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"abstract": "Bio-inspired surfaces with superamphiphobic properties are well known as effective candidates for antifouling technology. However, the limitation of large-area mastering, patterning and pattern collapsing upon physical contact are the bottleneck for practical utilization in marine and medical applications. In this study, a roll-to-plate nanoimprint lithography (R2P NIL) process using Morphotonics’ automated Portis NIL600 tool was used to replicate high aspect ratio (5.0) micro-structures via reusable intermediate flexible stamps that were fabricated from silicon master molds. Two types of Morphotonics’ in-house UV-curable resins were used to replicate a micro-pillar (PIL) and circular rings with eight stripe supporters (C-RESS) micro-structure onto polycarbonate (PC) and polyethylene terephthalate (PET) foil substrates. The pattern quality and surface wettability was compared to a conventional polydimethylsiloxane (PDMS) soft lithography process. It was found that the heights of the R2P NIL replicated PIL and C-RESS patterns deviated less than 6% and 5% from the pattern design, respectively. Moreover, the surface wettability of the imprinted PIL and C-RESS patterns was found to be superhydro- and oleophobic and hydro- and oleophobic, respectively, with good robustness for the C-RESS micro-structure. Therefore, the R2P NIL process is expected to be a promising method to fabricate robust C-RESS micro-structures for large-scale anti-biofouling application.",
"conclusion": "4. Conclusions The robustness of micro- or nano-structures with a high aspect ratio (A.R.) and the scalability of the large-area patterning and mass production of it, are one of the most critical issues to produce cost-effective antifouling surfaces with both superhydrophobic and superoleophobic properties. In this research, a micro-pillar pattern of A.R. 5.0 was successfully replicated by Morphotonics’ R2P NIL process on their automated Portis NIL600 system using in-house UV-curable resins with low SFE onto PC and PET foil substrates, as an alternative fabrication method for the conventional PDMS soft lithography process. The imprinted micro-pillar (PIL) pattern of A.R. 5.0 showed excellent replication quality without defects and good pattern fidelity (<6% pattern height deviation) which resulted in superhydrophobicity and oleophobicity (WCA above 150°). Furthermore, the well-designed robust circular rings with eight stripe supporters (C-RESS) pattern of A.R. 5.0 was replicated with the same process and materials. The replication quality of this challenging C-RESS imprint pattern was not perfect yet showing defects like filled holes and delaminated features due to large delamination forces. Nevertheless, the imprinted C-RESS micro-structure exhibited a good pattern fidelity (<5% pattern height deviation), already resulting in high hydro- and oleophobicity (WCA above 145°). In addition, the imprinted C-RESS pattern has a good durability during scratch tests, thereby maintaining its pattern shape and largely also its hydro- and oleophobicity. The R2P NIL results have been compared to PDMS samples fabricated by a (conventional) soft lithography process. These samples have a lower WCA due to lower A.R. and lower replication quality. Therefore, the R2P NIL process available at Morphotonics is expected to be a promising patterning process to fabricate large-scale C-RESS micro-structure patterned substrates with antifouling properties in practical utilization for medical and marine applications.",
"introduction": "1. Introduction Biofouling from colonization of various organisms, pathogens and inorganic macromolecules (mostly proteins) is the unwanted accumulation of biological and inorganic matters on wetted surfaces [ 1 ]. The contamination of surfaces, such as marine infrastructure, medical devices and other engineering components, has been a global issue with significant impact on the environment, health risks and economics [ 1 , 2 ]. Biofouling by numerous pathogens such as viruses, bacteria, fungi and other infectious agents causes a spread of infectious diseases in public space which potentially leads to thousands of annual deaths worldwide [ 1 ]. Being submerged in seawater, surfaces of a ship hull are exposed to thousands of species of fouling organisms such as barnacles, mussels and seaweed. Issues include marine corrosion and increased ship hull drag, which result in reduced speed, increased fuel consumption and emissions of greenhouse gases (CO 2 , NO x , and SO 2 ) [ 3 ]. On top of that, it costs the global economy USD 150 billion yearly due to the environmental and significant economic impacts [ 2 , 3 ]. For antibacterial and antifouling solutions in medical environments, such as a surgery room and ward area, expensive materials such as Teflon and paint with nanoparticles (NPs) are commonly used. However, the processes to fabricate silver (Ag), titanium dioxide (TiO 2 ) and zinc oxide (ZnO) NPs as well as the manufacturing and the spray coating of the paint with non-bonded NPs can be toxic if not taking careful precautionary measures [ 4 , 5 , 6 ]. In 2008, the use of biocide-based paint that contains toxic substances such as Tributhyltin (TBT) and lead (Pb) was banned because of its severe effect on living organisms in the ocean [ 7 ]. Subsequently, non-biocide-release approaches, such as water jet cleaning and ultrasonic wave methods, were proposed. However, these technologies are very harmful for the operator working in underwater environment. Moreover, the ultrasonic waves can interfere the communication of marine mammals [ 8 , 9 ]. Therefore, alternative methods that are inexpensive, robust, easy to apply, scalable, and environmentally friendly are required. Super dewetting or antifouling surfaces have shown excellent resistance to stains, bacteria, proteins, and various marine organisms due to the absence of effective adhesion points on these surfaces. The super dewetting surfaces exhibit good anti-biofouling and self-cleaning properties, which have the potential to address the concerns of the above-mentioned traditional biocide-based antifouling methods. There are three types of antifouling surfaces: superhydrophobic surfaces, underwater superoleophobic surfaces, and slippery liquid-infused porous surfaces (SLIPS). Among these, superhydrophobic surfaces, with a contact angle of water (surface tension, γ lv = 72.1 mN/m) greater than 150° and a sliding angle smaller than 10°, are one of the promising technologies for antifouling purpose [ 8 , 9 , 10 , 11 , 12 ]. Such superhydrophobic surfaces are often inspired by nature. For instance, it is reported that the surfaces of various natural animals and plants, such as lotus leaves, red rose petals, butterfly wings, mosquito eyes, Salvinia leaves, water strider legs, gecko feet, and shark skin, show exceptional wetting behavior with superhydrophobicity [ 13 , 14 , 15 , 16 , 17 , 18 ]. Basically, surface wettability is categorized by the contact angle of the liquid droplet [ 19 , 20 ]. Firstly, if the water contact angle (WCA) is smaller than 90°, a surface is considered hydrophilic. Secondly, if the WCA is greater than 90°, it is considered hydrophobic. Lastly, if the WCA is greater than 150°, it is considered superhydrophobic [ 21 ]. Typically, the contact angle of liquid droplets on a flat surface can be explained by Young’s model as shown in Figure 1 a. However, a surface is never completely smooth and generally exhibits a surface roughness. The effect of surface roughness on the apparent contact angle of liquid droplets can be explained by the Wenzel and Cassie-Baxter models as shown in Figure 1 b,c, respectively [ 22 ]. The Wenzel model is used to describe the wetting behavior of a rough surface by calculating the apparent contact angle of the textured surface ( θ w * ) based on its surface roughness ( r ), surface tension between solid–gas ( γ sv ), solid–liquid ( γ sl ), and liquid–gas ( γ lv ) interfaces, and an intrinsic contact angle of the liquid droplet on a flat surface of the same material ( θ ), as shown in Equation (1) [ 22 , 23 , 24 ]. In the Wenzel state, the liquid wets the surface and completely fills all voids on the rough surface. The contact angle in the Wenzel state is defined by: (1) cos θ W ∗ = r γ s v − γ s l γ l v = r cos θ \nin which the surface roughness factor r is defined by the ratio of the actual surface area of the rough surface ( A h ) to the projected area ( A f ), as shown in Equation (2): (2) r = 1 + A h A f The Cassie-Baxter model describes that the ultimate liquid-repellent nature of the rough surface is caused by microscopic air pockets filled in the space between the rough micro- or nano-structures and the liquid droplet. The air pockets then create a combination of air–liquid–solid interfaces [ 13 , 21 , 25 ]. If ϕ s is the fraction of the solid in contact with the liquid, the Cassie-Baxter equation can be expressed as Equation (3).\n (3) cos θ C ∗ = − 1 + ϕ s ( 1 + cos θ ) To maximize the WCA in Wenzel’s model, Young’s contact angle ( θ ), as determined on a flat surface, has to be minimized and the surface roughness ( r ) has to be maximized [ 26 ]. There are two methods to construct a superhydrophobic surface. The first one is to reduce the surface energy of the material, and the other is to increase the surface roughness. In the past decades, many research groups designed different hierarchical micro-/nano-structures on low surface energy material to produce a biomimetic superhydrophobic surface. The value of r of the patterned surface has to be maximized by reducing the pattern width (a) and pattern spacing (b) down to the nanometer scale, and by increasing the pattern height (h) [ 27 , 28 , 29 ]. This is shown schematically in Figure 2 a–c, respectively, in which the surface roughness r of an example micro-/nano-structure is increased by increasing the packing factor (P = a/b) and the aspect ratio (A.R. = h/a). Note that here the pattern width is equal to the pattern spacing (a 1 = b 1 , a 2 = b 2 , a 3 = b 3 ) but where a 1 < (a 2 = a 3 ) and (h 1 = h 2 ) < h 3 . The highest packing factor can be achieved with the smallest surface structures (i.e., nano-structures). These are typically made in a conventional lithography process. In making such silicon (Si) master molds, the resolution of the lithographic exposure tool and performance of the deep reactive ion etching (DRIE) tool limits a maximum value of the packing factor and a maximum value of the aspect ratio of the hierarchical micro-/nano-structures. As structured substrate material, Polydimethylsiloxane (PDMS) is commonly known for its low surface energy ( γ sv = 12–16 mJ/m 2 ), low Young’s modulus (∼2.0 MPa), good thermal and oxidative stability, non-toxicity, good biocompatibility, and low cost. PDMS also provides a conformal contact and it is released easily from a Si master mold [ 30 , 31 ]. Moreover, PDMS has a great degree of flexibility during the patterning process due to its relatively high toughness and high elongation at break (>150%) [ 32 , 33 ]. Based on all of these benefits combined, PDMS becomes one of the best material choices that is widely used to fabricate surfaces with superhydrophobic properties using a soft lithography process [ 32 , 34 , 35 ]. A flat PDMS surface only shows hydrophobic properties with a WCA of 107–110° [ 36 ]. Therefore, the fabrication of a rough surface with engineered hierarchical micro-/nano-structures having controlled geometries by the soft lithography process is needed to make PDMS become superhydrophobic [ 33 , 34 ]. Regarding our previous work, PDMS surfaces patterned with a conventional square-like pillar pattern arranged in a square array can demonstrate superhydrophobicity (WCA > 150°) when r and A.R. are greater than 2.75 and 3.0, respectively [ 27 ]. To obtain a superoleophobic and superamphiphobic surface, the A.R. of the micro-/nano-structures must even be greater than 5.0. Typically, there are two ways to create a nature-inspired superhydrophobic surface with hierarchical micro-/nano-structured rough surface on a substrate with low surface energy: replication of a biological surface by a casting (i.e., soft lithography) process or an engineered rigid master template in a “top-down approach” photolithographic method. The soft lithography process is widely studied because it is easy and accurate to replicate the micro-/nano-patterns with various A.R. on the relatively soft PDMS substrate. However, the flexibility of PDMS (σ: 5.0 MPa, ε: 116% @RT) limits its feasibility in the processability of high A.R. structures and increasing pattern density, hydrophobicity, and mechanical strength. The challenges of using PDMS also include deformation, merging, and collapsing of structures, which result in decreased hydrophobicity [ 35 ]. Therefore, there are three main approaches to improve the robustness and strength of these superhydrophobic surfaces. Firstly, a well-designed robust micro-/nano-structure is required to prevent the PDMS pattern from collapsing and maintain its superhydrophobicity [ 36 ]. Secondly, utilization of PDMS-based composite materials to improve its mechanical properties [ 37 , 38 ]. Note that the surface energy of the PDMS-based composite materials is often higher, which adversely affects the superhydrophobic properties. Thirdly, development of new materials, besides PDMS, with low surface energy and high mechanical strength. To realize the full potential of antifouling surfaces, engineered hierarchical micro-/nano-structures with superhydrophobic and superoleophobic properties need to be produced over a large area in a cost-efficient manner for practical applications [ 39 ]. This continuous and efficient fabrication of superhydrophobic surfaces on large areas is challenging and few processes have been adopted by industrial concerns. This is due to the fact that most of the reported methods require multiple complex processing steps, and have low throughput, substrate limitations, or high production cost [ 40 , 41 , 42 , 43 , 44 ]. Among many conventional micro- and nano-patterning techniques that have been developed in the past few decades, the roll-to-plate ultraviolet (UV) nanoimprint lithography (R2P NIL) and the roll-to-roll UV nanoimprint lithography (R2R NIL) technologies are some of the promising solutions due to the lower cost, higher throughput, larger patterning area, and higher resolution beyond the limitations set by light diffraction or beam scattering that are encountered in other traditional micro-/nano-fabrication techniques [ 44 ]. One of the technical challenges of the UV NIL process is the scaling of the master. As the patterns have to be transferred from a Si master mold (or other master material) in order to fabricate a flexible stamp that can be reused, the fabrication of large-area Si molds tends to be difficult as the feature sizes go down to lower ranges of the nanometer scale. Therefore, often a scaling up of a small area on a (expensive) master mold containing the micro- or nano-structures needs to be performed. Additionally, the material selection for the UV NIL process is also crucial in overcoming critical issues such as the well-known stamp sticking problem, polymerization shrinkage, and thermal and hygroscopic expansion as well as prolonged lifetime of the flexible stamp [ 44 ]. Moreover, the replication of micro-/nano-structures becomes challenging when the A.R. is greater than 2.0 because of stamp releasing problems due to increased contact area. Since most superhydrophobic surfaces can be easily contaminated by different types of fat- and oil-based liquids that have much lower surface tension, such as decane ( γ lv = 23.8 mN/m) and octane ( γ lv = 21.6 mN/m) [ 45 ], the superhydrophobic applications are limited and challenged in several situations [ 25 ]. Instead of using superhydrophobic surfaces, superoleophobic surfaces (organic liquids repellent) and superamphiphobic surfaces (water and oil repellent) are more likely to be used for water-/oil-proof properties in polluted water or greasy environment [ 25 ]. Therefore, this study extends to an investigation of the superoleophobicity of the micro-structures. In this research, the fabrication of high A.R. micro-structures with superhydrophobicity and oleophobicity using R2P NIL process was investigated and demonstrated. The effect of applying a low surface energy resin to replicate micro-structures having A.R. 5.0 onto both polycarbonate (PC) and polyethylene terephthalate (PET) foil substrates on the pattern qualities and pattern fidelity was studied. The effects of the imprinted hierarchical micro-structures on the hydrophobicity, oleophobicity and robustness were investigated as well. Furthermore, the performance of the R2P NIL process in fabricating the water- and oil-repellent properties and robustness of the hierarchical micro-structures has been compared to conventional PDMS micro-structures fabricated by a soft lithography process.",
"discussion": "3. Results and Discussion 3.1. PDMS Pattern Qualities and Surface Properties In case of the PDMS pattern design, the dimensions of the PIL and C-RESS micro-structures on the Si master molds are (a = 2.0 µm, b = 2.0 µm, h = 2.5 µm) and (a = 1.0 µm, b = 1.5 µm, h = 2.5 µm), respectively. Therefore, the A.R. of these PIL and C-RESS Si micro-structures are 1.25 and 2.50, respectively, which are lower than of the PIL and C-RESS micro-structures on the Si master molds used for the R2P NIL replication processes. Nevertheless, the pattern heights are the same so that a comparison between the replication quality and pattern fidelity of the PDMS soft lithography and R2P NIL fabrication processes can be done to this extent. Note that the feature size was limited to 1.0 µm because here, the Si mold patterning was done using a contact mask aligner (EVG model 620, EV Group Europe & Asia/Pacific GmbH, St. Florian am Inn, Austria). Furthermore, here the Si master molds contain the inverse PIL (i.e., holes) and C-RESS micro-structures because the PDMS soft lithography process consists of only one casting step as opposed to the R2P NIL process used in this study. Figure 7 a,b show the SEM images of the PDMS-PIL and PDMS-C-RESS replicated micro-structures before scratch test, respectively. It can be seen that these PDMS patterns were successfully released from the HMDS primed Si master molds. Both PDMS micro-structures were well replicated from the Si molds without defects like pattern clumping, collapsing or breaking off. It is observed that the PDMS patterns have very smooth surfaces without sidewall scallops from the Si mold features, as well as less steep vertical sidewalls. This could possibly have been caused by insufficient curing or a (thermal) reflow effect of the PDMS patterns. The cross-sectional SEM images in Figure 8 a,b show that the pattern width (a) of the PDMS-PIL (a: 1.9 ± 0.02 µm) and PDMS-C-RESS patterns (a: 0.9 ± 0.10 µm) was well controlled resulting in a −5.0% and −10.0% deviation (i.e., shrinkage) from the pattern design, respectively. Note that the vertical sidewalls are less steep so that the width at the top of the pattern is smaller than at the bottom. The pattern heights (h) were measured at 4.8 ± 0.06 µm for the PDMS-PIL and 2.3 ± 0.07 µm for the PDMS-C-RESS pattern resulting in a 92.0% elongation and an 8.0% shrinkage compared to the pattern design, respectively. These numbers result in an A.R. of 2.53 and 2.56 for the PDMS-PIL and PDMS-C-RESS micro-structures, respectively. The differences of the PDMS pattern heights could be explained by a number of factors. Firstly, the pattern depths on the Si master molds could differ due to the micro-loading and the aspect ratio dependent etching (ARDE) effects, which cause the Si etch rate to be dependent on the density and A.R. of the micro-structures, respectively [ 51 , 52 , 53 ]. Secondly, it could be that the flexible PDMS patterns are stretched during peeling from the Si mold (possibly the case for the PDMS-PIL samples) or have shrunk during curing (possibly the case for the PDMS-C-RESS samples). In order to investigate the surface wettability behavior, the WCA of the PDMS-PIL and PDMS-C-RESS micro-structures before the scratch test were measured as 145 ± 3.2° and 130 ± 2.4°, respectively. Both patterned PDMS samples did not show any superhydrophobic properties with the WCA greater than 150°. This is due to the still relatively low A.R. of ~2.5 of the designed and subsequently replicated micro-structures. In addition, CAH of the PDMS-PIL and PDMS-C-RESS micro-structures are 1.5° and 10.7°, respectively, showing a better stability of the surface wettability for the PIL pattern. Next, the robustness of the PDMS replicated patterns was studied by means of a scratch test. After the scratch test, the PDMS-PIL pattern was mostly found collapsed due to the applied external forces, as shown in Figure 9 a. The pattern collapsing was caused by the poor mechanical strength of the PDMS. Furthermore, pattern mating and clumping were also observed after the scratch tests. These defects are due to the fact that the Van Der Waals force between the adjacent patterns is larger than pulling force or recovery force. Moreover, the electrostatic discharge (ESD) induced during the scratch test can generate an adhesion force between the pillars. In contrast, the PDMS-C-RESS pattern did not collapse after the scratch tests and did not exhibit other defects or damage, as shown in Figure 9 b. This is due to the robust design of the C-RESS micro-structure pattern. After scratch tests, the WCA of the PDMS-PIL sample was decreased to 135.9 ± 9.5° due to the induced defects, while the WCA of the PDMS-C-RESS pattern stayed quite the same at 130.0 ± 4.9°, respectively. It was also found that the standard deviation (S.D.) of the WCA of the PDMS-PIL pattern has increased after scratch tests. Moreover, the CAH of the PDMS-PIL pattern has increased significantly to 21.4°. This is due to the variation of the surface roughness across the PDMS-PIL surface due to the pattern collapsing, mating, and clumping. In contrast, the S.D. and CAH (11.5°) of the PDMS-C-RESS patterns did not really increase because the C-RESS micro-structure is robust enough to maintain the pattern shape and surface roughness after the scratch test. Based on the results, the C-RESS pattern is considered attractive for antifouling applications because of its robustness and already quite high hydrophobicity. However, the pattern width and spacing should be further reduced and the pattern height should be further increased to reach an A.R. of 5.0, which is minimally needed in order to obtain superhydrophobicity as well as superoleophobic properties. 3.2. R2P NIL Pattern Qualities and Surface Properties The R2P NIL imprints have been made using another Si master mold. The laser confocal microscopy image of the pillar (PIL) micro-structure on the Si mold in Figure 10 a shows that the DRIE process at TMEC was well-controlled resulting in a high-quality pattern with no defects or contamination. This confocal microscope gives a general quality indication. Due to the steep angles the confocal microscope cannot determine the structure dimensions (and therefore not replication fidelity) accurately. SEM characterization and step profilometer measurement confirmed that the etch depth of the Si micro-structures was found uniform across a six-inch Si wafer with only 2.0% deviation from the pattern design (data not shown). A precise and uniform flexible stamp (intermediate resin mold) containing the inverse polarity of the PIL pattern (i.e., holes) was well fabricated from the in-house releasing agent treated Si master mold, as shown in Figure 10 b. Using the R2P NIL process, the pillar micro-structure from the Si mold (A.R. of 5.0) was well replicated onto both PC and PET foil substrates with both resin A (PIL-A) and resin B (PIL-B), as shown in Figure 10 c,d. According to the laser confocal microscopy images, no pattern clumping, collapsing or breaking off of the micro-pillars was found on the Si master mold and the imprinted samples PIL-A and PIL-B, as shown in Figure 10 a,c,d, respectively. Moreover, no air bubble defects were present on the samples after imprinting. These results are further corroborated by SEM analysis of the samples, which gives a more detailed view of the replicated pattern quality and allows for an accurate determination of the replication fidelity. This is important for a good evaluation of the antifouling behavior of the imprinted micro-structures. The SEM images of the pillar micro-structures imprinted with resin A (PIL-A) and resin B (PIL-B) before scratch test are shown in Figure 11 a,b, respectively. It can be seen that, with the aid of Morphotonics’ in-house Si mold releasing agent and due to the low SFE of the used resins, the micro-pillars were well replicated from the Si master mold and subsequently from the flexible stamp within the R2P NIL process. Again, no pattern clumping, collapsing or breaking down was found as well as no air bubble defects. Furthermore, in Figure 12 a,b, the cross-sectional SEM images show that the pattern width (a) of the PIL-A (a: 458.3 ± 20 nm) and PIL-B patterns (a: 586.0 ± 37 nm) was different resulting in a −8.3% and +17.2% deviation from the original design, respectively, despite having experienced the same R2P NIL fabrication process. The almost vertical sidewalls and rough surfaces with sidewall scallops from the Si master mold were also observed on the PIL-A and PIL-B patterns, while they were absent on the PDMS samples. This underlines the high patterning resolution of the R2P NIL process. The pattern height (h) was measured at 2.57 ± 0.13 µm and 2.64 ± 0.07 µm, respectively. Calculation of the imprinted pattern height deviation from the original design gives a 2.8 and 5.6% elongation resulting in an A.R. of 5.6 and 4.5 for the PIL-A and PIL-B micro-structures, respectively. These differences are likely attributed to the discrepancy between the original design and the actual Si mold pattern heights and to the different resin properties which result in different polymerization shrinkage values upon UV curing and different flexibilities during delamination, amongst others. Here, due to the large surface area the forces during delamination are such high that the cured micro-pillars could have been stretched out more than they have shrunk. Besides replicating the micro-pillar pattern, also fabrication of the more robust C-RESS micro-structure with the R2P NIL process was investigated. Without Morphotonics’ in-housing Si mold releasing agent treatment (i.e., with the HMDS vapor primed Si wafer) the C-RESS structure was not successfully replicated. The laser confocal microscopy images in Figure 13 show that the patterns are completely delaminated/broken off from the substrate, as can been seen from the comparison with the Si master mold pattern. This is caused by the high forces during delamination of the flexible stamp from the cured patterns, which is due to the large surface area of the C-RESS micro-structure and the relatively high SFE of the HMDS primed Si master mold and, subsequently, of the flexible stamp, despite the use of the low SFE resins. With the aid of Morphotonics’ in-house Si mold releasing agent, however, the replication of the C-RESS pattern was significantly improved though still challenging and several defects were observed. Firstly, as shown in Figure 14 , it is observed on the imprinted C-RESS-A and C-RESS-B samples that many of the small holes are filled instead of well-replicated. This could be explained by the incomplete filling of the holes in the Si master mold during fabrication of the flexible stamp or by the breaking off of the pillars on the flexible stamp during delamination. Secondly, it can be seen that sometimes also other parts of the C-RESS pattern can be broken off, again indicating the high forces that are present during delamination. Nevertheless, these results show that the choice of Si mold releasing agent in conjunction with the used resins and flexible stamp materials and the imprint settings is key in achieving a good replication of the high A.R. C-RESS micro-structure. Here, the intermediate flexible stamp (not shown) used was made from the Si master mold after the in-house releasing agent treatment. Note that the artefact seen in the top left corner is part of the design on the Si master mold (see Figure 13 a) and is, therefore, copied onto the samples. Detailed SEM imaging of the C-RESS-A and the C-RESS-B micro-structures before the scratch test further corroborate the abovementioned results and are shown in Figure 15 a–c, respectively. Although the first two SEM images seem to presume that the replications were perfect and without defects, they are very local recordings of the patterned area. Moreover, a third SEM image shows indeed that many of the filled holes seem to be due to the breaking off of the pillars on the flexible stamp during delamination. Furthermore, no pattern mating, clumping or collapsing of the robust C-RESS micro-structure was found on the imprints as well as no air bubble defects. The cross-sectional SEM images in Figure 16 a,b show that the pattern width (a) of the C-RESS-A (a: 1.52 ± 0.11 µm) and PIL-B patterns (a: 1.53 ± 0.04 µm) was practically the same and only deviating 1.3% and 2.0% from the original design, respectively. Similar to the pillar micro-structure the C-RESS-A and C-RESS-B replicated patterns also exhibit the rough surfaces with sidewall scallops due to the Si master mold fabrication (DRIE process), again showing the high patterning resolution of the R2P NIL process. The pattern height (h) was measured at 2.38 ± 0.04 µm and 2.39 ± 0.06 µm, respectively. This results in a pattern height shrinkage of 4.8% and 4.4% compared to the original design. Since the pattern fidelity values for both the C-RESS-A and C-RESS-B samples are so close to each other, it may be concluded that the two resins exhibit similar shrinkage upon UV curing (for this particular micro-structure). It is likely the challenging design of the C-RESS pattern that limits a flawless replication. The difference between the replicated PIL and the C-RESS pattern heights (but also part of the observed deviations from the pattern design) can be explained by a different pattern depth on the Si master molds due to the earlier mentioned micro-loading and ARDE effects, which cause the Si etch rate to be dependent on the density and A.R. of the micro-structures [ 51 , 52 , 53 ]. Taking this into consideration, it may be that the actual pattern height fidelity of the C-RESS micro-structure replications are possibly even better and that the A.R. could be close to 5.0. In order to examine the surface wetting behavior, each pattern was fabricated multiple times to investigate the reproducibility of the R2P NIL process by measuring sample-to-sample deviations. Therefore, the micro-structure replicated with resin A was labeled with sample identification numbers (sample ID) as PIL-A-1, PIL-A-2, C-RESS-A-1, and C-RESS-A-2 and the micro-structure replicated with resin B as PIL-B-1, PIL-B-2, C-RESS-B-1, and C-RESS-B-2. The WCA of the PIL-A, PIL-B, C-RESS-A, and C-RESS-B samples before the scratch test was measured as shown in Table 1 and the EGCA was measured as shown in Table 2 . In addition, the advancing and receding WCA and EGCA are presented in Table 1 and Table 2 as well as the respective CAH. Furthermore, the WCA, the EGCA and their corresponding droplet shapes on the different micro-structures before scratch test are shown in Figure 17 a,b, respectively. From a first glance, it can be concluded that there is no significant difference of the surface wettability between the patterns replicated with resin A and resin B. This shows that the SFE of the cured imprint resins does not necessarily has to be very low, because the A.R. of the micro-structure patterns themselves (~5.0) already induce a large portion of the surface (super) hydrophobicity. In order to make a strong conclusion about this, the micro-structures should be replicated using higher SFE resins as well. These higher SFE will have the difficulty that, most probably, the imprint will fail due to stamp sticking problems during delamination. Figure 18 a,b show the CAH of the water and the ethylene glycol (EG) droplets on the various replicated micro-structure surfaces. The water CAH of the PIL and the C-RESS micro-structures are in the range of 1.0 ± 0.3° to 1.7 ± 1.3° and 6.9 ± 1.7° to 11.8 ± 2.0°, respectively. The EG CAH of the PIL and the C-RESS micro-structures are in the range of 1.4 ± 1.3° to 3.4 ± 1.4° and 11.8 ± 2.3° to 15.3 ± 8.5°. From this, it can be concluded that the surface wettability of the PIL micro-structure is more stable than that of the C-RESS micro-structure because of the lower value of CAH. This can be explained by the better imprint quality and fidelity of the PIL micro-structure than compared to the C-RESS micro-structure. In addition, the PIL-A and the PIL-B micro-structures show superhydrophobicity and superoleophobicity because the WCA and the EGCA were greater than 150° and the value of the water CAH and EG CAH was lower than 10°. In contrast, the C-RESS-A and the C-RESS-B micro-structures show only hydrophobicity and oleophobicity, although the WCA and EGCA values are not that much lower than of the PIL-A and PIL-B samples. This is likely due to the fact that the C-RESS pattern was replicated less well by the R2P NIL process and with more artefacts (such as the filled holes) compared to the PIL pattern. Nevertheless, if the pattern fidelity of the C-RESS micro-structure can be improved, the surface wettability may become superhydrophobic and superoleophobic. Furthermore, the hydrophobicity (and oleophobicity) of both the PIL and C-RESS patterns replicated by the R2P NIL process is higher than that of the PDMS samples fabricated by the (conventional) soft lithography process. This is mostly due to the higher A.R. of the patterns on the R2P NIL samples (~5.0) compared to those on the PDMS samples (~2.5). In addition, there could also be differences in the surface wettability due to the different properties of the used materials. However, since the SFE of the used resins and of PDMS are quite similar, these differences are expected to be very minor. Nevertheless, it could be that the better replication quality of the R2P NIL samples (as opposed to the smoothed PDMS patterns) results in the very high WCA and EGCA values in combination with the higher A.R. Moreover, the R2P NIL patterns showed lower water CAH and EG CAH compared to the PDMS samples. This means that the R2P NIL process has a higher patterning resolution and higher pattern fidelity with better uniformity across the sample surfaces compared to the conventional soft lithography process. 3.3. Effects of Micro-Structure Pattern and Resin Types on the Surface Energy Table 3 shows the WCA and diiodomethane contact angle (DICA) of the PIL-A, PIL-B, C-RESS-A, and C-RESS-B imprinted patterns. Note that the data were obtained using the mobile surface analyzer (MSA) system (KRÜSS GmbH, Hamburg, Germany), which is a different contact angle measurement tool than what has been used in the previous section. Therefore, these contact angle values are slightly different. The WCA values of all samples were higher than their DICA values, as shown in Figure 19 a. This is an effect of the lower value of the water surface tension ( γ lv = 72.1 mN/m) compared to that of diiodomethane from Sigma-Aldrich, St. Louis, MO, USA ( γ lv = 50.8 mN/m). The values of the WCA and DICA were used to calculate the SFE ( γ sv ) of the imprinted samples using the OWRK model. It was found that the γ sv of the PIL-A and PIL-B patterns before the scratch test was in the range of 1.33 ± 0.4 to 1.70 ± 0.4 mN/m and 4.83 ± 1.9 to 4.94 ± 1.7 mN/m, respectively, and that of the C-RESS-A and C-RESS-B patterns in the range of 0.70 ± 0.2 to 1.38 ± 2.5 mN/m and 1.35 ± 0.6 to 2.15 ± 1.1 mN/m, respectively. Figure 19 b shows that the γ sv of the micro-structures imprinted with resin A is lower than that of the micro-structures imprinted with resin B, even though the SFE of a flat sample of resin A ( γ sv ~15 mN/m) is higher than that of a flat sample of resin B ( γ sv ~10 mN/m). This difference is especially pronounced for the PIL pattern. This effect is not very well understood yet, since it contrasts to the results in the previous section. However, it is possible that there could be variations in replication quality and pattern fidelity between the samples. Moreover, since resin B is still quite experimental, it could be that its properties change over time or are inhomogeneous across multiple samples, thereby causing this discrepancy. More research should be performed in order to fully understand this. 3.4. Robustness of the R2P NIL Imprinted Micro-Structures after Scratch Test After performing scratch tests, SEM analysis was carried out again and the WCA and EGCA were remeasured in order to investigate the robustness of the R2P NIL replicated micro-structures. The PIL-A and PIL-B micro-structures were mostly found collapsed, twisted or even broken off by the applied external forces, as is shown in Figure 20 . Besides pillar collapse and the removal of pillars also pattern mating and clumping were observed. This is due to the fact that the Van Der Waals force between the pillars is larger than the pulling force or recovery force [ 54 ]. Moreover, the ESD induced during the scratch test can generate an adhesion force between the pillars. The collapsing or breaking off of the micro-pillars was caused by their poor (inherent) mechanical strength and the low Young’s modulus of the used resins. Although the latter is higher for the used R2P NIL resins than compared to PDMS in the reference soft lithography fabrication process, it is still insufficient for use as a robust anti-biofouling coating. To this end, the C-RESS micro-structure pattern was designed. After the scratch tests, both the C-RESS-A and C-RESS-B patterns remained intact, as shown in Figure 21 . For both samples, there is no pattern collapsing, twisting or breaking off observed. This result shows that the mechanical strength of the used imprint resins is sufficiently high when used in combination with the robustly designed C-RESS micro-structure pattern in order to withstand the scratch test. After the scratch tests, the WCA and EGCA of the PIL-A, PIL-B, C-RESS-A, and C-RESS-B imprinted micro-structures were found to be reduced to (143.3 ± 2.0° and 137.3 ± 4.0°), (127.4 ± 9.3° and 109.1 ± 12.1°), (135.8 ± 5.6° and 135.5 ± 8.2°), and (138.8 ± 5.0° and 121.9 ± 9.4°), respectively. As shown in Table 4 , it was also found that the S.D. of the WCA and EGCA of the PIL-A and PIL-B micro-structures significantly increased after the scratch tests. This can be explained by the variation of the surface roughness across the sample surface due to the collapsing, clumping and breaking off of the pillars. Surprisingly, the S.D. of the WCA and EGCA of the C-RESS-A and C-RESS-B patterns increased as well after the scratch test, despite the C-RESS micro-structure being robust enough to preserve its original pattern structures. Furthermore, the WCA and EGCA of the PIL-B sample were found to be significantly lower than those of the PIL-A and even the C-RESS-A and C-RESS-B imprints after the scratch tests. Additionally, the CAH values of the PIL-B sample were much higher after the scratch test than before. Therefore, it could be that the PIL-B imprinted pattern also has a higher degree of chemical degradation of the surface besides the mechanical defects, although this is difficult to conclude from this small sample set. The decrease in the WCA and EGCA of the C-RESS-A and C-RESS-B patterns might be related to the chemical degradation of the surface after the scratch tests. For example, the resin surface properties, including surface charge, surface free energy (wettability), and nano-scale surface roughness could have been altered after scratching [ 55 ]. Compared to the PIL micro-structure, the replicated C-RESS patterns have a higher (mechanical) durability resulting in a smaller decrease in the WCA and EGCA after the scratch test, as shown in Figure 22 . There was no significant difference of the WCA and EGCA between the C-RESS-A and C-RESS-B imprints after the scratch test, even though the SFE of resin A ( γ s ~15 mN/m) is higher than that of resin B ( γ s ~10 mN/m). However, the CAH of the water and EG droplets on the C-RESS-B sample was found to be larger than those on the C-RESS-A sample, which could point to additional differences in the surface quality between resin A and B after the scratch test. Nevertheless, if the R2P NIL replication quality of the C-RESS micro-structure can be improved, the initial surface wettability will be better and the small decrease in the WCA and EGCA after scratch test could be acceptable for robust large-area antifouling application. In summary, based on the above-mentioned results, the C-RESS micro-structure fabricated by R2P NIL using resin A is considered attractive for robust large-area antifouling purposes because of three main benefits. Firstly, although the high A.R. C-RESS micro-structure was challenging to imprint, the pattern fidelity was not too bad (<5% shrinkage compared to the pattern design) so that the A.R. remained close to 5.0. These imprints already result in a hydro- and oleophobicity with the WCA and EGCA of up to 144.6 ± 2.9° and 144.5 ± 2.7° before scratch test, respectively. These values could even be higher if the replication quality can be improved by reducing the amount of filled holes. Moreover, Morphotonics can scale up this pattern from the 6 inch Si wafers to square-meter sized areas, which can then be imprinted more than a thousand times using a single flexible stamp, making the R2P NIL process highly cost-effective. Secondly, the unique surface topology of the C-RESS pattern may create an air cushion layer even when the surface did not qualify as a superhydrophobic and superoleophobic surface in the Cassie-Baxter regime (WCA and EGCA > 150°). This air cushion layer changes the solid–liquid interface of the C-RESS micro-structure to a combination of solid-liquid and air-liquid interfaces [ 25 , 56 ]. Therefore, the contact area between the micro-organisms and the C-RESS pattern is reduced. Consequently, the surface adhesion force of the micro-organisms decreases and the interaction strength is also reduced [ 57 ]. It was also reported that the high A.R. C-RESS pattern with hydrophobic and oleophobic properties reduced the adhesion strength of the adhesive layer, called extracellular polymeric substance (EPS), which can reduce the formation of a biofilm and subsequently suppresses the accumulation of micro-organisms on the material surface [ 36 ]. Thirdly, due to its robustness, the imprinted C-RESS pattern can maintain its pattern shape during the scratch tests and, thereby, largely its hydrophobicity and oleophobicity. It can be concluded that the robust C-RESS micro-structure fabricated with a resin having properties like resin A by using the R2P NIL process available at Morphotonics is expected to be one of the promising robust antifouling technologies for large-area medical and marine applications. Nevertheless, the long-term mechanical durability and chemical stability of the C-RESS micro-structure and its hydro- and oleophobicity are still among the most important challenges. It has been investigated that the dewetting properties and the liquid contact angles of the (conventional) micro-structures can change over time in laboratory environments already and can severely degrade in realistic application scenarios under various working conditions (e.g., low or high alkalinity, salinity, ions, photodegradation, and high temperatures) [ 58 , 59 ]. This might be due to the degradation of the micro-structure patterns and the alteration of the chemical composition of the top surface, which increase the material surface energy and decrease the hydro- and oleophobic properties [ 58 ]. However, our previous report showed that the unique surface topology and durability of the PDMS-C-RESS micro-structure can maintain the level of the surface roughness and its hydrophobicity during a field test in seawater environment for 5 months [ 36 ]. In future work, such tests should also be conducted for the R2P NIL fabricated C-RESS patterns in order to investigate the performance and long-term mechanical and chemical stability in the field of the samples made by this method."
} | 11,213 |
38020375 | PMC10646967 | pmc | 7,498 | {
"abstract": "The conversion of light into chemical energy is the game-changer enabling technology for the energetic transition to renewable and clean solar fuels. The photochemistry of interest includes the overall reductive/oxidative splitting of water into hydrogen and oxygen and alternatives based on the reductive conversion of carbon dioxide or nitrogen, as primary sources of energy-rich products. Devices capable of performing such transformations are based on the integration of three sequential core functions: light absorption, photo-induced charge separation, and the photo-activated breaking/making of molecular bonds via specific catalytic routes. The key to success does not rely simply on the individual components' performance, but on their optimized integration in terms of type, number, geometry, spacing, and linkers dictating the photosynthetic architecture. Natural photosynthesis has evolved along this concept, by integrating each functional component in one specialized “body” (from the Greek word “soma”) to enable the conversion of light quanta with high efficiency. Therefore, the natural “quantasome” represents the key paradigm to inspire man-made constructs for artificial photosynthesis. The case study presented in this perspective article deals with the design of artificial photosynthetic systems for water oxidation and oxygen production, engineered as molecular architectures then rendered on electrodic surfaces. Water oxidation to oxygen is indeed the pervasive oxidative reaction used by photosynthetic organisms, as the source of reducing equivalents (electrons and protons) to be delivered for the processing of high-energy products. Considering the vast and abundant supply of water (including seawater) as a renewable source on our planet, this is also a very appealing option for photosynthetic energy devices. We will showcase the progress in the last 15 years (2009–2023) in the strategies for integrating functional building blocks as molecular photosensitizers, multi-redox water oxidation catalysts and semiconductor materials, highlighting how additional components such as redox mediators, hydrophilic/hydrophobic pendants, and protective layers can impact on the overall photosynthetic performance. Emerging directions consider the modular tuning of the multi-component device, in order to target a diversity of photocatalytic oxidations, expanding the scope of the primary electron and proton sources while enhancing the added-value of the oxidation product beyond oxygen: the selective photooxidation of organics combines the green chemistry vision with renewable energy schemes and is expected to explode in coming years.",
"conclusion": "Conclusions and perspectives We have discussed herein a collection of case-studies that shed light on the key interplay of molecular and supramolecular chemistry with materials science to engineer functional photoelectrodic surfaces for oxygenic photosynthesis, which still remains a fundamental hurdle for solar fuel production via PEC technology. A survey of the major achievements reached in the last 15 years put under the spotlight the conceptual and experimental efforts in integrating components and functions to shape the light-phase machinery of the oxygenic engine. This is not trivial, since the single molecular components, such as the photosensitizer (PS), the water oxidation catalyst (WOC), or any redox-manifold relays, are optimized separately, according to their a-solo performance, and mostly under very diverse solution/environment homogeneous conditions that are not operative on the final photoelectrodic surface. This observation calls for a change of paradigm in the photosystem design, aiming at addressing the system complexity while targeting possible emerging properties related to the cooperative domains as a whole. In particular, orchestration of the multi-functional assembly requires the engineering of several interfaces by the introduction of mediators, hydrophilic/hydrophobic residues, and transport/protective layers, which can play a fundamental role in implementing the overall efficiency. Nowadays, the performances achieved with PEC devices based on molecular interfaces are still far from the ones targeted for real applications, both in terms of photocurrent density and stability: this suggests that there is much room for improvement. 12 In this respect, the fundamental knowledge achieved in fabricating supramolecular polymers and materials controlled at the molecular level is expected to have a major impact on the development of novel and more efficient photosynthetic materials that can rival the best features of the biological machinery. Finally, we expect that the possibility of designing and fine-tuning molecular components and their assembly will find space in photoelectrochemical devices targeting selective oxidation catalysis for new and light-powered processing of organic molecules.",
"introduction": "Introduction In the novel “The mysterious island” published between 1874 and 1875, the visionary French writer Jules Verne suggested that water, decomposed into its primitive elements, could be the fuel of the future, and provide an inexhaustible source of heat and light, of an intensity of which coal is not capable. In 1912, the Italian photochemist Giacomo Ciamician envisioned a quieter civilization based on the utilization of solar energy, contrasting the black and nervous civilization based on coal. 1 Water and solar energy are indeed the pillars of artificial photosynthesis, a long sought dream process for splitting water into hydrogen and oxygen by means of solar light, thus providing an inexhaustible resource of green and renewable fuels to satisfy the increasing global energy demand. 2,3 The water splitting reaction ( eqn (1) and Scheme 1 ) can be formally decomposed into two redox semi-reactions of proton reduction to hydrogen ( eqn (1A) ) and of water oxidation to oxygen ( eqn (1B) ), vide infra ; accordingly, the Δ G 0 for eqn (1) at 298 K can be reported to be 1.23 eV, being the normalized value per exchanged electron (4 in the case of eqn (1) ). † † The Δ G 0 at 298 K for eqn (1)–(6) are calculated from the difference between the Δ G 0 formation of the products and of the reactants. The following values taken from a physical chemistry handbook were used (values in kJ mol −1 ): H 2 O (l): −237.13; CO 2 (g): −394.36; CH 4 (g): −50.72; CH 3 OH (l): −166.27; HCOOH (l): −361.35; C 6 H 12 O 6 , β- d -glucose: −910; NH 3 (g): −16.45. By definition, Δ G 0 formation of H 2 , O 2 , and N 2 is 0. It is useful to exploit this normalized value since light absorption events are mostly associated with single electron transfer, and therefore this value can be associated with the energy (or with the wavelength) of the electromagnetic radiation ( i.e. 1.23 eV corresponds to a radiation wavelength of 1008 nm). This formalism also enables a direct comparison of the energetic requirement of photosynthetic processes: in the case of natural photosynthesis ( eqn (2) ), this value is 1.24 eV, very close to the one of water splitting. Scheme 1 Schematic representation of the energetic requirements of selected photosynthetic reactions (see eqn (1)–(6) in the main text). Although water splitting for production of hydrogen is the most investigated process, the operating principle can be extended to CO 2 or N 2 reductive conversion ( Scheme 1 ): 4–6 some representative examples are reported in Scheme 1 and eqn (3)–(6) , where water provides reducing equivalents to produce methane, methanol, formic acid (from CO 2 ) or ammonia (from N 2 ). Also for these reactions, the standard free energy at 298 K normalized per electron exchanged in the corresponding semireactions is reported ( eqn (3)–(6) ). Water splitting 1 2H 2 O (l) ⇌ 2H 2 (g) + O 2 (g); 1.23 eV per e − 1A 4H + + 4 e − ⇌ 2H 2 (g) 1B 2H 2 O (l) ⇌ O 2 (g) + 4H + + 4e − Natural photosynthesis 2 6CO 2 (g) + 6H 2 O (l) ⇌ C 6 H 12 O 6 (s) + 6O 2 (g); 1.24 eV per e − 2A 6CO 2 (g) + 24H + + 24e − ⇌ C 6 H 12 O 6 (s) + 6H 2 O 2B 12H 2 O (l) ⇌ 6O 2 (g) + 24H + + 24e − Carbon dioxide reductive conversion (coupled to water oxidation) 3 2H 2 O (l) + CO 2 (g) ⇌ CH 4 (g) + 2O 2 (g); 1.06 eV per e − 3A CO 2 (g) + 8H + + 8e − ⇌ CH 4 (g) + 2H 2 O (l) 3B 4H 2 O (l) ⇌ 2O 2 (g) + 8H + + 8e − 4 2H 2 O (l) + CO 2 (g) ⇌ CH 3 OH (l) + 3/2O 2 (g); 1.21 eV per e − 4A CO 2 (g) + 6H + + 6e − ⇌ CH 3 OH (l) + H 2 O (l) 4B 3H 2 O (l) ⇌ 3/2O 2 (g) + 6H + + 6e − 5 H 2 O (l) + CO 2 (g) ⇌ HCOOH (l) + 1/2O 2 (g); 1.40 eV per e − 5A CO 2 (g) + 2H + + 2e − ⇌ HCOOH (l) 5B H 2 O (l) ⇌ 1/2O 2 (g) + 2H + + 2e − Nitrogen conversion (coupled to water oxidation) 6 3H 2 O (l) + N 2 (g) ⇌ 2NH 3 (g) + 3/2O 2 (g); 1.17 eV per e − 6A N 2 (g) + 6H + + 6e − ⇌ 2NH 3 (g) 6B 3H 2 O (l) ⇌ 3/2O 2 (g) + 6H + + 6e − When reactions (1)–(6) are triggered by light, the radiative energy turns out to be stored in the product chemical bonds, yielding the so called “solar fuels” to feed fuel-cells and provide energy with an overall carbon zero-impact cycle. The development of efficient devices for the sustainable production of solar fuels represents the key challenge for a radical step forward in the field of renewable energy schemes. In particular, solar-energy conversion and storage has been recently demonstrated through promising technologies implementing artificial photosynthesis. These include: (i) a consolidated photo-electrochemical approach (solar-to-hydrogen efficiency up to STH = 30%), 7 implying the coupling of photovoltaic and electrochemical modules (PV–EC) or the fabrication of integrated photo-electrodes wired within photo-electrochemical cells (PEC); 8–10 (ii) a recently assessed photocatalytic (PC) technology based on wireless and bias-free particulate materials suspended in photoreactors for the continuous extraction of solar fuels. 11 This approach has been awarded with the European Innovation Council – Horizon Prize 2022, ‘Fuel from the Sun: Artificial Photosynthesis’ recognizing the promising potential of a 100 m 2 prototype built with an array of panel photoreactors filled with particles based on aluminum-doped strontium titanate with co-loaded Rh, Cr and Co co-catalysts and enabling green hydrogen production, albeit with a limited STH efficiency of 0.76%. 12 Very recently, a record STH value of 9.2% has been achieved using concentrated solar light conditions and particulate photocatalysts based on indium gallium nitride loaded with rhodium/chromium oxide and cobalt oxide co-catalysts, at an optimal temperature of 70 °C. 13 In all these systems (PV–EC, PEC, PC), three main functionalities are pivotal to trigger the photosynthetic process: (i) visible light harvesting tuning the absorption properties; (ii) a cascade of charge separation events upon photo-induced electron transfer; (iii) orchestrated multi-redox catalytic routes to drive solar energy conversion into the chemical energy of new molecular bonds. Noteworthily, a bio-inspired compartmentalization of the photosynthetic complexity enables the breakdown of the overall process into separate modules that can be optimized separately. 14,15 However, the key to success lies on the engineering of a-solo components that can be then operated within an integrated function, in order to maximize the photosynthetic efficiency. 16 A source of inspiration is the natural photosynthetic system, 17 consisting of an orchestrated functional architecture, where each step, from light absorption to electron/proton transport and multi-redox catalysis, is performed by a highly specialized unit incorporated in a structure-directing protein matrix. The great beauty of the natural process has thus inspired the invention of artificial replica based on novel photoactive molecules and materials, to be combined into an integrated photosynthetic assembly. Herein we focus on the central role of photo-assisted water oxidation, evolving oxygen and liberating reduction equivalents (protons and electrons) to be used for the cascade production of solar fuels, including green H 2 or CO 2 or N 2 reduction products (see eqn (1)–(6) ). In this scheme, water activation and cleavage of what are among the strongest molecular bonds (Bond Dissociation Free Energy of the O–H bond in liquid H 2 O, BDFE OH = 115.8 kcal mol −1 ), 18 provides the renewable and ubiquitous primary vector to drive solar energy conversion and storage, optimized along billions of years of aerobic life evolution. Indeed, oxygenic photosynthesis occurs in nature by the vital function of photosystem II (PSII), a unique membrane protein complex whose multi-site architecture and dynamics regulate the photosynthetic efficiency within the thylakoids of plants, cyanobacteria, and algae. In the same way, the artificial perspective relies on light-activated materials and molecular ensembles enabling photocatalytic water oxidation on tailored photoanodes for regenerative PEC technology, and/or as components of wireless photocatalytic systems (PC) mimicking the biological asset. Since the seminal report in 2009 by Mallouk and co-workers, 19 research on the oxygenic “artificial leaf” has exploded, with the last few years witnessing a crescendo of scientific achievements addressing the complexity of the photosynthetic design. In particular, new directions can be traced in the most recent literature regarding: - The rapid and continuous progress in the field of water oxidation catalysis (WOC): T. J. Meyer remarked in 2008 that “catalysts for water oxidation are so rare that the discovery of a new family is cause for celebration”; 20 since then, the number and type of molecular WOCs have been increasing exponentially 21 and current state-of-the-art WOC based on a tda–ruthenium complex (tda = 2,2′:6′,2′′-terpyridine-6,6′′-dicarboxylate) reaches turnover frequency up to 50 000 s −1 , 22 overarching by two orders of magnitude the tetra-manganate natural oxygen evolving centre (TOF = 100–400 s −1 ), while showing more than 1 million turnovers when probed under dark electrocatalytic conditions. 23 - The evolution of photosensitizer (PS) structures relative to their assembly behaviour and related photophysics. 24 The first requirement for the PS choice is a broad light absorption in the visible region spanning the 380–740 nm range, which corresponds to the solar emission peak and accounts for 43% of the total solar radiation at the Earth surface. While photocatalytic systems performing in homogeneous solutions have been dominated by molecular PS operating through long-lived triplet excited state manifolds, as in the case of Ru( ii ) polypyridine complexes, the PS integration within heterogeneous/colloidal photosynthetic architectures opens novel routes engaging singlet excited states, as in the case of dye-sensitized semiconductors. 25 - The use of redox-mediators (relays) to decouple light-induced electron transfer, charge separation and recombination events. 26,27 Quinoid electron transfer relays have been recently exploited by Fukuzumi et al. enabling the combined water reduction/oxidation under homogeneous conditions mimicking the native electron/proton transport mechanism. 28 - The use of non-covalent synthetic strategies to engineer the assembly of the photosynthetic components. This bio-inspired approach complements the synthetic design of covalent chromophore–catalyst conjugates to engineer photocatalytic dyads and/or the joint grafting of chromophores and catalysts on electrode surfaces. 29 To this end, supramolecular strategies can include electrostatic assemblies favoured by multi-charge interactions, 30,31 as in the case of tetravalent cations (such as Zr IV , vide infra ) binding to carboxylate pendants, 32,33 liposome membranes, 34,35 polymeric coatings, 36 and hierarchical photosynthetic architectures with controlled morphology, optimized for the light-quanta conversion. 37–41 - Management of concomitant proton and electron transport so as to trigger favourable PCET mechanisms that are of fundamental importance to lower the energy requirement of photosynthetic reactivity. 18,42,43 - Optimization of semiconductor (SC) technologies to boost charge transport and avoid energy losses. Innovation in the field is envisaged to control light harvesting, surface areas and porosity, electronic structures and the excited-state properties. 44 Cutting-edge research in artificial photosynthesis builds on these innovative approaches as will be highlighted in the following sections addressing the state-of-the-art water splitting photoanodes from a molecular perspective and including relevant bio-hybrid case-studies based on photosystem II (PSII) as the natural paradigm. Photosynthetic water oxidation at engineered electrode surfaces The design of oxygen evolving photoanodes requires a careful design and assembly of some minimal components: a semiconductor, a photosensitizer and a water oxidation catalyst. Hence, the compliance of energetic requirements is essential, but the precise control of the interactions among the components and between interfaces is crucial to obtain a perfectly orchestrated chain of electron transfer events regulated by the photosynthetic assembly where we can pinpoint diverse roles and features as follows: The semiconductor (SC) An n-type nanostructured metal oxide SC film, such as TiO 2 , SnO 2 , ZnO or WO 3 (ref. 45 ), with good electron mobility is used in order to favour charge separation and transport: for the PEC cell to achieve overall unassisted water-splitting, the conduction band edge must be higher in energy (more negative potential) with respect to the H + /H 2 couple. The band gap of the semiconductor should be wide enough to guarantee minimal overlapping with the absorption range of the photosensitizer. Nanostructuring of the SC, usually in mesoporous nanocrystalline films, is necessary to increase the active surface and therefore the dye uptake, resulting in enhanced light absorption and enhanced light harvesting efficiency (LHE). The photosensitizer (PS) A light-harvesting chromophore is used to absorb light and generate oxidizing holes upon injection of photoexcited electrons into the semiconductor conduction band: the excited state level should be sufficiently higher in energy (0.2–0.3 eV) with respect to the semiconductor conduction band edge for efficient electron injection; the ground-state level must be lower (more positive potential) than the O 2 /H 2 O couple; the reduction potential of the oxidised PS must be sufficiently high to oxidise the catalyst to its final active state ( E [PS + /PS] > E [ WOC 4+ /WOC 3+ ]). In addition, to achieve high solar-to-oxygen efficiencies, a suitable photosensitizer must have a broad and intense ( ε > 10 4 M −1 cm −1 ) absorption in the visible and possibly near infrared range, being inert against oxidation and photobleaching. In order to favour electron injection and limit the dye leaching, its covalent anchoring to the semiconductor surface is typically exploited although with some drawbacks regarding the tuning of a multi-chromophore photosystem assembly. 46 The water oxidation catalyst (WOC) The WOC acts as a hole scavenger upon photo-induced electron transfer to the oxidised PS: the progressive collection of four oxidizing holes drives the water oxidation cycle, and the starting state of the WOC is finally restored by oxidation of water and evolution of oxygen. The WOC should be able to undergo multiple electron transfers within a narrow potential range and form sufficiently stable high-valent intermediates: catalysts that can evolve by regulating proton-coupled electron transfer (PCET) mechanisms are more likely to satisfy both criteria, thanks to the charge neutralization deriving from the loss of one electron and one proton. 47 The 4 electrons/4 protons mechanism of light-driven water oxidation by dye-sensitized/SC photoanodes generally involves the following steps: (i) excitation of the photosensitizer (*PS, eqn (7) ), (ii) *PS electron injection into the SC conduction band and generation of its oxidized state (PS + , eqn (8) ), (iii) WOC sequential hole scavenging steps generating high valent WOC states (WOC + /WOC ( n +1)+ , eqn (9) and (9A) ), (iv) water oxidation by the tetra-oxidized WOC 4+ , closing the catalytic cycle by regenerating the starting WOC state ( eqn (10) ): 7 PS + hν → *PS 8 SC + *PS → SC(e − ) + PS + 9 PS + + WOC → PS + WOC + 9A PS + + WOC n + → PS + WOC ( n +1)+ 10 WOC 4+ + 2H 2 O → WOC + O 2 + 4H + At variance with homogeneous photocatalysis using terminal sacrificial oxidants, PEC applications and SC technology suffer from parallel deactivation routes, deriving from electron–hole recombination pathways within the SC material and/or involving the oxidised dye (PS + in eqn (11) ), or the high valent WOC manifold (WOC n + in eqn (12) ), 11 SC(e − ) + PS + → SC + PS 12 SC(e − ) + WOC n + → SC + WOC ( n −1)+ Meanwhile, unproductive quenching of the PS excited state can also occur, via energy transfer ( eqn (13) ) or oxidative electron transfer ( eqn (14) ) involving the WOC sites: 13 *PS + WOC n + → PS + *WOC n + → relax to the ground state 14 *PS + WOC n + → PS + + WOC ( n −1)+ The main key performance indicators typically used to benchmark photoanodes for water oxidation include: 48 (i) The onset potential of the oxygenic photocurrent, i.e. the minimum potential of the electrode at which a productive photocurrent response is observed ( i.e. photoinduced electron injection is collected by the circuit); since the thermodynamic potential for the OER is 1.23 V vs. the reversible hydrogen electrode (RHE), efficient photoanodes should operate well below this potential value (underpotential regime), and ideally without any applied bias to improve the SC electron injection and counteract recombination pathways. (ii) The photocurrent density plateau and saturation onset, i.e. the maximum photocurrent density value generally reached above an applied potential threshold (plateau or saturation photocurrent and onset). The photocurrent density should be determined after subtraction of any dark-current component registered at a given potential, so as to be correlated with the photo-catalytic reaction occurring at the photoelectrode. (iii) The faradaic efficiency or yield (FE or FY) associated with water oxidation is a measure of the photocatalytic yield and selectivity, being the fraction of the observed photocurrent that is due to oxygen evolution. Non-unitary faradaic efficiencies are indicative of competitive processes occurring in concomitance with water oxidation to oxygen. (iv) The light harvesting efficiency (LHE) represents the fraction of light that is absorbed by the photoanode, depending on the dye surface loading and on the resulting molar extinction coefficient (absorption cross section); it can be expressed as a function of the light wavelength namely LHE( λ ) = 1–10 − A ( λ ) , with A = Γσ ( λ ) being the resulting absorbance related to Γ (the number of moles of sensitizer per cm 2 ) and σ ( λ ) i.e. the absorption cross-section in cm 2 per mole. (v) The incident photon to current efficiency (IPCE) or external quantum efficiency (EQE) is the fraction of incident photons that are converted into photocurrent, defined as the mathematical product of light-harvesting efficiency, electron injection efficiency ( φ ), charge collection efficiency ( ɳ ) of the photoanode: IPCE = (LHE) × φ × ɳ . (vi) The absorbed photon to current efficiency (APCE) or internal quantum efficiency (IQE) is defined as the fraction of absorbed photons that are converted into photocurrent, given by the ratio between IPCE and LHE. (vii) The photocurrent stability under operation conditions (typically controlled potential photoelectrolysis at a given potential) can be given by the fraction of residual photocurrent after a certain amount of time, or by the time at which the initial photocurrent is halved. Besides the photoanode performance metrics, parameters associated with the WOC performance are also considered, including the turnover frequency and number (TOF and TON). These parameters are generally estimated by correlating the oxygenic photocurrent density with the WOC loading, and/or with the resulting electroactive surface catalyst. However, the precise identification of the active WOC concentration is often elusive so that performance benchmarking via TOF and TON metrics might be misleading. 49 In the next paragraphs, we will showcase the progress in the last 15 years (2009–2023) in the development of strategies for integrating the molecular photosensitizers, multi-redox water oxidation catalysts and semiconductor materials building blocks, highlighting how additional components such as redox mediators, hydrophilic/hydrophobic pendants, and protective layers can impact on the overall photosynthetic performance. We have chosen to group the literature reports in separate paragraphs, starting from the photosystem II machinery, and then collecting the artificial examples based on the photosensitizer nature, as its characteristics (absorption range, band levels, lifetime of the excited state, aggregation, proton-coupled electron transfer reactivity) often dictate the overall design of the device. Finally, emerging directions in the field will be presented, exploiting the modular tuning of the multi-component device to target a diversity of photocatalytic oxidations, thus enhancing the added-value of the oxidation product beyond oxygen: the selective photooxidation of organic substrates incorporates the green chemistry vision with circular economy policies and is expected to explode in the near future. The native photosystem II (PSII) machinery and PSII wired bio-hybrid photoanodes More than 3 billion years ago oxygenic photosynthesis triggered our aerobic life, originating at the PSII protein within thylakoid membranes of photosynthetic organisms such as bacteria, algae and higher plants. The crystal structure of PSII from Thermosynechococcus vulcanus was reported at 1.95 A resolution by Suga et al. ; 50 PSII exists in a dimeric form with 700 kDa molecular mass 51,52 , where each subunit contains the functional components enabling light absorption, energy transfer, and electron and proton separation, ultimately leading to oxygen evolution. 53 The process occurs at the reaction centre RC, composed of D1 and D2 subunits, and initiates at a P D1 /P D2 porphyrin dimer, characterized by weak electronic coupling (85–150 cm −1 ; for comparison in the anoxygenic purple bacterial reaction centre the coupling between P L and P M is 500–1000 cm −1 ). This weak coupling enables P D1 and P D2 to maintain properties typical of monomers: in particular, generation of the first excited state *P with 1.83 eV energy is possible through direct excitation of P or via energy transfer from the internal or external PSII antennas (CP47 and CP43 are the inner antennas in D1 and D2, respectively, while LHC1 and LHC2 are the outer antennas). 54 *P is considered the primary electron donor in PSII: as represented in Fig. 1 for P D1 , the excited state transfers one electron in a few ps to a neighbouring pheophytin Ph D1 , with the assistance of a chlorophyll Chl D1 . The P D1 ˙ + /Ph D1 ˙ − secondary radical pair represents thus the first charge separated state. The ground state of P D1 is restored upon electron transfer to P D1 ˙ + from a tyrosine residue; the process is proton-coupled with the assistance of a proximal histidine residue acting as a base, and allowing the generation of a neutral tyrosine radical; this step occurs within 50 to 250 ns, depending on the oxidation state of the oxygen evolving centre. Finally, the Tyr-O˙ acts as a 1e − oxidant towards the Mn 4 oxygen evolving centre, Mn 4 -OEC (30–200 μs, depending on the oxidation state of the OEC); the stepwise hole accumulation at the Mn 4 -OEC is represented by the Joliot–Kok cycle, finally releasing O 2 from the highest oxidized state S 4 (the subscripts 0–4 indicate the oxidation level of oxidation of the Mn 4 -OEC, with the S 1 being the dark stable state), and operating with a turnover frequency of the order of 10 2 s −1 . 55 From the acceptor side, the electron chain continues with a subsequent electron transfer from Ph D1 ˙ − to a quinone Q A (within 400 ps), and from Q A ˙ − to a quinone Q B in 0.2 to 0.8 ms, depending on the redox state of Q B . Fig. 1 Energy scheme and schematic representation of the photoinduced charge separation in photosystem II (red arrows represent the electron transfer steps, the blue numbers represent the order in the sequence of electron transfer events). Reprinted from ref. 54 with permission from Elsevier, copyright 2012. Indeed, Q B can be reduced twice through a proton coupled process and transforms into the two-electron reduced form Q B H 2 , which is released from PSII (and replaced by a Q B present in the membrane) and transfers the reducing equivalents to a membrane heme-cofactor Cyt b 6 f. The concomitant transfer of electrons and protons is assisted by “water channels” that connect the protein bulk surface with the protein interior. 56 Clearly, the possibility of transferring reducing equivalents outside the PSII enzyme opens the possibility of engineering bio-hybrid interfaces with artificial systems, in particular by exploiting protein film photo-electrochemistry. 57,58 Strategies for PSII wiring on photoelectrodes resulting in bio-hybrid PEC devices applied to water splitting have been recently reviewed; 52 current state-of-the art performances of PSII based photoelectrodes reach photocurrent densities of ca. 1 mA cm −2 . 59 Reisner and co-workers reported several studies on PSII photoelectrodes, with PSII extracted from particular cyanobacteria and immobilised onto nanostructured indium tin oxide (ITO). 48,59–62 Since photo-instability is a major issue for isolated PSII that cannot benefit from the continuous “self-healing” machinery of the in vivo system, 48 a recent strategy is to wire the cyanobacterium Synechocystis sp. PCC 6803 live cells on ITO electrodes. 63,64 Bio-hybrid PSII/ITO photoelectrodes are capable of oxidizing water using red-light low-energy photons (680 nm) with a low onset potential of 0.6 V vs. RHE at pH 6.5, reaching the photocurrent saturation below the OER thermodynamic limit, and therefore behaving as ideal photoanodes ( Table 1 ). Performances and experimental conditions of hybrid protein-film photoanodes; pH = 6.5; source of PSII: Cyanobacterium Entry and photoanode Light intensity (mW cm −2 ) \n E (V) vs. RHE \n J (μA cm −2 ) and IPCE F.E.(O 2 ) (%) TOF (s −1 ) Ref. 1, IO-mesoITO|PSII 679 nm; 10 mW cm −2 0.88 20 (direct electron transfer, DET) no IPCE 75 ± 4 —(DET) \n 59 \n 930 ± 30 (mediated electron transfer, MET via DCBQ) (IPCE 17.0 ± 0.5% at 679 nm) 12.9 ± 0.4 (MET via DCBQ) 2, IO-mesoITO|P Os |PSII 685 nm; 10 mW cm −2 0.88 381 ± 31 (DET) (IPCE 6.9 ± 0.9% at 685 nm) 85 ± 9 4.0 ± 0.4 (DET) \n 62 \n 513 ± 29 (MET via DCBQ) (IPCE 9.3 ± 1.2% at 685 nm) 6.7 ± 0.7 (MET via DCBQ) 3, IO-TiO 2 |dpp|P Os –PSII AM 1.5G, 100 mW cm −2 , λ > 420 nm 0.68 a 130–140 (DET) (IPCE 2.7% at 560 nm, I ph = 6 mW cm −2 ) 88 ± 12 — \n 65 and 66 0.78 b 99 ± 4 (DET) 70 (formate) a Coupled to a hydrogenase cathode. b Coupled to a formate dehydrogenase cathode. To address one major limitation due to the low PSII loading on mesoporous ITO (mesoITO) ( ca. 20 pmol cm −2 ), limiting the photocurrent density to the sub-microampere range, 48 ITO substrates with hierarchical porosity and the inverse opal (IO) morphology were used to allow higher PSII loading increasing the effective surface area and favouring a stable anchoring of the enzyme. 59 The optimized IO-mesoITO|PSII photoanodes can reach up to 20 μA cm −2 photocurrent density in the absence of redox mediators, which highlights the challenge to improve the electrical communication between PSII and the electron-collecting ITO (entry 1, Table 1 ). This issue was later addressed through co-adsorption of PSII with an osmium-based redox active polymer (P Os ), allowing the collection of electrons from PSII, regardless of the relative orientation and proximity of the natural enzyme to the ITO surface ( Fig. 2 ). 62 Under irradiation with monochromatic red light, the improved IO-mesoITO|P Os –PSII photoanodes showed an outstanding 50-fold increase of the saturation photocurrent ( ca. 400 μA cm −2 ) and 15-fold increase of IPCE (4.4%), with a 90% faradaic efficiency for oxygen evolution and TOF max of 4 s −1 per PSII center (entry 2, Table 1 ). Fig. 2 (a) PSII wired via a redox polymer to IO-ITO electrodes (SEM image of IO-ITO is also shown), and (b) energy diagram of electron transfer events among PSII, redox polymer and IO-ITO electrode. Reprinted from ref. 62 with permission from the Royal Society of Chemistry, copyright 2016. More recently, a further advancement was the integration of a diketopyrrolopyrrole dye (dpp) as a green light absorbing unit, integrated into inverse opal mesoporous titanium oxide (IO-TiO 2 ) electrodes, functionalized with PSII and with the co-immobilized osmium polymer mediator (P Os ). In the IO-TiO 2 |dpp|P Os –PSII photoanodes, an artificial Z-scheme takes place by simultaneous excitation of PSII and of the dpp dye; this latter is responsible for light induced electron injection into TiO 2 from its excited state dpp* with formation of the oxidized dpp + , which is further restored to the neutral state by the electron chain photo-promoted by PSII, with the assistance of the P Os redox mediator ( Fig. 3 ). The photoelectrochemical process leading to water oxidation is associated with a photocurrent density of ca. 80 μA cm −2 . 66 The association of the photocurrent with the simultaneous excitation of the diverse chromophores was confirmed by the action spectrum response, which turns out to be consistent with the spectral overlap of PSII with dpp, peaking at 560 nm and characterized by an external quantum efficiency of 2.7%. Besides broadening the absorption spectrum of the electrode, a benefit of using the dpp dye is also an anticipation of the photoanodic current onset potential (−0.5 V vs. SHE, ca. 0.5 V more favourable than sole PSII photoelectrodes), which allows the bias-free application of IO-TiO 2 |dpp|P Os –PSII electrodes. Fig. 3 (a) Representation of the photoelectrochemical cell developed by Reisner and co-workers for bias-free water oxidation and carbon dioxide reduction to formate. The photoanode is an IO-TiO 2 |dpp|P Os –PSII photoelectrode, while the cathode is an IO-TiO 2 |FDH. (b) Energy diagram. Reprinted from ref. 65 with permission from the American Chemical Society, copyright 2018. Indeed, the IO-TiO 2 |dpp|P Os –PSII electrodes have been successfully employed in a bias-free photoelectrochemical cell combining [NiFeSe] hydrogenase 66 or W-dependent formate dehydrogenase (FDH) 65 photocathodes ( Fig. 3 and entry 3, Table 1 ). Ruthenium polypyridine photosensitizers for PEC technology applied to water oxidation The established properties of Ru( ii ) polypyridine complexes as photosensitizers 67 lead to an extensive investigation of this class of compounds in light driven water oxidation. The long lived triplet excited state of such species allowed their investigation for homogeneous photocatalysis, in water, in the presence of a sacrificial electron acceptor. 25 Moreover, ultrafast photoinduced electron injection is observed when these Ru-based sensitizers are anchored onto semiconductors, occurring in a timescale of pico-seconds (hundreds of fs to ps). ‡ ‡ Ru( ii ) trisbipyridine chromophores have also been found to be capable of injecting electrons into TiO 2 semiconductors from their reduced form, in an “anti-biomimetic pathway”, where the excited state of the dye is first reductively quenched by electron acceptors in solution ( i.e. ascorbate) (see ref. 69 ). 68,69 This behaviour has been exploited to design a fully integrated photoanode for photoelectrochemical water oxidation in combination with suitable WOCs. In 2009, the first water splitting dye-sensitized PEC (DS-PEC) was assembled by T. E. Mallouk, 70 with a Ru trisbipyridine photosensitizer-IrO x NPs catalyst covalent dyad anchored onto a nanostructured TiO 2 photoanode (entry 1, Table 2 ). This ground-breaking result was the forerunner of further technology development including many diverse and increasingly sophisticated strategies to optimize both the overall stability and efficiency of the resulting DS-PEC. 71 Performance and experimental conditions of ruthenium polypyridine photosensitizer based photoanodes Entry and photoanode Light intensity (mW cm −2 ) \n E (V) vs. RHE and pH \n J (μA cm −2 ) F.E.(O 2 ) (%) Ref. 1, TiO 2 |Ru(bpy)-IrO x 450 nm, 7.77 mW cm −2 0.55, pH 5.75 30–10 (IPCE 0.9% at 450 nm) 20 \n 70 \n 2, TiO 2 |3P–Ru-2-IrO x a White light AM 1.5G, >410 nm 0.75, pH 5.8 100 (2.3% internal quantum yield) >85 \n 72–74 \n TiO 2 |RuP|IrO 2 0.70, pH 6.8 Up to 225 (IPCE up to 6.75% when integrated from 410 to 700 nm) 98 3, TiO 2 |RuP|Co 3 O 4 AM 1.5G, 100 mW cm −2 , λ > 400 nm 0.90, pH 6.8 135 (IPCE not reported) — \n 78 \n 4, TiO 2 |-RuPNa 2 -Ru 4 POM 450 nm (LED), 33 mW cm −2 0.55 (pH = 5.8) 54.8 (IPCE 0.392% at 450 nm) 86 \n 84 \n 0.63 (pH = 7.2) 34.2 (IPCE 0.228% at 450 nm) 80 5, SnO 2 /TiO 2 |(PAA/PS-Ru) 5 /(PAA/RuC) 5 White light 100 mW cm −2 , λ > 400 nm 0.85, pH = 7 18 (IPCE not reported) 22 \n 86 \n 6, TiO 2 |RuP/Ru(bda) b White light, 300 mW cm −2 , λ > 400 nm 0.60, pH = 6.8 1700 (IPCE 14% at 450 nm) 83 \n 88 \n 7, nanoSnO 2 |TiO 2 (3 nm)|-RuP-Ru(bda) c White light, 100 mW cm −2 , λ > 400 nm 1.05, pH = 7 400 (IPCE 3.75% at 430 nm) 22 \n 89 \n 8, SnO 2 (5.5 μm)/TiO 2 (4.3 nm)|RuP-R 2+ /Ru(bda) d 100 mW cm −2 0.64, pH = 5.7 1500 f , 1440 g (IPCE not reported) 88 f , 97 g \n 90 \n SnO 2 (5.5 μm)/TiO 2 (4.3 nm)|RuP 3 2+ -Zr( iv )–Ru(bda) e 1450 (IPCE not reported) 74 9, nanoSnO 2 |TiO 2 (3 nm)|RuP 2 2+ ALD SnO 2 -1 White light, 100 mW cm −2 , λ > 400 nm 0.7, pH = 4.65 800 (IPCE 17.1% at 440 nm) 80–90 \n 91 \n 10, SnO 2 |TiO 2 |-RuP-L O-C10 -Ru(bda) White light, 100 mW cm −2 , λ > 400 nm 0.82, pH = 7 1400 (IPCE 24.8% at 440 nm) 83 \n 92 \n 11, TiO 2 |-(RuP 2+ ) 5 -Ru(bda) White light, 100 mW cm −2 , λ > 400 nm 0.75, pH = 5.8 1700 (IPCE 25% at 450 nm) 90 \n 93 \n 12, nanoITO|-MV 2+ -S-Fe( ii )–Ru( ii ) White light, 100 mW cm −2 , λ > 400 nm 0.77, pH = 4.65 250 (IPCE 2.3% at 440 nm) 67 \n 94 \n a 2-IrO x = benzimidazole-phenol (BIP) and 2-carboxyethylphosphonic acid (CEPA) capped Ir NPs. b Catalyst with silatrane-terminated anchoring group. c RuP and Ru(bda) are vinyl terminated. d Electrode synthesized via co-loading. e Electrode prepared by layer-by-layer deposition. f Photosensitizer functionalized with R = H. g Photosensitizer functionalized with R = Me. One major issue of the [Ru(bpy) 3 ]-IrO x assembly was indeed the slow electron transfer from IrO x to the oxidized form of the Ru photosensitizer (hole scavenging), occurring in a ms timescale. The introduction of a benzimidazole-phenol based redox mediator grafted on the IrO x nanoparticles did not significantly alter the ET rate domain, although an increase of the internal quantum efficiency up to 2.3% was observed ( Fig. 4 : in this case both the ruthenium polypyridyl complex and the IrO x were independently anchored onto TiO 2 via covalent phosphonate binding, entry 2, Table 2 ), and the photoelectrode's resulting charge transport dynamics was indeed affected by the choice of the deposition solvent. 72–74 Fig. 4 Schematic representation of the photosynthetic system proposed by Mallouk and co-workers, constituted by a Ru polypyridine photosensitizer, IrO x WOC and a benzimidazole-phenol (BIP) based redox mediator, embedded onto a TiO 2 surface. Reprinted from ref. 72 with permission from the Proceedings of the National Academy of Sciences (PNAS), copyright 2012. Slow hole scavenging processes seem to be a common feature characterizing also other metal oxide nanoparticles, including very active Co 3 O 4 ; 75,76 in this case the transfer of one electron is accompanied by transfer of one proton (proton coupled electron transfer, PCET), and the nature of the aqueous medium and in particular the presence of bases can impact the overall PCET rate, through general base catalysis ( Fig. 5 ). 77 This pathway is likely occurring also in the photoanode developed by Na and coworkers, combining a Ru( ii ) trisbipyridine photosensitizer and Co 3 O 4 nanoparticles anchored to a TiO 2 semiconductor through a 3-amino-propyltriethoxysilane linker, providing photocurrent densities up to 135 μA cm −2 (entry 3, Table 2 ). 78 Fig. 5 Representation of photoinduced proton coupled electron transfer occurring at the surface of Co 3 O 4 nanoparticles WOC, where the electron is transferred to Ru III (bpy) 3 3+ and the proton to borate; below is reported the dependence on the rate constant on the pH and on the concentration of the borate base, indicative of a general base catalysis. Reprinted from ref. 77 with permission from the Royal Society of Chemistry, copyright 2018. These results lead other groups to further investigate the dynamics of the hole scavenging process, in order to identify WOCs possibly capable of fast electron transfer. In 2010, in collaboration with Franco Scandola and Sebastiano Campagna, we reported the application of a robust inorganic tetraruthenate Ru 4 POM WOC on a Ru( ii ) polypyridine DS-photoanode, providing evidence of fast hole-scavenging ( Fig. 6 ). 79 The Ru 4 POM WOC, {Ru 4 (μ-OH) 2 (μ-O) 4 (H 2 O) 4 (γ-SiW 10 O 36 ) 2 } 10− , 79–84 features a tetraruthenate catalytic core embedded within two oxidatively stable polyoxotungstate ligands; since the four ruthenium atoms at the WOC core are connected through μ-oxo and μ-hydroxo bridges, Ru 4 POM is capable of undergoing consecutive one-electron oxidations through PCET within a narrow potential range, resulting in oxygen evolution at overpotentials between 200 and 300 mV, depending on the pH. 85 Ru 4 POM readily adsorbs on TiO 2 photoanodes sensitized with Ru(bpy) 2 (dpbpy) (dpbpy = [4,4′-(PO 3 H 2 ) 2 bpy]) through electrostatic interaction with the positively charged dye, and exhibits very fast hole scavenging in the sub-ns timescale, as evidenced by laser flash photolysis studies. 79 Fig. 6 Representation of a Ru trisbipyridine sensitized TiO 2 photoanode with a Ru 4 POM catalyst assembled by electrostatic interactions, and schematic view of the photoinduced electron transfer events (1 is the Ru 4 POM catalyst). Reprinted from ref. 79 with permission from the Royal Society of Chemistry, copyright 2010. A later study by Hill and co-workers 84 aimed at the enhancement of the dye–catalyst coupling by functionalization of a Ru-polypyridyl dye with two crown ether moieties capable of binding Na + or Mg 2+ cations, and acting as a tweezer-like recognition group for Ru 4 POM; they reported an almost three-fold increase of photocurrent and APCE between the pristine and the crown ether-functionalized dye (entry 4, Table 2 ). The assembly of catalyst/sensitizer through complementary charge was also exploited by Meyer and Schanze, via a layer-by-layer deposition onto FTO|SnO 2 /TiO 2 core shell structures of a cationic polystyrene-based Ru polypyridine chromophore and a [Ru(tpy)(2-pyridyl- N -methylbenzimidazole)(OH 2 )] 2+ water oxidation catalyst codeposited with a poly(acrylic acid) polyanion; the resulting device provided limited photocurrent densities lower than 20 μA cm −2 (0.4 V vs. NHE applied bias, phosphate buffer pH 7) and a modest faradaic yield for oxygen evolution of 22% (entry 5, Table 2 ). 86 Besides the fast electron transfer to the oxidised dye, another important feature required for the WOC is the high turnover frequency of oxygen evolution. Concerning this point, state-of-the-art catalysts are Ru( ii ) derivatives with the 2,2′-bipyridine-6,6′-dicarboxylate ligand (bda) 87 or [2,2′:6′,2′′-terpyridine]-6,6′′-dicarboxylate (tda) ligands. 22 These coordination complexes operate with turnover frequency up to 50 000 s −1 , 22 operating through high valent Ru( iv ) or Ru( v )-oxo intermediates. In 2013, Sun and co-workers 88 reported one of the currently top-performing molecular photoanodes by co-absorbing on TiO 2 the ruthenium trisbipyridine dye through phosphonate linkers and [Ru II (bda)] catalyst functionalized with a long insulating silatrane-terminated anchoring group ( Fig. 7 ). Photocurrent densities as high as 1.7 mA cm −2 and 80% faradaic efficiency were obtained at pH 6.8 with a low applied bias (0.6 V vs. RHE), though under 3 sun irradiation, resulting in a 14% IPCE at the 450 nm absorption maximum (entry 6, Table 2 ). Fig. 7 Photoanode reported by Sun and co-workers, based on the ruthenium trisbipyridine dye anchored to TiO 2 through phosphonate linkers and a Ru II (bda) WOC functionalized with a long insulating silatrane-terminated anchoring group. Reprinted from ref. 88 with permission from the American Chemical Society, copyright 2013. Meyer and co-workers tried then to improve the performance of this system through an engineered design. 89 The RuP photosensitizer and WOC components were integrated in a covalent dyad: both photosensitizer and catalyst were functionalized with vinyl groups, and the dyad was then electro-assembled directly on the sensitized electrode, through a layer-by-layer method. Secondly, core–shell SnO 2 |TiO 2 photoanodes were engineered by depositing a thin (3 nm) TiO 2 overlayer on 8 μm thick mesoporous SnO 2 film by the atomic layer deposition technique (ALD). A photocurrent density of 400 μA cm −2 was achieved at 1 V vs. RHE in pH 7 phosphate buffer, almost doubled with respect to SnO 2 |TiO 2 (3 nm)|RuP and ten-fold higher with respect to the photocurrent registered for the same electro-assembly on TiO 2 photoanodes, confirming the successful effect of the core–shell design in limiting back-electron transfer. However, a marked instability of the electro-assembly was evidenced by the low faradaic efficiency for oxygen evolution of 22% (entry 7, Table 2 ). An alternative approach to synthetically demanding PS/WOC covalent binding was based on the use of Zr( iv ) linkers, exploiting phosphonate binders both at the PS and WOC ( Fig. 8 ). 90 The PS/WOC layer-by-layer zirconate assembly was compared to the co-loaded approach ( Fig. 8 ) on SnO 2 /TiO 2 core–shell electrodes under 1 sun illumination in pH 5.7, 0.1 M acetate buffer solutions. Under the optimized conditions, the two approaches displayed similar performance, reaching photocurrent densities of 1.44 and 1.45 mA cm −2 for the co-loaded and LBL assembly, respectively, associated with faradaic efficiencies for O 2 evolution of 97 and 74% for the co-loaded and LBL assembly, respectively. An advantage of the Zr( iv ) based assembly appeared to be the stability under operating conditions, for up to 20 minutes (entry 8, Table 2 ). Fig. 8 Top: Covalent approach to anchor the Ru trisbipyridine photosensitizer and Ru(bda) WOC. Reprinted from ref. 89 with permission from the American Chemical Society, copyright 2015. Bottom: Co-loaded and Zr( iv ) assembly approaches. Adapted from ref. 90 with permission from the American Chemical Society, copyright 2016. The layer-by-layer strategy for cation mediated self-assembly of the photosensitizer and catalyst was further tuned in 2017, employing an atomic layer deposition for derivatizing phosphonate linkers in the gas phase, embedding Al( iii ), Ti( iv ), Zr( iv ) or Sn( iv ) ions. 91 The same core–shell SnO 2 |TiO 2 (3 nm) photoanodes were used, and the best performance was achieved by the photoanode with the SnO x -bridged dyad, delivering ca. 800 μA cm −2 at pH 4.6 with an applied bias of 0.7 V vs. RHE (1 sun, λ > 400 nm), with 90% faradaic yield and 17% IPCE at 440 nm (entry 9, Table 2 ). The same approach was also extended to embed a nickel hydrogen evolving catalyst. Nevertheless, Sun, Meyer and co-workers recently achieved record-breaking efficiencies upon improvement of the former co-loaded design. 92,93 In the first case, 92 a simpler synthetic strategy was exploited for the covalent anchoring of the Ru(bda) WOC: in particular, the MO x surface was pre-functionalized by anchoring through a phosphonate bridge a long pyridine-terminated alkyl linker (L O-C10 ) that was exploited to coordinate and anchor the WOC ( Fig. 9 , top). In pH 7 phosphate buffer, the resulting SnO 2 |TiO 2 |-RuP-L O-C10 -Ru(bda) photoanodes achieved a photocurrent of 1.4 mA cm −2 under an applied bias of 0.8 V vs. RHE, with 83% faradaic efficiency and a 24.8% IPCE at 440 nm. Fig. 9 Top: Coordination of a Ru(bda) WOC at MOx surfaces exploiting a long pyridine-terminated alkyl linker; the Ru trisbipyridine photosensitizer is anchored through phosphonate linkers at the bpy. Bottom: Immobilization of a Ru(bda) WOC on TiO 2 through a pyridine based anchoring group. Reprinted from ref. 92 with permission from the American Chemical Society, copyright 2018 and from ref. 93 with permission from the Nature Publishing Group, copyright 2020. The hydrophobic alkyl chain showed a protecting effect towards hydrolysis of the phosphonate bridges of both the Ru photosensitizer and Ru(bda) catalyst (entry 10, Table 2 ). Recently, superior performances and increased stability were found when employing an unprecedented pyridine anchor for the immobilization of Ru(bda) ( Fig. 9 bottom): 93 the pyridyl-derivatized Ru(bda) displayed an increased hydrolytic stability at near neutral pH; upon stepwise loading of RuP and Ru(bda) on TiO 2 , a 5 : 1 chromophore to catalyst ratio was obtained, and the resulting photoanodes achieved a photocurrent of 1.7 mA cm −2 under an applied bias of 0.55 V vs. RHE at pH 5.8, with a faradaic efficiency over 90% for 2 hours and a record-breaking IPCE of 25% at 440 nm (entry 11, Table 2 ).To conclude this section, it is worth mentioning the promising performances obtained by a truly biomimetic molecular photoanode, recently published by Meyer and co-workers: 94 the photoanode is based on a molecular assembly which can autonomously achieve photoinduced charge separation, supported on mesoporous ITO, similarly to the hybrid PSII photoelectrodes. In close parallelism with the main components of PSII, the photoanode ( Fig. 10 ) is structured as follows: the mesoITO collector plays a role as acceptor of the plastoquinone Q A ; a methyl viologen (MV 2+ ) mediator, anchored to ITO through a phosphonate bridge, acts as the pheophytin primary electron acceptor; a [Ru(bpy)(dpbpy) 2 ] sensitizer (S) acts as the primary donor P680, transferring the photoexcited electron to MV 2+ ; an Fe( ii )-terpyridine (Fe) acts as the tyrosine mediator, regenerating the sensitizer and slowly withdrawing electrons from a [Ru II (bda)] WOC (Ru). Noteworthily, the assembly is easily generated on the ITO surface through a layer-by-layer method, exploiting the methodology of Zr( iv )-phosphonate bridges. The introduction of MV 2+ significantly hinders back electron-transfer from ITO to the oxidized sensitizer or WOC: indeed, ITO|MV-S-Ru shows an 8-fold increase in photocurrent with respect to ITO|-S-Ru. A maximum photocurrent of ca. 250 μA cm −2 was obtained by the complete ITO|-MV-S-Fe-Ru photoanode at 0.77 V vs. RHE in pH 4.65 buffer (AM 1.5G light, λ > 400 nm), coupled with a 67% faradaic efficiency and a 2.3% IPCE at 440 nm (entry 12, Table 2 ). 94 Fig. 10 The bioinspired assembly proposed by Meyer and co-workers, exploiting MV and Fe( ii ) redox mediators combined with a Ru trisbipyridine photosensitizer and a Ru(bda) WOC, mimicking the natural architecture in PSII. Reprinted from ref. 94 with permission from the American Chemical Society, copyright 2019. The potential of totally organic photosensitizers Despite the unique photophysical properties which make ruthenium trisbipyridine derivatives the most investigated family of sensitizers, this class of dyes is definitely not suitable for a sustainable DS-PEC technology, due to the high cost and narrow blue-centered absorption range: moreover, the photogenerated Ru( iii )bpy derivatives are susceptible to attack by water and buffer anions, leading to irreversible degradation under photocatalytic conditions. 47 However, SC-based photoanodes where electron injection occurs from the photosensitizer excited state in the ultrafast (fs-to-ps) regime can work with totally organic photosensitizers displaying short-lived singlet excited states. This behaviour shows a marked difference from homogeneous systems, where long lived excited states are typically required to promote diffusion-controlled electron transfer events. Indeed, the potential of dye chemistry for photosynthetic processes has been recently demonstrated in several case-studies. Moreover, the complex supramolecular systems that can originate from the dye self-assembly in solution and on electrodic surfaces open new possibilities in terms of the electrochemical and photochemical properties, since these can be dependent on the molecular aggregation state. 24 These aspects will be highlighted for representative classes of organic photosensitizers that are receiving a great deal of attention for PEC technology. Bioinspired photosensitizers: the class of porphyrinoid chromophores Taking direct inspiration from biological photosystems and building on recent progress in the dye-sensitized solar cells (DSSC) research, 95 porphyrinoid chromophores have been considered for PEC technology applied to artificial photosynthesis. Brudvig and co-workers reported in 2011 the first example of a DS-PEC displaying a fluorinated Zn-porphyrin with a high oxidation potential (ZnPor, 1.35 V vs. NHE for the first reversible one-electron oxidation) in combination with a molecular Cp*Ir precatalyst (Cp* = pentamethylcyclopentadienyl). Both photosensitizer and Ir-based WOC were functionalized with terminal carboxylates in order to be covalently anchored onto TiO 2 ( Fig. 11 , top). 96 In this first case-study, the photocurrent density reached up to 30 μA cm −2 albeit no oxygen measurement was performed (entry 1, Table 3 ). Fig. 11 Pioneer examples of porphyrinoid derivatives coupled to Ir precatalysts. Reprinted from ref. 96 and 97 with permission from the Royal Society of Chemistry copyright 2011 and 2015. Performances and experimental conditions of porphyrinoid photosensitizer based photoanodes Entry and photoanode Light intensity (mW cm −2 ) \n E (V) vs. RHE and pH \n J (μA cm −2 ) F.E. (O 2 ) (%) Ref. (1) TiO 2 |ZnPor-Cp*Ir White light, 200 mW cm −2 , λ > 400 nm 0.91, pH = 7 30 (IPCE not reported) — \n 96 \n (2) TiO 2 |PPor/CpIr White light, 200 mW cm −2 , λ > 400 nm 0.91, pH = 7 20–30 (IPCE not reported) — \n 97 \n (3) TiO 2 –IrO 2 /Por \n λ > 410 nm (power not reported) 0.70, pH = 6.8 ≈50 (IPCE 0.014–0.032% integrating the photon flux from 410 nm to 700 nm) 100 ± 2 \n 98 \n (4) SnO 2 |P/Ir White light, ≈100 mW cm −2 , λ > 420 nm 1.15, pH = 6 50 for the 2 : 1 material 80 ± 10 \n 101 \n 60 for the 8 : 1 material (IPCE 0.9% at 520 nm) (5) SnO 2 /TiO 2 /ZnTPPF 20- CN/IrWOC White light, 100 mW cm −2 , λ > 450 nm 1, pH = 1 100 (IPCE not reported) >95 \n 102 \n (6) TiO 2 |ZnP–Ru Halogen lamp 100 W, 35 mW cm −2 , λ > 380 nm 0.24, pH = 7.3 100 (IPCE 17 ± 1% at 424 nm) 33 \n 104 \n (7) TiO 2 /SP-Ru(bda) White light, 100 mW cm −2 , λ > 420 nm 0.63, pH = 7.3 60 (IPCE 6% at 400 nm) 64 \n 105 \n (8) TiO 2 /BODIPY-Ru(bda) White light, 200 mW cm −2 , λ > 400 nm 0.55, pH = 5.8 80 (IPCE 4% in the 400–700 nm range) 77 \n 106 \n In another pioneering work, van der Est and co-workers exploited highly oxidizing P( v ) porphyrin sensitizers (oxidation potential in the range 1.62–1.65 V vs. NHE), bound to an SnO 2 semiconductor through benzoate-like pendants in the axial coordination of the hexavalent P( v ) center ( Fig. 11 , bottom) so as to avoid aggregation of the porphyrin dyes on the electrode surface. 97 By combining time-resolved tetrahertz spectroscopy and electron paramagnetic resonance measurements, the authors demonstrated the occurrence of electron injection into SnO 2 from the S 1 and S 2 excited states of the P-porphyrins in a 3–30 ps timescale and generated the oxidized radical cation, PPor˙ + , followed by electron transfer to PPor˙ + from an iridium( iii ) phenylpyridine derivative co-deposited as a precatalyst onto the SnO 2 surface. This was supported by the abatement of a photoinduced EPR signal at g = 2 attributed to the oxidized PPor˙ + when the Ir-species was co-anchored onto SnO 2 , while a new rhombic EPR spectrum arises ( g -values g 1 = 2.57, g 2 = 2.09 and g 3 = 1.83), attributable to an Ir( iv ) species. For this system, photocurrent densities of the order of 20–30 μA cm −2 were registered, although oxygen measurement and quantification was not reported (entry 2, Table 3 ). Mallouk and co-workers considered free base porphyrins for sensitizing mesoporous TiO 2 ( Fig. 12 ). 98 Typically, free base porphyrins are ca. 200 mV more oxidizing than the corresponding Zn( ii ) counterparts. 99 This property enables access to a suitable oxidizing porphyrin radical cation from the free base systems even in the absence of electron-withdrawing groups: in particular in this study a potential in the range 1.02–1.29 V vs. Ag/AgCl was measured in a series of seven free-porphyrins chemisorbed to TiO 2 through benzoic acid linkers. 98 These dye sensitized photoelectrodes generated photocurrent densities of ca. 50 μA cm −2 with quantitative faradaic yield for oxygen evolution, when combined with a co-deposited IrO x catalyst (entry 3, Table 3 ). Fig. 12 Free base porphyrins considered by Mallouk and co-workers for sensitization of TiO 2 , in combination with an Ir oxide WOC. Reprinted from ref. 98 with permission from the Proceedings of the National Academy of Sciences (PNAS), copyright 2015. Interestingly, porphyrin and Ru-polypyridine sensitizers supported on photoelectrodes have been compared in terms of electron injection, hole transport and charge recombination behaviour. Electron injection from a porphyrin-type dye is 3–10 times less efficient with respect to the performance of Ru-polypyridine analogs, as determined by the resulting photon-to-current efficiency (APCE). Concerning the hole transport, and considering the cross-surface electron diffusion coefficients, D app , Ru-polypyridine sensitizers outperform porphyrins by two-orders of magnitude ( D app = 10 −9 –10 −10 cm 2 s −1 and 10 −11 cm 2 s −1 respectively for Ru-polypyridine and porphyrin-type dyes). Besides these negative aspects, porphyrin sensitized electrodes generally display a more favourable, slower back electron transfer recombination with respect to the Ru-polypyridine analogs. 98 Progress in this field by Brudvig and co-workers includes a redesign of porphyrin sensitized photoelectrodes by addressing various aspects: (i) a –CF 3 meso-substituted free-base tetraphenyl porphyrin to increase the sensitizer stability against photo-oxidation; (ii) the installation of the oxidatively robust 2-(2′-pyridyl)-2-propanoate (pyalc) ligand on the Cp*Ir WOC, further stabilizing the high-valent Ir states by electron-donating effects; 100 (iii) the engineering of the covalent anchoring of both the porphyrin sensitizer and the Ir WOC, using a conjugated hydroxamic acid-terminated anchor to increase the electronic coupling of the dye with the SnO 2 surface, while a long insulating silatrane anchor was used for the Cp*Ir(pyalc) WOC in order to favour hole accumulation, by decreasing the probability of unproductive back-electron transfer; (iv) the tuning of the dye/WOC ratio to maximize the rate of hole accumulation at the WOC. Improved photocurrents up to 50–60 μA cm −2 and faradaic yield up to 80% were achieved by the 2 : 1 and 8 : 1 SnO 2 |ZnPor|Cp*Ir(pyalk) photoanodes at 1.16 V vs. RHE; however, recombination and long-term photodegradation remain one major issue (entry 4, Table 3 ). 101 In a recent work by Tessore and co-workers, 102 perfluorinated ZnPor dyes bearing a conjugated electron-acceptor linker, terminating with a cyanoacrylic anchor (ZnPor-CN), were combined with the bridged μ-oxo dimer of Ir(pyalc) (Ir-blue catalyst): 103 the two components were co-loaded on SnO 2 |TiO 2 photoanodes, which were engineered both to reduce recombination and to favour the dye absorption. This system achieved a photocurrent density of 100 μA cm −2 and 95% faradaic yield in pH 1 electrolyte at 1.0 V vs. RHE: however, transient absorption spectroscopy evidenced an incomplete recovery of the ground state of the dye, due to limited electronic communication between the dye and the Ir-WOC (entry 5, Table 3 ). In 2016 the groups of Sun and Imahori reported a TiO 2 photoanode sensitized by a photocatalytic covalent dyad, formed by a pegylated zinc porphyrin (ZnP) connected to a Ru(bda) WOC through a π-conjugated linker ( Fig. 13 ). 104 Fig. 13 A Zn-porphyrin/Ru(bda) photosensitizer/WOC dyad covalently bound to TiO 2 . Reprinted from ref. 104 with permission from the Royal Society of Chemistry, copyright 2016. We thank Prof. Hiroshi Imahori for providing the figure in high resolution. Photocurrents higher than 100 μA cm −2 and outstanding IPCE of 17% were achieved at neutral pH with just 0.24 V vs. RHE applied bias at λ > 380 nm (which does not exclude direct excitation of the TiO 2 ). However, a low faradaic efficiency for oxygen evolution of 33% was reported in contrast with the high IPCE record value, thus suggesting that a competitive oxidative degradation of the ancillary PEG moiety was occurring (entry 6, Table 3 ). Interestingly, the same authors have reported a novel push–pull dye resulting from a sub-porphyrin (SubPor) dye, decorated with two triphenylamine electron-donating groups while a carboxyphenyl electron-acceptor terminal serves as an anchoring group to the semiconductor ( Fig. 14 , top). Indeed, the molecular LUMO turns out to be conveniently localized on the carboxyphenyl terminal unit, thus favouring electron injection into the semiconductor, while the HOMO is located on the triphenylamine moiety, far from the semiconductor surface, thus preventing back recombination ( Fig. 14 , top). When co-anchored on TiO 2 with the Ru(bda) WOC, at neutral pH with an applied bias of 0.6 V vs. RHE, the resulting photoanodes showed photocurrents of 60 μA cm −2 , 6% IPCE at 400 nm and 2% at 520 nm, though a 64% faradaic yield for oxygen evolution was obtained due to the concomitant degradation of the dye (entry 7, Table 3 ). 105 Fig. 14 Photosynthetic systems combining a Ru(bda) WOC and a subporphyrin (top) or BODIPY (bottom) photosensitizer, anchored onto a TiO 2 semiconductor. Reprinted from ref. 105 and 106 with permission from the Royal Society of Chemistry, copyright 2016 and 2017. A somehow related boron-dibenzopyrromethene dye (BODIPY) was later applied for the first time to DSPECs by Kubo and co-workers. 106 The π-conjugated skeleton of BODIPYs can be considered as a porphyrinoid fragment, displaying similar photophysical properties, i.e. broad absorption in the visible reaching the near IR regions (400–500 nm and 600–750 nm), with molar extinction coefficients as high as 10 5 M −1 cm −1 , and showing an excellent photostability. The Kubo group specifically aimed at the development of a water oxidizing DSPEC exploiting low-energy radiation, and therefore successfully synthesized a π-extended BODIPY absorbing up to 800 nm, with a strong absorption maximum at ca. 690 nm ( ε = 1.09 × 10 5 M −1 cm −1 ). Upon co-anchoring with Ru(bda) on TiO 2 with a 5 : 1 ratio ( Fig. 14 bottom), the cell achieved anodic photocurrents of 80 μA cm −2 in neutral medium at 0.6 V vs. RHE, coupled with a 77% and 66% faradaic yield for oxygen and hydrogen, respectively, with an IPCE at 400 nm up to 4%, extending up to 700 nm (entry 8, Table 3 ). Perylene bisimide, when aggregation matters Perylene bisimide (PBI) dyes are characterized by strong and broad absorption in the visible region (400–700 nm) due to π–π* transitions, with easily tunable HOMO and LUMO levels, and are conveniently obtained via low-cost synthetic protocols, featuring high thermal and oxidative stability. 107 In addition, PBIs show a vast supramolecular chemistry, arising from directional π-stacking interactions (H- and J-aggregates) that regulate the collective optical and photophysical properties of these multichromophoric supramolecular polymers. Another important feature of PBI dyes is that the energy of the singlet excited state S 1 (optical band gap, estimated from the intersection of normalized absorption and emission spectra) matches the electrochemical band gap (estimated from the difference of the oxidation and reduction potentials). This means that an excited state in aggregates (consider a PBI*|PBI dimer for simplicity) can evolve almost isoergonically into a radical ion pair state PBI + |PBI − , through a symmetry-breaking charge separation event (SBCS). 108–110 The SBCS typically occurs in a ps timescale, being competitive to other relaxation pathways, and more energetically favourable in high polar solvents. These characteristics make PBI-based materials excellent n-type organic semiconductors (OSC) with high electron affinity and mobility. For these reasons PBI-based OSCs have been exploited in the field of organic field-effect transistors and as electron acceptor layers in organic photovoltaics. Noteworthily, a bis-phosphonate PBI sensitizer was employed by Finke in combination with cobalt oxide/phosphate catalyst Co-P i for the fabrication of an oxygen evolving photoanode ( Fig. 15 ). 111 In particular, a thin film of bis(phosphonomethyl)PBI (PMPBI) was spin-coated onto an ITO substrate, and the Co-P i catalyst was then photoelectrochemically grown on the PBI film. Thanks to the strong phosphonate bridges installing the PBI-thin film between the ITO substrate and Co-P i and to the optimal film thickness (50 nm, i.e. lower than the exciton diffusion length), the ITO|PMPBI|Co-P i photoanode exhibited photocurrents as high as 150 μA cm −2 and faradaic efficiency for oxygen evolution of ca. 80% at 1.6 V vs. RHE despite a light harvesting efficiency (LHE) as low as 12% (entry 1, Table 4 ). Attempts to increase the efficiency of PMPBI-based photoanodes 112 aimed at substituting the flat ITO with a high surface area SnO 2 substrate. SnO 2 also has a lower energy conduction band with respect to other n-type semiconductors, thus making the electron injection from the excited state of the dye more energetically favourable. However, despite a nearly quantitative LHE, SnO 2 |PMPBI|Co-P i photoanodes systematically showed lower photocurrent densities in the order of 20 μA cm −2 at 0.86 V vs. RHE in pH 7 phosphate buffer, and a low faradaic yield for oxygen evolution of ca. 30% (entry 2, Table 4 ). These results were ascribed to a so-called “anti-catalyst” effect of the cobalt oxide, due to major recombination issues and likely dependent on adventitious carbon impurities in the SnO 2 material, originating from the organic precursor employed in the synthesis. 113 Fig. 15 Perylene bisimide (PBI) photosensitizers combined with a cobalt oxide WOC onto ITO or mesoporous SnO 2 , developed by Finke and co-workers. Reprinted from ref. 111 and 112 with permission from the American Chemical Society, copyright 2017 and 2022. Performances and experimental conditions of perylene bisimide derivative based photoanodes Entry and photoanode Light intensity (mW cm −2 ) \n E (V) vs. RHE and pH \n J (μA cm −2 ) F.E.(O 2 ) (%) Ref. 1, ITO|PMPDI|CoO x 100 mW cm −2 , λ = 315–700 nm 1.62, pH = 7 150 (IPCE 0.12% at 480 nm) 80 ± 15 \n 111 \n 2, SnO 2 |PMPDI|CoO x 100 mW cm −2 , λ = 400–700 nm 0.86, pH = 7 20 (IPCE not reported) 31 ± 7 \n 112 \n 3, WO 3 |PBI 2+ -IrO 2 AM 1.5G light, λ > 435 nm 0.93, pH = 3 70 (IPCE 0.9% at 450 nm) — \n 114 \n 4, nanoWO 3 |{[PBI] 5 Ru 4 POM} n AM 1.5G, 100 mW cm −2 , λ > 450 nm 0.91, pH = 3 44 (IPCE 0.5% at 490 nm) >97 \n 117 \n 5, IO-ITO|QS AM 1.5G, 850 mW cm −2 , λ > 450 nm 1.52, pH = 7 290 ± 40 >95 \n 39 \n IO-ITO|QS-TEG lock 370 ± 30 (IPCE 1.2% at 500 nm) The first application of PBI-based non-covalent aggregates deposited onto conventional DS-photoanodes was reported by Prato, Caramori and Bignozzi 114 using the dicationic [ N , N ′-bis(2-(trimethyl-ammonium)-ethylene)-3,4,9,10-perylenebisimide] (PBI 2+ ) displaying a favourable electrostatic adhesion on the negatively charged metal oxide surface ( Fig. 16 ). In fact, this approach was effective with mesoporous nanocrystalline films of WO 3 , SnO 2 and TiO 2 , in combination with IrO 2 nanoparticles as the water oxidation catalyst. According to transient absorption spectroscopy experiments electron injection was most effective on WO 3 , due to the higher driving force for injection and to the enhanced electronic coupling with the dye, determined by the low isoelectric point of WO 3 . The combined use of a PBI-based photogenerated oxidant with high oxidation potential (1.9 V vs. NHE) suitable for water oxidation and the co-deposition of IrO 2 NPs resulted in a six-fold enhancement of the photocurrent density in 0.1 M NaClO 4 pH 3 (AM 1.5G light, λ > 435 nm), reaching 70 μA cm −2 at 0.93 V vs. RHE (entry 3, Table 4 ). Fig. 16 A cationic perylene bisimide derivative, PBI 2+ , absorbed on a nanostructured WO 3 semiconductor and coupled to an IrO x nanoparticle WOC, developed by Prato, Caramori and Bignozzi. Reprinted from ref. 114 with permission from the American Chemical Society, copyright 2015. Building on the supramolecular chemistry of the bis-cationic PBI, in 2019, we designed a novel approach towards artificial photosystems resulting in the synthesis and characterization of the first PSII-inspired artificial “quantasome” evolving oxygen under visible light irradiation. The quantasome concept, firstly reported in 1932 and then reprised in 1964, describes the minimal photosynthetic unit responsible for ‘quantum’ solar energy conversion in natural photosystems (PSI and PSII), as an integrated “body” composed of light-harvesting antennas, reaction centers and catalytic cofactors. 115,116 Following natural guidelines, the artificial quantasome is designed as a supramolecular photosynthetic material in which a dicationic perylene bisimide derivative (PBI 2+ ) is shaped to a core–shell architecture embedding a tetraruthenium polyoxometalate (Ru 4 POM) as the oxygen evolving center. These two organic–inorganic molecular building blocks self-assemble in water, through complementary electrostatic interactions, with a definite charge-balanced stoichiometry of 5 : 1 ( Fig. 17 ). Fig. 17 Self-assembly in water of artificial quantasomes (QS) from a dicationic perylene bisimide PBI 2+ and a decaanionic Ru 4 POM WOC. Reprinted from ref. 117 with permission from the Nature Publishing Group, copyright 2019. The supramolecular assembly consists of a POM-encapsulated structure in which the inorganic polyanion templates a corolla-like arrangement of five surrounding PBIs, yielding a [PBI 2+ ] 5 Ru 4 POM unit that evolves oxygen with a multi-photon/electron/proton mechanism 118 thus behaving as a natural quantasome ( Fig. 17 ). Moreover, the core–shell organic–inorganic amphiphiles undergo hierarchical aggregation in water forming 2D lamellae nano-stacks with a striking resemblance to the appressed chloroplast membranes. When wired to a tungsten oxide substrate (nanoWO 3 |{[PBI 2+ ] 5 Ru 4 POM} n ), the photoanodic device reported a quantitative faradaic yield for oxygen production (>97%, λ > 455 nm), with photocurrents up to 44 μA cm −2 at 0.91 V vs. RHE at pH 3 thus anticipating the thermodynamic barrier of 1.23 V vs. RHE, incident photon to current efficiency of IPCE = 0.5% and APCE = 1.30% (at λ = 490 nm) that exceeds by 1 order of magnitude the nanoTiO 2 |[Ru(dpbpy)(L 1 ) 2 ]|Ru 4 POM photoanode using Ru(bpy) as sensitizer (entry 4, Table 4 ). 117 A second-generation improved quantasome structure was reported in 2022, by installing cross-linked hydrophilic tetraethylene glycol chains (TEG) on the PBI terminals via click-chemistry ( Fig. 18 ). 39 This modification is inspired by the natural water channels in PSII 119 while yielding an inter-locked assembly of the quantasome units with improved water access and reinforced proximity of the photocatalytic units, paired by the TEG cross-linkers (QS-TEG lock , Fig. 18 ). PSII pairing in the natural membrane, being reinforced by the overlap of peripheral antennas, is instrumental to its oxygenic efficiency. 120 Along these lines, the second-generation QS-TEG lock performs as a supramolecular photosynthetic material with increased water solvation properties, controlled colloidal growth (particles with diameters of ca. 20 nm, estimated by dynamic light scattering) and up to 340% (at 1.12 V vs. RHE applied bias) enhancement of the oxygenic photocurrent compared to the parent QS, as probed on 3D-Inverse Opal Indium Tin Oxide (IO-ITO) electrodes under analogous conditions. The highest photocurrent densities are J (QS-TEG lock ) = 370 ± 30 μA cm −2 and J (QS) = 290 ± 40 μA cm −2 at 1.52 V vs. RHE, respectively, associated with FE O 2 > 95% ( Fig. 18 and entry 5, Table 4 ). 39 Indeed, the TEG-ylated quantasome displays the specific formation of TEG-templated hydration shells, probed by Raman microscopy, where water molecules undergo a structural “ordering” by effect of a H-bonding chain, as it results from the Raman peak (band area <3350 cm −1 compared to the disordered water region observed above 3350 cm −1 ). 121 This behaviour confirm the importance of water transport and harvesting in the proximity of the OEC, and sets a key parallelism with the water channel function of the natural PSII. Fig. 18 Second-generation quantasomes, exploiting an inter-locked multi-chromophoric antenna system based on PBI photosensitizers bearing hydrophilic tetraethylene glycol chains (TEG). Reprinted from ref. 39 with permission from the American Chemical Society, copyright 2022. Moving electrons and protons with dyes enabling PCET The Z-scheme photosynthetic chain transports electron AND protons. In some cases, the electrons and the proton take different routes, in a multiple site proton coupled electron transfer (MS-PCET). 18,122 This is the case of the oxidation of the tyrosine to tyrosine radical (Tyr-OH → Tyr-O˙) where the electron is transferred to the oxidized P 680 ˙ + , and the proton to a histidine residue. In other cases, electrons and protons convey to a single acceptor, as the quinone Q B that is twice reduced to H 2 Q B (see previous discussion in the “The Native Photosystem II (PSII) machinery and PSII wired bio-hybrid photoanodes” paragraph). In 2020, Sartorel, Galloni et al. reported the unprecedented application of KuQuinone (KuQ) dyes for dye-sensitized OER photoanodes. 123 KuQuinones are biomimetic polyquinoid dyes, characterized by broad and intense absorption in the visible region (400–600 nm, ε up to 1.5 × 10 4 M −1 cm −1 ) owing to the fully conjugated pentacyclic core: furthermore, due to their quinoid nature, their redox behaviour follows a proton-coupled electron transfer mechanism, which is an unprecedented feature among dyes sensitized photoanodes ( Fig. 19 ). Combining the electrochemical properties of the ground state and the E 00 energy of the excited state, this latter turns out to be highly oxidizing with a redox potential for the couple of 2.5 V vs. RHE, where indicates the reduced form of the dye upon addition of one electron and one proton. This species was indeed characterized by transient absorption spectroscopy on mesoporous SnO 2 |KuQ electrodes in ascorbate aqueous solution, with the dye anchored on the semiconductor through a carboxylate bridge. This evidence speaks in favour of a reductive quenching mechanism, where the excited KuQ dye oxidizes ascorbate, and the generated, reduced injects electrons into the SnO 2 semiconductor, thus causing the photocurrent response. When integrated with a Ru 4 POM WOC embedded in a Nafion matrix (see Fig. 19 ), the resulting mesoSnO 2 |KuQ|Ru 4 POM photoanodes showed a remarkable light harvesting efficiency of 90% at 530 nm, and, under irradiation in pH 5.8 buffer, exhibited a low potential onset of 0.64 V vs. RHE and a photocurrent of 20 μA cm −2 at 1.14 V vs. RHE, coupled with a 70 ± 15% faradaic yield for O 2 . Conversely, no O 2 was detected for mesoSnO 2 |KuQ, confirming the fundamental role of the Ru 4 POM catalyst in evolving oxygen. However, the mesoSnO 2 |KuQ|Ru 4 POM photoanodes showed a maximum IPCE of 0.09% at 490 nm, which was ascribed to the negative effect of the Nafion matrix, and a limited stability under operation (entry 1, Table 5 ). Fig. 19 Anchoring of KuQ dye onto a mesoporous SnO 2 surface, coupled with embedding of a Ru 4 POM WOC in a Nafion membrane. Energy levels of the photosynthetic assembly are shown on the right. Reprinted from ref. 123 with permission from the Royal Society of Chemistry, copyright 2020. Performances and experimental conditions of literature relevant examples of recent classes of organic dyes employed in oxygenic photoanodes Entry and photoanode Light intensity (mW cm −2 ) \n E (V) vs. RHE and pH \n J (μA cm −2 ) F.E.(O 2 ) (%) Ref. 1, mesoSnO 2 |KuQ|Ru 4 POM White light, 100 mW cm −2 , λ > 400 nm 1.14, pH = 5.8 20 (IPCE 0.09% at 490 nm) 70 ± 15 \n 123 \n 2, TiO 2 |L0 + Ru1 White light, 100 mW cm −2 , λ > 400 nm 0.62, pH = 7 a 300 (IPCE 25% at 380 nm) 73 \n 124 and 125 0, pH = 7 b 70 (in the overall PEC configuration) 55 (H 2 FY yield) 3, SnO 2 |TiO 2 |[P-A-π–D]–Ru(bda) 2 White light, 100 mW cm −2 , λ > 400 nm 0.85, pH = 7 1400 to 100 (decay in 60 s) (IPCE 17% at 420 nm with a hydroquinone donor) 8 \n 126 \n 4, SnO 2 /TiO 2 |dye(Al 2 O 3 )–Ru(bda)-(PyP) 2 White light, 100 mW cm −2 , λ > 400 nm 0.68, pH = 4.8 500 (IPCE 33% at 400 nm) 82 \n 127 \n 5, SnO 2 /TiO 2 /Org1-/1.1 nm Al 2 O 3 /-RuP 2+ -WOC c White light, 100 mW cm −2 , λ > 400 nm 0.87, pH = 4.65 500–800 c (IPCE 32% at 400 nm) 100 \n 128 \n 6, TiO 2 |D1-CoF Xenon arc lamp 300 W, 100 mW cm −2 , λ > 400 nm 1, pH = 7 100 (IPCE not reported) 77 \n 129 \n 7, TiO 2 /[CoFe-JG] White light, 100 mW cm −2 , λ > 420 nm 1.23, pH = 7 50 (IPCE 0.6% at 430 nm) 83 \n 130 \n 8, SnO 2 /TiO 2 |-[T2-BTD]/Ru(bda) White light, 100 mW cm −2 , λ > 400 nm 0.63, pH = 3.9 38 μA cm −2 (IPCE 20% at 360 nm with a hydroquinone donor) 12 \n 131 \n 9, TiO 2 |QAP-C16|Zr 4+ |RuOEC White light, 100 mW cm −2 , λ > 400 nm 0.71, pH = 7 253 μA cm −2 (IPCE 6% at 520 nm) 27 \n 132 \n 10, TiO 2 /PH/CoO(OH) x White light, λ > 420 nm 1.12, pH = 7 400 μA cm −2 (IPCE 7% at 420 nm) 34 \n 133 \n a Photoanode tested in a standard three electrode photoelectrochemical cell set-up. b Photoanode tested in a two-electrode set-up. c The two data points refer to different lengths of the spacer in the WOC Ru(bda)(py(CH 2 ) x P(O 3 H) 2 ) 2 (bda is 2,2-bipyridine-6,6-dicarboxylate with x = 3 or 10). Triarylamine-based push–pull sensitizers In 2015 Sun and co-workers introduced the use of push–pull sensitizers and demonstrated the versatility of such organic dyes developing a p/n tandem DSPEC capable of unassisted water splitting under irradiation with visible light. 124 The photoanode was composed of a simple triarylamine dye (electron-donor) adsorbed on TiO 2 through an electron-accepting cyanoacrylate anchor and a co-loaded [Ru(pda)] WOC (pda = 2,6-pyridinedicarboxylate ligand) ( Fig. 20 ). When irradiated with visible light in neutral buffer at 0.6 V vs. RHE, the photoanode delivered an initial photocurrent of 300 μA cm −2 (though a decay of 70% was observed over 1 h) with a 70% faradaic efficiency for oxygen evolution. The system was further associated with a NiO based molecular photocathode sensitized by a similar push–pull triarylamine dye and employing a co-loaded Co cobaloxime as a hydrogen evolving catalyst. 125 The fully assembled cell, limited by the photocathode performance, delivered a photocurrent of 70 μA cm −2 with no applied bias, associated with a 55% faradaic efficiency for H 2 production, corresponding to a 0.05% solar-to-hydrogen efficiency (entry 2, Table 5 ). Fig. 20 Example of an entire photoelectrochemical cell for water splitting, where the photoanode is designed from a triphenylamine photosensitizer and a Ru WOC. Reprinted from ref. 124 with permission from the American Chemical Society, copyright 2015. A similar triarylamine dye was exploited in combination with a Ru(bda) catalyst in a photosynthetic system proposed by Meyer et al. assembled onto FTO|SnO 2 /TiO 2 (3 nm) electrodes with a core/shell SnO 2 /TiO 2 ( Fig. 21 ). 126 Gaining inspiration from the DSSC field, the triarylamine dye was covalently bound to a dithiophene unit that integrated the phosphonate anchoring group for the semiconductor. Upon photoexcitation, the triarylamine donor transfers an electron to the dithiophene unit, which further injects the electron into TiO 2 . The core/shell SnO 2 /TiO 2 junction is beneficial for retarding back electron transfer, which was observed to occur in 170 ns on TiO 2 , and in 1.02 μs on the core/shell oxide through transient absorption spectroscopy. This retarded recombination was instrumental for enhancing the photocurrent response of the photoelectrodes, when probed for the oxidation of hydroquinone. However, when investigating the water oxidation process through the combination of the Ru(bda) catalyst (co-anchored in a 1 : 5 ratio with respect to the dye), the photoelectrodes provided fast decreasing photocurrents associated with a very low faradaic yield for oxygen evolution of ca. 8%, due to the competitive oxidation of the dye under photoelectrolysis conditions (entry 3, Table 5 ). Fig. 21 Photosynthetic electrode by co-adsorbing a triarylamine photosensitizer and a Ru(bda) WOC through phosphonate linkers. Reprinted from ref. 126 with permission from the Royal Society of Chemistry, copyright 2016. Despite these discouraging results, the combination of a triarylamine dye and a Ru(bda) catalyst onto core shell SnO 2 /TiO 2 was then successfully exploited for water oxidation by adding an Al 2 O 3 layer as a further element of the electrode ( Fig. 22 ). The role of the Al 2 O 3 layer is twofold: protecting the triarylamine from hydrolysis and allowing sufficient loading of the Ru(bda) catalyst; the thickness of the Al 2 O 3 layer is crucial for the oxygenic performance of the system. Under the optimized conditions (4 μm thickness of 4.5 nm SnO 2 /TiO 2 , 7–10 Å Al 2 O 3 ), the photocurrent density was ca. 100 μA cm −2 over one hour, with 80% faradaic efficiency in oxygen evolution (entry 4, Table 5 ). 127 Fig. 22 4.5 nm SnO 2 /TiO 2 particles sensitized with a triphenylamine photosensitizer, embedding a 7–10 Å Al 2 O 3 protecting layer, exploited to anchor a Ru(bda) WOC. Reprinted from ref. 127 with permission from the American Chemical Society, copyright 2017. Further development of photoanodes employing these molecular components envisaged the use of Ru trisbipyridine derivatives as electron transfer mediators between the oxidized triphenylamine dye and the Ru(bda) catalyst; the optimized assembly is shown in Fig. 23 . 128 In the postulated mechanism, corroborated by transient absorption spectroscopy measurements, photoinduced electron injection into the semiconductor is promoted by excitation of the triphenylamine dye (its absorption dominates with respect to the Ru polypyridine in the high energy portion of the visible spectrum, with a maximum around 400 nm), while there is no evidence of photoinduced electron injection from the Ru polypyridine chromophore (absorption maximum around 450 nm), prevented by a 1.1 nm thick Al 2 O 3 insulating layer (by atomic layer deposition, ALD in Fig. 23 ). The role of the Ru trisbipyridine is instead to transfer an electron to the oxidized triphenylamine dye, with the generated Ru( iii ) trisbipyridine ( E = 1.28 V vs. NHE) able to subsequently oxidize the Ru(bda) WOC, thus acting as an electron transfer mediator. In the optimized setup the photoelectrodes reach photocurrents of ∼500 μA cm −2 and quantitative O 2 evolution at pH 4.65, with IPCE of 32% at 400 nm (entry 5, Table 5 ). The IPCE profile resembles the absorption of the TPA chromophore, supporting the postulated mechanism. Fig. 23 Photoanodes employing a triphenylamine photosensitizer (green ball) bound to the semiconductor, a protective ALD layer used to anchor a Ru(bda) WOC (red ball) and a Ru( ii ) trisbipyridine redox mediator (purple ball). Reprinted from ref. 128 with permission from the Proceedings of the National Academy of Sciences (PNAS), copyright 2018. Still exploiting triphenylamine push–pull dyes, Meyer, Sun et al. recently reported the first example of a molecular catalyst based, noble metal-free, dye-sensitized photoanode. 129 In particular, the catalyst takes advantage of a bioinspired tetracobalt cubane, stabilized by pyridine and carboxylate ligands. These latter bear hydrophobic fluorinated aliphatic chains that help in stabilizing the organic dye on the TiO 2 electrode surface ( Fig. 24 ). Besides the performance of the optimized system, reaching photocurrent densities around 100 μA cm −2 and associated with a faradaic yield of 77% (pH 7 phosphate buffer, entry 6, Table 5 ), it is interesting to mention the mechanistic analysis, performed by transient spectroscopic measurements, which confirmed injection efficiencies for the dyes in the range 86–90%, and subsequent electron transfer from the cubane catalyst to the oxidized dye, as confirmed by a shortening of the lifetime of the oxidized dye from 169 to 60.4 μs in the presence of the cubane. Fig. 24 Representation of the photosynthetic assembly proposed by Meyer and co-workers based on a triphenylamine photosensitizer and a tetracobalt cubane WOC. Reprinted from ref. 129 with permission from the Royal Society of Chemistry, copyright 2022. Novel, recent classes of organic dyes employed in oxygenic photoanodes Ghobadi et al. reported a dye-sensitized TiO 2 /[CoFe-JG] photoanode, where the molecular components constitute a triad composed of a Janus Green B dye (JG, i.e. a phenazine based dye with a quaternized N atom), a pentacyano ferrate group (Prussian blue analog) acting as an electron shuttle between the JG dye and a cobalt catalytic center ( Fig. 25 ). 130 The TiO 2 /[CoFe-JG] photoanode performs photoelectrochemical water oxidation with a stable photocurrent of 50 μA cm −2 along two hours of electrolysis at 1.23 V vs. RHE in aqueous phosphate buffer pH 7, associated with an 83% faradaic yield for oxygen evolution (entry 7, Table 5 ). Surprisingly, the IPCE of the system was found to be around 0.6% at 430 nm, while flattening off at 500 nm, thus not matching with the absorption spectrum of the [CoFe-JG] triad (reaching a maximum at around 650 nm). The authors attributed this mismatch to an improper alignment of the conduction band of TiO 2 and the LUMO of the dye, which limits photoconversion efficiencies; nevertheless, fast injection into TiO 2 was claimed based on the absence of ground state bleaching in femtosecond transient absorption experiments. Fig. 25 Structure of the photoanode reported by Karadas and co-workers, based on the incorporation of a Prussian blue structure for the sensitization of TiO 2 , acting as an electron shuttle between a Co based catalytic centre and a phenazine-based Janus green B dye with a quaternized nitrogen. Reprinted from ref. 130 with permission from Wiley, copyright 2020. A low faradaic yield of 12% was obtained employing the SnO 2 /TiO 2 core shell structure with a 2,2′-(benzo[ c ][1,2,5]-thiadiazole-4,7-diyl)bis(thiophene-3-carboxylic acid) dye combined with a Ru(bda) catalyst derivative (giving 38 μA cm −2 in acetate buffer, pH 3.9, entry 8, Table 5 ). 131 Hua and co-workers have recently reported the use of a quinacridone dye derivative in a bias-free photoelectrochemical cell for water splitting ( Fig. 26 ). 132 Quinacridone (pigment violet 19) is a commercially available dye used in paints; in their work, Hua et al. exploited a derivative of QNC embedding pyridine dicarboxylic acid pendants to anchor the dye to TiO 2 and to NiO semiconductors in the anodic and cathodic compartments, respectively. Long alkyl chain substituents (C4–C16) at the nitrogen atom prevent flopping down of the dye to the hydrophilic TiO 2 surface. In the photoanode, the pyridine dicarboxylic acid pendant was exploited also to anchor the dye to a Ru single site catalyst bearing the same linker, by exploiting Zr( iv ) bridges. Concerning the photoanode, the QNC dye has sufficient oxidizing power ( E in the range 1.59–1.77 V vs. RHE) to feed the water oxidation by the Ru catalyst ( ca. 1.61 V vs. RHE) working at pH 7. Indeed, a photocurrent response was observed at an onset potential of −0.13 V vs. RHE, reaching a plateau photocurrent density of up to 250 μA cm −2 , IPCE up to 6% at 520 nm, but a limited faradaic efficiency for oxygen evolution of ca. 30% (entry 9, Table 5 ). Nevertheless, the photoanode was combined with a photocathode based on the same dye (the photocathode was assembled by co-adsorbing a Co-cobaloxyme hydrogen evolving catalyst through phosphonate linkers) to achieve bias free hydrogen evolution with a photocurrent density of ca. 110 μA cm −2 , a faradaic efficiency of 89% and a solar to hydrogen efficiency of 0.11% when irradiating both the photoanode and the photocathode. Fig. 26 A bias free photoelectrochemical cell for water splitting into hydrogen and oxygen, based on a quinacridone dye both at the photoanode and at the photocathode. In particular, a Ru WOC is assembled at the photoanode exploiting carboxylic pendants through Zr( iv ) bridges. Reprinted from ref. 132 with permission from the Royal Society of Chemistry, copyright 2021. Despite the many reports on photoanodes based on rare metal-free sensitizers, very few “fully rare metal-free” systems have been published to date. The first example was developed by Beranek and co-workers in 2012 and is based on a rather uncommon polyheptazine (PH, or graphitic carbon nitride, g-C 3 N 4 ) sensitizer, coupled to photoelectrodeposited Co-P i ( Fig. 27 ): 134,135 noteworthily, polyheptazine has an optical band gap of 430 nm, but, when directly grown on TiO 2 , the resulting TiO 2 |g-C 3 N 4 composite shows broad light absorption up to 540 nm, suggesting a direct photoinduced electron transfer from the HOMO of g-C 3 N 4 to the TiO 2 conduction band ( Fig. 27 ). Under irradiation with visible light ( λ > 420 nm) in pH 7 phosphate buffer, the TiO 2 |g-C 3 N 4 |Co-P i photoanodes showed a 2-fold increase in photocurrent (50 μA cm −2 at 1 V vs. RHE) with respect to TiO 2 |g-C 3 N 4 : O 2 was only detected for the complete photoanode, though the faradaic efficiency was not reported; a maximum IPCE of 12% was registered at 350 nm, but ca. 1.7% IPCE was still obtained at 450 nm. 135 Fig. 27 (a) Hybrid photoelectrodes based on nanocrystalline TiO 2 sensitized with polyheptazine and loaded with a CoO x WOC, and (b) energy levels evidencing the direct optical charge-transfer excitation of an electron from the polyheptazine HOMO into the conduction band of TiO 2 . Reprinted from ref. 134 with permission from Springer, copyright 2013. The system was subsequently implemented by replacing the electrodeposited CoPi catalyst with ultrasmall (1–2 nm) CoO(OH) x nanoparticles via a two-step impregnation method. 133 The ultrasmall nanoparticles provide the advantage of being highly transparent, thus allowing to reach high levels of loading without impacting on the g-C 3 N 4 light absorption. The optimized TiO 2 |g-C 3 N 4 |CoO(OH) x photoanodes provided up to 400 μA cm −2 in borate buffer at 1.12 V vs. RHE, although with a limited faradaic efficiency of 34% (entry 10, Table 5 ). Beyond the oxygen evolution reaction: selective organic photosynthesis at engineered photoanodes The four-photon/four-electron manifold to accomplish water oxidation to dioxygen represents a huge kinetic bottleneck, for either natural or artificial photosystems. This is evident from the severe efficiency limitations shown by the current state-of-the-art photoanodes applied to water-oxidation as reported in the previous sections ( Tables 1–5 ). In Fig. 28 , we graphically represent the performance of these systems depending on the wavelength. We selected IPCE (circles; only maximum values are reported for the sake of simplicity, although some of the systems display activity in a broad range of the spectrum) and FY (empty squares) as the key performance parameters representing the photon-to-current and current-to-oxygen performance, respectively. From this plot, it is evident that: (i) best performing systems exploit high energy radiation ( λ < 475 nm), as in the case of Ru-polypyridine chromophores; (ii) porphyrinoids and organic dyes overstepping this barrier ( λ between 475 and 550 nm) are still associated with low IPCE values; (iii) the “green region” above 550 nm where the PSII operates is almost unexploited in artificial systems. Fig. 28 Plot of IPCE (circles; only the maximum values are reported) and FE (empty squares) depending on the wavelength for the systems described in Tables 1–5 . Despite the strong photocatalytic challenge, biological photosynthesis has evolved by using water as the primary, vast and abundant source of reducing equivalents (electron and protons) necessary to feed large scale ( i.e. terrestrial and oceanic) photosynthetic machineries. In this process, O 2 is generated as a side-product by the water oxidation semi-reaction, that, while being of paramount importance for a circular processing of our aerobic atmosphere, retains scarce commercial interest per se . 7,120,121 Considering these economic and sustainability factors, man-made photosynthetic devices have been reconfigured to bypass water oxidation while engineering the photoanodic process with diverse aims: (i) to lower the energy-barrier of the oxidative transformation, (ii) to address relevant sustainability goals via advanced oxidation processes (AOP) and/or (iii) to direct the photocatalytic oxidation towards valuable synthetic targets. As a simple and practical example, the low-energy bromide photo-oxidation can be used to efficiently store energy, since the Br − /Br 2 or Br − /Br 3 − couples can be readily interconverted by electrochemical means. 136,137 This principle is valid for halides in general, especially considering the high concentration of Cl − and Br − in the most abundant water source, i.e. seawater. 102,138 In addition, a few examples of PECs performing H 2 evolution in tandem with the oxidative degradation of organic pollutants have been reported. 138 Increasing attention is being dedicated to selective photosynthesis by the photoelectrochemical oxidation of organic reagents to afford value-added chemicals using visible light. Moreover, the electro-oxidation of organic compounds (electrochemical reforming), by tailored electrocatalysts and/or redox mediators, has been proven also in tandem with the cathodic hydrogen evolving reaction (HER) or CO 2 -reduction reaction (CO 2 RR). 139,140 To this end, the oxidation of alcohols is one of the most investigated strategies, 141 that is often accomplished by integrating a photoanodic process with an aminoxyl radical catalyst, 142 added in solution or chemically anchored to the photoelectrode. Primary and benzylic alcohols are generally oxidised between 0.7 and 1.5 V vs. NHE 143,144 to afford the corresponding aldehyde as a two-electron oxidation product, eventually undergoing a sequential oxidation step to the corresponding carboxylic acid. The oxidation of hydroxymethylfurfural (HMF, easily derived from biomass) to 2,5-furandicarboxylic acid (FDCA) provides a valuable synthetic target for the polymer industry. 138,139 The photoelectrochemical oxidation of HMF or of other benzyl alcohol derivatives was reported with BiVO 4 (ref. 145 and 146 ) and with a graphitic carbon-coated TiO 2 nanowire photoanode. 147 In recent years the development of dye sensitized photoanodes has been considered for this application, and the subject has been recently reviewed. 141 The subject was pioneered by T. J. Meyer and co-workers, 148 who reported the dehydrogenation of benzyl alcohol (BnOH) to benzaldehyde, with concomitant cathodic production of H 2 , with a DSPEC based on a core–shell nanoITO|TiO 2 photoanode co-derivatized with the classical [Ru(bpy) 2 (dpbpy)] sensitizer and a Ru( ii )-polypyridyl catalyst, for which the Ru IV \n \n\n<svg xmlns=\"http://www.w3.org/2000/svg\" version=\"1.0\" width=\"13.200000pt\" height=\"16.000000pt\" viewBox=\"0 0 13.200000 16.000000\" preserveAspectRatio=\"xMidYMid meet\"><metadata>\nCreated by potrace 1.16, written by Peter Selinger 2001-2019\n</metadata><g transform=\"translate(1.000000,15.000000) scale(0.017500,-0.017500)\" fill=\"currentColor\" stroke=\"none\"><path d=\"M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z\"/></g></svg>\n\n O active intermediate responsible for BnOH oxidation to benzaldehyde is generated by a two-photon/two-electron oxidation. A 5-fold photocurrent increase, up to 250 μA, was indeed obtained upon addition of 0.1 M BnOH, and a 37% faradaic efficiency for benzaldehyde was registered over 3 h photoelectrolysis at 0.87 V vs. RHE in pH 4.6 aqueous buffer under monochromatic irradiation (3.7% APCE at 445 nm, 60 mW), with a concomitant 87% faradaic efficiency for H 2 evolution at the cathode. 148 Among the examples of noble-metal-free or organic photosensitizers employed in these systems are zinc porphyrins, 149 thienopyrroledione, 150 diketopyrroles, 151 perylenes, 152 and polyquinoids. 153 The same concept was recently employed for the photoelectrochemical oxidation of glycerol, an archetypical biobased compound for which oxidation to glyceraldehyde or dihydroxyacetone is an extremely appealing target reaction. 154,155 Bruggeman et al. reported a mesoporous TiO 2 electrode sensitized with a thienopyrroledione based organic dye ( E = 1.8 V vs. NHE for the D + /D couple) and integrated with TEMPO catalyst for glycerol oxidation ( Fig. 29 ). 156 Interestingly, both the sensitizer and the catalyst are integrated in a 3 mm thick acetonitrile based gel at the surface of the TiO 2 semiconductor, thus creating a biphasic system with the aqueous solution. When irradiated with one sun in a 0.1 M glycerol aqueous solution (saturated NaCl, NaHCO 3 pH 8.3) the photocurrent density approached 200 μA cm −2 , remaining stable for up to 48 hours, with an almost quantitative faradaic efficiency for the production of glyceraldehyde. The acetonitrile gel was pivotal in protecting and stabilizing the photoanode components from delamination under the alkaline conditions required for glycerol oxidation (pH 8.5; under a purely aqueous system the photocurrent density rapidly fell to tens of μA cm −2 ); crucial to the system is the diffusion and transport of the photogenerated TEMPO + and related intermediates within the gel and crossing the solution interface. Fig. 29 Photoelectrochemical cell for glycerol oxidation and simultaneous H 2 evolution proposed by Reek and co-workers. At the photoanode, the yellow and azure colours represent the redox-gel layer and the aqueous solution, respectively, while oxidation of glycerol by oxoammonium TEMPO + occurs at the interface (green area). Reprinted from ref. 156 with permission from Wiley, copyright 2022. Noteworthily, engineered photoanodes have been considered also for the oxidative activation of C–H bonds, the holy grail for selective photosynthesis. 157–159 Activation of a C–H bond is regulated by the C–H bond dissociation free energy, which is associated with the homolytic breaking of the bond via a hydrogen atom transfer (HAT) mechanism. In nature, this mechanism occurs typically by a high valent Fe-oxo species in cytochrome P450; 160–162 artificial systems for photogenerating bio-inspired metal-oxo species capable of C–H activation have been pioneered by Nam and Fukuzumi. 163–165 Alternative strategies to promote photochemical HAT mechanisms include: (i) the use of photocatalysts enabling HAT by a radical-type excited state, with examples being aromatic ketones 166,167 or the inorganic decatungstate (W 10 O 32 4− ) species; 159,168 (ii) the use of a multiple site proton coupled electron transfer mechanism (MS-PCET), 18,43 as the removal of the hydrogen atom is formally equivalent to the removal of an electron and a proton that can be promoted by a photogenerated oxidant (Ox + ) and by a cooperative base function (B). For this case, J. Mayer 18 and R. R. Knowles 43 pioneered the identification of a formal effective Bond Dissociation Free Energy (BDFE eff ) for the Ox + /B system regulated by the redox potential and by the p K a of the Ox + /Ox and BH + /B couples, respectively. Photoelectrochemical C–H activation at photoanode surfaces has been proposed by direct irradiation of metal-oxide semiconductors such as WO 3 (cyclohexane photooxidation cyclohexanol/cyclohexanone, i.e. KA oil), 169 BiVO 4 (benzylic/allylic photo-oxygenation of tetralin and cyclohexene to the corresponding carbonyl products) 146 and Fe 2 O 3 (arene C–H amination). 170 In these cases, irradiation of the semiconductor promotes the photoexcitation of electrons from the valence to the conduction band, accompanied by the formation of holes at the valence band, mainly localized on the oxygen atoms of the semiconductor, which results in the photogeneration of metal-oxyl radicals thus enabling a photo-induced HAT mechanism. More recently, a proof of concept for photoelectrochemical C–H activation was reported with dye-sensitized photoanodes, exploiting a quinacridone dye (QNC) sublimated under vacuum onto TiO 2 or SnO 2 semiconductors ( Fig. 30 ). As demonstrated by cyclic voltammetry and the Pourbaix diagram, the key feature of QNC is its oxidative reactivity through a proton-coupled electron transfer, which implies the generation of a nitrogen-based radical. A BDFE of 80.5 ± 2.3 kcal mol −1 was estimated for the N–H bond in QNC by combining the redox potential of the QNC(N˙)/QNC(N–H) and H + /H 2 couples and the Δ G 0 of formation of H 2 . 171 Fig. 30 Left: Schematic representation of quinacridone sensitized SnO 2 , capable of promoting C–H activation in organic substrates towards a Hydrogen Atom Transfer (HAT) mechanism. On the right, the photoelectrochemical response towards the organic substrate is shown, in terms of the J sub / J 0 parameter depending on the BDFE of the C–H bond. Reprinted from ref. 171 with permission from Wiley, copyright 2023. When embedded onto the surface of semiconductors, excitation of QNC promotes ultrafast electron injection in a ps timescale, likely accompanied by proton transfer from the dye to the metal-oxide surface. The photogenerated QNC(N˙) can react with C–H bonds, as demonstrated in the case of γ-terpinene where the photocurrent density is enhanced by a factor of 2.4 ± 0.7, while photoelectrolysis produces p -cymene through a radical chain mechanism involving dissolved oxygen. Interestingly, the photocurrent density associated with the C–H bond photooxidation (measured as J sub / J 0 photocurrent enhancement in the presence of the organic reagent) depends on the BDFE values of the allylic or benzylic C–H bond examined and of the N–H bond in the QNC photosensitizer. Specifically, a photoelectrochemical response was observed for substrates below the 80.5 kcal mol −1 BDFE threshold of QNC (xanthene, γ-terpinene, dihydroanthracene), while more challenging substrates (BDFE > 80.5 kcal mol −1 threshold) provided a null photocurrent enhancement ( J sub / J 0 ca. 1). This result combined with control experiments (negligible photocurrent enhancement with alkylated QNC derivatives or for electron rich substrates lacking C–H functionalities) enabled the authors to propose a hydrogen atom abstraction from the oxidized form of the dye QNC(N˙) as the primary step activating the C–H bond. This elegant strategy highlights the potential for the design of novel photoanodes with a tailored photo-induced HAT driving force."
} | 26,283 |
35460195 | PMC9284154 | pmc | 7,499 | {
"abstract": "Abstract High‐performance flexible pressure sensors have attracted a great deal of attention, owing to its potential applications such as human activity monitoring, man–machine interaction, and robotics. However, most high‐performance flexible pressure sensors are complex and costly to manufacture. These sensors cannot be repaired after external mechanical damage and lack of tactile feedback applications. Herein, a high‐performance flexible pressure sensor based on MXene/polyurethane (PU)/interdigital electrodes is fabricated by using a low‐cost and universal spray method. The sprayed MXene on the spinosum structure PU and other arbitrary flexible substrates (represented by polyimide and membrane filter) act as the sensitive layer and the interdigital electrodes, respectively. The sensor shows an ultrahigh sensitivity (up to 509.8 kPa –1 ), extremely fast response speed (67.3 ms), recovery speed (44.8 ms), and good stability (10 000 cycles) due to the interaction between the sensitive layer and the interdigital electrodes. In addition, the hydrogen bond of PU endows the device with the self‐healing function. The sensor can also be integrated with a circuit, which can realize tactile feedback function. This MXene‐based high‐performance pressure sensor, along with its designing/fabrication, is expected to be widely used in human activity detection, electronic skin, intelligent robots, and many other aspects.",
"conclusion": "3 Conclusions In summary, this work reports a simple and universal method to prepare the high‐performance pressure sensor with self‐healing function for tactile feedback. The device consists of spinosum MXene/PU and MXene‐based interdigital electrodes, and the interaction of these two parts results in an excellent performance. The sensitivity of the sensor (PI as the interdigital electrodes substrate) is up to 509.8 kPa –1 and the response and recovery times are 67.3 and 44.8 ms, respectively. After 10 000 loading–unloading cycles, the sensor still maintains excellent stability. The sensor also owns the self‐healing function. After the cutting–healing of the sensitive layer, the sensitivity reduction of the sensor is less than 16.2%. The tactile feedback is also achieved by connecting the sensor to a circuit. Overall, we fabricated a high‐performance pressure sensor by using a low‐cost and universal method. The sensor shows good self‐healing function and can be used for tactile feedback and it has potential application in robotics and electronic skin.",
"introduction": "1 Introduction The rapid growth of bioelectronics, [ \n \n 1 \n , \n 2 \n \n ] smart home, [ \n \n 3 \n \n ] intelligent robots, [ \n \n 4 \n \n ] and human–machine interfaces [ \n \n 5 \n , \n 6 \n \n ] has greatly promoted the market demand for flexible pressure sensors. Flexible pressure sensors are mainly based on several types of working mechanisms, such as capacitive, [ \n \n 7 \n , \n 8 \n \n ] piezoresistive, [ \n \n 9 \n , \n 10 \n , \n 11 \n \n ] piezoelectric, [ \n \n 12 \n , \n 13 \n \n ] and triboelectric. [ \n \n 14 \n \n ] Piezoresistive sensors based on piezoresistive effect are used due to their high sensitivity, fast signal response, simple manufacturing process, and stable sensing performance. [ \n \n 15 \n \n ] Accordingly, the preparation of high‐performance piezoresistive sensors that can meet the needs of various situations has become a hot topic in recent years. The recent research on the design of flexible piezoresistive sensors mainly focuses on the microstructural design of the sensitive layers. It has been proved that the microstructural design of the flexible substrate can significantly improve the sensing performance of the sensor. [ \n \n 16 \n \n ] Some microstructures have received special attention because of their simple preparation processes, the most typical of which is the spinosum structure made from sandpaper. [ \n \n 10 \n , \n 17 \n \n ] Although some progress has been made in the research of piezoresistive sensors on microstructure, the ideal flexible piezoresistive sensor only has excellent sensing performance, which is far from enough. In the practical applications, the flexible piezoresistive sensors unavoidably face complex working environments, and the sensitive layer is easily subjected to a variety of external mechanical damage. Moreover, most fabrication processes of flexible sensors limit the choice of flexible substrates. All these problems hinder the wide application of flexible piezoresistive sensors. [ \n \n 18 \n \n ] \n MXene, as a 2D sheet material, can be easily combined with other flexible substrate materials to form sensitive layers, and some MXene based sensitive layers with microstructure can be obtained, which can effectively improve the performance of the sensor. [ \n \n 19 \n \n ] The flexible substrate materials for the flexible piezoresistive sensors mainly include polyimide (PI), [ \n \n 20 \n , \n 21 \n \n ] polydimethylsiloxane, [ \n \n 20 \n , \n 22 \n \n ] and polyethylene terephthalate. [ \n \n 23 \n , \n 24 \n \n ] Self‐healing materials have attracted the attention of researchers due to their ability to provide long working life and excellent mechanical stability to sensors. [ \n \n 25 \n \n ] Polyurethane (PU) can be healed by itself due to its hydrogen bond, which can promote wide application prospects in the research and development of various flexible electronic devices. [ \n \n 26 \n \n ] \n The diverse application scenarios of the flexible piezoresistive sensors raise various requirements for the flexible substrate materials of electrodes. Au, Ag, and indium tin oxide, [ \n \n 27 \n , \n 28 \n , \n 29 \n \n ] as traditional electrode materials, have excellent conductivity. However, the preparation process of these electrodes is still dominated by the traditional methods such as magnetron sputtering, vacuum evaporation, and pulse electrochemical deposition. [ \n \n 30 \n , \n 31 \n \n ] These technologies not only increase costs of the sensor preparation but also limit the choice of the flexible substrate. For example, the vacuum evaporation requires the high temperature heating, which results in the demand on the heat bearing capacity of the substrate. [ \n \n 32 \n \n ] Moreover, the rigidity of metal and metal oxide will results in cracks in the electrode when the substrate is bent, which will seriously affect the robustness of the sensors. Therefore, a simple, low‐cost, and universal method for preparing the flexible electrodes with high flexibility and conductivity must be established. The ultimate goal of manufacturing the flexible piezoresistive sensor is for practical application. Tactile feedback is an essential function for the practical application of sensors. [ \n \n 33 \n \n ] Touch can be felt all over the body, helping people feel pressure. Tactile feedback can make corresponding instructions according to the pressure felt by the human body to ensure its normal activities. Therefore, the tactile feedback is very important for people. The right amount of force is strictly needed for grasping an object, especially tiny and fragile ones. The body feels the pressure and passes it on to our brain, which gives us tactile feedback so that we can smoothly grab an object. [ \n \n 34 \n \n ] We must give the robot tactile perception and feedback functions to make it work like a human being. The tactile feedback of the sensor can be achieved by combining the sensors with a circuit. However, tactile feedback is rarely mentioned in most of the work related to the flexible piezoresistive sensors. Herein, we propose an MXene‐based high‐performance flexible piezoresistive sensor with self‐healing function for tactile feedback by a simple full spray method. PU with a spinosum structure is used as the flexible substrate of the sensitive layer. The MXene/PU sensitive layer with the self‐healing function was obtained by depositing the MXene nanosheets on the spinosum structure surface of PU. Furthermore, the MXene‐based flexible interdigital electrodes were prepared by a low‐cost and universal template spraying method. The choice of the flexible substrate for the interdigital electrodes prepared by this method can be arbitrary. We prepared the MXene‐based piezoresistive sensors with PI and membrane filter as substrates to verify the arbitrariness of the flexible substrate of the interdigital electrodes. Their sensitivity can be up to 509.8 and 408.4 kPa –1 , the corresponding response times are 67.3 and 68.4 ms and the recovery times are 44.8 and 46.5 ms. Moreover, the current of the sensor remains stable after 10 000 pressure cycles. In addition, the sensitivity of the sensor (PI as the flexible substrate for the interdigital electrodes) can still reach up to 456.9 kPa –1 after the sensitive layer experienced “cutting‐healing” for 18 h. In practical application, the sensor can not only detect human activities but also combine with software and hardware design to make the manipulator realize tactile feedback function. Therefore, the fully sprayed MXene‐based high‐performance pressure sensor has great potential in human activity detection, electronic skin, intelligent robots, and so on.",
"discussion": "2 Results and Discussion 2.1 Fabrication and Characterization The fabrication procedure of the fully sprayed MXene‐based high‐performance pressure sensor is shown in Figure \n \n 1 a . The preparation of the sensor includes two important procedures. One is the preparation of the sensitive layer. The flexible substrate with random distribution spinosum structure can be obtained by casting PU on the microstructure surface of an abrasive paper. After drying and stripping, the MXene conductive layer was evenly distributed throughout the spinosum structure surface of the flexible substrate, which formed the spinosum MXene/PU sensitive layer. A series of abrasive papers with different roughness such as nos. 100, 180, 280, 400, 600, and 800 were prepared to further study the influence of the spinosum MXene/PU sensitive layer on the sensor. The other one is the preparation of the MXene‐based interdigital electrodes. An arbitrary flexible film (represented by PI and membrane filter) was selected as the substrate of the interdigital electrodes. The interdigital electrodes mask plate was placed on the substrate, and a certain amount of MXene solution was sprayed on the surface of the substrate. After removing the interdigital electrodes mask plate, the MXene‐based interdigital electrodes with a thickness of ≈5 µm can be obtained. Finally, the spinosum MXene/PU sensitive layer and MXene‐based interdigital electrodes were assembled together, and the MXene‐based high‐performance pressure sensor was obtained. Figure 1 a) Fabrication procedure of the fully sprayed MXene‐based high‐performance pressure sensor. b) Schematic diagram of the self‐healing mechanism of the sensitive layer. The PU shows excellent self‐healing characteristics. Figure 1b shows the cutting‐healing process of the sensitive layer with spinosum structure. After cutting the sensitive layer with a scalpel, the sensitive layer will complete self‐healing under the action of a large number of hydrogen bonds at the PU interface. Stretchability and compressive strength tests on PU before and after self‐healing were performed. Figure S1a in the Supporting Information shows the stress–strain curve of PU in virgin and after self‐healing state. The strain of the original PU can reach 1600%, while that of the self‐healing PU still attains more than 1400%. The pressure–strain curve in Figure S1b in the Supporting Information shows that PU has excellent compressive performance, the compressive performance does not significantly weaken after self‐healing. Therefore, PU has excellent stretchability, compression resistance, and self‐healing ability. These features ensure that the sensor has excellent mechanical properties and robustness. MXene, which owns more adjustable functional groups (—F, —H, —OH), [ \n \n 35 \n \n ] good hydrophilicity, [ \n \n 36 \n , \n 37 \n \n ] high conductivity (6500 S cm –1 ), [ \n \n 38 \n , \n 39 \n \n ] and excellent mechanical properties, [ \n \n 40 \n , \n 41 \n , \n 42 \n \n ] was used as sensitive material. [ \n \n 43 \n \n ] The preparation of MXene nanosheets is shown in Figure S2 in the Supporting Information and the mixed solution of HCl and LiF was used to etch the “Al” layer from the precursor MAX phase (Ti 3 AlC 2 ). After the etching, the multilayer MXene (Ti 3 C 2 T \n x \n ) was achieved and the single‐layer MXene nanosheets were obtained by ultrasonic stripping. [ \n \n 44 \n \n ] The collected final product is a dark green colloidal dispersion, in which MXene nanosheets are evenly dispersed. When the laser is irradiated in the MXene solution, Tyndall effect will be evident (Figure S3a , Supporting Information). [ \n \n 45 \n \n ] Furthermore, the Raman spectrum also indicates the successful synthesis of MXene (Figure S3b , Supporting Information). The Ti—C and C—C vibrations of the oxygen terminated MXene cause characteristic peaks at ≈203 and 724 cm –1 , respectively. In addition, the vibrations of the oxygen atoms (E g and A 1g , respectively) causes characteristic peaks at ≈386 and 571 cm –1 . [ \n \n 46 \n \n ] We characterized MXene nanosheets by transmission electron microscopy (TEM), as shown in Figure \n \n 2 a . The image inserted in the upper right corner is the corresponding selected area electron diffraction (SAED), from which the MXene nanosheets show a hexagonal crystal structure. Figure 2b is the corresponding energy‐dispersive spectroscopy (EDS) mapping images of the MXene nanosheets. The C, Ti, O, and F elements are uniformly distributed throughout the Ti 3 C 2 T \n x \n nanosheets. Figure 2c shows the thickness (2.03 nm) of the specified MXene nanosheets measured with an atomic force microscope (AFM), which proves that the single layer MXene was successfully prepared. The MAX phase and MXene were characterized by X‐ray diffraction (XRD), as shown in Figure 2d . After the synthesis of MXene, the peak of the MAX phase at ≈39° disappears, which indicates that the “Al” layer in the precursor was etched. In addition, the peak value (002) of the MAX phase is around 10°, while the peak value (002) of MXene shifts to the left at ≈6°, indicating that the interlayer spacing increases. [ \n \n 47 \n , \n 48 \n \n ] All these phenomena indicate the successful synthesis of the MXene nanosheets. Figure 2 a) TEM image of the MXene nanosheets, and the inset is the corresponding SAED pattern. b) energy dispersive spectrometer (EDS) mapping images of MXene (Ti 3 C 2 T \n x \n ). c) AFM image of the MXene nanosheet. d) XRD pattern of the MAX phase (Ti 3 AlC 2 ) and MXene Ti 3 C 2 T \n x \n nanosheet. e–j) SEM images of the sensitive layers with the different spinosum structures (nos.100, 180, 280, 400, 600, and 800). k) EDX mapping images of no. 280 sensitive layer. Figure 2e–j shows the sensitive layer (denoted as nos. 100, 180, 280, 400, 600, and 800) images with the different spinosum structures on the PU characterized by scanning electron microscopy (SEM). These spinosum structures come from the abrasive papers with the different roughness and the surface curves of the spinosum structure were measured with a step profiler with a distance of 2.0 mm. These figures exhibit that the density of spinosum in the same area increases from no.100 to no.800, while the maximum height of spinosum decreases in turn. Figure 2k shows the EDS mapping images of the spinosum structure surface of the no.280 sensitive layer, which proves that MXene has been uniformly and densely sprayed on the spinosum structure surface. In addition, the square resistance of the spinosum structure sensitive layer with the increase of spraying times was summarized (Figure S4 , Supporting Information). All structures show a similar trend of change. The resistance quickly drops in the early stages and slowly later. Moreover, the resistance rapidly decreases with the gradual flattening of the spinosum structure (from no.280 to no.600). The electrode was also carefully selected as an important part of the pressure sensor. The interdigital electrodes are widely used in sensors because of their ease of operation. The time‐dependent line resistance of the interdigital electrodes was measured during the preparation of the MXene‐based interdigital electrodes (Figure S5a , Supporting Information). The line resistance less than 5.0 Ω means that the MXene‐based interdigital electrodes have been successfully prepared. The successful preparation of the interdigital electrodes is attributed to the good hydrophilicity and conductivity of MXene. Figure S5b in the Supporting Information depicts the optical image of interdigital electrodes on the PI substrate. Figure S5c in the Supporting Information reveals the thickness of the interdigital electrodes, which is ≈5.245 µm. The small resistance can guarantee that the circuit is smoothly energized and the appropriate thickness of the interdigital electrodes will provide more microstructures. The above‐mentioned two aspects are beneficial to the improvement of the sensitivity of the sensor. Figure S6a–c in the Supporting Information shows the optical images of the MXene/PU sensitive layer, MXene‐based interdigital electrodes (PI as flexible substrate), and MXene‐based flexible pressure sensor. Moreover, bending tests were carried out on the different components and they all show excellent flexibility. Therefore, the sensor can be attached to a variety of complex 3D carrier surfaces. 2.2 Sensing Properties of the MXene‐Based Pressure Sensor The flexible pressure sensor, as a “medium,” converts the pressure signal into an electrical signal, which makes the pressure digital and visual. Some performance parameters are needed to quantitatively evaluate the comprehensive performance of the device to design a flexible pressure sensor with excellent comprehensive performance and strong practicability. These performance parameters include sensitivity (S), sensing range, response time, recovery time, and cycle stability. [ \n \n 36 \n \n ] Here, we study the sensing performance of the sensor by using the system assembled by a computer, motion propulsion device, dynamometer, and high‐precision electric signal detection source meter (Agilent B2901A). When the driving voltage was 0.10 V, the change of the real‐time output electric signal of the sensor was measured by the testing system. S refers to the slope of the curve of resistance versus applied pressure and it is a key performance parameter describing the ability of the pressure sensor to convert pressure signal into resistance signal. The sensitivity of a piezoresistive sensor is defined as follows: S = δ (ΔI/I 0 )/ δ P, where ΔI is the current change value under external force, I \n 0 is the current value in the initial state, and P is the external pressure. [ \n \n 49 \n \n ] \n The sensitivities of the fully sprayed MXene‐based sensors (PI as flexible substrate) were measured from no.100 to no.800, and the sensor of no.280 has the highest value compared with the others, which is attributed to the interaction mechanism between the sensitive layer and the interdigital electrodes, as shown in Figure \n \n 3 a . The sensitivity could be divided into three sections: S \n 1 is located in the low‐pressure range (0.20–1.70 kPa), S \n 2 is in the middle‐pressure range (1.70–5.70 kPa), and S \n 3 exists in the high‐pressure range (5.70–20.30 kPa). The corresponding values of S \n 1 , S \n 2 , and S \n 3 are 281.54, 509.78, and 66.68 kPa –1 , respectively. The following investigations on other properties were performed by the no.280 sensor. The current–time ( I–T ) curves show a gradual increasing trend in the current with the gradual increase of the external pressures (Figure 3b ). Figure 3c shows the current–voltage ( I–V ) curves of the sensor with the voltage varying from −1.0 to 1.0 V, and the linear dependence of the voltage on the current at various external pressures indicates a good ohmic contact between the sensitive layer and the interdigital electrodes. Furthermore, the sensor exhibits a rapid response (67.8 ms) and recovery time (44.8 ms) due to the excellent resilience of the PU (Figure 3d ). Figure 3e,f shows that the flexible piezoresistive sensor can identify the external pressures (1.52 and 1.81 kPa) from the different frequencies and speeds. Figure 3g reveals the I–T and pressure–time ( P–T ) curves under the same periodic pressure. The two curves are highly synchronized, which further proves the quick response time and excellent performance of the piezoresistive sensor. The 10 000 cycles of loading and unloading were also tested to further evaluate the service life and mechanical stability of the piezoresistive sensor (Figure 3h ). During the loading and unloading, the output current signal of the sensor remains stable. After 10 000 cycles, the attenuation of the electrical signal is negligible. Accordingly, the sensor has excellent stability and durability under normal conditions. Table S1 in the Supporting Information shows the sensing performance of this sensor and other MXene‐based piezoresistive sensors, indicating that every performance index of the sensor is excellent. Figure 3 Sensing properties of the MXene‐based pressure sensor (PI as the interdigital electrodes substrate). a) Sensitivity of the sensors from no.100 to no.800. b) The I–T curves of the no.280 sensor under serial pressures. c) The I–V curves of the no.280 sensor under serial pressures. d) The response and recovery time of the sensor. e) The frequency response performance of the sensors under 1.52 kPa. f) The different speed response performances of the sensors under 1.81 kPa. g) The response of I–T and P–T curves under periodic loading–unloading cycles. h) After 10 000 pressure cycles at 14.2 kPa, the device shows excellent stability. i) Sensing sensitivities of the nos.100–800 sensors were detected after the sensitive layer self‐healing for 18 h. Stretching and compression simultaneously occur when the sensor is bent by an external force. Here, the sensing performance of the sensor in the bending states was tested. The test system, which is used to test the sensor at different bending angles, is shown in Figure S7a in the Supporting Information. The I–T curve of the different bending angles is shown in Figure S7b in the Supporting Information, and the current intensity of the sensor increases with the increase of the bending angle. Figure S7c in the Supporting Information shows the I–T curve of the sensor stretching between 0° and 90°. These findings prove that the sensor can also detect stretching and compression caused by bending. However, the sensor would inevitably suffer from the external mechanical damage during practical application. Consequently, a sensor with a self‐healing function that can improve the durability of the sensor in practical application must be prepared. As previously mentioned, the fully sprayed MXene‐based pressure sensor has the self‐healing function. Figure S8a–d in the Supporting Information shows the whole cutting‐healing process of the sensor sensitive layer in the natural environment. After 18 h of the self‐healing, the sensitive layers are closely integrated again, the MXene conductive layers are tightly in contact with each other, the sensitivities of the nos.100–800 sensors were tested (Figure 3i ) and the no.280 sensor still shows the highest sensitivity, as shown in Figure S8d in the Supporting Information. The sensitivities in the low‐pressure range (0.30–2.00 kPa), middle‐pressure range (2.00–5.70 kPa), and high‐pressure range (5.70–20.70 kPa) are 281.4, 456.9, and 57.1 kPa –1 , respectively. The data of the nos.100– 800 sensors before and after the cutting‐healing are listed in Table S2 in the Supporting Information. In comparison with the virgin state, the sensitivity of the sensors after the cutting‐healing slightly decreases. The sensitivity of the no.280 sensor reduces by only 0.04% in the low‐pressure range. Many flexible substrates are unavailable for sensor fabrication due to the limitation of the current manufacturing process. Mixed cellulose filter membrane, as a commonly used filter membrane in laboratory, has the characteristics of super‐flexibility. However, this membrane cannot be applied to the flexible sensors as the electrode substrates due to the limitations of traditional electrode preparation technology. To prove that the preparation of interdigital electrodes by spraying is a low‐cost and universal method, a mixed cellulose filter membrane was selected as the flexible substrate of the interdigital electrodes, and the MXene‐based interdigital electrodes were prepared by the same method as above. The sensor still has excellent sensing performance, as shown in Figure S9a in the Supporting Information: S \n 1 is in the low‐pressure range (0.36–2.34 kPa), S \n 2 exists in the middle‐pressure range (2.34–4.57 kPa), and S \n 3 is located in the high‐pressure range (4.57–19.73 kPa), and the corresponding values of S \n 1 , S \n 2 , and S \n 3 are 99.8, 408.4, and 23.4 kPa –1 , respectively. Figure S9b in the Supporting Information shows the I–T curve of the sensor. The output current signal of the sensor regularly increases with the increase of the pressure. Figure S9c in the Supporting Information exhibits the I–V curves of the sensor, which indicates that the sensor has good ohmic contact. The sensor shows fast response (68.4 ms) and recovery time (46.5 ms), as shown in Figure S9d in the Supporting Information. Moreover, the I–T and P–T curves are highly synchronized, proving once again that the sensor has extremely fast response speed (Figure S9e , Supporting Information). After 10 000 pressure cycle tests at 10.7 kPa, the sensor still maintains excellent stability (Figure S9f , Supporting Information). The excellent sensing performance of the sensor proves the universality of the spraying method. 2.3 Working Mechanism of the Fully Sprayed MXene‐Based Pressure Sensor A model of the spinosum structure MXene/PU sensitive layer was established according to the SEM image and surface contour curve of the sensitive layer to understand the sensing mechanism of the designed fully sprayed flexible pressure sensor (Figure 2e–j ). The model of MXene interdigital electrodes was also established according to the optical image and thickness of interdigital electrodes (Figure S5b,c , Supporting Information). The meshes of the models use densely arranged free triangles (Figure S10 , Supporting Information). Then the stress distribution of the two components under different pressures is analyzed by using the finite element method. The stress of the MXene/PU sensitive layer is only distributed on the tip of the spinosum structure when the external load pressure is 1.0 Pa, as shown in Figure \n \n 4 a . The stress distribution concentrates on the top of the spinosum structure and extends to the bottom of the spinosum structure when the external load pressure is increased to 1.0 kPa (Figure 4b ). Figure 4c demonstrates that the stress is evenly distributed on the surface of the MXene‐based interdigital electrodes when the external load pressure is 1.0 kPa. These results indicate that the contact between the spinosum structure and the interdigital electrodes becomes closer with the increase in the external load pressure. Figure 4 Working mechanism of the fully sprayed MXene‐based pressure sensor. Simulation results of the pressure distribution of the sensitive layer at a) 1.0 Pa and b) 1.0 kPa. c) Simulation result of the pressure distribution of the interdigital electrodes at 1.0 kPa. Schematic diagrams of circuit molds corresponding to d) initial state, e) light load state, and f) heavy load state. Based on the above simulation analysis, the cross‐sectional schematic of the interaction between the sensor sensitive layer and the interdigital electrodes under the initial state, light load state, and heavy load state has been created (Figure 4d–f ). Moreover, an equivalent circuit has been postulated to describe the working mechanism of the sensor, as follows: R = R 1 + R 2 R 3 R 2 + R 3 ; where R \n 1 is the intrinsic resistance of the sensitive layer and the interdigital electrodes, R \n 2 represents the contact resistance between the sensitive layer and the interdigital electrodes, and R \n 3 represents the resistance generated by the extrusion of the spinosum structure on the surface of the sensitive layer. In the initial state, slight contact occurs between the interdigital electrodes and the interface of the sensitive layer (Figure 4d ). When a light load is applied to the sensor, the contact area of the interface between the two components increases and is accompanied by a slight deformation of the spinosum structure of the sensitive layer (Figure 4e ). When the contact area increased, the conductive channel and conductivity also increased. In this process, the change of resistance in the circuit is mainly attributed to R \n 1 and R \n 2 because the deformation degree of the spinosum structure is deficient. Next, the contact area continues to increase, and the spinosum structure of the sensitive layer is squeezed during the continuous loading process. R \n 1 , R \n 2 , and R \n 3 all made important contributions to the reduction of resistance in the circuit (Figure 4f ). When the interface contact is close to saturation and the load continues, the only change in the circuit's resistance due to the decrease of R \n 3 . Accordingly, the increase in the conductivity of the sensor will slow down. This finding is consistent with the experimental results, and the sensor shows the highest sensitivity when R \n 1 , R \n 2 , and R \n 3 can all contribute to the change of the resistance in the circuit. In addition, this mechanism can explain that the no.280 sensor has the best sensing performance. The spinosum structures on the surface of the sensitive layer are sparse for the no.100 sensor, so the change of R \n 2 in the equivalent circuit is relatively small. Meanwhile, the large spinosum structures of the no.100 sensor make it difficult to deform and the change of R \n 3 in the equivalent circuit is also limited. In the case of the no.800 sensor, the small and dense spinosum structures of the sensitive layer will not only lead to weak deformation ability but also make the contact interface difficult to expand. Accordingly, R \n 2 and R \n 3 will show minor changes in the equivalent circuit. However, the R \n 2 and R \n 3 of the no.280 sensor in the equivalent circuit change most obviously after being subjected to external pressure. Therefore, the no.280 sensor can make fully use of the spinosum structures, which allows the sensor to be more sensitive to pressure. 2.4 Practical Applications of the Fully Sprayed MXene‐Based Pressure Sensor The minimum detection limit of the flexible piezoresistive sensor is also considered as one of the key factors that determine the application range of the sensor. Herein, a mung bean and a soybean were used to evaluate the detection ability of the sensor under an extremely low‐pressure. The tiny pressure exerted by a mung bean (7.8 Pa) or a soybean (26.3 Pa) can be clearly detected by the sensor, as shown in Figure \n \n 5 a and Figure S11 in the Supporting Information. Therefore, the sensor has great potential applications in real‐time monitoring of human activities and tiny physiological signals. The sensor is attached to the muscles or joints of the human body with adhesive tape, which successfully realizes real‐time monitoring of the physical signals generated by the human activities such as wrist flexion, finger flexion, finger pressing, smiling, ankle bending, and throat swallowing (Figure 5b–g ). The electrical signal output by the sensor changes with the variation of elbow bending angle, so the human behavior can be accurately inferred by the quantitative analysis of the output electrical signal, as shown in Figure 5h . Moreover, the pulse beat can be detected in real‐time by tightly sticking the sensor to the wrist artery. Figure 5i shows the regular pulse wave of ≈76 beats per minute (bpm) for a woman. The curve of pulse waves can not only obtain the bpm of people but also indicate important physiological signals such as blood pressure and arteriosclerosis. The characteristic peaks of the pulse waves include percussion (P), tidal (T), and dicrotic (D), as shown in the insert of Figure 5i . The vascular aging and arterial stiffness can be observed by the radial enhancement index (AI r = T / P ). [ \n \n 50 \n , \n 51 \n \n ] We also tested the practical application of the sensor after self‐healing. The sensor can still monitor human activities in real‐time, as shown in Figure S12 in the Supporting Information. Figure 5 Applications of the fully sprayed MXene‐based pressure sensor in minimum detectable pressure and real‐time monitoring of human activities. The signal responses in the form of current changes come from a) tiny object pressure provided by a grain of mung bean (7.8 Pa), b) wrist bending, c) finger bending, d) finger tap, e) smile, f) ankle bending, g) throat swallowing, h) elbow bending at different angles, and i) wrist pulse (the enlarged illustration is a magnified view of the pulse vibration waveform). Besides detecting various physiological signals of the human body, the sensor can also be applied to the tactile perception, such as electronic skin and robot sensing devices. [ \n \n 52 \n , \n 53 \n \n ] We also designed a 4 × 4 fully sprayed MXene‐based piezoresistive sensor array to explore its sensing ability to the pressure distribution and its application in the field of artificial electronic skin. The current intensities at the different positions of the array sensor are distinguished according to the weight of the object when an astronaut pendant and a key are placed on the array surface, as shown in Figure \n \n 6 a–c . This notion means that the weight or pressure distribution of a specific object can be qualitatively and quantitatively analyzed by referring to the current intensity of each matrix point. Figure 6 Applications of the fully sprayed MXene‐based pressure sensor in the tactile sensing. a) Related pressure distribution is obtained by the astronaut pendant on the surface of electronic skin. b) Optical images of an astronaut pendant and a key on the surface of electronic skin. c) Related pressure distribution is obtained by a key on the surface of electronic skin. d) A general schematic diagram of a pressure sensing system that enables the manipulator to realize accurate tactile feedback. e) The system is used to catch tofu and balloon. f) The mechanical palm grabs‐releases the soft bread with different frequencies. Furthermore, the intelligent robot industry has rapidly developed in recent years. Tactile feedback is an important part of a robot's working process. [ \n \n 54 \n \n ] A single tactile perception cannot realize the whole process of “action‐perception‐feedback” for robots like humans. [ \n \n 34 \n , \n 55 \n \n ] Therefore, we have designed a tactile sensing and feedback system for the mechanical palm, which can make the manipulator feel the pressure change and realize accurate tactile feedback. The system contains five parts, namely, the manipulator and sensor, resistance‐voltage converter, SGS‐THOMSON Microelectronics (STM) 32 microprogrammed control unit (MCU), central processing unit (CPU) of the manipulator, and touchscreen, as shown in Figure 6d . Figure S13a in the Supporting Information shows the hardware structure diagram of the device in operation. The designed sensor is attached to the surface of the mechanical finger, which is used to sense the pressure change when the manipulator touches the object in the process of executing the action commands. The sensor is connected to the resistance‐voltage converter and collects the change of the output electric signal of the flexible pressure sensor. Then, the data are transmitted to the STM 32 MCU for signal analysis and processing. The analyzed data are transmitted to the CPU of the manipulator to control the manipulator and make corresponding tactile feedback. The diagram of the software system in the device is shown in Figure S13b in the Supporting Information. The STM 32 MCU is also connected with a touchscreen to display the change curve of the electrical signals. In Figure 6e , the manipulator grabs fragile tofu and deformable balloon, respectively. The electrical signal output by the sensor greatly changes when the manipulator just touches the tofu and balloon. The manipulator immediately provides feedback according to the change of the electrical signal and stays on the surface of the object to protect its original shape (Videos S1 and S2 , Supporting Information). Moreover, the manipulator is set to grab the soft bread at different frequencies. The soft bread maintains its original shape. We can see the change curve of the electrical signal of the pressure sensor from the touchscreen in Figure 6f , which realizes the digitization and visualization of the force. The above system completes the functions of tactile perception and feedback. Therefore, the sensor has great potential in the application for the tactile feedback of robots."
