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gene expression
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Bioinformatics : Drawbacks of using ORA(Overlap Analysis)
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https://biology.stackexchange.com/questions/15058/bioinformatics-drawbacks-of-using-oraoverlap-analysis
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<p>What do you think are the potential drawbacks/weakness of using ORA to explain distinction between two phenotypes.</p>
<p>I identified a few which were the dependencies of DE and the statistical method used to filter the starting DE list.</p>
<p>Any other weakness?</p>
<p>Thanks</p>
|
<p>It really depends on the specific methods you're using. If you're using a pathway-based methodology, I'd strongly recommend reading Khatri et al (2012) (<a href="http://www.ploscompbiol.org/article/info%3adoi/10.1371/journal.pcbi.1002375" rel="nofollow" title="Khatri et al (2012)">1</a>), which provides a good overview. </p>
<p>The main issue that's not touched on in that work is that pathway-based methods are highly dependent on the pathway definitions used, and the contents of the pathways are not always what you might expect in terms of their topology (a good example is KEGG's Neuroactive ligand-receptor interaction (<a href="http://www.genome.jp/kegg-bin/show_pathway?map=hsa04080&show_description=show" rel="nofollow">2</a>), which contains a huge number of events that look like 'single ligand binds to receptor', with no downstream events).</p>
| 34
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gene expression
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Is the regulation of lactose operon different between Gram + and Gram -?
|
https://biology.stackexchange.com/questions/15125/is-the-regulation-of-lactose-operon-different-between-gram-and-gram
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<p>I know that in E. coli the lactose operon is shut down by CAP protein when binding cAMP. Is this true also for Gram positive bacteria?</p>
|
<p>I know it's stupid but I answer my own question, for those who are interested.
It is different. CAP protein regulates lactose operon only in Gram -. In Gram + the presence of glucose shuts down the operon with another mechanism: the TCRS that relies to concentration of fructose 1,6 phosphate.</p>
| 35
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gene expression
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What is the significance of and biological mechanisms demonstrated in lac operon?
|
https://biology.stackexchange.com/questions/15406/what-is-the-significance-of-and-biological-mechanisms-demonstrated-in-lac-operon
|
<p>I would appreciate it someone could explain clearly how the genes in the <a href="http://en.wikipedia.org/wiki/Lac_operon" rel="nofollow"><em>lac</em> operon of E coli</a> are activated to allow the bacteria to metabolize lactose? </p>
<p>The part that I really don't understand is the activation of the lac operon. A good answer would make clear to me how the introduction or removal of lactose from the envirnment activates and deactivates the different genes there. </p>
<p>Also, what are the specific functions of each of the genes (lacA, lacI, lacY, lacZ).</p>
<p>I am in AP Biology and I will not see the light of day again if I do poorly on this test. Please help!</p>
|
<p>The <em>lac</em> operon in E coli is a set of four genes which work together to allow the bacterium to make use of lactose for energy. An <a href="https://en.wikipedia.org/wiki/Operon" rel="nofollow noreferrer">Operon</a> is a set of genes which are co-transcribed on a single mRNA, controlled from a common promoter. While operons are nearly always found in bacteria, eukaryotes (and viruses that infect eukaryotes) do have some sets of genes organized into operons. </p>
<p>lacZ and lacY is the business end of the lac operon. They are the only 2 genes necessary for lactose usage in the cell. </p>
<p><em>lacZ</em> codes for beta-galactosidase, an enzyme that cleaves the lactose disaccharide into D-galactose and D-glucose. Most of know that glucose is an important source or energy via the glycolysis pathway, which is highly connected energy usage in the cell. Galactose is readily converted by an enzyme (galactose mutarotase) into glucose, making lactose an efficient source of energy. </p>
<p><img src="https://i.sstatic.net/EXUpt.jpg" alt="enter image description here"></p>
<p><em>lacY</em> codes for a protein found in the cell membrane called <a href="https://en.wikipedia.org/wiki/Lactose_permease" rel="nofollow noreferrer">lactose permease</a> which pumps lactose into the cell from the outside using the proton gradient inside the cell for its motive force. </p>
<p>The <em>lacA</em> gene codes for an enzyme which transfers an acetyl group to galactose, which may prevent the buildup of galactose in the cell. </p>
<p>The way the operon works is more important than what it does. the lac operon was one of the first examples of transcription regulation every studied. lacI is not in the lac operon, but it is the single gene which controls whether the operon is copied to RNA from the chromosome. lacI is translated to the lac repressor protein (LacI), which binds to one of three sites in front of the lac operon. </p>
<p>lacI is a repressor gene - when it is active, it prevents the lac operon from being transcribed into RNA. LacI is a tetramer - four copies of the protein form a complex. LacI binds to allolactose, a derivative of lactose, when it is present in sufficient quantities, which then causes it to release itself from the chromosomal DNA, allowing transcription to occur and the lac genes may be expressed. </p>
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gene expression
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Is it possible to elicit transient gene silencing by using virus induced gene silencing (VIGS) in plants?
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https://biology.stackexchange.com/questions/15648/is-it-possible-to-elicit-transient-gene-silencing-by-using-virus-induced-gene-si
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<p>I am looking for a molecular tech' which could result in transient gene silencing in plants. The objective is to not make transgenic plant, but to use these tech' to silence a gene of interest for a short time. From my limited knowledge, I found that virus induced gene silencing (VIGS) may be an option, I wonder how easy and how long such silencing last? Is there any alternative method?</p>
<p>I don't have any candidate gene to be silenced at this moment, but the tissue will be flower. so it would be nice if the protocol works for flower.</p>
<p>Thank you in advance</p>
|
<p>Virus induced gene silencing (VIGS) is definitely an option. </p>
<p>The ease of using VIGS depends on a lot of factors. Current VIGS vectors have limited host ranges. Depending on the species of plant that you are working with, there may or may not be suitable, pre-made VIGS vectors available and published techniques for using them. Many of the VIGS vectors that are available may be limited in terms of which tissues they can infect. Working with the vectors themselves requires that you have some way to propagate them and some way of getting them into your target plants (for example Biolistics, Agrobacterium or direct application of infectious virus). </p>
<p>There have been a number of VIGS vectors developed over the years, capable of infecting a diversity of plant species. Modified Tobacco mosaic virus (TMV) and Tobacco rattle virus (TRV) are two common VIGS vectors used for silencing in a variety of plants. TRV in particular is known to have a very wide host range. If your species doesn't fall within or even near the documented host range of available vectors it may be worth just trying a few different ones. Or, you could always isolate a virus specific to your target plant and build you're own. What fun!</p>
<p>The length of time that silencing will last is difficult to predict. In my experience, it will typically last a few weeks. But this may vary depending on a number of host factors and the VIGS vector used.</p>
<p>One potential alternative would be to just use Agrobacterium. It could be combined with a recombinase system to satisfy your condition of transience. To build such a system you could insert you're silencing construct into a binary vector. By including an inducible recombinase sequence adjacent to your silencing construct sequence and by flanking both of these with the recombinases recognition sequences, you would be able to remove inserted DNA at some point down the road after transforming the plant.</p>
<p>Again, depending on which species and variety of plant you're working on, this could require some trial and error as there may not be published techniques for Agro mediated transformation of you're target plant. </p>
<p>While Agro mediated transformation may not quite be what you're looking for in terms of transient silencing, it may be sufficient for a proof of concept.</p>
| 37
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gene expression
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Multi-modal distribution for gene expression data
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https://biology.stackexchange.com/questions/27816/multi-modal-distribution-for-gene-expression-data
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<p>Why would some genes have more than two modes in their expression distribution? What external factors would cause this anomaly?</p>
<p>I'm referring to the expression distribution of a gene across different tissue samples. For example, if one was to download a bunch of data from NCBI GEO, and pinpoint one gene and plot the expression level versus the frequency for that gene across all those data sets, some genes would have more than 2 modes (2 expression levels with very high frequency). This is the only case I'm interested in: more than 2 modes - not bimodal. So what would cause more than two modes?</p>
|
<p>One trivial situation in which this can happen is when the tissue used for expression studies is heterogeneous. Different cells express different levels of the gene. </p>
<p>Bimodality can be observed when the system can actually occupy two stable states; i.e. a gene can either have a high expression or a low expression. When you sample the population you would get two peaks. Bistablity (two stable steady states) is a common phenomenon in biological systems and positive feedbacks generally exhibit such behavior. In bistable systems there is also an unstable steady state which lies "between" the two stable states (like a mountain separating two valleys). If the system is in the unstable state, it can fall to either of the two stable states. (See <a href="http://jb.asm.org/content/194/5/1088.full" rel="nofollow">this</a> article for an example). This concept can be extended to multistable systems but they are a little more complex than the simple feedbacks. However they can theoretically exist (I don't know of a biological example yet). </p>
<p>Bimodality/multimodality can be also observed in the absence of a deterministic bistability in the system. This happens because of the expression noise due to stochasticity and is observed in case of transcription bursts (See <a href="http://www.sciencedirect.com/science/article/pii/S0006349512007837" rel="nofollow">here</a>).</p>
| 38
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gene expression
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Why are riboswitches mostly present in bacteria and not in eukaryotes?
|
https://biology.stackexchange.com/questions/27946/why-are-riboswitches-mostly-present-in-bacteria-and-not-in-eukaryotes
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<p>Riboswitches are a rather elegant way to regulate gene expression without any additional machinery. A small ligand binds to the mRNA and directly influences transcription or translation. </p>
<p>Most of the known riboswitches are found in bacteria, there are few examples of riboswitches in eukaryotes. There are no classical riboswitches in humans as far as I know (there is one example, but triggered by a protein and not a metabolite), it seems that more complex organisms tend to use other methods of gene regulation.</p>
<p>Are there any known reasons for this? What are the drawbacks of regulating gene expression with riboswitches compared to using regulatory proteins? Is there an explanation for the lack of riboswitches in more complex organisms?</p>
|
<p>You get higher accuracy and more timely control at a post translational level (think about the time it takes to affect a pathway with cofactor stimulation compared to gene expression stimulation). You also have more points of control throughout the pathway if you affect activity post translationally allowing for a more complex interaction between stimulating and repressing factors.</p>
| 39
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gene expression
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IPTG and lac operator with e coli for foreign gene question
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https://biology.stackexchange.com/questions/29751/iptg-and-lac-operator-with-e-coli-for-foreign-gene-question
|
<p>We did an experiment were we have e coli with a plasmid with a gene from another bacteria in it, and we put in IPTG in for induction. Will after looking up more about IPTG online I see it's related to the lac operator, which from what I've found just deals with lactose. Is there some other function that has? How can this be related to or effect the thing we put in and what we're doing? I'm missing the connection here.</p>
|
<p>The <a href="http://en.wikipedia.org/wiki/Lac_operon" rel="nofollow">lac operon</a> contains genes which are important for the metabolization of lactose as an energy source - normally glucose is used for this purpose. Usually the operon is tighly regulated and as long as there is another source of energy it is kept in an inhibited state.</p>
<p>The presence of lactose removes the lac repressor from the lac operon and allows the expression of the genes and thus allowing the metabolization of lactose. The mechanism can be turned on and off depending on the presence of lactose.</p>
<p><a href="http://en.wikipedia.org/wiki/Isopropyl_%CE%B2-D-1-thiogalactopyranoside" rel="nofollow">IPTG</a> is a substance which mimicks the presence of allolactose (a metabolite of lactose) and it can activate transcription from the lac operon. As IPTG (in contrast to allolactose) cannot be hydrolyzed by β-galactosidase, it's concentration in the cell stays the same. Using the lac operon and IPTG enables you to switch on the expression of the gene on your plasmid and to start the overexpression.</p>
| 40
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gene expression
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Two heterozygote mice for skin color are reproduced. Find the probability that in 3 children 2 will be dark and one white
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https://biology.stackexchange.com/questions/30028/two-heterozygote-mice-for-skin-color-are-reproduced-find-the-probability-that-i
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<p>Two heterozygote mice for skin color are reproduced. Black is dominant to white color. Find the probability that in 3 children 2 will be dark and one white. How did you do the ordering. Well I found it that in F1: 1/4 are AA, 1/2 Aa, 1/4 aa or 3/4 black and 1/4 white.Now nI think I should multiply the chances: 3/4*1/4*3/4, but it would be according to an order. What should I do? Is my answer correct?</p>
|
<p>You are on the right track, but you have to keep in mind there are multiple ways to have two dark and one child in a group of three. You have to add the probabilities of each unique outcome that results in two dark and one light child. So, the probability is (1/4) x (3/4) x (3/4) PLUS (3/4) x (1/4) x (3/4) PLUS (3/4) x (3/4) x (1/4)</p>
| 41
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gene expression
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What network motifs or other mechanisms can make the expression of a gene invariable to the environment?
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https://biology.stackexchange.com/questions/30127/what-network-motifs-or-other-mechanisms-can-make-the-expression-of-a-gene-invari
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<p>Next to double positive feedback loops and chromatin modification, which other mechanisms can make a gene susceptible to a certain environment in one cell-type but not in another?</p>
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<p>This phenomenon of being insensitive to certain fluctuations is called robustness. The fluctuations can be of two kinds for an input-output device such as a gene that is activated by a signal:</p>
<ol>
<li>Fluctuations in the signal</li>
<li>Fluctuations in the intrinsic parameters</li>
</ol>
<p>Signal fluctuations can be temporal but parameter fluctuations are not (parameters are supposed to be time invariant). Parameter fluctuation can exist in a genotypic space or a population of cells because of variation.</p>
<p>Some motifs are robust to signal perturbations whereas some are robust to parameter fluctuations. </p>
<p>Negative feedbacks and incoherent feed-forward can confer robustness by correcting the output fluctuations because of fluctuations in the input. </p>
<p>When an all or none sort of (binary: one state need not be smaller in magnitude than the other) behaviour is important, then positive feedbacks confer robustness to such systems because of their property of bistability. </p>
<p>I cannot recall any particular motif that is robust to parameters. There are certain cases though (<em>I am still working on that!! :P</em>).</p>
<p>In any case environment can be thought of as an input. <br> For your question <strong>"what mechanisms can make a gene susceptible to a certain environment in one cell-type but not in another"</strong>:</p>
<p>There can be a heterogeneous population of cells which can arise because of bistability or even otherwise, due to stochastic effects. If the gene that is in one of the two states (expression levels) in these two sub-population of cells, and this gene is responsible for the expression control (the controller gene in feedback), then one sub-population will be sensitive to the environment while the other will not be.</p>
<p>For more information on biological robustness read this <a href="http://www.nature.com/nrg/journal/v5/n11/abs/nrg1471.html" rel="nofollow">review</a>.</p>
| 42
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gene expression
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Name two reasons why it is impossible to determine a gene's nucleotide sequence from the amino acid sequence of the polypeptide
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https://biology.stackexchange.com/questions/30220/name-two-reasons-why-it-is-impossible-to-determine-a-genes-nucleotide-sequence
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<p>I can only think of one reason, which is because different codons can specify the same amino acids. However I am having trouble thinking of another reason. </p>
|
<p>I can think of at least 3 reasons in addition to the one you gave:</p>
<p>1: As mentioned in the comments, <a href="http://en.wikipedia.org/wiki/RNA_splicing">RNA splicing</a> takes place on most messenger RNA encoding proteins in eukaryotes. Sections of the mRNA may be spliced out, therefore multiple mRNAs with different codon sequence can encode the same gene. </p>
<p>2: Translation is a <a href="http://en.wikipedia.org/wiki/State_%28computer_science%29">stateful process</a>, since it depends on the <a href="http://en.wikipedia.org/wiki/Reading_frame">frame</a> of the codon. Therefore, a gene with the sequence GGATGATGATGTAA will encode the same protein as a gene with the sequence ATGATGATGTAA, due to the start codon shifting the frame of translation downwards. </p>
<p>3: Genes contain <a href="http://en.wikipedia.org/wiki/Untranslated_region">untranslated regions</a> in regions before the start and after the stop codon. These nucleotides cannot be predicted from protein sequence, but are generally important in regulating protein expression. </p>
| 43
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gene expression
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Comparing gene expression levels between control and disease at different time points
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https://biology.stackexchange.com/questions/30536/comparing-gene-expression-levels-between-control-and-disease-at-different-time-p
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<p>I have a data set with expression levels of a list of genes, measured in replicate at two different time points between two groups; a control group and a disease group.</p>
<p>I want to identify the changes in expression between the two groups, however I'm having some trouble on formulating how best to do this. For example, if I have $[C_0]$ and $[C_1]$ as the control group measured at $t=0$ and $t=1$ respectively, and $[D_0]$ and $[D_1]$ as the disease group, I had tried to do:</p>
<p>$$\frac{([D_1] - [D_0]) - ([C_1] - [C_0])}{[C_1] - [C_0]}$$</p>
<p>I feel like a fold change would be appropriate, however it doesn't seem to make any sense logically for the genes where $[C_0] = [C_1]$ or $[D_0] = [D_1]$.</p>
<p>Could anyone suggest an appropriate ratio or measurement? This is straightforward enough when it's simply comparing between C and D, (e.g. you just find $\frac{D}{C}$), however I'm not sure how to treat the different time points.</p>
|
<p>The gene expression profile may change at different time points between the two groups; you should decide what you actually want to measure. If you want to see if the diseased group is different from the control then you should compare them at every time point. For most situations you would need to compare just their steady state behaviour.</p>
<p><em>Imagine a diseased individual who shows some physiological differences at certain developmental stages compared to the control but in the end turns out to be perfectly normal. So what matters in most cases is the steady state and not the transients.</em></p>
<p>However if you are interested in the <strong>change in expression</strong> then you should compare <strong>([D<sub>1</sub>] - [D<sub>0</sub>])</strong> with <strong>([C<sub>1</sub>] - [C<sub>0</sub>])</strong>. This will tell you if the dynamics of the diseased and the control samples are similar or not.</p>
<p>There are issues with fold changes. Though they are decent measures, you cannot really apply a t-test with fold changes (normalizing to 1 is a different thing).</p>
<p>You can do another t-test between <strong>[C<sub>1</sub>]</strong> and <strong>[C<sub>0</sub>]</strong> (similarly for <strong>D</strong>). This would tell you if the diseased or control population changes its expression at time <strong>t=1</strong> or not.</p>
<p>AFAIK you cannot compare the dynamics and the values simulatenously. What you should test depends on what you are interested in.</p>
| 44
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gene expression
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Is there a consensus on the CaMV 35S minimal promoter sequence?
|
https://biology.stackexchange.com/questions/34681/is-there-a-consensus-on-the-camv-35s-minimal-promoter-sequence
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<p>We have an algal enhancer element and a transcription factor that probably binds it. Basal expression of the enhancer element or full promoter driving luciferase in tobacco protoplast was extremely low. I heard this could be overcome by fusing it to a minimal 35S promoter fragment but I can't seem to find a clear sequence for this minimal promoter.The best I could find was on the cambia website where they say it is -90 <a href="http://www.cambia.org/daisy/promoters/242/g1/250/264.html" rel="nofollow">http://www.cambia.org/daisy/promoters/242/g1/250/264.html</a> </p>
<p>1) Does anybody have experience with increasing the expression of enhancer elements like this?
2) And what sequence did you use for this?</p>
|
<p>In case anybody ever has the same question: I found the answer in this paper by Ow et al. 1987 (fig1)
<a href="http://www.pnas.org/content/84/14/4870.full.pdf" rel="nofollow">http://www.pnas.org/content/84/14/4870.full.pdf</a></p>
<p>Just to clarify, I did not want to boost expression of the enhancer element in my algae, it needed boosting in tobacco protoplasts/leaves.</p>
| 45
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gene expression
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Could fingerprints potentially be changed using a gene gun?
|
https://biology.stackexchange.com/questions/36738/could-fingerprints-potentially-be-changed-using-a-gene-gun
|
<p>Not to confuse with your "DNA fingerprint" I've read surgery is readily used to not just remove but even to change people's prints through employing very small grafts between opposing hands.</p>
<p>About 5 years ago a Chinese group identified SMARCAD1 as a key player in the development of fingerprints. this was discovered by generating gene expression profiles of people with a very rare condition called adermatoglyphia. These people have no finger prints.</p>
<p>A gene gun, which uses micropartical bombardment is a technique that propels microscopic particles of heavy metals, coated with the gene of interest, "deep" into tissues. </p>
<p>If you were to alter the genetics of the epidermal stem cells, you could potentially permanently change the tissue that arises from those stem cells. Could this in principle work if over expression of SMARCAD1 resulted in remodeling of the prints or has other more important genes been shown since to be involved?</p>
<p>Do any model organisms have fingerprints, or a version thereof?</p>
<p>I know I'm fishing here, lots of questions. I thought it was an interesting topic and wanted to see what people here had to say.</p>
|
<p>Chimpanzees have fingerprints. Next all you have to do is find the homologue of SMARCAD1 and let the animal testing begin! But actually I doubt it will work. <a href="http://scienceline.ucsb.edu/getkey.php?key=2650" rel="nofollow">This</a> website goes into some depth and links some additional sources that show fingerprints are developed in the womb and are fully set by 6 months of gestation. </p>
<p>It seems likely that SMARCAD1 may have to do with having fingerprints or not, but not likely that it has anything to do with their composition. It would be difficult for one gene to have enough variation to provide 6 billion variations in output. You could hypothesize that it's a combinatorial output from other genes as well, but the studies linked above focus more on environmental interaction as the cause of variation.</p>
<p>I would guess that the patterns are set and no amount of gene therapy is going to change your fingerprints. The simplest experiment would be to knockout the above gene in an adult for some period of time and see if the fingerprints fade.</p>
| 46
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gene expression
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Question about cutting gene in Plasmid
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https://biology.stackexchange.com/questions/40140/question-about-cutting-gene-in-plasmid
|
<p>I am designing a researching proposal for the class. Because it uses microinjection to up-regulate the gene in C. elegans, the plasmid pCFJ104 - Pmyo-3::mCherry::unc-54 sequences has been chosen. But because the plasmid already has a unc-54, I wonder if there a way that to cut the unc-54 out of the plasmid?</p>
|
<p>Following the link you provided confirms that the <em>C. elegans</em> expression vector will express your insert of choice in the transgenic animals' pharyngeal muscle cells (driven by the <em>myo-3</em> promoter). </p>
<p>From examining the two images of the plasmid's restriction map on the page you linked to, I infer that a <em>SacI</em> x <em>XbaI</em> double digest should excise the mCherry insert, and be suitable for sub-cloning your fragment of choice.</p>
<p>However you will need to confirm this for yourself. In general, I think it extremely unlikely that you would find an individual on Biology SE who could provide such precise information as "what enzyme sites should I use for my sub cloning experiment."</p>
<p>A general approach would be to </p>
<ol>
<li><p>Research to find out if you can obtain a fasta file containing the complete DNA sequence of the starting plasmid.</p></li>
<li><p>Search GenBank to see if there is a record containing annotations for the starting plasmid sequence--that will tell you the start points and end points of each functional region.</p></li>
<li><p>If the plasmid is not in a sequence database try using the sequence in a BLAST search of a Non-redundant sequence database. In this example you would have retrieved high scoring hits on the <em>unc-54</em> gene, the <em>myo-3</em> gene, the mCherry gene, the beta-lactamase gene from pMB9/pBR322/pUC, and the <em>E. coli</em> <em>lacZ</em> gene (among others).</p></li>
<li><p>You should also consult the original publication (if there is one) because it may contain additional useful information, including how to contact the authors--who may have sequence files, useful maps, etc.</p></li>
<li><p>With the sequence in hand you will be able to create your own restriction map using a suitable software program (there are many commercial ones), e.g. the EMBOSS suite of open source bioinformatics software.</p></li>
</ol>
<p>In your case most of this work was done for you because the AddGene site had two annotated restriction maps that showed almost all of the information you needed. N.B. One map had the locations of the useful restriction enzyme sites, and the other map had the annotations showing the extent and locations of the worm fragments and the reporter gene. It was only by integrating the information from both maps that I was able to suggest one possible solution to your query.</p>
| 47
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gene expression
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How to Download the broadpeak files from the encode chip-seq experiment matrix?
|
https://biology.stackexchange.com/questions/43321/how-to-download-the-broadpeak-files-from-the-encode-chip-seq-experiment-matrix
|
<p>I have tried the SqlDatabase of Encode opened it trough R ,i have tried other packages in R, i have tried the ENCODExplorer package but none of them seems to do what i want. I have an app that asks the user which cell type and which antibody factor wants to choose in Shiny. These cell types and antibody targets are drawn from chip-seq matrix here <a href="https://genome.ucsc.edu/ENCODE/dataMatrix/encodeChipMatrixHuman.html" rel="nofollow">https://genome.ucsc.edu/ENCODE/dataMatrix/encodeChipMatrixHuman.html</a>. I want to download the .broadpeak file from the experiment that was made using the two selections of the user . I cant find where the data from this matrix are stored and for sure they are not stored in the new website database of ENCODE.
Does anyone has an idea ??
