pmid stringlengths 8 8 | pmcid stringlengths 8 11 ⌀ | source stringclasses 2
values | rank int64 1 9.78k | sections unknown | tokens int64 3 46.7k |
|---|---|---|---|---|---|
24031094 | null | s2 | 1,272 | {
"abstract": "Social groups balance flexibility and robustness in their collective response to environmental changes using feedback between behavioural processes that operate at different timescales. Here we examine how behavioural processes operating at two timescales regulate the foraging activity of colonies of the harvester ant, "
} | 80 |
34640083 | PMC8510011 | pmc | 1,273 | {
"abstract": "Ice formation on the aerodynamic surfaces of an aircraft is regarded as a major problem in the aerospace industry. Ice accumulation may damage parts, sensors and controllers and alter the aerodynamics of the airplane, leading to a range of undesired consequences, including flight delays, emergency landings, damaged parts and increased energy consumption. There are various approaches to reducing ice accretion, one of them being the application of icephobic coatings. In this work, commercially available polyurethane-based coatings were modified and deposited on NACA 0012 aircraft airfoils. A hybrid modification of polyurethane (PUR) topcoats was adopted by the addition of nanosilica and three-functional spherosilicates (a variety of silsesqioxane compound), which owe their unique properties to the presence of three different groups. The ice accretion on the manufactured nanocomposites was determined in an icing wind tunnel. The tests were performed under three different icing conditions: glaze ice, rime ice and mixed ice. Furthermore, the surface topography and wetting behavior (static contact angle and contact angle hysteresis) were investigated. It was found that the anti-icing properties of polyurethane nanocomposite coatings strongly depend on the icing conditions under which they are tested. Moreover, the addition of nanosilica and spherosilicates enabled the reduction of accreted ice by 65% in comparison to the neat topcoat.",
"conclusion": "5. Conclusions Ice reduction of up to 65% was achieved by the means of the chemical modification of polyurethane coatings. Coatings with the hybrid modifications SiO 2 + DC88 and SiO 2 + POSS14 were proven to perform better in terms of ice reduction than coatings with only one modifier. In higher temperatures ( − 5 ° C ), i.e., when glaze ice was formed, the coatings with only DC88 or SiO 2 accreted slightly less ice than the coatings modified with POSS14. However, in lower temperatures, when mixed or rime ice were formed, the sole addition of DC88 or POSS14 led to obtaining much better results than the addition of SiO 2 . Moreover, in temperatures of − 10 ° C and − 15 ° C , the best coatings were the ones modified with both SiO 2 and POSS14, which was manufactured according to the authors’ receipt and is not a commercially available compound. It is also the most hydrophobic coating out of the tested ones. The addition of SiO 2 causes an increase in surface roughness. Icephobicity is a superposition of the structural effects (caused by SiO 2 ) and the effects associated with the introduction of perfluorinated functional groups. The POSS14 additive used in the publication differs from the commercial DOWSIL 88 due to the fact that, in one molecule, we have both functional groups that bind chemically to the SiO 2 surface (methoxide groups) as well as surface energy modifiers in the form of alkyl and perfluorinated groups. The variation of wettability in terms of the roughness of the samples may lead to the conclusion that a hierarchical structure was formed in the case of the hybrid modifications.",
"introduction": "1. Introduction In various industries, such as aerospace, telecommunication, automotive or wind power plants, implemented materials are subjected to not only mechanical loads but also adverse weather conditions. One of the most important problems in aviation is ice formation on the aerodynamic surfaces, which may cause major issues, such as the alternation of the aerodynamics of an aircraft, jamming, damage of parts and sensors and even, in the case of thick ice layers, premature stall [ 1 , 2 , 3 ]. These may further lead to emergency landings, flight delays, the obligatory replacement of parts of the machine, increased consumption of energy and, as a result, restricted flight operations [ 4 ]. During the flight, supercooled water droplets are the main source of the accreted ice. When water droplets with a temperature below the freezing point strike the leading surfaces of the aircraft, they may freeze either immediately or after moving across the surface. Spreading may be caused by the relative velocity between the airplane and the surroundings [ 5 ]. The build-up of thick and heavy ice layers may be a result of the gradual accumulation of ice over time due to the consecutive impingement of multiple water droplets [ 6 ]. There are various methods of dealing with the icing problem, including mechanical or chemical ice removal as well as thermal and electrical deicing systems [ 7 , 8 , 9 , 10 ]. The other, presumably more optimal, solution is the application of anti-icing coatings on the surfaces susceptible to ice accretion [ 11 , 12 , 13 ]. Hydrophobic and superhydrophobic coatings are often investigated in terms of icephobicity [ 14 ]. Many polyurethane-based nanocomposite coatings, which were widely described in the literature [ 15 , 16 , 17 ], showed potential in anti-icing application as well. It was found that the hierarchical structure obtained by the addition of nanoparticles (e.g., SiO 2 , TiO 2 , ZrO 2 ) together with a thin layer of highly hydrophobic components (e.g., fluorine compounds, stearic acid, polydimethylsiloxane (PDMS), etc.) rendered the surface superhydrophobic [ 18 , 19 , 20 , 21 , 22 ]. In the last 10 years, organosilicon compounds have drawn great attention due to their effectiveness in creating chemical structures with hydro- and icephobic properties [ 23 ]. Their special usefulness should be explained by the chemical structure and properties of functional groups, characterized by the presence of various organic groups and, on the other hand, silanol groups capable of forming permanent covalent bonds with the surface of steel, concrete, aluminum or alloys. It should be noted here that the role of these connections, resulting from the properties of functional groups and the structure of molecules, is important to understand from the point of view of designing new materials [ 24 ]. Recently, an increase in the surface tension modifying applications using organofunctional silsesquioxanes and their derivatives, e.g., spherosilicates, was observed. Moreover, their effectiveness in the formation of icephobic coatings was noted [ 25 ]. Polyhedral oligomeric silsesquioxanes make a group of organosilicon compounds of well-defined structure, most of them being described by a general formula [RSiO 1,5 ]n, where R may be a hydrogen atom, an alkyl group, an aryl group and their derivatives. The character of this group is interesting due to the possibility of obtaining new, unique properties through various modification procedures and reactive or non-reactive substituents at the silicon atom located in the corner of the cage. Silsesquioxanes are hybrid compounds that combine the features of inorganic (siloxane core of silsesquioxanes) and organic (organic functional groups attached to the core structure) compounds. These reagents owe their popularity to a growing number of applications in various industries, mainly due to good thermal and mechanical properties, dispersion properties as well as the ease of their further functionalization towards desirable rheological or solubility properties [ 24 , 26 ]. Functionalized organosilicon compounds have hydrophobic, often superhydrophobic, properties and are successfully used as surface modifiers to obtain the desired characteristics [ 27 ]. Hydrophobic properties, as well as icephobic ones, depend to a large extent on the surface structure and its free energy. The ability to effectively repel water particles, prevent water condensation inside the structure and reduce the effect of ice adhering to the surface is related to the low free energy of the surface [ 28 ]. Silsesquioxanes derivatives are one of the most effective surface energy modifiers that, due to their multifunctional structure, can also effectively and permanently combine with the structure of the polymer matrix used [ 29 ]. Unfortunately, most of the cited works deal only with wetting properties. There are insufficient studies concerning PUR-based nanocomposite coatings with improved anti-icing properties. F. Carreno et al. [ 30 ] presented the two-step procedure for obtaining the icephobic coatings based on an organic-inorganic sol-gel applied over a modified commercial polyurethane-based paint that is fluoride and nanoparticle-free. The proposed modifications led to the reduction of the adhesion force of the ice up to 80% with respect to the original paint. In another work [ 31 ], the authors measured the water contact angle and sliding angle of in-house synthesized fluorinated polyurethane after exposure in −10 °C. It was presented that the superhydrophobicity of the coating was still achieved after 100 h at −10 °C. Nonetheless, the proposed technologies have several limitations, such as high costs or complicated preparation procedures. Moreover, the type of accumulated ice is an important factor in the measurement of anti-icing properties and thus the obtained results [ 32 , 33 ]. When water freezes in various atmospheric conditions, different types of ice are created. These different types of ice vary in microstructures and densities and behave in different manners when adhering to the investigated surface. The first one, glaze ice, is formed in relatively high temperatures below 0 °C, and it is usually dense, clear and smooth. The second one, rime ice, is formed in lower temperatures and is characterized by a white and feathery appearance; it is also less dense. Discrepancies in the properties of the icing types are caused mainly by differences in their forming. Water droplets turn into glaze ice immediately after contact with a surface. On the contrary, rime ice forms when some of the water droplets move along the surface before freezing, with some of them falling off before changing their state of matter. It is suggested that, due to its physical properties, glaze ice prohibits higher adhesion pressure and, hence, is harder to remove than rime ice. There is also mixed ice, which consists of both rime and glaze ice [ 34 , 35 ]. Various researchers have undertaken the challenge of coming up with prediction models of ice formation in different temperatures [ 36 , 37 , 38 , 39 , 40 ]; however, they are still far from perfect. Among the applications of anti-icing surfaces, there is a need to remove several different types of ice depending on the icing conditions. As a result, it is a limitation of most research that only one type of ice is tested for anti-icing surfaces in each laboratory with the same measurement techniques [ 41 , 42 ]. In order to fill this gap in the literature, in this work, icing wind tunnel tests were carried out in three different temperatures where three different types of ice were accreted (glaze, rime and mixed). Moreover, to avoid edge effect and simulate realistic conditions, the NACA0012 aircraft airfoils were used in this study. Polyurethane coatings with anti-icing properties were modified by the addition of nanosilica and in-laboratory synthesized siloxane-based compounds and applied on NACA profiles by air gun spraying. Measurements of the wettability parameters (static contact angle and contact angle hysteresis) on the investigated surfaces were carried out to determine the relationship between hydrophobic and anti-icing properties. The surface topography was investigated to identify the relationship between roughness and the results obtained in the icing wind tunnel. It was found that the anti-icing properties of polyurethane nanocomposite coatings strongly depend on the icing conditions under which they are tested. Moreover, it was demonstrated that the relationship between hydrophobic and anti-icing properties is not as simple as presented in the literature so far (the “higher hydrophobicity, higher icephobicity” theory). As a result of the performed hybrid modifications of polyurethane chemical composition, the mass of accreted ice on the investigated NACA0012 profiles during the icing wind tunnel tests was significantly reduced (in some cases by around 65%).",
"discussion": "4. Discussion 4.1. Roughness and Wettability In Figure 5 , the relationship between the roughness and contact angle of the samples is shown. The samples with hybrid modifications, SiO 2 + DC88 and SiO 2 + POSS14, are the most hydrophobic ones. They are quite rough. However, the S a value of Sample 3, modified with only SiO 2, is similar to that of Sample 6, yet its contact angle is similar to Samples 4 and 5, which are characterized by smooth surfaces. The possible explanation is that hierarchical structures were achieved for Samples 2 and 6, which resulted in better hydrophobic characteristics. 4.2. Relationship between Roughness, Wettability and Ice Reduction It could be observed in the Results part of this paper that the coatings that achieved the best results in preventing ice accretion of one kind of ice did not necessarily achieve the best outcomes for the other types. Therefore, the rest of this section is divided into three parts in order to discuss in detail the relationship between the tested parameters for glaze, rime and mixed ice. 4.2.1. Glaze Ice In Figure 6 , the relationship between the roughness of the samples, their wettability and ice reduction in − 5 ° C is presented. The highest ice reduction was obtained for Sample 2, which is the roughest one. It also exhibits the second highest contact angle. There seems to be no clear pattern in the aspect of increasing ice reduction by the means of roughness as the values above 62% are achieved by Samples 2, 3 and 4, which are characterized by the highest, medium and lowest values of S a . In terms of wettability, Sample 2 exhibits the second highest contact angle. Similar values of contact angle were measured for Samples 3 and 4, which showed equal ice reduction percentages. Having said that, the trend is disrupted by the fact that Sample 6 is the most hydrophobic one, yet its ice reduction is only 60%. However, in the case of glaze ice, the ice reduction values are very close to each other, especially taking into account their standard deviations. Therefore, it is possible that there is actually a direct correlation between wettability and ice accretion that could not be observed due to the measurements’ uncertainty, apart from the fact that the transition from the hydrophilic surface (reference sample) to the hydrophobic one (chemically modified samples) leads to ice reduction of more than 56%. Based on the forming mechanism of glaze ice, it is suggested that the greater portion of the water droplets fell off the coating before freezing, due to the water-repellent behavior of the surface, leading to lower ice accretion. 4.2.2. Mixed Ice The influence of roughness and wettability on mixed ice accretion is presented in Figure 7 . Sample 6 is represented by the highest ice reduction, medium roughness and highest contact angle. Once again, the influence of roughness on ice accretion is not clear. Nonetheless, there is a clear correlation between the contact angle and ice reduction values. The conclusion may be drawn that the more hydrophobic the coating is, the more icephobic behavior it exhibits. The dependence is not linear as there is a significant decrease in ice reduction for Sample 3 compared to Sample 4, yet the difference in their contact angle is quite small. Having that said, there is clearly a trend. 4.2.3. Rime Ice The anti-icing behavior of coatings in − 15 ° C with rime ice forming was also investigated, as shown in Figure 8 . In the case of rime ice accretion, the most hydrophobic Sample 6 once again exhibits the best anti-icing properties. Moreover, the least hydrophobic Sample 3 is the one with the lowest ice reduction. The wettability of Samples 4 and 5 is similar, and so is their ice reduction value. Both characteristics of Samples 4 and 5 are lower than those of Sample 3. However, the relationship between contact angle and anti-icing cannot be stated as in the case of mixed ice due to the fact that Sample 2 is the second most hydrophobic one yet the second least icephobic. There is no clear correlation between ice accretion and the roughness of the samples. The fact that there was no correlation found between the roughness of the surfaces and ice accretion in any temperature may lead to a conclusion, presented in Part 4.1. of this paper, that some of the samples (namely 2 and 6) may have hierarchical structures formed, while the others do not have such structures."
} | 4,131 |
27739593 | PMC5248637 | pmc | 1,274 | {
"abstract": "Summary \n In general, plants and arbuscular mycorrhizal ( AM ) fungi exchange photosynthetically fixed carbon for soil nutrients, but occasionally nonphotosynthetic plants obtain carbon from AM fungi. The interactions of these mycoheterotrophic plants with AM fungi are suggested to be more specialized than those of green plants, although direct comparisons are lacking. We investigated the mycorrhizal interactions of both green and mycoheterotrophic plants. We used next‐generation DNA sequencing to compare the AM communities from roots of five closely related mycoheterotrophic species of Thismia (Thismiaceae), roots of surrounding green plants, and soil, sampled over the entire temperate distribution of Thismia in Australia and New Zealand. We observed that the fungal communities of mycoheterotrophic and green plants are phylogenetically more similar within than between these groups of plants, suggesting a specific association pattern according to plant trophic mode. Moreover, mycoheterotrophic plants follow a more restricted association with their fungal partners in terms of phylogenetic diversity when compared with green plants, targeting more clustered lineages of fungi, independent of geographic origin. Our findings demonstrate that these mycoheterotrophic plants target more narrow lineages of fungi than green plants, despite the larger fungal pool available in the soil, and thus they are more specialized towards mycorrhizal fungi than autotrophic plants.",
"introduction": "Introduction The interaction between arbuscular mycorrhizal (AM) fungi and over 80% of land plants is one of the most widespread mutualisms on Earth (Smith & Read, 2008 ). AM fungi, which are abundant in most terrestrial ecosystems, are obligatorily associated with the roots of plants and act like extensions of plant root systems to increase the uptake of nutrients, especially phosphorus (Karandashov & Bucher, 2005 ). However, despite the ubiquity of the interaction, the mechanisms that control its above‐ and belowground diversity are not well understood (van der Heijden et al ., 2015 ). Plant diversity and productivity are significantly influenced by the AM fungal diversity in the soil (van der Heijden et al ., 1998 ; Vogelsang et al ., 2006 ). A key component of plant productivity is photosynthetic fixation of inorganic carbon. It is this carbon that plants transfer to their mycorrhizal partners in exchange for soil nutrients (Smith & Read, 2008 ). Occasionally, plant lineages lose the ability to perform photosynthesis but maintain belowground links with mycorrhizal fungi. This phenomenon has long fascinated researchers (e.g. Ramsbottom, 1929 ; McLennan, 1958 ) because, in such systems, the expected outcome is that the fungi would also withdraw their participation in the interaction (Sachs & Simms, 2006 ). Instead, these nonphotosynthetic plants, known as mycoheterotrophs, still harbor AM fungi growing in their roots (e.g. Leake, 1994 ; Bidartondo et al ., 2002 ; Merckx et al ., 2012 ). Mycoheterotrophy is a trophic strategy present in > 20 000 plant species (Merckx, 2013 ). It is characterized by the absence of photosynthesis, with plants obtaining carbon via the mycorrhizal fungi associated with their roots. The only known way in which AM fungi obtain their carbon is through symbiosis with a photosynthetic plant. Thus, mycoheterotrophic plants must rely on established mutualisms between photosynthetic plants and AM fungi, becoming cheaters within three‐partite interactions (Bidartondo, 2005 ; Sachs & Simms, 2006 ). Mycoheterotrophy can occur (1) throughout the life cycle of a plant, such as in some orchids and monotropes, (2) simultaneously with autotrophy, this being termed partial mycoheterotrophy, as in some orchids (Gebauer & Meyer, 2003 ), or (3) during a short period in the life cycle of a plant, being subsequently replaced by an autotrophic mode of nutrition, such as in many ferns and lycopods, and some orchids (but see Gebauer et al ., 2016 ). Thus, mycoheterotrophy can be seen as a dynamic interaction along a continuum of possible outcomes. Because mycorrhizal associations are generally mutualistic (Smith & Read, 2008 ), it is intriguing why, and which, fungi are part of a mycoheterotrophic interaction. In particular, the differences between mycorrhizal associations of mycoheterotrophic and green plants, and potential preferences for particular fungal lineages, remain poorly understood. Many mycoheterotrophic plants are known to have more specialized interactions with basidiomycete fungi (i.e. they interact with fewer fungal lineages) than ectomycorrhizal green plants, presumably to increase their fitness by optimizing host adaptation (Cullings et al ., 1996 ; Bidartondo, 2005 ). However, the level of mycorrhizal specificity for arbuscular mycoheterotrophic plants remains poorly understood, as comprehensive direct comparisons between AM interactions of mycoheterotrophic and green plants have not been reported. To investigate this, data on the mycorrhizal partners of mycoheterotrophic plants need to be generated and compared with those for the fungal communities associated with green plants. In the past few years, the study of fungal diversity patterns has become more important in understanding the mechanisms driving plant biodiversity (Öpik et al ., 2009 ; Davison et al ., 2011 ; Peay et al ., 2013 ). Next‐generation sequencing techniques to identify AM fungi allow assessments of the complex fungal communities in soil and plant roots (Toju et al ., 2014 ). However, species delimitation of the ancient and apparently strictly asexual AM fungi has long been debated and no consensus has been achieved for suitable molecular markers with sufficient resolution for species‐level identification, nor for the cut‐off values to be used in clustering operational taxonomic units for species prediction (Bruns & Taylor, 2016 ). Thus, measuring species richness with standard methods may introduce a bias in the assessment of the composition of fungal communities. To better understand how communities are structured, an integration of phylogenetic structure, trait information and community composition can offer relevant insights into the evolutionary and ecological processes shaping communities (Webb et al ., 2002 ). At the community scale, species should be segregated based on relative strengths of habitat filtering and competition among similar species. Community structure can be phylogenetically clustered, random, or overdispersed on the phylogeny of the entire available pool of species. For example, Kembel & Hubbell ( 2006 ) showed that phylogenetic structure of rainforest tree communities varied among habitats in Panama. They found communities with more closely related taxa than expected by chance (phylogenetically clustered), suggesting strong habitat filtering as the driving force of community assemblages, while other communities were composed of more distantly related taxa (overdispersion), suggesting current or past competitive exclusion between closely related taxa, or convergent evolution of important traits for persistence in such habitats. In this study, we considered a community to be composed of fungal operational taxonomic units (OTUs) belonging to the same trophic level and the same guild (AM fungi: mycorrhizal fungi from the Glomeromycota phylum) co‐occurring spatially in the roots of a plant. We compared the phylogenetic structure of the fungal communities associated with Thismia plants and co‐occurring green plants (comparing plant nutrition types: mycoheterotrophic and autotrophic) confined to the distribution area of the selected mycoheterotrophic lineage, by studying the fungal community composition in their roots using high‐throughput DNA sequencing methods. We considered the level of phylogenetic clustering as a proxy for the mycorrhizal specificity of a plant. A plant species can have specialized mycorrhizal interactions by targeting a single or a few phylogenetically narrow fungal clades, or generalist mycorrhizal interactions by targeting more dispersed phylogenetic fungal lineages. We focused on temperate mycoheterotrophic Thismia species to evaluate the mycorrhizal association patterns within a lineage of closely related mycoheterotrophic plants. Because specificity in biotic interactions may differ considerably over a species’ distribution range (Thompson, 2005 ), we studied the interactions over the geographic range of this Thismia clade. Soil samples were included to estimate the fungal pool available for these species. To evaluate general differences in fungal community structure between mycoheterotrophic and autotrophic plants, we used phylogenetic measures to infer community structure.",
"discussion": "Discussion The plant sampling was designed to investigate the fungal community structure of closely related mycoheterotrophic plant species over their entire geographic range and, at the same time, compare their fungal community structure with that of the surrounding autotrophic plants, as a proxy for mycoheterotrophic and autotrophic types of nutrition, respectively. The soil data were used as a proxy for the diversity of local AM fungi. As expected, the soil presented a higher fungal diversity compared with individual plants, as it harbors the fungal reservoir from which the plant species obtain their fungal partners (Table S1). Our results indicate that, in general, mycoheterotrophic and green plants have distinct fungal community compositions with no geographic pattern (Fig. 2 ; Adonis test). In addition, the five closely related Thismia species tended to associate with more closely related AM fungi more often than expected by chance. Observations of other cases of mycoheterotrophic species growing on narrow phylogenetic lineages of AM fungi have been reported previously, for example Arachnitis (Bidartondo et al ., 2002 ), Afrothismia (Merckx & Bidartondo, 2008 ), Burmannia (Ogura‐Tsujita et al ., 2013 ) and Petrosavia (Yamato et al ., 2011 ). Moreover, we observed that the phylogenetic structure of the fungal communities can vary according to the type of nutrition of a plant (i.e. mycoheterotrophic vs autotrophic; see Fig. 3 ). For the mycoheterotrophic plants, we detected significant NRI and NTI values (Table 1 ). These two indices provide information about community structure that is different from that provided by richness or taxonomic composition. In view of the unequal number of specimens of mycoheterotrophic and green plants and differences in sequencing success, we calculated the improved richness estimator C hao 2 of Chiu et al . ( 2014 ), incorporating a small‐sample correction. This estimator reduces the bias when the heterogeneity of species detection probabilities is relatively high (Chiu et al ., 2014 ). While the estimated richness was higher for the green plants than for the mycoheterotrophic plants, the observed richness was higher for the mycoheterotrophic plants. Considering phylogenetic relatedness among the taxa, we found that, within the Glomeraceae family, the fungi associated with mycoheterotrophic plants belonged to one subclade, while green plants had fungal partners in two subclades (Fig. 1 ). Thus, the higher estimated richness for the green plants corresponded to a higher phylogenetic diversity compared with the mycoheterotrophic plants. The phylogenetic clustering pattern observed in the mycoheterotrophic plants’ fungal communities reflected ecological rather than biogeographic patterns, as there was no geographical structure of the fungal communities. Moreover, the tendency of Thismia species to target the same narrow clades of AM fungi (Fig. S5), and their similar levels of mycorrhizal specificity (Table 1 ), also reconstructed to have been present in the most recent common ancestor of the clade (Fig. S4), strongly suggest that the high level of mycorrhizal specificity is prone to phylogenetic niche conservatism (Harvey & Pagel, 1991 ; Lord et al ., 1995 ), that is, the tendency of these Thismia species to retain similar ecological traits (i.e. similar fungal communities) over time (Wiens & Graham, 2005 ; Wiens et al ., 2010 ). The phylogenetic niche conservatism observed in Thismia may be attributable to a reduction in the potential range of ecological character evolution caused by fixation of ancestral traits, enabling the descendants within this plant lineage to be more successfully adapted in particular and similar habitat types (Lord et al ., 1995 ). The reason for the preference for targeting certain lineages of AM fungi in this mycoheterotrophic interaction is still not well understood. It is certainly not caused by a limited local availability of AM fungi, because we detected a much larger and phylogenetically broader pool of available fungi in the soil. Similar to the explanation for the high host specificity of many parasites, the mycoheterotrophs may fine‐tune their physiology on particular lineages of fungi to maximize their carbon uptake (Leake & Cameron, 2010 ). Alternatively, the mycoheterotrophic plants may be rejected by most fungal lineages in the pool of available fungi, and therefore the pattern would result from an evolutionary arms race (Bidartondo, 2005 ). Therefore, it is our interpretation that the fungal communities associated with these mycoheterotrophic plants might have been shaped not only by habitat filtering (occurrence of the fungal partners in space), but also by an effect of the ancestry of the plant species, which allow this local third‐party cheater ( Thismia ) to participate in the globally mutualistic AM interaction with autotrophic plants. For the green plants, some species showed significantly phylogenetically clustered AM fungal communities (Table 1 ). Specific patterns in the fungal associations of green plants have been previously reported in other studies (e.g. Öpik et al ., 2009 ; Davison et al ., 2011 ; Peay et al ., 2013 ). Nonetheless, other green plants in our study presented a randomly assembled fungal community. This may reflect a different community structure according to plant species, but it may also be an effect caused by an underrepresentation of the fungal communities, which was more likely to occur in the green plants than in the mycoheterotrophic plants because of sampling method limitations. For the green plants we could only collect a few centimeters of the extensive root system, so, because of the scattered pattern of AM fungal colonization along the roots, we may have assessed a limited fraction of the whole diversity, while for the mycoheterotrophic plants, we collected the entire small root system. Nevertheless, we do not think that this underrepresentation of green plants’ fungal communities introduced bias to our results, because although it could be assumed that we were observing partial diversity, we obtained less phylogenetic clustering in green plants than in mycoheterotrophic plants. The phylogenetic clustering of these communities would become even more diluted with the introduction of more phylogenetically different taxa in the analysis, and therefore the specificity would decrease (Webb, 2000 ). Generally, the comparison of fungal communities associated with mycoheterotrophic and autotrophic plants showed that this particular lineage of mycoheterotrophic Thismia species have significantly more specialized interactions than the green plants living in the same regions (Fig. 3 ). Mycoheterotrophic plants had significantly more specialized fungal interactions than green plants, because the mycoheterotrophs showed higher NRI values almost exclusively. Similarly, mycoheterotrophic plants also had generally higher ranks of NTI values (Table 1 ). This suggests that, within the Glomerales subclade targeted by mycoheterotrophic plants, these plants also tend to target specific lineages at a lower taxonomic level. These results support the view that mycoheterotrophic mycorrhizal interactions are highly specialized. By contrast, green plants did not always show significantly clustered patterns. If we excluded the green plants for which we detected fewer than three OTUs (minimum number of OTUs found in the Thismia species), we found that half of the autotrophic plants ( Doryphora sassafras , Bignoniaceae sp., Laurelia novae‐zelandiae and Vitaceae sp.) tended to associate with more closely related main lineages of AM fungi than expected by chance, but generally with lower ranks of positive NRI and NTI values compared with Thismia . We also found that the other half (Apocynaceae sp., Ceratopetalum apetalum , Beilschmiedia tawa and Pomaderris apetala ) did not present a significantly clustered pattern. In conclusion, even though some green plants may also tend to target more closely related AM fungal taxa than expected by chance, in general these green plants have less specialized interactions compared with Thismia . In this study, we tested the association between these two ecological traits (type of plant nutrition (mycoheterotrophic vs autotrophic) and phylogenetic fungal community structure) for these Thismia species and surrounding green plants. The study of fungal community structure needs to be extended to other distantly related lineages of mycoheterotrophic plants before we make generalizations about the processes shaping the fungal interactions involved in mycoheterotrophy. Moreover, understanding how the fungal communities associated with plants in general are assembled can provide us with knowledge of how belowground ecological processes influence the global distribution of plants in ecosystems."
} | 4,431 |
35494131 | PMC9044548 | pmc | 1,275 | {
"abstract": "In this article, we propose an artificial synaptic device based on a proton-conducting peptide material. By using the redox-active property of tyrosine, the Tyr–Tyr–Ala–Cys–Ala–Tyr–Tyr peptide film was utilized as a gate insulator that shows synaptic plasticity owing to the formation of proton electric double layers. The ion gating effects on the transfer characteristics and temporal current responses are shown. Further, timing-dependent responses, including paired-pulse facilitation, synaptic potentiation, and transition from short-term plasticity to long-term plasticity, have been demonstrated for the electrical emulation of biological synapses in the human brain. Herein, we provide a novel material platform that is bio-inspired and biocompatible for use in brain-mimetic electronic devices.",
"conclusion": "Conclusion In summary, our study demonstrates the brain-mimetic performance of three-terminal artificial synapses based on tyrosine-rich peptides. The Y7C peptide, designed to realize the coupling effect between protons and electrons, enabled synaptic plasticity owing to high proton conduction, in addition to low power operation. In an effort to enable its use in artificial spiking neural networks for neuromorphic computing, we explored various aspects of synaptic plasticity, including the PPF, transition from STP to LTP, and synaptic potentiation. Our findings highlight the material potential of the peptide for novel processors and also provide a new strategy for designing proton-based electronics by using tyrosine as a design motif.",
"introduction": "Introduction The recent emergence of artificial intelligence has impacted a wide range of research areas owing to its superior performance in cognitive computing including inference, decision, and prediction, which has been regarded as a human role. 1 The large amount of data and repetitive processing for training have driven increasing demands for the development of high-performance processors. However, conventional processors have parallel processing limits for cognitive computing owing to their von Neumann architecture, which has separate memory and processing units. Transferring data between them induces a considerable waste of time and power, called the von Neumann bottleneck. Neuromorphic devices have emerged to emulate human brain functions to overcome the von Neumann bottleneck. 2–6 In contrast to man-made computers, the biological brain is composed of ∼10 11 neurons and ∼10 15 synapses that process data locally and in parallel, thus affording extreme efficiency in terms of time and energy. 7 Synaptic devices that mimic the fundamental function of synapses have been proposed as building blocks for brain-like processors. 8–10 Several researchers have developed artificial synapses for spiking neural networks by using the timing-dependent electrical characteristics of ion-based devices to realize synaptic plasticity. 11,12 Among the various approaches, synaptic transistors are regarded as promising candidates for artificial synapses owing to their functional similarity to synapses, low power consumption, and controllability of synaptic performance. 13–16 Peptide materials, which are short chains of amino acids, offer significant advantages for use in electronic devices as their chemical and electrical properties can be programmed by designing amino acid sequences, controlling their folding, and inducing assembly. 17–20 More importantly, they play key roles in ion transfer in biological signaling systems, implying their potential role for ion-controlling in electronics. 21 Recently, we designed a certain tyrosine-rich peptide (TRP) to show proton-conducting characteristics using tyrosine. 22–24 Introducing repeating tyrosine units at both ends of the peptide sequences enables high proton-conducting and redox-active insulating properties in thin films. In this regard, we explored the possibility of TRP materials for use in biomedical devices by utilizing their proton-mediated redox reaction as well as their biocompatibility and biodegradability, and further applicability for neuromorphic devices. 25–27 In this letter, we report a proton-gated synaptic transistor using an In–Ga–Zn–O (IGZO) semiconducting film on a Tyr–Tyr–Ala–Cys–Ala–Tyr–Tyr (YYACAYY, Y7C) peptide thin film. The proton-conducting property of the TRP film not only enabled excellent performance with an on/off ratio of around 10 7 but also large hysteresis of the transfer curves owing to the formation of electric double layers of protons. Thus, the timing-dependent synapse-mimetic responses of the drain current modulated by gate voltage spikes are presented. Treating the device as an artificial synapse, we explored its synaptic plasticity including paired-pulse facilitation (PPF), short-term to long-term transition, and potentiation.",
"discussion": "Results and discussion Tyrosine is a redox-active amino acid known to play a key role in various enzymatic reactions in biological systems such as photosynthesis II. 21 Tyrosine transfers protons and electrons simultaneously via an inherent deprotonation of its phenolic hydroxyl group, known as proton-coupled electron transfer (PCET). 21,28 This phenomenon can also be observed in the TRP thin film, where protons are transported via phenolic hydroxyl groups as hopping sites. 24,27 Therefore, the Y7C peptide thin film exhibits high proton conductivity, in contrast to low electron conductivity. This suggests its potential for use in proton-based synaptic devices for neuromorphic applications. Thus, we fabricated an IGZO thin-film transistor with a Y7C peptide film as a gate insulator. The Y7C peptide solution was spin-coated onto a highly doped p-type Si wafer. The thickness of the Y7C film was measured by the AFM (see Fig. S1 † ). Fig. S2 † shows the I – V characteristics of the insulating Y7C film. The IGZO active layer and Mo source/drain metal layers were deposited using RF sputtering and DC sputtering, respectively. \n Fig. 1 shows the schematics of the Y7C peptide synaptic transistor and the corresponding biological synapse between the two neurons. In biological synapses, presynaptic stimuli from pre-neurons induce the emission of neurotransmitters such as Na + , K + , and dopamine to the synaptic cleft, as shown in Fig. 1a . Subsequently, neurotransmitters activate receptors on post-neurons, resulting in postsynaptic responses. 29,30 Changes in synaptic connectivity under stimulus construct memory activity in the brain. Similarly, in the Y7C peptide synaptic transistor, which is shown in Fig. 1b , voltage spikes on the bottom gate corresponding to the presynaptic spikes facilitate current responses through the channel corresponding to the excitatory postsynaptic current (EPSC). Therefore, the Y7C peptide thin film acts as a synapse between the two neurons. Fig. 1 Schematics of biological synapse and corresponding Y7C peptide synaptic transistor. (a) Biological communication between synapses through a synaptic cleft. Neurotransmitter is transmitted from the pre-synapse to the post-synapse, resulting in post-synaptic responses. (b) Driving mechanism of the Y7C peptide synaptic transistor. Presynaptic spikes are applied to the bottom gate electrode, and postsynaptic responses are measured at the drain electrode. Inset shows the chemical structure of the Y7C peptide. \n Fig. 2 shows the electrical characteristics of the Y7C peptide synaptic transistor. The gate voltage sweep induced current modulation, as shown in the transfer curves. Fig. 2a shows the changes in the on-current at a gate voltage of 20 V, and voltage hysteresis at a drain current of 1 μA as a function of the gate voltage sweep rate is shown in Fig. 2b . The on-current values are 27.56 μA, 24.72 μA, and 18.32 μA at sweep rates of 1.7, 4, and 8 V s −1 , respectively. A slower voltage sweep was induced, and a higher current modulation was observed. Thus, the on/off current ratio reached 9.4 ×10 6 at the slowest sweep rate. In addition, the voltage hysteresis values, i.e. , the voltage differences between the forward and reverse sweeps at which the drain current equals 10 μA, are 12.38 V, 14.15 V, and 16.2 V at sweep rates of 1.7 V s −1 , 4 V s −1 , and 8 V s −1 , respectively. A large hysteresis, which increases as the sweep rate increases, indicates that ionic movement in the peptide film is the origin of the gating effect. 31 This result corresponds to our previous results from the electrochemical impedance analysis of the peptide-insulating layer. 32 The response of the transfer curves to repeated gate sweeps is shown in Fig. S3. † Therefore, a presynaptic spike induced a decay curve of the EPSC, as shown in Fig. 2c . This decaying property corresponds to the history-dependent output, resulting in the emulation of synaptic plasticity. As the amplitude of the presynaptic spikes increased, the EPSC decay slowed ( Fig. 2d ). Thus, the relaxation time after the stimulus increased almost linearly with the spike amplitudes. This indicates that the short-term plasticity of the device changes to long-term plasticity depending on the amplitude of the spikes. Thus, the memory property of the device can be modulated by controlling the amplitude of the stimuli, which is an important characteristic of spiking neural networks. Fig. 2 Electrical characteristics of Y7C peptide synaptic transistor. (a) Transfer characteristics under 1 V drain voltage. The arrows indicate sweep directions. (b) On-current (blue) and hysteresis (red) as a function of the sweep rate of transfer curves. On-current values are measured at a gate voltage of 20 V. Voltage hysteresis is calculated as the difference between voltage values at a drain current of 10 μA during forward and reverse sweep. (c) Presynaptic spike (top) and corresponding excitatory postsynaptic current (EPSC) (bottom). (d) Pulse amplitude dependency on the EPSCs. Inset shows the relaxation time, defined as the time required to return to the original current value after stimulus. Several reports have shown that the accumulation of protons under the channel region induces electrostatic effects, enabling carrier generation in the channel. 31,33–35 The Y7C peptides exhibit high proton conductivity, compared to the other peptides, owing to the phenolic OH groups in tyrosine that act as hopping sites for protons and their structural stability from disulfide bonding. 22,27 Fig. 3 shows the mechanism of proton-induced gating phenomenon in the Y7C peptide film. When a positive gate bias is applied to the bottom electrode, protons ( i.e. positively charged hydrogen atoms) move upward through the Y7C peptide layer. Protons accumulate at the interface between the Y7C layer and the IGZO channel layer, thereby forming an electric double layer (EDL). Thus, carrier generation in the IGZO channel is induced, resulting in the current modulation of the device. This mechanism is analogous to the residual effects of Ca 2+ dynamics in biological synapses. Fig. 3 Mechanism proton-induced potentiation and decay in the Y7C peptide synaptic transistor. (a) Proton accumulation-induced carrier generation and excitatory postsynaptic current. Generated current decays with time and is restored to the initial value as accumulated protons are dissipated in the Y7C film. (b) (1) Accumulation of protons near the channel/Y7C interface as a response to gate input. (2) Dissipation and diffusion of protons after removal of input stimulus. (3) Recovery to the initial state before the input stimulus. Red dots and blue dots indicate electrons and protons, respectively. \n Fig. 4 describes the EPSC responses triggered by consecutive presynaptic stimuli representing the emulation of synaptic plasticity. PPF, which denotes the amplitude ratio of the second EPSC response to the first response facilitated by two successive spikes (1 V, 100 ms), was investigated at various time intervals, as shown in Fig. 4a . It was observed that the PPF gradually decreased as the time interval increased. The PPF index, defined as A 2 / A 1 (%), as a function of the time interval, was fitted by using a double exponential decay curve: where x is the interval time; A 1 and A 2 are the initial magnitudes of the rapid and slow phases, respectively; and τ 1 and τ 2 denote the characteristic relaxation times of the respective phases. The fitting shown in Fig. 4b yields A 1 = 9.26%, A 2 = 7.9%, τ 1 = 161.57 ms, and τ 2 = 1398.78 ms. The PPF results suggest that the consecutive stimuli facilitate EPSC. Furthermore, five successive presynaptic pulses (1 V, 1 s) induced a gradual increase in the EPSC amplitude corresponding to potentiation of the synaptic connectivity, as shown in Fig. 4c . The response of the synaptic response to repeated presynaptic pulses is shown in Fig. S4. † Fig. 4 Synaptic behaviors of the Y7C synaptic transistor. (a) EPSCs stimulated by paired pulses with different interval times from 0 s to 4 s. The amplitude and duration of the presynaptic spikes are 1 V and 100 ms, respectively. (b) PPF index as a function of the time interval between paired pulses. (c) Five consecutive presynaptic pulses (top) and the corresponding potentiation of the EPSCs (bottom). The amplitude and duration of the spikes are 1 V and 1 s, respectively. (d) Pulse duration dependency on the EPSCs. (e) EPSCs stimulated by 5 consecutive presynaptic pulses at different pulse durations. The pulse duration dependency on the facilitation of the EPSC was further investigated with a voltage amplitude of 1 V. As shown in Fig. 4d , the facilitation of EPSC increased as the pulse duration increased from 0.25 s to 4 s. Five consecutive presynaptic pulses (1 V) with various pulse durations from 0.25 s to 4 s were applied to the Y7C peptide synaptic transistor ( Fig. 4e ). As the number of stimuli increased, the increase of the EPSC was facilitated independent of the pulse duration. The fabricated Y7C peptide synaptic transistors have analogous synaptic responses to a biological neuron. This makes the implementation of synaptic functions in an artificial device to mimic the processing system of an actual neural network."
} | 3,541 |
30577690 | null | s2 | 1,276 | {
"abstract": "Materials synthesized by organisms, such as bones and wood, combine the ability to self-repair with remarkable mechanical properties. This multifunctionality arises from the presence of living cells within the material and hierarchical assembly of different components across nanometer to micron scales. While creating engineered analogues of these natural materials is of growing interest, our ability to hierarchically order materials using living cells largely relies on engineered 1D protein filaments. Here, we lay the foundation for bottom-up assembly of engineered living material composites in 2D along the cell body using a synthetic biology approach. We engineer the paracrystalline surface-layer (S-layer) of Caulobacter crescentus to display SpyTag peptides that form irreversible isopeptide bonds to SpyCatcher-modified proteins, nanocrystals, and biopolymers on the extracellular surface. Using flow cytometry and confocal microscopy, we show that attachment of these materials to the cell surface is uniform, specific, and covalent, and its density can be controlled on the basis of the insertion location within the S-layer protein, RsaA. Moreover, we leverage the irreversible nature of this attachment to demonstrate via SDS-PAGE that the engineered S-layer can display a high density of materials, reaching 1 attachment site per 288 nm"
} | 338 |
37861333 | PMC10715148 | pmc | 1,277 | {
"abstract": "ABSTRACT Aerobic gammaproteobacterial methanotrophs (gMOB) are key organisms controlling methane fluxes at the oxic-anoxic interfaces of freshwater ecosystems. Under hypoxic environments, gMOB may shift their aerobic metabolism to fermentation, resulting in the production of extracellular organic acids. We recently isolated a gMOB strain representing the Methylobacter spp. of boreal lake water columns (i.e., Methylobacter sp. S3L5C) and demonstrated that it converts methane to organic acids (acetate, formate, malate, and propionate) under hypoxic conditions. Annotation for putative genes encoding organic acid production within the isolate’s genome and in environmental metagenome-assembled genomes (MAGs) representing Methylobacter spp. suggests that the potential for methane conversion into organic acids is widely found among Methylobacter spp. of freshwater ecosystems. However, it is not known yet whether the capability to convert methane to organic acids is restricted to Methylobacter spp. or ubiquitously present among other freshwater gMOB genera. Therefore, we isolated representatives of two additional gMOB genera from the boreal lake water columns, i.e., Methylomonas paludis S2AM and Methylovulum psychrotolerans S1L, and demonstrated similar bioconversion capacities. These genera could convert methane to organic acids, including acetate, formate, succinate, and malate. Additionally, S2AM produced lactate. Furthermore, we detected genes encoding organic acid production within their genomes and in MAGs representing Methylomonas spp. and Methylovulum spp. of lake and pond ecosystems. Altogether, our results demonstrate that methane conversion to various organic acids is a widely found trait among lake and pond gMOB, highlighting their role as pivotal mediators of methane carbon into microbial food webs of freshwater lake and pond ecosystems. IMPORTANCE Aerobic gammaproteobacterial methanotrophic bacteria (gMOB) play an important role in reducing methane emissions from freshwater ecosystems. In hypoxic conditions prevalent near oxic-anoxic interfaces, gMOB potentially shift their metabolism to fermentation, resulting in the conversion of methane to extracellular organic acids, which would serve as substrates for non-methanotrophic microbes. We intended to assess the prevalence of fermentation traits among freshwater gMOB. Therefore, we isolated two strains representing relevant freshwater gMOB genera, i.e., Methylovulum and Methylomonas , from boreal lakes, experimentally showed that they convert methane to organic acids and demonstrated via metagenomics that the fermentation potential is widely dispersed among lake and pond representatives of these genera. Combined with our recent study showing coherent results from another relevant freshwater gMOB genus, i.e., Methylobacter , we conclude that the conversion of methane to organic acids is a widely found trait among freshwater gMOB, highlighting their role as pivotal mediators of methane carbon into microbial food webs."
} | 761 |
35902599 | PMC9334620 | pmc | 1,278 | {
"abstract": "CMOS-based computing systems that employ the von Neumann architecture are relatively limited when it comes to parallel data storage and processing. In contrast, the human brain is a living computational signal processing unit that operates with extreme parallelism and energy efficiency. Although numerous neuromorphic electronic devices have emerged in the last decade, most of them are rigid or contain materials that are toxic to biological systems. In this work, we report on biocompatible bilayer graphene-based artificial synaptic transistors (BLAST) capable of mimicking synaptic behavior. The BLAST devices leverage a dry ion-selective membrane, enabling long-term potentiation, with ~50 aJ/µm 2 switching energy efficiency, at least an order of magnitude lower than previous reports on two-dimensional material-based artificial synapses. The devices show unique metaplasticity, a useful feature for generalizable deep neural networks, and we demonstrate that metaplastic BLASTs outperform ideal linear synapses in classic image classification tasks. With switching energy well below the 1 fJ energy estimated per biological synapse, the proposed devices are powerful candidates for bio-interfaced online learning, bridging the gap between artificial and biological neural networks.",
"introduction": "Introduction As the world becomes more interconnected and data-driven, effective deployment of data-intensive computation methods becomes more critical. Large and complex data structures require constant extrapolation, interpolation, and classification, which are ill-suited for memory-constrained von Neumann architectures 1 . A promising approach for overcoming the power and latency shortfalls of traditional computing is through massively parallel neuromorphic systems 2 , 3 . A wide variety of devices have been proposed to build such systems, from mature technologies such as metal-oxide 4 , 5 and phase change memories 6 , 7 to emerging devices such as electrochemical 8 and magnetic memories 9 – 12 . Most of these systems, however, employ rigid materials, making them less suited for direct integration with biological matter. Direct interfacing of artificial neuromorphic systems with biological living neurons is a highly ambitious goal, which in the long term may lead to effective brain implants and creation of artificial tissue. There have recently been device innovations to this end utilizing organic materials such as maltose-ascorbic acid 13 , zein 14 , PVA 15 , and cellulose 16 but with various deficiencies in synaptic performance. Two-dimensional (2D) materials are a promising material class for bioelectronics 17 , 18 and neuromorphics 19 – 21 due to their unique electronic properties and atomically thin structure, allowing for imperceptible interfacing with tissue. However, existing 2D-material based neuromorphic systems often employ elements that would induce toxicity when interacting with biological systems, e.g., involving elements like Li + ionic carriers 22 , 23 which directly impact the nervous system 24 . Other 2D carbon-based systems have non-ideal conductance responses that negatively impact performance in neuromorphic applications 25 – 27 . As a result, new device innovations are needed for future neuromorphic computing solutions that can directly integrate with biological tissue. The biocompatible graphene-based artificial synaptic transistors (BLAST) introduced in this work are a combination of two flexible, soft, and biocompatible elements: Nafion and graphene. Nafion plays the role of a solid polymeric electrolyte made of a negatively charged polysulfonated backbone 28 with mobile islands of positively charged water/proton clusters (Fig. 1a ). When Nafion is in an environment with a high concentration of protons, channels are formed in the material matrix, allowing for high mobility transport of protons 29 . In contrast, when there is a low concentration of protons, the protonic charge carriers exist in the form of semi-mobile clusters 30 . When a current pulse is applied through the Nafion, we hypothesize that the positively charged clusters move in the opposite direction of electron current and provide an effective change in the local electrical double layer (EDL) at the Nafion-graphene interface, yielding high-precision conductance states for synaptic operation in artificial neural networks. Altogether, the proposed devices feature favorable synaptic characteristics and energy efficiency down to 50 aJ/µm 2 . We evaluate this behavior through neuromorphic simulations on several classification tasks using a prototypical neural network and show that the BLAST devices feature metaplasticity that allows online learning performance exceeding ideal linear, numerical synapse results. Fig. 1 BLAST configuration and functionality. a Photograph of a transparent BLAST device. b 3D schematic of the BLAST device showing source (S), drain (D), and gate (G) electrodes. c Cross-sectional schematic of BLAST device operation in high and low conductance states. Nafion (teal) contains mobile positively charged clusters of protons (dark red) carried through the membrane; source, drain, and gate gold contacts are shown in yellow with source grounded. The pre-synaptic write pulse is labeled I G and the corresponding post-synaptic read current change is labeled I D . Applied post-synaptic voltage (green) is labeled V D . d Measured BLAST conductance vs. time as the gate current is periodically pulsed, showing distinct and repeatable conductance levels. The color/direction and length of the depicted pulses represents the sign and relative amplitude of the applied pulse, respectively. e Transfer characteristics with forward and reverse sweep at various sweep rates (11 mV/sec – blue, 55 mV/sec – green, and 110 mV/sec – yellow). Solid lines represent drain-source current; Dashed lines represent gate-source current. f Performance for positive and then negative trains of 20 write pulses each while gradually increasing current pulse amplitudes from 1 µA (black) to 10 µA (yellow) for 1 ms duration, showing that conductance weights can be modulated by the gate-source current and desired synapse characteristics of high symmetry and linearity."