} | 9,360 |
36144318 | PMC9503713 | pmc | 7,500 | {
"abstract": "The application of plant beneficial microorganisms is widely accepted as an efficient alternative to chemical fertilizers and pesticides. It was shown that annually, mycorrhizal fungi and nitrogen-fixing bacteria are responsible for 5 to 80% of all nitrogen, and up to 75% of P plant acquisition. However, while bacteria are the most studied soil microorganisms and most frequently reported in the scientific literature, the role of fungi is relatively understudied, although they are the primary organic matter decomposers and govern soil carbon and other elements, including P-cycling. Many fungi can solubilize insoluble phosphates or facilitate P-acquisition by plants and, therefore, form an important part of the commercial microbial products, with Aspergillus , Penicillium and Trichoderma being the most efficient. In this paper, the role of fungi in P-solubilization and plant nutrition will be presented with a special emphasis on their production and application. Although this topic has been repeatedly reviewed, some recent views questioned the efficacy of the microbial P-solubilizers in soil. Here, we will try to summarize the proven facts but also discuss further lines of research that may clarify our doubts in this field or open new perspectives on using the microbial and particularly fungal P-solubilizing potential in accordance with the principles of the sustainability and circular economy.",
"conclusion": "5. Conclusions In the few last years, the search for substitutes for phosphate fertilizers is of high importance and urgency as the natural P-source (rock phosphate) is a finite resource. Other reasons also include public acceptance of bio-based agricultural products, climate change, and the growing population. In controlled conditions (laboratories and greenhouses), a large number of microorganisms were reported to solubilize inorganic and organic phosphates. However, the biotech companies were not focused on mass-producing bio-based fertilizers due to their high cost when compared with the low prices of mineral fertilizers. Particularly at this moment, the situation is different: due to the crisis provoked by the war in Ukraine, the prices of chemical fertilizers are extremely high. On the other hand, the success of the field application of biofertilizers is not always visible. The reasons for this are mainly the wrong schemes of product development and a lack of collaboration between experts in different fields of research. Wrong experiments in soil without any microbial inoculant development/formulation could be the reason for a “new” theory or call for reconsideration of the current status. The implementation of new technologies and high investments are not sufficient for the development of serious biotechnological production of P-biofertilizers. What is needed is the establishment of expert protocols for each step of the P-biofertilizer production, which should include all potential possibilities and risks ( Figure 2 ). Alternative P-sources should be tested including low-P rocks. In soil and out of soil microbial solubilization should be considered depending on previous deep analysis of variants. Multidisciplinary approaches and tools including soil science, microbiological, biotechnological, and plant physiology analysis, artificial intelligence, machine learning, and mist computing should be widely used to predict, select and control plant (P) nutrition, particularly in field conditions based on biofertilizers (and precision agriculture in general) and create a larger view on the effects of the multiple properties of the fungal microorganisms from seed germination to fruit quality. All this is following a strategy similar to personalized medicine for humans but is oriented to “cure” a specific deficiency in a soil–plant system. Multiple abiotic and biotic soil factors and plant characteristics and plant–soil–microbe history should be considered before taking a final management decision. This diversity of variables means that one approach for the production and application of fungal P-solubilizers cannot fit all the different contexts, but that different and interconnected strategies should be investigated ( Figure 2 ). Based on the scientific literature, a strong wave of novel strategies and wider application of fungal biofertilizers are expected in the near future including in the field of fungal P-solubilization, always looking for safe and healthy final products [ 106 , 107 ].",
"introduction": "1. Introduction The continuously growing human population determines the increased global demand for high agricultural productivity, which, at the same time, should follow the principles of sustainability and circular economy. In the last 15 years, several biotechnological approaches were developed to enhance plant growth and health with safe and environmentally mild alternatives, including those based on microorganisms. The practical realization of the proposed strategies will significantly reduce the indiscriminate use of chemical fertilizers and pesticides. Despite the environmentally harsh conditions of surviving, soil contains many individual microbial taxa, including different members of the three domains of life. Although we still sub-estimate (for methodological reasons) microbial diversity [ 1 ], microorganisms are one of the key components of both natural and cultivated soils thus affecting the soil quality and plant productivity [ 2 ]. It should be noted that long-term chemical fertilization and application of pesticides decreased both the soil microbial species richness and microbial–plant beneficial interactions as a part of the plant holobiont [ 3 ]. Therefore, rebuilding soil productivity by applying bioeffectors (biostimulants or biofertilizers) is a priority and one of the most studied biotechnological alternatives to chemical fertilizers. The term biofertilizer has different definitions but in general, it includes plant beneficial microorganisms and their derivates (metabolites), excluding biocontrol agents [ 4 , 5 , 6 , 7 ]. Among beneficial microorganisms, bacteria and fungi are considered the most important in helping plant nutrient acquisition and improving plant health. In general, the co-existence of fungi and bacteria is reported in microbiomes with different profile characteristics (animal, soil, and food microbiomes) [ 8 ]. Particularly in soils, they are reported as the most abundant microorganisms with 10 2 –10 4 times more biomass than protists, archaea and viruses [ 1 ]. Amongst various functions that bacteria and fungi perform in soil ecosystems, particularly important is their contribution to plant growth and development, and plant diversity. It was demonstrated that fungi play an important role in the utilization of easily available and more complex litter-derived C than bacteria, thus actively taking part in soil formation [ 9 ]. However, both bacteria and fungi are present in the soil microbial hotspots where the soil organic carbon decomposition is much higher than in the bulk soil [ 10 ]. It was shown that annually, mycorrhizal fungi and nitrogen-fixing bacteria are responsible for 5 to 80% of all nitrogen, and up to 75% of P plant acquisition [ 2 ]. However, while bacteria are the most studied soil microorganisms and most frequently reported in the scientific literature, the role of fungi is relatively understudied [ 11 ], although they are the primary organic matter decomposers and govern soil carbon and other elements cycling [ 12 ]. It is also well established that fungi, particularly in the zone with an abundant presence of fungal hyphae or roots and hyphae (mycosphere or mycorrhizosphere, respectively), greatly affect bacterial growth in soil and, consequently, their interactions with plants [ 13 ]. The potential rapid growth and distribution of a given functional bacterium within the community are often linked to fungi as mediators of ecological processes which also impact the diversity of bacterial communities [ 14 ]. On the other hand, the cooperation between fungi and bacteria is a selective process depending on the soil, although this phenomenon should be further studied in soil and other systems as well [ 13 , 14 ]. Fungi are known as a diverse and multifunctional group of soil microorganisms, which demonstrate a high capacity to adapt to various adverse abiotic conditions such as salinity, drought, heavy metals, and extreme pH [ 15 , 16 , 17 ]. It is also important to mention that fungi manifest significant tolerance to low water activity (a w ) values and high osmotic pressure as proved when growing on solid substrates [ 18 ], preserving at the same time high metabolic activity. In soil, 1.5 million fungal species can be found free-living in the bulk soil or as endophytes occupying plant tissues, the mycorrhizae being the most studied beneficial fungus–plant association [ 19 ]. Many fungi are able to solubilize insoluble phosphates or facilitate P-acquisition by plants and, therefore, form an important part of the commercial microbial products, with Aspergillus , Penicillium and Trichoderma being the most efficient. In this paper, the role of fungi in P-solubilization and plant nutrition will be presented with a special emphasis on their production and application. Although this topic has been repeatedly reviewed, some recent views questioned the efficacy of the microbial P-solubilizers in soil. This short review opinion will try to summarize the proven facts, but also discuss further lines of research that may clarify our doubts in this field or open new perspectives on using the microbial and particularly fungal P-solubilizing potential in accordance with the principles of sustainability and circular economy."
} | 2,431 |
34526096 | PMC8444440 | pmc | 7,502 | {
"abstract": "Background The plant microbiome is an integral part of the host and increasingly recognized as playing fundamental roles in plant growth and health. Increasing evidence indicates that plant rhizosphere recruits beneficial microbes to the plant to suppress soil-borne pathogens. However, the ecological processes that govern plant microbiome assembly and functions in the below- and aboveground compartments under pathogen invasion are not fully understood. Here, we studied the bacterial and fungal communities associated with 12 compartments (e.g., soils, roots, stems, and fruits) of chili pepper ( Capsicum annuum L.) using amplicons (16S and ITS) and metagenomics approaches at the main pepper production sites in China and investigated how Fusarium wilt disease (FWD) affects the assembly, co-occurrence patterns, and ecological functions of plant-associated microbiomes. Results The amplicon data analyses revealed that FWD affected less on the microbiome of pepper reproductive organs (fruit) than vegetative organs (root and stem), with the strongest impact on the upper stem epidermis. Fungal intra-kingdom networks were less stable and their communities were more sensitive to FWD than the bacterial communities. The analysis of microbial interkingdom network further indicated that FWD destabilized the network and induced the ecological importance of fungal taxa. Although the diseased plants were more susceptible to colonization by other pathogenic fungi, their below- and aboveground compartments can also recruit potential beneficial bacteria. Some of the beneficial bacterial taxa enriched in the diseased plants were also identified as core taxa for plant microbiomes and hub taxa in networks. On the other hand, metagenomic analysis revealed significant enrichment of several functional genes involved in detoxification, biofilm formation, and plant-microbiome signaling pathways (i.e., chemotaxis) in the diseased plants. Conclusions Together, we demonstrate that a diseased plant could recruit beneficial bacteria and mitigate the changes in reproductive organ microbiome to facilitate host or its offspring survival. The host plants may attract the beneficial microbes through the modulation of plant-microbiome signaling pathways. These findings significantly advance our understanding on plant-microbiome interactions and could provide fundamental and important data for harnessing the plant microbiome in sustainable agriculture. \n \n Video abstract \n \n Supplementary Information The online version contains supplementary material available at 10.1186/s40168-021-01138-2.",
"conclusion": "Conclusions Based on the presented data, the host compartment exerts the strongest effect on the bacterial and fungal microbiome assembly, followed by FWD, and the sampling site. Fungal communities are more sensitive to FWD than bacterial communities, and fungal taxa play a more important role in the diseased co-occurrence interkingdom network than the healthy network. Microbiomes of the reproductive compartments are less affected by FWD than those of the vegetative compartments. The compartments of diseased pepper plant may recruit beneficial bacterial taxa that could provide protective functions to host plants. The current study siginificantly improves our understanding on microbiome assembly and function in both the below- and aboveground compartments of chili pepper under FWD and provids potential for manipulating the plant microbiome to promote plant health and sustainable agricultural production.",
"discussion": "Discussion In this study, we sought to investigate the effect of FWD on chili pepper microbiomes using amplicons and metagenomic approaches. By profiling both bacterial and fungal communities in twelve below- and aboveground compartments of healthy and FWD pepper plants, we reveal that fungal networks are less stable and their communities are more sensitive to FWD than the bacterial communities. FWD has a stronger impact on the microbiome assembly of vegetative organs than on those of reproductive organs, with the strongest effects on the upper stem epidermis and root endosphere. Metagenomic sequencing data from these two compartments further suggested that several functional genes involved in detoxification, biofilm formation, and plant–microbiome signaling pathways (i.e., chemotaxis) were significantly enriched in the FWD plants. Moreover, our work provides evidence that other organs of pepper plants besides the root, such as stem and fruit, can also recruit potential beneficial bacteria to the FWD plants. Through this work, we provide evidence that FWD not only changes the diversity, assembly, and network of microbial communities, but also impacts their ecological functions. Below, we discuss how these findings have advanced our understanding of disease-induced changes in plant microbiome assembly, co-occurrence patterns and functions. FWD affects less on the microbiome of reproductive organs than vegetative organs Uncovering how the host plant and its associated microbiomes respond to plant disease is of great importance to advance the co-evolutionary theory of plant-microbiome interactions [ 87 ]. Our study demonstrated that FWD affects the bacterial and fungal communities in the reproductive organ (fruit) to a lesser extent than those in vegetative organs (root or stem). Changes in the fungal community were associated with co-infection with other potential fungal pathogens in the root and stem, but not in the fruit. Thus, the less-pronounced effect of FWD on the fruit, relative to that on the root and stem, may represent a life history tradeoff strategy of a plant to ensure survival of the next generation (fruit and seed) rather than investing in the contemporary diseased individual. Secondary metabolites, such as capsaicinoids, may protect the chili fruit and seed from fungal pathogens [ 88 ]. The strongest effect of FWD on microbial communities was in the upper stem epidermis compared with other soil and plant compartments. FWD-induced changes in plant physiological characteristics, such as water relations [ 89 ], could strongly affect the aboveground parts of the plant. For the stem, the effect of FWD on both bacterial and fungal communities in epidermis compartments was more pronounced than that on those in the xylem compartments. The epidermis is a more favorable niche for microbes than the xylem in terms of accessibility of organic nutrients (such as small sugars) [ 90 , 91 ]. For the root, a pronounced effect of FWD on the bacterial and fungal communities was observed in the endosphere than in the episphere, for which the epidermis and xylem were not considered separately in the current study. The episphere was supposed to be an important interface between the host and the environment, and the root episphere microbiomes were determined by both host selection and soil characteristics [ 13 , 14 ]. Since fungi are the important consumers of belowground inputs of plant-derived carbon [ 50 – 52 ], the mycobiome in the root endosphere could respond strongly to FWD. The microbial communities in the diseased plants were more variable than those in the healthy plants in most compartments. This is contrary to the expectation, based on homogeneous selection [ 92 ], that the same environmental selection pressure often leads to similar community structures. Plant-associated microbiomes were shaped by multiple host and environmental factors, such as plant compartment, host genetics, and edaphic factors. A recent study indicated that host selection (i.e., compartment niche and host species) has a greater determining effect on shaping the plant microbiome than the environmental factors [ 14 ]. The pronounced effect of the host compartment observed herein for pepper has been also observed in sorghum [ 93 ] and Populus [ 16 , 94 ]. The current study provides additional evidence in support of the niche occupation theory of plant microbiome assembly [ 37 , 94 ] under both healthy and diseased conditions. Having observed a predominant effect of the host compartment on microbial community composition, we propose that disease may lessen the plant effect and, thereby, potentiate community dissimilarity in the diseased plant. Fungal communities are more sensitive to FWD than bacterial communities Cooperative and competitive interactions among microbial species and network modularity can influence the community stability [ 40 , 95 ]. In this study, bacterial networks and their hub taxa in both healthy and diseased plants were characterized by a higher proportion of negative correlations than those in the fungal networks. Mutually negative interactions, indicating ecological competition, can improve microbiome stability by dampening the destabilizing effects of cooperation [ 40 ]. The host may benefit from microbial competition, which results in improved resistance to external stress [ 53 ]. In contrast to bacterial communities, the fungal communities were more affected by FWD, probably due to enhanced positive intra-kingdom correlations among fungal taxa observed in FWD networks as compared with the healthy networks. Also, lower modularity in fungal network may exacerbate the destabilizing effect due to the higher prevalence of cross-module correlations among taxa [ 39 , 41 ]. These findings indicate that fungal community was more sensitive to FWD than bacterial communities as demonstrated by its lower network stability. A previous study reported that soil bacterial networks were less stable under drought stress than fungal networks [ 17 ]. Since our samples were plant-associated compartments and the external stress is biotic, these could account for the contrasting results. Our results indicated that sampling site had a higher impact on the bacterial community than on the fungal community. The sampling site effect represented the interaction effect of site-dependent environmental characteristics (e.g., climate and soil type) and the cultivar (host genotype) at each site, which may co-influence the microbiome composition. Bacteria and fungi differ in body size [ 96 , 97 ], diversity, metabolic activity [ 98 ], dispersal potential [ 99 ], and the interaction with host or other microbes, which may affect species sorting and the community assembly process. Our data indicated that FWD decreased the complexity of bacterial networks but increased the complexity of fungal networks. The contrasting pattern between the bacterial and fungal networks parallels recent observation based on soil macroecological patterns of Fusarium wilt [ 100 ]. Previous study has revealed the importance of the network complexity [ 53 ] and hub taxa [ 101 , 102 ] in supporting ecosystem functions. The fungal connectivity, mainly belonging to intra-kingdom cooperative interactions, increased in the diseased plants, thus inducing the ecological importance of fungal taxa. In addition, we found the cooperative correlations dominated within each microbial kingdom but the competitive correlations dominated between bacteria and fungi, which may be explained by the fact that the bacteria and fungi normally compete for plant-derived substrates [ 52 ]. Disease-induced changes in microbiome composition and functions Deciphering the keystone taxa (e.g., biomarker taxa, core taxa, and network hubs), and their correlations with the host plant and pathogens, is critical for harnessing the plant microbiome to enhance plant growth and health [ 4 , 12 ]. Several potential beneficial bacteria, such as Pseudomonas , Streptomyces , and Bacillus , were enriched in diseased plants in the current study, which were also identified as the core taxa (i.e., present in all samples) in plant microbiomes. Previous studies have revealed that many members of the Pseudomonas , Streptomyces , and Bacillus genera colonize different plant compartments (e.g., phyllosphere and rhizosphere) and play a vital role in modulating host performance, especially in plant pathogen suppression [ 4 , 54 , 87 , 103 , 104 ]. For example, Streptomyces is well known for excreting antibiotic compounds and can protect plants from pathogens [ 105 – 107 ]. Pseudomonas and Bacillus are the two most dominant taxa of plant-beneficial bacteria, and some representatives of these two genera can coexist and cooperate with each other [ 21 ]. Our results indicated that the host plant may selectively regulate the community abundance of some core taxa under pathogen stress. Further, several bacterial taxa, such as Microbacterium , Streptomyces , and Pantoea , were enriched in diseased plants and were also identified as hub taxa in the co-occurrence networks. Hub taxa hold key topological positions within the network and may be deployed to organize favorable plant microbiomes [ 12 ]. For instance, a study on Arabidopsis thaliana suggested that the host plant selectively impacts its associated microbiomes and microbe-microbe interactions by modulating the hub taxa Albugo laibachii and Dioszegia spp. in the phyllosphere [ 15 ]. The overlap between the biomarker taxa, core taxa, and network hubs suggests that some bacterial taxa recruited by the diseased plants may act as keystone taxa for plant microbiomes and ensure the survival of the next generation. The current study provides evidence on the critical role of bacterial taxa in the “cry for help” strategy of the host plant, in which the plant actively involves its microbial partners to maximize its or its offspring survival and growth under external stress. This is a survival strategy conserved across the plant kingdom [ 18 , 25 , 87 ]. For example, a study of sugar beet Rhizoctonia damping-off disease indicated that members of the Chitinophagaceae and Flavobacteriaceae become enriched within the plant endosphere upon pathogen invasion and that reconstruction of a synthetic community of Flavobacterium and Chitinophaga consistently suppresses fungal root disease [ 11 ]. Several recent studies also suggested that the aboveground pathogen infection induces an assemblage of a plant-beneficial bacterial consortium in the root microbiome [ 23 , 26 ]. Berendsen et al. [ 23 ] reported that A. thaliana specifically promotes three bacterial taxa ( Stenotrophomonas sp., Xanthomonas sp., and Microbacterium sp.) in the rhizosphere upon foliar infection with Hyaloperonospora arabidopsidis , and together these three bacteria will induce systemic resistance against pathogen and promote growth of the plant. Similarly, based on the pepper data presented in the current study, an infection with a soil-borne pathogen (e.g., FWD) has driven the recruitment of beneficial microbes to the aboveground parts of the host plant. Intriguingly, Liu et al. [ 22 ] provided evidence for the recruitment of beneficial microbes to the wheat rhizosphere and root endosphere to suppress the soil-borne pathogen Fusarium pseudograminearum . The study also showed that the beneficial microbe Stenotrophomonas rhizophila could boost plant defenses in the aboveground parts when the pathogen was present. Metagenomic analyses indicated that microbiome functional genes involved in detoxification, chemotaxis, and biofilm formation were enriched in the diseased plant compared with the healthy plant. UDP-glucuronosyltransferases were enriched in the microbiome from the upper stem epidermis of diseased pepper. UDP-glucuronosyltransferases encode a family of detoxifying enzymes [ 108 – 110 ] that may detoxify the toxic metabolites, such as fusaric acid, trichothecenes, fumonisins, and enniatins produced by Fusarium spp. [ 45 , 111 ] or by other co-infected pathogenic fungi. CsgD LuxR family transcriptional regulator was enriched in the microbiome of diseased root endosphere. This is the master regulator of biofilm formation pathway, which could protect microbes from the adverse environmental conditions, thereby enhancing microbial survival [ 112 – 114 ]. Several genes encoding MCPs associated with plant-microbiome signaling pathways were enriched in the microbiome of diseased root endosphere. MCPs are the predominant chemoreceptors in motile bacteria that alter the activity of CheA histidine kinase and the bacterial swimming behavior upon detection of specific chemicals [ 115 ]. MCPs have been identified in typically beneficial bacteria, e.g., Bacillus subtilis [ 116 ] and Pseudomonas spp. [ 117 , 118 ], which were also significantly enriched in diseased plant in the current study. Under stress conditions, such as pathogen invasion, a plant can attract distant beneficial microbes by actively releasing nonvolatile root exudates, such as amino acids, nucleotides, and long-chain organic acids [ 26 ], or by actively emitting blends of volatile organic compounds [ 24 ]. The findings of the current study suggest that the MCP gene enrichment in diseased plants may be related to the response of MCP-producing bacteria to plant-released signal molecules. These bacteria would use MCPs to detect specific concentrations of these molecules in the extracellular matrix, enabling directional accumulation of the bacteria to the plant. Although the taxonomic and functional analyses of healthy and diseased pepper microbiomes provide evidence for the plant “cry for help” strategy, culture-based experiments are required to verify the hypothesis. Specifically, the enriched potential beneficial bacteria should be isolated and their disease-suppressing effects tested in vivo. The putative plant signal molecules released under biotic stress are also worthy of further exploration. Finally, metagenomic analyses revealed that FWD significantly decreased the functional diversity of KO, COG, and Resfam profiles of the microbiome of the upper stem epidermis. The functional diversity reduction could be largely caused by a drop in microbial diversity. A number of studies have demonstrated the importance of biodiversity for ecosystem function [ 119 – 122 ]. Similarly, our data showed that high microbiome diversity in healthy plant could ensure its better involvement in multiple ecosystem functions. Highly diverse microbiome communities tend to be more complex and possess greater functional redundancy and interkingdom associations [ 53 ]. By contrast, pathogen invasion could reduce the microbiome diversity and functional diversity as a result of disease-induced inhibition of plant photosynthesis [ 123 ] and change in water physiological characteristics [ 89 ]. In the current study, the relative abundance of alkaline phosphatase gene phoD , which is responsible for the recycling of organic phosphorus, was reduced in the diseased root endosphere, suggesting that the FWD affects plant phosphorus absorption [ 124 ]. Greater functional variation in the upper stem epidermis microbiome than that in the root endosphere microbiome may also reflect the density of microbes surrounding each plant organ, which is vastly greater in the root than in the stem [ 36 ]."
} | 4,744 |
32296945 | PMC7228911 | pmc | 7,505 | {
"abstract": "Drought reduces the availability of soil water and the mobility of nutrients, thereby limiting the growth and productivity of rice. Under drought, arbuscular mycorrhizal fungi (AMF) increase P uptake and sustain rice growth. However, we lack knowledge of how the AMF symbiosis contributes to drought tolerance of rice. In the greenhouse, we investigated mechanisms of AMF symbiosis that confer drought tolerance, such as enhanced nutrient uptake, stomatal conductance, chlorophyll fluorescence, and hormonal balance (abscisic acid (ABA) and indole acetic acid (IAA)). Two greenhouse pot experiments comprised three factors in a full factorial design with two AMF treatments (low- and high-AMF colonization), two water treatments (well-watered and drought), and three rice varieties. Soil water potential was maintained at 0 kPa in the well-watered treatment. In the drought treatment, we reduced soil water potential to − 40 kPa in experiment 1 (Expt 1) and to − 80 kPa in experiment 2 (Expt 2). Drought reduced shoot and root dry biomass and grain yield of rice in both experiments. The reduction of grain yield was less with higher AMF colonization. Plants with higher AMF colonization showed higher leaf P concentrations than plants with lower colonization in Expt 1, but not in Expt 2. Plants with higher AMF colonization exhibited higher stomatal conductance and chlorophyll fluorescence than plants with lower colonization, especially under drought. Drought increased the levels of ABA and IAA, and AMF colonization also resulted in higher levels of IAA. The results suggest both nutrient-driven and plant hormone-driven pathways through which AMF confer drought tolerance to rice. Electronic supplementary material The online version of this article (10.1007/s00572-020-00953-z) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusion AMF colonization in rice fields is usually low, but it may be possible to enhance colonization by adding AMF inoculum. Increased RLC improves rice plant performance through uptake of nutrients such as N and P, resulting in higher grain yields (hence a higher harvest index), without much effect on total plant biomass. Moreover, AMF increase photosynthesis, especially under drought, via a smaller reduction in stomatal closure and by maintaining higher levels of chlorophyll fluorescence. These effects are likely mediated both through nutrients and through regulation of plant hormones, especially IAA. AMF therefore contribute to a better recovery after drought resulting in higher rice grain yields. The outcomes of our study may be relevant under climate change where drought is becoming a major factor restricting rice production. Increasing AMF colonization may be important for water savings.",
"introduction": "Introduction Rice ( Oryza sativa L.) is a staple food feeding more than half of the world’s population. Demand for it is increasing due to an increase in the global population (FAO 2002 ). More than 75% of global rice production is from lowland rice cultivated under submerged conditions, and the remainder is from upland rice grown under non-submerged conditions (Maclean et al. 2013 ). Submerging rice paddy fields increases the availability of nutrients in the soil and limits the growth of weeds. However, this practice requires very large amounts of water (Haefele et al. 2008 ). Whereas, water can be sufficiently supplied in irrigated farming systems, water availability is a problem under rain-fed rice farming. Under those conditions, rainfall is the only water source; therefore, the productivity is highly dependent on the amount of rainfall. Less rainfall leads to water deficit in the soil, inducing drought, which can be a major constraint for producing rice. Due to global climate change, drought likely will occur more frequently and more severely than in the past, causing problems for crop production in several regions of the world. Compared to other cereals, rice is particularly sensitive to drought. Drought affects growth and grain yield of rice by limiting water and nutrient availability, especially phosphorus (P) (Suriyagoda et al. 2014 ). In addition, drought reduces stomatal conductance as a mechanism to reduce water loss. However, lower stomatal conductance decreases gas exchange and photosynthesis efficiency and reduces yields (Lauteri et al. 2014 ). The effects of drought on rice depend on timing and severity (Prasertsak and Fukai 1997 ). For instance, drought during vegetative stages has a smaller negative impact on yield than when it occurs during the panicle development stage (Boonjung and Fukai 1996 ). Drought reduces leaf expansion and delays maturation during the vegetative stage (Lilley and Fukai 1994 ). Drought can reduce rice yield by more than 60% when it occurs during the panicle development stage (Boonjung and Fukai 1996 ; Venuprasad et al. 2007 ). Growth and yield reduction can be mitigated by irrigation. However, such management is not practical for rain-fed farming. Hence, rain-fed farming needs other means to cope with drought. Some drought-tolerant rice varieties have been successfully developed through breeding, for instance, Sahbhagi Dhan in India, Sahod Ulan in the Philippines, Sookha Dhan in Nepal, and IR64 in India (Dar et al. 2014 ). These varieties yield 0.8–1.2 t ha −1 more than drought-susceptible varieties under drought (Dar et al. 2014 ). Plant phenotypic plasticity is important to cope with drought, ideally enabling plants to withstand drought without a yield penalty. Highly adaptable plants can respond to drought by producing more roots, reducing water loss via stomatal closure and early maturation (Jearakongman et al. 1995 ; Fukai and Cooper 1995 ). The changes of stomatal conductance under drought also can be related to plant growth hormones, for instance, abscisic acid (ABA) and indole-3-acetic acid (IAA). ABA is the hormone that inhibits shoot growth, especially under drought. Under drought, ABA will be produced in the shoot (Borghi et al. 2015 ) or transported from the root to the shoot (Ko and Helariutta 2017 ), inducing stomatal closure. Haider et al. ( 2018 ) found a significant increase in leaf ABA content of rice plants under drought. IAA is important for root and shoot development, and it has been reported that IAA can induce the establishment of arbuscular mycorrhizal fungi (AMF) (Lüdwig-Müller and Güther 2007 ; Fitze et al. 2005 ). The contribution of AMF to plant levels of IAA has not been well explored. Apart from these mechanisms, some plants deal with drought through interaction with and assistance by soil micro-organisms. One major group of soil micro-organisms that play an important role in enhancing drought tolerance comprises AMF (Rodriguez and Redman 2008 ; Ruiz-Lozano and Aroca 2010 ; Ruiz-Sánchez et al. 2010 ; Ruiz-Lozano et al. 2016 ). The symbiosis of AMF and roots increases plant nutrient uptake under drought, especially phosphorus (P) uptake (Augé 2001 ). In addition, AMF can alter photosynthetic efficiency of plants under drought by maintaining stomatal conductance (Augé 2001 ; Querejeta et al. 2007 ; Augé et al. 2015 ; Ruiz-Lozano et al. 2016 ) and the efficiency of photosystem II (PS II) (Mirshad and Puthur 2016 ). Augé et al. ( 2015 ) reported that the stomatal conductance of mycorrhizal plants is 24% higher than that of non-mycorrhizal plants. The changes in stomatal conductance also may be related to the effects of AMF regulating plant hormones. According to Estrada-Luna and Davies ( 2003 ), the flux of ABA in the shoots of AMF plants is lower than in non-AMF plants, which also results in higher transpiration and leaf water potential. There are only few studies on AMF symbiosis and rice. This may be because rice is mostly grown in waterlogged conditions, which usually inhibit AMF colonization. Nevertheless, the symbiosis of AMF and rice plants has been reported (Maiti et al. 1995 ; Wangiyana et al. 2006 ; Lumini et al. 2011 ; Watanarojanaporn et al. 2013 ; Vallino et al. 2014 ). For instance, the system of rice intensification promotes root colonization and diversity of AMF species in rice roots compared to conventional rain-fed rice cultivation systems (Watanarojanaporn et al. 2013 ). AMF are more abundant in low-input farming and under aerobic conditions than under partly anaerobic and submerged conditions (Lumini et al. 2011 ; Vallino et al. 2014 ). Hence, field management that promotes the functioning of AMF symbioses and possibly additional AMF inoculation could increase AMF colonization in rice. Increased AMF colonization may subsequently make rice more tolerant of drought, but the magnitude of this effect is still unknown and therefore needs to be investigated. We investigated the contribution of AMF to the growth of six different rice varieties with different drought tolerances, under well-watered and drought conditions. Furthermore, we attempted to understand underlying mechanisms of mycorrhiza-enhanced drought tolerance, such as higher nutrient uptake, enhanced stomatal conductance, and elevated efficiency of PS II. We also studied the effects of AMF on the regulation of plant hormones in rice without and with drought. In this study, we included the measurement of ABA and IAA hormones. In order to add a level of realism with respect to field conditions, we compared plants with higher and lower colonization by AMF (through inoculum addition), rather than comparing plants with and without mycorrhizas. We hypothesized that (i) Rice with higher levels of AMF colonization have higher uptake of N and P, and more biomass (shoot, root, grain yield) than plants with lower levels of colonization, and these AMF benefits are larger under drought than under well-watered conditions. (ii) Rice with higher levels of AMF colonization have higher stomatal conductance and higher quantum yield of PS II ( F v / F m ) than plants with lower levels of colonization, and these mycorrhizal effects are larger under drought than under well-watered conditions. (iii) Rice with higher levels of AMF colonization have lower leaf ABA and higher leaf IAA concentrations than plants with lower levels of AMF colonization.",
"discussion": "Discussion Addition of commercial inoculum increased AMF colonization, possibly through both changes in inoculum potential and changes in AMF species composition. We did not assess species composition of the low- and high-AMF treatments, so cannot evaluate the relative importance of possible qualitative changes in the AMF community. Our study showed that inoculum addition resulted in higher grain yields (Expt 1; marginally so in Expt 2), whereas there were no effects on shoot and root dry biomass. There also were no significant mycorrhiza × water availability interactions, except for root dry biomass in Expt. 2, partly supporting our first hypothesis. The second hypothesis also was partly supported by a significant effect of mycorrhizas and the mycorrhiza × water availability interaction for stomatal conductance (Expt 1; marginally so for Expt 2); quantum efficiency was significantly influenced by mycorrhizas in both experiments, but the mycorrhiza × water availability interaction was not significant. There was no effect of mycorrhizas on ABA, whereas the mycorrhizal effect on IAA was significant. The results therefore confirmed our hypotheses on the positive effects of increased AMF colonization on rice under drought, but an interaction between AMF and drought was seldom evident. AMF colonization Our experiments showed similar fractional colonization as previous studies. Zhang et al. ( 2014 ) reported 2–3% RLC in non-inoculated rice plants and 12–19% RLC in rice roots inoculated with AMF. Wangiyana et al. ( 2006 ) found 3–5% RLC in rice roots growing in paddies without AMF inoculation. AMF inoculation increased RLC, suggesting inoculum limitation in the field. The higher root colonization in Expt 2 than in Expt 1 is likely due to the build-up of AMF in the soil between years, as inoculum potential doubled from five to ten AMF spores per 100 g soil between samplings. However, evidence for inoculum limitation, as shown by higher grain yields of plants and higher stomatal conductance and chlorophyll fluorescence with higher levels of colonization, persisted in the second year. Drought increased mycorrhizal colonization significantly in Expt 1 (but not in Expt 2), in agreement with studies by Lumini et al. ( 2011 ) and Vallino et al. ( 2014 ), who observed that mycorrhizal colonization was higher in rice roots growing in dry conditions compared to submerged conditions. These studies reflected a change from anaerobic to aerobic conditions and considering the strictly aerobic characteristics of AMF such an increase is not surprising. It is not clear whether our well-watered treatment (0 kPa) created anaerobic conditions. As the effect of drought on mycorrhizal colonization is much smaller than that of the inoculation treatment, our results suggest that a shift from irrigated rice to rain-fed rice will only gradually result in increases in mycorrhizal inoculum potential, and that inoculum addition or management, possibly with the help of cover crops when fields are fallow, could contribute to the build-up and maintenance of sufficient mycorrhizal inoculum, which then has beneficial consequences for yield. Shoot and root dry biomass and grain yield Drought reduced rice shoot dry biomass. The moderate drought of Expt 1 had a smaller impact on root dry biomass than the more severe drought of Expt 2. The decrease of root and shoot dry biomass under drought could be both due to the reduced availability of water, which impeded photosynthetic carbon gain, and through drought-induced reduction of nutrient availability, especially of nutrients with low mobility such as P (Prasertsak and Fukai 1997 ; Suriyagoda et al. 2014 ). The responses of rice roots under drought contradicted previous reports, which proposed that rice develops increased roots under drought (Yoshida and Hasegawa 1982 ). Our results did not show that the most drought-tolerant varieties produced more roots than the less drought-tolerant varieties. The marginally significant interaction between mycorrhizas and water in Expt 1 ( P = 0.064) suggests that under moderate, but not severe drought, AMF can somewhat alleviate this interaction effect. Drought decreased grain yield of rice in both experiments. Moderate drought of 4 days had a smaller negative effect than strong drought that lasted 6 days. Our result is in line with the study of Venuprasad et al. ( 2007 ), who found a reduction of rice yield of more than 60% under drought. Similarly, Ghosh and Singh ( 2010 ) found significantly decreased rice yield when soil water potential decreased to − 60 kPa. Both water and nutrients are major limiting factors for rice at the grain filling stage (Fageria 2003 ). Even though AMF did not increase shoot and root dry biomass, AMF increased rice grain yield in our experiments. In addition, Zhang et al. ( 2016 ) stated that AMF plants increase the allocation of N and P to rice panicles compared to non-AMF plants during the grain filling stage, and the grain yield of rice increased about 28%. Stomatal conductance and chlorophyll fluorescence Drought substantially decreased stomatal conductance, which can be explained by the plant physiological mechanisms that enabled reduced water loss. When water becomes limiting, stomata are closed to prevent the loss of water via transpiration, which simultaneously reduces the exchange of CO 2 . As stated by Hasegawa and Yoshida ( 1982 ), the decrease in transpiration rate of upland rice occurs when soil water potential is reduced below − 20 kPa. Under drought, plants with higher AMF colonization exhibited higher stomatal conductance than plants with lower AMF colonization. With more severe drought in Expt 2, the effect was smaller with only a marginally significant effect. The meta-analysis of Augé et al. ( 2015 ) showed that, averaged over all studies, stomatal conductance of AMF plants is 24% higher than in non-AMF plants. Higher stomatal conductance might be due to the extension of hyphae to the water and nutrient sources that are inaccessible to plant roots (Smith and Read 2010 ), but has been hypothesized also to be due to hormonal changes consequent upon mycorrhizal colonization (Birhane et al. 2012 ). The interaction between AMF and drought in both experiments indicates that AMF can alleviate the negative consequences of stomatal closure under drought. This is in agreement with the meta-analysis of Worchel et al. ( 2013 ), who also found greater effects of AMF on the growth of grasses grown under dry than under normal conditions. Li et al. ( 2014 ) found a positive effect of AMF ( Rhizophagus intraradices ) on barley, but no effect of drought on stomatal conductance. Quantum efficiency of PS II was unaffected by the moderate drought of Expt 1, but was significantly reduced by the strong drought of Expt 2. These results are in agreement with the study of Puteh et al. ( 2013 ), who reported that the quantum efficiency of rice decreased from 0.78 to 0.60 after 8 days of drought. In our Expt 1, where we did not provide water for 4 days, drought might not have been sufficiently severe to cause a reduction of quantum efficiency. Apparently, chlorophyll fluorescence acts at a different temporal scale than stomatal conductance, in that chlorophyll fluorescence is more resistant to a short drought (Trueba et al. 2019 ). The values of chlorophyll fluorescence in well-watered plants are close to the theoretical optimum of 0.83 (Björkman and Demmig 1987 ). Despite values of well-watered plants close to that theoretical maximum, plants with higher AMF colonization had slightly but significantly higher values of chlorophyll fluorescence, possibly due to sink stimulation of photosynthesis by the AMF symbiosis (Kaschuk et al. 2009 ). Beneficial effects of AMF on chlorophyll fluorescence also have been reported by de Andrade et al. ( 2015 ), who found that mycorrhizal rice plants had higher chlorophyll fluorescence under arsenate and arsenite pollution than non-mycorrhizal plants. Mathur et al. ( 2019 ), studying the response of wheat to very severe drought, also noted a beneficial effects of AMF on chlorophyll fluorescence. However, Porce et al. ( 2015 ) observed that mycorrhizal plants exhibited lower chlorophyll fluorescence than non-mycorrhizal plants, except at high salt levels where fluorescence values increased in mycorrhizal plants compared to a treatment with lower salt levels. Nutrient uptake: N and P concentration, N:P ratio Drought limits the availability of nutrients for plant uptake (Suriyagoda et al. 2014 ). Drought effects were noted for plant biomass, but less so for nutrient concentrations. Mild drought of Expt 1 did not affect leaf N and P concentrations, whereas the more severe drought of Expt 2 did positively affect concentrations of both nutrients. Our results contrast with previous studies that reported reduction of P uptake under drought (Suriyagoda et al. 2014 ; Sardans and Peñuelas 2004 ). A meta-analysis by He and Dijkstra ( 2014 ) indicated that drought on average reduced plant N and P concentrations by 3.7 and 9.2% respectively. However, their meta-analysis also showed that drought experiments involving a drying–rewetting cycle (their type II, as in our experiment) did not have a negative effect on those concentrations, with rather non-significant positive effect sizes as in our experiment. Higher AMF colonization did not affect leaf N concentration, suggesting that N immobilization in the mycorrhizal mycelium was not important. N is important for grain filling and ripening. More than 60% of N is finally translocated from shoot to grain during the reproductive stage (Fageria 2003 ). AMF rice plants allocate more N to the panicle than non-AMF rice plants (Zhang et al. 2016 ). However, we cannot confirm the effects of AMF on N allocation, because we did not analyze the N concentration in the roots and grain in our experiments. Increasing mycorrhizal colonization increased P concentrations in Expt 1 but did not have an effect in Expt 2. In Expt 1, rice plants were N- rather than P-limited (to judge from N:P ratios below 10), so a major part of the additionally acquired P could not be translated into biomass increase but rather showed as higher P concentrations. In Expt 2, plants were P-limited, as N:P ratios were above 20, but it is unclear why plants did not show a biomass response to higher AMF colonization. Plant hormones (ABA and IAA) ABA has been considered the abiotic stress hormone by Bahadur et al. ( 2019 ), and the increase of ABA under drought agrees with their review. Dobra et al. ( 2010 ) found that ABA increased about 50–80 times in tobacco leaves grown under drought. Ludwig-Müller ( 2010 ) and Bahadur et al. ( 2019 ) also included data on changes in ABA levels due to mycorrhizal colonization, and both decreases in root ABA (in tomato and the legume ( Glycyrrhiza ) and increases in ABA (in maize) have been noted. Reduction of ABA in AMF plants has also been reported by Estrada-Luna and Davies ( 2003 ) in mycorrhizal Capsicum annuum compared to non-inoculated plants. Higher levels of ABA would result in stomatal closure and a lowering of stomatal conductance, so we cannot explain a mycorrhiza effect on stomatal conductance without an effect on ABA levels in our study. According to Borghi et al. ( 2015 ), plants may produce or transport more ABA to the leaves to regulate stomatal closure when subjected to drought. However, earlier studies referred to ABA levels in roots, and therefore may not be comparable to our study where we assessed ABA levels in shoots as data on root–shoot signaling through hormones remain scarce (Ludwig-Müller 2010 ). Both drought and AMF resulted in increased IAA levels. The increase of IAA in response to drought is not consistent with observations by Dobra et al. ( 2010 ) on tobacco, who observed decreases in IAA levels in young leaves (we collected the second leaf for hormone analysis), but increases in IAA levels in middle and lower leaves and also in roots. Literature data indicate both cases where IAA levels were upregulated by AMF and cases where hormone levels were unchanged, but most of the available data refer to changes in hormone levels in roots (Ludwig-Müller 2010 ). Some plant species produce IAA also to stimulate the symbiosis with soil micro-organisms under stress conditions. That could be the reason that IAA content in plants with higher AMF colonization was higher than in plants with lower AMF colonization. AMF inoculation also may increase the level of IAA in plant leaves. Fitze et al. ( 2005 ) found an increase of IAA in maize after 20 and 30 days after AMF inoculation. However, there are other studies that reported that IAA does not change with AMF inoculation (Torelli et al. 2000 ; Shaul-Keinan et al. 2002 )."
} | 5,759 |
31549074 | PMC6750057 | pmc | 7,506 | {
"abstract": "Shape morphing is a critical aptitude for the survival of organisms and is determined by anisotropic tissue composition and directional orientation of micro- and nanostructures within cell walls, resulting in different swelling behaviors. Recent efforts have been dedicated to mimicking the behaviors that nature has perfected over billions of years. We present a robust strategy for preparing 3D periodically patterned single-component sodium alginate hydrogel sheets cross-linked with Ca 2+ ions, which can reversibly deform and be retained into various desirable inside-out shapes as triggered by biocompatible ions (Na + /Ca 2+ ). By changing the orientations of the patterned microchannels or triggering with Na + /Ca 2+ ions, various 3D twisting, tubular, and plant-inspired architectures can be facilely programmed. Not only can the transformation recover their initial shapes reversibly, but also it can keep the designated shapes without continuous stimuli. These inside-out 3D reversible ion-triggered hydrogel transformations shall inspire more attractive applications in tissue engineering, biomedical devices, and soft robotics fields.",
"introduction": "1. Introduction Shape morphing has all-pervading presence in biological systems and is a critical aptitude for the survival of organisms. For example, in order to better adapt to the complex and ever-changing environment, many plants (e.g., Venus flytrap, mimosa, and pinecones) are able to change their shapes, of which the organs such as leaves, flowers, and tendrils respond to environmental stimuli (such as touch, light, or humidity) by varying internal turgor [ 1 , 2 ]. It causes dynamic deformations due to the differences in local swelling behaviors, which are determined by anisotropic tissue composition and directional orientation of micro- and nanostructures within cell walls. Essentially, these deformations arise from the typical out-of-plane and in-plane gradient compositions or structures, or a combination of both, which amplify internal stresses under external stimuli [ 1 , 3 – 5 ]. So far, scientists and engineers have been dedicated to the research of man-made, nonliving materials mimicking the behaviors that nature has perfected over billions of years. Inspired by nature, efforts have been made on the exploration of various shape-morphing materials in the past decades, such as shape memory polymers, liquid crystal elastomers, and hydrogels [ 3 , 6 – 12 ]. Among these, hydrogels represent one of the most promising candidates. Hydrogels are a class of three-dimensional (3D) networks formed by hydrophilic polymer chains embedded in a water-abundant environment, which can swell and shrink in response to certain stimuli, for example, light, pH, temperature, biochemical processes, and electric and magnetic fields. With the abilities to change their volumes sizably and reversibly, together with structures and functionalities comparable to biological systems, hydrogels favor competent applications in traumatic injuries, tissue engineering, and biosensors [ 13 – 17 ]. In recent years, various pathways for preparing shape-morphing hydrogels to mimic nature dynamic architectures have also been developed, which vastly broadens the application fields of hydrogels, including reconfigurable electronics, actuators, and soft robotics [ 18 – 22 ]. Their shape-morphing abilities are generally governed by nonuniform internal stresses led by uneven swelling/shrinking of different parts within a hydrogel sample. Therefore, a differentiated design at the molecular level (e.g., different swelling/shrinking properties design) and microscale (e.g., bilayer or patterned structure design) is necessary for designated deformations of the hydrogels. Conventionally, the shape-morphing hydrogels are prepared with different components across the hydrogel thickness (out-of-plane), for example, a bilayer design, which are prepared by combining two different layers with different swelling/shrinking rates or degrees [ 21 , 23 ]. Recently, hydrogels with differential distributive components in-plane are also prepared via different approaches, for example, ionoprinting techniques, photopatterning techniques, and doped oriented fibers, which show in-plane differential responsiveness [ 3 , 5 , 10 , 11 , 19 , 24 – 27 ]. However, none of these approaches employ a single and sustainable material which can transform controllably with the original 3D shape inside-out, nor do they obtain various reversible complex 3D shape-morphing hydrogels triggered by near-physiological stimuli. Here, we demonstrate an intriguing strategy of combining the out-of-plane stress and in-plane stress for preparing 3D periodically patterned single-component polysaccharide (sodium alginate, SA) hydrogel sheets cross-linked with Ca 2+ ions, which can precisely deform into designated shapes, as triggered by biocompatible ions (Na + /Ca 2+ ). Due to being differentially cross-linked with Ca 2+ ions, these hydrogels possess cross-linking density gradients both across the thickness (out-of-plane) and at the bottom surface (in-plane) via heterogeneous design by replicating microchannels at the bottom surfaces of the hydrogel sheets. Upon swelling or shrinking, the differential volume and out-of-plane stresses across the thickness cause bending deformations, while in-plane heterogeneity also leads to modulated internal stresses, resulting in controllable 3D deformations in water or calcium chloride (CaCl 2 ) or sodium chloride (NaCl) solutions. Due to the cooperative effects, the deformation can be facilely programmed by changing the microchannel orientations. Therefore, tube-curling, twisting, and rolling deformations can easily be customized. By releasing part of the cross-linker Ca 2+ ions with Na + ions, the 3D hydrogel sheets can alter their shapes from 3D to 2D, even to complete inside-out 3D structures. Furthermore, various cooperative deformations and complex configurations can be obtained by combining differently oriented microchannels into one side of the hydrogel sheet, for example, “T”- or “H”-shape tubular structures, double helix and torsional helix structures, and various plant-inspired architectures. With an understanding on the basic design rules and robust strategies for cooperative deformations, a broad range of responsive materials can be employed and miniaturized to micrometer scales for more advanced and potential applications in tissue engineering, biomedical devices, and soft robotics fields.",
"discussion": "3. Discussion Based on the hydrogel shape-morphing behaviors with different microchannel alignments demonstrated in the previous examples, our model provides a simple strategy for the design of predictable, controllable, and reversible 3D transformation of 2D materials. More importantly, the results arouse inspirations for the design and application of shape-morphing materials to meet specific targets and standards. As an unprecedented attempt, we demonstrate the possibility of enabling controllable and precise deformation in a desirable manner using a single component of a natural polysaccharide with convenient and nontoxic ions stimuli (Na + /Ca 2+ ). Simply by varying the concentration of Na + or Ca 2+ ions, the fabricated hydrogels are able to transform spontaneously between the shapes of a complex 3D structure and 2D planar architecture. The good agreement among the dynamic 3D shape morphing, morphological gradient, Young's modulus variation, and change of Na + /Ca 2+ in hydrogels verifies the hypothesis that ionic cross-links with Ca 2+ can be released by Na + ions of certain concentration and thus cause secondary transformation with good reversibility. Our ion-triggered shape-morphing strategy relies on a combination of out-of-plane and in-plane stresses resulting from the cross-linking density gradients across the thickness and at the bottom surface of the hydrogel during the swelling or shrinking process. This strategy could be a platform technology which is applicable to not only the demonstrated hydrogels but also a broad range of polymers (for example, UV-polymerized materials, other ionic-cross-linked hydrogels). Through the control of deformation parameters, which are as simple as pattern width, pre-cross-linking time, hydrogel sheet thickness, microchannel orientation, ionic concentration, and ion-triggering time, we can create various architectures and demonstrate programmable deformations comparable to the flowering process by immersion in certain ionic solutions. Due to the employed single-component material, our system can be extended to a multicomposite or multifunction system for fabricating various architectures with specific properties or functions via introducing other components or sensing functionalities (for example, temperature sensing, photo sensing, and magnetic sensing) into this system [ 9 , 19 , 32 ]. Owing to our biocompatible and sustainable hydrogels together with the triggering method of near-physiological stimuli, our study opens new avenues for creating desirable shape-morphing architectures for tissue engineering, biomedical devices, soft robotics, and beyond."
} | 2,291 |
35557857 | PMC9085624 | pmc | 7,507 | {
"abstract": "Biogas produced from anaerobic digestion consists of 55–65% methane and 35–45% carbon dioxide, with an additional 1–2% of other impurities. To utilize biogas as renewable energy, a process called biogas upgrading is required. Biogas upgrading is the separation of methane from carbon dioxide and other impurities, and is performed to increase CH 4 content to more than 95%, allowing heat to be secured at the natural gas level. The profitability of existing biogas technologies strongly depends on operation and maintenance costs. Conventional biogas upgrading technologies have many issues, such as unstable high-purity methane generation and high energy consumption. However, hydrogenotrophs-based biological biogas upgrading offers an advantage of converting CO 2 in biogas directly into CH 4 without additional processes. Thus, biological upgrading through applying hydrogenotrophic methanogens for the biological conversion of CO 2 and H 2 to CH 4 receives growing attention due to its simplicity and high technological potential. This review analyzes the recent advance of hydrogenotrophs-based biomethanation processes, addressing their potential impact on public acceptance of biogas plants for the promotion of biogas production.",
"conclusion": "5 Conclusion Recently, the biogas conversion to a high-quality biomethane has been a strategic target in many countries. Although physical/chemical upgrading methods are at a high level of technological readiness, their wide application is limited. Biological upgrading via the HBM process is a new technology that creates new prospects for integrating different forms of renewable energy, including upgrading advances in energy storage and decoupling bioenergy production from biomass availability. As far as the physical/chemical upgrade process is concerned, refining and upgrading processes in biogas production account for 60–70% of the total costs. As such, stabilizing the process for a long time and solving issues (e.g., methane concentration and efficacy of impurity removal) are essential. Further technological development is necessary to solve issues such as CH 4 loss, environmental impact, maintenance costs, energy consumption in the separation process, CO 2 separation conditions for solidification, and optimization to maintain appropriate partial pressure. Recent research has been directed towards biogas upgrading using the HBM process. Upgrading via the HBM process is considered to be a low-cost, highly efficient way to upgrade biogas, and because CH 4 content has the potential to reach up to 95% concentration through this process, it is possible to reduce CH 4 purification costs by replacing existing technologies with biological biogas upgrading. The method, which uses HMs, consumes CO 2 and H 2 from the AD process and from outsourcing. As such, it consumes relatively little energy and has low costs. However, an issue with an inefficient conversion rate of the gas to liquid during the H 2 injection should be addressed. As long as the hydrogen economy is revitalized in the future and the H 2 supply is stabilized through water electrolysis using renewable energy, the application of biogas upgrading via HBM process to field plants will be possible. With the HBM process, it is possible to create a sustainable energy source and promote biogas plants development. Despite the long history and high potential, in many regions the biogas market is undeveloped. Thus, the growing concern about renewable energy is a great opportunity to promote biogas production by biological biogas upgrading applications and to develop the green energy sector.",
"introduction": "1 Introduction Over the last 2 decades, the bioenergy sector has received increasing attention, especially in the usage and production of biogas. The number of facilities producing biogas via anaerobic digestion (AD) processes has increased steadily. Germany is a leader in terms of biogas plants. Currently, about 9,000 farm-scale digesters are operating in the country ( Vasco-Correa et al., 2018 ). In the US (U.S. EPA, 2017 & 2018), there are a total of 209 anaerobic digesters fed with food-waste and 1,250 anaerobic digesters fed with wastewater sludge. In 2017, Australia had 242 biogas plants, half of which were on landfill sites ( Carlu et al., 2019 ). In Denmark, 150 biogas-producing plants were operating in 2015 ( EBA, 2015 ). According to Kalyuzhnyi (2008) , there were around 100 anaerobic digesters in Russia in 2008. From 2012 to 2020, the number of biogas plants in the Republic of Korea increased from 49 to 110 ( Kim et al., 2012 ; Korean Ministry of Environment, 2020 ). In China, the amount of wastes treated by the AD process increased from 21,600 tons per day in 2015 to 36,400 tons per day in 2020 ( Khalid et al., 2020 ). Nonetheless, actual biogas production is only about 6% of the potential for China (35 Mtoe vs. 570 Mtoe), according to the International Energy Agency (IEA) (2018). In India, approximately five million small-size family biogas plants have been installed, but only 56 biogas-powered plants are operating ( Mittal et al., 2018 ). It appears that the biogas production and usage has a great potential for development and application. Although the number of biogas plants has increased, the produced biogas has been limitedly utilized to produce electricity or heat for homes or towns in the vicinity. It is mainly because the amount of biogas produced by a plant is not large enough to supply to industrial plants and the biogas is not pure enough to directly supply to a gas grid or automobiles without further purification. Therefore, biogas upgrading to biomethane, i.e., biogas mainly consisting of methane, has recently received particular attention from biogas producers. The composition of biogas produced during AD is around 55–65% methane and 35–45% carbon dioxide, similar to landfill gas ( Oslaj et al., 2010 ; Nasir et al., 2012 ; Ounnar et al., 2012 ). To meet the requirements to be used as biofuel (e.g., for gas-powered vehicles), biogas must be purified to increase the methane gas content ( ISO 13686:1998(en) Natural gas—Quality designation, 1998 ). Thus, biomethane is supplied to natural gas facilities and used directly as a raw material for energy production and the chemical industry. Biogas upgrading aims to remove or separate the carbon dioxide and other impurities from the biogas to achieve a methane content of up to 95%, thereby securing heat at the natural gas level and further utilization as a fuel ( Sun et al., 2015 ). One of the purposes of biogas upgrading is to make biogas a stable energy source and an alternative to fossil fuels ( Lecker et al., 2017 ). Additionally, the upgraded biogas can be injected directly into existing gas pipelines with no extra processes required. However, issues such as unstable production of high-purity methane gas, high operation costs, large facility size, and high energy consumption during the upgrading process are still a challenge in biogas upgrading that must be resolved ( Ahern et al., 2015 ; Adnan et al., 2019 ). The application of conventional biogas upgrading includes many scrubber processes that utilize water or amine as an absorbent or use pressure swing adsorption and membrane separation ( Angelidaki et al., 2018 ; Struk et al., 2020 ; Nguyen et al., 2021 ). Although the membrane-based upgrading process has high energy efficiency and is easy to operate and maintain, additional capital investment is required for the installation of compressors, membrane modules, heat exchangers, and off-gas treatment devices ( Angelidaki et al., 2018 ; Nguyen et al., 2021 ). Furthermore, a large amount of energy is required to achieve a high level of purity of methane, which is the issue to maintain operating costs in an acceptable range ( Angelidaki et al., 2018 ; Nguyen et al., 2021 ). In addition, physical condensation and chemical adsorption or absorption methods are applied mostly to remove moisture, H 2 S, ammonia, and other trace elements. To remove CO 2 from biogas, additional technologies (e.g., chemical absorption, water scrubbing, cryogenic separation, membrane separation, or pressure separation) are necessary ( Ryckebosch et al., 2011 ; Muñoz et al., 2015 ; Awe et al., 2017 ). The use of physical and chemical methods has many disadvantages, including, but not limited to, high energy consumption, difficult operation, CH 4 loss during purification, and a high cost of investment and operation ( Awe et al., 2017 ). Compared to those technologies, biological upgrading technologies overcome these problems ( Khan et al., 2021 ). With specific microorganisms known as hydrogenotrophic methanogens, conversion of CO 2 into CH 4 is possible, allowing an increase in CH 4 content of up to 95% and meeting natural gas standards ( ISO 13686:1998(en) Natural gas—Quality designation, 1998 ). Recent research has demonstrated that hydrogenotrophs-based biological methanation (HBM) could be a promising technology for biogas upgrading ( Singhal et al., 2017 ; Adnan et al., 2019 ). In fact, HBM has been demonstrated to be the most effective way of converting excess electricity into natural gas to avoid energy losses ( Lecker et al., 2017 ). Based on the findings, Luo and Angelidaki (2012) proposed excessive hydrogen utilization via biological biogas upgrading. The study by Adnan et al. (2019) has reviewed different biogas upgrading techniques and found HBM as a good potential for sustainability, cost-effectiveness, and environmental impact, although the development of biological upgrading is still in its early stage. However, due to its novelty, there are just a few case studies concerning biological methane upgrading in large-scale systems ( IEA Bioenergy, 2018 ; Jensen et al., 2018 ; Lebranchu et al., 2019 ). Additionally, since HBM is a developing technology, there are only a few studies focusing on review of the biological upgrading processes ( Lecker et al., 2017 ; Zabranska and Pokorna, 2018 ; Voelklein et al., 2019 ; Fu et al., 2020 ). This review examines biogas upgrading systems utilizing hydrogenotrophic methanogens. For the first time, this review explores the microbial pathways of hydrogenotrophic methanogens involved in the biogas upgrading to biomethane. The pros and cons of the different biogas-upgrading system configurations are analyzed, along with methods to improve H 2 transfer and the operational conditions. Perspectives for the improvement of public acceptance of biogas production are discussed, and directions for future research are suggested."
} | 2,652 |
34684986 | PMC8539025 | pmc | 7,508 | {
"abstract": "Dielectric materials with excellent thermally conductive and mechanical properties can enable disruptive performance enhancement in the areas of advanced electronics and high-power devices. However, simultaneously achieving high thermal conductivity and mechanical strength for a single material remains a challenge. Herein, we report a new strategy for preparing mechanically strong and thermally conductive composite films by combining aramid nanofibers (ANFs) with graphene oxide (GO) and edge-hydroxylated boron nitride nanosheet (BNNS-OH) via a vacuum-assisted filtration and hot-pressing technique. The obtained ANF/GO/BNNS film exhibits an ultrahigh in-plane thermal conductivity of 33.4 Wm −1 K −1 at the loading of 10 wt.% GO and 50 wt.% BNNS-OH, which is 2080% higher than that of pure ANF film. The exceptional thermal conductivity results from the biomimetic nacreous “brick-and-mortar” layered structure of the composite film, in which favorable contacting and overlapping between the BNNS-OH and GO is generated, resulting in tightly packed thermal conduction networks. In addition, an outstanding tensile strength of 93.3 MPa is achieved for the composite film, owing to the special biomimetic nacreous structure as well as the strong π−π interactions and extensive hydrogen bonding between the GO and ANFs framework. Meanwhile, the obtained composite film displays excellent thermostability ( T d = 555 °C, T g > 400 °C) and electrical insulation (4.2 × 10 14 Ω·cm). We believe that these findings shed some light on the design and fabrication of multifunctional materials for thermal management applications.",
"conclusion": "4. Conclusions In summary, this work demonstrates the fabrication of ultrahigh thermally conductive and mechanically strong ANF/GO/BNNS composite films with a “brick-and-mortar” structure for high-performance thermal management materials via the vacuum-assisted filtration followed by a hot-pressing approach. The microstructures, thermal conductivity, mechanical properties, electrical insulation, and thermal stability of the nacre-like composite films are investigated in detail. The ANF/GO/BNNS composite film with GO content of 10 wt.% and BNNS-OH content of 50 wt.% shows outstanding mechanical properties with a tensile strength of 93.3 MPa, benefiting from the high-performance ANF substrate, the π−π interactions, and extensive hydrogen-bonding interaction, as well as the “brick-and-mortar” structure. Meanwhile, the ANF/GO-10/BNNS-50 composite film exhibits an exceptional thermal conductivity of 33.4 Wm −1 K −1 due to highly effective thermally conductive networks are constructed by the addition of GO sheets with high aspect ratio and high contents of BNNS-OH, and the good interface compatibility between ANFs, GO, BNNS-OH further reduces interface thermal resistance. Furthermore, high electrical insulation and remarkable thermal stability are simultaneously achieved for the ANF/GO/BNNS. The results demonstrate that ANF/GO/BNNS composite film with superior thermal management performance has great potential for application in modern integrated electronics and high-power electrical devices. More importantly, the combination of excellent mechanical, insulating, and thermally conductive properties for ANFs composite films open up opportunities to design advanced insulation system for generators, motors, transformers, and wide bandgap semiconductors.",
"introduction": "1. Introduction With the rapid development of advanced electronics to higher voltages, higher frequency, and higher temperature, efficient heat dissipation of devices has become a great challenge [ 1 , 2 , 3 , 4 , 5 ]. Advanced thermal management materials (TMMs) with high thermal conductivity and excellent mechanical properties offer significant promise in alleviating the issue of heat concentration. Polymeric TMMs have attracted tremendous attention, owing to their unique characteristics of easy processing, lightweight, and excellent flexibility [ 6 , 7 ]. However, the intrinsically low thermal conductivity and heat-resistance temperature of most of the polymers restricts their further applications. Recently, aramid nanofibers (ANFs), as a novel one-dimensional (1D) nanoscale building block formed by interacting with each other via strong and highly aligned hydrogen-bonded networks of poly(p-phenylene terephthalamide) (PPTA) chains [ 8 ], have exhibited a great potential in the fabrication of multifunctional materials due to their nanoscale morphology, high aspect ratio, excellent mechanical strength, and thermostability [ 9 , 10 , 11 , 12 ]. Nevertheless, ANF-based composite films exhibit poor heat-conducting characteristics [ 11 ]. Incorporating thermally conductive fillers (such as carbon nanotubes [ 13 ], graphene [ 14 ], silver particles and nanowires [ 15 ], aluminum oxide [ 16 ], aluminum nitride [ 17 ], silicon carbide [ 18 ], boron nitride [ 19 , 20 ], etc.) into the ANF matrix has been demonstrated to be an effective method to improve the thermal conductivity of the composite films. Zhang and coworkers reported that with a core-sheath graphene fiber wrapped by ANF, an ultimate tensile stress of 380 MPa was achieved for the hybrid fiber. Unfortunately, the high electric conductivity still prevents its further application in integrated circuits and high power devices [ 21 ]. Therefore, it is necessary to find thermally conductive yet electric insulating fillers that can effectively establish heat transport channels as well as act as electric barriers in the composites. Boron nitride nanosheet (BNNS), as a structural analog of graphene (also called “white graphene” [ 22 ]), exhibits inherent high thermal conductivity (~2000 Wm −1 K −1 ) [ 23 ], wide band gap (~5.9 eV) [ 24 ], low dielectric constant (~3.9), high thermal stability [ 25 ], and large aspect ratio, and has been proved to be a good choice to set up a thermally conductive path in composites [ 26 , 27 ]. For instance, Xiao et al. prepared the ANF/boron nitride composite films with ultrahigh thermal conductivity of 122.5 Wm −1 K −1 . However, the mechanical properties of the composite films decreased significantly to ~30 MPa, owing to the poor stress transfer between ANF framework and thick BN platelets [ 20 ]. Natural nacre, a binary composite system that contains 95 vol% two-dimensional (2D) inorganic platelets and 5 vol% organic polymers, evolves into a well-ordered ‘‘brick-and-mortar’’ architecture to provide extraordinary mechanical properties [ 28 , 29 ]. A nacre-like ANFs/montmorillonite nanocomposite film with layered microstructure was successfully constructed by Si et al. via simple vacuum-assisted filtration, and the “brick-and-mortar” structure of 2D platelets and polymer contributes to the excellent mechanical properties of composite film [ 30 ]. Lei et al. reported an ultrathin, highly robust, super-flexible, and thermostable composite film via engineering ANFs with Ti 3 C 2 T x (MXene) into a hierarchical 2D/1D brick-and-mortar architecture, and achieved an unprecedented tensile strength (300.5 MPa) at 40 wt.% MXene loading [ 31 ]. In addition, although the heat conduction network of the polymer matrix can be well constructed while fillers form a random close-packed structure, the high fillers loading will generally deteriorate the superior mechanical performance of a polymer matrix [ 32 ]. To address this issue, a solution for the combined use of hybrid fillers is proposed [ 33 , 34 , 35 , 36 , 37 ]. Zhao et al. reported a new strategy to synergistically enhance the thermal conductivity of epoxy composites with 2D BNNS and 0D boron nitride microspheres (BNMSs). The result shows that the thermal conductivity of BNNSs/BNMSs/epoxy composite (1.148 Wm −1 K −1 ) with a filler loading of 30 wt.% is approximately 28.0 and 51.5% higher than that of BNNSs/epoxy and BNMSs/epoxy composites, respectively [ 38 ]. Jiang et al. reported that the thermal conductivity of the polystyrene (PS) composites reached a maximum and exhibited the highest thermal conductivity enhancement up to 20% while the mass ratio of graphene oxide/hydroxylated boron nitride (GO/BN-OH) was 7:3. This demonstrated that the thermal conductivity of the PS composites could demonstrate significantly improved benefit from the synergistic effect of GO and BN-OH [ 39 ]. Graphene possesses ultrahigh thermal conductivity and a large aspect ratio, which is the best choice for the fabrication of thermally conductive composites [ 40 , 41 , 42 ]. However, the high electrical conductivity of graphene restricts the application of TMMs. GO sheets, as inorganic heat-dissipating filler are as important as graphene; it is found that the oxygen-containing groups on the surface of GO not only substantially enlarged the interlayer spacing of GO sheets, but effectively improve the dispersibility in the polymer matrix [ 43 , 44 ]. Most importantly, the oxygen-containing groups are not conducive to the conduction of carriers. Wang et al. fabricated composite films by blending GO sheets in ANFs, and enhanced the mechanical stability of composite films through the π–π stacking interactions between the ANFs and GO sheets in this system [ 45 ]. Note that excessive GO sheets may greatly reduce the reliability of polymer composites as TMMs due to their inherent electrical conductivity [ 46 ]. In this study, the biomimetic nacreous aramid nanofiber-based composite films with outstanding mechanical properties and high thermal conductivity were fabricated by employing GO sheets and edge-hydroxylated BNNS (BNNS-OH). Special “brick-and-mortar” structures, as well as strong hydrogen-bonding, are generated between the functional groups of the GO, hydroxyl group of BNNS-OH, and the amide group of ANFs, which plays a significant role in improving the mechanical properties of ANF/GO/BNNS composite films. In addition, tightly packed thermal conduction networks are established in the biomimetic nacreous layered structure, contributing to high thermal conductivity of the composite films. Meanwhile, the low content of GO in the composite film remains low electron transport efficiency, resulting in high electrical insulating properties of composite films.",
"discussion": "3. Results and Discussions The macroscopic Kevlar fibers ( Figure 2 a) were approximately 11 μm in diameter, and a smooth surface lead to a poor interfacial adhesion, as shown in Figure 2 b. The deterioration of composite properties is always related to the weak interfacial strength [ 9 ], therefore, it is particularly critical to improve the chemical inertness of the Kevlar fibers. A previous report has shown that Kevlar fibers that are exposed to a potassium hydroxide/dimethyl sulfoxide (KOH/DMSO) system abstracts the mobile protons from amide groups to generate the negatively charged nitrogen ions [ 47 ]. The electrostatic repulsion and the destroyed hydrogen bonding interactions between the polymer chains facilitate the transformation from Kevlar fibers to numerous ANFs. Meanwhile, physical tangles and π–π stacking in the polymer backbone hinder the further dissociation of ANFs into polymer chains [ 48 ]. Figure 2 c shows the preparation of ANFs dissolved in DMSO, obtained a dark red, highly stable, and homogeneous ANFs/DMSO solution. The synthesized ANFs are ~50 nm in diameter and several micrometers in length, exhibiting a network-like structure ( Figure 2 d). The inset of Figure 2 d shows the obtained ANFs/DMSO dispersion presented a strong Tyndall effect, indicating its colloidal characteristic and good dispersibility. The GO exhibits a large surface and curly sheet with smooth surface morphology according to the results of SEM ( Figure 2 e). Meanwhile, the TEM image of GO ( Figure 2 f) also displays a single layer structure and slight wrinkles, indicating that the GO could be well utilized as an excellent support material with a large specific surface area [ 49 ]. XPS analysis was performed to characterize the chemical structure of GO. Figure 2 g presents the XPS spectra of GO. The GO shows distinct peaks for C1s at 286.4 eV and O1s at 532.1 eV. The atomic fractions of carbon and oxygen are 70.8% and 29.2%, respectively [ 50 ]. For a detailed investigation, The C 1s spectrum of GO (inset of Figure 2 g) exhibits the characteristic peaks of C−C at 284.6 eV, C−O at 286.7 eV, and C=O at 287.5 eV corresponding to the hydroxyl and carboxyl groups. In Figure 2 h, BNNS-OH remains with an intact crystalline structure and is highly electron transparent in TEM observations, indicating the prepared BNNS-OH possesses negligible defects and ultrathin nature after exfoliation and functionalization. The few-layer structures of BNNS-OH can also be clearly observed in the AFM image of BNNS-OH ( Figure 2 i), BNNS-OH with a lateral size of ~0.5 μm and an ultrathin thickness of ~1 nm is observed. It proves that the exfoliated BNNS-OH is composed of ~3 layers because an isolated BNNS is approximately 0.4–0.5 nm [ 7 , 51 ]. The decreased thickness and crystalline structures of BNNS-OH can be further confirmed from the X-ray diffraction (XRD) patterns analysis ( Figure 2 j). In comparison to h-BN, the typical (002) diffraction peak of BNNS-OH exhibits a tiny angle shift from 26.72° to 26.63°, suggesting the increased interplanar distance of BNNS-OH and the hexagonal lattices of the BNNS-OH are not damaged during the exfoliation and functionalization processes. In addition, the visible lower intensity and broader width of the (002) diffraction peaks of BNNS-OH than those of h-BN are observed, which further indicates the thickness of the BNNS-OH decreases [ 38 ]. The thinner thickness and well-retained crystalline structure of BNNS-OH are favorable for enhancing interfacial phonon coupling in composite films. The XPS profile of h-BN shows two strong boron and nitrogen peaks at ~190.1 and 398.1 eV, along with a small oxygen peak at ~532.1 eV. After exfoliation and functionalization, the intensity of the oxygen peak increased (from 1.10% for h-BN to 1.82% for BNNS-OH), indicating the formation of surface hydroxyl groups, which roughly corresponds to one hydroxyl group for every 67 B-N atoms ( Figure 2 k) [ 52 ]. Figure 2 l demonstrates the TGA curves of h-BN and BNNS-OH. The weight loss of BNNS-OH increases with the increase in temperature and exhibits a weight loss of 8.1% at 600 °C, mainly due to the decomposition of the hydroxyl group grafted on the edge of BNNS. Besides, a slight loss of BNNS-OH was observed at temperatures below 150 °C, the loss originated from molecular water adsorption on the BNNS-OH surface [ 51 ]. In conclusion, the above characterizations and analysis confirm the successful fabrication of BNNS-OH with thin thickness and well-retained crystalline structure. The ANF/GO/BNNS composite films were fabricated by vacuum-assisted filtration and hot-pressing methods to form a dense film. Figure 3 a,b shows the cross-section morphologies; it is clearly observed that numerous ANFs are attached to the surface of these GO sheets and the surface of BNNS-OH is relatively smooth. This is because abundant oxygen-containing groups exist on the surface of GO to form strong hydrogen bonds with ANFs, and π−π interactions exist between the GO’s graphitic basal plane and the ANFs’ polymer backbone [ 53 , 54 ]. By contrast, the prepared BNNS-OH possess fewer hydroxyl groups, and the hydrogen bond between the ANFs and BNNS-OH is relatively weak. The interaction between ANFs, GO, and BNNS-OH is demonstrated in Figure 3 c. Fourier transform infrared (FTIR) spectra was carried out to demonstrate these strong interfacial interactions among ANFs, GO, and BNNS-OH ( Figure 3 d,e). As can be seen, the FTIR spectrum of ANF film presents the band at 1640 cm −1 corresponding to the C=O stretching vibrations, the band at 1610 cm −1 corresponding to the stretching vibrations of aromatic ring, and the band at 3315 cm −1 corresponding to the N-H stretching vibrations [ 48 ]. The formation of new hydrogen bonds could be confirmed by the blue shift of C=O stretching vibrations to 1644 and 1643 cm −1 for the ANF/GO-5/BNNS and ANF/GO-10/BNNS composite films, respectively. Besides, the blue shift of N-H stretching vibrations to 3317 cm −1 for the ANF/GO-5/BNNS also indicates the formation of new hydrogen bonds between ANFs, GO sheets, and BNNS-OH. It is found that the strongest peak around 1610 cm −1 (the stretching vibrations of the aromatic ring of ANFs) underwent a gradual redshift upon the addition of more GO sheets. Such a result can be direct evidence for the existence of π–π interactions between ANFs and GO sheets [ 54 , 55 ]. The crystal structures are shown in X-ray diffraction (XRD) patterns; Figure 3 f confirms the presence of among ANFs, GO, and BNNS-OH in the ANF/GO/BNNS composite films. The ANF film exhibited a strong peak at around 20.3° (d = 0.44 nm), assigned to a crystal plane of (110) [ 53 ]. The XRD patterns of the ANF/GO/BNNS composite films exhibited diffraction peaks of ANFs (~20.3°), GO (~26.8°), and BNNS-OH (~26.8°, ~42.9°, and ~55.2°). Although it is difficult to interpret because the diffraction peaks at ~26.8° are similar to that of both the GO sheets and the BNNS-OH, BNNS-OH also exhibits other diffraction peaks at ~42.9° and 55.2°, corresponding to the (100) and (101) crystal planes, respectively. Compared to ANF/GO-5/BNNS, the intensity of the diffraction peaks at ~26.8° of ANF/GO-10/BNNS tends to become stronger with the increasing of GO loading, which confirms the good crystal structure of GO sheets [ 24 ]. Figure 4 a–c displays the SEM images for the cross-sectional morphologies of ANF film, ANF/GO-5/BNNS-10, and ANF/GO-10/BNNS-50 composite films. All the films exhibit a well-ordered layered structure, and the good dispersion of BNNS-OH and GO sheets in ANF/GO-5/BNNS-10 composite film. For ANF/GO-10/BNNS-50 composite film, with increasing content of GO sheets and BNNS-OH, the contact area between the high thermal conductivity fillers increases. In addition, the BNNS-OH and GO sheets are well distributed in the composite film, as can be confirmed from the energy dispersive X-ray mapping of elements B, C, N, and O in ANF/GO-10/BNNS-50 ( Figure 4 d). Moreover, the ANFs, GO sheets, and BNNS-OH are orderly arranged in the horizontal direction in the SEM images of ANF/GO/BNNS composite film, which is similar to the “brick-and-mortar” structure of the natural nacre. It is well observed that BNNS-OH nanosheets and GO sheets, which are regarded as the “brick” in the nacre-like structure, are integrated appropriately at the interfaces with the “mortar” (ANFs) ( Figure 4 e) and the “brick-and-mortar” layered structure always displays an excellent mechanical property [ 56 ]. As shown in Figure 4 f, the ANF/GO/BNNS composite film can endure the bending, stretching of heavy weight (500 g), as well as complex folding without any breakages. The typical stress–strain curves of ANF/BNNS composite films are shown in Figure S1 . It can be observed that the tensile strength of ANF/BNNS composite films decreases significantly with the increase of BNNS contents. In addition, at the same filler contents, the tensile strength of ANF/GO composite film is much higher than those of ANF/BNNS composite film ( Figure S2 ). Therefore, the GO was utilized to further enhance the thermal conductivity and mechanical properties of ANF/BNNS composite film. The mechanical properties of ANF/GO-5/BNNS and ANF/GO-10/BNNS composite films with different contents of BNNS-OH were examined by tensile testing as shown in Figure 4 g,h, respectively. Meanwhile, combining tensile strength, elongation at break of ANF/GO/BNNS composite films are displayed ( Figure 4 i,j). It can be easily observed that the mechanical properties of ANF/GO-5/BNNS are stronger than that of ANF/GO-10/BNNS because of the stronger hydrogen bond formed between GO sheets and ANFs, while the addition of 5 wt.% GO sheets in composite films and the conclusion is demonstrated in the FTIR of ANF/GO/BNNS. The tensile strength and elongation at break of the ANF/GO-5/BNNS-10 composite films were 259.4 MPa and 14.8%, which is 48.4% and 151% higher than ANF film’s tensile strength and elongation at break of 174.8 MPa and 5.9%, respectively. The enhanced mechanical properties of the ANF/GO-5/BNNS-10 composite films are mainly ascribed to the extensive hydrogen bonding and π−π interactions between the ANFs and the GO sheets, and a tightly stacked, orderly multilayered nacre-like structure among ANFs, GO sheets, and BNNS-OH sheets [ 31 , 53 ]. For the ANF/GO/BNNS with a certain amount of GO sheets, the mechanical properties of ANF/GO/BNNS decrease with an increasing amount of BNNS-OH to some degree. The reason is that the fewer hydroxyl groups grafted on the edge of BNNS-OH, and the hydrogen bond formed between BNNS-OH and ANFs is weaker. In addition, the excessive introduction of BNNS-OH will cause insufficient “mortar” between the connecting “bricks”, which introduces structural defects and stress concentration points to the composite film [ 57 ]. Figure 5 a shows the schematic illustrating the potential thermal conduction mechanisms within the ANF film and ANF/GO/BNNS composite film. When heat is applied from one end of the ANF film and ANF/GO/BNNS composite film, the thermal conductivity of the ANF/GO/BNNS composite film is significantly improved because multiple thermal transport pathways are possible with GO/BNNS-OH and its oriented lamellae forming a continuous network structure as can see from Figure 4 c. Figure 5 b shows the in-plane thermal conductivities ( λ ) of the ANF/BNNS, ANF/GO-5/BNNS, and ANF/GO-10/BNNS thermally conductive composite films, respectively. The values of λ for the composite films were calculated from Equation (1) using the measurement results of C p , α , and ρ [ 27 ]: λ = C p × α × ρ (1) To further illustrate the effectiveness of improving the thermal conductivity, a parameter η was introduced, which is defined as follows [ 58 ]: η = ( λ c − λ m )/ λ m × 100% (2) \nwhere λ c and λ m represent the thermal conductivity of the composite films and pure ANF films, respectively. The η values are shown in Figure 5 c. As can be seen, with the increase of BNNS-OH loading, the λ of the ANF/GO/BNNS composite films show a dramatic increase and achieve an ultrahigh value of 33.4 Wm −1 K −1 for the ANF/GO-10/BNNS-50 composite film, which is 2080% higher than that of the ANF film (~1.55 Wm −1 K −1 ). For ANF/GO-10/BNNS-50 composite films, ANFs, GO sheets, and BNNS-OH tend to be oriented horizontally via vacuum-assisted filtration and hot-pressing, and the large GO sheets can intercalate the gap between BNNS-OH and bridge the separated BNNS-OH, contribute to the formation of the more effective thermal conductive networks. Besides, the strong hydrogen bonds interaction of BNNS-OH, GO sheets, and ANFs, as well as π–π conjugation interactions between ANFs and GO sheets facilitate the reduction of the thermal interface resistance in the ANF/GO/BNNS composite films. To visualize the mechanical and thermal conductivity properties together, we plot the tensile strength vs thermal conductivity of our results compared against other composite films collected from the literature ( Figure 5 d and Table 1 ). The plot shows that the ANF/GO/BNNS composite films here exhibit a good combination of mechanical properties and superior in-plane thermal conductivity performances as compared to most other composite films, highlighting its superiority in the development of high-performance TMMs. Figure 5 e displays the electrical resistivity of the ANF film, ANF/GO-5/BNNS, and ANF/GO-10/BNNS composite films as a function of BNNS-OH loading. The ANF film shows a high electrical resistivity of 7.8 × 10 14 Ω·cm, and exceeds the standard of electrical insulation (10 9 Ω·cm). The addition of GO sheets and BNNS-OH leads to a negligible decrease of electrical resistivity owing to the wide band-gap of BNNS-OH with ultrahigh electrical resistivity as an electron transmission barrier in the ANF/GO/BNNS composite film, and the contents of GO sheets are too low to form an effective electron channel. In addition, the thermal stabilities of the ANF/GO/BNNS composite films were verified by the TGA results ( Figure 5 f). As can be seen, the degradation rate decreased with an increase of BNNS-OH mass percent due to the high thermal stability of BNNS-OH. ANF film’s decomposition temperature of 10 wt.% weight loss ( T d ) was 530 °C, owing to the high thermal durability of the ANFs, the T d of ANF/GO-10/BNNS-30, and ANF/GO-10/BNNS-50 increases by 13 and 25 °C, respectively. The reason can be ascribed to the high thermal durability and high intrinsic heat capacity of the GO sheets and BNNS-OH, as well as the “tortuous path effect” caused by the “brick-and-mortar” structure. Meanwhile, DSC results also show thermal stabilities of ANF film and ANF/GO/BNNS composite films ( Figure 5 g). The glass transition temperatures of all the films are higher than 400 °C due to PPTA polymer chains with sufficient amide bonds and strong interaction between the ANFs, GO, and BNNS-OH, indicating an excellent potential for electronic applications at high temperature. To evaluate the cooling efficiency of this film in real operating conditions, the pure ANF film, ANF/GO-10/BNNS-10, and ANF/GO-10/BNNS-50 were used, respectively, for heat dissipation of high-power LED modules (3 W, see Figure 6 a) with an ambient temperature of 20 °C. Note that the lifetime of LED chip is closely related to the operating temperature, suggesting that every 10 °C rise of temperature can lead to a decrease by half in its lifetime [ 67 ]. As expected, a lower hotspot temperature is displayed in the ANF/GO-10/BNNS-50 composite films as heat spreaders with respect to that of the ANF film and ANF/GO-10/BNNS-10 composite film substrate, indicating that the higher thermal conductivity of ANF/GO-10/BNNS-50 composite film provides an effective heat transfer rate. Figure 6 b shows the corresponding temperature evolution of the ANF film and ANF/GO-10/BNNS composite films with 30 wt.% and 50 wt.% BNNS-OH loading, respectively. The ANF/GO-10/BNNS-50 composite film exhibits the lowest hotspot temperature, demonstrating the high efficiency of heat transfer. In short, the ANF/GO-10/BNNS-50 composite films with excellent mechanical properties, superior in-plane thermal conductivity performances, high electrical resistivity, and thermal durability would contribute to their applications in the thermal management of advanced electronics."
} | 6,653 |
24822064 | PMC4009226 | pmc | 7,509 | {
"abstract": "Carboxydothermus hydrogenoformans is a carboxydotrophic hydrogenogenic bacterium species that produces hydrogen molecule by utilizing carbon monoxide (CO) or pyruvate as a carbon source. To investigate the underlying biochemical mechanism of hydrogen production, an elementary mode analysis of acetyl-CoA pathway was performed to determine the intermediate fluxes by combining linear programming (LP) method available in CellNetAnalyzer software. We hypothesized that addition of enzymes necessary for carbon monoxide fixation and pyruvate dissimilation would enhance the theoretical yield of hydrogen. An in silico gene knockout of pyk , pykC , and mdh genes of modeled acetyl-CoA pathway allows the maximum theoretical hydrogen yield of 47.62 mmol/gCDW/h for 1 mole of carbon monoxide (CO) uptake. The obtained hydrogen yield is comparatively two times greater than the previous experimental data. Therefore, it could be concluded that this elementary flux mode analysis is a crucial way to achieve efficient hydrogen production through acetyl-CoA pathway and act as a model for strain improvement.",
"introduction": "1. Introduction \nUse of fossil fuels causes adverse effect on environment through pollution. Moreover, the availability of fuels such as oils and natural gases is limited and are likely to be depleted soon [ 1 ]. Therefore, it is indispensable to search for alternate fuel source and hydrogen is one of the efficient sources of energy that could effectively replace the available fossil fuels. It is also considered as fuel of the future, since it is eco-friendly and emits zero carbon. Besides its application as a fuel, hydrogen can also be used as a potential electron donor for various reactions in biotechnological and chemical industrial processes [ 2 ]. Hydrogen is conventionally produced from fossil fuels by steam reforming other industrial methods such as coal gasification and electrolysis [ 3 ]. However, these methods uses nonrenewable energy source to produce hydrogen. Therefore, biological hydrogen production by microorganisms especially by hydrogenogens is the most convenient one [ 4 , 5 ]. Over the past two decades, various researches are going on for enhanced biological hydrogen productivity [ 6 , 7 ] and improvement of such a product from organisms by optimizing their genetic process is commonly referred to as metabolic engineering [ 8 ]. The knowledge of reactions and selection of optimal enzymatic route between the substrate and product is an ultimate task in biological research. Computational based theoretical metabolic yield is a key criterion to study the substrate utilization and product formation of microorganisms [ 9 – 11 ]. Carboxydothermus hydrogenoformans Z-2901 is one of the most promising and potential acetogenic hydrogenogenic bacterium produces species which produces hydrogen by utilizing CO and pyruvate as a carbon source [ 12 ]. In hydrogenogenic microorganisms, the autotrophic fixation of CO and pyruvate dissimilation have been achieved through acetyl-CoA or Wood-Ljungdahl pathway and hydrogen molecule has been produced as one of the end product. The reactions involved in CO fixation are activated into acetyl group that contains metal ions. The CooX cluster of genes is the major component of this pathway that fixes CO and pyruvate dissimilation catalyzed by pdh gene during acetyl-CoA pathway, a key biochemical feature that supports hydrogen production [ 13 , 14 ]. Elementary flux mode (EFM) analysis is one of the powerful tools for metabolic pathway analysis. It allows us to calculate all possible steady-state flux distributions of the network, thereby determining the theoretical molar yield of products and studying their effects of any genetic modifications [ 15 – 17 ]. Such studies would help to design an organism for obtaining the efficient product formation through metabolic engineering. Recently, elementary mode analysis has been used to develop a rational model of methionine production from well-known organisms such as Escherichia coli and Corynebacterium glutamicum [ 18 ], and polyhydroxybutanoate production from Saccharomyces cerevisiae [ 19 – 21 ]. The experimental analysis of hydrogen production in wild type E. coli resulted in a flux distribution indicating a hydrogen production of 0.17 mol per mole of glucose consumption [ 22 ]. The predicted hydrogen production of E. coli through metabolic flux analysis by the deletion of ldh gene was 0.23 mol per mole of glucose consumed which is slightly higher than the wild type strain. In another case, computational flux analysis studies on hydrogen production in E. coli through the formate hydrogen lyase reaction have suggested that the level of hydrogen production matches experimental observations [ 23 ]. In this paper, elementary mode based flux analysis has been carried out for the newly modeled acetyl-CoA pathway of C. hydrogenoformans that comprises necessary reaction stoichiometry collected from KEGG database [ 24 ]. Theoretical capabilities of hydrogen yield limited by the utilization of CO and pyruvate and through in silico gene knockout have been studied using metabolic flux analysis tools and software. This elementary mode flux analysis also provides a basis to design a system that has specific phenotypes, metabolic network regulation, and robustness that facilitates the understanding of cell physiology and implementation of metabolic engineering strategies of C. hydrogenoformans to improve the hydrogen productivity.",
"discussion": "4. Discussion \n In C. hydrogenoformans, pyruvate is initially converted to acetyl-CoA and formate by pyruvate formate lyase (pfl) enzyme and formate are subsequently metabolized into hydrogen and carbon dioxide. In another case, CO can be directly fixed and converted into CO 2 and hydrogen through water gas shift reaction and this reaction is being catalyzed by CO dehydrogenase enzyme complex [ 45 ]. Our strategy for improving hydrogen production involved the modification of energy metabolism to direct the flow of major metabolites pyruvate and acetyl-CoA through elementary flux mode analysis. The biochemical reactions comprised in acetyl-CoA pathway are illustrated in Figure 1 and the functions of corresponding genes are summarized in Table 1 . This is the first flux analysis study reported on acetyl-CoA pathway and hydrogen production of C. hydrogenoformans . The gene knockouts of selected genes ( Table 2 ) obtained from elementary mode analysis were hypothesized to increase the pyruvate and CO influx rate, thereby increasing the flux rate of hydrogen production. The rate of pepc and pyc genes encoding phosphoenolpyruvate (PEP) carboxylase and pyruvate kinase was disrupted to increase the pyruvate concentration in cellular system for acetyl-CoA synthesis [ 39 , 46 ]. A previous metabolic engineering study by gene deletion on model microorganism Escherichia coli described that one mole of glucose has maximum hydrogen yields of approximately 14.9 mmols/mg dry cell mass [ 47 ]. Similarly, the overexpression studies on transcriptional regulatory genes, fhl and fnr genes of E. coli, resulted in the yield of 34 mmol of H 2 /mg of dry cell mass [ 48 ]. As a result of elementary mode flux analysis, we obtained a maximum theoretical flux rate of hydrogen yield of 47.62 mmol/gCDW/h for one mole of pyruvate consumption was comparatively comparatively higher than E. coli simulation. The elimination of fdh and pyk genes in E. coli strains also results in increase of pyruvate metabolism towards hydrogen [ 49 ]. Here, we suggested that gene knockout of pyk and mdh genes would increase the flux rate of hydrogen during pyruvate dissimilation of acetyl-CoA pathway in C. hydrogenoformans . Thus, the analysis of the elementary mode based fluxes showed that the hydrogen yield through acetyl-CoA pathway model proposed here was validated with the experimental data. As acetyl-CoA is one of the precursors of hydrogen formation and the yield depends on the rate of acetyl-CoA and other intermediate produced [ 50 ], it was keenly observed that pyk and mdh genes involved in both EMs 9 and 21 were obtained zero constraints, since their absence does not affect the carbon flux during acetyl-CoA pathway. This in silico elementary mode analysis and flux analysis of acetyl-CoA model indicated that the reactions available are feasible for the carbon flow from substrates pyruvate and CO to produce maximum amount of hydrogen. After flux optimization, EMs 21 and 9 (Figures 2(a) and 2(b) ) were predicted to be the efficient reaction sets for enhanced hydrogen productivity. As discussed above, to improve the hydrogen yield by C. hydrogenoformans , a gene knockout of mdh , pyk, and pykA genes during acetyl-CoA pathway would be a prior consideration. Gene knockout of pyk and pykA could redistribute the flux of pyruvate into acetyl-CoA synthesis for hydrogen production. It has been reported that knock-out of pyruvate kinase (pyk), pyruvate kinase type-II (pykA), and malate dehydrogenase (mdh) enzymes could increase both the growth rate and yield of hydrogen [ 11 , 39 , 50 ]. The knockout of enzyme pyruvate kinase controls the flux from PEP towards pyruvate, resulting in a relative difference in the rate of carbon flow toward oxaloacetate and other products such as formate and acetate [ 39 ]. Our results clearly showed that the disruption of pyruvate kinase enzyme activity maintains the steady-state flux through the combined reactions of oxaloacetate to pyruvate and pyruvate to phosphoenolpyruvate. The results presented in this work illustrate the fixation of CO, dissimilation of pyruvate, and formate related to acetyl-CoA biosynthesis, to achieve the maximum theoretical hydrogen yield. Thus, undercontrolled intake of pyruvate, metabolic perturbations, resulting from pyruvate kinase, and malate dehydrogenase gene knockout led to strongly increase the flux rate of hydrogen formation. proposed in silico gene knockout and flux analysis model in this paper will help to improve the strain through metabolic engineering for obtaining the enhanced hydrogen production phenotype."
} | 2,546 |
37250063 | PMC10213550 | pmc | 7,510 | {
"abstract": "The production and anaerobic oxidation of methane (AOM) by microorganisms is widespread in organic-rich deep subseafloor sediments. Yet, the organisms that carry out these processes remain largely unknown. Here we identify members of the methane-cycling microbial community in deep subsurface, hydrate-containing sediments of the Peru Trench by targeting functional genes of the alpha subunit of methyl coenzyme M reductase ( mcrA ). The mcrA profile reveals a distinct community zonation that partially matches the zonation of methane oxidizing and –producing activity inferred from sulfate and methane concentrations and carbon-isotopic compositions of methane and dissolved inorganic carbon (DIC). Mcr A appears absent from sulfate-rich sediments that are devoid of methane, but mcr A sequences belonging to putatively methane-oxidizing ANME-1a-b occur from the zone of methane oxidation to several meters into the methanogenesis zone. A sister group of ANME-1a-b, referred to as ANME-1d, and members of putatively aceticlastic Methanothrix (formerly Methanosaeta ) occur throughout the remaining methanogenesis zone. Analyses of 16S rRNA and mcr A-mRNA indicate that the methane-cycling community is alive throughout (rRNA to 230 mbsf) and active in at least parts of the sediment column (mRNA at 44 mbsf). Carbon-isotopic depletions of methane relative to DIC (−80 to −86‰) suggest mostly methane production by CO 2 reduction and thus seem at odds with the widespread detection of ANME-1 and Methanothrix . We explain this apparent contradiction based on recent insights into the metabolisms of both ANME-1 and Methanothricaceae , which indicate the potential for methanogenetic growth by CO 2 reduction in both groups.",
"conclusion": "Conclusion We provide the first complete community profile of active methane-cycling archaea in deep subseafloor sediments, and show based on DNA and RNA sequence data that anaerobic methane-cycling archaea are present throughout the SMTZ and methanogenesis zone of ODP Site 1230 in the Peru Trench. Of essential importance for the detection of mcr A, mcr A-mRNA, and 16S rRNA of methane-cycling archaea was the use of redesigned general mcrA primers and development of new group-specific mcrA and 16S rRNA gene primers. While these primers improved the detection sensitivity of methane-cycling archaea, they confirm the notion that methane-cycling archaea only account for a small fraction of deep subsurface microbial communities, even in AOM and methanogenesis zones ( Lever, 2013 ). Even though DNA- and RNA-based detections of methane-cycling archaea generally match the distributions of AOM and methanogenesis based on geochemical data, the detected phylogenetic groups appear at odds with the inferred dominant methane-cycling pathways. ANME-1, which are historically considered to be anaerobic methanotrophs, were detected to sediment depths that were > 10 m (ANME-1a-b) and > 100 m (ANME-1d) below the SMTZ. Based on published sedimentation rates for Site 1230 (0.25 mm yr. −1 ; Shipboard Scientific Party, 1988 ), these distances suggest the continued existence of ANME-1a-b and ANME-1d populations in methanogenic sediments for >40,000 and > 400,000 years after their burial below the SMTZ, respectively. Given the measured methane concentration and DIC-isotopic data, and that no other methane-cycling archaea were detected, a switch to methanogenesis by CO 2 reduction offers the most parsimonious explanation for the occurrence of ANME-1a-b far below the SMTZ. Similarly, methanogenesis by CO 2 reduction may sustain populations of ANME-1d in deeper layers, and also explain why members of Methanothrix – that were historically assumed to be aceticlastic - are pervasive throughout sediments that appear to be dominated by methanogenic CO 2 reduction. Herein, the pathway of CO 2 reduction remains unclear, but could bypass H 2 as an electron source through direct electron transfer.",
"introduction": "Introduction The detection of active microbial populations to 80 mbsf in Peru Margin sediments during Ocean Drilling Program (ODP) Leg 112 in 1988, was the first demonstration of an deep subseafloor biosphere ( Cragg et al., 1990 ). Since then, numerous studies and multiple lines of evidence from a range of locations have shown a vast microbial biomass in deep subseafloor sediments (for syntheses, see D’Hondt et al., 2004 ; Kallmeyer et al., 2012 ; Parkes et al., 2014 ) with metabolically active cells to at least 1,500 mbsf ( Roussel et al., 2008 ; Inagaki et al., 2015 ; Heuer et al., 2020 ), and the existence of a subsurface microbiome that is distinct from that found in marine surface sediments (e.g., Deng et al., 2020 ; Hoshino et al., 2020 ). Several sites sampled during ODP Leg 112 were revisited in 2002 during ODP Leg 201, now 22 years ago, during the first ocean drilling expedition to focus on subseafloor life ( D’Hondt et al., 2003 ). Porewater concentration gradients of microbially consumed electron acceptors such as nitrate or sulfate indicated active microbial populations to depths of >400 mbsf in the sediment column ( D’Hondt et al., 2004 ). Molecular biological studies, e.g., polymerase-chain-reaction (PCR) assays of 16S rRNA genes ( Parkes et al., 2005 ; Inagaki et al., 2006 ; Webster et al., 2006 ) and 16S rRNA gene transcripts ( Biddle et al., 2006 ; Sørensen and Teske, 2006 ), fluorescence- in-situ -hybridization (FISH; Mauclaire et al., 2005 , Schippers et al., 2005 ), and metagenomic signatures of whole-genome amplified DNA ( Biddle et al., 2008 ) provided insights into the community structure and metabolic potential of microbial populations. Yet, specific links between microbial activity based on geochemical gradients and microbial identity based on genetic and genomic assays could not be established. For instance, sulfate and methane profiles suggested that sulfate reduction, anaerobic oxidation of methane (AOM), and methanogenesis were all important microbially-driven in situ processes ( D’Hondt et al., 2004 ). However, sulfate-reducing, methanogenic, or methane-oxidizing microorganisms were surprisingly rare or absent from clone libraries of transcribed, PCR-amplified 16S rRNA ( Biddle et al., 2006 ; Sørensen and Teske, 2006 ) and PCR-amplified 16S rRNA genes ( Parkes et al., 2005 ; Inagaki et al., 2006 ). Functional genes that encode for enzymes that are unique to certain metabolisms can be targeted to identify microorganisms that are involved in these metabolisms. Functional genes that have been investigated in targeted studies at ODP Leg 201 sites include the gene for dissimilatory sulfite reductase ( dsrAB ), a key enzyme of dissimilatory sulfate reduction ( Wagner et al., 2005 ), the gene for reductive dehalogenase ( rdh A) of reductive dehalorespiration ( Futagami et al., 2009 ), the gene for formyl tetrahydrofolate synthetase ( fhs A), a crucial enzyme of acetogenewsis ( Lever et al., 2010 ), and the gene for the α subunit of methyl coenzyme M reductase ( mcrA ), an enzyme that catalyzes the terminal step of biological methanogenesis and is also present in anaerobic methane oxidizers ( Friedrich, 2005 ; Knittel and Boetius, 2009 ; Wang et al., 2021 ). Patchy PCR detections of dsr AB and mcr A in only a few samples ( Parkes et al., 2005 ; Inagaki et al., 2006 ; Webster et al., 2006 ) remain at odds with porewater concentration profiles of sulfate and methane, which indicate microbial sulfate reduction, AOM, and methanogenesis ( D’Hondt et al., 2004 ). Similar observations were made based on quantitative PCR and metagenome sequencing in methane-rich deep subseafloor sediments of Hydrate Ridge in the Northeastern Pacific ( Colwell et al., 2008 ), the Black Sea and off Namibia ( Schippers et al., 2012 ), the Baltic Sea ( Marshall et al., 2018 ), and Adélie Basin off Antarctica ( Carr et al., 2018 ). It was thus proposed that methanogens account for low percentages (<1%) of microbial cells in subseafloor sediments, or are not detected by PCR assays due to primer mismatches or use of unrecognized genetic pathways ( Lever, 2013 ). Here we take a closer look at the in situ community of methanogens and anaerobic methanotrophs in the sediment column of ODP Site 1230 in the Peru Trench via PCR assays of mcrA . We investigate the relationship between community zonation and geochemical profiles [sulfate, methane, formate, acetate, hydrogen, δ 13 C-methane and -dissolved inorganic carbon (DIC)], and identify active members of the methane-cycling community via reverse transcription-PCR (RT-PCR) of 16S rRNA and mcrA -mRNA. Redesigned general mcrA primers ( Lever and Teske, 2015 ) and new group-specific mcrA and 16S rRNA gene primers allow us to detect methane-cycling functional genes in the AOM and methanogenesis zones inferred from porewater chemical gradients. While updated primers improve the detection of methane-cycling archaea, they reinforce the notion that methane-cycling archaea only account for a small proportion of microbial subsurface communities even in sediments with clear geochemical evidence for methanogenesis and AOM.",
"discussion": "Discussion We present a depth profile of mcrA that relates distribution patterns of deep subseafloor methanogens and anaerobic methanotrophs to the geochemical context. While the genetic and gene transcript analyses in our study are present-day snapshots of methane-cycling activity, the measured geochemical data in part capture much longer time scales, such as the accumulation of methane over millions of years. Nonetheless, we observe a clear relationship between the community profile of methane-cycling archaea and porewater geochemical gradients. We, moreover, resolve the paradox of earlier studies in which methane-rich sediments at ODP Site 1230 appeared largely devoid of methanogens in the methanogenesis zone ( Inagaki et al., 2006 ), and completely devoid of anaerobic methanotrophs in the SMTZ ( Biddle et al., 2006 ). Geochemical and functional gene profiles indicate a distinct depth stratification of the active methane cycling community ( Table 2 ; Figure 5 ). No nucleic acid evidence of present-day methane-cycling was detected in the upper part of the sulfate reduction zone (0 to ~7 mbsf) despite methane concentrations in the micromolar range. Throughout the SMTZ (~7 to 9 mbsf in borehole A, up to 1 m deeper in boreholes B and C), sulfate concentrations diminished in typical concave-down profiles, and methane concentrations increased. These gradients coincide with the detection of mcr A of ANME-1a-b ( Figure 5 ), members of which are known to be anaerobic methanotrophs ( Knittel and Boetius, 2009 ). Therefore, our sulfate and methane concentration profiles and mcrA composition in the SMTZ are consistent with AOM. In the underlying methanogenesis zone (~9 to 269+ mbsf), methane concentrations and δ 13 C-DIC increase drastically in the upper tens of meters and stay high throughout, while sulfate remains depleted ( Figures 2 , 3 ). Interestingly, ANME-1a-b Archaea were detected in the upper meters of the methanogenesis zone (from 9.7 to 16.1 mbsf), in line with past indications that ANME-1a-b might be capable of methanogenesis in addition to methanotrophy ( House et al., 2009 ; Lloyd et al., 2011 ; Beulig et al., 2019 ). Moreover, ANME-1a-b were vertically separated from ANME-1d and Methanothrix mcr A sequences, which were only found in deeper, methanogenic sediment layers. The three groups only overlapped in core 3H-5 (20.6 mbsf), which marked the deepest sample in which ANME-1a-b and shallowest sample in which ANME-1d and Methanothrix were detected. Implications of the 13 C-isotopic data The changes in δ 13 C-DIC and –methane provide insights into the sources of DIC and pathways of methane production at ODP Site 1230. The δ 13 C-DIC isotopic values in the upper ~9 mbsf (−10.4 to −13.2‰) are consistent with organic matter mineralization becoming the main DIC source with increasing sediment depth. Most of this organic matter is likely to be phytoplankton-derived organic matter ( δ 13 C-total organic carbon: ~22–23‰; Biddle et al., 2006 ) that was initially deposited under the upwelling regime of the Peru Margin, and subsequently reworked and laterally transported downslope to the Peru Trench. Toward the sediment surface, the δ 13 C-DIC increases, most likely due to an increasing contribution of 13 C-enriched DIC from deep sea bottom water, which typically bears a 13 C-composition of ~0 to +1.2‰ ( Lynch-Stieglitz et al., 1995 ). Notably, despite the strong geochemical evidence for AOM in the SMTZ, which might be expected to produce highly 13 C-depleted DIC from the oxidation of methane, we do not observe a strong downward swing in δ 13 C-DIC within the SMTZ. This phenomenon has been observed previously in SMTZs and has been explained with concomitant AOM and methane production ( Beulig et al., 2019 ), microbially mediated isotope exchange between methane and DIC ( Yoshinaga et al., 2014 ), and reversibility of intracellular methane-cycling reactions at low sulfate concentrations ( Wegener et al., 2021 ). In our case, the mcr A data argue against the first scenario, if ANME-1a-b are assumed to only perform methanotrophy. Yet, if – as proposed previously - ANME-1a-b are facultative methanogens, which matches the detection of this group throughout the upper ~12 m of the methanogenesis zone, then the first scenario is also plausible. Notably, porewater dissolved barium concentrations increase sharply throughout the AOM and upper methanogenesis zone (e.g., from 2.7 μM at 6.15 mbsf to 290 μM at 23.15 mbsf at ODP Site 1230A; D’Hondt et al., 2003 ), consistent with (slow) release of sulfate through chemical dissolution of barite (BaSO 4 ). This sulfate could fuel low rates of AOM, and thus also support concomitant AOM and methane production throughout the upper methanogenesis zone. AOM coupled to iron or manganese reduction could also support low rates of AOM, as was recently proposed for subsurface sediments of the South China Sea, where ANME-1 were detected meters below the SMTZ ( Zhang et al., 2023 ). Yet, the low porewater concentrations of Fe 2+ (0.6 to 3.9 μM) and Mn 2+ (0 to 0.3 μM) in the upper methanogenic sediment layer where we detected ANME-1a-b at ODP Site 1230 ( D’Hondt et al., 2003 ) do not support an important role of AOM coupled to metal reduction. Below 9 mbsf, the δ 13 C-DIC increased, consistent with a strong isotopic imprint of methanogenesis by CO 2 reduction. Strong isotopic discrimination against 13 C-CO 2 is the norm in methanogenesis from H 2 /CO 2 ( Whiticar, 1999 ; Penning et al., 2005 ) and can result in significant 13 C-enrichment of the residual DIC pool ( Alperin and Hoehler, 2009 ; House et al., 2009 ). Based on measured porewater geochemical data, methanogenesis from H 2 /CO 2 is, however, not thermodynamically favorable ( Figure 6 ), with in situ Gibbs energies in the positive (i.e., endergonic) range (ΔG \n r \n ’ > 0 kJ mol −1 ) throughout the sediment column of ODP Site 1230. Since methanogenesis from formate follows the same biochemical route as hydrogenotrophic methanogenesis after the initial oxidation of formate to CO 2 and H 2 by formate dehydrogenase ( Sparling and Daniels, 1986 ), a similar isotopic fractionation can be expected. Indeed, the complete conversion reaction of formate to methane is thermodynamically favorable, and based on that alone formate a potential methanogenic substrate at ODP Site 1230 ( Figure 6 ). Yet, assuming that energy is not conserved during the initial formate oxidation step, but only in the second step involving methanogenic CO2 reduction with H 2 ( Schink et al., 2017 ), then formate conversion to methane appears less plausible. This is because intracellular H 2 concentrations can be expected to be close to equilibrium with H 2 concentrations in the surrounding sediment due to H 2 leakage out of methanogenic cells ( Finke et al., 2007 ). As stated above, however, measured H 2 concentrations in the surrounding sediment are too low to energetically support hydrogenotrophic methanogenesis. A more recently documented form of methanogenic CO 2 reduction involves interspecies electron transfer (IET). This form of methanogenesis, which was first discovered in Methanothrix harundinaceae ( Rotaru et al., 2014 ), involves cellular structures, e.g., cytochromes, that attach to conductive mineral surfaces or syntrophic partner organisms ( Gao and Lu, 2021 ). The isotopic fractionations of these reactions are not known but most likely also cause δ 13 C-enrichment of residual DIC. In principle, the conversion of formate to methane could also operate via a direct electron transfer mechanism, e.g., from syntrophic bacteria to methanogens. This mechanism could bypass H 2 as a catabolic intermediate and even render formate catabolism a potential source of methane. Thus, based on the available geochemical data, the dominance of methanogenic CO 2 reduction at Site 1230, which was inferred from the δ 13 C-DIC profile below 9 mbsf, is most plausibly explained with electron transfer from syntrophic partner organisms or mineral surfaces to methanogens. Figure 6 Calculated in situ Gibbs energy yields (Δ Gr ’) of methanogenesis reactions from H2 + CO2 (HCO3 – + 4 H2 + H + ➔ CH 4 + 3 H 2 O) and acetate (CH 3 COO – + H 2 O ➔ CH 4 + HCO 3 – ), and the methanogenic conversion of formate to methane (4 HCOO – + H 2 O + H + ➔ CH 4 + 3 HCO 3 – ; note: this reaction includes the initial oxidation of formate to H 2 and HCO 3 – , which may not be coupled to energy conservation). Calculations were done for in situ conditions as described in the Materials & Methods. By contrast, chemoautotrophy, acetogenesis or other methanogenic pathways are unlikely drivers of the observed δ 13 C-DIC increase in the methanogenesis zone. Although (certain) ANME-1a-b are chemoautotrophs ( Kellermann et al., 2012 ), past studies indicate that AOM of isotopically highly depleted methane (~ − 75 per mil) to CO 2 occurs at much (≥40-fold) higher rates than C-assimilation by chemoautotrophy (e.g., Nauhaus et al., 2007 ; Wegener et al., 2008 ). Consequently, AOM would be expected to overprint any C-isotopic enrichment of DIC by chemoautotrophy. Acetogenesis from H 2 /CO 2 , which also strongly discriminates against 13 C ( Gelwicks et al., 1989 ), is unlikely based on δ 13 C-acetate values of −12 to −18‰ at ODP Site 1230 that indicate fermentation as the main acetate source ( Heuer et al., 2006 ). The other widespread methanogenesis pathways from acetate (aceticlastic methanogenesis) and methylated substrates (e.g., methanol, dimethyl sulfide and methyl amines; methylotrophic methanogenesis), produce rather than consume CO 2 ( Whitman et al., 2014 ). In aceticlastic methanogenesis, this CO 2 has the same 13 C-depleted isotopic composition as the methane produced ( Gelwicks et al., 1994 ) and would thus lower (rather than increase) the δ 13 C-DIC. Despite high concentrations of acetate, our calculations, moreover, indicate that aceticlastic methanogenesis is close to thermodynamic equilibrium throughout most of the methanogenesis zone ( Figure 6 ), with Gibbs energies not reaching the theoretical minimum required for biological energy conservation by proton translocation (ΔG \n r \n ’ ≅ 10 kJ mol −1 ; Hoehler et al., 2001 ; Lever et al., 2015 ). 13 C-depletion of DIC is also expected for methylotrophic methanogenesis, even though this pathway produces methane with similar isotopic fractionations as CO 2 reduction ( Conrad, 2005 ). The reason for 13 C-depletion of DIC is that the main isotopic fractionation of methylotrophic methanogenesis is produced by the first enzymes in the reaction chain (methyl transferase I and/or II; Krzycki et al., 1987 ) and hence upstream of where C fractions enter separate enzymatic pathways to produce CO 2 and methane ( Thauer, 1998 ). Notably, another form of methylotrophic methanogenesis, which involves methylated substrates and hydrogen, e.g., methanol + H 2 does not produce CO 2 ( Dridi et al., 2012 ; Whitman et al., 2014 ). A fourth methanogenic pathway that involves the conversion of methoxy-groups from lignin monomers to methane with CO 2 as a co-substrate ( Mayumi et al., 2016 ) is in theory also possible. Yet, this pathway is unlikely to be important given the primarily phytoplanktonic origin of organic matter at ODP Site 1230 ( Shipboard Scientific Party, 1988 ; D’Hondt et al., 2003 ) and recent evidence suggesting minimal long-term degradation of lignin in anoxic sediment ( Han et al., 2022 ). The increase in δ 13 C-DIC with depth is steepest from the lower SMTZ to ~20 mbsf ( Figures 3 , 5 ), consistent with rates of methanogenic CO 2 reduction being highest in this interval. The subsequent decrease in the slope of δ 13 C-DIC with depth can be explained with an increase in the DIC pool size and decline in the rates of CO 2 reduction. In addition, it is possible that the relative contributions of other methanogenic pathways, e.g., aceticlastic methanogenesis, increase below this depth. Nonetheless, the 13 C-isotopic depletions of −80 to −86‰ of δ 13 C-methane relative to δ 13 C-DIC that were consistently measured below 18 mbsf ( Figure 3 ) indicate that CO 2 reduction accounts for most of the methane that has accumulated throughout the methanogenesis zone of ODP Site 1230. Community zonation When examined in the geochemical context, the distribution of mcrA genes within the methanogenesis zone of ODP Site 1230 may be surprising. Isotopic compositions of DIC and methane suggest predominance of methanogenesis by CO 2 reduction, whereas detected mcr A sequences belong to phylotypes of putatively anaerobic methane-oxidizing ANME-1a-b, its catabolically uncharacterized sister group ANME-1d, and Methanothrix , a genus that was traditionally believed to consist uniformly of obligately aceticlastic methanogens. The presence of ANME-1a-b in the SMTZ and in underlying sediment that is net methanogenic can be explained with different scenarios. The first one is that ANME-1a-b are indeed facultatively methanogenic, as proposed previously based on strong heterogeneity in δ 13 C of ANME-1-biomass in seep sediments ( House et al., 2009 ), detection of ANME-1a-b mcr A transcripts in methanogenic sediment ( Lloyd et al., 2011 ), and combined methanogenesis rate measurements and mcr A analyses across anaerobic methane-oxidizing and methanogenic sediment ( Beulig et al., 2019 ). This environmental evidence has been supported by recent genomic detections of hydrogenase genes, that are potentially involved in hydrogenotrophic methanogenesis, across multiple ANME-1a-b and ANME-1c taxa ( Laso-Pérez et al., 2023 ). Alternatively, AOM by ANME-1a-b may continue as a cryptic process in the presence of methanogenesis throughout the uppermost part of the methanogenesis zone. Our thermodynamic calculations indicate that a reversal of methanogenic CO 2 reduction with H 2 is thermodynamically favorable throughout bulk sediments of ODP Site 1230 ( Figure 6 ), though the electron acceptor is unclear. As discussed earlier, the increase in dissolved barium indicates barite (BaSO 4 ) dissolution in this part of the sediment column as a potential source of sulfate, whereas the very low Fe 2+ and Mn 2+ concentrations argue against a significant role of AOM coupled to metal reduction. Under this scenario, the organisms that were responsible for the production of the measured methane are unknown. While neither possibility can be ruled out, the available evidence from this and past studies supports ANME-1a-b contributing to the production of methane by CO 2 reduction in the upper methanogenesis zone of ODP 1230. The metabolism of ANME-1d, which replaces ANME-1a-b in deeper sediment layers of the methanogenesis zone, is even less understood than that of ANME-1a-b. This group, which was previously also referred to as “ANME-1-related group” and represents a poorly studied, sister family, or even sister order, of ANME-1a-b ( Lever and Teske, 2015 ), has been found across a range of anoxic environments. These include hydrothermal vents in ultramafic settings ( Kelley et al., 2005 ), deeply buried terrestrial coalbeds ( Fry et al., 2009 ), marine gas hydrate sediments ( Kormas et al., 2005 ), and tidal creek sediments ( Edmonds et al., 2008 ). Given the sole detection of ANME-1d DNA and mRNA deep in the methanogenesis zone, a methanogenic lifestyle seems likely. This group could reduce CO 2 to methane using electrons from IET and thus contribute to the observed strong δ 13 C-depletion of methane relative to DIC. The predominant detection of Methanothrix-mcr A sequences below 20 mbsf, despite δ 13 C-DIC compositions that indicate mainly methanogenesis by CO 2 reduction, and Gibbs energies of aceticlastic methanogenesis near thermodynamic equilibrium, is perplexing, given that members of Methanothrix are traditionally considered to be obligate aceticlasts. One explanation is that these sequences belong to inactive or dead cells. Yet, this explanation does not match the detection of rRNA of Methanothrix ( Table 2 ), and is at odds with research suggesting that the vast majority of DNA from dead microorganisms is degraded over time scales of centuries in subsurface sediments ( Torti et al., 2018 ). Instead, the Methanothrix mcr A and 16S rRNA sequences may not belong to (obligate) aceticlasts. While genomic data of Methanothrix thermophila indicate potential for hydrogenotrophic metabolism in this group ( Smith and Ingram-Smith, 2007 ), methanogenesis involving H 2 has never been shown for Methanothricaceae . Yet, more recent experiments with pure cultures have demonstrated that members of Methanothrix - including Methanothrix harundinacea , which mcr A sequences from ODP Site 1230 cluster with ( Figure 5 ) - are capable of methanogenic growth by CO 2 reduction using electrons received directly or through mineral intermediates from syntrophic partner organisms ( Rotaru et al., 2014 ; Yang et al., 2019 ; Gao and Lu, 2021 ). Experiments involving rice paddy soils and lake sediments have provided additional evidence for CO 2 reduction by Methanothrix in the environment ( Holmes et al., 2017 ; Rotaru et al., 2019 ). Consequently, the observed δ 13 C-DIC and δ 13 C-methane compositions and dominance of mcr A sequences of Methanothrix may not be a contradiction, but instead match revised knowledge on the metabolic capabilities of Methanothrix ."
} | 6,656 |
33763291 | PMC7976604 | pmc | 7,512 | {
"abstract": "The UbiD family of\nreversible (de)carboxylases depends on the recently\ndiscovered prenylated-FMN (prFMN) cofactor for activity. The model\nenzyme ferulic acid decarboxylase (Fdc1) decarboxylates unsaturated\naliphatic acids via a reversible 1,3-cycloaddition process. Protein\nengineering has extended the Fdc1 substrate range to include (hetero)aromatic\nacids, although catalytic rates remain poor. This raises the question\nhow efficient decarboxylation of (hetero)aromatic acids is achieved\nby other UbiD family members. Here, we show that the Pseudomonas\naeruginosa virulence attenuation factor PA0254 / HudA is a pyrrole-2-carboxylic acid decarboxylase. The crystal structure\nof the enzyme in the presence of the reversible inhibitor imidazole\nreveals a covalent prFMN – imidazole adduct\nis formed. Substrate screening reveals HudA and selected active site\nvariants can accept a modest range of heteroaromatic compounds, including\nthiophene-2-carboxylic acid. Together with computational studies,\nour data suggests prFMN covalent catalysis occurs via electrophilic\naromatic substitution and links HudA activity with the inhibitory\neffects of pyrrole-2-carboxylic acid on P. aeruginosa quorum sensing.",
"introduction": "Introduction The\nUbiD family of enzymes catalyzes the reversible nonoxidative\ndecarboxylation of a wide range of unsaturated aliphatic and aromatic\ncompounds, the latter including phenolic compounds, 1 heteroaromatics, 2 phthalates, 3 polycyclics, 4 as well\nas benzene itself 5 (recently reviewed in\nref ( 6 )). Recent insights\ninto the UbiD mode of action came from studies on the fungal enzyme\nferulic acid decarboxylase Fdc1. 7 These\nrevealed that UbiD enzymes require a modified flavin cofactor, prenylated-FMN\n(prFMN), for activity 8 ( Figure 1 ). The genetically associated\nUbiX acts as the flavin prenyltransferase, attaching a prenyl moiety\nto the N5 and C6 positions of reduced FMN, thereby extending the cofactor\nwith a fourth nonaromatic ring. 9 , 10 Following UbiD binding,\nthe reduced prFMNH 2 produced by UbiX is proposed to undergo\noxidative maturation to yield the active prFMN iminium species.\nThe azomethine ylide character of the prFMN iminium supports\na reversible 1,3-dipolar cycloaddition underpinning the (de)carboxylase\nmechanism of Fdc1 8 ( Figure 1 ). Recent structural insights into a range\nof covalently bound substrate/cofactor adducts confirmed that cycloadducts\nare formed during the catalytic cycle. 11 However, the extent to which 1,3-dipolar cycloaddition occurs for\nUbiD enzymes acting on (hetero)aromatic substrates has been questioned,\nas the necessary dearomatization of the substrate presents a substantial\nbarrier to cycloadduct formation. Figure 1 Covalent catalysis by prFMN in UbiD enzymes.\nprFMN cofactor is\nformed through FMN prenylation followed by oxidative maturation (prenylation\nshown in red). Unsaturated carboxylic acid is proposed to form a covalent\nadduct with the prFMN iminium cofactor leading to decarboxylation.\nIn the case of acrylic acid substrates, substantial evidence supports\na 1,3-dipolar cycloaddition process leading to intermediate 1 ( Int 1 ), followed by decarboxylation to form Int 2 +\nCO 2 . Exchange of CO 2 with\na conserved acidic residue leads to protonation to form Int\n3 , which is proposed to form product through cycloelimination.\nThe exact nature of the various intermediate species remains unclear\nin the case of (hetero)aromatic substrates. Unfortunately, recent structural and biochemical characterization\nof three UbiD decarboxylases acting on aromatic substrates has not\nyielded detailed mechanistic insights to answer this question. In\nthe case of the canonical Escherichia coli UbiD,\nthe purified enzyme failed to mature the active form of the cofactor,\ninstead accumulating an inactive prFMN radical species. 12 Active enzymes could be obtained for HmfF (catalyzing\nthe decarboxylation of 2,5-furandicarboxylic acid 13 ) and AroY (decarboxylating protocatechuate to catechol 14 ). In each case, crystals of the holo -enzyme did not yield any substrate complexes despite several attempts.\nThe discrepancy between the closed, solvent-occluded conformation\nof the Fdc1 active site (which readily binds substrates or inhibitors)\nand the more open, solvent-accessible conformations (which hitherto\nhave not yielded any ligand-bound structures) observed for the UbiD,\nHmfF, and AroY structures can be explained by a putative hinge motion\nof the prFMN-binding domain. 14 − 16 Such a conformational change\nwould link the postulated open and closed conformations, but as yet\nno UbiD enzyme has been demonstrated to exhibit both conformations.\nTo further complicate matters, the dimeric Fdc1 belongs to a distinct\nbranch of the UbiD family tree as compared to the hexameric UbiD/HmfF\nand AroY enzymes, reflected in the distinct substrate specificities\nof these enzymes. However, recent protein engineering studies on Fdc1\nhave been able to extend the substrate scope to include (hetero)aromatic\ncompounds using a single active site substitution. 15 This suggests that quaternary structure or position within\nthe UbiD-family tree does not have a fundamental link to substrate\nspecificity. We sought to provide further detailed insights\ninto the UbiD reaction\nwith heteroaromatic substrates, focusing on pyrrole-2-carboxylate\n(P2C) decarboxylases. We here report that the UbiD-like Pseudomonas\naeruginosa virulence attenuation factor PA0254/HudA is a\nclose homologue of Bacillus megaterium PYR2910 pyrrole-2-carboxylate\n(P2C) decarboxylase and show that PA0254 is capable of prFMN-dependent\ndecarboxylation of P2C as well as carboxylation of pyrrole. Structure\ndetermination of the PA0254 holo -enzyme reveals a\nclosed conformation with a buffer-derived imidazole moiety covalently\nbound to the prFMN. Substrate screening reveals that a modest range\nof heteroaromatic substrates is accepted, including weak activity\nwith thiophene-2-carboxylate. Structure-based semirational engineering\nsupported a modest improvement in yields with the latter compound.\nIn combination with the DFT computational studies, our data suggests\nthat covalent catalysis occurs via electrophilic aromatic substitution.",
"discussion": "Discussion The unusual metamorphosis of flavin to prFMN iminium alters\nthe fundamental character of this cofactor. In contrast to the C4a/N5\nfocused reactivity of flavin, the N5–C6 prenylation and subsequent\noxidative maturation of prFMN iminium lead to a stabilized\nazomethine ylide species with a reactive C4a/N5/C1′ center. 8 , 41 Assuming prFMN iminium underpins catalysis in all UbiD\nenzymes, certain general principles are likely to apply across this\nubiquitous microbial enzyme family. Arguably, the best-understood\nenzyme is the A. niger ferulic acid decarboxylase\nthat acts predominantly on cinnamic acid-type substrates. 8 , 42 , 43 In this case, sufficient evidence\nhas accumulated that supports a reversible 1,3-dipolar cycloaddition\nmechanism underpinning the (de)carboxylation reaction. 11 Chemical precedent exists for the reaction of\ncinnamic acid-type dipolarophiles with azomethine ylide species, and\nthe proposed mechanism also provides an explanation for the need of\nthe elaborate FMN to prFMN iminium transformation. However, the substrate scope of the wider UbiD family extends far\nbeyond cinnamic acid substrates, including both heteroaromatic and\naromatic acids. 6 It is clear that the latter\nsubstrates have inherently different reactivity and impose distinct\nconformational and energetic challenges for the enzyme. In the case\nof A. niger ferulic acid decarboxylase, variants\nhave been developed that accept (hetero)aromatic acids with low reactivity\nobserved for 2-naphthoic acid. 15 In this\ncase, an electrophilic aromatic substitution process has been proposed\nwith stabilization of the charge on the Wheland intermediate through\nstacking with the prFMN iminium . In contrast, the decarboxylation\nof 3,4-dihydroxybenzoic acid substrates by AroY is proposed to occur\nvia a quinoid intermediate formed concomitant with prFMN C1′–substrate\nC alpha bond formation. 14 Finally, reversible\ndecarboxylation of furan dicarboxylic acid by HmfF has been proposed\nto occur through either a cycloaddition or an electrophilic aromatic\nsubstitution process. 13 In the case\nof PA0254, the structure of the covalent prFMN iminium C1′–imidazole\nC2 adduct provides further\ninsight into the general reaction of UbiD enzymes with heteroaromatic\ncompounds. Crucially, the imidazole-2-carboxylic acid is not a substrate\nfor the enzyme, while imidazole acts as a reversible inhibitor. The\nchemical reactivity of imidazole for electrophilic aromatic substitution\nis substantially lower than that of the corresponding pyrrole and\nonly occurs on C4/C5 positions. In contrast, the imidazole C2 position\nis electron deficient and undergoes nucleophilic aromatic substitution\nwhen a suitable leaving group is present. This suggests that reversible\nbond formation with imidazole C2 might occur through nucleophilic\nattack of C1′ concomitant with protonation at N3. Crucially,\nthis prFMN adduct species (labeled Inhib in Figure 16 ) would not support\nH/D exchange or (de)carboxylation at the C2 position, in line with\nour observations in solution. Figure 16 Proposed mechanism for PA0254/HudA. prFMN iminium electrophilic\naromatic substitution reaction with pyrrole underpins reversible decarboxylation,\nwhile nucleophilic addition to the imidazole C2 position leads to\nreversible inhibition. In contrast, reaction\nwith pyrrole/furan/thiophene compounds is\nlikely to occur through electrophilic aromatic substitution at the\nC2 position via a Wheland-type intermediate Int1 open /Int3 open ( Figure 16 ). While DFT calculations indicate an Int1 closed species\nmight occur, it is unclear what role it plays in catalysis. It is\nhowever interesting to note the Int1 closed species appears\ninaccessible to the zwitterionic imidazole-2-carboxylic acid. The\nInt1 and Int3 intermediates provide access to the central Int2 species\nvia, respectively, (de)carboxylation and (de)protonation. It is possible\nthat additional through-space electronic interactions with the prFMN iminium stabilize the charge on the Wheland intermediate 44 and assist with retaining the strained configuration\nof Int2. The latter configuration is required within the context of\nthe closed active site as highlighted by the PA0254 UbiX –imidazole complex. A configuration whereby the C1′\nprFMN substituent is positioned in the plane of the substrate aromatic\nring would require active site reorganization, similar to the domain\nmotion observed when comparing the apo - and holo -forms of PA0254. However, to ensure rapid turnover,\nhighly stable covalent intermediates\nshould be avoided, and we propose that the aromatic group in the Int2\nadduct remains parallel rather than perpendicular to the prFMN iminium plane. The trend in yields obtained with pyrrole-,\nfuran-, and thiophene-2-carboxylic acid compounds mirrors the respective\nreactivity toward electrophilic aromatic substitution in solution.\nNo activity with pyrrole-3-carboxylic acid could be detected, but\nthe related indole-3-carboxylic acid readily yielded indole. This\nagain mirrors the trends for electrophilic aromatic substitution reactivity,\nwhich is preferred for pyrrole at the 2 position while indole occurs\nat the 3 position. Unfortunately, no reaction could be observed with\nbenzoic acid, a substrate that arguably presents the most formidable\nbarrier due to the high aromaticity of the benzene ring. However,\nUbiD enzymes have been implicated in microbial anaerobic benzene degradation\nwhere carboxylation is proposed to activate the substrate for further\ndegradation. 45 We have not been able to\nestablish whether benzoic acid can bind to PA0254 UbiX ,\nwhile variants aimed at creating a more hydrophobic active site (i.e.,\nN318A/V/L) did not readily bind prFMN. It thus remains possible that\na UbiD enzyme with an active site optimized for benzene/benzoic acid\nbinding might be able to catalyze electrophilic aromatic substitution\nat rates sufficient to support the relatively slow microbial growth\nseen during anaerobic benzene degradation. Furthermore, the domain\ndynamics indirectly observed here, but not invoked for either Fdc1\nor PA0254 reaction, might couple to the reaction coordinate in the\ncase of more challenging transformations such as benzene/napthalene\nor phenylphosphate carboxylation. 29 , 45 , 46 While the exact biological role of PA0254/HudA\nas a pyrrole-2-decarboxylase\nis yet to be established, the recent observation that P2C eliminates\nthe expression of quorum sensing cascade and pathogenic factors of P. aeruginosa PAO1 on both phenotypic and genotypic levels 47 suggests that it could be involved in P2C detoxification.\nPrevious identification of PA0254/HudA as a virulence attenuation\nfactor, on the other hand, 21 might indicate\nthat the product of the decarboxylation reaction, pyrrole, is responsible\nfor the observed effects."
} | 3,258 |
36983971 | PMC10057978 | pmc | 7,517 | {
"abstract": "Exploring austere environments required a reimagining of resource acquisition and utilization. Cyanobacterial in situ resources utilization (ISRU) and biological life support system (BLSS) bioreactors have been proposed to allow crewed space missions to extend beyond the temporal boundaries that current vehicle mass capacities allow. Many cyanobacteria and other microscopic organisms evolved during a period of Earth’s history that was marked by very harsh conditions, requiring robust biochemical systems to ensure survival. Some species work wonderfully in a bioweathering capacity (siderophilic), and others are widely used for their nutritional power (non-siderophilic). Playing to each of their strengths and having them grow and feed off of each other is the basis for the proposed idea for a series of three bioreactors, starting from regolith processing and proceeding to nutritional products, gaseous liberation, and biofuel production. In this paper, we discuss what that three reactor system will look like, with the main emphasis on the nutritional stage.",
"conclusion": "10. Conclusions Over the last decade and half, the science of exploring the use of ISRU/BLSS bioreactors has advanced tremendously. New siderophilic strains with improved bioweathering capacity continue to be discovered. Many species have been characterized by their ability to provide a portion of a human diet, as well as provide a breathable atmosphere and propellant to continue missions. From a nutrition standpoint, Arthrospira is a genus that has been most studied and which has secondary benefits that cannot be refuted. Other species provide similar benefits as well and should not be discounted. For atmospheric control, from the research, oxygen production has been effectively seen in many bioreactors in the past and can sustain human needs in space. The optimization of carbon fixation processes should be further investigated. Enzyme specificity and efficiency are included in the current roadblocks, but gene manipulation shows hope for a better solution. Fuel production is a mixed story. Ethanol does not have the energy density of other compounds. Sustainable hydrogen production has not been effectively developed. Biodiesel/gasoline are not optimal for rocket engines. However, methane is a fuel that could be employed for an ascent engine, and perhaps the Mars–Earth trans-injection burn, and it shows promise for large-scale ISRU production. When used with the oxygen byproduct of the photosynthetic reactor, this makes extra-terrestrial fuel production a real possibility. Promising species have been identified for each part of a complete system, but there is always room for improvement. Models of complementary photosynthetic–methanogenic bioreactors have shown compatibility to a degree, but should still be improved for efficiency. Though we do not have access to large amounts of lunar or Martian regolith now, analogs have been made to jumpstart trials of biological ISRU systems. This field is advancing fast and once solved, not only will we exceed the current limits on space travel, but also shape the distribution of renewable food and energy here on Earth.",
"introduction": "1. Introduction Human expeditions to other celestial bodies have been achieved with the Apollo program, but current goals are to travel farther and for longer. With missions no more than 2 weeks in duration, all food, fuel, and other supplies were packed in from launch to landing with no need for resupply. The International Space Station (ISS) has enabled continuous human presence in space for over 2 decades, proving our capacity to live off-planet for an extended time frame, however, in low Earth orbit (LEO), a resupply vehicle is only a few hours away. Some current goals of the newer solar system exploration reference missions are to travel farther away from Earth, with longer duration, and greater need for autonomous crew sustenance. Several lunar design reference missions call for a continuous presence on the moon to learn how to reliably live off the native resources [ 1 ]. Mars surface reference missions have both short and long surface stay options, but with 2–3 years total mission duration. Both would require solutions to three of the main limiting factors, food, air, and fuel. One of the critical factors in planning a mission to Mars is timing the launch within the launch window. Based on the Hohmann transfer orbit, these limited windows of opportunity typically occur once every 26 months when Earth and Mars are in suitable positions to minimize the fuel and time expended [ 2 ]. Since 1976 with the Viking program, we have been able to send unmanned spacecraft to the surface of Mars. Clearly, the current knowledge of orbital trajectories and mechanics has allowed us to reliably reach the planet with conventional rocketry, but the challenge for human missions remains the need for life-sustaining resources, and a return trip home. The question NASA and other agencies are trying to answer is how to reliably sustain human life in such austere environments, beyond immediate aid. A one-way trip to Mars involves between a 7–12 month exposure to microgravity, a lack of gaseous resources, cosmic radiation exposure, and a lack of available nutrients to harvest. Two of the biggest limiting factors of what we can launch from Earth are mass and volume. Providing all the food, air, and fuel for crewmembers from launch will incur a heavy tax on the capacity of our craft to carry other necessary supplies. Further, any unplanned burns or the life support system failure of one of the oxygen tanks could be irreversibly terminal. This is why we must look for more sustainable options for food, oxygen, fuel, or a combination, something generated during the mission that would reduce the percentage of static material occupying volume on the spacecraft. A possibility for this is a three reactor system ( Figure 1 ). Stage 1 involves using siderophilic cyanobacteria and their organic bioacids to liberate minerals and gasses from the lunar and Martian regolith. Martian regolith is full of essential minerals, metals, and more needed for life to flourish, including iron. However, it is not available to a lot of organisms in its current state and environment. Stage 2 will involve a photosynthetic reactor using a different species of microorganism that has been studied and cultivated for human consumption here on Earth. This reactor will use the compounds and minerals liberated from the regolith in Stage 1, along with solar radiation and the carbon dioxide from the crew, with possible supplementation by the Martian atmosphere, to produce an edible biomass to supplement the food stores for the mission. Stage 3 will involve a third bioreactor with a different microorganism to form biofuels. Excess biomass from Stage 2 along with some nutrients from Stage 1, if necessary, could be used as nutrition for this reactor as it creates the desired fuel. The current optimal candidate for fuel production is methane, due to its reasonably high Isp, its incorporation into several design reference missions, and known bacterial digestive effluent, e.g., human colonic flatus. Many teams, agencies and projects have aimed to solve this life support puzzle. Namely, the Lunar-Mars Life Support Test (LMLSTP), BioHAB, and the Micro-Ecological Life Support System Alternative (MELiSSA), all provided advances in understanding of the intricacies of developing self-sustainable life support systems. The LMLSTP aimed to incorporate higher order plants in an isolated ecological circle. The BioHAB project aimed to create a biological habitat that would provide support functions itself through a mycelium-based wall with other microorganisms included. MELiSSA is an ongoing initiative to create autonomous systems for exploration missions capable of regenerating food, oxygen, and water. The loop concept for this project consisted of four compartments (liquefying, photoheterotrophic, nitrifying, and photoautotrophic) working together to create biologically relevant compounds, as well as recycle waste. Many of the teams involved in the MELiSSA project have made large strides in bioreactor technology involving many of the principles and species mentioned in this review. A brief summary of these projects can be found in a similar review by these authors [ 3 ]. Not mentioned in that review is the Biosphere 2 program. Biosphere 2 was a project undertaken in the 1990s with the goal to create “the first indefinitely operating bioregenerative system capable of full human life support” [ 4 ]. The structure itself, which is now run by the University of Arizona, is a multi-ecosystem facility designed to be completely isolated from the outside world except for the sunlight and energy used for atmospheric temperature control. Ecosystems included were tropical rain forest, mangrove wetlands, a fog desert, savannah grassland, and an ocean with a coral reef. Two manned missions were created. The first one began in 1991 and lasted for 2 years, though many problems occurred, including medical emergencies with brief evacuations and atmospheric calculation failures resulting in very high carbon dioxide levels attributed to the high rates of respiration by soil bacteria. The second mission was cut short largely due to budgetary problems. Today, the artificial ecosystem facility serves as a model for research into other relevant topics like the understanding and mitigation of the effects of climate change [ 5 ]. In this paper, we will briefly review data surrounding Stages 1 and 3 while focusing on Stage 2, the nutrition and biogas generation component of the system. We discuss a few species of microorganisms that have been identified as candidates for this system, going into their nutrition benefits and any drawbacks. Further, we will discuss the state of the research into oxygen liberation and carbon fixation in these systems and what that may look like at scale."
} | 2,493 |
26656851 | PMC4675544 | pmc | 7,519 | {
"abstract": "Over the past decade, technological advances in experimental and animal tracking techniques have motivated a renewed theoretical interest in animal collective motion and, in particular, locust swarming. This review offers a comprehensive biological background followed by comparative analysis of recent models of locust collective motion, in particular locust marching, their settings, and underlying assumptions. We describe a wide range of recent modeling and simulation approaches, from discrete agent-based models of self-propelled particles to continuous models of integro-differential equations, aimed at describing and analyzing the fascinating phenomenon of locust collective motion. These modeling efforts have a dual role: The first views locusts as a quintessential example of animal collective motion. As such, they aim at abstraction and coarse-graining, often utilizing the tools of statistical physics. The second, which originates from a more biological perspective, views locust swarming as a scientific problem of its own exceptional merit. The main goal should, thus, be the analysis and prediction of natural swarm dynamics. We discuss the properties of swarm dynamics using the tools of statistical physics, as well as the implications for laboratory experiments and natural swarms. Finally, we stress the importance of a combined-interdisciplinary, biological-theoretical effort in successfully confronting the challenges that locusts pose at both the theoretical and practical levels.",
"conclusion": "Concluding Remarks Modeling and understanding locust swarming has a dual role, or presents two approaches. The first views locusts as a quintessential example of animal collective motion. As such, due to major advances in experimental and animal tracking technologies, it allows the testing and evaluation of theories regarding the onset and maintenance of order and synchronization in moving swarms. Indeed, most of the models presented above take this approach, as they aim at abstraction rather than analysis and prediction of natural swarm dynamics. These models correspond to the general literature on collective motion, at the risk of failing to capture features unique to the locust swarms. Locusts have much to offer with respect to our general understanding of coordinated movement in nature. Similarly, we can take advantage of successful modeling efforts in other organisms in order to explain the locust phenomena. Indeed, one of the major remaining challenges in the growing field of collective animal movement lies in relating the similarities and differences between the mechanistic and behavioral modes of motion of different organisms to the observed large-scale coordinated behavior they exhibit. The second approach views locust swarming as a scientific problem of its own merit. From this more biological perspective, the main goal will be to use experiments in order to identify the principal interactions between animals and apply them in agent-based models. Our own work in [ 59 ] offers an initial step in deriving a simplified model based on first principle dynamics. In particular, all parameters used are fitted from experiments. The successful use of modeling efforts in describing and, moreover, in predicting the dynamics of real-life locust swarms crucially depends on taking into account many aspects and details of locust movement known to have a pivotal impact on their behavior: for example, the effect of temperature, the choice of direction, daily behavioral patterns, differences between marching and flight, etc. The locust phenomenon comprises different spatial and temporal scales, ranging from the individual (centimeters and minutes) all the way to vast, natural swarms consisting of millions of insects (kilometers and hours). Currently, there is a gap between the individual-based approaches presented early in this review (the section “Modeling Marching Locust Nymphs”) and the later-discussed continuous models (the two last sections). A key direction for future work will be to employ realistic and biologically accurate models to drive coarse-grained continuous models in order to understand the dynamics of entire swarms. The discussion on time scales in the related section above (“Coarse-Graining and Macroscopic Observables”) is an example of the intricate manner in which the local and global dynamics are connected. From the point of view of spatial scales, additional experimental and theoretical work is needed in order to understand the effects of the environment, e.g., climate, topography, etc. The major effects of anthropogenic factors, before and mainly during outbreaks (e.g., the efficiency of pesticides in containing outbreaks), should also be considered. We should also attempt to include global population dynamics in addition to local ones—can we treat a species’ entire global population as one?. Some hints for future work may come from genetic analyses of divergence among locust populations (e.g., [ 97 – 99 ]). However, this direction still awaits interpretation by way of solid theoretical models. Another significant gap in our understanding is related to the role of learning and memory-related mechanisms in the different aspects of locust behavior. Geva et al. [ 20 ] have made an important step in this direction by introducing a role for long-term memory in phase transformation. This should be extended to include a role for learning and memory in locust swarming and coordinated marching. With the increasing accumulation of biological knowledge, it is becoming clear that only a combined-interdisciplinary, biological-theoretical effort can advance our understanding of the locust phenomenon in general and of locust collective movement in particular. There is great importance in performing further controlled empirical experiments to test the hypotheses generated by the various models and the predictions resulting from them.",
"introduction": "Introduction—Why Locusts? “The locusts have no king, yet go they forth all of them by bands” (Proverbs 30:27, The Holy Bible , King James Version . Cambridge Edition. 1611). The Old Testament, like other ancient scripts, has several references to locusts and their behavior, specifically to the spectacular phenomenon of marching locust hopper bands. Part of our fascination with locust swarms is due to the fact that they always have been and still are a major threat to agriculture (e.g., [ 1 , 2 ]). Locusts are described as a pest of unusually destructive powers: A desert locust adult can consume roughly its own weight, i.e., about two grams, in fresh food per day [ 3 ]. The notorious 1915 locust attack in the Middle East, for example, resulted in wiping out a largely underestimated 536,000 tons of food [ 4 ]. According to the Food and Agriculture Organization of the United Nations, in modern days, e.g., during the 2003–2004 locust invasions, this translated to around US$30 million spent by a typical African nation in anti-locust campaigns [ 5 ]. The coordinated activity of crowds consisting of millions of individuals, while not unique to locusts, has been and still is a challenge to laymen and scientists alike. Despite considerable progress in understanding the mechanisms underlying the emergence and synchronization among moving crowds of animals as well as humans, locust swarming still presents several fundamental open questions. These include key questions regarding locust biology as well as more theoretical aspects. Some of the open, or far from fully answered, questions include: What are the principle interactions between conspecifics in a swarm? What is the effect of the environment on the swarm and vice versa? What are the functional and evolutionary advantages to swarming? How do local dynamics within a swarm translate to macroscopic dynamics of large swarms consisting of millions of individuals? Do order and disorder in locust swarms constitute a phase transition in the sense of statistical physics, or are there metastable states of the dynamics? Are there quantifiable traits unique to locust swarms in respect to other animal crowds (fish, birds, humans, etc.)? In the hope of encouraging more research into the above, as well as to provide a showcase of current knowledge, in this review, we summarize the different attempts to describe or capture locust collective behavior by way of theoretical modeling. As presented below, some of these efforts are heavily rooted in biological data and observations, while others offer a more mathematical or physical perspective. Some are specifically tailored and aimed toward explaining locust behavior; others are more general descriptions of collective motion, adapted to the locust case. The emphasis of the review is on marching locust nymphs. From the biological point of view, this is the critical stage during which the phenomenon of locust aggregation begins. Accordingly, recent years have seen several theoretical and modeling attempts to explain the emergence and maintenance of order in marching locust nymphs. We start with the biological background: locusts, density-dependent phases in locusts, swarming, and collective movement (marching and flying). We then move on to present some of the attempts to model locust collective behavior, from the early models of Self-Propelled Particles (SPPs) to our own recent attempt based on intermittent pause-and-go motion. Models of flying swarms, locust phase change, and evolutionary models are also briefly surveyed. We conclude with a discussion of the success (or failure) of theoretical models in addressing the key questions presented above, as well as the benefits of such models in dealing with the locust problem."
} | 2,420 |
26501832 | PMC4623080 | pmc | 7,520 | {
"abstract": "The intrinsic scaling-down ability, simple metal-insulator-metal (MIM) sandwich structure, excellent performances, and complementary metal-oxide-semiconductor (CMOS) technology-compatible fabrication processes make resistive random access memory (RRAM) one of the most promising candidates for the next-generation memory. The RRAM device also exhibits rich electrical, thermal, magnetic, and optical effects, in close correlation with the abundant resistive switching (RS) materials, metal-oxide interface, and multiple RS mechanisms including the formation/rupture of nanoscale to atomic-sized conductive filament (CF) incorporated in RS layer. Conductance quantization effect has been observed in the atomic-sized CF in RRAM, which provides a good opportunity to deeply investigate the RS mechanism in mesoscopic dimension. In this review paper, the operating principles of RRAM are introduced first, followed by the summarization of the basic conductance quantization phenomenon in RRAM and the related RS mechanisms, device structures, and material system. Then, we discuss the theory and modeling of quantum transport in RRAM. Finally, we present the opportunities and challenges in quantized RRAM devices and our views on the future prospects.",
"conclusion": "Conclusions In this paper, we explained the resistive switching mechanism and operating principles of filamentary RRAM and analyzed their connection with the conductance quantization effect. Then, we introduced some typical researches on the conductance quantization effect of RRAM. The device structures, switching material system, and the operating methods of RRAM related to conductance quantization effect were summarized in detail. Next, the theory and modeling of quantum transport in the atomic CF of RRAM ascribing to the conductance quantization effect were discussed. Finally, we evaluated the opportunities and challenges of the quantized CF system in RRAM devices for the multi-level storage and any other applications in the future.",
"introduction": "Introduction The persistent perusing of massive storage volume has been driving the scaling-down process of memory devices for decades. Memories characterized by low-power consumption and low fabrication cost are needed. Predominant flash memory has met a scaling-down limitation around 10-nm magnitude [ 1 , 2 ]. Therefore, intensive studies have been carried out in seeking for the next-generation memories. Resistive random access memory (RRAM) has become one of the most promising candidates for the next-generation memory [ 3 – 14 ] because of the intrinsic excellent scalability, simple metal-insulator-metal (MIM) structure, low fabrication cost, 3D integration feasibility, and promising performances in speed, power, endurance, retention, etc. RRAM stores information based on the resistive switching effect. Under appropriate external electrical field, the resistance state of the RRAM device can be reversibly switched between a high resistance state (HRS) or OFF-state and a low resistance state (LRS) or ON-state. There are two resistive switching modes, i.e., unipolar and bipolar switching operations under the same or opposite bias polarities, respectively, which are closely related to the different material systems and the different switching mechanisms. The resistive switching can be a uniform or localized phenomenon. Uniform switching proportionally scales with the total area of the switching material, while localized switching is usually based on the formation and disruption of conductive filament (CF). Abundant resistive switching materials, electrode materials, and their various interfaces are involved in RRAM switching mechanisms which are rather complex. Rich electrical, thermal, magnetic, and optical effects are therefore presented. Typical physical/chemical effects accompanied in resistive switching processes and in HRS/LRS states include electrochemical/thermochemical reactions [ 15 – 27 ], metal-insulator transition [ 28 , 29 ], magnetic modulation [ 30 – 47 ], etc. In this regard, the RRAM device can serve as a rich platform for studying the multiple physical/chemical effects. In the CF-type RRAM device, when the CF in the resistive switching (RS) layer is formed, RRAM changes to LRS. If the CF is ruptured, the device switches back to HRS. The formation and rupture of the CF can be understood as cation or anion migration under applied voltage companied by electrochemical reaction of the metal or oxygen vacancies. Therefore, CF is believed to be consisted of metal or oxygen vacancies. The dimension of the CF can be electrically modulated to be in the order of several tens to a few nanometers, which has been evidenced by the observation of high-resolution transmission electron microscopy (HRTEM) [ 20 , 48 – 60 ], scanning TEM (STEM) [ 59 ], and atomic force microscopy (AFM) [ 61 – 63 ]. In the localized filamentary switching, the scaling down of the RRAM device [ 64 ] would not influence its memory characteristics until the area is approaching the CF magnitude. As the CF size is in the range of nanoscale to atomic size, which is comparable to the mean free path (Fermi wavelength) of conduction electron, the scattering might be absent, resulting in ballistic electron transport [ 65 ] and the quantized conductance (QC) [ 66 – 68 ]. In recent studies, conductance quantization phenomena have been proved to exist in the atomic-sized CF in RRAM [ 69 – 72 ], and the interest for studying them continues. Revealing the QC effect is of great significance to deeply understand the physics of RS mechanism in mesoscopic dimension, which is important to control the performance, reliability, and variability [ 73 , 74 ] of RRAMs and to advance their practical application as non-volatile memories. At the same time, if the conductance quantization behaviors can be well modulated, it in turn can be utilized to realize the multi-level storage for ultra-high-density memory applications. Thus, summarizing and discussing the QC effect in RRAM is very necessary. In this review paper, we focus our attention on the recent development of the research on the QC effect in CF-based non-volatile RS devices including basic QC phenomenon in RRAM, RS mechanisms, device structures, materials, theory, and modeling of conductance quantization in RRAM."
} | 1,574 |
31813608 | PMC6926482 | pmc | 7,521 | {
"abstract": "Summary Bacterial lipo-chitooligosaccharides (LCOs) are key mediators of the nitrogen-fixing root nodule symbiosis (RNS) in legumes. The isolation of LCOs from arbuscular mycorrhizal fungi suggested that LCOs are also signaling molecules in arbuscular mycorrhiza (AM). However, the corresponding plant receptors have remained uncharacterized. Here we show that petunia and tomato mutants in the LysM receptor-like kinases LYK10 are impaired in AM formation. Petunia and tomato LYK10 proteins have a high affinity for LCOs ( K d in the nM range) comparable to that previously reported for a legume LCO receptor essential for the RNS. Interestingly, the tomato and petunia LYK10 promoters, when introduced into a legume, were active in nodules similarly to the promoter of the legume orthologous gene. Moreover, tomato and petunia LYK10 coding sequences restored nodulation in legumes mutated in their orthologs. This combination of genetic and biochemical data clearly pinpoints Solanaceous LYK10 as part of an ancestral LCO perception system involved in AM establishment, which has been directly recruited during evolution of the RNS in legumes.",
"introduction": "Introduction Arbuscular mycorrhiza (AM) is an ancient mutualistic symbiosis between Glomeromycota fungi and the majority of land plants, in which fungi provide plants with nutrients acquired from the soil in exchange for carbohydrates and lipids [ 1 , 2 ]. To colonize plant roots, arbuscular mycorrhizal fungi (AMFs) first cross epidermal and outer cortical cells and then spread inter- or intra-cellularly within roots. Inside inner root cortical cells, AMFs form highly branched structures called arbuscules, across which most nutrient exchange takes place. In the more recent nitrogen-fixing root nodule symbiosis (RNS) that occurs between legumes and rhizobia, the bacteria can fix gaseous nitrogen inside the root nodules. Although the microorganisms are different between these two endosymbioses, the RNS is thought to have evolved through recruitment of genes implicated in the more ancient AM [ 3 ]. Nodule organogenesis and bacterial colonization rely on the secretion of lipo-chitooligosaccharide (LCO) signaling molecules by rhizobia [ 4 ]. All the rhizobial LCOs have a core structure of 4/5 N -acetyl glucosamine (GlcNAc) units of which the terminal non-reducing sugar is substituted with an acyl chain. Additional substitutions, which are important for host specificity, are characteristic of each bacterial strain [ 5 ]. Rhizobial LCOs are perceived by Lysin motif receptor-like kinases (LysM-RLKs) that are encoded by a multigenic family, some of which have the ability to bind LCOs [ 6 , 7 , 8 ]. Members of the LysM-RLK LYRIA phylogenetic group ( Figure S1 A) [ 9 ], such as Medicago truncatula NFP ( MtNFP ) or Lotus japonicus NFR5 ( LjNFR5 ), are required for activation of a signaling pathway leading to oscillations of the nuclear Ca 2+ concentration (Ca 2+ spiking), nodule organogenesis, and bacterial colonization [ 10 , 11 , 12 ]. Two lines of evidence suggest that AM establishment also involves LCO-mediated signaling. The first line is the identification of LCOs from AMFs, and the second is the identification of potential plant LCO receptors. LCOs isolated from AMFs by Maillet et al. (hereafter collectively referred to as Myc-LCOs) have a core structure similar to the rhizobial LCOs and can be sulfated or not on the reducing sugar [ 13 ]. Exogenous application of these Myc-LCOs both increases the level of AMF root colonization [ 13 ] and activates Ca 2+ spiking in various plant species [ 14 , 15 ]. Short-chain chitooligosaccharides (COs) produced by AMFs can also activate Ca 2+ spiking [ 16 ], indicating that both LCOs and short-chain COs have the potential to be involved in partner recognition during AM. However, whether Myc-LCOs and/or short-chain COs are indeed involved in AM establishment is not known. Several LysM-RLKs ( Parasponia andersonii PanNFP1 and/or PanNFP2 , tomato SlLYK10 and SlLYK12 , Medicago truncatula MtLYK9 , and rice OsCERK1 ) have been shown to be involved in AM [ 17 , 18 , 19 , 20 , 21 , 22 ], but their LCO/CO binding properties have not been determined so far. SlLYK12, MtLYK9 , and OsCERK1 belong to the LYKI phylogenetic group ( Figure S1 B [ 9 ]). These LysM-RLKs are likely co-receptors, since MtLYK9 and OsCERK1 have a dual function in AM and defense [ 19 , 20 , 23 ], and OsCERK1 is involved in perception of various ligands including short-chain COs, chitin, and peptidoglycan [ 24 , 25 , 26 ], the latter two being components of fungal and bacterial cell walls, respectively, known as plant defense elicitors. The other LysM-RLKs known to control AM belong to the LYRIA group that contains members only in plant species that establish AM and/or RNS [ 27 , 28 ]. In tomato, virus-induced silencing of the unique LYRIA gene ( SlLYK10 ) resulted in significantly lower levels of AM colonization [ 21 ]. Although the current hypothesis is that the RNS evolved by coopting genes involved in the AM [ 3 ], it is unclear how LCO receptors may have evolved to become key players in RNS establishment. Here, we functionally characterize LCO receptors from Solanaceae, a plant family that establishes AM but not RNS. We use heterologous expression in legumes to infer an evolutionary scenario of LCO receptor recruitment for RNS. Our data suggest that non-legume LYRIA genes encode LCO receptors involved in AM and that the transcriptional regulation required for LCO receptor function in RNS has been directly co-opted from AM.",
"discussion": "Discussion Myc-LCOs can induce gene transcription, Ca 2+ spiking, and root branching [ 13 , 14 , 15 , 41 , 42 ]. However, until now it was not clear whether they are involved in AM establishment. Here, we demonstrate high-affinity LCO-binding properties of PhLYK10 and SlLYK10, which, together with the mycorrhizal phenotype of the Phlyk10 - 1 and Sllyk10 - 1 mutant lines, provide the strongest evidence to date that Myc-LCOs are directly involved in AM establishment. Detailed characterization of PhLYK10 and SlLYK10 revealed that they are high-affinity LCO-binding proteins that discriminate LCOs versus COs; their affinity for LCOs being as high as that of the previously characterized legume LYRIA protein, LjNFR5, expressed in the same heterologous system [ 8 ]. SlLYK10 recognized the Myc-LCO structures described in [ 13 ] with similar affinity for sulfated and non-sulfated Myc-LCOs. However, SlLYK10 exhibited a higher affinity for LCO-V(C18:1,NMe,S) compared with the published Myc-LCO structures, indicating that such LCOs or related structures could potentially represent additional Myc-LCOs. The similarity of the AM phenotype in the petunia line knockout for PhLYK10 , the tomato line bearing a point mutation in SlLYK10 , and the tomato SlLYK10 -silenced plants [ 21 ] provides compelling evidence that the LYRIA gene is involved in AM establishment in Solanaceae. Reduction in the number of colonization sites in the above-mentioned plants suggests a role at early stages for AMF penetration in roots. Moreover, the aberrant arbuscule development observed in Phlyk10 - 1 and SlLYK10 -silenced plants suggests an additional role in arbuscule development. The activity of the SlLYK10 promoter in tomato roots initially in the epidermis and upon colonization in arbuscule-containing cells further supports a role of the LYRIA gene at several steps of AM establishment in Solanaceae. Although Phlyk10 - 1 , Sllyk10 - 1 , and the SlLYK10 -silenced plants are affected in AM establishment, AMFs can still colonize roots and form arbuscules. In a mutant of the rice LYRIA gene OsNFR5 , AM-marker gene expression was decreased, but the number of AMF colonization sites was not affected [ 18 ]. Mutants in MtNFP are also colonized normally by AMFs [ 19 , 43 ] despite an almost complete block of symbiosis-related responses to both rhizobial LCOs and Myc-LCOs [ 13 , 14 , 43 , 44 ]. Moreover, a double mutant in the two LYRIA genes LjNFR5 and LjLYS11 was not affected in AM establishment [ 45 ]. Altogether, this suggests redundancy at the level of LCO perception or that other signals could activate the LCO-mediated signaling pathway. Indeed, Ca 2+ spiking can be measured in an Mtnfp mutant after treatment with CO4 [ 16 ], suggesting that short-chain CO receptors are also involved in AM establishment. Other signals such as karrikin-like molecules and effector proteins produced by AMFs are known to play important roles in plant-AMF communication [ 46 ], but the connection of their perception and/or mode of action to LCO-mediated signaling remains elusive. It has been postulated that RNS has evolved through recruitment of genes implicated in AM, but it is unclear how the LCO perception machinery may have been affected by the evolution of RNS. Our data are compatible with a scenario in which an ancestral LYRIA gene involved in LCO perception in AM was directly recruited for LCO perception for RNS in legumes ( Figure 7 ). Because both symbiotic interfaces are intracellular, it can be proposed that LYRIA genes participate in these conserved accommodation mechanisms [ 47 ]. The promoters of the single LYRIA gene from the Solanaceae or from the legume M . pudica have the ability to drive dual expression both in mycorrhizal roots and in nodules of M . truncatula . In contrast, the LYRIA gene pairs in the legumes Medicago and Lotus , MtNFP/LjNFR5 , and MtLYR1/LjLYS11 have retained transcriptional regulation only during nodulation or AM, respectively [ 10 , 36 , 45 ]. This is indicative of promoter sub-functionalization following the whole genome duplication that predated the radiation of the Papilionoideae, the legume clade to which Medicago and Lotus belong ( Figure 7 ). Interestingly, RNS is evolutionarily more stable in Papilionoideae than in any other clade of RNS-forming plants, including the Mimosoideae to which Mimosa belongs [ 48 ]. In other words, the probability for a given species in the Papilionoideae to lose RNS is much lower than in other clades. Although the reason for this greater stability remains unknown, one possibility is that duplication and sub-functionalization of genes with a dual function in AM and RNS such as the LYRIA genes, for separated functions in AM and RNS, may have allowed stabilized symbiotic associations. Figure 7 Proposed Scenario for Evolution of the LYRIA Genes (1/) Ancestral LYRIA genes were involved in AM. (2/) When the RNS appeared, LYRIA genes had a dual function in AM and RNS in legumes. (3/) After gene duplication, LYRIA genes were sub-functionalized for a role in RNS or in AM. Shown are putative (observed in the M . truncatula heterologous system) or known (bold, demonstrated in the endogenous system) expression in mycorrhizal roots (AM) and/or nodules (RNS). Putative or known (highlighted) role in AM and/or RNS are shown. Ph , Petunia hybrida; Sl , Solananum lycopersicum (tomato); Mp , Mimosa pudica ; Mt , Medicago truncatula ; and Lj , Lotus japonicus . The AAAGCTANNGACA sequence conserved in LYRIA promoters could represent an ancestral cis -regulatory element involved in transcriptional regulation during AM that has been recruited for transcriptional regulation during RNS. This putative cis -regulatory element is, however, conserved in the promoters of both paralogous LYRIA genes from the Papilionoideae, suggesting that sub-functionalization of the LYRIA promoter pairs has not occurred through divergence in this sequence. Further studies are required to validate the function of this putative cis -regulatory element and to identify the mechanism of LYRIA promoter sub-functionalization in Papilionoideae. Strikingly, the Solanaceae LYRIA proteins PhLYK10 and SlLYK10 can restore the full nodulation program in the legume LYRIA mutants Mtnfp and Ljnfr5 , although with lower efficiency than the respective endogenous LYRIA genes MtNFP and LjNFR5. This suggests that the legume and non-legume LYRIA proteins can fulfill the function of endogenous LYRIA proteins for both nodule formation and rhizobial colonization. Lower complementation efficiency of SlLYK10, PhLYK10, and PsSYM10 compared with MtNFP correlated with lower levels of protein detected in complemented Mtnfp roots. However, lower complementation efficiency of heterologous LYRIA proteins in Mtnfp and Ljnfr5 may also be due to inefficient interactions with the respective co-receptors MtLYK3 and LjNFR1, two LysM-RLKs belonging the LYKI group. It has been suggested that evolution of the LYRIA gene for a new role in RNS may have involved a tandem gene duplication (preceding the advent of RNS) followed by neofunctionalization of one copy for RNS and loss of other copy in the species that acquired the RNS [ 49 ]. However, our results suggest that both the promoter and the CDS of the ancestral non-duplicated LYRIA gene were already fully competent for both symbioses. Intriguingly, our results raise the question of how signal specificity in AM and RNS may be encoded. The fact that PhLYK10 can complement both Mtnfp and Ljnfr5 for nodule formation while M . truncatula and L . japonicus can specifically recognize the respective major LCOs produced by Sinorhizobium meliloti (LCO-IV(C16:2,S) [ 50 ] and Mesorhizobium loti (LCO-V(C16:1,Cb,Fuc,Ac) [ 51 ] argues for limited LCO selectivity of MtNFP, LjNFR5, and their Solanaceous orthologs PhLYK10 and SlLYK10. This questions the hypothesis that MtNFP and LjNFR5 recognize specific LCO structures and suggests that co-receptors such as MtLYK3/LjNFR1, or yet unidentified proteins, may interact with MtNFP and LjNFR5 to confer LCO binding specificity to LCO receptor complexes. Consistent with such a scenario, the number of LysM-RLKs in the LYKI group has dramatically increased in legumes compared with non-legumes and contains a legume-specific subgroup to which MtLYK3 and LjNFR1 belong [ 52 ]."
