased upon adipogenic induction in C3H10 and 3T3-L1 cells (Fig. 3D). As adipogenic differentiation progressed, more PPARγ bound to SND1. During adipogenesis, the downstream proteins of PPARγ, including CD36 and Adipsin, were up-regulated in MFAP5-knockdown cell lines compared to the control (Fig. 3E). Therefore, MFAP5 directly binds to and suppresses SND1, inhibiting PPARγ-mediated transcriptional activation.Figure 3 MFAP5 directly bound to and suppressed SND1, inhibiting activation of the PPARγ signaling pathway. (A and B) Co-immunoprecipitation showed MFAP5 and SND1 interacted at the protein level with an IgG antibody as a negative control in C3H10 and 3T3-L1 cells. (C) Knockdown of MFAP5 up-regulated SND1 expression. (D) During adipogenesis, SND1 expression was up-regulated and bound to PPARγ in C3H10 and 3T3-L1 cells. (E) CD36 and Adipsin (downstream genes of PPARγ) were significantly up-regulated in MFAP5-knockdown cells. n = 3, the experiment was repeated 3 times.
|
| 110 |
+
|
| 111 |
+
Knockdown of SND1 reversed the inhibition of adipogenesis
|
| 112 |
+
|
| 113 |
+
To confirm that MFAP5 suppressed adipogenesis by inhibiting the expression of SND1, we knocked down SND1 in MFAP5-silenced cells and assessed their adipogenic differentiation capacity (knockdown efficiency is shown in Supplemental File 2). Compared to MFAP5-silenced cells, knockdown of SND1 relieved the overexpression of SND1 (Fig. 4A). At 0 and 10 d of adipogenic induction, downstream proteins (including CD36 and Adipsin) were reversed in MFAP5-knockdown cells, similar to the control group (Fig. 4B). Oil red O staining also indicated that knockdown of SND1 on the basis of MFAP5 silencing cell lines made its level of adipogenesis ability return to that of control group (Fig. 4C). We also analyzed the mRNA level of the adipogenic biomarkers CEBPα, FABP4, and SREB1 in three cell lines. As shown in Fig. 4D-F, knockdown of SND1 reversed the effect of MFAP5 silencing on adipogenic ability. Therefore, MFAP5 suppressed adipogenesis by inhibiting SND1, thereby restraining the PPARγ signaling pathway.Figure 4 Silencing of SND1 in MFAP5-knockdown cell lines reversed the promotion of adipogenesis. (A) Western blotting of SND1 in MFAP5-knockdown cells compared to the control. (B) SND1 knockdown reversed the activation of PPARγ downstream proteins, including CD36 and Adipsin, in MFAP5-knockdown cells before and after adipogenic induction. (C) Accumulation of lipid droplets by Oil red O staining 10 days after adipogenic induction in the control, MFAP5-sh, and MFAP5-SND1-sh groups. (D–F) Relative expression levels of adipogenic biomarkers—CEBPα, FABP4, and SREB1—by qRT-PCR on day 10 of adipogenesis. n = 3, the experiment was repeated 3 times. Values are means ± SD. *P < 0.05, **P < 0.01 and ***P < 0.001.
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MFAP5 overexpression inhibited adipogenesis by suppressing the expression of SND1
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To validate the above results, we established MFAP5 overexpression C3H10 and 3T3-L1 cell lines and evaluated their gene expression profiles (Fig. 5A-C). Oil red O staining (Fig. 5D) and absorbance measurement (Fig. 5I) showed that MFAP5 overexpression significantly inhibited adipogenic differentiation of both cell lines. This was supported by the mRNA expression levels of adipogenic biomarkers (Fig. 5F-H). At 0, 3, 7, and 10 d of adipogenic induction we found that overexpression of MFAP5 inhibited the expression of SND1. This suppressed CD36 and Adipsin, downstream proteins of PPARγ in adipogenesis (Fig. 5E). Therefore, MFAP5 negatively regulates adipogenic differentiation by directly binding to and inhibiting the expression of SND1, retarding the accumulation of lipid droplets and the maturation of fat cells.Figure 5 MFAP5 overexpression suppressed adipogenesis by inhibiting SND1. (A–C) Establishment of MFAP5-overexpressing C3H10 and 3T3-L1 cells. (D) Lipid droplets accumulation was significantly reduced in the MFAP5-overexpressing group. (E) Expression of SND1, CD36, and Adipsin during adipogenic induction in the control and MFAP5-overexpressing groups. (F–H). Relative mRNA levels of CEBPα, FABP4 and SREB1 showed that MFAP5 overexpression hindered adipogenic differentiation of C3H10 and 3T3-L1 cells. I. Absorbance at 510 nm of Oil red O-stained cells. n = 3, the experiment was repeated 3 times. Values are means ± SD. *P < 0.05, **P < 0.01 and ***P < 0.001.
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Discussion
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Normal adipogenesis or adipocyte differentiation, which is regulated by a cascade of sequentially acting chromatin-modifying coregulators and transcription factors, plays an important role in balancing cell ratios in bone marrow. In older adults, the differentiation of adipocytes is enhanced, causing increased intraosseous pressure, avascular necrosis, and inhibition of homologous cell differentiation28. Here, we found that the expression of MFAP5 was significantly down-regulated during adipocyte differentiation and maturation. We verified the sequencing results and demonstrated the function of MFAP5 in adipogenesis by silencing or overexpression in C3H10 and 3T3-L1 cells29–32. As mesenchymal stem cells, C3H10 cells are more primitive than 3T3-L1 cells and have multidirectional differentiation ability. Both cell lines are used in adipogenic differentiation research. Our findings showed that MFAP5 inhibits adipogenesis by suppressing an essential coactivator of PPARγ.
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MFAP5 is a component of extracellular elastic microfibrils, implicated in cardiovascular progression, breast cancer, carcinogenesis, and alveolar elastogenesis18,20,33,34. Maija et al.35 reported that MFAP5 was highly expressed in adipose tissue, and the expression of MFAP5 decreased during adipocyte differentiation in SGBS cells. However, they focused on adipose tissue inflammation and did not conduct an in-depth study of changes in gene expression or the role of MFAP5 in regulating adipocyte differentiation. During tumor development, MFAP5 may participate in the notch1, notch2, and Akt signaling pathways, which are related to adipocyte differentiation36–38. Therefore, MFAP5 may be involved in the regulation of adipogenesis.
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The ligand-activated transcription factor PPAR, a nuclear receptor of the steroid, thyroid, and retinoic acid receptor superfamily, is the master regulator of adipogenesis39. After binding to ligands, activated PPAR combines with 9-cis-retinoic acid retinoid X receptors to form a heterodimer, then binds to the peroxisome proliferator response element of a target gene, activating its transcription40. PPARs play an important regulatory role in physiological processes such as fat synthesis, lipid metabolism, insulin sensitivity, and particularly the synthesis of enzymes involved in fatty acid β-oxidation41. According to their structure and function, PPARs are divided into three subtypes: PPARα, PPARβ/δ, and PPARγ42. Based on their promoter structure and mRNA splicing mode, PPARγ genes can be divided into PPARγ1, PPARγ2, PPARγ3, and PPARγ4. Among them, PPARγ1, PPARγ3, and PPARγ4 encode the same protein43. Compared with other types of PPARs, PPARγ is the most adipocyte-specific; its expression is high in adipose tissue and adipose cell lines, but low in other tissues and cell lines44. Activated PPARγ regulates the expression of adipocyte-related genes and promotes the differentiation and increases the number of adipocytes. Co-activators—including SND1, SRC-1, PRIP, p300 and TATA—are necessary for transcriptional activation of target genes45–47. Adipocyte differentiation is inhibited in the absence of these co-activators15,47,48. Duan et al.15 knocked out the expression of SND1 in 3T3-L1 cells and cultivated them in adipogenic induction medium for 8 days. Adipogenic differentiation almost completely stopped compared to control cells.
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MFAP5 directly binds to SND1, as determined by co-immunoprecipitation, suggesting that the two proteins interact. In MFAP5-knockdown cells, the expression of SND1 was significantly inhibited. Notably, the downstream genes of PPARγ were markedly inhibited during adipogenesis in MFAP5-knockdown C3H10 and 3T3-L1 cells. Next, we knocked down the expression of SND1 in MFAP5-silenced cells, followed by adipogenic induction. As expected, the promotion of adipocyte differentiation by MFAP5-silenced cells was reversed. Therefore, SND1 is implicated in the negative regulation by MFAP5 of adipogenic differentiation.
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Conclusions
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MFAP5 directly binds to and inhibits the expression of SND1. Our findings expand the upstream molecules of the PPARγ signaling pathway and suggest molecular targets for related research. MFAP5 knockdown may facilitate the development of novel therapeutic strategies for diseases caused by excessive adipogenic differentiation by inhibiting adipogenic differentiation of BMSCs in the femoral head of patients on long-term glucocorticoids.
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Supplementary Information
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| 135 |
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Supplementary Information.
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| 137 |
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Abbreviations
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| 138 |
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| 139 |
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MFAP5 Microfibril associated protein 5
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| 140 |
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| 141 |
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BMSCs Bone marrow stromal cells
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| 142 |
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| 143 |
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SND1 Staphylococcal nuclease and tudor domain containing 1
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| 144 |
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| 145 |
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PPARγ Peroxisome proliferator activated receptor gamma
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| 146 |
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| 147 |
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SONFH Steroid-induced osteonecrosis of the femoral head
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| 148 |
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| 149 |
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CEBPα CCAAT enhancer binding protein alpha
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| 150 |
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| 151 |
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FABP4 Fatty acid binding protein 4
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| 152 |
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| 153 |
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SREB1 G protein-coupled receptor 27
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| 154 |
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| 155 |
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IBMX Isobutylmethylxanthine
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| 156 |
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| 157 |
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DXMS Dexamethasone
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| 158 |
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| 159 |
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ID Indomethacin
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| 160 |
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| 161 |
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DMEM Dulbecco’s modified eagle medium
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| 162 |
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| 163 |
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FBS Fetal bovine serum
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| 164 |
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| 165 |
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PBS Phosphate buffered saline
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| 166 |
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| 167 |
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PBST Phosphate buffered saline tween
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| 168 |
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| 169 |
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shRNA Short hairpin RNA
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| 170 |
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| 171 |
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qRT-PCR Quantitative real-time PCR
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| 172 |
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| 173 |
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PMSF Phenylmethanesulfonyl fluoride
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| 174 |
+
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| 175 |
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PVDF Polyvinylidene fluoride
|
| 176 |
+
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| 177 |
+
TBST Tris buffered saline tween
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| 178 |
+
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| 179 |
+
Supplementary Information
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| 180 |
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| 181 |
+
The online version contains supplementary material available at 10.1038/s41598-023-32868-y.
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| 183 |
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Acknowledgements
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We would like to acknowledge Textcheck for providing high-quality editing service. The English in this document has been checked by at least two professional editors, both native speakers of English. For a certificate, please see: http://www.textcheck.com/certificate/zrhB7H.
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Author contributions
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| 188 |
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| 189 |
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T.L.Z. and H.R.L.: Conceptualization, Software, Investigation, Writing—Original Draft, S.W.S. and W.L.Z.: Methodology, Validation, T.Q.Z. and Y.M.Y.: Data Curation, Writing—Review & Editing, Q.W. and M.H.W.: Resources, Supervision, Project administration, All authors read and approved the final manuscript.
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| 191 |
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Funding
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This work was sponsored by Natural Science Foundation of Shanghai (22ZR1448900); Natural Science Foundation of Minhang District, Shanghai (2021MHZ081, 2020MHZ028); the Key Department of Minhang District, Shanghai (2020MWTZB03); the Key Department of the Fifth People's Hospital of Shanghai (2020WYZDZK03); the Fifth People's Hospital of Shanghai, Fudan University (2018WYZT01); the Fifth People's Hospital of Shanghai, Fudan University (N123E5); the Minhang District Leading Talent Development Funds. The funding sources had no involvement in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.
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Data availability
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The gene expression profiles of undifferentiated and differentiated adipocytes, including GSE20696, GSE40565, and GSE119593, were acquired from the GEO database (https://www.ncbi.nlm.nih.gov/). The data that supported the findings of this study were available from the corresponding author upon reasonable request.
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Competing interests
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The authors declare no competing interests.
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Publisher's note
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Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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These authors contributed equally: Tianlong Zhang and Haoran Li.
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==== Refs
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
J Anim Sci Biotechnol
|
| 4 |
+
J Anim Sci Biotechnol
|
| 5 |
+
Journal of Animal Science and Biotechnology
|
| 6 |
+
1674-9782
|
| 7 |
+
2049-1891
|
| 8 |
+
BioMed Central London
|
| 9 |
+
|
| 10 |
+
833
|
| 11 |
+
10.1186/s40104-023-00833-4
|
| 12 |
+
Research
|
| 13 |
+
Profiling of N6-methyladenosine methylation in porcine longissimus dorsi muscle and unravelling the hub gene ADIPOQ promotes adipogenesis in an m6A-YTHDF1–dependent manner
|
| 14 |
+
Gong Huanfa 12
|
| 15 |
+
Gong Tao 12
|
| 16 |
+
Liu Youhua 12
|
| 17 |
+
Wang Yizhen 12
|
| 18 |
+
Wang Xinxia xinxiawang@zju.edu.cn
|
| 19 |
+
|
| 20 |
+
12
|
| 21 |
+
1 grid.13402.34 0000 0004 1759 700X Key Laboratory of Molecular Animal Nutrition, Ministry of Education, College of Animal Sciences, Zhejiang University, Hangzhou, 310058 People’s Republic of China
|
| 22 |
+
2 grid.13402.34 0000 0004 1759 700X Key Laboratory of Animal Nutrition and Feed Science in Eastern China, Ministry of Agriculture, College of Animal Sciences, Zhejiang University, Hangzhou, 310058 People’s Republic of China
|
| 23 |
+
6 4 2023
|
| 24 |
+
6 4 2023
|
| 25 |
+
2023
|
| 26 |
+
14 5017 8 2022
|
| 27 |
+
4 1 2023
|
| 28 |
+
© The Author(s) 2023
|
| 29 |
+
https://creativecommons.org/licenses/by/4.0/ Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
|
| 30 |
+
Background
|
| 31 |
+
|
| 32 |
+
Intramuscular fat (IMF) content is a critical indicator of pork quality, and abnormal IMF is also relevant to human disease as well as aging. Although N6-methyladenosine (m6A) RNA modification was recently found to regulate adipogenesis in porcine intramuscular fat, however, the underlying molecular mechanisms was still unclear.
|
| 33 |
+
|
| 34 |
+
Results
|
| 35 |
+
|
| 36 |
+
In this work, we collected 20 longissimus dorsi muscle samples with high (average 3.95%) or low IMF content (average 1.22%) from a unique heterogenous swine population for m6A sequencing (m6A-seq). We discovered 70 genes show both differential RNA expression and m6A modification from high and low IMF group, including ADIPOQ and SFRP1, two hub genes inferred through gene co-expression analysis. Particularly, we observed ADIPOQ, which contains three m6A modification sites within 3′ untranslated and protein coding region, could promote porcine intramuscular preadipocyte differentiation in an m6A-dependent manner. Furthermore, we found the YT521‑B homology domain family protein 1 (YTHDF1) could target and promote ADIPOQ mRNA translation.
|
| 37 |
+
|
| 38 |
+
Conclusions
|
| 39 |
+
|
| 40 |
+
Our study provided a comprehensive profiling of m6A methylation in porcine longissimus dorsi muscle and characterized the involvement of m6A epigenetic modification in the regulation of ADIPOQ mRNA on IMF deposition through an m6A-YTHDF1-dependent manner.
|
| 41 |
+
|
| 42 |
+
Supplementary Information
|
| 43 |
+
|
| 44 |
+
The online version contains supplementary material available at 10.1186/s40104-023-00833-4.
|
| 45 |
+
|
| 46 |
+
Keywords
|
| 47 |
+
|
| 48 |
+
ADIPOQ
|
| 49 |
+
Intramuscular fat
|
| 50 |
+
N6-methyladenosine
|
| 51 |
+
Pig
|
| 52 |
+
YTHDF1
|
| 53 |
+
http://dx.doi.org/10.13039/100014718 Innovative Research Group Project of the National Natural Science Foundation of China No. U21A20249 Wang Yizhen http://dx.doi.org/10.13039/501100010031 Postdoctoral Research Foundation of China 2022M712794 Gong Huanfa issue-copyright-statement© The Author(s) 2023
|
| 54 |
+
==== Body
|
| 55 |
+
pmcBackground
|
| 56 |
+
|
| 57 |
+
Intramuscular fat (IMF) content is a critical indicator in pork consume, and also linked to insulin resistance [1], aging [2] and obesity [3] in human. Pig works as an ideal human biomedical model with advantage over primates and other livestock due to its high similarities with human being from the anatomy and physiology [4]. Therefore, illustrating the molecular mechanism underlying the IMF deposition is vital for pork consumption and human health.
|
| 58 |
+
|
| 59 |
+
N6-Methyladenosine (m6A) is the most prevalent post-transcriptionally modification in eukaryotic cells, emerging as an important epigenetic regulator in various physiological processes [5, 6]. Dynamic mRNA m6A modification is regulated by dedicated methyltransferases (“writers”) and demethylases (“erasers”) [7]. RNA-binding proteins (“readers”) could recognize m6A-containing transcripts to drive RNA processes [8, 9], such as mRNA stability [9], splicing [10] or translation [11]. For instance, YT521‑B homology domain family protein 1 (YTHDF1) promotes breast cancer metastasis via enhancing FOXM1 translation in an m6A-dependent manner [12]. Fat mass and obesity-associated (FTO) protein regulates the splicing of adipogenic regulatory factor RUNX1T1 through affecting m6A level around splice site [13]. It has been reported that m6A is highly enriched around the stop codons and 3’UTRs [5]. Recent progress also indicated that m6A methylation of the 3’UTR of FLC causing depletion of its mRNA, controlling flowering in Arabidopsis [14].
|
| 60 |
+
|
| 61 |
+
Accumulating evidences suggested that m6A modification played important roles in regulating various aspects of mRNA metabolism during adipose tissue expansion [15–18]. For instance, NADP modulates m6A methylation and adipogenesis by enhancing FTO activity in 3 T3-L1 preadipocytes [19]. Consistently, Zfp217 mediates mRNA m6A methylation through FTO and YTHDF2 to regulate adipogenesis [20]. Furthermore, m6A modification of two adipogenesis-related genes, UCP2 and PNPLA2, would both regulate adipogenesis between Chinese indigenous breed Jinhua (fatty) and Western commercial breed Landrace (lean) in backfat, whereas in an opposite way [21]. Although it has been reported that YTHDF1 directly targets MTCH2 to promote adipogenesis in porcine intramuscular preadipocytes, our understanding about the function of m6A modification in IMF deposition was still limited.
|
| 62 |
+
|
| 63 |
+
Here we aimed to provide a valuable resource to determine the effects of m6A modified genes potentially involving in adipogenesis of IMF, permitting us to better understanding how to improve pork quality and providing potential target for therapy of obesity.
|
| 64 |
+
|
| 65 |
+
Materials and methods
|
| 66 |
+
|
| 67 |
+
Animal, phenotype and sample collection
|
| 68 |
+
|
| 69 |
+
This study utilized a mosaic swine population to uncover the relationship of m6A regulation mechanism and IMF deposition. The heterogeneous pig stock was derived from eight founder breeds (F0) consisting of the four Western commercial breeds (Duroc, Large White, Landrace and Pietrain pigs) and the four Chinese indigenous breeds (Erhualian, Laiwu, Bamaxiang and Tibetan pigs). All the pigs were raised under the same condition and purposeful mating, crossbreed strategy in detail was described previously [22, 23]. Animals were slaughtered in commer abattoir at 240 ± 10 d. We selected the longissimus dorsi muscle (LDM) from the 6th generation (F6; average IMF: 2.28%, range 0.92%–7.45%) [23]. LDM was obtained between the 3rd and 4th lumbar vertebrae, and flash frozen in liquid nitrogen and stored at −80 °C before use. The intramuscular fat content was measured using the routine Soxhlet extraction method [24].
|
| 70 |
+
|
| 71 |
+
Intramuscular preadipocytes cells were isolated from the LDM of 3-day-old Duroc-Landrace-Yorkshire piglets under sterile conditions [15]. The experimental procedures were in compliance with guidelines of the Committee on Animal Care and Use and Committee on the Ethic of Animal Experiments of Zhejiang University (Hangzhou, China).
|
| 72 |
+
|
| 73 |
+
RNA extraction and m6A RNA immunoprecipitation sequencing
|
| 74 |
+
|
| 75 |
+
Total RNA was isolated and purified using Trizol reagent (Invitrogen, Carlsbad, CA, USA) refer to the instruction, criteria with RIN > 7.0, total RNA > 50 μg, concentration > 50 ng/μL and OD260/280 > 1.8 were left for subsequent use. Poly (A) RNA is purified from 50 μg total RNA using DynabeadsTM Oligo (dT)25–61005 (Thermo Fisher Scientific Baltics UAB; Vilnius, Lithuania) using two rounds of purification. Then the poly(A) RNA was fragmented into small pieces using Magnesium RNA Fragmentation Module (NEB, cat.e6150, USA) under 86 °C for 7 min.
|
| 76 |
+
|
| 77 |
+
Approximately 50 ng of fragmented mRNA was saved as input sample, which was used to eliminate the background. m6A-sepecific methylated RNA sequencing was performed according to the previous report [25]. In brief, the other fragmented mRNA was incubated with 3 μg methylated RNA-specific antibodies (No. 202003, Synaptic Systems, Göttingen, Germany) in RIP buffer (150 mmol/L NaCl, 10 mmol/L Tris and 0.1% NP-40) at 4 °C. After 2 h, adding the washed protein A/G magnetic beads (Millipore, Billerica, MA, USA) and incubating at 4 °C for further 2 h. Beads, washed 6 times in RIP buffer, incubated with immunoprecipitation buffer (Sigma-Aldrich, St Louis, MO, USA) to elute RNA. Immunoprecipitated RNA was extracted with phenol/chloroform, and RNA samples were sent for next-generation sequencing. All libraries were sequenced for 150 bp paired-end sequencing under an Illumina Novaseq™ 6000 (LC-Bio Technology CO., Ltd., Hangzhou, China) following the vendor’s recommended protocol.
|
| 78 |
+
|
| 79 |
+
Quantitative of m6A level by liquid chromatography-tandem mass spectrometry (LC-MS/MS)
|
| 80 |
+
|
| 81 |
+
Quantification of m6A in mRNA was conducted based on the previous study [26]. In brief, 300 ng of mRNA was digested by nuclease P1 (2 U) at 42 °C for 2 h, followed by the addition of alkaline phosphatase (0.5 U) with incubation at 37 °C for 2 h. The total amount of m6A in RNA was measured using Waters Acquity UPLC coupled to a Waters Xevo TQ mass spectrometer (Waters, Milford, USA). Quantification was achieved by comparing with the standard curve obtained from pure nucleoside standards. The ratio of m6A to A was calculated based on the determined concentration.
|
| 82 |
+
|
| 83 |
+
RNA mapping and quality control
|
| 84 |
+
|
| 85 |
+
Raw data were evaluated with FastQC v0.11.9 [27], the heading 10 bp were removed using trimmomatic v0.39 on account of GC bias [28]. Clean data were mapped to Sus scrofa 11.1 using STAR v2.7.8a, SAMtools v1.11 was used for sorting and marking duplicated reads [29, 30]. IP data were performed the same mapping procedure as input data.
|
| 86 |
+
|
| 87 |
+
MeRIP-seq data analysis
|
| 88 |
+
|
| 89 |
+
For IP data, m6A peak calling was conducted by MACS2 with “--nomodel -g 2.5e9 --broad --keep-dup all” on whole transcript level. Differentially peaks were identified with in-house R script according to previous study [31, 32]. Briefly, bedtools was used to combine all peaks from High and Low group into a reference peak. Normalized depth of each peak was inferred by following method: Normarlized depth = ((IP reads of Peak Region/Total reads of IP sample) − (Input reads of Peak Region/Total reads of input sample))/Length of peak. Total number of each sample’ read was calculated by SAMtools v1.11 flagstats based on BAM file. Coverage of peaks were inferred using SAMtools v1.11 bedcov.
|
| 90 |
+
|
| 91 |
+
Differentially methylated peaks (P < 0.05 and abs (log2foldchange ) > log21.5) were identified by comparing average normalized depth of each peak between High and Low group using t-test in R program. VEP software was using for annotating the differential peaks. HOMER software was applying for uncovering the motif in conserved peak regions.
|
| 92 |
+
|
| 93 |
+
Input data analysis
|
| 94 |
+
|
| 95 |
+
Input data were used for annotating, merging and quantifying with StringTie v2.1.7. raw counts of transcripts then were normalized (described in the legend of Fig. 3f) and low expression genes (gene counts > 9 in less than 4 samples) were filtered. Differential expression transcripts/genes were uncovered by the DESeq2 software [33, 34]. (abs (log2foldchange )) > log21.5 and P < 0.05 were identified as differentially expressing transcripts/genes.
|
| 96 |
+
|
| 97 |
+
Principal component analysis was conducted with DESeq2 [33]. Briefly, high expression gene counts were used for constructing DESeq data with the function DESeqDataSetFromMatrix(). And then data was normalized by the function rlogTransformation(). PCA was inferred with the function plotPCA() and visualized in R program. Pheatmap package was performed for visualing heatmap.
|
| 98 |
+
|
| 99 |
+
Weighted gene co-expression network analysis
|
| 100 |
+
|
| 101 |
+
Co-expression network analysis was performed with WGCNA (Wegithed Gene Co-expression Network Analysis) R package [35]. Briefly, raw count of genes were infered from the input data, and then low expression genes (gene counts > 9 in less than 4 samples) were filtered. Reserved gene counts were normalizd with transcript per millon (TPM) method. The soft threshold power β is determined based on the standard scale-free network, inferred from the function pickSoftThreshold().The adjacency matrix was calculated using topological overlap measure (TOM) [36], hierarchically clustering coexpressed genes into modules. Module-trait associations were calculated as the Pearson’s correlation between the module eigengene and trait of interest [37]. The most relevant traits of module was selected for analyzing their biological function and uncovering hub genes. Hub genes are a group of genes with the highest connectivity, and determine the characteristics of the gene module. We defined hub genes which are the significant correlation with clinical characteristics (Gene Significance, GS > 0.2) and high module characterization (Module Membership, MM > 0.8) in the module.
|
| 102 |
+
|
| 103 |
+
Functional enrichment analysis
|
| 104 |
+
|
| 105 |
+
Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted by ClueGO in Cytoscape v3.9.0. Pathways with P ≤ 0.05 were selected, P-value was chosen from the term P-value corrected with Bonferroni step down. GO ontologies involve biological process, cellular component and molecular function.
|
| 106 |
+
|
| 107 |
+
Western blot analysis
|
| 108 |
+
|
| 109 |
+
Cells were lysed with the mixture containing cell lysis buffer for Western and IP and 1% phenylmethanesulfonyl fluoride (PMSF) (Biosharp, Beijing, China) on ice to extract protein. Protein samples were separated by SDS-PAGE and then transferred to polyvinylidene difluoride membranes. And the membranes were blocked with 5% non-fat milk at room temperature for 1 h, then incubated with the primary antibody overnight at 4 °C and next with the secondary antibody for 1 h at room temperature. The protein bands were visualized using ECL Protect from Light (Biosharp) and quantified using Image J software. The primary antibodies used in this study were as follows: ADIPOQ (sc-136131, Santa Cruz, Watsonville, CA, USA, diluted 1:200), FLAG (20543–1-AP, Proteintech, Rosemont, IL, USA, diluted 1:1,000), YTHDF1 (17479–1-AP, Proteintech, diluted 1:1,000), GFP (ET160–25, Huabio, Hangzhou, China, diluted 1:5,000), β-actin (M1210–2, Huabio, diluted 1:5,000). The secondary antibodies were as follows: goat anti-mouse IgG-HRP (HA1006, Huabio, diluted 1:2,000), goat anti-rabbit IgG-HRP (HA1001, Huabio, diluted 1:2,000).
|
| 110 |
+
|
| 111 |
+
Real-time quantitative PCR (qPCR) analysis
|
| 112 |
+
|
| 113 |
+
Total RNA was extracted using TRIzol (Biosharp) according to the product protocol. After examination of RNA purity and concentration, 2 μg RNA was used as a template to reverse transcribe to cDNA by using M-MLV Reverse Transcriptase Kit (Invitrogen). Reverse transcription conditions were under 5 min at 25 °C, 45 min at 50 °C, 5 min at 85 °C. qPCR analysis was performed using the SYBR Green PCR Master Mix (Roche, Basel, Switzerland) with the ABI Step-One PlusTM Real-Time PCR System (Applied Biosystems, Waltham, MA, USA). Relative level of RNA expression was determined with 2−ΔΔCt method after normalization to GAPDH. Reaction conditions were 95 °C for 1 min, 40 cycles of 95 °C for 15 s and 60 °C for 30 s. Primers used in this study were listed in Table 1.Table 1 Primer sequences used in this work
|
| 114 |
+
|
| 115 |
+
Name Forward primer (5′→3′) Reverse primer (5′→3′)
|
| 116 |
+
ADIPOQ TATGATGTCACCACTGGCAAA TAGAGGAGCACAGAGCCAGAG
|
| 117 |
+
PPARγ AGGACTACCAAAGTGCCATCAAA GAGGCTTTATCCCCACAGACAC
|
| 118 |
+
CEBPβ GCACAGCGACGAGTACAAGA TATGCTGCGTCTCCAGGTTG
|
| 119 |
+
aP2 CAGGAAAGTCAAGAGCACC ATGATACATTCCACCACCAA
|
| 120 |
+
GAPDH ACACTCACTCTTCCACTTTTG CAAATTCATTGTCGTACCAG
|
| 121 |
+
|
| 122 |
+
Oil Red O staining
|
| 123 |
+
|
| 124 |
+
Oil Red O staining was performed as following procedures: cells were washed and fixed with 10% formalin for 1 h, and then washed 3 times with 60% isopropanol. Cells were stained with Oil Red O working solution (0.35% Oil Red O dye in 60% isopropanol) for 10 min, and further washed 4 times with distilled water. Cells were eluted the stained lipid droplets using 100% isopropanol for 10 min, and then measuring optical density (OD) at 500 nm to conduct the quantitative of lipid content.
|
| 125 |
+
|
| 126 |
+
Intramuscular preadipocytes (IMF cells) isolation
|
| 127 |
+
|
| 128 |
+
IMF cells were isolated based on the previous study [15]. Briefly, the LDM of 3-day-old Duroc-Landrace-Yorkshire piglets were separated under sterile conditions. Visible connective tissue was removed and finely minced. Muscle tissues were then digested in a digestion buffer consisting of 1 mg/mL collagenase type I (Gibco, Carlsbad, CA, USA) in a shaking water bath for 1.5 h at 37 °C. The digested sample was filtered aseptically through 80 and 200 μm nylon mesh filters to isolate cells. Filtered cells were then washed 3 times with Dulbecco’s Modified Eagle Medium (DMEM) via centrifugation at 1,500 r/min for 5 min. Cells were seeded in growth medium that consisted of DMEM medium containing 10% fetal bovine serum (Gibco) and 1% penicillin-streptomycin (Gibco). After 1 h, cells were rinsed with DMEM medium to remove unadhered cells, and the adhered cells consisted of pure IMF cells.
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Cell culture and adipocyte differentiation
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| 132 |
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Cells were cultured in DMEM containing 10% fetal bovine serum (Gibco) and 1% penicillin-streptomycin (Gibco). At 2 d after confluence, defined as d 0, cells were induced to differentiation medium containing 0.5 mmol/L 3-Isobutyl-1-methylxanthine (IBMX), 1 μmol/L dexamethasone and 5 μg/mL insulin (Sigma, St. Louis, MO, USA). On d 2, the medium was replaced with maintenance medium containing 5 μg/mL insulin (Sigma) every 2 d until d 8. Two hundred and ninety-three T cells were cultured in DMEM/F12 medium containing 10% fetal bovine serum and 1% penicillin-streptomycin (Gibco). Cells were uniformly cultured in a 5% CO2 incubator with 37 °C.
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| 133 |
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Cell transfection, plasmids and RNA knockdown
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| 136 |
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The plasmids and siRNA transfections were performed using Hieff Trans™ Liposomal Transfection Reagent and Hieff Trans™ in vitro siRNA/miRNA Transfection Reagent (Yeasen, Shanghai, China), according to the product protocol. The adenoviruses ADV4-ADIPOQ-CDS wild-type (ADV4-ADIPOQ-CDS-WT), ADV4-ADIPOQ-CDS mutant (m6A C534 and C570 were replaced by T, ADV4-ADIPOQ-CDS-MUT) and ADV4-ADIPOQ-CDS negative control (ADV4-ADIPOQ-CDS-NC) were generated by GenePharma (Shanghai, China). IMF cells were infected with the multiplicity of infection (MOI) of 25:1 by ADV4-ADIPOQ-CDS-WT, ADV4-ADIPOQ-CDS-MUT and ADV4-ADIPOQ-CDS-NC, respectively, and added 1 μg/mL polybrene to improve the infection efficiency, according to GenePharma’s protocol. Porcine YTHDF1 cDNA was generated via PCR and cloned into the pFLAG-CMV2 expression plasmid. Sequences of siRNA, synthesizd by GenePharma (Shanghai, China), were as follows: siADIPOQ-F, 5′- AGAAAGCGCCUAUGUCUACTT-3′ and siADIPOQ-R, 5′-GUAGACAUAGGCGCUUUCUCC-3′; siYTHDF1-F, 5′-UUAGUAUCCUGUCCUUUUGUU-3′ and siYTHDF1-R, 5′-CAAAAGGACAGGAUACUAAAG-3′.
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| 137 |
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| 138 |
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m6A-specific methylated RNA immunoprecipitation real-time PCR
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| 139 |
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| 140 |
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m6A-qPCR analysis was conducted according to previously report [38]. Briefly, mRNAs fragmented by RNA fragmentation reagent (Invitrogen) at 70 °C for 15 min. 10% of fragmented RNAs was used as input control mRNAs. The remaining 90% was immunoprecipitated with anti-m6A antibody coupled to Dynabeads (Invitrogen) in immunoprecipitation buffer (RNase inhibitor, 10 mmol/L Tris-HCl, 150 mmol/L NaCl, 0.1% Igepal CA-630 [Sigma]) at 4 °C for 2 h. mRNAs containing m6A were eluted twice with m6A 5′-monophosphate sodium salt (Sigma) at 4 °C for 1 h. After ethanol precipitation, all mRNAs were reversely transcribed into cDNA by M-MLV reverse transcriptase (Invitrogen). And then m6A enrichment was determined by qPCR. Data were analyzed with the 2−ΔΔCt method, and the relative enrichment of m6A in each sample was calculated by normalizing to input. The primers were as follows: ADIPOQ-CDS-F, 5′- TCCTTCCACATCACGGTCTACT-3′ and ADIPOQ-CDS-R, 5′- CTCCAGATAGAGGAGCACAGAG-3′; ADIPOQ-3’UTR-F, 5′-CCACTGTGTTTCCTCAGGTTC-3′ and ADIPOQ-3’UTR-R, 5′- CCACAGCCCTGTGTTTGACTT-3′.
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| 141 |
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| 142 |
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RNA immunoprecipitation assay
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| 143 |
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| 144 |
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The experiment pipeline was performed according to the previous research [39]. Briefly, FLAG-YTHDF1 overexpressed IMF cells were lysed in lysis buffer for 30 min at 4 °C and the supernatant was collected for further use. We saved 50-μL aliquot of cell lysate as input, and the remaining was incubated with anti-FLAG or immunoglobulin G (IgG) antibody-conjugated magnetic beads (Sigma) for 4 h at 4 °C. The beads were washed with buffer containing 0.1% SDS and proteinase K (Invitrogen), detecting fold enrichment with qPCR.
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| 145 |
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| 146 |
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Dual-luciferase reporter and mutagenesis assays
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| 147 |
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| 148 |
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To evaluate the effect of 3’UTR m6A site on ADIPOQ expression, wild type or mutant (m6A A650 was replaced by T) of ADIPOQ-3’UTR was inserted into downstream of pmirGLO Dual-Luciferase vector (Promega, Madison, WI, USA). After 48 h post transfection, the activities of firefly luciferase and Renilla luciferase in each 24-well plates’ well were determined by a Dual-Luciferase Reporter Gene Assay Kit (Yeasen) according to the product protocol.
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| 149 |
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Statistical analysis
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| 151 |
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All data were presented as mean ± SEM. Statistical differences in the dual luciferase reporter assay were determined by Mann-Whitney test, and other statistical significance between multiple groups were determined by Student’s t-test with GraphPad Prism 9. P < 0.05 was considered exceeding the significant level.
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Results
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Description of m6A modification between high and low IMF content groups
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To investigate the role of m6A modification on adipogenesis in LDM, we collected 20 extreme phenotypic samples of IMF content from the 6th generation individuals in a unique heterogeneous swine population, which exhibits a large variation of IMF content [22, 23]. The samples were divided into high and low group according to IMF content (High and Low), and LC-MS/MS was performed to evaluate the m6A modifications levels across the samples. We found that IMF content (left in Fig. 1a) and level of m6A modifications (right in Fig. 1a) displayed opposite trend across the group, while both of those were significantly divergent among High and Low (P < 0.01), in agreement with previous study [15]. We uncovered 20,738 and 20,117 peaks among High and Low (Fig. 1b), respectively. A total of 23,250 peaks as a m6A modification panel within this population were obtained by “bedtools merge -d 0”. Conserved m6A modification motif among the panel was concordance with previous study (RRACH (R = G or A and H = A, C or U)) using HOMER (Fig. 1d). m6A modification sites were accumulating at the stop codon site (Fig. 1c) [15]. Peaks, annotated with ChIPseeker, were mainly enriched in the 3’UTR (Fig. 1e). These results together suggested our data was credible to further investigate the effect of m6A modification on lipid deposition in LDM.Fig. 1 Overview of m6A modification in High and Low IMF content groups. a Intramuscular fat ratio (right) and m6A/A content (left) among High and Low group, n = 10. b Venn diagram of peaks among two groups. c Density of m6A modification across mRNA region. d Conserved motif in m6A peaks using HOMER software. e Annotation of location of m6A peak at whole-transcript level. ***P < 0.001
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| 159 |
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| 160 |
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Identifying co-expression gene module of LDM
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Co-expression network analysis enable us to identify genes which have a tendency to show a coordinated expression pattern among samples, uncovering the complexity of a cellular transcription network [37, 40]. Thus, we conducted the WGCNA software [35] to construct a co-expression network with 13,245 highly expressing genes (≥ 10 reads in at least 16 individuals) among 19 samples from the input RNA sequencing (RNA-seq) data of m6A-seq. L96 was excluded for outlier clustering according to the PCA and heatmap (Fig. S1a–d). We then chosen the optimal weighting coefficient β = 7 to construct the network based on pickSoftThreshold parameter in WGCNA. Figure 2a shows the cluster tree of the 19 samples and the corresponding traits information. Of 33 identified gene modules (Fig. 2b), MEdarkturquoise (module eigengene in dark turquoise) with 70 genes (Fig. 2c; Table S1) was detected significantly positively related to IMF content (r = 0.62; P = 0.004) and highly negatively associated with m6A content (r = − 0.51; P = 0.03) respectively, suggesting these genes within the module potentially participant in fat deposition. To investigate the underlying role of these co-expression genes, we performed the KEGG and GO pathway enrichment analysis by ClueGO in Cytoscape v3.9.0 [41]. The significant biological processes were involved in several adipogenesis related pathways, such as regulation of fat cell differentiation (ADIPOQ, BMP2, CEBPα, PPARγ, SFRP1), positive regulation of fat cell differentiation (BMP2, CEBPα, PPARγ, SFRP1) and PPAR signaling pathway (ADIPOQ, PLIN1, PPARγ) (Table S5). In addition, we identified 12 hub genes (ADIPOQ, PLIN1, UNC93A, SFRP1, HACD2, SNCG, SDR16C5, PPARγ, ITIH3, FFAR4, SORL1 and ACE2) from the dark turquoise module based on |geneModuleMembership| > 0.8 and |geneTraitSignificance| > 0.2 (Table 2). Of these, ADIPOQ, PLIN1, SFRP1, PPARγ and FFAR4 have been reported to participate in adipogenesis related function [42–45]. Remarkably, ADIPOQ, PLIN1 and FFAR4 were identified higher expression in subcutaneous fat and intramuscular fat compared with LDM among the same heterogeneous swine population [23], hinting these hub genes may play critical roles in adipogenesis.Fig. 2 Network analysis of MeRIP-seq input data of LDM samples. a Sample dendrogram from 19 LDM samples and trait heatmap including content of IMF and m6A modifications. Color intensity is directly proportional to the value of corresponding trait. b Cluster dendrogram of 13,245 highly expressing genes. Thirty-three co-expression modules were identified, each color represents a module. c Heatmap of the correlation between module eigengenes (MEs) and traits. Left value is correlation, and right enclosed in bracket is P-value. d Scatter plot for 70 genes in dark turquoise module, gene significance (GS) > 0.2 and module membership (MM) > 0.8 were selected as hub gene
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Table 2 Hub genes screened with WGCNA in porcine LDM
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Gene stable ID Gene name MMvalue GSvalue Gene description
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ENSSSCG00000039103 ADIPOQ 0.874557699 0.858025625 Adiponectin, C1Q and collagen domain containing [Source:VGNC Symbol; Acc:VGNC:85140]
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| 168 |
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ENSSSCG00000001844 PLIN1 0.855238258 0.785834744 Perilipin 1 [Source:VGNC Symbol; Acc:VGNC:91557]
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| 169 |
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ENSSSCG00000027404 UNC93A 0.864469943 0.688918599 unc-93 homolog A [Source:VGNC Symbol; Acc:VGNC:94711]
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| 170 |
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ENSSSCG00000025822 SFRP1 0.867467057 0.671675851 Secreted frizzled related protein 1 [Source:VGNC Symbol; Acc:VGNC:95493]
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| 171 |
+
ENSSSCG00000034786 HACD2 0.864057374 0.645773129 3-hydroxyacyl-CoA dehydratase 2 [Source:VGNC Symbol; Acc:VGNC:88766]
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| 172 |
+
ENSSSCG00000026850 SNCG 0.801110493 0.572908619 Synuclein gamma [Source:NCBI gene (formerly Entrezgene); Acc:100125343]
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| 173 |
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ENSSSCG00000006245 SDR16C5 0.838140788 0.569356922 Short chain dehydrogenase/reductase family 16C member 5 [Source:VGNC Symbol; Acc:VGNC:98853]
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| 174 |
+
ENSSSCG00000011579 PPARγ 0.823399895 0.542931625 Peroxisome proliferator activated receptor gamma [Source:VGNC Symbol; Acc:VGNC:91684]
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| 175 |
+
ENSSSCG00000011451 ITIH3 0.840818259 0.506913162 Inter-alpha-trypsin inhibitor heavy chain 3 [Source:VGNC Symbol; Acc:VGNC:89248]
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| 176 |
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ENSSSCG00000010478 FFAR4 0.953347586 0.485423388 Free fatty acid receptor 4 [Source:VGNC Symbol; Acc:VGNC:107392]
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| 177 |
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ENSSSCG00000015135 SORL1 0.88145227 0.479634802 Sortilin related receptor 1 [Source:HGNC Symbol; Acc:HGNC:11185]
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| 178 |
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ENSSSCG00000012138 ACE2 0.815256029 0.246877132 Angiotensin converting enzyme 2 [Source:VGNC Symbol; Acc:VGNC:85008]
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| 179 |
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MMvalue Value of Module Membership, the correlation of the module eigengene and the gene expression profile; GSvalue Value of Gene Significance, the absolute value of the correlation between the gene and the trait
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| 180 |
+
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| 181 |
+
ADIPOQ gene display significantly difference in both m6A modification and RNA expression between high and low group
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| 182 |
+
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| 183 |
+
To determine the role of m6A modification in intramuscular fat, we annotated the differential peak regions: 953 and 654 genes (Fig. 3a) were uniquely modified with m6A across the High and Low, respectively. One thousand and eighty-five genes (Fig. 3b; Table S2) were identified for significantly differential modified (abs (log2foldchange) > log21.5; P < 0.05). Gene ontology analysis of these m6A modified regions were significantly enriched in lipoprotein related functions (Fig. 3c), suggesting mRNA m6A in longissimus muscle play a potential role in regulating fat deposition. Among the 8 top significant differentially modified genes (according to P-value), we observed ADIOPQ (P = 5.09E−05) and SH3PXD2B (P = 1.28E−04) were reported to regulate the fat cell differentiation (Fig. 3b) [46, 47]. Similarly, we discovered 422 differential expression genes (abs (log2foldchange) > log21.5; P < 0.05) among the High and Low based on input RNA-seq data from m6A-seq (Fig. S1e; Table S3). Gene enrichment analysis revealed lipid droplet (CIDEC, PLIN1, PNPLA3, SDR16C5, TMEM135) and PPAR signaling pathway (ADIPOQ, AQP7, aP2, PLIN1, PPARγ) enriched in up regulation gene set (Fig. S1f; Table S5). We also observed the ADIPOQ gene displaying significantly differential RNA expression (P = 7.65E−14) among High and Low. Accumulating evidence indicated that mRNA m6A modification could mediate transcription regulation [12, 48]. Thus, to investigate whether m6A contributes to translation regulation in longissimus muscle, we overlapped the genes significantly difference both in the level of m6A modification and RNA expression between High and Low. Finally, we found 70 target co-differential genes (Fig. 3d, e), including ADIPOQ and SFRP1, which were related to several pathways such as PPAR signaling pathway (ADIPOQ, AQP7, aP2) (Table S4). SFRP1 gene has been reported that inhibits the Wnt/β-catenin signaling pathway, regulating the adipogenesis both in human and murine [49]. ADIPOQ gene is expressed specifically in adipose tissue [50], which exhibited higher expression in porcine fat tissues including subcutaneous fat and intramuscular fat than LDM in the same population [23]. To illustrate the mechanism of m6A modification on regulating the adipogenesis, we then chosen the hub gene ADIPOQ with remarkably methylated and RNA expression co-differential for further investigation (Fig. 3f, g).Fig. 3 RNA expression differentially and m6A modification differentially genes between High and Low. a Venn diagram of m6A modified genes across High and Low groups. b Volcano plot of m6A modified differential gene, P < 0.05 and fold change > 1.5 were marked as differentially methylated genes (blue and red), fold change value is calculated by High/Low. c GO and KEGG pathways of down (blue) and up (red) regulated m6A modification genes. d Venn diagram and (e) four quadrant diagram of methylated and RNA expression differential genes (P < 0.05 and fold change > 1.5) between High and Low group, 70 genes were observed significantly co-differential in e. f and g m6A methylation and mRNA expression of ADIPOQ gene between High and Low group, n = 8. Normalized read count was employed for comparing the level of m6A methylation between High and Low. Normalized read Count = SRN/ITR, SRN is site of reads number, while ITR is individual of total reads. SRN was counted using SAMtools v1.11 bedcov, ITR was inferred using SAMtools v1.11 flagstats based on BAM file. Input and IP data were both under the same pipeline of normalization. h Protein level of ADIPOQ between High and Low, n = 3
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| 185 |
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ADIPOQ promotes adipogenesis of preadipocytes in vitro
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| 186 |
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| 187 |
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To re-validate whether ADIPOQ gene regulates adipogenesis, intramuscular preadipocytes were isolated for adipogenic differentiation by the standard IBMX, dexamethasone, and insulin (MDI) cocktail (Fig. 4a). The lipid accumulation and mRNA expression levels of adipogenic genes (PPARγ, CEBPβ and aP2) were significantly increased after MDI induction (Fig. S2a, b). Simultaneously, the expression of ADIPOQ mRNA and protein were significantly increased from d 0 to 8 (Fig. S2c; Fig. 4b).Fig. 4 ADIPOQ promote adipogenesis of preadipocytes in vitro. a Workflow of porcine intramuscular adipocytes inducing in vitro. b Protein levels of ADIPOQ in intramuscular preadipocytes at 0, 2, 4 and 8 d during adipogenesis. c The mRNA levels of ADIPOQ (48 h) after siRNA transfection of porcine intramuscular preadipocytes, n = 3. d The protein expression levels of ADIPOQ (48 h) after siRNA transfection of porcine intramuscular preadipocytes. e–g TAG content and Oil Red O staining of siADIPOQ at 8 d after adipogenic induction, n = 3. h RT-qPCR of PPARγ, CEBPβ and aP2 of siADIPOQ at 8 d after adipogenic induction, n = 3. i The mRNA expression levels of ADIPOQ after overexpression ADIPOQ (48 h), n = 3. j The protein expression levels of ADIPOQ after overexpression ADIPOQ (48 h). k, l TAG content and Oil Red O staining of ADIPOQ-overexpression at 8 d after adipogenic induction, n = 3. m RT-qPCR of PPARγ, CEBPβ and aP2 of ADIPOQ overexpression at 8 d after adipogenic induction, n = 3. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001
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| 189 |
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Previous research had indicated that interference with ADIPOQ gene expression could inhibit the differentiation of porcine preadipocytes [42]. Thus, we established siRNA and overexpression plasmid to address the function of ADIPOQ in the process of adipogenic differentiation in our work. Not surprisingly, mRNA expression and protein level of ADIPOQ were significantly inhibited after siRNA interference at d 8 (Fig. 4c, d). Meanwhile, lipid accumulation of siADIPOQ was remarkably decreased according to triacylglycerol (TAG), Oil Red O staining and adipogenic genes (PPARγ, CEBPβ and aP2) mRNA expression (Fig. 4e–h). Next, we observed the overexpression of ADIPOQ in porcine intramuscular preadipocytes cell could significantly increase the levels of its mRNA expression and protein (Fig. 4i, j), promoting lipid accumulation (Fig. 4k–m). On the basis of above results, we concluded that ADIPOQ was expressed at the later stage of induction and promoted porcine intramuscular preadipocyte differentiation and lipid accumulation.
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| 191 |
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mRNA m6A modification can promote ADIPOQ expression
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| 192 |
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| 193 |
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Although we acquired that ADIPOQ could promote the lipid accumulation in intramuscular preadipocytes, the role of m6A modification in ADIPOQ remain unclear [42, 47]. To further explore the function of mRNA m6A modification on ADIPOQ expression, we firstly scanned the transcript to uncover the m6A sites of ADIPOQ gene based on the RRACH conversed feature. Three potential m6A sites including one in 3’UTR (AGACT, chr13:124,645,333–124,645,337) and two in CDS (GGACA, chr13:124,644,484–124,644,488; GGACA chr13:124,644,520–124,644,524) were found in the longest ADIPOQ transcript ENSSSCT00000047495 (Fig. 3f). To explore the role of m6A modification in 3’UTR and CDS of ADIPOQ, we constructed the dual-luciferase reporter plasmid and adenovirus vector with mutation in 3’UTR (ADIPOQ-3’UTR-MUT) and CDS (ADIPOQ-CDS-MUT), respectively (Fig. 5a, b; Table S6). Analysis of m6A-IP-qPCR found that m6A methylation levels of ADIPOQ-CDS-WT and ADIPOQ-3’UTR-WT were higher than ADIPOQ-CDS-MUT and ADIPOQ-3’UTR-MUT, respectively (Fig. 5a). Luciferase assays results indicated that mutation of ADIPOQ 3’UTR significantly decreased the luciferase activity in 293 T cells (Fig. 5c). Consistently, the mRNA expression and protein level of ADIPOQ in ADIPOQ-CDS-WT IMF cells were also higher than ADIPOQ-CDS-MUT (Fig. 5d, e). We also found ADIPOQ-CDS-MUT decreases lipid accumulation (Fig. 5f, g) and adipocyte differentiation-related gene expression including PPARγ, CEBPβ and aP2, relative to ADIPOQ-CDS-WT (Fig. 5h). Taken together, we concluded that the m6A modification of ADIPOQ in 3’UTR and CDS could both promote its expression.Fig. 5 ADIPOQ promotes adipogenesis of preadipocytes in a m6A-dependent manner. a m6A-IP-qPCR analysis of ADIPOQ-3’UTR WT or MUT (A to T mutation) in 293 T cells, n = 3. b m6A-IP-qPCR analysis ADIPOQ-CDS WT or MUT (C to T mutation) in porcine intramuscular preadipocytes, n = 3. c Relative luciferase activity of WT or MUT of ADIPOQ-3’UTR in 293 T cells, n = 3. d The mRNA expression levels of ADIPOQ of porcine intramuscular preadipocytes with NC, WT or MUT of ADIPOQ-CDS, n = 3. e The protein expression levels of ADIPOQ of porcine intramuscular preadipocytes with NC, WT or MUT of ADIPOQ-CDS. f and g TAG content and Oil Red O staining of porcine intramuscular preadipocytes with NC, WT or MUT of ADIPOQ-CDS at 8 d after adipogenic induction, n = 3. h RT-qPCR of PPARγ, CEBPβ and aP2 of porcine intramuscular preadipocytes with NC, WT or MUT of ADIPOQ-CDS at 8 d after adipogenic induction, n = 3. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001
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| 194 |
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| 195 |
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YTHDF1 mediates the regulation of ADIPOQ in an m6A-dependent manner
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| 196 |
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| 197 |
+
We then explored the mechanism about how m6A modification regulated ADIPOQ expression. YTHDF1 was reported to promote translation of m6A methylated transcripts [51]. Regarding the m6A sites in 3’UTR or CDS could promote the translation of ADIPOQ, we assumed that ADIPOQ is the target of YTHDF1. Thus, we performed YTHDF1 knockdown and overexpressing experiments to identify whether it could regulate ADIPOQ expression. Not surprisingly, YTHDF1 knockdown decreased ADIPOQ protein expression (Fig. 6a), while YTHDF1 overexpression increased ADIPOQ protein expression (Fig. 6b). RIP-qPCR assay revealed that ADIPOQ interacted with YTHDF1-FLAG, which confirmed that ADIPOQ is the target of YTHDF1 (Fig. 6c, d). To further explore whether YTHDF1 targets and recognizes the ADIPOQ mRNA m6A modification site, we transferred YTHDF1 overexpression plasmid into ADIPOQ-3’UTR-WT (or MUT) and ADIPOQ-CDS-WT (or MUT) cells, respectively. Overexpression of YTHDF1 increased luciferase activity and ADIPOQ protein level in ADIPOQ-3’UTR-WT 293 T cells, but no change in ADIPOQ-3’UTR-MUT (Fig. 6e, f) cells. Similarly, overexpressing YTHDF1 increased the mRNA and protein expression of ADIPOQ in ADIPOQ-CDS-WT IMF cells but no change in ADIPOQ-CDS-MUT cells (Fig. 6g, h). Moreover, we also observed overexpressing YTHDF1 increases lipid accumulation (Fig. 6i, j) and adipocyte differentiation-related gene expression including PPARγ, CEBPβ and aP2 (Fig. 6k) in ADIPOQ-CDS-WT but not in ADIPOQ-CDS-MUT. Collectively, these results together suggest YTHDF1 promotes the translation of hub gene ADIPOQ by recognizing m6A sites in both 3’UTR and CDS.Fig. 6 YTHDF1 regulate the translation of ADIPOQ in IMF cells. a The protein levels of ADIPOQ in porcine intramuscular preadipocytes transfected with siControl or siYTHDF1 (48 h). b The protein levels of ADIPOQ after overexpression YTHDF1 (48 h). c The protein levels of YTHDF1 of porcine intramuscular preadipocytes transfected with control or YTHDF1-FLAG plasmid (48 h). d RIP analysis of the interaction of ADIPOQ with FLAG in porcine intramuscular preadipocytes transfected with YTHDF1-FLAG plasmid. Enrichment of ADIPOQ with FLAG was measured by qPCR and normalized to input. e The protein levels of YTHDF1 of 293 T cells transfected with WT or MUT of ADIPOQ-3’UTR or YTHDF1 overexpression plasmid (48 h). f Relative luciferase activity of WT or MUT of ADIPOQ-3’UTR or YTHDF1 overexpression in 293 T cells, n = 3. g The mRNA expression levels of ADIPOQ of porcine intramuscular preadipocytes with WT or MUT of ADIPOQ-CDS or YTHDF1-overexpression plasmid (48 h), n = 3. h The protein expression levels of ADIPOQ of porcine intramuscular preadipocytes with WT or MUT of ADIPOQ-CDS or YTHDF1-overexpression plasmid (48 h). i and j TAG content and Oil Red O staining of porcine intramuscular preadipocytes with WT or MUT of ADIPOQ-CDS or YTHDF1 overexpression plasmid at 8 d after adipogenic induction, n = 3. k RT-qPCR of PPARγ, CEBPβ and aP2 of porcine intramuscular preadipocytes with WT or MUT of ADIPOQ-CDS or YTHDF1 overexpression plasmid at 8 d after adipogenic induction, n = 3. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001
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Discussion
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In this work, we performed the m6A-seq of LDM from a unique heterogenous swine population to investigate the underlying mechanism of mRNA m6A modification regulating IMF deposition. We revealed that hub gene ADIPOQ could promote its mRNA translation in an m6A-YTHDF1-dependent manner, providing novel evidence of m6A methylation regulating adipogenesis.
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Fat deposition is highly relevant to human health [52, 53], uncovering the mechanism porcine intramuscular adipogenesis is better for understanding gene regulation underlying the fat deposition of corresponding tissues in humans. Accumulating evidences demonstrate that m6A modification is involving in adipogensis pathway [17–19]. Although previous finding has been revealed that m6A modification of MTCH2 promotes adipogenesis in LDM when comparing obese Asian domesticated Jinhua pig and lean Western commercial pig, these results was still limited because of the selected validation gene merely obtain from top 10 methylation in Jinhua breed [15]. In this study, we possessed different hallmark from previous studies in that a unique swine population was used [15, 54], and found that some individuals exhibits a large variation of IMF content. More importantly, IMF content was negatively related to the mRNA m6A level across the High and Low group (P < 0.01), indicating a potential role of m6A in intramuscular fat deposition, which was consistent to previous study.
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To explore the underlying role and mechanism of m6A in porcine intramuscular fat, we performed a large sample size of MeRIP data (n = 10 per group), which allowed us to explore more significant differential m6A modification sites. Tao et al. uncovered 5,872 and 2,826 m6A peaks respectively, in the porcine muscle and adipose tissue transcriptomes [54]. Here, we identified a total of 23,250 m6A peaks in this population, to our knowledge, it is largest m6A data set in procine intramuscular fat. Besides, the consensus motif sequence RRACH in our study was consistent with previous work. mRNA m6A sites were enriched around stop codons, sharing a smiliar distribution to those of human, mice and plants [55–57]. Taken together, using larger sample size and stringent m6A calling parameters, our results allow a reliable picture of the mRNA m6A epi-transcriptome in porcine skeletal muscles.
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To uncover which key genes regulate adipogenesis in m6A-dependent manner, we performed gene co-expression network using WGCNA to explore the biologically relevant associations between phenotype and module [35]. Finally, we uncovering 70 modules among 19 high expression RNA input data, including 12 hub genes, were significantly corelated with IMF content and m6A modification level. Emerging evidences have indicated that WGCNA could reveal potential candidate gene in affecting the IMF content of Duroc [58] and Italian Large White pigs [59]. Thus, we overlapped RNA expression differential and m6A methylated differential genes, discovering 70 co-differential genes. We further found 2 hub gene ADIPOQ and SFRP1 including in co-differential gene set. These results largely advanced our knowledge towards co-expression networks in IMF deposition.
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| 208 |
+
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| 209 |
+
In this work, we found ADIPOQ gene displayed remarkably differential both in RNA expression (P = 7.65E−14) and m6A methylation (P = 5.09E−05). ADIPOQ has been identified as candidate gene for the metabolic syndrome and T2DM by genome wide associated study [60, 61]. Previous work also indicated ADIPOQ exhibited higher expression in both intramuscular fat and subcutaneous fat than LDM in the same swine population [23]. Consistently, previous study provided supportive evidence for silencing of ADIPOQ efficiently suppresses preadipocyte differentiation in porcine [42]. By establishing the lipogenesis model in vitro, we revalidated the ADIPOQ gene could promote the adipogenesis of porcine preadipocyte. We further found mRNA m6A modification could promote the expression of ADIPOQ and lipid accumulation by constructing the dual-luciferase reporter plasmid and adenovirus vector in 3’UTR and CDS, respectively.
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| 210 |
+
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| 211 |
+
Various m6A binding proteins, especially YTHDF family, have been proved their functions in different aspects, such as RNA translation, splicing, export or degradation [62, 63]. YTHDF1 selectively recognizes m6A in cytosolic mRNAs, recruiting initiation factor eIF3 to facilitate mRNA translation [51]. YTHDF2 brings m6A-modified translatable mRNAs to mRNA decay sites (e.g., P-bodies), and recruiting CC chemokine receptor 4-negative regulator of transcription complex to trigger mRNA deadenylation [9, 64]. YTHDF3 promotes mRNA translation in synergy with YTHDF1 and accelerated decay of m6A-containing mRNAs through interaction with YTHDF2. Accumulating evidences suggest YTHDF1 promote RNA expression via recognizing mRNA m6A site [65, 66]. YTHDF1 interacting with MTCH2 mRNA to enhance translation of its protein in porcine intramuscular preadipocytes [15, 67]. Thus, we here have conducted interference and overexpression YTHDF1 to confirm its function. Not surprising, we observed YTHDF1 promoting the translation of hub gene ADIPOQ, confirming that ADIPOQ was a target of YTHDF1 through m6A-IP and RIP experiments.
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+
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| 213 |
+
Conclusions
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| 214 |
+
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In conclusion, our study characterized the m6A modification genes which were potentially involved in regulating IMF deposition. Furthermore, we presented a novel regulatory mechanism of IMF deposition via the m6A-YTHDF1-ADIPOQ axis, highlighting the critical role of mRNA m6A modification of the hub gene in IMF adipogenesis.
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Supplementary Information
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| 218 |
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| 219 |
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Additional file 1: Fig. S1. RNA expression analysis of MeRIP-seq input data. a and b PCA and heatmap of highly expression genes among 20 and (c and d) 19 samples (excluded L96), respectively. e Volcano plot of RNA differential expression gene (P-adjust < 0.05 and fold change > 1.5), DSPP gene in the dotted box for extremely outlier of the figure (log2foldchange = − 25.3; P-adjust = 1.36E−17)
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| 220 |
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Additional file 2: Fig. S2. Establishment of lipogenesis model in vitro. a Oil Red O staining of porcine intramuscular preadipocytes at 0, 2, 4 and 8 d after adipogenic induction, n = 3. b RT-qPCR of ADIPOQ of porcine intramuscular preadipocytes at 0, 2, 4 and 8 d after adipogenic induction, n = 3. c RT-qPCR of PPARγ, CEBPβ and aP2 of porcine intramuscular preadipocytes at 0, 2, 4 and 8 d after adipogenic induction, n = 3. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001
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| 222 |
+
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| 223 |
+
Additional file 3: Table S1. 70 genes in MEdarkturquoise module
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| 224 |
+
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| 225 |
+
Additional file 4: Table S2. m6A differential modified genes
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| 226 |
+
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| 227 |
+
Additional file 5: Table S3. RNA expression differential genes
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| 228 |
+
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| 229 |
+
Additional file 6: Table S4. Methylated and RNA expression co-differential genes
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| 230 |
+
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| 231 |
+
Additional file 7: Table S5. KEGG and GO analysis of gene set from Table S1-S4
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| 232 |
+
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| 233 |
+
Additional file 8: Table S6. m6A modification mutation site of ADIPOQ cDNA in CDS and 3′ UTR
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| 234 |
+
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| 235 |
+
Abbreviations
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| 236 |
+
|
| 237 |
+
ACE2 Angiotensin converting enzyme 2
|
| 238 |
+
|
| 239 |
+
ADIPOQ Adiponectin
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| 240 |
+
|
| 241 |
+
aP2 Fatty acid binding protein 4
|
| 242 |
+
|
| 243 |
+
AQP7 Aquaporin 7
|
| 244 |
+
|
| 245 |
+
BAM Binary Alignment/Map format
|
| 246 |
+
|
| 247 |
+
BMP2 Bone morphogenetic protein type 2
|
| 248 |
+
|
| 249 |
+
CDS Coding sequence
|
| 250 |
+
|
| 251 |
+
CEBPα CCAAT enhancer binding protein alpha
|
| 252 |
+
|
| 253 |
+
CEBPβ CCAAT enhancer binding protein beta
|
| 254 |
+
|
| 255 |
+
CIDEC Cell death inducing DFFA like effector c
|
| 256 |
+
|
| 257 |
+
DMEM Dulbecco’s modified eagle medium
|
| 258 |
+
|
| 259 |
+
FFAR4 Free fatty acid receptor 4
|
| 260 |
+
|
| 261 |
+
GO Gene ontology
|
| 262 |
+
|
| 263 |
+
HACD2 3-hydroxyacyl-CoA dehydratase 2
|
| 264 |
+
|
| 265 |
+
IBMX 3-Isobutyl-1-methylxanthine
|
| 266 |
+
|
| 267 |
+
IgG Immunoglobulin G
|
| 268 |
+
|
| 269 |
+
IMF Intramuscular fat
|
| 270 |
+
|
| 271 |
+
IP Immunoprecipitation
|
| 272 |
+
|
| 273 |
+
ITIH3 Inter-alpha-trypsin inhibitor heavy chain 3
|
| 274 |
+
|
| 275 |
+
KEGG Kyoto Encyclopedia of Genes and Genomes
|
| 276 |
+
|
| 277 |
+
LDM Longissimus dorsi muscle
|
| 278 |
+
|
| 279 |
+
m6A N6-methyladenosine
|
| 280 |
+
|
| 281 |
+
MDI Dexamethasone, and insulin
|
| 282 |
+
|
| 283 |
+
MTCH2 Mitochondrial carrier homolog 2
|
| 284 |
+
|
| 285 |
+
MUT Mutation
|
| 286 |
+
|
| 287 |
+
OD Optical density
|
| 288 |
+
|
| 289 |
+
PLIN1 Perilipin 1
|
| 290 |
+
|
| 291 |
+
PMSF Phenylmethanesulfonyl fluoride
|
| 292 |
+
|
| 293 |
+
PNPLA3 Patatin like phospholipase domain containing 3
|
| 294 |
+
|
| 295 |
+
PPAR Peroxisome proliferator activated receptor
|
| 296 |
+
|
| 297 |
+
PPARγ Peroxisome proliferator activated receptor gamma
|
| 298 |
+
|
| 299 |
+
Qpcr Real-time quantitative PCR
|
| 300 |
+
|
| 301 |
+
RIP RNA immunoprecipitation
|
| 302 |
+
|
| 303 |
+
SDR16C5 Short chain dehydrogenase/reductase family 16C member 5
|
| 304 |
+
|
| 305 |
+
SFRP Secreted frizzled-related protein 1
|
| 306 |
+
|
| 307 |
+
SH3PXD2B SH3 and PX domain-containing protein 2B
|
| 308 |
+
|
| 309 |
+
SNCG Synuclein gamma
|
| 310 |
+
|
| 311 |
+
SORL1 Sortilin related receptor 1
|
| 312 |
+
|
| 313 |
+
TAG Triacylglycerol
|
| 314 |
+
|
| 315 |
+
T2DM Type 2 diabetes mellitus
|
| 316 |
+
|
| 317 |
+
TMEM135 Transmembrane protein 135
|
| 318 |
+
|
| 319 |
+
UTR Untranslated region
|
| 320 |
+
|
| 321 |
+
UNC93A Unc-93 homolog A
|
| 322 |
+
|
| 323 |
+
WGCNA Weighted correlation network analysis
|
| 324 |
+
|
| 325 |
+
WT Wide type
|
| 326 |
+
|
| 327 |
+
YTHDF1–3 YT521‑B homology domain family proteins 1–3
|
| 328 |
+
|
| 329 |
+
Acknowledgements
|
| 330 |
+
|
| 331 |
+
This work was supported by funds from the National Natural Science Foundation of China (Grant No. U21A20249) and China Postdoctoral Science Foundation (2022 M712794). We are deeply grateful to Prof. Lusheng Huang and all the colleagues from State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University, Nanchang for supporting the samples and critical suggestions.
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| 332 |
+
|
| 333 |
+
Authors’ contributions
|
| 334 |
+
|
| 335 |
+
YW and HG collected the foundation. YW and XW supervised the project. HG, TG and XW wrote the manuscript. HG analyzed the data and performed visualization. TG performed the experiments and visualization. YL helped in designing the experiments. All the authors have read and agreed the published version of the manuscript.
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| 336 |
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|
| 337 |
+
Declarations
|
| 338 |
+
|
| 339 |
+
Ethics approval and consent to participate
|
| 340 |
+
|
| 341 |
+
The experimental procedures were in compliance with guidelines of the Committee on Animal Care and Use and Committee on the Ethic of Animal Experiments of Zhejiang University (Hangzhou, China).
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| 342 |
+
|
| 343 |
+
Consent for publication
|
| 344 |
+
|
| 345 |
+
Not applicable.
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| 346 |
+
|
| 347 |
+
Competing interests
|
| 348 |
+
|
| 349 |
+
The author declare no competing interests.
|
| 350 |
+
|
| 351 |
+
Huanfa Gong and Tao Gong contributed equally to this work.
|
| 352 |
+
==== Refs
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63. Zaccara S Ries RJ Jaffrey SR Reading, writing and erasing mRNA methylation Nat Rev Mol Cell Biol. 2019 20 10 608 624 10.1038/s41580-019-0168-5 31520073
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| 418 |
+
64. Du H Zhao Y He J Zhang Y Xi H Liu M YTHDF2 destabilizes m(6)A-containing RNA through direct recruitment of the CCR4-NOT deadenylase complex Nat Commun 2016 7 12626 10.1038/ncomms12626 27558897
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| 419 |
+
65. Zaccara S, Jaffrey SR. A unified model for the function of YTHDF proteins in regulating m6A-modified mRNA. Cell. 2020;181(7):1582–95. 10.1016/j.cell.2020.05.012.
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| 420 |
+
66. Wang X Zhao BS Roundtree IA Lu Z Han D Ma H N6-methyladenosine modulates messenger RNA translation efficiency Cell 2015 161 6 1388 1399 10.1016/j.cell.2015.05.014 26046440
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| 421 |
+
67. Huang H, Weng H, Chen J. m6A modification in coding and non-coding RNAs: roles and therapeutic implications in cancer. Cancer Cell. 2020;37(3):270–88. 10.1016/j.ccell.2020.02.004.
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| 422 |
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puc/PMC10081256.txt
ADDED
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@@ -0,0 +1,30 @@
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
bioRxiv
|
| 4 |
+
BIORXIV
|
| 5 |
+
bioRxiv
|
| 6 |
+
Cold Spring Harbor Laboratory
|
| 7 |
+
|
| 8 |
+
10.1101/2023.03.27.534456
|
| 9 |
+
preprint
|
| 10 |
+
1
|
| 11 |
+
Article
|
| 12 |
+
Single-cell transcriptome dataset of human and mouse in vitro adipogenesis models
|
| 13 |
+
Li Jiehan
|
| 14 |
+
Jin Christopher
|
| 15 |
+
Gustafsson Stefan
|
| 16 |
+
Rao Abhiram
|
| 17 |
+
Wabitsch Martin
|
| 18 |
+
Park Chong Y.
|
| 19 |
+
Quertermous Thomas
|
| 20 |
+
Bielczyk-Maczynska Ewa
|
| 21 |
+
Knowles Joshua W.
|
| 22 |
+
29 3 2023
|
| 23 |
+
2023.03.27.534456http://biorxiv.org/lookup/doi/10.1101/2023.03.27.534456
|
| 24 |
+
nihpp-2023.03.27.534456.pdf
|
| 25 |
+
Abstract
|
| 26 |
+
|
| 27 |
+
Adipogenesis is a process in which fat-specific progenitor cells (preadipocytes) differentiate into adipocytes that carry out the key metabolic functions of the adipose tissue, including glucose uptake, energy storage, and adipokine secretion. Several cell lines are routinely used to study the molecular regulation of adipogenesis, in particular the immortalized mouse 3T3-L1 line and the primary human Simpson-Golabi-Behmel syndrome (SGBS) line. However, the cell-to-cell variability of transcriptional changes prior to and during adipogenesis in these models is not well understood. Here, we present a single-cell RNA-Sequencing (scRNA-Seq) dataset collected before and during adipogenic differentiation of 3T3-L1 and SGBS cells. To minimize the effects of experimental variation, we mixed 3T3-L1 and SGBS cells and used computational analysis to demultiplex transcriptomes of mouse and human cells. In both models, adipogenesis results in the appearance of three cell clusters, corresponding to preadipocytes, early and mature adipocytes. These data provide a groundwork for comparative studies on human and mouse adipogenesis, as well as on cell-to-cell variability in gene expression during this process.
|
| 28 |
+
==== Body
|
| 29 |
+
pmc
|
| 30 |
+
|
puc/PMC10092757.txt
ADDED
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@@ -0,0 +1,329 @@
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|
| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Int J Biol Sci
|
| 4 |
+
Int J Biol Sci
|
| 5 |
+
ijbs
|
| 6 |
+
International Journal of Biological Sciences
|
| 7 |
+
1449-2288
|
| 8 |
+
Ivyspring International Publisher Sydney
|
| 9 |
+
|
| 10 |
+
10.7150/ijbs.82178
|
| 11 |
+
ijbsv19p1713
|
| 12 |
+
Research Paper
|
| 13 |
+
BAP31 depletion inhibited adipogenesis, repressed lipolysis and promoted lipid droplets abnormal growth via attenuating Perilipin1 proteasomal degradation
|
| 14 |
+
Wei Xueying 1#
|
| 15 |
+
Li Liya 2#
|
| 16 |
+
Zhao Jie 1
|
| 17 |
+
Huo Yan 1
|
| 18 |
+
Hu Xiaodi 1
|
| 19 |
+
Lu Jingyi 1
|
| 20 |
+
Pi Jingbo 3
|
| 21 |
+
Zhang Wei 4
|
| 22 |
+
Xu Lisheng 5
|
| 23 |
+
Yao Yudong 6
|
| 24 |
+
Xu Jialin 1✉
|
| 25 |
+
1 Institute of Biochemistry and Molecular Biology, College of Life and Health Sciences, Northeastern University, Shenyang, 110819, Liaoning, China
|
| 26 |
+
2 Institute of Microbial Pharmaceuticals, College of Life and Health Sciences, Northeastern University, Shenyang, 110819, Liaoning, China
|
| 27 |
+
3 School of Public Health, China Medical University, Shenyang, 110122, Liaoning, China
|
| 28 |
+
4 Department of Hepatobiliary Surgery, General Hospital of Northern Theater Command of the Chinese People's Liberation Army, Shenyang, 110016, Liaoning, China
|
| 29 |
+
5 College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110819, Liaoning, China
|
| 30 |
+
6 Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, 07030, USA
|
| 31 |
+
✉ Corresponding author: Jialin Xu, Ph. D., Institute of Biochemistry and Molecular Biology, College of Life and Health Sciences, Northeastern University, Shenyang, 110819, Liaoning, China Phone: (+86) 2483656117, E-mail: Jialin_xu@mail.neu.edu.cn
|
| 32 |
+
# These authors contributed equally to this work
|
| 33 |
+
|
| 34 |
+
Competing Interests: The authors have declared that no competing interest exists.
|
| 35 |
+
|
| 36 |
+
2023
|
| 37 |
+
13 3 2023
|
| 38 |
+
19 6 17131730
|
| 39 |
+
27 12 2022
|
| 40 |
+
25 2 2023
|
| 41 |
+
© The author(s)
|
| 42 |
+
2023
|
| 43 |
+
https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
|
| 44 |
+
BAP31 expression was robustly decreased in obese white adipose tissue (WAT). To investigate the roles of BAP31 in lipid metabolism, adipocyte-specific conditional knockout mice (BAP31-ASKO) were generated. BAP31-ASKO mice grow normally as controls, but exhibited reduced lipid accumulation in WAT. Histomorphometric analysis reported increased adipocyte size in BAP31-ASKO mice. Mouse embryonic fibroblasts (MEFs) were induced to differentiation to adipocytes, showed reduced induction of adipogenic markers and attenuated adipogenesis in BAP31-deficient MEFs. BAP31-deficiency inhibited fasting-induced PKA signaling activation and the fasting response. β3-adrenergic receptor agonist-induced lipolysis also was reduced, accompanied by reduced free-fatty acids and glycerol release, and impaired agonist-induced lipolysis from primary adipocytes and adipose explants. BAP31 interacts with Perilipin1 via C-terminal cytoplasmic portion on lipid droplets (LDs) surface. Depletion of BAP31 repressed Perilipin1 proteasomal degradation, enhanced Perilipin1 expression and blocked LDs degradation, which promoted LDs abnormal growth and supersized LDs formation, resulted in adipocyte expansion, thus impaired insulin signaling and aggravated pro-inflammation in WAT. BAP31-deficiency increased phosphatidylcholine/phosphatidylethanolamine ratio, long chain triglycerides and most phospholipids contents. Overall, BAP31-deficiency inhibited adipogenesis and lipid accumulation in WAT, decreased LDs degradation and promoted LDs abnormal growth, pointing the critical roles in modulating LDs dynamics and homeostasis via proteasomal degradation system in adipocytes.
|
| 45 |
+
|
| 46 |
+
BAP31
|
| 47 |
+
Perilipin1
|
| 48 |
+
Lipid droplet
|
| 49 |
+
Lipolysis
|
| 50 |
+
Proteasomal degradation
|
| 51 |
+
==== Body
|
| 52 |
+
pmcIntroduction
|
| 53 |
+
|
| 54 |
+
Obesity is one of the most widespread problems facing our society's health and is highly associated with type 2 diabetes, cardiovascular disease, fatty liver disease, and cancer 1. Aberrant expansion of adipose tissue occurs through an increase in adipocyte numbers (hyperplasia) or an enlargement in adipocyte size (hypertrophy) 2. Adipogenesis is the process which stores excessive energy in the form of lipid droplets (LDs). LDs are dynamic cellular organelles that store free-fatty acids (FFA) into triglycerides (TAG), and suppress lipotoxicity by preventing cell death, endoplasmic reticulum (ER) stress, and mitochondrial dysfunction 3. LDs provide a natural source of stored lipids that can be mobilized, which release FAs that can be broken down by β-oxidation for energy use. However, enlarged LDs due to lipid overloading increased adipocyte size and promoted unilocular LDs formation, and leaded to the development of obesity and insulin resistance 4. Controlling LDs abnormal growth is promised to be one of the options for preventing the development of obesity. Protein factors on LDs surface is vital for controlling LD biology and is most apparent during adipocyte differentiation.
|
| 55 |
+
|
| 56 |
+
Perilipin1 (Plin1) is one of the most important LD-associated surface proteins, involved in LDs stabilization and lipolysis by lipase and the cofactors 5. Plin1 has been reported playing a dual role in inhibiting basal or facilitating stimulated lipolysis. Signaling or agonists leads to PKA signaling activation, and induces the phosphorylation of Plin1, which promotes the translocation of Hormone-sensitive lipase (Hsl) to LDs surface and enhance TAG hydrolysis 5. Plin1-null mice exhibited enhanced basal lipolysis rate, due to the loss of the protective roles of Plin1 and the barrier for LDs. Loss-of-perilipin function resulted in lean and healthy mice, which are resistant to diet-induced obesity and insulin resistance 6. Plin1 promoted unilocular LDs formation and increased LD size through the activation of Fat-specific protein 27 (Fsp27), illustrating the functional cooperation between Plin1 and Fsp27 is required for LDs growth 7. Plin1 protein levels on LDs surface were dynamically regulated. Lipid overloading promoted LDs growth and increased perilipin protein levels via post-translationally stabilization of newly synthesized perilipins 8. Plin1 interacted with ubiquitin, and the ubiquitin-proteasome system was confirmed involved in Plin1 protein degradation 9, 10.
|
| 57 |
+
|
| 58 |
+
B-cell receptor-associated protein 31 (BAP31) is a multi-pass transmembrane protein of the ER 11, expresses ubiquitously and has been implicated in apoptosis 12, cancer development 13, ER exporting and retention 14, immune system regulation 15, protein degradation and quality control 16. Patients with BAP31 mutations suffered from motor and intellectual disabilities, dystonia, and cholestatic liver disease 17. The endothelial depletion of BAP31 attenuated LPS-induced acute lung injury via attenuating neutrophils-ECs adhesion, suggesting the important roles of BAP31 in regulating inflammatory response 18. Even ER plays an important role in lipid metabolism and BAP31 services as an evolutionarily conserved protein of the ER, relatively few research focused on lipid metabolism is available. BAP31 and ABCD1 mutation resulted in hepatomegaly and visible vacuoles in hepatocytes 19. BAP31 coupled with VAPB, VCP, FAF1, and Derlin-1, regulated the degradation of ΔF508-CFTR and lipid homeostasis, leading to the observed phenotypes of lipid abnormalities in protein folding diseases 20. Our previous publications reported that BAP31-deficiency in hepatocytes promoted SREBP1C activity and increased hepatic lipid accumulation 21, and enhanced ER-stress induced liver steatosis in mice 22. Whether BAP31 affects ER-derived LDs biology and modulates lipid accumulation in white adipose tissue (WAT) is still uncertain. Herein, the adipocyte-specific conditional knockout mice were generated. The effects on lipid accumulation and the underlying mechanisms regarding LDs growth and lipolysis were determined.
|
| 59 |
+
|
| 60 |
+
Materials and Methods
|
| 61 |
+
|
| 62 |
+
Mice breeding
|
| 63 |
+
|
| 64 |
+
BAP31 is an X-linked gene. BAP31flox allele mice (BAP31flox/-) on C57BL/6 background 21 were mated with the transgenic mice expressing Cre recombinase under adiponectin promoter (adipo-Cre) control, to obtain adipo-Cre;BAP31flox/- and adipo-Cre;BAP31flox/flox offspring, and then were crossed with BAP31flox/flox or BAP31flox/-allele mice, to generate adipo-Cre;BAP31flox/- (specific deletion of BAP31 in adipocyte, BAP31-ASKO) and BAP31flox/- (WT) mice. Male mice were used in the current study. All procedures were approved (NEU-EC-2021A036S) by the institutional review board of Northeastern University in accordance with the Guide for the Care and Use of Laboratory Animals.
|
| 65 |
+
|
| 66 |
+
HFD feeding
|
| 67 |
+
|
| 68 |
+
WT and BAP31-ASKO mice (6-week-old) were fed with a high-fat diet (HFD. H10060, Beijing HFK Bioscience Co. Ltd.) for 14 weeks. Body weight (BW) was measured every 4 days. After exposure for 13 weeks, mice were food deprived for 16 or 5 hours, and then injected with glucose (2 mg/kg) or insulin (0.75 U/kg) solution intraperitoneally. The blood glucose at 0, 15, 30, 60, and 120 minutes were determined using a one-touch glucometer (Bioland technology, Shenzhen, China).
|
| 69 |
+
|
| 70 |
+
Fasting treatment
|
| 71 |
+
|
| 72 |
+
WT and BAP31-ASKO mice were food deprived with free access to water for 24 hours, and then were decapitated under deep anesthesia with isoflurane. Liver and WAT were dissected. The blood samples were withdrawn. Sera were purified and stored in -80°C for future experiments.
|
| 73 |
+
|
| 74 |
+
Hematoxylin and eosin (H/E) staining
|
| 75 |
+
|
| 76 |
+
Sections (4 μm) of paraffin-embedded WAT, BAT and liver were cut and stained with hematoxylin and eosin before histopathologic analysis. For adipocyte diameter analysis, five fields from each section were taken and totally more than 400 adipocytes were analyzed for each group.
|
| 77 |
+
|
| 78 |
+
Serum and lipid extracts measurement
|
| 79 |
+
|
| 80 |
+
Serum glucose, TAG, FFA, cholesterol, and glycerol were measured using the kits from Nanjing Jiancheng Biomedical Company (Nanjing, China) and Solarbio Life Sciences (Beijing, China). Differentiated adipocytes or WAT (~50 mg) were lysed with PBS. Lipids were extracted with chloroform-methanol (2:1; v/v), and then were evaporated to dryness in a vacuum dryer set at 45°C for 2 hours. The lipid residue was dissolved in 100% ethanol containing 1% Triton X-100. TAG and FFA content were determined. The results were normalized with used tissue weight or cellular protein amount 23.
|
| 81 |
+
|
| 82 |
+
Induction of adipocyte differentiation
|
| 83 |
+
|
| 84 |
+
Mouse embryonic fibroblasts (MEFs) were isolated from 13.5- to 15.5-dpc mouse embryos. MEFs and 3T3-L1 preadipocytes were cultured in DMEM containing 10% FBS. Two days post 90% confluence, MEFs were induced to differentiation to adipocytes by switching to differentiated media (10 μg/mL insulin, 1 μM dexamethasone, and 0.5 mM isobutylmethylxanthine) for the first 3 days, and then incubated with the maintaining media (10 μg/mL insulin) for the remaining days 23.
|
| 85 |
+
|
| 86 |
+
DNA transfection and gene silencing
|
| 87 |
+
|
| 88 |
+
Full-length cDNAs encoding various mouse proteins were amplified by PCR from the cDNA of 3T3-L1 preadipocytes. cDNA encoding mouse BAP31 and Plin1 were cloned into pcDNA3.1(-) (Thermo Fisher Scientific). Plasmid DNA and siRNA were introduced into 3T3-L1 preadipocytes by using lipo8000TM (Beyotime Biotechnology, Shanghai, China). For the stable cell line, 3T3-L1 preadipocytes were infected with lentivirus targeted with BAP31 for 24 hours, and then treated with 2 μg/mL of puromycin for 4-5 days to select the positive clones. The resistant cells were diluted and seeded on a 96-well plate to form a single colony. The knockdown efficiency was evaluated by immunoblotting analysis.
|
| 89 |
+
|
| 90 |
+
Immunostaining
|
| 91 |
+
|
| 92 |
+
3T3-L1 preadipocytes cultured on coverslips were fixed and permeabilized, blocked with 10% goat serum for 1 hour and incubated with anti-BAP31 (1:200) and anti-Plin1 (1:200) antibodies at 4°C overnight, followed by incubation with the secondary antibodies (1:500) for 1 hour at room temperature. LDs were stained with Nile red (1:1000. Sigma-Aldrich. 72485) in PBS for another 10 minutes. Nucleus were stained with DAPI for 5 minutes. The fluorescence was visualized using a confocal laser scanning microscope (Leica Biosystems, Wetzlar, Germany).
|
| 93 |
+
|
| 94 |
+
Quantitative Real-time PCR
|
| 95 |
+
|
| 96 |
+
RNA was extracted with Trizol reagent and 2 μg of total RNA was converted to cDNA. The relative mRNA levels were quantified by quantitative real-time PCR using a CFX96 Touch™ real-time PCR detection system (Bio-Rad Laboratories, CA, USA). SYBR chemistry was used and the primer sequences are listed in table S1. 18S rRNA expression was used as the loading control. Comparative cycle threshold method (ΔΔCt) was used for gene expression analysis.
|
| 97 |
+
|
| 98 |
+
Immunoblotting analysis
|
| 99 |
+
|
| 100 |
+
WAT and adipocytes homogenates were prepared with RIPA buffer (150 mm NaCl, 50 mm Tris-HCl, 0.5% sodium deoxycholate, 1% Triton X-100, 0.1% SDS) containing freshly added protease and phosphatase inhibitors. The homogenates were resolved by SDS-PAGE, and then transferred to PVDF membrane. The membrane was blocked with 5% nonfat dry milk or 2% BSA in TBST, and then immunoblotted with the primary antibodies at 4°C overnight, followed by incubation with the secondary antibodies for 1 hour at room temperature. The sources and dilutions of antibodies are listed in table S2. GAPDH and β-Actin were used as the loading control in the individual experiment.
|
| 101 |
+
|
| 102 |
+
Co-immunoprecipitation (Co-IP)
|
| 103 |
+
|
| 104 |
+
Cells transfected with BAP31-Flag and/or Pin1-HA constructs were lysed with IP lysis buffer (20 mM Tris (pH 7.5), 150 mM NaCl, 1% Triton X-100) with protease inhibitor cocktail (Beyotime Biotechnology). After being centrifuged at 12,000 g, the supernatants were incubated with anti-Flag and/or anti-HA antibodies overnight at 4°C with slow shaking. The protein A/G beads were added and incubated at 4°C for 3-4 hours. The beads were washed with IP buffer three times before adding the laemmli loading buffer. Proteins Co-IP were analyzed by immunoblotting analysis.
|
| 105 |
+
|
| 106 |
+
Lipolysis rate measurement
|
| 107 |
+
|
| 108 |
+
WT and BAP31-ASKO mice (12-week-old) were injected with CL316,243 (0.1 mg/kg) intraperitoneally. One hour later, mice were sacrificed under anesthesia and sera were extracted. Serum FFA and glycerol were determined to illustrate the lipolysis rate 24. Or the epididymal and subcutaneous fat pads were dissected and minced into small pieces of about 3 mm, and then were placed in serum-free culture medium (phenol red-free DMEM containing 1 μM of CL316,243 with 1% FA-free BSA). Two hundred microliters medium was collected at 0, 1, 2, and 3 hours after CL316,243 treatment. FFA and glycerol released in the medium were measured then.
|
| 109 |
+
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| 110 |
+
The primary mature adipocytes were isolated from epididymal and subcutaneous fat pads of WT and BAP31-ASKO (12-week-old) mice as previously described 25; and then were incubated with phenol red-free and serum-free DMEM containing 1% FA-free BSA, in the presence or absence of 10 nM of isoproterenol (ISO). FFA and glycerol released into the medium were measured at 0, 1, 2, 3, and 5 hours after ISO administration.
|
| 111 |
+
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| 112 |
+
Lipidomics analysis
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| 113 |
+
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| 114 |
+
Lipids in epididymal WAT were extracted following a modified Bligh and Dyer's method described as before 26. Lipid profiles were measured using a high-coverage targeted lipidomic approach constructed principally on HPLCMRM, with the modification of the selection of internal standards used for quantification. The lipidomic analyses were performed using an Exion LC-system coupled with a QTRAP 6500 PLUS system (Sciex). The content of the individual lipids from various classes were quantitated relative to the respective internal standard.
|
| 115 |
+
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| 116 |
+
Statistical analysis
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| 117 |
+
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| 118 |
+
Data were presented as mean ± SE. The statistical analysis was plotted using Graphpad Prism 5.0. One-way ANOVA followed by Tukey post hoc test was used to determine the significance of the individual differences. All statistical tests with p < 0.05 were considered as significant.
|
| 119 |
+
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| 120 |
+
Results
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| 121 |
+
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| 122 |
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BAP31-deficiency reduced lipid accumulation in white adipose tissue, but induced adipocyte expansion in mice
|
| 123 |
+
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| 124 |
+
BAP31 mRNA and protein levels were reduced in WAT of diet-induced obese mice (Figure 1A and 1B), and also decreased in leptin deficiency-induced obese mice (Figure 1C), pointing the reasonable roles involved in obesity. Therefore, mice with targeted deficiency in adipocytes were generated. BAP31 expression was depleted in white and brown adipose tissues (Figure 1D). The conditional knockout mice grow normally as controls. BW curve analysis also shows no significant difference between these two genotypes of mice (Figure 1E and 1F). BAP31-ASKO mice exhibited reduced epididymal, mesenteric, and perirenal WAT mass than WT controls, with no difference in subcutaneous WAT mass at 20- and 50-week-old age, suggesting that BAP31-deficiency inhibited lipid accumulation in WAT (Figure 1G and 1H). No difference in food intake was determined, pointing that the reduced lipid accumulation was not due to energy intake (Figure 1I). Histomorphometric analysis revealed that the adipocytes from BAP31-ASKO mice were bigger than WT controls (Figure 1J). The analysis of adipocyte size frequency confirmed this observation, which showed increased number of hypertrophic adipocytes in BAP31-ASKO mice. The mean size of adipocytes in BAP31-ASKO mice is almost two folds than that of WT controls (Figure 1K), suggesting that BAP31-deficiency induced adipocyte expansion in mice. Liver and BAT weight were increased; no difference in skeletal muscles weight was observed (Table S3).
|
| 125 |
+
|
| 126 |
+
BAP31-dificiency inhibited adipocyte differentiation
|
| 127 |
+
|
| 128 |
+
MEFs were isolated and induced to differentiation to adipocytes. Less staining of mature adipocytes was determined in BAP31-ASKO MEFs than WT controls (Figure 2A). Cellular TAG was reduced due to the reduced adipogenesis (Figure 2B). The transcriptional levels of the adipogenic markers, including CCAAT enhancer-binding protein alpha (Cebpα), Cebpβ, Peroxisome proliferator-activated receptor γ (Pparγ), Fatty acid binding protein 4 (Fabp4), Lipoprotein lipase (Lpl), and Adiponectin were decreased (Figure 2C). Immunoblotting analysis also reported decreased protein levels of Cebpα, Pparγ, Fabp4, and Fatty acid synthase (Fas) in BAP31-ASKO MEFs, demonstrating that BAP31-deficiency prevented MEFs differentiation to adipocytes (Figure 2D). In addition, BAP31flox/- or BAP31flox/flox MEFs infected with Ad-LacZ and Ad-Cre were induced to differentiation to adipocytes, which reported decreased mature adipocyte staining in Ad-Cre MEFs (Figure 2E). TAG content was decreased again (Figure 2F). The transcription and protein levels of adipogenic markers were both decreased in Ad-Cre MEFs (Figure 2G and Figure S1). Furthermore, the adipogenic markers in WAT were determined and displayed reduced expression pattern in BAP31-ASKO mice (Figure 2H), demonstrating that BAP31-deficiency inhibited the differentiation to adipocytes, and contributed to reducing lipid accumulation in WAT. After induction to differentiation to adipocytes, the cell numbers increased by 2-3 folds in control 3T3-L1 preadipocytes, but were reduced in sh-BAP31 cells, demonstrating that BAP31-deficiency inhibited the mitotic clonal expansion (MCE) and impaired the adipogenesis process (Figure 2I), which is in concordance with the reduced Cyclin D1 expression (Figure 2J).
|
| 129 |
+
|
| 130 |
+
Lipid profiling
|
| 131 |
+
|
| 132 |
+
A total of 485 lipid species spanning 21 individual lipid classes was identified and quantitated in WAT lipidome. No significant difference in the total molar amount of TAG was determined (Figure 3A). However, TAG with carbon number of 48-53 was decreased, with carbon number of 54-60 was increased in BAP31-ASKO mice, suggesting that BAP31-deficiency modulated TAG ratio and facilitated long chain TAG accumulation in WAT (Figure 3B). No difference in DAG was determined (Figure 3A). Total amount of FFA was decreased insignificantly, with FFA22:6 and FFA20:5 were significantly decreased (Figure 3A and 3E). Total amount of phospholipids (PLs) was increased (Figure 3A), including the species of phosphatidylcholines (PC), lyso-PC (LPC), plasmalogen PC (PCp), plasmalogen phosphatidylethanolamines (LPE), phosphatidylinositols (PI), and sulfatides (SL) (Figure 3C). The PC/PE ratio was increased in BAP31-ASKO mice (Figure 3D). Figure 3E and 3F listed the significantly regulated lipid species between WT and BAP31-ASKO mice, suggesting that most PLs were up-regulated due to BAP31-deficiency.
|
| 133 |
+
|
| 134 |
+
BAP31-deficiency reduced adipose tissue lipolysis
|
| 135 |
+
|
| 136 |
+
TAG in WAT was increased in BAP31-ASKO mice, accompanied by decreased FFA content (Figure 4A). We suggested that BAP31-deficiency reduced adipose tissue lipolysis, which leaded to increased TAG accumulation and decreased FFA release in adipocytes. Thus, mice were food deprived and the lipolytic effects were determined. BAP31-deficiency blocked fasting-induced hypoglycemia, reduced TAG content, and repressed serum FFA and glycerol releasing from WAT via lipolysis. No difference in cholesterol was determined (Table 1). The mRNA levels of Adipose triglyceride lipase (Atgl), Hsl, and Monoglyceride lipase (Mgl) were reduced in BAP31-ASKO-Fasted mice (Figure 4B), as well as PKA signaling activation, p-Hsl (563) phosphorylation and Atgl expression, pointing that BAP31-deficiency attenuated fasting-induced lipolysis (Figure 4C). This attenuation was not observed in liver tissues, demonstrating that the reduced lipolysis is due to the specific depletion of BAP31 in adipocytes (Figure S2). It was noted that BAP31-deficiency increased Plin1 expression at fed and fasted status (Figure 4C). Again, mice were treated with β3-adrenergic receptor agonist. BAP31-deficiency increased blood glucose, but decreased FFA and glycerol release from WAT. No difference in TAG was determined (Table 2). Consistently, p-PKA and p-Hsl (563) were reduced, along with reduced Atgl expression, suggesting that BAP31-deficiency reduced CL316,243-induced lipolysis in mice (Figure 4D).
|
| 137 |
+
|
| 138 |
+
Next, the lipolytic effects were explored from primary adipocytes. The release of FFA and glycerol increased along with ISO-treatment, but was attenuated in BAP31-ASKO adipocytes (Figure 4E). ISO-induced PKA signaling activation was reduced, accompanied by reduced p-Hsl (563) levels, demonstrating that BAP31-deficiency inhibited ISO-induced lipolysis in vitro (Figure 4F). Furthermore, ex vivo lipolysis was performed on epididymal and subcutaneous WAT explants. CL316,243 increased FFA and glycerol release, but the induction was repressed in BAP31-ASKO explants (Figure 4G and 4H). PKA signaling activation was reduced, as well as p-Hsl (563) levels. It was noted that p-Hsl (565) levels, which were phosphorylated by AMPK signaling 27, exhibiting no difference between WT and BAP31-ASKO explants, suggesting that AMPK signaling may not be involved in BAP31 function on lipolysis (Figure 4I). BAP31-deficiency in adipocytes reduced the total lipase activity in epididymal WAT, as well as in quadriceps muscles, but not in serum and liver tissues (Figure S3).
|
| 139 |
+
|
| 140 |
+
BAP31-deficiency caused lipid droplets abnormal growth
|
| 141 |
+
|
| 142 |
+
BAP31 is one of the integral ER membrane proteins and LDs are ER-derived neutral lipid storage organelles. We suggested that BAP31 localizes on LDs surface via ER budding, and regulates TAG hydrolysis and LD size. Oleic acid (OA) increased lipid accumulation in 3T3-L1 preadipocytes and induced LDs enlargement (Figure 5A and 5B). In accompaniment with OA treatment, Plin1 was increased significantly in 3T3-L1 preadipocytes. On the contrary, BAP31 was reduced via a time- and dosage-dependent pattern, exhibiting a negative correlation with Plin1 expression (Figure 5C). BAP31 colocalizes with LDs, pointing the possible roles in LDs growth (Figure 5D). 3T3-L1 preadipocytes depleted with BAP31 were induced with OA and LD size was determined. The results demonstrated that BAP31-deficiency increased LD size and promoted LDs abnormal growth (Figure 5E). In control preadipocytes, a large number of small LDs accumulated in the presence of OA. However, in BAP31-deficient preadipocytes, reduced a few small LDs were observed, and these LDs expanded rapidly grew into supersized ones (Figure 5F and 5G). Cellular TAG was increased in BAP31-deficient preadipocytes, attributing to the reduced TAG hydrolysis (Figure 5H).
|
| 143 |
+
|
| 144 |
+
BAP31 increased lipolysis and rescued lipid droplets abnormal growth via modulating Perilipin1 expression
|
| 145 |
+
|
| 146 |
+
When BAP31 was reintroduced into BAP31-deficient preadipocytes, LD size was decreased and the number of visible LDs were decreased, showing a restoration of normal LD morphology (Figure 6A and 6B). In accordance with the morphological observation, the reduced PKA signaling activation was restored. Increased p-PKA and p-Hsl phosphorylation levels, and increased Atgl expression were determined due to enhanced BAP31 expression, promoted ISO-induced TAG hydrolysis, thus modulated the supersized LDs to normal morphology (Figure 6C and 6D). OA increased Plin1 protein stability and/or protein levels, stabilized LD dynamics and promoted the formation of supersized LDs (Figure 6E). BAP31-deficiency increased Plin1 protein levels (Figure 4B and 6E). Whether BAP31 regulates LD size via modulating Plin1 protein levels and/or protein stability in adipocytes? Gene silencing reduced BAP31 expression dosage-dependently, which induced Plin1 expression and exhibited a negative correlation consequently (Figure 6F and 5C). Immunofluorescence assay confirmed this observation, displaying enhanced Plin1 staining due to a transient deficiency of BAP31 expression (Figure 6G). Enhanced Plin1 expression repressed ISO-induced PKA signaling activation and reduced the lipolysis, illustrating the possibility of that BAP31 regulated LDs growth and LDs degradation via modulating Plin1 protein (Figure 6H). Thus, the interaction of BAP31 and Plin1 were determined. BAP31 colocalizes with Plin1 on LDs surface (Figure 6I). Co-IP assay further demonstrated that BAP31 and Plin1 interacts with each other (Figure 6J). A series of BAP31 mutants with Flag-tag were exogenously expressed together with HA-tagged Plin1 in 3T3-L1 preadipocytes. Cell lysates were then immunoprecipitated using an antibody against HA and analyzed by immunoblotting analysis. The truncated BAP31 containing amino acids 123-245 (123-245-Flag) and 165-245 (165-245-Flag) interacted with Plin1, whereas the mutants which lack the C-terminal cytoplasmic portion of the protein (1-165-Flag and 1-124-Flag) completed abolished the interaction (Figure 6K), suggested that amino acids 165-245 of BAP31 are necessary for its interaction with Plin1.
|
| 147 |
+
|
| 148 |
+
BAP31 regulated Perilipin1 expression via modulating the proteasomal degradation
|
| 149 |
+
|
| 150 |
+
3T3-L1 preadipocytes were transfected with Plin1-HA and BAP31-Flag plasmids, and then were treated with the protein synthesis inhibitor of cycloheximide (CHX), demonstrating that BAP31 leaded to the instability of Plin1 protein (Figure 7A). Therefore, cells were treated with CHX in a time-course experiment. Plin1 protein levels were decreased and reached to ~50% at 2 hours after CHX treatment, implying protein degradation involved in Plin1 turnover (Figure 7B). BAP31 was depleted in 3T3-L1 preadipocytes, which induced Plin1 expression and exhibited even higher levels than that with the presence of CHX, suggesting that BAP31-deficiency inhibited the protein degradation of Plin1 (Figure 7C). MG132, the proteasomal inhibitor, time-dependently increased Plin1 expression (Figure 7D). BAP31-deficiency enhanced the increase, pointing the possibility of that knockdown of BAP31 attenuated the proteasomal degradation of Plin1 (Figure 7E). To confirm the proteasomal protein degradation involved in Plin1 turnover, 3T3-L1 preadipocytes were transfected with Plin1-HA, and then were treated with CHX, followed by incubation with the lysosomal inhibitor of chloroquine (CQ) or MG132. The results demonstrated that MG132, instead of CQ, blocked BAP31-deificiency induced Plin1 increase (Figure 7F). In contrast, BAP31 reduced Plin1 expression, MG132 not CQ repressed the reduction of Plin1 expression (Figure 7G), suggesting that the proteasomal degradation, not the lysosomal degradation involved in BAP31-mediated Plin1 turnover. MG132 inhibits the proteolytic activity of the 26S proteasome complex, results in the accumulation of ubiquitin-conjugated proteins, but was reduced in BAP31-deficient preadipocytes, illustrating that BAP31 is needed and essential for the proteolytic activity of the proteasome. (Figure 7H). Co-IP assay further demonstrated that MG132 increased the protein levels of ubiquitinated Plin1-HA, but was totally blocked in sh-BAP31 preadipocytes, suggesting that BAP31-deficiency inhibited Plin1 ubiquitination and decreased the proteasomal degradation (Figure 7I).
|
| 151 |
+
|
| 152 |
+
BAP31-deficiency reduced HFD-induced obesity, but attenuated insulin signaling and increased the inflammatory response in mice
|
| 153 |
+
|
| 154 |
+
Upon HFD-feeding, BAP31-ASKO mice exhibited reduced BW increase than WT controls (Figure 8A). The epididymal pads were smaller, along with reduced Epi, Mes and total WAT mass, suggesting that BAP31-deficiency prevented diet-induced lipid accumulation in WAT (Figure 8B and 8C). More bigger adipocytes were observed in BAP31-ASKO mice. The analysis of adipocyte size confirmed this observation, demonstrating that BAP31-deficiency promoted adipocyte expansion, keeping consistency with the results from chow diet (Figure 8E and 8G). BAT and liver weight were increased in BAP31-ASKO mice (Figure 8D), accompanied by enhanced ectopic lipid accumulation (Figure 8E and 8F). BAP31-deficiency reduced the adipogenic markers of Cebpα, Cebpβ, Pparγ, Fabp4, Lpl, Adiponectin expression, and induced Monocyte chemotactic protein-1 (Mcp1) and C-C motif chemokine ligand 3 (Ccl3) expression (Figure 8H). BAP31-ASKO mice exhibited higher glucose at 0 and 15 minutes, and insignificant higher at 120 minutes (p=0.07) upon glucose challenge (Figure 8I). For the ITT assay, enhanced glucose was determined at 30, 60, and 120 minutes, with insignificant increase at 15 minutes (p=0.07) (Figure 8J), demonstrating that BAP31-deficiency in adipocytes reduced insulin signaling in mice. The phosphorylation levels of p-PKA and p-Hsl were decreased, along with decreased Hsl and Atgl protein levels in WAT of BAP31-ASKO mice upon HFD-feeding. Plin1 was increased, and no difference of Caveolin-1 (Cav-1) was determined (Figure 8K), pointing that BAP31 effects on Plin1 protein regulation are specific. The protein levels of Glucose-regulated protein 78 (Grp78), C/EBP homologous protein (Chop), Protein disulfide isomerase (PDI), and p-JNK, Mcp1 were increased in BAP31-ASKO mice, suggesting enhanced ER stress and promoted pro-inflammatory response in WAT (Figure 8L).
|
| 155 |
+
|
| 156 |
+
Discussion
|
| 157 |
+
|
| 158 |
+
Currently we reported the novel roles of BAP31 in regulating lipid metabolism in adipocytes. BAP31-deficiency inhibited MCE, reduced adipogenesis, and prevented lipid accumulation in WAT. Also, BAP31 collaborates with Plin1 by the C-terminal cytoplasmic portion and regulates Plin1 protein levels via modulating the proteasomal degradation. BAP31-deficiency blocked Plin1 degradation and increased Plin1 expression on LDs surface, attenuated LDs degradation and promoted the formation of supersized LDs. Furtherly, BAP31-deficiency inhibited PKA-signaling activation and the lipolysis process, resulted in adipocyte expansion, which promoted inflammation in WAT and impaired insulin signaling in mice (Summary in Figure 9). Based on our knowledge, this is the first report illustrating BAP31 function in regulating adipocyte differentiation, as well as LDs biogenesis and degradation in adipocytes, maintaining LDs homeostasis via modulating the LD-associated protein proteasomal degradation.
|
| 159 |
+
|
| 160 |
+
BAP31-deficiency promoted Plin1 protein levels on LDs surface, and played the protective role against agonist-induced lipolysis. The current study reported the novel roles of BAP31 in regulating LD-associated protein degradation and modulating LDs growth, strengthening the biological function of BAP31 in lipid metabolism in adipocytes. BAP31 locates on LDs surface and regulated lipid metabolism via LD catabolism, serving as one of LD-associated proteins in adipocytes 11. BAP31 accumulates at the juxtanuclear region of a few cells, interacted with Tom40 and formed the mitochondrial complex I, facilitated the translocation of NDUFS4, representing a mechanism for the ER-mitochondria communication 28. We suggested that BAP31 may undergo regulated translocation from the ER to the LDs, raising the theoretical possibility that traffic between the phospholipid monolayer of the LDs and the ER. Lipolysis is mediated by the activation of a PKA-mediated pathway, promotes TAG hydrolysis on LDs surface by the sequential activation of Atgl, Hsl, and Mgl lipases 29. BAP31-deficiency reduced PKA signaling activation, decreased Atgl expression, accompanied by reduced Hsl phosphorylation, eventually reduced the lipolysis rate in adipocytes (Figure 4). Reduced lipolysis leaded to enhanced lipid accumulation and TAG content in adipocytes, resulted in the formation of supersized LDs, which is in agreement with the observation of increased TAG content in OA-induced sh-BAP31 preadipocytes (Figure 5H), also keeping consistency with the previous study of that BAP31-deficiency in hepatocytes promoted hepatic lipid accumulation and worsened insulin resistance 21. LDs are emerging as dynamic cellular organelles and play a crucial role in lipid and membrane homeostasis. LDs size and protein compositions vary between cell type and the underlying conditions. Upon lipid overloading, cells can respond to lipids storage pressure by either increasing the number and/or the volume of the LDs. Supersized LDs provided the most efficient ways for fat storage that is necessary and beneficial under lipid overloading or lipotoxic conditions. Enhanced Plin1 leaded to the formation of large unilocular LDs that are a unique of WAT. Nascent LDs in adipocytes are coated with Plin3 and Plin4, and replaced by Plin1 on the surface of giant and unilocular LDs, which facilitates the formation of giant LDs 30, suggesting the possibility of the formation of supersized LDs with enhanced Plin1 expression in BAP31 deficient adipocytes.
|
| 161 |
+
|
| 162 |
+
BAP31 was reported playing an integral role in the recognition of misfolded protein by triggering ER-associated degradation, and considered as a component of the ER quality control compartment 31, recognized the newly synthesized CFTRΔF508 and promoted the retro-translocation from the ER and the degradation by the 26S proteasome system 16, pointing the key roles of BAP31 in regulating protein stability and the related protein degradation. Two independent groups have proposed different domains of BAP31 to be critical for the interaction. Annaert et al. demonstrated that the three transmembrane regions of BAP31 are required for the binding with cellubrevin 32. Ducret et al. reported that the cytoplasmic domain of BAP31 is responsible for the interaction with γ-actin 33. BAP31 translocates from the ER to the LDs, and interacts with Plin1 on the LDs surface. Immunoprecipitation assay demonstrated that the C-terminal cytoplasmic portion is essential and critical for the interaction (Figure 6). This specific interaction of Plin1 and BAP31 is supported by the presence of a coiled-coil region of BAP31, in which α-helices intertwine to form a superhelical bundles and has been considered as the simplest of all protein interaction motifs 34, and may facilitate the controlling of Plin1 turnover via the proteasomal protein degradation. Plin1 protein levels on LDs surface are dynamically regulated, via modulating the ubiquitination-proteasome pathway 9. Given the roles of Plin1 in protecting LDs lipids from lipase hydrolysis, it is reasonable to anticipate that the assembly of Plin1 in macrophages might reduce lipolysis and hence increase lipid retention in ApoE-deficiency plaques 35. Reduced BAP31 expression repressed the proteasomal degradation of Plin1 and leaded to Plin1 accumulation on LDs surface, blocked agonist-induced PKA signaling activation and the lipolysis in adipocytes. This study shows the essential roles of BAP31 in controlling the homeostasis of LD-associated surface proteins via the proteasomal degradation system, suggesting the important function of BAP31 in regulating protein quality control and LD metabolism.
|
| 163 |
+
|
| 164 |
+
BAP31-deficiency reduced adipogenesis and lipid accumulation in WAT, even though the induced adipocytes expansion and enhanced cellular TAG accumulation due to reduced TAG hydrolysis on LDs surface, suggesting that the effects of reduced adipogenesis with reduced lipid accumulation in WAT overwhelmed the consequence of increased TAG accumulation due to reduced lipolysis rate within adipocytes. Two in vitro MEFs cell culture models demonstrated that BAP31-deficiency repressed the expression of adipogenic markers, and prevented the differentiation to adipocytes. When induced to differentiation, growth arrested preadipocytes synchronously reenter the cell cycle and undergo the required process of MCE, followed by the expression of genes aiming to adipocyte phenotype, including Cyclin D1, Cebpβ, cdk2-cyclin E, and so on 36, 37. BAP31-deficiency inhibited Cyclin D1 expression and reduced MCE in 3T3-L1 preadipocytes, consequently attenuated the process of adipogenesis. cAMP-PKA signaling is important both in adipogenesis and lipolysis in WAT, and cAMP-dependent PKA activation promotes adipogenesis 38. PKA signaling was decreased after BAP31 depletion, contributed to reducing adipocyte differentiation and lipid accumulation in WAT of BAP31-ASKO mice. Reduced PKA signaling activation decreased TAG hydrolysis and reduced FAs release from the adipocytes. The reduced FAs content furtherly repressed Pparγ signaling and inhibited the adipogenesis process 39. We failed to detect the direct evidence of BAP31 regulation on Cebpα and Pparγ transcription. Whether BAP31 traffics into the nuclear or fuses with the nuclear membrane via LDs transportation or fusion, and then regulates the adipogenic marker transcription by direct binding to the promoter element will be interested in future studies 3, 40. Reduced adipogenesis prevented excessive lipids incorporating into WAT, leaded to ectopic lipid accumulation in the liver and BAT, and decreased insulin signaling transduction in mice. Obesity or high-lipid loading decreased BAP31 expression, which prevented the adipogenesis process and lipid accumulation in WAT, worsening obesity-induced lipid dysfunction. BAP31-deficiency reduces lipolysis and increases LDs expansion in adipocytes, even worsens insulin signaling, forming a vicious circle in adipocytes. We currently reported the dual roles of BAP31 in lipid metabolism via modulating adipogenesis and lipolysis in adipocytes, pointing the importance of proper expression of BAP31 in maintaining lipid homeostasis in WAT.
|
| 165 |
+
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| 166 |
+
LDs are phylogenetically conserved organelles, with a unique physical structure: consisting of a hydrophobic core of neutral lipids, and capsuling by a phospholipid monolayer that is decorated by a diverse proteome 41. Different LDs in a cell contain different protein composition 42, and have different rates of acquiring TAG. Change in lipid composition of LDs has been implicated in numerous physiological and pathophysiological functions, including cancer 43, obesity, fatty liver, and neurodegeneration disorders 44. Exposure of phosphatidylserine (PS) on the plasma membrane is widely observed during cellular apoptosis, contributes to the recognition and subsequent removal of apoptotic bodies by phagocytes, and providing a binding site for the annexin V for apoptotic cell detecting 45. BAP31-deficiency increased PS content, as well as PL, LPC, PCp, and PI content in WAT of BAP31-ASKO mice (Figure 3). The function of BAP31 on membrane PS composition and the related apoptosis induction should be warranted in future studies. BAP31-deficiency promoted long chain PUFA-enriched TAG content in WAT (Figure 3), and is consistent with the previous observations from obese murine model and human species 46. Also, BAP31-deficiency increased PC/PE ratio. Obesity is associated with increased de novo PC synthesis, promoted PC turnover, and induced pro-inflammatory activation of adipose tissue macrophages 47. We determined increased expression of macrophage marker of Mcp1 in BAP31-ASKO mice upon HFD-feeding, suggesting that the increased PC/PE ratio may be involved in the increased pro-inflammation in WAT. BAP31-deficiency promoted most PLs content in WAT of mice, which are mostly localized in cell membrane. The composition is highly associated with molecular transportation, apoptosis, and signaling transduction 48, suggesting that BAP31 may modulate PLs composition and subsequently change the related biological reactions.
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| 167 |
+
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| 168 |
+
Overall, we reported the dual role of BAP31 in regulating lipid metabolism. BAP31-deficiency inhibited lipid accumulation via suppressing adipogenesis in WAT; prevented Plin1 degradation and promoted LDs abnormal growth, which reduced the lipolysis process and leaded to adipocyte expansion in mice.
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| 169 |
+
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| 170 |
+
Supplementary Material
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| 171 |
+
|
| 172 |
+
Supplementary figures and tables.
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| 173 |
+
|
| 174 |
+
Click here for additional data file.
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| 175 |
+
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| 176 |
+
This work was supported by National Natural Science Foundation of China (grants 81974120 and 81570788 to J.X.; grant 32072208 to L.L.).