} | 1,557 |
29222443 | PMC5864196 | pmc | 1,279 | {
"abstract": "Small acidophilic archaea belonging to Micrarchaeota and Parvarchaeota phyla are known to physically interact with some Thermoplasmatales members in nature. However, due to a lack of cultivation and limited genomes on hand, their biodiversity, metabolisms, and physiologies remain largely unresolved. Here, we obtained 39 genomes from acid mine drainage (AMD) and hot spring environments around the world. 16S rRNA gene based analyses revealed that Parvarchaeota were only detected in AMD and hot spring habitats, while Micrarchaeota were also detected in others including soil, peat, hypersaline mat, and freshwater, suggesting a considerable higher diversity and broader than expected habitat distribution for this phylum. Despite their small genomes (0.64–1.08 Mb), these archaea may contribute to carbon and nitrogen cycling by degrading multiple saccharides and proteins, and produce ATP via aerobic respiration and fermentation. Additionally, we identified several syntenic genes with homology to those involved in iron oxidation in six Parvarchaeota genomes, suggesting their potential role in iron cycling. However, both phyla lack biosynthetic pathways for amino acids and nucleotides, suggesting that they likely scavenge these biomolecules from the environment and/or other community members. Moreover, low-oxygen enrichments in laboratory confirmed our speculation that both phyla are microaerobic/anaerobic, based on several specific genes identified in them. Furthermore, phylogenetic analyses provide insights into the close evolutionary history of energy related functionalities between both phyla with Thermoplasmatales. These results expand our understanding of these elusive archaea by revealing their involvement in carbon, nitrogen, and iron cycling, and suggest their potential interactions with Thermoplasmatales on genomic scale.",
"conclusion": "Concluding remarks Ultra-small members of the DPANN superphylum are widely distributed [ 3 – 7 ], nevertheless cultured representatives are limited and their ecological roles are largely unknown. In this study, we have increased the genomic sampling of two DPANN phyla, Micrarchaeota and Parvarchaeota and thereby revealed their distribution in environments, and inferred their metabolic potentials. Although these Micrarchaeota and Parvarchaeota genomes are among the smallest archaeal genomes, they contained pathways for carbon, nitrogen, and iron cycling. The absence of biosynthesis pathways for amino acids and nucleotides indicated their potential dependence on co-occurring community members when nutrients are limited. Moreover, we were able to successfully enrich both phyla in high relative abundance under low O 2 conditions in the laboratory, and comparative genomic analyses indicated the evolutionary history of several energy related proteins between both Micrarchaeota and Parvarchaeota phyla and Thermoplasmatales, providing first insights into their close relationship in nature and laboratory enrichments. Overall, this study reveals shared and specific features of novel genomes from little studied organisms related to the Micrarchaeota and Parvarchaeota lineages and provides new insights into the interactions and functioning of AMD and hot spring communities.",
"introduction": "Introduction Archaea constitute a considerable portion of microbial diversity, and play significant roles in many biogeochemical cycles on Earth [ 1 ]. However, compared to bacteria they are much less understood and fewer genomes have been sequenced [ 2 ]. The recently delineated superphylum DPANN includes several phyla of archaea with small cell and genome sizes and limited metabolic capabilities [ 3 – 6 ]. To date, 48 DPANN draft genomes are available (Supplementary Table 1 ; see references therein) and only two symbiotic Nanoarchaeota co-cultures have been obtained [ 5 , 7 ]. Two DPANN phyla, Micrarchaeota and Parvarchaeota, referred to as Archaeal Richmond Mine Acidophilic Nanoorganisms (ARMAN), were first reported in acid mine drainage (AMD) biofilms of Iron mountain (Richmond, CA, USA) and are among the smallest microorganisms described to date [ 8 , 9 ]. The AMD biofilms in Iron Mountain have been comprehensively studied for microbial ecology and evolution [ 10 ]. Four genomes of ARMAN have been obtained from this site, including ARMAN-1 and ARMAN-2 from Micrarchaeota, and ARMAN-4 and ARMAN-5 from Parvarchaeota. The metabolic functions of ARMAN-2, -4 and -5 in the AMD biofilms have been speculated based on metaproteomic analyses [ 11 ], while ARMAN-1 was published recently only to report its CRISPR–Cas system [ 12 ]. Interestingly, ARMAN cells were observed having interactions with Thermoplasmatales cells via pili-like structures [ 11 ], and this phenomenon was further documented using cryogenic transmission electron microscope technology [ 13 ], while the ecological significance of such interactions remains unclear. Moreover, ARMAN-specific PCR primers and metagenomics have revealed their occurrence in many other AMD-related environments [ 14 – 17 ], indicating wide distributions of related microorganisms in nature. Despite these investigations described above, we know little about their biodiversity, environmental distribution (in other acidic and non-acidic environments), physiologies, and roles in biogeochemical cycling. To address these gaps, we assembled and binned 39 new genomes from metagenomic datasets obtained from two AMD and three hot spring related environments around the world, and the environmental distribution of Micrarchaeota and Parvarchaeota taxa were evaluated by analyzing 16S rRNA gene sequences from those new genomes and NCBI and IMG/M databases. Metabolic potentials of Micrarchaeota and Parvarchaeota were predicted based on functional annotation of their genes, to reveal their metabolic functions and potential roles in nature. Additionally, genomic information likely suggested that ARMAN spp. are microaerobic and/or anaerobic, thus enrichments with inoculum from AMD systems were performed for these elusive archaea (Supplementary Fig. 1 ).",
"discussion": "Results and discussion New Micrarchaeota and Parvarchaeota genomes reconstructed from metagenomes A total of 10 unpublished metagenomic datasets were obtained from two AMD (one AMD outflow and five AMD sediment metagenomes from Fankou mine tailings of China, and two AMD streamer metagenomes from Los Rueldos of Spain) and two hot spring related environments (one hot spring endolithic metagenome from Tengchong of China, one hot spring mat metagenome from Los Azufres National Park of Mexico), and another two data sets were retrieved from public databases (one AMD outflow metagenome from Fankou mine tailings of China [ 15 ]; and one hot spring sediment metagenome from Yellowstone National Park of USA) (Supplementary Figs. 1 and 2 ). Similar to the Iron mountain where ARMAN were first reported, all these sampling sites except the Yellowstone National Park Obsidian pool were characterized by low pH values (Supplementary Table 2 ). A total of ~200 Gbp of raw sequences were obtained from all these 12 metagenomes (Materials and methods; Supplementary Table 3 ). Quality control, de novo assembly and subsequent genome binning from these metagenomes resulted in a total of 27 Micrarchaeota and 12 Parvarchaeota genomes (Supplementary Fig. 3 ). Based on the occurrence of 54 archaeal single-copy genes [ 3 ], the newly constructed genomes showed a completeness of 78–100% (93% on average), and a very low degree of genomic contamination estimates (0.8% on average) (Supplementary Table 4 ). These genomes have a genome size approximating 0.64–1.08 Mb, and on average encoding 912 genes for Micrarchaeota, and 897 genes for Parvarchaeota, which were comparable to those of the four published ARMAN genomes [ 11 , 12 ] (Table 1 and Supplementary Table 5 ). Compared with the Micrarchaeota genomes (unpaired t test, P < 0.05), Parvarchaeota have significantly shorter average gene length (820 bp vs. 843 bp), higher coding density (92.2% vs. 90.4%) and higher frequency of overlapping genes (19% vs. 10%) (Table 1 and Supplementary Table 5 ). Table 1 General features of the ARMAN genomes that newly reconstructed and previously published ARMAN genomes Newly reconstructed Previously published a \n Micrarchaeota Parvarchaeota ARMAN-1 ARMAN-2 b \n ARMAN-4 ARMAN-5 No. of genomes 27 12 1 1 1 1 No. of scaffolds 3–59 (22) 7–78 (32) 66 1 44 73 Total length (Mb) 0.66–1.08 (0.85) 0.64–0.96 (0.80) 0.87 1.01 0.79 0.92 GC content (%) 28.3–54.2 (44.5) 32.9–44.5 (37.4) 45.6 48 34.4 34.2 No. of tRNA genes 27–48 (37) 30–48 (42) 36 38 43 45 No. of protein-coding genes 743–1181 (912) 701–1095 (897) 993 1069 933 1076 Gene length (bp) 793–891 (843) 767–857 (820) 793 859 767 770 Overlapped genes (%) 7–15 (10) 17–20 (19) 9 10 18 20 Coding density (%) 87.3–92.7 (90.4) 90.4–93.4 (92.2) 89.4 91.3 90.7 90.8 Estimated completeness c \n 78–100 (94) 78–98 (92) 89 100 80 85 Contamination (%) d \n 0–2.8 (0.7) 0–2.9 (1.2) 0 0.9 3.3 5.6 \n a The previously published ARMAN genomes were analyzed (annotation and others) as for newly reconstructed ones \n b The closed genome of ARMAN-2 is reported in this study \n c For 54 archaeal single-copy genes (SCGs) previously used for genome completeness evaluation as in [ 3 ]. Four Micrarchaeota genomes were detected with all the 54 SCGs (Supplementary Table 4 ), while not closed \n d The contamination of each genome were evaluated with CheckM [ 26 ] using a set of 149 archaeal SCGs. Those in brackets are average numbers. See Supplementary Table 5 for details \n Relative abundance and microbial composition Though 25 out of 39 new genomes were reconstructed from metagenomic data sets obtained by filtration for small cells (Materials and methods), 17 out of these 25 genomes showed a relative abundance of <1% (Supplementary Fig. 5 ). However, one Micrarchaeota genome (FK_Sedi_bin_12_4) was detected with a relative abundance of 5.3–21.3% in AMD sediment layers of FK_Sedi_C1_3, C1_4 and C1_5), indicating its potential significance in the corresponding AMD sediments. Interestingly, while the microbial composition of the analyzed communities were remarkably different from each other (Supplementary Fig. 6 ), the “alphabet plasmas” (e.g., A-, E-, G-, I-plasma; [ 47 ]) belonging to the order Thermoplasmatales (phylum, Euryarchaeota; class, Thermoplasmata) were detected in all of them. “Alphabet plasma” are abundant inhabitants in AMD ecosystems [ 47 , 48 ], our analyses indicated they may also favor acidic hot spring related environments. Phylogeny and biodiversity of Micrarchaeota and Parvarchaeota Based on a phylogenetic analysis of 16 concatenated ribosomal protein sequences, both Micrarchaeota and Parvarchaeota branched in the DPANN superphylum of the archaeal domain (Fig. 1 ), Micrarchaeota clustered with Diapherotrites, and Parvarchaeota clustered with Nanoarchaeota, Pacearchaeota, and Woesearchaeota. The 16S rRNA gene sequences based phylogeny showed a different pattern as reported in a previous study [ 3 ], with Parvarchaeota clustered with Pacearchaeota and Woesearchaeota, and then clustered with Micrarchaeota (Supplementary Fig. 7 ). With the availability of sufficient genomes obtained in this study, both phylogeny revealed that Micrarchaeota and Parvarchaeota are not monophyletic but two distinct phyla, and should not be combined as one [ 4 ]. Fig. 1 Phylogenetic analyses of Micrarchaeota and Parvarchaeota genomes The phylogenetic tree was constructed based on 16 concatenated ribosomal protein sequences from each Micrarchaeota and Parvarchaeota genome and reference archaeal genomes (or scaffolds with the target ribosomal protein sequences) (Materials and methods). The three archaeal superphyla TACK, Asgard and DPANN, and the number of genomes included for each phylum are shown. Previously published genomes are indicated by arrows, and the metagenomic datasets of “YNP hot spring” and “FK AMD outflow (2010)” were retrieved from public databases. Bootstrap values are based on 100 replicates \n Based on similarity thresholds of 16S rRNA gene sequences for taxonomic level definition (genus, 94.5%; family, 86.5%; [ 36 ]), the previously published ARMAN-1 and -2 represent two genera in a single family, as well as ARMAN-4 and -5 (Supplementary Fig. 7 ). In this study, the newly reconstructed Micrarchaeota genomes represented at least 12 genera within two families, and the Parvarchaeota genomes represented at least three genera within one family, greatly expanding the phylogenetic and genomic diversity of these two lesser known phyla. Environmental distribution of Micrarchaeota and Parvarchaeota Comparison of Micrarchaeota 16S rRNA gene sequences from around the world revealed their considerable biodiversity, especially within AMD and hot springs. Micrarchaeota were also found in a variety of non-acidic environments, including hypersaline mats, soils, peat, freshwater lakes, and underground water, indicating their potential highly adaptive capacities and phylogenetic diversity of at least two classes (Supplementary Fig. 8 ). In contrast for Parvarchaeota, all the retrieved 16S sequences from NCBI GenBank were from AMD-related environments, and were affiliated within the same family as found within the Tengchong acidic endolithic community reported in this study (Materials and methods). The limited distribution of the known Parvarchaeota may be due to their lower phylogenetic diversity, indicating more Parvarchaeota clades remain to be discovered, while their low abundance in nature may hinder this process. For those Micrarchaeota and Parvarchaeota spp. with genomic information obtained in this study, some of them showed clear environmental preference. Micrarchaeota genus 12 and Parvarchaeota genus 1 and 2 members (Supplementary Fig. 7 ) were all obtained from environments with higher temperature (Supplementary Table 2 ). And the three Micrarchaeota members from Fankou AMD sediment tended to have higher relative abundance in the lower layers, which were characterized by a higher Fe 2+ concentration and lower Fe 2+ /Fe 3+ ratio, while the only Parvarchaeota member from these layers (FK_Sedi_55_70) showed the opposite trend (Supplementary Fig. 5 and Supplementary Table 2 ). Comparative genomic analysis based on KEGG Orthology To reveal if there are any clade specific metabolisms for both phyla, a hierarchical clustering analysis was performed based on the occurrence of KEGG Orthology (KO) patterns in each genome (Fig. 2 ) (Materials and methods). Compared to the phylogeny analyses results shown in Fig. 1 (left panels of Figs. 2a, b ), different clades in both phyla generally have their unique gene contents, indicating variations in metabolic potentials between clades. For Micrarchaeota, the non-oxidative pentose phosphate pathway, aspartate-semialdehyde dehydrogenase, saccharopine dehydrogenase and zinc transporter genes were found only in group 1, Carbon monoxide dehydrogenase CooS and arginase genes occurred only in group 3, and ammonium transporter genes were only detected in group 7 (Fig. 2a ). For Parvarchaeota, glutamine synthetase and L-asparaginase genes were exclusively found in group 1 and heptose III glucuronosyltransferase and inositol transporter genes in group 3 (Fig. 2b ). It is reasonable to speculate that the specific gene contents of different clades may help them to inhabit distinct niches when they coexist with each other. A similar trend has been observed for members of Thermoplasmatales AMD archaea, the “alphabet plasmas”, which were also detected in our metagenomic samples. It has been found that the Thermoplasmatales AMD archaea differentiate by subtle genomic differences that allow their co-existence even if they share a great number of metabolic capabilities [ 49 ]. Fig. 2 Comparative analyses of gene contents of Micrarchaeota and Parvarchaeota genomes. For a Micrarchaeota and b Parvarchaeota, the phylogeny cluster pattern (from Fig. 1 ) and the corresponding KEGG Orthology clustering pattern (based on occurrence of KOs in each genome; see Materials and methods) were compared, and the genomes were manually assigned to several clades/groups based on the cluster patterns. The same clade/group in a phylogeny cluster and gene contents clusters were linked with a solid line \n Metabolic potentials of Micrarchaeota and Parvarchaeota In order to resolve the physiological capabilities encoded in these genomes (including the four published ARMAN genomes), we used a variety of functional gene database comparisons for annotation (Materials and methods). Though the metabolisms of Micrarchaeota and Parvarchaeota have been previously predicted based on three genomes [ 11 ]; with a higher number of genomes representing higher phylogenetic diversity, we now have a better understanding of their metabolic versatility. The metabolic potentials of Micrarchaeota and Parvarchaeota based on all 43 genomes are detailed in the following several sections. Cell membrane biosynthesis Isoprenoids are essential in all living organisms, and vital for cell wall and membrane biosynthesis. As detected in other archaea, Micrarchaeota possess genes involved in the mevalonate pathway for biosynthesis of isoprenoid precursors (i.e., isopentenyl diphosphate and dimethylallyl diphosphate; IPP and DMAPP) [ 50 ]. Additionally, the presence of isopentenyl phosphate kinase genes indicates that they also have the alternative pathway for isopentenyl diphosphate synthesis (Supplementary Fig. 9 ). Notably, no genes of the mevalonate pathway or the methylerythritol 4-phosphate pathway [ 51 ] for IPP and DMAPP biosynthesis were detected in Parvarchaeota. However, considering their high genome completeness (Supplementary Table 4 ), it is possible that these pathways are present and the related genes too novel to be identified via sequence similarity comparison. Alternatively, they may obtain isoprenoids from the environment. Stress reponse Many genes related to environmental resistance were detected in both phyla, including those for drugs, antibiotics, heat shock, heavy metals, and oxidative stress (Fig. 3 and Supplementary Table 8 ). Interestingly, 15 Micrarchaeota and 10 Parvarchaeota genomes were detected with genes encoding resistance protein for fosmidomycin, which is an inhibitor of isoprenoid biosynthesis [ 52 ]. Almost all genomes of both phyla carry a superoxide dismutase and an alkyl hydroperoxide reductase allowing for a quick response to oxidative stress. Notably, Micrarchaeota carry a Fe and the Parvarchaeota carry a Mn superoxide dismutase, likely indicating their distinct evolutionary histories of obtaining this function. Interestingly, evidence of Micrarchaeota acting as a pathogen targeting other Bacteria was detected in three genomes that encode for a lytic murine transglycosylase [ 4 ], which could be transported outside of the cell via the Sec-SRP secretion system (Fig. 3a ). Fig. 3 Overview of potential metabolic capabilities. Metabolic pathways were constructed based on the annotation of predicted genes (Materials and methods) and shown for a Micrarchaeota and b Parvarchaeota taxa. The glycolysis and gluconeogenesis pathways, the pentose phosphate pathway, the pyruvate metabolism, beta-oxidation of fatty acids, the TCA cycle and oxidative phosphorylation chain, protein biosynthesis-related pathways, membrane transporters, and other significant metabolisms are shown. The corresponding enzymes are represented by an ID in the figure and Supplementary Table 8 contains the gene copy number of each enzyme as well as of transporters, carbohydrate-degrading enzymes and peptidases. G6P glucose 6-phosphate, F6P fructose 6-phosphate, F1,6BP fructose 1,6-bisphosphate, GAP glyceraldehyde-3-phosphate, 3PG 3-phosphoglycerate, 2PG 2-phosphoglycerate, PEP phosphoenolpyruvate, KDG 2-keto-3-deoxygluconate, GA glyceraldehyde, G3P glycerol-3-phosphate, DHAP dihydroxyacetone phosphate, Ribu-5P ribulose 5-phosphate, Xylu-5P xylulose 5-phosphate, Ribo-5P ribose-5-phosphate, PRPP phosphoribosyl pyrophosphate, Oaa oxaloacetate, Cit citrate, Iso isocitrate, 2-Oxo 2-oxoglutarate, Suc-CoA succinyl-CoA, Succ succinate, Fum fumarate, Mal malate, Glu glutamate, Gln Glutamine, Fd ferredoxin, 3-HB-CoA 3-hydroxybutyryl-CoA, But-CoA Butyryl-CoA, As arsenic \n Amino acid and nucleotide biosynthesis Although Micrarchaeota are able to generate alanine and glutamate respectively from pyruvate and aspartate (Fig. 3a ), these organisms lack biosynthetic pathways for other amino acids, and Parvarchaeota lack biosynthetic pathways for all amino acids. However, both phyla encode for a variety of extracellular (e.g., S16, S53), membrane (e.g., M48, M50), and cytoplasmic (e.g., M01, M24) peptidases and transporters (e.g., amino acid permease) potentially allowing them to scavenge amino acids from the environment and thus to contribute to nitrogen cycling (Fig. 3 and Supplementary Table 8 ). Both phyla appear to lack genes for de novo biosynthesis of nucleotides from phosphoribosyl pyrophosphate (PRPP) (Supplementary Fig. 10 ), albeit some Micrarchaeota might produce PRPP from ribose-5-phosphate (Fig. 3a ). However, complete pentose phosphate pathways (for ribose-5-phosphate generation) were not detected in these phyla, though some Micrarchaeota genomes harbored genes for the non-oxidative pentose phosphate pathway. To date, complete pentose phosphate pathways in Archaea have been detected in only two Nanohaloarchaea [ 53 , 54 ] and two Woesearchaeota [ 3 ]. Consequently, both phyla may acquire nucleotides from the environment and/or other community members, for survival and cell proliferation, though free nucleotides may be very unstable in an acidic habitat where Micrarchaeota and Parvarchaeota are often found (pH value 0.5–4.0; Supplementary Table 2 ). Carbon fixation None of the six known carbon fixation pathways/cycles was detected in the Micrarchaeota and Parvarchaeota genomes, likely indicating that both phyla are heterotrophic. However, the ribulose 1,5-bisphosphate carboxylase/oxygenase (RubisCO), which is integral to the fixation of carbon dioxide, were detected in two Micrarchaeota genomes (Fig. 3a and Supplementary Table 8 ). The genes encoding for RubisCO, adenosine monophosphate (AMP) phosphorylase and ribose-1,5-bisphosphate isomerase were syntenic in these two genomes, indicating these RubisCOs likely function in a pathway for AMP metabolism as detected in other archaea [ 55 ]. Carbohydrate degradation Genes encoding carbohydrate-degrading enzymes (glycoside hydrolases; GH) were detected in 41 out of 43 genomes (Fig. 3 and Supplementary Table 8 ), including the alpha-glucosidase (EC3.2.1.20; GH31) for degradation of starch and disaccharides, beta-glucosidase (EC3.2.1.21; GH1 and GH39) for disaccharides degradation, glucoamylase (EC3.2.1.3; GH15), alpha-amylase (EC3.2.1.1; GH57), and pullulanase (EC3.2.1.135; GH13) for starch degradation, endoglucanase (EC3.2.1.4) for cellulose degradation, and also a glycogen-debranching enzyme. Among them, GH1, GH15 and GH39 families were detected in both phyla, while GH13, GH31, and GH57 families were only detected in Parvarchaeota. This indicates that both phyla can degrade and utilize complex carbon sources from the environment, and that Parvarchaeota may be more versatile with more available related genes. Additionally, we detected that several Parvarchaeota contained genes for glycerol utilization such as the glycerol-3-phosphate dehydrogenase and glycerol kinase (Fig. 3b ). Glycolysis and gluconeogenesis The glycolytic pathway was present, while gluconeogenesis was absent in both phyla (Fig. 3 ). A modified nonphosphorylative Entner–Doudoroff (ED) pathway has been described in other acidophilic archaea [ 56 – 58 ]. Several ED pathway related genes were found in 12 of the Micrarchaeota genomes, including the glucose dehydrogenase, gluconate dehydratase, 2-dehydro-3-deoxy-D-gluconate aldolase, and glyceraldehyde dehydrogenase (Fig. 3a ). Though the pathway was incomplete, these genes were syntenic, indicating that the missing genes were undetectable due to novelty or these archaea are using an alternative pathway. A unique Embden–Meyerhof–Parnas (EMP) glycolysis pathway was detected in all Parvarchaeota (Fig. 3b ), which utilize NAD(P)-dependent nonphosphorylating glyceraldehyde-3-phosphate dehydrogenase for the oxidation of glyceraldehyde-3-phosphate to 3-phosphoglyceric acid, without the formation of 1,3-bisphosphoglyceric acid and ATP [ 59 ]. Similar activities have been detected in other thermoacidophiles [ 60 , 61 ]. For both phyla, their glycolysis pathways could not generate ATP with only NAD(P)H for anabolism, indicating the significance of alternative ATP generation ways for their activity and growth. Pyruvate metabolism Micrarchaeota are able to utilize pyruvate by converting pyruvate to acetyl-CoA using the pyruvate dehydrogenase complex (in 25 genomes) and pyruvate:ferredoxin oxidoreductase (in one genome). It is surprising that these genes were absent in Parvarchaeota, considering they have the potential to use multiple carbon resources (e.g., starch, disaccharides; see above) to generate pyruvate (Fig. 3b ). However, the 2-oxoglutarate/2-oxoacid ferredoxin oxidoreductase (OFOR) detected in Parvarchaeota may convert pyruvate to acetyl-CoA, as evidenced in Sulfolobus tokodaii strain 7 [ 62 ]. Otherwise, Parvarchaeota may transfer pyruvate into the TCA cycle via phosphoenolpyruvate synthase and phosphoenolpyruvate carboxykinase (Fig. 3b ). Moreover, Parvarchaeota genomes encoded for a cytoplasmic ferredoxin (Supplementary Table 8 ), which may have the potential to convert pyruvate. TCA cycle Distinct from other DPANN members [ 3 ], a complete or near-complete TCA cycle was identified in both phyla (Fig. 3 ). All but one Micrarchaeota genome lacked genes encoding succinyl-CoA synthetase transferring succinyl-CoA to succinate in the TCA cycle, however, the detected malate dehydrogenase (oxaloacetate decarboxylating) may generate malate from pyruvate. Additionally, a methylisocitrate lyase gene was detected in seven Micrarchaeota genomes (Fig. 3a ), and may generate succinate from methylisocitrate to complete the TCA cycle. Interestingly, both phyla have a two-subunit type OFOR for converting 2-oxoglutarate to succinyl-CoA, which is often utilized by microaerophilic and strictly anaerobic organisms for redox coupling of ferredoxin [ 63 ]. Aerobic respiration A NADH dehydrogenase was detected in both phyla, however, lacking the NADH-binding module (encoded by nuoEFG) (Fig. 3 ), a feature has been observed in some bacteria [ 64 , 65 ] and all Thermoplasmatales [ 45 ]. Such a NADH dehydrogenase was suggested to accept electrons from reduced ferredoxin produced by pyruvate ferredoxin oxidoreductase or 2-oxoglutarate ferredoxin oxidoreductase enzymes to generate a proton motive force [ 65 ]. Accordingly, the succinate dehydrogenase/fumarate reductase (complex II) may be used as electron inflow into the respiratory chain, as proposed in Cuniculiplasma divulgatum [ 45 ]. A cytochrome bc1 complex was detected as complex III, while the absence of the iron-sulfur subunit in most genomes (only detected in two Micrarchaeota and one Parvarchaeota), raise doubts in its involvement in a respiratory chain. Both phyla contained a cytochrome bd-II terminal oxidase, which was reported to be induced under O 2 limiting conditions as cytochrome bd-I [ 66 ], and other terminal oxidase genes were absent. A V-type H + -transporting ATP synthase containing 9 subunits was encoded in both phyla for ATP production. Fermentation Based on their gene content both phyla have the capacity to ferment and respire aerobically (Fig. 3 and Supplementary Table 8 ). Most Micrarchaeota likely are able to ferment alcohol via the aldehyde dehydrogenase and alcohol dehydrogenase (Fig. 3a ). Conversely, only alcohol dehydrogenase genes were detected in Parvarchaeota, which may use the acetaldehyde produced via deoxyribose-phosphate aldolase as substrate (Fig. 3b ). Additionally, evidence for butyrate fermentation were also detected in 16 Micrarchaeota genomes (Fig. 3a ). Genes encoding an ADP-forming acetyl-CoA synthetase, which is responsible for acetate production and ATP generation from acetyl-CoA [ 67 ], were detected in both phyla, indicating their potential in acetate fermentation (Fig. 3 ). Potential iron oxidation Interestingly, we detected an operon containing homologous proteins of rusticyanin (copper blue) and multicopper oxidases in six Parvarchaeota genomes (Fig. 4a ). Structural prediction indicated two hypothetical proteins in the operon, a multicopper oxidase and one rusticyanin containing a transmembrane motif, while the other rusticyanin was a periplasmic or extracellular protein, and the third hypothetical protein was located in the cytoplasm (Supplementary Table 9 ). Similar rusticyanin proteins have been shown to be involved in iron oxidation in Acidithiobacillus ferrooxidans [ 68 ] (Fig. 4b ). Considering the high availability of ferrous iron in the AMD environments populated by Parvarchaeota (Supplementary Table 2 ), they are likely involved in iron oxidation, which is speculative and requires experimental confirmation. Fig. 4 Cluster of rusticyanin related genes detected in Parvarchaeota. a A rusticyanin cluster was detected in 6 Parvarchaeota genomes between a MscS (small-conductance mechanosensitive channel-like) gene and a hypothetical protein and a PEP (phosphoenolpyruvate) carboxykinase gene (middle panel). No inserted cluster was found in other Parvarchaeota (above panel). The cluster includes two rusticyanin proteins, one multicopper protein and three hypothetical proteins (bottom panel). The amino acid length of all proteins are shown. b Phylogeny analyses of rusticyanin protein sequences encoded in ARMAN (those two in the cluster and others detected in ARMAN) and genomes of confirmed iron oxidizers, also including the similar key iron oxidase of sulfocyanin. The tree was built using MEGAN (version 7.0.14) using Maximum Likelihood method with 100 replicates, bootstrap numbers are shown \n As stated above, genomic analyses of Micrarchaeota and Parvarchaeota revealed that several central metabolic pathways were absent. Both phyla lacked biosynthetic pathways of amino acids with the exception of Micrarchaeota that seems to be able to synthesize alanine and aspartate. Additionally, both phyla did not encode genes for de novo biosynthesis of nucleotides, and only few pentose phosphate pathway genes were detected. Gluconeogenesis was absent in both phyla, several nonphosphorylative ED glycolysis pathway related genes were detected in 12 Micrarchaeota genomes, however, it is so far unclear whether the pathway was complete. In comparison, a full EMP glycolysis pathway was detected in all Parvarchaeota genomes. The TCA cycle was detected to be near complete in all Micrarchaeota genomes (except in FK_AMD_2014_bin_31 and TC_Endo_bin_32). Notably, only FK_AMD_2014_bin_90 contained the gene encoding succinyl-CoA synthetase, while this gene and a complete or near-complete TCA pathway was detected in all Parvarchaeota genomes. Relatedly, parts of the aerobic respiration chain including a cytochrome bc1 complex and a cytochrome bd-II terminal oxidase were detected in both phyla, while the NADH dehydrogenase and succinate dehydrogenase genes were absent in the two abovementioned Micrarchaeota genomes without the TCA cycle. Additionally, no isoprenoid precursors biosynthesis pathway genes were detected in Parvarchaeota, thus hindering the membrane biosynthesis. In summary, the disabilities of both phyla to synthesize amino acids and nucleotides are likely their largest obstacle for their growth, and these molecules may thus be obtained from those in environments and/or other community members. Laboratory enrichment of Micrarchaeota and Parvarchaeota When Micrarchaeota and Parvarchaeota genomes were first reported [ 11 ], they were thought to be aerobic based on their high levels of succinate dehydrogenase in the proteomic pool. However, Ziegler et al. found that ARMAN spp. were detected only to inhabit the anoxic niches of an acidic snottite, indicating they may be anaerobic, which was documented by anaerobic enrichment [ 17 ]. In this study, our broader genomic sampling of both phyla suggests a microaerobic or anaerobic lifestyle based on two clues, (a) an aerobic respiratory chain and fermentation potential were detected, (b) genomes of both phyla encode OFOR and the terminal oxidase cytochrome bd-II, which are often utilized by microaerophilic and strictly anaerobic organisms. To confirm this speculation, we performed enrichments under microaerobic/anaerobic conditions (dissolved oxygen, ~0.4 mg/L) provided with different nutriments (Fig. 5a ; see Materials and methods for details). Fig. 5 Laboratory enrichment of ARMAN from a simulated AMD system. a Diagram showing the experimental design of the enrichment experiment (Materials and methods). The dissolved oxygen concentration was determined when collecting enriched cells. b Relative abundance of taxa in the inoculum and enrichments with different nutriments. The exact numbers for ARMAN taxa are shown, and those from MDA metagenomes are indicated by asterisks. c Circos-based alignment of genomes from enriched communities against those from environmental samples reported in this study. The alignment of Micrarchaeota sp. 2 contained too many scaffolds and is not shown. Each scale on the scaffold represents a length of 20 kbp \n ARMAN were detected in all the three enrichments supplemented yeast extract, peptone, and beef extract, respectively, while found absent in the control treatment lacking nutriment addition (Supplementary Fig. 4 ). This suggests that ARMAN spp. either could not grow in medium without additional nutriment, or were below the detection level of 16S rRNA gene PCR analyses. These results suggested that ARMAN can grow in the three enrichments added with nutriments. Due to the low biomass of enriched communities (likely due to the relatively short growth period of 14 days), we used MDA prior to shotgun metagenome sequencing. Metagenomic co-assembly and genome binning of the three enriched communities obtained two Micrarchaeota (Micrarchaeota sp. 1 and sp. 2) and two Parvarchaeota genomes (Parvarchaeota sp. 1 and sp. 2) (Fig. 5b and Supplementary Fig. 11 ). These enriched genomes showed a high sequence similarity to the genomic bins from the environments, with average amino acid identity (AAI) from 95.2–97.0%. One exception was the Parvarchaeota sp. 1 which exhibited a lower AAI of 77.4% with LR_AMD_bin_3 (Fig. 5c ). As it was reported that MDA may skew the relative abundance analyses [ 46 ], we assessed this bias by comparing the non-MDA inoculum community with its MDA data (in triplicates) (Materials and methods). The three MDA replicates yielded highly consistent results (low SE values; Supplementary Table 10 ) while many of the taxa with relative abundance <0.5% in the non-MDA sample could no longer be detected in the MDA samples. The two Micrarchaeota spp. and the two Parvarchaeota spp. all tended to have higher relative abundance values in the amplified samples (Supplementary Table 10 ). In details, Micrarchaeota sp. 1 raised from 15.04% in the non-MDA sample to 17.85% on average in the three MDA replicates, Micrarchaeota sp. 2 from 2.94 to 4.34% on average, Parvarchaeota sp. 1 from 1.35 to 2.76% on average, and Parvarchaeota sp. 2 from 0.60 to 0.72% on average. For those species in the enrichments, Micrarchaeota sp. 1 has a slightly higher abundance only in the yeast extract enrichment, which may be a result of the MDA treatment as stated above. However, Parvarchaeota sp. 1 and sp. 2, both have a much higher relative abundance in the peptone enrichment (49.03 and 20.00%, respectively), as compared to the inoculum (1.35 and 0.60%, respectively) (Fig. 5b ). Such dominance by the two Parvarchaeota spp. does not seem to be a result of the MDA step. Thus, the water-soluble mixture of polypeptides and amino acids in peptone may be favored by these Parvarchaeota members for their growth in laboratory condition. Additionally, two of the enriched communities were detected with the strict anaerobic microorganism of Desulfitobacterium (Fig. 5c ), which was neither observed in the non-MDA community nor in MDA inoculums, indicating the enrichments also accelerated the growth of other anaerobes. Altogether, all these results abovementioned supported the growth of ARMAN spp. in these enrichments under microaerobic/anaerobic condition. Due to the low biomass of the enriched communities, more direct approaches such as fluorescence in situ hybridization and imaging-based cell quantifications could not be performed. Extended enrichment time period and/or successive transfers are needed in future studies for a better understanding of their physiology and metabolisms. Current knowledge of connection between Micrarchaeota spp. and Thermoplasmatales members During the review course of this manuscript, two stable co-cultures of Micrarchaeota sp. and Thermoplasmatales were reported from samples from AMD-related environments [ 69 , 70 ]. Krause et al. obtained a consortium after 2.5 years of successive transfers in an anoxic medium [ 70 ]. This consortium included one Micrarchaeota sp. (A_DKE), one Cuniculiplasma divulgatum related Thermoplasmatales (C_DKE; sharing 100% 16S rRNA gene sequence similarity with Cuniculiplasma divulgatum ), another Thermoplasmatales member related to Thermogymnomonas acidicola (sharing 91.6% 16S sequence similarity) and a fungus (Fig. 6 and Supplementary Fig. 12 ). CARD-FISH showed A_DKE cells were mostly located in cell agglomerates formed by B_DKE and/or C_DKE. The host of A_DKE could not be determined because no stable co-culture could be obtained that included only A_DKE and one of the two Thermoplasmatales. More recently, Golyshina et al. reported the dependent host of a Micrarchaeota sp. (Mia14) was an isolated Thermoplasmatales sp., Cuniculiplasma divulgatum PM4 (Fig. 6 and Supplementary Fig. 12 ), by using CARD-FISH analyses and thereby confirmed their interaction [ 69 ]. Fig. 6 Phylogenetic analyses of Thermoplasmatales related taxa detected in the microbial communities analyzed in this study. The tree was built using all available Thermoplasmatales related rpS3 sequences detected in the metagenomes, and those of related published genomes (in italic bold) and included A-plasma, I-plasma, E-plasma, G-plasma (also Cuniculiplasma spp.; four genomes in total, while C_DKE lacks rpS3 due to low completeness), Thermoplasma volcanium , Thermoplasma acidophilum , Thermogymnomonas acidicola , and Thermoplasmatales archaeon B_DKE. For a comparison, the G-plasma related spp. in the analyzed communities sharing 100% rpS3 sequence similarity with published genomes, were binned to obtain their genomes (indicated by stars), and these eight G-plasma related genomes share high 16S rRNA simiarity (98.5–100%) and ANI (94.1–99.4%) \n Notably, Micrarchaeota Mia14 lacks the TCA cycle and the respiratory chain is incomplete and consisted only of a V-type H + -transporting ATP synthase and cytochrome bd-II terminal oxidase, thus it remains unclear if Micrarchaeota Mia14 can generate energy by itself, even though it contains an acetyl-CoA synthetase that could generate energy over substrate level phosphorylation. This is consistent with our findings for FK_AMD_2014_bin_31 and TC_Endo_bin_32, which clustered with Micrarchaeota Mia14 on phylogeny (Supplementary Fig. 12a ). Additionally, Mia14 shares a 16S rRNA gene sequence similarity of 95.5% with TC_Endo_bin_32 (no 16S rRNA gene was binned for FK_AMD_2014_bin_31), indicating they belong to the same genus [ 36 ] (Supplementary Fig. 12b ). Altogether, these results suggest that the absence of these pathways could be linked to a specific phylogenetic clade of Micrarchaeota. To date, three experimentally validated examples of interactions between small-sized archaea and their hosts have been reported, Nanoarchaeum equitans and Ignicoccus hospitalis [ 71 ], Nanoarchaeota Nst1 and Sulfolobales spp. [ 72 ], and Candidatus Nanopusillus acidilobi and Acidilobus spp. [ 5 ]. All these small archaea lack most primary biosynthesis pathways, and more importantly, depend on their hosts for energy production, which is likely a key point for such close relationships between these species (“ectoparasitic lifestyle”). Thus, it is important to understand why Micrarchaeota Mia14 (and related group members) lack the whole TCA cycle and contain only some components of respiratory chain, and two distinct scenarios of evolution are proposed. The first one is that, the lowest common ancestor (LCA) of all Micrarchaeota clades analyzed in this study harbored the TCA cycle and complete respiratory chain, which were retained by most of the genomes during their evolution history, except for Micrarchaeota Mia14. And the second, the LCA lacked the TCA cycle and respiratory chain, and most Micrarchaeota clades gained these functionalities during their evolution history, while the Micrarchaeota Mia14 related clade only obtained part of them. To distinguish between these two scenarios, we searched for homologs involved in energy generation by searching for related proteins in NCBI and subsequently performed phylogenetic analyses (Materials and methods). First, we analyzed energy generation related components shared by Micrarchaeota Mia14 and other Micrarchaeota spp., that is, V-type H + -transporting ATP synthase and cytochrome bd-II terminal oxidase and acetyl-CoA synthetase. To reconstruct their evolution history, homologs searching of related proteins in NCBI and subsequent phylogenetic analyses were performed (Material and methods). Phylogenetic analyses of ATP synthase subunit D showed all Parvarchaeota and most Micrarchaeota spp. clustered with Thermoplasmatales members. Interestingly, seven Micrarchaeota spp. (five of them were from Family 1 Micrarchaeota; Supplementary Fig. 7 ) showed a distinct evolutionary history with different genetic structure of the ATP synthase complex (Supplementary Fig. 13a ), and all these members lacked the cytochrome bd-II terminal oxidase. For Mia14 and 16 Micrarchaeota and 13 Parvarchaeota genomes that encoded a cytochrome bd-II terminal oxidase, a phylogenetic analyses of both subunits (I and II) consistently revealed their evolutional connections with those from Thermoplasmatales (Supplementary Fig. 13b, c ). For the acetyl-CoA synthetase, all 33 Micrarchaeota genomes contained both the alpha chain and beta chain, while both subunits were fused as a single gene in Parvarchaeota, which has been reported in Thermoplasmatales such as G-plasma [ 45 ]. A phylogeny analysis of the acetyl-CoA synthetase showed that Micrarchaeota clustered most closely to these proteins in other DPANN members (Supplementary Fig. 13d ), and the phylogenetic pattern was highly consistent with the taxonomic phylogeny shown in Fig. 1 , indicating this functionality was gained by the LCA of all these Micrarchaeota clades. While Parvarchaeota clustered with Methanocaldococcus spp. and only distantly related to Thermoplasmatales (Supplementary Fig. 13d ). Next, we investigated the phylogeny of other TCA cycle and respiratory chain proteins absent in Micrarchaeota Mia14, such as NADH dehydrogenase, succinate dehydrogenase, citrate synthase, aconitate hydratase and others. The succinate dehydrogenase was analyzed based on its flavoprotein subunit and this revealed that, Micrarchaeota spp., ARMAN-2 and all Family 1 Micrarchaeota members (Supplementary Fig. 7 ) and was most closely related to sequences from Caldisphaera lagunensis (Supplementary Fig. 13e ), a thermoacidophilic Crenarchaeota species isolated from a hot spring in the Philippines (Itoh et al., 2003). The other Micrarchaeota and all Parvarchaeota spp. genomes clustered with Thermoplasmatales, indicating that Micrarchaeota spp. have experienced at least two different evolutionary events for the succinate dehydrogenase. Similarly, phylogenetic analyses of the citrate synthase and aconitate hydratase showed their close evolutional history with Thermoplasmatales (Supplementary Fig. 13e–g ). Overall, these phylogenetic analyses revealed that the evolutionary history of energy related pathways in ARMAN are very complex, especially for Micrarchaeota (Supplementary Figs. 13a–g ). The current situation could be well explained by the second evolutionary scenario mentioned above, but this complex scenario might also be caused by several gain and loss events. These results provide first insights into the close evolutionary relationship between both Micrarchaeota and Parvarchaeota with Thermoplasmatales, which is consistent with their co-occurrence in all the analyzed communities (Fig. 6 ) and the two co-culture studies [ 69 , 70 ]. Moreover, the G-plasma related species are likely the potential hosts of some ARMAN members [ 69 , 70 ], and it is surprising to find their extremely high genomic sequence similarities when considering the large geographic distances (eight genomes shown in Fig. 6 were from Europe, Asia, North America, and South America). Our data suggest that most of the Micrarchaeota and Parvarchaeota members analyzed in this study “only” lacked the ability to synthesize amino acids and nucleotides, thus it is reasonable to speculate that they may depend on multiple potential hosts [ 69 ]. The availability of valuable co-cultures will provide ample opportunities to experimentally test these intriguing relationships in future studies."
} | 11,476 |
33930184 | PMC8361744 | pmc | 1,280 | {
"abstract": "Summary \n Recent studies show that the variation in root functional traits can be explained by a two‐dimensional trait framework, containing a ‘collaboration’ axis in addition to the classical fast–slow ‘conservation’ axis. This collaboration axis spans from thin and highly branched roots that employ a ‘do‐it‐yourself’ strategy to thick and sparsely branched roots that ‘outsource’ nutrient uptake to symbiotic arbuscular mycorrhizal fungi (AMF). Here, we explore the functionality of this collaboration axis by quantifying how interactions with AMF change the impact of root traits on plant performance. To this end, we developed a novel functional–structural plant (FSP) modelling approach that simulates plants competing for light and nutrients in the presence or absence of AMF. Our simulation results support the notion that in the absence of AMF, plants rely on thin, highly branched roots for their nutrient uptake. The presence of AMF, however, promotes thick, unbranched roots as an alternative strategy for uptake of immobile phosphorus, but not for mobile nitrogen. This provides further support for a root trait framework that accommodates for the interactive effect of roots and AMF. Our modelling study offers unique opportunities to incorporate soil microbial interactions into root functionality as it integrates consequences of belowground trait expression.",
"conclusion": "Concluding remarks Our work is a first step towards a whole‐plant FSP modelling approach that provides opportunities to explore belowground plant–plant and plant–microbe interactions in a way that was not possible before, either experimentally or with previous (modelling) approaches. We included plant–mycorrhizal fungus interaction into a mechanistic modelling framework that aims to simulate how multidimensional plants interact with multidimensional environments that include both abiotic conditions and biotic interactions to shape plant fitness. Our modelling results support the notion that the collaboration of plants with AMF provides an alternative strategy to a highly branched root system for the uptake of low‐mobility (e.g. P) but not high‐mobility (e.g. N) nutrients. This provides further support for a functional root economics space that accommodates the interactive effect of roots and mycorrhizal fungi, as proposed by Bergmann et al . ( 2020 ). Future developments should see validation of the model on experimental data that covers a range of species that adopt different strategies in the root economics space. This is needed to further elucidate the dynamics of plant–plant and plant–soil interactions, and to advance our understanding of the role of mycorrhizal fungi in extending root trait variation and the functioning of root traits.",
"introduction": "Introduction Plants require multiple resources to grow and reproduce, and display considerable variation in traits related to the acquisition and conservation of these resources. A common hypothesis to explain this variation is the growth–survival tradeoff, which implies that combinations of linked traits map along an axis of functional strategies (Wright et al ., 2004 ). On one end of this axis, we find species with high resource acquisition resulting in fast growth but a short life span. On the other end of this axis, we find conservative strategies with slow growth but a long life span. This tradeoff in functional plant strategies has mainly been demonstrated for leaf traits. For example, acquisitive leaves have a high specific leaf area (SLA) and photosynthetic capacity, while conservative leaves have the opposite (Wright et al ., 2004 ; Poorter & Bongers, 2006 ). Recent attempts to apply this one‐dimensional leaf economics spectrum (LES) to root traits have shown limited success (Kong et al ., 2016 ; Kramer‐Walter et al ., 2016 ; Roumet et al ., 2016 ; Weemstra et al ., 2016 ). Mycorrhizal fungi play a vital role in a recently proposed two‐dimensional – rather than one‐dimensional – belowground trait framework aimed at functionally understanding root trait variation (McCormack & Iversen, 2019 ; Bergmann et al ., 2020 ). Next to the ‘conservation’ axis that compares to the classical one‐dimensional economics spectrum analogous to the LES, a second ‘collaboration’ axis was proposed that reflects a range of strategies from ‘do it yourself’ vs ‘outsourcing’ of nutrient acquisition via mycorrhizal symbiosis (Bergmann et al ., 2020 ; Supporting Information Fig. S1 ). It is well known that the symbiosis between plants and arbuscular mycorrhizal fungi (AMF; Smith & Read, 2010 ; Kiers et al ., 2011 ) plays an important role in the diversity and productivity of plant communities through increased resource acquisition (Van der Heijden et al ., 1998 ; Vogelsang et al ., 2006 ), and only recently have we started to realize that these fungi are intrinsically related with root traits (Laliberté, 2017 ; Kuyper et al ., 2021 ). Root colonization by AMF is positively correlated with root diameter, and hence negatively correlated with specific root length (SRL) (Baylis, 1975 ; St John, 1980 ; Ma et al ., 2018 ; Bergmann et al ., 2020 , but see Maherali et al ., 2016 ). This suggests that plants can rely either on their own root system for nutrient acquisition by having thin roots or on outsourcing of nutrient acquisition to AMF by having thick roots that increase mycorrhizal colonization (Baylis, 1975 ; Freschet et al ., 2021 ). The inclusion of the mycorrhizal symbiosis opens a second dimension in the root economics space that is key to understanding root trait variation (Bergmann et al ., 2020 ). However, we do not know how different strategies along the collaboration axis pay off when plants are competing in mixed stands for limited soil nutrients such as nitrogen (N) and phosphorus (P), which differ greatly in their availability in soils and mobility in the soil matrix. In this study, we aim to further explore this ‘collaboration’ axis with a theoretical exercise that aims to gain a better understanding of how AMF affect the relationship between root traits and the performance of plants competing for above‐ and belowground resources. To this end, we developed a novel three‐dimensional plant growth model that is designed to simulate competitive interactions driven by the basic mechanisms of light acquisition and nutrient acquisition by roots and AMF, which requires simulation of monospecific and mixed stands composed of multiple individually distinct plants. This functional–structural plant (FSP) modelling approach uses explicit representations of both shoot and root architecture and captures the dynamic interactions between plants through the feedback between changing plant phenotype and resource capture, both above and below ground (Evers et al ., 2018 ). The novelty of our approach lies in its focus on dynamic interactions between individually distinct plants through a functional representation of shoots, roots and AMF. This allows us to elucidate how root trait variation affects competitive interactions between plants with equal or differing trait values under nutrient‐limiting conditions, and how AMF associations change these effects of root trait variation.",
"discussion": "Discussion Root trait functionality in association with AMF Here we show that Dinit and LMA are more important to plant performance than FSR and RLR. A decrease in Dinit led to a disproportional increase in plant biomass in mixtures, as the benefits of increased resource acquisition through increased SRL were not offset by the presence of negative feedbacks that would affect thinner roots in reality (e.g. shorter root life span, lower resistance against pathogens, etc.). Essentially, a decrease in Dinit in the model represents an increase in root proliferation rate at no extra cost (i.e. it increases SRL while total root biomass remains the same, leading to increased root length), making it a very beneficial trait from the perspective of nutrient acquisition. For much the same reasons that resulted in a negative sensitivity to changes in the Dinit, a decrease in LMA represents an increase in leaf area and subsequently in light foraging potential, whereas it does not incur costs in the form of a decreased light absorptance of the leaf or a decreased resistance against herbivores or pathogens. Moreover, the Dinit is more important under low‐nutrient conditions, where nutrients are the most limiting resource, and the LMA is more important in high‐nutrient conditions, where light is the most limiting resource. This also explains the reduction in model sensitivity to changes in RLR under increased nutrient conditions, which decreases nutrient limitation and therefore decreases the importance of producing roots compared with leaves. These results reflect the theory on functional equilibria (Poorter et al ., 2012 ), showing that the impact of a trait on plant performance is dependent on the availability of the resource whose acquisition it affects. We also show that mycorrhizal associations change the functionality of first‐order roots under P limitation but not under N limitation. This difference between the role of first‐order roots in N‐ and P‐limiting conditions can be attributed to the way we assumed first‐order roots contribute to the uptake of N and P. The first‐order roots are assumed not to make an additional contribution to the N uptake of second‐order roots, which is mass flow‐limited and therefore the depletion zone around the roots is expected to extend well beyond the first‐order roots. Conversely, the first‐order roots are expected to contribute to P uptake, which is diffusion‐limited and therefore the depletion zone around the roots is expected to extend just beyond the length of the root hairs. This advantage of first‐order roots in P‐limiting conditions disappeared in the presence of AMF, indicated by the negative model sensitivity (Fig. 3d , monostand +AMF). This can be attributed to the AMF being more efficient in taking up P than the first‐order roots owing to the mycorrhizal hyphae having a smaller diameter and a lower C \n min (Silveira & Cardoso, 2004 ; Freschet et al ., 2021 ) than the first‐order roots. The AMF and roots were equally efficient in taking up N, so the addition of AMF did not increase total N uptake of the plant as the roots were already able to deplete the soil of its N in the absence of AMF. The first‐order roots are thus beneficial to plant performance when the plant has to acquire P by itself, but they reduce plant performance when the plants can outsource P acquisition to AMF. Our model therefore supports a two‐dimensional root economics space that includes mycorrhizal interactions (Bergmann et al ., 2020 ). While our model simulated annual dicots, the mechanistic nature of the modelling approach allows us to generalize our conclusions and speculate on the relevance of the results for other plant functional groups. In tree species, AMF have been hypothesized to alter the functional relation of root traits along the acquisition–conservation axis (Weemstra et al ., 2016 ) as AMF associations correlate with root traits that have traditionally been linked to resource conservation strategies, such as a large root diameter, low SRL and long life (Brundrett, 2002 ; Bergmann et al ., 2020 ). Arbuscular mycorrhizal fungi may help trees to ‘escape’ from the classical conservation–acquisition axis by providing a more efficient alternative to roots in the acquisition of immobile nutrients (mainly P; Raven et al ., 2018 ). Our model provides evidence to support this hypothesis as the presence of AMF increased the uptake of P and changed the qualitative effect of the first‐order root density on plant performance under P limitation from positive to negative. Conversely, graminoid species have been shown to fit a one‐dimensional root economics space (Roumet et al ., 2016 ). Graminoids are characterized by the absence of secondary growth and therefore have thinner roots and a higher SRL than dicots. This suggests that graminoids can rely more on their own root system than on AMF for their nutrient acquisition, which is in line with large‐scale experiments that reported lower AMF colonization in monocots vs dicots (Cornwell et al ., 2001 ; Weishampel & Bedford, 2006 ). This is consistent with our results that show plants benefiting from a thin root system in the absence of AMF, despite the fact that our model does not simulate the root architecture of a graminoid. Root phenotypic plasticity In contrast to our simulated plants, real plants react to temporal and spatial heterogeneity of nutrients in the soil with a myriad root physiological and morphological responses (Hodge, 2004 ). These responses integrate both local and systemic signals (Boer et al ., 2020 ) and are strong determinants of the plant’s competitive ability under nutrient‐limiting conditions (Fort et al ., 2014 ). Root architectural responses to maximize P acquisition include a highly branched root system (Niu et al ., 2013 ) and long root hairs (Bates & Lynch, 1996 ), while a sparsely branched root system is optimal for the acquisition of N (Lynch, 2013 ). Our results reflect these optimal phenotypes by showing that first‐order roots benefit the plant under P‐limiting conditions but decrease plant performance under N limitation. Plants can exhibit the root architectural phenotype that optimizes the acquisition of the most limiting nutrient in response to the soil nutrient conditions (Linkohr et al ., 2002 ). However, the extent to which plants show these plastic responses varies greatly between species (Kembel et al ., 2005 ; Mommer et al ., 2011 ), especially in a competitive environment (Mommer et al ., 2012 ; Ravenek et al ., 2016 ). In the future, our model can be extended to simulate the phenotypic plasticity of root systems morphology to the availability of nutrients that differ in their mobility in the soil matrix (e.g. N and P), to capture the variation in these responses and their consequences for plant performance. Size asymmetry in nutrient competition Comparing monostands and mixtures shows that the competitive interactions simulated by the model were size‐asymmetric. Asymmetric competition is the unequal division of resources between plants relative to their size, meaning that larger individuals take a disproportionate share of the available resources compared with their size and thereby suppress the growth of smaller individuals (Weiner, 1990 ). One of the requirements of size‐asymmetric competition is for the resource to be ‘pre‐emptive’ (Schwinning & Weiner, 1998 ), meaning that the acquisition of that resource by one individual denies the acquisition by another individual. Light is the prime example of such a ‘pre‐emptive’ resource, leading to size asymmetry in competitive interactions between plants, which has been demonstrated in game‐theoretical models (Falster & Westoby, 2003 ), individual based models (Dybzinski et al ., 2011 ; de Vries et al ., 2019 ), and in experiments (Ejrnæs et al ., 2006 ). In addition to light, N was another ‘pre‐emptive’ resource in our model as it was quickly depleted from the soil, leading to strong size‐asymmetric competition under N‐limiting conditions. Conversely, P was not so easily depleted from the soil and therefore did not show this competitive size asymmetry. P limitation did lead to a high model sensitivity to changes in the Dinit in both monostands and mixtures, which indicates that this sensitivity is directly caused by a positive feedback loop between root system growth and P uptake rather than being an indirect effect of competition. Competition for belowground resources is generally considered more size‐symmetric than competition for light (Schwinning & Weiner, 1998 ; Cahill & Casper, 2000 ). However, size asymmetry in belowground competition has been predicted in other modelling studies (Gersani et al ., 2001 ; O'Brien et al ., 2005 ) and size‐related root traits allowed competitive suppression of neighbouring plants in an experimental grassland (Semchenko et al ., 2018 ). Our results suggest that nutrient availability and mobility play an important role in determining symmetry of competitive interactions for the nutrient in question. Limitations and further perspectives This modelling approach takes a step towards mechanistic integration of AMF in FSP models, but still lacks several mechanisms that play an important role in plant–plant–AMF interactions. First, our model simulates AMF as an extension of the root system, rather than as individual organisms with their own fitness that actively mediate the C/N/P exchange with their plant hosts. Our model treats roots and AMF additively; that is, that there is no effect of AMF on root biomass. However, studies have suggested that mycorrhizal plants generally have a lower root : shoot mass ratio than nonmycorrhizal plants (Zhang et al ., 2011 ; Veresoglou et al ., 2012 ). While the model posits a lower C min for P uptake for AMF than for roots, it has the same C min values for N uptake for both structures. However, a smaller C min for N uptake for AMF could explain why most plants with thin roots still maintain the mycorrhizal symbiosis, as in mixed stands they could otherwise be outcompeted by mycorrhizal plants (Kuyper & Kiers, 2014 ). We also modelled plants and AMF having similar nutrient requirements, but this could be modified in a further extension of our model that could, for instance, assign AMF biomass a higher N concentration than roots. Under conditions of (strong) N limitation, mycorrhizal plants could then perform more poorly than nonmycorrhizal plants, as has been shown for several grasses (Püschel et al ., 2016 ). Furthermore, plants are typically colonized by several AMF species, which are in turn connected to several individual plants of potentially different species in common mycorrhizal networks (Newman, 1988 ; Smith & Read, 2010 ). This has led to a debate on the mechanisms of C/N/P exchange between these different partners and their role in maintaining the mutualistic relationship between plants and AMF (Johnson et al ., 1997 , 2015; Kiers & Van der Heijden, 2006 ; Bever et al ., 2009 ; Corrêa et al ., 2014 , 2015 ; Werner et al ., 2018 ). This complexity of the C/N/P exchange between plants and AMF has also made it difficult to generalize the role of AMF in mediating the outcome of competitive interactions between plants of the same or different species. Some studies show that shared mycorrhizal networks have little effect on the competitive interactions between plants (Stanescu & Maherali, 2017b ; Milkereit et al ., 2018 ), while other studies show that shared mycorrhizal networks intensify intraspecific competition and alleviate interspecific competition (Moora & Zobel, 1996 ; Walder et al ., 2012 ; Stanescu & Maherali, 2017a ; Weremijewicz et al ., 2018 ). Second, our model simplifies soil processes that can have profound effects on AMF functioning, nutrient stoichiometry and competitive interactions between plants, such as soil water status (Augé, 2001 ; Al‐Karaki et al ., 2004 ) and mineralization of nutrients (Aerts, 2003 ). Third, our model does not include the plastic responses that allow plants to navigate this complex web of interactions with the soil, AMF and competing plants to optimize their C/N/P acquisition. Future developments might see the use of mechanistic FSP models to shed light on the mechanisms that drive these complex three‐way interactions among plants, AMF and the soil environment. Concluding remarks Our work is a first step towards a whole‐plant FSP modelling approach that provides opportunities to explore belowground plant–plant and plant–microbe interactions in a way that was not possible before, either experimentally or with previous (modelling) approaches. We included plant–mycorrhizal fungus interaction into a mechanistic modelling framework that aims to simulate how multidimensional plants interact with multidimensional environments that include both abiotic conditions and biotic interactions to shape plant fitness. Our modelling results support the notion that the collaboration of plants with AMF provides an alternative strategy to a highly branched root system for the uptake of low‐mobility (e.g. P) but not high‐mobility (e.g. N) nutrients. This provides further support for a functional root economics space that accommodates the interactive effect of roots and mycorrhizal fungi, as proposed by Bergmann et al . ( 2020 ). Future developments should see validation of the model on experimental data that covers a range of species that adopt different strategies in the root economics space. This is needed to further elucidate the dynamics of plant–plant and plant–soil interactions, and to advance our understanding of the role of mycorrhizal fungi in extending root trait variation and the functioning of root traits."
} | 5,257 |
36875665 | PMC9978206 | pmc | 1,281 | {
"abstract": "Event cameras are asynchronous and neuromorphically inspired visual sensors, which have shown great potential in object tracking because they can easily detect moving objects. Since event cameras output discrete events, they are inherently suitable to coordinate with Spiking Neural Network (SNN), which has a unique event-driven computation characteristic and energy-efficient computing. In this paper, we tackle the problem of event-based object tracking by a novel architecture with a discriminatively trained SNN, called the Spiking Convolutional Tracking Network (SCTN). Taking a segment of events as input, SCTN not only better exploits implicit associations among events rather than event-wise processing, but also fully utilizes precise temporal information and maintains the sparse representation in segments instead of frames. To make SCTN more suitable for object tracking, we propose a new loss function that introduces an exponential Intersection over Union (IoU) in the voltage domain. To the best of our knowledge, this is the first tracking network directly trained with SNN. Besides, we present a new event-based tracking dataset, dubbed DVSOT21. In contrast to other competing trackers, experimental results on DVSOT21 demonstrate that our method achieves competitive performance with very low energy consumption compared to ANN based trackers with very low energy consumption compared to ANN based trackers. With lower energy consumption, tracking on neuromorphic hardware will reveal its advantage.",
"conclusion": "4. Conclusion In this paper, we propose a novel spiking convolutional tracking network directly trained with SNN, which can process event stream without any other preprocessing operations. We propose a new loss function that introduces an exponential IoU in the voltage domain so as to make SCTN more suitable for object tracking. Moreover, we present a new publicly available event-based tracking dataset, dubbed DVSOT21. Experimental results on DVSOT21 demonstrate that our method achieves competitive performance with very low energy consumption compared to other competing trackers.",
"introduction": "1. Introduction Object tracking is a nontrivial problem in computer vision, and is widely used in security monitoring, sports events broadcasting, robotics, unmanned aerial vehicles and other fields. In recent years, object tracking with traditional cameras has become very mature, represented by algorithms based on Siamese networks (Zhang et al., 2020 , 2021 ) and Transformers (Chen et al., 2021 ; Wang et al., 2021 ; Cui et al., 2022 ). Unfortunately, traditional cameras have difficulty capturing moving objects under extreme conditions of high speed and high dynamic range. Event camera, such as the Dynamic Vision Sensor (DVS), is a novel, asynchronous, and neuromorphically inspired visual sensor (Gallego et al., 2020 ). Each pixel on the sensor can independently detect the illumination changes in the scene, and once the changes exceed the threshold, it will output visual information in the form of events. Since the brightness changes are usually caused by the movement of objects, event cameras only capture the dynamic information from their visual input and output it in the form of events, ignoring the static information in the scene (Khoei et al., 2019 ). In contrast to traditional cameras, event cameras have the advantages of high time resolution, high dynamic range, low power consumption, and low information redundancy. Therefore, it can well capture the movement of objects in the dark environment or the fast-moving scene without motion blur, which is ideal for object tracking. Several event-based object tracking methods have been proposed in the past few years. which can be roughly divided into two categories. The first category is that each incoming event is determined in time whether it belongs to the target or the background. In (Litzenberger et al., 2006 ), the authors performed event-based object tracking with the clustering algorithm, where each incoming event is assigned to a cluster and then the parameters of the cluster are updated. Ni et al. ( 2015 ) proposed an event-based tracking method by making a continuous and iterative estimation of the geometric transformation. Although these methods are very fast to track, they are easily affected by noise events. A single noise event may cause the tracker to make a wrong inference. Furthermore, they are susceptible to complex background, shape variation and so on. It is difficult to decide whether it belongs to the target based on a single event. Because they cannot utilize the implicit associations between events, which mean the temporal and spatial associations between events. The other category is to collect events over a period of time and track objects according to their features. In Lagorce et al. ( 2014 ), the authors proposed an asynchronous event-based multi-kernel algorithm, which is based on the assumption that events generated by object motion approximately follow a bivariate normal distribution. In Mitrokhin et al. ( 2018 ), the authors presented a tracking-by-detection method, where a novel time-image representation was proposed. This representation gives temporal information to events projected to the same pixel, which facilitates subsequent motion compensation. RMRNet (Chen et al., 2020 ) was formulated to predict 5-DoF object motion regression, which allows end-to-end event-based object tracking. These methods will have a certain delay compared to the first category, but usually they will make the tracking more accurate. In addition to these methods, traditional trackers applied in frame-based video sequences can also be used for event-based tracking. In this way, the event stream is expected to be converted into frames at first. In Henriques et al. ( 2014 ), the authors proposed kernelized correlation filters (KCF), using multi-channel features and mapping the ridge regression of linear space to nonlinear space through the kernel function, and the Fourier space diagonalization is used in the circulant matrices. Siamese network and its variants have achieved excellent performance in recent years. SiamFC (Bertinetto et al., 2016 ) is the pioneering work, which uses a fully convolutional Siamese network for object tracking, and the frame rate exceeds the real-time requirements. Inspired by this work, many algorithms based on Siamese networks were generated (Li et al., 2018 ; Wang et al., 2019 ; Zhang et al., 2020 , 2021 ), all achieving very good performance in object tracking. On the basis of Siamese networks, TrDiMP (Wang et al., 2021 ) combines Transformer and exploits temporal context for object tracking. The transformer encoder facilitates object templates through attention-based feature enhancement, which is beneficial for the generation of high quality tracking models. The transformer decoder propagates tracking cues from previous templates to the current frame, thus simplifying the object search process. However, the event stream should be firstly converted into static images when ANNs are used to process the output of the event cameras, leading to the loss of precise temporal information within events. Since events contain precise spatio-temporal information, they are more suitable to be processed by SNN, which uses spike coding to integrate timing information (Ghosh-Dastidar and Adeli, 2009 ). In this way, events are treated as spikes that can be handled directly by SNN (Jiang et al., 2021 ). SiamSNN (Luo et al., 2021 ), the deep SNN for object tracking, uses the model converted from SiamFC and achieves low precision loss on the benchmarks. But SiamSNN is not directly trained with SNN, it is trained using the conversion algorithm with pretrained ANN. In this work, we propose a novel tracking architecture, referred to as Spiking Convolutional Tracking Network (SCTN), for single object tracking in event-based video sequences. SCTN can not only process the event stream without any additional operations, but also make full use of the temporal information in it. Unlike Nam and Han ( 2016 ), online learning is dispensable in our model, since it is time-consuming during test and it contributes little to tracking performance. The power of this online learning method stems from fine-tuning the network according to the tracking results in the first few testing frames, however, the network will be updated in the wrong direction due to taking the inaccurate tracking results as online training samples. As far as we know, SCTN is the first event based single object tracking network directly trained with SNN. Compared with ANN-based tracking methods, our method can accept the input of event stream without any preprocessing operations and take full advantage of the temporal information in it, and especially show remarkable capabilities of energy-efficient computing. We propose a new loss function that introduces an exponential IoU between ground-truths and training bounding boxes in the voltage domain, while the candidate bounding box corresponding to the largest voltage is regarded as the target bounding box in the test. Besides, we present a novel publicly available event-based tracking dataset, named DVSOT21, under challenge conditions by implementing the bounding boxes generation module to extend the ESIM simulator (Rebecq et al., 2018 ).",
"discussion": "3.5. Discussion In fact, a general event-based object tracking algorithm can highlight the advantages of event cameras in many applications. Here, we discuss two major limitations of SCTN as below. The first limitation is that SCTN cannot process the bounding boxes with spatial resolution less than 10 × 10. Because the number of events contained in the small bounding boxes is insufficient, the C-LIF neurons in the deep layers cannot emit spikes. Thus, investigating a more general model is necessary in the future. The other limitation is that the tracking precision of our method is not as good as state-of-the-art ANN models. This is because SNN cannot deal with numeric regression problems directly, resulting in certain errors in generating target bounding boxes. Hence, an event based tracking model combining ANN and SNN is needed for the further work. Thus, how to capture the tiny objects and improve the tracking performance of SNN is a worthwhile topic in the future. We believe this work could lay the foundation for building universal event-based object tracking on the neuromorphic hardware."