} | 3,519 |
28973575 | PMC5538326 | pmc | 7,522 | {
"abstract": "Abstract Lignin impedes access to cellulose during biofuel production and pulping but trees can be genetically modified to improve processing efficiency. Modification of lignin may have nontarget effects on mechanical and chemical resistance and subsequent arthropod community responses with respect to pest susceptibility and arthropod biodiversity. We quantified foliar mechanical and chemical resistance traits in lignin-modified and wild-type (WT) poplar ( Populus alba × Populus tremula ) grown in a plantation and censused arthropods present on these trees to determine total abundance, as well as species richness, diversity and community composition. Our results indicate that mechanical resistance was not affected by lignin modification and only one genetic construct resulted in a (modest) change in chemical resistance. Arthropod abundance and community composition were consistent across modified and WT trees, but transgenics produced using one construct exhibited higher species richness and diversity relative to the WT. Our findings indicate that modification of lignin in poplar does not negatively affect herbivore resistance traits or arthropod community response, and may even result in a source of increased genetic diversity in trees and arthropod communities.",
"discussion": "Discussion Genetic modification of lignin content and composition had no detectable effect on mechanical resistance and only a moderate effect on chemical resistance traits. Modification of lignin did not significantly influence arthropod abundance or community composition, but did affect species richness and diversity. Richness and diversity were highest on the “reduced-lignin” trees (construct 1049) relative to all other trees. In short, moderate effects of lignin modification on defense translated to mostly insubstantial effects on arthropod communities. In contrast to our predictions, we found trends toward higher mechanical resistance in our “reduced-lignin” trees (construct 1049) relative to all other modified and WT trees. This finding reinforces the notion that reducing S and G content may not result in total lignin reduction due to a compensatory increase in H lignin. Because H lignin is naturally present in such trace amounts in Populus , we did not expect a large effect on H content in response to reduction of S and G content. Modification of lignin content or composition also did not substantially alter levels of chemical resistance. The only transgenic trees exhibiting altered chemical resistance relative to the wild type were the “low-S” trees (construct 1036). We conclude that these modifications did not have substantial effects on mechanical or chemical defenses in poplar but we caution that this may not be the case for other lignin modifications and each must be evaluated separately. Modification had no effect on mechanical resistance and only a moderate effect on chemical resistance, and as a consequence, whole arthropod community response did not substantially vary among our modified and WT trees. Species richness and diversity were the only arthropod response factors that varied among our trees. We documented higher species richness and diversity on our “reduced-lignin” trees (construct 1049) relative to all other modified and WT trees. As mentioned previously, 1,049 trees were modified for reduced lignin but levels of foliar lignin did not differ between 1,049 and WT trees, possibly due to increases in H lignin. Neither reduced mechanical nor chemical resistance could be implicated as mechanisms underlying higher arthropod species richness and diversity on trees produced using this construct over all other engineered trees. Higher species richness and diversity may have resulted from factors influencing herbivore attraction rather than resistance. Determinants of host–plant preference include moisture content, olfactory stimuli (i.e., volatiles), and visual stimuli (e.g., apparency, coloration, architecture; Williams 1954 , Patt and Sétamou 2007 ). We did not, however, observe noticeable physical differences in appearance among our experimental trees. Arthropod community composition was statistically similar among modified and WT trees, although some noticeable trends emerged in “low-S” trees (construct 1034). Composition of functional groups on trees engineered with this construct shifted toward more generalist pests and fewer natural enemies, relative to composition on all other transgenic and WT trees. Abundance, but not richness and diversity, of generalists and natural enemies differed between trees produced using construct 1034 and all other transgenic and WT trees. Although not significant, low abundance of natural enemies on 1,034 trees may have resulted in more generalist pests. As with trees produced using construct 1034, those produced with construct 1036 were also modified for reduced S lignin but the latter did not demonstrate a similar trend in functional group composition. This observation speaks to the variable outcomes possible for trees with similar modifications. Genotype is known to determine chemical profiles in plants, which, in turn, influence arthropod community composition ( Fritz and Simms 1992 , Wimp et al. 2007 , Robinson et al. 2012 ). Variation in chemistry across genotypes (in this case, genetically modified trees), however, is not always sufficient to influence arthropods ( Brown 1956 , Prittinen et al. 2003 , Donaldson and Lindroth 2004 ). Levels of some chemical resistance traits varied among our modified and WT trees by as much as 53%, but these differences were insufficient to translate to effects on arthropods. Genetic modification has proved to be beneficial for the enhancement of target traits in biofuel and forestry crops ( James 2008 , Mannion and Morse 2012 ). The ultimate goal of lignin modification is to improve the efficiency of lignin extraction, but such work should also attempt to avoid disruption of plant–arthropod dynamics. Genetic enhancement of crops is a valuable tool but may come at a cost if pest susceptibility or arthropod ecosystem services are negatively affected. The arthropod communities identified in this study represent what might be expected in one cycle of a short-rotation coppice plantation of lignin-modified poplar ( Figs. 4 and 5 ). Results from this research suggest that genetic modification of lignin in Populus does not substantially alter nontarget traits in leaves that confer resistance against arthropod pests or negatively influence arthropod communities."
} | 1,633 |
35023908 | PMC8744080 | pmc | 7,523 | {
"abstract": "In the marine environment, coastal nutrient pollution and algal blooms are increasing in many coral reefs and surface waters around the world, leading to higher concentrations of dissolved organic carbon (DOC), nitrogen (N), phosphate (P), and sulfur (S) compounds. The adaptation of the marine microbiota to this stress involves evolutionary processes through mutations that can provide selective phenotypes. The aim of this in silico analysis is to elucidate the potential candidate hub proteins, biological processes, and key metabolic pathways involved in the pathogenicity of bacterioplankton during excess of nutrients. The analysis was carried out on the model organism Escherichia coli K-12 , by adopting an analysis pipeline consisting of a set of packages from the Cystoscape platform. The results obtained show that the metabolism of carbon and sugars generally are the 2 driving mechanisms for the expression of virulence factors.",
"conclusion": "Conclusions Transcriptomic data are increasingly numerous and varied, facilitating data mining at a system level. A large number of approaches/tools have been developed to detect pathways and processes that are significantly altered between different experimental conditions during stress by pollutants or other substances. The objective of this work is to study the capacity of bacterioplankton during eutrophication and algal blooms in the model organism E coli K12 , through the analysis of a profile of DEGs collected from several bibliographic sources to predict hub proteins, BP and MP involved in copiotrophic species selection, and bacterioplankton virulence. The obtained results suggested that the metabolic behavior and central BPs are strongly correlated with carbon and carbohydrate metabolism, contributing to the progression of complications that can affect the cellular behavior and phenotype of bacterioplankton. The involvement of hub proteins related to carbohydrate, protein, nucleic acid metabolism, and membrane transport has been reported in the selection of copiotrophic and pathogenic species during excess of nutrients, but these findings require further study. The bacterial stress adaptation of E coli to excess nutrients and the possibility of increased virulence associated with stress need to be studied in more detail to prevent potential risks of host-microbiota interactions. This is important because understanding the mechanisms and regulation of bacterioplankton stress adaptation will provide information for pathogen control and enhance the effective design of new control methods. Furthermore, the identification of moonlight proteins is clearly not an easy process as most of the currently identified bacterial moonlight proteins were discovered by chance. Today, researchers are using antimicrobial susceptibility testing to address the problem of multidrug resistance by Gram-positive and Gram-negative commensal and pathogenic bacteria. But questions arise as to their use in the treatment of pathogenesis in aquatic habitats. In aquatic environments, the use of such strategy has often been associated with aquaculture. Moreover, with the mechanisms of microbial evolution, their adaptations, the poor practices of treatment, and discharge of microbes in some laboratories in developing countries and the discharge of wastewater into aquatic environments, such a process suggests the development and diffusion of resistance genes to biomolecules (phenolic compounds) through horizontal and vertical transfers while creating a new problem to be solved but in the long term.",
"introduction": "Introduction In recent decades, the emergence of molecular methods, especially the omics approach, has facilitated the study of microbial communities to understand their activities, compositions, interactions between taxa, and the use of nutrients. \n 1 \n Transcriptomics has often been coupled with other methods to understand the response of microbes to ecological interactions, nutrient acquisition, membrane transport, and growth, generating a large number of results that require strong tools to derive useful information. 2 , 3 The marine coastal areas are increasingly subjected to anthropogenic and natural pollutants that affect the growth of macroorganisms and microorganisms. \n 4 \n Bacterioplankton has been linked to several types of pollution including wastewater, 5 , 6 chemicals, \n 7 \n organic or biological products, and waste. \n 8 \n During nutrient pollution (NP) caused by excess of nutrients specifically in coastal areas, the biota is negatively affected by algal blooms, increased growth of macroalgae, increased sedimentation and oxygen consumption, oxygen depletion in lower water layers and, sometimes, mortality of benthic animals and fish. \n 9 \n Through these negative effects, the bacterioplankton also undergoes several types of stress that act directly and indirectly on the functioning of the ecosystem and the microbiota. \n 10 \n This stress is caused by the higher concentrations of dissolved organic carbon (DOC), Nitrogen (N), Phosphate (P), and Sulfur (S) compounds, 11 , 12 to which the adaptation of bacterioplankton depends on the community structure, the physiology of the organisms, the variety of environmental conditions, and their interactions. 13 , 14 To survive changing environments, bacteria have evolved exquisite systems that not only sense stress but also trigger appropriate responses. \n 15 \n Their responses are related to an adaptation that involves a known resistance process especially in pathogenic bacteria such as the case of Listeria monocytogenes and a direction also of the expression of virulence genes at the appropriate time and place. 16 , 17 An appreciation of stress responses and their regulation is therefore essential to understand bacterial pathogenesis. Among the modules of understanding used is the analysis of changes at the molecular and cellular level regulated by highly complex signaling pathways. \n 18 \n The whole is modulated in the form of protein-protein interaction (PPI) networks and other resulting networks because the phenomenon of protection against stress strongly suggests the presence of central proteins that control the various responses to stress. \n 19 \n The study of PPI networks requires several open source or integrated software packages that allow the integration of biomolecular interaction networks with high-throughput expression data and other molecular states in a unified conceptual framework. \n 20 \n Cytoscape is a powerful platform in this field, with its various plugins and its conjunction with large databases, it allows the extraction of central processes, central metabolic pathways (MPs), and hubs proteins during a particular stress in humans and model organisms. 21 - 23 The investigation of interactomes in model organisms such as Arabidopsis thaliana (L.) , \n 24 \n \n Saccharomyces cerevisiae (Meyen), and Escherichia coli K-12 \n 25 \n has been involved in predicting and improving the understanding of cellular processes and biological interactions in other organisms. 26 , 27 Furthermore, the power of Cytoscape plugins in the analysis of microbiota has been documented in several works and in different microbiomes including intestinal, \n 28 \n oral, \n 29 \n vaginal, \n 30 \n and marine. 31 , 32 The study of the behavior of bacterioplankton during nutrient excess as one of the environmental parameters that affect its capacity of pathogenesis is not well documented and has never been analyzed in silico. In this work, we want to study this capacity during eutrophication and algal blooming in the model organism Escherichia coli K12 , through the analysis of a profile of differentially overexpressed genes (DEGs) collected from several bibliographic sources to predict hubs proteins, biological processes (BPs), and MPs involved in the selection of copiotrophic species and the virulence of bacterioplankton.",
"discussion": "Results and Discussion String results The list of 196 collected proteins ( Table 1 ) was imported and analyzed by the StringApp. This latter has mapped and annotated all the genes right away. The results were performed in the format of a network with different evidence indexes ( Figure 2 ), and the PPI networks obtained have identified 7 associated networks with a total of 165 out of 196 nodes, 442 edges, and a P value <10 − 16 . The 165 annotated proteins in the principal network are linked either directly or indirectly through one or more interacting proteins, which enhances the existence of functional links between them. These results suggest that the proteins are at least partially biologically connected as a group, maybe participate together in the same process and have the same phenotype, which has given great importance to co-expression and high weight to genetic and protein interactions. Figure 2. Predicted protein-protein interaction networks. Parameters: Score (0.4), no additional nodes; interaction sources used: experimentation, databases, co-expression, co-occurrence, gene fusion, and neighborhood. In the interaction networks, separate lines of different colors are used to show the type of evidence that supports each interaction. The obtained PPI network was accompanied by a global functional enrichment analysis where BP, hub proteins, and MPs were exported. The results of the most 5 representative terms are shown in Table 2 , where GO terms are generation of precursor metabolites and energy (GO.0006091), monocarboxylic process (GO:0032787), nicotinamide and metabolic process (GO:0046496), antibiotic metabolic process (GO:0016999), and small molecule biosynthetic process (GO:0044283), and the most significant MP are carbon metabolism (eco01200), pyruvate metabolism (eco00620), glycolysis/gluconeogenesis (eco00010), pentose phosphate pathway (eco00030), and methane metabolism (eco00680). These BPs and MPs involve biochemical reactions and pathways that ultimately lead to the formation of precursor metabolites and substances from which energy is derived. 39 - 44 This energy production is essential for the regulation of nutrient content during stress, to persist long enough, continue its cycle, and invade a new host. \n 45 \n Table 2. Most representative GO terms of biological processes and their associated pathways. Category GO term Description FDR value Number of genes GO Process GO:0036091 Generation of precursor metabolites and energy 9.48E-36 44 GO:0032787 Monocarboxylic process 3.12E-21 34 GO:0046496 Nicotinamide and metabolic process 1.1E-20 21 GO:0016999 Antibiotic metabolic process 9.2E-20 23 GO:0044283 Small molecule biosynthetic process 8.82E-15 32 GO:0036006 Glucose metabolic process 3.45E-14 14 KEGG Pathway eco01200 Carbon metabolism 1.14E-57 51 eco00620 Pyruvate metabolism 3.57E-26 25 eco00010 Glycolysis/gluconeogenesis 1.16E-20 20 eco00030 Pentose phosphate pathway 1.52E-18 17 eco00680 Methane metabolism 1.79E-16 15 eco00020 Citrate cycle (TCA cycle) 2.48E-16 15 Simultaneously, the 10 genes chosen as hub proteins ( Table 3 ) based on their combined score and their connectivity in Figure 2 , which shows a co-expression profile, neighborhood, and appearance links between them and between ( eno, ftsH, ravA, codA, hemN/yggW, puuD, codA, mngB, norV, can ) that encoded for virulence factors such as ferrochatalases, metalloenzymes, enolases, hydrolases, and cytotoxic chemotherapeutic agents. These factors are often linked to MPs for nutrients and toxins such as lipopolysaccharides, proteases (zinc metalloproteases), and virulence factors induced by sugar metabolism in bacteria. 46 , 47 Table 3. List of top 10 hub proteins with their betweenness centrality (BC) and degree values. Row Gene name Protein name BC Degree 1 \n pfo \n Probable pyruvate-flavodoxin oxidoreductase 0.16 36 2 \n pykF \n Pyruvate kinase I (formerly F) 0.03 29 3 \n gltA \n Citrate synthase 0.05 28 4 \n glcB \n Malate synthase G 0.02 27 5 \n pgi \n Glucose-6-phosphate isomerase 0.04 26 6 \n maeB \n NADP-dependent malic enzyme 0.02 25 7 \n aceE \n Pyruvate dehydrogenase E1 component 0.02 23 8 \n ptA \n Phosphate acetyltransferase 0.02 22 9 \n tktB \n Transketolase 2 0.02 21 10 \n aceF \n Dihydrolipoyllysine-residue acetyltransferase component of pyruvate dehydrogenase complex 0.008 20 Kennelly and Potts (1996) have stated that during stress conditions, microorganisms develop signal transduction systems from the outside to the inside of the cell. \n 48 \n These signals include degradative enzymes such as proteases, lipases, and substrate capture enzymes such as glutamine synthetase and alkaline phosphatase to detect environmental stresses and to control the coordinated expression of genes involved in cellular defense mechanisms. 49 - 51 Their response to these signals will enable their survival; enhance their resistance to a number of environmental stresses such as low pH, heat, and oxidative stress; 52 , 53 and/or enhance their virulence. This is relatively true because Gram-positive bacteria especially Actinobacteria and Firmicutes present a diverse collection of regulatory proteins ( CcpA, CodY, and Rex ) of central metabolic capacities and virulence, which have been shaped by reductive evolution. 45 , 54 , 55 Among these Gram-positive bacteria is Staphylococcus aureus ( S aureus ), a strain indigenous to aquatic environments and thus transferred by discharges. In the presence of excess carbon, the regulatory protein CcpA stimulates transcription of ilvB operon, making CodY more active as a repressor of many pathways that remove intermediates from glycolysis and gluconeogenesis to be fully pathogenic. \n 45 \n And in Gram-negative bacteria, regulation is stimulated by FNR which is influenced by the histone-like protein H-NS ; nevertheless, FNR has been shown to be important for virulence and survival of Salmonella . 15 , 56 In the light of the above discussed results, we suggest that the metabolic behavior and central BPs are highly correlated with nutrient metabolism, contributing toward the progression of complications that can affect cell behavior and bacterioplankton phenotype, because as it has been mentioned, the growth of microorganisms in a non-optimal environment suggests evolutionary adaptations through specific mutations responsible for a physical form. \n 57 \n In addition, the involvement of hub proteins related to carbohydrate metabolism, proteins, nucleic acids, and membrane transport have been reported in the selection of copiotrophic and pathogenic species, 34 , 58 but these results require further studies because the existing research to date has not thoroughly evaluated the 4 nutrients (C, N, P, and S) together. Subselection and network analyzer results The network generated by string software was imported as a pre-existing unformatted array in Cytoscape software. The network analyzer plugin function was used for providing network filtration and customization. The principal subnetwork obtained ( Figure 3 ) provides 72/165 nodes with a confidence score of 0.8 and a PPI enrichment P value <10 − 16 . The list of 72 genes was filtered and 10 hub proteins were subselected ( Table 3 ). All of these genes exhibit the highest interactions between them to regulate some cellular functions. Indeed, several studies have demonstrated the key role of these enzymes in microbial metabolism such as glycolysis/gluconeogenesis, \n 59 \n pyruvate metabolism, \n 60 \n secondary metabolite biosynthesis, carbon metabolism, \n 61 \n and other fundamental intracellular processes. These results would be linked to the virulence of bacteria in the presence of an excess of nutrient. \n 59 \n According to this work, other studies have suggested that these enzymes are considered moonlight proteins and are involved in microbial virulence. 46 , 47 , 62 , 63 Figure 3. Topological mapping of the hub proteins obtained in the subselection analysis based on the cutoff value BC <0.02 and node degree >20. The larger circles correspond to the higher degrees and brown to blue color refers to increment of betweenness; the thickness of the lines represents the confidence score of the associations and different colors are used to show the type of evidence that supports each interaction . ClueGO results ClueGOapp was launched by an ontological and metabolic analyses to evaluate over-represented GO terms and MP by annotating subselected proteins and their first neighbors in biological terms hierarchically (parent-child relation) and to assign them to functional MP pathways. The results are presented as a pie chart ( Figure 4 ) for BP and a functionally grouped network ( Figure 5 ) for MP, and 80 terms were associated with the 72 proteins. The major representative terms for GO processes are the metabolic process of small molecules, the catabolic process of organic substances, the metabolic process of carbohydrates, the metabolic process of alpha-amino acids, and the positive regulation of biological process; the major representative terms for MP are glycolysis/glycogenesis, pyruvate metabolism, the 2-component system, purine metabolism, and oxidative phosphorylation for MPs. Figure 4. Predicted functional enrichment pie chart for the GO BPs by ClueGO. Figure 5. In ClueGO, metabolic pathways were predicted from KEGG as a network with the terms of the enriched pathways visualized using Cytoscape’s ClueGo/CluePedia plugin where several proteins share common functions. The size of the nodes corresponds to the importance of the metabolic pathway. The ClueGO results are consistent with those provided by StringApp, which also involve biochemical reactions and pathways that ultimately lead to the formation of precursor metabolites and substances from which energy is derived and most of them refers to the MPs of the purine and citrate cycle (tricarboxylic acid [TCA] cycle). The metabolic process of purine seems to be a widespread phenomenon. \n 64 \n It has been found to be a key modulator in virulence of pathogens. \n 65 \n The TCA cycle, also known as the citric acid cycle or Krebs cycle, produces energy by the complete oxidation of acetate, derived from carbohydrates, fats and proteins, to carbon dioxide. \n 66 \n In Table 2 , 51 out of 165 proteins were assigned to carbon metabolism, which suggests it as the central metabolic process and the main nutrient during eutrophication. Deutscher et al and Görke and Stülke reported the binding of carbon catabolism to microbial virulence. 67 , 68 Excessive carbon sources and DOC were documented as enhancers of bacterial growth, oxygen removal, and selector for copiotrophs and opportunistic pathogens in both seawater and coral holobiota 69 , 70 using their preferred carbon substrate through ATP-binding cassette (ABC) transporters. 71 , 72 The ABC transporters were reported in studies involving genes related to virulence and symbiotic interactions \n 73 \n and highly reported in copiotrophs to the opposites of oligotrophs. \n 74 \n Haas et al \n 75 \n reported the abundance of Gammaproteobacteria and Alphaproteobacteria in enriched and algal-dominated waters in contrast to coral-dominated oligotrophic waters, and this suggests the possible adaptation of the studied bacterioplankton in case of existence in such an environment, but all this needs further study and discussion to draw strong conclusions. In Figure 5 , many proteins are multitasking and provide at least 2 MPs, which reminds us of moonlighting proteins. The existence of moonlighting proteins in microorganisms is a known, but still poorly understood phenomenon. \n 76 \n Most of these proteins exercise their role in the cytoplasm and outside the cell. Their existence has been linked to virulence and they are often domestic enzymes, especially those of the glycolytic pathway, such as enolase, aldolase, dehydrogenase, heat shock proteins, and transcription factors, and they may perform non-catalytic roles with different functions depending on their cellular localization and the concentration of substrates. \n 62 \n In the analyzed differential gene expression (DGE) profile, pyruvate metabolism, \n 60 \n carbon metabolism, \n 61 \n and glycolysis/gluconeogenesis \n 59 \n ( Figure 5 ) are central glycolytic MP that involved moonlight proteins and are related to virulence in bacteria. Taken together, the analyses of BP and MP ( Figures 4 and 5 ) reveal that the interconnected proteins during the nutrient excess and the bloom proliferation phase in the model organism E Coli K12 are involved in chemical reactions and cellular metabolism involving carbohydrates and organic acids. Thus, several studies have reported the relationship between moonlight proteins, carbon catabolism, and microbial virulence factors. 67 , 68 In addition, the involvement of hub proteins related to carbohydrate metabolism, proteins, nucleic acids, and membrane transport has been reported in the selection of copiotrophic and pathogenic species. 34 , 58"
} | 5,231 |
30018464 | PMC5989813 | pmc | 7,525 | {
"abstract": "A novel design of microbial fuel cells (MFC) fuelled with undiluted urine was demonstrated to be an efficient power source for decentralised areas, but had only been tested under controlled laboratory conditions. Hence, a field-trial was carried out to assess its feasibility for practical implementation: a bespoke stack of 12 MFC modules was implemented as a self-sufficient lit urinal system at UK's largest music festival. Laboratory investigation showed that with a hydraulic retention time (HRT) of 44 h, a cascade of 4 modules (19.2 L displacement volume) was continuously producing ≈150 mW. At the same HRT, the chemical oxygen demand (COD) was reduced from 5586 mg COD·L −1 to 625 mg COD·L −1 . Field results of the system under uncontrolled usage indicate an optimal retention time for power production between 2h30 and ≈9 h. When measured (HRT of ≈11h40), the COD decreased by 48% and the total nitrogen content by 13%. Compared to the previous PEE POWER ® field-trial (2015), the present system achieved a 37% higher COD removal with half the HRT. The 2016 set-up produced ≈30% more energy in a third of the total volumetric footprint (max 600 mW). This performance corresponds to ≈7-fold technological improvement.",
"conclusion": "4 Conclusions The results from the Glastonbury trial demonstrate that the performance of the system followed the projections stemming from the laboratory investigation. With regard to the amount of urine produced daily (∼1200L), only ∼220L fuelled the MFCs stack whilst the remaining ∼980L was unused and piped away through the system's overflow. To accommodate such an amount, the MFC stack should have comprised 60–70 modules. Since the power produced by 12 modules (424 ± 36 mW) was below the requirement for the 2.544 W lighting system, it can be projected that a stack of 60–70 modules would power a lighting system of ≈6–7 W. In such a case, the challenge would be to homogenise fuel distribution. For a PEE POWER ® system which would directly discharge the effluent to the environment, the results indicate that: i) the legal COD levels could be reached with an HRT of ∼64 h, and ii) a 4-modules cascades is yet insufficient to reach the total nitrogen concentrations allowing such direct discharge. However, to the authors' best knowledge, the MFC is the only biotechnology able to directly treat neat urine – with no dilution at any step of the process, and without inhibition due to high nitrogen concentrations – within this level of efficiency and with energy production (i.e. not energy consumption), which is the case for the majority of other biological technologies or processes. Overall, although results from this study show that there is still room for improvement before any commercial deployment, the MFC technology is sufficiently mature to be introduced as a carbon neutral pre-treatment system that would positively impact liquid waste stream management in urban, as well as rural areas. Moreover, the results in this study strengthen the thesis that MFCs can act as a power supply in decentralised areas.",
"introduction": "1 Introduction Microbial fuel cells (MFCs) are energy transducers, first reported in 1911 [ 1 ], which produce electricity through the bio-electro-oxidation of organic compounds. Over the last two decades, during which research in the field has intensified, oxygen has become the most common end-terminal electron acceptor in the cathode, due to its availability and high redox value [ [2] , [3] , [4] , [5] ]. Individual MFCs produce relatively low levels of power, hence a plurality of units must be assembled in stacks to reach useful power levels [ 6 , 7 ]. However, deploying MFC stacks in real environments presents two main challenges: cost and complexity. Self-stratifying membraneless MFCs (SSM-MFC) have been shown to address such a dual need [ 8 ]. At the same time, SSM-MFCs have demonstrated the capacity to be scaled-up in size, up to a certain extent, without significant power density losses [ 8 ]. The principle behind SSM-MFCs is to employ the ability of microorganisms to vertically self-stratify across physicochemical conditions of any given water column (e.g. lake, or urine). In such a column, cathodes are placed on the top whilst the anodes are placed on the bottom layers. This configuration is somewhat similar to single compartment MFCs with multiple cathodes and anodes. The main difference being that the cathode is partially submerged into the electrolyte and occupies about half of the available urine column's depth. Since the upper layer of the urine column (i.e. the catholyte) is separated from the bottom layer (i.e. the anolyte) by a bioelectrochemical gradient, an interpretation could be that this gradient is a transient membrane renewed after each feeding pulse. This aspect led to the naming of this type of MFC a SSM-MFC: Self-stratifying membraneless MFCs. However, until now this type of MFC has only been tested under controlled laboratory conditions [ 8 , 9 ]. This study was carried out from an implementation perspective and focused on the generation of energy from urine. Employing urine as fuel presented several advantages, one of which is that MFCs can be fuelled directly with neat urine (i.e. without any dilution nor pre-treatment) [ 10 ], a waste stream representing 75% of the nitrogen found in domestic wastewater [ 11 ]. Such a technology could lower the burden on wastewater treatment plant. By integrating the MFC technology in waterless urinals, the energy consumption of wastewater treatment plants would be reduced, but with useful energy being produced near the source (e.g. for charging smart phones, providing light or automation of sanitary peripherals) [ 9 , 12 , 13 ]. Although numerous reports focus on improving the technology, there is a relatively small number of field trial studies describing pilot-scale MFC systems deployed under real conditions. The first practical demonstration, which can be considered as field-trial, is to be found in the world of electronic/robotic with the “gastrobot” [ 14 ], or the Ecobot series [ 6 , 15 ]. Along these prototypes demonstrating the potential of MFC to act as power source, another series of early successful trials demonstrated the use of benthic and marine MFCs to power sensors [ [16] , [17] , [18] ]. As discussed in these previous studies, the implementation of MFC implies the use of power management circuitry (e.g. DC-DC converters, power harvester, capacitors/batteries) to match the MFC's lower but constant energy production to the application's higher, and sometimes intermittent, energy needs. Aside robotics and marine environments, wastewater treatment is the other main niche in which research focuses. A recent review documents the performance of litre-scale MFCs treating real wastewater at continuous flow mode, thus illustrates the potential for implementation and technology readiness [ 19 ]. Up until 2010, only three pilot-scale trials had been tested [ 20 ]. The first large pilot-scale MFC stack treating wastewater was fuelled by brewery waste in Yatala (Queensland, Australia), where twelve 3 m high MFC modules with a total volume of 1 m 3 were used [ 20 ]. Since then, several studies have been conducted “out-of-the-lab” and/or at a pilot-scale: MEC for hydrogen production from wastewater [ 21 ], benthic microbial fuel cells [ 18 ], MFC in constructed wetland for wastewater treatment [ 22 , 23 ] and prototypes to be integrated in wastewater treatment plants [ 19 , [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] ], Floating MFCs combined with plants that act as autonomous sensors able to transmit a signal in natural water bodies [ 32 ], and MFC-based urinal system [ 13 ], have also been reported. The aim of the present trial was to assess the feasibility of SSM-MFC to be deployed as an electricity-generating sanitation solution in decentralised areas for periodic usage [ 9 ]. In order to test SSM-MFC in real conditions, the site for the trial should (i) have a need for lighting, automation or device charging, (ii) have a high number of users to provide the fuel and (iii) have a need for waterless in-situ treatment. Due to the existing collaboration between the Bristol BioEnergy Centre and the Glastonbury Music Festival, the PEE POWER ® urinal was tested in real conditions for a short period of time (3 weeks in total, including the 6 days of the music festival) at Glastonbury 2016. The Glastonbury Music Festival attracts approximately 250,000 people (festival goers and staff) and has a strong environmental agenda, with a high interest for on-site treatment and off-grid power. However, for such a purpose the system had to be re-designed to meet the on-site needs (i.e. a very high number of users per day; automatic feeding) [ 13 ]. Practically this meant scaling-up the whole system, whilst keeping the MFC modules smaller than the ones used in the PEE POWER ® urinal of 2015, adapting a passive feeding mechanism, and setting-up the appropriate energy management system, to harvest the energy and power the higher-energy consuming lights. Compared to its predecessor [ 13 ], the aim was to provide twice the amount of lighting (the urinal was twice the size) with a smaller footprint MFC system (<1/3 vol by comparison). Overall, the present study provides (i) results from laboratory investigation, (ii) performance under real conditions-of-use at the festival (iii) a self-sufficient system comprising MFCs and peripherals delivering a service to the users.",
"discussion": "3 Results and discussion Coulomb/Coulombic efficiency (CE) and energy recovery are calculated against and normalized to the amount of removed COD ( Supplementary information §1.2 ). 3.1 Scaling-up the module size The modules employed here were twice the size in length and width as the ones tested in earlier laboratory experiments [ 8 , 9 ]. Once stabilised (i.e. reaching steady-state), the power output of a single module reached an absolute value of ≈55 mW at 525 mV and 105 mA. In order to compare its performance with earlier results of the same design, the total displacement volume ( Table 1 ) was used for normalising power density. The volumetric power density of this larger module was of ≈11.5 W m −3 , which is similar to the ones of a smaller size (i.e. ≈12 W m −3 )[ 8 ]. These preliminary results further confirmed that a SSM-MFC can be scaled-up with limited power density losses. With regard to the total volumetric footprint of the modules, the smaller module had a power density of ≈2.9 W m −3 [ 8 , 9 ] whilst the larger one produced ≈2.8 W m −3 . Table 1 Summary of the performance of “out-of-the-lab” and pilot scale MFCs treating real waste streams. Some data ( a ) were extracted with permission from Ref. [ 19 ]. NER: normalised energy recovery. Table 1 Waste stream Influent COD (mg/L) Anode Volume a (L) HRT (h) COD removal (%) Power density (W/m 3 ) Coulombic efficiency (%) Max. NER (kWh/m 3 ) Max. NER (kWh/kgCOD) References Domestic Wastewater b 279 ± 144 4 11 65-70 max. 1.14 10.7 max. 0.0127 0.0649 [ 30 ] Domestic Wastewater b 156 ± 42 96 18 78.8 max. 1.35 1.4 max. 0.0243 0.1976 [ 31 ] Brewery wastewater b 3196 ± 978 18.8 156.6 94.5 max. 0.44 13.9 max. 0.0691 0.0229 [ 19 ] Brewery wastewater b 3321 90 144 87.6 max. 1 19.1 max. 0.1440 0.0495 [ 27 ] Neat urine* 5586 ± 139 19.2* 44 88* 9.9 3.81 0.3460 0.0704 This Study Neat urine** 6770 ± 98 57.6 11.7 48 7.31 1.63 0.0860 0.0247 This Study Neat urine*** – 300*** 22 25 1 N/A 0.0220 N/A [ 13 ] *Laboratory experiment with the cascade of 4 modules. Energy calculated from the area under curve ( Fig. 4 a, current curve under 2Ω, last 44 h). **Data from the present field trial at the time of the COD sampling (not the max. power produced). Energy calculated from the area under curve ( Fig. 5 , current curve 11.7 h prior COD sampling). ***Data extracted from the 2015 field trial [ 13 ]. a Volumetric power densities were calculated using anode liquid volume for past studies ( b ,***) and total electrolyte volume for the present study (*, **). b The data extracted from Lu et al. 2017 [ 19 ] use the max. power densities and the max. Coulombic efficiencies. 3.2 Electrical performance of the module when assembled in stacks Because the adjustment of the feeding mechanism was difficult, the pulsated bursts were delivering ≈1.7 L of urine instead of 1.25 L, which is what was used for the single module lab testing. Moreover, due to the availability fuel supply, the tests with similar HRT time were carried out over shorter periods. Compared to the performance of a single module, under the same feeding regime (1.7 L.2 h −1 ), a single cascade of 4 modules electrically connected in parallel was producing, at steady state (from 63 h to 74 h; Fig. 3 a), an average of 181 ± 9 mW at 425 ± 11 mV and 425 ± 11 mA (n = 2; Fig. 3 a). The power density of a cascade was 18% lower than that of a single module; 2.2 W m −3 and 2.7 W m −3 footprint volume respectively. Fig. 3 ( a ) Performance of the two electrically independent cascades (i.e. duplicate) under different feeding regimes and corresponding loads: all the modules within each cascade are connected in parallel. ( b ) Electrical behaviour when both cascades are electrically connected in series (1 stack) whilst all the modules within each cascade are connected in parallel. The black arrow indicates a fault on the timer controlling the pump that malfunctioned and pumped the 20 L of fuel in one go. The next feeding occurred 6 h later. The white arrow indicates a manual feed of 10L. ( c ) Electrical performance of the 8 modules stack: modules electrically connected in parallel by pairs, within a single cascade, and the 4 pairs connected in series. The top graph shows the stack behaviour (voltage, current, power) whilst the bottom one shows the modules' behaviour (voltage as dashed lines, power as plain lines). The black arrow indicates when the last feed occurred and the white one indicate a single feed of 5L per cascade. Fig. 3 Once the two cascades were connected in series to form a single stack (with all MFC in a cascade connected in parallel), and under a similar feeding regime (1.7 L.2 h −1 ), the average power was of 352 ± 10 mW at 838 ± 11 mV and 419 ± 6 mA (from 17.5 h to 27 h; Fig. 3 b). Results show that this one stack of 2 cascades was producing an energy equivalent to the sum of the energy produced by each single cascade. Connecting the two cascades in series increased the voltage (838 ± 11 mV instead of 425 ± 11 mV) and maintained an equivalent current (419 mA and 425 mA, respectively). Under lower feeding pulses (1 burst of 1.7L every 4 h), the steady-state power output of a single cascade was 151 ± 2 mW at 549 ± 4 mV and 274 ± 2 mA (n = 2 cascades/stacks; Fig. 3 a; last 44 h). Again, when electrically connected in series the voltage was doubled, making the average power 305 ± 3 mW at 1105 ± 5 mV and 276 ± 1 mA (t ≈ first 17 h; Fig. 3 b). The impact of the timer failure illustrates the dependency on the feeding regime for power (1.7 L.2 h −1 , black arrow, Fig. 3 b). After being fed 10L per cascade at once (black arrow, Fig. 3 b), the stack reached a maximum power of 432 mW at 939 mV and 465 mA. These results indicate that these modules have the potential to produce even more power when placed under a higher feeding regime. Twenty hours after the 10 L feed-burst, a steady-state similar to its previous state was reached i.e. ≈ 372 mW at 862 mV and 432 mA (from 42 h to 46 h; Fig. 3 b). To confirm this dependence, a 5L per cascade fuel-burst at the end of the run significantly increased the power output to 412 mW (white arrow). Following these results, a third electrical configuration was tested. Whilst keeping 2 cascades (i.e. hydraulic configuration), pairs of modules were electrically connected in parallel, and the pairs were then electrically connected in series. However as explained earlier, with fuel being progressively depleted as it travels through the multiple four-module cascades, the downstream modules of the cascade produce less power than the initial ones. To achieve a more balanced system, the first module of a cascade was electrically connected in parallel with the third one, whilst the second was paired with the fourth. The series connection was made by connecting the second pair of the first cascade (A2-A4) with the first one of the same cascade (A1-A3). The latter pair (A1-A3) was then put in series with the first pair of the second cascade (B1-B3), which was then connected in series with the last pair (B2-B4). The positive terminal port of this setup was the pair A2-A4, and the negative port was the pair B2-B4. The hydraulic retention time was then progressively decreased from 1.7L.4 h −1 to 1.7L.2 h −1 and then to 1.7L.1 h −1 ( Fig. 3 c). The load applied to the stack was adjusted accordingly from 16Ω to 8Ω. The load applied when the stack was under 1.7L.1 h −1 was kept to 8Ω since this corresponded to the maximum power transfer point of the stack, as indicated by the polarisation sweep (415 mW, 1824 mV, 228 mA; Fig. 4 a). Fig. 4 Polarisation sweep results from the stack of 8 modules ( a ), and from the module pairs ( b ). Fig. 4 In addition to the increased power output due to the increased feeding regime, the stack's electrical behaviour matched previous results. With a pulse-fed every 4 h, the stack produced 306 ± 1 mW (from 0 h to 23 h, Fig. 3 c), which corresponds to the same power produced when the stack was under the previous configuration shown in Fig. 3 b (from 0 h to 17 h). As half the number of modules was electrically connected in parallel, but double the number was connected in series, the current was naturally halved (138 ± 0.1 mA instead of 276 ± 1 mA; Fig. 3 c and b) and the voltage doubled (2213 ± 2 mV instead of 1105 ± 5 mV; Fig. 3 c and b). Accordingly, under a 2 h pulse-feed regime (HRT ≈ 6 h per module), the stack produced 369 ± 4 mW at 1719 ± 10 mV and 215 ± 1 mA (from 23 h to 40 h, Fig. 3 c). When the regime was changed to 1 feeding per hour, the stack ran out of fuel before reaching a steady state (black arrow, Fig. 3 c). Nevertheless, during the 2 h following the last feed, the stack produced an average of 434 ± 0.6 mW at 1864 ± 1 mV and 233 ± 0.2 mA (2 h after black arrow, Fig. 3 c). Again, these results show that (i) these MFC-modules behave as conventional power sources, and (ii) such a setup would be able to handle a large quantity of urine in proportion to its size. 3.3 Glastonbury Music Festival trial: a reliable and effective system During the first 3 days, the stack installed at the Glastonbury Music festival behaved as expected from the results obtained during the laboratory tests. The power output gradually increased (2 days; Fig. 5 a) to a steady state of 590 ± 12 mW at 217 ± 5 mA ( Fig. 5 a), which held for 28 h until most of the festival attendees had arrived (from day 3 to day 5). This corresponds to 50 KJ of electrical energy or 14 Wh for every day that the system was running. After adapting to the new feeding regime and conditions (i.e. passive system), a new steady-state was reached from days 5–9 ( Fig. 5 a). During this period, which includes all variations, the average power generated from the stack was of 424 ± 36 mW at 156 ± 12 mA ( Fig. 5 a). Fig. 5 Electrical behaviour of the system before and during the festival. ( a ) Power and current output levels of the stack of 12 modules, voltage of the batteries and feeding-pulses that fed the 6 MFC cascades. ( b ) Average of the absolute power output for all six cascades (light blue); the average power output of the five cascades showing comparable power outputs (A,B,C,D,F; yellow) – error bars show the standard deviation (n = 5 per time point) – the absolute power output of module E showing its drift from the average (white); and the air temperature (red points). Orange bars indicate the periods of illumination of the urinal (from ≈ 9pm to ≈ 7am). * indicates when samples were taken for the COD and nitrogen analysis. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.) Fig. 5 The majority of the festival attendees arrived on the third day. It is likely that both temperature and feeding patterns would have contributed to the diurnal variations. During the night from day 7 to day 8, the feeding rate was relatively high (≈1 feed every 25 min; Fig. 5 a), and the consequent power level variation more pronounced than during the previous night. Since the temperature was higher during day 6 than day 7 ( Fig. 6 b), the difference in power fluctuation between these two successive days could thus be attributed to the feeding regimes. Results therefore indicate that for this system with this specific module size, a feeding rate of 1 feed every 25 min was too high (decrease of power; Fig. 5 a), and a feeding rate of 1 feed every 90 min seems optimum (stable and/or increasing power production; Fig. 5 a). These feeding rates correspond, for the whole system (57.6L), to a hydraulic retention time of ≈2h30 min (≈559L.d −1 ) and ≈9 h (≈155L.d −1 ), respectively. It is important to note that this is a field test with a passive feeding system (i.e. no energy consumption). Hence, the feeding regimes depend on the uncontrolled usage. The observed decrease of power due to frequent feed-pulses (1 feed every 25 min) could be of two origin. Either the feeding rate, which mix the electrolyte and disrupts the electrochemical stratification, is faster than the capacity of the system to re-stratify (system's resilience) – and/or the feeding rate is higher than the microbial population's growth rate (washing out phenomenon) [ 34 ]. These results together with the laboratory tests lead to the conclusion that the optimum HRT was comprised between 2 h30min, which is too short, and ≈9 h, which might be too long. Fig. 6 Battery bank voltage during the charging phase. Charge 1 was during day 8 and charge 2 during day 9 (1 point every 2 min). Dark grey area indicates the period when the lights were on, prior being switched off (light grey area). Fig. 6 With regard to the total volumetric footprint of the MFC stack, the power density was 1.7 W m −3 . The results of the 2015 trial only reported the footprint volume of each module (i.e. total of 403.2 L), without taking into account the air-gaps between modules [ 13 ]. Hence, in order to make a direct comparison for this year, the air gap volume (6 L) was also discounted from the total footprint volume. Under these normalising conditions, the power density obtained is 2.45 W m −3 . In comparison to the 2015 setup (mean of 300 mW corresponding to 0.74 W m −3 ), the power density of the 2016 setup was improved by 331%. When normalising by the displacement volume (≈58 L and 300L, respectively), results show a 731% improvement from the SSM-MFC design ( Table 1 ). The calculation of the Coulombic efficiency was done with whole volume of electrolyte was taken into account. When considering a stack of MFCs, the equation has to be modified to reflect the electrical connections. Thus, for a stack with a series configuration, the current – in equation (1) ( Supplementary Information )– should be multiplied by the number of MFCs in series. Considering these parameters, the coulombic efficiency obtained are 3.81%, 3.43% and 1.63% for a HRT of 44 h, 22 h and 11.7 h, respectively. However, NER values are more suited to go beyond coulombic efficiency and better reflect energy production by emphasising the fact that MFC are wastewater treatment systems [ 35 , 36 ]. Using equations (2) and (3) the obtained NER values reflecting the treatment capacity of the system for the HRT of 44 h, 22 h and 11.7 h, are 0.346 ± 0.005, 0.207 ± 0.010 and 0.086 ± 0.007 kWh.m −3 , respectively. With regard to the conversion efficiency of the system, the NER values for the HRT of 44 h, 22 h and 11.7 h, are 0.070 ± 0.001, 0.049 ± 0.002 and 0.025 ± 0.002 kWh.kg-COD −1 , respectively. Since the system presented here was fuelled by neat urine, comparison with previous systems fuelled with domestic or brewery wastewaters is challenging. Nonetheless, the system presented here shows similar performance to what has been published ( Table 1 ). Moreover, even though the power densities were the highest amongst the compared ones ( Table 1 ), the NER values were in the same range, which strengthen the notion that NER values would be more appropriate to compare MFC system in the context of practical implementation [ 36 ]. At the beginning of the field trial all the cascades (A, B, C, D, E, F; Fig. 1 ) had comparable power outputs. However, the performance of cascade E, which was already the weakest of the system, started diverging from the other 5 cascades beginning of day 4. The power outputs levels of these cascades were always comparable throughout the trial (±5.1 mW on day 5 and ± 9 mW on day 9, Fig. 5 b). However, the drift from cascade E decreased the power output of the stack by 8% (difference between average of five and average of six modules). It should be noted that it is difficult to evaluate the real impact of this drift, since it could have inhibited the activity of the other connected modules. Hence, the power output of the stack could have been higher than 8%. In comparison with the significant power decrease of module E (43% less power than the average on day 9), the 8% power decrease illustrates that the MFC stack was a robust power source, even with an “underperforming” cascade. The energy was stored in a battery bank during day time and powered the lights at night. The duty cycle was of ≈14h30 charge time and ≈9h30 discharge time. However, as can be seen in Fig. 6 , the voltage level of the battery was decreasing. This result indicates that during a 24 h period the lighting system was consuming more energy than that produced. Assuming a hypothetical 100% efficiency from the energy management system (i.e. harvester, battery and output voltage regulator) the 6 LED strips were consuming ≈87 kJ of electrical energy (2.544 W during 9h30) whilst the MFC stack was producing between ≈52 kJ (≈0.600 W continuously; days 0–4) and ≈37 kJ (≈0.425 W continuously; days 6–9). The reason for the decrease in power is the irregular feeding during the festival, as already discussed. To balance the system and achieve self-sustainability, whilst delivering the same service (2.544 W lighting during 9.5 h), since the MFC stack could process 220L of urine out of the 1,200L received daily from the urinal, the size of the stack could have been doubled to produce more power than that consumed by the LEDs. 3.4 Treatment capacity of SSM-MFCs During the laboratory investigation, the HRT applied to the MFC cascades was longer than the one adjusted for the PEE POWER ® system during the festival. This was due to the challenges of collecting sufficient fuel in the lab, which is why for the lab trials, the systems had a 22 h and 44 h HRT applied. As explained earlier, feeding regime and produced power are correlated. This is why the applied loads differed for the different HRTs ( Fig. 3 ). Under these conditions, if longer HRT displayed higher nutrient removal, the correlation was not linear ( Fig. 7 a). During the Glastonbury trial, the COD decreased by 48% ( Fig. 7 b)– with an HRT of 11h40 min at the time of analysis – and the total nitrogen (TN) content had decreased by 13% ( Fig. 7 a). Compared to the previous trial (2015) [ 37 ], the COD removal for the current trial was 92% higher, with half the HRT. Fig. 7 Chemical Oxygen Demand (COD) ( a, b ), total nitrogen and ammonium reduction ( c, d ) in treated urine stream during laboratory investigation ( a, c ) and during the field trial at 11h40 HRT ( b, d ). The HRTs in ( a ) were obtained by changing the pulse-feed duty cycles: 22 h and 44 h correspond to 1.7L.2 h −1 and 1.7L.4 h −1 , respectively ( Fig. 3 ). Fig. 7 The nitrogen removal was ≈50% lower than the previous trial, but this was recorded for an HRT which was 50% shorter; it can therefore be assumed that the nitrogen removal rates were similar, and in both cases, were slower than the corresponding COD removal rates. The treatment efficiency of the stack comprising 2 cascades of 4 modules (laboratory experiment) was plotted against the HRT, together with the results of the Glastonbury trial ( Fig. 8 ). This projection indicates that the higher the HRT the more efficient the waste treatment. Longer HRT could be achieved either by increasing the number of modules in a cascade or by adjusting the pulse-feeding regime. Fig. 8 COD and total nitrogen (TN) removal percentage depending on the hydraulic retention time of a cascade. The first data points (HRT = 11h40) correspond to the samples taken from the Glastonbury trial, whilst the second (HRT = 22 h) and the third (HRT = 44 h) correspond to the laboratory testing (i.e. data merged from two different experiments). Fig. 8 Compared to the industry standards (92% COD and 20% TN reduction) [ 38 ], the results from the 44 h HRT are relatively close (88% COD and 29% TN reduction). However, in our case we were treating a much more concentrated waste stream (5500–6800 mg COD.L −1 ) compared to the mixed wastewater streams received by a municipal wastewater treatment plant (e.g. rain water, grey water, black water). Regarding the legal maximum discharge concentration in the European Union (conc. <125 mg COD·L −1 ; <10–20 mg TN L −1 ) [ 39 ], the 4 module stack with an HRT of 44 h does not meet the requirements (≈670 mg COD·L −1 ; ≈3230 mg TN L −1 ). To reach the legal acceptable limits, the COD should be decreased by 98%. According to the Michaelis-Menten equation that fits the COD removal projection ( Fig. 8 ), it can be hypothesised that the required COD discharge concentration could be reached with a HRT of ≈64 h. Since the TN removal rate is not yet substrate-limited (linear correlation, Fig. 8 ), it is not possible to give an estimation of the optimal HRT."
} | 7,518 |
22574181 | PMC3344890 | pmc | 7,526 | {
"abstract": "The temporal stability of aggregate community properties depends on the dynamics of the component species. Since species growth can compensate for the decline of other species, synchronous species dynamics can maintain stability (i.e. invariability) in aggregate properties such as community abundance and metabolism. In field experiments we tested the separate and interactive effects of two stressors associated with storminess–loss of a canopy-forming species and mechanical disturbances–on species synchrony and community respiration of intertidal hard-bottom communities on Helgoland Island, NE Atlantic. Treatments consisted of regular removal of the canopy-forming seaweed Fucus serratus and a mechanical disturbance applied once at the onset of the experiment in March 2006. The level of synchrony in species abundances was assessed from estimates of species percentage cover every three months until September 2007. Experiments at two sites consistently showed that canopy loss significantly reduced species synchrony. Mechanical disturbance had neither separate nor interactive effects on species synchrony. Accordingly, in situ measurements of CO 2 -fluxes showed that canopy loss, but not mechanical disturbances, significantly reduced net primary productivity and temporal variation in community respiration during emersion periods. Our results support the idea that compensatory dynamics may stabilise aggregate properties. They further suggest that the ecological consequences of the loss of a single structurally important species may be stronger than those derived from smaller-scale mechanical disturbances in natural ecosystems.",
"introduction": "Introduction Current rates of species loss have spurred studies testing the influence of diversity on the stability of natural communities [1] , [2] . As a result, ecologists recognise today that community stability depends on the temporal dynamics of the species that form the communities [1] . Species abundances can be highly variable over time, influenced by external abiotic factors, internal biotic interactions, and the combination of both [3] . The effect of species' abundance variability on community stability may depend on the degree to which species fluctuations are synchronous or compensatory [4] . Theoretical models indicate that the loss or decline of species can be compensated by others with different environmental tolerances, maintaining relative stability (i.e. invariability) in aggregate, community-level properties like community abundance and productivity [1] , [3] , [5] , [6] . However, field-based evidence that compensatory dynamics maintain community stability is still inconclusive [7] , [8] , [9] , [10] . Community respiration, defined as the sum of metabolic rates across species, is an important aggregate property because of its determinant role in the carbon cycle [11] . In addition, it directly reflects resource availability, representing therefore a powerful indicator of ecosystem “health” and ecological conditions [8] . Several studies show that compensatory species dynamics maintain a steady state in the rates of resource supply and resource use [12] , [13] , [14] , [15] . Therefore, it can be predicted that the degree of synchrony in species abundances may influence the temporal variation in community metabolism [16] . According to Micheli [4] , testing this hypothesis needs species attributes to vary independently from those at the community-level. Both, species abundances and community-level metabolism should be measured independently. In addition, it is still necessary to assess the effect of key species on community stability [17] . On temperate rocky shores, canopy-forming algae are key structural elements that modify the environment and facilitate or suppress the occurrence of other species [18] , [19] , [20] . Facilitation by canopy-forming seaweeds may occur by alleviating abiotic stress through shading and reduced desiccation [21] , [22] . Canopies may prevent recruitment of understorey species by pre-emption or sweeping fronds [23] , [24] , [25] . In addition, large and dominant species can be more persistent than subordinate ones [26] , [27] . So, the presence of a dominant species may increase the stability of aggregate properties [28] . This could be the case of canopy-forming macroalgae, whose structural specialisation of thallus may confer them toughness and resistance to mechanical stress [29] . Moreover, canopy-forming seaweed can be responsible for a significant proportion of community metabolism [30] , [31] , [32] . These effects on species abundances and community-level properties suggest that canopies influence the temporal variability at both levels of ecological organisation. 10.1371/journal.pone.0036541.g001 Figure 1 CAP ordination plots of species composition (A) before and (B) 1–3 days after canopy removal and mechanical disturbance treatments, and (C) long-term mean cover of Fucus serratus canopy. In panels A and B, the first and second CAP axes explained 41% and 34% of total inertia, respectively, at Nordostwatt and 68 and 17, respectively, at Westwatt. D− and D+ are undisturbed or disturbed treatments, respectively; C+ and C− indicate presence and removal of canopy, respectively. In panel C asterisks indicate significant differences between canopy treatments, and values are given as means ± SEM (n = 5) Loss of large canopy-forming species is accelerated [33] , and mechanical stress on coastal ecosystems increases as a consequence of, for instance, increased storminess [34] . Canopy loss may also exacerbate the effects of additional storm-induced disturbances on community stability. Crashing waves can dislodge or harm benthic organisms on rocky shores [35] , and these effects can be disproportionately larger on delicate growth forms than massive canopy-forming seaweeds [29] . Consequently, mechanical disturbances may affect the composition of understorey assemblages without necessarily removing canopies. Since canopies can limit the subset of species able to colonise the substratum [23] , the effects of disturbances on the understorey community could be weak when canopies are present, but strong when canopies are removed. Cumulative evidence suggests that canopy removal and mechanical disturbances interactively affect community structure [20] , [36] , [37] ; however, studies linking these interactive effects to stability are still necessary to acquire a mechanistic understanding of the ecological consequences of anthropogenic impacts on natural communities. Here we tested the separate and interactive effects of canopy removal and mechanical disturbance on species synchrony and the temporal variability in community respiration of intertidal rocky shore communities. Species synchrony was defined as the degree to which species' abundances vary simultaneously over time; for example, species synchrony will be high if most species' abundances show parallel increases or decreases. We measured species abundances and community-level respiration independently, instead of calculating the latter as a scalar function of species attributes [15] . This allowed independent estimators of species- and community-level variability. Factorial field experiments were conducted to test the predictions (1) that canopy removal and mechanical disturbances affect species synchrony and metabolic variability, and (2) that the effects of mechanical disturbance are stronger in communities that have lost the canopy than in communities with a canopy present.",
"discussion": "Discussion Our results showed that species synchrony significantly decreased as a result of the loss of canopy, indicating that compensatory dynamics may have been strengthened upon canopy removal. Canopy removal led to a decrease in net primary productivity (NPP) and temporal variation of community respiration ( V CR ). Neither separate nor interactive effects of mechanical disturbance on species synchrony, NPP, and V CR were observed. These results support the notion that compensatory species dynamics stabilise aggregate community properties. They also indicate that canopy removal, but not smaller-scale mechanical disturbances, may significantly affect mechanisms contributing to community stability. Canopy-forming species usually reduce the variability in environmental factors [21,22]. Since seasonal changes in, for example, temperature and light, can be large in Helgoland [44], experimental canopy removal exposed the understorey assemblage to a wide range of environmental conditions. Different species may be competitively dominant at different times [61], which can foster the occurrence of asynchronous, compensatory dynamics among species exposed to large environmental variability [3,62]. In our experiment, for instance, canopy loss had lead to an average increase in light regime of ca. 400% during summer months [63]. Such changes may have detrimental effects for some understorey species, like low-light adapted seaweeds, but may have beneficial effects for high-light adapted macroalgae. In fact, abundance of low-light adapted crustose red algae (e.g. Phymatolithon spp.) declined in plots where the F. serratus canopy was removed, while abundance of high-light adapted green algae (e.g. Ulva spp.) increased here relative to control plots. Moreover, insulation effects of F. serratus canopies at the study site during low tide may reduce air temperature in the understory for several hours during sunny afternoons by up to 20°C (M. Molis, unpublished data). Changes in sedimentation rate, light, and temperature regimes as a consequence of canopy loss have been reported as important abiotic drivers of community structure during subsequent succession in seaweed dominated communities [64,65]. Therefore, differential abilities of understorey species to cope with enhanced environmental variability upon canopy loss probably decreased species synchrony. According to theoretical models, decreased species synchrony should lead to increased stability of aggregate properties [3,6]. Our results support this prediction, as V CR significantly decreased upon canopy removal. Asynchronous dynamics, due to contrasting environmental responses of understorey species, may have maintained the steady state in the rates of resource supply and resource use. Differences in life history traits between low-light and high-light adapted species, for instance, may have led to asynchronous variation in metabolic activity [66]. Therefore, it is likely that compensatory dynamics in metabolic functions may well occur, at least, between these two functional groups. This hypothesis however still needs to be tested through proper experimentation. On the other hand, the temporal variability in the abundance or metabolism of the dominant species may also affect the community-level stability. Canopy-forming seaweeds can significantly contribute to the metabolism of benthic habitats [30,31,32]. Accordingly, the significant negative effects of canopy removal on NPP and CR, and the fact that understorey community respiration did not differ between C+ and C– treatments indicates that F. serratus canopy comprised the bulk of productivity and respiration of un-manipulated communities. Thus, the steady state between resource supply and resource use of the community probably depended mostly on the metabolic activity of F. serratus . These results contradict previous work showing that increased dominance by one or few species increases the stability of the total community [26,27,28]. Dominance can enhance community stability when the dominant species are more resistant to events of destruction than subordinate species [26,67]. On the contrary, the small attachment area of F. serratus holdfasts may result in dislodgement by dragging forces and cobble bash. Single storm events, for instance, may remove across the entire study site up to 60 % of F. serratus canopy (I. Bartsch, unpublished data). Winter losses of F. serratus cover could be positively correlated with significant wave height, as shown for giant kelps in California [68,69] and a dominant fucoid in southern New Zealand [70]. In addition, recent manipulative work shows that strengthened compensatory dynamics upon canopy loss can stabilise the total community abundance [71]. Therefore, dominance and monopolisation of resources would actually reduce stability if the dominant species were prone to large variations through time. In our study, mechanical disturbance had no significant effect on species synchrony, community productivity, and stability, although disturbance can strongly affect species diversity and composition in different benthic systems [72,73]. High seasonality in recruitment patterns and quick re-colonisation may explain the lack of separate and interactive effects of mechanical disturbances. We applied a pulse event of destruction at the onset of the experiment in March, before the main settlement period of several ephemeral, corticated, and leathery algae [44], and during the main reproductive period of F. serratus and F. vesiculosus [43]. This indicates that propagules of these species could have been available when mechanical disturbances were applied. Covers higher than 20% of F. serratus recruits, however, were observed between June and December, and no recruit of F. vesiculosus was observed on our plots during the experiment (N. Valdivia, unpublished data). Patches of empty substratum can be re-colonised by both local propagule dispersal and lateral expansion of species with clonal or colonial growth [74,75]. Rapid re-colonisation by expansion of adults could have prevented disturbance-generated patches of habitats from being available during the main settlement period of algae. Variability during early stages of colonisation, in addition to priority effects of the species that happen to colonise first, can determine much of the subsequent dynamics in the assemblage [76,77]. Extreme storms, nevertheless, can be observed every ca. 2 years in the Atlantic basin [78]. At the temporal scale of our study, therefore, timing and frequency of mechanical disturbance seemed to be appropriate to mimic the impact of extreme winter storms. Some caution should be used to interpret our results. We assumed that abundance and energy use are equivalent measures of community function [15]. The validity of this assumption depends, however, on unmeasured variables such as body size distribution [15,79,80]. On the other hand, calculation of variation in community respiration was constrained by weather conditions and tides to only 3 repeated measurements, indicating the need for longer-term datasets of in situ metabolic community functions. Finally, lack of interactive effects between stressors observed in this study agrees with previous manipulative field-based experiments [64,81], but it contradicts a major synthesis of ca. 170 laboratory-based studies [82]. These opposing results hint at the need for more manipulative and field-based experiments accounting for interactive effects of simultaneous stressors on ecosystems [37]. Through manipulative experiments and assessing eco-physiological variables such as species percentage cover, biomass, NPP, and CR, we have tested in natural conditions the effects of multiple anthropogenic stressors on mechanisms that maintain community stability. Our analyses showed that stressors related with storminess may affect species and community-level variability by removal of dominant canopies, but not necessarily by associated smaller-scale mechanical disturbances. These results shed light on the mechanisms that may drive the response of communities facing present and future anthropogenic pressures."
} | 3,951 |
23926448 | null | s2 | 7,528 | {
"abstract": "Bacterial swarming is an example of dynamic self-assembly in microbiology in which the collective interaction of a population of bacterial cells leads to emergent behavior. Swarming occurs when cells interact with surfaces, reprogram their physiology and behavior, and adapt to changes in their environment by coordinating their growth and motility with other cells in the colony. This review summarizes the salient biological and biophysical features of this system and describes our current understanding of swarming motility. We have organized this review into four sections: 1) The biophysics and mechanisms of bacterial motility in fluids and its relevance to swarming. 2) The role of cell/molecule, cell/surface, and cell/cell interactions during swarming. 3) The changes in physiology and behavior that accompany swarming motility. 4) A concluding discussion of several interesting, unanswered questions that is particularly relevant to soft matter scientists."
} | 241 |
29415041 | PMC5802861 | pmc | 7,530 | {
"abstract": "Trained recurrent networks are powerful tools for modeling dynamic neural computations. We present a target-based method for modifying the full connectivity matrix of a recurrent network to train it to perform tasks involving temporally complex input/output transformations. The method introduces a second network during training to provide suitable “target” dynamics useful for performing the task. Because it exploits the full recurrent connectivity, the method produces networks that perform tasks with fewer neurons and greater noise robustness than traditional least-squares (FORCE) approaches. In addition, we show how introducing additional input signals into the target-generating network, which act as task hints, greatly extends the range of tasks that can be learned and provides control over the complexity and nature of the dynamics of the trained, task-performing network.",
"introduction": "Introduction A principle focus in systems and circuits neuroscience is to understand how the neuronal representations of external stimuli and internal intentions generate actions appropriate for a particular task. One fruitful approach for addressing this question is to construct (or “train”) model neural networks to perform analogous tasks. Training a network model is done by adjusting its parameters until it generates desired “target” outputs in response to a given set of inputs. For layered or recurrent networks, this is difficult because no targets are provided for the “interior” (also known as hidden) units, those not directly producing the output. This is the infamous credit-assignment problem. The most widely used procedure for overcoming this challenge is stochastic gradient-decent using backpropagation (see, for example, [ 1 ]), which uses sequential differentiation to modify interior connection weights solely on the basis of the discrepancy between the actual and target outputs. Although enormously successful, this procedure is no panacea, especially for the types of networks and tasks we consider [ 2 ]. In particular, we construct continuous-time networks that perform tasks where inputs are silent over thousands of model integration time steps. Using backpropagation through time [ 3 ] in such cases requires unfolding the network dynamics into thousands of effective network layers and obtaining gradients during time periods during which, as far as the input is concerned, nothing is happening. In addition, we are interested in methods that extend to spiking network models [ 4 ]. As an alternative to gradient-based approaches, we present a method based on deriving targets not only for the output but also for interior units, and then using a recursive least-squares algorithm [ 5 ] to fit the activity of each unit to its target. Target- rather than backpropagation-based learning has been proposed for feedforward network architectures [ 6 ]. Before discussing a number of target-based methods for recurrent networks and presenting ours, we describe the network model we consider and define its variables and parameters. We use recurrently connected networks of continuous variable “firing-rate” units that do not generate action potentials (although see [ 4 ]). The activity of an N -unit model network ( Fig 1a ) is described by an N -component vector x that evolves in continuous time according to\n τ d x d t = - x + J H ( x ) + u in f in ( t ) , (1) \nwhere τ sets the time scale of the network dynamics (for the examples we show, τ = 10 ms). H is a nonlinear function that maps the vector of network activities x into a corresponding vector of “firing rates” H ( x ) (we use H ( x ) = tanh( x )). J is an N × N matrix of recurrent connections between network units. An input f in ( t ) is provided to the network units through a vector of input weights u in . The output of the network, z ( t ), is defined as a sum of unit firing rates weighted by a vector w ,\n z ( t ) = w T H ( x ( t ) ) . (2) 10.1371/journal.pone.0191527.g001 Fig 1 Network architecture. (a) Task-performing network. The network receives f in ( t ) as an input. Training modifies the elements of J and w so that the network output z ( t ) matches a desired target output function f out ( t ). (b) Target-generating network. The network receives f out ( t ) and f in ( t ) as inputs. Input connections u , u in and recurrent connections J D are fixed and random. To verify that the dynamics of the target-generating network are sufficient for performing the task, an optional linear projection of the activity, z D ( t ), can be constructed by learning output weights w D , but this is a check, not an essential step in the algorithm. Tasks performed by this network are specified by maps between a given input f in ( t ) and a desired or target output f out ( t ). Successful performance of the task requires that z ( t ) ≈ f out ( t ) to a desired degree of accuracy. A network is trained to perform a particular task by adjusting its parameters. In the most general case, this amounts to adjusting J , w and u in , but we will not consider modifications of u in . Instead, the elements of u in are chosen independently from a uniform distribution between -1 and 1 and left fixed. The cost function being minimized is\n C w = 〈 ( z ( t ) − f out ( t ) ) 2 〉 , (3) \nwhere the angle brackets denote an average over time during a trial and training examples. The credit assignment problem discussed above arises because we only have a target for the output z , namely f out , and not for the vector x of network activities. Along with backpropagation, a number of approaches have been used to train recurrent networks of this type. A number of of these involve either ways of circumventing the credit assignment problem or methods for deducing targets for x ( t ). In liquid- or echo-state networks [ 7 – 9 ], no internal targets are required because modification of the internal connections J is avoided entirely. Instead, modification only involves the output weights w . In this case, minimizing C w is a simple least-squares problem with a well-known solution for the optimal w . The price paid for this simplicity in learning, however, is limited performance from the resulting networks. An important next step [ 10 ] was based on modifying the basic network eq 1 by feeding the output back into the network through a vector of randomly chosen weights u ,\n τ d x d t = - x + J H ( x ) + u in f in ( t ) + u z ( t ) . (4) Because z = w T H ( x ), this is equivalent to replacing the matrix of connections J in Eq 1 by J + u w T . Learning is restricted, as in liquid- and echo-state networks, to modification of the output weight vector w but, because of the additional term uw T , this also generates a limited modification in the effective connections of the network. Modification of the effective connection matrix is limited in two ways; it is low rank (rank one in this example), and it is tied to the modification of the output weight vector. Nevertheless, when combined with a recursive least-squares algorithm for minimizing C w , this process, known as FORCE learning, is an effective way to train recurrent networks [ 11 ]. Although the FORCE approach greatly expands the capabilities of trained recurrent networks, it does not take advantage of the full recurrent connectivity because of the restrictions on the rank and form of the modifications it implements. Some studies have found that networks trained by FORCE to perform complex “real-world” problems such as speech recognition require many more units to match the performance of networks trained by gradient-based methods [ 12 ]. In addition, because of the reliance of FORCE on random connectivity, the activity of the resulting trained networks can be overly complex compared, for example, to experimental recordings [ 13 ]. A suggestion has been made for extending the FORCE algorithm to permit more general internal learning [ 11 , 14 ]. The idea is to use the desired output f out to generate targets for every internal unit in the network. In this approach, the output is not fed back into the network, which is thus governed by Eq 1 not Eq 4 . Instead a random vector u is used to generate targets, and J is adjusted by a recursive least-squares algorithm that minimizes\n C J eF = 〈 | J H ( x ( t ) ) - u f out ( t ) | 2 〉 . (5) Although this “extended” FORCE procedure can produce functioning networks, minimizing the above cost function is a rather unusual learning goal, If learning could set C J eF = 0 , the effective equation of the network would be τd x / dt = − x + u f out ( t ) + u in f in ( t ). This equation is incompatible with the output z ( t ) being equal to f out ( t ) because f out ( t ) cannot, in general, be constructed from a low-pass filtered version of itself. Thus, the success of this scheme relies on failing to make C J eF too small, but succeeding enough to assure that the target output is a partial component in the response of each unit. Laje & Buonomano [ 15 ] proposed a scheme that uses a second “target-generating” network to produce targets for the activities of the network being constructed. They reasoned that the rich dynamics of a randomly connected network operating in the chaotic regime [ 16 ] would provide a general basis for many dynamic tasks, but they also noted that the sensitivity of chaotic dynamics to initial conditions and noise ruled out chaotic networks as a source of this basis (see also [ 17 ]). To solve this problem, they used the activities of the chaotic target-generating network, which we denote as x chaos ( t ), as targets for the actual network they wished to construct (which we call the “task-performing” network). They adjusted J to minimized the cost function\n C J LB = 〈 | H ( x ( t ) ) - H ( x chaos ( t ) ) | 2 〉 . (6) After learning, the task-performing network matches the activity of the target-generating network, but it does so in a non-chaotic “stable” way, alleviating the sensitivity to initial conditions and noise of a truly chaotic system. Once this stabilization has been achieved, the target output is reproduced as accurately as possible by adjusting the output weights w to minimize the cost function 3 . Like the approach of Laje & Buonomano [ 15 ], our proposal uses a second network to generate targets, but this target-generating network operates in a driven, non-chaotic regime. Specifically, the target-generating network is a randomly connected recurrent network driven by external input that is strong enough to suppress chaos [ 18 ]. The input to the target-generating network is proportional to the target output f out ( t ), which gives our approach some similarities to the extended FORCE idea discussed above [ 11 , 14 ]. However, in contrast to that approach, the goal here is to minimize the cost function as much as possible rather than relying on limited learning. Because our scheme allows general modifications of the full connection matrix J , but otherwise has similarities to the FORCE approach, we call it full-FORCE. In the following, we provide a detailed description of full-FORCE and illustrate its operation in a number of examples. We show that full-FORCE can construct networks that successfully perform tasks with fewer units and more noise resistance than networks constructed using the FORCE algorithm. Networks constructed by full-FORCE have the desirable property of degrading smoothly as the number of units is decreased or noise is increased. We discuss the reasons for these features. Finally, we note that additional signals can be added to the target-generating network, providing “hints” to the task-performing network about how the task should be performed [ 19 , 20 ]. Introducing task hints greatly improves network learning and significantly extends the range of tasks that can be learned. It also allows for the construction of models that span the full range from the more complex dynamics inherited from random recurrent networks to the often simple dynamics of “hand-built” solutions.",
"discussion": "Discussion We have presented a new target-based method for training recurrently connected neural networks. Because this method modifies the full recurrent connectivity, the networks it constructs can perform complex tasks with a small number of units and considerable noise robustness. The speed and simplicity of the recursive least-squares algorithm makes this an attractive approach to network training. In addition, by dividing the problem of target generation and task performance across two separate networks, full-FORCE provides a straightforward way to introduce additional input signals that act as hints during training. Utilizing hints can improve post-training network performance by assuring that the dynamics are appropriate for the task. Like an animal or human subject, a network can fail to perform a task either because it is truly incapable of meeting its demands, or because it fails to “understand” the nature of the task. In the former case, nothing can be done, but in the latter the use of a well-chosen hint during training can improve performance dramatically. Indeed, we have used full-FORCE with hints to train networks to perform challenging tasks that we previously had considered beyond the range of the recurrent networks we use. The dominant method for training recurrent neural networks in the machine learning community is backpropagation through time [ 3 ]. Backpropagation-based learning has been used successfully on a wide range of challenging tasks including language modeling, speech recognition and handwriting generation ([ 1 ] and references therein) but these tasks differ from the interval timing and delayed comparison tasks we investigate in that they do not have long periods during which the input to the network is silent. This lack of input requires the network dynamics alone to provide a memory trace for task completion, precisely the function of our hint signal. When using backpropagation through time, the network needs to be unrolled a sufficient number of time steps to capture long time-scale dependencies, which, for our tasks, would mean unrolling the network at least the maximum length of the silent periods, or greater than 2,000 time steps. Given well-known gradient instability problems [ 27 ], this is a challenging number of unrollings. While we make no claim that gradient-based learning is unable to learn tasks such as those we study, full-FORCE’s success when a well-selected hint is used is striking given the algorithmic simplicity of RLS and architectural simplicity of the units we use. Although we have highlighted the use of hints in the full-FORCE approach, it is worth noting that hints of the same form can be used in other types of learning including traditional FORCE learning and backpropagation-based learning [ 19 , 20 ]. In these cases, f hint ( t ) would be added as a second target output, along with f out ( t ). By requiring the learning procedure to match this extra output, the network dynamics can be shaped appropriately. Within backpropagation-based learning, doing so might avoid gradient instability problems and perhaps release these methods from a reliance on more complex networks units such as LSTMs (Long Short-Term Memory units; [ 28 ]). Studies of recurrent neural networks that perform tasks vary considerably in their degree of “design”. At one end of this spectrum are hand-tuned models in which a particular solution is hard-wired into the network by construction (examples of this include [ 26 , 29 ]). Networks of this type have the advantage of being easy to understand, but their dynamics tends to be simpler than what is seen in the activity of real neurons [ 24 , 30 ]. At the other extreme are networks that rely on dynamics close to the chaos of a randomly connected network [ 16 ], a category that includes the work of Laje & Buonomano [ 15 ] and much of the work in FORCE and echo-state networks. This approach is useful because it constructs a solution for a task in a fairly unbiased way, which can lead to new insights. Networks of this type tend to exhibit fairly complex dynamics, an interesting feature [ 31 ] but, from a neuroscience perspective, this complexity can exceed that of the data [ 13 , 24 ]. This has led some researchers to resort to gradient-based methods where regularizers can be included to reduce dynamic complexity to more realistic levels [ 13 ]. Another approach is to use experimental data directly in the construction of the model [ 32 , 33 ]. Regularization and adherence to the data can be achieved in full-FORCE through the use of well-chosen hints imposed on the target-generating network. More generally, hints can be used for a range of purposes, from imposing a design on the trained network to regulating its dynamics. Thus, they supply a method for controlling where a model lies on the designed-to-random spectrum. By splitting the requirements of target generation and task performance across two networks, full-FORCE introduces a freedom that we have not fully exploited. The dimension of the dynamics of a typical recurrent network is considerably less than its size N [ 21 ]. This implies that the dynamics of the target-generating network can be described by a smaller number of factors such as principle components, and these factors, rather than the full activity of the target-generating network, can be used to produce targets, for example by linear combination. Furthermore, in the examples we provided, the target-generating network was similar to the task-performing network in structure, parameters ( τ = 10 ms for both) and size. We also made a standard choice for J D to construct a randomly connected target-generating network. None of these choices is mandatory, and a more creative approach to the construction of the target-generating network (different τ , different size, modified J D , etc.) could enhance the properties and performance of networks trained by full-FORCE, as well as extending the range of tasks that they can perform."
} | 4,535 |
26812639 | null | s2 | 7,534 | {
"abstract": "A negatively charged hydrophilic low fouling film was prepared by thermally cross-linking a blend consisting of polystyrene sulfonic acid (PSS) and polyethylene glycol (PEG). The film was found to be stable by dip-washing. The fouling resistance of this material toward bacterial (Escherichia coli) and colloidal (polystyrene particles) attachment, non-specific protein (fibronectin) adsorption and cell (3T3 NIH) adhesion was evaluated and was compared with glass slides modified with polyethylene glycol (PEG) brushes, oxidized 3-mercaptopropyltrimethoxysilane (sulfonic acid, SA), and n-octadecyltrichlorosilane (OTS). The extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory and thermodynamic models based on surface energy were used to explain the interaction behaviors of E. coli/polystyrene particles-substrate and protein-substrate interactions, respectively. The cross-linked PSS-PEG film was found to be slightly better than SA and PEG toward resisting non-specific protein adsorption, and showed comparable low attachment results as those of PEG toward particle, bacterial and NIH-3T3 cells adhesion. The low-fouling performance of PSS-PEG, a cross-linked film by a simple thermal curing process, could allow this material to be used for applications in aqueous environments, where most low fouling hydrophilic polymers, such as PSS or PEG, could not be easily retained."
} | 346 |
35474688 | PMC9035279 | pmc | 7,535 | {
"abstract": "Mine soil is not only barren but also contaminated by some heavy metals. It is unclear whether some rhizobia survived under extreme conditions in the nickel mine soil. Therefore, this study tries to isolate some effective soybean plant growth promoting and heavy metal resistant rhizobia from nickel mine soil, and to analyze their diversity. Soybean plants were used to trap rhizobia from the nickel mine soil. A total of 21 isolates were preliminarily identified as rhizobia, which were clustered into eight groups at 87% similarity level using BOXA1R-PCR fingerprinting technique. Four out of the eight representative isolates formed nodules on soybean roots with effectively symbiotic nitrogen-fixing and plant growth promoting abilities in the soybean pot experiment. Phylogenetic analysis of 16S rRNA, four housekeeping genes ( atpD - recA - glnII - rpoB ) and nifH genes assigned the symbiotic isolates YN5, YN8 and YN10 into Ensifer xinjiangense and YN11 into Rhizobium radiobacter , respectively. They also showed different tolerance levels to the heavy metals including cadmium, chromium, copper, nickel, and zinc. It was concluded that there were some plant growth promoting and heavy metal resistant rhizobia with the potential to facilitate phytoremediation and alleviate the effects of heavy metals on soybean cultivation in nickel mine soil, indicating a novel evidence for further exploring more functional microbes from the nickel mine soil.",
"conclusion": "Conclusions Our study used soybean pot experiment to trap 21 rhizobia strains from nickel mine soil. As a result, we selected three Ensifer xinjiangense strains (YN5, YN8, and YN10) and one Rhizobium radiobacter (YN11) with good nitrogen fixing ability, which can significantly improve the soybean plant height, root length, and biomass yield. Moreover, these four strains carried the symbiotic gene nifH that can encode dinitrogenase reductase enzyme, which further confirmed their abilities to form root nodules and fix nitrogen. E. xinjiangense YN5 and R. radiobacter YN11 tolerated higher levels of heavy metals than E. xinjiangense YN8 and YN10. Taken together, the results showed that the nickel mine soil is a potential source for plant growth promoting rhizobia strains, which could be applied as indigenous inoculants in the phytoremediation of slightly contaminated farmland and in the alleviation of the adverse effects of heavy metals on soybean cultivation.",
"introduction": "Introduction Heavy metal contamination in mining related soils affects both the mining site and the surrounding environment. Heavy metals in soil can originate from natural minerals, yet anthropogenic activities are the main source ( Lebrazi & Fikri-Benbrahim, 2018 ). Heavy metal contamination is a risk to food security, ecological environment, and even to human health through bioaccumulation in the food chain ( Zhang et al., 2012 ; Zhou et al., 2013 ; Long et al., 2021 ; Qin et al., 2021 ; Tauqeer, Turan & Iqbal, 2022 ). Therefore, areas with severe heavy metal-contaminations need to be remediated before being used for the cultivation of crops, and the selected crops should not accumulate contaminants when growing on the slightly-contaminated areas. Remediating the contaminated soils requires efficient and economical methods such as bioremediation, which is considered eco-friendly, secondary contamination-free, and suitable for non-point source contamination ( Shao et al., 2020 ; Zhang et al., 2020 ; Yu et al., 2021 ). Phytoremediation, especially in-situ enhanced phytoremediation, is widely used for the bioremediation of heavy metal-contaminated soil ( Thakare et al., 2021 ). The growth of plants in contaminated soil can be facilitated by utilizing the biological nitrogen fixation (BNF) ability of legume-rhizobia symbionts ( Hao et al., 2014 ; Yu et al., 2017 ; Wang et al., 2019 ; Salmi & Boulila, 2021 ). For example, soybean ( Glycine max L. Merrill) is applicable in remediating heavy metal-contaminated sites ( Li et al., 2019 ). In the symbiosis, rhizobia induce the formation of nodules on the roots of the host plant. Inside the nodules, rhizobia fix atmospheric nitrogen into ammonia which serves as a N source for the legume ( Lindstrom & Mousavi, 2020 ; Wang et al., 2020 ). Inoculation of effective N fixing rhizobial strains leads to the growth promotion of legumes ( Catroux, Hartmann & Revellin, 2001 ). It has been proposed that strains suitable for legume-rhizobia phytoremediation can be isolated from the contaminated sites ( Limcharoensuk et al., 2015 ; Fan et al., 2016 ; Balakrishnan et al., 2017 ; Dhuldhaj & Pandya, 2020 ). Rhizobia include strains with heavy metal resistance and are capable to promote plant growth under heavy metal stress ( Grandlic, Palmer & Maier, 2009 ; Fan et al., 2018b ). It showed that a copper-resistant S. meliloti strain promoted the growth of alfalfa under copper stress ( Duan et al., 2019 ). Rhizobial strains resistant against several heavy metals have the potential to be applied in the in-situ bioremediation of soils contaminated with multiple heavy metals ( Grandlic, Palmer & Maier, 2009 ; Abd-Alla et al., 2012 ; Yu et al., 2014 ; Hao et al., 2015 ; Yu et al., 2017 ; Ke et al., 2021 ). However, indigenous rhizobia resources that could be applied in in situ phytoremediation are still scarce in Southwest China. We hypothesized that heavy metal-contaminated soil could be a putative source for such strains. Thus, soybean plants were used to trap rhizobia from nickel mine soil in Xichang, Sichuan Province, China. The isolates were identified using molecular methods, and soybean growth-promoting abilities and heavy metal resistance of these strains were tested. The results provide better understanding of the potential of using indigenous microbial resources for the alleviation of heavy metal contamination.",
"discussion": "Discussion We trapped rhizobia from nickel mine soil using soybean plants in Xichang, Sichuan Province, China, to find effectively plant growth promoting and heavy metal resistant strains for the enhancement of phytoremediation of heavy metal contaminated soil and for the promotion of soybean growth on slightly contaminated farmland. The low organic matter, N, P and K implied that the soil was barren ( Zhang et al., 2012 ; Wu et al., 2021 ), yet the rhizobia-trapping plants were nodulated, and the isolates from nodules were diverse based on the BOXA1R-PCR fingerprints. However, when inoculated on soybeans, only four out of the eight representative isolates formed nodules on the roots. Similar to rhizobia isolated from Glycyrrhiza spp. ( Li et al., 2012 ), the four non-nodulating isolates may have been sporadic symbionts or other endophytes that had entered the nodules along with a genuine symbiont. Similar to the model inoculant of soybean, Bradyrhizobium diazoefficiens USDA110 ( Sibponkrung et al., 2020 ), inoculation with the symbiotic isolates resulted in over two times higher biomass than in the non-inoculated control; the higher biomass was accompanied with higher shoot nitrogen content. In addition, even the non-nodulating isolates showed some plant growth promoting abilities. Especially, inoculation with all the representative isolates resulted in higher root N content than in the nitrogen-free control. In most of the inoculated plants, the increase in root N content was accompanied with lower P content. As a host plant, soybean is promiscuous and may be nodulated with both fast- and slow-growing rhizobia ( Chen et al., 2021 ). Based on the 16S rRNA gene analysis, three of our isolates were identified as Ensifer americanum, E. fredii or E. xinjiangense , i.e. , species with closely related 16S rRNA genes ( Peng et al., 2002 ; Wang et al., 2013 ). Further analysis using MLSA of the four housekeeping genes assigned the symbiotic isolates into the fast-growing rhizobial species Ensifer xinjiangense and Rhizobium radiobacter , strains of which have been identified as plant growth promoting symbionts of soybean plants ( Peng et al., 2002 ; Iturralde et al., 2019 ). To our knowledge, neither E. xinjiangense (formerly Sinorhizobium xinjiangense ) nor R. radiobacter (formerly Agrobacterium tumefaciens ) strains have been applied as a single-inoculant plant growth promoter in bioremediation, yet co-inoculation of an A. tumefaciens strain with S. meliloti promoted the growth of Medicago lupulina under Cu and Zn stresses ( Jian et al., 2019 ). R. radiobacter is traditionally considered as a plant pathogen and is a free-living nitrogen fixer ( Kanvinde, Sastry & Microbiology, 1990 ). In our study, the amplification and sequencing of the nifH gene, which encodes nitrogenase iron protein, showed that both the Ensifer strains and R. radiobacter YN11 had the genetic potential for nitrogen fixation. The nodulation and plant growth promotion capacity of R. radiobacter YN11 added to the growing body of evidence that when carrying the nodulation genes, Rhizobium ( Agrobacterium ) clade strains can be legume-nodulating symbionts ( Cummings et al., 2009 ). In the soil from mining areas, the concentrations of heavy metals vary considerably from below the background values to hundreds of times higher than the average values for all soils ( Li et al., 2014 ). Bacteria inhabiting the heavy metal-contaminated sites include legume nodulating strains with high tolerance against the metals ( Mohamad et al., 2017 ). In our study, the symbiotic strains showed varied heavy metal resistance; E. xinjiangense YN5 outperformed the other E. xinjiangense isolates and the resistance levels of R. radiobacter YN11 fell in-between. Compared to the rhizobia isolated directly from V-Ti magnetite mine tailing soil and those from the nodules Robinia pseudoacacia in a Pb-Zn mining area ( Yu et al., 2014 ; Fan et al., 2018a ; Fan et al., 2018b ), our isolates tolerated lower levels of Cd 2+ and Cu 2+ . One possible explanation is the level of contamination on the sites where the strains were isolated; the V-Ti magnetite and Pb-Zn mining areas were seriously contaminated ( Yu et al., 2014 ; Fan et al., 2018a ), but only Zn content in the nickel mine soil was higher than in the background value for soils in China ( Li et al., 2014 ). The levels of heavy metals tolerated are approximately 10 to 100 times lower in liquid medium than on solid medium ( Hassen et al., 1998 ). It is also important to take into account the different testing methods for the Zn tolerance of E. xinjiangense YN5. The V-Ti magnetite and Pb-Zn mining area isolates were tested on solid media ( Yu et al., 2014 ; Fan et al., 2018a ) but our isolates in liquid medium, yet E. xinjiangense YN5 tolerated a higher level of Zn 2+ ."
} | 2,689 |
30813443 | PMC6412854 | pmc | 7,536 | {
"abstract": "Solution-processable nonvolatile memory devices, consisted of graphene oxide (GO) embedded into an insulating polymer polymethyl methacrylate (PMMA), were manufactured. By varying the GO content in PMMA nanocomposite films, the memristic conductance behavior of the Ni/PMMA:GO/Indium tin oxide (ITO) sandwiched structure can be tuned in a controllable manner. An investigation was made on the memristic performance mechanism regarding GO charge-trap memory; these blends were further characterized by transmission electron microscope (TEM), scanning electron microscope (SEM), Fourier transform infrared spectra (FTIR), Raman spectra, thermogravimetric analysis, X-ray diffraction (XRD), ultraviolet-visible spectroscopy, and fluorescence spectra in particular. Dependent on the GO content, the resistive switching was originated from the charges trapped in GO, for which bipolar tunable memristic behaviors were observed. PMMA:GO composites possess an ideal capability for large area device applications with the benefits of superior electronic properties and easy chemical modification.",
"conclusion": "4. Conclusions The ITO/PMMA:GO/Ni structure that is capable of exhibiting bistably bipolar memristic characteristics, is demonstrated. Electrical conductance behaviors, turn-on voltage, and ON/OFF state current ratio, can be tuned through the control of the GO content in the composites. Under ambient conditions, both the OFF-state and ON-state of the bistable memory devices are stable under a constant voltage stress. The conductance switching effects of the composites can be attributed to electron trapping in GO sheets. With the benefits of its solution processability and good performance, the PMMA:GO composite memory device is potentially useful for high capacity and low-cost data storage in electronics in the future.",
"introduction": "1. Introduction Resistive Random Access Memory (ReRAM), as a disruptive technology, can be compatible with conventional semiconductor processes, attracting much attention [ 1 , 2 ]. It can revolutionize the product performance in digital memories, particularly capable of substituting all current up-to-date memories like hard disk drives, random-access memories, and Flash memories. Among all the technology candidates, memristor-based ReRAM operates faster than phase change random access memory (PCRAM), and it possesses not a simpler, but a smaller cell structure than magnetic random access memory (MRAM) or shared transistor technology random access memory (STT-RAM) [ 3 , 4 , 5 ]. Confronted with a traditional Metal-Oxide-Semiconductor (MOS)-accessed memory cell, memristor-based RRAM bears the promising potential of forming a cross-point structure without access devices, for the sake of achieving an ultra-high density form of data storage. That is one of the emerging memory technologies, with a two-terminal metal-insulator-metal (MIM) configuration. Induced by applying different voltages to the device terminals, it utilizes functional materials switching among more than two distinct resistance states. Based on memristors where migrating oxygen atoms give rise to changable resistance, metal oxide nanolayers are investigated by many companies, shifted by voltage pulses, with the fact that the electric field leads to conducting filaments through an insulating oxide. Relying on the bistable resistance states, this device can be used with nearly any oxide material, such as NiO, ZnO, ZrO 2 , HfO 2 , SrZrO 3 , and BaTiO 3 [ 6 , 7 , 8 , 9 , 10 ]. Confronted with theoretical and physical restrictions for conventional Si-based memory devices, a great number of efforts have been made to exploit novel functional materials for remarkable resistive switching behaviors in future memristors. Doping carbon-based nanomaterials as charge acceptors into organic matrix has attracted considerable interest for memristors [ 11 , 12 , 13 , 14 , 15 ]. The design and synthesis of a solution-processable polymer nanocomposite with tunable doping levels, predominantly desirable for memory device applications, can not only tailor the electronic memristor characteristics but also acquire excellent chemical, mechanical, and biocompatible properties. An ultrathin 2D-layered material graphene oxide (GO) plays a crucial role in developing electronic devices on the basis of atomically thin films. The chemical structure of GO has carbonyl and carboxyl groups at the edge of the plane. Doping levels of GO in the polymer nanocomposites will have a crucial influence on the charge transport processes in the bulk and at the interface, because of the excellent electronic properties of graphene, and this will consequently impact on memristic performance [ 16 , 17 , 18 , 19 , 20 , 21 ]. The electrical properties of GO-based nanocomposite films can be regulated by the amount of oxygen-functional groups that are attached to GO sheets, so that GO-based hybrid films can act as a remarkable active layer in memristors. Herein, GO charge-trap memory devices, which are composed of polymethyl methacrylate (PMMA) blended with GO, were demonstrated by both simple and cost-effective solution-processable techniques at relatively low temperature. Although the memristic behaviors can be tunable by the GO content, we focus on the operating mechanism, as well as the influence of GO on the device performance. The prepared PMMA:GO nanocomposites were analyzed by means of transmission electron microscope (TEM), scanning electron microscope (SEM), Fourier transform infrared spectra (FTIR), Raman spectra, thermogravimetric analysis (TGA), X-ray diffraction (XRD), ultraviolet-visible spectroscopy, and fluorescence spectra. The principle for the memristic characteristics based on the GO charge trap was represented by fluorescent quenching."
} | 1,439 |
26173699 | PMC4502231 | pmc | 7,537 | {
"abstract": "ABSTRACT In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC ( https://img.jgi.doe.gov/abc ), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG’s comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC’s focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in Alphaproteobacteria . IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules.",
"conclusion": "Conclusion. Computation of biosynthetic gene clusters in newly loaded genomes and metagenomes and their maintenance are now part of the IMG data-loading and annotation pipeline. The growing number of predicted BCs, in conjunction with continuous development of the analysis and search functions available through the system, will ensure that IMG-ABC will always have the latest and most complete publicly available information for the study of secondary metabolism in microbial genomes and metagenomes.",
"introduction": "INTRODUCTION Secondary metabolites (SMs) are small organic compounds that are not essential to the life of an organism but have, nevertheless, a broad biological activity spectrum. SMs derived from plants have been used for thousands of years in the form of natural extracts due to their pharmacological properties ( 1 ), while in the modern era, SMs from plants and microorganisms have been a rich source of therapeutics ( 2 ). Certain classes of SMs, such as terpenes, are good candidates for biofuel production ( 3 ). SMs serve as important chemical agents of communication between bacteria in complex communities or in symbiotic relationships, such as in plant-microbe interactions ( 4 ). In this context, some SMs provide biological control of plant pathogens and thus may have important agricultural applications ( 5 ). Discovery of new SMs, therefore, will benefit the development of novel biotechnological applications and provide better understanding of the interactions within complex communities. Traditionally, microbial SMs have been isolated by screening cultured microbes for the desired pharmacological and/or biological activity ( 6 ). This approach has its limitations, since many microorganisms are difficult or impossible to obtain in pure culture. Additionally, the bioactive chemicals may not be produced due to the absence of specific environmental stimuli or may remain undetectable through conventional screening methods ( 7 – 9 ). The rapid growth of genomic data from both isolate organisms and microbial communities (metagenomes) ( 10 ), in conjunction with the development of tools for computational identification and classification of biosynthetic gene clusters (BCs) ( 11 , 12 ), present a new opportunity for the discovery of SMs with novel chemical structures ( 13 ). Computationally identified BCs can be cloned or synthetically reconstructed and expressed in heterologous systems, which can then be monitored for the production of potentially novel metabolites. Further, the application of this approach to uncultured strains in single cells and metagenomes enables the detection of SM pathways in microbial dark matter ( 14 ). In response to an increasing interest in the identification of novel microbial SMs, a number of databases have been developed in recent years with information on BCs and SMs. StreptomeDB is a database focused on bioactive molecules produced by members of the Streptomyces genus ( 15 ). DoBISCUIT provides carefully curated annotations of a limited number of BCs ( 16 ), while Clustermine360 focuses on polyketide synthase (PKS) and nonribosomal peptide synthetase (NRPS) type clusters and allows for user submissions of clusters ( 17 ). ClustScanDB provides detailed information about thiotemplate modular systems ( 18 ). Although some of these efforts provide useful high-quality manually curated annotations, they come at the cost of narrow specificity and often have no or limited maintenance. Most of these systems are limited either by specific classes of organisms (e.g., Streptomyces ) or biosynthetic cluster types (e.g., NRPS/PKS). Additionally, some have relatively few records and do not provide the tools for in-depth sequence analyses, while others are no longer updated. In order to alleviate some of the above limitations and to pave the way from big data to small molecules, we have developed IMG-ABC, an a tlas of b iosynthetic gene c lusters within the Integrated Microbial Genomes (IMG) system. IMG-ABC is a database of biosynthetic gene clusters and the chemicals they are known to produce and, through its integration with the IMG data management system ( 10 , 19 ), it provides the following capabilities: (i) access to an exhaustive collection of both predicted and published BCs in over 23,000 public isolate microbial genomes and more than 2,200 metagenomes; (ii) class-agnostic inclusion of all classes and types of BCs and SMs; (iii) integration with structural and functional annotations and metadata from IMG and the Genomes Online Database (GOLD) ( 20 ); (iv) enhanced search and analysis capabilities; (v) expert user curation capability; (vi) a track record of continuous maintenance and user support. As newly sequenced data sets are integrated into IMG, they are automatically processed through IMG’s BC prediction pipeline, constantly feeding IMG-ABC with new putative BCs. We expect IMG-ABC to become the primary starting point for the sequence analysis of BCs and to provide the knowledge base needed for the heterologous expression of BCs that produce novel and potentially useful chemical compounds.",
"discussion": "DISCUSSION In the last few years, there has been a resurgence of interest in the discovery of natural products, and this resurgence has been fueled by the explosion in the availability of microbial genomic sequences and the expansion of sampling to previously unstudied habitats and environments. However, a very large gap exists between the throughput of sequencing and the rate of discovery of novel pathways involved in secondary metabolism, predominantly because of the absence of tools that facilitate this intellectually and computationally difficult task. Additionally, no public resources exist that allow for the global analysis and comparison of putative biosynthetic gene clusters. These analyses have been accessible only to laboratories staffed with computational biologists and with access to high-performance computing resources. For the first time, IMG-ABC links information regarding genomic pathways for the biosynthesis of secondary metabolites with chemical structure information on a scale of several thousand data sets. With careful efforts for quality control, it combines the predictive power of state-of-the-art computational tools, such as ClusterFinder and AntiSMASH, with the exhaustive analysis framework offered by the IMG family of systems. This combination delivers a powerful punch, predicting both familiar and novel biosynthetic gene pathways in thousands of cultured isolates, single cells, and metagenomes. Future work: filling four existing knowledge gaps. (i) Pairwise similarities. By computing pairwise similarities between biosynthetic pathways, we will annotate new BCs demonstrating very high similarity scores (indicating equivalence) with validated biosynthetic pathways. This process will also shed light on previously unknown enzymatic mechanisms. (ii) Computationally linking SMs with BCs. Traditionally, secondary metabolites were extracted from cultures of isolate organisms and tested for activity, often without any effort to identify the biosynthetic gene cluster responsible for the compound’s synthesis. However, in many cases, the genome of the producing organism has since been sequenced and, therefore, it may be feasible to computationally link SMs with BCs. We will explore new approaches to use IMG-ABC’s extensive collection of predicted BCs and whole-genome sequences to discover the relevant, but unknown, biosynthetic pathways for organisms known to produce specific compounds. (iii) A searchable database of predicted SM backbone structures. We will create a searchable database of predicted SM backbone structures for the more than 30,000 BCs that contain either NRPS or type I PKS enzymes ( 12 , 32 , 33 ). This function will be extremely useful for the identification of interesting chemical scaffolds that may be useful starting points for combinatorial chemistry. (iv) Compatibility and synchronization with the MIBiG centralized database. A major obstacle in collecting data describing experimentally verified BCs and SMs is the absence of a standardized way of reporting these data in public databases. Recently, a consortium of scientists have undertaken the Minimum Information about a Biosynthetic Gene cluster (MIBiG) initiative to provide structured data and high-quality annotations of BCs and the SMs they produce. In the future, we plan to adopt the database structure of MIBiG within IMG-ABC and perform regular synchronizations with the MIBiG centralized database to ensure that the content of experimentally verified data sets in IMG-ABC will continue to grow and reflect the most current and accurate public information. Conclusion. Computation of biosynthetic gene clusters in newly loaded genomes and metagenomes and their maintenance are now part of the IMG data-loading and annotation pipeline. The growing number of predicted BCs, in conjunction with continuous development of the analysis and search functions available through the system, will ensure that IMG-ABC will always have the latest and most complete publicly available information for the study of secondary metabolism in microbial genomes and metagenomes."
} | 2,695 |
22678395 | PMC4902277 | pmc | 7,538 | {
"abstract": "Metagenomics holds enormous promise for discovering novel enzymes and organisms that are biomarkers or causes of processes relevant to disease, industry and the environment. In the last two years we have seen a paradigm shift in metagenomics to the application of broad cross-sectional and longitudinal studies enabled by advances in DNA sequencing and high-performance computing. These technologies now make it possible to broadly assess microbial diversity and function, allowing systematic investigation of the largely unexplored frontier of microbial life. To achieve this aim, the global scientific community must collaborate and agree upon common objectives and data standards to enable comparative research across the Earth’s microbiome. Improvements in comparability of data will facilitate the study of biotechnologically relevant processes such as bioprospecting for new glycoside hydrolases or identifying novel energy sources.",
"conclusion": "Conclusion As it occurred with many other technologies such as computing, telecommunications and photography (which, like sequencing, began with scientific applications but rapidly transformed consumers’ lives across the globe), metagenomics is in a time of transition. The community is moving from a situation in which technologies are first deployed centrally by large organizations, then by departments, by individual laboratories, and it is perhaps not unreasonable to speculate that sequencing devices will soon be owned by individuals, perhaps even in a handheld format. Standard protocols are necessary to integrate the information and to allow easy communication across studies—after all, the role played by the internet in today’s world is only possible because computers everywhere can communicate with a set of standard, open protocols. While currently these initiatives are focused on DNA sequencing (amplicon sequencing and metagenomics), it will be necessary to determine integration of metabolomics, proteomics and single-cell genomics into these efforts to improve community characterization, and enable more appropriate ecological inferences. The ‘omics ratio (ratio of applied techniques, e.g. genomics:transcriptomics:proteomics:metabolomics) should always be determined by the hypothesis. We believe and hope that MIxS and the EMP will enable the same type of functionality for ecologists, allowing us to construct not just a catalog of organisms on Earth but also to understand and exploit the critical processes they perform in the environment over a vast range of spatial and temporal scales.",
"introduction": "Introduction The Earth hosts more than 10 30 microbial cells 1 , a figure that exceeds the number of known stars in the universe by nine orders of magnitude. This richness of single-celled life, the first life to evolve on the planet, still accounts for the vast majority of functional drivers of our planet’s ecosystems 2 . Yet the diversity and interdependencies of these microscopic organisms remain largely unknown. Likewise, our understanding of the functional potential of most individual microbial taxa residing within any ecosystem is extremely limited and generally restricted to measurements of gross enzymatic processes of the community. Moreover, sequenced metagenomic datasets have, to date, only played a limited role in biotechnological knowledge discovery, with the majority of novel developments occurring through heterologous expression of enzymes. Our knowledge of microbial diversity on Earth is poised to be revolutionized by the development of new technologies that will permit us to ‘see’ the ‘who, what, when, where, why, and how?’ of microbial communities. Most recently, next-generation sequencing methods have begun to rapidly improve our understanding of the functional and evolutionary processes necessary to advance the field of microbial ecology. Matching these technological strides are progress in scientific community cooperation, increases in interdisciplinary interaction, and the development of standards for experimental and sample contextual “metadata” acquisition, which are essential for downstream interpretation 3 . Here we discuss how advances in DNA sequencing, the handling of contextual data and improvements in study design can unlock the potential of metagenomics. We discuss the need for robust experimental design 4 (e.g., replication and improved ecosystem characterization) and highlight the need for an Earth Microbiome Project that will rely on metagenomics to explore Earth’s microbial dark matter across temporal and spatial scales and simultaneously facilitate novel gene discovery. Through standardized data generation approaches and metadata collection, we stand poised to make rapid progress toward advancing biotechnological goals."
} | 1,185 |
34276750 | PMC8280758 | pmc | 7,541 | {
"abstract": "Phosphorus (P) availability is usually low in soils around the globe. Most soils have a deficiency of available P; if they are not fertilized, they will not be able to satisfy the P requirement of plants. P fertilization is generally recommended to manage soil P deficiency; however, the low efficacy of P fertilizers in acidic and in calcareous soils restricts P availability. Moreover, the overuse of P fertilizers is a cause of significant environmental concerns. However, the use of arbuscular mycorrhizal fungi (AMF), phosphate–solubilizing bacteria (PSB), and the addition of silicon (Si) are effective and economical ways to improve the availability and efficacy of P. In this review the contributions of Si, PSB, and AMF in improving the P availability is discussed. Based on what is known about them, the combined strategy of using Si along with AMF and PSB may be highly useful in improving the P availability and as a result, its uptake by plants compared to using either of them alone. A better understanding how the two microorganism groups and Si interact is crucial to preserving soil fertility and improving the economic and environmental sustainability of crop production in P deficient soils. This review summarizes and discusses the current knowledge concerning the interactions among AMF, PSB, and Si in enhancing P availability and its uptake by plants in sustainable agriculture.",
"conclusion": "Conclusion P is a vital element in crop nutrition. Adverse environmental effects of chemical-based P fertilizers have compelled us to find a sustainable approach for efficient P availability in agriculture to meet the ever-increasing global demand of food. According to the review paper, the use of AMF, PSB, and the addition of Si can be an effective and economical way to improve the availability and efficacy of P. Based on what is known about them, the combination of AMF, PSB, and Si (or SSB) may be utilized as a strategy for improving plant growth in P-deficient soils and minimizing chemical fertilization to exercise sustainable agriculture ( Figure 5 ). The combination can help plants effectively utilize the low-solubility P sources by solubilizing them into utilizable forms that are later absorbed by plants. This may assist in solving problems encountered with the crop production economy and food shortages, which also make the co-inoculation with Si or SSB a promising technique for use in commercial inoculant formulations. FIGURE 5 Synergetic role of among arbuscular mycorrhizal fungi (AMF), phosphate-solubilizing bacterium (PSB), and silicon (Si) in improving phosphorus (P) uptake by plant.",
"introduction": "Introduction There is a growing need to improve food production to meet the requirements of the increasing world population. This may be done in either of two ways: increasing the area under cultivation or enhancing the yield per unit area. The former is not possible in many countries of the world due to a number of restrictions including the availability of water or soil resources, climate change, drought, and soil salinization ( Etesami and Noori, 2019 ). On the other hand, one of the ways to increase the yield per unit area is to improve the nutritional properties of the soil. As an essential plant nutrient, P is required for carbon metabolism, energy generation, energy transfer, enzyme activation, membrane formation, and nitrogen (N 2 ) fixation ( Schachtman et al., 1998 ). P also forms key biological molecules like ATP, nucleic acids, and phospholipids ( Marschner, 1995 ). P deficiency is a significant limiting factor for the growth and yield of crops that affects approximately 50% of all agricultural ecosystems around the world ( Lynch, 2011 ; Ringeval et al., 2017 ; Etesami, 2020 ). To address this issue, there has been an enormous worldwide increase in the use of P fertilizers. The high agricultural P demand has put the sustainability of P mining for fertilizer production into question ( Elser, 2012 ). P fertilizers often lead to the addition of a large excess of P in agricultural soils. Unfortunately, >80% of the P fertilizers applied to the soil is lost due to adsorption and fixation processes ( de La Vega et al., 2000 ; Vance et al., 2003 ) or it is transformed into organic forms ( Holford, 1997 ), which represent 40–80% of total soil P ( Bünemann et al., 2010 ), with phytates as the most common form ( Menezes-Blackburn et al., 2014 ). Therefore, the availability of this added P to plants is limited (about 0.1% of the total P). P is usually absorbed by the plant in a limited range of soil conditions, i.e., pH 6.5–7 as H 2 PO 4 – and HPO 4 2– . When the soil pH exceeds 7.0, inorganic phosphate (Pi) is predominantly mineralized and immobilized as calcium phosphates. At lower soil pH levels, P is usually bound/adsorbed by soluble aluminum (Al), iron (Fe), manganese (Mn), or the associated hydrous oxides ( Brady and Weil, 1999 ). At neutral pH, Pi adsorbs to weathered silicates such as clay minerals ( Rajan, 1975 ). Thus, the P concentration in soils with pH < 6.5 or pH > 7 is suboptimal, and is generally about 1–10 μM ( Schachtman et al., 1998 ), which can result in crop yield depressions of 5–15% ( Shenoy and Kalagudi, 2005 ). The theoretical increase in plant growth efficiency from adding chemical P fertilizers has peaked so that additional chemical P fertilization cannot be expected to significantly increase plant yield ( Etesami, 2020 ). Twenty-two million tons of P (3–4% of the total P demand) are annually extracted from natural sources (i.e., non-renewable phosphate rocks), according to the US geological survey ( Gaxiola et al., 2011 ), which puts the natural P sources in risk of depletion ( Cordell et al., 2009 ). Therefore, a more efficient use of P is needed, including maximizing P acquisition and utilization efficiencies ( Veneklaas et al., 2012 ). Some plants can efficiently acquire and/or use P to maintain metabolism and growth ( Lambers et al., 2010 ; Aziz et al., 2014 ). Some plant mechanisms for improving P acquisition efficiency include ( Ramaekers et al., 2010 ; Johri et al., 2015 ): (i) increased expression of high affinity P transporters; (ii) soil exploration at a minimal metabolic cost; (iii) topsoil foraging; (iv) stimulation of root hair growth; (v) redistribution of growth among root types; (vi) increase of the root-to-shoot ratio; (vii) the secretion of organic acids (e.g., citrate, malate, or oxalate) from roots to the soil; (viii) the activation of an advanced bio-molecular system; and (xi) enhanced acid phosphatase (rAPase) or phytase secretion. Plants have also developed some biotic interactions with diverse soil microorganisms that promote plant growth. Arbuscular mycorrhizal fungi (AMF) and plant growth-promoting bacteria (PGPB) are the most common such microorganisms. AMF and PGPB, and especially the phosphate-solubilizing bacteria subgroup (PSB), are known to help overcome P deficiency in plants. PSB and AMF are a part of the key biogeochemical cycling processes ( Sharma et al., 2013 ; Etesami, 2020 ). Phosphate–solubilizing bacteria exist in most soils ( Rodrìguez and Fraga, 1999 ). In in vitro conditions, they can improve P bioavailability by lowering the soil pH, solubilizing Pi, activating synthesized phosphatases, mineralizing organic P, and/or chelating P from Al 3+ , Ca 2+ , and Fe 3+ ( Rodrìguez and Fraga, 1999 ; Browne et al., 2009 ; Sharma et al., 2013 ; Etesami, 2020 ). Nearly all soils also contain AMF, which associate with approximately 80% of all plant roots ( Smith and Read, 2008 ; Brundrett and Tedersoo, 2018 ). The ability of AMF to promote plant growth and yield and enhance P uptake has been well documented ( Miransari, 2010 ; Jansa et al., 2011 ; Smith et al., 2011 ; Smith and Smith, 2011 ; Nadeem et al., 2014 ; Brundrett and Tedersoo, 2018 ; Etesami, 2020 ). As a consequence of variable soil conditions, microorganisms may change crop productivity. Climate change also has a substantial impact on the effectiveness of microorganisms. One way to increase the efficiency of microorganisms under adverse environmental conditions is the co–inoculation of microorganisms ( Nadeem et al., 2014 ; Etesami et al., 2015b ; Etesami and Maheshwari, 2018 ; Ghorchiani et al., 2018 ) that stimulates plant growth through various mechanisms ( Bashan et al., 2004 ). AMF and PGPB can work together to yield sustainable plant growth in malnourished environments ( Zarei et al., 2006 ; Mohamed et al., 2014 ; Nadeem et al., 2014 ; Lee et al., 2015 ; Xun et al., 2015 ). Combinations of AMF and PGPB are commonly used to increase crop yields ( Mäder et al., 2011 ; Ghorchiani et al., 2018 ), improve fruit quality ( Ordookhani et al., 2010 ; Bona et al., 2016 ), boost phytoremediation, enhance the fertilizer nutrient use efficiency ( Xun et al., 2015 ), lower chemical fertilization application requirements ( Adesemoye et al., 2009 ), and increase salinity tolerance ( Gamalero et al., 2009 ). The use of silicon (Si) fertilizer has also been proposed as an environmentally friendly, ecologically compatible method of improving plant growth and the resistance to multiple environmental stresses including nutritional imbalances ( Etesami and Jeong, 2018 , 2020 ; Etesami et al., 2020 ). Previous studies have reported that Si increases plant uptake of P ( Kostic et al., 2017 ; Neu et al., 2017 ; Rezakhani et al., 2019a , b ; Schaller et al., 2019 ). Combining Si and microorganism applications has been proposed to effectively induce improved plant growth and nutrition ( Etesami, 2018 ; Etesami and Adl, 2020 ). Previous studies have observed that AMF and Si work together to improve plant growth regardless of the stress conditions ( Hajiboland et al., 2018 ; Moradtalab et al., 2019 ), and that PSB and Si synergistically help plants better uptake P ( Rezakhani et al., 2019a , b ). However, how AMF, PSB and Si interact to affect P availability for plants is poorly understood. Thus, a better understanding of the interactions of AMF, PSB and Si would allow growers to rely less on chemical P fertilizers and instead utilize biological processes to maintain fertility and enhance plant growth. Hence, this review discusses the mechanisms which AMF, PSB, and Si, individually and together, use to increase plant uptake of P in agricultural systems where proper nutrition might otherwise suggest heavy use of P fertilizers. This review also highlights future research needs regarding how to improve plant uptake of P using AMF, PSB, and Si. In addition, the role of silicate-solubilizing bacteria (SSB), which convert insoluble silicate forms to available forms for the plant, in increasing P and Si availability and their uptake by plants is discussed."
} | 2,687 |
32624978 | PMC6999062 | pmc | 7,543 | {
"abstract": "Abstract Current global environmental issues raise unavoidable challenges for our use of natural resources. Supplying the human population with clean water is becoming a global problem. Numerous organic and inorganic impurities in municipal, industrial, and agricultural waters, ranging from microplastics to high nutrient loads and heavy metals, endanger our nutrition and health. The development of efficient wastewater treatment technologies and circular economic approaches is thus becoming increasingly important. The biomass production of microalgae using industrial wastewater offers the possibility of recycling industrial residues to create new sources of raw materials for energy and material use. This review discusses algae‐based wastewater treatment technologies with a special focus on industrial wastewater sources, the potential of non‐conventional extremophilic (thermophilic, acidophilic, and psychrophilic) microalgae, and industrial algae‐wastewater treatment concepts that have already been put into practice.",
"conclusion": "6 CONCLUDING REMARKS Clean water has become a limiting resource in many regions of the world. The most efficient approach to reduce the pollution of water resources with nitrates, phosphates, and high organic loads is to remove these components at the point of origin, i.e. at the processing sites. However, conventional biological WWT systems are often unable to fulfil this cleaning task because the pH values, high organics, or temperatures are often non‐compatible to microbiological physiology. Extremophilic microalgae offer a potential means, so‐far largely unexplored, to solve this problem. Microalgae in general, conventional and extremophile can play an important role in a circular bio‐economy by providing high‐quality products, such as proteins, lipids, and colorants, within the biomass produced by the WWT cleaning process. Some selected examples of algae‐based WWT technologies have been reviewed here, with a special focus on concepts that have been validated at technical scale.",
"introduction": "1 INTRODUCTION Water is one of the most important natural resources on our planet. However, in addition to an inadequate clean water supply in many developing countries, water quality in industrialized nations has reached a worrying state 1 , 2 . The pollution of municipal, agricultural, and industrial wastewater with a huge number of organic and inorganic contaminants, such as microplastics 3 , xenobiotics 1 , heavy metals 4 , and high concentrations of nitrates 5 , phosphates 6 , and carbon (C) compounds 2 , puts a strain on the food chain and thus the basis of human life. Wastewater treatment (WWT) is a global issue that cannot be managed by a single technology because of the extremely variable scales, types of contaminants, and regional conditions involved (Figure 1 ). Figure 1 Wastewater sources and their typical impurities Conventional WWT plants focus on the removal of suspended solids (mostly mechanically) and the reduction of biological oxygen demand by activated sludge 7 . This biodegradation involves the breakdown of organic molecules and inorganic constituents (nitrogen [N] and phosphorous [P] compounds), which is of great importance to prevent the eutrophication of downstream waters such as rivers and lakes. The degradation capacity of these conventional technologies is limited, especially with regard to heavy metals, extremely high nutrient loads, and xenobiotics, leading to an increasing accumulation of these substances in groundwater 1 , 2 , 3 , 4 , 5 , 6 . Because of the metabolic flexibility of microalgae, i.e. their ability to perform photoautotrophic, mixotrophic, or heterotrophic metabolism 8 , 9 , they represent promising biological systems for treating a variety of sources of wastewater. In particular, in the context of a circular and bio‐based economy and the development of biorefinery concepts 10 , microalgae biomass produced from wastewater streams offers a great potential for sustainable bioproducts (dependent on national legislation on reusing microalgae biomass/bioproducts), such as proteins 11 , fatty acids 12 , pigments 13 , biofertilizers/biochar 14 , 15 , and animal feed 16 . Algae‐based WWT technologies have in fact been researched since the 1950s, mainly because of their very efficient fixation of inorganic N and P. The usage of microalgae in WWT plants has two main aims: (1) the direct uptake or transformation of water contaminants, and/or (2) improving the purification performance of bacterial systems (microalgae‐bacteria aggregates) by providing additional oxygen from photosynthesis (symbiotic cocultures), thus reducing the total energy costs of direct (gassing performance) or indirect (stirring performance) oxygen supply 17 . Until now, research on algae‐based WWT has focused mainly on the conventional microalgae and cyanobacteria such as Chlorella ssp. 18 , Arthrospira ssp. 19 , Scenedesmus ssp. 20 , and Nannochloropsis ssp. 21 , 22 because of their potential to accumulate high levels of lipids and starch. This review provides an overview of these biological systems, with a particular focus on the potential application of extremophilic microalgae (thermophilic, psychrophilic, and acidophilic), the technological systems used for WWT (suspension vs. immobilized systems), and algae based WWT approaches that have already been put into practice. PRACTICAL APPLICATION This minireview presents the biological and technological approaches concerning microalgae‐based wastewater treatment technologies. The biological and technical systems must be adapted to the respective wastewater conditions, since the scale and composition of the wastewater sources can vary greatly. The minireview shows different solution strategies, especially for the treatment of industrial wastewater. The special focus is on the distinction between immobilized and suspended biological systems, the potential of extremophilic microalgae and the presentation of plant concepts that have already been implemented on a technical scale."
} | 1,516 |
28344249 | PMC5304690 | pmc | 7,544 | {
"abstract": "During evolution, living organisms have learned to design biomolecules exhibiting self-assembly properties to build-up materials with complex organizations. This is particularly evidenced by the delicate siliceous structures of diatoms and sponges. These structures have been considered as inspiration sources for the preparation of nanoscale and nanostructured silica-based materials templated by the self-assembled natural or biomimetic molecules. These templates range from short peptides to large viruses, leading to biohybrid objects with a wide variety of dimensions, shapes and organization. A more recent strategy based on the integration of biological self-assembly as the driving force of silica nanoparticles organization offers new perspectives to elaborate highly-tunable, biofunctional nanocomposites.",
"conclusion": "5. Conclusions The biological routes by which living organisms create elaborated hierarchical silica structures are still far from being fully understood. Model in vitro systems have suggested that a combination of silica formation activation via attractive electrostatic interactions and biomolecular self-assembly providing multi-scale templating is involved in the biopatterning process. These guidelines have proven useful for the synthesis of a wide diversity of artificial siliceous structures with complex morphology. Recent works indicate that it is possible to go beyond the sole structural properties of self-organized biomolecules and to take advantage of their intrinsic biological activity to design biofunctional silica nanoparticle assemblies. We strongly believe that it opens the way towards highly-tunable new materials with a wide diversity of compositions, structures and properties and, ultimately, applications.",
"introduction": "1. Introduction Biomineralization encompasses all biological pathways leading to the formation of a condensed inorganic phase [ 1 ]. As such, it includes both biologically-induced and biologically-controlled precipitation. In the first situation, the formation of the inorganic solid is adventitious, arising from non-specific interactions between mineral sources and components or metabolic products of living organisms. In the second case, mineralization occurs through a complex cellular pathway by the production of specific molecules that control the composition, shape, organization and, ultimately, the properties and functions of the inorganic phase. Because such a control implies a strong intimacy between the inorganic system and the biomolecules involved in mineralization control, resulting biominerals are in fact composite materials, where the organic fraction can range from less than 1 wt% (urchin spikes) to 50 wt% (crab shells) [ 2 ]. These molecules have three main functions: confinement (to control mineral particle size), activation (to control mineral sources concentrations) and templating (to control particle morphology) [ 3 ]. Ultimately, these functions also contribute to the spatial organization of the particles within the composite structure. Thus, one of the key properties of biomineralizing molecules is their self-assembly ability, either as single components or cooperatively with others. These self-assembly processes have largely contributed to the merging of experts in material science, earth science, biology and medicine in order to achieve a better understanding of biomineralization pathways. In chemistry, one of the main motivations was related to the possibility to mimic or get inspired by biological routes for the design of novel synthetic strategies and/or new objects [ 4 ]. In this context, the possibility to control the formation and organization of inorganic particles from the nano- to the macroscale using soft matter principles raised great hopes for the development of chemically-diverse, structurally-complex and bio-responsive devices [ 5 , 6 , 7 ]. Silica-based materials occupy a specific position in this field. Silicon is the most abundant element in soils, a fraction of which originates from the sedimentation and diagenesis of biogenic silica. This is related to the fact that biosilicification occurs in many living organisms, being terrestrial (higher plants) or aquatic (diatoms, radiolarians, sponges) [ 8 ]. Biogenic silica materials often exhibit astonishing morphologies that have no synthetic equivalent. This reflects the malleability of silica in a hydrated amorphous form, as obtained by condensation of silicic acid in ambient conditions [ 9 ]. Such a malleability is in fact one of the major factors explaining the wide use of silica as the main component of many synthetic materials. Therefore it does not come as a surprise that biomimetic or bio-inspired routes to silica-based materials have been widely developed. Several reviews covering the principles and applications of these approaches are available [ 10 , 11 , 12 ]. In this paper, we choose to focus on one specific aspect of biosilicification processes and biomimetic/bioinspired silica synthesis that is the role and use of biomolecular self-assembly for the controlled formation of nanoscale and nanostructured materials. After a brief presentation of the current knowledge of self-organization pathways in diatoms and sponges, we describe how natural or nature-like molecules, from peptides to virus, can be used as templates for silica formation. As a perspective, we introduce an alternative strategy to combine biological molecules and silica via a bottom-up approach that opens a wide range of possibilities for the design of functional bionanocomposites."
} | 1,388 |
29230893 | null | s2 | 7,546 | {
"abstract": "Host-associated microbial communities consist of stable and transient members that can assemble through purely stochastic processes associated with the environment or by interactions with the host. Phylosymbiosis predicts that if host-microbiota interactions impact assembly patterns, then one conceivable outcome is concordance between host evolutionary histories (phylogeny) and the ecological similarities in microbial community structures (microbiota dendrogram). This assembly pattern has been demonstrated in several clades of animal hosts in laboratory and natural populations, but in vertebrates, it has only been investigated using samples from faeces or the distal colon. Here, we collected the contents of five gut regions from seven rodent species and inventoried the bacterial communities by sequencing the 16S rRNA gene. We investigated how community structures varied across gut regions and whether the pattern of phylosymbiosis was present along the length of the gut. Gut communities varied by host species and gut region, with Oscillospira and Ruminococcus being more abundant in the stomach and hindgut regions. Gut microbial communities were highly distinguishable by host species across all gut regions, with the strength of the discrimination increasing along the length of the gut. Last, the pattern of phylosymbiosis was found in all five gut regions, as well as faeces. Aspects of the gut environment, such as oxygen levels, production of antimicrobials or other factors, may shift microbial communities across gut regions. However, regardless of these differences, host species maintain distinguishable, phylosymbiotic assemblages of microbes that may have functional impacts for the host."
} | 428 |
37351294 | PMC10284049 | pmc | 7,549 | {
"abstract": "Abstract One of the most intriguing questions in eusocial insects is to understand how the overt reproductive conflict in the colony appears limited when queens or kings are senescent or lost because the morphologically similar individuals in the colony are reproductively totipotent. Whether there are some individuals who preferentially differentiate into replacement reproductives or not has received little attention. The consistent individual behavioral differences (also termed “animal personality”) of individuals from the colony can shape cunningly their task and consequently affect the colony fitness but have been rarely investigated in eusocial insects. Here, we used the termite Reticulitermes labralis to investigate if variations in individual personalities (elusiveness and aggressiveness) may predict which individuals will perform reproductive differentiation within colonies. We observed that when we separately reared elusive and aggressive workers, elusive workers differentiate into reproductives significantly earlier than aggressive workers. When we reared them together in the proportions 12:3, 10:5, and 8:7 (aggressive workers: elusive workers), the first reproductives mostly differentiated from the elusive workers, and the reproductives differentiated from the elusive workers significantly earlier than from aggressive workers. Furthermore, we found that the number of workers participating in reproductive differentiation was significantly lower in the groups of both types of workers than in groups containing only elusive workers. Our results demonstrate that the elusiveness trait was a strong predictor of workers’ differentiation into replacement reproductives in R. labralis . Moreover, our results suggest that individual personalities within the insect society could play a key role in resolving the overt reproductive conflict.",
"discussion": "Discussion Reproductive differentiation is common in eusocial insects, and especially remarkable in groups of lower termite species, in that, except for nymph-derived neotenic reproductives, the workers are able to maximize their fitness by developing into neotenic reproductives when the original reproductives are lost ( Miyata et al. 2004 ; Korb and Hartfelder 2008 ; Boomsma and Gawne 2018 ). However, whether all reproductively totipotent workers have the same chance of differentiation is unknown. Our study showed that R. labralis workers consistently exhibited 2 behaviors when encountering heterospecific individuals, either actively attacking or immediately retreating. Furthermore, workers which exhibit consistent elusiveness are more likely to differentiate into neotenics than those which exhibit consistent aggressiveness. The effect of consistent individual behavioral differences in colony efficiency has already been observed in some social species. For example, in the ant Temnothorax longispinosus in which aggressive individuals defend the nest while docile individuals take care of the brood ( Modlmeier and Foitzik 2011 ), and aggressive individuals in the social spider Anelosimus studiosus are faster to attack and subdue preys and consequently improve the efficiency of the foraging activity in contrast to the docile individuals ( Pruitt and Riechert 2011 ). Previous reviews about the evolutionary significance of consistent individual differences in behavior suggest that it is beneficial to the efficiency of the group ( Dall et al. 2004 , 2012 ). Our findings demonstrate that the consistent individual behavioral differences in R. labralis workers affect reproductive differentiation and thus the future fitness of the colony. When we separately reared the 2 behavioral types of workers, the elusive workers differentiated significantly earlier into neotenics compared to the aggressive workers, and the number of elusive workers which differentiated during the whole experiment was significantly higher than the one of aggressive workers. When we reared them together in different proportions (except the proportion 14:1 for aggressive workers: elusive workers), the first neotenics were mostly differentiated from the elusive workers than from the aggressive workers, and the time needed for the elusive workers to differentiate into neotenics was significantly shorter than that of the aggressive workers. The defense of the termite colony is not restricted to the action of the soldiers alone; workers actively attack unfamiliar individuals and not only in soldierless species ( Thorne 1982 ; Šobotník, Jirošová et al. 2010 ; Šobotník, Sillam-Dussès et al. 2010 ). The evolutionary implications of workers’ elusive behavior may benefit the colony. From our observations, the elusive behavior performed by workers is similar to the docility or the shyness detected in other animals ( Dall 2004 ; Réale et al. 2007 ), but could also be considered as an act of self-preserving life in a dangerous environment. When the colony is under attack, the aggressive workers defend their colony, and may be injured or killed. Although the elusive workers are not directly involved in defensive fights, they greatly increase their own survivability by retreating and thus serve as candidates to quickly inherit the reproductive task in the colony in case of the death of the reproductives. Therefore, a colony containing both of these workers might be able to handle emergency situations to ensure the colony survives. Our study also showed that colonies of R. labralis containing a mixture of workers of elusiveness and aggressiveness types may weaken the overt reproduction conflict during the process of colony inheritance. Reproduction conflicts are widespread in social insects, including termites ( Korb 2007 ; Korb and Hartfelder 2008 ). Previous studies have focused more on revealing how individuals successfully inherit reproductive status after differentiation (e.g. Sun et al. demonstrated that both successful neotenics and workers in the termite R. flavipes attack other neotenics to regulate the reproductive division, Sun et al. 2020 ), but little has been investigated on the mechanisms which may exist to limit the number of individuals participating in the differentiation. Our results show that the number of R. labralis workers involved in reproductive differentiation in groups containing different proportions of elusive workers and aggressive workers was significantly lower than those in groups containing elusive workers only. The few workers involved in reproductive differentiation in mixed groups suggest that groups of R. labralis that have a mixture of workers with both behaviors would have a less overt reproductive conflict during reproductive differentiation than groups that only have elusive workers. However, the number of workers which differentiated into neotenics did not differ significantly among mixed groups in comparison to groups with aggressive workers only. Even though the aggressive workers in a group may protect the colony in the dangerous environment and reduce reproduction conflict in inheritance, their presence in large numbers in a colony prolongs the time needed for differentiation into reproductives. Our results show that as the number of aggressive workers decreases in the group, the time needed for workers to differentiate significantly decreases. Therefore, our results indicate that R. labralis groups with a mixture of elusiveness and aggressiveness types could not only facilitate the rapid differentiation of reproductives but also reduce the overt reproductive conflict. Although our data on consistent individual behavioral differences in termite workers are linked to replacement reproductive differentiation, there are still some aspects that require further exploration and verification, such as whether consistent individual behavioral differences in termite workers is gender specific or not. We did not distinguish the sexes of the workers in our study to prevent to harm them and thus to affect their differentiation, but a previous study has shown that the neotenics stimulate workers of the opposite sex to differentiate into replacement reproductive in the termite R. flavipes ( Sun et al. 2017 ). Therefore, except for the appearance of the first neotenic, the sex of the subsequent neotenics that either differentiate from elusive workers or aggressive workers might be affected by the sex of the existing neotenics in R. labralis . Moreover, consistent individual behavioral differences in termite workers may be age dependent. It is already well known that the behavioral changes of workers in social insects are often associated with age (i.e. age polyethism). Young workers usually perform tasks within the nest, such as caring of the brood and the reproductives, whereas older workers perform riskier tasks, such as foraging activity or defense of nestmates outside the nest ( Seeley 1982 ; Jeanne 1986 ; Wakano et al. 1998 ). In honey bee workers, it has been demonstrated that some behaviors, particularly their tendency to physically interact with other bees, remain somewhat consistent even if they age within the colony ( Walton and Toth 2016 ). In our study, the workers we used were chosen randomly, which makes it theoretically possible that the aggressive workers we chose were older workers whose tasks were defensive, whereas the elusive workers chosen were younger and living inside the colony. However, the observations made during our experiments suggest that even the last instar workers were able to show elusive or aggressive behaviors which tend to indicate that these behaviors are not necessarily age related. In conclusion, our experiments generally support that some consistent individual behavioral differences of workers contribute to reproductive differentiation which may act to resolve the reproductive conflict of the colony and to increase the fitness benefits of the colony."