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| 177 |
+
|
| 178 |
+
Author Contributions
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| 179 |
+
|
| 180 |
+
X.W. and L.L. devised the research questions, formulated the research plan, researched the data, and wrote/reviewed/edited the manuscript. X.W., L.L., J.Z., Y.H., and J.L. devised the research questions and formulated the research plan. W.Z., L.X., and Y.Y. contributed to discussion, and reviewed/edited the manuscript. J.P. contributed to discussion. All authors drafted or revised the article and approved the final version of the manuscript. J.X. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
|
| 181 |
+
|
| 182 |
+
Abbreviations
|
| 183 |
+
|
| 184 |
+
BAP31 B-cell receptor-associated protein 31
|
| 185 |
+
|
| 186 |
+
BW body weight
|
| 187 |
+
|
| 188 |
+
Cebpα CCAAT enhancer-binding protein alpha
|
| 189 |
+
|
| 190 |
+
Chop C/EBP homologous protein
|
| 191 |
+
|
| 192 |
+
CHX cycloheximide
|
| 193 |
+
|
| 194 |
+
CQ chloroquine
|
| 195 |
+
|
| 196 |
+
Co-IP Co-immunoprecipitation
|
| 197 |
+
|
| 198 |
+
ER endoplasmic reticulum
|
| 199 |
+
|
| 200 |
+
Fabp4 fatty acid binding protein 4
|
| 201 |
+
|
| 202 |
+
Fas fatty acid synthase
|
| 203 |
+
|
| 204 |
+
FFA free-fatty acids
|
| 205 |
+
|
| 206 |
+
Fsp27 fat-specific protein 27
|
| 207 |
+
|
| 208 |
+
Grp78 glucose-regulated protein 78
|
| 209 |
+
|
| 210 |
+
H/E hematoxylin and eosin
|
| 211 |
+
|
| 212 |
+
Hsl hormone-sensitive lipase
|
| 213 |
+
|
| 214 |
+
ISO isoproterenol
|
| 215 |
+
|
| 216 |
+
LDs lipid droplets
|
| 217 |
+
|
| 218 |
+
Lpl lipoprotein lipase
|
| 219 |
+
|
| 220 |
+
MEFs mouse embryonic fibroblasts
|
| 221 |
+
|
| 222 |
+
Mgl monoglyceride lipase
|
| 223 |
+
|
| 224 |
+
OA oleic acid
|
| 225 |
+
|
| 226 |
+
PC phosphatidylcholines
|
| 227 |
+
|
| 228 |
+
PDI protein disulfide isomerase
|
| 229 |
+
|
| 230 |
+
PE phosphatidylethanolamine
|
| 231 |
+
|
| 232 |
+
PI phosphatidylinositols
|
| 233 |
+
|
| 234 |
+
Plin1 perilipin1
|
| 235 |
+
|
| 236 |
+
Pparγ peroxisome proliferator-activated receptor γ
|
| 237 |
+
|
| 238 |
+
PS phosphatidylserine
|
| 239 |
+
|
| 240 |
+
TAG triglycerides
|
| 241 |
+
|
| 242 |
+
WAT white adipose tissue
|
| 243 |
+
|
| 244 |
+
Figure 1 BAP31-deficiency reduced lipid accumulation in white adipose tissue, but induced adipocyte expansion in mice. (A and B) BAP31 mRNA and protein levels were decreased in WAT of HFD-induced obese mice. *p<0.05, compared to SD mice. (C) BAP31 protein levels were decreased in WAT of ob/ob mice. (D) BAP31 expression was depleted in adipocyte-specific BAP31 conditional knockout mice (BAP31-ASKO). sWAT: subcutaneous WAT. mWAT: mesenteric WAT. (E) The photos of WT and BAP31-ASKO mice. (F) The body weight was comparable between WT and BAP31-ASKO mice. n=9. (G) The representative pictures of epididymal WAT. (H) The organ indexes of epididymal WAT (Epi), mesenteric WAT (Mes), perirenal WAT (Peri), and subcutaneous WAT (Sub) from 20-week-old (n=8) and 50-week-old mice (n=8-10). (I) Food intake is comparable between WT and BAP31-ASKO mice. n=8. (J) The representative images of H/E staining of epididymal WAT. Scale bar=50 μm. n=4. (K) The frequency of adipocytes and the mean adipocyte size in epididymal WAT. *p<0.05, ***p<0.001, compared to WT mice.
|
| 245 |
+
|
| 246 |
+
Figure 2 BAP31-deficiency inhibited adipocyte differentiation. (A) The representative images of Nile red staining of MEFs induced to differentiation to adipocytes. Scale bar=50 μm. (B) TAG content in differentiated MEFs. MEFs were isolated and induced to differentiation to adipocytes. The mature adipocytes were stained with Nile red at day 3 (D3), day 5 (D5), and day 7 (D7) post differentiation. Lipids were extracted from differentiated MEFs at day 7 post differentiation and TAG content was quantified. **p<0.01, compared to WT MEFs. (C) The transcriptional levels of adipogenic markers of Cebpα, Cebpβ, Pparγ, Fabp4, Lpl, and Adiponectin were reduced in BAP31-ASKO MEFs than WT controls. *p<0.05, compared to WT MEFs. (D) The protein levels of Fas, Cebpα, Pparγ, Fabp4, and BAP31 were determined in WT and BAP31-ASKO MEFs. (E) The representative images of oil red O staining of MEFs induced to differentiation to adipocytes. MEFs isolated from BAP31flox/- or BAP31flox/flox embryos were infected with adenovirus of Ad-LacZ and Ad-Cre to deplete BAP31 expression, and then were induced to differentiation to adipocytes. Cells were stained with oil red O at day 8 post differentiation. Scale bar=50 μm. (F) Lipids were extracted from differentiated MEFs and TAG content was measured. *p<0.05, compared to Ad-LacZ MEFs. (G) The protein levels of Cebpα, Pparγ, Fabp4, and BAP31 were determined in differentiated MEFs infected with Ad-LacZ and Ad-Cre adenovirus. (H) The protein levels of Cebpα, Pparγ, Fabp4, Adiponectin, and BAP31 were determined in WAT of WT and BAP31-ASKO mice. (I) BAP31-deficiency inhibited mitotic clonal expansion during 3T3-L1 preadipocytes differentiation induction process. 3T3-L1 preadipocytes differentiation was induced with the standard induction protocol. The cell number was determined at the indicated time after the induction to differentiation. *p<0.05, compared to sh-Ctrl. (J) The transcriptional levels of Cyclin D1 were determined in 3T3-L1 preadipocytes induced to differentiation to adipocytes. *p<0.05, compared to sh-Ctrl.
|
| 247 |
+
|
| 248 |
+
Figure 3 The lipidomic analysis of epididymal white adipose tissue. (A) The molar amount of TAG, DAG, FFA, and PLs was determined from epididymal white adipose tissue. (B) BAP31-deficiency promoted long chain PUFA-enriched TAG accumulation in white adipose tissue. (C) The species of PC, LPC, PCp, PE, LPE, PEp, PI, PS, SM, CL, and PA, LPA, LPI, LPS, PG, SL, BMP, GM3 were determined. (D) The ratio of PC/PE was increased in BAP31-ASKO mice. (E and F) The heatmap displaying statistically significantly regulated lipid molecular species between WT and BAP31-ASKO mice. *p<0.05, **p<0.01, compared to WT mice.
|
| 249 |
+
|
| 250 |
+
Figure 4 BAP31-deficiency reduced adipose tissue lipolysis. (A) TAG and FFA content in subcutaneous WAT of mice. n=6. *p<0.05, compared to WT mice. (B and C) BAP31-deficiency attenuated fasting response in mice. WT and BAP31-ASKO mice were food deprived for 24 hours. The epididymal WAT was dissected for future experiments. The mRNA levels of the lipase of Atgl, Hsl, and Mgl were reduced. n=6-7. #p<0.05, compared to WT-Fasted mice (B). The protein levels of lipolysis-related genes of p-PKA, PKA, p-Hsl (563), Hsl, Atgl, Plin1, and BAP31 were determined (C). (D) BAP31-deficiency reduced β3-adrenoceptor agonist-induced lipolysis in vivo. WT and BAP31-ASKO mice were treated with CL316,243 (0.1 mg/kg), and then the epididymal WAT were dissected. The protein levels of p-PKA, PKA, p-Hsl (563), Hsl, Atgl, and BAP31 were determined. (E and F) BAP31-deficiency reduced ISO-induced lipolysis in vitro. The primary mature adipocytes were isolated and incubated with ISO (10 nM) for 5 hours. FFA and glycerol released into the medium were measured (E). The protein levels of p-PKA, PKA, p-Hsl (563), Hsl, and BAP31 were determined (F). (G-I) BAP31-deficiency reduced β3-adrenoceptor agonist-induced lipolysis ex vivo. The epididymal and subcutaneous WAT were dissected and minced into small pieces, followed by incubation with CL316,243 (1 μM) for 3 hours. FFA and glycerol released into the medium from epididymal (G) and subcutaneous WAT (H) were measured. The protein levels of p-PKA, PKA, p-Hsl (563), p-Hsl (565), Hsl, Atgl, and BAP31 were determined in white adipose explants (I). *p<0.05, compared to WT mice.
|
| 251 |
+
|
| 252 |
+
Figure 5 BAP31-deficiency caused lipid droplets abnormal growth. (A and B) Oleic acid increased LD size in 3T3-L1 preadipocytes. 3T3-L1 preadipocytes were treated with oleic acid (300 μM) for 48 hours. LDs were visualized via Nile red staining (A). The diameter of the largest LDs was analyzed (B). ***p<0.001, compared to vehicle control. (C) Oleic acid reduced BAP31 protein levels and induced Plin1 protein levels in 3T3-L1 preadipocytes. 3T3-L1 preadipocytes were treated with 300 μM of oleic acid for 0, 12, 24, 48 hours, or with 0, 100, 300, 500 μM of oleic acid for 24 hours. (D) BAP31 colocalizes with LDs in 3T3-L1 preadipocytes. 3T3-L1 preadipocytes cultured on coverslips were treated with oleic acid (300 μM, 48 hours), then stained with anti-BAP31 antibody (green), Nile red for lipid droplets (red), and DAPI for nucleus (blue). Scale bar=15 μm. (E-H) BAP31-deficiency increased LD size and lipid accumulation in 3T3-L1 preadipocytes. The stable cell line of BAP31-deficiency (sh-BAP31) and control (sh-Ctrl) were treated with 300 μM of oleic acid for 48 hours, then stained with Nile red for LDs and visualized by confocal microscope. BAP31-deficiency alters the morphology in 3T3-L1 preadipocytes. Scale bar=15 μm (E). Histogram showing the mean number of LDs per cell in each diameter in E (F). BAP31-deficiency increased the diameter of the largest LDs in 3T3-L1 preadipocytes (G). BAP31-deficiency increased TAG content in 3T3-L1 preadipocytes (H). *p<0.05, ***p<0.001, compared to Sh-Ctrl.
|
| 253 |
+
|
| 254 |
+
Figure 6 BAP31 increased lipolysis and rescued lipid droplets abnormal growth via modulating Perilipin1 expression. (A) Over-expression of BAP31 rescued the induction of LD expansion due to BAP31-deficiency. (B) Histogram showing the mean LDs number in each diameter. **p<0.01 and ***p<0.001, compared to sh-Ctrl. ###p<0.001 compared to sh-BAP31. (C) The protein levels of lipolysis-related genes of p-PKA, PKA, p-Hsl (563), Hsl, and Atgl were determined. (D) Over-expression of BAP31 increased ISO-induced lipolysis. 3T3-L1 preadipocytes transfected with BAP31-Flag were incubated with ISO (10 μM) for 24 hours, then the protein levels of p-PKA, PKA, p-Hsl (563), Hsl, and Atgl were determined. (E) BAP31-deficiency promoted Plin1 protein levels in oleic acid-treated 3T3-L1 preadipocytes. (F) Reduced BAP31 expression resulted in enhanced Plin1 protein levels. 3T3-L1 preadipocytes were infected with different titer of lentivirus targeted with BAP31 for 72 hours. The protein levels of BAP31 and Plin1 were determined then. (G) BAP31-deficiency increased Plin1 fluorescence intensity. 3T3-L1 preadipocytes cultured on coverslips were transfected with si-Ctrl and si-BAP31 for 72 hours, and then were fixed and immunostained with anti-BAP31 (green), anti-Plin1 (red), and DAPI (blue). The relative fluorescence intensity was calculated. Scale bar=10 μm. *p<0.05 compared to Si-Ctrl. (H) Enforced expression of Plin1 repressed ISO-induced PKA signaling activation. 3T3-L1 preadipocytes transfected with Plin1-HA or vector were incubated with ISO (10 μM) for 4 hours. The cells were lysed with RIPA buffer and the protein levels of p-PKA, PKA, p-Hsl (563), Hsl, and Atgl were determined. (I) BAP31 colocalizes with Plin1 in 3T3-L1 preadipocytes. 3T3-L1 preadipocytes cultured on coverslips were immunostained by anti-BAP31 (green), anti-Plin1 (red), and DAPI (blue). Scale bar=10 μm. (J) Co-IP demonstrated the interaction of BAP31 and Plin1 in 3T3-L1 preadipocytes. (K) Mapping interaction domains in BAP31 and Plin1. A series of BAP31 mutants with Flag-tag (T1, T2, T3, and T4) were co-transfected with Plin1-HA in 3T3-L1 preadipocytes. Protein extracts were immunoprecipitated with an anti-HA antibody. Immunoprecipitants were analyzed by immunoblotting analysis with an anti-Flag antibody. FL: full length. Ve: vector.
|
| 255 |
+
|
| 256 |
+
Figure 7 BAP31 regulated Perilipin1 expression via modulating the proteasomal degradation. (A) BAP31 promoted Plin1-HA degradation. 3T3-L1 preadipocytes transfected with Plin1-HA and BAP31-Flag plasmids were treated with CHX (10 μg/mL) for 0, 0.5, 1, 2, 4, and 8 hours. Plin1-HA and BAP31-Flag expression were determined using immunoblotting analysis. The degradation curve was calculated based on the protein quantification of Plin1-HA. *p<0.05, compared to Ctrl group. (B) 3T3-L1 preadipocytes were treated with CHX (10 μg/mL) for 0, 0.5, 1, 2, 4, and 8 hours, and then Plin1 protein levels were determined. (C) BAP31-deficiency increased Plin1 protein levels in CHX-treated preadipocytes. (D) 3T3-L1 preadipocytes were treated with 100 nM of MG132 for 0, 0.5, 1, 2, 4, and 8 hours, and then Plin1 protein levels were determined. (E) BAP31-deficiency promoted Plin1 protein levels with or without MG132 treatment. (F) The effects of BAP31-deficiency increasing Plin1-HA expression were prevented by proteasomal inhibition, not via lysosomal inhibition. Sh-Ctrl and sh-BAP31 3T3-L1 preadipocytes were transfected with Plin1-HA plasmids, and then were treated with CHX (10 μg/mL) for 2 hours. After that, cells were treated with chloroquine (CQ, 15 mM) or MG132 (100 nM) for another 2 hours. Immunoblotting analysis was performed with the cell lysates. (G) BAP31 reduced Plin1-HA expression was prevented via proteasomal inhibition, not via lysosomal inhibition. 3T3-L1 preadipocytes were transfected with BAP31-Flag and Plin1-HA plasmids, and then were treated with CHX (10 μg/mL) for 2 hours. After that, cells were treated with chloroquine (15 mM) or MG132 (100 nM) for another 2 hours. (H) BAP31 is needed for the proteasomal degradation. Sh-Ctrl and sh-BAP31 3T3-L1 preadipocytes were treated with MG132 (100 nM) for 2 hours. The ubiquitinated protein was detected using an anti-Ub antibody. (I) BAP31-deficiency repressed Plin1 proteasomal degradation in 3T3-L1 preadipocytes. Sh-Ctrl and sh-BAP31 3T3-L1 preadipocytes were transfected with Plin1-HA plasmids, and then treated with MG132 (100 nM) for 2 hours. Cell lysates were immunoprecipitated with an anti-HA antibody. The ubiquitinated Plin1-HA was detected via immunoblotting analysis.
|
| 257 |
+
|
| 258 |
+
Figure 8 BAP31-deficiency reduced HFD-induced obesity, but attenuated insulin signaling and increased the inflammatory response in mice. (A) BW change was reduced in BAP31-ASKO mice upon HFD-feeding. (B) The representative images of epididymal WAT. (C) The epididymal WAT (Epi), mesenteric WAT (Mes), perirenal WAT (Peri), subcutaneous WAT (Sub), and total WAT mass were recorded in WT and BAP31-ASKO mice with HFD-feeding. (D) The organ indexes of BAT and liver. (E) The representative images of H/E staining of epididymal WAT, BAT, and liver. Scale bar=50 μm. n=4. (F) TAG content of BAT and liver. (G)The frequency of adipocytes in epididymal WAT from (E). (H) The mRNA levels of Cebpα, Cebpβ, Pparγ, Fabp4, Lpl, Adiponectin, Mcp1, and Ccl3 were determined. (I and J) Glucose and insulin tolerance tests were performed with WT and BAP31-ASKO mice. (K and L) The protein levels of p-PKA, PKA, p-Hsl (563), Hsl, Atgl, Plin1, Cav-1, and p-JNK, JNK, Grp78, Chop, PDI, Mcp1 were determined. *p<0.05, **p<0.01, compared to WT-HFD mice.
|
| 259 |
+
|
| 260 |
+
Figure 9 The working model of BAP31 function on lipid metabolism in adipocytes. BAP31-deficiency reduced mitotic clonal expansion, attenuated adipogenesis and lipid accumulation in white adipose tissue; expanded adipocytes size and promoted LDs abnormal growth through attenuating LDs hydrolysis via preventing Perilipin1 proteasomal degradation in mice.
|
| 261 |
+
|
| 262 |
+
Table 1 Serum metabolites of WT and BAP31-ASKO mice with food deprivation for 24 hours (unit: mM).
|
| 263 |
+
|
| 264 |
+
WT-Fed BAP31-ASKO-Fed WT-Fasted BAP31-ASKO-Fasted
|
| 265 |
+
Glucose 7.36±0.28 8.69±0.65* 1.72±0.25& 2.38±0.18#
|
| 266 |
+
TAG 0.51±0.06 0.84±0.09* 0.79±0.07& 0.63±0.05#
|
| 267 |
+
FFA 0.76±0.05 0.60±0.03* 1.44±0.03& 1.27±0.06#
|
| 268 |
+
Cholesterol 5.15±0.26 4.72±0.13 5.94±0.34& 5.71±0.18
|
| 269 |
+
Glycerol 0.44±0.01 0.41±0.00* 0.47±0.00& 0.43±0.00#
|
| 270 |
+
WT and BAP31-ASKO mice were food deprived with free access to water for 24 hours, then were sacrificed under anesthesia. Blood was extracted and sera were purified. Serum metabolites were determined using the commercial kits. n=6-7. *p<0.05, compared to WT-Fed mice; &p<0.05, compared to WT-Fed mice. #p<0.05, compared to BAP31-ASKO-Fed mice.
|
| 271 |
+
|
| 272 |
+
Table 2 Serum metabolites of mice treated with CL316,243 for 1 hour (unit: mM).
|
| 273 |
+
|
| 274 |
+
WT-CL BAP31-ASKO-CL
|
| 275 |
+
Glucose 4.95±0.36 5.96±0.39*
|
| 276 |
+
TAG 0.74±0.05 0.67±0.05
|
| 277 |
+
FFA 0.58±0.04 0.45±0.06*
|
| 278 |
+
Glycerol 0.47±0.01 0.44±0.01*
|
| 279 |
+
WT and BAP31-ASKO mice (12-week-old) were injected with CL316,243 (CL, 0.1 mg/kg BW) intraperitoneally. One hour later, mice were sacrificed under anesthesia. Blood was extracted and sera were purified. Serum metabolites were determined using the commercial kits. n=7. *p<0.05, compared to WT-CL mice.
|
| 280 |
+
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43 Petan T Lipid Droplets in Cancer Rev Physiol Biochem Pharmacol 2020
|
| 324 |
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44 Farmer BC Walsh AE Kluemper JC Johnson LA Lipid Droplets in Neurodegenerative Disorders Front Neurosci 2020 14 742 32848541
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| 325 |
+
45 Lee SH Meng XW Flatten KS Loegering DA Kaufmann SH Phosphatidylserine exposure during apoptosis reflects bidirectional trafficking between plasma membrane and cytoplasm Cell Death Differ 2013 20 64 76 22858544
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| 326 |
+
46 Lange M Angelidou G Ni Z Criscuolo A Schiller J Bluher M AdipoAtlas: A reference lipidome for human white adipose tissue Cell Rep Med 2021 2 100407 34755127
|
| 327 |
+
47 Petkevicius K Virtue S Bidault G Jenkins B Cubuk C Morgantini C Accelerated phosphatidylcholine turnover in macrophages promotes adipose tissue inflammation in obesity Elife 2019 8
|
| 328 |
+
48 Groves JT Kuriyan J Molecular mechanisms in signal transduction at the membrane Nat Struct Mol Biol 2010 17 659 65 20495561
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| 329 |
+
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puc/PMC10093881.txt
ADDED
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Int J Mol Sci
|
| 4 |
+
Int J Mol Sci
|
| 5 |
+
ijms
|
| 6 |
+
International Journal of Molecular Sciences
|
| 7 |
+
1422-0067
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
10.3390/ijms24076155
|
| 11 |
+
ijms-24-06155
|
| 12 |
+
Article
|
| 13 |
+
Med25 Limits Master Regulators That Govern Adipogenesis
|
| 14 |
+
Saunders Jasmine Conceptualization Investigation Writing – original draft 1†
|
| 15 |
+
Sikder Kunal Conceptualization Investigation 1†‡
|
| 16 |
+
Phillips Elizabeth Investigation 1
|
| 17 |
+
Ishwar Anurag Investigation 1
|
| 18 |
+
https://orcid.org/0000-0003-0583-4058
|
| 19 |
+
Mothy David Investigation 1
|
| 20 |
+
Margulies Kenneth B. 2
|
| 21 |
+
Choi Jason C. 1*
|
| 22 |
+
Pandey Manoj Kumar Academic Editor
|
| 23 |
+
1 Center for Translational Medicine, Department of Medicine, Thomas Jefferson University, Philadelphia, PA 19107, USA
|
| 24 |
+
2 Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
|
| 25 |
+
* Correspondence: jason.choi2@jefferson.edu; Tel.: +1-215-503-5685
|
| 26 |
+
† These authors contributed equally to this work.
|
| 27 |
+
|
| 28 |
+
‡ Current address: School of Biological Sciences and Department of Sports Science and Yoga, Ramakrishna Mission Vivekananda Educational and Research Institute (RKMVERI), Belur 711202, West Bengal, India.
|
| 29 |
+
|
| 30 |
+
24 3 2023
|
| 31 |
+
4 2023
|
| 32 |
+
24 7 615520 2 2023
|
| 33 |
+
21 3 2023
|
| 34 |
+
22 3 2023
|
| 35 |
+
© 2023 by the authors.
|
| 36 |
+
2023
|
| 37 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 38 |
+
Mediator 25 (Med25) is a member of the mediator complex that relays signals from transcription factors to the RNA polymerase II machinery. Multiple transcription factors, particularly those involved in lipid metabolism, utilize the mediator complex, but how Med25 is involved in this context is unclear. We previously identified Med25 in a translatome screen of adult cardiomyocytes (CMs) in a novel cell type-specific model of LMNA cardiomyopathy. In this study, we show that Med25 upregulation is coincident with myocardial lipid accumulation. To ascertain the role of Med25 in lipid accumulation, we utilized iPSC-derived and neonatal CMs to recapitulate the in vivo phenotype by depleting lamins A and C (lamin A/C) in vitro. Although lamin A/C depletion elicits lipid accumulation, this effect appears to be mediated by divergent mechanisms dependent on the CM developmental state. To directly investigate Med25 in lipid accumulation, we induced adipogenesis in Med25-silenced 3T3-L1 preadipocytes and detected enhanced lipid accumulation. Assessment of pertinent mediators driving adipogenesis revealed that C/EBPα and PPARγ are super-induced by Med25 silencing. Our results indicate that Med25 limits adipogenic potential by suppressing the levels of master regulators that govern adipogenesis. Furthermore, we caution the use of early-developmental-stage cardiomyocytes to model adult-stage cells, particularly for dissecting metabolic perturbations emanating from LMNA mutations.
|
| 39 |
+
|
| 40 |
+
LMNA
|
| 41 |
+
mediator complex
|
| 42 |
+
lipid accumulation
|
| 43 |
+
adipogenesis
|
| 44 |
+
NIH/NHLBIR01HL150019 R00HL118163 This research was funded by NIH/NHLBI R00HL118163 and R01HL150019 to J.C.C.
|
| 45 |
+
==== Body
|
| 46 |
+
pmc1. Introduction
|
| 47 |
+
|
| 48 |
+
The nuclear resident intermediate filament proteins lamin A/C are multi-functional proteins encoded by the LMNA gene. Mutations in the LMNA gene have been known to cause a wide array of syndromes collectively termed laminopathies, with diseases affecting highly metabolic tissues of mesenchymal origin [1]. As such, striated muscle and adipose tissue diseases, in the form of muscular dystrophy and lipodystrophy, respectively, comprise the vast majority of laminopathy cases [2]. One of these is cardiomyopathy with variable skeletal muscle involvement (herein referred to as LMNA cardiomyopathy), which is characterized by dilatation of ventricles due to CM damage and the ensuing pathological remodeling [3]. Current clinical recourse is limited to therapies aiming to mitigate the symptoms of congestive heart failure. Despite considerable efforts, mechanistic underpinnings of how LMNA mutations cause disease remain largely elusive, and this lack of basic insights has impeded the development of effective targeted therapies.
|
| 49 |
+
|
| 50 |
+
Dysregulation of lipid metabolism in cardiomyopathy is a well-established phenomenon, particularly from those arising within the context of obesity [4]. Although originally believed to contribute to disease pathogenesis, it is currently debated whether the observed lipid accumulation in cardiomyopathy occurs as a compensatory response [4]. Nevertheless, end-stage heart failure leads to a deficit of lipid availability/utilization as an energy source, causing the myocardium to rely on glucose and ketones for ATP generation [5]. Notably, myocardial lipid accumulation has been previously described in a knock-in mouse model harboring an Lmna p.delK32 mutation [6]. A mutation identified in human patients, the p.delK32 mutation produces lamin A/C proteins with a deletion of a lysine in position 32 in the N-terminal domain, leading to severe cardiac phenotype and early lethality within the first month of life [6].
|
| 51 |
+
|
| 52 |
+
At the molecular level, a functional link between the nuclear envelope and intranuclear lipids appears to be evolutionarily conserved, and its relevance is just beginning to be elucidated. Intranuclear lipid accumulation has been observed in yeast [7], as well as in mammalian cells [8,9], and plays diverse and essential roles in the nucleus. For example, a series of studies from Hovak and colleagues demonstrated that phosphatidylinositol 4,5-bisphosphate (PIP2) and its binding proteins are abundantly found in the nucleus [10,11]. They subsequently showed that PIP2 acts to recruit and enrich various proteins involved in RNA polymerase II (Pol II)-mediated transcription, creating a compartmentalized space within the nucleus, termed nuclear condensates [12,13]. These studies highlight the novel roles of lipids and their derivatives as well as the importance of maintaining proper lipid metabolism homeostasis necessary for fundamental nuclear processes including transcriptional regulation.
|
| 53 |
+
|
| 54 |
+
We recently showed in a novel tamoxifen-inducible CM-specific Lmna deletion model that fulminant cardiomyopathy and pathological fibrosis develops within 4 weeks post cessation of tamoxifen administration [14]. Coincident with the incipient phase of the disease, in which subtle histological and molecular changes are evident without impacting myocardial pump function, we discovered the upregulation of Med25 protein in a translating mRNA screen [14]. Med25 is a member of the Mediator complex, an evolutionarily conserved multi-subunit complex that integrates cellular signals and relays to the basal Pol II transcriptional machinery to generate an appropriate transcriptional response. Disruption of various mediator subunits has been shown to cause defective cardiac development and cardiomyopathy [15,16,17]. Although Med25 is well characterized in Arabidopsis thaliana, particularly regulating the jasmonate signaling pathway [18], comparatively less is known about its role in the mammalian system. Prior studies have linked Med25 to regulating lipid metabolism, nuclear receptors, and ER stress responses [19,20,21]. Interestingly, Med25 has also been demonstrated to bind directly to the polyunsaturated fatty acid arachidonic acid [22], further implicating its function in regulating lipid metabolism/signaling. Interestingly, jasmonate signaling in plants is analogous to the mammalian eicosanoid pathway [23,24], which further supports the direct connection between Med25 and arachidonic acid from which eicosanoids are derived. Collectively, these studies suggest that Med25 is a stress-responsive mediator member regulating lipid signaling-induced transcriptional responses.
|
| 55 |
+
|
| 56 |
+
In the current manuscript, we show that lipid accumulation occurs in the adult myocardium following induced CM-specific Lmna deletion during the incipient phase of the disease. Similar to the phenotype observed in patients with heart failure, this increase is transient and returns to below baseline at end-stage heart failure. This transient lipid accumulation is concomitant with the upregulation of Med25 protein expression. In vitro experimental models to recapitulate in vivo lipid accumulation in CMs depleted of lamin A/C revealed that the circuitry governing lipid metabolism is divergent depending on the developmental stage of the CMs. By leveraging the well-established 3T3-L1 preadipocyte differentiation system, we demonstrate that Med25 maintains a limit on adipogenic potential by suppressing the levels of master regulators that govern adipogenesis.
|
| 57 |
+
|
| 58 |
+
2. Results
|
| 59 |
+
|
| 60 |
+
2.1. Lipid Accumulation in the Myocardium of CM-Specific Lmna Deletion Model of LMNA Cardiomyopathy
|
| 61 |
+
|
| 62 |
+
We recently described a novel cre recombinase driver line referred to as CM-CreTRAP mice [14]. It is a bi-cistronic transgenic line wherein tamoxifen (Tam)-inducible Cre recombinase (CreERT2) and EGFP-L10a fusion protein are co-expressed under the control of a CM-specific promoter, myosin heavy chain 6 (Myh6) promoter. EGFP-L10a is a fusion of enhanced green fluorescent protein and ribosomal protein L10a, a component of the 60S ribosomal protein, which allows tagging of polysomes for immunoaffinity purification of translating mRNA termed Translating Ribosome Affinity Purification (TRAP) [25]. These mice develop molecular and histological changes by 2 weeks post Tam administration and a severe decline in cardiac function and pathological fibrosis by 4 weeks [14]. Following 100 mg/kg Tam administration at 12 weeks of age for 5 consecutive days followed by 2 days rest to delete Lmna specifically in CMs, we assessed lipid accumulation by oil-red-O staining at the indicated time points (Figure 1A and Supplementary Figure S1). We observed significant CM lipid accumulation at 2 weeks post Tam treatment (Figure S1). By 4 weeks, the lipid accumulation was far less pervasive and more focal, which resembled the pattern of progression in human heart failure [5].
|
| 63 |
+
|
| 64 |
+
To validate our oil-red-O staining results and to ensure that the lipid accumulation observed in CMs is not due to overall increases in the circulation, we measured triglyceride levels in both the myocardial tissue and blood serum from these mice. Consistent with our histological data, we noted significant lipid accumulation at 2 weeks post Tam that returned to baseline and a deficit at 3 and 4 weeks post Tam, respectively (Figure 1C,D). Despite the observed pattern of lipid accumulation in the myocardial tissue, no significant changes in the triglyceride levels were noted in the circulating serum, demonstrating that (1) Lmna-deleted CMs accumulate lipids at 2 weeks post Tam, (2) this increase in accumulation is not due to overall higher lipid levels in the circulation, and (3) the pattern of lipid accumulation in our induced CM-Lmna deletion mice recapitulates the phenotype in the human disease of heart failure. To determine whether a similar phenomenon can be observed in the human disease, we performed oil-red-O staining on heart sections from human patients (LMNAmut) along with age-/sex-matched controls. In three out of four hearts from LMNA cardiomyopathy patients, we noted obvious focal lipid accumulation, whereas age-/sex-matched non-failing hearts showed far less and more diffuse staining (Figure 1E).
|
| 65 |
+
|
| 66 |
+
We previously showed that there is a gradual elevation of Med25 protein expression that reaches its peak by 2 weeks post Tam in hearts of CM-Lmna-deleted mice [14]. To determine whether a similar elevation of Med25 protein expression occurs in the human disease, we performed immunoblot analyses on myocardial tissue from human patients and compared them to age-/sex-matched controls (Figure 1F). Despite the inherent variability and the advanced stage of the human disease, we consistently observed higher protein expression of MED25 in the patient samples (Figure 1F). We confirm this in our mouse model, in which MED25 expression remains elevated at 4 weeks post Tam (but lower than the peak at 2 weeks), despite an overall deficit in lipid availability (Figure 1G). Of note, we consistently detected multiple MED25 bands in hearts of CM-Lmna-deleted mice. The PhosphoSitePlus® database shows that Med25 can be phosphorylated, ubiquitylated, acetylated, and methylated. Furthermore, there are five transcript variants in mice (but only two variants in humans), in which a putative variant-switching mechanism may also explain the multiple bands. Although the nature of the observed multiple bands is currently unclear, these results indicate that our CM-specific Lmna-deletion mouse model recapitulates the human phenotype with regard to lipid accumulation and MED25 expression.
|
| 67 |
+
|
| 68 |
+
2.2. Lmna Deletion Causes Lipid Accumulation in Early Development CMs
|
| 69 |
+
|
| 70 |
+
Given the lipid accumulation in the Lmna-deleted CMs in vivo, we sought to determine whether the depletion of lamin A/C directly causes lipid accumulation. To achieve this, we employed neonatal CMs (nCMs) isolated from Lmna+/+ and Lmnaflox/flox mice coupled with adenoviral delivery of cre recombinase (AdCre) to delete Lmna in vitro. nCMs depleted of lamin A/C by this method recapitulate many in vivo phenotypes, including MED25 upregulation, observed in the hearts of CM-specific Lmna-deleted mice [14], suggesting that this may be a viable model to study CM lipid accumulation in response to lamin A/C depletion. The AdCre-treated cells were then stained with BODIPY 495/503, which stains neutral lipids. AdCre treatment of nCMs isolated from Lmnaflox/flox resulted in increased presence of lipid droplets but not in nCMs from Lmna+/+ (Figure 2A). Our quantitative assessment revealed that an average of ~20% of lamin A/C-depleted nCMs contained lipid droplets (Figure 2B, left). We also observed increased intranuclear lipid accumulation in the LmnaKD nCMs relative to the Lmna+/+ counterparts (Figure 2B right and Supplementary Figure S2A). Despite their presence, only a small subset of nuclei (~5%) contained visible lipid droplets, so their significance is currently unknown. These results indicate that the deletion of the Lmna gene, and the resulting depletion of lamin A/C proteins, directly elicits lipid accumulation.
|
| 71 |
+
|
| 72 |
+
To begin to pinpoint the underlying mechanisms of lipid accumulation following lamin A/C depletion, we initially focused on the enzymatic pathways regulating triglyceride generation (Dgat1 and Dgat2) and breakdown (Pnpla2 encoding ATGL and Lipe encoding HSL) as shown in the schematic in Figure 2C. Following Lmna deletion in nCMs, we performed RT-qPCR analyses to ascertain the levels of mRNA transcripts encoding the genes indicated above (Figure 2D). We observed that Dgat2 is specifically elevated in response to lamin A/C depletion, which is consistent with increased lipid accumulation (Figure 2D). Additionally, we also assessed fatty acid transporters (Cd36 and Cpt1b) and observed no significant changes with lamin A/C depletion (Figure 2D).
|
| 73 |
+
|
| 74 |
+
We then assessed the generalizability of elevated Dgat2 in response to lamin A/C depletion. To achieve this, we utilized human induced CMs (hiCMs) derived from induced pluripotent stem cell (iPSC) line SCVI114 [26], which is the wild type for the LMNA gene. Following differentiation into CMs using a previously established procedure [27] (Supplementary Figure S2A), we observed spontaneously contracting CMs (Supplementary Figure S2B and associated video file) as well as robust expression of CM-specific markers such as Tnnt2 and Myh6 (Supplementary Figure S2C). Furthermore, immunofluorescence analysis using anti-troponin T antibodies revealed not only a positive staining, but the expressed troponin T proteins spontaneously arranged themselves into sarcomere-like striations (Figure 2E).
|
| 75 |
+
|
| 76 |
+
We then depleted lamin A/C in the hiCMs using short hairpin-mediated silencing via lentiviral vectors. Having confirmed knockdown of lamin A/C (Figure 2F), we measured DGAT2 transcripts and observed a ~3-fold elevation in hiCMs with lamin A/C depletion compared to controls (hiCMs infected with lentiviruses carrying a blank shRNA) (Figure 2G). To ascertain whether a similar elevation of DGAT2 transcripts is induced in response to the expression of a mutant variant of lamin A/C (instead of a deletion model), we derived hiCMs from an IPSC line SCVI88 [26] that was generated from a patient identified with a K117fs mutation [28]. hiCMs derived from this iPSC line also displayed elevated DGAT2 transcripts relative to hiCMs from SCVI114 (Figure 2G), despite lacking an isogenic control for an ideal comparison. Nevertheless, our data indicate that both human and mouse CMs with disrupted LMNA gene expression display increased expression of DGAT2.
|
| 77 |
+
|
| 78 |
+
2.3. Distinct Mechanisms Underlying Lipid Regulation between Adult and Early Development CMs
|
| 79 |
+
|
| 80 |
+
Having shown that CMs depleted of lamin A/C elicit Dgat2 expression, we sought to determine whether similar increases are observed in the myocardium of our CM-specific Lmna-deletion mice. We isolated mRNA from ventricular tissue after 1–4 weeks post Tam dosing and performed RT-qPCR to measure Dgat1 and Dgat2 transcript levels. Compared to vehicle (corn oil) controls, we observed no elevation of Dgat1 and Dgat2 levels (Figure 2H). To the contrary, Dgat2 levels were significantly reduced at the 4 week time point relative to the vehicle control (Figure 2H, bottom panel). Given that the myocardial tissue is heterocellular in nature, we aimed to remove the contribution from other cell types in the heart. We achieved this by performing TRAP on the hearts isolated from mice treated with Tam to immunopurify translating mRNA specifically from CMs (Figure 2I). No elevation of Dgat1 and Dgat2 expression was observed (Figure 2I, right panel); their expression pattern resembled those observed from the ventricular tissue, further indicating that Dgat2 is not elevated in the hearts of adult mice with CM-specific Lmna deletion. Finally, we measured DGAT1 and DGAT2 in myocardial tissue from human patients as well as their sex-/age-matched controls and observed no differences in DGAT1 but a significant decrease in DGAT2 (Figure 2J), which again is consistent with our observations in hearts from the CM-specific Lmna-deletion mice. Taken together, our results indicate that lipid metabolism perturbations emanating from lamin A/C depletion may be mutually exclusive depending on the developmental state of the CMs. Hence, we caution the use of CMs of neonatal and embryonic origin, while much more amenable for experimental manipulation, as a model to dissect mechanisms underlying metabolic perturbations of adult CMs arising from LMNA mutations.
|
| 81 |
+
|
| 82 |
+
2.4. Med25 Depletion Enhances Adipogenesis
|
| 83 |
+
|
| 84 |
+
Given the divergent Dgat2 expression profiles between adult and early-development CMs, we pursued a different strategy to determine the functional relevance of Med25 in lipid accumulation. We employed the well-established 3T3-L1 preadipocyte model, in which we depleted Med25 by shRNA-mediated silencing, followed by differentiation induction into adipocytes by dexamethasone, IBMX, and insulin. We employed two previously described shRNAs [14] to deplete Med25 in 3T3-L1 cells and show that both shRNAs are able to achieve ~90% knockdown (KD) of Med25 mRNA (Figure 3A) and ~90% and ~95% KD at the protein levels for sh1 and sh2, respectively, relative to 3T3-L1 cells expressing blank shRNA controls (Figure 3B,C).
|
| 85 |
+
|
| 86 |
+
Following confirmation of Med25 KD, we induced these cells to differentiate into adipocytes according to the schematic in Figure 3D. We also included unmodified 3T3-L1 cells to ensure that the lentiviral transduction in and of itself does not alter the differentiation phenotype. At day 6 post initiation of differentiation, we stained the cells with BODIPY and observed that 3T3-L1 cells depleted of Med25 (with either sh1 or sh2) displayed enhanced adipocyte differentiation as reflected by lipid accumulation (Figure 3D,E; full-well micrographs are shown in Supplementary Figure S3). No observable differences were noted between unmodified 3T3-L1 cells and those infected with lentiviruses carrying blank shRNA, indicating that the lentiviral infection itself did not affect the differentiation efficiency (Figure 3D,E and Supplementary Figure S3). We then assessed transcript levels of various adipocyte markers. During our qPCR analyses, we noted that the typically used internal control genes such as Gapdh, Actb, and Hprt all displayed a pattern of expression that varied by more than 1 CT (cycle threshold) value (Supplementary Figure S4). We tested additional genes as potential candidates (Rpl13a, B2m, and Mapk1) for use as internal controls and found that Mapk1, which encodes ERK2 (p42), displayed the lowest CT value variance from undifferentiated 3T3-L1 to 4 days post adipogenic differentiation (Supplementary Figure S4). Based on the foregoing, all qPCR data relating to adipogenic differentiation were normalized to Mapk1 mRNA values. Our assessment of various adipocyte markers revealed that Cd36 and Pnpla2 levels were significantly elevated on day 4 in cells with Med25 KD relative to control cells. This observation further supports the notion that the depletion of Med25 enhances adipocyte differentiation and lipid accumulation. Based on these results, we conclude that Med25 expression acts to dampen adipogenesis and lipid accumulation.
|
| 87 |
+
|
| 88 |
+
2.5. Med25 Depletion Elevates the Expression of Adipogenic Master Regulators
|
| 89 |
+
|
| 90 |
+
In order to determine the underlying mechanism responsible for the enhanced adipogenesis mediated by Med25 KD, we dissected the signaling pathways and transcriptional regulators that govern differentiation into adipocytes. Molecular regulation governing adipogenesis in 3T3-L1 preadipocytes is complex and involves successive waves of primary, secondary, and even tertiary transcriptional regulators in an adipogenic transcriptional cascade. We focused our analyses on three major areas in the adipogenic cascade: (1) core kinase phosphorylation cascades important for establishing early-stage differentiation such as ERK1/2 as well as AKT signal transduction pathways, (2) cell-type-agnostic transcription factors involved in adipogenesis including the CCAAT-enhancer-binding protein (C/EBP) family of transcription factors [29,30,31], and (3) cell-type-restricted master regulators such as the peroxisome proliferator-activated receptor (PPAR) family of nuclear hormone receptors, some of which are regulated by C/EBP proteins [29,31].
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We initiated our studies assessing ERK1/2 (Thr202/Tyr204) and AKT (Ser473) phosphorylation status during the early phase (15 min and 3 h) as well as throughout the rest of the differentiation process (1, 2, 4 days). We observed that the patterns of both total and phosphorylated ERK1/2 between control and Med25 KD cells were virtually identical (Supplementary Figure S5A). Interestingly, despite little to no change in the Mapk1 mRNA expression as shown earlier, the encoded protein (p42/ERK2) expression increased during the latter part of the differentiation (Supplementary Figure S5A), suggesting that these changes are driven at the post-transcriptional level. Moreover, the levels of total and phosphorylated AKT were also comparable between control 3T3-L1 and the two Med25 KD cells (Supplementary Figure S5B). These results indicate that the core signal transduction pathways such as ERK and AKT cascades are not impacted by the depletion of Med25.
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We then assessed transcription factors involved in adipogenesis that are expressed in various tissues. We focused on Sterol Regulatory Element-Binding Transcription Factor 1 (SREBF1) and C/EBP family members, as they are well established to regulate the activity of adipogenic master regulator PPARγ [29,31,32]. We observed peak SREBF1 expression on day 1 of the differentiation process, and although the Med25 KD cells appeared to express higher levels than control cells during the peak expression, the extent of the increase was variable (Figure 4A,B). However, the largest difference in expression was observed in C/EBPα; we noted peak expression on day 2 that was significantly enhanced in cells with the Med25 KD (Figure 4A,B). Moreover, whereas C/EBPα returned to baseline by day 4 in control 3T3-L1, it remained elevated in cells with Med25 KD, further validating the enhanced C/EBPα phenotype (Figure 4A,B). Notably, the elevated C/EBPα expression occurred despite the comparable levels of its activators C/EBPβ and C/EBP expression (Figure 4A,B). As expected, we did not detect Med25 in the KD cells, but interestingly, its expression in control cells decreased with adipogenic differentiation, further supporting the notion that Med25 expression antagonizes adipogenesis (Figure 4A).
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C/EBPα plays an important role in regulating the expression level of PPARγ [29,31], a master regulator of adipogenesis. Given that Med25 KD enhances C/EBPα expression in the context of adipogenesis, we reasoned that there would be similar increases in the PPARγ activity and/or expression. There are two PPARγ isoforms generated by differential splicing and promoter usage [33]: PPARγ1, which is expressed in other cell types, and PPARγ2, which is largely restricted to adipocytes [33]. Serine 273 phosphorylation of PPARγ, which was shown to play a critical role in obesity and insulin resistance, is mediated by the Cdk5/ERK1/2 axis [34]. Therefore, we measured the Ser273 phosphorylation status as well as the expression levels of PPARγ1 and PPARγ2. Our immunoblot analyses revealed that although no obvious differences were noted for both the total and phospho-PPARγ1 (pPPARγ1) levels between the Med25 KD and control 3T3-L1 cells during adipocyte differentiation, we observed significant increases for PPARγ2 in Med25 KD cells (Figure 4C,D). The expression patterns between pPPARγ2 and total PPARγ2 were virtually identical, indicating that the rate-limiting step for Ser273 phosphorylation of PPARγ2 is its expression. PPARα, which can also contribute to adipogenesis, was similarly elevated in the Med25 KD cells on day 4 relative to controls, but the extent of the increase was modest, which further suggests that the enhanced adipogenicity is driven primarily by de novo PPARγ2 expression (Figure 4C,D). We also measured the levels of retinoid-X receptor isoforms as they form heterodimers with PPARγ and utilize Med25 to mediate their transcriptional activation potential. We observed no significant differences in RXRα and RXRβ between cells with and without Med25, indicating that no compensatory mechanisms affect these nuclear receptors (Figure 4C,D). RXRγ is a muscle-restricted isoform, and we did not detect its expression in our control or Med25 KD 3T3-L1 cells (data not shown). Finally, we show that the kinetics of the increased expression of PPARγ2 were consistent with a similar pattern of increase in the Pparg2 mRNA expression (Figure 4E), indicating that the observed effect is mediated at the level of transcription. No increases were noted for Pparg1, which is consistent with the observed protein expression for PPARγ1 (Figure 4E). Taken together, we conclude that Med25 maintains a limit on adipogenic potential by suppressing the levels of C/EBPα and PPARγ2 that govern adipogenesis.
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3. Discussion
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In this study, we explored the functional relevance of Med25 in lipid accumulation during adipogenesis and show that depletion of Med25 increased lipid accumulation during 3T3-L1 differentiation into adipocytes. Furthermore, our data indicate that the increased lipid accumulation is due to enhanced differentiation into adipocytes, driven primarily by the increased expression of adipogenic master regulators PPARγ2 and C/EBPα. Although we observed an elevation of PPARα in response to Med25 silencing as well, it was relatively modest compared to PPARγ and C/EBPα.
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The impetus of our studies was based on our observation that Med25 was elevated at the protein level following CM-specific Lmna deletion in vivo prior to any functional decline in cardiac performance [14]. Its increased expression coincided with diffuse and pervasive myocardial lipid accumulation, suggesting a functional link between the emergence of Med25 and myocardial lipid accumulation. This is further supported by a previously reported study demonstrating Med25 as a lipid-binding protein [22]. Based on our results using 3T3-L1 preadipocytes as a model, it is attractive to hypothesize that the expression of Med25 in response to Lmna deletion in CMs underlies the clearance of lipids with the worsening disease, but how this is achieved remains unclear. Med25 was previously shown to regulate lipid metabolism in the liver by acting as a coactivator for liver-specific transcription factor HNF4α [20], which is not expressed in CMs. Moreover, our current study demonstrates that Med25 depletion enhances the expression of PPARγ2, which is restricted to adipose tissue [35]. Therefore, a similar molecular circuitry, but with different set of specific “actors”, likely governs the lipid dysregulation observed in the hearts with CM-specific Lmna deletion.
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Our observation showing lipid droplet accumulation, particularly inside the nucleus, in response to lamin A/C warrants further investigation. Lipid accumulation is a hallmark of endoplasmic reticulum (ER) stress, and given that the nuclear envelope is contiguous with the ER membrane, the depletion of lamin A/C likely causes ER stress. Consistent with this notion, we observed a selective activation of the ER stress response following Lmna deletion in vivo [14]. Furthermore, the ER, as well as the nuclear envelope, has been shown to be a site of lipid droplet formation [7,8], further implicating lamin A/C with lipid accumulation. As more nuclear-resident processes that depend on lipids are discovered (e.g., PIP2 regulation of nuclear condensates [12,13]), they will help explain why a cell under stress would commit to an energy-intensive process of generating neutral lipids.
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We established culture models of CMs with in vitro lamin A/C-depletion to dissect the underlying mechanisms. Although lipid droplet formation is induced in response to Lmna deletion in nCMs, our data presented here demonstrate that the metabolic circuitry in response to lamin A/C-depletion in early developmental CMs (nCM and hiCMs) is different from adult CMs. This is not surprising, given the multitude of distinct characteristics that define nCM and adult CMs, from simple morphological differences (that impact mitochondrial distribution) [36], to the ability to regenerate [37], as well as fuel-type switching from reliance on glycolysis to oxidative phosphorylation [38]. Therefore, extreme caution should be taken when using nCMs and hiCMs to model adult CM phenomena; concordance in biochemical and molecular phenotypes should be confirmed between the developmentally distinct CMs prior to extrapolating data between them.
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4. Materials and Methods
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4.1. Animals
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All animal procedures were approved by the Institutional Animal Care and Use Committee of Thomas Jefferson University. All methods adhered to the NIH Guide for the Care and Use of Laboratory Animals. Lmnaflox/flox mice [39], procured from The Jackson Laboratory on a mixed background, were backcrossed to C57BL/6J mice for a minimum of 8 generations and genotyped as indicated by the distributor. CM-CreTRAP transgenic mice were generated in a C57BL/6 background by Cyagen Biosciences. The construction of the bi-cistronic transgene was described in detail in [14]. Genotyping was performed on genomic DNA purified from tail clippings by standard PCR using primers indicated in Supplementary Table S2. The mice were housed in a disease-free barrier facility with 12/12 h light/dark cycles and fed a chow diet ad libitum. Tamoxifen (MilliporeSigma, St. Louis, MO, USA, cat# T5648) was reconstituted in corn oil (MilliporeSigma, St. Louis, MO, USA, cat# C8267) and delivered intraperitoneally.
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4.2. Human Samples
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Heart tissue from human subjects with LMNA cardiomyopathy were obtained at the time of heart transplantation. Sex- and age-matched control myocardium was obtained from brain-dead organ donors. Use of human heart tissue for research was approved by the University of Pennsylvania Institutional Review Board, and the use of hearts from brain-dead organ donors for was approved by the Gift-of-Life Donor Program in Philadelphia, PA, USA. Detailed methods for harvesting of tissue can be found in [14]. The human samples were obtained through a Uniform Biological Materials Transfer Agreement with The Trustees of the University of Pennsylvania. The samples were collected de-identified and not specifically for the proposed research by interacting with living individuals.
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4.3. Primary nCM Isolation and Lmna Deletion
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Primary murine nCMs were isolated from the ventricles of 1–2 day old wild-type C57BL/6 and Lmnaflox/flox mouse pups using MACS neonatal heart dissociation kit according to the manufacturer (Miltenyi Biotec, Bergisch Gladbach Germany cat# 130-098-373) as previously described [14]. Following isolation, nCM cells were plated onto 10 μg/mL laminin-coated wells with 50 kPa hydrogels (Matrigen, Irvine, CA, USA, cat# SW12-EC-50 PK). To prevent the potential growth of non-myocyte cells, the culture media was also supplemented with 100 μM 5-bromo-2-deoxyuridine (BrdU) and 10 µM cytosine arabinoside (Ara-C). The cells were maintained at 37 °C in 95% humidity with 5% CO2 concentration. The cells were allowed to attach overnight, after which the medium (composed of DMEM + 10% FBS + 10 µM Ara-C) was replaced after 2x rinse with PBS to remove dead cells. To delete Lmna in vitro, adenovirus carrying mCherry-Cre (AdCre) (Vector Biolabs, Malvern, PA, USA, cat# 1773) was used at 50 MOI. Comparable infection efficiencies were confirmed by mCherry.
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4.4. iPSC-Derived hiCMs
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Human iPSC lines were obtained from Dr. Joseph C. Wu at the Stanford Cardiovascular Institute. They were derived by reprogramming PBMC of a 41-year-old healthy Asian male volunteer (SCVI-114) and human dermal fibroblast of a 60-year-old Asian male patient having the K117fs LMNA mutation (SCVI-88) [28]. The iPSC lines were cultured and differentiated into hiCMs according to a previously published protocol [27]. Contracting organoids emerged around day 7 of differentiation with maximal contraction achieved by 15–21 days. The beating organoids were kept in culture for 4 weeks before dissociating to single-cell suspension for metabolic selection of hiCMs [40]. To dissociate the beating organoids into single-cell suspension, they were trypsinized with 0.05% trypsin for 10–15 min at 37°. After centrifugation at 800–900 rpm for 5 min, the cells were seeded in matrigel-coated plates at high confluency with DMEM media with 5% FBS, bFGF2 (ProspecBio, East Brunswick, NJ, USA, cat# cyt-557-b), and ROCK inhibitor (Y-27632; Selleck Chemicals, Houston, TX, USA, cat# S1049). The next day, the medium was changed to glucose- and pyruvate-free DMEM (ThermoFisher Scientific, Waltham, MA, USA, cat# 11966025) but supplemented with 5% FBS, 4 mM lactate (MilliporeSigma, St. Louis, MO, USA, cat# L7022), and b-FGF2. Cells were replenished with fresh media every 2 days with vigorous washing to get rid of dead cells of non-CM population.
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4.5. 3T3-L1 Culture, shRNA Knockdown, and Adipogenic Differentiation
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3T3-L1 cells (American Type Culture Collection, Manassas, VA, USA, cat# CL-173) were maintained in DMEM supplemented with 10% FBS at 37 °C with 5% CO2 and subcultured at ~60–70% confluency. Viral packaging cell line 293T cells were maintained in the same media. For stable knockdown of Med25, we used two independent shRNAs in the pLKO.1 lentiviral vector backbone identified from murine Med25 shRNA (MilliporeSigma, St. Louis, MO, USA, cat# SHCLNG-NM_029365) with the sequences GCAGCTGTTCGATGACTTTAA (shRNA1) and TGCAGCTGTTCGATGACTTTA (shRNA2). For stable knockdown of LMNA in hiCMs, shRNA with the following sequence was used: AAGCAACTTCAGGATGAGATC. The lentiviral vectors were co-transfected into 293T cells with the packaging vectors pCMV-dR8.2 dvpr and pCMV-VSV-G (cat# 8455 and 8454, respectively, from Addgene, Watertown, MA, USA). Virus-infected cells were selected with 2 μg/mL puromycin. Adipocyte differentiation was performed according to the protocol available at ATCC with slight modifications. Briefly, the viral-infected 3T3-L1 cells were plated in DMEM with 10% BCS and grown to confluency. Once the cells were fully confluent, control (undifferentiated) samples of each cell type were harvested for RNA/protein, and the remaining samples were treated with MDI induction medium composed of DMEM with 10% FBS, 200 nM insulin (MilliporeSigma, St. Louis, MO, USA, cat# I5500), 11.5 μg/mL IBMX (MilliporeSigma, St. Louis, MO, USA, cat# I7018), and 1 μM dexamethasone (MilliporeSigma, St. Louis, MO, USA, cat# D4902). After 2 days of treatment with the MDI induction medium, the medium was replaced with insulin medium (DMEM with 10% FBS and 200 nM insulin). After 2 days, the medium was replaced with DMEM with 10% FBS.
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4.6. Protein Extraction, Immunoblot Analysis, and TG Analysis
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Samples were homogenized in chilled radioimmunoprecipitation assay (RIPA) buffer (MilliporeSigma, St. Louis, MO, USA, cat# R0278) with Pierce protease-inhibitor cocktail (ThermoFisher Scientific, Waltham MA, USA cat# A32963) and 1 mM sodium vanadate (MilliporeSigma, St. Louis, MO, USA, cat# S6508). After brief sonication (Dismembrator Model F60, ThermoFisher Scientific, Waltham, MA, USA), the samples were prepped in Laemmli buffer, after which 15 to 30 µg of the protein extracts were loaded for SDS-PAGE. Antibodies and the dilutions used in the study are provided in Supplementary Table S1. Proper loading was confirmed by probing with GAPDH antibodies for primary heart tissue and β-actin for cell lines. Immunoblot images were captured using an Odyssey® Fc Imaging System, and densitometry of blots was performed using Image Studio software version 5.2 (LI-COR Biosciences, Lincoln, NE, USA) normalized to loading controls. Uncropped blot images are provided in Supplementary Figure S6. TG content of myocardial tissue and serum was assessed using a Triglyceride Colorimetric Assay Kit (Cayman Chemical, Ann Arbor, MI, USA, cat# 10010303) according to the manufacturer’s instructions.
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4.7. RNA Isolation, Translating Ribosome Affinity Purification, and RT-qPCR
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Total RNA was isolated using a Direct-zol RNA kit (Zymo Research, Irvine, CA, USA, cat# R2053) with a minor modification. Samples were harvested in TRIzol (Zymo Research, Irvine, CA, USA, cat# R2050-1-200), and the aqueous phase containing total RNA was separated by adding chloroform (20% volume of TRIzol). The aqueous fraction was carefully collected, to which 100% molecular grade ethanol was added at a 1:1 ratio and then further processed using the Direct-zol RNA kit according to the manufacturer’s instructions. cDNA was generated from 500 ng of RNA and primed with a 1:1 ratio of random hexameric primers and oligodT using a RevertAid RT kit (ThermoFisher Scientific, Waltham, MA, USA, cat# K1691). qPCR was performed in duplicates with QuantStudio5 qPCR system (Life Technologies) using PowerUP SYBR-green (ThermoFisher Scientific, Waltham, MA, USA, cat# A25743). For data presented in Figure 2, Gapdh was assessed to ensure fidelity of enzymatic reactions and used as an internal control to normalize qPCR results. For adipocyte differentiation with 3T3-L1, Mapk1 was used. Fold-changes in gene expression were determined by the ΔCt method [41] and presented as fold-change (FC) over negative controls. We employed two approaches to generate ΔΔCT: (1) for all qPCR data from tissue samples, the FC of all samples (including controls) was calculated relative to the mean value of control samples. For FC data from cell lines in kinetics experiments (Figure 3F,G and Figure 4E), the value of the control sample at the 0 timepoint was set to “1” and all other samples’ FC calculated relative to this control sample. For TRAP, we processed the ventricular tissue exactly as described previously [25]. Mice (12 weeks old) were treated with either vehicle or Tam as described in Figure 2I. Two weeks after Tam (or vehicle) dosing, ventricular tissue were harvested and translating mRNAs purified from n = 3 biologically independent samples. For cDNA synthesis of TRAP mRNA, 100 ng of translating mRNA was used. A complete list of primer sets used in the study is provided in Supplementary Table S2.
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4.8. Microscopy and Histopathological Analysis
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Oil-red-O staining was performed by Translational Research & Pathology Shared Resources (Thomas Jefferson University, Philadelphia, PA, USA) using standard methods. For immunofluorescence, cells were fixed in ice-cold methanol:acetone (3:1) and processed using standard methods with antibodies at listed concentrations in Supplementary Table S2. Cellular neutral lipid staining was performed on paraformaldehyde-fixed nCMs by incubating 10 μM BODIPY 493/503 (ThermoFisher Scientific, Waltham, MA, USA, cat# D3922) dissolved in PBS for 20 min at 37 °C. DAPI was used as a counterstain. Micrographs were captured using an EVOS M7000 Imaging System (ThermoFisher Scientific, Waltham, MA, USA). All image analysis was performed using ImageJ 2.0 software [42]. Quantification of % nCMs containing lipid droplets was performed by dividing the number of cells containing circular BODIPY positive signals larger than 1.5 μm in diameter by the total number of cells (~280 cells per condition) across 6 images per condition from 2 independent experiments.
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4.9. Statistical Analysis
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Statistical analyses were performed using Graphpad Prism 9 (GraphPad Software, Boston, MA, USA). Statistical significance of binary comparisons was determined by a 2-tailed, unpaired Student’s t-test, with a value of p < 0.05 considered significant. Statistical significance of three or more variables was determined by one-way ANOVA with post-hoc Tukey error correction (for multiple comparisons) or Dunnett’s for comparison to a specific control. p < 0.05 was considered significant. Values with error bars shown in figures are means ± SEM unless indicated otherwise. Sample sizes are indicated in the figure legends.
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Acknowledgments
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We thank Joseph C. Wu for providing iPSC lines. Figure 1A, Figure 2C and Figure 3D were created with BioRender.com, accessed on 17 March 2023.
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Supplementary Materials
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The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms24076155/s1.
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Click here for additional data file.
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Author Contributions
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Conceptualization, J.S., K.S. and J.C.C.; investigation, J.S., K.S., E.P., D.M., A.I. and K.B.M.; writing—original draft preparation, J.S. and J.C.C.; writing—review and editing, J.C.C.; supervision, J.C.C. All authors have read and agreed to the published version of the manuscript.
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Institutional Review Board Statement
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The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of University of Pennsylvania (protocol #848421 approved on 10 January 2023) for studies involving humans. The animal study protocol was approved by the Institutional Review Board of Thomas Jefferson University (protocol #01744-1 approved on 15 October 2021).
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Informed Consent Statement
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Informed consent was obtained from all subjects involved in the study.
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Data Availability Statement
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All data associated with this study are available in the main text or the Supplementary Materials. Human cardiac samples were obtained through MTA with The Trustees of the University of Pennsylvania. TRAP GFP antibodies were obtained through MTA with Bi-Institutional Antibody and Bioresource Core Facility.
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Conflicts of Interest
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The authors declare no conflict of interest.
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Figure 1 LMNA cardiomyopathic hearts accumulate lipids during disease pathogenesis. (A) Schematic of tamoxifen (Tam) administration schedule. Syringe denotes days of Tam injection. IP denotes intraperitoneal, Veh denotes vehicle (corn oil). (B) Oil-red-O staining of heart sections from CM-CreTRAP: Lmnaflox/flox mice at 1, 2, and 4 weeks post final Tam dosing. Yellow arrows denote focal lipid accumulation. Representative images from 3 independent sections from 3 mice per group are shown. All scale bars = 100 μm. (C) Triglyceride (TG) measurements of the heart tissue extracts from CM-CreTRAP: Lmnaflox/flox mice treated with vehicle (Veh) or Tam. 1–4w denote weeks post Tam treatment. Error bars denote = SEM. * denotes p < 0.005 using one-way ANOVA with Dunnett’s post hoc test. n = 3. (D) TG measurements of serum from CM-CreTRAP: Lmnaflox/flox mice treated with vehicle (Veh) or Tam for 1–4 weeks. n = 3. (E) Oil-red-O staining of human hearts from LMNA cardiomyopathy patients (LMNAmut) and age-/sex-matched non-failing wild-type LMNA hearts (LMNA+/+). Representative images from 10 independent sections per group are shown. (F) Immunoblot of MED25 and GAPDH on human hearts as described in (E), with quantitation on the bottom. Numbers on top of blots denote individual heart samples. n = 4 per group. (G) Immunoblot of MED25 and GAPDH on tissue extracts from CM-CreTRAP: Lmnaflox/flox mice treated with vehicle, 1, 2, and 4 weeks post final Tam dosing. Numbers on top of blots denote individual heart samples. n = 3 per group. Quantitation is shown on the bottom.
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Figure 2 Increased DGAT2 mRNA expression in response to lamin A/C depletion in neonatal and embryonic but not in adult CMs. (A) nCMs isolated from Lmna+/+ and Lmnaflox/flox mice (Lmna KD) infected with AdCre and cultured on 50 kPa matrix for 48 h, after which they were stained with BODIPY 495/503 and DAPI. Representative images from n = 3 experiments are shown. Scale bar = 100 μm. (B) Left panel shows quantitation of BODIPY-positive cells represented as % of BODIPY-positive cells (>1.5 μm diameter) from total number of cells counted. The individual data points denote % of BODIPY-positive cells per image for each group from three independent experiments. Right panel shows % of nuclear BODIPY-positive cells from the same set of experiments. (C) Schematic of triglyceride (TAG) metabolism and catabolism with enzymes that catalyze the reaction. DAG and MAG denote diacylglycerol and monoacylglycerol, respectively. TAG is shown encapsulated by a phospholipid monolayer also bound by lipid droplet binding proteins (multi-colored motifs). (D) qPCR analyses of Dgat1, Dgat2, Pnpla2 (encoding ATGL), Lipe (encoding HSL), Cd36, and Cpt1b on mRNA isolated from Lmna+/+ and Lmnaflox/flox mice (Lmna KD) infected with AdCre. All fold-change values were derived relative to the mean of five Lmna+/+ samples. n = 5. p values were derived using unpaired, two-tailed Student’s t test. (E) Troponin T and DAPI staining on wild-type undifferentiated human iPSCs (left panel) and those differentiated into CMs (hiCMs) (right panel). The dashed white box denotes inset, which shows sarcomeric striations. Scale bar = 100 μm. (F) Immunoblot analyses of hiCMs infected with lentivirus carrying either a blank vector (Ctrl) or encoding shRNA targeting LMNA (KD) probed for LMNA, MED25, and β-actin. A representative blot is shown from three independent experiments. (G) qPCR analyses probing DGAT2 mRNA expression in Ctrl and KD hiCMs as indicated in 2F as well as hiCMs derived from SCVI88 iPSCs (88). Fold-change values were derived by setting the Ctrl sample value as 1. p values were derived using one-way ANOVA with Dunnett’s correction. n = 3. (H) qPCR analyses of Dgat1 (top) and Dgat2 (bottom) mRNA expression in myocardial tissue of CM-CreTRAP: Lmnaflox/flox mice at 1 to 4 weeks post Tam dosing. Veh denotes vehicle (corn oil). Fold-change was derived from the mean value of 5 Veh samples used as a relative reference. p values were derived using one-way ANOVA with Dunnett’s correction. n = 5 for all groups except for 1w (n = 3). (I) Schematic of experimental design using TRAP. Right panel shows qPCR analyses on CM-specific translating mRNAs probed for Dgat1 and Dgat2 from CM-CreTRAP: Lmnaflox/flox mice 1 and 2 weeks post Tam treatment. p values were derived using one-way ANOVA with Dunnett’s post hoc. Fold-changes with the mean value from Veh group as a reference control. n = 3. (J) qPCR analyses of DGAT1 and DGAT2 in myocardial tissue from human patients. Fold-change was calculated relative to the mean value from five healthy patient samples. n = 5 per group. p values were derived using unpaired, two-tailed Student’s t-test. All error bars denote SEM in this figure.
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Figure 3 Med25 silencing enhances adipogenesis. (A) mRNA expression analysis validating Med25 expression knockdown relative to controls (ctrl–3T3-L1 infected with lentiviruses carrying blank vector) using two independent shRNAs (sh1 and sh2) that target Med25. Fold-change was derived from the mean value of ctrl samples used as a relative reference. n = 3. Error bars = SEM. (B) Immunoblot of MED25 and β-actin in nuclear extracts from 3T3-L1 cells expressing sh1 and sh2. (C) Densitometry measurements of MED25 protein levels normalized to β-actin and represented in arbitrary units. n = 3. Error bars = SEM. (D) Adipocyte differentiation schema using the ctrl and two (sh1, sh2) Med25 KD cells. Dex denotes dexamethasone. (E) BODIPY 495/503 and DAPI staining on 3T3-L1 cells differentiated into adipocytes for 6 days. Bright-field image is also shown to reveal lipid-filled, differentiated adipocytes. Representative images from three independent differentiation experiments are shown. Scale bar = 100 μm. (F,G) qPCR analyses of Cd36 (F) and Pnpla2 (G) at undifferentiated (0), 1 day (1D), 2 days (2D), and 4 days (4D) post initiation of adipogenic differentiation. p values were derived using one-way ANOVA with Tukey’s post hoc. Fold-change values were derived by setting the ctrl 0 h sample value for each respective set as “1”. n = 3. Error bars = SEM.
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Figure 4 Med25 suppresses the expression of adipogenic master regulators. (A) Kinetics of protein expression analyses on control and MED25-depleted 3T3-L1 cells (sh1 and sh2) and differentiated into adipocytes probed for SREBF1, C/EBPα, C/EBPβ, C/EBPδ, MED25, and β-actin (loading control). Cells for protein extraction were collected on days 0 (undifferentiated), 1, 2, and 4 after differentiation initiation as shown in Figure 3D. Representative blots are shown out of n = 3 experiments. (B) Quantitation of the immunoblot analyses shown in 4A. The densitometry values for the probed proteins were normalized to β-actin and represented as fold-change relative to 0 hr, which was set as “1”. Error bars denote SEM from three independent experiments. (C) Kinetics of protein expression analyses on MED25-depleted 3T3-L1 cells differentiated into adipocytes as in 4A but probed for phospho-Ser273 PPARγ1 (pPPARγ1) and pPPARγ2, total PPARγ1 and PPARγ2, PPARα, RXRα, RXRβ, and β-actin. Representative blots are shown out of n = 3 experiments. (D) Quantitation of the immunoblot analyses shown in 4C. The densitometry values for the probed proteins were normalized to β-actin and represented as fold-change relative to 0 h, which was set as “1”. Error bars denote SEM from three independent experiments. (E) qPCR analyses of Pparg1 and Pparg2 mRNA expression at undifferentiated (0), 1 day (1D), 2 day (2D), and 4 day (4D) post initiation of adipogenic differentiation. p values were derived using one-way ANOVA with Tukey’s post hoc. Fold-change values were derived by setting the ctrl “0” sample value for each respective sets as “1”. n = 3. Error bars = SEM.
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Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
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puc/PMC10135657.txt
ADDED
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Antioxidants (Basel)
|
| 4 |
+
Antioxidants (Basel)
|
| 5 |
+
antioxidants
|
| 6 |
+
Antioxidants
|
| 7 |
+
2076-3921
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
10.3390/antiox12040882
|
| 11 |
+
antioxidants-12-00882
|
| 12 |
+
Article
|
| 13 |
+
Standardized Sanguisorba officinalis L. Extract Inhibits Adipogenesis and Promotes Thermogenesis via Reducing Oxidative Stress
|
| 14 |
+
Zheng Yulong Methodology Software Investigation Writing – original draft Visualization 1
|
| 15 |
+
Lee So-Yeon Methodology Software Investigation Data curation 1
|
| 16 |
+
Lee Yeji Methodology Validation 1
|
| 17 |
+
Lee Tae-Kyeong Software Investigation Visualization 1
|
| 18 |
+
Kim Ji Eun Formal analysis Resources 2
|
| 19 |
+
https://orcid.org/0009-0000-9229-1324
|
| 20 |
+
Kim Tae Hyeon Formal analysis Resources 2
|
| 21 |
+
https://orcid.org/0000-0003-0314-5195
|
| 22 |
+
Kang Il-Jun Conceptualization Formal analysis Writing – review & editing Supervision Project administration Funding acquisition 1*
|
| 23 |
+
Omaye Stanley Academic Editor
|
| 24 |
+
1 Department of Food Science and Nutrition & the Korean Institute of Nutrition, Hallym University, Chuncheon 24252, Republic of Korea
|
| 25 |
+
2 Ju Yeong NS Co., Ltd., Seoul 05854, Republic of Korea
|
| 26 |
+
* Correspondence: ijkang@hallym.ac.kr; Tel.: +82-33-248-2135; Fax: +82-33-256-3420
|
| 27 |
+
04 4 2023
|
| 28 |
+
4 2023
|
| 29 |
+
12 4 88207 3 2023
|
| 30 |
+
24 3 2023
|
| 31 |
+
03 4 2023
|
| 32 |
+
© 2023 by the authors.
|
| 33 |
+
2023
|
| 34 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 35 |
+
Obesity produces many health problems, including systemic oxidative stress. This study comprehensively investigated the effects of Sanguisorba officinalis L. extract (SO) as an antioxidant on abnormal lipid accumulation and oxidative stress in 3T3-L1 adipocytes and high-fat diet (HFD)-induced obese mice (n = 48). We evaluated the anti-adipogenic and antioxidant effects of SO on 3T3-L1 by cell viability, Oil red O staining, and NBT assays. The ameliorative effects of SO in HFD-induced C57BL/6J mice were investigated by measuring body weight, serum lipids, adipocyte size, hepatic steatosis, AMPK pathway-related proteins, and thermogenic factors. In addition, the effect of SO on oxidative stress in obese mice was evaluated by the activity of antioxidant enzymes and the production of lipid peroxidation products and ROS production in adipose tissue. We found that SO dose-dependently decreased lipid accumulation and ROS production in 3T3-L1 adipocytes. In C57BL/6J obese mice, SO (above 200 mg/kg) attenuated the HFD-induced gain in body weight and white adipose tissue (WAT) weight without affecting appetite. SO also decreased serum glucose, lipid, and leptin levels and attenuated adipocyte hypertrophy and hepatic steatosis. Furthermore, SO increased the expression of SOD1 and SOD2 in WAT, decreased ROS and lipid peroxides, and activated the AMPK pathway and thermogenic factors. In summary, SO reduces oxidative stress in adipose tissue by increasing antioxidant enzyme activity and improves obesity symptoms through AMPK-pathway-regulated energy metabolism and mitochondrial respiratory thermogenesis.
|
| 36 |
+
|
| 37 |
+
Sanguisorba officinalis L. extract
|
| 38 |
+
obesity
|
| 39 |
+
reactive oxygen species
|
| 40 |
+
oxidative stress
|
| 41 |
+
antioxidant enzymes
|
| 42 |
+
AMPK pathway
|
| 43 |
+
thermogenesis
|
| 44 |
+
Ministry of Small and Medium-sized Enterprises (SMEs) and Startups (MSS), Korea, under the “Regional Specialized Industry Development Plus ProgramS3094185 Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education2021R1A6A1A03044501 This research was financially supported by the Ministry of Small and Medium-sized Enterprises (SMEs) and Startups (MSS), Korea, under the “Regional Specialized Industry Development Plus Program (R&D, S3094185)” supervised by the Korea Technology and Information Promotion Agency for SMEs (TIPA). This research was also supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2021R1A6A1A03044501).
|
| 45 |
+
==== Body
|
| 46 |
+
pmc1. Introduction
|
| 47 |
+
|
| 48 |
+
Obesity has long been a worldwide public health problem [1]. Obesity makes the body bloated and brings inconvenience to daily life. More importantly, excessive obesity can make people vulnerable to atherosclerosis, heart disease, diabetes, hypertension, and other metabolic syndromes [2]. Adipose tissue is the main organ that regulates the overall energy homeostasis of the organism [3]. It stores excess energy in triglyceride (TG) form broken down to nourish other tissues during low energy availability [4]. Therefore, the fundamental reason for obesity is a persistent imbalance between energy intake and consumption.
|
| 49 |
+
|
| 50 |
+
Adipose tissue is mainly divided into two tissue types with different characteristics: white adipose tissue (WAT) and brown adipose tissue (BAT) [5]. WAT is the primary energy storage organ converting excess energy into TG for accumulation. In contrast, BAT is mitochondrially enriched and converts fatty acids to heat via uncoupling protein-1 (UCP-1)-mediated mitochondrial respiration [6]. Recent studies have found a beige adipose tissue that is an intermediate between WAT and BAT [7]. Beige adipose tissue shares characteristics similar to WAT, but its gene expression pattern tends toward BAT and it also has thermogenic effects [8]. Given the inducibility of beige adipose tissue, inducing gene expression in WAT to beige adipose tissue has emerged as a novel strategy for treating obesity [9].
|
| 51 |
+
|
| 52 |
+
Another problem with obesity is persistent oxidative stress. Obesity-induced high concentrations of free fatty acids circulating in the bloodstream activate the nicotinamide adenine dinucleotide phosphate (NADPH) oxidase pathway, and abnormal accumulation of lipids disrupts the antioxidant defense system of adipocytes [10]. These consequences initiate a chain reaction that leads to a rise in reactive oxygen species (ROS) levels in adipocytes and systemic oxidative stress. Excessive ROS accumulation raises proinflammatory factors [11] and reduces insulin sensitivity [12], causing adipokine disturbance [10] and mitochondrial dysfunction [13]. Therefore, natural products with antioxidant properties have the potential to improve obesity symptoms [14]. Korean traditional herbs such as mulberry leaf [15] and red ginseng [16] have been reported to alleviate oxidative stress and improve metabolic syndrome.
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| 53 |
+
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| 54 |
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Sanguisorba officinalis L. (SO) is widely distributed as a medicinal natural product in China, Korea, and Japan and is well known for its antioxidant properties [17,18]. SO has been proven to have anti-inflammatory [19], antibacterial [20], antitumor [21], and hypoglycemic [22] physiological activities in addition to its antioxidant effects. Traditionally, SO is not only an edible plant but has also been used to treat ailments such as duodenal ulcers, diarrhea, hemorrhoids, and varicose veins [23]. This research aimed to assess the antioxidant capacity of SO in adipocytes and investigate its potential to improve obesity symptoms through thermogenesis.
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| 56 |
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2. Materials and Methods
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| 57 |
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2.1. Reagents
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Ethanol (EtOH) was acquired from Daehan Ethanol life (Hwasung, Republic of Korea). Acetonitrile (ACN), methanol (MeOH), and isopropanol were acquired from J.T. Baker Chemical (Phillipsburg, NJ, USA). Dulbecco’s modified Eagle’s medium (DMEM) was acquired from Welgene (Daegu, Republic of Korea). WST-1 cell viability assay kit was acquired from Dogenbio (Seoul, Republic of Korea). Bovine calf serum (BCS), fetal bovine serum (FBS), penicillin/streptomycin (P/S), insulin, RIPA buffer, and BCA protein assay kit were acquired from Thermo Fisher Scientific (Waltham, MA, USA). Quercitrin, dimethyl sulfoxide (DMSO), dexamethasone (Dex), 3-isobutyl-1-methylxanthine (IBMX), nitro blue tetrazolium (NBT), dihydroethidium (DHE) 3,3′-diaminobenzidine tetrahydrochloride (DAB), Oil Red O (ORO), 2-methyl-2-butanol, and 2,2,2-tribromoethanol (avertin) were acquired from Sigma-Aldrich (St. Louis, MO, USA). The primary and secondary antibodies utilized in this research were acquired from Cell Signaling Technology (Danvers, MA, USA), Santa Cruz Biotechnology (Dallas, TX, USA), and Abcam (Cambridge, UK).
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| 62 |
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2.2. Sample Preparation
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| 63 |
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Sanguisorba officinalis L. was provided by JuYeong NS Company (Seoul, Republic of Korea). Dried leaves and stems were extracted twice with 54% EtOH at 73 °C under reflux for 8 h. The extract was condensed using a vacuum and converted into a powder sample by spray drying. The obtained Sanguisorba officinalis L. extract (SO) was stored in a desiccator.
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| 65 |
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2.3. Sample Standardization
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| 67 |
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Samples were standardized by HPLC analysis of quercitrin content in the extracts. The Agilent 1260 system (Agilent Technologies, Waldbronn, Germany) consists of a quaternary pump (G311), standard autosampler (G1329B), column oven (G1316A), and diode array detector (G4212B) that detected an output signal at a wavelength of 254 nm which was used to conduct HPLC analysis. Extract (1 g) was weighed into a 100 mL volumetric flask and dissolved by ultrasonication with 80 mL 50% MeOH for 20 min. Then, the same solvent was applied to the line of the flask and filtered with a 0.45 μm syringe filter (Whatman, Marlborough, MA, USA). In addition, quercitrin standards were dissolved in 50% MeOH, sonicated, and filtered. The solution was then diluted according to concentration. SO was chromatographically separated using a Kinetex C8 column (4.6 × 250 mm, 5 μm, Phenomenex Inc., Torrace, CA, USA) at a column temperature of 30 °C. The solvent system for analyzing SO comprised phase A (water with 0.1% formic acid) and phase B (ACN with 0.1% formic acid) flowing at a 1.0 mL/min rate. The conditions for gradient elution involved 90% A at 0–5 min, 75% A from 5–30 min, 90% A from 30–35 min, and 90% A at 40 min. HPLC analysis was repeated 3 times at different periods to measure the quercitrin content in the extract.
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2.4. Cell Culture and Differentiation
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The 3T3-L1 preadipocytes (American Type Culture Collection; Manassas, VA, USA) were grown in DMEM supplemented with 10% BCS and 1% P/S at 37 °C and 5% CO2 level. Cells were inoculated into 24-well plates at 5 × 104 cells/well density and allowed to confluence. The differentiation medium (MDI; DMEM containing 10% FBS, 1% P/S, 0.5 mM IBMX, 1 μM Dex, and 10 μg/mL insulin) was replaced two days after the cells were 100% confluent and recorded as day 0. The differentiation medium without IBMX and Dex on was changed on day 2 and the differentiation medium containing only 10% FBS and 1% P/S on day 4. After that, the medium was changed every two days until day 8. Cells were treated with 100–400 μg/mL of SO and 200 μg/mL of Garcinia cambogia water extract (GC) at each medium change.
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2.5. Cell Viability Assay
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The viability of 3T3-L1 preadipocytes and adipocytes was measured using the WST-1 assay kit. Preadipocytes were seeded in 24-well plates at a density of 5 × 104 cells/well and treated with SO (100–400 μg/mL) for 24 h at 100% confluency, or adipocytes’ cell viability was measured on day 8 of induced differentiation. After incubation, 500 μL of medium (containing 20 μL WST-1) was replaced in each well. Following 2 h later, the medium was moved to 96-well plates, and the optical density was quantified at 450 nm by a UV-visible spectrophotometer (Multiskan FC; Thermo Fisher Scientific, Waltham, MA, USA).
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2.6. ORO Staining and NBT Assay
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Adipocytes differentiated to day 8 were immobilized in 4% paraformaldehyde (Biosesang, Seongnam, Republic of Korea) for 40 min at room temperature. Subsequently, the cells were rinsed with 60% isopropanol and stained with ORO solution for 20 min at room temperature. The dyed cells were visualized through a microscope and photographed (ECLIPSE Ni-U; Nikon, Melville, NY, USA). The dried cells were redissolved in 100% isopropanol, and the UV-visible spectrophotometer was used to measure the absorbance at 520 nm. ROS accumulation in adipocytes was measured using the NBT assay. Differentiated adipocytes were incubated with 0.2% NBT solution for 90 min. Following cell drying, 300 μL of DMSO (DMSO:1 N KOH = 7:3) was introduced into each well and eluted for 10 min on a shaking device. Then, 300 μL of distilled water was introduced into each well, and the UV-visible spectrophotometer was utilized to quantify the absorbance at 570 nm.
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2.7. Animal Experiment
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Male C57BL/6J mice with a body weight ranging from 18–20 g and aged 5 weeks were obtained from Central Laboratory Animal Inc. (Seoul, Republic of Korea). The mice were housed in a 12-h cycle of light and darkness facility, and the temperature was maintained at 25 ± 2 °C with a relative humidity of 55 ± 5%. During the experiment, mice were allowed unrestricted access to food and water and were given 1 week to acclimate. Experimental animals were separated into 6 groups and 8 mice in each group: normal-fat diet group (NFD) with 10% kcal fat (Envigo, Madison, WI, USA), high-fat diet group (HFD) with 60% kcal fat (Envigo, Madison, WI, USA), HFD supplemented with SO (100, 200, and 400 mg/kg) group, and HFD supplemented with GC (200 mg/kg) as a positive control group [24]. For the first two weeks of the experiment, only dietary induction was performed, followed by the 10-week period in which the extract was dissolved in distilled water and given orally daily. The amount of food and water consumed by the animals and their body weight was recorded once a week.
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2.8. Serum Analysis and Tissue Collection
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Indicators for serum analysis were performed as previously described [25]. After the experiment, mice were deprived of food for 12 h and given avertin anesthesia to collect blood samples from their orbital vein. Blood was separated into serum using a centrifuge (Eppendorf, Hamburg, Germany) at 3000× g for 20 min at a temperature of 4 °C. Serum analysis was used with an automated clinical chemistry analyzer (DRI-CHEM NX500i; FUJI, Tokyo, Japan), and serum leptin quantification was performed with an ELISA kit (R&D Systems, Minneapolis, MN, USA). Organs were collected and weighed after mice were euthanized. Serum and tissue samples were preserved at −80 °C.
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2.9. Histological Analysis
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| 91 |
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Epididymal adipose and liver tissue were immersed in 4% paraformaldehyde for 48 h. Fixed tissues were dehydrated through an automated tissue processor (TP1020; Leica Biosystems, Nussloch, Germany) and embedded in paraffin following previously described methods [26]. Paraffin-embedded blocks were sectioned at 6 µm and dyed with a combination of hematoxylin and eosin (H&E). Observation of tissue staining was conducted under a light microscope, and adipocyte size was measured using Adiposoft software 1.13 (National Institutes of Health, Bethesda, MD, USA).
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2.10. Histofluorescence Staining
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DHE histofluorescence staining was carried out to investigate in situ production of superoxide anion. Briefly, as described previously [27], the tissue slices were balanced in Krebs-HEPES buffer (pH 7.4) for 35 min at 35 °C. Afterward, the sections were soaked in fresh buffer containing 0.01 mM DHE for 2 h at 37 °C. Using an epifluorescent microscope (Carl Zeiss, Göttingen, Germany), digital images of DHE fluorescence were captured with 520–540 nm of wavelength. The images were adjusted to fit a tissue area array of 250 μm2. Ethidium fluorescence intensity was quantified utilizing Image J software (version 1.46; National Institutes of Health, Bethesda, MD, USA). The DHE fluorescence intensity ratio was converted into a percentage of the fluorescence intensity in the control group.
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2.11. Immunohistochemistry
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| 99 |
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The avidin-biotin complex (ABC) method was utilized for immunohistochemistry. In brief, according to previously described methods [28,29], deparaffinized and hydrated sections were reacted with 0.3% hydrogen peroxide (in 100 mM phosphate-buffered saline, pH 7.4) for 20 min at room temperature. After that, the sections were immersed into 5% normal goat, rabbit, or horse serum (Vector Laboratories Inc., Burlingame, CA, USA) for 30 min at room temperature. Next, the tissue slices were immunoreacted with individual primary antibodies for 48 h at 4 °C: sheep anti-Cu, Zn-superoxide dismutase (SOD1), sheep anti-Mn-superoxide dismutase (SOD2), and mouse anti-4-hydroxy-2-nonenal (4-HNE). The sections undergoing immunoreaction were subsequently incubated with each secondary antibody for 2 h at room temperature: goat anti-sheep IgG and horse anti-mouse IgG (Vector Laboratories Inc., Burlingame, CA, USA). Afterward, the sections were exposed to ABC solution (Vector Laboratories Inc., Burlingame, CA, USA) for 1 h at room temperature. For visualization, the sections were reacted with 0.06% DAB (in 100 mM phosphate-buffered saline, containing 0.1% hydrogen peroxide, pH 7.4). Images of the immunoreactive structures were taken using a light microscope (BX53; Olympus, Tokyo, Japan). These digital images were calibrated into an array of 250 μm2 of tissue area. The captured images were converted to 8-bit grayscale with an intensity scale ranging from 0 (black) to 255 (white) to evaluate grayscale intensities. The average optical density of each immunoreactive structure was determined by Image J software. The relative optical density (ROD) was expressed as a percentage of the ROD in the control group.
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2.12. Western Blot Analysis
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Protein was extracted from WAT with RIPA buffer and quantified using the BCA method. Then, 20 μg of protein was separated by 8–10% SDS-PAGE at 100 V for 90 min. Separated proteins were transferred to PVDF membranes by semi-dry transfer cells (Trans-Blot SD Cell; Bio-Rad, Hercules, CA, USA) at 15 V for 30 min. Membranes were blocked with 5% skim milk in TBST for 1 h at room temperature. The membrane was washed 3 times with TBST and incubated overnight at 4 °C with the primary antibody. Afterward, the membrane was rewashed 3 times and incubated with the secondary antibody for 2 h at room temperature. After the incubation, the membrane was washed 3 times, and the specific protein bands were chemiluminescent by ECL solution and visualized with a Western blotting detection system (ImageQuan LAS 500; GE Healthcare, Chicago, IL, USA). The shaded areas of specific bands were quantified using Image J software.
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2.13. Statistical Analysis
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The results were presented as average value ± standard deviation and plotted using GraphPad Prism (version 8.1; GraphPad Software, San Diego, CA, USA). Significance levels were determined by one-way analysis of variance (ANOVA) utilizing SPSS software (version 25.0; Statistical Package for Social Science, Inc., Chicago, IL, USA), and statistical significance was considered at p < 0.05.
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3. Results
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3.1. Quantification of Quercitrin in SO
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| 114 |
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The HPLC chromatograms of SO and quercitrin standards are shown in Figure 1. The quercitrin content was determined to be 10.31 ± 0.31 mg/g by comparing the retention time and signal intensity of the peak spectrum of SO and the standard.
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| 115 |
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| 116 |
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3.2. SO Has No Apparent Cytotoxicity to 3T3-L1 Cells
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| 117 |
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| 118 |
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The cell viability of preadipocytes and adipocytes treated with SO was lower than the control group. However, cell viability was reduced by 11.39% at most in preadipocytes treated with SO for 24 h (Figure 2A) and up to 10.04% in adipocytes treated with SO for 8 days (Figure 2B). The viability of cells treated with all concentrations of SO (100–400 μg/mL) was above 80%, indicating no apparent toxicity to the cells [30].
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| 119 |
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|
| 120 |
+
3.3. SO Reduces Lipid Accumulation and ROS Production in 3T3-L1 Adipocytes
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| 121 |
+
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| 122 |
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SO dose-dependently reduced lipid accumulation in 3T3-L1 adipocytes starting from 100 μg/mL (Figure 3A,C). SO showed a similar lipid accumulation inhibition rate to GC at 200 μg/mL and up to 50% lipid accumulation inhibition rate at 400 μg/mL. SO also dose-dependently reduced ROS production in 3T3-L1 adipocytes (Figure 3B). The inhibitory effect of SO on ROS production in 3T3-L1 adipocytes was higher than that of GC at the same concentration (200 μg/mL).
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| 123 |
+
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| 124 |
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3.4. SO Attenuates Body Weight Gain in HFD-Induced Obese Mice without Affecting Appetite
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| 125 |
+
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| 126 |
+
The average body weight of mice in each group did not differ significantly before diet induction (Figure 4A). Mice in the HFD group (44.31 ± 3.88 g) gained 1.47 times more body weight than the NFD group (30.23 ± 1.33 g) after 12 weeks of diet induction (Figure 4B). Compared to the HFD group, the group supplemented with 100 mg/kg/day (SO100) of SO lost 9.28% of body weight, 12.34% in the 200 mg/kg/day group (SO200), 14.90% in the 400 mg/kg/day group (SO400), and 11.85% in the GC 200 mg/kg/day group (GC200). Body weights of the SO200, SO400, and GC200 groups were statistically different from the HFD group but insignificant between them. Food and water intake were slightly lower in the SO supplementation group but not statistically different (Figure 4C,D).
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| 127 |
+
|
| 128 |
+
3.5. SO Reduces Adipose Tissue Weight in HFD-Induced Obese Mice
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| 129 |
+
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| 130 |
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Kidney, spleen, and BAT weights showed no significant difference between the HFD and SO supplementation groups (Figure 5A–C). SO supplementation significantly reduced WAT (visceral, epididymal, perirenal, retroperitoneal, and subcutaneous fat) weight compared with the HFD group (Figure 5D). Although the reduction in WAT weight was dose-dependently associated with SO, it was not significant.
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| 131 |
+
|
| 132 |
+
3.6. SO Ameliorates Hepatic Steatosis and Adipocyte Hypertrophy in HFD-Induced Obese Mice
|
| 133 |
+
|
| 134 |
+
Liver weight was significantly lower in SO200 and SO400 groups than in the HFD group but insignificant between SO200 and SO400 groups (Figure 6A). Liver H&E staining showed that SO supplementation alleviated the abnormal accumulation of hepatic fat; in particular, the liver tissue of the SO400 group tended toward the NFD group (Figure 6B). H&E staining of epididymal adipose tissue showed hypertrophy of adipocytes induced by the HFD (Figure 6C). SO supplementation reduced adipocyte size in a dose-dependent manner, and the cell size of the SO400 group was similar to the NFD group (Figure 6D).
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| 135 |
+
|
| 136 |
+
3.7. SO Improves Serum Biochemical Parameters in HFD-Induced Obese Mice
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| 137 |
+
|
| 138 |
+
Aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels were not significantly different between the SO supplementation group and the HFD group (Figure 7A,B). SO supplementation dose-dependently reduced elevated serum glucose (GLU), total cholesterol (TC), TG, and leptin levels due to the HFD, but only the SO400 group was statistically different from the HFD group (Figure 7C–F).
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| 139 |
+
|
| 140 |
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3.8. SO Increases WAT Antioxidant Enzyme Expression and Decreases Oxidative Stress in HFD-Induced Obese Mice
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| 141 |
+
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| 142 |
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The expression levels of antioxidant enzymes SOD1 and SOD2 in the HFD group were significantly lower than those in the NFD group by immunohistochemistry on WAT (Figure 8A,B). SO supplementation re-increased the expression of SOD1 and SOD2 but not significantly between SO200 and SO400 groups. SO supplementation above 200 mg/kg reduced ROS production and lipid peroxidation end products as oxidative stress markers (Figure 8C,D). Similar to the expression trend of antioxidant enzymes, there was no significant difference between SO200 and SO400 groups.
|
| 143 |
+
|
| 144 |
+
3.9. SO Improves WAT Energy Metabolism and Promotes Thermogenesis in HFD-Induced Obese Mice
|
| 145 |
+
|
| 146 |
+
Supplementation with SO at doses higher than 200 mg/kg significantly increased adiponectin expression levels and promoted phosphorylation of AMP-activated protein kinase (AMPK) and acetyl-CoA carboxylase (ACC) compared to the HFD group (Figure 9A). SO supplementation above 200 mg/kg also increased the expression of peroxisome proliferator-activated receptor alpha (PPARα) and UCP-1 expression levels in a dose-dependent manner (Figure 9B). In addition, SO dose-dependently increased the expression level of carnitine palmitoyltransferase I (CPT-1), but no further changes were observed at 400 mg/kg.
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| 147 |
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|
| 148 |
+
4. Discussion
|
| 149 |
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| 150 |
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In a previous study, we isolated and characterized isorhamnetin-3-O-d-glucuronide and ellagic acid from SO as potential anti-adipogenic active compounds and validated their lipid accumulation inhibitory effect in 3T3-L1 adipocytes [31]. However, the anti-adipogenic mechanism of SO needs to be clarified, and its effect on obesity-related oxidative stress has been less studied. In this study, we found that SO as a potent antioxidant not only decreased ROS production in 3T3-L1 adipocytes and WAT but also reduced lipid accumulation and cellular hypertrophy, which were associated with the regulation of SO in antioxidant enzymes (SOD1 and SOD2), energy metabolism (AMPK pathway), and thermogenic factors (PPARα, CPT-1, and UCP-1). Furthermore, the administration of SO in HFD-induced obese mice reduced body weight gain, improved hepatic steatosis, lowered serum glucose and lipids, and restored dysregulated adipokines (leptin and adiponectin).
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| 151 |
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| 152 |
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The antioxidant properties of SO are derived from its phenolic acid and flavonoid compounds [32]. In addition to quercitrin, which was used as an index ingredient in this study, the main components in the leaves and stems of SO contained ellagic acid, caffeoylquinic acid, rosmarinic acid, ursolic acid, sanguisorbic acid, catechin, quercetin, kaempferol, sanguisorbigenin, and sanguiin [17,33]. These compounds exhibited antioxidant activity, among which ellagic acid [34], caffeoylquinic acid [35], rosmarinic acid [36], ursolic acid [37], catechin [38], and quercetin [39] have been reported to enhance SOD activity in obese mice. SOD facilitates the transformation of superoxide radicals into H2O2, which is then converted to water through the assistance of catalase (CAT) and glutathione peroxidase (GPx) [40]. These enzymes collectively establish the antioxidant defense mechanism to counteract free radicals generated by normal mitochondria metabolism [13]. However, excess energy can overload the mitochondria and disrupt the antioxidant defense system [41]. Previous studies have shown that sustained oxidative stress downregulates the expression of thermogenic factors [42]. Although ROS is one of the necessary conditions for mitochondrial thermogenesis [43], respiratory thermogenesis is only possible if the normalized mitochondrial function is ensured. The imbalance of ROS also leads to the ectopic accumulation of TG and the disturbance of energy metabolism caused by mitochondrial dysfunction [44]. The study found that the HFD reduced SOD1 and SOD2 expression in WAT and increased ROS and lipid peroxides (Figure 8A,B). SO supplementation reduced ROS production and oxidative stress by restoring SOD1 and SOD2 expression in WAT to protect mitochondrial function (Figure 8C,D).
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| 153 |
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|
| 154 |
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Increased ROS in adipocytes leads to the dysregulation of adipokines [10]. In this study, serum leptin levels were notably elevated in the HFD group compared to the NFD group (Figure 7F). The elevated circulating leptin levels can lead to leptin resistance and chronic inflammation [45]. SO supplementation effectively lowered serum leptin levels, although they did not return to normal. Adiponectin is a positively regulated adipokine in adipocytes closely related to insulin sensitivity, skeletal muscle cell glucose uptake, fatty acid β-oxidation in adipocytes, and mitochondrial biogenesis [46]. We observed a significant reduction in adiponectin expression in the WAT of HFD-induced mice (Figure 9A). SO supplementation resulted in increased adiponectin secretion in mice WAT accompanied by decreased serum glucose and lipid levels (Figure 7C–E). These results are similar to previous studies in that the antioxidant capacity of natural products alleviated the oxidative stress increased by an HFD to restore adipokine levels [15].
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| 155 |
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|
| 156 |
+
Adiponectin is also an activator of AMPK and an active ligand of PPARα [47]. AMPK as a regulator of energy homeostasis promotes energy synthesis and suppresses energy expenditure processes, in other words, stimulating lipolysis and inhibiting lipogenesis [48]. We speculated that the AMPK pathway was activated due to the increased adiponectin expression in the WAT of obese mice induced by an HFD (Figure 9A). Activation of AMPK causes direct phosphorylation of downstream ACC to prevent carboxylation of acetyl-CoA to malonyl-CoA [49]. Malonyl-CoA competitively inhibits the activity of CPT-1, which is responsible for facilitating the mitochondrial transmembrane movement of fatty acids (FAs) [50]. SO supplementation enhanced CPT-1 activity and allowed enough FAs to be transported as substrates to mitochondria for β-oxidation and respiratory thermogenesis (Figure 9B).
|
| 157 |
+
|
| 158 |
+
UCP-1 is responsible for the uncoupling respiratory chain in the inner mitochondrial membrane and allows fatty acid oxidation [51]. When free FAs bind to UCP-1, they cause conformational changes in the activated proteins, leading to the dissipation of the electrochemical gradient in the inner mitochondrial membrane and promoting heat production in the mitochondria [52]. AMPK can promote UCP-1 expression through downstream cascades [53], while PPARα acts as a transcription factor binding to the PPAR-responsive element to facilitate UCP-1 transcription and mitochondrial fatty acid oxidation [54]. Similar to previous studies, SO supplementation did not change the weight of BAT, but the weight of WAT decreased significantly (Figure 5C,D) [55]. This suggests that the SO activates thermogenesis through PPARα and AMPK-induced UCP-1 expression in WAT, thereby attenuating adipocyte hypertrophy and abnormal lipid accumulation.
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| 159 |
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|
| 160 |
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5. Conclusions
|
| 161 |
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|
| 162 |
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Available data suggest that at least 200 mg/kg of SO can reduce ROS production and oxidative stress by increasing antioxidant enzyme expression and improving energy metabolism by activating the AMPK pathway to reduce mitochondrial load. In addition, phosphorylation of AMPK and upregulation of PPARα induced not only UCP-1 expression but also promoted CPT-1 activity to provide FAs as a substrate for oxidative and respiratory thermogenesis. In conclusion, SO improves obesity symptoms and the accompanying oxidative stress without significant toxicity and affecting appetite and is an alternative material for preventing and treating obesity.
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|
| 164 |
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Author Contributions
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| 165 |
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|
| 166 |
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Conceptualization, I.-J.K.; methodology, Y.Z., S.-Y.L. and Y.L.; software, Y.Z., S.-Y.L. and T.-K.L.; validation, Y.L.; formal analysis, I.-J.K., J.E.K. and T.H.K.; investigation, Y.Z., S.-Y.L., and T.-K.L.; resources, J.E.K. and T.H.K.; data curation, S.-Y.L.; writing—original draft preparation, Y.Z.; writing—review and editing, I.-J.K.; visualization, Y.Z. and T.-K.L.; supervision, I.-J.K.; project administration, I.-J.K.; funding acquisition, I.-J.K. All authors have read and agreed to the published version of the manuscript.
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|
| 168 |
+
Institutional Review Board Statement
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| 169 |
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|
| 170 |
+
The animal study protocol was approved by the Institutional Animal Care and Use Committee (IACUC) of Hallym University (approval number: Hallym 2021-11).
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| 171 |
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| 172 |
+
Informed Consent Statement
|
| 173 |
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|
| 174 |
+
Not applicable.
|
| 175 |
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|
| 176 |
+
Data Availability Statement
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| 177 |
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|
| 178 |
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The data presented in this study are available from the corresponding author upon request.
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| 180 |
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Conflicts of Interest
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| 181 |
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|
| 182 |
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Ju Yeong NS Co., Ltd. and its employees provided samples, some reagents, and instruments used in this study and helped us complete the HPLC chromatographic test. Therefore, we listed two employees J.E.K. and T.H.K., as co-authors. The authors declare no conflict of interest.
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Figure 1 HPLC chromatograms of SO and quercitrin. The identity of quercitrin in SO was determined by comparing the retention times with standards.
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| 186 |
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Figure 2 Effect of SO on cell viability of 3T3-L1 preadipocytes (A) and adipocytes (B). Values are expressed as mean ± SD of experiments (n = 3). Different alphabets indicate significant differences at the level of p < 0.05.
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| 188 |
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Figure 3 Effect of SO on lipid accumulation (A) and ROS production (B) in 3T3-L1 adipocytes. (C) Oil red O staining on day 8 of adipocyte differentiation. Values are expressed as mean ± SD of experiments (n = 3). Different alphabets indicate significant differences at the level of p < 0.05.
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Figure 4 Effects of SO on body weight and diet in HFD-induced obese mice: (A) body weight change trend of mice during the experiment; (B) final body weight of mice at the end of the experiment; (C,D) food intake and water intake of mice during the experiment. GC200, HFD supplemented with 200 mg/kg/day of GC; SO100, HFD supplemented with 100 mg/kg/day of SO; SO200, HFD supplemented with 200 mg/kg/day of SO; SO400, HFD supplemented with 400 mg/kg/day of SO. Values are expressed as mean ± SD of experiments. Different letters indicate significant differences at the level of p < 0.05.
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Figure 5 Effect of SO on organ weights in HFD-induced obese mice: (A) kidney weight; (B) spleen weight; (C) brown adipose tissue weight; and (D) white adipose tissue weight (visceral, epididymal, perirenal, retroperitoneal, and subcutaneous fat). GC200, HFD supplemented with 200 mg/kg/day of GC; SO100, HFD supplemented with 100 mg/kg/day of SO; SO200, HFD supplemented with 200 mg/kg/day of SO; SO400, HFD supplemented with 400 mg/kg/day of SO. Values are expressed as mean ± SD of experiments. Different letters indicate significant differences at the level of p < 0.05.
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Figure 6 Effects of SO on hepatic steatosis and adipocyte hypertrophy in HFD-induced obese mice: (A) liver weight; (B) quantification of adipocyte area in white adipose tissue; (C) H&E staining of the liver; and (D) H&E staining of white adipose tissue. GC200, HFD supplemented with 200 mg/kg/day of GC; SO100, HFD supplemented with 100 mg/kg/day of SO; SO200, HFD supplemented with 200 mg/kg/day of SO; SO400, HFD supplemented with 400 mg/kg/day of SO. The scale bar represents a length of 50 μm. Values are expressed as mean ± SD of experiments. Different letters indicate significant differences at the level of p < 0.05.
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Figure 7 Effects of SO on serum biochemical parameters in HFD-induced obese mice: (A) serum aspartate aminotransferase (AST) level; (B) serum alanine aminotransferase (ALT) level; (C) serum glucose level (GLU) level; (D) serum total cholesterol (TC) level; (E) serum triglyceride (TG) level; (F) serum leptin level. GC200, HFD supplemented with 200 mg/kg/day of GC; SO100, HFD supplemented with 100 mg/kg/day of SO; SO200, HFD supplemented with 200 mg/kg/day of SO; SO400, HFD supplemented with 400 mg/kg/day of SO. Values are expressed as mean ± SD of experiments. Different letters indicate significant differences at the level of p < 0.05.
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Figure 8 Effect of SO on oxidative stress in WAT of HFD-induced obese mice: (A,B) SOD1 and SOD2 expression measured by immunohistochemistry in WAT; (C) lipid peroxidation products determined by immunohistochemistry of 4HNE in WAT; (D) ROS production measured by histofluorescence staining of DHE in WAT. GC200, HFD supplemented with 200 mg/kg/day of GC; SO100, HFD supplemented with 100 mg/kg/day of SO; SO200, HFD supplemented with 200 mg/kg/day of SO; SO400, HFD supplemented with 400 mg/kg/day of SO. The scale bar represents a length of 50 μm. Values are expressed as mean ± SD of experiments. Different letters indicate significant differences at the level of p < 0.05.
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Figure 9 Effects of SO on energy metabolism and thermogenesis in WAT of HFD-induced obese mice: (A) adiponectin and AMPK pathways; (B) thermogenesis-related factors. GC200, HFD supplemented with 200 mg/kg/day of GC; SO100, HFD supplemented with 100 mg/kg/day of SO; SO200, HFD supplemented with 200 mg/kg/day of SO; SO400, HFD supplemented with 400 mg/kg/day of SO. Values are expressed as mean ± SD of experiments. Different letters indicate significant differences at the level of p < 0.05.
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Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
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| 1 |
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==== Front
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Int J Mol Sci
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| 4 |
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Int J Mol Sci
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| 5 |
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ijms
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International Journal of Molecular Sciences
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1422-0067
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MDPI
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| 9 |
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| 10 |
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10.3390/ijms24087120
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ijms-24-07120
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Article
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Tetrahydrocannabivarin (THCV) Protects Adipose-Derived Mesenchymal Stem Cells (ASC) against Endoplasmic Reticulum Stress Development and Reduces Inflammation during Adipogenesis
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| 14 |
+
Kowalczuk Anna Methodology Writing – original draft Supervision 1
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| 15 |
+
Marycz Krzysztof Investigation Writing – review & editing Supervision 23*
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| 16 |
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https://orcid.org/0000-0003-4765-4776
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Kornicka Justyna Formal analysis Writing – original draft Visualization 4
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| 18 |
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Groborz Sylwia Methodology Validation Formal analysis Data curation Writing – original draft 23
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https://orcid.org/0000-0002-8667-908X
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| 20 |
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Meissner Justyna Writing – review & editing Supervision 3
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https://orcid.org/0000-0001-8189-9545
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Mularczyk Malwina Resources Writing – review & editing Funding acquisition 23
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| 23 |
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Damiano Fabrizio Academic Editor
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+
1 National Medicines Institute, Chełmska 30/34, 00-725 Warsaw, Poland
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2 International Institute of Translational Medicine, Jesionowa 11, 55-114 Malin, Poland
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3 Department of Experimental Biology, Faculty of Biology and Animal Science, Wrocław University of Environmental and Life Sciences, Norwida 27B, 50-375 Wrocław, Poland
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4 Faculty of Electronics, Photonics and Microsystems, Wrocław University of Science and Technology, Smoluchowskiego 25, 50-372 Wrocław, Poland
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* Correspondence: krzysztof.marycz@upwr.edu.pl
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12 4 2023
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| 30 |
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4 2023
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| 31 |
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24 8 712024 2 2023
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| 32 |
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01 4 2023
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05 4 2023
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+
© 2023 by the authors.
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2023
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https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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The endoplasmic reticulum (ER) fulfills essential duties in cell physiology, and impairment of this organelle’s functions is associated with a wide number of metabolic diseases. When ER stress is generated in the adipose tissue, it is observed that the metabolism and energy homeostasis of the adipocytes are altered, leading to obesity-associated metabolic disorders such as type 2 diabetes (T2D). In the present work, we aimed to evaluate the protective effects of Δ9-tetrahydrocannabivarin (THCV, a cannabinoid compound isolated from Cannabis sativa L.) against ER stress in adipose-derived mesenchymal stem cells. Our results show that pre-treatment with THCV prevents the subcellular alteration of cell components such as nuclei, F-actin, or mitochondria distribution, and restores cell migration, cell proliferation and colony-forming capacity upon ER stress. In addition, THCV partially reverts the effects that ER stress induces regarding the activation of apoptosis and the altered anti- and pro-inflammatory cytokine profile. This indicates the protective characteristics of this cannabinoid compound in the adipose tissue. Most importantly, our data demonstrate that THCV decreases the expression of genes involved in the unfolded protein response (UPR) pathway, which were upregulated upon induction of ER stress. Altogether, our study shows that the cannabinoid THCV is a promising compound that counters the harmful effects triggered by ER stress in the adipose tissue. This work paves the way for the development of new therapeutic means based on THCV and its regenerative properties to create a favorable environment for the development of healthy mature adipocyte tissue and to reduce the incidence and clinical outcome of metabolic diseases such as diabetes.
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| 38 |
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| 39 |
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endoplasmic reticulum (ER)
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| 40 |
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Δ9-tetrahydrocannabivarin
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| 41 |
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adipocyte
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| 42 |
+
UPWR 2.0: International and interdisciplinary programme of development of Wrocław University of Environmental and Life SciencesEuropean Social Fund under the Operational Program Knowledge Education DevelopmentPOWR.03.05.00-00-Z062/18 National Medicines Institute in Warsaw and the International Institute of Translational Medicine in Malin, PolandPublication financed by the project “UPWR 2.0: International and interdisciplinary programme of development of Wrocław University of Environmental and Life Sciences”, co-financed by the European Social Fund under the Operational Program Knowledge Education Development, under contract No. POWR.03.05.00-00-Z062/18 of 4 June 2019. The research has also been co-financed by the National Medicines Institute in Warsaw and the International Institute of Translational Medicine in Malin, Poland as part of the project “Assessment of insulin sensitivity of selected compounds based on CBD and modulating the activity of the PTP1B pathway”.
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| 43 |
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==== Body
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pmc1. Introduction
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| 45 |
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The endoplasmic reticulum (ER) is an intracellular transport system that participates in a number of essential cellular processes, such as protein synthesis, folding and maturation, as well as in many other signaling pathways. The function of this complex system may be partially impaired by genetic or environmental factors, leading to ER stress [1]. Substantial ER stress activates a complex signaling pathway known as the unfolded protein response (UPR), which drives the cell into the apoptotic or autophagic pathways. This process is transduced and executed by three transmembrane proteins: PKR-like ER kinase (PERK), inositol-requiring enzyme 1 (IRE1), and activating transcription factor 6 (ATF6) [2]. Excessive ER stress is directly associated with several diseases, such as diabetes, insulin resistance, inflammation, atherosclerosis, heart diseases, and neurodegenerative disorders such as Alzheimer’s disease [3].
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+
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The ER stress dysfunction of adipose tissue (AT) plays a critical role in the development of obesity-associated metabolic disorders such as type 2 diabetes (T2D) through regulation of the metabolism and energy homeostasis [4]. Obesity is a global health problem, and it is expected that by 2025, more than 300 million people will develop T2D as a result of excessive fat accumulation in adipose tissues [5]. In individuals with obesity, AT is characterized by an abnormal production of cytokines and other pro-inflammatory molecules [6]. For adipose tissue to reach its full maturity and develop its endocrine and immunological function, the process of adipogenesis is activated, where precursors defined as adipose-derived mesenchymal stem cells (ASCs) are differentiated into mature adipocytes [7]. Recent studies show that both in mice and humans, there is a correlation between obesity and impaired ASCs migration, proliferation, and angiogenic potential, hence reducing the therapeutic potential of these cells [8]. Therefore, given the association of ASCs with metabolic disorders such as obesity and obesity-related metabolic diseases, methods for positive ASC stimulation and promotion of positive differentiation are being carefully studied [9,10]. Substantial research efforts have also been undertaken to unravel the correlation between increased ER stress in ASC and conditions such as obesity or insulin resistance [11].
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+
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The endocannabinoid system (ECS) is a compound cell-signaling system identified in the 1990s during research on the main compound derived from Cannabis sativa L.—Δ 9-tetrahydrocannabinol (THC) [12]. ECS consists of the G-protein-coupled cannabinoid receptors type 1 (CB1R) and type 2 (CB2R), their endogenous ligands (endocannabinoids), and the enzymes responsible for their synthesis and degradation. The main endocannabinoids are anandamide (arachidonoylethanolamide, AEA) and 2-arachidonoylglycerol (2-AG) [13]. The endocannabinoid signaling system is located in the body both centrally (brain) and peripherally (adipose tissue, liver, pancreas, skeletal muscle, gastrointestinal track) and is involved in multiple physiological processes, including maintenance of the energy balance by lipid and glucose metabolism [14]. It has been suggested that ECS plays an important role in adipogenesis and lipogenesis, participating in the development of obesity and type 2 diabetes [15]. It has been shown that CB1 receptor stimulation and its increased mRNA levels lead to inflammation and free fatty acid (FFA) accumulation in cultured adipocytes [14]. Since ECS receptors are expressed in ASCs, their proliferation, differentiation, and overall plasticity can be modulated by either the activation or inhibition of CB1 or CB2, thus modulating the activity and morphology of the mature adipose tissue.
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+
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Cannabis sativa is a distinctive plant mostly known for its primary psychoactive constituent delta-9-tetrahydrocannabinol (THC). Above that, the plant comprises about 100 different phytocannabinoids including Δ9-tetrahydrocannabivarin (Δ9-THCV), cannabinol (CBN), cannabidiol (CBD), cannabidivarin (CBDV), cannabigerol (CBG), and cannabichromene (CBC). Due to their ability to interact with CB1 and CB2 receptors as their antagonists and inverse agonists, cannabinoids show broad prospects as therapeutic factors in many metabolic diseases, such as obesity, insulin resistance, multiple sclerosis, anorexia, inflammation, epilepsy, schizophrenia, glaucoma, and Parkinson’s and Alzheimer’s disease [16,17]. Among the cannabinoid compounds, the non-psychoactive Δ9-tetrahydrocannabivarin (Δ9-THCV) has gained special interest for its unique properties and non-psychoactive effects, which set it apart from its psychoactive analog, THC. Recent studies indicated that THCV-CB1 receptor antagonists/inverse agonists ameliorated insulin sensitivity and improved glucose tolerance in two mouse models of obesity [18], reduced accumulated lipid levels in vitro in a hepatosteatosis model and in adipocytes [19], and decreased fasting plasma glucose with improved pancreatic β-cell function in a randomized, double-blind, placebo-controlled study on type 2 diabetes [20]. Nonetheless, the anti-obesity feature of THCV is still not well understood, and further research is necessary to confirm the potential therapeutic properties of Δ9-THCV for the treatment of obesity, metabolic syndrome and type 2 diabetes.
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| 53 |
+
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In the present work, we introduce an alternative approach based on a pretreatment with Δ9-tetrahydrocannabivarin to overcome issues related to the molecular impairment of ASC and subsequent functions of mature adipocytes. The aim of this strategy is to prevent ER stress and inflammation and its downstream harmful effects, including the development of obesity-associated metabolic disorders such as type 2 diabetes (T2D).
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+
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2. Results
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2.1. Evaluation of Morphology and Proliferation Rate
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Cell morphology in control and experimental (TUN and THCV) conditions was assessed by confocal microscopy. In this work, we used tunicamycin to induce ER stress; tunicamycin is an inhibitor of UDP-N-acetylglucosamine-dolichol phosphate N-acetylglucosamine-1-phosphate transferase (GPT), therefore blocking the initial step of glycoprotein biosynthesis in the ER. This leads to an accumulation of unfolded glycoproteins in the ER, leading to ER stress. We observed that cells treated with tunicamycin presented deformed cell nuclei with an irregular size and with a more condensed chromatin (Figure 1A). The distribution of F-actin, assessed with the phalloidin staining, was also altered in the tunicamycin-treated cells (Figure 1A). We found reduced actin fibers with the abnormal organization in the TUN group in comparison to the control group. Moreover, the number of mitochondria were reduced and localized near the nuclei compared to the control group, where the mitochondrial network was expanded (Figure 1A). Interestingly, pre-treatment with different doses of THCV successfully protected cells against ER stress, as evidenced by the re-establishment of the mitochondria network, the cytoskeleton integrity and the morphology of the cell nuclei (Figure 1A). We also observed that different concentrations of THCV in the range of 0–10 μM did not affect either cell viability or population doubling time (Figure 1B,C); however, THCV used at 50 and 100 μM reduced cell viability by up to 40% (Figure 1B).
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| 61 |
+
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| 62 |
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To further study the effect of THCV on cell proliferation, we performed the scratch assay, which showed that the pre-treatment of HuASCs with THCV at concentrations of 1 µM and 5 µM promoted cell migration after 12 h compared to the TUN group (Figure 1D); after 48 h of treatment, cell expansion in the THCV1 and THCV5 groups was around 90% compared to cells treated with tunicamycin (5%) (Figure 1D). Intriguingly, the β-galactosidase activation assay in the HuASCs revealed that THCV reduced the number of age-senescence cells compared to the control group and the tunicamycin-treated group (Figure 1E). Additionally, we investigated the influence of different doses of THCV on the cell proliferation of the HuASCs by quantifying the proliferation marker KI-67. The immunostaining experiment revealed a reduction of the number of KI-67-positive cells in the TUN group compared to the non-treated group (Figure 1F). Interestingly, pre-treated cells with 1 μM THCV presented similar levels of KI-67-positive cells compared to cells treated with tunicamycin (Figure 1F); however, a higher dose of THCV (5 μM) appears in the image more visibly, which may indicate a greater amount of KI-67-positive cells compared to the TUN-treated and non-tread group (Figure 1F).
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| 63 |
+
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| 64 |
+
We then analyzed the effect of THCV in the cell’s colony-forming capacity as experimental evidence of the proliferation-inducing effect of THCV. We observed that tunicamycin inhibited cell proliferation and the ability to form colonies, while pre-treatment with THCV in any tested concentration enhanced cell division, evidenced by the higher number of CFUs detected in the clonogenic assay (Figure 1G).
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| 65 |
+
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| 66 |
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In order to study cell proliferation at the transcriptional level, the relative expression of miRNA involved in cell proliferation was assessed by qRT-PCR. Results showed that in the tunicamycin-induced ER stress group, the expression of miR101 1/2 was significantly enhanced in comparison to the experimental and control groups (Figure 1H). The opposite phenomenon was noticed in the expression of miR17, where transcript levels were upregulated not only in the TUN group, but also in the THCV groups (Figure 1I).
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| 67 |
+
|
| 68 |
+
The data obtained indicate that THCV used in concentrations of 1 μM and 5 μM promotes cell proliferation, as well as their migration and clonogenic potential.
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| 69 |
+
|
| 70 |
+
2.2. Evaluation of Apoptosis
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| 71 |
+
|
| 72 |
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To establish whether pre-treatment with THCV modulates cell death, the gene expression of some apoptotic markers was assessed by qPCR. Results clearly showed that THCV reduced p53 expression compared to the TUN group (Figure 2A). Moreover, we observed that p21 was upregulated upon treatment with THCV 1 μM, while THCV at 5 μM reduced its expression levels, with no differences compared to the TUN condition (Figure 2B). Regarding the gene expression of Casp9, it was increased in response to the TUN group, but the addition of THCV 5 μM reestablished the control levels (Figure 2C). Furthermore, the results showed an increased expression of BCL2 in cells pre-treated with different doses of THCV (Figure 2D). Interestingly, we observed an upregulation of BAX in both the TUN and THCV 1 μM groups compared to THCV 5 μM (Figure 2E). In order to confirm the role of THCV in the modulation of the apoptotic cell death pathway, we performed an immunostaining of Casp3, observing an increased number of Casp3-positive cells in the TUN group compared to the control group (Figure 2G). Most importantly, THCV at 1 μM and 5 μM decreased the Casp3 signal, indicating that THCV partially protects from tunicamycin-induced apoptosis (Figure 2G). This finding was supported by the data obtained from the qRT-PCR analysis and the Western blot analysis, where the expression of caspase-3 was decreased by THCV at the gene (Figure 2H) and protein level (Figure 2I). To support the results obtained in the apoptosis experiments, we performed the Muse® Annexin V & Dead Cell analysis and the Muse® MultiCaspase analysis, which showed significant differences in the percentage of live cells between TUN and the THCV conditions (Figure 2J,K). Additionally, we found that 10% of the cells were caspase-3-positive in the tunicamycin-treated group, while only 1% were caspase-positive cells in the THCV group (Figure 2J,K). THCV treatment of HuASCs reduced the caspase-3-positive cells from 15% to 5% (## p < 0.01 for THCV1 and ### p < 0.001 for THCV5).
|
| 73 |
+
|
| 74 |
+
2.3. Evaluation of ER Stress
|
| 75 |
+
|
| 76 |
+
We then aimed to evaluate the effect of THCV on tunicamycin-induced ER stress with different approaches. First, we found that tunicamycin induced a rearrangement of the ER network and the nuclei shape compared to the control condition, while pre-treatment with THCV partially restored these tunicamycin-induced effects (Figure 3A). These results were supported by the observation of the upregulation of the UPR-genes PERK, IRE, ATF6, eIF2-α, CHOP and XBP1 by qRT-PCR (Figure 3B–G). It is important to note that PERK expression was decreased in the THCV pre-treated condition compared to the TUN group (Figure 3B). Interestingly, the expression of IRE and ATF6 was downregulated to a greater extent in the THCV 1 μM condition compared to the THCV 5 μM group (Figure 3C,D). Furthermore, we found that THCV application significantly reduced CHOP, XBP and eIF2-α gene expression compared to the TUN condition (Figure 3E–G). These findings were in accordance with the protein expression analysis, where we found that the eIF2-α protein was upregulated in the TUN group compared to the control and subsequently downregulated in the presence of THCV (Figure 3H).
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| 77 |
+
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| 78 |
+
2.4. Evaluation of Inflammation
|
| 79 |
+
|
| 80 |
+
We then sought to study the inflammatory response in native adipogenesis conditions by analyzing the gene expression of different biomarkers. We found that the expression of the anti-inflammatory genes TGFβ and IL-10 was decreased in response to TUN and THCV (Figure 4A,B). Interestingly, IL-13 expression was upregulated in the TUN group, and treatment with THCV reestablished the control condition expression level (Figure 4C). Importantly, we found that tunicamycin increased IL-1β and IL-6 gene expression, and treatment with THCV at 5 μM decreased the tunicamycin-induced IL-1β (Figure 4D,E). Surprisingly, IL-6 gene expression in THCV 5 μM was downregulated compared to the TUN condition, which increased the basal IL-6 expression levels (Figure 4F). However, the analysis of the expression at the protein level revealed that IL-6 was downregulated upon pre-treatment with THCV at 5 μM (Figure 4G).
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| 81 |
+
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| 82 |
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Additionally, micro-RNA expression was evaluated. Intriguingly, in the THCV pre-treated group, the relative expression of miR 16-5p was increased compared to the TUN group (Figure 4H). Furthermore, in each group, we observed an increased expression of miR203b (Figure 4I). Interestingly, in the TUN group, miR21 expression was downregulated, but in the THCV 1 μM and THCV 5 μM group, it was increased (Figure 4J). We also observed an upregulated expression of miR24-3p for both concentrations (Figure 4K). The same phenomenon as that in miR21was observed in miR146-5p expression (Figure 4L).
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| 84 |
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Most importantly, the expression of the pro-inflammatory genes TNF-α (Figure 4M) and IL-6 (Figure 4N) as well as the protein levels of IL-6 (Figure 4O) were decreased after pre-treatment with THCV. IL-4 was increased in the adipogenic conditions when treated with tunicamycin, while pre-treatment with THCV 5 μM decreased the expression of that gene (Figure 4P).
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| 85 |
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| 86 |
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3. Discussion
|
| 87 |
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|
| 88 |
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The pharmacological and prophylactic application of cannabinoids has a huge therapeutic potential in degenerative diseases of the nervous system and blood system and in obesity. However, the effects of individual compounds isolated from marijuana are not well understood [18,21,22]. In this study, the protective properties of THCV were investigated. Here, we describe very promising effects of THCV on HuASCs morphology, expansion, cell senescence, apoptosis, inflammation and protection against ER stress. Moreover, we found that the pre-treatment of THCV has strong anti-inflammatory properties in cells during adipogenesis, which may prove to be a crucial and fundamental aspect in the treatment of obesity.