} | 2,618 |
35755439 | PMC9213755 | pmc | 1,282 | {
"abstract": "Cleaning symbioses are key mutualistic interactions where cleaners remove ectoparasites and tissues from client fishes. Such interactions elicit beneficial effects on clients’ ecophysiology, with cascading effects on fish diversity and abundance. Ocean acidification (OA), resulting from increasing CO 2 concentrations, can affect the behavior of cleaner fishes making them less motivated to inspect their clients. This is especially important as gnathiid fish ectoparasites are tolerant to ocean acidification. Here, we investigated how access to cleaning services, performed by the cleaner wrasse Labroides dimidiatus , affect individual client’s (damselfish, Pomacentrus amboinensis ) aerobic metabolism in response to both experimental parasite infection and OA. Access to cleaning services was modulated using a long-term removal experiment where cleaner wrasses were consistently removed from patch reefs around Lizard Island (Australia) for 17 years or left undisturbed. Only damselfish with access to cleaning stations had a negative metabolic response to parasite infection (maximum metabolic rate— Ṁ O 2Max ; and both factorial and absolute aerobic scope). Moreover, after an acclimation period of 10 days to high CO 2 (∼1,000 µatm CO 2 ), the fish showed a decrease in factorial aerobic scope, being the lowest in fish without the access to cleaners. We propose that stronger positive selection for parasite tolerance might be present in reef fishes without the access to cleaners, but this might come at a cost, as readiness to deal with parasites can impact their response to other stressors, such as OA.",
"introduction": "Introduction Parasite infection can adversely impact fish. When a parasite feeds on host tissues and resources, it alters the host physiological states, compromising activities that require energy expenditure ( Sheldon and Verhulst, 1996 ; Lochmiller and Deerenberg, 2000 ). Specifically, ectoparasites can impact the hosts’ energy budgets by affecting the metabolism (inducing higher resting metabolic rate), growth, and reproduction ( Fenton and Rands, 2006 ; Jones and Grutter, 2008 ; Grutter et al., 2011 ). On coral reefs, dedicated cleaner fishes provide cleaning services by eating ectoparasites off the bodies of other “client” fishes ( Grutter, 1999 ; Vaughan et al., 2017 ). The cleaner wrasse, Labroides dimidiatus, is the most ubiquitous species of cleaner in the Indo-Pacific region. This cleaner engages in more than 2,200 interactions with clients, eating more than 1,100 ectoparasites a day ( Grutter, 1996 ). Analysis of cleaners’ stomach contents indicates that these cleaners mostly eat body-fluid feeding gnathiid isopod ectoparasites, removed during their cleaning interactions with clients ( Grutter, 1996 ; Grutter, 1997 ). In addition to their effect on host metabolism, gnathiids can lower the blood volume of their hosts (up to 85% from young damselfish, Pomacentrus amboinensis ) ( Grutter et al., 2011 ), transmit blood-borne parasites ( Hayes et al., 2011a ), and in large numbers, can even kill the adult fish ( Hayes et al., 2011b ). Since cleaners can consume most of the daily emerged gnathiids on a reef per day, access to cleaning services represents a substantial advantage to clients, as cleaners can directly remove the parasites from client surfaces and control gnathiid populations by reducing the parasite infection rates ( Grutter, 2008 ; Grutter et al., 2018 ). Therefore, it is no surprise that the presence of L. dimidiatus is associated with the increased client condition, growth and body size, and influences fish abundance, biodiversity, and juvenile recruitment ( Bshary, 2003 ; Grutter et al., 2003 ; Clague et al., 2011 ; Ros et al., 2011 ; Waldie et al., 2011 ; Sun et al., 2015 ; Wagner et al., 2015 ). Reef fishes can be vulnerable to ocean acidification (OA) caused by a decrease in seawater pH by the absorption of anthropogenic CO 2 emissions. High CO 2 , and thus the associated lower pH, has been documented to impact behavior traits such as activity, homing, anxiety, learning, lateralization, and olfactory and auditory systems (reviewed by Clements and Hunt, 2015 ). Recent studies have also documented low or no effect of OA on fish behavior ( Sundin et al., 2017 ; Raby et al., 2018 ; Clark et al., 2020 ), suggesting the species-specific variability in fish behavioral responses to OA. In addition, cleaning mutualisms are not immune to OA. After prolonged exposure to OA, interactions between the cleaners and clients are reduced and the cleaners lose their motivation to engage in cleaning interactions along with a disruption in interaction quality through possible neurobiological disruption ( Paula et al., 2019a ) and interaction-derived cognitive performance ( Paula et al., 2019b ). Within this context, the client fishes’ ability to reduce ectoparasite loads diminishes due to lower cleaner motivation, along with the resulting potential increase in the infection rates onto fish ( Grutter et al., 2018 ), as reduced cleaning activity also may not control local gnathiid population densities ( Sikkel et al., 2019 ). However, it is also possible that after the long-term lack of access to cleaning services, surviving client fishes might be physiologically adapted to deal with ectoparasite infections. Moreover, a previous study showed that gnathiid survival is not affected by laboratory acclimation to high CO 2 , suggesting that gnathiids can tolerate ocean acidification ( Paula et al., 2020 ). High CO 2 has also been documented to impact the reef fish physiological traits such as escape performance ( Allan et al., 2013 ; Allan et al., 2014 ), metabolism ( Wisenden, 2012 ; Couturier et al., 2013 ; Rummer et al., 2013 ; McMahon et al., 2020 ), and reproduction ( Miller et al., 2013 ; Welch and Munday, 2016 ). A meta-analysis of fish metabolic responses to OA revealed that there is an increase on resting metabolic rate ( Ṁ O 2Rest ), but there seems to be no overall effect of OA on fish absolute aerobic scope ( Ṁ O 2Max - Ṁ O 2Rest ) ( Hannan and Rummer, 2018 ). Metabolic rate can be measured during resting (resting metabolic rate— Ṁ O 2Rest ), giving us information on the basal metabolic costs of an organism to perform life-sustaining functions. During maximum exercise, metabolic rate measures the maximum rate of aerobic metabolism (maximum metabolic rate— Ṁ O 2Max ) an animal can reach, and it is related to the maximum rate of oxygen transport, extraction, and use ( Hannan and Rummer, 2018 ; Hasley et al., 2018 ). Aerobic scope represents the animal’s capacity to increase its aerobic metabolic rate above the maintenance levels (i.e., the difference between Ṁ O 2Max and Ṁ O 2Rest ), being used as proxy for physiological fitness ( Clark et al., 2013 ). Aerobic scope can be presented in absolute terms (i.e., Ṁ O 2Max - Ṁ O 2Rest ) or as factorial aerobic scope (i.e., Ṁ O 2Max / Ṁ O 2Rest ). These measures indicate an absolute or proportional increase, respectively, in the oxygen consumption rates that an animal can reach above the baseline levels ( Clark et al., 2013 ). Measuring and presenting these different metabolic variables in the context of environmental stress research is crucial to understand how a given stressor (such as OA) can add a cost to the basal life-sustaining functions ( Ṁ O 2Rest ), impact oxygen transport ( Ṁ O 2Max ), and affect physiological fitness. So far, only four studies have reported a decreased in aerobic scope (along with lower Ṁ O 2Max ; Methling et al., 2013 ; Tirsgaard et al., 2015 ; or no differences in Ṁ O 2Max and Ṁ O 2Rest ; Hamilton et al., 2017 ) and of those only one used CO 2 levels predicted to occur at the end of the century (along with higher Ṁ O 2Rest ; Munday et al., 2009 ). In contrast, 19 studies have reported no effects on aerobic measures of performance and in three studies performance increased over 12 different fish species (reviewed by Hannan and Rummer, 2018 ). One explanation for these conflicting results is that there is a species-specific response to high CO 2 . Since the cleaners’ motivation to interact with clients drops with OA ( Paula et al., 2019a ), one can conceive a future scenario where client fishes must deal with the physiological impacts of OA together with the stress induced by ectoparasitism, without having access to a way to remove parasites (i.e., cleaning interactions). To understand how access to cleaning interactions can modulate fish physiological responses to parasitic infection and OA, we used the small resident ambon damselfish ( Pomacentrus amboinensis ) collected from a long-term cleaner removal experiment on Lizard Island (Australia) maintained since 2000 ( Waldie et al., 2011 ; Grutter et al., 2019 ). In this long-term experiment, 18 isolated patch reefs have been manipulated so that half had all juvenile and adult L. dimidiatus removed around every 3 months over 17 years, whereas the other reefs were left unmanipulated as controls. This created habitats where fish either have no access to cleaning interactions and a potentially higher exposure to ectoparasites, or access to cleaning with a potentially lower parasite exposure ( Grutter et al., 2018 ). Since this long-term experiment has been running longer than the lifespan of this damselfish [approximately 6.5 years ( McCormick, 2016 )], individuals from “cleaner-absent” reefs had no access to cleaners and possibly had higher ectoparasite exposure for their lifetime. Importantly, since each reef is separated by at least 5 m of sand, these territorial resident damselfish do not cross between the reefs once juveniles have settled on the reef ( Binning et al., 2018 ). We combined this long-term experiment with a 10-days laboratory exposure to high CO 2 and examined whether living on reefs with or without the access to cleaner wrasses ( L. dimidiatus ) influences clients’ ( P. amboinensis ) metabolic responses under OA (the predicted conditions of ocean acidification for 2100, ∼1,000 μatm, RCP 8.5 scenario; Bindoff et al., 2019 ). Moreover, we also performed an experimental parasite infection assay using the cultured gnathiid isopods. This allowed us to test the effects of CO 2 treatment, cleaner presence, and parasite infection on client fish aerobic metabolism, namely resting and maximum metabolic rate, and aerobic scope (both factorial and absolute aerobic scope are presented and analyzed, providing transparency as suggested in Halsey et al., 2018 ).",
"discussion": "Discussion Cleaner wrasses provide an essential ecological service to their clients by controlling their ectoparasite loads through direct removal of ectoparasites from their surfaces and reducing infection rates by lowering gnathiid densities ( Grutter, 1996 ; Grutter, 1999 ; Grutter et al., 2018 ). We hypothesized that clients deprived of access to cleaning services would be physiologically adapted to deal with ectoparasite infections. In line with this hypothesis, we found that the ectoparasite infection results in a decreased maximum metabolic rate [ Ṁ O 2Max , inducing so-called limiting stress, as defined in Heuer and Grosell, 2014 )] with parasitism, only in ambon damselfish from the cleaner-present reefs. As infected damselfish of cleaner-present reefs had lower Ṁ O 2Max than infected damselfish from cleaner-absent reefs ( Figure 3B ), this suggests that damselfish from the cleaner-absent reefs are more adapted to tolerate ectoparasite infection. Parasite infection might be lowering Ṁ O 2Max due to the elevated costs of activation of an immune response. In mice, activation of the immune response led to a decrease in Ṁ O 2Max , and the selection for animals with higher Ṁ O 2Max led to a reduction in the innate immune function ( Downs et al., 2013 ). Even low parasite infections can have huge costs, especially for the small hosts like damselfish at settlement, as gnathiids can kill their hosts, or by consuming 85% of their blood, which can cause significant sublethal effects ( Clague et al., 2011 ; Waldie et al., 2011 ). Therefore, in reefs where cleaners are absent, fish might either develop a higher tolerance to gnathiid infection (e.g. better immune response) or be exposed to strong selective pressure for a tolerance to gnathiids. Indeed, at settlement stage, gnathiid infection can increase damselfish oxygen consumption (resting metabolic rate) and decrease their critical swimming speed, making damselfish more prone to predation ( Grutter et al., 2011 ). Previously, Grutter et al. (2011) , suggested that if gnathiids affect the settlement stage damselfishes, they might ultimately affect the adult population distribution and abundance. The observed tolerance to ectoparasite infection observed in damselfishes from the cleaner-absent reef might indeed reflect this, where, due to the absence of cleaner fishes and high parasitism, only individuals that tolerate parasite infections could successfully settle and reach adulthood. Variation of tolerance to ectoparasitism in wild fish populations has been previously described in dace ( Leuciscus leuciscus ) ( Blanchet et al., 2010 ). This variation could be due to an investment in limiting tissue degradation during ectoparasite feeding, such as investing in higher cell regeneration (i.e. better immune response, Råberg et al., 2009 ), or it could be a selection for individuals that are genetically better at dealing with infection ( Klemme et al., 2020 ). However, the mechanisms that could provide higher parasite tolerance to damselfishes from the cleaner-absent reefs observed here remain unknown and need to be further investigated. In contrast, in reefs without cleaners, selection might favor damselfish that suppress their innate immune function, preventing a limitation on their aerobic capacity ( Ṁ O 2Max ), as described in mice selected for higher Ṁ O 2Max ( Downs et al., 2013 ). \n Ṁ O 2Rest was not altered by parasite infection regardless of its access to cleaning or CO 2 . Infection with small ectoparasites in salmon also had no effects on Ṁ O 2Rest ( Hvas et al., 2017 ). On the other hand, studies using larger parasites, such as Anilocra spp . isopods , showed enhanced resting metabolic rate in the coral reef fish ( Östlund-Nilsson et al., 2005 ; Binning et al., 2013 ). Yet, it is worth mentioning that such an increase in the resting metabolic rate was due to the destabilizing effect of the asymmetrically attached parasite rather than any physiological effect of parasitism. This indicates that parasite infection does not add a so-called loading stress (as defined in Heuer and Grosell 2014 ). Moreover, as found by Couturier et al., 2013 , exposure to high CO 2 did not affect the damselfish resting metabolic rate ( Ṁ O 2Rest ), suggesting that the metabolic costs of living in a high CO 2 environment, namely potentially altered acid-base balance, ion regulation, and cardiorespiratory function also do not add a loading stress for this species ( Figure 3A ). When we analyzed damselfish oxygen transport capacity relative to their resting rate of oxygen uptake (i.e., aerobic scope), we observed that their response to parasite infection was dependent on access to cleaning services. Only fish from the cleaner-present reefs decreased AAS ( Ṁ O 2Max - Ṁ O 2Rest ) with parasite exposure. This suggests that fish who lack access to cleaning services have a higher physiological tolerance to parasite infection. Yet, independent of cleaner presence and only in fish without parasite infection, FAS ( Ṁ O 2Max / Ṁ O 2Rest ) decreased with CO 2 (but not AAS). Here, fish under control conditions without parasite infection had the highest average FAS and CO 2 significantly decreased damselfish FAS. This indicates that the combination of parasite stress and CO 2 does not have an additive effect. However, by comparing FAS with both Ṁ O 2Max and Ṁ O 2Rest , we observed that this decrease in FAS results from different physiological processes for both the stressors. On one hand, the decrease in FAS under high CO 2 could be driven by a slight (nonsignificant) increase in Ṁ O 2Rest , suggesting that a slight increase in resting metabolic costs (i.e., increase in loading stress) under high CO 2 is what is causing a lower damselfish aerobic capacity (FAS). On the other hand, the decrease in FAS (and AAS) due to parasite infection is driven by a decrease in Ṁ O 2Max , possibly due to an increase in the damselfish immune response. The difference between FAS and AAS is related to their different sensitivities for each metabolic parameter measured. While both FAS and AAS are used to represent an animal’s capacity to increase its aerobic metabolic rate above the maintenance levels, AAS is more widely used for when the variability in Ṁ O 2Rest is the major concern, and FAS is more widely used when Ṁ O 2Max is the main concern ( Halsey et al., 2018 ). Following the best practices used in the field, we present both measures. Yet, we must interpret this result with caution as the present exposure to high CO 2 had no evolutionary component and was of a relatively short duration ( Sunday et al., 2014 ). Therefore, we cannot exclude the possibility that these fishes could be able to adapt to this increase in CO 2 . Experiments on species’ resilience to climate change stressors should be analyzed in an evolutionary perspective. This study starts with the premise that cleaning interactions could be altered with OA, since Paula and collaborators found significant changes in cleaning motivation after a 45 day acclimation period to high CO 2 ( Paula et al., 2019a ). Additionally, in a follow-up study, it was observed that: i) cleaner wrasse populations have a standing variation to deal with mild increases of CO 2 (i.e., 750 µatm pCO 2 ) from a behavioral perspective and ii) only at higher acidification levels (980 µatm pCO 2 ) was their cognitive performance severely affected ( Paula et al., 2019b ). However, one should note that to fully address the climate change problem, we should consider a multistressor perspective, e.g., including a temperature increase ( Gunderson et al., 2016 ). Within this context, it is worth noting that both the cleaner and clients are particularly sensitive to extreme heatwave events (e.g., 2016 marine heatwave and associated coral bleaching), as their abundance can diminish drastically after such extreme events ( Triki et al., 2018 ; Triki and Bshary, 2019 ). Gnathiid abundance also decreased at our study site during the same extreme event (2016), and to a following one in 2017. But while it quickly recovered after the first extreme event (possibly due to lower coral cover, see Paula et al., 2021 ), it did not do so in 2017 and remained low postbleaching (in 2018) ( Sikkel et al., 2019 ). This overall decrease in gnathiids may have been caused by an interaction between the short-term negative impacts of thermal stress on gnathiids, as shown in laboratory studies ( Shodipo et al., 2020 ), and a decline in host availability, causing gnathiid abundance to drop ( Sikkel et al., 2019 ; Triki and Bshary, 2019 ). Since heatwave intensity and frequency is increasing ( Oliver et al., 2018 ), client fish (e.g., P. amboinensis ) population attempts of adaptation to either ocean acidification or parasite infection can quickly be erased following such extreme events, if, for example, individuals that develop tolerance to either parasite infection or OA die during such extreme events. Additionally, this possible adaptation to parasite infection (e.g., putative higher investment in higher cell regeneration) may come at a cost, as damselfish from the cleaner-absent reefs are smaller, and thus probably less fecund, since fecundity and size are correlated in these fish ( Birkeland and Dayton 2005 ; Clague et al., 2011 ). In conclusion, we demonstrated, for the first time, that cooperative cleaning interactions, fundamental ecological components of coral reef fish ecosystems, can influence the physiological fitness of a client fish species. Namely, we found that the lack of access to cleaning services leads to more physiological tolerance to parasite infection. However, independent of access to cleaners, high CO 2 lowered fish fitness, although this was not exacerbated by parasite infection. This study adds a layer of complexity to the climate change-related studies, namely the importance of species interactions, that should be included to fully understand the biological impacts of climate change in the ocean of tomorrow."
} | 5,153 |
38024730 | PMC10653055 | pmc | 1,283 | {
"abstract": "Most chemicals are manufactured by traditional chemical\nprocesses\nbut at the expense of toxic catalyst use, high energy consumption,\nand waste generation. Biotransformation is a green, sustainable, and\ncost-effective process. As cyanobacteria can use light as the energy\nsource to power the synthesis of NADPH and ATP, using cyanobacteria\nas the chassis organisms to design and develop light-driven biotransformation\nplatforms for chemical synthesis has been gaining attention, since\nit can provide a theoretical and practical basis for the sustainable\nand green production of chemicals. Meanwhile, metabolic engineering\nand genome editing techniques have tremendous prospects for further\nengineering and optimizing chassis cells to achieve efficient light-driven\nsystems for synthesizing various chemicals. Here, we display the potential\nof cyanobacteria as a promising light-driven biotransformation platform\nfor the efficient synthesis of green chemicals and current achievements\nof light-driven biotransformation processes in wild-type or genetically\nmodified cyanobacteria. Meanwhile, future perspectives of one-pot\nenzymatic cascade biotransformation from biobased materials in cyanobacteria\nhave been proposed, which could provide additional research insights\nfor green biotransformation and accelerate the advancement of biomanufacturing\nindustries.",
"conclusion": "5 Conclusions and Future Perspective Traditional chemical synthesis has the disadvantages of hazardous\ncatalysis, high energy consumption, and waste-generating chemical\nprocesses. In comparison, biotransformation is a green, sustainable,\nand cost-effective process. Cyanobacteria, important members of the\nphotoautotrophic organism class, have attracted extensive attention\ndue to their tremendous potential for the sustainable production of\ngreen chemicals. As cyanobacteria use light as the energy source to\npower the synthesis of NADPH and ATP, using cyanobacteria as the chassis\norganisms to design and develop light-driven biotransformation platforms\nfor chemical synthesis provides a theoretical and practical basis\nfor the sustainable and green biotechnology production of chemicals. Notwithstanding several proof-of-concept studies demonstrating\nthe applicability of light-driven biotransformation in cyanobacteria,\nthe applicability of cyanobacteria-mediated biotransformation has\nreceived relatively little attention due to the poor biotransformation\nperformance, which is not good enough to meet industrial needs. To\nexploit the potential of cyanobacterial biotransformation, an assessment\nof cyanobacteria as hosts for light-driven biotransformation is still\nmissing. As is known to all, the titer of chemicals by the biotransformation\nmethod is usually low in wild-type cyanobacterial strains, and biotransformations\nwith recombinant cyanobacteria strains contribute significantly to\nthe industrial scale. Moreover, engineered cyanobacteria have greater\npotential in the formation of new products by artificial cascades\nof enzymatic reactions, 102 , 103 and enzymes involved\nin related metabolic pathways should be manipulated to achieve highly\nselective activity, 104 which could also\navoid the possible side reactions. 105 However,\nthere is limited literature on the exploration of engineered cyanobacteria\nfor one-pot enzymatic cascade biotransformation by artificial multienzyme\ncomplexes in the production of green chemicals. Consequently, synthetic\nbiology and genome editing techniques should be used to further engineer\nand optimize cells of cyanobacteria to achieve efficient light-driven\nsystems for synthesizing various chemicals, as these could provide\nadditional research insights for green biotransformation and accelerate\nthe advancement of biomanufacturing industries. Currently, synthesis\nof the green chemicals in cyanobacteria is\nmainly focused on introducing heterologous synthetic pathways to drive\nthe utilization of intermediate metabolites; however, genetic engineering\nof cyanobacteria faces numerous challenges. The first challenge is\nthat it is difficult for cyanobacteria to reach the theoretical yield\ndue to the deficiency of genetic manipulation tools, and novel promoters\nor ribosome binding sites for precise gene expression control should\nbe further investigated. The next challenge is that although the genome\nediting of cyanobacteria is simple, the cycle is relatively slow.\nThe traditional homologous recombination-mediated approach should\nintegrate heterologous expression modules into chromosomes or endogenous\nplasmids but has the challenge of being time-consuming, and the use\nof a broad-host-range vector faces the problem of compatibility. 106 Further, developing stable shuttle expression\nvectors in cyanobacteria will accelerate the construction of recombinant\ncyanobacteria. 107 Moreover, the industrial\napplication of cyanobacteria-mediated\nlight-driven biotransformation is limited due to scale-up difficulties,\nand the illumination efficiency and light availability were the main\nlimiting factors. 108 Consequently, novel\nphotobioreactors should be developed to allow a short light path between\nthe light source and the reaction medium. Taken together, the development\nof stable shuttle expression vectors and novel photobioreactors would\nprovide us with better research capabilities in cyanobacteria-mediated\nlight-driven biotransformation.",
"introduction": "1 Introduction Most chemicals are currently\nmanufactured using petroleum-derived\nfeedstocks through traditional chemical processes, and chemical catalysts\nhave been used to achieve the conversion of substrate molecules and\nproduct molecules under harsh conditions such as high temperature,\nhigh pressure, strong acids, and strong bases. Although chemical products\nproduced from fossil materials have greatly improved our living standards\nover the last two centuries, a series of problems have arisen and\ncreated increasing pressure, including resource waste, greenhouse\ngas emissions, and environmental pollution, posing a challenge and\nthreat to human health. 1 − 3 Along with the rising global energy demands and pressing\nenvironmental issues, efforts are intensifying to bridge the gap between\nfossil carbon consumption and renewable supply. 4 An increasing number of scientific researchers are committed\nto developing sustainable production processes of the same chemical\nproducts with renewable feedstocks as the raw materials to render\nthe production of chemical products more cost-effective, reduce energy\nconsumption, and limit the emission of harmful gases. 5 Consequently, more attention has converged toward such\ngreen types of chemical synthesis in recent years, which has stimulated\nextensive research on several biomasses to support renewable chemical\nsynthesis. 5 − 13 Enzymes have been widely used as biocatalysts in organic synthesis\ndue to their substrate specificity and high catalytic activity, especially\nfor the introduction of several enantiomeric or regioselective functional\ngroups. Enzymatic catalysis has the advantages of convenient reaction\nprotocols, mild reaction conditions, excellent stereoselectivity,\nbroad substrate scope, and short reaction time and may help avoid\nvarious problems in chemical synthesis, including isomerization or\nracemization. Photobiocatalysis, a light-mediated enzymatic catalysis,\nhas achieved significant progress due to the capacity to use light\nfor organic synthesis, which has provided versatile protocols and\napproaches to synthesis various natural or non-natural products. 14 Since then, different applicable tools in photobiocatalysis,\nsuch as photoenzymes, enzyme–photocatalyst-coupled systems\n(EPCSs), and light-driven biotransformation, have been well documented,\nand the current status of photoenzymes and EPCS have been reported\nin previous reviews. 15 − 18 Light-driven biotransformation conforms to the principle of “green\nchemistry” and has been also accessible in a mature technology.\nWith this emphasis, this paper focuses on the advances and challenges\nof cyanobacteria-mediated light-driven biotransformation toward the\nefficient synthesis of green chemicals. In particular, we display\nthe potential of cyanobacteria as a promising light-driven biotransformation\nplatform for the efficient synthesis of green chemicals and current\nachievements of light-driven biotransformation processes in wild-type\ncyanobacteria or recombinant cyanobacteria. Meanwhile, future perspectives\nof one-pot enzymatic cascade biotransformation from biobased materials\nin cyanobacteria have been proposed, which could provide additional\nresearch insights for green biotransformation and accelerate the advancement\nof biomanufacturing industries."
} | 2,167 |
39370460 | PMC11456601 | pmc | 1,284 | {
"abstract": "Microbial fuel cells (MFCs) use the metabolic actions of microorganisms in an anode chamber to convert the chemical energy from wastewater into electrical energy. To improve the MFC power generation performance and chemical oxygen demand (COD) removal efficiency, Stenotrophomonas acidaminiphila was added to the anode chamber of a dual-compartment MFC. In this process, Stenotrophomonas acidaminiphila promotes the degradation of macromolecules such as bis(2-ethylhexyl) phthalate in food waste oil. Additionally, the generated electrical energy reduced Cu 2+ in the copper-containing wastewater in the cathode chamber to Cu monomers. The maximum power density of the MFC was 49.5 ± 3.5 mW/m 2 , the maximum removal efficiencies of COD and Cu 2+ were 63.5 ± 5.8% and 96.5 ± 1.0%, respectively, and Cu 2+ was reduced to brick-red Cu monomers. This study provides insights into the simultaneous implementation of food waste oil treatment and metal resource recovery. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-024-74856-w.",
"conclusion": "Conclusion In this study, Stenotrophomonas acidaminiphila can transfer electrons either by direct contact with an electrode or by secretion through an electronic medium. Besides, the degradation of substances from kitchen waste into small molecules promotes the growth of itself and electroactive bacteria. This, in turn, enhanced MFC power generation. Furthermore, the oil enriched the nutrients in the anode chamber substrate, while the anode microbial community degraded the oil. The generated substrate strengthened the biofilm on the electrode, promoted electron transfer, and improved the removal efficiency. Overall, this process reduced the cost of wastewater treatment.",
"introduction": "Introduction Microbial fuel cells (MFCs) can generate electrons by degrading organic matter (e.g., oils, starch, proteins, cellulose, monocyclic aromatic hydrocarbons, unsaturated fatty acids, and trans-fatty acids), which can reduce certain strongly oxidising substances (e.g., O 2 and Cu 2+ ) 1 . In terms of urban economic growth, the global catering industry is developing rapidly and becoming increasingly large in scale, resulting in increased daily food waste production. It has been reported that the mass fraction of oil (wet basis) in food waste is in the 2.5–5% range, making it difficult to degrade and treat 2 . They are prone to rancidity, produce a variety of disease-causing components, emit a foul odour, and jeopardise human health if exposed for a long time. If not processed and discharged directly into the water, it produces a film on the surface of the water body, leading to the death of aquatic plants and animals 3 . The oil in food waste can be mechanically separated and utilised. It exists in various forms (e.g., floatable oil, emulsified oil, dissolvable oil, and solid-phase internal oil), of which only floatable oil is easier to separate. However, the recovery rate fluctuates considerably (27–62%) 4 . Biological treatment uses the metabolism of organisms to transform and stabilise the pollutants in food waste oil to make them harmless and resourceful. It has the advantages of low cost, no secondary pollution, and the recovery of energy converted into environmentally beneficial products, which has a vast potential for application 5 , 6 . Microorganisms such as Pseudomonas aeruginosa 7 , Bacillus sp 8 . and Serratia marcescens 9 , among others, are commonly used to treat oils. Zhang et al. utilised a salt-tolerant bacterial strain, Serratia marcescens subsp , to convert various animal fats and vegetable oils from food waste compost; a removal efficiency reaching 87.37% of the mixed oils at 30℃ for 24 h was achieved 10 . However, it was only applicable to be performed at high NaCl concentrations for a short period. Single-chamber MFCs 11 or dual-compartment MFCs 12 have been used to treat kitchen waste wastewater with a chemical oxygen demand (COD) removal efficiency of 40–87% and bioelectricity generation 13 of 10–560 mW/m 2 . This suggests that MFCs can convert bioenergy from food waste into electricity. However, the activated sludge used in conventional MFCs is ineffective, and there is much room for further development. Therefore, organic matter (e.g., food waste oil) can be used as fuel in the anode chamber of the MFC, and the generated electrons reduce oxidising substances (e.g., copper-containing wastewater and chromium-containing wastewater). With the development of industrial production and social progress, heavy-metal pollution is becoming increasingly severe and has become a priority of environmental protection 14 . Cu 2+ is the most toxic and abundant element found in the environment. Copper-containing wastewater is difficult to biodegrade and requires physicochemical treatment, and direct discharge without treatment can seriously harm plants, animals, and humans. Traditional physicochemical techniques exhibit good removal efficiency; however, secondary contamination and high costs limit their development prospects 15 . Researchers have recently used MFCs enriched with sulfate-reducing bacteria to treat copper-containing wastewater and attained a Cu 2+ of 20 mg/L device and Cu 2+ removal efficiency (98%), which has the advantages of low cost and harmlessness but it is not suitable for treating high-concentration copper-containing wastewater 16 . With increasing concentration of copper-containing wastewater in the cathode chamber, the amount of Cu 2+ passing through the proton-exchange membrane (PEM) to inhibit the activity of microorganisms in the anode chamber and reduce the generation of bioelectricity increases, resulting in a decreased Cu 2+ removal efficiency 17 . This study aimed to construct a bacteria-enhanced dual-compartment MFC for treating kitchen waste, in which the electrical energy generated from waste oil reduces Cu 2+ in copper-containing wastewater to realise Cu recovery. The MFC was used to treat both kitchen waste oil and copper-containing wastewater simultaneously. The effects of Stenotrophomonas acidaminiphila , oil content, and Cu 2+ concentration on the power generation performance, oil degradation, and Cu 2+ removal of MFC were investigated. The results of this study will provide a research basis for the oil degradation characteristics of Stenotrophomonas acidaminiphila and new insights into the development of low-cost and sustainable wastewater removal technologies.",
"discussion": "Discussion Influence of microbial communities on power generation All the nine MFCs could produce electricity. High-throughput sequencing was used to analyse the microbial communities in the anode chamber and to detect the presence of electroactive bacteria in the activated sludge to further demonstrate the effect of the anode microbial communities on MFC power generation. Exponential characterisation analysis and principal co-ordinates analysis (PCoA) are shown in Supplementary Table S3–S4 and Fig. S6. Statistical analyses were performed to examine microbial community composition at the gate level. As shown in Supplementary Fig. S2–S3 and Fig. 3 j and k, respectively. As shown in Fig. 3 j, categorised by the fungal phylum, Ascomycota was more abundant in MFC-4 and MFC-8, Basidiomycota was more abundant only in MFC-7, Rozellomycota was more abundant in MFC-1, MFC-3, and MFC-9, and Mortierellomycota is only was more abundant in MFC-2, Mucoromycota was more abundant in MFC-6, Chytridiomycota was more abundant in MFC-1 and MFC-9, and Blastocladiomycota was more abundant only in MFC-3. MFC-1, MFC-3, and MFC-6 contained the most abundant fungal species. It can be seen from Supplementary Fig. S6A that the species in MFC-1, MFC-3, MFC-5, MFC-6, and MFC-9 are similar, and the percentage difference is not significant; the species in MFC-4 and MFC-8 are similar, and the percentage difference is not significant, among which the species in MFC-2 and MFC-7 are different, and the percentage is not the same as that of the other sample sites; the difference is also significant between these two groups, which fully verifies the results of the PCoA. As shown in Fig. 3 k, categorised by bacterial phylum, Proteobacteria were the most abundant in MFC-3, Firmicutes were more abundant only in MFC-7, Bacteroidetes were more abundant only in MFC-6, Synergistetes were more abundant only in MFC-4, Chloroflexi were more abundant only in MFC-2, MFC-7, and MFC-8, and Planctomycetes were more abundant only in MFC-7. Among these, only MFC-7 was the most abundant. It can be seen from Supplementary Fig. S6B that the species in MFC-1 and MFC-6 are similar and have a slight difference in percentage, and the species in MFC-2, MFC-3, MFC-4, MFC-7, MFC-8, and MFC-9 are similar and have a slight difference in percentage, whereas MFC-5 and the other sample sites have different species and have different percentages, which fully verifies the results of the principal coordinate analysis of the PCoA. In summary, Proteobacteria , Firmicutes , Bacteroidetes , Synergistetes , Chloroflexi , Planctomycetes , Ascomycota , Basidiomycota , Rozellomycota , Mortierellomycota , Mucoromycota , Chytridiomycota , and Blastocladiomycota , among others, were the dominant phyla. Proteobacteria and Firmicutes have been identified as the main power-generating strains in many MFC-related studies, with both efficiently transferring electrons from electroactive bacteria to electrodes via cytochrome-C to enhance power generation 45 . Proteobacteria is the most abundant gate in power generation. It oxidises acetate, nitrite, and other organic matter to release electrons 46 , plays a role in the transfer of electrons, and supports its own growth. At the end of the experiment, a high-throughput genome sequence database of microorganisms in the anode chamber of the MFC was produced, from which the community structure at the genus level was obtained, as in Fig. 3 a and i. All eight devices except MFC-2 contained Stenotrophomonas acidaminiphila , a strain belonging to Proteobacteria , and it has been shown that Stenotrophomonas acidaminiphila is an electroactive bacterium owing to its direct contact with electrodes or electron transfer through secreted electron mediators 39 , 40 . Thus, Stenotrophomonas acidaminiphila directly or indirectly promoted lipid degradation and MFC power generation. As shown by the voltage (Supplementary Fig. S1 ) and power density (Fig. 2 a), the power generation of MFC-2 was lower than that of the other eight devices, confirming that Stenotrophomonas acidaminiphila can produce electricity. The cell walls of gram-negative Firmicutes are much thicker than those of gram-positive bacteria, a feature that can affect the transfer of electrons, such that such bacteria are less capable of producing electricity. Bacteroidetes are common soil microorganisms that promote the metabolism of microorganisms; thus, they promote the growth of electroactive bacteria, which in turn can improve their ability of electroactive bacteria to produce electricity. Wei et al 47 . reported that Chloroflexi can participate in power generation. The dominant species in the anode liquid were not all electroactive bacteria. There were also fermenting bacteria and fungal communities that degrade organic matter in sewage and provide a suitable substrate for electroactive bacteria. For example, Mortierellomycota utilises its synthesised and secreted acids to dissolve organic matter, such as mineral phosphorus, in anode sludge and enhances the nutrients in the anode substrate 48 . Effect of oil content on the performance of microbial fuel cells Increased oil content promotes MFC power generation. Studies have shown that Stenotrophomonas acidaminiphila enhanced the solubility of polycyclic aromatic hydrocarbons and removed contaminated waste lubricating oils from sand 49 , indicating that Stenotrophomonas acidaminiphila can degrade oil. With increasing oil content, nutrients in the anode chamber substrate become enriched. The anode microbial community degrades the oil and other organic matter while strengthening the biofilm on the electrode (Supplementary Fig. S7), and the bacteria on the biofilm facilitate direct interspecies electron transfer, which is conducive to improving the power generation performance of the MFC 39 – 41 , 50 . Effect of cu2+ concentration on the performance of microbial fuel cells Increased Cu 2+ content promotes MFC power generation. As the Cu 2+ concentration increased, the ionic strength of the cathodic liquid, electrical conductivity, electron output rate, and output voltage increased. Liu et al 17 . found that a high Cu 2+ concentration decreased the concentration of Cu 2+ by adsorption on the electrode, and microorganisms in the anode chamber absorbed small amounts of Cu 2+ as a nutrient and continued producing protons by degrading organic matter. This prevented further passage of Cu 2+ to the anode chamber, thus reducing the inhibitory effect of Cu 2+ on microbial degradation, improving the removal efficiency of COD, and increasing the efficiency of power generation in the MFC. Prospects for microbial fuel cells To date, no relevant studies have used MFCs to treat wastewater containing food waste oil and copper. Miran et al 16 . utilised an anode enriched with Sulphate Reducing Bacteria to investigate the effect of Cu 2+ on the performance of MFC; the results showed Cu 2+ removal (> 98%) for a device with a Cu 2+ concentration of 20 mg/L. In contrast, the present study was conducted to degrade oil and copper-containing wastewater using an MFC enhanced by Stenotrophomonas acidaminiphila and to investigate its effect on the performance of MFCs. Bioelectricity generated by the degradation of oils by Stenotrophomonas acidaminiphila was used to reduce Cu 2+ to monomeric Cu in the cathode chamber. The Cu 2+ removal efficiency in this experiment was in the range of 86.3–96.5%, which differs slightly from that in the above experiment, probably because of the significant difference in the concentration of Cu 2+ . A lower Cu 2+ concentration may have the best effect; however, it is unsuitable for high-concentration industrial applications. Ke et al 8 . utilised the consortium flora of Pseudomonas putida and Bacillus sp. for starch solubilisation in a lipase-catalysed hydrolysis process, resulting in a degradation rate of 59.0% within 48 h when the initial food waste oil concentration was 8.0%. The COD removal efficiency of MFC-9 in this experiment was 63.5 ± 5.8%, indicating that it more effectively degrades oils. It also utilised the bioelectricity generated from the degradation of food waste to treat copper-containing wastewater. Both the degradation of oil and the removal of Cu 2+ were closely related to the power generation performance of the device. Increases in the Cu 2+ concentration indirectly enhanced the power generation capacity of electroactive bacteria in the anode chamber, strengthened its growth and metabolic level and that of the microbial community, and promoted the degradation efficiency of Stenotrophomonas acidaminiphila in oil 40 , 42 , 44 . The improved performance of MFC power generation promotes COD and Cu 2+ removal, thereby facilitating copper recovery. MFCs utilise various organic wastes to recycle resources and reduce environmental pollution. A reduction reaction using electrons transferred from the anode is used to treat strongly oxidising wastewater and recover valuable substances. In this study, a bacteria-enhanced dual-compartment MFC was used to purify wastewater and generate electricity. However, practical applications of MFCs still face challenges. Therefore, further optimisation of the MFC performance and cost reduction are important research directions in the field of biopower generation."
} | 3,979 |
24065962 | PMC3777014 | pmc | 1,286 | {
"abstract": "Lignocellulosic biofuels are promising as sustainable alternative fuels, but lignin inhibits access of enzymes to cellulose, and by-products of lignin degradation can be toxic to cells. The fast growth, high efficiency and specificity of enzymes employed in the anaerobic litter deconstruction carried out by tropical soil bacteria make these organisms useful templates for improving biofuel production. The facultative anaerobe Enterobacter lignolyticus SCF1 was initially cultivated from Cloud Forest soils in the Luquillo Experimental Forest in Puerto Rico, based on anaerobic growth on lignin as sole carbon source. The source of the isolate was tropical forest soils that decompose litter rapidly with low and fluctuating redox potentials, where bacteria using oxygen-independent enzymes likely play an important role in decomposition. We have used transcriptomics and proteomics to examine the observed increased growth of SCF1 grown on media amended with lignin compared to unamended growth. Proteomics suggested accelerated xylose uptake and metabolism under lignin-amended growth, with up-regulation of proteins involved in lignin degradation via the 4-hydroxyphenylacetate degradation pathway, catalase/peroxidase enzymes, and the glutathione biosynthesis and glutathione S-transferase (GST) proteins. We also observed increased production of NADH-quinone oxidoreductase, other electron transport chain proteins, and ATP synthase and ATP-binding cassette (ABC) transporters. This suggested the use of lignin as terminal electron acceptor. We detected significant lignin degradation over time by absorbance, and also used metabolomics to demonstrate moderately significant decreased xylose concentrations as well as increased metabolic products acetate and formate in stationary phase in lignin-amended compared to unamended growth conditions. Our data show the advantages of a multi-omics approach toward providing insights as to how lignin may be used in nature by microorganisms coping with poor carbon availability.",
"conclusion": "Conclusions Previous work has shown that E. lignolyticus SCF1 possesses a suite of membrane pumps that confer tolerance to high concentrations of both salt and ionic liquids, which are used as an alternative pre-treatment for lignin removal in plant feedstock material (Khudyakov et al., 2012 ). We also know that SCF1 is derived from a wet tropical forest soil environment that is characterized by low and fluctuating redox conditions as well as very fast rates of litter decomposition (Parton et al., 2007 ; Silver et al., in press ). This work shows that E. lignolyticus SCF1 is able to use lignin in both assimilatory and dissimilatory pathways, where assimilatory pathways are glycolysis and the pentose phosphate pathway, and dissimilatory reduction seem to occur by oxidative phosphorylation via the electron transport chain. Dissimilatory reduction of lignin-model compounds and aromatics has been well established (Harwood and Parales, 1996 ), as has the ability for a range of bacteria to shuttle electrons via quinones and soluble humic substances (Newman and Kolter, 2000 ). It is also remarkable that SCF1 is able to grow so well in the presence of lignin, which contains many soluble products that have proven to be inhibitory to growth of many other organisms including popular model organisms for metabolic engineering such as E. coli . While there are many studies that demonstrate degradation of lignin for assimilatory pathways (Bugg et al., 2011a ), this is the first to demonstrate both assimilatory and dissimilatory reduction of the complex heteropolymer plant lignin by a soil bacterium. Conflict of interest statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.",
"introduction": "Introduction Lignocellulose is the most abundant biopolymer on earth, and a recent joint analysis by the DOE and USDA shows that there is sufficient national supply to make lignocellulosic biofuels technically feasible (Perlack, 2005 ). Development of renewable, sustainable biofuels from plant feedstock material has emerged as a key goal of the US Department of Energy. The use of lignocellulose as a renewable energy source has many advantages, above all that lignocellulose production is domestic and independent of food agriculture (Lee et al., 2008 ). The deconstruction of plant biomass is a key first step in the conversion of plant sugars to biofuels, though this step has posed a great challenge to making biofuels economically viable. The major hurdles involve lignin occlusion of cellulose, as well as lignin derivatives that inhibit lignocellulose deconstruction and fuel synthesis (Lee et al., 2008 ). Lignin comprises up to 25% of plant biomass (Wei et al., 2009 ), and as such is an abundant and potentially valuable waste stream that is currently burned to produce energy as heat (Jaeger and Eggert, 2002 ). Our primary goal is to improve biofuel production through better saccharification of pretreated feedstock (switchgrass) from pathways and enzymes of anaerobic bacterial lignin degraders. By characterizing anaerobic lignin degradation in the bacterium Enterobacter lignolyticus SCF1, we may be able to incorporate these enzymes and pathways into metabolic engineering of biofuel- and biodiesel-producing bacteria. These discoveries also promise to provide insight to the natural processes of bacterial lignin decomposition. Tropical soils are responsible for near complete decomposition of leaf plant litter in as little as 18 months (Parton et al., 2007 ). There is an apparent contradiction of tropical forest soils, where rapid and efficient lignocellulose mineralization proceeds rapidly under low or fluctuating redox conditions. Rapid decomposition may be fueled by fluctuating redox conditions that regenerate oxidized iron; up to 10% of tropical bacteria are capable of iron reduction (Dubinsky et al., 2010 ). Resident microbes are adapted to the low and fluctuating redox potential in the soil (Silver et al., 1999 , in press ; Pett-Ridge et al., 2006 ), in contrast to temperate systems where oxidative enzyme activities are rate-limiting for decomposition (Paul and Clark, 1996 ; Freeman et al., 2001 ; Fierer et al., 2009 ). Thus wet tropical soils are attractive targets for discovery of bacterial lignin-degraders, which would be amenable to industrial engineering and efficient for removing lignin inhibitors to cellulose availability for biofuels. Though fungi are considered primary decomposers, capabilities for genetic manipulation fungi are not as well-developed as for other biological systems, and current fungal enzymes of commercial interest have been too non-specific and too expensive to produce industrially. Fungi have well-characterized mechanisms for breaking open lignin phenol rings via oxygen free-radicals generated by dioxygenase enzymes (Sánchez, 2009 ; Fujii et al., 2013 ). Though fungi are thought to dominate decomposition in terrestrial ecosystems, few fungi are known to be able to tolerate the frequent anoxic conditions characteristic of tropical forest soils (Boer et al., 2005 ; Baldrian and Valášková, 2008 ). Based on previous observations of considerable anaerobic decomposition in the lab and field (Pett-Ridge and Firestone, 2005 ; DeAngelis et al., 2010a , b , 2012 ), we suspect that tropical soil bacteria play a larger role in decomposition under anaerobic and fluctuating redox conditions. Few bacteria are known to degrade lignin, and even fewer anaerobically. Known potential lignin-degrading bacteria are in the groups α-proteobacteria, γ-proteobacteria, Firmicutes and Actinomycetes (Bugg et al., 2011b ) and most bacteria employ extracellular peroxidases, which require oxygen availability (Bugg et al., 2011a ). For example, the novel isolates in the phylum Firmicutes Bacillus pumilus strain C6 and Bacillus atrophaeus strain B7 were identified to have very high laccase activity as well as the ability to aerobically degrade Kraft lignin and the lignin model dimer guaiacylglycerol-b-guaiacyl ether (Huang et al., 2013 ). Many bacterial processes have been successfully engineered into consolidated bioprocessing for biofuels, such as cellulose conversion to sugars (saccharification) and ionic liquid pretreatment tolerance (Blanch et al., 2008 ; Lee et al., 2008 ; Singh et al., 2009 ), with an emerging role for bacterial lignin degradation (Bugg et al., 2011b ). Among anaerobic bacterial lignin or phenol degraders, Sphingomonas paucimobilis SYK-6 produces a β-aryl etherase (Masai et al., 2007 ), and Rhodococcus sp. RHA1 contains a β-ketoadipate pathway (McLeod et al., 2006 ); Kocuria and Staphylococcus also likely degrade phenol (DeRito et al., 2005 ). Another Enterobacter species, E. solis strain LF7, was isolated from tropical forest soils in Peru based on its ability to degrade alkali lignin as a sole C source under aerobic growth conditions (Manter et al., 2011 ). E. solis strain LF7 and our strain E. lignolyticus SCF1 share 97% sequence identify for their 16S ribosomal RNA genes, which is a relatively low homology for the Enterobacteraceae. E. lignolyticus SCF1 is a γ-proteobacteria, and a novel isolate in the class Enterobacterales which has been previously shown to be capable of anaerobic lignin-degradation (DeAngelis et al., 2011 ), though the mechanisms are unknown. The facultative anaerobe E. lignolyticus (formerly cloaceae) SCF1 was originally isolated on lignin as sole C source from soil in the El Yunque Experimental Forest, Puerto Rico, USA (DeAngelis et al., 2011 ). The genome sequence of SCF1 suggested that two multi-copper oxidases (putative laccases) and a putative peroxidase may be involved in lignin degradation, with one or more glutathione S-transferase (GST) proteins involved in cleaving β-aryl ether linkages. This is the case with LigE/LigF in S. paucimobilis , where lignin is degraded by way of the protocatechuate pathway, catalyzed in part by the protocatechuate 4,5-dioxygenase enzyme LigB and the extradiol dioxygenase LigZ (Masai et al., 2007 ; Peng et al., 2008 ). However, SCF1 does not posses the core protocatechuate and 3-O-methylgallate degradation pathways found in S. paucimobilis . Instead, lignin catabolism seemed likely to proceed via homoprotocatechuate through the 4-hydroxyphenylacetate degradation pathway, a gene cluster that is conserved among the Enterobacter and Klebsiella (Bugg et al., 2011a ). In this study, we use proteomics, transcriptomics, metabolomics analysis and measures of enzyme activities to characterize the mechanism by which E. lignolyticus SCF1 is able to degrade lignin during anaerobic growth conditions.",
"discussion": "Results and discussion SCF1 is capable of degrading 56% of the lignin under anaerobic conditions within 48 h, with increased cell abundance in lignin-amended compared to unamended growth (Figure 1 ). Lignin degradation is measured by absorbance at 310 nm, where decreases in absorbance indicate decreasing concentrations of soluble phenolic and polyphenolic compounds (Ahmad et al., 2010 ). During growth, we also observed color change of the cultures, and production of bubbles that likely signify CO 2 evolution during the metabolism of the xylose and lignin in the media. We performed experiments to observe lignin degradation during growth on xylose minimal media amended with lignin, because we were unable to detect growth of SCF1 on lignin as sole C source under anaerobic conditions. While this strain was originally isolated growing anaerobically under conditions of minimal agar media with lignin as the sole C source (DeAngelis et al., 2011 ), the colonies took about 12 weeks to form, and we have been unable to recreate these growth conditions in liquid media for cell biomass sufficient to perform detailed genetic and proteomic analysis. Because of this, genetic, metabolic and proteomic analysis of lignin degradation is performed by comparing lignin-amended xylose minimal media to unamended xylose minimal media, and lignin degradation mechanisms and pathways are inferred by differential gene expression and protein production. Figure 1 Anaerobic growth and lignin degradation by E. lignolyticus SCF1. (A) This replicated growth curve experiment ( n = 3) shows increased cell abundance with lignin, and decreased lignin over time. The arrow denotes the time that samples were collected for transcriptomics, proteomics and metabolomics studies. After 48 h of growth, color change in the lignin media and bubbles indicating CO 2 gas formation (B and C) inoculated with SCF1 (bottles lig1–3) is evident when compared to the darker, uninoculated control [“(−) ctl”]. Proteomics analysis produced 7883 unique peptides and 871 unique proteins. Our previous study showed that the SCF1 genome encodes 4449 protein encoding genes (DeAngelis et al., 2011 ). There were 229 proteins that were significantly differentially abundant between the lignin-amended and unamended growth conditions. Of these, 127 proteins were at least 2-fold up-regulated in the presence of lignin. Pathways with the most hits included proteins associated with metabolism, biosynthesis of secondary metabolites, and ABC transporters (Supplemental Table 2 ). We further examined proteins and pathways likely associated with xylose degradation, lignin degradation, and dissimilatory lignin reduction to explore the ways in which SCF1 might be gaining a growth advantage in lignin-amended compared to unamended cultivation conditions. Transcripts were sequenced as 50 bp tags on ABI SOLiD4, and aligned to the SCF1 genome. Data (number of transcripts) was normalized to reads per kilobase of gene per million reads. Of the 4716 genes detected by transcriptomics, 273 were differentially regulated, and 147 were up-regulated in the lignin-amended compared to the xylose only control (Table 1 ). These included mostly genes associated with metabolism, biosynthesis and transporters (Supplemental Table 3 ). Table 1 Proteomic and transcriptomic data and differential regulation in lignin-amended compared to unamended samples . Unique Significant ( P < 0.05) Up-regulated Down-regulated Peptides 7883 855 626 229 Proteins 869 285 207 79 Transcripts 4716 273 147 126 We chose to analyze both transcripts and proteins after 48 h of anaerobic growth of SCF1 in lignin-amended and unamended xylose minimal media. Sampling during stationary phase was chosen because at this time point, cells had demonstrated lignin degradation, and no further cell growth or significant lignin degradation was observed after around this time. However, we recognize that the choice of stationary phase likely precluded the observation of many transcripts that may have been illuminating for lignin degradation. Indeed, at the gene level, there was little observed overlap between the sequenced transcripts and the observed expressed proteins: of the 871 unique proteins detected, only 11 lignin up-regulated proteins and 4 lignin down-regulated proteins were also observed in the transcripts (Table 2 ). These constitutively expressed gene products detected by both methods were likely important to growth and survival during the transition into stationary phase, because they had been expressed for lignin degradation and continued to be expressed during transition into stationary phase. For the lignin-amended cultures, the up-regulated and highly transcribed genes included mostly transporters and proteins in the TCA cycle. A carbon starvation protein CstA (Entcl_3779) encoding a predicted membrane protein, also had significantly more transcript and protein in lignin-amended conditions (Schultz and Matin, 1991 ). The CstA protein is located just upstream of the 4-hydroxyphenylacetate degradation pathway (Entcl_3796-3806), which is also the case for E. coli (Prieto et al., 1996 ). Carbon starvation genes have long been associated with metabolism of aromatic compounds (Blom et al., 1992 ), and are thought to be a result of membrane toxicity of hydrocarbons that can integrate into cell membranes and cause a leak of the proton motive force (Sikkema et al., 1995 ). The CstA protein is thought to be involved in transport of nucleic acids, where expression is a hallmark of the cell trying to avoid entry into stationary phase (Schultz and Matin, 1991 ; Kraxenberger et al., 2012 ). Table 2 Genes significantly differentially detected both by transcriptomics and proteomics, where positive fold change in ratios of transcripts or proteins indicates up-regulation in lignin compared to unamended growth, and negative fold-change indicates down-regulation in lignin compared to unamended growth . GeneID Protein description Pathway Fold change for transcripts Fold change for proteins Entcl_0332 Phosphoenolpyruvate carboxykinase (ATP) (complement(365954..367573)) Citrate cycle (TCA cycle) 2.670 3.102 Entcl_3179 UspA domain-containing protein (3394773..3395201) None given 3.080 2.953 Entcl_4175 Periplasmic binding protein/LacI transcriptional regulator (complement(4503494..4504456)) ABC transporters 2.170 2.796 Entcl_3779 Carbon starvation protein CstA (4066791..4068944) None given 2.670 2.701 Entcl_1304 Malic protein NAD-binding (1376647..1378926) Pyruvate metabolism 3.770 2.490 Entcl_0617 AI-2 transport system substrate-binding protein (642484..643485) ABC transporters 3.180 1.780 Entcl_4402 Periplasmic binding protein/LacI transcriptional regulator (complement(4764359..4765249)) ABC transporters 2.020 1.704 Entcl_1207 ABC transporter, substrate-binding protein (complement(1260320..1261303)) ABC transporters 2.380 1.564 Entcl_2658 Isocitrate dehydrogenase, NADP-dependent (complement(2808830..2810080)) Glutathione metabolism 2.010 1.091 Entcl_0176 D-xylose ABC transporter, periplasmic substrate-binding protein (complement(183475..184470)) ABC transporters 2.410 1.035 Entcl_3614 2-oxo-acid dehydrogenase E1 subunit, homodimeric type (complement(3877006..3879669)) Glycolysis/Gluconeogenesis 2.500 −0.229 Entcl_1941 Phosphoribosylglycinamide formyltransferase 2 (complement(2053388..2054566)) Purine metabolism −2.080 −0.779 Entcl_1559 Cytidine deaminase (complement(1657176..1658060)) Pyrimidine metabolism −3.710 −1.169 Entcl_0641 Cys/Met metabolism pyridoxal-phosphate-dependent protein (complement(670311..671459)) None given −2.000 −1.757 Entcl_3443 Taurine dioxygenase (complement(3672816..3673664)) Taurine and hypotaurine metabolism −14.850 −2.995 Genome sequence analysis of SCF1 had revealed a lack of core protocatechuate and 3-O-methylgallate degradation pathways like those found in S. paucimobilis (Masai et al., 2007 ; Peng et al., 2008 ). Instead, lignin catabolism seemed likely to proceed via homoprotocatechuate through the 4-hydroxyphenylacetate degradation pathway, a gene cluster that is conserved among the Enterobacter and Klebsiella . Proteomics supports this, and metabolomics suggests that lignin may also act as a terminal electron acceptor, increasing the growth efficiency on xylose. For these studies, SCF1 was grown in xylose minimal media with and without lignin. All reported differences below have minimum 2-fold changes with significant corrected P-values (Benjamini and Hochberg, 1995 ). Xylose utilization The SCF1 genome encodes many proteins related to xylose degradation. D-xylose is likely recognized by an ABC related substrate binding protein (SBP) and transported into the cells by ATP-driven ABC transport system. Once inside the cell, xylose isomerase converts it to D-xylose and subsequently converted in to D-xylose 5-phosphate by xylulokinase. D-xylulose 5-phosphate then enters pentose phosphate pathway with the help of certain transketolase enzyme. The proteins D-xylose ABC transporter ATPase and D-xylose ABC transporter periplasmic substrate-binding protein, xylose isomerase, and xylulokinase were all detected in our growth conditions. More efficient xylose utilization in the presence of lignin was suggested by the fact that many proteins associated with xylose uptake and degradation were significantly up-regulated in the lignin-amended compared to the unamended controls (Table 3 , Figure 2A ). Xylose transport system proteins were significantly up-regulated, as were both ATPase transport and SBPs related to D-xylose ABC type transport system: D-xylose ABC transporter ATPase subunit (Entcl_0175) and D-xylose ABC transporter periplasmic SBP (Entcl_0176). While the expression of xylose isomerase (Entcl_0177) was detected but not significantly up-regulated in our lignin-amended sample, xylulokinase (Entcl_0178) was significantly up-regulated in the lignin treated sample. Various proteins related to transketolase were also up-regulated in lignin-amended sample (Entcl _0820, Entcl_1430, and Entcl_1431), though only transketolase (Entcl_1430) was significant. Adav et al. ( 2012 ) has shown up-regulation of xylose isomerase in the secretome of the thermostable filamentous bacteria Thermobifida fusca when grown on different lignocellulosic biomass. As our proteomics were performed on cell pellets, it is possible that secretomes were either missed or not induced due to the soluble nature of lignin. Adav et al. also showed expression of different ABC type-sugar transport systems depended upon the type of lignocellulosic biomass T. fusca was grown on, consistent with our observations of up-regulated ABC transporters. Table 3 Proteins over-expressed in lignin-amended compared to unamended controls . Locus Tag Protein Description Pathway Fold change p -value XYLOSE DEGRADATION Entcl_0175 D-xylose ABC transporter ATPase subunit ABC transporters 4.2 2.5e-08 Entcl_0176 D-xylose ABC transporter periplasmic SBP ABC transporters SBP 2.0 2.1e-10 Entcl_0178 Xylulokinase Xylose degradation I 2.0 2.0e-04 Entcl_1430 Transketolase Pentose phosphate 2.3 4.2e-02 Entcl_0081 Glycoside hydrolase family 31 – 2.6 7.4e-10 PUTATIVE LIGNIN DEGRADATION Peroxidase Entcl_4301 Catalase/Peroxidase HPI Tryptophan metabolism 3.5 1.5e-29 Entcl_1327 Dyp-type peroxidase family – 2.7 1.5e-02 β-aryl linkage Entcl_2195 Glutathione S-transferase domain Glutathione metabolism 2.6 4.3e-12 Entcl_0481 Glutathione S-transferase domain Glutathione metabolism 2.5 9.2e-04 LIGNIN AS ELECTRON ACCEPTOR Entcl_1442 NADH:quinone oxidoreductase B subunit Electron transport 4.5 4.2e-03 Entcl_1445 NADH:quinone oxidoreductase F subunit Electron transport 3.1 1.8e-04 Entcl_1446 NADH:quinone oxidoreductase G subunit Electron transport 4.7 3.6e-22 Entcl_0986 NADH dehydrogenase (ubiquinone) Electron transport 2.4 2.3e-04 Entcl_0361 Nitrite reductase [NAD(P)H)] Electron transport 3.5 1.8e-04 Entcl_2895 DMSO reductase subunit A Electron transport 2.7 3.0e-12 Transporters Entcl_4417 ATP synthase F0, β subunit Energy metabolism 2.5 3.4e-04 Entcl_4419 ATP synthase F1, α subunit Energy metabolism 2.2 4.8e-12 Entcl_0286 Branched chain polypeptide extracellular SBP ABC transport SBP 4.3 6.2e-20 Entcl_0288 Branched chain polypeptide extracellular SBP ABC transport SBP 3.2 1.9e-02 Entcl_1207 ABC transporter ABC transport 2.9 1.0e-03 All listed were either 2-fold over-expressed or greater (Ratio) or had a significant p-value. Figure 2 Pathways associated with (A) xylose degradation, (B) lignin degradation, the 4-hydroxyphenylacetate degradation pathway, a possible pathway of lignin catabolism, and (C) dissimilatory lignin reduction via the electron transport chain. For each pathway, the number next to the protein ID denotes the fold-level induction in lignin-amended compared to unamended growth conditions. All genes listed were statistically significantly up-regulated in lignin-amended compared to unamended controls; see Table 3 for values. Because we observed reproducible increased cell abundance on xylose minimal media amended with lignin compared to controls, we also looked for evidence of increased efficiency in respiration, hypothesizing that SCF1 may be using lignin as a terminal electron acceptor and thus increasing its efficiency of growth. After 60 h of growth, we observed no difference in xylose remaining in the media by NMR, but we detected significantly higher levels of acetate and formate produced in the lignin amended media compared to the unamended control (Table 4 ). However, differences in metabolites in lignin-amended media (no cells) compared to unamended revealed that the lignin may obscure some of the NMR signals of metabolites, so we analyzed xylose concentrations using HPLC. HPCL is not as sensitive (detection limits are in the mM range, compared to NMR which has limits in the μ M range), but there is no interference of lignin. HPLC demonstrated that both lignin-amended and unamended samples were degrading xylose. After 48 h the lignin-amended samples had 5% less measurable xylose compared to the unamended samples (0.703 ± 0.012% xylose in the xylose only growth conditions, compared to 0.667 ± 0.012% xylose in the lignin-amended growth conditions, P = 0.09). This could suggest that the degradation of lignin somehow aids in the breakdown of xylose, which may support lignin as a terminal electron acceptor. Table 4 Metabolite analysis based on NMR of supernatants for SCF1 grown in xylose minimal media with and without lignin . Xylose only media Xylose + lignin media P Cells + Xylose only Cells + Xylose + lignin P Xylose 47352 ± 1380 51464 ± 541 ** 59512 ± 4948 67402 ± 1068 n.s. Acetate 22.0 ± 3 3.0 ± 0.1 ** 841 ± 51.2 1340 ± 126 * Ethanol 175 ± 32 122 ± 30 ** 6715 ± 4699 4788 ± 624 n.s. Formate 161 ± 2.6 110 ± 4.7 ** 1625 ± 149 1908 ± 0 *** Averages are listed (n = 3), and P-values are denoted as not significant (n.s.s), * P < 0.05, ** P < 0.01, *** P < 0.001. All concentrations are in μ M. Lignin degradation Because lignin concentrations based on absorbance decreased significantly over the course of SCF1 growth, we expected to find lignin degradation pathway proteins up-regulated in the lignin-amended compared to the unamended controls. We identified SCF1 homolog targets that have been implicated in other lignin or poly-phenolic degrading bacteria. Targets consisted of enzymes associated with lignin or polyphenolic degradation, and other genes that might be involved in sugar utilization (Ramachandra et al., 1988 ; Harwood and Parales, 1996 ; Masai et al., 2007 ; Rakotoarivonina et al., 2011 ). This included the enzymes of the protocatechuate pathway found in S. paucimobilis (Masai et al., 2007 ), proteins of the protocatechuate pathway conserved among Pseudomonas , Acinetobacter , and Arthrobacter species (Harwood and Parales, 1996 ), a Thermobacillus xylanilyticus feruloyl esterase and two hypothetical β-aryl esterases from Bacillus clausii (Rakotoarivonina et al., 2011 ), and extracellular lignin peroxidase from Streptomyces viridosporus (Ramachandra et al., 1988 ). A commonly found bond in the complex heteropolymer lignin is the diphenyl, a simplified type of di-aryl ether bond, which should be degraded by phenol oxidase, peroxidase or laccase enzymes (Ramachandra et al., 1988 ; Chang, 2008 ). Based on our initial genomics analysis and reports of other lignin-degrading microbes, we identified the 4-hydroxyphenylacetate degradation pathway, catalase/peroxidase enzymes, and the glutathione biosynthesis and GST pathways as likely implicated in SCF1 lignin degradation. The catabolite 4-hydroxyphenylacetate is an intermediate in the degradation of lignin monomers (Grbić-Galić, 1985 ), and can be degraded under anaerobic conditions by a number of denitrifying and sulfate-reducing bacteria (Heider and Fuchs, 1997 ; Gibson and Harwood, 2002 ). In this pathway, 4-hydroxyphenylacetate is degraded into the TCA cycle intermediate succinate and in this way provides energy to the bacteria (Martín et al., 1991 ). The SCF1 genome encodes the entire 4-hydroxyphenylacetate degradation pathway gene in a single gene cluster HpaRGEDFHIXABC (DeAngelis et al., 2011 ). Protein abundance data showed several proteins typically associated with this pathway activated under lignin-amended samples. Proteins encoded by HpaE (Entcl_3798) and HpaG (Entcl_3797) genes were present in lignin-amended sample. Lignin degradation has been extensively studied in fungi, which produce extracellular peroxidases/catalase that are able to degrade lignin (Wong, 2009 ). Similarly, several published studies also report soil bacteria that are able to degrade lignin with the use of catalase or peroxidase enzymes. Streptomyces viridosporous , Nocardia autotrophica , and Rhodococcus sp. are well studied aerobic lignin degrading bacteria that produce extracellular peroxidase (Zimmermann, 1990 ). We found two peroxidase type proteins which are significantly up-regulated in lignin-amended sample: catalase/peroxidase HPI (Entcl_4301) and DypB-type peroxidase (Entcl_1327) (Figure 2B ). The dyp type peroxidase protein family was identified in Rhodococcus jostii RHA1 (Ahmad et al., 2011 ) and was suggested for lignin degradation by β-aryl ether breakdown. This enzyme is activated by Mn 2+ ions and was shown to degrade lignin and produce monoaryl like 2, 6-dimethaoxybenzoquinone (Singh et al., 2013 ). However, the nature of the involvement of peroxide in anaerobic lignin degradation is still unclear. We expected to find strong phenol oxidase and peroxidase activity in SCF1, because it was isolated from the Luquillo LTER soils, where soil phenol oxidase and peroxidase activities were detected across an elevational gradient spanning 2.5 km (Silver et al., 1999 , in press ). Soils from the Short Cloud Forest site (SCF) were highest in phenol oxidase and peroxidase activity compared to the lower elevation, fluctuating redox and aerobic sites (DeAngelis et al., 2013 ). Though L-DOPA is an inexpensive and easily detectable assay for cell cultures, it has been criticized as a poor soil assay substrate because it is susceptible to chemical oxidation (Sinsabaugh, 2010 ), which likely comprised some of the background activity we detected in our soils (DeAngelis et al., 2013 ). Enzyme activity analysis of SCF1 using L-DOPA as a substrate revealed no peroxidase production, or phenol oxidase production, under aerobic and anaerobic conditions. We also used ABTS as a substrate and detected phenol oxidase activity at 3.3 mU (10 6 cells) −1 , and peroxidase activity at 2.3 mU (10 6 cells) −1 . These rates potentially support a pathway for lignin degradation that includes catalase and peroxidase enzymes, but further study will be required to understand if these proteins are expressed anaerobically as well as aerobically. However, the enzyme assay method will continue to be hindered by substrate specificity, where there are many substrates in nature and available for analysis (Mayer and Staples, 2002 ; Sinsabaugh, 2010 ). GST has been studied as a method of detoxification metabolism in eukaryotes (Yin et al., 2000 ; Cho et al., 2001 ). A few Proteobacteria genomes also contain large sets of GST genes and are known to be involved in the degradation of aromatic compounds (Lloyd-Jones and Lau, 1997 ; Vuilleumier and Pagni, 2002 ). GST has been shown to have etherase activity and involved in β-aryl ether cleavage in lignin degradation in S. paucimobilis SYK-6 (Masai et al., 1999 , 2007 ). The activity of GST for lignin degradation is enhanced by the addition and presence of glutathione (Masai et al., 1993 ). Glutathione synthesis from its precursor glutamate takes place in the cytosol, and we found glutamate/cysteine ligase (Entcl_1035) and glutathione synthetase (Entcl_0809) proteins involved in glutathione biosynthesis expressed in our cultures, though with no difference in abundance between lignin-amended and unamended growth conditions (Figure 2B ). We also found ABC transport related to glutamate/aspartate transport system (Entcl_3149) up-regulated in lignin-amended samples. Similarly, different sets of GST protein (Entcl_2195 and Entcl_0481) and ABC transport related glutathione transport system (Entcl_2986) were significantly up-regulated in lignin-amended sample. Thus, the presence of glutathione biosynthesis proteins and transport system, and GST protein and its transport system could suggest a possible mechanism of lignin depolymerization by β-aryl ether cleavage in lignin-amended sample. Dissimilatory lignin reduction It is possible that SCF1 is using lignin as a terminal electron acceptor, and in this way degrading lignin in a dissimilatory manner. Various substituted quinones have been identified as key intermediates in the degradation of lignin model compounds (Ander et al., 1980 ; Buswell and Eriksson, 1988 ; Schmidt et al., 1989 ). These intermediates include substituted quinones, hydroquinones, benzaldehydes, benzoic acids, and ring-opened fragments (Buswell and Eriksson, 1988 ; Higuchi et al., 1990 ). Because lignin is a complex heteropolymeric molecule, it is possible that any of these intermediates could exist as analogous moieties and be used by the SCF1 as a terminal electron acceptor. Intracellular NADH-quinone oxidoreductase reduces 2-methoxyquinone and several other substituted quinones to their hydroquinones (Buswell et al., 1979 ; Buswell and Eriksson, 1988 ). Quinones have been studied as potential electron acceptor in anaerobic environment by facultative anaerobes (Newman and Kolter, 2000 ) and are important electron-accepting groups in humic substances (Scott et al., 1998 ). While lignin is made up of only three monolignol builfinh blocks, including coniferyl alcohol, sinapyl alcohol, and p-coumaryl alcohol, they are polymerized during biosynthesis in the plant by way of oxidative radicalization and coupling of phenols, which creates a wide variety of molecular moieties available for reduction or depolymerization via biotic degradation (Vanholme et al., 2010 ). Because of this variety, NMR analysis would be required to both elucidate the structure of the lignin as well as the chemical characters of the reduced and possibly depolymerization products that result from SCF1 degradation. We have applied proteomics to elucidate the reduction pathways of SCF1 in lignin-amended vs. unamended growth on xylose minimal media. We found three NADH-quinone oxidoreductase proteins (Entcl_1446, Entcl_1442, and Entcl_1445) significantly up-regulated in lignin amended samples (Figure 2C ). These proteins are integral in electron transport chain (Brandt, 2006 ) and are involved in transfer of electron from NADH to quinone like molecule as electron acceptor. Since lignin may be a precursor to humic substances, we assume degradation of lignin may result in quinone molecules used as electron acceptors to harvest the energy for microbial respiration. These reduced seimiquinones abiotically transfer electrons between dehydrogenase and the reductase enzyme, and this electron transfer would yield energy for bacterial growth (Scott et al., 1998 ). We also found significant up-regulation of NADH dehydrogenase (Entcl_0986), nitrite reductase (Entcl_0361) and DMSO reductase (Entcl_2895) in lignin amended sample. NADH serves as the electron donor, nitrite/DMSO as the electron acceptor and seimiquinones as mediator and could form a modular electron transport chain. We assume the addition of lignin is enhancing efficiency of energy production in SCF1 in lignin-amended samples. This was distinct from high cell abundance and high growth of SCF1 in treatment samples. Addition of vanillin, an intermediate during fungal lignin degradation, has shown to enhance energy productions in basidomycetes which seem to be required for xenobiotic metabolism and as well for cell growth (Shimizu et al., 2005 ). Enhanced energy production in this study was related to the up-regulation of ATP synthase. We also found proteins related to various subunits of ATP synthase F0/F1 (Entcl_4417, Entcl_4418, Entcl_4419, Entcl_4420, and Entcl_4421). Significant up-regulation of ATP synthase in lignin-amended sample could be justified as SCF1 may require more energy to overcome the high energy barrier for ring reduction in lignin. The transport of small aromatic molecules after lignin degradation is important because these small molecules likely account for a significant source of energy and biomass among lignin-degrading microbes (Michalska et al., 2012 ). Aromatic compounds derived from lignin degradation could be imported by an ATP-depended mechanism (Paulsen et al., 2000 ; Chaudhry et al., 2007 ). These transportations are mediated by ATP-binding cassette (ABC) transporters. The bacterial ABC transporter is composed of a transmembrane permease, a cytoplasmic ATPase subunit, and a periplasmic solute-binding protein (SBP) (Michalska et al., 2012 ). In known lignin degrading bacteria, these SBPs are identified as branched-chain amino acid-binding proteins (Giuliani et al., 2008 ; Oda et al., 2008 ). In Rhodopseudomonas palustris , a cluster of ABC transporter genes are likely involved in the uptake of benzoate into cells (Egland et al., 1997 ). This bacterium also contains several periplasmic binding-protein components of an ABC system involved in active transport for lignin-derived aromatic substrates (Salmon et al., 2013 ). We have also found significant up-regulation of an ABC transporter (Entcl_1207) and branched chain polypeptide extracellular ligand-binding receptor (Entcl_0286 and Entcl_0288) in lignin amended samples. These ABC system proteins with SBP could be involved in active transportation of lignin derived simpler aromatic compounds into the cells after degradation by putative lignin degrading proteins produced by SCF1. While the proteomics and metabolomics data support the hypothesis that lignin is being used by the SCF1 as an additional terminal electron acceptor as well as a C source, we wanted to rule out the possibility that were contaminants in the lignin that might contribute to the observed increased cell growth and activity. By HPLC, no sugar peaks or peaks of any size appeared after 7.5 min, specifically none between 9 and 13 min, where any sugars should appear. For example, glucose runs at 10.16 min, fructose at 10.39, xylose at 10.39, rhamnose at 11.20, and arabinose at 11.34 min. The detection limit of the HPLC is in the mM range for sugars. We also used NMR to test the media for sugars. Only xylose was detected, and although there was significantly more xylose detected in the lignin-amended compared to the unamended samples (51.7 ± 2.95 mM xylose in the lignin-amended media, 47.4 ± 5.4 mM unamended xylose minimal media, mean ± standard deviation, P < 2e-5), NMR did not detect any other sugars, with detection limits in the μ M range. NMR may also be subject to peak interference of lignin, suggesting that increased xylose detection is an artifact. Metabolomics analysis of the media by HPLC and NMR both showed that it is extremely unlikely that the increased cell biomass and microbial activity were due to sugar contamination in the lignin. In addition, the increased production of proteins in the hydroxyphenylacetate pathway, analogous to pathways of lignin degradation observed for other bacteria, further support the hypothesis that SCF1 is using lignin in both assimilatory and dissimilatory pathways. Despite the molecular microbial evidence that E. lignolyticus SCF1 is able to use lignin in both assimilatory and dissimilatory pathways, there are still unanswered questions. For one, the products of SCF1 anaerobic lignin reduction remain unclear. These products could include phenolic aldehyde, acid, or ketone monomers that are observed to be released during alkaline CuO oxidation (Thevenot et al., 2010 ), or any of the catabolic pathway intermediates that have observed during anaerobic lignin degradation of other bacteria, such as the catabolic pathways described for degradation of lignin and lignin-derived compounds in S. paucimobilis SYK-6 (Masai et al., 2007 ) and others (Harwood and Parales, 1996 ; DeRito et al., 2005 ; McLeod et al., 2006 ; Bugg et al., 2011b ; Huang et al., 2013 ). The use of lignin dimers or model lignin compounds such as artificial or naturally occurring aromatics would permit measurement of specific rates of degradation of specific bonds present in lignin (Kato et al., 1998 ; Koga et al., 1999 ; Chang, 2008 ). However, dissimilatory reduction of the complex heteropolymer lignin might result in increased saturation of bonds or hydrolysis of end groups, which would not result in production small molecules. To make these measurements would require high resolution molecular analysis using NMR, mass spectrometry or FTIC, where specific structural details of chemical bonds and end groups indicative of specific breakdown products can be identified (Morreel et al., 2010 ; Vanholme et al., 2010 ). These methods in combination with tracer experiments using 13 C labeled lignin should be used in the future to determine specific degradation pathways and moieties of lignin that are released. For example, growth of Fibrobacter succinogenes S85 on 13 C-wheat straw revealed succession of different fractions of wheat straw without preferential degradation of amorphous vs. crystalline cellulose (Matulova et al., 2005 ). This type of study would strongly advance our understanding of anaerobic bacterial lignin degradation, though currently 13 C-lignin studies seem to be concentrated on determining the structure of lignin, which may preclude knowing degradation products in detail (Morreel et al., 2010 ; Foston et al., 2012 ). Finally, the investigation of a single time point potentially masked detection of other degradation pathways or control points that would have been evident in early or mid logarithmic growth, before significant lignin had been degraded. An examination of the transcripts and proteins over a time-course of lignin degradation should be analyzed in order to link the controls over initiation and termination of assimilatory and dissimilatory lignin degradation."