} | 2,479 |
29327410 | PMC5900883 | pmc | 7,550 | {
"abstract": "Summary Members of the phylum Acidobacteria are abundant and ubiquitous across soils. We performed a large‐scale comparative genome analysis spanning subdivisions 1, 3, 4, 6, 8 and 23 ( n = 24) with the goal to identify features to help explain their prevalence in soils and understand their ecophysiology. Our analysis revealed that bacteriophage integration events along with transposable and mobile elements influenced the structure and plasticity of these genomes. Low‐ and high‐affinity respiratory oxygen reductases were detected in multiple genomes, suggesting the capacity for growing across different oxygen gradients. Among many genomes, the capacity to use a diverse collection of carbohydrates, as well as inorganic and organic nitrogen sources (such as via extracellular peptidases), was detected – both advantageous traits in environments with fluctuating nutrient environments. We also identified multiple soil acidobacteria with the potential to scavenge atmospheric concentrations of H 2 , now encompassing mesophilic soil strains within the subdivision 1 and 3, in addition to a previously identified thermophilic strain in subdivision 4. This large‐scale acidobacteria genome analysis reveal traits that provide genomic, physiological and metabolic versatility, presumably allowing flexibility and versatility in the challenging and fluctuating soil environment.",
"conclusion": "Conclusions and future outlook Members of the phylum Acidobacteria are ubiquitous across terrestrial ecosystems worldwide, yet their ecological role(s) in these environments remains elusive. In this study, we sought to use comparative genomics to provide genomic insights into their ecophysiology. The vast majority of the analysed genomes originated from strains isolated from terrestrial environments, along with a few stemming from environments such as freshwater hot springs, freshwater mud, alkaline microbial mats, aquifer, acid mine drainage and geothermally heated microbial mat. Interestingly, these non‐terrestrial strains typically harboured a reduced genome size and proportion of paralogous genes, suggesting that these environments could be more stable and, therefore, metabolic versatility might not be necessary. In support of this conjecture, we found that the native isolation environment of the investigated strains along with the subdivision classification was a factor in shaping the distribution of genes across genomes. Genomes of acidobacterial strains isolated from soils were larger and typically harboured a more versatile repertoire of genes necessary for a changing environment, namely the genomic potential to use O 2 at different concentrations, a diverse collection of carbohydrates, both inorganic (ammonia and/or nitrate/nitrite) and organic N (amino acids and other high molecular weight compounds) as their N sources and H 2 at atmospheric concentrations. Mobile genetic elements, including temperate bacteriophages seem to have played a particular role in shaping the genomes of terrestrial acidobacterial genomes, yet it is unclear at this time if these events were vectors of horizontal gene transfer that introduced metabolism‐relevant genes. Recent metagenomic investigations of environmental samples expanded our notion of the microbial tree of life, redefining the taxonomic definitions of phyla and give insights into potential physiologies. Although this study was limited to 24 genomes, the discussed findings are based on strains to which downstream growth‐based investigations can be performed to test working hypotheses. We believe that the appreciation of the discussed features in the potential physiological repertoire of soil acidobacteria will facilitate our understanding of this fascinating phylum and continue to bridge the knowledge gap between their ubiquity and their function in soil environments. Experimental procedures Genome sequencing and assembly Strains were grown on either a modified minimal medium or R2 medium as described previously (Eichorst, 2007 ; Eichorst et al ., 2011 ; Kulichevskaya et al . 2010 ). Genomic DNA was isolated using a modified CTAB DNA extraction protocol as recommended by the DOE Joint Genome Institute (JGI). The genome IDs and accession numbers can be found in Supporting Information Table S1. Sixteen genomes were publically available, while eight were newly sequenced in this study (Supporting Information Table S2). Generation of these genomes was done using either Pacific Biosciences (PacBio) ( Acidobacteriaceae bacterium KBS 146 and Bryobacter aggregatus MPL3 ) , Illumina technology (Bennett, 2004 ) ( Acidobacteriaceae bacteria KBS 89 and KBS 83, Acidobacteria bacterium KBS 96 and Terriglobus sp. TAA 43), a combination of Illumina (Bennett, 2004 ) and 454 technologies (Margulies et al ., 2005 ) ( Terriglobus roseus KBS 63) or a combination of PacBio and Illumina ( Acidobacteriaceae bacterium TAA 166). All general aspects of library construction and sequencing performed at the JGI can be found at http://www.jgi.doe.gov . Briefly, data were assembled with HGAP (version: 2.0.0) (Chin et al ., 2013 ) or AllpathsLG (Gnerre et al ., 2011 ) when either the PacBio or combination of PacBio and Illumina technologies were utilized respectively. All raw Illumina sequence data were passed through a filtering program (DUK), which removes known Illumina sequencing and library preparation artifacts (Mingkun L, Copeland A, Han J – in house script). The following steps were then performed for assembly of Illumina‐based libraries: (i) filtered Illumina reads were assembled using Velvet (version 1.1.04) (Zerbino and Birney, 2008 ), (ii) 1–3 kb simulated paired end reads were created from Velvet contigs using wgsim ( https://github.com/ih3/wgsim ), (iii) Illumina reads were assembled with simulated read pairs using Allpaths–LG (version r41043) (Gnerre et al ., 2011 ). The 454 Titanium standard data and the 454 paired end data were assembled together with Newbler, version 2.3‐PreRelease‐6/30/2009. The Newbler consensus sequences were computationally shredded into 2 kb overlapping fake reads (shreds). Illumina sequencing data were assembled with VELVET, version 1.0.13 (Zerbino and Birney, 2008 ), and the consensus sequence were computationally shredded into 1.5 kb overlapping shreds. The 454 Newbler consensus shreds were integrated, the Illumina VELVET consensus shreds and the read pairs in the 454 paired end library using parallel phrap, version SPS – 4.24 (High Performance Software, LLC). The software Consed (Ewing et al ., 1998 ; Ewing and Green, 1998 ; Gordon et al ., 1998 ) was used in the following finishing process. Illumina data were used to correct potential base errors and increase consensus quality using the software Polisher developed at JGI (A. Lapidus, unpublished). Possible mis‐assemblies were corrected using gapResolution (C. Han, unpublished), Dupfinisher (Han and Chain, 2006 ), or sequencing cloned bridging PCR fragments with subcloning. Gaps between contigs were closed by editing in Consed, by PCR and by Bubble PCR (J‐F Cheng, unpublished) primer walks. A total of 40 additional reactions were necessary to close gaps and raise the quality of the finished sequence. Genome annotation Genes were identified using Prodigal (Hyatt et al ., 2010 ), followed by a round of manual curation using GenePRIMP (Pati et al ., 2010 ) for finished genomes and draft genomes in fewer than 20 scaffolds. The predicted CDSs were translated and used to search the National Center for Biotechnology Information (NCBI) nonredundant database, UniProt, TIGRFam, Pfam, KEGG, COG and InterPro databases. The tRNAScanSE tool (Lowe and Eddy, 1997 ) was used to find tRNA genes, whereas ribosomal RNA genes were found by searches against models of the ribosomal RNA genes built from SILVA (Pruesse et al ., 2007 ). Other non–coding RNAs such as the RNA components of the protein secretion complex and the RNase P were identified by searching the genome for the corresponding Rfam profiles using INFERNAL ( http://infernal.janelia.org ). Additional gene prediction analysis and manual functional annotation was performed within the Integrated Microbial Genomes (IMG) platform developed by the Joint Genome Institute, Walnut Creek, CA, USA ( http://img.jgi.doe.gov ) (Markowitz et al ., 2009 ). General genome analysis and pan genome analysis CheckM was used to estimate completeness and contamination of the genomes based on lineage‐specific markers (Parks et al ., 2015 ). The phylogenomic tree was constructed using a concatenated data set of 43 universally conserved marker genes of ribosomal proteins and RNA polymerase domains and calculated by Bayesian inference running in PhyloBayes (Lartillot et al ., 2009 ), the tree topology converged within 11 000 generations. The list of the universally conserved marker genes used in this study can be found in Parks et al ., 2015 . A comprehensive set of outgroups was included. General genome statistics (such as genome size and percent of paralogous genes) was determined using the JGI IMG database (Markowitz et al ., 2009 ). Average nucleotide identity (ANI) was calculated using MiSI (Varghese et al ., 2015 ). Average amino acid identity (AAI) (Konstantinidis and Tiedje, 2005b ) was calculated directionally between each genome pair using amino acid sequences predicted by Prodigal (Hyatt et al ., 2010 ). Target amino acid sequences were required to align over 70% of the query sequence with at least 30% identity. For each directional calculation, the percent identity was normalized by query gene length and the reported AAI is the average between each directional AAI calculation. The neighbour‐joining algorithm in ARB was used for the generation of the acidobacteria phylogenetic tree (Fig. 1 ) of the 16S rRNA gene using sequences (ca. 1400 bp) obtained from cultivated representatives from the SILVA_Living Tree (v106), publically available genomes and from genomes of this study. Sequences were aligned by the SINA online tool (Pruesse et al ., 2012 ). The Neighbour‐Joining, Jukes‐Cantor substitution model in the Geneious software v10.0.8 (Auckland, New Zealand) was used for bootstrapping analysis. Displayed bootstrap values are based on 1000 bootstrap iterations. Tree is displayed using the Interactive Tree of Life (Letunic and Bork, 2016 ). For evolutionary and functional analysis, COG/NOGs were predicted with NCBI COGSoft (Kristensen et al ., 2010 ), based on the eggNOG database (4.0 release) (Powell et al ., 2014 ). Local COG/NOG assignments in proteins were encoded in a custom database according to the COGSoft requirements. The acidobacterial pan genome analysis was based on the distribution of the predicted COG/NOGs: core genomes was defined as being present across all investigated genomes; variable genomes need to be present in 2 or more genomes and unique genomes were COG/NOGs unique to the respective genome. Permutational multivariate analysis of variance (PERMANOVA) was performed using the adonis function and PcoA using the vegdist function, both found in the vegan package in R ( https://www.R-project.org ). To ascertain if there were any functional differences in the genomic potential of the acidobacteria across environments and subdivision (1 vs. 3), the distribution of the COG functional categories were compared using a chi‐square test for goodness of fit with a Bonferroni's error rate adjustment (Samuels, 1989 ) and the average within each category was compared using analysis of variance in the R package (aov function) ( https://www.R-project.org ). Aerobic and anaerobic respiration, fermentation, nitrogen metabolism, carbon metabolism THE IMG website was used for comparative genome analyses and comparing function profiles across the genomes. The Pfam, COG, KOG, TIGRFam, KEGG and InterPro databases were used to identify marker genes and key enzymes of interest. Additionally, the gene neighbourhoods of detected genes were inspected manually. Locus tags for the genes identified across the acidobacterial genomes encoding for cytochrome terminal oxidases can be found in Supporting Information Table S5, anaerobic respiration and fermentation (Supporting Information Tables S6 and S7 respectively), heterotrophic carbon dioxide fixation (Supporting Information Table S8) and those for the identified marker genes involved in nitrogen metabolism in Supporting Information Table S6. The CDSs involved in carbohydrate metabolism were identified using the database for automated Carbohydrate‐active enzyme annotation (dbCAN) (Yin et al ., 2012 ). Detection of group 1h/5 hydrogenases The detection of the group 1h/5 large and small catalytic subunit genes was initially detected by keyword searches and ProteinBLAST in the JGI IMG database (Markowitz et al ., 2009 ) and confirmed with the HydDB (Søndergaard et al ., 2016 ). Further phylogenetic analysis of the large and small catalytic subunits along with annotation of the conserved L1 and L2 signatures (Constant et al ., 2011 ) were done in ARB (Ludwig et al ., 2004 ). The gene synteny of the structural and maturation genes was visualized with the GenoPlotR package in R (Guy et al ., 2010 ). Locus tag for the genes identified across the acidobacterial genomes encoding for group 1h/5 [NiFe]‐hydrogenases can be found in Supporting Information Table S9. Detection of prophages The genomes were screened for the presence of prophages using VirSorter (Roux et al ., 2015a ) and PHASTER (Arndt et al ., 2016 ). Prophage predictions were manually curated to remove false‐positives and verify prophage ends, leading to a total of 35 prophages identified. Predicted proteins from these prophages (extracted from VirSorter output) were affiliated against RefSeq Virus v70 (O'Leary et al ., 2016 ) using blastp (Altschul et al ., 1997 ), and against PFAM v27 (Finn et al ., 2014 ) using HMMER 3 (Finn et al ., 2011 ). Prophages were classified as active when they included at least 1 gene Involved in virion formation (i.e., coding for a capsid, terminase, or portal protein). The hypothesis is that only prophages lacking these genes would be likely defective, i.e., not able to switch to a lytic cycle, and thus would stay inserted into the host genome until they progressively decay. It has to be noted, however, that such prophages lacking a virion machinery are not necessarily defective, but could also represent satellite phages, while some prophages encoding capsid‐related genes have been shown to lack the ability to self‐replicate (Casjens, 2003 ). Hence, we chose to designate prophages only as ‘predicted’ active or inactive. A genome‐based classification of these prophages, based on protein clustering and network clustering as done previously (Lima‐Mendez et al ., 2008 ; Roux et al ., 2015a , 2015b ), was performed using vContact ( https://bitbucket.org/MAVERICLab/vcontact , sig score ≥ 2, default parameters otherwise). Briefly, viral genomes (complete or partial, from free‐living viruses or integrated prophages) are clustered into approximately genus‐level groups based on a shared genes network. The database used here included complete bacteria and archaea virus genomes from RefSeq v70, the VirSorter Curated Dataset (Roux et al ., 2015a , 2015b ), and the Earth's Virome Dataset (Paez‐Espino et al ., 2016 ). Easyfig (Sullivan et al ., 2011 ) was used to generate genome comparison plots with members of two clusters including five Acidobacteria prophages each (clusters 140 and 153, Fig. 3 ). Pairwise Amino‐acid identity levels between (pro)phages were calculated using the aai tool from the enveomics package (Rodriguez‐R and Konstantinidis, 2016 ).",
"introduction": "Introduction The phylum Acidobacteria constitute an abundant and ubiquitous bacterial phylum typically found in soils and sediments. The widespread nature across members of this phylum in soils is clear; they have been detected in agricultural soils (Navarrete et al ., 2013 ), forest soils (Štursová et al ., 2012 ), peat soils (Pankratov, 2012 ), arctic tundra soils (Männistö et al ., 2012a ), desert soils (Kuske et al ., 1997 ; Dunbar et al ., 2002 ) and across many edaphically (defined here as of or relating to soil) diverse temperate soils (Jones et al ., 2009 ). Not only are they ubiquitous, they also have a high relative abundance based on rRNA gene libraries (as high as 40% (range ca. 20%–40%) (Lipson and S. K. Schmidt, 2004 ; Janssen, 2006 ) and have a breadth of phylogenetic diversity similar to that of the Proteobacteria (Hugenholtz et al ., 1998 ) spanning 26 subdivisions known to date (Barns et al ., 2007 ). Based on previous genomic and physiological investigations, many subdivision 1 and 3 strains have been described as versatile heterotrophs that grow optimally at low pH, produce copious amounts of extracellular material, harbour a low rRNA operon copy number suggesting an oligotrophic (more K‐selected) lifestyle, and contain both low‐specificity major facilitator superfamily and high‐affinity ABC‐type transporters (Ward et al ., 2009 ; Rawat et al ., 2012 ; Kielak et al ., 2016 ). Some more striking physiologies such as iron reduction and/or fermentative growth (Liesack et al ., 1994 ; Coates et al ., 1999 ), phototrophy (Garcia Costas et al ., 2012 ), along with the ability to grow under thermophilic conditions have been described in select strains from subdivision 4, 8, 10 and 23 (Izumi et al ., 2012 ; Losey et al ., 2013 ; Crowe et al ., 2014 ; Stamps et al ., 2014 ; Tank and Bryant, 2015a ). Yet the vast majority of acidobacteria detected in soils based on culture dependent and independent approaches are members of subdivisions 1, 2, 3, 4, 5 and 6 (Janssen, 2006 ; Jones et al ., 2009 ). Many strains in culture collections stem from these aforementioned ubiquitous subdivisions and were originally isolated from soil environments such as tundra soils (Männistö et al ., 2012a ), peatland soil (Pankratov et al ., 2012 ; Dedysh et al ., 2012 ), agricultural soil or meadow grassland soil (Eichorst et al ., 2007 ; Eichorst and Kuske, 2012 ; Foesel et al ., 2013 ), forest soils (Koch et al ., 2008 ; Lladó et al ., 2016 ) and subtropical soil (Huber et al ., 2016 ). Therefore, it is particularly pertinent to better understand these environmentally relevant soil strains. To that end, we sought to elucidate the potential ecophysiology of the soil acidobacteria by undertaking a large‐scale comparative acidobacterial genomic investigation comprising 24 genomes. Previous comparative genomic investigations on acidobacteria coupled with physiological‐based investigations have been limited to either three or six strains and have generated tremendous insights into their physiology (Ward et al ., 2009 ; Rawat et al ., 2012 ). The expansion of published genomes in the databases along with novel genomes from this study demanded an updated investigation, with a focus on the features in the genomes that could help explain their ubiquity and abundance in soil. More specifically, we investigated (i) if there are (any) systematic differences in gene content among these ‘subdivision’ classifications and/or environments from which the strains were isolated, (ii) events that shaped the genome structure of the strains, (iii) the genes that comprise the acidobacterial pan genome and (iv) what potential physiological features could allow for their ubiquity and prevalence across many soil environments.",
"discussion": "Results and discussion Phylogeny of investigated acidobacterial strains The genomes investigated in this study along with the references and abbreviations used can be found in Supporting Information Table S1. The general genome features of the new strains from this study are summarized in Supporting Information Table S2 and described in more detail in (Trojan et al ., in preparation). Briefly, the genome sizes of the new strains ranged from 4.9 to 6.7 Mb with a genome GC content of 57%–60%. The number of estimated protein coding sequences (CDS) with predicted function ranged from 68% to 76%. Based on the 16S rRNA gene, the investigated genomes spanned subdivisions 1, 3, 4, 6, 8 and 23 (Fig. 1 ). There were at least two species in the genera Terriglobus and Acidobacterium , while the other genera were represented by one species. Nearly all genomes were at least 95% complete, with < 5% contamination based on CheckM analysis (Supporting Information Table S3) making them suitable for phylogenomic and comparative analyses (Parks et al ., 2015 ). Terriglobus roseus KBS 63 was the one exception, with 100% completeness and 13.79% contamination; however, all marker genes (except one that was seen in multiple copies) were 100% identical at the amino acid level and the number of genes detected in the genome was not disproportionately high. This indicates a low level of population diversity rather than the presence of a contaminating organism and is not expected to affect phylogenomic and/or comparative analyses. The phylogenomic tree, based on 43 concatenated universally conserved marker genes, depicted a similar subdivision topology to the 16S rRNA gene tree, namely with clear distinctions across subdivisions 1, 3, 4, 6, 8 and 23 (Fig. 2 , Fig. S1). Based on the phylogenomic tree, the phylum Acidobacteria branches as a sister clade to the Aminicenantes (formerly Candidate division OP8) (Supporting Information Fig. S1). Aminicenantes have been found in hydrocarbon‐impacted environments, marine habitats, aquatic, groundwater samples and terrestrial springs, typically having a higher relative abundance in environments characterized by low O 2 concentrations, high temperatures and moderate to high salinity (Farag et al ., 2014 ). Figure 1 Neighbour‐joining tree of the acidobacterial 16S rRNA gene sequences retrieved from cultivated strains across subdivisions 1, 3, 4, 6, 8, 10 and 23. Strains investigated in this study are depicted in bold . Tree is displayed using the Interactive Tree of Life (Letunic and Bork, 2016 ). Number to the right of the shaded sections of the tree corresponds to the respective acidobacterial subdivision of the phylum. Verrucomicrobium spinosum (X90515) was used as an outgroup. The tree was bootstrapped 1000 times based on Jukes‐Cantor, and nodes with consensus support > 90% ( ) and > 70% (○) are displayed. The scale bar indicates 0.01 changes per nucleotide. Figure 2 Bayesian inference phylogenomic tree based on a concatenated dataset of 43 universally conserved marker genes. Subdivisions are indicated to the right of the tree. The GenBank assembly accession number are depicted to the right of the strain. All nodes have ≥ 80% consensus support; more specifically nodes with > 99% ( ) and > 94% (○) are displayed. The scale bar indicates 0.4 changes per nucleotide. Subdivision 1 has the best representation in the phylogenomic tree with 15 genomes (Fig. 2 ). Within this subdivision, there is one main grouping consisting of three lineages: (i) Silvibacterium and Acidobacterium ; (ii) Terracidiphilus and (iii) Terriglobus , Granulicella and Edaphobacter . There appears to be a major split with ‘ Candidatus Koribacter versatilis’ Ellin345, as it is distinct from these lineages. The branching order of the phylogenomic tree relative to the 16S rRNA gene tree is fairly consistent with the exception of Terracidiphilus , which based on the 16S rRNA gene clusters with Silvibacterium and Acidobacterium (Supporting Information Fig. S1). Genomes stemming from the genus Terriglobus exhibited a monophyletic grouping consisting of Terriglobus saanensis SP1PR4, T. roseus KBS 63 and Terriglobus sp. TAA 43, and were most similar to a grouping consisting of Granulicella and Edaphobacter genomes. Interestingly, the two species in the Granulicella genus did not have a monophyletic nature based on the phylogenomic analysis, but formed a larger grouping with Acidobacteriaceae bacteria KBS 89, TAA 166 and KBS 146 along with Edaphobacter aggregans DSM19364. A similar pattern was observed in the 16S rRNA gene tree (Supporting Information Fig. S1). The other noted monophyletic genus cluster in subdivision 1 was the Acidobacterium genus, which encompassed Acidobacterium capsulatum ATCC51196 and Acidobacterium ailaaui PMMR2 (Fig. 2 ). This phylogenomic analysis provided additional insight into the phylogeny across members in the phylum Acidobacteria . It also suggests that genome information of additional strains will allow a better differentiation of the lineages and thus resolve the topology of the tree especially within subdivision 1. Average nucleotide and amino acid identity The average nucleotide identity (ANI) and average amino acid identity (AAI) were compared across all investigated genomes (Supporting Information Fig. S2). The highest pairwise ANI values observed were between 70% and 78%, suggesting that all investigated genomes represented unique species (based on the proposed species definition encompassing shared gene content, which corresponds to the traditional 70% DNA‐DNA association standard (Konstantinidis and Tiedje, 2005a ; Rodriguez‐R and Konstantinidis, 2014 )). Genome clustering based on AAI was consistent with the subdivision‐level classification of the strains, and even within subdivisions it was largely consistent with known genera such as the Terriglobus cluster. The highest AAI ranged between 60% and 67% in subdivision 1 genomes, generating 3 clusters of high similarity: Silvibacterium bohemicum S15 and A. ailaaui PMMR2 with an AAI of 62%; T. roseus KBS 63 and T. sp. TAA 43 with an AAI of 67%; and E. aggregans DSM19364 having an AAI of 63% with Acidobacteriaceae bacterium KBS 89, 64% with Acidobacteriaceae bacterium TAA 166, and 68% with Acidobacteriaceae bacterium KBS 146. The clustering of these aforementioned genomes based on AAI could suggest that these are species of the same genus (Konstantinidis and Tiedje, 2005b ). Genome structure and plasticity Many factors can influence the composition, structure and plasticity of a genome, such as duplication events and genome rearrangements triggered by phages and other transposable and mobile elements. These events not only help to shape the genomes, but can also lead to the acquisition of new genetic potential (such as auxiliary metabolic genes) (Soucy et al ., 2015 ). Genomes of acidobacterial strains isolated from soils typically harboured a larger genome size and proportion of paralogous genes, as compared to strains from 'other' environments such as hot springs and microbial mats (Supporting Information Fig. S3). Paralogous genes can stem from gene duplication events giving rise to potential genes with new function, as previously suggested for acidobacteria (Challacombe et al ., 2011 ). Alternatively, this redundancy could be due to ecoparalogues (Sanchez‐Perez et al ., 2008 ) – genes that have similar functions but are being expressed under different environmental conditions. Both features could be advantageous during resource fluctuations in soils and thus explain the larger proportion of paralogous genes compared to the genomes from ‘other’ environments such as hot springs, microbial mats and geothermal soils. A total of 35 putative prophages were identified across 19 genomes (Table 1 ). The majority of genomes, in which prophages were detected, were from strains stemming from soils. This is in line with the notion that soils can have ca. 10 8 virus particles per gram soil (Reavy et al ., 2014 ) and harbour an extensive diversity and abundance of bacteriophage populations (Williamson et al ., 2005 ). Prophages were not detected in Acidobacteriaceae bacterium KBS 146 (subdivision 1) and strains from ‘other’ environments (such as geothermal soils, hot springs, microbial mats), namely Thermoanaerobaculum aquaticum MP‐01 (subdivision 23), Pyrinomonas methylaliphatogenes K22 (subdivision 4), Chloracidobacterium thermophilum B (subdivision 4) and A. ailaaui PMMR2 (subdivision 1). Table 1 Detected prophages and mobile genetic elements‐associated genes across the acidobacterial genomes. Activity # of phage marker genes Transposases & Integrases # of detected prophages Active \n a \n \n Inactive/ decayed \n b \n \n Phage‐Capsid Terminase LSU Portal Phage Transposase & Integrase Transposons‐ Transposase Retro‐transposon R_integrase Immunity Superinfection \n Subdivision 1 \n \n Terriglobus roseus KBS 63 1 1 ND ND 1 1 8 1 ND 1 \n Terriglobus sp. TAA 43 3 2 1 ND 1 1 8 1 ND ND \n Acidobacteriaceae bacterium KBS 89 3 3 ND 2 ND 2 19 1 ND ND \n Acidobacteriaceae bacterium KBS 146 ND ND ND ND ND 1 9 1 1 ND \n Acidobacteriaceae bacterium TAA 166 2 2 ND 2 1 2 24 3 5 1 \n Acidobacteriaceae bacterium KBS 83 2 1 1 1 ND 1 12 4 ND 1 \n Acidobacterium capsulatum ATCC51196 1 1 ND ND 1 1 6 4 17 ND \n Acidobacterium ailaaui PMMR2 ND ND ND ND ND 1 6 1 ND 1 \n Granulicella tundricola MP5ACTX9 1 1 ND 1 1 1 19 36 4 ND \n Granulicella mallensis MP5ACTX8 2 2 ND 1 2 1 8 2 11 1 \n ‘Candidatus Koribacter versatilis’ Ellin345 3 3 ND ND 2 2 6 ND 1 ND \n Edaphobacter aggregans DSM19364 4 2 2 2 ND ND 57 64 3 ND \n Silvibacterium bohemicum S15 1 1 ND 1 1 1 14 6 2 ND \n Terracidiphilus gabretensis S55 1 1 ND ND ND 1 8 3 1 1 \n Terriglobus saanensis SP1PR4 2 2 ND ND 1 1 10 1 6 2 \n Subdivision 3 \n \n Acidobacteria bacterium KBS 96 4 4 ND 4 3 2 14 2 5 ND \n Bryobacter aggregatus MPL3 1 1 ND ND 1 ND 13 16 10 ND \n ‘Candidatus Solibacter usitatus’ Ellin6076 1 1 ND ND 2 ND 31 14 32 ND \n Subdivision 4 \n \n Chloracidobacterium thermophilum B ND ND ND ND ND ND 4 2 ND ND \n Pyrinomonas methylaliphatogenes K22 ND ND ND ND ND ND 2 ND ND ND \n Subdivision 6 \n \n Luteitalea pratensis DSM100886 1 1 ND 4 ND ND 9 11 13 ND \n Subdivision 8 \n \n Geothrix fermentans DSM14018 1 ND 1 ND ND ND 5 3 1 ND \n Holophaga foetida TMBS4 1 ND 1 ND ND ND 14 28 5 ND \n Subdivision 23 \n \n Thermoanaerobaculum aquaticum MP‐01 ND ND ND ND ND ND 2 ND ND ND ‘ND’ – not detected. a. Indicate genomes where active prophages, defined as harbouring 1 or more virion‐associated genes, were detected. Multiple prophages were detected in the genomes of Terriglobus sp. TAA 43, Acidobacteriaceae bacteria KBS 89, TAA 166, KBS 83, G. mallensis MP5ACTX8, ‘ Ca. K. versatilis Ellin345’, E. aggregans DSM19364, T. saanensis SP1PR4, and Acidobacteria bacterium KBS 96. b. Indicate genomes lacking virion‐associated genes, and likely representing decayed prophages from past infections. Although in silico determination of the state of a temperate infection is challenging, as gene content alone cannot accurately reflect the activity of an integrated prophage, 29 out of these 35 putative prophages had a clear predicted prophage and harboured at least one virion‐associated gene (i.e., coding for the capsid, terminase, or portal, Table 1 under ‘Active’ and ‘# of phage marker genes’). This suggests that most of these predicted prophages may still have the genetic potential to complete a lytic cycle and, therefore, were considered as likely active. The remaining 6 putative prophages, identified across 5 genomes, did not display any virion‐associated gene, and were thus considered as likely representing degraded prophages (Table 1 , under ‘Inactive/decayed’). These degraded prophages could be retained from past phage infections, which was previously observed and hypothesized to be one of the mechanisms by which ‘ Candidatus Solibacter usitatus’ Ellin6076 acquired its large 9.9 Mb genome (Challacombe et al ., 2011 ). Many of the detected predicted prophages did not have a strong similarity to known phages and were instead identified due to a high concentration of unknown genes and a genome organization consistent with a phage genome. Based on the affiliation of the capsid‐related genes identified, these ‘acidobacterial prophages’ could nonetheless be tentatively affiliated to the order Caudovirales . None of the identified prophages clustered with sequenced phage isolates using a gene‐content based classification (corresponding to approx. genus‐level groupings) as described in (Lima‐Mendez et al ., 2008 ). More specifically in this clustering, 12 prophages were singletons, 8 prophages clustered exclusively with other acidobacterial prophages, and the remaining 15 were associated with other prophages identified in publicly available microbial genomes or soil metagenomes (Roux et al ., 2015b ; Paez‐Espino et al ., 2016 ). Two clusters were notable: one (Cluster 140) harbouring prophages from 5 different acidobacteria genomes (many of the genus Granulicella ) alongside prophages from an Alphaproteobacterium ( Euryhalocaulis caribicus JL2009) and a Chloroflexi ( Nitrolancea hollandica Lb) with an average amino‐acid sequence identity (AAI) of 34.8% (Fig. 3 A), and a second (Cluster 153) containing prophages from six acidobacterial genomes (many of the genus Terriglobus ) and two phage genomes identified in soil microbial metagenomes with an average sequence identity of 37.8% (Fig. 3 B). Given these amino‐acid identities, it suggests that these clusters are within the same subfamilies (Lavigne et al ., 2008 ). At this time, further work is needed to better identify and characterize these potentially new viral groups associated with the phylum Acidobacteria . Figure 3 Two prophage clusters with high representation of the acidobacteria. A. Cluster 140 harbouring 6 scaffolds with acidobacteria (from top: (1) Acidobacteria bacterium KBS 96, ARMF01000004 G004DRAFT, scaffold00001_1_C4, 0 to 50000; (2) Acidobacteria bacterium KBS 96, ARMF01000009 G004DRAFT, scaffold00001_1_C9, 1290000 to 1335000; (3) Silvibacterium bohemicum S15, LBHJ01000004 contig_4, 395000 to 435000; (4) Acidobacteriaceae bacterium KBS 89, ARME01000012, G003DRAFT, scaffold00007_7_C, 50000 to 75000; (5) Granulicella tundricola MP5ACTX9 NC015064, 2275000 to 2325000; and (6) Granulicella mallensis MP5ACTX8, NC016631, 2110000 to 2160000). Additional contigs include Euryhalocaulis caribicus JL2009, contig00028; Nitrolanceae hollandica Lb, CAGS 00000000, contig 00252 to 1568; and a soil metagenome, contig 300000364, a_INPhiseqgaiiFebDRAFT_100851888. B. Cluster 153 with 6 scaffolds of acidobacteria (from top: (1) Terriglobus saanensis SP1PR4, NC014963, 3780000 to 3820000; (2) Terriglobus sp. TAA 43, JUGR01000001_M504DRAFT_scaffold00001_1_C, 80000 to 140000; (3) Terriglobus roseus KBS 63, NC018014, 150000 to 180000; (4) Acidobacteriaceae bacterium KBS 89, ARME01000010_G003DRAFT_scaffold00005_5_C, 60000 to 90000; (5) Terracidiphilus gabretensis S55, LAIJ01000009_contig10, 700000 to 740000; and (6) ‘ Candidatus Koribacter versatilis’ Ellin345, NC008009, 5150000 to 5190000. Additional contigs include soil metagenome contig 3300001397_a_JGI20177J14857, 1000003 and 3300003218_a_JGI26339J46600, 10000010. The tBLASTx identity scores are given from 21% to 100%. The scale bar for each cluster is depicted in the respective label. There is evidence that select acidobacterial genomes could have been subject to multiple simultaneous viral infections. Eight genomes have traces of multiple prophages (i.e., multiple capsid, portal or terminase genes, Table 1 , under ‘# of phage marker genes’), and 3 genomes ( Granulicella mallensis MP5ACTX8, ‘ Ca . K. versatilis’ Ellin345, and Acidobacteria bacterium KBS 96) contain 2 distinct and likely active prophages (in each case, both prophages include ≥ 40 genes and 1 or more virion‐associated genes). This level of polylysogeny is more typically associated with microbial pathogens, although recent work also suggested that lysogens may be favoured under conditions of highly variable bacterial densities (Touchon et al ., 2016 ). This would be consistent with the soil environment, often limited in the availability of nutrients leading to sporadic growth and thus patchy distribution of soil organisms, which could promote polylysogeny in soil Acidobacteria . It is also noteworthy that 7 genomes ( T. roseus KBS 63, Acidobacteriaceae bacteria KBS 83 and TAA 166, G. mallensis MP5ACTX8, A. ailaaui PMMR2, T. saanensis SP1PR4, Terracidiphilus gabretensis S55) include immunity to superinfection‐like genes (PFAM domain, Imm_superinfect) (Table 1 ). These genes are not necessarily in intact prophages suggesting that the bacteria might have acquired these genes from a decayed prophage and retained it to confer some level of immunity. Beyond the observation of multiple viral infections, the conservation of these prophage‐originating superinfection‐preventing genes is an additional indicator of the likely intense viral pressure experienced by soil Acidobacteria . Further features that can shape bacterial genomes are transposable elements, which were also found in the investigated acidobacterial genomes based on the detection of transposase genes and putative retro‐transposons (Table 1 , under ‘Transposases & Integrases'). These mobile genetic elements are more abundant than prophages in the acidobacterial genomes and in some cases, transposons and prophages are co‐localized in the same genome region, raising the possibility for gene transfer and/or recombination events between mobile genetic elements. Previous investigations notably detected various insertion sequence (IS) families across acidobacterial genomes (Challacombe and Kuske, 2012 ). Insertion sequences are short DNA sequences (< 2500 bp) that encode their own mobility proteins and can span multiple families and sub‐families (Mahillon and Chandler, 1998 ). Here, a general assessment of IS elements revealed that a broad range of IS elements were detected in select acidobacterial genomes (Supporting Information Table S4) highlighting that, in addition to prophages, these mobile genetic elements likely contribute substantially to soil Acidobacteria genome evolution. Mobile elements and/or prophages can act as horizontal gene transfer agents and shuttle metabolically‐relevant genes across strains and species, which will impact the long‐term evolution and ecological success of their host (Frost et al . 2005 ). They can also encode in their own genome ‘auxiliary metabolic genes’ (i.e., genes expressed by the plasmid/phage), which in turn could help bacteria cope with adverse environmental conditions. The latter was documented previously in Escherichia coli (Wang et al ., 2010 ) and bacteria in the deep ocean (Anantharaman et al ., 2014 ; Roux et al ., 2016 ), but remains mostly uncharacterized in soil systems. As such, this is a key and very interesting finding of this study and the first time prophage integration events were found to play a major role in the acidobacteria along with the detection and presences of putative active prophages and transposable elements in members of the Acidobacteria across many subdivisions. Downstream investigations should focus on whether these new mobile elements and/or prophage events act as a source of novel metabolic genes in the acidobacteria, possibly helping them to cope in adverse conditions. Genomic metabolic potential based on COG/NOGs The phylum Acidobacteria is subdivided into 26 subdivisions, yet it is unclear if these phylogenetic groupings correspond to different physiological capabilities among the strains. Of these 26 subdivisions, members of subdivision 1, 2, 3, 4, 5 and 6 are typically the most prevalent subdivisions in terrestrial environments (Janssen, 2006 ; Jones et al ., 2009 ), suggesting that these members harbour a wide physiological range or core set of genes, which allow them to exploit various niches in soils. We expanded on previous comparative genome analysis on acidobacteria (Ward et al ., 2009 ; Rawat et al ., 2012 ) and revisited their genomic metabolic potential across 24 genomes. Our large‐scale acidobacterial pan‐genomic analysis revealed that the core genome of acidobacteria consisted of 466 COG/NOGs (Fig. 4 A), which were distributed across multiple categories, with particular dominance in cellular processes and signalling [Cp], information storage and processing [Isp] and metabolism [Me] (Supporting Information Fig. S4). Approximately 9.8% of the acidobacterial core genome was classified as poorly characterized (Pc) (Supporting Information Fig. S4). The variable genomes (found in at least two genomes) comprised of 6,942 COG/NOGs (Fig. 4 A), and they were also distributed across multiple categories. Across the 24 genomes, the number of unique COG/NOGs ranged from 111 ( A. ailaaui PMMR2) to 740 (‘ Ca . S. usitatus’ Ellin6076) (Fig. 4 A). Figure 4 Analysis of the acidobacterial pan genome. A. The acidobacterial pan genome across strains in subdivisions 1, 3, 4, 8 and 23. The number of COGs/NOGs making up the core (dark green), variable (light green) and unique (yellow) genomes across the strains are depicted. Strains are displayed based on their phylogenetic clustering. B. The PCoA plot based on the COG/NOGs of the acidobacterial genomes calculated with the Bray–Curtis distance. Subdivisions are depicted in different colours and abbreviations for the strains can be found in Supporting Information Table S1. Principle coordinate analysis of the COG/NOG categories across the 24 strains depicted clear groupings across strains in select subdivisions (Fig. 4 B). The PcoA1 axis explained most of the variability (41%) and appeared to be due to the original isolation environment. Seventeen out of the nineteen strains that clustered were isolated from soil environments (such as meadow, agricultural or tundra soils – further description can be found in Supporting Information Table S1) spanning subdivision 1, 3 and 6 (Fig. 4 B, red, blue & orange points), whereas strains from ‘other’ environments (such as hot springs, alkaline or thermophilic microbial mats, anoxic sediments and geothermal soil) clustered and belong to subdivision 4, 8 and 23 (Fig. 4 B, green points). Permutational multivariate analysis of variance (PERMANOVA) revealed significant patterns due to the differences in subdivisions ( p < 0.001) and environments ( p < 0.006) illustrating that both factors helped to shape the distribution of the shared gene pool across the genomes. The distinct clustering based on environment and subdivisions was further investigated to determine potential functional categories driving this structure. A chi‐square goodness of fit revealed that the functional categories did not have a similar distribution across genomes stemming from strains isolated of soil environment compared to ‘other’, suggesting that environment played a role in shaping the genomes. More specifically, the genomes of soil isolated strains had a significantly larger proportion of COG/NOGs in carbohydrate metabolism and transport (Me_G) ( p < 0.003) and poorly characterized (Pc_S) ( p < 0.0001), while ‘other’ genomes had a significantly larger proportion in energy metabolism (Me_C) ( p < 0.005) and translation, ribosomal structure and biogenesis (Isp_J) ( p < 0.003) (Supporting Information Fig. S5A). The differential clustering between genomes in subdivision 1 and 3 was further investigated, as these harboured the largest number of genomes available for an initial subdivision‐level comparison. Some individual COG/NOGs were unique to respective subdivisions; for example, a copper resistance gene (NlpE, COG3015) and cyctochrome C biogenesis protein (COG4233) were only found in genomes of subdivision 1, while a tRNA isopentenyl‐2‐thiomethyl‐A‐37 hydroxylase (MiaE, COG4445) was only found in the genomes of subdivision 3. Although the distributions across functional categories were different between genomes of subdivision 1 and 3 based on chi‐square goodness of fit, no significant differences in the proportion across the individual categories were noted (Supporting Information Fig. S5B). We hypothesize that the differences between genomes of subdivision 1 and 3 stem from functionally related proteins in similar COG/NOG functional categories, suggesting that members of these subdivisions do not differ in the function itself, rather the manner in which they are able to perform the function. However, additional genomes, especially in subdivision 3, are necessary to strengthen this working hypothesis. The shared gene pool was further explored in members of subdivision 1 to ascertain if there was differential clustering on the genus‐level COG/NOGs; however, there was no clear clustering of the COGs/NOGs across strains in subdivision 1 (Supporting Information Fig. S6). Relationship to oxygen The majority of the acidobacteria strains have been described as aerobes, capable of growing at 20% oxygen (O 2 ) (vol/vol) and some capable of growth under reduced O 2 (such as 1% or 2% O 2 ) (Table 2 ) (Eichorst et al ., 2011 ; Pankratov et al ., 2012 ; Tank and Bryant, 2015a , 2015b ). There is a, albeit small, collection of investigated acidobacteria that were reported to be either facultative (such as A. ailaaui PMMR2 , A. capsulatum ATCC51196) (Pankratov et al ., 2012 ; Myers and King, 2016 ) or strict anaerobes, namely in subdivision 8 (such as Geothrix fermentans DSM14018, Holophaga foetida TMBS4) (Liesack et al ., 1994 ; Coates et al ., 1999 ) and subdivision 23 (such as T. aquaticum MP‐01) (Losey et al ., 2013 ). Given the prevalence of aerobic acidobacteria, we aimed at investigating whether some strains could have the genomic potential to respire O 2 at atmospheric and sub‐atmospheric (or microoxic) concentrations. Therefore, we performed a detailed analysis on the presence and distribution of terminal oxidases with low‐ and high affinities for O 2 across the investigated genomes. Table 2 Catalytic subunits of high and low affinity terminal oxidases identified across the acidobacterial genomes and the strains’ previously reported relation to oxygen. No. of genes detected Low‐affinity terminal oxidase High‐affinity terminal oxidase Reported growth regarding oxygen HCO \n a \n Superfamily \n bd ‐type oxidase \n b \n \n Type A Type C ( cbb \n 3 ) \n Subdivision 1 \n \n ‘Candidatus Koribacter versatilis’ Ellin345 2 ND 1 Not reported \n Terriglobus saanensis SP1PR4 5 ND ND Aerobic \n d \n \n \n Terriglobus roseus KBS 63 2 1 ND \nAerobic \n e \n \n \nMicroaerobic \n e \n \n \n Terriglobus sp. TAA 43 3 ND ND \nAerobic \n e \n \n \nMicroaerobic \n e \n \n \n Granulicella mallensis MP5ACTX8 3 ND 1 Aerobic \n f \n \n \n Granulicella tundricola MP5ACTX9 3 ND ND Aerobic \n f \n \n \n Acidobacteriaceae bacterium KBS 89 3 ND ND \nAerobic \n e \n \n \nMicroaerobic \n e \n \n \n Acidobacteriaceae bacterium KBS 146 1 ND 1 Microaerobic \n g \n \n \n Acidobacteriaceae bacterium TAA 166 2 ND 1 \nAerobic \n e \n \n \nMicroaerobic \n e \n \n \n Edaphobacter aggregans DSM19364 5 2 ND Aerobic \n h \n \n \n Terracidiphilus gabretensis S55 2 ND ND Aerobic \n i \n \n \n Acidobacteriaceae bacterium KBS 83 4 ND ND \nAerobic \n e \n \n \nMicroaerobic \n j \n \n \n Acidobacterium capsulatum ATCC51196 1 1 1 \nAerobic \n k \n \n \nMicroaerobic \n l \n \n \nAnaerobic \n l \n \n \n Silvibacterium bohemicum S15 5 ND 2 Aerobic \n m \n \n \n Acidobacterium ailaaui PMMR2 3 1 ND \nAerobic \n l \n \n \nMicroaerobic \n l \n Anaerobic \n l \n \n \n Subdivision 3 \n \n ‘Candidatus Solibacter usitatus’ Ellin6076 4 1 1 Not reported \n Acidobacteria bacterium KBS 96 4 1 ND \nAerobic \n j \n \n \nMicroaerobic \n j \n \n \nAnaerobic \n j \n \n \n Bryobacter aggregatus MPL3 2 ND ND Aerobic \n n \n \n \n Subdivision 4 \n \n Chloracidobacterium thermophilum B 1 ND 1 \n c \n \n Microaerobic \n o \n \n \n Pyrinomonas methylaliphatogenes K22 1 ND 1 Aerobic \n p \n \n \n Subdivision 6 \n \n Luteitalea pratensis DSM100886 3 1 1 Aerobic \n q \n \n \n Subdivision 8 \n \n Holophaga foetida TMBS4 1 ND 1 Anaerobic \n r \n \n \n Geothrix fermentans DSM14018 1 ND 2 Anaerobic \n s \n \n \n Subdivision 23 \n \n Thermoanaerobaculum aquaticum MP‐01 1 ND 1 \n c \n \n Anaerobic \n t \n \n *Classified as aerobic when growth was reported under 20% oxygen (atmospheric conditions). Classified as microaerobic when growing at 2% O 2 (Eichorst, 2007 ; Eichorst et al ., 2007 ), 0.2% O 2 (Myers and King, 2016 ) or in the oxic‐anoxic interface of agar deep tubes (Tank and Bryant, 2015a , 2015b ). Classified as anaerobic when growth was reported under 100% N 2 (anoxic conditions). \n a. HCO, heme‐copper oxygen oxidases, \n b. \n bd ‐type oxidase = cytochrome bd quinol oxidase. ‘ND’. not detected. For locus tags of the detected genes see Supporting Information Table S5. \n c. Catalytic subunit‐like sequence with a cytochrome C domain. \n d. Männistö et al . ( 2011 ); \n e. Eichorst et al . ( 2007 ); \n f. Männistö et al . ( 2012b ); \n g. Eichorst ( 2007 ); \n h. Koch et al . ( 2008 ); \n i. García‐Fraile et al . ( 2016 ); \n j. Eichorst et al . ( 2011 ); \n k. Kishimoto et al . ( 1991 ); \n l. Myers and King, 2016 ; \n m. Lladó et al ., 2016 ; \n n. Kulichevskaya et al ., 2010 ; \n o. Tank and Bryant ( 2015a , 2015b ); \n p. Crowe et al ., 2014 ; \n q. Vieira et al ., 2017 ; \n r. Liesack et al ., 1994 ; \n s. Coates et al ., 1999 ; \n t. Losey et al ., 2013 . A total of 85 genes encoding for the catalytic subunits of terminal oxidases were detected and spanned superfamilies of both the heme‐copper oxidases (HCO) as well as the cytochrome bd quinol oxidase (not homologues to the superfamily of HCOs) across the investigated genomes (Table 2 , Supporting Information Table S5). More specifically, all investigated genomes contained at least one homologue of the low‐affinity terminal oxidase belonging to the type A of the HCO superfamily (Pereira et al ., 2001 , 2008 ) (Table 2 ). Additionally, seven strains in subdivisions 1, 3 and 6 harboured the catalytic subunit for the high‐affinity cbb \n 3 terminal oxidase (HCO type C) ( T. roseus KBS 63, E. aggregans DSM19364, A. capsulatum ATCC51196, A. ailaaui PMMR2, ‘ Ca . S. usitatus’ Ellin6076, Acidobacteria bacterium KBS 96 and Luteitalea pratensis DSM100886). The high‐affinity bd ‐type was even more prevalent and widespread across the strains, as it was detected in 13 strains in subdivisions 1, 3, 4, 6, 8 and 23 (‘ Ca . K. versatilis’ Ellin345, G. mallensis MP5ACTX8, Acidobacteriaceae bacteria KBS 146 and TAA 166, A. capsulatum ATCC51196, S. bohemicum S15, ‘ Ca . S. usitatus’ Ellin6076, C. thermophilum B, P. methylaliphatogenes K22, L. pratensis DSM100886, H. foetida TMBS4, G. fermentans DSM14018 and T. aquaticum MP‐01) (Table 2 ). Only 3 strains harboured all three putative catalytic subunits of the high‐ and low‐affinity terminal oxidases: A. capsulatum ATCC51196, ‘ Ca . S. usitatus’ Ellin6076 and L. pratensis DSM100886. Alternative oxidases (AOX) in the acidobacterial genomes were not detected. Taken together this indicates that select acidobacteria, notably many strains originating from soils, harbour both putative high‐ and low‐affinity terminal oxidases thus having the genomic potential to respire O 2 at atmospheric and sub‐atmospheric (or microoxic) concentrations. This genomic feature could provide a selective advantage in soils, since O 2 is depleted in microenvironments such as soil aggregates and as soil moisture increases (Sexstone et al ., 1985 ; Paul and Clark, 1996 ; van Elsas et al ., 1997 ), and could help contribute to their success and ubiquity in soil. Yet beyond the function as a respiratory oxygen reductase, the high‐affinity terminal oxidases can accomplish additional physiological functions, such as O 2 ‐scavenging ((Giuffrè et al ., 2014 ) and references therein) and cyanide‐sensitive nitric oxide reductase activity (Elena et al ., 2001 ). Likewise, the low‐affinity terminal oxidase can also play an important role in oxygen protection and detoxification (Ramel et al ., 2013 ). These alternative functions could explain the existence of genes encoding for bd‐ type (high‐affinity) and HCO type A (low‐affinity) oxidases in the genomes of anaerobic acidobacteria ( G. fermentans DSM14018, H. foetida TMBS4 and T. aquaticum MP‐01 ) , as growth for those strains in the presence of O 2 has not been demonstrated (Liesack et al ., 1994 ; Coates et al ., 1999 ; Losey et al ., 2013 ). Using a recent definition put forward by Morris and Schmidt, 2013 , we propose that acidobacteria harbouring either HCO type C ( cbb 3 ‐type) or the bd ‐type oxidase found in this study are microaerobes due to genomic detection of high‐affinity oxidases, presumably giving them the ability to respire O 2 at microoxic concentrations. In support of this hypothesis, strains harbouring either the cbb 3 or bd ‐type oxidase, such as T. roseus KBS 63, A. capsulatum ATCC51196, Acidobacteriaceae bacteria KBS 146 and TAA 166 and Acidobacteria bacterium KBS 96 were previously shown to grow under low O 2 conditions (1% or 2% O 2 v/v) ((Eichorst, 2007 ; Eichorst et al ., 2007 a; 2011 ), D. Trojan, S.A. Eichorst, unpublished work). This illustrates that some of these strains indeed have the capacity to respire at microoxic concentrations. Our microaerobe hypothesis of the remaining strains would need to be confirmed with growth‐based testing, in addition to testing the aforementioned alternative functions of these oxidases, which too would be advantageous in soil. Anaerobic respiration Although not frequently described across typical soil acidobacteria (subdivision 1 and 3 strains), we, nevertheless, investigated the genomic potential for dissimilatory nitrate, nitrite, sulfate and sulfite reduction. Homologues of functional marker genes of dissimilarity sulfate reduction ( dsrABC , aprBA ) were not detected in any of these genomes. None of the strains seem to be able to perform complete denitrification to dinitrogen gas as several crucial marker genes were missing in all of the genomes (Supporting Information Table S6), yet there have been examples of this process being performed by a microbial consortium (Hayatsu et al ., 2008 ). The narG operon, encoding for a membrane‐bound respiratory nitrate reductase (EC: 1.7.99.4) was detected in the genome of G. fermentans DSM14018 (Supporting Information Table S6), which is in accordance with growth‐based studies (Coates et al ., 1999 ). The genome of T. aquaticum MP‐01 harboured the napA operon (Supporting Information Table S6) involved in dissimilatory nitrate reduction (e.g., Moreno‐Vivián et al ., 1999 ; Morozkina and Zvyagilskaya, 2007 ), yet this capacity was not observed in growth‐based investigations (Losey et al ., 2013 ). Although G. mallensis MP5ACTX8 was described to reduce nitrate to nitrite (Männistö et al ., 2012b ) and Acidobacteria bacterium KBS 96 was reported to reduce a small percentage (ca. 3%) of nitrate to nitrite (Eichorst et al ., 2011 ), no dissimilatory nitrate reductases were identified in their genomes (Supporting Information Table S6). However, both genomes harboured putative assimilatory nitrate reductase genes ( nasA genes), which has been suggested to be involved in dissimilatory nitrogen metabolism (e.g., Morozkina and Zvyagilskaya, 2007 ). \n NirS , a marker gene for denitrification encoding a cytochrome cd 1 ‐containing nitrite reductase, was not found in any genome. Interestingly, Acidobacteria bacterium KBS 96 harbours two copies of nirK , which encodes for the dissimilatory copper‐containing nitrite reductase (NiR) (Supporting Information Table S6). The genome of Acidobacteria bacterium KBS 96 encoded ORFs with copper‐binding motifs T1Cu (Cys‐Met‐His 2 ) and T2Cu (His 3 ‐H 2 O) along with the active site residues Asp and His, which are required for nitrate reducing activity (e.g., Antonyuk et al ., 2005 ; Merkle and Lehnert, 2012 ; Antonyuk et al ., 2013 ) suggesting that both CuNiR might be functional. However, at this time it is rather unlikely that Acidobacteria bacterium KBS 96 is indeed a denitrifying organism as no known nitric oxide reductase is encoded in the genome. The genomes of L. pratensis DSM100886 (subdivision 6), G. fermentans DSM14018 (subdivision 8) and H. foetida TMBS4 (subdivision 8) harboured genes encoding for a dissimilatory nitrite reductase ( nrfHA) that catalyses the reduction of nitrite to ammonia, in contrast to NirK or NirS that catalyse the conversion of nitrite to nitric oxide. This respiratory nitrite ammonification is not only described to contribute to energy conservation but also plays a major role in detoxification as it mediates the nitrosative stress response caused, e.g., by the presence of nitric oxide, nitrite or hydroxylamine (e.g., Zumft, 1997 ; Kern et al ., 2011 ; Rajeev et al ., 2015 ). Homologues for norBC (also termed cNOR) and norZ (also termed qNOR) were detected in the putative nitrate/nitrite‐ reducing strains ( L. pratensis DSM100886, G. fermentans DSM14018 , H. foetida TMBS4 and T. aquaticum MP‐01), but also in subdivisions 1 and 3 strains that did not harbour any dissimilatory nitrate/nitrite reductases (Supporting Information Table S6). The norZ gene has been found to date in both denitrifiers and non‐denitrifying strains, suggesting a function in detoxifying nitric oxide (Cramm et al ., 1999 ; Büsch et al ., 2002 ; Leang et al ., 2003 ; Braker and Tiedje, 2003 ; Philippot, 2005 ) rather than in denitrification. Taken together, anaerobic respiration with either nitrate, nitrite, nitric oxide or nitrous oxide as alternative electron acceptors does not appear to be common among these investigated genomes. Candidate homologues pertaining to iron reduction ( mtrA / mtrB genes) were detected in several genomes (‘ Ca . S. usitatus’ Ellin6076, Acidobacteriaceae bacteria KBS 83 and KBS 146, Acidobacteria bacterium KBS 96, S. bohemicum S15, T. gabretensis S55, Bryobacter aggregatus MPL3, ‘ Ca . K. versatilis’ Ellin345, E. aggregans DSM19364, G. mallensis MP5ACTX8, Granulicella tundricola MP5ACTX9, L. pratensis DSM100886 and T. saanensis SP1PR4), but none of the genomes had the complete mtr / omc operons as described for dissimilatory iron reducers in Shewanella and Geobacter species (Leang et al ., 2003 ; Wang et al ., 2008 ). This suggests that these strains do not use dissimilatory Fe (III)‐reducing pathways similar to Shewanella and Geobacter species, in accordance with previous reports (Ward et al ., 2009 ). Although G. fermentans DSM14018 and T. aquaticum MP‐01 were previously described as iron reducers (Coates et al ., 1999 ; Nevin and Lovley, 2002 ; Losey et al ., 2013 ), a cluster of c‐type cytochrome genes that seem to be related to the omcA / mtrC family was only detected in the genome of G. fermentans DSM14018 (G398DRAFT_01334–01338). Few of the investigated strains have been described to be capable of fermentative growth ( T. aquaticum MP‐01, G. fermentans DSM14018, H. foetida TMBS4, A. ailaaui PMMR2) (Liesack et al ., 1994 ; Coates et al ., 1999 ; Losey et al ., 2013 ; Myers and King, 2016 ). We detected putative homologues of possible fermentation genes (Supporting Information Table S7); however, many of the enzymes show bifunctional activities and can be part of respiratory complexes, thus their true function remain to be confirmed with growth‐based studies. Taken together, the genome information is consistent with published growth‐based reports of these strains; neither anaerobic respiration nor fermentation are typically observed in strains of subdivision 1 and 3. Assimilatory nitrogen metabolism, nitrification and nitrogen fixation Nitrogen (N) is an essential nutrient, and typically limiting for microorganisms in soils (Geisseler et al ., 2010 ). As such, many soil microorganisms have the capacity of attaining N from mineral and organic forms – a feature that we explored in the acidobacteria. All investigated acidobacteria (except T. aquaticum MP‐01) harboured homologues for ammonia uptake, namely genes for the ammonium channel transporter family ( amtB gene, TC: 1.A.11) and candidate genes for glutamate dehydrogenase (GDH, EC: 1.4.1.−2/3/4; encoded by gdhA/gdh2 ), glutamine synthetase (GS, EC: 6.3.1.2; encoded by gltBD ) and glutamate synthase (GOGAT, EC: 6.3.1.2; encoded by glnA ) (Supporting Information Table S6). Furthermore, the amtB gene was located in an operon with glnK (a signal transduction protein and member of the N regulatory protein P‐II, which is known to be involved in sensing the N status of the cell). It is hypothesized that glnK and amtB genes could interact directly via protein‐protein interaction serving multiple purposes, e.g., regulating ammonia assimilation during N starvation (Coutts et al ., 2002 ; Blauwkamp and Ninfa, 2003 ). Putative genes encoding for an assimilatory nitrate reductase (NaR), nitrite reductase (NiR) and nitrate/nitrite porter (NNP, TC: 2.A.1.8) were found in T. roseus KBS 63, G. mallensis MP5ACTX8, G. tundricola MP5ACTX9, A. ailaaui PMMR2, ‘ Ca . S. usitatus’ Ellin6076, P. methylaliphatogenes K22, L. pratensis DSM100886 and Acidobacteria bacterium KBS 96, Acidobacteriaceae bacteria KBS 146 and KBS 89 and T. sp. TAA 43. Only NNP genes were detected in ‘ Ca . K. versatilis’ Ellin345, T. saanensis SP1PR4, Acidobacteriaceae bacterium TAA 166, T. gabretensis S55, A. capsulatum ATCC51196, S. bohemicum S15, B. aggregatus MPL3, C. thermophilum B, H. foetida TMBS4, G. fermentans DSM14018 and T. aquaticum MP‐01, whereas NiR genes were only detected in Acidobacteriaceae bacterium KBS 83 (Supporting Information Table S6). Genes for the amino acid‐polyamine‐organocation superfamily (TC: 2.A.3) as well as for the dicarboxylate/amino acid:cation symporter family (TC: 2.A.23) were abundant across the genomes. Additionally, the detection of chitinase genes could indicate that chitin might serve not only as a carbon source (Supporting Information Fig. S8) but also as a source of N. We also found evidence that select acidobacterial genomes harbour putative homologues encoding for extracellular peptidases. Extracellular microbial peptidase activity is of great importance in soils, as it mobilizes ammonium along with other N cycling compounds (Bach et al ., 2001 ). Many soil microorganisms express proteolytic activities (Bach et al ., 2001 ) due to serine endopeptidases (EC: 3.4.21) (such as serine alkaline peptidases, subtilisins and subtilisin‐like peptidases) (Vranova et al ., 2013 ), along with other bacterial extracellular peptidases (such as alkaline and neutral metalloendopeptidases (EC: 3.4.24) (Kalisz, 1988 ). Serine endopeptidases are often used as a marker enzyme for proteolysis activity in soil (Fuka et al ., 2008 ; Brankatschk et al ., 2011 ) and were widely distributed across most acidobacterial genomes (the secreted subtilisin‐like peptidase family S8 (sub)). In addition, the peptidases of family S53 were detected in all genomes except in those of the subdivision 8 members H. foetida TMBS4 and G. fermentans DSM14018 (Supporting Information Table S6). Homologues for various extracellular metalloendopeptidases were also detected across select genomes (Supporting Information Table S6). The presence of these putative peptidases in the acidobacterial genomes, especially ones originating from soils, could allow them to exploit different niches for N uptake during times of limitation. Altogether, it seems possible that acidobacteria can use both inorganic (ammonia and/or nitrate/nitrite) and organic N (amino acids and other high molecular weight compounds) as their N sources. The abundance of transporters specific for amino acids, polyamines and organocations seemed to be especially high in the genomes stemming from terrestrial strains (Supporting Information Table S6), suggesting their potential to not only use inorganic but also organic N sources via mineralization. Soils have been reported to contain varying types and amounts of free amino acids (Monreal and McGill, 1985 ; Kielland, 1994 ), which could serve as a source of N. Although select strains have been reported to grow on ammonia, nitrate, nitrite and/or amino acids (Eichorst, 2007 ; Koch et al ., 2008 ; Dedysh et al ., 2012 ; Crowe et al ., 2014 ; Tank and Bryant, 2015b ; Myers and King, 2016 ; Vieira et al ., 2017 ; D. Trojan and S.A. Eichorst, unpublished data), a more detailed growth‐based study is warranted, as previous work illustrated that while C. thermophilum B harboured putative genes for ammonium uptake, it was unable to grow solely on ammonium (Tank and Bryant, 2015b ). In accordance with previous reports (Ward et al ., 2009 ; Kielak et al ., 2016 ), we could not find any genomic evidence that acidobacteria are capable of nitrification as neither amoCAB nor nxrAB genes were found in the currently available genomes, nor N 2 fixation ( nif genes) except in the genome of H. foetida TMBS4 where the nif HDKEN operon was detected (Supporting Information Table S6) (Kielak et al ., 2016 ). Carbohydrate metabolism The potential to utilize carbon (C) was previously investigated in a reduced number of genomes (Ward et al ., 2009 ; Rawat et al ., 2012 ), therefore, we wanted to revisit this analysis to encompass additional genomes. Typically 5%–9% of the CDSs across the acidobacterial genomes were dedicated to genes involved in the biosynthesis, transfer, breakdown and/or modification of carbohydrates with exceptions (Supporting Information Fig. S7). There were no visible patterns observed among the different subdivisions, but the genomes of G. fermentans DSM14018, H. foetida TMBS4 and C. thermophilum B appear to have a lower portion of their genomes dedicated to carbohydrate‐active enzymes, which is in line with their previously described physiology (Liesack et al ., 1994 ; Coates et al ., 1999 ; Tank and Bryant, 2015a ). Interestingly these strains were not originally isolated from soils, which could suggest that terrestrial acidobacteria might dedicate more of their genome to carbohydrate metabolism (and presumably regulation of carbohydrate metabolism) potentially allowing for more flexibility and versatility. Across all investigated genomes, 131 glycoside hydrolase (GH) families were found (Supporting Information Fig. S8), some of which are important enzymes for the breakdown of plant cell wall (Gilbert, 2010 ). The most prevailing GH families across the acidobacterial genomes were GH109 and GH74, both presumed to be involved in polymeric carbohydrate degradation. GH109 is an alpha‐N‐acetylgalactosaminidase (EC: 3.2.1.49) that acts on O‐linked oligosaccharides, which is typically found in chitin, bacterial peptidoglycan and lipopolysaccharide (Liu et al ., 2007 ), whereas GH74 is an enzyme family that target the β‐1,4‐linkage of glucans (polysaccharide of glucose). Across the genomes, H. foetida TMBS4 did not harbour GH109 nor GH74, and there were few occurrences of GH109 in T. aquaticum MP‐01, G. fermentans DSM14018, and C. thermophilum B. Various GH families involved in the degradation of β‐glucosidic bonds, typical bonds found in cellulose (Berlemont and Martiny, 2013 ), were found across these investigated genomes. More specifically, GH5 was more consistently found across subdivision 1, 3, 4 and 6, while GH8, GH9, GH44 and GH12 were only detected in a few genomes of subdivision 1 ( T. sp. TAA 43, ‘ Ca . K. versatilis’ Ellin345, T. gabretensis S55, and G. mallensis MP5ACTX8) and once in subdivision 3 (GH9, ‘ Ca . S. usitatus’ Ellin6076), supporting some of the previous GH family investigations (Ward et al ., 2009 ). GH3 can encode for β‐glucosidase (an enzyme that hydrolyses the glycosidic bonds in oligosaccharides to glucose); it was found across all investigated genomes. Putative chitinases (GH18 and GH19 family) were previously identified in the genomes of G. mallensis MP5ACTX8, G. tundricola MP5ACTX9 and T. saanensis SP1PR4 (Rawat et al ., 2012 ). Here we found CDSs mainly for GH18 across all subdivision 1 genomes, two genomes of subdivision 3 (‘ Ca . S. usitatus’ Ellin6076 and Acidobacteria bacterium KBS 96), one genome of subdivision 4 ( P. methylaliphatogenes K22), L. pratensis DSM100886 (subdivision 6) and H. foetida TMBS4 (subdivision 8), whereas CDSs for GH19 were only found in G. fermentans DSM14018, P. methylaliphatogenes K22, L. pratensis DSM100886, T. saanensis SP1PR4 and E. aggregans DSM19364 (Supporting Information Fig. S8). In addition to the degradation of polymeric C compounds, select strains appear to have the possibility of anaplerotic carbon dioxide fixation. Homologues of phosphoenolpyruvate carboxylase and isocitrate dehydrogenase were detected across numerous genomes (Supporting Information Table S8) and were mostly, but not exclusively, distributed across the strains stemming from terrestrial environments. This feature could be advantageous for these strains as soils harbour pockets of elevated carbon dioxide. The presence of these CDSs suggests the possibility of carbon supplementation via anaplerotic pathways as was shown previously in P. methylaliphatogenes K22 (Lee et al ., 2015 ). Select genomes also contained putative homologues for the korAB genes for carboxylation of succinyl CoA (via 2‐ketoglutarate ferredoxin oxidoreductase) and putative homologues for porABDG and/or por/nifJ for acetyl CoA carboxylation (pyruvate ferredoxin oxidoreductase) (Supporting Information Table S8). CDSs of RuBISco (EC: 4.1.1.39) were not detected. The genomic data suggest that select strains have the potential to degrade plant polymeric C (such as cellulose and chitin) supporting previous findings (Ward et al ., 2009 ; Rawat et al ., 2012 ) and that they can also supplement intermediates in the citric acid cycles through anaplerotic pathways. Previous growth‐based work among many of the strains supports these findings with the utilization of a diverse collection of carbohydrates, such as plant polymeric C (Eichorst et al ., 2011 ; Dedysh et al ., 2012 ; Rawat et al ., 2012 ). H 2 scavenging The thermophilic acidobacterial strain P. methylaliphatogenes K22 (subdivison 4) was identified to harbour the membrane‐bound hydrogen (H 2 )‐uptake [NiFe]‐hydrogenases group 1h (formely group 5) (hereafter referred to as ‘group 1h/5 hydrogenase’) (Greening, et al ., 2015a ). This strain was able to consume atmospheric levels of H 2 due to the presence of this gene. Furthermore, the catalytic subunit was upregulated in stationary phase relative to the exponential phase suggesting that H 2 uptake could be a strategy to survive periods of starvation (Greening, et al ., 2015a ). Although acidobacteria are detected in thermophilic environments, they are most abundant in more temperate soils (Jones et al ., 2009 ). Select mesophilic strains, ‘ Ca . S. usitatus’ Ellin6076 and G. mallensis MP5ACTX8 were previously identified to harbour the group 1h/5 hydrogenase (Constant et al ., 2011 ; Greening, et al ., 2015a ). We expanded on this observation and identified two additional strains in subdivision 1 ( Acidobacteriaceae bacterium KBS 83 and E. aggregans DSM19364) and one strain in subdivision 3 ( Acidobacteria bacterium KBS 96) that harbour the group 1h/5 hydrogenase (Fig. 5 A). Multiple genes predicted to be the necessary structural genes for this group 1h/5 hydrogenase, such as the small subunit ( hhyS ), large subunit ( hhyL ), a putative Fe‐S cluster ( hhyE ), a putative endopeptidase ( HupD ) as well as conserved hypothetical proteins (HP) (Fig. 5 B) were identified in these aforementioned strains. All strains encode one copy of the large subunit of the hydrogenase, and the L1 and L2 signatures of this subunit were similar to the reported signatures of the group 1h/5 [NiFe]‐hydrogenase type (Constant et al ., 2011 ) (Supporting Information Fig. S9). The large subunit across all identified acidobacteria share on average 75.8% deduced amino acid sequence identity to Streptomyces avermitilis ATCC31267. Furthermore, these acidobacteria strains form a distinct cluster, which is most similar to a strain in the phylum Verrucomicrobia , Pedosphaera parvula Ellin514 (average sequence identity of 77.5%) (Fig. 5 A). Within these structural genes, three highly conserved proteins (Fig. 5 A, ‘HP’) were detected, previously characterized as specific for this high‐affinity hydrogenase across all organisms encoding group 1h/5 hydrogenases, yet their function remains unknown (Greening, et al ., 2015b ). The structural subunits contain all residues to bind a [NiFe]‐centre for H 2 cleavage (large subunit) and the three [4Fe4S] clusters for electron transfer (small subunit), suggesting that these hydrogenases could be functional in these acidobacterial strains. Multiple genes predicted to encode for maturation genes ( hypABCDEF ) (Fig. 5 A), which are required for the function of hydrogenases (Greening, et al ., 2015b ), were also detected across the acidobacterial strains. The operon structure of these newly identified strains is somewhat conserved to Streptomyces avermitilis MA‐468 and P. methylaliphatogenes K22 (Fig. 5 B). Conversely, the gene synteny of the previous identified acidobacteria, ‘ Ca . S. usitatus’ Ellin6076 and G. mallensis MP5ACTX8 (Constant et al ., 2011 ; Greening, et al ., 2015a ), were very distinct from S. avermitilis MA‐468 and P. methylaliphatogenes K22, namely the maturation protein genes for G. mallensis MP5ACTX8 were upstream of the catalytic subunits, while the catalytic subunits of ‘ Ca . S. usitatus’ Ellin6076 were flanked by maturation proteins (Supporting Information Table S9). Figure 5 Distribution and gene organization of the group 1h/5 hydrogenases across the acidobacterial genomes. A. A neighbour‐joining tree based on the deduced amino acid sequence (ca. 560 amino acid positions) of the group 1h/5 [NiFe]‐hydrogenase large subunit. The tree was bootstrapped 1000 times, and the consensus support is displayed [> 95% ( ) and > 90% ( )]. The outgroup (not shown) was the group 1 [NiFe]‐hydrogenase from Desulfovibrio sp. strain TomC (A0A0B1U1E4). B. The gene synteny of structural and maturation genes for the group 1h/5 [NiFe]‐hydrogenase across newly identified members of the phylum Acidobacteria . Streptomyces avermitilis MA‐4680 and Pyrinomonas methylaliphatogenes K22 are also shown for comparison. Unlabelled grey arrows depict other genes associated with the hydrogenase‐encoding locus: asterisks depict a putative phosphoheptose isomerase ( gmhA ), crosses depict a putative glutaredoxin 3 and circles depicts hypothetical proteins. Locus tags can be found in Supporting Information Table S9. Our analysis extends the detection of group 1h/5 hydrogenases to mesophilic acidobacteria in subdivision 1 and 3, yet the functionality of this hydrogenase across the strains still needs to be confirmed. Nevertheless, these data suggest that select members of the acidobacteria have the genes predicted to function as a group 1h/5 hydrogenases, which could provide them with a selective advantage for periods of starvation as hypothesized for P. methylaliphatogenes K22 (Greening, et al ., 2015a ). With this, the genomic potential to oxidize H 2 at atmospheric levels using the group 1h/5 hydrogenase spans members in subdivisions 1, 3 and 4, which are typical subdivisions found in soils (Jones et al ., 2009 ). Although it does not appear to be a widespread trait among all investigated acidobacterial genomes, it seems that the presence of these putative hydrogenases is not unique to a particular subdivision or environment type. A similar pattern can be seen in the Actinobacteria – select members in the Streptomycetes are believed to play a critical role in soil H 2 consumption (Constant et al ., 2010 ), yet not all Actinobacteria harbour a hydrogenase gene. Soils have been described as the major sink for H 2 , and soil bacteria are believed to control this consumption (Conrad, 1996 ; Greening, et al ., 2015b ). It has been hypothesized that this uptake could sustain approximately 6 x 10 7 H 2 ‐oxidizing soil bacteria per gram of soil, yet the identity of these potential H 2 ‐oxidizing soil bacteria remains unknown (Conrad, 1996 ; Constant et al ., 2011 ). Group 1h/5 hydrogenases were not the only hydrogenases detected in the acidobacteria. We also found evidence for other [NiFe]‐hydrogenases in strains from subdivision 1, 3 and 23, such as group 1c [‘ Ca . S. usitatus’ Ellin6076 (Acid_6926) and ‘ Ca . K. versatilis’ Ellin345 (Acid345_4240)], group 1d [ T. aquaticum MP‐01 (EG19_11475)], group 3c [ T. aquaticum MP‐01 (EG19_05165)] and group 1f [ S. bohemicum S15 (Ga0077217_103189) and A. capsulatum ATCC51196 (ACP_3053)]. Group 1f was also reported in a thermophilic strain in subdivision 1 ( A. ailaaui PMMR2) (Myers and King, 2016 ). At this time, more physiological investigations across these non‐group 1h/5 hydrogenases are warranted."
} | 19,300 |
30250697 | PMC6145019 | pmc | 7,551 | {
"abstract": "Abstract Ecotones between distinct ecosystems have been the focus of many studies as they offer valuable insights into key drivers of community structure and ecological processes that underpin function. While previous studies have examined a wide range of above‐ground parameters in ecotones, soil microbial communities have received little attention. Here we investigated spatial patterns, composition, and co‐occurrences of archaea, bacteria, and fungi, and their relationships with soil ecological processes across a woodland‐grassland ecotone. Geostatistical kriging and network analysis revealed that the community structure and spatial patterns of soil microbiota varied considerably between three habitat components across the ecotone. Woodland samples had significantly higher diversity of archaea while the grassland samples had significantly higher diversity of bacteria. Microbial co‐occurrences reflected differences in soil properties and ecological processes. While microbial networks were dominated by bacterial nodes, different ecological processes were linked to specific microbial guilds. For example, soil phosphorus and phosphatase activity formed the largest clusters in their respective networks, and two lignolytic enzymes formed joined clusters. Bacterial ammonia oxidizers were dominant over archaeal oxidizers and showed a significant association ( p < 0.001) with potential nitrification ( PNR ), with the PNR subnetwork being dominated by Betaproteobacteria . The top ten keystone taxa comprised six bacterial and four fungal OTU s, with Random Forest Analysis revealing soil carbon and nitrogen as the determinants of the abundance of keystone taxa. Our results highlight the importance of assessing interkingdom associations in soil microbial networks. Overall, this study shows how ecotones can be used as a model to delineate microbial structural patterns and ecological processes across adjoining land‐uses within a landscape.",
"conclusion": "5 CONCLUSION Using geostatistics, quantitative PCR, high‐throughput sequencing and network analysis, we demonstrated spatial patterns and co‐occurrences of archaeal, bacterial, and fungal communities across a woodland‐grassland ecotone. The abundance, structure, and taxonomic composition of soil microbial communities were significantly different in the transition zone than the woodland and grassland. Microbial networks predominantly comprised positive interactions that reflected the high C, N, and P levels at this site. Microbial co‐occurrences showed clusters based on habitats, soil properties, and ecological processes. Although microbial networks were dominated by bacterial OTUs, fungal and archaeal members were also abundant, highlighting the importance of interkingdom associations in soil microbial networks. Nitrification was driven by ammonia‐oxidizing bacteria, and this was supported by the dominance of Betaproteobacteria OTUs in the PNR subnetwork. A coherence of spatial patterns and co‐occurrences of microbial communities was thus demonstrated across the ecotone.",
"introduction": "1 INTRODUCTION Ecotones between adjacent ecosystems or biomes that harbor contrasting plant communities represent useful areas for investigation, as they support unique ecological dynamics (Anadón, Sala, & Maestre, 2014 ; Archer & Predick, 2014 ). However, recent studies show that ecotones are highly responsive to environmental change and this is especially true for ecotones in the arid and semi‐arid regions such as the ones in Australia (Delgado‐Baquerizo et al., 2014 ). Grassland‐woodland ecotones around the world are subject to dynamic shifts toward an unstable state, and this has received considerable research attention in recent years (Bradford, Schlaepfer, Lauenroth, & Burke, 2014 ; Sala & Maestre, 2014 ). Ecotones encompass interactions occurring between adjoining systems and are useful because the local effects of shifts in vegetation can be explicitly assessed independently of the environmental variability that may occur over broader spatial scales (Gosz, 1993 ). In addition, such areas can reveal the edge effect between two adjacent habitats (Lacasella, Gratton, & De Felici, 2015 ; Malmivaara‐Lämsä et al., 2008 ; Murcia, 1995 ). Edge effect is the result of the abiotic and biotic interactions between adjoining habitats when the habitats are separated by an abrupt transition (sensu Murcia, 1995 ). Previous studies have focused on ecotones to examine impacts on community structure (e.g., species diversity and distribution patterns) as well as a range of ecological processes such as above‐ground biotic interactions, hydrology, fire dynamics, and responses to climate change (Archer & Predick, 2014 ; Eldridge et al., 2011 ; Ratajczak, Nippert, Briggs, & Blair, 2014 ). In contrast, understanding of belowground communities and interactions within the soil microbiota has received less attention (Malmivaara‐Lämsä et al., 2008 ). Soil microbiota provide a range of important ecosystem services including soil aggregation, organic matter decomposition, nutrient cycling, and mutualistic and pathogenic interactions with plants (Bardgett & van der Putten, 2014 ; Killham, 1990 ; Richardson, Barea, McNeill, & Prigent‐Combaret, 2009 ; Schimel & Schaeffer, 2012 ; van der Heijden, Bardgett, & Van Straalen, 2008 ). While patterns across ecotones have been observed for some soil parameters (e.g., moisture, temperature, carbon storage, etc.) and macrobiota in previous studies (Lacasella et al., 2015 ; Magura, 2017 ; Schmidt, Jochheim, Kersebaum, & Lischeid, 2017 ), little information is available on soil microbiome (Malmivaara‐Lämsä et al., 2008 ). The soil microbiome comprises a vast diversity and abundance of different microbial groups and complex trophic interactions (Bardgett & van der Putten, 2014 ; van der Heijden et al., 2008 ). Microbial co‐occurrence networks can reveal associations among network members and yield insight into microbiome functioning (Bissett, Brown, Siciliano, & Thrall, 2013 ; Cardona, Weisenhorn, Henry, & Gilbert, 2016 ; Faust & Raes 2012 ; Fuhrman, 2009 ;). For example, patterns of microbial co‐occurrence have been demonstrated for a diverse range of aquatic and terrestrial environments (Banerjee, Baah‐Acheamfour et al., 2016 ; Barberán, Bates, Casamayor, & Fierer, 2012 ; De Menezes et al., 2015 ; Graham et al., 2017 ; Shi et al., 2016 ). Previous studies using network analysis have often only assessed bacterial communities and not fungal or archaeal communities (Banerjee, Baah‐Acheamfour et al., 2016 ; Barberán et al., 2012 ; Shi et al., 2016 ; Vick‐Majors, Priscu, & Amaral‐Zettler, 2014 ). Thus, the roles of these latter groups have been underrepresented in microbial network analyses and only a few studies have investigated associations all three kingdoms (Ma et al., 2016 ; Steele et al., 2011 ). Moreover, network analysis provides a statistical tool to identify keystone taxa that play a key role in microbiome structure and functioning (Banerjee, Schlaeppi, & van der Heijden, 2018 ; Power et al., 1996 ). A number of studies have used network‐based scores to identify putative keystone taxa in different environments (Hartman et al., 2018 ; Lupatini et al., 2014 ; Shi et al., 2016 ; Vick‐Majors et al., 2014 ) and linked their abundance to soil nutrient cycling processes (Banerjee, Kirkby et al., 2016 ; Li, Chen, Zhang, Yin, & Huang, 2017 ). A major challenge in ecology is to link microbial co‐occurrences to processes that contribute to soil function. For example, extracellular enzymes are ubiquitous in soil environments and play critical roles in ecosystem functioning through mediation of carbon (C), nitrogen (N), and phosphorus (P) mineralization, thus, facilitating soil organic matter decomposition (Burns, 1982 ). Soil enzyme activities have often been used as indicators of soil health and microbial function (Allison & Vitousek, 2005 ; Saiya‐Cork, Sinsabaugh, & Zak, 2002 ; Sistla & Schimel, 2013 ). Likewise, ammonia oxidation is important for soil nutrient availability as it is a key step for nitrification in which ammonia is converted to hydroxyl amine and subsequently to nitrite and nitrate (Kowalchuk & Stephen, 2001 ). The functional gene, amoA, is present in both bacteria and archaea and has been used in many studies to quantify the abundance of ammonia oxidizers in different environments (Di et al., 2009 ; Jia & Conrad, 2009 ; Leininger et al., 2006 ). Spatial patterns of ammonia oxidizers across ecotones can unravel niche differentiation and partitioning among bacteria and archaea based on nutrient availability (Prosser & Nicol, 2012 ). However, few studies have assessed microbial co‐occurrences in relation to soil nitrification and enzyme activities. In a previous study, we found similar spatial patterns for a wide range of soil properties and extracellular enzyme activities across two native woodland‐grassland ecotones (Banerjee, Bora, Thrall, & Richardson, 2016 ). In this study, we further investigated patterns of abundance, diversity, and co‐occurrence for archaeal, bacterial, and fungal communities in one of these ecotones. Our overall hypothesis was that soil microbial properties are different in the transition zone than either of the adjacent woodland or grassland communities. A multifarious approach was used to address the following specific questions: (a) How do the spatial structure, composition, and co‐occurrences of soil archaeal, bacterial, and fungal communities change across a woodland‐grassland ecotone?; (b) How are ammonia oxidizing bacteria and archaea linked to potential nitrification across such ecotones?; (c) Is the composition of microbial networks related to soil properties and ecological processes?; and (d) Which soil properties drive the abundance of microbial keystone taxa across the woodland‐grassland ecotone?",
"discussion": "4 DISCUSSION 4.1 Microbial communities across the ecotone In this study, we explored the abundance, structure, and co‐occurrences of soil archaea, bacteria, and fungi, and their relationships with relevant soil ecological processes along a woodland‐grassland ecotone. Firstly, using spatial interpolation, we showed how the overall abundance of archaea, bacteria, and fungi changed between woodland and grassland soil samples. The woodland samples had significantly higher microbial abundance than was observed for the grassland samples with a visually distinct transition zone. This higher abundance was observed generally for overall archaea, bacteria, and fungi, and specifically for ammonia oxidizing archaea and bacteria. The overall gene copy numbers of these microbial groups we found in our woodland and grassland soils are comparable to previous studies (Banerjee, Baah‐Acheamfour et al., 2016 ; Gleeson et al., 2010 ; Kemnitz, Kolb, & Conrad, 2007 ; Lauber, Strickland, Bradford, & Fierer, 2008 ). Secondly, our analyses of α‐ diversity indices showed that the woodland samples had significantly higher diversity of archaea while the grassland samples had significantly higher diversity of bacteria. It should be noted that the grassland soils at our site had significantly higher N and P levels than the woodland soils. Typically, bacteria are more responsive to nutrient‐rich conditions than archaea (Carey, Dove, Beman, Hart, & Aronson, 2016 ), which indicates their copiotrophic nature (Fierer, Bradford, & Jackson, 2007 ). Our results show that the habitat edge between woodland grassland significantly influenced microbial β‐diversity. Microbial communities formed distinct clusters in woodland and grassland samples with the transition zone forming a gradient between those two adjoining systems. Moreover, OTUs belonging to Acidobacteria in bacteria and Agaricomycetes and Leotiomycetes in fungi was significantly higher in the woodland samples than elsewhere. Several members of these oligotrophic microbial groups are involved in wood decomposition, and our results are consistent with previous studies reporting greater abundance of these groups in forest soils (Edwards & Zak, 2011 ; Jones et al., 2009 ). Several members of the Agaricomycetes are ectomycorrhizal (van der Heijden, Martin, Selosse, & Sanders, 2015 ), which may also explain their higher abundance in the woodland soils. Similarly, we found that the number of OTUs belonging to Agaricostilbomycetes was significantly higher in the grassland samples than the woodland samples. Interestingly, a previous study showed a positive relationship between the abundance of OTUs of this group and plant community richness in grassland (LeBlanc, Kinkel, & Kistler, 2014 ). Overall, microbial diversity and composition were significantly influenced by the habitat edge as revealed across this ecotone. 4.2 Potential nitrification driven by bacterial ammonia oxidizers Bacterial rather than archaeal ammonia oxidizers drove potential nitrification in the N‐rich soils at this site, and this pattern was consistently shown by multiple analytical approaches employed in this study. For example, ordinary kriging revealed that both bacterial amoA and PNR had visually similar spatial patterns and operated at similar spatial ranges. Consequently, these groups were also positively correlated ( p < 0.001) across the ecotone. Network analysis further indicated that the PNR subnetwork was dominated by unclassified members of Betaproteobacteria and not archaea. It should be noted that soils across this ecotone were relatively N rich with average %N, NH 4 ‐N and DON of 0.287% (w/w), 12.1 μg and 78.8 μg per gram of soil, respectively (Banerjee, Bora et al., 2016 ). While archaeal ammonia oxidizers are important for nitrification and dominant in many ecosystems (Leininger et al., 2006 ), they are well‐acknowledged for their oligotrophic nature (Erguder, Boon, Wittebolle, Marzorati, & Verstraete, 2009 ; Hatzenpichler, 2012 ). On the other hand, bacterial ammonia oxidizers are typically copiotrophic which makes them particularly suited for more nutrient rich soils. Interestingly, archaeal amoA was more abundant than bacterial amoA in both woodland and grassland soils in our study, but despite this, bacterial ammonia oxidizers displayed a stronger correlation with potential nitrification. Previous studies have similarly found that archaeal ammonia oxidizers are less responsive to nitrification in N‐rich soils even when they are relatively more abundant than their bacterial counterparts (Di et al., 2009 ). The higher responsiveness of ammonia oxidizing bacteria in N‐rich soils was also noted in a recent global meta‐analysis (Carey et al., 2016 ). The different spatial ranges of bacterial and archaeal ammonia oxidizers in our study indicate a possible niche differentiation of these communities as previously suggested (Prosser & Nicol, 2012 ). While the majority of Betaproteobacteria nodes in the PNR subnetwork were unclassified members, the association between the PNR subnetwork and Betaproteobacteria members reinforces the importance of this bacterial group for nitrification in N‐rich soils. 4.3 Microbial co‐occurrences across ecotone We found a similarity between microbial co‐occurrence and spatial patterns. For example, microbial nodes in the woodland, grassland, and transition zone were structured into separate clusters with the woodland habitat having a significantly higher number of nodes. Similarly, kriging showed a significantly higher abundance of all microbial groups in the woodland samples. Importantly, our results illustrate how network complexity, indicated by the number of nodes and edges, changes between two adjoining ecological systems within one landscape and how archaeal, fungal, and bacterial patterns of co‐occurrence are influenced in the transition zone. Previous studies using network analysis have often only assessed bacterial communities and not fungal or archaeal communities (Banerjee, Baah‐Acheamfour et al., 2016 ; Barberán et al., 2012 ; Shi et al., 2016 ; Vick‐Majors et al., 2014 ). Thus, the roles of these latter groups have been underrepresented in microbial network analyses (Ma et al., 2016 ; Steele et al., 2011 ). While the networks were dominated by bacterial nodes, fungal and archaeal nodes were also abundant. Our results highlight the importance of assessing interkingdom associations in soil microbial networks. 4.4 Relationships between microbial co‐occurrences and ecological processes Linking microbial community composition to function is a central goal in ecology (Graham et al., 2016 ; Prosser et al., 2007 ). In this study, soil P and C:N formed large clusters dominated by bacterial nodes and these clusters were also connected with other C and N properties. Similarly, the processes of C, N, and P cycling were also correlated with microbial co‐occurrence. Interestingly, soil P and phosphatase activity formed the largest clusters in their respective networks whereas two lignolytic enzymes (phenol oxidase and peroxidase) formed joined clusters. Extracellular enzymes are involved in the decomposition and mineralization of soil organic matter, which is a “broad” process that involves many steps and operated by functionally and taxonomically diverse generalist microbial groups (Fierer et al., 2007 ; Schimel & Schaeffer, 2012 ). On the other hand, ammonia oxidation is a “narrow” process facilitated by specialist groups of bacteria and archaea (Kowalchuk & Stephen, 2001 ). The distinct cluster of PNR was mainly dominated by Betaproteobacteria , reinforcing the observation that nitrification at this site was driven by ammonia oxidizing bacteria. 4.5 Keystone taxa and determinants A useful feature of network analysis is that it can identify “hubs” or keystone taxa that have significant influence on the structure and functioning of microbiomes (Newman, 2003 ). Identifying keystone taxa and the factors that drive their abundance and spatiotemporal distribution is of particular importance in microbial ecology. The concept of keystone taxa was originally proposed some decades ago by ecologist Paine ( 1966 ). Keystone taxa have been identified in microbial communities both statistically (Banerjee, Kirkby et al., 2016 ; Hartman et al., 2018 ; Lupatini et al., 2014 ; Shi et al., 2016 ) and empirically (Curtis et al., 2014 ; Fisher & Mehta, 2014 ; Hajishengallis, Darveau, & Curtis, 2012 ). Berry and Widder ( 2014 ) used network‐based scores such as high mean degree, high closeness centrality, and low betweenness centrality to identify keystone taxa with 85% accuracy. Using the method proposed by Berry and Widder ( 2014 ), we identified six bacterial and four fungal OTUs in this study as representing the top ten keystone taxa. In a recent study, we also reported that bacterial and fungal keystones were significantly correlated to organic matter decomposition in an agricultural soil (Banerjee, Kirkby et al., 2016 ). Soil carbon and nitrogen contents likewise emerged as the drivers of keystone taxa that we identified here across the woodland‐grassland ecotone. One limitation of this study is that high‐throughput sequencing of microbial communities was performed on 18 soil samples. These samples were randomly selected equally from the three zones with six samples at each habitat component. Thus, careful consideration was made to obtain representative samples across this woodland‐grassland ecotone. Moreover, the selection of a single ecotone site in this study was based our previous observation that spatial patterns of a range of soil properties and extracellular enzyme activities were similar across two native woodland‐grassland ecotones (including this one) located approximately 150 km apart (Banerjee, Bora et al., 2016 )."
} | 4,945 |
34577660 | PMC8465357 | pmc | 7,554 | {
"abstract": "A control chip with a multistage flow-rate regulation function based on the correlation between the flow resistance and flow rate has been developed in this article. Compared with the traditional proportional solenoid valve, this kind of flow valve based on microfluidic technology has the characteristics of being light-weight and having no electric drive. It solves such technical problems as how the current digital microfluidic chip can only adjust the flow switch, and the adjustment of the flow rate is difficult. To linearize the output signal, we propose a design method of weighted resistance. The output flow is controlled by a 4-bit binary pressure signal. According to the binary value of the 4-bit pressure signal at the input, the output can achieve 16-stage flow adjustment. Furthermore, we integrate the three-dimensional flow resistance network, multilayer structure microvalve, and parallel fluid network into a single chip by using 3D printing to obtain a modular flow control unit. This structure enables the microflow control signal to be converted from a digital signal to an analogue signal (DA conversion), and is suitable for microflow driving components, such as in microfluidic chip sampling systems and proportional mixing systems. In the future, we expect this device to even be used in the automatic control system of a miniature pneumatic soft actuator.",
"conclusion": "5. Conclusions This article investigated the structure and performance of a microfluidic DA conversion device that uses the design approach of an electrical circuit. The conversion unit can operate with four input pressure codes and achieve 16-stage output flow rates. The experiments demonstrate that this device can realize continuous multistage flow rate adjustment. The basic device-operating characteristics have been obtained by signal analysis, with a 250~750 ms settling time and a 5% linearity. By connecting the microfluidic chip to a pneumatic flexible actuator, we simply demonstrate an application of the DA chip in the driver of a soft robot. The associated modelling allows us to control a complex microfluidic system with only a pump, and not only channel switch operation, but also flow rate adjustment. In the future, such microfluidic processors will have the potential to replace electronic devices in certain special environments, such as underwater environments or those with strong electric or magnetic fields.",
"introduction": "1. Introduction The fluid signal processing function has been one of the most popular research directions for microfluidic devices in recent years. It is also a significant branch of digital microfluidic technology. Compared to being used as an experimental container for biochemical reactions, a microfluidic device with this function can expand the application of microfluidic technology to mechanical and electronic fields. As early as 2015, Au et al. reported the prototype of a microfluidic device with automated control functions [ 1 ]. Subsequently, based on summarizing the microfluidic logic control methods in recent years, Sochol et al. reported a microfluidic device with a digital processing function fabricated through a 3D printing method [ 2 ] that can process fluid signals itself. Woodhouse et al. demonstrated a microfluidic logic system and applied it to the study of the self-assembly behavior of photochemically active matter [ 3 ]. Elatab et al. noted that the next generation of microfluidic devices should be able to perform in situ analysis and processing of complex fluid behavior, similar to the current integrated electronic circuits that use logic gates to perform complex operations. This would enable the microfluidic system to make decisions autonomously according to Boolean rules and eliminate the need for any external intervention [ 4 ]. Some emerging fields have urgent needs for this technology. For example, Wehner et al. reported that soft robots have many attributes, many of which will be very complicated when implemented with rigid structures. The soft robot must be bound to the control and power systems of the rigid robot. To realize the potential of soft actuators, new strategies are needed to create completely soft drives, actuators, and robot structures. These key components include flexible mechanical systems and pressure-driven 3D microfluidic chips with logic operations [ 5 ]. Pneumatic soft actuators can contact and manipulate soft and fragile objects without damaging them, such as manufacturing assembly line robots, automatic packaging robots, fruit picking robots, and so forth. Furthermore, it can safely interact with human beings, which is suitable for nursing workplaces, such as hospitals and nursing homes. Its continuous working mode is also similar to the working process of bionic motion robot muscles, which has great bionic application potential. At present, fluid signals, such as flow and pressure, can be processed by microfluidic devices, but the methods are mainly based on switching behaviour. The basic element is the membrane microvalve structures invented by Quake [ 6 ]. On this foundation, researchers have realized a series of logic behaviours that achieve functions similar to electrical systems. This kind of chip is also called an integrated fluidic circuit (IFC) [ 7 ]. These devices are based on fluid equivalent theory [ 8 ]. Under laminar flow, the voltage-resistance-current relationship in the electronic circuit approximately corresponds to the pressure-flow and resistance-flow-rate relationship in the fluidic circuit. By transforming the diodes in the electronic circuit into microvalves in the fluidic circuit, the microfluidic chip itself can perform direct logic control based on the fluid motion behaviour and realize the conversion from ‘electronic-controlled fluid’ to ‘fluid-controlled fluid’. The logic function of electronic circuits can be correspondingly used in the microfluidic chip [ 9 ]. Lesher–Perez et al. used the phase difference between multiple microvalves to realize fluidic oscillation behaviour, and the output could be oscillating pressure or flow rate signals [ 10 ]. The structure was similar to the ring oscillator in an electronic circuit, and the generated pressure or flow rate signal were used in the drive of a vibrating table [ 11 ] and a soft actuator [ 5 ]. Grove et al. used vacuum pressure as the source signal to obtain the logic gate structure of AND/OR/NO. These gates can be connected into a high-order digital network to realize the trigger and latch structure under a fluid medium. These devices realize the signal storage function of the chip by the microfluidic system itself [ 12 ]. Zhou et al. proposed the idea of a microfluidic arithmetic unit and carried out the preliminary design and experiment of the adder logic [ 13 ]. Although IFC chips have achieved certain research results, their functions still belong to the category of digital circuits in electronics. The signals of their output ports are all with or without fluid, and the difference in signals is only distinguished by the difference in the flow channels. According to the history of the electronics field, this pure digital signal processing has limited development potential. Digital circuits always need to be used in conjunction with analogue circuits to enrich the control functions [ 14 ]. In a microfluidic system, we can regard analogue signal processing as the continuous physical expression of the flow rate or pressure, in other words, as control of the flow rate or pressure. Most microfluidic device functions are realized based on flow rate regulation, such as the reaction rate of polymerase chain reaction [ 15 ], physical sorting performance of cancer cells [ 16 , 17 ], noise and thermal response performance of an enzyme measurement sensor [ 18 ], and dynamic dialysis speed of a solution [ 19 ]. Normally, we can easily adjust the flow rate in a pipeline through manual control, such as via faucets and drain valves. However, in the field of automatic control, there is no strict analogue signal. The analogue signals we currently use are processed from digital signals. To obtain an analogue signal, a device with a digital-to-analogue (DA) conversion circuit must be used. Therefore, the current flow adjustment in a microfluidic system still relies on external electromagnetic devices, such as syringe pumps or peristaltic pumps, or on variable physical fields such as electricity, magnetism, and heat. These external devices and physical field controllers must also have analogue output. Heo et al. began with the pump control algorithm and improved the accuracy and stability of the flow regulation in a microfluidic network [ 20 ]. Xu et al. used the adjustable temperature to change the size of vapour bubbles in a flow channel and blocked fluid movement through the bubbles, which can realize flow adjustment [ 21 ]. Zhang et al. used a membrane microvalve as a flow adjustment unit and adjusted the output flow by changing the opening size of the valve core through adjustable air pressure [ 22 ]. Perdigones et al. reduced the stiffness of a membrane microvalve and achieved a larger range of flow regulation under the same external pressure [ 23 ]. Casals–Terré et al. set up a V-type cobalt-nickel electrodeposited layer in a flow channel. An external permanent magnet field drives the movable structure attached to the deposition layer and changes the size of the flow channel opening to achieve the flow rate regulation function [ 24 ]. Johansson et al. used MEMS technology to make a silicon-based piston microvalve structure to adjust the gas flow [ 25 ]. Chong et al. used the acoustic induction method to change the flow rate in a T-shaped channel, which can adjust the size of the generated droplets [ 26 ]. To date, no microfluidic chip can adjust the flow rate without external analogue control signals. In this paper, we report a microfluidic system based on a weighted flow resistance network that converts multichannel pressure digital signals to an adjustable flow rate. Its design and manufacturing process are simple, and it can be easily integrated into existing microfluidic devices. In the current design, the output flow rate can be adjusted via the permutation and combination of the pressure signals at the four inlets, which are either with or without pressure. This is similar to the conversion of binary numbers to decimal numbers. We demonstrate the concept of weighted flow resistance. By weighting the flow resistance of different branches, we can obtain the upper limit of the flow rate that can be controlled by each branch. We use membrane microvalves to control the ‘on’ and ‘off’ state of each branch. The control signals of these membrane microvalves are the 4-bit pressure signals we input. When the input signal is 4 bits, the output can realize 16-level orderly control. According to experiments, this microfluidic chip with a DA conversion function shows good linearity in its flow curve. Table 1 summarizes the characteristics of different flow regulation methods. In this paper, the flow control method with a DA conversion function provides novel ideas for the application of microfluidics in the field of pneumatic or hydraulic automatic control.",
"discussion": "4. Results and Discussion The software used for simulation analysis is Comsol Multiphysics (Comsol, Inc. Stockholm, Sweden). The grid is a hexahedral grid with five boundary layers, and the minimum mesh size is 20 μm. The inlet is a constant flow rate boundary, and the outlet is an open boundary. The flow resistance can be expressed as R = Q/Δp, where Q is the inlet flow rate and Δp is the pressure difference between the two ends of the flow resistance network. Figure 4 a shows the change in flow resistance under different flow rates and different flow channel lengths, where the length of a single unit is l = 3 mm. The simulation results show that the flow resistance in the flow channel changes nonlinearly with increasing flow rate. When the flow rate changes from 0 to 1000 μL/min, the flow resistance has a change rate of approximately 20%. With a further increase in the flow rate, the change curve of the flow resistance gradually becomes a smooth, straight line. When the input flow rate remains steady, the flow resistance has an obvious linear relationship with the length of the flow channel. These results indicate that the input flow rate does not have a very large impact on the flow resistance, and the flow resistances for different lengths are proportional under the same flow rate. For the design dimensions in this article, when the flow rate is less than 200 μL/min, the rate of change in the flow resistance is relatively large. When the flow rate is higher than 200 μL/min, the flow resistance change curve is basically level. Therefore, to ensure the consistency of the flow resistance in each branch of the device, we need to ensure that the smallest flow rate is greater than 200 μL/min, that is, Q/16 = 200 μL/min, where Q is represented by the minimum flow rate for the binary number 1111. To reduce the amount of calculation, subsequent simulations use two-dimensional models for calculation, and the flow resistance values in these two-dimensional models are consistent with those in the three-dimensional models. Figure 4 b shows the flow rate in a branch when the branch microvalve is opened. This analysis is mainly employed to ensure that the branch microvalve can function as a diversion channel. The simulation results show that when the microvalve is opened, 95% of the flow in the branch can be discharged through the microvalve. Due to the adhesive force and surface tension of the fluid itself, part of the fluid in the branch will always enter the output channel. However, because the amount is very small, it is temporarily ignored here. Figure 4 c shows the mutual interference curve of the flow rate between different branches. During the simulation process, microvalve S 3 is controlled to switch between 0 and 1, and the output flow rate for the flow resistance R in parallel with the S 3 branch is tested. The flow through R directly enters the follow-up branch. The calculation results show that the input flow of the subsequent branch changes with the change in the S 3 state, but this change is only approximately 2%, so the influence of a single branch microvalve on the remaining branches can be ignored. Figure 4 d shows the simulation curve of the input and output characteristics during the working process of the entire system, where the binary sequence of the input port is {S0, S1, S2, S3} = 0000~1111. The simulation results show that the system can achieve 16-level flow regulation. The flow rate of each sequence in order shows a linearly increasing regulation. Figure 5 a shows the experimental device obtained by 3D printing. Although the material itself is of natural colour and low transparency, the three-dimensional channel and microvalve structure are still clearly visible. Figure 5 b shows the flow regulation curve of the device when the input flow is 5000 μL/min. Experiments show that the device basically achieves 16-level flow regulation, but its linearity is lower than the simulation results. Next, we test multiple batches of devices. The linearity error is approximately 5%, indicating that the linearity difference is mainly caused by the inherent error of the manufacturing method. The 3D printing method leads to variations in roughness and microstructure. Much room for improvement remains in terms of consistency. The settling time is an important parameter used to describe the speed of DA conversion, and it can be equivalent to the stabilization time when the control signal is switched. We increase the sampling frequency of the flow signal to 50 Hz and roughly measure this physical quantity through simple waveform analysis. As shown in Figure 5 c, during the different stages of DA conversion, obvious differences are observed in the settling time. For example, the settling time is approximately 250 ms from 0010 to 0011, but the settling time is as long as 750 ms from 0011 to 0100. Figure 5 d shows the settling time for each conversion stage from n-1 to n, where n is the input binary number. The result shows that the settling time of DA conversion is related to the number of microvalve switch state conversions in each stage. For example, only one microvalve is involved in the 0010–0011 process, while two microvalves have their states flipped in the 0011–0100 process. When more microvalves participate in DA conversion, the settling time will be longer. When a certain flow passes through a high flow resistance network, a large pressure difference will be generated at both ends of the flow resistance network. This pressure can be used to drive flexible actuator movement. Figure 5 e shows the movement of a flexible bending actuator driven by the flow regulation. The flow rate at the input end of the device is 5000 μL/min for the working conditions of the flexible manipulator when collecting different binary input signals. As the input binary signal increases, the bending of the flexible manipulator gradually increases."
} | 4,299 |
30519367 | null | s2 | 7,555 | {
"abstract": "Cell-free biocatalysis systems offer many benefits for chemical manufacturing, but their widespread applicability is hindered by high costs associated with enzyme purification, modification, and immobilization on solid substrates, in addition to the cost of the material substrates themselves. Herein, we report a \"bootstrapped\" biocatalysis substrate material that is produced directly in bacterial culture and is derived from biofilm matrix proteins, which self-assemble into a nanofibrous mesh. We demonstrate that this material can simultaneously purify and immobilize multiple enzymes site specifically and directly from crude cell lysates by using a panel of genetically programmed, mutually orthogonal conjugation domains. We further demonstrate the utility of the technique in a bienzymatic stereoselective reduction coupled with a cofactor recycling scheme. The domains allow for several cycles of selective removal and replacement of enzymes under mild conditions to regenerate the catalyst system."
} | 252 |
35266649 | PMC9286555 | pmc | 7,557 | {
"abstract": "Abstract Microbial communities are continuously exposed to unpredictable changes in their environment. To thrive in such dynamic habitats, microorganisms have developed the ability to readily switch phenotypes, resulting in a number of differently adapted subpopulations expressing various traits. In evolutionary biology, a particular case of phenotypic heterogeneity that evolved in an unpredictably changing environment has been defined as bet‐hedging. Bet‐hedging is a risk‐spreading strategy where isogenic populations stochastically (randomly) diversify their phenotypes, often resulting in maladapted individuals that suffer lower reproductive success. This fitness trade‐off in a specific environment may have a selective advantage upon the sudden environmental shift. Thus, a bet‐hedging strategy allows populations to persist in very dynamic habitats, but with a particular fitness cost. In recent years, numerous examples of phenotypic heterogeneity in different microorganisms have been observed, some suggesting bet‐hedging. Here, we highlight the latest reports concerning bet‐hedging phenomena in various microorganisms to show how versatile this strategy is within the microbial realms. This article is categorized under: Infectious Diseases > Molecular and Cellular Physiology",
"conclusion": "5 CONCLUSIONS It has been long acknowledged that microbial populations employ bet‐hedging strategies to persist in very dynamic and unpredictable habitats. In the last decades, due to their high relevance in the food industry (e.g., food spoilage caused by germination of persistent spores) and the medical field (e.g., antibiotic‐resistant persister cells), endospore and persister cell formation have been particularly studied in bacteria (Balaban et al., 2004 ; Lewis, 2007 ; Veening et al., 2005 ). Nonetheless, despite the difficulties in identifying bet‐hedging, recent research studies on phenotypic heterogeneity have provided many promising indications of bet‐hedging strategies employed by a plethora of microorganisms. Current studies have shown that bet‐hedging traits may concern many physiological aspects (Figure 3 ), which provides further evidence of how frequently microorganisms hedge their bets. Yet, more extensive, long‐term evolutionary studies to assess the fitness gains in fluctuating environments are required to confirm the authenticity of bet‐hedging cases described in previous classification reviews (de Jong et al., 2011 ; Grimbergen et al., 2015 ; Simons, 2011 ).",
"introduction": "1 INTRODUCTION In many natural environments, microbial populations are constantly exposed to fluctuations of biotic and abiotic factors. For instance, soil‐inhabiting microorganisms like Bacillus subtilis sense frequent changes of osmolarity caused by interchanging rain and drought periods and accordingly regulate the transport and biosynthesis of osmoprotectants (i.e., proline and glycine betaine) to avoid further cell rupture or desiccation (Bremer & Krämer, 2019 ). Therefore, microorganisms must evolve various adaptation strategies to sense and process environmental information readily and avoid extinction. In a direct response to challenging environmental conditions, microorganisms exploit various gene regulatory networks, such as operons and regulons, to modulate their phenotype and/or behavior (Benson & Haldenwang, 1992 ; Crombach & Hogeweg, 2008 ; Jacob & Monod, 1961 ; Krell et al., 2010 ; Siebring et al., 2012 ). The capacity to adapt by reversibly switching between different phenotypic states, analogously to ON/OFF switches, is known as phenotypic switching (Henderson et al., 1999 ; van der Woude & Bäumler, 2004 ). However, phenotypic switching usually occurs only in a fraction of the population due to the presence of intra‐ and extracellular noise and the topology of regulatory networks involved in the sensing and processing of the environmental signals (i.e., bi‐ or multi‐stable networks; Elowitz et al., 2002 ; Ozbudak et al., 2002 ; Paulsson, 2004 ; Pedraza & van Oudenaarden, 2005 ; Veening, Smits, et al., 2008 ). As a result, a nongenetic differentiation within an isogenic population gives rise to several phenotypically distinct subpopulations. This phenomenon is known as phenotypic heterogeneity, and some of its examples include lactose utilization in Escherichia coli (van Hoek & Hogeweg, 2007 ), cellular differentiation in B. subtilis (Kearns & Losick, 2005 ; Smits et al., 2005 ; Veening, Igoshin, et al., 2008 ; Yüksel et al., 2016 ), flagellin phase variation in Salmonella enterica (Bonifield & Hughes, 2003 ), and the development of stress‐resistant yeast (Bishop et al., 2007 ). Phenotypic heterogeneity may arise from a responsive event to specific environmental cues (responsive switching), but it can also be the result of random changes in gene expression that are independent of the varying environmental conditions (stochastic switching) (Elowitz et al., 2002 ; Kussell, 2005 ; Levine et al., 2013 ). These strategies have different advantages and disadvantages for populations exposed to certain fluctuating environmental conditions (Figure 1 ). Since responsive switching strongly depends on the maintenance and the activation of stress‐specific sensory circuits, it causes an adaptive lag that can be critical for survival when the environment fluctuates (Acar et al., 2008 ; Kaern et al., 2005 ). In unpredictable environments, stochastic switching can be advantageous over responsive switching by generating a variety of maladapted phenotypes (i.e., phenotypes with reduced fitness), which overall increase the long‐term fitness of the population (Ackermann, 2015 ; Kussell, 2005 ; Kussell et al., 2005 ). This particular form of phenotypic heterogeneity, in which the individuals stochastically express maladapted phenotypes, is known as “bet‐hedging.” FIGURE 1 Responsive versus stochastic switching (adapted from Kussell et al., 2005 ). Isogenic cell populations adapt to changing conditions by switching their phenotype, either responsively (upper panel) or stochastically (lower panel). A schematic representation of the switching strategies is shown, in which the color of the fittest individuals matches the color of the environment. In responsive switching, cells change their phenotype when sensing an environmental change to maximize temporal fitness. The population survives if the majority of the individuals successfully commit to the switch. However, when the environment changes in a stochastic manner, the stochastic switching strategy becomes critical for adaptation. Populations that randomly employ stochastic switching, express a number of maladapted phenotypes of reduced fitness that may suit another environment in the future In evolutionary biology, bet‐hedging has been described as a risk‐spreading strategy displayed by isogenic populations that explicitly evolved in fluctuating environments (Gillespie, 1974 ; Kussell, 2005 ; Philippi & Seger, 1989 ). Under such conditions, clonal populations stochastically generate phenotypes with different fitness‐related traits, resulting in individuals suffering lower reproductive success. Because the environmental changes favor different phenotypes at different times, the presence of randomly fit individuals may have a selective advantage when the sudden environmental shifts occur. Populations that employ bet‐hedging minimize the temporal fitness variance of surviving offspring and maximize the long‐term geometric mean fitness across generations (de Jong et al., 2011 ; Grimbergen et al., 2015 ; Kussell et al., 2005 ; Seger, 1987 ; Starrfelt & Kokko, 2012 ). Importantly, this temporal trade‐off between fitness mean and variance does not occur in any other adaptation strategies. One of the most prominent and well‐studied cases of how microbes use a bet‐hedging strategy is the formation of persister cells in different bacteria, including E. coli , S. meliloti , or, in more recently reported studies, Staphylococcus aureus and Caulobacter crescentus (Balaban et al., 2004 ; Huang et al., 2020 ; Keren et al., 2004 ; Kussell et al., 2005 ; Zalis et al., 2019 ). In this mechanism, under antibiotic stress conditions, a part of the initially isogenic population stochastically and reversibly enters into dormancy and becomes resistant to a killing dose of the antibiotics (Figure 2 ). Furthermore, once the antibiotic pressure is relieved, the dormant cells can regrow and repopulate the environment. In this regard, the presence of persister cells becomes highly relevant in common antibiotic treatments (Fisher et al., 2017 ; Lewis, 2007 , 2010 ). FIGURE 2 Schematic representation of persister cell formation in Caulobacter crescentus . It has been proposed that antibiotic persistence in C. crescentus is promoted by HipA1 and HipA2 toxins, which are serine/threonine kinases that phosphorylate the aminoacyl‐tRNA synthetases GltX and TrpS, preventing synthesis of charged tRNAs (Huang et al., 2020 ). Phosphorylation of GltX/TrpS leads to translation arrest and activation of the amino acid starvation‐signaling pathway (SpoT). Activation of SpoT is also stochastically triggered by carbon or nitrogen starvation (indicated by the dashed arrow). Elevated levels of (p)ppGpp, a stringent response alarmone, contribute to translational arrest. Activation of SpoT and further transcriptional changes in the isogenic population of C. crescentus allow most cells to adapt to the starvation conditions, whereas only a fraction of the population becomes dormant (phenotypic heterogeneity). Dormant cells (blue cells) are not metabolically active and can survive high doses of antibiotics. The persister state is reversible; therefore, when the optimal conditions arrive, dormant cells can repopulate the environment (orange cells). The gradient red‐colored bar indicates starvation stress Theoretical studies have shown that the evolution and success of bet‐hedging strategies depend on many factors, including the environment's reliability, that is, the frequency and magnitude of environmental changes (Gaál et al., 2010 ; Kussell, 2005 ); the ability of the population to respond to changes by mutations and rare phenotype selection (King & Masel, 2007 ; Wolf et al., 2005 ); the presence of a suitable environmental cue at the time (King & Masel, 2007 ); and the co‐occurrence of other evolutionary strategies (King & Masel, 2007 ). Considering all these ecological factors, it is very challenging to provide empirical evidence for true bet‐hedging strategies for several reasons. First, bet‐hedging traits evolve in isogenic populations, and since the microbial genomes are subjected to natural genetic modifications or acquired mutations, the genetic composition of the studied population should be considered in the experimental setup. Second, because adaptive changes usually arise after long periods, and the fitness gains must be quantified across several generations, it is necessary to perform long‐term evolutionary experiments under fluctuating growth conditions. Consequently, authors of recent reports have discussed six categories of experimental evidence for bet‐hedging strategies (de Jong et al., 2011 ; Grimbergen et al., 2015 ; Simons, 2011 ). Until now, only a few studies have experimentally demonstrated stochastic phenotypic switching in dynamic environments, including the elegant work of Beaumont et al. ( 2009 ), which provided the evidence for de novo evolution of bet‐hedging traits in Pseudomonas fluorescens under frequently fluctuating conditions (Beaumont et al., 2009 ). Here, selection of phenotypes was achieved by repeatedly imposing the exclusion rule and a population bottleneck. Applying both at the point of environmental shift enabled to maintain diversity in the population by excluding the most common phenotype (the exclusion rule) and to select for a random variant among the surviving cells to minimize the cost of bet‐hedging (a bottleneck). Interestingly, the authors showed that in two out of 12 experimental replicates, surviving genotypes persisted due to stochastic phenotype switching. Furthermore, in one of the switching genotypes, they identified a mutation in the carB gene, encoding for a subunit of carbamoylphosphate synthase involved in pyrimidine and arginine biosynthesis. It is speculated that this mutation caused significant changes in the central metabolism of the evolved population that further translated to molecular noise and promoted stochastic phenotype switching. This experimental example was later revisited by Libby and Rainey ( 2011 ). Here, the authors used mathematical models and simulations to investigate the benefits of stochastic switching in populations of P. fluorescens subjected to the exclusion rule and population bottleneck (Libby & Rainey, 2011 ). Importantly, they observed that switching populations could invade and even replace the nonswitchers despite the high fitness costs and the frequency with which the switching occurred. Besides, the simulations showed that the results are robust to alterations in switching rate, the fidelity of exclusion, bottleneck size, duration of environmental state, and growth rate. Both studies demonstrated that the exclusion rules and bottlenecks can shape the adaptation of populations responding to fluctuating conditions and that experimental studies, reinforced with theoretical models, can be a superior strategy in proving the evolution of bet‐hedging. Nonetheless, much more remains to be discovered, including the mechanisms of stochastic switching, which is the most challenging to follow. This mini‐review discusses the most recent empirical studies where authors claim the role of bet‐hedging in observed phenotypic heterogeneity. Specifically, we focus on describing microbial systems that display a bet‐hedging strategy, but without stressing the six categories of experimental evidence proposed by de Jong et al., 2011 , Grimbergen et al., 2015 and Simons, 2011 . In Figure 3 , we compiled all the examples discussed that fall into diverse microbial lifestyle areas, including signaling, resource use and dormancy. FIGURE 3 Overview of recent studies on phenotypic heterogeneity and possible employment of bet‐hedging strategies in various microorganisms. In this work, we highlight some recent studies regarding bet‐hedging traits that fall into several categories of microbial lifestyle, including signaling (purple), dormancy (yellow), and resource use (blue). In some cases, the same population manifests different bet‐hedging strategies because of direct or indirect relationships between traits. With an asterisk, we marked examples of studies where a population was shown to employ several bet‐hedging strategies, for example, nutrient utilization is directly involved in spore or persisters formation",
"discussion": "4 DISCUSSION AND OUTLOOK 4.1 Does phenotypic heterogeneity always benefit a population? An environment where resources, especially nutrients, are constantly changing is a scenario in which microorganisms can develop different phenotypes to increase their survival chances (Childs et al., 2010 ; van Boxtel et al., 2017 ) (Figure 4 ). Although many studies have demonstrated how phenotypically variable bacterial strains are able to thrive in a niche, showing successful outcomes of using a bet‐hedging strategy, few studies have studied the adverse effects of heterogeneity in bacterial phenotypes (Levy, 2016 ). In this regard, do microorganisms always benefit from displaying heterogeneity? FIGURE 4 Nutrient fluctuations and cell consequences during a bet‐hedging strategy. Bacteria develop phenotypic heterogeneity during changes in environmental conditions (Environment A to B), and a bet‐hedging strategy results in subpopulations of cells with different fitness. While cells with low fitness are subjected to different outcomes (e.g., sporulation), the fitter cells thrive. Eventually, (change to Environment C) the cells display the diversity in phenotypes by a random switch Troselj and Wall ( 2018 ) investigated the population response of the soil bacterium Myxococcus xanthus when a subpopulation of cells are starving (auxotrophic for amino acids; Troselj et al., 2018 ; Troselj & Wall, 2018 ). While no bacterial interaction occurs in a mixed population of prototrophic and auxotrophic cells in rich media, an antagonistic interaction is established in a starvation medium. A toxin produced by the prototrophic cells kills the auxotrophic cells, via the type VI secretion system (T6SS). An analysis of the mechanism underlying this antagonism between sibling cells shows that starving cells have lower amounts of immunity factors than the growing cells. Thus, this observation suggests that growing cells eliminate the less fit cells of the population. Several scenarios have been suggested for the biological implications of this interaction. For instance, it might be that growing cells obtain nutrients from the lysed cells, and therefore, the population becomes fitter without the starving cells, that is, as a homogeneous population. Another possibility is eliminating the nongrowing cells to avoid sporulation, which is a decision at the population level and an energetically expensive process. It would be interesting to explore whether similar antagonistic interactions against the less fit subpopulation are present in some known cases of bet‐hedging strategies by bacteria, where studies have been focused on the exclusive benefits to the subpopulation that is favored under a specific nutritional condition. Changes in nutrients have revealed bet‐hedging and other phenotypic heterogeneity strategies (Gasperotti et al., 2020 ; van Boxtel et al., 2017 ). The importance of this evolutionary adaptation relies on the possibility to persist and thrive in niches where the availability of nutrients fluctuates (Balaban et al., 2004 ; Martín et al., 2019 ; Ratcliff & Denison, 2011 ). Since bacteria live in densely populated environments, and nutrient availability is expected to change, bet‐hedging represents an adaptive evolution strategy that allows bacteria to cope with unstable environmental conditions."
} | 4,557 |
33397907 | PMC7782550 | pmc | 7,558 | {
"abstract": "With the advent of the big data era, applications are more data-centric and energy efficiency issues caused by frequent data interactions, due to the physical separation of memory and computing, will become increasingly severe. Emerging technologies have been proposed to perform analog computing with memory to address the dilemma. Ferroelectric memory has become a promising technology due to field-driven fast switching and non-destructive readout, but endurance and miniaturization are limited. Here, we demonstrate the α-In 2 Se 3 ferroelectric semiconductor channel device that integrates non-volatile memory and neural computation functions. Remarkable performance includes ultra-fast write speed of 40 ns, improved endurance through the internal electric field, flexible adjustment of neural plasticity, ultra-low energy consumption of 234/40 fJ per event for excitation/inhibition, and thermally modulated 94.74% high-precision iris recognition classification simulation. This prototypical demonstration lays the foundation for an integrated memory computing system with high density and energy efficiency.",
"introduction": "Introduction The rise of artificial intelligence has led to explosive growth in emerging data-centric applications represented by images recognition and classification 1 , 2 . Data-intensive tasks require computing systems to perform batch parallel processing, frequently accessing results and interacting from memory domains 3 . The computing and memory components of modern computers are physically separated 4 , and massive communication increases unexpected power consumption and degrades efficiency, causing the so-called von Neumann bottleneck 5 . Emerging memory devices such as memristors 6 , memtransistors 7 , phase change memory 8 , electrical double-layer transistors 9 , two-dimensional (2D) heterojunction devices 10 , and ferroelectric field effect transistors (FeFETs) 11 are used to perform analog computation in an attempt to break out of the dilemma. FeFETs with switchable electric dipoles, fast operation 12 , 13 and non-destructive readout 14 are ideal for building low-power 12 , high-efficiency memory computing integrated systems. However, traditional FeFETs use ferroelectrics as the dielectric layer to modulate channel conductance 14 . The residual polarization decreases with cumulative switching cycles, and ferroelectric fatigue occurs 15 , resulting in memory with limited endurance 16 . In addition, the future trend of high-integration artificial intelligence applications is pushing the design of memory and computing elements toward miniaturization 17 , 18 . Bulk perovskite 19 , oxide 11 , 20 , or organic ferroelectric polymer 21 are served as the gate dielectric in conventional FeFETs, which is insufficient for continuous scaling both in vertical and planar dimensions 22 . 2D layered semiconductors with atomic thickness possess the potential for continuous shrinking 23 – 25 , which is a promising candidate for future high-density memory and computing systems 26 , 27 . Particularly, 2D layered α-In 2 Se 3 exhibits robust ferroelectricity at room temperature (RT) without annealing 14 , 28 , 29 , and thanks to the intrinsic interlocking of dipoles in α-In 2 Se 3 18 , 22 , it can maintain ferroelectric polarization even at atomic scale. Here, distinct from the conventional FeFETs, 2D ferroelectric semiconductor α-In 2 Se 3 was exploited as the channel materials to demonstrate a compact scalable device that integrates non-volatile memory (NVM) and neural computing functions. 2D α-In 2 Se 3 ferroelectric channel transistors (FeCTs) show absorbing performance, including NVM large memory hysteresis windows, long-term retention, enhanced endurance by internal electric field, fast write speed of 40 ns, flexible adjustment of neuroplasticity and ultra-low power consumption of 234/40 fJ per event for excitation/inhibition. Moreover, 2D FeCTs exhibit thermal tunability in both memory and neural computation, and based on FeCTs, a simulated iris recognition and classification with the best accuracy of 94.74% comparable to the software is realized. The elaborate prototype devices pave the way for building high-density, energy-efficient memory and computing fusion systems, providing promising candidates for eliminating the physical separation of memory and computing.",
"discussion": "Discussion To summarize, we have demonstrated the 2D α-In 2 Se 3 based FeCTs that integrate ultrafast nonvolatile memory and neural computing functions, which is completely different from conventional FeFETs. As a NVM with large hysteresis windows and long-term robust retention, in addition, thanks to the effect of the internal electric field, the endurance is optimized, and a nonvolatile switching behavior of 40 ns ultra-fast programming is realized. For neural computing, short- and long-term plasticity modulation is implemented, including amplitude-dependent PSC, SRDP, LTP, and LTD. Remarkably, the ultra-low energy consumption of 234/40 fJ per spike for excitation/inhibition is impressive, making it a promising candidate for future energy-efficient memory computing fusion systems. Furthermore, the 2D FeCTs with NVM and neuromorphic computing exhibit flexible thermal tunability, which is essentially that the thermal temperature modulates the polarization of α-In 2 Se 3 channel ferroelectric, and realizing iris recognition and classification simulation with an accuracy of 94.74% comparable to the software. In brief, 2D α-In 2 Se 3 FeCTs as an alternative, provide a promising perspective on building high-density and energy-efficient emerging applications for memory computation integration."
} | 1,414 |
25575309 | PMC4478700 | pmc | 7,560 | {
"abstract": "Methods developed in geochemical modelling combined with recent advances in molecular microbial ecology provide new opportunities to explore how microbial communities are shaped by their chemical surroundings. Here, we present a framework for analyses of how chemical energy availability shape chemotrophic microbial communities in hydrothermal systems through an investigation of two geochemically different basalt-hosted hydrothermal systems on the Arctic Mid-Ocean Ridge: the Soria Moria Vent field (SMVF) and the Loki's Castle Vent Field (LCVF). Chemical energy landscapes were evaluated through modelling of the Gibbs energy from selected redox reactions under different mixing ratios between seawater and hydrothermal fluids. Our models indicate that the sediment-influenced LCVF has a much higher potential for both anaerobic and aerobic methane oxidation, as well as aerobic ammonium and hydrogen oxidation, than the SMVF. The modelled energy landscapes were used to develop microbial community composition models, which were compared with community compositions in environmental samples inside or on the exterior of hydrothermal chimneys, as assessed by pyrosequencing of partial 16S rRNA genes. We show that modelled microbial communities based solely on thermodynamic considerations can have a high predictive power and provide a framework for analyses of the link between energy availability and microbial community composition.",
"conclusion": "Concluding remarks Although we analysed a limited number of samples and the energy metabolism of some of the detected microbial groups was not always clear, the high degree of consistency between community compositions assessed by 16S rRNA gene sequences and predicted community compositions indicates that energy availability to a large extent shape microbial communities in hydrothermal systems. Our study demonstrates how the combination of modelled and observed communities provides a framework for the generation of hypothesis about abiotic geochemical processes as well as the overall distribution of functional groups of microbial primary producers. Future investigations, including rate measurements and modern omics technology, seem to be a promising path to further elucidate the importance of energy availability in these environments and how different functional groups are energetically connected. It should be realized that hydrothermal systems are excellent natural laboratories for investigations of general ecological principles regarding relationships between energy availability and the distribution of functional groups of organisms in biological communities.",
"introduction": "Introduction How microbial communities are shaped by environmental conditions has been extensively studied during the past decades. Numerous efforts have been made to assess the effect of directly measurable environmental parameters, such as temperature, salinity and concentrations of single chemical species. However, the question of to what extent energy availability determines the structure of chemotrophic microbial communities has received little attention. Nevertheless, as all life forms require an energy source, energy availability must constrain the distribution of functional groups of organisms in any biological community. Marine and terrestrial hydrothermal systems represent in many ways excellent natural laboratories for the exploration of how energy landscapes shape communities of chemotrophic microorganisms. Indeed, energy availabilities from redox reactions have been extensively analysed in deep sea ( McCollom and Shock, 1997 ; McCollom, 2000 , 2007 ; Amend et al. , 2011 ), shallow sea ( Amend et al. , 2003 ; Rogers and Amend, 2005 , 2006 ; Rogers et al. , 2007 ) and terrestrial hot spring environments ( Meyer-Dombard et al. , 2005 ; Spear et al. , 2005 ; Shock et al. , 2010 ). In particular, terrestrial hot springs offer the opportunity to link in situ energy availabilities, derived from in situ chemical analyses, with observed microbial communities. However, it is also evident that attempts to reveal the connections between energy availability and microbial community composition in hot springs are made difficult by the general high number of organisms with unknown metabolic capabilities in these habitats (see for example, Rogers and Amend, 2005 ). Also, phototrophic organisms often dominate under mesophilic to moderately thermophilic conditions in terrestrial hydrothermal systems, complicating the assessment of how microbial communities are shaped by available chemical energy sources under these conditions. In marine hydrothermal systems, hot and reduced hydrothermal fluids (HFs) enriched in potential electron donors (e.g. H 2 S, CH 4 , H 2 ) mix with cold seawater (SW), which is rich in potential electron acceptors (e.g. O 2 , SO 4 2− ). Consequently, chemical metastable disequilibria are formed, which can be used as energy sources by mesophilic to hyperthermophilic chemotrophic primary producers ( Jannasch and Mottl, 1985 ; McCollom and Shock, 1997 ). Fluid mixing may occur in hydrothermal chimney walls, hydrothermal sediments and hydrothermal plumes forming in the water column above the vent fields. Energy landscapes and metabolic rates in these types of habitats have been assessed through modelling based on the chemical endmember composition of HFs and ambient SW ( Tivey, 1995 ; McCollom and Shock, 1997 ; McCollom, 2000 , 2007 ; Shock and Holland, 2004 ; Amend et al. , 2011 ; LaRowe et al. , 2014 ). However, it should be emphasized that a detailed understanding of how energy landscapes shape microbial communities are hampered by the lack of integrated studies that combine models and field observations ( Houghton and Seyfried, 2010 ). Also, although modelled energy landscapes have been used as a framework for general predictions of the distribution of functional groups of microorganisms in hydrothermal systems, models of community composition based on thermodynamic calculations have so far not been established. In this study, we develop such models and assess their predictive power based on Bray–Curtis dissimilarities (BCDs) between modelled and observed communities in two vent fields at the Arctic Mid-Ocean Ridge in the Norwegian-Greenland Sea. In addition, we report for the first time a dominance of the Crenarchaeotal MCG and the anaerobic methanotrophic archaea group (ANME-1) in hydrothermal chimneys under thermophilic conditions.",
"discussion": "Discussion In this study, we developed, for the first time, microbial community composition models that are based on modelled energy landscapes. Through comparisons between observed and modelled communities, we provide evidence that the distribution of functional groups within chemotropic microbial communities is largely determined by chemical energy availability. Our results also indicate that a sedimentary influence in the host rocks can have a large impact on energy landscapes, and hence microbial communities, in hydrothermal systems. Finally, we demonstrate some of the sensitivity of the community composition predictions to assumptions regarding geochemical processes and metabolic capabilities. Energy landscapes ( Figure 4 ) were modelled using a similar approach as in a recent study that compared energy landscapes in hydrothermal systems at different geological settings ( Amend et al. , 2011 ), including the basalt-hosted Endeavour field, which is inferred to be sediment influenced based on elevated methane and ammonium concentrations ( Lilley et al. , 1993 ). However, energy availability from aerobic methane oxidation in the systems investigated by Amend et al. (2011) never exceeded 4 kJ l −1 HF at 1% HF:SW mixing ratios, which is only one-third of the maximum energy availability from this reaction at LCVF ( Figure 4b ). In all of the systems investigated by Amend et al. (2011) , anaerobic methane oxidation was found to be anemic or minimally exergonic at 1 and 10% HF contribution in SW:HF mixtures, which is in sharp contrast to high energy availabilities from this process above 20 °C at LCVF. Amend et al. (2011) did not calculate energy availability from ammonium oxidation, but it should be noted that among all vent fields investigated, the Endeavour field had the highest endmember ammonium concentration (0.503 m M ) ( Seewald et al. , 2003 ; Seyfried et al. , 2003 ), which is only about one-tenth of the concentration observed at LCVF ( Table 1 ). Taken together, this suggests that the sediment-influenced LCVF represents an extremity regarding the energetic potential for hosting anaerobic and aerobic methane oxidizers, as well as aerobic ammonium oxidizers. Sluggish reaction rates of abiotic methane oxidation, sulphide oxidation, iron oxidation and sulphate reduction have been observed under conditions relevant for deep-sea hydrothermal systems ( Kadko et al. , 1990 ; Shock and Holland, 2004 ; Houghton and Seyfried, 2010 ; Foustoukos et al. , 2011 ). Hence, the assumption that modelled energy landscapes reflect relevant energy availabilities for microbial communities seems justified. Remarkably, it was recently argued that energy density (energy availability per volume) is a far better indicator of biomass in sediment cores than the energy available per mole of reaction or per mole of electrons transferred from the electron donor to the electron acceptor ( LaRowe and Amend, 2014 ). This lends confidence to our community composition predictions, which are based on modelled energy densities. The microbial community compositions were predicted under slightly different assumptions: with or without some abiotic sulphide oxidation or letting anaerobic methane oxidizers have or not have the ability to reduced nitrate in addition to sulphate. Under the conditions in the SMVF flange (with an in situ temperature of 72 °C), models not allowing abiotic reactions predict that there is enough oxygen for aerobic organisms to dominate from 0–130 °C ( Figure 5a ). However, the dominance of putative strictly anaerobic methane oxidizers in the flange indicates anaerobic conditions. Furthermore, the absence or very low abundance of putative aerobic organisms in the flange samples indicates that any oxygen removal is not biogenic. Hence, the assumption that oxygen is reduced abiotically seems justified in this case. In line with this, fluids can be expected to flow relatively slowly through the pores in the flange, potentially giving enough time for reducing agents (e.g. sulphide) to react with oxygen, thereby providing conditions that favour the anaerobic methane oxidizers, as predicted by our models ( Figures 5c and e ). Higher flow rates and less abiotic sulphide oxidation could be expected in the chimney wall. Interestingly, the predicted higher abundance of hydrogen and sulphide oxidizers under such conditions ( Figure 5a ) is consistent with the low abundance of ANME and an elevated abundance of putatively microaerobic and thermophilic sulphide oxidizers of the Aquificaceae family in the W1 sample. It was recently shown that some ANME are able to grow by reduction of nitrate to nitrite combined with reverse methanogenesis ( Haroon et al. , 2013 ). We have no strong support for assuming that the ANME detected in the SMVF flange can grow by denitrification, but it is interesting to note that models using this assumption provides the community composition predictions that are mostly consistent with the observed communities ( Figure 8 ). We have not included thermal conduction in our models, which would have had the effect that each temperature would have consistently been associated with a lower SW:HF mixing ratio than in the current models. Hence, as seen in Figure 5 and Figure 8 , assuming heat transfer by thermal conduction in the SMVF flange may have resulted in predictions that are highly consistent with the observed dominance of ANME even when ANME are assumed to be obligate sulphate reducers. Organic compounds (other than methane) are available to organotrophic organisms from primary production, and may also be present in the venting fluids at LCVF and JMVF. Organotrophic organisms were therefore expected to be present in these systems. Indeed, putative organontrophic Bacteroidetes and potentially organotrophic Chloroflexi were present in the ROV3, ROV4 and ROV9 mats with relative abundances of up to 4.2% (Bacteroidetes) and 6.2% (Chloroflexi) ( Supplementary Figure 1 ), suggesting some energy transfer from primary producers to microbial organotrophic consumers in these habitats. Some putative organotrophic and thermophilic Thermotogales and Thermococcales were also detected (<0.7%) ( Supplementary Figure 1 ), indicating that these organisms are important organotrophic consumers in the chimney wall. It could also be that some of the Crenarchaeota or Thaumarchaeota detected in the flange and chimney wall at SMVF ( Figure 6 ) are organotrophs. Some Epsilonproteobacteria may also grow organotrophically (e.g. on formate), which partly could explain the high abundance of Epsilonproteobacteria at LCVF. Yet, a high gene expression of genes involved in hydrogen oxidation, sulfide oxidation and carbon fixation by these Epsilonproteobacteria is suggestive of a lithoautotrophic lifestyle ( Dahle et al. , 2013 ). However, owing to our lack of knowledge regarding organic compounds in the venting fluids and as considering entire food webs was beyond the scope of our study, organotrophic organisms were not included in the community composition models. Hence, the predicted communities should be regarded as predicted distributions of lithoautrotrophic and methanotrophic organisms only. Future studies, more directed towards assessing energy landscapes relevant for organotrophic organisms in combination with analyses of more environmental samples, may clarify the energy flow from autotrophic primary producers to heterotrophic consumers in hydrothermal systems. A detailed investigation of the extent to which energy availability shape microbial communities is difficult without a detailed knowledge about the geochemical processes that influence the energy landscapes and the metabolic capabilities of the organisms using the available energy sources. Nevertheless, our models seem, to a large extent, to correctly predict which functional groups of organisms dominate under different energy landscapes: consistent with the predicted community compositions, putative mesophilic sulphide and hydrogen oxidizers, as well as methane oxidizers, dominate on chimney surfaces at LCVF, whereas ANME dominate in the SMVF flange. This predictive power is further illustrated in Figure 8 , which shows that by only assessing energy landscapes and the distribution of functional groups in our samples, we could have correctly predicted if the samples were associated with low or high SW:HF mixing ratios (or high or low temperatures). This indicates that, at least on a broad level, there is a close connection between energy availability and microbial community composition. The discrepancies between predicted and observed communities are also interesting. In the predicted community composition for LCVF, ammonium oxidizers reached abundances of up to 20% at high SW:HF mixing ratios. Yet, none of the organisms detected in the LCVF samples seem to be affiliated to this metabolic group. Possibly, ammonium oxidizers are outcompeted by organisms using more exergonic redox reactions on the chimney surface, such as methane and sulphide oxidation. Similarly, anaerobic methane oxidizers may outcompete sulphide and hydrogen oxidizers at high temperatures in SMVF. Given the high energy availability from ammonium oxidation at LCVF, elevated abundances of ammonium oxidizers can be expected to be present in the hydrothermal plume forming in the water column above this vent field. Interestingly, elevated ammonium concentrations and ammonium oxidation rates have been observed in other hydrothermal plumes ( Lam et al. , 2008 ) Members of MCG have been detected in a variety of habitats including hot springs, marine sediments and mud volcanoes ( Barns et al. , 1996 ; Parkes et al. , 2005 ; Heijs et al. , 2007 ; Kubo et al. , 2012 ). Typically, ANME have been detected in marine methane seeps or hydrothermal sediments, but have also been inferred to be present in low-temperature exterior parts of flange samples from the Lost City hydrothermal field ( Brazelton et al. , 2006 ). Yet, to our knowledge, this is the first report of the presence of ANME and MCG in flange interiors. Recently, members of ANME were detected in thermophilic enrichments using hydrothermally influenced sediments as inoculum ( Holler et al. , 2011 ), whereas putatively thermophilic ANME were detected in diffuse hydrothermal vent fluids ( Merkel et al. , 2013 ). No direct evidence for the existence of thermophilic MCG have so far been obtained. Based on three observations, we infer that ANME and MCG in the SMVF flange are thermophiles: (i) owing to the high porosity of the lower part of the flange where the samples were taken, it seems unlikely that the in situ temperature at the sampling sites were much different than the in situ temperature measured directly under the flange (>70 °C). (ii) Dominating OTUs within MCG and ANME-1 are close relatives of organisms detected in hydrothermal or thermophilic enrichments. (iii) MCG and ANME co-occurred with members of thermophilic groups such as Aquificacea, Thermodesulfobacteria, Archaeoglobi and the Terrestrial Hot Spring Group ( Figure 5 ; Supplementary Figure 1 )."
} | 4,406 |
29468118 | PMC5779730 | pmc | 7,561 | {
"abstract": "The conversion of biomass-derived sugars and aromatic molecules to cis , cis -muconic acid (referred to hereafter as muconic acid or muconate) has been of recent interest owing to its facile conversion to adipic acid, an important commodity chemical. Metabolic routes to produce muconate from both sugars and many lignin-derived aromatic compounds require the use of a decarboxylase to convert protocatechuate (PCA, 3,4-dihydroxybenzoate) to catechol (1,2-dihydroxybenzene), two central aromatic intermediates in this pathway. Several studies have identified the PCA decarboxylase as a metabolic bottleneck, causing an accumulation of PCA that subsequently reduces muconate production. A recent study showed that activity of the PCA decarboxylase is enhanced by co-expression of two genetically associated proteins, one of which likely produces a flavin-derived cofactor utilized by the decarboxylase. Using entirely genome-integrated gene expression, we have engineered Pseudomonas putida KT2440-derived strains to produce muconate from either aromatic molecules or sugars and demonstrate in both cases that co-expression of these decarboxylase associated proteins reduces PCA accumulation and enhances muconate production relative to strains expressing the PCA decarboxylase alone. In bioreactor experiments, co-expression increased the specific productivity (mg/g cells/h) of muconate from the aromatic lignin monomer p -coumarate by 50% and resulted in a titer of >15 g/L. In strains engineered to produce muconate from glucose, co-expression more than tripled the titer, yield, productivity, and specific productivity, with the best strain producing 4.92±0.48 g/L muconate. This study demonstrates that overcoming the PCA decarboxylase bottleneck can increase muconate yields from biomass-derived sugars and aromatic molecules in industrially relevant strains and cultivation conditions.",
"introduction": "1 Introduction Muconic acid is an intermediate in the β-ketoadipate pathway employed by many microbes for catabolism of aromatic compounds ( Harwood and Parales, 1996 , Ornston and Stanier, 1966 ). There is substantial interest in producing muconic acid from biomass, typically motivated by the ability to efficiently convert muconic acid to adipic acid by catalytic hydrogenation under mild conditions ( Vardon et al., 2015 ). Adipic acid is an industrially important dicarboxylic acid that is a precursor to nylon 6,6, among other polymers. It is conventionally produced by nitric acid oxidation of cyclohexanol and cyclohexanone, releasing nitrous acid. With a market volume of 2.6 million tons per year, adipic acid production contributes substantially to the nitrous acid-mediated generation of ozone-producing free radicals, thus prompting substantial efforts to produce it from renewable resources ( Deng et al., 2016 , Polen et al., 2013 , Van de Vyver and Román-Leshkov, 2013 ). Recently, it has been shown that trans,trans -muconic acid can be converted catalytically to diethyl terephthalate, another important commodity polymer precursor ( Lu et al., 2015 ). Muconic acid can be produced biologically by dioxygenase enzymes that catalyze intradiol ring-cleavage of catechol, a central intermediate in one branch of the β-ketoadipate pathway ( Fig. 1 ) ( Xie et al., 2014 ). However, many aromatic molecules derived from the depolymerization of lignin, which accounts for 15–30% of the dry weight of biomass, are metabolized through a parallel branch of the β-ketoadipate pathway in which protocatechuate (PCA), rather than catechol, serves as the central intermediate. Employing a PCA decarboxylase, which converts PCA to catechol, has enabled the production of muconate from lignin monomers such as p -coumarate, ferulate, 4-hydroxybenzoate, and vanillate ( Vardon et al., 2015 ) as well as from glucose via a 3-dehydroshkimate (3-DHS) dehydratase that converts this intermediate in the shikimate pathway for aromatic amino acid biosynthesis to PCA ( Curran et al., 2013 , Draths and Frost, 1994 , Jung et al., 2015 , Niu et al., 2002 , Weber et al., 2012 ). An accumulation of PCA has been observed in strains engineered to produce muconate from aromatic molecules and sugars ( Curran et al., 2013 , Sonoki et al., 2014 , Weber et al., 2012 ) and is an indication of insufficient PCA decarboxylase activity. The accumulation of intermediates not only reduces the yield and productivity of the engineered biocatalyst, but even trace amounts of residual aromatic compounds can significantly affect the separation of muconate from fermentation broth ( Vardon et al., 2016 ). Fig. 1 Metabolic pathways for production of muconate from glucose and lignin-derived aromatic compounds. In P. putida KT2440, glucose is metabolized through the Entner-Doudoroff (ED) and pentose phosphate (PP) pathways to produce phosphoenolpyruvate (PEP) and erythrose 4-phosphate (E4P), which can be condensed to enter the shikimate pathway for aromatic amino acid biosynthesis. An intermediate in the shikimate pathway, 3-dehydroshikimate, can be converted to PCA by the action of a 3-DHS dehydratase, such as AsbF from Bacillus cereus used here. Deletion of the genes encoding the PCA dioxygenase, PcaHG, and integration of genes encoding the PCA decarboxylase AroY from Enterobacter cloacae and two associated proteins, EcdB and EcdD, from enables PCA to be converted to catechol rather than entering the β-ketoadipate pathway. Two paralogous dioxygenases, CatA and CatA2, convert catechol to muconate, which accumulates due to deletion of the genes encoding CatB and CatC, two enzymes required for further metabolism of muconate. Lignin-derived aromatic molecules are metabolized through upper pathways to form catechol in the case of phenol or guaiacol while p -coumarate, ferulate, 4-hydroxybenzoate, and vanillate are metabolized to form PCA, which can then be converted to catechol by the action of the PCA decarboxylase for subsequent conversion to muconate. Fig. 1. Sonoki et al. recently described a means of increasing activity of the PCA decarboxylase that may enable those pursuing strategies to produce muconate via PCA to overcome this bottleneck ( Sonoki et al., 2014 ). Most genes encoding decarboxylases in the hydroxyarylic acid decarboxylase family that includes the PCA decarboxylase, AroY, are co-expressed as an operon with two other small genes shown to be important to activity of the decarboxylase ( Lupa et al., 2005 , Lupa et al., 2008 , Matsui et al., 2006 ). These three genes, BCD , are typically clustered in an operon and named for the organism in which they are found (i.e. Klebsiella pneumoniae decarboxylase: kpdB , kpdC , and kpdD ) with the C gene encoding the decarboxylase. While AroY from Klebsiella pneumoniae exhibits activity when expressed alone in Escherichia coli , Sonoki et al. hypothesized that co-expression of KpdB and/or KpdD, might enhance activity of AroY ( Sonoki et al., 2014 ). Weber and colleagues had previously co-expressed KpdB and KpdD with AroY, but did not compare the PCA decarboxylase activity they achieved with the activity of AroY expressed alone so as to be able to interpret the importance of KpdB and KpdD co-expression ( Weber et al., 2012 ). Sonoki and colleagues found that, in an Escherichia coli host, plasmid-based co-expression of KpdB and, in some cases KpdD, enhanced PCA decarboxylase activity relative to expression of AroY alone, essentially eliminating this bottleneck and enhancing production of muconate from vanillin, a lignin-monomer model compound ( Sonoki et al., 2014 ). While the function of B and D proteins were previously unknown, it was recently discovered that homologues of the B protein, UbiX from E. coli and PAD1 from Saccharomyces cerevisiae , synthesize a novel, prenylated flavin cofactor required for the activity of decarboxylases homologous to the hydroxyarylic acid decarboxylases ( Lin et al., 2015 , Payne et al., 2015 , White et al., 2015 ). It is likely, then, that KpdB also produces this cofactor, which is required for the decarboxylase activity of AroY. We previously reported the production of muconate from model lignin monomers as well as alkaline pretreated corn stover by an engineered P. putida KT2440 strain ( Vardon et al., 2015 ). This strain utilized the AroY PCA decarboxylase from Enterobacter cloacae , which enabled muconate production but also exhibited a substantial accumulation of PCA, similar to that observed by others as described above. In the present study, we sought to apply co-expression of the decarboxylase-associated proteins examined by Sonoki et al. to our system, aiming to improve muconate production. Using genome-integrated gene expression in P. putida KT2440-based strains, we demonstrate that co-expression of these proteins reduces PCA accumulation and enhances muconate production from the lignin monomer p -coumarate in both shake flask experiments and fed-batch bioreactor studies. Further, we demonstrate a three-fold improvement in muconate yields from glucose upon co-expression of these proteins. Together, these results suggest that the co-expression of these proteins enhances PCA decarboxylase activity and could enable industrial-scale, biological production of muconic acid from both the lignin and carbohydrate fractions of biomass.",
"discussion": "4 Discussion and conclusions In this study, we have clearly demonstrated that co-expression of EcdB and EcdD reduces the accumulation of PCA in P. putida KT2440-based strains engineered using genome-integrated gene expression to produce muconate from aromatic molecules in shake flask (Fig. 2) and bioreactor (Fig. 3) cultivations. In addition to the obvious effect upon product yields, reducing the accumulation of an aromatic intermediate such as protocatechuate could substantially reduce costs associated with separation of the final product by reducing the required loading of activated carbon for removal of residual aromatic compounds ( Vardon et al., 2016 ). We have also demonstrated that expression of EcdB increased muconate production by about 3-fold in strains engineered to produce muconate from glucose, both in shake flask (Fig. 4) and bioreactor experiments (Fig. 5). The maximum titer (4.92±0.48 g/L) and yield (0.077±0.005 mol/mol) of muconate from glucose reported here (Table 2) are nearly an order of magnitude higher than those described in yeast-based systems ( Curran et al., 2013 , Weber et al., 2012 ), but considerably lower than those reported in E. coli host systems ( Draths and Frost, 1994 , Niu et al., 2002 ). All of these previously described systems, however, relied on plasmid-based gene expression and, in most cases, the introduction of mutations that required cultures to be supplemented with aromatic amino acids, both of which are generally inconsistent with at-scale production processes. As such, it is important to note that the P. putida KT2440-based strains described here represent the only reported system for production of muconate from glucose by strains engineered using entirely genome-integrated gene expression, without the requirement of costly amino acid supplementation. Additional metabolic engineering to increase the flux of carbon to muconate will undoubtedly be of benefit to the “base case” strains described here and will be necessary to achieve industrially-relevant levels of production; this work is ongoing in our laboratory currently. In shake flask experiments, co-expression of EcdB or EcdB and EcdD also had the unexpected benefit of increasing the rate of catabolism of p -coumarate ( Fig. 2 B and 2C vs. 2A), though this ultimately resulted in greater accumulation of 4-hydroxybenzoate. Based on the data from these shake flask experiments, the accumulation of 4-hydroxybenzoate appears to represent a substantial bottleneck in the pathway to muconate. In the corresponding bioreactor experiments ( Fig. 3 ), however, a substantial accumulation of 4-hydroxybenzoate was not observed. Conversely, however, these bioreactor cultures exhibited lower growth rates once feeding of p -coumarate was initiated relative to the strain expressing AroY alone ( Fig. 3 B and 3C vs. 3A), which were not observed in shake flask experiments. This might be associated with the increased accumulation of muconate, which could be inhibitory. Further experiments will be required to determine if this can be overcome with additional optimization of bioreactor conditions or the strains themselves. The differences in performance of these strains under different growth conditions underscores the importance of evaluating strains in the controlled environment of a bioreactor. Efforts to understand the mechanism whereby the expression of EcdB modulates the activity of the AroY PCA decarboxylase may be informed by an examination of the function of its homologues. Decarboxylases in the hydroxyarylic acid decarboxylase family, which includes AroY and the C proteins discussed in the introduction, are homologous to UbiD, a bacterial 3-octaprenyl-4-hydroxy-benzoate decarboxylase required for biosynthesis of ubiquinone (coenzyme Q), and the ferulic acid decarboxylase (FDC) from Saccharomyces cerevisiae ( Lupa et al., 2005 , White et al., 2015 ). The B genes usually co-expressed with the decarboxylase C genes are homologous to the bacterial ubiX and yeast PAD1 genes that were recently shown to encode a flavin prenyltransferase responsible for producing a prenylated-FMN cofactor required by UbiD and FDC ( Lin et al., 2015 , Payne et al., 2015 , White et al., 2015 ). It is likely, then, that the B proteins produce the same specialized cofactor that is utilized by the C decarboxylases as well as AroY. This would explain why AroY is active when expressed without the B protein in E. coli , in which the prenylated-FMN is already produced by UbiX, or S. cerevisiae ( Curran et al., 2013 ), where it is produced by PAD1. PCA decarboxylase activity is enhanced by co-expression of the B protein in E. coli ( Sonoki et al., 2014 ), probably by increasing production of prenylated-FMN beyond what is synthesized by the native UbiX alone, which is apparently insufficient to also support full activity of the heterologously expressed AroY. This likely also applies to expression of AroY in P. putida KT2440, which also natively expresses a UbiX homologue (PP_0548, Genbank: NP_742711.1). The role of the D protein, which shows no homology to any proteins characterized to date, remains elusive. We have shown that co-expression of ecdD with ecdB and aroY provides a slight, but consistent reduction in accumulated PCA and improvement in muconate production relative to expression of only ecdB and aroY in strains engineered to produce muconate from aromatic lignin monomers ( Fig. 2 , Fig. 3 , Table 1 .). However, in strains engineered to produce muconate from glucose by the incorporation of the DHS dehydratase, AsbF, its expression attenuates muconate production below that observed by expression of AroY alone ( Fig. 4 , Fig. 5 , Table 2 ). Sonoki and colleagues observed similarly inconsistent results with expression of kpdD in their E. coli host; when aroY was expressed on one plasmid and kpdB and kpdD were expressed on a second plasmid, it resulted in greater PCA decarboxylase activity than when the second plasmid expressed only kpdB . When all of these genes were expressed on a single plasmid, however, the addition of kpdD reduced decarboxylase activity relative to the plasmid expressing only aroY and kpdB ( Sonoki et al., 2014 ). Taken together, these results suggest that the effect of the D protein on the PCA decarboxylase activity of AroY and the B protein is highly context dependent. While in the study by Sonoki et al., differing effects were seen in cases where kpdD may have been expressed at very different levels relative to aroY , our P. putida KT2440-derived strains KT2440-CJ184 and KT2400-CJ202 only differ in that the asbF gene was incorporated in the synthetic operon integrated into the genome of KT2440-CJ202 (Ptac: aroY : ecdB : ecdD : asbF ), in which the activity of the PCA decarboxylase was attenuated by co-expression of EcdD, but not in that of KT2440-CJ184 (Ptac: aroY : ecdB : ecdD ), in which EcdD co-expression enhanced its activity. We believe it is unlikely that the asbF gene, which was incorporated at the 5′ end of the operon, would affect expression of ecdD upstream of it, but it is still formally possible that expression of ecdD is affected by the addition of asbF . It is also formally possible that AsbF and EcdD interact in a way that affects the function of EcdD. Because the benefit of co-expressing the D gene on PCA decarboxylase activity is negligible at best and has the potential to be deleterious based on our findings and those of Sonoki and colleagues, it is tempting, and even advisable, to forgo its inclusion in metabolic engineering strategies that incorporate the PCA decarboxylase. Its evolutionary conservation, coupled with our findings and those of Sonoki et al. ( Sonoki et al., 2014 ) demonstrating that it can enhance PCA decarboxylase in certain circumstances, may justify greater examination of this protein. The PCA decarboxylase itself is certainly worthy of further investigation. While molecules such as 4-hydroxybenzoate and vanillate, which are generated by relatively mild lignin depolymerization methods ( Linger et al., 2014 , Salvachúa et al., 2015 ) are metabolized through PCA, their decarboxylated counterparts, phenol and guaiacol, less substituted products arising from harsher lignin depolymerization methods ( Katahira et al., 2016 , Kruger et al., 2016 ), are metabolized through catechol. Decarboxylases capable of catalyzing these reactions have been characterized and demonstrated to, technically if not efficiently, catalyze the reverse reaction (carboxylation) as well ( Chow et al., 1999 , Lupa et al., 2008 , Lupa et al., 2005 ), as has the PCA decarboxylase ( He and Wiegel, 1996 ; Yoshida at al., 2010 ). Thus, AroY and these other hydroxyarylic acid decarboxylases can essentially bridge the PCA and catechol branches of the β-ketoadipate pathway as well as the upper pathways that funnel into them, a capability that is likely to become important as interest grows in metabolic engineering aimed at lignin valorization ( Beckham et al., 2016 )."
} | 4,606 |
33184305 | PMC7665202 | pmc | 7,563 | {
"abstract": "Microorganisms that display unique biotechnological characteristics are usually selected for industrial applications. Bacillus cereus NWUAB01 was isolated from a mining soil and its heavy metal resistance was determined on Luria–Bertani agar. The biosurfactant production was determined by screening methods such as drop collapse, emulsification and surface tension measurement. The biosurfactant produced was evaluated for metal removal (100 mg/L of each metal) from contaminated soil. The genome of the organism was sequenced using Illumina Miseq platform. Strain NWUAB01 tolerated 200 mg/L of Cd and Cr, and was also tolerant to 1000 mg/L of Pb. The biosurfactant was characterised as a lipopeptide with a metal-complexing property. The biosurfactant had a surface tension of 39.5 mN/m with metal removal efficiency of 69%, 54% and 43% for Pb, Cd and Cr respectively. The genome revealed genes responsible for metal transport/resistance and biosynthetic gene clusters involved in the synthesis of various secondary metabolites. Putative genes for transport/resistance to cadmium, chromium, copper, arsenic, lead and zinc were present in the genome. Genes responsible for biopolymer synthesis were also present in the genome. This study highlights biosurfactant production and heavy metal removal of strain NWUAB01 that can be harnessed for biotechnological applications.",
"introduction": "Introduction Industrialisation and mining activities have continued to put an increasing burden on the environment as a result of metal pollution 1 . The unrestrained release of metals into the environment from these activities poses a threat to the ecosystem and health of living organisms. Mining industries, fertilizer and pesticide production release cadmium into the environment 2 . Mining, electroplating, paints and pigments, batteries, tanning and textile industries release chromium and lead into the environment 2 – 4 . Heavy metals have been known to cause various diseases and ailments in humans, for example, cadmium causes bone disease, headache, hypertension, kidney diseases, lung and prostate cancer 2 , 3 , 5 . Chromium causes chronic bronchitis, skin irritation, liver diseases, renal failure and lung cancer 4 , 6 while lead causes chronic nephropathy insomnia, learning disorder, renal damage, reduced fertility and is a risk factor for Alzheimer’s disease 2 , 5 , 7 . Conventional methods of heavy metal removal involve treatment with chelating agents, organic and inorganic acids, reverse osmosis, surfactants and water. However, these techniques are often expensive and ineffective for low metal concentration removal 1 , 5 . Other challenges often encountered with the use of these conventional techniques include non-specificity of these methods, space requirements, impractical nature of some techniques and high energy demand 1 , 8 . Thus, there is the need for bioremediation using microorganisms with potential for remediation of polluted environments and production of eco-friendly secondary metabolites 9 . Bioremediation of heavy metals offers an alternative and effective means of decontaminating metal-polluted environments. Heavy metal remediation of contaminated environment mediated by microorganisms is efficient and cost effective 8 . Microorganisms have developed various mechanisms for detoxifying heavy metals. These mechanisms include biosorption, biotransformation, bioaccumulation, and biomineralisation 10 . These organisms also secrete a range of metal-sequestering polymers that are employed in metal uptake 11 , 12 . These biopolymers also trap and absorb metal sulphides and oxides 12 . The use of microbial biopolymers to enhance metal removal effectiveness is emerging as a promising technique. Similarly, these polymers can survive different pH and temperature range 13 . Their metal-binding capability depends on the producing organism, functional groups on the biopolymer, metal affinity and specificity, temperature and pH 13 – 15 . They are eco-friendly, versatile and economic compared to chemical polymers. One of the numerous polymers of microbial origin is biosurfactant, with various applications in detergents, cosmetics, medicine, food industries, petroleum and bioremediation 16 . There have been various reports in literature on the metal-complexing abilities of biosurfactants in removing heavy metals from polluted soil and wastewaters 15 , 17 – 19 . They solubilise metal ions through increased wettability and reduced surface tension, thereby bringing metal ions out of the soil matrix 17 . Biosurfactants of microbial origin are good metal-complexing agents due to their stability, degradability, low toxicity and environmental compatibility 20 . They form stable complexes with metal ions as a result of electrostatic interaction between charged polymers 18 . With advances in genome sequencing, different microbial products have gained increasing attention through elucidation and prediction of biosynthetic genes. In this study, we present the genome sequence of Bacillus cereus NWUAB01 and its underlying genetic information associated with pollutants’ degradation and resistance. In addition, based on the nature of biosurfactants and their several applications in reclamation of polluted sites, their application in the removal of cadmium, chromium and lead, which have been listed among toxic elements within the first twenty pollutants priority list that are of significance to public health 21 was also investigated.",
"discussion": "Discussion Soils polluted with heavy metals are usually sources of organisms resistant to metals 23 , 24 . Mining soils are rich sources of potential bacterial population resistant to heavy metals, but with reduced bacterial diversity, population size and metabolic activities 25 . Metal resistance might have evolved due to the presence of heavy metals in their growth medium 26 . In this study, soil samples from a gold-mining environment, with natural occurrence of heavy metals, were used for isolating strain NWUAB01, which is consistent with the studies of Oladipo et al. 27 and Reith et al. 28 that isolated B. cereus from gold mining soil. Thus, the metal-containing environment might have led to the evolvement of mechanisms of resistance to heavy metals in the organism. Elevated level of tolerance to metals is an important criterion for metal removal by bacterial strains 23 and strain NWUAB01 showed multiple tolerance to the metals tested and good preliminary metal removal properties, with the ability to grow on all concentrations of Pb tested and on 200 mg/L of Cd and Cr. The organisms showed the ability to withstand varying metal concentrations as reported in different studies 29 , 30 from different polluted sites and higher tolerance compared to those observed by Oladipo et al. 27 . Varied responses of strain NWUAB01 to different metal ions observed in this study could be attributed to different modes of action, unique chemistry and level of toxicity of each metal 27 , 31 . Multi-metal resistance by microbial strains gives mutual benefits to the single component and is suitable for metal removal 32 . Multi-metal resistance shows various combinations of genetic determinants for metal resistance. This could have probably evolved in the natural environment of the organism. The genetic determinants encode specific metal transport proteins involved in the sequestration of metal ions and regulating active efflux 33 . The resistance pattern of strain NWUAB01 to the tested metals showed that the organism tolerated Pb than Cd and Cr. Many reports have also reported many bacteria with multi-metal resistance abilities 23 , 34 , 35 . Multi-metal tolerance in Bacillus species has been well documented. Various mechanisms are employed by microbial cells for metal removal 10 . These include bioaccumulation, biomineralisation, biosorption and biotransformation. The growth kinetics of the organism on different metal revealed that the OD increases with time for all metals and control. The growth rate of strain NWUAB01 on exposure to metal-enriched medium varied with each tested metal. The growth rate was enhanced in the presence of Pb, while there was a reduced growth rate in the presence of Cr. The same pattern of growth rate was observed for Cd and the control. Similarly, the generation time in Pb-medium was lower than that of Cd, Cr and the control. This shows that the doubling time was faster in Pb-medium, which also has a higher number of generations, compared to Cr, Cd and the control. This is an indication that Cd and Cr toxicity to strain NWUAB01 may be dose-dependent 27 . Increased generation time is usually observed for environmental constraint. However, generation time depends on all factors influencing growth, thus growth rate can vary considerably between the different experimental setups. A decrease in the OD of strain NWUAB01 was observed in the presence of heavy metals compared with the metal-free medium. This is similar to the pattern observed by Shim et al. 30 and Raja et al. 36 . The decrease in the growth of B. cereus in the presence of heavy metals might be due to the metal ion interaction with the cell membrane, which increases metal-binding sites and makes it less effective for the transport of materials essential for growth 37 . To understand the mechanism of resistance to metals, growth kinetics is used as an index of adaptation to external constraints 27 . The inverse growth rate relationship observed between metal concentrations and growth rate in tolerant bacteria are characteristics of bacterial growth in response to external stress 38 . The low inhibitory values obtained for Cd and Cr along with a decrease in growth rate in the presence of these metals could be attributed to the decline in efficiency of substrate utilisation as a result of high energy cost of the organism subjected to metal stress 39 . The presence of extracellular substances, which serve as a barrier in Gram-positive bacteria enhances metal resistance compared to Gram-negative organisms 40 . A direct comparison of metal resistance by strain NWUAB01 with other studies is difficult due to the composition and strength of the medium, the nature of the medium that influences metal bioavailability, complexation, organic constituents, diffusion rate and incubation period, which cause variations in inhibitory concentrations 30 , 41 . Genes encoding metal resistance can eliminate or reduce metal toxicity 42 . Hence, strain NWUAB01 was screened for metal-resistant genes. The amplification of primer-specific heavy metal-resistant genes of chromosomal DNA of strain NWUAB01 yielded amplicons of the expected band size for cadA, CzcD, and PbrA . cadA , which is a P-type ATPase, was also found to be present on the organism. cadA is cadmium-specific ATPase used for Cd efflux and confers metal resistance to strain NWUAB01. CzcD is responsible for the efflux of cobalt, zinc and cadmium. Both CzcD and cadA operons are energy-dependent efflux systems that confer cadmium resistance 43 . The efflux systems are actively involved in the pumping out of toxic metal ions that enter the cell through ATPase diffusion. PbrA is the protein responsible for lead uptake and down-regulation of the metal concentration, which occurs in response to high levels of lead 44 . It thus revealed that isolate NWUAB01 has a functional gene that is key in lead resistance. PbrA is an active efflux pump protein that transports Pb ions against the concentration gradient using energy provided by ATP hydrolysis 42 . Metal transport proteins are involved in transporting metal ions outside the cell membrane 45 . These metal transporting proteins are a group of PIB-type ATPases, which governs metal resistance. cadA, CzcD and PbrA belong to these groups of proteins present in strain NWUAB01 which are involved in metal resistance. These proteins prevent metal accumulation of highly reactive and toxic metals within the cell membrane and play a key role in metal resistance by strain NWUAB01 45 . No amplification was observed for CzcA, CzcB, PbrT, chrA , and chrB . This might be as a result of the lack of mechanisms responsible for metal resistance in the genetic system of the organism. The organism may also use other mechanisms different from the efflux system for metal tolerance. However, heavy metal resistance/transport genes are abundant in the genome of B. cereus NWUAB01, which include several resistance genes encoding arsenic, cadmium, copper, cobalt and zinc as well as transport genes for chromium, cadmium, lead, magnesium and mercury. The abundant metal-resistant genes in the genome of strain NWUAB01 suggest that the organism can tolerate different metals, which is consistent with a previous report demonstrating the uptake and heavy metal resistance in B. cereus 28 . The organism uses different genome-mediated resistance mechanisms such as the transport proteins and efflux pump to survive heavy metal stress. The genome also revealed genes involved in the degradation and metabolism of xenobiotic compounds. The production of different biosynthetic gene clusters and metabolism of different compounds are adaptive mechanisms for surviving diverse ecological niches 9 , which can be harnessed for different environmental and industrial purposes. The synthesis of biopolymers in bacteria occurs through four pathways namely: ATP-binding cassette transporter-dependent, extracellular synthesis using sucrase protein, Wzx/Wzy-dependent, and synthase-dependent pathways 46 , 47 . Bacteria using the Wzx/Wzy dependent pathway carry the flippase (Wzx) and polymerase (Wzy) gene in their extracellular polysaccharide operons 47 . The presence of the Wzx (O-antigen flippase) and Wzy (oligosaccharide repeat unit polymerase) gene in the genome of strain NWUAB01 signified the production of extracellular polymer using the Wzx/Wzy-dependent pathway. This pathway produced polymers of various sugar components that results in heteropolysaccharide production 47 . Blood agar has been used to quantify and screen for biosurfactant production by bacteria 48 , 49 . Carrillo et al. 50 and Kumar et al. 49 found an association between the surfactant production and haemolytic activity, and recommend blood lysis as screening method for the biosurfactant production. Although the lysis of erythrocytes could exclude some biosurfactant producing organisms, it has helped in initial screening of biosurfactant producing organisms. Strain NWUAB01 showed complete haemolysis on erythrocytes and was used as the initial screening test for its selection. The reduction in surface tension of water has been reported in several studies 49 , 51 , 52 for various biosurfactant producing Bacillus species. The reduction in surface tension confirmed the production of biosurfactant by strain NWUAB01. The ability to reduce the surface tension of water from 72 to 35 mN/m has been considered as a characteristic of a good surfactant 18 . Strain NWUAB01 has a surface tension that is similar to that produced by B. cereus NK1, which has a value of 38 mN/m 51 . It has a better surface tension than B. cereus , B. sphaericus and B. fusiformis , with surface tension of 50, 55.2 and 56.4 mN/m respectively 53 , and B. amyloliquefaciens and B. thuringiensis with surface tension of 57.7 m/Nm each 54 . Strain NWUAB01 has lower surface tension potential compared to Bacillus sp reported by Heryani and Putra 55 , that had a value of 27.1 mN/m. The differences in the surface tension values can be attributed to different production medium, conditions of growth and uniqueness of individual organisms. The emulsification index is another criterion used in the selection of surface-active-producing bacterial isolates. Satpute et al. 56 suggested that more than one screening method should be used in the primary screening of potential surface-active agents. Strain NWUAB01 produced stable emulsions with various hydrocarbons and vegetable oil. This appreciable emulsifying property made the organism a suitable surface-active agent. The ability of biosurfactant to emulsify different hydrocarbons and vegetable oil had been reported for Bacillus species with different results. Sriram et al. 51 reported B. cereus NK1 to emulsify motor oil, diesel oil, crude oil, petrol and vegetable oil with E 24 of 80.36%, 55.5%, 70%, 44% and 50.47% respectively. Strain NWUAB01 had lower emulsification index compared to what was reported for B. cereus NK1. Likewise, Barakat et al. 54 reported emulsification index of 60% and 69% with paraffin oil for B. amyloliquefaciens and B. thuringiensis respectively. This might be as a result of the different components of the production medium and different carbon sources used for producing biosurfactant 57 . The production of biopolymers that confer resistance to microorganism growing in polluted environments is an important defence mechanism against environmental stress and for survival 20 . Biosurfactants are applied in several fields and their application depends on their stability at different temperatures and pH 58 . Reduction in the stability of the emulsion was observed at the extreme temperature and pH. As the pH increases, there was an increase in the stability of the emulsion until pH 7, after which the stability begins to reduce. The result indicated that an increase in pH had a positive effect on the stability of the emulsion. This could be as a result of the precipitation of biosurfactant at high pH values 58 . Lower stability at reduced pH (< 4) can be attributed to distortion of the biosurfactant structure and precipitation 59 . The FTIR characterisation of the biosurfactant produced by strain NWUAB01 suggested that the surfactant produced by strain NWUAB01 contained peptide-like moieties, which is typical of lipopeptide surfactants produced by Bacillus species described in literature 51 , 57 , 60 . The MALDI-TOF spectra of the detected groups could be attributed to the iturin variants as described by Jasim et al. 61 and Cho et al. 62 . The lack of specific iturin homologs can be attributed to the loss of some of the amino acids such as asparagine, glycine and tyrosine in the structure of iturin, which makes many homologs of the lipopeptide difficult to identify 63 . The composition of the medium of production of lipopeptides can be attributed to some of the variations in the structure 64 . This showed that different compounds could be expressed by Bacillus species during changes in growth condition 63 . Biosurfactant soil washing has been used for metal removal from polluted soils and sediments due to their biodegradability, low toxicity and eco-friendly nature 18 , 65 . In this study, we evaluated the metal removal capability of biosurfactant produced by strain NWUAB01. We found that the biosurfactant produced by strain NWUAB01 is efficient in removing metal from contaminated soil. In a multi-metal system, the percentage removal of each metal decreases compared to a single metal system. The ability of the biosurfactant to remove metals from contaminated soil was also examined in comparison with strain NWUAB01. We observed that the percentage metal removal was higher for the organism than the surfactant. The results of this study showed that Pb has the highest percentage removal followed by Cd and Cr. This could be due to the affinity of the biosurfactant to different metals 66 , 67 . The efficiency of metal removal by biosurfactants also depends on the type of biosurfactant and its concentration, soil characteristics and other additives such as acids and bases that may be added 67 . Metal removal efficiency of strain NWUAB01 biosurfactant is higher than those reported by Singh and Cameotra 65 . However, the metal removal efficiency of lipopeptide of marine origin reported by Das et al. 1 was higher than that of strain NWUAB01. The metal removal potential of strain NWUAB01 corroborated the work of Mulligan et al. 68 , who reported the use of lipopeptide from B. subtilis for the removal of Cd, Cu and Zn. Lipopeptides, which are anionic in nature, have better metal sequestration properties and are more effective in metal removal 18 . Removal of metals by biosurfactant has been proposed to occur by surfactant sorption to the soil surface, followed by complexation with metals; thus leading to metal detachment from soil surface by the reduction in the interfacial tension 18 . In conclusion, the findings in this study showed that strain NWUAB01 is metabolically versatile with high heavy metal affinity that can be harnessed for industrial applications. The presence of diverse metal transport/resistant genes and xenobiotic compounds degradation revealed the ability to survive in varied ecological niches. This study also demonstrated the potential of the biosurfactant produced by strain NWUAB01 for effective removal and recovery of heavy metals for environmental applications."
} | 5,245 |
22004563 | PMC3214846 | pmc | 7,565 | {
"abstract": "Background Poly-3-hydroxybutyrate (PHB) is a polyester with thermoplastic properties that is naturally occurring and produced by such bacteria as Ralstonia eutropha H16 and Bacillus megaterium . In contrast to currently utilized plastics and most synthetic polymers, PHB is biodegradable, and its production is not dependent on fossil resources making this bioplastic interesting for various industrial applications. Results In this study, we report on introducing the bacterial PHB pathway of R. eutropha H16 into the diatom Phaeodactylum tricornutum , thereby demonstrating for the first time that PHB production is feasible in a microalgal system. Expression of the bacterial enzymes was sufficient to result in PHB levels of up to 10.6% of algal dry weight. The bioplastic accumulated in granule-like structures in the cytosol of the cells, as shown by light and electron microscopy. Conclusions Our studies demonstrate the great potential of microalgae like the diatom P. tricornutum to serve as solar-powered expression factories and reveal great advantages compared to plant based production systems.",
"conclusion": "Conclusions Altogether, this study has demonstrated that microalgae like the diatom P. tricornutum have a great potential not only as biosynthetic factory for recombinant proteins but also as photosynthetically fueled bioreactors for synthesizing biotechnologically relevant polymers like PHB. Even though no enzyme engineering, no adaptations to P. tricornutum specific codon-usage, and no large-scale screening have been applied in these initial analyses, relatively high PHB levels of up to 10.6% of algal dry weight have been obtained. Thus, in the future, there will be a focus on various targets for enhancing PHB biosynthesis in P. tricornutum . Other subcellular compartments such as the plastids might yet be interesting sites for PHB synthesis. Diatoms are naturally rich in lipids and silicate and already have applications in biotechnology [ 17 ]. Hence, inserting and/or altering biochemical pathways in diatoms in order to synthesize complex molecules, biologically active substances, and raw materials may have a number of applications in for example the nanotechnology industry and the production of renewable biofuels.",
"discussion": "Results and Discussion The enzymes PhaA (ketothiolase), PhaB (acetoacetyl-CoA reductase) and PhaC (PHB synthase) of the Gram-negative bacterium R. eutropha H16 were expressed in the cytosol of the diatom P. tricornutum to test whether polyhydroxybutyrate (PHB) can be produced in a microalgal system. Initial in vivo localization studies with GFP fusion proteins demonstrated that all three enzymes are expressed in the heterologous system and accumulate within the cytosol (Figure 1 ). P. tricornutum cells that were co-transfected with sequences for all three enzymes being under the control of a nitrate-inducible promoter were first analyzed via PCR for the integration of all three constructs and were subsequently checked for morphological anomalies. Interestingly, when transferred to nitrate containing medium for 5-7 days (inducing the expression of PhaA, PhaB and PhaC) transfectants accumulated large amounts of granule-like structures within the cytosol, which were specifically labeled with the lipophilic dye Nile Red used in many other studies for in vivo staining of PHB granules (Figure 2A ). Electron microscopic analyses confirmed these data demonstrating that cells were filled with granules that are not present in wild type cells or non-induced cells of the same line (Figure 2B-F ). Gas chromatographic analyses of P. tricornutum phaA / phaB / phaC -transfectants transferred to nitrate-containing medium for 7 days revealed that such cells indeed accumulate PHB to levels of up to 10.6% of algal dry weight (Figure 3 ). Thereby, PHB accumulation turned out to be dependent on the induction period as only 1-3 days of PhaA/PhaB/PhaC expression resulted in much lower PHB quantities (data not shown). Importantly, wild type cells did not accumulate PHB by natural means (Figure 3 ). Figure 1 In vivo localization studies on PhaA, PhaB and PhaC expression in P. tricornutum . Sequences for PhaA (ketothiolase), PhaB (acetoacetyl-CoA reductase) and PhaC (PHB synthase) of R. eutropha H16 were introduced as GFP fusion proteins in P. tricornutum . All three enzymes were expressed in the heterologous system and accumulate in the cytosol as no specific targeting signal was added. Plastid autofluorescence is shown in red and GFP fluorescence is depicted in green. Scale bar represents 10 μm. PAF - plastid autofluorescence, Re - R. eutropha H16 Figure 2 Fluorescence and electron microscopic analyses on PHB accumulation in P. tricornutum . Cytosolic expression of enzymes PhaA, PhaB and PhaC of R. eutropha H16 induces the formation of granule-like structures that are stained by the lipophilic dye Nile red as visualized by fluorescence microscopy (A: NO 3 - ). Under non-induced conditions no such granules were observed (A: NH 4 + ). Electron microscopic analyses confirm cytosolic accumulation of electron-translucent granules (exemplarily marked by arrows) in cell lines expressing bacterial enzymes of the PHB pathway (C-F). PHB granules are about 0.1-0.3 μm in size and were not observed under non-induced conditions (B). Scale bar represents 1 μm (B-D) and 500 nm (E/F). DIC - differential interference contrast, G - golgi apparatus, Mt -mitochondrium, Nu - nucleus, PAF - plastid autofluorescence, Pl - plastid, V - vacuole Figure 3 Quantification of PHB synthesis in the cytosol of P. tricornutum . The level of PHB synthesis for five transgenic P. tricornutum cell lines (No. 8, 11, 15, 18, 28) was analyzed by gas chromatography coupled to mass spectrometry. After 7 days of PhaA/PhaB/PhaC expression PHB levels of 8.0 to 10.6% of algal dry weight were detected. Wild type cells were negative for PHB synthesis. dwt - dry weight, wt - wild type The results of this study show for the very first time that PHB production is possible in a microalgae system. Interestingly, in comparison to efforts on PHB synthesis in the cytosol of plants, PHB expression levels in P. tricornutum are about 100-fold higher [ 7 ]. This might be due to large lipid deposits present in the cytosol of P. tricornutum , as these microalgae naturally produce valuable omega-3-fatty acids [ 22 - 24 ]. Therefore, the acetyl-CoA pool, which is the basis for PHB synthesis, might be notably high in the cytosol of P. tricornutum and hence enable very efficient PHB production. To circumvent acetyl-CoA limitations as a drawback for PHB production in plants, other cellular compartments were tested, and indeed plastids, which provide a high acetyl-CoA content because of fatty acid synthesis, turned out to produce much higher levels of PHB [ 11 , 12 ]. The best PHB synthesis levels in plants with fertile offspring thus far were achieved in tobacco with PHB contributing to 18% of dry weight [ 13 ]. Upon a first glance, this looks promising, however, taking production time as an important economic factor into account plants do poorly in direct comparison to P. tricornutum , which needs approximately two weeks to accumulate similar PHB levels reached by plants during a vegetation period of 3 months. Of course PHB production in P. tricornutum cannot presently compete with bioplastic production in R. eutropha , which was established commercially many years ago. Nevertheless, this pilot experiment together with many other current projects on microalgal biotechnology highlights the immense potential of these photosynthetically driven production systems. Surely, such progress in microalgal biotechnology will boost the development of efficient photobioreactors for use in large-scale cultivation, which is currently one of the most limiting factors to put low-cost production into practice."
} | 1,974 |
40234571 | PMC12000348 | pmc | 7,566 | {
"abstract": "Piezoelectric composite materials have demonstrated significant potential for developing high-performance wearable sensors. However, optimizing the piezoelectric output performance in polymer-based devices remains challenging due to the suboptimal synergy between the piezoelectric reinforcement phase and substrate materials. Moreover, the instability of response signals further hampers the sensor’s practical utility. In this investigation, wet-spinning technology was applied to fabricate a novel Barium Titanate (BaTiO 3 )/Polyvinylidene fluoride (PVDF) composite fiber. Through this approach, we enhanced the piezoelectric properties of the material. Notably, our electron diffraction analysis revealed compelling lattice deformations in the ceramic particle-polymer interface, yielding significant enhancements in the piezoelectric characteristics. Remarkably, incorporating just 1.5 wt% of BaTiO 3 in PVDF led to a piezoelectric output of 0.88 V during dynamic cycle tests at 1 Hz. Encouragingly, the output signal exhibited a robust linear correlation (R 2 = 0.996) with applied compression force. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-025-96516-3.",
"conclusion": "Conclusion In conclusion, this study successfully employed the wet electrospinning process to craft BT/PVDF composite fibers, which demonstrate enhanced sensing capabilities. Our analysis revealed that the wet spinning process not only retains the advantages of traditional techniques for β phase enhancement but also significantly improves interface interactions between the organic and inorganic components. This enhancement further augments the piezoelectric performance of the materials. Notably, the BT/PVDF composite containing 1.5 wt% BT exhibited a remarkable peak piezoelectric voltage of 0.88 V under a 50 N compression force, representing a 3-fold increase compared to unfilled PVDF fibers. This method, as an environmentally conscious approach to composite manufacturing, holds significant promise for the production of large-scale, cost-effective medical and wearable systems.",
"introduction": "Introduction Piezoelectric materials play a pivotal role in wearable sensors 1 . Drawing from the mechanism of pressure signal propagation, the utilization of polytetrafluoroethylene (PTFE) and fluorinated ethylene propylene (FEP) materials has come to the fore. These materials are integral to the construction of fluorocarbon piezoelectric pressure sensors (FPS) 2 , a technology specifically designed to track radial artery pulse waves. Furthermore, the combination of PVDF and ZnO has proven valuable in gesture-based remote-control applications 3 . Notably, composites intertwining carbon nanotubes and polyvinylidene fluoride (CNT/PVDF) have been ingeniously designed as shoe sensors. These composite sensors exhibit the remarkable capability of not only performing assessments but also providing personalized guidance for football training 4 . Unlike non-polar carbon chains, PVDF demonstrates ferroelectricity due to its repeated -CH₂-CF₂- monomer units 5 . Moreover, the electropositive hydrogen atoms and electronegative fluorine atoms allow PVDF to form five crystalline phases: α, β, γ, δ, and ε 6 . Typical wearable piezoelectric sensors also include ceramic/polymer composites. Ceramic materials exhibit high piezoelectric constants but are limited by their rigidity 7 . In contrast, polymers generally offer greater flexibility 8 but are hindered by low piezoelectric voltage coefficients. Consequently, the development of flexible ceramic/polymer composites that combine the advantages of both ceramics and polymers has garnered significant attention in recent decades 9 – 11 , aiming to achieve piezoelectric composites with excellent sensitivity. Recent research on PVDF has shown that the preparation of nanofiber mats by electrospinning is an effective method for producing the β phase in PVDF 12 . After electrospinning, PVDF predominantly exhibits a mix of α and β phases, and further doping with inorganic ceramic materials can enhance its piezoelectric and ferroelectric properties 13 . Common inorganic ceramic dopants include zinc oxide (ZnO) 14 , lead zirconate titanate (PbZr₀.₅₂Ti₀.₄₈O₃, PZT) 15 , and barium titanate (BaTiO₃, BT) 16 . Among these, BaTiO₃, as an environmentally friendly, lead-free piezoelectric material with a high piezoelectric strain coefficient, has received significant attention. Nonetheless, incorporating BaTiO₃ as a piezoelectric reinforcing phase in nanocomposites presents challenges due to its weak interfacial bonding and inadequate dispersion. These issues significantly undermine the electromechanical properties of the nanocomposites, including stress/strain response and piezoelectric coefficients. As a result, the potential for enhancing piezoelectric output performance is severely limited 17 . Furthermore, due to the inherent porosity of the material, the device exhibits substantial changes in dipole moment during compression and release cycles. This tendency to generate imbalanced signal outputs while monitoring subtle signals undermines the composite fiber’s viability for sensor applications 18 . In composite preparation, the conventional electrospinning process often induces excessive aggregation of filler particles within the polymer matrix 19 . The agglomeration of BaTiO₃ particles disrupts the piezoelectric dipole dynamics 20 , while interface defects trap generated charges, leading to increased leakage current 21 . These combined effects hinder the enhancement of piezoelectric nanocomposite performance. Additionally, in conventional electrospinning processes that involve metal collectors, charges frequently dissipate through these collectors during spinning. This reduced retention of effective charges on the fibers adversely affects the high-pressure bonding at the organic-inorganic material interface 22 . As a result, the interaction between BaTiO₃ and PVDF in the BaTiO₃/PVDF (BT/PVDF) composite weakens, reducing the transmission of applied stress from the matrix to BaTiO₃. This ultimately leads to decreased mechanical conversion efficiency and a deterioration in composite performance. Therefore, numerous studies have emphasized the importance of optimizing the effective combination of the piezoelectric reinforcement phase with the base material. These studies suggest that such optimization is crucial for increasing the βphase content in PVDF, which enhances piezoelectric performance, and for significantly improving the application potential of composite fibers. For instance, Netzahualpille et al. introduced a bubble electrospinning setup where the electrode was integrated within the polymer solution reservoir 23 . Similarly, Greiner et al. manipulated membrane morphology by electrospinning poly(L-lactide) (PLLA) atop a liquid reservoir to promote polymer crystallization 24 . Kong et al. achieved a thin surface layer on nanofibers by increasing humidity during their experiment. This layer slowed solvent evaporation, delaying nanofiber solidification and providing sufficient time for β-phase nucleation and growth 25 . Zhang et al., on the other hand, enhanced the interaction between the polymer matrix and BaTiO₃ nanoparticles by incorporating graded methacrylate monomers (MMA or TFEMA) onto the surface of BT nanoparticles within the PVDF matrix 26 . Using the non-solvent-induced phase separation (NIPS) effect 27 , they exploited the lack of hydrogen-bond interactions between PVDF interfaces and water 28 . This allowed low-conductivity water to function as a collector without disrupting the spinning process. Consequently, they achieved increased accumulation of electret charges within the composite, enhancing effective polarization at the organic-inorganic interface 29 . To date, various studies have reported on PVDF/BaTiO₃ composites to improve piezoelectric performance using techniques such as casting, spinning and electrospinning. However, the wet-electrospinning technique for PVDF-BT composites has not yet been explored. This study comprehensively explores the crystallinity of BT/PVDF nanofibers in the context of a water collector and analyzes the influence of BaTiO₃ particles on the piezoelectric output characteristics of PVDF fibers. Flexible BT/PVDF piezoelectric composites were meticulously prepared, ensuring uniform fiber diameters and filler concentrations ranging from 0.5 to 1.5 wt%. While the literature on piezoelectric composites and electrospinning is extensive, our study offers a nuanced perspective by demonstrating that, at filler concentrations of 0.5–1.5 wt%, lattice distortion between BT and PVDF plays a more pivotal role in enhancing piezoelectric performance than merely increasing the β-phase content in PVDF. This effect is particularly pronounced when optimal compatibility is achieved through interface lattice distortion between the inorganic filler and the organic matrix. Moreover, our use of a water collector-assisted electrospinning technique further improved interfacial compatibility. Upon final packaging, the BT/PVDF composite exhibited an average piezoelectric output of 0.88 V under a 50 N compression force, with a highly linear correlation between the output and the applied force (R² = 0.996). These findings not only validate the key role of interface engineering in enhancing piezoelectric performance but also offer novel optimization strategies for sensor and related applications.",
"discussion": "Results and discussion Structural and crystal studies The surface morphology of the as-received BaTiO₃ powder, electrospun PVDF, and BT/PVDF composites was analyzed using field emission scanning electron microscopy (FESEM), as shown in Fig. 2 . Pristine PVDF fibers exhibited an irregularly arranged fibrous morphology with uneven fibers, primarily due to the use of a water medium during electrospinning 32 . Upon incorporating different amounts of BT, the resulting electrospun membranes displayed a mixture of fibers and BT particles (Fig. 2 b-d). The as-received BT powder demonstrated a spherical morphology (Fig. 2 e), and its combination with PVDF fibers indicated the successful formation of composite films. The effect of BT content on fiber diameter was analyzed using Image-J software. Fiber diameters were measured at over 40 locations, with average values provided in Table S2 (Supporting Information). The fiber distribution plots are shown as insets in Fig. 2 a-d, and the average fiber diameters for PVDF and BT/PVDF composites are summarized in Fig. 2 f. Pristine PVDF fibers had an average diameter of 0.37 μm, which gradually increased to 0.6 μm with the addition of 1.5 wt% BT. This increase in fiber diameter can be attributed to the incorporation of BT powder, which raises the viscosity of the solution as BT content increases (see Supporting Information Section S1 and Table S3 ). Generally, higher solution viscosity correlates directly with increased fiber diameter 34 . The regional distribution of BT aggregation, both before and after electrospinning, was also analyzed using Image-J software. Results, shown in Table S7 and Fig. S4 (Supporting Information), indicate that while the distribution of BT particles remains uniform, the particle size slightly increases to 0.5 ± 0.1 μm after agglomeration. This increase could result from possible agglomerations or the particles being surrounded by the PVDF polymer. Additionally, the spherical shapes of the BT particles were distorted during magnetic stirring and ultrasonication during solution processing. Smaller BT filler sizes have been reported to enhance piezoelectric performance by accommodating more interaction sites 35 . This suggests that controlling particle size and distribution is crucial for optimizing the material’s piezoelectric properties. \n Fig. 2 Surface morphology of electrospun membranes ( a ) Pristine PVDF fibers, ( b ) 0.5 wt% BaTiO 3 -PVDF fiber, ( c ) 1.0 wt% BaTiO 3 -PVDF fiber, (d) 1.5 wt% BaTiO 3 -PVDF fiber, ( e ) as-received BaTiO 3 powder, and ( f ) Distribution of fiber diameter for electrospun membranes as a function of BaTiO 3 content. \n In the experiment, piezoelectric ceramic particles with low doping content (0.5–1.5 wt%) were selected to minimize the likelihood of filler particle agglomeration 30 . Under the established spinning conditions, the fiber diameter exhibited a uniform distribution, and the piezoelectric ceramic particles were well-integrated with the polymer fibers. The phase composition and purity of the composite fibers prepared by electrospinning were characterized using X-ray diffraction (XRD) (Fig. 3 a). The pristine PVDF powder displayed primary 2θ peaks at 18.2°, 19.9°, and 26.5°, corresponding to the α phase, attributed to the reflections of (110), (020), and (021) planes, respectively. In contrast, the PVDF and BT/PVDF composite fibers exhibited a single broad peak at 20.3° (for 0.5 and 1.0 wt% BT) and 20.7° (for 1.5 wt% BT), replacing the three distinct α crystallization peaks shown in Fig. 3 a. This broad peak is attributed to the α crystalline phase (020) and an overlapping contribution from unresolved β crystalline phases (110)/(200) 31 . Additionally, the XRD patterns of BT/PVDF fiber mats revealed the characteristic β phase peaks, alongside distinct BT ceramic peaks at 22.1° (100), 31.4° (110), 38.7° (111), and 45.07° (200) (PDF card 97 - 016- 6225). \n Fig. 3 ( a ) XRD patterns for as-received powders and electrospun samples, ( b ) FTIR-ATR spectra for as-received powders and electrospun samples, ( c ) content of crystalline β of BT/PVDF, ( d ) TEM image of 1.5 wt% BaTiO 3 -PVDF. \n To gain detailed information about the phase transitions in the samples, FTIR-ATR (Fourier-Transform Infrared Spectroscopy: Attenuated Total Reflectance) analysis has been used. Figure 3 b shows the FTIR-ATR spectra of the untreated PVDF powder, pristine PVDF fiber, and BT/PVDF composite fiber. In each sample, the appearance of absorption bands at 763 cm −1 corresponding to the non-polar α phase in the FTIR spectrum. The exclusive peak at 1275 cm −1 corresponds to the β phase, while the peak at 1234 cm −1 indicates the presence of the γ phase. Intensive absorption band at 840 cm −1 is shared by both the β and γ phases 32 , 33 . The exact β phase percentage of the neat PVDF and its composite films were measured by Lamberts-Beer law as follows. The overall percentage of the β phase was calculated from Eqs. ( 1 )-( 2 ) based on the Lambert-Beer law 34 . 1 \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\:{F}_{EA}=\\frac{{I}_{EA}}{\\left(\\frac{{K}_{EA}}{{K}_{\\alpha\\:}}\\right){I}_{\\alpha\\:}+{I}_{EA}}\\times\\:100\\text{\\%}$$\\end{document} where I EA and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\:{I}_{\\propto\\:}$$\\end{document} are the absorbance at 840 and 763 cm −1 , respectively, and K EA and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\:{K}_{\\propto\\:}$$\\end{document} represent the absorption coefficients at the corresponding wavenumbers, which are 6.1 \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\:\\times\\:$$\\end{document} 10 4 and 7.7 \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\:\\times\\:$$\\end{document} 10 4 cm 2 mol [− 1 , respectively. The relative fraction of β phases can also be calculated by Eq. ( 2 ), respectively. 2 \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\:\\text{F}\\left({\\upbeta\\:}\\right)={F}_{EA}\\times\\:\\frac{\\varDelta\\:{H}_{\\beta\\:}}{\\varDelta\\:{H}_{\\beta\\:}+\\varDelta\\:{H}_{\\gamma\\:}}$$\\end{document} ΔH β is the absorbance difference between the peak around 1275 cm −1 and the nearest valley around 1260 cm −1 and ΔH γ is the height difference between the peak around 1234 cm −1 and the nearest valley around 1225 cm −1 . The calculated β phase percentage is provided in Fig. 3 c and Table S6. Based on the calculation results, the addition of BT leads to a slight increase in the β phase in PVDF, with no significant further increase observed as the BT content is raised. Further investigate the interface interaction of piezoelectricity through TEM. The FE-TEM image of locally magnified 1.5 wt% BT/PVDF nanofiber is displayed. Figure 3 d and Fig. S5 (Supporting Information) show the TEM morphology of embedded BaTiO 3 in the boundary of the PVDF fiber surface at 1.5 wt%. According to TEM images and electron diffraction patterns, the spacing of the lattice plane in Fig. 3 d is 0.247 nm, which changes 6 to 38% from the primary lattice spacing of (100) (110) (200) (PDF # 97 - 016- 6225). The change of surface spacing leads to lattice change. This enhanced lattice distortion is equivalent to a substantial electric dipole, which increases the polarization vector on the surface of BaTiO 3 crystal, and the absorbed free electrons transfer rapidly under the influence of the particle electric field, which improves the intrinsic piezoelectric effect 35 . Electrical characterization The complete schematic diagram of the device is shown in Fig. 4 a. Preparation of the piezoelectric sensing device: The BT/PVDF fiber mat has a thickness of approximately 100 μm and is covered on both sides with copper foil and a 50 μm Kapton tape. The overall dimensions of the device are 1.5 × 1.5 cm². The testing samples for piezoelectric output performance are subjected to reciprocating force via a grounded aluminum plate. Structurally, the samples consist of a Kapton shielding layer, a front electrode, the composite fiber membrane, and a rear electrode. The complete schematic representation of the cross-sectional view of the device is shown in Fig. 4 a. The finite deformation of the piezoelectric fiber leads to smaller displacements, which allow the piezoelectric signal to reach its peak more quickly. The piezoelectric signal is primarily force-dependent, so the electric force relationship is tested accordingly. Figure 4 b shows the electrical generation characteristics of the BT/PVDF nanofiber during pressing and releasing cycles. In the initial unpressurized state, the cations and anions’ charge centers are aligned, with no significant polarization. Upon pressure application, the deformation of the fibers generates negative strain and reduces the volume. The separation of charge centers forms electric dipoles, which leads to the development of a piezoelectric potential between the electrodes. If the electrodes are connected to an external load, the piezoelectric effect drives electrons through the external circuit, partially screening the piezoelectric potential and reaching a new equilibrium state. This process converts mechanical energy into electrical energy, consistent with the principles of nanoelectronics 36 . The piezoelectric effect of the composite fibers is primarily attributed to the intrinsic contribution, which arises from field-induced lattice distortion 37 . Under the influence of lattice stress or polarization vector rotation 38 , changes in the lattice parameters lead to lattice deformation. For the BT/PVDF composite, BaTiO₃ particles are uniformly distributed within the organic matrix. When an electric field is applied, the different polarization abilities of the ceramic particles and the polymer matrix generate bound charges at the BT/PVDF interface, causing local electric field distortion. Inorganic ceramic particles, like BaTiO₃, exhibit stronger polarization, leading to more significant bound charges on their surfaces. The composite’s internal electric field is the sum of the applied and bound electric fields, which enhances the formation of intrinsic piezoelectricity under field-induced lattice distortion. Due to the weak conductivity of wet spinning technology, the spinning process tends to increase the bound charge, which indirectly improves the piezoelectric properties of the composite fibers. During the spinning process, PVDF undergoes a phase transition to form β chains (trans chains). Adding BT particles can slow down this relaxation 39 , and the slowing effect is due to the interface interaction 34 (characterized by TEM, Fig. S5 , and Fig. 3 d). However, excessive agglomeration and uneven distribution of BT particles can lead to output nonlinearity. Therefore, the wet spinning method is used to control the degree of BT agglomeration, preventing a decrease in interface charge density. The results from this study show that increasing the BT content improves the linearity and stability of the output voltage, confirming that the composite fibers are well-suited for sensor applications. \n Fig. 4 ( a ) Illustrates the crossectional view of the piezoelectric device, ( b ) working mechanism of piezoelectric device. Figure 4a and b were generated using Microsoft PowerPoint (Version 2019), available at https://www.microsoft.com . \n Figure 5 a shows the output force and open-circuit voltage (V OC ) of PVDF and BT/PVDF composite membranes with varying BT content. The pristine PVDF fibers membrane exhibits a V OC of 0.3 V. The V OC increases gradually from 0.3 V to 0.88 V as the BT content increases from 0 wt% to 1.5 wt%. The piezoelectric performance of the optimized 1.5 wt% BT/PVDF device was evaluated as a function of frequency and load, as shown in Fig. 5 b. Meanwhile, the d33 value was measured, and the results show that it increased exponentially with increasing BT content (Fig. 5 c). However, this increase in d33 value did not directly correspond to a proportional increase in the output electrical performance. This is because the binding sites between BT powder and fibers are fixed, and the degree of dispersion remains relatively consistent in the range of 0.5–1.5 wt% BT. However, as the BT content increases, agglomeration can occur, limiting further improvements in piezoelectric properties due to reduced interfacial interactions, as shown in Fig. S5 . When the frequency varied from 0.5 to 2.0 Hz in intervals of 0.5 Hz, the VOC remained relatively stable when the applied load was fixed at 50 N. Therefore, we conclude that the V OC of the 1.5 wt% BT/PVDF device is independent of frequency. Additionally, as the applied load increased from 5 N to 50 N, the VOC of the 1.5 wt% BT/PVDF device increased from 0.1 V to 0.88 V, demonstrating good linearity (R² = 0.996) in this range (Fig. 5 d). The presence of BaTiO₃ particles in the composite leads to the formation of stress concentration points within the fiber. When force is applied at these points, the localized stress increases, enhancing the output voltage 40 . \n Fig. 5 a ) V OC response of BT/PVDF device employing 50 N load, ( b ) I sc response of the BT/PVDF device employing 50 N load. ( c ) d33 value of PVDF fiber with different BT content (0, 0.5, 1.0, 1.5 wt%) on the V OC response of 1.5 wt% of BT/PVDF under 50 N load, ( d ) Effect of applying load (5 to 50 N) on the V OC response of 1.5 wt% of BT/PVDF."