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| 89 |
+
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| 90 |
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It is been widely known that ER stress induced with tunicamycin stimulates the cellular response (UPR), leading to cell dysfunction, including proliferation, inflammation, and apoptosis. We found that the pre-treatment of HuASCs with THCV protects against the harmful effects of ER stress while preserving natural cell morphology, similar population doubling time (PDT) and expansion properties. In fact, we revealed that THCV protects cells against senescence and stimulates cells for increased proliferation and colony formation. Interestingly, the opposite phenomenon was shown by Hohmann T et al. [23], where they observed that the application of cannabinoids had an influence on cell motility, morphology and actin organization in cancer cells, showing anti-cancer properties. Our data indicate that cannabinoids, and in particular THCV, have a huge protective potential in terms of increasing the ability of MSCs to proliferate and migrate, which is necessary during the regeneration of damaged cells in obesity and other degenerative diseases. To our knowledge, no study so far has been presented on THCV’s effects on ER-stress-induced MSC. However, we speculate that the obtained data in this study are the result of cell type and are closely related to the presence of CB1 receptors on the surface of specialized cells [24].
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| 91 |
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| 92 |
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One of the most important consequences of the disruption of cellular homeostasis caused by tunicamycin is increased cellular stress and the activation of the apoptosis pathway. As we have shown, the implementation of higher doses of the cannabinoid prior to the application of tunicamycin resulted in reduced levels of pro-apoptotic mRNAs, in particular p53, p21, BAX and caspases (Casp3, Casp6 and Casp9), known apoptosis activators. Moreover, we showed a reduced percentage of caspase-3-positive cells as well as a reduced percentage of early and late apoptotic HuASCs at both 1 µM and 5 µM, further supporting the protective properties of THCV. On the other hand, according to the latest data, cannabinoids have strong anti-cancer properties, which are revealed by the induction of pro-apoptotic genes in many cancer lines [23,25,26]. These reports make THCV a desirable compound in the fight against altered cancer cells, but as our research shows, THCV can promote cell survival and ER stress protection for stem cells at the same time, making it a compound with high therapeutic potential and a broad spectrum of activity.
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| 93 |
+
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| 94 |
+
Recent studies have shown that endoplasmic reticulum stress and activation of the unfolded protein response (UPR) promotes obesity and insulin signaling disturbance [27]. Indeed, ER stress and UPR activation can cause damage at the beginning of adipose tissue formation, i.e., in the HuASCs, by activating proinflammatory cytokines [28]. Thus, altered progenitor function may disturb their regenerative potential. On the other hand, this can be can be a novel way for targeting those cells as therapy targets in metabolic disorders [29].
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| 95 |
+
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| 96 |
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Here, we investigated the impact of human adipose-delivered stem cells pre-treated with THCV to evaluate their influence on ER stress and inflammation-related genes. Moreover, we found that the expression levels of the key UPR-related factors PERK, IRE, ATF6, CHOP, XBP1 and eIF2-α were reduced in the groups pre-treated with the cannabinoid compound. This finding is in agreement with our previous studies with another cannabinoid—CBD (cannabidiol) [30]. The results obtained when THCV was used at 1 µM and 5 µM were similar between genes, suggesting that both of the concentrations are similarly effective. Although the correlation between ER stress signaling and the cannabinoid system is still not well understood, our research shows for the first time that THCV can protect the ER in HuASCs from degenerative pathway activation and can regulate key ER stress factors. Moreover, we evaluated sufficient markers of the chronic inflammation state, which usually occurs simultaneously with ER stress and activation of the unfolded protein response in many diseases, including diabetes and obesity [31]. The inflammatory status of HuASCs can contribute to pathological changes in adipocytes, resulting in the secretion of adipokines and proinflammatory cytokines, thus disturbing their beneficial regenerative and immunomodulatory properties [32]. Many studies have been published related to this, including our own that focus on improving the potential of HuASCs in regenerative medicine, including low-energy extracorporeal shock wave therapy [33], external magnetic field [34], 5-Azacytydine and resveratrol treatment [35], astaxanthin treatment [36] and many more. Herein, we proposed THCV as another factor for the retention of the unfavorable microenvironment of inflamed HuASCs. While the effect on the inflammatory cytokines in native HuASCs were not significant, we observed that THCV in a 5 µM concentration can effectively retain the expression of pro-inflammatory cytokines during adipogenesis. These findings correspond with other research that revealed that THCV suppresses signs of inflammation and inflammatory pain in mice [37]. On the other hand, we performed PCR analysis for key micro-RNAs involved in inflammation. Pre-treatment with THCV in a 5 µM concentration significantly upregulated the expression of miR 16-5p, which can inhibit the expression of IL-6 and TNF-α as well as apoptosis [38]. Similarly, we observed that the overexpression of miR-203b has a beneficial effect on metabolic homeostasis [39]. We have also found an increase in the expression of miR-21, miR-24-3p and miR-146-5p, which are involved in the activation of a pro-inflammatory macrophage phenotype and the attenuation of inflammation [40,41,42].
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| 97 |
+
|
| 98 |
+
These results strongly suggest that THCV can effectively reduce inflammation in tunicamycin-impaired HuASCs; nevertheless, there is still a need for the further examination of detailed Δ9-Tetrahydrocannabivarin mechanisms of action. For a better understanding of THCV’s impact on adipose tissue development, we examined the inflammatory gene expression levels during adipogenesis. We observed significant downregulation of the key pro-inflammatory cytokines IL-6, TNF-α and IL-4 for HuASCs pre-treated with THCV 5 µM before adipogenesis induction. Surprisingly, for the same groups, we noticed a reduced expression of IL-4, which is well known to suppress adipocyte differentiation [43].
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| 99 |
+
|
| 100 |
+
In summary, our studies revealed that pre-treatment with THCV can mitigate the negative effects of metabolically impaired HuASCs due to a promoting effect on viability, proliferation, and multipotency, as well as due to the improvement of normal morphology. Indeed, we report that THCV can reduce ER stress and inflammation in HuASCs, which can improve their regenerative properties and create a stable environment for the development of healthy adipocyte tissue, thus preventing metabolic diseases such as diabetes. Our research reveals the great potential of plant cannabinoid; nonetheless, there still is a need for further experiments that could explore the molecular mechanisms and receptors by which THCV modulates HuASCs metabolism. Furthermore, we are planning to expand our research with a detailed adipogenesis panel for a greater understanding of THCV’s impact on the differentiation of adipocyte precursor cells in mature adipose tissue. Considering that nowadays there is still a need for metabolic disorder (including obesity) prevention and the enhancement of regenerative outcomes of autologous stem cells, the potential use of the natural plant compound THCV, which is non-psychotropic, could be an effective and economical way to cope with those obstacles.
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4. Materials and Methods
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4.1. Experimental Model Setting
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Human adipose-derived stem cells (HuASCs) were seeded onto 24-well plates at a density of 25 × 104/per well. HuASCs were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM, Gibco Carlsbad, CA, USA) containing 1 g/L glucose, supplemented with 10% fetal bovine serum (FBS, Gibco Carlsbad, CA, USA) and 1% penicillin-streptomycin antibiotic solution (Gibco Carlsbad, CA, USA). Cell cultures were pre-treated with THCV (Cayman Chemical, 18091, Ann Arbor, MI, USA) at a concentration of 1 µM and 5 µM for 24 h (h). Then, the medium was replaced by medium containing 5 mmol/mL tunicamycin (Sigma-Aldrich, T7765, Poznan, Poland).
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+
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For adipose differentiation, HuASCs were cultured in commercially available medium StemPro® Adipogenesis Differentiation (A1007001, Gibco, Thermo Fisher Scientific, Warsaw, Poland). Cells were seeded onto 24-well plates at a density of 20 × 104/per well. The culture medium containing Adipocyte Differentiation Basal Medium, Adipogenesis Supplement and Gentamicin 5 μg/mL was changed every 3 days. Adipose differentiation was conducted for 14 days; then, cells were used for further experiments.
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4.2. Proliferation Rate and Scratch Assay
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Cell viability was evaluated with a resazurin-based assay (TOX8 In Vitro Toxicology Assay Kit, Sigma Aldrich, Poznan, Poland). After 24 h of incubation with THCV at a concentration range of 0–100 μM, culture medium was replaced by medium containing DMEM, 10% FBS, 1% PS and 10% v/v resazurin dye. Cells were incubated for 4 h at 37 °C. The post-cultured medium was transferred to a 96-well plate in a volume of 100 µL in triplicate. The fluorescence was measured at 600 nm and 690 nm as a reference wave. Population Doubling Time (PDT) was calculated using an online algorithm (http://www.doubling-time.com/compute.php (accessed on 10 October 2022)).
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| 114 |
+
In order to test the ability of cells to form colonies, a clonogenic assay was performed. For this purpose, cells were seeded onto a 6-well plate at a density of 1 × 102/per well. Cells were treated with THCV and/or tunicamycin. After 7 days of incubation, cells were fixed with cold 4% PFA (Sigma-Aldrich, P6148), and then colonies were stained with pararosaniline (Sigma-Aldrich, P3750). A series of photos were taken via phone. Colony-forming unit fibroblastic assays (CFU-Fs) were analyzed using the formula described by Kornicka et al. [35].
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| 115 |
+
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| 116 |
+
A scratch assay was performed to evaluate the ability of the cells to migrate. Cells were seeded onto a 96-well plate at a density of 10 × 104/per well. HuASCs were treated with compounds as described above. Then, a horizontal line (scar) in the center of the 96-well plate was made using a 10 μL pipette tip. The pictures were taken with the Zoe Fluorescent Cell Imager after 0 h, 12 h, 24 h and 48 h after scarring. Data were analyzed with ImageJ (version 1.53t, Bethesda, MD, USA) and GraphPad Prism 8 Software (San Diego, CA, USA).
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4.3. Visualization of Cell Organelles
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| 120 |
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A confocal microscope (Observer Z1 Confocal Spinning Disc V.2 Zeiss) was used for the visualization of the cell nucleus, mitochondria, cytoskeleton and the endoplasmic reticulum. The endoplasmic reticulum was stained with 1 µM ER-Tracker™ Green (Invitrogen™, E34251, Thermo Fisher Scientific, Warsaw, Poland). For this, cell medium was changed to Hank’s Balanced Salt Solution with calcium and magnesium containing 1 µM ER-Tracker™ Green. After 30 min (min) of incubation at 37 °C, cells were fixed with cold 4% paraformaldehyde for 30 min. Mitochondria were stained with 100 nM MitoRed dye (Sigma-Aldrich, 53271, Poznan, Poland) on viable cells for 30 min in the dark at 37 °C. Medium containing the MitoRed dye was removed, and cells were washed three times with PBS. Cells were fixed with 4% PFA as described above and permeabilized with 0.1% Triton X-100 (Sigma-Aldrich, 93443, Poznan, Poland) solution for 20 min. The cytoskeleton was stained using atto-488-labeled PI (Sigma-Aldrich, 49409, Poznan, Poland) (1:800 in PBS) for 45 min in the dark at RT. Cell nuclei were stained with DAPI (Invitrogen™, Warsaw, Poland), following the instructions of the manufacturer (Faramount Aq Mounting Medium, Dako).
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+
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4.4. Immunostaining with KI-67
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To visualize the proliferation marker Ki-67, immunostaining with Ki-67 antibody (Abcam, ab15580, Cambridge, UK) was performed. HuASCs were treated with the appropriate compounds for 24 h; then, the medium was removed and cells were fixed with 4% PFA as described above. Samples were washed with PBS twice and permeabilized with 0.05% Triton X-100 in PBS for 15 min at room temperature in the dark. Treated and non-treated cells were incubated overnight with the Ki-67 antibody diluted in 10% Goat Normal Serum (Invitrogen, #31872, Warsaw, Poland) in PBS at 4 °C (1:1000). Cells were washed with PBS three times and incubated with atto-594 secondary antibody (Sigma-Aldrich, 77671) diluted in PBS for 1 h in the dark at RT (1:1000). Cell nuclei were stained with DAPI (Faramount Aq Mounting Medium, Dako). Cells were visualized with a confocal microscope (Observer Z1 Confocal Spinning Disc V.2 Zeiss, Germany), and the obtained data were analyzed using Image J Software (Bethesda, MD, USA).
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+
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4.5. Evaluation of β-Galactosidase Activation
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Cell senescence is a process characterized by a decreased rate of cell division and structural changes in the cell morphology. In order to investigate the senile cell processes, a test with Senescence Cells Histochemical Staining Kit (Sigma Aldrich, Poznan, Poland) was performed according to the manufacturer’s instructions. Cells were treated with 1× Fixation Buffer for 6 min, incubated in Staining Mixture at 37 °C overnight, and visualized with an invert microscope (Leica DM1000 LED, Wetzlar, Germany).
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| 129 |
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| 130 |
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4.6. Gene Expression Analysis
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To evaluate the gene expression of the selected biomarkers (Table 1), cells were homogenized using EXTRazol (Blirt, Gdańsk, Poland) according to the instructions provided by the manufacturer. Total RNA was diluted in DEPC-water, and its concentration and purity were measured using a nanospectrophotometer (Epoch, BioTek, Janki, Poland). A total of 150 ng of RNA were used to synthesize cDNA by using the Takara PrimeScriptTM RT Reagent Kit with gDNA Eraser (Perfect Real Time)(Biokom, Janki, Poland). Real-Time PCR was performed using the SensiFast SYBR & Fluorescein Kit (Bioline, London, UK) according to the instructions provided by the manufacturer. The Real-Time PCR program was set as follows: 95 °C for 2 min, followed by 41 cycles at 95 °C for 15 s, annealing for 30 s and elongation at 72 °C for 15 s. The qPCR results were replicated in 3 independent experiments, and data were statistically analyzed. Relative gene expression was normalized by the housekeeping gene glyceraldehyde 3-phosphate dehydrogenase (GAPDH) using the 2−ΔΔCT method.
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In order to analyze miRNA expression, the Mir-X miRNA First Strand Synthesis Kit (Takara, Biokom, Janki, Poland) was used. Briefly, gDNA traces were removed by incubating the RNA with the DNase I at 37 °C for 30 min. Then, RNA was mixed with mRQBuffer (2X) and mRQEnzyme. The reaction mixture was incubated at 37 °C for 1 h, then at 85 °C for 5 min. The expression level of miRNA was analyzed by Real-Time PCR using the MicroRNA first-strand synthesis kit according to the instructions provided by the manufacturer. Briefly, the reaction mixture contained water, SensiFast SYBR & Fluorescein Kit (Bioline, London, UK), miRNA-specific primer (Table 2), mRQ 3’primer, and cDNA. As a reference sample, U6F primer and U6R primer were used.
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| 135 |
+
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| 136 |
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4.7. Proteins Profiling Using Western Blot
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In order to evaluate protein levels in cells, Western blot analysis was conducted. After 24 h of treatment under different conditions, HuASCs were harvested and homogenized in RIPA buffer on ice. Protein concentrations were verified using the Pierce™ BCA Protein Assay Kit (Life Technologies, Carlsbad, CA, USA). A final concentration of 25 µg of protein was used for each sample and denatured in a 4 × Laemmli loading buffer (Bio-Rad, Hercules, CA, USA) for 5 min at 95 °C prior to electrophoresis. Denatured proteins were separated by SDS-PAGE electrophoresis at 100 V for 90 min in Tris/glycine/SDS buffer and transferred onto polyvinylidene difluoride (PVDF) membranes (Bio-Rad, USA) at 100 V, 250 mA for 1 h at 4 °C in a Tris/glycine buffer/methanol as described previously in Malicka A. et al. [44]. The obtained membranes were then blocked in a 5% non-fat milk solution in TBST for 1 h at room temperature. Membranes were then incubated with the corresponding primary antibody (Table 3) overnight at 4 °C. Excess antibodies were washed with TBST, and membranes were additionally incubated for 1 h at room temperature with HRP-conjugated secondary antibodies (dilution 1:1000 in TBST, Sigma). The chemiluminescent signals were monitored with the ChemiDoc MP Imaging System (Bio-Rad, USA), and the results were analyzed with Image Lab Software (Bio-Rad, Hercules, CA, USA).
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| 140 |
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4.8. Cell Cycle Analysis
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| 142 |
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The analysis of the cell cycle was performed by the Muse® Cell Cycle Kit, following manufacturer’s instructions. Cells were suspended in ice cold 70% ethanol and incubated overnight at −20 °C in the dark. Cells were diluted in the Muse® Cell Cycle Reagent and incubated for 30 min in the dark at RT. The cell cycle was tested using Muse™ Cell Analyzer (Merck, Darmstadt, Germany).
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| 143 |
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|
| 144 |
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4.9. Evaluation of Apoptosis
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| 145 |
+
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| 146 |
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To evaluate cells apoptosis, the Muse® Annexin V & Dead Cell Kit was used, following the manufacturer’s instruction. Treated and non-treated cells were incubated with Muse® Annexin V & Dead Cell reagent in the dark for 20 min at RT. Data were acquired with a Muse™ Cell Analyzer (Merck, Germany).
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| 147 |
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|
| 148 |
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4.10. Statistical Analysis
|
| 149 |
+
|
| 150 |
+
Obtained data were analyzed by one-way variance analysis (ANOVA) using GraphPad Software 8 (San Diego, CA, USA) according to Tukey test. Statistically significant results (comparison of non-treated cells [CTRL] to cells treated with THCV at a concentration of 1 and 5 μM or/and tunicamycin [TUN]) were indicated with asterisks depicted as follows: p < 0.05 (*), p < 0.01 (**) and p < 0.001 (***). Statistically significant results (comparison of treated cells with THCV [THCV1, THCV5] to cells treated with tunicamycin) were indicated with a hash, depicted as follows: p < 0.05 (#), p < 0.01 (##) and p < 0.001 (###). Data were obtained from at least three independent experiments and represented as mean ± standard deviation (SD).
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| 151 |
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|
| 152 |
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Author Contributions
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| 153 |
+
|
| 154 |
+
A.K., K.M., J.K., S.G., J.M. and M.M. participated in writing the manuscript, experiment planning, and cell culture and data analysis; A.K., K.M., J.K., S.G. and J.M. participated in writing the manuscript and experiment planning; S.G., A.K. and J.K. participated in the interpretation of the obtained result, validation, methodology, and data curation, A.K. and J.M. designed and coordinated the study, A.K. and M.M. provided funding. A.K., K.M., J.K., S.G., J.M. and M.M. participated in manuscript reviewing and editing. All authors have read and agreed to the published version of the manuscript.
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| 155 |
+
|
| 156 |
+
Institutional Review Board Statement
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| 157 |
+
|
| 158 |
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The study was approved by the independent ethics committee of the Jagiellonian University, Krakow, Poland (1072.6120.220.2018). Informed consent for surgical treatment was obtained from all patients before the procedure.
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|
| 160 |
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Informed Consent Statement
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| 162 |
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Not applicable.
|
| 163 |
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|
| 164 |
+
Data Availability Statement
|
| 165 |
+
|
| 166 |
+
The data that support the findings of this study are available from the corresponding author, upon reasonable request.
|
| 167 |
+
|
| 168 |
+
Conflicts of Interest
|
| 169 |
+
|
| 170 |
+
The authors declare no conflict of interest.
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| 171 |
+
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Figure 1 Effects of pre-treatment of THCV on HuASCs. (A) Morphological changes of the cells were visualized by confocal microscopy. Cells were stained with DAPI (nuclei), phalloidin (F-actin), and MitoRed dye (mitochondria) (B). The changes in cytoskeleton caused by tunicamycin are marked with white arrow. Cell viability was analyzed by the resazurin-based assay. (C) Population doubling time was determined in the shown conditions. (D) The scratch assay and (G) clonogenic assay were performed. (E) Cell senescence was estimated by the β-galactosidase activation assay. (F) The expression of the proliferation marker KI-67 was assessed with a specific antibody and visualized by confocal microscopy. (H,I) Expression of miR 101 1/2 and miR17 was investigated with qRT-PCR. Data are expressed as mean ± SD. Statistical significance is indicated with an asterisk (*) when comparing the results to the CTRL condition and with a hashtag (#) when compared to the TUN condition; they are depicted as follows: * p < 0.05, ## p < 0.01, ***, ### p < 0.001.
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| 174 |
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Figure 2 THCV protect HuASCs against apoptosis. (A–F,H) Relative expression of apoptosis-related genes (p53, p21, Casp9, BCL2, BAX, Casp6, Casp3) was determined by qRT-PCR. (G) Immunostaining of caspase-3 with a specific antibody. (I) Caspase 3 (Casp3) protein expression by Western blot. (J) Muse® Annexin V & Dead Cell analysis and (K) Muse® Multicaspase to quantify cell viability and apoptotic cells. Data are expressed as mean ± SD. Statistical significance indicated with an asterisk (*) when comparing the results to the CTRL condition and with a hashtag (#) when comparing to the TUN condition; they are depicted as follows: *, # p < 0.05, **, ## p < 0.01, ***, ### p < 0.001.
|
| 175 |
+
|
| 176 |
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Figure 3 THCV reduce ER stress in HuASCs. (A) Representative ER Tracker images of the endoplasmic reticulum staining under the indicated conditions. (B–G) Relative expression of genes related to ER stress (PERK, IRE, ATF-6, eIF2-α, CHOP and XBP1) was assessed with qRT-PCR. (H) The relative protein level of eIF2-α was quantified by Western blot. Data are expressed as mean ± SD. Statistical significance indicated with an asterisk (*) when comparing the results to the CTRL condition and with a hashtag (#) when comparing to the TUN condition; they are depicted as follows: # p < 0.05, **, ## p < 0.01, ***, ### p < 0.001, **** p < 0.0001.
|
| 177 |
+
|
| 178 |
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Figure 4 THCV mitigate inflammation in human adipose-derived stem cells. (A–F) Analysis of the gene expression of pro-inflammatory and anti-inflammatory genes by qRT-PCR (TGFB, IL-10, IL-13, IL-1b, IL-6, TNFa). (G,O) Quantification of IL-6 protein level by Western blot. (H–L) Relative expression of microRNA by qRT-PCR (miR16-5p, miR203b, miR21, miR24-3p, miR146-5p). (M,N,P) Analysis of the gene expression of inflammatory factors by qRT-PCR (IL-4, IL-6, and TNFa). Data are expressed as mean ± SD. Statistical significance indicated with an asterisk (*) when comparing the results to the CTRL condition and with a hashtag (#) when comparing to the TUN condition; they are depicted as follows: *, # p < 0.05, **, ## p < 0.01, ***, ### p < 0.001, **** p < 0.0001.
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| 179 |
+
|
| 180 |
+
ijms-24-07120-t001_Table 1 Table 1 Sequences of primers used in qPCR.
|
| 181 |
+
|
| 182 |
+
Gene Primer Sequence (5′->3′)
|
| 183 |
+
BAX F: ACCAAGAAGCTGAGCGAGTGTC
|
| 184 |
+
R: ACAAAGATGGTCACGGTCTGC
|
| 185 |
+
BCL2 F: ATCGCCCTGTGGATGACTGAG
|
| 186 |
+
R: CAGCCAGGAGAAATCAAACAGAGG
|
| 187 |
+
p21 F: TGCCGAAGTCAGTTCCTTGT
|
| 188 |
+
R: GTTCTGACATGGCGCCTCC
|
| 189 |
+
p53 F: AGTCACAGCACATGACGGAGG
|
| 190 |
+
R: GGAGTCTTCCAGTGTGATGATGG
|
| 191 |
+
Casp3 F: GCGGTTGTAGAAGTTAATAAAGGT
|
| 192 |
+
R: CGACATCTGTACCAGACCGAG
|
| 193 |
+
Casp6 F: TCATGAGAGGTTCTTTTGGCAC
|
| 194 |
+
R: CACACACAAAGCAATCGGCA
|
| 195 |
+
Casp9 F: TTGGTGATGTCGAGCAGAAAG
|
| 196 |
+
R: CCAGGGTCTCAACGTACCAG
|
| 197 |
+
GPX F: CTCCGGAACAACAGCCTTCT
|
| 198 |
+
R: GGAAAGGGGTCTGTGATGGG
|
| 199 |
+
SOD1 F: GACCATTGCATCATTGGCCG
|
| 200 |
+
R: CAAGCCAAACGACTTCCAGC
|
| 201 |
+
SOD2 F: GGAGCGGCACTCGTGG
|
| 202 |
+
R: CAGATACCCCAAAGCCGGAG
|
| 203 |
+
SIRT1 F: ACAGGTTGCGGGAATCCAAA
|
| 204 |
+
R: GTTCATCAGCTGGGCACCTA
|
| 205 |
+
IL-1β F: AAACAGATGAAGTGCTCCTTCCAGG
|
| 206 |
+
R: TGGAGAACACCACTTGTTGCTCCA
|
| 207 |
+
IL-6 F: TCCTTCTCCACAAACATGTAACAA
|
| 208 |
+
R: ATTTGTGGTTGGGTCAGGGG
|
| 209 |
+
TNFα F: AGTGACAAGCCTGTAGCCCA
|
| 210 |
+
R: GTCTGGTAGGAGACGGCGAT
|
| 211 |
+
IL-4 F: CTTTGCTGCCTCCAAGAACAC
|
| 212 |
+
R: GCGAGTGTCCTTCTCATGGT
|
| 213 |
+
IL-10 F: AGACAGACTTGCAAAAGAAGGC
|
| 214 |
+
R: TCGAAGCATGTTAGGCAGGTT
|
| 215 |
+
PERK F: TGCTCCCACCTCAGCGAC
|
| 216 |
+
R: TTTCAGGATCCAAGGCAGCA
|
| 217 |
+
eIF2-α F: ATGTTTCAGCCAAGCCCAGA
|
| 218 |
+
R: ACCAGGGGATCTACCACCAA
|
| 219 |
+
CHOP F: TAAAGATGAGCGGGTGGCAG
|
| 220 |
+
R: GGATAATGGGGAGTGGCTGG
|
| 221 |
+
ATF6 F: ACCTCCTTGTCAGCCCCTAA
|
| 222 |
+
R: CACTCCCTGAGTTCCTGCTG
|
| 223 |
+
IRE1 F: CGGCCTCGGGATTTTTGGA
|
| 224 |
+
R: AGAAAGGCAGGCTCTTCCAC
|
| 225 |
+
XBP1 F: CGCGGATCCGAATGAAGTGAGGCCAGTG
|
| 226 |
+
R: GGGGCTTGG TATATATGTGG
|
| 227 |
+
BAX: BCL-2-associated X protein; BCL2: B-cell lymphoma 2; p21: cyclin-dependent kinase inhibitor 1A; p53: tumor suppressor p53; Casp3: Caspase-3; Casp6: Caspase-6; Casp9: Caspase-9; GPX: Glutathione peroxidase; SOD1: Superoxide dismutase [Cu-Zn]; SOD2: Superoxide dismutase 2; SIRT1: Sirtuin 1; IL-1β: Interleukin 1β; IL-6: Interleukin-6; TNFα: Tumor necrosis factor α; IL-4: Interleukin-4; IL-10: Interleukin-10; PERK: Protein Kinase RNA-like ER Kinase; eIF2-α: Eukaryotic Initiation Factor 2 α; CHOP: C/EBP homologous protein; ATF6: Activating Transcription Factor 6; IRE1: Inositol-requiring enzyme 1; XBP1: X-box binding protein 1.
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| 228 |
+
|
| 229 |
+
ijms-24-07120-t002_Table 2 Table 2 Sequences of microRNA primers used in qPCR.
|
| 230 |
+
|
| 231 |
+
Primer miRNAs Primer Sequence (5′->3′)
|
| 232 |
+
miR101-1/2 TACAGTACTGTGATAACTGAA
|
| 233 |
+
miR17-5p CAAAGTGCTTACAGTGCAGGTAG
|
| 234 |
+
miR16-5p TAGCAGCACGTAAATATTGGCG
|
| 235 |
+
miR-203b TTGAACTGTTAAGAACCACTGGA
|
| 236 |
+
miR-21 TAGCTTATCAGACTGATGTTGA
|
| 237 |
+
miR 24-3p TGGCTCAGTTCAGCAGGAACAG
|
| 238 |
+
miR 146-5p TGAGAACTGAATTCCATGGGTT
|
| 239 |
+
miR: micro RNA.
|
| 240 |
+
|
| 241 |
+
ijms-24-07120-t003_Table 3 Table 3 List of antibodies used in study.
|
| 242 |
+
|
| 243 |
+
Antibodies Concentrations CAT Numbers Company
|
| 244 |
+
β-actin 1:1000 orb10033 Biorbyt (Cambridge, UK)
|
| 245 |
+
Casp3 1:1000 c8487 Sigma (Poznan, Poland)
|
| 246 |
+
IL-6 1:1000 ab6672 Abcam (Cambridge, UK )
|
| 247 |
+
eIF2- α 1:500 nbp2-67353 Novus (Centennial, CO, USA)
|
| 248 |
+
Casp3: Caspase-3; IL-6: Interleukin 6; eIF2-α: Eukaryotic Initiation Factor 2 α.
|
| 249 |
+
|
| 250 |
+
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
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==== Refs
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| 298 |
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|
puc/PMC10138540.txt
ADDED
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Int J Mol Sci
|
| 4 |
+
Int J Mol Sci
|
| 5 |
+
ijms
|
| 6 |
+
International Journal of Molecular Sciences
|
| 7 |
+
1422-0067
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
10.3390/ijms24087367
|
| 11 |
+
ijms-24-07367
|
| 12 |
+
Article
|
| 13 |
+
Leuconostoc citreum Inhibits Adipogenesis and Lipogenesis by Inhibiting p38 MAPK/Erk 44/42 and Stimulating AMPKα Signaling Pathways
|
| 14 |
+
Han Hyo-Shim Conceptualization Formal analysis 1
|
| 15 |
+
https://orcid.org/0000-0002-7854-5954
|
| 16 |
+
Soundharrajan Ilavenil Conceptualization Investigation Writing – original draft 2
|
| 17 |
+
Valan Arasu Mariadhas Data curation Writing – review & editing 3
|
| 18 |
+
Kim Dahye Methodology Validation Writing – review & editing 4*
|
| 19 |
+
https://orcid.org/0000-0001-8071-5097
|
| 20 |
+
Choi Ki-Choon Resources Supervision Project administration 2*
|
| 21 |
+
Ollero Mario Academic Editor
|
| 22 |
+
1 Department of Biotechnology, Sunchon University, Suncheon 57922, Republic of Korea; kkruki@hanmail.net
|
| 23 |
+
2 Grassland and Forages Division, National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Republic of Korea; ilavenil@korea.kr
|
| 24 |
+
3 Department of Botany and Microbiology, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia; mvalanarasu@gmail.com
|
| 25 |
+
4 Animal Genomics and Bioinformatics Division, National Institute of Animal Science, Jeonju 55365, Republic of Korea
|
| 26 |
+
* Correspondence: dhkim0724@korea.kr (D.K.); choiwh@korea.kr (K.-C.C.); Tel.: +82-63-238-7304 (D.K.); +82-41-580-6752 (K.-C.C.); Fax: +82-41-580-6779 (K.-C.C.)
|
| 27 |
+
17 4 2023
|
| 28 |
+
4 2023
|
| 29 |
+
24 8 736708 3 2023
|
| 30 |
+
12 4 2023
|
| 31 |
+
14 4 2023
|
| 32 |
+
© 2023 by the authors.
|
| 33 |
+
2023
|
| 34 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 35 |
+
Probiotics provide a range of health benefits. Several studies have shown that using probiotics in obesity treatment can reduce bodyweight. However, such treatments are still restricted. Leuconostoc citreum, an epiphytic bacterium, is widely used in a variety of biological applications. However, few studies have investigated the role of Leuconostoc spp. in adipocyte differentiation and its molecular mechanisms. Therefore, the objective of this study was to determine the effects of cell-free metabolites of L. citreum (LSC) on adipogenesis, lipogenesis, and lipolysis in 3T3-L1 adipocytes. The results showed that LSC treatment reduced the accumulation of lipid droplets and expression levels of CCAAT/ enhancer-binding protein-α & β (C/EBP-α & β), peroxisome proliferator-activated receptor-γ (PPAR-γ), serum regulatory binding protein-1c (SREBP-1c), adipocyte fatty acid binding protein (aP2), fatty acid synthase (FAS), acetyl CoA carboxylase (ACC), resistin, pp38MAPK, and pErk 44/42. However, compared to control cells, adiponectin, an insulin sensitizer, was elevated in adipocytes treated with LSC. In addition, LSC treatment increased lipolysis by increasing pAMPK-α and suppressing FAS, ACC, and PPAR-γ expression, similarly to the effects of AICAR, an AMPK agonist. In conclusion, L. citreum is a novel probiotic strain that can be used to treat obesity and its associated metabolic disorders.
|
| 36 |
+
|
| 37 |
+
Leuconostoc citreum
|
| 38 |
+
LSC
|
| 39 |
+
3T3-L1
|
| 40 |
+
adipogenesis
|
| 41 |
+
lipogenesis
|
| 42 |
+
lipolysis
|
| 43 |
+
This research received no external funding.
|
| 44 |
+
==== Body
|
| 45 |
+
pmc1. Introduction
|
| 46 |
+
|
| 47 |
+
Globally, obesity is becoming an epidemic issue, with an increasing occurrence rate. Obesity rate is 30.4% in the United States, 12.8% in Europe, and 10.7% in China [1,2,3]. Global assessments have shown that almost 2.3 billion children and adults are overweight or obese. If the current conditions continue, 2.7 billion adults might be overweight or obesogenic in 2025. The World Health Organization (WHO) forecasts that 39% of people in 2035 might become obese [4]. According to Organization for Economic Co-operation & Development (OECD), more than 4% and almost 30% of the adult population in Korea are obese and overweight, respectively. Jung et al. 2020 projected that Korean adults would have a median body mass index (BMI) of 23.55 kg/m2 in 2040. Based on BMI classification, 70.05% of all adults will become obese by 2040 [5]. As obesity increases, it poses a greater public health threat and economic problem in the long run because it is closely linked to several chronic diseases, including cardiac disease, aging, cancer, diabetes mellitus, skeletal muscle illness, inflammatory diseases, and fatty liver accumulation [6,7]. Every year, obesity and its related diseases kill more than 2.8 million people in worldwide [8]. Although several factors, including a sedentary lifestyle, high calorie intake, depression, social and monetary issues, contribute to obesity, one common cause is the accumulation of lipids in white adipocytes through adipogenesis and lipogenesis [9]. The mechanism of depositing lipids in adipocytes has several complex processes involving several genes and transcriptional factors. Among various factors, CCAAT/enhancer-binding protein (C/EBPs) and peroxisome proliferator-activated receptor-γ (PPAR-γ) are key transcriptional genes that can induce lipogenesis-associated genes such as adipocyte fatty acid binding protein (aP2), fatty acid synthase (FAS), acetyl CoA carboxylase (ACC) [10,11,12]. Thus, most researchers are focused on developing dietary supplements to control excessive fat deposition in adipocytes. In terms of anti-obesity effectiveness, probiotics are among the major factors [13,14,15]. It has been shown that probiotics have anti-obesity effects by altering metabolic energy, improving the intestinal barrier, increasing metabolism, improving immune response, modulating nerve activity, and modulating appetite [15,16,17].
|
| 48 |
+
|
| 49 |
+
In the modern era, many drugs are available for treating obesity and its associated disorders. However, they can cause some adverse effects such as nausea, insomnia, constipation, gastrointestinal problems, and cardiovascular problems [18]. A potent strategy is required to find and develop anti-obesity supplements that can reduce fat deposition in the body, reduce the risk of obesity-related diseases, and minimize side effects. Recently, lactic acid bacteria have received a considerable amount of attention due to their effects on obesity and its associated metabolic disorders [19,20,21,22,23,24]. Several studies have shown that Leuconostoc spp.-mediated food supplements reduce obesity and metabolic diseases associated with obesity [25,26,27]. There has been a substantial variance in the present study in comparison to previously reported data on Leuconostoc species. We used a novel strain of Leuconostoc citreum in the present study to determine its efficiency as regards inhibiting differentiation and lipid accumulation in 3T3-L1 adipocytes. Therefore, the L. citreum strain was cultured in a 10% FBS-DMEM (Fetal Bovine Serum-Dulbecco’s Modified Eagle Medium) medium for the production of secondary metabolites. The secondary metabolites in the sample were then lyophilized. The effects of the cell-free supernatant of L. citreum (LSC) on the differentiation of adipocytes and fat deposition have been studied. A further investigation was conducted on the molecular mechanisms that may underlie LSC’s inhibition of lipogenesis and lipolysis.
|
| 50 |
+
|
| 51 |
+
2. Results
|
| 52 |
+
|
| 53 |
+
2.1. Impact of Cell Free Supernatant of L. citreum (LSC) on Cell Viability
|
| 54 |
+
|
| 55 |
+
As shown in Figure 1A,B, the effects of LSC at different concentrations (0.5 mg/mL to 0.001 mg/mL) on viability of 3T3-L1 adipocytes were observed at 24 h and 48 h. As compared to control cells, cells treated with LSC at a concentration of 0.5 mg/mL had a significantly lower viability at 24 h and 48 h. A concentration of LSC of less than 0.250 mg/mL did not affect cell morphology or viability, suggesting that LCS could be used for further experimental analysis.
|
| 56 |
+
|
| 57 |
+
2.2. LSC Treatment Reduces Fat Deposition in 3T3-L1 Cells
|
| 58 |
+
|
| 59 |
+
We first examined the effects of LSC at concentrations of 0.05, 0.1, and 0.15 mg/mL on differentiation and fat deposition on day 10 by Oil Red O stain (ORO). Microscopic examination revealed higher fat deposition spots at several locations with large sizes in control cells. The results showed that insulin, IBMX, and dexamethasone successfully induced differentiation and fat deposition in adipocytes. In contrast, cells treated with LSC at different concentrations from the beginning of differentiation to the end of the experiment showed reduced fat deposition spots and fat size in a dose-dependent manner. At 0.15 mg/mL, fat deposition was strongly inhibited compared to other dose ranges. LSC at 0.1 mg/mL also strongly decreased fat deposition in cells during differentiation (Figure 2). Additionally, the ORO strain was extracted from experimental adipocytes using 99% 2-propanol and absorbance was measured at 450 nm, providing strong evidence for microscopic visualization. The percentage of lipid deposition in experimental cells revealed that LSC treatment reduced lipid content in a dose-dependent manner compared to control on day 10. LSC at 0.15 mg/mL inhibited the most fat deposition (Figure 2).
|
| 60 |
+
|
| 61 |
+
2.3. LSC Downregulates Differentiation and Fatty Acid Synthesis Associated Proteins
|
| 62 |
+
|
| 63 |
+
Microscopical observations and lipid quantification data confirmed that LSC treatment reduced adipocyte fat accumulation. Western blot was used to determine molecular mechanisms involved in LSC treatment-induced fat reduction in adipocytes. Key transcriptional factors such as PPAR-γ, C/EBP-α/β, and SREBP-1c associated with differentiation were downregulated in adipocytes treated with LSC on day 10 (Figure 3A). LSC treatment also inhibited the expression of key lipogenesis-associated proteins such as FAS, ACC, and aP2. Other proteins related to insulin resistance and insulin sensitivity such as resistin and adiponectin levels were also determined. Results showed that LSC treatment decreased resistin but increased adiponectin expression in adipocytes compared to control (Figure 3A,B).
|
| 64 |
+
|
| 65 |
+
2.4. LSC Competes with Rosiglitazone (RGZ)-Induced Lipid Accumulation and PPAR-γ Expressions
|
| 66 |
+
|
| 67 |
+
The effect of LSC treatment on fat deposition can be attributed to the downregulation of key adipogenesis and lipogenesis-associated proteins. The effects of rosiglitazone (RGZ), a PPAR-γ agonist, and LSC on PPAR-γ and fat accumulation in adipocytes were then determined. RGZ treatment alone rapidly increased fat deposition in adipocytes by upregulating PPAR-γ expression compared to the control, whereas treatment with LSC alone strongly decreased fat accumulation by downregulating PPAR-γ expression compared to the control (Figure 4A–C). Cells treated with LSC in the presence of RGZ significantly reduced the lipid content of cells and PPAR-γ expression compared to RGZ alone. However, there was no statistically significant difference between the control and the LSC + RGZ treatment.
|
| 68 |
+
|
| 69 |
+
2.5. LSC Inhibits Differentiation and Fat Deposition through p38MAPK and Erk1/2 Signaling Pathways
|
| 70 |
+
|
| 71 |
+
LSC treatment significantly inhibited fat accumulation in adipocytes through adipogenesis and lipogenesis-related proteins. The effects of LSC on signaling pathways related to adipocyte differentiation and lipid accumulation were then investigated. Western blot analysis revealed that LSC treatment inhibited phosphorylation of p38MAPK at Thr180/Tyr182 and Erk1/2 at Thr202/Tyr204 as compared with the control (Figure 5).
|
| 72 |
+
|
| 73 |
+
2.6. LSC Induces Lipolysis by Activating AMPK-α in Differentiated Adipocytes
|
| 74 |
+
|
| 75 |
+
Differentiated adipocytes treated with LSC at 0.15 mg/mL or AICAR (5-Aminoimidazole-4-carboxamide ribonucleotide) at 1 mM, an AMPK-α agonist, for 12 h increased phosphorylation of AMPK-α closely associated with lipolysis but decreased PPAR-γ, FAS, and ACC expression levels closely associated with adipocyte differentiation and fatty acid synthesis (Figure 6). The results obtained for LSC were significantly comparable with those obtained for the AICAR treatment.
|
| 76 |
+
|
| 77 |
+
3. Discussion
|
| 78 |
+
|
| 79 |
+
In this study, we investigated the anti-adipogenic and anti-lipidemic properties of cell-free supernatants produced by Leuconostoc citreum (LSC) in adipocytes. The number of studies exploring the beneficial effects of the microbiome in humans has increased recently [28,29]. In general, probiotics can colonize epithelial cells of the gastrointestinal tract (GIT) and regulate key signaling molecules that are closely associated with human health [30]. In addition, post-biotics derived from gut-associated probiotics are essential candidates for the development of therapeutics against obesity [31]. Moreover, probiotics can produce many secondary metabolites and branched chain fatty acids that could reduce obesity [32]. Several researchers are actively involved in the production of fermented products in the presence of Leuconostoc spp with significant biological potential. As examples, the soymilk fermented with L. kimchi, L. citreum and L. plantarum significantly reduced fat deposition in 3T3-L1 adipocytes by inhibiting key transcription factors C/EBP-α and PPAR-γ. Furthermore, Soypro treatment reduced low density lipoprotein cholesterol (LDL) levels without affecting body weight in obese rats [25]. Another study reported that pear extract and robusta fermented with L. mesenteroids significantly reduced body weight and adipose tissue mass, and the size of lipids in liver in obese rats compared to control rats [27,33]. Supplementation with L. mesenteroids reduced blood urea nitrogen, glucose, and triglyceride levels in obese mice serum, as well as fatty liver development and liver steatosis in comparison with controls [26,34]. Thus, we investigated the effects of LSC on fat deposition and differentiation in 3T3-L1 adipocytes. However, a significant difference exists between this study and previous studies on Leuconostoc species. The results of this study showed that the amount and size of fat deposition spots in cells treated with LSC at different concentrations were significantly reduced. In the presence of a differentiation-inducing cocktail, huge amounts of lipid accumulation with large sizes were observed in several places of adipocytes. However, LSC treatment reduced lipid accumulation in a dose-dependent manner. This study confirmed that LSC could exert anti-adipogenic and anti-lipogenic effects.
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Adipogenesis is regulated by a variety of transcription factors, including C/EBP family members and PPAR-γ [35]. At an early stage of differentiation, C/EBP-β and C/EBP-δ become highly expressed in adipocytes. They can act as positive modulators of differentiation and lipid accumulation [11,36]. C/EBP-β is considered the most important factor induced by adipogenic cocktail stimuli. Knockdown of C/EBP-β can inhibit adipogenesis in 3T3-L1 cells [37,38,39]. PPAR-γ is the master regulator of differentiation of adipocytes and metabolism [10]. PPAR-γ and C/EBP-α cooperate with each other to orchestrate the entire adipogenic program [40]. In the present study, adipogenic stimulation significantly increased fat deposition in adipocytes, whereas LSC treatment significantly reduced fat accumulation compared to the control. The mechanisms behind the inhibition of differentiation and lipid accumulation in adipocytes in response to LSC treatment were determined. The results suggested that C/EBP-β was downregulated in adipocytes treated with different concentrations of LSC compared to the control cells. Subsequently, the expression levels of PPAR-γ and C/EBP-α protein also decreased following LSC treatment. A competitive study was performed between LSC and rosiglitazone (RGZ), an agonist for PPAR-γ. RGZ treatment increased fat deposition and PPAR-γ expression in adipocytes, whereas LSC treatment in the presence of RGZ significantly reduced fat accumulation as well as PPAR-γ expression compared to RGZ treatment. This study showed that LSC treatment could abolish RGZ-induced fat accumulation and expression of PPAR-γ.
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Other transcriptional factors such as cyclic AMP response element (CREB) and sterol regulatory binding protein-1 (SREBP-1) can promote adipogenesis and differentiate pre-adipocytes into mature adipocytes. SREBP-1 is highly expressed in adipocytes [41,42]. It can stimulate PPAR-γ expression and fatty acid synthesis [11,43]. It also regulates genes responsible for lipogenesis such as FAS [44]. LSC significantly downregulated SREBP-1c during the differentiation of adipocytes. The downregulation of SREBP-1c is also one of the reasons for the inhibition of differentiation and the expression of PPAR-γ, suggesting that downregulation of C/EBP-β expression in LSC treated cells simultaneously reduced the expression of PPAR-γ, C/EBP-α, and SREBP-1c, which reduced adipocyte differentiation. An induction of PPAR-γ, C/EBP-α, and SREBP-1c can promote fatty acid synthesis by increasing key proteins associated with lipogenesis such as FAS and ACC [45,46]. In the terminal phase of differentiation, FAS, ACC, and aP2 expression levels are increased by several folds (>20 folds) [47,48]. ACC, FAS, and aP2 expression levels are positively associated with fatty acid synthesis. Among these enzymes, FAS and ACC are responsible for the synthesis of lipids and triglycerides. The key event in lipid metabolism is malonyl CoA production via carboxylation of acetyl CoA by acetyl CoA carboxylase. In the present study, we found that LSC significantly decreased the expression of FAS and ACC, which limited the synthesis of fatty acids in adipocytes, which was positively correlated with Oil Red O-stained lipid accumulation in LSC and control adipocytes. aP2 is only secreted by adipocytes. Several metabolic disorders and cardiovascular diseases are closely associated with high levels of aP2. Moreover, inhibiting aP2 might be a good strategy to reduce insulin resistance and type-2 diabetes [49,50]. Adipokines such as adiponectin, resistin, and leptin are physiological active cytokines. They are secreted from fat cells. They are well-known to influence adipogenesis [51,52,53]. High adiponectin levels in the circulation are associated with a lower incidence of diabetes [54,55]. However, a high level of resistin is associated with insulin resistance and diabetes [56,57]. In the present study, cells treated with LSC showed significantly increased adiponectin levels but reduced resistin protein expression in adipocytes. As a result of the current study, adipocyte differentiation was markedly influenced by LSC treatment, which reduced aP2 and resistin expression levels but increased adiponectin expression, suggesting that LSC treatments might negatively affect insulin resistance and diabetes development by improving insulin sensitivity and glucose uptake by cells.
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Adipocyte differentiation is directed by p38MAPK and ERK1/2 [58]. By inhibiting p38MAPK and ERK1/2 phosphorylation, specific inhibitors have been shown to decrease adipocyte differentiation and lipid accumulation [59,60,61], suggesting that both p38MAPK and ERK1/2 initiations are crucial to lipogenesis and adipogenesis. Cells treated with LSC showed lower levels of phosphorylation of p38MAPK at Thr180/Tyr182 and Erk1/2 at Thr202/Tyr204 than control cells, which inhibits key transcriptional factors PPAR, C/EBP-α and C/EBP-β as well as lipogenesis-associated enzymes FAS and ACC [24]. AMPK can regulate fatty acid metabolism, thermogenesis, and adipose tissue development [62]. Activation of AMPK can inhibit lipogenesis and enhance fatty acid oxidation by inhibiting ACC and FAS and restoring carnitine palmitoyltransferase 1 (CPT1) [63,64]. Activated AMPK can inhibit adipocyte differentiation by inhibiting early mitotic clonal expansion phase, resulting in the reduced expression of adipogenic and lipogenic markers such as FAS, SREBP-1c, and aP2 [65,66]. In addition, activation of AMPK can reduce fat accumulation and the expression of PPAR-γ, C/EBPα, and early adipogenic transcriptional factors such as C/EBPβ and C/EBPδ [67]. Therefore, we determined the impact of LSC on lipolysis related molecular mechanism in differentiated adipocytes compared to the effect of AICAR, an AMPK agonist that could activate AMPK-α via phosphorylation and inhibit the expression of PPAR-γ, FAS, and ACC [68,69]. The results revealed that treatment with both LSC or AICAR for 12 h significantly increased the activated AMPK-α compared to control. This activation further downregulated the expression of adipogenic key transcriptional factor such as PPAR-γ and lipogenic enzymes such as FAS and ACC, suggesting that LSC could inhibit adipocyte differentiation and fat deposition by inhibiting adipogenic and lipogenic proteins while increasing lipolysis through the activation of AMPK-α by increasing its phosphorylating level. The results after LSC treatment were comparable to those after AICAR treatment.
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4. Materials and Methods
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4.1. Isolation and Characterization of Leuconostoc citreum
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De Man Rogosa and Sharpe Agar (MRS agar, CONDA, Madrid, Spain) medium was used for isolating Leuconostoc citreum (LSC) from whole crop rice samples. Biochemical analysis and 16SrRNA sequencing were used to identify the bacteria at the species level (Solgent Co, Seoul, Republic of Korea).
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4.2. Production of Cell Free Supernatant of L. citreum (LSC) and Lyophilization
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To obtain a fresh culture, LSC was grown in MRS broth and incubated at 37 °C for 48 h with mild shaking (125 rpm). LSC was prepared by centrifuging cultured LSC at 4000× g for 60 min at 4 °C, filtrating with filter membranes having different pour sizes, and then filtered sample was lyophilized at −40 °C under less than 50 m Torr pressure for 72 h (Ilshin Lab. Co., Ltd., Ansan-si, Gyeonggi-do, Republic of Korea) The BreeZe mini (sun clean bactericide, 30,000 ppm, Mirai Co., Chiba, Japan) was used to sterilize the LSC powder [24].
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4.3. Cytotoxic Effects of LSC
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Preadipocytes of 3T3-L1 (3T3-L1, ATCC-173, Manassas, VA, USA) were seeded into 96-well cell culture plates containing 10% fetal bovine serum in Dulbecco’s modified eagle medium (FBS-ATCC 30-2020 and DMEM ATCC 30-2002, Manassas, VA, USA) at a density of 10,000 cells/well. The plates were then incubated at 37 °C with 5% CO2 for 24 h. Different doses (0.5 mg–0.001 mg/mL) of LSC were added to the cells followed by incubation at 37 °C with 5% CO2 for 24 h and 48 h. EZ-cytox reagent (DoGenBio, Seoul, Republic of Korea) (10 µL/well) was added to each well followed by incubation at 37 °C with 5% CO2 for a further 30 min. Optical intensity was then measured with i3 Spectramax (Molecular Device, San Jose, CA, USA). The percentage of cell viability following LSC treatment compared to that of control cells was then calculated.
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4.4. Differentiation and Lipid Deposition Induction in 3T3-L1 Cells
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Cells were seeded into 12-well or 6-well plates at 15,000 or 30,000 adipocytes/well, respectively. Plates were incubated at 37 °C with 5% CO2. The incubations were continued for an additional 48 h in order to arrest growth. After 48 h, differentiation and lipid accumulation were initiated with 10% FBS-DMEM: 30–2002 medium containing insulin (1 μg/mL), IBMX (0.5 mM), and dexamethasone (1 mM). The cells were then switched to an insulin medium for 48 h. For treatment, cells were treated with different concentrations of cell free Supernatant of L. citreum (LSC) from the starting day of differentiation to the end of the experiment [70].
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4.5. Detection and Determination of Fat Deposition by Oil Red O (ORO) Staining
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Differentiated cells were fixed with formalin (10% in PBS) for an hour and then washed three times with PBS (Thermo Fisher Scientific, Waltham, MA, USA). Afterwards, cells were incubated with 60% isopropyl alcohol (IPA) for five minutes, covered with ORO (Sigma-Aldrich, St. Louis, MO, USA) working solution, and then incubated at room temperature for ten minutes. The ORO solution was discarded and the cells were washed 3–5 times with water or until excess stain was eliminated. ORO-stained cells were captured with an Evos cell image system (Fisher Scientific, Waltham, MA, USA). The ORO stain was then extracted from experimental cells and its intensity was measured at 490 nm. The percentage of fat deposition in cells treated with LSC compared with that in control cells was then calculated [24].
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4.6. Proteins Extraction and Immunoblot Analysis
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On day 10, the protein was extracted from experimental cells using RIPA cell lysis buffer containing 1× phosphatase and protease inhibitors (Roche, Basel, Switzerland; and Sigma-Aldrich, St. Louis, MO, USA). Protein content in cells was determined using the BCA method (Thermo Fisher Scientific, Waltham, MA, USA). An equal concentration of proteins from each experimental group was separated using mini SDS-PAGE gels (Biorad, Hercules, CA, USA). Afterwards, the proteins were transferred to polyvinylidene difluoride membranes (PVDF) using a semiwet transfer method (Turbo Transfer Gel method, Biorad, Hercules, CA, USA). Targeted proteins were immunoblotted overnight at 4 °C with primary antibodies (Cell Signaling Technology, Danvers, MA, USA). Membranes were then incubated with secondary antibodies linked to HRP (Cell Signaling Technology, Danvers, MA, USA). ECL reagent (Biorad, Hercules, CA, USA) was used to detect targeted protein bands. The intensity of the protein band was quantified using ImageJ software, 1.49 versions (Wayne Rasband, National institute of Health, Bethesda, ML, USA [19].
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4.7. Statistical Analysis
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Statistical analysis was performed for experimental data using SPSS16.0 (SPSS-Version 16.0, SPSS Inc., Chicago, IL, USA). One-way ANOVA and independent t-test were used to determine statistical significance between experimental samples at p-value less than 0.05.
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5. Conclusions
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Cell-free supernatants from Leuconostoc citreum (LSC) could inhibit adipogenesis and lipogenesis by downregulating the expression of main differentiation transcriptional factors PPAR-γ, C/EBP α, and C/EBP β and vital lipogenic enzymes FAS and ACC through the p38 MAPK and Erk 44/42 facilitated signaling pathways. In addition, LSC treatment increased insulin-sensitizer adiponectin expression and reduced insulin resistance-related proteins such as resistin and aP2. Cells treated with LSC for 12 h showed enhanced lipolysis by increasing phosphorylation of AMPK-α at Thr172 and inhibiting lipogenesis-associated enzymes FAS and ACC. Overall, the results of this study suggest that LSC has potential as very effective multifunctional probiotic bacteria with anti-obesity activity. In order to fully understand the potential role of LSC in the gastrointestinal tract, more intensive studies are needed to confirm the potential role of LSC in the inhibition of obesity and its associated diseases/disorders in animal or human model experiments in the future.
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Author Contributions
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Conceptualization, H.-S.H., I.S. and K.-C.C.; Methodology, I.S. and D.K.; Formal analysis, I.S.; Data curation, I.S., H.-S.H., D.K. and M.V.A.; Writing—original draft preparation, I.S.; Writing—review and editing, H.-S.H., D.K., M.V.A. and D.K.; Software, I.S., M.V.A. and D.K.; Supervision, K.-C.C. All authors have read and agreed to the published version of the manuscript.
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Institutional Review Board Statement
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No applicable.
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Informed Consent Statement
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No applicable.
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Data Availability Statement
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Experimental data can be obtained from the corresponding author upon reasonable request.
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Conflicts of Interest
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The authors do not have any conflicts of interest.
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Figure 1 Effects of L. citreum cell-free supernatants on 3T3-L1 cells. Cells were incubated with different concentrations of LSC under normal cell culture conditions. After 24 h and 48 h, EZcytox reagent was used to determine cell viability. (A) Percentage of viable cells in experimental groups at 24 h; (B) Percentage of viable cells at 48 h. Data are expressed as mean (SD) of five replicates.
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Figure 2 Impact of LSC on fat deposition in adipocytes on day 10. Cells were seeded in a 6-well culture plate at the density of 3 × 104/well and incubated at 37 °C with 5% CO2. Differentiation was induced by differentiation cocktails (insulin, DEX and IBMX) for 48 h. The cells were then switched to insulin medium for another 48 h. LSC at different concentrations was used to treat cells when differentiation was initiated. ORO staining was performed to stain lipid depositions in differentiated cells. (A) Oil red O-stained cells (200 μm) were then observed using an Evos microscope (20×/20× magnifications). (B) Percentage of fat depositions in experimental adipocytes. Data are presented as mean ± standard deviation (n = 5). Different alphabets within the figure indicate significant differences at p < 0.05 level.
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Figure 3 Effects of LSC on adipogenesis and lipogenesis in 3T3-L1 cells on day 10. Proteins were extracted with protease and phosphatase inhibitors and quantified using BCA on day 10. Proteins were separated by SDS-PAGE. PPAR-γ, C/EBP-β, C/EBP-α, and SREBP-1c; lipogenic proteins such as FAS, and ACC, insulin sensitizer adiponectin (AdipoQ) in insulin resistance-inducing proteins such as FABP4 (aP2) and resistin were detected with specific antibodies using Western blot. Protein intensity was quantified with ImageJ software, 1.49 versions (32-bit). (A) Preliminary screening of key adipogenic and lipogenic proteins expression changes in experimental cells. (B) Impact of selected concentration of LSC on other proteins involved in adipogenesis and lipogenesis. Results are expressed as mean ± standard deviation of three replicates (n = 3). * p < 0.05. Different alphabets in the figure indicate significant differences at p < 0.05.
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Figure 4 LSC treatment aborts rosiglitazone (RGZ)-induced differentiation and fat deposition. Cells were incubated with LSC (0.15 mg/mL) or RGZ (1 µM) or RGZ plus LSC during differentiation. RGZ treatment alone increased differentiation and lipid synthesis in adipocytes, whereas LSC treatment alone reduced fat accumulation. Furthermore, LSC inhibits RGZ-induced lipid accumulation. (A) Microscopic views (20×/20× magnifications) of ORO-stained fat deposition in adipocytes. (B) Percentage of lipid accumulation in experimental cells (n = 5). (C) PPAR-γ protein expression in experimental cells on day 10 (n = 3). Data are presented as mean ± standard deviation. Different alphabets in the figure indicate significant differences (p < 0.05).
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Figure 5 LSC modulates phosphorylating levels of pp38MAPK and pERK 44/42 in adipocytes. On day 10, proteins were extracted with RIPA buffer containing protease and phosphatase inhibitors and quantified with BCA. SDS-PAGE was used to separate proteins. Erk 44/42 and p38MAPK phosphorylation levels were determined with specific antibodies. ImageJ was used to quantify protein intensity. Results are expressed as mean ± standard deviation. * p < 0.05 (n = 3).
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Figure 6 Effects of LSC on expression levels of lipolysis and lipogenesis related proteins in adipocytes. Differentiated adipocytes for eight days were treated with LSC or AICAR, an AMPKα agonist, for 12 h. Phosphorylation level of AMPK-α, a key adipocyte differentiation transcriptional factor PPAR-γ, and lipogenic enzymes such as FAS and ACC were determined using Western blot. Protein intensity was determined using ImageJ software. Data are expressed as mean ± standard deviation of three replicates. Different alphabets in the figure indicate significant differences at p < 0.05.
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==== Refs
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| 227 |
+
|
puc/PMC10138945.txt
ADDED
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Int J Mol Sci
|
| 4 |
+
Int J Mol Sci
|
| 5 |
+
ijms
|
| 6 |
+
International Journal of Molecular Sciences
|
| 7 |
+
1422-0067
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
10.3390/ijms24087012
|
| 11 |
+
ijms-24-07012
|
| 12 |
+
Article
|
| 13 |
+
Prostaglandin F2α Regulates Adipogenesis by Modulating Extracellular Signal-Regulated Kinase Signaling in Graves’ Ophthalmopathy
|
| 14 |
+
https://orcid.org/0000-0003-2575-2340
|
| 15 |
+
Zhu Ru Conceptualization Methodology Formal analysis Investigation Writing – original draft †
|
| 16 |
+
Wang Xing-Hua Conceptualization Validation Investigation Resources Writing – review & editing Funding acquisition †
|
| 17 |
+
Wang Bo-Wen Methodology Formal analysis Investigation
|
| 18 |
+
Ouyang Xuan Methodology Formal analysis Investigation
|
| 19 |
+
You Ya-Yan Methodology Formal analysis Investigation
|
| 20 |
+
https://orcid.org/0000-0003-4027-691X
|
| 21 |
+
Xie Hua-Tao Validation Formal analysis
|
| 22 |
+
Zhang Ming-Chang Data curation Writing – review & editing Funding acquisition *
|
| 23 |
+
Jiang Fa-Gang Resources Data curation Writing – review & editing Project administration *
|
| 24 |
+
Honoré Bent Academic Editor
|
| 25 |
+
Department of Ophthalmology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China
|
| 26 |
+
* Correspondence: mingc_zhang@hust.edu.cn (M.-C.Z.); fgjiang@hust.edu.cn (F.-G.J.); Tel.: +86-138-7122-6220 (M.-C.Z.); Fax: +86-135-5410-0999 (F.-G.J.)
|
| 27 |
+
† These authors contributed equally to this work.
|
| 28 |
+
|
| 29 |
+
10 4 2023
|
| 30 |
+
4 2023
|
| 31 |
+
24 8 701227 2 2023
|
| 32 |
+
24 3 2023
|
| 33 |
+
04 4 2023
|
| 34 |
+
© 2023 by the authors.
|
| 35 |
+
2023
|
| 36 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 37 |
+
Prostaglandin F2α (PGF2α), the first-line anti-glaucoma medication, can cause the deepening of the upper eyelid sulcus due to orbital lipoatrophy. However, the pathogenesis of Graves’ ophthalmopathy (GO) involves the excessive adipogenesis of the orbital tissues. The present study aimed to determine the therapeutic effects and underlying mechanisms of PGF2α on adipocyte differentiation. In this study primary cultures of orbital fibroblasts (OFs) from six patients with GO were established. Immunohistochemistry, immunofluorescence, and Western blotting (WB) were used to evaluated the expression of the F-prostanoid receptor (FPR) in the orbital adipose tissues and the OFs of GO patients. The OFs were induced to differentiate into adipocytes and treated with different incubation times and concentrations of PGF2α. The results of Oil red O staining showed that the number and size of the lipid droplets decreased with increasing concentrations of PGF2α and the reverse transcription-polymerase chain reaction (RT-PCR) and WB of the peroxisome proliferator-activated receptor γ (PPARγ) and fatty-acid-binding protein 4 (FABP4), both adipogenic markers, were significantly downregulated via PGF2α treatment. Additionally, we found the adipogenesis induction of OFs promoted ERK phosphorylation, whereas PGF2α further induced ERK phosphorylation. We used Ebopiprant (FPR antagonist) to interfere with PGF2α binding to the FPR and U0126, an Extracellular Signal-Regulated Kinase (ERK) inhibitor, to inhibit ERK phosphorylation. The results of Oil red O staining and expression of adipogenic markers showed that blocking the receptor binding or decreasing the phosphorylation state of the ERK both alleviate the inhibitory effect of PGF2a on the OFs adipogenesis. Overall, PGF2α mediated the inhibitory effect of the OFs adipogenesis through the hyperactivation of ERK phosphorylation via coupling with the FPR. Our study provides a further theoretical reference for the potential application of PGF2α in patients with GO.
|
| 38 |
+
|
| 39 |
+
Graves’ ophthalmopathy
|
| 40 |
+
prostaglandin F2α
|
| 41 |
+
orbital fibroblast
|
| 42 |
+
adipogenesis
|
| 43 |
+
hyperphosphorylation
|
| 44 |
+
National Natural Science Foundation of China82070934 81900912 This work was supported by two grants from the National Natural Science Foundation of China under Grants 82070934 and 81900912.
|
| 45 |
+
==== Body
|
| 46 |
+
pmc1. Introduction
|
| 47 |
+
|
| 48 |
+
Graves’ ophthalmopathy (GO) is an organ-specific autoimmune disease affecting the orbital tissues and often occurs in patients with Graves’ disease (GD) [1]. Approximately 50% of patients with GD present with GO manifestations such as eyelid retraction, proptosis, ocular motility disorders, corneal ulcers, and optic neuropathy [2]. The characteristic pathological changes in GO include the abnormal proliferation of the orbital adipose tissue and extraocular muscle tissue [3]. Although the pathogenesis of GO is not fully understood, the interaction between the thyroid-stimulating hormone receptor (TSHR) and insulin-like growth factor receptor I (IGF-1R) plays a crucial role in orbital fibroblasts (OFs) adipose differentiation [4]. TSHR and IGF-1R can activate the phosphatidylinositol-3-kinase (PI3K)/AKT pathway, upregulate the expression of peroxisome proliferator-activated receptor γ (PPARγ), and induce the differentiation of OFs into adipocytes [5,6].
|
| 49 |
+
|
| 50 |
+
As for the treatment of GO, different strategies are recommended for different stages and severities, including orbital decompression surgery, orbital radiotherapy, and medications such as glucocorticoids, rituximab, tocilizumab, teplizumab, and teprotumumab [7]. However, traditional treatments have limitations, and more clinical trials are needed to evaluate the safety and efficacy of novel medications [8]. Therefore, it is of great significance to find novel and safe medications that can inhibit adipose differentiation of OFs.
|
| 51 |
+
|
| 52 |
+
Prostaglandin analogs (PGAs) have been approved as first-line anti-glaucoma eyedrops [9], but their long-term use can lead to side effects, such as the deepening of the upper eyelid sulcus (DUES) [10]. It has been confirmed that DUES is attributed to the atrophy of the orbital adipose tissue, in which PGF2α, a common ingredient of PGAs, inhibits adipogenesis by activating the F-prostanoid receptor (FPR) [11]. Furthermore, it was found that PGs could significantly inhibit the expression of adipogenesis transcription factors and thereby inhibit the adipogenesis of 3T3-L1 cells [11]. Since the characteristic of GO is that OFs proliferate, synthesize the extracellular matrix, and differentiate into adipocytes, leading to tissue remodeling [3], later studies began to focus on the use of PGAs in GO, and Ichioka et al. found that PGF2α substantially decreased the size of the 3D organoids of GO OFs [12].
|
| 53 |
+
|
| 54 |
+
However, the mechanism underlying the role of PGF2α in GO adipogenesis remains unclear. In the present study, we selected OFs derived from the orbital tissue of patients with GO to study the effects and mechanisms of action of PGF2α derivatives on GO adipose differentiation.
|
| 55 |
+
|
| 56 |
+
2. Results
|
| 57 |
+
|
| 58 |
+
2.1. Expression of the FPR and Adipogenic Differentiation of OFs in Patients with GO
|
| 59 |
+
|
| 60 |
+
We investigated FPR expression in the orbital adipose tissues of patients with GO. According to the immunohistochemistry results, the receptor was positively expressed in the orbital tissue (Figure 1A). We further confirmed this observation via a WB analysis (Figure 1B). Primary cells showing a fibroblast-like morphology were successfully cultured from GO orbital tissues. Their identity was confirmed via immunofluorescence, using antibodies specific for vimentin, cytokeratin, desmin, S-100, and myosin (Supplementary Figure S1). We then used immunofluorescence and WB to confirm the expression of the FPR in GO orbital fibroblasts (Figure 1C,D). In conclusion, these results demonstrate that FPRs are expressed in GO orbital tissues and OFs. The oil red O staining of adipogenic-induced cells after 10 days showed a number of lipid droplets in the OFs, whereas cells in a normal growth medium remained negative (Figure 1E), indicating that the OFs were successfully differentiated into adipocytes in vitro.
|
| 61 |
+
|
| 62 |
+
2.2. Safe Working Concentration of PGF2α on OFs from Patients with GO
|
| 63 |
+
|
| 64 |
+
The Cell-Counting-Kit-8 (CCK-8) assay was used to evaluate the effect of PGF2α treatment on the proliferation of OFs. PGF2α inhibited the proliferation activity of the OFs at concentrations ≥ 300 nM, whereas it had no significant effect at concentrations ≤ 250 nM (Figure 2A). A flow cytometry detection of apoptosis showed no significant increase in annexin V-positive cells after PGF2α treatment at 50, 100, or 250 nM (Figure 2D), indicating that concentrations ≤ 250 nM of PGF2α did not induce cell death for 10 days. No significant differences in the percentage of G1-phase cells were observed among the treatment groups in the cell cycle experiment (Figure 2E), indicating that the proliferation and division cycle of cells were not affected by PGF2α at concentrations ≤ 250 nM. Therefore, PGF2α was applied at concentrations of 50 nM, 100 nM, and 250 nM in subsequent experiments.
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+
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| 66 |
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2.3. The Effect of PGF2α on the Inhibition of OFs Adipogenesis
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Different concentrations (50, 100, and 250 nM) of PGF2α were added during the adipogenic induction, and detection was performed ten days later. The oil red O staining showed that the number and size of the lipid droplets in the OFs decreased significantly with increasing concentrations of PGF2α (Figure 3A,B). The expressions of the adipogenesis indicators PPARγ and FABP4 in the 50, 100, and 250 nM PGF2α groups were significantly downregulated, and were 0.81, 0.63, and 0.4-fold, and 0.76, 0.58, and 0.26-fold lower than those in the induction group, respectively, as determined using reverse transcription-polymerase chain reaction (RT-PCR) (Figure 3C,D). The Western blotting (WB) results were consistent with those obtained using RT-PCR (Figure 3E). In summary, PGF2α inhibits the adipogenesis of OFs in a dose-dependent manner. Therefore, we chose the highest concentration (250 nM) of PGF2α for the subsequent experiments.
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2.4. FPR Mediates ERK Pathway Regulation in PGF2α Inhibition of OFs Adipogenesis
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+
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The binding of PGF2α to the FPR revealed a change in the mitogen-activated protein kinase (MAPK) pathway [11]. The MAPK pathway was examined, and ERK phosphorylation was significantly increased in the PGF2α group (Figure 4A); however, no significant changes were observed for the p38 and c-Jun N-terminal kinase. We further investigated the level of phosphorylated ERK from days 1 to 10 in the induction and PGF2α groups. ERK phosphorylation increased in the induced group from day 3, and then gradually increased with time, while PGF2α activated p-ERK/ERK levels from the first day, and the degree of ERK phosphorylation was significantly higher than that in the induction group at the same time point (Figure 4A,B).
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Therefore, we used Ebopiprant and U0126 to verify that the inhibitory effect of PGF2α on adipogenesis relies on the hyper-activation of ERK phosphorylation by binding to the FPR. First, we determined the safe concentrations of the FPR inhibitor and U0126 in OFs using CCK8, choosing 1 nM of Ebopiprant and 5 μM of U0126 for further experimentation (Figure 2B,C). Oil red O staining revealed that the size and number of the lipid droplets in the Ebopiprant + PGF2α and U0126 + PGF2α groups were significantly increased compared with those in the PGF2α group (Figure 5A,B). The changes in the expression levels of PPARγ and FABP4 using both RT-PCR and WB were consistent with the changes in oil red O staining (Figure 5C–E). In contrast, PGF2α induced strong ERK phosphorylation, which was 2.2-, 2.5-, and 1.7-fold higher than that in the induction, Ebopiprant + PGF2α, and U0126 + PGF2α groups, respectively (Figure 5E,F). This suggests that PGF2α binding to the FPR inhibits adipocyte differentiation via the hyperactivation of ERK phosphorylation.
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3. Discussion
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GO is a common refractory orbital disease that involves a complex pathogenesis. Characteristic pathological changes include the abnormal proliferation of the orbital adipose tissue and extraocular muscles [13]. The limited space within the bony orbit and the volume increase in the orbital tissue resulted in clinical symptoms, including proptosis, ocular motility disorders, and increased intraocular pressure [4]. Traditional treatments, such as glucocorticoids, immunosuppressants, and orbital radiotherapy, have certain curative effects; however, they have many side effects, such as hypertension, Cushing’s syndrome, and diabetes, as well as potential carcinogenic effects [14]. Surgical treatment, such as orbital decompression, can only improve the related symptoms, but it does not ameliorate the pathogenesis of GO [15]. Targeted therapies for GO pathogenesis have also been developed. For example, Teprotumumab [16], a monoclonal antibody to IGF-1R, was approved by the US Food and Drug Administration (FDA) for GO treatment in 2020; however, the cost exceeds affordability for most patients. Even though Rituximab, a monoclonal antibody [17] that targets CD20+ B cells, there is conflicting evidence regarding its therapeutic efficacy in two small and randomized controlled trials (RCTs) in Mayo [18] and Italy [19]. The safety and efficacy of these new drugs require further experimental evidence from large-scale, multicenter RCTs [20]. Thus, the search for a safe, inexpensive, and effective new treatment remains the focus of current research.
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Recently, researchers have focused on finding new uses for old drugs. PGF2α, a selective agonist of the FPR, is regarded as the first-line treatment for glaucoma because of its significant effects on intraocular pressure [9]. Thus, the clinical safety of PGF2α eye drops has been validated. However, PGF2α leads to orbital lipoatrophy [21]. Ocular hypertension often occurs in patients with GO, and the administration of IOP-lowering eye drops is required [2]. Interestingly, periorbital lipoatrophy is an unwanted side effect in patients with ocular hypertension, but not in patients with GO. PGF2α has been shown to inhibit adipogenesis in many studies [10,22]. Therefore, we assessed the suppression effect of PGF2α on GO OFs adipocyte differentiation and its underlying mechanism.
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First, we demonstrated the expression of the FPR in the orbital adipose tissue and OFs from patients with GO. We confirmed that PGF2α significantly inhibited the adipogenesis of GO OFs in a dose-dependent manner. PGF2α exerts its biological effects by coupling with the FPR. Recent studies have shown that PGF2α causes vasoconstriction and increases blood pressure independently of the FPR [23]. Therefore, we used FPR antagonists to interfere with this binding, and as a result, we found that PGF2α inhibits adipogenesis by binding to the FPR, indicating that the FPR plays an important role in this process.
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Several studies have shown that PGF2α can activate the MAPK signaling pathway after coupling with the FPR [24,25]. MAPK signaling regulates various biological activities, among which ERK activation is crucial during the early stage of adipogenesis and is essential for PPARγ transcription [26]. It has been confirmed that u0126, an ERK inhibitor, can directly inhibit the adipose differentiation of 3T3-L1 cells [27]. Chuang et al. found that high glucose levels promote 3T3-L1 adipogenesis by activating P13K/Akt via ERK [28]. At the same time, others found that the traditional Chinese herb Aristolochia manshuriensis inhibited the adipose differentiation of 3T3-L1 cells by activating the ERK pathway [29]. Wang et al. found that evodiamine also inhibited the adipogenesis of 3T3-L1 by promoting ERK phosphorylation [30]. ERK plays a dual role in 3T3-L1 adipogenic differentiation. Therefore, we further explored the role of ERK in the inhibition of the adipogenic differentiation of OFs by PGF2α. An adipogenesis induction medium activated ERK phosphorylation over time, while PGF2α resulted in an earlier and higher degree of ERK phosphorylation at the same time point. The effect of PGF2α on OFs adipogenesis was significantly attenuated by ERK phosphorylation inhibition or FPR antagonists, indicating that OFs adipogenesis is inhibited by PGF2α after hyperphosphorylation via its coupling with the FPR. It was proven that ERKs may also play dual roles in OF adipogenesis. Overall, these results reveal that PGF2α is likely to activate ERK phosphorylation continuously and excessively by binding to the FPR, thus partially mediating the anti-adipogenic effect on GO OFs.
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Nevertheless, our study has several limitations. First, no relevant animal models of GO have been developed to verify the mechanism of PGF2α in vivo. Second, the sample size of six patients is relatively small. Third, only the mechanism of action for the PGF2α-FPR-ERK pathway was examined in this study, and other anti-adipogenic pathways may exist. In view of the fact that PGF2α eye drops have been used widely in clinical practice and that their safety in vivo has been verified, we believe that the results of this study are noteworthy and reliable in that PGF2α leads to the upregulation of adipogenesis in patients with GO.
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4. Materials and Methods
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4.1. Materials
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Dulbecco’s modified Eagle medium (DMEM), 0.25% trypsin-ethylene diamine tetraacetic acid (EDTA) (1×), and the penicillin–streptomycin mixture were purchased from ThermoFisher Scientific (Carlsbad, CA, USA). Fetal bovine serum (FBS) and phosphate-buffered saline (PBS) were purchased from Procell (Wuhan, China). Biotin, pantothenic acid, rosiglitazone, transferrin, triiodothyronine (T3), dexamethasone, insulin, and 3-Isobutyl-1-methylxanthine (IBMX) were purchased from Sigma-Aldrich (Saint Louis, MI, USA). PGF2α, Ebopiprant (an FPR antagonist), and U0126 (an ERK inhibitor) were purchased from MedChemExpress (Monmouth Junction, NJ, USA).
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4.2. Primary Culture and Adipogenic Induction of OFs
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Orbital adipose tissue was obtained from six patients with inactive GO, aged between 18 and 65 years, without other eye diseases, major systemic diseases, or a medication history of prostaglandin analogs. In this study, all patients underwent decompression at the Department of Ophthalmology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. The clinical and patient information is shown in Table 1. The 7-item clinical activity score (CAS) scheme was used to assess GO activity [31]. GO is defined as inactive if the sum is ≤3/7. The severity and clinical activity of GO were graded according to the NOSPECS classification [7]. The study design and protocol were approved by the ethics committee of the Huazhong University of Science and Technology Union hospital that is attached to the Tongji University Medical School (UHCT22725), and informed consent was obtained from the patients for the collection of the specimens.
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The orbital adipose tissue samples were collected as surgical waste specimens of monocular decompression from 6 GO patients and washed three times with PBS. They were cut into small pieces of 1–2 mm3 and distributed evenly on the bottom of a culture flask. An appropriate amount of DMEM was added, and the tissue was cultured in a cell incubator at 37 °C and 5% CO2. When 80% of the bottom of the flask was occupied, the cells were digested with 0.25% trypsin for passage. Cells from passages 4 to 8 were used for subsequent experiments.
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Induction of Adipogenesis: The medium was replaced with adipogenesis induction medium (AM), which was prepared according to the literature [32] as follows: 10 μM rosiglitazone, 33 μM biotin, 17 μM pantothenic acid, 10 μg/mL transferrin, 0.2 nM T3, 1 μM insulin, 0.2 μM carbaprostaglandin, 1 μM dexamethasone, and 0.1 mM IBMX. The medium was changed every 2–3 days for a total of 10 d.
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4.3. Immunohistochemistry and Immunofluorescence Analysis
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The immunohistochemistry (IHC) staining of tissues was performed as previously described [33]. The primary antibody used was the anti-FPR (1:500; Cell Signaling Technology, Danvers, MA, USA). The secondary antibody used was biotin-conjugated anti-rabbit IgG (1:200; Servicebio, Wuhan, China). The staining was visualized using diaminobenzidine (DAB; Servicebio, Wuhan, China), with brown cells indicating a positive result.
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The immunofluorescence staining of the OFs was performed as previously described [34]. The primary antibodies used were the FPR (1:500; Cell Signaling Technology, Danvers, MA, USA), vimentin (1:500; Abclonal, Wuhan, China), cytokeratin (1:500; Abclonal, Wuhan, China), desmin (1:500; Abclonal, Wuhan, China), S-100 (1:500; Abclonal, Wuhan, China), and myosin (1:500; Abclonal, Wuhan, China). The secondary antibody was FITC-conjugated goat anti-rabbit IgG (H + L) (1:200; Servicebio, Wuhan, China).
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4.4. Detection of Cell Proliferation Activity
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Different concentrations of PGF2α, Ebopiprant, and U0126 were added to 96-well plates, and the drug and medium were replaced every 2–3 days. On the 10th day, a cell counting kit (CCK)-8 (MedChemExpress, Monmouth Junction, NJ, USA) was used to detect the absorbance at 450 nm using a microplate reader, according to the manufacturer’s instructions, to obtain the safe working concentration of each drug.
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4.5. Cell Cycle and Apoptosis Detection
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OFs were treated with 250 nM PGF2α, and the drug and medium were replaced every 2–3 days. After 10 days of co-cultivation, the OFs were stained with cell cycle (Elabscience Biotechnology, Wuhan, China) and apoptosis kits (Elabscience Biotechnology, Wuhan, China) according to the manufacturer’s instructions and detected via flow cytometry.
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4.6. Oil Red O Staining
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After cells were fixed with 4% paraformaldehyde (PFA) on day 10 of adipogenic induction, they were incubated with oil red O staining solution (Servicebio, Wuhan, China) for 30 min, stained with hematoxylin for visualization of the nuclei, and mounted with a glycerin gelatin-mounting medium. Staining was examined under a microscope (Olympus, Tokyo, Japan), and the intensity was measured using Image-Pro Plus 6.0. We analyzed the relative oil red O intensity using the AM group as a positive control.
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4.7. Reverse Transcription-Polymerase Chain Reaction (RT-PCR)
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The total RNA was extracted from the OF cells using the RNA quick purification kit (Omega Biotek, Norcross, GA, USA) according to the manufacturer’s instructions, and the RNA was reverse transcribed to generate complementary DNA (cDNA) using the PrimeScript RT kit (Vazyme, Nanjing, China). RT-PCR was performed using the SYBR Fast qPCR kit (Vazyme, Nanjing, China). The housekeeping gene, glyceraldehyde phosphate dehydrogenase (GAPDH), was used as an internal control. Supplementary Table S1 lists the primer sequences.
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4.8. Western Blot (WB)
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A radioimmunoprecipitation assay lysis buffer (Servicebio, Wuhan, China) was added, the supernatant was collected, and the protein concentration was detected using a bicinchoninic acid kit. Proteins were separated via sodium dodecyl sulfate-polyacrylamide gel electrophoresis, transferred to polyvinylidene fluoride membranes, blocked with 5% bovine serum albumin for 1 h at room temperature, and incubated with a primary antibody overnight at 4 °C. After incubation with a horseradish peroxidase-labeled goat anti-rabbit secondary antibody for 1 h at 37 °C, the protein intensity was detected using an electrochemiluminescence reagent and analyzed using ImageJ software (version 1.52).
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4.9. Statistical Analysis
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Graphpad Prism 9.0 software was used for the data analysis, the t-test was used to analyze the data between two groups, and the analysis of variance test was used for three or more groups. All experiments were repeated at least three times on samples from different individuals. When the p-value was <0.05, the difference was considered significant (*, p-value < 0.05; **, p-value < 0.01; ***, p-value < 0.001).
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5. Conclusions
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| 134 |
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The study of PGF2α elucidated the mechanisms contributing to the repression of adipogenesis and laid the foundations for future clinical applications, confirming the potency of PGF2α, a traditional drug that now has a potential new use as a candidate treatment for GO.
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Acknowledgments
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This study was supported by National Natural Science Foundation of China (Grant number 82070934 and 81900912).
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Supplementary Materials
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The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms24087012/s1.
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Click here for additional data file.
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Author Contributions
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Conceptualization, R.Z. and X.-H.W.; methodology, B.-W.W., X.O., Y.-Y.Y. and R.Z.; validation, H.-T.X. and X.-H.W.; formal analysis, R.Z., B.-W.W., X.O., Y.-Y.Y. and H.-T.X.; investigation, R.Z.; resources, X.-H.W. and F.-G.J.; data curation, M.-C.Z. and F.-G.J.; writing—original draft preparation, R.Z.; writing—review and editing, X.-H.W., M.-C.Z. and F.-G.J.; project administration, F.-G.J.; funding acquisition, M.-C.Z. and X.-H.W. All authors have read and agreed to the published version of the manuscript.
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Institutional Review Board Statement
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The studies involving human participants were reviewed and approved by the Ethics Committee of Union Hospital which is affiliated with Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (UHCT22725, date of approval 8 November 2022). The patients/participants provided their written informed consent to participate in this study.
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Informed Consent Statement
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Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patient(s) to publish this paper.
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Data Availability Statement
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The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
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Conflicts of Interest
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| 163 |
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The authors declare no conflict of interest.
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Figure 1 The expression of the FPR and adipogenic differentiation of the OFs of GO patients. (A) Immunohistochemistry for FPR expression in the orbital adipose tissue of patients with GO. Arrowheads designate positive staining (brown color). (B) Protein expressions of the FPR detected in the orbital adipose tissue of patients with GO. (C) Immunofluorescence for FPR expression in GO OFs. (D) The protein expressions of the FPR detected in GO OFs. (E) The oil red O staining for the control and induced groups.
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Figure 2 The cytotoxicity study of PGF2α in GO OFs. (A–C) Cell viability measurements using the CCK-8 assay after treatment with PGF2α, Ebopiprant, or U0126 for 10 d. (D) The flow cytometry detection of apoptosis in GO OFs after treatment with PGF2α; the alive rate is presented here. (E) The representative flow cytometric histograms show the cell cycle distribution after treatment with PGF2α; the cells in the G1 phase rate are presented here. Data are presented as the means ± SEMs (n = 3) (*, p-value < 0.05; ***, p-value < 0.001), ns = not significant.
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Figure 3 PGF2α exerts anti−adipogenic effects on GO OFs. (A) Oil red O staining after treatment with different concentrations of PGF2α. (B) The quantitative data from (A). (C,D) The mRNA levels of PPARγ and FABP4 after treatment with different concentrations of PGF2α. (E) The WB results for PPARγ and FABP4 in each group; the protein levels were quantified and normalized to the level of GAPDH for each sample. Data are presented as the means ± SEMs (n = 3) (*, p-value < 0.05; **, p-value < 0.01; ***, p-value < 0.001). AM: adipogenesis induction medium.
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Figure 4 ERK phosphorylation participated in the anti-adipogenic effects caused by PGF2α. (A) The WB results for the ERK, p-ERK, PPARγ, and FABP4 along with the time taken to induce the effects (10 days). (B) The degree of P-ERK/ERK protein expression at different time points. Data are presented as the means ± SEMs (n = 3) (*, p-value < 0.05; **, p-value < 0.01). AM: adipogenesis induction medium.
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Figure 5 PGF2α regulates the FPR/ERK pathway during OFs adipogenesis inhibition. (A) The oil red O staining assays for the induced, PGF2α, Ebopiprant + PGF2α, and U0126 + PGF2α groups. (B) The quantitative data from (A). (C,D) The mRNA levels of PPARγ and FABP4 in the control, induced, PGF2α, Ebopiprant + PGF2α, and U0126 + PGF2α groups. (E) The WB results of PPARγ and FABP4 for each group; (F) The degree of the P-ERK/ERK protein expression from (E). Data are presented as the means ± SEMs (n = 3) (*, p-value < 0.05; **, p-value < 0.01; ***, p-value < 0.001). AM: adipogenesis induction medium. ns = not significant.
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ijms-24-07012-t001_Table 1 Table 1 The clinical characteristics of donors in this study.
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Age
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| 179 |
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Range (Years) Sex
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| 180 |
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(M/F) Duration
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| 181 |
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of GO (Years) Proptosis
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| 182 |
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(R/L, mm) CAS GO Severity
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| 183 |
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Assessment Previous GO
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| 184 |
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Treatment Prostaglandin Analogues Surgery
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| 185 |
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Performed
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| 186 |
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40s M 1.1 20/18 3/7 IV GCs None Decompression
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| 187 |
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30s F 1.9 17.5/19 0/7 III None None Decompression
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| 188 |
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40s M 5 22/20 0/7 IV GCs None Decompression
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| 189 |
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40s F 3 24/20 1/7 IV GCs None Decompression
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| 190 |
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40s F 1 16/15 3/7 III GCs None Decompression
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| 191 |
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40s M 1 25/20 1/7 IV GCs None Decompression
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| 192 |
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CAS, clinical activity score; F, female; GCs, glucocorticoids; GO, Graves’ Ophthalmopathy; GO severity assessment (0 = no symptoms or signs; I = only signs, no symptoms; II = soft tissue involvement; III = proptosis; IV = extraocular muscle involvement; V = corneal involvement; VI = sight loss due to optic nerve involvement); M, male; R/L, right or left eye.
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Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
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==== Refs
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puc/PMC10147829.txt
ADDED
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Stem Cell Reports
|
| 4 |
+
Stem Cell Reports
|
| 5 |
+
Stem Cell Reports
|
| 6 |
+
2213-6711
|
| 7 |
+
Elsevier
|
| 8 |
+
|
| 9 |
+
S2213-6711(23)00061-9
|
| 10 |
+
10.1016/j.stemcr.2023.03.001
|
| 11 |
+
Article
|
| 12 |
+
WNT7A suppresses adipogenesis of skeletal muscle mesenchymal stem cells and fatty infiltration through the alternative Wnt-Rho-YAP/TAZ signaling axis
|
| 13 |
+
Fu Chengcheng 1
|
| 14 |
+
Chin-Young Britney 1
|
| 15 |
+
Park GaYoung 1
|
| 16 |
+
Guzmán-Seda Mariana 12
|
| 17 |
+
Laudier Damien 1
|
| 18 |
+
Han Woojin M. woojin.han@mssm.edu
|
| 19 |
+
13∗
|
| 20 |
+
1 Department of Orthopaedics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
|
| 21 |
+
2 Department of Biomedical Engineering, Polytechnic University of Puerto Rico, San Juan, PR, USA
|
| 22 |
+
3 Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
|
| 23 |
+
∗ Corresponding author woojin.han@mssm.edu
|
| 24 |
+
30 3 2023
|
| 25 |
+
11 4 2023
|
| 26 |
+
30 3 2023
|
| 27 |
+
18 4 9991014
|
| 28 |
+
30 6 2022
|
| 29 |
+
28 2 2023
|
| 30 |
+
1 3 2023
|
| 31 |
+
© 2023 The Author(s)
|
| 32 |
+
2023
|
| 33 |
+
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
|
| 34 |
+
Summary
|
| 35 |
+
|
| 36 |
+
Intramuscular fatty infiltration in muscle injuries and diseases, caused by aberrant adipogenesis of fibro-adipogenic progenitors, negatively impacts function. Intramuscular delivery of wingless-type MMTV integration site family 7a (WNT7A) offers a promising strategy to stimulate muscle regeneration, but its effects on adipogenic conversion of fibro-adipogenic progenitors remain unknown. Here, we show that WNT7A decreases adipogenesis of fibro-adipogenic progenitors (FAPs) by inducing nuclear localization of Yes-associated protein (YAP) through Rho in a β-CATENIN-independent manner and by promoting nuclear retention of YAP and transcriptional co-activator with PDZ-binding motif (TAZ) in differentiating FAPs. Furthermore, intramuscular injection of WNT7A in vivo effectively suppresses fatty infiltration in mice following glycerol-induced injury. Our results collectively suggest WNT7A as a potential protein-based therapeutic for diminishing adipogenesis of FAPs and intramuscular fatty infiltration in pathological muscle injuries or diseases.
|
| 37 |
+
|
| 38 |
+
Highlights
|
| 39 |
+
|
| 40 |
+
• WNT7A decreases the adipogenic potential of fibro-adipogenic progenitors
|
| 41 |
+
|
| 42 |
+
• WNT7A does not promote nuclear localization of β-CATENIN
|
| 43 |
+
|
| 44 |
+
• WNT7A promotes nuclear activation of YAP/TAZ in fibro-adipogenic progenitors
|
| 45 |
+
|
| 46 |
+
• Delivery of WNT7A decreases intramuscular fatty infiltration in vivo
|
| 47 |
+
|
| 48 |
+
In this article, Fu and colleagues show that WNT7A decreases adipogenesis of skeletal muscle-derived fibro-adipogenic progenitors. WNT7A promotes nuclear localization and retention of YAP/TAZ in a β-CATENIN-independent manner in differentiating fibro-adipogenic progenitors. When administered intramuscularly in vivo following glycerol-induced injury, WNT7A significantly suppressed fatty infiltration.
|
| 49 |
+
|
| 50 |
+
Keywords
|
| 51 |
+
|
| 52 |
+
WNT7a
|
| 53 |
+
skeletal muscle
|
| 54 |
+
fatty infiltration
|
| 55 |
+
adipogenesis
|
| 56 |
+
YAP/TAZ
|
| 57 |
+
fibro-adipogenic progenitors
|
| 58 |
+
mesenchymal stem cells
|
| 59 |
+
Published: March 30, 2023
|
| 60 |
+
==== Body
|
| 61 |
+
pmcIntroduction
|
| 62 |
+
|
| 63 |
+
Persistent fatty infiltration, known as myosteatosis, is a common hallmark of chronic skeletal muscle injuries and diseases that negatively impacts function and poses significant health and socioeconomic burden (Minagawa et al., 2013; Yamamoto et al., 2010). For example, in rotator cuff tendon injuries, irreversible fatty infiltration is prevalent in the associated muscles, which directly increases muscle dysfunction and retear rates following surgical repair (Fu et al., 2021; Gladstone et al., 2007; Park et al., 2015b). In muscular dystrophies, pervasive intramuscular fatty infiltration positively correlates with the disease severity (Li et al., 2015). Fatty infiltration is also common in the paraspinal and neck muscles of astronauts following spaceflights (Burkhart et al., 2019; McNamara et al., 2019). Recent evidence suggests that fibro-adipogenic progenitors (FAPs), a population of muscle-resident mesenchymal stem/stromal cells, are the primary cellular culprit that generates intramuscular fatty infiltration (Joe et al., 2010; Liu et al., 2016; Uezumi et al., 2010; Wosczyna et al., 2012). Although this link between FAPs and fatty infiltration is established, therapies that limit such pathologic fatty infiltration without compromising myogenesis currently do not exist.
|
| 64 |
+
|
| 65 |
+
FAPs play a critical role in muscle regeneration by secreting paracrine factors that promote activation and expansion of muscle stem/satellite cells (Joe et al., 2010; Uezumi et al., 2010; Wosczyna et al., 2012, 2019). Furthermore, skeletal muscles with depleted FAPs not only exhibit significantly impaired muscle regeneration but also lead to muscle atrophy under homeostatic conditions, highlighting the importance of FAPs in muscle maintenance (Wosczyna et al., 2019). Upon muscle injury, immune cells initially infiltrate the injured space to remove debris and activate both FAPs and satellite cells (Butterfield et al., 2006; Heredia et al., 2013; Tidball and Villalta, 2010). As the inflammation resolves, tumor necrosis factor α (TNF-α) released by macrophages induces apoptotic clearances of FAPs, while activated satellite cells continue to undergo myogenesis (Lemos et al., 2015). In chronic muscle pathology, however, FAPs undergo unchecked proliferation and give rise to adipocytes and myofibroblasts (Lemos et al., 2015). The resulting fatty infiltration and fibrosis perturb the highly aligned and organized muscle structure and consequently reduce the ability of muscles to contract and regenerate. Thus, identifying molecular mechanisms that regulate the adipogenic conversion of FAPs is critical for establishing strategies to combat pathologic fatty infiltration.
|
| 66 |
+
|
| 67 |
+
Intramuscular delivery of wingless-type MMTV integration site family 7a (WNT7A) offers a promising strategy to both stimulate muscle regeneration and prevent muscle degeneration (Han et al., 2019; von Maltzahn et al., 2012, 2013; Schmidt et al., 2020). WNT7A promotes myofiber hypertrophy through the non-canonical AKT/mTOR pathway and increases the symmetric expansion of muscle satellite cells through the non-canonical planar cell polarity pathway (Le Grand et al., 2009; von Maltzahn et al., 2011). In preclinical models of Duchenne muscular dystrophy, WNT7A administration significantly increases satellite cell quantity, myofiber hypertrophy, and muscle strength (von Maltzahn et al., 2012). Controlled delivery of WNT7A using a bioengineered hydrogel also increases satellite cell quantity and myofiber hypertrophy, presenting WNT7A as an effective therapeutic candidate for treating various acute and degenerative muscle conditions (Han et al., 2019). While the past findings collectively corroborate that WNT7A can be used as a potential pro-myogenic therapeutic, the effect of WNT7A on FAPs, and specifically whether it limits adipogenic conversion of FAPs, remains unknown.
|
| 68 |
+
|
| 69 |
+
The objective of this study was to determine the mechanistic effect of WNT7A on FAPs adipogenic conversion. By using freshly isolated primary murine FAPs, we demonstrate that WNT7A effectively decreases the adipogenic potential of FAPs. We show that while WNT7A does not directly increase nuclear localization of β-CATENIN, it does induce nuclear localization of Yes-associated protein (YAP) through Rho and promotes nuclear retention of YAP and transcriptional co-activator with PDZ-binding motif (TAZ) in differentiating FAPs. We additionally show that WNT7A suppresses intramuscular fatty infiltration following glycerol injury without negatively impacting myogenesis or causing fibrosis in vivo. Collectively, we provide mechanistic evidence that WNT7A effectively reduces adipogenesis of FAPs and intramuscular fatty infiltration.
|
| 70 |
+
|
| 71 |
+
Results
|
| 72 |
+
|
| 73 |
+
WNT7A decreases adipogenesis of FAPs
|
| 74 |
+
|
| 75 |
+
To evaluate the effect of WNT7A on lineage specification of differentiating FAPs, we carried out a series of in vitro experiments using primary murine FAPs. Primary FAPs (CD31−, CD45−, ITGA7−, SCA1+) were isolated from the hindlimb muscles of C57Bl6/J mice using previously reported methods (Figure S1A) (Marinkovic et al., 2019). Freshly isolated FAPs express PDGFRα (80.4% ± 4.8%; Figure S1B), a defining marker of murine FAPs (Joe et al., 2010; Uezumi et al., 2010). Primary FAPs differentiated into myofibroblasts characterized by stress fibers expressing α-smooth muscle actin (αSMA) when maintained in fibrogenic differentiation medium (FM) for 4 days (Figures S1C and S1D; p < 0.001), but when maintained in adipogenic differentiation medium (ADM) for 4 days, FAPs differentiated into oil red O (ORO)+/PLIN1+ adipocytes (Figures S1C–S1F; p < 0.001). Collectively, these results confirm the functional identity of the isolated primary FAPs to be used in the subsequent experiments.
|
| 76 |
+
|
| 77 |
+
To determine the dose-dependent effect of WNT7A on the adipogenic potential of FAPs, we seeded freshly isolated FAPs in a dish and let the cells proliferate to near confluency for 4 days in growth media. Proliferating FAPs were further maintained in growth medium (GM ± WNT7A) or ADM (ADM ± WNT7A) for an additional 3–4 days (Figure 1A). Note, in GM, the FAPs begin to spontaneously differentiate into both myofibroblasts and adipocytes (Joe et al., 2010). In both GM and ADM, WNT7A decreased adipogenesis in a dose-dependent manner (Figures 1B and 1C). The dose of 200 ng/mL significantly reduced the formation of ORO+ adipocytes compared with the control (0 ng/mL; Figures 1B and 1C; p < 0.01). Based on this, we chose to use 200 ng/mL for the subsequent in vitro experiments.Figure 1 WNT7A decreases FAP adipogenesis
|
| 78 |
+
|
| 79 |
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(A) Experimental timeline. GM, growth media; ADM, adipogenic differentiation media; AMM, adipogenic maintenance media.
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(B) Percentage of ORO+ cells treated with varying doses of WNT7A. Two-way ANOVA with Bonferroni post-hoc analyses. Mean ± SEM. Dose effect p = 0.0021. Media effect p < 0.0001. ∗∗p < 0.01. n = 4. Colors represent biological replicates.
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| 82 |
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(C) Representative images of ORO-labeled cells treated with varying doses of WNT7A. Scale bar: 100 μm.
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| 84 |
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(D) Representative immunofluorescence images of perilipin-labeled FAPs cultured in GM and ADM ± WNT7A (200 ng/mL). Scale bar: 100 μm.
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(E) Perilipin area normalized by cell quantity. Two-tailed unpaired t test. ∗p < 0.05. n = 6. Dotted line: mean of GM.
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(F) Representative immunofluorescence images of PPARγ-labeled FAPs cultured in GM and ADM ± WNT7A (200 ng/mL). Scale bar: 100 μm. Inset scale bar: 25 μm.
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| 90 |
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(G) Percentage of PPARγ+ nuclei. Two-tailed unpaired t test. ∗∗p < 0.01. n = 4. Dotted line: mean of GM.
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| 92 |
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To further validate the effect of WNT7A on the suppression of FAPs adipogenesis, we cultured freshly isolated FAPs to near confluency and subsequently maintained the cells in either GM or ADM, with or without 200 ng/mL WNT7A (Figure 1A). Note, the dH2O vehicle for WNT7A (0.2% v/v in media) does not affect FAP adipogenesis (Figure S2). WNT7A significantly reduced the formation of PLIN1+ (perilipin; lipid droplet-associated protein) adipocytes (Figures 1D and 1E; p < 0.0001) as well as nuclear activation of PPARγ, a master regulator of adipogenesis, compared with the control (Figures 1F and 1G; p < 0.01). In the adipogenic condition, WNT7A also reduced PLIN1 and PPARγ expressions to below the mean of spontaneously differentiating condition (GM; Figures 1D–1G). These results demonstrate that WNT7A effectively decreases the adipogenic potential of FAPs.
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We next quantified the number of cells expressing αSMA+ stress fibers, a hallmark of activated myofibroblasts (Goffin et al., 2006; Hinz, 2007), to determine if WNT7A increases fibrogenesis in the adipogenic condition. We observed that PLIN1− FAPs in ADM with or without WNT7A treatment exhibited a base level of diffuse αSMA, but only in the fibrogenic (FM) and spontaneously differentiating (GM) conditions did the FAPs differentiate into myofibroblasts, exhibiting structurally apparent αSMA+ stress fibers (Figures S3A and S3B). In ADM with or without WNT7A treatment, significantly fewer αSMA stress fibers-expressing myofibroblasts formed (Figures S3A and S3B; p < 0.0001). This suggests that WNT7A does not promote fibrogenesis in adipogenic culture conditions in vitro. WNT7A treatment also did not affect cell viability and proliferation (Figures S3C, S3D, and S4). Altogether, these results demonstrate that WNT7A dampens adipogenesis of FAPs without promoting fibrogenesis in adipogenic conditions in vitro.
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WNT7A reduces adipogenesis of FAPs in a β-CATENIN-independent manner
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The canonical Wnt signaling inhibits adipogenesis through suppression of the adipogenic transcription factor PPARγ in preadipocytes, marrow-derived mesenchymal stromal cells, and muscle FAPs (Bennett et al., 2002; Kang et al., 2007; Longo et al., 2004; Moldes et al., 2003; Reggio et al., 2020; Ross et al., 2000). To determine if WNT7A inhibits adipogenesis of FAPs through the canonical Wnt pathway, we cultured freshly isolated FAPs in the GM for 4 days and then subsequently treated the cells in the ADM containing WNT7A (200 ng/mL) or the prototypically canonical activator WNT3A (200 ng/mL) for 4 or 48 h (Figures 2A–2C). As expected, brief 4-h treatment with WNT3A exhibited significantly increased nuclear intensity of β-CATENIN compared with both vehicle control and WNT7A conditions (Figures 2B and 2D; p < 0.05 vs. WNT7A, p < 0.01 vs. control). Similarly, WNT3A treatment significantly increased the percentage of β-CATENIN+ nuclei compared with both the vehicle control and WNT7A (Figure 2E; p < 0.05 vs. WNT7A and control). However, FAPs treated with WNT7A did not exhibit an increased nuclear intensity of β-CATENIN after 4- and 48-h treatment compared with the vehicle control (Figures 2B–2F). WNT7A also had no effects on the percentage of β-CATENIN+ nuclei after 4- and 48-h treatment (Figures 2E and 2G). Gene expression analyses of Wnt-related genes of FAPs after 2-day WNT7A treatment revealed that genes related to the canonical WNT signaling (e.g., Lrp5, Lrp6, Axin1, Axin2, Gsk2b, and Ctnnb1) were insignificantly altered (Figures S5A and S5B). These data collectively suggest that WNT7A suppresses adipogenesis of FAPs in a β-CATENIN-independent manner.Figure 2 WNT7A reduces adipogenesis of FAPs in a β-CATENIN-independent manner
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(A) Experimental timeline of β-CATENIN expression and adipogenesis study. GM, growth media; ADM, adipogenic differentiation media.
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(B) Representative immunofluorescence images of β-CATENIN-labeled FAPs treated with vehicle, WNT3A (200 ng/mL), and WNT7A (200 ng/mL) for 4 h. Scale bar: 100 μm.
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(C) Representative immunofluorescence images of β-CATENIN-labeled FAPs treated with vehicle and WNT7A (200 ng/mL) for 48 h. Scale bar: 100 μm.
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(D) Nuclear β-CATENIN intensity analyzed at the 4-h time point. >1,000 cells analyzed per condition in an automated manner from n = 3 biological replicates. One-way ANOVA with Tukey’s post-hoc analyses applied on the medians of biological donors. Mean ± SEM. ∗p < 0.05; ∗∗p < 0.01. n = 3. Colors represent biological replicates. Dotted line (at 10 a.u.) indicates the mean of WNT3A condition.
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(E) Percentage of β-CATENIN+ nuclei analyzed at the 4-h time point. One-way ANOVA with Tukey’s post-hoc analyses. Mean ± SEM. ∗p < 0.05. n = 3. Colors represent biological replicates.
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(F) Nuclear β-CATENIN intensity analyzed at the 48-h time point. >440 cells analyzed per condition from n = 4 biological replicates. Two-tailed unpaired t test applied on the medians of biological donors. Mean ± SEM. n = 4. Colors represent biological replicates. Dotted line (at 10 a.u.) indicates the mean of WNT3A condition from (D).
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(G) Percentage of β-CATENIN+ nuclei analyzed at the 48-h time point. Two-tailed unpaired t test. Mean ± SEM. n = 4. Colors represent biological replicates.
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(H) Representative images of ORO-labeled cells treated with DMSO, PNU74654 (50 μM), and PNU74654 (50 μM) + WNT7A (200 ng/mL). Scale bar: 100 μm.
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(I) Percentage of ORO+ cells with DMSO-, PNU74654-, and PNU74654 + Wnt7a-treated conditions. One-way ANOVA with Tukey’s post-hoc analyses. Mean ± SEM. ∗p < 0.05; ∗∗p < 0.01. n = 4. Colors represent biological replicates.
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To further corroborate this finding, we next sought to inhibit the activity of β-CATENIN using a small-molecule inhibitor, PNU-74654. This inhibitor specifically prevents the binding of β-CATENIN and the T cell factor (TCF) in the nucleus. In this assay, we found that concentrations beyond 50 μM diminish FAP proliferation in vitro, and thus we chose to use 50 μM for the inhibition study (Figure S5C). As expected, inhibiting β-CATENIN/TCF binding with PNU-74654 significantly increased FAP adipogenesis compared with the DMSO vehicle control (Figures 2H and 2I; p < 0.01). However, treating FAPs with both WNT7A and PNU-74654 resulted in a marked reduction in adipogenesis compared with the PNU-74654 condition (Figures 2H and 2I; p < 0.05). This serves as additional evidence that WNT7A suppresses adipogenesis of FAPs in a β-CATENIN-independent manner, as WNT7A effectively reduces adipogenesis, while β-CATENIN activity remains inhibited.
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WNT7A induces nuclear localization and retention of YAP
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Actin cytoskeleton disassembly through Rho-ROCK signaling and subsequent cell area changes drive adipogenic differentiation of the mouse 3T3-L1 preadipocyte cell line and human stromal stem cells (Chen et al., 2018; Nobusue et al., 2014). To determine whether WNT7A reduces FAP adipogenesis through modulation of cell area and morphology, we expanded freshly isolated FAPs for 4 days and then cultured the cells in either growth and adipogenic differentiation, with or without WNT7A (Figure 3A). FAPs in the adipogenic condition (ADM) exhibited significantly reduced cell area compared with the growth condition (GM; Figures 3B and 3C; p < 0.0001). Note that this decrease in cell area is also accompanied by elevated levels of nuclear PPARγ (Figure 3B). In ADM, WNT7A significantly increased cell area and maximum (max) Feret diameter compared with its WNT7A-free control (Figures 3B–3D; p < 0.0001). In the spontaneously differentiating growth condition (GM), WNT7A also significantly increased both cell area and max Feret diameter compared with its WNT7A-free control (Figures 3B–3D; p < 0.001). WNT7A-treated FAPs in ADM also exhibited cell area and morphology comparable to FAPs maintained in WNT7A-free GM (Figures 3B and 3C). WNT7A treatment does not alter cell density and proliferation (Figure S4), ruling out the possibility of cell density affecting these measurements. Therefore, these results suggest that WNT7A in the adipogenic condition prevents the shrinking of cell area and maintains morphology.Figure 3 WNT7A induces nuclear localization and retention of YAP
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(A) Experimental timeline of cell morphology and YAP quantification. GM, growth media; ADM, adipogenic differentiation media.
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(B) Representative images of F-actin- and PPARγ-labeled FAPs. Scale bar: 50 μm.
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(C) Cell area quantification. Kruskal-Wallis test with Dunn’s multiple comparisons. Median ± interquartile range (IQR). ∗∗p < 0.01; ∗∗∗p < 0.001; ∗∗∗∗p < 0.0001. n = 179–219 cells analyzed from 3 biological replicates.
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| 130 |
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(D) Max Feret diameter quantification. Kruskal-Wallis test with Dunn’s multiple comparisons. Median ± IQR. ∗∗∗p < 0.001; ∗∗∗∗p < 0.0001. n = 179–219 cells analyzed from 3 biological replicates. Colors represent biological replicates (C and D).
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(E) Representative immunofluorescence images of YAP-labeled cells after 4-h treatment in GM ± Wnt7a (200 ng/mL) and ADM ± WNT7A (200 ng/mL). Scale bar: 100 μm.
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(F) Quantification of YAP nuclear:cytosol intensity ratio at the 4-h time point. Values were log transformed. Kruskal-Wallis with Dunn’s post-hoc analyses. Median ± IQR. ∗∗∗∗p < 0.0001. n = 180 cells analyzed from 3 biological replicates. Colors represent biological replicates.
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| 136 |
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| 137 |
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(G) Percentage of YAP+ nuclei. One-way ANOVA with Tukey’s post-hoc analyses. Mean ± SEM. ∗p < 0.05; ∗∗p < 0.01. n = 3. Colors represent biological replicates.
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| 138 |
+
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(H) Representative immunofluorescence images of YAP-labeled cells after 3-day treatment in GM ± WNT7A (200 ng/mL) and ADM ± WNT7A (200 ng/mL). Scale bars: 25 μm.
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(I) Quantification of YAP nuclear:cytosol intensity ratio of the 3-day time point. Values were log transformed. Kruskal-Wallis with Dunn’s post-hoc analyses. Median ± IQR. ∗p < 0.05; ∗∗p < 0.01; ∗∗∗∗p < 0.0001. n = 179 cells analyzed from 3 biological replicates. Colors represent biological replicates.
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| 142 |
+
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| 143 |
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(J) Percentage of YAP+ nuclei. One-way ANOVA with Tukey’s post-hoc analyses. Mean ± SEM. ∗∗p < 0.01; ∗∗∗p < 0.001; ∗∗∗∗p < 0.0001. n = 3. Colors represent biological replicates.
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| 144 |
+
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| 145 |
+
YAP-1 and its paralog TAZ act as biochemical mechanotransducers that convert mechanical cues and resulting cellular changes (e.g., cell contractility and shape) into cell-specific transcriptional activities (Dupont et al., 2011). Recent evidence also suggests that YAP/TAZ also act as downstream modulators of Wnt pathways (Azzolin et al., 2012, 2014; Park et al., 2015a). Based on such evidence and our observation that WNT7A reduces FAP adipogenesis by maintaining cellular shape (Figures 3B–3D), we next questioned whether non-canonical WNT7A signaling promotes nuclear localization of YAP (Figure 3A). Nearly all freshly isolated and proliferating FAPs exhibited higher cytosolic YAP in vitro (Figures 3E–3G). Culturing the proliferating FAPs in WNT7A-containing GM and ADM for 4 h significantly increased the YAP nuclear-to-cytosolic ratio compared with their respective controls (Figures 3E and 3F; p < 0.0001). YAP nuclear localization was also significantly higher in ADM containing WNT7A compared with GM containing WNT7A (Figures 3E and 3F; p < 0.0001), suggesting context-dependent responsivity. The percentage of YAP+ nuclei also significantly increased when FAPs were treated in ADM containing WNT7A compared with all other groups, further corroborating this finding (Figures 3E and 3G; p < 0.05). These results indicate that WNT7A promotes nuclear localization of YAP in proliferating FAPs in vitro.
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| 146 |
+
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| 147 |
+
To further determine if prolonged exposure of FAPs to WNT7A promotes nuclear retention of YAP, we cultured FAPs in growth (GM) and adipogenic (ADM) conditions with or without WNT7A supplementation for 3 days (Figure 3A). In GM, we observed a bimodal distribution of cells expressing nuclear and cytosolic YAP (Figures 3H and 3I), likely indicating the bifurcating lineage commitment of FAPs, but WNT7A significantly increased nuclear retention of YAP (Figures 3H and 3I; p < 0.05). By day 3, FAPs undergoing adipogenesis in ADM exhibited cytosolic YAP (Figures 3H–3J). In ADM, 3-day treatment with WNT7A significantly increased the nuclear retention of YAP and the percentage of YAP+ nuclei compared with its control (Figures 3H–3J; p < 0.01). In addition, this WNT7A treatment also resulted in a comparable distribution of cells exhibiting nuclear and cytosolic YAP (i.e., bimodal) with GM without WNT7A (Figures 3H and 3I; p > 0.05). Finally, we conducted an additional experiment to determine if WNT7A-induced nuclear retention of YAP correlates with non-adipogenic FAPs. To do this, we cultured the FAPs in adipogenic conditions (ADM) with WNT7A for 3 days and co-immunolabeled the cells for both YAP and PLIN1 (Figure S6A). Approximately 85% of cells expressing nuclear YAP were PLIN1− (Figures S6B and S6C), while approximately 35% of the cells expressing nuclear YAP were PLIN1+ (Figures S6B and S6C), indicating that WNT7A-induced nuclear retention of YAP negatively correlates with the adipogenic FAPs. Collectively, these data suggest that WNT7A treatment promotes nuclear localization and retention of YAP, and this likely decreases the adipogenic potential of FAPs.
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| 148 |
+
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| 149 |
+
WNT7A promotes YAP nuclear localization through Rho
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| 150 |
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| 151 |
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We next asked whether WNT7A promotes nuclear localization of YAP through the alternative Wnt signaling axis involving Wnt-FZD/ROR-Rho GTPases-Lats1/2 (Park et al., 2015a; Thorup et al., 2020). In the alternative Wnt signaling, inhibition of Rho prevents Wnt-induced YAP activation. To mechanistically test this hypothesis, we pretreated FAPs in adipogenic media (ADM) containing a Rho GTPase inhibitor (purified C3 transferase; CT04) or vehicle (dH2O) for 2 h (Figure 4A). The cells were further maintained in ADM with or without CT04 and WNT7A for an additional 4 h (Figure 4A). Here, we note that 6-h culture in ADM begins to increase the fraction of FAPs exhibiting YAP nuclear localization, contributing to an insignificant increase in the percentage of YAP+ nuclei following WNT7A treatment (Figures 4B and 4C). Even so, WNT7A significantly increased the nuclear intensity ratio of YAP compared with the ADM control (Figure 4D; p < 0.0001). Rho inhibition alone did not significantly affect the nuclear intensity ratio of YAP compared with the control (Figure 4D). However, when Rho was inhibited, WNT7A failed to increase the nuclear intensity ratio of YAP (Figure 4D). The overall fraction of FAPs with nuclear or cytosolic YAP also remained unaffected when treated with WNT7A with Rho inhibited (Figure 4E). In sum, the results suggest that Rho is required for WNT7A-induced activation of YAP in FAPs.Figure 4 WNT7A activates YAP through Rho
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| 152 |
+
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| 153 |
+
(A) Experimental timeline of Rho inhibition study. GM, growth media; ADM, adipogenic differentiation media.
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| 154 |
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| 155 |
+
(B) Representative immunofluorescence images of YAP-labeled cells. Scale bar: 50 μm.
|
| 156 |
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| 157 |
+
(C) Percentage of YAP+ nuclei. One-way ANOVA with Tukey’s post-hoc analyses. n = 5. Colors represent biological replicates.
|
| 158 |
+
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| 159 |
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(D) Quantification of YAP nuclear:cytosol intensity ratio. Values were log transformed. Kruskal-Wallis with Dunn’s post-hoc analyses. Median ± IQR. ∗∗∗∗p < 0.0001. n = 300 cells analyzed from 5 biological replicates. Colors represent biological replicates.
|
| 160 |
+
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| 161 |
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(E) Quantification of the cell proportions with nuclear and cytoplasmic YAP localization. Chi-squared tests. Adjusted p values for Bonferroni correction.
|
| 162 |
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| 163 |
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WNT7A promotes nuclear retention of TAZ
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| 164 |
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| 165 |
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TAZ, a paralog of YAP-1, regulates the differentiation potential of mesenchymal stem cells by directly repressing PPARγ while activating Runx2 genes (Hong et al., 2005). To test if WNT7A promotes TAZ nuclear localization in a similar manner to YAP, we maintained proliferating FAPs in the GM or ADM containing WNT7A for 4 h (Figure 5A). In contrast to YAP (Figures 3E–3G), most FAPs exhibited higher nuclear TAZ in vitro (Figures 5B–5D). WNT7A treatment in either the growth or adipogenic condition did not result in further increases in nuclear TAZ intensity (Figures 5B–5D), suggesting that WNT7A does not promote nuclear localization of TAZ in proliferating FAPs in vitro.Figure 5 WNT7A promotes nuclear retention of TAZ
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| 166 |
+
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| 167 |
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(A) Experimental timeline of TAZ quantification. GM, growth media; ADM, adipogenic differentiation media.
|
| 168 |
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| 169 |
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(B) Representative immunofluorescence images of TAZ-labeled cells after 4-h treatment in GM ± WNT7A (200 ng/mL) and ADM ± WNT7A (200 ng/mL). Scale bar: 50 μm.
|
| 170 |
+
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| 171 |
+
(C) Quantification of TAZ nuclear:cytosol intensity ratio at the 4-h time point. Values were log transformed. Median ± IQR. n = 180 cells analyzed from 3 biological replicates. Colors represent biological replicates.
|
| 172 |
+
|
| 173 |
+
(D) Percentage of TAZ+ nuclei at the 4-h time point. Mean ± SEM. n = 3. Colors represent biological replicates.
|
| 174 |
+
|
| 175 |
+
(E) Representative immunofluorescence images of TAZ-labeled cells after 24-h treatment in ADM ± WNT7A (200 ng/mL). Scale bar: 50 μm.
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| 176 |
+
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| 177 |
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(F) Quantification of TAZ nuclear:cytosol intensity ratio at the 24-h time point. Values were log transformed. Two-tailed unpaired t test. Median ± IQR. ∗∗∗∗p < 0.0001. n = 180 cells analyzed from 3 biological replicates. Colors represent biological replicates.
|
| 178 |
+
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| 179 |
+
(G) Percentage of TAZ+ nuclei at the 24-h time point. Two-tailed unpaired t test. Mean ± SEM. ∗∗p < 0.01. n = 3. Colors represent biological replicates.
|
| 180 |
+
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| 181 |
+
To determine if WNT7A promotes nuclear retention of TAZ in differentiating FAPs, we maintained FAPs in the ADM containing WNT7A for 24 h (Figure 5A). Nearly 80% of FAPs maintained in the ADM without WNT7A exhibited cytosolic TAZ (Figures 5E–5G), suggesting that adipogenic FAPs displace TAZ from their nucleus to cytosol. However, 24-h WNT7A treatment significantly increased nuclear retention of TAZ, quantified by both the nuclear intensity ratio of TAZ and the percentage of TAZ+ nuclei (Figures 5E–5G; p < 0.01). In GM, FAPs homogeneously expressed nuclear TAZ at this time point, and WNT7A treatment did not further alter the TAZ nuclear localization (Figures S6D–S6F). Altogether, the results suggest that while WNT7A does not stimulate nuclear localization of TAZ, it effectively promotes nuclear retention of TAZ in differentiating FAPs in the adipogenic condition.