} | 10,544 |
22250003 | PMC3259624 | pmc | 1,287 | {
"abstract": "Major feedstock sources for future biofuel production are likely to be high biomass producing plant species such as poplar, pine, switchgrass, sorghum and maize. One active area of research in these species is genome-enabled improvement of lignocellulosic biofuel feedstock quality and yield. To facilitate genomic-based investigations in these species, we developed the Biofuel Feedstock Genomic Resource (BFGR), a database and web-portal that provides high-quality, uniform and integrated functional annotation of gene and transcript assembly sequences from species of interest to lignocellulosic biofuel feedstock researchers. The BFGR includes sequence data from 54 species and permits researchers to view, analyze and obtain annotation at the gene, transcript, protein and genome level. Annotation of biochemical pathways permits the identification of key genes and transcripts central to the improvement of lignocellulosic properties in these species. The integrated nature of the BFGR in terms of annotation methods, orthologous/paralogous relationships and linkage to seven species with complete genome sequences allows comparative analyses for biofuel feedstock species with limited sequence resources. Database URL: \n http://bfgr.plantbiology.msu.edu",
"introduction": "Introduction With growing interest in the utilization of plant biomass for the production of ethanol and other biofuels, the use of plant species as biofuel feedstocks has become a research focal point. However, due to concerns about diverting grain and seed from human and livestock feed to biofuel feedstock production, emphasis has shifted to the use of lignocellulose-derived biofuel production, and research is now directed at improving not only lignocellulosic yield but also quality traits in these species ( 1–3 ). One key step in agronomic trait improvement relevant to biofuel feedstock production is identifying and understanding the genetic factors involved in the production and regulation of yield and quality traits. However, while many species have been considered for use as lignocellulosic biofuel feedstocks ( 4–9 ), only Populus trichocarpa , Sorghum bicolor and Zea mays have sequenced genomes with accompanying annotation resources that can be used to enable genome-assisted crop improvement ( 10–14 ). Currently, genome sequencing efforts are in progress for a number of other biofuel feedstock species including Miscanthus × giganteus , Panicum virgatum and Pinus taeda ( http://www.jgi.doe.gov/genome-projects/ ; http://pinegenome.org/pinerefseq/ ). However, for a wide range of biofuel feedstock species, access to genic regions is limited to transcript sequence resources in the form of assembled and annotated Sanger-generated Expressed Sequence Tags (ESTs) ( 15–17 ). Although the methods used by these various genome and transcriptome annotation projects differ, they typically include sequence alignments to genes and transcript sequences from other species, protein domain identification, gene ontology (GO) assignments ( 18 ), gene family computations and functional descriptions. All of these provide an initial estimation of gene function and enable functional genomics. Access to genome and transcriptome sequences from multiple species permits comparative analyses that are highly informative in determining gene function at either the bioinformatic or the experimental level. Comparative analyses between closely related and more distantly related species are both useful. With more closely related species, clade-specific genes can be identified, but comparative analyses involving more distantly related species permit the identification of highly conserved genes that may have roles in core biological processes. Comparative analyses are essential for species lacking a genome sequence as is the case for a large number of biofuel feedstock species, and in this report, we describe the Biofuel Feedstock Genomic Resource (BFGR), a database that provides high-quality, uniform, integrated and comparative functional annotation of gene and transcript assembly sequences from species of interest to lignocellulosic biofuel researchers. The annotated sequences include genes from seven species with sequenced genomes and transcript assemblies from an additional 47 biofuel and biofuel-related species. All sequences have been uniformly annotated and assigned functional descriptions. Annotation includes BLAST alignments ( 19 ) to UniRef proteins ( 20 ) and the proteomes of seven plant species with sequenced genomes in addition to InterPro protein domain analysis ( 21 ). Where possible, sequences have been mapped to KEGG metabolic pathways ( 22 ). Analyses have been performed to identify Simple Sequence Repeats (SSRs) from all sequences and Single Nucleotide Polymorphisms (SNPs) from the transcript assembly sequences to provide researchers with candidate genetic markers. Most importantly, ortholog analysis has been performed on all sequences so as to facilitate identification of orthologous and paralogous sequences from closely related species thereby leveraging data between species. The BFGR database also includes information about sequence resources, expression data sets, Pubmed records and germplasm resources. No other database is similarly focused on providing such a broad and fully integrated annotation of sequences from biofuel feedstock and related species.",
"discussion": "Results and discussion The major goal for BFGR was to develop a resource that not only provides high-quality, uniform and integrated annotation across sequences from multiple species but that would also permit biofuel researchers to easily perform comparative analyses on sequences from different species. The BFGR provides annotation for 1 550 736 gene and transcript assembly sequences from 54 species that include lignocellulosic biofuel feedstock species, closely related species and species with sequenced genomes ( Table 1 ). Several species for which there is relatively little sequence data are represented by only a few thousand transcript assemblies, but for a few species, the number of transcript assemblies in the database is very large and may represent a near complete representation of the transcriptome from those species. BFGR website The project website ( http://bfgr.plantbiology.msu.edu ) contains all sequence annotations as well as pages with information about sequence, germplasm and publication data available for each BFGR species. As many investigators are comfortable viewing gene annotations through graphical genome browsers, genome browsers for seven species have been prepared that display gap2 alignments of BFGR sequences to those genomes. The primary resource at BFGR is the annotation report page that is available for each sequence within the database. Each annotation report page contains information about the gene or transcript assembly sequence, protein translation, BLAST alignments to proteins from UniRef and seven plant genomes, protein domain alignments, matches to KEGG orthologs with links to KEGG pathways, gene orthologous group results, SSR markers, predicted SNPs for PUT sequence assemblies and microarray probe matches. The annotation report pages are an important component of the BFGR not only because of their content but also because of their central position in the organization of the BFGR website ( Figure 1 ). The results from all search pages include links to the annotation report pages of BFGR annotated sequences. Additionally, the annotation report page links to other homologous BFGR sequences via the BLAST alignment results and the orthologous gene tree results, and if a gene or PUT sequence has been mapped to a KEGG pathway, the annotation report page links to a KEGG pathway graphic with links to other sequences from that species mapped to the same KEGG pathway. Each annotation report page also contains a link to the original annotation resource.\n Figure 1. Information flow within the BFGR website. The Annotation Report Page maintains a central position within the organization of the BFGR database website. Features in tracks on the genome browsers, BLAST results and multiple other search results all provide links to sequence Annotation Report Pages. Additionally, Annotation Report Pages present graphical KEGG pathway maps and orthologous gene trees have links to the Annotation Report Pages for other sequences. Links also exist from Annotation Report Pages to the BFGR genome browsers and the original sequence source of the sequence. Sequence mapping to KEGG pathways A total of 545 808 BFGR annotated sequences have been mapped to KEGG orthologs, and 338 031 of these are also associated with at least one of 265 KEGG pathways ( Table 1 ). The number of sequences within a species that map to KEGG orthologs varies roughly proportionally to the number of sequences from each species, but all species have sequences that are mapped to more than 200 different KEGG pathways. An example of the utility of the KEGG annotations within the BFGR can be seen by examining the Starch and Sucrose Metabolism pathway which utilizes 71 enzymatic processes. The number of sequences with significant homology to KEGG orthologs assigned to this pathway varies from 32 Pseudotsuga manziesii var. menziesii transcript assemblies assigned to 17 different enzymatic steps to 1405 T. aestivum transcript assemblies assigned to 35 different enzymatic steps ( Supplementary Table S1 ). Besides being useful as a means to suggest a biochemical pathway within which a gene may function, by examining a relevant pathway, a researcher can quickly jumpstart a search for gene sequences related to a biochemistry of interest. Reviewing a pathway of interest for a particular species can also show the quality of sequence coverage within that pathway ( Table 1 and Supplementary Table S1 ). Additionally, by examining pathways from related species, a researcher may discern whether it is likely that there are additional relevant genes that remain to be discovered in a target species. Molecular marker analysis Genes from sequenced genome species were analyzed for SSRs, and PUT sequence assemblies were examined for both SNPs and SSRs. PUT sequences contained 354 099 putative SNPs from 80 734 sequences ( Supplementary Table S2 ). The numbers of each allele identified during SNP discovery are provided with SNP results so that a user may evaluate the quality of the putative SNP. SSRs were slightly less numerous with 336 653 SSRs found in 261 541 sequences ( Supplementary Table S2 ). The base motif for each SSR and the number of times that the motif is repeated in the given sequence are given with the SSR results. If a mapping population exists, pre-computed data about SSRs and predicted SNPs can be used to develop molecular markers for mapping genes of interest. Orthologous gene groups While many components of the BFGR annotation pipeline are commonly used by other annotation databases, orthologous group analysis is rarely furnished, but it provides a key feature in that it not only integrates sequence analysis within BFGR but also helps to leverage existing sequence and functional knowledge across species. Ortholog analysis was separately performed using the seven genome species plus all transcript assembly predicted translations from either monocot, dicot or gymnosperm species. More than half of all BFGR sequences (887 568) were assigned to 153 229 orthologous groups ( Table 1 ). Figure 2 provides a summary of the orthologous group results from the monocot and dicot analyses relative to the model genome species. These plots show that the majority of ortholog groups contain a large number of species and that there are hundreds of ortholog groups that contain protein sequences from almost every species used for ortholog analysis. There are fewer groups with sequences from many species as only a few of the non-model genome species have complete transcriptomes. Brachypodium distachyon tended to belong to fewer small ortholog groups, suggesting that either the B. distachyon genome is incomplete or that orthologous sequences from its most closely related species are not well represented in BFGR ( Figure 2 A). The large number of S. bicolor and Z. mays ortholog groups with a single additional monocot species ( Figure 2 A) may be due to rare gene sequences that are only represented in S. bicolor and Z. mays , the two most closely related sequenced genome species in BFGR. Populus trichocarpa tended to have sequences that are members of smaller dicot ortholog groups, and this is likely due to the large number of Populus species ( 11 ) in the database and probably reflects genus-specific sequences ( Figure 2 B).\n Figure 2. Number of additional species in orthologous groups with B. distachyon , O. sativa , S. bicolor and Z. mays. ( A ) For each orthologous group, the number of other Poaceae species present within the orthologous group was quantified. Counts were determined separately for orthologous groups containing B. distachyon , O. sativa , S. bicolor and Z. mays sequences . Proteins from A. thaliana , P. trichocarpa and V. vinifera were not included in these species counts. ( B ) For each orthologous group, the number of other dicot species present within the orthologous group was quantified. Counts were determined separately for orthologous groups containing A. thaliana , P. trichocarpa and V. vinifera sequences . Proteins from B. distachyon , O. sativa , S. bicolor and Z. mays were not included in these species counts. Due to the large number of orthologous groups and time constraints, it was necessary to use the time-efficient Swofford and Rogers tree searching algorithm when generating the ortholog trees. Nonetheless, when examining orthologous groups of well-studied gene families, the relationships depicted in these BFGR ortholog trees are consistent with expectations. For example, the monocot orthologous gene tree for the phytochrome gene family shows three main subtrees that correspond to phytochromes A, B and C ( Supplementary Figure S4 ). Several species have multiple gene/transcript identifiers within the three main subtrees indicating the presence of either multiple alternative transcript isoforms or distinct close paralogous genes. Ortholog analysis in the PAL gene family To characterize a gene family more directly relevant to lignocellulose biofuel production, members of the monocot phenylalanine ammonia-lyase (PAL) gene family were chosen for closer analysis. PAL enzymes convert phenylalanine to cinnamic acid, the first committed step in lignin production ( 36 ). Supplementary Table S3 shows the 617 monocot sequences within the BFGR database that have a functional annotation of ‘phenylalanine ammonia-lyase’ and the orthologous groups to which each belongs. The 27 PAL genes from A. thaliana , P. trichocarpa and V. vinifera are also included in Supplementary Table S3 as they were part of the OrthoMCL analysis of monocot sequences. The largest orthologous group (cluster 59) contained 127 PAL sequences. No other ortholog group had more than 13 members, but there were 396 PAL-annotated sequences that had not been assigned to any group. The average length of the proteins in cluster 59 (517 ± 197 amino acids) is notably longer than the average length of the proteins from all other clusters (220 ± 135 amino acids) and from the unassigned sequences (196 ± 87 amino acids). This suggests that incomplete gene or transcript assemblies produced truncated protein predictions were more likely to result in BLAST alignment scores that were insufficiently strong for OrthoMCL to cluster the truncated sequences with full-length members of the same gene family. There are also a few exceptions where presumably full-length protein sequences from the model genomes were either not assigned to any ortholog group or assigned to a minor cluster, and these sequences may represent PAL genes that have significantly diverged from the core PAL gene family. Given the variable completeness of gene and transcript assembly sequences in the BFGR database, the ortholog analyses are unlikely to have captured a complete picture of the ortholgous relationships in this complex gene family. This is an inherent result of working with incomplete sequence data. Nonetheless, the ortholog tree for the sequences from cluster 59 suggests interesting orthologous, paralogous and homologous relationships in this large gene family ( Supplementary Figure S5 ). The dicot PALs are found in a single subtree, unlike the phytochrome ortholog tree, suggesting that monocot and dicot PALs have significantly diverged from each other."
} | 4,179 |
31068664 | PMC6506546 | pmc | 1,288 | {
"abstract": "Temperate marine ecosystems globally are undergoing regime shifts from dominance by habitat-forming kelps to dominance by opportunistic algal turfs. While the environmental drivers of shifts to turf are generally well-documented, the feedback mechanisms that stabilize novel turf-dominated ecosystems remain poorly resolved. Here, we document a decline of kelp Saccharina latissima between 1980 and 2018 at sites at the southernmost extent of kelp forests in the Northwest Atlantic and their replacement by algal turf. We examined the drivers of a shift to turf and feedback mechanisms that stabilize turf reefs. Kelp replacement by turf was linked to a significant multi-decadal increase in sea temperature above an upper thermal threshold for kelp survival. In the turf-dominated ecosystem, 45% of S. latissima were attached to algal turf rather than rocky substrate due to preemption of space. Turf-attached kelp required significantly (2 to 4 times) less force to detach from the substrate, with an attendant pattern of lower survival following 2 major wave events as compared to rock-attached kelp. Turf-attached kelp allocated a significantly greater percentage of their biomass to the anchoring structure (holdfast), with a consequent energetic trade-off of slower growth. The results indicate a shift in community dominance from kelp to turf driven by thermal stress and stabilized by ecological feedbacks of lower survival and slower growth of kelp recruited to turf.",
"introduction": "Introduction Globally, forests of kelp and other habitat-forming brown seaweeds have been replaced by mats of low-lying turf-forming algae, representing a loss of ecosystem structure and biodiversity 1 – 4 . Declines of habitat-forming kelps in disparate regions over the past 3 decades have been linked to a range of stressors, with ocean warming and eutrophication being the most commonly identified environmental drivers 5 . However, despite localized kelp declines, there is no unifying global pattern of kelp change, with some populations remaining unchanged and others expanding over the past half century 6 . Based on studies at early life-history stages, it is predicted that warm-adapted kelp populations existing at the equatorial range limits of species distributions may be the most resilient to climate change and most likely to persist into the future 7 . Longitudinal field observations at the range limits of kelp species are required to test this hypothesis. Where regime shifts from kelp to turf dominance have occurred, various feedback mechanisms may stabilize the turf-dominated ecosystem state contributing to its temporal persistence 5 . Such feedbacks include high sediment loads, kelp spore limitation, and space limitation on turf reefs, which prevent recruitment and reestablishment of kelps 8 – 10 . However, in general, information is scant on the ecological functioning of novel turf-dominated ecosystems 11 . In particular, it is unknown whether the turf-dominated state represents an alternative stable state (sensu Scheffer et al . ref. 12 ) of the kelp ecosystem, with both kelp- and turf-dominated states occurring under the same set of environmental conditions (i.e. with hysteresis) 5 . A better theoretical ecological understanding of regime shifts to turf will improve our ability to predict the reversibility of these shifts once an initial environmental driver (e.g., eutrophication) is relaxed. At the southern extent of kelp forests in the Northwest Atlantic, the dominant kelp species Saccharina latissima exists near its upper thermal threshold for survival 13 , providing a useful model for examining the resilience of warm-adapted kelp forests. Peak recruitment in this region occurs in the winter and spring following sporogenesis in early autumn and spring 14 , 15 . The life history of S. latissima alternates between annual and biennial growth, with annual cohorts occurring in the warmest years due to blade degradation in the late summer and low survival into the following year 16 . This is in contrast to more northerly locations in the North Atlantic where populations of S. latissima are perennial with individual lifespans of 2–3 years 17 , 18 . The macroscopic diploid sporophyte stage of S. latissima has a lower thermal tolerance than the microscopic haploid gametophyte stage 15 . Laboratory and field studies have indicated that at the southern extent, the gametophyte stage can persist through supraoptimal summer temperatures, acting as a warm-tolerant oversummering “resting stage” as an adaptation to dealing with warm temperatures 15 . Surprisingly, the most recent quantitative data of kelp abundance (biomass and density) for this region are from the 1980s 16 , 19 . At that time, kelp forests in Rhode Island Sound and Long Island Sound, USA had primary productivity similar to that of more northerly populations in Nova Scotia, Canada, and the United Kingdom, with standing biomass of up to 24 kg m −2 16 , 19 , indicating healthy kelp forests at the southern extent. However, mean sea surface temperatures over ~6 decades from 1948 to 2012 warmed at the southern extent at a rate of 0.3 °C decade −1 20 , with unknown impacts on kelp populations. In fall 2017, divers observed low abundance of kelp at a site (Fort Wetherill) at the mouth of Narragansett Bay, Rhode Island that was previously dominated by a dense S. latissima kelp forest 19 . Young S. latissima sporophytes that were present were largely attached to turf-forming macroalgae rather than rocky substrate, a phenomenon that was previously rare 19 . The observations prompted us to conduct a field study to evaluate the state of kelp forests at the southern extent with 4 main objectives: (1) to quantify kelp biomass and density for comparison with available baseline data from the 1980s; (2) to determine whether algal turf has replaced kelp as the dominant benthic primary producers; (3) to examine correlative evidence for the environmental drivers of an apparent decline of kelp and the rise of turf; and (4) to elucidate the feedback mechanisms that stabilize a turf-dominated ecosystem; specifically, by examining the ecological consequences of kelp recruiting onto turf (e.g., morphology, growth, and survival of kelp on turf versus rocky substrate). To determine whether long-term ocean warming is a likely driver of kelp decline, we analyzed weekly sea surface temperature data from the Narragansett Bay Plankton Time Series collected over a 58-year period from 1959 to 2017 (see Methods). Based on previous observations that the rate of erosion of the distal end of S. latissima sporophytes exceeds the rate of meristematic growth at temperatures above 20 °C 14 , and that 22 °C is an upper critical limit for S. latissima gametophyte survival 21 , we developed a thermal integral of weeks with sea temperatures ≥22 °C (degree-week) for each year as an indication of the magnitude of kelp thermal stress through time. Given that eutrophication also is cited as a common cause of a regime shift from kelp to turf (e.g., in Russia, Denmark, Norway, Brazil, and Australia) 5 , we also examined time series of ammonium, nitrate, and phosphate concentrations from the Narragansett Bay Plankton Time Series collected over a 46-year period from 1972 to 2018.",
"discussion": "Discussion Kelp forests are some of the most biodiverse ecosystems in the world and support primary productivity comparable to that of tropical rain forests 23 , 24 . However, these marine forests are under threat due to anthropogenic environmental degradation driven by climate change and local stressors such as eutrophication 5 , 6 . Understanding the primary drivers of kelp decline and the functioning of novel anthropogenic ecosystems that replace kelp forests is of critical importance to management and conservation of marine resources 5 . Here, we documented a substantial decline of kelp abundance at sites at the southernmost extent of kelp forests in the Northwest Atlantic, with order of magnitude decreases in kelp biomass and density in 2017–2018 as compared to baseline data collected in the 1980s. Contemporary biomass values at or near zero are well outside expected natural intra- or interannual variability of S. latissima populations 18 , 19 , suggesting we are observing the loss of kelp forests from this region. Furthermore, we found that once-dominant kelp was replaced by turf-forming macroalgal species, contributing to a global pattern of kelp loss followed by the “rise” of turfs 5 . The loss of kelp forests at sites in Narragansett Bay is consistent with a multidecadal increase in sea surface temperature above a threshold for survival of S. latissima sporophytes and resting-stage gametophytes. This pattern of kelp loss occurred despite a significant decrease in local nutrient loads over the study period. A decrease in ammonium, nitrate, and phosphate concentrations in Narragansett Bay from 1972 to the present is best explained by passage of the Clean Water Act in 1972, which reduced the discharge of pollutants into United States watersheds ( https://www.epa.gov/laws-regulations/summary-clean-water-act ). This finding indicates a success story for local water management, but with the important implication that local management cannot necessarily protect marine ecosystems against degradation in the face of global climate change. Given current trends in sea temperatures, we predict the continual decline and absence of kelp at the southern extent in the Northwest Atlantic. Thus, despite optimistic forecasts that warm-adapted kelp populations should be the most resilient to climate change impacts 7 , these S. latissima populations likely do not have the adaptive capacity to respond to warming sea temperatures at current rates under global climate change. Our findings are consistent, rather, with predictions that distributions of marine species at their upper thermal physiological range limits will contract poleward 25 . Turf-forming macroalgal species identified as part of our study ranged two phyla (Rhodophyta and Chlorophyta) with diverse evolutionary histories and growth forms (e.g., plumose, filamentous, and finely and coarsely branching), indicating the complex nature of the novel turf-dominated ecosystem. Turf communities are generally comprised of opportunistic, “weedy” species with high tolerance to stress; however no overarching definition of “turf” has been established 11 . Indeed, many studies examining shifts from kelp to turf dominance do not characterize the composition or structure of the turf community outside of general descriptions such as “filamentous” turfs 8 or “fast-growing” turfs 3 . This exemplifies the extent to which we understand very little about the ecological functioning of these communities, limiting the ability of researchers to generalize their findings across globally disparate turf-dominated ecosystems. Feedback mechanisms that stabilize the turf-dominated ecosystem may increase the resilience of the ecosystem to a reverse shift back towards kelp dominance, and may indicate the presence of alternative stable states 5 . While we cannot directly test for hysteresis in our dataset, as kelp forests and turf reefs occur under separate environmental conditions of sea temperature, we did identify feedback mechanisms that may stabilize the turf-dominated ecosystem. The presence of such mechanisms suggests that if sea temperature trends were to reverse, the turf-dominated ecosystem could persist beyond the point at which an initial regime shift to turf occurred. We determined that space preemption by turfs results in kelp sporophytes attaching to turf rather than rocky substratum. The turf-attached kelp had lower survival as compared to rock-attached kelp, likely due to significantly weaker attachment strength. Dislodgement of kelp likely occurred during two strong wave events (>3 m significant wave heights) on 17 and 26 April 2018 (Supplementary Fig. S1 ). This interpretation is consistent with the findings of Burek et al . (ref. 9 ), who observed lower survival of turf-attached as compared to rock-attached kelp transplanted from wave-protected to exposed sites in Nova Scotia, Canada, and who suggest that this creates a feedback mechanism that stabilizes the turf-dominated ecosystem. Turf-attached kelp allocate significantly more biomass to the holdfast and have significantly more complex holdfasts than rock-attached kelp 9 . We observed reduced growth rates of turf-attached kelp, which may represent a trade-off in resource allocation from blade growth to holdfast development and extension of haptera to strengthen attachment on a suboptimal substrate. Slower growth of turf-attached as compared to rock-attached kelp may act to limit the reproductive output of kelp in turf-dominated ecosystems, as the size of the sorus will be constrained by blade size 26 . Thus, in combination, increased mortality of turf-attached kelp due to dislodgement, and slower growth of turf-attached individuals should create a feedback loop that stabilizes the turf-dominated ecosystem and limits the reestablishment of kelp. The mean growth rate of rock-attached kelp in our study (1.2 cm d −1 ) was similar to that observed in the early 1980s by Brady-Campbell et al . (ref. 19 ). This result suggests that individual-based productivity rates for rock-attached kelp have not changed over an ~40-year period. However, given that approximately half of the kelp were attached to turf and had significantly slower mean growth rates (0.9 cm d −1 ), and kelp biomass also was much lower in 2017 and 2018, population-scale kelp productivity likely has substantially declined. Kelp have a potentially important role in mitigating climate change through the sequestration and storage of carbon that is transported to deep ocean regions as macroalgal detritus 27 . Thus, loss of kelp productivity could act as a positive feedback for climate warming. A recent study in the Gulf of Maine demonstrated 150 times greater S. latissima density at offshore sites (Caches Ledge) than coastal sites, despite thermal stress of kelp in both regions 28 . No information currently exists for offshore kelp forests at the southern limit of S. latissima in the Northwest Atlantic. Future research should therefore be focused on determining whether a localized community shift to turf observed on reefs in Narragansett Bay is a region-wide phenomenon, and should investigate management strategies to prevent or reverse the disappearance of kelp forests. In addition to curbing global climate change, local management strategies that involve the removal of turfs to open up space for kelp recruitment should be considered given the ecological feedbacks associated with recruiting to turf documented here. The purple sea urchin Arbacia punctulata has the ability to clear small patches in the algal turf and create bare space (authors’ pers. obs.). Interactions between algal turfs, kelp, and grazers on these reefs therefore warrant investigation. Grazing by sea urchins could destabilize a turf-dominated ecosystem if grazed patches are colonized by kelp propagules that survive to reproductive maturity."
} | 3,802 |
30322171 | PMC6215152 | pmc | 1,289 | {
"abstract": "Super-hydrophobic natural surfaces usually have multiple levels of structure hierarchy. Here, we report on the effect of surface structure hierarchy for droplet evaporation. The two-level hierarchical structures studied comprise micro-pillars superimposed with nanograss. The surface design is fully scalable as structures used in this study are replicated in polypropylene by a fast roll-to-roll extrusion coating method, which allows effective thermoforming of the surface structures on flexible substrates. As one of the main results, we show that the hierarchical structures can withstand pinning of sessile droplets and remain super-hydrophobic for a longer time than their non-hierarchical counterparts. The effect is documented by recording the water contact angles of sessile droplets during their evaporation from the surfaces. The surface morphology is mapped by atomic force microscopy (AFM) and used together with the theory of Miwa et al. to estimate the degree of water impregnation into the surface structures. Finally, the different behavior during the droplet evaporation is discussed in the light of the obtained water impregnation levels.",
"conclusion": "4. Conclusions In this study, the strong effect of a two-level hierarchical structure on prolonged life of hydrophobicity of a polymer sample is shown through droplet evaporation. An attempt to explain this effect showed a possible wetting level for a nano-rough surface compared to a hierarchical micro/nano-rough surface. A method for estimation of the wetting level using direct results from the AFM measurements is presented. In further studies, different types of more robust nano-patterns should be tested, as well as a larger number of hierarchy levels. The mass-production roll-to-roll platform seems to give robust reproducible results, and the scalability of the pattern production, including techniques to allow for larger origination areas, should be investigated.",
"introduction": "1. Introduction The wetting properties of materials are strongly influenced by their surface roughness. Sparked by advancements in scanning electron microscopy (SEM) that led to a resolution of the surface structure of the lotus flower [ 1 ], different artificial patterned surfaces have been fabricated in an attempt to mimic this and other bionic effects [ 2 ]. Typical lotus-like structures rely on roughness defined on multiple length scales and a hydrophobic surface chemistry. While in nature such structures can comprise up to six levels of hierarchy [ 3 ], the current study comprises a two-level hierarchical structure which is compared to the two structure types it is built from. A common practical definition of a super-hydrophobic surface includes two requirements: the apparent contact angle (CA) with water has to be above 150°, at the same time the CA hysteresis (the difference between the advancing and receding contact angles) has to be low (below ~10°). As pointed out in several studies, this definition is somewhat arbitrary [ 4 , 5 ], and a more well-defined and more forgiving, yet less practical, definition would be a surface with a water CA exceeding the one for the theoretically most hydrophobic flat surface comprising the closest hexagonally packed -CF 3 groups having a water contact angle of ~119° [ 6 ]. Super-hydrophobicity should, however, not be confused with self-cleaning, as even though the requirements for the CA and CA hysteresis are met, the surface can lose the water-repellent qualities over time and undergo a so-called wetting transition [ 7 , 8 , 9 , 10 ]. Such wetting transitions are typically studied through applied pressure [ 8 , 11 ], evaporation [ 12 , 13 ], and vibration of the droplet [ 14 ] or using bouncing droplets [ 15 , 16 ]. In this article we study how droplets behave over time when left to evaporate from different surfaces. This approach has been widely used for the investigation of the droplet evaporation rates [ 17 , 18 ] and for analyzing superhydrophobic and patterned surfaces [ 19 , 20 , 21 ], and several modeling techniques have been proposed to describe this process [ 19 , 22 , 23 , 24 ]. Erbil published a review on the topic in 2012 [ 25 ]. The apparent contact angles measured on rough surfaces are conventionally described in terms of the so-called Wenzel [ 26 ] and Cassie-Baxter [ 27 ] models from 1936 and 1944, respectively. The models are based on a thermodynamic approach whereby the Gibbs free energy is minimized in terms of the CA for the system comprising the three states of matter, namely, the solid substrate, the liquid droplet, and the surrounding gas [ 28 ]. Although, a prediction of the apparent CAs based on this approach often fails, and has led to heated scientific debates about its validity [ 29 , 30 , 31 ], it is conceptually well established that a droplet in the so-called “Wenzel state” completely wets the surface texture, while a droplet in the so-called “Cassie-Baxter state” rests on the summits of the surface texture. The shortcomings of the Wenzel and Cassie Baxter models seem to be associated with droplet pinning, where droplets get trapped in metastable states representing local minima in the free energy [ 16 ]. Stated in terms of force arguments, pinning may also stem from minute elastic deformations due to the vertical projection of a Young-type reaction force per unit length of the triple line [ 32 ]. Pinning effects are also considered responsible for the so-called contact angle hysteresis [ 33 , 34 ]. For pointy surface protrusions having typical opening angles 2 α , it can be argued, by imposing the requirement of the CA on a microscale being equal to the Young CA, θ Y , that the droplet will end up in the Wenzel state if θ Y < α + 90 ° , while for larger Young CA, the triple phase line will move and impregnate the texture until θ Y = α + 90 ° is fulfilled corresponding to a partly wetted surface texture [ 35 ]. A more realistic Cassie-Baxter type of equation to predict the apparent CA, θ , for a partially wetted surface was given by Miwa et al. [ 36 ]. Here, we state this model in terms of the impregnation depth, Z , measured from the summits of the protrusions, such that positive Z values are obtained when water impregnates the surface texture from above.\n (1) cos θ = R f · φ ( Z ) · cos θ Y + φ ( Z ) − 1 where R f > 1 is the Wenzel roughness parameter, i.e., the actual surface area to the projected surface area, θ Y is the Young contact angle, and φ ( Z ) is the ratio of the projected wetted area to the total area. The problem with Equation (1) is, however, that the parameter φ ( Z ) is usually not known. Hence, in this study, we employ AFM measurements to determine the range of half opening angles α ( Z ) of structures at a given impregnation depth, Z , and impose the condition,\n (2) θ Y = α ( Z ) + 90 ° to estimate Z . When used together with φ ( Z ) , also determined by atomic force microscopy (AFM), we are able to predict the apparent CAs by using Equation (1) and compare them with experiments. Thus, one of the novel findings in this work is a proposed method to estimate the level of wetting on the micro-level and to exploit this information to enable a theoretical computation of contact angle data based on actual measured surface shapes. Measurements of the rough surfaces in Si and other hard materials are important for understanding the wetting properties, however, for real-life applications the structures need to be transferred to a cheaper materials platform allowing for mass-production of large areas. For this study, the initial Si structures are replicated in polypropylene (PP) flexible foils via a roll-to-roll extrusion coating method (R2R EC), which is a well-established method in the packaging industry. Extrusion coating has a capacity for the manufacturing of up to 2 m wide packaging foils at the production speed up to 1000 m/min. Production of micro- and nano-patterns using R2R EC is a relatively new method that has shown promising results for scaling up the production of biomimetic surfaces [ 37 , 38 , 39 ].",
"discussion": "3. Results and Discussion In this study, three types of surfaces are compared: micro-patterned pillar surfaces (as presented by Okulova et al. [ 39 ]), randomly patterned nano-grass surfaces (as investigated by Telecka et al. [ 38 ]), and hierarchical surfaces, where the micro-pillars are superimposed with the nano-grass structures. A micrograph of the hierarchical pattern is presented in Figure 1 . The preliminary study on morphologies of the nano-grass has been conducted by Schneider et al. [ 35 ] and an optimized structure is used in this study. 3.1. Contact Angle and Droplet Evaporation The results of the measurements are presented in Table 1 . It is worth noticing that according to these measurements, both the hierarchical structures and the nano-grass samples are superhydrophobic and have very similar wetting properties. The surfaces are further characterized by CA recordings for sessile droplets resting on the structured surfaces during evaporation. The contact angles for each type of structure during evaporation are shown in Figure 2 A, plotted as a function of the evaporated volume from each sessile droplet. Each curve is an average of two independent measurements (the shown standard deviation is calculated for the average of the two measurements and angles on both sides of the droplet). The data shows an interesting effect of the hierarchy: the apparent CA for the pure nano-grass sample decreases much faster than for the hierarchical sample. The two samples had seemingly the same CA and CA hysteresis properties to start with, however, the difference between the two structures is evident after the 30 min evaporation. The hierarchical surfaces seem to have a similar rate of contact angle decrease as the micro-pillar surfaces; an attempt to explain this behavior is presented in the last part of this article. Another noticeable effect is a change in the behavior for the micro-pillar sample. The second part of the curve has a slope around one, which could be due to the droplet reaching the receding contact angle and hence jumping from one pillar to another (a zoom-in on the area is presented in the insert of Figure 2 A). In order further to analyze the measured effect, contact diameter values are extracted from each frame using MATLAB. The contact diameter here is the diameter of the circle enclosed by the triple line—where air, water, and PP are in contact. The results of these measurements are presented in Figure 2 B. The contours of the droplet during evaporation are presented in Figure 2 C–E, and the corresponding structure micrographs are seen in Figure 2 F–H. The stair-like shape of the contact line plot comes from the limit of the resolution of the camera; each step simply corresponds to the pixel-size. Each curve is fitted with a linear fit and the slope of each curve is shown directly under each plot. The contact angle measurements seem to be in agreement with the contact diameter measurements. The contact line shrinks twice as fast for the hierarchical structures than for the nano-grass structures. This is also seen in the contour lines in Figure 2 D, the droplet is more pinned to the nano-grass than to the other two structure types shown in Figure 3 C,E. Confirming the results from the contact angle measurements, the micro-pillar sample reaches the receding contact angle and seems to start unpinning faster, and the contact diameter drops more rapidly. The contours of the droplets seem to be more pinned on one side than the other, which is not surprising when taking the possible defects on the nano-pillar surface and the stochastic nature of the nanograss structure into account. The droplet on the hierarchical surface in Figure 3 C seems, however, mainly to evaporate in constant CA mode, whereas the droplet on the plain nano-grass surface in Figure 3 D mainly seems to evaporate when in constant contact diameter mode as described by Kulinich and Farzaneh [ 24 ]. This hints that the droplet sitting on the hierarchical surface is less pinned than the droplet on the plain nano-grass surface. The last droplet in Figure 3 E, is clearly strongly pinned in an asymmetric mode. The micro-pillar pattern is at this point assumed to be in Cassie-Baxter state at all times, the contact angle for the presented micro-pillar pattern calculated using Wenzel equation [ 26 ] is 104.5°, while the Cassie-Baxter contact angle [ 27 ] for the same structure is 157.0°, which is in agreement with the results presented in Table 1 for the apparent CA. The produced micro-pillar structures were designed to never undergo a wetting transition from the Cassie-Baxter state into the Wenzel regime. According to Jung and Bhushan [ 41 ], the full wetting transition will occur for similar pillar-patterns at pitches above 50 µm. The wetting transition for the current pattern will take place only when the droplet volume decreases below 10–20 µm, and at this size the contact angle is not detectable for the used equipment (the lowest droplet size used in this study was ~700 µm). 3.2. AFM Measurements and the Wetting Level The nano-grass covered samples were imaged using AFM and the data from the measurements were used for the estimation of the wetting level. First, the supposedly wetted area of the pattern was used for calculating the φ ( Z ) (the projected area over the full area of the sample), here, the integral of the structure height distribution (Abbott curve) was used. This value was then used directly in Equation (1) to calculate the expected contact angle at each depth of the pattern (note that in this calculation the tips of the black silicon structure were set as the zero value). The results of this calculation are presented in Figure 3 . For these calculations, the roughness parameter R f was read out from the AFM measurements and was taken as a constant average for all the surfaces with nano-grass. The value used in all calculations was R f = 3.78. The apparent contact angle of a water droplet on a flat PP surface (a replica of the part of the shim based on a polished Si wafer) was used as the value for the Young contact angle, θ Y = (102 ± 1)°. The surface topography obtained from AFM measurements was used for calculating the half-opening angle α ( Z ) = a c o t ( ( d Z / d X ) 2 + ( d Z / d Y ) 2 ) , where d Z / d X and d Z / d Y values were extracted directly from the AFM data. The measured values for all ( X , Y ) coordinates are plotted against the Z -measured height in Figure 4 A. In order to visualize where on the pattern the particular opening angle is found, a one-dimensional (1D) cut through the dataset through the middle of the pillar is shown as the black line. The critical α ( Z ) value was calculated using Equation (2) and for PP foils with apparent contact angle on the flat surface of 102°, used here as the Young contact angle, α ( Z ) = 12 ° . This critical angle is shown in the graph with a vertical dashed black line. For all the values below this angle, the wetting should not be possible according to Equation (2). Two areas, where a significant amount of opening angle values are below 12° can be distinguished from the graph: on the top part of the pillar, where the top layer of the nano-grass pattern is shown (blue) and the valley area, where the second layer of the nano-grass pattern is present (red). Both areas are framed with horizontal lines, and for each of the 4 Z -values, a 3D AFM image including the expected wetting degree is sketched out in Figure 4 B (1–4, respective to each line in the Figure 4 A). Compared to the FIB-SEM image of the structure ( Figure 1 B), the AFM tip experiences a slight tip convolution, which creates many faulty high values of the opening angle at every top and bottom part of the grass pattern. Due to the random nature of the nano-grass pattern, the height of each individual tip varies, which makes it difficult to trust an average value of the opening angle. However, the values for each middle part of the needles must be close to the true value, and hence can be trusted. To summarize the results in Figure 4 , the level of wetting in such a nano-grass covered sample must lie somewhere between the blue lines or between the red lines, as that is where the local water-air-substrate interaction prevents the water from travelling further down along the protrusion. Compared to the results from the calculated theoretical value of the contact angle according to the Miwa model, originated from the modified Cassie-Baxter equation) presented in Figure 3 , the contact angle for the hierarchical pattern should lie between Z -values of −0.7 µm and −0.25 µm, which corresponds to the contact angle range 168°–176°. If compared to the measured value of the contact angle for the hierarchical pattern, if this theory is correct, the wetting of the hierarchical pattern must correspond to Figure 4 B (2), where the top part of the pillar is covered with water but does not touch the bottom part of the nano-grass carpet. This could explain why the hierarchical structure experiences less pinning: the water droplet is only in contact with 1/10 of this nano-grass pattern for these structures compared to the pure nano-grass sample. For the hierarchical structures, the unpinning from each pillar-top seems to have a lower threshold than unpinning from the fully covered nano-grass “carpet”."
} | 4,375 |
38474537 | PMC10934110 | pmc | 1,290 | {
"abstract": "Spider silk protein, renowned for its excellent mechanical properties, biodegradability, chemical stability, and low immune and inflammatory response activation, consists of a core domain with a repeat sequence and non-repeating sequences at the N-terminal and C-terminal. In this review, we focus on the relationship between the silk structure and its mechanical properties, exploring the potential applications of spider silk materials in the detection of energetic materials.",
"conclusion": "5. Conclusions and Outlook Various spider species produce specific silk proteins in morphologically distinct glands. Since 1990, numerous silk genes have been identified for different silk proteins, accompanied by a plethora of physical studies. The spider silk protein comprises a core domain with a repeat sequence and non-repeating N-terminal and C-terminal sequences. The structures, properties, and functions of spider silk proteins depend on the arrangement of different amino acids. Spider silk fibers exhibit mechanical properties superior to the best synthetic fibers produced by modern technology, such as Kevlar and nylons. Additionally, spider silk exhibits excellent biological properties, making it attractive for biomedical applications. Apart from fibers, spider silk proteins possess exceptional versatility for processing in various colloidal forms, such as particles, foams, gels, films, sponges, porous systems, capsules, non-woven fiber mats, and emulsions. Their ability to be processed in aqueous solutions under ambient conditions, coupled with their favorable characteristics, makes them an excellent candidate for applications in electronic and photonic devices. Researchers have shifted their attention from conventional substrates, like glass and silicon, to exploring the potential offered by biopolymer silk fibroin scaffolds, applicable for material development, device fabrication, and, notably, the detection of nitroaromatic explosives [ 178 ]. These sensors exhibit a significant change in resistivity when exposed to the vapors of nitroaromatic compounds, such as TNP and TNT. The similarity between spider silk and silk fibroin makes the use of spider silk materials and impedimetric sensing techniques an ideal choice for detecting explosive vapors, aligning with the ambitious goal of sustainability. It is, however, disappointing that spider silk materials have not been actively utilized in the field of explosives detection. Exploring this aspect could prove to be a significant avenue for future research and development.",
"introduction": "1. Introduction Natural spider silk fibers, having evolved over 400 million years, serve crucial functions in feeding, reproduction, and survival [ 1 ]. With a remarkable diversity of over 45,000 species, spiders exhibit the ability to produce task-specific silks with diverse mechanical properties originating from their unique silk glands [ 2 , 3 ]. Several types of spidroins, with different structures, determine their specific physical properties corresponding to their biological roles ( Figure 1 ). Major ampullate silk (MaSp) (dragline silk) and minor ampullate silk (MiSp), known for their high strength, together with flagelliform silk (Flag), known for its high elasticity, contribute to the intricate production of a spider’s orb web, facilitating both its formation and effective capture of prey insects [ 4 ]. Aggregate silk (AgSp) (aggregate glue) provides spider silk with its renowned stickiness [ 5 ]. Tubuliform silk (TuSp) (cylindriform spidroin (CySp)) is the main constituent used by female spiders to manufacture egg cases [ 6 ]. Aciniform silk (AcSp) is applied for wrapping prey and protecting the egg sac from predators and environmental fluctuations, such as temperature and humidity changes [ 7 ]. Pyriform silk (PySp) is utilized in creating the attachment disc, enabling the web to adhere to different surfaces [ 8 ]. Exhibiting an intriguing blend of light weight, high strength, and exceptional elasticity, spider silk stands out as a stellar biomaterial. Its mechanical properties are on par with the best synthetic fibers manufactured by state-of-the-art technology. Its low toxicity and immunogenicity, coupled with its slow biodegradability and an apparent propensity for cell adhesion and growth, make it a compelling selection for biomedical applications [ 10 , 11 ]. In addition, silk threads also demonstrate interesting properties, featuring torsional memory, supercontraction, and self-healing [ 12 , 13 , 14 ]. Spider silk has been used by humans since ancient times. During the Middle Ages, and even as far back as the ancient Greek and Roman cultures, spider webs were employed for wound dressing [ 15 ]. The first pair of gloves and stockings made of spider silk were displayed at the Paris Academy of Sciences in 1710. Another pair of stockings was made by an American [ 16 ]. During the past years, dragline silk has been the most researched object of all the spider silks, while studies on minor ampullate silk, flagelliform silk, pyriform silk, aciniform silk, aggregate glue, and tubuliform silk have all been reported [ 3 , 9 , 10 , 11 , 12 ]. Nowadays, recombinant spider silk proteins have gained widespread employment in various fields, including biomedical, cosmetic, and technical applications. However, owing to the territorial and cannibalistic nature of spiders and the challenge of generating substantial quantities of silk proteins at an economical cost, spider farming has been deemed impractical. Consequently, the best alternative is the biotechnological production of spider silk proteins. This process comprises two strategies: One involves the use of prokaryotic hosts, like E. coli , leveraging the well-established techniques of cell disruption and protein purification [ 17 , 18 , 19 ]. The disadvantage of prokaryotic expression systems is their inherent limitation in the size of synthetic genes. Another approach employs eukaryotic hosts, such as yeast, Bombyx mori , transgenic plants, bovine mammary epithelial alveolar cells, etc., which produce recombinant proteins most closely resembling natural silks [ 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ]. Unlike the above-mentioned genetic engineering methods, chemical synthesis only replaces some regions of the silk protein with organic polymers [ 28 ]. However, the mechanical properties of the new fiber material are worse than those of natural silk. In this review article, our focus is on how the silk structure determines its mechanical properties and its potential applications in detecting energetic materials. The repetitive domain is important for the mechanical properties of spider silk. Each repeat consists of crystalline stretches and amorphous areas, which collectively influence the strength and elasticity of the spider silk. The assembly of spidroins is controlled by non-repetitive domains, and some spider silk proteins feature a linker region bridging the terminal and repetitive regions of the silk protein. The structure and influence of these regions have yet to be discussed. Spider glues, microscopic glycoprotein nodules on capture silk that do not stick to each other, contribute to the stickiness of spider silk. Apart from the primary structure of spider silk, spinning techniques also have an important influence on the silk properties. Different forms of silk proteins have unique mechanical properties, rendering them suitable for various applications in different areas. Recombinant spider silks have found applications in diverse areas, particularly as exceptional candidates for biomedical applications, including tissue engineering, as well as in functionalized textiles, electronic engineering, cosmetics, etc. In response to the growing need for high-performance and eco-friendly materials in the sensor industry, it is essential to engineer green sensors capable of identifying explosive vapors at ambient temperature. Spider silk protein, which has shown promise in bioelectronic materials, could function as an eco-compatible sensory material for detecting the vapors of standard nitroaromatic explosives."
} | 2,029 |
28289730 | PMC5340862 | pmc | 1,291 | {
"abstract": "This study elucidates how a cyanobacterial primary producer acclimates to heterotrophic partnership by modulating the expression levels of key metabolic genes. Heterotrophic bacteria can indirectly regulate the physiology of the photoautotrophic primary producers, resulting in physiological changes identified here, such as increased intracellular ROS. Some of the interactions inferred from this model system represent putative principles of metabolic coupling in phototrophic-heterotrophic partnerships.",
"introduction": "INTRODUCTION Interspecies microbial interactions are controlled by the genome-encoded functions belonging to individual organisms and from their responses to environmental cues. Community-level responses are a function of all species, including those in low abundance, and comprehensive analyses require species-level resolution ( 1 ). Most microbial communities in nature are structurally and functionally complex, and it is technically challenging to make species-specific observations of behavior. Hence, model microbial consortia, maintained under controlled environments, are attractive for interrogating the principles by which multispecies interactions mediate the exchange of nutrients, vitamins/cofactors, and energy under different growth conditions and environmental constraints ( 2 – 6 ). Phototroph-heterotroph partnerships are essentially ubiquitous in photic environments and mediate key biogeochemical and ecological processes on a global scale ( 7 ). In this study, we employed a bottom-up approach to infer and test specific interactions occurring within a constructed binary consortium containing a unicellular cyanobacterium, Thermosynechococcus elongatus BP-1, and an obligate aerobic heterotroph, Meiothermus ruber strain A (here T. elongatus and M. ruber , respectively). T. elongatus is a thermophilic, unicellular cyanobacterium previously investigated in numerous ecophysiological and biotechnological studies ( 8 – 13 ). Its genome is well characterized ( 14 ) and was first isolated from a hot spring cyanobacterial mat environment near Beppu, Japan ( 15 ). M. ruber strain A is an aerobic, heterotrophic thermophile isolated from an enrichment culture of Synechococcus sp. strain JA-3-3-Ab, which was sampled from a cyanobacterial mat inhabiting the outflow of Octopus Spring in Yellowstone National Park (WY, USA) ( 16 , 17 ), and shares 98.6% nucleotide identity to the 16S rRNA gene of a closely related strain, Meiothermus ruber DSM 1279 ( 18 ). At the genome level, both M. ruber strains display substantial functional relatedness with regard to carbohydrate and energy metabolism, including genes for glycolysis, tricarboxylic acid cycle, oxidative pentose phosphate, Entner-Doudoroff, and aerobic respiratory electron transfer pathways ( 16 ). Similarly to M. ruber DSM 1279, strain A lacks an assimilatory nitrate reduction pathway; hence, it depends upon reduced N sources produced by T. elongatus when cocultured in minimal medium containing only nitrate. This consortium was constructed specifically to identify interactions underlying acclimation responses to heterotrophic partnership. Simplified consortia, such as the system presented here, are useful tools for studying microbial interactions at the species level. It is much more difficult to interrogate species-resolved responses to partnership in natural systems, in which membership cannot be controlled. Typically, such studies have invoked only bulk measurements of physiological or biochemical activities derived from the entire community or have examined subsets, focusing on only the dominant members ( 19 ). In this study, analyses were performed on both member species by interrogating transcriptional and physiological data associated with a commensal “producer-consumer” interaction ( 20 ). These data were collected across tightly controlled steady states maintained via discrete incident irradiance (I i ) and dissolved O 2 tension (pO 2 ) treatments. The strains were chosen because of an obligate dependency of M. ruber on cyanobacterium-derived carbon and nitrogen, when the consortium was grown in autotrophic minimal medium containing nitrate. These are representative thermophiles derived from hot spring cyanobacterial mats that are hallmark habitats for high solar I i and pO 2 that significantly influence microbial interactions and the ecosystem properties ( 21 – 25 ). We designed controlled cultivation experiments that compared axenic growth of T. elongatus to growth in the consortium and concluded that M. ruber acted as a commensal partner supported by direct metabolite exchange. We then hypothesized that T. elongatus sensed and acclimated to its partner and that this behavior represented indirect interspecies regulation where each species coordinated some transcriptional events in response to the other. We conclude that some of these behaviors that relate to the most foundational functions of life, such as carbon and energy acquisition, may represent generalizable principles for phototroph-heterotroph interactions that can occur in habitats subjected to a dynamic range of light and oxygen tensions.",
"discussion": "DISCUSSION The cyanobacterium T. elongatus responded to heterotrophic partnership with M. ruber by altering the expression of key functional genes. This primary result is evidence of indirect interspecies regulation. It is important to note that the turbidostat culturing platform provided a constant, optically thin, nutrient-replete environment. Hence, the addition of M. ruber to T. elongatus cultures did not alter the growth environment by reducing availability of actinic light or nutrients needed to support T. elongatus . The net specific rate of O 2 production decreased during binary cultivation compared to the T. elongatus axenic controls. These rates are functionally equivalent to net photosynthesis rates and account for the gross rate of oxygenic photosynthesis minus all oxygen-consuming reactions, including photorespiration (RuBisCO oxygenase activity) and heterotrophic respiration ( 29 , 30 ). The net photosynthesis rates are conservative interpretations for the lower bound of oxygenic photosynthesis and relatable as proxy measurements for the minimum consortium-wide energy acquisition rates, assuming 0.125 quanta absorbed and 2 NADPH produced per mole O 2 formed via PS II-mediated charge separation ( 31 ). Hence, the energy efficiency for biomass production is greater in the binary consortium than in the T. elongatus axenic control. These increases likely result from heterotrophic capture of reductant that would otherwise be lost from the system as either photosynthate or necromass. The addition of M. ruber partnership also resulted in an observed decrease in O 2 sensitivity compared to T. elongatus axenic controls ( Fig. 2 ). A decrease in sensitivity is equivalent to an increase in O 2 stress resistance. We note that this effect was observed under identical pO 2 treatments (binary versus axenic), which supported O 2 tensions sufficient to render the bulk effects resulting from heterotrophic O 2 removal as negligible. However, attachment or close cellular proximity of M. ruber to T. elongatus cells may create localized gradients and microheterogeneities in I i and pO 2 experienced by the T. elongatus population. Interactions that occur when cells from each species are in close contact could account for the observed differences in O 2 sensitivity and the photosynthetic quotients which were based on measurements taken from the well-mixed (bulk) volume. The M. ruber -induced decrease of O 2 sensitivity ( Fig. 2 ) originally led us to hypothesize that heterotrophic partnership reduced cyanobacterial oxidative stress and that this effect could be observed by comparing intracellular ROS-RNS between axenic and binary conditions. Interestingly, we found that heterotrophic partnership had the opposite effect and that increased pO 2 had no effect on intracellular ROS-RNS ( Fig. 4 ). However, the binary culture’s observed decrease in O 2 sensitivity did correspond to enrichment of genes within the functional category photosystem I high-light-stabilizing complex ( Fig. 3 ). The T. elongatus genes in this category include hliACD ( tsl2208 , tsr0446 , and tsr1916 ) and tsl0063 , annotated as a member of the CAB/ELIP/HLIP protein family, which are known to be stress-induced genes that help cyanobacteria cope with free radicals and excess excitation energy ( 32 , 33 ). The increases in ROS-RNS observed as a direct result of heterotrophic partnership corresponded with increased relative transcript abundances of T. elongatus genes required for mitigating ROS, showing that the cyanobacterium acclimates to heterotrophic partnership by increasing protection from oxidative stress ( Fig. 4 and 5 ). This is contrary to previous observations made in consortia constructed from oligotrophic cyanobacteria and heterotrophs, in which Prochlorococcus species have been reported to benefit and/or depend upon heterotrophic bacteria, such as Alteromonas -like species, to reduce oxidative stress ( 34 , 35 ). In contrast, evidence of cyanobacterium-mediated ROS mitigation was reported within the binary consortium of Synechococcus sp. strain PCC 7002 coupled with Shewanella putrefaciens W3-18-1, cultured under very different conditions than those employed in the current study ( 2 ). Both T. elongatus and Synechococcus sp. PCC 7002 were isolated from eutrophic environments (mat and marine sediment, respectively), which can presumably support higher levels of heterotrophic growth than oligotrophic marine environments. Cyanobacteria are equipped to detoxify intracellular ROS-RNS and mitigate oxidative stress, because ROS production is an inherent by-product of oxygenic photosynthesis and photosynthetic electron transfer ( 36 , 37 ), while heterotrophic bacteria are recognized for production of extracellular ROS ( 27 ). The principle that is inferred from these collective results is that some cyanobacteria, such as Synechococcus species adapted to eutrophic environments exposed to high irradiance, specialize in ROS-RNS mitigation ( 38 , 39 ). The metabolic dependency of M. ruber upon T. elongatus for reduced carbon, nitrogen, and certain vitamins (i.e., B 12 , biotin, and niacin) was corroborated through the coexpression of genes encoding enzymes that metabolize and transport shared metabolites. These inferences are made through the basic assumption that the coexpressed genes, i.e., correlated mRNA abundances between the two species, correspond to protein frequency and activity. Clustering the relative mRNA abundance profiles of the two organisms together provided the means to infer which specific metabolic exchanges are coordinated and how these interactions respond to I i and pO 2 . Specifically, the results suggest that multiple carbon compounds derived from the cyanobacterium could be exchanged and taken up by M. ruber . While evidence for the exchange of organic acids (e.g., acetate) was observed, polysaccharides, peptides, and EPS may have also supplied the carbon and reductant required to support stable M. ruber populations. Ample evidence also supports the likelihood that amino acids can serve as a source of reduced N (and possibly carbon) required by M. ruber . For example, the expression of genes involved in the synthesis, transport, and salvage of specific amino acids showed coordinated patterns shared by each species. Specifically, T. elongatus transcripts of methionine and glutamate biosynthesis genes clustered into groups that increased with µ (clusters D and G) while M. ruber homologs showed opposite patterns (clusters C and H), suggesting the specific exchange of these amino acids. The relative abundance profiles for M. ruber genes encoding vitamin B 12 -dependent methionine synthesis showed expression patterns in common with vitamin B 12 salvage and T. elongatus vitamin B 12 synthesis genes, indicating that one exchanged resource (e.g., vitamin B 12 ) may affect requirement of another exchangeable resource (e.g., methionine) that has a closely linked pathway. The collection of experimental results presented here clearly shows that the cyanobacterium responded and acclimated to heterotrophic partnership. In this experimental system, T. elongatus is either indirectly regulated by environmental changes instigated by M. ruber or directly regulated via molecular signals. The integrated kinetics- and global transcriptomics-based inferences were not targeted enough to capture a mechanism for direct interspecies regulation. Although direct interspecies regulation cannot be ruled out, our conclusion is that this heterotrophic partnership establishes an indirect interspecies regulation of gene expression resulting in measurable changes of growth and photosynthesis kinetics of the binary culture compared to the cyanobacterial axenic control. The outcomes described here can be generalized to understand microbial cyanobacterium-heterotroph interactions better ( Fig. 7 ). For instance, the cyanobacterium was inferred to sense the presence of its commensal heterotrophic partner and respond by altering its gene expression. Interspecies modulation of gene expression, via indirect regulation, is supported by results reported in previous studies that investigated very different cyanobacterium-heterotroph platforms ( 2 , 4 ), and a number of notable commonalities emerge. A previous study, investigating a consortium composed of cyanobacterium Synechococcus sp. PCC 7002 coupled with Shewanella putrefaciens W3-18-1 ( 2 ), reported a >2-fold change in mRNA abundances of cyanobacterial genes (compared to axenic) that encode enzymes belonging to the same functional groups that were statistically enriched from T. elongatus in the current study ( Fig. 3 ). These include some of the most notable examples, such as carbon concentration, carboxysome synthesis, PS II, oxidative phosphorylation, methionine metabolism, and Fe-S cluster biogenesis. Similarly to the results from this study, Synechococcus sp. PCC 7002 was also reported to show >2-fold changes in B 12 salvage processes when partnered with S. putrefaciens W3-18-1, although the current study investigated a cyanobacterial B 12 prototroph. Another study, which investigated the transcriptional responses of Synechococcus sp. WH8102 cocultured with Vibrio parahaemolyticus , also reported changes in expression of genes sharing the functions reported here. These include amino acid biosynthesis, cofactor biosynthesis, PS II, NAD(P)H-dehydrogenase, and ATPase. The functional similarities of cyanobacterial genes being influenced and potentially indirectly regulated by the activity of a heterotrophic partner are remarkable considering the difference in species, their origins, and the treatments and culturing platforms compared. Interspecies modulation of gene expression likely serves as a fundamental principle enabling microbial communities to coordinate their metabolism and coacclimate to each other and environmental cues. FIG 7 Schematic outline of responses to heterotrophic partnership observed and inferred as indirect interspecies regulation events and metabolic coupling."