} | 6,047 |
28591626 | null | s2 | 7,567 | {
"abstract": "Studies of interspecies interactions are inherently difficult due to the complex mechanisms which enable these relationships. A model system for studying interspecies interactions is the marine hyperthermophiles Ignicoccus hospitalis and Nanoarchaeum equitans. Recent independently-conducted 'omics' analyses have generated insights into the molecular factors modulating this association. However, significant questions remain about the nature of the interactions between these archaea. We jointly analyzed multiple levels of omics datasets obtained from published, independent transcriptomics, proteomics, and metabolomics analyses. DAVID identified functionally-related groups enriched when I. hospitalis is grown alone or in co-culture with N. equitans. Enriched molecular pathways were subsequently visualized using interaction maps generated using STRING. Key findings of our multi-level omics analysis indicated that I. hospitalis provides precursors to N. equitans for energy metabolism. Analysis indicated an overall reduction in diversity of metabolic precursors in the I. hospitalis-N. equitans co-culture, which has been connected to the differential use of ribosomal subunits and was previously unnoticed. We also identified differences in precursors linked to amino acid metabolism, NADH metabolism, and carbon fixation, providing new insights into the metabolic adaptions of I. hospitalis enabling the growth of N. equitans. This multi-omics analysis builds upon previously identified cellular patterns while offering new insights into mechanisms that enable the I. hospitalis-N. equitans association. Our study applies statistical and visualization techniques to a mixed-source omics dataset to yield a more global insight into a complex system, that was not readily discernable from separate omics studies."
} | 455 |
24443657 | null | s2 | 7,568 | {
"abstract": "Microgel multi-layer films assembled from anionic particles and linear polycation were prepared on elastomeric substrates and their self-healing properties studied. Dried films were imaged "
} | 47 |
35459210 | PMC9026648 | pmc | 7,569 | {
"abstract": "Background During fermentation, industrial microorganisms encounter multiple stresses that inhibit cell growth and decrease fermentation yields, in particular acid stress, which is due to the accumulation of acidic metabolites in the fermentation medium. Although the addition of a base to the medium can counteract the effect of acid accumulation, the engineering of acid-tolerant strains is considered a more intelligent and cost-effective solution. While synthetic biology theoretically provides a novel approach for devising such tolerance modules, in practice it is difficult to assemble stress-tolerance modules from hundreds of stress-related genes. Results In this study, we designed a set of synthetic acid-tolerance modules for fine-tuning the expression of multi-component gene blocks comprising a member of the proton-consuming acid resistance system ( gadE ), a periplasmic chaperone ( hdeB ), and reactive oxygen species (ROS) scavengers ( sodB and katE ). Directed evolution was used to construct an acid-responsive asr promoter library, from which four variants were selected and used in the synthetic modules. The module variants were screened in a stepwise manner under mild acidic conditions (pH 5–6), first by cell growth using the laboratory Escherichia coli strain MG1655 cultured in microplates, and then by lysine production performance using the industrial lysine-producing E. coli strain MG1655 SCEcL3 cultured first in multiple 10-mL micro-bioreactors, and then in 1.3-L parallel bioreactors. The procedure resulted in the identification of a best strain with lysine titer and yield at pH 6.0 comparable to the parent strain at pH 6.8. Conclusion Our results demonstrate a promising synthetic-biology strategy to enhance the growth robustness and productivity of E. coli upon the mildly acidic conditions, in both a general lab strain MG1655 and an industrial lysine-producing strain SCEcL3, by using the stress-responsive synthetic acid-tolerance modules comprising a limited number of genes. This study provides a reliable and efficient method for achieving synthetic modules of interest, particularly in improving the robustness and productivity of industrial strains. Supplementary Information The online version contains supplementary material available at 10.1186/s12934-022-01795-4.",
"conclusion": "Conclusions This study demonstrates a useful strategy to improve growth robustness and productivity for industrial E. coli in fermentation at mildly acidic pH, through the use of synthetic acid tolerance modules, which involve only a limited number of genes, in our case, periplasmic protein chaperone ( hdeB ), ROS scavenging enzymes ( sodB and katE ), and a transcription factor for the AR system ( gadE ). The functional optimization of these modules can be realized by the use of acid-responsive promoters of different strengths, and screened with a stepwise protocol, from a growth-guided high-throughput screening to a production performance-guided fermentation evaluation.",
"discussion": "Discussion During industrial bioprocesses, the gradual decrease of environmental pH causes multiple stresses that impair cell growth and lower the fermentation yields [ 7 , 52 – 55 ]. Engineering acid resistant strains is potentially an important strategy to increase productivity, decrease base consumption, and facilitate the downstream separations [ 7 ]. Synthetic biology is an inspiring route to construct acid-tolerance modules that are functional in industrial strains. However, it is difficult to assemble reasonable stress-tolerance modules from hundreds of stress-tolerant genes. For example, in E. coli , there are at least 274 genes involved in acid stress regulation [ 12 ], and 217 genes involved in oxidative stress regulation [ 56 ]. Based on our previous observations [ 15 , 25 ], in this study, we focused our attention on the proton-consuming acid resistance system AR2, periplasmic chaperones, and ROS scavengers. We successfully obtained two improved lysine-producing E. coli strains, namely SC 3124 and SC 2121, for which the lysine titers at pH 6.0 were 118% and 116% of that of the parent strain at pH 6.8, and the lysine yields from glucose were 105% and 97% of that of the parent strain at pH 6.8. In addition, the lysine yield for SC 3124 was 115% of the parent strain at pH 6.0. By a rough estimation, this yield could save about 260 kg of glucose per ton of lysine produced, while fermentation at pH 6.0 could save 5–10% of the amount of acid added during purification of lysine in industrial settings. This study strengthens the notion that periplasmic molecular chaperons are important for acid resistance of E. coli [ 15 , 33 ]. This is likely because when the protons from the acidic environment permeates into the cell, the periplasmic space becomes the first line of defense and the periplasmic proteins become vulnerable, thus requiring the protection afforded by chaperones [ 26 , 33 ]. Although the glutathione (GSH) system has been used for ROS scavenging to increase the tolerance for bacterial or yeast cells, it requires a complex engineering route to balance the NADPH/NADP + ratio [ 28 , 57 ]. Thus, an enzymatic system like SodB-KatE [ 44 ] rather than GSH might be more advantageous. Along this line, it is interesting to note that at the cell growth assay level, we found that gadE was not a necessary component for the synthetic acid tolerance modules, but at the lysine productivity level, the best strains all contained synthetic modules with this gene (in addition to its genomic copy). As GadE is responsible for regulating the AR2 system, we attempted to replace it with the two AR2 component genes coding for GadB (variant GadB(dHT) which has enhanced activity at pH 4–6 [ 58 ]), and YbaS, but the effort only yielded strains with lower performance both in terms of cell growth and lysine productivity (data not shown). There is a possibility that overexpressing gadE could up-regulate the lysine-dependent acid resistance system (AR4) [ 30 ]. This remain to be further investigated. Recently, a combinatorial strategy was used for engineering multiple-stress-tolerant ethanol-producing Saccharomyces cerevisiae strains [ 44 ]. The study involved a much larger library of four sets of genes, more specifically, a set of 5 genes coding for heat shock proteins with chaperone functions, 16 genes involved in the antioxidant system, 5 genes coding for ubiquitins and autophagy proteins that remove denatured proteins, and 6 transcription factors that regulate stress-related networks were combined via the golden gate assembly with 14 different promoters and screened at high temperatures (35 °C or 37 °C). The best strain obtained in terms of ethanol titer was found to contain overexpressed sodA , sodB from E. coli and an endogenous cAMP phosphodiesterase PDE2 . It appeared that PDE2 alone activated a number of stress tolerance pathways, and thus the effects of other factors like the heat shock proteins, ubiquitins and autophagy proteins were likely masked under the overexpression of PDE2 [ 59 – 61 ]. This study also hints that PDE2 like regulators with an appropriate activation range could also be tested for E. coli . The best strain finally was subjected to adaptive evolution by atmospheric and room temperature plasmas (ARTP), yielding a final strain with an enhanced ethanol titer of 6.9% in a large scale 200-L fermenter. In this work, we constructed a synthetic asr promoter library with an enlarged operation range both in terms of absolute promoter strength as well as of pH response ratio at different pH (pH 5.0 vs pH 7.0). This promoter is regulated by RstBA and PhoRB systems. The RstA box is located at − 77 to − 55 of the promoter region, and the PhoB is located at − 39 to − 22, thus overlaps the -35 element (Additional file 1 : Fig. S1) [ 37 , 38 ]. RstBA induces asr under mild acidic conditions, while PhoRB induces asr at low inorganic phosphate concentrations [ 38 , 62 ]. Previous saturation mutagenesis experiments performed at the RstA box [ 63 ] produced only four notable variants with strengths at pH 5.0 ranging from 1.6 to 40.0% of the wild type, and the pH response ratios ranging from 0.7 to 14.4% of the wild type. Therefore, we chose to target the 9 bp spacer region between PhoB box and − 10 sequence, which has been shown to affect the strengths of several promoters [ 39 , 40 ]. Our strategy proved to be successful, and the resulting series of variants may be useful for constructing other acid-responsive synthetic modules or circuits [ 8 ]. It is noteworthy that the mutations in this region also can cause loss of the acid responsiveness of the promoter, even though it is located downstream of the RstA box. However, a previous study on the engineering of an osmic stress-responsive ect promoter also showed that the mutations or deletions in the spacer region of the promoter changed the osmotic responsiveness [ 43 ]."
} | 2,242 |
34927023 | PMC8646179 | pmc | 7,571 | {
"abstract": "Summary Nowadays, wearable devices mainly exist in the form of portable accessories with various functions, connecting various kinds of terminals like mobile phones to form various wearable systems. In a wearable system, the wearable power supply device is the key component as energy dispenser for all devices. Nanosheets, a kind of two-dimensional material, which always displays a high surface-to-volume ratio and thus is lightweight and has remarkable conductive as well as electrochemical properties, have become the optimal choice for wearable power supply devices. The development and status of nanosheet-based wearable power supply devices including nanosheet-based wearable batteries, nanosheet-based wearable supercapacitors, nanosheet-based wearable self-powered energy suppliers are introduced in this article. Besides, the future opportunities and challenges of wearable devices are discussed.",
"conclusion": "Conclusion and perspective In this review, three common and popular wearable power supply devices based on nanosheet materials are introduced, which are nanosheet-based wearable batteries, nanosheet-based wearable supercapacitors, and nanosheet-based wearable self-powered energy suppliers. The specific researches toward these three kinds of nanosheet-based wearable power supply devices and their comparison are tabulated in Tables 1 , 2 , and 3 . Besides, three figures ( Figures 10 , 11 , and 12 ) illustrating the development and science problem of nanosheet-based power supply devices, advantages/disadvantages, as well as the current/potential applications are included to offer a concise and clear overview of each device. Table 1 Comparison among the nanosheet-based wearable batteries based on different nanosheets Classification of nanosheet-based wearable batteries Nanosheet materials Modification/functionalization/fabrication Capacity/specific capacity Cyclic behaviors and capacity retention Energy density Ref Li-ion batteries Titanium oxide Hybridized with reduced graphene oxide 89 mAh g −1 at 0.0425 mA After 200 cycles at 0.0085 mA, the capacity retention is more than 70% – Hoshide et al. (2017) Li-Sulfur batteries MXene Combined with S 2–4 /carbon composite 1,029.7 mAh g −1 at 0.1 C After 200 cycles with 91.9% retention – Zhao et al. (2019b) Li-air batteries CuCo 2 S 4 – 9,673 mAh g −1 at 100 mA g −1 Over 164 cycles – Long et al. (2019) Zn-ion batteries V 2 O 5 Decorated with titanium nitride (TiN) nanowires as a (TiN)@V 2 O 5 three-dimensional nanostructure 532.9 mAh g −1 Cyclic performance of more than 3,500 cycles and capacity retention of 90.6% 373.0 Wh kg −1 Li et al. (2019b) MoS 2 Expending the layer spacing of MoS 2 nanosheets to get E-MoS 2 nanosheets 202.6 mAh g −1 Over 600 cycles with a capacity retention of 98.6% 148.2 Wh kg −1 Li et al. (2019a) MnO 2 Using lithium treatment to expand the interlayer spacing of MnO 2 nanosheets and combined with the carbon cloth (CC) 3.63 mAh cm −2 at the current density of 3.93 mA cm −2 Up to 5,000 cycles 5.11 mWh cm −2 Zhao et al. (2021) Zn-air Co 3 O 4 An integrated electronic system in a layer-by-layer 2 × 2 structure 595 mAh g −1 More than 20 cycles 573 Wh kg −1 Qu et al. (2017) N-doped carbon CoNi alloy nanoparticles and carbon nanotubes decorated N-doped carbon nanosheet arrays on carbon cloth (CoNi alloy/NCNSAs/CC) 879 mAh g −1 Over 40 cycles 98.8 mW cm −2 Zhang et al. (2020) RuO 2 N-doped carbon 802 Wh kg −1 at 5 mA cm −2 1,000 cycles 115 mW cm −2 Zhao et al. (2020) Nickel-Fe batteries Ni(OH) 2 3D printed 268.3 mAh g −1 91.3% capacity retentions after 10,000 cycles 28.1 mWh cm −3 at a power of 10.6 mW cm −3 Kong et al. (2020) NiCoP Hydrothermal synthesis and pursuant gas phosphating process 0.294 mAh cm −2 at 2 mA cm −2 89% after 4,000 cycles 235.6 μWh cm −2 Yang et al. (2020) The cyclic behaviors refer to the charging-recharging cycles. Table 2 Comparison among the nanosheet-based wearable supercapacitors based on different nanosheets Classification of nanosheet-based wearable power supply devices Nanosheet materials Modification/functionalization/fabrication Capacity/specific capacity Cyclic behaviors with capacity retention Energy density Ref Supercapacitors Ni(HCO 3 ) 2 Decorating Ni(HCO 3 ) 2 nanosheets to flexible PVA/carbon nanotube – 85.5% capacitance retention after 2,000 cycles – Song et al. (2019) NiCo 2 S 4 Covering CoS 2 nanowires onto NiCo 2 S 4 nanosheets in situ 168.3 mAh g −1 at 1 A g −1 80% capacity retention after 6,000 charge-discharge cycles 60.2 Wh kg −1 at 800 W kg −1 Shao et al. (2020) Depositing on activated carbon cloth 2392 F g −1 85.1% even after 10,000 cycling test 30.1 Wh kg −1 Zhao et al. (2019c) Fabricated on carbon cloth by a facile multistep solution-based strategy – 2,000 cycles 2.7 mWh cm −3 Huang et al. (2020) NiCo 2 O 4 Printing MnO 2 on the nanosheet-based substrate – 93.1% after 5,000 cycles at 50 mA cm −2 37.8 mW cm −3 , Sundriyal and Bhattacharya (2020) Growing on Ni wire – 78% at 0.1 mA after 5,000 cycles 1.44 mWh cm −3 Wang et al. (2014) MnO 2 Doped with NA 265.4 mF cm −2 92.2% after 5,000 cycles at 1 mA cm −2 178.4 μWh cm −2 Zong et al. (2018) Combined with single-wall carbon nanotubes (SWCNTs) 74.8 F cm −3 94% capacitance retention over 5,000 cycles 10.4 mWh cm −3 Li et al. (2018a) Ni(OH) 2 Embedded the nanosheets on the carbon nanotubes 24.8 F cm −3 93.8% over 3,000 cycles 5.8 mWh cm −3 Shi et al. (2018b) VGNs After VGNs growing on ductile nickel wires, MnO 2 was deposited on the nanostructure of VGNs/NiWs 56 mF cm −2 80% of its original value after 2,000 cycles 7.7 mWh cm −2 Zhou et al. (2021) MnO Integrated with NPCTT – 86.2% after 5,000 cycles 176 μWh cm −2 Ding et al. (2020) CoNi 2 S 4 Combined 3D printing with electrodeposition 28.71 F cm −3 92.2% after 5,000 cycles at 500 mA cm −3 0.582 mWh cm −3 Chang et al. (2020) The cyclic behaviors refer to the charging-recharging cycles. VGN, vertical graphene nanosheet; NiW, Ni wire; NPCTT, nanoporous carbon tube textile. Table 3 Comparison among the nanosheet-based wearable self-powered energy suppliers based on different nanosheets Classification of wearable self-powered energy suppliers Nanosheet materials Modification/functionalization/fabrication Output voltage Output current Cyclic behaviors Ref. Piezoelectric nanogenerators (PENGs) Graphene Using electrospun nanocomposite fiber mats comprising graphene nanosheets, barium titanate (BT) nanoparticles, and poly(vinylidene fluoride) (PVDF) Peak voltage is 112V – Over 1,800 cycles for stretch test Shi et al. (2018a) Applied vertically oriented graphene nanosheets to grow and transfer the aligned single-crystalline GaN nanorods (NRs) More than 8 V 1.2 mA – Tsai et al. (2018) ZnO On a flexible Al substrate with a low growth temperature of 80°C using synthesis hydrothermal method to prepare the Zn nanosheet networks 100 mV for a single device – – Manjula et al. (2020) Two-stage preparation process of 2D ZnO nanosheets 35 mV 0.15 μA under the load of 1 kgf – Wang et al. (2018) Doping Br into the ZnO nanosheets 17.78 V 8.89 μA cm −2 – Rafique et al. (2021) Doping vanadium into ZnO nanosheets 1.5V 80 NA Over 10,000 cycles for bend test Zhang et al. (2018a) Triboelectric nanogenerators (TENGs) Au Au nanosheets embedded into both PDMS matrix and micropyramid-patterned PDMS 98.9 V – Over 10,000 cycles in stretch test Lim et al. (2017a) MoS 2 MoS2 nanosheets were wrapped the silver nanowires (AgNWs) 95.8V at a 30 Hz frequency – Over 10,000 cycles for stretch test Lan et al. (2019) MXene Integrating the poly(vinyl alcohol) (PVA) with MXene nanosheets 117.7 V – 124,000 cycles for contact test Jiang et al. (2019) Graphene Based on polyvinylidene fluoride (PVDF) via graphene nanosheets incorporation in conjunction with electrospinning technology 1511 V 189 mA m −2 80,000 cycles for contact test Shi et al. (2021) Nanosheet-based thermoelectric generators Metal dichalcogenide (TMDC) Chemically exfoliated – – Over 100 cycles for stretch test Oh et al. (2016) Adding highly conducting single-wall carbon nanotubes – – More than 10,000 cycles for stretch test Kim et al. (2019) Nanosheet-based solar cells CuS ITO (indium tin oxide)-free and Pt-free flexible quantum-dot solar cells (QDSCs) were assembled into a typical sandwich structure – – 500 cycles for bending test Xu et al. (2017) Figure 10 Overview of each nanosheet-based battery including advantages/disadvantages and current/future applications Figure 11 Overview of each nanosheet-based supercapacitor including its benefits and drawbacks, as well as present/potential uses Figure 12 Overview of each nanosheet-based self-powered energy supplier including advantages/disadvantages and current/future applications Nanosheets, a class of two-dimensional materials, manifest a high surface-to-volume ratio, and thus more conducive and electrocatalyst sites. Therefore, the conductivity of distinct kinds of nanosheets is always high and the application of nanosheet can minimize the size of wearable power supply devices. Nanosheets possess the highest possible specific surface area among nanomaterials and are the key materials to form the 3D nanostructures, both of which make nanosheets the optimal basic materials for power supply applications. By applying nanosheets as the basic materials for wearable power supply devices and combining nanosheets with plenty of zero-dimensional nanoparticles, one-dimensional nanowires, nanotubes, as well as nanorods to form three-dimensional nanostructures, the power storage and supply performance of all wearable power supply devices will dramatically increase. The nanosheet-based wearable batteries exhibit satisfactory cyclic stability, lightweight, and better energy density than other power supply devices like supercapacitors. As a result, the nanosheet-based wearable batteries are the optimal choice for the application that need less charge-discharge times and long-term duration for one time use, e.g., wearable smart watches and earphones, as well as the application with the requirement of large power consumption like Google glasses and VR/AR glasses. However, safety is a crucial issue for wearable nanosheet-based batteries considering that they are always mounted on human skin. Therefore, supercapacitors with nontoxic aqueous electrolytes can act as an alternative choice. Although the energy density of the nanosheet-based wearable supercapacitors is lower than that of batteries, the charge-discharge cyclic behaviors of nanosheet-based wearable supercapacitors are much better than those of nanosheet-based wearable batteries and the charging time is faster, which makes nanosheet-based wearable supercapacitors more suitable for the electronic device applications with shorter duration for one time and the requirements of multiple uses, e.g., wearable sensors. The limited energy density for nanosheet-based wearable batteries and supercapacitors can be modified by combining them with nanosheet-based self-powered energy suppliers including TENG, PENG, thermoelectric generators, and solar cells. The power obtained by self-powered energy suppliers is not continuous and the energy harvested is always not enough, both of which lead to the limited application of the nanosheet-based self-powered energy suppliers toward the wearable electronic devices with low-energy consumption and long internal time between uses. To be specific, LIBs are the market-leading classification of distinct batteries. Zn-based batteries based on nanosheets also attract great attention, as compared with Li, Zn is abundant, safe, and environmentally friendly. Besides Li-based and Zn-based batteries, other batteries, e.g., Ni-Fe batteries, are also attempted to achieve wearability owing to their high cycling stability. When it comes to the nanosheet-based wearable supercapacitors, NiCo 2 S 4 nanosheets and NiCo 2 O 4 nanosheets are the most applied nanosheet materials for the wearable solid-state supercapacitors owing to their prominent electrochemical performance, redox activity, and capacity values. Compared with conventional solid-state supercapacitors, fiber-shaped supercapacitors are more intriguing owing to their better flexibility and smaller volume and are thus easier for wearability. The applied nanosheets include MoS 2 nanosheets, MnO 2 nanosheets, Ni(OH) 2 nanosheets, and vertical graphene nanosheets. TENGs and PENGs are the most widely applied self-powered energy suppliers. For wearable PENGs, ZnO nanosheets and graphene are the two of the welcome basic nanosheet materials, whereas for wearable TENGs, researchers select Au nanosheets, MoS 2 nanosheets, MXene nanosheets, and graphene nanosheets as the basic nanosheet materials. Besides nanogenerators that work by mechanical energy conversion, there exist some researches toward thermoelectric generators based on nanosheets, e.g., dichalcogenide (TMDC) nanosheets. The nanosheet-based wearable solar cell is another hot research target for self-powered energy suppliers as solar energy is an abundant, green, and inexhaustible energy resource. However, the mechanical strength and electrical conductivity of nanosheet-based wearable solar cells need further improvement to be commercialized. From a prospective view, nanotechnology is enabling the development of devices on a scale ranging from one to a few hundred nanometers. At the scale, the novel nanosheets show new properties and behaviors not observed at the microscopic level. In the future, with the development of wearable power supply devices based on nanosheets, networks of nanodevices with the ability of biomedicine, environmental protection, entertainment, homeland security, and beyond will play a significant role in almost every field of our society. Moreover, researchers will develop more nanosheet materials with better properties to make the nanosheets more suitable in power supply applications. As for the wearable batteries based on nanosheets, the technique should be improved and novel nanosheet materials used should be developed to improve the cyclic behaviors and capacity retention, while energy density needs to be enhanced for the wearable supercapacitors. Among the wearable power supply devices, wearable self-powered energy suppliers based on nanosheets hold the brightest future as by means of application of wearable self-powered energy suppliers, the wearable devices can be self-powered and thus low cost, facile, and environmentally friendly. Furthermore, with the development of technology, wearable batteries and supercapacitors can be applied together with wearable self-powered energy suppliers to store the extra energy not used by wearable devices. The combination of wearable nanosheet-based batteries/supercapacitors and self-powered energy suppliers is expected to be the future development trend as self-powered, consistent, and sufficient power supply devices are badly required for all types of wearable/unwearable electronic devices and the realization of the Internet of Things. This field will be the focus of a vast number of studies. However, there are still some challenges that need to be overcome for the practical application of wearable power supply devices. First of all, nanosheet materials are quite expensive, which prevents the nanosheet-based power supply device from further commercialization. To solve this problem, novel nanosheets with low cost and satisfactory properties should be built and a one-step, facile, and low-cost nanosheet production process should be developed. In addition, the energy storage of nanosheet-based batteries and supercapacitors is limited. The frequent charge or replacement will bring inconvenience for users. Therefore, improving the energy capacity and combining it with wearable self-powered energy suppliers were optimal solutions. The power supply of wearable self-powered energy suppliers based on nanosheets is unstable, which also indicates that the combination of wearable nanosheet-based batteries, supercapacitors as well as self-powered energy suppliers must be the future trend. Besides, the power supply of the self-powered energy suppliers needs to be improved a lot to make it possible for applications with large power consumption.",
"introduction": "Introduction With the rapid development of computer technology, sensors, and communication technology at home and abroad, miniaturization and rapid operation meet the requirements of wearable devices on people ( Li et al., 2021 ), so a variety of wearable devices gradually appear in the eyes of the public, gradually emerging in the fields of medical care, education, military, and daily life and show extremely important research value and application potential ( Almusawi et al., 2021 ; Beniczky et al., 2021 ; Faruk et al., 2021 ; Huifeng et al., 2020 ). With the maturity of wearable technology, various wearable devices have poured into the lives of ordinary people on a large scale. Power supply devices are always the key components of integrated wearable systems, which guarantees wearable systems to keep operating uninterruptedly, continuously, and for a long term ( Gao et al., 2021 ). Consequently, the wearable power supply device is required to be flexible, durable, safe, and with high energy density ( He et al., 2021 ). To meet all these requirements, nanosheets, a kind of two-dimensional (2D) nanomaterial with excellent physical and mechanical properties including ultra-thin thickness, high flexibility, stretchability, and excellent adhesion have triggered great research enthusiasm and become the optimal material for wearable power supply device due to these remarkable characteristics ( Kim et al., 2021 ; Liang et al., 2018 ; Nie et al., 2020 ; Zhong et al., 2019 ). Especially, the extremely large surface-to-volume ratio of the nanosheets provides the miniaturization of wearable power supply devices and greatly increases the capability of power storage and supply for wearable power supply devices ( Jin et al., 2020 ; Zhou et al., 2021 ) considering that nanosheets bring numerous electrocatalytic sites and thus catalyze the electrochemical reaction at the electrode. A large number of nanosheets, e.g., graphene analogues (GA), including graphene oxide (GO) nanosheets, reduced graphene oxide (rGO) nanosheets, and graphdiyne nanosheets, and transition metal element nanosheets, including MoSe 2 nanosheets, Ru-Ni nanosheets, MoS 2 nanosheets, ZnO nanosheet, and organic nanosheets like PLLA nanosheets, have been produced by researchers ( Careta et al., 2021 ; Guo et al., 2019 ; Liu et al., 2021 ; Yang et al., 2019a , 2019b ; Yu et al., 2019 ; Zhang et al., 2018b , 2021 ) since the first-developed nanosheets, graphene, was reported in 2004 ( Novoselov et al., 2004 ). Among nanomaterials, nanosheet materials display the highest possible specific surface area ( Mohammadpour and Majidzadeh, 2020 ), which brings better performance in power supply applications. Besides the higher surface area over zero-dimensional (0D) nanoparticles and distinct kinds of one-dimensional (1D) nanomaterials, nanosheets can act as the nanoplatform to be decorated/combined with 0D and 1D nanomaterials or be coated on other nanomaterials so that three-dimensional nanostructures with unique and better properties can be obtained to meet more requirements. In this review, the wearable power supply devices based on nanosheets are divided into three classifications: nanosheet-based wearable batteries, nanosheet-based wearable supercapacitors, and nanosheet-based wearable self-powered energy suppliers. The nanosheets applied in such three classifications of nanosheet-based wearable power supply devices are summarized. In addition, on the basis of the related literature, the perspective and future research trend of the nanosheet-based wearable power supply devices are also discussed in this review. Nanosheet-based wearable batteries Next-generation electronic devices need portable, continuous, and stable power supplies for charging. Among all wearable power supply devices, wearable batteries possess satisfactory cyclic stability, are lightweight, and have prominent energy density, all of which make the wearable batteries one of the optimal wearable power supply devices to charge next-generation electronic devices such as wearable sensors, touch screens, roll-up displays, as well as implantable medical devices. Besides, wearable electronic devices with broad applications (e.g., organic light-emitting diode [LED] devices, integrated circuits, and photodetectors) are always applied under constant deformation and large mechanical strain. To supply energy to such stretchable electronic devices, nanosheet-based batteries are gradually applied as power supplies thanks to the stability of electronic properties. Moreover, thanks to the application of nanosheet materials, wearable batteries can be more lightweight. The development of graphene nanosheets has ushered two-dimensional (2D) nanomaterials into the limelight for energy conversion and storage devices ( Tan et al., 2017 ; Xu et al., 2013 ; Zhang, 2015 ). Particularly, as the thickness of 2D nanosheets reduces into a few unit-cell layers, some physical and chemical properties (e.g., bandgap, wettability, in-plane transport) will become distinct from their bulks or rigid and thick nanosheets, and these changes may affect their electrochemical properties for ion transport and storage ( Wu et al., 2014 ). Up to now, a variety of metal oxide nanosheets (e.g., V 2 O 5 , MnO 2 , SnO 2 , Co 3 O 4 , Fe 2 O 3 ) have been successfully fabricated and explored as cathode/anode materials for different types of batteries, including lithium-ion batteries (LIBs), sodium-ion batteries, metal-sulfur batteries, and metal-air/oxygen batteries ( Mei et al., 2018 ; Sun et al., 2016 ; Wu et al., 2014 ). Among them, the Li-ion battery is the market-leading one for energy storage applications, especially for power batteries in stationary power plants and electric/hybrid vehicles as well as consumer batteries in electronics ( Pan et al., 2018 ). Therefore, the investigation toward wearable Li-ion batteries (LIBs) based on nanosheets has become a focused area ( Manthiram, 2017 ). For instance, Hoshide et al. fabricated a flexible Li-ion fiber battery based on the most used LIB material, titanium oxide, but processed into nanosheets by a wet-spinning process ( Hoshide et al., 2017 ). The titanium oxide nanosheets are stacked regularly and hybridized with reduced graphene oxide, another kind of nanosheets, to obtain a novel current collector with high efficiency. The application of nanosheets and the unique stacking structure enable the wearable battery with prominent battery performances including cyclic behaviors, linear densities, and rate capabilities, as well as remarkable mechanical properties, and provide a novel and promising way for the advanced wearable energy storage systems. By applying LiMn 2 O 4 as the cathode, the device exhibits a high working voltage from 3.9 to 4.2 V and a LED of 60 mW can be powered continuously for no less than 5 hours by only a 10-cm hybrid fiber ( Figure 1 i). After 200 cycles at 0.0085 mA, the capacity retention is more than 70%. Besides the TiO 2 nanosheets, molybdenum disulfide (MoS 2 ) nanosheets and gallium chalcogenide (GaX) nanosheets can also be the basic material for wearable LIBs, which demonstrate the great potential of LIBs in future wearable device applications ( Lu et al., 2020 ; Zhang et al., 2017a ). As the market-leading batteries, the production technique of LIBs is mature and achieves low cost. Although the energy density and cyclic behavior of the LIBs are not as good as other kinds of batteries, LIBs are the optimal choice to be first applied as the energy supply components in distinct wearable electronic devices for commercialization. Figure 1 Wearable Li batteries based on nanosheets (i) (a) The Li-ion battery with the ability to continuously light a lamp for no less than 5 h. (b) Voltage output when bending and recovering ( Hoshide et al., 2017 ). (ii) Schematic showing the fabrication procedure of the flexible MSC film ( Zhao et al., 2019b ). (iii) Photos illustrating (a, c) the digital LEDs (b) and a mobile phone powered by the lithium-oxygen battery ( Long et al., 2019 ). However, the energy density of the LIBs is insufficient at 200–250 Wh kg −1 , which prevents the batteries from further applications ( Wu and Cui, 2012 ; Yin et al., 2018 ). Therefore, alternative batteries are needed for the development of wearable devices. Li-sulfur battery with an excellent energy density of 2,600 Wh kg −1 is a promising candidate for the next generation of wearable batteries as it is also environmentally friendly and low cost ( Peng et al., 2017 ). In the work of Zhao et al., conventional cyclo-S 8 was replaced by S 2-4 , small sulfur molecules, to eliminate the shuttle effect, which is the most significant hindrance for the practical application of lithium-sulfur batteries ( Zhao et al., 2019b ). MXene nanosheets are applied as the flexible backbone and conductive binder and combined with S 2-4 /carbon composite to develop a small-sulfur electrode ( Figure 1 ii). Encouraged by the MXene nanosheets and the S 2-4 /carbon composite, the wearable power supply device is found to have excellent electrochemical properties, including a high capability of 1,029.7 mAh g −1 at 0.1 C and satisfactory cyclic behavior (after 200 cycles, the capability maintains 946.7 mAh g −1 with 91.9% retention). Meanwhile, while at 2 C current density, the capability of the electrode is still 502.3 mAh g −1 . In this work, the MXene nanosheets are applied as the flexible backbone and conductive binder, which provides a new strategy for Li-sulfur batteries to be practically applied in wearable device areas and achieve flexibility together with excellent performance. As a result, this MXene-based Li-sulfur battery can be widely applied in wearable electronic devices with the requirements of high energy density and capacity like wearable VR/AR glasses and Google glasses. Except for the Li-sulfur battery, the rechargeable lithium-oxygen battery is also an optimal alternative for wearable applications resulting from its much higher density energy of 3,500 Wh kg −1 than the LIB ( Khetan et al., 2015 ). Long et al. designed a Li-O 2 battery based on CuCo 2 S 4 nanosheets as an electrode with satisfactory efficiency ( Long et al., 2019 ) ( Figure 1 iii). The free-standing CuCo 2 S 4 nanosheets play a significant part in the increase of catalytic properties and the deliberately designed structure further improves the performance. As a result, the Li-O 2 battery possesses the enhanced capability of 9,673 mAh g −1 at 100 mA g −1 , the improved cycle life of 164 cycles and yield lower overpotential of 0.82 V and satisfactory performance under distinct bending and twisting cases. The prominent capability enables the battery to be the wearable power supply device toward the large-energy consumption like smartphones. Lithium is not an abundant element and dozens of alarmists regard it as the next gold in the next century ( Song et al., 2018 ). In addition, the leading market battery, the LIB, is not environmentally friendly, especially when used for less than a thousand cycles ( Larcher and Tarascon, 2015 ). As a result, the earth-abundant multivalent cations (Mg 2+ , Ca 2+ , Zn 2+ , Al 3+ ) attract extraordinary attention to develop polyvalent metal-ion batteries ( Blanc et al., 2020 ). Among them, Zn-ion batteries are investigated most and possess well-developed techniques because Zn is abundant and safe and has large volumetric capacity compared with other elements ( Rajput et al., 2018 ). V 2 O 5 is a welcome material for energy devices because of the low cost of vanadium and high theoretical capacity ( De Juan-Corpuz et al., 2019 ). For instance, a wearable chargeable Zn-ion battery based on V 2 O 5 nanosheets was reported to be developed by Li et al. ( 2019b ). The V 2 O 5 nanosheets are decorated with titanium nitride (TiN) nanowires as (TiN)@V 2 O 5 three-dimensional nanostructures. Such hierarchical core-shell heterostructure was deposited on carbon nanotube fibers (CNTFs) to form the binder-free cathode ( Figure 2 i). Benefit from the TiN nanowires and layered V 2 O 5 nanosheets, the cathode shows great energy storage properties, a large rate capability of 486.8 mAh g −1 (1.11 mAh cm −2 ) at 10 mA cm −2 , and a large capacity of 636.0 mAh g −1 (1.45 mAh cm −2 ) at 0.5 mA cm −2 . Besides, the wearable aqueous Zn-ion batteries deliver a large energy density of 373.0 Wh kg −1 (283.5 mWh cm −3 ), large capacity of 532.9 mAh g −1 (405 mAh cm −3 ), large capacity retention of 90.6%, and remarkable cyclic performance of more than 3,500 cycles. As a result, this power supply device is a promising choice for applications with the requirements of mildly high power consumption and charge-discharge for thousands of times, e.g., wearable sensors and even epidermal sensors for continuous monitoring. Especially, the energy density (373.0 Wh kg −1 ) of such battery is nearly twice higher than the standard of blade electric vehicles in China (125 Wh kg −1 ), which illustrates that such Zn-ion device can fit almost all standards of all electronic devices. More significantly, the unique materials applied, (TiN)@V 2 O 5 structures, endow the Zn-ion battery with integration and flexibility characteristics. Furthermore, V 2 O 5 nanosheets can grow on the titanium substrate ( Javed et al., 2020 ) or be combined with N-doped carbon (NC) nanowall arrays ( He et al., 2019 ) to form the electrode of wearable Zn-ion batteries and improve the energy storage performance of Zn-ion batteries. Bedsides the V 2 O 5 , MoS 2 nanosheet is also a promising candidate for energy storage and conversion applications as the layered structure enables MoS 2 with dramatic ion intercalation capability ( Zhang et al., 2021 ). In the study of Li et al., MoS 2 nanosheets expanded inter-layer spacing (E-MoS 2 ) was first demonstrated as the encouraging cathode materials for rechargeable Zn-ion batteries ( Li et al., 2019a ). The E-MoS 2 nanosheet electrode manifests a prominent energy density of 148.2 Wh kg −1 , desirable cyclic ability over 600 cycles with large capacity retention (98.6%), and a decent capacity of 202.6 mAh g −1 ( Figure 2 ii). With the assistance of the novel starch/polyacrylamide (PAM)-based polymer electrolyte showing outstanding conductivity of Zn ion, the MoS 2 nanosheet-based battery displays satisfactory performance even under distinct huge deformations and paves the way for applications in wearable devices that need large deformations in a prospective view, for example, the wearable sensors mounted at elbow or knee. The high energy density of 148.2 Wh kg −1 is slightly better than the standard of blade electric vehicles in China (125 Wh kg −1 ), which illustrates that such Zn-ion device is a great choice for the miniaturization of electronic devices. In addition, Zhao et al. reported a MnO 2−x nanosheet-based Zn-ion battery and combined it with perovskite solar cells to fabricate a self-powered and flexible waistband system ( Zhao et al., 2021 ). By the lithium treatment to expand the interlayer spacing of MnO 2 nanosheets and combined with the carbon cloth (CC), the MnO 2−x @CC was first developed. Even with large mass loading of more than 25.5 mg cm −2 , the MnO 2−x @CC electrode has outstanding cycle stability up to 5,000 cycles, much improved rate performance, and a specific capacity of 3.63 mAh cm −2 at the current density of 3.93 mA cm −2 . More importantly, the Zn-ion battery achieves ultrahigh safety under various severe conditions and a wide range of temperatures and has been applied to power a wearable smart bracelet. However, the low energy density (5.11 mWh cm −2 ) and the low capacity prevent such Zn-ion battery from commercialization, and after further research toward this MnO 2−x nanosheet-based Zn-ion battery, it shows great potential in applications of self-powered electronic devices that need thousands of charge-discharge cycles. Figure 2 Wearable Zn-ion batteries based on nanosheets (i) Schematic diagram showing the fabrication process of TiN@V 2 O 5 NWAs on a CNTF ( Li et al., 2019b ). (ii) Schematic diagram illustrating the structure of the flexible battery based on starch/PAM polymer electrolyte. ( Li et al., 2019a ). (iii) Safety experiments of the battery under various conditions, including soaking, hammering, cropping, burning, puncturing, and cutting ( Zhao et al., 2021 ). Metal-air batteries are regarded as the optimal candidate for wearable battery applications as the energy density of metal-air batteries is much higher than that of the market-leading batteries, LIBs, and even several times larger than the threshold energy density of LIBs ( Li and Lu, 2017 ; Zubi et al., 2018 ). Among the metal-air batteries, Zn-air and Li-air batteries are the most promising ones. As the Li is not abundant and has a safety hazard, Zn-air batteries show great potential for the alternative of Li-air batteries ( Chi et al., 2021 ; Yu et al., 2020 , 2021 ). For example, Qu et al. conducted a Co 3 O 4 nanosheet-based Zn-air battery array fabricated by an integrated electronic system in a layer-by-layer 2 × 2 structure. The Zn-air battery manifested stable electrochemical behaviors under 100% strain and could be discharged at bending and high-frequency dynamic stretching conditions. After being rearranged of the electrode array, the flexible Zn-air battery array could generate a broad range of voltage from 1 to 4 V. The above-mentioned properties have made it capable for an experiment to power a green light band with 60 LEDs ( Figure 3 i) ( Qu et al., 2017 ). Flexible Zn-air batteries (FZABs) hold remarkable potential in powering flexible electronics in other researches as well. Zhang et al. prepared a flexible Zn-air battery that is assembled with CoNi alloy/NCNSAs/CC-800. 3D hierarchical nanostructure enabled the Zn-air with a significant mechanical cycle ability (charge/discharge cycles at flat and folded states with a low voltage gap of 0.66 V), a high energy density (98.8 mW cm −2 ), as well as a high capacity (879 mAh g −1 ). Two series of Zn-air batteries were assembled to power an “HBU” indicator consisting of 51 red LEDs, which indicated the Zn-air battery was a prominent candidate for electrochemical energy conversion and storage ( Figure 3 ii) ( Zhang et al., 2020 ). For such Li-air and Zn-air batteries, their poor cyclic behaviors of more than 20 and 40 cycles, respectively, are the most significant hindrance for their commercialization. Further research is needed for these two batteries to be applied practically. In addition, the construction of a chargeable Zn-air battery device consisting of RuO 2 and N-doped carbon nanosheets with a liquid electrolyte and BN/C catalyst was proposed by Zhao et al. ( 2020 ) The proposed battery exhibited a peak power density of ∼115 mW cm −2 , a good performance in an open-circuit potential of 1.36 V, and excellent durability (1,000 cycles in 14 days operation). The battery can also be charged under different bending states. Therefore, such wearable Zn-air battery based on N-doped carbon nanosheets displays a great future for application in wearable electronic devices with the need of mildly high capacity as well as energy density and large deformations like wearable sensors mounted at the neck, elbow, or knee. Apart from these works with distinct nanosheets, many other nanosheets including reduced graphene oxide nanosheets and zeolitic imidazolate framework nanosheets ( Li et al., 2018b ; Zhao et al., 2019d ) have been applied to be the basic materials for Zn-air batteries, which demonstrates that Zn-air batteries are the most attractive ones for the future wearable batteries. Figure 3 Wearable Zn-air batteries based on nanosheets (i) (a-c) Exploded view of the layout of the various layers in the Zn-air battery array structure (# 4 in parallel, # 2 in series & 2 in parallel, and # 4 in series), with open-circuit voltages of 1.35, 2.6, and 5.5 V, respectively. (d) Charge-discharge curves of the three types of such arrays at a current density of 2 mA cm −2 , with each cycle being 40 min. (e) Photograph of a Zn-air battery array (# 4 in parallel) sewn on clothes to light a LED band (scale bar, 2 cm). (f) Photograph of the array (# 4 in parallel) being stretched and bent by body movement ( Qu et al., 2017 ). (ii) (a) Schematic illustration showing components of FZABs, and (b) photograph. (c) Photographs of an “HBU” indicator including 51 red LEDs, which obtain power through a wearable bracelet with two-series FZABs ( Zhang et al., 2020 ). Besides Li-based and Zn-based batteries, Kong et al. found that quasi-solid-state Nickel-Fe batteries (QSS-NFBs) demonstrated an ultrahigh energy density and excellent cycling stability as well. The QSS-NFB was fabricated by 3D printing. With the compressible feature, the QSS-NFB is expected to be applicable in next-generation stretchable electronics ( Kong et al., 2020 ). Another flexible Ni-Fe battery based on NiCoP nanosheets was also listed in the work of Yang et al. with negligible capacity loss, significant capacity, and high energy density ( Yang et al., 2020 ). The prominent charge-discharge cyclic behaviors of over 10,000 cycles and 4,000 cycles, respectively, for such two Ni-Fe batteries demonstrate an excellent promise in the use of technological gadgets that need a large number of charging-discharging times. The low capacity and energy density of the Ni-Fe battery of Yang et al., however, preclude its commercialization and practical application and more work is urgently required. Nanosheet-based wearable supercapacitors Together with nanosheet-based batteries, nanosheet-based supercapacitors, particularly stretchable all-solid-state supercapacitors, make great contributions to wearable electronics as well due to the rapid charge-discharge rates, high power density, and excellent cycling stabilities ( An and Cheng, 2018 ; Augustyn et al., 2014 ; Brezesinski et al., 2010 ). In addition, tens of thousands of cycle life together with the application of the nontoxic aqueous electrolytes in supercapacitors make the supercapacitors more suitable for wearable electronic devices with the requirements of the long-term application and environmental friendliness. However, although the high cyclic behavior, the power density of supercapacitors is relatively lower than that of the traditional batteries, which greatly prevents the supercapacitors from further application of wearable devices ( Muralee Gopi et al., 2020 ). Therefore, nanosheet materials with a high surface-to-volume ratio and thus more energy storage and electrocatalyst sites are applied to address this problem. For instance, Song et al. prepared a solid-state supercapacitor electrode by decorating Ni(HCO 3 ) 2 nanosheets to flexible PVA/carbon nanotube ( Song et al., 2019 ). The prepared device with remarkable stretchable and bendable ability exhibited an instant response to the finger bending with the capacitance variation of more than 35% ( Figure 4 i), which proved the potential of composite nanomaterials as wearable devices and the potential of the device as the wearable sensors at fingers. Besides the Ni(HCO 3 ) 2 nanosheets, which can improve the electrochemical performance of the supercapacitors, NiCO 2 S 4 , and NiCO 2 O 4 nanosheets as battery-type materials are the potential Faradaic redox materials owing to their ability to offer improved electrochemical performance, excellent redox activity, and outstanding capacity values ( Conway, 2013 ). For example, Shao et al. conducted a stainless-steel meshes (SSMs)-based supercapacitor that was obtained by covering CoS 2 nanowires onto NiCo 2 S 4 nanosheets in situ ( Shao et al., 2020 ). The SSM-based supercapacitor manifested prominent performances with respect to a remarkable tensile recovery (≤40% elongation), high energy density (60.2 Wh kg −1 at 800 W kg −1 ), and high stability (≈76.4% capacity retention at 30% strain for 1,000 stretching cycles). The highly flexible supercapacitor was sewn on the elbow of a garment to power a LED, which demonstrated its high applicability to wearable electronics like wearable sensors or electric light installed on the elbow of a garment ( Figure 4 ii). In the work of Sundriyal et al., MnO 2 –NiCo 2 O 4, and rGO were applied as the positive and negative electrodes, respectively, to form a solid-state supercapacitor ( Sundriyal and Bhattacharya, 2020 ). The formed supercapacitor was fabricated by a replicable printing process with different metal oxide inks on the bamboo fabric substrate. Notably, the supercapacitor showed remarkable electrochemical performances under various mechanical deformation conditions including a finger bending test, which demonstrated its excellent mechanical strength and flexibility ( Figure 4 iii). The ink-printed technique endows the solid-state supercapacitor with various shapes and paves the way for the future self-design of wearable power supply devices. Moreover, Zhao et al. and Wang et al. also reported the wearable supercapacitors based on NiCo 2 S 4 nanosheets and NiCo 2 O 4 nanosheets, respectively ( Wang et al., 2014 ; Zhao et al., 2019c ), which demonstrates the great potential of NiCo 2 S 4 nanosheets and NiCo 2 O 4 nanosheets in the field of wearable power supply. Figure 4 Wearable solid-state supercapacitors based on nanosheets (i) (a) Photographs of the supercapacitor fixed onto the index finger; (b) cyclic stability of supercapacitor ( Song et al., 2019 ). (ii) Schematic illustration showing (a) SSM together with (b) the stainless-steel plain cloth. (c) SEM image of SSM. (d) Image of a hollow tube of SSM under the size of 3 cm × 3 cm at natural state. (e) SSM knitted applying a modified Raschel warp knitting machine ( Shao et al., 2020 ). (iii) Schematic diagram illustrating the construction of printed MnO 2 –NiCo 2 O 4 electrode over the bamboo fabric ( Sundriyal and Bhattacharya, 2020 ). Fiber-shaped supercapacitors are more intriguing owing to their better flexibility and smaller volume and thus have easier wearability compared with the conventional solid-state supercapacitors ( Li et al., 2020 ; Lim et al., 2017b ; Liu et al., 2015 ; Yu et al., 2016 ; Zhao et al., 2019a ). In the research of Zong et al., a fiber-shaped asymmetric supercapacitor (FASC) based on carbon nanotube fibers (CNTFs), MoS 2, and MnO 2 nanosheets was developed ( Zong et al., 2018 ). The MnO 2 nanosheets are doped with Na and grown on the carbon nanotube fibers to form the positive electrode, while MoS 2 nanosheets-coated carbon nanotube fibers are applied as the negative electrode. Thanks to the unique design of electrodes, such fiber-shaped supercapacitors manifest an excellent specific capacitance (265.4 mF cm −2 ) and a high operating potential window of up to 2.2 V ( Figure 5 i). However, the poor energy density (178.4 μWh cm −2 ) of such fiber-shaped supercapacitors hinders them from commercialization and only the wearable electronic devices with low-power consumption like a wearable electronic watch can apply such fiber-shaped supercapacitor. Besides, reported by Li et al., MnO 2 nanosheets can also be combined with single-wall carbon nanotubes (SWCNTs) to form the electrode of a wearable capacitor with an ultrahigh energy density of 10.4 mWh cm −3 , the excellent volumetric capacitance of 74.8 F cm −3 , as well as outstanding cyclic stability of more than 5,000 cycles, all of which illustrate a bright future for application in distinct kinds of wearable electronic devices, especially in the wearable devices with the need for high capacity as well as cyclic behaviors like Google glass. ( Li et al., 2018a ). In addition, Shi et al. facilely synthesized the Ni(OH) 2 nanosheets, the average thickness of which is 2 nm, and after that embedded the nanosheets on the carbon nanotubes to develop the electrode of a fiber capacitor ( Figure 5 ii) ( Shi et al., 2018b ). The Ni(OH) 2 nanosheets/carbon nanotubes nanostructure not only enables the electrode with superior rate performance, as well as an excellent volumetric capacitance (335.9 F cm −3 at the current density of 0.8 A cm −3 ), but also endows the hybrid supercapacitor with satisfactory mechanical stability after repeated bending experiments for 5,000 bending-unbending cycles, an outstanding energy density (5.8 mWh cm −3 ), as well as a dramatic specific capacitance (24.8 F cm −3 ). The excellent cyclic behavior in the bending experiment illustrates that the hybrid supercapacitor can be applied in wearable devices that need to bend thousands of times, e.g., wearable sensors worn on the elbow or knee. Moreover, MnO 2 and vertical graphene nanosheets were applied as the basic materials for a fiber-shaped supercapacitor, which was constructed by Zhou et al. ( 2021 ). After growing the vertical graphene nanosheets (VGNs) on ductile nickel wires, MnO 2 was deposited on the nanostructure of VGNs/NiWs ( Figure 5 iii). With the help of the solid-state electrolyte consisting of sodium sulfate and carboxymethylcellulose, a moldable supercapacitor can be developed by the two electrodes. Result from the synthesis of MnO 2 as well as the VGNs, the supercapacitor delivers a high areal power density (5 mWh cm −2 ), areal energy density (7.7 mWh cm −2 ), and areal capacitance up to 56 mF cm −2 . The following bending and twisting tests also illustrate the great mechanical properties of such supercapacitor as there is little loss of performance after molding into various shapes by twisting and bending and show great potential of such supercapacitor in practical application of wearable sensors worn on the elbow, neck, or knee. Figure 5 Wearable fiber-shaped supercapacitors based on nanosheets (i) A detailed illustration of the FASCs ( Zong et al., 2018 ). (ii) (a) Schematic of the development of the Ni(OH) 2 /CNT nanostructure. (b) Scanning electron microscopy (SEM) images as well as EDS mapping of the hybrid fiber of Ni(OH) 2 /CNT. (c) The conductivity of the Ni(OH) 2 /CNT nanofiber structure with various loads of the nanosheets with 20, 40, 60, and 80 wt%, respectively ( Shi et al., 2018b ). (iii) Schematic illustration of construction procedure of the fiber-shaped supercapacitors ( Zhou et al., 2021 ). The development of wearable nanosheet-based supercapacitors is still immature. Although some researches have not progressed to the point of wearability, they have delivered great potential in wearable electronic devices. Chang et al. combined 3D printing with electrodeposition to print a CoNi 2 S 4 /NiCo-LDHs nanocomposites-based supercapacitor ( Figure 6 i) ( Chang et al., 2020 ). The combined stretchable symmetric supercapacitor exhibited a superior capacitance of 28.71 F cm −3 and satisfactory stability in stretching and bending cycles. The above properties are highly comparable with previously reported stretchable supercapacitors. The relatively low energy density of 0.582 mWh cm −3 indicates there should be further research toward such stretchable supercapacitors. In the work of Ding et al., homogeneously distributed α-Fe 2 O 3 nanobelt arrays were reported to fabricate a stretchable and flexible electrode ( Figure 6 ii) ( Ding et al., 2020 ). In the experiments, the reported supercapacitor possessed a great stretchability and excellent flexibility together with a high specific areal capacitance. This study opens a new way to the designing method of next-generation wearable electronics. In addition, Huang et al. fabricated a facile hierarchical NiCo 2 S 4 @NiCu−LDH nanotube/nanosheet hybrid supercapacitor on carbon cloth by a solution-based strategy in multistep. The NiCo 2 S 4 @NiCu−LDH had a volumetric energy density up to 2.7 mWh cm −3 , a power density of 21.3 mW cm −3 , and long-term cycling robustness over 2000 cycles. This work exhibited the possibility of designing and fabricating nickel-based LDHs as supercapacitors toward highly efficient and durable soft energy storage devices ( Figure 6 iii) ( Huang et al., 2020 ). Furthermore, a carbon nanosheet-based large-area supercapacitor was proposed by Jun et al. The exceptional mechanical stability of the capacitor was confirmed. As a result, only an approximate 15% increase in the electrical resistance was measured under a tensile strain of 100%. The initial resistance was fully recovered after release, which met requirements for wearable electronics ( Jun et al., 2018 ). Besides, lots of other materials have been applied in constructing nanosheet-based supercapacitors such as MoS 2 nanosheets on spindle-like α-Fe 2 O 3 , Cu@Ni@NiCoS nanofibers network based on Ni-Co-S nanosheets, and carbon nanotube-MnO 2 nanocomposite film based on MnO 2 nanosheet, which are reported by Man et al., Soram et al., and Wang et al., respectively ( Man et al., 2020 ; Soram et al., 2020 ; Wang et al., 2019 ). Figure 6 Nanosheet-based supercapacitors showing great potential in wearable applications (i) Schematic diagram illustrating the fabrication process of 3D-printed stretchable CoNi 2 S 4 /NiCo-LDHs/Ni/PL electrode as well as the construction procedure of the supercapacitor ( Chang et al., 2020 ). (ii) (a) Photo of a cotton T-shirt for sale; (b) digital photographs of the color changes of a piece of pristine cotton textile cut from the T-shirt before (left) and after alkaline activation, Fe 3+ infiltration, and the resulting Fe 2 O 3 nanobelts/NPCTT; (c) schematic illustration of fabrication procedure of the Fe 2 O 3 /NPCTT. The schematic illustrations below present detailed changes of the surface layer for a single fiber and the features of the grown nanostructures at various steps ( Ding et al., 2020 ). (iii) Schematic diagram showing the various production stages of NiCo 2 S 4 @NiCu-LDH nanostructure on carbon cloth ( Huang et al., 2020 ). Nanosheet-based wearable self-powered energy suppliers Keeping up with the developments of batteries and supercapacitors, the use of self-powered energy suppliers is indispensable for generating wearable electronics ( Alam and Ramakrishna, 2013 ; Buscema et al., 2013 ). In the past decade, triboelectric nanogenerators (TENGs) and piezoelectric nanogenerators (PENGs) have gained massive attention owing to their exceptional capability to transfer mechanical energy to electric power ( Gao et al., 2017 ; Karan et al., 2016 ; Kim et al., 2014 ; Ku et al., 2017 ; Seung et al., 2017 ; Tsai et al., 2017 ; Zhou et al., 2018 ). PENGs have become a hot research field for nanosheet-based self-powered energy suppliers owing to their unique merits of mechanical-electrical energy conversion capability, lightweight, low cost, and easy manufacturing, which can harvest various types of mechanical energy by utilizing the piezoelectric effect. By applying nanosheets as the alternative to conventional materials, the power production performance of PENGs increases dramatically. For example, in the work of Shi et al., a PENG with high output and good flexibility was proposed ( Shi et al., 2018a ). The proposed PENG was fabricated by using electrospun nanocomposite fiber mats comprising graphene nanosheets, barium titanate (BT) nanoparticles, and poly(vinylidene fluoride) (PVDF). The open-circuit voltage generated by the PENG can reach as high as 11 V under a loading frequency of 2 Hz and a strain of 4 mm with no obvious decline of the open-circuit voltage. In addition, the PENG generated a peak voltage as high as 112 V during a finger pressing-releasing process, which can light up 15 LEDs and drive an electric watch. The PENG can also be activated by movements of different parts of the human body including wrist bending, finger tapping, and foot stepping by heel and toe ( Figure 7 i). As a result, the PENG can provide the power for the wearable devices mounted at various body parts including finger, feet, elbow, and knee. Moreover, Tsai et al. applied vertically oriented graphene nanosheets to grow and transfer the aligned single-crystalline GaN nanorods (NRs) so that a transparent flexible PENG with an output current of 1.2 mA and an ultrahigh output voltage of more than 8 V can be obtained ( Tsai et al., 2018 ). Figure 7 Wearable piezoelectric nanogenerators based on nanosheets (i) Photographs together with voltage output produced through human motions for (a) wrist bending, (b) finger tapping, together with foot stepping by (c) heel as well as (d) toe ( Shi et al., 2018a ). (ii) (a) Voltage output of four nanogenerators connected in series, (b)–(d) photog of the experiments of foot pressure, bending, muscle stretching, respectively, for the nanogenerator in real time ( Manjula et al., 2020 ). (iii) (a) Wearable PENG deposited at the wrist joint and its corresponding output signal. 10 (b) Wearable PENG attached onto finger joint and its electrical output signal ( Rafique et al., 2021 ). (iv) Current output signal (a) while the page turning forward and (b) turning back. (c-d) The ability of the LCD screen to connect with the PENGs while turning the page. (e) After releasing or bending for 10,000 cycles, the current output remains stable. The inset image illustrates the break strength of the V-ZnO/BC film compared with the print paper as well as the regenerated BC paper ( Zhang et al., 2018a ). Applied most, ZnO nanosheets are the most promising material for PENGs because ZnO nanosheets not only display outstanding biological compatibility compared with other materials for piezoelectricity, environmental friendliness, pyroelectricity, as well as excellent piezoelectricity ( Theerthagiri et al., 2019 ; Yang et al., 2012 ) but also can be produced by the one-step process ( Zhang et al., 2017b ), all of which make the ZnO nanosheets the most applied in PENGs ( Manjula et al., 2020 ; Rafique et al., 2021 ; Wang et al., 2018 ; Zhang et al., 2018a ). For instance, in the work of Manjula et al., a flexible PENG based on ZnO nanosheets was fabricated ( Figure 7 ii) ( Manjula et al., 2020 ). On a flexible Al substrate with a low growth temperature of 80°C, a one-step, facile, and cost-effective synthesis hydrothermal method was applied to prepare the Zn nanosheet networks. The wearable device can output 100 mA for a single device and 400 mA for four devices connected in series. A reasonable output voltage is obtained and the simple production method used illustrates a bright future of ZnO nanosheets for wearable nanogenerators. In addition, Wang et al. reported a two-stage preparation process of 2D ZnO nanosheets ( Wang et al., 2018 ). With the assistance of the ZnO nanosheets, the current output of the PENG increased from ∼40 nA to ∼0.15 μA compared with the conventional PENG based on one-dimensional nanowires under the same compressive load of 1 kgf. Besides, it is demonstrated that, with the thinner of the nanosheets, the output performance of the PENG becomes better. In the work of Rafique et al., by doping Br into the ZnO nanosheets through a simple hydrothermal process on nanoporous anodic aluminum oxide (AAO) template, the output voltage of the PENG based on ZnO nanosheets can reach 8.82 V at a frequency of 6 Hz ( Figure 7 iii) ( Rafique et al., 2021 ). Besides, vanadium can also be doped into ZnO nanosheets to improve the performance of the wearable PENGs based on ZnO nanosheets, and in the work of Zhang et al., the output voltage of the wearable device can reach 1.5 V ( Figure 7 iv) ( Zhang et al., 2018a ). Although the output voltage and output current are relatively lower for these ZnO nanosheet-based PENGs, these researches pave the way for the wide application of wearable PENGs based on ZnO nanosheets in the piratical energy harvest field with the development of techniques. TENGs are developed on the basis of the coupling mechanism between the electrostatic as well as the triboelectric charge to achieve energy production and this energy is one of the most common power in our surrounding environments ( Zhou et al., 2020 ). The features of ease to access, satisfactory power density, and low cost lead to the wide application in the power supply industry ( Kang et al., 2019 ; Liu et al., 2019 ). For instance, Lim et al. conducted a highly durable TENG that was based on gold-nanosheet (AuNS) electrodes ( Lim et al., 2017a ). It was found that the novel design of the AuNS electrodes highly improved the mechanical flexibility, enabling one to achieve the remarkable output stability of the AuNS electrode-based TENG. The conducted AuNS-TENGs are successfully employed in the self-powered human-motion detection for wearable electronics and exhibit ultrahigh voltage output of up to 98.9 V and output stability up to 10,000 cycles ( Figure 8 i). Moreover, in the study of Lan et al., MoS 2 nanosheets were wrapped by the silver nanowires (AgNWs) to form a high conductive nanocomposite ( Lan et al., 2019 ). Thanks to such unique structure, the composite film exhibits outstanding conductivity as well as flexibility and enables the stretchable triboelectric nanogenerator (sTENG) formed by such nanocomposite with ultrahigh output voltage up to 95.8 V at a 30 Hz frequency with the 2.5-cm 2 contact area, output stability more than 10,000 cycles, which is similar to TENG in the work of Lim et al., and prominent stretchability for 50% ( Figure 8 ii). The stretchability of the sTENG is so high that such sTENG illustrates great potential for application in smart cloth or smart shoes. MXene nanosheets with outstanding mechanical and hydrophilic properties ( Yang et al., 2019c ) are also a reasonable basis material for TENG. By integrating the poly(vinyl alcohol) (PVA) with MXene nanosheets for the electrospinning nanofibers, a kind of novel flexible all-electrospun TENG based on MXene nanosheets was fabricated ( Jiang et al., 2019 ). Owing to the high biocompatibility and triboelectricity, silk fibroin (SF) is applied as the electrospinning nanofibers. As a result, the MXene-based nanogenerator manifests a remarkable output voltage of 117.7 V, extremely high durability of 124,000 cycles, as well as peak power density of 1,087.6 mW m −2 , all of which enable such MXene-based nanogenerator with deep potential for applications in all kinds of wearable electronic devices. Surprisingly, reported by Shi et al., the application of graphene nanosheets and polyvinylidene fluoride (PVDF) in TENG can obtain a dramatic peak power density of ∼130.2 W m −2 and output voltage of ∼1511 V ( Shi et al., 2021 ). Figure 8 Wearable triboelectric nanogenerators based on nanosheets (i) Optical images and output as the function of voltage responses to the repeated bending/relaxation of the triboelectric nanogenerator that was attached onto the (a, b) index finger, (c, d) knuckle, and (e, f) wrist, respectively ( Lim et al., 2017a ). (ii) Output voltage of stretchable triboelectric nanogenerator with the size of 1 cm × 2.5 cm. (a) Output VOC of stretchable triboelectric nanogenerator at various forces under a fixed 10 Hz frequency. (b) Output VOC of stretchable triboelectric nanogenerator at distinct frequencies under a fixed force of 10 N. (c) Voltage and current output under various load resistances related to stretchable triboelectric nanogenerator. (d) Output power density under different resistances of the external loads ( Lan et al., 2019 ). Besides nanogenerators that are mounted on mechanical energy conversion (PENGs and TENGs), nanosheet-based thermoelectric generators are competitive as well to power wearable devices. This is because the human body is a stable power source (about 36.5°C) to assist attaching devices to produce direct current (DC) electric power ( Liu et al., 2017 ; Ma et al., 2016 ; Meng et al., 2010 ). Oh et al. demonstrated an intrinsically stretchable and foldable thermoelectric generator that is based on chemically exfoliated 1T-transition metal dichalcogenide (TMDC) nanosheets (NSs). The conducted thermoelectric generator was able to constantly produce an output power up to 38 nW at Δ60 K. After 100 bending cycles and 100 stretching cycles of 50% strain, the thermoelectric device stably sustained its performance. A thermoelectric generator for a glove-type wristband has proved its compatibility in wearable applications ( Figure 9 i) ( Oh et al., 2016 ). Moreover, Kim et al. constructed a multi-stacked metal dichalcogenide (TMD) nanosheet-based thermoelectric generator. The constructed generator possessed a high thermoelectric power factor of 47 μW K −2 m, which is capable of powering wearable devices ( Kim et al., 2019 ). The commercialization of thermoelectric generators still needs a lot of further work. However, thermoelectric generators hold the brightest future as the power supply is stable and consistent compared with PENGs and TENGs. Figure 9 Wearable thermoelectric generators and solar cells based on nanosheets (i) A wearable thermoelectric generator for a glove-type wristband. (a) Output voltage generated from the heat of a human wrist at room temperature. The inset photos represent the device configuration and the operating situation. (b) Output power produced from 16 units in series with multi-stacked units in parallel ( Oh et al., 2016 ). (ii) (a) Schematic illustrating the QDSCs based on CuS TCEs; (b) SEM images of the side view and the top view of the TNARs on Ti foil; (c) Raman spectra of the CdSe/CdS co-sensitized TNARs ( Xu et al., 2017 ). Wearable power supply devices can also benefit from flexible solar cells. As solar energy is an abundant, green, and inexhaustible energy resource, it has attracted great interest, especially in the wearable industry. Xu et al. presented a flexible quantum-dot solar cell (QDSC) based on CuS-nanosheet networks, which is highly transparent and flexible ( Xu et al., 2017 ). The networks are applied as the counter electrode, and the sheet resistance of the networks is 50 Ω sq -1 at 85% transmittance. CuS nanosheet networks are applied as prominent catalysts for reducing polysulfide (S 2− /S x 2− ) electrolytes, as well as conducting films in order to collect electrons from external circuits ( Figure 9 ii). As a result, this QDSC displays a high power conversion efficiency of 3.25% and satisfactory stability after bending for 500 cycles. It is believed that this CuS nanosheet-based solar cell with high flexibility, transparency, conductivity, and catalytic activity will be widely employed in wearable electronic devices like solar vests to supply power for every wearable electronic device. In the work of Arbab et al., a wearable all-carbon dye-sensitized solar cell (C-DSSC) was constructed ( Arbab et al., 2020 ). The carbon front electrode demonstrates great sheet conductivity and 50% light transmittance, while the counter electrode dip-coated with graphene oxide nanosheet displays a decreasing charge transfer resistance of 0.79 Ω cm 2 and outstanding electrocatalytic activity. C-DSSC's sustainable design achieves a 6 ± 0.5% efficiency with a high photocurrent density of 18.835 mA cm 2 . The enhanced charge mobility, reduced internal resistance, and improved interfacial electrode contact of C-DSSC are credited with its superior performance. Resulting from the application of graphene oxide nanosheet, C-DSSC is 3 mm thick so that no stiff glass is required in the dye-sensitized solar cell. There are still many obstacles to overcome, such as improving mechanical strength and electrical conductivity. Therefore, additional work has to be done in order to expand the use and achieve the commercialization of nanosheet-based wearable solar cells."
} | 15,973 |
30421473 | null | s2 | 7,572 | {
"abstract": "Scale-invariant timing has been observed in a wide range of behavioral experiments. The firing properties of recently described time cells provide a possible neural substrate for scale-invariant behavior. Earlier neural circuit models do not produce scale-invariant neural sequences. In this article, we present a biologically detailed network model based on an earlier mathematical algorithm. The simulations incorporate exponentially decaying persistent firing maintained by the calcium-activated nonspecific (CAN) cationic current and a network structure given by the inverse Laplace transform to generate time cells with scale-invariant firing rates. This model provides the first biologically detailed neural circuit for generating scale-invariant time cells. The circuit that implements the inverse Laplace transform merely consists of off-center/on-surround receptive fields. Critically, rescaling temporal sequences can be accomplished simply via cortical gain control (changing the slope of the f-I curve)."
} | 253 |
37687867 | PMC10490608 | pmc | 7,573 | {
"abstract": "In reinforcement learning, the epsilon (ε)-greedy strategy is commonly employed as an exploration technique This method, however, leads to extensive initial exploration and prolonged learning periods. Existing approaches to mitigate this issue involve constraining the exploration range using expert data or utilizing pretrained models. Nevertheless, these methods do not effectively reduce the initial exploration range, as the exploration by the agent is limited to states adjacent to those included in the expert data. This paper proposes a method to reduce the initial exploration range in reinforcement learning through a pretrained transformer decoder on expert data. The proposed method involves pretraining a transformer decoder with massive expert data to guide the agent’s actions during the early learning stages. After achieving a certain learning threshold, the actions are determined using the epsilon-greedy strategy. An experiment was conducted in the basketball game FreeStyle1 to compare the proposed method with the traditional Deep Q-Network (DQN) using the epsilon-greedy strategy. The results indicated that the proposed method yielded approximately 2.5 times the average reward and a 26% higher win rate, proving its enhanced performance in reducing exploration range and optimizing learning times. This innovative method presents a significant improvement over traditional exploration techniques in reinforcement learning.",
"conclusion": "6. Conclusions This paper presents a method to address the challenge of initial exploration in reinforcement learning by utilizing a transformer decoder. The proposed approach involves two stages: pretraining the transformer decoder using expert data and subsequent training using reinforcement learning. Specifically, actions are selected using the pretrained Transformer decoder, and the action policy is updated during the initial exploration phase of reinforcement learning based on the threshold δ. Subsequently, the traditional epsilon-greedy strategy is employed for learning. This method effectively mitigates the prolonged learning times associated with reinforcement learning, which result from extensive exploration during the initial phase, by leveraging a transformer decoder pretrained with expert data. The experiment was conducted using the basketball game FreeStyle1, where a comparison was made between the traditional DQN model and a DQN model augmented with the pretrained transformer decoder. When trained for the same number of episodes, the DQN with the transformer decoder achieved a reward per episode that was approximately 150% higher. Moreover, in games where three agents utilized the traditional DQN and the remaining three employed the DQN with the transformer decoder, the latter exhibited an approximately 26% higher win rate. Through this paper, we expect to arouse people’s interest by creating an AI that moves according to the player’s actions rather than mechanically. Additionally, it can be applied not only to the game field but also to various fields such as sensor data in health care, finance, and education.",
"introduction": "1. Introduction Reinforcement learning, a prominent machine learning method, involves an agent receiving rewards for actions taken and selecting actions to maximize these rewards [ 1 ]. It has witnessed significant progress through the application of deep learning and finds extensive use in gaming [ 2 , 3 , 4 , 5 ], robot control [ 6 , 7 , 8 , 9 ], and autonomous driving systems [ 10 , 11 , 12 , 13 ]. Gaming, in particular, benefits from reinforcement learning as it allows visual recognition of game screens as states and a clear definition of rewards, making it more intuitively manageable. Consequently, the field of gaming has seen a wide range of reinforcement learning research employing deep learning techniques, achieving performance comparable to that of humans [ 14 , 15 , 16 ]. Subsequent studies have explored action execution methods to enhance the naturalness and evolution of AI characters in games, further increasing players’ interest [ 17 , 18 , 19 ]. Exploration is a crucial aspect of reinforcement learning [ 1 ]. Agents need to visit various states and identify the optimal actions to learn the optimal policy, which necessitates exploration. Traditional reinforcement learning achieves exploration by randomly selecting actions using the epsilon-greedy strategy. However, in scenarios with a high number of actions, the action space becomes large, leading to prolonged learning times. Thus, there is a need for a method that reduces the exploration range of the agent’s state space during the early stages of exploration. Methods have been proposed to address the exploration range issue in reinforcement learning by leveraging expert data. One approach involves narrowing the exploration range through statistical measures based on expert data when a significant discrepancy exists between predicted and actual actions during the agent’s exploration and learning process [ 20 ]. However, this approach has limitations as it cannot learn about states or actions not included in the expert data. Another method initiates and learns episodes based on consecutive states included in the expert data [ 21 ], but it restricts exploration to states within or adjacent to the starting positions found in expert data. Combining expert data with replay memory is another approach [ 22 ], wherein expert data are stored in replay memory and used alongside the agent’s experience, prioritizing learning from the expert data. However, this method presents challenges such as the need for large replay memory capacity and the risk of overfitting to the expert data. Methods utilizing expert data for pretraining [ 23 , 24 , 25 ] enhance the representation power of neural networks in reinforcement learning through the use of pretrained models. These models are then employed for reinforcement learning after pretraining on expert data. However, these methods primarily focus on improving sample efficiency and generalization capabilities by utilizing pretrained models from different domains, rather than directly addressing the initial exploration problem in reinforcement learning. In other words, they effectively learn image representations through pretraining and utilize them to select better actions during reinforcement learning. Furthermore, since these methods directly utilize pretrained models on expert data as deep learning models for reinforcement learning, they are susceptible to overfitting. Therefore, there is a need for a method that directly reduces the initial exploration range across the entire state space using expert data, while mitigating overfitting and improving action prediction accuracy through a pretrained model. This paper proposes a method to address the issue of extended learning time during initial exploration in reinforcement learning by employing a transformer decoder pretrained through supervised learning with massive expert data. Initially, the agent’s actions are determined by the pretrained transformer decoder based on expert data. To prevent overfitting, once a certain level of learning is achieved, the epsilon-greedy strategy is employed to perform random actions and actions derived from the reinforcement learning model, facilitating policy learning. By learning the policy through expert data, the exploration range can be reduced while considering the entire state space. Additionally, using the transformer decoder as a pretrained model allows for the consideration of consecutive states while mitigating the long-range dependency problem encountered in models based on Recurrent Neural Networks (RNN). Therefore, in contrast to existing methods that primarily use pretraining to improve sample efficiency and generalization capabilities, the proposed method directly addresses the initial exploration problem in reinforcement learning. Furthermore, this method promotes learning and reduces the risk of overfitting by judiciously incorporating a pretrained model into the reinforcement learning process. The main contributions of the proposed method are as follows: Enhancing action prediction ability by leveraging the transformer decoder as a pretrained model. Reducing the exploration range while considering the entire state space, rather than limiting exploration to adjacent states included in the expert data. Mitigating overfitting, reducing the initial exploration range, and shortening the learning time by employing the pretrained model of the transformer decoder, which helps guide agent actions for a certain episode before the reinforcement learning model is employed. The remainder of this paper is organized as follows. Section 2 discusses the related research pertaining to the proposed method. Section 3 provides a detailed explanation of the proposed method. Section 4 presents the learning environment and various experimental results. Finally, Section 5 summarizes the proposed method, highlights the experimental results, and discusses the anticipated benefits.",
"discussion": "5. Discussion The proposed method does not modify the reward and penalty structure used in the underlying DQN model. Instead, it alters the action selection mechanism during the initial exploration phase. Regardless of whether an action is chosen based on the pretrained transformer decoder or according to the epsilon-greedy strategy, the received reward or penalty remains unaffected. In this way, our method maintains the inherent structure of the reinforcement learning process while striving to improve initial exploration problem and model performance. Our method relies on the availability of reliable expert data. Therefore, in cases where such data are not available or is unreliable, the application of our method could be limited. Additionally, our method assumes that the overall situation can be encapsulated in data, some of which can be expressed as images. For example, the coordinates of the agents may be requested. Thus, in scenarios where such data representation is not feasible, the implementation of our method might not be suitable. In this paper, we use expert data to guide the initial exploration, which allows us to reduce the exploration in reinforcement learning and potentially shorten the learning time. However, a potential downside of our method is that if the quality of the expert data, which we assume as ground truth, is not good, then a lot of time may be spent in exploration. This may require more exploration to find the optimal action compared to traditional reinforcement learning methods. The proposed method performs well with structured data like images. However, to apply this method to more complex data like natural language, additional considerations would be necessary. For instance, we would have to use specific techniques for processing language (like word embeddings or deformed model) to transform the data into a form that our model can handle. We plan to explore these ideas further in our future work. Future work could extend upon the proposed method by applying it to various other reinforcement learning algorithms like Proximal Policy Optimization (PPO) or Actor-Critic methods. These algorithms, which involve policy gradient methods, could potentially benefit from an initial policy derived from our method. The proposed method in this paper can be applied across various fields. In healthcare, it could potentially be applied to predictive healthcare models. Using historical patient data or sensor data as expert data, it could learn to predict disease progression or patient outcomes, informing treatment strategies. Similarly, in finance, the proposed technique could be employed in optimizing trading strategies, where historical trades could be treated as expert data. It could potentially learn from the most successful past actions to suggest profitable future trades. We hope that our method will be useful in a variety of scenarios represented by these examples."
} | 3,000 |
39937909 | PMC11817932 | pmc | 7,574 | {
"abstract": "Memristive in-memory computing has demonstrated potential for solving matrix equations in scientific computing. However, the inherent inaccuracies of analog mechanisms create challenges in achieving high-precision solutions while maintaining low-energy consumption. This study introduces a memristive matrix equation solver that considerably accelerates solutions by performing mathematical iterations directly within an analog domain. Our approach facilitates rapid approximate solutions with a scalable circuit topology and expedites the high-precision refinement process by substantially reducing the digital-to-analog conversion overhead. We experimentally validated this methodology using a heterogeneous computing system. We performed simulations of multiple scientific problems on these circuits, including solving the diffusion equation and modeling equilibration in silicon P-N junctions. Notably, our memristive solver, combined with digital refinement, achieved software-equivalent precision (with an error of 10 −12 ). Compared to conventional digital processing units, this approach offered a 128-fold improvement in solution speed and a 160-fold reduction in energy consumption. This work establishes a foundation for future scientific computing using imprecise analog devices.",
"introduction": "INTRODUCTION Modern scientific and engineering simulations span a wide range of fields, from microscale phenomena to macroscale systems, including density functional theory, technology computer-aided design, and computer-aided engineering. These simulations inherently involve solving partial differential equations (PDEs) ( 1 , 2 ), which are typically converted into matrix equations using mathematical discretization methods ( Fig. 1A ) ( 3 ). Consequently, solving matrix equations efficiently is central to contemporary computational modeling techniques. In high-precision simulations, modern computing systems face increasing demands for solving complex, high-dimensional matrix equations. However, mainstream digital computers are constrained by the high polynomial-time complexity of digital solution methods, such as iterative algorithms [typically O( N 3 ), where N represents the problem size]. In addition to the von Neumann bottleneck—stemming from the separation architecture of memory and processing units further exacerbates processing time and energy consumption ( Fig. 1B ) ( 4 – 6 ). Fig. 1. Concepts of the memristor-based fully analog iteration. ( A ) Computing simulations from the macro to micro scale—such as computer-aided engineering, technology computer-aided design, and density functional theory—are commonly realized by solving matrix equations. ( B ) Architecture of the von Neumann computer and processing workflow of the MVM. ( C ) Analog MVM using memristor array. ( D ) Comparison of the processing time complexity of the digital computer and the memristor array. ( E ) Workflow of the previous hybrid iteration-solving concept; while capable of achieving high-solution precision, it suffers due to enormous data conversion consumption and is constrained by the convergence speed of digital iteration. ( F ) Workflow of the previous analog inverse-solving concept; while enabling high-efficiency processing with low time complexity, it faces challenges due to high-precision multilevel programming requirements and restricted scalability. ( G ) Workflow of the proposed fully analog iteration-solving concept. This concept overcomes the limitations of existing memristive matrix equation solvers and can substantially accelerate the solution of matrix equations while maintaining remarkable energy efficiency. Recently, memristive in-memory analog computing has emerged as a promising solution for these challenges ( 7 ). Leveraging Ohm’s and Kirchhoff’s laws, memristor-based crossbar arrays facilitate highly parallel analog matrix-vector multiplication (MVM) ( Fig. 1C ) ( 8 , 9 ). This O( 1 )-complex analog computing mechanism substantially outperforms traditional digital computing platforms, such as central processing units (CPUs) and graphical processing units, in terms of data-intensive matrix processing efficiency ( Fig. 1D ). Memristor technology has demonstrated its effectiveness in diverse applications, including signal and image processing, deep neural networks, and data mining ( 9 – 17 ). Although memristor arrays hold the potential for accelerating the solutions of matrix equations ( 18 – 20 ), they encounter unique challenges compared to the other applications where analog computing concepts achieve high efficiency without severe accuracy degradation. Solving matrix equations requires balancing energy efficiency, time complexity, and solution precision. This trade-off arises primarily from the intrinsic imprecision of analog MVM concepts ( 21 ). A promising strategy to mitigate analog computing errors involves a memristive hybrid iteration approach ( Fig. 1E ) ( 18 , 19 , 22 ). This approach uses memristor arrays to accelerate imprecise MVM processing, combined with high-precision mathematical iterations using peripheral digital processors. While recent hybrid approach enhances the energy efficiency of analog MVM operations through improved circuit structures and programming methods, it still relies heavily on frequent analog-to-digital conversion, leading to additional energy overhead ( 23 ). Furthermore, the processing speed remains constrained by the digital iteration procedure, limiting the complete utilization of the advantages offered by analog computing. In addition to this architecture, the solution of matrix equations can also be accelerated entirely in the analog domain using traditional analog matrix inversion techniques ( 24 ). Recent studies have demonstrated that this approach can achieve O( 1 ) solution time complexity ( 20 , 25 – 27 ). However, these analog computing implementations require precise multilevel conductance programming of memristors, which poses scalability challenges and limits solution precision ( Fig. 1F ). Despite these drawbacks, fully analog processing still offers a pathway for accelerating matrix equation solutions. To address these challenges, we developed a concept integrating hybrid iteration approaches into the analog domain to solve matrix equations ( Fig. 1D ). This approach offers the following advantages: (i) The proposed analog computing approach achieves accelerated solutions with high efficiency and O( 1 ) time complexity. In addition, it emphasizes hardware scalability and enables fully analog solutions using binary memristors, eliminating the need for stable multilevel devices. (ii) This approach supports integration with digital refinement procedures, creating a rapid, high-precision solver with sufficiently reduced analog-to-digital conversion overhead. We experimentally validated analog computing concept using fabricated W/AlO x /Al 2 O 3 /Pt memristor arrays. The analog iteration method provided approximate solutions of the matrix equation. Furthermore, the integration of heterogeneous computing system demonstrated the effectiveness of analog iterations with digital refinement (AIDR) for achieving high-precision results. Our method was applied to solve multiple scientific problems, including modeling diffusion phenomena and equilibrium in semiconductor P-N junctions. The AIDR solver achieved software-equivalent solution precision (solution errors below 10 −12 ) and delivered remarkable improvements in solution speed (approximately 41× to 128×) and energy efficiency (approximately 82× to 160×) compared to state-of-the-art digital processors. We believe that the superior performance of the AIDR indicates its potential as a promising memristor-based computing platform for the efficient acceleration of scientific computing.",
"discussion": "DISCUSSION Our fully analog iteration concept has been validated and shown to substantially outperform digital processors in processing speed and energy consumption while maintaining comparable precision. To further assess the effectiveness of our approach, we benchmarked it against state-of-the-art in-memory matrix equation solvers using equilibrium P-N junction modeling tasks. The AIDR solver was initially compared to the hybrid in-memory iteration solver outlined in ( 19 ) for high-precision solutions. This high-precision solver employs a memristor array for fast matrix multiplication, while a digital processor handles solution updates. To achieve a high-precision solution, this solver incorporates an inner precision improvement approach known as the bit-slice concept (fig. S17A) ( 41 ). Similar to our analog iteration concept, this mapping approach employs multiple devices representing a given bit. However, in this hybrid iteration solver, the shift-and-add operation for a partial product relies on digital circuits rather than analog ones ( 42 ). For equilibrium P-N junction modeling, we implemented the Jacobi iteration algorithm using the matrix slicing concept (fig. S10B). This process required 20,755 iterations to reach a preset tolerance of 10 −12 for a 64 × 64 problem (fig. S17B). Additional benchmarks revealed that this high-precision solver requires 1.67 × 10 −2 s to obtain a high-precision solution, with an energy consumption of approximately 0.26 J (refer to text S6 for detailed evaluations). Consequently, our AIDR solver provided a 1.7× improvement in solution speed and exhibited a 2× reduction in energy consumption (table S4). Subsequently, we compared our fully analog iteration approach with the previously reported analog inverse solver detailed in ( 20 ) for a fast approximation. The analog inverse solver was used for the fast calculation of x = A − 1 · b (fig. S18A), demonstrating a convergence speed of approximately 100 μs (fig. S18B) for the 64 × 64 equilibrium P-N junction modeling problem. Its energy consumption was approximately 13 μJ (detailed calculations are provided in text S6). These findings indicate that our fully analog iteration concept achieves an ~2.94× higher solution speed with ~2× lower energy consumption than the analog inverse solver for approximate solutions (table S4). Note that while binary conductance states were used in this study to enhance computing precision, we fully understand that analog conductance states can offer superior computational efficiency. Recent research indicates analog conductance states can achieve arbitrary computing precision ( 23 ). We anticipate integrating this technology with our circuit topology to develop highly precise, highly efficient, and fully analog computing hardware for practical scientific computing workloads. This endeavor will require further optimization of device performance and experimental validation. In summary, we proposed and experimentally demonstrated a memristive, fully analog iteration concept for solving matrix equations. This concept exhibits remarkable improvements in processing speed, energy efficiency, and scalability performance for real-world applications. By leveraging the fast-processing capability of an analog iteration circuit combined with digital refinement, the AIDR approach efficiently achieved approximate solutions in a single-step operation, substantially expediting the process of obtaining high-precision solutions. In both the diffusion and equilibrium silicon P-N junction modeling tasks, the AIDR solver achieved software-equivalent solution precision compared to state-of-the-art CPUs. Moreover, it demonstrated impressive improvements of 128× and 41× in solution speed, accompanied by reductions of 160× and 81× in energy consumption, respectively. This study underscores the potential of the proposed approach to provide a high-speed, energy-efficient platform that surpasses existing in-memory computing approaches for solving hyperdimensional matrix equations. We believe this study expands the realm of applications for memristor technologies and paves the way for the future acceleration in fundamental scientific computing and engineering research using imprecise analog devices."
} | 3,015 |
36134360 | PMC9400516 | pmc | 7,576 | {
"abstract": "The controlled transport of liquid on a smart material surface has important applications in the fields of microreactors, mass and heat transfer, water collection, microfluidic devices and so on. Porous membranes with special wettability have attracted extensive attention due to their unique unidirectional transport behavior, that is, liquid can easily penetrate in one direction while reverse transport is prevented, which shows great potential in functional textiles, fog collection, oil/water separation, sensors, etc. However, many porous membranes are synthesized from multilayer structural materials with poor mechanical properties and are currently prone to delamination, which limits their stability. While a monolayered porous membrane, especially for gradient structure, is an efficient, stable and durable material owing to its good durability and difficult stratification. Therefore, it is of great significance to fabricate a monolayered porous membrane for controllable liquid manipulation. In this minireview, we briefly introduce the classification and fabrication of typical monolayered porous membranes. And the applications of monolayered porous membranes in unidirectional penetration, selective separation and intelligent response are further emphasized and discussed. Finally, the controllable preparation and potential applications of porous membranes are featured and their prospects discussed on the basis of their current development.",
"conclusion": "5. Conclusion and outlook To date, impressive progress has been achieved in the areas of monolayered porous membranes from materials and methods to next-generation unidirectional devices. In addition to materials technology, membrane materials are developing into mature platforms that serve a wide range of applications, such as separation and penetration, wearable smart fabric products, unidirectional transport, responsive gating and other fields. This article has reviewed research progress into gradient monolayered porous membranes in recent years. The classification of porous membranes was introduced first, and common fabrication methods were further featured. Finally, recent applications of monolayered porous membrane were summarized, which will boost development in this significant research area. However, as a young and exciting research field, monolayered porous membranes still present challenges, such as spontaneous liquid transport in the positive direction usually meaning weak penetration resistance in the reverse direction. 123–125 Therefore, it is urgent to improve the strategy to fabricate monolayered porous membrane with spontaneous unidirectional penetration behaviour. And constructing an anisotropic gradient structure is a promising protocol to further improve the performance of existing membranes, which will open up new development opportunities for materials science and technology. Moreover, gradient monolayered porous membranes require further advances as a tool for the development of functional applications, such as unidirectional ion regulation, and seawater salinity gradient energy generation.",
"introduction": "1. Introduction Nature is an important source of inspiration for many scientists. Learning from nature, humans have designed and prepared many materials with excellent properties, promoting the progress of social civilization. 1–6 Directional liquid transport on a surface has important applications in microreactors, lubrication, inkjet printing, self-cleaning surfaces, microfluidics and so on, which already exists in nature and has been used by numerous organisms to perform a variety of functions. 7–11 For example, nepenthes plants can obtain water droplets on their gradient surfaces, 12 and the ratcheting scales of a butterfly's wings can move a water droplet away from its body in a directional manner. 13 All these phenomena are due to the existence of gradient anisotropic structures oriented on the biological surface, resulting in directional wetting or adhesion. 14 Therefore, it is of great significance to fabricate a micro–nano surface with gradient wettability for liquid transport with controllable direction, which will bring about broad applications in the fields of materials, energy, biology, medicine, the environment, non-dynamic liquid transportation and the preparation of unidirectional devices, etc. In recent years, many porous membranes with special wetting properties have attracted a lot of attention because of their unique unidirectional transport behaviours. 15–17 These membranes can be divided into two main types: multilayer porous membranes containing two closely connected layers with opposite wettability or different pore sizes and monolayered porous membranes with a morphology gradient or asymmetric modification. 18–24 Due to the poor mechanical properties and weak interfacial bonding of a multilayer porous structure, the membrane is prone to delamination, which limits its stability. 25 The monolayered porous membrane has been widely favored as a kind of efficient, stable and durable material owing to its structural integrity and unicity, which are of great significance in fabricating a monolayered porous membrane for controllable liquid manipulation. Therefore, summarizing the research progress on monolayered porous membranes in recent years will boost the development of this significant research area. In this minireview, the classification and fabrication of typical monolayered porous membranes are briefly introduced and discussed ( Fig. 1 ). The next part focuses on the application of monolayered porous membrane in unidirectional transport, intelligent response, selective separation, biomedical devices and smart textiles. Finally, we summarize the current challenges for gradient monolayered porous membranes and their device applications with their future perspectives. Fig. 1 Summary of gradient structures and their corresponding applications of gradient monolayered porous membranes."
} | 1,492 |
34436597 | PMC8388608 | pmc | 7,577 | {
"abstract": "Abstract Worker division of labor is a defining trait in social insects. Many species are characterized by having behavioral flexibility where workers perform non-typical tasks for their age depending on the colony’s needs. Worker division of labor and behavioral flexibility were examined in the little fire ant Wasmannia auropunctata (Roger, 1863), for which age-related division of labor has been found. Young workers perform nursing duties which include tending of brood and queens, and colony defense, while older workers forage. When nurses were experimentally removed from the colony, foragers were observed carrying out nursing and colony defense duties, yet when foragers were removed nurses did not forage precociously. We also administered juvenile hormone analog, methoprene, to workers. When methoprene was applied, foragers increased their nursing and defense activities while nurses became mainly idle. The behavioral flexibility of foragers of the little fire ant may be evidence of an expansion of worker’s repertoires as they age; older workers can perform tasks they have already done in their life while young individuals are not capable of performing tasks ahead of time. This may be an important adaptation associated with the success of this ant as an invasive species.",
"discussion": "Discussion By using an age category parameter of cuticle color, workers of the little fire ant Wasmannia auropunctata can be classified at different developmental ages. Light-colored individuals, considered nurses, cared for queens and brood. Dark-colored individuals, considered older workers, searched for food and were seen at the feeding area. Similar associations between age and cuticle color have been described in the monomorphic ant Acromyrmex octospinosus ((Reich, 1793 [Hymenoptera: Formicidae]) Armitage and Boomsma 2010 , Norman and Hughes 2016 ), where a lighter cuticle color is related to nurses and darker cuticle color is related to foragers. Under typical conditions, nurses of W. auropunctata were never seen outside of the nest, and foragers were not seen manipulating brood. Results from colony manipulation experiments demonstrate that the little fire ant workers have partial behavior flexibility. Older workers (i.e., foragers), which in typical colonies performed foraging, carried out nursing duties when younger workers (i.e., nurses) were absent. After young worker removal, older workers performed queen and brood care, yet foraging activity did not stop completely. The limited foraging observed, maybe due to a lack of response in foraging individuals due to there being sufficient reverted foragers performing the necessary nursing duties ( Tripet and Nonacs 2004 ) In contrast to older worker behavior, younger workers, which typically perform nursing duties, were not observed foraging when older workers were absent. In the absence of foragers, nurses remained inside the nest and performed their typical behaviors. The limited foraging activity that was observed may have been performed by older or transitioning nurses. It is likely that these were workers who began their onset of foraging behavior within the experimental period. During the colony defense assays, we observed that the majority of the defensive response was carried out by young workers. While young workers displayed a defensive response, older workers were observed returning to the nest and moving out brood. This outcome in particular was surprising. Typically in social insects, older workers (eg., Honey bees; Moore et al. 1987 , Breed et al. 1990 ) display more defensive behavior than young workers. Ants use a combination of defensive behaviors such as pheromones ( Hölldobler and Wilson 1990 , Vander Meer and Alonso 1998 ) and behavioral modifications ( Hölldobler and Wilson 1998 , Santos et al. 2005 ) among others. One possibility as to how nurses, who are inside the nest, respond quickly to intruders could be from recruitment by foragers using alarm pheromones as they enter the nest to move the brood. In colonies where older workers were removed, young workers continued performing defense behavior. However, when young workers were removed, we observed a higher number of old workers performing defense behavior from what we had observed prior. Since older workers seem to perform a wider variety of tasks when compared to younger workers, when it comes to colony defense, we could argue that older workers are more valuable to the colony than younger workers. During colony defense, if nurses are lost, older workers can take on nursing duties, ensuring colony survival. The capability of foragers to carry out nursing and colony defense tasks, while nurses don’t seem to forage precociously, may be related to the expansion of their behavioral repertoire ( Seid and Traniello 2006 , Muscedere et al. 2009 ) or the unidirectional behavioral flexibility model. In contrast to the bidirectional behavioral flexibility model, where foragers revert to nursing and nurses accelerate to foraging, the little fire ant seems to be only capable of reversal. Similar to other species of ants such as P. dentata ( Seid and Traniello 2006 , Muscedere et al. 2009 ), W. auropunctata might be considered an example of the repertoire expansion model. There could be several factors that may be involved in the lack of foraging in W. auropunctata young ants. Nurses may depend on their age but also on their nutritional status ( Toth and Robinson 2005 , Dussutour et al. 2016 , Ortiz-Alvarado et al. 2020 ). In social insects, foraging individuals tend to have lower amount of lipids than nursing individuals ( O’Donnell 2001 , Weeks et al. 2004 , Toth et al. 2005 ). Some studies have also demonstrated that reversing individuals have been associated with an increase of lipid stores ( Amdam et al. 2005 , Bernadou et al. 2015 ). During the observations after forager removal, we observed young individuals feeding on eggs. Isotope and nutrient content studies of ant eggs have shown that these are rich in carbohydrates ( Feldhaar et al. 2010 . Melo-Ruiz 2013 ) which promotes higher lipid content ( Weeks et al. 2004 , Kunieda et al. 2006 , Crumière et al. 2020 ). From this we can infer that young individuals might have a higher lipid reserve and hence the lack of need to forage. Other factors that could cause a lack of foraging behavior in young ants are neurological and endocrine differences with older workers ( Seid and Traniello 2005 ; Seid et al. 2005 , 2008 ). Our methoprene treatment results showed an effect on behavior, likely reflecting these endocrine differences. When young workers were treated with methoprene, these individuals reduced their nursing and observed defense activity, whereas older workers treated with methoprene decreased their foraging activity while increasing their nursing activity. These results defer from our hypothesis, as we expected nurses treated with methoprene to accelerate their foraging activities as other studies have shown ( Robinson 1985 , Giray et al. 2005 , Norman and Hughes 2016 ). Temporal polyethism is typically associated with physiological changes such as hormone levels (e.g., Foraging activities) being associated with an increase of JH ( Robinson 1985 , Huang and Robinson 1995 ) and lipid metabolism (e.g., loss of lipids associated with reduced nursing and increase of foraging ( Toth et al. 2005 , Dussutour et al. 2016 ). Other physiological changes are seen in ovary development ( de Wilde and Beetsma 1982 , Hoover et al. 2006 ) that typically correspond with the age of brood and queen care while ovary reabsorption corresponds to the age of foraging ( McDonald and Topoff 1988 , Vieira et al. 2010 ). In our study, nurses treated with methoprene reduced their nursing activities and remained idle inside the nest. Moreover, we observed those nurses being cared for and groomed by other nurses. We associate those behaviors with what we previously determined as queen grooming behavior. In a previous study with W. auropunctata queens, it was shown that a lower expression of JH related genes is associated with foraging behaviors and higher JH related gene expression with egg laying behavior ( Ortiz-Alvarado and Rivera-Marchand 2020 ). Taken together, methoprene treatment in nurses might be triggering a physiological response within the young worker system to lay eggs. Although it is not known if workers of the little fire ant are capable of laying eggs, this behavior has been observed in other eusocial insects ( Ratnieks 1993 , Iwanishi et al. 2003 ). JH is also known to change cuticle hydrocarbon (CHC) composition, and this composition varies depending on the task performed by the workers ( de Biseau et al. 2004 , Lengyel et al. 2007 ). CHC is involved in nest mate and species recognition in social insects ( Vander Meer and Morel 1998 , Stuart and Herbers 2000 ). The behavior observed of young workers being groomed as if they were queens, could be related to changes in the cuticle hydrocarbons and how they are recognized by nest mates. Moreover, our results suggest that there might be a negative association between JH levels and foraging activity in the little fire ant. This is seen in foragers that reduced their foraging activity and increased their nursing activities after methoprene treatments. Interestingly, the observed defense activities also increased after treatment in older workers, a behavior that was observed to be performed by young workers. The results of this study show differences from what was expected in other studies with other social insects. In a variety of cases, nurses were found to be able to forage precociously in the absence of foragers as demonstrated in honey bees ( Robinson 1992 ), and the ant P. dentata ( Calabi and Traniello 1989 ). The effects of methoprene were also different from what we expected. In other studies, increasing levels of JH through methoprene application led to precocious foraging in honey bees ( Robinson 1987 , Sullivan et al. 2000 , Chang et al. 2015 ), species of ants ( Norman and Hughes 2016 ) and wasps ( O’Donnell and Jeanne 1993 , Giray et al. 2005 , Shorter and Tibbetts 2009 ). Although our results were different from what has been reported in social insects before, we see in general a role of JH in behavioral flexibility. Experimental approaches have tested the involvement of JH in reproduction ( Brent and Vargo 2003 , Lu et al. 2009 ), division of labor ( Robinson 1987 , Giray et al. 2005 , Norman and Hughes 2016 ), and defense ( Robinson 1985 , Pearce et al. 2001 ). With the gamut of observations on JH and its role in social organization, we could argue that our results are in general in agreement with known variation in JH and plasticity in social insects. Even if our results seem to support the idea of W. auropunctata workers having unidirectional behavioral flexibility, more studies are needed. There is a caveat in our experimental colonies, where the effect of age and density on behavior is confounded due to removing all the individuals of one worker type. Adding an experimental control where only part of the nurses and part of the foragers are removed would solve this. Additionally, assays where the brood is manipulated or removed to record the behaviors from workers, should also be considered. Brood pheromone is known to delay the onset of foraging on socials insects and the absence of the brood promotes early foraging ( Le Conte et al. 2001 , Smedal et al. 2009 ). Therefore, we can further test the unidirectional behavioral flexibility model in the little fire ant workers. Lastly, since we are using cuticle coloration as a broad age parameter, a clear quantification of chronological cuticle color is needed to further classify little fire ant age and tasks. The behavioral flexibility of the little fire ant may explain the success of this ant as an invasive species. An organism that arrives in a new environment may face stochastic events that can cause a population decline, especially since this ant changes colony sites frequently (personal observation; Wetterer and Porter 2003 ). After an event that decreases the worker population, the probability of colony growth and survival may increase by old workers investing in queen and brood care. The cost of reduced foraging may be small since the colony will only have reduced foraging capacity for a few days until some nurses age into foragers and new nurses emerge days later. High investment by young and older workers in nursing after a population decline can better benefit the colony by assuring growth during this short period."
} | 3,165 |
35480720 | PMC9038061 | pmc | 7,578 | {
"abstract": "Magnetotactic bacteria, which synthesize biological magnetite nanoparticles (BMs), are the main microbial source of magnetic nanomaterials. Although the use of BMs has been explored in vitro and in vivo for new anticancer formulations, targeted treatments of fungal and parasitic diseases would also benefit from biogenic magnetic nanoformulations. Due to the necessity of new formulations of amphotericin B, we developed a magnetic-nanoparticle based conjugate of this drug using bacterial magnetosomes. Different amphotericin B preparations were obtained using BMs extracted from Magnetovibrio blakemorei strain MV-1 T as well as glutaraldehyde and poly- l -lysine as linking reagents. The highest capture efficiencies and drug loadings were achieved using 0.1‰ poly- l -lysine as the only linking agent (52.7 ± 2.1%, and 25.3 ± 1.9 μg per 100 μg, respectively) and 0.1‰ poly- l -lysine and glutaraldehyde 12.5% (45.0 ± 5.4%, and 21.6 ± 4.9 μg per 100 μg, respectively). Transmission electron microscopy and infrared spectroscopy analyses confirmed the association of amphotericin B to the BM surface. Moreover, controlled drug release from these nanoparticles was achieved by applying an alternating magnetic field. In this condition the release of amphotericin B in PBS increased approximately four-fold as compared to the release under standard conditions with no applied magnetic fields. Hence, the functionalization of BMs with amphotericin B produces stable nanoformulations with a controllable drug release profile, thus, enabling its potential in the treatment of fungal and parasitic diseases.",
"conclusion": "Conclusions Here we first demonstrated the functionalization of magnetosomes from Mv. blakemorei strain MV-1 T and the decoration of magnetosomes with an antifungal/antiparasitic drug. ‡ ‡ The results obtained in this study have been registered under the patent number BR1020210056835 held in Brazil. In our experiments, it is evidenced that PLL increase binding of AmB onto magnetosomes in the presence and absence of GA. We also demonstrated the controlled drug release from these conjugates with the application of an AMF, which can be useful in localized chemotherapy. These results expand the potential applicability of these magnetic nanoparticles in the treatment of neglected diseases.",
"introduction": "Introduction Magnetic nanoparticles have extensive usage in nanomedicine, mainly because of their employability in drug delivery, biomolecule immobilization, and cell separation. 1 In drug immobilization, nanoparticles lead to the increased biocompatibility of these compounds as they reduce toxic effects by preventing systemic distribution. 1,2 Besides, they drive therapeutic molecules to the site of interest ( i.e. , site of infection or tumors) leading to a higher local concentration than when using non-immobilized drugs. 2 Several magnetic nanoparticle systems have been developed in the last decades. 1 Most of them comprise synthesis of nanoparticles by precipitation of iron minerals such as magnetite. 1,3 Surface modifications of these nanoparticles are usually performed to make them able to bind to functional moieties. 3 However, processes of chemical synthesis may not yield particles with uniform sizes, and shapes and their magnetic properties are difficult to predict. 4 Bacterial magnetite nanoparticles (BMs), known as magnetosomes, overcome these limitations. 5 These nanoparticles, which are synthesized in a finely-controlled biomineralization process by magnetotactic bacteria, 6 comprise a core mineral crystal of magnetite or greigite enveloped by a lipid bilayer membrane. 7 Biomineralization process yields single domain magnetic nanoparticles within a narrow size range (30–100 nm) and uniform shape. 8 Further surface modification steps are straightforward because of the natural membrane bilayer of these nanoparticles. Proteins responsible for the magnetosome synthesis are embedded in this outer lipid bilayer, 6 being useful for functionalization processes. 5,10 They can work as anchors for expression genetically-engineered fusion proteins such as enzymes or antibodies. 11,12 Alternatively, their amino groups (–NH 2 ) may serve as sites for crosslinking with other molecules, such as drugs. 13,14 All those characteristics are advantageous for biomedical applications. 5,8 Additionally, bacterial synthesis of magnetite nanoparticles is considered environmentally friendly. 3,9 Several applications for BMs have been described. In small-molecule immobilization, gangliosides and the antitumor drugs doxorubicin and cytarabine have been surface-bound to BMs and, in all cases, their activities were shown to be enhanced in the magnetic conjugate. 13,15,16 However, all of these tests were performed with highly hydrophilic molecules and both drugs tested were anticancer. 13,15,16 Unlike the examples above, amphotericin B (AmB) is a poorly water-soluble, antifungal and leishmanicidal drug belonging to polyene class. 17 Because of poor dispersibility in aqueous media and serious toxic side-effects, nanoparticle formulations for this drug could come as beneficial for its therapeutic use. 18–20 Different formulations have been developed for AmB such as Fungizone® and AmBisome®, which are less toxic and disperse well in bodily fluids. 20 Zaioncz et al. 21 reviewed several works on AmB formulations using nanoparticles as carriers, including polymeric-based, protein-based, and solid lipid-based nanoparticles, some of the which with more efficacy, bioavailability, and less toxicity than other formulations on market. More recently, a formulation of AmB-loaded polycaprolactone (PCL) was designed for topical treatment with significant lower IC 50 compared with free AmB and AmBisome®. 22 To benefit from the stimuli-responsiveness of magnetic materials, Niemirowicz and colleagues developed a magnetic nanoformulation that was efficient at inhibiting biofilm formation of Candida sp. and increase the antifungal activity of polyene antibiotics, even in resistant Candida strains. 23 Nevertheless, the nanoparticle tested was chemically synthesised. The use of BMs for immobilizing AmB could bring additional advantages to magnetic formulations, such as low side-effects, and, additionally, the surrounding biological membrane could facilitate functionalization because of the availability of functional groups on their surface for chemical modification. In addition, AmB biocompatibility and dispersibility would be enhanced. In the present work, we describe a rapid and simple preparation of BMs–AmB conjugates. The drug was attached to the surface of elongated prismatic BMs from the magnetotactic vibrio Magnetovibrio blakemorei strain MV-1 T through crosslinking with glutaraldehyde (GA), coating with poly- l -lysine (PLL) and a combination of both in different concentrations. Finally, we investigate AmB release under standard condition and under application of an alternating magnetic field (AMF).",
"discussion": "Results & discussion BM production BMs were obtained from a culture of Mv. blakemorei strain MV-1 T grown in a 5 L bioreactor using medium and operational optimized conditions. 24 Cells were then lysed by sonication and extracted BMs were washed four times using HEPES buffer (10 mM; pH 6.8) before their utilization in the experiments. Size of isolated BMs ( n = 540) averaged 64.3 ± 0.5 nm in length and 41.6 ± 0.3 nm in width (Fig. S1 † ) as measured from transmission electron microscopy (TEM) images. Preparation of functionalized nanoparticles Although the abundance of phosphatidyl components of BM membrane 11 gives these nanostructures an overall negative charge, other functional groups are present. 5 The functional groups available on the BM surface are those from side chains of amino acid residues making up membrane proteins. 5 The most important for chemical modifications are amino groups, as these groups have been extensively reported in literature 5,10,14 as anchors for covalent binding of functional molecules. The immobilization of drug molecules onto BMs is usually achieved with iminium-forming crosslinkers, like GA. 13 From that knowledge, different concentrations of GA, ranging from 0.2% to 12.5%, were used for the treatment of BM with AmB (BM–GA–AmB) in this work. In addition, polyaminoacids are also promising agents for adsorption of drugs onto these nanoparticles based on charge interactions. 5,10 Thus, BMs were coated with PLL (concentrations ranging from 0.001 to 0.1‰) before treatment with AmB. PLL-coated BMs were also treated with AmB in the presence and absence of GA (BM–PLL–GA–AmB and BM–PLL–AmB, respectively) in the concentration that yielded the best drug capture efficiency (0.1‰ PLL). When applied as the only linking agent, maximum tested concentrations of either GA and PLL returned the most substantial encapsulation efficiency (35.2 ± 3.5% for BM–GA–AmB and 52.7 ± 2.1% for BM–PLL–AmB) and drug loading (15.5 ± 3.1 μg per 100 μg for BM–GA–AmB and 25.3 ± 1.9 μg per 100 μg for BM–PLL–AmB) ( Fig. 1A ). Overall, all BMs treated with tested PLL concentrations returned better drug entrapment than those using GA. This is probably due to the fact GA links only to amino groups located in proteins of BM membrane whereas PLL covers BM surface as a whole because of net negative charge provided by phospholipids. No statistically significant difference in encapsulation efficiency and drug loading was found between BM–PLL–AmB (0.1‰ PLL; 45.0 ± 5.4% and 21.6 ± 4.9 μg per 100 μg, respectively) and when both reagents (BM–PLL–GA–AmB) were used (0.1‰ PLL + 12.5% GA; 52.7 ± 2.1% and 25.3 ± 1.9 μg per 100 μg, respectively). Fig. 1 Encapsulation efficiencies (%) and drug loadings (μg per 100 μg) (A) for different concentrations of GA and PLL in functionalization of BMs. Average zeta potential (B) ( n = 10) for each preparation. In both analysis PLL and GA were used in the maximum tested concentrations (0.1‰ and 12.5%, respectively). ANOVA tests showed statistically significant difference in efficiencies ( p < 0.0001, ****). Spectroscopy analyses and chemical structure The attachment and adsorption of AmB onto BMs were then confirmed using ATR-FTIR spectroscopy analyses (Fig. S2 † ) and a schematic representation of each preparation is displayed on Fig. 2 . Fe–O stretching vibration peaks from magnetite were found in all nanoparticle preparations, ranging from 534 to 564 cm −1 . Additionally, the multiplicity of functional groups, including primary amines, has been confirmed in our spectroscopic analysis of raw BMs by the characteristic fingerprint region (1400 to 500 cm −1 ). The peaks 1643 and 1654 cm −1 in BM–GA–AmB and BM–PLL–GA–AmB are assigned to (–CN) vibrations, suggesting the covalent attachment of AmB, 13,23 as illustrated in structures ( Fig. 2B and C ). The bands ranging from 2943 and 2827 cm −1 correspond to –CH 2 and –CH 3 stretching vibrations of the polyene structure of AmB. 27 In BM–PLL–AmB and BM–PLL–GA–AmB the peak 1622 cm −1 is assigned to bending vibration of N–H of amide groups from polyaminoacid backbone of PLL 28 ( Fig. 2D and E ). Peaks 1528 cm −1 in BM–PLL–AmB and BM–PLL–GA–AmB and 1562 cm −1 in BM–GA–AmB and AmB correspond to superposed –NH 2 bending and –COO − stretching vibrations from AmB 27 ( Fig. 2D and E ). Peaks 1383–1401 cm −1 in functionalized nanoparticles and AmB correspond to –COO − stretching and –C \n \n\n<svg xmlns=\"http://www.w3.org/2000/svg\" version=\"1.0\" width=\"13.200000pt\" height=\"16.000000pt\" viewBox=\"0 0 13.200000 16.000000\" preserveAspectRatio=\"xMidYMid meet\"><metadata>\nCreated by potrace 1.16, written by Peter Selinger 2001-2019\n</metadata><g transform=\"translate(1.000000,15.000000) scale(0.017500,-0.017500)\" fill=\"currentColor\" stroke=\"none\"><path d=\"M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z\"/></g></svg>\n\n O bending vibrations from AmB. 27 Finally, peaks 1072–1037 cm −1 and 1000–1014 cm −1 from the same spectra are assigned to pyranose C–O–C stretching and –CH trans bending from polyene structure 27 ( Fig. 2B–E ). These findings support the effective binding of AmB in these preparations and indicate the possible mechanisms in which GA, PLL and AmB interacts with BMs during the preparation of nanoconjugates. When used as the sole linking agent (BM–GA–AmB), GA activates BM surfaces for the covalent binding to molecules containing primary or secondary amino groups through iminium formation. 10,29 When AmB is added to a GA-activated BM suspension, the amino group presents within the mycosamine ring ( Fig. 2B ) reacts with GA-derived aldehyde group to form a second covalent iminium bond ( Fig. 2C ). In preparations containing PLL (BM–PLL–AmB and BM–PLL–GA–AmB), the polyaminoacid side chain, which is comprised of a four-carbon chain with a terminal primary amine, is positively charged at neutral pH. Thus, positively charged PLL side chains electrostatically binds to negatively charged phospholipids on the surface of BMs ( Fig. 2D and E ). The interaction of AmB with PLL in BM–PLL–AmB probably occurs by a hydrogen bond between amine side chain of PLL and carboxyl group present in AmB ( Fig. 2E ). For BM–PLL–GA–AmB, the BMs are first coated with PLL prior to activation by GA (refer to Preparation of functionalized nanoparticles in Experimental section). In this sense, one of aldehyde groups of GA forms an iminium bond with the aliphatic amino group of the PLL coating ( Fig. 2D ). Then, the GA-activated complex binds covalently to AmB molecules in a manner analogous to that of BM–GA–AmB. Fig. 2 Representation of free magnetosome (A) and structures of free amphotericin B, with the mycosamine ring at the bottom right, (B) and their conjugates: BM–GA–AmB (C), BM–PLL–GA–AmB (D) and BM–PLL–AmB (E). The adsorption and the stability of AmB attached to the BM–PLL–AmB and BM–PLL–GA–AmB – chosen due to the highest drug loadings – were investigated through UV-vis spectroscopy. For both preparations, absorption peaks were observed, in crescent intensity order, at 364, 382 and 406 nm (Fig. S3 † ). The relative intensities between peaks were maintained for the tested nanoformulations, as enforced by the International Pharmacopoeia. 25 This finding corroborates that our synthesized nanoformulations are in accordance to regulatory requirements and meet quality standards for pharmaceutical use. Membrane thickening measurements Measurements of membrane thickness of different BMs preparations from TEM images revealed the surface interactions observed after functionalization experiments. All preparations had progressively larger membrane thickness measurements than non-functionalized BMs ( Fig. 3 and S4 † ), with the largest membrane thickness observed for BM–PLL–GA–AmB, when most reagents were attached to the surface of BMs. These results suggest the BM membrane became thicker as more functional moieties were added to its surface. The increase in BM membrane thickness as result of insertion of organic molecules has also been observed in other works. 10,30 It is suggested that such phenomenon could prevent aggregation of BMs caused by interaction between nuclei of single magnetic domain. 31 TEM images also suggested some level of aggregation of nanoparticles, especially in those prepared with GA. This is probably due to unspecific BM–BM crosslinking, which could also explain a lower encapsulation efficiency when using this GA as crosslinking agent. Fig. 3 TEM images of free BMs (A) and its conjugates: BM–GA–AmB (B), BM–PLL–GA–AmB (C) and BM–PLL–AmB (D). Note the membrane thickness increase for different preparations. Zeta potential The zeta potential was measured to evaluate the dispersive properties of the functionalized nanoparticles. For non-functionalized BMs, a zeta potential of −33.6 ± 2.3 mV was found and agrees with values found for cuboctahedral BM from Magnetospirillum strains 14,31 ( Fig. 1B ). As in other Magnetospirillum , BMs in Mv. blakemorei strain MV-1 T are formed from vesicles internalized from the inner cell membrane, 32 which is composed of negatively charged phospholipids and causes a negative zeta potential. Values between −33 and −28 mV were observed for preparations tested, except BM–PLL–AmB, whose potential was −15.1 ± 3.8 mV ( Fig. 1B ). Despite the increase of zeta potential value towards zero, all dispersions of tested preparations may be considered at least relatively stable. 33 The change in zeta potential of particles derived from different functionalization methods showed the response of membrane charge to the interaction with the foreign molecules, as corroborated by the encapsulation, membrane thickening and spectroscopic results. This trend has been recently discussed by another work, 29 in which immobilization of anthracycline molecules also leads to significant changes in BM surface charges, as evaluated by zeta potential. Magnetic characterization To our knowledge, this is the first time BMs of prismatic shape have its functionalization potential explored. Because of that, magnetic properties for this type of nanoparticle were not available and had to be evaluated. Magnetization measurements were performed on non-functionalized BMs and presented a behaviour of single magnetic domain particle, as expected ( Fig. 4 ). The values for saturation magnetization and coercivity were 52 emu g −1 and 115 Oe. These characteristics and measured values were compatible with the values reported for the cuboctahedral BM of Magnetospirillum magneticum strain AMB-1 (ref. 34 ) and bioinspired greigite nanoparticles. 35 These findings reflect similar applicability potential for the elongated prismatic BMs from Mv. blakemorei strain MV-1 T and those nanoparticles already studied. Fig. 4 Magnetization curve of lyophilized magnetosomes from Mv. blakemorei strain MV-1 T showing hysteresis loops (inset). Heating capacities of suspensions containing 1.2 and 4.8 mg mL −1 of magnetite in water were examined under an AMF (field amplitude = 200 Gs; frequency = 307 kHz). The increase in temperature in response to the application of an AMF was the highest (6.3 °C) in the suspension containing the largest amount of magnetite ( Fig. 5 ). When the concentration of magnetite was 1.2 mg mL −1 , the temperature increase was also lower (1.4 °C). The specific absorption rate (SAR) is defined as the rate in which magnetic energy is converted into thermal energy by unit of mass. 36 This property is dependent on mass, shape, size of nanoparticle and on the frequency and the intensity of the applied magnetic field. 36 The SAR values calculated from our experiments are 2.9 and 7.0 W g Fe 3 O 4 −1 for suspensions of BMs with 1.2 and 4.8 mg mL −1 , respectively. Both the temperature variation and SAR value achieved here are lower than previously reported values for hyperthermia using BMs. 34,37 However, a similar temperature increase was obtained using similar parameters for AMF-induced heating of BMs from Magnetospirillum gryphiswaldense strain MSR-1. 38 Fig. 5 Heating profile of BM samples (1.2 mg mL −1 and 4.8 mg mL −1 ) subjected to an AMF of 200 Oe and frequency of 307 kHz. AmB-releasing profile The amount of AmB released into the medium relative to the amount of drug associated within the nanoparticle was measured in the standard drug release condition (37 °C) 26 and under the application of an AMF. For these experiments, only the preparations with the highest loading of AmB were used ( Fig. 6 ). The release in the standard condition within 1 h was 11.1 ± 0.4% for BM–PLL–GA–AmB and 15.0 ± 1.2% for BM–PLL–AmB. When the suspension was subjected to the AMF, the drug release in the same time interval increased by approximately four times, reaching 41.3 ± 0.5% for BM–PLL–GA–AmB and 53.8 ± 6.2% for BM–PLL–AmB. This increase in the release is attributed to Brown relaxation, which responds for rotation of nanoparticles under AMF, rather than hyperthermia. 36,39 This was also observed in a study in which an increase of about four times of doxorubicin release from cyclodextrin-decorated magnetite nanoparticles was observed without the rise in temperature. 39 In another study, a sharp release of rhodamine B from rhodamine B-fluorescent BMs in response to an AMF occurred in a temperature variation smaller than 2.5 °C. 40 Fig. 6 Cumulative release profile of AmB from different preparations under standard (37 °C) and AMF. PLL and GA were used in the maximum tested concentrations (0.1‰ and 12.5%, respectively)."
} | 5,149 |
25620679 | null | s2 | 7,579 | {
"abstract": "Recombinant protein overexpression of large proteins in bacteria often results in insoluble and misfolded proteins directed to inclusion bodies. We report the application of shear stress in micrometer-wide, thin fluid films to refold boiled hen egg white lysozyme, recombinant hen egg white lysozyme, and recombinant caveolin-1. Furthermore, the approach allowed refolding of a much larger protein, cAMP-dependent protein kinase A (PKA). The reported methods require only minutes, which is more than 100 times faster than conventional overnight dialysis. This rapid refolding technique could significantly shorten times, lower costs, and reduce waste streams associated with protein expression for a wide range of industrial and research applications."
} | 187 |
31316475 | PMC6611431 | pmc | 7,581 | {
"abstract": "Plant-derived carbon (C) is considered fundamental to understand the interaction between rhizosphere microbes and plants in terrestrial ecosystems. Biochar soil amendment may enhance plant performance via changing soil properties or microbial diversity in the rhizosphere. However, our knowledge of how plant-microbiome associations respond to biochar amendment remains rather limited. Herein, 13 CO 2 steady-state labeling combined with DNA stable-isotope probing was used to characterize soil bacterial communities in the rhizosphere contributing to the utilization of plant-derived C. The diversity of bacteria active in the utilization of root exudates was determined after biochar amendment in a legume-based intercropping system ( Vicia faba L., with Zea mays L.). The results showed the biochar application not only changed the bacterial community structure and diversity in the rhizosphere, but also altered bacterial members actively assimilating plant-derived C. There were more labeled species in the biochar-amended soils than the control soils. Compared with the control, the biochar amendment increased the relative abundances of Firmicutes and Bacteroidetes members (i.e., Bacillus , Clostridium , Sporomusa , Desulfosporosinus , and Alicyclobacillus ) while decreasing the abundances of Proteobacteria members (e.g., Methylobacterium and Sphingomonas ) utilizing plant-derived C. In contrast, slow-growing species of the phyla Acidobacteria, Planctomycetes, and Gemmatimonadetes were barely labeled. The bacteria found stimulated by the biochar amendment are known for their ability to fix nitrogen, solubilize phosphorus, or reduce iron and sulfur, which may potentially contribute to the “biochar effect” in the rhizosphere. This study is the first to provide empirical evidence that biochar amendment can alter the soil bacterial community assimilating plant-derived C; this may have consequences for nutrient cycling and improving plant performance in intercropping systems.",
"introduction": "Introduction Modern agricultural systems provide high crop yields, but they also generate serious impacts on the environmental. For example, intensive use of mineral fertilizers and pesticides leads to such soil acidification ( Gollany et al., 2005 ), groundwater contamination ( Gollany et al., 2004 ), and increasing greenhouse gas emissions ( Dalal et al., 2003 ). Intercropping is an ancient and traditional agricultural practice, and especially legume-based intercropping systems have great potential for contributing to agricultural productivity through increasing nitrogen (N) inputs and phosphorous (P) bioavailability ( Rose et al., 2015 ; Tang et al., 2016 ) in the terrestrial system. In this regard, an intercropping system provides a way to introduce soil available nutrients into the agro-ecosystem, thus avoiding the excessive use of fertilizers and pesticides relied upon during conventional cultivation. Furthermore, a recent meta-analysis indicated that intercropping can increase crop yields in Africa by an average of 23% compared with monocropping ( Himmelstein et al., 2017 ). Hence, an improved understanding of nutrient cycling in intercropping systems may offer new insights into achieving long-term agricultural productivity. Plants and microbiomes build and engage in a complex and varied molecular “dialogue” in the rhizosphere ( Gkarmiri et al., 2017 ). It has been estimated that rhizodeposition accounts for 17% of total photoassimilated carbon (C), and belowground C allocation by grasses was higher than crops ( Nguyen, 2003 ; Pausch and Kuzyakov, 2018 ). The beneficial effects of an intercropping system are closely related to the partitioning of C that occurs belowground and its utilization by different functional groups of microbes ( Fan et al., 2008 ). However, this soil microbial community is often influenced by plant species due to differences in the quantity and quality of C resources produced by root exudates ( Garland, 1996 ; Liu et al., 2017 ). Additional factors controlling plant C allocation belowground include drought events, water status, and fertilization regimes ( Drigo et al., 2010 ; Yao et al., 2012 ; Fuchslueger et al., 2016 ; Wang et al., 2016 ). Nevertheless, plants can actively select beneficial microbes or disrupt the invasion of pathogenic microbes in the rhizosphere by secreting particular root exudates ( Chapelle et al., 2016 ). Meanwhile, shifts in the microbial community consuming plant-derived C may have strong effects on plant development and soil nutrient cycling ( Hannula et al., 2017 ). Biochar is a C-rich product of biomass pyrolysis intended for use as a soil amendment. Biochar amendment has been found to increase both the soil water-holding capacity ( Abel et al., 2013 ) and nutrient availability ( Zheng et al., 2018 ), and to also increase the pH in acidic soil ( Whitman et al., 2016 ). Some studies have shown that biochar-induced changes in soil properties (e.g., pH and nutrient availability) may have beneficial effects on crop productivity ( Lehmann et al., 2011 ; Liu et al., 2017 ). However, it is worth noting that application of the biochar into soil would be expected to have wide-ranging effects, depending on the quality of the biochar in terms of feedstock and pyrolysis temperature ( Jaiswal et al., 2014 ; Imparato et al., 2016 ). Recently, some studies have shown that biochar amendment may increase the diversity of soil microbes; this phenomenon, may be contributed to the release of non-labile biochar-associated organic compounds or the changes in soil properties induced by biochar amendment ( Kolton et al., 2011 ; Lehmann et al., 2011 ; Zhang et al., 2017 ). Kolton et al. (2017) found that biochar-enhanced plant performance was related not only to greater microbial richness but also linked to higher metabolic potential in the rhizosphere. However, it is still an open question whether biochar applications can facilitate soil microbes assimilating plant-derived C, leading to a tight-knit plant-microbiome association in the rhizosphere. Moreover, numerous studies tend to focus on the overall microbial community and its diversity in the rhizosphere of monocropping systems. By contrast, how biochar amendment may affect soil microbial community composition and diversity in intercropping systems is understudied. Plants can release a variety of root exudates into the rhizosphere, and these biologically active compounds from root exudate are known to influence the rhizosphere microbiome ( Baetz and Martinoia, 2014 ; Mendes et al., 2017 ). Salicylic acid and γ-aminobutyric acid concentrations have been shown to be correlated with specific taxa that are enriched in the rhizosphere ( Badri et al., 2013 ; Zhalnina et al., 2017 ). Biochar amendment may change the influences of root exudates on the rhizosphere microbiome. For example, biochar may alter rhizosphere microbial communities, facilitating propagation of microbes via absorption of root exudates ( Gu et al., 2017 ) or via physical attributes generated by the porous properties of biochar ( Pietikäinen et al., 2000 ). In the present study, we performed 13 CO 2 steady-state labeling coupled with DNA-stable isotope probing (SIP) and investigated soil bacterial diversity via high-throughput amplicon sequencing in an intercropping system. The objectives of the present study were: (1) to explore the effects of biochar amendment on soil bacterial communities actively utilizing plant-derived C, and (2) to understand the interactions between root exudates and soil bacterial communities after biochar amendment in an intercropping system. Our hypothesis was that biochar amendment not only stimulates bacterial species affiliated with the phyla Bacteroidetes and Firmicutes, but also alters a subset of bacterial communities consuming plant-derived C in the rhizosphere, leading to a distinct plant-microbe association in the intercropping system.",
"discussion": "Discussion Recent studies have shown that using a system of legume-based intercropping can enhance N fixation and phosphorous P availability in the rhizosphere over that of a monoculture ( Tang et al., 2014 ; Rose et al., 2015 ). In the present study, we found no significant differences in soil available nutrients or plant biomass in the legume-based intercropping system between the biochar and control treatments. The minor differences in soil nutrient availability and plant biomass between treatments can be attributed to multiple factors. For example, the original soil organic matter content in the intercropping system was relatively high, while the biochar rate (2%) used in the study could not high enough to markedly improve soil nutrient conditions or plant grawth. Other, studies have shown that biochar amendment may have the potential to improve soil nutrient status and alleviate soil nutrient stress ( Ding et al., 2016 ; Pandit et al., 2018 ). Furthermore, Graber et al. (2015) found that substances extracted from biochar have a strong effect on root hair development under abiotic growing conditions. Phylogenetic affiliation of the 16S rRNA gene sequences revealed that biochar-induced shifts in soil microbial community composition were mainly ascribed to a remarkable increase in the relative abundances of the phyla Firmicutes and Bacteroidetes, as well as a significant decrease in the relative abundance of the phylum Proteobacteria. These results are consistent with those reported by Hu et al. (2014) , who found that Firmicutes and Bacteroidetes occurred distinctively in a red-oxidized loam soil after short-term biochar amendment compared with the control samples. Members of Bacteroidetes, widely found in soils and animal-centric canals, have the ability to degrade polysaccharides and cellulose ( Fierer et al., 2007 ; Hu et al., 2014 ; Wolińska et al., 2017 ). A study also found that the relative abundance of Bacteroidetes was substantially higher in the root-associated community of biochar-amended soil, while the abundance of Proteobacteria was much higher in the control treatment ( Kolton et al., 2011 ). Firmicutes are recognized as copiotrophs (or r-strategists), which explains their predominance in the soil after biochar amendment. A large proportion of members from the family Clostridiaceae in the phylum Firmicutes are capable of N fixation ( Ding et al., 2017 ). The Chao 1 estimator of the bacterial community greatly increased after biochar amendment, although whereas we did not find significant differences in the observed species. The similarity in observed species between treatments may be attributed to the fact that identifying diversity in complex soil environments is very challenging. Furthermore, the richness estimated by the “breakaway” package did not significantly differ between treatments. The discrepancies between Chao 1 estimator and estimated richness may be attributed to the results of Chao 1 problematic in environments where many rare OTUs are never detected ( Willis et al., 2017 ). Pulse-labeling plants with 13 CO 2 emphasized the current photosynthate, which may not label all plant C pools to the same degree ( De Visser et al., 1997 ; Yao et al., 2012 ). In the current study, we applied a steady-labeling approach instead of pulse-labeling to ensure that all the plant-derived C was labeled to the same degree. During the 35-day period of continuous labeling with 13 CO 2 , the biomass of faba bean and maize seedlings was synthesized. At the end of this labeling period, the δ 13 C values of rhizosphere soil were labeled up to 300‰ for both the control and biochar treatments ( Supplementary Figure S2 ). This labeled CO 2 in soil would have participated in a fair number of processes, including microbial incorporation and the respiration of root exudates. Hence, the experimental set-up used in this study allowed us to explore, in a more direct way, the effects of soil biochar amendment on the interaction between plant and microbes in the rhizosphere. The “cross-feeding” is a common limitation for DNA-SIP approach. Ideally a short sampling time should be selected to reduce the cross-feeding effect, but this is difficult to optimize in practice. If sampling is too late, the rate of label incorporation by primary autotrophic assimilation may be slower than secondary heterotrophic incorporation; if sampling is too early there may be insufficient 13 C label in DNA for accurate detection. Herein the 35-day continuous labeling was performed to generate enough amount of labeled DNA. Despite the above-mentioned limitations and complications, the continuous labeling technique combined with DNA-SIP is the most powerful tool available for identifying the microbial communities primarily utilizing plant-derived C. For both the unlabeled 13 CO 2 -labeled and labeled samples, fraction density played a major role in 16S rRNA gene composition. This result was expected because genome G+C content is positively related to DNA buoyant density and therefore influence the 16S rRNA gene sequence structure. Additionally, we observed that the biochar application changed the soil bacterial community composition and diversity in the rhizosphere, while altering the members involved in actively assimilating the plant-derived C. Recent studies have documented that despite the high diversity of microbes occurring in the rhizosphere, only a few microbial groups (less than 4% of the total proportion) effectively utilize the plant-derived C ( Gschwendtner et al., 2016 ; Hannula et al., 2017 ). In the current study, we found a wide range of bacterial taxa involved in the utilization of plant-derived C, in both control and biochar treatments ( Figure 4 ). These results may suggest that bacterial species from these taxa grew more slowly, and this phenomenon may be attributed to different lifestyle strategies of these taxa. For example, Acidobacteria are recognized as slow-growing bacteria, or “oligotrophs,” which have high C use efficiency and are abundant in soil with high recalcitrant organic matter concentration ( Fierer et al., 2007 ; Trivedi et al., 2017 ). Similarly, Gemmatimonadetes have been found to decrease their relative abundance after fresh organic matter input, and they are more likely to decompose existing soil organic C rather than fresh organic matter ( Pascault et al., 2013 ; Whitman et al., 2016 ). In the control treatment, Firmicutes and Proteobacteria were two predominant bacterial phyla utilizing the plant-derived C. By comparison, the biochar treatment clearly stimulated more bacterial members to utilize the plant-derived C ( Figure 4 ). Specifically, the biochar amendment significantly enhanced the utilization of plant-derived C by Firmicutes and Bacteroidetes members (e.g., Clostridium , Sporomusa , Desulfosporosinus , Alicyclobacillus , Flavisolibacter , Geobacter , and Bacillus ), however, in the control treatment, Proteobacteria members (e.g., Methylobacterium and Sphingomonas ) tended to increase in their relative abundance to consume the plant-derived C. Bacillus and Clostridium were found in both the control and biochar treatments, and these two taxa are known, respectively, for their N-fixing and P-solubilizing abilities ( Long et al., 2018 ). Our results imply that Bacillus and Clostridium may play an important role in N and P cycling in a faba bean-maize intercropping system. Interestingly, Desulfosporosinus , Alicyclobacillus , and Geobacter are known for their iron and sulfur oxidation abilities ( Ding et al., 2015 ). Therefore, the participation of these taxa in nutrient cycling (e.g., by fixing N or solubilizing P) should be addressed in the intercropping system in future research. Generally, the pronounced shifts in the soil bacterial community utilizing the plant-derived C provide strong evidence that biochar amendment induces a distinct plant-microbiome interaction in the rhizosphere. Our results indicate that biochar amendment not only changed the overall bacterial community in the rhizosphere but also favored the presence and abundance of bacteria with N-fixing and P-solubilizing abilities in the legume-based intercropping system ( V. faba L., with Z. mays L.). Their utilization of plant-derived C may thus have crucial consequences for C storage and dynamics, as well as nutrient cycling and plant performance more generally, in agro-ecosystems that use intercropping."
} | 4,110 |
31404449 | null | s2 | 7,582 | {
"abstract": "Self-assembly of peptides is a powerful method of preparing nanostructured materials. These peptides frequently utilize charged groups as a convenient switch for controlling self-assembly in which pH or ionic strength determines the assembly state. Multidomain peptides have been previously designed with charged domains of amino acids, which create molecular frustration between electrostatic repulsion and a combination of supramolecular forces including hydrogen bonding and hydrophobic packing. This frustration is eliminated by the addition of multivalent ions or pH adjustment, resulting in a self-assembled hydrogel. However, these charged functionalities can have profound, unintended effects on the properties of the resulting material. Access to neutral self-assembled nanostructured hydrogels may allow for distinct biological properties that are not available to highly charged analogues. Here, we designed a series of peptides to determine if self-assembly could be mediated by the steric interactions created by neutral hydroxyproline (O) domains, eliminating the need for charged residues and creating a neutral peptide hydrogel. The series of peptides, O "
} | 292 |
33820990 | null | s2 | 7,583 | {
"abstract": "Genetically modified microorganisms (GMMs) can enable a wide range of important applications including environmental sensing and responsive engineered living materials. However, containment of GMMs to prevent environmental escape and satisfy regulatory requirements is a bottleneck for real-world use. While current biochemical strategies restrict unwanted growth of GMMs in the environment, there is a need for deployable physical containment technologies to achieve redundant, multi-layered and robust containment. We developed a hydrogel-based encapsulation system that incorporates a biocompatible multilayer tough shell and an alginate-based core. This deployable physical containment strategy (DEPCOS) allows no detectable GMM escape, bacteria to be protected against environmental insults including antibiotics and low pH, controllable lifespan and easy retrieval of genomically recoded bacteria. To highlight the versatility of DEPCOS, we demonstrated that robustly encapsulated cells can execute useful functions, including performing cell-cell communication with other encapsulated bacteria and sensing heavy metals in water samples from the Charles River."
} | 291 |
30018381 | PMC6050331 | pmc | 7,584 | {
"abstract": "Recent advances in the preparation of shape-shifting and size-growing nanostructures are hot topics in development of nanoscience, because many intelligent functions are always relied on their shape and dimension. Here we report a tunable manipulation of sequential self-assembled transformation in situ via a hierarchical assembly strategy based on a living thiol–disulfide exchange reaction. By tailoring the external stimuli, the reactive points can be generated at the ends of initially unimolecular micelles, which subsequently drive the pre-assemblies to periodically proceed into the hierarchically micellar connection, axial growth, bending, and cyclization processes from nanoscopic assemblies to macroscopic particles. Of particular interest would be systems that acquired the shape control and size adjustment of self-assemblies after termination or reactivation of disulfide reshuffling reaction by regulating external stimuli whenever needed. Such a hierarchical strategy for self-assembled evolution is universally applicable not only for other disulfide-linked dendritic polymers but also for exploitation of biological applications.",
"introduction": "Introduction The “bottom up” or “engineering up” approach from a single molecule to functional architectures has a great significance in understanding biologically spontaneous self-assembly process, which offers an efficient strategy for creating a myriad of well-organized nanostructures in applications of drug delivery, cosmetics, dispersant technology, photonic detector, sensor, and nanoreactor arenas 1 – 12 . Recently, a great effort has been focused on the dynamic process of solution-assembled nanostructures in highly selective solvents through the elaborate design of the molecular architectures and careful control of the external environments to study the real-time self-assembled evolution. The preparation of shape-shifting and size-growing structures is emerging as one of the advanced strategies in organic-based nanoscience and nanotechnology, because most of the smart functionalities of nanocarriers are directly determined by their shapes and sizes, which not only provides detailed information on the structural transformation but also guides the outcome of morphology and functionality in response to outside stimuli. Frequently used methodologies to create temporal evolution of the self-assembly pathway always require precise polymer syntheses, sophisticated architectural design (hydrophobic/hydrophilic balance, composition, geometry, dimension, surface chemistry, and flexibility) 13 – 35 , fine control of the environmental conditions (pH, temperature, stress, photons, ultrasound, ionic strength, and solvents) and sophisticated optimization of solution assembly kinetic pathways 36 – 45 . Nevertheless, these methods are still unable to delicately manipulate the self-assembly system and veritably obtain the full-scale solution assemblies due to the difficulty in achieving the precise control of amphiphilic inherent essences at any moment once the self-assembly system is initiated. In other words, regulation of real-time morphology evolution with an instant on/off function at arbitrary time to gain the desired self-assemblies remains a grand challenge. To circumvent this problem, it is greatly desired to design the manipulative reactions and conditions to tailor self-assembly systems with the strict criteria that the self-assembly behaviors should be able to be activated, controllably terminated and interrupted, and reinitiated by the external stimuli whenever needed, because many envisioned applications endeavor to exploit solution assemblies as intelligent nanocontainers for the high encapsulation and controlled release of small molecule cargoes, requiring a detailed understanding of the dynamic processes, long-term stability, and stimulative responsibility of solution assemblies. Our previous studies exploited a living controlled hydrogel formation method for tailor-made in situ gelling systems 46 , 47 . Specifically, a star-shaped POSS-(SS-PEG) 8 molecule (Supplementary Fig. 1 ), containing a disulfide-linked core/shell structure with one polyhedral oligomeric silsesquioxane (POSS) core and eight easy-leaving polyethylene glycol (PEG) shells, was adopted to produce various hybrid hydrogels with customized structures and properties based on a pH-responsive on/off reaction. Supplementary Fig. 2 illustrated the mechanism of pH-triggered thiol–disulfide exchange reaction that could result in the dissociation of PEG shells and linkage of POSS cores. The driving force was shifting of equilibrium toward the stable disulfide-linked products through the release of PEG shells on account of the selective core/shell separations. So, rational control of system pH and reaction time can tailor the hydrophobic/hydrophilic ratios and topologies, thus manipulating the self-assembled architectures and dimensions in aqueous media. In this case, it is believed that the continuously time-dependent morphology transformation and size evolution with an instant on/off function can be facilely achieved by this switchable method. Of particular interest would be systems that acquired the shape control and size adjustment of self-assemblies after termination or reactivation of the disulfide reshuffling reaction by regulating the system pH. Herein we propose a living hierarchical self-assembly strategy to manipulation of the morphology and size evolution in situ by tuning the pH stimuli to activate and/or terminate the thiol–disulfide exchange reaction of the amphiphilic POSS-(SS-PEG) 8 polymer (Fig. 1 ). By activing the disulfide reshuffling reaction in aqueous solutions, the constructive linkage of POSS-embedded domains and removal of PEG segments caused the amphiphiles gather into unimolecular micelles, which acted as the pre-assemblies that further proceeded to the micellar connection, axial growth, bending, and cyclization processes driven by the reactive points at the ends with high-sufficient activity, presenting a periodically hierarchical self-assembly behavior on the all of nanoscales, microscales, and macroscales. Besides, the rigid POSS-embedded backbone and strong aggregation ability can furnish these POSS-containing hybrid polymers with unique self-assembly behaviors 48 – 57 , thereby generating various nanostructures with a second level of hierarchy. Notably, such a real-time self-assembled evolution could be interrupted at any point of time by neutralization or restarted by rebasification. Using this principle, many sophisticated materials with controlled structures and special properties may have great applications in biomedical platform. Fig. 1 Controllable strategy for morphology evolution with a pH-switched on/off function. Schematic representation of the living controlled thiol–disulfide exchange reaction and the pH-triggered self-assembled evolution. When the thiol–disulfide exchange reaction is activated in the presence of catalytic thiols in pH 12 solutions, the selective core/shell separation gradually leads to the continuous connections of POSS-embedded cores; in this case, the self-assembled evolution is performed from unimolecular micelles to the elliptic nanoparticles. Once neutralizing the system pH to 7 at any moment, the exchange reaction is deactivated, and thus no further morphology evolution is conducted any more. However, these stable inert sites can be reactivated by basification whenever needed, and the trapped morphology evolution can return back on the previous track",
"discussion": "Discussion In summary, we demonstrated a tunable manipulation of solution assemblies evolution in situ based on the living hierarchical self-assembly of amphiphilic POSS-(SS-PEG) 8 polymer. Careful tailor of the pH-triggered thiol–disulfide exchange reaction and self-assembled conditions could make the reactive points at the ends of these nanoparticles with high activity, thus presenting the intriguing morphology and size evolutions like periodically micellar connection, axial growth, bending and cyclization processes from the initially unimolecular pre-assemblies on the stepwisely self-assembly behaviors, by which the multifarious morphologies like spherical micelles, cylinders, vesicles, worm-like micelles, hollow spheres, and elliptic nanoparticles as well as the gradual size growths were formed in sequence. Such controllable strategy to guide the hierarchical self-assembled evolution was applicable from the nanoscopic assemblies to microscopic and macroscopic aggregates. Notably, this hierarchical self-assembled evolution could be interrupted and reactivated at any moment only by removal of the external stimuli, and thus the desirable morphology and size was facilely gained with good stability, which provided unique advantages and more opportunities to fabricate the intelligent drug carriers with high loading efficiency and stimuli-responsive property. This hierarchical concept to program the dynamic morphology and size evolution is also universal for other disulfides-linked dendritic polymers with well-structured cores, which will provide useful guidance for achieving more well-worth exploring self-assembly mechanism and artificial superstructures with defined shapes and desired functions."
} | 2,320 |
36133490 | PMC9416975 | pmc | 7,585 | {
"abstract": "The continuous expansion of smart microelectronics has put forward higher requirements for energy conversion, mechanical performance, and biocompatibility of micro-energy storage devices (MESDs). Unique porosity, superior flexibility and comfortable breathability make the textile-based structure a great potential in wearable MESDs. Herein, a timely and comprehensive review of this field is provided according to recent research advances. The following aspects, device construction of textile-based MESDs (TMESDs), fabric processing of textile components and smart functionalization ( e.g. , mechanical reliability, energy harvesting, sensing, self-charging and self-healing, etc. ) are discussed and summarized thoroughly. Also, the perspectives on the microfabrication processes and multiple applications of TMESDs are elaborated.",
"conclusion": "5. Conclusion and perspective The growing demand for miniaturized flexible devices will lead to the rapid development of TMESDs and derive a variety of applications. In this review, the constructing methods of TMESDs, the role of fabrics in flexible MESDs and the applications that meet the actual scenarios are elaborated and summarized, so as to systematically describe the development of TMESDs. Following the introduction to device design, several typical microfabrication techniques are discussed in details and compatibility with fabric still needs much attention. We elaborated the construction of thin-film MESDs and fiber-shaped MESDs from the perspective of the electrode material. Commercial fabrics have better control of cost while making higher requirements of other functional additives and active agents. Given interdigital MESDs, we believe the compatibility between microelectrode materials and the process of precise micro–nano fabrication will pave the way for higher energy and power densities. Furthermore, we summarized the processing strategies of functionalized fibres based on their different dimensions. By preparing a single conductive unit or integrating electronic function into large-area textiles, functionalized improvements are achieved, providing the ordinary fabric more opportunities and a more intelligent life to match people's desires. Regarding practical applications, realistic requirements such as energy storage, mechanical reliability, customizable shapes, sensing, and self-healing are put forward. In the future, electronic integration on comfortable clothing will probably appear as a display screen or a real-time monitor. And a rapid increase in innovative research results and publications is emerging. Despite great achievements, there are still some critical challenges. These improvements mainly concentrate on rational designs, new microconstruction techniques, and innovative electrode materials. For security purposes, it is necessary to consider replacing the toxic element in electrolyte with degraded polymer. From the point of microfabrication technique, it is a challenge for miniaturization processes to coexist with material preparation, such as obtaining high-resolution patterns without destroying the growth of active materials. When meeting the demand for power sources, some actual requirements such as washability, less occupancy of space, lightweight also make sense. Besides, there are more cooperative ways between textile and nanomaterials to be explored. The new smart textiles will be presented in future studies.",
"introduction": "1. Introduction The field of portable electronics is gradually broadening as an essential concomitant for decades with the development of the Internet of Things (IoT). 1–4 Among them, the combination of artificial intelligence and highly integrated microelectronics has derived significant advantages and many applications are developed, such as electronic textiles, 5 intelligent sensor 6 and smart medical implant. 7 Miniaturized components and microfabrication processes endow micro energy storage devices (MESDs) with high energy density for practical applications. Based on requirements of energy supply, the fabricated MESDs should show desirable flexibility and durability for practical applications. However, most of the MESDs under chemical and mechanical strain will form multiple fractures and eventually lose electrical contact. Therefore, apart from favorable electrochemical performance, it is also a challenge for such a micropower source to have excellent mechanical performance. 8 Textiles serve as the daily necessities with a rich history dating back thousands of years and are attracting much attention because of their unique porosity and high flexibility. 9–11 The rough and porous structure of textiles is beneficial for high electron transport, and can be bent, twisted even rolled up without any cracks caused by the bending stress, resulting in both outstanding electrical and mechanical performance ( Scheme 1 ). 12 Scheme 1 A concept map of TMESDs. “Construction”: reproduced with permission. 13 Copyright 2016, American Association for the Advancement of Science. Reproduced with permission. 14 Copyright 2019, American Chemical Society. Reproduced with permission. 15 Copyright 2021, Elsevier. “Technique fundamental”: reproduced with permission. 16 Copyright 2021, Elsevier. Reproduced with permission. 17 Copyright 2020, De Gruyter. Reproduced with permission. 18 Copyright 2020, American Chemical Society. “Functionalization”: reproduced with permission. 19 Copyright 2019, American Chemical Society. Generally, the contribution of textiles to the micro device/system is mainly reflected in the following aspects. For fibers with large microscopic diameters, nanostructures can be built inside or on the surface to achieve the goal of overall modification. Spinning technology that adds conductive functional materials to the precursor is developed rapidly in recent years. 13 Electrospinning technology acting under high electric potential produces fibers with a diameter at a nanometer scale, such as carbon nanofibers with high electrical conductivity and large-range stretchability. 20 Simultaneously, the all-fiber structured textile-based pressure sensor made by this strategy has the desired sensing accuracy. 21 Modifying the surface of textile is also a feasible processing method. Among them, printing technology can selectively deposit electronic components, and the compatibility of printing ink for textile allows the microelectrode composed of conductive layers to directly cover the surface of the textile. Furthermore, a single fiber embedded with electronic function can be woven into large-area clothing fabric. Crisscross networked structure endows fabric ductility, achieving a large-scale extension of electronic functions, such as electroluminescence. Processing fabrics at different dimensions satisfies the customized construction of devices. In terms of energy conversion equipment, MESDs such as microbattery (MB) and microsupercapacitor (MSC) possess significant advantages. In the matter of appearance, high integration of MESDs provides the device with multifunction and compact construction that is tailored to portability. For energy loading, miniaturized electrochemical equipment ensures high energy density and stable voltage output. MSCs have an ultrahigh power density, long operating lifetime 22 (>100 000 cycles) and fast charge/discharge in seconds. 23 While MBs have more advantages in energy storage owing to their outstanding energy density. To date, wearable devices have increasing requirements on textile-based MESDs (TMESDs), such as electronic skin (e-skin), 24 and textile-based displays. 25 According to the type of microelectrode, MESDs can be divided into sandwiched thin-film MESDs, 26 interdigital MESDs 27 and fiber-type MESDs. 28 Specifically, fiber-shaped miniaturized devices possess unique one-dimensional (1D) ductility and intrinsic knittability due to high-aspect-ratio fibers. The main challenges for fiber-shaped microdevices are ascribed to the preparation of functional nanomaterials for hybrid fiber electrodes and the integration with other components. Compared with the 1D structure, it is more convenient to obtain stacked micro/nano structures and interlayer functionalization in the 2D planer structure. 28,29 Interdigital devices fabricated by constructing process with elaborate parallel finger-shaped microelectrodes facilitate higher energy loading and adjustable width for fast ion transport in the microelectrode. Simultaneously, it puts forward extremely strict requirements on the micromachining process. The uneven surface of the fabric, for example, facilitates the production of lithographic patterns. In addition to micromachining accuracy, the compatibility between material and the textile substrate should be taken into account as well. As an instance, laser engraving utilizing the thermal energy of laser beam without chemical reactions will obtain intact electrode patterns without influence on fabric fibers. 30 Hence, several elements around TMESDs should be taken into consideration, namely, stability of active material, 31 textile-fitting miniaturization technology, 32 and outstanding mechanical reliability of devices. 30 Serving as one important product with great potential in consumer electronics, flexible wearable equipment is flourishing with the increasing demand and textile-based miniaturized devices. 22 To date, the fabric characteristics and applications are reported as a starting point in various fields. However, few reviews discuss the application of textiles in microelectronics, especially MESD from the perspective of construction. Herein, we discuss recent advances in wearable TMESDs from the following aspects of device design, techniques fundamental in multiple functional textiles and their emerging applications. Finally, the critical challenges in smart textile devices and systems are elaborated and summarized, also further perspectives are proposed."
} | 2,488 |
35082431 | PMC9123188 | pmc | 7,587 | {
"abstract": "Hydrothermal plumes transport reduced chemical species and metals into the open ocean. Despite their considerable spatial scale and impact on biogeochemical cycles, niche differentiation of abundant microbial clades is poorly understood. Here, we analyzed the microbial ecology of two bathy- (Brothers volcano; BrV-cone and northwest caldera; NWC) and a mesopelagic (Macauley volcano; McV) plumes on the Kermadec intra-oceanic arc in the South Pacific Ocean. The microbial community structure, determined by a combination of 16S rRNA gene, fluorescence in situ hybridization and metagenome analysis, was similar to the communities observed in other sulfur-rich plumes. This includes a dominance of the vent characteristic SUP05 clade (up to 22% in McV and 51% in BrV). In each of the three plumes analyzed, the community was dominated by a different yet uncultivated chemoautotrophic SUP05 species, here, provisionally named, Candidatus Thioglobus vadi (McV), Candidatus Thioglobus vulcanius (BrV-cone) and Candidatus Thioglobus plumae (BrV-NWC). Statistical analyses, genomic potential and mRNA expression profiles suggested a SUP05 niche partitioning based on sulfide and iron concentration as well as water depth. A fourth SUP05 species was present at low frequency throughout investigated plume samples and may be capable of heterotrophic or mixotrophic growth. Taken together, we propose that small variations in environmental parameters and depth drive SUP05 niche partitioning in hydrothermal plumes.",
"conclusion": "Conclusion By applying several complimentary culture-independent techniques, supported by an extensive set of geochemical measurements, we could shed light into the ecology of three novel candidate species of the clade SUP05. As expected, reduced chemical compounds present in the plume seem to have a significant influence on niche differentiation. Water depth seems to be another important factor. We show that the bathypelagic plumes are dominated by two different, yet uncultivated SUP05 species, Candidatus Thioglobus vulcanius, and Candidatus Thioglobus plumae, whereas the mesopelagic plume is dominated by the also yet uncultivated species Candidatus Thioglobus vadi. Knowing the physico-chemical characteristics of the environment, it is possible to predict the dominant SUP05 species in plumes of different hydrothermal systems, and vice versa certain SUP05 species might be indicators for the prevailing plume characteristics.",
"introduction": "Introduction Hydrothermal vents occur along oceanic spreading zones and volcanic arcs, in back-arc basins, and in intra-plate volcanoes. At these sites, high-temperature fluids enriched in reduced chemical compounds vent from the seafloor and mix with ambient seawater until they reach a depth of neutral buoyancy. These plumes spread over large spatial scales and thus, have a substantial impact on biogeochemical cycles [ 1 – 4 ]. As the vent-sourced catabolic energy input is considerable for the deep-sea [ 5 ], plumes offer a thriving habitat for microorganisms. Microbial communities inhabiting hydrothermal plumes are diverse, owing to the mixing of typical deep-sea bacteria, such as SAR11, SAR324 and MG-I Archaea [ 6 ] with chemolithoautotrophs indicative of the different physico-chemical plume signatures [ 7 , 8 ]. A microbial clade well known to inhabit hydrothermal sulfur-rich plumes, is the SUP05 clade within the Gammaproteobacteria [ 9 ]. Members of this diverse clade have successfully adapted to various lifestyles such as free-living organisms in plumes [ 8 ], oxygen-minimum zones (OMZ) [ 10 – 12 ], pelagic redoxclines [ 13 , 14 ] and as symbionts of clams, mussels and sponges [ 15 – 17 ]. In addition to dark carbon fixation fueled by reduced sulfur compounds and hydrogen oxidation [ 18 ], SUP05 clade bacteria have also been postulated to maintain a heterotrophic metabolism [ 19 , 20 ]. Several representatives of this clade have already been cultivated and assigned to the genera Candidatus Thioglobus and Pseudothioglobus [ 21 – 23 ]. Despite the widespread occurrence and high diversity of this clade, the localization and niche partitioning of SUP05 in hydrothermal plumes has not yet been elucidated. In this study, we address microbial diversity and niche partitioning of SUP05 in hydrothermal plumes derived from degassing volcanoes in the Kermadec intra-oceanic arc. The vent fluids in this hydrothermal system exhibit large compositional variability due to differences in the type of sub-seafloor magmatic-hydrothermal reactions and water depth [ 24 , 25 ]. We investigated three plumes in the Kermadec Arc, one of which is sourced from Macauley volcano (McV, ~300 m depth) and the other two are sourced from two distinct hydrothermal sites hosted in the Brothers volcano (BrV, ~1600 m depth). Kleint et al. [ 26 ] have shown that the geochemical variability of these vent fluids in terms of acidity as well as metal and gas contents is extremely large. In our study, we combined an extensive geochemical dataset with 16S rRNA gene analysis, fluorescence in situ hybridization (FISH), metagenomics and metatranscriptomics to distinguish different species within the SUP05 clade and develop a hypothesis on SUP05 niche separation.",
"discussion": "Discussion Sulfur-rich plumes act as oases for chemolithoautotrophic SUP05 [ 56 , 58 , 68 ]. In order to better understand their diversity and ecology, we investigated the microbial communities of three plumes expelled by two submarine volcanoes with a multidisciplinary approach. Thereby, we were able to characterize and describe three new, yet uncultivated SUP05 species, Candidatus Thioglobus vadi (corresponding to SUP05-1-4), Candidatus Thioglobus vulcanius (corresponding to SUP05-5) and Candidatus Thioglobus plumae (corresponding to SUP05-6; Table S7 ). Each of these three species dominated a different plume which suggests that they partition into different environmental niches. SUP05 niche differentiation As the sulfur-oxidizing SUP05 were the prominent primary producers in McV and BrV, we compared the SUP05 populations of three plumes. This comparison revealed a distinct presence of SUP05 species in bathy- and mesopelagic plumes. The BrV was composed of two bathypelagic plumes, which were dominated by different SUP05 clusters, SUP05-5 in the BrV-cone (~1300 mbsl) and SUP05-6 in the BrV-NWC (~1600 mbsl), suggesting a niche differentiation between the two plumes. Since these MAGs fulfill the standards given in Konstantinidis et al. [ 69 ] and Murray et al. [ 70 ] for a genome-based taxonomy, we propose SUP05-5 as Candidatus Thioglobus vulcanius and SUP05-6 as Candidatus Thioglobus plumae (Table S7 ). Both species were more abundant in bathypelagic plumes (Abe, Mariner, Tahi Moana, Kilo Moana and Tui Manilla) compared to SUP05-1-4 but exhibited extremely low abundance in other analyzed locations (DCM, surface and deep open ocean), establishing their niche in the bathypelagic sulfur-rich plumes. Regarding the factors that drive the niche differentiation between these two species in BrV-cone and BrV-NWC, Ca . T. vulcanius seemed to be better equipped to endure the toxicity of heavy-metals present in the plume (Fig. S15 ). However, different properties such as substrate affinity and sulfide toxicity still need to be investigated [ 23 ]. Secondly, SUP05-1-4 represented the dominant SUP05 species in the mesopelagic plume of McV (~300 mbsl), and were present at higher abundances in the open ocean and specifically the coastal areas. In line with our observation in McV, SUP05-1-4 also prevail in a mesopelagic buoyant plume sampled at Woody Crack in a depth of 828 m. According to ANI values, SUP05-1-4 MAGs are evidently strains of the same species. Although the completeness of these MAGs does not exceed 85%, likely reflecting the challenges arising from high strain heterogeneity, MAG-1 to 4 fulfill the standards given in Konstantinidis et al. [ 69 ] and Murray et al. [ 70 ] to be characterized as a new Candidatus species. Here, we propose the name Candidatus Thioglobus vadi, meaning bacterium “of a shallow place”. Statistical analysis suggests that this species prefers oxygenated sites with lower sulfide (highest abundance in 10CTD_b4–202.3 µM H 2 S) and higher iron concentration (10CTD_b4–22.2 nM; Fig. 2 ). Global distribution of Ca . T. vadi indicates that also depth may have a niche determining effect (Figs. 7A and S13 ). Fig. 7 Overview of features of newly described SUP05 species and hypothesis on their distribution. A SUP05 clade unique features found in MAGs: Candidatus Thioglobus vadi, Candidatus Thioglobus vulcanius and Candidatus Thioglobus plumae, dominating different plumes. B Suggested schematic distribution of the SUP05 population in the cold oxygenated background water as it mixes with the hot reduced fluid and subsequently is diluted with the plume. The SUP05 population is represented with white dashed circles and the chemical reduced species are depicted in black circles. The size of the circles refers to the concentration of reduced species and the abundance of the SUP05 clade. C Sketch depiction of the communities in three bathy- and mesopelagic plumes. Global patterns of the SUP05 species are based on their reads per kilobase per million mapped reads (RPKM) in the surface and deep chlorophyll maximum (DCM) TARA Ocean metagenomes. Epsilonprotebacteria have recently been reclassified to Campylobacterota (phyl. nov.) [ 85 , 86 ]. SUP05 MAG-7_1, 7_2 and 7_3 affiliated to Ca . Pseudothioglobus singularis, a representative of the recently classified Pseudothioglobus genus [ 23 ]. They were characterized by high expression of oligopeptide, branched-chain amino acid and nucleoside transporters (Fig. S11c ), and a missing sulfur-oxidizing (SOX) pathway. Growth experiments done by Spietz et al. [ 20 ], using the closely-related species CPS PS1, reported that carbon fixation is not critical for their growth and suggested the capacity for heterotrophy. Nevertheless, due to the low completeness of the MAGs, it is challenging to identify the lifestyle of these closely-related species. In conclusion, niche differentiation of SUP05 within hydrothermal plumes, seems to predominantly affect chemoautotrophic subclades, whereas supposedly heterotrophic SUP05, like MAG-7_1 to MAG-7_3 are more omnipresent (Figs. 2 and 7C ). Considering the role of iron It was previously shown that SUP05 bacteria use energy gained from the oxidation of reduced sulfur species to fuel dark carbon fixation [ 71 ]. Particularly, the SUP05 clade is distinguished by the formation of sulfur globules and the oxidation of sulfur via the reverse dissimilatory sulfate reduction pathway (rDSR) [ 72 ]. The ability to hoard sulfur is an advantageous trait that could support a cosmopolitan and opportunistic lifestyle. In order to understand the potential preference of Ca . T. vadi for iron-rich niches, we conducted an in-depth investigation of its genetic potential and expression profiles. Similar to Ca . T. autotrophicus, our data support the oxidation of reduced sulfur compounds with oxygen as electron acceptor. Typically, genes coding for proteins involved in sulfur oxidation are the most expressed in hydrothermal vent plumes [ 56 ] due to the thermodynamic favourability of oxidizing sulfur compounds. The total dissimilatory energy available is eight times greater for sulfide oxidation. Indeed, in Ca . T. vadi, sulfur oxidation related genes were among the most expressed. Also, the high mRNA expression level of cytochrome genes was noteworthy. This expression coincided with an exceptionally high number of cytochrome genes in the McV metagenomes compared to those from background seawater and other sites. Since cytochromes participate in energy conversion processes in the respiratory chain and during iron oxidation, the high expression of them in Ca . T. vadi could either mean that these cells were highly active, or that they were engaged in iron oxidation [ 64 ]. The first explanation is not supported by a relatively low expression of Ca . T. vadi house-keeping genes (Fig. S4a ). Iron oxidation by Ca . T. vadi is also hard to verify, yet the following two considerations might make it at least plausible. Firstly, although under neutral pH, the spontaneous chemical oxidation of iron outcompetes the biological oxidation [ 73 ], in situ measurements indicate that the excess sulfide keeps Fe reduced due to a catalytic cycle. Slowly oxidizing nanoparticulate pyrite might therefore likely persist in the plume [ 74 , 75 ]. Secondly, the exceptionally high expression of cytochrome oxidases genes might be linked to iron oxidation. However, the diversity of iron oxidation (FeOx) pathways and the divergence of the genes involved in iron oxidation [ 64 , 76 , 77 ] pose major challenges when assessing MAGs [ 78 ]. Nevertheless, we compared the SUP05 MAGs to the basic model of neutrophilic iron oxidation in Zetaproteobacteria [ 79 ]. SUP05 MAGs possess genes encoding for modules of the FeOx model, including cbb3 cytochrome c oxidase, bc1 cytochrome c oxidase, NADH dehydrogenase and ATP synthase. Although, cytochromes reported to be involved in FeOx extracellular electron exchange such as Cyc2, Pio or MtrCAB [ 73 ] were missing in Ca . T. vadi MAGs, other cytochromes with multiple heme-binding motifs (-CXXCH-) [ 65 ] were expressed. Here, the function of porin-cytochromes for electron transport could be substituted by multiheme cytochromes with Fe, potentially in a pyrite form, being oxidized by a different cellular mechanism other than the one known from neutrophilic iron-oxidizing bacteria [ 80 ]. Therefore, in our case, the iron oxidation hypothesis on Ca . T. vadi was supported by: (1) a high number of cytochrome genes being expressed; (2) cytochromes containing heme-binding motifs, which could substitute known modules in the neutrophilic FeOx pathway; (3) positive influence of DFe concentration on Ca . T. vadi abundance. We conclude that, although, there are good hints for iron oxidation by Ca . T. vadi, these are not yet conclusive. Plume ecology The ability of SUP05 to constitute up to 50% of the microbial community in an ephemeral plume remains enigmatic considering their immotility. Since SUP05 are absent in the early stages of the plume, due to suboptimal conditions, Sheik et al. [ 68 ] and Lesniewski et al. [ 81 ] suggested that vent-adapted microorganisms (SUP05) are entrained from surrounding water. This hypothesis is in line with our findings (Fig. 6 ) and other studies which have shown the influence of the background microbial community on the plume [ 4 , 82 ]. As the background seawater contains a low number of SUP05 cells (5.94 × 10 2 cell/ml—04CTD_b4; Fig. S4 ), only a low number of cells entrains the plume. In the plume, SUP05 reaches up to 1.56 × 10 4 cell/ml (04CTD_b6), suggesting that they can react swiftly to reduced chemical species and are capable of rapid growth in their preferable spot in the hydrothermal plume (Fig. 7B ). We observed that the absolute cell concentration of SUP05 in plumes was independent of depth (BrV—054CTD_b8: 2.68 × 10 4 cell/ml; McV—10CTD_b4: 3.49 × 10 4 cells/ml), although, due to the low number of cells in the deep-sea, the 16S rRNA analysis gives the impression that the bathypelagic plumes have a higher abundance of SUP05 (Fig. 2 ). On the contrary, the SUP05 “preferable spot” is an ephemeral site, which is characterized by low temperature, high oxygen concentration and low concentration of reduced sulfur species [ 58 ]. Shah et al. [ 71 ] showed that concentrations as low as 10 nM of reduced sulfur could support sulfur oxidation in oxygenated seawater. Therefore, owing to their ability to use miniscule amounts of reduced chemical species and to store sulfur [ 71 , 83 ], SUP05 persevere in the background water (Fig. 6 ) as the cold water mixes with the hot reduced fluid (Fig. 7 ). Nevertheless, the dilution of the plume and the depletion of reduced chemical species, is followed by a reduction in SUP05 abundance. This could be observed in the 54CTD samples, where the vertical profile of SUP05 abundance closely resembles the vertical profile of the plume indicators (Table S8 ). As the plume gets diluted, background seawater could feedback into the plume and re-introduce microorganisms [ 68 ], especially since the age of the plume is shown to be up to ~30 days [ 84 ]. Due to this cycle of entrainment and dilution of the vent-adapted microorganisms such as SUP05, the plume acts as growth chambers for SUP05, from which they are released into the surrounding water and could re-inoculate plumes."