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| 182 |
+
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| 183 |
+
WNT7A suppresses fatty infiltration in skeletal muscle
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| 184 |
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| 185 |
+
We next sought to evaluate the efficacy of WNT7A in suppressing intramuscular fatty infiltration in vivo using the glycerol injury model. Intramuscular injection of glycerol stimulates a robust and reproducible fatty infiltration without affecting muscle regeneration, thus serving as an excellent proof-of-concept in vivo model to evaluate therapeutics targeted for reducing intramuscular adipogenesis (Pisani et al., 2010). To induce injury, tibialis anterior (TA) muscles were injected with glycerol (50% v/v). WNT7A or saline was injected into the belly of the injured TA muscles 1 day post-injury (Figure 6A). The muscles were then harvested 14 days post-injury for analyses (Figure 6A). Glycerol-injured TAs with saline treatment exhibited a severe fatty infiltration, marked by PLIN1 expression within the interstitial space (Figures 6B and S7A). However, glycerol-injured TAs with WNT7A treatment exhibited a significantly reduced PLIN1 expression (Figures 6B, 6C, and S9A; p < 0.05). We observed no statistically significant differences in the myofiber area distribution (Figures 6D and 6E). We also observed no qualitative and quantitative differences in fibrosis assessed by trichrome staining and polarized light imaging (Figures S7B–S7D). These data collectively show that WNT7A effectively suppresses intramuscular fatty infiltration in vivo without negatively impacting myogenesis or inducing fibrosis.Figure 6 WNT7A suppresses fatty infiltration in skeletal muscle
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| 187 |
+
(A) Experimental timeline outlining in vivo glycerol injection, WNT7A administration, and analyses. Created with BioRender.
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| 188 |
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| 189 |
+
(B) Representative cross-sections of glycerol-injured TA muscles treated with WNT7A or saline. Scale bars: 500 μm.
|
| 190 |
+
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| 191 |
+
(C) Perilipin area normalized by the TA cross-sectional area. Two-tailed unpaired t test. ∗p = 0.027.
|
| 192 |
+
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| 193 |
+
(D) Median fiber cross-sectional area. Two-tailed unpaired t test.
|
| 194 |
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| 195 |
+
(E) Histogram of fiber cross-sectional area. Mean ± SEM.
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| 196 |
+
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Discussion
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Persistent fatty infiltration is a chronic hallmark of skeletal muscle injuries and diseases, such as rotator cuff injuries and Duchenne muscular dystrophy (Fu et al., 2021; Li et al., 2015). WNT7A has been emerging as a potential therapeutic for muscle diseases and injuries due to its pro-regenerative effects on muscle satellite cells and myofibers (Han et al., 2019; Le Grand et al., 2009; von Maltzahn et al., 2011), but its effects on FAPs remain unknown. Thus, addressing the effects of WNT7A in modulating fatty infiltration and FAP function is critical for translating WNT7A as a potential therapeutic. In this study, we determined the mechanistic effect of WNT7A on adipogenesis of FAPs, which are the precursors to fatty infiltration in skeletal muscle pathology (Joe et al., 2010; Liu et al., 2016; Uezumi et al., 2010; Wosczyna et al., 2012). Our data reveal that WNT7A suppresses adipogenesis by inducing nuclear localization of YAP through Rho and, subsequently, by promoting nuclear retention of YAP and TAZ.
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| 200 |
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The mechanistic role of canonical Wnt signaling and β-CATENIN in suppressing adipogenesis is well established in other cell types (Bennett et al., 2002; Kang et al., 2007; Longo et al., 2004; Moldes et al., 2003; Reggio et al., 2020; Ross et al., 2000). For instance, WNT5A reduces adipogenesis of FAPs through canonical Wnt signaling (Reggio et al., 2020). Thus, we first sought to determine if WNT7A increased nuclear β-CATENIN through the canonical pathway in FAPs. WNT7A did not increase nuclear β-CATENIN in FAPs (Figures 2B–2G). Furthermore, WNT7A remained effective in reducing adipogenesis even when β-CATENIN activity was inhibited using PNU-74654 (Figures 2H and 2I), suggesting that WNT7A acts through a non-canonical pathway. We also observed that WNT7A retained a larger cell area of FAPs in adipogenic culture conditions while preventing adipogenesis (Figures 3B–3D). Based on these findings, we then asked if WNT7A acts through alternative Wnt signaling, where YAP is activated through the Wnt-FZD/Ror-Rho GTPases-Lats1/2 signaling axis independent of β-CATENIN (Park et al., 2015a). In support of our hypothesis, a brief 4-h WNT7A treatment induced nuclear localization of YAP in FAPs (Figures 3E–3G). We found that WNT7A failed to induce nuclear localization of YAP when Rho was inhibited using CT04 (Figure 4). These data suggest that WNT7A activates YAP through Rho-dependent alternative Wnt signaling in FAPs (Figure S10). These findings also raise an interesting hypothesis in which fatty infiltration that arises from skeletal muscle unloading (Kaneshige et al., 2022) may potentially be compensated through exogenous WNT7A that acts through the mechanosignaling pathway involving Rho and YAP (Figure 7). In contrast to YAP, however, we found that WNT7A does not promote TAZ nuclear localization (Figures 5B–5D). This is likely because most proliferating FAPs express nuclear TAZ (Figures 5B–5D), while YAP is localized in the cytosol (Figures 3E–3G). Nonetheless, FAPs differentiating into adipogenic lineage begin to displace both YAP and TAZ from their nuclei, and WNT7A promotes nuclear retention of YAP and TAZ. (Figures 3H–3J, 5E–5G, and 7).Figure 7 WNT7A retains nuclear YAP/TAZ and decreases FAP adipogenesis
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(A) During adipogenesis, YAP/TAZ translocate to cytosol. WNT7A promotes nuclear retention of YAP/TAZ within the nucleus, thereby preventing FAP adipogenesis.
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(B) WNT7A may rescue mechanical unloading-induced FAP adipogenesis by reinforcing YAP/TAZ activity through cell contractility-mediated mechanisms.
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How does WNT7A-induced YAP/TAZ nuclear retention inhibit PPARγ and adipogenesis of FAPs? First, published evidence suggests that the nuclear activity of YAP/TAZ inhibits adipogenesis by repressing PPARγ in multiple cell types (Deng et al., 2019; El Ouarrat et al., 2020; Hong et al., 2005; Lorthongpanich et al., 2019; Pan et al., 2018). Specifically, TAZ directly represses PPARγ while activating Runx2 genes in mesenchymal stem cells (Hong et al., 2005). The same mechanism may also be reducing the adipogenesis of FAPs when treated with WNT7A because WNT7A promotes nuclear retention of YAP/TAZ in differentiating FAPs and suppresses adipogenesis. Second, YAP/TAZ activity and TEAD-induced transcription may trigger the secretion of canonical Wnt modulators (Park et al., 2015a). As noted above, Wnt/β-CATENIN signaling is a crucial mediator of adipogenesis, where its downregulation results in the differentiation of preadipocytes into mature adipocytes (Bennett et al., 2002; Longo et al., 2004; Ross et al., 2000). In the current study, we observed that inhibiting β-CATENIN activity using PNU-74654 alone increased adipogenesis of FAPs (Figures 2H and 2I), suggesting that β-CATENIN indeed plays a role in modulating adipogenesis. However, WNT7A did not promote nuclear localization of β-CATENIN in FAPs after 4- and 48-h treatment (Figures 2B–2G), nor did it significantly increase expressions of genes related to the canonical Wnt signaling (Figures S5A and S5B), suggesting that WNT7A-induced YAP/TAZ activity does not significantly upregulate the canonical Wnt signaling. Interestingly, Wisp1, which directly binds and represses PPARγ to inhibit adipogenesis (Ferrand et al., 2017), was significantly upregulated with WNT7A treatment.
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WNT7A promotes nuclear localization of YAP through Rho, increases nuclear retention of YAP/TAZ in differentiating FAPs, and suppresses adipogenesis, but it is currently unclear which receptors expressed by FAPs are binding to WNT7A to elicit the observed downstream effects. WNT7A binds to FZD7 to promote satellite cell expansion and myotube hypertrophy (Le Grand et al., 2009; von Maltzahn et al., 2011), and because FZD7 is also expressed by the FAPs (Reggio et al., 2020), it is also likely that WNT7A promotes nuclear localization and retention through FZD7. Furthermore, based on the published prior studies that describe the mechanistic link between the Wnt and Hippo signaling pathways (Park et al., 2015a; Thorup et al., 2020), we speculate that WNT7A acts by binding to the Frizzled and tyrosine kinase-like orphan receptor-1/2 (ROR1/2) complexes. In this non-canonical pathway, the binding of Wnt ligands to Frizzled and ROR1/2 co-receptors increases Rho activity that subsequently inhibits Lats1/2 (Park et al., 2015a; Thorup et al., 2020). Interestingly, querying the publicly available single-nucleus skeletal muscle gene expression database (https://research.cchmc.org/myoatlas/) (Petrany et al., 2020) revealed that ROR1 is highly expressed by murine FAPs at all ages (postnatal day 3 through 30 months of age). Whether WNT7A binds the ROR1 co-receptor to promote YAP/TAZ nuclear localization and retention remains to be addressed in future studies.
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While in vivo administration of WNT7A to the glycerol-injured TA significantly suppressed fatty infiltration, WNT7A did not improve muscle regeneration. This is in contrast to previous findings that demonstrated that WNT7A enhances muscle regeneration (Han et al., 2019; Le Grand et al., 2009; von Maltzahn et al., 2011). The difference between the current and prior findings on the effect of WNT7A on muscle regeneration is likely due to different modes of injury used: cardiotoxin vs. glycerol. While cardiotoxin and glycerol injections induce comparable levels of muscle damage, the regeneration rate following glycerol-induced injury is dampened compared with cardiotoxin-induced injury (Lukjanenko et al., 2013). Furthermore, ectopic fatty infiltration formed following glycerol-induced injury is significantly higher compared with cardiotoxin injection, which may further reduce WNT7A-induced regeneration and hypertrophy (Lukjanenko et al., 2013). Finally, glycerol-induced injury also elicits increased gene expression of anti-inflammatory cytokines compared with cardiotoxin (Lukjanenko et al., 2013). These differences, along with the single time point assessed in the current study, likely contribute to an insignificant improvement in regeneration.
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The current study has its limitations. Our current in vitro experiments applied a narrow time frame in which these FAPs are either spontaneously differentiating or induced to differentiate in cell culture settings. Future investigations will validate the observed mechanisms using clinically relevant in vivo injury and disease models. The cellular identity of the WNT7A-treated FAPs in vivo is also an important consideration. To further develop WNT7A as therapeutic, potential cross-talk between FAPs and other cell populations should be considered in vivo in a context-dependent manner as well. Functional measures, including muscle contractile force, mouse gait, and fibrosis, should also be considered to comprehensively evaluate WNT7A as a potential therapeutic. Ultimately, an effective delivery method using biomaterials such as engineered hydrogels should be tested to show the effectiveness and efficiency of WNT7A release on therapeutic models.
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In conclusion, we identified that WNT7A suppresses adipogenesis of FAPs by inducing nuclear localization of YAP through Rho in a β-CATENIN-independent manner and by promoting nuclear retention of YAP and TAZ. Our data provide insight into applying WNT7A as a potential therapeutic for mitigating intramuscular fatty infiltration in various skeletal muscle pathologies.
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Experimental procedures
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Resource availability
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Corresponding author
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Request for resources, reagents, and protocols should be addressed to the corresponding author, Woojin M. Han, PhD (woojin.han@mssm.edu).
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Materials availability
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This study did not generate unique materials.
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Mice
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All animal procedures were conducted under the approved protocol by the Icahn School of Medicine at Mount Sinai Institutional Animal Care and Use Committee. Mice were housed and maintained in the Center for Comparative Medicine and Surgery Facility of the Icahn School of Medicine at Mount Sinai. C57BL/6J mice were acquired from the Jackson Laboratory (stock #000664). Both male and female mice were used in a randomized manner.
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Glycerol injuries and WNT7A administration
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2-month-old mice were anesthetized with isoflurane. 50 μL 50% glycerol in saline was intramuscularly injected into both TA muscles. After 24 h, 2.5 μg/30 μL recombinant human WNT7A (PeproTech) and 30 μL saline were injected into the TA muscles in a randomized manner. Buprenorphine shots were subcutaneously administered every 12 h at the onset of the procedure for 3 days. Mice were sacrificed on day 14 for histological analyses.
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Isolation of FAPs
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Primary FAPs were isolated from 4- to 6-week-old mice by magnetic-activated cell sorting (MACS) as described previously (Marinkovic et al., 2019). Mouse hindlimb muscles were dissected and incubated in digestion media (2.5 U/mL Dispase II, Thermo Fisher Scientific, and 0.2% w/v collagenase type II, Worthington, in DMEM) on a shaking incubator at 37°C for 1.5 h. Deactivation media (20% FBS in Ham’s F-10; Gibco) was added to inactivate the reaction. The muscle digest was filtered through a 70-μm cell strainer and then centrifuged (300 × g, 5 min, 4°C). Cell pellets were resuspended in Staining Buffer (0.5% bovine serum albumin and 2 mM EDTA in PBS) and filtered through a 35-μm cell strainer. Cells were incubated with biotin anti-mouse CD31 (BioLegend, cat. no. 102503; 1:150), Biotin anti-mouse CD45 (BioLegend, cat. no. 103103; 1:150), and biotin anti-integrin α7 (Miltenyi, cat. no. 130-101-979; 1:10) antibodies at 4°C for 45 min. Cells were pelleted through centrifugation and incubated with 10 μL streptavidin beads (1:30) at 4°C for 15 min. Labeled cells were passed through an LD column (Miltenyi) for negative selection. The remaining cells were incubated with biotin anti-mouse Ly-6A/E (SCA-1) antibody (BioLegend, cat. no. 122504; 1:75) at 4°C for 20 min and then 10 μL streptavidin beads (1:30) at 4°C for 10 min. Cells were then passed through an LS column (Miltenyi) and enriched for SCA-1+ cells. Cells were filtered through a 35-μm cell strainer once more before cell seeding.
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FAP culture and differentiation
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Isolated FAPs were seeded at ∼10,000 cells per 1 cm2 well in GM (10% FBS and 1× penicillin-streptomycin in DMEM) containing 2.5 ng/mL bFGF (Peprotech) on laminin- (Gibco; 10 μg/mL) and collagen I-coated (Thermo Fisher Scientific; 5 μg/mL) plates. Cultures were maintained at 37°C and 5% CO2 levels. Adipogenic differentiation was performed by incubating the FAPs in ADM: 0.5 mM 3-isobutyl-1-methylxanthine (Millipore Sigma), 0.25 μM dexamethasone (Millipore Sigma), and 1 μg/mL insulin (Millipore Sigma) in GM and adipogenic maintenance medium: 1 μg/mL insulin in GM. Fibrogenic differentiation was performed by incubating the FAPs in fibrogenic medium: 10 ng/mL TGF-β1 (PeproTech) in GM.
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In vitro assays and reagents
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Unless otherwise noted, recombinant human WNT7A (PeproTech; 200 ng/mL; vehicle: dH2O) was added to the culture media. To inhibit β-CATENIN binding to TCF4, PNU-74654 (Cayman Chemicals; 50 μM; vehicle: DMSO) was added to the media for 3 days in ADM. To inhibit Rho, CT04 (cytoskeleton; 2 μg/mL; vehicle: dH2O) was added to the media for 2 h as pretreatment plus an additional 4 h with or without WNT7A. The live/dead staining assay was performed using the LIVE/DEAD Cell Imaging Kit (Thermo Fisher Scientific) following the manufacturer’s instructions. Cell-permeant Calcein AM was used as the live cell indicator, and cell-impermeant BOBO-3 iodide nucleic acid dye was used as the dead cell indicator.
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Real-time quantitative PCR
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mRNA was extracted from cells using the RNeasy Plus Microkit (Qiagen, cat. no. 74034), and cDNA was prepared using the RT2 First Strand Kit (Qiagen, cat. no. 330401). RT2 SYBR Green qPCR Master Mix (Qiagen, cat. no. 330504) and RT2 Profiler PCR Array Mouse WNT Signaling Pathway ABI 7900HT Standard Block plates (Qiagen, cat. No. PAMM-043ZA) were used for qPCR.
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Immunocytochemistry staining
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Cells were fixed with 4% paraformaldehyde (PFA) for 20 min at room temperature. Samples were washed three times with 1× PBS and incubated in blocking/permeabilization buffer (5.0% goat serum, 2.0% bovine serum albumin, 0.5% Triton X-100 in PBS) overnight at 4°C. For PDGFRα staining, blocking/permeabilization buffer without the goat serum (2.0% bovine serum albumin, 0.5% Triton X-100 in PBS) was used. The following primary and secondary antibodies were used for immunocytochemistry in this study: anti-PLIN (Abcam; ab3526; 1:200); anti- αSMA (Abcam; ab7817; 1:200); anti-YAP (Santa Cruz Biotechnology; sc101199; 1:200); anti-TAZ (Cell Signaling Technology; 83669S; 1:100); anti-PPARγ (Santa Cruz Biotechnology; sc7273; 1:200); anti-PDGFRα (R&D Systems; AF1062; 1:200); anti-β-CATENIN (Cell Signaling Technology; 8480S; 1:100); goat anti-rabbit Alexa 488 (Thermo Fisher Scientific; A11008; 1:500); goat anti-mouse Alexa Fluor 546 (Thermo Fisher Scientific; A11003; 1:500); goat anti-mouse Alexa 488 (Thermo Fisher Scientific; PIA32723; 1:500); and goat anti-rabbit Alexa 647 (Thermo Fisher Scientific; PIA32733; 1:500). Hoechst 33342 (Thermo Fisher Scientific; 1:1,000) and Phalloidin-iFluor 488 (Cayman Chemicals; 1:1,000) were used to stain nuclei and F-actin, respectively.
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Oil Red O (ORO) staining
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Cells were fixed with 4% PFA for 20 min at room temperature. Samples were washed three times with 1× PBS and incubated in blocking/permeabilization buffer (5% goat serum, 2% bovine serum albumin, 0.5% Triton X-100 in PBS) overnight at 4°C. Cells were incubated in isopropanol (60%) for 5 min and then incubated in ORO for 20 min. Cells were washed five times with 1× PBS and then counterstained with Hoechst 33342 (Thermo Fisher Scientific; 1:1,000).
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Histology and immunohistochemistry
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Detailed protocol is provided in the supplemental experimental procedures.
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Imaging and image analysis
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Images were taken on a Leica Microsystems THUNDER DMi8 microscope using LAS-X software for processing. Detailed image analysis protocol is provided in the supplemental experimental procedures.
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Statistical analysis
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Statistical analyses were performed using GraphPad Prism software. Normality was determined using the Shapiro-Wilk test and Q-Q plot. To test statistical significance, two-tailed t test, one-way analysis of variance (ANOVA) with Tukey’s post-hoc analysis, two-way ANOVA with Bonferroni post-hoc analysis, and Kruskal-Wallis test with Dunn’s multiple comparisons were performed depending on data normality and the number of comparisons. p <0.05 was considered statistically significant. All experiments and studies had at least three biological replicates.
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Author contributions
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C.F., B.C.-Y., and W.M.H. conceived and designed the studies. C.F., B.C.-Y., G.P., M.G.-S., D.L., and W.M.H. conducted experiments and analyzed data. C.F., B.C.-Y., G.P., and W.M.H. wrote and revised this manuscript.
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Supplemental information
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Document S1. Figures S1–S7 and supplemental experimental procedures
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Document S2. Article plus supplemental information
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Data and code availability
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All data needed to evaluate the conclusion of the paper are present in the paper or the supplemental information.
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Acknowledgments
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We thank Nada Marjanovic (Sinai qPCR Core) for her work on the qPCR and gene expression analysis. This study was supported by the Department of Orthopedics at the 10.13039/100007277 Icahn School of Medicine at Mount Sinai to W.M.H. and by the 10.13039/100000069 National Institute of Arthritis and Musculoskeletal and Skin Diseases of the 10.13039/100000002 National Institutes of Health under award number R01AR080616. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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Conflict of interests
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The authors declare no competing interests.
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Supplemental information can be found online at https://doi.org/10.1016/j.stemcr.2023.03.001.
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==== Refs
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Uezumi A. Fukada S.i. Yamamoto N. Takeda S. Tsuchida K. Mesenchymal progenitors distinct from satellite cells contribute to ectopic fat cell formation in skeletal muscle Nat. Cell Biol. 12 2010 143 152 10.1038/ncb2014 20081842
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|
| 348 |
+
|
puc/PMC10149209.txt
ADDED
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@@ -0,0 +1,308 @@
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
J Biol Chem
|
| 4 |
+
J Biol Chem
|
| 5 |
+
The Journal of Biological Chemistry
|
| 6 |
+
0021-9258
|
| 7 |
+
1083-351X
|
| 8 |
+
American Society for Biochemistry and Molecular Biology
|
| 9 |
+
|
| 10 |
+
S0021-9258(23)00277-6
|
| 11 |
+
10.1016/j.jbc.2023.104635
|
| 12 |
+
104635
|
| 13 |
+
Research Article Collection: Metabolism
|
| 14 |
+
Inhibition of nucleotide biosynthesis disrupts lipid accumulation and adipogenesis
|
| 15 |
+
Shinde Abhijit B. 1‡
|
| 16 |
+
Nunn Elizabeth R. 1‡
|
| 17 |
+
Wilson Genesis A. 1
|
| 18 |
+
Chvasta Mathew T. 1
|
| 19 |
+
Pinette Julia A. 1
|
| 20 |
+
Myers Jacob W. 1
|
| 21 |
+
Peck Sun H. 23
|
| 22 |
+
Spinelli Jessica B. 4
|
| 23 |
+
Zaganjor Elma elma.zaganjor@vanderbilt.edu
|
| 24 |
+
156∗
|
| 25 |
+
1 Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, USA
|
| 26 |
+
2 Division of Clinical Pharmacology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
|
| 27 |
+
3 Department of Veterans Affairs, Nashville Veterans Affairs Medical Center, Nashville, Tennessee, USA
|
| 28 |
+
4 Program in Molecular Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA
|
| 29 |
+
5 Vanderbilt Digestive Disease Research Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
|
| 30 |
+
6 Vanderbilt Diabetes Research Center, Vanderbilt University, Nashville, Tennessee, USA
|
| 31 |
+
∗ For correspondence: Elma Zaganjor elma.zaganjor@vanderbilt.edu
|
| 32 |
+
‡ These authors contributed equally to this work.
|
| 33 |
+
|
| 34 |
+
23 3 2023
|
| 35 |
+
5 2023
|
| 36 |
+
23 3 2023
|
| 37 |
+
299 5 10463521 11 2022
|
| 38 |
+
21 2 2023
|
| 39 |
+
© 2023 The Authors
|
| 40 |
+
2023
|
| 41 |
+
https://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
|
| 42 |
+
Energy balance and nutrient availability are key determinants of cellular decisions to remain quiescent, proliferate, or differentiate into a mature cell. After assessing its environmental state, the cell must rewire its metabolism to support distinct cellular outcomes. Mechanistically, how metabolites regulate cell fate decisions is poorly understood. We used adipogenesis as our model system to ascertain the role of metabolism in differentiation. We isolated adipose tissue stromal vascular fraction cells and profiled metabolites before and after adipogenic differentiation to identify metabolic signatures associated with these distinct cellular states. We found that differentiation alters nucleotide accumulation. Furthermore, inhibition of nucleotide biosynthesis prevented lipid storage within adipocytes and downregulated the expression of lipogenic factors. In contrast to proliferating cells, in which mechanistic target of rapamycin complex 1 is activated by purine accumulation, mechanistic target of rapamycin complex 1 signaling was unaffected by purine levels in differentiating adipocytes. Rather, our data indicated that purines regulate transcriptional activators of adipogenesis, peroxisome proliferator–activated receptor γ and CCAAT/enhancer-binding protein α, to promote differentiation. Although de novo nucleotide biosynthesis has mainly been studied in proliferation, our study points to its requirement in adipocyte differentiation.
|
| 43 |
+
|
| 44 |
+
Keywords
|
| 45 |
+
|
| 46 |
+
lipid droplets
|
| 47 |
+
adipocytes
|
| 48 |
+
nucleotides
|
| 49 |
+
purine
|
| 50 |
+
pyrimidine
|
| 51 |
+
adipogenesis
|
| 52 |
+
metabolism
|
| 53 |
+
Abbreviations
|
| 54 |
+
|
| 55 |
+
5FU 5-fluorouracil
|
| 56 |
+
|
| 57 |
+
6MP 6-mercaptopurine
|
| 58 |
+
|
| 59 |
+
AMPK AMP-activated protein kinase
|
| 60 |
+
|
| 61 |
+
ATGL adipose triglyceride lipase
|
| 62 |
+
|
| 63 |
+
AVN AVN944
|
| 64 |
+
|
| 65 |
+
BRQ brequinar
|
| 66 |
+
|
| 67 |
+
C/EBP CCAAT/enhancer-binding protein
|
| 68 |
+
|
| 69 |
+
DHODH dihydroorotate dehydrogenase
|
| 70 |
+
|
| 71 |
+
DMEM Dulbecco’s modified Eagle's medium
|
| 72 |
+
|
| 73 |
+
FABP4 fatty acid binding protein 4
|
| 74 |
+
|
| 75 |
+
FAO fatty acid oxidation
|
| 76 |
+
|
| 77 |
+
FBS fetal bovine serum
|
| 78 |
+
|
| 79 |
+
HSL hormone-sensitive lipase
|
| 80 |
+
|
| 81 |
+
IBMX 3-isobutyl-1-methylxanthine
|
| 82 |
+
|
| 83 |
+
IMP inosine monophosphate
|
| 84 |
+
|
| 85 |
+
IMPDH inosine monophosphate dehydrogenase
|
| 86 |
+
|
| 87 |
+
LOM lometrexol
|
| 88 |
+
|
| 89 |
+
MIZ mizoribine
|
| 90 |
+
|
| 91 |
+
MPA mycophenolic acid
|
| 92 |
+
|
| 93 |
+
mTORC1 mechanistic target of rapamycin complex 1
|
| 94 |
+
|
| 95 |
+
PPARγ peroxisome proliferator–activated receptor γ
|
| 96 |
+
|
| 97 |
+
SREBP1 sterol-regulatory element binding protein 1
|
| 98 |
+
|
| 99 |
+
SVF stromal vascular fraction
|
| 100 |
+
|
| 101 |
+
T3 triiodothyronine
|
| 102 |
+
|
| 103 |
+
Reviewed by members of the JBC Editorial Board. Edited by Alex Toker
|
| 104 |
+
==== Body
|
| 105 |
+
pmcAdipose tissue is a critical organ in coordinating energy balance, releasing nutrients in times of fasting and storing nutrients in times of nutritional excess. In the context of overnutrition, adipose tissue can expand through adipocyte hypertrophy or through the formation of new adipocytes, termed adipogenesis. Adipogenesis is thought to be a protective and adaptive response to excess nutrients. The transcriptional regulation of adipogenesis is well established (1, 2). CCAAT/enhancer-binding proteins (C/EBPs), C/EBPδ and C/EBPβ, are early inducers of adipogenesis (3). These factors stimulate peroxisome proliferator–activated receptor γ (PPARγ), which in turn supports the activation of C/EBPα (4, 5, 6). C/EBPα exerts positive feedback on PPARγ to maintain differentiation. Sterol-regulatory element binding protein 1 (SREBP1) is thought to promote adipogenesis through the production of an endogenous PPARγ ligand and regulation of lipogenic gene expression (7, 8).
|
| 106 |
+
|
| 107 |
+
Adipogenesis is further modulated through post-translational regulatory mechanisms. In response to nutrients, the mechanistic target of rapamycin complex 1 (mTORC1) stimulates adipogenesis (9). Although the mechanism remains unclear, mTORC1 activity promotes positive feedback between PPARγ and C/EBPα (10, 11). AMP-activated protein kinase (AMPK) is a cellular sensor of energy and nutrient stress and a potent negative regulator of adipogenesis (12, 13, 14). AMPK blocks lipid storage by suppressing lipogenesis while promoting fat oxidation (15). Specifically, activation of AMPK hinders lipogenesis through direct inhibition of SREBP1, which results in significant transcriptional repression of adipogenesis (16). In addition, AMPK antagonizes lipogenesis through the inhibitory phosphorylation of acetyl CoA carboxylase 1 (ACC1). AMPK supports fatty acid oxidation (FAO) through inhibition of acetyl CoA carboxylase 2 (ACC2), which results in decreased malonyl CoA levels and subsequent increased activity of a rate-limiting FAO, enzyme carnitine palmitoyltransferase 1 (17). Finally, AMPK activation increases lipolysis, although it can positively or negatively regulate distinct lipolysis enzymes, hormone-sensitive lipase (HSL) and adipose triglyceride lipase (ATGL), in a context-specific manner (18).
|
| 108 |
+
|
| 109 |
+
Much like transcription and signaling events, metabolites regulate adipocyte differentiation (19). To induce adipogenesis, glucose generates NADPH, a cofactor critical for lipogenesis, through the pentose phosphate pathway (20). Branched-chain amino acid catabolism produces lipogenic acetyl-CoA to boost adipogenesis (21). Branched-chain amino acid catabolism also stimulates PPARγ transcriptional activity, suggesting that metabolic regulation of adipogenesis occurs early in the process of differentiation (22). Alternatively, glutamine oxidation is inhibitory to adipogenesis, although the mechanism remains unclear (23). While it is evident that nutrients modulate adipocyte differentiation, the mechanism by which metabolites engage with the signaling and transcriptional machinery to drive this process is poorly understood. Using metabolic profiling, we found that adipocyte differentiation is associated with altered nucleotide accumulation. Inhibition of purine and pyrimidine biosynthesis prevents lipid storage within adipocytes. Unlike in proliferating cells (24, 25), purine inhibition does not block mTORC1 activation in cells undergoing differentiation. Instead, purine inhibition activates AMPK signaling, a negative regulator of lipogenesis. However, rather than altering AMPK substrate phosphorylation, purine inhibition reduces gene expression of lipid metabolism enzymes. This observation led us to examine whether preventing purine biosynthesis interferes with the transcriptional program that regulates adipocyte differentiation. Indeed, inhibition of purine biosynthesis downregulated PPARγ−C/EBPα expression, a necessary transcriptional program that regulates adipogenesis. Thus, our study suggests that sustained purine biosynthesis is an indispensable pathway in the transcriptional activation of adipogenesis.
|
| 110 |
+
|
| 111 |
+
Results
|
| 112 |
+
|
| 113 |
+
Nucleotide metabolism is an enriched signature accompanying adipocyte differentiation
|
| 114 |
+
|
| 115 |
+
Transcriptional and signaling programs that regulate adipogenesis are well defined. In addition, recent studies have revealed a critical function of metabolic rewiring to support this process (19). However, most of these studies were performed using the immortalized 3T3-L1 system, which originates from a single clone and fails to recapitulate all the characteristics of primary cell culture models (26). We hypothesized that examining metabolic alterations associated with adipogenesis using primary preadipocytes would reveal new metabolic pathways that participate in the initiation and maintenance of this differentiated state and may be relevant in vivo. Therefore, primary preadipocytes from the stromal vascular fraction (SVF) were stimulated to differentiate for 6 days using a cocktail containing 3-isobutyl-1-methylxanthine (IBMX), dexamethasone, insulin, rosiglitazone, troglitazone, and triiodothyronine (T3) (Fig. 1A). Cell differentiation was confirmed using BODIPY and Oil Red O staining of neutral lipids (Fig. S1, A and B). Using mass spectrometry, we compared the steady-state metabolite profiles of undifferentiated and 6 day differentiated primary adipocytes (Fig. 1A). To gain a broad view of the metabolic rewiring that occurs during differentiation, we profiled a total of 218 metabolites and discovered that 117 metabolites were significantly altered. Our analysis confirmed the depletion of amino acids as previously reported (22), suggesting the conservation of these metabolic pathways during differentiation in primary adipocytes (Fig. 1B). Moreover, using MetaboAnalyst 5.0 (https://www.metaboanalyst.ca/MetaboAnalyst/), we observed that the purine and pyrimidine biosynthetic pathways are the top signatures altered during adipocyte differentiation (Fig. 1C). Because purine metabolism was the pathway most significantly altered during differentiation, we further focused on examining the relative metabolite levels in this pathway (Fig. S1C). Carbamoyl aspartate, 5-aminoimidazole-4-carboxamide ribonucleotide, and inosine monophosphate (IMP), intermediates in the de novo purine synthesis pathway required to produce nucleotides, were depleted (Figs. 1D and S1, C and D). ADP and GDP, which are products of the purine synthesis pathway, were generated, suggesting that the nucleotide biosynthetic pathway is engaged during adipogenesis (Figs. 1, D and E and S1C). Urate and allantoin, metabolites in the nucleotide degradation pathway, were similarly enriched in differentiated adipocytes (Figs. 1, D and E and S1C). Metabolites in the nucleotide salvage pathway were both enriched and depleted, suggesting that this pathway is also likely active during adipocyte differentiation (Figs. 1, D and E and S1C). Altogether, our results reveal major alterations in nucleotide abundance associated with adipocyte differentiation.Figure 1 Nucleotide metabolism is an enriched signature accompanying adipocyte differentiation.A, schematic of the experimental setup, the cell model, and sample preparation for steady-state metabolomics. B, intracellular abundance of metabolites profiled from 6 days of differentiated primary adipocytes relative to undifferentiated primary preadipocytes. C, table of the metabolic pathways significantly affected by 6-day differentiation. The pathway analysis module in MetaboAnalyst 5.0 was used for the analysis. D, schematic of the purine biosynthetic pathway illustrating metabolites that are depleted (red) or enriched (green) in 6-day differentiated primary adipocytes. E, relative levels of differentiation-enriched metabolites in the nucleotide biosynthesis pathway. Data shown are from four biological replicates. Statistical significance was determined using the Student’s t test. Error bars indicate mean ± SD, ∗p ≤ 0.05, ∗∗p ≤ 0.01, and ∗∗∗p ≤ 0.001.
|
| 116 |
+
|
| 117 |
+
Inhibition of nucleotide biosynthesis prevents lipid accumulation in differentiating adipocytes
|
| 118 |
+
|
| 119 |
+
To determine the function of nucleotide metabolism in differentiating adipocytes from the SVF, we treated cells with inhibitors of de novo purine synthesis or purine salvage and inhibitors of de novo pyrimidine biosynthesis while inducing differentiation (Figs. 2A and S2A) (27, 28). Inhibition of de novo purine synthesis enzymes inosine monophosphate dehydrogenase 1 and 2 (IMPDH1 and IIMPDH2) with mizoribine (MIZ) or phosphoribosyl pyrophosphate amidotransferase with 6-mercaptopurine (6MP) resulted in inhibited expression of perilipin and fatty acid binding protein 4 (FABP4), markers of lipid storage and adipocyte differentiation, as measured by Western blot, and decreased lipid accumulation as visualized by Oil Red O and BODIPY in primary adipocytes (Figs. 2, B–D and S2B). Of note, 6MP may also inhibit the purine salvage pathway via hypoxanthine–guanine phosphoribosyltransferase 1 and thus may be a more potent inhibitor of adipocyte differentiation. The broader activity of 6MP may explain why this inhibitor exhibits less dose-dependent activity on the expression of adipogenic markers than MIZ (Fig. S2, D and E). Inhibition of de novo purine synthesis enzyme phosphoribosylglycinamide formyltransferase with lometrexol (LOM) had no effect on lipid accumulation in primary adipocytes. Inhibition of pyrimidine synthesis enzymes dihydroorotate dehydrogenase (DHODH) with leflunomide or brequinar (BRQ) or thymidylate synthase with 5-fluorouracil (5FU) had a lesser effect on expression of differentiated state markers and lipid accumulation (Figs. S2, A and B, and 2, B–D). However, with increasing drug concentrations, BRQ and 5FU produced an inhibitory effect on adipogenic markers (Fig. S2, F and G). We next sought to determine whether inhibition of nucleotide biosynthesis also influences differentiation in 3T3-L1 cells, a homogenous preadipocyte population. Blocking purine biosynthesis with LOM, MIZ, or 6MP resulted in a reduced expression of differentiation markers perilipin and FABP4 and decreased lipid accumulation (Figs. 2, E–G and S2C). The distinct effects of LOM on lipid accumulation in primary versus 3T3-L1 cells raise the possibility that compensatory mechanisms may counteract the loss of purine biosynthesis in primary cells. To identify whether structurally distinct compounds targeting a single enzyme have comparable effects on lipid accumulation, we examined the effects of IMPDH inhibitors mycophenolic acid (MPA) and AVN944 (AVN). Both MPA and AVN blocked the expression of perilipin and FABP4, mimicking the actions of MIZ (Fig. S2H). As in primary adipocytes, inhibition of pyrimidine biosynthesis had a lesser effect on lipid accumulation during 3T3-L1 differentiation (Figs. 2, E–G and S2C). Genetic perturbation of purine synthesis via shRNA-mediated knockdown of IMPDH1 had a similar inhibitory effect on 3T3-L1 differentiation, as evidenced by decreased expression of perilipin and FABP4 and decreased BODIPY staining (Fig. 2, H and I). Similarly, the knockdown of DHODH reduced the expression of perilipin and FABP4, supporting the requirement of pyrimidine biosynthesis in differentiating adipocytes (Fig. S2I). Collectively, our results demonstrate that disrupting nucleotide metabolism blocks lipid accumulation in differentiating adipocytes.Figure 2 Inhibition of purine and pyrimidine metabolism disrupts lipid droplets in differentiating adipocytes.A, schematic depicting de novo purine synthesis and salvage pathways. Inhibitors of purine synthesis pathways in blue. B, protein levels of perilipin, FABP4, and α-tubulin in undifferentiated SVF preadipocytes or after 6 days of differentiation in the presence or the absence of 50 μM 6-mercaptopurine (6MP), 2 μM lometrexol (LOM), 25 μM mizoribine (MIZ), 10 μM leflunomide (LEF), 1 μM brequinar (BRQ), or 1 μM 5-fluororacil (5FU). Media were changed every 2 days, and drug was replenished. Data shown are from two biological replicates. C, representative images of BODIPY 493/503 staining of untreated primary SVF cells or treated with indicated drugs, differentiated for 6 days. D, quantification of Oil Red O extracted from primary adipocytes treated with indicated drugs normalized to untreated cells. All cells were differentiated for 6 days. Data shown are from three biological replicates. Statistical significance was determined using one-way ANOVA multiple comparisons test. E, protein levels of perilipin, FABP4, and α-tubulin after 6 days of differentiation of 3T3-L1 adipocytes treated as in (B). Data shown are from two biological replicates. F, quantification of Oil Red O staining in 3T3-L1 adipocytes treated with indicated drugs normalized to untreated cells. All cells differentiated for 6 days. Data shown are from three biological replicates. Statistical significance was determined using one-way ANOVA multiple comparisons test. G, representative images of BODIPY 493/503 staining of untreated 3T3-L1 cells or treated with indicated drugs, differentiated for 6 days. H, Western blot analysis of perilipin, FABP4, IMPDH1, and tubulin from 3T3-L1 cells infected with shControl or shIMPDH1 (two distinct shRNAs) and differentiated for 8 days. Data shown are from two biological replicates. I, representative images of BODIPY 493/503 staining of 3T3-L1 cells infected with shControl or shIMPDH1 and differentiated for 8 days. Error bars indicate mean ± SD, ∗p ≤ 0.05, ∗∗p ≤ 0.01, and ∗∗∗p ≤ 0.001. All data are representative of 2 to 3 independent experiments. FABP4, fatty acid binding protein 4; IMPDH, inosine monophosphate dehydrogenase.
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Inhibition of nucleotide metabolism does not obstruct mTORC1 signaling in differentiating adipocytes
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mTORC1 exquisitely senses nutrients to regulate cell growth and stimulate anabolic processes such as lipogenesis (29). As such, purine depletion prevents mTORC1 activation in some proliferating cell types (24, 25). We probed the effect of inhibiting nucleotide biosynthesis on mTORC1 activity by measuring the phosphorylation of its substrates S6 and S6K or mobility shift of 4E-BP1, indicative of a change in phosphorylation (Fig. S3A). While we observed the previously reported loss of mTORC1 signaling by blocking purine metabolism in HeLa cells (24, 25), proliferating 3T3-L1 cells were much less sensitive to such sensing, as evidenced by maintained S6 phosphorylation (Fig. S3, B and C). Moreover, differentiating primary adipocytes or 3T3-L1 cells for 6 days in the presence of purine or pyrimidine metabolism inhibitors did not prevent phosphorylation of mTORC1 substrates S6 or S6K or alter mobility of 4E-BP1 (Fig. 3, A and B). These data suggest that the disruption of lipid accumulation observed in adipocytes following inhibition of nucleotide biosynthesis is not dependent on mTORC1 inactivation.Figure 3 Inhibition of purine metabolism in differentiating cells does not alter mTORC1 activity.A, Western blot analysis of pS6, S6, pS6K, S6K, and 4E-BP1 after 6 days of SVF cell differentiation into primary adipocytes and treatment with indicated drugs as in Figure 2B. Data shown are from two biological replicates. B, Western blot analysis of pS6, S6, and 4E-BP1 after 6 days of differentiation in 3T3-L1 cells and treatment with indicated drugs. Data shown are from two biological replicates. All data are representative of 2 to 3 independent experiments. mTORC, mechanistic target of rapamycin complex.
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Inhibition of purine biosynthesis activates phosphorylation of AMPK but not its targets in differentiating adipocytes
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AMPK is another energy and nutrient sensor that regulates lipid metabolism in response to stress (30) (Fig. 4A). We probed the effect of inhibiting nucleotide biosynthesis on AMPK by measuring its activating phosphorylation at residue T172. Suppression of purine biosynthesis with 6MP and MIZ results in modest AMPK activation as evidenced by increased phosphorylation (Fig. 4, B and C). Because AMPK activation blocks lipogenesis (Fig. 4A), we sought to investigate whether MIZ and 6MP also affected this functional output. We measured de novo lipogenesis by analyzing the incorporation of 14C-glucose into the lipid fraction in the presence of an ACC inhibitor, 5-tetradecyloxy-2-furoic acid and detected decreased incorporation, indicating that the assay is adequate to measure lipogenesis (Fig. S4A). In MIZ- and 6MP-treated SVF cells differentiated for 6 days, de novo lipogenesis is diminished, which is consistent with the decrease in both the transcription and protein expression of enzymes that regulate this process (Fig. 4D). We noted a similar effect of inhibition of purine biosynthesis on lipogenesis in 3T3-L1 cells differentiated for 6 days (Fig. S4A). AMPK regulates lipid metabolism by directly phosphorylating its substrates, including ACC, HSL, and ATGL (Fig. 4A). We examined the effects of purine and pyrimidine biosynthesis inhibitors on the phosphorylation state of AMPK substrates. Inhibiting pyrimidine biosynthesis had no significant effect on the phosphorylation state of AMPK substrates (Fig. 4E). Although 6MP and MIZ activate AMPK, we did not observe an increase in phosphorylation of ACC, HSL, and ATGL (Fig. 4E). Instead, the expression of these proteins is downregulated by 6MP and MIZ treatment (Fig. 4E). Given that mTORC1 remains active following the inhibition of purine biosynthesis in adipocytes, we hypothesized that while protein translation may be functioning properly, transcription may be decreased. Moreover, AMPK is a known regulator of SREBP1 (31), which promotes the transcription of many lipid metabolism enzymes (32, 33, 34). Thus, we examined the mRNA expression of Srebp and its targets and found that both MIZ and 6MP downregulate the Srebp transcriptional program as well as Srebp1c and Srebp2 expression (Fig. 4F). Collectively, our data demonstrate that interfering with purine biosynthesis decreases lipogenesis and final lipid content in differentiating adipocytes. These changes in lipid metabolism may be regulated at the level of transcription.Figure 4 Inhibition of purine biosynthesis in differentiating cells potentiates AMPK and disrupts lipogenesis.A, schematic of AMPK regulation of lipid metabolism. B, Western blot analysis of pAMPK and AMPK after 6MP and MIZ treatment in primary SVF cells differentiated into adipocytes for 6 days. Data shown are from two biological replicates. C, quantification of band intensity from (B). Statistical significance was determined using one-way ANOVA multiple comparisons test. Error bars indicate mean ± SD, ∗∗p ≤ 0.01 and ∗∗∗p ≤ 0.001. D, 1-14C glucose incorporation into lipid fraction analyzed from primary SVF cells differentiated for 6 days and treated with vehicle, 6MP, or MIZ. Statistical significance was determined using one-way ANOVA multiple comparisons test. Error bars indicate mean ± SD, ∗∗p ≤ 0.01. E, Western blot analysis of pAMPK, AMPK, pACC, ACC, pHSL, HSL, pATGL, and ATGL in primary SVF cells after 6 days of differentiation and treatment with indicated drugs. Data shown are from two biological replicates. F, gene expression profile in primary SVF cells differentiated for 6 days and treated with vehicle, 6MP, or MIZ. Statistical significance was determined using one-way ANOVA multiple comparisons test. All data are representative of 2 to 3 independent experiments. 6MP, 6-mercaptopurine; ACC, acetyl CoA carboxylase 1; AMPK, AMP-activated protein kinase; ATGL, adipose triglyceride lipase; MIZ, mizoribine.
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Inhibition of purine biosynthesis blocks adipogenesis by downregulating the expression of key transcriptional regulators
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Given that Srebp1c and Srebp2 were downregulated transcriptionally by purine biosynthesis inhibitors, we postulated that MIZ and 6MP may modulate early events of transcriptional regulation that promote cell differentiation. If our hypothesis is correct, we would detect a lesser or no effect on lipid accumulation if cells are treated with these compounds after transcriptional initiation. Indeed, treating SVF cells with MIZ and 6MP 4 days after initiation of differentiation had minimal effects on lipid accumulation (Fig. 5, A and B), suggesting that interfering with purine biosynthesis may impair early regulatory events that promote adipogenesis. Blocking purine biosynthesis with 6MP and MIZ 2 days after initiation of differentiation effectively inhibited lipid accumulation and expression of adipogenic markers (Fig. 5, A and B). To identify the possible factors that may be regulated by inhibition of purine biosynthesis, we profiled transcription factor activation in primary SVF cells stimulated to differentiate into adipocytes over a time course of 6 days (Fig. S5, A and B). As established in the literature, C/EBPδ and C/EBPβ are activated early and already expressed in preadipocytes, whereas PPARγ and C/EBPα are stimulated after 1 to 3 days of differentiation (Fig. S5, A and B). Blocking purine biosynthesis did not disrupt the activation of transcriptional regulators that are induced after 1 day of differentiation (Fig. 5C) suggesting that CEB/Pδ and C/EBPβ may not be directly regulated by these nucleotides. However, after 2 days of differentiation, expression of PPARγ and C/EBPα was suppressed by both MIZ and 6MP treatment, suggesting that these factors are key transmitters of nucleotide mediation on adipogenesis (Fig. 5C). To evaluate whether restoring key transcriptional regulation is sufficient to prevent adipogenic repression induced by the nucleotide biosynthesis inhibitors, we overexpressed PPARγ2. In the context of PPARγ2 overexpression, MIZ and 5FU failed to block adipogenesis as evidenced by maintained expression of perilipin and FABP4 (Figs. 5D and S5C). Collectively, our data indicate that nucleotide biosynthesis inhibition downregulates transcriptional activators PPARγ and C/EBPα and subsequently blocks adipogenesis.Figure 5 Inhibition of purine biosynthesis blocks adipogenesis by downregulating the expression of key transcriptional regulators.A, Western blotting analysis of primary preadipocytes differentiated for 8 days after adding 6MP or MIZ at day 0 and then every other day, at day 2 and then every other day, or at day 4 and then every other day. Duplicate samples represent two biological replicates. B, cells were treated as in (A), and Oil Red O staining was performed. Statistical significance was determined using one-way ANOVA multiple comparisons test. Error bars indicate mean ± SD, ∗p ≤ 0.05, ∗∗p ≤ 0.01, ∗∗∗p ≤ 0.001, and ∗∗∗∗p ≤ 0.0001. C, MIZ and 6MP were added at the start of primary SVF differentiation. Cells were differentiated for 1, 2, or 4 days. C/EBPδ, C/EBPβ, PPARγ, C/EBPα, and tubulin were analyzed by Western blotting. Duplicate samples represent two biological replicates. D, 3T3-L1 cells stably expressing pBABE control vector or PPARγ2 were differentiated and treated with 25 μM MIZ or DMSO control for 6 days. Lysates were analyzed by Western blotting as indicated. The data are representative of three independent experiments. 6MP, 6-mercaptopurine; C/EBP, CCAAT/enhancer-binding protein; DMSO, dimethyl sulfoxide; MIZ, mizoribine; PPARγ, peroxisome proliferator–activated receptor γ.
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Nucleoside and nitrogenous bases rescue the effects of de novo purine inhibition on adipogenesis
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We hypothesized that the effects of inhibiting de novo purine biosynthesis on adipogenesis may be due to decreased purine availability and thus could be rescued by exogenous nucleoside and nitrogenous bases that can produce nucleotides through the purine salvage pathway. To determine whether adipogenesis can be rescued by the addition of purine nucleosides, we exposed primary SVF cells to adenosine, inosine, and hypoxanthine in the presence of 6MP or MIZ. The addition of nucleosides substantially rescued a 6MP-mediated block in adipogenesis, as assessed by the increased expression of differentiation markers FABP4 and perilipin (Fig. 6A), increased Oil Red O accumulation (Fig. 6B), and increased BODIPY staining (Fig. S6A). MIZ inhibition of adipogenesis was not rescued by adenosine, inosine, and hypoxanthine, as expected, given that MIZ should deplete cellular guanosine and guanine. We next examined whether the addition of nitrogenous bases had the capacity to restore adipogenesis in the presence of purine biosynthesis inhibitors. We observed that adenine addition could rescue the loss of adipogenic markers observed with 6MP (Fig. 6C). Similarly, guanine addition rescued the loss of adipogenic markers and decreased lipid accumulation induced by MIZ (Figs. 6D and S6B). Given that 6MP and MIZ block transcriptional activators of adipogenesis, we next examined whether the addition of nitrogenous bases rescued the expression of PPARγ and C/EBPα (Fig. 6, E and F). We noted that adenine and guanine addition restored PPARγ and C/EBPα expression, potentially indicating that purines are sensed to modulate transcriptional programs that regulate cellular outcomes, and limitations in purine availability therefore prevent adipocyte differentiation.Figure 6 Nucleoside and nitrogenous bases rescue the effects of de novo purine inhibition on adipogenesis.A, Western blot analysis of FABP4, perilipin, and α-tubulin after 6 days of differentiation in primary SVF cells treated with 6MP, LOM, or MIZ, and rescued with a cocktail of nucleotides (AIH) containing 5 μM adenosine, 5 μM inosine, and 5 μM hypoxanthine. B, quantification of Oil Red O staining in primary SVF cells treated with indicated drugs with or without nucleotide cocktail (as in A) normalized to untreated cells, differentiated for 6 days. Statistical significance was determined using one-way ANOVA multiple comparisons test. Error bars indicate mean ± SD, ∗p ≤ 0.05, ∗∗p ≤ 0.01, and ∗∗∗p ≤ 0.001. C, Western blot analysis of perilipin, FABP4, and α-tubulin after 6 days of differentiation into primary adipocytes treated with 6MP and rescued with 50 μM adenine. D, Western blot analysis of perilipin, FABP4, and α-tubulin after 6 days of differentiation into primary adipocytes treated with MIZ and rescued with 50 μM guanine. E, Western blot analysis of PPARγ, C/EBPα, and vinculin after 6 days of differentiation into primary adipocytes treated with 6MP and rescued with 50 μM adenine. F, Western blot analysis of PPARγ, C/EBPα, and vinculin after 6 days of differentiation into primary adipocytes treated with MIZ and rescued with 50 μM guanine. Data shown are from two biological replicates. All data are representative of 2 to 3 independent experiments. 6MP, 6-mercaptopurine; C/EBPα, CCAAT/enhancer-binding protein; FABP4, fatty acid binding protein 4; LOM, lometrexol; MIZ, mizoribine; PPARγ, peroxisome proliferator–activated receptor γ.
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Discussion
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In this study, we sought to elucidate how metabolites regulate adipogenesis using a primary SVF adipocyte cell model. Steady-state metabolomics revealed nucleotide metabolism as the topmost signature altered by differentiation. Inhibition of purine, and to a lesser extent pyrimidine, biosynthesis blocks the transcriptional advancement of adipogenesis, decreasing lipid accumulation in both primary and 3T3-L1 adipocytes. Mechanistically, this regulation does not appear to involve mTORC1, which has previously been shown to sense purines and promote purine biosynthesis in proliferating cells (24, 25). Importantly, our studies reveal that the bidirectional regulation between mTORC1 signaling and purine synthesis may not extend to all postmitotic cells.
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Because nucleotide availability also alters AMPK activity (35), we focused our studies on this regulator of lipid metabolism. We found that blocking purine biosynthesis increased AMPK phosphorylation. Interestingly, this activation of AMPK did not result in increased phosphorylation of its direct substrates that modulate lipolysis or FAO. Instead, after inhibition of purine biosynthesis, we observed a decreased lipogenic transcriptional profile that may be deactivated through the loss of expression of AMPK substrate SREBP1. Subsequently, our de novo lipogenesis assay confirmed the hypothesis that purine inhibitors block lipogenesis in differentiating adipocytes. Our findings agree with previously published work that demonstrated that 5-aminoimidazole-4-carboxamide ribonucleotide, an activator of AMPK, decreases PPARγ expression and differentiation in 3T3-L1 cells (13). Moreover, it has been observed that in multipotent mesenchymal stem cells, activation of AMPK promotes commitment to the osteogenic lineage, whereas suppression of AMPK activity promotes adipogenesis (36). Therefore, future studies may investigate whether antagonizing purine biosynthesis could likewise push pluripotent cells toward the osteogenic lineage.
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While we demonstrate that impeding purine biosynthesis dampens the PPARγ-C/EBPα transcriptional profile that is required to drive adipogenesis, the mechanism by which this occurs remains unclear. Significantly, the effect of purine biosynthesis inhibition can be rescued by adding exogenous nucleoside and nitrogenous bases. Previous studies identified xanthine oxidoreductase, an enzyme that catalyzes the catabolism of purines, as a novel regulator of adipogenesis (37). It was demonstrated that xanthine oxidoreductase potentiates PPARγ activation, complementing our findings that altering purine biosynthesis obstructs PPARγ activation. How purine biosynthesis modulates transcriptional regulation remains to be identified. IBMX, a xanthine derivate, is commonly used in adipogenic differentiation cocktails and is thought to promote the process by elevating cAMP and cGMP levels (38). Therefore, one possibility is that purine biosynthesis promotes adipocyte differentiation by increasing cAMP or cGMP availability.
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Although nucleotide biosynthesis has been well studied in the context of proliferation, in part because of their importance in DNA and RNA synthesis (27), little is known about the role of nucleotides in cell physiology and cell fate decision. Recent studies reveal that although nucleotide biosynthesis inhibition limits proliferation, it stimulates cell migration and the epithelial–mesenchymal transition transcriptional program characterized by N-cadherin and vimentin upregulation (39). Furthermore, perturbing nucleotide abundance regulates differentiation in various cell systems; depletion of nucleotides stimulates acute myeloid leukemia differentiation, but elevation in nucleotides may also promote cardiac mesoderm lineage through paracrine signaling (40, 41). Now our study adds a new role of nucleotide biosynthesis in the regulation of adipogenesis. Collectively, these studies reveal the critical impact of nucleotide alterations in cell physiology and cell functions beyond proliferation.
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In sum, we have identified purine biosynthesis as a required pathway to stimulate adipogenesis. Further studies are warranted to determine whether modulating nucleotide pools can alter adipogenesis and weight gain in vivo in the context of overnutrition.
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Experimental procedures
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Primary preadipocyte isolation
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Primary SVF cells were isolated from the inguinal white adipose tissue of 4- to 6-day-old mice. The experimental procedures have been approved by the Vanderbilt University Subcommittee on Animal Research Care (IACUC, Institutional Animal Care and Use Committee) as required by the Public Health Service Policy on Humane Care and Use of Laboratory Animals. White adipose tissue was dissected and digested in 1 mg/ml collagenase type II (Sigma; catalog no.: C6885) dissolved in 3% bovine serum albumin (Sigma; catalog no.: A1470) in Hanks buffered saline solution with calcium and magnesium for 30 min at 37 °C while shaking at 300 RPM. Dulbecco’s modified Eagle's medium (DMEM) with high glucose and no sodium pyruvate was supplemented with 10% fetal bovine serum (FBS), 10 μM nonessential amino acids (Thermo; catalog no.: 11140050), 2 mM glutamine, 20 mM Hepes, and 0.1 μM mercaptoethanol (Sigma; catalog no.: M3148) was used for cell washing and separation through a 100 μm cell strainer. The filtered cell suspension was centrifuged at 600g for 5 min at 4 °C. The cell pellet was resuspended in the same media and plated. Growth medium was changed every other day until cells reached 100% confluency, at which point differentiation was induced.
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Primary preadipocyte differentiation
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DMEM/nutrient mixture F-12 supplemented with 10% FBS, 1% penicillin and streptomycin, 1.7 μM insulin, 1 μM dexamethasone, and 0.5 mM IBMX was used to induce differentiation. Cells were kept in an induction medium for 2 days and then switched to “maintenance media” consisting of DMEM/nutrient mixture F-12 with 10% FBS, 1% penicillin and streptomycin, 17 nM insulin, 2 μM troglitazone, 1 μM rosiglitazone, and 1 nM T3. Maintenance medium was changed every other day until the end point assays.
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3T3-L1 cell culture
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3T3-L1 preadipocytes were purchased from American Type Culture Collection (CL-173). Cells were cultured in DMEM (Corning) supplemented with 10% FBS (Gibco) and 1% penicillin and streptomycin (Gibco). Once confluent, 3T3-L1 cells were stimulated to differentiate with DMEM containing 10% FBS, 1% penicillin, and streptomycin, and a chemical cocktail of 0.5 mM IBMX, 1 μM dexamethasone, and 1.5 μg/ml insulin. Media were changed every 2 days during the differentiation time course.
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Drug treatment
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Cells were treated during the differentiation time course as indicated with 25 μM MIZ (Cayman; catalog no.: 23128), 2 μM LOM (Cayman; catalog no.: 18049), 50 μM 6MP (Cayman; catalog no.: 23675), 1 μM 5FU (Cayman; catalog no.: 14416), 1 μM BRQ (Cayman; catalog no.: 24445), 10 μM leflunomide (Cayman; catalog no.: 14860), 10 μM MPA (Cayman; catalog no.: 21716), or 10 μM AVN (Cayman; catalog no.: 21284), unless indicated otherwise in the figure legends.
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Metabolomics
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Cells were plated in triplicates for metabolite extraction and in triplicates for cell count normalization. Prior to experiments, cells were differentiated/treated as indicated. For metabolite extraction, cells were washed twice with ice-cold PBS, and polar metabolites were extracted directly on the dish using 1 ml ice-cold LC–MS grade 80:20 methanol:water (Thermo Fisher Scientific). Plates were scraped on dry ice, and lysates were collected in Eppendorf tubes. Lysates were vortexed for 10 min at 4 °C and centrifuged at 16,000g for 10 min at 4 °C. Supernatants were immediately dried down in a Vacufuge plus Benchtop Vacuum Concentrator. Dried pellets were stored at −80 °C until they were run on LC–MS.
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| 170 |
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| 171 |
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LC–MS (polar)
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| 172 |
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| 173 |
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A QExactive bench top orbitrap mass spectrometer equipped with an Ion Max source and a HESI II probe coupled to a Dionex UltiMate 3000 HPLC system (Thermo Fisher Scientific) was used to perform all LC–MS experiments. The instrument underwent mass calibration using the standard calibration mixture every 7 days. About 2 μl of resuspended polar metabolite samples were injected onto a SeQuant ZIC-pHILIC 5 μm 150 × 2.1 mm analytical column equipped with a 2.1 × 20 mm guard column (MilliporeSigma). The column oven was held at 25 °C, and the autosampler tray was held at 4 °C. Buffer A comprised of 20 mM ammonium carbonate and 0.1% ammonium hydroxide. Buffer B was 100% acetonitrile. The chromatographic gradient was run at a flow rate of 0.150 ml/min as follows: 0 to 20 min: linear gradient from 80 to 20% B; 20 to 20.5 min: linear gradient from 20 to 80% B; 20.5 to 28 min: hold at 80% B. The mass spectrometer was operated in full-scan polarity-switching mode, with the spray voltage set to 3.0 kV, the heated capillary at 275 °C, and the HESI probe at 350 °C. The sheath gas flow was 40 units, the auxiliary gas flow was 15 units, and the sweep gas flow was 1 unit. MS data were collected in a range of m/z = 70 to 1000. The resolution was set at 70,000, the automatic gain control target at 1 × 106, and the maximum injection time was set at 20 ms. An additional scan (m/z = 220–700) was included in negative mode only to enhance the detection of nucleotides.
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Oil Red O staining and quantification
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Accumulation of lipids after 6 days of differentiation was assessed by Oil Red O staining. Oil Red O (Sigma) stock solution was prepared as a 0.3% solution in isopropanol. Cells were washed with PBS, fixed with 4% paraformaldehyde for at least 2��h, washed with 60% isopropanol, and then stained with filtered Oil Red O solution (75% Oil Red O stock solution, 25% water). Cells were washed with dH2O to remove the excess stain before imaging. Following imaging, Oil Red O stain taken up by lipid droplets was solubilized in 100% isopropanol and quantified by reading absorbance at 492 nm.
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Generation of stable cell lines
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pBABE puro PPARγ2 plasmid was obtained from Addgene (#8859). shRNAs against IMPDH1 and DHODH were subcloned in the pLKO.1 puro vector (Addgene Plasmid #8453) at EcoRI and AgeI sites. Primer sequences for cloning were used: sh_DHODH:
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Forward: CCGGCGACGGACTGATCATCACAAACTCGAGTTTGTGATGATCAGTCCGTCGTTTTTG,
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Reverse: AATTCAAAAACGACGGACTGATCATCACAAACTCGAGTTTGTGATGATCAGTCCGTCG and shIMPDH1_1:
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Forward: CCGGGATAAGGTGAAGATCGCACAACTCGAGTTGTGCGATCTTCACCTTATCTTTTTG.
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| 188 |
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Reverse: AATTCAAAAAGATAAGGTGAAGATCGCACAACTCGAGTTGTGCGATCTTCACCTTATC shIMPDH1_2:
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Forward: CCGGCTCCAGAACTAAGTGGTCCATCTCGAGATGGACCACTTAGTTCTGGAGTTTTTG.
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| 192 |
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Reverse: AATTCAAAAACTCCAGAACTAAGTGGTCCATCTCGAGATGGACCACTTAGTTCTGGAG. Subcloning was confirmed with sequencing. Subcloned plasmids were transfected into human embryonic kidney 293T cells with lentiviral packaging vectors. After 48 h, lentivirus was harvested, and target cells were infected in the presence of 10 mg/ml polybrene. Following infection, cells were selected with puromycin.
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BODIPY staining and imaging
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Accumulation of lipids after 6 days of differentiation was measured by BODIPY staining in live cells. Media were replaced with 500 μl DMEM containing 10% FBS and 1% penicillin and streptomycin. BODIPY 493/503 (Cayman) was prepared to a working concentration of 1:500 in DMEM without serum or antibiotics. About 500 μl of this solution was added to the cells and incubated for 30 min at 37 °C. Cells were imaged using a fluorescence microscope (Evos M5000; Life Technologies).
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Western blotting
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| 201 |
+
Adherent cells were washed twice with PBS and lysed with radioimmunoprecipitation assay lysis buffer (1% NP-40, 150 mM NaCl, 25 mM Tris base, 0.5% sodium deoxycholate, 0.1% SDS, 1% phosphatase inhibitor cocktails #2 and #3 [Sigma], one cOmplete protease inhibitor tablet [Sigma]). Protein content was quantified using a Bicinchoninic Acid assay (Thermo Scientific), and equal protein was run on 4 to 20% Tris–Glycine Gels (Invitrogen). Protein was transferred to a nitrocellulose membrane (Bio-Rad). Membranes were incubated with primary antibodies overnight at 4 °C: perilipin (CST; catalog no.: 9349), FABP4 (CST; catalog no.: 2120), α-tubulin (Novus; catalog no.: NB100-690), phospho-S6 240/244 (CST; catalog no.: 5364), RPS6 (Novus; catalog no.: NB100-1595), phospho-p70 Thr389 (CST; catalog no.: 9234), p70 49D7 (CST; catalog no.: 2708), phospho-Acetyl-CoA Carboxylase (CST; catalog no.: 3661), acetyl-CoA carboxylase (CST; catalog no.: 3662), phospho-AMPKα (CST; catalog no.: 2535), AMPKα (Invitrogen; catalog no.: MA5-15815), 4EBP1 (CST; catalog no.: 9644), p-HSL Ser565 (CST; catalog no.: 4137T), HSL (CST; catalog no.: 4107T), ATGL (CST; catalog no.: 2439S), p-ATGL (Abcam; catalog no.: ab135093), C/EBPδ (CST; catalog no.: 2318T), C/EBPβ (CST; catalog no.: 3087S), PPARγ (CST; catalog no.: 2443S), and C/EBPα (CST; catalog no.: 8178S). Secondary antibodies used were at 1:10,000: IRDye 800CW Donkey Antimouse immunoglobulin G (H + L) (Li-Cor; catalog no.: 925-32212) and IRDye 680RD Donkey Anti-Rabbit immunoglobulin G (H + L) (Li-Cor; catalog no.: 926-68073). Blots were imaged with the Li-Cor Odyssey CLx infrared imaging system and are representative of at least two independent experiments.
|
| 202 |
+
|
| 203 |
+
RNA isolation and RT–PCR
|
| 204 |
+
|
| 205 |
+
RNA was extracted with the Quick-RNA MiniPrep kit (Zymo Research) directly from adherent cells. Complementary DNA was synthesized from 1 μg of RNA using the iScript complementary DNA synthesis kit (Bio-Rad). Real-time quantitative PCR was performed on a Bio-Rad CFX96 using SsoAdvanced Universal SYBR Green SuperMix (Bio-Rad). Mouse quantitative PCR primer sequences used are listed:
|
| 206 |
+
|
| 207 |
+
Fasn: Forward: CAGCAGAGTCTACAGCTACCT and Reverse: AACACCAGAGACCGTTATGC;
|
| 208 |
+
|
| 209 |
+
Scd1: Forward: GAAGTCCACGCTCGATCTCA and Reverse: TGGAGATCTCTTGGAGCATGTG;
|
| 210 |
+
|
| 211 |
+
Acaca: Forward: TGACAGACTGATCGCAGAGAAAG and Reverse: TGGAGAGCCCCACACACA;
|
| 212 |
+
|
| 213 |
+
Hmgcr: Forward: CTTGTGGAATGCCTTGTGATTG and Reverse: AGCCGAAGCAGCACATGAT;
|
| 214 |
+
|
| 215 |
+
Hmgcs: Forward: GCCGTGAACTGGGTCGAA and Reverse: GCATATATAGCAATGTCTCCTGCAA;
|
| 216 |
+
|
| 217 |
+
Srebp1c: Forward: GGAGCCATGGATTGCACATT and Reverse: GGCCCGGGAAGTCACTGT;
|
| 218 |
+
|
| 219 |
+
Srebp1a: Forward: GGCCGAGATGTGCGAACT and Reverse: TTGTTGATGAGCTGGAGCATGT;
|
| 220 |
+
|
| 221 |
+
Srebp2: Forward: GCGTTCTGGAGACCATGGA and Reverse: ACAAAGTTGCTCTGAAAACAAATCA.
|
| 222 |
+
|
| 223 |
+
Lipogenesis
|
| 224 |
+
|
| 225 |
+
For measurement of lipogenesis, cells were starved in no-glucose serum-free media for 24 h. Following starvation, labeling with 1-14C glucose (PerkinElmer) was performed overnight. Cells were washed twice with PBS before lysis in 0.5% Triton X-100. The lipid fraction was extracted by the addition of chloroform and methanol (2:1 v/v). Samples were centrifuged, and 14C incorporation was measured from the lipid-containing phase using a scintillation counter. Each condition was normalized to total cellular protein concentrations and assessed using a Bicinchoninic Acid Protein Assay Kit (ThermoFisher Scientific).
|
| 226 |
+
|
| 227 |
+
Quantification and statistical analysis
|
| 228 |
+
|
| 229 |
+
Details regarding the specific statistical tests, the definition of center, and the number of replicates (n) can be found for each experiment in the figure legends. GraphPad Prism (GraphPad Software, Inc) and MS Excel were used for all quantifications and statistical analyses.
|
| 230 |
+
|
| 231 |
+
Data availability
|
| 232 |
+
|
| 233 |
+
Any information required to reanalyze the data reported in this article is available from the lead contact upon request.
|
| 234 |
+
|
| 235 |
+
Supporting information
|
| 236 |
+
|
| 237 |
+
This article contains supporting information.
|
| 238 |
+
|
| 239 |
+
Conflict of interest
|
| 240 |
+
|
| 241 |
+
The authors declare that they have no conflicts of interest with the contents of this article.
|
| 242 |
+
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| 243 |
+
Supporting information
|
| 244 |
+
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| 245 |
+
Supporting Figure S1 Nucleotide metabolism is an enriched signature accompanying adipocyte differentiation.A, representative images of Oil Red O staining in primary SVF undifferentiated cells and 6-day differentiated adipocytes. B, representative images of BODIPY 493/503 staining of primary SVF undifferentiated cells and 6-day differentiated adipocytes. C, heat map of metabolites in the nucleotide biosynthesis pathway significantly altered during differentiation. D, relative levels of metabolites in the nucleotide metabolism pathway depleted in differentiation. Data shown are from 4 biological replicates. Error bars indicate mean ± SD, ∗p ≤ 0.05, ∗∗p ≤ 0.01, and ∗∗∗p ≤ 0.001. SVF, stromal vascular fraction.
|
| 246 |
+
|
| 247 |
+
Supporting Figure S2 Inhibition of purine and pyrimidine metabolism disrupts lipid droplets in differentiating adipocytes.A, schematic depicting pyrimidine synthesis pathway. Inhibitors of pyrimidine synthesis are shown in green. B, Oil Red O staining of primary adipocytes differentiated for 6 days and treated with vehicle or indicated drugs every other day. C, Oil Red O staining of 3T3-L1 cells differentiated for 6 days and treated with vehicle or indicated drugs every other day. (D) 6MP, (E) MIZ, (F) BRQ, and (G) 5FU dose studies in µM range followed by western blot analysis of perilipin, FABP4, and tubulin. H, Western blot analysis of perilipin, FABP4, perilipin, and α-tubulin after 6 days of differentiation in primary adipocytes treated with 10 µM MPA or 10 µM AVN. I, Western blot analysis of perilipin, FABP4, DHODH, and tubulin from 3T3-L1 adipocytes infected with shControl or shDHODH and differentiated for 8 days. 6MP, 6-mercaptopurine; MIZ, mizoribine; BRQ, brequinar; 5FU, 5-fluorouracil; FABP4, fatty acid binding protein 4; MPA, mycophenolic acid; AVN, AVN944; DHODH, dihydroorotate dehydrogenase.
|
| 248 |
+
|
| 249 |
+
Supporting Figure S3 Inhibition of purine metabolism in differentiating cells does not alter mTORC1 activity.A, schematic of mTORC1 substrate phosphorylation. (B) Western blot analysis of phospho-S6, S6, and 4E-BP1 in HeLa cells. Cells cultured in DMEM supplemented with 10% FBS or 10% dialyzed FBS and treated with 2 µM LOM and 10 µM LEF for 24 hours. (C) Western blot analysis of pS6, S6, and 4E-BP1 in 3T3-L1 cells. Cells cultured in DMEM supplemented with 10% FBS or 10% dialyzed FBS and treated with LOM and LEF as in S3B for 24 hours. All data are representative of 2-3 independent experiments. mTORC1, mechanistic target of rapamycin complex 1; DMEM, Dulbecco’s modified Eagle's medium; FBS, fetal bovine serum; LOM, lometrexol; LEF, leflunomide.
|
| 250 |
+
|
| 251 |
+
Supporting Figure S4 Inhibition of purine biosynthesis in differentiating cells potentiates AMPK and disrupts lipogenesis.A, 1-14C glucose incorporation into lipid fraction analyzed from 3T3-L1 adipocytes differentiated for 6 days and treated with vehicle or MIZ. TOFA was added during starvation and during 1-14C glucose labeling. Data shown are from 3 biological replicates. Error bars indicate mean ± SD, ∗p ≤ 0.05, ∗∗p ≤ 0.01, and ∗∗∗p ≤ 0.001. Data are representative of 2-3 independent experiments. AMPK, AMP-activated protein kinase; MIZ, mizoribine.
|
| 252 |
+
|
| 253 |
+
Supporting Figure S5 Inhibition of purine biosynthesis blocks adipogenesis by downregulating the expression of key transcriptional regulators.A, model of the transcriptional program that regulates adipogenesis. B, primary SVF cells were maintained undifferentiated or differentiated for 1, 2, 3, 4, or 6 days. Equal amount of protein was loaded and C/EBPd, C/EBPb, PPARg, C/EBPa, and tubulin were analyzed by Western blotting. C, 3T3-L1 cells stably expressing pBABE control vector or PPARg2 were differentiated and treated with 5 µM 5FU or DMSO control for 6 days. Lysates were analyzed by Western blotting as indicated. The data are representative of 3 independent experiments. SVF, stromal vascular fraction; 5FU, 5-fluorouracil; DMSO, dimethyl sulfoxide.
|
| 254 |
+
|
| 255 |
+
Supporting Figure S6 Nucleoside and nitrogenous bases rescue the effects of de novo purine biosynthesis inhibition on adipogenesis.A, BODIPY 493/503 staining of primary adipocytes after 6 days of differentiation untreated or treated with 6MP, or 6MP and a nucleoside cocktail (AIH) containing 5 µM adenosine, 5 µM inosine, and 5 µM hypoxanthine. B, representative images of BODIPY 493/503 staining after 6 days of differentiation in primary SVF cells that were untreated, treated with MIZ, or MIZ and 50 µM guanine. 6MP, 6-mercaptopurine; MIZ, mizoribine.
|
| 256 |
+
|
| 257 |
+
Author contributions
|
| 258 |
+
|
| 259 |
+
E. Z. conceptualization; A. B. S., E. R. N., and E. Z. methodology; A. B. S., E. R. N., J. B. S., and E. Z. formal analysis; A. B. S., E. R. N., G. A. W., M. T. C., J. A. P., J. W. M., J. B. S., and E. Z. investigation; S. H. P. resources; A. B. S., E. R. N., and E. Z. writing–original draft.
|
| 260 |
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|
| 261 |
+
Funding and additional information
|
| 262 |
+
|
| 263 |
+
E. Z. was supported by a P30 058404 DDRTC Pilot and Feasibility Award and DK020593 Vanderbilt Diabetes and Research Training Center and 10.13039/100006537 Vanderbilt University the Seeding Success Grant. J. A. P. was funded by the American Heart Association predoctoral fellowship.
|
| 264 |
+
==== Refs
|
| 265 |
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|
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puc/PMC10164900.txt
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==== Front
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J Biol Chem
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J Biol Chem
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The Journal of Biological Chemistry
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0021-9258
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1083-351X
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American Society for Biochemistry and Molecular Biology
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S0021-9258(23)00253-3
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10.1016/j.jbc.2023.104611
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104611
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Research Article Collection: Glycobiology
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Glycocalyx engineering with heparan sulfate mimetics attenuates Wnt activity during adipogenesis to promote glucose uptake and metabolism
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Trieger Greg W. 12
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Pessentheiner Ariane R. 2
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Purcell Sean C. 1
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Green Courtney R. 3
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DeForest Natalie 2
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Willert Karl 4
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Majithia Amit R. 25
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Metallo Christian M. 3
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Godula Kamil kgodula@ucsd.edu
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16∗
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Gordts Philip L.S.M. pgordts@health.ucsd.edu
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26∗
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1 Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, California, USA
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2 Department of Medicine, Division of Endocrinology and Metabolism, University of California, San Diego, La Jolla, California, USA
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3 Department of Bioengineering, University of California, San Diego, La Jolla, California, USA
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4 Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, California, USA
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5 Department of Pediatrics, University of California, San Diego, La Jolla, California, USA
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6 Glycobiology Research and Training Center, University of California, San Diego, La Jolla, California, USA
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∗ For correspondence: Philip L. S. M. Gordts; Kamil Godula kgodula@ucsd.edupgordts@health.ucsd.edu
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15 3 2023
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5 2023
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15 3 2023
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299 5 10461115 11 2022
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1 3 2023
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© 2023 The Authors
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2023
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https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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Adipose tissue plays a crucial role in maintaining metabolic homeostasis by storing lipids and glucose from circulation as intracellular fat. As peripheral tissues like adipose tissue become insulin resistant, decompensation of blood glucose levels occurs causing type 2 diabetes (T2D). Currently, modulating the glycocalyx, a layer of cell-surface glycans, is an underexplored pharmacological treatment strategy to improve glucose homeostasis in T2D patients. Here, we show a novel role for cell-surface heparan sulfate (HS) in establishing glucose uptake capacity and metabolic utilization in differentiated adipocytes. Using a combination of chemical and genetic interventions, we identified that HS modulates this metabolic phenotype by attenuating levels of Wnt signaling during adipogenesis. By engineering, the glycocalyx of pre-adipocytes with exogenous synthetic HS mimetics, we were able to enhance glucose clearance capacity after differentiation through modulation of Wnt ligand availability. These findings establish the cellular glycocalyx as a possible new target for therapeutic intervention in T2D patients by enhancing glucose clearance capacity independent of insulin secretion.
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Keywords
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proteoglycan
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heparan sulfate
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adipocyte
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glucose
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Wnt signaling
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Abbreviations
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| 52 |
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| 53 |
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DMEM Dulbecco's modified Eagle's medium
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+
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| 55 |
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FFA free fatty acid
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| 56 |
+
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| 57 |
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GP glycopolymer
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| 58 |
+
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| 59 |
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GPC4 glypican 4
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| 61 |
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HS heparan sulfate
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| 62 |
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LPL lipoprotein lipases
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| 64 |
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| 65 |
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MEF mouse embryonic fibroblast
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Ndst1 N-deacetylase-N-sulfotransferase 1
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| 69 |
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T2D type 2 diabetes
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| 70 |
+
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| 71 |
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VLDL very-low density lipoprotein
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| 72 |
+
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| 73 |
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Reviewed by members of the JBC Editorial Board. Edited by Robert Haltiwanger
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==== Body
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pmcType 2 diabetes (T2D) is a growing global health problem caused by excess caloric intake, reduced energy expenditure, and the resulting onset of obesity (1, 2). The constant nutrient influx associated with a Western diet results in high frequency of elevated blood glucose levels. This hyperglycemia demands a continuous insulin secretion from pancreatic beta cells to ensure glucose uptake for energy production and storage (3). The continuous insulin secretion will desensitize its perception by adipocytes, where glucose is normally stored in the form of lipids (4, 5). This insulin resistance coincides with the onset of T2D, leading ultimately to beta cell failure (6, 7). T2D patients have a high risk to develop neuropathy, retinopathy, cardiovascular disease, stroke, and poor outcomes when coping with infectious disease (8). Overall, this greatly reduces their quality of life and life expectancy. As a result, T2D has been a prominent focus of medical research to find effective treatments. Current treatment strategies focused on increasing insulin perception, augmenting oxidative tissue activity, or decreasing excessive food consumption or nutrient absorption have been limited by poor efficacy or detrimental side-effects as exemplified by the COVID-19 pandemic (8, 9, 10). An alternative approach to increase insulin-independent glucose clearance is to capitalize on adipose tissue expandability and its functional metabolic flexibility and reprogram adipogenesis to increase basal glucose clearance capacity in adipose tissue (11, 12, 13, 14).
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The cellular glycocalyx has been well-established to play a regulatory role during adipogenesis and in adipocyte function and can serve as a potential target for therapeutic intervention in T2D (15, 16, 17). Although, the functions of specific cell-surface glycans during adipogenic programing and their impact on glucose clearance capacity of terminally differentiated adipocytes are yet to be fully elucidated. For instance, an unbiased proteomic screen of human adipose tissues and plasma identified glypican 4 (GPC4), a heparan sulfate (HS) proteoglycan, as an adipokine (15, 18). In patients, plasma GPC4 levels correlate positively with the severity of insulin resistance, impaired glucose uptake, and high body mass index (15, 19). Genetic knockout or shedding of GPC4 is associated with an overall reduction in adipogenesis in vitro, which manifests in concurrent reduction of glucose uptake, insulin sensitivity, and lipid accumulation in adipocytes (19). It is not clear whether the adipokine function of GPC4 stems from the protein core or its glycosylation modification with HS glycans (20).
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HS are polysaccharide chains comprised of repeating units of N-acetylglucosamine and glucuronic acid, which are enzymatically modified through N-deacetylation, epimerization at the uronic acid residue, and sulfation (15). These modifications produce domains with negatively charged residues, which are selectively recognized by HS-binding proteins (21). Cell surface HS has been extensively studied in the context of promoting lipoprotein uptake and metabolism (22). Accordingly, defects in lipid accumulation in differentiated adipocytes lacking Syndecan-1, also an HS proteoglycan, or the HS biosynthetic enzyme, N-acetylglucosamine N-deacetylase-N-sulfotransferase 1, have been attributed to decreased endocytosis of triglyceride-rich lipoproteins (23, 24). Cognizant of the regulatory roles of HS in cellular signaling and differentiation (25), we set to investigate the possible roles of HS during adipogenic differentiation in defining the metabolic activity of terminally differentiated adipocytes.
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Using a combination of genetic and chemical approaches to manipulate HS presentation and activity in the glycocalyx of pre-adipocyte cells (26), we uncovered the contributions of HS in regulating Wnt signaling to establish metabolic set points after differentiation. Further, glycocalyx engineering in pre-adipocytes with HS mimetics attenuated Wnt signaling and altered their differentiation program to produce adipocytes with increased glucose uptake and utilization. Chemical engineering of the glycocalyx thus opens a new therapeutic window for improving glucose clearance in T2D patients independent of their insulin sensitivity.
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Results
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HS deficiency prevents lipid accumulation in mature adipocytes
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To define the impact of HS during adipogenic differentiation on establishing the metabolic setpoint of adipocytes, we utilized immortalized mouse embryonic fibroblasts (MEFs) with defective HS biosynthesis. As a model, we utilized MEFs lacking the HS biosynthetic enzyme, N-deacetylase-N-sulfotransferase 1 (Ndst1), which is required for the generation of sulfate domains that modulate interaction of HS with its binding proteins (27). We observed a significantly diminished lipid storage in adipocytes after differentiation of these Ndst1-deficient (Ndst1−/−) MEFs (Figs. 1, A and B and S1, A–C). The lack of lipid accumulation was not the result of altered growth rate (Fig. 1C) nor a consequence of defective adipogenesis (Fig. 1, D–K). Comparison of several adipogenic markers in Ndst1−/− MEFs to WT cells indicated that adipogenic genes are upregulated (such as Fas) and pre-adipocyte marker (i.e., Dlk) are more repressed. A similar lipid accumulation phenotype was generated in wildtype MEFs during adipogenesis upon treatment with high dose of heparin (100 μg/ml), which is a highly sulfated form of HS that serves as a competitive inhibitor for cell surface HS at the concentration used (Figs. 1, A–C and S1D). Previous studies in pre-adipocytes indicated that exogenous heparin treatment and Ndst1 inactivation reduced lipid accumulation by interfering with HS-mediated endocytosis of triglyceride-rich lipoproteins, including very-low density lipoprotein (VLDL) (28, 29). In contrast, Ndst1 inactivation in MEF-derived adipocytes had no effect on VLDL binding and uptake (Fig. 1L). Exogenous heparin or Ndst1 inactivation resulted in reduced binding of lipoprotein lipase (LPL), an HS-binding protein responsible for the release of free fatty acids (FFAs) from VLDL (Fig. 1M). In our MEF cell model system, however, RNAseq analysis indicated a lack of Lpl mRNA in MEFs at all stages of differentiation. No VLDL-derived FFA uptake above the background in both undifferentiated and differentiated wildtype and Ndst1-deficient cells could be detected. Accordingly, it is unlikely that impaired LPL binding contributes to defective FFA delivery to alter lipid accumulation in HS sulfation impaired MEFs. Furthermore, genetic or chemical inhibition of HS did not negatively affect direct FFA uptake (Fig. 1N), suggesting collectively that altered lipid accumulation upon HS inactivation was independent of lipid uptake.Figure 1 Cell surface heparan sulfate regulates lipid storage in differentiating adipocytes.A, Oil Red O stain of differentiated WT and Ndst1−/− adipocytes treated with or without heparin (100 μg/ml). Nuclei visualized with DAPI. B, quantified Oil red stain performed by elution of stain (two-way ANOVA, n = 3). C, MTT assay of WT and Ndst1−/− adipocytes treated with or without heparin (100 μg/ml) (n = 3). D–K, RNAseq quantification of adipogenesis markers relative to day 0 expression levels of WT and Ndst1−/− MEFs undergoing adipogenesis (two-way ANOVA, n = 2). L, cell surface binding of very low-density lipoprotein (VLDL) binding to the WT and Ndst1−/− cells (n = 3). M, lipoprotein lipase (LPL) binding to WT or Ndst1−/− adipocytes treated with or without heparin (100 μg/ml) (two-way ANOVA, n = 3). N, radiolabeled fatty acid 3[H]-Palmitate uptake in WT or Ndst1−/− adipocytes treated with or without heparin (100 μg/ml) (two-way ANOVA, n = 3). Data are presented as mean ± SD, ∗∗∗∗p < 0.0001, ∗∗∗p < 0.001, ∗∗p < 0.01, ∗p < 0.05. Hep, Heparin; MEF, mouse embryonic fibroblast; Ndst1, N-deacetylase-N-sulfotransferase 1.
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| 88 |
+
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| 89 |
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HS inactivation in pre-adipocytes alters insulin-independent glucose uptake after differentiation
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| 90 |
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| 91 |
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Insulin-stimulated glucose clearance is one of the primary functions of adipocytes (5). We reasoned that the potential discrepancy between reduced lipid storage and unaltered lipid uptake could be a consequence of altered cellular glucose metabolism. To test this hypothesis, we first examined the impact of HS function in MEFs on glucose uptake in mature adipocytes. We observed a significant 84% reduction of glucose uptake in Ndst1-deficient adipocytes (Fig. 2A), which was paralleled by a 45% reduction in WT cells treated with exogenous heparin (Fig. 2B). Treatment of Ndst1−/− with exogenous heparin did not have an additive effect on glucose uptake (Figs. 2C and S2A). We observed a similarly impaired glucose uptake in adipocytes derived from primary murine white adipose tissue pre-adipocytes differentiated in the presence of heparin (Figs. 2D and S3). Surprisingly, the same differentials in glucose uptake between WT and HS sulfation-impaired cells were maintained after insulin stimulation (−84% and −44% respectively; Fig. 2, A and B). Both in WT and Ndst1−/− adipocytes insulin stimulates relative glucose uptake to the same extend (Fig. S2B). Thus, the relative response to insulin is identical in WT and Ndst1−/− adipocytes. However, because of the dramatic baseline difference in glucose uptake, the insulin stimulated Ndst1−/− adipocytes do not reach similar absolute levels in insulin-stimulated glucose uptake as compared to WT cells. This observation suggests that HS alters glucose uptake without altering insulin sensitivity. This was further supported by similar levels of AKT phosphorylation in WT and HS sulfation-impaired cells upon stimulation with insulin (Fig. 2E). The observed diminished glucose uptake could be the result of reduced expression of cell surface glucose transporters, i.e., GLUT1 and GLUT4. However, Western blot analysis of isolated plasma membrane fractions indicated unaltered levels of GLUT4 (Fig. 2F) and GLUT1 (Fig. S4) in response to HS inactivation. These observations collectively indicate a link between cell surface HS levels and changes in glucose uptake in adipocytes, which is independent of glucose transporter expression and insulin activity.Figure 2 Loss of cell surface heparan sulfate interactions during adipogenesis reduce glucose uptake. A, Ndst1−/− cells have a significantly reduced glucose uptake potential relative to WT adipocytes (two-way ANOVA, n = 2; one representative experiment out of 3). B, heparin treatment (100 μg/ml) reduces glucose uptake potential relative to WT adipocytes (two-way ANOVA, n = 2; one representative experiment out of 3). C, heparin treatment does not further reduce Ndst1−/− adipocytes ability to access glucose (n = 2, one representative experiment out of 3). D, primary adipocytes derived from murine subcutaneous white adipose tissue (sWAT) stromal vascular cells presented with reduced glucose uptake when co-incubated with heparin during adipogenesis (two-way ANOVA, n = 2). E, stimulation of mature adipocytes (day 6) with insulin (20 nM) leads to equal signaling transduction via AKT phosphorylation regardless of HSPG interaction modulation (n = 3). F, glucose transporter 4 protein (GLUT4) is similarly expressed at the cell surface of WT and HSPG inhibited adipocytes (n = 3). Data are presented as mean ± SD, ∗p < 0.05; #p <0.05 relative to WT with no insulin stimulation. Hep, Heparin; HSPG, HS proteoglycan; Ndst1, N-deacetylase-N-sulfotransferase 1.
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HS inactivation induces a switch from glycolysis to oxidative metabolism
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| 95 |
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A decrease in glucose uptake without changes in glucose transporter expression in HS sulfation-impaired adipocytes can stem from reduced cellular glucose utilization (5). The attenuated demand for cellular glucose could be the result of a switch from glycolysis to fatty acid–dependent oxidative metabolism. We suspected such a metabolic switch based on the observed reduction in lipid storage (Fig. 1, A and B) and lactate production (Fig. 3, A and B) in HS sulfation-impaired adipocytes. This decreased lactate production was also mirrored by high glucose levels remaining in the culture medium (Fig. 3C). Typically, reliance on oxidative metabolism will drive breakdown of intracellular lipids that can be compensated for by increased fatty acid uptake from external sources. Accordingly, we observed a significant reduction in intracellular palmitate levels (Fig. 3D) and increased influx of isotopically labeled [U-13C16]palmitate in HS sulfation-impaired cells (Fig. 3E). Under oxidative metabolism, palmitate is converted into citrate via the citric acid (TCA) cycle. In agreement with enhanced oxidative metabolism in HS sulfation-impaired cells, we observed a significant increase in isotopically labeled citrate production in our experiment (Fig. 3F). Collectively, these observations support a switch in the metabolic program of adipocytes induced by HS.Figure 3 Heparan sulfate deficiency during adipogenesis promotes fatty acid oxidation. A, WT cells produce a greater amount of lactate than Ndst1−/− adipocytes or adipocytes treated with heparin (100 μg/ml) during differentiation, as observed by discoloration of the phenol red indicator on day 6 of the differentiation over a 48-h period. B, YSI measurement of lactate in spent media collected on the final day (day 6) of adipogenesis. Fresh media have a concentration of 1.5 mmol/L lactate on day 6 of the differentiation over a 48-h period. (two-way ANOVA, n = 2, one representative experiment out of 3). C, YSI measurement of glucose in spent media collected on the final day (day 6) of adipogenesis over a 48-h period, with fresh media at a concentration of 19 mmol/L glucose (two-way ANOVA, n = 2, one representative experiment out of three). D, palmitate abundance relative to control WT cells from saponified lipids measured using mass spectroscopy, indicating total intracellular palmitate is higher in WT control cells (two-way ANOVA, n = 3). E, intracellular [U-13C16] palmitate levels indicate that HSPG-inhibited conditions present with increased palmitate uptake compared to control WT adipocytes (two-way ANOVA, n = 3). F, tracing of [U-13C16] palmitate metabolism indicates that palmitate is being increasingly converted to citrate in HSPG-inhibited adipocytes compared to control WT controls (Two-way ANOVA, n = 3). Data are presented as mean ± SD, ∗∗∗p < 0.001, ∗∗∗∗p <0.0001. HSPG, HS proteoglycan; Ndst1, N-deacetylase-N-sulfotransferase 1.
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HS defines metabolic activity of adipocytes during early adipogenesis
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| 99 |
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To determine if HS defines the metabolic switch during or after adipogenesis, we subjected mature WT and Ndst1−/− adipocytes to a 3[H]-2-deoxyglucose challenge in the presence of soluble heparin or after cell surface HS removal with heparin lyases. Neither method of acute HS inhibition resulted in altered glucose uptake (Fig. 4, A and B), suggesting a role for HS during adipogenesis. Further support comes from lack of an effect of HS inhibition on glucose uptake in undifferentiated pre-adipocytes (MEF) or in terminally differentiated cells of nonadipogenic origin (Hep3B) (Fig. 4C) (30). To define the time window during adipogenesis when HS exerts its effect, we added or removed heparin at different timepoints during differentiation (Fig. 4, D and E). We observed that treatment with heparin for the first 3 days of differentiation was required to significantly reduce glucose uptake in mature adipocytes (Fig. 4, D and E). The data point to the role for HS in defining the glucose uptake capacity early in the adipogenic program, focusing our search for a putative mechanism in this 3-day differentiation window.Figure 4 Heparan sulfate modulates adipocyte glucose clearance capacity early during adipogenesis. A, adipocytes simultaneously treated with heparin (100 μg/ml) during 3[H]-2-deoxy-glucose administration present with unaltered glucose uptake (n = 3) and independent of cell surface heparan sulfate presentation (n = 3). B, treatment of adipocytes with heparin lyases I-III (30 min) prior to 3[H]-2-deoxy-glucose uptake did not alter glucose uptake (n = 3). C, undifferentiated Ndst1−/− MEFs and Ndst1−/− Hep3B (human hepatoma) cells have no significant difference in their 3[H]-2-deoxy-glucose uptake capacity (n = 2). D, heparin removal: all conditions except untreated (ctrl.) cells were initially conditioned with heparin (100 μg/ml) in the media. On the indicated days [day (D) 1 up to D6], heparin was removed from media to allow heparin-free differentiation conditions from that day onward. Glucose uptake potential was assessed at day 6 for all conditions. Heparin addition significantly reduced glucose uptake if cells were treated up to day 3 and beyond (two-way ANOVA, n =��3). E, heparin addition: all conditions except untreated (day 0, D0) MEFs begin with no heparin in the media. Glucose uptake potential was assessed at day 6 for all conditions. Heparin is added at indicated days during differentiation. Addition of heparin after day 4 of differentiation can no longer impact glucose uptake in mature adipocytes (two-way ANOVA, n = 3). Data are presented as mean ± SD, ∗p < 0.05 compared to control (ctrl.). MEF, mouse embryonic fibroblast; Ndst1, N-deacetylase-N-sulfotransferase 1.
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The HS-Wnt signaling axis defines the metabolic program in adipocytes
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The HS can regulate cellular differentiation by influencing a number of signaling pathways, including the FGF, SHH, TGF-ß, VEGF, and Wnt superfamilies of signaling proteins (21, 25). To identify HS-dependent signaling pathways pertinent to metabolic programming in adipocytes, we performed comparative transcriptomic analysis of genetically (Ndst1−/−) and chemically (WT + heparin) HS-inhibited MEFs at early (day 3) and late (day 6) stages of adipogenesis. Overall, both genetic and chemical inactivation of HS resulted in a significant change in gene expression compared to WT controls (Fig. 5A). Not surprisingly, the genetic Ndst1 deletion had a more profound overall effect on the transcriptome compared to the heparin-treated MEFs. Nonetheless, both conditions resulted in a shared set of transcripts that were significantly altered compared to WT controls (Fig. 5A). Metascape analysis of the overlapping sets of genes indicated no major differences in typical adipogenic pathways (Fig. 5B) (31). A closer examination of enriched transcripts relevant to signaling pathways regulated by HS revealed a characteristic gene signature associated with Wnt signaling (Fig. 5, B and C) (11, 21, 25). The genes most upregulated by HS inhibition in the early stage of adipogenesis are Wnt readout-effector genes Plpp3, Gli3, Grk5, and Rnf213, indicating strong activation of the Wnt pathway (Fig. 5C). In agreement with increased Wnt signaling, the genes Sox2, Lgr6, and Klf5 were downregulated in HS inhibited cells compared to WT controls (Fig. 5C). These observations are consistent with the known role for canonical Wnt signaling in regulating adipocyte metabolism during adipogenesis (11). However, how HS influences Wnt activity in this particular process is unclear and often context dependent (32, 33). Our data suggest that the functional role of HS is to attenuate Wnt activity during adipogenesis (25, 34, 35). To confirm this hypothesis, we performed differentiation experiments in WT and Ndst1−/− MEFs in the presence or absence of small molecule inhibitors of Wnt. We used the canonical Wnt signaling inhibitors niclosamide and XAV-939, as well as Wnt-C59, which additionally inhibits the noncanonical arm of the signaling pathway (Fig. 5, D–I). All three Wnt inhibitors significantly increased the glucose uptake capacity in Ndst1-deficient adipocytes (Figs. 5, E and G, I and S5) and showed a modest effect in WT cells (Fig. 5, D, F, and H). These experiments confirm that attenuation of Wnt signaling during early stages of adipogenesis in Ndst1-deficient cells promoted glucose uptake in adipocytes after differentiation.Figure 5 HS modulation of Wnt signaling during adipogenesis promotes glucose clearance in mature adipocytes.A, Venn diagram showing the number uniquely upregulated (1.5-fold enhancement relative to WT on that day) and downregulated (1.5-fold reduction relative to WT on that day) genes on day 3 and day 6 of Ndst1−/− adipocytes and WT adipocytes treated with heparin (100 μg/ml) (n = 4). Overlapping central regions indicate the number of genes upregulated or downregulated by both Ndst1−/− and WT cells treated with heparin. B, Metascape gene ontology analysis of genes equally affected by Ndst1 inactivation or heparin addition during adipogenesis indicate enrichment of Wnt signaling–regulated genes. C, heatmap of RNASeq data of Wnt-related genes showing fold change in relative to untreated WT MEFs undergoing adipogenesis. D–E, niclosamide, a Wnt inhibitor, treatment during the first 3 days of adipogenesis is unable to significantly enhance glucose clearance in differentiated WT adipocytes (n = 2–3). Niclosamide is able to enhance glucose clearance in Ndst1−/− adipocytes at 12.5 nM (one-way ANOVA, n = 2–3). F–G, treatment during the first 3 days of adipogenesis of WT and Ndst1−/− adipocytes with Wnt inhibitor, XAV-939, enhances glucose clearance in differentiated adipocytes (one-way ANOVA, n = 3). H–I, WT cells differentiated in the presence of Wnt-C59 had no effect on cellular glucose clearance (10 nM was toxic to WT adipocytes). Treatment of Ndst1−/− cells with Wnt-C59 enhanced glucose clearance capacity in differentiated Ndst1−/− adipocytes (one-way ANOVA, n = 2–3). Data are presented as mean ± SD, ∗∗∗p < 0.001, ∗∗p < 0.01, ∗p < 0.05. HS, heparan sulfate; MEF, mouse embryonic fibroblast; Ndst1, N-deacetylase-N-sulfotransferase 1.
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Chemical remodeling of the pre-adipocyte glycocalyx enhances glucose uptake after differentiation
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Our results point to the role of cell surface HS in inhibiting Wnt activity, presumably by sequestering the ligand away from its receptor Frizzled (Fig. 6A) (33). Targeting the Wnt signaling pathway has been suggested previously as a therapeutic opportunity for increasing glucose uptake capacity in adipose tissues (11, 36). However, in our experiments, we were able to observe only marginal benefits (up to 40% increase in glucose uptake) in WT cells in the presence of chemical Wnt signaling inhibitors at the maximum tolerated dosage (Fig. 5F). We employed an alternative strategy to augment the natural capacity of the pre-adipocyte glycocalyx to inhibit Wnt signaling in order to enhance glucose clearance. We engineered the cell surfaces of WT and Ndst1−/− MEFs to present synthetic mimetics of HS (37). The HS mimetics comprise a synthetic linear polymer backbone decorated with disaccharide motifs representing the basic structural units of HS (Fig. 6A). The disaccharide side chains were differentially sulfated to provide a range of binding avidity for the Wnt ligands (Fig. 6B). The HS mimetics carrying the most sulfated disaccharide (D2S6) showed Wnt5b and Wnt10a binding characteristics comparable to heparin (Fig. 6C). Additionally, the HS mimetics were endowed with a hydrophobic lipid (DPPE) anchor, for insertion into the cell membranes, and a flurophore (AF488) for quantification. Incubation of pre-adipocytes with the HS mimetics for 1 h at 37 ºC resulted in efficient and dose-dependent cell membrane incorporation (Fig. S6). We observed higher incorporation levels for sulfated HS mimetics in Ndst1−/− MEFs compared to WT controls (Fig. S6). This can be expected based on the reduced overall negative charge of HS in the glycocalyx of Ndst1−/− MEFs. The remodeled pre-adipocytes were subjected to differentiation with the polymer being re-introduced once a day over the previously identified HS activity window (Day 0–3). On day 6 of differentiation, the adipocytes were assayed for glucose uptake and lactate production (Fig. 6, E and F). The sulfated Wnt-binding HS mimetics were able to restore the reduced basal glucose clearance associated with Ndst1 inactivation. The membrane targeting of the HS-mimetics is critical for their activity as supplementation with soluble heparin had no effect (Fig. 6, E and F). Similarly, sulfation of the disaccharide is important for activity, as the nonsulfate control HS-mimetic D0A0 showing only a limited ability to improve glucose uptake. Importantly, unlike treatment with small molecule Wnt inhibitors, cell surface engineering with HS mimetics carrying the sulfated D2A6 and D2S6 disaccharides significantly improved basal glucose uptake capacity in WT adipocytes by 39% and 47%, respectively (Fig. 6E). This suggests that engineering the glycocalyx of pre-adipocytes to tune Wnt signaling sensitivity may provide a new effective approach for controlling the metabolic status of adipocytes favoring glucose clearance and utilization.Figure 6 Membrane-incorporation of synthetic HS glycopolymers during adipogenesis rescues the impaired glucose uptake in HS-deficient adipocytes.A, synthetic glycopolymers bearing a HS GAG disaccharide repeats were prepared and incorporated into the membranes of differentiating MEFs. Schematic of Wnt ligand sequestration by cell membrane anchored HS glycopolymers. B, selected HS GAG disaccharides D2A6 (disulfated), D2S6 (trisulfated), and D0A0 (unsulfated). C, Wnt5a binding activity assessed by ELISA with D2S6 glycopolymer (EC50 = 5.1 nM, r2 = 0.94, n = 3) or heparin (EC50 = 28.2 nM, r2 = 0.87, n = 3), showing dose-dependent binding activity. D, Wnt10b binding activity assessed by ELISA with D2S6 glycopolymer (EC50 = 5.1 nM, r2 = 0.97, n = 2) or heparin (EC50 = 30.1 nM, r2 = 0.95, n = 3), showing dose-dependent binding activity. E, Ndst1−/− and WT MEFs are treated with glycopolymer for 1 h at 37 °C on day 0 to 3 of adipocyte differentiation. Sulfated glycopolymers D2A6 and D2S6 are able to dose-dependently enhance 3[H]-2-deoxy-glucose uptake in differentiated adipocytes (day 6) (two-way ANOVA, n = 3). F, media of treated Ndst1−/− adipocytes (day 6) was assessed for glucose and lactate concentration using YSI. Cells treated with sulfated glycopolymers show a dose–response rescue of glucose utilization (lowered media concentration) and increased production of the glycolysis product lactate (two-way ANOVA, n = 2). Data are presented as mean ± SD, ∗∗∗∗p < 0.0001, ∗∗∗p < 0.001, ∗∗p < 0.01. HS, heparan sulfate; MEF, mouse embryonic fibroblast; Ndst1, N-deacetylase-N-sulfotransferase 1.
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Discussion
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A key challenge in formulating therapeutic approaches for treatment of diabetes is the management of glucose levels. The mainstream therapeutic approach is to improve insulin-mediated glucose clearance or to restrict dietary glucose intake (9). An alternative approach may involve reprogramming of newly generated fat tissues to increase their overall cellular metabolism and glucose demand (11, 12, 13, 14). Here, we present evidence that we can steer the adipogenic program to generate newly matured adipocytes with enhanced oxidative glucose metabolism to drive an increase in basal insulin-independent glucose uptake.
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Using a combination of genetic and chemical tools to manipulate the HS composition on the cell surface, we identified a key role for these glycans in generating this metabolic phenotype and narrowed down the activity window during the first 3 days of adipogenesis. Lack of Ndst1 expression did result in changes in the expression of adipogenic genes. However, many of those adipogenic genes and pre-adipocyte marker are more repressed. This is suggesting an increased adipogenic potential of Ndst1-deficient MEFs, but certainly no defective adipogenesis. Moreover, when we treat wildtype MEFs with heparin, we observed almost no significant differences in expression of adipogenic and pre-adipogenic genes, yet similar metabolic consequences (akin to NDST1 inactivation) are observed in the heparin-treated cells. This is further supported by gene ontology and ingenuity pathway analysis of our transcriptomic data. These analyses did not indicate that genes associated with adipocytes or adipogenesis were overrepresented or underrepresented, supporting the concept that the adipogenic program was activated equally and potentially more so in Ndst1-deficient cells but certainly equal in heparin-treated cells compared to the controls. Therefore, the improved glucose uptake in Ndst1-deficient adipocytes after glycocalyx remodeling cannot be rationalized by their increased differentiation potential. The disconnect between differentiation potential and glucose uptake in HS sulfation-impaired cell models is fascinating and will need to be investigated to identify the molecular mechanism.
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However, transcriptomic analysis did reveal that Wnt signaling was most perturbed in response to HS modulation within a differentiation window. The heparin addition at the concentration we used will have a stronger inhibitory effect compared to NDST1 inactivation; some signaling interactions will still be stimulated by HS despite the NDST1 inactivation. This discrepancy in potency can explain the transcriptome differences between the heparin treatment and the Ndst1−/− cells. Nevertheless, the fact that despite these dissimilarities, we still find a common affected Wnt signaling pathway underscores the robustness of this finding. Wnt signaling is a well-established HS-dependent modulator of metabolic programming during adipogenesis and as such has been considered as a target for therapeutic intervention (11, 25, 32, 36). However, Wnt targeting is challenging due to its pleiotropic effects in numerous other biological systems as well as poorly defined contribution of HS function during adipogenesis (36).
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Cell surface HS can both promote and inhibit cell signaling events via either promoting signaling complex formation or by sequestering ligands away from cognate receptors, respectively (22, 25). In this study, we observed that eliminating cell surface HS activity pre-adipocytes led to enhanced Wnt signaling, pointing to an inhibitory role of endogenous cell surface HS in Wnt regulation. This conclusion was further supported by the restoration of the wildtype phenotype, upon application of small molecule inhibitors of Wnt signaling. Recent work identified that the protein backbone of a subclass of glypicans, including GPC1 and GPC4, can bind the lipid moiety of palmitoylated Wnt, serving as a ligand sequestering depot before being handed over to cognate receptors (38). Mutual binding of the lipid moiety to the GPC4 core protein and the interaction of protein moiety with GPC4 HS chains will increase its Wnt binding affinity and promote sequestration. However, whether such a dual binding mechanism can occur and support the central role of GPC4 as a modulator of adipogenesis remains to be established. Interestingly, we find that both Gpc1 and Gpc4 as well as the 6-O sulfotransferase, Hst6st1, are upregulated in Ndst1-deficient MEFs (Fig. S7, A–F). Hence, it is possible that by compensating for the loss of N-sulfation these GPCs and enzymes are upregulated to indirectly augment Wnt signaling. Given our Wnt signaling data, we do not believe this compensation can entirely offset the loss of HS N-sulfation to restore cellular metabolism. Furthermore, the HS mimetics indicate that reconstitution with functionally sulfation of HS is essential to fully rescue the metabolic phenotype. We also did not observe this compensatory HS gene expression pattern in heparin-treated WT cells.
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Although chemical inhibition of Wnt activity during adipogenesis moderately enhanced the metabolic phenotype of WT adipocytes, it required inhibitor concentrations close to the maximum tolerated dose. To overcome these limitations, we instead augmented the cellular glycocalyx with synthetic HS-mimetics with Wnt sequestering activity. The materials, based on synthetic poly(acrylamide) chains, had a Wnt binding domain composed of HS disaccharides carrying N-, 2-O and 6-O sulfation and a DPPE lipid for membrane targeting. This approach delivered a more robust enhancement of glucose uptake in both HS-deficient and WT adipocytes after differentiation. Interestingly, in Ndst1-deficient pre-adipocytes, the polymer treatment resulted in a 100% improved glucose uptake capacity above the basal levels in untreated WT adipocytes. This indicates a comparable or better ability of these HS-mimetics to attenuate HS-mediated signaling compared to endogenous HS in WT cells. In WT cells, we observed a somewhat lower but still robust improvement in glucose uptake by approximately 50%. This outcome is consistent with less efficient incorporation of the sulfated HS-mimetics presumably due to increased electrostatic shielding from endogenous HS structures in WT cells. Further investigation should focus on optimizing the HS-mimetic architecture to further improve Wnt inhibition as well as plasma membrane targeting and localization. Our findings also open the possibility for future efforts to probe if natural variation in HS composition on adipocytes between individuals can help explain the predisposition of at-risk patients for T2D (39).
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In conclusion, we show for the first time that HS engineering can alter adipogenesis to improve glucose metabolism and clearance in newly differentiated adipocytes. This approach may open up new therapeutic avenues for the treatment of diabetes; this is particularly relevant when insulin signaling is refractory to any other treatment modality.
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Experimental procedures
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Adipogenic differentiation
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Cells were seeded on a 24-well plate at a density of 30,000 cells/cm2. Cells were allowed to grow to confluence for 48 h in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% FBS containing FFA and 1% Pen-Strep (Sigma). At this point (Day 0), the media were removed, cells were washed with PBS, and differentiation media with or without heparin (100 μg/ml) were added. Differentiation media consisted of 0.1 μM dexamethasone, 450 μM 3-isobutyl-1-methylxanthine, 2 μM insulin, and 1 μM rosiglitazone in DMEM supplemented with 10% FBS containing FFA and 1× Pen-Strep (Sigma). On day 3 of differentiation, cells were washed with PBS and treated with insulin media, which consisted of 2 μM insulin, and 1 μM rosiglitazone in DMEM with 10% FBS containing FFA and 1× Pen-Strep (Sigma). The cellular cholesterol and triglyceride content was determined after lysing cells in 0.1 M NaOH. Total plasma cholesterol and plasma triglyceride levels (Sekisui Diagnostics) and protein levels (BCA protein assay) were determined using commercially available kits. All procedures were approved by the University of California San Diego Institutional Animal Care and Use Committee.
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Gene expression analysis
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Total RNA from homogenized tissue and cells was isolated and purified using E.Z.N.A. HP Total RNA (Omega) or RNeasy mini (Qiagen) kits according to the manufacturers’ instructions. The quality and quantity of the total RNA was monitored and measured with NanoDrop (NanoDrop Technologies, Inc). 5 to 10 ng of cDNA was used for quantitative real-time PCR with gene-specific primers (Table S1) and TBP as a house keeping gene on a BioRad CFX96 Real-time PCR system (Bio Rad).
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RNA-seq library preparation
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Cells were lysed in Trizol, and total RNA was extracted using the Direct-zol kit (Zymo Research). On column DNA digestion was also performed with DNAse treatment. Stranded RNA-Seq libraries were prepared from polyA-enriched mRNA using the TruSeq Stranded mRNA library prep kit (Illumina). Library construction and sequencing was performed by the University of California San Diego Institute for Genomic Medicine. Libraries were single-end sequenced for 76 cycles on a HiSeq 4000 to a depth of 20 to 30 million reads.
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RNASeq analysis
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The Kallisto/Sleuth differential expression pipeline analysis was performed for each of the 16 samples. Kallisto was run for single-end read quantification, using the parameters: kmer size = 31, fragment length = 280, and sd = 25. For each of the 16 samples, Kallisto quantified transcript abundance with 10 bootstraps. Normalized transcript abundances were further passed into sleuth, which were then aggregated to gene level. The data are deposited in the GEO database under GSE217323.
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Oil Red O assay
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MEFs differentiated to day 6 into adipocytes in a 24-well plate are washed twice with PBS, then fixed in 4% paraformaldehyde for 10 min. The cells are then washed twice with PBS and once with MilliQ water before being then incubated for 1 min in 60% isopropanol. Then, the oil red working solution is placed on the cells for 8 min. The working solution is prepared from an Oil Red O stock solution consisting of 0.5 g Oil Red O in 100 ml isopropanol which has been heated to 56 °C until the Oil Red O has dissolved. The working solution is prepared by taking 30 ml of stock solution and adding to 20 ml distilled water. The mixture must stand for at least 10 min then be filtered before use. After the 8 min incubation, cells are incubated in 50% isopropanol for 1 min, followed by another 1 min incubation in 10% isopropanol, then MilliQ water, followed by tap water. After each of these 1 min incubations, the fixed, stained cells are placed in MQ water and imaged. The water is removed, and the wells are allowed to dry. The stain can then be eluted in 200 μl 100% isopropanol over a 10 minute incubation period. The eluted stain is then placed into a 96-well plate, and absorbance is measured at 500 nm.
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MTT assay
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MEFs differentiated to day 6 into adipocytes in a 24-well plate, and on day 6, cells are treated with 50 μl of the Cytoselect MTT assay preformulated reagent, which is added directly to media. The cells are incubated in this mixture for 4 h as violet precipitates form. The cells are then treated with 500 μl of the supplied detergent solution for 2 h, and wells are agitated with pipetting to enhance the dissolution of the precipitate. The detergent with dissolved precipitate is then moved to a fresh 24-well plate, and absorbance is measured at 570 nm.
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LPL binding assay
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Bovine LPL generously provided by Gunilla Olivecrona (Department of Biomedical Sciences, Umeå University) (40). The LPL binding assays were performed using biotin-labeled LPL using the EZ-Link NHS-Biotin (ThermoFisher). Molar ratio of biotin to LPL was determined in a HABA displacement assay (Pierce Biotin Quantitation Kit). Cells were harvested using Accutase cell detachment solution (Millipore) and washed twice with PBS. Cells were incubated for 15 min at 37 °C in serum-free media in the absence or presence of 5 mU/ml each of recombinant heparin lyases I, II, and III. Treated and untreated cells were washed twice with PBS, chilled on ice for 20 min, and incubated with 50 nM biotinylated LPL in 1% FFA-free bovine serum albumine (BSA) supplemented PBS at 4 °C for 1 h. Following the incubation, cells were washed twice in ice-cold PBS and incubated with 0.4 μg/ml Phycoerythrin-Cy5–conjugated Streptavidin in 1% FFA-free BSA supplemented PBS at 4 °C. A set of cells was exposed only to Phycoerythrin-Cy5–conjugated Streptavidin and was used as background control. Cells were washed twice with PBS and analyzed by flow cytometry.
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VLDL binding to adipocytes
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Human VLDL (δ < 1.006 g/ml) was isolated from plasma by buoyant density ultracentrifugation and quantified by BCA protein assay (Pierce) (30). To label the particles, 1 to 2 mg of VLDL were combined with 100 μl of 3 mg/ml 1,1′-dioctadecyl-3,3,3′,3′-tetramethylindodicarbocyanine perchlorate (Invitrogen) in DMSO and then re-isolated by ultracentrifugation. After incubation with VLDL for 30 min at 4 ºC, cells were rinsed with PBS and lysed by adding 0.1 M NaOH plus 0.1% SDS for 40 min at room temperature (30). Fluorescence intensity was measured with appropriate excitation and emission filters in a plate reader (TECAN GENios Pro) and normalized to total cell protein.
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Glucose and lactate quantification
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MEFs are differentiated to day 6 into adipocytes in a 24 well plate, and on day 6, 500 μl of media is collected from each well in an Eppendorf tube and immediately frozen in liquid nitrogen. Once all samples are collected, the frozen samples are thawed on ice and filtered through an Amicon ultra 3000 molecular weight cut-off centrifugal filter at 4 °C. Then, the filtrate is analyzed using a YSI 2900, where the sample is loaded into two wells of a 96-well plate, 200 μl media per well. The samples are then analyzed for lactate and glucose concentration.
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3[H]-2-deoxy-glucose uptake assay
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Cells are washed twice with PBS and placed into DMEM with 2 mg/ml BSA for 2 hours. Then, if cells are to be insulin stimulated, they are treated with 200 nM insulin for 30 min at 37 °C in freshly prepared transport solution (i.e., 137 mM NaCl, 1.2 mM MgSO4, 1.2 mM KH2PO4, 4.7 mM KCl, 2.5 mM CaCl2, and 20 mM Hepes with a pH of 7.3). The insulin solution is then removed, and the cells are washed twice with transport solution before radioactive transport solution is added, which consists of 0.25 μCi/well of 3[H]-2-deoxy-glucose and 0.025 mM 2-deoxy-glucose. After a 10 min incubation in the radioactive transport solution, it is removed, and the glucose uptake is halted by addition of ice-cold PBS. The cold PBS is removed, and each well is washed twice with PBS. Then, lysis buffer consisting of 0.1 M NaOH and 0.1% w/v sodium dodecyl sulfate is added to each well. The radioactive lysate was transferred to a scintillation vial containing 5 ml of Ultima Gold liquid scintillation fluid and analyzed using a liquid Scintillation counter.
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Palmitate tracer study
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MEF cells on day 8 of adipogenesis were incubated for 6 h in 100uM [U-13C16]Palmitate-containing media. The media contained 10% delipidated FBS and 5% (v/v) of an FFA-free BSA-conjugated [U-13C16]Palmitate stock. To make the stock, briefly, 100 mM [U-13C16]Palmitic acid was dissolved in ethanol at 50 °C. A solution of 4.4% essentially FA-free BSA (Sigma) in PBS was warmed to 37 °C. A 50:1 mixture BSA:Palmitate solution was made and incubated at 37 °C for 1 to 2 h before aliquoting and freezing in glass tubes. The stock contains a 3:1 FA:BSA ratio. After incubation, cells are lysed on ice and prepared for GC-MS analysis, as previously reported (41).
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3[H]-Palmitate uptake assay
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Cells are washed twice with PBS and placed into DMEM with 2 mg/ml BSA for 2 hours. During this time, 1[9,10-3H(N)]-palmitic acid (PerkinElmer) is complexed with FFA-free BSA at a molar ratio of 1:1 for 30 min. After the cells have been starved for 2 h, the cells washed twice with PBS and incubated in transport solution (137 mM NaCl, 1.2 mM MgSO4, 1.2 mM KH2PO4, 4.7 mM KCl, 2.5 mM CaCl2, and 20 mM Hepes with a pH of 7.3) with 1 μCi/well [9,10-3H(N)]-palmitic acid:FA-free BSA for 10 min. After a 10 min incubation in the radioactive transport solution, it is removed, and the glucose uptake is halted by addition of ice-cold PBS. The cold PBS is removed, and each well is washed twice with PBS. Then, lysis buffer consisting of 0.1 M NaOH and 0.1% w/v sodium dodecyl sulfate is added to each well. The radioactive lysate was transferred to a scintillation vial containing 5 ml of Ultima Gold liquid scintillation fluid and analyzed using a liquid Scintillation counter.
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+
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| 173 |
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Insulin stimulation
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| 174 |
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| 175 |
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MEFs differentiated to day 6 into adipocytes in a 24-well plate in the presence or absence of exogenous heparin (100 μg/ml), and on day 6, cells are washed with PBS and serum starved for 2 h in DMEM with 2 mg/ml BSA. After 2 h, each well is stimulated with insulin at a final concentration of 10 nM, with the insulin delivered directly to the serum-free media as a 10 μl aliquot. The plate is then placed into an incubator at 37 °C for the indicated amount of time. After stimulation, the entire 24-well plate is placed on ice, and the wells are washed with ice-cold PBS twice. Then, 100 μl RIPA buffer with protease inhibitor and phosphostop is added to each well. The cell lysate is collected into an Eppendorf, placed on ice for 30 min, and then centrifuged at 14,000g at 4 °C for 15 min. The supernatant is then transferred to a fresh tube, and protein concentration is determined using a BCA assay.
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| 177 |
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Determination of Wnt binding to HS-mimetics via ELISA
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| 179 |
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Wnt5a and Wnt10b proteins (10 nM solution in 1% (w/v) BSA/DPBS) were immobilized on 96-well tissue culture–treated plates overnight at 4 °C. The plates were washed twice with 0.05% (v/v) Tween-20 in DPBS and blocked with 1% (w/v) BSA/DPBS for 6 h at room temperature. Biotinylated HS-mimetic glycopolymers (GPs) or heparin were added to the wells at increasing concentrations in 1% (w/v) BSA/DPBS. After 1 h incubation, the wells were washed three times with 0.05% Tween-20 in DPBS. Streptavidin-HRP (1:1000 in 1% BSA/DPBS) was added for 45 min at ambient temperature. The wells were again washed three times in 0.05% Tween-20 in DPBS, followed by treatment with 100 μl of TMB substrate for 2 to 5 min before quenching with 100 μl of 2N sulfuric acid. Absorbance (450 nm) was measured using a Molecular Devices SpectraMax plate reader.