} | 3,836 |
34878117 | PMC8691061 | pmc | 1,293 | {
"abstract": "Abstract Massive corals of the genus Porites , common, keystone reef builders in the Indo-Pacific Ocean, are distinguished by their relative stress tolerance and longevity. In order to identify genetic bases of these attributes, we sequenced the complete genome of a massive coral, Porites australiensis . We developed a genome assembly and gene models of comparable quality to those of other coral genomes. Proteome analysis identified 60 Porites skeletal matrix protein genes, all of which show significant similarities to genes from other corals and even to those from a sea anemone, which has no skeleton. Nonetheless, 30% of its skeletal matrix proteins were unique to Porites and were not present in the skeletons of other corals. Comparative genomic analyses showed that genes widely conserved among other organisms are selectively expanded in Porites . Specifically, comparisons of transcriptomic responses of P. australiensis and Acropora digitifera , a stress-sensitive coral, reveal significant differences in regard to genes that respond to increased water temperature, and some of the genes expanded exclusively in Porites may account for the different thermal tolerances of these corals. Taken together, widely shared genes may have given rise to unique biological characteristics of Porites , massive skeletons and stress tolerance.",
"conclusion": "Conclusions We sequenced the complete genome of P. australiensis with reasonable quality. We showed that homologs of all Porites skeletal matrix protein genes exist in other corals and anemones. Moreover, we revealed that conserved genes shared with other taxa may be selectively expanded in the Porites lineage and that these expanded genes include those that respond to diverse environmental stresses. This suggests that genes conserved among many organisms may have contributed significantly to distinctive Porites biological characters, their massive skeletons and high stress tolerance. Comparison of transcriptomic responses to changing environments using Porites and Acropora highlighted dynamic differences of their responses to environmental changes. Some genes expanded exclusively in Porites , including HSP20 and peroxidasin , respond to increased seawater temperature, possibly accounting for the different stress tolerances of these corals. The present genomic resources, together with other coral genomic data, will provide a powerful resource to understand the divergent ecology of reef-building corals as well as mechanisms of coral calcification.",
"introduction": "Introduction Coral reefs support the most diverse marine ecosystems on Earth ( Wilkinson 2008 ); however, they face a range of anthropogenic challenges, including ocean acidification, increasing seawater temperatures ( Hoegh-Guldberg et al. 2007 ), and deoxygenation ( Hughes et al. 2020 ). Tropical storms, predation by crown-of-thorns starfish, and coral bleaching, a breakdown of the mutualism between corals and their endosymbiotic photosynthetic algae, are major causes of coral reef decline ( De'ath et al. 2012 ). Bleaching, largely caused by increased seawater temperature, has been observed circumglobally with increasing frequency ( Hughes et al. 2017 ; Nakamura 2017 ). Because roughly 35% of all marine species depend upon coral reefs at some stage of their life cycles, loss of coral reefs also destroys the habitats of diverse marine species, making extensive loss of reef habitats one of the most pressing environmental issues of our time. Stony corals of the genus Porites are common, important reef builders in the Indo-Pacific Ocean, and massiveness and longevity are their distinguishing characters. Porites colonies that may have survived more than 400 years have been reported (e.g., Kawakubo et al. 2017 ). More than 80 named species and numerous unclassified forms have been identified in this genus ( Hoeksema and Cairns 2021 ). Porites species have thicker tissues and appear more robust to thermal stress than other corals, such as Acropora sp., which have thinner tissues (e.g., Loya et al. 2001 ). Thus, Porites corals have been used for comparative analyses of stress responses ( Fitt et al. 2009 ). Because of their massiveness and longevity, geochemical tracers called “proxies,” such as oxygen isotope ratios, strontium-calcium ratios, and heavy metal concentrations, in growth rings of CaCO 3 Porites skeleton have been used to monitor changes in sea surface temperature, salinity, and/or marine pollutants ( Shen et al. 1987 ; Beck et al. 1992 ; Gagan et al. 2000 ; Inoue and Tanimizu 2008 ). Seawater acidification reduces Porites calcification ( Anthony et al. 2008 ; Iguchi et al. 2012 ; Olde et al. 2015 ). Using coral calcification as an index, Porites taxa have been used to reconstruct past environmental changes so as to better understand tropical climate systems and to predict future climate change ( Cobb et al. 2003 ; Solomon et al. 2007 ). Recently, detailed geochemical studies on mechanisms of coral calcification have been conducted in order to investigate the validity of proxies and/or to improve the use of proxies ( Gagan et al. 2012 ; McCulloch et al. 2012 ; Hayashi et al. 2013 ); however, biological studies on Porites corals have been few in number compared with other coral taxa. Recent rapid accumulation of coral genomic data enables us to better understand molecular mechanisms underlying coral biology ( Shinzato et al. 2011 ; Prada et al. 2016 ; Voolstra et al. 2017 ; Cunning et al. 2018 ; Ying et al. 2018 , 2019 ; Helmkampf et al. 2019 ; Shumaker et al. 2019 ; Shinzato et al. 2021 ). Reef-building corals are diverse not only morphologically, but also physiologically and ecologically. Susceptibilities to bleaching vary among coral taxa ( Marshall and Baird 2000 ), and in warming sea temperatures, massive Porites became “winners,” increasing relative percent cover after a massive coral bleaching event caused coverage decreases of bleaching-sensitive taxa or “losers” ( Loya et al. 2001 ; van Woesik et al. 2011 ). Why are Porites corals stress-tolerant and how do they survive longer under adverse conditions? Although a Porites lutea genome was reported previously ( Robbins et al. 2019 ), that study focused only on possible genomic interactions between host corals, symbiotic algae, bacteria, and archaea. Molecular mechanisms underlying biological characteristics of Porites are largely unknown to date. In this study, we sequenced the complete genome of a common Porites species in Okinawa, Japan, Porites australiensis ( fig. 1 A ), and explored genomic features that might shed light on unique biological characters of Porite s, for example, stress tolerance and massive skeletons. Understanding genetic mechanisms underlying unique characters of Porites and comparing them with those of other coral taxa may facilitate predictions about whether and how coral reef ecosystems, which comprise multiple reef-building corals, can survive current global warming. Fig. 1. Genome sequencing of Porites australiensis . ( A ) Photo of a P. australiensis colony in Okinawa, Japan. ( B ) Spawning of a male colony of P. australiensis . Sperm can be observed on the surface of the colony. ( C ) A heatmap showing numbers of shared HOGs among anthozoans. Scleractinian species are shaded in blue. Porites is in red; Acropora species are in yellow. Robust coral species are in blue and corallimorpharians are in green. ( D ) Molecular phylogeny of anthozoans using 1,878 single-copy, orthologous genes (429,044 amino acids). All nodes are supported with 100% bootstrap support. ( E ) The cystathionine β-synthase (CBS) locus in the Porites genomes. The cysteine biosynthesis pathway is shown above, and the syntenic relationship around CBS in the P. australiensis , P. lutea , Acropora tenuis , and A. digitifera genomes is shown below. Genes are shown with arrows (arrow directions correspond to gene directions) and Porites CBS genes are shown as red arrows. Genes belonging to the same OG are connected by dotted lines.",
"discussion": "Discussion Conserved Genes May Contribute to Unique Characters of Massive Porites Massive Porites are regarded as stress-tolerant and long-lived, and a recent study showed that these corals have higher thermal tolerance and that they may acclimatize fast enough to keep pace with current global warming ( DeCarlo et al. 2019 ). We found that some conserved genes shared with other organisms are underwent duplication in the Porites lineage ( fig. 3 ). Interestingly, these expanded genes include those involved in environmental stress responses in a variety of animals, and involvement of these genes in environmental stress responses in corals has been suggested and investigated. Consistent with our finding that numbers of HSP20 genes in Porites genomes are larger than those of other corals, corallimorpharians, and sea anemones ( fig. 3 A ), Ying et al. (2018) reported that numbers of HSP20 genes in P. lutea , as well as in a Goniastrea genomes, are larger than those of Acropora corals and that different numbers of HSP20 genes may correlate with coral stress tolerance. Tyrosinases , or tyrosinase-type phenoloxidases are responsible for the immune response of the phenoloxidase pathway in invertebrates via melanin synthesis, and coral tyrosinase-type phenoloxidases respond to various environmental stressors, including heat stress, disease, pathogens, sedimentation, nutrient loading, and damage (Mydlarz et al. 2008 , 2009 ; Palmer et al. 2011 , 2012 ; Sheridan et al. 2014 ; van de Water et al. 2015 , 2018 ; Kelly et al. 2016 ; Wall et al. 2018 ; Dougan et al. 2020 ). Peroxidasin genes are involved in oxidative stress responses and are differentially expressed in corals under heat stress ( Voolstra et al. 2009 ; Barshis et al. 2013 ; Louis et al. 2017 ). Taken together, conserved environmental stress−response genes may contribute to the stress tolerance of massive Porites . Although gene expression of Porites -specific expanded tyrosinase genes was not affected by increased seawater temperature or increased light intensity, four out of seven expanded HSP20 genes and two out of six tandem-duplicated peroxidasin genes were upregulated by increased seawater temperature (four upregulated and one downregulated; fig. 3 ), suggesting that some Porites -specific expanded HSP20 and peroxidasin genes may be involved in its high-temperature response, but that tyrosinase genes serve other functions. Massive skeletons are unique to Porites corals. Sequence similarity searches revealed that a set of orthologs encoding nine SOMP s ( cadherin , neurexin , MAM and LDLr dcp , TSP1 and VWA dcp , SAARPs , and USOMP8 ) is shared among Porites , Acropora , and Stylophora ( fig. 2 B ; supplementary table 6 , Supplementary Material online ), suggesting that these functioned as basic SOMPs in the common ancestor of extant scleractinians. An acidic protein family (SAARPs) is commonly found in coral skeletons ( fig. 2 B ), indicating its essential role in coral biomineralization. Negatively charged side chains of aspartic acid residues may interact with calcium ions to regulate nucleation, inhibition, and orientation of calcium carbonate crystal growth ( Addadi and Weiner 1985 ; Albeck et al. 1993 ; Marin and Luquet 2007 ). In P. australiensis SOMP s, we identified novel acidic SOMP s that have CUB domains ( Pau-SAARP , supplementary table 4 , Supplementary Material online ), which may also act as calcium binding sites ( Blanc et al. 2007 ) and/or may interact with other proteins to construct the skeletal organic matrix. Other acidic SOMPs, skeletal acidic proteins, or SAPs that are present in Acropora skeletons ( Shinzato et al. 2011 ; Ramos-Silva et al. 2013 ) were not detected in Porites . This supports previous reports that SAP s are unique to Acropora species ( Shinzato et al. 2011 ; Takeuchi et al. 2016 ). In summary, our comparative study of Porites and other coral SOMP s highlights essential proteomic components for coral skeletal formation, such as cell membrane proteins and acidic proteins. Notably, all Porites SOMP genes have putative homologs in other corals and even in a sea anemone, which has no skeleton ( fig. 2 C ; supplementary table 3 , Supplementary Material online ). In particular, domain architectures of three cell membrane SOMP s ( cadherin , neurexin , and MAM and LDLr dcp ) are well conserved between Porites and Nematostella ( fig. 2 D ), suggesting that these proteins originally functioned in cell adhesion, attaching ancestors of these organisms to the substrate. Taken together, most SOMP genes existed in the ancestor of scleractinians and anemones, dating back about 500 Ma ( Shinzato et al. 2011 ), and were co-opted for coral skeleton formation in the scleractinian lineage ( Takeuchi et al. 2016 ). Different Molecular Responses of Acropora and Porites to Increased Temperature May Reflect Their Divergent Stress Tolerance Because of their algal endosymbionts, light is important to maintain coral health. Light-enhanced calcification of reef-building corals is a well-known phenomenon ( Cohen et al. 2016 ). However, in this study, expression of very few genes was affected by increased light intensity in either Porites or Acropora ( fig. 4 A ; supplementary table 7 , Supplementary Material online ), indicating that host corals show no universal molecular response to increased irradiation and that increased light intensity has a limited impact on either coral host. The small number of DEGs that responded to increased irradiation, which did not include SOMP s, is consistent with a previous experiment using symbiotic and apo-symbiotic coral polyps, showing that light-enhanced coral calcification could be caused by increased pH of the calcifying fluid induced by algal photosynthesis, rather than by the increase of symbiont photosynthetic products supplied to host corals ( Inoue et al. 2018 ). Nevertheless, HLF transcription factors are the only genes that were commonly upregulated in both Porites and Acropora ( fig. 4 A ; supplementary table 7 , Supplementary Material online ). Although the function of HLF genes in corals is unclear, HLF transcription factors regulate expression of apoptotic and circadian clock genes ( Waters et al. 2013 ; Takahashi 2017 ), suggesting that increased light may affect circadian rhythm of Porites and Acropora , although no expression changes of apoptotic and circadian clock genes were detected in this study. Among the 2,300 SC-HOGs differentially expressed in response to increased seawater temperature, 16% (389) were differentially expressed in both Porites and Acropora , and 29% (702) and 53% (1,209) were exclusive to Porites and Acropora , respectively ( fig. 4 A ). Upregulation of protein biosynthesis, DNA replication, DNA damage, and cell cycle genes were observed in Porites , but not in SC-HOGs solely in Acropora , indicating that Porites actively reacts to higher temperatures at the cellular level and that these mechanisms may contribute to its stress tolerance. Another interesting point is that expression patterns of some transcription factors, controlling expression of numerous downstream genes and affecting various biological processes, were reversed in Porites and Acropora under increased seawater temperature ( fig. 4 B ). Maf transcription factors are involved in cellular responses against oxidants and heavy metals ( Suzuki et al. 2001 ; Bensellam et al. 2015 ). These transcription factor genes may reveal the diversity of molecular responses of corals to environmental changes. FPs are thought to serve multiple functions in corals, including maintenance of obligate symbioses with dinoflagellates, quenching of oxygen radicals, and stress responses (e.g., Bou-Abdallah et al. 2006 ; Dove et al. 2001 ; Kawaguti 1969 ; Matz et al. 2002 ; Rodriguez-Lanetty et al. 2009 ; Salih et al. 2000 ; Seneca et al. 2010 ). Corals possess three FPs [cyan (CFP), green (GFP), and red (RFP)], and nonfluorescent blue/purple chromoprotein ( Kelmanson and Matz 2003 ; Field et al. 2006 ). Expression of coral FP genes is affected by external stimuli, such as light, heat, and injury ( D’Angelo et al. 2008 , 2012 ; Rodriguez-Lanetty et al. 2009 ; Roth et al. 2010 ; Seneca et al. 2010 ; DeSalvo et al. 2012 ; Roth and Deheyn 2013 ). Chromoproteins exhibit higher absorption and lower emission ( Matz et al. 2002 ; Bou-Abdallah et al. 2006 ) and may have higher antioxidant activity than FPs ( Palmer et al. 2009 ). Although it has been reported that expression of a chromoprotein in Porites astreoides was upregulated by heat stress ( Kenkel et al. 2011 ), in this study, all differentially expressed chromoprotein genes were downregulated under increased temperature ( fig. 4 C ). Although it could be that seawater temperature in this study was not increased enough to induce upregulation of chromoprotein genes, their functions in Porites may be more diverse, for example, maintenance of homeostasis. Studying functions of chromoproteins and FPs in corals should enable greater understanding of coral biology. Conclusions We sequenced the complete genome of P. australiensis with reasonable quality. We showed that homologs of all Porites skeletal matrix protein genes exist in other corals and anemones. Moreover, we revealed that conserved genes shared with other taxa may be selectively expanded in the Porites lineage and that these expanded genes include those that respond to diverse environmental stresses. This suggests that genes conserved among many organisms may have contributed significantly to distinctive Porites biological characters, their massive skeletons and high stress tolerance. Comparison of transcriptomic responses to changing environments using Porites and Acropora highlighted dynamic differences of their responses to environmental changes. Some genes expanded exclusively in Porites , including HSP20 and peroxidasin , respond to increased seawater temperature, possibly accounting for the different stress tolerances of these corals. The present genomic resources, together with other coral genomic data, will provide a powerful resource to understand the divergent ecology of reef-building corals as well as mechanisms of coral calcification."
} | 4,626 |
38027382 | PMC10666214 | pmc | 1,294 | {
"abstract": "Rheological and mechanical comparative tests of the new\nAquaSun\nantifouling sol–gel coating coated on shipbuilding steel compared\nto a commercial silyl acrylate antifouling top coat containing cuprous\noxide and copper pyrithione show further evidence of the practical\nviability of this multifunctional coating for the protection of the\nimmersed surfaces from biofouling. AquaSun is a less rigid or less\nviscous material than commercial top coat but more adherent to the\nsteel substrate. These results support further investigation of this\nmultifunctional sol–gel coating as an eco-friendly antifouling\npaint.",
"conclusion": "4 Outlook and Conclusions The results\nof the first rheological and mechanical comparative\nanalyses carried out on the new AquaSun antifouling sol–gel\ncoating clearly show that AquaSun is a less rigid and less viscous\nmaterial than a state-of-the-art commercial antifouling top coat but\nsubstantially more adherent to shipbuilding steel substrate. The reason\nis linked to its lower viscosity and lower stiffness thanks to which\nthe glassy organosilica sol containing plentiful Si–OH groups\nis able to chemically bind to the Fe–OH groups at the steel\nsurface eventually affording a strongly cohesive thin film. 22 Such a thin film is ideally suited to coat and\nprotect the outer steel surface not only from corrosion 23 but also from biofouling. Involving rapid\nmicrobial surface colonization followed by biofilm\ndevelopment and eventually attachment of large and hard marine organisms, 24 marine biofouling of submerged objects such\nas boat or ship hulls and pier pylons is a biological colonization\nprocess causing significant economic losses worldwide. The new photocatalytic\nAquaSun coating combines the foul release properties of the organosilica\nwith the photocatalytic generation of H 2 O 2 and\nhydroxyl radicals driven by sunlight that prevent microbial colonization\nand biofilm deposition. 12 , 13 The powerful biocidal\nhydrogen peroxide generated in situ readily decomposes\ninto O 2 and H 2 O eventually posing no harm to\nthe marine environment. 25 A “triple\nbottom line” sustainability analysis of\nAquaSun production and commercial uptake recently concluded that the\ntechnology has significant potential toward replacing conventional\nantifouling coatings with a single product of broad applicability. 26 Besides proof of prolonged activity first in\ncoated surfaces at sea, 15 and then in real\nvessels and offshore platforms in open marine waters, what is required\nfor practical utilization of this new coating are good rheological\nand mechanical properties. The outcomes of this work, thus, contribute\nan additional important step toward practical utilization of this\nnew eco-friendly antifouling coating. Further applications of AquaSun\nagainst biofouling on different surfaces in contact with water or\nmoisture can be anticipated.",
"introduction": "1 Introduction Today chiefly based on\n“self-polishing” copolymer\npaints containing cuprous oxide (Cu 2 O) as the main biocide\noften in combination with other biocidal species to broaden the spectrum\nof action against the widely different organisms (barnacles, mussels,\nalgae, dog teeth, etc.) comprising marine biofouling, antifouling\n(AF) paints are applied to commercial and recreational vessels at\n100,000 t/a yearly rate. 1 , 2 Over 3–5 years,\nthe AF coating applied to the vessel’s hull releases all Cu + and booster biocides into seawater significantly impacting\nmarine life including coastal macrofouling communities. 3 , 4 The leached biocides, indeed, are poorly biodegradable and therefore\nremain in marine sediments for a long time, harming the aquatic environment. 5 − 7 Numerous new “green” commercial AF paints exist. 7 , 8 Yet, most of them are significantly more expensive than conventional\nbiocidal antifouling coatings. 9 , 7 Xerogels of organically\nmodified silica (ORMOSIL) are the most recently commercialized eco-friendly\nfoul release (FR) coatings. 10 Likewise\nto much thicker silicone-based FR coatings, these top coats act by\nminimizing the surface energy of the protected hull, thereby reducing\nthe initial stages of fouling development and easing the removal of\nthe fouling network that accumulates during the vessel motion. 11 Unfortunately, these biocide-free FR coatings\nexert little antifouling function when the vessel is stationary, such\nas in port waters or during idling, and generally underperform in\nwarm marine waters with water temperatures above 25 °C. AquaSun is a new ORMOSIL-based antifouling coating functionalized\nwith flower-like microparticles of visible-light photocatalyst Bi 2 WO 6 , which merges the solar-driven photocatalytic\ngeneration of powerful oxidizing species H 2 O 2 and hydroxyl radicals that readily degrade biomolecules and microbiological\nspecies, with the FR properties of conventional ORMOSIL xerogels. 12 , 13 Composed of a thin ORMOSIL film encapsulating the aforementioned\nvisible-light photocatalyst, the coating also shows high strength\nof adhesion to real ship steel substrates and complete lack of ecotoxicity. 14 Recent comparative tests carried out for 3 months,\nfurthermore, unveiled the AF activity of AquaSun even in highly polluted\nport seawaters for prolonged time under stationary condition of the\ncoated shipbuilding steel substrates. 15 To further demonstrate the practical applicability of this\nnew\nmultifunctional (AF/FR) coating, in this study, we report the outcomes\nof rheological (through dynamic stress sweep test, amplitude sweep\ntest, and temperature sweep tests) and mechanical (through cross-cut\ntest and pull-off test) characterization aimed at evaluating the adhesive\nand rheological properties of the AquaSun top coat compared to a commercial\ntop coat. Adhesion to shipbuilding steel is a crucial feature for\nthe effectiveness of both FR and AF paints. The rheological properties\nof paints and coatings, in turn, crucially impact the application\nand subsequent behavior of paints. To ensure optimal deposition and\navoid sagging or casting, for example, the rheological parameter of\nviscosity should be of intermediate value, namely, not too high nor\ntoo low. 16 , 17 Knowledge of the rheological behavior of\na coating at different shear rates, furthermore, is important for\nthe design of the equipment required for the application of such coatings. 18 − 20",
"discussion": "3 Results and Discussion 3.1 Evaluation of the Rheological Features of\nthe Coatings Displaying the loss ( G ″,\nred curve) and conservative ( G ′, black curve)\nmodulus vs temperature curves for the commercial antifouling (CT,\na) and the AquaSun (b) coatings, Figure 1 clearly shows the crossing point of each\npair of curves defining the point where the resins cross-link. Figure 1 Thermal behavior\nof loss ( G ″) and conservative\n( G ′) moduli of SeaQuantum Ultra S commercial\n(CT, a) and AquaSun (b) coatings. The crossing point decreases from 146 °C for\nthe commercial\ntop coat to 105 °C for the AquaSun sol–gel coating. This\nshows evidence that the commercial resin cross-links at significantly\nhigher temperatures because of its higher structural complexity compared\nto the AquaSun organosilica layer which cross-links at temperatures\nslightly exceeding 100 °C. Revealing the organic polymer\nnature of the commercial top coat,\nits elastic conservative G ′ modulus is more\nthan 3 orders of magnitude higher than that of AquaSun consisting\nof a glassy ORMOSIL. The higher structural complexity of the commercial\ntop coat compared to the experimental sol–gel coating is confirmed\nby the complex viscosity (η*) of the three coatings shown in Figure 2 . Figure 2 Thermal behavior of the\ncomplex viscosity (η*) of SeaQuantum\nUltra S commercial (CT) and AquaSun coatings. Below 100 °C, the value of η* of the\ncommercial coating\nis about 7 × 10 6 mPa x s, while that of the AquaSun\ncoating is more than 3 orders of magnitude lower (∼1400 mPa\nx s for AquaSun). The gel point, i.e., the temperature at which exponential\ngrowth of viscosity is observed as the resin begins to cross-link,\noccurs at 103 °C, whereas it shifts to 146 °C for the commercial\ntop coat. The rheological behavior of the top coats (both the\ncommercial\norganic polymer and AquaSun) was studied at different temperatures.\nThe graphs in Figure 3 show the shear stress vs shear strain curves of the top coats at\n25, 30, 40, 50, and 75 °C at different strain rates. The curves\nin Figure 3 a, 3 b reveal rigid plastic materials. In detail, the\ncurves in Figure 3 a,\ncloser to each other, show that the rheological behavior of the commercial\npolymeric coating CT is more stable when increasing the temperature\ncompared to the organosilica thin film comprising the AquaSun coating.\nThe latter retains good mechanical performance up to 50 °C. At\n75 °C, the CT coating has a strikingly different behavior when\ncompared to AquaSun, with the shear stress increasing, rather than\ndecreasing, and eventually reaching the highest value amid all thermal\nconditions tested. Figure 3 Shear stress vs shear strain curves of SeaQuantum Ultra\nS commercial\n(CT, a) and AquaSun (b) coatings in the 25–75 °C temperature\nrange. This behavior is likely due to the complete evaporation\nand removal\nof the solvent from the CT layer, leaving a rigid top coat that completely\nlost its initial elasticity. Indeed, after the rheological test, the\nCT polymer film (deposited on the rheometer plate) appeared with cracks\nand internally split, showing evidence of lost homogeneity. On the\ncontrary, the robust AquaSun hybrid glassy coating retained its ductility\neven at the highest temperature tested (75 °C). Figure 4 , furthermore,\ncompares the shear stress of AquaSun (containing the photocatalyst\nBi 2 WO 6 ) with the shear stress of CT coating\nat 75 °C. The curves show that the shear stress at the high\nshear rate of 1000 s −1 , changes by about 1 order\nof magnitude, going from about 2200 mPa s for the commercial coating\nto 195 mPa s for the AquaSun top coat. Similarly, in Figure 5 the viscosity curves confirm\nthe trend of the shear stress because the viscosity of the CT increases\nwith the temperature whereas that of AquaSun decreases. At 75 °C\nthe viscosity of CT at the shear rate of 1000 s −1 is about 2 mPa s while that of AquaSun is about 0.2 mPa s, according\nto data in Figure 3 . This shows evidence that the AquaSun coating has a lower viscosity\nand is significantly softer when compared to CT reference coating. Figure 4 Shear\nstress vs shear strain of SeaQuantum Ultra S commercial (CT)\nand AquaSun coatings at 75 °C. Figure 5 Viscosity vs shear strain of commercial SeaQuantum Ultra\nS commercial\n(CT, a) and AquaSun (c) coatings at different temperatures within\nthe 25–75 °C range. 3.2 Evaluation of the Adhesion Power of the Coatings The outcomes of the cross-cut and pull-off mechanical tests used\nto evaluate the adhesion power of the coatings are displayed in Figure 6 . The optical microscopy\nphotographs therein suggest a different morphology of the reference\nsample (CT), which is opaque compared to the glossy appearance of\nthe AquaSun vitreous coatings. Figure 6 Optical microscopy photographs of the\ncross-cut test grid in commercial\nSeaQuantum Ultra S (a) and AquaSun (b) coatings at 50× (c, d)\nand 400× (e, f) magnification. To better observe the effects of adhesion strength\non the metallic\nsubstrate, optical microscopic photographs of the cut area were taken\nat 50× and 400× magnification on each sample. The CT reference\nsample showed a grid in which the cutting edge descends to the bottom\nof the coatings, unveiling the gray color of the primer, while the\ntie coat is distributed on the lateral sides of each groove left by\nthe cutter. On the other hand, the lateral redistribution of the antifouling\ntop coat was less visible in the substrate coated with AquaSun where\nthe gray primer substrate was significantly less evident. Hence, it\nmay be concluded that the AquaSun top coat has a better adhesive power\nthan the commercial top coat. The stress–strain curves of the\nadhesive adhesion power of AqauSun and the commercial finish in Figure 7 d showing the outcomes\nof the pull-off adhesion test clearly reveal the substantially stronger\nadhesion of the AquaSun sol–gel coating in comparison to the\npolymeric commercial antifouling paint. Figure 7 Pull-off test: fixing\nphase of the dolly in the dynamometer (a);\nimages of the metal specimen and the dolly before and after the pull-off\ntest for AquaSun (b, c) sample; stress/strain curves of SeaQuantum\nUltra S commercial (CT) and AquaSun coatings (d). Visual examination of the relevant adhesion area\nfor each coating\nafter the rupture of the adhesive layer between the coating and the\ncoated dolly also clearly reveals that AquaSun exhibits the highest\nmechanical adhesion ( Figure 7 c). The main mechanical parameters for the commercial and\nAquaSun coatings are listed in Table 1 . Table 1 Mechanical Parameters of Commercial\nSeaQuantum Ultra S (CT) and AquaSun Coatings sample E (MPa) σr (MPa) εr (%) Lr (N) W r (J) CT 29.98 ± 1.08 0.14 ± 0.07 0.75 ± 0.05 9.75 ± 0.52 0.0004 ± 0.0001 AquaSun 130.42 ± 1.61 0.81 ± 0.05 0.75 ± 0.08 61.76 ± 0.57 0.0022 ± 0.0001 Statistical analysis confirmed that the mechanical\nparameters of\nthe pull-off test of the coatings were statistically highly significant\nfor all samples ( p < 0.0001). As mentioned above,\nthe AquaSun top coat showed better adhesion than the commercial coating.\nIn detail, the commercial paint showed a modest percentage elongation\n(εr% = 0.75) reaching the yield point, and therefore plastic\ndeformation, with a stress of only 0.14 MPa ( p <\n0.0001). The AquaSun coating had the same percentage of deformation\nat break (εr% = 0.75) but at a tensile strength of 0.81 MPa\n( p < 0.0001), namely, which is reflected in a\nwork at break enhancement growing from ∼9 N for the commercial\npaint to ∼61 N ( p < 0.0001) for the AquaSun\nsol–gel coating. Finally, the Young’s modulus improved\nby more than 4 times, going from ∼30 MPa for the commercial\npolymeric antifouling paint to ∼130 MPa ( p < 0.0001) for the AquaSun coating."
} | 3,515 |
39404300 | PMC11477948 | pmc | 1,295 | {
"abstract": "The traditional computer with von Neumann architecture has the characteristics of separate storage and computing units, which leads to sizeable time and energy consumption in the process of data transmission, which is also the famous “von Neumann storage wall” problem. Inspired by neural synapses, neuromorphic computing has emerged as a promising solution to address the von Neumann problem due to its excellent adaptive learning and parallel capabilities. Notably, in 2016, researchers integrated light into neuromorphic computing, which inspired the extensive exploration of optoelectronic and all-optical synaptic devices. These optical synaptic devices offer obvious advantages over traditional all-electric synaptic devices, including a wider bandwidth and lower latency. This review provides an overview of the research background on optoelectronic and all-optical devices, discusses their implementation principles in different scenarios, presents their application scenarios, and concludes with prospects for future developments.",
"introduction": "1. Introduction Traditional computers have had extraordinary achievements. AlphaGo, a “deep thinking” Go robot developed by Google, won the game against the world-famous player Lee Sedol in 2016, becoming the first robot to defeat the world champion of Go since IBM Deep Blue defeated Kasparov in 1997 [ 1 ]. Since then, artificial intelligence has gained more attention. However, the traditional von Neumann computer architecture has hindered its development speed. The fundamental principles of von Neumann architecture have remained unchanged until John von Neumann introduced the concept of stored programs in 1952 at the Institute for Advanced Study Machine [ 2 ]. Presently, CPU processing speeds significantly surpass memory access speeds, resulting in CPUs idling while waiting for data retrieval. Furthermore, this segregation between storage and computation structures also contributes to substantial energy consumption [ 3 ]. Nevertheless, with the emergence of the Internet of Things (IoT), traditional computers face increasingly daunting challenges posed by storage and power consumption bottlenecks inherent in von Neumann architecture [ 4 ]. In contrast, the human brain is arguably the most sophisticated system on Earth [ 5 ], excelling in processing diverse analog signals and integrating them into coherent images, storing certain memories for decades, and exhibiting remarkable reasoning capabilities [ 6 ]. It is worth mentioning that these functions only necessitate approximately 20 W of energy [ 7 , 8 ], which is roughly one-tenth of what a typical desktop computer consumes. With around 10 11 neurons and 10 15 synapses [ 9 ], the brain forms an incredibly intricate yet efficient network [ 10 ]. Neurons communicate through synapses, where neurotransmitters are released when signal strength surpasses a threshold, carrying vital information [ 11 ]. This process is shown in Figure 1 a. The transmission strength between synapses relies on synaptic weights or connection strengths [ 12 ], with synapses themselves displaying plasticity to enable changes in synaptic weights to occur [ 13 , 14 ]. This unique phenomenon is absent in the conventional memory system. Drawing inspiration from this, numerous researchers have endeavored to develop artificial neurons that mimic information transmission processes within the brain ( Figure 1 b). Using traditional CMOS technology will require multiple comparators and capacitors. Nonetheless, high-value capacitors are costly in standard CMOS processes [ 15 ], and comparators occupy substantial area space. Therefore, CMOS devices do not offer advantages in terms of energy efficiency or scalability [ 16 ] because CMOS devices were not originally developed to simulate neurons. Figure 1 c depicts an ideal model where just one unit can emulate a neuron; such an advancement would be groundbreaking, both in terms of power consumption and spatial coverage. The pursuit of achieving the large-scale deployment of neural morphologies necessitates the collaborative efforts of synapse devices, axon devices, and dendrite devices. Currently, there exist silicon-based CMOS analog synapses, exemplified by IBM’s TrueNorth chip [ 17 ] and Intel’s Loihi chip [ 18 ]. In recent years, there has been a proliferation of neuromorphic computing devices, such as various three-terminal transistors and two-terminal memristors [ 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 ], capable of achieving in-memory computation. This capability is particularly advantageous for overcoming the von Neumann memory wall. By applying different stimuli to these devices, they exhibit diverse responses that resemble real neural synapses, thus earning the designation of artificial neural synapses. The strength of connections between synapses can be quantified by measuring the conductivity between devices [ 28 , 29 , 30 ]. These artificial synapses offer promising hardware foundations for the advancement of neuromorphic computing chips. However, most existing artificial synapses primarily rely on electrical stimulation, which inevitably imposes limitations on their operational speed and bandwidth due to inherent device constraints [ 31 , 32 , 33 , 34 , 35 ]. Introducing light as a stimulus presents an effective solution to this predicament since light boasts high bandwidth, low crosstalk, low power consumption, and no RC delay [ 33 , 36 , 37 ]. Figure 1 d is an example that demonstrates the device’s response to light by overlaying different functional layers. A superior artificial synapse should not only accurately simulate synaptic behavior, but also possess characteristics such as low power consumption, low operating voltage, excellent durability, linear conductivity rise and fall, and good symmetry [ 38 , 39 , 40 , 41 ]. These requirements also apply to optoelectronic synapses and all-optical control synapses, presenting challenges in material selection and coordination among different functional layers.\n Figure 1 ( a ) Diagram of neurons and synapses. Spike signals are produced by postsynaptic neurons upon the integration of an adequate amount of signals from synapses. Schematic diagram of ( b ) CMOS artificial neuron circuits and ( c ) artificial neuron devices [ 12 ]. ( d ) An example of an artificial all-optical synapse [ 42 ]. In recent years, more and more researchers have tried to introduce light into artificial synapses. These artificial synapses involving light stimulation can be classified into two categories: optoelectronic artificial synapses and all-optical artificial synapses. For the former, excitatory synapses are elicited by light, while inhibitory synapses still require electrical pulse stimulation [ 43 , 44 , 45 ]. For the latter, both excitatory and inhibitory synapses can be elicited by light. Recently, numerous all-optical artificial synapses have emerged, for instance, those employing IGZO/SnO/SnS heterostructure [ 46 ], Ag-TiO 2 nanoclusters/sodium alginate film [ 47 ], photochromic perovskites [ 48 ], and phase change material [ 49 ]. The all-optical synapse can fully exploit the advantages of light because there is no involvement of electrical stimulation. Compared with the optoelectronic synapse that requires a combination of light and electrical stimulation, the operation of the all-optical synapse is simpler, as the experimenter does not need to consider too many issues of coordinating light and electricity. In the all-optical synapse, a suitable small voltage bias is usually applied to both ends of the device (many articles refer to this as the read voltage), and the subsequent operation will not involve any electrical components. Currently, there have been studies that suggest this separation operation model can reduce device power consumption, minimize the damage caused by Joule heat to the device microstructure, and help to solve the issue of device stability [ 43 ]. In view of the many related papers published in recent years, it is necessary to summarize these optical bio-inspired synaptic devices, explore the physical explanations behind the synaptic functions that these devices can achieve, and explain their practical applications. This review mainly summarizes the recent research results of optoelectronic synapses and all-optical synaptic devices, along with their principles. Section 3 is about optoelectronic artificial synapses and Section 4 is about all-optical artificial synapses, followed by materials ( Section 5 ), applications ( Section 6 ), and future challenges ( Section 7 ), and the second chapter will introduce some basic knowledge about neural synapses and how they are manifested in devices. As mentioned earlier, all-optical artificial synapses have more advantages compared to optoelectronic artificial synapses, and considering the lack of comprehensive reviews on all-optical artificial synapses at present, this article will focus more on introducing all-optical artificial synapses. This review will help researchers who are about to engage in artificial synapses to understand this field more efficiently. At the same time, it helps researchers who have carried out research in this field by summarizing findings and inspiring them."
} | 2,314 |
34409139 | PMC8361290 | pmc | 1,296 | {
"abstract": "This research data set contains data related to experimental dataset on the effect of the electron acceptors in energy generation from brewery wastewater via a microbial fuel cell. The presented data gives information on the generation of electricity and waste minimization as various electron acceptors adopted in microbial fuel cells. Dual-chamber microbial fuel cell (MFC) system was assembled with aluminium mesh electrode as an anode and sulfonated tetrafluoroethylene membrane for proton exchange as a cathode at 500–2000 mg/L chemical oxygen demand (COD). A 0.4 and 0.6 M of Potassium permanganate (KMnO 4 ) and potassium cyanide K 3 [Fe(CN) 6 were used anaerobically as a mediator for electron acceptor in the cathode chamber. Furher more, The pH, COD, total nitrogen, biochemical oxygen demand, total phosphorous, total suspended solid and electrical conductivity for the raw brewery wastewater were measured. Inaddition, the voltage generated and the current density have been obtained for both (KMnO 4 ) and K 3 [Fe(CN) 6 electron acceptors. Moreover, the COD removal efficiency, Columbic efficiency, voltage generation, current, and power density were measured."
} | 293 |
35604161 | PMC9241726 | pmc | 1,297 | {
"abstract": "ABSTRACT In the opportunistic pathogen Pseudomonas aeruginosa , many virulence traits are finely regulated by quorum sensing (QS), an intercellular communication system that allows the cells of a population to coordinate gene expression in response to cell density. The key aspects underlying the functionality of the complex regulatory network governing QS in P. aeruginosa are still poorly understood, including the interplay between the effector protein PqsE and the transcriptional regulator RhlR in controlling the QS regulon. Different studies have focused on the characterization of PqsE- and RhlR-controlled genes in genetic backgrounds in which RhlR activity can be modulated by PqsE and pqsE expression is controlled by RhlR, thus hampering identification of the distinct regulons controlled by PqsE and RhlR. In this study, a P. aeruginosa PAO1 mutant strain with deletion of multiple QS elements and inducible expression of pqsE and/or rhlR was generated and validated. Transcriptomic analyses performed on this genetic background allowed us to unambiguously define the regulons controlled by PqsE and RhlR when produced alone or in combination. Transcriptomic data were validated via reverse transcription-quantitative PCR (RT-qPCR) and transcriptional fusions. Overall, our results showed that PqsE has a negligible effect on the P. aeruginosa transcriptome in the absence of RhlR, and that multiple RhlR subregulons exist with distinct dependency on PqsE. Overall, this study contributes to untangling the regulatory link between the pqs and rhl QS systems mediated by PqsE and RhlR and clarifying the impact of these QS elements on the P. aeruginosa transcriptome. IMPORTANCE The ability of Pseudomonas aeruginosa to cause difficult-to-treat infections relies on its capacity to fine-tune the expression of multiple virulence traits via the las , rhl , and pqs QS systems. Both the pqs effector protein PqsE and the rhl transcriptional regulator RhlR are required for full production of key virulence factors in vitro and pathogenicity in vivo . While it is known that PqsE can stimulate the ability of RhlR to control some virulence factors, no data are available to allow clear discrimination of the PqsE and RhlR regulons. The data produced in this study demonstrate that PqsE mainly impacts the P. aeruginosa transcriptome via an RhlR-dependent pathway and splits the RhlR regulon into PqsE-dependent and PqsE-independent subregulons. Besides contributing to untangling of the complex QS network of P. aeruginosa , our data confirm that both PqsE and RhlR are suitable targets for the development of antivirulence drugs.",
"introduction": "INTRODUCTION Quorum sensing (QS) is a cell-to-cell communication system based on the production, secretion, and perception of signal molecules. QS enables bacterial cells to behave as a community, coordinating gene expression and the display of related phenotypes at the population level depending on cell density and environmental cues. QS networks are widespread in bacteria, driving essential traits for pathogenicity such as the production of virulence factors, biofilm formation, group motility, and antibiotic resistance ( 1 – 3 ). The Gram-negative human pathogen Pseudomonas aeruginosa is considered a model organism for QS and quorum-quenching studies. P. aeruginosa possesses a sophisticated QS network consisting of three main interacting systems which, overall, control over 10% of the P. aeruginosa genome. P. aeruginosa QS plays a crucial role in biofilm formation and the regulation of multiple virulence factors, including pyocyanin, rhamnolipids, hydrogen cyanide, LasB elastase, LasA protease, and LecA and LecB lectins ( 3 , 4 ). Consequently, QS interference is considered a promising strategy for reducing P. aeruginosa pathogenicity ( 5 – 9 ). P. aeruginosa has two N -acyl homoserine lactone (AHL)-dependent QS circuits, namely, the las and rhl systems, based on the LasR and RhlR transcriptional regulators activated by N -3-oxo-dodecanoyl-homoserine lactone (3OC 12 -HSL) and N -butanoyl-homoserine lactone (C 4 -HSL) signal molecules, respectively. The synthesis of 3OC 12 -HSL and C 4 -HSL is directed by the LasI and RhlI synthases, respectively. Once activated, LasR and RhlR regulate the transcription of multiple target genes ( 2 ). A third QS system, pqs , uses the 2-alkyl-4-quinolones (AQs) molecules 2-heptyl-3-hydroxy-4-quinolone (also known as the Pseudomonas quinolone signal, PQS) and 2-heptyl-4-hydroxyquinoline (HHQ) as QS signals. HHQ synthesis requires the enzymes encoded by the first four genes of the pqsABCDE - phnAB operon. The PqsH monooxygenase, encoded by the pqsH gene, converts HHQ to PQS. Both HHQ and PQS bind to and activate the transcriptional regulator PqsR ( 10 – 11 ). Unlike LasR and RhlR, activated PqsR does not act as a global regulator, but mainly promotes transcription of the pqsABCDE-phnAB operon by activating the P pqsA promoter ( 12 ). This autoregulatory loop results in the amplified synthesis of AQs and increased production of the effector protein PqsE, encoded by the fifth gene of the pqsABCDE-phnAB operon. Despite the fact that PqsE is required for full virulence in P. aeruginosa ( 13 – 15 ), its mechanism of action has not yet been clarified. Structural studies revealed that PqsE has a typical metallo-β-lactamase fold, without obvious DNA-binding motifs ( 16 ). PqsE has thioesterase activity involved in the hydrolysis of 2-aminobenzoyl-acetyl-CoA (2-ABA-CoA) to 2-aminobenzoyl-acetate (2-ABA), an intermediate of HHQ and PQS synthesis ( 17 ). However, HHQ and PQS levels are unaltered in P. aeruginosa \n pqsE -deletion mutants relative to those in their isogenic wild-type strains, as other thioesterases can substitute for PqsE activity ( 14 , 17 , 18 ). Intriguingly, mutations in its catalytic site and inhibitors of its thioesterase activity do not inhibit the ability of PqsE to promote the expression of virulence genes, such as those involved in pyocyanin and rhamnolipid production, indicating that PqsE is a multifunctional protein ( 19 – 23 ). Different studies have shown that PqsE-dependent control of these virulence factors requires RhlR ( 12 , 13 , 24 – 27 ). Furthermore, deletion of either pqsE or rhlR in P. aeruginosa causes a strong attenuation of virulence in different plant and animal infection models ( 12 – 15 , 28 , 29 ). Great effort has been directed towards uncovering the mechanism(s) by which PqsE and RhlR impact the regulation of common target genes. It has been demonstrated that the RhlR/C 4 -HSL complex can trigger gene transcription in the absence of PqsE ( 26 , 30 ) and that PqsE stimulates the RhlR/C 4 -HSL-dependent activation of pyocyanin and rhamnolipid genes ( 15 , 26 , 31 , 32 ). In the last few years, possible mechanisms have been proposed to explain this regulatory link, including the synthesis by PqsE of an alternative RhlR ligand, which would activate the expression of some target genes even in the absence of C 4 -HSL ( 15 , 31 ), direct interaction between PqsE and RhlR, which would increase RhlR affinity to target promoters ( 22 , 23 ), and a PqsE-mediated increase in RhlR intracellular abundance, which was proposed to occur independently of alterations in rhlR gene transcription and mRNA translation ( 33 ). Transcriptomic analyses showed that PqsE is required for the expression of more than 100 genes independent of the other elements of the pqs QS system, many of which encode virulence factors ( 12 – 14 , 23 ). However, since previous experiments were performed in RhlR-proficient genetic backgrounds, it is not clear whether and to what extent PqsE can control gene expression independently of RhlR. Moreover, the impact of RhlR on the P. aeruginosa transcriptome has never been investigated in a pqsE- negative background; hence, the genes regulated by RhlR in a PqsE-dependent or PqsE-independent manner have not yet been defined. Outlining the specific effects of PqsE and RhlR on the P. aeruginosa transcriptome is a challenging task since the las , rhl , and pqs QS systems are closely interconnected ( 3 , 34 ). Indeed, the LasR/3OC 12 -HSL complex exerts a positive control on the expression of the rhlR , rhlI , pqsR , and pqsH genes, thus stimulating activation of both the rhl and pqs QS systems ( 18 , 35 – 39 ). The rhl system, in turn, has positive and negative effects on lasI and pqs gene expression, respectively ( 38 – 42 ). Finally, the pqs QS system has a positive effect on the expression of rhlR and rhlI ( 24 , 43 ). In this context, to fill the gap of knowledge regarding the specific contributions of PqsE and RhlR to the P. aeruginosa transcriptome, in this study we generated a P. aeruginosa PAO1 mutant strain with deletions in all the genes involved in the synthesis and reception of the QS signal molecules 3OC 12 -HSL, C 4 -HSL, and HHQ/PQS, which carries chromosomally integrated and episomal genetic elements for inducible expression of pqsE and/or rhlR , respectively. RNA-seq analysis performed in this genetic background allowed us to untangle the roles played by PqsE and RhlR on the P. aeruginosa transcriptome and classify the RhlR-controlled genes into distinct subregulons based on their PqsE dependency.",
"discussion": "DISCUSSION In this study, we generated recombinant strains to untangle the regulatory roles of PqsE and RhlR in P. aeruginosa PAO1. In these genetic backgrounds, pqsE and rhlR could be independently expressed, alone or in combination, so that the production of each regulatory element did not affect the levels of the other. In this way, we managed to define the regulon controlled by PqsE in the absence of RhlR in the ΔQS-Eind genetic background, which surprisingly contains a single transcriptional unit, PA2827. This gene, whose expression is activated in response to sodium hypochlorite, encodes the sulfoxide reductase MsrB, involved in in vitro oxidative stress resistance and required for full virulence in the insect infection model of Drosophila melanogaster ( 49 ). Although the functional link between PqsE and MsrB remains to be determined, we can reasonably exclude a general effect of PqsE on the oxidative stress response, as other genes required for P. aeruginosa antioxidant defense were not altered by pqsE expression. It should be considered that PqsE likely exerts a more pronounced RhlR-independent effect on the P. aeruginosa transcriptome in the wild-type PAO1 strain compared to that in the ΔQS-Eind mutant. Indeed, in accordance with previous data ( 14 ), in this study we confirmed that PqsE negatively regulates P pqsA activity independently of RhlR. This effect was not observed in the RNA-seq analysis, possibly because the P pqsA promoter is not active in the ΔQS-Eind genetic background due to the lack of PqsR. Considering that both the pqsR and lasR genes are deleted in the ΔQS-Eind strain, this indicates that a possible RhlR-independent repressive activity of PqsE on additional genes activated by PqsR and/or LasR could have escaped our analysis. Moreover, the possibility that PqsE can directly affect the regulatory activity of transcriptional regulators other than RhlR, possibly including PqsR and LasR, or ancillary regulators controlled by these QS receptors, cannot be excluded. From a mechanistic point of view, the RhlR-independent control exerted by PqsE on the PA2827 gene and the pqsABCDE-phnAB operon could be also ascribed to its thioesterase activity. This would be in line with recent findings showing that PqsE variants unable to interact with RhlR or impaired in their catalytic activity control distinct sets of genes in P. aeruginosa PA14 ( 23 ). Although PqsE showed a limited effect on the P. aeruginosa transcriptome in the absence of RhlR, its regulatory role was evident in an RhlR-proficient genetic background, in which PqsE production significantly expanded the RhlR regulon and modulated the expression of a subgroup of RhlR-controlled genes. Here, in more detail, we show that the RhlR-regulated genes can be classified in four different classes based on their PqsE dependency: (i) the expression of class I genes is controlled by RhlR independently of PqsE; (ii) class II genes are differentially expressed in response to RhlR and even more affected when both RhlR and PqsE are present; (iii) class III genes are differentially expressed exclusively in the presence of both RhlR and PqsE; and (iv) the expression of class IV genes is promoted by RhlR and repressed by PqsE when rhlR is highly expressed. Literature data showing that PqsE increases RhlR levels ( 33 ) and/or its affinity to target promoters ( 23 ) could both justify the regulatory pattern here observed for class II genes. On the other hand, it is not clear why class I genes are not affected in response to a PqsE-dependent increase in RhlR levels and/or affinity to DNA. It would be tempting to speculate that the higher affinity of RhlR to class I relative to class II promoters could result in a saturating regulative response of class I genes to RhlR alone, thus making class I genes insensitive to the stimulation of the RhlR regulatory activity caused by PqsE. However, this hypothesis contrasts with the evidence that the mean FC values of class I genes in pqsE -proficient and pqsE -deficient conditions were not higher than those of of class II genes when rhlR alone was expressed, and with the similarity of the putative RhlR-binding sites identified on class I and class II promoters. The insensitivity of some class I genes to PqsE could be ascribed to a contrasting positive effect exerted by PqsE on these genes via RhlR stimulation, and a simultaneous negative effect exerted by PqsE on the same genes independently of RhlR. In this case, when both rhlR and pqsE are expressed, the PqsE negative effect could be counterbalanced by the RhlR-mediated positive regulation, enhanced by PqsE itself, resulting in an apparent PqsE insensitivity. The negative control exerted by PqsE on class I genes might be not apparent when only PqsE is present, as these genes would be not expressed in the absence of RhlR. A negative effect exerted by PqsE on the induction of RhlR-controlled promoters is evident for class IV genes. In this case, the RhlR stimulating activity is predominant for low levels of RhlR and PqsE, while the PqsE repressing effect overcomes the RhlR-mediated positive regulation when these effectors are produced at higher levels. At present, it is not possible to determine how many genes classified as class I based on the RNA-seq data are really insensitive to PqsE (proper class I genes) or are subject to an opposite effect by RhlR and PqsE (class IV genes). Moreover, it is not possible to define whether PqsE exerts its repressive effect on class IV genes via an RhlR-dependent or RhlR-independent mechanism. In this regard, since the class IV genes vqsR and clpP2 are positively regulated by LasR ( 76 , 77 ), future experiments performed in a LasR-proficient genetic background could help clarify whether PqsE repression on class IV genes also occurs in the absence of RhlR, when different regulators promote their expression. The possibility that RhlR may alternatively act as a transcriptional activator or transcriptional repressor based on its activation state should be also considered. Indeed, transcriptional regulators which switch between activating and repressing functions depending on their activity/expression level have been described. As an example, in P. fluorescens ST, the StyR response regulator acts as an activator of the styrene catabolic operon when intermediate phosphorylation levels drive its binding to high-affinity sites on the P styA promoter. When its phosphorylation level increases, StyR turns into a repressor of the styrene catabolic operon by binding to a low-affinity binding site on P styA ( 78 – 80 ). Dual-function transcriptional regulators have been described also among QS regulators. Indeed, the QS receptors LuxR and EsaR, from Vibrio alginolyticus and Pantoea stewartii subsp. stewartii , respectively, can alternatively act as activators or repressors of gene transcription based on the sequence and/or positioning of their binding sites on target promoters ( 81 , 82 ). In this context, our preliminary in silico analysis on the promoter regions of RhlR-controlled transcriptional units did not highlight clear differences between the sequences and positioning of the putative RhlR-binding sites for class I, II, and IV genes (data not shown). Concerning class III genes, their promoter regions may contain degenerated low-affinity RhlR-binding sites, resulting in the ability of RhlR to control their expression only when its level/activity is augmented by PqsE. This would be in line with the lower mean FC values of class III genes compared to those of class I and II genes, and with the few putative RhlR-binding sites identified on the promoter regions of class III transcriptional units. However, the latter evidence, together with the different distributions of activated/repressed class III genes compared to those of class I and II genes, would be also in line with the hypothesis that a consistent fraction of class III genes is indirectly regulated by RhlR via ancillary regulators. In this context, it is noteworthy that 27 genes coding for characterized or putative transcriptional regulators have been identified in the RhlR regulon, including qscR , vqsR , mpaR , bexR , antR , pvdS , and pchR . It has to be considered that every hypothesis on the differential impact of PqsE on RhlR-controlled genes is complicated by the fact that the mechanism of action of PqsE has not been clearly defined. In this regard, we demonstrated that C 4 -HSL is essential for the regulatory activity of RhlR, consistent with recent findings obtained in the PA14 strain ( 23 , 32 ), while PqsE does not seem to produce a secreted molecule able to activate RhlR in PAO1, as previously described in PA14 ( 15 , 31 ). Concerning the impact on the QS regulon of the reciprocal control exerted by RhlR on the pqs system, and by PqsE on RhlR activity, it is interesting to highlight that RhlR seems to limit its own regulatory activity by downregulating pqsE expression via P pqsA repression, both in the absence of PqsE and even more so when both RhlR and PqsE are present. This regulatory link implies that stimuli increasing RhlR levels would decrease pqsE expression, thus reducing the RhlR-stimulating activity exerted by PqsE, while stimuli reducing RhlR levels would result in increased PqsE production, thus increasing the PqsE-dependent regulatory activity of RhlR. This homeostatic control of RhlR activity is expected to differentially impact the expression of genes exclusively responsive to RhlR (class I genes) compared to that of genes whose expression is controlled by both RhlR and PqsE (class II, III, and IV genes). In fact, the expression of genes regulated by both PqsE and RhlR is expected to be robust with respect to fluctuations in RhlR levels, as the increase/decrease of this regulator could be counterbalanced by consequent adjustment of PqsE levels. On the contrary, the expression of class I genes, which are insensitive to PqsE, is expected to parallel RhlR levels. This regulatory network possibly enhances P. aeruginosa phenotypic plasticity in response to environmental fluctuations and resembles the incoherent feed-forward loop generated by LasR and RsaL in the las QS system. Indeed, it has been shown that genes whose expression is activated by LasR and not repressed by the LasR-controlled repressor RsaL are responsive to variations in LasR levels, while the expression of genes simultaneously activated by LasR and repressed by RsaL is robust with respect to fluctuations in LasR levels ( 83 ). It is noteworthy that many P. aeruginosa key virulence genes are classified as class II genes, strengthening the notion that both RhlR and PqsE are relevant for P. aeruginosa pathogenicity. In accordance, both the RhlR inhibitor meta-bromo-thiolactone and the PqsE inhibitors nitrofurazone and erythromycin estolate downregulate PqsE/RhlR-dependent virulence traits in P. aeruginosa , including pyocyanin production and biofilm formation ( 84 , 85 ). While some rewiring of the canonical QS regulatory cascade has been observed in P. aeruginosa clinical isolates ( 86 – 88 ), strains defective in the rhl or pqs systems are less frequently isolated from cystic fibrosis patients compared to las- deficient strains ( 89 – 91 ). Overall, these observations support PqsE and RhlR as promising targets for the development of antivirulence drugs reducing the pathogenic potential of P. aeruginosa ."