These are some notes not all from a what i searched </p>
<blockquote>
<pre><code>1)https://www.bioconductor.org/packages/3.3/bioc/vignettes/ENCODExplorer/inst/doc/ENCODExplorer.html
New portal of ENCODE https://www.encodeproject.org/
#Load the ENCODExplorer
suppressMessages(library(ENCODExplorer))
#Find all the files from the experiment with biosample from A549 human cell using H2AFZ as antibody target
query_results <- searchEncode("a549 chip-seq homo sapiens h2afz") or
search_results <- searchEncode(searchTerm = "a549 chip-seq h2afz", limit = "all")
//downloadEncode(resultSet = search_results, resultOrigin = "searchEncode", format = "bed_broadPeak")
cant find any broadpeak files
2)Connect to an Oracle database(Encode sql Database) using R
http://rprogramming.net/connect-to-database-in-r/
channel <- odbcConnect("genome-mysql.cse.ucsc.edu", uid="genomep", pwd="password", believeNRows=FALSE)
http://stackoverflow.com/questions/15420999/rodbc-odbcdriverconnect-connection-error
#Database schema
install.packages("RMySQL")
library(RMySQL)
drv = dbDriver("MySQL")
con = dbConnect(drv,host="genome-mysql.cse.ucsc.edu",user="genomep",pass="password")
album = dbGetQuery(con,statement="show tables")
Tables_in_hgcentral
1 blatServers
2 clade
3 dbDb
4 dbDbArch
5 defaultDb
6 gbNode
7 genomeClade
8 geoIpNode
9 hubPublic
10 jorgetest
11 liftOverChain
12 liftOver_bkup
13 sessionDb
14 tableDescriptions
15 targetDb
16 userDb
17 wikiTrack
3)Not working-->https://www.simple-talk.com/sql/reporting-services/making-data-analytics-simpler-sql-server-and-r/
</code></pre>
</blockquote>
| 48
|
|
gene expression
|
Genes that exist in old Affymetrix platform but not in the newer one
|
https://biology.stackexchange.com/questions/45393/genes-that-exist-in-old-affymetrix-platform-but-not-in-the-newer-one
|
<p>I am using two gene expression datasets from an Affy U95Av2 platform and an Affy U133 Plus 2.0 platform. When I map the Affy probe names to HUGO gene names, there are thousands of genes which exist in the newer Affy U133 Plus 2.0 dataset while not in the old Affy U95Av2 dataset, which is something expected. But there are also 97 genes which exist in the old Affy U95Av2 platform while not in Affy U133 Plus 2.0 platform. I would not expect that because Affy U133 Plus 2.0 is a much newer platform and I would expect it to contain all genes that were measured by Affy U95Av2. What does that mean? Should I understand that those 97 gene measurements in the Affy U95Av2 platform were not reliable and that's why they don't exist in Affy U133 Plus 2.0? Here are those 97 genes:</p>
<p>"ACSL4" "ACSM2A" "AP3S1" "AQP7" "ARPC3" "ATF4" "ATP5H" "BAK1" "BAK1P1" "CBX1" "CCL15" "CELP" "CFHR3" "CHEK2" "CLCNKA" "COL8A1" "CS" "CXorf40B" "CYP2D6" "DDI2" "EIF3F" "EIF3IP1" "EIF5AL1" "FCGR2A" "FCGR3A" "GBX1" "GPX1" "HAVCR1" "HBZ" "HIST1H2AH" "HIST1H2AI" "HIST1H2BC" "HIST1H2BJ" "HIST1H4I" "HOXA9" "HSPB1" "IFNA14" "IGF2" "IL9R" "ITGA1" "KAT7" "KRT33A" "KRTAP26-1" "LDHA" "MAGEA12" "MAP2K4P1" "MIA" "MKRN3" "MROH7" "MSX2P1" "MT1A" "MT1B" "NDUFV2" "OPHN1" "OR7E24" "PARP4" "PCDHA12" "PCDHA13" "PCDHGA12" "PCDHGB4" "PINK1-AS" "PMS2P3" "PSMC6" "PSME2" "RAB13" "RCN1" "RNF216P1" "RNF5" "RPL10A" "RPL18" "RPL27" "RPL35" "RPL37" "RPLP1" "RPS15A" "RPS26" "RPS29" "RPS5" "RPS9" "RSC1A1" "S100A7" "SAA1" "SAA4" "SNX29" "SPRR2D" "TOMM40" "UBC" "UBE2E3" "UBE2S" "UGT2B7" "UQCRFS1" "UQCRH" "VDAC2" "VENTXP7" "VOPP1" "XCL2" "ZNF799"</p>
|
<p>aI used to work at Affymetrix when most of these arrays were designed. I was not on the design team itself, but I can maybe talk about this a bit more. </p>
<p>RNA Array designs were built to cover anything that might possibly be real transcript in the mix of EST collections, cDNA, <em>in silico</em> gene detections and miscellaneous entries in public databases. There were a lot of different people trying to find genes as quickly as possible and a good deal of it was not real gene naturally. I'm sure there was a reasonable amount of contamination in the millions of transcripts we took in as well. </p>
<p>The team would find a good number of errors in the sequence database. There is no way to submit this in a meaningful way to most bioinformatics databases by the way. Just a note:)</p>
<p>When a new design came out the team would do auditing to see if any of the transcripts had fallen out of favor with the evidence and some of those 'genes' would be pared from the content. </p>
<p>This is useful because DNA hybridization tech is very high throughput for the dollar but it has a background noise and even a probeset with no correspondence in the RNA sample will give numbers that are non-zero. </p>
<p>RNAseq has similar issues from assemblies and sensitivity from limits of reads on the sample BTW. There's no perfect solution as of yet.</p>
<p>BTW sometimes genes get renamed. I didn't get into your methods to see if this is a case, but something to keep in mind.</p>
| 49
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gene expression
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What do the intervals between groups of arrays in microarray gene expression data images mean?
|
https://biology.stackexchange.com/questions/52056/what-do-the-intervals-between-groups-of-arrays-in-microarray-gene-expression-dat
|
<p>This can be a dummy question, but I am not familiar with microarray experiments at all. In <a href="https://en.wikipedia.org/wiki/Binary_logarithm#/media/File:Mouse_cdna_microarray.jpg" rel="nofollow">this image</a>, what does each of 16 big squares mean, and what are the black intervals between them are? I know each small square corresponds to a gene expression value, but I don't know what each separated group of expression values means. Oftentimes I see those separated expression values in microarray dataset images. I would be happy if someone can explain. Thanks!</p>
|
<p>The borders provide visual cues for the image analysis software to know which spot is which. The spots are also not printed all at once, but by a series of print heads, and the spaces allow for a small amount of error in the alignment of the print heads. It also allows for humans to more easily eyeball the results - the chip map can be printed in groups, and if you're looking to see what gene X did in your experiment, and know it's in the 2nd row, in the 2nd block, row 8, column 4, you can find it more easily than just knowing it's in row 73, column 27.</p>
| 50
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gene expression
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Proteome patterns between treated and control cells
|
https://biology.stackexchange.com/questions/53669/proteome-patterns-between-treated-and-control-cells
|
<p>We did 4 experiments to compare the amount of certain proteins in treated and untreated cells. Each experiment was done separately. Because of the high cost of experiment, we were able to perform only one pair (one treated and one untreated) sample for each experiment. We want to see which proteins are differentially expressed (minimum 1.5 fold up/down). </p>
<p>First approach: We have compared protein levels of all 4 treated (as a group) with the 4 untreated (as a second group). There is of course variability between all experiments, because of the nature of the cells. We have a list of the proteins that are differentially expressed as a result of the treatment, however this list is not very long. </p>
<p>My question is (second approach): Can we compare the proteins levels pairwise for each experiment (treated vs its respective control) and make 4 corresponding lists, and then compare these four list using a statistical tool and find which proteins are consistently up- or down-regulated? DO you think that these two different approach will generate different lists of the affected proteins?</p>
|
<p>If I understand you did a treatment to some cells and compared them with non-treated ones. Instead of running the four experiments at the same time, you did one treated and one untreated at a time. Then you did proteomics for each sample. Is the treatment the same in all four experiments? </p>
<p>Edit after the further comments of the OP: So, since the four treated samples are the same and the four untreated also (same conditions except from the treatment and the treatment is the same), then the way to go is as what your collaborator did. </p>
<p>Identification and quantification of the detected proteins is one thing and every sample of the four are replicates. Comparison between the two conditions is another thing.
The software he uses for ID can combine the same samples and already perform the statistical analysis, so the list you have now has higher credibility in terms of the proteins it includes and their levels for your cells when they are treated or not.</p>
<p>Using only one of your replicates, although it might give you different number of detected proteins or different amounts of each, has lower credibility, because it's only one sample out of four. In plain words, the presence or absence or the amount of a protein might be an artifact or insignificant.</p>
<p>What has to be clear is that the comparison between treated and untreated conditions is done after you have received the statistically correct list of detected proteins.</p>
<p>Thus, and in accordance to what I had said before the edit, if you take the list for each treated sample and compare them with any of the lists of the untreated ones, it will lead to conclusions that won't be as statistically significant as when you combine all treated together and all untreated together (as your colleague did). In plain words, your conclusions will have a higher chance to be wrong.</p>
<p>Every statistical analysis you do yourself for each sample should eventually lead to a similar consensus as your colleague got using the statistical analysis of his software.</p>
<p>As a sidenote, considering how many types of proteins are in a cell, now that you have a quite short list might not be a bad thing at all and you can proceed by:</p>
<ol>
<li>Concluding that the treatment had minor effect in the proteins that you expected it would affect (if they are not present in your lists as significant different)</li>
<li>Trying to understand, identify and hypothesize on the role of the proteins that made it in your comparison threshold, as they have a much higher probability of being indeed different between the two conditions.</li>
</ol>
<p>Splitting the samples in your analysis might have a point if the conditions of the experiment were not exactly the same or the treatment level is different etc. In that case you could split the samples accordingly, but that would definitely reduce your certainty level for your conclusions.</p>
| 51
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gene expression
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Gene products of recessive/mutated alleles
|
https://biology.stackexchange.com/questions/53713/gene-products-of-recessive-mutated-alleles
|
<p>I probably would not cite a specific example, but some recessive allele work by encoding for the non-functional form of an enzyme. While the dominant allele encodes for sufficient levels of functional enzyme that the dominant phenotype is present in heterozygous individuals. Will the individual have many uselessly non-functional proteins floating around along with everything else?</p>
| 52
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gene expression
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Query for gene upregulation in cBioPortal
|
https://biology.stackexchange.com/questions/56265/query-for-gene-upregulation-in-cbioportal
|
<p>there! Could anyone help me with some biostatistical problems using cBioPortal.</p>
<p>We are looking for cell lines with upregulation of certain genes on cBioPortal. My supervisor is teaching me to use this website because I have no prior experience. She is using EXP >= 0.5 to define upregulation. Although I am of no bioinformatics background, my opinion is that 0.5SD away from the average is not strong enough to define an upregulation. I think it better to use EXP >= 2 or 1.5. I have discussed this with my supervisor but she insists using EXP >= 0.5.</p>
<p>Does anyone have any experience with this issue since I am still not convinced by what I was told. Thanks a lot!</p>
|
<p>Well, I have worked with expression patterns. Unfortunately there is no clear cut or magical numbers for cutoffs . I agree with you that 0.5 is not stringent. However, to explore data usually one can parse it using lower cutoffs and later on you can rise the bar to see what happens. </p>
| 53
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gene expression
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Validation of houskeeping genes in a mixture of cDNAs of two species
|
https://biology.stackexchange.com/questions/57867/validation-of-houskeeping-genes-in-a-mixture-of-cdnas-of-two-species
|
<p>I have a parasite sample (mixed with host blood) and I need to check gene expressions of parasite using relative quantification (RT_qPCR). For this, I need a good housekeeping gene. I chose 10 genes (suggested as housekeeping) that I need to validate and after choose the most stable one(s). My problem is that my parasite cDNA is mixed with host cDNA and it is impossible to separate them or count the parasite. I do not know how I could choose the best housekeeping gene in this case? I do not have the real amount of parasite cDNA used for qPCR, and I do not have any good internal control. Basically, it is circular problem: In order to validate my target gene I need a good housekeeping gene for internal control, but I do not have an internal control to make relative quantification of my housekeeping genes and to chose the best one. Could you please suggest any study or method that deals with such a case? </p>
|
<p>Two possibilities:</p>
<ol>
<li><p>Design primers based on differences in the sequences of the gene for the same protein between the two organisms. (Suggested by @Artem)</p></li>
<li><p>Identify an aspect of the metabolism of your parasite that is not present in the host, then use enzymes from that pathway. If the parasite is a worm and the host a mammal, for example, you should surely be able to find something.</p></li>
</ol>
| 54
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gene expression
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Overexpression by integration of an additional copy vs promoter exchange
|
https://biology.stackexchange.com/questions/68586/overexpression-by-integration-of-an-additional-copy-vs-promoter-exchange
|
<p>In <a href="http://www.sciencedirect.com/science/article/pii/S1096717611000048" rel="nofollow noreferrer">Becker et al (2011)</a>, the authors increase the expression of several genes through different methods. For some genes (e.g., <em>lysA</em>, <em>ddh</em>), they achieve overexpression by integrating an additional copy of the gene and its flanking regions. On the other hand, for other genes (e.g., <em>lysC</em>, <em>dapB</em>, <em>fbp</em>, and the <em>tkt</em> operon) they take another approach and instead replace the native promoter with a strong constitutive promoter (P<em>sod</em> or P<em>etfu</em>).</p>
<p>Is there an advantage of one technique over the other? Why was one technique preferred over the other one for certain genes?</p>
|
<p>Modifying promoters can give finer, more targeted control of expression than changing copy numbers. In the <a href="http://www.sciencedirect.com/science/article/pii/S1096717611000048" rel="nofollow noreferrer">paper you referenced</a>, for the <em>ddh</em> gene, it sounds like they just wanted to boost production of that protein, so making a second copy made sense. But with some of the other genes, they wanted to alter metabolite fluxes through a more complex pathway. Copying a whole operon would not achieve this, because then you would just get two pathways doing the exact same thing. But even copying the one or two genes in the operon that you want to investigate might change their relation to the other genes in the operon. Bacterial operons are generally organized such that the genes for the transcriptional regulators are located adjacent to the genes they regulate. This proximity is necessary for the proper functioning of the operon, and if you copy a gene, depending on where you put the copy, it may not function as it usually does. In these cases, it's better to mess with the promoters because you can leave the organization of the operon largely intact.</p>
| 55
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gene expression
|
Question: What is CINWntUp and CINnormL?
|
https://biology.stackexchange.com/questions/78814/question-what-is-cinwntup-and-cinnorml
|
<p>What is CINWntUp and CINnormL?</p>
<p>I read a paper that uses this two things as classes but Im not sure what they represent. I imply that CIN is referring to Chromosomal instability but I don't know what WntUp & normL refer to. (<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4214593/" rel="nofollow noreferrer">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4214593/</a>)</p>
|
<p>From the paper:</p>
<blockquote>
<p>The dataset contains six colon cancer subtypes: class 1 = CINImmune-Down (116 samples), class 2 = dMMR (104 samples), class 3 = KRASm (75 samples), class 4 = CSC (59 samples), class 5 = CINWntUp (152 samples), and class 6 = CINnormL (60 samples).</p>
</blockquote>
<p>CINWntUp and CINnormL are therefore two classes of colon cancer. You are correct, CIN is for chromosomal instability; WntUp refers to upregulation of Wnt, a signalling pathway involved in some cancers and named for a Wingless/Integrated phenotype in fruit flies and the homologous gene in vertebrates. normL stands for "normal-like."</p>
<p>See the original paper describing these classes:</p>
<p>Marisa, L., de Reyniès, A., Duval, A., Selves, J., Gaub, M. P., Vescovo, L., ... & Kirzin, S. (2013). Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value. PLoS medicine, 10(5), e1001453.</p>
| 56
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gene expression
|
What are mutator genes which cause copying errors in other genes?
|
https://biology.stackexchange.com/questions/80205/what-are-mutator-genes-which-cause-copying-errors-in-other-genes
|
<p>Reading Dawkins' book "The Selfish Gene," I came across this line: "There are even genes--called mutators--that manipulate the rates of copying errors in other genes." (The context is his argument that such a gene is looking out for its best interest by killing off the competition.)</p>
<p>What are these "mutator" genes, and how do they function?</p>
|
<p>Most obvious examples are the genes directly involved in <a href="https://en.wikipedia.org/wiki/DNA_mismatch_repair" rel="nofollow noreferrer">DNA mismatch repair (MMR)</a> such as <a href="https://en.wikipedia.org/wiki/MSH2" rel="nofollow noreferrer">mutS</a>, <a href="https://www.uniprot.org/uniprot/P23367" rel="nofollow noreferrer">mutL</a>, <a href="https://www.uniprot.org/uniprot/P06722" rel="nofollow noreferrer">mutH</a>, MLH1 and MLH2.</p>
| 57
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gene expression
|
Is there a difference between "genetic cross regulation" and "crosstalk"?
|
https://biology.stackexchange.com/questions/89607/is-there-a-difference-between-genetic-cross-regulation-and-crosstalk
|
<p>What is the difference between genetic cross regulation and crosstalk? I'm a physics major and learning about bioinformatics now. So it might seem trivial to many but from the article "<a href="https://jb.asm.org/content/jb/174/7/2053.full.pdf" rel="nofollow noreferrer">Wanner BL. Minireview. Is cross regulation by phosphorylation of two component response regulator proteins important in bacteria? J Bacteriol 1992; 174:2053-8.</a>" I could not find a quantitative way to separate these two kind of gene regulations. Also, I would appreciate if anyone can suggest me something to read for further knowledge on this topic. Thanks!</p>
| 58
|
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gene expression
|
Mutated and unmutated PCR product
|
https://biology.stackexchange.com/questions/92719/mutated-and-unmutated-pcr-product
|
<p>If I have a mutated colony containing the fusion protein, mCherry instead of the stop codon TAA, and an unmutated colony which does not contain the protein. Why will the PCR products of the two colonies have the same size?</p>
<p>I thought that since the mutated colony contains the protein instead of the stop codon, this would cause this product to be larger in size than the unmutated product. However, from experimental data it shows that both products are of same size. Could someone please explain why this is?</p>
<p>Thank you!</p>
|
<p>If mCherry was successfully cloned replacing the stop codon, you would indeed expect a fusion protein that is about 27 kDa larger than the original protein.
However, with a PCR you are not testing for the full length protein, but rather for a part of the target gene sequence. </p>
<p>The length of the PCR product very much depends on the position of your primers: If both primers are targeted at your unmutated sequence, the product size will not change by adding mCherry behind the targeted sequence. The product size of the PCR would only change, if one primer is located before or in your unmutated protein and the other one behind mCherry. This would probably result in a very large PCR product and hinder the PCR reaction from being effective.</p>
<p>To check for correct integration of mCherry, you would need to design a primer pair with the forward primer in your unmutated protein and the reverse primer in mCherry. This should result in a product in the fusion protein colonies, but not in the unmutated ones. </p>
<p>Alternatively, you could sequence your products.</p>
| 59
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gene expression
|
What is a good book to start with if I'm interested in Gene clustering analysis?
|
https://biology.stackexchange.com/questions/100285/what-is-a-good-book-to-start-with-if-im-interested-in-gene-clustering-analysis
|
<p>As a beginner, I would like to learn more about gene clustering analysis, namely discovering groups of correlated genes potentially coregulated or associated to some conditions or finding patterns in gene expression data, identification of coexpressed genes from microarray data.</p>
<p>I was looking up for some books, but all of them are a little too much biology-heavy for me, given the fact that I have a Computer Science background. I would like to dive into algorithms such as hierarchical clustering, k-means algorithm, pattern-based clustering and other methods, so a book addressing these would be of real help.</p>
<p>If you have any suggestions, I would be grateful.</p>
| 60
|
|
gene expression
|
Relative abundance of transcription factors and protein kinases
|
https://biology.stackexchange.com/questions/101511/relative-abundance-of-transcription-factors-and-protein-kinases
|
<p>Are transcription factors and protein kinases only expressed at low levels in eukaryotes?</p>
<p>As regulatory proteins, I would expect their abundance to be lower than most other proteins, but I cannot find any published research to support that.</p>
|
<p><strong>Summary</strong>
<br>
The abundance of protein kinases and transcription factors vary among and between these broad classes of protein.</p>
<p><strong>General Considerations</strong>
<br>Let us first think what might be expected for the abundance of transcription factors and protein kinases.<br>
<em>Protein kinases:</em> These would be expected to be less abundant than their substrate proteins as they are enzymes catalysing a reaction. However some protein kinases are part of amplification cascades (e.g. <a href="https://en.wikipedia.org/wiki/Mitogen-activated_protein_kinase" rel="noreferrer">MAP kinases</a>) so the abundance of individual member would be expected to differ.<br>
<em>Transcription factors:</em> <a href="https://en.wikipedia.org/wiki/Transcription_factor" rel="noreferrer">Transcription factor</a> is a portmanteau term that includes both proteins that act generally on promoters (e.g. the TATA-binding proteins TFIIA, TFIIB etc.) and ones that are specific for the promoters of particular genes or classes of genes (e.g. heat shock factor). The abundance of transcription factors might be expected to be inversely proportional to their specificity.
<br>
<em>Correlation between Protein Kinases and Transcription Factors:</em> I can see no reason to group these two classes together as the regulation of metabolic activity and gene expression are very different processes. All I would expect is that they would to less abundant than structural proteins such as actin or ribosomal proteins (although differing in abundance among themselves).</p>
<p><strong>One Possible Approach</strong>
<br>
To the man with a hammer, everything looks like a nail. My particular hammer may not be the best tool for this particular nail, and there are certainly other tools available which other answers may mention, but it’s something you can do at home (without even adult supervision). The hammer is called <em>FlyAtlas 2</em> and can be accessed at <a href="http://flyatlas.gla.ac.uk/FlyAtlas2/index.html" rel="noreferrer">http://flyatlas.gla.ac.uk/FlyAtlas2/index.html</a>. It allows one to examine the extent of expression of different genes in the tissues of the fruit fly, <em>Drosophila melanogaster</em>.</p>
<p><strong>Some Words of Caution</strong>
<br>
Before looking at experimental data, one should be aware that the abundance of enzymes will vary depending on the particular tissue examined and the physiological conditions. One should also be aware that the data are for abundance of mRNA transcripts, which may not always be proportional to the amount of the encoded protein. Further, although the resource has been published in a <a href="https://doi.org/10.1093/nar/gkx976" rel="noreferrer">peer-reviewed journal</a>, as is normal in science, the referees have not repeated the experiments.</p>
<p><strong>How to Proceed</strong></p>
<p><a href="https://i.sstatic.net/U7jGw.png" rel="noreferrer"><img src="https://i.sstatic.net/U7jGw.png" alt="FlyAtlas 2 selections" /></a></p>
<ol>
<li>Connect to <a href="http://flyatlas.gla.ac.uk/FlyAtlas2/index.html" rel="noreferrer">http://flyatlas.gla.ac.uk/FlyAtlas2/index.html</a></li>
<li>There are two ways of proceeding here. One can go to the <em>Category</em> page, type in a term in either as a <em>Category</em> or <em>Free Search</em>, and select from the menu, as shown.</li>
<li>Alternatively go to the <em>Gene</em> page, click (or tap) on <em>Gene Name</em> and choose from the autocomplete. This gives fewer results than 2, but they tend to be grouped in a way that makes it easier to make repeated searches.</li>
<li>Click <em>Search</em> and tick <em>Whole Body</em> in the results (which may be downloaded in a spreadsheet-friendly format). An example is shown.</li>
</ol>
<p><a href="https://i.sstatic.net/s3XFl.png" rel="noreferrer"><img src="https://i.sstatic.net/s3XFl.png" alt="FlyAtlas 2 results" /></a></p>
<p><strong>Results</strong>
<br>
A quick application of this approach shows that:
<br></p>
<ol>
<li><p>Protein kinases are expressed in whole flies in a ten-fold range, from just detectable (e.g. Cyclin-dependent kinase 2) to 20–40 FPKMs (protein kinase A, calmodulin-dependent protein kinase).</p>
</li>
<li><p>Some protein kinases are highly expressed, but only in specific tissues (e.g. Erk7 in testis).</p>
</li>
<li><p>Transcription factors are expressed in whole flies in a range from just detectable (e.g. Transcription factor AP-2) to about 10 FPKM (TF IIB, heat shock factor)</p>
</li>
<li><p>Some Transcription factors are tissue-specific (e.g. TF B4 in ovary and testis).</p>
</li>
<li><p>Comparative values of cellular enzymes are glycogen phosphorylase (c. 100), phosphofructokinase (c. 50), enolase (c. 200).</p>
</li>
</ol>
| 61
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gene expression
|
Can proteins structure change depending of alimentation of an organism?
|
https://biology.stackexchange.com/questions/67565/can-proteins-structure-change-depending-of-alimentation-of-an-organism
|
<p>In my understanding protein are built using information caring by RNA. So a given protein should always have the same structure in a given organism has the DNA of this organism does not change.</p>
<p>I'm asking this question because peoples told me that "cow milk protein become longer because how we feed them today". But I don't understand how a protein can become longer or shorter.</p>
<p>Info: I have no background in biology. I do not try to solve a problem, but simply have a better understanding.</p>
|
<p>While it is theoretically possible for a protein to change size (based on length) because of nutrition, I don't think that's happening here. </p>
<p>You are right-- DNA encodes information that is transcribed to RNA which is translated into proteins. Proteins are made of a finite number of amino acids, which are the building blocks of proteins. Proteins can be modified (and can be cleaved to make the protein shorter), but I think this claim of "cow milk protein becomes longer" is a misunderstanding because there is not a single "cow milk protein", but rather many. </p>
<p>There are many different proteins in cow milk, and most of them are casein proteins. <a href="http://ajcn.nutrition.org/content/51/1/37.short" rel="nofollow noreferrer">source</a></p>
<p>The milk protein likely at the root of this claim is beta-casein. It was a hot topic in the 1990s, because there are a dozen different variants of this beta-casein protein. Two of these variants are the most common in milk have been studied a lot: variant A1 and A2. The only way these are different is a single amino acid change at amino acid position 67 (remember that proteins are made of amino acids). Variant A1 has a histidine amino acid but variant A2 has a proline. What does that mean? That means that A1 can be cut (in your body) to produce a smaller protein bit (called a peptide). Because of the proline in the A2 variant, it cannot be cut like the A1 variant. The peptide resulting from the A1 getting cut is called BCM7. </p>
<p>In short:
beta-casein variant A1: can be cut to produce BCM7
beta-caesin variant A2: gets cut way less than A1 so way less BCM7 is produced. </p>
<p>So, what is BCM7? It had been reported to been linked to some different diseases but the European Food Safety Authority (EFSA) published <a href="http://onlinelibrary.wiley.com/doi/10.2903/j.efsa.2009.231r/epdf" rel="nofollow noreferrer">this report</a> which concludes that there is no link between BCM7 and non-communicable diseases. Despite this, there is still a lot of talk about A1 vs A2 in the dairy community. While websites such as <a href="http://www.snowvillecreamery.com/a1-and-a2-beta-casein-in-cow-milk.html" rel="nofollow noreferrer">this</a> appear compelling, remember the EFSA report! </p>
<p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4487594/" rel="nofollow noreferrer">this paper</a> is open source and has the information about these variants that is summarized above. </p>
<p>So what does all this have to do with "cow milk protein" changing size? Maybe more cows used as dairy cows have the A2 variant, which would not produce as much BCM7 (the small peptide). Since A2 is not cleaved to produce BCM7, it could be thought of as "longer"... at least relative to only a few thousand years ago.
The beta-casein A2 variant is thought to be the original version of beta-casein from undomesticated cows. </p>
<p>So, if this claim was originally about beta-casein, you can respond that "yes, the beta-casein protein can be thought of longer because it is not cut to produce the BCM7 peptide as much as the A1 variant is, but it is also the original beta-casein size." Whether it was 10,000 years ago or just now, the A2 beta-casein variant is the same size.</p>
<p>tl;dr / Good reading from the <a href="http://cdrf.org/2017/02/09/a2-milk-facts/" rel="nofollow noreferrer">California Dairy Research Foundation</a>.</p>
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gene expression
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What does it mean that the transcript is enriched?