} | 4,176 |
32082342 | PMC7000926 | pmc | 7,589 | {
"abstract": "The complex and heterogeneous polyphenolic structure of lignin confers recalcitrance to plant cell walls and challenges biomass processing for agroindustrial applications. Recently, significant efforts have been made to alter lignin composition to overcome its inherent intractability. In this work, to overcome technical difficulties related to biomass recalcitrance, we report an integrated strategy combining biomass genetic engineering with a pretreatment using a bio-derived deep eutectic solvent (DES). In particular, we employed biomass from an Arabidopsis line that expressed a bacterial hydroxycinnamoyl-CoA hydratase-lyase (HCHL) in lignifying tissues, which results in the accumulation of unusual C 6 C 1 lignin monomers and a slight decrease in lignin molecular weight. The transgenic biomass was pretreated with renewable DES that can be synthesized from lignin-derived phenols. Biomass from the HCHL plant line containing C 6 C 1 monomers showed increased pretreatment efficiency and released more fermentable sugars up to 34% compared to WT biomass. The enhanced biomass saccharification of the HCHL line is likely due to a reduction of lignin recalcitrance caused by the overproduction of C 6 C 1 aromatics that act as degree of polymerization (DP) reducers and higher chemical reactivity of lignin structures with such C 6 C 1 aromatics. Overall, our findings demonstrate that strategic plant genetic engineering, along with renewable DES pretreatment, could enable the development of sustainable biorefinery.",
"conclusion": "Conclusions Plant cell wall engineering has been developed for the production of biofuels and renewable chemicals. In this study, we strategically expressed the HCHL gene in Arabidopsis to reduce the degree of lignin polymerization via incorporation of side-chain-truncated monomers in lignin polymer ends. The transgenic Arabidopsis yielded higher levels of fermentable sugars compared to WT plants when pretreated with the lignin-derived DES at mild conditions. The results of this work clearly indicate that interfering with the lignin biosynthetic pathway has the potential to improve the conversion of biomass into biofuels and other intermediate products. Together with the development of tailor-made biomass that is more amenable to chemical processes, biomass pretreatment using a renewable DES could make the biofuel industry more economically feasible in the future.",
"introduction": "Introduction Growing concerns over global warming and our over-dependence on fossil resources have forced society to demand sustainable and green products ( Isikgor and Becer, 2015 ). Lignocellulosic biomass presents a promising source of renewable carbon, holding enormous potential for the production of chemicals and fuels. In order to utilize biomass as a source of renewable energy and chemicals, there have been significant efforts to develop an efficient process for biomass conversion ( Demirbaş, 2001 ). Among several technologies developed within the biorefinery concept, the production of second-generation biofuels (e.g., bioethanol) from lignocellulosic biomass is well established and close to commercialization. Despite the successful demonstration of biomass conversion to biofuels, the production of cellulosic biofuels still encounters several technical challenges for achieving a sustainable energy future ( Dale et al., 2014 ; Maity, 2015 ; Kim and Kim, 2018 ). Lignin, an essential component of biomass that provides mechanical strength for upright growth and acts as a physical barrier against pathogens ( Boudet, 2007 ), is often blamed for conferring recalcitrance to biomass against processing and utilization. In the typical biological conversion process, effective removal of lignin is crucial to maximize the utilization of carbohydrates to produce fuels and building block chemicals ( Ding et al., 2012 ; Ragauskas et al., 2014 ). However, considering its complex and heterogeneous structure, hydrophobic character, and other intractable properties, lignin is one of the most challenging biomaterials to handle ( Himmel, 2009 ). During the last decades, researchers have developed several routes to overcome lignin-associated recalcitrance. For example, the lignin-first approach was introduced to extract the reactive lignin at the early stage of biomass fractionation, providing opportunities for the use of both lignin and carbohydrates ( Renders et al., 2017 ). In contrast to the conventional carbohydrates-oriented pretreatment technologies of biomass, this new biorefinery scheme offers potential valorization routes for both lignin fractions and residual carbohydrates. While the above strategy focuses on the development of processes to overcome the technical difficulties related to lignin, another effort to reduce the biomass recalcitrance through genetic engineering has shown its effectiveness ( Chen and Dixon, 2007 ; Bhagia et al., 2016 ; Thomas et al., 2017 ). Previously, biomass cell wall engineering was directed to strategically reduce total lignin content by downregulating one or more enzymes in the monolignol pathway, which includes cinnamate 4-hydroxylase ( C4H ) ( Schilmiller et al., 2009 ), 4-coumarate-CoA ligase ( 4CL ) ( Xu et al., 2011 ), and cinnamoyl-CoA reductase ( CCR ) ( Chabannes et al., 2001 ). Although the decrease in the amount of lignin was proven to improve processing efficiency, this method often involves an agronomic penalty ( Bonawitz and Chapple, 2013 ). Moreover, modification of lignin monomeric composition leading to structural modifications has been extensively studied to make biomass more amenable to processing without compromising biomass yield. In-planta expression of a bacterial 3-dehydroshikimate dehydratase resulted in the higher deposition of H-units and lower amounts of G- and S-units, resulting in more than a two-fold improvement in saccharification efficiency ( Eudes et al., 2015 ). Incorporation of chemically labile ester linkages (zip-lignin) in the lignin backbone was proven to enhance biomass pretreatment efficiency ( Wilkerson et al., 2014 ; Kim et al., 2017 ). Previous work also reported a strategy for the overproduction of uncommon lignin monomers through in-planta expression of a bacterial hydroxycinnamoyl-CoA hydratase-lyase (HCHL) in biomass ( Mitra et al., 2002 ; Eudes et al., 2012 ). \n Figure 1 \n describes the enzymatic reactions catalyzed by HCHL which is expressed in lignifying tissues of engineered plants. HCHL cleaves the side-chain of coumaroyl-CoA and feruloyl-CoA, resulting in an increased amount of unusual C 6 C 1 end-groups in lignin, including 4-hydroxybenzaldehyde, vanillin, syringylaldehyde, and 4-hydroxybenzoic acid ( Eudes et al., 2012 ). Figure 1 Enzymatic steps catalyzed by hydroxycinnamoyl-CoA hydratase-lyase (HCHL). The two products of HCHL activity (in gray) are converted into several other C6C1 aromatics in plant tissues. PAL , phenylalanine ammonia lyase; C4H , cinnamate 4-hydroxylase; 4CL , 4-coumarate-CoA ligase; HCT , hydroxycinnamoyl-CoA shikimate hydroxycinnamoyl transferase; C3H, coumarate 3-hydroxylase; CSE , caffeoyl shikimate esterase; CCOMT, caffeoyl-CoA O -methyltransferase. Bio-derived deep eutectic solvents (DESs) have gained considerable attention because of their potential uses in biomass pretreatment and processing. DESs are mixtures of compounds formed by strong intermolecular hydrogen bonds, resulting in a lower melting point than that of any individual component ( Dai et al., 2013 ). As an alternative to organic solvents for biomass pretreatment, DESs exhibit promising solvent properties including high dissolution capability, low vapor pressure, tunability, stabilization of carbohydrates through hydrogen-bond interactions, and compatibility with certain microorganisms ( Vigier et al., 2015 ). Recently, DESs synthesized from lignin-derivable phenolic compounds were found to be effective in lignin removal, and thus resulted in enhanced biomass saccharification efficacy ( Kim et al., 2018 ). Also, renewable DESs prepared from phenolic aldehydes (e.g., vanillin and 4-hydroxybenzaldehyde) with choline chloride (ChCl), integrated with the use of low-recalcitrant engineered biomass via down-regulation of cinnamyl alcohol dehydrogenase (CAD), demonstrated the potential of developing a closed-loop biorefinery process ( Kim et al., 2019 ). In this work, we employed, as a raw material for DES-assisted pretreatment, the biomass from a previously described plant genetic engineering approach that increases non-conventional C 6 C 1 monomers in lignin via HCHL expression. We also demonstrate the use of renewable DES for pretreating such biomass designed for improved processability.",
"discussion": "Discussion Throughout the last decades, cell wall engineering has been a critical approach to reduce biomass recalcitrance by altering lignin structures. Perturbations of genes on the biosynthesis pathway of lignin result in significant structural changes, which allows designing readily tractable biomass structures for the production of biofuels and chemicals ( Ralph et al., 2019 ). The strategic expression of HCHL in lignifying tissues of Arabidopsis resulted in the overproduction of side-chain-truncated (C 6 C 1 ) lignin monomers incorporated in lignin as end-groups ( Eudes et al., 2012 ). 2D HSQC NMR analysis confirms that isolated lignin from HCHL transgenic biomass contains a significant amount of oxidized C 6 C 1 units. Considering the similar lignin content with a slight difference in molecular weight of isolated lignin, as well as comparable ultrastructural morphologies between the WT and HCHL lines, we propose that engineering the biosynthesis of C 6 C 1 monomers in-planta is an effective approach to modify lignin without any agronomic penalty. In this work, VAN, an oxidized C 6 C 1 unit found in HCHL plants, was used to synthesize ChCl-VAN, a renewable DES that was previously shown to be effective for biomass pretreatment ( Kim et al., 2018 ). Furthermore, integration of lignin-derived DES with HCHL-engineered biomass offers opportunities to move closer towards achieving a closed-loop biorefinery ( Kim et al., 2019 ). The pretreatment of WT and HCHL biomass using ChCl-VAN showed that lignin removal from transgenic biomass was higher, resulting in enhanced saccharification efficiencies. Considering that lignin content in both samples is quite similar, the improvement of biomass digestibility for the HCHL line is associated with 1) significant structural alteration in lignin, and 2) the higher reactivity of short-side chain lignin monomers. Regarding the chemical properties of lignin derived from HCHL plants, DFT-based calculation revealed higher reactivity for structures corresponding to C 6 C 1 monomers linked to lignin. Moreover, lignin with side-chain-truncated monomers requires less energy for the cleavage of β-aryl ether bond, which is typically necessary for lignin fractionation during biomass pretreatment. Previously, lignins rich in H-units were computationally found to be more reactive than other types of lignins (G- and S-unit) ( Shi et al., 2016 ), and transgenic biomass consisting of H-lignin yielded higher sugars upon saccharification ( Bonawitz et al., 2014 ). As discussed above, the more reactive nature of C 6 C 1 monomers with aldehyde or carboxylic acid functionalities that form lignin end-groups contributed to the increased pretreatment efficiency followed by higher saccharification yield. It is noted that although both empirical and computational results undoubtedly support the hypothesis, more work is necessary to gain a far-reaching insight of structural modification resulting from the expression of HCHL. However, the pretreatment of transgenic biomass using a bio-derivable DES offers opportunities to operate reactors with reduced amount of energy and chemicals, which is highly desirable in developing a sustainable bioeconomy."
} | 2,982 |
37177184 | PMC10181017 | pmc | 7,591 | {
"abstract": "Chitosan/PVA nanofibrous electroresponsive soft actuators were successfully obtained using an electrospinning process, which showed fast speed displacement under an acidic environment. Chitosan/PVA nanofibers were prepared and characterized, and their electroactive response was tested. Chitosan/PVA nanofibers were electrospun from a chitosan/PVA solution at different chitosan contents (2.5, 3, 3.5, and 4 wt.%). Nanofibers samples were characterized using Fourier transform infrared analyses, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), optical microscopy, and tensile test. The electroactive behavior of the nanofiber hydrogels was tested under different HCl pH (2–6) under a constant voltage (10 V). The electroactive response test showed a dependence between the nanofiber’s chitosan content and pH with the bending speed displacement, reaching a maximum speed displacement of 1.86 mm −1 in a pH 3 sample with a chitosan content of 4 wt.%. The results of the electroactive response were further supported by the determination of the proportion of free amine groups, though deconvoluting the FTIR spectra in the range of 3000–3700 cm −1 . Deconvolution results showed that the proportion of free amine increased as the chitosan content was higher, being 3.6% and 4.59% for nanofibers with chitosan content of 2.5 and 4 wt.%, respectively.",
"conclusion": "4. Conclusions Chitosan/PVA nanofibers at different chitosan content were successfully obtained using the electrospinning method. Furthermore, the electrospun nanofibers demonstrated the potential to be used as electroactive nanofibrous actuators. The developed nanofiber actuators showed a fast tip displacement under a low voltage, reaching a maximum speed displacement of 1.86 mm s −1 at a pH 3 and a voltage of 10 V. The fact that nanofibers have a higher response may be related to their one-dimensional morphology. This increases the exposure of −NH 2 groups to the acidic environment. Consequently, the protonation of amino groups in the material is favored. The results on the electroactive response were supported by deconvoluting the FTIR spectra in the 3000–3700 cm −1 region. Deconvolution showed that the proportion of free amine changes in relation to the chitosan; samples with lower chitosan content had a lower proportion of free amine (3.6%), whereas nanofiber samples with higher chitosan content had a higher proportion of free amine (4.59%). From the electroactive response experiments, it was possible to observe a dependence on the chitosan content and the pH with the bending activation of the nanofibers. This study demonstrated that chitosan/PVA nanofiber is a potential material for the development of soft actuators using biopolymers as base material, which can be useful not only in the field of soft robotics but, due to chitosan’s biocompatibility, can open the possibility for its application in the biomedical field. Some of its potential applications can be found in the development of soft grippers for the manipulation of small objects immersed in an aqueous environment, the fabrication of electroresponsive scaffolds, or the development of microrobotic systems.",
"introduction": "1. Introduction Regarding the evolution of robotics, it is possible to observe that the aim is to develop a system capable of fully imitating a biological system. This trend is referred to as Biomimetics, which represents the study and imitation of nature’s methods, designs, and processes [ 1 ]. One of the biggest challenges faced in the field of robotics is trying to mimic the actuation systems that endow animals with locomotion. New materials have been developed addressing this situation; these materials are often referred to as soft actuators or artificial muscles [ 2 ], which can be defined as materials capable of changing their shape or size in response to physical stimuli such as light, humidity, pH, electricity, and so forth [ 3 ]. To date, many technologies have been developed for their use as soft actuators driven by various types of external stimuli, such as magnetically responsive actuators [ 4 , 5 ], shape memory polymers (SMPs) [ 6 , 7 ], and pneumatic actuators [ 8 , 9 ]. Among the many materials that can serve as soft actuators, electroactive polymers have gained the attention of scientists and engineers due to characteristics such as large deformation, flexibility, low density, tuneability, and ease of manufacture. Moreover, they exhibit a similar actuation behavior to biological muscles. Electroactive polymers (EAPs) can be classified into two major groups, depending on their actuation mechanism. In the first group are electronic EAPs (which are driven by electric field or coulomb forces), including ferroelectric polymers, dielectric elastomers, and liquid crystal elastomers. The second group is composed of ionic EAPs (which change shape by mobility or diffusion of ions and their conjugated substances), including ionic polymer gels, ionic polymer–metal composites (IPMC), conductive polymers, and others [ 10 , 11 , 12 ]. Among EAPs, dielectric elastomer actuators (DEAs) and liquid crystal elastomers have been widely studied for the development of soft actuators due to their flexibility, high energy density, high strain, and good electromechanical actuation performance. However, both DEAs and liquid crystal elastomers have disadvantages, such as high activation voltages (in kV), which can lead to dielectric breakdown [ 13 , 14 ]. In contrast, hydrogel materials have been extensively studied due to their ability to respond to various external stimuli such as light, magnetic fields, pH, and electric fields [ 15 ]. Electroactive hydrogels are a type of electroresponsive material belonging to the group of ionic EAPs. More specifically, these materials fall into the subcategory of ion-exchange polymer–metal composites (IPMCs), whose actuation is governed by the transport or migration of ions inside their three-dimensional polymeric networks [ 16 ]. Electroactive hydrogel exhibits large deformation in response to an electric field, fast actuation, and biomimetic materials properties [ 17 ]. Hydrogel-based nanofibers are a relatively new class of nanomaterials where hydrogels are structured in nanofibrous form. Hydrogel nanofiber combines the desirable properties of both hydrogel and nanofiber, such as flexibility, soft consistency, elasticity, and others [ 18 ]. Although hydrogels are great candidates for the development of stimuli-responsive materials [ 19 ], nanofibers stand out as electroresponsive materials due to their morphology. Due to the fact that the rate of actuation is inversely proportional to the size of the hydrogel, reducing the size will promote a shorter response time [ 20 ]. Because nanofibers are one-dimensional materials with a high surface-to-volume ratio, the surface area of each fiber is greater, increasing the ionization of functional groups when interacting with the medium. In addition, the high porosity of the nanofiber mat optimizes the diffusion of free ions migrating from the inside to the outside of the material and vice versa, increasing the deformation of the material and improving the mechanical strength in relation to hydrogels. In recent decades, biopolymers have been studied as potential electroactive materials [ 21 ]. Natural polymers such as chitosan, cellulose, starch, and gelatin, among others, exhibit good electromechanical properties due to their polar groups, which are vulnerable to polarization, such as amino, hydroxyl, and carboxyl [ 22 ]. Chitosan is a linear polysaccharide composed of randomly distributed deacetylated units (β-(1,4)-D-glucosamine) and acetylated units (N-acetyl-D-glucosamine). Chitosan has amino groups and hydroxyl groups on its backbone, which gives chitosan a polycationic property [ 23 , 24 ]. Due to its polycationic characteristic, chitosan has been studied for the development of electroresponsive materials. Emine et al. [ 25 ] reported a chitosan–PDAD (poly (diallyldimethylammonium chloride)) base actuator. Wang et al. [ 26 ], with the use of chitosan and cellulose, developed an electroactive paper (EAPap) actuator. Jinzhu Li et al. [ 27 ], using carbon nanotubes, electrodes, and chitosan, developed an actuator with a superfast response (~19 ms) under low voltages (>8 V). Polyvinyl alcohol (PVA) is a synthetic, linear, semicrystalline polymer that is composed of a carbon chain as the backbone and a hydroxyl group as a functional group. PVA exhibits many important features; for example, it is readily available, water-soluble, has excellent film-forming ability, and is thermostable, along with others [ 28 ]. Furthermore, it can also aid in improving fiber spinning by reducing repulsive forces within charged polymer solutions [ 29 , 30 ]. Electrospinning is a process in which a high voltage is applied to a polymeric solution injected through a capillary or needle. An electrostatic charge accumulates at the tip of the droplet; therefore, charge repulsion overcomes the surface tension of the droplet generating a cone-like jet (commonly known as a Taylor cone) and is collected on a grounded electrode plate [ 31 , 32 ]. During the electrospinning process, factors such as technical parameters (flow rate, voltage, and needle collector distance), solution parameters (conductivity, viscosity, polymer concentration), and environmental parameters have a direct influence on the morphology of the electrospun fibers [ 33 ]. This method allows the formation of a hierarchical architecture that could help mimic the fibrous morphology of biological muscles when developing nanofiber-based electroactive gels. Many works have been devoted to the study of fibrous hydrogels as soft actuators. Miranda et al. [ 34 ] reported a hybrid nanofiber hydrogel based on poly (acrylamide and acrylic acid) mixed with aniline; the electroactive response was assessed in an electrochemical cell. The hybrid material exhibited a high electrical conductivity, reaching values near 0.01 S cm −1 , as well as a fast time response (2.5 mm s −1 ) and reversible displacement at low electrical potential (1 V) in 1 MΩ cm distilled water. Ismail et al. [ 35 ] proposed a novel approach for the fabrication of flexible hydrogel nanofiber actuators based on PVA/PANI. The hybrid actuator had a maximum linear actuation strain of 1.8% in 1 M methane sulfonic acid solution and showed a stable actuation in extended electrochemical cycles reaching up to 250 cycles. Nevertheless, the number of works reporting the use of biopolymers as a base material for the fabrication of nanofiber hydrogels as soft actuators are very limited. In this work, the use of chitosan at different concentrations as a base material for the production of nanofibers hydrogel as a potential material for the development of soft actuators is reported. The electrospinning method was utilized for the formation of chitosan/PVA nanofiber mats. The electroactive response of the material was tested at different pH of HCl solution at a constant electrical potential, and the displacement speed (mm s −1 ) was measured for each sample.",
"discussion": "3. Results and Discussion 3.1. Morphology and Diameter Distribution of Chitosan/PVA Nanofibers In Figure 2 , nanofibers with 2.5, 3, 3.5, and 4 wt.% of chitosan and 5 wt.% PVA electrospun nanofibers are shown. From the obtained samples, it is possible to observe that the concentration of chitosan has a major influence on the quality of the fibers ( Table 1 ). Chitosan is a cationic polysaccharide with amino groups attached to its backbone. Amino groups react with acetic acid, forming -NH 3 ions. The protonation of amino groups generates charge repulsions causing the chitosan chains to expand. As a result, the interaction between chitosan and PVA increases, enhancing the fiber formation by maintaining the stability of the ejected jet during electrospinning. It is safe to say that a lower concentration of chitosan diminishes the entanglement and polymer–polymer interaction, thus, causing the ejected jet to lose its fibrous structure, shattering into interconnected sections [ 36 , 37 , 38 ]. Furthermore, these sections can get split into smaller sections and form spherical shapes; meanwhile, the interconnected parts will form fine filaments, as shown in Figure 2 a. 3.2. FTIR Spectroscopy With the purpose of investigating the molecular interaction in the chitosan/PVA nanofibers, the FTIR spectrum of chitosan, PVA powder, and chitosan/PVA nanofiber mat were analyzed. Figure 3 shows the FTIR spectra of chitosan, PVA and chitosan/PVA nanofibers (Cs-5, Cs-6, Cs-7, and Cs-8). The FTIR spectra of PVA exhibited characteristic absorption peaks at about 3290 cm −1 (−OH). The peak at 2937 cm −1 is related to antisymmetric CH 2 stretching. Peaks at 1709 are associated with stretching vibrations of C=O bonds present in acetate units in PVA. The peak at 1420 cm −1 refers to the vibration of C−H of the methyl group. The peak around 1087 is related to the asymmetric stretching vibration of the C−O bond of the acetate group. The 1141 cm −1 is related to the −C−O group. These results are in agreement with the reported data in the literature [ 39 ]. The FTIR of chitosan shows the characteristic absorption peak at 3354 cm −1 assigned to O−H stretching overlapped with N−H stretching. The peak at 2926 cm −1 corresponds to aliphatic C−H stretching. The peak at 1561 cm −1 is related to the stretching vibration of the amino group. Another two characteristic peaks related to the saccharide structure of chitosan can be observed at 892 and 1150 cm −1 ; similar results have been reported in [ 36 , 40 ]. For all chitosan/PVA nanofibers samples, it is noticeable that the FTIR spectra are very similar to the PVA spectra, but depending on the polymer concentrations, the peaks shift and change in intensity. It was possible to observe a broad and intense peak around 3300 cm −1 related to O−H and N−H stretching vibrations. From the spectra, it is possible to notice the formation of a hydrogen bond between PVA and chitosan, which can be deduced by the shift toward lower values of O−H and N−H stretching vibration peak of chitosan (3354 cm −1 ) to around 3300 cm −1 for chitosan/PVA nanofibers. Additionally, it was possible to notice a shift from the peak from around 1590 cm −1 to 1560. This shifting can be related to the −NH of chitosan’s group with OH groups of PVA (1562, 1558, 1557, and 1557 cm −1 for Cs-5, Cs-6, Cs-7, and Cs-8, respectively), where for the samples with higher PVA concentration (Cs-5), this peak appear less intense, which can be related to hydrogen bonding between chitosan and PVA, as well. Peaks around 1709 and 1640 cm −1 are associated with stretching vibrations of the C=O and C−O bonds of acetate units in PVA molecules. The peak at 1420 cm −1 corresponds to the vibrations of the C−H bond of the methyl group (−CH 3 ). The asymmetric stretching vibration of the C−O bond of the acetate group can be observed in the peak at 1085 cm −1 . The peak around 840 cm −1 is associated with bending vibrations of C−H bonds in the molecule. These results are in good agreement with previous reports [ 36 ]. 3.3. Thermal Properties The TGA thermogram of chitosan/PVA nanofibers (Cs-5, Cs-6, Cs-7, and Cs-8) showed the weight loss profile at various temperatures ( Figure 4 ). The weight loss of chitosan and PVA went through two stages. For chitosan, the first weight loss happens at 35–118 °C, corresponding to the loss of moisture (~5%), while the second weight loss took place at 182–400 °C, corresponding to thermal degradation with the deacetylation of chitosan (~49.68%) [ 41 ]. For PVA, the first weight loss occurred at 51–134 °C, related to moisture vaporization (~4%), while the second weight loss was at 157–450 °C, associated with the thermal degradation of PVA (~90.52%) [ 42 ]. TGA data for chitosan/PVA nanofibers are summarized in Table 2 . The mass loss of all chitosan/PVA nanofibers samples happens in three stages, as shown in Figure 5 [ 43 ]. The first mass loss stage occurred in the range of 50–158 °C, which is related to moisture and solvent residue vaporization. From the DTG curves, it is possible to observe that two peaks are formed in this stage; this can be due to the presence of acetic acid residues, which have a higher boiling point (118 °C) in comparison to water. The second mass loss took place in the range of 180–375 °C, corresponding to the thermal degradation of chitosan and PVA. DTG curves show that the second mass loss for nanofiber samples is composed of two peaks. The first peak, observed at a temperature around ~267 °C, is related to the destruction of the chitosan/PVA complex. The second peak, observed at a temperature of ~310 °C, is related to the destruction of chitosan and PVA without any interaction. It is also noticeable that the samples with a lower chitosan content formed a lower polymeric complex between chitosan and PVA. Whereas the third mass loss observed in the range of 375–530 °C is related to the degradation of PVA byproducts generated during the thermal degradation process [ 44 , 45 ]. From the obtained result, it is possible to observe that the thermal stability of the electrospun nanofibers decreases as the chitosan content increases. Even more, if comparing the thermal stability of nanofibers samples with the pure PVA and chitosan, a major reduction in the thermal stability can be noticed ( Table 2 ). The decrease in the thermal stability in the chitosan/PVA nanofibers can be explained by polymer–polymer interaction. The amorphous structure of chitosan dispersed along PVA polymeric chains generates defects in the crystalline phase of PVA, thus, hindering the development of the crystalline structure. Hence, less heat is needed to destroy the hydrogen bonding and free PVA chains to melt, which results in a lower melting point from the chitosan/PVA composites [ 46 , 47 ]. Figure 6 a shows the DSC thermographs of chitosan and PVA. The DSC thermograph of chitosan shows a broad endothermic peak at 180 °C followed by an exothermic peak at 286 °C [ 48 ]. The first peak can be attributed to the molecular arrangement of chitosan chains, while the second peak corresponds to the thermal decomposition of chitosan, which is in good agreement with the data obtained from the DTG analysis, where the thermal decomposition for chitosan was found around 290 °C. From the DSC thermograph for PVA, it is possible to observe a change in the baseline at 71 °C related to glass transition [ 41 ]. The melting point peak was detected at 170 °C, within the temperature range of 150–178 °C. The characteristic peak of the crystalline polymer fraction of PVA was observed at 220 °C [ 49 ]. Figure 6 b shows the DSC thermograph of chitosan/PVA nanofibers. From the DSC curves of chitosan/PVA nanofibers, it is possible to notice that the change in the baseline related to the glass transition of PVA has completely disappeared for all nanofiber samples. The orientation of the polymeric chains caused by the shear and tensile stress exerted by the electric field during the electrospinning process can be responsible for this [ 38 ]. From the DSC curves in all nanofibers samples, an endothermic peak at 165, 165, 164, and 163 °C for Cs-5, Cs-6, Cs-7, and Cs-8, respectively, can be observed. This first peak can be related to the melting point. This is followed by an exothermic peak at 231, 229, 229, and 227 °C for Cs-5, Cs-6, Cs-7, and Cs-8, respectively, which can be caused by a cross-linking (complex formation between chitosan and PVA) reaction on the chitosan molecules [ 36 ]. The third peak, an exothermic peak at 271, 268, 265, and 264 °C for Cs-5, Cs-6, Cs-7, and Cs-8, respectively, is associated with the thermal decomposition of the nanofibers, which are in good agreement with TGA results ( Table 2 ). Although it is well known that the electrospinning process can increase the crystallinity of the electrospun polymer, this has been the case with pure PVA, as reported by Koosha et al. [ 36 ]. Nevertheless, it has been reported that the crystalline microstructures of electrospun fibers may not develop due to the high-speed solidification process of the stretched polymer. Therefore, the resulting fibers exhibit decreased crystallinity compared to their powdered and film counterparts [ 36 , 46 ]. In addition, another factor influencing the decrease in crystallinity of chitosan/PVA nanofibers is due to polymer–polymer interactions. As a result of hydrogen bonding between −OH groups of PVA and −NH 2 of chitosan, the ordered structure of the PVA polymer chain is disrupted [ 50 , 51 ]. 3.4. Mechanical Properties The tensile strength, Young’s moduli, and elongation at break of chitosan/PVA nanofibrous mats are displayed in Table 3 . From the obtained results, it is possible to notice that the tensile strength increased from 3.84 MPa (Cs-5) to 6.42 MPa (Cs-7) with the increase in chitosan concentration, as shown in Figure 7 . It could be found that the Young’s modulus of the nanofibers samples increased from 299.7 MPa (Cs-5) to 648.45 MPa (Cs-8) with increasing chitosan concentration. This behavior could be due to the intermolecular interaction between chitosan and PVA, where the polymer–polymer interaction is caused by hydrogen bonds between amino (−NH 2 ) and hydroxyl (−OH) groups in chitosan and hydroxyl groups in PVA, as can be deduced from the FTIR data [ 52 ]. Nevertheless, it is possible to notice that tensile strength for Cs-8 decreases (2.82 MPa). This can be related to the increment of molecules with high molecular weight (~261 kDa) and the hard backbone of chitosan, which is well-known to be a rigid and brittle natural polymer [ 53 , 54 ]. Similar results have been reported by Bin Duan et al. [ 55 ] in their work on chitosan/PVA nanofibers electrospun from a solution with a volume ratio of 60:40 (chitosan:PVA). The tensile strength and elongation at break were 4.3 ± 0.4 MPa and 4.3 ± 0.6%, respectively. Similarly, Koosha M. et al. [ 36 ] reported the fabrication of PVA and chitosan/PVA nanofibers with a 30% chitosan content. Chitosan/PVA nanofibers had a tensile strength and elongation at break of 5.26 ± 0.53 MPa and 4.5 ± 1%, respectively. Meanwhile, PVA nanofibers had a tensile strength and elongation at break of 7.4 ± 0.37 MPa and 50.2 ± 5%, respectively. 3.5. Swelling Ratio of Chitosan/PVA Nanofiber Hydrogels Figure 8 shows the swelling behavior of chitosan/PVA nanofiber hydrogels. The samples were immersed in the solution for 24 h until they swelled to equilibrium, which was reached after confirming the samples’ weight steadiness. From the obtained results, it was possible to notice that the maximum swelling for all nanofiber samples (Cs-5, Cs-6, Cs-7, and Cs-8) was obtained in the pH range 5–6. However, as the pH decreases, it is possible to notice that the swelling ratio also decreases. This behavior can be explained as follows. Amino groups in chitosan are protonated at low pH, which induces a change in chitosan structure. It has been suggested that the pKa of chitosan is in the pH range of 6–7 [ 56 ]. In this pH range, the amino groups of chitosan are ionized, and −NH 3 + groups are distributed among the fiber network. Increasing the osmotic pressure between the inside and outside leads to a higher swelling degree; furthermore, the electrostatic repulsion between the chains increases the swelling degree of the nanofiber. Nonetheless, as the pH lowers, the concentration of H + ions increases, leading to a reduction in the osmotic pressure, thus, decreasing the swelling behavior of the nanofibers. Moreover, the excess of Cl - ions contributes to the deswelling at this pH range [ 57 ]. 3.6. Electroactive Response of the Nanofiber Hydrogels 3.6.1. Influence of Chitosan Content on the Speed Displacement at Different pH The electroactive response of electrospun nanofiber hydrogels was studied by measuring the displacement of the samples as a function of time in an electrochemical cell. The influence of chitosan concentration and pH (from 2 to 12) on the electroactive response was analyzed. For this experiment, the samples used had a dimension of 20 × 4 mm (length × width) with a thickness of ~0.03 mm in a dry state. Figure 9 shows the bending deformation of a chitosan/PVA (Cs-8) nanofibrous hydrogel in an HCl pH 4 under an electrical potential of 10 V for 50 s, which exhibited a maximum displacement of 8.1 mm. It was observed that the speed displacement is strongly related to the concentrations of chitosan as well as to the pH of the electrolyte solution, as shown in Figure 10 . As the chitosan concentration increased, the nanofibers became more electrical responsive, exhibiting a larger displacement at all pH solutions, reaching a maximum speed displacement of 1.86 mm s −1 in a pH 3. Meanwhile, the sample with the lowest chitosan concentration (2.5 wt.%) exhibited a speed displacement of 1.2 mm s −1 under the same conditions. This behavior can be related to the increase in free amino groups in the chitosan/PVA nanofibers complex. Furthermore, the electroactive response of the nanofibers was tested at pH > 7. Contrary to when the pH decreased from 6 to 3 and the electroactive response of the nanofibers increased, it was observed that as the pH increased from 7 to 12, the electroactive performance of the nanofibers dramatically decreased. When the solution reached a pH > 10, none of the samples showed any electroactive response ( Figure 10 ). Briefly, the decline in the electroactive response as pH increases is related to the decrease in H + available to protonate the polycationic structure of chitosan (further explanation is given in the next paragraph). A characteristic that endows chitosan with its electroactive properties is the presence of amino groups. Amino groups within the chitosan structure are protonated in an acidic environment (pH < 7). Thus, chitosan behaves as a cationic polyelectrolyte [ 56 ]. Therefore, the bending deformation of the nanofibers under an electric field can be explained by Flory’s theory of osmotic pressure, according to the literature [ 57 , 58 ]. When applying an electric field, free ions are attracted to the counter electrode; this ion mobility generates a concentration gradient of mobile ions in the solution. As a result, the ionic concentration between the inside and outside of the nanofibers is different, causing the osmotic pressure of the anode side (π 1 ) not to bend equally to that of the cathode side (π 2 ), as a result of the osmotic pressure difference ∆ π ∆ π = π 1 − π 2 , the material will bend. For any polyanionic hydrogel, the bending deformation will be toward the cathode, whereas for any polycationic hydrogel, the bending deformation will be toward the anode [ 59 , 60 ]. 3.6.2. Determination of Free Amine (−NH 2 ) by Spectra Deconvolution It is known that amino groups are involved in the electroactive behavior of chitosan. As reported in many works, when chitosan is in contact with an acidic environment (pH < 7), amino groups −NH 2 are protonated, which causes chitosan to behave as a cationic polyelectrolyte [ 61 ]. Nonetheless, when chitosan and PVA interact with one another, intramolecular and intermolecular hydrogen bonds are formed, as shown in Figure 11 . As a result of these interactions between polymers, the quantity of free amino groups can be reduced, hence influencing the electroactive properties of the material. Aiming to determine the hydrogen bonding interaction and the proportion of free amine, a deconvolution in Gaussian line shapes was performed on the 3000–3700 cm −1 peak in the FTIR spectrum ( Figure 12 ). Hydrogen bond types were analyzed in the −OH region and the −NH region. For the −NH region, the characteristic absorption peak of the free amine group is around 3408 cm −1 , the characteristic absorption peak of intermolecular association (N 2 −H 1 …O 5 /N 2 −H 2 …O 1 ) is around 3335 cm −1 , the characteristic absorption peak of the amide group (−CONH−) is around 3240 cm −1 , and the characteristic absorption peak of primary ammonium (−NH + 3 ) is around 3100 cm −1 . For the −OH region, the characteristic absorption peak of free hydroxyl (−OH) is around 3580 cm −1 , and the characteristic peak of multimer intermolecular association (O 6 H…N 2 ) is around 3462 cm −1 [ 62 , 63 , 64 , 65 , 66 ]. The area under the curve is assigned to each characteristic peak which represents the composition ratio of hydrogen bonds in the −NH and −OH regions; all results are shown in Table 4 . From Table 4 , it is possible to observe that the proportion of free amine increases from 3.6% to 4.59% as the concentration of chitosan increases. Additionally, it is possible to notice that the proportion of intermolecular association decreases as the chitosan content increases, reaching a minimum value of 39.15% for the nanofiber sample Cs-8 (4% chitosan/5% PVA). From these results, the electroactive behavior of the material could be better understood. As chitosan content is lower, higher hydrogen bonds are formed, these hydrogen bonding can take part in −NH 2 …−OH interactions, reducing the available free amino groups that can be protonated and be participants in the electro-activation of the chitosan/PVA nanofibers. As for the samples with a higher chitosan content, due to the larger number of amino groups, it is possible for the polymer to form −NH 2 …−OH hydrogen bonds while maintaining a greater proportion of free amino groups available to be protonated, hence increasing the electro-activation sensitivity which can be noticed in its faster speed displacement."
} | 7,428 |
32670750 | PMC7341084 | pmc | 7,593 | {
"abstract": "Abstract The precise deployment of functional payloads to plant tissues is a new approach to help advance the fundamental understanding of plant biology and accelerate plant engineering. Here, the design of a silk‐based biomaterial is reported to fabricate a microneedle‐like device, dubbed “phytoinjector,” capable of delivering a variety of payloads ranging from small molecules to large proteins into specific loci of various plant tissues. It is shown that phytoinjector can be used to deliver payloads into plant vasculature to study material transport in xylem and phloem and to perform complex biochemical reactions in situ. In another application, it is demonstrated Agrobacterium ‐mediated gene transfer to shoot apical meristem (SAM) and leaves at various stages of growth. Tuning of the material composition enables the fabrication of another device, dubbed “phytosampler,” which is used to precisely sample plant sap. The design of plant‐specific biomaterials to fabricate devices for drug delivery in planta opens new avenues to enhance plant resistance to biotic and abiotic stresses, provides new tools for diagnostics, and enables new opportunities in plant engineering."
} | 297 |
36554172 | PMC9778616 | pmc | 7,594 | {
"abstract": "Aiming at the path planning problem of unmanned aerial vehicle (UAV) base stations when performing search tasks, this paper proposes a Double DQN-state splitting Q network (DDQN-SSQN) algorithm that combines state splitting and optimal state to complete the optimal path planning of UAV based on the Deep Reinforcement Learning DDQN algorithm. The method stores multidimensional state information in categories and uses targeted training to obtain optimal path information. The method also references the received signal strength indicator (RSSI) to influence the reward received by the agent, and in this way reduces the decision difficulty of the UAV. In order to simulate the scenarios of UAVs in real work, this paper uses the Open AI Gym simulation platform to construct a mission system model. The simulation results show that the proposed scheme can plan the optimal path faster than other traditional algorithmic schemes and has a greater advantage in the stability and convergence speed of the algorithm.",
"conclusion": "5. Conclusions This paper investigated the path planning problem in the process of collecting the location information of the affected people by UAV base station based on deep reinforcement learning algorithm and proposed a DDQN-SSQN reinforcement learning algorithm combining state splitting and optimal state to complete the optimal path planning in the process of UAV information collection. In order to realize the collection of the location information of the trapped people on the ground by the UAV base station, we introduced RSSI as the search indication of the disaster victims and input tedit into the algorithm network as status information for learning, which reduced the difficulty of search and rescue decision-making of the UAV base station. In this paper, the virtual disaster relief scenario model was constructed using the Open AI Gym simulation platform, and the network structure of the algorithm was improved on the basis of the DDQN algorithm, and then the new algorithm designed in this paper was compared with the traditional reinforcement learning algorithm through simulation comparison experiments. The simulation experimental results showed that the proposed algorithm could find the optimal search path in the shortest time compared with several other reinforcement learning algorithms. The proposed algorithm was better than the traditional algorithm in many aspects such as training speed, task completion rate, and obstacle avoidance rate. In future research, we plan to consider the constraints related to terrain and environment when dividing the mission area, so as to avoid wasting resources due to UAV search and exploration in uninhabited land. In addition, the location information of the trapped people on the ground collected by the UAV can be further processed to achieve three-dimensional coordinate positioning of the disaster-stricken people.",
"introduction": "1. Introduction Nowadays, with the development of 5G communication technology and the improvement of the mobile Internet of Things, unmanned aerial vehicle (UAV) base stations have begun to be widely used in auxiliary communication and post-disaster rescue tasks [ 1 , 2 ]. The UAV air base station has the characteristics of strong maneuverability, controllable mobility, and convenient deployment and can support the high-speed transmission of communication data, etc. [ 3 ]. The application of UAV base stations in disaster relief scenarios improves the problem of communication signals being difficult to reach in complex environments, and also makes it possible to provide all-round coverage of communication signals in disaster relief mission areas. Considering the special nature of UAV base stations and the complexity of the disaster relief environment [ 4 , 5 ], how to use the high flexibility of UAVs to plan an optimal collision-free path in the complex situation with obstacles after a disaster is the most pending problem of UAVs in disaster rescue missions. In the scenario where UAVs search for location information of disaster victims, the path planning problem of UAVs is the key to accomplish such tasks. Traditional UAV path planning algorithms include the artificial potential field method, heuristic algorithm, ant colony algorithm, etc. The UAV path planning method using an improved artificial potential field was proposed in [ 6 , 7 ], which effectively solved the path planning of multi-UAS and UAV obstacle avoidance against dynamic obstacles by introducing a rotating potential field and Markov prediction model. In [ 8 , 9 , 10 ], an improved heuristic algorithm was proposed to solve the problem of UAV path planning and mission area coverage in complex environments. To solve the coverage path planning problem for autonomous heterogeneous UAVs over a finite area, an original clustering-based algorithm was designed in [ 11 ], which divided the mission area into clusters to obtain the optimal UAV point-to-point path. For the multi-target search and path planning problem in unknown environment, Refs [ 12 , 13 ] proposed an improved artificial bee colony algorithm, which greatly improved the stability of UAV flight and the speed of UAV path planning. In [ 14 ], a combination of a pseudospectra algorithm and an ant colony algorithm was used to solve the 3D path planning problem of solar powered UAV. In [ 14 ], a combination of the pseudospe-tral and colony algorithms was used to solve the 3D path planning problem of solar powered UAV. For the path planning problem of multiple UAVs, the authors of [ 15 , 16 ] proposed the use of a sparrow search algorithm and a two-level coordination framework approach to achieve path planning for UAV swarms in dynamic obstacle environments, respectively. In order to improve the stability of the algorithm and the efficiency of the task completion during the task execution, designing a new alternative framework for UAV motion performance can effectively reduce the task execution time of UAVs while improving the robustness of the algorithmic framework [ 17 , 18 ]. A non-rigid hierarchical discrete grid structure was proposed in [ 19 ] to achieve path planning of UAVs in 3D space. These optimization algorithms based on traditional algorithms were all based on converting the UAV path planning problem into a path optimization problem and solving the optimization model to obtain the optimal flight path. However, these methods often suffer from a low intelligence level, a long solution time and restricted application scenarios, and cannot be applied to post-disaster rescue scenarios with complex environments and changing scenarios. In recent years, artificial intelligence technology has flourished, and deep reinforcement learning has gradually been applied to solve the path planning problems of UAVs in various complex environments. In [ 20 , 21 ], the use of the DDPG algorithm was proposed to enable UAVs to autonomously avoid threat areas and thus obtain an optimal flight path. The improved DRL algorithm was used in [ 22 , 23 , 24 ] to implement real-time UAV path planning in the respective application scenarios. In [ 25 ], to improve the collection of global and local information during the flight of UAVs, a multi-layer path planning algorithm based on reinforcement learning (RL) technique was proposed, which divided the information into upper and lower layers and then coordinated the processing of the upper and lower layers to finally plan a collision-free path for the UAV. By introducing a UAV mobile edge computing platform in [ 26 , 27 , 28 ], a better quality of path planning for reinforcement learning algorithms was provided while risk avoidance was achieved. In scenarios where there is no basic communication infrastructure or where communication with the Internet is not possible due to emergencies such as disasters, a reinforcement learning-based path planning scheme for IoT UAVs was proposed in [ 29 ] to achieve autonomous path planning for UAVs in unknown environments. A DL-based collision avoidance method for UAV communication networks was proposed in [ 30 ], while a series of convex optimization problems were formulated and solved to effectively solve the optimal trajectory planning problem for UAV communication networks. To optimize the flight trajectory and improve the energy management capability of the solar powered aircraft, a neural network controller was trained using the RL method in [ 31 ] and used as an integrated controller for aircraft navigation and guidance. In [ 32 , 33 ], the algorithms of dual-latency deep deterministic policy gradient (TD3) participant-critic deep reinforcement learning (DRL) framework and multi-step duel DDQN (multi-step D3QN) were used to implement UAV path design in 3D space, respectively. For the path planning problem of multi-UAV wireless data collection, the process was solved by the DRL method in [ 34 ] and an approximate optimal UAV control strategy with unknown environmental data information was implemented. Traditional reinforcement learning algorithms and traditional path planning algorithms often have good test effects in some simple scenarios with simple environments and small state dimensions of algorithm input, but the execution effect of the algorithms will be greatly reduced in some scenarios with complex environments, many obstacles, and large state information dimensions input by the algorithms. For the shortcomings of traditional path planning algorithms, this paper studies the path planning problem of UAV base stations collecting location information of trapped people based on deep reinforcement learning technology, proposes the reinforcement learning idea of combining state splitting and optimal value, and also designs the DDQN-SSQN reinforcement learning algorithm to solve the path planning problem of UAVs in performing search and rescue tasks by combining the received signal strength indication (RSSI) collected by UAV base stations in real time during the flight. Finally, the DDQN-SSQN algorithm is used to simulate the built task environment and compare with the traditional reinforcement learning algorithm to demonstrate the advantages of the proposed algorithm. The proposed algorithm improves the network structure of the algorithm on the basis of the traditional DDQN algorithm, and the algorithm classifies the multi-dimensional environmental state and conducts targeted training, which greatly improves the decision-making efficiency of the Agent. The main contributions of this paper are as follows: (1) The path decision-making algorithm based on deep reinforcement learning is used to classify and store multi-dimensional state information, and the optimal path information is obtained through targeted training, which greatly improves the efficiency of UAV to complete search and rescue tasks; (2) Use the self-built virtual environment model to complete the training of the drone, which effectively avoids the training loss of the physical UAV and reduces the cost of model training; (3) Introduce the received signal strength indication (RSSI) into the algorithm model of deep reinforcement learning and use this to affect the reward obtained by the agent, which reduces the difficulty of UAV decision-making and improves the positioning accuracy of the ground user’s location coordinates. The structure of this article is as follows: In the second chapter, the construction of a virtual disaster relief scenario is introduced. The construction of the scene model is mainly completed from three aspects: system environment model, obstacle model, and ground user model. In the third chapter, the design ideas of the DDQN-SSQN algorithm proposed in this paper and the network structure of the algorithm are introduced. In the fourth chapter, the relevant parameters of the algorithm simulation are given, and the test effect of the proposed algorithm and the traditional reinforcement learning algorithm is compared to verify the advantages of the proposed new algorithm. The full text is summarized and prospected in Section 5 ."
} | 3,015 |
25302567 | PMC4208098 | pmc | 7,596 | {
"abstract": "Plasmids are important drivers of bacterial evolution, but it is challenging to understand how plasmids persist over the long term because plasmid carriage is costly. Classical models predict that horizontal transfer is necessary for plasmid persistence, but recent work shows that almost half of plasmids are non-transmissible. Here we use a combination of mathematical modelling and experimental evolution to investigate how a costly, non-transmissible plasmid, pNUK73, can be maintained in populations of Pseudomonas aeruginosa . Compensatory adaptation increases plasmid stability by eliminating the cost of plasmid carriage. However, positive selection for plasmid-encoded antibiotic resistance is required to maintain the plasmid by offsetting reductions in plasmid frequency due to segregational loss. Crucially, we show that compensatory adaptation and positive selection reinforce each other’s effects. Our study provides a new understanding of how plasmids persist in bacterial populations, and it helps to explain why resistance can be maintained after antibiotic use is stopped.",
"discussion": "Discussion Non-transmissible plasmids are common in both pathogenic and environmental bacteria 25 27 39 40 41 and it is difficult to understand how these plasmids can persist in bacterial populations as a result of the cost of plasmid carriage. To understand the ecological and genetic mechanisms that promote the stability of plasmids, we deliberately chose to work with a plasmid (pNUK73) that is highly unstable in Pseudomonas populations due to the fact that it has a high rate of segregational loss and imposes a substantial cost. Classical models of plasmid evolution predict that conjugation is necessary for plasmid maintenance 6 7 8 9 , but we found that compensatory adaptation to ameliorate the cost of plasmid carriage coupled to rare selection for plasmid-encoded antibiotic resistance was sufficient to stabilize this bacteria/plasmid association. We therefore argue that our study presents a new understanding of why non-conjugative plasmids are so common, and also helps to explain why resistance genes persist in bacterial populations even in the absence of antibiotic use. At the start of our experiment, the frequency of the pNUK73 plasmid rapidly declined, but the rate of decline in plasmid frequency slowed down as a result of chromosomal compensatory adaptation that removed the cost of plasmid carriage (similar kinetics of decline in antibiotic resistance have been observed in natural populations) 42 . However, compensatory adaptation was not sufficient to stably maintain pNUK73. First, although compensatory adaptation eliminated the absolute cost of plasmid carriage, segregational loss of plasmids continually decreased plasmid frequency. Second, relatively common plasmid-free lineages acquired more general beneficial mutations, compared with relatively rare plasmid-bearing lineages, resulting in an effective cost of plasmid carriage. Crucially, we found that selection for plasmid-encoded antibiotic resistance was necessary to maintain the plasmid, as has been observed before 43 . The immediate effect of antibiotic exposure was that the frequency of the plasmid increased to almost one. Following this immediate ‘rescue’ effect, the frequency of the plasmid declined, but the rate of decline following treatment gradually slowed as compensatory mutations spread through the plasmid-bearing population. In other words, compensatory adaptation resulted in an increased plasmid half-life following antibiotic exposure ( Supplementary Fig. 3 ). The long-term consequence of antibiotic exposure was that increased population size allowed plasmid-bearing lineages to evolve general adaptations, effectively eliminating selection against plasmid carriage. Therefore, we argue that it is the interaction between compensatory adaptation and positive selection that helps to stabilize non-conjugative plasmids in bacterial populations. As a result of the large cost imposed by pNUK73, there was strong selection to minimize the cost of plasmid carriage. The ability of bacteria to evolve compensatory mutations that offset the cost of pNUK73 played an important role in stabilizing the plasmid. A number of studies have shown that compensatory adaptation rapidly eliminates the cost of plasmid carriage 21 23 44 45 , but the precise genetic mechanisms underpinning adaptation to the cost of plasmid carriage remain poorly characterized. We found that mutations in three chromosomal genes completely compensated the cost of the plasmid without imposing any additional fitness burden ( Fig. 2b,c ). The compensatory mutations that we identified are found in genes that code for a putative helicase carrying an UvrD-like helicase C-terminal domain, and two contiguous putative serine/threonine protein kinases ( Fig. 6 ). The specific role of these mutations in the molecular mechanisms of compensation will be investigated explicitly in a future study. Although it is clear that compensatory adaptation and positive selection can maintain non-conjugative plasmids on a time scale of hundreds of generations, the maintenance of these plasmids over longer time scales remains enigmatic, because plasmid-encoded genes could theoretically move to the chromosome, rendering the plasmid redundant. In this case, we would expect that the plasmid would gradually be eliminated from the population due to segregational loss, even if the plasmid carried no cost. One potential resolution to this dilemma is that some genes carried on non-conjugative plasmids may confer a greater fitness benefit when they are carried on plasmids than when they are integrated into the chromosome, for example, because carrying multiple copies of the gene enables high levels of expression, or because heterogeneity in plasmid copy number generates adaptive heterogeneity in gene expression between plasmid-bearing cells. Second, it is possible that rare episodes of horizontal transfer might allow the maintenance of non-conjugative plasmids. Mechanisms such as transduction or co-integration with other mobile genetic elements that could facilitate the horizontal transfer of non-conjugative plasmids probably play an important role. In the future, we will extend the approach developed here to understand the mechanisms that permit the long-term maintenance of non-transmissible plasmids."
} | 1,595 |
28753209 | PMC5702725 | pmc | 7,598 | {
"abstract": "Root endophytes have been shown to have important roles in determining host fitness under periods of drought stress, and yet the effect of drought on the broader root endosphere bacterial community remains largely uncharacterized. In this study, we present phylogenetic profiles of bacterial communities associated with drought-treated root and rhizosphere tissues of 18 species of plants with varying degrees of drought tolerance belonging to the Poaceae family, including important crop plants. Through 16S rRNA gene profiling across two distinct watering regimes and two developmental time points, we demonstrate that there is a strong correlation between host phylogenetic distance and the microbiome dissimilarity within root tissues, and that drought weakens this correlation by inducing conserved shifts in bacterial community composition. We identify a significant enrichment in a wide variety of Actinobacteria during drought within the roots of all hosts, and demonstrate that this enrichment is higher within the root than it is in the surrounding environments. Furthermore, we show that this observed enrichment is the result of an absolute increase in Actinobacterial abundance and that previously hypothesized mechanisms for observed enrichments in Actinobacteria in drought-treated soils are unlikely to fully account for the phenomena observed here within the plant root.",
"conclusion": "Conclusion Drought is an important selective pressure that may drive plant and bacterial evolutionary responses ( terHorst et al. , 2014 ). The influence of drought on bacterial communities in soils is increasingly recognized ( Sheik et al. , 2011 ; Pold et al. , 2016 ); our study adds to this emerging field by showing that drought significantly impacts the composition and diversity of the plant root microbiome, and that recently observed enrichments in Actinobacteria under drought are in fact more pronounced in root endosphere than in the surrounding soils. Additionally, our study provides evidence that while different plant hosts show selection for specific root bacterial communities in a manner correlated with their evolutionary histories, drought in fact provokes a relatively conserved response across a broad range of plant species. Our research suggests that previously hypothesized causes for this enrichment in soils, including sporulation and relative fitness in dry environments, are unlikely to fully explain the enrichment observed here in roots. Further research aimed at understanding the causes and consequences for this highly conserved relationship between an entire class of bacteria and many species of plants will be important for improving our understanding of the role that environmental parameters have in shaping plant–bacterial interactions.",
"introduction": "Introduction Few environmental stresses are as omnipresent and devastating to agriculture as drought, which annually results in billions of dollars in losses worldwide ( Lesk et al. , 2016 ). While some crop responses to drought are conserved across most species, including increased ABA production and stomatal closure, other adaptations are host-specific, such as special carbon uptake pathways, increased cuticle thickness and altered root morphology ( Fang and Xiong, 2015 ). As plants are intimately intertwined with the communities of microbes living in and around them ( Gaiero et al. , 2013 ; Philippot et al. , 2013 ; Berg et al. , 2016 ), perturbations in plant physiology and metabolism, such as those resulting from drought response mechanisms, can be expected to alter the composition of the plant microbiome with potential consequences for host fitness ( Berg et al. , 2014 ). However, little information is available on how drought influences the plant root microbiome, and the degree to which such changes are conserved across different plant hosts. Recent studies have noted enrichment of the bacterial taxa Actinobacteria in drought-treated soils across a range of environments ( Bouskill et al. , 2013 , 2016 ) and in drought-treated rhizospheres (soils adhering to the root surface) for several plant species ( Nessner Kavamura et al. , 2013 ; Taketani et al. , 2016 ). It has been suggested that this observed relative enrichment is due to differing life strategies of soil microorganisms; specifically, the spore-forming ability of Actinobacteria, which allows them to enter a stable and quiescent state during periods of environmental stress, would lead them to persist under drought conditions, while less fit bacterial lineages decrease in abundance ( Nessner Kavamura et al. , 2013 ; Taketani et al. , 2016 ). Whether Actinobacteria are also enriched within the plant root under drought, and the degree to which such enrichment patterns are generalizable across a broad range of hosts and Actinobacterial taxa, remains unknown. We hypothesize that the plant root microbiome will exhibit significant shifts during drought, including an increase in Actinobacteria, and that these changes will be, at least in part, host specific as a result of differing drought response mechanisms. While the effect of drought on the root microbiome remains largely unexplored, more effort has been made to understand the role of plant host genotype in shaping root-associated bacterial communities ( Kuske et al. , 2002 ; Brusetti et al. , 2005 ; Aleklett et al. , 2015 ; Bulgarelli et al. , 2015 ). Different host species not only have unique exudation patterns ( Cavaglieri et al. , 2009 ) but also root architecture, lifespan and rooting depth, all of which have been shown to influence microbiome structure ( Fierer et al. , 2003 ; Shi et al. , 2011 ; Berendsen et al. , 2012 ; Badri et al. , 2013 ; Chaparro et al. , 2013 ). As these root phenotypes are under genetic control of their hosts, genetically similar hosts might be expected to harbor comparable microbiome profiles ( Parker and Spoerke, 1998 ; Ushio et al. , 2008 ). Indeed, host phylogenetic relationships were recently shown to be correlated with microbiome dissimilarity in the rhizosphere ( Bouffaud et al. , 2014 ), and among accessions of a single species, similar hosts had more comparable microbiota in rhizosphere and roots ( Peiffer et al. , 2013 ; Bulgarelli et al. , 2015 ). However, the relative strength of this correlation within roots and rhizospheres have yet to be compared within a phylogenetically diverse host framework. Additionally, it remains to be seen whether drought stress strengthens or weakens the correlation between host phylogeny and bacterial community composition. We hypothesize that a positive correlation between host phylogenetic and microbiome distance exists and will be strongest inside the root, where plants have greater influence over bacterial interactions and recruitment; furthermore, we hypothesize that drought will strengthen this correlation, because the metabolic and phenotypic factors driving host-specific differences in bacterial recruitment are, at least in part, adaptive traits to differing water availability in each host’s native environment. To test these hypotheses, we analyzed bacterial community composition in root endosphere and rhizosphere for 18 grass species in the Poaceae clade, grown in the field under drought conditions. We included nine species with C4 carbon metabolism and nine with C3 carbon metabolism, as plant species using C4 metabolism are better adapted to arid environments ( Fang and Xiong, 2015 ). The grasses we chose included agronomically valuable C3 crops with moderate to poor drought tolerance, such as wheat and barley ( Nezhadahmadi et al. , 2013 ; Ghotbi-Ravandi et al. , 2014 ), and also highly drought-tolerant C4 species, such as sorghum ( Sabadin et al. , 2012 ). Our experimental design allowed us to investigate the effect of drought on the grass microbiome, to observe whether such effects are unique or conserved across a broad range of hosts with differing drought tolerances, and assess the degree of correlation between host phylogeny and the root microbiome under normal and drought conditions.",
"discussion": "Discussion Cereal host root microbiome composition correlates with host phylogenetic distance A wide range of host and environmental factors have been shown to influence plant microbiome composition ( Berg and Smalla, 2009 ; Gaiero et al. , 2013 ). Using canonical analysis of principal coordinates analysis, we found that sample type, host species and watering treatment were the three most important sources of compositional variance. Sample type has been implicated as the largest source of variation in multicompartment data sets ( Lundberg et al. , 2012 ; Marasco et al. , 2012 ; Bulgarelli et al. , 2015 ; Cherif et al. , 2015 ; Edwards et al. , 2015 ; Coleman-Derr et al. , 2016 ; Fonseca-García et al. , 2016 ). Previous studies investigating the effect of host genetics have tended to focus on varieties of a single given host species, such as barley ( Bulgarelli et al. , 2015 ), maize ( Peiffer et al. , 2013 ) or agave ( Desgarennes et al. , 2014 ; Coleman-Derr et al. , 2016 ), or on a few distinct species ( el Zahar Haichar et al. , 2008 ; Bouffaud et al. , 2014 ; Schlaeppi et al. , 2014 ). In these studies, species effects tended to be nonsignificant ( Schlaeppi et al. , 2014 ) or small ( Lundberg et al. , 2012 ; Peiffer et al. , 2013 ; Fonseca-García et al. , 2016 ). By comparison, we found that host species was highly significant and explained ~19.4 and 23.4% of variance within the rhizosphere and root endosphere. The species effect size observed in our study as compared with the relatively low values observed in previous studies suggests that the influence of host species on the root microbiome should be considered in the context of the working phylogenetic framework, and a broader array of considered species will accordingly produce a greater host effect. Differences in the developmental timelines between species may have introduced variability with respect to developmental stage at the time of harvest between species; however, based on field observations for flowering time, the time points we selected broadly represented pre- and postflowering stages for nearly all species. In contrast to our hypothesis that drought might increase the differences in root community composition between different hosts, we observed that the effect of host species was not substantially different between drought and control when using Bray–Curtis distances, and was marginally reduced when using weighted UniFrac distances. These results are consistent with the large shift in Actinobacteria we observe in roots, which is broadly conserved across all hosts we examined. Other environmental stresses may provoke similar trends in conserved enrichment patterns across hosts, whether in Actinobacteria or other bacterial taxa, and will need to be investigated. While previous studies have confirmed the role of genotype in determining microbiome composition, very few have tested the correlation between host phylogenetic and microbiome distances. In examining four Brassicaceae members, microbiota diversification was not consistent with host distance ( Schlaeppi et al. , 2014 ); similarly, two studies of maize inbred lines ( Bouffaud et al. , 2012 ; Peiffer et al. , 2013 ) found that differences in rhizobacterial communities did not correlate with host genetic distance. However, these studies may have been hampered by low sample size and close relatedness of host species. A study using five maize varietals and two additional Poaceae members ( Bouffaud et al. , 2014 ) did detect a significant correlation between plant phylogenetic distance and microbiome distance in rhizospheres, but did not investigate root endospheres. In this study, we expand on previous results by: (1) incorporating many distinct species from both C3 and C4 grasses; (2) examining the relative effect size in the rhizosphere and root endosphere; and (3) investigating how environmental stress might perturb the relationship between host phylogeny and microbiome composition. Our data confirm our hypothesis of a positive correlation between host phylogenetic and microbiome distance that is strongest in roots, weaker in the rhizosphere and nonexistent in the surrounding soil, indicating that host-selective forces on the microbiome grow in magnitude with increased plant–microbe intimacy, which has been recently demonstrated in two studies ( Beckers et al. , 2017 ; Samad et al. , 2017 ). We also observed that drought generally decreased the effect size and significance of the Mantel’s statistic, most notably at the early time point, contradicting our hypothesis that drought strengthens the correlation between host phylogeny and microbiome distance due to host species-specific drought response mechanisms. Instead, these results are consistent with the idea that conserved plant responses to drought, especially early in development (such as increased ABA production), have larger effects on microbiome composition than individual and species-specific adaptations. Additionally, the observation that in the late time point drought provokes a less similar, and therefore a more host-specific, microbial community across hosts, as indicated by the relatively larger size and significance of the Mantel's correlation, is evidence that perhaps host specificity due to species-specific drought responses may take time to accumulate. Phylogenetic distance is not the only factor that differentiates our selected grasses: for example, root morphology can vary significantly between different grasses ( Rich and Watt, 2013 ) and could have affected the microbiome composition. To account for this factor, plant roots were harvested to a consistent rooting depth (25 cm) for all species, athough it is possible that root morphology or other species-specific root characteristics that do not necessarily correlate with host phylogenetic relatedness may represent compounding factors in our analysis of the host effect. Actinobacteria enrichment under drought To our knowledge this represents the first major investigation of the role of drought in determining root endosphere microbiome composition. Here we identified watering treatment as a significant factor in determining community composition within root communities; drought was found to explain 8.8% and 9.9% of variance within the root and rhizosphere, as compared to 5.6% within soils. While drought induced many changes in microbiome composition, the most significant at the class level was an increase of Actinobacteria. While enrichment of Actinobacteria under drought has been reported in soils ( Hayden et al. , 2012 ; Bouskill et al. , 2013, 2016 ) and rhizosphere ( Nessner Kavamura et al. , 2013 ; Taketani et al. , 2016 ), enrichment has not been reported in the root endosphere, nor have enrichment trends been compared between these distinct microhabitats. Our observation that enrichment of Actinobacteria under drought is significantly higher in the root endosphere compared with either rhizosphere or bulk soil suggests that while the Actinobacterial enrichment under drought is not unique to roots, it is enhanced by them. Indeed, 24 genera, including Saccharopolyspora , Glycomyces and Actinopolymorpha , were exclusively enriched in roots and rhizosphere and not in surrounding soil. The observed enrichment in Actinobacteria under drought treatment within roots was found in two field sites, suggesting that these results may be generalizable not only across different plant hosts but also across distinct environments as well. Additionally, while levels of enrichment for individual Actinobacterial lineages were largely consistent across all hosts, there were notable exceptions. For example, an Actinobacteria genus with the most significant enrichment under drought in grass roots (20.3-fold), Glycomyces , had the opposite pattern in tomato. Further comparative genomic analyses and functional studies using these lineages that exhibit sample type- and host-specific enrichment patterns might help decipher underlying mechanisms involved in this process. The general enrichment of nearly all Actinobacteria under drought suggests that the force driving this enrichment is related to one or more conserved properties of the Actinobacterial lineage. For example, among bacteria, they are highly tolerant of life in arid environments ( Bull and Asenjo, 2013 ; Pearce et al. , 2013 ; Stevenson and Hallsworth, 2014 ; Cherif et al. , 2015 ) where other bacterial lineages have difficulty surviving, owing in part to their ability to form spores. Our observation that only about half of drought-enriched Actinobacteria in our study are likely capable of forming spores suggests that sporulation is not fully responsible for their prevalence under drought observed here. Additionally, the two Actinobacteria genera observed to be enriched under control conditions in the Kearney data set are both reported to be capable of forming spores, suggesting that the ability to form spores does not necessarily lead to enrichment under drought conditions ( Bergey’s, 2010 ); however, the evidence presented in this study is based on reports in the literature and bioinformatic analyses, and further experimental evidence is needed to determine whether this pattern holds true for other lineages and in other environments and hosts. Alternatively, the strong enrichment for Actinobacteria within plant-associated samples could be the result of direct or indirect effects due to drought-induced changes in plant root traits, exudation patterns or changes in niche opportunities on and inside the root surface. One putative mechanism for this selection could include shifts in cell wall biochemistry, as plants are known to modulate cell wall components in response to drought ( Gall et al. , 2015 ) and as Actinobacteria are capable of responding to and using some of these compounds that may be a part of their own drought response ( Pold et al. , 2016 ). Whether this selection is ultimately beneficial for the host remains unclear. Many Actinobacteria, particularly members of order Actinomycetales, are known saprophytes ( Solans, 2007 ) with the capability to degrade relatively recalcitrant plant polymers, such as lignin and suberin ( Komeil et al. , 2013 ; de Gonzalo et al. , 2016 ). However, three drought-tolerant strains of the Actinobacteria genus Streptomyces were shown to enhance wheat seedling vigor in water-stressed soils ( Yandigeri et al. , 2012 ); additionally, Actinobacteria were reported to alleviate drought stress in peppers ( Marasco et al. , 2012 ). The highly conserved nature of this enrichment across both diverse hosts and microbes suggests to us that this is an ancient and potentially mutually beneficial relationship, although further molecular and biochemical analyses will be necessary to explore this hypotheses. Common taxa in the grass root microbiome Interestingly, within the 18 grasses tested, the sorghum species exhibited larger and more distinct sets of commonly observed taxa compared with the other hosts. In addition to their remarkable drought tolerance, sorghum plants are known to exude novel secondary metabolites from their roots ( Dayan et al. , 2010 ). One such product, the terpenoid sorgoleone , has been shown to have significant allelopathic properties ( Uddin et al. , 2014 ), although its effect on the root microbiome has yet to be tested. Despite host-specific differences, all cereals in our study shared a subset of their common root OTUs; it is interesting that more than 95% of these were also detected as part of the common taxa found in tomato, which suggests that these microbes may be generalist colonizers of the plant root. It should be noted that criteria used to define the shared microbiome have a large effect on the specific taxa that are identified, and that the choices used in this analysis were intentionally permissive to select a broader list of shared microbes. One caveat to our observations for the common taxa microbiome, and indeed the root microbiome generally, is that the microbiome is heavily influenced by the local soil environment from which samples were collected; even genotypically identical grasses may have strikingly distinct root microbiota patterns when grown in different environments ( Lundberg et al. , 2012 ; Rascovan et al. , 2016 ). More work will be needed to determine if the patterns observed here are found across a broad range of other soil types and locales."
} | 5,150 |
34381306 | PMC8327927 | pmc | 7,599 | {
"abstract": "The furan Diels–Alder (DA) cycloaddition reaction has become an important tool in green chemistry, being central to the sustainable synthesis of many chemical building blocks. The restriction to electron-rich furans is a significant limitation of the scope of suitable dienes, in particular hampering the use of the furans most readily obtained from biomass, furfurals and their oxidized variants, furoic acids. Herein, it is shown that despite their electron-withdrawing substituents, 2-furoic acids and derivatives (esters, amides) are in fact reactive dienes in Diels–Alder couplings with maleimide dienophiles. The reactions benefit from a substantial rate-enhancement when water is used as solvent, and from activation of the 2-furoic acids by conversion to the corresponding carboxylate salts. This approach enables Diels–Alder reactions to be performed under very mild conditions, even with highly unreactive dienes such as 2,5-furandicarboxylic acid. The obtained DA adducts of furoic acids are shown to be versatile synthons in the conversion to various saturated and aromatic carbocyclic products.",
"conclusion": "Conclusions Herein we showcase the successful use of biomass-derived 2-furoic acids, esters and amides as dienes in Diels–Alder cycloadditions. Thus, a variety of novel DA adducts could be selectively obtained following a green synthetic protocol involving the use of renewable feedstock, aqueous solvent, mild conditions, and non-chromatographic purification. The DA couplings proceed surprisingly efficiently with these readily available dienes, which represents an important expansion of the current scope of furan DA reactions to include underrepresented electron-poor derivatives. Some opportunities for downstream diversification of the adducts into valuable chemical products, including substituted bio-based aromatics, is also demonstrated. Expansion of the dienophile scope beyond maleimides 52 is currently underway in our laboratories.",
"introduction": "Introduction Since its discovery in 1929, 1 the furan Diels–Alder (DA) reaction has been extensively applied in organic chemistry, with the resulting 7-oxabicyclo[2.2.1]hept-2-enes being exploited in natural product synthesis, drug discovery, bioconjugation, as well as in polymer and materials science applications. 2–7 Indeed, furan DA reactions allow versatile synthons of considerable molecular complexity to be generated in an atom-economical fashion, making it a highly attractive strategy for green chemical synthesis of cyclic compounds. 8 The reactivity of furan derivatives as dienes has been the subject of numerous theoretical and experimental studies. The general consensus is that good kinetics requires electron-rich furanic rings, as found in the parent furan and derivatives decorated with electron-donating substituents ( e.g. alkyl-, alkoxyalkyl-, acetals etc ., Scheme 1A ) 9–13 and accordingly most applications employ such dienes. Scheme 1 Diels–Alder reactions with 2-furoic acid-derived dienes. Conversely, Diels–Alder reactions involving electron-poor derivatives such as furoic acids (furans substituted with a COOH group) are very much underexplored. 14–21 That such highly oxygenated furanics cannot be readily used in DA-based synthesis strategies is a missed opportunity. Furoic acids are readily available via renewable platform molecules such as furfural and 5-hydroxymethyl furfural (5-HMF). 22 Furoic acids also offer the advantage of being stable renewable platform molecules, this in contrast to, for instance, 5-HMF and its hydrogenated derivatives (2,5-dimethyl furan, 2,5-bishydroxymethyl furan) which can readily degrade and/or polymerize. 23 Together, this makes them attractive building blocks for the atom- and redox-efficient synthesis of a large number of renewable value-added carboxylic acid- or ester-containing chemical products, including biobased aromatics. Unfortunately, only a handful of recent reports describe attempts to capitalize on these advantages. Instead, the vast majority of chemistry developed in this area relies on the well-established use of electron-rich furan dienes. While this conventional approach may be efficient for the individual DA step, it is often redox uneconomical overall, as exemplified for instance by the cycloaddition between 2,5-dimethyl furan and ethylene targeting renewable terephthalic acid ( Scheme 1A ). 24–27 This route is, in essence, the conversion of a highly oxygenated bio-derived resource ( e.g. 5-HMF) to an oxygen-rich product (terephthalic acid) via a non-oxygenated hydrocarbon intermediate, p -xylene. The non-productive use of redox reactions featured in this approach (the so-called “redox-detour”) greatly reduces the incentive for scale-up of such routes. In contrast, as solution to this problem, the groups of Davis, 15–17 Clark 18 and Jae 19 and a patent by Avantium 20 have disclosed new routes towards terephthalic acid starting from furan carboxylic (di)acids or their esters and ethylene, but these diene/dienophile combinations require very harsh conditions and the overall yields are low ( Scheme 1B ). Relatedly, Sibi et al. was successful in the valorisation of the dimethyl 2,5-furandicarboxylate with benzyne as highly reactive dienophile ( Scheme 1C ). 21 Finally, the furoate ester/maleimide couple has on occasion been described in macromolecular applications, 28–31 even though the molecular version was deemed unfeasible by Boutevin et al. 10 To the best of our knowledge, there is a single study thoroughly investigating the reactivity of furoic acids in Diels–Alder chemistry. Bowman et al. showed that reactions of 3-furoic acid with maleimides are actually favoured both kinetically and thermodynamically; 32 on the other hand, the more readily available 2-regioisomer was found to be much less reactive, with the coupling also being strongly entropically disfavoured. Interestingly, the authors note that reactivity could be tuned by solvent effects: rate and equilibrium conversions were significantly higher in water compared to reactions in dimethyl formamide. Encouraged by this precedent and following our interest in the development of synthetic applications based on the Diels–Alder chemistry of readily available oxygenated bio-based furans, 33,34 we decided to investigate 2-furoic acids as underexplored class of dienes.",
"discussion": "Results and discussion Reaction optimization In line with the observations of Bowman et al. , the reaction between furoic acid 1a and N -methyl maleimide 2a was slow in all common organic solvents. No obvious reactivity trend ( Table 1 ) could be discerned, although polar solvents seemed more beneficial for the reaction (MeOH, EtOH, DMSO, AcOH). Hydrogen bonding interactions with the solvent might be important as only traces of product could be detected in apolar aprotic solvents (CH 2 Cl 2 , CHCl 3 ; toluene being a curious exception with 5% yield). Undoubtedly, the electron-withdrawing effect of the COOH substituent on the furan ring translates into a lowered energy level for the HOMO of the diene and consequently a high activation barrier for the cycloaddition. We reasoned that the addition of a base would counteract this effect, as neutralization to the carboxylate diminishes the electron-withdrawing capability of the COOH substituent: 35 indeed, in all solvents tested, the yields increased substantially in the presence of 1 equiv. of triethylamine. Adduct yields of nearly 50% (6 h reaction time, 50 °C) were now observed in CH 2 Cl 2 , CHCl 3 and EtOH. Correlating reactivity with solvent properties is again not straightforward; plausibly, the extent of proton transfer and charge separation play a major role here. Solvent effects in the cycloaddition between 2-furoic acid 1a and maleimide 2a \n \n Entry Solvent Yields in neutral conditions Yields with NEt 3 (1 equiv.) \n exo - 3 , % \n endo - 3 , % Total, % \n exo - 3 , % \n endo - 3 , % Total, % 1 MeOH 10 0 10 34 6 40 2 EtOH 8 Trace 8 49 1 50 3 AcOH 6 0 6 n.a. n.a. n.a. 4 DMSO 7 Trace 7 35 1 36 5 DMF 3 0 3 25 2 27 6 MeCN 3 0 3 28 5 33 7 AcOEt 4 0 4 28 3 31 8 THF 3 Trace 3 27 1 28 9 Acetone Trace 0 Trace 27 5 32 10 CHCl 3 2 0 2 50 0 50 11 CH 2 Cl 2 Trace 0 Trace 41 6 47 12 Toluene 5 0 5 38 2 40 13 H 2 O 56 7 63 83 3 86 Next, we turned our attention to water as solvent. The rate-enhancement ability of water in Diels–Alder chemistry is well known and many arguments have been proposed to explain it. 36,37 In our system, the rate of reaction between 1a and 2a (63% conversion in 6 h at 50 °C, Table 1 , entry 13) is one order of magnitude higher than in all organic solvents tested; in fact, the reaction of the free acid in water even proved faster than the best result obtained in an organic solvent in the presence of base ( Table 1 , entry 2 or entry 10). The reaction also clearly benefited from the synergy of using aqueous solvent and the base effect: nearly quantitative yield of 1a was obtained when the cycloaddition was performed in water in the presence of 1 equiv. of NaOH ( Table 2 , entry 4). The reaction efficiency correlates with the base strength (NaOH ≈ Na 2 HPO 4 > NEt 3 > NaH 2 PO 4 ); clearly, the effect of the base is not catalytic, as lowering the NaOH loading (entries 7 and 8) produced results comparable to those obtained when using the weaker base NaH 2 PO 4 . Finally, the effect of temperature is typical for a reversible [4 + 2] cycloaddition: at lower temperatures (20 °C, entry 10), the reaction is under kinetic control, with the major product being the endo adduct, while at elevated temperatures (80 °C, entry 9), the formation of exo - 3a is nearly exclusive (see also Fig. 1 , bottom); noteworthy, the total yield diminishes with increasing temperature due to the unfavourable entropy contribution. Fig. 1 Kinetic traces for the cycloadditions between 2-furoic acid 1a and maleimide 2a (1 : 1 ratio at 0.5 M) in water (top), with the addition of 1 equiv. NaOH (bottom); see ESI † for details; cf . Tables 2 and 3 : reactions run at 1 : 1.5 ratio 1 : 2 and 1 M concentration. DA reaction between 2-furoic acid 1a and maleimide 2a in aqueous solution: effect of base \n \n Entry Additive Amount, equiv. Temp., °C Time, h \n exo - 3 , % \n endo - 3 , % Total, % 1 None n/a 50 6 56 7 63 2 None n/a 50 16 76 3 79 3 NaOH 1 50 6 90 5 95 4 NaOH 1 50 16 94 3 97 5 Na 2 HPO 4 1 50 6 89 6 95 6 NaH 2 PO 4 1 50 6 71 8 79 7 NaOH 0.5 50 6 75 6 81 8 NaOH 0.25 50 6 67 7 74 9 NaOH 1 80 6 81 3 84 10 NaOH 1 20 6 25 35 60 Scope of DA reaction between 2-furoic acids and maleimides in aqueous solution \n \n Entry R 1 R 2 \n 3 \n Conv. 1 a \n exo - 3 , % \n endo - 3 , % Isolated b , % 1 H Me \n 3a \n 98 97 1 77(92) c 2 H H \n 3b \n 95 95 Trace 68 3 H \n n Pr \n 3c \n 96 93 3 72 4 d H Ph \n 3d \n 51 51 Trace 21 5 d H Cy \n 3e \n 18 16 2 n.d. 6 d , e H Cy \n 3e \n 56 53 3 31 7 Me Me \n 3f \n 93 88 5 75 8 CH 2 OH Me \n 3g \n 91 72 19 51 f 9 d CH 2 OH Ph \n 3h \n 28 28 Trace 11 10 g CHO Me \n 3i \n <10 ∼5 Trace n.d. 11 g COOH Me \n 3j \n 20 20 0 n.d. 12 g , h COOH Me \n 3j \n 56 56 0 n.d. a Conversion determined from the 1 H-NMR ratios of product isomers and starting material in the crude mixture. b Isolated yield after acidification. c 40 mmol scale. d Poor dissolution of 2 . e Methanol was used as cosolvent. f After hydrogenation on Pd/C. g Extensive hydrolysis of 2a to maleic acid. h With 2 equiv. of NaOH. The reaction profiles depicted in Fig. 1 illustrate the significant enhancement of the rate of the cycloaddition in the presence of stoichiometric base: compared to the additive-free reaction ( Fig. 1 , top), the NaOH-mediated conversion is approx. 5 times faster, in the first 30 min. In addition, the system is nearly at equilibrium within 12 h, which is not the case for the base-free experiment. Importantly, the conversion of 1a was clean in both cases, with no side products originating from the diene detected. On the other hand, some hydrolysis of 2a (towards maleic acid) does occur, to a low extent, and if the NaOH stoichiometry is increased beyond the 1 : 1 ratio, the sodium salt of N -methyl maleamic acid is formed (see also note 52 ). Reaction scope The choice of water as reaction solvent allows the convenient isolation of DA adducts 3 by precipitation. To maximize conversion and simplify purification, we performed the title reaction between 1a and 2a under more concentrated conditions (2 M) and with 1 : 1 stoichiometry; the precipitated product was isolated by filtration in a 63% yield. Unreacted starting materials were recovered from the filtrate and reused without loss of reaction efficiency (see ESI † for details). This example is an excellent showcase of the green chemistry principles: renewable raw materials use, 100% atom-economy, eco-friendly solvent, simple isolation, no additives and no waste. In studying the reaction scope, we chose the conditions shown in entry 4, Table 2 (with 1 equiv. NaOH), with the aim of minimizing the amount of minor adduct endo - 3 and simplifying the isolation of a pure product following a general protocol. Thus, after reaction, the excess maleimide can be washed away (and recovered) with an organic solvent, while acidification of the aqueous phase typically leads to the selective precipitation of exo - 3 . This procedure allowed for the isolation of the exo -adducts 3a–c in good yields ( Table 3 , entries 1–3); the performance of the reactions is only modestly influenced by the nature of the maleimide substituent in the series H/Me/ n Pr. Higher homologues ( N -Ph, N -Cy) proved problematic, however, due to poor solubility of the dienophile in the aqueous medium (entries 4 and 5); the addition of a cosolvent (MeOH) was beneficial in this case (entry 6) and although the conversion levels were moderate, synthetically useful yields of pure adducts 3d and 3e could be obtained without excessive adjustment of the general procedure. Next, we proceeded with the investigation of the furan diene scope, with the focus on easily accessible biomass-derived 5-substituted 2-furoic acids. We found that both the kinetics and the thermodynamics of the reaction are greatly influenced by the nature of the 5-substituent. Expectedly, electron-donating groups (Me) increase the reaction rate (entry 7, see ESI † ) while electron-withdrawing groups (CH \n \n\n<svg xmlns=\"http://www.w3.org/2000/svg\" version=\"1.0\" width=\"13.200000pt\" height=\"16.000000pt\" viewBox=\"0 0 13.200000 16.000000\" preserveAspectRatio=\"xMidYMid meet\"><metadata>\nCreated by potrace 1.16, written by Peter Selinger 2001-2019\n</metadata><g transform=\"translate(1.000000,15.000000) scale(0.017500,-0.017500)\" fill=\"currentColor\" stroke=\"none\"><path d=\"M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z\"/></g></svg>\n\n O, COOH) showed the opposite effect, in line with the generally-accepted Frontier Molecular Orbital theory-derived interpretation of kinetics in DA reactions. Substitution at the furan 5-position, regardless of the nature of the substituent, not only influences kinetics but also the equilibrium position and likely destabilizes the DA adduct with respect to its addends, plausibly due to increased steric encumbrance in 3 . 11 The implication is that the most reactive diene in a series does not necessarily lead to the most thermodynamically favourable cycloaddition and hence the highest adduct yield at equilibrium. In the series R 1 = H/Me/CH 2 OH, the parent reaction (formation of 3a , R 1 = H) was found to exhibit the highest equilibrium conversion ( Table 3 , entry 1 vs . 7 and 8; see also ESI † for further details) while the relative reactivity was Me > H > CH 2 OH. Despite the somewhat less favourable equilibrium, adduct 3f (R 1 = Me) could nonetheless be isolated in a good yield (75%). Next, a high isolated yield was anticipated based on the analysis of the crude reaction mixture for adduct 3g (R 1 = CH 2 OH) but unfortunately this very polar molecule is highly water soluble, which complicated its isolation. Nonetheless, a yield of 51% of pure exo product was obtained after the sequential, one-pot conversion of 3g to a more stable derivative, i.e. by hydrogenation over Pd/C, a method used before in furan DA chemistry. 38–41 The less water-soluble Ph-analogue could be obtained utilizing our standard protocol, albeit in a low yield and purity (11%, entry 9). As expected, the presence of a second electron-withdrawing substituent is highly detrimental for the kinetics of the reaction (and likely also for the thermodynamics 9,12,34 ): adducts 3i and 3j (R 1 is CH O and COOH respectively) were formed in low amounts in the crude reaction mixtures. On the other hand, with 2 equiv. of NaOH, 2,5-furandicarboxylic acid (FDCA) gave a fast equilibration to the exo -bis-Na salt of its adduct with 2a . In this case, isolation after acidification was hampered by the highly polar nature, as noted previously, and facile cycloreversion of the (neutral) adduct back to the addends. Noteworthy, all these reactions feature high stereoselectivity for the exo adduct, typically above 15 : 1 (with the exception of adduct 3g ); the isolated products were single diastereoisomers. We then turned our attention to other furoic acid derivatives, such as esters and amides, anticipating that the electronic properties of the furan diene would not be significantly different for the substituent series COOH/COOR/CONR 2 . However, the physical properties, water miscibility in particular, are certainly strongly modulated by the nature of the substituent and this might impact the performance of the aqueous Diels–Alder cycloaddition. This proved indeed to be the case ( Table 4 ). The 2-furoic acid esters tested (Me, Et, i Pr, t Bu) are liquids with poor water miscibility; however, reactions still proceeded smoothly with so-called ‘on-water’ activation. 42,43 Scope of DA reaction between 2-furoic acid derivatives (esters, amides) and maleimides under aqueous conditions \n \n Entry X R 2 \n 3 \n Conv. 1 a \n exo - 3 , % \n endo - 3 , % Isolated b , % 1 OMe Me \n 3k \n 70 65 5 52(74) 2 OMe H \n 3l \n 67 65 2 43(64)/82 c 3 OMe Et \n 3m \n 65 61 4 47(72) 4 OEt Me \n 3n \n 63 59 4 29(46) 5 O i Pr Me \n 3o \n 54 50 4 26(49) 6 O t Bu Me \n 3p \n 54 51 3 25(46) 7 NH 2 Me \n 3q \n 94 91 3 77(83) 8 NMe 2 Me \n 3r \n 81 77 4 41(51) 9 NHOH Me \n 3s \n 92 76 16 69(75) a Conversion determined from the 1 H-NMR ratios of product isomers and starting material. b Isolated yield after (chromatographic) workup (in brackets, yield corrected on reacted starting material). c 2 M initial concentration. For ease of comparison, we employed reaction conditions similar to those found in the optimization of the cycloadditions with 1a (1 mL water per mmol, 50 °C, 16 h). The reactivity differences in the ester homologous series were marginal under these conditions. Product properties did vary, however, as the adducts of the methyl ester turned out to be much more crystalline than the rest. Simple filtration of the resulting suspensions was sufficient in this case to provide good yields of pure ( exo -) products 3k–m (43–52%). Moreover, the adduct 3l could be obtained in a much-improved yield (82%), simply by performing the reaction in more concentrated conditions (see ESI † for details). Notably, the reactions are clean and the filtrate containing unreacted starting materials can readily be recycled. Such crystallization from the crude reaction mixture did not occur with higher homologous esters (entries 4–6), necessitating chromatographic purification to isolate the adducts. Most likely some cycloreversion occurs in the process, leading to erosion of the final yield. Finally, 2-furamides were included in the substrate scope and also proved to be surprisingly reactive dienes (entries 7–9). The water soluble dimethylamide adduct 3r was formed in a comparable yield to the parent compound 3a under similar conditions ( Table 2 , entry 2), whereas adduct precipitation likely pushed conversions above 90% for products 3q and 3s by favourably shifting the thermodynamic equilibrium. Thus, the ester and amide derivatives of 2-furoic acid also show good reactivity towards maleimides and the aqueous protocol generally allows for a facile synthesis and isolation of the corresponding adducts. Again, the reactions feature high stereoselectivity towards the exo diastereoisomer (typically >12 : 1, with the exception of adduct 3s ). To the best of our knowledge, none of the adducts 3 have been previously synthesized and characterized. In particular, while acknowledging the fact that the reactive diene is not FDCA itself but its Na salt, we would like to highlight the distinct nature of this adduct ( Table 3 ) among the typical structures of furan DA adducts. 44,45 Follow-up chemistry In addition to their facile preparation, Diels–Alder adducts 3 represent valuable synthons for further synthetic elaboration ( Scheme 2 ). To complement the broad synthetic scope of our methodology, diversification at the X- and R 2 -positions in 3 ( Scheme 2 ) can also be readily achieved by straightforward transformations of title adducts 3a and 3l : ethyl ester 3n can be obtained by esterification of 3a in the presence of SOCl 2 (90% yield), whereas alkylation of 3l with benzyl bromide afforded 3t in 88% yield. Aromatization of the 7-oxanorbornene core by dehydration is a particularly interesting (and extensively studied) transformation, 45 as it provides access to renewable aromatics based on the carbohydrate fraction of lignocellulosic biomass. For the substrates studied here, the presence of an electron-withdrawing substituent at the bridghead position in 3 is anticipated to hinder (typically) acid-mediated dehydration. Nonetheless, preliminary experimentation indicated that 33 wt% HBr in AcOH 46 is a suitable acid for the conversion of 3a to phthalimide derivative 4 (66% isolated yield). Acidic hydrolysis of 4 produces in high yield hemimellitic acid 5 , an aromatic tricarboxylic acid with potential application in the polymer and lubricant industry. 47,48 Finally, catalytic hydrogenation towards oxanorbornane derivative 6 was also facile. Scheme 2 Follow-up chemistry starting with adduct 3 . Reagents and conditions: a. SOCl 2 , EtOH, rt (from 3a ); b. BnBr, K 2 CO 3 , DMF, rt (from 3l ); c. 33 wt% HBr in AcOH, rt to 60 °C (from 3a ); d. 35% HCl, 100 °C (from 4 ); e. H 2 , Pd/C, rt (from 3a ). Mechanistic understanding The above shows that furan carboxylic acid derivatives undergo surprisingly efficient Diels–Alder couplings to maleimides in aqueous solution. This result challenges the widely accepted idea that the diene scope in furan Diels–Alder chemistry is limited to electron-rich derivatives. While the nature of the furan substituent impacts the cycloaddition kinetics in a relatively predictable manner (the stronger the electron-withdrawing effect, the slower the DA reaction), we would like to note that moderate thermal activation can provide sufficient acceleration for seemingly unreactive inputs such as the 2-furoic acid derivatives used here; this is particularly true when water is used as solvent. The effect water has on the reaction can have multiple causes and may differ for the furoic acids on the one hand and the esters and amides on the other, depending on their physical characteristics. The hydrophobic effect 49 is evidently relevant for the biphasic reactions, but may not play a decisive role for the highly water-soluble 2-furoic acid substrates. To probe the operation of the hydrophobic effect in this case, we studied the title reaction between 1a and maleimide 2a in the presence of salting-in and salting-out reagents ( Table 5 ). The effect of salt additives on the rate of aqueous Diels–Alder reactions has been extensively studied. 50 In general, salting-out reagents ( e.g. simple inorganic salts like NaCl and CaCl 2 ) lead to rate enhancements, whereas additives that disturb hydrophobic interactions like guanidinium (Gn) salts characteristically retard conversion. 51 In addition, enhanced hydrophobic interactions are typically associated with an increased preference for the endo configuration of the adduct (the more compact geometry). Both of these hallmarks of the hydrophobic effect are consistently augmented with increasing additive concentration. Data in Table 5 summarizes the effect of additives on the rate of the cycloaddition between 1a and 2a (0.2 M). The observed yield and stereochemistry are generally consistent with the expected trends, illustrating that hydrophobic effect is a relevant influence in this system. DA reaction between 2-furoic acid 1a and maleimide 2a in aqueous solution: effect of additives \n \n Entry Additive Amount \n exo - 3a , % \n endo - 3a , % Total, % \n endo selectivity, % 1 None n/a 39 5 44 13 2 NaCl 1 M 42 5 47 12 3 NaCl 2 M 43 7 50 16 4 NaCl 4 M 43 9 52 22 5 CaCl 2 2 M 50 9 59 18 6 GnCl a 2 M 37 4 41 11 a GnCl = guanidinium chloride. In addition, hydrogen bonding is likely to also play an important role in our system, for instance by preferentially stabilizing the transition state (and product) over the addends. 37 For example, the electron density around the oxygen atom in the furan ring expectedly changes significantly during the reaction since aromaticity is lost as the reaction proceeds; moreover, in the product (and transition state), both oxygen lone pairs can serve as hydrogen bond acceptors. In addition, the engagement of the COOH group as H-bond donor in interactions with surrounding water molecules increases the electron density around the furan ring and thus the rate of the DA coupling. Indeed, the addition of base is the extreme case of this, i.e. leading to complete proton transfer, as illustrated by the observations that 2-furoate salts already react with maleimides at ambient temperatures and that the bis-Na salt of FDCA is, counter to expectation, a reactive diene. It is important to also note that in base-mediated reactions the thermodynamics is favourably impacted as well: adduct 3a is roughly 4 times more acidic than the starting 2-furoic acid 1a (Δp K a approx. 0.6, see ESI † ), which supplies an additional −3.6 kJ mol −1 to the , sufficient to render the reaction essentially irreversible (>95% equilibrium conversion, see Table 2 , entry 4 vs . entry 2). When 2-furoic acid esters are used as dienes, the system is no longer homogeneous and the reactions proceed ‘on-water’. Hydrophobic interactions and hydrogen bonding with water molecules at the interface play an activating role here, together with the high local concentration effect (in neat conditions for example, the reaction also proceeds readily, but conversion is hampered by the poor solubility of 2a in methyl furoate). In addition, the yield of adduct formed, i.e. the ultimate efficiency of the reaction, is definitely impacted by the crystallization of the product; this improves kinetics by reducing the rate of the back reaction and pushes the conversion beyond the solution equilibrium. Indeed, in all examples where product crystallization occurred, increased conversions were obtained ( e.g. Table 4 , entries 1, 7 and 9). Finally, furamides show comparable behaviour to the parent furoic acids, as the aqueous reactions commence homogeneously at 50 °C. In terms of kinetics, furamides are likely somewhat more reactive than furoic acids, while the tendency of the corresponding adducts to crystallize out of aqueous solution is more pronounced. For instance, with unsubstituted 2-furamide precipitation was observed within minutes (at 50 °C), benefiting conversion. In the absence of product crystallization (entry 8, Table 4 , adduct 3r ) the efficiency of the reaction is lower and quite comparable to the case of parent furoic acid 1a under similar conditions (entry 2, Table 2 )."
} | 6,993 |
33630994 | PMC8318111 | pmc | 7,600 | {
"abstract": "Abstract Background and Aims Knowledge of plant resource acquisition strategies is crucial for understanding the mechanisms mediating the responses of ecosystems to external nitrogen (N) input. However, few studies have considered the joint effects of above-ground (light) and below-ground (nutrient) resource acquisition strategies in regulating plant species responses to N enrichment. Here, we quantified the effects of light and non-N nutrient acquisition capacities on species relative abundance in the case of extra N input. Methods Based on an N-manipulation experiment in a Tibetan alpine steppe, we determined the responses of species relative abundances and light and nutrient acquisition capacities to N enrichment for two species with different resource acquisition strategies (the taller Stipa purpurea , which is colonized by arbuscular mycorrhizal fungi, and the shorter Carex stenophylloides , which has cluster roots). Structural equation models were developed to explore the relative effects of light and nutrient acquisition on species relative abundance along the N addition gradient. Key Results We found that the relative abundance of taller S. purpurea increased with the improved light acquisition along the N addition gradient. In contrast, the shorter C. stenophylloides , with cluster roots, excelled in acquiring phosphorus (P) so as to elevate its leaf P concentration under N enrichment by producing large amounts of carboxylate exudates that mobilized moderately labile and recalcitrant soil P forms. The increased leaf P concentration of C. stenophylloides enhanced its light use efficiency and promoted its relative abundance even in the shade of taller competitors. Conclusions Our findings highlight that the combined effects of above-ground (light) and below-ground (nutrient) resources rather than light alone (the prevailing perspective) determine the responses of grassland community structure to N enrichment.",
"introduction": "INTRODUCTION The amount of reactive nitrogen (N) input to terrestrial ecosystems has dramatically increased over time due to intensified human activities (e.g. agricultural fertilization) and continuous atmospheric N deposition ( Galloway et al. , 2008 ). Reactive N enrichment can directly affect ecosystem functions such as gross primary productivity and the carbon (C) cycle by altering plant physiology and soil biogeochemistry ( Manning et al. , 2006 ; Zhang et al. , 2019 ). Indirectly, external N input-induced changes in community structure, such as altered community composition and decreased species diversity, can also mediate the trajectories of ecosystem functions under N enrichment ( Manning et al. , 2006 ). Considering that the indirect effects of reactive N inputs on community structure might even dominate ecosystem responses ( Hooper et al. , 2012 ), our knowledge of the dynamics of community structure and the associated mechanisms is crucial for accurately predicting the responses of ecosystem functions to N enrichment. During the last few decades, many studies have been conducted to investigate the effects of external N inputs on community structure and composition as well as the underlying mechanisms ( Hautier et al. , 2009 ; Borer et al. , 2014 ; Dickson et al ., 2014 ; DeMalach et al. , 2017 ; Tian et al. , 2020 ). These studies highlighted that aggravated light competition was the primary driver of the contrasting responses of various species to N enrichment ( Dickson et al ., 2014 ; DeMalach et al. , 2017 ; Xiao et al. , 2021 ). Considering that light is a unidirectional (decay from the top of the canopy to the bottom) and size-asymmetrical (taller individuals receive more light per unit of size than shorter individuals) resource ( Onoda et al. , 2014 ), N inputs would favour tall species, as they can compete for light effectively ( Tilman, 1987 ; Dickson et al ., 2014 ; Gross and Mittelbach, 2017 ). Meanwhile, the light deficiency induced by the shadow of tall species would suppress the biomass and richness of short species ( Dickson et al ., 2014 ; DeMalach et al. , 2017 ). However, none of these studies has quantified the amount of light acquired by various species, which leaves unexplored the fundamental linkages between the responses of species relative abundance to N enrichment and plant light acquisition capacity. Moreover, N-induced increases in leaf area and specific leaf area ( Zhang et al. , 2019 ) would also favour light acquisition by short species even when being shaded by their taller competitors ( Hirose and Werger, 1995 ; Kohyama and Takada, 2009 ; Onoda et al. , 2014 ). For this reason, the accurate quantification of the amount of light acquired by various species is essential for better exploring the mechanisms underlying the fates of various species under N enrichment. Apart from increasing light acquisition, plants would cope with N-induced light competition by altering their acquisition of non-N nutrients [e.g. phosphorus (P) and some micronutrients] due to the strong regulation of light use efficiency by leaf nutrient status ( Wright et al. , 2004 ). However, few studies have focused on the different trajectories of leaf non-N nutrient concentrations among different species under N input. Taking leaf P concentration as an example, the prevailing perspective suggests that leaf P concentration would decline under external N input due to the imbalance between the N-induced increase in plant P demand and the elevated soil P supply as a result of the enhancement of root and soil phosphatase activity ( Li et al. , 2016 ; Deng et al. , 2017 ). In addition to secreting phosphatase, plants could also acquire P by altering their P resorption, mycorrhizal colonization, root morphology, root vitality, root carboxylate exudation and utilization of different soil P fractions ( Shen et al. , 2011 ; Lambers et al. , 2015 ; Yu et al. , 2020 ). More importantly, these P acquisition strategies could allow some species (e.g. plants with cluster roots) to acquire P effectively even under P-poor conditions ( Vance et al. , 2003 ) and further induce different responses to N enrichment in the leaf P concentrations of various species. However, to date few studies have quantified the differences in these nutrient acquisition strategies among species and considered the combined effects of above-ground (light) and below-ground (nutrients) resource acquisition in regulating the responses of species relative abundance to N enrichment. To fill this knowledge gap, we explored the effects of N input on species relative abundance, light acquisition and leaf nutrient concentrations of two species with different resource acquisition strategies [the taller, dominant species Stipa purpurea , which is colonized by arbuscular mycorrhizal fungi (AMF), and the shorter subordinate species Carex stenophylloides , which has cluster roots] and quantified the linkages between species relative abundance and above-/below-ground resource acquisition in a Tibetan alpine steppe. We also examined the relationship between species relative abundance and resource acquisition for two extra species (subordinate species Poa poophagorum and subordinate species Potentilla multifida ) whose relative abundance declined under N enrichment. To further investigate the drivers of the contrasting resource acquisition trends of S. purpurea and C. stenophylloides , we measured a series of plant and soil parameters, including plant height, leaf and root morphology, mycorrhizal colonization, root vitality, root extracellular enzyme activity, root carboxylate exudation, leaf nutrient resorption efficiency and rhizosphere soil nutrient status. The aim of our study was to explore the mechanisms underlying the species-specific responses of plant relative abundance to N enrichment. We hypothesized that above-ground (light) and below-ground (nutrients) resource acquisition would co-determine the effects of N input on species relative abundance. Specifically, plants would invest additional N in shoot growth and further acquire more light. Species relative abundance would then increase with the improved light acquisition. Meanwhile, both S. purpurea (colonized by AMF) and C. stenophylloides (with cluster roots) might alter their nutrient acquisition traits (e.g. synthesizing and secreting more phosphatase and carboxylates) to take up more non-N nutrients and thus enhance leaf nutrient concentrations. The increased leaf nutrient concentrations would then promote species relative abundance, even under a strong light competition scenario.",
"discussion": "DISCUSSION Based on the quantification of above-ground (light) and below-ground (P and other non-N nutrients) resources acquired by specific species, this study provided the first evidence that light and nutrients co-drove the response of plant species to N enrichment ( Fig. 7 ). Specifically, structural equation model and stepwise regression analyses ( Supplementary Data Table S3 ) revealed that light acquired by each species dominated the different fates of S. purpurea , P. poophagorum and P. multifida under N enrichment. This finding advances our understanding of the crucial role of light in shaping the complex responses (increasing, decreasing and unimodal) of plant species to N enrichment beyond the traditional perspective about the inhibition of short species by monotonously increasing community light interception ( Borer et al. , 2014 ) or light asymmetry ( Supplementary Data Fig. S7 ; DeMalach et al. , 2017 ). For S. purpurea , its stronger light acquisition promoted its relative abundance, while the weaker light acquisition of P. poophagorum induced a decrease in its relative abundance. It has been reported that light is a unidirectional and asymmetrical resource input from the top of the canopy to the bottom ( Onoda et al. , 2014 ) and that N enrichment would increase light asymmetry ( DeMalach et al. , 2017 ). In this study, S. purpurea acquired light more efficiently than other species because S. purpurea included tall individuals and showed increased leaf area along the N addition gradient. Meanwhile, the light acquisition of P. poophagorum may be suppressed by increased shading and light asymmetry ( Borer et al. , 2014 ; DeMalach et al. , 2017 ); thus, its relative abundance decreased. However, for P. multifida , whose light acquisition showed a unimodal response to N enrichment, its relative abundance increased initially but decreased after a threshold of 8 g N m −2 year −1 . The initial increase in light acquisition at low N levels may have occurred because N enrichment could also stimulate the growth of shorter species and increase their plant height and leaf area ( Zhang et al. , 2019 ), which was beneficial for light acquisition. Consequently, the relative abundance of P. multifida increased, especially under low N levels when the shading effect of taller species and the light asymmetry were not strong. Nevertheless, the inhibitory effect of the intensified shading exceeded the facilitation of increased plant size at high N levels, leading to decreased light acquisition and relative abundance for P. multifida . Overall, the quantification of light by different species, as performed in this study, offers the possibility of revealing the mechanisms underlying the species-specific responses to various N addition levels. Fig. 7. Schematic diagram showing how above- (light) and below-ground (P and micronutrient) acquisition strategies of S . purpurea and C. stenophylloides regulate their species relative abundance. Red arrows indicate that the parameter significantly increases along the N gradient, blue arrows represent a significant decrease, and double triangles represent non-significant changes. Light acquisition of C. stenophylloides is labelled with both a red arrow and a blue arrow, indicating that plant light acquisition first increases and then decreases along the N addition gradient. Arrow width is in proportion to the change of the parameter along the N addition gradient. Item a represents light acquisition trait, item b represents P acquisition trait, item b1 represents trait related to root P absorption, item b2 represents root exudation, item b3 represents rhizosphere soil nutrient status. Our results also demonstrated that the increased leaf nutrient (especially P) concentrations of C. stenophylloides offset the negative effect of decreased light acquisition under high N levels, and promoted its relative abundance even in the shade of taller competitors ( Fig. 6C , D ). This finding agrees with our hypothesis that above- and below-ground resource acquisition strategies co-determine the response of community structure in the case of N input and does not support the previously suggested view that light itself determines species persistence under N enrichment ( Hautier et al. , 2009 ; Borer et al. , 2014 ; DeMalach et al. , 2017 ). Although light competition is important in regulating community structure under N enrichment, plants would cope with light competition not only by modifying their light acquisition capacity but also by altering their light use efficiency ( Anten, 2005 ; Onoda et al. , 2014 ). In this study, light acquisition by S. purpurea increased along the N addition gradient, which stimulated its relative abundance. However, for C. stenophylloides the light acquired initially increased but subsequently decreased at levels higher than 8 g N m −2 year −1 . Nevertheless, N enrichment improved the light use efficiency of C. stenophylloides ( Supplementary Data Fig. S8A ), and thus induced its high relative abundance at high N levels. The increased light use efficiency of C. stenophylloides could be driven by its higher leaf P concentrations under N enrichment, due to the close associations between light use efficiency and plant nutrient levels ( Supplementary Data Fig. S8B ; Wright et al. , 2004 ). We further explored the mechanisms underlying the increased leaf P concentrations for C. stenophylloides under N enrichment. The prevailing perspective suggests that N enrichment should elevate soil P availability but that the increased soil P supply always fails to meet the increased plant P demand and thus induces a decrease in leaf P concentrations ( Deng et al. , 2017 ). In contrast, we observed that C. stenophylloides showed efficient P acquisition under N enrichment through its cluster roots, which further elevated its leaf P concentration. Under the external N input, C. stenophylloides increased its investment in below-ground nutrient acquisition, and its cluster roots became more efficient in acquiring P. Specifically, N enrichment stimulated the exudation of carbon-rich carboxylates ( Fig. 3E ), which can release soluble Pi and Po from insoluble P forms that are strongly sorbed onto soil particles by ligand exchange (mainly NaOH-Pi and Po, and HCl-Pi; Vance et al. , 2003 ; Lambers et al. , 2015 ; Table 1 ). The soluble Pi released during this process can be directly absorbed by cluster roots, while the soluble Po is first converted into soluble Pi by phosphatase and then taken up by plants ( Lambers et al. , 2015 ). Meanwhile, the root vitality and root PME activity of C. stenophylloides also increased significantly after additional N input. Consequently, the leaf P concentration of C. stenophylloides increased along the N addition gradient. Interestingly, though the root vitality, root PME activity and root carboxylate exudation of S. purpurea also increased under N enrichment, its leaf P concentration declined. This might be due to the fact that S. purpurea invested more photosynthate in shoot growth, reduced its below-ground C inputs, and induced a decline in AMF root colonization along the N gradient (the plant supplied all the C that the fungi required; Smith et al. , 2011 ). Although AMF could only utilize the labile P forms, it usually takes up soluble Pi more efficiently than roots (by exploring more soil volume; Smith et al. , 2011 ; Raven et al. , 2018 ). As a result, the decreased AMF root colonization might restrict P absorption of S. purpurea , and contributed to the decline of its leaf P concentration. In addition to P, the changed nutrient acquisition traits could also help in the acquisition of other micronutrients. Consistent with this deduction, our results revealed a positive association between leaf micronutrient concentrations of C. stenophylloides and its root carboxylate exudation ( Supplementary Data Fig. S6 ). Nevertheless, apart from alleviating nutrient limitations, the accumulation of micronutrients in leaves can have a negative effect on C. stenophylloides due to the inhibition of the plant photosynthetic rate and growth by metal toxicity ( Tian et al. , 2016 ). These contrasting effects of leaf micronutrients may have led to the weak linkages between the relative abundance and leaf micronutrient concentration of C. stenophylloides along the N addition gradient. In summary, this study revealed that above- and below-ground resource acquisition strategies co-determine the responses of plant species to N enrichment ( Fig. 7 ). The relative abundance of the taller S. purpurea increased with its increased light acquisition. Meanwhile, the increased non-N nutrient (especially P) concentrations in leaves promoted the relative abundance of cluster-rooted C. stenophylloides even in the shade of taller competitors. These results demonstrated that the increased leaf P in the shorter species stimulated their light use efficiency and facilitated their relative abundance along the N addition gradient. These findings conflict with previous findings that the aggravation of light limitation induced by N input drives shorter species to extinction ( Borer et al. , 2014 ; DeMalach et al. , 2017 ). Given that decreases in species diversity and changes in community composition always constrain the responses of ecosystem productivity to N enrichment ( Hooper et al. , 2012 ), the persistence of short species may contribute to the consistent positive effects of N inputs on ecosystem productivity. Therefore, considering the differences in species resource acquisition strategies can help to reveal the mechanisms underlying the dynamics of community structure and ecosystem functions under an N enrichment scenario."
} | 4,616 |
35403772 | PMC9539497 | pmc | 7,601 | {
"abstract": "Abstract Loss of habitats and native species, introduction of invasive species, and changing climate regimes lead to the homogenization of landscapes and communities, affecting the availability of habitats and resources for economically important guilds, such as pollinators. Understanding how pollinators and their interactions vary along resource diversity gradients at different scales may help to determine their adaptability to the current diversity loss related to global change. We used data on 20 plant–pollinator communities along gradients of flower richness (local diversity) and landscape heterogeneity (landscape diversity) to understand how the diversity of resources at local and landscape scales affected (1) wild pollinator abundance and richness (accounting also for honey bee abundance), (2) the structure of plant–pollinator networks, (3) the proportion of actively selected interactions (those not occurring by neutral processes), and (4) pollinator diet breadth and species' specialization in networks. Wild pollinator abundance was higher overall in flower‐rich and heterogeneous habitats, while wild pollinator richness increased with flower richness (more strongly for beetles and wild bees) and decreased with honeybee abundance. Network specialization ( H \n 2 ′), modularity, and functional complementarity were all positively related to floral richness and landscape heterogeneity, indicating niche segregation as the diversity of resources increases at both scales. Flower richness also increased the proportion of actively selected interactions (especially for wild bees and flies), whereas landscape heterogeneity had a weak negative effect on this variable. Overall, network‐level metrics responded to larger landscape scales than pollinator‐level metrics did. Higher floral richness resulted in a wider taxonomic and functional diet for all the study guilds, while functional diet increased mainly for beetles. Despite this, specialization in networks ( d ′) increased with flower richness for all the study guilds, because pollinator species fed on a narrower subset of plants as communities became richer in species. Our study indicates that pollinators are able to adapt their diet to resource changes at local and landscape scales. However, resource homogenization might lead to poor and generalist pollinator communities, where functionally specialized interactions are lost. This study highlights the importance of including different scales to understand the effects of global change on pollination service through changes in resource diversity.",
"conclusion": "CONCLUSIONS Assessing how the diversity of resources at the local and landscape scales shape pollinator communities and their pollination interactions is essential to understand the effects of anthropogenic changes on the pollination services. This study shows that resource diversity at both scales enhances abundance and richness of wild pollinators and the complexity of plant–pollinator networks. Pollinators' diet breadth is mostly related to resources at the local scale, with wild pollinators widening their diets but also increasing their specialization in networks as flower richness increases. Our study indicates that pollinators are able to adapt their diet to cope with resource homogenization at local and landscape scales, induced by global change drivers. However, resource homogenization might lead to poor, generalist, and more functionally redundant pollinator communities, where pollination interactions are mainly driven by neutral processes, potentially hindering the maintenance of quality pollination services.",
"introduction": "INTRODUCTION Wild pollinators are essential for plant reproduction and the maintenance of ecosystem function (Kremen et al., 2007 ; Ollerton et al., 2011 ). Literature over the last decades have described a global pollinator decline (Burkle et al., 2013 ; Potts et al., 2010 ); however, recent reviews suggest a less alarming situation (Guzman et al., 2021 ; Saunders et al., 2020 ), in which the decline mostly occurs in anthropogenic ecosystems (Herrera, 2019 ). Such decline is thought to be mainly driven by land‐use changes that lead to the homogenization of landscapes (Holzschuh et al., 2007 ) and communities (Gossner et al., 2016 ), affecting the availability of habitats and resources that pollinators need (Kremen et al., 2007 ). To predict and anticipate the effects of global change on the pollination service provided by wild pollinators, it is necessary to understand how variation in resource diversity affects pollinator communities and their pollination interactions. Resource diversity varies both at landscape and local spatial scales (Figure 1a ), affecting pollinators and their interactions differently (Moreira et al., 2015 ; Sjodin et al., 2008 ; Steffan‐Dewenter et al., 2002 ). At the landscape scale, an increase in the diversity of available habitats (landscape heterogeneity), may support more diverse pollinator communities (Figure 1b ; Andersson et al., 2013 , Mallinger et al., 2016 , Ropars et al., 2020 , Steckel et al., 2014 ), both because more habitats imply more niches to be exploited by different species (Holzschuh et al., 2008 ; Lázaro & Alomar, 2019 ) and because landscape heterogeneity might favor landscape complementation (i.e., the use of several habitats by pollinators to fulfill their needs for specific resources; Gathmann & Tscharntke, 2002 , Klein et al., 2004 ). At the local scale, variation in flower diversity determines the availability of feeding resources (Potts et al., 2003 ), thus affecting the composition of pollinator communities (Figure 1b ; Potts et al., 2003 , Frund et al., 2010 ). However, different pollinators might have contrasting responses to resource variation at landscape or local scales. For instance, wild bees might be more sensitive than honeybees or hoverflies to variations in resource configuration (Blaauw & Isaacs, 2014 ), and different flying capabilities might influence pollinators' vulnerability to landscape modifications (Steffan‐Dewenter et al., 2002 ; Westphal et al., 2006 ). However, it is still unclear how and to what extent resource diversity at different scales affects the components of pollinator communities. FIGURE 1 Conceptual diagram depicting the expected effects of resource diversity on pollinator communities and pollination interactions. (a) Variation in resource diversity at different scales. (b) Expected relationships between resource diversity and pollinator abundance and richness, the structure of plant–pollinator networks, and pollinators' diet breadth and specialization The structural properties of plant–pollinator networks may also change along gradients of resource diversity (Tylianakis & Morris, 2017 ). Previous work has shown increases in network specialization and modularity (Figure 1b ) in relation to increases in landscape diversity (Escobedo‐Kenefic et al., 2020 ) and local flower diversity (Ebeling et al., 2011 ; Lázaro, Tscheulin, Devalez, Nakas, Stefanaki, et al., 2016 ; Traveset et al., 2018 ). Both metrics represent structural properties of ecological networks, typically linked to their stability (Gilarranz et al., 2017 ; Grilli et al., 2016 ; May, 1972 ). In addition, pollinator functional complementarity may also change along resource gradients (Figure 1b ), because pollinators are expected to segregate niches to increase feeding efficiency and/or reduce competition (Blüthgen & Klein, 2011 ; Fründ et al., 2013 ; Venjakob et al., 2016 ), ultimately increasing network modularity and dietary specialization (Izquierdo‐Palma et al., 2021 ). Overall changes in network structure along gradients may be related to changes in species composition, but also to changes in interaction frequencies (Tylianakis & Morris, 2017 ). Pollination interactions are determined by trait matching and spatiotemporal constraints (Jordano et al., 2003 ; Santamaría & Rodríguez‐Gironés, 2007 ; Vázquez et al., 2009 ), as well as by neutral processes, i.e., abundant species interact more frequently and with more species than rare species if pollinators distribute themselves randomly across the plant community (Vázquez, 2005 ; Vázquez et al., 2009 ). It is likely that the relative importance of these processes vary along resource gradients, because pollinators are able to adjust their diet based on their preferences (Cusser et al., 2019 ; Kelly & Elle, 2021 ) and/or to reduce competition (Inouye, 1978 ; Jeavons et al., 2020 ; Pasquaretta et al., 2019 ; Wignall et al., 2020 ). Facilitation processes among plants for pollination (Braun & Lortie, 2019 ; Tur et al., 2016 ) might also modulate pollinators' perception of resource distribution and influence how they adjust their diets to improve foraging efficiency. It could be hypothesized that the greater range in resources in diverse communities might result in a higher frequency of actively selected interactions. However, to our knowledge, no study to date has directly assessed the influence of resource diversity at different scales on interaction patterns (random vs. actively selected interactions). Diet adjustments along resource gradients may also influence wild pollinators' diet breadth (i.e., diversity of plant species and flower traits included in their diet; hereafter taxonomic and functional diet breath, respectively) and species' specialization ( d ′, Blüthgen et al., 2006 ) in the networks (Figure 1b3 ). Pollinators' taxonomic and functional diet breath might not be correlated in modified landscapes, because a high taxonomic diversity of plants is not necessarily associated with a high functional diversity (see, e.g., Cursach et al., 2020 ). Although species' specialization in the networks and diet breadth are expected to be negatively correlated, these variables may be unrelated if pollinators expand their diet but still make use of a small proportion of the available resources (Kelly & Elle, 2021 ). Similarly, specialization may be related or unrelated to functional complementarity, depending on whether specialist species share or not their functional niche (Blüthgen & Klein, 2011 ). Several studies, mostly in bees, have demonstrated that diet breadth and specialization ( d ′) change as a consequence of interspecific competition (Inouye, 1978 , Jeavons et al., 2020 , Pasquaretta et al., 2019 , Wignall et al., 2020 ); however, only a few of them have assessed the influence of resource diversity on pollinators' diet (Cusser et al., 2019 , Kelly & Elle, 2021 ). Understanding how pollinators' diets vary across gradients of resource availability may allow us to address community functions more accurately (Kelly & Elle, 2021 ). In this study, we evaluate how resource diversity at landscape (landscape heterogeneity) and local (flower richness) scales affect wild pollinator richness and abundance, the structure of pollination networks and the use of flowering resources. For this, we used data on 20 natural plant–pollinator communities along gradients of landscape heterogeneity and flower richness. As the abundance of managed honeybees is known to affect wild pollinator diversity and abundance (Lázaro et al., 2021 ; Magrach et al., 2017 ; Ropars et al., 2019 ), we also assessed the effect of honeybee densities when testing the effects of resource diversity. Particularly, we aimed at evaluating the following hypotheses: (1) Wild pollinator abundance and richness will increase with resource diversity at both spatial scales, but at different rates for different pollinator guilds due to their different life history traits; (2) A high abundance of honeybees will negatively affect wild pollinator abundance and richness; (3) Pollination networks will become more complex in richer plant communities within heterogeneous landscapes; (4) The proportion of plant species that will be selected more than expected at random (i.e., those interactions not occurring by neutral processes) will change with local flower richness and changes in pollinator composition related to landscape heterogeneity; And (5) local flower diversity will increase wild pollinators' diet breadth, but also their species' specialization in networks, as pollinators visit a smaller subset of available plants.",
"discussion": "DISCUSSION In this study, we showed that resource diversity at local and landscape scales were significant predictors of the abundance and richness of wild pollinators, the structure of their pollination interactions and their diet breadth and specialization. Resource‐diverse habitats held richer and more abundant wild pollinator communities. Flower richness and landscape heterogeneity led to more specialized and modular networks, and more functionally complementary pollinators than expected at random. In flower‐rich habitats neutral processes were less common, and wild pollinators widened their taxonomic and functional diets, but also increased their specialization in the networks (i.e., reduced the number of plant species they visited from those available). Wild pollinator abundance and richness As expected, we found higher pollinator abundance in flower‐rich communities (Kennedy et al., 2013 ; Lázaro, Tscheulin, Devalez, Nakas, Stefanaki, et al., 2016 ), and in heterogeneous landscapes (Kennedy et al., 2013 ; Mallinger et al., 2016 ), although this last relationship was only marginally significant. We also expected wild pollinator richness to increase with flower richness (Gómez‐Martínez et al., 2020 ; Lázaro, Tscheulin, Devalez, Nakas, Stefanaki, et al., 2016 ) and with landscape heterogeneity (Andersson et al., 2013 ; Mallinger et al., 2016 ; Steckel et al., 2014 ), but we failed to find the latter relationship. Heterogeneous landscapes may present a high variety of different habitats and microhabitats (Holzschuh et al., 2008 ), which increase landscape complementation (Brotons et al., 2004 ; Fahrig, 2003 ), and potentially harbor functionally different pollinators (Lázaro & Alomar, 2019 ) that may need resources scattered in different habitats, such as nesting sites or feeding resources (Gathmann & Tscharntke, 2002 ; Klein et al., 2004 ). Therefore, while local flower richness positively influences both richness and abundance, our results seem to indicate that heterogeneous landscapes primarily enhance wild pollinator abundance, perhaps through the increase in nesting resources (Moreira et al., 2015 ). Interestingly, agreeing with other authors (Lázaro et al., 2021 ; Ropars et al., 2020 ; Valido et al., 2019 ), we also found a negative relationship between honeybee abundance and wild pollinator richness. Honeybees are social insects and highly generalist feeders (Michener, 2007 ), with a great ability to communicate location of flower resources among colony members to respond quickly to resources availability (Beekman & Ratnieks, 2000 ). For these reasons, when honeybees are introduced at high abundances, they may out‐compete and displace wild pollinators by dominating the most abundant food resources (Hung et al., 2019 ). The displacement of wild pollinators by honeybees is a major concern because honeybees cannot replace the pollination services provided by wild species (Garibaldi et al., 2013 ). Therefore, the massive introduction of honeybees might deeply affect pollination interactions in natural ecosystems (Lázaro et al., 2021 ; Magrach et al., 2017 ) and agroecosystems, where it may drive to substantial economic losses (Cusser et al., 2021 ). Beetles and wild bees were the guilds that responded more strongly to flower richness in terms of species richness, while richness of flies, wasps, and butterflies did not vary significantly along the flower richness gradient. Little is known about the effects of plant richness on beetle communities, and the findings are so far inconclusive, with some authors describing positive effects of plant diversity on beetle diversity (Woodcock et al., 2005 ), while others failing to find any relationship (Sjodin et al., 2008 ). Likely, the pattern found for beetles is related to the fact that is one of the most species‐rich guilds in our study system and by far the most abundant. On the other hand, positive effects of flower diversity on wild bee richness are largely described in literature (e.g., McCullough et al., 2021 ; Williams et al., 2015 ). It is not surprising that wild bee richness is closely related to flower richness, as these pollinators depend on flowering resources in all their life stages and castes (Michener, 2007 ). On the contrary, flies are a diverse group with many different feeding strategies in adult and larvae stages (Yeates & Wiegmann, 2005 ), which could be the reason for not finding a relationship between flower richness and fly richness in our system. Several studies have found positive effects of flower richness on hoverflies and/or bee flies (Lázaro, Tscheulin, Devalez, Nakas, & Petanidou, 2016 ; Meyer et al., 2009 ; Robertson et al., 2020 ), the main groups within flies specialized in flower feeding at the adult stage (e.g., Kastinger & Weber, 2001 ; Larson et al., 2001 ). In our communities, hoverflies and bee flies were scarce and the guild of flies was mostly composed by other types of flies (mainly Calliphoridae, Rhiniidae, Anthomyiidae, Empididae, and Chloropidae); therefore, flower‐specialist flies were pooled with the rest of flies for analyses (separating them in the analyses did not change the results; see Appendix S1 : Table S13 and Figure S3 ). For this heterogeneous group, other factors not included in this study might be influencing their richness; for instance, aphidophagous species are found to thrive in agroecosystems, while saproxylic species are linked to forest (Jauker et al., 2009 ). The structure of plant–pollinator networks Network specialization, modularity, and functional complementarity were always higher than expected at random, which is not surprising as different constraints as phenology, trait‐mismatching or pollinator preferences may prevent from a completely random distribution of interactions (Vázquez et al., 2007 ). They also became much higher than expected at random as both flower richness and landscape heterogeneity increased. The three metrics pointed in the same direction: high resource diversity at both local and landscape scales drives to more specialized and modular networks, where wild pollinator species decrease their interspecific niche overlap by using different flowering resources. Pollinators may segregate niches when resources are diverse to reduce competition, select more rewarding flowers and/or increase their foraging efficiency (Fründ et al., 2013 ; Venjakob et al., 2016 ), which may in turn lead to a higher specialization and modularity in the networks (Lázaro, Tscheulin, Devalez, Nakas, Stefanaki, et al., 2016 ; Olesen et al., 2007 ). Such increased niche differentiation might have important functional consequences, because functional complementarity has been shown to be positively related to plant reproductive success (Magrach et al., 2019 ). Therefore, heterogeneous landscapes might favor overall pollination service through the increase in functional complementarity in the networks. Although the three analyzed metrics were related to landscape heterogeneity, network specialization ( H \n 2 ′) and modularity were affected by the landscape at a larger scale (1 km) than functional complementarity (250 m). Likely, these differences are due to the nature of the metrics, as H \n 2 ′ and modularity are network‐level properties (Blüthgen & Klein, 2011 ), while functional complementarity is a group‐level property (Devoto et al., 2012 ) regarding just one trophic level of the network (wild pollinators, in our case). The effect on functional complementarity of landscape heterogeneity at 250 m might indicate that the processes involving the relationships among pollinator species are modulated at local scales of resource distribution. However, further work is needed to evaluate whether the scale‐patterns found here also are found in other plant–pollinator communities. Neutral processes versus active selection of flowers as determinants of interaction patterns As expected, we found that local flower richness enhances the proportion of actively selected interactions that occur more than expected based on the relative abundance of the plant species (Vázquez et al., 2007 ). This might be related to non‐random process as trait matching (Jordano et al., 2003 ; Santamaría & Rodríguez‐Gironés, 2007 ; Vázquez et al., 2009 ), but also to higher selection of preferred/more rewarding flowers (Cusser et al., 2019 ), or to higher niche segregation to reduce competition (Inouye, 1978 ; Jeavons et al., 2020 ; Pasquaretta et al., 2019 ; Wignall et al., 2020 ) when flower availability increases. The relationship between flower richness and the proportion of actively selected interactions is similar to the relationship between flower richness and modularity, as wild pollinators preferentially visiting certain plant species is part of the process involved in the modular structure of interactions. However, while all the guilds increased their proportion of actively selected interactions with flower richness, landscape heterogeneity at 250 m slightly decreased the proportion for wild bees and beetles, but not for flies. The reasons for this are not clear, but some authors have argued that structurally complex habitats make efficient searching difficult (Brose et al., 2005 ; Laliberté & Tylianakis, 2010 ) and reduce the frequency of interactions, while less structurally complex habitats can improve search efficiency and increase the proportion of potential interactions (Laliberté & Tylianakis, 2010 ; Tylianakis & Morris, 2017 ). Perhaps landscape heterogeneity, as a measure of landscape complexity (Chaplin‐Kramer et al., 2011 ), reduces the proportion of actively selected interactions by hindering encounter probability between wild pollinators and their preferred plants. As in the case of functional complementarity, actively selected interactions were related to landscape heterogeneity at the 250 m scale, agreeing with the idea that processes occurring within the pollinator trophic level were influenced by the landscape at a smaller scale than processes influencing the whole network level. In any case, our results clearly indicate that interaction patterns are context dependent, and that wild pollinators show high plasticity in their diet, which allow them to adapt to different situations (Cusser et al., 2019 ; Inouye, 1978 ; Jeavons et al., 2020 ). It is important to note that, even for the guilds with a higher proportion of actively selected interactions, still over a 55% of the interactions could be explained as random encounters, as estimated avoided interactions represented less than a 5% of total interactions. This indicates that more than half of the interactions occurring in these plant–pollinator communities are driven by stochastic processes and modulated by relative abundances (Vázquez et al., 2007 ). Diet breadth and specialization Overall, our results show a high foraging plasticity as response to variation in local flower richness. We found that wild pollinators widen their taxonomic and functional diet as flower richness increases in the communities, i.e., pollinators fed on more plant species and with a higher variety of traits. However, there was no effect of landscape heterogeneity on taxonomic or functional diet. Cusser et al. ( 2019 ) also showed the diet breadth of two bee species was locally constrained by flowering resources and did not respond to landscape modifications. However, they just studied two bee species, while we have shown the same patterns studying over 33 species belonging to very different pollinator guilds (17 beetles, eight flies, and eight wild bees, that were present in at least 10 study sites and with at least five visits per site). Our result was expected, because a higher diversity of food resources implies more opportunities to feed on different flowering plant species. Despite that there were no differences among pollinators on how taxonomic diet breadth increased with flower richness, functional diet breadth increased more strongly for beetles than for flies and wild bees. In concordance with this, we also showed that the increase in the proportion of actively selected interactions as flower richness increased was faster for wild bees and flies than for beetles. It seems that beetles are highly opportunistic and randomly interact with plant species, therefore increasing their functional diet breadth when more flowering species are available. Flies and wild bees, on the contrary, seem to always feed on a relatively constant diversity of traits. Interestingly, despite the higher taxonomic and functional diet in more flower‐rich communities, species' specialization in the networks ( d ′) also increased with flower richness, consistently for the three guilds. Similarly, Lázaro, Tscheulin, Devalez, Nakas, Stefanaki, et al. ( 2016 ) showed that the specialization ( d ′) of bees, beetles and flies decreased along a gradient of grazing intensity (i.e., as communities became flower poorer). Our results are also in concordance with those reported by Kelly and Elle ( 2021 ) on the solitary bee Andrena angustitarsa , since they showed that this dietary generalist species increased its specialization ( d ′) as the abundance of Apiaceae flowers increased. Overall, our results indicate that pollinators can adjust their diet, by including more species in it as flower richness increases, but also segregating niches and feeding on a narrower subset of plants from those available. Further studies might perform deeper sampling of each population diets to confirm these patterns."
} | 6,485 |
32392238 | PMC7213722 | pmc | 7,602 | {
"abstract": "Here we present the synthesis and characterization of two new conducting materials having a high electro-chemo-mechanical activity for possible applications as artificial muscles or soft smart actuators in biomimetic structures. Glucose-gelatin nanofiber scaffolds (CFS) were coated with polypyrrole (PPy) first by chemical polymerization followed by electrochemical polymerization doped with dodecylbenzensulfonate (DBS - ) forming CFS-PPy/DBS films, or with trifluoromethanesulfonate (CF 3 SO 3 - , TF) giving CFS-PPy/TF films. The composition, electronic and ionic conductivity of the materials were determined using different techniques. The electro-chemo-mechanical characterization of the films was carried out by cyclic voltammetry and square wave potential steps in bis(trifluoromethane)sulfonimide lithium solutions of propylene carbonate (LiTFSI-PC). Linear actuation of the CFS-PPy/DBS material exhibited 20% of strain variation with a stress of 0.14 MPa, rather similar to skeletal muscles. After 1000 cycles, the creeping effect was as low as 0,2% having a good long-term stability showing a strain variation per cycle of -1.8% (after 1000 cycles). Those material properties are excellent for future technological applications as artificial muscles, batteries, smart membranes, and so on.",
"conclusion": "4. Conclusions We have shown that the CFS materials coated with conducting polymers (PPy/DBS and PPy/TF) remained with a biomimetic bundle-like structure (as seen in the SEM images). The FTIR measurements identified successful combination of CFS with PPy/DBS and PPy/TF. It was shown that 20% linear strain and 0.1 MPa stress for CFS-PPy/DBS (CFS-PPy/TF reached 8% linear strain) was achievable, which is similar to the respective parameters of natural skeletal muscles. For both materials, a single ion species (the anion) dominates the actuation direction (expansion at oxidation). Of the two materials, CFS-PPy/DBS should be preferred based on the maximum strain and stress reached, but also for lower creep with useful response stability in square wave potential step measurements over 1000 cycles at 0.1 Hz. The behavior is well described using theoretical models, allowing consistent characterization and control of potential devices. The main drawback of the fibrous linear actuators compared to natural muscles is the significantly lower strain rates. Further research in optimizing is needed in order to reach applications in soft robotics and multifunctional smart materials truly mimicking natural muscles.",
"introduction": "1. Introduction The development of reliable soft robotics and smart devices mimicking the multifunctionality of natural organs of living creatures requires new actuators in biomimetic structures and artificial muscles, working at low potentials with low energy consumption while exhibiting high strain variation per potential cycle and high long-term stability. Conducting polymers actuators [ 1 ] that work at low voltage, undergo large bending displacements [ 2 ] and linear strains as high as 26% [ 3 ]; 20% of strain variation was reported in case of PPy-Platinum/Iridium coil structures [ 4 ]. Inspired by similar coil designs, researchers try to increase linear strain by using carbon nanotubes and other natural or artificial electrospun materials [ 5 ] in their plain form or with a conducting polymer coating (CP). In addition, the electrochemical reaction of the CP driving the actuator senses, simultaneously, the physical and chemical conditions [ 6 ] allowing the development of sensing [ 7 ] and tactile [ 8 ] actuators suitable for mimicking the multifunctionality of haptic natural muscles and developing artificial proprioceptive systems [ 9 , 10 ]. At present, the main technological problem is the described poor long-term stability, the high strain variations are only achieved in the initial potential cycles. The actuation mechanism has been intensely studied in the past [ 11 – 15 ] with no unified model established. The main idea behind any model or development is making an “artificial muscle” in biomimetic structures comparable to skeletal muscles [ 1 ] showing ~ 20% of strain variation during an actuation cycle developing a stress higher than 0.1 MPa (0.3 MPa from cardiac muscles). Natural muscles have fiber bundle structures constituted by chemical molecular machines, i.e. actin-myosin-ATP, that develop that strain and stress variation at high rates during milli seconds, comparable performance has not been achieved by conducting polymer-based actuators. Fiber-actuators based on polyaniline have reached strains in range of 1.2% [ 16 ]. 3% strain has been reported for actuators based on interpenetrated networks of hollow fibers- of poly(3,4-ethylenedioxythiophene) [ 17 ]. Use of solid polymer electrolytes (SPE) [ 18 ] in linear fiber-actuators as well as encapsulated design [ 19 ] have led to linear strain of 0.5% [ 20 ] with drawbacks in actuator performance [ 21 ]. Different fiber-actuator designs of knitted and twisted yarns have been applied [ 22 ] to increase linear strain up to 3%. Using a single Lyocell PPy fiber a diametrical strain up to 6% was achieved [ 23 ]. Previous research [ 24 ] has also described a solution based on different elastic stretchable silicon yarns coated with electropolymerized PPy that reached 0.1% strain. Nanofiber scaffolds produced by electrospinning have fiber bundle structures that can be applied as is, or coated with PPy, in tissue engineering for skeleton muscle repair [ 25 ] due to its biocompatibility with cells [ 26 , 27 ]. Thus, besides the right conducting polymer, the substrate material has a great influence on the attained electrochemical actuation. Following those ideas for increasing the mechanical performance of linear actuators our goal here was to use conductive nanofiber scaffold material coated with electropolymerized PPy for designing biomimetic active materials, which could be comparable to natural skeletal muscles in terms of structure, achievable strain and stress, and importantly—with long life time. The conductive nanofiber scaffold (CFS) consist of chemical coated used in previous works [ 28 , 29 ] as the substrate for electrodes to develop new materials by electropolymerization. This material can be stretched up to 17% without a major loss of conductivity. 1.1 Driving electrochemical reactions Two different materials were obtained by using the conductive fiber scaffold (CFS) to electrodeposit a new PPy coat from solutions containing two different electrolytes: CFS-PPy/DBS and CFS-PPy/TF. Linear strain and force measurements were performed by cyclic voltammetry in LiTFSI propylene carbonate (PC) solutions. The material actuation (reversible volume change by swelling/shrinking) is driven by reversible electrochemical oxidation/reduction reactions of the PPy material exchanging anions and solvent with the electrolyte for charge and osmotic balance [ 30 – 32 ] following Eq 1 : forwards, oxidation-swelling reaction; backwards, reduction-shrinking reaction:\n [ ( P P y ) ( D B S − ) m ( L i + ) m ( P C ) o ] + n T F S I − + p P C ⇄ [ ( P P y ) n + ( D B S − ) m ( L i + ) m ( P C ) ( o + p ) ( T F S I − ) n + n ( e − ) m e t a l (1) The un-dissociated Li + DBS - ions pairs were incorporated during the electropolymerization process remaining now trapped in PC solutions, as was proved by XPS. The PPy/TF material also follows an anion driven actuation [ 33 ] without trapping ions seen in Eq 2 :\n ( P P y 0 ) + n ( T F S I − ) s o l + m ( P C ) ⇄ [ ( P P y n + ) ( T F S I − ) n ( P C ) m ] + n ( e − ) (2) The left side shows the reduced PPy material and the right side the oxidized PPy material where the solvated anions TFSI - incorporate in the positively charged PPy and are remove as the PPy is reduced. As a typical anion driven actuator, the simplest material model of the intracellular matrix (ICM) of the muscular cells [ 34 ].",
"discussion": "3. Results and discussion 3.1 Electropolymerization and morphology The electropolymerization curves (chronopotentiometric responses during the electropolymerization process) and the SEM images of the attained free standing PPy/DBS and PPy/TF films are presented in S1 Fig . The electropolymerization responses during the synthesis of the CFS-PPy/DBS and CFS-PPy/TF films, as well as the SEM images of the attained materials are shown in Fig 1A–1C . 10.1371/journal.pone.0232851.g001 Fig 1 a: Chronopotentiometric response during the galvanostatic electropolymerization of the CFS-PPy/DBS (black line) and CFS-PPy/TF (red line) scaffold materials. The SEM surface images (scale bar 5 μm); each inset shows the cross section of a single fiber (scale bar 1 μm): b, CFS-PPy/DBS, and c, CFS-PPy/TF. Fig 1A shows that the CFS-PPy/DBS samples grew during 11.1h under a constant electropolymerization potential of 2.55 V, while the electropolymerization of the CFS-PPy/TF sample was a more resistive process, going through a potential maximum of 3.45 V after 0.5h and then decreasing gradually to 3.22 V by the end of the polymerization time. These observations can be attributed to the different electronic conductivity of the samples immersed in different electrolytes; 0.42 ± 0.2 S cm -1 in aqueous-ethylene glycol solution, and 0.11 ± 0.1 S cm -1 in PC solution similar to those found in a previous work [ 29 ]. The reference electropolymerization of PPy/DBS and PPy/TF films on stainless steel sheets ( S1 Fig ) required lower voltages: 1.17 V for PPy/TF and 0.9 V for PPy/DBS, due to the higher conductivity of the underlayer, but also pointing to less overoxidation-degradation processes during the material generation. Fig 1B shows that the CFS-PPy/DBS sample presents a quite uniform coating film of electrodeposited PPy/DBS material. The diameter of the cross section of the fiber is 2.2 ± 0.2 μm. The diameter of the original chemically coated nanofiber scaffold was 1.4 ± 0.1 μm [ 28 ], accordingly, the PPy/DBS electrodeposition added 0.8 ± 0.04 μm (inset of Fig 1B ). The CFS-PPy/TF sample (inset of Fig 1C ) shows a diameter in range of 2.5 μm. The SEM images of PPy/DBS and PPy/TF free standing films, S1B and S1C Fig , revealed the typical PPy morphology seen before [ 37 , 38 ], with a dense cross section (inset of S1B and S1C Fig ). Table 1 present both, conductivities and thicknesses of the dry samples, as well as those of the free standing PPy/DBS and PPy/TF films. 10.1371/journal.pone.0232851.t001 Table 1 Electronic conductivities and thicknesses of CFS-PPy/DBS and CFS-PPy/TF samples as well PPy/DBS and PPy/TF free standing films (after polymerization). Samples Conductivity [S cm -1 ] Thickness [μm] CFS-PPy/DBS 2.4 ± 0.2 125 ± 8 PPy/DBS 15.4 ± 0.5 24 ± 1.1 CFS-PPy/TF 10.0 ± 0.7 136 ± 9 PPy/TF 11.4 ± 0.8 20 ± 0.1 The free standing films present the highest conductivities, as expected for solid films, 15.4 S cm -1 for PPy/DBS and 11.4 S cm -1 for PPy/TF quite close to the CFS-PPy/TF sample, 10 S cm -1 ; the CFS-PPy/DBS sample was the most resistive, at 2.4 S cm -1 . The results can be related to the influence of the PC solvent on the electropolymerization process [ 39 ], but also on the different real (active material) density of the materials. 3.1.1 FTIR and EDX spectroscopy Fig 2A shows the FTIR spectra obtained from the original CFS material and from the CFS-PPy/DBS and CFS-PPy/TF samples. Fig 2B and 2C show the EDX spectroscopic results (using cross section of the CFS-PPy/DBS and CFS-PPy/TF) from both, the oxidized and the reduced samples in order to try to identify the different ion content of the two states. 10.1371/journal.pone.0232851.g002 Fig 2 a: FTIR spectra of CFS-PPy/DBS (black line), CFS-PPy/TF (red line) and CFS samples (blue line) in wavelength range of 2000 to 800 cm -1 . EDX spectra of oxidized (5min, 1V, black line) and reduced (5 min at -0.55 V, red line) in b: CFS-PPy/DBS and c: CFS-PPy/TF. The CFS material ( Fig 2A ) contained some PPy from the original chemical polymerization (using APS oxidant) on the glucose-gelatin nanofiber scaffold. The sharp peak at 1778 cm -1 seen in CFS sample is from the carboxyl group (C = O) formed by PPy overoxidation [ 40 ]. Typical signals for glucose-gelatin are shown at 1640 and 1533 cm -1 [ 41 ] as the amide I and amide II peaks, respectively. The peak at 1640 cm -1 can be clearly identified in CFS, CFS-PPy/TF and CFS-PPy/DBS. The peak at 1533 cm -1 for CFS-PPy/DBS is overlapped by the 1542 cm -1 peak, which represents the polypyrrole ring stretching vibration (C = C) [ 42 ]. Other typical PPy peaks can be found at 1452 cm -1 (C-C stretching vibrations) and 1280 cm -1 (C-N stretching mode) [ 43 ] and the band at 1160 cm -1 –1200 cm -1 , which was identified in CFS-PPy/DBS at 1168 cm -1 as the breathing vibration of the PPy ring [ 44 ]. The 1183 cm -1 peak found for CFS and CFS-PPy/TF describe the same breathing vibrations of PPy rings [ 44 ]. The polaron band is found in CFS and CFS-PPy/DBS at 1040 cm -1 (in literature 1045 cm -1 [ 45 ]). In CFS-PPy/TF a new peak at 1023 cm -1 was associated with the triflate anion [ 46 ]. It can be concluded that PPy/DBS and PPy/TF were indeed deposited on CFS material. Fig 2B and 2C show the EDX spectroscopic results from CFS-PPy/DBS and CFS-PPy/TF samples, respectively, in the oxidized (at 1.0 V) and the reduced (at—0.55 V) states. The peaks correspond to the different atoms present in the samples: carbon (C) at 0.27 keV, nitrogen (N) at 0.38 keV, oxygen (O) at 0.52 keV, fluorine at 0.68 keV and sulfur (S) at 2.32 keV. The oxidized CFS-PPy/DBS material presented an increase of fluorine, oxygen and sulfur content compared to those of the reduced material indicating the incorporation of TFSI - anions during the oxidation reaction. A small amount TFSI - remained trapped in the reduced state of the CFS-PPy/DBS material, as observed before [ 38 ] using free standing PPy/DBS films. The high amount of sulfur after reduction refers to: entrapped TFSI - anions, the immobile DBS - anions in PPy and some SO 4 2- anions from the initial chemical polymerization of PPy on CFS [ 47 ]. The peaks of oxygen, fluorine and sulfur increased after the oxidation of the CFS-PPy/TF samples, indicating again the entrance of balancing TFSI - anions from the solution during the oxidation of the material. After reduction, some fluorine, related to the residual immobilized spherical triflate anions [ 48 ] (CF 3 SO 3 - ) from the PPy electropolymerization were present, as also seen previously [ 37 ]. As a partial conclusion, the EDX results indicate that the CFS-PPy/DBS and CFS-PPy/TF samples follow anion-active TFSI - exchange for charge balance during the reversible redox cycles. 3.2 Linear actuation The bundle-like fibers coated individually with PPy (as seen in Fig 1B and 1C ) are envisaged to bring closer the concept of an “artificial muscle”. To mimic the natural contraction/elongation of muscle tissue, linear actuation of the CFS-PPy/DBS and CFS-PPy/TF samples was carried out to ensure that those materials could be suitable for the envisaged soft robots and smart multifunctional applications. The aforementioned suitability was further investigated by long-term measurements, at 0.1 Hz frequency to prove the durability of the material and consistency of the response. 3.2.1 Reversible electro-chemo-mechanical changes under cyclic voltammetry Cyclic voltammetry results describe the response of the materials to closer-to-equilibrium conditions, as the driving signal is a (relatively slow) sweep rather than the abrupt polarity change of square wave potential steps. Fig 3 presents the CV (scan rate 5 mV s -1 ) driven results, with the electro-chemo-mechanical response of strain and stress in 3a and 3b, respectively. The voltammetric responses (current density vs. potential) are shown in Fig 3C . Fig 3D presents the charge density (mC cm -3 ) calculated by the integration of the cyclic voltammograms, taking into account the sweep rate. Fig 3A reveals that the samples swell/shrink by oxidation/reduction, respectively, indicating anion-driven actuation ( Eq 1 for PPy/DBS and Eq 2 for PPy/TF materials). Upon oxidation, the anions ingress into the material from the solution in order to balance the positive charges generated by electron loss on the polymer chains. The material swelling results, under constant force, in the increase of strain, up to 18% for CFS-PPy/DBS and 8.2% for CFS-PPy/TF films. Upon reduction, the material recovers the original position of the beginning of the potential cycle. To our knowledge, the results presented here represent the highest strain variation reported for any nanofiber scaffold materials. 10.1371/journal.pone.0232851.g003 Fig 3 Cyclic voltammetry (scan rate 5 mV s -1 ) of CFS-PPy/DBS (black line) and CFS-PPy/TF (red line) in LiTFSI-PC (potential range 1 V to -0.55 V against Ag/AgCl (3 M KCl) reference electrode, 4 th cycle) showing in a: strain ε; b: stress σ, c: current density j and d: charge density Q against potential E. The arrows indicate the direction of scan. The stress variations at constant length, Fig 3B , reveal a similar response for both the studied materials: 0.14 MPa for CFS-PPy/DBS and 0.12 MPa for CFS-PPy/TF, both in the range of the skeletal muscles (0.1 MPa). The reference actuator responses from free-standing films, S2A Fig , show a reversible strain variation in range of 20% for the PPy/DBS, and 8.6% for the PPy/TF films. The stress evolves, S2B Fig , in range of 0.24 MPa for PPy/DBS and 1.38 MPa for PPy/TF free standing films. The presence of a stress maximum and two crossing loops suggest the existence of some mixed ion actuation (entrance of some cations at the most cathodic potentials). Such excellent strain performance could be attributed to the underlying CFS material, as indicated in previous works [ 28 ]. Typically, conducting polymers have been deposited on inert metals such as (sputtered) gold or platinum, which can develop failures by cracking if stretched [ 49 ], reducing the conductivity up to 25 times after 20% stretching, becoming non-conductors after 30% stretching. Recently [ 29 ] it was observed that the conductivity of the CFS in aqueous solution under modified EIS measurements dropped by 50% after 16,7% stretching. The closed charge density loops in Fig 3D indicate full reversibility of the oxidation/reduction reactions inside the studied potential range: the presence of irreversible parallel oxidation or reduction reactions, i.e., solvent electrolysis, should give open Q/E loops. This confirms that the anodic/cathodic charges are used to oxidize/reduce the conducting polymer (“steady state”). The reversible redox cycles are expected to result in faradaic actuators [ 50 ]: linear variation of the strain with the reaction charge density. For comparison, the cyclic voltammetric results attained from free standing PPy/DBS and PPy/TF films are shown in S2C Fig and those for CFS-PPy/DBS and CFS-PPy/TF samples in Fig 3C . The maximum redox charge ( Fig 3D and S2D Fig ) gives the involved charge densities as: 30.4 C cm -3 for CFS-PPy/DBS, 42 C cm -3 for CFS-PPy/TF, 90.4 C cm -1 for PPy/DBS and 78.5 C cm -1 for PPy/TF. The higher densities for free-standing films are logically explained by their much higher content of active material. The Young’s modulus of conducting polymers also typically changes during reversible redox cycles, altering the response, as it becomes lower in the reduced than in the oxidized state [ 51 ]. Continues cycling/actuation also tends to cause changes. Table 2 shows the Young’s modulus attained for our oxidized materials before and after actuation cycles. 10.1371/journal.pone.0232851.t002 Table 2 Young’s Modulus of linear actuator samples in LiTFSI-PC before and after actuation cycles. Samples Young’s Modulus [kPa] Young’s Modulus [kPa] Before actuation (oxidized state) After actuation (oxidized state) PPy/DBS 980 ± 60.3 700.2 ± 50.4 PPy/TF 260 ± 16.5 222.4 ± 12.3 CFS-PPy/DBS 123.8 ± 9.8 22.7 ± 1.2 CFS-PPy/TF 55.5 ± 4.7 43.2 ± 3.3 The high value of the modulus of the PPy/DBS and PPy/TF free standing films is attributed to the significantly denser and compact structure. In addition to the obviously more fibrous structure of the CFS, the conducting polymer deposited on the CFS samples is also less compact, as the synthesis potential was higher. Whichever the studied sample, the modulus decreases after cycling in LiTFSI-PC ( Table 2 ). This drop can be related [ 52 ] to the exchange of solvent and ions, creating a dense PPy gel and the modulus decreases [ 53 ]. For CFS-PPy/DBS samples the modulus decreases up to 5 times after actuation, having a direct (positive) effect on strain, as previously found for PPy-CDC or PPy-PEO/DBS free standing films [ 54 , 55 ]. Otherwise, the PPy/DBS films operating in LiTFSI-PC ( Eq 1 ) contained un-dissociated Li + DBS - ion couples [ 38 ] that tend to precipitate, accordingly, the exchanged counterions increase the amount of solvent in the film to maintain the osmotic balance [ 32 ] during the redox cycles, thus, decreasing the modulus. 3.2.2 Square wave potentials steps and actuator life-time Three different samples of every studied material were submitted to consecutive square potential cycles involving a high oxidation/reduction charge density at different frequencies ranging between 0.0025 Hz and 0.1 Hz in order to follow the strain evolution during the actuator life-time ( S1 Table ). Fig 4A shows the applied potential cycles (dashed lines) and the corresponding strain response of the materials (CFS-PPy/DBS and CFS-PPy/TF). The mean strain values with standard deviations as a function of both, the applied frequency and the redox charge are shown in Fig 4B and 4C , respectively. 10.1371/journal.pone.0232851.g004 Fig 4 Square wave potential measurements in potential range 1 V to -0.55 V in LiTFSI-PC electrolyte showing in a: the strain ε (2 nd -3 th cycles) of CFS-PPy/DBS (black line) and CFS-PPy/TF (red line) with potential E (dashed) against time t (frequency, 0.0025 Hz). At frequencies 0.0025 Hz to 0.1 Hz, the maximum strain of CFS-PPy/DBS (black, ■) and CFS-PPy/TF (red, ★ ) against logarithmic scale of frequency are shown in (b). The obtained charge densities Q from each chronopotentiogram shown in c: strain ε against the charge density Q. The dashed lines in c represent linear fits and are shown just as visual guides. At the lowest frequency, 0.0025 Hz, corresponding to higher oxidation/reduction charge, 22% of strain variation was recorded ( Fig 4A ) for the CFS-PPy/DBS material. This high strain corroborates the above attained (18%) by cyclic voltammetry ( Fig 3A ). Creep (different material length at the beginning and at the end of the cycle) was noticeable after two consecutive cycles: 1.2% for the CFS-PPy/DBS samples and 2.5% for CFS-PPy/TF samples. Rising loads (MPa) and lower frequencies (longer time in oxidation/reduction) produce higher creeping effects [ 56 ]. Higher oxidation/reduction charges at lower frequencies with more ions exchanged per cycle increases the viscosity PPy[ 57 ] and more solvent exchange enhances the plasticization process [ 32 ], allowing increased creep. The presence of some parallel irreversible reactions can also increase the creeping effect [ 58 ]. Fig 4B and 4C present the strain evolution as a function of the applied frequency and of the redox charge density, respectively. As usual, the strain decreases with increasing frequency; however, at each frequency the strain shown by CFS-PPy/DBS was two times higher than for the CFS-PPy/TF. The charge densities were obtained at each applied frequency from the concomitant chronoamperometric (current/time) responses. The strain of every material increased linearly with the redox charge density ( Fig 4C ), as expected for any faradaic actuators [ 50 ], as the volume variation (exchange of ions and solvent) is controlled by the redox charge. Whichever the frequency, for the same redox charge density the strain variation of the CFS-PPy/DBS samples is over two times that of the CFS-PPy/TF samples. Clearly, the coupling between ion/solvent flux and polymer matrix is much stronger in the former, likely due to the structure generated by the original doping ions. The interaction of ion flux with the polymer matrix upon redox cycling must reflect in the (apparent) diffusion coefficient of the counterions through the material. Thus, the diffusion coefficients during oxidation and reduction were calculated using Eqs 3 and 4 , for CFS-PPy/TF and CFS-PPy/DBS samples with thickness of 136 μm and 125 μm, respectively. Fig 5A shows the linear dependence of the diffusion coefficients during the oxidation reaction on the applied frequency. The diffusion coefficients upon reduction against the applied frequency are shown at S3 Fig . Fig 5B presents the linear relationships between the strain rate (% s -1 ) and the diffusion coefficients during the material oxidation. 10.1371/journal.pone.0232851.g005 Fig 5 CFS-PPy/DBS (■) and CFS-PPy/TF ( ★ ) showing in a: Diffusion coefficients D ox (upon oxidation) obtained from Eqs 2 and 3 against the applied frequency f and b: the strain rate ν ox against diffusion coefficients D ox . The dashed lines represent the linear fit and shown for orientations. Both Figs agree to the electrochemically stimulated conformational-relaxation (ESCR) model [ 11 ]: at higher frequencies the average swelling/shrinking change driven by the conformational relaxation of the polymeric chains of the conducting polymer are slower giving a lower density gel structure, with concomitant higher diffusion coefficients. In parallel, higher strain rate ν ox of CFS-PPy/DBS was attained with rising experimental frequencies which correspond to, as stated in the previous sentence, higher diffusion coefficients: a linear relationship is attained between the strain rate and D. The suitability of those two materials (CFS-PPy/DBS and CFS-PPy/TF) in biomimetic structure with such high strain for applications in soft robotics, artificial muscles and multifunctional devices requires long term stability of the actuation response. Fig 6 presents the results of the strain during 1000 actuating cycles at 0.1 Hz ( S3 Table ). 10.1371/journal.pone.0232851.g006 Fig 6 Stability test: Square wave potential steps at frequency 0.1 Hz (1000 cycles) in potential range 1 V to -0.55 V in LiTFSI-PC showing in a: the strain ε of CFS-PPy/DBS (black) and CFS-PPy/TF (red) against time t and in b: the strain ε (main values with standard deviation) of CFS-PPy/DBS (■) and CFS-PPy/TF ( ★ ) against cycle number. The creep after 1000 cycles was ( Fig 6 ) 0.2% for CFS-PPy/DBS samples and 0.7% for CFS-PPy/TF samples. Of the studied materials, CFS-PPy/DBS is better suited for most applications when the strain response as well as the creep effect are considered. The strain variation per cycle decreases with the number of cycles ( Fig 6B ): 1.83% after 50 cycles and 1.75% after 1000 cycles for CFS-PPy/DBS and 1.09% after 50 cycles and 0.95% after 1000 cycles for CFS-PPy/TF. While the strain was higher for CFS-PPy/DBS, the loss of strain was lower for CFS-PPy/TF, indicating higher stability, which can be beneficial in technological applications. Overall, the CFS-PPy/DBS material with a biomimetic structure presents great potential for technological applications in soft robotics applications due to its high strain of over 20%, low creeping effect (0,2% after 1000 cycles) and long term persistence of the strain variation achieved in a cycle (-1.8% after 1000 cycles). All of these compare favorably to natural skeletal muscles, although at a lower response rate. The actuation speed needs be optimized in future studies."
} | 6,942 |
29740615 | PMC5938284 | pmc | 7,604 | {
"abstract": "NIR-responsive dynamic wrinkles with excellent reversibility and sensitivity are presented for the first time.",
"introduction": "INTRODUCTION Micro/nanoscale surface patterns that can endow materials with unique and intriguing physical, chemical, and biological properties have attracted growing scientific interest ( 1 – 9 ), with a particular focus on the exploitation of dynamic surface patterns to realize a controllable adjustment of surface properties such as optical characteristics, friction, wettability, and adhesion ( 3 , 10 – 23 ). Among numerous alternative processes for generating patterned surfaces, especially with dynamic morphology, surface wrinkles of a stiff skin bound to an elastomeric substrate have been harnessed to create reversible patterns that are responsive to external stimuli and provide unique dynamic characteristics of surface morphology and properties. Wrinkles occur to minimize the total energy of the bilayer system when the compressive strain (ε), caused by the modulus mismatch between the skin layer and the substrate induced by thermal, mechanical, or osmotic stimuli, exceeds the critical threshold (ε c ), defined by the mechanical properties of the bilayer system ( 24 – 28 ). According to linear buckling theory, the characteristic amplitude ( A ) of the sinusoidal wrinkles can be predicted on the basis of the applied strain ε in the system ( 13 ), as in Eq. 1 ln ( A 2 + h f 2 ) = ln 4 ε + ( ln 2 h f + 2 3 ln E f ¯ + 2 3 ln 3 E s ¯ ) (1) Here, A , h f , ε, and Ē represent the amplitude of the wrinkles, the thickness of the skin layer, the applied strain, and the plane-strain modulus, respectively, and the subscripts f and s refer to the skin layer and the substrate in the bilayer system. For a given thermally induced wrinkle system, the compressive strain can be estimated as ε = ( α s − α f ) × Δ T (2) where α s and α f are the linear thermal expansion coefficients for the substrate and the skin layer, respectively, and Δ T represents the temperature variation. If the parameters h f and E s ¯ are fixed, then the modulus of the top layer ( E f ¯ ) and the applied strain (ε) can be used as control parameters for the regulation of the formation and size of wrinkle patterns. By precisely regulating the modulus of the top layer ( E f ¯ ) and the applied strain (ε), a series of dynamic wrinkles with responsive morphology have been developed on the basis of bilayer systems; for example, the wrinkle pattern can be tailored reversibly through externally imposed stimuli such as wetting and dewetting of the solvent ( 4 , 29 – 32 ) and the stretch and release of prestrain ( 3 , 33 – 38 ). Seki et al . ( 39 ) and Lu et al . ( 40 ) demonstrated the light-erasable wrinkles on a poly(dimethylsiloxane) (PDMS) substrate, respectively, in which the top azobenzene-containing polymer layer could be softened and compressive stress released by the trans/cis photoisomerization of azobenzene moieties upon illumination. By regulating the modulus and cross-linking density of the skin layers via the dynamic chemistry, such as the reversible Diels-Alder reaction, photodimerization, and supramolecular chemistry, our group recently developed a facile strategy for the fabrication of multiresponsive dynamic wrinkling patterns ( 13 , 41 , 42 ). To mimic the wrinkling phenomenon of finger skin after prolonged exposure to water, Sun and co-workers ( 29 ) demonstrated three types of moisture-responsive wrinkles by tailoring the cross-link degree/gradient of the polyvinyl alcohol top layer to allow for moisture-dependent changes in the modulus and swelling degree. In these works, much attention was paid to the design and fabrication of complicated stimulus-responsive materials as the skin layer in the bilayer system to realize a dynamic patterned surface, in which the surface morphology is always dependent on physical or chemical properties of the top layers. This means that the morphology and surface composition cannot be regulated independently of each other. Here, by controlling the applied strain (ε) via near-infrared (NIR) light radiation, we demonstrated a simple and general strategy for the fabrication of NIR-responsive dynamic wrinkle patterns based on bilayer systems, in which the PDMS substrate was modified by incorporating a small amount of single-walled carbon nanotubes (CNTs), and varieties of functional polymers can serve as the top stiff layers ( Fig. 1A ). Owing to the high photon-to-thermal energy conversion efficiency and absorption ability in the NIR region, the thermal expansion of the elastic CNT-PDMS substrate can be easily tuned by the NIR irradiation, resulting in the regulation of the applied strain (ε) of the bilayer system dynamically to obtain the reversible wrinkle patterns. As a noncontacting and harmless stimulus, NIR provides an expedient and efficient approach to spatially and temporally tuning the surface features and inherently has the unique advantages of ultrarapid response, controllable operability, and region selectivity for the resulting dynamic wrinkling pattern over other stimuli such as solvents ( 4 , 29 ), temperature ( 13 ), electrical and magnetic fields ( 43 , 44 ), and mechanical force ( 3 , 35 ). This NIR-responsive dynamic wrinkle provides a facile and general approach for the fast morphology control of a functional surface on demand and may find potential applications in smart displays, dynamic gratings, and light control electronics. Fig. 1 Schematic illustration of NIR-driven dynamic wrinkle pattern fabrication. ( A ) Fabrication process of NIR-driven dynamic wrinkles. RT, room temperature. ( B ) Temperature variation of CNT-PDMS in NIR on/off switch. ( C ) Atomic force microscopy (AFM) images to test reversibility of the NIR-driven wrinkles. NIR intensity is approximately 1.5 W/cm 2 .",
"discussion": "DISCUSSION In summary, we demonstrated a novel NIR-responsive dynamic wrinkle pattern with excellent reversibility and sensitive response by using a CNT-containing PDMS substrate for bilayer systems, in which the applied strain can be regulated by NIR-induced thermal expansion of the CNT-PDMS substrate, owing to the efficient photon-to-thermal energy conversion of CNT. The erasure and generation of the wrinkles are controlled by NIR on/off switches, and various functional materials can be used as the skin layer for fabricating a smart surface for the desired function. This NIR-responsive dynamical wrinkle can be used as a dynamic platform for the realization of the dynamic light gratings, no-ink displays, and NIR-controlled electronics. We believe that our strategy can be extended to a general method to provide real-time responsive wrinkles by the introduction of various responsive materials into the elastic substrate, such as other NIR-responsive materials (for example, graphene, metal nanoparticles, organic dyes, and conjugated polymers) and electromagnetic-responsive compounds. Furthermore, the NIR-driven wrinkling strategy is expected to expand the applications to prepare the dynamic anisotropic wrinkles by exploring more versatile elastic substrate materials, for example, liquid crystalline elastomers ( 53 , 54 ). We envision that the real-time dynamic strategy for preparing NIR-responsive wrinkle patterns can be applied in situ for on-demand tuning of surface properties."