} | 5,226 |
37715250 | PMC10503168 | pmc | 1,298 | {
"abstract": "Microbial fuel cell (MFC) is a bio-electrical energy generator that uses respiring microbes to transform organic matter present in sludge into electrical energy. The primary goal of this work was to introduce a new approach to the green electricity generation technology. In this context a total of 6 bacterial isolates were recovered from sludge samples collected from El-Sheikh Zayed water purification plant, Egypt, and screened for their electrogenic potential. The most promising isolates were identified according to 16S rRNA sequencing as Escherichia coli and Enterobacter cloacae , promising results were achieved on using them in consortium at optimized values of pH (7.5), temperature (30°C) and substrate (glucose/pyruvate 1%). Low level red laser (λ = 632.8nm, 8mW) was utilized to promote the electrogenic efficiency of the bacterial consortium, maximum growth was attained at 210 sec exposure interval. In an application of adding standard inoculum (10 7 cfu/mL) of the photo-stimulated bacterial consortium to sludge based MFC a significant increase in the output potential difference values were recorded, the electricity generation was maintained by regular supply of external substrate. These results demonstrate the future development of the dual role of MFCs in renewable energy production and sludge recycling. Supplementary Information The online version contains supplementary material available at 10.1186/s12934-023-02187-y.",
"conclusion": "Conclusion The main objective of this work was to introduce an ecofriendly and economically viable method to generate green electricity, promising results were obtained by utilization of the potent electrogenic bacterial strains E. coli and E. cloacae as consortium at optimum conditions. Low level red laser was applied to boost the electrogenic potentiality of the bacterial consortium, results declared significant increase in the efficiency of MFC inoculated with the photo-stimulated consortium. The approach of using photo-stimulated bacterial strains serves as a dual solution for both pollution treatment and renewable energy generation. In future work, in depth study of the enzymatic mechanism of the dual role of photo-stimulated electrogenic bacterial consortium in renewable energy and biohydrogen production will be performed.",
"introduction": "Introduction Energy requirement is ever increasing throughout the world, electricity is considered the basic energy in our daily life. Seeking alternative cheap and ecofriendly sources of energy generation have become a must [ 1 ]. Microbial fuel cell (MFC) is considered a bio-electrical energy system that converts chemical energy contained in organic substrates into electrical energy by the microbial activities, so it acts as a promising sustainable inexpensive alternative for renewable energy generation [ 2 ], the efficiency of MFC technology comes from the capability of electrogenic bacteria to oxidize organic matter under anaerobic conditions [ 3 ], the oxidation process produces electrons and protons, the electrons released at the anode travel through an external electrical circuit to the cathode, creating a flow of electric current, while the protons move directly to the cathode through the solution [ 4 ]. Studies reported that transferring electrons to the anode can take place either by mediator electron transfer via an exogenous redox mediator [ 5 ] or by direct electron transfer as the microbe physically contacted to the anode forming a biofilm [ 6 ]. Traditional wastewater treatment methods faced significant difficulties from high operational costs, high energy usage, and environmental pollution [ 7 ]. In addition to green energy production electrogenic microbes have enzymatic potential to degrade different macromolecules with high conversion efficiency compared to other electrochemical cells [ 8 ] Biodegradable substrates are considered as electron sources in the MFC, these substrates range from simple compounds to complex organic compounds [ 9 ], previous reports documented that sludge is used as a fuel for several anaerobic and facultative anaerobic bacterial species because of its nutrient richness and year-round availability. It is made up of effluents obtained from urban, industrial, and other sources, which are regarded as the primary source of energy to produce electricity [ 10 ]. Pure or mixed cultures of microorganisms can be used in MFC, however mixed cultures are more efficient energy generators [ 11 ]. Electrogenic microorganisms are obtained from widely used sources such as soil or marine sediment, the natural microbial population, and brewery wastewater are added to mixed cultures to increase biological constancy [ 12 ]. Suitable environmental conditions including pH, temperature and nutrients are required for the growth and multiplication of electrogenic bacteria [ 13 ]. Temperature and pH affect the activity of enzymes, which will have a great impact on the growth and reproduction of microorganisms. When the temperature is greater or lower than the optimum value, the intracellular enzymatic activity will decrease, thus affecting the power generation potentiality of the MFC [ 14 ], also environmental pH is closely related to the life activities and metabolic performance of electrogenic bacteria, so the power generation capacity of MFCs varies greatly under different pH conditions [ 15 ]. In addition, studies have reported that the lack or excess of nutrients in the growth environment of microorganisms will directly affect their metabolic activities consequently their electricity production [ 16 ], Kim et al [ 17 ] reported that the produced power was more efficient on using glucose compared to other substrates. Light biotechnology is a recent field that contributes to the studies related to the environment through the photo stimulation of the bioenergetic processes of microorganisms [ 18 ]. Photo-energizing systems include low level red laser that emits light with a relatively narrow spectral band at a certain wavelength [ 19 ], it is hypothesized that induction of the photo-modulatory microbial system by red laser promotes the increase in cellular biomass and protein synthesis [ 20 ], since this inducer tool is cost -effective so it is introduced in many environmental and medical applications. The aim of the present work is to isolate, screen and identify the most potent electrogenic bacterial isolates from sludge samples, assess the effect of different environmental factors and different substrates on their growth, finally investigate the effect of photo-stimulation using low level red laser on the electrogenic potentiality of the bacterial consortium to introduce a new approach in boosting the efficiency of green electricity production.",
"discussion": "Discussion Sludge production volumes have been increased steadily every year [ 29 ]. Major issues arise when large amounts of sludge are dumped into the environment, including worsened odors, an increased risk of pathogenic microorganisms, and heavy metal accumulation [ 30 ]. In the present study four sludge samples acting as a microbial source were obtained from El-Shiekh Zayed water purification plant, the higher recorded results of the concentrations of metals and ions detected in S3 sample might be due to the rain effect which causes soil erosion, so different elements were then transported to the combined sanitation network and dumped into the water treatment plant as described by Brahimi et al. [ 31 ], also the higher values of turbidity and electric conductivity reflects higher microbial load as reported by Mucha and Kułakows [ 32 ]. The two analytical parameters biological oxygen demand (BOD), and chemical oxygen demand (COD) reflected the oxygen content possibly present due to pollutants in the investigated sludge samples, BOD determines the amount of dissolved oxygen consumed by bacteria to oxidize organic compounds, while COD is an indicative measure of the amount of oxygen needed for complete oxidation of organic compounds [ 33 ], higher BOD and COD values reveled higher concentration of organic substrates needed for the persistent microflora, additionally low COD/BOD ratio (< 2) indicated high performance of oxidation-reduction reactions by the naturally occurring microflora [ 34 ]. Temperature affected the physicochemical parameters of sludge samples, so it is considered as a key factor in shaping the structures of microbial populations. High records of microbial loads of S3 sample are harmonious with the results of Madni et al [ 35 ] who reported that high temperature favors the survival of microorganisms. The global energy crisis and the limited resources necessitates the search for alternative sustainable energy sources. in MFCs the organic matter present in the sludge samples was subjected to biochemical conversion system to produce electric current [ 36 ], the electrogenic microflora acts as a catalyst that oxidizes the organic matter resulting in the release of electrons and protons, electrons were migrated to the anode and consequently transferred to the cathode through an external wire, while the protons transferred directly to the cathode through the solution, the created potential difference can be recorded [ 37 ]. The measured values of potential difference (mV) indicated that the microflora in all samples have electrogenic potential and they can manifest this potential if they are properly re-inoculated into their habitat, the electricity generation passes through four stages initiated by a rapid fall in the output voltage, then a nearly stable interval of electricity generation, followed by another rapid fall in the output voltage, finally a stage of nearly steady state of low voltage. Similar electricity generation pattern was recorded by Cau et al [ 2 ], the highly statistically significant results recorded for S3 samples are in correspondence to that of the TVC results. The isolation of six bacterial strains from the selected sludge sample declared the fact that electrogenic bacteria are present in all ecosystems [ 38 ], with different electrogenic potentialities due to their multiple reducing mechanisms [ 39 ], primary and rapid identification using VITEK®2 system showed that our isolated bacterial collection included A. salmonicida which is associated with fish [ 40 ], S. lentus, E. cloacae , and E. coli which are associated with animals [ 41 ], C. testosterone and Pantoea sp which are mainly found in soil, waste water and sludge [ 42 ], in agreement with the results recorded by Nguyena et al [ 43 ] the most potent electrogenic isolates were E. cloacae , and E. coli , consequently they were subjected to confirmatory molecular characterization by using the 16S rRNA marker gene which has served as an important tool for determining phylogenetic relationships between bacteria. [ 44 ]. BLAST was applied to find regions of similarity between biological sequences and the results of phylogenic characterization showed that the strains NR_028912.1 and NR_112558.1 were most likely related to the strains E. cloacae and E. coli respectively, the sequence alignment of 16S rRNA gene illustrated the presence of some mutations including substitution (inversion and transversion mutation), deletion and insertion in both isolates. Generation of green electricity depends on the massive growth of electrogenic bacteria which carry out oxidation reduction reactions to generate electric current, growth conditions play a significant role in the biomass production of the microorganisms that are capable of converting pollutants to electric current via electrochemical reactions [ 45 ]. There are many physical, chemical and biological parameters that affect the operation of MFCs [ 46 ]. In our study the optimum conditions studied for isolated electrogenic bacterial isolates ( E. cloacae and E. coli ) were evaluated by determination of the total viable bacterial count in terms of cfu/mL as their increase reflects the ability of substrate utilization and consequently increasing electrons flow rate [ 26 ]. pH value is one of the crucial factors that significantly impact the bacterial growth rate, it affects the catalytic ability of enzymes, and it also alters the ionic charge of many biomolecules affecting the metabolic reactions [ 47 ]. for both E. cloacae and E. coli was pH 7.5 was reported as the optimum pH value at which maximum total viable count was achieved. Near results were obtained by Kim et al. [ 17 ] who reported that the optimum pH range for the growth of Enterobacteriaceae was between 6 and 8. Temperature affects the spatial arrangement of the atoms in the biomolecules and hence at the optimum temperature the biomolecules retain a stable and active structure which enables it to carry out its function. At low temperatures, enzymes stop functioning as low temperatures increase the viscosity of fluids and hardening of lipids, while high temperatures cause rupture of hydrogen bonds in proteins and in DNA resulting in protein denaturation [ 48 ]. It was evident from our results that the optimum incubation temperature at which the maximum population was 30°C. These results are consistent with those reported by Sihag et al [ 49 ] who indicated that most bacteria are active in the mesophilic range of 25°C to 40°C. Nutrient utilization strategy affect the growth rate of microbial cells, microorganisms can grow on a variety of growth substrates and hence possess versatile metabolic activities, previous literature reported that carbon sources are categorized into groups based on their mechanism of joining the metabolic pathway [ 48 ], in our study higher population scores were recorded on using glucose/pyruvate, these results are consistent with those of Wang et al [ 50 ] who reported that the bacterial isolates tend to co-utilize both sources simultaneously leading to catabolite motivation. It is well known that the efficient applicability of MFC systems depends on the enzymatic degradation ability of the electrogenic microorganisms, to overcome this challenge mixed cultures were suggested [ 51 ], so using the two most potent electrogenic bacterial isolates ( E. cloacae and E. coli ) in consortium was significantly more efficient than using them individually. In agreement with the findings of Khater et al [ 22 ] who reported that, regular addition of fresh substrate overcome the depletion of nutrients and activate the bacterial culture leading to the restoration of the cell potential, feeding the MFC with 100mL glucose/pyruvate at regular intervals maintain a steady energy generation along the interval of operation. Trying to improve the performance of MFCs, the bacterial consortium was subjected to LLRL to enhance the cell proliferation, protein synthesis and metabolic activities [ 20 ]. Previous studies on the effect of laser radiation indicates its bio-stimulatory effect, this effect returned to the photoexcitation of the protein cytochrome C complex, consequently it pumps more photons thus the amount of ATP increases leading to increase in the growth rate, on the other hand high irradiation doses causes cytotoxic effect leading to the damage of the cell structure [ 28 ], our results are harmonious with those of Crugeira et al [ 18 ] who reported that the stimulatory effect of LLRL is dose dependent and has positive influence on thermophilic bacterial kinetics. In an application of assessing the efficiency of new MFC designed using sludge which contain the metabolically active bacterial cells as culture medium was done, addition of exogenous bacterial inoculum of the photo-stimulated bacterial consortium led to significantly high synergistic action that increased the cell performance, as acceleration of cell proliferation consequently led to intensifying the electron flow, also the addition of fresh medium containing glucose /pyruvate (1%) at regular intervals over comes the depletion of nutrients and led to the revival of the endogenous and exogenous microbial flora, thus the mean value of the potential difference was maintained during the time of operation."
} | 4,026 |
33997673 | PMC8091062 | pmc | 1,299 | {
"abstract": "Summary Critical minerals are essential for the ever-increasing urban and industrial activities in modern society. The shift to cost-efficient and ecofriendly urban mining can be an avenue to replace the traditional linear flow of virgin-mined materials. Electrochemical separation technologies provide a sustainable approach to metal recovery, through possible integration with renewable energy, the minimization of external chemical input, as well as reducing secondary pollution. In this review, recent advances in electrochemically mediated technologies for metal recovery are discussed, with a focus on rare earth elements and other key critical materials for the modern circular economy. Given the extreme heterogeneity of hydrometallurgically-derived media of complex feedstocks, we focus on the nature of molecular selectivity in various electrochemically assisted recovery techniques. Finally, we provide a perspective on the challenges and opportunities for process intensification in critical materials recycling, especially through combining electrochemical and hydrometallurgical separation steps.",
"introduction": "Introduction Critical raw elements are essential in our modern society, being ubiquitous in all areas of industry, especially renewable energy technologies and metallurgical manufacturing, and in everyday life, for example in electronic devices, phones, and electric vehicles. Global accessibility to these important resources poses a major challenge, due to their rapidly increasing demand, and ever-decreasing supply. The global use of critical resources is expected to double between 2010 and 2030, following predicted economic growth ( European Commission, 2018 ), thus placing serious pressure related to sustainable supply chains and environmental issues. The US Department of Energy (DOE) “Critical Materials Strategy” report assessed 16 elements based on their criticality to the clean energy industry and associated supply risk ( U.S. Department of Energy, 2011 ). In addition, the European Commission recently carried out an assessment of 83 raw materials and identified 30 elements as critical, based on economic significance and supply risks ( European Commission, 2020 ), with the major critical materials highlighted in Figure 1 . Figure 1 Assessment of material criticality based on economic importance and supply risk Dark green: heavy rare earths, light green: light rare earths, red: platinum group metals, dark gray: non-metallic elements in supply risk, blue: other metals in supply risk within criticality zone of high economic importance (≥2.8) and supply risk (≥1). Adapted with permission ( European Commission, 2020 ). In particular, the ongoing technological evolution has resulted in a rapidly growing generation of waste electrical and electronic equipment (WEEE) ( Işıldar et al., 2018 ). It has been reported that over 40 Mt of electronic waste have been generated every year since 2014, with only 20% being recycled, and with a projected increase to over 52 Mt in 2021 ( Figure 2 ) ( Baldé et al., 2017 ; Gollakota et al., 2020 ). Thus, the high metal content in WEEEs makes them a valuable, secondary raw stream for urban mining and recycling. In addition to value-added benefits in recycling, our current reliance of a great deal of commodities and raw materials on virgin sources poses serious environmental risks ( Zeng et al., 2018 ). Owing to a variety of toxic substances in electronic devices, WEEE leads to significant harmful effects on the environment and human health ( Baldé et al., 2017 ). Therefore improving the efficiency of recovery of metal from either primary mining processing or from secondary waste, as well as sustainable urban mining/recycling, is of utmost importance to both the economy and environment, enabling the transition from a traditional linear supply chain that is described as “take, make, and dispose” to a closed loop for a sustainable circular economy ( Gaustad et al., 2018 ). Figure 2 Increasing trend of the generation of worldwide electronic wastes Adapted from ( Gollakota et al., 2020 ). In the current recycling trains, an initial stage of energy-intensive shredding and physical separation takes place before the separation of ferrous/non-ferrous metal streams and non-metallic fractions ( Hsu et al., 2019 ). Subsequently, the metal-rich streams are subjected to pyrometallurgical or hydrometallurgical refining. Because of intrinsic limitations of conventional pyrometallurgical processes, e.g., large energy input, environmental hazard, the need of additional processing, lack of selectivity, and high capital cost, hydrometallurgical methods have been welcomed as a more sustainable alternative compared with pyrometallurgical routes ( Sethurajan et al., 2019 ; Tunsu and Retegan, 2016 ). In hydrometallurgical refining processes, leach liquor or contaminated water streams from acid/base leaching have to be treated with separation techniques such as solvent extraction, ion exchange, precipitation, adsorption, and electrochemical methods ( Sethurajan et al., 2019 ). The state-of-the-art for hydrometallurgical recoveries have been presented in several recent review articles and cover a broad range of different technologies ( Hsu et al., 2019 ; Sethurajan et al., 2019 ; Tunsu and Retegan, 2016 ) Recently, remarkable attention has been paid to electrochemical metal recovery for the purpose of enabling circular economy ( Chernyshova et al., 2020 ; Jin and Zhang, 2020 ). Contrary to traditional recovery techniques, which are chemically intensive and often require large pH or thermal swing ( Ambaye et al., 2020 ; Tunsu and Retegan, 2016 ), electrochemical methods offer a modular approach as an alternative of traditional chemical/thermal swing-based separations ( Su, 2020a ). The main challenge is selectivity; because the target metal ions are usually minority components in the presence of excess competing species in the primary mining or secondary waste stream, there have been extensive efforts to ensure selective recovery in dilute streams, and electrochemically mediated technologies offer a desirable platform tackling this selectivity issue ( Gamaethiralalage et al., 2021 ; Su, 2020a ). In this review, we present recent advances in electrochemically mediated metal recovery technologies, as well as its close synergistic connection with hydrometallurgical approaches. We place a special focus on hydrometallurgical and electrochemical approaches that can benefit critical materials recycling, especially for rare earth elements and other valuable transition metals. We also seek to provide insights into the mechanisms and applications for different electrochemical techniques, namely, electrodeposition, electrosorption, electrodialysis, and electrocoagulation (EC), and highlight the need for the design of molecular selectivity in the development of next-generation electrochemical recovery. Finally, we discuss the challenges and opportunities for electrochemically assisted recovery techniques, both at an interfacial electrode level, and from a process design perspective."
} | 1,775 |
33800960 | PMC7961771 | pmc | 1,300 | {
"abstract": "In order to replace nonrenewable resources and decrease electronic waste disposal, there is a rapidly rising demand for the utilization of reproducible and degradable biopolymers in flexible electronics. Natural biopolymers have many remarkable characteristics, including light weight, excellent mechanical properties, biocompatibility, non-toxicity, low cost, etc. Thanks to these superior merits, natural functional biopolymers can be designed and optimized for the development of high-performance flexible electronic devices. Herein, we provide an insightful overview of the unique structures, properties and applications of biopolymers for electronic skins (e-skins) and flexible strain sensors. The relationships between properties and sensing performances of biopolymers-based sensors are also investigated. The functional design strategies and fabrication technologies for biopolymers-based flexible sensors are proposed. Furthermore, the research progresses of biopolymers-based sensors with various functions are described in detail. Finally, we provide some useful viewpoints and future prospects of developing biopolymers-based flexible sensors.",
"conclusion": "4. Conclusions and Perspectives In this review, several natural biopolymers and their applications in e-skins and flexible strain sensors are proposed and summarized to meet rising requirement of green electronics, soft integration and biocompatible manufacturing technologies. Biopolymers have many merits, such as unique structures, mechanical flexibility, biocompatibility, biodegradability, nontoxicity, renewability, etc. In order to obtain desirable and high-performance sensing properties, various advanced technologies and methods for preparing functional biopolymers and biopolymers composites have been developed. Despite the great advances has been achieved in recent research of biopolymers and biopolymer-based sensors, there are some challenges in realizing the practical application of biopolymers in flexible electronics. For instance, firstly, although natural biopolymers have been developed as non-toxic, biocompatible and biodegradable platforms for flexible electronics, other incorporated components (e.g., metal nanoparticles/nanowires, carbon materials, conductive polymers) have limitations in this regard. Secondly, further mechanistic research and synthetic methods for novel biopolymers need to be developed so as to endow biopolymers with new special and outstanding properties, for example, electronic conductivity, bioactivity, thermostability, 3D conformal properties and high ion mobility on skins and curved surface; Finally, reasonable surface/interface engineering techniques, fabrication technology of substrates and multifunctional integration of biopolymers-based flexible sensors need to be investigated and enhanced. Undoubtedly, biopolymers provide an exciting strategy to exploit new functional flexible electronics that are of great significance for improving their applications in green and sustainable and smart electronic devices.",
"introduction": "1. Introduction Recently, flexible and wearable electronics devices have shown tremendous application potential in the fields of Internet of Things (IoT), sensor, energy, biomedical systems, artificial intelligence (AI) and smart robots [ 1 , 2 , 3 ]. Compared with traditional electronic equipment, flexible electronics have many advantages such as portability, flexibility, extensibility, low manufacturing cost, unique deformability and so on. As key parts of flexible electronics, electronic skins (e-skins) and flexible strain sensors can be widely used for humans’ daily activities monitoring, human-machine interfaces, AI, and the prevention and rehabilitation of human diseases [ 4 , 5 ]. The flexible sensors include optical-, electronical-based sensors and some sensors based on other technologies. Optical fiber sensors are widely used in flexible and wearable devices due to their advantages such as multiplexing capabilities, compact size and electromagnetic immunity [ 6 , 7 ]. These advantages provide an intrinsically safe solution for underwater, intrusive and harsh environment applications [ 8 , 9 ]. Flexible and wearable electronical-based sensors exhibit excellent features, such as portability, high sensitivity, a simple preparation process and low cost, which benefit from the electromechanical properties of their conductive materials. So far, multiple flexible conductive materials, for instance, metal nanoparticles and metal oxides [ 10 , 11 ], one dimension (1D) carbon nanotubes (CNTs) [ 12 , 13 ], two dimensional (2D) transition metal dichalcogenides [ 14 , 15 ], graphene [ 16 , 17 ] and carbide nanosheets [ 18 , 19 ], three dimensional (3D) metal-organic frameworks (MOFs) [ 20 , 21 ] and conductive polymers [ 22 , 23 ] have been used for the fabrication of flexible sensors. Despite the fact these materials have been widely investigated, their intrinsic low mechanical properties, poor stability, non-biocompatibility, non-biodegradability and toxicity have limited their applications. Natural biopolymers are naturally derived from bio-based materials, e.g., a kind of raw materials (such as microorganisms, plants, fats, sugars, proteins and their components) by biological and chemical synthesis methods [ 24 ]. In comparison with synthetic nanomaterials, biopolymers possess many unique advantages, such as natural abundance, robust structures, hydrophilicity, water solubility, multiple active sites, self-cleaning, lightweight, mechanical flexibilities, biocompatibility, biodegradability, non-toxicity, renewability, low cost, etc.) ( Figure 1 ). Biopolymers are promising materials for developing environmentally friendly and sustainable flexible sensors [ 24 , 25 ]. At first, the special layered topographic characteristics of biopolymers provide adjustable elastic modulus, offering customizable mechanical properties to conform bending interface and dynamic surface [ 26 ]. Specifically, some unique properties of biopolymers, including self-cleaning and self-healing properties, allow biopolymer-based sensors to avoid interference from external influences (e.g., humidity, temperature, dust, etc.) and improve the test accuracy. In addition, the low cost, light weight, non-toxicity, and biological characteristics can accommodate green and large-scale fabrication of flexible sensors, and reduce the discomfort of long term attachment on the human skin surface. This kind of sensors have shown significant potentials in human health monitoring. At last, the existence of abundant functional groups in biopolymers, such as hydroxyl, carboxylic, amino groups, etc. [ 25 ] is conducive to further functionally modify biopolymers and endow biopolymers more functionalities. In this paper, we summarize the recent development of natural biopolymers with various nanostructures as functional and sensing materials in flexible electronics. The functional design strategies and fabrication technologies for biopolymers-based flexible sensors are proposed by analyzing the structures and properties of biopolymers. Then, the research progresses of biopolymers-based sensors with various functions in flexible electronics devices are summarized. In the end, the current challenges and trends of biopolymers-based sensors are described and discussed."
} | 1,831 |
34538267 | PMC8451101 | pmc | 1,301 | {
"abstract": "Background Recent research articles indicate that direct interspecies electron transfer (DIET) is an alternative metabolic route for methanogenic archaea that improves microbial methane productivity. It has been shown that multiple conductive materials such as biochar can be supplemented to anaerobic digesters to increase the rate of DIET. However, the industrial applicability, as well as the impact of such supplements on taxonomic profiles, has not been sufficiently assessed to date. Results Seven industrial biogas plants were upgraded with a shock charge of 1.8 kg biochar per ton of reactor content and then 1.8 kg per ton were added to the substrate for one year. A joint analysis for all seven systems showed a decreasing trend for the concentration of acetic acid ( p < 0.0001), propionic acid ( p < 0.0001) and butyric acid ( p = 0.0022), which was significant in all cases. Quantification of the cofactor F420 using fluorescence microscopy showed a reduction in methanogenic archaea by up to a power of ten. Methanogenic archaea could grow within the biochar, even if the number of cells was 4 times less than in the surrounding sludge. 16S-rRNA gene amplicon sequencing showed a higher microbial diversity in the biochar particles than in the sludge, as well as an accumulation of secondary fermenters and halotolerant bacteria. Taxonomic profiles indicate microbial electroactivity, and show the frequent occurrence of Methanoculleus , which has not been described in this context before. Conclusions Our results shed light on the interplay between biochar particles and microbial communities in anaerobic digesters. Both the microbial diversity and the absolute frequency of the microorganisms involved were significantly changed between sludge samples and biochar particles. This is particularly important against the background of microbial process monitoring. In addition, it could be shown that biochar is suitable for reducing the content of inhibitory, volatile acids on an industrial scale. Supplementary Information The online version contains supplementary material available at 10.1186/s13068-021-02034-5.",
"conclusion": "Conclusions The use of biochar in industrial biogas plants caused significant changes in the concentration of organic acids as well as in taxonomic profiles. Even if the reduction in the concentration of organic acids could be interpreted as an indication of DIET, this interpretation contradicts the high abundance of the genus Methanoculleus , which has not yet been associated with DIET. As indicated in another study [ 16 ], another, previously unknown mechanism could be involved. While caution should be exercised based on microscopic counts, epifluorescent microscopy indicated a shift in the number of methanogenic archaea, suggesting that there is a decrease in methanogenic cell numbers in sludge and an increase in the respective biochar particles. One of the digesters was analyzed in more detail by 16S-rRNA gene amplicon high-throughput sequencing, comparing the taxonomic profiles in the sludge and in hand-picked biochar particles from fresh digestate. The taxonomic profile in the biochar particles substantially differed from the one observed in the sludge samples, and this profile suggested an increased electroactivity associated to the biochar particles, as well as an increased biodiversity, which should be characterized in depth in future studies.",
"discussion": "Results and discussion Influence of biochar on the spectrum of organic acids At the beginning of the project, seven customers (BGP1–BGP7) were acquired who, when using biochar in the context of the present study, agreed to allow insight into process data during the upgrade of the anaerobic digester plants (as described in Material and methods ). At first, only BGP2 and BGP6 were in a critical condition reaching very high concentrations of total volatile fatty acids (TVFAs; 8059 mg L −1 of TVFAs for BGP2 and 2696 mg L −1 for BGP6). BGP1, BGP2-BGP5 and BG7 had TVFA concentrations lower than 2000 mg L −1 . Some authors provide general information about inhibition thresholds from TVFAs. To give here an example: It was recommended that when using leftover food as a substrate, the amount of TVFAs should remain below 4000 mg L −1 [ 15 ]. However, the inhibition threshold varies depending on the situation at hand. The point at which an organic acid has an inhibiting effect depends considerably on the buffer capacity, the chemical composition, pH value and the type of acid [ 15 ]. According to Kroiss, a 10% inhibition is reached at acetic acid concentrations of approximately 1000 mg L −1 . If the concentration is increased further to 3000 mg L −1 , there is already a 50% inhibition. [ 16 ] Unlike acetic acid, propionic acid has a very strong inhibiting effect. At a pH of 6.5, a concentration of 150 mg L −1 propionic acid is already alarming. Under the same conditions, an equally strong inhibitory effect for acetic acid would only be expected at 1000 mg L −1 [ 17 ]. In this context, it is particularly alarming that some of the analyzed systems (BGP2-5) showed high levels of propionic acid at the beginning of the experiment (Additional file 1 ). Propionic acid concentrations were particularly high for BGP2 (1800 mg L −1 ) and BGP6 (1915 mg L −1 ). The fact that biogas was still formed at such high concentrations of propionic acid can be explained by the high pH value (between 7.5 and 8.0 for all plants; Fig. 1 B). With a pK S value of 4.87, propionic acid is almost completely deprotonated at pH values > 7.5. Protonated acids in particular are inhibitory, and the degree of protonation increases with a low pH value. The fact that pH values between 7.5 and 8.0 were maintained despite such high acid concentrations could be explained by an increased buffer capacity due to high NH 4 -N contents (Fig. 1 C). With NH 4 -N concentrations ≥ 5 kg t −1 , BGP1, BGP6 and BGP2 in particular showed high values. Fig. 1 Chemical parameters collected by the plant operators: total volatile fatty acids (TFVAs, A ); pH ( B ); ammonium nitrogen (NH4-N, C ), FOS/TAC ( D ); total solids (TS) as percent of fresh biomass ( E ) and volatile solids (VS) as percent of TS Although no reliable dataset for the biogas productivity was given, all operators have regularly commissioned suitable service providers for chemical analyses, as described in Material and methods and Fig. 1 . All raw data are provided in the Additional file 1 . Most of the raw data yielded no meaningful interpretation. Although small variations were observed for pH, NH 4 -N, FOS/TAC, total solids (TS) and volatile solids (VS), no clear trend was observed for the respective parameters (Fig. 1 B–F). However, upon biochar supplementation a decrease throughout time of TFVAs was observed (Fig. 1 A). A non-parametric Spearman test was used to verify this observation (Table 1 ). Since VFAs longer than butyric acid were mostly not present or only in very low concentrations (Additional file 1 ), this analysis was limited to acetic, propionic, butyric acid and the sum of all VFAs (TVFA). No significant trend was observed for BGP4, BGP6 and BGP7. BGP3 and BGP5 indicated a decrease in VFAs, but did not provide enough data points for a reliable comparison. A significant decrease was observed for BGP1 and BGP2. In order to increase comparability and also to include BGP3 and BG5 in the significance analysis, all seven systems were treated as a data cloud in a joint analysis. For this, VFA concentrations of all 7 biogas plants were initially normalized to a value between 0 and 1. The values of all 7 systems were then averaged and treated as a data cloud. The resulting data cloud was then subjected to a non-parametric Spearman analysis. The trend was clear and significant for acetic acid and propionic acid (Fig. 2 A and B). For butyric acid, only a slight—but yet significant—decrease was observed (Fig. 2 C). Table 1 Correlation of VFAs over time applying a nonparametrical Spearman test TVFAs Acetic acid Propionic acid Butyric acid R 2 p -value R 2 p -value R 2 p -value R 2 p -value BGP1 0.4807 < 0.0001**** 0.5663 < 0.0001**** 0.2558 < 0.0001**** 1.000 na BGP2 0.4849 < 0.0001**** 0.4633 0.0003*** 0.5118 < 0.0001**** 0.3455 0.0001**** BGP3 0.7677 na 0.7617 na 0.7349 na 0.7349 na BGP4 0.3696 0.1041ns 0.1058 0.1967ns 0.1627 0.6441ns 1.000 na BGP5 0.9505 na 0.9504 na 0.9456 na 1.000 na BGP6 0.0350 0.1965ns 0.0100 0.4650ns 0.1104 0.0924ns 0.0272 0.3847ns BGP7 0.0011 0.7833ns 0.0091 0.9500ns 0.0007 > 0.9999ns 1.000 na Several results were not significant (ns). The significance level was not determined for fewer than three values (na) Fig. 2 Evolution of organic acid concentration upon biochar supplementation: after normalization to a value between zero and one, mean values were calculated for all seven digesters (BGP1–BGP7). Concentrations were recorded over a duration of one year. The significance of the decrease in organics acids was assessed for acetic acid ( A ), propionic acid ( B ) and butyric acid ( C ) applying a nonparametrical Spearman test The observed decrease in acetic, propionic, and butyric acid concentrations is in accordance with existing literature. A recent study at laboratory scale demonstrated that conductive materials help to lower the concentrations of propionic and butyric acids, and explained that this phenomenon is due to an increased rate of DIET, which in turn reduced the amount of inhibiting hydrogen [ 7 ]. In this context, the falling concentrations of organic acids could be interpreted as an indication for DIET, even if the observation of the acids alone is not sufficient for this. It must be taken into account that other mechanisms besides DIET must now also be considered. In a recent study, it was shown that carbon nanotubes had a positive effect on methane formation without the DIET being detected [ 18 ]. The organic loading rate for all digesters is shown in Table 2 , and all plant operators confirmed that the respective loading rate was maintained throughout the study. Therefore, the reduced concentration of organic acids cannot be explained by a change of loading rate. Table 2 Overview on digester systems: all systems were mesophilic continuous stirred tank reactors (CSTRs) Anaerobic digester Substrates Loading rate [kg VS m −3 d −1 ] Retention time in days [d] Volume of all fermenters excluding the digestate storage [m 3 ] BGP1 Corn silage, poultry manure, cereal silage, sugar beet, swine manure, grain kernel (mashed) 2.9 117 7.700 BGP2 Corn silage, poultry manure, grass silage, sugar beet 3.1 113 7.000 BGP3 Corn silage, grain kernel (mashed), perennial rye, cereal silage, cattle manure, cattle slurry 2.7 85 2.900 BGP4 Corn silage, cereal silage, cup plant, swine slurry, cattle manure 4.3 54 3.200 BGP5 Cattle manure, corn silage, poultry manure, swine slurry 2.1 105 4.600 BGP6 Corn silage, cereal grain (mashed), poultry manure, cattle manure with feed residues 3.2 95 2.600 BGP7 Corn silage, cereal silage, grass silage, sugar beet, cereal grains (mashed) 2.3 153 4000 F420-fluorescent microscopy upon biochar addition Before biochar was applied to BGP1-BGP7, all plant operators provided fresh sludge samples for the analysis of methanogenic archaea based on the cofactor F420. After 9 and 11 months, all plant operators provided further samples for F420 analysis. F420 signals were counted using the ImageJ software (Fig. 3 ). In general, the detected concentration of methanogenic archaea was in a similar range as in other studies [ 19 , 20 ]. Interestingly, the number of methanogenic archaea seemed to decrease slightly throughout time upon the addition of biochar. Although the decrease was not observed for all timepoints (BPA1 behaved different) and samples for BGP6 and BGP7 were not accessible during month 11, a two-tailed paired t-test revealed a significant decrease of the archaea number for BGP2, BGP3, BGP5 and BGP6. Although not significant, BGP4 and BGP7 showed a decrease in methanogenic archaea as well (Fig. 3 B). Fig. 3 Quantification of methanogenic archaea before and after supplementation: The cofactor F420 was used to count methanogenic archaea using epifluorescent microscopy. The QQ plot resulting from the Shapiro–Wilk test ( A ) is shown as an example for the counting of all archaea ( B ), but it was also carried out for the counting of Methanosarcina -like clusters ( C ) and rod-shaped and thread-like archaea ( D ). Analysis was performed before biochar was added, and 9 and 11 months after supplementation. Each bar shows a mean value of 48 pictures taken from three different slides. A two-tailed paired t-test was applied to assess significance Regarding methanogenic phenotypes, mainly cocci were observed. In a recent study, conductive particles led to an increase in the ratio of acetoclastic methanogens [ 10 ]. Acetoclastic methanogens that are typically involved in anaerobic digestion processes are Methanothrix and Methanosarcina [ 21 , 22 ]. However, typical phenotypes for Methanothrix (thread-like) or Methanosarcina (sarcina-like cluster) were scarcely detected. On average, less than one Methanosarcina cluster was detected per picture (Fig. 3 C). Although this number is very small, it is interesting that all of the plants tested, with the exception of BGP7, showed an increase in the number of Methanosarcina -like clusters and some of them were significant. No clear trend was observed for rod-like and thread-like phenotypes (Fig. 3 D). As the hydrogenotrophic methanogen Methanoculleus (coccus shape) is usually enriched in continuous stirred tank reactors [ 21 ], and mainly methanogenic cocci were detected in the analyzed digesters, our results suggest that Methanoculleus was also prevalent in the present study. In the case of BGP1, this assumption was verified by 16S-rRNA gene amplicon high-throughput sequencing (Fig. 6 ). Under the assumption that supplemented biochar increased the rate of DIET, our results suggest that hydrogenotrophic methanogens could be involved in DIET. In concordance with this hypothesis, recent studies have suggested that DIET is more widespread than previously thought, and that DIET is not only restricted to acetoclastic methanogens. To give some examples: recently, the first methanogen able to produce electrically conductive pili was detected, and identified as the hydrogenotrophic Methanospirillum hungatei [ 13 ]. Another recent study suggested that the hydrogenotrophic Methanobacterium is able to perform DIET [ 14 ]. Regarding Methanoculleus , several species have been tested in vitro, but were not able to grow in syntrophic co-culture with the typical electrogenic bacterium Geobacter metallireducens [ 23 ]. However, the observed results could also be explained using other mechanisms. In a study published in 2017, a positive effect was found using carbon nanotubes without indications of DIET. The realization that mechanisms other than DIET could be involved is particularly interesting because no DIET has yet been detected for the hydrogenotrophic methane generator Methanoculleus (as already described above). The observation that carbon nanotubes exerted a stronger effect on hydrogenotrophic methanogens than on acetoclastic methanogens and this presumably without DIET therefore opens up a different perspective for the results presented here and is in accordance with the high proportion of Methanoculleus among the methanogens. The exact mechanism triggered by carbon nanotubes is not yet fully understood, but it has been described that they increasingly shift the redox potential into the negative. Fluorescence microscopy with ground biochar particles The fluorescence microscopy results shown in Fig. 3 were performed with diluted sludge as described in Material and methods . The counting of methanogenic archaea in the defined volume of sludge does not take into account those archaeal cells, which are immobilized in the biochar. Therefore, further experiments were performed focusing on a defined weight of ground biochar particles. The plant operator of BGP1 provided access to several tons digestate, which left the reactor exactly before the sampling. Two falcon tubes were filled with biochar particles, which were collected directly from the digestate. In a first analysis, biochar particles were ground to powder and resuspended in 1 ml of PBS buffer per 1 g of powder. Upon inverting, the samples were analyzed using fluorescence microscopy (Fig. 4 ). Fig. 4 Methanogenic archaea found in biochar particles: after applying the Shapiro–Wilk test ( A ), a two-tailed paired t-test was used to assess significance for all archaea. Number of methanogenic archaea based on the quantification of cofactor F420 signals ( B ). Biochar particles from BGP1 were collected from the digestate immediately after it left the digester. Pictures of methanogenic archaea found in biochar particles ( C ). Methanosarcina -like clusters are highlighted with white arrows Although the number of methanogenic archaea was much lower in the ground biochar powder compared to the fresh sludge (Fig. 4 A), ground biochar particles clearly contained methanogenic archaea (Fig. 4 B). Biochar samples which were not inserted into the digesters did not show F420-signals. As previously described for highly viscous sludge from continuous stirred tank reactors [ 21 ], very little Methanosarcina -like clusters were found, which was also the case in BGP1–BGP7 (Fig. 3 C). Still, a few Methanosarcina were observed, even in the ground biochar, suggesting that the biochar pores were big enough for such cluster-forming methanogens (Fig. 4 C). The majority of the observed methanogens were cocci, suggesting that the same methanogens were present in both the biochar and the sludge. Analysis of taxonomic profiles of ground biochar particles at phylum level To obtain a more detailed insight into the taxonomic profiles present in the sludge and in the biochar particles from BGP1, 16S-rRNA gene amplicon high-throughput sequencing was performed. The main phyla present in all samples were Firmicutes (~ 69%), Bacteroidota (~ 13%) and Proteobacteria (~ 4%) (Fig. 5 ). Fig. 5 Taxonomic profiles in sludge and biochar from BGP1 at phylum level, obtained through 16S-rRNA gene amplicon high-throughput sequencing. For the sake of simplicity, only the most abundant phyla are shown. Differences in the mean values that are significant are highlighted by yellow stars in the legend. Significances were analyzed using the DESeq2 differential abundance analysis [ 46 ] and p -values were < 0.05 The ground biochar samples displayed a higher—yet not significant—relative abundance of Bacteroidota and a lower relative abundance of Firmicutes (FDR adjusted p -value < 0.05; DESeq2 test) in comparison to the digester sludge samples. Firmicutes are well-known degraders of plants and complex carbohydrates [ 24 ]. The lower ratio of Firmicutes in the biochar samples might indicate that bacteria within biochar particles are rather associated with secondary fermentation (acetogenesis) than with hydrolytic and acidogenic events. Our results also revealed that biochar powder contained higher relative abundances of Acidobacteria , Halanaerobiaeota , Halobacterota and Proteobacteria , although only Acidobacteria changed significantly. This suggests that biochar particles are subjected to more stressful conditions: Acidobacteria are described as robust and adapted to stressful conditions in soil [ 25 ]; Halanaerobiaeota and Halobacterota are generally known to be associated with high salt contents and their higher abundance might be explained by the adsorptive characteristics of biochar; and Proteobacteria are associated with nitrogen and ammonium metabolism [ 26 ] and, therefore, their increased abundance in the biochar might be explained due to precipitation of ammonia within the biochar. Altogether, our results indicate that adsorptive characteristics of biochar particles can lead to locally increased concentrations of salt and other inhibitors, which in turn has a strong impact on the underlying taxonomic profile. At this point, it should be considered that adsorption effects, DIET and other effects are difficult to distinguish. A study from 2017 investigated the possibility of adsorption-based extraction of organic acids and indicated that the adsorption of organic acids by numerous interfering ions such as Na + , K + , H 2 PO 4 − /HPO 4 2− , Cl − , and SO 4 2− is problematic [ 27 ]. There was no activation process of the carbon used in the present work, so that the adsorption capacity is lower than for activated carbon. If the observed effects were mainly caused by adsorption, one could have expected a significant reduction in the concentrations of organic acids in all anaerobic digester plants. However, there was no decrease in organic acids in BGP4, BGP6 and BGP7. Nevertheless, it cannot be ruled out that adsorption-based processes had an influence on observed effects, which could also be responsible for the higher relative abundance in biochar of microorganisms involved in secondary fermentation processes. In this relation, it must be noted that the phylum Chloroflexi showed a significant higher abundance in the biochar powder (FDR adjusted p -value < 0.05; DESeq2 test). In a previous report, an enrichment of Chloroflexi in anaerobic biofilms was described [ 28 ]. It has also been reported that Chloroflexi can be involved in syntrophic relations [ 29 , 30 ]. In relation to the aforementioned decrease of Firmicutes , this supports the hypothesis that biochar particles are particularly involved in syntrophic degradation processes. On the other hand, Cyanobacteria were overrepresented in the sludge samples (FDR adjusted p -value < 0.05; DESeq2 test). It has to be noted that the sequencing reads assigned to Cyanobacteria could correspond partially to chloroplasts, which are an indicator of undegraded plant biomass. Less than 1% of the reads represent chloroplasts (PCC-6307). The remaining reads (2%), which were assigned as Cyanobacteria , are represented by the genus Cyanobium (data not shown) . This phenomenon has been previously reported for a lab-scale reactor, which was fed with fresh grass biomass and a high ratio of Cyanobacteria was observed [ 28 ]. Analysis of taxonomic profiles of ground biochar particles at genus level The most abundant genera detected in both sets of samples were Limnochordia MBA03 (36% in biochar samples and 46% in sludge), Proteiniphilum (14% and 7%), Caldicoprobacter (5% and 8%) and Amphibacillus (2% and 4%). The frequency of Limnochordia MBA03 is of special interest, since this genus was observed in a cathodic enrichment culture in 2018 [ 31 ]. In a recent article, in which 20 biogas plants were compared, this organism was observed together with Methanosarcina , and a syntrophic relationship has been suggested between both of them [ 32 ]. The fact that Limnochordia MBA03 occurs both in the biochar particles and in the liquid phase could indicate that the biochar particles can also be used as conductive structures by microorganisms in the liquid phase. At this point, however, it cannot be ruled out that Limnochordia MBA03 also grows on other conductive structures or even without conductive structures, as this genus was also abundant in anaerobic digesters not treated with conductive particles [ 32 ]. Besides Limnochordia MBA03, the genus Proteiniphilum is another hint for electroactivity as this genus has been described within electroactive consortia [ 33 ]. Proteiniphilum is known to grow on nitrogen rich substrates (e.g., yeast, peptone). In the case of Proteiniphilum acetatigenes , this species is unable to grow on multiple carbohydrates, alcohols and fatty acids [ 34 ], suggesting an intense nitrogen metabolism within biochar particles. This might be explained by the fact that poultry manure, known for its high nitrogen content, was among the substrates that were fed into BGP1 (Table 2 ). Regarding the sludge samples, the ratio of Proteiniphilum was much lower in comparison to the biochar samples. On the other hand, the sludge samples displayed much higher ratios for Caldicoprobacter , a genus known to grow with high ammonium concentrations [ 35 ]. A reason for the shift from Caldicoprobacter to Proteiniphilum might be a local enrichment of ammonia in the biochar particles, which Proteiniphilum might tolerate better than Caldicoprobacter. Another explanation could be that nitrogen metabolism by Proteiniphilum was supported by electroactivity by electroactivity in the biochar particles, as it is well known that several amino acids are degraded in syntrophic relations [ 8 ]. It has been previously postulated that Caldicoprobacter is involved in syntrophic oxidation processes, but this has not yet been brought into connection with electroactivity [ 36 ]. Therefore, it could be possible that biochar particles increased the rate of DIET during nitrogen metabolism, which in turn caused a shift from Caldicoprobacter to Proteiniphilum. Although bacteria-specific primers were used (as described in Material and methods ), several archaea were recorded. One methanogen ( Methanoculleus ) was even among the most abundant prokaryotic genera (Fig. 6 ). The fact that mainly Methanoculleus was found is in accordance with above-described microscopic results, where mainly cocci were found. Taking into account that applied biochar particles may increase the rate of DIET, our results suggest that Methanoculleus may be involved in DIET. However, since Methanoculleus has not been described as capable to perform DIET so far, this needs to be further studied. Although the total number of methanogenic archaea found in biochar samples was lower than the number of archaea found in sludge—as measured by fluorescence microscopy—the relative abundance of Methanoculleus was higher in the biochar particles (2%) than in the sludge (less than 1%), supporting the previous hypothesis that biofilms on biochar particles are more involved in secondary fermentations steps (in syntrophic relation with methanogenesis). Fig. 6 Taxonomic profiles in sludge and biochar from BGP1 at genus level and obtained through 16S-rRNA gene amplicon high-throughput sequencing. For the sake of simplicity, only the most abundant genera are shown. Differences in the mean values that are significant are highlighted by yellow stars in the legend. Significances were analyzed using the DESeq2 differential abundance analysis [ 46 ] and p -values were < 0.05 Microbial diversity on biochar particles is increased To investigate whether microbial diversity differed between biochar particles and general sludge, the α- and β-diversity of both groups of samples were calculated (Fig. 7 ). The β-diversity is shown in a principal component analysis (PCoA) and indicates that the microbial communities of sludge samples and powdered biochar are substantially different from each other. Regarding archaea, the biochar samples analyzed in this work did not only display a higher relative abundance of Methanoculleus (Fig. 6 ), but also a higher α-diversity of methanogenic archaea (Fig. 7 A). Interestingly, this increased diversity was also observed when considering all prokaryotic genera (Fig. 7 B). There are several reasons, which might explain these observations. For example, the porous surface could facilitate biofilm formation, and adsorption might influence the microbial community as well. Due to adsorption, a local enrichment of salt and inhibitors might cause very harsh conditions in the biochar particles, forcing the involved microorganisms to continuously adapt. Although one might expect to obtain a lower diversity under harsh or even extreme conditions, some authors describe high diversities under extreme conditions. For example, it has been described that numerous alkaline and hypersaline environments show high microbial diversity, and that the adaptive mechanisms under extreme conditions can enable very useful capabilities, such as a “ control of membrane permeability, control of intracellular osmotic balance, and stability of the cell wall, intracellular proteins, and other cellular constituents ” [ 37 ]. Fig. 7 Microbial diversity in biochar particles on genus level: A α-diversity of archaea according to richness (Observed) and diversity indices (Shannon and Simpson); B α-diversity of all genera according to richness (Observed) and diversity indices (Shannon and Simpson); C β-diversity of all genera represented through a principal coordinates analysis Based on the aforementioned observations, it is possible to hypothesize that digester sludge provides a diverse microbial community, that is forced to develop adaptive mechanisms once they come into contact with the respective biochar particles. The aforementioned assumption that salt and inhibiting compounds are enriched in biochar particles is in agreement with the existing literature. For example, a recent study described that 5 different biochar types, which were evaluated as supplements for anaerobic digestion, retained Fe, Co, Ni and Mn [ 38 ]. Also, the potential enrichment of functional microbes has been previously suggested, particularly with respect to the stimulation of the secretion of extracellular polymeric substances (rapid sludge granulation), increased microbial abundance and improvement of DIET [ 39 ]. Interestingly, other authors have described an enrichment of Sporanaerobacter and Enterococcus , Methanosarcina [ 40 ] and Methanothrix [ 41 ] on biochar. In the present study, none of these genera were enriched. A reason for this difference might be that the biochar surface and the inner region of the biochar particles can be colonized differently. Although many of the articles discussed in a recent review [ 39 ] highlight an enrichment of Methanosarcinales , it is also mentioned that these species grow especially on the surface of biochar particles. In contrast, the inner regions might promote the growth cocci such as Methanoculleus , which are smaller than the threadlike or cluster-forming Methanosarcinales [ 39 ]."
} | 7,584 |
36604311 | PMC10034640 | pmc | 1,302 | {
"abstract": "Abstract In addition to being an important intermediate in the TCA cycle, L‐malate is also widely used in the chemical and beverage industries. Due to the resulting high demand, numerous studies investigated chemical methods to synthesize L‐malate from petrochemical resources, but such approaches are hampered by complex downstream processing and environmental pollution. Accordingly, there is an urgent need to develop microbial methods for environmentally‐friendly and economical L‐malate biosynthesis. The rapid progress and understanding of DNA manipulation, cell physiology, and cell metabolism can improve industrial L‐malate biosynthesis by applying intelligent biochemical strategies and advanced synthetic biology tools. In this paper, we mainly focused on biotechnological approaches for enhancing L‐malate synthesis, encompassing the microbial chassis, substrate utilization, synthesis pathway, fermentation regulation, and industrial application. This review emphasizes the application of novel metabolic engineering strategies and synthetic biology tools combined with a deep understanding of microbial physiology to improve industrial L‐malate biosynthesis in the future.",
"conclusion": "CONCLUDING REMARKS AND FUTURE PROSPECTS In this review, we comprehensively summarized the microbial biosynthesis of L‐malate from the aspects of chassis, substrate utilization, synthesis pathway, fermentation regulation and industrial applications. Although a large‐scale metabolic engineering strategy and microbial chassis strains were developed to efficiently synthesize L‐malate, there are still significant challenges facing the translation of microbial L‐malate production to the industrial scale. Therefore, future studies should further focus on the following aspects:\n Constructing a more efficient CO 2 sequestration system. This can mainly be achieved by enhancing the CO 2 fixation capacity and reducing CO 2 emissions to further increase the carbon yield of L‐malate synthesis. This strategy can not only enhance the yield of the L‐malate pathway, but it can also relieve global warming. This approach can be implemented by increasing the ATP and NADH pool based on a light‐driven CO 2 sequestration system to reinforce the L‐malate pathway yield. Finally, CO 2 fixation combined with the primary substrate utilization achieved an L‐malate yield of 1.48 mol/mol (Hu et al., 2021 ). Developing natural and artificial organelles for enhancing the carbon flux in the L‐malate pathway. Natural organelles, such as the mitochondria, endoplasmic reticulum, Golgi and carboxysomes, can be engineered to concentrate enzymes and increase the metabolic flux of key pathways in chemical synthesis (Avalos et al., 2013 ; Hammer & Avalos, 2017 ; Huang et al., 2018 ). In addition, artifical membrane‐less organelle, artificial mitochondria and artificial chloroplasts can be designed to compartmentalize target enzymes and supplying a specific environment, which will be conducive to highly efficient enzymatic reactions (Li, Feng, et al., 2018 ; Wang et al., 2022 ; Xu, Fei, et al., 2019 ; Xu, Shan, et al., 2019 ). Based on the available studies, the L‐malate pathway can be further enhanced by designing natural and artificial organelles. Improving the tolerance of production strains to extracellular environmental stress. Osmotic stress and acid stress may be the key factors that limit L‐malate production, as they are intrinsic to L‐malate accumulation. Therefore, it is necessary to improve the stress resistance of chassis cells (Guan & Liu, 2020 ; Polizzi & Kontoravdi, 2015 ; Sun et al., 2018 ). In general, resistance to high osmotic pressure is a desirable phenotype for strains used in the production of organic acids (Kwon et al., 2011 ). L‐malate and succinate fermentations are both faced with high osmotic stress during the late stages of the fermentation process. Previous studies added sulfur‐containing amino acids or overexpressed copper efflux genes to improve osmotolerance. Finally, a cusS mutant was introduced to increase the cell mass and succinate titre by 120% and 492% (Xiao et al., 2017 ). In addition to acid stress, the membrane integrity, membrane fluidity and membrane permeability can be disturbed due to L‐malate accumulation, which affects the membrane composition and membrane functions (Qi et al., 2019 ). For example, the physiological functions and productive capacity of C. glabrata were confirmed to be affected by L‐malate accumulation, and a dynamic tolerance system was constructed based on the transcription factors CgUSV1 and CgYAP3, combined with the L‐malate‐driven promoter Pcgr‐10 to improve the strain robustness. The L‐malate titre and productivity of the final strain 012 respectively reached 35.5 g/L and 0.33 g/L/h by applying this dynamic tolerance system (Liang et al., 2021 ). Constructing intelligent genetic circuits for regulating L‐malate synthesis. The L‐malate pathway flux is affected due to byproduct synthesis and irrelevant carbon waste, which can affect cell growth and chemical production (Zelle et al., 2008 ). Thus, regulating carbon flux with intelligent genetic circuits could further improve L‐malate synthesis (Gupta et al., 2017 ; Hou et al., 2020 ; Soma & Hanai, 2015 ). Spatiotemporal switches can assist the pathway‐independent dynamic regulation of chemical production, mainly using visible light regulation, temperature regulation and oxygen regulation (Moser et al., 2018 ; Yu et al., 2022 ; Zhao et al., 2018 ). For example, the pfkA gene in the EMP pathway and zwf gene in the PPP pathway were repressed using thermosensors coupled with a CRISPRi system to regulate the carbon flux of cell growth and increase the 2′‐fucosyllactose titre to 28.2 g/L (Yu et al., 2022 ).",
"introduction": "INTRODUCTION L‐malate, also known as 2‐hydroxy succinate, is a widely used food additive, as well as a valuable chemical and pharmaceutical intermediate (Chi et al., 2016 ; Iyyappan, Baskar, et al., 2019 ; Iyyappan, Bharathiraja, et al., 2019 ; Wang et al., 2013 ). As one of the C4‐dicarboxylic acids, L‐malate has a number of high‐value applications (Cao et al., 2020 ; Werpy, 2004 ). However, problems related to environmental pollution and resource waste are limiting the further application of chemical synthesis of L‐malate (Ahn et al., 2016 ; Ferone et al., 2019 ; Luo et al., 2021 ). Thus, new strategies for L‐malate synthesis should be economical and environmentally friendly (Li, Shen, et al., 2021 ; Li, Yang, et al., 2021 ). In this review, we comprehensively summarized recent advances in biotechnological approaches for L‐malate biosynthesis, including the microbial chassis (e.g. bacteria, yeast, Aspergillus sp., and other chassis strains), substrate utilization (e.g. carbon sources, nitrogen sources, and other substrates), synthesis pathway (TCA cycle, transport, and other pathways), fermentation regulation (process engineering and other fermentation factors), as well as industrial application (food additive, chemical, pharmaceutical industry). Furthermore, we discuss the future prospects of improving L‐malate synthesis by constructing a more efficient CO 2 sequestration system, developing Aspergillus oryzae as a novel chassis, improving the tolerance of the strain to environmental stress conditions, compartmentalizing key enzymes to enhance the biotransformation, and decoupling cell growth from L‐malate synthesis (Figure 1 ). FIGURE 1 Recent advances in producing L‐malate chassis, substrate, and pathway. The main advances were involved in microbial chassis, substrate utilization, synthesis pathway, fermentation regulation and industrial application."
} | 1,919 |
26934187 | PMC4774936 | pmc | 1,303 | {
"abstract": "Bacterial biofilms are usually assumed to originate from individual cells deposited on a surface. However, many biofilm-forming bacteria tend to aggregate in the planktonic phase so that it is possible that many natural and infectious biofilms originate wholly or partially from pre-formed cell aggregates. Here, we use agent-based computer simulations to investigate the role of pre-formed aggregates in biofilm development. Focusing on the initial shape the aggregate forms on the surface, we find that the degree of spreading of an aggregate on a surface can play an important role in determining its eventual fate during biofilm development. Specifically, initially spread aggregates perform better when competition with surrounding unaggregated bacterial cells is low, while initially rounded aggregates perform better when competition with surrounding unaggregated cells is high. These contrasting outcomes are governed by a trade-off between aggregate surface area and height. Our results provide new insight into biofilm formation and development, and reveal new factors that may be at play in the social evolution of biofilm communities.",
"introduction": "Introduction Surface-attached communities known as biofilms are believed to be the predominant mode of existence for bacteria in many environmental settings [ 1 ]. Understanding how biofilms establish and grow is also clinically important given their ubiquity in medical implant infections [ 2 ], chronic wounds [ 3 ], and in the respiratory tracts of cystic fibrosis patients [ 4 ]. In the clinical context, biofilm communities often show enhanced virulence [ 5 ], resistance to antibiotics [ 6 ], and resistance to the host immune system [ 7 ]. These features may be associated with the spatial structure of the biofilm, which not only affects material transport, e.g., penetration of nutrients/antibiotics, but is also associated with differences in metabolism and gene expression among cells within the community [ 8 , 9 ]. In the canonical picture of biofilm development, individual cells land on a surface, attach and proliferate to form first micro-colonies and later 3-dimensional structures [ 10 ]. However, bacteria are also known to form dense aggregated clumps when they are grown in liquid (planktonic phase) [ 11 – 13 ]. Moreover, cells often disperse from existing biofilms as clumps of aggregated cells. Thus it is very likely that when a biofilm forms, some cells may arrive on the surface already in an aggregated state. In support of this view, evidence exists for the seeding of infections by pathogenic bacteria already in an aggregated state [ 14 , 15 ], and bacterial aggregates are abundant in cystic fibrosis [ 4 , 5 ] and tuberculosis [ 16 ] infections. Having arrived on the surface, e.g., a plant leaf [ 17 ], a surgical implant [ 2 ] or an industrial component [ 18 ], it is to be expected that cells within a bacterial aggregate will have to compete during biofilm development, both with other aggregates and with initially non-aggregated cells, to which they may or may not be genetically related. We take a first step towards understanding the role of pre-formed aggregates in biofilm development by investigating this competitive process, using agent-based simulations. Such simulations, in which the spatial structure of a biofilm emerges from local interactions between individual cells, have become a staple tool for investigating biofilm structure and dynamics [ 19 – 21 ], as well as social evolutionary aspects of biofilm development [ 22 , 23 ]. Using this approach, we determine how a pre-existing aggregate of bacteria impacts the spatial structure of a biofilm, both in the presence and absence of competing unaggregated bacterial cells. Our main focus here is on the role of the initial shape of the aggregate. It is well known that bacterial interactions with a surface depend on features such as extra-cellular polymeric substances (EPS), presence of cell surface appendages (such as pili), and cell surface charge, which are species- and strain-dependent [ 24 ]. Moreover, soft-matter science has established that the nature of material-surface interactions can drastically affect the shape of fluid or semi-fluid droplets on surfaces [ 25 ]. It is therefore reasonable to suppose that in some circumstances, bacterial aggregates will spread out in contact with a surface, while in other scenarios, aggregates will adopt a more compact configuration. Here we investigate the biological consequences of aggregate shape in the seeding of biofilm growth. Simulating the development of biofilms initiated from initially spread or rounded aggregates, we find that the initial configuration of a bacterial aggregate on a surface is crucial in determining its eventual fate within the biofilm. In the absence of competitor cells on the surface, aggregates that maximise the extent to which they initially spread on the surface perform better than rounded ones because their initial access to nutrients (in the surrounding media) is greater. However when faced with strong competition from neighbouring unaggregated cells, initially rounded aggregates perform better over long durations, despite the fact that the rounded aggregate shape has a smaller surface area and hence a reduced exposure to nutrients. Importantly, we show that in an initially rounded aggregate, cells at the top of the aggregate proliferate at the expense of cells in the aggregate centre. This has interesting possible consequences for social evolution given that cooperation within clumps of aggregated cells has been suggested to be a stepping stone in the evolution of multicellularity [ 26 , 27 ]. Our study highlights the effects of nutrient gradients and bacterial aggregate shape on long-term biofilm development. Our work reveals that these factors alone can produce a trade-off between nutrient access and competition, with the balance between these factors depending sensitively on aggregate shape. While the link between biofilm spatial structure and nutrient access has been highlighted in many other studies [ 8 , 23 , 28 – 30 ], our work is the first to focus on the role of pre-formed aggregates in this context. Our study should help to decipher the role of pre-formed aggregates in biofilm infections. More generally, our findings emphasise the need to consider pre-formed aggregates in our current understanding of biofilm development.",
"discussion": "Discussion Given the tendency of many bacteria to aggregate, and the frequent observation of aggregates in diverse environmental situations [ 5 , 46 , 47 ], it seems likely that natural biofilms are often initiated from pre-formed aggregates. Despite this, the role of pre-formed aggregates in biofilm development has, to our knowledge, not yet been addressed. In this paper, we have investigated the fate of pre-aggregated cells during biofilm formation, using individual-based simulations. Our study shows that an initial aggregate can have a significant and long-lasting effect on biofilm spatial structure, even after many generations of cell growth. Focusing on the role of aggregate shape, we find that, in the absence of competition for nutrients from surrounding cells, an aggregate that is initially spread on the surface is favoured over one that is initially rounded even over long periods of biofilm development. This is likely to be because the spread aggregate has initially a larger surface over which it can absorb nutrients, giving it an initial growth advantage that is then maintained as the biofilm grows. Strikingly though, our results change qualitatively in the presence of competition from surrounding, unaggregated cells. When this competition is strong, although the spread aggregates still grow faster in the early stages of biofilm development, rounded aggregates become more successful (produce more progeny) as the biofilm develops over longer times. This effect appears to arise from a trade-off between height (as nutrients diffuse from above) and exposed surface area. In the absence of competition, surface area is more important than height, and the spread aggregate is favoured. However, in the presence of competition, height becomes more important, since cells at the top of the aggregate can avoid competing for nutrients with the surrounding competitors. Since the rounded aggregate is taller than the spread aggregate, it gains a “fitness” advantage under conditions of strong competition that is only realised after long times. Bacterial biofilm formation is a complex phenomenon which involves a plethora of biological mechanisms including cell motility [ 48 ], EPS production [ 49 , 50 ], metabolic and other phenotypic differentiation [ 9 , 47 , 51 ], and cell-cell interactions such as quorum sensing [ 52 – 54 ]. In our simulations, almost all of this biological complexity has been neglected; our model takes account only of nutrient gradients established by cell consumption, nutrient-dependent growth, and competition among cells for space. Nevertheless this simplistic approach produces biologically interesting, and potentially testable, predictions. In particular our simulations predict that being initially spread on a surface is a better strategy for a bacterial aggregate in the absence, but not in the presence, of competition. Understanding how further biological complexity might affect this picture would be a very interesting topic for further work. Another avenue worth investigating would be the effects of biofilm erosion and the subsequent detachment of cells. Here, our simulations have not included the effects of fluid flow, which among other effects, may flatten the biofilm by detaching protruding cells or clumps. In such cases, the initial height advantage of the rounded aggregate might be detrimental as its progeny cells are more likely to sloughed from the biofilm first. If however, it is desirable to colonise new surfaces, for instance downstream, then being sloughed off quickly might be beneficial. In reality, the effect of fluid flow on aggregated phenotypes within biofilms is much more complex because the cells within such aggregates may be more resistance to sloughing due to a high degree of cohesive interactions between the cells. How might aggregates of different shape arise in nature? It is well known that bacterial interactions with surfaces can vary greatly depending both on the physical and chemical properties of the surface [ 55 – 57 ], and on bacterial phenotypes such as EPS production and the presence of surface appendages. It is therefore very likely that aggregates formed from bacteria of different taxa or strains, landing on different surfaces, might adopt different configurations. For example, certain bacteria produce surfactant which can alter the morphology of a developing biofilm and allow them to expand over surfaces more efficiently [ 58 , 59 ]. Our work suggests that such spreading phenotypes might be selected for in environments where there is little competition for resources, whereas a more compact clumping phenotype would have a selective advantage in an environment where competition for resources is high. In high competition environments, manifestation of this clumping phenotype would no doubt involve the production of cohesive polymers such as extracellular DNA, proteins, and polysaccharides. Our work has been inspired by the observation that bacterial aggregates often form in the planktonic phase [ 11 – 13 ]. Aggregates are known also to form via the detachment of bacterial clumps from a mother biofilm [ 15 , 60 , 61 ]; should such aggregates land on a pristine surface, similar phenomena to those discussed here would be expected to arise. Moreover, our results could also be relevant to aggregates that form on the surface itself. In the classical picture of P . aeruginosa biofilm development, individual cells land on a surface, upon which they migrate and proliferate to form small aggregates (i.e. microcolonies). Surface-induced motility mechanisms [ 62 , 63 ] such as twitching [ 64 ], crawling [ 65 ] and walking [ 66 ] have been implicated in this process. Once formed, such small aggregates would compete with surrounding cells for nutrients in much the same way as the pre-formed aggregates that we have investigated in this paper. This study has focused on a single pre-formed aggregate seeding the surface and competing with initially unaggregated cells during biofilm formation. To further understand biofilms in nature, this work should be extended to investigate competition between multiple aggregates arranged on the surface, and competition between aggregates and mixed strains of bacteria, i.e., strains with different growth rates. Recently cooperation within clumps of aggregated cells has been suggested to be a stepping stone in the evolution of multicellularity [ 26 , 27 ]. Our study thus also hints that interesting social interactions might arise between cells within an aggregate. For all aggregate shapes, we observe heterogeneity in fitness among cells within the aggregate. This is particularly pronounced for the rounded aggregate, where cells at the top are strongly favoured while those in the centre of the aggregate hardly proliferate. Based on arguments recently put forward by West and Biernaskie [ 26 , 27 ], one might predict that rounded aggregates would be favourable under conditions where cells within the aggregate are closely related, whereas spread aggregates, in which fitness differences between cells are less pronounced, might form where cells are less closely related. This leads to interesting further questions, e.g., when a rounded aggregate initiates biofilm growth, do the majority of cells in the aggregate “sacrifice” their future progeny in favour of their kin at the top? This idea supports previous suggestions that height plays a crucial role in competition within biofilms [ 33 ]. While previous work pointed to EPS production as a means to push progeny cells above the surrounding competitors [ 33 , 67 ], our work shows that aggregate formation also provides a means to this end. Such a picture raises new questions about the evolutionary implications of bacterial aggregation."