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https://biology.stackexchange.com/questions/89180/what-does-it-mean-that-the-transcript-is-enriched
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<p>I think I don't get the meaning of "enriched" in the context of genes.
What's the difference of gene being "enriched" and "expressed" in the cell?</p>
|
<p>In the context of transcriptomics the term 'enrichment' is usually connected to differential analysis:</p>
<ul>
<li>If a transcript (or some/all transcripts of a gene) are detected in a given sample that transcript is <em>expressed</em></li>
<li>If a transcript is detected at (statistically significant) higher levels in sample (or condition) A compared to another sample B, that transcript is <em>enriched</em> in sample A.</li>
</ul>
<p>In some cases one might compare two cell types, where only one expresses a given transcript, in this expression and enrichment in that cell line (compared to the other one) would be almost the same.</p>
| 63
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gene expression
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PCR for gene expression
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https://biology.stackexchange.com/questions/109015/pcr-for-gene-expression
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<p>Could somebody please explain the basic principle behind how qPCR can detect if a gene is expressed or not? I tried looking at literature on ScienceDirect and other websites but I could not find any information. I understand what qPCR is supposed to do - amplify a target DNA and provide numbers for the resulting DNA after cycles. I am familiar with the concept of gene expression.</p>
|
<h2>What is qPCR? What's the central concept?</h2>
<p>qPCR (or more stringently, qRT-PCR, a term that is less ambiguous) usually refers experiments which use <strong>quantitative polymerase chain reactions</strong> to quantitate (measure) gene expression in real time ("RT"), and when the source material is RNA, it is reverse-transcribed first ("RT") because PCR does not work well with single-stranded nucleic acids such as RNA.</p>
<p>The idea behind it is simply two-fold:</p>
<ul>
<li>we amplify DNA (using PCR), and</li>
<li>we measure the DNA in real time during each step/cycle of the PCR, until the reaction is exhausted or plateaus or is sufficient for making a determination about DNA amount.</li>
</ul>
<p>Over many PCR cycles, say 40 or 50, the amount of DNA product reaches a plateau that is not directly correlated with the amount of target DNA initially. So we must survey the amount of DNA before we hit the plateau! That's why we do it in real time. Simple.</p>
<h2>How is DNA actually measured?</h2>
<p>We measure DNA at the end of each PCR cycle using reporters. Typically, a fluorescent dye that intercalates (binds) with DNA is used. To simplify somewhat, more fluorescence means more DNA strand. We can measure <strong>absolutely</strong> (comparing to known amounts, or DNA standards, which we calibrate to) or <strong>relatively</strong> (relative to another gene or segment of DNA which we are amplifying using known primers). When you do quantitation, you must make sure as best as possible that your sample and the standard have the same amplification efficiency, so that the <em>assumption</em> that each cycle will amplify equally across samples will be assured.</p>
<h2>How does qPCR measure gene expression specifically? DNA is not gene expression.</h2>
<p>We use the amount of DNA transcript (mRNA) as a proxy for the expression of the gene. We can treat expression as numerical quantities. For example, 5 mRNA strands that act as transcripts of the insulin INS gene are assumed to be a tenth of what 50 insulin mRNA transcripts are. In the second case, you have a 10-fold higher expression than in the case with only 5 transcripts.</p>
<p>However, qPCR does not work with RNA (single-stranded nucleic acids) since PCR depends on two-strandedness of DNA. So to quantitate a gene's expression (mRNA) we must first reverse transcribe all the mRNA into complementary DNA (cDNA) which we can then put into the qPCR machine!</p>
<p>So, the proxy for gene expression is mRNA amount, but now we are using a proxy for mRNA amount in the form of cDNA.</p>
<p>With this cDNA, we can now precisely quantify how much of it there is. Then we can make an indirect statement about how much mRNA for specific genes we found in our sample (e.g. biopsy, lysed cells, bodily fluids, harvested tissues, etc.). So we've achieved quantifying expression of our sample.</p>
<h2>The devil in the details</h2>
<p>Importantly, the whole process takes place within PCR conditions, so you are very dependent on your primers and thermal cycling conditions. If your extension temperature step is too short, long strands may not have enough time to complete duplication by the polymerase. If your primers are designed incorrectly, or are in conditions in which they cannot anneal efficiently, you will have incorrect amplification and the quantitation will not be possible. If you do not prepare the initial reaction with sufficient dNTPs (DNA building blocks), your reaction will be exhausted prematurely. If you forget to add a polymerase enzyme, there will be no amplification. For some reactions, you need to use specific polymerase enzymes which are more thermostable, more efficient, or are more stringent in that they make fewer errors in duplicating DNA strands. A lot of little things must be satisfied in order to run a good qRT-PCR with dependable read-out, so please refer to standardized practices and considerations. <a href="https://pubmed.ncbi.nlm.nih.gov/19246619/" rel="nofollow noreferrer">Here is an old but good one to familiarize yourself with.</a></p>
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gene expression
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One flybase gene number (FBgn), many Affymetrix Id's
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https://biology.stackexchange.com/questions/7646/one-flybase-gene-number-fbgn-many-affymetrix-ids
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<p>I am trying to convert a set of Affymetrix ID's, like this one 143053_at_3745, to Flybase Gene Numbers (FBgn) like this one FBgn0000015. I have downloaded the <a href="http://flybase.org/static_pages/downloads/bulkdata7.html" rel="nofollow">Flybase file</a> required to do so (as described <a href="http://flybase.org/static_pages/docs/datafiles.html#exons_affy1_overlaps" rel="nofollow">here</a>) but I have noticed that most of the FBgn's have more than one associated Affy id. </p>
<p>My question is, how do I know which to assign to my data? From the list of affy-ids that I have, how do I label each one with the <strong>appropriate</strong> FBgn? I am using data from the <a href="http://www.nature.com/ng/journal/v41/n3/full/ng.332.html" rel="nofollow">Ayroles et al 2009 (DGRP)</a> which has a column of AffyID which look similar to the ones in the Flybase file but shorter (1638273_at). Perhaps I don't grasp why there would be more than one.</p>
<p>Some have one affy id which is repeated across 15 columns in the file, whereas some seem to have several affy id's associated with them.</p>
<p><strong>Some questions this problem raises:</strong></p>
<p>Why does a singular FBgn identifier have more than one associated affy identifier? </p>
<p>Why do some datasets, such as the dataset I have, have shorter versions of the affy identifier? </p>
<p>Where can I find an up to date and appropriate list matching these Affy id's the FBgn identifiers correctly?</p>
|
<p>I can answer this - I may not have time to dig though the file you are pointing to... but here's some explanation - lmk if you need more. </p>
<p>The shorter names (123456_at) are the original names for the probe sets that Affymetrix gave. The file you area asking about has been extended for FlyBase's purpose and I'm only dimly aware of its existence. It looks like Flybase has tried to rename the probe set to a minimal gene list and create less ambiguous mappings. I'm not familiar with it. If I have time Ill try to look at it and put something here, but I'm fairly slammed this week. </p>
<p>In general you should know, there is a many to many relationship between probe sets from arrays and genes. </p>
<p>There are a few reasons for this. The most common reasons: </p>
<p><em>More than one probe set per gene</em>
1) More than one start sequence per gene. The IVT arrays such as you are looking at read only the 3' end of the gene. If there are more than one such terminii, you will have more than one probe set.
2) Duplicate genes. If the 3' end of the gene has been duplicated recently, then a probe set may read more than one gene and not be able to distinguish them, so it will have both gene references in its annotation files.
3) Duplicate probe sets. For older arrays, this did happen where the probes in two probe sets will be mostly or entirely the same.
4) formerly separate genes are now joined into a single gene. This is similar to (1) above, but with the added reason that two neighboring transcripts seen separately at the time of the array design are currently known to be part of the same transcript. This is something we often don't think about, but the array may have been designed before your current gene of interest had a full length sequence. </p>
<p>In several cases the transcription behavior of the two probe sets will be quite different and you can decide which one to take based on how it behaves experimentally. for example one of the probe sets may never respond while another one may register large changes with biological sample conditions. Sorry I can't be of more help here. There are too many possible scenarios to consider to write about cogently. </p>
<p><em>More than one gene per probe set</em>
1) a single stretch of DNA, even on the same strand, may simply be associated with more than one gene and the probe set will read both of them.
2) Even if they are not exactly the same, some genes resemble each other in nucleotide sequence that is impossible to choose probes which do not read both of them. </p>
<p>Since they have similar read length to a probe set, all this is also true to some extent for short read NGS sequencers in RNASeq data. </p>
<p>As you can hopefully see, ambiguity is something you have to expect to some extent when deciding to work with a biological system. In many cases (~ 80%) you will have a single gene read per probe set, but with those odds you'll be looking at the genome browser for a half dozen of your favorite experimental results. </p>
| 65
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gene expression
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water stress expression markers in arabidopsis thaliana
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https://biology.stackexchange.com/questions/14980/water-stress-expression-markers-in-arabidopsis-thaliana
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<p>So far I found papers that show studies using RNA arrays on whom they categorized water stress gene markers in root. Water stresses were reproduced by different protocols (manitol...) but always on several week old plants. Does anyone know any study carried on young (6 days more or less) arabidopsis thaliana plants?</p>
| 66
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gene expression
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Word denoting genetic state
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https://biology.stackexchange.com/questions/23822/word-denoting-genetic-state
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<p>Is there a single word, or brief phrase, that denotes the state of the total genetic machinery (genome + transcriptome + proteome + ...) of a cell or organ or organism at a particular point in time?</p>
| 67
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gene expression
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Why people fear GMOs? Can't we map a plant composition?
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https://biology.stackexchange.com/questions/29875/why-people-fear-gmos-cant-we-map-a-plant-composition
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<p>My main question is can we map what a fruit is made of? For instance apples are made of 0.0002% of protein X, 0.00001 of protein Y, 0.001% of amino acid Z... etc...</p>
<p>If we can, then my next question would be why do people fear eating GMOs?
I understand the argument that if you introduce a new compound to your body you don't know its effect on you, but if for instance you insert a new gene into the plant where it is resistant to drought- can we not simply analyze its product and if its composition haven't changed than everything is alright?</p>
<p>Thank you very much!</p>
|
<p>People are not always rational when it comes to what they eat, especially when the compounds that make up the food have long, arcane-sounding names. </p>
<p>It is indeed possible to analyse the amino acid composition of a food substance. However, this has no bearing whatsoever on the safety of the food product. </p>
<p>For example, the following are two truncated protein sequences. One of them is a fragment constituent of cobra venom, the other is a fragment of harmless DNA polymerase. Without looking up or otherwise referring to the PDB IDs, it is not obvious which is which, even to an experienced molecular biologist. </p>
<blockquote>
<p>3HRZ:A|PDBID|CHAIN|SEQUENCE
ALYTLITPAVLRTDTEEQILVEAHGDSTPKQLDIFVHDFPRKQKTLFQTRVDMNPAGGMLVTPTIEIPAKEVSTDSRQNQ</p>
<p>1KLN:A|PDBID|CHAIN|SEQUENCE
VISYDNYVTILDEETLKAWIAKLEKAPVFAFATETDSLDNISANLVGLSFAIEPGVAAYIPVAHDYLDAPDQISRERALE</p>
</blockquote>
<p>Furthermore, even if scientists can prove beyond reasonable doubt that the two products are chemically identical, people will still irrationally purchase them. A clear example is the different prices commanded by "natural" versus "artificial" flavourings, as seen in <a href="http://www.scientificamerican.com/article/what-is-the-difference-be-2002-07-29/" rel="nofollow">this Scientific American article</a>. </p>
<blockquote>
<p>Consumers pay a lot for natural flavorings. But these are in fact no better in quality, nor are they safer, than their cost-effective artificial counterparts. </p>
</blockquote>
| 68
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gene expression
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Expression of an ancestral gene
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https://biology.stackexchange.com/questions/3225/expression-of-an-ancestral-gene
|
<p>Why would the expression of an ancestral gene and comparing the product to a modern protein give misleading conclusions about heredity?</p>
<p>Update:
By ancestral gene I mean a gene which was used by an ancestor but than changed slightly through evolution, though it still serves the same purpose. And by the misleading conclusion I mean that using this similarity between the product of the ancestral gene and the modern protein as evidence that the organism is descended from the ancestor.</p>
|
<p>Your updated question is still very vague, but I'm going to assume it is basically: "Why would the ancestral version of a gene be mistaken for a more recent version than the modern gene?"</p>
<p>If this is incorrect, please let me know and modify your question to clarify.</p>
<p>The simple answer to that question is that the mutations that occurred after the <em>Ancestral</em> gene resulted in less apparent divergence than the LCA (last common ancestor), which would cause the <em>Ancestral</em> gene to seemingly have more polymorphisms - and the general assumption is that the more polymorphisms (mutations) that a gene has undergone, the more recent it is.</p>
<p>So let's say you have the following DNA sequences:</p>
<p>5' - AAAT - 3' = LCA (Template)</p>
<p>5' - AAAG - 3' = Sample 1 : # Differences = 1 Nucleotide</p>
<p>5' - AACG - 3' = Sample 2 : # Differences = 2 Nucleotides</p>
<p>The <em>general</em> assumption is that the larger the difference from the LCA, the more mutations have occurred over time. So, under the general assumption, <em>Sample 2</em> is probably the most recent version of the sequence.</p>
<p><strong>However</strong>, and this is what I think is the answer to your question, because mutations can occur in any order and at any place in the genome, it is <strong>entirely possible</strong> for the third (from left) Nucleotide to have followed this mutation path: A -> C -> A</p>
<p>That would make <em>Sample 2</em> <strong>appear</strong> to be more recent than it is because it essentially mutated "back" to the LCA version of the gene, despite being a linearly older version than <em>Sample 1</em>. In this way, an Ancestral gene can be mistaken for a more recent evolution of a gene. This is also why genomic data is never as strong as when paired with fossil records or other corroborating data that also aligns with the genomic data's proposed timeline; though the odds of a mistake being made grow exponentially less as more of the genome is compared and analyzed. </p>
<p>With very recent mutations; on the scale of hundreds to thousands of years, it's sometimes necessary to analyze thousands of base pairs to calculate an adequately confident answer.</p>
| 69
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gene expression
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Mutating a protein without mutating the gene?
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https://biology.stackexchange.com/questions/46507/mutating-a-protein-without-mutating-the-gene
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<p>Is it possible to mutate a region of a protein (says about 300 amino acids long) without actually mutating the gene?</p>
<p>One possible way that I can think of is to use RNAi and specifically block that region of the mRNA which codes for the 300 amino acids in the protein?</p>
<p>But then wouldn't it cause a problem in the translation of the remaining region of the protein?</p>
<p>Are there any methods out there to mutate a region of a protein without mutating the DNA?</p>
|
<p>I assume that you mean changing the amino acid sequence in a single protein in an organism to one that no longer reflects the sequence predicted from the DNA sequence. In that case, I would suggest using ADAR (Double-stranded RNA-specific adenosine deaminase) or similar enzymes. ADAR deaminates adenosine to inosine, which is read by the ribosome as a guanine. I know that it's activity is regulated, but I'm not sure how you could redirect it (perhaps with an antisense RNA that yields a double-stranded binding stretch in the target RNA. </p>
| 70
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gene expression
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Negative value on linear gene expression in microarrays
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https://biology.stackexchange.com/questions/10797/negative-value-on-linear-gene-expression-in-microarrays
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<p>I am starting to use microarrays and maybe this is a dumb question:</p>
<p>Using Illumina microarrays, linear gene expression can be negative? Or maybe some artefacts have been introduced?</p>
<p>And, in this case, how to correct them? With scaling (adding the absolute value of the minimum negative value) or flooring (converting negative values to zeros)?</p>
<p>Thanks</p>
|
<p>I'm not personally familiar with Illumina arrays, but I can give some notes here. This link is a <a href="http://res.illumina.com/documents/products/technotes/technote_gene_expression_data_quality_control.pdf" rel="nofollow noreferrer">paper which describes the array quality controls specifically</a>. This presentation describes the <a href="http://www.ncbi.nlm.nih.gov/pubmed/18467348" rel="nofollow noreferrer">calculation of the intensities in bioconductor</a>. </p>
<p>The answer is yes: you will find negative numbers sometimes. They should be rare. The Intensities numbers from a scanner which essentially takes an image of the bead fluorescence on the glass slide and tries to subtract a background signal. </p>
<p>The background is the typical level of signal you see on a bead with no sample DNA bound to it. You will get some pixels lighting up a bit even there. </p>
<p>In expression microarrays, this is not a perfect system as each bead has a different nucleotide sequence on it. Each bead has a specific DNA sequence has non-specific binding which is pretty much unique on the slide. That is to say, the oligomer on the bead might bind strongly to DNA from your sample which is not its reverse complement to varying degrees. </p>
<p>I think what happened is that there will be a handful of cases you can find a bead which has less fluorescence than the background controls on the slide. It's possible that the probe has a design flaw but I would generally assume that the negative number means that there is no detectable target cDNA in the sample for that oligo. </p>
<p>I probably wouldn't convert the number to a zero, but you could probably justify it to yourself in some cases. Most difference experiments are the logarithm of the ratio so zero is not a great number in those cases.</p>
<p>@Luke 's comments are well said. </p>
<p>I think that negative values can still represent signal because of the variance of sequence-dependent effects for the purposes of scaling, and difference experiments. But I'd tend to think of them as zero signal in any case. There are probably genes which express at or below detection threshold all the time, which is not zero information, so the number has some value. </p>
| 71
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gene expression
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why should someone study mRNAs instead of miRNAs as a biomarker
|
https://biology.stackexchange.com/questions/59514/why-should-someone-study-mrnas-instead-of-mirnas-as-a-biomarker
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<p>why should someone study mRNAs instead of miRNAs as a biomarker from liquid cell-free biopsy like from exosomes? Is it wrong to do it? Does it offer you something different? Thank you in advance</p>
| 72
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gene expression
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How to preprocess htseq counts for gene expression (TCGA)
|
https://biology.stackexchange.com/questions/56841/how-to-preprocess-htseq-counts-for-gene-expression-tcga
|
<p>I want to prepare a matrix of gene expression to analyse TCGA LAML data.</p>
<p>The required data is available at <a href="https://gdc-portal.nci.nih.gov/search/s?facetTab=files&filters=%7B%22op%22:%22and%22,%22content%22:%5B%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.program.name%22,%22value%22:%5B%22TCGA%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.primary_site%22,%22value%22:%5B%22Bone%20Marrow%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.project_id%22,%22value%22:%5B%22TCGA-LAML%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.disease_type%22,%22value%22:%5B%22Acute%20Myeloid%20Leukemia%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22files.data_category%22,%22value%22:%5B%22Transcriptome%20Profiling%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22files.experimental_strategy%22,%22value%22:%5B%22RNA-Seq%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22files.analysis.workflow_type%22,%22value%22:%5B%22HTSeq%20-%20Counts%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22files.data_type%22,%22value%22:%5B%22Gene%20Expression%20Quantification%22%5D%7D%7D%5D%7D" rel="nofollow noreferrer">TCGA LAML - Gene expression quantification</a>.</p>
<p>The following is an example of the kind of data retrieved from the TCGA data portal:</p>
<pre><code>ENSG00000000003.13 9
ENSG00000000005.5 1
ENSG00000000419.11 661
ENSG00000000457.12 1434
ENSG00000000460.15 1211
ENSG00000000938.11 405
ENSG00000000971.14 251
ENSG00000001036.12 786
ENSG00000001084.9 4423
ENSG00000001167.13 5038
ENSG00000001460.16 246
ENSG00000001461.15 2773
ENSG00000001497.15 1932
ENSG00000001561.6 1693
ENSG00000001617.10 55
ENSG00000001626.13 8
ENSG00000001629.8 4629
</code></pre>
<p>Each row displays, for each gene, the quantification of read counts by the htseq tool.</p>
<p>My question is, how do I have to preprocess the data (e.g. regarding gene length) before using data for subsequent analysis?</p>
<p>In this case I will not consider normalisation (such as loess) and batch effects removal (e.g. with combat).</p>
| 73
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gene expression
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Can Blood Types Change?
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https://biology.stackexchange.com/questions/58562/can-blood-types-change
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<p>I recently heard a radio show where two callers claimed that their blood types had changed. One caller claimed that he was born O-, but recent tests said he was A+. Another caller claimed to change from AB- to AB+. Both callers claim that they had multiple tests before and after the change.</p>
<p>What I noticed is that both cases claim a conversion from Rh- to Rh+, or from type O to some other type. These could potentially be explained by a person carrying a gene for Rh factor or some other blood type, but failing to express the protein. Then the gene starts expressing, changing their blood type.</p>
<p>Of course both stories could be false, intentionally or otherwise. This is purely anecdotal evidence, and one caller claimed that her blood type change was due to extraterrestrial interference. I couldn't find any better documented cases of blood type changes after a quick search on the internet, so I thought I'd ask here.</p>
<p>Are there any documented cases of a change in blood type?</p>
|
<p>Blood group antigens are either sugars or proteins found attached to the red blood cell membrane. ABO blood group antigens are the most clinically important antigens because they are the most immunogenic. As red blood cell antigens are inherited traits, they are usually not altered throughout the life of an individual. There have been occasional case reports of ABO blood group antigen change in malignant conditions,ABO antigen alteration associated with acute myeloid leukemia. <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5242122/" rel="nofollow noreferrer">https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5242122/</a></p>
<p><a href="https://www.ncbi.nlm.nih.gov/pubmed/15135601" rel="nofollow noreferrer">https://www.ncbi.nlm.nih.gov/pubmed/15135601</a> ( B to O change)</p>
<p><a href="https://www.ncbi.nlm.nih.gov/pubmed/22270426" rel="nofollow noreferrer">https://www.ncbi.nlm.nih.gov/pubmed/22270426</a> (New laboratory procedures and Rh blood type changes in a pregnant woman.)</p>
<p>A bone marrow transplant will replace the cells which make your blood cells with cells from the donor. Over about 3-4 months (life span of a red cell), your blood will become your donors type.</p>
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gene expression
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Is there a resource to query gene expression similarity? Stratified by sex?
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https://biology.stackexchange.com/questions/78265/is-there-a-resource-to-query-gene-expression-similarity-stratified-by-sex
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<p>We developed such a resource. The editors of "Bioinformatics" (at OUP) rejected the paper on the grounds that we did not run a comparison with "state-of-the-art" [similar] resources. Can someone help me find similar resources?
Link to our own resource, <a href="http://unmtid-shinyapps.net/exfiles/" rel="nofollow noreferrer">ExFiles</a>. </p>
|
<p>There are some similar resources, which at the same time do not mix the ingredients in the same way as your tool. Hope that pointing out the respective differences will help your rebuttal or resubmission! e.g.:</p>
<ul>
<li>A similar web service is part of <a href="https://www.flyrnai.org/tools/dget/web/similar_genes/" rel="nofollow noreferrer">flyrnai</a>, where tissue-specific expression can also be compared based on sex, and genes can be queried by the similarity of their gene expression profile to other genes.</li>
<li>A resource which has some conceptual relatedness regarding sex-specific similarity in gene expression, and which is also based on the GTEx dataset, has recently been published in the form of tables by <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5297171/" rel="nofollow noreferrer">Gershoni et Pietrokovski, BMC Biol, 2017</a>.</li>
<li>A very nice and broad resource of high-quality gene expression profiles on individual tissues, but also on response to stimuli, is <a href="https://www.ebi.ac.uk/gxa/home" rel="nofollow noreferrer">EBI GXA</a>. Though the web interface only allows to query sex-specific expression profiles, computationally minded people could readily compute (dis)similarity between samples after downloading the (well-structured) data dump of EBI GXA.</li>
<li>A similar tool in terms of the visualization of sex-specific expression patterns is part of <a href="https://gtexportal.org/home/" rel="nofollow noreferrer">gtexportal</a>, though it seems limited to displaying a single gene.</li>
</ul>
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gene expression
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How are oncogenes targeted for therapy?
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https://biology.stackexchange.com/questions/58472/how-are-oncogenes-targeted-for-therapy
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<p>How would oncogenes be targeted for therapy and are there any examples of existing therapies for such cancers if the gene was upregulated (i) as a result of copy number variation and (ii) due to increased promoter activity?</p>
| 76
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gene expression
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Are there any papers that give examples of what is a "high" and "low" TPM expression value for given gene types?
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https://biology.stackexchange.com/questions/114653/are-there-any-papers-that-give-examples-of-what-is-a-high-and-low-tpm-expres
|
<p>My question relates to how to interpret TPM gene expression values, and what might be considered as "high" and "low" expression values, based on the gene type. For example, a receptor tyrosine kinase or an enzyme can catalyse many reactions and so only needs a relatively low gene expression to have a high effect, whereas something like a ligand may need a higher expression value.
Does anyone know of any rule of thumb TPM expression values that have been defined in the literature e.g. 50-100 TPM is considered standard for a receptor, etc?
Thanks in advance</p>
|
<p>No.</p>
<p>High and low gene expression are not absolute concepts, as the poster himself would seem to recognize in his speculations about different types of protein. In science you can only talk about “high” and low in relation to some reference <strong>normal</strong> situation, and this means making a measurement on some appropriate <strong>control</strong>.</p>
<p>What control is appropriate will depend on your biological system, and that requires careful consideration, followed by the necessary work. Is it appropriate to compare different tissues, ages, stimuli, organisms? What is not appropriate is to make a declaration in a vacuum.</p>
| 77
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gene expression
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In which phenomena does one gene pair hide the effect of other unit?
|
https://biology.stackexchange.com/questions/37450/in-which-phenomena-does-one-gene-pair-hide-the-effect-of-other-unit
|
<p>This question was asken in an exam,</p>
<p><img src="https://i.sstatic.net/dm32D.png" alt="image"></p>
<p>The answer they are saying is "Epistasis". But I think "Dominance" fits better, because it is not mentioned whether genes of same allele are to be considered or different allele. Also it is not told whether genes in same locus are being talked of or different.</p>
<p>Please give some reference if you can. I know only school level biology. I do not know even in detail what allele and locus are. As far as I could understand from wikipedea and other sources I think "Dominance" is correct.</p>
|
<p>The definition of "gene", according to <a href="http://dictionary.reference.com/browse/gene" rel="nofollow">The American Heritage Science Dictionary</a> is:</p>
<p>"A segment of DNA, occupying a specific place on a chromosome, that is the basic unit of heredity. Genes act by directing the production of RNA, which determines the synthesis of proteins that make up living matter and are the catalysts of all cellular processes. The proteins that are determined by genetic DNA result in specific physical traits, such as the shape of a plant leaf, the coloration of an animal's coat, or the texture of a person's hair. Different forms of genes, called alleles, determine how these traits are expressed in a given individual. Humans are thought to have about 35,000 genes, while bacteria have between 500 and 6,000. See also dominant, recessive. See Note at Mendel."</p>
<p>So, when the question refers to genes, it must be referring to two different genes on two different loci. If the question was referring to alleles of the <em>same</em> gene on the <em>same</em> locus, the correct answer would be dominance, but since it is referring to two different genes, the answer is epistasis.</p>
| 78
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gene expression
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How do I read an RNA expression pattern?