} | 1,836 |
27877628 | PMC5090589 | pmc | 7,608 | {
"abstract": "Novel low-dimensional thermoelectric (TE) materials suffer from poor mechanical reliability, which limits their applications, especially in mechanically harsh environments. Here, we propose a new concept, in which the novel, abundant, thermally stable TE-nanostructures are dispersed and then intimately embedded inside a protective, mechanically reliable tetragonal ZrO 2 (TZP) ceramic matrix with a low thermal conductivity. We also demonstrate an experimental proof-of-principle verification of our concept in reduced-graphene oxide (GO)–3 mol% Y 2 O 3 –ZrO 2 (3YSZ or 3Y-TZP) nanocomposite system. TE characterizations suggest that our protective TZP matrix does not degrade the intrinsic TE property of the reduced GO network. These preliminary results are promising and encouraging to start research on similar TZP-matrix TE-nanocomposites, which contain more effective TE-nanostructures with larger intrinsic power factors. In this regard, we propose a scalable approach for fabrication of similar dense TE-nanocomposites composed of other one-dimensional and/or two-dimensional TE-nanostructures, which involves an aqueous colloidal approach and a subsequent spark plasma sintering. These new TZP-matrix TE-nanocomposites could be used for sustainable clean power generation, especially in mechanically harsh environments with thermal/mechanical shocks and vibrations, where energy availability, reliability and durability are more important than the energy efficiency. Considering the excellent biocompatibility of TZP matrix, they could even be used inside the body to power implanted medical devices.",
"introduction": "Introduction Harvesting clean electricity from waste heat, an abundant source of energy, by using thermoelectric (TE) materials could indeed play an important role in addressing the energy crisis in the near future. The performance of TE solid is generally judged by the value of dimensionless figure of merit, ZT , which is S 2 σT / κ , where S is Seebeck coefficient or thermopower, σ is electrical conductivity, κ is thermal conductivity and T is temperature [ 1 , 2 ]. The higher the ZT , the higher the heat-electricity conversion efficiency; currently, materials with ZT around 1 could be considered as potential candidates for commercial applications in temperature ranges where they are stable. Without considering the materials price, availability and environmental issues, some prominent examples are systems of (Bi 1− x Sb x ) 2 (Se 1 − y Te y ) 3 alloys (bismuth chalcogenides) [ 3 – 6 ], Pb–Te alloys [ 7 , 8 ], Si–Ge alloys [ 9 – 11 ], phonon-glass electron-crystal systems such as partially filled skutterudites (CoSb 3 family) [ 12 – 15 ], half Heusler alloys [ 16 – 18 ], and transition metal oxides (layered cobaltites [ 19 – 22 ] and Ruddlesden–Popper phase SrTiO 3 -based perovskites in the form of (SrTiO 3 ) n (SrO) m [ 23 , 24 ], doped ZnO [ 25 , 26 ], etc). In conventional TE material systems, increasing the ZT has been a great challenge, as S , σ and κ are interrelated and could not easily be controlled independently; for instance increasing σ would generally decreases S and enhances the carrier contribution to the total κ ( κ lattice + κ carrier ) [ 1 – 26 ]. Note that S is strongly dependent on the carrier concentration and thereby σ . However, as the material size decreases approaching nanometer scales, new phenomena such as quantum-confinement effects could potentially enhance S and facilitate an independent control of S , σ and κ over a wide range of temperature for further increasing of ZT (e.g. increasing S more than decreasing σ ) [ 2 ]. In addition, by reducing the size, many interfaces are created, which could potentially scatter phonons more effectively than the electrons and therefore, effectively lower the lattice κ at the same time [ 2 ]. These possibilities attracted many researchers and started a new field of low-dimensional thermoelectricity in 1990s [ 2 ]. Now, it has been well established that nanostructures and nanostructured TE composites, compared to their normal bulk counterparts with similar compositions, could possess superior TE characteristics. Some prominent examples are 2D PbTe/Pb 1− x Eu x Te quantum-well superlattices [ 27 , 28 ], PbTe/PbSe 0.98 Te 0.02 quantum-dot superlattices [ 29 ] and Sb 2 Te 3 /Bi 2 Te 3 superlattice thin films [ 30 ], nanostructured Si–Ge bulks [ 31 ] or superlattices [ 32 , 33 ], disordered plasma-treated few-layer graphene (FL-G) films [ 34 ] and carbon nanotubes (CNTs) [ 35 ], 2D hexagonal CoO 2 in layered cobaltites [ 19 – 22 , 36 , 37 ], one-dimensional (1D) [ 38 , 39 ] and two-dimensional (2D) [ 40 ] bismuth chalcogenide nanostructures, Bi nanowires [ 41 , 42 ], 1D [ 43 , 44 ] and 2D [ 45 , 46 ] perovskite SrTiO 3 nanostructures and Ca 9 Co 12 O 28 nanowires [ 47 ]. Unfortunately, these promising low-dimensional TE systems are highly fragile and mechanically unreliable (e.g. even fracture toughness of their sintered, dense bulk counterparts is highly poor, even less than 1 MPa m 0.5 [ 48 ]), the fact that reduces their reliability especially in mechanically harsh environments. Most of them are also expensive and contain rare and environmentally hazardous elements. However, if those abundant, inexpensive and environmentally safe TE-nanostructures, such as oxides [ 36 , 37 , 43 – 47 ] and semiconducting carbon [ 34 , 35 ] could be dispersed like a three-dimensional (3D) connective network and embedded within a protective strong, tough, hard and wear-resistant ceramic host matrix having also a very low thermal conductivity, the important issue of poor mechanical reliability of these novel low-dimensional TE systems might be effectively addressed. Here, we propose our new concept, in which tetragonal ZrO 2 -based ceramics (hereafter referred to as TZP) with excellent mechanical properties and low thermal conductivities [ 49 – 54 ] are used as a host matrix to protect the novel 1D and/or 2D TE-nanostructures and their fragile networks, especially in mechanically harsh environments. In addition, we demonstrate an experimental proof-of-principle verification of our concept in reduced few-layer graphene oxide (FL-GO)–3 mol% Y 2 O 3 -stabilized TZP (3YSZ or 3Y-TZP) matrix system. Here, thermally reduced FL-GO nanosheets are considered as the thermally stable TE-nanostructures. Furthermore, we propose a facile, scalable approach for the large-scale fabrication of similar TE-nanocomposites, which involves an aqueous colloidal approach [ 55 ] and a subsequent spark plasma sintering (SPS) [ 56 , 57 ]."
} | 1,656 |
34106494 | PMC8453988 | pmc | 7,609 | {
"abstract": "Abstract Corals are experiencing unprecedented decline from climate change‐induced mass bleaching events. Dispersal not only contributes to coral reef persistence through demographic rescue but can also hinder or facilitate evolutionary adaptation. Locations of reefs that are likely to survive future warming therefore remain largely unknown, particularly within the context of both ecological and evolutionary processes across complex seascapes that differ in temperature range, strength of connectivity, network size, and other characteristics. Here, we used eco‐evolutionary simulations to examine coral adaptation to warming across reef networks in the Caribbean, the Southwest Pacific, and the Coral Triangle. We assessed the factors associated with coral persistence in multiple reef systems to understand which results are general and which are sensitive to particular geographic contexts. We found that evolution can be critical in preventing extinction and facilitating the long‐term recovery of coral communities in all regions. Furthermore, the strength of immigration to a reef (destination strength) and current sea surface temperature robustly predicted reef persistence across all reef networks and across temperature projections. However, we found higher initial coral cover, slower recovery, and more evolutionary lag in the Coral Triangle, which has a greater number of reefs and more larval settlement than the other regions. We also found the lowest projected future coral cover in the Caribbean. These findings suggest that coral reef persistence depends on ecology, evolution, and habitat network characteristics, and that, under an emissions stabilization scenario (RCP 4.5), recovery may be possible over multiple centuries.",
"introduction": "1 INTRODUCTION Rapidly increasing temperatures are threatening coral populations around the world through mass bleaching events that have increased in frequency and severity in recent decades (Hughes et al., 2018 ). Although projections of coral persistence into the future are often dire (Hoegh‐Guldberg et al., 2017 ), recent work highlights potential evolutionary mechanisms that may facilitate coral adaptation to warming waters (Bay et al., 2017 ; Kleypas et al., 2016 ). This is particularly relevant in the context of networks or metapopulations because each reef's adaptive capacity is constrained by the balance between selection and migration (Lenormand, 2002 ). Subpopulations experience selection to adapt to their local environment, yet can also receive immigrants adapted to different environments. While there is an increasing recognition for the contribution of evolution to coral persistence under future conditions (Logan et al., 2014 ; Matz et al., 2018 , 2020 ; Walsworth et al., 2019 ), there is less understanding of the interactions between evolutionary potential and reef characteristics on coral survival within regional‐scale reef networks. From a demographic perspective, larval dispersal links coral reefs within a network. Connectivity matrices describe the probabilities of viable larvae reaching one reef from another through dispersal and are typically generated from ocean circulation models (Kool et al., 2011 ; Treml et al., 2008 ; Watson et al., 2010 ) or population genetics data (Davies et al., 2015 ; Galindo et al., 2010 ; Matz et al., 2018 ). An important metric of connectivity is destination strength, which is the sum of incoming connection probabilities into a particular patch and is associated with a greater probability of reef survival (McManus et al., 2020 ). While modeling studies have explored the ecological importance of particular sites within a metapopulation (Kininmonth et al., 2019 ; Watson et al., 2011 ), few papers examine the combined ecological and evolutionary consequences of connectivity that are likely to be important across metapopulations (but see Matz et al., 2020 ). In addition, the relative importance of connectivity to coral persistence as compared to local factors such as baseline temperature and warming remains unclear. For example, bleaching records suggest that reefs that have experienced warm temperatures in the past are less likely to bleach in the future (Guest et al., 2012 ). Because temperatures are rising, coral populations in cooler conditions will likely benefit from receiving larvae that are pre‐adapted to warmer environments while relatively warm reefs are susceptible to the arrival of maladapted larvae (Norberg et al., 2012 ). In addition, temperature changes are likely to vary from one location to another (e.g., Ban et al., 2012 ). Generally, populations that experience a faster rate of environmental change are less likely to adapt (Lindsey et al., 2013 ), suggesting variation in extinction susceptibilities across reef networks. Due to evidence of thermal adaptation and heritability of heat tolerance in corals (Dixon et al., 2015 ; Dziedzic et al., 2019 ; Kirk et al., 2018 ), metrics that quantify the relative temperature of a patch and overall temperature change may be consequential determinants of individual reef persistence. In fact, in a recent modeling study of corals in the Indo‐West Pacific, both the proportion of recruits immigrating from warmer locations and the present‐day temperature were found to be useful factors in determining corals’ projected adaptive response (Matz et al., 2020 ). Therefore, from an evolutionary perspective, larval dispersal facilitates the exchange of traits across a network. Climate change is impacting reefs across the world, but the rates of temperature change (McClanahan et al., 2019 ) and the structure of dispersal networks (Wood et al., 2014 ) differ substantially across regions. While most modeling work addressing coral adaptation has focused on the Indo‐West Pacific region (Kleypas et al., 2016 ; Matz et al., 2018 , 2020 ), corals exist around the world, including throughout the Pacific and in the Caribbean (Veron, 1995 ). Comparisons among reef systems are important for understanding which results are general and which are sensitive to particular geographic contexts. Here, we implemented a dynamic eco‐evolutionary metacommunity model for years 1870–2300 on three spatially realistic reef networks: the Caribbean, Southwest Pacific (SWP), and Coral Triangle (CT). To simulate the response of a coral community to climate change, we modeled the dynamics of two competing coral types with contrasting life‐history strategies: a fast‐growing, temperature‐intolerant species (“fast coral”) and a slow‐growing, temperature‐tolerant species (“slow coral”; Baskett et al., 2014 ; Darling et al., 2012 ; Walsworth et al., 2019 ). In addition to important regional differences, we find that across all three regions, reefs with higher destination strength (larger numbers of immigrating larvae) and lower relative ocean temperatures were most likely to adapt successfully to future warming and that these metrics outperformed other potential predictors of reef persistence.",
"discussion": "4 DISCUSSION Reefs around the world are projected to experience frequent severe bleaching and mortality events during this century (Donner, 2009 ; Frieler et al., 2013 ; Logan et al., 2014 ; van Hooidonk et al., 2013 ). In this study, we implemented climate change projections across the Caribbean, Southwest Pacific, and Coral Triangle, and we explored a suite of temperature‐ and connectivity‐based reef patch characteristics to assess their relative impact on coral adaptive potential. Despite differences in dispersal and SST patterns among the regions, we find that several important general conclusions emerged. First, our model provides further evidence of corals’ capacity to evolutionarily adapt, but that such recovery would not be possible without evolution (Bay et al., 2017 ; Matz et al., 2020 ; Walsworth et al., 2019 ). Coral populations in our model collapsed with no additive genetic variance ( V = 0), and we found that the declines were less severe under more rapid evolution. Second, differences in minimum coral cover were associated with both connectivity and temperature, including the proportion of incoming larvae and relative SST, which can help inform conservation strategies designed to maintain coral cover. Lastly, we explicitly modeled the dynamics of two coral life‐history strategies and found that an initial loss of fast‐growing corals over the coming century may be offset by their faster recovery if thermal conditions stabilize. We examined whether temperature and larval connectivity characteristics were useful for explaining which reefs would persist with high cover and which would not. Analyses of past bleaching events have found that temperature‐based metrics, including mean SST, temporal variability of SST, and degree heating weeks (a measure of thermal stress) are strong predictors of past coral bleaching and mortality at specific sites (Hughes et al., 2018 ; McClanahan & Maina, 2003 ; Safaie et al., 2018 ; Sully et al., 2019 ; Welle et al., 2017 ). Studies that link larval connectivity patterns to marine population persistence typically focus on the network scale and calculate centrality metrics to identify sites which disproportionately contribute to metapopulation growth (Kininmonth et al., 2019 ; Treml & Halpin, 2012 ; Watson et al., 2011 ). Our work focused on integrating these two types of metrics with additional site‐specific connectivity measures such as destination strength (Thompson et al., 2018 ), self‐recruitment, and local retention (Burgess et al., 2014 ; Hastings & Botsford, 2006 ), as several previous studies have asserted that larval settlement and recruitment rates directly limit the local population size (Caley et al., 1996 ; Hughes, 1990 ; Menge et al., 2003 ). This comprehensive assessment not only highlighted the independent contributions of temperature and connectivity to coral persistence and adaptation but also the importance of their interactions for future reef persistence when there is potential for an evolutionary response. While evolution has a broadly positive effect on coral persistence at all sites and across all regions, variation exists among sites’ resilience to ocean warming due to differences in temperature and connectivity. We found a consistently positive effect of a reef's destination strength and a consistently negative effect of initial SST on minimum cover during warming, regardless of region or level of genetic variance. The positive effect of destination strength likely operated through the ecological effects of larval immigration, implying that the demographic benefits of connectivity outweighed the potential negative evolutionary effects of gene swamping (Lenormand, 2002 ). Furthermore, the negative effect of initial SST was likely due to warmer reefs receiving cold‐adapted larvae: as the network warmed, cold‐adapted larvae arriving in relatively warm reefs counteracted evolutionary adaptation (McManus et al., 2021 ; Norberg et al., 2012 ). Recently, Matz et al. ( 2020 ) found that pre‐warming SST and the fraction of recruits immigrating from sites that were at least 0.5℃ warmer (pr05) were strong predictors of reef persistence in the Indo‐West Pacific. Larvae that were pre‐adapted to warmer conditions strongly benefited cooler reefs, consistent with genetic theory (Norberg et al., 2012 ). Our results support some of Matz et al.’s findings: we found that initial SST and pr05 were relatively effective predictors in our model, although neither was as effective as destination strength. There are a few potential reasons for this discrepancy. Matz et al. ( 2020 ) used an individual‐based model based on forward genetic simulations, which was fundamentally different to our metapopulation approach with mean‐field local interactions, and also included fewer predictors in their statistical model. Matz et al. also explicitly included a “juvenile” coral stage where locally maladapted individuals may have experienced mortality before reproduction, whereas in our model, immigrants were immediately incorporated into the local population. Nevertheless, our study adds robust support for the importance of relative SST and the quantity and traits of incoming larvae on future coral cover, as these findings were consistent across (1) all three regions with different connectivity matrices (with different underlying assumptions) and unique SST trajectories and (2) multiple eco‐evolutionary models (this study and Matz et al., 2020 ). These ecological and evolutionary interactions highlight the importance of considering both sets of processes to understand future reef states. Previous studies also projected spatial variation in coral declines. Couce et al. ( 2013 ) implemented a statistical habitat suitability model to project global coral habitat suitability in response to ocean warming and acidification for years 2010, 2040, and 2070. They found the greatest declines in the Western Pacific Warm Pool, which corresponds to much of the Coral Triangle and northern SWP in our model where we also found marked declines in cover. The regions projected to maintain high suitability for corals in the Couce et al. model also correspond to most of the regions which maintain cover in our model (e.g., Southern Great Barrier Reef in both the CT and SWP regions, Greater Sunda Islands, South China Sea in the CT, American Samoa, and the Solomon Islands in the SWP). However, the Couce et al.’s model projects that the entire Caribbean will maintain high suitability, or even increase in suitability, while our model projects severe declines in cover throughout much of the region. Differences in our results are expected due to the imperfect correlation between habitat suitability and abundance, as the former ignores all biological processes, as well as the coarser resolution of their model inputs (1 × 1 degrees). Matz et al. ( 2020 ) projected a similar spatial distribution of declines across the Coral Triangle as seen in our model and the Couce et al. results, with the highest declines occurring in near equatorial reefs and higher maintenance of coral cover in northwestern and southeastern reefs away from the equator. However, the Matz et al.’s study projected less severe coral cover declines in both warming scenarios as compared to our model. This could be attributed to differences in the way that reproduction, dispersal and genetic variation were specified in our two models, as well as the combination of parameter values used in the simulations. Overall, our work provides additional support for several projected geographic patterns of coral persistence that have been previously reported, despite the application of vastly different approaches. Our results indicate that shifts in coral community composition in response to increasing temperatures should be expected and may be reversed during coral population recovery. In our simulations, the fast‐growing coral with a narrow temperature tolerance (with stronger strength of selection) experienced greater initial declines but also exhibited a higher capacity for adaptation relative to the slow‐growing species. Our fast‐growing coral closely resembles branching corals from the family Acroporidae (Darling et al., 2012 ). While this may imply that acroporid populations in the Caribbean can eventually recover when warming stabilizes, we note that the observed declines in real populations are primarily attributed to disease (Aronson & Precht, 2001 ), herbivore die‐offs (Lessios, 2016 ) and local stressors (Cramer et al., 2020 ), all of which we did not model, in addition to thermal stress (Hughes, 1994 ). We also do not model the possibility of range expansion in response to increases in temperature, which has been observed in the acroporid fossil record (Baird et al., 2012 ; Precht & Aronson, 2004 ; Yamano et al., 2011 ). Additionally, genomic analyses indicate that acroporids experienced a period of population decline following the Mid‐Pleistocene Transition (global cooling), and then a period of rapid diversification and population growth following the Northern Hemisphere Glaciation (global warming and sea‐level rise; Mao et al., 2018 ). While our model indicates that acroporids may be more sensitive to short‐term (years to decades) shifts in temperature than other scleractinian families, their fossil record and genome indicate that they may be poised for long‐term range expansion in a warmer climate, given their survival. Several regional differences in population dynamics were apparent in our simulations. For example, there was higher initial coral cover, slower recovery, and more evolutionary lag (a larger mismatch between coral traits and local temperature) in the Coral Triangle, which has a larger number of reefs and greater rates of potential larval recruitment. The lowest minimum coral cover occurred in the Caribbean, which had fewer reefs and high local retention of larvae. The Caribbean also experienced the longest pre‐recovery period. The Southwest Pacific had the least evolutionary lag and correspondingly recovered to near‐historical levels of coral cover by 2300. The SWP experienced the least warming on average, had the greatest variation in temperature and warming across the network, and had a higher proportion of cool sites, all of which may have contributed to the region's recovery. To our knowledge, no other study has modelled multiple regional coral networks under an eco‐evolutionary framework, and thus the regional differences suggested by our model stand to be tested. The observed regional differences in population dynamics are likely due to intrinsic differences in temperatures and dispersal among the regional networks, but may also be due, in part, to methodological differences in the models used to generate the connectivity relationships in our model (Schill et al., 2015 ; Thompson et al., 2018 ; Treml et al., 2008 ). These results suggest that future research and management should consider the unique characteristics of each region and that there is a need for additional regional comparison studies. While difficult to implement, consistent dispersal simulation approaches across regions would assist with these comparisons. Although destination strength and initial SST had consistent effects across all regions, we also found that the types of reefs most likely to survive future warming differed among regions in important ways. For example, self‐recruitment had a stronger negative association with cover in the Caribbean, and area had a stronger negative effect in the Coral Triangle. Self‐recruitment is an indication of the “openness” of a reef, or the amount of larval input from the rest of the network relative to the contribution from the reef itself. In other words, reefs with high self‐recruitment received a lower proportion of larvae from locations other than their own. The Caribbean's prevailing surface currents tend to move larvae from warm sites to cold sites or other warm sites, but rarely from cold to warm (Carrillo et al., 2015 ; Chollett et al., 2012 ). Thus, open reefs in the Caribbean generally received evolutionarily neutral or beneficial larvae and only rarely received maladapted larvae. Relatively closed reefs in this region did not experience the synergistic benefits of demographic support and beneficial gene flow from warm‐adapted larvae. Next, the stronger negative association of area with minimum cover in the Coral Triangle was likely due to the wider range of reef areas in this region, including the presence of extremely small sites that were much less abundant in other regions. Therefore, this region was more likely to contain connections between sites with a large difference in area. Because the quantity of larvae dispersing in our model scaled with both reef area and coral cover, larger sites were more likely to demographically support smaller sites than vice versa, leading to a strong association between reef size and minimum cover in the CT. Again, these results suggest that future research and management would benefit from considering the unique characteristics of each region. Evolution mitigated the impact of the environmental variation among sites in each regional network. As additive genetic variance decreased, the magnitudes of coefficients associated with all network factors increased. In other words, with reduced evolutionary capacity, the local temperature and connectivity of each site had a greater effect on its coral cover. In contrast, all sites tended to have higher cover if evolutionary capacity was high. Thus, the maintenance of genetic variation in coral networks would help support coral persistence across a range of environments. With little evolutionary potential, we can expect that well‐connected small reefs in colder microclimates are most likely to persist under warming. Our projections contained a number of important assumptions. We assumed that within‐reef coral dynamics were identical among reefs and regions, except for temperature and network connectivity. This assumption allowed us to investigate evolutionary, network, and environmental effects on coral cover, holding other characteristics constant. In reality, coral communities in different regions are composed of different species (beyond our model of fast and slow corals) that have varied responses to environmental stress (Darling et al., 2012 ). We also assumed that the corals’ thermal optima and growth rate were not correlated to other traits which affect fitness; however, the rate of adaptation seen in our model may not be possible if thermal tolerance trades‐off with other traits affecting fitness (Etterson & Shaw, 2001 ). In addition, we only tracked coral cover in two dimensions, which ignored three‐dimensional reef structural complexity that plays a prominent role in ecosystem services (Darling et al., 2019 ). Some coral communities may also exhibit ecological alternative stable states when interactions with macroalgae are included (Mumby et al., 2007 ). In this study, we did not include non‐coral species and chose to parameterize the model to ensure coexistence, rather than alternative stable states between the corals (Tekwa et al., 2020 ). While this choice allowed for outcomes that were not as sensitive to initial conditions, one interesting avenue for future investigation would be the interaction of evolution with ecological alternative stable states. Eco‐evolutionary feedbacks have been linked to alternative community compositions in lake systems (Strauss, 2014 ; Walsh et al., 2012 ) and may have similar impacts on coral reefs (Mumby et al., 2007 ). Another caveat is that the timescale of initial decline in coral cover and subsequent recovery can only be interpreted qualitatively. Our results suggest that eventual recovery is possible with evolution, but it is not possible to infer from our model when recovery will occur. That is because recovery timescales are affected by both growth rates and additive genetic variance, which are difficult to measure and may vary greatly across species and regions (but see Anderson et al., 2017 ; Carilli et al., 2010 ; D’Croz & Maté, 2004 ; Edmunds, 2005 ; Jokiel & Coles, 1977 for estimates of coral growth rates; Dziedzic et al., 2019 ; Kirk et al., 2018 ; for estimates of additive genetic variance). Lastly, we note that our results are limited to assessing the response of individual reefs to warming; the impact of any particular reef on the network is beyond the scope of this work. Based on our results, some general strategies are likely beneficial for coral conservation under warming. First, limiting greenhouse gas emissions and hence warming will facilitate coral adaptation, as demonstrated by the stark differences in coral cover between RCP4.5 and RCP8.5. Second, evolutionary potential is critical for mitigating coral loss and facilitating recovery of corals around the world, both during and after warming. Thus, policies that maintain genetic diversity are likely to have important long‐term benefits. For example, implementing protection across environmentally distinct sites can maintain relatively high additive genetic variance at the network scale by preserving populations that are locally adapted to different thermal regimes (Baums et al., 2019 ; Howells et al., 2013 ). Because higher genetic variance also leads to persistence at local scales, genotyping approaches to quantify local genetic variation can help inform conservation and restoration efforts (e.g., protecting sites with high diversity; Baums et al., 2019 ). Third, our results identify the characteristics of reefs that are likely to maintain coral cover versus those that will likely experience significant coral declines. For example, relatively cool reefs with high larval input may have a greater chance of coral cover maintenance or recovery in response to conservation measures that aim to mitigate external stressors such as reductions in local sedimentation (Bégin et al., 2016 ; Dubinsky & Stambler, 1996 ) and nutrient input (Dubinsky & Stambler, 1996 ). On the other hand, warm reefs with low larval input may benefit the most from larval supplementation (Cruz & Harrison, 2017 ) or restoration efforts (Baums et al., 2019 ; Ladd et al., 2018 ) since they are predicted to have less recovery potential overall. This finding also has implications for reef managers in terms of site selection criteria for management interventions. Managers could intentionally aim to include some cooler reefs and those with high larval settlement (resistant reefs), as well as some hotter reefs and those with low larval settlement (vulnerable reefs) within the managed network. Including a portfolio of reef types within a managed network helps to facilitate multiple means of adaptation to warming, including evolutionary and demographic rescue, in addition to local adaptation (Mumby et al., 2011 ; Walsworth et al., 2019 ). Our projections suggest that a future for corals is possible if warming is limited. Maintaining evolutionary potential and habitat connectivity are both important for the continued existence of coral populations. While we predict a sharp decline in reef cover, we also expect recovery with sufficient genetic variability under a less severe warming scenario. In this work, we linked individual reef characteristics to coral cover response in three major reef networks. Future work can build on these results to investigate how conservation strategies could harness adaptive potential across the reef network as a whole under climate change."
} | 6,673 |
28658203 | PMC5499630 | pmc | 7,611 | {
"abstract": "Single cells, as part of their evolution, acquired the ability to sense their internal and external environment, move to or away from a particular environment, the latter depending on the appropriate integration of the sensory input with motor ability. Clearly, the ability to sense stimuli must be a rapid process and one that has been selected upon for survival over long periods of time in concert with environmental challenges. Interestingly, various differing sensory inputs have their own receptors to respond to a specific stimulus. Thus, we have many mechanisms that alert a cell/tissue/organism to the fact its environment has been perturbed via a specific process (receptor) e, g., light, taste etc. However, the response component of this communication exhibits commonalities (respond, dampen the response or inhibition). Utilizing the wisdom of evolutionary trial, error and random occurrences, technologies today have focused not only on highly sensitive biosensors but specific ones for select targets, including “natural ones” as well as those considered important enough to make a sensor. The novel newly developed sensors include and are not limited to amperometric probes, e.g., nitric oxide, enzymes, chemical messengers to name a few. DNA chip sensors exist, which can detect genetic expression as well as product, e.g., protein polymorphisms. Cell-free protein synthesis can lead to membrane anchored receptors. Molecularly imprinted polymers can and will substitute for antibodies and the newer DNA based chips and DNA sequencers allow for the identification of other materials that can be found in cells and organisms. The strength and stability of substances, like graphene, provides a nano substance matrix with high selectivity and a rapid process time whereby sensor elements could be attached, functioning in real-time. These sensor technologies will allow one to explore cells and organisms in an unprecedented manner, providing many different views of the process in question. In this regard, as the ability to sense more potential stimuli and targeted entities increases, the ability to interpret the ever growing information and its patterns of expression in real-time becomes more difficult for our cognitive abilities, not only for the complexity of the underlying process but also for the data deluge provided by these technologies. The significance of big data and modeling through bioinformatics emerges because it can assemble meaning from the enormous amounts of data that, for example, will emerge from cognitive and non-cognitive sensing. Our minds have limited quantitative sensing abilities, however, given the ever increasing growth of bioinformatic potential, the sensory experience will undoubtedly grow along with meaning of pattern oriented association of the incoming information. It can easily be surmised that there will be an enhanced development of autonomous biosensors, which can be linked for pattern significance. This assemblage of inputs with the potential for outputting the information in an understandable form via appropriate integration will be the basis of computer-assisted enhanced intelligence. Thus, what began as a simple assembly of sensing- and -motor- processes and their integration, in the future, is only destined for being embellished in regard to the number of components that fit into the simple scheme that evolved millions of years ago. In short, what works is preserved, however, commonality complexity and novel assemblages of the same old components mask the origin. Biomedicine will grow within this arena of development since novel technologies will emerge to claim their momentary place in advancing the discipline. In a real sense, the burst of knowledge has the potential to save lives, make for better treatment options, pursuing precision medicine by means of more cost-effective, noninvasive and patient oriented therapies [ 1 – 3 ]."
} | 981 |
38625676 | PMC11028027 | pmc | 7,612 | {
"abstract": "ABSTRACT Poplar stands as one of the primary afforestation trees globally. We successfully generated transgenic poplar trees characterized by enhanced biomass under identical nutrient conditions, through the overexpression of the pivotal nitrogen assimilation gene, pxAlaAT3. An environmental risk assessment was conducted for investigate the potential changes in rhizosphere soil associated with these overexpressing lines (OL). The results show that acid phosphatase activity was significantly altered under ammonium in OL compared to the wild-type control (WT), and a similar difference was observed for protease under nitrate. 16SrDNA sequencing indicated no significant divergence in rhizosphere soil microbial community diversity between WT and OL. Metabolomics analysis revealed that the OL caused minimal alterations in the metabolites of the rhizosphere soil, posing no potential harm to the environment. With these findings in mind, we anticipate that overexpressed plants will not adversely impact the surrounding soil environment.",
"conclusion": "5. Conclusion This study comprehensively assessed the impact of transgenic P. × xiaohei on rhizosphere soil, examining soil chemical properties, enzymatic activity, microbial communities, and metabolites. Our findings show that the rhizosphere soil remained largely unchanged between OL and WT plants under either nitrate nitrogen or ammonium nitrogen supplementation. Comparative analysis of the inter-root metabolome revealed changes in 21 metabolites under ammonium nitrogen and 26 metabolites under nitrate nitrogen. These consisted of primary metabolites, such as organic acids and amino acids, and no harmful substances were identified. Notably, transgenic P. × xiaohei had a slight effect on the enzymatic activity of acid phosphatase under ammonium nitrogen and protease under nitrate nitrogen. In summary, transgenic P. × xiaohei had no significant impact on the chemical properties, microbial communities, or metabolites and enzymes of rhizosphere soil, and did not cause any identifiable harmful effects. However, it is crucial to further investigate whether GM P. × xiaohei in field trials yield different results and whether the ongoing growth and development of GM P. × xiaohei will have environmental repercussions.",
"introduction": "1. Introduction The widespread adoption of genetically modified (GM) crops has led to substantial economic and societal benefits, with the majority of cotton (79%) and soybean (74%) currently produced worldwide being genetically modified. 1 , 2 The cultivation of GM crops is considered a vital strategy for addressing the challenges related to food scarcity, climate change, sustainable development, and environmental conservation. However, the biosafety of GM crop cultivation and application has sparked an ongoing debate. The introduction of GM plants has raised biosafety concerns, both for human health and the environment. Early environmental risk assessments of transgenic plants primarily focused on their impact on the aboveground ecosystem components. More recently, the analysis of the effects of transgenic plant cultivation on soil has become an integral component of the comprehensive safety assessment of transgenic plants. 1 Likely due to the influence of variable biotic and abiotic factors, the impact of GM plants on soil microorganisms is still heavily debated among researchers and no consensus has been reached 3 ; existing studies have yielded conflicting outcomes. Some studies suggest that transgenic plants cause a reduction of soil microbial diversity, 3 , 4 whereas an increasing body of research has demonstrated that cultivating GM plants has either minimal or no impact on soil microbial communities. 3 , 5 , 6 Nevertheless, several reports have highlighted the negative effects of transgenic plants on soil physicochemical properties, enzymatic activity, and microbial diversity. 7–9 Given the absence of a universal standard for evaluating the influence of transgenic plants on soil parameters and microbial diversity, assessing the risk of planting transgenic plants in soil remains a challenging task. Currently, the most effective approach for assessing the outcomes of using GM crops is to employ plant- and gene-specific methodologies. 10 Poplar, a deciduous tree of the Salicaceae family, serves as a model woody plant and is one of the world’s most important forest tree species. Possessing attributes of rapid growth and robust regenerative capabilities, it occupies a pivotal role in global tree cultivation. 11 Since Parsons et al.. (1986) 12 first confirmed that poplar can undergo genetic transformation and express foreign genes, this technology has been used to enhance various important traits, including insect resistance, cold tolerance, drought resilience, salt tolerance, and wood quality. 13–16 Poplar became the most widely genetically modified woody plant globally, and multiple transgenic poplar lines have been created with outstanding traits. Studies have demonstrated the significant role of the AlaAT gene, a pivotal gene in nitrogen metabolism, in enhancing plant resistance and augmenting biomass production. 17 , 18 Overexpression of the barley AlaAT gene led to a substantial increase in grain yield and biomass in both canola 19 and rice. 20 Additionally, sugarcane exhibited improved nitrogen use efficiency under low nitrogen conditions upon overexpression of this gene. 21 Moreover, overexpression of AlaAT genes from other species in Arabidopsis thaliana has been shown to enhance nitrogen use efficiency. 22 However, it remains unclear whether overexpression of the AlaAT gene would induce changes in poplar biomass. Recently, we successfully cloned the full-length sequence of the Populus × xiaohei pivotal nitrogen assimilation gene pxAlaAT3 , coding an alanine aminotransferase. Using Agrobacterium-mediated transformation, we effectively introduced pxAlaAT3 into P. × xiaohei and obtained plants with high expression levels of the transgene. In this study, we assessed the biomass of these transgenic plants. More importantly, we evaluated the ecological risks of overexpressing the pxAlaAT3 gene in P. × xiaohei by examining its impact on rhizosphere soil supplemented with two forms of nitrogen. We grew P. × xiaohei overexpressing pxAlaAT3 and wild-type plants under controlled greenhouse conditions and analyzed the changes in soil chemistry, enzyme activity, bacterial communities, and metabolites. The results of this study will establish a crucial theoretical foundation for subsequent field experiments with transgenic P. × xiaohei and also serve as a reference for future assessment of the ecological safety of GM poplar plant lines.",
"discussion": "4. Discussion The majority of the world’s food crops consist of herbaceous plants. In contrast to these food crops, woody cash crops are perennial and have slow growth rates. These distinctions introduce novel factors to be considered in the safety assessment of GM crops. Firstly, the fact that woody plants, including poplar, typically have significantly longer flowering periods than most herbaceous crops, mitigates concerns regarding foreign gene transfer from transgenic plants. Nevertheless, cultivation of transgenic poplar may still lead to unpredictable changes to the soil, therefore requiring comprehensive scrutiny during biosafety evaluation. Secondly, woody plants have different lifecycles than the previous GM crops developed. For instance, while there is no analogous process of straw return as in GM corn, 34 woody plants lead to the accumulation and decomposition of fallen leaves. Consequently, safety assessments of GM woody plants should consider these lifecycle differences. Additionally, unlike food crops, poplar is cultivated across diverse environments and can thrive in soils supplied with either ammonium or nitrate nitrogen as nitrogen sources. 35 However, variations in the physical and chemical properties of the soil arise when different nitrogen sources are present. 36 In the experiments described here, we conducted safety assessments of a transgenic poplar line using either ammonium or nitrate nitrogen sources, laying a crucial experimental foundation for subsequent field trials of transgenic poplar. The chemical properties of soil affect soil quality and are critical indicators for assessing soil fertility. 36 However, as the cultivation of genetically modified crops expands, concerns about whether these crops might impact the surrounding soil ecology have become increasingly prominent, as changes in soil properties can affect crop growth. In our study, we found evidence that the chemical properties of rhizosphere soil can be influenced by the form of nitrogen supplied for plant growth but remain unaffected by the presence of the AlaAT3 transgene. This finding is in line with previous studies of rhizosphere soil properties in transgenic Bt cotton 37 and maize 38 cultivation. These results collectively indicate that the introduction of the AlaAT3 gene into P. × xiaohei has no discernible impact on the chemical properties of rhizosphere soil. Soil enzymes play a crucial role in various biochemical reactions involving the transformation of nitrogen, phosphorus, organic matter, and carbon within the soil. Their activities serve as valuable indicators for assessing the extent and direction of soil biotransformation. 39 These enzymes primarily originate from soil microorganism decomposition, plant root exudates, and plant and animal residues. 29 Their activity is highly susceptible to environmental factors, like climate, and specific cultivation conditions, including temperature and humidity. 40 , 41 In this study, we investigated the changes in the activities of nine enzymes within the rhizosphere soil of OL and WT greenhouse-grown plants. We observed that the activities of seven major soil functional enzymes were not significantly different between the two lines. However, when subjected to the ammonium nitrogen treatment, the activity of acid phosphatase was notably higher in the rhizosphere soil of OL than in the WT. This is of particular significance as acid phosphatase is closely associated with rhizosphere phosphorus content and phosphorus cycling efficiency, thereby promoting the mineralization of soil organophosphorus. 41 , 42 These changes in acid phosphatase activity might be attributed to alterations in the root microbial community. Conversely, soil protease activity, which plays a critical role in nitrogen mineralization and transformation, 43 was also significantly altered, but only under nitrate nitrogen supplementation, although it remains unclear why. Microorganisms play an integral role in metabolic activities involving the use of carbon and nitrogen sources. The microbial functional diversity constitutes a crucial characteristic within biological communities in soil ecosystems. 44 However, previous studies examining soil microbial communities in the roots of GM plants compared to control plants had conflicting results. For instance, bacterial community structure, abundance, and diversity were markedly different in transgenic rice and maize. 17 , 45 , 46 Additionally, a sugarcane transgenic line engineered with Ea- DREB2B led to a significantly different rhizosphere microbial community diversity compared to the WT. 47 In contrast, studies on transgenic maize expressing Hahb-4 and transgenic rice expressing CaMSRB2 only observed minor effects on root-associated bacterial communities. 48 , 49 In this study, we found no significant difference in microbial diversity indices between transgenic and non-transgenic P. × xiaohei plants. This suggests that OL plants did not have an impact on the rhizosphere soil microbial community species richness, dominance, or evenness. It is worth noting that Colombo et al. 50 suggested that plant genotype could be one of the contributing factors to changes in the root microbiome. 51 Furthermore, considering that soil properties are easily influenced by environmental factors, it is plausible that differences in environmental control between field experiments and controlled laboratory conditions may account for the varying results for the analysis of transgenic root microbiomes. The comparative analysis of the rhizosphere soil metabolome between the OL and WT revealed significant differences in 21 metabolites under ammonium treatment and 26 metabolites under nitrate treatment. It is important to note that these significantly different metabolites accounted for 7.4% and 9.1% of all detected metabolites, respectively. The majority of the detected metabolites did not have significant changes in expression. Furthermore, the classification of these significantly different metabolites showed they primarily belong to organic acids, amino acids, and other organic compound groups ( Figure 9 ). In line with previous research, these metabolites, including L-Glutamate, Uridine, Stachyose, L-Tryptophan, Argininosuccinic acid, AMP, cis-Aconitate, Succinate, L-Cystine, and Dihydrothymine, have been associated with metabolism in living organisms. 4 , 52 Importantly, these substances have no demonstrated toxic effects on environmental microorganisms or plants. Therefore, our findings suggest that transgenic P. × xiaohei have a minimal impact on metabolite composition in the rhizosphere soil. The RDA results offer some insight into which metabolites may influence the microbial population, but it remains unclear whether these metabolic differences are due to changes in microbial communities or in substances secreted by the plant roots. This topic will be a focal point for future research. This study explored the impact of transgenic P × xiaohei on rhizosphere soil, encompassing soil chemistry, soil enzymatic activity, microbial populations, and metabolites. In conclusion, we found that OT plants have limited to negligible effects on the soil environment when cultivated in controlled greenhouse conditions. The influence of transgenic plants on the rhizosphere likely depends on various additional factors. 3 , 5 , 41 , 53 Furthermore, recent studies suggest that the specific developmental stage of the tested transgenic plants may impact the soil microbial community differently. As a next step, we plan to perform extended field trials, taking into account the impact of the transgene on the soil during different seasons and plant developmental stages."
} | 3,625 |
37332941 | PMC10272320 | pmc | 7,614 | {
"abstract": "There are two major problems in the world, fuel deficiency and environmental pollution by fossil fuels. Microalgae are regarded as one of the most feasible feedstocks for the manufacturing of biofuels and are used in the degradation of fossil fuel spills. The present study was possessed to investigate the ability of green alga Chlorella vulgaris , blue-green alga Synechococcus sp, and its consortium to grow and degrade hydrocarbon such as kerosene (k) with different concentrations (0, 0.5, 1, and 1,5%), and also using algal biomasses to produce biofuel. The algal growth was estimated by optical density (O.D) at 600 nm, pigment contents such as Chlorophyll a,b carotenoid, and dry weight. The kerosene degradation was estimated by FT-IR analysis after and before the cultivation of algae and its consortium. The components of the methanol extract were determined by GC-MS spectroscopy. The results denote the best growth was determined by O.D, algae consortium with 1.5% Kerosene after ten days, meanwhile, the highest dry weight was with C. vulgaris after ten days of cultivation. The FT-IR demonstrated the algae and consortium possessed high efficacy to degrade kerosene. After 15 days of algae cultivation with 1% K, C.vulgaris produced the maximum amount of lipids (32%). The GC-MS profile of methanol extract of two algae and consortium demonstrated that Undecane was presented in high amounts, C.vulgaris (19.9%), Synechococcus sp ( 82.16%), algae consortium (79.51%), and also were presented moderate amounts of fatty acid methyl ester in Synechococcus sp. Overall, our results indicate that a consortium of algae can absorb and remove kerosene from water, and at the same time produce biofuels like biodiesel and petroleum-based fuels.",
"conclusion": "4 Conclusion This study insight into the cultivation of green alga C. vulgars, cyanobacterium Synechococcus, and its consortium in different concentrations of kerosene, and also determined the biomasses and lipid content. The mixotrophic C. vulgaris, cyanobacteria Synechococcus, and its consortium can remove Kerosene from media. C. vulgaris grown under mixotrophic conditions possessed the highest amount of dry weight and lipide content. The maximum compound presented in the methanol extract of Synechococcus and consortium of C. vulgars, and Synechococcus was Undecane. Cyclotetrasiloxane, octamethyl was the furthermost compound found in the methanol extract of C. vulgaris . The C. vulgars, Synechococcus, and its consortium can absorb, and complete the removal of alkene from surrounding media. It is possible to use algae and consortium grown under mixotrophic as feedstock to produce biofuel.",
"introduction": "1 Introduction One of the most important environmental problems is the contamination of water and soil by hydrocarbons derived from petroleum[ 1 ]. Large amounts of wastewater called produced water (PW) are created during the extraction of oil and gas. Produced water was discovered to have excessive lingering petroleum hydrocarbons, which significantly harmed the ecology[ 2 ]. Wastewater from the oil industry contains stubborn contaminants such as sulfur compounds, dissolved solids, and highly concentrated hydrocarbons that may constitute harm to the environment[ 3 ]. Insufficient water resources have made it harder to reduce water contamination and improve water quality[ 4 ]. Diesel and kerosene fuels are the maximum widely spread organic environmental pollutants[ 5 ]. All fossil fuels and minerals are depleting and nonrenewable. As a result, these resources are scarce both physically and, to a greater extent, commercially[ 6 ]. Every day, enormous amounts of petroleum products like diesel and kerosene are used as fuel to run vehicles, power industries, and heat houses[ 7 ]. Petroleum hydrocarbons, which are still a major source of energy utilized around the world, constitute a significant global environmental pollution[ 8 ]. The predicted scarcity of oil and phosphorus in the foreseeable future has induced several countries with global economies to search for fossil fuel alternatives and more efficient reservation and exploration of resources[ 9 , 10 ]. To clarify, biofuel production using microorganisms is expected to be solving various issues introduced by fossil fuels. Microbial Fuel Cells (MFCs), can generate renewable energy, and also remediate petroleum refinery wastewater[ 11 , 12 ]. Liquid fuels produced from biomass are known as biofuels, and they can be produced from fermented sugars (bioethanol) or oils (biodiesel)[ 13 ]. However, the production of biofuel can result in a conflict between food and fuel because it has a low energy content and is not compatible with the current fuel infrastructure [ 14 ]. According to Ref. [ 15 ]; Cyanobacterium appears to have few additional advantages over other microbes including fungi, yeast, and mosses because of their bigger mucilage volume with greater binding affinity, high surface area, and simple food requirements. Microalgae are highly preferred in biomass production due to their high natural accumulation of strains which reaches up to 50% of dry weight in lipids[ 16 ]. They are capable of generating various types of biofuels such as bioethanol, biodiesel, bio-oil, biomethane, bio-hydrogen, and others. Utilizing microalgae for biodiesel production has various advantages. In general, they require minimum care to grow and use contaminated water that has nutrients. They reproduce by using photosynthesis to transform solar energy into chemical energy, completing a growth cycle every few days[ 17 ]. [ 18 ]; reported microalgae may be the most promising biofuel feedstock, and it is being widely used to produce a sizeable amount of sustainable biomass that can be used as a viable agent for conversion to biodiesel. The substantial factors to consider in biodiesel production are the lipid content and fatty acid composition of every biodiesel feedstock. As a result, the microalgae species that are most convenient for biodiesel production require high lipid productivity and suitable fatty acid (FA) composition[ 19 ]. [ 20 ] assert that the production of biofuels using microalgae species that belong to the genera Chlorella, Dunaliella, Scenedesmus, Spirulina, and Chlamydomonas that contain large amounts of starch, may be considered as a valuable material for bioethanol production. An environmentally friendly sector with promising futures is the use of microalgae for the simultaneous production of biomass and wastewater purification[ 21 , 22 ]. Microalgae cultivation in wastewater, and saline water may be considered a suitable scientific approach to treat the imposed threats due to some favorable aspects like multi-functionality, genuine biological conversion competency, flexibility with growth system, wastewater accumulation, CO 2 sequestration, and a significant amount of carbohydrate-lipid-protein content[ 23 ]. Additionally, the simultaneous application of wastewater treatment and microalgae cultivation is a valuable method for biofuel production and pollution control[ 24 , 25 ]. Some types of microalgae can produce enzymes that break down dangerous organic molecules and change petroleum hydrocarbons into less toxic chemicals[ 26 ]. Naphthalene, indeno[1,2,3- c , d ]pyrene, benzo( a )pyrene (BaP), anthracene, phenanthrene, and other PAHs have all been found to be removed by several microalgae strains [ 27 ]. [ 28 ]; noticed very slow growth of Chlorella vulgaris and C. variegata at 5% of kerosene and no growth at 10%, and death within 15 and 10 days at 10 and 20% of kerosene. Chlorella vulgaris, Anabaena variabilis, Neochloris vigensis , and Desmodesmus produced 34.28%, 37.8%, 19.29%, and 50% respectively of lipid content in synthetic wastewater[ 24 ]. In terms of biofuel production, Chlorella sp. with high biomass productivity and good energy content seems to be an ideal material for biofuel production[ 21 , 29 , 30 ]. The culture conditions imposed on Chlorella vulgaris cells can increase the lipids content two or three times[ 31 ]. Because C. vulgaris has a high content of lipids, it has been used as an “algae model” by most researchers[ 32 ]. Furthermore, Synechococcus sp. Biomass was studied for bioethanol production[ 33 ]. The objectives of this work were to examine for the first time the potential of microalga C. vulgaris , and cyanobacterium Synechococcus sp each and in the consortium by volume (1:1) to grow and remove petroleum hydrocarbons such as kerosene under mixotrophic conditions. As well as investigate the ability C. vulgaris , and Synechococcus each or in combination to degrade kerosene petroleum hydrocarbons. Determine the amount of biomass and lipids content, after 15 days of incubation to possible uses as feedstock in biofuel production.",
"discussion": "3 Results and discussion 3.1 Growth assessment 3.1.1 Optical density Results in Fig. 1 demonstrate the influence of different concentrations of Kerosene (K) (0, 0.5, 1, and 1.5%) in algal growth and algae consortium with days. The results denoted that the highest growth of Synechococcus sp was obtained with 1.5% K ( Fig. 1 a). C. vulgaris cultivated with 1.5% Kerosene showed optical density at 1.15 nm at seven days of cultivation. The growth of C. kessleri was increased with days using a high concentration of crude oil 1%[ 38 ]. Kerosene (1.5%) enhanced the growth of C.vulgaris at 7 days, and the optical density was 1.15 nm ( Fig. 1 b). The maximum growth of the algal consortium was obtained on the tenth day with various concentrations (0, 0.5, 1, and 1.5%), but the best growth with obtained with 1.5% Kerosene at 10 days ( Fig. 1 c). The best growth of microalgae is when growing in mixotrophic conditions, which caused the promotion of biomass than that to grow under autotrophic conditions[ 39 ]. The results demonstrated that through ten days algae and consortium grow to accelerate and after that algae start to the death phase, that due to the metabolism of kerosene and produce toxic intermediate compounds that affect algae growth. The presence of hazardous chemicals caused by biodegradation, which have an impact on algal development, maybe the cause of the microalgae's promotion after ten days of cultivation in crude oil[ 40 ]. Fig. 1 Effects of different concentrations of Kerosene on Synechococcus sp (a), C. vulgaris (b), and its consortium(c) growth measured as optical density (600 nm). Fig. 1 3.1.2 Dry weight Results in Fig. 2 demonstrate the impact of kerosene concentrations on the algae growth represented by dry weight after 15 days of cultivation. The results show the best dry weight of algae and consortium with 1% k, and the best dry weight was with C. vulgaris followed by algae consortium and Synechococcus sp. The results demonstrate the different concentrations of kerosene had significant effects on the dry weight of Synechococcus sp. The dry weight of C. vulgaris cultivated under different concentrations had a significant impact among treatments, and also the dry weight of consortium under different concentrations had a significant effect. The results demonstrated that the dry weight of both the two algae and its consortium grown (0% K) were different from that were grown in mixotrophic conditions (0.5, 1, and 1.5 K) [ 38 ]. reported that the dry weight of Anabeana oryzae and Chlorella kessleri grew autotrophically and were near that that grows under mixotrophic conditions. Chlorella vulgaris cultivated under mixotrophic possessed high dry weight than those cultivated under photoautotrophic[ 41 , 42 ]. Fig. 2 Effect of different concentrations of Kerosene in dry weight of algae and its consortium. Fig. 2 3.1.3 Pigment determination The results obtained in Table 2 refer to the influence of different concentrations of Kerosene on Chlorophyll-a and carotenoid (μg mL −1 ) of Synechococcus sp. There are variations in Chl a and carotenoid contents in Synechococcus sp, the best chlorophyll-a contents (2.78 ± 0.01 μg mL −1 ), in Synechococcus sp., when applied 0.5% Kerosene with 10 days of incubation. The highest concentration of carotenoid was 4.15 ± 0.3 μg mL −1 when the alga was treated with 0.5% Kerosene at 10 days of cultivation [ 43 ]. reported Chl a of Synechococcus sp. PCC 7002 was cultivated under mixotrophic by the addition of 3 gm glucose/L, higher than that cultivated under autotrophic conditions. The best chlorophyll contents of Synechococcus sp that cultivated with acetate-mixotrophic cultures[ 44 ]. Table 3 reports the effects of different concentrations of Kerosene on Chlorophyll- a , Chlorophyll- b , and carotenoid (μg mL −1 ) of C. vulgaris , the results denote the best Chl a contents (2.02 μg mL −1 ) were obtained with Chlorella sp at seven days of cultivation with 1.5% Kerosene. Meanwhile, the best contents of Chl b were 0.5% followed by 1.5% Kerosene 5.6 ± 0.3, and 5.31 ± 0.56 μg mL −1 at seven days of growth respectively. And also has the best carotenoid contents of Chlorella sp at seven days of cultivation with 1.5% Kerosene (6.33 ± 1.22 μg mL −1 ). Chlorella protothecoides mixotrophic cultures produced more biomass than their autotrophic counterparts, although the latter culture accumulated more chlorophyll and carotenoids in its cells. However, the stress management technique improved carotenogenesis, enabling cellular storage of highly cited carotenoids[ 45 ]. With the large-scale growth of microalgae to create carotenoids, mixotrophy may be a promising method[ 46 ]. Table 2 Effect of different concentrations of Kerosene on Chlorophyll-a, and carotenoid (μg mL −1 ) of Synechococcus sp. Table 2 Conc., % Control 0.5 1.0 1.5 Days Chl a Car Chl a Car Chl a Car Chl a Car 3 0.822 ± 0.03f 1.97 ± 0.04j 1.31 ± 0.02h 257.5 ± 1.3a 0.20 ± 0.002b 1.39 ± 0.033d 0.44 ± 0.006cd 1.92 ± 0.07f 7 1.17 ± 0.11f 0.96 ± 0.15c 0.49 ± 0.01d 2.02 ± 0.1h 0.66 ± 0.02e 2.09 ± 2.19h 0.48 ± 0.023d 0.58 ± 0.06a 10 0.449 ± 0.07cd 1.68 ± 0.04e 2.78 ± 0.01 i 4.15 ± 0.3k 0.50 ± 0.006d 1.39 ± 0.58d 0.449 ± 0.079cd 1.96 ± 0.09 fg 14 0.331 ± 0.01bc 0.93 ± 0.03c 0.055 ± 0.002a 0.70 ± 0.1a 0.66 ± 0.046e 1.34 ± 1.02d 0.728 ± 0.011ef 1.35 ± 0.06d The impact of different concentrations of Kerosene on Chlorophyll- a , Chlorophyll- b , and carotenoid (μg mL −1 ) of C. vulgaris and Synechococcus sp consortium is demonstrated in Table 4 . The results investigate the most Chl a , Chl b , and carotenoid content obtained with 1.5% Kerosene at ten days of cultivation, 19.47, 29, and 23.23 μg mL −1 respectively [ 38 ]. reported the highest amount of carotenoid content was obtained when the consortium of C. kessleri and A. oryzae was grown with 1.0% crude oil. Table 3 Effect of different concentrations of Kerosene on Chlorophyll- a , Chlorophyll- b , and carotenoid (μg mL −1 ) of C. vulgaris . Table 3 Con% Control 0.5 1.0 1.5 Days Chl a Chl b Car Chl a Chl b Car Chl a Chl b Car Chl a Chl b Car 3 0.81 ± 0.006cd 0.76 ± 0.023abc 2.10 ± .0.25g 1.2 ± 0.13g 3.4 ± 0.04f 4.06 ± .13k 1.55 ± 0.002f 2.6 ± 0.01d 2.94 ± 0.33i 0.37 ± 0.00b 0.46 ± 0.01a 1.70 ± 0.1f 7 0.80 ± 0.098cd 1.17 ± 0.029bcd 2.13 ± 0.259h 1.52 ± 0.02h 5.6 ± 0.3g 6.91 ± 02. 1.02 ± 0.01de 2.2 ± 0.06ed 3.59 ± 0.3j 2.02 ± 0.11f 5.31 ± 0.56g 6.33 ± 1.22 m 10 1.1 ± 0.018e 1.24 ± 0.001d 1.87 ± 0.33g 1.97 ± 0.04i 6.9 ± 0.01h 4.90 ± 0.15n 0.63 ± 0.04bc 1.2 ± 0.02ed 1.31 ± 0.6d 0.56 ± 0.01bc 0.73 ± 0.01 ab 1.01 ± 0.3c 14 1.13 ± 0.01e 0.66 ± 0.01a 1.53 ± 0.32e 0.20 ± 0.05b 0.33 ± 0.06a 0.64 ± 0.11b 0.47 ± 0.04b 0.79 ± 0.02abc 1.08 ± 0.12c 0.04 ± 0.01 0.43 ± 0.01a 0.21 ± 0.05e 3.2 FT-IR spectroscopy analysis FT-IR spectroscopy was used to compare the functional groups presented in different concentrations of Kerosene and functional groups presented in culture filtrates of algae and consortium that were grown with various concentrations of Kerosene (0, 0.5,1 and 1.5%). Table 5 \n Table 5 and Fig. 3 report the different bands found in different concentrations in diluted Kerosene, FT-IR proved that there are five bands in 0.5% Kerosene at Wavenumbers 3446,2375,1638,1091 and 632 cm −1 which represent the following active groups O–H, CO 2 asymmetric stretching, C \n \n\n<svg xmlns=\"http://www.w3.org/2000/svg\" version=\"1.0\" width=\"20.666667pt\" height=\"16.000000pt\" viewBox=\"0 0 20.666667 16.000000\" preserveAspectRatio=\"xMidYMid meet\"><metadata>\nCreated by potrace 1.16, written by Peter Selinger 2001-2019\n</metadata><g transform=\"translate(1.000000,15.000000) scale(0.019444,-0.019444)\" fill=\"currentColor\" stroke=\"none\"><path d=\"M0 440 l0 -40 480 0 480 0 0 40 0 40 -480 0 -480 0 0 -40z M0 280 l0 -40 480 0 480 0 0 40 0 40 -480 0 -480 0 0 -40z\"/></g></svg>\n\n C double bonds, C–O single bond and [OH] bonding respectively ( Fig. 3 a). The number of bands present in 1% Kerosene is 7 bands such as 3448, 2372, 1637, 1468,1387, 665, and 620 cm −1 , these bands are slightly modified from the 0.5% Kerosene ( Fig. 3 b). In 1.5% Kerosene, 9 bands are present, the two different bands are 3591 and 3549 cm −1 , which represent O–H and H–O •H., the change of bands number and small modification may be due to the increase in mixing between BG11 medium and Kerosene ( Fig. 3 c). Table 4 Effect of different concentrations of Kerosene on Chlorophyll- a , Chlorophyll- b , and carotenoid (μg mL −1 ) of C. vulgaris and Syenchococcus sp consortium. Table 4 Conc., % Control 0.5 1.0 1.5 Days Chl a Chl b Car Chl a Chl b Car Chl a Chl b Car Chl a Chl b Car 3 0.51 ± 0.01b 0.52 ± 0.00a 1.76 ± 0.1a 0.46 ± 0.00b 0.74 ± 0.01a 1.89 ± 0.06a 1.59 ± 0.01e 2.5 ± 0.02d 1.65 ± 0.08a 0.42 ± 0.015b 0.59 ± 0.22a 1.82 ± 0.2. a 7 0.44 ± 0.07b 0.55 ± 0.07a 1.68 ± 0.04a 0.16 ± 0.00a 0.51 ± 0.01a 1.28 ± 0.10a 0.95 ± 0.04c 1.3 ± 0.04bc 0.91 ± 0.06a 2.8 ± 0.086f 8.95 ± 0.11f 11.34 ± 0.9b 10 0.48 ± 0.01b 1.72 ± 0.07c 2.21 ± 0.11a 1.13 ± 0.03d 2.38 ± 0.05d 2.19 ± 0.2a 5.2 ± 0.13h 11.9 ± 0.05g 6.99 ± 0.2a 19.47 ± 0.053i 29 ± 0.46h 23.23 ± 22a 14 0.47 ± 0.02b 1.21 ± 0.02b 2.21 ± 0.2a 0.53 ± 0.01b 0.74 ± 0.02a 1.50 ± 0.08a 0.44 ± 0.02b 0.37 ± 0.02a 0.30 ± 0.03a 3.96 ± 0.017g 7.1 ± 0.021e 0.5 ± 0.08a Fig. 3 FT-IR spectroscopy analysis of Kerosene 0.5,(a), 1 (b) and 1.5(c) %. Fig. 3 The results obtained in Supplementary Fig. S1 and Table 6 represent the FTIR spectroscopy analysis of culture media containing different concentrations of Kerosene (0, 0.5, 1, and 1.5) after 15 days of cultivation of C. vulgaris , Synechococcus, and consortium ( Supplementary Fig. S1 \n C. vulgaris (0, 0.5, 1, and 1.5) (S1a,b,c, and d), Sneycoccocus (0, 0.5, 1, and 1.5) (S1e,f,g, and h), consortium (0, 0.5, 1, and 1.5), (i,j,k, and m)). The results denote there were many active groups were obtained, the active group ν (NH) and ν (OH) were obtained at 3902 cm −1 was found in 1 and 1.5% Kerosene with Chlorella sp, and in control of consortium, this may be obtained when C. vulgaris cultivated in stress conditions. The active group at 3852 cm −1 was present in all treatments except in 1 and 1.5% Kerosene with the consortium. These groups naturally occur with algae metabolism and disappeared with high concentrations of Kerosene 1 and 1.5% with algae consortium. Also, 3838 cm −1 was not found in 1.5% k with C. vulgaris, 1, and 1.5% k with the consortium. Bands at 3820 and 3801 cm −1 represent stretching OH completely disappeared in Synechococcus. The peak at 3750 cm −1 attributed to vibrations of the free OH-group was found in control (0% K) with a small modification in Synechococcus (cyanobacteria). The peak at 3735 cm −1 was present in the culture media of algae and all treatments with slight modification after 15 days of cultivation. Band 3711 cm −1 assigned H-bonding, was found with 1%k with C. vulgaris, and consortium with treatments 0, 1and 1.5% K. Band at 3675 cm −1 was present only in consortium control. Peak 3648 cm −1 was found in control and all treatments except 0.5% k with C . vulgaris . Band 3347 cm −1 represents OH symmetric and asymmetric stretching are present in control and all treatments with small modification except 1.5% K with C . vulgaris. Bands 2131 and 2119 cm −1 revealed to CO, approximately present in all treatments and control. The band at 1771 cm −1 related to COOH protonated groups was present only with 1% K with the consortium. Band 1733 cm −1 is present in all treatments and control of consortium, meanwhile absent with Syenchococcus (cyanobacteria). Bands at 1716 revealed C–H bending, which was present only with C. vulgaris and algae consortium with 1% K, which may be related to algae metabolism with Kerosene. The band at 1646 cm −1 represented OH groups was presented in all treatments and control with some modification. The band at 1640 cm −1 was detected with C. vulgaris., control, 0.5% K with Synechococcus and 1 and 1.5% K with algae consortium. Bands 1558 cm −1 presented in all treatments except 0.5% K with C. vulgaris and Synechococcus . Bands at 1540 cm −1 were presented in all treatments except with 0.5% K with Synechococcus and algae consortium. The band at 1507 cm −1 was presented in all treatments and control. Bands at 1489 cm −1 revealed to NH, were presented in all control, and all treatments of consortium. The band at 1472 cm −1 did not present only with 0.5% k and Synechococcus. The band at 1457 cm −1 revealed to C–H was present in all treatments except 0.5% K with algae consortium. Bands at 1418 cm −1 revealed Lipids, α-methylene CH 2 scissoring band detected in the control and all treatments of algae consortium, and not detected with control and treatments of Synechococcus. The results obtained in Table 4 denote the bands obtained in different concentrations of kerosene at 3591, 3549, 3446, 3303, 2375, 2091, 1638, 1468, 1387, 1091, 665, and 632 cm −1 that were completely absent in treatments with C. vulgaris, Synechococcus and its consortium, that denote to complete degradation of kerosene. Rhodococcus , Bacillus , and Aerobacter species used kerosene as the sole carbon source of energy[ 47 ]. Achromobacter, Alcaligenes, and Cupriavidus decomposed 1% kerosene, which showed that aromatic fractions deteriorated more quickly than aliphatic fractions[ 48 ]. Through its mixotrophy, C. vulgaris . might effectively use petroleum hydrocarbons as a source of carbon [ 49 ]. By using the hydrocarbon present in oil field formation water as a source of carbon, C. vulgaris BS1 may cultivate[ 50 ]. Table 5 FT-IR spectroscopy analysis of different concentrations of Kerosene. Table 5 Wavenumber cm −1 0.5 1 1.5 Active groups References 3591 ND ND D O–H [ 51 ] 3549 ND ND D H–O •H [ 52 ] 3446 D +2 −2 Stretching O–H symmetric [ 53 ] 3303 ND ND D free/unbound O–H [ 54 ] 2375 D −3 +1 CO 2 asymmetric stretching [ 55 ] 2091 ND ND D C–N stretch [ 56 ] 1638 D −1 −2 C C double bonds [ 57 ] 1468 ND D ND CH 2 bending [ 58 ] 1387 ND D D C–C [ 59 ] 1091 D ND ND C–O single bond [ 60 ] 665 ND D +36 CO 2 [ 61 ] 632 D −12 ND [OH] bonding [ 62 ] 3.3 Lipid content percentage The effect of Kerosene on the lipids percentage of algae and consortium dry weight obtain in Figure (4) . The results demonstrate that C. vulgaris was grown in 1% kerosene and had the best lipids content 32%. In all treatments, C.vulgaris possessed the highest lipid contents. There were significant effects of different concentrations of kerosene on lipid contents in Syenchococcus and algae consortium. Chlorella sorokiniana accumulated up to 16.4% lipids when wasted under mixotrophic conditions[ 63 ]. High lipid content of C. vulgaris (37.6%wt) when grown in a shaker under mixotrophic conditions after 6 days of cultivation[ 64 ]. Bioelectro-stimulants evidenced efficient degradation of hydrocarbons in contaminated soils than control operation[ 65 ]. Soil microenvironment in correlation with the based bioelectrochemical system(BES) forms complex processes, providing suitable conditions for the effective treatment of petroleum refinery wastewater (PRW) [ 66 ]. Fig. 4 Effect of Kerosene concentration (0,0.5,1 and 1.5%) on lipids percentage of C vulgaris , Syenchococcus, and consortium after 15 days of growth. Fig. 4 The chemical formula of kerosene is C 12 H 26 –C 15 H 32 , and kerosene consists of n−n−alkanes, alkyl benzenes, and naphthalenes. The structure of kerosene is present in Fig. 5 . Fig. 5 Structure of kerosene. Fig. 5 The results in Table 7 demonstrate the GC-MS analysis of methanol extract C. vulgaris , Syenchococcus sp, and its consortium developed with 1% kerosene, after 15 days of cultivation. The GC-MS analysis demonstrated there were 5 compounds were found, Cyclotetrasiloxane, octamethyl 51.98%,1-Hexanol, 2-ethyl14.07%, Undecane 19.9%, 2,5-Dihydroxybenzaldehyde10.85%, and Cyclododecane 3.20%. These compounds may be related to absorbed C. vulgaris to kerosene. The GC-MS analysis of Syenchococcus sp reported there were 9 compounds, Undecane 82.16%, Octanoic acid methyl ester 10.64%, Pentadecanoic acid, 14-methyl-, ester 0.88%, Pentadecanoic acid, 13-methyl-, ester 1.77%, Hexadecanoic acid, methyl ester 0.50%, Cyclotrisiloxane, hexamethyl (1.25%), Perhydro-htx-2-one, 2-pentyl-, acetate ester(1.35%),5-(4-Nitrophenyl)-1,3,4-oxadiazole 2(5H)-one (0.35%), and 2-(1,3-Benzodioxol-5-ylmethyl)-1H- isoindole-1,3(2H)-dione (1.11%). The GC-MS analysis of methanol extract of algae consortium ( C. vulgaris + Syenchococcus sp) possessed 5, compound Cyclotetrasiloxane, octamethyl (15.69%), Undecane (79.51%),5,5″-Diethynyl-2,2':6′,2″-terpyrid(2.19%),2-(1,3-Benzodioxol-5-ylmethyl)-1H- isoindole-1,3(2H)-dione(1.43%), and 1,1,1,3,5,5,5-Heptamethyltrisiloxa ne (1.17%). Dodecamethylcyclohexasiloxane is one of the most lipophilic was found in C. vulgaris biomass when grown in wastewater effluents, that due to microalgae adsorption from wastewater effluents[ 67 ]. Decamethyl tetrasiloxane was presented in C. vulgaris biomass before and after the degradation of Disp. Orange 2RL[ 68 ]). Volatiles compounds such as1-Hexanol are produced by microalga Phormidium autumnale, when grown in heterotrophic conditions[ 69 ]. The results demonstrated that the presence of a high amount of Undecane in C.vulgaris (19.90), Syenchococcus sp (82.16), and consortium (79.51%), maybe the absorption of low molecular weight of hydrocarbon (alkene) kerosene contents. The main compounds of microalgae Tetradesmus obliquus cultivated for 15 days using biodigester effluent as nutrients were undecane (8.1% w/w) and pentadecane (10.62% w/w) [ 70 ]. The fatty acid methyl ester octanoic acid has been discovered in biodiesels produced by transesterifying a mixture of beef tallow, soybean oil, and babassu oil[ 71 ]. The main Fatty acid methyl esters found in coconut oil kerosene-like fuel are octanoic acid methyl ester[ 72 ]. 2,4-dihydroxybenzaldehyde is a natural phenol compound [ 73 ]. The usage of cyclododecane in various reaction-type power plants is extremely appropriate. Because this particular compound has a very high heat of combustion both in terms of weight and volume, it can be used to good effect in turbine and jet propulsion engines, depending on the need for fuels with extremely high energy contents. Additionally, this fuel has a “very high luminometer number,” making it even more advantageous for usage in reaction-style power plants[ 74 ]. Pandecanoic acid is converted into the methyl ester and identified as a trace element in biodiesels produced through the transesterification of mixtures of soybean oil, babassu oil, and beef tallow[ 71 ], there was a higher amount of Cyclotetrasiloxane, octamethyl in methanol extract of C. vulgaris that cultivated with 1% kerosene. Siloxanes may have been adsorbed from wastewaters and removed from the biomass samples, where they may have been used as fuel additives, cleaning/washing agents, adhesives, paints, lacquers, and varnishes, fillers, reprographic agents, process regulators, anti-set-off, and anti-adhesive agents, among other things[ 75 ]. Microgreen alga Scenedesmus obliquus can grow under mixotrophic and heterotrophic conditions using azo dye as a carbon source to produce a high lipid content and also the highest dye removal percentage [ [76] , [77] ]. (see ). Table 6 FT-IR spectroscopy analysis of culture filtrates of algae and its consortium, grown with different concentrations of Kerosene (0,0.5, 1, and 1.5) after 15 days. Table 6 Wavenumber cm −1 K% C.vulgaris Sneycoccocus Consortium Active groups References 3902 0 ND** ND D a ν (NH) and ν (OH) [ 78 ] 0.5 ND ND ND 1 D ND ND 1.5 D ND ND 3852 0 D +1 +1 O–H stretching [ 79 ] 0.5 D +1 +1 1 +1 D ND 1.5 D D ND 3838 0 D D D stretching OH - [ 80 ] 0.5 D D D 1 D D ND 1.5 ND D ND 3820 0 D ND D stretching OH - [ 80 ] 0.5 ND ND D 1 D ND ND 1.5 D ND ND 3801 0 D ND D stretching OH - [ 80 ] 0.5 ND ND D 1 ND ND D 1.5 ND ND D 3750 0 D −2 D vibrations of the free OH-group [ 81 ] 0.5 ND ND D 1 D ND ND 1.5 D ND D 3735 0 D D D stretching O single bond H bonds [ 82 ] 0.5 D D −1 1 +1 D −5 1.5 D D D 3711 0 ND ND −1 H-bonding [ 83 ] 0.5 ND ND −1 1 D ND ND 1.5 ND ND −1 3675 0 ND ND D nitrile H-bonded [ 84 ] 0.5 ND ND ND 1 ND ND ND 1.5 ND ND ND 3648 0 D D D O–H stretching [ 85 ] 0.5 ND D D 1 D D D 1.5 D D D 3347 0 D −1 +7 OH symmetric and asymmetric stretching [ 86 ] 0.5 −1 −6 +15 1 +8 −6 D 1.5 ND +7 D 2131 0 D ND ND CO [ 87 ] 0.5 ND ND +4 1 +7 −1 ND 1.5 D ND D 2119 0 ND +1 D CO [ 88 ] 0.5 D ND ND 1 ND ND D 1.5 ND D ND 1771 0 ND ND ND COOH protonated groups [ 89 ] 0.5 ND ND ND 1 ND ND D 1.5 ND ND ND 1733 0 D ND D C O stretching [ 90 ] 0.5 ND ND D 1 D ND D 1.5 ND ND D 1716 0 ND ND ND C–H bending [ 91 ] 0.5 ND ND ND 1 D ND D 1.5 ND ND ND 1646 0 D +7 +7 OH groups [ 92 ] 0.5 +6 +7 +7 1 +7 +7 +6 1.5 D +6 +6 1640 0 D ND ND C O groups in amides [ 93 ] 0.5 ND D ND 1 ND ND −4 1.5 ND ND −4 1558 0 D D D Amide II [ 94 ] 0.5 ND ND D 1 D D D 1.5 D D D 1540 0 D D D Amide II [ 95 ] 0.5 D ND ND 1 D D D 1.5 D D D 1521 0 D D D C–C aromatic compounds [ 96 ] 0.5 ND ND D 1 D D D 1.5 D D D 1507 0 D D D Skeletal vibration of aromatic rings [ 97 ] 0.5 D D D 1 D D D 1.5 D D D 1489 0 D D D NH [ 98 ] 0.5 ND ND D 1 D ND D 1.5 ND ND D 1472 0 D D D C C stretch [ 99 ] 0.5 D ND D 1 D D D 1.5 D D D 1457 0 D D D C–H [ 100 ] 0.5 D D ND 1 D D D 1.5 D D D 1418 0 D ND D Lipids, α-methylene CH 2 scissoring band [ 101 ] 0.5 ND ND D 1 D ND D 1.5 ND ND D a D – Detected, ND**- Not Detected. Table 7 GC-MS analysis of dry-weight algae and consortium methanol extracts after 15 days of cultivation. Table 7 Rt Compounds Chemical formula C. vulgaris Syenchococcus sp Consortium 6.980 Cyclotetrasiloxane, octamethyl C 8 H 24 O 4 Si 51.98 Nd a 15.69 7.612 1-Hexanol, 2-ethyl C 8 H 18 O 14.07 Nd Nd 8.912 Undecane C 11 H 24 19.90 82.16 79.51 9.394 Octanoic acid methyl ester C 9 H 18 O 2 Nd 10.64 Nd 9.896 2,5-Dihydroxybenzaldehyde C 7 H 6 O 2 10.85 Nd Nd 15.530 Cyclododecane C 12 H 24 3.20 Nd Nd 23.613 Pentadecanoic acid, 14-methyl-, ester C 17 H 34 O Nd 0.88 Nd 23.691 Pentadecanoic acid, 13-methyl-, ester C 16 H 32 O Nd 1.77 Nd 23.743 Hexadecanoic acid, methyl ester C 17 H 34 O 2 Nd 0.50 Nd 28.454 5,5″-Diethynyl-2,2':6′,2″-terpyrid C 19 H 11 N 3 Nd Nd 2.19 28.521 2-(1,3-Benzodioxol-5-ylmethyl)-1H- isoindole-1,3(2H)-dione C₁₆H₁₁NO₄ Nd Nd 1.43 28.549 Cyclotrisiloxane, hexamethyl C 6 H 18 O 3 Si 3 Nd 1.25 Nd 28.577 1,1,1,3,5,5,5-Heptamethyltrisiloxa ne C 7 H 22 O 2 Si 3 Nd Nd 1.17 28.604 Perhydro-htx-2-one, 2-pentyl-, acetate ester C 7 H 14 O 2 Nd 1.35 Nd 28.633 5-(4-Nitrophenyl)-1,3,4-oxadiazole 2(5H)-one C 9 H 7 N 3 O 3 Nd 0.35 Nd 28.916 2-(1,3-Benzodioxol-5-ylmethyl)-1H- isoindole-1,3(2H)-dione C 16 H 11 NO 4 Nd 1.11 Nd a Nd – Not detected."
} | 7,926 |
35930645 | PMC9355359 | pmc | 7,616 | {
"abstract": "Tactile perception includes the direct response of tactile corpuscles to environmental stimuli and psychological parameters associated with brain recognition. To date, several artificial haptic-based sensing techniques can accurately measure physical stimuli. However, quantifying the psychological parameters of tactile perception to achieve texture and roughness identification remains challenging. Here, we developed a smart finger with surpassed human tactile perception, which enabled accurate identification of material type and roughness through the integration of triboelectric sensing and machine learning. In principle, as each material has different capabilities to gain or lose electrons, a unique triboelectric fingerprint output will be generated when the triboelectric sensor is in contact with the measured object. The construction of a triboelectric sensor array could further eliminate interference from the environment, and the accuracy rate of material identification was as high as 96.8%. The proposed smart finger provides the possibility to impart artificial tactile perception to manipulators or prosthetics.",
"introduction": "INTRODUCTION As an important sensory function for humans in direct contact with the external environment, tactile perception originates from the response of subcutaneous tactile corpuscles to different stimuli in the environment and the brain’s recognition of signals afferent through nerve fibers. Therefore, the sense of touch not only reflects the tactile response to external physical stimuli (e.g., temperature, humidity, and pressure) but also includes a series of psychological parameters based on extraction and analysis of information by the brain, such as recognition of texture and roughness through tactile sensation. Bionic tactile sensors have attracted a great deal of attention since the 1980s, and high expectations are placed on simulating the tactile function of human skin. With the rapid development of functional materials and micro-nano processing technology, tactile sensors with high flexibility, spatial resolution, and sensitivity have been developed. Up to now, various types of physical information, including pressure ( 1 – 7 ), humidity ( 8 , 9 ), and temperature ( 2 , 7 , 10 ), have been successfully identified through the contact of various sensing elements with objects based on piezoresistive ( 1 , 2 ), capacitive ( 1 ), pyroelectric ( 10 ), and piezoelectric principles ( 11 – 14 ), which have been used in intelligent robots, medical rehabilitation, etc. ( 15 – 20 ). However, as psychosensory parameters are difficult to quantify, it remains challenging to simulate human tactile perception to determine the type and roughness of materials, which is crucial for the interaction between intelligent robots and the environment, in the context of both industrial sorting and the daily life of physically challenged people who rely on prosthetics. Many efforts have been made to develop sensors or devices capable of identifying materials based on various strategies, such as thermal conductivity, ultrasound, computer vision, etc. ( 10 , 21 – 26 ). As summarized in table S1, despite great progress in material recognition technology, it also has limitations. For example, identifying the material type by thermal conductivity has the advantages of low cost and high accuracy, but it requires long test times. Electromagnetic methods have good response speeds, but identification is limited to metals. Although computer vision has good robustness with respect to external noise, the integration of acquisition modules and algorithms is more complicated, and the types of materials that can be identified are limited. Therefore, there is an urgent need for a low-cost, high-efficiency, and widely applicable technique for tactile-like material identification. On the basis of the coupling of triboelectrification and electrostatic induction, triboelectric nanogenerators (TENGs), as proposed by Z.L.W., can convert mechanical energy into electrical signals and have been widely used as energy-harvesting and sensing devices ( 27 ), such as biosensors ( 28 , 29 ), implantable medical sensors ( 30 – 32 ), ocean energy-harvesting devices ( 33 , 34 ), and biomechanical energy-harvesting devices ( 35 – 37 ), among other applications ( 38 – 47 ). The triboelectric effect refers to the contact-induced electrification that occurs at various interfaces. The transformation process from physical contact to electricity prompted us to use TENGs as a powerful tool for tactile perception simulation. Materials differ in their ability to gain and lose electrons, and surface electron transfer occurs when two materials come into contact; thus, materials take opposite charges after physical contact ( 40 ). According to the above theory, a triboelectric series can be established in which the unique position of each material determines the capacity and efficiency of charge exchange. Therefore, the fixed detector can effectively identify the type of touched material according to different triboelectric output signals. In light of these considerations, we designed a triboelectric smart finger that surpassed human tactile perception for use in intelligent robots or artificial prosthetics ( Fig. 1A ). A sensor array composed of several typical materials in different positions in the triboelectric series was integrated into the smart finger, which could identify the type and roughness of materials based on triboelectric sensing. Moreover, machine learning–based data processing minimized environmental interference, substantially improving the identification accuracy to 96.8%. In addition, the wireless communication and display module integrated in the smart finger allowed the recognition results to be presented more intuitively. When the smart finger touched the material to be tested, the recognition information was directly projected onto the organic light-emitting diode (OLED) screen. This work quantified tactile psychological parameters through the triboelectric effect, which paves the way for a new era in modeling human tactile perception. Fig. 1. Design and structure of the smart finger. ( A ) Schematic diagram of the material identification process of the triboelectric tactile perception smart finger. ( B ) Structure of the triboelectric tactile perception smart finger, consisting of a triboelectric sensor array, data acquisition and transmission module, and display module. ( C ) Schematic diagram of the output signals of the triboelectric sensor array when the smart finger identifies different materials. a.u., arbitrary units. ( D ) Typical materials located in different positions in the triboelectric series: Electronegativity increases from right to left; conversely, electropositivity increases from left to right. ( E ) Flowchart of the interaction between the modules of the smart finger when identifying materials.",
"discussion": "DISCUSSION Here, we proposed a strategy to simulate human tactile perception and quantify tactile psychosensory parameters based on triboelectric sensing. As the ability to gain and lose electrons differs among materials, triboelectric fingerprint outputs with unique amplitudes and waveforms could be generated when the triboelectric sensor array was placed in contact with different objects. On the basis of the above principles, we developed a smart finger with transcended human tactile perception for use in prosthetics and manipulators to achieve identification of material type and roughness. With the aid of machine learning, the material recognition accuracy rate was as high as 96.8% under the premise of using only four sensors, and a variety of common materials (such as acrylic, EVA, glass, PU, PVC, silicon, and wood) could be recognized accurately. In addition, integration of the wireless transmission and display modules into the smart finger freed it from the requirement for a data cable, and the recognition results were displayed intuitively on the OLED screen. The triboelectric tactile perception smart finger has the advantages of simple fabrication, a fast response, high accuracy, wide applicability, and sensing without damaging samples. Going forward, more complex and practical applications could be achieved by building interfaces of smart fingers with robots or even humans. For example, it could help robots to check whether products meet manufacturing standards in terms of composition and surface structure or help physically challenged people who rely on prosthetics to recreate their perception of the external environment. On the other hand, further research is required to improve the flexibility, miniaturization, and multifunctionalities of the sensors. In the future, artificial intelligence chips will be integrated into smart fingers to make them “smarter” and confer the ability to process data independent of the computer. In addition, pressure, temperature, and humidity sensors will be introduced to build a combination of multimodal information. It is believed that the tactile simulation technology based on triboelectric sensing has great potential in the fields of medical rehabilitation and intelligent industry."
} | 2,297 |
36679208 | PMC9865060 | pmc | 7,617 | {
"abstract": "A novel superhydrophilic and underwater superoleophobic modified PVDF membrane for oil/water separation was fabricated through a modified blending approach. Pluronic F127 and amphiphilic copolymer P (MMA-AA) were directly blended with PVDF as a hydrophilic polymeric additive to prepare membranes via phase inversion induced by immersion precipitation. Then, the as-prepared microfiltration membranes were annealed at 160 °C for a short time and quenched to room temperature. The resultant membranes exhibited contact angles of hexane larger than 150° no matter whether in an acidic or basic environment. For 1, 2-dichloroethane droplets, the membrane surface showed a change from superoleophilic to superoleophobic under water with aqueous solutions with pH values from 2 to 13. This as-prepared membrane has good mechanical strength and can then be applied for oil and water mixture separation.",
"conclusion": "4. Conclusions Pluronic F127 and amphiphilic copolymer P(MMA-AA) as hydrophilic polymer additives were used for blending with PVDF to attain a modified membrane. Then, a superhydrophilic membrane was achieved when the as-prepared microfiltration membrane was annealed at 160 °C for a short time and quenched to room temperature. The membranes show good mechanical strength. The PVDF-F127-P(MMA-AA) membrane shows underwater superoleophobic and low oil-adhesion properties that allow for the effective separation of oil–water mixtures. It is expected to be a promising candidate for applications in industrial oil-polluted water treatments and oil spill cleanup.",
"introduction": "1. Introduction A large amount of oily wastewater is produced due to the rapid pace of industrialization, which presents an issue for the survival and development of human society [ 1 ]. Several traditional approaches are used to separate oil/water mixtures, including centrifuge and flotation and skimming [ 2 , 3 ]. However, the traditional separation technologies are energy-intensive and require complicated machinery. Thus, membrane materials have been an important separation technology over the past several decades because of their relatively simple operational process, low energy requirement, high stability and good separation efficiency [ 4 , 5 , 6 ]. Poly (vinylidebe fluoride) (PVDF), due to its excellent chemical stability, thermal stability and radiation resistance [ 7 , 8 ], has been an important microfiltration material. However, the PVDF membrane is easily fouled by organic proteins and other biomolecules, which limits its practical application in the separation process. Surface stable water hydration is generally considered as the key to its resistance to nonspecific protein adsorption [ 9 ]. Considerable work, including surface grafting [ 10 ], surface coating [ 11 ] and blending with hydrophilic polymers, has been done to prevent protein adsorption on microfiltration membrane surfaces to enhance the antifouling ability of the membrane. By comparison, the blending method is the most adapted because of its versatile controlling conditions for preparing a hydrophilic and good fouling resistance membrane [ 12 , 13 ]. Polyvinylpyrrolidone (PVP) and polyethyleneglycol (PEG) [ 14 , 15 ] are the simplest, most widely hydrophilic polymers and can be directly blended with PVDF to improve its anti-fouling property. However, the elution of these additives is unavoidable during the membrane formation and filtration process. Thus, amphiphilic copolymers [ 16 , 17 , 18 ] have recently been synthesized and used for blending with PVDF to fabricate antifouling microfiltration membranes. The hydrophilicity and fouling resistance of the PVDF membranes using the three amphiphilic polymers as modifiers were better than the membrane using PEG [ 19 ]. A novel copolymer with oppositely charged groups was prepared by Shen et al., and was blended with PVDF to resist effective protein adsorption and initial microbial adhesion [ 20 ]. Liu et al. developed a porous PVDF hollow fiber membrane in the phase process using the ampliphilic brush-like copolymer P (MMA-EGMA) as the macromolecular additive. The hollow fiber membrane had good protein fouling resistance and the flux was recovered easily by simple water washing [ 21 ]. However, there is little in the literature describing a membrane being made hydrophilic by only a blending method to separate oil /water mixture. Membranes with superoleophobic surfaces could help solve the oil fouling problem and achieve the effective separation of oil/water mixtures [ 22 , 23 ]. Normally, superoleophobic surfaces in air are very hard to attain due to the low surface tension of organic liquids [ 5 ]. Hydrophilic surfaces with low values of polymer–water interfacial energy provide stable water layers to restrain protein adsorption and oil adhesion. Membranes with underwater superoleophobicity are a possible method of separating oil/water mixtures without exhausting any external energy, using superhydrophilic and underwater superoleophobic hydrogel-coated mesh for oil/water separation [ 6 , 24 ]. Many kinds of modification methods have been developed to enhance the hydrophilicity of membranes [ 25 , 26 , 27 ]. However, there are still some limitations for the wide application of surface modification because the complicated process of polymerization is inevitable. Herein, a simple strategy through a two-step method is used to fabricate a superhydrophilic and underwater superoleophobic PVDF membrane with a hierarchically structured surface. Pluronic F127 and amphiphilic copolymer P (MMA-AA) synthesized as hydrophilic additives were blended with PVDF to attain a modified membrane. Then, the as-prepared microfiltration membranes were annealed at 160 °C for a short time and quenched to room temperature. Thus, a superhydrophilic PVDF membrane was achieved by blending with subsequent thermal treatment. In comparison with the traditional methods, such as surface coating and surface grafting, the preparation process of modified blending is very simple, time-saving and inexpensive. Moreover, the mechanical strength of the membrane after the heating treatment is higher than that of the membrane without the overheating treatment, which is important for a wide range of practical applications. This novel kind of hybrid membrane to separate oil/water mixtures has high water flux and energy-saving filtration under ultralow transmembrane pressure.",
"discussion": "3. Results and Discussion Non-solvent induced phase separation (NIPS) is a simple and convenient method to prepare porous membrane. The PVDF membrane precipitated from ethanol, as shown in Figure 1 , shows the typical symmetric structure. The cross-section presents a microporous structure composed of spherical particles. It is well known that PVDF is a semicrystalline polymer. Such a structure indicates that the precipitation process is a crystallization-dominated precipitation via nucleation and crystal growth [ 30 ]. However, it is believed that the virgin PVDF membrane shows very low tensile strength due to poor adhesion between the spherical particles from the cross-sectional structure. Thus, the tensile strength of the membrane is the first problem to be solved. Quenching is a very simple method to improve membrane tensile strength [ 31 , 32 ]. Take the case of the virgin PVDF membrane: the tensile strength of the membrane and the membrane via the heating treatment are shown in Figure 2 A. The mechanical property changes are obvious and the tensile strength of the PVDF membrane via the heating treatment is increased to 2.5 MPa, which is an important determinant for practical application. The first reason is given from the SEM analysis results. The SEM of the virgin PVDF membrane after the heating treatment is also shown in Figure 1 c,d, which is different from the untreated PVDF membrane. The surface has the typical agglomerates of interconnected bulge. The spherical particles of the cross-section become small and interconnected. The reason for the morphological change is that at a low quenching temperature the crystallization rate is fast, so more clusters are formed but their augmentation time is short; as a result, the size of the spherical clusters remains small [ 33 ]. The thickness of membranes becomes denser after the heating treatment, as shown in Figure S3 , which is another reason for the improvement of the tensile strength of the membranes. A low quenching temperature is propitious to obtaining a distinct mechanical property. The contact angle for water on the virgin PVDF membrane is above 110° and for oil it is 0° (in Figure 3 ); that is, PVDF is intrinsically hydrophobic and oleophilic due to the low surface energy of PVDF. Therefore, PVDF membranes are easily fouled because of surfactant adsorption or pore plugging by many oil droplets. The hydrophilic improvement of the membrane is the second problem solved. Blending modification is an effective method that can be applied to industrial-scale production. Thus, hydrophilic Pluronic F127 and amphiphilic copolymer P (MMA-AA) are used to blend with PVDF to enhance the surface hydrophilicity of the membranes through forming hydrogen bonds with surrounding water molecules to reconstruct a thin water layer on the membrane surface. However, it is very surprising that the novel composite membrane PVDF-F127 and PVDF-F127-P (MMA-AA) turn superhydrophilic after a simple heating treatment method, as shown in Figure 3 , and the surface wettability of the membrane will be discussed in detail below [ 34 ]. The SEM of the PVDF-F127 and PVDF-F127-P (MMA-AA) membranes after the heating treatment is shown in Figures S4 and S5 . The morphology change is analogous to the original PVDF membrane. Meanwhile, the treated PVDF-F127 and PVDF-F127-P (MMA-AA) membranes also show better tensile strength than the untreated membranes, as shown in Figure 2 B,C. The reason, as with the PVDF membrane, is that the morphology and thickness of the membranes have changed. How much can the surface wettability of the membrane have changed? The surface chemical compositions of the pristine PVDF, PVDF-F127 and PVDF-F127-P (MMA-AA) membranes and of all the membranes after the heating treatment were compared via XPS measurements and the results are shown in Figure 4 . The XPS spectra of pristine PVDF membranes and membranes after heating treatment ( Figure 4 A1–A2) both have two strong peaks at 284.8 eV and 684.7 eV, assigned to C1s and F1s, respectively. In the cases of the PVDF-F127 membrane and the PVDF-F127-P (MMA-AA) membrane after heating treatment ( Figure 4 B2–C2), a strong O1s peak is detected at 530.9 eV compared with the untreated membranes ( Figure 4 B1–C1), which is the element from the F127 and P (MMA-AA) polymer. The corresponding composition of these membrane surfaces is listed in Figure 4 D. It is also noted that the oxygen content increases sharply for the PVDF-F127 and PVDF-F127-P (MMA-AA) membranes after the heating treatment, which confirms the anchoring of the F127 and P (MMA-AA) polymers at the membrane surface [ 35 , 36 ]. The enrichment of F127 and P (MMA-AA) at the membrane surface may be due to the thermodynamic incompatibility between PVDF and the hydrophilic chains of F127 and P (MMA-AA) during the heating treatment process. The hydrophobic chains (PPO and PMMA segments) can guarantee the compatibility of PVDF with hydrophobic materials, while the hydrophilic PEO and PAA chains stretch out of the membrane surface during the heating treatment process due to the segregation impact, providing a high coverage of a hydrated polymer layer anchored by a hydrophobic backbone that is not soluble in water and entangled with the PVDF polymer [ 37 ]. The C1s core-level spectrum of the pristine PVDF membrane shows two typical peaks in Figure 5 A, one at a binding energy (BE) of 284.8 eV for the carbon bonded to hydrogen (CH 2 ) and the other at a BE of 289.2 eV for the carbon single bonder to flour (CF 2 ). Concerning the PVDF-F127 membrane, as shown in Figure 5 B, the C1s core-level spectrum can be resolved into seven representative peaks corresponding to CF 2 (289.2 eV) and CH 2 (284.8 eV) assigned to PVDF, CH (283.4 eV), C-O (285.0 eV PEG) assigned to F127. Concerning the PVDF-F127-P (MMA-AA) membrane, three other new peak components (with a BE at 287.4 eV for the COO species, at 284.1 eV for the C-COO species and at 285.2 eV for the COO-C species) have appeared in the C1s core-level spectrum ( Figure 5 C). Furthermore, the peak component area ratio for [C-COO]/[COO-C]/[COO] is about 5:3:5 according to the integral area, which is in good agreement with the theoretical ratio for the chemical structure of P (MMA-AA). Based on the above results, the surface chemical compositions of the membranes are changed by intruding hydrophilic polymers together with a simple heating treatment to attain a superhydrophilic membrane. In this section, the surface wettability of the membrane was evaluated by the contact angle measurements, as shown in Figure 6 . According to the Wenzel mode, for a hydrophilic substrate, the superhydrophilic surface can be attained by enhancing surface roughness due to the capillary effect. Analogously, an oleophilic surface will become more superoleophilic. The pristine PVDF membrane shows hydrophobic and superoleophilic properties, which are attributed to the micro/nanohierarchical rough structure arising from phase separate technology together with the high surface free energy. Thus, the pristine PVDF membrane is not suited to separate oil/water mixtures. For the PVDF-F127 membrane, the water droplet can spread out and permeates through the membrane immediately, exhibiting a superhydrophilic character, which is also due to the micro/nanohierarchical rough structure and the hydrophilic chain enrichment from F127 on the membrane surface. Figure 6 a,b show the wetting behavior of underwater oil (hexane and 1, 2-dichloroethane) on the membrane with increasing water pH. When a hexane droplet makes contact with the membrane surface, oil exhibits a high CA above 130° and the contact angles remain constant in acidic and even basic water (pH 2–12). The reason is that when the PVDF-F127 membrane is immersed in water, water is trapped into the hierarchical structure to form an oil/water/solid interface in the presence of the oil and the trapped water serves as a support to prevent the penetration of the oil droplets. However, when a 1, 2-dichloroethane droplet makes contact with the membrane surface underwater, it immediately spreads out and a contact angle of nearly 0 is observed in acidic and even basic water (pH 2–12). It is hard to explain this uncommon wetting phenomenon on the membrane surface by using the Cassie theory and Wenzel. It seems a great challenge to explain this unconventional wetting phenomenon by utilizing a strategy for tunable surface wettability through the control of the Lewis acid-base interactions at the liquid–liquid interface, through which a tunable liquid–liquid interfacial tension can be achieved [ 38 ]. The possible reason is that dichloromethane has a much greater density than water and the layer of trapped water is very thin. An oil droplet is easy to spread out on the membrane surface, so an underwater superoleophilic phenomenon is attained and the PVDF-F127 membrane is also not very suited to separate oil–water mixtures. The underwater oil contact angles on the PVDF-F127-P (MMA-AA) membrane surface as a function of the pH value in the aqueous phase are also shown in Figure 6 c,d. It is shown in Figure 6 c that the contact angles of hexane are larger than 150° no matter whether the aqueous phase is acidic or basic. The variation in the oil contact angles is in good agreement with the wetting of the PVDF-F127 membrane. For the 1, 2-dichloroethane droplet, as shown in Figure 6 d, the contact angle is 0° and keeps constant with aqueous solutions with pH values from 2 to 9, indicating the surface shows superoleophilicity. While the aqueous phase changes to basic (pH > 10), the 1, 2-dichloroethane droplet shows a spherical shape with a contact angle larger than 150°. The membrane surface displays a change from superoleophilic to superoleophobic underwater with aqueous solutions with pH values from 2 to 13. Considering the membrane surface is pH responsive, it is supposed that the surface wetting transition can be attributed to the surface chemical composition changes on the substrates. When the pH values are over 10, the membrane surface acid carboxyl groups dissociate into carboxylate ions, leading to the enhancement of hydrogen bonds between the membrane and water. In addition, with the presence of hierarchical structures, water molecules near the membrane surface region more easily form a continuous, compact and stable hydration layer, which can exert a strong repulsive force to oil trying to approach the membrane surface. Thus, it is expected that 1, 2-dichloroethane shows a macroscopic CA exceeding 150° in a basic aqueous environment. Figure 7 shows a schematic illustration of the change of the PVDF-F127-P (MMA-AA) membrane after immersion in a basic environment to present the change of the membrane surface charge. Figure 8 shows the CA of the 1, 2-dichloroethane droplets on the PVDF-F127-P (MMA-AA) membrane surface with a pH from 12 to 2. When the pH values are larger than 5, the surfaces are superoleophobic underwater with an oil CA above 150°. For the oils in an acidic aqueous environment (pH < 5), the surface shows underwater superoleophilicity. The pKa of PAA in solution is approximately 4.3–4.9. When the pH is lower than 5, the carboxyl acid groups of the PAA chains are protonated and could lead to weak hydrogen bonds forming between the acid carboxyl groups of PAA and water. The result is that the membrane is immersed in a basic environment before use and can be used to separate the oil–water mixtures at pH > 5. The oil/water separation capability of PVDF-F127-P (MMA-AA) membranes was performed as shown in Figure 9 . In the case of the PVDF-F127-P (MMA-AA) membrane, a 200 mL mixture of hexane and water, where hexane was dyed red using oil Red O, was poured onto the as-prepared membrane. As shown in Figure 9 A, the water including acidic and basic water permeated through the membrane within 3 min and oil was retained above due to the underwater superoleophobicity and low oil-adhesion properties. In addition, as shown Figure 9 B, hexane cannot permeate through the filter membrane even after 24 h, which indicates this oil-removing membrane is a good candidate in industrial oil-polluted water treatments."
} | 4,660 |
36812202 | PMC9992777 | pmc | 7,618 | {
"abstract": "Significance Besides direct interactions, many creatures utilize indirect communication via pheromone-like shared memory fields, and exhibit a rich array of behavior. Field memory usually remains for a long time, affecting many individuals, or evaporates quickly, and thus updates itself over time. Therefore, controlling and quantifying momentary contributions to global behavior in the complex natural environment is challenging. Our pheromone-based autonomous agent system contains self-propelled microswimmers and a phase-change material that physically mimics the elemental process of memory-induced collective behavior. The system allows us to study not only the dynamics under continuous tuning of pheromone interaction but also the different states of collective motion. This can provide insights into how a spatiotemporally varying field affects the activity of living things.",
"discussion": "Discussion To investigate collective motions induced by stigmergy, we developed a pheromone-based autonomous agent system combining Janus particles and a phase-change material (GST). A self-propelled Janus particle leaves a crystalline trail on GST by means of its lens heating effect. The crystallization leads to a drastic drop in electric resistance and this induces a passive ACEO flow at the interface. We could tune the passive flow by changing the depth of crystallization and the frequency of the AC field; then, we exploited this passive flow as a tunable pheromone interaction between a particle and the trail. At a low frequency, the passive flow was strong enough for Janus particles to be trapped inside their own crystalline trails, performing self-caging motion. By contrast, at a higher frequency, the passive component was suppressed and exceeded by the active component of Janus particles; therefore directional motion occurred. In the same way, the collective particles also exhibited caging behavior, forming some microcolonies consisting of several particles at low frequency. However, at a high frequency, the collective particles enhanced their trail over time, and finally executed highly ordered line-forming motions. In this study, we introduced a static pheromone-based stigmergy into our physical system. In general, however, chemical pheromones in nature have spatiotemporally varying characteristics, such as evaporation and spreading. For example, a swarm of ants utilize the evaporation of pheromone to eliminate wasteful detour paths and form a straight path between their nest and food ( 6 ). However, our result showed a path including curves and branches ( Movie S3 and Fig. 5 B ), which is because there was no evaporation; therefore, the trackless path remained attracting Janus particles all the time. In our system, the evaporating process can be implemented by the constant reamorphization that occurs with global laser irradiation with higher fluence. Regarding the spread of the pheromone, previous studies have revealed that it is useful for seeking shorter neighboring paths ( 40 ) and for avoiding traffic jamming in the path ( 41 ). To imitate the property of pheromone spreading, a microswimmer could be used that leaves chemical secretions ( 27 , 42 ). To further improve our system, realizing a switching function for the microswimmers is also necessary. It is widely known that ants switch their direction depending on whether they have food or not, and single-celled Dictyostelia discoideum switches to aggregate forming into a single fruiting body upon nutrient depletion ( 43 ). To mimic these switching behaviors, an internal state-memory should be incorporated into the microswimmers themselves, not only into the external platform. Although homogeneous control of the dynamics of the microswimmers by applying a bias field is possible, it remains difficult to demonstrate switching behavior without an internal memory. It would be promising to utilize functionalized Janus particles half-coated by soft ( 44 ) and hard ( 45 ) phase-change materials that can switch the phase to memorize the internal state. We can meet the challenge of implementing the “natural intelligence” seen in natural swarms of creatures into our system by combining such functions as evaporation, spreading, and switchability. While “cyber-physical” systems ( 46 ) have attracted great attention recently, it would also be interesting to design a computer based on natural intelligence driven in a single integrated “physical–physical” system that physically performs in-memory computing ( 47 )."
} | 1,129 |
40163742 | PMC12007882 | pmc | 7,620 | {
"abstract": "Abstract Motivation A challenging problem in microbiology is to determine nutritional requirements of microorganisms and culture them, especially for the microbial dark matter detected solely with culture-independent methods. The latter foster an increasing amount of genomic sequences that can be explored with reverse ecology approaches to raise hypotheses on the corresponding populations. Building upon genome-scale metabolic networks (GSMNs) obtained from genome annotations, metabolic models predict contextualized phenotypes using nutrient information. Results We developed the tool Seed2LP , addressing the inverse problem of predicting source nutrients, or seeds , from a GSMN and a metabolic objective. The originality of Seed2LP is its hybrid model, combining a scalable and discrete Boolean approximation of metabolic activity, with the numerically accurate flux balance analysis (FBA). Seed inference is highly customizable, with multiple search and solving modes, exploring the search space of external and internal metabolites combinations. Application to a benchmark of 107 curated GSMNs highlights the usefulness of a logic modelling method over a graph-based approach to predict seeds, and the relevance of hybrid solving to satisfy FBA constraints. Focusing on the dependency between metabolism and environment, Seed2LP is a computational support contributing to address the multifactorial challenge of culturing possibly uncultured microorganisms. Availability and implementation Seed2LP is available on https://github.com/bioasp/seed2lp .",
"introduction": "1 Introduction In the past decades, metagenomic sequencing had a profound impact on microbiology with substantial expansion of known genome collections ( Nayfach et al. 2021 , Nishimura and Yoshizawa 2022 , Zeng et al. 2022 ). While the previously widespread paradigm that only 1% of microorganisms are culturable tends to be rejected ( Martiny 2019 ), estimations state that a high proportion of archaea and bacteria remain uncultured across most biomes ( Steen et al. 2019 ). The prevalence of microbial interactions in natural environments is a strong hypothesis underlying the difficulty to culture many taxa ( Yan et al. 2023 ), and more and more studies pinpoint the role of metabolism in setting up these interactions ( Pande and Kost 2017 , Pacheco et al. 2019 ). While microbiology is essential to solve the problem of culturability, computational methods taking advantage of the availability of genomes coupled to simulation approaches can provide complementary hypotheses to tackle this issue. Computational models of metabolism enable the prediction of metabolic activity in organisms, taking into account a description of environmental conditions and additional constraints. In practice, the information related to the biochemical reactions a microbe could catalyse is abstracted in genome-scale metabolic networks (GSMNs), that are in turn used in models for simulation, such as flux balance analysis (FBA) ( Orth et al. 2010 ). GSMNs can be automatically or semi-automatically built starting from genomes ( Gu et al. 2019 ), although it is unrealistic to expect a high-quality GSMN based on a fully automatic process ( Karp et al. 2018 ): manual curation, expert knowledge and refinement are needed to reach a level of quality sufficient for quantitative simulations of the model ( Thiele and Palsson 2010 , Bernstein et al. 2021 ). As a result, it is much more difficult to model the metabolism of poorly studied organisms, that are sometimes not experimentally grown in pure culture and defined medium, and for which only a (possibly incomplete) genome is available. For these cases, quantitative models of metabolism are hardly applicable in first intention. Topological analysis of the graph structure of GSMNs and qualitative simulations are then a good trade-off to gain knowledge on possibly incomplete models ( Biggs et al. 2015 , Bosi et al. 2017 ) and improve them prior to quantitative simulations ( Bernstein et al. 2019 ). Using GSMNs to predict the growth environment of a species has previously got attention. Three categories of approaches can be distinguished: structural methods relying on the topology of the graph, reachability methods enabling a qualitative abstraction of metabolic activation and constraint-based models ensuring steady-state. In the first category, Borenstein et al. (2008) calculated the minimal subset of exogenously acquired metabolites, or seeds , using the decomposition of a directed simple GSMN graph into strongly connected components (SCC). An SCC without an incoming edge is a source component among which one seed can be identified. An implementation of these concepts was proposed in NetSeed ( Carr and Borenstein 2012 ), then in an R package for reverse ecology ( Cao et al. 2016 ), and reused in a Python implementation ( Hamilton et al. 2017 ). In the second category, Romero and Karp (2001) first introduced a notion of qualitative graph-based activation as a means to predict the set of compounds that can be produced in a GSMN, regardless of their quantity, solving a forward propagation problem, and the backtracking problem identifying precursor compounds to produce essential metabolites. The forward identification of activable pathways and producible metabolites in GSMNs was later included in the network expansion (NE) algorithm ( Ebenhöh et al. 2004 ) as a means to decipher the scope of a GSMN starting from a set of seed metabolites, i.e. available nutrients. The scope encompasses all the metabolites that can be reached from the seeds, regardless their stoichiometry in reactions. In line with this Boolean abstraction of metabolic producibility, Handorf et al. (2008) developed a greedy algorithm for the reverse scope problem, i.e. identifying precursors or seeds for a GSMN, by iteratively reducing the set of seed metabolites. A logic programming implementation using answer-set programming (ASP) of reverse scope has also been proposed by Schaub and Thiele (2009) . It must be noted that the complexity of the reverse scope problem is NP-complete even in acyclic graphs ( Nikoloski et al. 2008 , Liu et al. 2009 , Damaschke 2015 ). As an alternative, Cottret et al. (2008) and Acuña et al. (2012) provide algorithms computing precursors of a GSMN, with the originality of taking into account self-regenerating cycles, thus being less stringent than NE and the scope towards the initiation of reachability from seeds. Lastly, in the third category, constraint-based approaches involve mixed-integer linear programming (MILP) and linear programming (LP) to ensure flux steady state. The MENTO algorithm ( Zarecki et al. 2014 ) calculates minimal environments for genome-scale metabolic models, ensuring production of biomass, although no implementation is currently available. If a set of exchange reactions is pre-defined in the model, COBRApy ( Ebrahim et al. 2013 ) implements two approaches: solving an LP problem that minimizes their corresponding sum of flux, and an MILP formulation that minimizes the number of activated exchange reactions, such as in the EMAF approach ( Santos et al. 2017 ). SASITA ( Andrade et al. 2016 ) also solves an MILP problem identifying sets of precursors which enable target metabolite production from the GSMN’s hypergraph while constraining the system with the steady-state assumption. Graph-based and constraint-based methods of the literature do not ensure compound NE reachability, while reverse scope-based methods relying on NE do not guarantee steady flux in the objective reactions. Moreover, in practice, constraint-based approaches typically identify cardinal-minimal sets of seeds among pre-defined media of exchange reactions, which limits their application to highly curated GSMNs for which such reactions are identified. Our aim is to tackle these shortcomings by combining reverse scope computation and FBA, and by allowing all metabolites to be considered as potential seeds, including internal ones. Thus, the resulting seeds enable both a steady-state flux in the objective reaction and the triggering of necessary reactions for reaching the objective reaction. Moreover, by relieving the necessity to pre-determine potential reaction exchanges, we extend the applicability of these methods to less curated GSMNs, yet with a challenge on the scalability. In this paper, we propose and benchmark several logic-based solving algorithms for the inverse scope problem combined with FBA. Instead of minimizing the cardinality of the sets of identified seeds, our algorithms focus on the identification of subset-minimal sets of seeds. This offers a larger variety of solutions. For instance, if { A , B } and { B , C , D } are both subset-minimal solution sets of seeds, only the former is returned by cardinal minimization. Moreover, any non-minimal solution extends at least one subset-minimal solution. We tested the scalability and relevance of our approach on 107 high-quality GSMNs from the BiGG database ( King et al. 2016 ) demonstrating that a qualitative approach based on knowledge representation and reasoning is a good trade-off between computational efficiency and quality of the predictions. We provide a Python library, Seed2LP, that implements the solving using logic programming and permits customizing the parameters of the problem to fit the most use-cases in environment prediction from metabolic networks.",
"discussion": "4 Discussion We developed a seed detection tool, Seed2LP, relying on a Boolean approximation model of metabolic producibility, that can be combined with FBA to infer growth medium nutrients. Obtaining chemically defined or synthetic media has multiple applications in microbiology, especially for fastidious and uncultured microorganisms ( Stewart 2012 ). Microbial dark matter, identified with techniques such as metagenomics impedes the understanding of most ecosystems harbouring a wide diversity of organisms ( Mu et al. 2021 , Kapinusova et al. 2023 ), but other use cases exist, for instance in the context of endosymbiont bacteria that cannot be grown outside of their hosts ( Masson and Lemaitre 2020 ). Solving the culturability bottleneck has multiple applications, given the wide range of metabolic functions with biotechnological interest that microorganisms can provide ( Lewis et al. 2021 , Rämä and Quandt 2021 ). Systems biology and reverse ecology, through the implementation of dedicated computational models, can help addressing these objectives by suggesting necessary nutrients for growth. Seed2LP is highly flexible, allowing users to choose between different seed search methods, focusing solely on the producibility of reactants of an objective reaction, or on the reachability of all metabolites in the network. Multiple parameters enable constraining seed inference, and solving modes based on Reasoning or Hybrid NE–FBA customize further the search. The reasoning NE-based model is highly scalable and efficient, often providing a thousand solutions well before the 45 min timeout of our benchmark, all ensuring that reactants of the objective reaction are reachable. We chose the ability of models to carry flux in FBA as a validation method, an approach that is widely acknowledged in systems biology. We showed that Seed2LP Reasoning outperforms other existing methods such as graph methods (NetSeed) or alternative NE flavours ( Supplementary Material ). Even if constraint-based modelling such as FBA is independent of NE, we observe that for the majority of GSMNs in both Target and Full Network modes, at least one solution ensures a positive flux in the biomass reaction. Hybridizing NE with FBA ensures biomass production but comes with a computational cost that results in fewer solutions being generated, and a smaller solution space being explored. We demonstrate nonetheless that a first solution can be obtained within a few seconds for most GSMNs. Reasoning and Hybrid modes achieve varying level of diversity during seed enumeration, and among the Hybrid ones, Hybrid-GC div reaches the most diverse solution contents. Comparing Seed2LP Hybrid to an MILP implementation ensuring FBA highlighted the computational efficiency of the former in exploring the solution space, and the relevance of subset minimality optimization. The topology of GSMNs is very diverse and can facilitate or complicate the inference of seeds, resulting in solving modes that can be more or less efficient depending on the network. As such, there is no optimal combination of parameters suitable for any GSMN, and one may benefit from testing and comparing several of them. While the inference can be fully automatized and performed systematically on a large collection of GSMNs, Seed2LP’s flexibility aims at making it useful in practice for experimental applications. It can be used in a back-and-forth process with bench work to partly automatize metabolic modelling-based medium inference, a use case that typically requires curation ( Tejera et al. 2020 , Nev et al. 2024 ). Selecting seeds among a subset of metabolites or forbidding some molecules to be used as seeds may prove useful in such iterative process. Seed2LP is a support to find the nutrient-associated missing link among the numerous environmental factors impacting culturability: nutrients, pH, osmotic conditions, temperature and others ( Stewart 2012 ). A limitation of Seed2LP is therefore that it only considers metabolism to predict growth. Impact of molecule concentration, regulation processes or the dynamics of metabolism are additional facets whose analysis could be carried with more complex computational models, for instance in between seed inference and experimentation. From a computational standpoint, our experiments suggest that the pure Boolean constraints of NE together with non-accumulation constraints form an efficient abstraction of the complete Hybrid NE–FBA problem, with a limited false positive rate. This tends to justify the use of pure logic-based solving methods to pre-process the solution space rather than rely on hybrid solving techniques, being either logic programming combined with LP or MILP. While we show here that both NE and FBA are compatible, it has to be noted that cofactors or currency metabolites identification may be of importance for NE specifically ( Belcour et al. 2020 ), and more generally for reasoning-based or graph-based approaches. Seed2LP includes the possibility to forbid or force certain seed compounds, which can be used to consider those metabolites accordingly. Future work may investigate further discrete constraints that would make the Boolean over-approximation even more accurate, reducing the need for linear constraints checking, and alternative implementations using MILP-based technologies. While use cases presented in this paper concern individual populations, the question of seed inference can be extended to co-culture contexts ( Stewart 2012 ), where interactions among species and division of labour can impact the minimal requirements of the community ( Lewis et al. 2021 ). Seed inference in that case could answer several objectives, ranging from stabilizing or guiding the community to designing medium by taking cooperation into account or favouring it."
} | 3,844 |
34163371 | PMC8215126 | pmc | 7,623 | {
"abstract": "Coral reefs are declining worldwide due to global changes in the marine environment. The increasing frequency of massive bleaching events in the tropics is highlighting the need to better understand the stages of coral physiological responses to extreme conditions. Moreover, like many other coastal regions, coral reef ecosystems are facing additional localized anthropogenic stressors such as nutrient loading, increased turbidity, and coastal development. Different strategies have been developed to measure the health status of a damaged reef, ranging from the resolution of individual polyps to the entire coral community, but techniques for measuring coral physiology in situ are not yet widely implemented. For instance, while there are many studies of the coral holobiont response in single or limited-number multiple stressor experiments, they provide only partial insights into metabolic performance under more complex and temporally and spatially variable natural conditions. Here, we discuss the current status of coral reefs and their global and local stressors in the context of experimental techniques that measure core processes in coral metabolism (respiration, photosynthesis, and biocalcification) in situ , and their role in indicating the health status of colonies and communities. We highlight the need to improve the capability of in situ studies in order to better understand the resilience and stress response of corals under multiple global and local scale stressors.",
"introduction": "Introduction Coral reef ecosystems are hotspots of biodiversity and productivity in the ocean ( Roberts et al., 2002 ) that exceed that of tropical rainforests ( Ray, 1988 ). They provide crucial ecosystem functions and services such as providing goods for subsistence and economic fisheries, coastline protection from storms, and centers of the growing field of ecotourism ( Cesar et al., 2003 ; Knowlton et al., 2010 ; Van Zanten et al., 2014 ). As a key habitat-forming taxa, corals are critical to both reef systems and the coastal human populations that rely on them, and it is imperative to accelerate advances to ensure the longevity and survival of corals and coral reefs. Coral reefs have drastically declined worldwide in the last 30 years because of recruitment failures, reduced growth rates, and acute and chronic mortalities ( Hughes et al., 2011 , 2019 ), with only a fraction expected to survive in their current form over the next three decades in the Indo-Pacific region ( Bruno and Selig, 2007 ; Descombes et al., 2015 ). One of the most significant and widespread anthropogenic causes of this degradation is the change in climate drivers associated with the rise in atmospheric carbon dioxide (CO 2 ) and other greenhouse gases ( Goulletquer et al., 2014 ; Hannah, 2016 ). Local stressors also go hand in hand with global stressors, such as coastline erosion or development, which threaten the resilience of corals through pollution and sedimentation ( D’Angelo and Wiedenmann, 2014 ; Silbiger et al., 2018 ; Loiola et al., 2019 ; Jones et al., 2020 ). Increased energy consumption since the Industrial Revolution has led to the highest CO 2 levels recorded in the atmosphere since human evolution (>410 ppm; Dlugokencky and Tans, 2020 ). Of the multiple greenhouse gases [such as N 2 O, CH 4 , or chlorofluorocarbons (CFCs)] affecting global biogeochemical cycles, biodiversity, and human health ( Galloway et al., 2004 ; Bustamante et al., 2012 ), CO 2 has been the most relevant to marine ecology because of its dual role in marine heatwaves ( Gruber, 2011 ) and ocean acidification ( Ciais et al., 2013 ; Figure 1 ). Overall average seawater temperatures in tropical regions have increased by almost 1°C over the past 100 years and are projected to continue increasing at 1–2°C per century ( Kuffner et al., 2015 ). Increased seawater temperatures are a major contributor to coral bleaching and are considered as the limiting factor for coral survival ( Hughes et al., 2017b , 2019 ). Roughly half of the CO 2 emitted into the atmosphere dissolves into the surface ocean, reacting with water to form several dissolved inorganic components of the carbonate system ( Zeebe and Wolf-Gladrow, 2001 ) and lowering seawater pH ( Anthony et al., 2008 ). In comparison with pre-Industrial Revolution levels, seawater pH has decreased by approximately 0.1 ( Caldeira and Wickett, 2003 ), which equates to roughly 30% increase in acidity and may decrease further by 0.06 to 0.32 based on emission scenarios ( Ciais et al., 2013 ). This process of ocean acidification is particularly disruptive to marine organisms like reef-building hard corals that create calcium carbonate skeletons, increasing the energy requirements for growth and survival ( Anthony et al., 2008 ; Cohen and Holcomb, 2009 ; Eyre et al., 2014 ). Thus, corals and coral reefs may be significantly more vulnerable than previously thought when considering the combined effects of ocean acidification and warming ( Hoegh-Guldberg et al., 2007 ; Pandolfi et al., 2011 ). Figure 1 Local and global impacts affecting the nutritional energy of reef-building corals. Full lines indicate direct interactions; dotted lines indicate indirect interactions. Although climate drivers are widely recognized as dominating factors in coral loss and reef ecosystem shifts ( Hughes et al., 2017b ), localized stressors also are impacting coral health, where a survival-resilience pattern is observable in urban subtropical reefs subjected to several anthropogenic stressors ( Heery et al., 2018 ). Here, there are indications that stress-tolerant hard coral species have been selected to foster more resistant though less diverse reefs ( Darling et al., 2012 ). Impacts from eutrophication, increased turbidity, and lowered dissolved oxygen significantly affect coral metabolism, changing energy pathways and reef ecology ( Figure 1 ). A coral as a holobiont includes diversity functional, genomic, and potential epigenetics traits that regulate its ecological plasticity under an environmental change. But not all coral species showed the same response patterns under anthropogenic threats. Turbid water conditions commonly occur within inshore shallow coastal waters ( Browne et al., 2014 ), owing to the collective interactions of river runoff and the natural re-suspension of sediments (e.g., tides or storms) as well as anthropogenic activities (e.g., ship wakes, coastline modification, and storm and other sewage discharge). The adaptive responses that corals require to survive these conditions are both stressful and energetically costly ( Brown and Bythell, 2005 ), utilizing energy that otherwise would be put towards growth and reproduction. One consequence of increased turbidity is the reduction of the in situ irradiance and thereby photosynthesis, while high levels of settling sediments can hinder feeding or smother coral polyps ( Fabricius, 2005 ). The resulting decreases in photosynthetic efficiency and increases in respiration lower the daily productivity of corals [measured as the ratio of photosynthesis to respiration (P/R)]. This decreased productivity, in turn, lowers the coral nutritional energy reserves (e.g., reduced lipids content and changes in lipids class composition), which can lead to mortality ( Weber et al., 2012 ; Jones et al., 2020 ). Lower productivity also can increase coral susceptibility to infection and bleaching ( Anthony et al., 2007 ), generating community- and ecosystem-level impacts. In contrast, corals associated with urban developments are frequently exposed to acute sedimentation but appear to escape tissue mortality by better acclimation to low light conditions ( Dubinsky et al., 1984 ) and by increasing their feeding rates to offset energy deficits from photosynthesis ( Anthony and Fabricius, 2000 ). However, any increased frequency or severity of acute sedimentation contributes additional stress to corals that can be functioning near the limits of their physiological tolerances ( Bessell-Browne et al., 2017 ; Loiola et al., 2019 ; Jones et al., 2020 ). Although increased planktonic production can enhance the food supply for corals, very high photosynthetic production rates can generate hyperoxic conditions in reef waters that can cause coral damage and photorespiration ( Mass et al., 2010 ). At best, hyperoxic conditions may shift coral energy use into the production of antioxidants rather than calcification ( Wijgerde et al., 2014 ). In contrast, low oxygen concentrations also challenges coral survival, stimulating metabolic acclimation through the expression of hypoxia-inducible factors in corals ( Alderdice et al., 2021 ). There are few reports of hypoxic events and dead zones in the tropical coral reef environments, though episodic or seasonal hypoxia has been recently linked to bleaching and mortality in deeper water corals ( Altieri et al., 2017 ). The anthropogenically derived increased inputs of nutrients and organic matter in coastal regions have degraded many coral reefs, and this cultural eutrophication might exacerbate the effect of global warming on coral survival ( Silbiger et al., 2018 ; DeCarlo et al., 2020 ). The nutrient gradient affects the nutritional status of corals, in particular when the calcification rate is reduced but heterotrophy enhanced under high nutrient loading ( Sawall et al., 2011 ). Indeed, traces of nitrate pollution can be found in both hard and soft corals through the analysis of radioisotopes δ 15 N in the tissue ( Baker et al., 2011 ; Duprey et al., 2017 ) and δ 13 C as an estimate of particulate organic matter ingestion ( Baker et al., 2010 ; Conti-Jerpe et al., 2020 ). At the community level, a shift from net community calcification (NCC) to dissolution can occur under high nutrient conditions ( Silbiger et al., 2018 ), due to combination of direct and indirect responses of corals. Indeed, nutrient enrichment might negatively affect the physiological performance of coral metabolism, increase the productivity of reef macroalgae, or both, inducing a cascade of change in the coral ecosystems ( D’Angelo and Wiedenmann, 2014 ; Silbiger et al., 2018 ). Eutrophic conditions can increase the productivity of reef waters by increasing food availability (e.g., particulate matter; Fabricius, 2005 ), although macroalgae, turf, and bioeroders can inhibit competitively the coral recruitment ( D’Angelo and Wiedenmann, 2014 ). However, several factors influencing the susceptibility to eutrophication have to be included, such as hydrodynamic connectivity and location ( Fabricius, 2011 ). Even so, Sawall et al. (2011) found higher photosynthetic rates of coral endosymbionts nearshore along an anthropogenic driving inshore-offshore nutrient gradient, showing that eutrophication effects on coral may not always be negative. Gaining knowledge of the stress responses of corals and their effects on reef ecology, along with the pathways to best minimize these impacts, depends on two related tasks: understanding coral health from polyp-endosymbiont symbiosis to the community level and achieving early detection of the onset of the stress responses. The first provides the foundation for studying and developing potential mitigation and managements strategies, and the second is crucial for implementing these strategies soon enough to help minimize impacts. While most early studies of an environmental change on coral health focused on the effects of single drivers (e.g., temperature, ocean acidification, and turbidity), their interactive effects require addressing multiple stressor effects on physiological processes at the holobiont level if we are to comprehensively understand their impacts on coral communities. Some of these drivers have major effects (e.g., temperature and light), but there undoubtably are other interactions that can affect the resistance and recovery response of coral communities, factors critical for reef management and proactive preventative planning. However, our current understanding of coral stress responses is largely based on experimental manipulation studies in laboratory systems that are poor representations of their natural habitats. In situ studies, by either SCUBA or automated sensors, could provide a better understanding of local and global impacts, but only a few recent studies have undertaken the logistical complexities of studying fine-scale physiological processes of corals in situ recently ( Roth et al., 2019 ; Cyronak et al., 2020 ; Srednick et al., 2020 ). The primary objective of this review is to summarize the current strategies for quantifying aspects of coral metabolism to highlight the benefits of non-destructive methodologies. A list of recommendations is provided that would expand the efficacy of underwater studies for improving local knowledge and better understanding of how corals respond to stressors.",
"discussion": "Discussion and Conclusion We have collated and summarized here the underwater methodologies from 55 studies on coral metabolism and physiology conducted since 1991 ( Table 1 ). The current knowledge of combined effects of local and global stressors comes from a wide breadth of manipulation studies on coral responses under predicted future scenarios but limited in representing complex abiotic factors in ecosystems. Interaction among environmental variables, including temporal changes in inorganic carbon chemistry, physical parameters, or nutrient loads, is an important factor affecting the biogeochemistry of coral health ( Doo et al., 2019 ) and can play a key role in population dynamics. Though invaluable as a study tool, manipulation studies are limited in the ability to mimic important spatial-temporal patterns and interactions. On the other hand, comprehensive long-term in situ metabolic measurements still are lacking but nevertheless necessary to understand the energetics and trophodynamics of reef ecosystems. Laboratory-based studies have provided a strong foundation for understanding coral metabolism and the responses to stress, and they will continue to serve as a primary means of research under controlled conditions. However, the expanding role of in situ -based studies of coral systems is essential for extrapolating and modulating these laboratory-based findings to the temporal and spatial complexity of natural reef and environmental conditions. The advantages of in situ experimental techniques described here relate to the ability for measuring metabolic and biogeochemical properties of different benthic habitats having both simple (sediments) and complex (corals or rocky bottom) structures. Standardization of methods and replication of experimental studies would allow the simultaneous measures of coral health in different locations with the ability to compare the ecosystem functions. However, there are limitations to in situ methodologies. In the case of benthic chambers, there are restrictions to which substrate surfaces are suitable for study, and they are not well suited, even with enhanced flow capabilities, for longer-term monitoring of coral health. These restricted systems also have limited spatial footprints and thus may not adequately account for all benthic of pelagic components (e.g., macroalgae and fish). In the case of DBL approaches, limitations include the needed maintenance and fragility of microsensors, which can limit deployments to shorter duration, or under more quiescent weather conditions. Long-term continuous observations of coral biological process are critical to the assessment of responses to climate and other anthropogenic drivers and though so far lacking newly developed platforms for general oceanographic study offer this potential moving forward. In particular, autonomous platforms, such as gliders and surface vehicles, are incorporating biogeochemical sensors (i.e., pCO 2 , dissolved oxygen, pH, and chlorophyll a), able to cover spatial, vertical, and temporal observations ( Chai et al., 2020 ; Cryer et al., 2020 ). While these autonomous devices are not well suited for shallow reef environments, the advances in sensor development and operational constraints will be valuable in designing systems or autonomous robots that can provide reliable long-term assessments of the status of reef ecosystems. Indeed, autonomous measurements of light, dissolved oxygen, and alkalinity were used to estimate the NCP and NCC in order to evaluate the efficacy of coral restoration in supporting the net ecosystem metabolism ( Platz et al., 2020 ). Autonomous sensors can be used also to measure the seasonal variability in carbonate chemistry and the relationship between carbonate chemistry and biological activity of benthic organisms identifying spatial differences according to different substrates, like corals, seagrasses, or mangroves ( Meléndez et al., 2020 ). These systems are especially important in natural ocean acidification laboratories, such as hydrothermal vents, characterized by naturally high fluctuations of pH and temperature ( Kerrison et al., 2011 ; Fabricius et al., 2015 ; Torres et al., 2021 ). Co-deployment of multiple instrumentation approaches, from water chemistry and physics to coral physiology, will be needed to ensure both accuracy and logistic practicality in monitoring fluxes of O 2 , changes of pH, and other aspects of the carbonate system in coral reefs. Even with these accounted for, most studies on coral metabolic rates rely on observation of changes in DIC and alkalinity in a specific (small) area to calculate the carbon fluxes for productivity and biocalcification estimates ( Anthony et al., 2011 ); the movement of seawater flow and aspects of reef heterogeneity cannot be fully taken into account, leading to potentially biased findings that may not adequately reflect natural conditions. Moving forward then, it will be more informative by combining different scales of in situ techniques, such as the application of flow respirometry approaches to estimate carbon fluxes over a small spatial scales and different substrate type within a reef, coupled with reef-scale methods that provide an integrative assessment of the temporal variability in coral productivity and growth ( McMahon et al., 2018 )."
} | 4,570 |
37782799 | PMC10576140 | pmc | 7,624 | {
"abstract": "Significance Life on Earth has long been suggested to have originated in submarine hydrothermal systems. Although this hypothesis has been investigated by numerous prebiotic experiments, it remains a conundrum what geochemical mechanism led to accumulation of ammonia, an essential nitrogen species for abiotic synthesis of life’s building blocks. Here, we show that mackinawite, an iron sulfide mineral common in submarine hydrothermal systems, drastically enhances its adsorption capability for ammonia through electroreduction to zero-valent iron, enabling over 90% accumulation of 1 mM ammonia in 1 M NaCl at neutral pH. Given spontaneous generation of electricity widespread in present ocean hydrothermal vent environments, our demonstrated electrochemical mechanism of ammonia accumulation is likely to have been a ubiquitous geochemical phenomenon on the early seafloor.",
"discussion": "Discussion The origin of life in deep-sea hydrothermal systems is a long-standing hypothesis supported by diverse scientific disciplines, including geology ( 44 ), biology ( 45 ), and astronomy ( 46 ). However, its chemical plausibility remains a question because of the apparent difficulty in the retention and accumulation of key prebiotic components. Here, we demonstrated that partial electroreduction of mackinawite drastically enhances its ammonia accumulation capability, by up to 55-fold for the solid/liquid partition coefficient, enabling over 90% adsorption of 1 mM ammonia in 1 M NaCl at neutral pH ( Fig. 2 B ). The electrochemical conditions favorable for this process are fully compatible with those suitable for prebiotic carbon and nitrogen fixations in the formation of the building blocks of life ( 10 , 11 , 25 – 31 ) ( Fig. 4 ). The threshold potential ( − 0.6 V SHE ) corresponds to the H + / H 2 redox potential in a moderately alkaline, high-temperature hydrothermal environment [e.g., pH 8.7 at 100 °C in the presence of 1 mM H 2 ( 27 )], which is available even in present-day alkaline hydrothermal systems ( 47 , 48 ). Although modern ocean alkaline hydrothermal vents are mainly composed of carbonate minerals that are electrochemically nonconductive ( 49 ), the early counterparts were sulfide-rich, owing to the presence of metal-rich seawater ( 50 ). Fig. 4. Geoelectrochemical mechanism of ammonia accumulation in the early ocean hydrothermal system. The schematic was depicted based on our experimental results together with the field and laboratory findings on the geoelectrochemical processes in submarine hydrothermal systems reported in the literature ( 10 , 11 , 23 , 24 , 29 , 30 ). Thermodynamic calculations for the H + / H 2 redox potential as a function of pH and temperature ( 31 ) ( Right ) indicate that the electric potential necessary for the FeS − to − Fe 0 reduction and the subsequent NH 3 accumulation ( ≤ − 0.6 V SHE ) is readily realizable in H 2 -rich, alkaline hydrothermal systems that were ubiquitous on the early ocean floor ( 51 ). Iron sulfide must have been a predominant sulfide component of the ancient vent chimneys ( 51 ). Its catalytic surface with metal impurities (e.g., Ni 2 + ) facilitates both the oxidation of H 2 ( H 2 ⟶ 2 H + + 2 e − ) and the reduction of oxidative chemicals (e.g., CO 2 + H + + 2 e − ⟶ HCOO − ) ( 29 ); hence, a sustained electron flow across the potential gap between the reductive hydrothermal fluid and seawater has been envisioned ( Fig. 4 ). Pure and electroreduced mackinawite is also capable of facilitating ammonia formation ( 30 ) and promotes the amination reaction when a sufficient concentration of ammonia is available ( 30 , 37 ). These facts, along with our demonstrated extreme accumulation of ammonia on electroreduced mackinawite, suggest that mackinawite played a pivotal role in the formation, accumulation, and assimilation of organic compounds of ammonia in the early ocean hydrothermal vent environments. Submarine hydrothermal systems are currently the sole environment in which spontaneous electricity generation has been observed ( 24 ), thus possessing a crucial advantage in abiotic nitrogen assimilation, a requisite step for the originating of life."
} | 1,043 |
36164830 | PMC9514845 | pmc | 7,625 | {
"abstract": "Are animals’ preferences determined by absolute memories for options (e.g. reward sizes) or by their remembered ranking (better/worse)? The only studies examining this question suggest humans and starlings utilise memories for both absolute and relative information. We show that bumblebees’ learned preferences are based only on memories of ordinal comparisons. A series of experiments showed that after learning to discriminate pairs of different flowers by sucrose concentration, bumblebees preferred flowers (in novel pairings) with (1) higher ranking over equal absolute reward, (2) higher ranking over higher absolute reward, and (3) identical qualitative ranking but different quantitative ranking equally. Bumblebees used absolute information in order to rank different flowers. However, additional experiments revealed that, even when ranking information was absent (i.e. bees learned one flower at a time), memories for absolute information were lost or could no longer be retrieved after at most 1 hr. Our results illuminate a divergent mechanism for bees (compared to starlings and humans) of learned preferences that may have arisen from different adaptations to their natural environment.",
"introduction": "Introduction What do animals remember about items out of context? For example, suppose we learn that different options (e.g. coffee shops) result in different reward outcomes (e.g. waiting time and quality), and later we are presented with a choice between two previously encountered options which we have never experienced side-by-side. What types of values do we remember for those options now presented in a novel context? Do our memories of the subjective values for each option contain absolute information (e.g. delay to reward), remembered ranking (how they compared to previous alternatives), or a weighted combination of both? In typical studies exploring the economic choices of animals including humans, subjects do not have to use distant memories of the options; they are presented with choices where the objective values (e.g. amount, cost, and status) are concurrently visible and can be directly compared. Under such conditions, a wealth of research shows that animals’ choices can be influenced by the presence of additional options ( Hunter and Daw, 2021 ; Spektor et al., 2021 ). An example of this phenomenon is frequently used in marketing: when given a choice between popcorn options in different sizes, e.g. $3 for small and $7 for large, most people choose the smaller cheaper option, but when a $6 medium option is added, more people choose the large because it now seems like a good deal. Evidence of contextual effects like this on direct assessments has been found across the animal kingdom, e.g. humans and other primates ( Berkowitsch et al., 2014 ; Parrish et al., 2015 ; Trueblood et al., 2013 ), bats ( Hemingway et al., 2021 ), birds ( Bateson, 2002 ; Morgan et al., 2012 ), frogs ( Lea and Ryan, 2015 ), fish ( Reding and Cummings, 2017 ), bees ( Shafir et al., 2002 ), and worms ( Iwanir et al., 2019 ). However, little is known about the type and degree of information (absolute and/or relative) that is encoded in the remembered subjective values of options. Only more recently have investigations of absolute and relative information traversed into the realm of reinforcement learning, where value must be inferred from memories. Studies on starlings ( Pompilio and Kacelnik, 2010 ) and humans ( Bavard et al., 2018 ; Bavard et al., 2021 ; Klein et al., 2017 ) demonstrated that both absolute memories and remembered ranking are combined in particular ways to give rise to these animals’ preferences. So far, however, no other species have been investigated for the roles played by absolute memories and remembered ranking in learned preferences. Here, we examine this in bumblebees ( Bombus terrestris ), an invertebrate and a key model for examining the economy of decision-making outside of humans ( Real, 1996 ). Specifically, we adopt an instrumental learning paradigm that combines a contextual training phase and a transfer-test phase ( Palminteri and Lebreton, 2021 ). This paradigm essentially involves two distinct learning contexts (e.g. AB context and CD context; Figure 1 ), with each context offering two options of contrasting properties (e.g. A>B and C>D in reward sizes). After training, animals’ learned preferences are tested with a novel combination of options (e.g. B vs C). Note that behavioural tests for transitive inference ( Guez et al., 2013 ; Vasconcelos, 2008 ) involve a similar task design, which includes several training phases and a test phase of new combinations. However, this method provides overlapped relational premises during training (e.g. A>B, B>C, C>D, and D>E) in order to examine if animals can infer the relationship between a pair of options within the chained sequence which had previously not been experienced together (e.g. B vs D). In contrast, our paradigm provides no direct overlapped training between contexts (e.g. A>B and C>D), and therefore, animals cannot infer the relationship between unchained options (e.g. B vs C). Rather, by providing both absolute and relative information during training, our paradigm is used to assess whether, and in what combination, bumblebees retain and utilise absolute and ranking memories. Figure 1. Bumblebees make decisions based on ordinal comparisons. ( A , C , and E ) The corresponding sucrose concentration of each stimulus is displayed on a log scale to visually represent their relative differences according to Weber’s Law ( Akre and Johnsen, 2014 ). Training sessions are indicated by separate grey backgrounds, and the test options in each experiment are indicated with dashed lines. The bi-colour squares indicate that the colours for the focal options used were counterbalanced across bees. ( B , D , and F ) Test results for each experiment. Groups indicate different counterbalanced training sequence and colour-reward contingency (see Figure 1—figure supplement 3 for more details). Each filled circle represents the proportion of choices for option C by an individual bumblebee (10 individuals per group). Dashed horizontal lines indicate chance performance. Vertical lines indicate mean ± SEM. p values were calculated from generalised linear models (Materials and methods); NS: p > 0.05; *: p < 0.01. Figure 1—figure supplement 1. General setup for experiments 1, 2, and 3. In each experiment, artificial flowers of paired colours were horizontally presented in the training and testing phase. Figure 1—figure supplement 2. Specifications of the colours used for all the experiments. ( A ) Spectral reflectance plot of blue, orange, yellow, and green colours used. ( B ) Loci of colours in the hexagonal bee colour space, determined by the responses each colour elicits on the bee’s UV, blue, and green photoreceptors ( Chittka, 1992 ). Figure 1—figure supplement 3. Counterbalanced colour sets used in experiments 1–6. Groups of bees were trained and tested with counterbalanced colour sets and training sequences in each experiment. Figure 1—figure supplement 4. Bees can discriminate flowers of different colours and sucrose concentrations. To ensure that bees were able to learn to discriminate between two differently coloured flowers in our setup, we examined bees’ preference between two flower types after having been trained individually on these flowers. One group of bees (n=10) learned that blue flowers contained 45% sucrose solution and that yellow flowers contained 30% sucrose solution. Another group of bees (n=10) learned the counterbalanced colour-reward contingency. During a subsequent unrewarded test (all flowers with unrewarding water), bees showed a clear preference for (landed more often on) the flowers that had been associated with the higher reward during training (generalised linear model [GLM]: N=20, 95% CI = [0.64, 1.37], and p=3.39e-5). These results show that in our setup, bumblebees were able to easily learn to discriminate the different flower colours used in our experiments and do so via the different sucrose concentrations associated with each flower type. Groups indicate different counterbalanced colour-reward contingency for bees. Dotted horizontal lines indicate chance performance. Vertical lines indicate mean ± SEM. p values were calculated from generalised linear models (Materials and methods); *: p < 0.01.",
"discussion": "Discussion Our results suggest that bumblebees are only able to make use of ordinal ranking memories to guide foraging choices outside their original learning contexts. Although absolute information is essential for any animal to compare any two options initially, our findings show that only ordinal ranking can be recalled by bumblebees later in new contexts. Our results suggest that temporal adjacency is necessary for absolute information of different options to be compared by bees. That is, once bees experience one option, in order to utilise the absolute information, they must experience a second option within several minutes. Both our proof-of-concept experiment (experiment 6) and other previous multi-choice semi-realistic foraging tasks (e.g. Greggers and Menzel, 1993 ) show that with short inter-flower visits, bees can utilise absolute information in order to compare and rank flowers. Another potential mechanism worth discussing which could potentially explain bumblebees’ preferences is state-dependent valuation learning (SDVL; for a review see McNamara et al., 2012 ; Table 1 ). If bees’ choices were a result of SDVL instead of remembered ordinal ranking, then their preferences should be quantitative, i.e. larger values should be assigned with larger differences between internal state and flower experience. However, the results of experiment 3 speak against this interpretation because bees were indifferent between equally ranked A and C even though they were experienced in a richer and poorer environment, respectively. Why would bumblebees have evolved to use only memories for ordinal comparisons while humans and starlings evolved to retain and recall both absolute and ranking memories? Breadth of diet has been suggested to play a role in the evolution of cognition ( Hemingway et al., 2017 ; MacLean et al., 2014 ; Simons and Tibbetts, 2019 ). Humans and starlings forage on a range of different foods, whereas adult bumblebees feed almost exclusively on nectar and pollen from flowers. Perhaps a varied diet, whereby one might need a common currency across vastly different food types ( Chib et al., 2009 ; Levy and Glimcher, 2012 ) may have forced some animals to retain and use absolute memories, whereas a limited diet and limited dimensionality of reward might have favoured memories for ordinal relationships alone. There is no reason yet to suggest a bee’s brain lacks the neural substrates to retain and recall absolute memories for options for later use in novel contexts. In fact, recent electrophysiological recordings on the gustatory neurons of bumblebees demonstrated that the spiking rates of these peripheral sensory neurons increased as a function of sucrose concentration ( Miriyala et al., 2018 ). These gustatory neuronal signals could theoretically be used by higher centres of an animal’s brain to encode an option’s utility as a cardinal (absolute) value ( Schultz, 2015 ). However, our results suggest that bumblebees do not access or utilise any potentially stored absolute memories when it would be of benefit in novel contexts. Given our results, it would be intriguing to determine the differences in the underlying neural mechanisms responsible for the utilisation of absolute properties and ordinal ranking memories. Whatever the ultimate and proximate causes of bumblebees’ ordinal-only memories for options’ values, our findings demonstrate a fundamental difference in the mechanisms underlying learned preferences between those of bumblebees and those of starlings and humans."
} | 2,995 |
40263516 | PMC12015284 | pmc | 7,629 | {
"abstract": "Driven by the rapid development of the Internet of Things (IoT), deploying deep learning models on resource-constrained hardware has become an increasingly critical challenge, which has propelled the emergence of TinyML as a viable solution. This study aims to deploy lightweight deep learning models for human activity recognition (HAR) using TinyML on edge devices. We designed and evaluated three models: a 2D Convolutional Neural Network (2D CNN), a 1D Convolutional Neural Network (1D CNN), and a DeepConv LSTM. Among these, the DeepConv LSTM outperformed existing lightweight models by effectively capturing both spatial and temporal features, achieving an accuracy of 98.24% and an F1 score of 98.23%. After performing full integer quantization on the best model, its size was reduced from 513.23 KB to 136.51 KB and was successfully deployed on the Arduino Nano 33 BLE Sense Rev2 using the Edge Impulse platform. The device’s memory usage was 29.1 KB, flash usage was 189.6 KB, and the model’s average inference time was 21 milliseconds, requiring approximately 0.01395 GOP, with a computational performance of around 0.664 GOPS. Even after quantization, the model maintained an accuracy of 97% and an F1 score of 97%, ensuring efficient utilization of computational resources. This deployment highlights the potential of TinyML in achieving low-latency and efficient HAR systems, making it suitable for real-time human activity recognition applications.",
"introduction": "Introduction In recent years, the integration of IoT, AI, and cloud computing has spurred considerable innovation across various domains.By 2030, it is projected that there will be more than 30 billion IoT devices globally 1 . However, these applications often require significant computing resources, including memory, CPU, and network bandwidth. As data continues to grow, traditional cloud computing solutions may struggle to keep up 2 . By 2035, autonomous vehicles are expected to account for approximately 66% of total car sales in China 3 , presenting significant challenges for traditional cloud-based methods. In particular, data transmission errors or malicious attacks could lead to incorrect decisions, causing serious social and economic consequences 4 . Therefore, exploring more sustainable distributed computing models, such as edge computing, has become increasingly important 5 . Edge computing reduces dependence on centralized cloud services by processing data on local devices, thereby lowering latency and improving real-time processing capabilities 6 . Human Activity Recognition (HAR) is a classification problem that involves predicting activities such as jogging, lying down, and standing based on data collected from individual users 7 . HAR has vast potential applications, including smart homes, healthcare, and other automated domains reliant on human behavior analysis. For example, HAR can be used to monitor the health status of elderly individuals 8 and assist people with disabilities 9 . HAR is primarily achieved through wearable sensors 10 and cameras 11 . In comparison, sensor-based solutions offer higher efficiency and better privacy protection, and they are not affected by environmental factors such as lighting 12 .Moreover, the significantly lower cost of sensors compared to their counterparts has led to rapid research advancements in this field 13 . Today, sensor-based HAR applications have expanded into various fields, including healthcare systems 14 , 15 , vehicle travel time prediction 16 , and context-aware systems 17 . Initially, HAR relied primarily on traditional machine learning techniques, achieving significant results 18 . For example, 19 analyzed various machine learning models, including Decision Tree, Random Forest, and XGBoost, for HAR on wearable devices, achieving state-of-the-art accuracy on the Human Activity Recognition with Smartphones dataset. XGBoost, in particular, achieved an accuracy of 99.52%, demonstrating the potential of machine learning models in HAR tasks. However, these methods typically require substantial computational resources and considerable manual intervention by domain experts, making it difficult to adapt to new environments. Consequently, research has gradually shifted from traditional machine learning to deep learning, opening up broader possibilities.Due to its hierarchical structure, deep learning enables models to learn from raw, unprocessed data. In recent human activity recognition (HAR) research, reference 20 proposed a stacked LSTM network, achieving an accuracy of 93.13% on the UCI dataset. However, this model relies solely on LSTM units and fails to fully capture temporal features, leaving room for improvement in accuracy. Reference 21 introduced a CNN-GRU model, which achieved an accuracy of 96.54% on the WISDM dataset. However, its complex structure increases computational resource demands, making it difficult to deploy in resource-constrained environments. Reference 22 designed a hybrid CNN and BiLSTM model, which captures bidirectional dependencies through bidirectional LSTM, achieving an accuracy of 96.05% on the WISDM dataset. Nevertheless, the model’s multi-branch architecture and extensive use of convolutional and pooling layers significantly increase computational overhead, limiting its applicability on edge devices. Reference 23 proposed a CNN-LSTM model incorporating a self-attention mechanism, achieving an accuracy of 99.93% on its proprietary dataset and 93.11% on the UCI-HAR dataset. Although the attention mechanism enhances the model’s classification capabilities, it also significantly increases storage and computational requirements, making it challenging to deploy in resource-constrained environments. Therefore, how to reduce computational demands while maintaining high accuracy and enabling efficient deployment on IoT devices remains a critical challenge. To address these challenges, this study focuses on designing lightweight deep learning models that can be efficiently deployed on resource-constrained devices. In 24 , the authors explored four architectures (CNN, LSTM, ConvLSTM2D, and CNN-LSTM), among which the CNN-LSTM model achieved the highest accuracy of 97.68% on the WISDM dataset. However, 25 used CNN-LSTM and CNN-GRU models, but none exceeded 98% accuracy. Additionally, in 26 , the authors compared 1D CNN and 2D CNN and ultimately selected 1D CNN for training, achieving an accuracy of 97.8%.In 27 , the authors proposed a neural architecture search (NAS) method based on a latency lookup table (LUT) to optimize HAR models for mobile devices. Their approach significantly reduced search time and improved inference efficiency by tailoring models to specific hardware constraints. However, on the WISDM dataset, their model achieved an F1 score of only 88%, indicating room for improvement in balancing accuracy and efficiency.Although these methods have achieved promising results, there is still room for improvement in model performance. Therefore, we selected three primary architectures for evaluation: 1D CNN, 2D CNN, and DeepConv LSTM. 1D CNN was chosen for its efficiency in extracting temporal features from sequential sensor data, while 2D CNN was selected for its capability to capture spatial features. DeepConv LSTM integrates convolutional layers with LSTM networks, allowing it to capture both spatial and temporal dependencies, making it more suitable for recognizing complex human activities. With the rapid development of IoT devices, they are now capable of supporting more advanced algorithms at the edge computing layer 28 . This progress reduces the reliance on cloud computing, thereby improving response times, lowering latency, and reducing bandwidth consumption. Consequently, the concept of integrating artificial intelligence with IoT devices has emerged, combining AI technology into IoT systems 29 . Traditionally, deep learning algorithms primarily relied on cloud computing for processing. However, in real-time analysis scenarios, high latency can occur, affecting service quality. In contrast, TinyML 30 focuses on developing models that can be deployed on IoT devices, enabling these devices to make decisions at the point of data generation. TinyML has now become a new trend 31 and is being widely applied across various domains. For example, in 32 , LSTM autoencoders were used for unsupervised anomaly detection of urban noise, achieving an accuracy of 99.99%. After quantization, the model was successfully deployed on microcontroller units (MCUs) with an average inference time of approximately 4 milliseconds. In 33 , TinyML sensors predicted the shelf life of date fruits, with both training and deployment conducted on the Edge Impulse platform, significantly reducing computational resource requirements and energy consumption, with all samples achieving over 93% accuracy. In 34 , the authors proposed an anomaly detection system based on the Isolation Forest algorithm, capable of detecting anomalies within 16 milliseconds, demonstrating the low-latency and adaptability of TinyML in extreme industrial environments. In 35 , a binarized neural network was deployed on a Raspberry Pi for low-latency human activity recognition, utilizing 721KB of memory and achieving 98.2% accuracy. Therefore, the combination of TinyML and human activity recognition (HAR) offers advantages such as low power consumption, enhanced security, and fast response times, addressing hardware and connectivity challenges while improving system efficiency 36 . The main contributions of this study are: We designed three Human Activity Recognition (HAR) models and identified DeepConv LSTM as the optimal model, achieving an accuracy of 98.24%. Compared with existing lightweight HAR models, our proposed model demonstrates superior performance. The model was fully quantized and deployed on the Arduino Nano 33 BLE Sense Rev2, addressing the gap in previous studies where lightweight models were not deployed on resource-constrained devices. We analyzed the feasibility of deploying the model to the Arduino Nano 33 BLE Sense Rev2, including model inference time, flash memory, RAM usage, and power consumption, ensuring efficient execution on resource-constrained devices. The remainder of this paper is structured as follows: Section “Methods” Presents the preprocessing methods and provides a detailed description of the three model architectures. Section “Results” evaluates our models on the WISDM dataset and analyzed the results to identify the best-performing model for deployment. Section “Discussion” summarizes the findings and proposed directions for future work.",
"discussion": "Discussion This study utilized a dataset provided by the WISDM Lab at the Department of Computer and Information Science, Fordham University, Bronx, New York. During the preprocessing phase, the raw data was aggregated into 100 samples per 5-second segment to generate new features, and a 50% overlapping sliding window was applied to retain information from the previous window. We designed and evaluated three different deep learning models to identify the most suitable model for deployment on edge devices. The experimental results indicate that the DeepConv LSTM model outperformed the 1D CNN and 2D CNN models, achieving a classification accuracy of 98.24% and a validation loss of 0.0699. After full integer quantization, the size of the DeepConv LSTM model was reduced to 136.51 KB, with RAM usage of 29.1 KB, flash memory usage of 189.6 KB, and an average inference time of 21 milliseconds. The model’s accuracy slightly decreased from 98.24% to 97.09%. Due to the resource constraints of the Arduino Nano 33 BLE Sense Rev2, the inference time for real-time recognition was approximately 2 seconds. Considering that our window size is 5 seconds, this makes the on-board processing functionally feasible. This edge deployment aims to reduce reliance on cloud services and enhance user privacy. Additionally, the model’s ability to process time-dependent data demonstrates its broad application potential, further validating the feasibility of using TinyML technology to handle complex computational tasks in resource-constrained environments. Although the DeepConv LSTM model achieved excellent performance on the WISDM dataset, it has not been tested on other datasets or deployed on resource-constrained devices with varying capabilities. In future research, the model could be evaluated on multiple datasets to ensure its generalizability. Additionally, the WISDM dataset is highly imbalanced, which can affect the model’s performance on minority classes. and techniques such as data augmentation or oversampling could be explored to improve the model’s performance on minority classes."
} | 3,188 |
36910953 | PMC9996783 | pmc | 7,630 | {
"abstract": "The preparation methods of the superhydrophobic surface\nplay an\nimportant role in its application, but most of the existing preparation\nmethods are complicated in operation, high in cost, and polluting\nto the environment. In order to find a simple, rapid, low-cost, and\nnonenvironmentally polluting preparation method of the superhydrophobic\nsurface, this paper used liquid silicone rubber as the carrier. Before\nthe liquid silicone rubber was nearly cured, it was evenly covered\nwith a layer of silicon dioxide powder, and then 5 N weight was used\nto compact the powder on the rubber surface, so that the superhydrophobic\nsurface was quickly formed on its surface. The wettability, bouncing\nperformance, self-cleaning performance, and bending durability of\nliquid silicone rubber before and after treatment were compared. The\nresults show that the static contact angle and rolling angle of the\nliquid silicone rubber after powder pressing were 158.22 ± 2.01°\nand 1.00 ± 0.50°, respectively. Moreover, the superhydrophobic\nsurface formed by the powder pressing method had good self-cleaning\nperformance, high temperature resistance, bending resistance, and\nexcellent droplet bounce performance. The strategy of preparing a\nsuperhydrophobic surface by a one-step powder pressing method may\nbe applied to the preparation of the superhydrophobic surface on a\nlarge scale.",
"conclusion": "4 Conclusion In this paper, the superhydrophobic\nsurface was successfully prepared\nby covering a layer of HB-192V particles on the surface of liquid\nsilicone rubber by a powder pressing method. This work had the characteristics\nof simple operation, high speed, low cost, and no environmental pollution.\nThe self-cleaning test, normal temperature drop bounce test, high-temperature\naging test, and antibending durability test had been carried out,\nand some main conclusions were as follows. (1) The RTV/HB-192V superhydrophobic surface\nprepared by the powder pressing method was green and pollution-free,\nwhich can form a superhydrophobic layer quickly and at low cost. It\nalso had good self-cleaning, high-temperature resistance, and good\nbounce performance in a normal temperature drop bounce test. (2) By covering a layer of\nHB-192V particles\non the surface of liquid silicone rubber to make a microstructure,\nthe contact angle of the rubber surface was increased from 112.84\n± 0.55° to 158.22 ± 2.01°, and the rolling angle\nwas decreased from 51.02 ± 0.78° to 1.00 ± 0.50°. (3) After 500 antibending\ntests, the contact\nangle of the prepared superhydrophobic surface was 152.98 ± 0.72°,\nand the rolling angle was 7.40 ± 0.62°, which proves that\nthe prepared superhydrophobic surface had good antibending durability.",
"introduction": "1 Introduction Superhydrophobic surface\nrefers to the surface where the contact\nangle between water droplets and solid materials is greater than 150°,\nand the rolling angle is less than 10° when solid materials are\nin contact with water droplets. 1 − 5 Superhydrophobic surfaces are widely used in industry, military,\nand daily life because of their excellent hydrophobicity. 6 − 9 An important application of superhydrophobic surfaces is self-cleaning, 10 which can effectively improve the waterproof\nand antifouling ability of its surface when it is used on glass, clothing,\nand metal. Superhydrophobic materials can also be used in pipeline\nantiscaling, oil–water separation, drag reduction, antiskid,\nanticorrosion, and other applications. Therefore, the research and\ndevelopment of superhydrophobic materials is of great significance\nto daily life and industrial development. The current method of forming\na superhydrophobic surface is to construct a micronano structure on\nthe surface with low surface energy or modify the micronano structure\nwith low surface energy substances. 11 − 14 At present, the methods for preparing\nsuperhydrophobic surfaces mainly include: the layer-by-layer self-assembly\nmethod, 15 spraying method, 16 template method, 17 chemical\nvapor deposition method, 18 sol–gel\nmethod, 19 etching method, 20 spin-coating method, 21 and so\non. For example, Chi 22 and others used\nhydrophobic silicon dioxide particles and organosilane binder to prepare\nan antireflection coating with mechanical firmness and self-cleaning\nperformance. Wang 23 et al. used traditional\nnucleophilic polycondensation and simple electrospray technology to\nmodify common polyaryletherketone (PAEK) into hexafluorobisphenol\nA-PAEK and prepared a new superhydrophobic polyaryletherketone membrane\nfor the first time. He 24 et al. prepared\na three-dimensional superoleophilic/superhydrophobic carbon fiber\nfelt (CFF) material surface by anchoring hydrophobic Fe 3 O 4 nanoparticles on 3D CFF. The prepared CFF material\nshowed high water contact angle and low oil contact angle. Davis 25 et al. produced a highly solid superhydrophobic\nsilicone whole through expandable and environmentally friendly emulsion\ntechnology. It is first found that stable and surfactantless water-in-polydimethylsiloxane\n(PDMS) emulsions can be formed through mechanical mixing, and they\nhad good durability. Bayer 26 et al. mentioned\nthat perfluorinated compounds can cause some environmental problems.\nMoreover, most of the formulations and processes of superhydrophobic\ncoatings were considered to be not environmentally friendly, unable\nto maintain large-scale manufacturing, or too expensive to be converted\ninto a standard industrial practice. Recently, however, people had\nmade superhydrophobic coatings by using natural materials and sustainable\nprocesses, thus reducing potential environmental pollution. Silicone rubber is widely used in antifouling coatings, aerospace,\nmachinery, biomedicine, electrical insulators, and other fields because\nof its superior weather resistance, electrical insulation, transparency,\nlow toxicity, and hydrophobicity. 27 − 29 Therefore, silicone\nrubber is favored by many scholars in the preparation of superhydrophobic\nsurfaces. 30 , 31 For example, Maghsoudi 32 et al. directly copied the surface of superhydrophobic\nhigh-temperature vulcanized silicone rubber by a compression molding\nsystem, and its surface contact angle was greater than 160° and\nrolling angle less than 3°. Wan 33 et\nal. put forward a simple and cheap dipping–coating–curing\nstrategy. A strong, environmentally friendly melamine-formaldehyde\nsponge with a superhydrophobic and superoleophilic MoS 2 coating was prepared through the modification of room-temperature\nvulcanized silicone rubber. Most of the preparation methods of superhydrophobic\nsurfaces have limitations. For example, although the spraying method\nis simple in operation and low in cost, it emits pollution to the\nenvironment. Also, the etching process is complicated; the cost is\nhigh; and it is not suitable for mass production. In this work,\nthe liquid silicone rubber was used as the carrier,\nand before the liquid silicone rubber was nearly cured, a layer of\nsilicon dioxide powder was evenly covered on its surface. Then the\npowder on the rubber surface was compacted with a 5 N weight, so that\nits surface quickly formed a superhydrophobic surface. In order to\ntest the performance of the superhydrophobic surface, self-cleaning,\nhigh-temperature resistance, bending durability, and droplet bounce\nperformance were tested.",
"discussion": "3 Results and Discussion 3.1 Surface Morphology and Hydrophobic Properties It can be seen from Figure 2 (a) that HB-192V particles in the solution were agglomerated\nafter ultrasonic dispersion with alcohol solution. It can be seen\nfrom Figure 2 (b) that\nthe HB-192V particles were spherical in appearance, with a diameter\nof about 11 μm. When the particles were adsorbed on the rubber\nsurface, the convex structure of the rubber surface was increased,\nand the main characteristic peaks of the particles are −OH,\nSi–O–Si, stretching vibration, and bending vibration\nof Si–O bonds. Figure 2 SEM of HB-192V in alcohol solution (a). HB-192V particles\nand FTIR\n(b). SEM of the RTV surface (c). Enlarged electron microscope image\nof the RTV surface (d). Element distribution and element content percentage\non the RTV surface (e). SEM of RTV/HB-192V (f). Local magnified electron\nmicroscope image of RTV/HB-192V (g). Element distribution and element\ncontent percentage on the RTV/HB-192V surface (h). It can be seen from Figure 2 (c–e) that the surface of RTV was\nsmooth and had a\ngrain structure. According to the element distribution and element\nproportion on the RTV surface, three elements, C, O, and Si, were\nuniformly distributed on the RTV surface, among which the element\ncontent of Si was 27.67%; that of O was 19.29%; and that of C was\n53.04%. It can be seen from Figure 2 (f) that HB-192V powder was successfully attached to\nthe surface of RTV. It can be seen from Figure 2 (f) and Figure 2 (g) that there was a gap between HB-192V\nparticles attached to the rubber surface, and there was local agglomeration.\nThis phenomenon will cause the exposed HB-192V particles and air molecules\nto establish a Cassie–Baxter model 34 in the microstructure. According to the surface element distribution\nand element proportion of RTV/HB-192V in Figure 2 (h), the content of element C was 48.91%,\nand that of O was 24.10%. According to Figure 2 (e) and Figure 2 (h), the formula element ratio of silicon\ndioxide was Si:O = 1:2. It can be seen that the content of the silicon\nelement decreases, and the content of elemental oxygen increases on\nthe rubber surface after pressing HB-192V, which proves that HB-192V\npowder successfully adheres to the RTV surface. According to\nthe three-dimensional topography of the rubber surface\nin Figure 3 (a), the\nsurface of RTV was smooth, and the microscopic condition of the rubber\nsurface shown in Figure 2 (c) was verified. The surface roughness (Sa) of RTV was 11.97 μm.\nAfter the surface of RTV was covered with HB-192V particles, the Sa\non the surface of RTV was increased to 29.15 μm, which was 1.44\ntimes that of the surface without powder pressing. Therefore, the\npowder pressing behavior increased the surface roughness of RTV, and\na layer of microstructure covered by HB-192V particles was formed\non the surface of RTV. Figure 3 Three-dimensional topography of the RTV surface (a). Three-dimensional\ntopography of the RTV/HB-192V surface (b). Comparative histogram of\nthe static contact angle and rolling angle of the RTV surface and\nRTV/HB-192V surface (c). According to Figure 3 (c), the average contact angle and rolling angle of\nthe RTV surface\nwere 112.84° and 51.02°, and the average contact angle and\nrolling angle of the RTV/HB-192V surface were 158.22° and 1.00°,\nrespectively. Because the contact angle of the RTV surface was greater\nthan 90.00°, its surface was hydrophobic. After coating a layer\nof HB-192V powder on the RTV surface, HB-192V particles form a microstructure\non the RTV surface, which increased the roughness of the rubber surface,\nwhich greatly improved the hydrophobic property of the RTV/HB-192V\nsurface. The rolling angle of the RTV surface was 51.02 ± 0.78°,\nwhich indicated that the droplet adhesion of the RTV surface was relatively\nlarge, which led to the larger rolling angle of the RTV surface. The\nrolling angle of the RTV/HB-192V surface measured by a contact angle\ntester was 1.00 ± 0.50°, which proved that the RTV surface\ncovered by HB-192V powder showed good superhydrophobic performance. 3.2 Droplet Bounce Performance Test It\ncan be seen from Figure 4 (a) and Figure 4 (e)\nthat water droplets of the same volume lag behind at different heights,\nand with the increase of drop height, the spreading diameter of the\ndroplets on the surface of RTV/HB-192V gradually increased. It takes\nlonger to reach the maximum spreading diameter. This was because the\nhigher the drop height, the greater the gravitational potential energy\nof the droplets when the droplets touched the surface of RTV/HB-192V.\nThe gravitational potential energy and kinetic energy of the drop\nwere converted into the surface energy of the drop. The higher the\ndrop falling distance, the larger the surface energy and the larger\nthe surface area of the drop. Therefore, when the drop fell at different\nheights, the larger the height, the larger the surface area, and the\nlarger the spreading diameter of the drop. According to the comparison\nof Figure 4 (a), Figure 4 (b), and Figure 4 (e), when different\nvolumes of droplets fall at the same height, the larger the volume\nof droplets, the larger the maximum spreading diameter of droplets\non the surface of RTV/HB-192V. This was because the larger the volume\nof the droplets, the larger the diameter of the droplets; therefore,\nwhen droplets with different volumes at the same height fell on the\nsurface of RTV/HB-192V, the largest spreading diameter of droplets\nwith larger volume will be larger. Figure 4 Spreading behavior of droplets with different\nvolumes falling on\nthe surface of RTV/HB-192V at different heights (a,b). The bouncing\nbehavior of droplets with different volumes falling on the surface\nof RTV/HB-192V at different heights (c,d). Maximum spreading diameter\nof droplets with different volumes falling from different heights\nto the surface of RTV/HB-192V (e). Droplets of different volumes fall\nfrom different heights to the maximum bouncing height of the RTV/HB-192V\nsurface (f) and droplet bounce behavior of droplets dropping from\n15 mm height to the RTV surface (g). It can be seen from Figure 4 (c) and Figure 4 (f) that the droplets with the same volume\nfell behind at different\nheights, and with the increase of the falling height of the droplets,\nthe maximum bounce height of the droplets after contacting the rubber\nsurface was larger. The time to reach the maximum bounce height was\nlonger. The reason was that the higher the drop height, the greater\nthe gravitational potential energy of the drop. Because the surface\nof RTV/HB-192V had a microstructure, the gravitational potential energy\nand kinetic energy of the drop were converted into the surface energy\nof the drop, and a part of the potential energy was lost by impact\nand then converted into gravitational potential energy and kinetic\nenergy. The more gravitational potential energy was converted, the\nhigher the maximum bounce height of the drop. According to the comparison\nof Figure 4 (c) and Figure 4 (d), when the droplets\nwith different volumes fell on the surface of RTV/HB-192V at the same\nheight, the larger the droplet volume, the smaller the maximum bouncing\nheight of the droplets. The analysis may be that when the droplets\nwith larger volume fell on the surface of RTV/HB-192V at the same\nheight, the larger the droplet volume, the larger the maximum spreading\ndiameter. The larger the contact area, the more energy will be lost\nto overcome the friction resistance provided by the contact layer\nwhen the droplets bounce. Therefore, when droplets with different\nvolumes at the same height drop, the maximum bounce height of droplets\nwith small volume was larger. It can be seen from Figure 4 (g) that when water drops on\nthe surface of RTV the water\ndrops did not rebound but repeatedly stretched and shrank on the surface\nof RTV and then stopped steadily, indicating that there were strong\nwater drops attached on the surface of RTV. 3.3 Self-Cleaning Test It can be seen\nfrom Figure 5 (a) that\nwhen 5 drops of water were dropped on the surface of RTV the drops\nwere clustered together and adsorbed on the surface of RTV. As the\nwater drops increased to 15 drops, all the drops still clustered together\nand did not roll down the slope. It can be seen from Figure 5 (b) that when five drops of\nwater drop at the same height on the surface of the RTV/HB-192V sample\nsome drops bounced and rolled down quickly with carbon black. When\nthe number of water drops increased to 15 drops, most of the carbon\nblack on the surface of RTV/HB-192V had been taken away by water drops,\nand an obvious channel was formed on the rubber surface. Through the\ncomparison of two groups of self-cleaning test phenomena, it can be\nseen that the RTV surface treated by HB-192V powder had a good self-cleaning\neffect. Figure 5 Self-cleaning experimental process of original silicone rubber\n(a) and self-cleaning experimental process of silicone rubber composites\n(b). 3.4 Durability Test It can be seen from Figure 6 (a) and Figure 6 (b) that the Sa of\nthe RTV surface was 11.97 μm. After 72 h of high-temperature\naging, the Sa of the RTV surface was increased to 37.91 μm.\nThe high-temperature aging test increased the roughness of the RTV\nsurface. It can be seen from Figures 6 (c) and 6 (d) that the Sa of\nthe RTV/HB-192V surface was 29.15 μm, which was larger than\nthe surface roughness of RTV. After high-temperature aging, the Sa\nof the RTV/HB-192V surface was 45.93 μm, compared with that\nbefore aging. The surface roughness was increased, and the change\ntrend of Sa was the same as that before and after aging of RTV. By\ncomparison, the maximum height of RTV and the RTV/HB-192V surface\nbefore and after high-temperature aging was increased, which proves\nthat it was raised in the Z direction, which increased\nthe surface roughness. Figure 6 Comparison of three-dimensional morphology of RTV and\nRTV/HB-192V\nsurfaces before and after high-temperature aging (a–d). Comparison\nof the contact angle and rolling angle of RTV and RTV/HB-192V surfaces\nbefore and after high-temperature aging (e). Supplementary test chart\nof the rolling angle of RTV after high-temperature aging (f). According to Figure 6 (e), the contact angle of the RTV surface was 112.84\n± 0.55°;\nthe rolling angle was 51.02 ± 0.78°; the contact angle of\nthe RTV/HB-192V surface was 158.22 ± 2.01°; and the rolling\nangle was 1.00 ± 0.50°. After 72 h of high-temperature aging,\nthe contact angle of the RTV surface becomes 118.09 ± 0.76°,\nwhich was 5.25° larger than that before aging, indicating that\nthe increase of surface roughness increases the contact angle after\nhigh-temperature aging. Figure 6 (f) shows the phenomenon that water droplets fell on the surface\nof RTV after aging and rotated 180°, but the droplets still did\nnot fall, indicating that the rolling angle of the RTV surface after\nhigh-temperature aging was greater than 90° and had strong adsorption.\nAfter aging, the contact angle of the RTV/HB-192V surface was 151.73\n± 0.86°, which was 6.49° lower than that before aging.\nAfter aging, the rolling angle was 2.54 ± 0.62°, which was\n1.54° higher than that before aging at high temperature. The\nreason was that as the roughness of the surface increases the air\ncavity between concave and convex structures becomes larger, and the\nair density in a certain space decreases. The results show that the\nsurface of RTV/HB-192V was still superhydrophobic after 72 h of a\nhigh-temperature aging test, which indicated that this superhydrophobic\nsurface had good high-temperature durability. It can be seen\nfrom Figure 7 (a) and Figure 7 (b) that the characteristic\npeak at 3445 cm –1 was\nthe tensile vibration peak of hydroxyl (−OH) in water molecules.\nThe characteristic peaks at 1100 cm –1 and 810 cm –1 were caused by the tensile vibration and bending\nvibration of the Si–O–Si bond, and the characteristic\npeak at 2965 cm –1 was the tensile vibration peak\nof the C–H bond. The characteristic peak at 2345 cm –1 was produced by carbon dioxide. After RTV was covered with HB-192V\npowder, C–O and C–C on the surface of RTV could still\nbe detected, while the water hydroxyl groups in the particles disappeared.\nIt was speculated that the particles were adsorbed on the RTV surface\nand dried for a long time, so the water hydroxyl group was removed.\nAccording to the peak comparison between the two rubbers before and\nafter high-temperature aging, the functional groups on the surfaces\nof RTV and RTV/HB-192V did not change obviously after 72 h of high-temperature\naging. Figure 7 Fourier infrared spectrum of HB-192V particles (a). Comparison\nof FTIR spectra of RTV and RTV/HB-192V before and after high-temperature\naging (b). Figure 8 (a–c)\nwas the test chart of RTV/HB-192V specimen bent 500 times, and Figure 8 (c) was the most\ndamaged part taken out from the bending test, which was used for a\nhydrophobic test. The test was repeated five times, and the measured\ndata were counted. According to Figure 8 (a–d), after the RTV/HB-192V was bent 500 times,\nthe contact angle of the bent part measured by the contact angle tester\nwas 152.98 ± 0.72°, and the rolling angle was 7.4 ±\n0.62°, which was 5.24° lower than that of the original RTV/HB-192V.\nThe rolling angle was 6.40° higher. According to the analysis\nof Figure 8 (c), the\nbending test caused the uneven dispersion of HB-192V particles on\nthe surface of RTV/HB-192V, and some points exposed the surface of\nRTV. However, after 500 bending tests, the surface of RTV/HB-192V\nwas still a superhydrophobic surface, which proved that the prepared\nsuperhydrophobic surface had good bending durability. Figure 8 Bending test diagram\nof RTV/HB-192V (a–c) and comparison\ndiagram of the contact angle and rolling angle of RTV/HB-192V before\nand after bending (d)."