} | 3,554 |
27213013 | PMC4874023 | pmc | 1,304 | {
"abstract": "Background Lignin content and structure are known to affect recalcitrance of lignocellulosic biomass to chemical/biochemical conversion. Previously, we identified rare Populus trichocarpa natural variants with significantly reduced lignin content. Because reduced lignin content may lower recalcitrance, 18 rare variants along with 4 comparators, and BESC standard Populus was analyzed for composition of structural carbohydrates and lignin. Sugar yields from these plants were measured at 5 process conditions: one for just enzymatic hydrolysis without pretreatment and four via our combined high-throughput hot water pretreatment and co-hydrolysis (HTPH) technique. Results Mean of glucan + xylan yields and the best glucan + xylan yield from rare natural poplar variants were 34 and 50 relative percent higher than the high lignin comparator (BESC-316) at the highest severity HTPH condition, respectively. The ability of HTPH to solubilize a large portion of xylan from solids led to small differences in xylan yields among poplar variants. However, HTPH showed large differences in glucan yields, and hence glucan + xylan yields, among the poplar variants. The high lignin comparator did not display lowest glucan + xylan yields with HTPH at moderate pretreatment severity compared to rare variants, but on the other hand, the low lignin comparator was a consistent top performer at all 5 process conditions. Furthermore, the low lignin comparator (GW-11012) showed a 15 absolute percent increase in glucan + xylan yield compared to the high lignin comparator at the most severe HTPH condition. Overall, relative variant rankings varied greatly with pretreatment severity, but poplar deconstruction was significantly enhanced when the pretreatment temperature was increased from 140 and 160 to 180 °C at the same pretreatment severity factor. Conclusions Glucan yields from high severity HTPH of rare natural poplar variants with reduced lignin content were significantly higher than from the high lignin comparator. Because of the significant effect of processing conditions on the performance rankings, selection of the best performing biofuel feedstocks should be based on sugar yields tested at conditions that represent industrial practice. From a feedstock perspective, the most consistent variants, SKWE-24-2 and GW-11012, provide key insights into the genetic improvement of versatile lignocellulosic biofuels feedstock varieties. Electronic supplementary material The online version of this article (doi:10.1186/s13068-016-0521-2) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusions There was an overall 10–17 absolute percent difference between minimum and maximum glucan + xylan yields for poplar variants at all process conditions. The mean of glucan + xylan yields and the best glucan + xylan yield from rare natural poplar variants were 34 and 50 relative percent higher than the high lignin comparator at the highest severity HTPH condition, respectively. Thus, these plants promise to be superior feedstocks for fungal enzyme processing into sugars that can be fermented into ethanol or other products. However, sugar yields from all poplar variants were higher for liquid hot water pretreatment applied at 180 °C than at 140 or 160 °C, even though the severity was held constant. Although the high recovery of xylan from all samples by HTPH resulted in small differences in xylan yields among poplar variants, there were large differences in glucan yields among poplar variants with HTPH. The negative effect of high lignin content on glucan + xylan yield was clear with HTPH at high severity but not at moderate severity. The low lignin comparator had one of the highest sugar yields for all process conditions. Moreover, the low lignin comparator achieved a 15 absolute percent increase in glucan + xylan yields compared to the high lignin comparator at the more severe 180 °C HTPH condition. Overall, the large variance in poplar variant ranks with processing conditions shown here indicates that the choice of poplar feedstocks should be based on tests that mimic expected operating conditions and not based on performance without pretreatment or fully optimized conditions.",
"discussion": "Results and discussion Figure 1 shows the distribution of the mass of structural components glucan, xylan, glucan + xylan, and Klason lignin (acid insoluble lignin) for each of the poplar variants harvested from Clatskanie before processing. The glucan composition ranged from 41 to 47 % with median and mean values of 43 and 44 %, respectively. The xylan contents in unpretreated variants were between 15 and 20 %, with the median and mean being 16 and 17 %, respectively. Taken together, the total glucan + xylan composition ranged from 58 to 65 %, with median and mean values of 59.5 and 60 %, respectively. It is interesting to note that the glucan and xylan amounts varied independently, that is to say, plants with the highest glucan content did not have the highest amount of xylan (data not shown). Also, although S. cerevisiae and other yeast can realize high ethanol titers from glucose, native yeast lack the ability to anaerobically metabolize pentose, and even though strains have been developed to co-utilize xylose and glucose [ 21 ], a high cellulose content in the raw material can still be beneficial for facilitating conversion to ethanol or other products [ 22 , 23 ]. The Klason lignin contents of the rare variants ranged between 18 and 21 % and were lower than for the BESC standard poplar (BESC STD). Both the mean and median lignin contents for the rare variants were the same: 19.8 %. On the other hand, the high lignin comparator, BESC-316, had 23.3 % lignin, almost 5 % more than in the low lignin comparator, GW-11012 (18.4 %) in raw biomass. The two other comparators (BESC-97 and GW-9762) had lignin contents toward the lower end of approximately 20 %. BESC STD had the highest lignin contents (24.5 %) among all the plants tested. An additional file presents a bar plot of the differences from the mean of lignin content for all plants (see Additional file 1 ). Fig. 1 Composition of poplar variants. From left to right , these graphs show glucan, xylan, glucan + xylan, and Klason lignin compositions, respectively, of the raw poplar variants. Open circles represent rare variants, solid circles represent the low lignin comparator (GW-11012), solid squares represent the high lignin comparator (BESC-316), and the triangle and polygon represent BESC-97 and GW-9762 comparators, respectively. BESC standard poplar is shown with a solid star . The square inside the box plot represents the mean values of the population. All samples except BESC standard were part of the descriptive box plot statistics Figure 2 shows the xylan yields for conditions A – E . For the entire population, xylan yields from enzymatic hydrolysis without pretreatment (condition A ) were poor, with the maximum yield of 2 % being achieved with 100 mg total protein loaded per gram glucan + xylan in unpretreated poplar. At any of the HTPH conditions B through E , there was about 4–6 absolute percent difference between minimum and maximum of xylan yields among samples (not including BESC standard). HTPH conditions B (140 °C), C (160 °C), and D (180 °C) are at the same pretreatment severity factor (logR 0 = 3.6). Among these conditions, xylan yields increased by 1 absolute percent when the temperature was raised from 140 to 160 °C, and by 2 absolute percent for increasing it from 160 to 180 °C. Near theoretical xylan yields could be achieved when the severity factor was increased from 3.6 to 4.0 (condition D – E ). It is interesting to note that although increasing severity enhanced xylan yields for all samples, the ability of hot water pretreatment to solubilize a large portion of the xylan in all conditions resulted in small differences in xylan yield among samples. Fig. 2 Effect of pretreatment on xylan yields from poplar variants. Five process conditions are shown. A sugar release from enzymatic hydrolysis for 120 h without prior pretreatment; B HTPH at 140 °C for 264.4 min (logR 0 = 3.6); C HTPH at 160 °C for 68.1 min (logR 0 = 3.6); D HTPH at 180 °C for 17.6 min (logR 0 = 3.6); and E HTPH at 180 °C for 44.1 min (logR 0 = 4.0). Co-hydrolysis for all HTPH conditions was performed for 24 h at an enzyme loading of 75 mg cellulase protein + 25 mg xylanase protein per gram glucan + xylan in raw biomass. Open circles represent rare variants, solid circles represent the low lignin comparator (GW-11012), solid squares represent the high lignin comparator (BESC-316), and the triangle and polygon represent BESC-97 and GW-9762 comparators, respectively. BESC standard is shown with a black star . The square inside the box plot represents the mean of the population. All samples except BESC standard were part of the descriptive box plot statistics Figures 3 and 4 show that glucan and glucan + xylan yields for 120 h of enzymatic hydrolysis without prior pretreatment (condition A ) ranged between 4 and 14 % and 6 and 16 %, respectively. The highest 14 % glucan yield and 16 % glucan + xylan yield achieved from the entire population were from one of the rare variants (GW-9920). For comparison of enzymatic hydrolysis yields without pretreatment, the BESC standard poplar had a maximum glucan + xylan yield of 6 %, the high lignin comparator BESC-316 had a similar yield of 6 %, and the low lignin comparator GW-11012 had a yield of 13 %. Thus, these data suggest that some degree of pretreatment is essential for poplar conversion by fungal enzymes to be economically viable, as the best total sugar yield achieved with enzymatic saccharification alone was only 16 % for GW-9920. We can see that solubilization of structural sugars is largely incomplete without pretreatment, even with such a large dose of fungal enzymes. On the other hand, near theoretical yields could be achieved for some of the samples by proper selection of pretreatment conditions (Fig. 4 , condition E ). Thus, the ability of aqueous pretreatments such as hot water and dilute acid to remove most of the xylan, alter lignin, and increase cellulose accessibility substantially improves sugar release by fungal enzymes [ 24 – 26 ]. Fig. 3 Effect of pretreatment on glucan yields from poplar variants. Five process conditions are shown. A sugar release from enzymatic hydrolysis for 120 h without prior pretreatment; B HTPH at 140 °C for 264.4 min (logR 0 = 3.6); C HTPH at 160 °C for 68.1 min (logR 0 = 3.6); D HTPH at 180 °C for 17.6 min (logR 0 = 3.6); and E HTPH at 180 °C for 44.1 min (logR 0 = 4.0). Co-hydrolysis for all HTPH conditions was performed for 24 h at an enzyme loading of 75 mg cellulase protein + 25 mg xylanase protein per gram glucan + xylan in raw biomass. Open circles represent rare variants, solid circles represent the low lignin comparator (GW-11012), solid squares represent the high lignin comparator (BESC-316), and the triangle and polygon represent BESC-97 and GW-9762 comparators, respectively. BESC standard is shown with a black star . The square inside the box plot represents the mean of the population. All plants except BESC standard were part of the descriptive box plot statistics Fig. 4 Effect of pretreatment on glucan + xylan yields from poplar variants. Five process conditions are shown. A sugar release from enzymatic hydrolysis for 120 h without prior pretreatment; B HTPH at 140 °C for 264.4 min (logR 0 = 3.6); C HTPH at 160 °C for 68.1 min (logR 0 = 3.6); D HTPH at 180 °C for 17.6 min (logR 0 = 3.6); and E HTPH at 180 °C for 44.1 min (logR 0 = 4.0). Co-hydrolysis for all HTPH conditions was performed for 24 h at an enzyme loading of 75 mg cellulase protein + 25 mg xylanase protein per gram glucan + xylan in raw biomass. Open circles represent rare variants, solid circles represent the low lignin comparator (GW-11012), solid squares represent the high lignin comparator (BESC-316), and the triangle and polygon represent BESC-97 and GW-9762 comparators, respectively. BESC standard is shown with a black star . The square inside the box plot represents the mean of the population. All plants except BESC standard were part of the descriptive box plot statistics At any of the conditions A – E, there was a 10–11 absolute percent and 10–17 absolute percent difference between minimum and maximum of glucan yields (Fig. 3 ) and glucan + xylan yields (Fig. 4 ), respectively, among samples (not including BESC standard). These figures show that yields of glucan or glucan + xylan changed little between conditions B (HTPH at 140 °C) and C (HTPH at 160 °C) that correspond to the same pretreatment severity factor (logR 0 = 3.6). In particular, the mean and median of glucan yields both increased by 3 absolute percent, and glucan + xylan yields increased by 3 absolute percent when the temperature was raised from 140 to 160 °C at the same severity factor. However, the situation changed when the HTPH temperature was increased to 180 °C (condition D ) at the same pretreatment severity factor. In this case, raising the temperature from 160 to 180 °C increased the mean and median of glucan yields by 5 absolute percent and glucan + xylan yields by 8 absolute percent. Figure 4 clearly shows that glucan + xylan yields for poplar varieties can easily be increased by 10 absolute percent or more by increasing the temperature to 180 °C (condition D ) from 140 °C ( B) or 160 °C ( C ). These results point to the need to better appreciate the meaning of the pretreatment severity factor that combines time and temperature into a single variable that can facilitate trade-offs between pretreatment time and temperature [ 17 ]. A key to this approach is that xylan release from cellulosic biomass can be modeled as a first-order reaction with a rate constant that has an Arrhenius temperature dependence. The value of 14.75 corresponds to the reaction rate doubling with a 10 °C temperature rise [ 12 ]. However, the significant increase in sugar yields at 180 °C (condition D ) compared to 140 °C (condition B ) and 160 °C (condition C ), shows that pretreatment severity factor cannot always correctly project how the reaction will respond to varying temperature. This outcome is not surprising in that it would be expected that the bonds between different constituents of the hemicellulose complex would have different activation energies. As a result, the rate constants for breaking these different bonds would not be necessarily expected to all follow the same 10 °C rule, with the outcome that states that yields were higher for pretreatment at 180 °C than at lower temperatures even though the severity factor was the same. Another important consideration was to understand how yields from the variants responded to an increase in severity factor. In this case, when the severity factor was increased from 3.6 to 4.0 (condition D to E ), overall glucan yields increased by about 10 absolute percent (Fig. 3 ). As previously mentioned, xylan yields jumped up by virtually 100 % (Fig. 2 ). As a result, the trends in glucan yield and glucan + xylan yields look somewhat similar at the high severity factor. Because almost all the glucan was conserved in the solids produced by hot water pretreatment at the conditions tested (data not shown) and poplar contains far more glucan than xylan yield, glucan + xylan yields were largely determined by glucan yields from enzymatic hydrolysis. In addition, the fact that xylan yields were virtually 100 % of theoretical for many of the variants at condition E , up to 99 % of theoretical glucan + xylan yields could be achieved for one of the rare variants (BESC-35), followed by 94 % from SKWE 24-2. Figures 2 , 3 , 4 as well as Tables 2 and 3 show that many of the variants with reduced lignin content can be high sugar-yielding candidates compared to BESC standard poplar. Going in order from conditions A to E, first with just enzymatic hydrolysis without pretreatment and then with increasing temperature at the same severity and followed lastly by a higher severity at the highest temperature shows that the mean of glucan yields from rare variants increased from 3 to 16 absolute percent compared to standard poplar, the mean of xylan yields for the same variants increased from 1 to 4 absolute percent, and the mean of glucan + xylan yields rose from 3 to 20 absolute percent. It can be seen from Table 3 that the highest glucan + xylan yield from rare variants can be as high as 26 absolute percent and 77 relative percent compared to standard poplar. The relative increase in sugar yields for the rare variants increased in moving to condition B (140 °C) followed by conditions C (160 °C) and D (180 °C) for the same severity and E for a higher severity at (180 °C). Both Table 2 and 3 show that within the four HTPH conditions, the relative yield increase dropped in going from condition B to E . It is important to note that rare variants showed a greater relative increase in sugar yields at lower temperatures than standard poplar. Table 2 Relative and absolute percent changes in the mean of sugar yields among rare variants compared to the high lignin comparator, low lignin comparator, and BESC standard poplar Condition Condition details High lignin comparator Low lignin comparator Standard poplar Glucan Xylan Glucan + xylan Glucan Xylan Glucan + xylan Glucan Xylan Glucan + xylan A No pretreatment enzymatic hydrolysis 59 (3) a \n 44 (1) 56 (4) −30 (−4) −6 (−1) −27 (−4) 44 (3) 30 (1) 42 (3) B HTPH 140 °C logR 0 = 3.6 −3 (−1) −2 (−1) −3 (−1) −18 (−4) 4 (1) −11 (−4) 181 (12) 80 (5) 131 (17) C HTPH 160 °C logR 0 = 3.6 12 (−3) −9 (−2) −11 (−4) −18 (−5) 1 (1) −12 (−5) 137 (12) 51 (4) 95 (16) D HTPH 180 °C logR 0 = 3.6 −2 (−1) 3 (1) 1 (1) −22 (−7) −7 (−1) −17 (−8) 106 (14) 33 (4) 73 (17) E HTPH 180 °C logR 0 = 4.0 44 (11) 17 (3) 34 (14) −13 (−5) 6 (1) −8 (−4) 80 (16) 27 (4) 59 (20) \n a Values in parentheses represent absolute change Table 3 Relative and absolute percent changes in best sugar yields among rare variants compared to the high lignin comparator, low lignin comparator, and BESC standard poplar Condition Condition details High lignin comparator Low lignin comparator Standard poplar Glucan Xylan Glucan + xylan Glucan Xylan Glucan + xylan Glucan Xylan Glucan + xylan \n A \n No pretreatment enzymatic hydrolysis 188 (10) a \n 111 (2) 161 (10) 29 (4) 39 (1) 24 (4) 161 (9) 92 (2) 137 (10) \n B \n HTPH 140 °C logR 0 = 3.6 34 (7) 22 (3) 26 (8) 14 (3) 29 (4) 16 (5) 287 (19) 123 (8) 196 (25) \n C \n HTPH 160 °C logR 0 = 3.6 11 (3) 7 (1) 9 (4) 3 (1) 18 (3) 8 (3) 196 (17) 75 (6) 137 (23) \n D \n HTPH 180 °C logR 0 = 3.6 17 (5) 17 (3) 17 (7) −8 (−3) 7 (1) −4 (−2) 141 (18) 51 (6) 100 (23) \n E \n HTPH 180 °C logR 0 = 4.0 64 (16) 29 (5) 50 (20) 1 (1) 16 (3) 4 (3) 105 (21) 40 (6) 77 (26) \n a Values in parentheses represent absolute change As shown in Tables 2 and 3 , the mean and maximum glucan + xylan yields from rare variants increased by a relative 34 and 50 %, respectively, compared to the high lignin comparator (BESC-316) at condition E . For the high lignin comparator BESC-316, low glucan and glucan + xylan yields were only clearly evident at condition A , where yields were less than the 25 % percentile, and condition E where it was an outlier. For conditions B , C, and D that all were at a logR 0 of 3.6, its yields were not the lowest in the population. At condition B , the yield of the high lignin comparator was close to the population median. At condition C, its yield rose above the 75 percentile and dropped down to close to the median (50 % percentile) at condition D . Some of the rare variants had significantly lower sugar yields than the high lignin comparator at these conditions. The box plots in Figs. 3 and 4 show that glucan and glucan + xylan yields for the low lignin comparator (GW-11012) were above the 75 percentile of the population for all conditions A – E . The absolute and relative change in the mean of glucan + xylan yields from rare variants were negative compared to the low lignin comparator (GW-11012) (Table 2 ), as GW-11012 had one of the highest glucan + xylan yields (Fig. 4 ). At conditions D and E, it ranked highest in glucan yield among all samples. However, some of the rare variants gave 4 to 24 % higher relative glucan + xylan yields than the low lignin comparator (Table 3 ). The same three conditions in Fig. 3 show that the differences in glucan yields between low and high lignin comparator were only 2 to 3 absolute percent at the lower temperatures B (140 °C) and C (160 °C) but increased to 7 absolute percent at D (180 °C). At the higher severity factor condition E , this difference increased to 15 absolute percent. Going back to the plot for the distribution of Klason lignin content in Fig. 1 , we see that lignin contents for rare variants and three comparators (GW-11012, BESC-97, and GW-9762) are within a range of 3 absolute percent. These samples with only a 3 absolute percent difference in lignin content were found to have a 10 absolute percent variation in glucan + xylan yields. One of the rare variants (CHWH-27-2, Additional file 1 ) had a lignin content lower than but close to the low lignin comparator (GW-11012). Thus, although these rare variants might share common mutations, variation in sugar yields can be attributable to other genetic differences such that factors other than lignin content alone have significant effects on deconstruction. Standard poplar had an almost 5 absolute percent higher lignin content (24.5 %) than the mean of lignin contents of the rare variants (19.8 %) but was similar to that for the high lignin comparator BESC-316 (23.3 %). In fact, BESC standard poplar showed such a low sugar yield that statistical analysis found it to be an outlier at all conditions compared to any of the variants, including the comparators. One would expect that if only lignin content affected sugar yields, then BESC-316 and BESC STD would exhibit similar yields, but this was clearly not the case as the glucan + xylan yields for BESC-316 were 6 to 19 absolute percent higher than for BESC STD for the full range of HTPH conditions B – E . Since the BESC STD was a much older plant at harvest and grown at a different site than all other poplar variants in this study (rare variants + comparators), these observations suggest that environmental factors, harvest age, growth site, harvest season, climate, and soil conditions could affect phenotypic plasticity and cause significant difference cell wall characteristics and subsequent sugar yields [ 27 , 28 ]. Although standard poplar is not a true comparator to the variants, the differences in yields still point to an important result: there can be extreme differences in sugar yields within the same species, possibly due to differences in age or phenotypic plasticity. However, the significant differences in performance for samples grown, harvested, and processed under the same conditions suggest that genetic variability confers major differences in cell wall recalcitrance and provides opportunities for improving lignocellulosic biofuel feedstocks. As noted earlier, xylan yields did not change noticeably with plant variety in that a high percentage of xylan was always recovered. Thus, as shown in Fig. 2 , trends in xylan yields from low to high lignin comparators was unclear for lower temperature pretreatments at a severity parameter of 3.6 (conditions B and C ). In fact, the high lignin comparator BESC-316 produced about a 1 absolute percent higher xylan yield than the low lignin comparator GW-11012 for these two conditions. However, for both low severity (condition D ) and high severity (condition E ) pretreatments at 180 °C, the low lignin comparator had about 1 absolute percent higher xylan yields than from the high lignin comparator. Xylan yields as a percentage of the theoretical maximum were 85 and 91 % from the high and low lignin comparators, respectively, at condition D and increased to 91 and 99 %, in that order, at condition E . Overall, glucan + xylan yields were much greater from the low lignin comparator than from the high lignin comparator due to larger differences in glucan yields rather than xylan yields. At the most severe HTPH (condition E ), the theoretical glucan + xylan yields ranged from 73 to 99 % for the rare variants (data not shown), but the range dropped to 47 to 76 % (data not shown) at the lower severity factor condition D even though the temperature was the same. The two comparators, GW-9762 and BESC-97, had lignin contents and sugar yields similar to the rare variants. Figure 5 summarizes the overall ranking of glucan + xylan yields for all the samples included in this study. We can clearly see that glucan, xylan, and glucan + xylan yield ranks changed drastically with process conditions. For example, GW-9920 ranked 1st in glucan + xylan yield for enzymatic hydrolysis without prior pretreatment (condition A ) but dropped to 19th out of 22 total for high severity pretreatment at 180 °C (condition E ). On the other hand, the glucan + xylan yield rank of BESC-35 rose from 11 to 1 when moving from condition A to condition E . Thus, we can see that within the range of pretreatment conditions applied, severity factor and temperature both impacted sugar yield ranks. Low lignin comparator GW-11012 was one of the more consistent performers in that glucan + xylan ranks stayed between 1 and 6 out of 22 for all five process conditions. Rare variant SKWE 24-2 was also a consistent top performer as it displayed a high rank among the pretreatment conditions but average without pretreatment. Fig. 5 \n Graphs 1, 2, and 3 represent the total glucan + xylan yield ranks for 22 variants from at different processing conditions. The highest yield is rank as 1, and the lowest yield is ranked as 22. Conditions from left to right are ( 1 ) enzymatic hydrolysis for 120 h without prior pretreatment, ( 2 ) HTPH at 140 °C for 264.4 min (logR 0 = 3.6), ( 3 ) HTPH at 160 °C for 68.1 min (logR 0 = 3.6), (4) HTPH at 180 °C for 17.6 min (logR 0 = 3.6), and (5) HTPH at 180 °C for 44.1 min (logR 0 = 4.0). Enzymatic hydrolysis for all HTPH experiments was applied for 24 h. The enzyme loading for all conditions was 75 mg cellulase protein + 25 mg xylanase protein per gram glucan + xylan in the raw biomass Figure 5 also shows that although CHWH-27-2 produced 3rd from the best yields when enzymatically hydrolyzed without prior pretreatment (condition A ), its performance fell to 9th when subjected to the highest severity pretreatment prior to enzymatic hydrolysis (condition E ). On the other hand, the yield from the low lignin comparator GW-11012 rose from the 4th rank without pretreatment (condition A ) to 3rd rank at for the most severe pretreatment (condition E ). This shift in performance strongly suggests that factors other than lignin content have a major impact on sugar yields. It is important to remember that the lignin wall in lignocellulosic biomass can be viewed in terms of three major characteristics: lignin amount, lignin strength, and lignin location. For the first, high lignin contents have been shown to negatively affect sugar yields [ 12 ]. Strength, the second characteristic, depends on several underlying factors that affect nature of bonding. For one, the ratio of syringyl to guaiacyl units (S/G) affects the strength of lignin bonds in that the higher S/G ratios increase carbon to oxygen (β-O-4) linkages that are more susceptible to breakdown than carbon to such carbon bonds as β-β, β-5, β-1, and 5-5 [ 29 , 30 ]. Interactions with carbohydrates in lignin-carbohydrate complexes (LCC) also affect lignin strength [ 31 ]. The third category, location, refers to lignin distribution in native plant cell walls. Complex bond cleavage and re-association reactions occur in lignin when biomass is subjected to such high temperature processes as aqueous pretreatment. These reactions alter lignin distribution and are thought to move lignin from the interior of cell walls to the outer surface where it can still affect enzymatic deconstruction of cellulose [ 32 , 33 ]. The shift in one or more of these lignin attributes might be responsible for the high lignin comparator showing poor relative performance without pretreatment (condition A ) and for high severity HTPH at 180 °C (condition E ) while still performing relatively well when pretreated at moderate severity conditions ( B , C, and D ). This result also suggests that high lignin content may not universally result in very low yields within plant populations. These findings indicate that the optimum processing conditions can vary considerably even for a single species of plants. That is to say, plants that perform well without pretreatment may not perform best with pretreatment because yields are too low to be economically attractive without pretreatment for all the poplar varieties tested with fungal enzymes. Thus, making choices based on results from enzymatic hydrolysis without pretreatment is likely to eliminate feedstocks that have the greatest yield potential. Therefore, screening of plants for top candidates for cellulosic ethanol or biomass-derived products should be based on tests that mimic processing conditions to be applied in a commercial-scale biofuels plant."
} | 7,414 |
34522851 | PMC8426204 | pmc | 1,305 | {
"abstract": "Summary Biomethane is suggested as an advanced biofuel for the hard-to-abate sectors such as heavy transport. However, future systems that optimize the resource and production of biomethane have yet to be definitively defined. This paper assesses the opportunity of integrating anaerobic digestion (AD) with three emerging bioelectrochemical technologies in a circular cascading bioeconomy, including for power-to-gas AD (P2G-AD), microbial electrolysis cell AD (MEC-AD), and AD microbial electrosynthesis (AD-MES). The mass and energy flow of the three bioelectrochemical systems are compared with the conventional AD amine scrubber system depending on the availability of renewable electricity. An energy balance assessment indicates that P2G-AD, MEC-AD, and AD-MES circular cascading bioelectrochemical systems gain positive energy outputs by using electricity that would have been curtailed or constrained (equivalent to a primary energy factor of zero). This analysis of technological innovation, aids in the design of future cascading circular biosystems to produce sustainable advanced biofuels.",
"conclusion": "Conclusions Three future bioelectrochemical circular cascading systems with different configurations (P2G-AD, MEC-AD, and AD-MES) have been modeled and assessed in terms of the potential to reduce carbon emissions and maximize biomethane production. Mass flows show the highest modeled methane production (4943.3 Nm 3 per 100 t fresh weight grass silage normalized to 8% TS) in the MEC-AD system compared to the P2G-AD and AD-MES systems, possibly due to the potential for an efficient CO 2 -to-CH 4 conversion in a single integrated reactor. By the year 2050, when all electricity is proposed to come from renewables, the MEC-AD system is modeled as presenting the highest NEB value (NEB 25.1 MWh, primary energy input 22.4 MWh, primary energy output 47.5 MWh, as averaged by five selected feedstocks) compared to the conventional AD-amine scrubber (NEB 18.4 MWh, primary energy input 7.2 MWh, primary energy output 25.6 MWh, as averaged by five selected feedstocks). However, the theoretical maximum energy return of the MEC-AD system can only be achieved in a highly elaborate reactor at the limit of its potential. In contrast, the P2G-AD and AD-MES systems employ two reactors each for easier operation and control. P2G-AD, MEC-AD, and AD-MES cascading biosystems all gain positive energy returns when the electricity source would otherwise have been curtailed or constrained as defined by a PEF of zero. The electricity source is postulated to be the fundamental limitation on the sustainable commercial application of P2G-AD and AD-MES. This analysis aids in the decision process of how best to integrate the electricity grid into the production of advanced biofuels. Nonetheless, much remains to be optimized to bring these emerging bioelectrochemical technologies to possible industrial application. For example, a high applied voltage would be required to overcome the overpotential which means more input energy consumption than the theoretical requirement. Furthermore, the instability of microbial communities under an external voltage during long-term operation might result in sub-optimal reactor performance and low production rates of end-products in MES/MEC for an industrial process. Ultimately, both out of the box thinking and solid evidence of successful bioelectrochemical cascading circular systems are required to approach competitiveness in biogas production and upgrading.",
"introduction": "Introduction The EU-27 has targeted a complete transition to a sustainable energy landscape by 2050 ( Colmenar-Santos et al., 2019 ) in which all grid electricity will be supplied by renewable energy. However, the hard-to-abate sectors such as freight haulage, airlines, and shipping are not readily electrified. The development of advanced biofuels (such as biomethane) may provide flexibility in the progression of the European economy toward more sustainable use of renewable resources. The EU Renewable Energy Directive mandates a minimum share of advanced biofuels for transport of at least 3.5% in 2030 ( Giuntoli, 2018 ). By 2040, Europe aims to have 10% biomethane in gas grids on a volume basis ( IEA, 2020 ). The International Energy Agency (IEA) has assessed that the full utilization of sustainable biomethane could cover approximately 20% of today's worldwide gas demand ( IEA, 2020 ). Therefore, to maximize the potential of advanced biofuels, a roadmap for technology advances in the production of biofuels must be developed. Anaerobic digestion (AD) is a proven technology for producing biogas, which can be upgraded to biomethane (aka green gas) as a renewable energy vector. By the end of 2019, there were a total of 18,943 biogas plants and 725 biomethane plants across Europe according to the European Biogas Association Statistical Report 2020 ( EBA, 2020 ). It is predicted that the potential for global biogas will be 50% larger than today by 2040 due to the growing supply of available feedstocks ( IEA, 2020 ); this could enable the production of biomethane for use as an advanced renewable transportation fuel ( Ahlström et al., 2020 ). In addition to biogas production, the digestate produced in AD can be used to return essential nutrients to farmland in the form of organic fertilizer. The authors postulate that a beneficial use of on-farm feedstocks, cultivated marine feedstocks, and municipal wastes is in a sustainable closed-loop system which can generate revenues from the sale of renewable energy and biofertilizer ( Allen et al., 2016 ; Tabassum et al., 2016 ; Wall et al., 2013 ). However, most current digesters are implemented as stand-alone AD systems without optimization of circularity in system design. The implementation of conventional AD faces several challenges: the biodegradability of on-farm feedstocks (such as animal slurry, crop straws, and late-cut grass) can be low (less than 50%) in digesters; the energy contained within lignin and cellulose portions of the digestate cannot be fully utilized; and effective and economical approaches to biogas upgrading are challenging ( Allen et al., 2015 ; Pecchi and Baratieri, 2019 ; Ullah Khan et al., 2017 ). The composition of typical raw biogas from AD plants is 60–70% CH 4 , 30–40% CO 2, with small amounts of H 2 S, N 2, NH 3 , and water vapor ( Jönsson et al., 2003 ). In order to produce biomethane with a high CH 4 purity, techniques for biogas upgrading are mainly divided into two categories: CO 2 removal based processes, such as water/amine scrubbing, cryogenic separation, pressure swing adsorption, and membranes ( Nguyen et al., 2020 ); and CO 2 -hydrogenation-based processes, through various methods such as photocatalysis, electrocatalysis, biocatalysis, and heterogeneous catalysis. The combination of biocatalysis and electrocatalysis in bioelectrochemical systems (BESs) powered by renewable electricity sourced from wind turbines or solar PV ( Fu et al., 2020 ) may be used to directly reduce CO 2 to methane or provide H 2 which hydrogenates CO 2 into methane. Compared with CO 2 -removal-based technologies, CO 2 hydrogenation is advantageous due to the conversion of CO 2 to CH 4 , resulting in increased biomethane production. The integration of renewable electricity with AD may significantly improve the biomethane yield, whilst achieving simultaneous biogas production and upgrading; however, the economic feasibility of such methods would need to be addressed ( Rajendran et al., 2019 ; Vo et al., 2018 ). Furthermore, to realize deep sustainability in a circular system with synergistic utilization of by-products and residual streams, the supply of “surplus” renewable electricity would be a significant challenge since curtailed or constrained electricity is typically intermittent. In a typical BES system, electromethanogenesis is a biocathodic reaction whereby the electrical current and CO 2 can be converted to methane in the presence of biocatalysts, namely methanogens ( Blasco-Gómez et al., 2017 ; Cheng et al., 2009 ). BESs can realize this electrical-to-chemical energy conversion as a promising “power to methane” technology for renewable energy storage. Currently, Norway has a 98% share of electrical energy supply acquired from renewable sources, while in Iceland, up to 85% of the total primary energy supply comes from renewable sources. By availing of renewable electricity, synergies between bioelectrochemical and AD technologies can be expected with promising advantages in accelerating the degradation of COD or VFAs, enhancing methanogenesis and biogas production ( De Vrieze et al., 2018 ; Zakaria et al., 2020 ). The synergistic systems involve the engagement of the whole biomass-to-energy supply chain: biomethanation is optimized and harnessed as renewable energy, and natural resources such as biofertilizers are produced. However, other issues need to be addressed for its further practical development, such as energy conversion efficiency, system scale-up, reactor configuration, and economic feasibility ( Huang et al., 2020 ; Jourdin and Burdyny, 2020 ; Prévoteau et al., 2020 ; Salimijazi et al., 2020 ). A current research gap lies in the deep understanding of potentially innovative bioelectrochemical circular cascading systems with different configurations that enable maximum biomethane production. To address this gap, this paper proposes and contrasts AD-based systems integrated with power to gas (P2G), microbial electrolysis cell (MEC), and microbial electrosynthesis (MES) ( Figure 1 ). The advantages and challenges of the proposed systems are assessed to determine the optimal biomethane production scenario and to inform any larger-scale applications in the future. The objectives of this paper are to: (1) evaluate sustainable feedstocks for enhanced biogas production in a temperate oceanic climate context; (2) provide a state-of-the-art analysis of bioelectrochemical biogas upgrading technologies including P2G, MEC, and MES; (3) provide quantitative analysis of future AD-based circular cascading systems (namely P2G-AD, MEC-AD, and AD-MES) beyond 2025 in terms of mass balance and energy return. Figure 1 Different systems for biogas production and upgrading Three bioelectrochemical circular cascading systems with anaerobic digestion (AD) as a key platform integrated in turn with power to gas (P2G), microbial electrolysis cell (MEC) and microbial electrosynthesis (MES)."
} | 2,620 |
38113265 | PMC10756270 | pmc | 1,306 | {
"abstract": "Significance Coral reefs are in jeopardy as climate change leads to increasingly frequent marine heatwaves. Some corals survive these extreme events, and this exposure may prime corals to increase their heat tolerance. Yet, as the time between heatwaves decreases, the accumulation of stress experienced may preclude opportunities for beneficial gains in heat tolerance. This nearly decade-long study revealed that repetitive exposure to heatwaves leads to divergent coral bleaching and recovery trajectories. Some corals increased bleaching resistance and demonstrated physiological recovery, whereas others exhibited alarming seasonal bleaching and accumulating mortality without heat stress following successive heatwaves. As the climate continues to change, surviving corals must not only gain heat tolerance but also rapidly recover to maintain critical ecosystem services that humans rely on.",
"conclusion": "Conclusions. We have entered a new era of ocean warming that is affecting coral reefs in ways we are only just beginning to understand. Corals in the Main Hawaiian Islands have experienced a rise in offshore sea-surface temperatures of 1.15 °C in the last 60 y ( 64 , 65 ), leading to an unprecedented three coral bleaching events in the last decade (2014 to 2023) that were preceded by a single widespread coral bleaching event (1996) the entire century prior ( 57 , 66 ). The responses of individual corals to these increasingly frequent heatwaves demonstrate the divergent intra- and interspecific bleaching and recovery trajectories possible within a single coral community, highlighting the challenge of predicting future coral performance in a changing ocean. In one direction, P. compressa that were highly sensitive to marine heatwaves in 2014 and 2015 (i.e., severely bleached) have become visually and physiologically indistinguishable from bleaching-resistant conspecifics during a third heatwave (2019) and during extreme heat stress tests, indicating beneficial acclimatization that persists across many years. This increase in bleaching resistance was accompanied by rapid physiological recovery after repeat heat stress, although there remained evidence of persistent stress (e.g., weakened skeletons), suggesting that these corals may undergo tradeoffs that can erode ecosystem function. Increases in coral bleaching resistance across recurring heatwaves have become more prevalent on reefs across the globe ( 15 , 17 , 19 , 21 ), which is encouraging, as avoiding bleaching is often associated with greater survival ( 33 ) and stress hardening may thus promote the persistence of corals in our warming oceans. On the other hand, the extent of coral mortality has been increasing with each successive heatwave in this system, from <1% in 1996 to 13% in 2014, 22% in 2015, and >20% in 2019 ( 56 , 67 ). Furthermore, bleaching-susceptible M. capitata are visibly struggling from the recent barrage of heatwaves, manifesting as annual seasonal bleaching and escalating partial mortality in the absence of measurable heat stress. Importantly, even bleaching resistance was not associated with greater survival or recovery capacity in M. capitata , highlighting the danger of predicting future individual performance and reef function from a lack of visual bleaching alone. The inability of M. capitata of either bleaching phenotype to recover physiologically after 3 y following a repeat heatwave underscores that coral resilience is a multifaceted trait beyond bleaching resistance ( 60 ) and brings into question how we define coral resilience in the context of global change. Now, more than ever, seasonal and long-term studies are critically needed to identify corals that cannot just withstand and survive repeated heat stress events, but also rapidly recover ecosystem-defining traits (e.g., biomineralization) to continue providing the critical ecosystem services coastal communities directly rely on. Urgent, collective global action to eliminate greenhouse gas emissions remains the only approach that may provide sufficient time for corals to acclimatize and adapt to rapid climate-induced temperature increases in order for coral reef ecosystems to persist in the Anthropocene.",
"discussion": "Discussion Legacy Effects of Successive Heatwaves Have Led to Annual Bleaching in Susceptible M. capitata . Bleaching-susceptible colonies of M. capitata are now experiencing annual seasonal bleaching in the absence of anomalously high temperatures after a decade that included three marine heatwaves. This phenomenon was initially observed in the first summer following the 2015 heatwave and was likely exacerbated by the combined impacts of the back-to-back heatwaves in 2014 and 2015 ( 36 , 37 ). Encouragingly, in the second year after that heatwave, bleaching-susceptible M. capitata regained pigmentation over the winter and did not bleach again the following fall, indicating a ~2-y recovery period. Yet, when faced with a third marine heatwave just 4 y later (2019), these same M. capitata colonies bleached again even though the heatwave was less severe. Declining performance in response to a second heatwave has been observed in corals from Australia ( 29 ) to the Caribbean ( 28 ); however, that bleaching-susceptible M. capitata colonies repeatedly bleached during each of the three summers following the 2019 event, in the absence of thermal stress, is alarming. While seasonal declines in coral biomass and symbiont density during summer temperatures are common ( 38 , 39 ), they do not typically lead to the visually apparent bleaching observed here. These results indicate that the frequency of heatwaves in Hawai’i over the past decade has compounded the stress experienced by susceptible corals, leading to persistent declines in performance under ambient conditions. Furthermore, bleaching-susceptible individuals had higher partial mortality (~20%) than bleaching-resistant conspecifics (<5%) following the 2015 heatwave ( 33 ), underscoring the ecological significance of these differential responses. Encouragingly, bleaching-resistant individuals within this same population of M. capitata have remained consistently pigmented across multiple heatwaves and were 0.5 °C more heat tolerant than bleaching-susceptible conspecifics 3 y after the 2019 event. However, higher bleaching thresholds surprisingly did not translate into greater survival in the 3 y following the 2019 heatwave, indicating that the accumulation of stress following three successive heatwaves in under a decade negated the survival benefits of bleaching-resistance. Physiological data further confirmed that resistance to bleaching in M. capitata was not a sufficient measure of coral performance. Specifically, we observed incomplete recovery across multiple phenotypic and physiological metrics in both bleaching-resistant and bleaching-susceptible individuals in the 3 y following the 2019 marine heatwave, highlighting a legacy of stress that transcended visual bleaching assessments and persisted for several years. For example, neither phenotype exhibited complete recovery in symbiont or host protein densities during the 3-y period following the 2019 heatwave. At their peak (after 35 mo of recovery), symbiont densities only reached up to half of preheatwave densities [January 2014: 4 to 5 × 10 6 cells cm −2 ( 40 )]. Given the ongoing upward trajectory, symbiont recovery will likely continue so long as another heatwave does not occur. These results underscore that physiological recovery can be a multiyear process, even when visual recovery is apparent within a few weeks to months following heat stress ( 37 , 41 ). Interestingly, not all physiological parameters demonstrated a lag in recovery, with tissue biomass and lipid densities displaying apparent recovery followed by strong seasonality in the first year post heat stress. However, traits important for coral fitness, such as growth and fecundity, can take 4 y or more to recover following heat stress ( 18 , 42 – 44 ). Long-term investigations are clearly needed to observe recovery in metrics closely linked to fitness as marine heatwaves continue to increase in frequency and severity, and thus increasingly overlap with the time required by many corals to fully recover. Decreasing duration of periods of relief from thermal stress can compound physiological stress in many surviving corals, which may alter their relative performance and survival within communities ( 30 ) and will have important ramifications for community composition and ecosystem function. A better understanding of the mechanisms driving bleaching resistance may help predict the fate of corals in future reefs. For example, thermal tolerance in M. capitata is associated with a combination of host ( 31 ) and symbiont ( 45 ) factors. In Kāne‘ohe Bay, M. capitata can host Cladocopium (ITS2-type “C31”) and Durusdinium glynnii ( 46 – 48 ), and bleaching resistance is strongly correlated with higher proportions of D. glynnii ( 45 ). Indeed, the bleaching-susceptible colonies observed here hosted almost exclusively Cladocopium spp., while bleaching-resistant colonies predominantly hosted D. glynnii ( 31 , 49 ) ( SI Appendix , Table S11 ). Both phenotypes exhibited additional physiological signatures of Cladocopium - or Durusdinium -dominated symbioses, respectively. For example, bleaching-susceptible M. capitata had nearly half as many symbionts as bleaching-resistant colonies across all seasons, matching observations that Cladocopium -dominated M. capitata tend to have lower symbiont densities than Durusdinium -dominated colonies ( 34 , 37 ). While Durusdinium -dominated M. capitata were able to maintain bleaching resistance and higher symbiont densities, D. glynnii generally provides the host with fewer resources than Cladocopium spp. under both ambient and heat stress conditions ( 50 ), indicating that symbiont retention during heat stress is an incomplete measure of coral performance. However, the nutritional benefits of hosting Cladocopium spp. may diminish over time as heatwaves and bleaching become increasingly common, and the impacts of changing symbiont dominance on coral growth and survival, and thus ecosystem function, require further study. Environmental Memory of Heatwaves Has Led to Beneficial Acclimatization in P. compressa . Bleaching-susceptible and bleaching-resistant P. compressa appear to have converged on the same resistant phenotype despite past differences in bleaching susceptibility. Surprisingly, neither phenotype bleached significantly during the 2019 heatwave, even though the bleaching-susceptible colonies exhibited severe bleaching and some (~20%) partial mortality during the 2015 heatwave ( 33 , 34 ). While lower bleaching severity in 2019 may have been due to somewhat lower levels of heat stress accumulation than in 2015, experimental heat stress tests confirmed identical bleaching thresholds in bleaching-susceptible and bleaching-resistant phenotypes, and neither phenotype experienced significant mortality following the 2019 event. Together, these results indicate that beneficial acclimatization occurred and has persisted for several years in this species. Higher bleaching thresholds have been observed in multiple coral species following successive marine heatwaves ( 17 – 21 ), supporting the hypothesis that environmental memory of a prior stress event improves the response to a subsequent exposure, and is a common capability in corals. Increases in bleaching resistance from 2015 to 2019 were also observed in P. compressa across the population, which may also have stemmed from beneficial acclimatization; however, selection against weak corals or symbioses ( 20 , 23 , 30 ) or a shift to more stress-tolerant symbionts ( 30 ) is also possible. Support for these latter two hypotheses is limited for P. compressa in Kāne‘ohe Bay, where i) whole-colony mortality was low in the aftermath of the 2014 and 2015 heatwaves ( 33 , 36 ), ii) P. compressa does not exhibit evidence of cryptic host speciation ( 51 ), and iii) P. compressa maintains a specific symbiosis with a single symbiont species, Cladocopium ITS2-type “C15” ( 46 ). By following individual colonies across multiple heatwaves, this study indicates that the heatwaves in 2014 and 2015 resulted in stress hardening, not loss of sensitive individuals from the population, that first manifested as a decrease in bleaching severity in 2019, and this benefit has persisted within individuals for nearly a decade. While the exact mechanisms conferring this resilience have not been determined, physiological plasticity ( 18 , 37 ), constitutive upregulation of stress-response genes ( 52 , 53 ), and epigenetic modifications ( 54 ) all likely contribute and represent important avenues of future study. Importantly, whether the benefits of environmental memory of moderate heat stress will persist as heatwaves become more intense remains unknown. In the years following the 2019 heatwave, both phenotypes of P. compressa exhibited physiological recovery across multiple traits, requiring ~1.5 y to reach symbiont, chlorophyll- a and protein densities similar to historical preheatwave levels ( 55 ). Given their faster recovery and elevated bleaching thresholds (+0.7 to 1.2 °C) relative to M. capitata , P. compressa may become more dominant in this region as heatwaves become more frequent. Indeed, M. capitata exhibited greater partial mortality ( Fig. 2 ) and greater declines in benthic cover than P. compressa following the 2019 event ( 56 ), although both species experienced significant mortality across Kāne‘ohe Bay in 2019 [19% decline in P. compressa , 23% decline in M. capitata ( 56 )]. Greater bleaching resistance and lower mortality favors the dominance of P. compressa, which already reaches >75% cover on some reefs in Kāne‘ohe Bay ( 57 ). While high coral cover persists in this location despite bleaching-related mortality of these two dominant species, and has historically been considered a key metric of reef condition, the loss of biodiversity associated with transitioning from a multispecies assemblage to a predominantly P. compressa landscape would likely have a multitude of adverse effects on ecosystem function, from declining coral productivity to losses of blue food security ( 10 , 58 ). Further, critical processes such as reef accretion are projected to become uncoupled from coral cover under global change ( 59 ). Here, P. compressa was unable to sustain skeletal density as high as M. capitata , despite maintaining up to three times higher coral cover and exhibiting less bleaching and mortality. These patterns may be explained by: i) enhanced heat tolerance resulting in trade-offs with growth [( 60 , 61 but see ref. 62 ], and/or ii) the duration of our study was not long enough to capture the recovery of secondary calcification (i.e., densification) for this species, as recurring marine heatwaves could have delayed the revival of densification. Indeed, P. compressa are unable to recover calcification rates in the first 8 mo following heat stress ( 63 ), and elsewhere in the Pacific, Porites spp. can exhibit growth hiatuses for up to 4 y in the aftermath of a marine heatwave ( 44 ). Whether modern reefs are able to maintain net accretion and continue to provide the critical ecosystem services humans rely on remains to be seen. Conclusions. We have entered a new era of ocean warming that is affecting coral reefs in ways we are only just beginning to understand. Corals in the Main Hawaiian Islands have experienced a rise in offshore sea-surface temperatures of 1.15 °C in the last 60 y ( 64 , 65 ), leading to an unprecedented three coral bleaching events in the last decade (2014 to 2023) that were preceded by a single widespread coral bleaching event (1996) the entire century prior ( 57 , 66 ). The responses of individual corals to these increasingly frequent heatwaves demonstrate the divergent intra- and interspecific bleaching and recovery trajectories possible within a single coral community, highlighting the challenge of predicting future coral performance in a changing ocean. In one direction, P. compressa that were highly sensitive to marine heatwaves in 2014 and 2015 (i.e., severely bleached) have become visually and physiologically indistinguishable from bleaching-resistant conspecifics during a third heatwave (2019) and during extreme heat stress tests, indicating beneficial acclimatization that persists across many years. This increase in bleaching resistance was accompanied by rapid physiological recovery after repeat heat stress, although there remained evidence of persistent stress (e.g., weakened skeletons), suggesting that these corals may undergo tradeoffs that can erode ecosystem function. Increases in coral bleaching resistance across recurring heatwaves have become more prevalent on reefs across the globe ( 15 , 17 , 19 , 21 ), which is encouraging, as avoiding bleaching is often associated with greater survival ( 33 ) and stress hardening may thus promote the persistence of corals in our warming oceans. On the other hand, the extent of coral mortality has been increasing with each successive heatwave in this system, from <1% in 1996 to 13% in 2014, 22% in 2015, and >20% in 2019 ( 56 , 67 ). Furthermore, bleaching-susceptible M. capitata are visibly struggling from the recent barrage of heatwaves, manifesting as annual seasonal bleaching and escalating partial mortality in the absence of measurable heat stress. Importantly, even bleaching resistance was not associated with greater survival or recovery capacity in M. capitata , highlighting the danger of predicting future individual performance and reef function from a lack of visual bleaching alone. The inability of M. capitata of either bleaching phenotype to recover physiologically after 3 y following a repeat heatwave underscores that coral resilience is a multifaceted trait beyond bleaching resistance ( 60 ) and brings into question how we define coral resilience in the context of global change. Now, more than ever, seasonal and long-term studies are critically needed to identify corals that cannot just withstand and survive repeated heat stress events, but also rapidly recover ecosystem-defining traits (e.g., biomineralization) to continue providing the critical ecosystem services coastal communities directly rely on. Urgent, collective global action to eliminate greenhouse gas emissions remains the only approach that may provide sufficient time for corals to acclimatize and adapt to rapid climate-induced temperature increases in order for coral reef ecosystems to persist in the Anthropocene."
} | 4,696 |
28694844 | null | s2 | 1,307 | {
"abstract": "The ability to electronically interface living cells with electron accepting scaffolds is crucial for the development of next-generation biophotovoltaic technologies. Although recent studies have focused on engineering synthetic interfaces that can maximize electronic communication between the cell and scaffold, the efficiency of such devices is limited by the low conductivity of the cell membrane. This review provides a materials science perspective on applying a complementary, synthetic biology approach to engineering membrane-electrode interfaces. It focuses on the technical challenges behind the introduction of foreign extracellular electron transfer pathways in bacterial host cells and the past and future efforts to engineer photosynthetic organisms with artificial electron-export capabilities for biophotovoltaic applications. The article highlights advances in engineering protein-based, electron-exporting conduits in a model host organism, E. coli, before reviewing state-of-the-art biophotovoltaic technologies that use both unmodified and bioengineered photosynthetic bacteria with improved electron transport capabilities. A thermodynamic analysis is used to propose an energetically feasible pathway for extracellular electron transport in engineered cyanobacteria and identify metabolic bottlenecks amenable to protein engineering techniques. Based on this analysis, an engineered photosynthetic organism expressing a foreign, protein-based electron conduit yields a maximum theoretical solar conversion efficiency of 6-10% without accounting for additional bioengineering optimizations for light-harvesting."
} | 408 |
28855327 | PMC5576898 | pmc | 1,308 | {
"abstract": "Obligate endosymbiosis is operationally defined when loss or removal of the endosymbiont from the host results in the death of both. Whereas these relationships are typically viewed as mutualistic, molecular and cellular analysis reveals numerous instances in which these symbiotic relationships are established by alternative, nonmutualistic strategies. The endosymbiont usurps or integrates into core host processes, creating a need where none previously existed. Here I discuss examples of these addictive symbiotic relationships and how they are a likely outcome of all complex evolving systems."