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https://biology.stackexchange.com/questions/57138/how-do-i-read-an-rna-expression-pattern
|
<p>When reading about diseases one can find links to proteins and their associated genes, an example of which is <a href="https://en.wikipedia.org/wiki/LMNA" rel="nofollow noreferrer">here</a>.</p>
<p>I'm wondering how to decode/read the following graph as a non-specialist in this area:</p>
<p><a href="https://i.sstatic.net/o7QqX.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/o7QqX.png" alt="RNA expression pattern"></a></p>
<p>What does it all mean?</p>
|
<p>This image shows the expression of a gene (in your case Lamin A/C) in various tissues. A picture with a higher resultion for mouse looks like this (from <a href="http://biogps.org/#goto=genereport&id=4000" rel="nofollow noreferrer">here</a>):
<a href="http://biogps.org/#goto=genereport&id=4000" rel="nofollow noreferrer"><img src="https://i.sstatic.net/2R53p.png" alt="enter image description here"></a></p>
<p>You can see the median expression (calculated from all samples) and can also see, in which tissues this gene is highly expressed and in which there is less or no expression.</p>
<p>This is important if you want to analyze the function of a gene. The tissue specific expression pattern can vary strongly between different tissues (as you can see in the figure) which can give information about the function of the gene. The same is true if you look on the time distribution of gene expression, you can identify genes which are important for different steps of differentiation.</p>
| 79
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gene expression
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Is there a mechanism of timing or delaying the expression of gap genes?
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https://biology.stackexchange.com/questions/79805/is-there-a-mechanism-of-timing-or-delaying-the-expression-of-gap-genes
|
<p><strong>Summary</strong></p>
<blockquote>
<p>Gap genes are expressed in presence of the right combination and amount of
transcription factors. But is there any additional mechanism of timing the expression of the gap genes to ensure that they are expressed at the right time?</p>
</blockquote>
<p><strong>Context and Detailed Question</strong></p>
<p>Let's look at gap gene expression in <em>Drosophila</em>:</p>
<ol>
<li><p>Firstly, bicoid and nanos are expressed and diffused from anterior and posterior ends respectively and form gradients;</p></li>
<li><p>Then, hunchback gets expressed, with bicoid acting as promoter and nanos acting as suppressor; </p></li>
<li><p>Then, Krüppel gets expressed, with
hunchback acting as both promoter and suppressor - meaning that there must be enough hunchback, but not too much.</p></li>
</ol>
<p><a href="https://i.sstatic.net/squBU.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/squBU.jpg" alt="enter image description here"></a>
(or a video: <a href="https://www.youtube.com/watch?v=uaedzlrnBGY" rel="nofollow noreferrer">https://www.youtube.com/watch?v=uaedzlrnBGY</a>)</p>
<p>Makes perfect sense, unless you look at it from dynamic, biochemical perspective:</p>
<p>Firstly, bicoid and nanos slowly build up in the embryo:
<a href="https://i.sstatic.net/Yab55.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/Yab55.jpg" alt="enter image description here"></a></p>
<p>As soon as there's enough bicoid at the anterior region, hunchback immediately starts building up too: I mean, it can't just choose to wait for bicoid to establish its gradient or something - if there's a promoter for it, it should react accordingly.
<a href="https://i.sstatic.net/FITdR.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/FITdR.jpg" alt="enter image description here"></a></p>
<p>And so it "chases" the bicoid gradient, in a manner of speaking, and will continue to chase it until it stumbles into nanos protein, which suppresses it.</p>
<p>All this makes sense so far.</p>
<p>The only problem is that at this point, there's just perfect amount of it for Krüppel at the anteriormost region, so Krüppel should start being expressed there:
<a href="https://i.sstatic.net/T5OBj.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/T5OBj.jpg" alt="enter image description here"></a></p>
<p>Eventually, there'll be too much hunchback at the anterior region, so Krüppel should cease to be produced - but some quantity of it should be expressed there nonetheless. The final gradient should look like this:
<a href="https://i.sstatic.net/gWAh4.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/gWAh4.jpg" alt="enter image description here"></a></p>
<p>The only way to avoid it is if Krüppel kindly waited until the hunchback establishes its final gradient before even attempting to be expressed. But how is this possible? Is there some mechanism that prevents Krüppel from being expressed too early - and if so, then what releases it? Or maybe there's some mechanism of timing, that prevents genes from being expressed too early?</p>
<p>This Krüppel example is just one examples of several, when there must be some timing control in order for genes to be expressed properly.</p>
| 80
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gene expression
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Can we change the Eye/Hair color by knocking out the OCA2, HERC2 and MC1R genes using CRISPR in an adult human?
|
https://biology.stackexchange.com/questions/96043/can-we-change-the-eye-hair-color-by-knocking-out-the-oca2-herc2-and-mc1r-genes
|
<p>This paper seems to describe the use of a plasmid delivered by a gene gun to depigment rat skin;</p>
<blockquote>
<p><a href="https://www.nature.com/articles/3302264" rel="nofollow noreferrer">https://www.nature.com/articles/3302264</a>
Published: 27 May 2004
Seeing the gene therapy: application of gene gun technique to transfect and decolour pigmented rat skin with human agouti signalling protein cDNA</p>
</blockquote>
<p>Could a similar technique using CRISPR and chitosan change the eye and hair color of an an adult?</p>
|
<p>Let's first breakdown this question</p>
<blockquote>
<p><strong>What is CRISPR?</strong></p>
</blockquote>
<ul>
<li>CRISPR is a group of DNA sequences that play a key role in the antiviral defense system of prokaryotic organisms such as bacteria and archaea.</li>
<li>They are derived from DNA fragments of bacteriophages that had previously infected the prokaryotes.</li>
<li>These sequences are used to destroy DNA from similar bacteriophages for future infections.</li>
</ul>
<blockquote>
<p><strong>What is CRISPR-Cas?</strong></p>
</blockquote>
<ul>
<li>The CRISPR-Cas system is an immune system seen in prokaryotes that provides resistance to foreign elements such as plasmids and phages. This is a form of acquired immunity.</li>
<li>Some factors allow Cas protein which is an enzyme to recognize and cut foreign pathogenic DNA making them act like a pair of molecular scissors.</li>
</ul>
<blockquote>
<p><strong>What are OCA2, HERC2, and MC1R?</strong></p>
</blockquote>
<p>Now we know we can cut a specific part (Gene) of DNA. What do we accomplish by cutting out the genes which Andrew mentioned? To answer this we need to know what those three genes do.</p>
<ol>
<li><strong>OCA2 (P-gene):</strong> Provides instructions for making a protein called the P protein. This protein is located in specialized cells
(melanocytes) that produce a pigment called Melanin.
<em>Melanin is a natural skin pigment. Hair, skin, and eye color in people and animals mostly depends on the type and amount of melanin
they have.</em></li>
<li><strong>HERC2 (E3 ubiquitin ligase HERC2):</strong> Protein ligase which helps in DNA repair regulation, pigmentation, and neurological disorders.</li>
<li><strong>MC1R (Melanocortin 1 receptor):</strong> Proteins involved in regulating mammalian skin and hair color.</li>
</ol>
<p>In short, these Genes affect the Eye and Hair Colour and Andrew is suggesting to us that by removing/modifying them using CRISPR we change the Eye/Hair Colours.</p>
<blockquote>
<p><strong>Can we knock out OCA2, HERC2, and MC1R?</strong></p>
</blockquote>
<p>Yes, it has been done before and there are sequences available to target these genes within the genome. An example would be the gRNA sequences developed by Sigma-Aldrich and Genscript. I'll provide links of articles which has knocked out the respective gene and links to the gene sequences.</p>
<ul>
<li><strong>OCA2:</strong> (Article: <a href="https://pubmed.ncbi.nlm.nih.gov/29555241/" rel="nofollow noreferrer">https://pubmed.ncbi.nlm.nih.gov/29555241/</a> | Sequence:
<a href="https://www.genscript.com/gRNA-detail/4948/OCA2-CRISPR-guide-RNA.html" rel="nofollow noreferrer">https://www.genscript.com/gRNA-detail/4948/OCA2-CRISPR-guide-RNA.html</a>)
<br></li>
<li><strong>HERC2:</strong> (Article:
<a href="https://jmg.bmj.com/content/early/2020/06/22/jmedgenet-2020-106873" rel="nofollow noreferrer">https://jmg.bmj.com/content/early/2020/06/22/jmedgenet-2020-106873</a> |
Sequence: <a href="https://www.sigmaaldrich.com/catalog/genes/HERC2" rel="nofollow noreferrer">https://www.sigmaaldrich.com/catalog/genes/HERC2</a>) <br></li>
<li><strong>MC1R:</strong> (Article:
<a href="https://www.genscript.com/gRNA-detail/4157/MC1R-CRISPR-guide-RNA.html" rel="nofollow noreferrer">https://www.genscript.com/gRNA-detail/4157/MC1R-CRISPR-guide-RNA.html</a>
| Sequence:
<a href="https://www.genscript.com/gRNA-detail/4157/MC1R-CRISPR-guide-RNA.html" rel="nofollow noreferrer">https://www.genscript.com/gRNA-detail/4157/MC1R-CRISPR-guide-RNA.html</a>)
<br></li>
</ul>
<blockquote>
<p><strong>Can we change the Eye/Hair Colour by modifying the above genes?</strong></p>
</blockquote>
<p>An Interesting article from MIT Technology Review called <a href="https://www.technologyreview.com/2015/03/05/249167/engineering-the-perfect-baby/" rel="nofollow noreferrer">Engineering the Perfect Baby</a> gives you a nice idea of what I am going to tell you.</p>
<p><strong>In Theory:</strong> It's technically possible. We can put up a convincing theory and there is a huge chance that this can be successfully done.</p>
<p><strong>In Reality:</strong> Well, Reality kinda sucks cause most of the genetic engineering breakthrough starts from failures. Killing a rat for scientific purposes won't make any big difference but what about killing a fetus? It's almost <em><strong>impossible to get the permissions required to use CRISPR to edit the human genome</strong></em> even if it is to find a cure for a deadly disease that would actually improve the human race significantly. Due to its obvious ethical questions, people always stand against it. I said "almost impossible" cause there are few people who actually got the permissions and there are indeed few ongoing trials experimenting with CRISPR on Human Genome.</p>
<p>A popular Example would be <strong>He Jiankui</strong> who gave rise to the first-ever gene-modified human babies "Lulu and Nana". He had to forged ethical review documents, misled doctors into unknowingly implanting gene-edited embryos into two women, and many more things which haven't come out yet. What are the consequences? <a href="https://www.popularmechanics.com/science/health/a25383837/crispr-baby-scientist-he-missing/" rel="nofollow noreferrer">He's bloody missing</a>! <em>May 2022 Update: <a href="https://www.technologyreview.com/2022/04/04/1048829/he-jiankui-prison-free-crispr-babies/" rel="nofollow noreferrer">He's been found.</a></em></p>
<p>The point is, there is absolutely no way they would approve the usage of CRISPR for modifying something as silly as Eye/Hair color.</p>
<p>I mean we all like our babies to look like Megan Fox but I totally doubt if anyone would dare to modify a human genome for changing mere appearance cause people would start protesting if they find out someone is putting all those innocent fetuses at unknown and uncalculatable risk for changing external traits.</p>
<p>We want people to use CRISPR for things like this - <a href="https://edition.cnn.com/2017/09/29/health/gene-edit-beta-thalassemia-study/index.html" rel="nofollow noreferrer">Scientists edit gene for blood disease in human embryos</a> and not for things like this - <a href="https://www.dailymail.co.uk/femail/article-3433718/The-rise-designer-baby-Parents-paid-20-000-choose-sex-child-say-decision-no-brainer-spending-years-failing-conceive-naturally.html" rel="nofollow noreferrer">The rise of the designer baby: Parents who paid $16,500 to choose the sex of their child.</a></p>
<p><strong>TL;DR (Too Long; Didn't Read):</strong> <br></p>
<blockquote>
<p><strong>What is CRISPR-Cas?</strong></p>
</blockquote>
<p><em>Technique in which we can edit genes relatively more precise than before.</em></p>
<blockquote>
<p><strong>What are OCA2, HERC2, and MC1R?</strong></p>
</blockquote>
<p><em>Genes which control the color of Eyes, Hair, Skin, and has other purposes.</em></p>
<blockquote>
<p><strong>Can we remove OCA2, HERC2, and MC1R genes using CRISPR?</strong></p>
</blockquote>
<p><em>Yes</em></p>
<blockquote>
<p><strong>Has it been done before?</strong></p>
</blockquote>
<p><em>Yes</em></p>
<blockquote>
<p><strong>In Humans?</strong></p>
</blockquote>
<p><em>Nope cause we got all those ethics and stuff.</em></p>
<blockquote>
<p><strong>What are we trying to accomplish by removing those genes?</strong></p>
</blockquote>
<p><em>To change the Colour of the Eyes/Hair of a human being.</em></p>
<blockquote>
<p><strong>Can we change the Colour of the Eyes/Hair of a human being?</strong></p>
</blockquote>
<p><em>In theory, it'll work. In Reality, nobody would allow it. They'd be better off with Hair Dye and Contact Lenses than to risk the lives of innocent fetuses.</em></p>
| 81
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gene expression
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How to choose a method for upregulating an endogenous protein?
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https://biology.stackexchange.com/questions/113282/how-to-choose-a-method-for-upregulating-an-endogenous-protein
|
<p>What factors affect the method that should be chosen to engineer a cell line that upregulates an endogenous protein? I am mostly asking permanent or long-term expression of nuclear proteins in mammalian cell lines, but more selection criteria for more applications would be appreciated too.</p>
<p>As I understand it, the possible methods are the following:</p>
<ul>
<li>Target the regulatory factors already present in (or adjacent to) the gene of interest responsible for the protein, possibly targeting known variants that express a phenotype associated with high protein expression</li>
<li>Introduce new regulatory elements to improve transcription and translation</li>
<li>If the cell line is immortalized, expand and select for higher expression of the target protein</li>
<li>Introduce a non-integrative element that expresses the mRNA transcript variant</li>
</ul>
<p>Are there any factors regarding the protein, gene, or cell type that make one of these better or worse? And are there any methods I'm not considering?</p>
|
<p>This is one of those questions that needs to be determined <a href="https://en.wikipedia.org/wiki/Empirical_research" rel="nofollow noreferrer">empirically</a>, as it is highly dependent on the protein in question. For any one system, the best method to use needs to be determined by trial and observation. Upregulation and over-expression can be problematic, depending on the system you are targeting. Check the literature to see what others have used.</p>
<p>You are missing a few methods, namely those that use a lower expression cf. the already determined level in your unaltered line:</p>
<p>In many cases it is possible to find a cell-line that has a naturally higher or lower expression of the protein that can be used experimentally to compare to another that has a lower/higher expression, or use/generate a Knock-Out (KO) version of the cell line. Generation of KO is generally easier than introduction of a gene for stable expression if you are aiming for integration into the genome. The exception here is where the gene is used on a mobile element like a plasmid and is continually selected for using selective marker for over-expression. Investigate CRISPR/Cas systems for these, as well as viral vector methods (lentivirus, adenovirus etc.)</p>
<p>You can also use methods such as <a href="https://en.wikipedia.org/wiki/Small_interfering_RNA" rel="nofollow noreferrer">siRNA</a> to target mRNA for degradation, but this is not stable, needs to be done individually for each experiment, and may or may not work for your system.</p>
| 82
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gene expression
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Does penetrance depend in a regular way on zygosity?
|
https://biology.stackexchange.com/questions/116076/does-penetrance-depend-in-a-regular-way-on-zygosity
|
<p>I'm doing some self-directed study in genetics and microbiology. For example, I've viewed most of the videos from <a href="https://www.youtube.com/playlist?list=PLF83B8D8C87426E44" rel="nofollow noreferrer">the MIT OpenCourseWare series 7.01SC <em>Fundamentals of Biology</em></a> by Eric Lander and others. I have also read twenty or so papers, from individuals (and groups) like Avery, Brenner, Bressan, Crick, Davenport, Fisher, Hall, Jackman, Loomis, Mackey, Mendel, Radick, Spiegelman, Watson, and Weeden.</p>
<p>My question stems from my trying to wrap my brain around the concept of penetrance. I find—for instance in <a href="https://pubmed.ncbi.nlm.nih.gov/12092906/" rel="nofollow noreferrer">a 2001 paper by Kurtz et al. in <em>J. Neurogenet.</em></a>—that "penetrance is the percentage of animals of a specific genotype who express the phenotype associated with that underlying genotype" (in contrast to expressivity, which is "the degree that a particular genotype is expressed as a phenotype within an individual"). So as I understand it, penetrance is analogous to the percentage of Americans who are Baltimore Orioles fans, whereas expressivity is analogous to the fervor of some particular American's dedication to and affection for the Orioles.</p>
<p>From that (perhaps flawed) understanding, the question that arises is</p>
<blockquote>
<p>Since penetrance is a property of the set of all organisms with a particular genotype (and may thus be considered to be "with respect to" that genotype), wouldn't it vary in a somewhat consistent way between heterozygous and homozygous genotypes associated with a common phenotype?</p>
</blockquote>
<p>From my armchair intuition, I'd imagine the homozygous genotype to be reliably, I dunno, more compelling cause to express the phenotype in question than its heterozygous counterpart.</p>
|
<p>Yes, penetrance would "vary in a somewhat consistent way between heterozygous and homozygous genotypes". Some genes may usually show that (for a phenotype) one particular allele shows 0% penetrance in the heterozygous genotype and 100% (complete) penetrance in the homozygous genotype. Such an ideal allele would be called a Mendelian recessive allele. (Its partner in the heterozygous genotype would be the dominant allele; see <a href="https://en.wikipedia.org/wiki/Dominance_(genetics)" rel="nofollow noreferrer">Wikipedia</a>.)</p>
<p>Often, however, a particular genotype (whether it's a heterozygous or homozygous genotype that's of interest) will show partial penetrance, not either 0% or 100%. This is due to other factors, generally unknown, of environmental and/or genetic influence.</p>
| 83
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gene expression
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Time scale for cAMP-dependent pathway cascades
|
https://biology.stackexchange.com/questions/94262/time-scale-for-camp-dependent-pathway-cascades
|
<p>What is the time scale for cAMP-dependent pathway cascades that start at the level of ligand binding to a G-protein receptor and finish at the level of gene transcription regulation?</p>
<p>For example, when corticotropin releasing hormone binds to CRH receptor 1, a cAMP-dependent pathway cascade is initiated, which ultimately leads to an upregulation in the transcription of proopiomelanocortin (POMC) mRNA.</p>
<p>I recognize that this is a very broad question, that is likely highly case dependent (i.e. different from receptor-ligand pair to receptor-ligand pair). Nonetheless, are we looking at several hundred milliseconds? Several seconds? Several minutes?</p>
<p>In the case of CRH, how quickly does CRH-CRH receptor 1 binding lead to the upregulated transcription of POMC mRNA?</p>
<p>If there are any good sources to read about this, I would greatly appreciate it!</p>
| 84
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gene expression
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Limits of gene editing
|
https://biology.stackexchange.com/questions/94862/limits-of-gene-editing
|
<p>I was reading some articles about CRISPR and the world of gene editing, but then a lot of questions for which I couldn't find any answer online came into my mind. Those are all about how far can we edit an organism. So here is the general question, followed by some other to narrow down a little bit this broad subject:</p>
<p><strong>What are the limits of gene edition?</strong></p>
<ol>
<li>Can one edit the genes in its entire body? (as a human, or a multicellular organism)</li>
<li>What are the risks? I heard that some people who did try gene therapy ended up having some of their modified cells turned into cancer. Was is because of gene incompatibility or because of error during the gene editing process?</li>
<li>Can we go as far as adding some chromosomes or changing an entire chromosome? For example, if a male human would like to change their sex, could they switch all their Y to an X?</li>
</ol>
<p>EDIT: I decided to accept the answer from @MattDMo. However, I'm still interested in some development (clues with other technologies...)</p>
|
<p>Your question is very broad, but I'll try to address each of your points briefly.</p>
<ol>
<li><p>It would be nearly impossible to edit the genes in every cell of a human being or other complex organism simply due to the number (and accessibility) of cells. A full-grown human has in the neighborhood of 30 <em>trillion</em> cells - 30,000,000,000,000. Cells in locations such as the brain and central nervous system are protected by the <a href="https://en.wikipedia.org/wiki/Blood%E2%80%93brain_barrier" rel="nofollow noreferrer">blood-brain barrier</a>, which would keep most gene therapy vectors from accessing those cells. There are other reasons why editing each cell in the body is virtually impossible, such as vectors accumulating in the liver, but this is one of the main ones.</p>
</li>
<li><p>Cancer is indeed a risk from gene therapy in general, although DNA editing technologies like CRISPR in particular have a lower risk due to thTe circumstances surround exactly how the therapy is delivered to the nucleus of the cell where DNA resides. Other risks include potentially serious or fatal systemic inflammation due to an immune reaction to the viral vector which carries the CRISPR "machinery". Off-target effects can occur due to the wrong cells being targeted (although this risk is generally lower with CRISPR). Additionally, there is the very small but non-zero chance that the genetically-engineered vector could somehow regain its native infectious capability. Newer generations of gene therapy have significantly reduced this chance, however.</p>
</li>
<li><p>Very briefly, no. DNA is made up of "letters" (A, T, C, and G) called bases or base pairs, and typical CRISPR constructs only operate on 10-20 bases at the most — usually it's just one or a couple that are changed. A typical human chromosome has <em>millions</em> of base pairs encompassing hundreds to thousands of genes, so editing, adding, or removing an entire chromosome is simply out of the realm of possibility with this technology.</p>
</li>
</ol>
| 85
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gene expression
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Are the controls for RT-PCR the same as those for RT-qPCR?
|
https://biology.stackexchange.com/questions/96115/are-the-controls-for-rt-pcr-the-same-as-those-for-rt-qpcr
|
<p>I am searching for negative and positive controls for RT-PCR but all the results seem to point towards RT-qPCR. Are the controls the same for both?</p>
<p>I have found</p>
<ol>
<li>-RT control</li>
<li>No template control</li>
<li>exogenous control</li>
<li>endogenous control</li>
<li>no amplification control</li>
</ol>
<p>Do they apply for both or just RT-qPCR?</p>
| 86
|
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gene expression
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Meaning of “gene expression heterogeneity” of embryonic stem cells
|
https://biology.stackexchange.com/questions/96118/meaning-of-gene-expression-heterogeneity-of-embryonic-stem-cells
|
<p>What does it mean if a gene has a heterogeneous expression? Does it describe the differences of patterns of expression of that particular gene in a population of cells that are identical? The papers I have found did not really elaborate on what it meant, and I do not know where else to find the definition.</p>
<p>In particular, I want to understand heterogeneity in the context of stem cells. In the paper by <a href="https://onlinelibrary.wiley.com/doi/full/10.1002/bies.201600103" rel="nofollow noreferrer">Angarica and Sol, 2016</a>, it reads:</p>
<blockquote>
<p>“Experimental studies at the single-cell level have revealed that embryonic stem cells (ESCs), and more generally pluripotent stem cells (PSCs), exhibit significant <em>gene expression heterogeneity</em>.”</p>
</blockquote>
<blockquote>
<p>“Single-cell studies have allowed gene clustering, depending on the levels of heterogeneity in the gene expression landscape in PSCs.”</p>
</blockquote>
<p>Does it have more to do with the variation of its expression in the population?</p>
<blockquote>
<p>“In mouse ESCs genes exist that are uniformly expressed in most cells and exhibiting a unimodal distribution (Oct4, Rest, Tcf3, Sal4); other genes exhibit bimodal expression and are expressed in some populations but not in others (Nanog, Rex1, Tet1, Esrrb), and yet another group of genes display sporadic expression (Neurod1, Klf4, Otx2, Pax6) and are undetected in most cells but highly expressed in some specific subpopulations.”</p>
</blockquote>
<p>Reference:</p>
<ol>
<li><a href="https://onlinelibrary.wiley.com/doi/full/10.1002/bies.201600103" rel="nofollow noreferrer">Angarica and Sol, 2016, Modeling heterogeneity in the pluripotent state: A promising strategy for improving the efficiency and fidelity of stem cell differentiation.</a></li>
</ol>
|
<p><strong>Heterogeneity</strong> is a noun meaning:</p>
<blockquote>
<p><a href="https://dictionary.cambridge.org/dictionary/english/heterogeneity" rel="nofollow noreferrer">the fact of consisting of parts or things that are very different from each other</a></p>
</blockquote>
<p>In scientific use the context determines what is differing.</p>
<p>The context here is gene expression in individual embryonic stem cells (presumably single-cell RNASeq). Here the <em>heterogeneity in expression</em> would be for the genes</p>
<blockquote>
<p>…(Neurod1, Klf4, Otx2, Pax6)</p>
</blockquote>
<p>for which the expression is</p>
<blockquote>
<p>…undetected in most cells but highly expressed in some specific subpopulations.</p>
</blockquote>
<p>The conclusion is that although the embryonic stem cells may <em>appear</em> to be a homogeneous population (all alike) and do show similarities in many genes that they express, they must, in fact be a mixture of two (or more) types. (This makes the generally accepted assumption that the basis for distinguishing cells is the genes they express and the proteins they make.)</p>
<p>Thus the idea, expressed in the question, that the cells are <em>identical</em> is <em>incorrect</em>. I know little about stem cell differentiation, but I would assume the implication is that the subpopulation will differentiate on a different path to the rest of the population, or that it has already started to differentiate, or something of the sort (which I imagine is discussed in the paper).</p>
| 87
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gene expression
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variation in expression accounted for a SNP -- what's a usual percent?