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| 181 |
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Synthesis and characterization of GPs
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| 182 |
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The GPs prepared by Naticchia et al. (37) were used in the current study (Figs. S8–S10). Protected poly(acrylamide) backbone P terminated with DPPE-lipid and a sulfhydryl group (Figs. S8 and S9) (Mn= 41,562 g/mol, Mw= 53,061 g/mol, DP= 160, and Đ= 1.28) was used as the precursor for GP assembly. HS-mimetic GPs were generated from precursor P in a one pot synthesis through sequential chain-end labeling with AF488-maleimide reporter, side chain deprotection, and glycan ligation. The efficiency (%) of polymer chain labeling with AF488 and side-chain modification with glycans for each GP were determined by UV-Vis and 1H NMR analysis (Fig. S10).
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| 185 |
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MEF surface remodeling with membrane-targeting HS-mimetics
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| 187 |
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MEFs were cultured in 12-well plates until confluent. The cells were washed with DPBS and incubated with 200 μl solution of serum-free media (DMEM) with or without the HS-mimetic GPs at indicated concentrations for 1 h at 37 °C. After this time, the cells were washed with DPBS and dissociated from the plate using 0.25% trypsin. HS-mimetic membrane incorporation was analyzed by flow cytometry on a BD FACS Calibur instrument, with a minimum of 10,000 events collected per condition. Data were analyzed using FlowJo software, and samples were gated to a polymer untreated control.
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| 189 |
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Adipogenic differentiation of HS mimetic-engineered MEFs
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| 191 |
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Cells were differentiated for 6 days using the standard adipogenic differentiation protocol described above. Each day on days 0 to 3, the cells were washed with PBS and incubated with 200 μl solution of DMEM containing GPs at the indicated concentrations added for 1 h at 37 °C. After this time, the media were removed, the cells were washed with PBS, and fresh differentiation media (0.1 μM dexamethasone, 450 μM 3-isobutyl-1-methylxanthine, 2 μM insulin, and 1 μM rosiglitazone in DMEM supplemented with 10% FBS) were added. On day 6, the adipocytes were subjected to the 3[H]-2-deoxy-glucose uptake assay, and the spent media were analyzed for glucose and lactate content as described above.
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Statistical analysis
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If not otherwise stated, results are mean values ± SEM of at least three independent experiments or results show one representative experiment out of three. Statistical analysis was done on all available data. Statistical significance was determined using the 2-tailed student’s t test, one-way ANOVA followed by a Bonferroni post hoc test or two-way ANOVA to compare time courses. For statistical analysis, GraphPad prism 7 software was used. ∗ (p < 0.05), ∗∗ (p < 0.01), ∗∗∗ (p < 0.001).
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Data availability
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The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Supporting information
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This article contains supporting information.
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Conflict of interest
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P. L. S. M. G is a co-founder of Covicept Therapeutics. P. L. S. M. G and The Regents of the University of California have licensed a university invention to and have an equity interest in Covicept Therapeutics. The terms of this arrangement have been reviewed and approved by the University of California, San Diego, in accordance with its conflict-of-interest policies.
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Supporting information
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Supporting information
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Acknowledgments
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We like to thank Kristen Jepsen of the Institute for Genomic Medicine for performing RNA sequencing. RNA sequencing was conducted at the IGM Genomics Center, University of California, San Diego, La Jolla, CA (MCC grant # P30CA023100).
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Author contributions
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G. W. T., A. R. P., K. G., N. D., K. W., A. R. M., C. M. M., and P. L. S. M. G. conceptualization; G. W. T., A. R. P., S. C. P., C. R. G., K. W., A. R. M., C. M. M., K. G., N. D., and P. L. S. M. G. methodology; G. W. T., A. R. P., S. C. P., C. R. G., K. W., A. R. M., C. M. M., K. G., N. D., D. R. S., and P. L. S. M. G. investigation. K. W. and C. M. M. resources; G. W. T., A. R. P., S. C. P., C. R. G., N. D., K. W., A. R. M., C. M. M., K. G., D. R. S., and P. L. S. M. G. formal analysis; G. W. T., K. G., C. M. M., and P. L. S. M. G., writing-original draft; A. R. M., G. W. T., A. R. P., S. C. P., D. R. S., C. R. G., N. D., K. W., C. M. M., K. G., and P. L. S. M. G. data curation; G. W. T., K. G., and P. L. S. M. G. visualization; A. R. P., S. C. P., C. R. G., K. W., and A. R. M. writing-review and editing. A. R. M., C. M. M., K. G., and P. L. S. M. G. supervision; C. M. M., K. G., and P. L. S. M. G. funding acquisition.
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Funding and additional information
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This work was supported by Foundation Leducq 16CVD01 (to P. L. S. M. G), a UCSD Innovation Grant 13991 (to P. L. S. M. G.), the National Institutes of Health (NIH) grant from NIDDK P30 DK063491 (to P. L. S. M. G. and A. R. M.), an Erwin-Schrödinger FWF Grant J4031-B21 (A. R. P.), an NIH grant from NCI R01CA234245 (to C. M. M.), an NIH Director’s New Innovator Award NICHD 1DP2HD087954 to 01 (to K. G)., the Alfred P. Sloan Foundation FG-2017 to 9094 (to K. G)., and the Research Corporation for Science Advancement via the Cottrell Scholar Award grant # 24119 (to K. G). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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==== Refs
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21 Xu D. Esko J.D. Demystifying heparan sulfate-protein interactions Annu. Rev. Biochem. 83 2014 129 157 24606135
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22 Gordts P. Esko J.D. The heparan sulfate proteoglycan grip on hyperlipidemia and atherosclerosis Matrix Biol. 71-72 2018 262 282 29803939
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23 MacArthur J.M. Bishop J.R. Stanford K.I. Wang L. Bensadoun A. Witztum J.L. Liver heparan sulfate proteoglycans mediate clearance of triglyceride-rich lipoproteins independently of LDL receptor family members J. Clin. Invest. 117 2007 153 164 17200715
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24 Stanford K.I. Bishop J.R. Foley E.M. Gonzales J.C. Niesman I.R. Witztum J.L. Syndecan-1 is the primary heparan sulfate proteoglycan mediating hepatic clearance of triglyceride-rich lipoproteins in mice J. Clin. Invest. 119 2009 3236 3245 19805913
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25 Sarrazin S. Lamanna W.C. Esko J.D. Heparan sulfate proteoglycans Cold Spring Harb. Perspect. Biol. 3 2011
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26 Purcell S.C. Godula K. Synthetic glycoscapes: addressing the structural and functional complexity of the glycocalyx Interf. Focus 9 2019 20180080
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27 Abramsson A. Kurup S. Busse M. Yamada S. Lindblom P. Schallmeiner E. Defective N-sulfation of heparan sulfate proteoglycans limits PDGF-BB binding and pericyte recruitment in vascular development Genes Dev. 21 2007 316 331 17289920
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28 Wilsie L.C. Chanchani S. Navaratna D. Orlando R.A. Cell surface heparan sulfate proteoglycans contribute to intracellular lipid accumulation in adipocytes Lipids Health Dis. 4 2005 2 15636641
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29 Kasza I. Suh Y. Wollny D. Clark R.J. Roopra A. Colman R.J. Syndecan-1 is required to maintain intradermal fat and prevent cold stress PLoS Genet. 10 2014 e1004514
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30 Anower E.K.F. Singh G. Deng Y. Gordts P. Esko J.D. Triglyceride-rich lipoprotein binding and uptake by heparan sulfate proteoglycan receptors in a CRISPR/Cas9 library of Hep3B mutants Glycobiology 29 2019 582 592 31094413
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31 Zhou Y. Zhou B. Pache L. Chang M. Khodabakhshi A.H. Tanaseichuk O. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets Nat. Commun. 10 2019 1523 30944313
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32 Willert K. Nusse R. Wnt proteins Cold Spring Harb. Perspect. Biol. 4 2012 a007864 22952392
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33 Mii Y. Takada S. Heparan sulfate proteoglycan clustering in Wnt signaling and dispersal Front Cell Dev. Biol. 8 2020 631 32760727
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34 Ai X. Do A.T. Lozynska O. Kusche-Gullberg M. Lindahl U. Emerson C.P. Jr. QSulf1 remodels the 6-O sulfation states of cell surface heparan sulfate proteoglycans to promote Wnt signaling J. Cell Biol. 162 2003 341 351 12860968
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35 Dani N. Nahm M. Lee S. Broadie K. A targeted glycan-related gene screen reveals heparan sulfate proteoglycan sulfation regulates WNT and BMP trans-synaptic signaling PLoS Genet. 8 2012 e1003031
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36 de Winter T.J.J. Nusse R. Running against the Wnt: how Wnt/beta-catenin suppresses adipogenesis Front. Cell Dev. Biol. 9 2021 627429
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37 Naticchia M.R. Laubach L.K. Honigfort D.J. Purcell S.C. Godula K. Spatially controlled glycocalyx engineering for growth factor patterning in embryoid bodies Biomater. Sci. 9 2021 1652 1659 33409513
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38 McGough I.J. Vecchia L. Bishop B. Malinauskas T. Beckett K. Joshi D. Glypicans shield the Wnt lipid moiety to enable signalling at a distance Nature 585 2020 85 90 32699409
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39 Gordts P.L. Esko J.D. Heparan sulfate proteoglycans fine-tune macrophage inflammation via IFN-beta Cytokine 72 2015 118 119 25573804
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40 Bengtsson-Olivecrona G. Olivecrona T. Phospholipase activity of milk lipoprotein lipase Met. Enzymol. 197 1991 345 356
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41 Wallace M. Green C.R. Roberts L.S. Lee Y.M. McCarville J.L. Sanchez-Gurmaches J. Enzyme promiscuity drives branched-chain fatty acid synthesis in adipose tissues Nat. Chem. Biol. 14 2018 1021 1031 30327559
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Front Oncol
|
| 4 |
+
Front Oncol
|
| 5 |
+
Front. Oncol.
|
| 6 |
+
Frontiers in Oncology
|
| 7 |
+
2234-943X
|
| 8 |
+
Frontiers Media S.A.
|
| 9 |
+
|
| 10 |
+
10.3389/fonc.2023.1063673
|
| 11 |
+
Oncology
|
| 12 |
+
Original Research
|
| 13 |
+
CD146+ mural cells from infantile hemangioma display proangiogenic ability and adipogenesis potential in vitro and in xenograft models
|
| 14 |
+
Chen Jialin †
|
| 15 |
+
|
| 16 |
+
Chen Qianyi †
|
| 17 |
+
Qiu Yajing †
|
| 18 |
+
Chang Lei
|
| 19 |
+
Yu Zhang
|
| 20 |
+
Li Yuanbo
|
| 21 |
+
Chang Shih-jen
|
| 22 |
+
Chen Zongan *
|
| 23 |
+
|
| 24 |
+
Lin Xiaoxi *
|
| 25 |
+
|
| 26 |
+
The Department of Plastic and Reconstructive Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
|
| 27 |
+
Edited by: Jae-Sung Kwon, Yonsei University, Republic of Korea
|
| 28 |
+
|
| 29 |
+
Reviewed by: Estelle Oberlin, INSERM U1197 Unité Mixte de Recherche Interactions Cellules Souches-Niches, France; Gianandrea Pasquinelli, University of Bologna, Italy; Alessandro Boscarelli, Institute for Maternal and Child Health Burlo Garofolo (IRCCS), Italy
|
| 30 |
+
|
| 31 |
+
*Correspondence: Zongan Chen, zongan.chen@foxmail.com; Xiaoxi Lin, linxiaoxi@126.com
|
| 32 |
+
†These authors have contributed equally to this work and share first authorship
|
| 33 |
+
|
| 34 |
+
27 4 2023
|
| 35 |
+
2023
|
| 36 |
+
13 106367307 10 2022
|
| 37 |
+
03 4 2023
|
| 38 |
+
Copyright © 2023 Chen, Chen, Qiu, Chang, Yu, Li, Chang, Chen and Lin
|
| 39 |
+
2023
|
| 40 |
+
Chen, Chen, Qiu, Chang, Yu, Li, Chang, Chen and Lin
|
| 41 |
+
https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
|
| 42 |
+
Objective
|
| 43 |
+
|
| 44 |
+
Infantile hemangioma (IH), the most common infantile vascular neoplasm, is uniquely characterized by rapid proliferation followed by slow spontaneous involution lasting for years. In IH lesions, perivascular cells are the most dynamic cell subset during the transition from the proliferation phase to the involution phase, and we aimed to systematically study this kind of cell.
|
| 45 |
+
|
| 46 |
+
Methods and results
|
| 47 |
+
|
| 48 |
+
CD146-selective microbeads were used to isolate IH-derived mural-like cells (HemMCs). Mesenchymal markers of HemMCs were detected by flow cytometry, and the multilineage differentiation potential of HemMCs was detected by specific staining after conditioned culture. CD146-selected nonendothelial cells from IH samples showed characteristics of mesenchymal stem cells with distinct angiogenesis-promoting effects detected by transcriptome sequencing. HemMCs spontaneously differentiated into adipocytes 2 weeks after implantation into immunodeficient mice, and almost all HemMCs had differentiated into adipocytes within 4 weeks. HemMCs could not be induced to differentiate into endothelial cells in vitro. However, 2 weeks after implantation in vivo, HemMCs in combination with human umbilical vein endothelial cells (HUVECs) formed GLUT1+ IH-like blood vessels, which spontaneously involuted into adipose tissue 4 weeks after implantation.
|
| 49 |
+
|
| 50 |
+
Conclusions
|
| 51 |
+
|
| 52 |
+
In conclusion, we identified a specific cell subset that not only showed behavior consistent with the evolution of IH but also recapitulated the unique course of IH. Thus, we speculate that proangiogenic HemMCs may be a potential target for the construction of hemangioma animal models and the study of IH pathogenesis.
|
| 53 |
+
|
| 54 |
+
infantile hemangioma
|
| 55 |
+
mural cell
|
| 56 |
+
CD146
|
| 57 |
+
xenograft model
|
| 58 |
+
angiogeneis
|
| 59 |
+
adipogenensis
|
| 60 |
+
National Natural Science Foundation of China 10.13039/501100001809 81971847, 82272288, 82203895 Science and Technology Commission of Shanghai Municipality 10.13039/501100003399 22YF1421800 This work was supported by the National Natural Science Foundation of China (81971847, 82272288, 82203895) and the Yangfan Project of Science and Technology Commission of Shanghai Municipality (22YF1421800). The funding organizations had no role in the design or conduct of this research. section-at-acceptancePediatric Oncology
|
| 61 |
+
==== Body
|
| 62 |
+
pmc1 Introduction
|
| 63 |
+
|
| 64 |
+
Infantile hemangioma (IH) is the most common infantile vascular neoplasm, with a prevalence of 3%–10% in neonates (1). The disease is characterized by rapid proliferation in the first few weeks of life followed by slow spontaneous involution lasting for years. Growth is usually rapid during the first 6 months of the proliferative phase, especially within 3 months. The growth phase may extend until the 6th to 9th month at low speed. The involuting phase begins at approximately 1 year of age and continues for 3–7 years (1, 2). Six months to 1 year old were considered stable stage or late proliferation. Although oral propranolol has been proven clinically effective in treating infantile hemangioma, the mechanism of rapid angiogenesis initiation and spontaneous involution remains largely unknown (3, 4).
|
| 65 |
+
|
| 66 |
+
The progression of infantile hemangioma involves various cells, including hemangioma-derived mesenchymal stem cells (HemMSCs), stem cells (expressing CD133, HemSCs), endothelial cells (expressing CD31, HemECs), pericytes and vascular smooth muscle cells (VSMCs) (5–8). CD133-selected HemSCs are considered the cellular origin of infantile hemangioma, exhibiting a special phenotype similar to that of mesenchymal stem cells (MSCs) and the potential for de novo formation of blood vessels (7, 9). Recent studies have indicated that hemangioma pericytes, similar to HemSCs, have MSC-like features and may be an important source of fibrofatty tissue during involution (10). Mural cells, comprising pericytes and VSMCs, are perivascular cells embracing endothelial cells (11, 12)and have been recognized as a specific cell cluster of MSCs (13). In preliminary results from our research group, through single-cell RNA sequencing (scRNA-seq), we found that the most variable cell population during the transition from the proliferation phase to the involution phase was hemangioma mural cells (HemMCs). We also identified that cluster of differentiation 146 (CD146) can serve as a cell marker to distinguish HemMCs. Perivascular cells of proliferating IH tissue have been stained positive for neural glial antigen-2 (NG2), platelet-derived growth factor receptor-(PDGFR)-β, calponin I, α-smooth muscle actin (αSMA) and smooth muscle myosin heavy chain (smMHC) (5). Neither marker is specific to perivascular cells: PDGFRβ is expressed by fibroblasts, αSMA is expressed by myofibroblasts, and NG2 is expressed by oligodendrocyte progenitor cells (14).
|
| 67 |
+
|
| 68 |
+
CD146, also known as melanoma cell adhesion molecule (MCAM), is a transmembrane glycoprotein that acts not only as an adhesion molecule but also as a cellular surface receptor of miscellaneous ligands (15). CD146 is highly expressed in embryonic tissues but weakly expressed in normal adult tissues, and its expression is frequently increased in rapidly proliferating cells (16). Despite its role as an adhesion molecule, CD146 can act as a coreceptor for vascular endothelial growth factor receptor 2 (VEGFR2) to participate in angiogenesis and a receptor for growth factors to participate in cell growth, proliferation, differentiation, and survival (15). In adult human tissues, CD146 is expressed in mural cells of blood microvessels and is considered a pericyte marker (17). In a previous study, strong expression of CD146 was observed in pericyte-like cells residing in hemangiomas (18). Anti-CD146 antibody-conjugated microbeads were previously used to isolate this kind of cell (19), but their function remained unknown. Thus, we aimed to investigate the phenotype and function of hemangioma-derived CD146+ mural cells and their role in hemangiomas.
|
| 69 |
+
|
| 70 |
+
In this study, we isolated CD31-CD146+ HemMCs from proliferative IH specimens using antibody-conjugated microbead kits and investigated the phenotype and function of the cells in vitro and in vivo to explore their role in the proliferation and involution of IH and to establish a new experimental model for studying IH.
|
| 71 |
+
|
| 72 |
+
2 Materials and methods
|
| 73 |
+
|
| 74 |
+
2.1 Cell isolation and culture
|
| 75 |
+
|
| 76 |
+
All cells were isolated from three proliferative hemangiomas from three patients less than 6 months old. IH samples were placed in 50-mL sterile tubes containing phosphate-buffered saline immediately after excision and stored at 4°C. Cell suspensions were obtained by incubating minced specimens in endothelial cell growth medium 2 (EGM-2, PromoCell) supplemented with 2 mg/ml collagenase (Sigma Aldrich), 0.02 mg/ml DNase (Sigma Aldrich), 10% fetal bovine serum (Thermo Fisher Scientific) and 1% penicillin–streptomycin. HemSCs and HemECs were separated by magnetic activated cell sorting (MACS) using a CD133 MicroBead Kit (Miltenyi Biotec) and CD31 MicroBead Kit (Miltenyi Biotec), respectively, from a single-cell suspension as previously described (7, 20). Next, HemMCs were separated by CD146-positive selection from CD133-CD31- cells using a CD146 MicroBead Kit (Miltenyi Biotec). After separation, HemMCs were cultured in StemPro™ MSC serum-free medium (Thermo Fisher Scientific), and HemSCs were cultured in EGM-2 supplemented with Growth Medium 2 Supplement Mix (PromoCell) and 10% fetal bovine serum. For transcriptional analysis, HemMCs were transferred to complete EGM-2 for 3 days to minimize the influence of the medium. HUVECs were purchased from Promocell and cultured in EGM-2 supplemented with Growth Medium 2 Supplement Mix (PromoCell). All kinds of cells at passages 3–7 were used in the following experiments, including in vivo studies.
|
| 77 |
+
|
| 78 |
+
For mesenchymal differentiation, cells were cultured in adipogenic medium, osteogenic medium and chondrogenic medium (STEMCELL Technologies), and human adipose-derived stem cells (ADSCs), which were isolated and expanded following previously reported protocols (21), were used as a positive control in this study. Endothelial cell differentiation and neurogenic differentiation were induced according to a previous report (7).
|
| 79 |
+
|
| 80 |
+
To fluorescently label cells, the vector LV051-PHBLV-U6-MCS-EF1-mcherry-T2A-PURO containing the mCherry-encoding sequence was purchased from HanBio Technology. When the culture reached approximately 60% confluence, the HemMCs were infected with Lentivirus carrying the aforementioned vector (multiplicity of infection=10) for 24 hours. Next, the cells were cultured in the complete medium for 3 days. To obtain stable fluorescence-labeled cells, the cells were then screened using puromycin (at the concentration of 2.0 ug/mL for 2 days) and examined by fluorescence microscope (Nikon ECLIPSE microscope).
|
| 81 |
+
|
| 82 |
+
2.2 Flow cytometry analysis
|
| 83 |
+
|
| 84 |
+
When cell confluence reached 80%-90%, the HemMCs were dissociated using TrypLE™ Express Enzyme (Gibco) and suspended in Cell Staining Buffer (Biolegend). In this study, each test contained 5×105 cells in 100 µL staining buffer. To reduce nonspecific Fc receptor (FcR)-mediated binding, 5 µL FcR blocking solution (Biolegend) was applied per test (10 min incubation at room temperature). The fluorescence dye-conjugated primary antibodies (listed in Supplementary Table 2 ) were applied at recommended concentration indicated in the manufacturer’s instruction. After 30 min incubation at 4°C in the dark, the cells were washed using staining buffer (2 mL per test) for 2 times and then suspended in 200 µL staining buffer. The samples were immediately analyzed by the LSRFortessa flow cytometer (BD Biosciences) or CytoFLEX LX flow cytometer (Beckman Coulter) and FlowJo software (BD Biosciences).
|
| 85 |
+
|
| 86 |
+
2.3 RNA isolation and transcriptome sequencing
|
| 87 |
+
|
| 88 |
+
Total RNA was isolated from HemMCs and HemSCs using TRIzol and the RNA Nano 6000 Assay Kit with the Bioanalyzer 2100 system. After cDNA library preparation, clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumina). The library preparations were sequenced on the Illumina NovaSeq platform, and 150 bp paired-end reads were generated (Novogene Experimental Department). Hisat2 v2.0.5 was used for mapping. Feature Counts v1.5.0-p3 was used to count the read numbers mapped to each gene. Then, the FPKM of each gene was calculated based on the length of the gene and read count mapped to this gene. Differential expression analysis between two conditions/groups (three biological replicates per condition) was performed using the DESeq2 R package (1.20.0). The resulting P values were adjusted using Benjamini and Hochberg’s approach for controlling the false discovery rate. For differential expression analysis of two groups, genes with an adjusted P value <0.05 according to DESeq2 were considered differentially expressed. The data generated in this study has been deposited in NCBI’s Gene Expression Omnibus and is accessible through GEO Series accession number GSE216867.
|
| 89 |
+
|
| 90 |
+
2.4 Xenograft model of IH
|
| 91 |
+
|
| 92 |
+
The murine model of IH was established according to an adapted protocol of Boscolo et al (10). We used female BALB/c nude mice in this study. A total of 1×106 cells (per implant), which were HemMCs or HUVECs alone or the mixture of them at a 1:1 ratio, were suspended in 100 µL medium, mixed thoroughly with 100 µL Matrigel (Corning). Then, the cell/Matrigel mixture (200 µL per implant) was injected subcutaneously onto the back of mice aged 3 weeks (n = 6/group). At 1, 2, 4 and 8 weeks after the injection, the animals were sacrificed, and Matrigel plugs were harvested. The implants were fixed overnight in 4% paraformaldehyde at 4°C, and then paraffin-embedded and sectioned.
|
| 93 |
+
|
| 94 |
+
2.5 Immunohistochemical and immunofluorescence analysis
|
| 95 |
+
|
| 96 |
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The sections of eighteen paraffin-embedded IH samples were obtained from the Pathology Department of Shanghai Ninth People’s Hospital. These samples were from the patients who were assessed for the necessity of operation (2) and collected via surgical treatment in the last ten years at Shanghai Ninth People’s Hospital. Most of the lesions were located in the head or face, and it was difficult to achieve a satisfactory outcome after drug treatment or natural involution. Detailed patient information is listed in Supplementary Table S1 . The IH sample or Matrigel xenograft explant sections were deparaffinized by xylene and then hydrated in a series of graded alcohol solutions. Antigen retrieval was performed, using the PH 9.0 antigen retrieval buffer (GeneTech), by heating in a water bath at 60°C for 20 min. The sections were permeabilized in 0.1% Triton X-100 (dissolved in phosphate buffered saline (PBS)) for 5 min after they cooled down to room temperature. Next, the sections were blocked in 5% donkey serum (dissolved in PBS) at room temperature for 1 h and then incubated overnight with primary antibodies (details in Supplementary Table 2 ) at 4°C. The antibodies were applied at recommended concentration indicated in the manufacturer’s instructions. Next, the sections were washed with PBS-Tween 20 (PBST) for 3 times. For immunohistochemistry, the detection of the antigens and counterstaining of the nuclei was performed using a REAL EnVision Detection Kit (DAKO) according to the manufacturer’s instructions. Images of the processed sections were taken with a Nikon ECLIPSE microscope. For Immunofluorescence, the sections were incubated with fluorescein-conjugated secondary antibodies (details in Supplementary Table 2 ) for 1 h at room temperature and then mounted in DAPI containing mounting medium (SouthernBiotech). Immunofluorescence (IF) images were taken with a Leica TCS SP2 Acousto-Optical Beam Splitter confocal system.Immunostaining with each antibody was carried out on at least 3 samples from different patients, and representative images are presented.
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2.6 Statistical analysis
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Statistical significance was determined using GraphPad Prism 6 (GraphPad Software, La Jolla, CA, USA). The data were analyzed by ANOVA or Student’s t test, and differences were deemed significant at P<0.05.
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2.7 Study approval
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IH specimens were collected from the Department of Plastic and Reconstructive Surgery of Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University of Medicine. A diagnosis of IH was confirmed by experienced clinicians and pathologists. Written informed consent for use of the specimens was obtained before surgery. All experiments were performed according to protocols reviewed and approved by the Ethics Committee of Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University of Medicine.
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3 Results
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3.1 CD146+ cells are enriched in proliferative IH specimens
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CD146 expression was measured in specimens from patients with all stages of IH. CD146 expression was mainly located in perivascular cells surrounding CD31+ endothelial cells in hemangioma specimens of different phases ( Figure 1A ). In addition, CD146 is expressed in some of the CD31+ HemECs in proliferative IH ( Figure 1A ). Many CD146+ cells were costained with Ki67+ ( Figure 1B ). The number of CD146+Ki67+ cells was significantly higher in proliferating IH tissues than in involuting IH tissues ( Figure 1C ). The expression of CD146 mostly overlapped with that of PDGFRβ in proliferative hemangioma ( Supplementary Figure 1A ). However, PDGFRβ was also positively expressed in CD31-CD146- cells embracing CD146+ HemMCs, which were probably telocytes (19) or fibroblasts. PDGFRβ was not expressed in HemMCs in involuting hemangioma ( Supplementary Figure 1A ). Moreover, glucose transporter 1 (GLUT1)-positive HemECs were surrounded by CD146+ cells in both the proliferative and involuting phases ( Supplementary Figure 1B ). These results indicated that CD146 was more suitable as a marker to distinguish mural cells of IHs in different phases.
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Figure 1 CD146+ cells are enriched in proliferative IH specimens. (A) Representative images of IH specimens stained for CD146 (green) and CD31 (magenta). A representative proliferative IH specimen was collected from a 2-month-old patient with rapid growth hemangioma. White arrows indicate the CD31+ HemECs with CD146 expression. A representative stable IH specimen was collected from an 8-month-old patient with a stable hemangioma. A representative involuting IH specimen was collected from a 3-year-old patient with involuted hemangioma. The results were confirmed in 18 patients. Short scale bars=50 μm; long scale bars=100 μm. (B) Representative images of proliferative and involuting IH tissue stained for Ki67 (red), CD146 (green), and CD31 (yellow). (C) Quantification of Ki67+ and CD146+Ki67+ cells in proliferating and involuting IH tissue and proportions of CD146+Ki67+ cells and CD146-Ki67+ cells in total cells. Scale bars=50 μm. All nuclei were counterstained DAPI (blue). Data are expressed as the mean ± SDM. **, p <0.01. IH, infantile hemangioma.
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3.2 CD146+ HemMCs in combination with HemECs survived and proliferated in a xenograft model.
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HemMCs and HemECs were isolated from proliferating hemangioma tissues through MACS and cultured. To assess whether both HemMCs and HemECs survive and proliferate in a xenograft model, a mixture of Matrigel and the two kinds of cells, i.e., HemMCs and HemECs, were injected into immunodeficient nude mice. At 1 week, both CD31+ cells and CD146+ cells were found in the implants by immunostaining ( Figure 2 ). At 2 weeks, the density of both became higher ( Figure 2 ). Staining of a proliferative IH section was used as a positive control.
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Figure 2 HemMCs and HemECs survive and proliferate in a xenograft model. A mixture of HemECs and HemMCs in Matrigel was injected into nude mice. Explants were harvested at 1 and 2 weeks and then subjected to immunostaining of CD146 and CD31. Scale bars=50 μm. All nuclei were counterstained DAPI (blue). HemMCs, infantile hemangioma mural cells; HemECs, infantile hemangioma endothelial cells.
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3.3 CD146+ HemMCs express mesenchymal markers and display multilineage differentiation potential
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To further analyze the phenotypes of HemMCs, flow cytometry was performed to assess the expression of stem cell surface markers. Similar to HemSCs, HemMCs expressed the mesenchymal stem cell surface markers CD73, CD90 and CD105 but did not express CD14, CD34 or CD45 ( Figure 3A ). After culture, the percentage of CD146+ cells in HemMCs was maintained at 87.9%, while the percentage of CD146+ cells in HemSCs was 8.48%, both counted by flow cytometry (FCM). These results indicated that CD146 was suitable as a marker to distinguish cultured HemMCs. Most HemMCs (97.5%) expressed CD140b (PDGFRβ), which was consistent with our previous results indicating that CD146+ cells were localized to the perivasculature ( Figure 3A ). Then, to determine the mesenchymal stem cell differentiation potential of these cells, we cultured HemMCs in conditioned medium and compared them with HemSCs. ADSCs, which are known to have the potential for adipogenesis, osteogenesis and chondrogenesis, were cultured in the same conditioned medium as the positive control. Similar to HemSCs and ADSCs, HemMCs displayed the potential to differentiate into adipocytes, osteocytes, and chondrocytes in vitro ( Figure 3B ). HemMCs expressed the neural markers glial fibrillar acidic protein (GFAP) and β-tubulin III after conditioned induction ( Figures 3C, D ). Regarding endothelial differentiation, unlike HemSCs, HemMCs failed to express the EC markers CD31 and vascular endothelial cadherin (VE-cadherin) in the same endothelial differentiation medium.
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Figure 3 HemMCs express MSC markers and display multilineage differentiation potential. (A) Flow cytometric analysis of MSC marker expression in HemMCs and HemSCs. The dark gray histograms show cells labeled with fluorescein-conjugated antibodies. The light gray histograms show the negative control. The percentage of positive cells relative to total cells is shown. (B) In vitro differentiation of HemMCs into oil red O-stained adipocytes, alizarin red S-stained osteocytes and alcian blue-stained chondrocytes compared with HemSCs. ADSCs were also cultured in the same medium as a positive control. Scale bars=200 μm. (C) In vitro differentiation of HemMCs into CD31 (red)- or VE-cadherin (green)-positive endothelial cells. Black scale bars=200 μm. White scale bars=100 μm. (D) In vitro differentiation of HemMCs into GFAP (red)- or β-tubulin III (red)-positive neuroglial cells. Black scale bars=200 μm. White scale bars=100 μm. HemMCs, infantile hemangioma mural cells; MSC, mesenchymal stem cell; HemSCs, infantile hemangioma stem cells; ADSCs, adipose-derived stem cells; VE-cadherin, vascular endothelial cadherin; GFAP, glial fibrillar acidic protein.
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3.4 CD146+ HemMCs form adipose tissue in vivo
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To further evaluate differentiation potential in vivo, HemMCs were mixed with Matrigel and injected subcutaneously into nude mice. Two weeks or four weeks after injection, the HemMC/Matrigel implants were harvested, sectioned, and stained. Similar to the involuting infantile hemangiomas shown, hematoxylin and eosin (H&E) staining revealed that a portion of the explants formed adipose tissue at 2 weeks. At 4 weeks, many of the explants had turned into fat tissue ( Figure 4A ). IHC staining for human leukocyte antigen-ABC (HLA-ABC) or human nuclei antigen (HNA) indicated that these adipocytes were of a human source ( Figure 4A ). Moreover, mCherry-labeled HemMC/Matrigel explants were stained for perilipin-A, and the results showed that these cells were perilipin-A+ adipocytes derived from human cells ( Figure 4B ).
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Figure 4 HemMCs form adipocytes in vivo. HemMCs or mCherry-labeled HemMCs were mixed with Matrigel and injected into nude mice. (A) HemMC/Matrigel implants were harvested at 2 and 4 weeks and then subjected to H&E staining or IHC staining of HLA-ABC and HNA. Scale bars=50 μm. (B) mCherry-labeled HemMC/Matrigel implants were harvested at 4 weeks and then subjected to immunofluorescence staining for mCherry (green) and perilipin-A (red). Short scale bars=50 μm; long scale bars=100 μm. Red arrows indicate representative HNA-positive nuclei. Black arrows indicate representative HNA-negative nuclei; * indicates representative mCherry-negative adipocytes. HemMCs, infantile hemangioma mural cells; H&E, hematoxylin and eosin; IHC, immunohistochemistry; HLA-ABC, human leukocyte antigen-ABC. HNA, human nuclei antigen.
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3.5 CD146+ HemMCs exhibit a proangiogenic transcriptome and function
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To identify the molecular signature of CD146+ HemMCs and their different role in IH from HemSCs, we performed RNA sequencing (RNA-seq) and compared the transcriptome between in vitro cultured HemMCs and HemSCs. A total of 216 differentially expressed genes, including 131 upregulated genes and 85 downregulated genes, were found between HemMCs and HemSCs ( Figure 5A ). Three biological replicates from each group were subjected to clustered analysis. Gene Ontology (GO) enrichment analysis showed that the upregulated genes in HemMCs were involved in the extracellular matrix and angiogenesis ( Figure 5B ), which implied that HemMCs exhibited a pro-angiogenesis-associated transcriptome.
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Figure 5 HemMCs display pro-angiogenesis capacity. (A) Heatmap showing the transcriptional expression profiles of HemMCs and HemSCs. (B) GO enrichment analysis of the differentially expressed genes (the upregulated ones in HemMCs). (C) Representative images of tube formation on Matrigel in vitro by HUVECs cultured alone, cocultured with HemSCs, or cocultured with HemMCs. Scale bars=50 μm. (D) Semiquantitative analysis of the tube length and number of branch points of HUVEC tubes. ImageJ and GraphPad Prism software were used for analysis. *, p <0.05; **, p <0.01; ns, p>0.05. HemMCs, infantile hemangioma mural cells; HemSCs, infantile hemangioma stem cells; GO, gene ontology; HUVECs, human umbilical vein endothelial cells.
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To confirm the proangiogenic function of HemMCs, HUVECs were seeded on Matrigel to induce tube formation, cultured independently or cocultured with HemMCs or HemSCs. The results showed that the tube length and number of branch points of HUVEC tubes were increased in the HemMC coculture group compared with the HUVEC alone group or HemSC coculture group ( Figures 5C, D ). In addition, significantly enriched GO terms, including growth factor activity (GO: 0008083) and enhancer binding (GO: 0035326), may partly account for the proangiogenic function of HemMCs ( Supplementary Figure 2A, B ).
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3.6 CD146+ HemMCs in combination with HUVECs form GLUT1+ blood vessels in vivo
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To assess the proangiogenic function of HemMCs in vivo, a mixture of Matrigel and two kinds of cells, i.e., HemMCs and HUVECs, were injected into immunodeficient nude mice. At 2 weeks, a considerable number of newly formed small vessels with blood cells were observed in the implants, and HLA-ABC and HNA immunostaining confirmed that these vessels were of human origin ( Figure 6A ). Immunofluorescence staining indicated that the vessels consisted of VE-Cahderin+GLUT1+ endothelial cells surrounded by mCherry-labeled HemMCs ( Figure 6B ). At 4 weeks, the number of vessels was significantly decreased ( Figure 6C ), while the number of mCherry+Perilipin-A+ adipocytes in the implants was increased ( Figure 6D ).
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Figure 6 Combined injection of HemMCs and HUVECs leads to the formation of GLUT1+ vessels in vivo. (A) A mixture of HUVECs and HemMCs in Matrigel was injected into nude mice. Explants were harvested at 2 and 4 weeks and then subjected to H&E staining and IHC staining of HLA-ABC and HNA. Scale bars=50 μm. (B-D) A mixture of HUVECs and mCherry-labeled HemMCs in Matrigel was injected into nude mice. Short scale bars=50 μm; long scale bars=100 μm. (B) Explants were harvested at 2 weeks and then subjected to immunostaining for VE-cadherin (green), GLUT1 (red) and mCherry (magenta). (C) Explants were harvested at 4 weeks and then subjected to immunostaining for VE-cadherin (green), GLUT1 (red) and mCherry (magenta). (D) Explants were harvested at 4 weeks and then subjected to immunostaining for Perilipin-A (red) and mCherry (green). HemMCs, infantile hemangioma mural cells; HUVECs, human umbilical vein endothelial cells; GLUT1, glucose transporter 1; H&E, hematoxylin and eosin; IHC, immunohistochemistry; HLA-ABC, human leukocyte antigen-ABC. HNA, human nuclei antigen; VE-cadherin, vascular endothelial cadherin.
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4 Discussion
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In a previous study, it was found that pericytes and perivascular cells in IH lesions cannot be identified with a single pericyte marker; instead, extended characterization of 8 pericyte/smooth muscle cell markers and perivascular localization are needed to elucidate the specific phenotype of pericytes in IH lesions (10). However, hemangioma pericytes were previously isolated by a rough method, and proper markers for isolating perivascular cells have not been tested (5, 10); thus, other kinds of cells can also be present in adherent cultures. For example, fibroblasts share similar markers, including PDGFRβ, with pericytes, are also abundant in IH lesions and skin and easily adhere to uncoated culture dishes. In this study, we used anti-CD146 antibody-conjugated microbeads to isolate and concentrate CD31-CD146+ HemMCs from IH specimens for culture and further experiments. HemMCs exhibit phenotypic and functional characteristics of pericytes in IH tissues. Complementing the previous belief that endothelial cells derived from HemSCs are the main tumoral cells of hemangiomas (7), perivascular HemMCs also account for the majority of parenchymal cells in IH lesions. The number and proportion of HemMCs increase rapidly during the proliferation phase and gradually decrease in the involuting phase of IH.
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Our study shows that HemMCs display mesenchymal stem cell-like properties, specifically multilineage differentiation potential, especially the ability to differentiate into adipocytes. Furthermore, we found that HemMCs spontaneously differentiated into adipocytes after subcutaneous implantation in combination with Matrigel into immunodeficient mice. This adipogenic feature of HemMCs is similar to that of HemSCs and GLUT1+ endothelial cells (20), relating to adipogenesis in the involuting process of IH. A previous study suggested that peroxisome proliferator activated receptor gamma (PPAR-γ), which is a key transcription factor in adipogenesis, is mainly expressed in perivascular cells and in a few endothelial cells in IH (22). These findings indicate that targeting the phenotype and functional transition of HemMCs probably plays an important role in accelerating involution in IH.
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Rapid proliferation of IH is the result of dysregulation of both vasculogenesis and angiogenesis (1). HemSCs, which appear to be progenitor cells of IH, form functional blood vessels by differentiation into both ECs and pericytes, which is induced by angiogenic factors, such as vascular endothelial growth factor (VEGF) (23). This process is called vasculogenesis. The proliferation of endothelial cell and mural cells accounts for angiogenesis. Unlike retinal pericytes, Hem-pericytes can accelerate endothelial colony forming cell (ECFC) proliferation, migration, and VEGF-A secretion (10). We speculated that CD146-selective HemMCs play an important proangiogenic role in the growth phase of IH. Our study revealed that proangiogenic molecular pathways are enhanced in HemMCs and that HemMCs increase tube formation by HUVECs in vitro. Moreover, we found that HemMCs in combination with HUVECs can form VE-cadherin+ GLUT1+ microvessels, followed by Perilipin-A+ adipocytes in vivo, simulating the progression of IH. GLUT1 is expressed along the endothelium of hemangiomas in the proliferating and involuting phases. Immunostaining for GLUT1 can be used to distinguish IH lesions from other vascular tumors and vascular malformations (24, 25). In our murine xenograft model, the expression of GLUT1 in endothelial cells could be conditionally induced by HemMCs.
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Implantation of HemSCs combined with Matrigel into immunodeficient mice is the most widely used method for studying HemSC-derived vasculogenesis in IH (7, 26, 27). VEGFR-1 mediates HemSC-to-EC differentiation in vitro and vessel formation in a HemSC/Matrigel xenograft model (23). However, Greenberger et al. proposed that this model is unstable and added endothelial cells such as HUVECs and cord blood endothelial progenitor cells (cbEPCs) (28–30). In addition, Boscolo et al. found that HemSCs can be induced to differentiate into pericytes by cbEPCs via JAGGED1 signaling regulation in this model (5).
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Hem-pericytes cooperate with ECFCs to form CD31+ blood vessels when both are implanted into immunodeficient mice (10). Because GLUT1-positive HemECs are known to have the potential to differentiate into pericytes/smooth muscle cells (20), HUVECs were used in this study to identify the proangiogenic function of HemMCs. In this study, the CD146-selective HemMC/EC/Matrigel xenograft model represented pathological GLUT1+VE-cadherin+ microvessels surrounded by HemMCs, serving as a stable model for IH. In brief, the method used to establish this model is simple and standardized, as isolation of HemMCs with CD146-selective microbeads is efficient and repeatable. To reiterate, CD146-seletive HemMC should be added to IH models and used for research on the effectiveness of antiangiogenic or proangiogenic methods for the treatment of IH.
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There are several differences between the HemMC/EC/Matrigel xenograft model and the HemSC/Matrigel xenograft model. First, the number of CD133-selective HemSCs in IH is very small, i.e., approximately 0.2% (7), and is hard to detect in stable IH, while the number of CD146-selective HemMCs is large. Second, HemMCs exhibit rapid proliferation and stronger proangiogenic ability than HemSCs; thus, the HemMC/EC/Matrigel model is more suitable for studying new therapies to treat involuting IH. Finally, HemMCs do not have endothelial differentiation potential; thus, the value of this model for studying vasculogenesis is limited.
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In summary, HemMCs exhibit MSC-like features and proangiogenic ability in vitro, and a murine model established using HemMCs can simulate the pathological characteristics of IH. This study uses CD146-selective microbeads to isolate HemMCs, which surround the endothelium and proliferate quickly in IH. In vitro, HemMCs exhibit proangiogenic properties: they express markers of MSCs, exhibit strong angiogenesis-associated signaling, display multilineage differentiation potential, and enhance HUVEC tube formation. In vivo, CD146-selective HemMCs implanted with Matrigel spontaneously differentiate into adipocytes, while HemMCs implanted with HUVECs can form GLUT1-positive microvessels followed by Perilipin-A-positive adipose-like IH lesions. The proangiogenic function of HemMCs needs to be further studied to discover new drugs for the treatment of IH.
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Data availability statement
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The data generated in this study has been deposited in NCBI’s Gene Expression Omnibus and is accessible through GEO Series accession number GSE216867 or at this link: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE216867.
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Ethics statement
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The studies involving human participants were reviewed and approved by the Ethics Committee of Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University of Medicine. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements. The animal study was reviewed and approved by the Ethics Committee of Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University of Medicine.
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Author contributions
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ZC and XL were the primary contributor to research design. JC, LC, YQ, YL, S-JC and QC were responsible for recruitment of patients, provision of human samples, research execution and were contributors to data acquisition. ZC and JC were the primary contributors to data analysis and interpretation. JC and ZC prepared the manuscript with revisions provided by ZC, XL, LC and YQ. ZC and XL were in charge of funding provision and study supervision. All authors contributed to the article and approved the submitted version.
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Conflict of interest
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The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Publisher’s note
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
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Supplementary material
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The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2023.1063673/full#supplementary-material
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Click here for additional data file.
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==== Refs
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23 Boscolo E Mulliken JB Bischoff J . VEGFR-1 mediates endothelial differentiation and formation of blood vessels in a murine model of infantile hemangioma. Am J Pathol (2011) 179 (5 ):2266–77. doi: 10.1016/j.ajpath.2011.07.040
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24 Chen J Wu D Dong Z Chen A Liu S . The expression and role of glycolysis-associated molecules in infantile hemangioma. Life Sci (2020) 259 :118215. doi: 10.1016/j.lfs.2020.118215 32768579
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25 Rastogi K Singh L Khan NA Goyal S Khatri A Gupta N . Benign vascular anomalies: a transition from morphological to etiological classification. Ann Diagn Pathol (2020) 46 :151506. doi: 10.1016/j.anndiagpath.2020.151506 32200223
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26 Smadja DM Guerin CL Boscolo E Bieche I Mulliken JB Bischoff J . alpha6-integrin is required for the adhesion and vasculogenic potential of hemangioma stem cells. Stem Cells (2014) 32 (3 ):684–93. doi: 10.1002/stem.1539
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27 Zhang W Chen G Wang FQ Ren JG Zhu JY Cai Y . Macrophages contribute to the progression of infantile hemangioma by regulating the proliferation and differentiation of hemangioma stem cells. J Invest Dermatol (2015) 135 (12 ):3163–72. doi: 10.1038/jid.2015.321
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28 Greenberger S Boscolo E Adini I Mulliken JB Bischoff J . Corticosteroid suppression of VEGF-a in infantile hemangioma-derived stem cells. N Engl J Med (2010) 362 (11 ):1005–13. doi: 10.1056/NEJMoa0903036
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| 218 |
+
29 Greenberger S Yuan S Walsh LA Boscolo E Kang KT Matthews B . Rapamycin suppresses self-renewal and vasculogenic potential of stem cells isolated from infantile hemangioma. J Invest Dermatol (2011) 131 (12 ):2467–76. doi: 10.1038/jid.2011.300
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| 219 |
+
30 Mai HM Zheng JW Wang YA Yang XJ Zhou Q Qin ZP . CD133 selected stem cells from proliferating infantile hemangioma and establishment of an in vivo mice model of hemangioma. Chin Med J (Engl) (2013) 126 (1 ):88–94. doi: 10.1038/jid.2011.300 23286484
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| 220 |
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|
puc/PMC10173662.txt
ADDED
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Stem Cell Res Ther
|
| 4 |
+
Stem Cell Res Ther
|
| 5 |
+
Stem Cell Research & Therapy
|
| 6 |
+
1757-6512
|
| 7 |
+
BioMed Central London
|
| 8 |
+
|
| 9 |
+
3361
|
| 10 |
+
10.1186/s13287-023-03361-0
|
| 11 |
+
Research
|
| 12 |
+
HSPB7 oppositely regulates human mesenchymal stromal cell-derived osteogenesis and adipogenesis
|
| 13 |
+
Zhang Shuang
|
| 14 |
+
van de Peppel Jeroen
|
| 15 |
+
Koedam Marijke
|
| 16 |
+
van Leeuwen Johannes P. T. M.
|
| 17 |
+
http://orcid.org/0000-0003-4403-6497
|
| 18 |
+
van der Eerden Bram C. J. b.vandereerden@erasmusmc.nl
|
| 19 |
+
|
| 20 |
+
grid.5645.2 000000040459992X Laboratory for Calcium and Bone Metabolism, Department of Internal Medicine, Erasmus MC, Erasmus University Medical Center, Docter Molewaterplein 40, 3015 GD Rotterdam, The Netherlands
|
| 21 |
+
11 5 2023
|
| 22 |
+
11 5 2023
|
| 23 |
+
2023
|
| 24 |
+
14 1264 8 2022
|
| 25 |
+
2 5 2023
|
| 26 |
+
© The Author(s) 2023
|
| 27 |
+
https://creativecommons.org/licenses/by/4.0/ Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
|
| 28 |
+
Background
|
| 29 |
+
|
| 30 |
+
Recent evidence suggests that accumulation of marrow adipose tissue induced by aberrant lineage allocation of bone marrow-derived mesenchymal stromal cells (BMSCs) contributes to the pathophysiologic processes of osteoporosis. Although master regulators of lineage commitment have been well documented, molecular switches between osteogenesis and adipogenesis are largely unknown.
|
| 31 |
+
|
| 32 |
+
Methods
|
| 33 |
+
|
| 34 |
+
HSPB7 gene expression during osteogenic and adipogenic differentiation of BMSCs was evaluated by qPCR and Western blot analyses. Lentiviral-mediated knockdown or overexpression of HSPB7 and its deletion constructs were used to assess its function. The organization of cytoskeleton was examined by immunofluorescent staining. ALP activity, calcium assay, Alizarin Red S staining and Oil Red O staining were performed in vitro during osteoblast or adipocyte differentiation. SB431542 and Activin A antibody were used to identify the mechanism of Activin A in the regulation of osteogenic differentiation in BMSCs.
|
| 35 |
+
|
| 36 |
+
Results
|
| 37 |
+
|
| 38 |
+
In this study, we identified HSPB7 capable of oppositely regulating osteogenic and adipogenic differentiation of BMSCs. HSPB7 silencing promoted adipogenesis while reducing osteogenic differentiation and mineralization. Conversely, overexpression of HSPB7 strongly enhanced osteogenesis, but no effect was observed on adipogenic differentiation. Deletion of the N-terminal or C-terminal domain of HSPB7 led to decreased osteoblastic potency and mineralization. Mechanistically, our data showed that Activin A is a downstream target participating in HSPB7 knockdown-mediated osteogenic inhibition.
|
| 39 |
+
|
| 40 |
+
Conclusions
|
| 41 |
+
|
| 42 |
+
Our findings suggest that HSPB7 plays a positive role in driving osteoblastic differentiation, and with the capability in maintaining the osteo-adipogenesis balance. It holds great promise as a potential therapeutic target in the treatment of bone metabolic diseases.
|
| 43 |
+
|
| 44 |
+
Supplementary Information
|
| 45 |
+
|
| 46 |
+
The online version contains supplementary material available at 10.1186/s13287-023-03361-0.
|
| 47 |
+
|
| 48 |
+
Keywords
|
| 49 |
+
|
| 50 |
+
Bone marrow-derived mesenchymal stromal cells
|
| 51 |
+
Osteogenic differentiation
|
| 52 |
+
Adipogenic differentiation
|
| 53 |
+
Lineage commitment
|
| 54 |
+
HSPB7
|
| 55 |
+
Activin A
|
| 56 |
+
http://dx.doi.org/10.13039/501100004543 China Scholarship Council No. 201709370052 Zhang Shuang issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2023
|
| 57 |
+
==== Body
|
| 58 |
+
pmcBackground
|
| 59 |
+
|
| 60 |
+
Osteoporosis is the most common skeletal disorder characterized by low mineral density and bone structure deterioration, leading to increased fracture risk in the ageing population. In addition to the well-established concept that osteoporosis is caused by the imbalance between osteoblasts and osteoclasts [1, 2], growing evidence suggests the involvement of aberrant lineage allocation of bone marrow-derived mesenchymal stromal cells (BMSCs) [3, 4]. BMSCs are multipotent cells with the ability of self-renewal and multiple lineage differentiation including osteoblasts and adipocytes [5, 6]. However, this lineage commitment process is generally regarded to be inversely correlated, as osteogenic differentiation of MSCs requires suppression of adipogenesis, while increased marrow adipogenic differentiation takes place at the expense of osteoblast formation [7, 8]. Consistent with these findings, human studies have proposed that accumulated marrow adipose tissue is correlated with osteoporosis and increased fracture risk, particularly in the context of obesity and aging, further implicating the impairment of lineage allocation [9–13].
|
| 61 |
+
|
| 62 |
+
Cell fate decision and commitment of MSCs are strictly orchestrated by a variety of physical factors and molecular signals [14]. Cell shape and cytoskeletal (re)arrangement also contributes to lineage specification, as MSCs confined to a ‘star’ shape showed increased osteogenesis whereas ‘flower’ patterned confinement led to enhanced adipogenesis [15]. Transcription factors, such as RUNX2 and Osterix (SP7), are classically considered as the master regulators of osteogenesis [16], while PPARγ and CEBPα/β/δ play essential roles toward adipogenesis [17]. WNT and Hedgehog are well-known signals to stimulate osteogenic and antagonize adipogenic differentiation [18]. Some crucial domains within specific proteins could further prime MSCs toward specific lineages and mediate the response of MSCs to certain lineage-specific stimulators [19]. Identifying molecular switches is important to dictate the reciprocal relationship between osteoblast and adipocytes during fate determination and the ultimate control of osteo-adipogenic balance.
|
| 63 |
+
|
| 64 |
+
Small heat shock proteins (sHSPs), characterized by low molecular weight and highly conserved C-terminal domains (α-crystallin) were originally discovered as molecular chaperons against protein misfolding in pathological conditions. Over the past decade, numerous studies have demonstrated that sHSPs physically interact with different types of transcription factors as well as intrinsic and extrinsic signals, indicating a possible role in stem cell behavior. Evidence suggests that sHSPs are involved in bone metabolism through specific pathways regulating cell differentiation [20], growth factor secretion [21] and calcium deposition [22]. Being the most widely studied sHSP in osteoblasts, HSPB1 is critical for vascular endothelial growth factors (VEGF) release induced by transforming growth factor (TGF)-β and fibroblast growth factor (FGF)-2 [21, 23]. The non-phosphorylated version of HSPB7 could decrease the expression of osteocalcin, further enhancing mineralization in osteoblasts [14]. Dysregulation of HSPB8 has been associated with impaired osteogenic differentiation of dental pulp stem cells, further establishing the important role of sHSPs during osteoblast differentiation [22].
|
| 65 |
+
|
| 66 |
+
HSPB7 is one of the least studied members in sHSP family and is highly expressed in heart and skeletal muscle [24]. In this study, we demonstrated that HSPB7 capable of oppositely regulating osteogenic and adipogenic differentiation, indicating it to be a molecular switch mediating lineage allocation of BMSCs.
|
| 67 |
+
|
| 68 |
+
Methods
|
| 69 |
+
|
| 70 |
+
Cell culture and differentiation
|
| 71 |
+
|
| 72 |
+
Human bone marrow-derived mesenchymal stromal cells (BMSCs, Lonza, Basel, Switzerland) were cultured as previously described [25]. Briefly, BMSCs were maintained in alpha minimum essential medium (α-MEM, Gibco, Paisley, United Kingdom) supplemented with 10% heat-inactivated fetal calf serum. Following two days of attachment, osteogenic induction was initiated using 100 nM dexamethasone and 10 mM β-glycerophosphate. For adipogenic induction, BMSCs were treated with 0.1 μM dexamethasone, 60 μM indomethacin, and 0.5 mM 3-isobutyl-1-methylxanthine. Cells at passage 7 were used in all experiments and media was refreshed every 3 or 4 days. To block Activin A activity, SB431542 (Sigma-Aldrich, Zwijndrecht, the Netherlands) or Activin A neutralizing antibody (R&D Systems, Minneapolis, Minnesota, United States) was added during cell refreshment.
|
| 73 |
+
|
| 74 |
+
Generation of constructs and lentivirus-mediated knockdown and overexpression
|
| 75 |
+
|
| 76 |
+
As previously described [26], the constructs of short hairpin RNA (shRNA) targeting HSPB7 and the nontargeting shRNA with a scrambled sequence serving as negative control were purchased from TRC-1.0 library (Sigma-Aldrich, Zwijndrecht, the Netherlands; Additional file 1: Table S1). To obtain overexpression, full-length human HSPB7 cDNA (Horizon Discovery, Waterbeach, United Kingdom) containing a His-tag stop codon was cloned into a pEntr-TOPO vector and transferred by Gateway recombination into a pLenti6.3/V5–DEST vector (Gateway Vector Kits, Life Technologies Europe B.V., the Netherlands). HSPB7 deletion constructs were generated using Q5® Site-Directed Mutagenesis Kit (New England Biolabs, Massachusetts, Unite States) according to the manufacturer’s instructions. Following proofreading PCR (Primers were shown in Additional file 1: Table S2), the amplified product was added to a Kinase–Ligase–DpnI enzyme mix for 5 min enabling room temperature (RT) circularization and template removal. Subsequent products were transformed into E. coli and plasmid DNA isolation was performed after culture. All constructs were verified by Sanger sequencing.
|
| 77 |
+
|
| 78 |
+
Lentivirus was produced by transient transfection into 293FT cells using a standard calcium phosphate precipitation method with the addition of 1 μg/ml polybrene (Sigma-Aldrich, Zwijndrecht, the Netherlands) as described previously [27]. After 48 h, supernatants containing lentivirus were harvested and used immediately for BMSC transduction (24 h after attachment). One day later, medium was replaced with differentiation induction medium, and cells were cultured until further analysis.
|
| 79 |
+
|
| 80 |
+
Alkaline phosphatase (ALP) activity and mineralization assays
|
| 81 |
+
|
| 82 |
+
ALP activity was determined using p-nitrophenyl phosphate (pNPP) as a phosphatase substrate which turns yellow when dephosphorylated to p-Nitrophenol (pNP) by ALP. As previously described [25], cell extracts were harvested at different time points using PBS containing 0.1% triton X-100. The conversion step from pNPP to pNP was performed for 10 min at 37 °C. ALP activity was quantified by measuring the absorbance at 405 nm and adjusted to the total protein content. Total protein concentration was determined using a BCA protein assay kit (Thermo fisher scientific, Waltham, Massachusetts, United States) following manufacturer’s instruction.
|
| 83 |
+
|
| 84 |
+
For mineralization, cell lysates and the remaining plates were incubated overnight with 0.24 M HCl at 4 °C. Calcium content was determined in a colorimetric way using a combination of 1 M ethanolamine buffer (pH 10.6) with 0.35 mM 0-cresolphthalein in a 1:1 ratio. Total calcium content was calculated by combining calcium in cell lysates and calcium left behind in the plates. Alizarin Red S staining was performed as described previously [27]. Briefly, cells were fixed with 70% ethanol and stained for 15 min with Alizarin Red S solution at RT (pH 4.2, Sigma-Aldrich, St. Louis, Missouri, United States).
|
| 85 |
+
|
| 86 |
+
Oil red O staining
|
| 87 |
+
|
| 88 |
+
After 14 days of adipogenic differentiation, BMSCs were washed twice with PBS, fixed with 10% formalin, and subsequently stained with Oil Red O solution (Sigma-Aldrich, St. Louis, Missouri, United States). Cell number was determined by DAPI staining and pictures were taken by a Zeiss Axiovert 200MOT microscope (Zeiss, Sliedrecht, The Netherlands). Normalized absorbance was calculated using raw absorbance divided by cell count.
|
| 89 |
+
|
| 90 |
+
Cell viability assay
|
| 91 |
+
|
| 92 |
+
Cell viability was determined using Cell Counting Kit-8 (CCK-8) assays. BMSCs in the presence or absence of induction were incubated with CCK-8 reagent (Sigma-Aldrich, St. Louis, MO, USA) for 2 h in an incubator according to the manufacturer’s manual. The conversion of the tetrazolium salt WST-8 to formazan was measured at 450 nm.
|
| 93 |
+
|
| 94 |
+
RNA isolation and quantification of mRNA expression
|
| 95 |
+
|
| 96 |
+
RNA isolation, cDNA synthesis and real-time PCR reactions were performed as described before [25]. Oligonucleotide primer pairs were designed to be either on exon boundaries or spanning at least one intron (Additional file 1: Table S3). Gene expression was normalized to the expression of the housekeeping gene 36B4, using the equation. 2^−(Ct gene of interest – Ct housekeeping gene).
|
| 97 |
+
|
| 98 |
+
Immunostaining
|
| 99 |
+
|
| 100 |
+
Immunostaining was performed as previously described [27, 28]. Briefly, BMSCs were fixed with 4% PFA for 5 min at RT and washed with PBS. Immunostaining was performed after permeabilization with 0.1% Triton X-100 (Sigma-Aldrich, St. Louis, Missouri, United States) in PBS and blocking for 30 min in 1% bovine serum albumin at RT simultaneously. Cells were incubated with α-Tubulin antibody (1:100; Cell signaling #2125S, The Netherlands) or HSPB7 antibody (1:100; Novus Biologicals NBP1-84334, Abingdon, United Kingdom) overnight at 4 °C. The next day, cells were incubated with Alexa Flour 488 donkey anti-rabbit (1:200; Abcam #150073, Cambridge, United Kingdom) secondary antibody for 1 h at RT, followed by the addition of rhodamine-conjugated phalloidin (1:100, Thermo Fisher Scientific #10063052, Massachusetts, United States) for 1 h at RT. After 10 min incubation with DAPI, images were taken with a confocal laser scanning microscope (Leica Microsystems, Wetzlar, Germany).
|
| 101 |
+
|
| 102 |
+
Western blot
|
| 103 |
+
|
| 104 |
+
Western blot analysis was performed as described [28]. Total protein was collected in RIPA lysis buffer (Thermo Fisher Scientific, Massachusetts, United States). Equal amounts of protein per sample were loaded and separated by SDS-PAGE (Bio-Rad Laboratories B.V., Veenendaal, The Netherlands) and transferred onto a polyvinylidene difluoride membrane (Amersham™ Hybond® Western blotting membranes, Sigma-Aldrich, Zwijndrecht, the Netherlands). Each membrane was blocked with 5% non-fat milk in Tris-buffered saline containing 0.1% Tween-20 (TBS-T) at RT for 1 h before blotting with primary antibodies directed against HSPB7 (1:1,000; Novus Biologicals NBP1-69,072, Abingdon, United Kingdom), β-Actin (1:1,000, Cell signaling #4970, The Netherlands), PPARγ (1:1,000; Cell signaling #2435, The Netherlands), C/EBPα (1:1,000; Cell signaling #8178, The Netherlands), Perilipin (1:1,000, Cell signaling #9349, The Netherlands), FABP4 (1:1,000, Cell signaling #2120, The Netherlands), Fatty acid synthase (1:1,000; Cell signaling #3180, The Netherlands), Acetyl-CoA carboxylase (1:1,000, Cell signaling #3676, The Netherlands) at 4 °C overnight. After three washes in TBS-T, the membrane was incubated with anti-rabbit antibody (1:2,000; Cell signaling #7074, The Netherlands) conjugated with horse radish peroxidase for 1 h at RT. The proteins of interest were detected with Gel Doc XR System (Bio-Rad Laboratories B.V., Veenendaal, The Netherlands) using the Clarity™ Western ECL Substrate (Bio-Rad Laboratories B.V., Veenendaal, The Netherlands) and were semi-quantified using Image Lab software (Bio-Rad Laboratories B.V., Veenendaal, The Netherlands).
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| 105 |
+
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| 106 |
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Statistical analysis
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| 107 |
+
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| 108 |
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Data were displayed as means ± SE of representative experiments. All experiments were performed at least two times. Statistical analysis was performed using GraphPad Prism 9. Significance was calculated using the Student’s t-test, and one-way or two-way ANOVA after post-hoc testing.
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| 109 |
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Results
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HSPB7 is upregulated during osteogenic differentiation and downregulated during early adiopogenesis
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| 113 |
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| 114 |
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sHSPs are widely known to be distributed throughout cellular compartments but currently there is no indication of HSPB7 protein localization in BMSCs. Immunofluorescent detection reveals that HSPB7 is exclusively localized in the nucleoplasm in the presence or absence of induction (Fig. 1A). To determine the role of HSPB7 during BMSC differentiation, we measured the expression level of HSPB7 under osteogenic and adipogenic induction of BMSCs (Fig. 1B). In comparison with undifferentiation stage (day 0), HSPB7 expression is dramatically increased during osteogenesis, peaking at 3 days of differentiation. On the other hand, the expression of HSPB7 is decreased during early days of adipogenic differentiation, showing an opposite trend to that of osteogenic inductions. These data led us to further investigate HSPB7 as a candidate gene influencing BMSC differentiation.Fig. 1 HSPB7 expression is upregulated during osteogenic differentiation and downregulated during early adipogenic differentiation. A Cellular localization of HSPB7 in BMSCs with or without induction at day 3. B Relative mRNA expression levels of HSPB7 in BMSCs were assessed by qRT-PCR over 3 weeks. BMSC cultured in osteogenic condition was indicated with blue bars, and adipogenic condition was indicated with pink bars. Data are presented as means ± SEM and analyzed by one-way ANOVA (n = 2 per group) followed by post-hoc testing. Scale bars: 200 μm
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| 115 |
+
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| 116 |
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Silencing HSPB7 in BMSCs inhibits osteogenic differentiation and mineralization
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| 117 |
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| 118 |
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To delineate the role of HSPB7 in osteoblast fate decision, we first performed HSPB7 gene silencing in BMSCs. Efficient knockdown of HSPB7 was evaluated by gene expression analysis and Western blot. Figure 2A demonstrates that HSPB7 mRNA was inhibited by two different shRNAs, and these effects were further confirmed at the protein level (Fig. 2B). Cell viability indicated by CCK-8 experiment was decreased following HSPB7 silencing (Additional file 2: Fig. S1A), suggesting a potential effect on cell proliferation.Fig. 2 HSPB7 silencing in BMSCs inhibits osteogenic differentiation and mineralization. A–B HSPB7 silencing was assessed by quantification of HSPB7 mRNA expression by qRT-PCR at different time points (A) and Western blot (B) on day 3 under osteogenic induction. Full-length blots are presented in Additional file 7: Fig. S6. C ALP activity was evaluated at different time points under osteogenic induction. D–E Osteoblast mineralization was assessed by calcium deposition assay (D) and Alizarin Red S staining (E) after three weeks osteogenic induction. F osteogenesis-related genes were evaluated on day 6. Data are presented as means ± SEM and analyzed by one-way ANOVA (B, D and F, n = 3–4 per group) or two-way ANOVA (A, n = 4 per group) followed by post-hoc testing
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| 119 |
+
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| 120 |
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Next, we examined the consequence of HSPB7 silencing on classical biochemical markers during osteogenic differentiation and mineralization of BMSCs. BMSCs showed significantly less ALP activity at different time points after treatment with osteogenic induction media (Fig. 2C). Remarkably, mineralized nodule formation was completely abolished as shown by calcium deposition assay and Alizarin Red S staining (Fig. 2D–E). When assessing osteoblast marker genes, reduced levels of RUNX2 and ALPL were detected 6 days after HSPB7 silencing (Fig. 2F). Taken together, these findings indicate that HSPB7 inhibition impaired osteogenic differentiation.
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| 121 |
+
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| 122 |
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HSPB7 silencing in BMSCs affects cytoskeleton reorganization
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| 123 |
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| 124 |
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One of the most important features of sHSPs is the ability to interact with cellular components of the cytoskeleton, and this interaction protects the cytoskeleton from injury in a stressful environment [29]. Given that BMSCs change from a fibroblast-like phenotype to a spherical shape during osteoblastic differentiation, and end up as mature osteoblasts (or osteocytes), we hypothesized that HSPB7 participates in the rearrangement process of the cytoskeleton during osteogenic differentiation and mineralization. Therefore, we monitored the dynamic changes of microfilament and microtubule organization by immunostaining at multiple time points. BMSCs cultured in osteogenic media exhibited progressive morphological changes as indicated from day 3 to day 20, as thick actin patterns were recorded running across the entire cytoplasm toward the outermost parts of the cells during osteogenic differentiation (day 14 in Fig. 3, days 3, 7 and 20 in Additional file 3: Fig. S2A–C). However, there was no substantial reorganization regarding the microtubule structure.Fig. 3 HSPB7 silencing in BMSCs affects cytoskeleton organization. A Representative images of immunostainings against F-actin (phalloidin-rhodamine), α-tubulin (Alexa Fluor 488) and Nuclei (DAPI) at day 14 following osteogenic induction. Arrows indicate spindle-shaped fibroblast-like cells. Scale bars: 200 μm
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| 125 |
+
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| 126 |
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In contrast to the cuboidal phenotype of the osteoblasts in the control situation, HSPB7 silenced BMSCs (shRNA2) displayed a spindle-shape fibroblast-like morphology on day 14, with parallel actin filaments observed in the cytoplasm (Fig. 3). Remarkably, microtubule networks ran through the entire cell body in parallel rather than radiating from a perinuclear location (Fig. 3), as shown at different time points from day 3 to day 20 during osteogenic differentiation (Fig. 3, Additional file 3: Fig. S2A–C). Together, these data suggest that HSPB7 silencing during osteogenic differentiation leads to dynamic cytoskeletal changes influencing cell morphology.
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| 127 |
+
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| 128 |
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Silencing HSPB7 in BMSCs enhances adipogenesis
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| 129 |
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| 130 |
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It has been reported that the regulation of osteogenesis and adipogenesis from BMSCs is reciprocal [18]. Since loss of HSPB7 inhibited osteogenic differentiation, we explored whether HSPB7 silencing could promote adipogenesis. As shown by Oil Red O staining, knockdown of HSPB7 facilitated adipogenic differentiation (Fig. 4A, B) without influencing adipocyte proliferation, which was determined by assessing cell numbers (Fig. 4C) and calculating absorbance of individual cells (Fig. 4D). Consistently, elevated levels of adipocyte marker genes including PPARG, FABP4, LPL and PLIN1 were observed following HSPB7 silencing (Fig. 4E), and the expression levels of key transcription factors including Peroxisome proliferator-activated receptor gamma (PPARγ) and CCAAT/enhancer binding protein alpha (C/EBPα), as well as Perilipin-1 and Fatty acid binding protein 4 (FABP4) were further confirmed at protein level (Fig. 4F–G). Additionally, the expression of lipogenic proteins such as Fatty acid synthase (FASN) and Acetyl-CoA carboxylase (ACC) were increased up to fivefold following HSPB7 knockdown (Fig. 4F-G). Collectively, our findings indicate that reduced levels of HSPB7 lead to enhanced adipogenesis.Fig. 4 HSPB7 silencing in BMSCs enhances adipogenesis. A–D Representative images (A) and quantitative data (B) of Oil Red O staining performed after 14 days with adipogenic induction. Total cell number was determined by DAPI staining (C). Quantitative data of Oil Red O staining were adjusted by cell number (D). E The expression of adipogenic markers was evaluated by qRT-PCR at indicated time points. F–G Representative images (F) and quantitative data (G) of adipogenic genes were assessed on day 7 following adipogenic induction by Western blot. Full-length blots are presented in Additional file 7: Fig. S6. Abbreviations: Peroxisome proliferator-activated receptor gamma (PPARγ), Fatty acid binding protein 4 (FABP4), CCAAT/enhancer binding protein alpha (C/EBPα) and Perilipin-1 (PLIN1) Fatty acid synthase (FASN) and Acetyl-CoA carboxylase (ACC). Data are presented as means ± SEM and analyzed by one-way ANOVA (B–D and G, n = 3–4 per group) or two-way ANOVA (E, n = 4 per group) followed by post-hoc testing. Scale bars: 200 μm
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| 131 |
+
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| 132 |
+
HSPB7 overexpression in BMSCs enhances osteogenic differentiation and mineralization, but did not affect adipogenesis
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| 133 |
+
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| 134 |
+
To further provide insights into the role of HSPB7 during osteogenic differentiation, we examined the effect of HSPB7 gain-of-function on osteogenic differentiation and mineralization in BMSCs. qRT-PCR showed that HSPB7 expression is significantly increased at all investigated time points (Fig. 5A), and this enhanced expression was confirmed by Western blot (Fig. 5B). In contrast to HSPB7 knockdown, cell viability was not affected by HSPB7 overexpression (Additional file 2: Fig. S1B). Following osteogenic induction, ALP activity was increased when HSPB7 was overexpressed (Fig. 5C). Similarly, calcium deposition was also elevated following HSPB7 overexpression, as revealed by calcium quantitation and Alizarin Red S staining at day 21 (Fig. 5D–E). Moreover, overexpression of HSPB7 in BMSCs facilitated the expression of osteogenic marker genes, including ALPL and COL1A1 (Fig. 5F). However, cell morphology and cytoskeleton rearrangement looked similar between control and HSPB7 overexpression groups (Fig. 5G).Fig. 5 HSPB7 overexpression in BMSCs enhances osteogenic differentiation and mineralization, but not adipogenesis. A HSPB7 overexpression was assessed by quantification of HSPB7 mRNA expression at different time points. B Representative images and quantitative expression of HSPB7 were assessed by Western blot using HSPB7 antibody on day 3 following osteogenic induction. Full-length blots are presented in Additional file 7: Fig. S6. C ALP activity was evaluated at multiple time points with osteogenic media. D, E Osteoblast mineralization was assessed by calcium deposition assay (D) and Alizarin Red S staining (E) after 3 weeks osteogenic induction. F Osteogenesis-related gene were evaluated at different time points with osteogenic induction. G Representative images of immunostainings against F-actin (phalloidin-rhodamine), α-tubulin (Alexa Fluor 488) and Nuclei (DAPI) on day 14 following osteogenic induction. H, I Representative images (H) and quantitative data (I) of Oil Red O staining performed after 14 days with adipogenic induction. Total cell number was determined by DAPI staining. Quantitative data of Oil Red O staining was adjusted by cell number. Data are presented as means ± SEM and analyzed by two-tailed Student’s t-test ANOVA (B, D, F and I, n = 3–4 per group) or two-way ANOVA (A and C, n = 4 per group) followed by post-hoc testing. Scale bars: 200 μm
|
| 135 |
+
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| 136 |
+
Considering the reciprocal role of osteogenesis and adipogenesis, and the observation that gain-of-function of HSPB7 favors osteogenic differentiation and mineralization, we wondered whether the adipogenic differentiation of BMSCs could be affected by HSPB7 overexpression. In contrast to the osteogenic lineage effects, overexpression of HSPB7 in BMSCs failed to alter the lineage commitment toward adipocytes, as evidenced by unaffected Oil Red O staining (Fig. 5H, I). Collectively, these findings suggest that HSPB7 overexpression has a positive effect on osteogenic differentiation and mineralization, but does not influence adipogenesis in BMSCs.
|
| 137 |
+
|
| 138 |
+
The ability of HSPB7 to enhance osteogenic differentiation depends on the N- and C-terminal domains
|
| 139 |
+
|
| 140 |
+
sHSPs are characterized by a conserved α-crystallin domain flanked by a flexible sized N- and C-terminus that is mostly divergent among family members. However, the role of these functional domains in controlling the differentiation behavior of BMSC is unknown. Therefore, we explored the role of structural characteristics in HSPB7 toward osteogenic differentiation and mineralization. Apart from deleting the N- or C-terminal domains (ΔN or ΔC, respectively), we also focused our attention on the serine-rich stretch sequence (SRS, Δ17–29) within the N-terminal domain, which has been considered as a critical segment for proper HSPB7 function [30] (Fig. 6A). Based on sequence analyses, structure prediction showed that truncated proteins have different organization and 3D configuration compared to the original HSPB7 protein (Fig. 6B). To further explore the function of each domain, we then overexpressed them by lentiviral transduction and validated their expression and size by immunoblotting (Fig. 6C). The intensity of the bands may reflect protein instability or degradation as gene expression of these overexpression constructs was more or less similar (Additional file 4: Fig. S3). Compared to full-length overexpression, deletion of the SRS and N-terminus resulted in a decrease in ALP activity (Fig. 6D). C-terminus deletion also led to a decrease in ALP activity despite the strongly increased protein level compared to full-length HSPB7 (Fig. 6C–D). Interestingly, deletion of SRS led to a marginal decrease in mineralization while an absolute lack of mineralization was observed when the N-terminus was completely deleted (Fig. 6E, F). Also, deletion of the C-terminus domain led to a complete block of mineralization, i.e., a mineralization below control level (Fig. 6E, F). To determine whether impaired mineralization was caused by altered subcellular localization of deletion mutants, we performed immunostainings, using His antibody to detect full-length and truncated HSPB7 proteins. As shown in Additional file 5: Fig. S4, all three deletion mutants had similar subcellular localization as full-length HSPB7. Collectively, these data indicate N and C-terminus are dominant domains, while SRS is not involved in HSPB7-regulated osteogenesis.Fig. 6 The ability of HSPB7 to enhance osteogenic differentiation depends on N- and C-terminal domains. A A schematic representation of full-length HSPB7 and its truncated mutants. His tag is located at the C terminal in each construct B 3D structures of FL HSPB7 and its truncated mutants generated by SWISS-MODEL (https://swissmodel.expasy.org). These models were predicated with reference to the template of 4jut.1.A and were selected on the basis of GMQE and QMEANDisCo global scores. C BMSCs expressing the indicated HSPB7 constructs were immunoblotted with anti-histidine antibody in non-differentiating conditions. Control samples were transduced with dsRED. Full-length blots are presented in Additional file 7: Fig. S6. D ALP activity was evaluated in BMSCs expressing dedicated constructs under osteogenic induction at day 13. E, F Osteoblast mineralization was assessed by calcium deposition assay (E) and Alizarin Red S staining (E) after three weeks osteogenic induction in BMSCs. Abbreviations: ΔN, N-terminus deletion; ΔC, C-terminus deletion; SRS, serine-rich sequence stretch; FL, full-length. Data are presented as means ± SEM and analyzed by one-way ANOVA (n = 4 per group) followed by post-hoc testing
|
| 141 |
+
|
| 142 |
+
Activin A blockage overcomes the HSPB7 knockdown-mediated osteogenic inhibition
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| 143 |
+
|
| 144 |
+
Earlier work by others had proposed an interaction between HSPB7 and Activin A [31]. Besides, our previous findings have shown an inhibitory effect of Activin A on osteogenesis [32]. Therefore, we postulated that Activin A interacts with HSPB7 during osteogenic differentiation. ShRNA2 was selected to investigate the downstream effect as it showed the strongest knockdown of HSPB7 (Fig. 2A, B). The increased expression of Activin A was observed throughout the entire osteogenic differentiation process and knockdown of HSPB7 significantly stimulated Activin A expression encoded by INHBA (Fig. 7A). Such effects were more pronounced when evaluating Activin A expression using immunoblotting at late stages of osteoblast differentiation (Fig. 7B, C). On the other hand, Activin A expression showed a biphasic pattern following HSPB7 overexpression with an early increase on day 6 followed by a decline from day 13 onward, and at day 20, a significant down-regulation of INHBA was observed when HSPB7 was continually overexpressed (Additional file 6: Fig. S5A), consistent with the findings in Immunoblots (Additional file 6: Fig. S5B, C).Fig. 7 Blocking Activin A overcomes HSPB7 silencing-mediated osteogenic inhibition. A INHBA mRNA expression was assessed by qRT-PCR following HSPB7 silencing at different time points following osteogenic induction. B, C INHBA mRNA expression was assessed by Western blot following HSPB7 silencing at day 14 (B) and day 21 (C) following osteogenic induction. Full-length blots are presented in Additional file 7: Fig. S6. D Osteoblast mineralization was assessed by calcium deposition assay after three weeks osteogenic induction. BMSCs were induced to osteogenic differentiation following HSPB7 silencing in the presence of SB431542 (D) or neutralizing Activin A antibodies (E). F ECM genes were evaluated by qRT-PCR following HSPB7 silencing at day 13 and day 20. Data are presented as means ± SEM and analyzed by two-tailed Student’s t-test (B–C, n = 3 per group) or two-way ANOVA (A, D–F, n = 4 per group) followed by post-hoc testing
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| 145 |
+
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| 146 |
+
We next examined whether Activin A is a downstream target involving HSPB7-mediated osteogenic effect. Activin A signaling antagonist SB431542 prevented the HSPB7 knockdown-mediated inhibition of mineralization (Fig. 7D). To further confirm this finding, we used Activin A antibodies to neutralize secreted Activin A. As shown in Fig. 7E, HSPB7 silencing-mediated inhibition of osteoblast mineralization was abolished by Activin A antibody treatment (Fig. 7E). Collectively, these data demonstrate that Activin A plays a critical role in HSPB7-mediated osteogenesis.
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| 147 |
+
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| 148 |
+
Our previous work had suggested that Activin A negatively regulates osteoblast mineralization through altering the maturation of the extracellular matrix (ECM) [33]. Based on that, we selected several ECM genes and assessed whether the expression was changed during later stages of osteoblast differentiation (Fig. 7F and Additional file 6: Fig. S5D). COL5A3 and MMP2 were strongly regulated by HSPB7 silencing (Fig. 7F), while these effects were not observed in HSPB7 overexpressing cells (Additional file 6: Fig. S5D). One the other hand, POSTN and CLEC3B were significantly changed during late (day 20) osteoblast differentiation following HSPB7 overexpression (Additional file 6: Fig. S5D), but did not reveal differences following HSPB7 knockdown (Fig. 7F).
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| 149 |
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| 150 |
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Discussion
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| 151 |
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| 152 |
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In the present study, we demonstrate that HSPB7 is a molecular switch in regulating osteogenic and adipogenic differentiation of BMSCs (Fig. 8). Our gain- and loss-of-function studies showed that HSPB7 intrinsically promotes osteogenesis. Moreover, knockdown of HSPB7 stimulated adipogenesis, further emphasizing the importance of HSPB7 for BMSC differentiation. Meanwhile, we show that HSPB7 expression is indispensable for osteogenic induction by affecting cell morphology and cytoskeletal reorganization. Complete deletion of the N- or C-terminus of HSPB7 leads to absence of mineralization indicating that they are essential domains for osteogenesis. Our data indicate Activin A as a downstream target in the HSPB7 cascade controlling osteogenic differentiation. These findings pave the way for the identification of molecular switches, which mediate the inverse relationship between osteogenesis and adipogenesis when designing therapeutic strategies toward lineage commitment-related diseases.Fig. 8 A schematic diagram of HSPB7-regulated osteogenesis and adipogenesis. HSPB7 regulates the osteogenic differentiation through Activin A
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| 153 |
+
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| 154 |
+
HSPB7 was discovered as a cardiovascular-related chaperone, but recent studies revealed that HSPB7 participates in several physiological and pathological processes as it is ubiquitously expressed in other tissues than originally anticipated [30]. In addition to the high expression profile in heart and muscle, HSPB7 is strongly upregulated during osteogenic differentiation especially in late stages compared with undifferentiation stage (day 0). Structurally, HSPB7 forms hetero-oligomeric complexes with HSPB8 through interaction of their C-termini [34]. Downregulation of HSPB8 led to reduction of ALP activity and mineral deposition, as well as the expression of osteogenic markers in dental pulp stem cell [22]. Therefore, it is plausible to speculate that similar functional characteristics and activities could be shared between HSPB7 and HSPB8 in MSCs. Our observations following HSPB7 knockdown and osteogenic differentiation are in line with this notion and demonstrate an important function for HSPB7 in osteogenesis. In addition, the positive role of HSPB7 in osteogenesis and mineralization is further supported by our overexpression studies.
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| 155 |
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| 156 |
+
It has been demonstrated that adipocyte induction factors suppress osteogenesis, and conversely, osteoblast induction factors hamper adipogenesis [18]. In fact, various external cues including physical, chemical and biological signals could influence the balance between adipogenic and osteogenic differentiation. In this study, we showed that knockdown of HSPB7 increases adipogenic competency by promoting PPARγ and C/EBPα, which are master regulators of the adipocyte phenotype. Consistent with our findings, the expression of PPARγ and C/EBPα are maintained at high levels throughout the entire differentiation process and cooperate to regulate a number of adipogenic proteins such as FABP4 and Perilipin-1 [18, 35]. In addition, PPARγ is involved in de novo lipogenesis by mediating Acetyl-CoA carboxylase [36], which acts as a rate-limiting enzyme and catalyzes the production of malonyl-CoA used as an essential substrate for Fatty acid synthase. The disruption of HSPB7 has no direct impact on cell number in the adipogenic condition, highlighting that HSPB7 acts directly on differentiation and lipid synthesis in the adipocytes. Of note, as opposed to HSPB7 overexpression not affecting cell proliferation, HSPB7 silencing slowed down cell proliferation, suggesting that different mechanisms are involved in HSPB7-mediated osteogenesis. In contrast to our observations that knockdown of HSPB7 enhances adipogenic differentiation and impairs osteogenic differentiation, Jin et al. [20] observed the opposite trend in adipogenesis and osteogenesis using human adipose tissue-derived stem cells. The discrepant observation with our work may, apart from differences in methodologies, be due to different molecular mechanisms underlying the lineage commitment process between BMSCs versus adipose tissue-derived MSCs (ASC), as ASCs have significantly higher adipogenic capacity, while BMSCs have pronounced osteogenic capacity shown in a donor-matched study [37]. Collectively, our data demonstrate a role for HSPB7 in balancing the osteoblast and adipocyte differentiation potential from bone marrow MSCs.
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| 157 |
+
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| 158 |
+
A number of studies have demonstrated that actin filament-mediated cell shape changes are required for MSC differentiation [38, 39]. Moreover, actin has roles in determining nuclear shape, cell spreading, and cell stiffness, which eventually influence MSC fate decision [15]. In this study, we observed aberrant actin filament networks along with disrupted osteogenic differentiation and mineralization induced by HSPB7 silencing. Remarkably, rather than the classic cuboidal-shaped osteoblasts with actin stress fibers, BMSCs developed a spindle shape-like fibroblast morphology with thin microfilaments across the cytoplasm after 14 days of osteogenic induction in the absence of HSPB7. Consistent with our findings, genetic studies have reported that cardiacspecific deficiency of Hspb7 in mice show longer actin/thin filaments with abnormal actin filament bundles in sarcomeres, which is a contractile unit of striated muscle [40]. In addition, loss of HSPB7 in mouse cardiomyocytes upregulates the expression of Connexin43, which plays a critical role in osteogenesis and cell–cell communication in the skeleton [41, 42].
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| 159 |
+
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| 160 |
+
It has been reported that HSPB7 is the most potent molecular chaperone among the sHSP family in suppressing the aggregation of polyglutamine-containing proteins, which cause neurodegenerative conditions including Huntington’s disease and Kennedy’s disease [30], and most importantly, this anti-aggregation function is conserved among species [43]. The main structural hallmarks that make HSPB7 unique within the sHSP family are the SRS located near the N-terminus (13 amino acids) and the conserved C-terminal region composed of 9 residues [30]. The complete deletion of the N-terminal domain leads to the abrogation of its activity, suggesting the indispensable role for this protein domain [30]. Based on these previous findings, we generated different deletion constructs and investigated which parts of HSPB7 were required for osteoblastic differentiation and mineralization. Although the mechanism in promoting osteogenesis is probably different from neurodegenerative diseases, the deletion of the N-terminus renders the protein less functional, abrogating osteogenic stimulation induced by full-length HSPB7. In contrast to the negligible role of the C-terminal deletion in Huntington’s disease [30], our data shows that the osteogenic effect as indicated by ALP activity and calcium deposition, were less strong following deletion of the SRS in comparison with full-length HSPB7, despite increased amounts of protein. These results further underscore the structural importance of these specific domains within HSPB7.
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| 161 |
+
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| 162 |
+
Mechanistically, we found that Activin A is a downstream target of HSPB7-mediated osteogenic effects as knockdown of HSPB7 resulted in upregulation of Activin A expression. On the basis of these data, it can be hypothesized that HSPB7 stimulates the osteogenic capacity through mediating Activin A expression. This hypothesis is substantiated by the changes in expression levels of ECM genes. The altered ECM composition could impair the production of matrix vesicles, and further osteoblast mineralization [32]. In addition, blocking Activin A activity either by SB431542 [44], a selective inhibitor of Activin A signaling or by a neutralizing antibody treatment, rescued osteoblast mineralization suppressed by HSPB7 silencing. These findings are in accordance with previous reports that Activin A treatment suppresses osteogenesis leading to changes in ECM gene expression and significant reduction of the mineralization capacity [32, 45]. However, we did not observe difference in expression levels of Activin A following HSPB7 overexpression. Future studies are needed to investigate the molecular machinery between HSBP7 and Activin A, and to determine the extent to which Activin A is involved in HSPB7-enhanced osteogenesis.
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| 163 |
+
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| 164 |
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Conclusions
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| 165 |
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|
| 166 |
+
Osteoporosis is one of the most common bone metabolic diseases partially caused by aberrant lineage specification of BMSCs [46]. This abnormal lineage commitment is characterized by diminished osteoblast formation accompanied by excessive adipocyte accumulation in the bone marrow cavity [47, 48]. In this study, we revealed that HSPB7 plays a positive role in driving osteoblastic differentiation, and with the capability in maintaining the osteo-adipogenesis balance involving cytoskeletal changes and interplay with Activin A and modulation of ECM, it holds great promise as a potential therapeutic target in bone metabolic diseases and further supports a role for the sHSPs family in stem cell control and differentiation.
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| 167 |
+
|
| 168 |
+
Supplementary Information
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| 169 |
+
|
| 170 |
+
Additional file 1: Table S1. List of shRNAs used for HSPB7. Table S2. Primer sequences used to generate deletion constructs. Table S3. Primer sequences used for q-RT PCR in this study
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| 171 |
+
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| 172 |
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Additional file 2: Fig. S1. HSPB7 silencing in BMSCs affects cell viability. Cell viability was evaluated following HSPB7 knockdown or HSPB7 overexpression in the presence of osteogenic induction at indicated time points using CCK-8 assay. Data are presented as means ± SEM and analyzed by two-way ANOVA followed by post-hoc testing.
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| 173 |
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| 174 |
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Additional file 3: Fig. S2. HSPB7 silencing in BMSCs affects cytoskeleton reorganization. A–C Representative images of immunostaining for F-actin, α-tubulin and nuclei at day 3, day 7 and day 20 following osteogenic induction. Arrows indicate spindle-shaped fibroblast-like cells. Scale bars: 200 μm.
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| 175 |
+
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| 176 |
+
Additional file 4: Fig. S3. HSPB7 gene expression of lentivirally transduced deletion constructs. A–B HSPB7 mRNA expression was assessed by qRT-PCR following transduction with deletion constructs. His primers were used to amplify exogenous expression of HSPB7, while primers targeting coding DNA sequence were used to amplify both endogenous and exogenous expression of HSPB7. Data are presented as means ± SEM and analyzed by one-way ANOVA followed by post-hoc testing.
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| 177 |
+
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| 178 |
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Additional file 5: Fig. S4. Overexpression of HSPB7 deletion mutants have similar intercellular localization as full-length HSPB7. BMSCs expressing the indicated deletion constructs were immunostained with His and F-actin, and nuclei after 3 days osteogenic induction. Scale bars: 200 μm.
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| 179 |
+
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| 180 |
+
Additional file 6: Fig. S5. Overexpression of HSPB7 affects the expression of extracellular matrix genes. A INHBA mRNA expression was assessed by qRT-PCR following HSPB7 overexpression at multiple time points. B–C Representative images and quantitative expression of activin A were assessed by Western blot at day 14 and day 21 following osteogenic induction. Full-length blots are presented in Additional file 7: Fig. S6. D ECM genes were evaluated by qRT-PCR following HSPB7 overexpression at day 13 and day 20. Data are presented as means ± SEM and analyzed by one-way ANOVA followed by post-hoc testing or two-tailed Student’s t-test.
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| 181 |
+
|
| 182 |
+
Additional file 7: Fig. S6 Full-length blots.
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| 183 |
+
|
| 184 |
+
Abbreviations
|
| 185 |
+
|
| 186 |
+
BMSC Bone marrow-derived mesenchymal stromal cells
|
| 187 |
+
|
| 188 |
+
sHSPs Small heat shock proteins
|
| 189 |
+
|
| 190 |
+
VEGF Vascular endothelial growth factors
|
| 191 |
+
|
| 192 |
+
TGF Transforming growth factor
|
| 193 |
+
|
| 194 |
+
FGF Fibroblast growth factor
|
| 195 |
+
|
| 196 |
+
α-MEM Alpha minimum essential medium
|
| 197 |
+
|
| 198 |
+
PBS Phosphate-buffered saline
|
| 199 |
+
|
| 200 |
+
shRNA Short hairpin RNA
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| 201 |
+
|
| 202 |
+
RT Room temperature
|
| 203 |
+
|
| 204 |
+
ALP Alkaline phosphatase
|
| 205 |
+
|
| 206 |
+
pNPP p-Nitrophenyl phosphate
|
| 207 |
+
|
| 208 |
+
pNP p-Nitrophenol
|
| 209 |
+
|
| 210 |
+
PPARγ Proliferator-activated receptor gamma
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| 211 |
+
|
| 212 |
+
C/EBPα CCAAT/enhancer binding protein alpha
|
| 213 |
+
|
| 214 |
+
FABP4 Fatty acid binding protein 4
|
| 215 |
+
|
| 216 |
+
FASN Fatty acid synthase
|
| 217 |
+
|
| 218 |
+
ACC Acetyl-CoA carboxylase
|
| 219 |
+
|
| 220 |
+
ΔN N-Terminal domain deletion
|
| 221 |
+
|
| 222 |
+
ΔC C-Terminal domain deletion
|
| 223 |
+
|
| 224 |
+
ΔSRS Serine-rich stretch sequence deletion
|
| 225 |
+
|
| 226 |
+
ECM Extracellular matrix
|
| 227 |
+
|
| 228 |
+
ASC Adipose tissue-derived mesenchymal stromal cells
|
| 229 |
+
|
| 230 |
+
Acknowledgements
|
| 231 |
+
|
| 232 |
+
We thank Dr. Harm H. Kampinga from the department of Cell Biology at the University of Groningen for discussing the generation of HSPB7 constructs for this work.
|
| 233 |
+
|
| 234 |
+
Author contributions
|
| 235 |
+
|
| 236 |
+
SZ, JP, JL, and BE designed the studies. SZ, MK performed experiments and interpreted data. SZ wrote the manuscript. All authors read and approved the manuscript.
|
| 237 |
+
|
| 238 |
+
Funding
|
| 239 |
+
|
| 240 |
+
Shuang Zhang is supported by the China Scholarship Council through a PhD Research Fellowship Grant (No. 201709370052).
|
| 241 |
+
|
| 242 |
+
Availability of data and materials
|
| 243 |
+
|
| 244 |
+
The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.
|
| 245 |
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| 246 |
+
Declarations
|
| 247 |
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|
| 248 |
+
Ethics approval and consent to participate
|
| 249 |
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|
| 250 |
+
Not applicable as only commercially available materials are being used in this study (This also includes the human MSCs, which are derived from Lonza).
|
| 251 |
+
|
| 252 |
+
Consent for publication
|
| 253 |
+
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| 254 |
+
Not applicable.
|
| 255 |
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| 256 |
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Competing interests
|
| 257 |
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|
| 258 |
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The authors declare no competing interests.
|
| 259 |
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| 260 |
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Publisher's Note
|
| 261 |
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| 262 |
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Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
|
| 263 |
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==== Refs
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| 314 |
+
|
puc/PMC10183792.txt
ADDED
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Mol Cells
|
| 4 |
+
Mol Cells
|
| 5 |
+
Molecules and Cells
|
| 6 |
+
1016-8478
|
| 7 |
+
0219-1032
|
| 8 |
+
Korean Society for Molecular and Cellular Biology
|
| 9 |
+
|
| 10 |
+
37170770
|
| 11 |
+
10.14348/molcells.2023.2195
|
| 12 |
+
molce-46-5-268
|
| 13 |
+
Minireview
|
| 14 |
+
The Role of Splicing Factors in Adipogenesis and Thermogenesis
|
| 15 |
+
https://orcid.org/0009-0004-2841-6363
|
| 16 |
+
Naing Yadanar Than
|
| 17 |
+
https://orcid.org/0000-0003-3937-941X
|
| 18 |
+
Sun Lei *
|
| 19 |
+
Cardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, Singapore 169857
|
| 20 |
+
* Correspondence: sun.lei@duke-nus.edu.sg
|
| 21 |
+
31 5 2023
|
| 22 |
+
2 4 2023
|
| 23 |
+
2 4 2023
|
| 24 |
+
46 5 268277
|
| 25 |
+
27 12 2022
|
| 26 |
+
27 2 2023
|
| 27 |
+
3 3 2023
|
| 28 |
+
© The Korean Society for Molecular and Cellular Biology. All rights reserved.
|
| 29 |
+
2023
|
| 30 |
+
https://creativecommons.org/licenses/by-nc-sa/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/
|
| 31 |
+
Obesity is a significant global health risk that can cause a range of serious metabolic problems, such as type 2 diabetes and cardiovascular diseases. Adipose tissue plays a pivotal role in regulating energy and lipid storage. New research has underlined the crucial role of splicing factors in the physiological and functional regulation of adipose tissue. By generating multiple transcripts from a single gene, alternative splicing allows for a greater diversity of the proteome and transcriptome, which subsequently influence adipocyte development and metabolism. In this review, we provide an outlook on the part of splicing factors in adipogenesis and thermogenesis, and investigate how the different spliced isoforms can affect the development and function of adipose tissue.
|
| 32 |
+
|
| 33 |
+
adipogenesis
|
| 34 |
+
adipose tissue
|
| 35 |
+
splicing
|
| 36 |
+
splicing factors
|
| 37 |
+
thermogenesis
|
| 38 |
+
thermogenic adipocytes
|
| 39 |
+
==== Body
|
| 40 |
+
pmcINTRODUCTION
|
| 41 |
+
|
| 42 |
+
Adipose tissue is a vital metabolic organ and plays a critical role in energy homeostasis by coordinating lipogenesis, lipolysis, and fatty acid oxidation. Adipose tissue also functions as an endocrine organ by secreting adipose tissue-derived hormones, such as leptin and adiponectin (Hui et al., 2015; Trayhurn et al., 1999). There are at least three major adipose tissues, distinct anatomically and physiologically: white adipose tissue (WAT), brown adipose tissue (BAT), and beige adipose tissue. While WAT is specialized for modulating lipid storage, beige and BAT contribute to energy expenditure through Ucp1-dependent and -independent thermogenesis (Sakers et al., 2022).
|
| 43 |
+
|
| 44 |
+
Adipose tissue dysfunction underlies the development of many metabolic disorders such as obesity, insulin resistance, type 2 diabetes, atherogenic dyslipidemia, non-alcoholic fatty liver disease and cardiovascular diseases (Gesta et al., 2007). Adipose tissue can increase its mass through two mechanisms: hyperplasia (increased adipocyte numbers) and hypertrophy (increased adipocyte size). The hyperplastic WAT has a relatively mild detrimental effect on metabolic health, as adipocytes maintain normal metabolic function. In contrast, the hypertrophic WAT is often accompanied by adipocyte dysfunction and contributes more to metabolic abnormalities (Morigny et al., 2021). Beige and BAT, known as thermogenic adipocytes, are distinguished from WAT in their multilocular lipid droplets, higher mitochondrial activity, and abundant expression of the uncoupling protein 1 (UCP1). Beige adipocytes are dispersed in subcutaneous WAT and resemble white adipocyte morphology under a dormant state. However, they are activated upon cold or adrenergic stimulation to take on brown adipocyte-like appearances and functions (Sakers et al., 2022). It was reported that a reduced mass and activity of thermogenic adipose tissues could contribute to the development of obesity (Becher et al., 2021).
|
| 45 |
+
|
| 46 |
+
To date, an increasing number of studies indicate that alternative splicing plays an essential role in adipocyte biology (Chao et al., 2021). Most transcripts in mammals undergo splicing, a post-transcriptional mechanism that has evolved to expand protein diversity. Splicing can be largely classified into a few types, including exon inclusion/exclusion, intron retention, mutual exclusion of adjacent exons, or alternation in 5′ or 3′ splice sites (Pan et al., 2008). Alternative splicing is executed by spliceosome (U1, SF1, U2AF1, U2AF2), the core machinery of splicing (U4/U6 and U5), together with splicing factors (Chao et al., 2021; Ule et al., 2019) (Fig. 1) that often modulate the core splicing machinery by affecting their site specificity (Hang et al., 2015; Lim et al., 2011; Liu et al., 2017). Splicing factors are RNA binding proteins that act as activators or repressors of splicing by binding to pre-mRNA exonic or intronic enhancer or silencer elements (Fig. 1). Splicing factors are reported to play essential roles in cell differentiation, tissue identity, and organ development (Baralle and Giudice, 2017), and their functions in adipocytes are being increasingly appreciated. Some excellent reviews have been covered on implication of splicing in adipogenesis and obesity (Chao et al., 2021; Wong et al., 2018). This review will focus on the splicing factors involved in adipogenesis and thermogenesis. These studies are providing important new insights into the mechanism of obesity and related metabolic abnormalities.
|
| 47 |
+
|
| 48 |
+
SPLICING FACTORS IN ADIPOGENESIS
|
| 49 |
+
|
| 50 |
+
SRC associated with mitosis of 68 kDa (Sam68)
|
| 51 |
+
|
| 52 |
+
Sam68 recognizes the 5′-[AU] UAA-3′ rich regions and promotes exon inclusion (Feracci et al., 2016; Lin et al., 1997; Ray et al., 2009). Sam68 has been reported to promote mTOR splicing by interacting with U1 snRNP (small nuclear ribonucleoprotein) in mouse embryonic fibroblast (Subramania et al., 2019). It also contributes the exon 7 skipping of survival of motor neuron 2 (SMN2) in spinal muscle atrophy and regulates alternative exon splicing in neurogenesis (Chawla et al., 2009; Pedrotti et al., 2010).
|
| 53 |
+
|
| 54 |
+
Several recent studies have shown that Sam68 regulates adipogenesis via alternative splicing of mTOR and S6K1 mRNA (Huot et al., 2012; Song and Richard, 2015). Huot et al. (2012) showed that Sam68−/− mice developed lower body mass with fewer adipogenic progenitors. The deletion of Sam68 protected mice from diet-induced obesity due to increased energy expenditure and impaired white adipocyte differentiation with reduced Pparγ expression and lipid accumulation (Huot et al., 2012). The phenotypes of Sam68 knockout may be partially explained by the influence of Sam68 on mTOR splicing in WAT. Huot et al. (2012) reported an increased retention of intron 5 in mTOR transcript (mTORi5) and a decreased mTOR protein expression in WAT of Sam68 deficient mice. Mechanistically, the intron retention of intron 5 can produce a premature stop codon and unstable mTOR transcripts (Figs. 2A and 2B, Fig. 3). Knockdown of Sam68 using RNA interference in 3T3-L1 preadipocytes impaired insulin-stimulated Akt phosphorylation and inhibited adipocyte differentiation. Ectopic expression of a full-length mTOR transcript in the Sam68-depleted 3T3-L1 cells partially rescued the impaired adipogenesis, supporting that the dysregulated mTOR splicing is a key downstream event of Sam68 deficiency (Huot et al., 2012).
|
| 55 |
+
|
| 56 |
+
However, the full-length mTOR protein could not fully rescue the effects from Sam68 ablation on adipogenesis as Sam68 also regulates the alternative splicing of many other transcripts including S6K1 (Song and Richard, 2015). Rps6kb1, the gene encoded for S6K1 proteins, produced three isoforms: p70S6K, p85S6K, and p31S6K (Tavares et al., 2015). Song and Richard (2015) showed that knockdown of Sam68 in 3T3-L1 cells and Sam68 knockout in WAT increased the expression of p31S6K (Rps6kb1-002), a truncated protein lacking the region of mTOR- and PDK-phosphorylation (Ben-Hur et al., 2013) (Figs. 2C and 2D, Fig. 3). Interestingly, ectopic expression of p31S6K in 3T3-L1 impaired adipogenesis by lowing lipid storage and inhibiting the expression of Pparγ, CEPBα and Glut4. To further support this, the author proved that p31S6K depletion by siRNA in Sam68-deficient 3T3-L1 cells enhanced the lipid accumulation and the expression of differentiation markers. Thus, the reduced adipogenesis in Sam68 deficient cells was partially rescued by the loss of p31S6K expression (Song and Richard, 2015). Using cross linking and immunoprecipitation (CLIP) assays in preadipocytes, the authors showed Sam68 can bind to the intron 6 of Rps6kb1 transcript, preventing Serine/arginine-rich splicing factor 1 (SRSF1) from this region and facilitating the canonical Rps6kb1 splicing. In the absence of Sam68, SRSF1 recognizes exon 6 and promotes the inclusion of three extra exons to generate the p31S6K-encoding isoform (Song and Richard, 2015). Taken together, Sam68 regulates adipogenesis at least partially via alternative splicing of mTOR and S6K1 mRNAs. However, whether Sam68 regulates other mRNAs and how other targets influence adipogenesis remains unclear.
|
| 57 |
+
|
| 58 |
+
Serine arginine rich splicing factor 1 (SRSF1)
|
| 59 |
+
|
| 60 |
+
SRSF1, also referred to as SF2/ASF, has multiple functional impacts, including nonsense-mediated mRNA decay (NMD), mRNA nuclear transport, mRNA translation, miRNA processing, genome stability, chromatin association, protein sumoylation, and nuclear stress (Das and Krainer, 2014; Karni et al., 2007; Loomis et al., 2009; Pelisch et al., 2010; Pradeepa et al., 2012). SRSF1 plays a pivotal role in adipocyte biology by regulating the alternative splicing events of Rps6kb1 and Pparγ (Aprile et al., 2018; Karni et al., 2007; Song and Richard, 2015) (Figs. 2C-2F, Fig. 3). As discussed above, SRSF1 enhances the inclusion of three extra exons between exons 6 and 7 and favours the formation of Rps6kb1-002 transcript which encodes p31S6K, a truncated S6K1 lacking the region of mTOR and PDK-phosphorylating (Fig. 2D, Fig. 3). SRSF1 knockdown with siRNA in both HEK293 and 3T3-L1 cells reduced the P31S6K expression. Overexpression of P31S6K in 3T3-L1 cells impaired adipogenesis with decreased lipid accumulation and lower expression of Pparγ, C/EBPα and GLUT4. Conversely, siRNA knockdown of P31S6K enhanced the lipid accumulation in 3T3-L1 cells where Sam68 was knocked down (Song and Richard, 2015).
|
| 61 |
+
|
| 62 |
+
SRSF1 regulates the alternative splicing of Pparγ, the master regulator of adipocyte biology (Figs. 2E and 2F, Fig. 3). Aprile et al. (2018) reported that Pparγ expresses several natural isoforms and one of them excludes exon 5, referred to as PparγΔ5, which lacks the ligand-binding domain. Overexpressing PparγΔ5 in hTERT-immortalized adipose tissue-derived human mesenchymal stem cells (hMSCs) and primary human adipocyte progenitors negatively impacted adipogenesis with decreased lipid accumulation during differentiation, showing a negative role of PparγΔ5 on adipogenesis. In addition, SRSF1 ablation using siRNA alleviated the production of PparγΔ5 in hMSCs. The regulation of SRSF1 on Pparγ splicing is not limited to adipocytes since siRNAs knockdown of SRSF1 in HEK293cells can also enhance the exon 5 inclusion and reduce the production of PparγΔ5. CLIP-seq in HEK293 cells revealed a SRSF1-binding site in Pparγ exon 6, and the binding was confirmed by RNA immunoprecipitation (RIP) using anti-SRSF1. Taken together, SRSF1 is likely to negatively regulate adipogenesis by enhancing the p31S6k1 protein and PparγΔ5 expression.
|
| 63 |
+
|
| 64 |
+
Serine arginine rich splicing factor 10 (SRSF10)
|
| 65 |
+
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| 66 |
+
SRSF10 plays a critical role in tumour cell growth and glucose metabolisms (Wei et al., 2015; Zhou et al., 2014). In Hela cells, the function of SRSF10 is regulated by its phosphorylation state as its acts as a splicing repressor upon dephosphorylation (Cowper et al., 2001; Shin et al., 2004). Whole body SRSF10 knockout mice could not survive beyond the embryonic stage due to several cardiac defects, highlighting SRSF10 as a vital splicing factor (Feng et al., 2009).
|
| 67 |
+
|
| 68 |
+
Li et al. (2014) showed an impairment of axillary subcutaneous WAT development in SRSF10 knockout embryonic mice besides heart defects. SRSF10 knockout primary MEF cells exhibit decreased adipogenic capacity and lowered PPARγ and Adiponectin expressions. Consistently, shRNA SRSF10 knockdown in C3H10T1/2 resulted in down-regulated expression of Pparγ and Adiponectin and impaired lipid accumulation during C3H10T1/2 differentiation (Li et al., 2014). They further showed that SRSF10 binds to exon 8 of lipin1 in a sequence specific manner by 32P-labeled RNAs -gel shift assay and causes exon-skipping of exon 7 in primary MEF cells to favour the production of Lipin1α (Figs. 2G and 2H, Fig. 3). Conversely, knockdown of SRSF10 in C3H10T1/2 cells increased Lipin1β relative to Lipin1α. Overexpressing Lipin1α and Lipin1β respectively in SRSF10 knockdown C3H10T1/2 cells showed Lipin1α can rescue adipogenesis more efficiently than Lipin1β, evidenced by more lipid accumulation and higher expressions of Pparγ and Adiponectin in Lipin1α-infected cells (Li et al., 2014). Thus, the decreased usage of Lipin1α isoform may partially account for the comprised adipogenesis in SRSF10-deficient cells.
|
| 69 |
+
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| 70 |
+
Transformer 2 (Tra2)
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| 71 |
+
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| 72 |
+
Tra2, a regulator of sex determination in Drosophila, was reported as a sequence-specific splicing factor in Hela cells (Tacke et al., 1998). Mikoluk et al. (2018) showed that siRNA-mediated Tra2a knockdown in female Drosophila resulted in an increased fat body and longer survival rates on starvation. Tra2a deficiency can induce the usage of CPT1-6β over CPT1-6α (Fig. 3). As CPT1-6β is the less active in catalysing the formation of acyl carnitines, the Tra2a deficiency-induced CPT1-6β usage may lead to lower β-oxidation activity, resulting in increased lipid storage (Mikoluk et al., 2018).
|
| 73 |
+
|
| 74 |
+
Tra2b, also known as SFRS10, is a vital splicing factor, as the whole body Tra2b knockout caused embryonically lethal in mice (Pihlajamäki et al., 2011). Tra2b was reported to regulate alternative splicing of Wnt 11b in Xenopus, and lipin1 alternative splicing in HepG2 cells (Dichmann et al., 2015; Pihlajamäki et al., 2011). Patel et al. (2014) showed that Tra2b can regulate alternative splicing of PKCδ in 3T3-L1 cells to modulate the usage of PKCδ-1 (Patel et al., 2014), an apoptotic isoform, and PKCδ-2, a cell survival isoform (Figs. 2I and 2J, Fig. 3). Tra2b knockdown resulted in a decrease in PKCδ-1 while Tra2b overexpression increased the usage of PKCδ-1 in 3T3-L1 cells. The authors further utilized minigene and RIP assays to confirm that Tra2b regulated PKCδ splicing by affecting the 5′ splice site selection of the intron 9 (Patel et al., 2014) (Figs. 2I and 2J, Fig. 3). Consistent with these findings, during 3T3-L1 cell differentiation, the expression of Tra2b is gradually decreased, concomitant with a switch from PKCδ-1 to PKCδ-2. What about the role of PKCδ-1 in adipogenesis? siRNA knockdown of PKCδ-1 at day 1 of differentiation improved lipid accumulation and the expression of Pparγ and Adiponectin during the subsequent differentiation (Patel et al., 2014). Carter et al. (2013) reported that the preadipocytes from subcutaneous and omental adipose tissue of obese individuals showed a decrease in PKCδ-1 relative to PKCδ-2, which may partially explain their higher resistance to apoptosis than the preadipocytes from lean individuals. Thus, the Tra2b is likely to exert a negative influence on 3T3-L1 adipogenesis through favouring the generation of PKCδ-1 isoform, although the function of Tra2b in adipogenesis was not tested directly in these studies.
|
| 75 |
+
|
| 76 |
+
SPLICING FACTORS IN THERMOGENIC ADIPOCYTES
|
| 77 |
+
|
| 78 |
+
RNA binding motif protein 4a (RBM4a) and polypyrimidine tract binding proteins (PTBP)
|
| 79 |
+
|
| 80 |
+
RBM4a was reported to regulate alternative splicing events in malignant cells as well as in cells differentiation. It acts as a splicing regulator of several other splicing factors such as MBNL1, PTBP1, PTBP2, NOVA1 and SRSF3 (Lin et al., 2016a; 2016b; Lin and Tarn, 2011; Peng et al., 2018; Wang et al., 2014). RBM4a whole-body knockout mice displayed low insulin production and hyperglycaemia phenotypes (Lin et al., 2013). The expression of RBM4a is gradually increased along BAT differentiation, implying a role of RBM4a in BAT development. Indeed, the BAT of RBM4a deficient mice exhibited lower levels of brown adipocyte markers such as Myf5, Bmp7, Prdm16, and Ucp1. Furthermore, RBM4a-deficient BAT developed impaired lipid accumulation, decreased oxygen consumption, and reduced energy expenditure. Conversely, RBM4a overexpression in C3H10T1/2 cells enhances the expression of brown adipocyte markers and oxygen consumption rates (OCRs) (Lin et al., 2014).
|
| 81 |
+
|
| 82 |
+
The transcriptome profiling analysis of postnatal RBM4a KO BATs showed differential alternative splicing patterns of 186 genes (Lin et al., 2016a). One of the RBM4a-regulated alternative splicing events in adipose tissue occurs in Prdm16 (PR domain containing 16) (Figs. 4A and 4B, Fig. 5). Prdm16 is a BAT-enriched protein and play a key role in brown and beige adipocytes development (Cohen et al., 2014; Harms et al., 2014). Prdm16 expresses an exon 16-exclusive isoform (Prdm16S) and an exon 16-inclusive long (Prdm16L) isoform. Chi and Lin (2018) reported that overexpressing RBM4a enhanced the usage of Prdm16S while shRNA knockdown of RBM4a promoted the usage of Prdm16L isoform in C3H10T1/2. Prdm16S has a stronger effect on inducing the expression of PGC1-α and C/EBP-β than Prdm16L during the adipogenic differentiation of C3H10T1/2. Consistently, Prdm16S is also more effective in promoting OCR, ATP production, and lipid droplet formation than Prdm16L. Therefore, RBM4a-mediated Prdm16 isoform usage may be a critical mechanism to sustain BAT adipogenesis and thermogenesis (Chi and Lin, 2018).
|
| 83 |
+
|
| 84 |
+
Given the prominent phenotype of BAT defect in RBM4a knockout mice, it is no surprising to find that RBM4a targets some key BAT/beige regulators such as Prdm16. However, it is more intriguing that it also regulates some the splicing of some other splicing factors such as MBNL1 (Hung and Lin, 2020), PTBP (Lin et al., 2016b), and Nova1 (Lin et al., 2016a). Hung and Lin (2020) reported that RBM4a repressed MBNL1 exon 5 inclusion during BATs development in vivo and 3T3-L1 differentiation (Figs. 4C and 4D, Fig. 5). RBM4a knockout enhanced the inclusion of exon 5 of MBNL1 in BAT and siRNA-mediated RBM4a knockdown in 3T3-L1 increased the usage of the MBNL1+exon5 isoform. Conversely, overexpressing the MBNL1-exon5 isoform during 3T3-L1 differentiation, compared to the MBNL1+exon5 isoform, induced a more prominent effect on beige cell-related splicing events, expression of Prdm16 and UCP1, lipid accumulation, and oxygen consumption (Hung and Lin, 2020). Thus, RBM4a can regulate brown adipogenesis at least partially by modulating the alternative splicing of MBNL1 exon 5 skipping.
|
| 85 |
+
|
| 86 |
+
PTBP proteins are known to be involved in alternative splicing of pyruvate kinase in C2C12 cells, NIH-3T3 cells and Brain Tumour cells (David et al., 2010). PTBP has two paralogous genes PTBP1 and PTBP2. Each of these two genes can generate an NMD transcript, PTBP1-exon11 (exon 11 skipping) and PTBP2-exon10 (exon 10 skipping), respectively, and the usage of both isoforms increase from embryonic to neonatal BAT. RBM4a depletion promotes the usage of the canonical PTBP1 and PTBP2 transcripts during BAT development (Lin et al., 2016b), while RBM4a overexpression in C3H10T1/2 cells represses the usage of PTBP1 and PTBP2 canonical splicing by promoting exon 11 and exon 10 skipping, respectively, in C3H10T1/2 (Figs. 4E and 4G). Furthermore, the authors showed that PTBP2 overexpression reduced the Prdm16 and UCP1 transcripts during adipogenic differentiation of C3H10T1/2. Conversely, shRNA-mediated PTBP2 knockdown increased Pdrm16 and UCP1 expression and enhanced the lipid accumulation, which phenocopies RBM4a overexpression and suggests that PTBP2 is a major downstream effector of RBM4a.
|
| 87 |
+
|
| 88 |
+
A downstream target of PTBP2 is NOVA1. PTBP2 can bind to the 3′ UTR region of NOVA1 to stabilize the NOVA1 transcript, while the PTBP2 ablation destabilizes the NOVA1 mRNA. Overexpressing NOVA1 represses and shRNA-knockdown of NOVA1 promotes the expression of Prdm16 and Ucp1 in C3H10T1/2 cells, suggesting a negative role of NOVA1 in brown/beige adipogenesis (Lin et al., 2016a).
|
| 89 |
+
|
| 90 |
+
Based on the results described above, it is postulated that PTBP1 and RBM4a may play antagonistically roles in regulating BAT development at alternative splicing levels. While RBM4a is necessary for normal BAT development, PTBP functions as an adipogenic repressor (Chi and Lin, 2018; Lin et al., 2016b). However, further biochemistry analysis will be needed to illustrate the detailed molecular mechanism of how these factors regulate BAT development program.
|
| 91 |
+
|
| 92 |
+
Neuro oncological ventral antigen 1 (NOVA1)
|
| 93 |
+
|
| 94 |
+
NOVA1 recognizes RNA in a 5′-YCAY-3′ sequence-specific manner and was originally reported to play a critical role in neuronal viability (Jensen et al., 2000). Vernia et al. (2016) showed that NOVA is also an important regulator in adipose tissue thermogenesis. They analysed RNA splicing changes in adipose tissue during diet-induced obesity and connected the alternative splicing changes with NOVA1 splicing factor. To test the function of NOVA in adipose tissue, they generated adipose tissue-specific knockout mice to delete NOVA1 and NOVA2 at the same time. NOVA-deficient mice demonstrated increased adipose tissue thermogenesis and improved glycemia. During the cold challenge, high fat diet (HFD)-fed NOVA deficient mice had significantly less body and fat mass and higher core body temperature than the control mice at HFD (Vernia et al., 2016).
|
| 95 |
+
|
| 96 |
+
Authors suggested that NOVA may regulate adipose tissue thermogenesis by controlling the alternative splicing of Mapk8 (JNK1 protein kinase encoded gene) and Mapk9 (JNK2 protein kinase encoded gene) in beige adipocytes (Vernia et al., 2016) (Fig. 5, Figs. 6A and 6C). The NOVA-binding motif (YCAY) was found in the sequences around exon 7α and 7β of both Mapk8 and Mapk9 transcripts. NOVA knockout in adipose tissue caused an increase in the Mapk8α/β ratio and a decrease in the Mapk9α/β ratio, indicating that NOVA favours the usage Mapk8β (encodes JNK1β) and Mapk9α (encodes JNK2α) over the other isoform. Enzymic activity analysis using substrate c-Jun supported that JNK1β and JNK2α are the more active isoforms than Mapk8α-encoded JNK1α and Mapk9β-encoded JNK2β, respectively (Figs. 4A and 4C, Fig. 5). Consistently, NOVA KO adipocytes repressed the usage of Mapk8β (JNK1β) and Mapk9α (JNK2α) and showed markedly suppression in stress-induced phosphorylation of the JNK substrate pSer63 c-Jun. Knock-down of Mapk8β mRNA and Mapk9α mRNA using shRNA caused increased expression of the Prdm16 and Ucp1 genes in 3T3-L1 adipocytes, suggesting a negative role of Mapk8β mRNA and Mapk9α in brown adipogenesis. Overall, these studies suggest that NOVA is a suppressor of thermogenesis, partially by promoting the usage of Mapk8β (JNK1β) and Mapk9α (JNK2α) (Vernia et al., 2016).
|
| 97 |
+
|
| 98 |
+
Another study by Lin et al. (2016a) provides more evidence for the negative effects of NOVA on brown adipogenesis. The authors found that NOVA1 overexpression reduced the expression of brown adipogenesis markers CEBP, PGC-1, and UCP1 and reduced the number of mitochondria during C3H10T1/2 differentiation (Lin et al., 2016a).The authors showed that NOVA1 can enhance SRSF6 intron2 retention to silence SRSF6 function in C3H10T1/2 (Fig. 5, Figs. 6E and 6F). siRNA-mediated SRSF6 knockdown lowered the abundance of mitochondria and the overexpression of SRSF6 improved lipid accumulation and OCR during C3H10T1/2 adipogenesis (Lin et al., 2016a). Thus, NOVA1 plays a negative role in brown/beige adipogenesis by regulating multiple targets, but which targets may play more important roles than others warrant further investigations.
|
| 99 |
+
|
| 100 |
+
Serine arginine rich splicing factor 3 (SRSF3)
|
| 101 |
+
|
| 102 |
+
SRSF3 is a multifunctional RNA binding protein as it is involved in alternative splicing, transcriptional termination, alternative RNA polyadenylation, translational regulation, and RNA export (Guo et al., 2015). SRSF3 can bind to m6A-modified nucleotides and promote exon inclusion in 293 cells (Xiao et al., 2016). Interestingly, SRSF3 was reported to autoregulate its own splicing by enhancing the inclusion of its exon 4′ (an alternative exon between the classic exon 4 and exon 5) with an in-frame stop codon and this inclusion is impaired in oral squamous cell carcinoma cells (Guo et al., 2015).
|
| 103 |
+
|
| 104 |
+
SRSF3 is a negative regulator of brown adipogenesis, as shRNA-medicated SRSF3 knockdown resulted in elevated OCR and ATP production with up-regulated BAT markers such as Prdm16 and Ucp1, while SRSF3 overexpression reduced OCR, ATP, and BAT marker expression in C3H10T1/2 cells (Peng et al., 2018). The authors also observed an increase in SRSF3 exon 4′-containing transcript during BAT development and C3H10T1/2 differentiation. Interestingly, the inclusion of exon 4′ of SRSF3 is antagonistically catalysed by RBM4a and PTBP1 in C3H10T1/2 and BAT (Fig. 5, Figs. 7A and 7B). While RBM4a promotes exon 4′ inclusion by binding its intronic UUUCU element in postnatal BAT, PTBP1 represses this inclusion (Peng et al., 2018), which, again, supports an antagonistic role of RBM4a and PTBP1 in regulating the isoform usage program during brown adipogenesis. One of SRSF3��� targets is MAP4K4. SRSF3 binds the intron 17 of MAP4K4 and enhances its inclusion to form the isoform of MAP4K4-Iso-1 in BAT and C3H10T1/2 (Figs. 7C and 7D). Overexpression of MAP4K4-Iso-1 impaired OCR and ATP production during C3H10T1/2 differentiation. Thus, the SRSF3-mediated MAP4K4-Iso-1 production may partially explain the negative role of SRSF3 in brown adipogenesis (Peng et al., 2018).
|
| 105 |
+
|
| 106 |
+
CONCLUSION
|
| 107 |
+
|
| 108 |
+
Splicing factors are emerging as an essential class of regulators for adipocyte biology. The studies in the past decade have identified several splicing factors such as RBM4a, SRSF10, NOVA1 etc. that play regulatory roles in brown and white fat development. Moreover, several splicing events downstream these splicing factors were demonstrated to exert positive or negative influence on adipocyte differentiation. As expected, some of the downstream splicing events occur in known regulators of nutrient metabolism such as mTOR, Pparγ, Prdm16, etc. In addition, a significant portion of the downstream splicing events are also splicing factors such as MBNL1, PTBP2, NOVA1, etc. The regulated isoform usage of these splicing factors further affect adipocyte biology. These findings suggest a tentative model where splicing factors regulate the splicing of each other to form an interweaved network to regulate adipocyte development and metabolism, which is independent from but coordinated with gene expression-based regulations.
|
| 109 |
+
|
| 110 |
+
Several limitations were noted in earlier studies. First, most studies were conducted in cell lines in vitro and lack physiological relevance. Second, a majority of these studies focused on adipogenesis in white or brown/beige lineage, but the involvement of splicing factors or isoform usage events in complicated adipocyte metabolism in physiological and physiological contexts remain poorly explored. Last, while earlier studies have established the role of several specific splicing factor and splicing events in adipocytes, but how these factors and/or events are coordinated with each other and with the gene expression regulatory cascade in a spatiotemporal manner are unknown. These outstanding issues will need to be addressed in the future with more mouse genetic tools, deeper molecular biochemistry analysis, and more powerful high-throughput sequencing and bioinformatic analysis. Nonetheless, the studies about splicing in adipocytes have revealed important novel insights into the regulatory mechanism underlying adipocyte biology and will further provide the necessary information for developing new therapeutic approaches for clinical complications caused by adipose tissue dysfunction.