} | 5,283 |
33748702 | PMC7960941 | pmc | 7,632 | {
"abstract": "Summary In this paper, we report a finding that substrate affects the adhesion of charged super-repellent surfaces. Water droplet impacting on a super-repellent surface produces surface charge, whose expression depends on the substrate. The charged super-repellent surface is sticky to droplets for a suspended substrate made of dielectric materials, while it has low adhesion for a conducting substrate or stage attached at the bottom because of electrostatic induction. Theoretical analysis and simulation are conducted to elucidate the mechanism of substrate effect on surface adhesion. Finally, we develop a new approach to reversibly tune the adhesion of super-repellent surface by combining surface-charge-induced adhesion increase and electrostatic-induction-regulated express of net surface charge. As a proof-of-concept experiment, we demonstrate that droplet sorting and manipulations can be realized by using this controllable surface adhesion tuning approach, which has potential applications in advanced lab-on-a-drop platform.",
"conclusion": "Conclusion In conclusion, we found the charged super-repellent surface with a thin dielectric substrate is highly adhesive when it is suspended. On the other hand, the charged surface with a conductive substrate or placed on a metal stage behaves low adhesion. We analyzed the substrate effect on impacted surface adhesion based on surface charge and electrostatic induction. Further, we introduced a movable conductor to tune the adhesion of the impacted super-repellent surface. The distance between the conductive plate and the charged surface determines the amount of adhesive force on the basis of the theoretical analysis and electric simulation. Combining the dielectric substrate with a movable conductive plate, the adhesive force of the super-repellent surface can be easily regulated after charging by droplet impact. Droplet manipulation is demonstrated based on this adjustment method for surface adhesion. From a broader perspective, the reversible adhesion change illustrates that the surface charge does not dissipate but always exists at the position after water contact even when the substrate is a conductor or is placed on a stage. It is noteworthy that the charge on the super-repellent surface may have an imperceptible effect on the wetting experiment besides adhesion.",
"introduction": "Introduction Smart surfaces with specific liquid-solid interfacial adhesion are crucial in a variety of applications, including lab-on-chip devices ( Milionis et al., 2014 ), biochemical analysis ( Sun and Qing, 2011 ), cell adhesion ( Didar and Tabrizian, 2010 ; Ishizaki et al., 2010 ), and no loss droplet transportation ( Dai et al., 2019 ; Ding et al., 2012 ; Li et al., 2011 ; Tang et al., 2017 ; Wu et al., 2011 ; Yang et al., 2018 ). Different applications require specific liquid-solid interfacial adhesion for controllable droplet mobility on the surface. Typically, a low adhesion surface shows great advantages in applications due to their excellent anti-fouling properties. In some applications, certain surface adhesion is desired for a specific usage ( Callies and Quéré, 2005 ; Deng et al., 2012 ; Miwa et al., 2000 ; Tuteja et al., 2007 ). Intensive research studies have focused on designing surface morphology and chemical composite for tuning adhesion to water droplet. The specific adhesive surface is prepared by controlling various parameters. For example, morphologies, like nanopore arrays, nanotube arrays, and nanovesuvianite structures, produce different adhesive forces ( Lai et al., 2009 ). The orientations of surface microstructures are also designed to tune the liquid-solid interface adhesion on the same super-repellent surface ( Zheng et al., 2007 ). Chemical composite of the surface molecule is an alternative way to obtain high adhesion super-repellent surface. Examples include adhesion adjustment of TiO 2 films using 1 H , 1 H , 2 H , 2 H -perfluorooctyltriethoxysilane, and nitrocellulose ( Lai et al., 2008 ) or adjustable adhesion achieved by boiling coating ( Ding et al., 2018 ). Although these strategies are effective for preparing the super-repellent surface with low or high water adhesion, the process is irreversible, and therefore, the wettability of the surface is constant after treatment. In practical applications, active control of the adhesion is desired. To adaptively control the adhesion of surfaces, low surface energy materials were commonly used while external stimuli were employed for the adjustment. Strategies, including heat, light, pH, magnetic field, and electric field, have been used in the reversible regulation of adhesion. However, problems like complexity in setup, slow response, external energy consumption, additive to the sample droplets, and small tuning amplitude are unavoidable in these methods ( Cheng et al., 2008 ; Heng et al., 2015 ; Li et al., 2009 ). Simple, real-time control methods for reversible adjustment with a wide range of surface adhesion still present a challenge. We have reported that the surface charge can be created by water impact on a super-repellent surface coated on a piece of thin glass substrate ( Sun et al., 2019 ). Using this intense yet highly localized electric field on the top of the surface, we are able to create strong adhesion of the drop on the surface. Here, we investigated the expression of the electric field, which could be influenced by the substrate. Although all surfaces are supported by a substrate, consideration of the effect of the substrate on the surface property was usually neglected. We investigate the adhesion of a charged super-repellent surface regulated by the substrate. The surface adhesive force to droplets is disparate at the charged position when the substrate is different. Based on this finding, we develop an in situ strategy to adjust the surface adhesion reversibly and realize the droplet manipulation by actively controlling a conductive substrate.",
"discussion": "Results and discussion Increase in surface adhesion after drop impact on super-repellent surfaces with different types of substrates When a drop impacted on the prepared super-repellent surface, we found that the retraction process was strikingly distinct when the type of placing or substrate was changed. To demonstrate the difference in drop impacting process, we prepared two sample surfaces with the same super-repellent coating on varied substrates ( Figure 1 A). When a droplet impacted on a super-repellent surface with a thin glass substrate placed on a metal stage, the droplet rebounded and detached completely. On the other hand, a droplet split to a small droplet adhering on the impacted position under the same condition, except that the surface was suspended in the air. If the substrate was replaced by a silicon wafer, which is either suspended or placed on a metal substrate, such adhesion effect was remarkably mitigated. It can be found that the adhesion difference of super-repellent surface could be tuned by the substrate property and platform. The whole process is shown in Figure 1 B, demonstrated by the ratio of contact diameter ( D c ) and the diameter of the droplet ( D 0 ) as a function of normalized time ( τ = σ t 2 / ρ r 0 3 ). Here, σ is the surface tension of water, t is the time from contact, ρ is the density of the water, and r 0 is the radius of the droplet. The curves demonstrate that the spreading processes are identical but the rebounding process is hindered on the suspended super-repellent surface with a thin glass substrate. The droplet rebound test also indicates that the substrate of the impacted super-repellent surface heavily affects the surface adhesion ( Figure S1 ). A droplet was released from 1 cm height onto the super-repellent surface which was previously impacted by water droplets with different Weber numbers ( We = ρv 2 r 0 / σ ). Here, v is the impact velocity. Droplet on the suspended glass one always stops earliest because of the increased surface adhesion. Figure 1 The spread and retraction process of droplet impact on super-repellent surfaces (A) Snapshots of water droplet impact on the super-repellent surface with glass substrate placed on a metal stage (upper panel), suspended in air (second panel), the super-repellent surface with suspended Si substrate (third panel), and Si substrate on a metal stage (bottom panel), respectively ( We = 34). (B) Time-resolved variations of droplet contact length D c normalized by the droplet diameter D 0 on the surface in the spreading and retracting process. To verify the influence of the substrate on adhesion, we further measured the adhesive force at the position on the surface after water drop impacting. The measurement process is shown in Figure 2 A. The super-repellent surface approaches to, contacts, and then retracts from a hanging water drop. Figure 2 B shows the shapes of the water droplet during the adhesive force measurement. The droplet has obvious elongation on the suspended surface fabricated with the thin glass substrate, compared with the other two surfaces. To clarify the procedure of the measurement, the approaching and detaching steps were denoted as i-v, respectively. Image ⅰ in Figure 2 B is obtained before the surface contacts with the water droplet. At this stage, no obvious deformation was noticed because of the large distance between the drop and the surface. When the droplet further approached the surface, the water droplet was attracted onto the suspended surface prepared with the thin glass substrate (image ii), while this process was not found in the other two samples. The obvious elongation on the drop indicates that an attraction force exerts on the droplet. Image ⅲ shows the snapshot when the surface keeps closing the droplet. The deformation of the droplet was mitigated with the increasing height of the stage. Image ⅳ is the moment before the separation between surface and droplet, which represents the magnitude of the surface's adhesion. Large deformation was observed on the thin suspended glass substrate, compared to the other two samples. Image ⅴ is the droplet after detaching from the surface. From these images, it is apparent that the substrate has a significant influence on the adhesive force of the impacted super-repellent surface. The details of force measured in this process are plotted in Figure 2 C. The adhesive force of the drop-impacted suspended super-repellent surface on the thin glass is nearly six-fold larger than that on the other two surfaces. Contact angle and roll-off angle measurement ( Table S1 ) also indicates an obvious increase in adhesion for the suspended super-repellent surface on the thin glass. Figure 2 Adhesion test of super-repellent surface (A) Schematics showing the process of a super-repellent surface approaching to and retracting from a hanged water drop in the adhesion test. (B) Snapshots of droplet interaction with impacted glass-substrate super-repellent surface placed on a stage (upper panel) and suspended in air (ⅰ-ⅴ). The bottom panel is the Si-substrate super-repellent surface ( We = 47.6). (C) Force-distance curves during the impacted super-repellent surface approaching to and retracting from a hanged droplet corresponding to (A). We analyze that the increased adhesion comes from the surface charge generated from water droplet contacting and separating. It has been demonstrated that the super-repellent surface was charged when a water droplet impacted the surface ( Sun et al., 2019 ). A droplet sitting on the charged super-repellent surface could be attracted by dielectrophoresis force, originated from the non-uniform electric field generated by the charged surface. The adhesive force for a water droplet (considering a spherical particle) with radius r 0 can be calculated by the following equation ( Pethig, 2010 ): (Equation 1) F a d h ≈ F D E P = 2 π r 0 3 ε r ′ ε 0 ε r ′ − 1 ε r ′ + 2 ∇ E n e t 2 where E net is electric field strength, ε r ' is the relative dielectric constant of water, and ε 0 is the vacuum dielectric constant. For a water droplet with a certain radius, the adhesive force depends on the distribution of electric field. Though the charge distribution on the super-repellent coating is identical after droplet impacting at the same condition, the expression of the charge, namely the electric field, is largely influenced by the substrate underneath the coating. The effect of substrate on surface adhesion To demonstrate the effect of the substrate on the surface adhesive force, we measured the roll-off angle of the droplet located on the charged surface. The droplet on the charged super-repellent surface fabricated with a Si substrate or placed on a metal stage easily rolls down because of the meager adhesive force. The suspended charged super-repellent surface with a thin glass substrate is very sticky to the droplet ( Figure 3 A). In order to clarify how substrate and stage influence the surface adhesion, we consider the effect of substrate and stage on surface charge expression. We have analyzed that the substrate polarization can reduce the net surface charge ( Q net ) on the super-repellent surface ( Sun et al., 2019 ). The substrate effect is presented in Figure 3 B. Surface charge generates and exists on super-repellent coating after droplet impacting. The substrate produces an opposite positive charge to reduce the net surface charge through electrostatic induction. The net charge after induction can be expressed as follows ( Sun et al., 2019 ): (Equation 2) Q n e t = Q − Δ Q p o l = Q − ( ε r s − 1 ) ε 0 A ∫ 0 L ∇ ⋅ E d L where Q is the original surface charge, ε r s is the relative dielectric constant of the substrate material, A is the cross-sectional area of polarization, E is the electric field due to the surface charge, and L is the thickness of the substrate. It is concluded that the net or effective surface charge depends on the dielectric constant and the thickness of the substrate. For a suspended thin glass substrate, the expression of surface charge is barely influenced because of the low dielectric constant and thickness. On the other hand, because of the large dielectric constant for Si substrate and the infinite dielectric constant and thickness of the metal stage, the charge on super-repellent surface fabricated with Si substrate or placed on a metal stage is almost completely screened so as not to express, resulting in a low adhesion. A similar result is reported on solid-solid contact electrification. The distant substrates influence the outcome of contact electrification because the image charges induced in conductive supports can feedback the original surface charges ( Siek et al., 2018 ). Since the surface adhesion is determined by the net surface charge according to Equation 1 , the substrate's dielectric property and thickness can be used to control the adhesion of the super-repellent surface. Figure 3 The effect of substrate on surface-droplet adhesion (A) Droplet states on charged super-repellent surface by impact of an 8 μL of water drop ( We = 47.6). (B) Schematics of the substrate's effect on surface adhesion through electrostatic induction. We have verified the substrate effect on adhesion of the charged super-repellent surface, using materials with various dielectric constant and thickness as the substrate of super-repellent surfaces. All surfaces are charged by the mean of water drop impact at the same condition. As shown in Figure 4 , the adhesive force of the charged surface decreases with the increase of the substrate's dielectric constant and thickness. The material properties are listed in Table S2 . The experiment result fits well with our theoretical analysis above. Figure 4 The adhesive force of charged super-repellent surface fabricated with different substrates ( We = 68.1) Reversibly tunable surface adhesion According to the basic principle of substrate effect on the expression of charged super-repellent surface, we are able to tailor the surface adhesion precisely and reversibly through a removable conductive substrate. To demonstrate the tunable adhesion on a charged surface, we moved a copper plate to the surface to influence the expression of the charge. A droplet is stick onto the charged position on a super-repellent surface made from a thin glass slide and will not roll off even the surface was placed vertically. When a copper plate approaches the backside of the impacted position on the super-repellent surface, the droplet rolls off because of electrostatic induction between the copper plate and surface charge ( Figure 5 A). This process is analyzed based on the model mentioned above. The conductive plate reduces the net surface charge, which causes adhesion reduction. The electrostatic induction process reduces the surface charge density due to the image charge on metal, and the induction distance ( D ) determines the reduction amount of surface charge ( Figure 5 A and Video S1 ). The schematics illustrate the electrostatic induction process in Figure 5 B. The positive charge generates at the side close to the negative surface charge and partly cancels the net charge. At the same time, the opposite charge forms at the far end of the conductor or bleed off to the ground. The distance between the metal plate and super-repellent surface determines the electrostatic induction intensity. Closer induction distance leads to less net charge. Figure 5 Electrostatic induction regulated surface-droplet adhesion (A) Snapshots of droplet rolling off when a copper plate closes to the surface. (B) Schematics of electrostatic induction between a conductor and surface charge to induce adhesion change. (C) Controllable adhesive force of the charged surface ( We = 40.8) through electrostatic induction at different distances. (D) The switch of high and low adhesion state through substrate effect. (E) Simulation of substrate effect on surface charge expression. Video S1. Droplet rolling off when a copper plate closes to the vertically placed surface, related to Figure 5 We analyze this process by simplifying the surface charge to point charge because the charged area is small. The electric field intensity ( E ) produced by the original surface charge Q at one point in metal is E = Q 4 π ε 0 ( D + d ) 2 , where d is the distance between the point to the metal surface which is a constant. The tiny thickness and dielectric constant of the super-repellent surface are negligible. When a metal plate is moved close to the charged surface, the electric field across the metal drives the motion of charge to produce an equivalent and heterogeneous electric field to balance the former. As a result of electrostatic induction, the opposite charge ( q ) generated on the metal surface is q = − Q d 2 ( D + d ) 2 . The net charge after induction is expressed as follows: (Equation 3) Q N e t = Q + q = Q − Q d 2 ( D + d ) 2 Thus, we can control the net surface charge by adjusting D . The electric field strength around the super-repellent surface depends on the net surface charge density, allowing us to tune the surface adhesion. The roll-off angle changing trend with D confirms this ( Figure S2 ). Figure 5 B shows that the adhesive force control from 20 μN to 90 μN is achieved by changing the induction distance. The lower limit of the adhesion (~20 μN) is larger than that on the pristine candle-soot-templated super-repellent surface. This is caused by the residue electric field after induction. In this way, the adhesion of charged super-repellent surface is reversible between high adhesion state and low adhesion state ( Figure 5 D). We also confirmed that other types of super-repellent surfaces can be used to regulate the adhesion. We have fabricated another two super-repellent surfaces by commercial spray coating of Ultra-Ever Dry and Glaco on 170-μm-thick glass substrates. The adhesion of these surfaces can still be enhanced in the same way of droplet impact ( Figure S3 ). The differences in the value of elevated adhesion among these superhydrophobic surfaces under the same impact dynamics are probably caused by the structure or roughness of the prepared surfaces. Since the charging process is rewritable and programmable ( Sun et al., 2019 ), we can even design the adhesion at the appointed position in a programmable way by controlling the water impact and electrostatic induction parameters. It should be noted that the maximum reversible adhesion was determined by the surface charge density. This is essentially different from the traditional electrowetting on the super-repellent surface. The magnitude of the adhesion in these techniques is mostly limited by the breakup of the Cassie-Baxter state ( Yang et al., 2019 ). The maximum adhesion reported here was attributed to the dense charge distributed on top of the super-repellent coating ( Figures 3 B and 5 B). To further demonstrate the influence of the movable conductive substrate on surface charge expression, we simulated the electric potential distribution around the charged surface with varied induction distances using COMSOL software. The parameters used in this simulation are listed in Table S3 . As shown in Figure 5 E, the actual electric field strength around the charged surface reduces as the conductive plate closes to the surface. The weakened electric field causes the reduction of surface adhesive force. Demonstration of droplet sorting and manipulation by tunable surface adhesion We demonstrate the potential application of tunable droplet adhesion on the super-repellent surface via electrostatic induction effect for droplet sorting, as sketched in Figure 6 A. Droplets are released to a super-repellent surface with a tilted angle of 15°. A baffle is used for guiding the droplet rolling path that the droplet travels across the charged area. A copper plate as a conductor is movable for adjusting the electrostatic induction distance. When we set different values for the induction distance (0–20 mm), the droplets rolling length is distinguished so as to realize droplet sorting ( Figure 6 B). The time-lapsed images of the sorting process on this super-repellent surface with tunable adhesion show the capacity of this device to separate droplets ( Figure 6 C). With the strongest electrostatic induction effect at the distance of 0 mm, the drop advanced at a certain distance and finally fell off the surface. In contrast, the advancing distance of the drop significantly decreased at the electrostatic induction distance of 20 mm, and the drop fell off the surface at a shorter distance. This device runs without requiring electric power and an electrode, which is beneficial for extensive applications. Moreover, we have demonstrated another application for selectively trapping and releasing droplets. As shown in Figures 6 D and Video S2 , the charged position on the super-repellent surface serves as the trapping positions of a three-water-droplet array with the help of high adhesion. Using a piece of metal approaching to the droplet underneath the substrate, the trapped droplets can be released in a programmable way under the effect of electrostatic induction. This droplet trap and release approach is useful in biomedical and bioanalysis process. Figure 6 Droplet sorting and manipulation (A) Schematic of droplet sorting process based on tunable surface adhesion. The device is titled at 15°. D presents the electrostatic induction distance. (B) Droplet-advancing distance as a function of electrostatic induction distance. (C) Time-lapsed images of droplet advancing at different electrostatic induction distances. D presents the electrostatic induction distance. (D) Droplet trap and release. The super-repellent surface on a thin glass substrate becomes adhesive to seize droplet after impact ( We = 34.0) and returns to low adhesion via electrostatic induction ( D = 0.5 mm). The surface is titled at an angle of 20°. Video S2. Droplet array trapped on the surface and released in sequence using a copper plate, related to Figure 6 Conclusion In conclusion, we found the charged super-repellent surface with a thin dielectric substrate is highly adhesive when it is suspended. On the other hand, the charged surface with a conductive substrate or placed on a metal stage behaves low adhesion. We analyzed the substrate effect on impacted surface adhesion based on surface charge and electrostatic induction. Further, we introduced a movable conductor to tune the adhesion of the impacted super-repellent surface. The distance between the conductive plate and the charged surface determines the amount of adhesive force on the basis of the theoretical analysis and electric simulation. Combining the dielectric substrate with a movable conductive plate, the adhesive force of the super-repellent surface can be easily regulated after charging by droplet impact. Droplet manipulation is demonstrated based on this adjustment method for surface adhesion. From a broader perspective, the reversible adhesion change illustrates that the surface charge does not dissipate but always exists at the position after water contact even when the substrate is a conductor or is placed on a stage. It is noteworthy that the charge on the super-repellent surface may have an imperceptible effect on the wetting experiment besides adhesion. Limitations of the study The increased surface adhesion comes from the generated surface charge, whose stability is influenced by the environmental humidity. We need to recharge the super-repellent surface if the charge decays, especially in high air humidity conditions. The adhesion can be tuned to extremely low when there is no surface charge or the charge is screened, but the surface charge density has an upper limit, leading to the surface adhesion cannot be infinite."
} | 6,475 |
24945282 | PMC4063634 | pmc | 7,637 | {
"abstract": "Navigation of cells to the optimal environmental condition is critical for their survival and growth. Escherichia coli cells, for example, can detect various chemicals and move up or down those chemical gradients (i.e., chemotaxis). Using the same signaling machinery, they can also sense other external factors such as pH and temperature and navigate from both sides toward some intermediate levels of those stimuli. This mode of precision sensing is more sophisticated than the (unidirectional) chemotaxis strategy and requires distinctive molecular mechanisms to encode and track the preferred external conditions. To systematically study these different bacterial taxis behaviors, we develop a continuum model that incorporates microscopic signaling events in single cells into macroscopic population dynamics. A simple theoretical result is obtained for the steady state cell distribution in general. In particular, we find the cell distribution is controlled by the intracellular sensory dynamics as well as the dependence of the cells' speed on external factors. The model is verified by available experimental data in various taxis behaviors (including bacterial chemotaxis, pH taxis, and thermotaxis), and it also leads to predictions that can be tested by future experiments. Our analysis help reveal the key conditions/mechanisms for bacterial precision-sensing behaviors and directly connects the cellular taxis performances with the underlying molecular parameters. It provides a unified framework to study bacterial navigation in complex environments with chemical and non-chemical stimuli.",
"introduction": "Introduction Living systems detect changes in the environment and try to find optimal conditions for their survival and growth. As one of the best-studied systems in biology, bacterial chemotaxis allows bacteria (such as Escherichia coli ) to sense chemical gradients and navigate toward attractant or away from repellent [1] – [4] . This gradient sensing strategy makes cells move unidirectionally toward the extreme levels of stimuli. However, for other natural factors (such as pH and temperature), the physiological optimum does not locate at the extreme but at some intermediate level in the respective gradient. To find such intermediate point, it requires a more sophisticated strategy, namely, precision sensing . Both pH taxis [5] – [9] and thermotaxis of E. coli \n [10] – [16] provide us inspiring examples of precision sensing. Amazingly, E. coli cells use the same signaling system to achieve these different navigation tasks. Different external signals are sensed by several types of transmembrane chemoreceptors, among which the Tar and Tsr receptors are the most abundant [17] . For chemotaxis, binding of attractant (or repellent) molecules to chemoreceptors triggers their conformational changes and affects the autophosphorylation of the histidine kinase CheA [3] , [4] . Analogous to ligand binding in chemotaxis, both temperature and pH affect the conformational state of chemoreceptors and hence the CheA activity. Regardless of the way of being activated, phosphorylated CheA transfers its phosphate group to the response regulator CheY in the cytoplasm. The phosphorylated CheY molecules (denoted as CheY-P) then bind to the flagellar motors, increase their probability of clockwise rotations, and cause E. coli to tumble. The resulted alternating run and tumble pattern can steer cells to advantageous locations. To make temporal comparisons of stimuli, a short-term memory (or adaptation mechanism) is required [4] , [18] , [19] . This is achieved by the slow methylation-demethylation kinetics, as catalyzed by two enzymes (CheR and CheB) that add and remove methyl group at specific sites of receptors, respectively. How does a bacterium navigate through its environment with different chemical and nonchemical cues by using the same signaling and motility machinery? How do bacterial cells make decisions under competing chemical and/or nonchemical signals? How accurately and reliably can bacteria find their favored conditions (such as the preferred temperature or pH)? and how do they tune their preference for precision sensing? We aim to address these questions under a unified theoretical framework, given that different taxis behaviors are based on the same sensory/motion machinery. To this end, we develop a multi-scale model which incorporates intracellular signaling pathways into bacterial population dynamics. The continuum population model reveals a simple theoretical result for the steady state cell distribution, which is found to be determined by the direction-dependent tumbling rates (transmitted through intracellular signaling pathways) as well as the dependence of the swimming speed on external factors (such as temperature). This new finding enables us to systematically analyze bacterial navigation in chemical, pH, and temperature gradients. From each application, we have made quantitative comparison with the available experimental data and have gained new insights about the mechanisms of bacterial taxis. Our general model can be extended to study bacterial migration in complex environments (e.g., with a mixture of chemical and nonchemical stimuli) and provide quantitative predictions to be tested by future population level experiments.",
"discussion": "Discussion In this paper, we have incorporated the intracellular signaling pathways into the bacterial population dynamics and developed a unified model to study bacterial navigation in chemical and nonchemical gradients. This model leads to a general result, which shows that the steady state cell density is determined by the accumulative effect of the direction-dependent tumbling rates as well as the local swimming speed. In the following, we discuss some of the specific findings and related possible future directions. The Push-Pull Mechanism for Precision Sensing From the population model, we can construct an effective potential function , which provides a useful scheme to visualize different cases of bacterial taxis, as summarized in Fig. 7 . The effective potential for chemotaxis decreases monotonically with the chemoattractant concentration and thus steer cells up the chemical gradient ( Fig. 7 ). Our application to pH taxis illustrates how the competition between two pH sensors (Tar and Tsr) determines the preferred pH for the wild-type cells expressing both Tar and Tsr: a push-pull mechanism here creates a potential well for bacteria to accumulate ( Fig. 7 ). In the case of E. coli thermotaxis, the push-pull mechanism is more subtle as the “push” and the “pull” are provided by the two sub-populations of Tar receptors with their methylation levels above or below the critical level ( ). This leads to a well-defined critical temperature where cells tend to accumulate ( Fig. 7 ). The push-pull mechanism is likely a general strategy for precision sensing. For example, it was found that two receptors, Tar and Aer, leads to a preferred level of oxygen for E. coli aerotaxis [38] , which may also be studied within our unified model. 10.1371/journal.pcbi.1003672.g007 Figure 7 Schematic illustration of the effective potential for chemotaxis, pH taxis, and thermotaxis. In the case of chemotaxis, decreases monotonically as the chemoattractant concentration increases. For pH taxis, decreases with pH for Tsr-only mutant cells and increase with pH for Tar-only mutant. Based on the push-pull mechanism, for the wild-type E. coli represents the balancing effect between Tar and Tsr, leading to a local minimum in the effective potential. In the case of thermotaxis, can be shifted by the effect of temperature-dependent swimming speed . It is, however, insensitive to other temperature effects such as the temperature dependence of motor response, , parameterized by . Robustness and Sensitivity \n E. coli chemotaxis has served as a model system in studying robustness of biochemical networks [34] , [39] , [40] . Bacteria exhibit thermal robustness in their chemotaxis network output by counterbalancing temperature effects on different opposing network components [34] . For example, the dissociation constant for the motor switch is observed to increase with temperature [35] . This effect balances the increase of the adapted CheY-P level with temperature such that the motor switch is able to operate in a narrow optimal range with ultrasensitivity [31] . This, however, raises a question for bacterial thermotaxis: do those temperature-sensitive factors, such as and , hinder the thermotactic performance? According to our model analysis, the steady state distribution of cells in a temperature gradient is mainly determined by two effects: the temperature-dependent swimming speed and the direction-dependent tumbling rates. The system is actually robust/insensitive to those instantaneous/local temperature-sensitive factors (e.g. ) which do not contribute to the tumbling rate difference at any spatial point. The insensitivity of thermotaxis to , as shown from our model, is a highly desirable feature of the system as it allows robust thermotaxis without sacrificing motor-level sensitivity. Navigation in Complex Environments In the natural environment, cells are often exposed to multiple chemical stimuli [41] . Our general model can be applied to study such cases (with a specific example discussed in Text S1 ). The density of cells subject to a multitude of chemical gradients shall be given by , where denotes the free energy contribution from all the chemical signals that are sensed by the type- receptors. Quantitative predictions can be made about how bacterial cells integrate and respond to mixed or competitive chemical signals and how their response changes with the composition and relative abundance of their sensors. More complex situations exist when different stimuli are interdependent and/or interfere with non-chemical factors. For example, the chemical environment can be modified through consumption and secretion by the bacteria, a dynamical process depending on the bacterial cell density [36] . In addition, temperature can change the metabolic rates of bacterial cells and create temperature-dependent chemical (nutrients, oxygen) gradients. How cells navigate under such complex circumstances and how such behaviors lead to survival/growth benefits remain unclear. Our model can be extended to study those phenomena and help address those fundamental questions. In sum, the work presented here provides a general model framework to study population behaviors in the presence of both chemical and non-chemical signals based on realistic intracellular signaling dynamics."
} | 2,675 |
22859206 | null | s2 | 7,638 | {
"abstract": "Land plants associate with a root microbiota distinct from the complex microbial community present in surrounding soil. The microbiota colonizing the rhizosphere (immediately surrounding the root) and the endophytic compartment (within the root) contribute to plant growth, productivity, carbon sequestration and phytoremediation. Colonization of the root occurs despite a sophisticated plant immune system, suggesting finely tuned discrimination of mutualists and commensals from pathogens. Genetic principles governing the derivation of host-specific endophyte communities from soil communities are poorly understood. Here we report the pyrosequencing of the bacterial 16S ribosomal RNA gene of more than 600 Arabidopsis thaliana plants to test the hypotheses that the root rhizosphere and endophytic compartment microbiota of plants grown under controlled conditions in natural soils are sufficiently dependent on the host to remain consistent across different soil types and developmental stages, and sufficiently dependent on host genotype to vary between inbred Arabidopsis accessions. We describe different bacterial communities in two geochemically distinct bulk soils and in rhizosphere and endophytic compartments prepared from roots grown in these soils. The communities in each compartment are strongly influenced by soil type. Endophytic compartments from both soils feature overlapping, low-complexity communities that are markedly enriched in Actinobacteria and specific families from other phyla, notably Proteobacteria. Some bacteria vary quantitatively between plants of different developmental stage and genotype. Our rigorous definition of an endophytic compartment microbiome should facilitate controlled dissection of plant-microbe interactions derived from complex soil communities."
} | 451 |
30214432 | PMC6125326 | pmc | 7,643 | {
"abstract": "Microbial communities composition is largely shaped by interspecies competition or cooperation in most environments. Ecosystems are made of various dynamic microhabitats where microbial communities interact with each other establishing metabolically interdependent relationships. Very limited information is available on multispecies biofilms and their microhabitats related to natural environments. The objective of this study is to understand how marine bacteria isolated from biofilms in the Mediterranean Sea interact and compete with each other when cultivated in multispecies biofilms. Four strains ( Persicivirga mediterranea TC4, Polaribacter sp. TC5, Shewanella sp. TC10 and TC11) with different phenotypical traits and abilities to form a biofilm have been selected from a previous study. Here, the results show that these strains displayed a different capacity to form a biofilm in static versus dynamic conditions where one strain, TC11, was highly susceptible to the flux. These bacteria appeared to be specialized in the secretion of one or two exopolymers. Only TC5 seemed to secrete inhibitory molecule(s) in its supernatant, with a significant effect on TC10. Most of the strains negatively impacted each other, except TC4 and TC10, which presented a synergetic effect in the two and three species biofilms. Interestingly, these two strains produced a newly secreted compound when grown in dual-species versus mono-species biofilms. TC5, which induced a strong inhibition on two of its partners in dual-species biofilms, outfitted the other bacteria in a four-species biofilm. Therefore, understanding how bacteria respond to interspecific interactions should help comprehending the dynamics of bacterial populations in their ecological niches.",
"conclusion": "Conclusion This study highlights three main observations regarding bacterial interactions in multispecies biofilms. First, most of the marine strains inhibited each other in the two-, three-, and four- species biofilms. Second, one of the strain was able to benefit from one of its partners in the two- and three- species biofilms. In dual-species biofilms, they were able to produce an additional matrix compound. Third, the bacterial strain that was able to induce the strongest inhibition on several of its partners in dual-species biofilms, while being inhibited in a four-species biofilm, outfitted the other strains. These results confirm the importance of studying competitive bacterial interactions in multispecies biofilms and conditions close to the ones encountered in their natural environment to unravel the complexity of dynamics of bacterial population in their microhabitats.",
"introduction": "Introduction Interspecies interactions appear to have a preponderant role in natural ecosystems. Indeed, the composition of microbial communities, which populate most environments, is largely shaped by interspecies competition or cooperation. Environmental ecosystems are made of various dynamic microscale microhabitats, where microbial communities preferably interact “as metabolically interdependent groups” ( Zelezniak et al., 2015 ; Roder et al., 2016 ). Bacteria colonize microhabitats compatible with their physiologic and metabolic needs, which depend on their neighboring bacteria and this will influence the spatial structure of the community ( Stubbendieck et al., 2016 ). According to Roder et al. (2016) , microscale bacterial interspecies interactions studies are the “missing bridge” between mono and dual species studies and the large-scale investigations focusing on the overall diversity of a community. Microscale interactions studies have the advantage of bringing information on microhabitats and spatial organization as well as bacterial interspecies interactions. Interspecies interactions may also result in different microbial functions and abilities (reviewed in Roder et al., 2016 ). Very limited information except for the human oral cavities, where multispecies studies are the most abundant ( Filoche et al., 2004a , b ; Kuboniwa et al., 2006 ; Kolenbrander et al., 2010 ; Bloch et al., 2017 ), are available on microhabitats related to the natural environment ( Burmolle et al., 2006 ; Kuboniwa et al., 2006 ; Ren et al., 2015 ; Hansen et al., 2017 ; Liu et al., 2017 ). Studying changes in the community composition over the time or what is produced by the population can provide information on the ability of each individual to establish itself and survive in their microhabitat. As most biofilm communities are composed of multiple different bacteria living in close proximity, embedded in extracellular polymeric substances such as polysaccharides, proteins, nucleic acids, lipids, studying multispecies or multi-organisms biofilms, appears therefore a relevant challenge to take up with the goal to understand how the different populations interact with each others at the microscale level. Numerous obstacles exist in studying mixed biofilms such as labeling the different populations, in particular when they are not amenable to genetic manipulations, or identifying what is produced and by who, interpreting why one strain is better fit than another. Most studies on multi-species biofilms (with four or more species) have recently emerged in the last years but remain overall quite rare ( Lee et al., 2014 ; Ren et al., 2015 ; Sherry et al., 2016 ; Bloch et al., 2017 ; Hansen et al., 2017 ; Liu et al., 2017 ). Many studies have used different variants of the same strains or mathematical models and flow systems ( Momeni et al., 2013a , b ; Lee et al., 2014 ; van Gestel et al., 2014 ; Liu et al., 2017 ), whose flux acting as an additional external factor with a potential influence on the interactions, can be appropriate in certain studies but can restrict quickly space for the organisms on the surface and therefore their spatial organization ( Lee et al., 2014 ; van Gestel et al., 2014 ; Liu et al., 2017 ). Multiple species approaches with four or more strains, with a focus on only one or two of the partners, have also been performed, which can bring interesting information on the targeted strains ( Bloch et al., 2017 ; Hansen et al., 2017 ). Only a few studies following the fate of four (or more) bacterial species in biofilms in interaction, quantitatively ( Burmolle et al., 2006 ; Ren et al., 2015 ) and on their spatial organization ( Lee et al., 2014 ; Liu et al., 2017 ) are available. To our knowledge, only one dealt with marine bacterial isolates ( Burmolle et al., 2006 ). Our study focuses on the comprehension of the interaction within multispecies biofilms of four bacterial strains that have been isolated from immersed biofilms recovered from the Toulon bay (France). The selection of these strains for this study was based on their different phenotypic traits (such as motility, hydrophobicity, adhesion to a surface) and ability to form a biofilm in vitro ( Camps et al., 2011 ; Brian-Jaisson et al., 2014 ; El-Kirat-Chatel et al., 2017 ; Favre et al., 2017 ). The objective of this work is to understand how marine bacteria isolated from biofilms in the Mediterranean Sea interact and compete with each other when cultivated together. We investigated whether the outcome of mono or dual species biofilms between these four marine strains cultivated in artificial sea water could give some information on the behaviors they would have in three or four species biofilms. We hypothesized that even if some strains have been described as good or poor biofilm producers in mono-species biofilms, the outcome in a multispecies biofilm, which is not easily predicable, would give valuable information on their ability to colonize and survive in their microhabitats.",
"discussion": "Discussion In this study, we decided to pursue the comparison between the different biofilm formation abilities of 4 of the marine strains previously isolated from the Mediterranean sea ( Camps et al., 2011 ; Brian-Jaisson et al., 2014 ), with the objectives to understand to which extent their capacity of adhesion and biofilm formation are different in other conditions (low-nutrient medium, glass surfaces…) and how they could interact and compete with each other when cultivated in multispecies biofilms. In order to get closer from the natural marine environment and to induce metabolic interactions between the bacterial strains, artificial sea water was used for all the experiments. To set up multispecies biofilms, we selected four strains with different phenotypical particularities and abilities to adhere and to form biofilms ( Brian-Jaisson et al., 2014 ; El-Kirat-Chatel et al., 2017 ), hypothesizing that even if in some conditions bacteria appear to produce more biofilms than others, the outcome in a multispecies biofilm is not easily predictable, due to the existence of multiple types of interactions (antagonistic, synergetic…). TC4 a newly identified species of P. mediterranea , and TC5 a Polaribacter strain, characterized by a higher hydrophobicity, both non-motile rods, produced small biofilms when cultivated in microplates and rich media. Two motile bacilli belonging to the Shewanella genus, TC10 and TC11 appeared to produce more biofilm in the same conditions ( Brian-Jaisson et al., 2014 ). In addition, TC11 formed an important biofilm when inoculated in ASW on glass surface at high OD 600 nm , compared to TC5 and TC10 ( El-Kirat-Chatel et al., 2017 ). However, using Atomic Force Microscopy (AFM), TC11 appeared to display a phenotypic heterogeneity in the very early stage of the adhesion in sharp contrast with TC5 or TC10, whose individuals within the bacterial population presented more homogeneous adhesion forces ( El-Kirat-Chatel et al., 2017 ). In this study, we show that the strain, which adheres and covers the most the surface when in mono-species and static conditions is a strain initially described as a poor biofilm producer, P. mediterranea TC4 ( Brian-Jaisson et al., 2014 ). Overall, the development of bacterial biofilms of most strains within the multi-species biofilms appears to be inhibited compared to the development of their respective single-species biofilm, with the exception of TC4. In the two- and three-species biofilms, this strain is the only one able to benefit from its interaction with one of its partners, here Shewanella sp. TC10 ( Figures 5IIB , 7 ). In the four-species biofilm, Polaribacter sp. TC5 outfits all the other strains, including TC4, but its biofilm biovolume is still below the one measured in its mono-species biofilm ( Figure 8 ). In contrast, the strain which appears to be overall the most impacted is Shewanella sp. TC11. Indeed, in the dual-species biofilms, TC11 appears to be impacted negatively by all the strains and to be outfitted by its partners in the three- and four-species biofilms. However, since none of the TC11 cells have completely disappeared at 48 h, it is possible that due to its potential phenotypical heterogeneity ( El-Kirat-Chatel et al., 2017 ), presumably allowing an increased bacterial fitness, the cells of this strain could become a tolerant slow-growth subpopulation and/or could play a role in the overall growth fitness and spatial organization of the multispecies biofilm as it has been recently shown ( Grote et al., 2015 ; Liu et al., 2017 ). Specific sub-population of persister bacteria corresponding to phenotypic variants, which emerge under stressful conditions such as nutrient limitation, antibiotic pressure, or transition from planktonic to biofilm state, may be still present in small proportions in the biofilm. On another hand, TC11 might simply be less resistant to harsh or competitive conditions such as in multispecies biofilms than the other strains. In our study, we only observed the initial stage of the biofilm development in relation to the initial interactions. A longer incubation time in ASW might have given more insights on bacterial competition and spatial organization. However, mechanisms explaining how interspecies interactions affect spatial organization are poorly understood as this may correspond to complex and multiples dynamics sequential events involving many external parameters. Growth of some strains might be initially affected by both cooperative and competitive interactions, but this interrelationship might change over time with the development of the community in response to both cell–cell interactions and environmental factors ( Liu et al., 2016 ). In our case, the only strain which appears to secrete molecule(s) with an anti-biofilm activity is Polaribacter sp. TC5 ( Figure 4 ). We show that the TC5 supernatant inhibits the Shewanella sp. TC10 biofilm but not the one of Shewanella sp. TC11, although TC5 is able to inhibit both Shewanella in their dual-species biofilms ( Figures 5IID,E ). This suggests that in dual-species biofilms, secreted molecule(s) in the extracellular medium of TC5 could be involved in the TC10 inhibition, while a direct cell–cell interaction might also be required for the TC11 inhibition. Therefore, in our experiments, TC5 is potentially able to inhibit the two Shewanella strains TC10 and TC11 biofilms through different mechanisms. Whether this secretion has helped TC5 to outcompete the others strains in the four-species biofilm in particular at 48 h, is not known ( Figure 8 ). Some bacteria may secrete enzymes that could interfere with mechanisms involved in this secretion or counteract the secreted effectors and therefore could interfere with a specific population beneficial phenotype (reviewed in Sanchez-Vizuete et al., 2015 ; Wen et al., 2014 ). In addition, direct or physical interactions between bacteria, which involve for instance horizontal gene transfer, known to improve adaption and to originate new ecological populations (reviewed in Wiedenbeck and Cohan, 2011 ), could have taken place between the isolates, inducing different phenotypical consequences on the receiver(s) ( Sanchez-Vizuete et al., 2015 ). Although, we have tried repeatedly to transform the four strains with plasmids carrying GFP without success, except for TC10, this does not mean that gene transfer cannot occur in these biofilms conditions. It is interesting to note that TC4 and TC5 secrete mainly eDNA in their matrix in sharp contrast with TC10 and TC11 and that in the TC10 and TC4 dual-species biofilms, eDNA was still present. Overall, how these mechanisms take place within multispecies biofilms are difficult to decipher and poorly studied up to now. In our study, TC4 and TC10, produce a newly secreted compound (exopolysaccharide made of mannose and glucose residues), that is not present in their respective mono-species biofilm. This compound may be responsible for the TC4 increased biofilm, as it has been previously shown with other bacteria ( Zogaj et al., 2001 ). Even when TC11 is added to the dual-species biofilm of TC4 and TC10, the inhibitory effect of TC11 observed independently in the dual-species biofilms toward TC10 and TC4, does not affect the beneficial interactions between TC10 and TC4 in the three-species biofilm. Cooperative phenotypes could include the production of exopolymers in the biofilm matrix, which can enhance biofilm-related properties, such as resistance or growth. Secreted molecules can also be considered as cooperative public goods as they can be utilized by bacteria that are not producing them. The mechanisms by which public goods-producing bacteria avoid exploitation in biofilm is not fully understood. Public goods usually benefit nearby clonemates and factors such as restricted diffusion of nutrients, inoculation under flow or at low density are benefiting the public goods producing bacteria ( Drescher et al., 2014 ; van Gestel et al., 2014 ). While studies on the mechanisms involved in competition or synergy are rare in multispecies biofilms, a transcriptomic study focusing on gene expression analyses in multispecies biofilms involving Xanthomonas retroflexus , has recently shown that the majority of the genes only regulated in the four strains biofilm were downregulated. Interestingly, this suggests that X. retroflexus seems to deprioritize vital functions for mono species cultures, as partners may share products from energy-consuming pathways in the four-species biofilm ( Hansen et al., 2017 ). Therefore, metatranscriptomic approaches are interesting tools that can help deciphering some of the interaction mechanisms involved multispecies biofilms."
} | 4,124 |
35304537 | PMC8933433 | pmc | 7,644 | {
"abstract": "Spike-timing-dependent plasticity(STDP) is a biological process of synaptic modification caused by the difference of firing order and timing between neurons. One of neurodynamical roles of STDP is to form a macroscopic geometrical structure in the neuronal state space in response to a periodic input by Susman et al. ( Nat. Commun. \n 10 (1), 1–9 2019), Yoon, & Kim. Stdp-based associative memory formation and retrieval. arXiv:2107.02429v2 (2021). In this work, we propose a practical memory model based on STDP which can store and retrieve high dimensional associative data. The model combines STDP dynamics with an encoding scheme for distributed representations and is able to handle multiple composite data in a continuous manner. In the auto-associative memory task where a group of images are continuously streamed to the model, the images are successfully retrieved from an oscillating neural state whenever a proper cue is given. In the second task that deals with semantic memories embedded from sentences, the results show that words can recall multiple sentences simultaneously or one exclusively, depending on their grammatical relations.",
"introduction": "Introduction Spike-timing-dependent plasticity(STDP) is a biological process of synaptic modification according to the order of pre- and post-synaptic spiking within a critical time window 3 – 5 , and considered to be critical for understanding the cognitive mechanisms such as temporal coding 6 – 8 , and the formation of associative memory 9 , 10 . In our separate work 2 , we analyzed an STDP-based neural model and showed that the model can associate multiple high-dimensional memories to a geometric structure in the neural state space which we call a memory plane . When exposed to repeatedly occurring spatio-temporal input patterns, the neural activity based on STDP transforms the patterns into the corresponding memory plane. Further, the stored memories can be dynamically revived with macroscopic neural oscillations around the memory plane if perturbed by a similar stimulus. The presence and the function of the memory plane in the neural networks have caught attention in Ref. 1 , where it has been proposed that STDP can store transient inputs as imaginary-coded memories. In this work, we further emphasize a practical aspect of the memory plane, showing that it can play a central role in storing, retrieving, and manipulating structured information. Using the theoretical works in Ref. 2 , we intend to integrate an analytic and an implementation level description of the neural memory process based on the memory plane that is capable of handling high dimensional associative data. In this work, we propose that a STDP-based memory model, combined with a proper encoding scheme, can store and retrieve a group structured information in the neuronal state space. Among a number of schemes for encoding compositional structure that have been proposed over the last few years, we adopt Tensor Product Representation(TPR) 11 . TPR is a general method for generating vector-space embeddings of internal representations and operations, which prove to contain a variety of structural information such as lists of paired items, sequences and networks. We show that the STDP-based memory model with TPR can naturally provide a mechanism for segmenting continuous streams of sensory input into representations of associative bindings of items: first, we demonstrate an auto-associative memory task with a group of images. While the images are sequentially streamed into the system for storage, the corresponding information is internally stored in the connectivity matrix. Then the whole group of the images can be dynamically retrieved from the oscillating neural state, when the system is perturbed by a memory cue which is similar to any of the original images. In the second task for semantic manipulation, we use multiple semantic vectors to represent a sentence as a composite of words. Once several sentences are stored in the system via such semantic vectors, a single word can recall multiple sentences simultaneously or one exclusively, depending on their grammatical relations. This implies that the proposed method provides an alternative bio-inspiring approach to process multiple groups of associative data with composite structure.",
"discussion": "Discussion There is now substantial evidence accumulated that neural oscillations are related to memory encoding, attention, and integration of visual patterns 14 – 16 . In Ref. 1 , the idea has been proposed that memories constitute stable dynamical trajectories on a two-dimensional plane in which an incoming stimulus is encoded as a pair of imaginary eigenvalues in the connectivity matrix. We extended such an idea further through a specific memory system that can process a group of high dimensional associative data sets, by using the exact analytic relation between the inputs and the corresponding synaptic changes shown in Ref. 2 . While the Hopfield network 17 retrieves static single data as a fixed point, the proposed model explores multiple data sets through neural oscillations. Compared to other neural-based models capable of conducting explicit and perfect retrieval of grouped data such as 18 – 20 , the model proposed in this work has the novelty of using a simple and continuous framework to reconstruct a group of multiple data in the general vector form. Moreover, the model produces the output through neural oscillations in reaction to an external cue, showing a potential link to a real memory process occurring in the brain. We encode the input data with tag vectors based on the tensor representation, which has been proposed as a robust and flexible distributed memory representation 11 , 21 – 24 . This preprocess enables us to efficiently retrieve the stored data and, in addition, to deal with the composite structure in the data set. The ability to process associate multiple data sets with composite structures is essential in natural language understanding and reasoning. It has been shown that the proposed model can handle multiple sentences that describe distinct situations and can selectively allow the recall cue to arouse a group of associative memories according to its semantic relevance. From a practical perspective, our results suggest an alternative approach for a memory device. The conventional von Neumann architecture is non-scalable and its performance is limited by the so-called von Neumann bottleneck between nonvolatile memories and microprocessors. On the other hand, operating data with artificial synapses is benefiting from a parallel information process consuming a small amount of energy per synapse. Moreover, conventional digital memory systems convert the inputs to a binary code and save it in a separate storage device, likely destroying the correlation information by such physical isolation. The proposed model is based on continuous dynamical systems and provides a simple and robust approach to deal with a sequence of associative high-dimensional data. Processing data in the continuous and distributed system results in the plastic storage of the correlated information in the synaptic connections. In this work, we used a continuous model based on the average of local spiking activities of neurons. The model can be seen as a continuous approximation of Spiking Neural Network(SNN) which has been recognized as a promising arhitecture for bio-inspired neuromorphic hardware. There have been several studies showing the dynamical correspondence between SNNs and their firing-rate approximations including Wilson–Cowan model 25 – 27 . However, reproducing the memory process in this paper through SNN is substantial yet interesting challenge in practice, considering it requires establishing a proper conversion between a series of high dimensional data and spiking patterns."
} | 1,964 |
34620710 | PMC8521717 | pmc | 7,646 | {
"abstract": "Significance Marine dissolved organic matter, which originates from phytoplankton, holds as much carbon as Earth’s atmosphere; yet, the biological processes governing its fate are primarily studied under idealized laboratory conditions or through indirect measures such as genome sequencing. In this work, we used isotope labeling to directly quantify uptake of complex carbon pools from the two primary sources of marine organic carbon (diatoms and cyanobacteria) by a natural microbial community. Our data show that carbon pools are partitioned into distinct microbial lineages whose physiological properties and resource acquisition strategies match the chemical nature of their preferred substrates. Our results provide ecological and functional insights into the patterns of microbial community structure changes that occur during marine phytoplankton blooms.",
"conclusion": "Conclusion Contemporary oceans contain a highly heterogeneous pool of phytoplankton-derived DOM that varies substantially in quality and quantity over space and time ( 1 ). Variability in the type and timing of primary production is postulated to represent an important bottom-up driver of genotypic and phenotypic diversity in coexisting heterotrophic microorganisms ( 33 ), especially during phytoplankton blooms where substrate-controlled succession of taxa may hold integral control over the fate of fixed carbon ( 26 ). The results of our study support and extend our understanding of microbe–DOM interactions by demonstrating that separate pools of DOM from diatoms and cyanobacteria collected during simulated bloom phases of growth (exudates) and senescence (lysates) inordinately support the activities of taxonomically distinct subsets of the heterotrophic microbial community. Our approach using proteomic SIP allowed for the identification of newly synthesized proteins that represent rapid (<15 h) responses to DOM addition, revealing which taxonomic groups and metabolic functions were most active in assimilating the four distinct DOM pools before any observable shifts were recorded by unlabeled metaproteomic or metagenomic analyses. The strong signal of partitioned resource assimilation between phylogenetically distinct lineages allowed us to characterize the role of different heterotrophs in turning over each of the simulated bloom DOM pools. In a broad view, populations of Bacteroidetes are adapted to using relatively carbon-rich, high-molecular-weight DOM compounds that are more common in the lysates from diatom cells, while Proteobacteria lineages show more variability in their resource specialization, with numerically abundant Alphaproteobacteria, such as SAR11 and Roseobacter-clade populations, assimilating a vast majority of bioavailable cyanobacteria exudate DOM but with different apparent carbon use efficiencies. Based on these data we estimate the lineage-specific rates of carbon assimilation of these four DOM pools and conclude that these distributed resource preferences are crucial for efficient turnover (i.e., assimilation or respiration) of DOM during a bloom ( 26 , 48 ). Therefore, changes to the origin and composition of DOM inputs under future ocean conditions, such as increased CO 2 concentrations and higher temperatures, may have predictable consequences for global carbon cycling and nutrient flux rates through the microbial loop ( 69 , 70 ). For example, a Coupled Model Intercomparison Project (Phase 5) model suggests future surface oceans will be more stratified ( 71 ), indicating a potential for cyanobacterial blooms to become more prevalent due to their tolerance of higher temperatures and more oligotrophic conditions, while diatom blooms decrease due to reliance on cooler, more turbulent, and nitrate-rich waters. When considering this scenario in light of our results, the surface ocean could be expected to experience increased Alphaproteobacteria activity due to increased cyanobacterial exudation and a correspondingly lower contribution of Bacteroidetes activity due to the reduction of new diatom-derived DOM. Though our data does not provide direct insights into carbon use efficiencies of the taxa observed here, such a shift toward an Alphaproteobacteria-dominated community could depress carbon sequestration via the microbial carbon pump ( 72 ) by favoring organisms, such as Pelagibacteria spp., that have more tightly coupled and lower-efficiency carbon metabolisms ( 64 ). Overall, the different metabolic strategies and adaptations used by coexisting surface ocean heterotrophic populations that consume phytoplankton DOM dictate carbon use efficiency at the community level. This distributed community metabolism not only allows taxa to coexist by decreasing direct resource competition but also indicates that trophic transfer and remineralization rates in the microbial loop are strongly coupled to DOM properties. Experiments that provide complex, naturally occurring substrates to resident microbial communities and track the fate of carbon and nutrients, as well as the activity and ecophysiological characteristics of microbial populations, will be crucial to the ongoing effort to mechanistically connect marine microbial community dynamics to global biogeochemical cycles.",
"discussion": "Discussion A significant fraction of newly fixed marine DOM flows through heterotrophic cells in the microbial loop, which control its subsequent release as CO 2 through respiration or retention in food webs as biomass ( 32 ). The partitioning of the complex DOM pool among hundreds of co-occurring populations is a key mechanism controlling marine biogeochemical cycling ( 16 – 18 , 26 , 33 – 38 ). In this work, we combine the approach of proteomic SIP with paired metagenome sequencing and binning to measure partitioning of complex marine DOM into the population-specific biomass of a natural marine microbial community. Our results show that DOM composition has a strong bottom-up control in assembling the active subset of the total community, which is generally composed of populations with derived, specialized metabolic and ecophysiological traits. This implies that different lineages of abundant heterotrophic microbes can coexist in part due to differentiated resource use capabilities and that the distributed nature of metabolic strategies among active populations in the community facilitate the efficient turnover of the highly heterogeneous pool of DOM available throughout a phytoplankton bloom. In accordance with the largely labile nature of fresh phytoplankton-derived DOM ( 20 ), all four 13 C-labeled substrate pools were widely assimilated by the coastal heterotrophic community. Despite the fundamentally different character of the four substrates, the 15-h incubation periods led to high label frequency and 13 C-enrichment of all treatment metaproteomes (12.1 ± 3.0%; 54.4 ± 15.9%). The speed and extent of labeling observed here supports previous results using isotopically labeled model substrates ( 39 ) and phytoplankton-derived DOM ( 36 ). In our work, substrate addition did not significantly shift the taxonomic or functional compositions of metaproteomes recovered before versus after incubation. Rather, substrate-induced changes to the taxonomic composition of metaproteomes were only detected when comparing the initial metaproteome to the newly synthesized ( 13 C-labeled) metaproteome. These results highlight the sensitivity of the proteomic SIP method to detect rapid responses to environmental change prior to the large-scale shifts in biological activity that can be detected with unlabeled approaches (e.g., metagenomics), which are dependent on physiological responses such as genome replication and cell division. This observation has been noted elsewhere when measuring microbial responses to DOM inputs, where changes to protein expression (i.e., modulation of community function) occur before any detected changes in community taxonomic composition ( 40 ). Population-Level Substrate Preferences Are More Similar with Increasing Phylogenetic Relatedness. Shifts in taxonomic composition of labeled metaproteomes in each treatment could be attributed to different responses by common marine heterotrophic bacteria, confirming general patterns found in previous studies ( 41 – 44 ). The vast majority of peptides from labeled metaproteomes (>85%) were annotated to the marine and coastal microbial lineages Actinobacteria, Archaea, Alpha-, Gamma-, and Betaproteobacteria, and Bacteroidetes. All four DOM pools were assimilated at some level by all of these lineages, but the magnitude and frequency of protein labeling in each lineage varied significantly across treatments. Importantly, resource assimilation patterns were similar among populations belonging to the same taxonomic class but distinct between classes, corroborating previous findings that responses to model DOM compounds are typically conserved at broad phylogenetic resolution ( 17 , 22 ). This observation supports a model in which the strength of resource competition between heterotrophic populations is inversely related to their phylogenetic distance ( 45 ), implying that selection pressure exerted upon closely related taxa in the coastal ocean does not act on DOM utilization traits. Rather, as has been supported previously, allopatry and biogeography may be more important for generating species- or strain-level diversity in natural environments ( 46 , 47 ), while higher-level diversity is maintained by divergent resource niches that help reduce competitive overlap. Although the four substrate treatments appeared to strongly and reproducibly select for different sets of active taxa, individual population proteomes typically showed the same response, regardless of DOM treatment: proportional increases in synthesis of ribosomal proteins and decreases in substrate transporters after DOM amendment. This growth-prioritization response was exacerbated when the DOM was a preferred resource (i.e., when the overall proteome enrichment of the population was highest). From this pattern, we purport that the observed shift in metaproteome functional structure in each treatment is predominantly driven by a subset of “responder” populations that rapidly assimilate their preferred substrate into biomass when it becomes available, rather than being driven by a community-wide shift in which all populations alter their proteome in response to newly available resources. Differences in DOM Assimilation between Highly Abundant Taxa. Fitting our data into this theoretical framework, a general picture of how resources are distributed among taxa in the marine microbial loop emerges. Lineages of Bacteroidetes, represented predominately by a few major Flavobacteriales taxa in our samples, preferentially assimilate DOM components derived from diatom lysates that are probably rapidly available upon cell death from sloppy feed, viral lysis, or mass senescence in the terminal phase of a bloom. On the other hand, lineages of Alphaproteobacteria, represented primarily by Pelagibacterales, Rhodobacterales, and Rhodospirillales taxa, assimilate mostly cyanobacteria- rather than diatom-derived substrates and also specialize on the exuded fraction of DOM that is more consistently available during nominal phytoplankton growth or in the early stages of a bloom cycle. Despite representing ∼12% of unlabeled metaproteomes, Gammaproteobacteria lineages were not highly competitive in assimilating substrates in our experiments. For lineages such as Oceanospirillales and Cellvibrionales, which did demonstrate moderate labeling, their uptake patterns diverged from those of both the Alphaproteobacteria and Bacteroidetes lineages by exhibiting higher enrichment on diatom- compared to cyanobacteria-derived DOM and nearly twofold higher enrichment on exudates than lysates. Considering the magnitude of total assimilation accounted for by these three prevalent lineages, their strong preferences and competitive abilities for assimilating different resources are likely to be essential for the overall efficiency of DOM cycling in marine ecosystems ( 48 ), especially throughout the phases of a mixed-species phytoplankton blooms ( 6 ). Protein Expression and Ecophysiological Evidence for Bacteroidetes Lysate DOM Resource Preference. Combining metagenomics and metaproteomics with our SIP approach allowed for the exploration of how substrate preferences of active populations were related to their metabolic and ecophysiological characteristics. Bacteroidetes populations, which were most competitive in assimilating diatom lysate, almost exclusively expressed TBD membrane transport proteins among all identified substrate uptake systems in the metaproteome. These function by binding polymeric and carbon-rich molecules making up the structural and storage components of diatom cellular biomass ( 6 , 30 , 49 – 51 ). Not only were TBD transporters abundant within the genomes and proteomes of this lineage, but a significant proportion of newly synthesized proteins (i.e., 13 C-enriched proteins) from Flavobacteriales populations appear to function as part of the sus- like polysaccharide system, which acts to recognize and degrade glycans ( 52 ) and is involved in competitive uptake of phytoplankton carbohydrates ( 53 , 54 ). These results suggest a metabolic program within Bacteroidetes taxa that specializes on carbon-rich high-molecular-weight DOM, resulting in these taxa being most competitive when this substrate type is present and poorly competitive when it is not (e.g., in cyanobacteria exudate). Physiological signatures of this specialization pattern on C-rich DOM was also borne out in the estimated carbon:nitrogen requirement of Bacteroidetes nucleotides and amino acids, which was higher than other active taxa in the community we sampled. Also of note and exclusive to the Bacteroidetes proteomes was the detection of peroxiredoxin proteins, which provide protection against oxidative stress. Both peroxiredoxin enzymes and biopolymer transporters assigned to the Bacteroidetes became enriched in all substrate treatments, except for the cyanobacteria exudate treatment, implying that cells of this lineage are particularly well-suited for growth in the phycosphere, where oxygen levels and mucilage will be highest. The synthesis of these findings generally agrees with previous observations that Bacteroidetes populations increase in relative abundance and cell-specific activity in the middle and late phases of phytoplankton blooms and encode a large number of specialized enzymes allowing for the degradation and assimilation of polysaccharides ( 17 , 26 , 53 , 55 – 58 ). Our data further suggest that lysate DOM, particularly those derived from diatoms, stimulate higher cellular growth rates in Bacteroidetes taxa relative to other co-occurring populations and other substrates we tested, allowing this lineage to translate their resource use strategy into growth and division in a suitable environment. This hypothesis was also supported by examining the shift in proportional representation of functions in the labeled metaproteomes from each treatment compared to the control incubations; when diatom lysate was amended, the majority of substrate-derived (i.e., 13 C-labeled) ribosomal proteins and transcription/translation factors synthesized by the community were annotated to Bacteroidetes populations. When contextualizing proteome enrichment and cell abundance of Bacteroidetes as DOM carbon uptake rates, the ecological role of this lineage was salient, with ∼80-fold higher carbon uptake rates of diatom lysate compared to cyanobacteria exudate and over double the assimilation rate of diatom lysate compared to the other two major lineages. Protein Expression and Ecophysiological Evidence for Alphaproteobacteria Exudate DOM Resource Preference. In contrast to the Bacteroidetes, Alphaproteobacteria populations expressed mostly ABC and TRAP membrane transport proteins that target a wide range of polyamines, nucleosides, amino acids, short chain fatty acids, and other uncharacterized small molecules. Phytoplankton exudates are relatively rich in these compounds, and DOM exuded by cyanobacteria in particular can contain high concentrations of polyamines and organic osmolytes ( 31 , 59 , 60 ). Our observation that three-quarters of 13 C-enriched peptides in cyanobacteria exudate treatments were annotated to Alphaproteobacteria suggests that their reliance on ABC and TRAP expression is a highly successful strategy for assimilation of this specific DOM fraction. The relatively low estimated carbon:nitrogen ratio requirements of Alphaproteobacteria nucleotides and proteins also suggests that cyanobacteria DOM (generally one-half the C:N ratio of diatoms) is more congruent with the elemental requirements of this lineage than the other substrates fractions tested ( 42 , 43 ). As was the case in the Bacteroidetes lineage, the relatively higher estimated growth rates of Alphaproteobacteria taxa in the presence of their preferred resource pool suggests enhanced cellular growth and reproduction, and indeed, nearly 90% of newly synthesized ribosomal proteins and transcription/translation factors in the cyanobacteria exudate treatment were annotated to Alphaproteobacteria populations. Although Alphaproteobacteria populations constituted the proportional majority of labeled proteins in the cyanobacteria exudate treatment (probably due to low assimilation by other taxa), the average enrichment values of this lineage were remarkably consistent across all four substrates. Most Alphaproteobacteria taxa have been shown to have relatively stable abundances and metabolic activities during phytoplankton bloom cycles compared with other heterotrophic bacteria ( 26 ) and have been noted to lack strong spatiotemporal gene expression patterns during active blooms ( 57 , 61 , 62 ). Similarly, populations of the most abundant Alphaproteobacteria family in our samples, Rhodobacteraceae, have been shown to retain high and consistent metabolic activity and growth rate despite marked fluctuations in organic matter and chlorophyll concentrations in a natural bloom ( 56 ). These results are seemingly at odds with some isolate and coculture studies which show substantial remodeling of gene expression among copiotrophic Alphaproteobacteria populations ( 11 ); however, observations during naturally occurring blooms or experiments that used complex DOM sources may be more representative of steady metabolic activity in Alphaproteobacteria. Indeed, the Alphaproteobacteria as a whole showed little variability in carbon uptake rates across treatments and only dominated daily cyanobacteria exudate assimilation because Bacteroidetes and Gammaproteobacteria lineages appeared to have over an order of magnitude slower uptake rates. Taken together, our data suggest that populations in this lineage specialize on a subset of the low-molecular-weight and relatively N-rich molecules of marine DOM, which are probably present to some extent in all phytoplankton-derived resources but not accessed as readily by lineages of other phyla. Heterogeneity in DOM Responses between Alphaproteobacteria Populations. Although aggregating Alphaproteobacteria populations at the class level was informative for community-scale interpretation, there was a notable pattern of heterogeneity in the representation of individual Alphaproteobacteria taxa in labeled and unlabeled treatment metaproteomes, implying more nuanced metabolic strategies than in other heterotrophic lineages. For example, Rhodobacteraceae and Rhodospirillaceae proteomes both had slightly (but not significantly) lower relative abundance in DOM treatments compared the control, while Pelagibacteraceae proteomes were slightly more represented in the treatments (shown as deviations from the 1:1 relationship in SI Appendix , Fig. S4, Bottom ); this may imply that the latter taxon increased protein expression more than the former taxa during substrate incubations. However, Pelagibacteraceae had very low representation in the labeled portion of treatment metaproteomes compared to total treatment metaproteomes (unlabeled + labeled), while Rhodobacteraceae and Rhodospirillaceae had higher representation in the labeled protein pools (shown as deviations from the 1:1 relationship in SI Appendix , Fig. S4, Top ), implying a significant difference in the number of proteins synthesized from the amended 13 C-labeled DOM by these populations. We propose that this observation supports two possible conclusions. First, Pelagibacteraceae cells are synthesizing more proteins in the substrate-addition treatments compared to the no-substrate control, but they are not efficiently using 13 C-labeled resources for anabolism and are instead relying on existing (unlabeled) substrates for biomass synthesis. Alternatively, since these results are based on proportional abundance, the relative increase in Pelagibacteraceae representation in substrate treatments could result from an offsetting loss of protein biomass assigned to other taxa, even if the Pelagibacteraceae remain largely unresponsive during the incubation period. While our data cannot definitively rule out this zero-sum-game scenario, our results do show that most other dominant taxa did exhibit high 13 C-enrichment and activity, undermining the latter option that other abundant taxa were decreasing in biomass relative to the Pelagibacteraceae. Furthermore, there is precedence for a mechanism of metabolic partitioning that supports the former option describing a low carbon use efficiency model and that may be worth considering for future studies of Pelagibacteraceae physiology. For example, Guillemette et al. observed that freshwater bacterioplankton preferentially used autochthonous organic matter from phytoplankton for respiration, whereas allochthonous organic matter from terrestrial sources was used for biomass production ( 63 ). Applying this model to marine Pelagibacteraceae in our experiments would suggest that these cells preferentially use the amended freshly fixed, phytoplankton-derived ( 13 C-labeled) metabolites for respiration, and the preexisting pool of unlabeled DOM for biosynthesis. Evidence in partial support of this hypothesis comes from findings that key molecules of fresh DOM exuded from cyanobacteria are used primarily for ATP generation through respiration and only marginally for biomass production by Pelagibacteria spp. ( 64 – 66 ). Further experiments to trace labeled organic inputs into both anabolic and catabolic products will be needed to address these more nuanced metabolic processes. Protein Expression and Ecophysiological Evidence for Mixed or Inconclusive DOM Resource Preferences of Other Taxonomic Lineages. Gammaproteobacteria proteins comprised the third most abundant subset of all unlabeled metaproteomes and were highly represented in the compositional analysis of the metagenome assembly data. Gammaproteobacteria lineages appear to favor the assimilation of exudate rather than lysate DOM, with approximately double the number of labeled peptides being detected in both exudate treatments compared to lysate from the same phytoplankton. Overall, though, far fewer peptides could be confidently assigned to finer taxonomic levels compared to the proteomes of the Alphaproteobacteria and Bacteroidetes lineages, obscuring detailed analyses of most Gammaproteobacteria populations. For example, the relative abundances of the proteomes of assigned taxonomic families within the Gammaproteobacteria (i.e., Porticoccaceae, SAR86 and SUP05 clades) were generally comparable to those of other low-abundance taxa, such as the Marine Group II Euryacrhaeota and Acidimicrobiaceae. Low-abundance taxonomic groups showed similarly low levels of enrichment in substrate treatments on the time scale we used in our experiments. Given that we observed relatively little 13 C assimilation by low-abundance groups, their contribution to ecosystem-scale carbon cycling appears to be proportional to their low representation. In a recent estimate of microbial population-level production compared to relative abundance in a coastal community, the most abundant bacteria accounted for a disproportionately high amount of biomass and activity, whereas rare taxa were proposed to not be able to grow fast enough in these competitive communities to add significantly to the total production ( 67 ). Importantly though, the low-abundance taxa may occupy niches not filled by the abundant populations in the initial communities, which implies that substrate turnover may be dependent on initial community structure in addition to DOM acting as a bottom-up mechanism of community assembly. This simultaneous and reciprocal relationship between resource composition and biological community structure is supported by a literature with many cases of microbe-dependent DOM turnover and DOM-dependent microbial community assembly ( 36 , 50 , 68 )."
} | 6,265 |
27241731 | PMC5217072 | pmc | 7,647 | {
"abstract": "Abstract The importance of organic nitrogen (N) for plant nutrition and productivity is increasingly being recognized. Here we show that it is not only the availability in the soil that matters, but also the effects on plant growth. The chemical form of N taken up, whether inorganic (such as nitrate) or organic (such as amino acids), may significantly influence plant shoot and root growth, and nitrogen use efficiency (NUE). We analysed these effects by synthesizing results from multiple laboratory experiments on small seedlings (Arabidopsis, poplar, pine and spruce) based on a tractable plant growth model. A key point is that the carbon cost of assimilating organic N into proteins is lower than that of inorganic N, mainly because of its carbon content. This carbon bonus makes it more beneficial for plants to take up organic than inorganic N, even when its availability to the roots is much lower – up to 70% lower for Arabidopsis seedlings. At equal growth rate, root:shoot ratio was up to three times higher and nitrogen productivity up to 20% higher for organic than inorganic N, which both are factors that may contribute to higher NUE in crop production.",
"introduction": "Introduction While traditionally inorganic nitrogen (iN) has been viewed as the dominant N source for plants, the importance of organic N (oN) is now widely recognized. Organic and inorganic N forms coexist in soil and represent different stages in the N transformation processes. Because in soil oN is a precursor of iN it may be competitively advantageous for plants to preferentially take up oN, which has been observed in N limited tundra plants (Chapin et al . 1993 ) and wheat (Geisseler et al . 2009 ). With the exception of the initial period after N fertilizer application when iN concentrations are elevated, oN in the form of amino acids represent a significant proportion of exchangeable and soluble N pools in agricultural soils (Brackin et al . 2015 ; Holst et al . 2012 ; Jämtgård et al . 2010 ) and dominate in the organic layer of forest soils (Inselsbacher & Näsholm 2012 ). Peptides (Hill et al . 2011 ; Schmidt et al . 2003 ) and proteins (Paungfoo‐Lonhienne et al . 2008 ) also represent important oN sources. Even if the relative contribution of amino acids to the N budget of crops remains uncertain, all plants studied so far have the capacity to acquire and metabolize amino acids, and all soils studied in this respect contain amino acids (Paungfoo‐Lonhienne et al . 2012 ). Importantly, the effects of different N forms are interesting not only from a pure scientific perspective, but also for agriculture, in particular the potential of organic N to enhance N use efficiency (NUE) (Paungfoo‐Lonhienne et al . 2012 ). Although oN may increase NUE compared to inorganic N fertilizers, as shown for urea (Arkoun et al . 2012 ), most agricultural practices rely on inorganic fertilizers. As currently more than half of the N added to cropland is lost to the environment, producing threats to air, water, soil and biodiversity, improving NUE is of global importance (Lassaletta et al . 2014 ). Recent measurements of N availability at the scale of roots (rather than bulk soil) in a sugarcane plantation showed that plants were not able to fully capitalize the very high iN concentration in the soil after fertilization, but that they took up N efficiently under conditions prevailing between fertilization events, mainly in the form of oN (amino acids) (Brackin et al . 2015 ). This suggests a potentially important role of oN for improving NUE in agriculture – a role which is however not well understood in terms of the further growth effects on the plants. The effects of N form on plants have been mainly studied from an availability perspective. Many studies have addressed the preferences and partitioning of N forms among plants and, although results are variable (Andersen & Turner 2013 ; Ashton et al . 2008 ; Harrison et al . 2007 ; Harrison et al . 2008 ; McKane et al . 2002 ; Miller & Bowman 2002 ; Miller et al . 2007 ; Schimel & Chapin 1996 ; Wei et al . 2015 ; Wilkinson et al . 2015 ), it seems reasonable that plants are adapted, or acclimate, to preferentially take up the N form most available to them (Boczulak et al . 2014 ; Scott & Rothstein 2011 ). However, to better understand the role of N form for plant performance, it is necessary to know not only the availability of different N forms, but also what the benefits and costs of their uptake are for the plant. Does it matter to the plant if the N taken up is iN or oN? Because soil microbes may convert N between different forms, it is difficult to experimentally investigate the effects of N form on plants in the field, and the results of such experiments may be unreliable. In sterile laboratory experiments, plants supplied with oN showed different root morphology and higher root:shoot ratio than those supplied with iN, even though both N forms were supplied at the same N concentration and plants had similar internal N concentration (Cambui et al . 2011 ; Lonhienne et al. 2014). Potential underlying physiological mechanisms have been identified, including different assimilation sites of iN and oN (Cambui et al . 2011 ), and differences in assimilation costs (De Vries et al . 1974 ), which were quantified in the seminal work of Zerihun et al . ( 1998 ). However, the ultimate effects on whole plant growth and allocation of oN versus iN are not well understood. Whereas bottom‐up biochemical calculations suggest that the difference in assimilation costs between N forms is too small to influence growth and allocation (Zerihun et al . 1998 ), experimental studies show large effects on allocation (Cambui et al . 2011 ). These contrasting results may reflect differences among studies in growth conditions, such as soil N availability, plant size and light level, which interact with the biochemical effects of N form. For example, while oN have energetic assimilation advantages over iN (De Vries et al . 1974 ; Gruffman et al . 2013 ; Zerihun et al . 1998 ), it may require higher root investments for uptake, leading to reduced shoot:root ratio and, in‐turn, reduced light capture. To understand such potentially complex interactions, we need to understand how they are coordinated; in effect, an organizing principle for plant behaviour is required. Plant behaviour is ultimately the result of evolution towards increasing fitness (reproductive production per capita), accounting for growth, survival and reproduction over the lifetime of individuals. However, a particular life‐stage fitness can be approximated well by a simpler goal function (Dewar et al . 2009 ; Franklin et al . 2012 ). Small, young plants are expected to allocate C and N among organs to maximize relative growth rate (Ågren & Franklin 2003 ), a principle allowing us to construct a tractable model of plant growth and its response to N and light availability. Here we describe the model and use it to interpret the results of multiple laboratory experiments on the effects of N availability in different forms (nitrate, ammonium and amino acids) on plant growth, allocation and biomass N concentration. We find that the observed effects of N form are explainable based on two primary factors: N assimilation costs and N uptake per root mass. Specifically, compared to iN, growth on oN alone or in combination with iN leads to (1) lower N assimilation cost and (2) lower N uptake per root mass, i.e. higher root C costs per N taken up. We then used the model to answer the questions: How does the benefit of a lower N assimilation cost add up with its higher uptake cost, i.e. under which soil N conditions is the net growth effect positive for the plant?, and what are the consequences for N use efficiency?",
"discussion": "Discussion N form affects plant growth via its effects on root uptake and N assimilation cost. Using a tractable mechanistic model of plant growth we have shown that most of the effects of the form of N taken up by roots on plant growth, allocation and biomass N concentration can be explained by only two factors: N acquisition per root biomass and N assimilation costs. Importantly, we do not address how the availability of different N forms is controlled in the soil; rather, we focus on how a given acquisition of N per root biomass and the resulting N uptake affect plant growth. Growing seedlings on sterile agar plates in the Arabidopsis and poplar experiments ensured that the added N form was not converted to another form by microorganisms before it was taken up, and thus, true plant effects were observed. However, although non‐sterile soil was used for pine and spruce, they responded to added N form similarly to the other plants, which indicates the experimental treatments were effective despite potential conversion of one N form to another by soil microorganisms. A key advantage of our approach was that we used total N uptake per root biomass as an independent (observed) variable, thereby controlling for differences in root N availability, which otherwise complicates the interpretation of N‐form experiments. While the model explains most of the observed differences among plants and N treatments, the slightly lower ability to explain effects on growth rate compared to the other plant traits is largely because of variation within each N treatment in the pine and spruce experiments ( Fig. S4 ). However, the overall agreement between model and observations, as well as the consistently lower N assimilation costs for oN and ioN than iN (Fig. 3 ), strongly suggest that the model captures the key costs and benefits governing plant response to N form taken up. The effect of N form on N assimilation cost had previously not been quantified based on observations. Whereas bottom‐up chemical calculations suggested negligible effects of N form on growth (Zerihun et al . 1998 ), experiments showed significant effects of N form, at times with higher growth and always higher root allocation for oN than iN (Fig. 2 ; Cambui et al . 2011 ). Here we partly reconcile these divergent findings by confirming the chemically estimated differences between N forms (Zerihun et al . 1998 ) by our independent estimates based on whole plant traits (Fig. 3 ), while at the same time showing that these differences do indeed affect plant growth and root: shoot allocation (Figs. 2 , 4 , S2 ). In particular, the model shows that positive effects of oN relative to iN on growth can be ascribed to lower N assimilation costs (Fig. 3 ), which increases N productivity (Figs. 2 , 5 and S2 ). However, because of a simultaneous (observed) negative effect on root N acquisition (Fig. 2 c) only minimal effects on net growth were observed in most of the experiments (Figs. 2 a, 4a). The net result of these counteracting effects on growth depends on their relative sizes and on the overall N availability, as discussed below. However, both these effects contribute to higher root biomass fraction for oN than iN treatments (Fig. 1 ), which explains the consistent observations of this effect (Fig. 2 b, Cambui et al . 2011 ; Gruffman et al . 2012 ; Öhlund & Näsholm 2002 ). The benefit of organic N is largest for small plants with high biomass N concentration under high light. While our experiments provide data for a limited range of light and N availability, our mechanistic model allows us to evaluate resource levels beyond those used in the experiments, and to determine under which conditions N form is most important. We find that the effect of N form is largest at high N and high light intensity (Fig. 4 ). The reason is that under these conditions biomass N concentration is high, and thus the cost of N assimilation for biomass growth is high and therefore influential relative to other costs. Although this prediction appears to be in conflict with the general belief that oN would be most important for plants growing under low N availability (Paungfoo‐Lonhienne et al . 2012 ), recent measurements of N availability at the scale of roots (rather than bulk soil) indicate that, excluding a period immediately after N fertilizer addition, plants take up more oN than iN even in a fertile agricultural site (Brackin et al . 2015 ). The positive relationship between biomass N concentration and N assimilation costs means that the importance of N form declines as plants grow larger. As plants grow, self‐shading reduces intercepted radiation per leaf, reducing the optimal N concentration of the leaves at the same time as the production of low N tissues such as stems increases in many plants. However, for small plants even a small difference in growth rate may be important, especially in a competitive context. Although the difference in relative growth rate between the N forms in Fig. 2 appear rather modest, because of the exponential growth of these small plants it quickly leads to large differences in size over time (Fig. 4 c). In summary, while our estimates of the difference in N assimilation costs between N forms agree with bottom‐up chemically based estimates (Fig. 3 ), our whole plant perspective reveals that these apparently small differences scale up to significant effects on growth and allocation over time and may be more important than previously thought. Organic N is cheaper to use but more expensive to get than inorganic N – but what is the total effect on growth? Previous studies on N form preferences has been focused on the premise that plants are adapted, or acclimate, to preferentially take up the N form most available to them (Boczulak et al . 2014 ; Scott & Rothstein 2011 ), yet our findings imply that not only the availability of different N forms is important but also the cost of assimilation once the N has been taken up. Here we found that, compared to iN, oN is cheaper to assimilate but sometimes more expensive to take up (N uptake per root biomass is lower). A key question is how the benefit of a lower N assimilation adds up with the higher uptake cost, i.e. when is the net growth effect positive and therefore oN should lead to a higher plant growth than iN? Whereas the difference in N assimilation cost should be largely independent of environmental conditions, the uptake difference depends on how external factors vary among soils, in particular with soil N availability. In low N soils, mainly organic N forms are available (Inselsbacher & Näsholm 2012 ), whereas in fertile high N soils, NO 3 or NH 4 dominate (Nordin et al . 2001 ; Paungfoo‐Lonhienne et al . 2012 ). In line with the hypothesized correlation between availability and plant preference, when total soil N was abundant, root acquisition of oN ( u , measured on seedlings growing in nutrient solution) was lower than that of iN, but both rates were similar when soil N was scarce (Warren 2009 ). Based on these observations we modelled a gradient of increasing total soil N availability and decreasing soil oN: iN ratio (Fig. 5 ). Despite the declining relative availability of oN in this scenario, the growth rate advantage for oN compared to iN persists as N availability increases, even until acquisition of iN per root mass is three times higher than for oN (Figs. 5 a, d). This demonstrates that the benefit of cheaper N assimilation (the C bonus) may make oN preferable to iN despite lower availability in the soil. Organic N uptake promotes NUE by enhanced root growth and N productivity An important question for agriculture and forestry is how the form of N taken up by plants affects productivity and nitrogen use efficiency (NUE). There are many ways to define NUE (Lassaletta et al . 2014 ) and perhaps the most relevant from a practical perspective is the yield per N added. This NUE can be viewed as the combination of two factors: (1) the fraction of added N taken up by the plants, and (2) N productivity – the growth rate per plant N (Ågren & Bosatta 1998 ). For crop production, crop yield (e.g. grain) per biomass would be a third factor in the NUE equation, which however is mainly determined at a later stage of growth than the seedling phase considered here. Thus, our results are by no means directly applicable for quantitative predictions of agricultural yield, rather the indicate in which direction N form may change NUE and by which mechanism. Although the first factor, the fraction N taken up, is largely controlled by soil processes, such as competition with microbes (Wilson et al . 2013 ), beyond the scope of our model it is also influenced by root growth. Our analysis shows that root biomass fraction is always higher if plants are growing on oN than on iN (Fig. 5 ), which was partly because of lower root N acquisition oN in our experiments (Figs. 1 , 2 and 4 ). This means that a larger proportion of biomass production is allocated to roots rather than above ground crop yield. However, in all our experiments, except for poplar, there was higher relative growth rate for oN than iN treatments (Figs. 2 and S2). This advantage in relative growth rate may quickly compensate for the effect of a higher root:shoot ratio over time (Fig. 4 c) so that total above‐ground yield will be larger for oN than iN despite higher root:shoot ratio. Importantly, although it does not contribute to yield directly, the increase in root growth associated with oN leads to larger total N uptake capacity, which increases the fraction of added fertilizer N taken up and reduces N losses from the field and thereby increases NUE over time (Paungfoo‐Lonhienne et al . 2012 ). Indeed, higher N retention for oN than iN has been observed in pine and spruce seedling nurseries (Öhlund & Näsholm 2002 ). Our analysis shows that the second factor of NUE, the N productivity, is also higher for oN than iN because of lower N assimilation costs, unless oN availability is much lower than iN (<4% in Fig. 5 ). Interestingly, under rising atmospheric CO 2 this advantage of oN over iN (if in the form of nitrate) may increase further as the photo‐respiratory fuelling of nitrate assimilation declines because of reduced photo respiration (Bloom et al . 2014 ). In summary, although the empirical evidence is yet limited to a few species grown in laboratories, our results show that plant uptake of oN has a previously underestimated physiological advantage over iN in terms of lower N assimilation costs. Because the effect is strongest in small plants with high N concentration, especially where light is not limiting, these results are particularly relevant for establishment of tree seedlings in tree nurseries and agricultural crops, suggesting that NUE could be increased by increasing availability of organic N relative to inorganic N. While the magnitude of such an NUE effect may be smaller in other settings, its basis in fundamental biochemistry suggest that the relationship between N form and NUE should be of universal relevance for plant growth."
} | 4,753 |
25152885 | PMC4126474 | pmc | 7,649 | {
"abstract": "Many research groups are interested in engineering the metabolism of cyanobacteria with the objective to convert solar energy, CO 2 , and water (perhaps also N 2 ) into commercially valuable products. Toward this objective, many challenges stand in the way before sustainable production can be realized. One of these challenges, potentially, is genetic instability. Although only a handful of reports of this phenomenon are available in the scientific literature, it does appear to be a real issue that so far has not been studied much in cyanobacteria. With this brief perspective, I wish to raise the awareness of this potential issue and hope to inspire future studies on the topic as I believe it will make an important contribution to enabling sustainable large-scale biotechnology in the future using aquatic photobiological microorganisms.",
"conclusion": "Conclusion The limited amount of available information makes it difficult to assess how great an issue genetic instability really is toward the aim of developing aquatic photobiological biotechnology. Several other issues also exist including excessively expensive cultivation infrastructure and culture crashes as a result of biological contamination/invasion. In the absence of a recA -based solution, how can we prevent genetic instability? Currently, there are no other solutions in the literature that are obvious. At first, however, it would be good to at least confirm on an analytical level that genetic instability is indeed an issue and if so to determine whether or not it is inducible in cyanobacteria. It would be advisable to extend such studies to more than one model cyanobacteria species as they appear to be quite different in this respect, see (Guerrero et al., 2012 ) and Table 1 . Thereafter, the development of a model system that is not excessively unstable, yet also not too stable, would pave the way for both targeted and non-targeted screens for factors that are essential for the process. This may then lead on to possible solutions to minimize the negative impact of genetic instability in cyanobacteria for both fundamental and applied sciences, and thereby contribute toward the development of economically sustainable aquatic photo biotechnology using engineered biology in a hopefully not too distant future."
} | 572 |
31561467 | PMC6836247 | pmc | 7,650 | {
"abstract": "Stimuli-responsive conductive hydrogels have a wide range of applications due to their intelligent sensing of external environmental changes, which are important for smart switches, soft robotics, and flexible sensors. However, designing stimuli-responsive conductive hydrogels with logical operation, such as smart switches, remains a challenge. In this study, we synthesized pH-responsive conductive hydrogels, based on the copolymer network of acrylic acid and hydroxyethyl acrylate doped with graphene oxide. Using the good flexibility and conductivity of these hydrogels, we prepared a flexible sensor that can realize the intelligent analysis of human body motion signals. Moreover, the pH-responsive conductive hydrogels were integrated with temperature-responsive conductive hydrogels to develop logic gates with sensing, analysis, and driving functions, which realized the intellectualization of conductive hydrogels.",
"conclusion": "4. Conclusions In summary, we introduced a simple method of preparing pH-responsive conductive hydrogels. PAA was introduced as the pH-responsive component, GO was introduced as the conductive component, and PHEMA was introduced to increase flexibility. In the buffer solution of pH 2 to pH 8, the conductive hydrogel gradually increased in diameter and conductivity due to the gradual increase of the degree of ionization of the carboxyl group and the ion concentration in the hydrogel. A highly sensitive flexible sensor was fabricated using a flexible pH-responsive conductive hydrogel for monitoring human motions. At the same time, the two kinds of stimuli-responsive hydrogels were combined to sense the environment, regulate the volume change of the hydrogel, and realize intelligent control, thereby expanding the application range of the conductive hydrogel and making the chemical materials intelligent.",
"introduction": "1. Introduction Conductive hydrogels have mechanical flexibility and controllable electronic properties, and are one of the hottest materials for electronic sensors [ 1 , 2 ], flexible skins [ 3 , 4 ], supercapacitors [ 5 , 6 , 7 ], and nerve electrodes [ 8 ]. With the development of smart devices, more and more studies are focusing on smart materials [ 9 , 10 , 11 , 12 , 13 ]. The intellectualization of conductive hydrogels endues conductive hydrogels with stimuli-responsive functions, so that they can intelligently respond to external stimuli and produce changes in volume [ 14 ]. However, due to the complexity of environmental changes and the difficulty in constructing smart devices, using stimuli-responsive conductive hydrogels to construct complex smart devices remains a huge challenge in current scientific research. Recently, a number of studies have been conducted on stimuli-responsive conductive hydrogels, which can be used to realize the intellectualization of flexible sensors [ 14 , 15 ], drug release [ 16 ], and logical controllers [ 17 ]. Poly( N -isopropylacrylamide) (PNIPAM) was used to construct temperature-sensitive conductive hydrogels [ 17 , 18 , 19 , 20 ], which showed a good response to temperature and high electrical conductivity for making temperature-controlled switches [ 21 , 22 ]. However, for logic switches with intelligent control, one type of stimuli was not enough, due to the complexity of environmental changes [ 23 ]. At the same time, few studies reported pH-responsive conductive hydrogels [ 24 , 25 , 26 , 27 , 28 ] and did not focus on developing intelligent control devices [ 28 , 29 ]. Therefore, by mimicking the integrated circuit, the combination of two or more types of stimuli-responsive materials may achieve the fabrication of the device [ 23 ]. Hydrogel logic control devices have the advantage of convenient manipulation and reusability, with wide applications in the fields of flexible electronics and regenerative medicine. Kim et al. [ 30 ] used hydrogels as polyelectrolytes to prepare a pH-controlled organic electrochemical transistor, and applied it to electrochemical logic circuits to develop NOT, NOR, and NAND logic gates. Huang et al. [ 10 ] prepared novel ion-conducting supramolecular hydrogel with reversible photoconductivity, controlling the resistance of the circuit by switching the light source and applying it to the logic circuit to selectively control the on/off state of the circuit by light. Hu et al. [ 31 ] used semi-interpenetrating hydrogel film to achieve logical control of electroactive probes, providing a novel and convenient model for constructing multi-signal switchable bioelectrocatalysis. Deforest et al. [ 32 ] used a modular design to prepare hydrogel logic gates for drug delivery by combining different stimuli responsiveness. However, the aforementioned hydrogels are complicated in terms of preparation. For practical production, how to use the simple synthesis method to prepare hydrogels for constructing logic control devices is a problem worth considering. In order to solve this problem, we needed to prepare a pH-responsive conductive hydrogel. In general, polyacrylic acid hydrogels have good pH-responsiveness, which is commonly used as the drug controlled release material [ 33 , 34 ]. However, acrylic hydrogels are very brittle, which is a big problem in building smart devices [ 35 ]. Therefore, many studies have been reported on improving the mechanical properties of polyacrylic acid hydrogels to prepare smart devices, such as flexible sensors [ 36 , 37 ]. Herein, in the process of polymerization of acrylic acid and hydroxyethyl acrylate monomers into hydrogels, we added graphene oxide to a prehydrogel solution to prepare pH-responsive conductive hydrogels, which have high conductivity. At the same time, the addition of hydroxyethyl acrylate monomer effectively improved the mechanical properties of the acrylic hydrogel, and the conductive hydrogels had good flexibility. A flexible sensor with high sensitivity was fabricated to realize rapid monitoring and the feedback of human activity. Furthermore, we combined pH-responsive conductive hydrogels with temperature-sensitive conductive hydrogels to develop logic gates, such as YES, OR, and AND gates with intelligent control functions, which considerably enriched the application field of intelligent conductive hydrogels.",
"discussion": "3. Results and Discussion 3.1. Chemical Structures of pH-Responsive Conductive Hydrogels The chemical structure of P(AA-HEMA)/GO hydrogels was identified using FTIR spectroscopy. Figure 2 shows the FTIR spectra of PAA hydrogels and P(AA-HEMA)/GO hydrogels. The results show that the infrared absorption line of PAA exhibited a stretching vibration absorption peak of C = O in the carboxyl group at 1724 cm −1 . Note that a broad absorption peak appeared around 3440 cm −1 , which can be attributed to the stretching vibration of the hydroxyl group of AA and the hydroxyl group of HEMA. We obtained the microstructure of the hydrogels from freeze-dried hydrogel samples using scanning electron microscopy (SEM). The microstructure is crucial for pH-responsive hydrogels, which require water to rapidly go into or out of the whole gel. As shown in Figure 3 a, the hydrogels presented a homogenous and porous microstructure. This structure indicated the presence of interconnected channels in the hydrogels, which considerably improved the response rate because of the fast transport of water through the gel. As shown in Figure 3 b, there were many lamellar structures in the porous structure of the P(AA-HEMA)/GO hydrogel under the same magnification, which indicated the successful preparation of the PAA and GO composite materials. Moreover, by observation, we determined that the pore structure of the P(AA-HEMA)/GO hydrogels was smaller than the pure PAA hydrogels because of the following reasons [ 26 ]: the GO surface was hydrophilic and the sheet was compatible with the matrix, forming a dense polymer network structure; and the hydrogels contained the GO sheet, which prevented the growth of pores during the freeze-drying process. Figures S1 and S2 show the chemical structures of temperature-responsive conductive hydrogels. 3.2. pH-Responsiveness and Conductivity of P(AA-HEMA)/GO Hydrogels The P(AA-HEMA)/GO hydrogel contained a number of –COOH groups that showed an outstanding pH-responsiveness. Because the degree of dissociation of –COOH varied under different pH conditions, the hydrogel composites showed different degrees of swelling. As shown in Figure 4 a, the hydrogel remained in a contracted state at pH < 4. Even if the buffer concentration reached 4, the pH inside the hydrogel was still less than the pKa (4.3) of AA. The dissociation degree of the gel network was low, and electrostatic repulsion hardly contributed to the gel′s swelling. Therefore, when at pH < 4, the gel slightly swelled with the increase in pH. When at pH > 4, the dissociation degree of the gel network rapidly increased with ion exchange inside and outside of the hydrogel. Moreover, the electrostatic repulsion was considerably enhanced, and the diameter of the hydrogel was drastically increased [ 38 , 39 ]. As shown in Figure 4 b, when the pH increased, the conductivity of the hydrogel increased. This may have been caused by the change in the swelling states and microstructures of the hydrogels [ 19 ]. As the pH increased, electrostatic repulsion occurred, due to the continuous ionization of –COOH in the hydrogel, and the hydrogel volume increased. The water in the hydrogel increased, and the density of the polymer backbone decreased, which facilitated the transfer of electrons on graphene oxide. In comparison, we can see that the conductivity of P(AA-HEMA) was very small. As the pH changed, the conductivity remained essentially the same, which showed that the main carrier was electron from GO. We explain the change in diameter and conductivity with the temperature of PINPAM hydrogels in Figure S3 . As shown in Figure 4 c, we judged that the percolation threshold was about 0.35 wt %, and the GO concentration in the hydrogel was close to the threshold for GO percolation. As shown in Figure 4 d, we prepared hydrogels without acrylic acid under the same conditions. We found that in changing the pH, the conductivity of the hydrogels remained almost unchanged, indicating that the –COOH in acrylic acid had little effect on the conductivity of the hydrogels. At the same time, the –COOH in GO had very little effect on the conductivity of the hydrogels. Therefore, the main carrier was electron from GO. 3.3. Wearable Devices for Monitoring Human Motions The pH-responsive conductive hydrogel was assembled as a flexible wearable smart device for detecting human activity. The shape of the gel was rectangular parallelepiped. The length was 4.5 cm, the width was 1.5 cm, and the thickness was 1.5 mm. When the flexible sensor was used for human body detection, the hydrogel was constantly stretched and linked with real-time measuring equipment by electrical wires. The sensing response was calculated as relative resistance change, as follows: S (%) = ( R − R 0 )/ R 0 × 100% = Δ R / R 0 × 100% (1) \nwhere R 0 and R are the related original resistance of the sensor and the resistance after stretching, respectively. As shown in Figure 5 , the relative resistance change of the conductive hydrogel gradually increased when the hydrogel was stretched. This can be explained by the stretching of the conductive hydrogel, which narrowed the porous microstructure, and damaged the 3D network framework of GO for electron transport, giving rise to the growth of resistance [ 40 ]. As shown in Figure 5 a–c, the flexion of the finger was detected using a flexible sensor to show the hydrogel’s rapid response. Moreover, when the fingers were bent at different angles, the hydrogel attached to the fingers was stretched to different lengths, and thus the resistance was different, thereby outputting signals of different heights. Similarly, for wrist activity, when the hydrogel was mounted on the wrist, mechanical motions of the wrist were monitored by these output curves. As shown in Figure 5 d, the sensor distinguished the degree of pressure during compression. Different pressures corresponded to different resistance changes and output different waveforms. Since the hydrogels were the copolymers of AA and HEMA, the hydrogels had flexibility and stretchability. Besides pressure, the specific waveform was output when we stretched ( Figure 5 e) and twisted ( Figure 5 f) the sensor. Notably, the resistance-time curves of the three mechanical stimuli showed high signal-to-noise ratios, which indicated high sensitivity and reliability of the flexible sensor. As shown in Figure S4 , the hydrogels exhibited different geometries under different motions. Figure S5 indicates the stability of the sensor. 3.4. The Preparation of Logic Gates Based on pH-Responsive and Thermo-Responsive Conductive Hydrogels As shown in Figure 6 a, the shape of the printing mold was copied by the PDMS. As illustrated in the inset of Figure 6 b, we built the circuit using power, a bulb, PDMS molds, and stimuli-responsive conductive hydrogels. As shown in Figure 6 c, we specified a state input of 0 when the hydrogel shrunk, and a state input of 1 when the hydrogel expanded. When the lamp was unlit, we specified the output to be 0; however, when the lamp was lit, we specified the output to be 1. First, we used pH-responsive conductive hydrogels to make the YES logic gate and to prove our method. At pH 2, when the hydrogel was exposed to a solution, it shrunk (input 0) and the bulb went out (output 0); however, at pH 8, the hydrogel expanded (input 1) and the bulb illuminated (output 1); this process was reversible. Similarly, we developed the YES logic gate using temperature-responsive conductive hydrogels ( Figure S6, Supporting Information ). Using the specific design of the logic system, we built more complex logic gates. Figure 6 d,e show the methods of making OR and AND logic gates using stimuli-responsive conductive hydrogels. The devices included two stimuli-responsive hydrogels that respond to different stimuli. For the OR gate, the two hydrogels were adjacent to each other. Whenever any of the hydrogels expanded under the influence of the stimulus, the hydrogel expanded, the circuit turned on, and the bulb was illuminated (output 1). When both hydrogels were stimulated at the same time, they expanded and the circuit turned on (output 1). For the AND gate, we maintained a certain distance between the two hydrogels. When only one hydrogel expanded, it only expanded into the space and connected to another hydrogel, but did not turn on the circuit, and the bulb did not illuminate (output 0). Therefore, the circuit would only turn on when both hydrogels swelled, after which the bulb would illuminate (output 1). As shown in Figures S7 and S8 (Supporting Information) , we provide the size of the logic gates and the expansion ratios of the two responsive hydrogels. By combining the expansion ratios and the dimensional changes of the hydrogels, the preparation of the logic gate device can be better understood. We experimentally verified the expected execution of these two logic gates for all input states. The demonstrations show that we used different stimuli to respond to conductive hydrogels and controlled the position of the hydrogels, such that we developed different types of chemical logic gates. We constructed the logic gates using the integration of two stimulus responsive materials. A logic gate is a smart device that intelligently senses changes in the external environment, thereby driving its own volume change and achieving intelligent control. Connecting the logic gate to the circuit and constructing the intelligent switch as the control light bulb is one of the important applications of the logic gate. In addition, intelligent controlled release and molecular probes for drugs can be achieved by using logic gates."
} | 3,992 |
19386918 | null | s2 | 7,652 | {
"abstract": "Networks of model neurons were constructed and their activity was predicted using an iterated map based solely on the phase-resetting curves (PRCs). The predictions were quite accurate provided that the resetting to simultaneous inputs was calculated using the sum of the simultaneously active conductances, obviating the need for weak coupling assumptions. Fully synchronous activity was observed only when the slope of the PRC at a phase of zero, corresponding to spike initiation, was positive. A novel stability criterion was developed and tested for all-to-all networks of identical, identically connected neurons. When the PRC generated using N-1 simultaneously active inputs becomes too steep, the fully synchronous mode loses stability in a network of N model neurons. Therefore, the stability of synchrony can be lost by increasing the slope of this PRC either by increasing the network size or the strength of the individual synapses. Existence and stability criteria were also developed and tested for the splay mode in which neurons fire sequentially. Finally, N/M synchronous subclusters of M neurons were predicted using the intersection of parameters that supported both between-cluster splay and within-cluster synchrony. Surprisingly, the splay mode between clusters could enforce synchrony on subclusters that were incapable of synchronizing themselves. These results can be used to gain insights into the activity of networks of biological neurons whose PRCs can be measured."
} | 373 |
35757031 | PMC9218832 | pmc | 7,653 | {
"abstract": "We present for the first time highly stretchable and tough hydrogels with controlled light-triggered photodegradation. A double-network of alginate/polyacrylamide (PAAm) is formed by using covalently and ionically crosslinked subnetworks. The ionic Ca 2+ alginate interpenetrates a PAAm network covalently crosslinked by a bifunctional acrylic crosslinker containing the photodegradable o -nitrobenzyl (ONB) core instead of the commonly used methylene bisacrylamide (MBAA). Remarkably, due to the developed protocol, the change of the crosslinker did not affect the hydrogel's mechanical properties. The incorporation of photosensitive components in hydrogels allows external temporal control of their properties and tuneable degradation. Cell viability and cell proliferation assays revealed that hydrogels and their photodegradation products are not cytotoxic to the NIH3T3 cell line. In one example of application, we used these hydrogels for bio-potential acquisition in wearable electrocardiography. Surprisingly, these hydrogels showed a lower skin-electrode impedance, compared to the common medical grade Ag/AgCl electrodes. This work lays the foundation for the next generation of tough and highly stretchable hydrogels that are environmentally friendly and can find applications in a variety of fields such as health, electronics, and energy, as they combine excellent mechanical properties with controlled degradation.",
"conclusion": "3 Conclusion New photodegradable ONB crosslinkers were synthesized and incorporated into alginate/PAAm DN hydrogels, to develop for the first time highly stretchable and tough hydrogel, with triggerable photodegradation. The hydrogels were characterized by mechanical, photodegradation and cytocompatibility tests. Replacing MBAA with ONB crosslinkers, and despite the use of DMSO, excellent mechanical performances are retained. Rheological and mechanical analysis demonstrated the loss of properties of ONB-1 based DN hydrogel after irradiation, confirming the efficient destruction of the covalently crosslinked network, resulting in the loss of mechanical properties. SEM analyses also visually confirmed the network photodegradation. Cell viability and proliferation assays confirmed that these hydrogels and their photodegradation products do not induce any cytotoxicity on the NIH3T3 cell line. It is envisaged that the design of innovative on-demand photodegradable hydrogels which are tough, and safe provides an interesting alternative to a wide range of biomedical applications such as wearable devices, bioelectronics interfaces, and mechanically resilient batteries and supercapacitors.",
"introduction": "1 Introduction Hydrogels are soft and highly-hydrated materials, composed of a crosslinked three-dimensional (3D) network of hydrophilic polymer chains, capable of swelling and retaining large amounts of water in their network structure, without dissolving [ 1 , 2 ]. Due to their ability to absorb water, good biocompatibility, and similarity to human tissues, hydrogels are widely used for various biomedical applications, including tissue engineering [ 3 ], drug delivery [ 4 ], biosensors [ 5 ], wearable electrodes for biomonitoring [ 6 ], printed and stretchable batteries [ 7 ], and supercapacitors [ 8 ]. However, most hydrogels are very brittle (fracture energy ∼10 J m −2 ), due to the high water content in the network, which reduces the toughness and strength of hydrogels [ 9 , 10 ]. In the last two decades, new approaches have been used to improve toughness: interpenetrating network hydrogels [ 11 ], double-network (DN) hydrogels [ 12 , 13 ], nanocomposite hydrogels [ 14 , 15 ], slide-ring hydrogels [ 16 ], and others [ [17] , [18] , [19] ]. DN hydrogels have high mechanical performance, which can be adjusted by modulating the inter and/or intramolecular interactions and within or between two network structures, by different crosslinkers and/or crosslinking methods [ 20 ]. DN hydrogels have two interpenetrating networks with contrasting physical structures and properties: a rigid and brittle first network that breaks easily under large deformation to dissipate energy, while the soft and ductile second network contributes to stretchability and allows to return to the original configuration after deformation [ 21 ]. Nevertheless, the rupture of the covalent DN hydrogels network leads to permanent and irreversible damage, making recovery after initial loading difficult and leading to failure of the material under repeated loading [ 22 ]. The introduction of reversible, sacrificial, noncovalent bonds into the first network overcomes this limitation, which is due to the disruption–recrosslinking behaviour of physical networks [ 23 , 24 ]. The hybrid, physically and chemically crosslinked DN hydrogels have improved self-recovery capacity and fatigue resistance, which is extremely important in, for example, iterative soft load-bearing tissues, actuators, and implantable devices [ [25] , [26] , [27] ]. The best physical network for hybrid DN hydrogels are ionically crosslinked networks, composed of polysaccharides and multivalent ions [ 28 ]. Suo et al. [ 12 ] demonstrated that simultaneously ionically (alginate) and covalently (acrylamide, AAm) crosslinked networks form a notch-insensitive hybrid hydrogel that could be stretched over 20-fold of its original shape with fracture energy of 9000 J m −2 . Although rapid and promising progress has been made in the synthesis of mechanically robust hydrogels, a major problem remains unsolved. The properties of these hydrogels are usually fixed at the time of preparation, making it impossible to subsequently tune them afterward, [ 29 ]. Also, most of the polymers used to form the crosslinked network are not biodegradable [ 30 ] (e.g., PAAm). Biodegradable hydrogel networks based on cellulose, chitosan, and alginate have been investigated by several groups [ [31] , [32] , [33] ], but these networks are inadequate in terms of mechanical and chemical resilience. The synthesis of highly stretchable and tough hydrogels that can degrade in response to an external stimulus remains a challenge. The incorporation of stimuli-responsive units into the hydrogels would allow their properties to be changed in response to an externally applied stimulus [ 34 ]. Light has the advantage of allowing precise spatial and temporal control by using lights with different wavelengths, intensities, and irradiation times [ 35 , 36 ]. The most used photolabile core used in polymers are o -nitrobenzyl (ONB) derivatives [ 37 ]. Its mechanism of photolysis by UV light is well known, and they are considered biocompatible [ 38 ]. Chemical modifications of the aromatic ring or benzyl position of ONB derivatives [ 39 , 40 ], resulted in a redshift of the absorption window, improved cytocompatibility, increased rate of photocleavage, and the prevention of the formation of toxic by-products after photolysis [ 41 ]. Therefore, structural tuning of the chemical structure of ONB linkers offers the possibility of developing materials with light-tuneable mechanical properties [ 38 , 42 ]. In this work, photocleavable highly stretchable and tough DN hydrogels are prepared for the first time. Networks disruption can be remotely triggered using cytocompatible light wavelength. Alginate/PAAm DN hydrogels are prepared by a one-step method. Divalent cations (Ca 2+ ) were used for ionic crosslinking of alginate, while PAAm was covalently crosslinked by a new ONB-based bifunctional crosslinker. Since the new ONB-crosslinker is not water-soluble, a special protocol was developed using an optimized ratio of between DMSO/water to enable the preparation of the hydrogels. Hydrogels were characterized in terms of their mechanical and photodegradability as well as their in vitro toxicity. It is envisioned that these photodegradable hydrogels, with their improved properties, will open up new applications in various fields including artificial tissues, bioelectronics, and flexible sensors. As an example, we showed the application of these hydrogels in bio-potential acquisition for wearable electrocardiography and compared their skin-electrode impedance with the commonly used medical grade Ag/AgCl electrodes.",
"discussion": "2 Results and discussion The aim of this work is to develop highly stretchable and tough hydrogels that can be degraded when needed, by irradiation of ONB moieties inside the two polymer networks ( Fig. 1 ). Fig. 1 Overview of the approach: A) Synthesis of two o-nitrobenzyl (ONB) crosslinkers with different labile bonds. B) Photocleavage of ONB crosslinkers upon UV irradiation, forming an aromatic nitroso compound and a carboxylic acid. The R1 group determines the rate of photodegradation and the nature of resulting cleavage products. C) Structure of the alginate/PAAm hydrogels. In a polyacrylamide hydrogel, the polymer chains form covalent crosslinks through prepared ONB crosslinkers. The alginate hydrogel is formed by the ionic crosslinks through Ca 2+ and. the G-blocks. D) After UV irradiation of the DN hydrogel, the ONB crosslinkers undergo an irreversible photocleavage, breaking the polyacrylamide hydrogel crosslinks. When stretched the PAAm network cannot stabilize the deformation, while the alginate network unzips progressively, resulting in a high loss of the material toughness. Fig. 1 2.1 Photodegradable properties of the crosslinkers The photodegradation of ONB is triggered by the reduction of the NO 2 group to the nitroso group and the insertion of an oxygen atom into the C–H bond at the benzylic position [ [43] , [44] , [45] ]. Consequently, irradiation with 260 nm light leads to the release of carboxylic acid and o-nitrosobenzaldehyde (or nitrosoketone) as by-products [ 46 ]. Structural changes of ONB affect the molar absorptivity ( ε ), yield and kinetics of the photocleavage reaction [ 38 ]. The introduction of an α-CH 3 group at the benzylic carbon atom speeds up the cleavage and release a ketone by-product instead of an aldehyde [ 47 ]. Also, one or more alkoxy groups in meta and para positions cause a redshift in the absorption spectrum and increase the rate of photocleavage [ 40 ]. The balance between the strong electron-withdrawing capacity of the NO 2 group and the electron-donating effect of the OCH 3 group in para position to the NO 2 allows a shorter irradiation time for the cleavage of the photolabile compound [ 48 ]. The synthesis of the new photodegradable ONB crosslinkers exploits both the α-CH 3 group at the benzylic carbon and the alkoxy functionality (ONB-1, Fig. 1 A and Figure S1 ). These groups promote efficient photocleavage [ 29 ], making ONB-1 an excellent candidate for weakening the polymeric network upon irradiation. For comparison, an ONB crosslinker without both substituents was also synthesized (ONB-2, Fig. 1 A and Figure S1 ). The spectroscopical properties of the two synthesized crosslinkers were studied by UV-VIS spectrophotometry and 1 H NMR. The absorption spectra of ONB-1 showed three maximum absorption peaks at 243, 301 and 335 nm, while ONB-2 exhibited only one maximum absorption peak at 273 nm ( Figure S10 ). This change in the absorption profile between the two ONB crosslinkers suggests that the presence of the alkoxy group leads to a redshift in the spectrum [ 40 , 49 ]. Small structural changes in the ONB crosslinker lead to significant changes in ε , because at a given wavelength ε affects the photodegradation rate, and very low values of ε , imply limited or no photodegradation [ 50 ]. As observed for the ONB-1, the calculated ε 243 is 13892 M −1 cm −1 , ε 301 is 6289 M −1 cm −1 and ε 335 is 6122 M −1 cm −1 , while for the ONB-2 crosslinker the calculated ε 243 is 4090 M −1 cm −1 , ε 301 is 4050 M −1 cm −1 and ε 335 is 946 M −1 cm −1 ( Table S1 , Figure S11 - Figure S18 ). ε decreases with increasing wavelength, consistent with previous reports [ 50 , 51 ]. The red shift in absorption causes photolysis at a higher wavelength that also minimizes potential tissue damage and improves cytocompatibility [ 52 ]. Rapid photocleavage kinetics and a high ε result in a faster-degrading crosslinker, which shortens the irradiation time [ 50 ]. ONB-1 and 2 were analysed by 1 H NMR before and after irradiation with UV light in CHCl 3 . Photodegradation of ONB-1 yields a ketone and a carboxylic acid ( Fig. 1 B). 1 H NMR spectrum of ONB-1 ( Figure S19 ) shows the appearance of a new signal (m) at 2.5 ppm, belonging to the protons of the ketone –CH 3 group, indicating the cleavage of the ONB core. After 1 h of irradiation, the photocleavage conversion was 57%, and after 6 h was 100%. The 1 H NMR spectrum of ONB-2 ( Figure S20 ), shows the appearance of a new signal (i) at 10.45 ppm, corresponding to the proton of the aldehyde group of o -nitrosobenzaldehyde. However, after 1, 3 and 6 h, the photodegradation was only 3, 6, and 10%, respectively. To increase the photodegradation, the irradiation was extended to 24 h, but the conversion levelled off to 10%. This could be due to the release of o -nitrosobenzaldehyde, which can act as an internal light filter [ 44 , 49 , 53 ]. The compound ONB-1 exhibits faster photodegradation kinetics, due to the presence of an α-CH 3 group on the benzylic carbon, so it was selected as crosslinker for hydrogel preparation. 2.2 Preparation of the photodegradable DN hybrid hydrogels The photodegradable DN hybrid hydrogels were prepared using an ionically crosslinked Ca 2+ alginate network, and a covalently crosslinked PAAm network. In an aqueous solution, gelation of alginate occurs when divalent cations (such as Ca 2+ ) ionically interact with α-L-guluronic acid blocks (G-blocks) from different alginate chains, to form the first network [ 54 ]. The PAAm network, in turn, was prepared by conventional free radical polymerization of AAm in the presence of the photodegradable crosslinker. Normally, hydrogels are prepared using water as solvent because reagents are water soluble. However, as ONB-1 is hydrophobic, DMSO is added as co-solvent to promote its dissolution. Although DMSO dissolves ONB-1, it also causes rapid gelation of aqueous alginate solutions [ 55 ]. Therefore, the water/DMSO ratio must be carefully optimized to ensure that ONB-1 is completely dissolved, but without causing premature gelation of the Na-Alg solution. To this end, various amounts of DMSO were added to Na-Alg solutions ( Table S2 ). Visual inspection showed that the solution still flowed when 25 vol% and 30 vol% DMSO was added ( Figure S21 ). In contrast, solutions with more than 40 vol% DMSO gelled. Furthermore, a PAAm network must form under these conditions. The PAAm networks were considered finish if no gravitational flow occurred when the glass flash was inverted. With a curing time of 24 h, the lowest amount of DMSO to obtain a gel was 25 vol% ( Table S3 , Figure S22 ). Thus, photodegradable hydrogels (labelled as H25 and H30) were developed with 25 vol% and 30 vol% DMSO, respectively. Different concentrations of ONB-1 crosslinker allowed the investigation of the response of the hydrogel to the crosslink density ( Table S4 ). The concentrations of APS, TEMED and CaSO 4 were used according to previous work and kept constant in all formulations [ 12 ]. The control hydrogel was prepared without DMSO, and with MBAA instead of the ONB-1 crosslinker to compare the mechanical properties [ 12 ]. The amounts of each compound to prepare the control and photodegradable hydrogels are shown in Table 1 . After the curing step, the average solvent content of the control and photodegradable hydrogels was 84% and 86%, respectively ( Figure S23 ). Table 1 Different formulations used to prepare the DN hybrid hydrogels. Table 1 Type of hydrogel AAm (wt%) Na-Alg (wt%) Crosslinker (%) (m crosslinker/m AAm) APS (wt%) TEMED (%) (m TEMED/m AAm) CaSO 4 (%) (m CaSO 4 /m AAm) Solvent content (wt%) Control 12.25 1.75 0.06 0.043 0.25 13.28 84 (water) Photodegradable (H25 and H30) 12.25 1.75 0.06 0.043 0.25 13.28 86 (water + DMSO) 0.3 0.6 0.12 2.3 Mechanical properties of the photodegradable DN hybrid hydrogels The effect of the amounts of DMSO and ONB-1 crosslinker on the mechanical properties of the photodegradable DN hybrid hydrogels was investigated. Tensile tests were performed by pulling the samples to rupture at a constant strain rate of 20 mm min −1 ( Fig. 2 ). This strain rate was chosen because some samples exhibited minor brittleness and were difficult to test at higher strain rates. Fig. 2 Mechanical properties of photodegradable DN hydrogels determined by tensile tests: A) Stress-strain curves of gels with different percentages of DMSO (25–30 vol%) and amounts of covalent photodegradable crosslinker, ONB-1 (0.06%, 0.3%, 0.6% and 0.12% of ONB-1 is represented by 1, 2, 3 and 4, respectively). Each test was performed by pulling the samples at a constant rate of 20 mm min −1 . B) Tensile strength; C) Elongation at break; D) Elastic modulus calculated from the initial slopes of the stress-strain curves. The error associated with the values presented is the standard deviation of the five valid tests. Fig. 2 Intermediate concentrations of ONB-1 (0.3% and 0.6%) give the hydrogels with the best properties (higher tensile strength, higher elongation at break and higher elastic modulus). For the H25 and H30, 0.3% and 0.6% were the best concentrations, respectively. Hydrogels containing only 0.06% ONB-1 exhibited poor mechanical properties. A low ONB-1 concentration results in a loosely crosslinked network, that cannot withstand mechanical stress. On the other hand, hydrogels with the highest ONB-1 concentrations were also mechanically poor. Denser crosslinked networks, imply PAAm chains with a shorter length. When a load is applied and the chain breaks, the energy stored in the entire chain is dissipated, resulting in low fracture energy [ 12 ]. Formulations containing 25 vol% DMSO exhibit a more uniform change in mechanical properties when the amount of ONB-1 is changed. This suggests that increasing the amount of DMSO could affect the polymerization and crosslinking steps, resulting in hydrogels with greater variability in properties. These results indicate that the best formulation contains 25 vol% DMSO and 0.3% ONB-1 (H25_2), and it was selected for further testing. The effect of strain rate on the mechanical properties of the hydrogels was investigated. Tensile tests were performed at three different strain rates: 20, 50, and 100 mm·min −1 ( Figure S24 ). The strain-softening behaviour of the stress-strain curves is typical of tough hydrogels, which can be attributed to the breaking of the sacrificial bonds [ 56 ]. As expected, the elastic modulus increases with increasing strain rate, while the stretchability decreases. At strain rates of 50 and 100 mm min −1 , the values for elastic modulus are similar ( Table S5 ). To measure dehydration during the tensile test, all specimens were weighed before and after the tests. It was found that the hydrogels lost only ∼3% of the original weight at a higher stretching rate ( Figure S25 ). To minimize the change in properties due to water evaporation [ 57 ], a strain rate of 100 mm min −1 was used in the subsequent tensile tests, where the properties of the control hydrogel and the light-responsive hydrogel (H25_2) were compared. The stress-strain curves of the control and light-responsive hydrogels showed a similar mechanical behaviour ( Fig. 3 ) and their properties are in accordance with the previous work [ 12 ]. The tensile strength, elongation at break and elastic modulus were 165.4 ± 7.5, 23.5 ± 2.2, and 53.4 ± 5.9 kPa for the control hydrogel, and 165.7 ± 18.7, 27.9 ± 3.9, and 56.2 ± 3.5 kPa for the photodegradable gel, respectively ( Table 2 ). The two hydrogels have similar fracture energies ( Table 2 , Figure S26 ). These results show that the replacement of MBAA by the photodegradable crosslinker, and the use of DMSO in the formulation, do not affect the mechanical properties. In fact, slightly better mechanical properties were obtained for the photodegradable hydrogel. These properties result from the synergistic effect achieved by the combination of a highly extensible network and another, less stretchable network, interpenetrated in a topological entanglement [ 58 ]. As a crack in the hydrogel progresses, the more stretchable network bridges the crack and transmits forces to the bulk of the hydrogel, while the less stretchable network ruptures over a significant volume of the hydrogel [ 59 ]. In this case, the PAAm network remains intact and acts as an entropic spring. In contrast, the alginate network serves as a toughener and gradually unzips, resulting in dissipation of stored energy and preventing catastrophic crack propagation in the bulk [ 60 ]. Fig. 3 Mechanical properties of DN hydrogels determined by tensile tests: A) Stress-strain curves of the control hydrogel and the photodegradable hydrogel (H25_2). Each test was performed by pulling the samples at a constant rate of 100 mm·min −1 until rupture; B) Photodegradable hydrogel. Fig. 3 Table 2 Mechanical properties of DN hydrogels: tensile strength, elongation at break, elastic modulus, and fracture energy. The error associated with the presented values is the standard deviation of the five valid tests. Table 2 Mechanical properties Hydrogel samples Control H25_2 Tensile strength (kPa) 165.4 ± 7.5 165.7 ± 15.7 Elongation at break (mm mm −1 ) 23.5 ± 2.2 27.9 ± 3.9 Elastic modulus (kPa) 53.4 ± 5.9 56.2 ± 3.5 Fracture energy (J m −2 ) 6026.2 ± 649 6604.4 ± 557 2.4 Photodegradation of the DN hybrid hydrogels To understand the response of the photodegradable hydrogels, they were characterized by rheological and mechanical tests, and their morphology was evaluated by SEM before and after photoirradiation. Photodegradation was studied using the oscillatory amplitude sweep test to determine the changes in viscoelastic properties. The storage modulus (G′) and loss modulus (G″) were measured by the applied shear stress ( Fig. 4 ). The photodegradable hydrogel without light exposure showed a linear range and the values of G′ and G″ remained unchanged over the entire range of shear stress. The G′ values were higher than the corresponding G″ values, indicating the elastic behaviour of the hydrogel [ 61 ]. Upon irradiation, both G′ and G″ values decreased, indicating softening of the material. After 6 and 24 h of irradiation, the G′ curve intersected the G″ curve at a shear stress of 747 and 181 Pa, respectively. G′ was lower than G″ when the stress was above these critical values, indicating that the hydrogels changed from a solid to a liquid state, due to the breakdown of the network [ 62 , 63 ]. The photodegradation of the ONB-1 crosslinker caused the failure of the PAAm network. When the irradiated hydrogels are subjected to higher load stress, the photodegraded PAAm network cannot withstand the stress to its former extent, resulting in a severe loss of toughness of the material. Fig. 4 Rheological analyses of photodegradable hydrogels (H25_2) before and after UV irradiation, at different irradiation times. Fig. 4 The photodegraded hydrogels were also evaluated by tensile tests ( Fig. 5 ). Considering the rheological results, they were irradiated for 6 and 24 h. An increase in the irradiation time resulted in a greater decrease in the mechanical properties ( Fig. 5 ), which can be attributed to the increasing destruction of crosslinker ONB-1 and the failure of the PAAm network. As expected, the elastic modulus [ 64 ], drastically decrease by 41% and 73% for samples irradiated for 6 and 24 h, respectively ( Table 3 ) [ 64 ]. The tensile strength and elongation at break were 118.4 kPa and 18.9 for 6 h of UV light, and 32.8 kPa and 18.5 for 24 h of UV light, respectively ( Table 3 ). With increasing irradiation time, more ONB-1 cores are photocleaved, leading to a further decrease of tensile strength, elastic modulus and tensile strain. Even though the hybrid hydrogel is composed of an interpenetrating network, the physically crosslinked network cannot respond efficiently to mechanical solicitations if the covalent network is irreversibly destroyed. The results obtained in the tensile tests are consistent with those obtained in the rheological tests. Fig. 5 Stress-strain curves of photodegradable hydrogel (H25_2) without irradiation and after 6 and 24 h of UV irradiation. Each test was performed by pulling the samples to rupture at a constant velocity of 100 mm min −1 . Fig. 5 Table 3 Mechanical properties of DN hydrogels after UV irradiation: tensile strength, elongation at break and elastic modulus. The error associated with the presented values is the standard deviation of the five valid tests. Table 3 Mechanical properties Hydrogel samples H25_2 (6 h) H25_2 (24 h) Tensile strength (kPa) 118.46 ± 8.8 32.8 ± 4.4 Elongation at break (mm mm −1 ) 18.9 ± 6.2 18.5 ± 3.8 Elastic modulus (kPa) 33.4 ± 7.5 15.2 ± 4.8 SEM analysis was performed to observe the morphology of the cross-section before and after photodegradation ( Fig. 6 , Figure S27-S28 ). The morphology of the control hydrogel was also observed. Before irradiation, all hydrogels exhibited a homogeneous structure with a porous interpenetrating network, similar to other reports [ 65 ]. This morphology and interconnectivity between pores are beneficial for biomedical applications, as they facilitate cell adhesion/proliferation, and also drug delivery [ 66 ]. All hydrogels were irradiated for 24 h, as the greatest loss of properties occurred after this time, as indicated by the rheological and tensile tests. While the control hydrogels maintained their homogeneous porous structure regardless of irradiation ( Fig. 6 A–D), the photodegradable ones exhibited a porous structure interconnected with numerous circular holes after light exposure ( Fig. 6 G–H). One hypothesis, these pores are due to the migration of the soluble PAAm segments formed by the degradation of the PAAm network ( Fig. 6 E–H). This morphology analysis confirms the rheological and tensile tests. Since the hydrogel exhibits a higher porosity, after 24 h of irradiation, poor mechanical behaviour is expected. A photo of the photodegradable hydrogel before and after 24 h of irradiation is shown in Figure S29 . Fig. 6 Representative SEM images of the cross-section morphologies of control hydrogels before (A and B) and after 24 h of irradiation (C and D), and photodegradable hydrogels before (E and F) and after 24 h of irradiation (G and H). Fig. 6 2.5 Cytocompatibility of the hydrogels The potential cytotoxic effects of their degradation products were quantified using an AlamarBlue™ HS Cell Viability assay (indirect method). NIH3T3 fibroblast cells were exposed to gel-conditioned media (hydrogels with a thickness of 2 mm and a diameter of 8 mm diameter in 25 mL medium) at various time points (1–21 days of incubation), i.e., the cells were exposed to media in which the gels could continuously release soluble degradation products. The control and the light-responsive hydrogels (H25_2) without and after 24 h of irradiation were evaluated. Fig. 7 shows the relative cell viability (%) for NIH3T3 cells incubated with the extracts. Fig. 7 Results of in vitro cell viability when cells are exposed to gel conditioned medium. Data are represented as means ± standard deviation of three independent experiments with n = 3 samples for each treatment. The statistical significance was indicated as ∗∗∗∗p < 0.0001 by two-way ANOVA with a Tukey post-hoc test. Fig. 7 According to ISO 10993–5:1999, samples with cell viability greater than 75% can be considered non-cytotoxic. The viability of NIH3T3 cells exposed to the gel-conditioned medium was always >75%, indicating that any degradation by-products that may have been generated did not affect cell viability for 21 days. Compared with control hydrogels, the viability of cells exposed to the conditioned medium with photodegradable hydrogel after photodegradation (H25_2) was slightly higher and statistically significant at 1, 3 and 17 days. To corroborate these observations, we also evaluated the interaction of non-irradiated hydrogels (control hydrogel and H25_2 hydrogel) with NIH3T3 cells by confocal microscopy. For this purpose, NIH3T3 cells seeded on the surface of hydrogels were stained with Calcein-AM and BOBO-3 Iodide (LIVE/DEAD™ Cell Imaging Kit, Invitrogen) to compare cell viability in both hydrogels. BOBO-3 Iodide (dead cell indicator) was used to detect apoptotic and necrotic cells and Calcein-AM, a cell permeant dye, as an indicator of live cells. Viable cells emit light green fluorescence and non-viable cells emit red fluorescence. Fluorescence images of NIH3T3 cells cultured with control hydrogel and H25_2 hydrogel are shown in Fig. 8 A and 8B, respectively. Z-stack images showed that the cells internalized the hydrogels after 48 h. Cells in the control hydrogel grew poorly and some of the cells showed irregular morphology, a significant number of dead cells was detected ( Fig. 8 A). In the H25_5 hydrogel, the number of cells growing inside the hydrogel was higher, its morphology was good and no large number of dead cells was observed ( Fig. 8 B). These observations were consistent with the results of the AlamarBlue™ HS Cell Viability assay and with previous reports [ 67 , 68 ] in which the control hydrogels showed a decrease in cell viability, suggesting that the MBAA crosslinker has some effect on cells. This study highlights the good cytocompatibility and safety of the developed ONB-1 based hydrogels and the minimal acute cytotoxicity over long periods of time, which is important for any biomedical application. Fig. 8 Representative Z-stack images captured by confocal microscopy that were reconstructed into a 3D image using ZEN 2.3 Imaging Software. Green cells indicate live cell colonizing the surface and interior of the hydrogels, while dead cells appear in red colour, after 48 h of incubation. The white bar shown the scale is 100 pixel. Fig. 8 2.6 Cell growth and morphology analysis To evaluate the interaction between the cells and the developed hydrogels, NIH3T3 cells were cultured on the hydrogel surface. After 1 day of culture, only a few NIH3T3 cells were attached, but the cells spread very well on the surface of the hydrogels; and showed a round-shaped configuration with some cytoplasmic extensions (cell elongation) ( Fig. 9 A–D). As shown in Fig. 9 D-G, the NIH3T3 cells proliferated significantly on the surface of the hydrogels after the third day of sowing and remained viable in contact with the hydrogel and negative control (K − ). Moreover, the cells are distributed over a large area, have the typical fibroblastic morphology, and a continuous cell layer has formed [ 69 ]. After 72 h of incubation, the photodegradable hydrogels were completely destroyed by irradiation, but their degradation products allow cell proliferation to a large extent. Thus, with or without irradiation, the photodegraded hydrogels (H25_2) exhibit good cell adhesion and excellent cytocompatibility. Fig. 9 Microscopic phase contrast images of NIH3T3 cells grown on the surface of the hydrogels at different degradation time intervals - after 24 h incubation (top) and 72 h incubation (bottom). The magnification of all the photographs is the same with the scale bar equals to 200 μm. Fig. 9 2.7 Case study of application in bioelectronics An emerging application of hydrogels is in wearable biomonitoring [ [70] , [71] , [72] ]. Conductive hydrogel electrodes can be used to measure biopotentials, for monitoring of muscles, heart, and brain activity by electrocardiography (ECG), electromyography (EMG), and electroencephalography (EEG) [ 70 ]. To assess their suitability, we evaluated the quality of the interface between the skin and the electrodes through impedance spectroscopy in a range of 10 −2 Hz–10 5 Hz. Tests were performed for 9 pairs of electrodes 3 hydrogels pairs, 3 stainless steel 316 L, and 3 Medical grade Ag/AgCl pairs (see SI for more information). Fig. 10 A, shows the fitting to the equivalent skin-electrode impedance fitting. Our hydrogel electrodes exhibit a lower impedance even when compared to medical grade Ag/AgCl electrodes, especially at the low frequencies, which are the frequencies of interest for bioelectronics applications such as EMG, ECG, and EEG. Fig. 10 B, shows the R d and C d values. The hydrogel electrodes offer the highest C d values and the lowest R d values, which are both desired properties. Two hydrogels were integrated into a monitoring chest band ( Fig. 10 D), to acquire ECG signal. As can be seen in Fig. 10 C, an excellent signal amplitude can be observed along with an easy visualization of the QRST complex. Fig. 10 Case study of application in bioelectronics: A) Skin-electrode impedance in function of the frequency, for three different electrodes: Ag/AgCl, stainless steel and hydrogel electrodes. B) Cd and Rd values for all electrodes after fitting to the electrical equivalent circuit, during the impedance analysis. C) Portion of the ECG signal obtained with the hydrogel electrodes. D) Setup used for the acquisition of the ECG signal: monitorization chest band with integrated hydrogel electrodes. Fig. 10 As the interest in disposable wearable bioelectronics is rapidly growing, the use of degradable materials is a very important consideration for a sustainable future. This can be extended to other growing applications of hydrogels in energy storage batteries and Supercapacitors."
} | 8,446 |
35146390 | PMC8819398 | pmc | 7,654 | {
"abstract": "Summary Understanding the sets of inter- and intraspecies interactions in microbial communities is a fundamental goal of microbial ecology. However, the study and quantification of microbial interactions pose several challenges owing to their complexity, dynamic nature, and the sheer number of unique interactions within a typical community. To overcome such challenges, microbial ecologists must rely on various approaches to distill the system of study to a functional and conceptualizable level, allowing for a practical understanding of microbial interactions in both simplified and complex systems. This review broadly addresses the role of several conceptual approaches available for the microbial ecologist’s arsenal, examines specific tools used to accomplish such approaches, and describes how the assumptions, expectations, and philosophies underlying these tools change across scales of complexity.",
"conclusion": "Conclusions Unlike in many other disciplines within the field of ecology, microbial ecologists are faced with the inability to make direct observations of the various interactions that occur in their systems of study. To overcome this fundamental obstacle, we must rely on various conceptual frameworks to aid us in our development of a working model of interaction dynamics, given our current level of technological capability and data. In conclusion, co-occurrence networks may be used to pare down complex and high-dimensional compositional data to a simplified, comprehensible description of co-occurrence patterns that represent possible interactions occurring within taxa. Time series analysis can characterize the level of fluidity that interaction structures can exhibit, as well as elucidate time-dependent interactions. Finally, in vitro experimental techniques using synthetic communities and modeling approaches can investigate the validity of predicted relationships as well as validating mechanisms of interaction. Although the result from one single approach may not be conclusive on its own, the combination of these approaches is a powerful method for identifying universal interaction principles that govern global microbial community dynamics. The rate of progress that has been achieved in this field is promising; we are already beginning to see the widespread use and refinement of these tools for application in answering diverse questions in microbial ecology. Moreover, the conceptual approaches discussed in this review are now being advanced further through the incorporation of multi-omic datasets, allowing for an even deeper understanding of microbial interactions via their metabolomes, transcriptomes, and full genomes ( Ruiz-Perez et al., 2021 ; McDaniel et al., 2020 ; Aguiar-Pulido et al., 2016 ). We are optimistic that, similarly to how standardized sequencing protocols ( Gilbert et al., 2014 ) and user-friendly bioinformatic platforms ( Caporaso et al., 2010 ; Bolyen et al., 2019 ; Schloss et al., 2009 ; Schloss, 2020 ) have revolutionized the accessibility of basic microbiome analyses to a broader scientific community, many of the tools described here will follow a similar trajectory and become essential tools for any microbially inclined scientist to incorporate into their arsenal. \n Glossary Agent-based modeling —A simulation framework involving the actions and interactions of autonomous agents to study the behavior of a system and identify what controls its outcomes. Centrality —A method of measuring the degree to which a node is connected to the other nodes within a network, typically used in microbial ecology as a proxy for the influence of a microbial taxon onto the community. Constraint-based metabolic modeling —A set of specific methods and tools used to perform genome-scale metabolic simulations on a matrix associating metabolites to reactions, which can be used to infer biochemical processes at the system level. Co-occurrence networks —A visualization and analysis method that characterizes a microbial community through the depiction of associations found in the relative abundances of its constituent microbial taxa across a set of samples. Dynamic Bayesian networks (DBNs) —A directed graph-based approach that can be used to estimate the dynamic dependencies between nodes (representing either microbial taxa or environmental variables), by modeling nodes as a function of variables in preceding time points. Dynamic flux-balance models —A simulation modeling framework representing the cellular dynamics of a culture system and biochemical processes. Empirical dynamic modeling —An equation-free modeling approach that aims to characterize and predict the behaviors and relationships found within dynamic systems via the reconstruction of attractor manifolds from time series data. Generalized Lotka-Volterra (gLV) —A set of methods that estimate microbial interactions and growth rates via the Lotka-Volterra differential equations of population dynamics. Keystone taxa —Highly connected microbial taxa with disproportionate influence on the maintenance of community structure and/or function. Local Similarity Analysis (LSA) —An analytical method that employs dynamic programming to detect “local” associations that only occur in sub-intervals within time series, as well as to detect time-lagged associations. Microfluidic techniques —A set of techniques and technologies that allow for systems with the capability for precise manipulations of fluids with volumes at the scale of microliters to nanoliters. Network stability —The extent to which a network can lose individual nodes and still maintain its overall structure and function. Time-delayed interaction —A type of biological interaction in which the effect of a microbial member on another member is only experienced by the receiving member after a time lag.",
"introduction": "Introduction Aided by advances in next-generation sequencing methods and computational power, we are well on our way to successfully characterizing the vast and diverse microbial communities of our planet. Through collective sampling and sequencing efforts we have characterized microbial communities from a multitude of environments, ranging from soils, coral reefs, built environments, extreme environments, and various niches in the human body (e.g., Thompson et al., 2017 ; McDonald et al., 2018 ). These efforts have revealed the unequivocal importance of microorganisms in the maintenance of most ecosystems on the planet via processes such as nutrient cycling, biogeochemical reactions, and maintenance of metabolic homeostasis in animal hosts ( Gilbert and Neufeld, 2014 ; Paerl and Pinckney, 1996 ; Hooper et al., 2012 ). As the tools that enable us to observe and characterize the vast microbial world continue to be refined, there is a need to better understand the mechanisms driving the formation, maintenance, and function of microbial communities. However, microbial members do not exist in isolation but instead interact to form a community; therefore, an improved understanding of the principles that explain our observations of the microbial world requires a firm grasp of their various interactions. Understanding the interactions between members of a microbial community has been a fundamental goal in microbial ecology since the inception of the field ( Brock, 1966 ; Tsuchiya et al., 1972 ). Microbial interactions are central to ecosystem function and are hence important to consider for understanding mechanisms of biodiversity maintenance ( Bohannan and Lenski, 2000 ; Kerr et al., 2002 ), community structure ( Faust and Raes, 2012 ), and community function ( Fuhrman, 2009 ). By characterizing community interactions, we can identify keystone taxa ( Banerjee et al., 2018 ). Of importance, analysis of organismal interactions has demonstrated that microbes may have an impact disproportionate to their abundance ( Graham et al., 2016 ) and has led us to understand the importance of rare and/or conditionally rare taxa (which constitute the majority of microbial diversity) ( Shade et al., 2014 ). Interactions can act as a force multiplier of the direct and indirect effects that a keystone or important taxon exerts on a microbial community and therefore can serve as a useful metric of true community contribution. At the more holistic level, elucidation of such interaction dynamics can provide ecologists with insight into how the combined effects of relatively simple microorganisms amplify to produce large-scale emergent functions ( Bernabe et al., 2018 ). As an analogy, one can consider individual microbes as parts of a complex machinery; to reverse engineer its effect one must examine the parts individually as well as examine how each part corresponds to one another. Through the study of microbial individuals and interactions we can increase our understanding of the direct and indirect roles of specific members, predict how the community may respond to perturbations in the environment, and, perhaps, eventually engineer complex microbial communities for our benefit. In theoretical ecology, a biological unit can be thought to interact with another biological unit in one of three ways: positively (+), negatively (−), and neutrally (0). When considering the bidirectionality of interactions between two microbes and the mechanism by which they interact, we can propose classically recognizable categories such as mutualism (++), commensalism (+0), amensalism (−0), predator prey/parasitism (+-), and competition (--) ( Lidicker, 1979 ). Although such categorization suggests a finite nature of interactions that can be grasped for a given system, the study of real-world communities has revealed the complex, nuanced plasticity and dynamic nature of actual interactions. Interaction strengths (or even directionality) can change depending on a multitude of inter-specific, intra-specific, and environmental factors. For example, the mutualistic symbiosis between the dinoflagellate algae Symbiodinium spp. and its scleractinian coral host can shift to a parasitic relationship when ocean waters become excessively warm and/or eutrophic, causing Symbiodinium spp. to sequester more resources and reduce host fitness ( Baker et al., 2018 ). Such issues can obfuscate investigations of ecological interaction dynamics even in the most manageable and well-characterized biological communities. Moreover, scaling from individual interactions to microbial systems introduces additional complexity owing to the massive abundance of diverse microbial taxa present in most natural environments, the majority of which remain uncharacterized ( Zamkovaya et al., 2021 ). Fortunately, the microbial ecologist is now able to access an arsenal of tools to overcome such difficulties and test fundamental hypotheses of microbial interactions. Such tools can allow for the distillation of complex microbial datasets into manageable, conceptualizable systems. In this review we do not aim to extensively cover the technical aspects and methodology of the various analytical techniques or modeling methods in discussion. Rather, our goal is to (1) broadly describe the conceptual role of various tools in answering targeted questions about ecological interaction dynamics and (2) speculate on the future directions that microbial ecology may move toward from the use of these tools and anticipate how such tools may evolve as a response. We aim to contribute an assessment of how the study of interactions may contribute to a practical, useful understanding of global microbial dynamics."
} | 2,883 |
36306787 | null | s2 | 7,655 | {
"abstract": "Microbial assemblages are omnipresent in the biosphere, forming communities on the surfaces of roots and rocks and within living tissues. These communities can exhibit strikingly beautiful compositional structures, with certain members reproducibly occupying particular spatiotemporal microniches. Despite this reproducibility, we lack the ability to explain these spatial patterns. We hypothesize that certain spatial patterns in microbial communities may be explained by the exchange of redox-active metabolites whose biological function is sensitive to microenvironmental gradients. To test this, we developed a simple community consisting of synthetic Pseudomonas aeruginosa strains with a partitioned denitrification pathway: a strict consumer and strict producer of nitric oxide (NO), a key pathway intermediate. Because NO can be both toxic or beneficial depending on the amount of oxygen present, this system provided an opportunity to investigate whether dynamic oxygen gradients can tune metabolic cross-feeding and fitness outcomes in a predictable fashion. Using a combination of genetic analysis, controlled growth environments, and imaging, we show that oxygen availability dictates whether NO cross-feeding is deleterious or mutually beneficial and that this organizing principle maps to the microscale. More generally, this work underscores the importance of considering the double-edged and microenvironmentally tuned roles redox-active metabolites can play in shaping microbial communities."
} | 377 |
36306787 | null | s2 | 7,656 | {
"abstract": "Microbial assemblages are omnipresent in the biosphere, forming communities on the surfaces of roots and rocks and within living tissues. These communities can exhibit strikingly beautiful compositional structures, with certain members reproducibly occupying particular spatiotemporal microniches. Despite this reproducibility, we lack the ability to explain these spatial patterns. We hypothesize that certain spatial patterns in microbial communities may be explained by the exchange of redox-active metabolites whose biological function is sensitive to microenvironmental gradients. To test this, we developed a simple community consisting of synthetic Pseudomonas aeruginosa strains with a partitioned denitrification pathway: a strict consumer and strict producer of nitric oxide (NO), a key pathway intermediate. Because NO can be both toxic or beneficial depending on the amount of oxygen present, this system provided an opportunity to investigate whether dynamic oxygen gradients can tune metabolic cross-feeding and fitness outcomes in a predictable fashion. Using a combination of genetic analysis, controlled growth environments, and imaging, we show that oxygen availability dictates whether NO cross-feeding is deleterious or mutually beneficial and that this organizing principle maps to the microscale. More generally, this work underscores the importance of considering the double-edged and microenvironmentally tuned roles redox-active metabolites can play in shaping microbial communities."
} | 377 |
39543675 | PMC11566637 | pmc | 7,657 | {
"abstract": "Background Although numerous endophytic bacteria have been isolated and characterized from cadmium (Cd) hyperaccumulators, the contribution and potential application of the core endophytic microbiomes on facilitating phytoremediation were still lack of intensive recognition. Therefore, a 2-year field sampling in different location were firstly conducted to identify the unique core microbiome in Cd hyperaccumulators, among which the representative cultivable bacteria of different genera were then selected to construct synthetic communities (SynComs). Finally, the effects and mechanisms of the optimized SynCom in regulating Cd accumulation in different ecotypes of Sedum alfredii were studied to declare the potential application of the bacterial agents based on core microbiome. Results Through an innovative network analysis workflow, 97 core bacterial taxa unique to hyperaccumulator Sedum was identified based on a 2-year field 16S rRNA sequencing data. A SynCom comprising 13 selected strains belonging to 6 different genera was then constructed. Under the combined selection pressure of the plant and Cd contamination, Alcaligenes sp. exhibited antagonistic relationships with other genera and plant Cd concentration. Five representative strains of the other five genera were further conducted genome resequencing and developed six SynComs, whose effects on Cd phytoremediation were compared with single strains by hydroponic experiments. The results showed that SynCom-NS comprising four strains (including Leifsonia shinshuensis , Novosphingobium lindaniclasticum , Ochrobactrum anthropi , and Pseudomonas izuensis ) had the greatest potential to enhance Cd phytoremediation. After inoculation with SynCom-NS, genes related to Cd transport, antioxidative defense, and phytohormone signaling pathways were significantly upregulated in both ecotypes of S. alfredii , so as to promote plant growth, Cd uptake, and translocation. Conclusion In this study, we designed an innovative network analysis workflow to identify the core endophytic microbiome in hyperaccumulator. Based on the cultivable core bacteria, an optimized SynCom-NS was constructed and verified to have great potential in enhancing phytoremediation. This work not only provided a framework for identifying core microbiomes associated with specific features but also paved the way for the construction of functional synthetic communities derived from core microbiomes to develop high efficient agricultural agents. \n Video Abstract Supplementary Information The online version contains supplementary material available at 10.1186/s40168-024-01959-x.",
"introduction": "Introduction Soil cadmium (Cd) contamination not only hampers agricultural productivity but also poses significant health risks to humans through the food chain [ 1 ]. Existing soil remediation strategies involve physical and chemical methods, which are costly and prone to causing secondary pollution [ 2 ]. In contrast, phytoremediation using hyperaccumulator plants offers an in situ, cost-effective, and environmentally friendly alternative for the remediation and resource recovery of heavy metals in farmland [ 3 ]. The efficiency of phytoremediation largely depends on the metal accumulation capacity and aboveground biomass of hyperaccumulator plants. Unfortunately, most hyperaccumulator plants have relatively low biomass, presenting a significant bottleneck in the advancement of phytoremediation technology [ 4 ].\n The plant microbiome extends the functional potential of the host plant and is essential for plant growth, development, and adaptation to environmental stresses [ 5 ]. Although microorganisms cannot directly degrade heavy metals in soil, the success of phytoremediation largely depends on the interactions between the plant microbiome and the host plant [ 6 ]. Compared to plant-associated microbes in other niches, endophytic bacteria, which colonize the interior of the plant, have a closer symbiotic relationship with the host and pose lower environmental risks, making them advantageous for assisting in heavy metal phytoremediation [ 7 ]. Many studies have indicated that the bacterial communities inhabiting hyperaccumulators markedly differ from those in non-hyperaccumulators. For instance, significant differences in the abundance of Bacteroidetes, Firmicutes, and Verrucomicrobia were observed in Cd hyperaccumulator versus non-hyperaccumulator [ 8 ]. Additionally, species from the genera Streptomyces , Sphingomonas , and Sphingopyxis were found to be significantly associated with Cd hyperaccumulation in Sedum plants [ 9 ]. These endophytic bacteria enhanced heavy metal accumulation in host plants by promoting growth and reducing metal toxicity through siderophore secretion, hormone production, phosphate solubilization, and nitrogen fixation [ 10 ]. However, despite the isolation of numerous endophytic bacteria from hyperaccumulators and the identification of mechanisms by which some strains aid in heavy metal phytoremediation, most studies focused on single strains, overlooking their limitations in stability and functionality [ 11 – 13 ]. Furthermore, many conclusions are often based on correlations from omics data analyses. Therefore, the synergistic effects of endophytic bacteria in hyperaccumulators on plant heavy metal phytoremediation and their underlying mechanisms warrant further investigation. The construction of synthetic microbial communities (SynComs) is an effective approach to bridging the gap between single-strain studies and microbiome research [ 14 ]. Researchers can construct SynComs using either a bottom-up or top-down approach, based on reductionist or holistic principles. The bottom-up approach constructs a SynCom by starting with known functional strains and progressively adding species based on their interactions, while the top-down approach selectively assembles a subset of a natural microbiome based on its composition and functional responses to environmental conditions [ 15 ]. Despite both methods being widely employed, the bottom-up approach relies on extensive trial and error and may overlook key nodes in natural microbial networks [ 15 ]. Conversely, the top-down approach depends on prior knowledge of specific genes, pathways, or biological functions, potentially missing interactions and functions within microbial communities that are not well understood or are unknown [ 16 ]. To address this, SynComs can be constructed based on the core microbiome. The plant core microbiome consists of microbial assemblages that are stably associated with the plant or its surrounding environment and have significant impacts on plant growth and health [ 17 ]. These assemblages represent the minimal subset of microbes that stably and efficiently inherit and maintain community functions [ 18 ]. For instance, Luo et al. [ 19 ] constructed an artificial microbial consortium based on core taxa from the endophytic microbiome of peanuts, which suppressed root rot disease and increased yield under continuous cropping conditions. Similarly, Zhang et al. [ 20 ] developed a SynCom based on core microbiota from maize phloem that demonstrated efficient nitrogen fixation within the plant. Identifying the plant core microbiome in a top-down manner, followed by a bottom-up investigation of the interactions among these community members, can more effectively construct SynComs and better elucidate the processes through which endophytic bacteria synergistically support plant remediation efficiency. In this study, we investigated (1) the successional changes in the microbiome of Cd hyperaccumulator, (2) whether the endophytic core microbiome, particularly SynComs constructed from these core microbes, can enhance Cd phytoremediation, and (3) the mechanisms by which SynComs affect plant health and Cd accumulation (Fig. 1 ). We hypothesized that a unique set of core bacteria, crucial for plant Cd hyperaccumulation, existed in the hyperaccumulating ecotype of Sedum but was absent or insignificant in the non-hyperaccumulator. By studying the Cd accumulation characteristics of Sedum plants from different years, regions, and ecotypes, along with their associated endophytic bacterial communities, we identified the core endophytic microbiome associated with plant Cd hyperaccumulation using an integrated network pipeline. Based on the identification results and previously isolated endophytic bacteria from Sedum alfredii , we constructed a preliminary SynCom and investigated the colonization and synergistic effects of its members in sterile S. alfredii seedlings. Guided by these findings, we developed various SynComs and screened for the one with the highest Cd phytoremediation capability through solution culture experiments and genome resequencing. Furthermore, using transcriptomic approaches, we explored its role and underlying mechanisms in regulating the growth and Cd accumulation in two ecotypes of S. alfredii . This study will provide theoretical guidance for identifying core microbiomes associated with specific plant functions and lay a theoretical foundation for the application of SynCom based on endophytic core microbiomes in phytoremediation. Fig. 1 Constructing SynComsbased on endogenous core microbiota for plant Cd remediation. A simplified workflow for identifying core bacterial taxa unique to the hyperaccumulating ecotype (HE), constructing SynComs from core bacteria, and verifying their effects on Cd phytoremediation",
"discussion": "Discussion Identification of core endophytic microbiome associated with Cd hyperaccumulation In hyperaccumulator plants, endophytic bacterial communities regulate Cd accumulation through various mechanisms that include promoting plant growth, enhancing Cd transport, and mitigating Cd toxicity [ 41 – 43 ]. Our investigation revealed that ecotypic variation in Sedum plants significantly influenced the diversity of their endophytic bacterial communities, independent of geography, year, or plant compartment (Table S2). Core genera within these communities play essential roles in maintaining community stability and functional traits [ 21 , 44 ]. To conservatively and comprehensively identify unique core bacterial genera within the hyperaccumulators, we designed an innovative integrated network pipeline (Fig. S5). We identified 97 core bacterial genera specifically present in the hyperaccumulator Sedum , which were closely associated with Cd hyperaccumulation (Fig. 3 ). Among these genera, many are challenging to isolate and culture [ 45 , 46 ]. However, it is encouraging that several cultivable genera have been repeatedly reported to possess strong potential for aiding phytoremediation. For instance, Pseudomonas , a core genus in the roots and shoots of hyperaccumulator Sedum , has been reported to benefit plants through nitrogen fixation, solubilizing phosphorus and potassium, producing IAA, ACC deaminase activity, and siderophore production [ 47 , 48 ]. It was found that Pseudomonas fluorescens enhanced photosynthesis, carbon fixation, and Cd accumulation in S. alfredii [ 49 ]. Similarly, Leifsonia , a core endophytic genus specifically found in the shoots of hyperaccumulating Sedum , contained genes associated with heavy metal resistance and produced plant hormones such as gibberellins and auxins, promoting shoot growth [ 50 ]. Another core genus, Sphingomonas , was identified as enhancing shoot elongation and participating in the transport and detoxification of heavy metals within the plant [ 51 ]. And Wang et al. [ 52 ] revealed that Sphingomonas spp. SaMR12 alleviated Cd stress in mustard by regulating antioxidant enzyme activities. Although the roles and relevance of these biomarkers, core microbiomes, or potentially beneficial taxa have been proposed, their protective mechanisms and functional roles still require in situ validation through individual and collective culture-based methods. Functions of core endophytic microbiota in plant growth and Cd uptake In sterile soil culture experiments, the bias-corrected abundance of six target genera in both the roots and shoots significantly increased after inoculation with SynCom 13 , indicating successful colonization of the host plant roots and migration to the shoots (Fig. 4 a). Network analyses provided evidence of synergistic relationships among inoculated microbes, suggesting that strong interactions within target taxa may ensure the consistent presence and functionality of the core microbiome (Fig. 4 b). Although Alcaligenes was considered a plant-beneficial bacterium, it reduces Cd bioavailability through biomineralization by producing large amounts of organic biominerals [ 53 ]. In this study, Alcaligenes was negatively correlated with Cd concentration and antagonistic to other target genera in the host plants (Fig. 4 b). Conversely, Leifsonia , Novosphingobium , Pseudomonas , Sphingomonas , and Ochrobactrum showed significant positive correlations with each other and with Cd concentrations of plants. These genera likely have synergistic relationships within the plants, enhancing Cd accumulation. Such interactions may provide a selective advantage for co-colonization by community members, stabilizing the core community’s composition and ensuring its persistence in specific habitats [ 54 ]. The growth-promoting responses of plants under abiotic and biotic stress induced by single-strain inoculants have been well-documented [ 55 – 58 ]. However, these strains often failed when applied individually in field conditions due to competition from the native microbiome [ 59 , 60 ]. Consequently, the “one microbe at a time” approach has evolved into creating synthetic microbial communities. Through hydroponic experiments and the SynCom method, we provided evidence that SynComs constructed from the endophytic core microbiome significantly improve host plant Cd accumulation and growth (Fig. 4 c, d). These SynComs included key strains carrying genes essential for host performance, such as those involved in growth-regulating hormone production and nutrient mobilization (Fig. S17). Compared to other SynComs, SynCom-NS demonstrated a significant advantage in promoting plant growth and enhancing Cd hyperaccumulation (Fig. 4 d). Metabolic complementarity is crucial for the stability and efficiency of SynComs, as it ensures effective resource and function sharing among strains [ 61 , 62 ]. Genome resequencing revealed that out of the five candidate strains, strain SaSP1 had the fewest unique growth-promoting genes and limited potential for metabolic exchange (Figs. S18, S19, S20, S21, S22). SynCom-NS improved community performance by excluding strain SaSP1, thereby enhancing metabolic complementarity among the remaining strains. Mechanisms of SynCom-NS in promoting growth and Cd accumulation in S. alfredii Compared to non-hyperaccumulating ecotypes, hyperaccumulator S. alfredii can accumulate extremely high concentrations of Cd in shoots without exhibiting toxicity symptoms [ 63 ]. This differentiation likely results from a combination of genetic variation and environmental pressures, with the molecular basis of hyperaccumulation involving the high transcriptional expression of genes related to heavy metal uptake, transport, and detoxification [ 64 ]. It is well documented that an increase in the number of lateral roots, particularly new lateral roots, contributed to plant Cd uptake from the soil [ 65 , 66 ]. Following SynCom-NS inoculation, both ecotypes of S. alfredii exhibited a significant increase in the number and length of lateral roots, which enhanced Cd uptake in plants (Fig. S23). Plant hormones are critical in root development by regulating cell division, elongation, and differentiation [ 67 ]. Endophytic bacteria promote root development by modulating various plant hormone signaling pathways, such as the interaction between auxin and ethylene/jasmonic acid signaling [ 68 , 69 ]. Transcriptomic analysis indicated that SynCom-NS upregulated the expression of genes associated with multiple plant hormone signaling pathways, thereby promoting root growth and development, which in turn enhanced Cd uptake and accumulation in the host plants (Fig. 5 f). Efficient metal transport is a key trait that allows hyperaccumulating plants to thrive in contaminated environments while effectively extracting and remediating soil heavy metals [ 70 ]. In the pot experiment, SynCom-NS significantly enhanced Cd transport efficiency in two ecotypes of S. alfredii (Fig. 5 b, c). Due to the lack of specific Cd transport proteins, the mechanisms for Cd transport in plants are often closely associated with membrane transporters for other metal ions, including heavy metal ATPases, the natural resistance-associated macrophage protein (Nramp) family, and cation diffusion facilitators [ 71 ]. Therefore, the increased Cd transport capacity in S. alfredii may be attributed to the upregulation of divalent metal ion transporter proteins within the plant (Fig. 5 f, g). As a toxic heavy metal, Cd induces oxidative stress in plants, leading to the accumulation of reactive oxygen species (ROS), which damage cellular structures and functions [ 72 ]. Post-inoculation with SynCom-NS, both ecotypes of S. alfredii showed a significant decrease in H 2 O 2 content and a significant increase in GSH content in their leaves, indicating enhanced antioxidant capacity (Fig. 5 d, e). Plants rely on antioxidant enzymes such as superoxide dismutase (SOD), peroxidase (POD), glutathione peroxidase (GPx), and catalase (CAT), as well as nonenzymatic antioxidants like reduced glutathione (GSH) and flavonoids, to scavenge harmful ROS [ 73 , 74 ]. Genes related to these enzymes were highly upregulated after inoculation (Fig. 5 f). The improved antioxidant capacity likely contributes to the stability and robustness of the hyperaccumulator plants under heavy metal stress [ 75 , 76 ]. Thereby, the upregulation of antioxidant-related genes suggested that SynCom-NS not only supported Cd uptake and accumulation but also mitigated Cd-induced oxidative stress, enhancing overall plant health. In conclusion, we investigated the variation of endophytic bacterial communities in Sedum across different years, locations, and ecotypes, finding that the ecotype strongly influenced bacterial community assembly. An innovative network pipeline was designed to identify 97 core bacterial taxa specifically present in the hyperaccumulator Sedum and associated with Cd hyperaccumulation. Based on these findings and previously isolated endophytic bacteria from S. alfredii , we constructed different SynComs and identified SynCom-NS as the most effective in enhancing plant phytoremediation. Inoculation with SynCom-NS significantly upregulated genes related to Cd transport, antioxidant enzymes, and plant hormone signaling in both ecotypes of S. alfredii , promoting plant growth and Cd accumulation. This study establishes a theoretical foundation for identifying plant-specific functional core endophytic microbiomes and provides robust evidence for applying synthetic microbial communities derived from these core microbiomes to enhance plant Cd phytoremediation."
} | 4,815 |
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