|
https://biology.stackexchange.com/questions/2767/variation-in-expression-accounted-for-a-snp-whats-a-usual-percent
|
<p>I am reading a GWAS paper that found a SNP associated to predisposition to colon cancer and was assessed for gene expression of the nearby gene. They found that the genotype accounted for 55% of the variation in the nearby gene expression. 55% sounds like a lot to me, what is the usual percent accounted for a significant SNP in a study like this?</p>
<ul>
<li><a href="http://dx.doi.org/10.1038/ng.2293" rel="nofollow"> <strong>Dunlop MG, Dobbins SE, Farrington SM, Jones AM, Palles C, Whiffin N, Tenesa A, Spain S, Broderick P, Ooi L-Y, et al.</strong>. 2012. Common variation near CDKN1A, POLD3 and SHROOM2 influences colorectal cancer risk. Nature genetics 44: 770–776.</a></li>
</ul>
|
<p>eQTLs (expression quantitative trait loci) are variants that affect the expression of one or more genes.</p>
<p>There have been several 'genome-wide' studies of SNPs that directly affect expression. The actual effect sizes are hard to pin down in most of them, but in the supplementary data for <a href="http://dx.doi.org/10.1093/hmg/ddr328" rel="nofollow">this paper</a> is a list of the SNPs with the largest effects and coefficients of determination.</p>
<p>There are several common SNPs (cis-acting) that account for >50% of the variation in that genes expression in this (European) population cohort. That being said, that vast majority of variants account for <em>much</em> less variation in the expression, but this is to be expected.</p>
<p>I therefore can fully suppose that a disease-linked SNP could affect the expression of a gene to that degree, particularly if it is an oncogene or tumour suppressor.</p>
<p>Reference:</p>
<ul>
<li><a href="http://dx.doi.org/10.1093/hmg/ddr328" rel="nofollow"> <strong>Wood AR, Hernandez DG, Nalls MA, Yaghootkar H, Gibbs JR, Harries LW, Chong S, Moore M, Weedon MN, Guralnik JM, et al.</strong>. 2011. Allelic heterogeneity and more detailed analyses of known loci explain additional phenotypic variation and reveal complex patterns of association. Human molecular genetics 20: 4082–92.</a></li>
</ul>
| 88
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gene expression
|
Where can I find histograms and tables of prevalence of mutations in cancer?
|
https://biology.stackexchange.com/questions/3090/where-can-i-find-histograms-and-tables-of-prevalence-of-mutations-in-cancer
|
<p>At some point in the past I found a cancer portal site which had aggregated data for the relationships between various mutations and their prevalence in cancer types and tumor data. The data was presented in various pleasantly coloured interactive histograms and you could search per-gene or per-disease. </p>
<p>However after spending a few hours, I cannot find the site again. Though I have found many sites with a great deal of data and nice visualizations.</p>
<p>The nearest looking site, was this one:
<a href="http://plugins.biogps.org/data_chart/data_chart.cgi?id=673" rel="nofollow">http://plugins.biogps.org/data_chart/data_chart.cgi?id=673</a></p>
<p>But that doesn't have the level of detail that I remember.</p>
|
<p>Perhaps you mean <a href="http://www.sanger.ac.uk/perl/genetics/CGP/cosmic?action=bygene&ln=BRCA1&start=1&end=1864&coords=AA%3aAA" rel="nofollow">COSMIC</a>? The <a href="http://www.ebi.ac.uk/gxa/gene/ENSG00000012048" rel="nofollow">EBI Gene Expression Atlas</a> also has pretty charts, but now mutations.</p>
| 89
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gene expression
|
Where can I find the tissue-specific protein expression levels for hTERT (telomerase subunit)?
|
https://biology.stackexchange.com/questions/3404/where-can-i-find-the-tissue-specific-protein-expression-levels-for-htert-telome
|
<p>I find a number of contradictory sources regarding the tissues in which hTERT - the protein - is expressed. Does anybody know some resource that authoritatively (as authoritative or widely-accepted as is possible) lists the various tissues and hTERT's protein expression levels?</p>
<p>Any similar resource for gene expression of hTERT?</p>
|
<p>I have found that biogps.org has all expression data I need:</p>
<p><a href="https://biogps.org" rel="nofollow">https://biogps.org</a></p>
<p><a href="https://biogps.org/#goto=genereport&id=7015" rel="nofollow">https://biogps.org/#goto=genereport&id=7015</a></p>
| 90
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gene expression
|
What do breeders call the effect when a breed resists modification?
|
https://biology.stackexchange.com/questions/5037/what-do-breeders-call-the-effect-when-a-breed-resists-modification
|
<p>It is impossible to breed a blue rose or a cat with a bulldog shape. This is because breeding is limited by gene variations in the population. </p>
<p>What do breeders call this effect?</p>
<p><strong>UPDATE</strong></p>
<p>I guess this term is from medieval and/or handicraft breeders, not modern and hi-tech.</p>
<p><strong>UPDATE 2</strong></p>
<p>I am speaking not about principal impossibility but just about observable or tangible barrier. We can be sure that it is possible to turn dog into cat in billion years, but it is much harder than turn German Shepherd to Yorkshire Terrier, which is possible for hundreds of years.</p>
<p>So, there are are two main types of changes, ones take hundreds of years, others take hundreds of millions of years. Former require genetic recombination while latter require genetic mutation.</p>
<p>This barrier was felt by breeders in practice and caused some versions of anti-evolution beliefs.</p>
<p>I need to know how this barrier is named.</p>
|
<p>I'm honestly not sure if one exists. They simply lack the gene/allele - the only specific term I can think of when it comes to <em>lacking</em> a gene is referencing <strong>Knockout</strong> variations where a researcher purposefully removes a gene from a subject in order to observe the effect.</p>
<p>However, "Knockout Mice/etc." imply intent on behalf of the researcher, not a result of breeding or natural lack of an allele. Perhaps "Genetically Incapable" would be a phrase meaning the same thing - but I'm not aware of any 'official' shorthand for 'Cannot because it's not in their genes.'</p>
| 91
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gene expression
|
How to determine the direction of regulation of a gene by comparing gene expressions?
|
https://biology.stackexchange.com/questions/6885/how-to-determine-the-direction-of-regulation-of-a-gene-by-comparing-gene-express
|
<p>I am just learning about the gene expressions and regulation. Several researches focus on finding the genes of altered gene expressions on a microarray to claim that they have a correlation to a specific disease. </p>
<p>I am confused about how people can determine whether a gene is down-regulated or up-regulated by its gene expression. </p>
<p>Assume we have a few samples of a gene: some of the samples are normal patients samples and rest of them are disease-infected samples. Do we determine the direction of regulation of a gene by the ratio of gene expression of normal/disease-infected samples? </p>
<p>For example, if the ratio of expressions is a negative value, do we say that the gene is a down-regulated gene, otherwise, it is a up-regulated gene ? </p>
|
<p>If you have control expression values $c$ and e.g. disease expression values $d$, you take the ratio: $\frac{d}{c}$. If this is greater than one, it's up-regulated. Usually, the log-ratio is computed: $log\frac{d}{c}$. Now, if this is positive, the gene is up-regulated. </p>
<p>Gene expression values are usually measured genome-wide and then normalized before computing the ratios. So you rarely deal with individual raw expression values.</p>
| 92
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gene expression
|
What is the mechanism of regulation of PER /CRY genes?
|
https://biology.stackexchange.com/questions/8137/what-is-the-mechanism-of-regulation-of-per-cry-genes
|
<p>I've read multiple descriptions of biological/circadian clocks and they all mention PER, CRY and CLOCK genes. While I kinda get how they are connected, what interests me is how these actually regulate each other. <strong>Do these genes encode proteins that once created bind to the DNA and cover the transcription sites for other genes</strong>(like PER protein covering the binding site of CRY)?</p>
<p>A lot of diagrams and descriptions of the process are very complex, and I would appreciate a simple answer (if it exists).</p>
|
<p>Wikipedia gives a very good explanation of this, on the page for the suprachiasmatic nucleus.</p>
<blockquote>
<p>For example, in the fruitfly Drosophila, the cellular circadian rhythm
in neurons is controlled by two interlocked feedback loops.</p>
<p>In the first loop, the bHLH transcription factors clock (CLK) and
cycle (CYC) drive the transcription of their own repressors period
(PER) and timeless (TIM). PER and TIM proteins then accumulate in the
cytoplasm, translocate into the nucleus at night, and turn off their
own transcription, thereby setting up a 24-hour oscillation of
transcription and translation. In the second loop, the transcription
factors vrille (VRI) and Pdp1 are initiated by CLK/CYC. PDP1 acts
positively on CLK transcription and negatively on VRI. These genes
encode various transcription factors that trigger expression of other
proteins. The products of clock and cycle, called CLK and CYC, belong
to the PAS-containing subfamily of the basic helix-loop-helix (bHLH)
family of transcription factors, and form a heterodimer. This
heterodimer (CLK-CYC) initiates the transcription of PER and TIM,
whose protein products dimerize and then inhibit their own expression
by disrupting CLK-CYC-mediated transcription. This negative feedback
mechanism gives a 24-hour rhythm in the expression of the clock genes.
Many genes are suspected to be linked to circadian control by "E-box
elements" in their promoters, as CLK-CYC and its homologs bind to
these elements.</p>
<p>The 24-hr rhythm could be reset by light via the protein cryptochrome
(CRY), which is involved in the circadian photoreception in
Drosophila. CRY associates with TIM in a light-dependent manner that
leads to the destruction of TIM. Without the presence of TIM for
stabilization, PER is eventually destroyed during the day. As a
result, the repression of CLK-CYC is reduced and the whole cycle
reinitiates again. (<a href="http://en.wikipedia.org/wiki/Suprachiasmatic_nucleus#Fruitfly" rel="nofollow">http://en.wikipedia.org/wiki/Suprachiasmatic_nucleus#Fruitfly</a>)</p>
</blockquote>
<p>The suprachiasmatic nucleus (SCN) is a tiny part of our brain residing in the center. It maintains a biological clock through a gene expression cycle in the individual neurons. The mechanism for humans is very similar to the mechanism for fruit flies, as explained above, but to rehash a bit...</p>
<p>In the fruit fly model there are five players: CLK, CYC, PER, TIM, CRY.</p>
<p>CLK and CYC are transcription factors for PER and TIM, and bind to their promoters in order to activate the expression of PER and TIM.</p>
<p>When the expression level of PER and TIM gets very high, the PER and TIM proteins return to the nucleus, and inhibit their own transcription factors (CLK and CYC) through molecular interactions.</p>
<p>The CRY protein is light-sensitive, and so daylight (or artificial light) will cause CRY to destroy the TIM proteins. Without TIM, we no longer get the PER-TIM dimers that inhibit the CLK-CYC transcription factors.</p>
<p>In humans and other mammals it's the same concept, but with slightly different players (e.g., homologous genes).</p>
<p>What's important here is that we have a biological clock on the cellular level. We haven't gone into how this clock is used yet... But, it's my understanding that the SCN uses the information to tell the pineal gland when to produce melatonin.</p>
<p>The melatonin causes us to be drowsy, lowers our body temperatures, and causes us to fall asleep.</p>
<p>You can see another cycle at work here - our body temperature, which rises with wakefulness, and declines with sleep. </p>
<p>This gives a more general answer to how circadian rhythms are used to influence our sleep cycle. Your question was how the genes involved in circadian rhythms regulate each other. The answer is the transcription-translation negative feedback loop described above.</p>
<p>Hope this helps...</p>
| 93
|
gene expression
|
How is gene expression estimated?
|
https://biology.stackexchange.com/questions/8153/how-is-gene-expression-estimated
|
<p>I'm reading <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC509173/pdf/10111227.pdf" rel="nofollow">this fantastic article on estimating body time: Molecular-timetable methods for detection of body
time and rhythm disorders from single-time-point
genome-wide expression profiles</a> and one of the things that is not very clear to me is how the researchers estimated which genes are expressed and which ones are not:</p>
<blockquote>
<p>Total RNA was prepared by using Trizol reagent (GIBCOBRL). cDNA
synthesis and cRNA labeling reactions were performed as described (5).
Affymetrix high- density oligonucleotide arrays (Murine Genome Array
U74A, Version 1.0, measuring 9,977 independent transcripts) were
hybridized, stained, and washed according to the Technical Manual
(Affymetrix). Affymetrix software was used to deter- mine the average
difference (AD) between perfectly matched probes and
single-base-pair-mismatched probes. The AD of each probe was then
scaled globally so that the total AD of each microarray was equal. <strong>The
resulting AD values reflect the abundance of a given mRNA relative to
the total RNA popu- lation and were used in all subsequent analyses</strong></p>
</blockquote>
<p>I'm not sure if I'm reading this correctly - did the researchers look at all RNA available in the cells and calculated the levels of messenger RNA produced by expressed genes? if not, how can the level of expression of a gene be estimated?</p>
|
<p>The technique described here is called microarray. Your question has given me an opportunity to put forth one of my opinions about certain problems of gene expression studies.</p>
<p>Gene expression is a measure of the activity of any gene. If the gene performs its activity in the form of a protein, then its expression should be a measure of the protein. If a gene makes a non-coding RNA then its expression is a measure of the RNA concentration.</p>
<p><em>[You can omit the cases of post-translational modification because of signal transduction. They are highly expressed and transiently but frequently used. ]</em> </p>
<p>Like your example there are many studies which use mRNA concentration as a proxy for protein activity. This proxy works in many cases because transcriptional gene regulation is more frequently used mechanism for imparting stable changes. But the best strategy would always be to measure the proteins also. </p>
<p>Apart from microarray there are several techniques to measure RNA concentration:</p>
<ul>
<li>RNA sequencing (high throughput)</li>
<li>Real-Time PCR (medium throughput)</li>
<li>Northern Blotting (Low throughput, semi-quantitative)</li>
</ul>
<p>Many techniques exist for measuring proteins also:</p>
<ul>
<li>Mass spectrometry (high throughput)</li>
<li>ELISA (Low throughput, quantitative)</li>
<li>Western blotting (Low throughput, semi-quantitative)</li>
</ul>
<p>Usually the <strong>"proxy method"</strong> is used because protein quantification is comparatively more difficult. Antibody based techniques like ELISA and Western blotting have problems of cross comparison of proteins because of the variability of the antibody binding efficiency. </p>
| 94
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gene expression
|
Root hair formation in Arabidopsis
|
https://biology.stackexchange.com/questions/10355/root-hair-formation-in-arabidopsis
|
<p>In arabidopsis, 2 cell types arise in the root epidermis : root hair cells and hairless epidermal cells.</p>
<p>The immature epidermal cells that are in contact with 2 underlying cells of root cortex differentiate into root hair cells whereas the immature epidermal cells having contact with only one cortical cell do not develop root hair.</p>
<p>What is the advantage of this ?</p>
| 95
|
|
gene expression
|
Shine-Dalgarno sequence and expressing proteins
|
https://biology.stackexchange.com/questions/14242/shine-dalgarno-sequence-and-expressing-proteins
|
<ul>
<li>Shine-Dalgarno sequence present in the prokaryotic mRNA plays a role in initiation of translation. In eukaryotes a Shine-Dalgarno like sequence is present but does not play an important role in initiation of translation.</li>
<li>We often try to express a eukaryotic gene in a prokaryote. For example : expressing insulin gene in E.Coli.</li>
</ul>
<p>My question : If eukaryotes do not have the shine dalgarno sequence , then how can a eukaryotic protein be expressed in a prokaryote ? (I am especially interested in knowing about this in case of cDNA expression)</p>
|
<p>Eukaryotes have an analogous sequence called the Kozak sequence. cDNA is easily expressed in prokaryotes by substitution of the Kozak sequence for the Shine-Dalgarno sequence, using standard molecular biology techniques. A caveat is that not all eukaryotic protein will be properly expressed in bacteria because of they lack the ability to carry out post-translational modifications that would occur in a eukaryotic Golgi apparatus (e.g., glycosylation). Insulin is a special case because it is a small, unmodified peptides.</p>
| 96
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gene expression
|
Constitutive mutation in operator gene
|
https://biology.stackexchange.com/questions/14681/constitutive-mutation-in-operator-gene
|
<p>If a constitutive mutation happens in the operator of an inducible operon, does that mean that repressors won't be able to bind them ? Or does it mean that even if repressors are bound, they will not have any effect on the gene ?</p>
<p>I am specifically talking about lac operon.</p>
|
<p>For the lac operon there are two possibilities for constitutive expression mutations:</p>
<ol>
<li>The operator is never closed.</li>
</ol>
<p>Reason: Mutation of the repressor, so its not present, doesn't bind or binds only with very low affinity for the operon.</p>
<ol>
<li>The repressor can not bind.</li>
</ol>
<p>Reason: The binding site for the repressor is mutated.</p>
<p>See this <a href="http://www.ndsu.edu/pubweb/~mcclean/plsc431/prokaryo/prokaryo2.htm" rel="nofollow">Website</a> or this <a href="http://learning.covcollege.ac.uk/content/Jorum/GMB_Gene-organisation-regulation_LM-1.2/page73.htm" rel="nofollow">Website</a> for more information.</p>
| 97
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gene expression
|
regarding genetic disorders related to protein production
|
https://biology.stackexchange.com/questions/19526/regarding-genetic-disorders-related-to-protein-production
|
<p>I am not completely familiar with biology, but i had a genetics course in college along with practicals. Forgive me if there is something wrong with my question.</p>
<p>Is there a genetic disease which results in partially functioning or complete non functioning of genes resulting in little or no production of protein for eg Muscular dystrophy.</p>
<p>so why can't we supply these protein from outside the way we do in the case of diabetes(insulin)?</p>
|
<p>There are many protein deficiency issues caused by genetic mutation for eg: Protein C whose deficiency causes abnormal blood clots. This protein is controlled by the PROC gene whose mutation causes Type I Protein C deficiency (<a href="http://ghr.nlm.nih.gov/condition/protein-c-deficiency" rel="nofollow">reference</a>). </p>
<p>There are treatments of replacing proteins like in the case of Protein C deficiency, protein C concentrates are used (<a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2721356/" rel="nofollow">reference</a>). In the case of Alpha-1-antitrypsin (AAT) deficiency, augmentation is done with weekly intravenous infusion of the AAT protein (<a href="http://copd.about.com/od/aatdeficiency/a/Treatment-Of-Alpha-1-Antitrysin-Aat-Deficiency.htm" rel="nofollow">reference</a>). </p>
<p>So in many cases protein is actually supplied from outside the body and also many protein deficiency conditions can actually be controlled with balanced diets (<a href="http://lifespa.com/protein-deficiency-the-hidden-signs/" rel="nofollow">reference</a>) which unfortunately is not a solution for insulin deficiency. </p>
| 98
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gene expression
|
How to identify the genes that distal enhancers pair?
|
https://biology.stackexchange.com/questions/20799/how-to-identify-the-genes-that-distal-enhancers-pair
|
<p>I am writing a project proposal and I have to talk about this problem: <strong>how to identify the genes that distal enhancers pair</strong>?</p>
<p>I am really new to this topic and I don't know what it is all about. I have been searching the literature but I did not find anything useful. Can someone explain to me what it is all about?
Maybe suggest some papers to me.</p>
|
<p>Check this technique called Chromosome Conformation Capture (3C). Its variants exist such as 4C, Hi-C etc.</p>
<p>Basically, the principle of this technique is based on the physical interaction between the enhancer and promoter that is bridged by a transcriptional modulator(protein). </p>
<ol>
<li>The chromatin is crosslinked</li>
<li>DNA is sheared</li>
<li>The protein is pulled down (Optional)</li>
<li>The fragments of the promoter and enhancer are ligated together and then sequencing/qRTPCR is done. </li>
</ol>
<p>Sequencing (low throughput- sanger) can be used to identify enhancers of a given promoter. qRTPCR can be used to quantify the strength of the association.</p>
<p>What I just said is not a high throughput technique. Hi-C is high throughput variant of 3C. See the protocol <a href="http://www.jove.com/video/1869/hi-c-a-method-to-study-the-three-dimensional-architecture-of-genomes" rel="nofollow">here</a>. </p>
| 99
|
protein folding
|
Protein folding
|
https://biology.stackexchange.com/questions/88978/protein-folding
|
<p>I've two questions
1. Is free ATP available in the cytoplasm of the cell?
2. In the protein folding funnel, prions and other misfolded proteins are located at the local minima of the graph. If ATP was freely available, it could possibly give a kick to the misfolded structure to cross the energy barrier and this should help the structure to fold along the idealistic path. But such a thing does not happen in reality. Why?</p>
|
<ol>
<li>Yes</li>
<li>The energy released by ATP hydrolysis must be coupled, by enzymes, to some other reaction or process in order to be useful. It isn’t magic. There are <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3814418/" rel="nofollow noreferrer">ATP-dependent chaperones</a> that assist in protein folding. </li>
</ol>
| 100
|
protein folding
|
When does protein folding begin?
|
https://biology.stackexchange.com/questions/78477/when-does-protein-folding-begin
|
<p>I had always assumed that protein folding is an independent activity that occurs after translation is complete. However, recently, I learned that intermolecular forces begin shaping the peptide bonds <strong><em>as</em></strong> they exit the ribosome, while translation is still occuring. </p>
<p>This leads me to ask: when do the "stages" of protein folding take place? What is a general "timeline" for protein folding? For example, when do secondary and tertiary structures begin forming? Or, when do things like chaperones bind and act? </p>
|
<h2><strong>When does protein folding begin?</strong></h2>
<p>With reference to time you have asked, it can be after the translation has occurred (called <strong>Translational protein folding</strong>) or while translation is still occuring (called <strong>Co-Translational protein folding</strong>). Here is the <a href="http://www.jbc.org/content/272/52/32715.short" rel="noreferrer">link to an article</a> for basic understanding of co-translational protein folding.</p>
<p>There is a lot of debate on the true time. <em>Experimentalists have amassed extensive evidence over the past four decades that proteins appear to fold during production by the ribosome. Protein structure prediction methods, however, do not incorporate this property of folding</em> (<a href="https://www.ncbi.nlm.nih.gov/pubmed/17646290" rel="noreferrer">reference</a>). </p>
<p>If you are looking at particularly some organisms it is advised to refer to the research articles related to them.The primary mechanism is the interplay between several non-covalent interactions such as hydrophobic effect and hydrogen bonding in a <strong>cooperative</strong> manner (they also follow basic rules of thermodynamics) which leads to a <em>marginally stable</em> tertiary structure.</p>
<h2><strong>When do secondary and tertiary structures begin forming?</strong></h2>
<p>Ofcourse, after Primary structure forms.The alpha helices/beta sheets then fold in a cooperative manner to form a tertiary structure.</p>
<p>One point to note is that, slight variations in these cooperative act causes misfoldingng of proteins which may cause certain diseases.</p>
| 101
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protein folding
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Statistical Analysis of Protein Folding Problem
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https://biology.stackexchange.com/questions/8871/statistical-analysis-of-protein-folding-problem
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<p>I’m new to the field of protein folding. I’ve been searching and came across some books for predicting structures (<a href="http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470470593.html" rel="nofollow">Introduction to Protein Structure Prediction: Methods and Algorithms</a>). Does anyone know whether I can find some code (say in C++, Java, or R) related to the prediction of protein structures? Or, do you know other good articles or books related to the statistics of the protein folding problem?</p>
<p>Thanks for the help.</p>
|
<p>One of the quickest ways to get oriented on what is going in the world of protein folding and modeling is to look at the proceedings of the <a href="http://www.predictioncenter.org/casp10/" rel="nofollow">Critical Assessment of Structure Prediction</a> (CASP). CASP is basically a contest, held every 2 years where anyone can use their algorithm to predict the 3D structure of a protein whose structure is known, but not publicly available. </p>
<p>Its been a few years since I reviewed them results much - it looks like this year was interesting, but a perennial winner has been <a href="http://rosettadesigngroup.com/blog/865/a-plos-one-rosetta-collection/" rel="nofollow">Rosetta</a>, which has turned into an edifice of many suites of software which each execute different tasks in protein folding and modeling. </p>
<p>Open source software is pretty hard to find in this field. The software is complex. It usually includes components of machine and statistical learning, molecular dynamics, specialized algorithms that build up the protein one residue at a time, others which manipulate blocks of the protein structure around in space, electrostatic calculations, you name it. In addition, the software, once it gives some sort of result is quite valuable. I don't think any of these suites has really been released. I know that <a href="https://www.rosettacommons.org/" rel="nofollow">Rosetta</a> is available to use as a web service, but you have to apply for access to the source. I don't think its an easy thing to get. </p>
<p>Some of the most complicated components are available open source. Molecular modeling and molecular dynamics <a href="http://en.wikipedia.org/wiki/List_of_software_for_molecular_mechanics_modeling" rel="nofollow">open source software</a> is quite sophisticated. I think we need an open source protein folding suite open source. I think <a href="http://pmcb.jhu.edu/faculty/shortle-profile.html" rel="nofollow">David Shortle's algorithms</a> might be a candidate for such a suite as its not so complicated and it works in some cases. </p>
<p>This field is pretty obscure and difficult to get around in. There aren't any easy introductions that I know of. Protein structures are computationally expensive and painful to work with in terms of writing software. On the other hand protein folding that really works is a revolutionary breakthrough, at least equal to the impact of the development of computers as a technology. </p>
| 102
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protein folding
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Could AI be applied to protein folding?
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https://biology.stackexchange.com/questions/67115/could-ai-be-applied-to-protein-folding
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<p>Two years later, there is a follow up question to the one asked here: <a href="https://biology.stackexchange.com/questions/30240/how-do-we-know-if-the-foldinghome-project-results-are-right">How do we know if the folding@home project results are right?</a>
Since we are quite sure F@H is working right and following <a href="http://www.tomshardware.com/news/alphago-zero-no-human-data,35730.html" rel="nofollow noreferrer">this article's</a> statement:</p>
<blockquote>
<p>Similar techniques could be applied to protein folding, reducing energy consumption, or searching for revolutionary new drugs and materials.</p>
</blockquote>
<p>...I would like to ask if AI stuff, like deep learning, neural networks and the rest of today's buzz words could be applied to molecular dynamics, especially in the protein folding field?</p>
|
<p>Yes, and no :-)</p>
<p>In the meantime many protein structures can be predicted quite accurately - even those for which no reference fold had been known before. </p>
<p>In this case the important buzz word is "big data": co-mutations (of charged amino acids) that can be found when sequencing many independent genomes. (... which indirectly bypasses the emphasis on dynamics for protein folding)</p>
<p>Editorial: 2017, Science: <a href="http://www.sciencemag.org/news/2017/01/hundreds-elusive-protein-structures-pinned-down-genome-data" rel="nofollow noreferrer">http://www.sciencemag.org/news/2017/01/hundreds-elusive-protein-structures-pinned-down-genome-data</a></p>
<p>Perspective: Soding et al. , 2017, Science ( <a href="http://science.sciencemag.org/content/355/6322/248" rel="nofollow noreferrer">http://science.sciencemag.org/content/355/6322/248</a> ) </p>
<p>Research article: Ovchinnikov et al. 2017, Science ( <a href="https://www.bakerlab.org/wp-content/uploads/2017/01/ovchinnikov_science_2017.pdf" rel="nofollow noreferrer">https://www.bakerlab.org/wp-content/uploads/2017/01/ovchinnikov_science_2017.pdf</a> )</p>
| 103
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protein folding
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Thermodynamics of spontaneous protein folding: role of enthalpy changes
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https://biology.stackexchange.com/questions/51295/thermodynamics-of-spontaneous-protein-folding-role-of-enthalpy-changes
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<p>I'm trying to get clear why protein folding occurs spontaneously.</p>
<p>$$\ce\Delta G=\Delta H-T\Delta S$$</p>
<p>According to thermodynamics the ΔG should be negative for a process to occur spontaneously.