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| 111 |
+
|
| 112 |
+
Fig. 1 Schematic representation of splicing mechanisms in precursor messenger RNA (pre-mRNA).
|
| 113 |
+
|
| 114 |
+
The 5′ splice sites are recognized by U1, the branch points by SF1, the polypyrimidine tract by U2AF2, the 3′ splice sites by U2AF1. Tri snRNP (U4/U6 and U5) acts as the core catalytic machinery. Splicing factors regulate the spliceosome components recognition of 5′ and 3′ splice sites through binding to ESE, ESI, ISE, and ISI cis elements on pre mRNA. snRNP, small nuclear ribonucleoprotein.
|
| 115 |
+
|
| 116 |
+
Fig. 2 Schematic representation of canonical and alternative splicing of mTOR, ribosomal Rps6kb1, Pparγ, lipin1, and PKCδ in WAT.
|
| 117 |
+
|
| 118 |
+
(A) Sam68 binds to intron 5 and U1 binds to exon 5. Canonical mTOR transcript is produced. (B) mTORi5 is produced without Sam68. (C) Sam68 blinding to intron 5 blocks SRSF1 binding and canonical Rps6kb1 mRNA is expressed. (D) SRSF1 binds to exon 6 in the absence of Sam68 and Rps6kb1-002 transcript is produced. (E) SRSF1 binds to exon 6 of Pparγ and Pparγδ5 mRNA is produced. (F) Canonical Pparγ mRNA is formed in the absence of SRSF1. (G) SRSF10 binds to exon 8 and Lipin1α is produced. (H) Lipin1β mRNA is formed in the absence of SRSF10. (I) Tra2b binds to exon 9 of PKCδ and PKCδI is produced. (J) PKCδII is produced in the absence of Tra2b.
|
| 119 |
+
|
| 120 |
+
Fig. 3 Splicing factors and their targeted isoforms in adipogenesis.
|
| 121 |
+
|
| 122 |
+
Fig. 4 Schematic representation of canonical and alternative splicing of Prdm16, MBNL1 and PTBPs in BAT.
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| 123 |
+
|
| 124 |
+
(A) RBM4a binds to exon 16 and Prdm16S mRNA is produced. (B) PTBP1 binds to intron 16 in the absence of RBM4a and Prdm16L mRNA is formed. (C) RBM4a binds to exon 5 and MBNL-exon5 mRNA is produced. (D) Canonical MBNL1 transcript is formed in the absence of RBM4a. (E) RBM4a bind to exon 11 of PTBP1 pre mRNA and PTBP1-ex11 is produced. (F) Canonical PTBP1 transcript is produced in the absence of RBM4a. (G) RBM4a bind to exon 10 of PTBP2 pre mRNA and PTBP2-ex10 is produced. (H) Canonical PTBP2 transcript is produced in the absence of RBM4a. BAT, brown adipose tissue.
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| 125 |
+
|
| 126 |
+
Fig. 5 Splicing factors and their targeted isoforms in thermogenesis.
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| 127 |
+
|
| 128 |
+
Fig. 6 Schematic representation of the canonical and alternative splicing of Mapk8, Mapk9 and SRSF6 in BAT.
|
| 129 |
+
|
| 130 |
+
(A) NOVA1 binds to the intron 6, 7α and 7β and Mapk8β is produced. (B) Mapk8α is produced in the absence of NOVA1. (C) NOVA1 binds to the intron 6, 7α and 7β of Mapk9 and Mapk9α is produced. (D) Mapk9β is formed in the absence of NOVA1. (E) NOVA1 bind to intron 2 of SRSF6 and SRSF6+in2 is formed. (F) Canonical SRSF6 is produced in the absence of NOVA1. BAT, brown adipose tissue.
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| 131 |
+
|
| 132 |
+
Fig. 7 Schematic representation of alternative splicing of SRSF3 and MAP4K4 in BAT.
|
| 133 |
+
|
| 134 |
+
(A) PTBP1 binds to exon 4′ of SRSF3 and canonical SRSF3 transcript is produced in the absence of RBM4a. (B) RBM4a binds the intron 4′ and SRSF3-exon 4′ included transcripts is produced. (C) SRSF3 binds to intron 17 and MAP4K4-Iso1 is produced. (D) RBM4a binds to exon 17 and MAP4K4-Iso4 is produced. BAT, brown adipose tissue.
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| 135 |
+
|
| 136 |
+
AUTHOR CONTRIBUTIONS
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| 137 |
+
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| 138 |
+
Y.T.N. wrote the manuscript. L.S. provided expretise and feedback.
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| 139 |
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CONFLICT OF INTEREST
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| 142 |
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The authors have no potential conflicts of interest to disclose.
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==== Refs
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REFERENCES
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|
puc/PMC10202359.txt
ADDED
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Pérez Raúl F. 12345
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Urdinguio Rocío G. 2345
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Concellón Carmen 7
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Martínez-Chantar María Luz 89
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Fernández-Morera Juan Luis 2310
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Díaz-Quintana Antonio 6
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del Amo Vicente 7
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http://orcid.org/0000-0002-3792-4085
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Fernández Agustín F. agustin.fernandez@cinn.es
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12345
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http://orcid.org/0000-0001-8450-2603
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Fraga Mario F. mffraga@cinn.es
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12345
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1 grid.4711.3 0000 0001 2183 4846 Nanomaterials and Nanotechnology Research Center (CINN), Spanish National Research Council (CSIC), 33940 El Entrego, Spain
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2 Foundation for Biomedical Research and Innovation in Asturias (FINBA), 33011 Oviedo, Spain
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3 grid.511562.4 Health Research Institute of Asturias (ISPA), Av. del Hospital Universitario, 33011 Oviedo, Asturias Spain
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4 grid.10863.3c 0000 0001 2164 6351 University Institute of Oncology (IUOPA), University of Oviedo, 33006 Oviedo, Spain
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5 grid.452372.5 0000 0004 1791 1185 Center for Biomedical Network Research on Rare Diseases (CIBERER), 28029 Madrid, Spain
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6 grid.9224.d 0000 0001 2168 1229 Institute for Chemical Research (IIQ), Scientific Research Centre Isla de la Cartuja (cicCartuja), University of Seville – Spanish National Research Council (CSIC), Seville, Spain
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7 grid.10863.3c 0000 0001 2164 6351 Department of Organic and Inorganic Chemistry, University of Oviedo, Oviedo, Spain
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8 grid.420175.5 0000 0004 0639 2420 Liver Disease Lab, Center for Cooperative Research in Biosciences (CIC bioGUNE), Basque Research and Technology Alliance, Derio, Spain
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9 grid.452371.6 0000 0004 5930 4607 Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Carlos III National Health Institute, Madrid, Spain
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10 Endocrinology and Nutrition Department, Hospital Vital Alvarez Buylla (HVAB), 33611 Mieres, Spain
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22 5 2023
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22 5 2023
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2023
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13 82935 12 2022
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9 5 2023
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© The Author(s) 2023
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https://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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Obesity is associated with adipose tissue dysfunction through the differentiation and expansion of pre-adipocytes to adipocytes (hyperplasia) and/or increases in size of pre-existing adipocytes (hypertrophy). A cascade of transcriptional events coordinates the differentiation of pre-adipocytes into fully differentiated adipocytes; the process of adipogenesis. Although nicotinamide N-methyltransferase (NNMT) has been associated with obesity, how NNMT is regulated during adipogenesis, and the underlying regulatory mechanisms, remain undefined. In present study we used genetic and pharmacological approaches to elucidate the molecular signals driving NNMT activation and its role during adipogenesis. Firstly, we demonstrated that during the early phase of adipocyte differentiation NNMT is transactivated by CCAAT/Enhancer Binding Protein beta (CEBPB) in response to glucocorticoid (GC) induction. We found that Nnmt knockout, using CRISPR/Cas9 approach, impaired terminal adipogenesis by influencing the timing of cellular commitment and cell cycle exit during mitotic clonal expansion, as demonstrated by cell cycle analysis and RNA sequencing experiments. Biochemical and computational methods showed that a novel small molecule, called CC-410, stably binds to and highly specifically inhibits NNMT. CC-410 was, therefore, used to modulate protein activity during pre-adipocyte differentiation stages, demonstrating that, in line with the genetic approach, chemical inhibition of NNMT at the early stages of adipogenesis impairs terminal differentiation by deregulating the GC network. These congruent results conclusively demonstrate that NNMT is a key component of the GC-CEBP axis during the early stages of adipogenesis and could be a potential therapeutic target for both early-onset obesity and glucocorticoid-induced obesity.
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Subject terms
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Cell biology
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Chemical biology
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Molecular biology
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Health Institute Carlos III (Plan Nacional de I+D+I) co-funding FEDERPI18/01527 and PI21/01067 PI18/01527 and PI21/01067 Fernández Agustín F. Fraga Mario F. Spanish Association Against CancerPROYE18061FERN Fraga Mario F. Asturias Government (PCTI) co-funding 2018-2023/FEDERIDI/2018/146 and IDI/2021/000077 Fraga Mario F. issue-copyright-statement© Springer Nature Limited 2023
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==== Body
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pmcIntroduction
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Overweight and obesity are the fifth leading risk for global deaths, driven by comorbidities such as type 2 diabetes mellitus, cardiovascular disease, hypertension and stroke and certain forms of cancer1. Recently obesity has been associated with increased risk of hospitalization for COVID-192. Biological, social and lifestyle determinants as well as the prolonged use of some medications such as glucocorticoids (GCs) can strongly contribute to adipose tissue dysfunction3. Obesity is a multifactorial disease caused by the energy imbalance occurring when intake is higher than consumption, promoting hyperplasia and/or hypertrophy4. Since mature adipocytes are postmitotic, hyperplasia requires a pool of precursor cells in the adipose tissue to differentiate into new adipocytes5.
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Adipogenesis is a tightly coordinated program that integrates diverse extracellular signals within a temporally defined transcriptional network which can be divided into three phases: cell commitment, early- and terminal differentiation4. In vitro adipogenesis cell models are widely used, the 3T3-L1 cell line having become the gold standard. In post-confluent 3T3-L1 cell line, differentiation-inducing medium (DIM), composed of insulin, dexamethasone (DEX) and 3-isobutyl-1-methylxanthine (IBMX), activates IGF1 (Insulin Like Growth Factor 1), the glucocorticoid- and cAMP-signaling pathways, which in turn regulate the early differentiation stage. This adipogenic stimuli induces growth-arrested 3T3-L1 pre-adipocytes to synchronously reenter the cell cycle in a specific time window, the mitotic clonal expansion (MCE), when cells increase in number and activate a lineage commitment program, after which the cells permanently withdraw from the cell cycle, lose their fibroblast-like morphology and undergo terminal differentiation6.
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One of the earliest, and critical, events that initiates this adipogenic cascade is the transcriptional activation of CEBPB, in fact, when over expressed in 3T3-L1 pre-adipocytes, it can initiate adipogenesis regardless of hormone stimulation7. Furthermore, MEFs from C/EBP (/) mice, as well as C/EBP knockdown in 3T3-L1 cells, do not undergo MCE and do not differentiate into adipocytes8. Although rapidly expressed 4 h post-induction, CEBPB lacks DNA-binding activity until the cells reenter the cell cycle, traverse the G1-S checkpoint, and initiate MCE, approximately 20 h after induction9. Having acquired its DNA binding activity, CEBPB activates the expression of several genes required for the differentiation process; among them the two late-acting adipogenic transcription factors CEBPA and peroxisome proliferator-activated receptor gamma (PPARG)10, which in turn initiate an autoregulatory and feed-forward circuit that allows the cells to establish an adipocyte identity that is maintained upon stimulation11. Since these two proteins also have anti-mitotic functions, their expression also coordinates the timing of MCE by closing this proliferative window6. Although the PPARG and CEBPA proteins have been widely recognized as core to the transcriptional network of adipogenesis, a large set of genes that play critical roles in fat cell differentiation has been identified12–15.
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Nicotinamide N-methyltransferase (NNMT) is a metabolic enzyme that catalyzes the methylation of nicotinamide (NAM) using the universal methyl donor S-adenosyl methionine (SAM), linking the metabolic status of the cell with both methylation balance and intracellular levels of NAD+16. NNMT is abundantly expressed in liver and adipose tissue and in pathological conditions characterized by increased metabolic demand, such as some cancers, fatty liver disease and diabetes17. NNMT participates in several differentiation processes including naive-to-primed human embryonic stem cell transition18, myogenesis19 and both epithelial- and neural-mesenchymal transition in several cancers20,21. NNMT expression is regulated in a tissue and context specific manner rather than by a ubiquitous regulatory pattern17. Compelling evidence suggests a role for NNMT in obesity and type 2 diabetes22. Nnmt is upregulated in white adipose tissue (WAT) in a mouse model of obesity and diabetes23 and in the visceral adipose tissue of morbidly obese patients24. As a proof of concept, NNMT knock-down in the WAT and liver protected against diet-induced obesity, where it modifies the intracellular content of SAM and NAD+, two crucial mediators of cellular energy metabolism. In doing so, it controls the methyl donor balance, which in turn regulates the genes responsible for regulating energy consumption and promotes NAD+ depletion23. Additionally, some NNMT inhibitors (NNMTi) have been used to treat and/or prevent obesity and obesity-driven comorbidities in both preclinical animal models and 3T3-L1 cell line25,26. However, the underlying regulatory patterns and the mechanisms by which NNMT affects adipogenesis remain unclear. Using both a genetic and a pharmacological approach to suppress NNMT function, we demonstrated that NNMT is a key regulator of the early phase of adipocyte differentiation and that CEBPB regulates its expression following GC induction. Importantly, NNMT deficiency at this stage impairs the ability of pre-adipocyte’s to terminally differentiate.
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Materials and methods
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Cell culture and induction of differentiation
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3T3-L1 Mouse Embryonic Fibroblasts were purchased from American Type Culture Collection (ATCC CL-173). The cells were propagated and maintained in Dulbecco’s modified Eagle’s medium (DMEM, Gibco) supplemented with 10% calf serum (FCS) at 37 °C in 5% CO2 atmosphere. Subconfluents cells were expanded and utilized for the subsequent experiments at the passages 3–6. To induce differentiation, 2-day post-confluent 3T3-L1 pre-adipocytes were cultured for 48 h with DIM (DMEM supplemented with 10% fetal bovine serum (FBS), 1.0 µM Dexamethasone (G. Biosciences), 1.5 mg/mL Insulin (Sigma) and 0.5 mM IBMX (Sigma). Two days after induction the DIM medium was removed and the cells were maintained in DMED supplemented with 10% FBS and 1.5 mg/mL Insulin, which was replaced every 48 h, until the cells became fully differentiated (8–10 days after induction). C3H10T1/2 cells were purchased from American Type Culture Collection (ATCC, clone 8, CCL-226, were grown and induced to differentiate following the same protocol, with cell cultures < 3 passages.
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RNA isolation and real-time PCR
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Total RNA was extracted using the RNeasy kit (QIAGEN) and cDNA was synthesized by reverse transcribing 1 ug of total RNA using SuperScript™ III Reverse Transcriptase (Invitrogen) according to the manufacturer’s instructions. Real-time PCRs were performed using SYBR Green PCR Master Mix (Applied Biosystems) with an ABI PRISM 7900HT Sequence Detection System (Applied Biosystems). RT-PCR data were normalized to GAPDH and expressed relative to control (ddCt method). Real-time PCR primers are listed in Table 1. Table 1 List of primers for mus musculus used in this study.
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Primer name Forward sequence (5′–3′) Reverse sequence (5′–3′)
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Real-time PCR gene expression
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Gapdh GTGCAGTGCCAGCCTCGTCC GCCACTGCAAATGGCAGCCC
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Nnmt CTTTGGGTCCAGACACTGTGCA CCAGAGCCAATGTCAATCAGGAG
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| 84 |
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Cebpb GGTTTCGGGACTTGATGCA CAACAACCCCGCAGGAAC
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Cebpa TGGACAAGAACAGCAACGAGTAC GCAGTTGCCCATGGCCTTGAC
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qPCR ChIP
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| 87 |
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CEBPB Binding Site 1 (CBS1) AAATCACTCTGTAGTCCAGGCTGT GACTCCAAAAGCTAACTTCACAGG
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| 88 |
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CEBPB Binding Site 2 (CBS2) AGATTCCATCGTGTCTCAGCTC TCTAAGACTCCAAAAGCCAACTTC
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| 89 |
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CEBPB Binding Site 3 (CBS3) AAGTTGGCTTTTGGAGTCTTAGAG ACGTCTGCAGTCTATTTCACTGTC
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| 90 |
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CEBPB Binding Site 4 (CBS4) CAGTGAAATAGACTGCAGACGTTC ACTCCCCTCTTCTCCTAAGCTC
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| 91 |
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CEBPB Binding Site 5 (CBS5) TCATCTCCAAACAATCCAGTAGTC TTGTTTGTTCAAACTGAAACCATT
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CEBPB Binding Site 6 (CBS6) AGAAAAGGGAATGTGGGGTAAG CAGACTCCATCCGAGATTATTTTT
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| 93 |
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CEBPB Binding Site 7 (CBS7) TTTAAAACATGGACATTGTCTTCC CTCATTGAGTCCTAGTGGTGCTG
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CEBPB Binding Site 8 (CBS8) CTTCACAGAGTTGTTGCTCAAAAT GGAGATTCTCTGGGTGAGTTTTTA
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Luciferase reporter vector
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Nnmt-full promoter CGATCTAAGTAAGCTGAGACGGGGTCTAACTATGTAACTG CCGGAATGCCAAGCTCGTGTCTCAGCTCCGTGC
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Nnmt-mut CBS4 CAGTGAAATAGACTGCAGACGTTCAGGCTACGTAAGACAGTGATGAAATTCCTGGAGAAGGGAGCTTA TAAGCTCCCTTCTCCAGGAATTTCATCACTGTCTTACGTAGCCTGAACGTCTGCAGTCTATTTCACTG
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| 98 |
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Nnmt-mut CBS8 TTGATTAACCAGCCGGAGATGGGTAACACAATGCGAAAGCAGTAAGTTCCTGGCATCCCACG CGTGGGATGCCAGGAACTTACTGCTTTCGCATTGTGTTACCCATCTCCGGCTGGTTAATCAA
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CRISPR gRNAs vector
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| 100 |
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Nnmt-Guide1 CTTGTGGAAAGGACGAAACACCGGGAGAACTCCTGATTGACATGTTTTAGAGCTAGAAA TTTCTAGCTCTAAAACATGTCAATCAGGAGTTCTCCCGGTGTTTCGTCCTTTCCACAAG
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| 101 |
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Nnmt- Guide 2 CTTGTGGAAAGGACGAAACACCGGGGGACCAGTCAAAGGCTCCGTTTTAGAGCTAGAAA TTTCTAGCTCTAAAACGGAGCCTTTGACTGGTCCCCCGGTGTTTCGTCCTTTCCACAAG
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| 102 |
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Sanger sequencing
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| 103 |
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Nnmt-seq CCTTCTTCAGCCATTTCTGC TGCAGGTCCCTTCAGAAAGT
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Chromatin immunoprecipitation assay
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Chromatin immunoprecipitation (ChIP) was performed following the instructions for SimpleChIP® Enzymatic Chromatin IP Kit (Cell Signaling). For each immunoprecipitation performed, 1.6 × 106 3T3-L1 cells were seeded and grown to 2 days post–confluence (T0) before being treated, or not, with 1.0 uM DEX. After 20 h cells were fixed with 1% formaldehyde followed by glycine incubation. After cell lysis, chromatin was fragmented by micrococcal digestion and nuclear membranes were broken by sonication with a Bioruptor Sonicator (Diagenode). An aliquot of the digested chromatin (Input) was removed before sample immunoprecipitation with antibodies against either CEBPB (sc-7962, Santa Cruz Biotechnologies,) or a non-specific IgG control (Normal Rabbit IgG #2729, Cell Signaling). The complex co-precipitates were captured by Protein G magnetic beads and the cross-links were reverted before DNA purification. Chip-qPCR primers are listed in Table 1.
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Luciferase reporter assay
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| 110 |
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| 111 |
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The promoter region of mouse Nnmt (− 1572 to − 1 bp) was amplified via PCR from genomic DNA extracted from 3T3-L1 cell line and cloned into pGL3 basic vector (kindly provided by Dr. Monica Álvarez). Full length Nnmt promoter (PGL3-Full Promoter) acted as template for site-directed mutagenesis to generate two mutant constructs (CBS4-mut and CBS8-mut) (primers are listed in Table 1), Sanger sequencing was performed to confirm the presence of the desired mutations. 80% confluent 3T3-L1 cells were transiently transfected with PGL3-Full Promoter, PGL3-CBS4mut, PGL3-CBS8mut and an empty vector along with a renilla luciferase pRL-CMV plasmid (kindly provided by Dr. Monica Álvarez) using Lipofectamine 3000 (Thermo Fisher) according to manufacturer’s instructions. Two-day post-confluent 3T3-L1 were treated with 1 µM DEX (DEX+) or medium alone (DEX−). 24 h after treatment the Dual-Luciferase Reporter Assay System (Promega) was used, according to the manufacturer’s instructions, to determine luciferase activity.
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| 113 |
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Generating single cell-derived Nnmt knockout 3T3-L1 cell line
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| 115 |
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Two different single-guide RNAs (sgRNA) specifically targeting mouse Nnmt gene were designed using the CRISPR-ERA computational tool27 for gene repression. DNA oligonucleotides for the molecular cloning of the gRNA sequence (Table 1) were synthesized following the sequence structure 5-G-N19-NGG-3, as previously described28 adding a flanking region for proper cloning, using the In-Fusion® HD Cloning Kit (Takara). These oligonucleotides were cloned in a BamH1-BsmB1 linearized pLenti-Guide-Puro vector (Origene, GE100032) using the In-Fusion® HD Cloning system following the manufacturer’s recommendations. A two-vector approach was used to deliver Cas9 and the gRNAs to the cells. To assemble functional lentiviral particles, human HEK293 cells were independently transfected using Lipofectamine® 3000 transfection reagents (Invitrogen) with lentiCRISPR v2 blast vector (Addgene, #83480), scramble pLenti-Guide-Puro vector (Origene, GE100032), and with the two pLenti-Guide-Puro vectors containing the specific gRNA sequences. The virus-containing medium was collected 48 h and 72 h after transfection, filtered with a 0.45-μm filter and used to transduce 3T3-L1 cell line. Two stable 3T3-L1 cell lines were obtained, after two weeks of antibiotic selection with puromicine (2 mg/mL) and blasticidine (5 mg/mL), by virally delivering CRISPRv2 blast with the two pLenti-Guide-Puro vectors, each carrying one sgRNA (3T3-L1-CRISPR-Nnmt Knockout) or with an empty pLenti-Guide-Puro vector (3T3-L1-CRISPR/CAS9 mock). Single cells were isolated and plated into a 96-well plate by single cell sorting (FACS), after which individual microcolonies were clonally expanded. Single cell-derived colonies were genotyped by Sanger sequencing and the resulting trace data were analyzed with Synthego29. Only those clones where the CAS9 cut generated a new stop codon in Nnmt sequences in both alleles were expanded and used for downstream applications.
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| 117 |
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Oil red-O staining
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| 118 |
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Oil Red-O staining was used as previously described30. Briefly, cells were fixed for 30 min with 4% formaldehyde, stained with filtered Oil Red solution (0.2% oil red in 40% 2-propanol) and washed 5 times with distilled water. The accumulation of fat droplets in the cells was visualized and photographed under an inverted microscope (DMi1, Leica). The dye was eluted with 100% 2-propanol and quantified spectroscopically at 510 nm (Synergy HT, Bio-Tek).
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Flow cytometry cell cycle analysis
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| 122 |
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DNA staining with propidium iodide (PI) was used for cell cycle analysis. 3T3-L1 cells were collected at specific time points. For PI staining, cells were trypsinized, washed in PBS, fixed overnight with cold ethanol, stained with PI solution (3.8 mM sodium citrate, 50 µg/mL PI), and incubated with 0.5 mg/mL RNaseA for 45 min at 37 °C. DNA content was determined by FACS with a Cytomics FC500 Flow Cytometer (Beckman Coulter Life Sciences). Flow Cytometry data were analyzed with Modifit LT software (Verity Software House). Apoptosis was assessed using the Alexa Fluor® 488 annexin V/Dead Cell Apoptosis Kit (Invitrogen, V13241 and V13245) following the manufacturer’s instructions, and the data were analyzed with CXP Flow Cytometry software (Beckman Coulter Inc).
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RNA sequencing and data analysis
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| 126 |
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RNA sequencing was performed at Genewiz (Azenta, Life Sciences) using a polyA selection protocol and the NEBNext ultra–RNA Library prep kit for Illumina. Sequencing libraries were clustered in an Illumina Novaseq instrument and sequenced using a 2 × 150 bp paired end (PE) configuration. On average, we obtained ~ 25 million PE reads per sample analyzed. Adapter removal from raw Fastq data was performed using Fastp (v_0.20.1)31. The subsequent filtered reads were aligned to the mouse GRCm38 genome using RSEM (v_1.3.1)32 and the hisat2-hca paired end mode. Mapping efficiency was above 75% in all samples analyzed. Estimated counts per gene were obtained using RSEM output and the tximport function of the tximport R/Bioconductor package (v_1.18.0)33. Differential expression analysis was performed using the R/Bioconductor package DESeq2 (v_1.30.1)34. To assess the statistical significance of differential expression changes between conditions in the context of a time course analysis (0 h, 20 h, 48 h) we adopted the likelihood ratio test (LRT) implemented in DESeq2. Our full model included the variables condition (mock or Nnmt-KO), time (0 h, 20 h, 48 h) and—the main variable of interest—the difference between the effects of conditions over time (interaction). The reduced model only included the variables condition and time. The resulting p values were corrected using the Benjamini and Hochberg method, considering a threshold of p.adj < 0.05 for statistical significance and we performed a rlog conversion of the data for downstream purposes. Differentially Expressed Genes (DEGs) (p.adj < 0.05) were clustered according to their gene expression profile along the time course of the experiment using rlog scaled values. Pairwise Spearman correlations, computed across the different profiles, were converted to distances and clustered using the hierarchical clustering approach (Ward.D method). The optimal number of clusters was determined using the elbow method that employs the within-cluster sum of square errors. Pathway enrichment of clusters was conducted using the Molecular Signature Database hallmark gene set collection35 and the R/Bioconductor package goseq (v_1.42.0)36, which accounts for multiple types of selection bias. As a control, all the genes identified in the RNAseq experiment were included as background universe. Molecular pathways with a p.adj < 0.05 were considered as significant for descriptive purposes. Raw RNA-Seq fastq files have been deposited at the European Nucleotide Archive (ENA PRJEB55900).
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| 128 |
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|
| 129 |
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Synthesis of CC-410
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| 130 |
+
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| 131 |
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Methyl-(4S)-4-((3S,5S,7S,8S,10R,12R,13S,14R,17S)-3-acetoxy-7,12-diamino-10,13-dimethylhexadecahydro-1H-cyclopenta[a]phenanthren-17-yl) pentanoate -from now on termed as CC-410 for simplicity-was prepared in-house in multigram scale with a minimum of 98% purity following procedures previously described by our group37,38. The purity of the batches of compound CC-410 could be assessed by high-field nuclear magnetic resonance spectroscopy (1H and 13C-NMR) and high-resolution mass spectrometry. CC-410 was dissolved in dimethyl sulfoxide (DMSO; Sigma-Aldrich) and made up with the culture medium so that the concentration of DMSO was 0.5%. CC-410 molecule can be made available upon request at no cost.
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| 132 |
+
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| 133 |
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CC-410 cheminformatic evaluation
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| 134 |
+
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| 135 |
+
CC-410 chemical structure was initially submitted to the Open Innovation Drug Discovery program39 (Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, USA), and it was selected for its novelty and drug-like properties, based on cheminformatic evaluation. Briefly, the submitted molecular structure was firstly processed based on the Lilly Medical Chemistry Rules, which are aimed at identifying and eventually excluding from screening those compounds that may interfere with biological assays. Next, structure-based filters, including MW, cLogP, solubility and toxicity among others were analyzed to select molecules with high druggable features. Additionally, the compound was also filtered based on the number of heavy atoms, number of rings, number of aromatic rings, ring size and other physicochemical properties. Solubility and permeability of the compound were also considered for the screening. For molecules passing the cheminformatic evaluation a substance check and comparison with known drugs (both Lilly and PubChem collections) was performed in order to select for novelty. Once the molecule passed this selection it was physically submitted to be tested with a high throughput screening study, querying the activity of the molecule against a wide variety of possible therapeutic targets. Among the tested targets, CC-410 showed exclusive inhibitory activity against human NNMT.
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| 137 |
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NNMT inhibitor cell-based assay in HEK293 human hepatoma cell Line
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| 138 |
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| 139 |
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Enzymatic and cell-based assays were performed by Lilly corporation (Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, USA) and a full report with all the biological data was generated. Protocol from Lilly Research Laboratories: the HEK-293 (ATCC CRL-1573) cell line was seeded onto a 96-well plate at 25,000 cells/well in 0.1 mL growth medium and incubated at 37 °C in a 5% CO2/95% humidity incubator until 90% confluent. The day after, the 100× compounds were prepared in 100% DMSO in a 96-well polypropylene storage plate, starting from 10 mM for 11-points at 1:3 serial dilutions. 2.5 mL of 100× compounds were diluted onto fresh 96-well polypropylene plates containing 97.5 mL/well of growth medium to make 2.5×, then were transferred to 80 mL/well of 2.5× compound onto cell plate and incubated for 2 h at 37 °C in a 5% CO2/95% humidity incubator. 10× substrate mix were prepared in growth medium: 0.25 mM SAM (Sigma #A7007) and 5 mM NAM (Fluka #72340) or NAM-d4 (CDN Isotopes #D-3457). Followed by the addition of 20 mL/well of 10X substrates mix onto cell plates and incubated overnight at 37 °C in a 5% CO2/95% humidity incubator. 24 h post addition of substrate, 0.1 ml/well of conditioned medium was transferred onto 96-well polypropylene storage plates for measuring SAM, NAM, SAH, and MNAM or MNAM-d4 by LC-MS.
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| 140 |
+
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| 141 |
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Automated solid-phase extraction and mass spectrometry
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| 142 |
+
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| 143 |
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An Agilent 300 RapidFire automated extraction system (Agilent, Santa Clara, CA) with three HPLC quaternary pumps was coupled to an Agilent 6495 triple quadrupole mass spectrometer (Agilent Technologies, Santa Clara, CA) equipped with an electrospray ionization (ESI) interface source. The RapidFire Mass Spec system was equipped with a reusable HILIC (type H1) solid-phase extraction (SPE) cartridge (G9209A). Solvent A, used for sample loading and washing, was 0.1% formic acid in acetonitrile. Solvent B, used for sample elution, was 50% acetonitrile containing 0.1% formic acid. Samples were sequentially analyzed by aspirating 10 μL onto the collection loop under vacuum directly from multiwell plates. The 10 μL of sample was loaded onto the HILIC cartridge and washed, by quaternary pump 1, using solvent A at a flow rate of 1.25 mL/min for 6000 ms. The retained analytes were then eluted to the mass spectrometer by quaternary pump 3, using solvent B at a flow rate of 1.25 mL/min for 6000 ms. The system was re-equilibrated by quaternary pump 1, using solvent A at a flow rate of 1.25 mL/min for 3000 ms. The triple quadrupole mass spectrometer was equipped with an electrospray ionization (ESI) source and analytes monitored using selected reaction monitoring (SRM) in positive mode [M-H]+. S-Adenosyl-L-homocysteine was monitored at m/z 385.1/136.0, 13C10 S-Adenosyl-L-homocysteine was monitored at m/z 395.1/141.1. Methyl nicotinamide was monitored at m/z 137.1/94.0 and D7 methyl nicotinamide was monitored at m/z 144.1/101.1. The area ratio values for each metabolite were calculated using their respective internal standard. The IC50 values were determined by fitting the inhibition curve (percentage inhibition versus inhibitor concentration) using a four-parameter logistic curve. Values are calculated by dividing the AUC of the product (MNAM or SAH) by the AUC of their internal standard (d7-MNAM and d10-SAH, respectively). Data are area ratio values for MNAM and SAH.
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| 144 |
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Methyltransferases hot spot assay
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CC-410 was screened in biochemical assays for activity against a panel of 11 methyltransferases (MT) by using the radioisotope (3H-AdoMet) based MT Hot Spot Assay. All the assays were performed by Reaction Biology Corporation (RBC, Malven, PA, USA). Briefly CC-410 was incubated with the selected MTs, corresponding substrates, and radiolabeled SAM (S-Adenosyl-L-[methyl-3 H]methionine). The specific MTs assessed, and the corresponding substrates are as follows: DNMT1- Poly dl-dC, DNMT3a- Lambda DNA, DNMT3b- Lambda DNA, DOT1L- Nucleosomes, EZH2 Complex- Core Histone, METTL21A- HSPA8-[CTD], NRMT1- RCC1, PRMT3- Histone H4, PRMT5/MEP50- Histone H2A, SET1b -Core Histone Complex and SMYD2- Nucleosomes. Reaction mixtures were incubated and spotted onto filter papers, which were then washed to remove unreacted SAM, leaving the bound radiolabeled product. Detection of the radiolabeled, methylated product was performed via a nanoliter-scale radioisotope filter binding platform. The CC-410 compound was tested in 10-dose IC50 mode with threefold serial dilution, in singlet, starting at 300 μM. For each assay, control compounds were included as positive controls for enzyme function and assay reproducibility. Control compound, SAH (S- (5′-Adenosyl)-L-homocysteine), or LLY507, (used for SMYD2 assay) were tested in 10-dose IC50 mode with threefold serial dilution starting at 100 μM. IC50 was calculated by non-linear least square fitting dose–response curve. Percentage of enzyme activity (no inhibitor control as 100% activity) and curve fits were generated for all the control compounds and where the enzyme activities at the highest concentration of CC-410 were less than 65%.
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Docking computation in hNNMT a mNNMT and molecular dynamics
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The structure of CC-410 ligand was computed, in vacuum, at the b3lyp/6-31+G** level of theory. The so obtained xyz coordinates were used for docking study. Coordinates for (S)-4-((((2R,3R,4R,5R)-5-(6-amino-9H-purin-9-yl)-3,4-dihydroxytetrahydrofuran-2-yl)methyl)(naphthalen-2-ylmethyl)amino)-2-ammoniobutanoate a.k.a. compound 840 was generated with the aid of Chemoffice 2019 (Perkin Elmer) and UCSF Chimera41. Docking calculations were carried out with AutoDock Vina42 using a 25 Å × 25 Å × 25 Å region of interest targeting the center of mass of the active-site cavity. Recombinant mNNMT atomic coordinates—PDB ID: 5YJI25 and hNNMT, PDB ID: 6b1A43 and 2IIP (Bernstein et al., unpublished) were used as CC-410 targets. Notably, 5YJI coordinates already include a molecule of S-adenosyl-homocysteine (SAH) as ligand in the active site pocket. The hNNMT and mNNMT structures also incorporate coordinates of an His6 tag and a thrombin cleavage site at the interface between distinct biological molecules. These residues from the tag and the cleavage site have not been considered in the docking computations. Residues missing in the structure because of their mobility were added with Modeller 9v744. The resulting zDOPE score was − 2.23. The structure of mNNMT in complex with bisubstrate inhibitor MS275643 was used for comparison.
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Molecular dynamics and structural analysis
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Molecular dynamics (MD) computations were performed with the PMEMD module of AMBER 1645,46 under the AMBER-14SB force field47 for the protein, and the General Amber FF45 for the ligand atoms. The amine groups of CC-410 were protonated as pKa estimations yielded values above 9.5. AM1-BCC atomic charges48 for CC-410 were computed with the Antechamber module of AMBER. Apo-proteins and ligand target complexes were simulated under periodic boundary conditions using orthorhombic cells. The minimum distance between protein and cell faces was 10 Å. Sodium counter-ions were added to neutralize the system. The structures were solvated using the SPC/E water model49. Particle Mesh Ewald (PME) electrostatics were set with the Ewald summation cut-off at 9 Å. The SHAKE algorithm50 served to constrain bonds involving hydrogen atoms. The whole system was subjected to energy minimization, then to 500 ps of NPT MD to adjust box size and solvent density, followed by additional energy minimization and equilibration at 298 K using a Langevin thermostat. Then, 100 ns of production trajectories were recorded. These were analyzed with CPPTRAJ51. CASTp analysis52 enabled cavity characterization. LigPlot53 was used to explore protein–ligand interactions.
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Cell viability assay
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CellTiter-Blue® Cell Viability Assay (Promega) was used following the manufacturer’s instructions. 3T3-L1 cells were seeded at a density of 2 × 103 cells per well in 96-well plates and cultured till confluence in standard medium. Two-day post-confluent 3T3-L1 cells were induced with DIM and treated with 1, 5, 10 and 25 µM CC-410 along with an untreated control (0.5% DMSO) in 4 different conditions: every 48 h throughout the differentiation period; once in the first 20 h following DIM stimulation; once 48 h after DIM stimulation; or after the early differentiation phase. In all cases, cell viability was assessed at terminal differentiation. Cell viability percentages were calculated by normalizing the fluorescence recorder (560/590) for the treated samples over untreated controls.
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Results
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Glucocorticoids induce CEBPB-mediated transactivation of Nnmt during the early phase of 3T3-L1 pre-adipocytes differentiation
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To address the molecular and temporal regulation of NNMT, we used the standard protocol for inducing and tracking the synchronous progression of 3T3-L1 pre-adipocytes towards terminally differentiated adipocytes (Fig. 1A). Since these cells irreversibly commit to differentiating during the early phase of adipogenesis, we sought to investigate Nnmt expression and its regulatory pathways during this period. Confluent 3T3-L1 cells were treated for 48 h with DIM or individually with each component of the induction cocktail. Quantitative RT-PCR revealed that Nnmt expression increased after hormonal stimulation, and that DEX produced induction comparable with that of the whole cocktail. However, neither insulin nor IBMX impacted Nnmt expression significantly compared to unstimulated cells (Fig. 1B), demonstrating that NNMT is activated during the early phase of adipogenesis mainly by glucocorticoid signaling. Because of the well-recognized and temporally defined role of CEBPA and CEBPB during adipocyte differentiation, we followed their expression after DEX treatment. In agreement with previous reports54,55, DEX itself is able to induce a rapid increase, as soon as 2 h after induction, in Cebpb expression, which peaked between 4 and 12 h post-induction and gradually declined to almost its basal level at 24 h (Fig. 1C). As expected, Cebpa induction started later, almost 48 h after DEX induction, once the cells start withdrawing from the cell cycle. It is worth noting that Nnmt expression increased 18–24 h after DEX treatment, synchronously with the acquisition of CEBPB DNA binding activity and prior to Cebpa induction (Fig. 1C), suggesting that Nnmt could be a CEBPB transcriptional target. To study the binding of CEBPB to Nnmt promoter, we performed Chip-qPCR on both differentiating cells harvested 20 h after DEX treatment and unstimulated controls. We extrapolated putative CEBPB binding sites in the proximal and distal region of Nnmt promoter using the Gene Transcription Regulation Database (GTRD)56 (Fig. 1D). Experimental validation by Chip-qPCR confirmed that two regions, referred as CBS (CEBPB Binding Site) 4 and CBS 8, spanning respectively the chromosomal positions chr9:48605113-48605195 and chr9:48606327-48606478, were significantly enriched by CEBPB antibody 20 h after DEX induction (Fig. 1E) but not in the unstimulated samples, indicating that CEBPB binds to Nnmt promoter following GC treatment. The proximal CEBPB regulatory region CBS4 was located near a CIS-regulatory element and overlapped with the Nnmt transcription start site reported by eukaryotic promoter database (EPD)57 (Fig. 1D). Previous research21 demonstrated that in glioblastoma (GBM), CEBPB is the transcription factor that most significantly correlates with Nnmt expression, and that binding of CEBPB to Nnmt regulatory regions upregulates its expression. It is worth noting that the CBS8, discovered by ChIP-PCR in our study, overlaps with the most significantly CEBPB enriched regulatory motif on the NNMT promoter, previously characterized in GBM. These data suggest that both proximal CBS4 and distal CBS8 could be bona fide CEBPB regulatory elements. This was further confirmed by mutating the CEBPB consensus sequences within the CBS4 and CBS8 regions. A DNA wild-type fragment containing the 5′-flanking region of the Nnmt gene (from 0 to 1572 bp) and the two mutated constructs (Mut CBS4 and CBS8) were subcloned in a PGL3-basic plasmid and transfected in post-confluent 3T3-L1 treated or not with DEX for 20 h. Notably, hormonal stimulation in cells transfected with wild-type Nnmt promoter-luciferase plasmid caused a statistically significant increase in luciferase activity. Contrarily, mutations disrupting the consensus sequences for the two potential CEBPB binding sites totally abolished this transactivation (Fig. 1F). Overall, these data shows NNMT is activated during the early phase of adipogenesis through the GC transcriptional network and its transactivation is mediated by CEBPB recruitment onto the Nnmt promoter region.Figure 1 Transactivation of Nnmt by CEBPb is regulated by dexamethasone during the early phase of adipogenesis. (A) Schematic representation of 3T3-L1 pre-adipocyte differentiation protocol and chronological progression through the different phases of the cell cycle during the early phase of adipogenesis. (B) mRNA levels of Nnmt gene measured by Real-Time PCR after post confluent 3T3-L1 cells (T0) were exposed for 48 h to individual components of the DIM alone or in combination. Values are expressed as fold change (mean ± S.D, n = 3) relative to the untreated control (T0). (C) After DEX treatment, mRNA levels of Cebpb, Cebpa and Nnmt were analyzed at the times indicated by RT-qPCR. Data were normalized to the T0 time point of each gene. (D) CEBPB and CEBPA binding sites in the proximal and distal region of Nnmt promoter, obtained from the GTRD database, also including surrounding ENCODE cis- regulatory elements. Black rectangles represent the 8 putative CEBPB binding sites (CBS), corresponding to the amplicons spanning the ChIP-qPCR primer-targeted regions. (E) Effect of DEX on CEBPB recruitment to the Nnmt promoter. Post-confluent 3T3-L1 cells were treated, or not, with DEX (1uM) for 20 h and CEBPB binding on Nnmt promoter was analyzed by Chip-qPCR, with primer pairs specific to the putative CEBPB binding sites. Chip-qPCR was performed using control IgG and anti-CEBPB antibody. Chip data were expressed as percentage of input normalized to control IgG. Statistical significance was calculated by means of a one-sided Welch’s t-test between DEX- and DEX+ conditions for each amplicon. For interpretation purposes, only the regions that showed enrichment with anti-CEBPB higher than the control IgG for the same sets of primers were considered for the final statistical assignments. (F) 3T3-L1 cells were transfected with reporter plasmids containing the full Nnmt promoter (~ 1500 bp) or two mutant constructs (mut CBS4 and mut CBS8) and grown two days post-confluence before treatment, or not, with DEX for 20 h. Firefly and renilla luciferase activity were measured sequentially and the results expressed as ratios of firefly luciferase activity over relative renilla luciferase activity. An empty reporter vector was also used as internal control. The data represent three independent experiments, each with at least three technical replicates, and values are expressed as mean ± SEM. Statistical significance was calculated by means of a one-sided Welch’s t-test. For all the panels: *p < 0.05; **p < 0.01; ***p < 0.001.
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Nnmt ablation suppresses terminal adipocyte differentiation by delaying cell cycle exit during MCE
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To investigate how NNMT regulates adipogenesis, we generated stable, single cell-derived Nnmt knock-out 3T3-L1 cell lines (Nnmt-KO) with the CRISPR-Cas9 system28. Knockout efficiency was confirmed by Sanger sequencing and gene expression analysis. The selected Nnmt-KO cell line was cultured to confluence and induced to differentiate for 10 days. Oil Red-O staining showed that Nnmt-KO accumulated significantly less lipid than the control cell line (Fig. 2A,B). Morphological inspection confirmed that Nnmt ablation induced a severe adipogenesis defect and locked the cells in a pre-differentiated fibroblast-like stage, suggesting that NNMT is required for adipogenesis through regulating the adipose lineage commitment stage. Since we previously demonstrated that Nnmt is activated during MCE, we investigated whether NNMT deficiency could affect cell cycle progression during this time interval. Flow cytometry analyses revealed that Nnmt depletion did not affect cellular distribution in normally proliferating (data not shown) or post-confluent cell line (T0) (Fig. 2C,D). As expected, hormonal stimulation induced the growth-arrested cells to reenter the cell cycle, although 20 h post-induction Nnmt-KO resulted in a significant increase in cell population in G2/M phase (from 27 to 42%) with a concomitant reduction in G1 phase (from 41 to 25%) (Fig. 2C,D). To ascertain whether Nnmt inactivation produces a permanent or a transient block in the G2/M phase, FACS analysis was performed 48 h after DIM induction. Neither statistically significant differences in cell cycle distribution (Fig. 2C,D) nor increases in the percentage of apoptotic cells (Fig. 2E) were observed between control and Nnmt-KO cell lines, suggesting that, rather than a permanent block, lack of Nnmt induces a delay in the cell cycle progression during MCE. A recent study on adipogenic cell model demonstrated that cells undergoing terminal differentiation exit the last mitosis early compared with cells that do not differentiate58. Considering this, we can assume that NNMT controls pre-adipocyte commitment by coordinating the proper progression through the cell cycle during MCE. To fully understand the molecular mechanisms underlying NNMT function during adipogenesis, we performed gene expression profiling at different time points during MCE. RNA sequencing experiments were carried out on Nnmt-KO and mock control cell lines harvested at T0 (growth-arrested pre-adipocytes), 20 h (during MCE) and 48 h (post-mitotic) after DIM stimulation. To identify genes influenced by Nnmt depletion along this time course, we performed a Likelihood ratio test followed by a classical gene clustering approach. This strategy led to the identification of six enriched gene clusters (Fig. 3A). Cluster 1 was enriched in genes that showed progressive upregulation as a direct consequence of hormonal stimulation and are assumed to have a leading role in the differentiation process (Fig. 3A,B). Consistent with Nnmt-KO phenotype, adipogenesis was among the strongest enriched pathways in this cluster (Fig. 3C). At T0, the genes from this cluster were downregulated overall, with no statistically significant differences between Nnmt-KO and control cells lines. Interestingly, already at 20 h and more pronounced 48 h after hormonal stimulation, we observed an upregulation of adipogenesis-related genes in the control cell line that was significantly lower in the knock-out cell line, confirming that NNMT acts in a clearly defined period during the early phase of adipogenesis. As evidence, Nnmt depletion was associated with a reduction in the mRNA level of late-acting adipogenic genes such as, Cebpa, Pparg and Lpl (Lipoprotein Lipase), but did not influence Cebpb expression (Fig. 3D), corroborating that it may act upstream of NNMT by regulating its expression. Cluster 2 was significantly enriched in genes related to cell cycle progression, particularly E2F, the G2/M checkpoint and the mitotic spindle assembly pathways (Fig. 3B,C). The expression of these genes fluctuated in line with cell cycle phases during MCE and with FACS analysis (Fig. 2C,D). In fact, the expression of cluster 2 genes peaked 20 h after hormonal stimulation, indicating that the cells actively re-entered the cell cycle, and then dropped to a level comparable with T0 as the cells permanently withdrew from the cycle after MCE (48 h). However, compared to control cell line, Nnmt-KO induced an overall delay in downregulating G2/M-related genes, confirming that Nnmt depletion retains a higher population of cells in this cell cycle phase and that it can regulate cell commitment by shifting the timing of last mitotic exit. Of note, we found that Nnmt deficiency influence key factors in G2-M transition as well as genes involved in cytoskeleton organization during cytokinesis (Fig. 3D). Cluster 3 was enriched in genes belonging to the interferon-alpha and interferon-gamma signaling pathways (Fig. 3B,C). In accordance with their anti-adipogenetic function59,60, these two pathways showed an overall downregulation after hormonal stimulation, with statistically significant differences between the KO and control cell lines. Hypoxia and apical junctions and epithelial to mesenchymal transition were among the other significantly enriched pathways identified, indicating the potential role of NNMT as a central metabolic regulator of these cellular processes.Figure 2 Nnmt deficiency impairs adipocyte differentiation by regulating MCE. (A) Terminal adipogenesis was analyzed 10 days after DIM induction in 3T3-L1-Nnmt-KO (3T3-L1-CRISPR/CAS9 Nnmt guides) and mock control cells (3T3-L1-CRISPR/CAS9 empty) by Oil Red-O staining and bright field microscopy (20× magnification). (B) Statistical data for Red-Oil staining quantification by OD measurements. Data are presented as means ± S.D. (n = 3) and statistical significance was calculated with a one-sided Welch’s t-test. (C) DNA content was analyzed by PI staining and FACS analysis was performed at different times after hormonal stimulation (T0, 20 h DIM and 48 h DIM). The percentage of cells in each phase of the cell cycle are represented in the graph plot, which shows the results of three independent experiments. Statistical significance was calculated by a chi-squared test using a 3 × 2 contingency table including the percentage of cells at each cell cycle stage (G1, S, G2/M) and in each experimental condition (mock – Nnmt-KO) per triplicate. (D) Flow cytometry plots representative of one independent experiment. (E) Annexin and PI staining. Nnmt-KO and mock cell lines were stained 48 h after DIM induction with Fluor 488 annexin V and PI and analyzed by flow cytometry. The loss of Nnmt did not influence either cell viability or apoptotic rate. For all the panels: *p < 0.05; **p < 0.01; ***p < 0.001.
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Figure 3 NNMT regulates molecular pathways related with fat cell differentiation and cell cycle progression. (A) Heatmap representing the gene expression values of the significant genes (Adj. p.value < 0.05) obtained from a likelihood ratio test analysis comparing Nnmt-KO and mock samples across different time points. Genes were ascribed to different clusters according to their expression pattern. (B) Boxplots indicating the scaled gene expression values observed for genes contained in clusters 1, 2 and 3. (C) Barplots depicting the significant enrichment of molecular signatures (Hallmark gene set, MSigDB) of clusters 1, 2 and 3. Bar length represents statistical significance (− Log10 Adj. p.value) and color scale represents the Odds Ratio of the different gene pathways interrogated. (D) Differentially expressed genes in Nnmt-KO compared to mock 3T3-L1 cell lines during MCE as determined by RNA sequencing. The upper panel shows selected genes known to have a key role in adipogenesis. The middle panel shows the time-dependent upregulation of G2/M transition-related genes. And the lower panel shows selected genes related to cytoskeleton organization during cell cycle cytokinesis. For all the plots, gene levels are represented as the log2 of the Transcripts Per Kilobase Million (TPM), and statistical significance for the conditions was assessed using a likelihood ratio test, as described in the methods section.
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CC-410 is a new efficient and specific small molecule inhibitor of NNMT
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| 174 |
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| 175 |
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Small molecules are useful chemical tools that allow the modulation of protein function in a tunable and conditional manner. To this end, we characterized by biochemical and computational methods a novel specific small molecule inhibitor of NNMT, called CC-410. CC-410 was previously synthetized by our group 37,38; the molecule belongs to the steroid family, natural products with structural, regulatory, and hormonal functions. Particularly, CC-410 derives from cholic acid, a cheap naturally-occurring bile acid produced by the liver of mammals. It is equipped with two primary amine groups, borne on the C7 and C12 positions of the steroidal scaffold, and an ester function. These groups define a densely-functionalized cavity capable of hydrogen bonding and other supramolecular interactions (Fig. 4A). CC-410 was initially submitted to the Lilly Open Innovation Drug Discovery program 39 (Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, USA). Based on its cheminformatics evaluation, it was privileged for its drug-like properties and its activity was assessed against a wide variety of possible therapeutic targets, showing exclusive inhibitory activity against human NNMT. The concentration-dependent activity of CC-410 against human NNMT was evaluated using automated solid-phase extraction and liquid chromatography mass-spectrometry (LC–MS), resulting in an IC50 of 1.6 µM (Fig. 4B). The selectivity of CC-410 was further assessed by biochemical assays for activity against a panel of 11 MTs, chosen according for their structural and sequence similarities or because they have been described as possible off-targets of other NNMTi molecules 26,43. In the range of concentrations tested, CC-410 did not influence the activity of most MTs (Fig. 4C). In fact, of the 11 enzymes examined, only 3 MTs were inhibited by CC-410, although with IC50 values far greater than those obtained against NNMT. Specifically, CC-410 slightly inhibited PRMT3 and SET1b Complex (IC50 of 104 and 120 µM, respectively), while IC50 for SMYD2 was 34.25 µM (Fig. 4D). The fact that SMYD2 is not expressed in adipose tissue 61 excludes the possibility that, at least in this context, this MT might represent a possible off-target of CC-410. Computational docking studies were furthermore performed to elucidate how CC-410 interacts with the active sites of human (hNNMT) and mouse (mNNMT) NNMT proteins (Fig. 5A). CASTp analysis 52 of hNNMT (PBD-ID: 6B1A) and mNNMT (PBD-ID:5YJI) structures revealed a highly conserved internal cavity which includes residues necessary for catalysis, including a methyl-donor site interconnected to an acceptor site. Notably, CC-410 molecules have a polycyclic sheet structure with two different faces, amino groups on one and methyl groups on the other, and two different sidechains, with the acetoxi- (R1) and 5-methoxy-5oxopentan-2-yl (R2) at opposing ends (Fig. 4A). In line with this, best docking results (Table 2) showed that CC-410 well fits the NNMT cavity in two major orientations. In the first (A1), the R2 of CC-410 is located near the cavity opening while the rest of the inhibitor, including R1, completely fills the donor pocket of the active site. In the second orientation (B2) the R1 is located near the cavity opening and the R2 group lies within the acceptor pocket and the inhibitor partially occupies the donor site. The comparison of evaluation scores suggested that these alternative orientations are similarly stable, although best results for hNNMT had A-type orientation, whereas mNNMT preferred the B orientation. Since simulations yielded better scores with mNNMT than hNNMT, CC-410 was again docked with another set of hNNMT coordinates (PDB ID: 2IIP), confirming that the preference of hNNMT for A conformations was independent of the model chosen (Table 2). Best docking results were subjected to MD computations, including control trajectories without the ligand (Table 3). Along the trajectories, the structures of both hNNMT and mNNMT were invariable, according to statistical data (Fig. 5B,C). Further, the inhibitor remained within the active site: first, the ligand stays in the active site in the average structure (Fig. 5)—which wouldn’t be expected if the ligand leaves the enzyme—; second, the radius of gyration of complex is smaller than that of the free enzymes, as expected from the ligand being located in an internal cavity of the protein (Fig. 5). To assess energy degeneracy of A and B orientations, protein–ligand interaction was estimated from MD computations. Details of the structure closest to the MD average of CC-410 bound to mNNMT are shown in Fig. 5D. MD trajectories of mNNMT Auto Dock analysis for the two forms showed that the B and A orientations have only slight differences in energy. Moreover, the same analysis for mNNMT-SAH interaction demonstrated that, regardless of orientation, CC-410 binds to NNMT more tightly than to SAH (Table 3). Notably, this happens even when the average number of H-bonds partaken by SAH within the protein is larger. However, the contribution of H-bonds strongly depends on their geometry and the surrounding environment. Figure 5A shows the best docking solutions for CC-410-hNNMT and CC-410-mNNMT and SAH- mNNMT complexes, where SAH fills only the donor pocket of the active site 25. By overlapping the aligned structures of CC-410 and SAH (Fig. 5E) we further observed that while the A1 conformation fully overlaps with SAH, acting as a single-substrate inhibitor. However, B2 only overlaps SAH incompletely because CC-410 not only partially occupies the methyl-donor (S-adenosyl-methionine) site of the active site but also fills the acceptor (nicotinamide) pocket, behaving as a bisubstrate-like inhibitor. To illustrate this point, we aligned the A and B orientations of CC-410 with two known NNMT bisubstrate inhibitors MS2756 43 and compound 8 40 (Fig. 5F). Our analysis demonstrated that NNMT-CC-410 binding aligns well with these alternative inhibitory complexes and notably that, depending on its conformation, CC-410 can act as either a single substrate or a bisubstrate mimetic inhibitor. Taken together these data demonstrate that CC-410 is a stable and highly specific inhibitor of NNMT.Figure 4 CC-410 specifically inhibits NNMT. (A) The chemical structure of CC-410 compound. (B) concentration response curve (CRC) of hNNMT enzymatic modulation using LC/MS assay (IC50). The area ratio values for each metabolite were calculated using their respective internal standard. (C) Activity of CC-410 against 11 methyltransferases. Summary of IC50 values for CC-410 and respective controls. CC-410 compound was assessed in 10-dose IC50 mode with threefold serial dilution, starting at 300 μM. Control compound, SAH (S-(5′-Adenosyl)-L-homocysteine), or LLY507, was tested in 10-dose IC50 mode with threefold serial dilution starting at 100 μM. The empty cells indicate no inhibition or compound activity that could not be fitted to an IC50 curve. (D) Percentage of enzyme activity and curve fits for the only three methyltransferases that were moderately inhibited by CC-410. Curve fits were performed where the enzyme activity at the highest concentration of compounds were less than 65%.
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Figure 5 Molecular docking and molecular dynamics simulation reveal that CC-410 specifically inhibits NNMT by stably binding to its catalytic active site. (A) Best solutions of docking computations of CC-410 targeting hNNMT (top) and mNNMT (middle), and the complex between mNNMT and SAH (bottom) according to the X-ray diffraction model (PDB 5YJI). All the structures are based on the coordinates closest to the average of the last 70 ns of 100 ns molecular dynamics (MD) trajectories. Protein backbones are represented by Richardson’s ribbon diagram and the CC-410 molecule by sticks. Carbon atoms are in green, nitrogen in blue, oxygen in red and sulfur in yellow. Gray arrows point to the active-site cavity opening. (B) Statistics of MD computations. For each set of computations, the upper panel shows the Root Mean Square Deviation (RMSD) of protein main chain atoms with respect to the energy-minimized structure throughout trajectory calculations in the presence (red) and absence (black) of CC-410 ligand. The lower panels show radii of gyration (RG) of NNMT in the presence and absence of ligand. In red, RG of NNMT protein moiety in the presence of ligand, in green, RG of NNMT plus ligand, in black, RG of NNMT along the trajectory without ligand. (C) Atomic fluctuations and secondary structure analysis. Upper panels: Backbone fluctuations represented as per-residue root mean square fluctuations (RMSF) of atomic positions with respect to their average. Data corresponding to the apoprotein are in black, those for the bound protein in red. Lower panels: timeline of secondary structured as determined with Kabsh’s algorithm. Extended conformations are in blue, α-helices in dark red, 310 helices in orange, p helices are in red, turns are in beige, and bends in yellow. (D) Details of the structure closest to the MD average of CC-410 bound to mNNMT. Green lines represent hydrogen bonds. (E) Structural alignment of the MD-refined docking results of CC-410, in the B2 (mNNMT) and A1 (hNNMT) orientations, with SAH. Only the ligands are shown. (F) Structural alignments of bifunctional drugs MS2756 and compound 8 (cmpd8) docked to mNNMT with SAH and CC-410 docking solutions. The view has been rotated arbitrarily with respect to panel C to highlight the moiety of the bifunctional ligands that enter the nicotinamide (methyl-acceptor) pocket. * and # stand for R1 and R2 sidechains, respectively.
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| 178 |
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| 179 |
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Table 2 Summary of AutoDOCK Vina results for the interaction between NNMT and CC410.
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| 180 |
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| 181 |
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Target PDB Solution Score ubRMSD* (Å) No. H-bonds Orientation**
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| 182 |
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hNNMT 6b1a S1 − 3.9 0 2 A1
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| 183 |
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S2 − 3.8 8.92 1 B1
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| 184 |
+
S3 − 3.8 − 3.79 3 A2
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| 185 |
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hNNMT 2iip S1 − 2.4 0 1 A1
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| 186 |
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S2 − 2.2 8.92 1 B1
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| 187 |
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S3 − 2.0 8.52 0 B2
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| 188 |
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mNNMT 5yji S1 − 6.3 0 4 B2
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| 189 |
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S2 − 5.1 8.81 0 A1
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| 190 |
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S3 23.9 26.85 0 Surface
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| 191 |
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*Upper-bound RMSD with respect to best solution in each calculation. CC410 has C1 symmetry.
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| 192 |
+
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| 193 |
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**A1: methyl-pentanoate points to cavity mouth and acetoxy group locates within donor cavity; A2: methyl-pentanoate pointing to cavity mouth and acetoxy group gets inside nicotinamide pocket; B1: acetoxy group pointing to cavity mouth and the methyl-pentanoate group locates within donor cavity; B2: acetoxy group pointing to cavity mouth and methyl-pentanoate group gets inside nicotinamide pocket; Surface: molecule binds out of the active site pocket.
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| 194 |
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| 195 |
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Table 3 Summary of Protein–ligand interactions estimated from MD computations.
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| 196 |
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| 197 |
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Target PDB Ligand Orientation Average no. of ligand H-bonds ∆EVdW ∆EELEC
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| 198 |
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As donor As acceptor (kcal·mol−1)
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| 199 |
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hNNMT 6b1a CC-410 A1 2.5 ± 0.9 0.8 ± 0.8 − 30.1 ± 3.8 + 2.8 ± 12.7
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| 200 |
+
mNNMT 5yji CC-410 B2 1.2 ± 0.8 1.92 ± 0.8 − 30.8 ± 3.4 − 15.0 ± 11.2
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| 201 |
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5yji CC-410 A1 1.8 ± 0.8 0.44 ± 0.6* − 32.3 ± 3.3 − 1.5 ± 11.0
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| 202 |
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5yji SAH N.A 4.6 ± 0.9 5.2 ± 1.2 − 16.7 ± 4.5 + 2.7 ± 14.9
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| 203 |
+
Error values correspond to standard deviations. *All the H-bond data show skewed distributions. No negative values are neither recorded nor expected. N.A. stands for not applicable.
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| 204 |
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| 205 |
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NNMT is a key regulator of the glucocorticoid-mediated commitment state in the progression from pre-adipocyte to adipocyte
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| 206 |
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Once we corroborated that CC-410 specifically targets NNMT, the molecule was used to modulate enzyme activity over time. To check if CC-410 was able to inhibit adipogenesis, we firstly determined a range of concentrations where the drug showed the highest anti-adipogenic activity with the lowest cytotoxic effects. We treated post-confluent 3T3-L1 cell line with different drug concentrations throughout the differentiation process (during adipogenesis). Oil Red-O staining quantification showed that concentrations of 15 and 25 µM strongly reduced adipogenesis by 60% and 80% respectively compared to untreated control (Fig. 6A,B). Cell viability assays confirmed staining reduction was not due to the cytotoxic effect of CC-410, indeed at the highest concentration it induced only a slight reduction in cell viability (Fig. 6C). To confirm our previous results, 3T3-L1 pre-adipocytes were incubated with CC-410 at different time points. CC-410 treatment during the early phase (from T0 to 48 h) markedly reduced adipogenesis, with levels analogous to continuous treatment. Although with a slightly lower effect, CC-410 treatment strongly inhibited adipogenesis when administered in the first 20 h after hormonal induction, with 50% inhibition at the highest concentration tested. Importantly, no anti-adipogenic effect was evident when CC-410 was continuously dispensed after the early phase of adipogenesis, when the MCE window is already closed (Fig. 6A,B). This time-sensitive anti-adipogenic effect of CC-410 undeniably confirms that NNMT action is restricted to a discrete time interval from the middle to the end of MCE, concurrent with the cell fate commitment point. Importantly, the anti-adipogenic and phase sensitive effect of CC-410 was further confirmed in the mouse embryonic stem cell precursor cell line C3H10T1/2, demonstrating that the proposed mechanism is cell-type independent (Fig. 6D). It has been demonstrated that DEX provides a signal that primes pre-adipocytes toward differentiation as it activates a signalling cascade that is subsequently necessary for the pro-adipogenic action of IBMX62. Consistent with this, we observed that when 3T3-L1 was sequentially treated with DEX for 48 h followed by 48 h treatment with IBMX, the cells underwent terminal differentiation, while the opposite treatment failed to induce differentiation (Fig. 6E,F). Notably, we found that treatment with CC-410 during the 48 h of DEX stimulation strongly impaired adipogenesis, by inhibiting the DEX-primed pre-adipocytes state (Fig. 6F,G), demonstrating that NNMT is a key regulator of the glucocorticoid signalling network early in the commitment phase of adipogenesis.Figure 6 Time-dependent inhibition of NNMT using CC-410 molecule impairs terminal adipocyte differentiation by blocking the GC signaling cascade. (A) Post confluent 3T3-L1 cells were incubated with various concentrations of CC-410 with different schedules during the differentiation process. Oil Red-O-staining was assessed 10 days after adipogenic induction and quantified by OD measurement. Data are presented as means ± S.D. (n = 3) versus vehicle control (DMSO). (B) Representative images of culture plates following Oil Red-O staining in the untreated controls and CC-410 treated adipocytes. (C) Viability of 3T3-L1 cells treated with CC-410 (1–25 uM). Data are presented as average ± SEM normalized (% untreated control) versus CC-410 treated samples. (D) CC-410 treatments effectively inhibit adipogenesis in mouse embryonic stem cell precursor cell line C3H10T1/2. Representative microscope images (5× and 20×) of Oil Red-O stained C3H10T1/2 cell lines treated with vehicle control (DMSO) or 25 µM CC-410 in the first 48 h of DIM induction (Early phase) or continued throughout the period of differentiation (During adipogenesis). (E) Time schedule administration of the different combinations of hormonal inducers with/without CC-410 in 3T3-L1 cells. (F) Two days post-confluent 3T3-L1 were treated with the combinations indicated and stained 10 days later with Oil Red-O-staining. From top to bottom: DIM ± CC-410 48 h, IBMX ± CC-410 48 h followed by 48 h treatment with DEX and DEX ± CC-410 48 h followed by treatment with IBMX for 48 h. (G) Microscope images (5× and 20× magnifications) of Oil Red-O-staining of the DEX 48 h + IBMX 48 h condition with and without CC-410 treatment. Data represent three independent experiments each with at least three technical replicates. Statistical significance was calculated using a one-sided Welch’s t-test. For all panels: *p < 0.05; **p < 0.01; ***p < 0.001.
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Discussion
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Disclosing the molecular aspects and timing that coordinate the irreversible lineage commitment point and the molecular players that regulate this well-defined time lag is crucial to prevent hyperplasia and likely the onset and worsening of obesity. Although compelling evidence demonstrated that the genetic and chemical inhibition of NNMT protects against weight gain and associated negative metabolic effects in diet-induced obesity models, the upstream factors regulating its expression and the molecular patterns underling NNMT adipogenic function have not been characterized. By using the standard protocol for 3T3-L1 pre-adipocyte differentiation as an in vitro model that faithfully recapitulates the biology of adipose tissue and whose validity has been extensively corroborated in vivo4, we demonstrated that NNMT is an essential early player during the lineage commitment stage.
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We demonstrated that CEBPB, one of the initiators of the transcriptional cascade that triggers adipogenesis, transactivated Nnmt expression in response to DEX, and that deletion of CEBPB binding sites on Nnmt promoter impairs this transactivation. Nnmt-KO cell lines did not acquire the characteristic and specialized functions of terminal adipocytes but retained a fibroblast progenitor-like morphology. Accordingly, gene expression analysis demonstrated that depletion of Nnmt induces a reduction in the expression of late fat markers like Pparg, Cebpa and Lpl without affecting Cebpb.
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The link between the decision to terminally differentiate and both cell cycle length, particularly the G1 phase, and properly-timed cell cycle exit has been validated across several stem cell lineages63–65. Importantly, it has been demonstrated that cells that enter their final mitosis later do not differentiate58. Accordingly, we demonstrated that NNMT controls the adipocyte-commitment stage by regulating the proper timing of the cell cycle phases during MCE. In fact, NNMT deficiency delays permanent withdrawn from the cell cycle and shortens the length of the G1 phase as compared with control cell lines, which do differentiate.
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In order to unambiguously elucidate the role of NNMT during adipogenesis we used a complementary pharmacological approach to inhibit NNMT function. Compared to a genetic approach, the chemical inhibition of enzyme activity is an important tool for understanding complex regulatory mechanisms since small molecules allow the modulation of protein function in a tunable- and conditional manner. However, genetic and pharmacological approaches are not always truly equivalent as they may affect a protein’s activity in different ways and will therefore provide non-identical information about the protein’s biological function66,67.
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In this study we report the chemical and computational characterization of a novel small molecule NNMT inhibitor. We firstly demonstrated that CC-410 stably binds to and highly specifically inhibits NNMT, and then we used it to temporally modulate protein activity during pre-adipocyte differentiation stages. We demonstrated—to our knowledge for the first time—that the chemical inhibition of NNMT at the very early stages of adipogenesis impairs the ability of pre-adipocytes to terminally differentiate, acting by deregulating the glucocorticoid signalling network that primes the adipocyte precursor cells for differentiation. The overlapping results obtained here with both a chemical and a genetic approach, demonstrate the central role of NNMT in this cellular network and may help to define the mechanism of action of NNMTi compounds. In light of these results, NNMT can be considered as a potential therapeutic target not only, as previously described, to treat obesity but also to prevent early-onset and glucocorticoid-induced obesity.
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Acknowledgements
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The authors acknowledge Lilly’s Open Innovation Drug Discovery program (Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, USA) for preliminary results on the biological activity of CC-410. We thank Dr. Monica Álvarez-Fernández for kindly providing the pGL3 basic vector and the renilla luciferase pRL-CMV plasmid. We would like to thank Juan José Alba-Linares for help with bioinformatics analyses. We would like to thank Ronnie Lendrum for editorial assistance and all the members of Cancer Epigenetics and Nanomedicine laboratory (FINBA-ISPA, IUOPA, CINN-CSIC) for their positive feedback and helpful discussions.
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Author contributions
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A.R. and M.F.F. conceived and designed the study. I.D.-M. and A.D.-Q. performed computational chemistry studies. A.R, J.R.T, V.L, P.S.-O, R.G.U participated in data acquisition and experimental setup. J.R.T and R. F. P. analyzed the data. C.C and V.d.A. designed and synthetized NNMT inhibitor CC-410. J.L.F-M., M.L.M.-C., A.F.F, C.C. and V.d.A. contribute to design the study and supervise research. A.R, A.F.F and M.F.F wrote and reviewed the manuscript.
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Funding
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This work was supported by the Spanish Association Against Cancer (PROYE18061FERN to M.F.F.), the Asturias Government (PCTI) co-funding 2018-2023/FEDER (IDI/2018/146 and IDI/2021/000077 to M.F.F.), the Health Institute Carlos III (Plan Nacional de I+D+I) co-funding FEDER (PI18/01527 and PI21/01067 to M.F.F and A.F.F.), CIBERER Acciones Cooperativas y Complementarias Intramurales (ACCI20-35 to M.F.F.), the Fundación General CSIC (0348_CIE_6_E to M.F.F.), the ISCIII (COV00624 to J.R.T. and M.F.F.), ISPA and the Asociación Galbán (2021-052-INTRAMUR GALBAN-GOURR to R.G.U.), ISPA-Jannsen (2021-048-INTRAMURAL NOV-TEVAR to J.R.T.), CSIC (202020E092 to M.F.F), and the European Commission NextGenerationEU, through CSIC’s Global Health Platform (PTI Salud Global) and the Spanish Ministry of Science and Innovation through the Recovery, Transformation and Resilience Plan (SGL2021-03-39 and SGL2021-03-040). The authors are also grateful to the Spanish Ministry of Science and Innovation (PID2021-126663NB-100; CTQ2016-76829-R; PID2020-113473GB-I00), the Regional Government of Andalusia (BIO198 and P18-FR-3487) and the Ramón Areces Foundation (2021-2024). A.R. is supported by CSIC (SOLAUT_00038505 SGL2103040). J.R.T. is supported by a Juan de la Cierva fellowship from the Spanish Ministry of Science and Innovation MCIN/AEI/https://doi.org/10.13039/501100011033 (IJC2018-036825-I). R.F.P. (BP17-114) and P.S.M. (BP17-165) are supported by the Severo Ochoa program. R.G.U. is supported by the Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER). M.L.M.-C is supported by grants from Ministerio de Ciencia, Innovación y Universidades (MICINN) PID2020-117116RB-I00 integrated in Plan Estatal de Investigación Científica y Técnica y Innovación (to M.L.M.-C), and co-funded with Fondos FEDER (to M.L.M.-C), Subprograma Retos Colaboración RTC2019-007125-1 (to M.L.M.-C), La Caixa Foundation Program HR17-00601 (to MLM-C), Proyectos Investigación en Salud DTS20/00138 (to M.L.M.-C), Departamento de Industria del Gobierno Vasco (to M.L.M.-C), Elkartek (KK-2020/00008) (to M.L.M.-C). We also acknowledge support from the Institute of Oncology of Asturias (IUOPA, supported by Obra Social Cajastur Liberbank, Spain), the Health Research Institute of Asturias (ISPA-FINBA) and Consorcio Centro de Investigación Biomédica en Red (CIBERER-ISCIII).
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Data availability
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Raw RNA-Seq fastq files have been deposited at the European Nucleotide Archive (ENA) with the accession number PRJEB55900 (ERP140844); https://www.ebi.ac.uk/ena/browser/view/PRJEB55900.
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Competing interests
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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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Publisher's note
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Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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|
| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
STAR Protoc
|
| 4 |
+
STAR Protoc
|
| 5 |
+
STAR Protocols
|
| 6 |
+
2666-1667
|
| 7 |
+
Elsevier
|
| 8 |
+
|
| 9 |
+
S2666-1667(23)00268-X
|
| 10 |
+
10.1016/j.xpro.2023.102301
|
| 11 |
+
102301
|
| 12 |
+
Protocol
|
| 13 |
+
Protocol to evaluate the impact of murine MCT1-deficient CD8+ T cells on adipogenesis
|
| 14 |
+
Macchi Chiara chiara.macchi@unimi.it
|
| 15 |
+
14∗
|
| 16 |
+
Moregola Annalisa annalisa.moregola@unimi.it
|
| 17 |
+
14∗∗
|
| 18 |
+
Norata Giuseppe Danilo 12
|
| 19 |
+
Ruscica Massimiliano massimiliano.ruscica@unimi.it
|
| 20 |
+
135∗∗∗
|
| 21 |
+
1 Department of Pharmacological and Biomolecular Sciences “Rodolfo Paoletti,” Università degli Studi di Milano, 20133 Milan, Italy
|
| 22 |
+
2 SISA Center for the Study of Atherosclerosis, Bassini Hospital, Via M. Gorki 50, Cinisello Balsamo, 20092 Milan, Italy
|
| 23 |
+
3 Department of Cardio-Thoracic-Vascular Diseases - Foundation IRCCS Cà Granda Ospedale Maggiore Policlinico, Milan, Italy
|
| 24 |
+
∗ Corresponding author chiara.macchi@unimi.it
|
| 25 |
+
∗∗ Corresponding author annalisa.moregola@unimi.it
|
| 26 |
+
∗∗∗ Corresponding author massimiliano.ruscica@unimi.it
|
| 27 |
+
4 Technical contact
|
| 28 |
+
|
| 29 |
+
5 Lead contact
|
| 30 |
+
|
| 31 |
+
19 5 2023
|
| 32 |
+
16 6 2023
|
| 33 |
+
19 5 2023
|
| 34 |
+
4 2 102301© 2023 The Author(s)
|
| 35 |
+
2023
|
| 36 |
+
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
|
| 37 |
+
Summary
|
| 38 |
+
|
| 39 |
+
The infiltration of activated T cells, such as CD8+ effector, in metabolic tissues plays a crucial role for the initiation and propagation of obesity-induced inflammation. Given the pivotal role of lactate transporter monocarboxylate transporter 1 (MCT1) in immune cell activation, we present a protocol for the isolation and activation of CD8+ T lymphocytes selectively lacking MCT1. We describe steps for the induction of adipocyte differentiation, CD8+ T isolation and activation, and adipocyte-CD8+ T cell co-culture. We then detail qPCR analysis on differentiated adipocytes.
|
| 40 |
+
|
| 41 |
+
For complete details on the use and execution of this protocol, please refer to Macchi et al.1
|
| 42 |
+
|
| 43 |
+
Graphical abstract
|
| 44 |
+
|
| 45 |
+
Highlights
|
| 46 |
+
|
| 47 |
+
• Protocol to co-culture murine NIH-3T3 adipocytes and CD8+ T cells
|
| 48 |
+
|
| 49 |
+
• Steps for isolation of CD8+ T lymphocytes from lymph nodes and spleen of mice
|
| 50 |
+
|
| 51 |
+
• Investigating the impact of MCT1 deficiency in CD8+ T cells on adipogenesis
|
| 52 |
+
|
| 53 |
+
Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.
|
| 54 |
+
|
| 55 |
+
The infiltration of activated T cells, such as CD8+ effector, in metabolic tissues plays a crucial role for the initiation and propagation of obesity-induced inflammation. Given the pivotal role of lactate transporter monocarboxylate transporter 1 (MCT1) in immune cell activation, we present a protocol for the isolation and activation of CD8+ T lymphocytes selectively lacking MCT1. We describe steps for the induction of adipocyte differentiation, CD8+ T isolation and activation, and adipocyte-CD8+ T cell co-culture. We then detail qPCR analysis on differentiated adipocytes.
|
| 56 |
+
|
| 57 |
+
Subject areas
|
| 58 |
+
|
| 59 |
+
Cell Biology
|
| 60 |
+
Cell culture
|
| 61 |
+
Cell isolation
|
| 62 |
+
Flow Cytometry/Mass Cytometry
|
| 63 |
+
Metabolism
|
| 64 |
+
Model Organisms
|
| 65 |
+
Molecular Biology
|
| 66 |
+
==== Body
|
| 67 |
+
pmcBefore you begin
|
| 68 |
+
|
| 69 |
+
The protocol below primarily focuses on an in vitro co-culture between CD8+ T cells, specifically lacking monocarboxylate transporter 1 (MCT1), and murine adipocytes (NIH-3T3 cells).1. Prepare all the buffers required for the protocol: RPMI-10, MACS buffer, complete DMEM for culturing NIH-3T3 pre-adipocytes and maintain them sterile at 4°C.
|
| 70 |
+
|
| 71 |
+
2. Generation of the animal model (http://www.informatics.jax.org/reference/J:328998).
|
| 72 |
+
|
| 73 |
+
Breed mice carrying floxed alleles of Slc16a1 (termed Slc16a1f/f) on the C57BL/6 genetic background with CD4cre+ mice (kindly given by Prof. Marelli-Berg, Queen Mary University of London, UK) for specific deletion of Slc16a1 in both CD4+ and CD8+ T lymphocytes.3. Since the aim of this protocol is to assess late stages of adipogenesis, it is necessary that the preadipocytes are already in an advanced phase of the differentiation process when the lymphocytes are ready for the co-cultured.
|
| 74 |
+
|
| 75 |
+
Differentiation of NIH-3T3 pre-adipocytes in mature adipocytes2 (Figure 1A).a. Seed 6-well plates with NIH-3T3 preadipocytes at 100,000 cells per well. Use Dulbecco’s Modified Eagle’s Medium (DMEM) – high glucose supplemented with 10% FBS, 1% L-glutamine and 1% Penicillin-Streptomycin (10,000 U/mL) (complete DMEM). Use 2 mL of medium for each well.
|
| 76 |
+
|
| 77 |
+
b. Let cells to grow at 37°C with 5% of CO2 until they reach confluence.
|
| 78 |
+
|
| 79 |
+
c. Leave NIH-3T3 preadipocytes to grow for further 2 days (T0), after which the differentiation into mature adipocytes can be induced.
|
| 80 |
+
|
| 81 |
+
d. Replace the cell growth medium with a differentiation cocktail composed of complete DMEM (high glucose) containing insulin (10 μg/mL), dexamethasone (1μM), 3-isobutyl-1- methylxanthine - IBMX - 0.5 mM) for further 2 days (T2).i. Prepare insulin by a stock solution of 5 mg/mL in HCl 0.1M; dexamethasone by a stock solution of 5mM in EtOH 100%; IBMX by a stock solution of 250 mM in KOH 0.35M.
|
| 82 |
+
|
| 83 |
+
e. Replace the differentiation medium with the differentiation-maintenance one, consisting of complete DMEM (high glucose) containing insulin (10 μg/mL).i. Let the cells grow in this medium until day 6 (T6).
|
| 84 |
+
|
| 85 |
+
f. At day 6 co-culture adipocytes with CD8+ T cells.Note: This step (f) will last until day 9 (T9) which corresponds to the end of the differentiation protocol.
|
| 86 |
+
|
| 87 |
+
Figure 1 Step-by-step description of adipogenesis analysis in adipocytes co-cultured with activated CD8+ T cells
|
| 88 |
+
|
| 89 |
+
(A) Schematic representation of the co-culture timeline between activated CD8+ T cells and NIH-3T3 differentiated murine adipocytes. T0 represents the timepoint the differentiation of NIH-3T3 into mature adipocytes is induced.
|
| 90 |
+
|
| 91 |
+
(B) Example of results obtained by co-culturing activated CD8+ T lymphocytes with NIH-3T3 differentiated murine adipocytes. CD8+ T lymphocytes were isolated from Slc16a1f/fTcellcre mice selectively lacking MCT1 in CD8+T cells and their counterpart Slc16a1f/f mice. After activation, CD8+T cells were co-cultured with mature adipocytes. The gene expression of the adipogenic genes, Lpl and Glut 4 is reported.1 n= 5 per group. Glut4, glucose transporter type 4; Lpl, lipoprotein lipase; Slc16a1, solute carrier family 16 member 1 (monocarboxylic transporter 1). ∗p< 0.05 and ∗∗∗p< 0.001 (as assessed by Student's t-test).
|
| 92 |
+
|
| 93 |
+
Institutional permissions
|
| 94 |
+
|
| 95 |
+
All animal procedures were performed in accordance with the guidelines from directive 2010/63/EU of the European Parliament on the protection of animals used for scientific purposes and were approved by the Ethical Committee (Authorization 780/2016 to MR).
|
| 96 |
+
|
| 97 |
+
Key resources table
|
| 98 |
+
|
| 99 |
+
REAGENT or RESOURCE SOURCE IDENTIFIER
|
| 100 |
+
Antibodies
|
| 101 |
+
|
| 102 |
+
Purified anti-mouse CD3 antibody BioLegend Cat: 102102; RRID: AB_312659
|
| 103 |
+
Purified anti-mouse CD28 antibody BioLegend Cat: 102102; RRID: AB_312867
|
| 104 |
+
Anti-mouse CD69 APC-Cy7 antibody BD Pharmingen Cat: 561240 RRID: AB_10611852
|
| 105 |
+
|
| 106 |
+
Chemicals, peptides, and recombinant proteins
|
| 107 |
+
|
| 108 |
+
3-isobutyl-1-methylxanthine (IBMX) Merck (Sigma-Aldrich) Cat: I5869
|
| 109 |
+
Dexamethasone Merck (Sigma-Aldrich) Cat: D1756
|
| 110 |
+
Insulin Merck (Sigma-Aldrich) Cat: I6634
|
| 111 |
+
eBioscience™ 1X RBC Lysis Buffer Thermo Fisher Scientific Cat: 00-4333-57
|
| 112 |
+
Human recombinant IL-2 PeproTech Cat: #GMP200-02
|
| 113 |
+
|
| 114 |
+
Critical commercial assays
|
| 115 |
+
|
| 116 |
+
EasySep™ mouse CD8+ T cell isolation kit STEMCELL Cat: #19853
|
| 117 |
+
RNeasy Mini Kit (50) Qiagen Cat: 74104
|
| 118 |
+
|
| 119 |
+
Experimental models: Cell lines
|
| 120 |
+
|
| 121 |
+
Mouse: NIH-3T3-L1 ATCC CL-173
|
| 122 |
+
|
| 123 |
+
Experimental models: Organisms/strains
|
| 124 |
+
|
| 125 |
+
Mouse: Slc16a1flox/flox
|
| 126 |
+
For breeding;- Age: 7 weeks
|
| 127 |
+
|
| 128 |
+
- Sex: male and female
|
| 129 |
+
|
| 130 |
+
Sonveaux Pierre N/A
|
| 131 |
+
Mouse: CD4cre+
|
| 132 |
+
For breeding;- Age: 7 weeks
|
| 133 |
+
|
| 134 |
+
- Sex: male and female
|
| 135 |
+
|
| 136 |
+
Marelli-Berg Federica N/A
|
| 137 |
+
Mouse: Slc16a1flox/flox selectively lacking MCT1 in CD8+T cells
|
| 138 |
+
For CD8+T lymphocytes isolation:- Age: 28 weeks
|
| 139 |
+
|
| 140 |
+
- Sex: male
|
| 141 |
+
|
| 142 |
+
N/A N/A
|
| 143 |
+
|
| 144 |
+
Oligonucleotides
|
| 145 |
+
|
| 146 |
+
Primers: Cebpα
|
| 147 |
+
Fw: GAACAGCTGAGCCGTGAACT
|
| 148 |
+
Rev: TAGAGATCCAGCGACCCGAA Metabion https://wop.metabion.com
|
| 149 |
+
Primers: Cebpδ
|
| 150 |
+
Fw: GAACCCGCGGCCTTCTAC
|
| 151 |
+
Rev: GAAGAGTTCGTCGTGGCACA Metabion https://wop.metabion.com
|
| 152 |
+
Primers: Cidea
|
| 153 |
+
Fw: CACGCATTTCATGATCTTGG
|
| 154 |
+
Rev: CCTGTATAGGTCGAAGGTGA Metabion https://wop.metabion.com
|
| 155 |
+
Primers: Glut4
|
| 156 |
+
Fw: GCTCTGACGATGGGGAACC
|
| 157 |
+
Rev: GCCACGTTGCATTGTAGCTC Metabion https://wop.metabion.com
|
| 158 |
+
Primers: Lep
|
| 159 |
+
Fw: CAAGCAGTGCCTATCCAGA
|
| 160 |
+
Rev: AAGCCCAGGAATGAAGTCCA Metabion https://wop.metabion.com
|
| 161 |
+
Primers: Lpl
|
| 162 |
+
Fw: TCGGGCCCAGCAACATTATC
|
| 163 |
+
Rev: TGGTCAGACTTCCTGCTACG Metabion https://wop.metabion.com
|
| 164 |
+
Primers: Pparδ
|
| 165 |
+
Fw: TCTCCCAGAATTCCTCCCCT
|
| 166 |
+
Rev: GAGCTTCATGCGGATTGTCC Metabion https://wop.metabion.com
|
| 167 |
+
Primers: Pparγ
|
| 168 |
+
Fw: TGTGAGACCAACAGCCTGAC
|
| 169 |
+
Rev: AAGTTGGTGGGCCAGAATGG Metabion https://wop.metabion.com
|
| 170 |
+
Primers: Ppargc1α
|
| 171 |
+
Fw: CATTTGATGCACTGACAGATGGA
|
| 172 |
+
Rev: GTCAGGCATGGAGGAAGGAC Metabion https://wop.metabion.com
|
| 173 |
+
Primers: Rpl13a
|
| 174 |
+
Fw:GCGCCTCAAGTGGTGTTGGAT
|
| 175 |
+
Rev: GAGCAGCAGGGACCACCAT Metabion https://wop.metabion.com
|
| 176 |
+
|
| 177 |
+
Software and algorithms
|
| 178 |
+
|
| 179 |
+
GraphPad-Prism8 GraphPad https://www.graphpad.com/scientific-software/prism
|
| 180 |
+
Novoexpress Agilent https://www.agilent.com/en/product/research-flow-cytometry/flow-cytometry-software/novocyte-novoexpress-software-1320805
|
| 181 |
+
Bio-Rad CFX Manager Bio-Rad https://www.bio-rad.com/it-it/sku/1845000-cfx-manager-software?ID=1845000
|
| 182 |
+
|
| 183 |
+
Other
|
| 184 |
+
|
| 185 |
+
Counting chamber, Fast Read® 102 VWR Cat: 630-1893
|
| 186 |
+
Costar® 6-well cell culture plates (Product number: 3516) Merck (Sigma-Aldrich) Cat: 3516
|
| 187 |
+
Costar® 24 mm Transwell® with 0.4 μm Pore Polycarbonate Membrane Insert, Sterile Corning Cat: 3412
|
| 188 |
+
Maxima First Strand cDNA Synthesis Kit for RT-qPCR Thermo Fisher Cat: K1642
|
| 189 |
+
Maxima SYBR Green/Fluorescein qPCR Master Mix (2X) Thermo Fisher Cat: K0242
|
| 190 |
+
EasySep Magnet STEMCELL Cat: #18000
|
| 191 |
+
|
| 192 |
+
Materials and equipment
|
| 193 |
+
|
| 194 |
+
PCR cycling conditions are showed in Figure 2.Alternatives: For the real time PCR procedure, we use the instrument CFX Connect Real-Time System (Bio-Rad) although a different real-time PCR detection system can be used.
|
| 195 |
+
|
| 196 |
+
Alternatives: To determine CD8+ T cells activation we use the Novocyte 3000 cytofluorimeter but any other cytofluorimeter can be used as long as it has the laser to read the fluorophore used for the staining. We use CD69 APC-Cy7 which requires the 640 nm laser for excitation and has an emission peak of 799 nm, but it is possible to change the antibody used with another one with proper characteristics readable by the instrument.
|
| 197 |
+
|
| 198 |
+
RPMI-10
|
| 199 |
+
|
| 200 |
+
Reagent Final concentration Amount
|
| 201 |
+
RPMI 1640 N/A 429.5 mL
|
| 202 |
+
FBS (fetal bovine serum) 10% 50 mL
|
| 203 |
+
Sodium pyruvate (100mM) 1 mM 5 mL
|
| 204 |
+
HEPES (1M) 10 mM 5 mL
|
| 205 |
+
β-Mercaptoethanol (50mM) 50 μM 500 μL
|
| 206 |
+
Penicillin/Streptomycin 1% 5 mL
|
| 207 |
+
Glutamine (200mM) 2 mM 5 mL
|
| 208 |
+
Total N/A 500 mL
|
| 209 |
+
Store at 4°C. Heat to 37°C before use.
|
| 210 |
+
|
| 211 |
+
MACS buffer:
|
| 212 |
+
|
| 213 |
+
Reagent Final concentration Amount
|
| 214 |
+
PBS N/A 488 mL
|
| 215 |
+
FBS (fetal bovine serum) 2% 10 mL
|
| 216 |
+
EDTA (0.5M) 2 mM 2 mL
|
| 217 |
+
Total N/A 500 mL
|
| 218 |
+
Store at 4°C for at maximum 30 days
|
| 219 |
+
|
| 220 |
+
Note: Check before use if the buffer has floating particles. To overcome this issue, it is mandatory to filter the buffer with a sterile filter under the hood to be sure to use only sterile buffer.
|
| 221 |
+
|
| 222 |
+
Complete DMEM for culturing NIH-3T3 pre-adipocytes:
|
| 223 |
+
|
| 224 |
+
Reagent Final concentration Amount
|
| 225 |
+
Dulbecco’s Modified Eagle’s Medium (DMEM) – high glucose N/A 440 mL
|
| 226 |
+
FBS (fetal bovine serum) 10% 50 mL
|
| 227 |
+
L-glutamine 1% 5 mL
|
| 228 |
+
Penicillin-Streptomycin (10,000 U/mL) 1% 5 mL
|
| 229 |
+
Total N/A 500 mL
|
| 230 |
+
Store the medium at 4°C for at maximum 30 days. Heat to 37°C before use.
|
| 231 |
+
|
| 232 |
+
Figure 2 PCR cycling conditions
|
| 233 |
+
|
| 234 |
+
Initial denaturation (95°C for 10 min). Repeat 40 cycles of denaturation (95°C for 15 seconds) and annealing (60°C for 1 min).
|
| 235 |
+
|
| 236 |
+
Step-by-step method details
|
| 237 |
+
|
| 238 |
+
CD8+ T lymphocytes isolation from lymph nodes and spleen
|
| 239 |
+
|
| 240 |
+
Timing: 2.5 h
|
| 241 |
+
|
| 242 |
+
This section describes how to collect mice lymph nodes and spleen and how to process these tissues to obtain a uniform cell suspension for the isolation of CD8+ T cells to be used for the co-culture with mouse adipocytes NIH-3T3 cells.1. Collect the lymph nodes and spleen.a. Euthanize mouse with isoflurane (2%) or other approved methods.
|
| 243 |
+
|
| 244 |
+
b. Open the abdomen of the mice by using surgical scissors and tweezers. It is important to lift the skin without opening the peritoneum.i. Collect the two inguinal lymph nodes located in the subcutaneous adipose tissue of the inguinal left and right regions.
|
| 245 |
+
|
| 246 |
+
ii. Collect brachial and axillary lymph nodes located in the axillary left and right regions.
|
| 247 |
+
|
| 248 |
+
iii. Ensure to eliminate the surrounding adipose tissue.
|
| 249 |
+
|
| 250 |
+
iv. Place the organs collected in a 48-well plate containing 500μL of MACS buffer (PBS/2% FBS/2 μM EDTA) each well.3
|
| 251 |
+
|
| 252 |
+
c. Open the peritoneal cavity and collect the spleen which is located inside the rib cage on the left, above the stomach. Place the organ in the 48-well plate containing 500 μL of MACS buffer previously used also for lymph nodes.
|
| 253 |
+
|
| 254 |
+
2. Prepare a uniform cell suspension of primary lymphocytes from the lymph nodes and spleen.a. In a sterile biosafety cabinet, place a 70 μm cell strainer on top of a 50 mL tube.
|
| 255 |
+
|
| 256 |
+
b. Mash the lymph nodes and spleen, through the strainer by using a 1mL syringe plunger and 10 mL MACS buffer.Note: the percentage of CD8+ T cells obtained from the cell suspension (derived both from lymph nodes and spleen) is less than 10%.
|
| 257 |
+
|
| 258 |
+
c. Centrifuge the cells at 500 g for 5 min, aspirate the supernatant with the vacuum and resuspend the pellet in 1 mL of eBioscience™ 1X RBC Lysis Buffer. RBC or red blood lysis buffer is used for the lysis of erythrocytes in single-cell suspension. Leave the suspension at 4°C for 5 min.
|
| 259 |
+
|
| 260 |
+
d. Bring up the suspension to a volume of 10 mL by using MACS buffer. This step allows us to wash the cells. Centrifuge the suspension for 5 min at 500 g.Note: If there is a need to pool out lymph nodes and spleen collected from more than one mouse, then increase the volume of lysis buffer, and wash the cells with at least 3 times the volume of the lysis buffer used.
|
| 261 |
+
|
| 262 |
+
e. Aspirate the supernatant and resuspend the cells in 10 mL of MACS buffer.
|
| 263 |
+
|
| 264 |
+
f. Count the cells in the counting chamber by using a 1:20 dilution in Trypan blue.Note: Whether the number of cells is too high to be counted in the squares of the chamber, it is necessary to increase the dilution to limit count errors.
|
| 265 |
+
|
| 266 |
+
3. Isolate CD8+ T lymphocytes with negative selection beads present in the EasySep™ mouse CD8+ T cell isolation kit.a. Centrifuge cells at 500 g for 5 min.
|
| 267 |
+
|
| 268 |
+
b. Resuspend the cells in MACS buffer in order to achieve a concentration of 1×108 cells per mL and then transfer samples in a 5 mL sterile polystyrene round bottom tube.Note: For the isolation protocol, we usually use the EasySep™ magnet with which the isolation can be performed with 2 mL as a maximum volume of cells. If you have more than 2×108, divide the sample for two isolations, in two different tubes.
|
| 269 |
+
|
| 270 |
+
c. Add rat serum 50 μL/mL and 50 μL/mL of isolation cocktail supplied with the kit. This cocktail is done by biotinylated monoclonal antibodies against non-CD8+ T cells dissolved in PBS and 0.1% BSA. Mix briefly and incubate 10 min at 22°C.
|
| 271 |
+
|
| 272 |
+
d. Vortex the beads vial present in the kit for 10 s and add a concentration of 125 μL/mL to each sample.
|
| 273 |
+
|
| 274 |
+
e. Vortex rapidly and leave the tubes for 5 min at 22°C.
|
| 275 |
+
|
| 276 |
+
f. Fill in the tube with MACS buffer until reaching a volume of 2.5 mL.
|
| 277 |
+
|
| 278 |
+
g. Place the tube into the magnet and incubate for 2.5 min.
|
| 279 |
+
|
| 280 |
+
h. Pour the enriched cells by inverting the magnet and collect the CD8+ T cells in a new 15 mL tube.
|
| 281 |
+
|
| 282 |
+
i. Count the enriched cells with Trypan Blue with a 1:10 dilution.
|
| 283 |
+
|
| 284 |
+
j. Resuspend the cells in RPMI-10 medium in order to achieve a cell concentration of 2×106 cells/mL.
|
| 285 |
+
|
| 286 |
+
k. CD8+ T cells are ready for cells activation.Note: To assess CD8+ T cell activation, save an aliquot of your cells (2×105 cells are sufficient) to perform the cytometry staining the same day of the isolation (flow cytometry staining and evaluation of activation is described in the next paragraph 2 “Activation assessment”).
|
| 287 |
+
|
| 288 |
+
CD8+ T lymphocyte activation
|
| 289 |
+
|
| 290 |
+
Timing: 25 h
|
| 291 |
+
|
| 292 |
+
This section explains in detail how to activate CD8+ T lymphocytes in vitro and how to assess their activation through flow cytometry.4. In vitro activation.a. Coat a 12-well plate with 500 μL per well anti-CD3 (0.5 μg/mL) and CD28 (2.5 μg/mL) diluted in PBS, for 1 h at 37°C.4CRITICAL: The coating must be performed in PBS and not in MACS buffer because the presence of fetal bovine serum (FBS) can reduce the efficiency of anti-CD3 and anti-CD28 coating.
|
| 293 |
+
|
| 294 |
+
b. Aspirate the coating and plate 2×106 of isolated CD8+ T lymphocytes in each well ensuring to reach a final volume of 2.5 mL of complete RPMI medium (R10; RPMI plus 10% FBS, glutamine, HEPES, 2-ME, sodium pyruvate and antibiotics) preheated at 37°C.
|
| 295 |
+
|
| 296 |
+
c. Add interleukin (IL)-2 at a concentration of 25 U/mL and leave the cells to be activated for 24 h at 37°C in the presence of 5% CO2.
|
| 297 |
+
|
| 298 |
+
5. Harvesting of CD8+ T cells.a. After 24h of incubation, collect CD8+ T cells from the 12-well plate into a 15 mL tube. Use a 1 mL pipette.Note: if you have many wells to collect, use a 50 mL tube.
|
| 299 |
+
|
| 300 |
+
b. Add 1 mL of MACS buffer to the well and pipette again to be sure to collect all the cells.Note: to ensure that all cells are collected before throwing away the plate, add 1 mL of PBS to the well and check at the microscope to see if the plate is free of cells. Otherwise pipette again and add the solution to the previous collected cells.
|
| 301 |
+
|
| 302 |
+
c. Centrifuge the 15 mL tube containing the cells at 500 g for 5 min.
|
| 303 |
+
|
| 304 |
+
d. Aspirate the supernatant and resuspend the pellet with MACS buffer to allow the cells to be counted. Use Trypan Blue, as described above.
|
| 305 |
+
|
| 306 |
+
e. Centrifuge the 15 mL tube containing the cells at 500 g for 5 min.
|
| 307 |
+
|
| 308 |
+
f. Resuspend the counted cells in R10 complete medium to achieve a 2×106 cells every 1.5 mL.
|
| 309 |
+
|
| 310 |
+
g. CD8+ T cells are now ready to be co-cultured with adipocytes.
|
| 311 |
+
|
| 312 |
+
6. Activation assessment: the staining with anti-CD69 APC-Cy7, an early activation marker, allows us to evaluate changes in cell physical parameters.Note: If you want to evaluate the activation of the CD8+ T cells, you must compare the cells before the induction of activation with the activated ones, and you need to perform the same staining for not activated cells the day of the isolation and 24 h post activation (2×105 cells are sufficient for the staining).
|
| 313 |
+
|
| 314 |
+
a. Transfer 2×105 cells in a 96 well plate (V-bottom).
|
| 315 |
+
|
| 316 |
+
b. Centrifuge the plate at 800 g for 5 min.
|
| 317 |
+
|
| 318 |
+
c. Discard the supernatant and resuspend the pellet with 50 μL MACS buffer containing 0.5 μL of anti-CD69 antibody per well.
|
| 319 |
+
|
| 320 |
+
d. Incubate for 30 min at 4°C in the dark.
|
| 321 |
+
|
| 322 |
+
e. Add 150 μL of MACS buffer to each well to wash the cells.
|
| 323 |
+
|
| 324 |
+
f. Centrifuge 5 min at 800 g.
|
| 325 |
+
|
| 326 |
+
g. Repeat steps “e” and “f” once more.
|
| 327 |
+
|
| 328 |
+
h. Resuspend each well with 100 μL of MACS buffer and transfer cells to a 5 mL tube.
|
| 329 |
+
|
| 330 |
+
i. Bring each sample to a final volume of 250 μL with MACS buffer.
|
| 331 |
+
|
| 332 |
+
j. Acquire the samples with the cytofluorimeter: compare median of the forward scatter, the side scatter and CD69 fluorescence intensity between basal and activated cells (Figure 3).Note: During the activation process, the dimension (cell size) and complexity (cell granularity) of CD8+ T cells are raised. These features translate into a shift in the median fluorescence intensity read in the forward scatter (a physical parameter that refers to the cell size) and the side scatter (an index of cell granularity or complexity). The expression of cluster of differentiation (CD)69, a marker of early activation, increases rapidly after activation leading to a higher fluorescence that is detected in cytofluorimetric analysis if compared to a CD8+ T cell not stimulated.
|
| 333 |
+
|
| 334 |
+
Figure 3 Flow cytometry analysis of activated CD8+ T cells
|
| 335 |
+
|
| 336 |
+
The Left panel shows the comparison of forward scatter median fluorescence intensity between basal and activated cells.
|
| 337 |
+
|
| 338 |
+
The central panel comparison of forward scatter median fluorescence intensity between basal and activated cells. The right panel comparison of CD69 median fluorescence intensity between basal and activated cells.
|
| 339 |
+
|
| 340 |
+
Co-culture between activated CD8+ T lymphocytes and murine NIH-3T3 cells
|
| 341 |
+
|
| 342 |
+
Timing: 3 days
|
| 343 |
+
|
| 344 |
+
This section describes how to co-culture differentiating NIH-3T3 cells with CD8+ T lymphocytes to evaluate the impact of the MCT1 expression in CD8+ T lymphocytes on late stages of adipogenesis.7. Co-culture (Figure 1A).a. At day 6 (T6) of the differentiation protocol, put a transwell insert and add on the insert 2×106 activated CD8+ T cells, in a 1.5 mL volume, in each well of the 6-well plate.
|
| 345 |
+
|
| 346 |
+
b. Let the co-culture to growth for further three days, until the last day of the preadipocytes differentiation into mature adipocytes (T9).
|
| 347 |
+
|
| 348 |
+
c. Remove the transwell inserts and harvest cells from each well of the 6-well plate
|
| 349 |
+
|
| 350 |
+
8. RNA isolationa. Extract RNA through a spin column isolation method.Note: To isolate RNA, we usually use the RNeasy Mini Kit (Qiagen), but any other kit that allows for a good yield of high-quality RNA can be used.
|
| 351 |
+
|
| 352 |
+
b. Perform a reverse transcription to synthesize cDNA.Note: To obtain cDNA, we usually reverse transcribe 1 μg/μL of RNA with Maxima First Strand cDNA Synthesis Kit for RT-qPCR (Thermo fisher).5 Any other kit which ensures a good efficiency in cDNA synthesis can be used. If the RNA yield is low, reverse transcribe 0.5 μg/μL of RNA.
|
| 353 |
+
|
| 354 |
+
c. Perform a qPCR analysis to evaluate the expression of key genes involved in the adipogenesis, e.g., Cebpα (CCAAT/enhancer binding protein), Cebpδ, Cidea (cell death inducing DFFA like effector a), Glut4 (glucose transporter type 4), Lep (leptin), Lpl (lipoprotein lipase), Ppar (peroxisome proliferator-activated receptor) δ, Pparγ, Ppargc1α (Pparg coactivator 1 alpha). RPL (ribosomal protein L) 13a can be used as a housekeeping.Note: To perform a qPCR analysis, we usually use Maxima SYBR Green/Fluorescein qPCR Master Mix (2X) with a final concentration of primers of 300nM allowing a good efficiency (e.g, between 90% and 110% 6). Any other kit ensuring a good DNA detection and analysis together with a high PCR specificity and sensitivity can be used. It is mandatory to test primer efficiencies before performing the experiments.
|
| 355 |
+
|
| 356 |
+
Note: the in vitro adipogenesis is composed by two phases, each of which is characterized by the activation of different genes. Therefore, the day of the differentiation protocol in which to start the co-culture should depends on which stage of adipogenesis needs to be analyzed. Co-culturing activated CD8+ T cells at day 6 of the differentiation protocol allows to evaluate the possible effect on the second phase of adipogenesis, by studying the expression of genes such as GLUT4 and LPL (Figure 1).
|
| 357 |
+
|
| 358 |
+
Expected outcomes
|
| 359 |
+
|
| 360 |
+
The outcome of the present protocol is to give an in vitro tool to evaluate the potential crosstalk between CD8+ T cells, isolated from mice carrying a specific deletion of Slc16a1 in CD8+ T lymphocytes, and adipocytes. Indeed, the expression of cellular lactate transporter MCT1 (known as Slc16a1) increases during immune cell activation to cope with the metabolic reprogramming.7 During an obesogenic diet, while adipose tissue expands via adipocyte hypertrophy or via the formation of new adipocytes through differentiation of resident precursors,8 the accumulation of pro-inflammatory CD8+ T cells in metabolic tissues seems to be crucial for the initiation of obesity-induced inflammation.9 The evaluation of the effects of activated CD8+ T cells on adipogenesis could thus simplify the in vitro study of the immune-adipose tissue axis in both health and pathological conditions, such as obesity. The expected outcome is a downregulation of adipogenic genes driven by CD8+ T lymphocytes selectively lacking MCT1.1
|
| 361 |
+
|
| 362 |
+
Limitations
|
| 363 |
+
|
| 364 |
+
This protocol must be interpreted within a series of limitations. We activate CD8+ T cells with anti-CD3 and anti-CD28 but this is not the only protocol that can be used. It is interesting to activate T lymphocytes by using PMA and ionomycin. Since this method of activation is stronger, the timing of stimulation before co-culturing CD8+ T cells with adipocytes has to be reduced.10 Moreover, it is important to note that besides NIH-3T3 cells, other cellular models of preadipocytes could be used, such as C3H/10T1/2. In this case, the correct differentiation protocol must be used to obtain mature adipocytes at the end of the experiment.11 Lastly, the entire protocol is set up on animal in vivo and in vitro models. If the effect of human CD8+ T lymphocytes on human preadipocytes needs to be investigated, then several technical changes are required.
|
| 365 |
+
|
| 366 |
+
Troubleshooting
|
| 367 |
+
|
| 368 |
+
Problem 1
|
| 369 |
+
|
| 370 |
+
After lysis of erythrocytes with RBC lysis buffer the pellet after centrifugation is still red (step 2b).
|
| 371 |
+
|
| 372 |
+
Potential solution
|
| 373 |
+
|
| 374 |
+
Repeat the step. Add again 1 mL of RBC lysis buffer and leave the suspension at 4°C for 5 min. Bring up the suspension to a volume of 10 mL with MACS buffer. Centrifuge the suspension for 5 min at 500 × g and resuspend the pellet with 10 mL of MACS buffer.
|
| 375 |
+
|
| 376 |
+
Problem 2
|
| 377 |
+
|
| 378 |
+
Co-culturing NIH-3T3 cells at day 6 of the differentiation with CD8+ T lymphocytes does not affect adipogenesis (step 7).
|
| 379 |
+
|
| 380 |
+
Potential solution
|
| 381 |
+
|
| 382 |
+
It may be that the effect is not in the last stages of the process but in the first ones. To test whether this hypothesis is correct the co-culture could be started at day (T0) of the differentiation protocol. After 72h the RNA could be collected and the expression of adipogenic genes assessed. In this case an effect is expected on regulators of the early phase of adipogenesis, such as PPARγ.
|
| 383 |
+
|
| 384 |
+
Resource availability
|
| 385 |
+
|
| 386 |
+
Lead contact
|
| 387 |
+
|
| 388 |
+
Massimiliano Ruscica massimiliano.ruscica@unimi.it.
|
| 389 |
+
|
| 390 |
+
Materials availability
|
| 391 |
+
|
| 392 |
+
MCT1 mouse lines generated in this study have been deposited to https://www.informatics.jax.org/reference/J:328998.
|
| 393 |
+
|
| 394 |
+
Data and code availability
|
| 395 |
+
|
| 396 |
+
For complete details on data and codes, please refer to Macchi et al.1
|
| 397 |
+
|
| 398 |
+
Acknowledgments
|
| 399 |
+
|
| 400 |
+
The work of the authors is supported by 10.13039/501100002803 Fondazione Cariplo 2015-0552 (M.R.), 2018-0511 (M.R.), and 2019-1560 (F.B.) and Telethon Foundation [GGP19146], Progetti di Rilevante Interesse Nazionale [PRIN 2017 K55HLC], Ricerca Finalizzata, Italian Ministry of Health [RF-2019-12370896], PNRR NextGenerationEU [M4C2-Investimento 1.4-CN00000041 National Center for Gene Therapy and Drugs based on RNA Technology], PNRR NextGenerationEU [Multilayered Urban Sustainability Action – MUSA], and PNRR-MAD-2022-12375913 to G.D.N.
|
| 401 |
+
|
| 402 |
+
Author contributions
|
| 403 |
+
|
| 404 |
+
C.M. and A.M. performed most of the experiments and drafted the manuscript. M.R. and G.D.N. critically contributed to both the study design and the review of the manuscript for important intellectual input. M.R. and G.D.N. conceived and wrote the manuscript.
|
| 405 |
+
|
| 406 |
+
Declaration of interests
|
| 407 |
+
|
| 408 |
+
The authors declare no competing interests.
|
| 409 |
+
==== Refs
|
| 410 |
+
References
|
| 411 |
+
|
| 412 |
+
1 Macchi C. Moregola A. Greco M.F. Svecla M. Bonacina F. Dhup S. Dadhich R.K. Audano M. Sonveaux P. Mauro C. Monocarboxylate transporter 1 deficiency impacts CD8(+) T lymphocytes proliferation and recruitment to adipose tissue during obesity iScience 25 2022 104435 10.1016/j.isci.2022.104435 35707720
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| 413 |
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2 Gilardi F. Giudici M. Mitro N. Maschi O. Guerrini U. Rando G. Maggi A. Cermenati G. Laghezza A. Loiodice F. LT175 is a novel PPARalpha/gamma ligand with potent insulin-sensitizing effects and reduced adipogenic properties J. Biol. Chem. 289 2014 6908 6920 10.1074/jbc.M113.506394 24451380
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| 414 |
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3 Bonacina F. Moregola A. Svecla M. Coe D. Uboldi P. Fraire S. Beretta S. Beretta G. Pellegatta F. Catapano A.L. The low-density lipoprotein receptor-mTORC1 axis coordinates CD8+ T cell activation J. Cell Biol. 221 2022 e202202011 10.1083/jcb.202202011 36129440
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4 Palma C. La Rocca C. Gigantino V. Aquino G. Piccaro G. Di Silvestre D. Brambilla F. Rossi R. Bonacina F. Lepore M.T. Caloric restriction promotes immunometabolic reprogramming leading to protection from tuberculosis Cell Metab. 33 2021 300 318.e12 10.1016/j.cmet.2020.12.016 33421383
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| 416 |
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5 Macchi C. Greco M.F. Botta M. Sperandeo P. Dongiovanni P. Valenti L. Cicero A.F.G. Borghi C. Lupo M.G. Romeo S. Leptin, resistin, and proprotein convertase subtilisin/Kexin type 9: the role of STAT3 Am. J. Pathol. 190 2020 2226 2236 10.1016/j.ajpath.2020.07.016 32798443
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6 Macchi C. Greco M.F. Ferri N. Magni P. Arnoldi A. Corsini A. Sirtori C.R. Ruscica M. Lammi C. Impact of soy beta-conglycinin peptides on PCSK9 protein expression in HepG2 cells Nutrients 14 2021 193 10.3390/nu14010193 35011066
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| 418 |
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7 Murray C.M. Hutchinson R. Bantick J.R. Belfield G.P. Benjamin A.D. Brazma D. Bundick R.V. Cook I.D. Craggs R.I. Edwards S. Monocarboxylate transporter MCT1 is a target for immunosuppression Nat. Chem. Biol. 1 2005 371 376 10.1038/nchembio744 16370372
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| 419 |
+
8 Sun K. Kusminski C.M. Scherer P.E. Adipose tissue remodeling and obesity J. Clin. Invest. 121 2011 2094 2101 10.1172/JCI45887 21633177
|
| 420 |
+
9 Nishimura S. Manabe I. Nagasaki M. Eto K. Yamashita H. Ohsugi M. Otsu M. Hara K. Ueki K. Sugiura S. CD8+ effector T cells contribute to macrophage recruitment and adipose tissue inflammation in obesity Nat. Med. 15 2009 914 920 10.1038/nm.1964 19633658
|
| 421 |
+
10 Hou H. Zhou Y. Yu J. Mao L. Bosco M.J. Wang J. Lu Y. Mao L. Wu X. Wang F. Sun Z. Establishment of the reference intervals of lymphocyte function in healthy adults based on IFN-gamma secretion assay upon phorbol-12-Myristate-13-acetate/ionomycin stimulation Front. Immunol. 9 2018 172 10.3389/fimmu.2018.00172 29467761
|
| 422 |
+
11 Audano M. Pedretti S. Caruso D. Crestani M. De Fabiani E. Mitro N. Regulatory mechanisms of the early phase of white adipocyte differentiation: an overview Cell. Mol. Life Sci. 79 2022 139 10.1007/s00018-022-04169-6 35184223
|
| 423 |
+
|
puc/PMC10216179.txt
ADDED
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@@ -0,0 +1,322 @@
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Cells
|
| 4 |
+
Cells
|
| 5 |
+
cells
|
| 6 |
+
Cells
|
| 7 |
+
2073-4409
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
10.3390/cells12101350
|
| 11 |
+
cells-12-01350
|
| 12 |
+
Article
|
| 13 |
+
Impact of Combined Baricitinib and FTI Treatment on Adipogenesis in Hutchinson–Gilford Progeria Syndrome and Other Lipodystrophic Laminopathies
|
| 14 |
+
Hartinger Ramona Methodology Formal analysis Investigation Writing – original draft Visualization 1
|
| 15 |
+
https://orcid.org/0000-0002-1220-1040
|
| 16 |
+
Lederer Eva-Maria 1
|
| 17 |
+
Schena Elisa Methodology Formal analysis 23
|
| 18 |
+
https://orcid.org/0000-0002-7103-8722
|
| 19 |
+
Lattanzi Giovanna Methodology Formal analysis 23
|
| 20 |
+
https://orcid.org/0000-0003-4067-4977
|
| 21 |
+
Djabali Karima Conceptualization Methodology Formal analysis Investigation Writing – original draft Supervision Project administration Funding acquisition 1*
|
| 22 |
+
Gräf Ralph Academic Editor
|
| 23 |
+
1 Epigenetics of Aging, Department of Dermatology and Allergy, TUM School of Medicine, Munich Institute of Biomedical Engineering (MIBE), Technical University of Munich (TUM), 85748 Garching, Germany; ramona.hartinger@tum.de (R.H.); eva.lederer@tum.de (E.-M.L.)
|
| 24 |
+
2 Unit of Bologna, CNR Institute of Molecular Genetics “Luigi Luca Cavalli-Sforza”, 40136 Bologna, Italygiovanna.lattanzi@cnr.it (G.L.)
|
| 25 |
+
3 IRCCS Istituto Ortopedico Rizzoli, 40136 Bologna, Italy
|
| 26 |
+
* Correspondence: djabali@tum.de
|
| 27 |
+
09 5 2023
|
| 28 |
+
5 2023
|
| 29 |
+
12 10 135003 4 2023
|
| 30 |
+
27 4 2023
|
| 31 |
+
04 5 2023
|
| 32 |
+
© 2023 by the authors.