When a protein folds the ΔS (Entropy) is decreasing, because the protein gets more ordered. However I think the forming of the bonds (disulfide and other weak interactions) counterbalance this unfavourable rising entropy by forming an enthalpy (ΔH) which thus would result in a negative ΔG.</p>
<p>However I saw some other explanation online which didn't apply the Gibbs free energy formula to the protein but instead to the water. Because the water is more ordered when the protein is unfolded it would be favourable according to the second law of thermodynamics to fold the protein because after folding the water molecules can move more freely --> higher entropy -->negative ΔG --> spontaneous folding.</p>
<p>So my question is which of these two (or maybe both) are the cause of the spontaneous folding of proteins?</p>
|
<p><strong>Summary</strong></p>
<ul>
<li>The first explanation is commonly encountered.</li>
<li>The second explanation cannot be correct, <em>as it stands</em>, as it ignores the free energy change in the protein.</li>
<li>A modification of the second explanation (perhaps what was intended) is that it is necessary to consider the protein folding and change in the water as being coupled, in which case the overall free energy change — the sum of the two considered separately — is the determinant of protein folding. The assertion would then be that a negative free-energy change in the water system is the deciding factor. This view has been persuasively advocated on the basis of experimental measurements.</li>
</ul>
<p><strong>Free energy change in individual transformations</strong></p>
<p>It is <a href="http://www.ncbi.nlm.nih.gov/books/NBK22584/#A1024" rel="nofollow noreferrer">standard practice in biochemistry</a> to consider the Gibbs Free Energy of transformation of the sort A → B in isolation in determining whether it will proceed spontaneously. A chemical reaction for which ΔG is negative may generate heat (i.e. have a negative enthalpy change (ΔH) ) which affects its aqueous surroundings, but it seems justified to consider the reaction in isolation as there is no sense that the change in the vibration of the water molecules is driving or coupled to the reaction.</p>
<p>This approach has been applied to the structural change of protein folding with the conclusion (consistent with the first explanation) that the change in enthalpy (ΔH) is sufficient to produce a negative ΔG and hence drive protein folding (Citation 1, below).</p>
<p><strong>Free energy change in coupled transformations</strong>
Many biochemical changes involve transformations which individually have a positive free energy change, but are made possible by coupling to another reaction with negative free energy change, of greater magnitude:</p>
<blockquote>
<p>A → B , ΔG<sub>1</sub> = +x</p>
<p>C → D , ΔG<sub>2</sub> = –y</p>
</blockquote>
<p>If y>x and these two reactions are coupled (generally through a complex reaction path on an enzyme) , then we have:</p>
<blockquote>
<p>A + C → B + D , ΔG<sub>overall</sub> = –ve</p>
</blockquote>
<p><em>See</em> also <a href="http://www.ncbi.nlm.nih.gov/books/NBK22439/#A1946" rel="nofollow noreferrer">Berg et al.</a></p>
<p>Although one can reject the second explanation in the question as it stands because it ignores the free energy change in the protein folding, perhaps it was intended to mean that the folding of the protein (A → B) should be considered as coupled to the change in the environment of the water (C → D), and that the negative ΔG for the aqueous environment made a greater contribution to the overall ΔG than that for the protein folding.</p>
<p>Is it valid to consider these two systems as coupled? In the original version of my answer I argued against this point of view, but am no longer convinced by my own arguments. The water environment is clearly essential for the hydrophobic effect — the burying of the hydrophobic residues in the centre of the protein away from the water. This is evident if one considers the same protein in a hydrophobic environment such as a cell membrane — it would not fold. In membrane proteins it is hydrophobic residues that are exposed to the lipid bilayer and it is their interiors that sometimes have hydrophilic channels.</p>
<p>So in this coupled system, what is the determinant of the negative free energy change? Minikel (Citation 2, below) asserts that there is no net enthalpy change for the protein folding, and it is the entropy effect on the ΔG for the aqueous environment that drives the folding. He indicates that this view is supported by differential scanning colorimetry and, although he doesn’t cite references, there is a recent (if rather complex) review of this topic by <a href="https://doi.org/10.1016/j.abb.2012.09.008" rel="nofollow noreferrer">Christopher M. Johnson</a>.</p>
<p><strong>Citation 1: Assertion of role of ΔH of protein</strong></p>
<p>The following explanation, taken from <a href="https://www.wiley.com/college/pratt/0471393878/student/review/thermodynamics/7_relationship.html" rel="nofollow noreferrer">Essential Biochemistry</a>, treats the protein folding in isolation and asserts that change in enthalpy is sufficient to produce a negative free energy change:</p>
<blockquote>
<p>The folding of a protein also provides an example of the "ΔH" and "–TΔS" terms competing with one another to determine the ΔG of the folding process. As described above, the change in entropy of the protein as it folds is negative, so the "–TΔS" term is positive. However, in addition to entropic effects there are enthalpic contributions to protein folding. These include hydrogen bonding, ionic salt bridges, and Van der Waals forces. An input of thermal (heat) energy is required to disrupt these forces, and conversely when these interactions form during protein folding they release heat (the ΔH is negative). When all of these entropic and enthalpic contributions are weighed, the enthalpy term wins out over the entropy term. Therefore the free energy of protein folding is negative, and protein folding is a spontaneous process.</p>
</blockquote>
<p><strong>Citation 2: Rebuttal of role of ΔH of protein and assertion of role of water</strong></p>
<p>The following explanation, taken from <a href="https://www.cureffi.org/2014/09/05/molecular-biology-02/" rel="nofollow noreferrer">on-line lecture notes</a> of of Eric V. Minikel of Harvard University, rebutting the point of view above:</p>
<blockquote>
<p>An incorrect and simplistic view of protein folding is as follows. An unfolded protein has high configurational entropy but also high enthalpy because it has few stabilizing interactions. A folded protein has far less entropy, but also far less enthalpy. There is a tradeoff between H and S here. Note that because ΔG = ΔH - TΔS, increased temperature weights the S term more heavily, meaning that higher temperature favors unfolding.</p>
<p>That entire explanation only considers the energy of the protein and
not that of the solvent. In fact, hydrophobic domains of a protein
constrain the possible configurations of surrounding water (see
explanation above), and so their burial upon folding increases the
water’s entropy. Moreover, it turns out that the hydrogen bonding of
polar residues and the backbone is satisfied both in an unfolded state
(by water) and in a folded state (by each other). Therefore enthalpy
is “zero sum,” and protein folding is driven almost entirely by
entropy.</p>
</blockquote>
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protein folding
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Verifying Protein Folds
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https://biology.stackexchange.com/questions/19974/verifying-protein-folds
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<p>I have recently begun using <a href="http://folding.stanford.edu/home/" rel="nofollow">Folding@Home</a> and I am curious how people are prevented from cheating the system. It seems to me that unless the final result is easily verifiable users could submit bogus folds in order to quickly gain credits. Is it in fact the case that the final results of calculating a protein fold are easily verifiable?</p>
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<p>Besides duplication as verification there are numerous other computational methods to ensure that the result is valid. Proprietary software is used for folding at home so one can safely assume that they check <a href="http://en.m.wikipedia.org/wiki/Md5sum" rel="nofollow">hashes</a> on processors and files regularly. If integrity is broken (by a crash, memory corruption or God forbid injection) the software client side and server side trashes the result. One can imagine that faulty hardware or other problems can result in a ban from the servers.</p>
| 105
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protein folding
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Any good website/book to understand protein folding and enzymes?
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https://biology.stackexchange.com/questions/30810/any-good-website-book-to-understand-protein-folding-and-enzymes
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<p>I'm looking for a good, understandable and simple explanation about protein folding, mechanisms and function, and their relationship with enzymes. </p>
<p>I understand that the protein is a polypeptidic chain, I know its composition, but the part that I really can't figure out is "the folding of proteins", I mean "How a straight polypeptid chain turns into a complex folded structure?"</p>
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<p>Okay, so for introduction the 4 levels of protein structure (each level influences the levels after it):</p>
<ul>
<li>primary (1st): the order of amino acids.</li>
<li>secondary (2nd): alpha-helicies and beta-sheets</li>
<li>tertiary (3rd): complex 3d structure</li>
<li>quaternary (4th) : 3rd+ non-protein elements (ions, co-factors etc)<br>
and / or multple subunits interact. Not every protein has this kind<br>
of structure.</li>
</ul>
<p>I think the first does not need any explanation.</p>
<p>The secondary structure is where amino acids form 2D structures: alpha-helices or beta sheets. From wikipedia on <a href="http://en.wikipedia.org/wiki/Alpha_helix" rel="nofollow noreferrer">a-helix</a> and <a href="http://en.wikipedia.org/wiki/Beta_sheet" rel="nofollow noreferrer">b-sheet</a></p>
<blockquote>
<p>The alpha helix (α-helix) is a common secondary structure of proteins and is a righthand-coiled or spiral conformation (helix) in which every backbone N-H group donates a hydrogen bond to the backbone C=O group of the amino acid four residues earlier (i+4 \rightarrow i hydrogen bonding)</p>
<p>The β sheet (also β-pleated sheet) is the second form of regular secondary structure in proteins. It is less common than the alpha helix. Beta sheets consist of beta strands connected laterally by at least two or three backbone hydrogen bonds, forming a generally twisted, pleated sheet. </p>
</blockquote>
<p>Pictures are from <a href="http://www.nslc.wustl.edu/courses/bio2960/labs/02Protein_Structure/PS2011.htm" rel="nofollow noreferrer">here</a>, that is a great site that explains basic protein strucutre in a quite understandable way.
<img src="https://i.sstatic.net/sS4TT.gif" alt="a-helix"> <img src="https://i.sstatic.net/2omiz.jpg" alt="beta sheet"></p>
<p>These secondary structures are important because they can from motifs with specific functions like DNA binding, interaction surface with other proteins. The aforementioned wiki sites have detailed info. These secondary structures and motifs serve as building block for higher order functions. Between motifs "loose" non-structured parts can be found to allow for flexibility.</p>
<p>Tertiary structure:
This is the level where complex 3D geometric structure is defined. The aforementioned 2D structures are packed into domains - a single functional element of a protein. A single protein can have multiple domains and the relative position of these domains result in the tertiary structure. The domains themselves are connected with loose regions that do not show any high order structure and provide flexibility between the domains. Flexibility is necessary for conformational changes.</p>
<p>The quaternary structure is where non protein elements and / or multple subunits are involved. For example the positioning of the heme group in hemoglobin. Or when monomers from dimers, trimers etc. so in general when mature proteins get together to form a larger complex.</p>
<p>Here is a great image about the different structure levels:
<img src="https://i.sstatic.net/5ER3t.gif" alt="prot structure"></p>
<p>source: <a href="https://dopeahmeanbio.files.wordpress.com/2013/03/333.gif" rel="nofollow noreferrer">https://dopeahmeanbio.files.wordpress.com/2013/03/333.gif</a></p>
<p>So now onto the "how" part :)</p>
<p>As I mentioned in the beginning all levels influence the levels after it. So the amino acid sequence predestines the 2D structures to be formed. The secondary structures themselves are formed by amino acid forming hydrogen bonds with each other. This process occurs "naturrally", so by the inherent properties of the amino acids. At the third level <a href="http://en.wikipedia.org/wiki/Disulfide_bond" rel="nofollow noreferrer">disulfide bonds</a> stabilize the structure. This is also a naturally occuring event. Also binding ions, co-factors, etc also stabilizes the protein strucutre. </p>
<p>The folding process can also be supported by <a href="http://en.wikipedia.org/wiki/Chaperone" rel="nofollow noreferrer">chaperon</a> proteins, These proteins can actively "twist" the polypetide chain using ATP as energy source. They can "sense" if there are hidrophobic amino acid chains facing the outer surface of the protein, a thing usually avoided because these amino acids need to face inner surface of the protein where they can avoid water - this is energetically better. This signal (outward facing hidofobic AAs) indicate that either the protein is un/misfolded or it is damaged because of for example heat - that denatures ("unwinds") proteins.</p>
<p>Finally the <a href="http://en.wikipedia.org/wiki/Protein_folding" rel="nofollow noreferrer">wiki</a> page on protein folding if you need more. I hope this helps.</p>
| 106
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protein folding
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Relation of conformational entropy and protein folding
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https://biology.stackexchange.com/questions/51230/relation-of-conformational-entropy-and-protein-folding
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<p>I'm trying to figure out the relation between conformational entropy and protein folding.
I read the following in Lehninger, <em>Principles of Biochemistry</em> (6th edition): </p>
<blockquote>
<p>Most of the net change in free energy as weak interactions form within a protein is therefore derived from the increased entropy in the surrounding aqueous solution resulting from the burial of hydrophobic surfaces. This more than counterbalances the large loss of conformational entropy as a polypeptide is constrained into its folded conformation.</p>
</blockquote>
<p>In this context the meaning of conformational entropy is that the higher the stability of the proteïn is the lower the conformational entropy is (I think).</p>
<p><em>Why does the surrounding entropy increases because of the burial of hydrophobic residues?</em></p>
<p><em>Why does the burial of those hydrophobic residus couterbalances the large loss of conformational entropy?</em></p>
<p>I think maybe because the unfolded protein has more conformation then the protein when it's folded because of the hydorphobic core, it lowers the possible conformation because the hydrophobic interaction restrict the possiblities. Am I right?</p>
|
<p>This question is an example of an important general problem in chemical biology: “How does an ordered system arise without violating the second law of thermodynamics?” Berg <em>et al.</em>, <em>Biochemistry</em>, addresses this in the following manner:</p>
<blockquote>
<p>The Second Law of Thermodynamics states that the total entropy of a system and its surroundings always increases for a spontaneous process. At first glance, this law appears to contradict much common experience, particularly about biological systems. Many biological processes, such as the generation of a well-defined structure such as a leaf from carbon dioxide gas and other nutrients, clearly increase the level of order and hence decrease entropy. Entropy may be decreased locally in the formation of such ordered structures only if the entropy of other parts of the universe is increased by an equal or greater amount.</p>
</blockquote>
<p>Your question is about the spontaneous folding of proteins. You ask:</p>
<blockquote>
<p>In this context the meaning of conformational entropy is that the higher the stability of the proteïn is the lower the conformational entropy is (I think).</p>
<p><em>Why does the surrounding entropy increases because of the burial of
hydrophobic residues?</em></p>
</blockquote>
<p><strong>Comments on your interpretation:</strong> Do not use the term ‘stability’ in this context. It is not a thermodynamic term and its meaning is imprecise. If we think of entropy as the degree of disorder or randomness, then we can see that <em>Conformational entropy</em> is used by the authors to mean the entropy of the protein as a random coil which can adopt many different structures. This has clearly a greater entropy than the folded protein with (to an approximation) a single structure. The adoption of the folded structure is thermodynamically favoured because it represents a state of lower energy (specifically Gibbs Free Energy) compared with the random coil structures, but entails a loss of entropy.</p>
<p><strong>My answer:</strong> The surrounding entropy increases for the following reason. The surrounding entropy is that of the water molecules vibrating and interacting with other water molecules by means of the δ+ and δ– charges on H and O, respectively. In a system containing a protein with a random coil, the movement of these molecules is restricted by the hydrophobic side-chains they encounter, hence limiting the entropy, as it were. When the protein folds into a globule with polar residues on its surface, the vibrating water molecules are less restricted in their movement and hence have a higher entropy.</p>
<p>Further you ask:</p>
<blockquote>
<p><em>Why does the burial of those hydrophobic residus couterbalances the large loss of conformational entropy?</em></p>
<p>I think maybe because the unfolded protein has more conformation then
the protein when it's folded because of the hydorphobic core, it
lowers the possible conformation because the hydrophobic interaction
restrict the possiblities. Am I right?</p>
</blockquote>
<p><strong>My Answer:</strong> I have explained that in general terms above, in response to your first question. If you want a quantitative, mathematical justification you’ll be pushed to find one. Assuming that there are no other factors involved, we assume that it must be so because of the second law.</p>
<p><strong>Comments on Your Answer:</strong> I don’t understand what you mean by “it lowers the possible conformation”. You can decrease the number of possible conformations — you cannot "lower possible conformation”. I assume English is your first language. You must try to use it more precisely if you are going to write about science (as well as checking your spelling, grammar and capitalization). If I were marking this paragraph as an exam answer I would put a line through it as unintelligible. The key thing is that you are comparing a single conformation of the lowest energy involving specific weak interactions and a polar surface, with a number of conformations which expose hydrophobic residues and restrict the free vibrations of the water molecules.</p>
<p><strong>Further Clarification</strong></p>
<p>The diagram below illustrates the problem:
<a href="https://i.sstatic.net/tmrCN.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/tmrCN.png" alt="Protein folding and entropy" /></a></p>
<p>The protein is changing from a disordered to an ordered state so, its entropy is decreasing:</p>
<blockquote>
<p>ΔS<sub>protein</sub> = x , where x < 0</p>
</blockquote>
<p>Whereas the water is changing from a more ordered to a less ordered state, so its entropy is increasing:</p>
<blockquote>
<p>ΔS<sub>water</sub> = y , where y > 0</p>
</blockquote>
<p>and</p>
<blockquote>
<p>ΔS<sub>total</sub> = ΔS<sub>protein</sub> + ΔS<sub>water</sub> = x + y</p>
</blockquote>
<p>If ΔS<sub>protein</sub> + ΔS<sub>water</sub> = 0 (x + y = 0), we would say that the increase in entropy of the water counterbalances the increase in entropy of the protein. For the folding to occur spontaneously, the total entropy must increase (ΔS<sub>total</sub> > 0 , i.e. x + y > 0) and we would change the previous statement to “<em>more than</em> counterbalances”.</p>
| 107
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protein folding
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Protein folding, extra dimensions and bio-mathematics
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https://biology.stackexchange.com/questions/36740/protein-folding-extra-dimensions-and-bio-mathematics
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<p>One metaphor that I have found to explain how proteins fold so quickly to a native shape is that of <a href="http://www.funtrivia.com/en/SciTech/Biochemistry/Question2795680_51649F.html" rel="nofollow">the blind golfer</a>.</p>
<p>I have made <a href="http://openspark.com/foldit/lowest_energy/" rel="nofollow">a video to illustrate this metaphor</a>. This shows how the shape of a slope can determine precisely where individual elements will end up.</p>
<p>The video represents many zero-dimensional points each following its own one-dimensional path down a three-dimensional slope to end up in a two-dimensional arrangement. Or almost: the one-dimensional paths are curves in three-dimensional space, the final resting surface is not flat, and one marble sits on top of three others.) The movement takes place through the fourth dimension of time.</p>
<p>Proteins form three-dimensional shapes, so the "slope" that their components slide down must be in an extra dimension. </p>
<p>Atoms have been observed to jump through a crystal lattice, without any indication that, in travelling from their start point to their end point, they pass through the three-dimensional space that we can observe. Is it conceivable that the component parts of a protein move through an extra dimension as the protein "folds"?</p>
<p>There are <a href="http://onlinelibrary.wiley.com/doi/10.1002/prot.10230/abstract" rel="nofollow">very simple protein chains</a> whose native folded shape is well known. Is there any data available to suggest what path the different molecules in the protein follow during the folding process? Or do they appear to "jump"?</p>
<p>I imagine that it would be possible to create a mathematical model in n-dimensions to describe the simplest "slope" that the protein molecules could follow as the protein collapses into its native state.</p>
<p>What mathematical work is currently being done in this area?</p>
|
<h2>Short Answer</h2>
<blockquote>
<p>What mathematical work is currently being done in this area?</p>
</blockquote>
<p>A... lot?</p>
<h2>Longer Answer</h2>
<p>The "n-dimensional slope" thing that you're talking about shows up in the modern theory of protein dynamics as the "landscapes" concept. There's no truly standardized form for the theory, so it goes by many names. Try googling <a href="https://en.wikipedia.org/wiki/Folding_funnel" rel="nofollow noreferrer">folding funnel</a>, <a href="https://en.wikipedia.org/wiki/Energy_landscape" rel="nofollow noreferrer">energy landscape</a>, probability landscape, free energy surface, etc.</p>
<h3>adendum</h3>
<p>Oh, and also the current consensus is that the "quantum leap"-style effects that you were talking a little bit about don't play a large role in folding, at least in the initial stages. The current thinking is that most (not all!) of the dynamics of protein folding can be modeled using classical physics. Quantum effects can't come into play until the atoms of a protein are closely smooshed together (ie after the initial "collapse" phase of protein folding has finished).</p>
| 108
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protein folding
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Why is statistical mechanics relevant to RNA and protein folding?
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https://biology.stackexchange.com/questions/45459/why-is-statistical-mechanics-relevant-to-rna-and-protein-folding
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<p>This is a very naive question. As far as I understand the folding of a molecule is governed by the electromagnetic forces between its atoms and also between its atoms and the atoms in the surrounding environment (so basically a many body problem). So I don't understand how statistical mechanics, such as Boltzmann's law, come to play. </p>
<p>To my knowledge statistical mechanics and thermodynamics exist when we have an ensemble of particle such as in a liquid or a gas. So what is this ensemble for the RNA or protein folding problem?</p>
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<p>I’m no physicist, but your statement “To my knowledge statistical mechanics and thermodynamics exist when we have an ensemble of particle such as in a liquid or a gas” is surely incorrect. The problem of protein folding is one of thermodynamics — finding the structure of lowest free energy, and the path by which it is reached from a random coil. </p>
<p>One of the difficulties relating to the path is that of getting ‘stuck’ in a position in the energy landscape from which the protein cannot escape. This is called ‘frustration’ and there is apparently a quantitative treatment of ‘minimal frustration’ using the statistical mechanics of spin gasses. This is mentioned in a review by <a href="http://www.physics.uci.edu/~tritz/BP/curropin.pdf" rel="nofollow">Onuchic and Wolynes</a>, available on-line, which you will probably be able to understand better than I can.</p>
| 109
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protein folding
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How can predicting protein folding speed up drug discovery?
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https://biology.stackexchange.com/questions/97114/how-can-predicting-protein-folding-speed-up-drug-discovery
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<p>I'm asking this as a layperson without much knowledge in biology, so please correct me if my understanding is wrong.</p>
<p>Recently DeepMind's AlphaFold managed to predict protein structure from acid amino sequence with stunning accuracy. We are being told that this could "<strong>pave ways toward advances in drug discovery.</strong>"</p>
<p>But I fail to see how it can happen. From my understanding the combination of protein structure is infinite, and if we tweak a protein structure that works good to fight against a virus, it will either work better or worse, but the key point is <em>we don't know until we try</em>. So essentially this is still a hit-and-miss thing, depending purely on dumb luck.</p>
<p>So how can the fast, accurate prediction of protein folding help in drug discovery?</p>
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<p>Firstly protein structures are not infinite. Most proteins adopt specific structure.<br />
Drugs carry out their function by binding to its target protein. Structure prediction helps drug discovery process in two ways -</p>
<ol>
<li>it allows identification of pockets in target proteins (where drugs can bind) whose structures are not yet solved using experimental methods</li>
<li>it allows in silico experimentation i.e. you can take a large number of molecules and simulate whether they will bind to a specific location in your target</li>
</ol>
<p>I would suggest going through these reviews to get a better overview of the importance of fast and accurate structure determination in drug discovery :</p>
<ol>
<li><a href="https://www.cell.com/structure/comments/S0969-2126(00)00060-5" rel="nofollow noreferrer">Verinde and Hol, 1994, Structure</a></li>
<li><a href="https://portlandpress.com/essaysbiochem/article/61/5/431/78244/Structure-based-drug-design-aiming-for-a-perfect" rel="nofollow noreferrer">Montfort and Workman, 2017, Essays in Biochemistry</a></li>
</ol>
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protein folding
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What is protein folding and how is it relevant to disease?
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https://biology.stackexchange.com/questions/54739/what-is-protein-folding-and-how-is-it-relevant-to-disease
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<p>I am trying to understand what is protein folding and how it could help cure some diseases.</p>
<p>When reading articles about it, it looks like the goal is to find perfect folds for proteins because some diseases are due to proteins that don't fold correctly. I don't understand why do we need to find them in the first place? Don't correctly folded proteins already exist in the body of people who aren't affected by those diseases? Why do we need to manually find those structures instead of simply "reading" the structure of the correctly folded proteins in the body of non affected people?
In the end, is the goal to find the best structure or to find the folding proecess ? Or both ? </p>
<p>Thank you!</p>
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<p>Protein folding is a complex thing. There are huge computer algorithms and huge mainframes which are trying to predict the final 3D structure of a protein. </p>
<p>Knowing the tertiary and the quaternary structure of a protein, allows us to understand why diseases happen. In many cases a mutation of the gene provokes an aberrant protein folding. When the protein is misfolded, it is not able to do its function. This particular condition is called "Proteopathy".</p>
<p><a href="http://link.springer.com/article/10.1385%2FMN%3A21%3A1-2%3A083" rel="nofollow noreferrer">http://link.springer.com/article/10.1385%2FMN%3A21%3A1-2%3A083</a> </p>
<p>If you know the structure of a protein, you are able to design or improve drugs which can directly influence the protein structure and/or function, for example antibody therapies against cancer (Cetuximab-->against EGFR, in colorectal cancer; it is a drug which was very much improved when computers prediction/simulations are used).</p>
<p><a href="https://en.wikipedia.org/wiki/Cetuximab" rel="nofollow noreferrer">https://en.wikipedia.org/wiki/Cetuximab</a></p>
<p>It is hard to find out a protein's structure - for some proteins it can require years!</p>
<p>So you first go from the sequence of the healthy people, then you sequence their genomes, and you use this as reference for the people with certain diseases. You might find eventually some mutation is in certain loci in the genomes of people with a certain disease. Then you can study the protein structures, so you can design some new drugs which might tackle this protein. If the protein is misfolded, like the tau protein in the neurodegenerative diseases, then is good to study the structure of this misfolded protein so you can design some drugs for these protein too. </p>
<p>So in the end the structure is extremely important, but often times you have to study many stages of the protein folding process to understand the possible final structure that one protein might have in the body and/or in a certain disease.</p>
<p>I hope this can help!</p>
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protein folding
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What characteristics of the protein folding process ensure that the energy landscape is a funnel?
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https://biology.stackexchange.com/questions/60289/what-characteristics-of-the-protein-folding-process-ensure-that-the-energy-lands
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<p>The folding funnel hypothesis states that the energy landscape that proteins observe when they fold is funnel shaped with a single global optima. This ensures that no matter what sequence of folds the protein follows, it should eventually end up in the same folded configuration thanks to the laws of thermodynamics.</p>
<p>For example, see this illustration of the energy landscape from <a href="https://www.researchgate.net/profile/Ken_Dill/publication/233770794_The_Protein-Folding_Problem_50_Years_On/links/00b7d51a7648358726000000.pdf" rel="nofollow noreferrer">Dill & MacCallum (2012)</a> "The Protein-Folding Problem, 50 Years On" <em>Science</em> 338 (6110) pp 1042-1046:</p>
<p><a href="https://i.sstatic.net/Fkj9w.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/Fkj9w.jpg" alt="Funnel-shaped energy landscape"></a></p>
<p>Clearly, the folding works because the energy landscape is funnel shaped. Any other configuration, e.g. a landscape with multiple significant local optima or a flat landscape, would result in a protein folding in all kinds of different ways.</p>
<p>What are the characteristics of the overall system that ensure that the energy landscape is funnel shaped, and that nearly any protein in an unfolded state will reach the global optima? (e.g.: is it because the proteins themselves have certain statistical properties? or it is something to do with how the types of "moves" the protein makes on the energy landscape?)</p>
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<p>Naturally occurring proteins are evolved such that this is the case</p>
<p>Natural proteins only occupy a very small amount of sequence space. For a 200 aa protein, there are $20^{200} \approx 10^{260}$ possible sequences. There are nowhere near that many naturally occurring protein sequences, even if you take into account all the different alleles in the different organisms in the world.</p>
<p>What happens when you synthesize and express a random (non-natural) protein sequence? You get junk. It doesn't fold or it aggregates or something else happens. You don't get a stably folded protein. Heck, you don't even need to have a fully unnatural protein. You can take a naturally occurring protein and make a few mutations in it, and end up with non-folded junk.</p>
<p>Evolution has a very strong selective pressure to make sure proteins can fold properly and beat <a href="https://en.wikipedia.org/wiki/Levinthal%27s_paradox" rel="noreferrer">Levinthal's paradox</a>. If a protein can't fold, it can't perform any function in the cell, and thus there's no selective pressure to maintain expression. (The promoters get trashed, and the DNA gets mutated away to "junk" DNA.) Only if the protein is stably folded is selective pressure maintained. So you get the one-in-a-million sequences which does have a decent folding funnel.</p>
<p>So it's not that there isn't protein sequences out there with a flat energy landscape, or an energy landscape with lots of local minima. It's just that whenever such a protein forms, it can't fold. And if it can't fold, it's freed from evolutionary pressure and disappears from the gene pool - either because the organism that holds it can't survive without it, or because random mutations wipe it out with random noise. It's <a href="https://en.wikipedia.org/wiki/Survivorship_bias" rel="noreferrer">survivorship bias</a> -- you see proteins with a reasonably well-formed folding funnel because they're the only ones you <em>would</em> see.</p>
<p><em>(There are proteins out there with less-than-robust folding funnels, or with alternative energy states. A brief search of the literature will turn up a number of examples where protein folding requires cofactors or chaperones. Or where a protein has two different folded states, depending on environmental condition. Or where the most commonly folded state is only a meta-stable state, and there's a more stable conformation which the protein will convert to, if given a chanvce - amyloid fibrils being the most common example. These are refinements on the general principle. You don't need a rock solid folding funnel, you just need one "good enough" for the organisms' purpose.)</em></p>
<hr>
<p>You can see some of this in the "<em>de novo</em>" protein designs that come out of labs like <a href="https://www.bakerlab.org/index.php/publications/" rel="noreferrer">David Baker's</a>. They're able to take a protein topology and use a computer to <a href="https://doi.org/10.1038/nature11600" rel="noreferrer">design a sequence</a> "from scratch" which folds to that topology. But far from all of the sequences which their computer program spits out actually will fold. Only a small fraction of such designs will actually fold into a compact protein. </p>
<p>But one of the things that they've found which improves their success rate is to check the designs by "forward folding". That is, the computer spits out a design which it predicts will be a low-energy sequence for that structure. But just having a sequence which is predicted to be "low energy" isn't enough. As an additional step they run the sequence through a folding simulation to see if the sequence they designed also has a clear preference for the designed state. Roughly speaking, checking if there is a clear "folding funnel" which will drive the protein toward the desired folded state. By doing this subsequent computational check, they're able to greatly increase their success rate when the proteins are actually expressed.</p>
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protein folding
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Why does protein folding not depend on the order in which it is synthesized?
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https://biology.stackexchange.com/questions/88137/why-does-protein-folding-not-depend-on-the-order-in-which-it-is-synthesized
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<p>I read an article recently, written by researcher from Department of Biochemistry, University of Washington, which stated that:</p>
<blockquote>
<p>Similarly, success in de novo protein design bears on the question I get after every talk about the importance of the order of chain synthesis on the ribosome to protein folding; computational protein design calculations completely ignore the order of synthesis which hence cannot be critical to protein folding.</p>
</blockquote>
<p>I was wondering, how could it be that the form that the protein is folded to, does not have anything to do with the amino-acid sequence that constitute this protein? What I mean, is in case I look at mirror image of a protein, would it fold the same? if I consider for example the sequencers: ser-gly-ala-glu-pro-asp and asp-pro-glu-ala-gly-ser, will they both fold the same? (I think those are d-protein and it's l-protein counterpart)</p>
<p>Can anyone provide evidence that this is, in fact, so. Or do I misunderstand the section quoted?</p>
<p>link to the paper: sci-hub.tw/10.1002/pro.3588</p>
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<blockquote>
<p>how could it be that the form that the protein is folded to, does not have anything to do with the amino-acid sequence that constitute this protein?</p>
</blockquote>
<p>The quote by the researcher says that the form is unrelated to the direction of synthesis (N->C rather than C->N). It implies that <em>all</em> that matters is the amino-acid sequence that constitutes the protein, and that protein folding is driven by thermodynamic stability rather than by kinetics.</p>
<blockquote>
<p>in case I look at mirror image of a protein, would it fold the same?</p>
</blockquote>
<p>Yes, if you had an exact mirror image of a protein alone in solution it would adopt the same fold but mirrored. The N and C-temini would be on the same amino acids but all amino acids would be D rather than L chirality. This molecule would not generally be found in biology, since typically life uses L-amino acids. It would have different enzymatic behaviour on chiral molecules.</p>
<blockquote>
<p>if I consider for example the sequences: ser-gly-ala-glu-pro-asp and asp-pro-glu-ala-gly-ser, will they both fold the same? (I think those are d-protein and it's l-protein counterpart)</p>
</blockquote>
<p>These are not mirror images, they are entirely different molecules. They are not chiral counterparts (L and D). In general they would not fold to the same structure as the CO and N groups in the backbone are flipped, see more <a href="https://www.reddit.com/r/askscience/comments/34npph/if_you_reversed_a_proteins_primary_sequence_would" rel="nofollow noreferrer">on reddit</a>. However this is a topic of research and some reversible sequences have been found, see <a href="https://www.nature.com/articles/srep25138" rel="nofollow noreferrer">Zhang2016</a> and <a href="https://www.pnas.org/content/97/6/2562" rel="nofollow noreferrer">Mittl2000</a>.</p>
<p>On a deeper level, the researcher's claim that synthesis direction (and hence synthesis broadly) is unimportant is not clear cut. For designed proteins it may be true but these are small and hyperstable. For larger proteins and protein complexes kinetics play more of a role, and chaperones may be used to protect a growing chain as it comes off the ribosome. See for example discussion in <a href="https://biologydirect.biomedcentral.com/articles/10.1186/s13062-018-0217-6" rel="nofollow noreferrer">Sorokina2018</a> and <a href="https://academic.oup.com/bioinformatics/article/23/13/i142/227205" rel="nofollow noreferrer">Deane2007</a>.</p>
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protein folding
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Why is it thought that protein folding is determined solely by amino acid sequence?
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https://biology.stackexchange.com/questions/86264/why-is-it-thought-that-protein-folding-is-determined-solely-by-amino-acid-sequen
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<p>It seems that it is a generally accepted idea that protein folding is completely determined by the sequence of amino acids, but why do people believe that? Is it simply that no example of a protein with two different functional foldings (possibly with different functions) is known, or is there some theoretical reason that it would be impossible for such a protein to exist?</p>
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<p>This question is, in my opinion, based on an incorrect premise but nevertheless throws up a number of points about protein folding and protein structure that can be addressed, albeit briefly.</p>
<p><strong>The False Premise</strong></p>
<blockquote>
<p>“it is a generally accepted idea that protein folding <strong>is completely determined</strong>
by the sequence of amino acids”</p>
</blockquote>
<p>(My emphasis.) </p>
<p>No…</p>
<p><strong>What is thought to determine protein folding?</strong></p>
<p>The basic principle thought to be the main determinant in protein folding is thermodynamic. If possible†:</p>
<blockquote>
<p>“A protein will fold so that <em>the whole system of which it is a component</em> is
in the state with the lowest Gibbs Free Energy”</p>
</blockquote>
<p>Thus, the protein itself is <em>a major contributor</em> — but <em>not the sole contributor</em>.</p>
<p>There is no argument that amino acid sequence (and composition) will be an important determinant of the contribution of the protein to the thermodynamically most favourable state, as the chemistry of the amino acid residues determine how it can interact chemically with its environment (albeit with weak interactions) and how it may interact with itself to produce a conformation which may have an appropriate effect on the entropy of the whole system. </p>
<p>So this is viewpoint is based primarily on <em>chemical thermodynamic assumptions</em>, rather than special ideas of molecular biology. An elementary exposition of this idea can be found in <a href="https://www.ncbi.nlm.nih.gov/books/NBK22567/#A170" rel="nofollow noreferrer">Berg <em>et al.</em> Section 1.3.4.</a></p>
<p><strong>How can the environment affect protein folding?</strong></p>
<p>One major influence is whether the protein is in an aqueous (hydrophilic) environment, like the cell cytoplasm, or a non-aqueous (hydrophobic) environment, like the cell membrane. In the former environment a protein will fold so as to expose its hydrophilic residues to the environment, in the latter its hydrophobic residues (discussed, in <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1308317/" rel="nofollow noreferrer">this paper</a>, for example). Or it may be unable to fold at all in the wrong environment.</p>
<p>Another influence on the folding of a polypeptide chain may be the presence of another polypeptide chain with which it can interact, as in the case of the alpha and beta subunits of haemoglobin (see the <a href="https://www.nature.com/articles/228726a0.pdf" rel="nofollow noreferrer">classic paper by Perutz (1970)</a>)</p>
<p>Small molecules can influence the structure of a protein such as in the case of 2,3-diphosphoglycerate (2,3-BPG) on haemoglobin mentioned below.</p>
<p>When a protein is synthesized in an environment unconducive to correct folding it may require a <a href="https://en.wikipedia.org/wiki/Chaperone_(protein)" rel="nofollow noreferrer">chaperone protein</a> to transport it to an appropriate environment.</p>
<p>And if the final structure of a protein requires covalent linkages, e.g. <a href="https://www.sciencedirect.com/science/article/pii/S096800041100082X" rel="nofollow noreferrer">between the SH groups of cysteine residues</a>, an enzyme is need to oxidize them.</p>
<p><strong>What evidence do we have for this?</strong></p>
<p>We have evidence that some proteins that have been unfolded by putting them in environment that is thermodynamically unfavourable to their native (end enzymatically active) structure can refold when the environment is slowly returned to one that is favourable. This is the famous Anfinsen experiment with ribonuclease (described in <a href="https://www.ncbi.nlm.nih.gov/books/NBK22342/" rel="nofollow noreferrer">this book section</a>). Important as this experiment was in supporting the thermodynamic idea and showing that the contribution of the protein was inherent in its own composition, it does not prove that this is what happens <em>in vivo</em>, nor that the structure formed is the one with the lowest thermodynamic free energy.</p>
<p>The importance of individual amino acids in the sequence is attested by examples such as the mutation of a single amino acid in beta-globin in sickle-cell anaemia (glutamic acid to valine). Under certain circumstances this allows the haemoglobin molecules to polymerize into long fibres because of the interaction of the hydrophobic valine residues with residues in another subunit rather than with water.</p>
<p><strong>Different states of folding are possible in a single protein</strong> </p>
<p>This addresses the section of the question regarding a possible:</p>
<blockquote>
<p>…example of a protein with two different functional foldings</p>
</blockquote>
<p>There are many so-called allosteric proteins that are regulated by interaction with small molecules (their environment) which cause a shift from one conformation to another. The example <em>par excellence</em> is haemoglobin, which is in an equilibrium between two states that are influence by the binding of oxygen, hydrogen ions (i.e. the acidity of the blood) and <a href="https://biology.stackexchange.com/questions/55683/effect-of-2-3-bisphophoglycerate-2-3-bpg-on-haemoglobin">2,3-BPG</a>. </p>
<p>Another type of example is the shift that can occur between the secondary structures producing <a href="https://en.wikipedia.org/wiki/Amyloid" rel="nofollow noreferrer">amyloid proteins</a>.</p>
<p><strong>†Can we be sure that a protein always adopts the structure of the lowest energy?</strong></p>
<p>No. </p>
<p>The manner in which a random coil is a highly complex field, but, in brief, one can imagine that the path to the structure of lowest energy is blocked in some way (an energy barrier that would have to be overcome, perhaps) so that the structure adopted is, instead, the lowest attainable in practice.</p>
<p><a href="https://i.sstatic.net/tdony.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/tdony.png" alt="Energy Landscape"></a></p>
<p>[A rugged energy landscape with hills, traps and energy barriers and some narrow throughway paths to native — from <a href="https://www.nature.com/articles/nsb0197-10" rel="nofollow noreferrer">Dill & Chan, 1997</a>]</p>
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Predicting protein folding with Alphafold
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https://biology.stackexchange.com/questions/103194/predicting-protein-folding-with-alphafold
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<p>I’m trying to figure out how to use Alphafold, which is a biological analysis software for predicting the folding of amino acid sequences. I’ve been trying to follow the directions on the creators’ website for downloading it and using it but there’s one part I don’t understand (see the sections mentioned in the link below), and because a mistake here could be costly, I would like to understand it before I make a mistake. To me, the website seems to be saying that I have to download the software, and then also download the two terabytes worth of data that the model was trained on, and that having both the sotware and the training data will allow me to predict the folding of new amino acid sequences (kind of like if I’d have to train the model myself). This seems odd to me because although I don’t know much about modelling software, it was my understanding that the software creators use data to train a model, find what model would best predict new inputs, and then give you that pre-set model.</p>
<p>My question - do I have to download both the Alphafold model and all that data in order use the software to predict the folding of new amino acid sequences? In particular, if I really only just want a visualization of the folding and accompanying statistics, is this the simplest way for someone with little background in programming (although my university does have the storage capacity for the data if need be)?</p>
<p>(See the Model Parameters and Running Alphafold sections of this github link: <a href="https://github.com/deepmind/alphafold" rel="nofollow noreferrer">https://github.com/deepmind/alphafold</a>)</p>
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<p>If you have little experience with programming, I strongly suggest using the <a href="https://colab.research.google.com/github/deepmind/alphafold/blob/main/notebooks/AlphaFold.ipynb" rel="nofollow noreferrer">official Google Colab notebook</a> for AphaFold. It really involves only some button clicks and pasting the amino acid sequence.</p>
<p>This notebook folds without templates, but there is another <a href="https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/AlphaFold2.ipynb" rel="nofollow noreferrer">unofficial notebook</a> that uses the template generation.</p>
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How can computer predictions of protein folding be verified computationally?
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https://biology.stackexchange.com/questions/34344/how-can-computer-predictions-of-protein-folding-be-verified-computationally
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<p>Currently, there is a lot of research focused on solving the folding patterns of proteins using computers (Folding@Home, <a href="https://fold.it/portal/">https://fold.it/portal/</a>, etc.).</p>
<p>The question that I have is: How do you know when you get it right? Is there some way of verifying, <em>in silico</em>, that you have found a legitimate/correct structure for a protein?</p>
|
<h2>Overview</h2>
<p>Modelling has come on leaps and bounds over the last decade or so and in many cases has acted as a sometimes viable, and inexpensive substitute for experimental structures.</p>
<blockquote>
<p>How do you know when you get it right? </p>
</blockquote>
<p>Ultimately, one still <strong>needs experimental evidence</strong> to <em>know</em> when a model generated <em>in silico</em> is right. But there are ways of scoring a model for how <em>likely</em> it is to be right.</p>
<blockquote>
<p>Is there some way of verifying, in silico, that you have found a legitimate/correct structure for a protein?</p>
</blockquote>
<p>There are lots of ways to score and verify your models. Each method tells you something slightly different about the merits, or lack thereof, of your structural model. Some are designed to weed out the obviously awful models and some allow you to detect exactly where your model looks to be accurate or inaccurate.</p>
<h2>MODELLER Homology modelling output verification on the fly.</h2>
<p>I am most familiar with modeller for homology modelling. Other softwares are available and they are each evaluated by <a href="https://en.wikipedia.org/wiki/CASP" rel="nofollow noreferrer">CASP</a> every two years since 1994.</p>
<p>In homology modelling there are 3 common scoring systems that can be used to assess the biochemical viability of a model. <a href="https://salilab.org/archives/modeller_usage/2013/msg00016.html" rel="nofollow noreferrer">This email</a> covers when to use each one. My answer expands and explains a bit more.</p>
<p><a href="http://salilab.org/modeller/9.11/manual/node468.html" rel="nofollow noreferrer"><strong>molpdf</strong></a> is the Modeller objective function.
<strong>GA341</strong>, discussed <a href="http://salilab.org/pdf/John_NucleicAcidsRes_2003.pdf" rel="nofollow noreferrer">here</a> is derived from Z-score (calculated with a statistical potential
function), which is a target-template sequence identity, and a
measure of structural compactness.
<strong>DOPE</strong> is a more up to date method, first published in 2006, and is more true to "biological viability". From <a href="http://salilab.org/pdf/Shen_ProteinSci_2006.pdf" rel="nofollow noreferrer">the publication</a>:</p>
<blockquote>
<p>DOPE is based on an improved reference
state that corresponds to noninteracting atoms in a homogeneous sphere with the radius dependent on
a sample native structure; it thus accounts for the finite and spherical shape of the native structures.</p>
</blockquote>
<p>Which to use depends on what you want to do with the model, but of those three scores, DOPE is the most reliable at separating native-like models from "decoys". DOPE is usually the starting place for figuring out which models might be right and which models are just plain rubbish.</p>
<p><strong>Note:</strong> If you use Rosetta then there will be equivalents to these, or you can run your generated models through these techniques. If you are using <a href="http://swissmodel.expasy.org" rel="nofollow noreferrer">SWISS MODEL</a> that comes with it's own somewhat black box verification techniques but you can still export the model for further verification.</p>
<h2>General model check against experimental data.</h2>
<p>A further validation of homology modelling methods or other structural models is <a href="https://prosa.services.came.sbg.ac.at/prosa.php" rel="nofollow noreferrer"><strong>ProSA</strong></a>. ProSA provides a great visual representation of where the z-score lies amongst actual crystal and NMR structures. There are probably others that do similar functions, but this is my personal go-to to get an idea of where my structure lies among experimentally gathered structures.</p>
<h2>Sensitive residue by residue verification.</h2>
<p>Although the aforementioned methods examine each residue, they usually output an overall score. Residue by residue scores are also available and require a lot of careful interpretation. For example, if you are analysing catalytic activity, a surface looping region that scores poorly might not be an issue, but a core catalytic residue that scores poorly renders the model useless. This means that just because your model has a good (lower) overall DOPE score than another model, doesn't mean it is necessarily a more accurate model for what you are interested in. </p>
<p>There are plenty of sensitive modelling scoring systems. Some of which are <strong>XdVal, MTZdump</strong>, the famous albeit old-school <strong>Ramachandran Plotting</strong> method, <strong>pdbU</strong>, <strong>pdbSNAFU</strong>, <strong>PROCHECK</strong>, <strong>Verify3D</strong>, and <strong>ERRAT</strong> to name a few. Each has a place when checking how <em>correct</em> your model is.</p>
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What proportion of proteins require chaperone-assisted folding?
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https://biology.stackexchange.com/questions/76165/what-proportion-of-proteins-require-chaperone-assisted-folding
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<p>I am new to the field of biochemistry (I am a chemist, actually).</p>
<p>I have long known the process of folding as the process that leads to the minimum energy conformation of a protein.</p>
<p>Now, I am introduced to the chaperones, that I didn't know before.</p>
<p>What I am wondering is: my previous view of folding, as a proces of "self-assembly" (the protein folds without external assistance as it is assembled by the ribosome) is real, or any folding process is assisted by chaperones?</p>
<p>If both processes exist, how frequent is the "assisted" folding, compared to the spontaneous process?</p>
|
<p>I'm reminded of a lovely <a href="https://www.ncbi.nlm.nih.gov/pubmed/9538692" rel="nofollow noreferrer">review in Trends in Biochemical Sciences</a> that discusses chaperone independent, partially dependent, and fully dependent proteins in prokaryotes. The conclusion was that smaller polypeptides are less likely to require chaperone assistance. This is their figure:</p>
<p><a href="https://i.sstatic.net/L3FrW.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/L3FrW.png" alt="enter image description here"></a></p>
<p>That principle still holds to a certain extent (in prokaryotes), but folding assistance is <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3431865/" rel="nofollow noreferrer">now more broadly understood</a> to include much more than just specific proteins identified as molecular chaperones. The Anfinsen postulate (that the final tertiary structure of a protein depends only on its primary structure) may still hold for small globular proteins, but folding in vivo is almost certainly <em>always</em> assisted. Since you're coming from the perspective of a chemist, don't think of it as a reaction between two molecules in solution. It's a reaction in a gel packed with complex sugars, lipids, proteins, and nucleic acids. </p>
<p>If you're skeptical of the perspective of a crowded cytoplasm, read the review I linked. It's an important but often under-appreciated aspect of in vivo biochemistry. There is <em>much</em> more to read about it. You might try looking up Allen Minton (AP Minton) and macromolecular crowding in your favorite database.</p>
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protein folding
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What is Genome Folding?
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https://biology.stackexchange.com/questions/57195/what-is-genome-folding
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<p>Why does <a href="https://openi.nlm.nih.gov/detailedresult.php?img=PMC3102647_2046-1682-4-8-1&req=4" rel="nofollow noreferrer">genome folding</a> have such great interest? </p>
<p>For protein folding I could say that's important because protein's functionality closely depends on its folded state, since it affects its mechanical properties etc.</p>
<p>But genome? What does it even mean to be folded? Where does it happen? Any reference to papers would be appreciated. </p>
| 118
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protein folding
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Proteins folds: relation to splicing and post-translational modification?
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https://biology.stackexchange.com/questions/71358/proteins-folds-relation-to-splicing-and-post-translational-modification
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<p>Is the secondary structure pattern of protein folds related in any way to alternative splicing and post-translational modification?</p>
| 119
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protein folding
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How to obtain a list of proteins sorted by the ~1400 unique protein folds?
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https://biology.stackexchange.com/questions/44162/how-to-obtain-a-list-of-proteins-sorted-by-the-1400-unique-protein-folds
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<p>The databases CATH and SCOP both have around 1400 unique protein folds recorded from analysis of the PDB. However, I do not see any method to access this particular data.</p>
<ol>
<li><p>A list of each of the 1400 folds (just an id number, and/or a descriptor)?</p></li>
<li><p>For each individual fold (of the 1400), a list of PDB IDs for proteins which are known to adopt each individual fold? </p></li>
</ol>
|
<p>If there is a simple way provided to do this it is very well hidden. The tedious and stupid way to do 1 (get a list of folds) would seem to involve rolling your own:</p>
<ol>
<li><p>Go to <a href="http://scop.berkeley.edu/ver=2.07" rel="nofollow noreferrer">http://scop.berkeley.edu/ver=2.07</a> (or whatever is the latest version).</p>
</li>
<li><p>Click on each of the 12 classes in turn. e.g. (a) all alpha proteins will take you to <a href="http://scop.berkeley.edu/sunid=46456" rel="nofollow noreferrer">http://scop.berkeley.edu/sunid=46456</a> .</p>
</li>
<li><p>Save the source of each page as text.</p>
</li>
<li><p>Write and run your own parser to pull out the sunid (<em><strong><strong>) from the <a href="http://scop.berkeley.edu/sunid=" rel="nofollow noreferrer">http://scop.berkeley.edu/sunid=</a></strong></strong></em> and the description line if you wish. (This assumes you program.) I think this sunid is the fold id.</p>
</li>
</ol>
<p>If you can than find some database or table that has PDB and sunid values in it, you can write another program to find the answer to 2.</p>
<p><strong>Alternatively…</strong> (appended January 2021)</p>
<ol>
<li>Download <a href="http://scop.berkeley.edu/downloads/parse/dir.cla.scope.2.07-stable.txt" rel="nofollow noreferrer">dir.cla.scope.2.07-stable.txt</a> (or the latest version)</li>
<li>Save as a text file.</li>
<li>Open in Mircorsoft Excel. (Just dragging onto the app icon formatted it properly on my Mac. Your mileage may vary.)</li>
<li>You can just select the column with the ids, paste into another sheet, and then remove duplicates to get all the different fold ids. (Alternatively, you have about 276,000 entries to do with whatever you wish.)</li>
</ol>
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protein folding
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Is protein folding symmetric with respect to reversing the sequence order?
|
https://biology.stackexchange.com/questions/73105/is-protein-folding-symmetric-with-respect-to-reversing-the-sequence-order
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<p>Suppose that I have two proteins, protein A and protein B, and suppose that the sequence of amino acids of protein B is exactly the reverse of the sequence of protein A.</p>
<p>For example (these are made-up proteins):</p>
<pre><code>protein A = [G,A,L,G,M,F,R]
protein B = [R,F,M,G,L,A,G]
</code></pre>
<p>Will the 3D structure of protein B be somehow identical, or perhaps the mirror image, of the 3D structure of protein A?</p>
|
<p>No! Although there is a relationship, the protein would not fold properly since the C and N terminals are reversed consider the following: </p>
<p>H(NH)-A-C(=O)(NH)-B-C(=O)(NH)-C-C(=O)(NH)-D-C(=O)(NH)-E-(C=O)OH</p>
<p>as appose to :</p>
<p>HO(C=O)-A-(NH)(C=O)-B-(NH)(C=O)-C-(NH)(C=O)-D-(NH)(C=O)-E-(NH)H</p>
<p>These are completely different molecules! </p>
<p><a href="http://www.ncbi.nlm.nih.gov/pubmed/1604320" rel="nofollow noreferrer">http://www.ncbi.nlm.nih.gov/pubmed/1604320</a> <a href="http://www.pnas.org/content/95/13/7287.long" rel="nofollow noreferrer">http://www.pnas.org/content/95/13/7287.long</a> <a href="http://www.pnas.org/content/111/32/11679" rel="nofollow noreferrer">http://www.pnas.org/content/111/32/11679</a></p>
| 121
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protein folding
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What does 'kinetically accessible' mean in protein folding?