|
| 33 |
+
2023
|
| 34 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 35 |
+
Hutchinson–Gilford progeria syndrome (HGPS) is a rare genetic disease that causes premature aging symptoms, such as vascular diseases, lipodystrophy, loss of bone mineral density, and alopecia. HGPS is mostly linked to a heterozygous and de novo mutation in the LMNA gene (c.1824 C > T; p.G608G), resulting in the production of a truncated prelamin A protein called “progerin”. Progerin accumulation causes nuclear dysfunction, premature senescence, and apoptosis. Here, we examined the effects of baricitinib (Bar), an FDA-approved JAK/STAT inhibitor, and a combination of Bar and lonafarnib (FTI) treatment on adipogenesis using skin-derived precursors (SKPs). We analyzed the effect of these treatments on the differentiation potential of SKPs isolated from pre-established human primary fibroblast cultures. Compared to mock-treated HGPS SKPs, Bar and Bar + FTI treatments improved the differentiation of HGPS SKPs into adipocytes and lipid droplet formation. Similarly, Bar and Bar + FTI treatments improved the differentiation of SKPs derived from patients with two other lipodystrophic diseases: familial partial lipodystrophy type 2 (FPLD2) and mandibuloacral dysplasia type B (MADB). Overall, the results show that Bar treatment improves adipogenesis and lipid droplet formation in HGPS, FPLD2, and MADB, indicating that Bar + FTI treatment might further ameliorate HGPS pathologies compared to lonafarnib treatment alone.
|
| 36 |
+
|
| 37 |
+
progerin
|
| 38 |
+
lonafarnib
|
| 39 |
+
baricitinib
|
| 40 |
+
lamin A
|
| 41 |
+
adipogenesis
|
| 42 |
+
progeria
|
| 43 |
+
lipodystrophy
|
| 44 |
+
JAK/STAT
|
| 45 |
+
skin derived precursors
|
| 46 |
+
laminopathies
|
| 47 |
+
Deutsche Forschungsgemeinschaft#646337 #66527 Progeria Research FoundationPRF-2022-82 This research was funded by the Deutsche Forschungsgemeinschaft DFG #646337 and #66527 to KD and in part by the Progeria Research Foundation (PRF-2022-82 to KD).
|
| 48 |
+
==== Body
|
| 49 |
+
pmc1. Introduction
|
| 50 |
+
|
| 51 |
+
Hutchinson–Gilford progeria syndrome (HGPS; OMIM #176670) is a rare genetic disease with similar symptoms to physiological aging, including vascular disease, subcutaneous fat loss, sclerodermatous skin, loss of bone mineral density, and hair loss [1,2,3,4]. HGPS affects one child in 4–8 million births worldwide [2]. In 2022, approximately 140 children and young adults with HGPS were reported worldwide, with an average life expectancy estimated at 14.5 years [3,5]. Cardiovascular diseases are the major cause of HGPS mortality [2,6]. HGPS is primarily caused by a heterozygous single-point de novo mutation in the lamin A (LMNA) (c.1824 C > T; p.G608G), resulting in a cryptic splice site in exon 11 and the loss of 50 amino acids at the C-terminus of lamin A. The truncated prelamin A protein is known as progerin. Wild-type prelamin A undergoes several specific posttranslational modifications to form mature lamin A, including farnesylation of the C-terminal cysteine, cleavage of the last three amino acids, and carboxymethylation of the C-terminal cysteine, followed by a second upstream cleavage [6,7]. In HGPS, the final upstream cleavage step is not possible because the cleavage site for ZMPSTE24 is missing, generating a permanently farnesylated mutant prelamin A (progerin) [6,8,9]. Progerin is abnormally incorporated into the nuclear envelope as it remains farnesylated. Consequently, progerin accumulation in HGPS nuclei causes cytotoxicity in cells including changes in the nuclear lamina, nuclear disorganization and malfunction, premature senescence, and cell death [1,8,9,10].
|
| 52 |
+
|
| 53 |
+
Lipodystrophy is characterized by a general or selective loss of subcutaneous and visceral fat and alteration in the body fat compositions [11,12]. Genetic defects, causing lipodystrophy, can directly affect the differentiation of adipocytes, the lipid droplet formation, or the triglyceride transport [12,13]. There are three types of adipose tissues in humans: white (WAT), brown (BAT), and beige. BAT cells contain a large number of mitochondria and are localized in visceral tissues. BAT is involved in thermoregulation during adaptive thermogenesis [14,15]. The beige adipose tissue consists of brown-like adipocytes distributed in WAT [16] and is also involved in thermogenesis by absorbing large amounts of glucose. Beige adipose tissue can be found in muscles [17]. WAT constitutes the largest proportion of body fat, and its primary function is energy storage to regulate the energy homeostasis [16,18]. WAT is found throughout the body and is divided into subcutaneous WAT and visceral WAT, with approximately 80–90% of body fat in adults consisting of subcutaneous WAT [19,20,21]. In a healthy state, triglycerides accumulate in WAT and form large fat droplets inside the adipocytes [16,21]. Apart from its fat storage capacity, adipose tissues play an important hormonal and metabolic regulatory roles [22], and their dysfunction or absence can cause metabolic diseases, steatohepatitis and hepatic cirrhosis, premature cardiovascular disorders, and organ failure [12,13,22].
|
| 54 |
+
|
| 55 |
+
Lipodystrophy is a prominent clinical feature in patients with HGPS, with 20% of HGPS patients showing generalized lipodystrophy as the first predominant symptom, which can start as early as at six months of age [23]. Adipose tissues first decrease in the limbs and the thorax, then in the neurocranium, and later in the facial, buccal, and pubic areas. In most HGPS cases, abdominal fat remains unaffected, which confers a dominant abdomen characteristic in children with HGPS. Owing to thinning of the skin and the loss of subcutaneous adipose tissue, children with HGPS are characterized by prominent eyes and visible blood vessels on the face and scalp [2,3,23]. Interestingly, lipodystrophy also occurs in other laminophaties such as familiar partial lipodystrophy type 2 (FPLD2) and mandibuloacral dysplasia type B (MADB) [13,24,25]. Patients with HGPS, FPLD2, or MADB harbor mutations on the LMNA or ZMPSTE24, causing abnormalities in lamin processing and cellular changes. Overall, these diseases show typical lipodystrophy symptoms, such as subcutaneous fat loss and metabolic alterations [2,6,24,25,26,27].
|
| 56 |
+
|
| 57 |
+
FPLD2 is an autosomal dominant genetic disorder caused by a mutation in the LMNA that encodes lamin A and lamin C [13,22,24]. More than 80% of FPLD2 patients carry a single point mutation at position R482 located in the immunoglobulin fold domain of lamin A [26]. Usually, the first symptoms begin during puberty and manifest as an atypical distribution of subcutaneous fat (limbs, trunk, and extremities) and an accumulation of adipose tissue (neck, face, and back). Moreover, symptoms such as cardiovascular diseases, insulin resistance, hypertriglyceridemia, liver diseases, atherosclerosis, and altered bone formation have been reported [13,22,24,26,28]. Previous studies have reported a decrease in pre-adipocyte differentiation and adipogenic potential, impaired lipid droplet formation, and reduced autophagy in patients with FPLD2 [24,26,29,30].
|
| 58 |
+
|
| 59 |
+
MADB is a rare premature aging syndrome caused by a heterozygous mutation in the ZMPSTE24 gene on chromosome 1p34 encoding the enzyme zinc metalloprotease ZMPSTE24 [25]. ZMPSTE24 C-terminally cleaves the farnesylated and carboxymethylated tail of prelamin A to produce the mature lamin A [25,31]. In MADB, mutations in ZMPSTE24 causes a decrease or absence in the catalytic activity of this enzyme leading to prelamin A nuclear accumulation. MADB patients suffer from osteoporosis, fat loss (lipodystrophy type B), metabolic abnormalities, insulin resistance, delayed growth, dental crowding, skin atrophy, and brittle hair [25,26,27,31].
|
| 60 |
+
|
| 61 |
+
Although FPLD2, HGPS, and MADB carry different mutations, they are characterized by the expression of abnormal lamin A and the accumulation of permanently farnesylated prelamin A or progerin. All three diseases exhibit symptoms associated with lipodystrophy and altered adipogenesis. At the cellular level, toxic progerin or prelamin A accumulation causes DNA damage, nuclear dysfunctions, altered gene expression, and metabolic defects, which drive cells towards premature senescence and apoptosis [12,32,33,34,35]. Senescent cells remain in a state of irreversible permanent cell cycle arrest and produce a bioactive secretome, known as the senescence-associated secretory phenotype (SASP) [36,37]. The SASP acts as a primary mediator in senescent cells, and secreted inflammatory factors and proteases communicate with the microenvironment and the immune system [37,38]. SASP paracrine signaling has negative effects, including modulation of numerous pathways, such as ROS, MAPK signaling, proliferation, and WNT signaling [39], which can cause chronic and low-grade inflammation due to the constitutive activation of immune cells and secretion of proinflammatory cytokines [36,37,40].
|
| 62 |
+
|
| 63 |
+
Squarzoni et al. (2021) showed that progerin or farnesylated prelamin A induced the activation of NF-κB and interleukin 6 (IL) promoters and the increased of IL-6 levels in HGPS and MADB fibroblasts [41]. In vivo studies on LmnaG609G/G609G progeroid mice demonstrated that the inhibition of IL-6 with tocilizumab, a neutralizing antibody against IL-6 receptors, caused a decrease in senescence and progerin levels and ameliorated nuclear defects [41]. Additionally, prelamin A or progerin accumulation induced the activation of a NF-κB-driven inflammation via ATM and NEMO in ZMSPTE24-deficient and LmnaG609G mice, resulting in nuclear envelope defects and progeroid symptoms [34]. Adipose tissue appears to be highly sensitive to progerin accumulation [42]. For instance, progerin accumulation and high paracrine activation in adipocyte tissue caused chronic inflammation and cellular senescence in a LmnaG609G/G609G mouse model [42]. Additionally, loss of fat and other fat deposits was observed in LmnaG609G/G609G mice [43,44].
|
| 64 |
+
|
| 65 |
+
Over the years, several strategies have been investigated to treat HGPS. Targeting the post-translational modification of progerin to prevent its tethering to the nuclear envelope and increase its clearance is a promising strategy. The first tested compound is a farnesyltransferase inhibitor (FTI, lonafarnib) [6,45], and studies have shown that FTI ameliorates several cellular phenotypic changes in HGPS [10,45,46,47]. Clinical trials with lonafarnib caused a decrease in the mortality rate and improved bone mineralization, weight, and cardiovascular systems in patients with HGPS [1,6,45]. Presently, lonafarnib has been approved by the FDA for the treatment of HGPS [48]. Although lonafarnib ameliorates HGPS children’s condition, it is not a cure, and new therapies are urgently needed. One novel potential strategy is to reduce the downstream toxic effect of progerin at the cellular level. Recent studies have demonstrated that the JAK-STAT signaling is overactivated in HGPS cells, and that chronic low-grade inflammation may be a common etiology of various pathologies affecting patients with HGPS [49,50]. The JAK1/2-STAT1/3 inhibitor baricitinib (Bar), an FDA-approved treatment for rheumatic arthritis [51], has been shown to reduce senescence and progerin levels and improve nuclear shape, proliferation, and mitochondrial functions [50]. Moreover, several studies have shown a potential link between adipogenesis and the JAK/STAT pathway [52,53,54,55,56]. The JAK-STAT pathway can influence the proliferation and function of mature adipocytes and modulate their tissues [53,55]. Therefore, these findings suggest that Bar treatment may improve adipogenesis in HGPS.
|
| 66 |
+
|
| 67 |
+
As farnesylated progerin and farnesylated prelamin A expression induce several cellular changes, including premature senescence, it is likely that JAK-STAT overactivation may also occur in FPLD2 and MADB cells. Here, we elucidate the role of JAK/STAT signaling in the development of lipodystrophy in HGPS, FPLD2, and MADB, using an in vitro adipogenesis model. Specifically, we examined the effect of combined treatment with Bar and lonafarnib on adipogenesis in cells derived from patients with HGPS, FPLD2, and MADB. An ex vivo cellular model consisting of skin-derived precursors (SKPs) isolated from human primary fibroblast HGPS, FPLD2, and MADB was established using the pH-stress method [57,58]. Multipotent SKPs are found in adult human skin and express stem cell markers [59,60,61]. The SKPs were differentiated into adipocytes and cultured with Bar and/or FTI.
|
| 68 |
+
|
| 69 |
+
2. Materials and Methods
|
| 70 |
+
|
| 71 |
+
2.1. Cell Culture
|
| 72 |
+
|
| 73 |
+
In this study, the following human primary dermal fibroblast cell lines were used: control cell strains GM05757C (7-year-old male), GM05567A (12-year-old male), and GM01651C (13-year-old female) without mutations; HGPS cell strains HGADFN003 (2-year-old male), HGADFN164 (4-year-old female), and HGADFN178 (6-year-old female) with mutation on LMNA Exon 11, heterozygous c.1824C > T (p.Gly608Gly); FPLD2 cell strains CCLMA00336s, CCLMS337s, and CCBB00466s with mutations on position LMNA R482Q; MADB cells PSADFN317 (3-year-old male) and PSADFN318 (5-month-old male) with mutation on ZMPste24 Exon 6, heterozygous c.743C > T (p.Pro248Leu); Exon 10, heterozygous c.1349G > A. Human normal primary dermal fibroblast cells were obtained from the Coriell Institute for Medical Research (Camden, NJ, USA). HGPS and MADB cells were obtained from the Progeria Research Foundation Cell and Tissue Bank, and FPLD2 cells were provided by the Institute of Molecular Genetics IGM Bologna (G. Lattanzi).
|
| 74 |
+
|
| 75 |
+
The fibroblast monocultures were cultured in DMEM (Thermo Fisher—Gibco, Waltham, MA, USA, D6429) supplemented with 15% fetal bovine serum (FBS; Thermo Fisher—Gibco, 10270106), 1% L-glutamine (Thermo Fisher—Gibco, 25030081), 1% gentamycin (Thermo Fisher—Gibco, 15710049), and 1% penicillin/streptomycin (Thermo Fisher—Gibco, 1514022). All fibroblasts were cultured in a cell incubator (Binder, Tuttlingen, Germany, 9140-0046) at 37 °C and under a 5% CO2 atmosphere. The monocultures were sub-cultured and used with at 80% confluence, and a senescence < 5%. Additionally, monocultures with senescence >20% were used for western blots and immunofluorescence.
|
| 76 |
+
|
| 77 |
+
2.2. Senescence Associated βeta-Galactosidase Assay
|
| 78 |
+
|
| 79 |
+
β-galactosidase assay was performed to assess cell senescence, as previously described by Dimri et al. (1995) [62]. The adherent cells were washed once with phosphate-buffered saline (PBS) and fixed for 5 min in 0.2% glutaraldehyde (Sigma-Aldrich, St. Louis, MO, USA, G5882), and 2% formaldehyde (Sigma-Aldrich, 104003). The fibroblasts were washed 2 times with PBS and incubated overnight at 37 °C (in absence of CO2) with SA-β-Gal staining solution (5 mM potassium ferricyanide (Merck KGaA, 104973, Darmstadt, Germany), 5 mM potassium ferrocyanide (Sigma-Aldrich, P9387), 2 mM MgCl2 (Sigma-Aldrich, M-1028), 150 mM NaCl (Sigma-Aldrich, 310166), 0.5 mg/mL 5-bromo4-chloro-3-indolyl P3-D-galactoside (X-gal) (Sigma-Aldrich, 3117073001), and 40 mM citrate/sodium phosphate buffer (pH 6.0) at 37 °C). An average of 1000 cells were counted per sample, and blue-stained cells were classified as senescent.
|
| 80 |
+
|
| 81 |
+
2.3. Western Blot
|
| 82 |
+
|
| 83 |
+
Fibroblasts were washed with PBS and collected by trypsinization using trypsin-EDTA (Thermo Fisher—Gibco, 25200056), pelleted by centrifugation at 350× g for 5 min at room temperature (RT), and lysed (150 mM NaCl, 1% Triton, 1% SDS, 1 mM EDTA, 50 mM Tris). Total protein concentration was determined using the Bradford assay, with BSA as a standard (BioRad Laboratories, 5000206, Hercules, CA, USA). Proteins (10 µg) were separated in an 8% gel via electrophoresis and transferred onto nitrocellulose membranes via wet-transfer. The membranes were blocked by incubating with 5% non-fat milk for 1 h, followed by incubation with the primary antibodies, including anti-prelamin A (Merck Millipore, 7G11, rat, 1:2000, overnight, Dallas, TX, USA), anti-lamin A/C (E1, sc-376248, Santa Cruz Biotechnology, 1:10000), anti-lamin B1 (C12, sc-365214, Santa Cruz Biotechnology, 1:5000), and anti-GAPDH (G9545, Sigma-Aldrich, 1:5000) overnight at 4 °C. After washing three times with TBS-Tween, the membranes were incubated with horseradish peroxidase-conjugated secondary antibodies (Jackson ImmunoResearch Laboratories, West Grove, PA, USA), including anti-rabbit (1:5000), anti-rat (1:5000), or anti-mouse (1:5000) for 1 h at RT. Thereafter, luminol-enhanced chemiluminescence was performed and the signals were visualized using ChemiDoc™ MP and quantified using ImageJ software (NIH). The nlots were quantified by normalizing to GAPDH (internal control) expression levels.
|
| 84 |
+
|
| 85 |
+
2.4. Low-pH SKP Isolation Method and Culture of SKPs
|
| 86 |
+
|
| 87 |
+
SKPs were isolated from primary fibroblast cultures using the low pH stress method. Briefly, primary fibroblast cultures with senescence <5% and at 80% confluency were used for this analysis. Briefly, fibroblast cultures were washed with PBS, collected using trypsin-EDTA (Thermo Fisher—Gibco, 25200056), pelleted by centrifugation at 350× g for 5 min at RT, and washed with PBS. For SKP isolation, cells (1 × 106) were resuspended in pH-adjusted Hank’s balanced salt solution (HBSS) buffer (Thermo Fisher—Gibco, 14175053). The pH of the HBSS buffer was adjusted to 5.7 using HCL (Merck KGaA, Darmstadt, Germany, 1.00319.2500), and the cells were incubated at 37 °C for 25 min and resuspended every 5 min. After 25 min of incubation, the cell suspension was centrifuged at 350× g for 5 min at RT, and the cell pellet was suspended in 6 mL of SKP media (4:1—DMEM low glucose (Thermo Fisher—Gibco, 21885025):F12 (Thermo Fisher—Gibco, 21765029), 20 ng/mL EGF (Thermo Fisher—Gibco, PHG0311), 40 ng/mL bFGF (Thermo Fisher—Gibco, PHG0026), 2% v/v B27 (Thermo Fisher—Gibco, 17504044), 0.5 g/mL fungizone (Thermo Fisher—Gibco, 15290018), and 100 U/100 _g/mL penicillin/streptomycin) and equally split in two T25 non-tissue-culture-treated flasks (Fisher Scientific—Falcon, Hampton, NH, USA, 10112732) (Budel und Djabali, 2017). The SKP cultures were resuspended daily to prevent adherence of the SKP spheroids to the plastic flask. SKP cultures were supplemented every 2 d with 10× SKP media (10× concentration of EGF, bFGF, and B27), which was diluted to a final concentration of 1× SKP media.
|
| 88 |
+
|
| 89 |
+
2.5. SKP Cell Differentiation into Adipocytes
|
| 90 |
+
|
| 91 |
+
At 4 d after cultivation, the SKPs were collected and centrifuged at 350× g for 5 min at RT. The spheroids were washed twice with PBS, dissociated using trypsin-EDTA (Thermo Fisher—Gibco, 25200056), and seeded onto cover slips in 24-well plates. The seeding density differed for each cell type. Control SKPs were seeded at 8 × 105 cells per well, and HGPS SKPs were seeded at 1.2 × 106. The cells were cultured in adipocyte differentiation media (ADM) consisting of DMEM supplemented with 4.5 g/L glucose (Thermo Fisher—Gibco, 21885025), 0.5 mM 3-isobutyl-1-methylxanthine (IBMX, Sigma-Aldrich, St., Louis, MO, USA, I7018, stock in absolute ethanol (VWR chemicals, Radnor, PA, USA, 20821.33)), 10 μg/mL insulin (Sigma-Aldrich, I2643, stock in 0.01 M HCL [Merck KGaA, 1.00319.2500] in Ultra-Pure water from MilliQ [MQ]), 100 μM L-Ascorbic Acid (Sigma-Aldrich, A8960, stock in Ultra-Pure water from MilliQ [MQ]), 1 μM dexamethasone (Sigma-Aldrich, D4902 (stock in absolute ethanol)), 10% FBS, 0.5 μg/mL fungizone, 50 μM indomethacin (Sigma-Aldrich, I7378, stock in 100% DMSO [Sigma-Aldrich, D2650]), and 100 U/100 μg/mL penicillin/streptomycin. The media was replaced every 2–3 d [58].
|
| 92 |
+
|
| 93 |
+
For the drug treatment, a mock solution (no drug), 1 μM baricitinib (Selleck Chemicals GmbH, Munich), 0.025 μM lonafarnib (Merk KGaA, Darmstadt, Germany), or a combination of 1 μM of baricitinib and 0.025 μM of lonafarnib (Bar + FTI) was added to ADM.
|
| 94 |
+
|
| 95 |
+
2.6. Oil Red O (ORO) Staining
|
| 96 |
+
|
| 97 |
+
Differentiated adipocytes were fixed in 4% paraformaldehyde (PFA; Merck KGaA, 104005) for 30 min. Next, the cells were incubated in 60% isopropanol for 5 min, followed by incubation in ORO staining solution for 5 min. Thereafter, the coverslips were washed in tap water and screened under a microscope. The staining solution was prepared by mixing three parts of ORO stock solution (ORO powder (Sigma-Aldrich, O0625) in 99% isopropanol) with two parts of demineralized water and filtering two times using a filter paper (Rotilabo-Rundfilter, Typ 11A, Carl Roth GmbH + Co. KG, Karlsruhe, Germany).
|
| 98 |
+
|
| 99 |
+
2.7. Bodipy Staining
|
| 100 |
+
|
| 101 |
+
The differentiated adipocytes were fixed in 2% PFA (Merck KGaA, 104005) for 20 min and washed once with PBS. Lipid droplets were stained with 2 μM of Bodipy (Invitrogen, Waltham, MA, USA, D3922) for 45 min and then washed three times with PBS. The cells were counterstained with DAPI Vectashield mounting medium (Vector Laboratories, Burlingame, CA, USA, VEC-H-1200), and images were captured using an Axio Imager D2 fluorescence microscope (Light source: X-cite 120Q (EXFO Photonic Solutions Inc., Mississauga, ON, Canada); objectives used: EC-Plan Neofluar 10×/0.3 (420340-9901, Carl Zeiss), Plan-Apochromat 40×/0.95 Korr (440654-9902, Carl Zeiss); camera used: AxioCam MRm (Carl Zeiss, Oberkochen, Germany); excitation and emission filters used: filter set 49 (424931, Zeiss), filter set 38 HE (424931, Zeiss)).
|
| 102 |
+
|
| 103 |
+
2.8. Immunocytochemistry
|
| 104 |
+
|
| 105 |
+
Adipocytes, grown on glass cover slips, were fixed with 2% PFA (Merck KGaA, 104005) for 10 min and washed 3 times for 5 min with PBS. The cells were permeabilized with 0.2% Triton X-100 in PBS for 5 min and washed once with PBS for 5 min. After permeabilization, the cells were blocked with 10% FBS (Thermo Fisher—Gibco, 10270106) in PBS for 30 min at RT, then incubated overnight at 4 °C with the following primary antibodies: rat anti prelamin A (Merk Millipore, 7G11, 1:400, overnight), mouse anti-Lamin B1 (Santa Cruz Biotechnology, 1:200, overnight), and rabbit anti-progerin [63]. After four washes with blocking buffer, the cells were incubated with the secondary antibodies: affinity-purified Alexa Fluor® 488 or 555 conjugated anti-rat/-rabbit/-mouse antibodies (Life Technologies, Carlsbad, CA, USA, A21202 anti-mouse-488, A21208 anti-rat-488, and A31572 anti-rabbit-555, 1:1000) for 1 h at RT. Thereafter, the cells were washed twice with blocking buffer and twice with PBS and counterstained with DAPI Vectashield mounting medium (Vector Laboratories, Burlingame, CA, USA, VEC-H-1200). Images were captured using an Axio Imager D2 fluorescence microscope (AxioCam MRm, Carl Zeiss, Oberkochen, Germany).
|
| 106 |
+
|
| 107 |
+
2.9. Image Analysis
|
| 108 |
+
|
| 109 |
+
Images were analyzed using Fiji software (ImageJ 1.53f51, Java 1.8.0_172, Wayne Rasband, and contributors to the National Institutes of Health, USA). Brightness and contrast were adjusted [64], and ORO intensity, lipid droplet (LD) size, BODIPY intensity, and BODIPY-positive cells were determined. Inkscape (Version 1.1.2 (b8e25be833, 2022-02-05), GPL) was used for illustration. The total area of BODIPY was quantified by measuring the area with BODIPY-positive signal compared to total area of the coverslip.
|
| 110 |
+
|
| 111 |
+
2.10. Statistical Evaluation and Graphics
|
| 112 |
+
|
| 113 |
+
Three biological replicates were analyzed for each cell strain. For senescence, dysmorphic nuclei and BODIPY-positive cells (1000 cells per cell strain) were counted under the various treatment conditions. The lipid droplet size was measured using 150 cells/cell strain and treatments.
|
| 114 |
+
|
| 115 |
+
All results are presented as mean ± SD and were generated using the student’s t-test to compare the difference between 2 groups. For multiple groups’ comparison, 2-way ANOVA was used. Calculations and graphs were generated using GraphPad Prism (Version 6.01, GraphPad, San Diego, CA, USA). The following symbols indicate statistical significance: ns, not significant (p > 0.05); * p ≤ 0.05; ** p ≤ 0.01; and *** p ≤ 0.001.
|
| 116 |
+
|
| 117 |
+
3. Results
|
| 118 |
+
|
| 119 |
+
3.1. Adipocyte Differentiation of HGPS SKPs in the Presence of FTI and Baricitinib
|
| 120 |
+
|
| 121 |
+
Previous studies have successfully isolated SKP spheroids from primary fibroblast cultures using the low-pH stress method [57]. Senescence plays an important role in SKP differentiation [58]; therefore, young fibroblast cultures with <5% senescence rate were used for the analysis to prevent the effect of age on the differentiation potential of SKPs. The SKP isolation method is illustrated in Figure 1. After low-pH stress isolation, the SKPs were cultured in SKP medium, dissociated after 4 d (Figure 1), and cultured in adipocyte differentiation media (ADM) supplemented with either 0.025 μM FTI, 1 μM Bar, or the combination of 0.025 μM FTI and 1 μM Bar, or vehicle for 14 d to examine the effect of lonafarnib (FTI) and the JAK 1/2 inhibitor Bar on adipocyte differentiation
|
| 122 |
+
|
| 123 |
+
Lipid droplets were visible in both control and HGPS cells at 7 d after differentiation; however, mock- and FTI-treated HGPS cells had lower number of droplets compared to control groups (Figure 2, panel, day 7). Additionally, lipid formation was not affected by the different treatments in normal cells, whereas Bar and Bar + FTI treatments increased lipid droplet accumulation and adipocyte differentiation in HGPS cells compared to mock- or FTI-treated HGPS cells (Figure 2). After 14 d, there was a remarkable increase in the accumulation of lipid droplets in the control and HGPS cells (Figure 2). Specifically, lipid droplet accumulation and adipocyte differentiation were significantly lower in untreated and FTI-treated HGPS cells compared to Bar- or Bar + FTI-treated HGPS cells (Figure 2, panel, day 14). Collectively, these results indicated that Bar and Bar + FTI treatment improved the differentiation of HGPS-derived SKPs into adipocytes.
|
| 124 |
+
|
| 125 |
+
3.2. Baricitinib Alone or in Combination with FTI Improve Adipogenesis of HGPS SKPs
|
| 126 |
+
|
| 127 |
+
To determine whether the treatment with Bar or a combination of Bar + FTI can improve adipocyte differentiation in HGPS, cultures were fixed and stained with ORO or BODIPY at 14 d after differentiation (Figure 3). Adipocyte differentiation efficiency was quantified by analyzing the total area of ORO and BODIPY, measuring the lipid droplet size and counting the BODIPY-positive cells using Fiji software.
|
| 128 |
+
|
| 129 |
+
Compared with the mock control SKPs, there was no significant difference in the differentiation rate of control SKPs into adipocyte among all treatment regimens, indicating that the drugs did not affect the differentiation of normal (control) SKPs (Figure 3). Specifically, approximately 43% of normal SKPs differentiated into adipocytes and showed a positive BODIPY signal (Figure 3a,c). In contrast, SKPs differentiation into adipocytes was decreased in the mock- and FTI-treated HGPS groups, with only 24% adipocytes and BODIPY positive signal (Figure 3a,c). However, the treatment with Bar or Bar + FTI increased the number of differentiated cells and the accumulation of lipid droplets (Figure 3a–c). Compared with mock-treated HGPS SKPs, BODIPY positive signal increased by 40% in the Bar and Bar + FTI groups, with approximately 35% of the SKPs in Bar and Bar + FTI groups differentiating into adipocytes (Figure 3a,c). Similarly, ORO staining confirmed that Bar or Bar + FTI treatments improved adipocyte differentiation (Figure 3d–f), as evidenced by a 56% increase in the differentiation of Bar- or Bar + FTI-treated HGPS SKPs compared to mock- or FTI-treated HGPS SKPs, reaching a similar differentiation rate as mock-treated control SKPs (Figure 3b,e).
|
| 130 |
+
|
| 131 |
+
Consistent with the results of BODIPY staining, ORO staining showed that lipid droplet size was not significantly affected by treatments in normal SKPs (Figure 3c,f). In contrast, treatment of HGPS adipocytes with Bar or Bar + FTI increased lipid droplets by 2-fold compared to the mock-treated HGPS group (Figure 3f). Collectively, these results indicated that Bar and Bar + FTI treatments efficiently improved adipogenesis and lipid droplet formation in HGPS SKPs.
|
| 132 |
+
|
| 133 |
+
3.3. Effect of Baricitinib and FTI on FPLD2 and MADB Adipogenesis
|
| 134 |
+
|
| 135 |
+
Patients affected with FPLD2 and MADB, two other laminopathies linked to lamin A and ZMPSTE24 mutations, respectively, also suffer from lipodystrophy [22,26]. However, FPLD2 and MADB are caused by different mechanistically linked genes and have similar symptoms with HGPS, such as loss of fat and changes in fat depot distribution [13]. Therefore, we examined whether Bar and Bar + FTI treatments can also improve adipogenesis in SKPs isolated from primary fibroblasts derived from these distinct patients.
|
| 136 |
+
|
| 137 |
+
SKPs were isolated from young FPLD2 and MADB primary fibroblast cultures (senescence ≤5%) using the low-pH stress method and then differentiated into adipocytes (Figure 1). Adipocyte differentiation was examined and monitored daily. Lipid droplets were observed in control, FPLD2, and MADB groups after 7 d (Figure 4). Control cells were not significantly affected by the different treatments, as a similar number of lipid droplets were observed in all treatment groups (Figure 4). In contrast, mock and FTI treatment caused a decrease in lipid droplet formation in FPLD2 and MADB cells (Figure 4 and Figure 5). However, treatment of FPLD2 and MADB SKPs with Bar and Bar + FTI increased the adipocyte number and lipid droplets formation (Figure 4, panel day 7), which was more obvious after 14 d of treatments (Figure 4 and Figure 5). Notably, Bar- and Bar + FTI-treated FPLD2 and MADB showed higher adipocyte differentiation capability and lipid droplets formation than mock- and FTI-treated cells (Figure 4, panel day 14). Furthermore, MADB adipocytes had larger lipid droplets than control cells at 7–14 d after treatment (Figure 4).
|
| 138 |
+
|
| 139 |
+
BODIPY staining showed that the adipocyte differentiation rate was 43% in the control cells under all treatment regimens; however, only 22.5 and 30% of FPLD2 and MADB SKPs, respectively, differentiated into adipocytes following mock and FTI treatment, with an obvious decrease in the number of BODIPY-positive cells (Figure 5a,c). In contrast, Bar and Bar + FTI treatments increased the adipocyte differentiation rate by an average of 86% in the FPLD2 and 41% in the MADB groups, respectively (Figure 5a,c), which was confirmed by ORO staining (Figure 5). Similarly, Bar and Bar + FTI treatments significantly increased in adipogenesis and lipid droplets formation in the FPLD2 and MADB groups. Compared to the mock group, Bar and Bar + FTI treatments increased adipocyte differentiation in the FPLD2 and MADB groups by 1.5-fold (Figure 5d,e). Additionally, mock- and FTI-treated FPLD2 adipocytes had smaller-sized lipid droplets compared to the normal (control) cells (Figure 5). In contrast, treatment with Bar and Bar + FTI significantly increased lipid droplet size in the FPLD2 group to a size comparable to that (~76 µm2) in the control group (Figure 5f). Lipid droplet size was significantly larger in the MADB adipocytes compared to the control and FPLD2 adipocytes under all treatment regimens; moreover, MADB cell differentiation rate was improved by Bar and Bar + FTI treatments (Figure 5f). Overall, these results indicated that Bar and Bar + FTI improved adipocyte differentiation and lipid droplet formation in both FPLD2 and MADB SKPs.
|
| 140 |
+
|
| 141 |
+
3.4. Lamin Status in HGPS, FFLD2, and MADB Primary Fibroblast Cultures
|
| 142 |
+
|
| 143 |
+
To further understand how lamin status in HGPS, FPLD2, and MADB primary fibroblast cultures affects the SKP preparation and adipogenic potential, immunocytochemistry and western blot analyses were performed to determine progerin, prelamin A, lamin B1, and lamin A/C expression in young fibroblast cultures (<5% senescence, control cells passages 16–21, HGPS cells passages 10–14, FPLD2 cells passages 9–14, MADB cells passages 12–14) and old fibroblast cultures (>20% senescence, control cells passages 28–31, HGPS cells passages 18–19, FPLD2 cells passages 20–23, MADB cells passages 16–17).
|
| 144 |
+
|
| 145 |
+
Prelamin A and progerin were not detected in young control fibroblast cultures, whereas 10% of the cells were prelamin A-positive in old control cultures (Figure 6). In young and old HGPS fibroblast cultures, progerin was detected, and a weak signal for prelamin A was observed in brightly labeled progerin-positive cells (Figure 6). Hence, 27% of HGPS nuclei exhibited positive signal for prelamin A in young cultures, and this number increased to an average of 37% in later passages (Figure 6a,b). In FPLD2 and MADB cultures, although progerin was not detected, prelamin A was detected. Specifically, 18% of FPLD2 nuclei showed a weak prelamin A positive signal in young cultures but increased to 45% in late passages (Figure 6). In MADB fibroblast cultures, a strong prelamin A signal was detected in all nuclei from young and old passages, whereas progerin was not detected (Figure 6a,b). Furthermore, we scored the number of dysmorphic nuclei, showing abnormal and large nuclear morphologies instead of the typical ovoid nuclear shape, in fibroblast cultures from these three genetic disorders (Figure 6). In MADB, 35% of the nuclei were dysmorphic in early passages (<5% senescence), 19.6% in HGPS, and 16.7% in FPLD2 at similar passages (young cultures, Figure 6). In contrast the number of dysmorphic nuclei increased in old fibroblast cultures (senescence > 20%) from all three diseases including normal fibroblast cultures (Figure 6).
|
| 146 |
+
|
| 147 |
+
Western blot analyses were performed to quantify the levels of progerin, prelamin A, lamin B1, and lamin A/C expression levels in total protein from young (SNS ≤ 5%) and old (SNS ≥ 20%) fibroblast cultures. Lamin B1, like Lamin A/C, plays an important role in the build-up of the nuclear lamina structure and integrity and participates in chromatin and genome organization [65]. Lamin B1 expression was significantly lower in all three laminopathies, with HGPS and MADB cells having the lowest expression levels (Figure 7a,b). Compared with the control, there was a decrease in Lamin B1 by 30% in HGPS, 15% in FPLD2, and 60% in MADB (Figure 7b), which was confirmed by immunocytochemistry (Figure S1).
|
| 148 |
+
|
| 149 |
+
Expectedly, progerin was detected in both young and old HGPS fibroblasts (Figure 7d,e). In FPLD2 cells, prelamin A was detected only in old fibroblast cultures (Figure 7a–e). MADB cells showed high levels of prelamin A in young and old cells and low levels of lamin A (Figure 7c–f). In young and old control cells, lamin A/C signals were detected, but no progerin or prelamin A signals were detected (Figure 7d–f). Compared to control fibroblasts, lamin A expression level was lower in all laminopathies (Figure 7f).
|
| 150 |
+
|
| 151 |
+
Collectively, the expression of progerin or prelamin A in fibroblasts derived from these three laminopathies-caused alterations in A-type lamin proportions and, in addition, in lamin B1. These alterations are responsible for the perturbation of the lamina composition, which consequently induces nuclear envelope abnormalities, as indicated by the increased incidence of dysmorphic nuclei.
|
| 152 |
+
|
| 153 |
+
4. Discussion
|
| 154 |
+
|
| 155 |
+
In patients with HGPS, lipodystrophy is one of the main symptoms that can appear as early as at six months of age [23]. An alteration in adipocyte tissue ratio has a far-reaching effect on body functions and health status and is associated with autoimmune and cardiovascular diseases [22]. Therapies targeting lipodystrophy remain poorly explored, indicating the need for further studies, especially for cases associated with laminopathies. Presently, lonafarnib (FTI) is the only FDA-approved treatment for HGPS [48]. FTI has been reported to improve the HGPS cellular phenotype, ameliorate the cardiovascular burden, increase bone mineral density, and extend the life expectancy [1,46,47,48,66,67]. Nevertheless, it is associated with cellular side effects, such as donut-shaped nuclei, mitotic errors, genomic instability, anti-proliferative effects, and blockade of the farnesylation of functional proteins other than prelamin A [44,49,50,68,69,70,71,72,73,74].
|
| 156 |
+
|
| 157 |
+
In the present study, FTI treatment was ineffective in promoting adipogenesis in SKPs derived from normal, HGPS, MADB, and FPLD2 individuals. However, FTI-treated normal SKPs showed a comparable extent of adipocyte differentiation as their mock-treated counterparts, indicating that targeting the prenylation of prelamin A, progerin, and other prenylated proteins is not essential for adipogenesis. This suggest that FTI does not directly affect the signaling pathways or transcription factors responsible for the regulation of adipocyte differentiation [75]. In contrast, other studies have shown that FTI treatment can inhibit adipogenesis by interfering with adipogenic pathways and reducing the expression of the peroxisome proliferator-activator receptor γ (PPARγ) and CCAAT/enhancer binding protein α (C/EBPα), which are key transcription factors involved in adipogenesis [76]. Additionally, FTIs have been shown to inhibit the PI3K/Akt pathway by interfering with the prenylation and activation of small GTPases, such as Rho, Rac, and Cdc42, which are involved in the activation of PI3K [77,78]. Hence, inhibition of PI3K/Akt results in inactivation of its downstream target mTOR, inducing a decrease in protein synthesis and the expression of PPARγ and C/EBPα [79]. However, FTI directly blocks the prenylation of Rheb, an activator of mTOR, and has similar effects on the levels of these adipogenic transcription factors [80]. Furthermore, FTI may interfere with adipogenesis through antiproliferative and apoptotic effects via increasing ROS levels [81]. Specifically, FTI can interfere with adipogenesis in cancer cells, leading to oxidative DNA damage [82,83]. Under normal conditions, low ROS levels are necessary for adipocyte differentiation, whereas high ROS levels have a negative impact [84]. However, despite mild drug-related side effects such as diarrhea, fatigue, nausea, vomiting, and anorexia, FTI is well tolerated and safe for children with HGPS [85]. To overcome the limitation of FTI, the identification of novel compounds that can ameliorate lipodystrophy and are compatible with FTI is necessary. Therefore, we examined whether Bar, an FDA-approved JAK/STAT inhibitor, can ameliorate adipogenesis in HGPS-SKPs and exert a synergistic effect in combination with FTI. Treatment with Bar alone and in combination with FTI improved adipocyte differentiation and lipid droplet formation in cells derived from patients with three distinct diseases characterized by lipodystrophy. Although HGPS, FPLD2, and MADB have different molecular mechanisms, they all share a common etiology, which is the accumulation of abnormal lamin A [13].
|
| 158 |
+
|
| 159 |
+
Lamin A plays an important role in adipogenesis and normal cell function, and the toxic accumulation of progerin or farnesylated prelamin A causes oxidative stress and mitochondrial dysfunction, driving premature senescence [86,87,88,89]. Although FPLD2 is associated with mutations in LMNA that do not directly cause prelamin A accumulation, cellular age-dependent farnesylated prelamin A accumulation has been observed in fibroblasts from these patients. In present studies, the accumulation of progerin in HGPS and prelamin A in these three distinct diseases contributed to defects in adipogenesis. A previous study showed that treatment with Bar alone or in combination with FTI can improve HGPS cellular homeostasis and delay senescence [49]. Additionally, Bar treatment induced inhibition of the JAK/STAT signaling, enhanced progerin clearance, ameliorated the nuclear shape, decreased SASP, and delayed senescence [49]. The JAK/STAT pathway is overactivated in HGPS fibroblasts, triggering chronic inflammation and the secretion of pro-inflammatory factors [50]. Moreover, previous studies have shown that high levels of pro-inflammatory factors, such as IL-6, TGFβ, and TNF, promote cells to senescence and negatively affect adipogenesis [84]. Importantly, Bar treatment significantly inhibited JAK/STAT signaling in fibroblasts, thereby reducing the levels of pro-inflammatory markers [49,50]. Since senescent cells secrete SASPs, which include pro-inflammatory factors, an increase in their expression negatively affects adipogenesis [58]. Similarly, the presence of high number of senescent cells dramatically reduced the adipocyte differentiation potential of SKPs, whereas Bar treatment decreased the number of senescent cells and improved adipocyte differentiation [58]. In this present study, treatment with Bar and Bar + FTI ameliorated adipogenesis and lipid droplet formation. However, Bar + FTI treatment showed no additive effects relative to the Bar treatment alone, indicating that the beneficial effect of Bar was maintained in the presence of FTI, and that the combination is not toxic to the cells.
|
| 160 |
+
|
| 161 |
+
Patients with HGPS exhibit several cellular and tissue defects, including lipodystrophy, and FTI treatment alone is ineffective against all these symptoms. Therefore, we hypothesized that the combined FTI and Bar by targeting different cellular processes would further benefit patients with HGPS. Expectedly, Bar + FTI treatment improved adipocyte differentiation in SKPs derived from patients with FPLD2 and MADB. However, in MADB cells, the size of the lipid droplets was similar to that observed in normal adipocytes, in contrast to HGPS and FPLD adipocytes. Studies on ZMPSTE24-deficient mouse models have shown that fatty acid, glucose, and triglyceride levels are similar to those in wild-type mice [88,90]. Long chain fatty acids, such as triglycerides, accumulate in adipocytes to form lipid droplets [21]. The normal size of lipid droplets observed in MADB cells might suggests that ZMPSTE24 mutations may not severely affect lipogenesis; however, this requires further investigation.
|
| 162 |
+
|
| 163 |
+
The molecular mechanisms underlying HGPS-, FPLD2-, and MADB-associated lipodystrophy are likely different because these three diseases are linked to different mutations. HGPS and MADB disorders are linked to premature aging and lipodystrophy, while FPLD2 is mainly associated with alterations in adipogenesis with partial fat accumulation and metabolic syndrome [1,13,22,26]. To understand how lipodystrophy occurs in these three distinct genetic disorders, we examined the mechanism through which they alter adipogenesis. In this study, HGPS fibroblasts accumulated progerin and low levels of prelamin A; FPLD2 fibroblasts also accumulated low levels of prelamin A, while MADB fibroblasts constitutively expressed prelamin A due to mutation in ZMSPTE24. Consequently, all three cell models accumulated farnesylated prelamin A or progerin [26]. Overall, cells derived from these pathologies exhibited dysmorphic nuclei, nuclear blebbing, cellular senescence, and low proliferation rate [12,35,91]. However, the cellular alterations were more severe in HGPS and MADB cells than in FPLD2 cells, reinforcing the hypothesis that farnesylated prelamin A or progerin are critically toxic to cells. Accumulation of farnesylated prelamin A or progerin lead to DNA damage, altered chromatin organization, and changes in gene expression [49,92,93,94,95].
|
| 164 |
+
|
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Previous studies have shown that the accumulation of prenylated prelamin A isoforms is concomitantly followed by a reduction in lamin B1 [96,97]. Similarly, there was a decreased in lamin B1 levels in HGPS and FPLD2 fibroblasts in the present study, and this decrease was more prominent in MADB cells. A reduction in lamin B1 levels is linked to cellular senescence and changes in the lamina composition known to affect chromatin arrangement, replication, and transcription [98]. Hence, the lamina structure plays a role in mechanosensing, with lamin A and C providing nuclear stiffness and lamin B contributing to elasticity and deformation of the nuclear envelope [99]. Mutations in LMNA or ZMSPTE24 affect the composition of the lamina and can consequently alter the mechanotransduction of the nucleus and its response to intra- and extracellular signals [100,101,102]. Although it remains unclear why LMNA mutations affect lamin B1 levels, DNA damage and cellular senescence appear to be associated with reduced lamin B1 levels [96,99]. High levels of lamin B1 are expressed in preadipocytes and adipocytes [103], and its loss may contribute to alterations in nuclear membrane permeability and function [104,105]. Collectively, alterations in the nuclear lamina composition of HGPS, FPLD2, and MADB cells may underly the adipogenesis defects observed in these three pathologies.
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In the present study, we demonstrated the beneficial effect of Bar treatment alone and Bar+ FTI treatment on adipogenesis in HGPS, FPLD2, and MADB SKPs. Although in vivo studies are necessary to validate these results, our findings suggests that the Bar + FTI treatment combination might have therapeutic benefits for patients with HGPS-, FPLD2-, and MADB-associated lipodystrophy and possibly other age-related diseases.
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Acknowledgments
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We thank the Progeria Research Foundation and the patient families for providing HGPS fibroblasts.
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Supplementary Materials
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The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/cells12101350/s1, Figure S1: Lamin B1 detection in HGPS, FPLD2, and MADB fibroblasts; Figure S2: Full-length scan of western blots of Figure 7.
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Click here for additional data file.
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Author Contributions
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Conceptualization, K.D.; methodology, R.H., E.-M.L., E.S., G.L. and K.D.; formal analysis, R.H., E.-M.L., G.L. and K.D.; investigation, R.H. and K.D.; resources, K.D.; writing—original draft preparation, R.H. and K.D.; writing—review and editing, R.H. and K.D.; visualization, R.H.; supervision, K.D.; project administration, K.D.; funding acquisition, K.D. All authors have read and agreed to the published version of the manuscript.
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Institutional Review Board Statement
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The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the Faculty of Medicine of the Technical University of Munich (protocol 2836/10b S, approved on 17 October 2017).
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Informed Consent Statement
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Not applicable.
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Data Availability Statement
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Data are contained within the article and Supplementary Materials.
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Conflicts of Interest
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The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
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Figure 1 Schematic representation of low-pH isolation of SKPs from primary fibroblast cultures. Young fibroblasts (control cells passages 16–21, HGPS cells passages 10–16, FPLD2 cells passages 9–14, MADB cells passages 12–13) were treated with HBSS Buffer (pH 5.7) for 30 min at 37 °C. The SKPs were cultured in SKP media (DMEM low glucose plus EGF, FGF, and B27). After 4 d, SKPs spheroids were trypsinated and seeded in ADM (DMEM plus 10% FBS, IBMX, insulin, dexamethasone, L-ascorbic acid, fungizone, and penicillin/streptomycin) with or without drugs. After 14 d of differentiation, cells were fixed and stained with Oil Red O or BODIPY staining. HBSS: Hank’s Balanced Salt Solution; ADM: adipocyte differentiation media; DMEM: Dulbecco´s modified Eagle medium; EGF: epidermal growth factor; FGF: fibroblast growth factor; SKP´s: skin-derived precursor cells; FBS: fetal bovine serum; IBMX: isobutylmethylxanthine.
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Figure 2 Bright-field imaging of control (GM05567A, GM05757C, GM01651C) and HGPS (HGADFN003, HGADFN164, HGADFN178) adipocytes treated with the blank (mock), 0.025 μM FTI, with 1 μM baricitinib and a combination of 0.025 μM FTI and 1 μM baricitinib at 7 and 14 d after culture in adipocyte differentiation medium (ADM). SKPs were isolated with the low-pH stress method from primary fibroblast cultures and grown in SKP media. At 4 d, SKP were dissociated and cultured in ADM with indicated treatments. Lipid accumulation was clearly observed in control and HGPS adipocytes at 14 d of differentiation. Increased lipid droplet formation was observed in HGPS adipocytes treated with Bar and Bar + FTI. Scale bar: 50 μm.
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Figure 3 BODIPY (green) and oil red O (ORO) staining (red) of control and HGPS adipocytes after 14 d of differentiation under different treatment conditions. Treatments: no drug (mock), with 0.025 μM FTI, with 1 μM baricitinib and a combination of 0.025 μM FTI and 1 μM baricitinib. (a) BODIPY staining of lipid vesicles. Representative images for control (GM05567A, GM05757C, GM01651C) and HGPS (HGADFN003, HGADFN164, HGADFN178) adipocytes at d14 of differentiation. Cells were counterstained with DAPI. Scale bar 100 μm, scale bar: 20 μm. (b) Quantification of the total area of BODIPY signal. Total area of BODIPY was quantified by measuring the area with BODIPY-positive signal compared to total area of the coverslip. (c) Percentage of BODIPY positive cells. At least 1000 cells were counted per cell strains. (d) ORO staining of lipid droplets. Representative images for control (GM05567A, GM05757C, GM01651C) and HGPS (HGADFN003, HGADFN164, HGADFN178) adipocytes. Scale bar 100 μm, total images scale bar: 20 μM (e) Quantification of the total area of ORO signal. (f) Quantification of the lipid droplet size. (b,c,e,f) Values are presented as mean ± SD (n = 3); not significant (ns); ** p < 0.01; **** p < 0.0001; unpaired t-test.
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Figure 4 Bright-field imaging of control (GM05567A, GM05757C, GM01651C), FPLD2 (CCLMA00336s, CCLMS337s, CCBB00466s), and MADB (PSADFN317, PSADFN318) adipocytes treated without drug (mock), with 0.025 μM FTI, with 1 μM baricitinib, and with the combination of 0.025 μM FTI plus 1 μM baricitinib at 7 and 14 d after treatments. SKPs were isolated with low-pH stress method from primary fibroblast cultures and grown in SKP media. At 4 d, SKPs were dissociated and cultured in ADM containing indicated regimen. Lipid accumulation was more obvious in control, FPLD2, and MADB adipocytes at 14d of differentiation. Scale bar: 50 μm.
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Figure 5 BODIPY (green) and ORO (red) staining of control, FPLD2, and MADB adipocytes treated with 0.025 μM FTI, with 1 μM baricitinib, a combination of 0.025 μM FTI and 1 μM baricitinib, and mock solution after 14d of differentiation. (a) BODIPY staining of lipid vesicles. Representative images for control (GM05567A, GM05757C, GM01651C), FPLD2 (CCLMA00336s, CCLMS337s, CCBB00466s), and MADB (PSADFN317, PSADFN318) adipocytes. Cells were counterstained with DAPI. Scale bar 100 μm, total images scale bar: 20 μm. (b) Quantification of the total area of BODIPY signal. Total area of BODIPY was quantified by measuring the area of BODIPY-positive signal compared to total area of the coverslip. (c) Percentage of BODIPY-positive cells. (d) ORO staining of lipid droplets. Representative images for control (GM05567A, GM05757C, GM01651C), FPLD2 (CCLMA00336s, CCLMS337s, CCBB00466s), and MADB (PSADFN317, PSADFN318) adipocytes. Scale bar 100 μm, total images scale bar: 20 μM. (e) Quantification of the total area of ORO signal. (f) Quantification of the lipid droplet size. (b,c,e,f) Values are presented as mean ± SD (n = 3); not significant (ns); * p < 0.05; ** p < 0.01; *** p < 0.001; unpaired t-test.
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Figure 6 Localization of progerin and prelamin A in fibroblasts derived from different laminopathies: HGPS, FPLD2, and MADB. (a) Immunohistochemistry for progerin and prelamin A in young (senescence (SNS) ≤ 5%, control cells passages 16–21, HGPS cells passages 10–14, FPLD2 cells passages 9–14, MADB cells passages 12–14) and old (SNS ≥ 20%, control cells passages 28–31, HGPS cells passages 18–19, FPLD2 cells passages 20–23, MADB cells passages 16–17) control, HGPS, FPLD2, and MADB fibroblasts. Cell strains used for control (GM05567A, GM05757C, GM01651C), HGPS (HGADFN003, HGADFN164, HGADFN178), FPLD2 (CCLMA00336s, CCLMS337s, CCBB00466s), and MADB (PSADFN317, PSADFN318) fibroblasts. Cells were counterstained with DAPI. Scale bar 100 μm. (b) Quantification of the number of prelamin A positive nuclei in young (SNS ≤ 5%) and old (SNS ≥ 20%) control, HGPS, FPLD2, and MADB fibroblasts. (c) Representative images of normal (ovoid) and dysmorphic nuclei (abnormal and/or large nuclear shape), counterstained with DAPI. Scale bar 50 μm. (d) Quantification of the number of dysmorphic nuclei in young (SNS ≤ 5%) and old (SNS ≥ 20%) control, HGPS, FPLD2, and MADB fibroblasts. (b,d) Values are presented as mean ± SD (n = 3); not significant (ns); * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001; unpaired t-test.
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Figure 7 Progerin, prelamin A, lamin A/C, and lamin B1 status in young (SNS ≤ 5%, control cells passages 16–21, HGPS cells passages 10–14, FPLD2 cells passages 9–14, MADB cells passages 12–14) and old (SNS ≥ 20%, control cells passages 28–31, HGPS cells passages 18–19, FPLD2 cells passages 20–23, MADB cells passages 16–17) fibroblast cultures from different laminopathies associated with lipodystrophy. (a) Representative image of western blots for prelamin A and lamin B1 (n = 3). The percentage of senescence (SNS) cells in the cultures is indicated. (b) Quantification of lamin B1 levels. (c) Quantification of prelamin A levels. (d,e) Representative images of western blots for lamin A/C, prelamin A, and progerin in young and old fibroblast extracts (n = 3). (f) Ratio of prelamin A, lamin A, progerin, and lamin C in young and old fibroblasts (n = 3). (b,c) Graph show mean ± SD (n = 3); not significant (ns); * p < 0.05; *** p < 0.001; **** p < 0.0001; unpaired t-test.
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Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
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| 322 |
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|
puc/PMC10216850.txt
ADDED
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1 Division of Biochemistry and Molecular Biology, Department of Biomedical Sciences, Faculty of Medicine, Universitas Padjadjaran, Jatinangor, West Java, Indonesia
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2 Division of Cell Biology, Department of Biomedical Sciences, Faculty of Medicine, Universitas Padjadjaran, Jatinangor, West Java, Indonesia
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3 Department of Biomedical Sciences, Faculty of Medicine, Universitas Islam Bandung, Bandung, West Java, Indonesia
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4 Department of Pharmacy, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung, Bandung, West Java, Indonesia
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5 Politeknik Kesehatan Kementerian Kesehatan Makassar, Makassar, Indonesia
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6 Undergraduate Program Medical Doctor, Faculty of Medicine, Universitas Padjadjaran, Jatinangor, West Java, Indonesia
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Correspondence: Astrid Feinisa Khairani, Division of Cell Biology, Department of Biomedical Sciences, Faculty of Medicine, Universitas Padjadjaran, Jalan Raya Bandung – Sumedang Km 21, Jatinangor, West Java, 45363, Indonesia, Tel +62-22-7795594, Email astrid.khairani@unpad.ac.id
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22 5 2023
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2023
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15 217230
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26 1 2023
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08 5 2023
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© 2023 Ariyanto et al.
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2023
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Ariyanto et al.
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https://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
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Purpose
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We unravel the effect of anthocyanin-containing purple sweet potato synbiotic yogurt (PSPY) on 3T3-L1 adipocyte differentiation and its fundamental molecular mechanisms.
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Methods
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Molecular docking simulation was performed to observe and identify the affinity and interaction between bioactive compounds and targeted proteins. MDI (isobutylmethylxanthine, dexamethasone, and insulin)-containing medium, a cocktail that stimulates adipogenesis, was used in this study. The toxic effect possibility of the yogurt product was evaluated using 3-[4, 5-dimethylthiazol-2-yl]-2.5 diphenyl tetrazolium bromide (MTT) assay. A 0.25%, 0.5%, 1%, and 5% (v/v) plain or purple sweet potato yogurt supernatant was given to 3T3-L1 preadipocyte culture medium from 24 h after seeding until day 11 of MDI-induced differentiation. The mRNA expression and lipid accumulation were analyzed using RT-qPCR and Oil red O staining, respectively, on day 11 after differentiation induction.
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Results
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In silico study suggested that anthocyanin-derived compounds have the potential to inhibit peroxisome proliferator activated receptor gamma (PPAR-γ), a master regulator for white adipogenesis. Anthocyanin-containing PSPY significantly suppressed the expression of Pparg, Adipoq, Slc2a4, and Pgc1a. PSPY significantly suppressed Pparg with 1% and 5% concentrations, while with a concentration of 0.25%, PSPY significantly suppressed Adipoq expression as compared to control. Significant inhibition of Slc2a4 and Pgc1a was observed starting from a 0.25% concentration of PSPY. The suppression of adipogenic genes was also observed with the treatment of plain yogurt; however, the effects were relatively lower than the PSPY. The group treated with 1% and 5% of PSPY also showed inhibition effects on lipid accumulation.
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Conclusion
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This study demonstrated PSPY inhibition effect on white adipocyte differentiation through suppression of Pparg and its downstream genes, Adipoq and Slc2a4, indicating the potential of this yogurt as a functional food for obesity management and prevention.
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Keywords
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adipocyte differentiation
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anthocyanin
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Pparg
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purple sweet potato synbiotic yogurt
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Indonesian Endowment Fund for Education (Lembaga Pengelola Dana Pendidikan), Indonesia This work was funded by Indonesian Endowment Fund for Education (Lembaga Pengelola Dana Pendidikan), Indonesia (Grant number: PRJ-51/LPDP/2019). This research was also supported by The Ministry of Education, Culture, Research, and Technology, Indonesia, and Universitas Padjadjaran, Indonesia.
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==== Body
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pmcIntroduction
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Obesity is a global health problem whose prevalence increases from year to year.1 It is characterized by excessive fat deposition due to an imbalance between energy intake and energy expenditure.2 Obesity is accompanied by chronic low-grade inflammation, which is known to be an essential risk factor for the development of several metabolic diseases such as type 2 diabetes mellitus, coronary heart disease, cerebrovascular disease, and hypertension.3,4 To treat and prevent obesity, some strategies are required to change the lifestyle by improving physical activity and consuming healthy foods and a balanced diet.
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Yogurt is one of the functional foods that have the potential to improve human health, in which the lactic acid bacteria that ferment milk can act as probiotics. Probiotics consumption can modulate gut microbiota and give some benefits for health, such as maintaining intestinal permeability to prevent inflammation, transforming dietary phytochemicals into bioactive molecules, and producing antioxidants.5,6 It also has antimicrobial, immunomodulatory, and hepatoprotective effects and reduces adipogenesis and lipogenesis by suppressing insulin signaling.5–8
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Yogurt, which contains probiotics and prebiotics, is known as synbiotic yogurt.9 Lactic acid bacteria, a probiotic, use prebiotic substances to provide nutrition for their growth and proliferation.10 Purple sweet potato (Ipomoea batatas L.) is rich in fermentable carbohydrates. Therefore, it can be used to fortify yogurt and act as a prebiotic.11 In addition to carbohydrates, purple sweet potato also contains other nutrients such as carotenoids, proteins, lipids, vitamins, minerals, dietary fibers, and many anthocyanins, a class of flavonoid compounds.12 Many studies have revealed that anthocyanins in purple sweet potato have beneficial health effects such as antioxidative, antiaging, immunomodulatory, antihyperglycemic, hepatoprotective, antimicrobial, and anti-obesity effects.13–16 Furthermore, purple sweet potato yogurt was reported to have relatively higher antioxidant activity compared to plain yogurt.17
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A previous study by Khairani et al reported that purple sweet potato yogurt decreased visceral fat and liver weight in high-fat diet mice models and improved lipid profiles, including total cholesterol, triglycerides, and LDL level.18 However, the molecular mechanisms explaining how purple sweet potato yogurt exerts anti-obesity effects are still poorly understood. This study aimed to investigate the potential effects of purple sweet potato yogurt on adipocyte differentiation and the underlying molecular mechanisms using 3T3-L1 preadipocytes, the most commonly used cell line in elaborating the molecular mechanisms of adipocyte differentiation in vitro.
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Materials and Methods
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Molecular Docking Analysis
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Protein Preparation
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The proteins used in this simulation were PPAR-g, ADIPOQ, PGC-1α, and GLUT4. Crystallized protein structures were downloaded from Protein Data Bank Website (https://rcsb.org), while GLUT4 was modeled using the SWISS-MODEL Server.19 Protein structures were obtained and prepared using Discovery Studio 2017 and AutoDock 1.5.6. The preparation was carried out by removing water molecules and natural ligands, followed by adding polar hydrogen atoms and calculating the Kollman partial charge.20
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Molecular Modeling of the Test Compounds and Protein Active Site Identification
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Test compounds used in this study were Cyanidin-3-caffeoyl-p-hydroxy benzoyl sophoroside-5-glucoside, Peonidin-3-caffeoyl sophoroside-5-glucoside, and Peonidin-3-caffeoyl-p-hydroxy benzoyl sophoroside-5-glucoside that were included in anthocyanin-derived compounds. Molecular structures of the compound were drawn using GaussView Software and optimized geometrically using Gaussian 03W Software.21 The semi-empirical method was chosen with Austin Model 1 as the basic set. The optimized structures with modification of their partial charges were used as an input for molecular docking simulation.
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The macromolecular enzymes were prepared and processed for binding site identification, evaluation, and exploration process to check their biological activity using BIOVIA Discovery Studio 2020 Software.22
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Molecular Docking Simulation and Analysis
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Molecular docking simulation was performed using MGLTools 1.5.6 equipped with AutoDock4 to observe and identify the affinity and interaction between bioactive compounds and proteins. The gap between the enzyme and the bioactive compound surface was limited to 0.375 Å as a maximum radius. All simulations were carried out by 52 × 50 × 50 grid box size21 and continued using the Lamarckian Genetic Algorithm method with 100 confirmations.23
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Molecular interactions between protein and test compounds were identified and evaluated based on Gibbs’ binding value.21 The ligands’ docking conformation was determined by selecting the compounds with the highest affinity. Amino acid residues that play a role in the molecular interactions were then observed using BIOVIA Discovery Studio 2020 Software.22
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Preparation of Purple Sweet Potato Synbiotic Yogurt
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Lactic acid bacteria (L. bulgaricus ATCC-11842 and S. thermophilus FNCC-0015) were prepared to be used as probiotics. These probiotics were provided and prepared in Advanced Biomedical Laboratory, Division of Microbiology and Parasitology Laboratory, Faculty of Medicine, Universitas Padjadjaran, Indonesia. Firstly, the bacteria were cultured in medium I containing 10% skim milk in DeMan, Rogosa, and Sharpe (MRS) broth medium. Following that, 10% (v/v) of the cultured product from the medium I was subcultured into medium II (whole, skim milk) to make the starter yogurt. Finally, the starter yogurt was used to make the plain skim milk yogurt, and 3% of purple sweet potato flour was mixed to make the purple sweet potato yogurt.
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For yogurt treatment on 3T3-L1 preadipocytes, 10–12 mL of purple sweet potato yogurt was placed in a 15 mL conical tube and was centrifuged at 8000 rpm for 10 min. The supernatant of the yogurt was filtered using a 0.2 μm syringe filter and disposable syringe twice. The filtered supernatant-containing conical tube was wrapped in aluminum foil and stored in a 4°C storage cabinet until used in the following steps.
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Culture and Differentiation of 3T3-L1 Cells and Yogurt Treatment
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The 3T3-L1 cells, a murine fibroblast/pre-adipocyte cell line, were obtained from the German Diabetes Centre, Düsseldorf, and the Institute of Pharmacology and Toxicology, University Hospital of Bonn. The 3T3-L1 preadipocytes were cultured in high-glucose Dulbecco’s modified eagle medium (DMEM, Sigma, USA) containing 10% fetal bovine serum (FBS, Sigma, USA) and 1% penicillin-streptomycin at 37°C, 5% CO2. The cell line was cultured in 12-well plates with a seeding amount of 12 × 104 cells/well until 100% confluent. The confluent cells were further cultured in DMEM for 48 h. Afterward, the cells were induced by an MDI differentiation cocktail consisting of 0.5mM methyl-isobutyl-xanthine (Sigma, USA), 1 μM dexamethasone (Sigma, USA), and 10μg/mL insulin (Sigma, USA), which was determined as day 0 of the experiment.
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After culturing the cells in MDI-containing DMEM for 48 h, on day 3, the medium was then replaced with 10μg/mL insulin-containing DMEM. Further, to optimize glucose uptake and lipogenesis during the differentiation process, the cells were cultured with the same medium (10 μg/mL insulin-containing DMEM) until day 10. The medium replacement was conducted every 48 h. Yogurt treatment was given to the cells by adding 0.25%, 0.5%, 1%, and 5% (v/v) of plain yogurt supernatant and purple sweet potato yogurt supernatant into the medium starting from 24 h after cell seeding until day 11 throughout the experiment. Staining of lipid droplets in the cells and RNA extraction for RT-qPCR analysis were performed on day 11.
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MTT Assay
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The possibility of the toxic effect of purple sweet potato yogurt and plain yogurt on 3T3-L1 preadipocytes was done using 3-[4,5-dimethylthiazol-2-yl]-2.5 diphenyl tetrazolium bromide (MTT) assay as previously described.24 The cells were seeded in 96-well plates, incubated for 24 h, and treated with 0.25%, 0.5%, 1%, and 5% (v/v) of purple sweet potato yogurt supernatant or plain yogurt supernatant for 72 h. MTT reagents were then added to the cells for 4 h, and the reaction was stopped using DMSO. The plate was then shaken to dilute the crystal formazan before measuring the absorbance using a microplate reader at a wavelength of 550 nm. The percentage of cell death was calculated based on the absorbance value of the sample (cell treated with yogurt), control, and blank.
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Quantitative RT-qPCR Analysis
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Quantitative RT-qPCR was used to measure the mRNA expression of genes analyzed in this study. Total RNA was isolated from the cells using the Quick-RNA™ cDNA Synthesis Kit (Bioline Reagents Ltd., UK). Afterward, quantitative RT-PCR was performed using SensiFast™ SYBR® No-ROX Kit according to the manufacturer’s instructions. The polymerase activation was set at 95°C for 2 min, followed by 40 cycles of denaturation at 95°C for 5 s and annealing/extension at 60–65°C for 20 s. All mRNA expression was normalized with Ppib mRNA expression. The primers used in this study are listed in Table 1.25 Table 1 Primer Sequences for RT-qPCR Analysis
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No. Primer Name Sequences
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1 Pgc1a-Fw 5’-GAGGGCTCCGGCACTTC-3’
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2 Pgc1a-Rv 5’-CGTACTTGCTTTTCCCAGATGA-3’
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3 Pparg-Fw 5’-CAAGAATACCAAAGTGCGATCAA-3’
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4 Pparg-Rv 5’-GAGCTGGGTCTTTTCAGAATAATAAG-3’
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5 Adipoq-Fw 5’-CAGTGGATCTGACGACACCAA-3’
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6 Adipoq-Rv 5’-GAACAGGAGAGCTTGCAACAGT-3’
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7 Slc2a4-Fw 5’-TAACTTCATTGTCGGCATGGG-3’
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8 Slc2a4-Rv 5’-TGAAGAAGCCAAGCAGGAGG-3’
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Abbreviations: Fw, forward primer; Rv, reverse primer.
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Oil Red O Staining
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The cells were stained on day 11 of differentiation with Oil Red O (ORO, Sigma, USA) as previously described (Wakabayashi, 2009). Briefly, the cells were washed with phosphate-buffered saline (PBS, Sigma, USA) and fixed with 10% formaldehyde in PBS for 10 min. After washing the cells twice in PBS, the cells were stained for 15–20 min in freshly diluted ORO solution (0.18% (wt/vol) ORO in 60% isopropanol). After removing the stain, the cells were washed with PBS twice, and the images were taken under a microscope (Olympus CK40) with 100x and 200x magnifications.
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Statistical Analysis
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Statistical analysis in this study was performed using GraphPad Prism ver. 9 (GraphPad Software, Inc., La Jolla, CA) based on one-way ANOVA followed by Tukey’s post hoc test for multiple comparisons. The results were expressed as mean ± standard deviation (SD). Differences between groups were considered statistically significant at p<0.05.
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Results
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Anthocyanin-Derived Compounds Potentially Inhibit PPAR-γ
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Ligand and Protein Preparation
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In the molecular docking analysis, the three test compounds, namely Cyanidin-3-caffeoyl-p-hydroxy benzoyl sophoroside-5-glucoside, Peonidin-3-caffeoyl sophoroside-5-glucoside, and Peonidin-3-caffeoyl-p-hydroxy benzoyl sophoroside-5-glucoside were successfully imaged and optimized, as shown in Figure 1. The three compounds’ structural descriptions were taken from a previous study.26 Further, the protein structure was successfully prepared and visualized, as shown in Figure 2. Figure 1 The 3D Structures of Cyanidin-3-caffeoyl-p-hydroxybenzoyl sophoroside-5- glucoside (a), Peonidin-3-di caffeoyl sophoroside-5-glucoside (b), Peonidin-3-caffeoyl-p-hydroxybenzoyl sophoroside −5- glucoside (c).
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Figure 2 The 3D protein structures of ADIPOQ (a), GLUT4 (b), PGC-1α (c), and PPAR-γ (d).
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Molecular Docking
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The test compounds simulated in this study are the main active compounds in the purple sweet potato, which are reported to reduce blood sugar levels.27,28 In this study, the molecular docking of proteins related to adipogenesis was simulated to see whether the decrease in blood sugar levels was related to their activity on adipogenesis and precisely to determine the affinity strength. Each test compound was successfully docked to the receptor’s active site by producing 100 conformations for each compound.
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The tabulation of conformational energy for each compound against the protein is presented in Table 2. The compound with the lowest conformational energy, which indicated the highest affinity, was selected.29 The simulation results show that the compound Peonidin-3-caffeoyl-p-hydroxy benzoyl sophoroside-5-glucoside has a significantly higher affinity with PPAR-γ compared to other compound-protein combinations. Table 2 Tabulation of Conformational Energy of Each Compound Against the Protein
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Ligand Binding Energy (Kcal/mol)
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Adipoq Glut4 Pgc1-α PPAR-γ
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Cyanidin-3-caffeoyl-p-hydroxybenzoylsophoroside-5- glucoside 392.88 659.38 501.81 31.97
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Peonidin-3-dicaffeoylsophoroside-5-glucoside 606.91 1430 498.25 161.76
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Peonidin-3-caffeoyl-p-hydroxybenzoylsophoroside-5- glucoside 1340 379.44 161.3 16.1
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Interaction analysis was carried out to see the molecular binding mode of the compound with the lowest energy in each protein, as shown in Figure 3. Interaction analysis of each protein-compound complex shows interaction in red that is commonly referred to as unfavorable interactions developed a steric collision between amino acid side chains with chemical compounds, where this interaction indicates poor activity.30 However, there is a difference in the amount between each complex. The protein-compound complex with the least unfavorable interaction was PPAR-γ protein with only four unfavorable interactions.31 Meanwhile, the other proteins showed relatively more unfavorable interactions ranging between 7 and 11 interactions (Figure 3). Figure 3 Analysis of compound interaction with the lowest binding energy in ADIPOQ (a), GLUT4 (b), PGC-1α (c), and PPAR-γ (d) proteins.
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Purple Sweet Potato Synbiotic Yogurt Does Not Affect 3T3-L1 Viability
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The MTT assay aimed to confirm whether plain yogurt and purple sweet potato yogurt can affect 3T3-L1 growth and viability. The result shows that the treatment of 0.25%, 0.5%, 1%, and 5% (v/v) of plain yogurt supernatant (indicated as P0.25, P0.5, P1, and P5, respectively, in Figure 4) and PSPY supernatant (indicated as U0.25, U0.5, U1, and U5, respectively, in Figure 4) only affect less than 20% cell viability, suggesting that plain yogurt and PSPY up to the concentration of 5% are not toxic to 3T3-L1 preadipocytes.32 Figure 4 Viability of 3T3-L1 cell line under the treatment of plain yogurt supernatant (P) and purple sweet potato synbiotic yogurt supernatant (U) using MTT assay. P0.25: 0.25% plain yogurt, P0.5: 0.5% plain yogurt, P1: 1% plain yogurt, P5: 5% plain yogurt, U0.25: 0.25% purple sweet potato yogurt, U0.5: 0.5% purple sweet potato yogurt, U1: 1% purple sweet potato yogurt, U5: 5% purple sweet potato yogurt.
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Purple Sweet Potato Synbiotic Yogurt Inhibits White Adipocyte-Specific Genes During 3T3-L1 Adipocyte Differentiation
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The mRNA expression of Pparg, Adipoq, Slc2a4, and Pgc1a was measured to investigate PSPY’s capability to suppress white adipocyte-specific genes during 3T3-L1 adipocyte differentiation. Measurement of samples under the treatment of 0.25%, 0.5%, 1%, and 5% of plain yogurt supernatant (indicated as P0.25, P0.5, P1, and P5, respectively, in Figure 5) and PSPY supernatant (indicated as U0.25, U0.5, U1, and U5, respectively, in Figure 5) was conducted on day 11 of differentiation period. Figure 5 Relative mRNA expression of white adipocyte-specific genes on day 11 of 3T3-L1 adipocyte differentiation under the treatment of plain yogurt supernatant (P) and purple sweet potato synbiotic yogurt supernatant (U).
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Notes: (A) Inhibition of Pparg expression in a dose-dependent manner by PSPY. The expression of (B) Adipoq, (C) Slc2a4, and (D) Pgc1a is inhibited by both PSPY and plain yogurt in a dose-dependent manner. Pparg, Adipoq, Slc2a4, and Pgc1a mRNA expression was measured by RT-qPCR and normalized by Gapdh. RT-qPCR data are presented as mean+SD. *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001, n.s., not significant. P0.25: 0.25% plain yogurt, P0.5: 0.5% plain yogurt, P1: 1% plain yogurt, P5: 5% plain yogurt, U0.25: 0.25% purple sweet potato yogurt, U0.5: 0.5% purple sweet potato yogurt, U1: 1% purple sweet potato yogurt, U5: 5% purple sweet potato yogurt.
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The result showed that PSPY (indicated by U in Figure 5A) inhibited Pparg expression in a dose-dependent manner. Significant inhibition was observed in the concentration of 1% and 5% (Figure 5A). On the other hand, plain yogurt (indicated by P in Figure 2a) also inhibits Pparg expression in the concentration of 0.5%, 1%, and 5%. However, the degree of inhibition was not in line with the increase in concentration (Figure 5A).
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Further, the RT-qPCR result on Adipoq expression demonstrates the inhibitory effect of PSPY (indicated by U in Figure 5B) and plain yogurt (indicated by P in Figure 5B) on this gene in a dose-dependent manner, as compared with control. Interestingly, the degree of inhibition on Adipoq mRNA expression caused by PSPY treatment was higher than those caused by plain yogurt treatment (Figure 5B). With a concentration of 0.25%, PSPY treatment yields significant inhibition of Adipoq expression compared with control (p<0.01). Meanwhile, plain yogurt treatment with 0.25% concentration does not significantly inhibit Adipoq expression (p>0.05). Furthermore, for the concentration of 0.25% and 0.5%, the degree of inhibition caused by PSPY is about two-fold higher than those caused by plain yogurt. The statistical comparison between two yogurts at the same concentration does not show significant differences (Figure 5B). These findings imply that purple sweet potato synbiotic yogurt exerts a stronger inhibitory effect on Adipoq expression than plain yogurt.
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Treatment of purple sweet potato yogurt (indicated by U in Figure 5C) and plain yogurt (indicated by P in Figure 5C) decreased the expression of Slc2a4, a gene-encoding glucose transporter type 4 (Glut4), in a dose-dependent manner (Figure 5C). Moreover, the degree of inhibition yielded by purple sweet potato yogurt treatment is higher than those caused by plain yogurt treatment (Figure 5C). At a concentration of 0.25%, purple sweet potato yogurt treatment produced significant inhibition of Slc2a4 expression as compared with control (p<0.01), while plain yogurt treatment did not cause significant inhibition (p>0.05). In addition, at concentrations of 0.25%, 0.5%, and 1%, the degree of inhibition exerted by purple sweet potato yogurt is about two-fold higher than those caused by plain yogurt. At the concentration of 0.25%, the comparison between the two yogurts showed a very significant difference (p<0.0001, Figure 5C). These findings suggested that purple sweet potato synbiotic yogurt has a stronger inhibitory effect on Slc2a4 expression than plain yogurt.
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Similarly, Pgc1a mRNA expression during adipocyte differentiation significantly decreased in a dose-dependent manner (p<0.001) upon treatment with both purple sweet potato yogurt and plain yogurt. The higher the intervention concentration was given, the more inhibition was observed. Moreover, purple sweet potato yogurt demonstrated a stronger suppression effect on Pgc1a expression than plain yogurt at 0.25% and 0.5%. Even though the differences between the group with the same concentration were not statistically significant (Figure 5D), this result suggested that purple sweet potato synbiotic yogurt yields a stronger inhibitory effect on Pgc1a expression compared with plain yogurt.
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Purple Sweet Potato Synbiotic Yogurt Inhibits Lipid Accumulation During Adipocyte Differentiation
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The lipid droplets in the cells were stained with Oil red O to evaluate whether inhibition of adipogenic genes by purple sweet potato yogurt also leads to the inhibition of lipid accumulation during the differentiation process. The staining process was conducted on day 11 differentiation, and the lipid droplets were observed under the microscope. The results indicated that purple sweet potato yogurt treatment at a concentration of 1% and 5% inhibits the formation of lipid droplets. Meanwhile, plain yogurt inhibited lipid accumulation in the concentration of 5% (Figure 6). This finding demonstrated that purple sweet potato synbiotic yogurt inhibited lipid accumulation during 3T3-L1 adipocyte differentiation. Figure 6 Microscopic pictures of 3T3-L1 cells after Oil red O staining on day 11 of differentiation under the treatment of plain yogurt supernatant (P) and purple sweet potato synbiotic yogurt supernatant (U). P0.25%: 0.25% plain yogurt, P0.5%: 0.5% plain yogurt, P1%: 1% plain yogurt, P5%: 5% plain yogurt, U0.25%: 0.25% purple sweet potato yogurt, U0.5%: 0.5% purple sweet potato yogurt, U1%: 1% purple sweet potato yogurt, U5%: 5% purple sweet potato yogurt.
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Discussion
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The objective of this study was to elaborate on the potential effects of purple sweet potato synbiotic yogurt on white adipocyte differentiation and the underlying molecular mechanisms. Our data showed that anthocyanin-containing purple sweet potato synbiotic yogurt inhibited the expression of white adipocyte-specific genes (Pparg, Adipoq, and Slc2a4), consequently inhibiting lipid accumulation during adipocyte differentiation. Moreover, molecular docking analysis showed that anthocyanin-derived compounds potentially inhibit PPAR-γ.
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Adipocyte differentiation is a process that mostly depends on adipogenic gene expressions, including in 3T3-L1 preadipocytes. Those gene expressions will affect and can be seen in the adipocyte phenotype, such as lipid droplet accumulation at the end of the differentiation stage. Induction of Pparg, Cebpa, and their downstream genes such as Adipoq and Slc2a4 was reported to drive white adipocyte differentiation.33 Inhibition of adipocyte differentiation is one of the promising strategies for obesity management and prevention.34
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Yogurt is one of the anti-obesity probiotic diets with several underlying molecular mechanisms. Conjugated linoleic acid (CLA) content in yogurt can lower Pparg expression.35 A study conducted by Guanlin et al showed a dose-dependent decrease of Pparg expression after induction by CLA.36 Lactic acid-producing bacteria as probiotic content in yogurt also support anti-adipogenic properties of yogurt. Decreases in lipid accumulation and triglyceride content due to the effect of probiotic bacteria were observed in previous research conducted by Lee et al.37 The current study showed consistent results with previous reports that yogurt treatment to 3T3-L1 preadipocytes decreased the expression of Pparg and its downstream genes such as Adipoq and Slc2a4 in a dose-dependent manner.
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Anti-adipogenic effect of probiotic yogurt can be enhanced by mixing it with prebiotics such as purple sweet potato to form a synbiotic yogurt.18 Anthocyanin and oligosaccharides are rich in purple sweet potato, so they can produce optimal effects on preventing and treating obesity.38 The oligosaccharide in purple sweet potato increases the content of probiotic bacteria to be more optimal in reducing lipid accumulation. Moreover, anthocyanins which are pretty abundant in purple sweet potatoes and are known to inhibit the expression of Pparg and Cebpa.39 It might explain why in this study, purple sweet potato yogurt had a stronger inhibition effect on adipogenic gene expression, in this case, Pparg, Adipoq, and Slc2a4 compared with plain yogurt.
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Previous studies have suggested that peroxisome proliferator-activated receptor-gamma coactivator 1 alpha (PGC-1 alpha) plays an important role in the browning of adipose tissue by stimulating mitochondrial biogenesis and inducing transcription factor Ppara which subsequently stimulates the expression of brown adipocyte-specific genes such as Ucp1 and Prdm16.40,41 Interestingly, this study found that purple sweet potato yogurt and plain yogurt suppressed the mRNA expression of Pgc1a during 3T3-L1 differentiation, suggesting that brown adipogenesis might not increase as the compensation of inhibited white adipocyte differentiation. In addition to the inhibition effect of anthocyanin-containing purple sweet potato synbiotic yogurt on PPARG, this study also revealed the inhibition effect of sweet potato yogurt on Pgc1a expression. This finding supported the hypothesis that different molecular pathways regulate white and brown adipocyte differentiation.
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In this experiment, the control cells, which were only treated with MDI stimulation without yogurt supplementation, accumulated lipid. The lipid accumulation occurred due to several interrelated factors, such as the abundance of glucose in the medium, increased expression of Slc2a4, which encodes and facilitates glucose transporter 4 (GLUT4) synthesis, and the presence of cAMP agonist IBMX, dexamethasone, and insulin (MDI mixture) which in turn, activated the insulin-induced adipocyte differentiation.42 Furthermore, MDI also increased the expression of Pparg and Cebpa, which accelerated adipogenesis by inducing their downstream genes such as Slc2a4 and Adipoq.40 In purple sweet potato synbiotic yogurt-treated cells, the induction of Pparg, Slc2a4, and Adipoq was inhibited, resulting in reduced lipid accumulation.
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This study showed the inhibition effect of purple sweet potato synbiotic yogurt on adipocyte differentiation by suppressing Pparg and its down-regulated genes: Adipoq and Slc2a4. Although both plain and purple sweet potato yogurt showed an inhibition effect on these genes, more substantial inhibition effects were observed upon purple sweet potato yogurt supplementation.
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The limitation of this study is that the inhibition effect of purple sweet potato synbiotic yogurt on the accumulation of lipid droplets, as observed in the microscopic picture in Figure 6, is not very obvious. This result might happen due to several reasons. One possible reason is that the lipid accumulation in the control cells had not reached the optimal amount; thus, the inhibition in the purple sweet potato yogurt-treated cells could not be seen clearly. It was also possible that the white adipocyte accumulation happened through several molecular pathways. Therefore, it is recommended to investigate other genes responsible for other pathways, such as the insulin signaling pathway. Furthermore, this study showed promising results in adipogenic molecular pathway, and we also suggest to proceed this investigation to the in vivo study using mice models.
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Conclusion
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This study reveals the inhibition effect of purple sweet potato synbiotic yogurt on white adipocyte differentiation through the suppression of PPAR-γ, suggesting the potential of this yogurt for obesity management and prevention.
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Acknowledgments
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This study was conducted at Microbiology, Cell Culture, and Molecular Genetics Laboratories, Faculty of Medicine, Universitas Padjadjaran, Indonesia. We would like to express our gratitude to Dr. Afiat Berbudi for the kind gift of the 3T3-L1 cell line and Tenny Putri, Nurul Qomarila, Nurul Setia Rahayu, and Erlina Widiarsih for their technical assistance.
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Author Contributions
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All the authors made substantial contributions to the design, conducting research, acquisition of data, and data analysis; took part in drafting the article or critically revising for important intellectual content. All authors agreed to submit to this journal, given final approval of the version to be published and agreed to be accountable for all aspects of the work.
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Disclosure
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The authors declare they have no conflicts of interest to disclose.
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==== Front
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Genes (Basel)
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Genes (Basel)
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genes
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Genes
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2073-4425
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MDPI
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10.3390/genes14051121
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genes-14-01121
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Editorial
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Special Issue: Lipid Metabolism, Adipogenesis and Fat Tissue Metabolism: Gene Regulation
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https://orcid.org/0000-0003-4059-1362
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| 15 |
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Skrzypski Marek *
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https://orcid.org/0000-0003-0715-0223
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| 17 |
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Kołodziejski Paweł A. *
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| 18 |
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Department of Animal Physiology, Biochemistry, and Biostructure, Poznan University of Life Sciences, 60-637 Poznan, Poland
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* Correspondence: marek.skrzypski@up.poznan.pl (M.S.); pawel.kolodziejski@up.poznan.pl (P.A.K.); Tel.: +48-618466081 (M.S.); +48-488466085 (P.A.K.)
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22 5 2023
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5 2023
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14 5 112111 5 2023
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16 5 2023
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© 2023 by the authors.
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2023
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https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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This research received no external funding.
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==== Body
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pmcLipid metabolism is pivotal in controlling energy homeostasis. Impaired lipid metabolism is a hallmark of numerous health problems, including adiposity, cardiovascular diseases, diabetes, and several types of cancers [1]. This Special Issue, which encompasses six original works and two review articles, aimed to focus on recent advances regarding contributions related to gene-regulated mechanisms responsible for lipid metabolism regulation, adipogenesis, and biological functions of adipose tissue.
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Growing evidence demonstrates that the lipid metabolism of peripheral tissues is modulated by peptide hormones [2]. Leciejewska et al. focused on the role of the spexin hormone in controlling the development and metabolism of muscle cells [3]. The authors demonstrated that spexin promotes the replication of the skeletal muscle cell line C2C12 and the differentiation of these cells into muscles. Their results showed that spexin may be involved in controlling the metabolism and formation of muscles. Another peptide hormone, adropin, was studied by Jasaszwili et al., who demonstrated that it stimulates lipolysis in 3T3–L1 and rat primary adipocytes [4]. Furthermore, it was shown that adropin upregulates the expression of adiponectin while suppressing the expression of visfatin. This study indicated that a decline might contribute to the regulation of metabolism through direct interaction with mature white adipocytes.
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There is growing evidence that the metabolism of lipids is influenced by genetic variability, different miRNAs, and epigenetic modifications [5,6]. Alanbaei et al. revealed an association between ANGPTL3 gene variants and levels of irisin and lipid metabolism and insensitivity to insulin in Arab individuals from Kuwait [7]. Płatek et al. attempted to identify epigenetic modulations related to high levels of FGF-21 in obese non-diabetic individuals [8]. This study found that obese individuals with increased levels of FGF21 are characterized by alerted methylation in several genes encoding for a protein involved in regulating FGF-21 expression, its receptors, and cofactors. Furthermore, this study identified several miRNAs that may contribute to regulating FGF-21 expression and production in obesity. Hicks et al. used combined miRNome and transcriptome data to provide detailed characterization of miRNA-regulatory networks implicated in the development and functions of adipose tissue in the chick peri-hatching period [9]. Meanwhile, in their study, Małodobra-Mazur et al. investigated the influence of different fatty acids on the adipogenesis of subcutaneous- and visceral-derived mesenchymal stem cells [10]. This study identified metabolic differences between subcutaneous and visceral fat depots and showed that oleic acid has the most notable effect on adipogenesis.
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This Special Issue also includes two review articles. Our research group discussed the potential role of selected peptide hormones discovered in the present century (adropin, apelin, elabela, irisin, kisspeptin, MOTS-c, phoenixin, spexin, and neuropeptides B and W) in controlling the formation and biology of white and brown adipocytes [11]. Furthermore, Dixon et al. summarized and elaborated on recent evidence highlighting the importance of lipases and nuclear receptors, PPARs, and liver X receptor (LXR) in obesity, diabetes, and non-alcoholic fatty liver disease [12].
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| 36 |
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In conclusion, the experimental data published in this SI significantly improved our knowledge of the role of peptide hormones in controlling lipid metabolism in adipose tissue and other peripheral tissues such as muscles. This SI also sheds light on the importance of miRNAs expression and epigenetic mechanism in controlling lipid metabolism, adipose tissue development, and its endocrine and metabolic activity. We believe the published results will play a key role in future research aiming to identify new diagnostic and therapeutic tools in lipid metabolism abnormalities and adipose dysfunction.
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| 38 |
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Conflicts of Interest
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| 40 |
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The authors declare no conflict of interest.
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Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
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==== Refs
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References
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1. Natesan V. Kim S.-J. Lipid Metabolism, Disorders and Therapeutic Drugs—Review Biomol. Ther. 2021 29 596 604 10.4062/biomolther.2021.122 34697272
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2. Zhang D. Wei Y. Huang Q. Chen Y. Zeng K. Yang W. Chen J. Chen J. Important Hormones Regulating Lipid Metabolism Molecules 2022 27 7052 10.3390/molecules27207052 36296646
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3. Leciejewska N. Kołodziejski P.A. Sassek M. Nogowski L. Małek E. Pruszyńska-Oszmałek E. Ostarine-Induced Myogenic Differentiation in C2C12, L6, and Rat Muscles Int. J. Mol. Sci. 2022 23 4404 10.3390/ijms23084404 35457222
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4. Jasaszwili M. Pruszyńska-Oszmałek E. Wojciechowicz T. Strowski M.Z. Nowak K.W. Skrzypski M. Adropin Slightly Modulates Lipolysis, Lipogenesis and Expression of Adipokines but Not Glucose Uptake in Rodent Adipocytes Genes 2021 12 914 10.3390/genes12060914 34199277
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5. Desgagné V. Bouchard L. Guérin R. MicroRNAs in Lipoprotein and Lipid Metabolism: From Biological Function to Clinical Application Clin. Chem. Lab. Med. 2017 55 667 686 10.1515/cclm-2016-0575 27987357
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6. Axsom J.E. Schmidt H.D. Matura L.A. Libonati J.R. The Influence of Epigenetic Modifications on Metabolic Changes in White Adipose Tissue and Liver and Their Potential Impact in Exercise Front. Physiol. 2021 12 686270 10.3389/fphys.2021.686270 34512374
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7. Alanbaei M. Abu-Farha M. Hebbar P. Melhem M. Chandy B.S. Anoop E. Cherian P. Al-Khairi I. Alkayal F. Al-Mulla F. ANGPTL3 Variants Associate with Lower Levels of Irisin and C-Peptide in a Cohort of Arab Individuals Genes 2021 12 755 10.3390/genes12050755 34067751
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8. Płatek T. Polus A. Góralska J. Raźny U. Dziewońska A. Micek A. Dembińska-Kieć A. Solnica B. Malczewska-Malec M. Epigenetic Regulation of Processes Related to High Level of Fibroblast Growth Factor 21 in Obese Subjects Genes 2021 12 307 10.3390/genes12020307 33670024
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| 55 |
+
9. Hicks J.A. Liu H.-C. Expression Signatures of MicroRNAs and Their Targeted Pathways in the Adipose Tissue of Chickens during the Transition from Embryonic to Post-Hatch Development Genes 2021 12 196 10.3390/genes12020196 33572831
|
| 56 |
+
10. Małodobra-Mazur M. Cierzniak A. Pawełka D. Kaliszewski K. Rudnicki J. Dobosz T. Metabolic Differences between Subcutaneous and Visceral Adipocytes Differentiated with an Excess of Saturated and Monounsaturated Fatty Acids Genes 2020 11 1092 10.3390/genes11091092 32962087
|
| 57 |
+
11. Kołodziejski P.A. Pruszyńska-Oszmałek E. Wojciechowicz T. Sassek M. Leciejewska N. Jasaszwili M. Billert M. Małek E. Szczepankiewicz D. Misiewicz-Mielnik M. The Role of Peptide Hormones Discovered in the 21st Century in the Regulation of Adipose Tissue Functions Genes 2021 12 756 10.3390/genes12050756 34067710
|
| 58 |
+
12. Dixon E.D. Nardo A.D. Claudel T. Trauner M. The Role of Lipid Sensing Nuclear Receptors (PPARs and LXR) and Metabolic Lipases in Obesity, Diabetes, and NAFLD Genes 2021 12 645 10.3390/genes12050645 33926085
|
| 59 |
+
|
puc/PMC10232201.txt
ADDED
|
@@ -0,0 +1,320 @@
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|
| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Nutr Res Pract
|
| 4 |
+
Nutr Res Pract
|
| 5 |
+
NRP
|
| 6 |
+
Nutrition Research and Practice
|
| 7 |
+
1976-1457
|
| 8 |
+
2005-6168
|
| 9 |
+
The Korean Nutrition Society and the Korean Society of Community Nutrition
|
| 10 |
+
|
| 11 |
+
10.4162/nrp.2023.17.3.438
|
| 12 |
+
Original Research
|
| 13 |
+
Quercetin inhibits body weight gain and adipogenesis via matrix metalloproteinases in mice fed a high-fat diet
|
| 14 |
+
https://orcid.org/0000-0001-9333-1658
|
| 15 |
+
Song SeungMin
|
| 16 |
+
https://orcid.org/0000-0002-9342-5483
|
| 17 |
+
Ha Ae Wha
|
| 18 |
+
https://orcid.org/0000-0002-8652-5339
|
| 19 |
+
Kim WooKyoung
|
| 20 |
+
Department of Food Science and Nutrition, Dankook University, Chungnam 31116, Korea.
|
| 21 |
+
Corresponding Author: WooKyoung Kim. Department of Food Science and Nutrition, Dankook University, 119 Dandae-ro, Dongnam-gu, Cheonan 31116, Korea. Tel. +82-41-550-3471, Fax. +82-41-559-7955, wkkim@dankook.ac.kr
|
| 22 |
+
6 2023
|
| 23 |
+
23 11 2022
|
| 24 |
+
17 3 438450
|
| 25 |
+
14 9 2022
|
| 26 |
+
26 10 2022
|
| 27 |
+
04 11 2022
|
| 28 |
+
©2023 The Korean Nutrition Society and the Korean Society of Community Nutrition
|
| 29 |
+
2023
|
| 30 |
+
The Korean Nutrition Society and the Korean Society of Community Nutrition
|
| 31 |
+
https://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
|
| 32 |
+
BACKGROUND/OBJECTIVES
|
| 33 |
+
|
| 34 |
+
Limited studies reported that quercetin inhibited adipogenesis and neovascularization by inhibiting matrix metalloproteinases (MMPs) activity, but such mechanisms have not been elucidated in animal experiments. In this study, we investigated the inhibitory effects of quercetin on weight gain and adipose tissue growth through the regulation of mRNA expressions of adipogenic transcription factors and MMPs in mice fed a high-fat diet (HFD).
|
| 35 |
+
|
| 36 |
+
MATERIALS/METHODS
|
| 37 |
+
|
| 38 |
+
Five-wk-old C57BL/6J mice were fed a normal diet (ND), HFD, HFD containing 0.05% of quercetin (HFQ0.05), or HFD containing 0.15% of quercetin (HFQ0.15) for 16 wks. Glycerol-3-phosphate dehydrogenase (GPDH) activity was measured using a commercial kit. The mRNA expressions of transcription factors related to adipocyte differentiation were determined by real-time polymerase chain reaction (PCR). The mRNA expressions of MMPs and concentrations of MMPs were measured by real-time PCR and enzyme-linked immunosorbent assay kit, respectively.
|
| 39 |
+
|
| 40 |
+
RESULTS
|
| 41 |
+
|
| 42 |
+
Quercetin intake reduced body weight gain and epididymal adipose tissue weights (P < 0.05). GPDH activity was higher in the HFD group than in the ND group but lower in the quercetin groups (P < 0.05). The mRNA expressions of CCAAT/enhancer binding protein β (C/EBPβ), C/EBPα, peroxisome proliferator-activated receptor γ, and fatty acid-binding protein 4 were lower in the quercetin groups than in the HFD group (P < 0.05). Similarly, the mRNA expression and concentrations of MMP-2 and MMP-9 were significantly lower in the quercetin groups than in the HFD group (P < 0.05).
|
| 43 |
+
|
| 44 |
+
CONCLUSION
|
| 45 |
+
|
| 46 |
+
The study confirms that quercetin suppresses body weight gain and adipogenesis by inhibiting transcription factors related to adipocyte differentiation and MMPs (MMP-2 and MMP-9), in mice fed a HFD.
|
| 47 |
+
|
| 48 |
+
Quercetin
|
| 49 |
+
adipogenesis
|
| 50 |
+
angiogenesis
|
| 51 |
+
matrix metalloproteinase
|
| 52 |
+
obesity
|
| 53 |
+
National Research Foundation of Korea https://doi.org/10.13039/501100003725 NRF-2018R1D1A1B07043918
|
| 54 |
+
==== Body
|
| 55 |
+
pmcINTRODUCTION
|
| 56 |
+
|
| 57 |
+
The prevalence of obesity in Korea is steadily increasing. The adult obesity rate among Koreas aged ≥ 20 increased from 32.4% in 2012 to 38.3% in 2020. The obesity rate for men is higher than for women in 2020 (48.0% and 27.7%) [1]. It has been well established that obesity is strongly associated with increased risks of obesity-related disorders such as type 2 diabetes, hyperlipidemia, hypertension, and metabolic syndrome [2].
|
| 58 |
+
|
| 59 |
+
Obesity is caused by the growth and expansion of adipose tissue. Most tissues stop growing or reduce in size after adulthood, but adipose tissue increases in adults when caloric intake exceeds expenditure [3]. An increase in adipose tissue is not only dependent on the expressions of adipogenic genes but also requires angiogenesis to establish the blood vessels required to supply the nutrients necessary for adipocyte proliferation, differentiation, and growth.
|
| 60 |
+
|
| 61 |
+
Adipogenesis is controlled by several adipogenic transcription factors such as CCAAT/enhancer binding protein β (C/EBPβ), C/EBPα (expressed in the early stage of adipogenesis), and peroxisome proliferator-activated receptor γ (PPARγ) (expressed during the later stage) [45]. During adipogenesis, angiogenesis is essential to supply oxygen and nutrients to adipose tissue. Angiogenesis is a complex process stimulated by angiogenesis promoters and proceeds in a series of stages [6]. Angiogenesis-promoting factors are secreted and bind to their respective receptors on vascular endothelial cells, activating these cells. During the initial stage, matrix metalloproteinases (MMPs) are secreted and activated to decompose the basement membrane and extracellular matrix (ECM) around vascular endothelial cells, which then migrate and proliferate from existing blood vessels [7]. These previous observations show that adipogenesis and angiogenesis play important roles in adipocyte hyperplasia and the hypertrophic capacity of adipocytes.
|
| 62 |
+
|
| 63 |
+
Research on adipocyte differentiation and functional control using food-derived bioactive substances is being conducted [891011121314]. Quercetin (3,5,7,3′,4′-pentahydroxyflavone) is a polyphenol abundantly present in fruits and vegetables (especially onions). It has been reported to have anti-obesity effects by inducing adipocyte apoptosis [15] or inhibiting adipogenesis by inducing the expressions of genes involved in fatty acid oxidation and energy metabolism [16]. However, although it has been reported that the MMPs in adipose tissue play an important role in obesity [67], studies on the relationship between MMPs activation and quercetin are limited to in vitro cell studies [171819]. Thus, mechanistic studies are required in animal models of obesity to identify the biological mechanisms involved. Accordingly, this in vivo study was conducted to determine whether quercetin inhibits adipogenesis, and thus, obesity, by inhibiting MMP expressions in a high-fat diet (HFD)-induced animal model.
|
| 64 |
+
|
| 65 |
+
MATERIALS AND METHODS
|
| 66 |
+
|
| 67 |
+
Animals and study design
|
| 68 |
+
|
| 69 |
+
Five-wk-old C57BL/6J mice (Daehan Biolink, Eumsung, Korea) were randomly allocated to 4 experimental groups; a normal-fat diet group (ND, n = 8; containing 7% fat on a diet weight basis), HFD group (HFD, n = 8; containing 25% fat and 0.5% cholesterol), HFD with 0.05% quercetin group (HFQ0.05, n = 8; containing 25% fat, 0.5% cholesterol, and 0.05% quercetin), and HFD with 0.15% quercetin group (HFQ0.15, n = 8; containing 25% fat, 0.5% cholesterol, and 0.15% quercetin). All mice were fed the AIN-93G diet but with different amounts of fat, cholesterol, quercetin, and carbohydrate (Table 1). Quercetin (purity ≥ 95.0%) was purchased from Sigma-Aldrich (Sigma Aldrich, St. Louis, MO, USA). Mice were housed individually in stainless steel cages in conditioned rooms (temperature 23 ± 1°C, humidity 60%, 12:12-h light-dark cycle) and weighed weekly during the 16-wk experimental period. All experiments were approved beforehand by the Animal Testing Ethics Committee of Dankook University (DKU-19-021).
|
| 70 |
+
|
| 71 |
+
Table 1 Compositions of the experimental diets
|
| 72 |
+
|
| 73 |
+
Ingredients (g) Group1)
|
| 74 |
+
NF HFD HFQ0.05 HFQ0.15
|
| 75 |
+
Corn starch 529.486 344.486 343.986 342.986
|
| 76 |
+
Sucrose 100 100 100 100
|
| 77 |
+
Casein 200 200 200 200
|
| 78 |
+
L-cystine 3 3 3 3
|
| 79 |
+
Cellulose 50 50 50 50
|
| 80 |
+
Soybean oil 70 70 70 70
|
| 81 |
+
Lard - 180 180 180
|
| 82 |
+
Cholesterol - 5 5 5
|
| 83 |
+
Mineral mix2) 35 35 35 35
|
| 84 |
+
Vitamin mix3) 10 10 10 10
|
| 85 |
+
Choline bitartrate 2.5 2.5 2.5 2.5
|
| 86 |
+
t-Butylhydroquinone 0.014 0.014 0.014 0.014
|
| 87 |
+
Quercetin - - 0.5 1.5
|
| 88 |
+
Total (g) 1,000 1,000 1,000 1,000
|
| 89 |
+
Fat kcal (%) 16.0 46.6 46.6 46.6
|
| 90 |
+
1)ND, normal fat diet; HFD, high fat diet; HFQ0.05, high fat diet + quercetin 0.05%; HFQ0.15, high fat diet + quercetin 0.15%.
|
| 91 |
+
|
| 92 |
+
2)Mineral mixture (AIN-93G diet, per kg): calcium carbonate anhydrous, 357 g; potassium phosphate monobasic, 196 g; potassium citrate tripotassium monohydrate, 70.78 g; potassium sulfate sodium chloride, 74 g; magnesium oxide, 24 g; ferric citrate, 6.06 g; zinc carbonate, 1.65 g; sodium metasilicate, 1.45 g; manganese carbonate, 0.63 g; cupric carbonate, 0.30 g; chromium potassium sulfate, 0.275 g; boric acid, 81.5 mg; sodium fluoride, 63.5 mg; nickel carbonate, 31.8 mg; lithium chloride, 17.4 mg; sodium selenate anhydrous, 10.25 mg; potassium iodate, 10.0 mg; ammonium paramolybdate, 6.66 mg; powdered sucrose, 221.026 g.
|
| 93 |
+
|
| 94 |
+
3)Vitamin mixture (AIN-93G diet, per kg): nicotinic acid, 3.0 g; ca pantothenate, 1.6 g; pyridoxine HCl 0.7 g; thiamine HCl, 0.6 g; riboflavin 0.6 g; folic acid, 0.2 g; biotin, 0.02 g; vitamin B12, 2.5 g; vitamin E, 15.0 g; vitamin A, 0.8 g; vitamin D3, 0.25 g; vitamin K-1, 0.075 g; powdered sucrose, 974.655 g.
|
| 95 |
+
|
| 96 |
+
Sample preparation
|
| 97 |
+
|
| 98 |
+
After 16 wks of feeding, animals were fasted for 12 h and then anesthetized with CO2. Heart blood samples were placed in test tubes containing sodium heparin. Blood samples were centrifuged at 3,000 rpm for 15 min at 4°C, and plasma was collected. After blood sampling, livers, kidneys, spleens, thymuses, and epididymal fat pads were removed, washed with 0.9% NaCl solution, and weighed. All samples were stored at 70°C until analysis.
|
| 99 |
+
|
| 100 |
+
Glycerol-3-phosphate dehydrogenase (GPDH) activity in adipose tissue
|
| 101 |
+
|
| 102 |
+
A GPDH Assay Kit (Abcam, Cambridge, United Kingdom) was used to measure GPDH activity. Homogenized epididymal fat pads (10 mg) were mixed well with 200 μL GPDH buffer in the assay kit and centrifuged at 12,000 rpm for 5 min at 4°C. GPDH activity was determined in supernatants according to the manufacturer’s instructions. Absorbance was measured at 450 nm using a microplate reader (Molecular Devices, San Jose, CA, USA).
|
| 103 |
+
|
| 104 |
+
mRNA expressions of transcription factors related to adipocyte differentiation in liver
|
| 105 |
+
|
| 106 |
+
Total RNA isolation: Liver samples (0.2 g) were homogenized in 1 mL of TRI Reagent (Sigma Aldrich) and held for 5 min at room temperature (RT). Chloroform (200 μL; Sigma Aldrich) was added, shaken vigorously, allowed to stand for 3 min at RT, and centrifugated at 13,500 rpm for 45 min at 4°C. Isopropanol (500 μL) was then added to supernatants, mixed, allowed to stand for 10 min at RT, and centrifuged at 13,500 rpm at 4°C. After removing supernatants, RNA pellets were washed with 1 mL 75% ethanol and centrifugated at 9,500 rpm for 10 min at 4°C. Pellets were then thoroughly dried and dissolved in 50 μL RNase-free dH2O containing 0.1 mM ethylenediaminetetraacetic acid by trituration through a pipette tip. Absorbances were measured at 260 and 280 nm using a microplate reader (Molecular Devices). The purity of RNA preparations was evaluated using 260 vs. 280 nm absorbance ratios.
|
| 107 |
+
|
| 108 |
+
Reverse transcription: To obtain cDNA, total RNAs and RNase-free dH2O were added to a HiSenScript™ RH[] RT PreMix Kit (iNtRON Biotechnology, Seongnam, Korea) to 20 μL/tube. The reaction was conducted at 42°C for 30 min and 85°C for 10 min. Samples were stored at −20°C until required for further analysis.
|
| 109 |
+
|
| 110 |
+
Real-time polymerase chain reaction (PCR): After dispensing a 2 μL of cDNA into a strap tube, 6 μL of nuclease-free water, 10 μL 2X SYBR green Master mix (Applied Biosystems, Foster City, CA, USA), and 1 μL of each primer (Table 2) were added. Using Applied Biosystems StepOne software v.2.1, samples were subjected to 40 cycles of 10 min at 95°C, 15 min at 95°C, 1 min at 60°C, 15 min at 95°C, 1 min at 60°C, and 15 min at 95°C. The analysis was conducted using the ΔΔCT method.
|
| 111 |
+
|
| 112 |
+
Table 2 PCR primer sequences of transcription factors related to adipocyte differentiation and MMPs
|
| 113 |
+
|
| 114 |
+
Gene Primer Sequence1)
|
| 115 |
+
β-actin Forward primer 5′-GATATCGCTGCGCTGGTC-3′
|
| 116 |
+
Reverse primer 5′-GAGTCCTTCTGACCCATTCC-3′
|
| 117 |
+
C/EBPβ Forward primer 5′-GAGCGACGAGTACAAGATGC-3′
|
| 118 |
+
Reverse primer 5′-CTGCTCCACCTTCTTCTGC-3′
|
| 119 |
+
C/EBPα Forward primer 5′-AAGTCGGTGGACAAGAACAG-3′
|
| 120 |
+
Reverse primer 5′-GTTTGGCTTTATCTCGGCTC-3′
|
| 121 |
+
PPAR γ Forward primer 5′-CCTTTGTGGGAACCTGGAAG-3′
|
| 122 |
+
Reverse primer 5′-TACTCTCTGACCGGATGGTG-3′
|
| 123 |
+
FABP4 Forward primer 5′-TGACAGGAAAGACAACGGAC-3′
|
| 124 |
+
Reverse primer 5′-ATCGAAACTGGCACCCTTG-3′
|
| 125 |
+
MMP-2 Forward primer 5′-GGAGCATGGAGATGGATACC-3′
|
| 126 |
+
Reverse primer 5′-TACTTTACGCGGACCACTTG-3′
|
| 127 |
+
MMP-9 Forward primer 5′-TGTCATCCAGTTTGGTGTCG-3′
|
| 128 |
+
Reverse primer 5′-AAATGGGCATCTCCCTGAAC-3′
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| 129 |
+
β-actin, beta-actin (control); C/EBPβ, CCAAT/enhancer binding protein β; C/EBPα, CCAAT/enhancer binding protein α; PPARγ, peroxisome proliferator-activated receptor γ; FABP4, fatty acid binding protein 4; MMP-2, matrix metalloproteinase-2; MMP-9, matrix metalloproteinase-9.
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| 130 |
+
|
| 131 |
+
1)T, Thymine; A, Adenine; C, Cytosine; G, Guanine.
|
| 132 |
+
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| 133 |
+
mRNA expressions and concentrations of MMPs in adipose tissues
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| 134 |
+
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| 135 |
+
MMPs mRNA expression: The mRNA expressions of MMP-2 and MMP-9 were determined by reverse transcription-PCR using the conditions described above for reverse transcription. The forward and reverse primers used are shown in Table 1.
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| 136 |
+
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| 137 |
+
The concentraion of MMPs: MMP-2 and MMP-9 levels were measured using a mouse MMP-2 enzyme-linked immunosorbent assay (ELISA) kit (MBS722437; MyBioSouce, San Diego, CA, USA) and a mouse MMP-9 ELISA kit (MBS720876; MyBioSouce), respectively. Homogenized epididymal fat pads (100 mg) were mixed well with 500 μL phosphate-buffer saline (PBS) and centrifuged at 5,000 rpm for 15 min at 4°C. Supernatants were collected, and MMP-2 and MMP-9 protein levels were determined according to the manufacturer’s instructions. Absorbances were measured at 450 nm using a microplate reader (Molecular Devices).
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| 138 |
+
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| 139 |
+
The concentration of active MMPs: Active MMP-2 and MMP-9 levels were measured using the MMP-2 Biotrack activity assay system kit (RPN 2631; GE Healthcare, Chicago, IL, USA) and an MMP-9 activity assay kit (QuickZyme BioScience, Leiden, Netherlands), respectively. Homogenized epididymal fat pads (100 mg) were thoroughly mixed with 1 mL 50 mM Tris-HCl buffer and centrifuged at 10,338 rpm for 10 min at 4°C. Active MMP-2 and MMP-9 levels were determined in supernatants according to the manufacturer’s instructions by measuring absorbances at 405 nm using a microplate reader (Molecular Devices).
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| 140 |
+
|
| 141 |
+
Statistical analysis
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| 142 |
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| 143 |
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Statistical analysis was performed using SPSS version 26 software (SPSS Inc., Chicago, IL, USA). Results are presented as means ± SEs. One-way analysis of variance and Duncan’s multiple range test were used to determine the significance of intergroup differences. Statistical significance was accepted for P-values < 0.05.
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| 145 |
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RESULTS
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| 146 |
+
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Body weights, food intake, and organ weights
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| 148 |
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Mean initial mouse weights in the four groups were not significantly different. After 12 wk of feeding with the experimental diets, mean body weights were significantly different in the ND and HFD groups (P < 0.05) (Fig. 1, Table 3). Final mean body weights at 16 wk in the ND, HFD, HFQ0.05, and HFQ0.15 groups were 35.0 ± 1.6 g, 40.7 ± 0.9 g, 37.4 ± 1.2 g, and 35.9 ± 1.0 g, respectively, and body weights in the HFD and HFQ0.05 groups were significantly different (P < 0.05). Weight gains in the ND, HFQ0.05, and HFQ0.15 groups were significantly less than in the HFD group (P < 0.05) (Table 3). However, mean dietary intakes in the HFD and HFQ0.15 groups were significantly less than in the ND group, and food efficiency ratios (FER) in the ND, HFQ0.05, and HFQ0.15 groups were significantly lower than in the HFD group (P < 0.05).
|
| 150 |
+
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Fig. 1 Body weight changes in the experimental groups.
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Lines represent mean weights ± SEs of the experimental groups. Five-wk-old C57BL/6J mice (Daehan Biolink) were randomly allocated to 4 experimental groups: normal fat diet (ND); high fat diet (HFD); high fat diet + quercetin 0.05% (HFQ0.05); and high fat diet + quercetin 0.15% (HFQ0.15).
|
| 154 |
+
|
| 155 |
+
NS, no significant intergroup difference.
|
| 156 |
+
|
| 157 |
+
Different symbols above lines for each wk indicate significant intergroup differences at P < 0.05 as determined by Duncans multiple range test.
|
| 158 |
+
|
| 159 |
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Table 3 Body weights, body weight gains, dietary intakes, and FER of the experimental groups
|
| 160 |
+
|
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Group1) Initial weight (g) Final weight (g) Weight gain (g/16 wks) Diet intake (g/16 wks) FER2)
|
| 162 |
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ND 20.3 ± 0.3NS 35.0 ± 1.6b 14.6 ± 1.5b 410.1 ± 3.6a 0.04 ± 0.003b
|
| 163 |
+
HFD 20.3 ± 0.3 40.7 ± 0.9a 20.3 ± 0.7a 373.1 ± 8.3b 0.05 ± 0.003a
|
| 164 |
+
HFQ0.05 20.4 ± 0.3 37.4 ± 1.2ab 17.0 ± 1.1b 389.0 ± 13.6ab 0.04 ± 0.003b
|
| 165 |
+
HFQ0.15 20.4 ± 0.3 35.9 ± 1.0b 15.5 ± 0.9b 366.5 ± 10.2b 0.04 ± 0.002b
|
| 166 |
+
Values are presented as means ± SEs.
|
| 167 |
+
|
| 168 |
+
FER, food efficiency ratio; NS, not significant.
|
| 169 |
+
|
| 170 |
+
1)ND, normal fat diet; HFD, high fat diet; HFQ0.05, high fat diet + quercetin 0.05%; HFQ0.15, high fat diet + quercetin 0.15%.
|
| 171 |
+
|
| 172 |
+
2)FER = Body weight gains during 16 wks (g)/Dietary Intake during 16 wks (g).
|
| 173 |
+
|
| 174 |
+
Significance was determined using Duncans multiple range test (P < 0.05) (a > b).
|
| 175 |
+
|
| 176 |
+
Mean liver weights were significantly lower in the ND, HFQ0.05, and HFQ0.15 groups than in the HFD group, and mean epididymal fat pad weights were significantly lower in the ND and HFQ0.15 groups than in the HFD group (P < 0.05) (Table 4). Mean kidney, spleen, and thymus weights were not significantly different in the experimental groups.
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+
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Table 4 Mean organ weights in the experimental groups (g)
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| 179 |
+
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| 180 |
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Group1) Liver Kidney Epididymal fat pad Spleen Thymus
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ND 1.23 ± 0.05c 0.36 ± 0.01NS 1.17 ± 0.14c 0.09 ± 0.01NS 0.06 ± 0.01NS
|
| 182 |
+
HFD 2.20 ± 0.15a 0.36 ± 0.01 1.90 ± 0.11a 0.16 ± 0.05 0.05 ± 0.01
|
| 183 |
+
HFQ0.05 1.93 ± 0.10ab 0.35 ± 0.01 1.61 ± 0.12ab 0.10 ± 0.01 0.05 ± 0.00
|
| 184 |
+
HFQ0.15 1.81 ± 0.12b 0.36 ± 0.01 1.36 ± 0.18bc 0.10 ± 0.01 0.04 ± 0.01
|
| 185 |
+
Values are presented as means ± SEs.
|
| 186 |
+
|
| 187 |
+
FER, food efficiency ratio; NS, not significant.
|
| 188 |
+
|
| 189 |
+
1)ND, normal fat diet; HFD, high fat diet; HFQ0.05, high fat diet + quercetin 0.05%; HFQ0.15, high fat diet + quercetin 0.15%.
|
| 190 |
+
|
| 191 |
+
Significance was determined using Duncan's multiple range test (P < 0.05) (a > b > c).
|
| 192 |
+
|
| 193 |
+
GPDH activity assay
|
| 194 |
+
|
| 195 |
+
The effect of quercetin intake on triglyceride accumulation in epididymal fat pads was also investigated. GPDH activity was significantly lower in the ND, HFQ0.05, and HFQ0.15 groups than in the HFD group (P < 0.05) (Fig. 2).
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+
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| 197 |
+
Fig. 2 Effect of 16 weeks of quercetin administration on GPDH activity in adipose tissues.