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https://biology.stackexchange.com/questions/77790/what-does-kinetically-accessible-mean-in-protein-folding
|
<p>The <a href="https://en.wikipedia.org/wiki/Hydrophobic_collapse" rel="nofollow noreferrer">hydrophobic collapse model</a> discusses this term in the energetics section. What does this actually mean?</p>
|
<p>At some point during protein folding, there may exist lower energy states from a thermodynamic perspective (lower ΔG free enegy) which are actually unreachable in a given environment, because the required <a href="https://en.wikipedia.org/wiki/Activation_energy" rel="nofollow noreferrer">activation energy</a> is too high. These are kinetically inaccessible states, conversely accessible state are those that can be reached.</p>
<p>For example, that could mean a protein could reach a lower energy state by unfolding a bit, but exposing hydrophobic amino acid even temporarily would require too much energy. So the lower energy state is not kinetically accessible.</p>
<p>This is somewhat similar to the concept of <a href="https://en.wikipedia.org/wiki/Thermodynamic_versus_kinetic_reaction_control" rel="nofollow noreferrer">kinetic and thermodynamic reaction products</a> in chemistry.</p>
| 122
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protein folding
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Is it possible to isolate and analyse intermediates of protein folding?
|
https://biology.stackexchange.com/questions/30277/is-it-possible-to-isolate-and-analyse-intermediates-of-protein-folding
|
<p>I would like to know if there is an assay which could allow us to analyse a protein before it has assumed its 3D functional form.
While studying structural biology, I only came to know the forces that stabilize the structure, but not the gap between the original random coil and the protein in its native form.</p>
|
<p>Theoretically by <strong>molecular modeling</strong> -- see the works by Harold Scheraga:
<a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=Harold+Scheraga%5BAuthor%5D" rel="nofollow noreferrer">https://www.ncbi.nlm.nih.gov/pubmed/?term=Harold+Scheraga%5BAuthor%5D</a></p>
<hr>
<p>Note: An unfolded protein is not a random coil.</p>
<p>Fitzkee & Rose (2004) PNAS 101:12497-12502; emphasis mine:</p>
<blockquote>
<p><strong>denatured proteins</strong> are biased toward <strong>specific conformations</strong>, in
... conflict with the random-coil model</p>
</blockquote>
<p><a href="https://www.ncbi.nlm.nih.gov/pubmed/15314216" rel="nofollow noreferrer">https://www.ncbi.nlm.nih.gov/pubmed/15314216</a></p>
| 123
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protein folding
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Can a bacterium survive without GroEL protein?
|
https://biology.stackexchange.com/questions/55599/can-a-bacterium-survive-without-groel-protein
|
<p>In prokaryotes, GroEL protein (together with GroES) is required for protein folding. </p>
<p>Question: Can a bacterium survive without GroEL protein?</p>
|
<p>In E. coli, GroEL/GroES is found to interact with about 10% of all soluble proteins (Kerner et al. Cell 2005) and is the only chaperone essential to the bacterium under all tested conditions (Horwich et al. Cell 1993).</p>
| 124
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protein folding
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why do chaperones bring protein into mitochondria? why would mitochondria need protein?
|
https://biology.stackexchange.com/questions/64442/why-do-chaperones-bring-protein-into-mitochondria-why-would-mitochondria-need-p
|
<p>Sounds trivial? Please help to sort out. I saw this picture while looking at dehydration reactions and cell revision. </p>
<p><a href="https://i.sstatic.net/LiI6U.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/LiI6U.jpg" alt="enter image description here"></a></p>
<p>And proceeded to the <a href="http://faculty.samford.edu/~djohnso2/44962w/405/_11protsorting.html" rel="nofollow noreferrer">reference web page.</a> </p>
<blockquote>
<p>Protein Folding and Processing in the ER: Various changes occur to proteins in the ER.
Chaperones and Folding: Polypeptides must assume the correct folding pattern in order to function properly. The correct folding of a protein is mediated by chaperones (they also are proteins--chaperones are abundant in the ER lumen). A completed polypeptide will assume the correct folding pattern spontaneously, however before translation is complete, it could assume an incorrect formation or it could aggregate with other partially made polypeptides. To prevent this, chaperones in the ER (and cytosol) bind to the nascent polypeptide and keep it from interacting with anything until the polypeptide is completely synthesized. (<strong>Chaperones bind to polypeptides destined for mitochondria</strong> then release them as they pass through the mitochondrial membranes. Chaperones on the inside of mitochondria bind until these polypeptides have completely entered.)</p>
</blockquote>
<p>With regards to protein synthesis and folding, this kind of info is not in my textbook. Not in couple of the online open textbooks either. I even search for <code>where do protein fold?</code> to find out if there was a relationship. It doesn't say protein fold in mitochondria and turns out it's a question most scientist are looking for answers.</p>
<p>For whatever protein synthesis I have learnt so far, there was no mentioning of protein strands going into mitochondria but mitochondria as a power houses. What's going on here? </p>
<p>Why would a protein go into a mitochondria? How does it exit and where to?</p>
|
<p>As you probably know, mitochondria (together with chloroplasts) are a very interesting organelle: they are a result of an <a href="https://www.nature.com/scitable/topicpage/the-origin-of-mitochondria-14232356" rel="nofollow noreferrer">endosymbiotc relationship</a> that took place more than 1 billion years ago.</p>
<p>And, because of that, mitochondria have their own (circular, as a prokaryote) DNA. And here comes the common misconception: a lot of students think that mitochondria (and chloroplasts as well), because they have their own DNA, can synthesise <strong>all</strong> proteins they have (the most famous ones are the enzymes of Krebs cycle and Respiratory chain). But that's not correct.</p>
<p>What happened is that, generation after generation, along a very big period of time, mitochondrial genes were, little by little, transferred to the host's nucleus. According to Nature (2017):</p>
<blockquote>
<p>During the course of mitochondrial genesis, many genes were transferred from the genome of the mitochondrial endosymbiont to the genome of the host.</p>
</blockquote>
<p>Thus, today, a human mitochondria has only 37 genes:</p>
<p><a href="https://i.sstatic.net/9HVUx.jpg" rel="nofollow noreferrer"><img src="https://i.sstatic.net/9HVUx.jpg" alt="enter image description here"></a> </p>
<p>From those 37 genes, only 13 code for respiratory proteins. Therefore, those mitochondrial genes are responsible for only a minor fraction of the proteins present in a human mitochondrion. So, where do the other proteins come from?</p>
<p>They come from the nucleus, encoded in the nuclear DNA. Those proteins are synthesised in the cytosol and, using <a href="https://en.wikipedia.org/wiki/Signal_peptide" rel="nofollow noreferrer">peptide signals</a>, are transferred to the mitochondria. According to Dudek, Rehling and van der Laan (2013):</p>
<blockquote>
<p>Most mitochondrial proteins are encoded in the nucleus. They are synthesized as precursor forms in the cytosol and must be imported into mitochondria with the help of different protein translocases. </p>
</blockquote>
<p>According to the <a href="http://www.proteinatlas.org/search/subcell_location:Mitochondria;Validated,Supported" rel="nofollow noreferrer">Human Protein Atlas</a>, 1070 proteins have been detected in the human mitochondria. Thus, since 13 of them are from mitochondrial origin, we conclude that at least 98.7% of the mitochondrial proteins are imported from the cytosol.</p>
<p>Sources:</p>
<ul>
<li>Nature.com. (2017). Origin of Mitochondria | Learn Science at Scitable. [online] Available at: <a href="https://www.nature.com/scitable/topicpage/the-origin-of-mitochondria-14232356" rel="nofollow noreferrer">https://www.nature.com/scitable/topicpage/the-origin-of-mitochondria-14232356</a> [Accessed 5 Aug. 2017].</li>
<li>Dudek, J., Rehling, P. and van der Laan, M. (2013). Mitochondrial protein import: Common principles and physiological networks. Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, 1833(2), pp.274-285.</li>
<li>Proteinatlas.org. (2017). Search: subcell_location:Mitochondria - The Human Protein Atlas. [online] Available at: <a href="http://www.proteinatlas.org/search/subcell_location:Mitochondria" rel="nofollow noreferrer">http://www.proteinatlas.org/search/subcell_location:Mitochondria</a> [Accessed 5 Aug. 2017].</li>
</ul>
| 125
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protein folding
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How does the shape of a protein determine its function?
|
https://biology.stackexchange.com/questions/101805/how-does-the-shape-of-a-protein-determine-its-function
|
<p>There is currently much interest in protein folding and the problems in predicting how the sequence of amino acids determines how proteins fold into specific shapes. Accounts of this generally mention in passing that the shape of a protein determines its function.</p>
<p>How, in fact, does the shape of a protein determine its function?</p>
<p>And, looking at the other side of the coin, is it possible to predict how a protein will behave and function merely from its structure? If so, how?</p>
|
<p>Determining function and predicting function are two separate things. For example, a screwdriver's shape determines its function, but it might be hard to predict that function unless you also see some screws.</p>
<p>There are obviously a zillion different other molecules a protein might interact with, so just from its shape one probably couldn't tell much. However, we normally also have other information about the protein. To start with, the amino acid sequence gives us information about what other proteins are related by evolution; smaller parts of the sequence may include known functional motifs.</p>
<p>Also, experimental work may indicate other molecules that physically interact with the protein, and we may then be able to identify if a part of the protein "matches up" with part of another known molecule (this is the "lock and key" idea). Genetic analysis may show that changes in the protein tend to affect a certain function, and so forth.</p>
| 126
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protein folding
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Are Hsp70 proteins only activated in response to heat shock?
|
https://biology.stackexchange.com/questions/89224/are-hsp70-proteins-only-activated-in-response-to-heat-shock
|
<p>Hsp70 proteins are chaperones that assist in protein folding in my plant physiology textbook it says the Hsp70 proteins were discovered by inducing heat shock. But do they only work in response to heat shock stress? </p>
<p>I know these types of proteins are found in many organisms but I am interested in how they assist on protein folding or stress response in plants specifically. </p>
| 127
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protein folding
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What I can do in order to improve the folding of the protein?
|
https://biology.stackexchange.com/questions/19151/what-i-can-do-in-order-to-improve-the-folding-of-the-protein
|
<p>I am struggling with the expression of the certain protein. It seems that it is not properly folded and thus, it is not active. I tried to express it at the lower temperature and for the longer time, but it did not help. Can anyone give me a clue what I can try to do?</p>
<p>The size of the protein is around 55 kDa. I know that I have some soluble protein as I run western blot. The protein contain His-taq on the C-terminus so I started with Ni-NTA column chromatography. Steps of purification: </p>
<ol>
<li>Incubation the lysate with resin (30 min/4°C)</li>
<li>Unbound proteins were collected as the ‘Flow-through’ fraction</li>
<li>Wash 1 with buffer: 50 mM NaH2PO4, 1M NaCl, 10 mM Imidazole</li>
<li>Wash 2 with 10% buffer B in buffer A</li>
<li>Elution with buffer B: 50 mM NaH2PO4, 1M NaCl, 250 mM Imidazole</li>
</ol>
<p>Because the protein is co-purified with something else in size around 57 kDa (which might be a chaperone protein) I tried also:
1. add ATP to first wash in concentartion of 2.5 mM and incubate column for 1h/4C
2. add ATP to first wash in concentartion of 2.5 mM and incubate column overnight in 4C
3. add ATP to first wash in concentartion of 2.5 mM and incubate column overnight in room temperature
4. add ATP and glycerol to first wash in concentartion of 2.5 mM for ATP and 4M for glycerol and incubate column for 2h in 4add ATP to first wash in concentartion of 2.5 mM and incubate column overnight in 4C</p>
<p>All the method end up with two close to each other bands (only one of them is my protein) and protein is not active. </p>
|
<p>If you have over-expressed an eukaryotic full length protein or the enzymatic part, then <em>E. coli</em> does not necessarily provide a good environment for its folding so you need to express it in the same system which the original protein came from, e.g. mammalian or Drosophila etc. <em>E. coli</em> over expression is mostly used to generate wast amounts of protein for the purposes of protein sequence based Ab generation amongst other things. Look at this review for some of the solutions it offers for proteins not folding correctly in <em>E. coli</em> when over-expressed (<a href="http://www.biomedcentral.com/1472-6750/4/32" rel="nofollow noreferrer">http://www.biomedcentral.com/1472-6750/4/32</a>).</p>
<p>The remainder of your question is a duplicate of this question (<a href="https://biology.stackexchange.com/questions/19024/ni-nta-purification-problem-with-the-chaperone-protein">Ni-NTA purification, problem with the chaperone protein</a>), which I have provided an extensive answer/comments to!</p>
<p>In addition, since the lack of enzyme functionality is a potential indication of errors in its state/3D structure, it is however not a definitive reason. Could you provide some explanations as to what experiments you have conducted to reach that conclusion and how this second point about chaperone eluding with your protein relevant to the first and the last section of your question?</p>
| 128
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protein folding
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how long do chaperone proteins take to fold a protein?
|
https://biology.stackexchange.com/questions/74779/how-long-do-chaperone-proteins-take-to-fold-a-protein
|
<p>how long do chaperone proteins take to fold a protein?</p>
| 129
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protein folding
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Kinetics and de novo protein prediction
|
https://biology.stackexchange.com/questions/49019/kinetics-and-de-novo-protein-prediction
|
<blockquote>
<p>De novo conformation predictors usually function by producing candidate conformations (decoys) and then choosing amongst them based on their thermodynamic stability and energy state. Most successful predictors will have the following three factors in common:</p>
<p>1) An accurate energy function that corresponds the most thermodynamically stable state to the native structure of a protein</p>
</blockquote>
<p>This is an excerpt from Wikipedia. I have a very, very limited understanding about de novo protein prediction so here goes. </p>
<p>I asked the post-doc I'm working with about whether there are kinetic barriers to protein folding. Yes, everything wants to be at an energy minimum, but sometimes that just can't happen due to kinetic barriers (the reason your diamond ring doesn't turn into graphite/pencil "lead"). So, why does protein prediction software look for energy minimums? Do they also consider activation energy barriers? Do they take into account the presence of chaperonins? Are there examples where the thermodynamically most stable protein conformation is <em>not</em> the biologically active protein? The post-doc told me that perhaps most proteins do reach their thermodynamically most stable state. True? </p>
|
<p>Generally speaking, structure prediction programs look only at the thermodynamic minimum, without consideration of the kinetic trajectory of folding. </p>
<p>The main reason for this is mostly time considerations. It's very difficult to accurately model the true folding pathway of even a moderately sized protein. With special tricks and a bunch of computing power, we're barely able to simulate a folding trajectory of small, simple proteins. We aren't (yet) able to do so with anything of reasonable size.</p>
<p>Instead, what protein structure prediction programs do is take a shortcut, skip the physically-realistic folding simulation, and instead look for low energy models, with the assumption that these low energy states will look like the natively folded proteins. </p>
<p>(One such program I'm familiar with - Rosetta - effectively takes small backbone structures already seen in crystallized proteins, stitches them together and asks if that looks like a reasonable structure for the sequence. If not, it tweaks which backbone fragments it uses, repeating until it gets something it thinks looks good.)</p>
<p>This assumption - that the native structure of the protein is the global energy minimum - is called <a href="https://en.wikipedia.org/wiki/Anfinsen%27s_dogma" rel="nofollow">Anfinsen's hypothesis</a>. One rationale is related to <a href="https://en.wikipedia.org/wiki/Levinthal%27s_paradox" rel="nofollow">Levinthal's paradox</a>: unlike simple chemical reactions, a protein folding trajectory has too many degrees of freedom for even nature to exhaustively sample all conformations. This implies that stably folded proteins evolved with well defined "energy funnels" - that is, the energy landscape of well-folded proteins is such that the folded form is "downhill" from a large number of potential states. Since a large number of potential states need to point toward the folded form, this implies that the local minimum of energy which is the folded form is also likely the global minimum of folding.</p>
<p>The energy differences in protein folding also tend to be small - it's relatively easy for proteins to climb back up of local minimums and go elsewhere. Without the strong, global energy funnel to direct them toward a stable state, it's difficult to keep proteins from unfolding and refolding. This is why kinetic considerations like controlling the trajectory of folding from a ribosome, or having special chaperonins don't really work. Because chaperonins are catalysists, they change the <em>rate</em> of the reaction they're involved in, but not the equilibrium. Microscopic reversibility means that any protein which randomly collect enough energy can use the chaperonin to escape the dead end it was put in: it's not a one-way gate.</p>
<p>Now having the kinetic minimum be the thermodynamic minimum doesn't <em>have</em> to be the case - it's just the case for the vast majority of proteins we've seen. There are certain systems where we're pretty sure the normal folded form is in a local kinetic trap, and with time it can escape into a more stably folded version. Amyloid fibrils and prion proteins are thought to be one such instance. The normally produced version is in a low-energy kinetic minimum, but over time or through various interactions with amyloid or other prion proteins those proteins can relax into an alternative, lower energy conformation.</p>
<p>The keyword here for future literature searches is <em>"kinetic trap"</em>. Some kinetic traps are very short lived (microseconds), but other may be longer.</p>
<p>Finally, I'll point you to the paper "<a href="http://dx.doi.org/10.1146/annurev.biophys.37.092707.153558" rel="nofollow">The Protein Folding Problem</a>" by Dill et al., which is a good review on the topic of protein folding. </p>
| 130
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protein folding
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Solution based measurement of Solvent-Accessible Surface Area of macromolecules
|
https://biology.stackexchange.com/questions/1909/solution-based-measurement-of-solvent-accessible-surface-area-of-macromolecules
|
<p>The Solvent-Accessible Surface Area (SASA) is a valuable metric for looking at protein folding and protein-protein interactions. However, this measurement is typically done by calculating the SASA from a solved (and generally static) structure.</p>
<p>Chemical probes like diazirine and hydroxyl radicals show some bias regarding where they tend to bind. I'm realizing while I'm writing this question that NMR is a perfectly valid method to determine a solution based structure and then calculate the SASA. Similar strategies has also been used to examine structured RNAs. I'm curious about the variety of these methods and how accurate they are.</p>
|
<p>I only know of one method, but here it is. You create a sphere the diameter of the <a href="http://jmol.sourceforge.net/docs/surface/" rel="nofollow noreferrer">VdW radius of water, and then 'roll' it along the surface</a>. I know this as a Richards-Lee surface, wikipedia has another name for it. </p>
<p><img src="https://i.sstatic.net/pBANE.gif" alt="enter image description here"></p>
<p>This looks complicated, but its not. you move the probe sphere along the surface of the molecule in the XY plane until it just touches the vdW radius of the protein, keeping the center of the sphere as the surface, all the way around the molecule. If you like, you can color the surface by the charge of the position too, which is useful for discussing solvent interactions. </p>
<p>Then you translate along the z axis and do another contour until you run out of protein. Apparently jmol and other packages will do this for you. </p>
<p><a href="http://en.wikipedia.org/wiki/Accessible_surface_area#Methods_of_calculating_ASA" rel="nofollow noreferrer">Wikipedia references a more mathematical method LCPO</a>, which I am not so familiar with. </p>
<p>Is this accurate? As usual with such calculations its more of a guess than an answer. You can do the calculation on any structure or any ensemble of structures (like NMR gives). It doesn't understand how the molecule might be flexible or dynamic. If you read up on your physical chemistry you see that proteins breathe and can allow diffusion into the core rather readily. If I recall right, you can get rather large molecules quenching heme flouresence in hemoglobin at room temperature. </p>
<p>If you are looking to dock 2 proteins, SAS might be more useful. Its an important piece of information, but not an ultimate answer. I'm afraid with proteins that doesn't happen so easily. </p>
<p>@bobthejoe asked about SAS for which no structure exists.<br>
This is an extremely difficult thing to even guess at. The non helpful answer is that <a href="http://www.nature.com/nature/journal/v277/n5696/pdf/277491a0.pdf" rel="nofollow noreferrer">the surface of the protein goes as the cube root of the molecular weight of the protein</a>. </p>
<p>By getting a solution of the protein and shooting it in a syhcrotron, you can get a mean radius of gyration pretty easily which will give you an ellipsoidal volume (and surface area) for a protein. Again most of the particulars would be lost and this could easily be off by 25% for an irregularly shaped protein. For a regular globular protein it might give an answer similar to the power law above. </p>
<p>I have seen physical chemistry experiments that look for changes in osmotic pressure when the salt concentration in a solution of the protein changes substantially (Adrian Parsegian's work at NIH in the late 80s). </p>
<p>I doubt you will find any of these answers useful as their mean error is going to be very large (20-200%) and also assumes the protein is soluable and amenable to the experimental conditions. </p>
<p>Solvent probes can help too. For instance exposing the protein to D20 then doing mass spectroscopy on the protein. This is still only going to give you a general idea of how much of the peptide is surface exposed. Protein structure is still pretty necessary to getting any accurate measurement of SAS I think. </p>
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protein folding
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How to manufacture different sized micelles in nano -scale?
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https://biology.stackexchange.com/questions/2343/how-to-manufacture-different-sized-micelles-in-nano-scale
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<p>I am trying to answer <a href="http://tenttiarkisto.fi/exams/9605.1.pdf" rel="nofollow">q5</a>:</p>
<blockquote>
<p><strong>"How can you manufacture micelles in A) nanometerer -scale B) and in ten nanometer -scale?"</strong></p>
<p><strong>My Thinking</strong></p>
<blockquote>
<p><strong>Observations and some thinking</strong></p>
<ol>
<li>Oil in water forms a micelle <a href="http://en.wikipedia.org/wiki/Micelle" rel="nofollow">here</a>, not making it soluble.</li>
<li>Whey protein in Water forms a micelle or is this due to other reason? Protein folding with hydrophopic-tailed-and-hydrophilic-headed-particels? Is this micelle or not?</li>
</ol>
<p><strong>Required Vocabulary about one answer</strong></p>
<ol>
<li>what is IVC? </li>
<li>PLoS? </li>
<li>"[E]xtrusion step" = some sort of burst? </li>
<li>PCR=Polymerase chain reaction <a href="http://en.wikipedia.org/wiki/Polymerase_chain_reaction" rel="nofollow">here</a>. </li>
<li>monodisperse = A collection of objects that <code>"have the same size, shape, or mass."</code> (source
<a href="http://en.wikipedia.org/wiki/Monodisperse" rel="nofollow">here</a>).</li>
</ol>
</blockquote>
</blockquote>
|
<p>A key factor that determines the radii of a micelle is the <a href="http://en.wikipedia.org/wiki/Critical_micelle_concentration" rel="nofollow noreferrer">critical micelle concentration</a>. The other is the the hydrophobicity of the micelles which can be measured using the <a href="http://en.wikipedia.org/wiki/Contact_angle" rel="nofollow noreferrer">contact angle</a>. A lipid nanoparticle has a minimum size on the order of 50 nm due to the surface tension of the lipid bilayer. However, micelles can be much smaller.</p>
<p>As for the creation of uniform nanoparticles, I am going to claim that what I say next can be in no way a reasonable answer to a HW problem. Why? Because the information is hidden in some obscure PLoS paper (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0015275" rel="nofollow noreferrer">Stapleton and Swartz</a>) with 7 citations using IVC. Typically, micelles created for emulsion-PCR are created by vigorous mixing and followed by an extrusion step. However, this creates a polydisperse droplets. Alternatively, if you were to use a microfluidic device, then more monodispersed droplets can be formed. The control of droplet size can be achieved by varying the flow rates of the aqueous phase and the oil phase as well as changing the surfactant.</p>
<p><img src="https://i.sstatic.net/6zbEp.jpg" alt="Micelles"></p>
| 132
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protein folding
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Why is translation so much faster in prokaryotes than eukaryotes?
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https://biology.stackexchange.com/questions/70202/why-is-translation-so-much-faster-in-prokaryotes-than-eukaryotes
|
<p>Prokaryotes perform transcription and translation much faster than eukaryotes. If memory serves, a single 70S prokaryotic ribosome can incorporate around 20 amino acids per second, whereas the 80S eukaryotic counterpart is much slower, at around 2 amino acids per second. Is the reason for this known? The only possibility I can think of is that prokaryotic mRNAs are often polycistronic, whereas eukaryotic mRNAs are not and tend to involve co-translational protein folding. Slower translation may be able to improve folding accuracy. Other than that, I can't think of any reason the 80S ribosome would be physically slower than the 70S ribosome. It's not like DNA replication where accuracy is exceedingly more important in multicellular organisms than in fast-replicating unicellular prokaryotes.</p>
|
<p>Unless the poster can cite more recent papers to support the assertion regarding a difference in rates of prokaryotic and eukaryotic protein synthesis, I would say that this is incorrect.</p>
<p><a href="https://www.sciencedirect.com/science/article/pii/S0022283668800440" rel="nofollow noreferrer">Lacroute and Stent (1968)</a> reported a rate of <em>15 amino acids per sec</em> for β-galactosidase in <em>Escherichia coli</em>, whereas <a href="https://ac.els-cdn.com/0005278765901863/1-s2.0-0005278765901863-main.pdf?_tid=00dde252-0a99-11e8-a854-00000aab0f6c&acdnat=1517851470_edf07df617e2b366fa4f6a233b565957" rel="nofollow noreferrer">Knopf and Lamfrom (1965)</a> reported a rate of <em>7 amino acids per sec</em> for globin chains in rabbit reticulocytes. This does not appear much different to me, especially as a recent study by <a href="http://www.cell.com/abstract/S0092-8674(14)00232-3" rel="nofollow noreferrer">Li et al. (2014)</a> showed that the rate of protein synthesis varies with the complexity of the assembly (if any) into which a protein is incorporated.</p>
| 133
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