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| 198 |
+
|
| 199 |
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Bars represent means ± SEs of the experimental groups. Five-wk-old C57BL/6J mice (Daehan Biolink) were randomly allocated to 4 experimental groups:normal fat diet (ND); high fat diet (HFD); high fat diet + quercetin 0.05% (HFQ0.05); and high fat diet + quercetin 0.15% (HFQ0.15).
|
| 200 |
+
|
| 201 |
+
GPDH, glycerol-3-phosphate dehydrogenase.
|
| 202 |
+
|
| 203 |
+
Different letters above bars indicate significant intergroup differences at P < 0.05 as determined by Duncans multiple range test.
|
| 204 |
+
|
| 205 |
+
mRNA expressions of transcription factors related to adipocyte differentiation
|
| 206 |
+
|
| 207 |
+
mRNA expressions of hepatic C/EBPβ, C/EBPα, PPARγ, and fatty acid-binding protein 4 (FABP4) were significantly lower in the ND, HFQ0.05, and HFQ0.15 groups than in the HFD group, and quercetin was found to have a concentration-dependent inhibitory effect (P < 0.05) (Fig. 3).
|
| 208 |
+
|
| 209 |
+
Fig. 3 Effects of 16 weeks of quercetin administration on the mRNA expressions of transcription factors related to adipocyte differentiation in the liver.
|
| 210 |
+
|
| 211 |
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Total RNA was isolated using TRI-Reagent, and cDNA was synthesized using SuperScript II reverse transcriptase from total RNA. Real-time PCR with SYBR Green was performed using standard procedures to assess the mRNA expressions in liver samples obtained from each group. β-Actin levels were used to ensure equal loadings. Applied Biosystems StepOne software v2.1 was used. Bars represent means ± SEs of the experimental groups. Five-wk-old C57BL/6J mice (Daehan Biolink) were randomly allocated to 4 experimental groups: normal fat diet (ND); high fat diet (HFD); high fat diet + quercetin 0.05% (HFQ0.05); and high fat diet + quercetin 0.15% (HFQ0.15).
|
| 212 |
+
|
| 213 |
+
PCR, polymerase chain reaction; C/EBPβ, CCAT/enhancer-binding protein β; C/EBPα, CCAT/enhancer-binding protein α; PPARγ, peroxisome proliferator activated receptor γ; FABP4, fatty acid binding protein 4.
|
| 214 |
+
|
| 215 |
+
Different letters above bars indicate significant intergroup differences (P < 0.05 as determined by Duncans multiple range test).
|
| 216 |
+
|
| 217 |
+
mRNA expressions and concentrations of MMPs
|
| 218 |
+
|
| 219 |
+
The mRNA expression of MMP-2 (Fig. 4A), MMP-2 concentration (Fig. 4B), and active MMP-2 concentration (Fig. 4C) in epididymal fat pads were significantly lower in the ND, HFQ0.05, and HFQ0.15 groups than in the HFD group, and quercetin had a concentration-dependent inhibitory effect (P < 0.05).
|
| 220 |
+
|
| 221 |
+
Fig. 4 Effects of 16 weeks of quercetin administration on mRNA expression, concentrations of MMP-2 in adipose tissues.
|
| 222 |
+
|
| 223 |
+
To measure the mRNA expression of MMP-2, total RNA was isolated using TRI-Reagent, and cDNA was synthesized using total RNA and SuperScript II reverse transcriptase. Real-time PCR with SYBR Green was performed using standard procedures to assess mRNA expressions in epididymal fat pad samples. (A) β-Actin levels were used to ensure equal loadings. Applied Biosystems StepOne software v2.1 was used. (B) MMP-2 protein levels were measured using the MMP-2 ELISA kit (MBS722437, MyBioSouce. (C) MMP-2 activity was measured using the MMP-2 Biotrack activity assay system kit (RPN 2631; GE Healthcare. Bars represent means ± SEs of the experimental groups. Five-wk-old C57BL/6J mice (Daehan Biolink) were randomly allocated to 4 experimental groups: normal fat diet (ND); high fat diet (HFD); high fat diet + quercetin 0.05% (HFQ0.05); and high fat diet + quercetin 0.15% (HFQ0.15).
|
| 224 |
+
|
| 225 |
+
MMP, matrix metalloproteinase.
|
| 226 |
+
|
| 227 |
+
Different letters above bars indicate significant intergroup differences (P < 0.05 as determined by Duncans multiple range test).
|
| 228 |
+
|
| 229 |
+
The mRNA expressions (Fig. 5A) and active MMP-9 concentration (Fig. 5C) in epididymal fat pads were significantly lower in the ND, HFQ0.05, and HFQ0.15 groups than in the HFD group, and quercetin had a concentration-dependent inhibitory effect (P < 0.05). MMP-9 levels (Fig. 5B) in epididymal fat pads were significantly lower in the ND and HFQ0.15 groups than in the HFD group (P < 0.05).
|
| 230 |
+
|
| 231 |
+
Fig. 5 Effects of 16 weeks of quercetin administration on the mRNA expression, concentrations of MMP-9 in adipose tissues.
|
| 232 |
+
|
| 233 |
+
To measure the mRNA expression of MMP-9, total RNA was isolated using TRI-Reagent, and cDNA was synthesized using total RNA with SuperScript II reverse transcriptase. Real-time PCR with SYBR Green was performed using standard procedures to determine mRNA expressions in epididymal fat pad samples. (A) β-Actin levels were used to ensure equal loadings. Applied Biosystems StepOne software v2.1 was used. (B) MMP-9 levels were measured using the MMP-9 ELISA kit (MBS720876, MyBioSource, and (C) MMP-9 activities were measured using an MMP-9 activity assay kit (QuickZyme BioScience). Bars represent means ± SEs of the experimental groups. Five-wk-old C57BL/6J mice (Daehan Biolink) were randomly allocated to 4 experimental groups: normal fat diet (ND); high fat diet (HFD); high fat diet + quercetin 0.05% (HFQ0.05); and high fat diet + quercetin 0.15% (HFQ0.15).
|
| 234 |
+
|
| 235 |
+
MMP, matrix metalloproteinase; PCR, polymerase chain reaction; ELISA, enzyme-linked immunosorbent assay.
|
| 236 |
+
|
| 237 |
+
Different letters above bars indicate significant intergroup differences at P < 0.05 as determined by Duncans multiple range tests.
|
| 238 |
+
|
| 239 |
+
DISCUSSION
|
| 240 |
+
|
| 241 |
+
Adipose tissue is highly vascularized, and each adipocyte is nourished by an extensive capillary network, and thus the growth and differentiation of adipocytes are angiogenesis-dependent [5]. During angiogenesis, secreted MMPs degrade ECM components [6] and breach the ECM barrier to promote angiogenesis-related processes such as vascular cell migration to surrounding tissues and the release of angiogenic factors [7]. Therefore, we undertook this in vivo study to determine whether quercetin inhibits adipose tissue differentiation and growth by inhibiting MMPs, which are required for angiogenesis, in an HFD-induced mouse obesity model.
|
| 242 |
+
|
| 243 |
+
Quercetin is a flavonoid with excellent antioxidant activity and is widely distributed in fruits and vegetables. In a previous study, oral administration of quercetin to rats at 500 mg/kg/day did not cause DNA damage in the stomach or liver tissues and did not induce any toxicity-associated side effects [20]. In the present study, mice were fed 0.05% or 0.15% quercetin in the HFD (46% fat) for 16 wks, and at the end of the experimental period, the mean final body weight was found to be significantly higher in the HFD group than in the ND or HFQ0.15 groups (P < 0.05). Mean weight gain was up to 39% higher in the HFD group than in the ND group and significantly higher than in the HFQ0.05 and HFQ0.15 groups (by 16.3% and 23.6%, respectively; P < 0.05). Notably, mean dietary intake was significantly lower, but weight gain was greater (P < 0.05) in the HFD group than in the ND group. In the HFD group, 46.6% of dietary energy was provided as fat, whereas in the ND group, only 16.0% of dietary energy was provided as fat.
|
| 244 |
+
|
| 245 |
+
In several animal experiments [2122232425], quercetin intake resulted in weight loss, which is consistent with our results. Moon et al. [21] reported that when onion peel extract (OPE) containing quercetin at a concentration of 276 mg/g was added to HFD at 0.36% or 0.72% (by weight) and fed to 5-wk-old Sprague Dawley rats, mean final weight was significantly lower in the control group and the OPE intake group than in the HFD group. Furthermore, dietary intake was significantly higher in the control group than in the HFD group, but dietary efficiency was significantly higher in the HFD group than in the other groups, which again is consistent with the results of our study. Porras et al. [22] found that when 7-wk-old C57BL/6J mice were provided a HFD containing 0.05% quercetin aglycone, mean body weight was significantly lower in the quercetin group than in the HFD group. Jia et al. [23] also reported that when 12-wk-old apoE C57BL/6 mice with a HFD were administered 12.5 mg/kg of quercetin in water, the mean body weight was lower than that of mice in their HFD group. Lee et al. [24] reported that when quercetin was administered at 50 mg/day orally for 12 wk to 72 Korean overweight adult men and women (body mass index [BMI] > 23 kg/m2), mean body weights, BMI, skin thicknesses, and waist, hip, and thigh circumferences were significantly decreased. The above studies and the results of this study suggest that quercetin effectively reduces body weight in experimental animals and humans. In the present study, liver and epididymal fat weights were not significantly lower in the HFQ0.05 group than in the HFD group but were significantly lower in the HFQ0.15 group (P < 0.05). Jung et al. [25] reported body weight reductions in C57B1/6 mice fed 0.025% or 0.05% quercetin in a HFD, and Porras et al. [22] reported quercetin significantly reduced liver and epididymal adipose tissue weight as compared with HFD fed rat. These results are entirely consistent with the observations made during the current study.
|
| 246 |
+
|
| 247 |
+
In this study, GPDH activity was significantly higher in the HFD group than in the ND group, and quercetin intake lowered GPDH activity as compared with the HFD group, which suggests quercetin inhibited HFD-induced triglyceride (TG) and epididymal fat weight increases (P < 0.05). GPDH activation increases triglyceride production by converting dihydroxyacetone phosphate to glycerol-3-phosphate, whereas its inhibition reduces lipid accumulation in mature adipocytes [26].
|
| 248 |
+
|
| 249 |
+
We found the mRNA expressions of all transcription factors related to adipocyte differentiation in the liver examined (C/EBPβ, C/EBPα, PPARγ, and FABP4) were more than three times higher in the HFD group than in the ND group, and quercetin administration lowered their levels dose-dependently (P < 0.05). Adipocytes differentiate from preadipocytes under the influence of transcription factors that promote adipogenesis. C/EBPβ is a transcription factor expressed during the early stages of adipogenesis and adipogenesis and promotes preadipocyte differentiation by inducing the expressions of PPARγ and C/EBPα, which affect late differentiation [272829]. In addition, PPARγ induces the expression of FABP4 [30], a widely used marker of differentiated adipocytes essential for maintaining glucose and lipid metabolisms [31]. Jung et al. [25] found that when C57BL/6J mice were fed a diet containing 0.025% of quercetin in an HFD, the expression of PPARγ mRNA in liver tissue was significantly reduced, and Porras et al. [22] reported that when C57BL/6J mice were fed a diet containing 0.05% quercetin aglycone in an HFD, the mRNA expression of C/EBPα in liver tissues was significantly reduced as compared with those in the HFD group, which is consistent with our results. This observation shows that quercetin significantly inhibited the expressions of transcription factors involved in preadipocyte differentiation from the early to late stages, which is in line with observed reductions in adipose tissue weight.
|
| 250 |
+
|
| 251 |
+
In this study, the concentration and mRNA expressions of MMP-2 and MMP-9 were increased by the HFD diet, but quercetin administration with a HFD suppressed MMP-2 and MMP-9 concentration and mRNA expressions. These results suggest that quercetin-induced reductions in body weight and adipose tissue weights are driven by inhibition of MMP-2 and MMP-9, which have essential roles in angiogenesis.
|
| 252 |
+
|
| 253 |
+
Angiogenesis often precedes adipogenesis in developing adipose tissue, and it indicates the requirement of blood vessels for tissue formation and remodeling of ECM, in which MMP-2 and MMP-9 are mainly involved, is essential for both angiogenesis and adipogenesis. Several studies confirmed that blocking the transcription factors related to adipocyte differentiation, such as C/EBPs and PPARγ, pathway in preadipocytes inhibited not only their differentiation into adipocytes but also angiogenetic factors [345]. Among the angiogenic factors, especially MMP-2 and MMP-9 were highly expressed in adipose tissue, and their expression increased significantly during adipocyte differentiation [6].
|
| 254 |
+
|
| 255 |
+
Several studies have also reported that the inhibition of MMPs reduces adipose tissue expansion and that treatment with MMP inhibitors blocks adipogenesis [32333435]. Bouloumié et al. [32] reported that human adipocytes secrete MMP-2 and MMP-9, and Bauters et al. [33] showed that knockdown of the MMP-2 gene in 3T3-F442A preadipocytes reduced their differentiation and that preadipocyte to adipocyte differentiation was promoted when MMP-2 was overexpressed. In two rat studies, HFD activated the mRNA expressions of MMP-2 in epididymal adipose tissue [34], and the treatment of obese male rats fed HFD containing lemon balm (Melissa officinalis) reduced the gene expressions of vascular endothelial growth factor A and fibroblast growth factor-2 (angiogenesis promoters in adipose tissue), the mRNA expressions of MMP-2 and MMP-9, and blood vessel densities in adipose tissues, adipose tissue weights, and bodyweights [35]. The above studies suggest that adipogenesis is suppressed by the inhibition of angiogenesis.
|
| 256 |
+
|
| 257 |
+
Although understanding the relationship between adipocyte differentiation and neovascularization in adipose tissue growth is essential, study regarding the effect of quercetin on adipogenesis and MMPs is limited to in vitro cell studies [1718]. Hong et al. [17] reported that quercetin inhibited transcription factors related to adipocyte differentiation and mRNA expression of MMP-2 and MMP-9 in 3T3-L1 cells. Song et al. [18] reported that after MMPs were activated by phorbol 12-myristate 13-acetate in 3T3-L1 cells, quercetin-treatment dose-dependently suppressed both mRNA expressions of transcription factors related to adipocyte differentiation and MMP-9 mRNA levels.
|
| 258 |
+
|
| 259 |
+
Similar to the above studies, the results of this animal study also confirmed the intake of quercetin along with a HFD resulted in decreased body weight, adipose tissue, mRNA expressions of transcription factors related to adipocyte differentiation (C/EBPβ, C/EBPα, PPARγ, FABP4) and MMPs (MMP-2 and MMP-9). In summary, the present study shows that quercetin suppresses HFD-induced weight gain and fat accumulation in adipose tissues in mice by inhibiting adipogenesis and MMPs.
|
| 260 |
+
|
| 261 |
+
Funding: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2018R1D1A1B07043918).
|
| 262 |
+
|
| 263 |
+
Conflict of Interest: The authors declare no potential conflicts of interests.
|
| 264 |
+
|
| 265 |
+
Author Contributions: Conceptualization: Kim W.
|
| 266 |
+
|
| 267 |
+
Data curation: Song S, Kim W.
|
| 268 |
+
|
| 269 |
+
Formal analysis: Song S, Kim W.
|
| 270 |
+
|
| 271 |
+
Funding acquisition: Kim W.
|
| 272 |
+
|
| 273 |
+
Methodology: Song S, Kim W.
|
| 274 |
+
|
| 275 |
+
Project administration: Song S, Ha AW, Kim W.
|
| 276 |
+
|
| 277 |
+
Validation: Ha AW, Kim W.
|
| 278 |
+
|
| 279 |
+
Visualization: Ha AW, Kim W.
|
| 280 |
+
|
| 281 |
+
Writing - original draft: Song S, Ha AW, Kim W.
|
| 282 |
+
|
| 283 |
+
Writing - review & editing: Ha AW, Kim W, Song S.
|
| 284 |
+
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20 Park BS Han SH Lee JY Chung YS Evaluation of in vivo genotoxicity of plant flavonoids, quercetin and isoquercetin J Food Hyg Saf 2016 31 356 364
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| 305 |
+
21 Moon J Do HJ Kim OY Shin MJ Antiobesity effects of quercetin-rich onion peel extract on the differentiation of 3T3-L1 preadipocytes and the adipogenesis in high fat-fed rats Food Chem Toxicol 2013 58 347 354 23684756
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| 306 |
+
22 Porras D Nistal E Martínez-Flórez S Pisonero-Vaquero S Olcoz JL Jover R González-Gallego J García-Mediavilla MV Sánchez-Campos S Protective effect of quercetin on high-fat diet-induced non-alcoholic fatty liver disease in mice is mediated by modulating intestinal microbiota imbalance and related gut-liver axis activation Free Radic Biol Med 2017 102 188 202 27890642
|
| 307 |
+
23 Jia Q Cao H Shen D Li S Yan L Chen C Xing S Dou F Quercetin protects against atherosclerosis by regulating the expression of PCSK9, CD36, PPARγ, LXRα and ABCA1 Int J Mol Med 2019 44 893 902 31524223
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| 308 |
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24 Lee JS Cha YJ Lee KH Yim JE Onion peel extract reduces the percentage of body fat in overweight and obese subjects: a 12-week, randomized, double-blind, placebo-controlled study Nutr Res Pract 2016 10 175 181 27087901
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| 309 |
+
25 Jung CH Cho I Ahn J Jeon TI Ha TY Quercetin reduces high-fat diet-induced fat accumulation in the liver by regulating lipid metabolism genes Phytother Res 2013 27 139 143 22447684
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| 310 |
+
26 Bae CR Park YK Cha YS Quercetin-rich onion peel extract suppresses adipogenesis by down-regulating adipogenic transcription factors and gene expression in 3T3-L1 adipocytes J Sci Food Agric 2014 94 2655 2660 24634340
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| 311 |
+
27 Zhao X Hu H Wang C Bai L Wang Y Wang W Wang J A comparison of methods for effective differentiation of the frozen-thawed 3T3-L1 cells Anal Biochem 2019 568 57 64 30594506
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28 Boughanem H Cabrera-Mulero A Millán-Gómez M Garrido-Sánchez L Cardona F Tinahones FJ Moreno-Santos I Macías-González M Transcriptional analysis of FOXO1, C/EBP-α and PPAR-γ2 genes and their association with obesity-related insulin resistance Genes (Basel) 2019 10 706 31547433
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| 313 |
+
29 Moseti D Regassa A Kim WK Molecular regulation of adipogenesis and potential anti-adipogenic bioactive molecules Int J Mol Sci 2016 17 124 26797605
|
| 314 |
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30 Cristancho AG Lazar MA Forming functional fat: a growing understanding of adipocyte differentiation Nat Rev Mol Cell Biol 2011 12 722 734 21952300
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31 Zhang R Qin X Zhang T Li Q Zhang J Zhao J Astragalus polysaccharide improves insulin sensitivity via AMPK activation in 3T3-L1 adipocytes Molecules 2018 23 2711 30347867
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32 Bouloumié A Sengenès C Portolan G Galitzky J Lafontan M Adipocyte produces matrix metalloproteinases 2 and 9: involvement in adipose differentiation Diabetes 2001 50 2080 2086 11522674
|
| 317 |
+
33 Bauters D Scroyen I Van Hul M Lijnen HR Gelatinase A (MMP-2) promotes murine adipogenesis Biochim Biophys Acta 2015 1850 1449 1456 25869489
|
| 318 |
+
34 Bosco DB Roycik MD Jin Y Schwartz MA Lively TJ Zorio DA Sang QA A new synthetic matrix metalloproteinase inhibitor reduces human mesenchymal stem cell adipogenesis PLoS One 2017 12 e0172925 28234995
|
| 319 |
+
35 Park BY Lee H Woo S Yoon M Kim J Hong Y Lee HS Park EK Hahm JC Kim JW Reduction of adipose tissue mass by the angiogenesis inhibitor ALS-L1023 from melissa officinalis PLoS One 2015 10 e0141612 26599360
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| 320 |
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|
puc/PMC10232613.txt
ADDED
|
@@ -0,0 +1,65 @@
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
J Artif Organs
|
| 4 |
+
J Artif Organs
|
| 5 |
+
Journal of Artificial Organs
|
| 6 |
+
1434-7229
|
| 7 |
+
1619-0904
|
| 8 |
+
Springer Nature Singapore Singapore
|
| 9 |
+
|
| 10 |
+
36477434
|
| 11 |
+
1374
|
| 12 |
+
10.1007/s10047-022-01374-9
|
| 13 |
+
Correction
|
| 14 |
+
Correction: Preliminary report of de novo adipogenesis using novel bioabsorbable implants and image evaluation using a porcine model
|
| 15 |
+
http://orcid.org/0000-0003-1063-5272
|
| 16 |
+
Ogino Shuichi sogino12@belle.shiga-med.ac.jp
|
| 17 |
+
|
| 18 |
+
1
|
| 19 |
+
Yamada Atsushi 2
|
| 20 |
+
Kambe Yusuke 3
|
| 21 |
+
Nakano Takashi 4
|
| 22 |
+
Lee Sunghee 4
|
| 23 |
+
Sakamoto Michiharu 4
|
| 24 |
+
Kato Yuki 5
|
| 25 |
+
Okumura Saki 5
|
| 26 |
+
Okano Junko 1
|
| 27 |
+
Yamauchi Koji 5
|
| 28 |
+
Suzuki Yoshihisa 1
|
| 29 |
+
Yamaoka Tetsuji 3
|
| 30 |
+
Morimoto Naoki 4
|
| 31 |
+
1 grid.410827.8 0000 0000 9747 6806 Department of Plastic and Reconstructive Surgery, Shiga University of Medical Science, Seta Tsukinowa-Cho, Otsu, Shiga 520-2192 Japan
|
| 32 |
+
2 grid.410827.8 0000 0000 9747 6806 Department of Research and Development for Innovative Medical Devices and Systems, Shiga University of Medical Science, Seta Tsukinowa-Cho, Otsu, Shiga 520-2192 Japan
|
| 33 |
+
3 grid.410796.d 0000 0004 0378 8307 Department of Biomedical Engineering, National Cerebral and Cardiovascular Center Research Institute, 6-1 Kishibe-shimmachi, Suita, Osaka 564-8565 Japan
|
| 34 |
+
4 grid.258799.8 0000 0004 0372 2033 Department of Plastic and Reconstructive Surgery, Graduate School of Medicine, Kyoto University, 54 Shogoin, Kawahara-cho, Sakyou-ku, Kyoto, 606-8507 Japan
|
| 35 |
+
5 Gunze QOL Research Center Laboratory, 1 Zeze, Aono-cho, Ayabe, Kyoto 623-0051 Japan
|
| 36 |
+
7 12 2022
|
| 37 |
+
7 12 2022
|
| 38 |
+
2023
|
| 39 |
+
26 2 168169
|
| 40 |
+
© The Author(s) 2022
|
| 41 |
+
https://creativecommons.org/licenses/by/4.0/ Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
|
| 42 |
+
issue-copyright-statement© The Japanese Society for Artificial Organs 2023
|
| 43 |
+
==== Body
|
| 44 |
+
pmcCorrection: Journal of Artificial Organs (2022) 25:245–253 10.1007/s10047-022-01313-8
|
| 45 |
+
|
| 46 |
+
In the article titled “Preliminary report of de novo adipogenesis using novel bioabsorbable implants and image evaluation using a porcine model,” (Ogino et al., 2022) the authors found erroneous descriptions of magnetic resonance images. They should be described as in this erratum.In the Materials and methods section, the third sentence of the MRI procedure subsection should have been written as follows.
|
| 47 |
+
|
| 48 |
+
The images were scanned in the transverse plane using 3D T1-weighted gradient-echo 2-point Dixon imaging (TR/TE = 5.26/2.46 ms; flip angle = 10°; acquisition matrix = 352 × 172; field of view (FOV) = 285 × 350 mm2; slice thickness = 1.0 mm). In addition, to acquire each TE image, this Dixon imaging method additionally calculated fat-only and water-only images.
|
| 49 |
+
|
| 50 |
+
In the Results section, the second and third sentences of the MRI findings subsection should have been as follows.
|
| 51 |
+
|
| 52 |
+
In the fat-only images, the normal adipose tissue and the implant aggregate were able to be distinguished at all time points. The newly formed adipose tissue was identified as a high-intensity lesion in the fat-only images and a low-intensity lesion in the water-only images.
|
| 53 |
+
|
| 54 |
+
Figure 4 should have been as follows.
|
| 55 |
+
|
| 56 |
+
4. The fourth sentence of the figure legend for Figure 4 should have read as follows.
|
| 57 |
+
|
| 58 |
+
The newly formed adipose tissue was identified as hyperintense in the Dixon fat-only images and as hypointense in the Dixon water-only images at 1, 3, and 6 months after implantation.
|
| 59 |
+
|
| 60 |
+
The authors apologize for these mistakes and any inconvenience they may have caused.
|
| 61 |
+
|
| 62 |
+
Publisher's Note
|
| 63 |
+
|
| 64 |
+
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
|
| 65 |
+
|
puc/PMC10252591.txt
ADDED
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@@ -0,0 +1,277 @@
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|
| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Foods
|
| 4 |
+
Foods
|
| 5 |
+
foods
|
| 6 |
+
Foods
|
| 7 |
+
2304-8158
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
10.3390/foods12112202
|
| 11 |
+
foods-12-02202
|
| 12 |
+
Article
|
| 13 |
+
Anti-Obesity Effects of SPY Fermented with Lactobacillus rhamnosus BST-L.601 via Suppression of Adipogenesis and Lipogenesis in High-Fat Diet-Induced Obese Mice
|
| 14 |
+
Kang Taewook Conceptualization Methodology Formal analysis Investigation Resources Writing – original draft 12
|
| 15 |
+
Ree Jin Validation Formal analysis Investigation Data curation Writing – review & editing Visualization 12
|
| 16 |
+
Park Joo-Woong Conceptualization Validation Investigation Resources Supervision 2
|
| 17 |
+
Choe Hyewon Methodology Formal analysis Data curation 23
|
| 18 |
+
https://orcid.org/0000-0002-1749-0689
|
| 19 |
+
Park Yong Il Conceptualization Writing – review & editing Supervision Funding acquisition 1*
|
| 20 |
+
Yue Xiqing Academic Editor
|
| 21 |
+
Moreno Diego A. Academic Editor
|
| 22 |
+
1 Department of Biotechnology, Graduate School, The Catholic University of Korea, Bucheon 14662, Republic of Korea; twkang@biostream.co.kr (T.K.); jree@biostream.co.kr (J.R.)
|
| 23 |
+
2 Biostream Co., Ltd., Suwon 10442, Republic of Korea; pjwrnds@biostream.co.kr (J.-W.P.); hwchoe@biostream.co.kr (H.C.)
|
| 24 |
+
3 Graduate School of Genetics and Biotechnology, Kyung Hee University, Yongin 17104, Republic of Korea
|
| 25 |
+
* Correspondence: yongil382@catholic.ac.kr; Tel.: +82-2-2164-4512; Fax: +82-2-2164-4846
|
| 26 |
+
30 5 2023
|
| 27 |
+
6 2023
|
| 28 |
+
12 11 220217 4 2023
|
| 29 |
+
19 5 2023
|
| 30 |
+
27 5 2023
|
| 31 |
+
© 2023 by the authors.
|
| 32 |
+
2023
|
| 33 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 34 |
+
In this research, the potential anti-obesity efficacy of Lactobacillus rhamnosus BST-L.601 and its fermented product (named SPY) with mashed sweet potato paste were investigated using 3T3-L1 preadipocytes and high-fat diet (HD)-induced obese mice. SPY (0–0.5 mg/mL) dose-dependently and significantly reduced lipid accumulation and TG content and the expression of adipogenic markers (C/EBPα, PPAR-γ, and aP2) and fatty acid synthetic pathway proteins (ACC and FAS) in 3T3-L1 adipocytes, demonstrating that SPY suppresses adipocyte differentiation and lipogenesis. Oral administration of SPY (4 × 107 CFU/kg body weight) to HD-induced obese mice for 12 weeks significantly reduced the body and liver weight, the size of adipocytes, and the weight of epididymal, visceral, and subcutaneous fat tissues. SPY was more effective in decreasing body weight gain in HD mice than in treatment with BST-L.601 alone. Administration of SPY or BST-L.601 also reduced the serum level of total cholesterol and LDL cholesterol and leptin secretion at a similar level. These results revealed that both SPY and BST-L.601 effectively suppress HD-induced adipogenesis and lipogenesis, suggesting that these materials would be useful in the functional foods industry to ameliorate and/or prevent obesity.
|
| 35 |
+
|
| 36 |
+
Lactobacillus rhamnosus
|
| 37 |
+
probiotics
|
| 38 |
+
prebiotics
|
| 39 |
+
fermented sweet potato
|
| 40 |
+
anti-obesity
|
| 41 |
+
Biostream Technologies Co., Ltd.,M-2019-D0321-00001 Research Fund, 2020 of The Catholic University of KoreaThis research was funded by Biostream Technologies Co., Ltd., grant number M-2019-D0321-00001, and supported by the Research Fund, 2020 of The Catholic University of Korea.
|
| 42 |
+
==== Body
|
| 43 |
+
pmc1. Introduction
|
| 44 |
+
|
| 45 |
+
Obesity, one of the major metabolic diseases, is being magnified as a worldwide health problem related to various fatal diseases such as cardiac dysfunction, diabetes, hypertension, osteoarthritis, and cancer [1]. Recently, the incidence rate of obesity has rapidly increased, as reported by the OECD in 2017. Moreover, a serious problem with this situation is childhood obesity, with an estimated 15.5% of OECD infants being obese [2]. Obesity is defined as an abnormal accumulation of body fat, resulting in excessive expansion and growth of adipose tissue due to an imbalance between energy intake and expenditure [3]. The development of obesity is defined by an increased adipose tissue mass that can be driven by either an unusually larger number or expanded fat cells (adipocytes) [4]. The expanded size of adipocytes (hypertrophy) is predominantly attributed to the accumulation of lipids (lipogenesis), and the increased cell number of adipocytes (hyperplasia) leads to the proliferation and differentiation of adipocyte precursor cells to mature adipocytes, which is a cellular process called adipogenesis [4]. Therefore, the mass of adipose tissue can be controlled by inhibiting adipogenesis, reducing the accumulation of lipids, improving lipolysis, and/or guiding the apoptotic death of adipose cells [5]. During the differentiation of adipocytes, several adipogenic transcription factors such as sterol regulatory element-binding protein-1c (SREBP-1c), peroxisome proliferator-activator receptor-γ (PPAR-γ), and CCAAT/enhancer binding protein-α (C/EBPα), are essential regulators of adipogenesis. The expression of C/EBPα, PPAR-γ, and several lipogenic enzymes, including fatty acid synthase (FAS) and acetyl-CoA carboxylase (ACC), is stimulated by SREBP-1c products [4,6]. Activation of lipogenic enzymes converts acetyl-CoA to fatty acids and triglycerides and induces tissue uptake into plasma [7].
|
| 46 |
+
|
| 47 |
+
To solve the obesity issue, studies on how to change the intestinal microbiome composition with probiotics such as Lactobacillus have been conducted in recent decades [8]. These results suggested that when the composition of the intestinal microbiome is changed, intestinal microorganisms (mainly lactic acid bacteria, LAB) influence energy consumption and lipid accumulation; thus, microorganisms of human intestines are useful for obesity control [9]. It was also reported that the composition of the intestinal microbial community was adjusted through oral administration of probiotics to induce obesity suppression, and the ingestion of LAB caused a change in the human intestinal microbial community, especially Lactobacillus species, for a long period of time, which could be different from obese people [10]. Probiotic strains, especially Lactobacillus genera, have proven anti-obesity effects by reducing fat mass and body weight [11]. The anti-obesity efficacy of probiotics can be demonstrated by increasing satiety and lowering insulin resistance [12]. As it has been recently suggested that intestinal microbes could cause obesity, the anti-obesity effect of controlling intestinal microbes through probiotics is being studied [13]. These mechanisms include modifying the composition of the gut microflora, improving barrier integrity in the intestine, producing beneficial metabolites, and regulating the host immune system [14].
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Meanwhile, studies on obesity suppression using prebiotics along with probiotics have been conducted [15]. Prebiotics are indigestible, fermentable raw materials that can promote the proliferation of beneficial gut bacteria, or they are “A substrate that is selectively utilized by host microorganisms conferring a health benefit”, as suggested by the International Scientific Association for Probiotics and Prebiotics [16]. Nondigestible polysaccharides, such as inulin, galacto-oligosaccharides (GOS), fructo-oligosaccharides (FOS), lactulose, and resistant starch (RS), are recognized as prebiotics [17]. Prebiotics suppresses the proliferation of harmful bacteria and encourages the growth of healthful bacteria, such as Lactobacilli, to promote the production of short-chain fatty acids (SCFAs) such as acetate, butyrate, and propionate [18]. Among others, resistant starch is one of the fractions thoroughly or partly fermented in the large intestine but cannot be digested in the small intestine of robust people. Suppressing the glycemic response, working as healthy probiotics, lowering cholesterol levels, and boosting the generation of SCFAs in the large intestine is reported as a function of resistant starch [19]. Sweet potato is a good and appropriate resource for the supplement of resistant starch [20]. It was demonstrated that the anti-obesity effects of the gut microbiome are related to lactic acid bacteria [21], and the dietary fiber of sweet potato helps the gut microflora profile in a healthy way [22]. Indeed, the possible correlation between probiotics and obesity has been studied by several researchers, suggesting that a particular phylum or probiotic species can regulate energy metabolism [23]. Lactobacillus is known to induce the degradation (fermentation) of indigestible complex polysaccharides and to promote the efficiency of metabolism in our body. In previous studies, models based on these features proved that these two LAB have remarkable anti-obesity effects [24]. Among LAB, Lactobacillus rhamnosus is a strain of Lactobacillus species that are regarded as GRAS strains (generally regarded as safe). In this context, it would be quite probable to obtain a synergistic outcome with enhanced biological activities, such as anti-obesity activity, of Lactobacillus probiotics by using sweet potato as a source of prebiotics simultaneously [25].
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To address this hypothesis and to develop a new or better probiotic and/or probiotic-prebiotic combined composition for healthy functional food ingredient or a remedial agent to treat or prevent obesity, The purpose of this study is to compare and make an evaluation of the potential anti-obesity effects of a newly isolated probiotic strain, Lactobacillus rhamnosus BST-L.601 (deposited in KCTC under accession number KCTC13517BP), and the fermented product (named SPY) of mashed sweet potato paste (MSPP) with this strain, using 3T3-L1 preadipocyte cells and a high-fat diet (HD)-induced obese C57BL/6 mouse model.
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2. Materials and Methods
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2.1. Materials
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Dulbecco’s modified Eagle’s medium (DMEM), fetal bovine serum (FBS), and Dulbecco’s phosphate-buffered saline (DPBS) were purchased from Welgene (Gyeongsan, Republic of Korea). Trypsin-ethylenediaminetetraacetic acid (EDTA) and penicillin and streptomycin were purchased from Gibco-BRL (Grand Island, NY, USA). Isobutylmethylxanthine (IBMX), dexamethasone, insulin, Oil red O, and dimethyl sulfoxide (DMSO) were purchased from Sigma-Aldrich (St. Louis, MO, USA). The murine 3T3-L1 preadipocyte cell line (ATCC® CL-173™) was provided by the American Type Culture Collection (Manassas, VA, USA). 3-(4,5-Dimethylthiazolyl)-diphenyl tetrazoliumbromide (MTT) was obtained from DUCHEPA Biochemie (Haarlem, The Netherlands). Antibodies specific to β-actin, CCAAT/enhancer binding protein-α (C/EBPα), peroxisome proliferator-activated receptor-γ (PPAR-γ), adipocyte protein 2 (aP2), fatty acid synthase (FAS), acetyl-CoA carboxylase (ACC) and anti-rabbit IgG-HRP were purchased from Cell Signaling Technology (Danvers, MA, USA). Primers specific to β-actin, PPAR-γ, aP2, FAS, and ACC were purchased from Cosmo Genetech (Seoul, Republic of Korea).
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2.2. Preparation of Lactobacillus rhamnosus BST-L.601 and Mashed Sweet Potato Medium
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Lactobacillus rhamnosus BST-L.601 was isolated and identified from the stool of 20 randomly selected Korean people. Human stools were dissolved in germ-free PBS (pH 7.4) with a decimal method, inoculated into De Man, Rogosa, and Sharpe (MRS) agar broth (Becton-Dickinson, Franklin Lakes, NJ, USA), and cultured at 37 °C under anaerobic conditions for 24 to 48 h. After cultivation, the largest colonies were selected, inoculated into MRS broth medium, and cultured at 37 °C under anaerobic and static conditions for 24 to 48 h. From the culture broth showing confluent growth with over 1.0 absorbance at 600 nm, strains were selected and inoculated into skim milk medium (Becton-Dickinson, Franklin Lakes, NJ, USA). The strains showing smooth curd formation were selected and smeared again onto the skim milk agar medium. Finally, a single strain was isolated from a single largest colony. This strain was identified as a strain of L. rhamnosus by analyzing the 16S rRNA sequence and deposited in KCTC under accession number KCTC 13517 BP (Korea Patent No. 10-2020-0012236).
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A fermented sample (SPY) was prepared by fermentation of mashed sweet potato paste (MSPP) with L. rhamnosus BST-L.601. Sweet potato paste was prepared using domestic sweet potato cultivated and collected in Kangwon Province, Republic of Korea. After washing the sweet potatoes, the skin of the sweet potatoes was removed, cut randomly into smaller chips, and finely ground with equal amounts (by weight) of water using a grinder (HR3752/00, Philips, The Netherlands) to make the mashed sweet potato paste (MSPP). Yeast extract (20 g/L, Becton-Dickinson, Franklin Lakes, NJ, USA) was blended with MSPP, and the mixture was finely ground at 10,000 rpm for 10 min using a homogenizer (Daihan Scientific, Wonju, Republic of Korea). The pH of MSPP was adjusted from 6.5 to 8.0 using 1 M HCl before sterilization (15 min, 121 °C), and 40 g/L glucose solution was fortified to the paste after sterilization. L. rhamnosus BST-L.601 (1 × 106) CFU was inoculated into sweet potato paste with 40 g/L glucose solution to 10% (v/v) and fermented at 37 °C for 3 days. Additional fermentation was performed at 4 °C for 3 additional days after the first fermentation.
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2.3. Cell Culture and Differentiation of Pre-Adipocytes
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Murine 3T3-L1 preadipocyte cells (ATCC® CL173) were cultured in preadipocyte medium [PM; a mixture of Dulbecco’s modified Eagle medium (DMEM) added with 10% fetal bovine serum (FBS)] and a 1% penicillin–streptomycin mixture at 37 °C in a humidified atmosphere of 5% CO2 until reaching approximately 90% confluence. Unless stated otherwise, preadipocytes were seeded onto 6-well plates at a density of 24,000 cells/well and cultured until 80% confluence was reached. The differentiation of 3T3-L1 preadipocyte cells into mature adipocytes was achieved by culturing cells in differentiation media I [DMEM, 10% FBS, 1 mM dexamethasone, 0.5 mM 3-isobutyl-1-methylxanthine (IBMX), and 10 μg/mL insulin] and differentiation media II [DMEM, 10% fetal bovine serum (FBS), and 10 μg/mL insulin] for 48 h. After that, adipocytes were cultured in DMEM with 10% FBS for original growth and subcultured every 48 h until use.
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2.4. Cell Viability Determination
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Whether L. rhamnosus BST-L.601 and SPY are toxic to 3T3-L1 preadipocyte cells and differentiated mature adipocyte cells was assessed by measuring cell viability using an MTT assay. Cells were exposed to increasing concentrations of each sample (L.601 or SPY). 3T3-L1 preadipocytes (4000 cells/well) were cultured in 96-well plates with SPY at various concentrations (0.05, 0.1, 0.25, and 0.5 mg/mL) dissolved in PM culture medium at 37 °C in a humidified atmosphere of 5% CO2 for 48 h. Cell viability was determined by the addition of 50 mL MTT solution (1 mg/mL in phosphate-buffered saline; PBS) to each well and incubation at 37 °C for 4 h. After the culture medium is removed, DMSO was added to each well and incubated at room temperature for 30 min. Absorbance was measured at 570 nm on a microplate reader (Molecular Devices, Seoul, Republic of Korea).
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2.5. Oil Red O Staining
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To examine the effect of SPY on differentiation and lipogenesis, cells were cultured in MDI differentiation medium in 6-well plates, treated with SPY for 8 days, and stained with Oil red O dye. After incubation, cells were washed gently with PBS, fixed with 4% paraformaldehyde for 30 min at room temperature, rinsed with PBS, and then stained with freshly prepared 0.5% (w/v) Oil red O solution at 37 °C for 1 h. The stained cells were photographed using an inverted microscope (X100, Olympus, Tokyo, Japan) to visualize lipid droplets. To determine the lipid content, the retained dye in adipocytes was extracted with 100% isopropanol and quantified at 517 nm using a microplate reader. Compared to the control, the relative lipid content of each sample was expressed.
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+
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The intracellular TG contents were verified by a Cayman Chemical Triglyceride Assay kit (Ann Arbor, MI, USA), as a method of the manufacturer’s instructions. Differentiated adipocytes (Day 8) were treated with increasing amounts of SPY (0.05, 0.1, 0.25, and 0.5 mg/mL) in 6-well plates. The cells were washed and scraped with 200 mL of PBS, and homogenized by sonication for 2 min. Total TG in cell lysates was assayed after that.
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2.6. Total RNA Preparation and Reverse Transcription-Polymerase Chain Reaction (RT–PCR)
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To determine the mRNA expression levels of inducible FAS, ACC, PPAR-γ, and aP2, total RNA from SPY-treated cells was prepared using a total RNA extraction kit (Intron Biotechnology, Republic Korea). RT-PCR was performed using the One-step RT–PCR PreMix kit (Intron Biotechnology, Seongnam-si, Republic of Korea) with appropriate sense and antisense primers for FAS (sense 5′-CGGCTGCAGGTGGTCGATAGG-3′ and antisense 5′-TGTAGGGGTTGCCGCAATGTC-3′), PPAR-γ (sense 5′-GTCTGTGGGGATAAAGCATC-3′ and antisense 5′- CTGATGGCATTGTGAGACAT-3′), ACC (sense 5′-GAAGAGAACAAAAGCGACATG-3′ and antisense 5′-AATGGCTGATAGGAAGATAGA-3′), and β-actin (sense 5’-AGG+TATCCTGACCCTGAAGTACC-3’ and antisense 5’-GTTGCCAATAGTGATGACCTGGC-3’). Primers were amplified under incubation conditions of 95 °C predenaturation for 5 min and 30 cycles of 95 °C denaturation for 30 s, 58 °C annealing for 30 s, 72 °C extension for 40 s, and a final elongation step for 10 min at 72 °C. The products obtained by RT-PCR were separated on a 1.5% agarose gel and stained with ethidium bromide. The gels were then viewed under UV transillumination, and the relative levels of mRNA against β-actin were quantified using ImageJ software from NIH (Bethesda, MD, USA).
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2.7. Western Blot Analysis
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To determine the expression level of adipogenic-related proteins, western blot analysis was performed using the lysates from 3T3-L1 adipocytes cultured in a differentiation medium within or without SPY for 8 days. On Day 8, PBS buffer was used to wash the cells. Cold lysis buffer (pH 7.4) containing 20 mM Tris-HCl, 150 mM NaCl, 1 mM Na2EDTA, 1 mM EGTA, 1% NP-40, 1% sodium deoxycholate, 2.5 mM sodium pyrophosphate, 1 mM β-glycerophosphate, 1 mM Na3VO4, and 1 mg/mL leupeptin was used to resuspend the cells. The cell lysates were centrifuged at 17,700× g and 4 °C for 10 min. The Bradford method (Bio-Rad, Hercules, GA, USA) was applied to determine the protein concentrations. An equal quantity of protein was divided on a 10% SDS-polyacrylamide gel and transferred to PVDF membranes (Bio-Rad, USA). Tris-buffered saline (TBS, pH 7.4) containing 5% nonfat dry milk was used to block the membrane, and primary anti-mouse FAS, aP2, PPAR-γ, and ACC antibodies were incubated with the blocked membrane overnight at 4 °C. The membranes were incubated with anti-mouse IgG-HRP (Cell Signaling Technology) for 2 h at room temperature after washing blocked membranes with TBS containing 0.1% Tween 20. Protein bands were visualized through the ECL system (ABclon, Seoul, Republic of Korea). The ImageJ Program (National Institute of Health, Bethesda, MD, USA) was utilized to quantify the band intensities and to normalize the levels of PPAR-γ, aP2, FAS, and ACC compared to β-actin.
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2.8. Animal Care and Diets
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The Catholic University of Korea approved the animal protocols followed in the present research (Approval Number: 2019-019). Male C57BL/6 mice purchased from Orient Bio Inc. (Gyeonggi-do, Republic of Korea) were kept under controlled temperatures (22–23 °C) on a 12/12-h light-dark cycle. After the acclimatization period, the male C57BL/6 mice were divided into seven groups (n = 8 in each group) and given a normal diet (ND) or high-fat diet (HD) with the indicated doses of samples for 12 weeks, normal diet control group (2018C, Envigo, Indianapolis, IN, USA, 18% calories from fat); HD, high-fat diet (TD.06414, Envigo, USA, 60.5% calories from fat); GAR, HD + 1% Garcinia cambogia extract (100 mg/kg); SPY-L, HD + SPY (30 mg, 4 × 106 CFU/kg); SPY-H, HD + SPY (300 mg, 4 × 107 CFU/kg); BST-L.601-L, HD + BST-L.601 (4 × 108 CFU/kg); BST-L.601-H, HD + BST-L.601 (4 × 109 CFU/kg). Each dose of the sample was administered. The Garcinia cambogia extract was used as a positive reference. Body weights were measured every week. After 12 weeks of administration of SPY or L.601, the mice were fasted for 24 h and anesthetized with a mixture of alfaxalone (0.15 mL/25 g/mice) and xylazine hydrochloride (0.01 mL/25 g/mice) before sacrifice. Blood serum, adipose tissues, and liver were individually taken for further analyses.
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2.9. Serum Biochemical Analysis
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To collect blood samples, mice were fasted. Blood serum was collected by cardiac puncture and stored at −80 °C before use. To determine levels of total cholesterol (Total-c), high-density lipoprotein cholesterol (HDL-c), and low-density lipoprotein cholesterol (LDL-c) in collected blood serum, LH-1500 Automatic Analyzer (LH-1500, Incheon, Republic of Korea) was utilized.
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2.10. Chemical Composition Analysis
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The general chemical composition, total carbohydrate, protein, polyphenols, and caffeic acid, in the mashed sweet potato paste (MSPP) powder and SPY (the fermented MSPP with BST-L.601), were determined and compared. Total carbohydrate was measured by the phenol-sulfuric acid method at 490 nm using glucose as a reference [26]. Bradford method was operated to quantify total protein and BSA was used as a standard for Bradford method at 595 nm [27]. Total polyphenols were determined by the Folin-Ciocalteu reagent method using gallic acid as a reference at 750 nm [28]. Each powder sample was blended with distilled water to make a 1.0% (w/v) solution (10 mg/mL) for 1 h using a nutator mixer (FinePCR, Gunpo-si, Republic of Korea) while homogenizing with a sonicator (Branson, MO, USA) by 1 min sonication and 5 min cooling on ice-cold water. The sonication was repeated 10 times. After sonication, each suspension was diluted with distilled water to an appropriate concentration for analysis. The detection and quantification of the amount of caffeic acid in SPY and MSPP were performed by using an HPLC system equipped with a UV detector (1260 Infinity Ⅱ, Agilent, Santa Clara, CA, USA). Samples were dissolved in methanol, fractionated on an XDB-C18 column (150 × 4.6 mm, 5 μm column, Agilent), and eluted at 1.0 mL/min in gradient mode with a mobile phase composed of water (pH 3.15 by formic acid) and acetonitrile.
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2.11. Statistical Analysis
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The results were shown in the means ± SDs for each treatment group in each experiment. Statistical analysis was carried out by using the Statistical Analysis System software package (SAS Institute, Cary, NC, USA). Significance was determined by a one-way analysis of variance, followed by Dunnett’s range test for multiple comparisons, and data were analyzed using the SAS package program (SAS Institute Inc., Cary, NC, USA). Data were considered to be different at p < 0.05.
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3. Results
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3.1. Effects of SPY and BST-L.601 on the Viability of 3T3-L1 Pre-Adipocytes
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| 107 |
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To determine whether SPY and BST-L.601 are detrimental to 3T3-L1 preadipocytes, cell survival was evaluated by MTT assay with exposure to increasing doses of SPY (0.025, 0.05, 0.1, 0.25, and 0.5 mg/mL) containing BST-L.601 (2.5 × 107, 5 × 107, 1 × 108, 2 × 108, and 4 × 108 CFU/mL, respectively) (Figure 1A) or BST-L.601 (Figure 1B) for 24 h. As shown in Figure 1, both SPY (Figure 1A) and BST-L.601 (Figure 1B) were not significantly toxic to the growth of 3T3-L1 preadipocytes in the concentration range tested (up to 0.5 mg/mL for SPY and 4 × 108 CFU/mL for BST-L.601).
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3.2. Effects of SPY on Adipocyte Differentiation
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To assess the efficacy of SPY on inhibiting lipid accumulation, 3T3-L1 preadipocytes were exposed to varying levels of SPY for 8 days, and lipids in adipocytes were stained with Oil red O dye. Figure 2A, the representative images of Oil red O staining, shows that the undifferentiated control cells (UC) were not stained with dye, but huge numbers of stained spots (pink-colored) appeared in the differentiated control cells (Con). This indicates the preadipocytes were differentiated into mature adipocytes, actively synthesizing lipids (Figure 2A). However, these promoted lipids were substantially decreased by SPY (0.05, 0.1, 0.25, and 0.5 mg/mL) in a dose-dependent manner by 19.3%, 25.5%, 28.6%, and 47.4%, respectively, compared to the differentiated control cells (Con, 100%), showing that SPY effectively inhibited the differentiation of adipocyte cells (Figure 2A,B). Moreover, the markedly increased intracellular triglyceride (TG) contents in differentiating adipocytes (Con, 100%) were also effectively reduced to 23.2%, 28.8%, 33.3%, and 50.7% upon SPY (0.05, 0.1, 0.25, and 0.5 mg/mL) exposure (Figure 2C), indicating that SPY inhibited lipid accumulation, especially TG, during adipocyte differentiation.
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3.3. Inhibitory Effect of SPY on Differentiation and Lipogenesis-Related Protein Expression in 3T3-L1 Cells
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Throughout adipogenesis, factors and proteins related to adipocytes such as C/EBPα, PPAR-γ, and aP2 are expressed [23]. C/EBPα and PPAR-γ stimulate the expression of lipogenic enzymes similar to FAS and ACC in various ways during adipogenesis [16,24]. To determine the effects of SPY on the expression of these adipogenic and lipogenic marker proteins, 3T3-L1 cells were cultured in an MDI differentiation medium for 8 days with the indicated concentration of SPY. Western blot analysis showed SPY treatment (0.05, 0.1, 0.25, and 0.5 mg/mL) resulted in predominant inhibition in the expression of these proteins (Figure 3). SPY (0.5 mg/mL) considerably inhibited the protein levels of PPAR-γ by 48.4% (Figure 3A,B), C/EBPα by 73.7% (Figure 3A,C), and aP2 by 75.7% (Figure 3A,D) when it is compared with the differentiated, Sample-untreated control cells (Con, 100%). SPY treatment (0.5 mg/mL) also significantly inhibited the expression of ACC by 50.0% (Figure 3E,F) and FAS by 80.9% (Figure 3E,G) compared to the differentiated but SPY-untreated group (Con, 100%). These results proved SPY effectively suppressed the differentiation of preadipocytes through the downregulation of diverse adipogenesis-specific transcription factors and lipogenesis marker proteins.
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| 117 |
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3.4. Body and Organ Weight Changes of Mice Fed the Different Diets
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C57BL/6 mice were fed a high-fat diet (HD) for 12 weeks and used as the HD-induced obese model. Mice were randomly divided into 7 groups (n = 8): ND, normal diet group; HD, high-fat diet (control); GAR, HD + 1% Garcinia cambogia extract-treated group (100 mg/kg); SPY-L, HD + SPY (4 × 106 CFU/kg); SPY-H, HD + SPY (4 × 107 CFU/kg); L.601-L, HD + BST-L.601 (4 × 108 CFU/kg); L.601-H, HD + BST-L.601 (4 × 109 CFU/kg). Oral administration of diet for mice with or without doses of samples proceeded for 12 weeks, and the body weight of each mouse was checked once a week. As shown in Figure 4B, HD-induced obese mice had an increased body weight by 48.0% after 12 weeks of feeding, and the SPY-H group and L.601-H group had decreased body weight by 19.6% and 14.8%, respectively, compared with the HD group. The relative weights of epididymal fat, visceral fat, abdominal fat, and liver tissue in the HD group were higher than those in the ND group (Table 1). The administration of SPY and BST-L.601 decreased the weight of total fat tissues (epididymal, visceral and subcutaneous, and abdominal fat tissues) by 29.8% (SPY-H) and 25.4% (L.601-H), respectively (Table 1).
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3.5. SPY Prevents Hyperlipidemia in High-Fat Diet Mice
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To assess the effects of SPY and BST-L.601 on the serum biochemical parameters in HD-induced obese mice, total cholesterol (Total-c), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), and leptin were analyzed by automated analyzer after various diets were orally administered to HD-induced obese mice. SPY (SPY-H) reduced the cholesterol and LDL levels by 27.9% and 32.6%, respectively, and BST-L.601 (L.601-H) reduced cholesterol and LDL levels by 35.7% and 36.4%, respectively (Figure 5A,C) compared with the HD group (100%). Oral administration of SPY and BST-L.601 (L.601-H) increased the ratio of HDL/Total-c level by 21.9% and 8.3%, respectively (Figure 5D). SPY also decreased the secretion of leptin, one of the hormones secreted from visceral and subcutaneous adipose tissue. Leptin secretion was decreased in the SPY-H group by 24.0% and in the L.601-H group by 27.8%, respectively (Figure 5E), when the secretion of leptin in the HD group is set at 100%. These results indicated that SPY and BST-L.601 effectively regulate cholesterol levels in blood serum.
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3.6. Effects of SPY and BST-L.601 on the Size and Numbers of Adipocytes in Liver and Epididymal Fat Tissues
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The increment of the mass and the number of adipocytes mainly depends on the amount of lipids accumulated in the fat cells. Therefore, the size and number of adipocytes accumulated in epididymal adipose tissue and liver tissue are habitually evaluated indicators to assess the potential anti-obesity efficacy of ingredients [24]. To determine the numbers and sizes of adipocytes in liver tissues and fat tissues, tissues were stained by hematoxylin and eosin staining (H&E). Sections of epididymal adipose tissue of the HD group revealed an increased number of expanded adipocytes (red-arrow) following H&E staining is completed (Figure 6A). However, administration of SPY (SPY-H) and BST-L.601 (L.601-H) significantly reduced these enlarged cell sizes of adipocytes by 25.0% and 11.0%, respectively, and the number of adipocytes per 1.48 μm2 was increased by 28.5% and 7.6%, respectively (Figure 6B,C).
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3.7. SPY and BST-L.601 Suppress Adipogenic and Lipogenic Marker Protein mRNA Expression in HD-Induced Obese Mice
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RT-PCR analysis was performed to identify the effects of SPY and BST-L.601 on the expression levels of adipogenic markers in HD-induced obese mice. After 12 weeks of oral administration of SPY and BST-L.601, liver tissues were lysed, and the amount of mRNA was measured. Oral administration of SPY (SPY-H) and BST-L.601 (L.601-H) decreased the mRNA expression level of aP2 by 32.3% and 60.1% (Figure 7A), PPAR-γ by 31.0% and 25.5% (Figure 7B), FAS by 15.9% and 30.3% (Figure 7C), and ACC-1 by 13.3% and 41.0%, respectively (Figure 7D). These results suggested the exhibition of the anti-obesity ability of SPY and BST-L.601 through the downregulation of the expression of various adipogenesis-specific transcription factors and lipogenesis marker proteins.
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3.8. SPY and BST-L.601 Suppress Adipocyte Differentiation and Lipogenic Marker Protein Expression in Liver Tissue of HD-Induced Obese Mice
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To determine the effect of SPY and BST-L.601 on adipogenic and lipogenic marker proteins in HD-induced obese mice, the levels of adipocyte differentiation transcription factors as PPAR-γ and aP2 and lipogenic enzymes similar to ACC and FAS were investigated by Western blotting. SPY (SPY-H group) and BST-L.601 (L.601-H group) were shown to reduce PPAR-γ by 60.8% and 41.9% (Figure 8A,B) and aP2 by 48.8% and 40.7% (Figure 8A,C) when the β-actin level in the HD group was set at 100%. Administration of SPY (SPY-H) and BST-L.601 (L.601-H) also decreased ACC by 48.5% and 53.5% (Figure 8A,D) and FAS by 43.8% and 41.7% (Figure 8A,E). These results showed that SPY and BST-L.601 effectively downregulated adipogenesis and lipogenesis.
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3.9. Chemical Composition Profile of SPY and MSPP
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The chemical composition of MSPP and SPY was determined as summarized in Table 2. The MSPP and SPY sample preparations contained total carbohydrates up to 922.4 mg/g (92.24%, w/w) and 810.5 mg/g (81.05%), protein up to 30.7 mg/g (0.0307%) and 16.3 mg/g (0.0163%), and total polyphenols up to 1.65 mg/g (0.00165%) and 1.99 mg/g (0.00199%), respectively, indicating that both samples consist mostly of carbohydrates (Table 2). One of the possible explanations for the decreased level of total carbohydrates in SPY, compared to that of MSPP, would be that some of the digestible carbohydrates were consumed for the growth and proliferation of BST-L.601 during fermentation.
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The results from HPLC analysis for caffeic acid in MSPP (SP) and SPY confirmed the presence of caffeic acid in both samples up to 0.26 mg/g (MSPP) and 0.18 mg/g (SPY), respectively (Figure 9 and Table 2). One of the bioactive polyphenolic compounds of plant origin, caffeic acid (CFA) has been known to exert effects in anti-obesity by reducing body weight and regulating gut microbiota [29]. Therefore, in addition to BST-L.601 in SPY, CFA might contribute to the anti-obesity effects of SPY shown in this study, at least partly. Additionally, the presence of CFA in sweet potatoes was reported [30,31,32]. This suggests that CFA present in SPY can be utilized as an index compound for SPY and SPY-based products.
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4. Discussion
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Several researchers have reported that oral medication of lactic acid bacteria (LAB) with prebiotics promotes the intestinal activity of LAB [22]. It was reported that the anti-obesity efficacy of the gut microbiome is related to LAB, and the dietary fiber from sweet potatoes helps a gut microbiome profile in a healthy way [21,22]. In this study, a newly isolated probiotic strain, Lactobacillus rhamnosus BST-L.601 (KCTC13517BP), and its fermented product (named SPY) with mashed sweet potato paste (MSPP) were evaluated to prove the efficacy of anti-obesity through using 3T3-L1 preadipocyte cells and an HD-induced obese mouse model.
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Obesity is caused by the accumulation of triglycerides in adipocytes during the differentiation of 3T3-L1 preadipocytes [30]. Previous studies have shown that the first factors expressed after MDI treatment are C/EBPβ and C/EBPγ [33]. These two factors promote the expression of C/EBPα and PPAR-γ in the middle and end of preadipocyte differentiation [34]. Among them, C/EBPα is an essential factor inducing the inhibition of lipogenesis and adipogenesis. In addition, the decrease in the expression levels of C/EBPα and PPAR-γ induces a decrease in the expression of adipose protein 2 (aP2), which is known as a differentiation factor of preadipocytes, and PPAR-γ is a major factor involved in lipogenesis and adipogenesis [33]. The decrease in the expression level of these two factors leads to proteins that transport fatty acids to cells, causing lipid generation in cells [35]. This research showed that treatment of SPY decreased lipid droplets in 3T3-L1 preadipocytes and it means that SPY suppresses the adipogenesis of 3T3-L1 preadipocytes. Moreover, the expression of C/EBPα and PPAR-γ, which are the major adipogenesis factors, was significantly suppressed by SPY. Therefore, these results imply that SPY could negatively control the adipogenesis of 3T3-L1 preadipocytes.
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Acetyl-CoA carboxylase (ACC) inhibits the activity of AMP-activated protein kinase (AMPK), reducing the production of malonyl-CoA [36,37]. Malonyl-CoA is synthesized as palmitate by fatty acid synthase (FAS), and palmitate is known to reduce fat accumulation and inhibit lipolysis [38,39]. In this research, oral administration of SPY reduced the expression of ACC and FAS, demonstrating its ability to downregulate lipogenesis. These results mean that SPY controls the expression of ACC and FAS, and also can be an effective agent to control adipogenic and lipogenic metabolism in 3T3-L1 preadipocytes. In previous research, it was proven that one of the L. rhamnosus strains controls the expression of transcription factors associated with adipogenic metabolism in an HD-induced obese mouse model [40].
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The observed in vitro anti-obesity potential of SPY was further confirmed in an in vivo model system using HD-induced obese mice. The results showed that the significantly elevated body weight in HD mice was effectively reduced by oral administration of SPY or BST-L.601, with a more significant reduction by SPY than BST-L.601 treatment. The SPY used in this study was prepared by fermentation of mashed sweet potato paste (MSPP) with the BST-L.601 strain. Similar to our present observation, a combined preparation of prebiotics and probiotics was reported to reduce body fats [41]. LAB is demonstrated that it has efficacy in reducing hypercholesterolemia and preventing obesity [42]. Previously, it was reported that sweet potatoes contain significant amounts of resistant starch, caffeic acid, and many other compounds, including phenolic compounds, anthocyanins, and caffeoyl compounds [30,31,32]. One of the bioactive polyphenolic compounds of plant origin, caffeic acid (CFA) has been known to have various pharmacological activities such as anti-inflammatory, anti-cancer, anti-oxidant, and anti-obesity effects. Anti-obesity effectiveness of CFA is mediated by reducing body weight and regulating the gut microbiome in obese mice [29]. Resistant starch is known to express some beneficial effects related to metabolic syndrome such as inhibiting the increment of blood cholesterol and decreasing the glycemic response. Moreover, resistant starch acts as a functional prebiotic [19]. Therefore, although it is not proven right now, the observed results that SPY-H was more effective in decreasing the body weight gain in HD mice than treatment with BST-L.601 alone would be due to the presence of certain compounds contained in MSPP, such as resistant starch and CFA, which could synergistically contribute to the lowering of body weight gain in HD mice. Alternatively, it would also be possible that SPY may contain some other compounds produced during the fermentation of MSPP with BST-L.601 probiotics. On the other hand, hydroxycitric acid (HCA) is one of the key bioactive chemicals in Garcinia cambogia, and its anti-obesity effect has been explained unclearly for the last decades; thus, Garcinia cambogia has been widely added as a main raw material for anti-obesity functional foods [43]. In a previous study performed by another research group, it was confirmed that the administration of Garcinia cambogia powder (1%, w/w, 60% HCA) had an effect on inhibiting fat accumulation without toxicity [44,45]. For the above reasons, Garcinia cambogia was chosen as a positive control of anti-obesity efficacy for comparison with SPY. The results showed that SPY also exerted a significant positive effect on weight loss in fatty liver, epididymal adipose tissue, and visceral fat, which was comparable to that of the GAR (Garcinia cambogia extract, 100 mg/kg) group.
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Meanwhile, Oil red O staining and TG content measurement in differentiating adipocyte cells showed that SPY significantly decreased lipid accumulation. Furthermore, histopathological analysis of adipose tissue located on the liver and epididymis in HD-induced obese mice by H&E staining demonstrated that administration of SPY-H and BST-L.601-H significantly reduced the enlarged cell size and increased the cell numbers of adipocytes in these tissues. One of the indicators for anti-obesity assessment is the size and number of adipocytes. Especially, adipocytes accumulated in epididymal and liver tissue are a useful index for verifying anti-obesity efficacy from chemicals or natural ingredients [46]. The important factor to define obesity is an increment of adipose tissue mass driven by either an explosive increment of the number or size of adipocytes [4]. Hypertrophy is mainly due to the accumulation of lipids and the hyperplasia caused by the proliferation and differentiation of adipocyte precursor cells into mature adipocytes [4]. This process is called adipogenesis. Thus, the regulation of the adipose tissue mass is conducted by suppressing adipogenesis, reducing lipogenesis, and enhancing lipolysis. An additional method to control adipose tissue is inducing apoptotic death of cells [5]. Therefore, the results of our study that SPY and BST-L.601 significantly reduced the enlarged cell size and increased the cell numbers of adipocytes in these tissues suggest that both SPY and BST-L.601 exert anti-obesity effects by effectively reducing adipose tissue mass by inhibiting lipogenesis of adipocytes.
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On the other hand, as shown by H&E staining of liver tissues, oral administration of SPY and BST-L.601 prominently declined the immoderate generation and deposit of lipids in hepatocytes. This suggests that these materials may be potentially effective against hepatic steatosis, which is an important factor to define nonalcoholic fatty liver disease (NAFLD) [47]. Several animal studies using rodents have demonstrated that suppressing the accumulation of lipids in the liver tissue could be for hepatoprotection from HD-induced NAFLD [48,49]. The results of this study imply that SPY is useful for weight loss in fatty liver, epididymal adipose tissue, and visceral fat in HD-induced obese mice. Although it needs to be clarified through the following research, SPY, and BST-L.601 may exert protective effects to inhibit hepatic steatosis and thus NAFLD in HD-fed mice, which would be an additional health benefit of SPY and BST-L.601.
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SPY was also shown to suppress the secretion of leptin, an adipocyte hormone that is secreted by adipocytes in response to their triglyceride levels, and is known to regulate energy expenditure and food intake [50,51]. Circulating leptin levels in the blood are associated with the extent of obesity; thus, leptin is a sensitive biomarker to indicate obesity [51,52]. In this study, oral administration of SPY and BST-L.601 to HD-induced obese mice for 12 weeks resulted in reduced levels of leptin in blood serum, suggesting that both materials, SPY, and BST-L.601, attenuated the secretion of leptin, thereby downregulating lipid metabolism in HD-fed mice.
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5. Conclusions
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This study revealed that, with no detectable level of cytotoxicity, SPY, a fermented product (named SPY) of Lactobacillus rhamnosus BST-L.601 in mashed sweet potato paste (MSPP) medium, significantly reduced the lipid accumulation and TG contents in 3T3-L1 adipocytes. Moreover, SPY also inhibited the differentiation of adipocytes and lipogenesis through suppression of the expression of adipogenesis-related markers such as C/EBPα, PPAR-γ, and aP2 and fatty acid synthetic pathway proteins such as ACC and FAS. In HD-induced obese mice, oral administration of SPY or BST-L.601 for 12 weeks significantly reduced the body and liver weight, the size of adipocytes, and the weight of epididymal, visceral, and subcutaneous fat tissues. Administration of SPY or BST-L.601 also reduced the serum levels of total cholesterol and LDL cholesterol and leptin secretion. These results indicated that both SPY and BST-L.601 effectively suppress HD-induced adipogenesis and lipogenesis through the downregulation of the expression of adipogenic marker proteins and lipogenesis-related marker proteins. SPY was more effective in decreasing body weight gain in HD mice than in treatment with BST-L.601 alone. The results of the present study suggest that SPY and BST-L.601 can be potential candidates as active ingredients to develop health-beneficial functional foods or new probiotic-prebiotic combined compositions to prevent or treat obesity.
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Author Contributions
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Conceptualization, J.-W.P., T.K. and Y.I.P.; methodology, T.K. and H.C.; validation, J.R. and J.-W.P.; formal analysis, T.K., H.C. and J.R.; investigation, T.K., J.-W.P. and J.R.; resources, T.K. and J.-W.P.; data curation, J.R. and H.C.; writing—original draft preparation, T.K.; writing—review and editing, Y.I.P. and J.R.; visualization, T.K. and J.R.; supervision, Y.I.P. and J.-W.P.; funding acquisition, Y.I.P. All authors have read and agreed to the published version of the manuscript.
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Data Availability Statement
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The data presented in this study are available on request from the corresponding author.
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Conflicts of Interest
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This study was performed through the collaboration between University and Industrial company (The Catholic University of Korea- Biostream Technologies Co.) under the financial support from the company (grant number M-2019-D0321-00001). Authors, Joo-Woong Park, Hyewon Choe, and Taewook Kang, were (and till now) employed by the company Biostream Technologies Co. Taewook Kang and Jin Ree are affiliated to both company (Biostream Technologies Co.) and university (The Catholic University of Korea) as part-time graduate students. In addition to the financial support, the company research team (Dr. Joo-Woong Park, Hyewon Choe, and Taewook Kang) prepared the materials (probiotic strain, Lactobacillus rhamnosus BST-L.601, and the sweet potato yogurt, SPY, fermented with this strain) and performed composition analysis of these materials. Dr. Joo-Woong Park and Taewook Kang, as the company side, and Yong Il Park (the corresponding author) as the university side conceptualized, designed and supervised this study. The prepared materials were provided to university research team (Prof. Yong Il Park who is the corresponding author of this manuscript) for in vitro and in vivo bioactivity assay (Anti-obesity experiments). Taewook Kang, who is affiliated to both company and university as a part-time graduate student for Master degree performed most part of the bioactivity experiments and writing of the draft of this manuscript. Jin Ree and Hyewon Choe performed data curation and some instrumental analysis and data curation. The authors declare no conflict of interest.
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Figure 1 Effects of SPY and BST-L.601 on the viability of 3T3-L1 preadipocyte cells. Cytotoxicity of (A) SPY and (B) BST-L.601 was assessed by measuring cell viability using the MTT assay after 24 h of exposure to (A) SPY (0.025, 0.05, 0.1, 0.25, and 0.5 mg/mL) or (B) BST-L.601 (2.5 × 107, 5 × 107, 1 × 108, 2 × 108, and 4 × 108 CFU/mL). The data were expressed as a percentage normalized to sample-untreated control cells (Con). Values are the means ± SDs (n = 8). Values with different superscripts are significantly different among the groups by one-way ANOVA with Dunnett’s multiple comparison test at ** p < 0.01; *** p < 0.001, compared to the Control group.
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Figure 2 Effects of SPY on lipid accumulation and TG content in differentiating 3T3-L1 cells. Cells were cultured in an MDI differentiation medium and treated with varying concentrations of SPY (0.05, 0.1, 0.25, and 0.5 mg/mL) for 8 days. (A) Lipid droplets generated were stained with Oil red O dye and visualized under a microscope (×100). (B) Stained lipid droplets were solubilized with isopropanol and quantified at 517 nm on a microplate reader. (C) Intracellular triglyceride (TG) contents were measured using a triglyceride assay kit. Data are expressed as the means ± SDs (n = 3). Values with different superscripts are significantly different among the groups by one-way ANOVA with Dunnett’s multiple comparison test at *** p < 0.001 compared to the Control group. UC, undifferentiated normal control cells; Con, sample-untreated differentiated control cells.
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Figure 3 Inhibitory effect of SPY on differentiation and lipogenesis-related protein expression in 3T3-L1 adipocytes. (A) and (E) 3T3-L1 cells were cultured in MDI differentiation medium for 8 days with increasing concentrations of SPY (0.05, 0.1, 0.25, and 0.5 mg/mL), and cell lysates were used for Western blot analysis. The expression levels of (B) PPAR-γ, (C) C/EBPα, (D) aP2, (F) ACC, and (G) FAS were quantified by ImageJ software. β-Actin was used as a loading control. Each data point was expressed as the % of control cells (Con, 100%). Data are the means ± SDs (n = 3). Values with different superscripts are significantly different among the groups by one-way ANOVA with Dunnett’s multiple comparison test at * p < 0.05; ** p < 0.01; *** p < 0.001, compared to the Control group. UC, undifferentiated control cells; Con, untreated sample, differentiated control cells.
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Figure 4 Protocol for animal treatment and body weight change of mice fed the different diets. (A) ND, normal diet; HD, high-fat diet; GAR, HD supplemented with Garcinia cambogia extract (100 mg/kg); SPY−L, a high-fat diet supplemented with SPY (4 × 106 CFU/kg); SPY− H, HD supplemented with SPY (4 × 107 CFU/kg); L.601− L, HD supplemented with BST-L.601 (4 × 108 CFU/kg); L.601− H, HD supplemented with BST-L.601 (4 × 109 CFU/kg). L.601, L. rhamnosus BST-L.601. (B) Body weight change of mice fed the different diets. Mice were given their diets and indicated doses of samples for 12 weeks, and the body weight was weighed every week. Values are the means ± SDs (n = 8).
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Figure 5 Effects of SPY and BST-L.601 on hyperlipidemia markers. The blood serum of HD-induced obese mice was analyzed by an automated analyzer after oral administration of various diets for 12 weeks. (A) Total cholesterol (Total-c), (B) high-density lipoprotein-cholesterol (HDL), (C) low-density lipoprotein-cholesterol (LDL), (D) HDL/Total-c, (E) Leptin. ND, normal diet; HD, high-fat diet; GAR, HD supplemented with Garcinia cambogia extract (10 mg/kg); SPY−L, HD supplemented with SPY (4 × 106 CFU/kg); SPY− H, HD supplemented with SPY (4 × 107 CFU/kg); L.601− L, HD supplemented with BST-L.601 (4 × 108 CFU/kg); L.601− H, HD supplemented with BST-L.601 (4 × 109 CFU/kg). L.601, L. rhamnosus BST-L.601. Values are the means ± SDs (n = 8). Values with different superscripts are significantly different among the groups by one-way ANOVA with Dunnett’s multiple comparison test at * p < 0.05; ** p < 0.01; *** p < 0.001, compared to the HD group.
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Figure 6 Effect of SPY and BST-L.601 on the size and numbers of adipocytes in liver and epididymal fat tissues in HD-induced obese mice. Liver tissues and adipose tissues were stained with hematoxylin and eosin (H&E). (A) Sections of stained epididymal adipose tissue and liver tissue were monitored under a light microscope (magnification, ×200 for epididymal adipose tissues, ×400 for liver tissues). (B) Size of epididymal adipose tissue and (C) cell numbers in the measured area (measured unit area = 1.48 μm2). ND, normal diet; HD, high-fat diet; GAR, HD supplemented with Garcinia cambogia extract (100 mg/kg); SPY−L, HD supplemented with SPY (4 × 106 CFU/kg); SPY− H, HD supplemented with SPY (4 × 107 CFU/kg); L.601− L, HD supplemented with BST-L.601 (4 × 108 CFU/kg); L.601− H, HD supplemented with BST-L.601 (4 × 109 CFU/kg). L.601, L. rhamnosus BST-L.601. Values with different superscripts are significantly different among the groups by one-way ANOVA with Dunnett’s multiple comparison test at * p < 0.05; ** p < 0.01; *** p < 0.001, compared to the HD group.
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Figure 7 Effects of SPY and BST-L.601 on the mRNA levels of lipogenic markers in the liver tissue of HD-induced obese mice. To investigate the effects of SPY and BST-L.601 on the expression of (A) and (B) adipogenic markers (aP2 and PPAR-γ) and (C) and (D) lipogenic marker proteins (FAS and ACC-1), liver tissues of HD-induced obese mice treated with various diets for 12 weeks were homogenized and processed for RT-PCR and quantified by ImageJ software. The relative mRNA levels of lipogenic markers in the liver tissue were measured by RT-PCR. ND, normal diet; HD, high-fat diet; GAR, HD supplemented with Garcinia cambogia extract (100 mg/kg); SPY–L, HD diet supplemented with SPY (4 × 106 CFU/kg); SPY–H, HD supplemented with SPY (4 × 107 CFU/kg); L.601–L, HD supplemented with BST-L.601 (4 × 108 CFU/kg); L.601–H, HD supplemented with BST-L.601 (4 × 109 CFU/kg). L.601, L. rhamnosus BST-L.601. Values with different superscripts are significantly different among the groups by one-way ANOVA with Dunnett’s multiple comparison test at * p < 0.05; ** p < 0.01, *** p < 0.001, compared to the HD group.
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Figure 8 Effects of SPY and BST-L.601 on adipocyte differentiation and lipogenic marker proteins in the liver tissue of HD-induced obese mice. (A) Western blot analysis and ImageJ software were used to monitor and quantify the expression levels of adipocyte differentiation and lipogenic marker proteins, (B) PPAR-γ, (C) aP2, (D) ACC, and (E) FAS. β-Actin was used as a loading control. Each data point was expressed as the % of the HD group (100%). ND, normal diet; HD, high-fat diet; GAR, a high-fat diet supplemented with Garcinia cambogia extract (100 mg/kg); SPY−L, HD supplemented with SPY (4 × 106 CFU/kg); SPY− H, HD supplemented with SPY (4 × 107 CFU/kg); L.601− L, HD supplemented with BST-L.601 (4 × 108 CFU/kg); L.601− H, HD supplemented with BST.L-601 (4 × 109 CFU/kg). L.601, L. rhamnosus BST-L.601. Values with different superscripts are significantly different among the groups by one-way ANOVA with Dunnett’s multiple comparison test at * p < 0.05; ** p < 0.01; *** p < 0.001, compared to the HD group.
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Figure 9 HPCL analysis for caffeic acid in SPY and MSPP. (A) Authentic caffeic acid (Sigma, San Francisco, CA, USA). (B) SPY and (C) SP (MSPP) samples dissolved in methanol were separately fractionated on an XDB-C18 column and detected by a UV detector at 330 nm and quantified by comparing the peak area on the chromatogram set to the peak area of standard caffeic acid at 100% as described in the manuscript.
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foods-12-02202-t001_Table 1 Table 1 Changes in organ and fat tissue weights.
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Group ND HD GAR SPY− SPY− L.601− L.601−
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Liver weight (g) 1.59 ± 0.17 1.93 ± 0.44 1.61 ± 0.16 1.71 ± 0.47 1.49 ± 0.19 * 1.52 ± 0.19 * 1.49 ± 0.17 *
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Kidney weight (g) 0.45 ± 0.06 0.45 ± 0.04 0.48 ± 0.04 0.47 ± 0.08 0.49 ± 0.06 0.43 ± 0.06 0.48 ± 0.04
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Spleen weight (g) 0.081 ± 0.016 0.083 ± 0.007 0.079 ± 0.012 0.078 ± 0.009 0.079 ± 0.007 0.072 ± 0.01 0.074 ± 0.012
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Epididymis
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fat tissue (g) 1.029 ± 0.26 *** 3.246 ± 0.55 3.151 ± 0.21 2.920 ± 0.24 2.725 ± 0.41 3.446 ± 0.14 2.533 ± 0.48 **
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Visceral
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fat tissue (g) 0.449 ± 0.11 *** 1.752 ± 0.17 1.394 ± 0.19 ** 1.480 ± 0.17 * 1.321 ± 0.12 *** 1.578 ± 0.33 1.240 ± 0.11 ***
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Abdominal
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fat tissue (g) 0.889 ± 0.19 *** 4.797 ± 0.37 3.512 ± 0.56 *** 3.855 ± 0.39 ** 3.035 ± 0.56 *** 3.849 ± 0.34 ** 3.373 ± 0.85 ***
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Total fat (g) 2.48 ± 0.66 *** 10.14 ± 1.06 7.92 ± 0.67 ** 8.35 ± 0.62 * 7.12 ± 1.11 *** 8.50 ± 0.46 7.57 ± 1.93 ***
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ND, normal diet; HD, high-fat diet; GAR, HD supplemented with Garcinia cambogia extract (10 mg/kg); SPY–LHD supplemented with SPY (4 × 106 CFU/kg); SPY–H, HD supplemented with SPY (4 × 107 CFU/kg); L.601–L, HD supplemented with BST-L.601 (4 × 108 CFU/kg); L.601–H, HD supplemented with BST-L.601 (4 × 109 CFU/kg). L.601, L. rhamnosus BST.-L.601. Values are the means ± SDs (n = 8). Values with different superscripts are significantly different among the groups by one-way ANOVA with Dunnett’s multiple comparison test at * p < 0.05; ** p < 0.01; *** p < 0.001, compared to the HD group.
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foods-12-02202-t002_Table 2 Table 2 Chemical composition analysis.
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Total
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Carbohydrate A
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(mg GE/g) Total Protein B
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(mg BE/g) Total
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Polyphenols C
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(mg GAE/g) Caffeic Acid
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| 216 |
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(mg/mL)
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MSPP D 922.4 (±7.69) 30.7 (±1.69) 1.65 (±0.01) 0.26
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SPY 810.5 (±17.40) 16.3 (±1.00) 1.99 (±0.01) 0.18
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A Total carbohydrate was measured by the phenol-sulfuric acid method and expressed as glucose equivalent (GE) in 1 g of dry sample. B Total protein was quantified by the Bradford method and expressed as BSA equivalent (BE) in 1 g of dry sample. C Total polyphenols were determined by the Folin-Ciocalteu reagent method and expressed as gallic acid equivalents (GAE) in 1 g of dry sample. D MSPP, mashed sweet potato paste. SPY, the fermented product of MSPP with L. rhamnosus BST-L.601.
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==== Refs
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| 277 |
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| 1 |
+
|
| 2 |
+
==== Front
|
| 3 |
+
Int J Mol Sci
|
| 4 |
+
Int J Mol Sci
|
| 5 |
+
ijms
|
| 6 |
+
International Journal of Molecular Sciences
|
| 7 |
+
1422-0067
|
| 8 |
+
MDPI
|
| 9 |
+
|
| 10 |
+
10.3390/ijms24119402
|
| 11 |
+
ijms-24-09402
|
| 12 |
+
Article
|
| 13 |
+
Lysine Deprivation Suppresses Adipogenesis in 3T3-L1 Cells: A Transcriptome Analysis
|
| 14 |
+
https://orcid.org/0000-0002-2089-9311
|
| 15 |
+
Lee Leo Man-Yuen 123*
|
| 16 |
+
https://orcid.org/0009-0000-8547-4042
|
| 17 |
+
Lin Zhi-Qiang 3
|
| 18 |
+
Zheng Lu-Xi 3
|
| 19 |
+
Tu Yi-Fan 124
|
| 20 |
+
So Yik-Hing 12
|
| 21 |
+
Zheng Xiu-Hua 3
|
| 22 |
+
Feng Tie-Jun 3
|
| 23 |
+
https://orcid.org/0009-0000-7102-4649
|
| 24 |
+
Wang Xi-Yue 5
|
| 25 |
+
Wong Wai-Ting 1
|
| 26 |
+
https://orcid.org/0000-0003-3590-7027
|
| 27 |
+
Leung Yun-Chung 12*
|
| 28 |
+
Nixon Daniel W. Academic Editor
|
| 29 |
+
1 Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
|
| 30 |
+
2 Lo Ka Chung Research Centre for Natural Anti-Cancer Drug Development and State Key Laboratory of Chemical Biology and Drug Discovery, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
|
| 31 |
+
3 School of Biomedical Science, The Chinese University of Hong Kong, Shatin, New Territory, Hong Kong, China
|
| 32 |
+
4 Department of Obstetrics and Gynecology, The Chinese University of Hong Kong, New Territory, Hong Kong, China
|
| 33 |
+
5 Shenzhen Research Institute, The Hong Kong Polytechnic University, Shenzhen 518000, China
|
| 34 |
+
* Correspondence: man-yuen.lee@polyu.edu.hk (L.M.-Y.L.); thomas.yun-chung.leung@polyu.edu.hk (Y.-C.L.)
|
| 35 |
+
28 5 2023
|
| 36 |
+
6 2023
|
| 37 |
+
24 11 940206 4 2023
|
| 38 |
+
21 5 2023
|
| 39 |
+
26 5 2023
|
| 40 |
+
© 2023 by the authors.
|
| 41 |
+
2023
|
| 42 |
+
https://creativecommons.org/licenses/by/4.0/ Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
|
| 43 |
+
Growing evidence proves that amino acid restriction can reverse obesity by reducing adipose tissue mass. Amino acids are not only the building blocks of proteins but also serve as signaling molecules in multiple biological pathways. The study of adipocytes’ response to amino acid level changes is crucial. It has been reported that a low concentration of lysine suppresses lipid accumulation and transcription of several adipogenic genes in 3T3-L1 preadipocytes. However, the detailed lysine-deprivation-induced cellular transcriptomic changes and the altered pathways have yet to be fully studied. Here, using 3T3-L1 cells, we performed RNA sequencing on undifferentiated and differentiated cells, and differentiated cells under a lysine-free environment, and the data were subjected to KEGG enrichment. We found that the differentiation process of 3T3-L1 cells to adipocytes required the large-scale upregulation of metabolic pathways, mainly on the mitochondrial TCA cycle, oxidative phosphorylation, and downregulation of the lysosomal pathway. Single amino acid lysine depletion suppressed differentiation dose dependently. It disrupted the metabolism of cellular amino acids, which could be partially reflected in the changes in amino acid levels in the culture medium. It inhibited the mitochondria respiratory chain and upregulated the lysosomal pathway, which are essential for adipocyte differentiation. We also noticed that cellular interleukin 6 (IL6) expression and medium IL6 level were dramatically increased, which was one of the targets for suppressing adipogenesis induced by lysine depletion. Moreover, we showed that the depletion of some essential amino acids such as methionine and cystine could induce similar phenomena. This suggests that individual amino acid deprivation may share some common pathways. This descriptive study dissects the pathways for adipogenesis and how the cellular transcriptome was altered under lysine depletion.
|
| 44 |
+
|
| 45 |
+
lysine deprivation
|
| 46 |
+
amino acid depletion
|
| 47 |
+
adipogenesis inhibition
|
| 48 |
+
anti-obesity
|
| 49 |
+
Start-up Fund for RAPsP0036077 I2021A007 This research was funded by Start-up Fund for RAPs, grant number P0036077 and I2021A007.
|
| 50 |
+
==== Body
|
| 51 |
+
pmc1. Introduction
|
| 52 |
+
|
| 53 |
+
Obesity is a severe public health challenge in the 21st century, and its prevalence is increasing at an alarming rate [1]. It has also been associated with many other metabolic disorders, including diabetes, cardiovascular diseases, and hypertension, leading to a poor quality of life and a severe social burden [2]. One key factor contributing to the fat mass expansion is excessive nutrients, especially fat and carbohydrates. However, increasing evidence has shown that dietary protein and levels of individual amino acids are also crucial for adipogenesis and energy expenditure [3,4,5]. There is growing interest in controlling body weight via regulating dietary micronutrient levels, especially essential amino acids (EAAs). There are nine EAAs: histidine, isoleucine, leucine, lysine, methionine, phenylalanine, threonine, tryptophan, and valine. Research showed that histidine, leucine, lysine, threonine, and tryptophan supplementation could reduce body weight gain and visceral fat deposition in diet-induced obese rats [6,7,8,9,10]. In contrast, a depletion of all nine EAAs individually in the diet, similarly, could reduce body fat mass. The depletion of some EAAs could even lower glucose and triglyceride levels, and improve insulin sensitivity in normal and obese mouse models [3,11,12]. These paradoxical effects of amino acid imbalance on obesity prevention are still not fully understood.
|
| 54 |
+
|
| 55 |
+
Adipogenesis occurs when the body is overloaded with nutrients, contributing to a positive energy balance. It is a multi-step process involving stem cells’ differentiation into mature, lipid-containing adipocytes [13]. There are two phases of adipogenesis, determination and terminal differentiation. The determination step is the process of mesenchymal stem cells committing to the preadipocytes, while terminal differentiation starts when preadipocytes differentiate into mature adipocytes. Peroxisome proliferator-activated receptor gamma (PPARg) and CCAAT-enhancer-binding protein alpha (C/EBPa) are known to be central to white adipose tissue adipogenesis [14]. Other signaling pathways in the regulation of adipogenesis have been identified, such as activation of insulin-like growth factor 1 (IGF1) [15,16], cyclic adenosine monophosphate (cAMP) [17], and bone morphogenetic proteins (BMPs) signaling [18]. In contrast, inhibitory effects were observed from transforming growth factor beta (TGFb) signaling [19], WNT signaling [20], and retinoblastoma protein (Rb) signaling [21]. The presence of branched-chain amino acids (BCAA), including leucine, isoleucine, and valine, has been proven essential for driving adipogenesis in 3T3-L1 cells as they serve as a source of acetyl-coenzyme A for lipogenesis [22,23]. The inhibition of BCAA catabolism obstructs adipogenesis. However, the effect of other essential amino acids on the adipogenic process has rarely been studied. L-lysine is an essential amino acid that plays a vital role in anxiogenic behavior in humans and rodents [11,24]. Interestingly, the effect of lysine depletion on adipogenesis is controversial, particularly species-specific. Low lysine treatment stimulates bovine stromal vascular cells and intramuscular preadipocyte adipogenesis [25,26]. In mice, low lysine concentrations suppress adipogenesis in 3T3-L1 preadipocytes via the inhibition of PPARg [27], and the underlying mechanisms of lysine-deprivation-induced transcriptome changes in adipocyte differentiation have not been solved.
|
| 56 |
+
|
| 57 |
+
We herein performed RNA sequencing on 3T3-L1 preadipocytes in different statuses, including undifferentiated, differentiated, and differentiated with lysine depletion (Figure 1A). The transcriptome data were compared among groups with Kyoto Encyclopedia of Genes and Genomes (KEGG) database enrichment to screen out possible pathways induced by lysine deprivation and distinguish which pathways were critical for adipogenesis, and which pathways were triggered by the differentiation process but were irrelevant to the adipogenic process. We also discovered that the suppression of adipogenesis is not limited to lysine depletion but also applies to other essential amino acids such as methionine and cystine.
|
| 58 |
+
|
| 59 |
+
2. Results
|
| 60 |
+
|
| 61 |
+
2.1. Lysine Deprivation Suppressed Adipogenesis
|
| 62 |
+
|
| 63 |
+
To examine the effect of lysine starvation on 3T3-L1 cell differentiation, cells were cultured in a differentiation medium containing dexamethasone (Dex), 3-isobutyl-1-methylxanthine (IBMX), rosiglitazone (Rosig), and insulin in the presence or absence of 800 μM lysine (Figure 1A). Oil-Red O (ORO) staining was performed 3 days after the differentiation, demonstrating that the adipogenesis process was significantly inhibited in cells treated with lysin-deficient medium (Figure 1B). Coherent with the suppressed differentiation, the expressions of adipogenic and lipogenic genes such as fatty acid synthase (FASn), stearoyl-coenzyme A desaturase (SCD1), sterol regulatory element binding transcription factor 1 (SREBF1), and PPARg were found to be dramatically downregulated (Figure 2C,D). Cell viability assay demonstrated that there was no difference between cells cultured in normal and lysine-free medium (Figure 1C), proving that the suppression of adipogenesis is not related to reduced cell number. We also confirmed that cells could respond to lysine in a dose-dependent manner (Figure 1D), suggesting that cells sense the level of lysine in the environment. To ensure the absence of lysine in the culture medium, we measured the levels of major amino acids in the medium before and after lysine-free treatment using mass spectrometry. The lysine concentration in the lysine-free medium was ~19 μM before adding the cells (less than 3% of the normal concentration), and the level dropped to ~1 μM after 3 days of culture (around 0.2% against the control group without lysine depletion). We, hence, defined it as a lysine-free group. The absolute quantification of the amino acids and changes in individual amino acids in the medium was summarized in (Figure 1E and Supplementary Figure S1). Surprisingly, we found that the amino acid levels in the medium were dramatically distorted when cells were cultured in a lysine-depleted medium, suggesting a disruption of amino acid metabolism. Results showed that lysine was constantly absent in the medium before and after treatment. Other than the depletion of lysine, amino acids including glycine, asparagine, alanine, proline, aspartic acid, and glutamic acid were dramatically increased after 3 days of the absence of lysine (Supplementary Figure S1B). The concentrations of arginine, histidine, isoleucine, leucine, methionine, and valine in the medium were not greatly altered after the lysine-free culture, yet the control group consumed these amino acids in the medium. Meanwhile, the levels of glutamine, serine, and cystine were the same as in the control group and had not been altered (Supplementary Figure S1B). These results indicated the induction of a global alteration in amino acid metabolism or excretion via single amino acid deprivation.
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2.2. Transcriptome Profile of the 3T3-L1 Cells
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To unveil the underlying mechanism of how lysine deprivation inhibited adipogenesis, we performed RNA sequencing on cells in the undifferentiated group (Undifferentiated), differentiated group (Differentiated), and the differentiated group treated under lysine-free condition (Lysfree), with n = 3 for each group. An average of 45.32 million raw reads were generated from the samples (ranging from 39.86 million to 54.72 million), while the average clean reads were 44.4 million. From a stringent quality check, >93% of the obtained reads had a quality score of ≥Q30. The heatmap (Figure 2A) and PCA plot (Figure 2B) of all samples proved that the samples were highly consistent within groups and distinctly separated among treatment groups. Adipogenic and lipogenic genes, including FASn, SCD1, SREBF1, and PPARg, were chosen as a quality control against qPCR (Figure 2C). These critical genes that were quantified by RNAseq were in high coherence with the data from the qPCR in magnitude, and all genes were significantly suppressed under lysine deprivation (Figure 2D). The protein level of nuclear transcription factors SREBF1 and PPARg were quantified by Western blot (Supplementary Figure S2), and confirmed the same trend as the data from the RT-PCR and RNAseq.
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2.3. Comparison between Differentiated and Undifferentiated 3T3-L1 Cells
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The differentiated 3T3-L1 cells had 4864 differential expressed genes (DEGs), with 2544 genes downregulated and 2320 genes upregulated (Figure 3A). A KEGG pathways analysis showed that the differentiated cells had the most significant alteration in carbon metabolism and metabolic pathways, and mitochondria-related pathways (Figure 3B). A further analysis of the upregulated and downregulated DEGs individually demonstrated that most of the top altered pathways were upregulated. In the top 10 significantly enriched pathways (Figure 3B), 9 out of 10 were upregulated, and the only downregulated pathway was lysosome. Many of the upregulated pathways were metabolism-related, such as carbon, pyruvate, fatty acid metabolism, and mitochondria-correlated pathways that involved the TCA cycle and oxidative phosphorylation (Figure 3C). As demonstrated by the PPI network, the NADH:ubiquinone oxidoreductase subunit family (Nduf) was highly intercorrelated in several pathways, including Ndufb1, Ndufab1, Ndufb5, Ndufv1, Ndufv2, Ndufb8, Ndufa5, Ndufb6, Ndufc2, and Ndufs1, which were involved in the mitochondria respiratory chain (Figure 3E). The most enriched downregulated pathway was the lysosome pathway (Figure 3D), and surprisingly, PPI network analysis did not reveal any intercorrelation of the lysosome pathway with other pathways; instead, other intercorrelated pathways, including the Rap1 signaling pathway, PI3K-Akt signaling pathway, and AGE-RAGE signaling pathway, were found. Collagen and collagenase-related genes such as matrix metalloproteinase 9 (MMP9), MMP2, collagen type A1 (Colla1), and Colla2 (Figure 3F) were identified. These results suggested that the differentiation of 3T3-L1 dramatically activated metabolic pathways, especially carbon metabolism, which involved mitochondria, while the lysosome pathway was inhibited.
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2.4. Identification of Lysine-Depletion-Induced Pathways
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To dissect the lysine-deprivation-induced pathways that inhibited 3T3-L1 adipogenesis, we first compared the lysine-free group against the undifferentiated group (Lysfree vs. Undifferentiated). The DEGs obtained represented lysine-free-induced genes and genes induced by the differentiation medium but not involved in the adipogenesis process (Figure 4A). PPI analysis of the DEGs screened out the ribosome biogenesis pathway and purine and pyrimidine metabolism, which were upregulated, while the PI3K-Akt signaling pathway and ECM–receptor interaction were downregulated (Supplementary Figure S3A). The lysine-free group and the differentiated group were also compared (Lysfree vs. Differentiated). The DEGs obtained represented lysine-free-induced genes and genes that were critical for blocking adipogenesis (Figure 4B). PPI analysis on DEGs demonstrated that genes were downregulated in many metabolic pathways, especially carbon metabolism and mitochondria-related pathways such as the TCA cycle and oxidative phosphorylation (Supplementary Figure S3B). Moreover, interleukin 6 (IL6) was identified to have been significantly and dramatically upregulated in comparison with the undifferentiated or the differentiated groups (Supplementary Figure S3C). The DEGs from the two comparisons were then overlapped by Venn diagrams (Figure 4C), and the overlapped DEGs were considered as lysine-free-induced genes. Other than overlapping the DEGs of the two groups, we also individually analyzed the upregulated (Figure 4D) and downregulated DEGs (Figure 4E) to screen out the lysine-free enhanced and suppressed pathways, respectively.
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The overlapped DEGs representing lysine-free-induced genes (Figure 5A) are presented in Figure 5. KEGG analysis demonstrated that the most enriched pathway was vitamin digestion and absorption, while the highest gene counts were metabolic pathways (Figure 5B). In terms of upregulated genes, vitamin digestion and absorption was the top enriched pathway (Figure 5C). For downregulated DEGs, the most enriched pathway was alanine, aspartate, and glutamate metabolism, and the highest gene counts were the metabolic pathway (Figure 5D). We further dissected the 60 genes in metabolic pathways using Metascape (https://metascape.org/gp/index.html#/main/step1, accessed on 1 February 2023). Most of the metabolic pathways were found to be correlated with amino acid metabolism (particularly beta-alanine, tyrosine, phenylalanine, histidine, alanine, aspartate and glutamate, valine, leucine, and isoleucine metabolic pathways), and carbon metabolism pathways (including glycolysis/gluconeogenesis, glucagon signaling, and pyruvate metabolism) (Figure 5E). These results clearly showed that lysine deprivation specifically and strongly suppressed amino acids and carbon metabolism pathways in differentiated 3T3-L1 cells. PPI network analysis of the downregulated genes screened out dehydrogenase (including ADH1, Aldh6a1, Aldh3a1, and Aldh3b2), nitric oxide synthase (Nos1 and Nos3), and Slc2a4, an insulin-sensitive glucose transporter (known as glucose transporter 4, GLUT4) (Figure 5F).
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2.5. Genes Critical for Inhibition of 3T3-L1 Cell Differentiation and Adipogenesis
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To investigate the genes that were essential for the suppression of adipogenesis, DEGs between the Lysine-free and Differentiated groups, excluding the lysine-free-induced genes, were enriched with KEGG (Figure 6A). Interestingly, the results were opposite in the DEGs between the differentiated and undifferentiated groups (Figure 3). Eight out of the top ten enriched pathways were found to have been downregulated, and the majority of them were metabolic pathways, especially the mitochondria-related pathways, including carbon metabolism, oxidative phosphorylation, TCA cycle, and fatty acid metabolism (Figure 6D). To verify the functional impact in the suppression of mitochondrial TCA cycle and oxidative phosphorylation, we examined the mitochondrial ATP synthesis on 3T3-L1 cells using Agilent Seahorse XF ATP Real-Time rate assay. Concomitant with the transcriptomic data, a significant reduction in ATP synthesis was detected (Supplementary Figure S4), proving the consistency between transcriptomic and cellular functional changes. The most upregulated pathway was the lysosome pathway (Figure 6C). These results provided evidence to support the critical role of carbon metabolism, mitochondria function, and lysosome in the adipogenesis process.
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2.6. Pathways That Could Be Altered by Differentiation Medium but Not Critical for the Adipogenesis Process
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We also examined the pathways that were altered by the differentiation medium but were not related to adipogenesis by enriching the DEGs between the Lysine-free and Undifferentiated groups, excluding lysine-free-induced genes (Figure 7A). The ribosome biogenesis, pyrimidine, and purine metabolism pathway was the most enriched upregulated pathway (Figure 7B,C), and it was also identified to be upregulated in the Lysine-free group against the Undifferentiated group (Supplementary Figure S3A), suggesting that these pathways were upregulated accompanied with cell differentiation medium but they were not critical for 3T3-L1 cells adipogenesis. We also found enriched downregulated pathways such as the Rap1 signaling pathway, the PI3K-Akt signaling pathway, and ECM–receptor interaction (Figure 7D) that were the same as the downregulated KEGG pathways in comparing the Differentiated and Undifferentiated group (Figure 3D), proving that these pathways were not important for 3T3-L1 adipogenesis, just for the cellular response to differentiation medium.
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2.7. Suppression of Adipogenesis Is Not Limited to Lysine Depletion but Also Applied to Methionine and Cystine Deprivation Partially via IL6 Overexpression
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We have identified that IL6 was overexpressed in cells exposed to a lysine-free environment (Supplementary Figure S3). To explore whether IL6 could be one of the mechanisms for the suppression of adipogenesis, we first examined the IL6 level in the culture medium. Results showed that the medium IL6 level was dramatically increased 8-fold (Figure 8B) in the medium when cells were cultured under lysine starvation, and the upregulation was inversely proportional to medium lysine concentration (Supplementary Figure S5A). We found that such overexpression of IL6 is reversible after refeeding the cells with 800 μM lysine (Supplementary Figure S5B,C). To test whether such an increase in IL6 could contribute to the inhibition of adipogenesis, we added an equivalent amount of IL6 (1 ng/mL) in the medium during differentiation and examined the adiposity by Oil-Red O staining. We found that the cellular triglyceride content was partially suppressed (Figure 8C). We also tested whether such phenomena can be observed in other amino-acid-depleted conditions. Other than lysine depletion, a medium lack of essential amino acid methionine and cysteine individually could also suppress the adipogenesis process on 3T3-L1 cells, the same as lysine deprivation (Figure 8D). Coincidentally, the IL6 level in the medium was significantly upregulated in an amino acid depletion environment (Figure 8E), suggesting that the phenomenon is not just lysine-specific but also applicable to other essential amino acids.
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3. Discussion
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The current descriptive study is consistent with previous findings that showed that mRNA expressions of PPARg (Figure 2C,D) and C/EBPa (Supplementary Figure S6A) were inhibited in cells cultured in a low-lysine environment [27]. On the other hand, gene expressions of C/EBPb and C/EBPd were not downregulated by lysine deprivation in the culture medium (Supplementary Figure S6A). These results indicate that lysine depletion in the culture medium inhibited the differentiation of 3T3-L1 preadipocytes mainly by inhibiting the mRNA expressions of PPARg and C/EBPa. RNA-seq data comparing differentiated and undifferentiated 3T3-L1 cells were reported by Sun et al. [28]. Although our experimental design was not exactly the same, we found that our findings match their reported data. Trpv4, Trpm4, and Trpm5 were significantly downregulated, while Trpv1, Trpv2, and Trpc1 significantly increased in differentiated adipocytes (Supplementary Figure S6B,C).
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To examine whether lysine starvation could enhance the cellular lipid breakdown, we checked the transcription of the three major lipases, adipose triglyceride lipase (ATGL), hormone-sensitive lipase (HSL), and monoacylglycerol lipase (MGL), in the lipolysis pathway, which breaks triglyceride into glycerol and free fatty acid. Surprisingly, all three genes were significantly suppressed under lysine depletion (Supplementary Figure S7). Results suggest that lysine depletion could inhibit adipogenesis but not enhance lipolysis. Lipid metabolism is overall impaired in lysine-deficient conditions. The alteration of lipid metabolism by amino acid depletion has been reported in animal models. It has been shown that a deficiency in BCAAs including leucine, isoleucine, and valine individually can stimulate lipolysis in white adipose tissue [29,30]. Lysine deprivation, however, did not demonstrate such a change in lipolysis [11]. The controversy between the current and the reported in vivo data on lipolysis suggests that amino acid depletion in vivo is much more complex than in in vitro models, particularly the degree of amino acid depletion in the bloodstream and in the cells.
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The effect of lysine depletion on body composition in vivo is also controversial. In rats, lysine depletion can reduce body weight, fat mass, and lean mass [2,31]. Interestingly, pigs fed a lysine-depletion diet demonstrated a lower relative proportion of lean components; however, higher carcass fatty components were obtained, together with increased lipogenic genes [32]. Since lysine is an essential amino acid, long-term lysine depletion can be harmful, and currently, no human data are available.
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3T3-L1 cells could be the target cells for IL6. We identified that IL6 gene expression was significantly upregulated in a lysine-free environment (Supplementary Figure S3C). Coherent with the transcriptomic data, we found that the IL6 level in the culture medium was dramatically increased after treatment with a lysine depletion medium for 3 days (Figure 8B). To test whether the increased IL6 level could suppress the adipogenesis of 3T3-L1 cells, we added an equivalent amount of IL6 (1 ng/mL) in the medium during differentiation and examined the adiposity of cells. Surprisingly, the differentiation process was partially inhibited, suggesting that IL6 upregulation is one of the mechanisms for the lysine depletion environment to suppress adipogenesis (Figure 8C). IL6 has emerged as a crucial cytokine involved in metabolism regulation. It was reported that 3T3-L1 cells treated with IL6 displayed fewer lipids [33]. Furthermore, IL6 treatment led to decreased mitochondrial membrane potential, decreased cellular ATP production, and increased intracellular ROS levels. Consistent with previously published findings, we found that peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PPARGC1a) and nuclear respiratory factor 1 (NRF1) expression levels were markedly increased, an upregulation triggered by IL6 (Supplementary Figure S8A) [33]. Additionally, the gene transcription of insulin receptor substrate 1 (IRS-1), solute carrier family 2 member 4 (called Slc2a4 or glucose transport 4) (Supplementary Figure S8B), and PPARg (Figure 2C,D) were found to be significantly inhibited in cells under lysine depletion, a phenomenon that was also observed in 3T3-L1 cells treated with exogenous IL6 [34]. IRS-1 is responsible for insulin signaling, Slc2a4 is essential for the cellular glucose uptake, and PPARg is the key gene for adipogenesis. The expression of all these genes is essential for the formation of lipid droplets and the maturation of adipocytes. In animal models, during obesity development, IL6 production in adipose tissues is consistently elevated, especially in insulin-resistance adipocytes [35,36]. Such IL6 overexpression reduced subcutaneous adipocyte adipogenesis capacity with suppressed PPARg and C/EBPa expression [35], which is similar to our in vitro findings. However, how lysine, methionine, and cysteine depletion regulate IL6 levels is still unknown and worth investigating. We hypothesize that oxidative stress may be associated with IL6 overexpression. Lysine level was found to be correlated with antioxidant capacity [37]. Deficiencies in methionine and cysteine can affect the transsulfuration pathway and greatly reduce antioxidant glutathione production [38]. It has been reported that total glutathione levels were decreased by 42% in melanoma cells grown without methionine, and by 95% in cells grown without cysteine [39]. Importantly, oxidative stress can induce insulin resistance in adipocytes and dramatically increase IL6 secretion in 3T3-L1 cells 3-fold [40,41].
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Amino acid deprivation increases energy expenditure and reduces food intake and fat mass, primarily through the regulation of the general control nonderepressible 2 (GCN2) and mammalian target of rapamycin (mTOR) signaling. GCN2 and mTORC1 signaling pathways have been extensively studied for their regulation by amino acids, especially in the control of translation. GCN2 activated by uncharged tRNA during scarcity of amino acid can phosphorylate the α-subunit of eukaryotic initiation factor 2 (eIF2a) [42,43] and promote the translation of certain mRNAs by activating transcription factor 4 (ATF4) [44], which plays a key role in the adaptation of the cells to the lack of amino acids [45]. Surprisingly, we did not find any significant changes in GCN2, eIF2a, or downstream ATF4 expression. This phenomenon may indicate that 3T3-L1 cells cultured under a lysine deprivation medium may not really be under intracellular amino acid shortage but have other cellular changes to overcome the amino acid scarcity. We found that the lysosome pathway was strongly upregulated in both undifferentiated cells (Figure 3D and Supplementary Figure S9) and lysine-free-treated cells (Figure 6C). Lysosomes are an important component of the inner membrane system and participate in numerous cell biological processes, such as macromolecular degradation, intracellular pathogen destruction, plasma membrane repair, exosome release, and apoptosis [46]. The increase in lysosome might break down unused intracellular protein or damaged organelles to recycle some amino acids, which could provide an extra source of lysine for cell survival. Interestingly, we found that some lysosomal proteases such as Legumain (LGMN), tripeptidyl peptidase 1 (TPP1), and Cathepsin (CTS) (Supplementary Figure S9B,C) were upregulated, which could be one of the reasons for the increased amino acids in the medium, as described in Figure 1E and Supplementary Figure S1. Another lysosomal amino-acid-sensing pathway is the mammalian target of rapamycin (mTOR) pathway; however, no changes in the whole pathway, including amino-acid-sensing protein CASTOR1, regulatory-associated protein of mTOR (Raptor), mTOR, downstream S6 Kinase 1 (S6K1), and translation initiation factor 4E binding protein (4EBP), were observed. The activation of mTOR signaling involved the phosphorylation of proteins instead of gene expression. Further proteomic studies are required to confirm the mTOR signaling pathway and other significant DEGs identified.
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Various beneficial effects of dietary amino acid restriction, including anti-obesity, anticancer, and anti-aging effects in both obese patients and animal models, have been proven [47,48]. For example, it has been shown that dietary methionine restriction could prevent obesity. Methionine restriction by 80% decreased fat mass and body weight, primarily through fibroblast growth factor 21 (FGF-21) signaling [49,50]. More recently, it was shown that the oral intake of methioninase (METase), an enzyme catabolizing methionine, could significantly prevent the development of obesity symptoms and could be used as an anticancer treatment, demonstrating the potential for using amino-acid-depleting enzymes as therapeutic agents [51,52]. Moreover, the injection of pegylated arginine deaminase (ADI-PEG), an arginine-depleting enzyme, also demonstrated similar effects [53]. L-lysine oxidase, an enzyme that converts L-lysine to 6-amino-2-oxohexanoate, NH3, and H2O2, has been applied in in vivo in cancer treatment. L-lysine oxidase treatment completely inhibited the growth of mouse leukemic cells in vitro [54]. An intravenous injection of L-lysine oxidase to mice suffering from leukemia increased their average lifespan compared with the control animals [55]. We predicted that, like METase and ADI, L-lysine oxidase could be another candidate enzyme drug to combat obesity and aging. In animal studies, dietary lysine deprivation has been proven to decrease food intake and increase energy expenditure [6] mediated by enhanced serotonin release from the amygdala in rats [56].
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4. Materials and Methods
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4.1. Cell Culture
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3T3-L1 cells were obtained from ATCC. They were maintained in DMEM (Gibco, New York, NY, USA, #12800017) with 10 % BCS (Gibco, #16170078) at confluence for 3 days. The cells were then stimulated with a Differentiation medium (arginine and lysine-free DMEM (Gibco, #88364) supplemented with 10%FBS (Gibco, #26140-079), 800 μM lysine (Sigma, Marlborough, MA, USA), 400 μM arginine (Sigma), 1 μM dexamethasone (DEX, Sigma), 0.5 mM 3-isobutyl-1-methylxanthine (IBMX, Sigma), 1 μM rosiglitazone (Rosig) (Cayman, Ann Arbor, MI, USA), and 10 μg/mL insulin (Sigma)) to induce adipocyte differentiation. After differentiation, the medium was replaced with Maintenance medium (DMEM (Gibco, #12800017) supplemented with 10 % FBS (Gibco, #26140-079) and 10 μg/mL insulin) for 3 days. For lysine-free treatment, confluent pre-adipocytes were treated with a Differentiation medium without lysine addition during the differentiation, and the lysine-free treatment was stopped after the differentiation period. For the dose-dependent study, various concentrations of lysine (as indicated in Figure 1D) were supplemented during differentiation. For methionine and cystine depletion, the DMEM in the Differentiation medium was substituted with DMEM, no glutamine, no methionine, and no cystine (Gibco, #21013-024), supplemented with 4 mM glutamine (Sigma) and either 200 μM methionine (Sigma) or 200 μM cysteine (Sigma). Cells and medium were collected for RNA extraction and IL6 quantification after differentiation. Medium IL6 concentration was determined by a mouse IL6 ELISA assay kit (Invitrogen, Waltham, MA, USA). Cell viability was determined using MTT assay. Oil-Red O staining was performed after the maintenance period to check the cell adiposity.
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To examine the effect of IL6 on 3T3-L1 cell adipogenesis, cells were differentiated in DMEM (Gibco, #12800017) supplemented with 10%FBS (Gibco, #26140-079), 1 μM dexamethasone, 0.5 mM IBMX, 1 μM Rosig, and 10 μg/mL insulin with or without the addition of 1 ng/mL IL6 (Sigma) for 3 days. To test whether the upregulation of IL6 is reversible, cells were first differentiated for 2 days and refed with 800 uM lysine for 1 day.
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4.2. RNA Extraction, cDNA Synthesis, and RNA Sequencing
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The total RNA was isolated using the total RNA extraction kit (Favorgen, Pingtung, Taiwan) following the manufacturer’s instructions. Both qualities and quantities were measured using Bioanalyzer 2200 (Agilent Technologies, Santa Clara, CA, USA). The sequencing library of each sample was built using poly A enrichment preparation by the sequencing service provider Novogene (Beijing, China). Sequencing was performed using the NovaSeq (Beijing, China) PE150 platform with 150 bp paired-end reads generated. Low-quality reads (Qscore > 50% of the read) and reads with adaptors were removed to obtain clean data. The clean data were mapped to the mouse genome version 10 (mm10) using the HISAT2 algorithm with default parameters. RNAseq raw data are available in GEO database with accession number GSE223846.
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4.3. Differentially Expressed GENES (DEG) Analysis
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DESeq2 algorithm on OmicsBeam (http://omicsbean.cn/, accessed on 1 February 2023) was used to identify the differentially expressed genes (DEGs) in various treatment groups. DEGs were defined as showing a ≥2-fold change and padj < 0.05. Raw count values greater than 0 in any group were used. Principal component analysis (PCA) and hierarchical clustering were carried out to assess the variability in and repeatability of samples using the normalized RNA-Seq read counts. A volcano plot was used to visualize the overall distribution of DEGs.
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4.4. Functional Annotation Analysis
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Pathway analysis was used to highlight the significant pathways of the DEGs using the Kyoto Encyclopedia of Genes and Genomes database (KEGG, http://www.genome.jp/kegg/, accessed on 1 February 2023) [57], which stores information on how molecules and genes are networked, for pathway mapping. Pathways showing adjusted p-values < 0.05 were selected.
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4.5. Integration of Protein–Protein Interaction (PPI) Network and Module Analysis
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The Search Tool for the Retrieval of Interacting Genes (STRING) (http://string-db.org, accessed on 1 February 2023) [58] is an online tool designed for evaluating the differentially expressed mRNA-encoded proteins and PPI. The OmicsBean was used to construct a protein interaction relationship network and analyze the interaction relationships of differentially expressed candidate genes based on the STRING analysis results.
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4.6. Real-Time PCR Analysis
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Real-time PCR was performed using a high-capacity cDNA Reverse Transcription Kit (Applied Biosystem) to synthesize cDNA. Real-time PCR was performed on Real-Time System QS7 (Applied Biosystem, Waltham, MA, USA) with Powerup SYBR (Applied Biosystem) according to the manufacturer’s instructions. TATA box binding proteins (Tbp) were used as housekeeping genes. The (2−ΔΔCt) method was used to calculate the gene expression levels. The primer sequence of target genes and internal control Tbp are summarized in Table 1.
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4.7. Oil-Red O (ORO) Staining
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To examine the lipid droplets, ORO staining was performed. Briefly, the adipocytes were washed twice with PBS. Cells were then fixed with 10% formaldehyde for 15 min at room temperature, followed by PBS wash. Then, the cells were stained with freshly prepared ORO working solution in 60% isopropanol for 20 min. After staining, the images were captured with an Axiovert 40 CFL Zeiss microscope (Carl Zeiss, Baden-Württemberg, Germany) at a magnification of 40×. The intracellular lipid content was quantified by measuring the absorbance at 490 nm.
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4.8. Medium Amino Acid Analysis
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To determine the concentration of amino acids in the medium, Kairos Amino Acid Kit (Waters Corporation, Milford, MA, USA) was used. Briefly, 50 µL samples were mixed with 50 µL of Internal Standard and 50 µL of water and centrifuged for 15 min at 9000× g. Then, 10 microliter supernatant was collected and mixed with 70 µL of Borate buffer in a maximum recovery vial. The solution was derivatized by 20 µL AccQ-Tag reagent and then heated for 10 min at 55 °C. After the derivatization, 2 µL samples were analyzed by Agilent 6460 Triple Quadrupole liquid chromatography/mass spectrometry (Agilent Technologies, CA, USA).
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4.9. Western Blotting
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Twenty milligrams of cell protein lysate was resolved by SDS-PAGE and transferred to nitrocellulose membranes (Bio-Rad, Hercules, CA, USA) following standard protocol. Primary and secondary antibodies: PPARg (CST, Fall River, MA, USA, #2435), SREBF1 (Thermofisher, Waltham, MA, USA, #MA511683), GAPDH (CST, #2118), and HRP goat anti-rabbit secondary antibody (CST, #7074). The bands were captured using X-ray film (Fujifilm, Tokyo, Japan) exposed by chemiluminescent HRP substrate (Millipore, Burlington, MA, USA).
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4.10. Agilent Seahorse XF ATP Real-Time Rate Assay
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3T3-L1 cells were cultured in XFe96 cell culture microplate (Agilent) following previously described with the 3 groups, undifferentiated, differentiated, and lysine-free. After the differentiation stage, cells were subject to Agilent Seahorse XF ATP Real-Time rate assay following manufacturer’s protocol. In brief, basal oxygen consumption rate (OCR) was first monitored followed by addition of 15 μM Oligomycin to block the mitochondrial ATP synthase. The reduction in OCR representing the mitochondrial ATP synthesis was calculated using software Wave (Agilent Technologies, CA, USA).
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5. Conclusions
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The current research described the transcriptomic changes in 3T3-L1 cells in the absence of lysine in a culture medium. Other than traditionally identified pathways, we found that mitochondria and lysosome pathways were critical for adipocyte differentiation. Cells cultured under a lysine-depleted environment triggered the disruption of amino acid and carbon metabolism. We also identified that IL6 was overexpression in lysine-free conditions and can partially suppress the adipogenesis process in 3T3-L1 cells. Functional and proteomic studies are worth conducting to further confirm the findings in the current research. Our new findings shed light on the importance of manipulating amino acids as therapeutic targets against obesity and provide evidence to support the use of lysine-depleting enzymes for therapy.
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Acknowledgments
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We thank Alisa Shum (CUHK) and Tommy Lam (HKU) for useful discussion.
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Supplementary Materials
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The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms24119402/s1.
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Click here for additional data file.
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Author Contributions
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L.M.-Y.L. and Z.-Q.L. contributed equally as the first author. Conceptualization, Z.-Q.L. and L.M.-Y.L.; Cell culture and RNA preparation, Z.-Q.L.; Mass spectrometry, Y.-F.T. and Y.-H.S.; RNAseq analysis, L.-X.Z., Y.-F.T. and X.-H.Z.; writing—introduction, T.-J.F.; writing—methodology: X.-Y.W.; writing—results and discussion, L.M.-Y.L.; writing—review and editing, L.M.-Y.L. and Y.-C.L.; figures preparation, W.-T.W.; supervision, L.M.-Y.L. and Y.-C.L. All authors have read and agreed to the published version of the manuscript.
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Institutional Review Board Statement
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Not applicable.
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Informed Consent Statement
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Not applicable.
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Data Availability Statement
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RNAseq raw data are available in the GEO database with access number GSE223846.
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Conflicts of Interest
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The authors declare no conflict of interest.
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Figure 1 Lysine depletion during the 3T3-L1 cell differentiation period suppressed adipogenesis and altered amino acid metabolism. (A) The schematic diagram demonstrates the experimental design; lysine-free medium was applied only in the differentiation period. (B) Reduction in lipid formation in lysine-free treatment was found 3 days after differentiation by Oil-Red O (ORO) staining. (C) Cell viability of the cells determined by MTT assay. Data are expressed as means ± SE with n = 3 in each condition. * p <0.05 using the Mann–Whitney U test. (D) 3T3-L1 cell response to lysine concentration in a dose-dependent manner (800, 80, 8, 0.8, and 0.08 μM). Data are expressed as means ± SE with n = 3 in each condition. Correlation was analyzed using Pearson’s correlation test. (E) Heatmap of amino acid content in culture medium before and after treatment.
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Figure 2 RNAseq data were highly consistent within the group and coherent with real-time qPCR data. (A) Heatmap of all genes in samples of the 3 groups, including undifferentiated, differentiated, and lysine-free (Lysfree). (B) PCA plot showing that the samples within the group were highly stable. (C) qPCR of the representative adipogenic genes FASn, SCD1, SREBF1, and PPARg. (D) The expression level of the adipogenic genes in fpkm from RNAseq analysis. Data are expressed as means ± SE with n = 3 in each condition. *** p < 0.001 using the one-way ANOVA followed by the Bonferroni test.
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Figure 3 DEGs analysis from the differentiated group against the undifferentiated group. (A) Volcano plot presenting the distribution of DEGs with 2320 genes upregulated and 2544 genes downregulated. (B) KEGG enrichment of all DEGs. (C) KEGG enrichment of the upregulated DEGs. (D) KEGG enrichment of the downregulated DEGs. (E) PPI analysis of the upregulated pathways. (F) PPI analysis of the downregulated pathways.
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Figure 4 Venn diagram identifying DEGs specifically induced by lysine depletion, genes inhibited adipogenesis, and genes induced by differentiation medium but not critical for adipogenesis. (A) Volcano plot presenting the comparison between Lysfree and Undifferentiated groups with 1277 genes upregulated and 1965 genes downregulated. (B) Volcano plot presenting the comparison between Lysfree and Differentiated groups with 1917 genes upregulated and 2362 genes downregulated. (C–E) Venn diagram overlapping (C) all DEGs identified, (D) all upregulated DEGs identified, and (E) all downregulated DEGs identified.
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Figure 5 Lysine depletion dramatically downregulated amino acids and carbon metabolic pathways. (A) Venn diagram showing the portion of DEGs analyzed. (B–D) KEGG enrichment of DEGs induced by lysine-auxotroph: (B) all DEGs, (C) the upregulated DEGs, and (D) the downregulated DEGs. (E) KEGG enrichment of the downregulated DEGs from the metabolic pathways. (F) PPI analysis of the downregulated metabolic pathways.
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Figure 6 Suppression of metabolic pathways and upregulation of lysosome pathway were identified as critical transcriptomic changes for the inhibition of the adipogenesis process. (A) Venn diagram showing the portion of DEGs analyzed. (B–D) KEGG enrichment of DEGs, (B) all DEGs, (C) the upregulated DEGs, and (D) the downregulated DEGs.
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Figure 7 Identification of pathways that did not play any functional roles in adipogenesis but were induced during cell differentiation. (A) Venn diagram showing the portion of DEGs analyzed. (B–D) KEGG enrichment of DEGs, (B) all DEGs, (C) the upregulated DEGs, and (D) the downregulated DEGs.
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Figure 8 IL6 level in the medium was significantly increased in 3T3-L1 cells cultured under amino acid depletion medium for 3 days. (A) The schematic diagram demonstrated the experimental design. (B) IL6 level in medium raised in cells cultured under lysine-free medium. Data presented as pg/mL (left) and pg/mg cell protein (right). (C) Adipogenesis was partially suppressed by treatment with 1 ng/mL IL6 in the medium during the differentiation period. Data are expressed as means ± SE with n = 4 in each condition * p < 0.05, Mann–Whitney U test. (D) Methionine and Cystine depletion (Metfree and Cysfree) suppressed the adipogenesis of 3T3-L1 cells. (E) IL6 concentration in the medium was increased in cells cultured under Metfree and Cysfree environments. For (B,D,E), data are expressed as means ± SE with n = 3 in each condition * p < 0.05, one-way ANOVA followed by the Bonferroni test.
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ijms-24-09402-t001_Table 1 Table 1 Primer sequence for qPCR.
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Gene Forward Reverse
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FASn CCCAGCGGTAGAGAATAGCA GGGTCCACTAAACTGAGCCT
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SCD1 TCCAACTCATGTGCCTCTGT AACAACCAACCCTCGCATTC
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SREBF1 TTGTTCCTTTGCCTTCCAGC GATGCCGACCAGATTCCCTA
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PPARg TGACAGACCTCAGGCAGATC AGAAGGAACACGTTGTCAGC
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IL6 TCCTTCCTACCCCAATTTCCA GTCCACAAACTGATATGCTTAGG
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Tbp TGCTGTTGGTGATTGTTGGT ACTGGGAAGGCGGAATGTAT
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Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
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==== Refs
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