} | 149 |
33668786 | PMC7996188 | pmc | 1,309 | {
"abstract": "Plant-associated endophytic microorganisms are essential to developing successful strategies for sustainable agriculture. Grazing is an effective practice of grassland utilization through regulating multitrophic relationships in natural grasslands. This study was conducted for exploring the effects of grazing on the diversities and communities of bacteria and fungi presented in rhizosphere soils, roots, stems, and leaves of Leymus chinensis ( L. chinensis ), based on high-throughput sequencing. Grazing increased bacterial diversity but reduced fungal diversity in plant leaves. Further analysis confirmed that the abundance of Chloroflexi, Gemmatimonadota, Nitrospirota, Sordariales, and Pezizales in plant leaves was increased by grazing. The Bray–Curtis similarities of microbial communities in the endosphere were higher under grazing plots than non-grazing plots. Moreover, the bacterial communities were significantly correlated with ions, while the nutrient and negative ions exhibited strong influence on fungal communities. We concluded that grazing-induced changes of microbial diversities and communities in different compartments of a dominant perennial grass ( L. chinensis ) could be attributed to the nutrient and ion distribution in host plant. The current study highlights the importance of livestock in mediating diversities and communities of endophytic microbes, and will be useful for better understanding the complexity of multitrophic interactions in a grassland ecosystem.",
"conclusion": "5. Conclusions Grazing enhanced the available soil nutrient and ion concentrations, resulting in changes in nutrient and ion distribution among plant tissues. The microbial diversity and community structure were shaped by grazing, and the Mantel test further ensured that the bacterial community was strongly correlated with ions, while the nutrient and negative ions exerted considerable correlations with fungal communities. The interactions among bacterial genera were reduced by livestock grazing, while there was no difference in interactions among fungal genera between NG and G grasslands. Here, we provided a new understanding of the mechanisms involved in the effects of grazing on microbial diversity and community in the rhizosphere and endosphere compartments of a dominant perennial grown in grassland.",
"introduction": "1. Introduction Endophytes refer to microbes (mostly bacteria and fungi) that inhabit internal tissues of plants without causing disease. [ 1 , 2 ]. Most endophytic microbes come from the plant surface and rhizosphere soil, and enter the host plant through stomata, wounds, water holes, or root hairs [ 3 ]. They play a vital role in enhancing plant nutrient uptake, improving plant growth, and increasing plant tolerance to harsh environment [ 4 , 5 , 6 ]. In addition, endophytic microbes may exert a crucial impact on plant diversity and community structure via regulating competition and niche differentiation in resource use among different plants [ 7 , 8 , 9 ]. Endophytic microbial communities are highly variable in different plant organs, and are strongly influenced by host species and environmental factors, as well as plant physiological and biochemical state [ 10 , 11 , 12 ]. Therefore, understanding the diversity and community composition of endophytic microbes and the environmental variables that contribute to regulating their community structure has an important significance in highlighting their essential roles for plant growth and ecosystem function. At present, various endophytic microbes have been isolated from different plant species, and the abundance of endophytes in different tissues of the same plant has been found to be higher than previously expected [ 10 , 11 , 12 , 13 ]. The community compositions of endophytic bacteria and fungi are not only influenced by plant species [ 14 ], but also greatly vary in different tissues of the same plant [ 15 , 16 , 17 ]. Environmental factors were considered as main drivers to determine the composition and diversity of endophytic microbial communities, including geographic location, soil type, and climate [ 18 , 19 ]. A previous study showed that the diversity of endophytic fungi in Ginkgo biloba changed with the seasons [ 20 ]. Franzluebbers [ 21 ] suggested that the changes in soil C and N fractions due to endophytic fungi infection were minimal in the relatively short term (60 weeks), while the increase in plant productivity of tall fescue infected by endophytic fungi had been observed in long-term pastures. Similarly, Ren et al. [ 22 ] indicated that the community structure of endophytic bacteria was significantly related to soil characteristics, including temperature, pH, carbon and nitrogen content. Revealing the spatial niche difference in the composition of endophytic microbial communities among various tissues and its impact factors may improve our understanding of interactions between plant and endophytic microbes, and promote the effective use of beneficial environmental microbes. Grazing has been considered as one of the most important management strategies for grassland ecosystems. It is generally accepted that grazing can influence soil microbial community directly, through changing soil properties by animal trampling and dunging, or indirectly, through impacting plant physical and chemical properties by foraging [ 23 ]. Despite the importance of endophytic microbes for plant health and ecosystem functioning, it remains unclear whether and how they are impacted by human-caused disturbances, such as livestock grazing. Leymus chinensis (Trin.) Tzvel. is a key, dominant C3 grass across eastern areas of the Eurasian Steppe, and is known for its broad distribution and high environment adaptability [ 24 ]. As a perennial grass with strong saline–alkaline tolerance, L. chinensis has been considered as one of the most promising species for typical grassland rehabilitation in arid and semi-arid regions of northern China [ 24 ]. In addition, L. chinensis is also an important forage species, preferred by large herbivores because of its high nutritional value and good palatability [ 25 ]. Although endophytes are ubiquitous in plants, we know little about their diversity and community structure in different tissues of L. chinensis . Furthermore, grazing management is known to be one of the most important strategies for regulating vegetation composition and the nutrient cycle in grassland ecosystem, but there have been few studies about the impacts and mechanisms of long-term grazing management on plant endophytic microbial diversity and community composition. Therefore, checking the effects of grazing on endophyte diversity and community structure is urgently required to reveal the influence of human activities on the relationship between microorganisms and plants. Here, we propose two reasonable assumptions to present possible pathways for grazing to affect endophytic microbial diversity and community composition in plant compartments. Firstly, livestock can injure plants by foraging and trampling behaviors, resulting in the changing of plant metabolism. Endophytic microbes inside plant tissues receive nutrients from host plants to complete their life cycle. The changes in plant metabolism will indeed affect plant nutrient status, thereby exerting influence on the diversity and community composition of endophytic microbes. Secondly, soil microbial community structure is strongly impacted by soil properties, while grazing can influence soil properties by defoliation, treading, and dunging. The changes in soil microbial community composition will in turn regulate endophyte diversity and community composition inside different plant tissues, because endophytic microbes are mainly derived from rhizosphere soil microorganisms. Thus, the main objectives of the current study were to (1) determine endophytic bacterial and fungal diversity and community composition in different plant compartments, (2) explore the effects of grazing on diversity and community structure of endophytes, and (3) unveil the mechanisms how long-term grazing mediates the diversity and community of endophytic microbes in different plant compartments.",
"discussion": "4. Discussion 4.1. Grazing-Induced Changes in Soil Properties and Plant Characteristics Grazing can directly or indirectly impact soil properties in grassland by regulating the trampling and manure deposition, as well as changing the quantity and quality of litter returned to soil [ 45 , 46 ]. A previous study showed that soil SOC, TN, and TP in the grazed alpine grasslands were significantly lower compared with those in the non-grazed alpine grasslands [ 47 ]. In the current study, we found that free grazing significantly decreased soil carbon, TN, and TP in meadow steppes ( Figure S2 ). This result may be attributed to the reduction of litter mass, due to the decrease of vegetation coverage and plant biomass caused by livestock grazing [ 48 ]. In contrast, the impacts of grazing on TN and TP from different studies were more variable: positive [ 49 ], negative [ 50 ], and neutral [ 51 ] effects were equally common and varied considerably with grassland ecosystem, grazing intensity, and plant diversity. NH 4 + –N and NO 3 − –N are the two main inorganic N sources from soil that can be taken up and utilized by most plants. In addition, we found that grazing significantly increased the soil NH 4 + –N and NO 3 − –N by 27.6% and 54.1%, respectively, which was consistent with a previous study [ 52 ]. This could be attributed to the increase of N mineralization caused by the dung and urine deposition of livestock. The free grazing had higher soil pH, EC, and Na + , while no differences were found in K + and Ca 2+ between free grazing and grazing exclusion grasslands. The explanation for these findings should account for the influence of livestock grazing on the increase of soil ion content via urine, feces, and soil compaction [ 53 ]. A previous study showed that livestock grazing enhanced N and P concentrations in the leaves, stems, and roots of L. chinensis in the Inner Mongolia steppe [ 54 ], which was also supported by the results from our study ( Figure S4 ). The increase in N and P concentrations in plant different organs indicate a beneficial effect of grazing on plant growth by improving compensatory growth to reduce biomass loss. McNaughton et al. [ 55 ] showed that grazers were able to enhance the return of available forms of N and P to the soil, and thereby increase plant nutrient uptake and accumulation. The present study provides support for this by finding higher soil NH 4 + –N and NO 3 − –N under free grazing compared with that of grazing exclusion ( Figure S3 ). However, we did not observe any change in plant N/P ratios under free grazing, and this could be attributable to the increase of plant N and P by the same level [ 56 ]. 4.2. Grazing-Induced Changes in Endophytic Microbial Diversity and Community An increasing number of studies have indicated the crucial effect of microbes in external (rhizosphere) and internal plant compartments (root endosphere, stem endosphere, and leaf endosphere) on plant growth and health [ 57 , 58 ]. The synergistic information about microbial diversity and communities in different compartments of L. chinensis and their driving factors are still unclear, although L. chinensis is one of the most dominant plant species grown in the eastern region of the Eurasian Steppe, with high ecological and economic values. The lack of this knowledge to some extent hinders our in-depth understanding of the important roles of microorganisms in restoring degraded grassland and maintaining the stability of the ecosystem. Therefore, the characterization of bacterial and fungal diversities and communities in the endosphere compartments and rhizosphere soils of L. chinensis is valuable. In the current study, we compared and analyzed the microbial diversity and communities in the rhizosphere soils, roots, stems, and leaves of L. chinensis grown in non-grazed and grazed grasslands by Illumina amplicon sequencing. Based on an OTU assessment, the bacterial and fungal diversity in the rhizosphere and endosphere of L. chinensis was compared using alpha diversity indices (Sobs, Chao, and Shannon), suggesting higher microbial diversity in the rhizosphere and root compared with stem and leaf tissues in grazed grassland. A rhizosphere is a suitable microenvironment, enriched in nutrients, and contains a huge number and variety of microorganisms [ 59 ]. In addition, plant roots can secrete a wide range of chemical compounds that serve important roles in attracting microbes in the rhizosphere [ 60 ]. These two reasons might explain the higher microbial diversity in the rhizosphere soil than plant tissues. Rather, the microbes from the soil first colonized plant roots [ 61 ], while only some specific species were selected and able to migrate to the aerial parts of plant. With the increase of the distance from the colonized roots, the number of microbes supplied by the xylem gets smaller, resulting in a decrease of richness and diversity of microbial community in this order: root > stem > leaf. These findings were consistent with previous studies in other plant species, such as rice [ 62 ], poplar trees [ 57 ], and Medicago truncatula [ 58 ]. Interestingly, there is no difference in the bacterial diversity between rhizosphere and endosphere compartments in grazed grassland. In contrast, the Sobs index and Shannon index of fungal communities in leaf tissue were significantly lower compared with other compartments. We determined the Bray–Curtis similarity of microbial community among different samples to further reveal the role of grazing in shaping microbial community. The grazing tended to increase the similarities of bacterial and fungal community in the endosphere compartment ( Figure S2 ). In other words, the variation in diversity of the microbial community among different compartments become smaller by grazing. Moreover, the Shannon index of the bacterial community was higher in grazed grassland than non-grazed grassland in leaf tissue, while the grazing decreased the Shannon index of fungal communities in the leaf organ. Bacterial colonization could be enhanced by leaf injury caused by livestock feeding [ 63 ], resulting in a high number and diversity of airborne bacteria in leaf compartments in grazed grassland. On the other hand, a large number and diversity of bacteria enter the mouth of livestock when they feed on various plant species in the grassland. The bacteria in the mouth are easily migrated to the plants’ wounded leaves through livestock feeding behavior. However, the stronger competition ability of bacteria in plant leaves may greatly inhibit the colonization of fungi. Our study found that grazing significantly increased the relative abundance of four bacterial phyla (Firmicutes in the root, Chloroflexi, Gemmatimonadota, and Nitrospirota in the leaves) and three fungal orders (Capnodiales in the stem, Sordariales, unclassified_c_Sordariomycetes, and Pezizales in the leaves) ( Figure 3 ). Previous studies have reported that members of Actinobacteria, Proteobacteria, Bacteroidetes, and Firmicutes were commonly detected in various environments and are dominant in the endosphere, with Proteobacteria being the most dominant [ 64 , 65 ]. It has been indicated that Proteobacteria play an important role in fixing atmospheric dinitrogen to ammonia and providing it to the host plant [ 66 , 67 ]. Actinobacteriota have shown various implications, including available nutrient enhancement, plant growth improvement, and phytopathogens inhibition [ 68 , 69 ]. Hypocreales and Sordariales are notable in their ability to promote plant growth by extracting nutrients from multiple sources, and are considered to be important biocontrol fungi for plant herbivores and diseases [ 70 , 71 ]. Our results are in line with Cheng et al. [ 72 ], who reported that Firmicutes, Chloroflexi, and Gemmatimonadota were dominant taxonomic groups of soil bacteria in grazed and grazing exclusion grasslands. Because bacterial phyla Firmicutes, Chloroflexi, and Gemmatimonadota have the ability to adapt better to harsh environments [ 73 , 74 ], the changes in the taxonomic compositions were attributed to selective pressure caused by livestock grazing. The increase in the relative abundance of ascomycetes (Pezizales and Sordariales) in grazing plots can be regarded as an adaptation strategy for plants to livestock grazing. 4.3. How Grazing Influence Endophytic Microbial Diversity and Community Composition? Our study suggests that long-term grazing improves soil pH, EC, NH 4 + –N, and NO 3 − –N concentrations in a meadow steppe in the eastern Eurasian steppe. With the increase of soil available nutrients, plant accumulated more nutrients and K + in the leaves under grazing plots. We further detected that there was no significant difference in Na + , Ca 2+ , and SO 4 2− concentrations in plant leaves, although grazing enhanced their concentrations in plant roots. This may be an adaptative strategy for plants related to livestock grazing. A Mantel test was used to reveal the correlation between the microbial (bacterial and fungal) communities and nutrients (N and P), positive ions (Na + , K + , and Ca 2+ ), and negative ions (Cl − and SO 4 2− ). The study indicates that bacterial communities significantly correlated with positive and negative ions, while the nutrient and negative ions exhibited strong correlations with fungal community ( Table S1 ). As shown by the conceptual framework in Figure 7 , this study provided possible scientific values for understanding how long-term grazing impacts bacterial and fungal diversity and community composition in the rhizosphere and endosphere of L. chinensis in meadow steppes, based on our own research and previous studies. In a word, grazing affects microbial diversity and community composition in different compartments of L. chinensis through regulating nutrient and ion distribution in host plants. However, despite their importance, the rhizosphere and endosphere microbes remain poorly described, and we still lack an understanding of how their diversity and structural compositions are linked their function within different ecological niches. Further studies are required to demonstrate how the grazing-induced changes in microbiota can impact grassland ecosystem function."
} | 4,626 |
36838299 | PMC9967897 | pmc | 1,310 | {
"abstract": "Weeds have always been considered an insidious enemy, capable of reducing crop production. Conversely, the agroecological vision attributes a key role to the spontaneous flora in promoting plant diversity and belowground interactions, which may improve the ecological performance of agroecosystems. We summarized the literature on the weeds’ arbuscular–mycorrhizae (AM) interaction and we analyzed evidence on the: (i) AM suppressive/selective effect on weed communities; (ii) effect of weeds on AM colonization, and (iii) positive role of AM-supporting weeds on forming shared mycorrhizal hyphal connections in agroecosystems. While some authors conceptualized AM as a weed control tool, others underlined their selective effect on weed communities. Recent studies suggest that AM-host weeds can participate in the development of a common mycorrhizal mycelial network (MMN) among different plants species. Nevertheless, direct evidence of the actual exchange of nutrients and C between coexisting plants through MMN in agroecosystems is missing. Although the effect of agricultural practices on plant community-AM interactions are complex, more conservative farming management seems to foster AM populations. Future studies should focus on: (i) field studies, (ii) weed communities and their traits, rather than on the most abundant species, and (iii) the use of advanced analytical techniques, able to monitor MMN development and functionality.",
"conclusion": "5. Conclusions This study analyzed the scientific literature on weeds and AM colonization. Firstly, two main approaches were followed to study the weed–AM interaction. While some scientists conceptualized AM as a tool to control weeds, others underlined the selective effect of AM on weed communities. Secondly, the literature indicated that weeds have a critical role in mediating the population of AM in agroecosystems, thereby suggesting that weeds could be considered as “service crops” rather than solely a worrying element in agricultural fields. Thirdly, the AM ability to colonize the weed community in agroecosystems is a result of complex interactions belowground among plants and mycorrhizal fungi, where weed diversity, and particularly SAM traits, drive the success of the mycorrhizal infection. Although we found strong evidence of a common extra radical mycelium across different crop and weed species, studies that unequivocally verified the C and nutrients exchange mediated by MMN in agroecosystems were not found. Concerning agricultural management, farming practices act as an additional filter to weed communities and AM development. Mycorrhizal cover crops, intercropping crops with SAM traits, and the reduction/absence of soil tillage are agroecological practices that can promote the extra-radical hyphal connection and possibly the development of a MMN among coexisting plants. To this end, knowledge of weed community functional traits is instrumental to inform on (i) mechanisms underlying the development of a functional MMN in the field and (ii) other ecological services supplied by spontaneous flora as a means to increase the agroecosystem performances (e.g., productivity, support to pollinators, nutrient cycling). Finally, we would stress the importance of future research addressing: − In-field studies more than in confined systems, the latter not always being representative of the actual interactions among neighboring roots of plant species; − Experiments mostly focused on the effect of management on the whole weed community and its traits, rather than on the most abundant species; − Advanced analytical techniques, able to monitor the development and functionality of MMN among roots at the belowground and the soil C supply and P availability fluctuation.",
"introduction": "1. Introduction When asking farmers how they usually manage weeds, the most frequent approach is to eliminate or strongly contain them. The capacity of spontaneous flora to rapidly colonize a fertilized cropping system induces hard competition with the main crop for available water and nutrients, sometimes in favor of the weeds [ 1 ]. The interference between the main crop and weeds is the result of the competition for water and soil nutrients, and the allelopathy among the different plant species coexisting in a given agroecosystem [ 2 ]. Starting from 1990, several studies approached such a complex plant relationship [ 3 , 4 , 5 ]. More recently, some researchers focused on the capacity of mycorrhizal fungi, and particularly of arbuscular mycorrhizae (AM), to strongly influence the community composition of spontaneous flora in cropping systems. AM can affect the nature of weed communities in agroecosystems in different ways, including changing the relative abundance of mycotrophic AM-host weed species and non-mycotrophic non-host species [ 6 , 7 ]. When competing, weeds and crops modulate their behaviors in relation to soil microorganisms, showing a greater dependence on associations with the soil symbiotic microbiota to increase their growth [ 8 ]. The current agroecological approach attributes an important role to AM-host weeds, or spontaneous flora, in designing sustainable and performing agroecosystems [ 9 , 10 , 11 ]. Simard et al. (2012) [ 12 ] found that different forest species are able to develop a belowground common mycorrhizal mycelial network (MMN), which implies also material transfer, such as organic C, nutrients, water, defense signals, and allelochemicals among AM plants. From this finding, we can hypothesize that similar mechanisms could also occur in herbaceous systems, where mycorrhizal flora can contribute to the development of a MMN. Our hypothesis is that, in presence of AM fungi, the infection of mycorrhizal weeds could facilitate the connections among external AM hyphae by creating a shared mycelial network, thus boosting the mycorrhization in the whole agroecosystem, also benefiting the main crop. However, despite the growing research interest on the agroecological role of weeds in mediating AM colonization and, hence, contributing to improve agroecosystem functioning, a comprehensive analysis of the literature on weeds–AM fungi relationships is still missing. In this study, we reviewed the literature on weeds and AM symbiosis to analyze evidence on: (i) AM as a weed control practice and/or as a selector of specific weeds assemblages; (ii) the effect played by weeds on AM infection in cropping systems, and; (iii) the role of supporting arbuscular mycorrhizal (SAM) weeds in fostering AM hyphal connection in agroecosystems.",
"discussion": "4. Discussion We examined the results extrapolated from the literature to comprehensively address the issue concerning the relationships between mycorrhizal fungi, weeds, and their interactions in agroecosystems, and in particular: (i) the effect of mycorrhizal fungi on controlling/selecting spontaneous flora in cropping systems; (ii) the effect of weed community on AM infection in cropping systems, and; (iii) the development of a shared MMN among coexisting plants in cropping systems. 4.1. Do AM Control Weeds or Select Beneficial Flora? 4.1.1. AM to Control Antagonist Weeds One of the approaches applied when investigating the relationship between AM fungi and weeds is based on the application of mycorrhizal infection as a tool to control weeds. One of the first pieces of evidence of the capacity of AM fungi to contain spontaneous flora was observed in turfgrasses of the Agrostis stolonifera L. species. When AM fungi were abundant in the field, Poa annua L. was rare while A. stolonifera increased. These results could be due to a decline in AM fungi population due to P. annua , or to the AM fungi that could have instead altered the competition between the two grasses in favor of the mycorrhizal A. stolonifera , or limited the growth of P. annua , due to the fungi antagonistic effect [ 13 ]. This can potentially counteract the crop yield loss to weeds, limit the shift toward certain weed species’ predominance, and increase soil-beneficial organisms through a set of concomitant mechanisms [ 6 ]. The AM interaction was also reported to decrease weed seed germination. For example, a microcosm experiment showed that the seed germination of the Orobanche and Phelipanche species was reduced in the presence of root exudates from pea plants colonized by Glomus mosseae and G. intraradices [ 14 ]. In another microcosm experiment on sunflower, the total weed biomass was 47% less after the AM fungi inoculation of the main crop [ 15 ]. However, a previous pot experiment on striga ( Striga hermonthica (Del.) Benth) and sorghum reported a decrease in striga emergence and an increase in sorghum production, following G. mosseae inoculation: specifically, striga emergence was reduced by 62% and the sorghum dry matter yield increased by 30% [ 16 ]. Another study obtained similar results on the AM effect on striga in sorghum and maize cropping systems [ 17 ]. The paper reported a significant amount of reduction in striga shoots, by 30%, and a reduction of more than 50% in maize and sorghum, respectively. Nevertheless, such a decrease in striga did not translate into higher cereal yields. Overall, the effect of AM fungal taxa on weed growth seems to be not easily predictable. Concerning maize production, Li et al. (2019) [ 18 ] found that the effect of AM inoculants on weeds and maize growth varied greatly across plant species. Numerous AM taxa were shown to have negative effects on certain weeds but not on maize. These results suggest that the use of specific inoculants should be targeted to distinct species as a means of taking advantage of the selective effect of AM on weed communities. The interaction between AM and weeds was also reported from experiments in a glasshouse. Vatovec et al. (2005) [ 19 ] studied the response of seedlings to AM inoculants of 14 agronomic weed species, sampled from three cropping systems (organic, transitional-organic, and high-input/conventional). The weed biomass response to AM fungi was highly variable across species, depending on specific weed traits, namely strong/weak-host and non-host species. The weed biomass response to inoculants was also significantly dependent on cropping systems, suggesting that highly conservative management, such as organic farming, can make the difference on AM fungi—weed interactions. Two types of weed suppressive action were identified in different cropping systems: (i) direct effect, where weak host weeds were reduced as AM favored strong host weeds, and; (ii) indirect effect, where AM increased the competitive ability of strong host crops [ 20 , 21 , 22 , 23 ]. Based on these assumptions, the excellent meta-analysis by Li et al., (2016) [ 21 ] provided an array of management decisions based on the AM affinity of the crop and weeds, graphically represented in Figure 3 . 4.1.2. AM Selects Host Weed Assemblages While most of the studies cited in the previous section reported on the use of AM inoculant for weed control, other papers highlighted the effect of AM to gradually select “useful” weeds or, in other words, weeds with AM-supporting traits. Cameron (2010) [ 24 ] stressed the ability of AM fungi in facilitating the shift towards mycorrhizal host plant communities and suppressing the non-mycorrhizal ones. This can benefit the whole agroecosystem and is particularly relevant when mycorrhizal crop species are grown. The positive effect of AM fungi on selecting spontaneous flora was also found in grasslands. In these systems, Koziol and Bever (2017) [ 25 ] demonstrated that AM inoculants could promote plant diversity, and select functional weed assemblages able to provide a restoration outcome, while inhibiting less desirable weedy plants. In agroforestry, the contribution of plant diversification to weed management appeared to be mediated by AM fungi; integrating a Faidherbia albida tree into a sorghum cropping system maintained the persistence of AM fungi that protected the main crop from Striga hermonthica colonization [ 26 ]. One possible explanation of these selective mechanisms played by AM fungi relates to their ability to modulate phosphorus accessibility to plant roots. It was observed that, when the level of plant-available phosphorus is low, AM fungi colonization favors the P uptake by mycorrhizal species. As a result, the non-host species’ development is hindered by the combined effect of the low P availability and the high competition with AM-host species which can severely impact the non-host seedbanks in the long run [ 27 , 28 ]. Although the plant host trait has been indicated as a main criterion for the selective effect of AM on weed assemblages, the study by Säle et al., 2022 [ 29 ] reported that plant host trait does not always guarantee a positive contribution to the agroecosystem mycorrhization. Based on different AM fungi isolated from some European cropping systems, it was found to have a negative or neutral effect on aboveground biomass of Echinochloa crus-galli , Solanum nigrum and Papaver rhoeas , regardless of their AM-host/non-host trait. The authors concluded that some weed species do not benefit from AM fungi in terms of growth regardless of their traits, thereby strengthening the AM role in weed selection. Overall, the literature analyzed suggested that scientists conceptualized AM in the context of weed management in two primary ways: (i) as a tool to control weeds or (ii) as a biological tool to select specific weeds. While the former originated from a conventional approach to weed control, the latter could offer a more comprehensive view of weed management that recognizes the ecological dynamics of AM–weeds interaction. This could be further operationalized at the field level and be considered as a starting point to select weeds able to support ecosystem services without affecting, or even improving, crop production. 4.2. Effect of Weed Community on AM Colonization in Cropping Systems The other side of the coin concerns the role played by the whole weed community on mycorrhizal populations and the colonization of plants within cropping systems. The fact that several weeds are AM hosts, as reported by numerous studies, suggests that weeds hold a great potential to foster AM in agroecosystems. Among those, Ishii et al. (1998) [ 30 ] represents one of the first study focused on the whole weed community, where the presence and relative abundance of mycorrhizal host and non-host species were evaluated in terms of “cropping system mycorrhization”. In a citrus orchard, both spring and summer weeds as Rumex acetosa L., Agropyron tsukuhiense (Honda) Ohwi var. transiens (Hack.) Ohwi, Stellaria media Villars., Vicia cracca L., Lamium amplexicaule L., Medicago polymorpha L., Erigeron canadensis L., Amaranthus lividus L., Cynodon dactylon (L.) Pers., Beckmannia syzigachne (Steud.) Fern., Commelina communis L., Oxalis corniculata L., and Digitaria adscendens Henr.) were highly colonized by mycorrhizal fungi: particularly, in spring season, AM spores ewere mostly found on roots of some mycorrhizal host weeds, such as in Stellaria media , Vicia cracca , and Lamium amplexicaule . On the other hand, no AM infection was observed in Rumex japonicus Houtt., Equisetum arvensis L., and Polygonum blumei Meisn, as these species are usually recognized as non-mycorrhizal weeds. Given the effect of weed communities on AM population, weed control practices can also negatively affect the AM population in agroecosystems. In coffee production, weed community management was one of the key factors influencing the composition and abundance of AM spores [ 31 ]. Similarly, soil solarization was reported to significantly reduce AM weed hosts, and hence AM, with possible negative effects on AM crop colonization [ 32 ]. In general terms, highly diversified systems showed a significantly higher crop mycorrhizal colonization, compared to monocropping. Some examples concern (i) oil palms, by comparing monoculture to agroforestry [ 33 ]; (ii) different herbaceous crops [ Sorghum bicolor L. Moench (sorghum), Ambrosia artemisiifolia (L.) (ragweed), and Amaranthus powellii S. Wats. (pigweed)], grown as monocultures or in mixtures [ 34 ], (2021), and; (iii) maize [ 18 ], where a weeded system was compared to an non-weeded one, where C. album , E. crus-galli , and V. arvensis were the most abundant species [ 35 ]. A huge effort has also been put into collecting data concerning weeds and crop traits related to AM (e.g., [ 36 ]). Those studies are of fundamental importance to study the functionality of weed assemblages related to AM and their potential to act as “AM providers” to crops. Although those interactions are complex and variable, evidence of the positive effects of AM-host weeds on crop mycorrhization was reported. The first step towards the idea of a common fungal network among herbaceous plants and/or crops appeared when the extra-radical mycelium was observed on AM-host weed roots in arable cropping systems. Such interaction was reported to be critical to boost AM colonization of young wheat seedlings, both in the greenhouse and in organic cropping systems [ 10 , 37 ]. The use of diversification/conservative agricultural practices was reported to further increase weed communities able to support AM and contribute to the development of a common mycelial network with a positive effect on crops. Clear supporting evidence is provided by Ramos-Zapata et al. (2012) [ 38 ], who carried out a long-term experiment on maize production in the tropics. The authors found that the use of mycorrhizal cover crops ( Mucuna deeringian and Lysiloma latisiliquum ) had a positive impact on mycorrhizal weed species’ richness as well as on the percentage of plant roots colonized by AM fungi in field, increasing maize production in the long run [ 38 ]. These results are in line with those obtained by Feldmann and Boyle (1999) [ 39 ], who studied the role of host or non-host mycorrhizal traits of weeds in maize monocropping systems, both in field and greenhouse conditions. Specifically, the absence of any accompanying flora led to a loss of mycorrhizal spore types in the AM fungi community, lower effectiveness of the persistent AM fungi populations, and a decline in maize biomass production. Similar results were obtained for horticultural crops and orchards. AM-host weeds had a key role in improving lettuce mycorrhization with possible positive effects on crop production and quality [ 40 ]. Likewise, AM spores grew significantly with the increase in the number of weed species in subtropical citrus and Mediterranean olive orchards, thereby contributing to the mycorrhizal colonization of crops [ 31 , 41 , 42 ]. Nevertheless, the net positive effects of the higher AM biomass triggered by communities of AM-supporting weeds on the main crop were not always confirmed. For instance, the introduction of different cover crops in vineyards increased mycorrhizal colonization and AM fungal spore populations on spontaneous flora but did not positively affect mycorrhization of grapevine roots, probably due to the missed contact between colonized roots and excessive disturbance by tillage [ 43 , 44 ]. Finally, these results suggest that weed community composition and diversity, the cropping system, and the management practices are complementary key drivers, acting by supporting or inhibiting mycorrhization. The interactions across AM weeds and farming practices are complex and variable across production systems. Still, a growing body of literature is highlighting how weeds, if well managed, could be considered “service crops” able to foster AM colonization across the elements of the agroecosystem and potentially determine the final performance of the main crops. 4.3. The Agroecological Approach Applied to Cropping Systems: Extra-Radical Hyphal Connection and Hypothesis of Mycorrhizal Mycelial Network (MMN) Development in Herbaceous Systems The first studies that explored the AM fungi infection of different plant species date from 1990, when several pot experiments ( Chenopodium album L., spring wheat, lettuce) and field trials ( C. album , Galinsoga parviflora Cav., Sinapis arvensis L., Sonchus oleraceus L., spring wheat, and maize) showed that the AM colonization of weeds was increased in the presence of mycotrophic crops, taking place only when growing in the vicinity of the main crops [ 45 ]. On the contrary, weed AM infection decreased in the presence of facultative mycotrophic crops. Here, the first indirect evidence of the importance of the “proximity” between the root systems of SAM species to boost the formation of a shared fungal mycelium was observed. Nevertheless, this mechanism was not yet well explored in open-field, and particularly on herbaceous systems. Under the agroecological vision, the cropping system is constituted by a community of different plant species, as a result of a “suite” of functional traits, where the main crop, weeds, and AM fungi work together for optimizing the use of available water and nutrient resources [ 46 , 47 ]. Among those functional traits, the SAM trait drives the plant selection in the field in favor of those species able to mycorrhize, assuring them of an increased P uptake and an improved yield and quality [ 11 , 48 , 49 ]. Although the role of a mycorrhizal mycelial network (MMN) on biogeochemical cycling, plant community composition, and ecosystem functioning was deeply studied in natural systems [ 9 , 12 , 50 , 51 ], it has not been widely investigated in agroecosystems. Recently, in a greenhouse potted experiment, the effects of AM association on the interference of Bidens pilosa , Urochloa decumbens , and Eleusine indica on soybeans was evaluated under plant competition, with or without contact with roots of another species. Positive interactions between soybean mycorrhizal colonization and competing host plants were found, irrespective of weed species or root contact, although direct evidence of the exchange of C and nutrients across plants were not provided [ 52 ]. Apparently, in a confined pot system, AM fungi colonize all plants, independently from the plant species and their traits. Evidence of the aspecific AM root colonization capacity in the field, especially when tillage is reduced, was possibly found by Oehl and Koch (2018) [ 53 ]. The absence of tillage positively affected AM fungi diversity in different Chinese vineyards compared to tilled systems, regardless of the inter-row Lolium perenne cover, the level and type of P fertilization, apparently contrasting with the results obtained by De Cauwer et al. (2021) [ 27 ]. In parallel, on a multi-year alfalfa-winter cereal rotation, the highest mycorrhizae abundance and diversity were associated with a continuous ground cover of herbaceous plants and infrequent tillage, compared to frequently tilled plots [ 54 ]. The decrease in AM-seedbanks’ diversity in disturbed soils confirmed that tillage can favor i) ruderal and disturbance-tolerant AM fungi taxa and ii) a selection of SAM species able to be colonized only by these taxa [ 55 ]. However, the presence of SAM weeds does not always guarantee the increase in mycorrhizal infection in the agroecosystem, as the soil mechanical disturbance is a limiting factor, due to the interruption of hyphal connection among coexisting plant roots [ 56 ]. Several theories have been developed to explain the advantages for SAM plants which could form a common extra-radical hyphal connection. A first theory assumes that SAM plants can promote the mycorrhizal infection of neighboring seedlings, thereby acting as an inoculum to favor C supply and maintain a common MMN among plants [ 57 ]. A second theory focuses on the role of MMN in equally distributing nutrient resources via plant interconnection in a given ecosystem [ 58 ]. Unfortunately, measuring the transfer of nutrients, energy, or signals from one plant to another mediated by MMN in field is really challenging, and currently there is no reference method to assess the MMN functionality and development. Nevertheless, the extra-radical mycorrhizal mycelium formed by coexisting plant species—which does not always imply the internal AM infection of involved plant roots—can be observed using electron scanning microscopy. A first attempt to indirectly quantify the common extra-radical mycorrhizal mycelium was applied in Mediterranean organic winter cereal cropping systems, where the mycorrhiza-mediated interference between crops (rye or spelt) and weeds was studied. The contribution made by crops and specific weed species to promote mycorrhization led to the formulation of the quantitative indicator “mycorrhizal colonization intensity of the agroecosystem” [ 59 ]. Another evidence of the common extra-radical mycorrhizal mycelium in diversified systems was found when investigating non-SAM species. It is well known that the ability of Brassicaceae and Chenopodiaceae to exudate specific allelochemicals from roots inhibits the branching of AM fungi hyphae onto root external cells [ 60 ]. However, it was found that mycorrhizal extra-radical mycelium can cover also roots of weed species belonging to the Brassicaceae family: on these roots, morphological types of arbuscular and coiled hyphae were observed, which are the most common in grasses [ 61 ]. Similar results were obtained in an organic beetroot intercropping system: here, an extra-radical mycelium was found on beetroot roots surfaces as a result of the presence of SAM weeds (namely, Capsella bursa-pastoris L., Senecio vulgaris L., Spergula arvensis L., and Plantago maior L.) in intercropping, while the external hyphal mycelium was missed in the monocropping system, where SAM species were not recorded [ 62 ]. The common extra-radical mycorrhizal mycelium was also observed in an organic Cocumis melo L. production system, mulched with flattened durum wheat [ 11 ]. Here, in Polygonum aviculare L., Anagallis arvensis L., Rumex crispus L., Convolvulus arvensis L., and, secondarily, Plantago media L. and Sonchus oleraceus L., relative abundances were strongly correlated to the melon mycorrhizal colonization and to the common extra-radical mycorrhizal mycelium development, when compared to not mulched or weeded systems. The shared extra-radical mycelium was observed on undisturbed melon root fragments collected at melon harvesting, using Scanning Electron Microscopy (SEM) under variable pressure, equipped with a LaB 6 electron sources and back-scattered electrons detector ( Figure 4 ). This visual indirect evidence of a hyphal connection among different plant individuals allows us to hypothesize that a functional MMN could be potentially developed not only among different tree species, where ectomycorrhizal fungi are prevalent in colonizing roots [ 12 , 50 ], but also in herbaceous systems, where AM fungi dominate the plant-fungal symbiosis. In systems where AM-host cover crops were introduced (e.g., rye or spelt), the presence of a spontaneous mixed and highly diverse flora addresses the mycorrhizal colonization towards SAM weeds. Our interpretation attributes to SAM weeds the role of “functional internodes” within a common extra-radical mycorrhizal mycelium, thus promoting the mycorrhization and the growth of the following crop [ 11 , 63 ]. Conversely, when the non-SAM weed species dominate, the extra-radical mycelium develops only by covering the surface of non-SAM roots with coiled hyphae [ 61 ] and the surface fungal mycelium. In this case, the non-SAM weeds behave as “unfunctional internodes” within the common extra-radical mycorrhizal mycelium, guaranteeing a certain spatial AM hyphal continuity ( Figure 5 ). In cropping systems dominated by the spelt cover crop, Rumex crispus L., Stellaria media L., Veronica persica L., Polygonum aviculare L., and Anagallis arvensis L. SAM weeds were the most abundant. Conversely, in a non-weeded system, the non-SAM weeds’ abundance increased, thereby decreasing the mycorrhization of the whole agroecosystem [ 59 ] ( Figure 5 ). Those findings suggest that weeds are much more than a set of spontaneous species in constant competition with crops. Rather, weeds can strongly support the functionality of the agroecosystem, depending on their specific traits. Specifically, SAM species can both promote the growth of belowground fungal mycelium, useful to colonize crops via the AM extra-hyphae expansion or favor the AM mycelial connection among individual crops. Evidently, weeding practices can strongly impact native seedbanks’ diversity, potentially affecting the abundance of SAM weeds in the field and, consequently, limiting the fungal mycelium development and the ecosystem services provided by mycorrhizae. On the contrary, the introduction of SAM cover crops, such as the winter cereals [ 59 ], or the intercropping with legumes (e.g., faba bean, [ 62 ]) can promote the AM colonization of SAM weeds and, thus, of the whole cropping system."
} | 7,277 |
40113879 | PMC11926120 | pmc | 1,312 | {
"abstract": "Predictor-based Neural Architecture Search (NAS) utilizes performance predictors to swiftly estimate architecture accuracy, thereby reducing the cost of architecture evaluation. However, existing predictor models struggle to represent spatial topological information in graph-structured data and fail to capture deep features of entire architectures, leading to decreased accuracy and generalization issues. Additionally, during the search process, predictors only evaluate architectures without providing forward guidance for discovering new ones, resulting in inefficient search efficiency. Thus, we proposed AE-NAS, an attention-driven evolutionary neural architecture search algorithm, to achieve forward evolution. By incorporating the attention mechanism into the predictor model and integrating it with the existing path-based architecture encoding method, we aim to enhance the representation of topological information and accurately evaluate architecture performance. AE-NAS dynamically adjusts the search direction based on the importance of each path to architecture performance, prioritizing exploration of architectures with greater potential. Finally, our experiments on AE-NAS on the search spaces of NAS-Bench-101 and NAS-Bench-201 proved that the predictor model based on the attention mechanism can significantly improve the architectural performance prediction accuracy and search efficiency.",
"conclusion": "Conclusions In this paper, we propose a NAS performance predictor based on Transformer to enhance spatial topological information encoding. By incorporating the attention mechanism and combining it with existing path-based architecture encoding, the predictor accurately evaluates architecture performance. Moreover, We devise a neural architecture search algorithm utilizing the attention mechanism for forward evolution. The attention-based predictor accurately evaluates architecture performance and identifies critical paths. By dynamically adjusting the search direction based on path importance, AE-NAS can prioritize exploring architectures with greater potential, guiding the search process positively to enhance efficiency.",
"introduction": "Introduction Neural Architecture Search (NAS) automates designing neural architectures for specific tasks, surpassing manual designs in various tasks 1 – 3 . The original NAS method focused on improving the search for the best architecture within the search space. However, training each sampled candidate architecture from scratch during the search led to significant computational costs and time overheads 1 . Recent advancements in NAS algorithms have notably mitigated this cost, though many require specialized implementations 4 . For instance, weight sharing among neural architectures with identical operations reduces the need for training each architecture from scratch 5 . But while this saves resources, it adds complexity to the search process, requiring fine-tuning for optimal performance. To mitigate search costs in NAS, predictor-based methods expedite architecture accuracy prediction using model performance predictors, rather than training all architectures to achieve accuracy 6 – 8 . While simple training-free predictors exhibit potential in some scenarios, their actual performance often falls short. Consequently, numerous studies concentrate on designing effective training-based predictors, typically comprising an encoder and regressor module 9 – 11 . These predictors are trained on surrogate datasets comprising architecture-accuracy pairs. Leveraging pre-trained predictors enables direct querying of the performance of any network structure in the same search space, thereby accelerating the search process. During predictor training, architectures are represented with discrete encoding. Most predictor-based methods typically transform this discrete data into a continuous latent space, extracting meaningful features to model accurate architectural mappings. Among existing performance prediction methods, neural predictors 8 and CTNAS 7 rely on graph convolutional networks (GCN) 12 to capture the feature representation of the model structure, while SemiNAS 9 and GATES 13 achieve the feature representation of the architecture by learning the embedding matrix of candidate operations in the search space. ReNAS 14 calculates the type matrix, the FLOPs matrix, and the parameter matrix, and concatenates them to form a feature tensor to represent a specific architecture. AutoGO 15 employs an evolutionary strategy to perform mutations on the computational graphs of neural networks, aiming to optimize network performance and hardware compatibility. It assesses the impact of mutations using a pre-trained neural predictor and utilizes Mixed Integer Linear Programming (MILP) to ensure the validity of the resulting architectures. These methods have made some progress in performance prediction, but they still face challenges in capturing deep architectural features and optimizing the search process. There are two main issues: First, the generalizability of neural predictors is low. Predictors mainly focus on discovering how different operations at local nodes affect architecture performance, lacking attention to the entire path from input to output. Second, the efficiency of architecture search is low. Predictors only evaluate architectures and do not provide forward guidance for discovering new architectures. Unlike previous methods, we proposed an attention-driven evolutionary neural architecture search algorithm (AE-NAS) that achieves forward evolution using an attention mechanism. We integrate the attention mechanism into the predictor model based on Transformer 16 and utilize path-based architecture encoding 17 as the input for the predictor. Transformer offers several advantages for training effective performance predictors. First, the self-attention module can help explore better feature representations from the graph structure data. Second, the multi-head mechanism can further help encode the different subspace information at different positions from the graph structure data. Third, the path-based architecture encoding method also helps the predictor model attention module to identify critical paths in the architecture. Generally speaking, our contributions can be summarized as follows: We propose a NAS performance predictor based on Transformer to enhance spatial topological information encoding. By incorporating the attention mechanism and combining it with path-based architecture encoding, the predictor accurately evaluates architecture performance. We propose AE-NAS, a neural architecture search algorithm utilizing the attention mechanism for forward evolution. The attention-based predictor accurately evaluates architecture performance and identifies critical paths. By dynamically adjusting the search direction based on path importance, AE-NAS can prioritize exploring architectures with greater potential, guiding the search process positively to enhance efficiency. Our comparative experiments on AE-NAS within the search spaces of NAS-Bench-101 18 and NAS-Bench-201 19 confirm that the attention-based predictor model significantly enhances both the accuracy of architectural performance prediction and search efficiency."
} | 1,817 |
35185391 | PMC8856095 | pmc | 1,315 | {
"abstract": "ABSTRACT Due to its abundance, mechanical energy is a promising ambient energy source. Triboelectric nanogenerators (TENGs) represent an effective mechanical energy harvesting method based on the use of contact electrification. The existing liquid-based TENGs can operate robustly without surface damage; however, the output of these TENGs is considerably smaller than that of solid-based TENGs. Notably, liquid-based TENGs in which the liquid directly contacts the conductive material can produce an electrical current of more than few mA. However, the liquid reservoir must have an adequate volume, and sufficient space must be provided for the liquid to move for generating the electrical output. To ensure a compact and lightweight design and produce electrical output in the low input frequency range, we introduce a mobile stick-type water-based TENG (MSW-TENG). The proposed MSW-TENG can generate an open-circuit voltage and closed-circuit current of up to 710 V and 2.9 mA, respectively, and be utilized as self-powered safety device. The findings of this study can promote the implementation of TENGs in everyday applications.",
"conclusion": "4. Conclusion We developed a compact and lightweight MSW-TENG that can generate a high electrical output while operating in the low input frequency range. Owing to the charge accumulation and separation induced by the charge on the PFA surface, the proposed device can generate a high electrical output each time the water contacts the electrode inside the cylinder. The electrical output of the MSW-TENG is influenced by various design parameters such as the amount of liquid inside the device, area of the top electrode, spacing between the two electrodes, and length of the outer electrode. The highest output is generated when the MSW-TENG has adequate space for water to move and a high electrode area. The proposed MSW-TENG can generate an electrical output of up to 710 V and 2.9 mA with a mechanical input of 1.5 Hz. The MSW-TENG can be used as a safety traffic light baton that can power an LED array when manually shaken.",
"introduction": "1. Introduction With the increasing interest in internet of things (IoT) and small electronics, the demand for portable energy sources for power circuits and sensors has emerged. To power these devices, energy harvesting techniques have been developed to generate electrical power from the external environment of the generators. Among various ambient energy sources, such as solar and thermal energy, mechanical energy is a promising energy source owing to its abundance [ 1–3 ]. To effectively harvest mechanical energy, triboelectric nanogenerators (TENGs) have been developed, which can generate electricity through contact electrification [ 4 , 5 ]. Although TENGs have successfully powered portable electronics [ 6 , 7 ] and sensors for IoT applications [ 8–10 ] through mechanical motion, frictional damage inevitably occurs on the solid surface owing to the contact between two triboelectric materials [ 11 , 12 ]. To decrease this friction, the use of liquids as triboelectric materials was recommended [ 13–15 ]. Although liquid-based TENGs can operate robustly without surface damage, the generated output is considerably lower than that of solid-based TENGs. To enhance this electrical output, certain researchers developed liquid-based TENGs in which the liquid directly contacted the conductive material [ 16–18 ]. Through the continuous contact–separation between water and the electrode, the generator could produce an electrical current of more than few mA. However, the liquid reservoir was required to have a certain volume, and a certain amount of space was required for the liquid to move for generating the electrical output. This framework reduced the overall efficiency and increased the total size of the generator. To realize portable applications, it is necessary to adopt a liquid-based TENG that is compact and can produce a high electrical output with a limited mechanical input. Considering these aspects, we developed a lightweight mobile stick-type water-based triboelectric nanogenerator (MSW-TENG) that can produce electrical output through mechanical motion applied to the device. As the water inside the MSW-TENG directly contacts the electrode, a high electrical output can be generated through the charge separation and accumulation induced by the self-ionization of water. For an input of 1.5 Hz, a single MSW-TENG could generate an open-circuit voltage ( V OC ) and closed-circuit current ( I CC ) of up to 710 V and 2.9 mA, respectively. As the size of the generator and amount of liquid considerably influence the portability and output production of the device, quantitative analyses were performed considering the size ratio of the electrode, physical space between the electrodes, and amount of water to determine the optimized device design. The proposed TENG could be utilized as a traffic safety light baton that can power 100 LEDs each time an operator manually shakes the baton. Notably, the proposed device can be used as a self-powered safety device, which widens the potential for implementing TENGs in everyday applications.",
"discussion": "3. Results and discussion Figure 1a shows the schematic of the MSW-TENG. As shown in Figure 1a-i , the MSW-TENG consists of a PFA cylinder that serves as both the substrate and triboelectric material, with the inner and outer electrodes placed on the top and bottom of the cylinder. A certain amount of DI water is filled in the tube to ensure consistent contact and separation when a mechanical input is provided. The two inner electrodes seal both ends of the PFA tube, and two outer electrodes are attached on the sides of the device. Each generator includes an internal and external electrode and a closed circuit forming a freestanding-type TENG [ 19 ]. As shown in Figure 1a -ii, water inside the cylinder sequentially contacts both the top and bottom inner electrodes as mechanical vibration is applied. Because the PFA has a negative surface charge [ 20 , 21 ] and water can undergo self-ionization, the water ions are affected by the electrical field, causing charge separation and accumulation to occur [ 22 ]. When the charge-separated water contacts the electrode, a high electrical output is generated. Figure 1b and c show the V OC and I CC outputs of the MSW-TENG provided with mechanical vibration of 1.5 Hz, respectively. The maximum V o c and C c c are 710 V and 2.9 mA, respectively, and a positive peak-shape output is observed because the positively charged particles lead to a high output, as illustrated in Figure 2 and discussed in the subsequent text. Figure 1d and e show the average peak voltage and current under different external load resistance values, respectively. The MSW-TENG generates a power of approximately 5 mW when the device is vibrated at 1.5 Hz with a load resistance of 1 MΩ. Figure 2a schematically illustrates the working mechanism of the MSW-TENG. When the MSW-TENG is vertically excited via the mechanical input, water exhibits sloshing motion in the container [ 23 , 24 ]. Owing to the self-ionizing nature of water, charge separation and accumulation occur when an external electric field is introduced. As mentioned previously, the container is made of PFA, which is a negatively charged material. The electric field from the PFA surface can separate and accumulate the hydrogen, hydronium, and hydroxide ions in water. As shown in Figure 2a , a positive charge is accumulated as the water rises toward the top electrode. When the water with the accumulated charge contacts the top electrode, a high output peak is generated as the electrons flow to the top electrode to achieve charge equivalence. After this contact, the water flows downward owing to gravity, and the electrons move toward the outer electrode. Owing to the relatively low speed associated with water separation and the presence of residue water on the electrode surface, the output is lower than that when water contacts the electrode. As the water flows downward, charge is again accumulated owing to the effect of the PFA surface. When the water with accumulated charge contacts the bottom electrode, a high electrical peak is generated, and the generation process is restarted. This process occurs repetitively, and the MSW-TENG produces an alternative current output when external mechanical vibrations are continuously applied. Figure 2b and c, respectively, show the output V OC and I CC values of conventional TENG and MSW-TENG to facilitate a comparative analysis. As shown in Supplementary Material 1, the conventional TENG has the same structure and design parameters as those of the MSW-TENG, but the top and bottom electrodes are not directly exposed to water. The average peak voltage and current of the MSW-TENG are more than two times those of the conventional TENG because water with accumulated charge directly contacts the conductive material. Figure 2d and e, respectively, show the V OC and I CC values for an MSW-TENG with a single generator on the top and dual generator on both the top and bottom to facilitate a comparative analysis. In the single generator framework, the end of the tube to which electrodes are not attached is covered with a lid (in this study, the end was sealed using a PTFE tape). The peak output of the MSW-TENG with a single generator is higher than that of the dual generator; however, the dual-generator produces more output peaks compared to the single generator. Figure 3a shows the schematic of the MSW-TENG with various design parameters. A 1 and A 2 represent the area of the inner electrode and internal diameter of the cylinder, respectively. d 1 is the distance between the two electrodes, and d 2 is the length of the outer electrode. To compare the electrical output associated with different design parameters, the root-mean-square (RMS) values were calculated to evaluate the continuous power as the MSW-TENG generated a sharp peak-type output. The RMS voltage ( V RMS ) and current ( I RMS ) were calculated as follows: V r m s = ∫ V t 2 d t T , I r m s = ∫ I t 2 d t T Figure 3b shows the V RMS and I RMS values of the MSW-TENG with different water–PFA cylinder volume ratios. The total volume of the PFA cylinder is approximately 50 mL (cylinder diameter of 0.23 cm and height of 12 cm); 5 mL and 40 mL of DI water are used, occupying 10% and 80% of the volume of the device, respectively. As shown in Figure 3b , the water volume ratio of 10% generates the highest output, and the output declines as the water volume ratio increases. This finding indicates that as the water volume increases, the space for charge accumulation becomes limited. As mentioned in the previous paragraph, the main working mechanism for high output generation is charge separation and accumulation in water owing to the electric field of the PFA surface. As the empty space is occupied by water, less space is available for water to move and possess concentrated charge. In addition, as the PFA cylinder is filled, water naturally screens the electric charge on the PFA surface by creating an electrical double layer (EDL) [ 25–27 ]. Owing to the low-intensity electric field on the PFA surface, the MSW-TENG produces a lower output when most of the cylinder is filled with water. The V OC output plot against time for different volume ratios of water is shown in Supplementary Material 2. Figure 3c shows the V RMS and I RMS values for different sizes of the inner electrode. The inner diameter of the PFA cylinder is 23 mm, and the area is 415.265 mm 2 . The electrode area ratios of 5%, 25%, 50%, 75%, and 100% in Figure 3c correspond to inner electrode diameters of 5, 11, 16, 20, and 23 mm, respectively. Both V RMS and I RMS increase as the electrode area ratio increases. When water collides with the top surface of the PFA cylinder, mechanical energy is lost, and the velocity of water significantly decreases. In general, the charge separation and accumulation of water are closely related to the velocity of water [ 18 ]. Therefore, the water that contacts the electrode after having been in contact with the dielectric material is expected to have a less accumulated positive charge. As the size of the inner electrode reduces, the probability of water with a high mechanical energy contacting the inner electrode decreases, and a lower electrical output is generated. The V OC plot against time for different sizes of the inner electrode is shown in Supplementary Material 3. Figure 3d shows the V RMS and I RMS values of the MSW-TENG for different distances between the inner and outer electrodes. A 2-cm-wide electrode is attached on the side of the PFA cylinder at distances of 2, 4, 6, and 8 cm from the top surface of the cylinder. The MSW-TENG produces a higher electrical output when the electrode is placed closer to the top surface of the cylinder. When mechanical vibration excites the water, the water inside the cylinder forms a triangular shape owing to gravity [ 18 ]. Consequently, a larger area of the external electrode is covered by water as the outer electrode is close to the bottom of the cylinder. As the water screens the electrical potential of the PFA, it produces less electrical output. The V OC plot against time with different distances between the inner and outer electrodes is shown in Supplementary Material 4. When the device has a wide outer electrode, additional space is available to supplement the area covered by the water. Figure 3e shows the V RMS and I RMS outputs depending on the length of the outer electrode. Both V RMS and I RMS increase as the length of the outer electrode increases because more area is exposed to the air, yielding a large potential difference. The V OC plot for different outer electrode size is shown in Supplementary Material 5. In addition, the length of the PFA cylinder is also a key parameter in fabricating the MSW-TENG because long cylinder can makes more charge separated inside water. As shown in Supplementary Material 6, the electrical output increases as the length of the PFA cylinder increases. The proposed MSW-TENG can produce a high electrical output with a low input frequency of 1 to 3 Hz and is lightweight because only 10 mL of water is used. Therefore, the proposed device can be used in various portable applications. Figure 4a schematically illustrates an MSW-TENG-based safety traffic light baton. The PFA cylinder containing water and the electrodes is covered by red plastic. As shown in Supplementary Material 7, two TENGs are installed at the top and bottom of the cylinder to produce a higher electrical output with a single input. As shown in Figure 4b and Supplementary Videos 1 and 2, a 100-LED array connected to each generator can be powered when water contacts the electrode each time. Even in the low-frequency range, as the water lightly contacts or falls from the top and bottom of the cylinder, all the LEDs are lit. Figure 4c and d show the output V OC and I CC depending on the input frequency. The electrical output of the MSW-TENG is measured using a mechanical vibration device, as shown in Supplementary Material 8. The output increases with the increase in the input frequency because the higher mechanical input leads to high-velocity water movement, which increases speed and the number of times that the water contacts the electrode.\n Figure 4. MSW-TENG as traffic safety light baton . (a) Schematic of MSW-TENG-based traffic safety light baton. (b) Photograph of baton powering a 100 LED array when manually shaken. (c) V OC and (d) I CC of MSW-TENG depending on the mechanical vibration frequency."
} | 3,930 |
25325380 | PMC4817704 | pmc | 1,316 | {
"abstract": "Atmospheric carbon dioxide (CO 2 ) levels are rapidly rising causing an increase in the partial pressure of CO 2 ( p CO 2 ) in the ocean and a reduction in pH known as ocean acidification (OA). Natural volcanic seeps in Papua New Guinea expel 99% pure CO 2 and thereby offer a unique opportunity to explore the effects of OA in situ . The corals Acropora millepora and Porites cylindrica were less abundant and hosted significantly different microbial communities at the CO 2 seep than at nearby control sites <500 m away. A primary driver of microbial differences in A. millepora was a 50% reduction of symbiotic Endozoicomonas . This loss of symbiotic taxa from corals at the CO 2 seep highlights a potential hurdle for corals to overcome if they are to adapt to and survive OA. In contrast, the two sponges Coelocarteria singaporensis and Cinachyra sp. were ∼40-fold more abundant at the seep and hosted a significantly higher relative abundance of Synechococcus than sponges at control sites. The increase in photosynthetic microbes at the seep potentially provides these species with a nutritional benefit and enhanced scope for growth under future climate scenarios (thus, flexibility in symbiosis may lead to a larger niche breadth). The microbial community in the apparently p CO 2 -sensitive sponge species S. massa was not significantly different between sites. These data show that responses to elevated p CO 2 are species-specific and that the stability and flexibility of microbial partnerships may have an important role in shaping and contributing to the fitness and success of some hosts.",
"introduction": "Introduction Declining seawater pH, termed ocean acidification (OA), is a direct result of increasing atmospheric carbon dioxide (CO 2 ) that leads to higher partial pressure of CO 2 ( p CO 2 ) in seawater. Rising p CO 2 reduces the concentration of carbonate ions and the saturation state of calcium carbonate minerals, which are essential for calcification in carbonate-accreting invertebrates such as corals. Volcanic CO 2 seeps provide a unique opportunity to investigate how organisms respond to OA in situ ( Hall-Spencer et al. , 2008 ; Fabricius et al. , 2011 ). Within the D'Entrecasteaux Island group in Milne Bay Province, Papua New Guinea, tropical coral reef communities exist within natural volcanic seeps that continuously expel ∼99% pure CO 2 into the sediments and water column ( Fabricius et al. , 2011 ). The water chemistry, temperature, currents and light of the seep environment is otherwise consistent with reef sites <500 m away, providing a unique opportunity to study organisms in an un-manipulated natural p CO 2 /pH experiment. The composition of reef organisms along the p CO2/pH gradient between seep and non-seep sites varies such that as pH declines, so does the richness of structurally complex corals (e.g., branching, foliose and tabulate growth forms), crustose coralline algae, foraminifera, soft corals and a range of other macro-invertebrates ( Fabricius et al. , 2011 ; Uthicke et al. , 2013 ; Fabricius et al. , 2014 ). Although many of the same species are found inside and outside of the CO 2 seeps, the most abundant benthic organisms living at reduced pH are massive Porites spp., non-calcareous macroalgae and seagrass. Sponge communities are also common at these shallow water CO 2 seeps with recent surveys revealing that some species can tolerate extreme pH conditions, whereas others are particularly vulnerable to elevated CO 2 ( Goodwin et al. , 2013 ). However, at the community level, there appears to be a significant decline in sponge cover from normal to high CO 2 sites ( Fabricius et al. , 2011 ; Goodwin et al. , 2013 ). Corals and sponges rely on intimate and dynamic associations with diverse microorganisms for their health and physiology, yet little is known about how their microbiota respond to changes in p CO 2 . The ability of microbes to rapidly evolve means they can shift their host range, metabolic capabilities and other essential functions in response to changing environmental conditions. Thus, to predict the response and resilience of marine organisms under future climate scenarios, we need to understand how their associated microbiota responds to increasing p CO 2 . An increase in CO 2 or reduction in pH can have consequences for microbially driven nutrient cycling, including carbon and nitrogen fixation ( Hutchins et al. , 2007 ), nitrification ( Beman et al. , 2011 ) and iron availability ( Shi et al. , 2010 ). CO 2 enrichment studies in microcosms have documented distinct and seasonal changes in pelagic microbial communities ( Krause et al. , 2012 ), with some bacteria demonstrating enhanced growth efficiency and increased CO 2 fixation at elevated p CO 2 ( Teira et al. , 2012 ). Bacteria may even profit energetically if the homeostatic difference between external and internal pH (7.4 to 7.8) is reduced ( Padan et al. , 2005 ). Most previous studies were conducted on pelagic bacteria and it is unknown whether such microbial shifts and physiological changes also occur within host-associated communities. Furthermore, whether such changes compromise host health or infer an adaptive advantage has not yet been explored. Aquarium-based studies have shown that increased p CO 2 or reduced pH can cause microbial shifts in communities associated with corals, foraminifera and crustose coralline algae ( Meron et al. , 2011 ; Webster et al. , 2013a , 2013b ). However, to date, no study has explored microbial communities in organisms that have spent their entire lives at elevated CO 2 , with the potential for their communities to adapt or physiologically acclimatize over large timescales (>3 years). Coral-associated microbial communities are composed of a core population of species-specific bacteria, in addition to transient associates that can vary in response to geographic location, climate and other environmental factors ( Ritchie, 2006 ). Some coral species support highly specific associations, such as the coral Porites astreoides in the Caribbean and Stylophora pistillata in the Red Sea, which both host microbiomes largely composed of bacteria in the family Hahellaceae ( Endozoicomonas sp.; ( Morrow et al. , 2012 ; Bayer et al. , 2013a , 2013b ), whereas other corals have more diverse associations ( Bourne et al. , 2013 ). The significance of these diversity differences has not yet been fully elucidated although it is believed that this has an important role in host fitness and stability in changing environmental conditions. Marine sponges are also known to host dense, diverse and highly stable microbial communities with many of the microorganisms being specific to sponge hosts ( Simister et al. , 2012 ). Environmental disturbances such as temperature, bleaching, disease, nutrient enrichment and changes in pH can all cause dramatic changes in both coral and sponge microbiota ( Webster et al. , 2008 ; Vega Thurber et al. , 2009 ; Meron et al. , 2011 ; Fan et al. , 2012 ; Vega Thurber et al. , 2014 ). Symbiotically conferred stress tolerance has been demonstrated in a number of systems ( Rodriguez et al. , 2008 ) and may provide a strategy for withstanding the effects of climate change and/or OA. The current study uses 16S rRNA gene amplicon pyrosequencing to assess the p CO 2 /pH sensitivity of microbial associations within two coral and three sponge species and explore whether host tolerance to OA stress could be enabled via habitat-adapted microbial associations.",
"discussion": "Discussion Compared with preindustrial levels, global oceans have already experienced a 30% increase in acidity, and are predicted to undergo a further 170% increase in acidity by 2100 ( IGBP, IOC, SCOR, 2014 ), leading to reduced biogenic calcification ( Anthony et al. , 2008 ), increased bio-erosion ( Fang et al. , 2013 ) and significant changes to coral reef community structure ( Hall-Spencer et al. , 2008 ; Fabricius et al. , 2011 , 2014 ). This study assessed how the microbiomes of key reef invertebrates might respond to OA in situ , by surveying corals and sponges that have had a post-larval lifetime of exposure to elevated CO 2 within a volcanic CO 2 seep. The composition of invertebrate-associated microbial communities is known to be intimately linked to host health ( Bourne and Webster, 2013 ), and we therefore predicted that OA-sensitive species would host microbial communities that are clearly distinct from the same species under ambient conditions, including a potential loss of putative symbionts and the appearance of microorganisms from taxa commonly associated with stress and disease. Additionally, not all tropical reef organisms are detrimentally impacted by elevated p CO 2 ( Fabricius et al. , 2011 ); therefore, we also hypothesized that tolerance to OA stress in some species may be enabled via habitat-acclimated microbial associations. Here we have shown that distinct microbial communities have developed in two sponge species that appeared to benefit from high p CO2 / low pH conditions as well as one sponge species and two coral species that were apparently sensitive to this environment. The primary driver of microbial variation in the two sponge species that were more abundant at the seeps was an increased relative abundance of photosynthetic Synechococcus , whereas the major driver of variation in the apparently sensitive coral species was a loss of Gammaproteobacteria at the seep site, in particular the putatively endosymbiotic Endozoicomonas in A. millepora . The development of distinct microbial communities between sites may influence the fitness and success of the host, although the functional implications of these divergent microbial populations are still to be fully elucidated. Our understanding of how OA will directly affect marine microbial communities is limited ( Joint et al. , 2011 ), although microbial shifts in response to elevated p CO 2 have previously been reported from CO 2 mesocosm experiments on bacterioplankton and picoplankton ( Allgaier et al. , 2008 ; Meakin and Wyman, 2011 ), studies of surface-associated biofilms ( Witt et al. , 2011 ) and experimental analyses of host-associated microbes ( Meron et al. , 2011 ; Webster et al. , 2013a , 2013b ; Kerfahi et al. , 2014 ). Manipulative experiments with corals exposed to high p CO 2 / low pH have demonstrated an increase in the relative abundance of disease-associated bacteria within the class Flavobacteria in the coral Porites compressa ( Vega Thurber et al. , 2009 ). This is largely consistent with findings from the CO 2 seep where we also observed an increase in bacterial OTUs affiliated with Bacteroidetes ( A. millepora microbiome), specifically within the class Flavobacteria ( P. cylindrica microbiome). However, when two Mediterranean coral species were transplanted for 7 months into a CO 2 seep in the Gulf of Naples, Italy, and assessed by 16S rRNA gene clone sequencing, there was no detectable impact on the composition of their associated microbial communities in comparison with control sites ( Meron et al. , 2012 ). Microbial community shifts reported in these previous experimental studies tend to be host- and study-specific with no microbial taxa consistently reported as present or absent from specific pH/ p CO 2 treatments. It is likely that experiments conducted over extended time periods are required, particularly to enable host-associated microbial communities to adapt and reflect consistent patterns associated with environmental change. In most cases, these studies indicate that marine microbial communities can shift in response to high p CO 2 , yet the speed and stability of these changes, as well as the implications for host health, adaptation, acclimation or ecosystem function, have not yet been determined. Both coral species were less abundant and hosted significantly different microbial communities at the site of active CO 2 discharge compared with the adjacent control site. Within the A. millepora microbiome, a notable ∼50% reduction in the family Hahellaceae (order Oceanospirillales ) was observed, largely as a result of loss of sequences related to Endozoicomonas sp. The Endozoicomonas are commonly found in close association with marine invertebrates, including the deep-sea bone-eating polychaete Osedax frankpressi ( Goffredi et al. , 2005 ), the Pacific sea slug Elysia ornata ( Kurahashi and Yokoto, 2007 ), the hydrothermal vent snail Alviniconcha ( Beinart et al. , 2014 ), in addition to gorgonians ( La Rivière et al. , 2013 ; Bayer et al. , 2013b ) and sponges ( Bourne et al. , 2013 ). Associated with corals specifically, members of the genus Endozoicomonas have been isolated from Montipora aequituberculata in the Pacific ( Yang et al. , 2010 ), comprise up to 80% of the microbiome of Porites astreoides from the Caribbean ( Morrow et al. , 2012 ; Rodriguez-Lanetty et al. , 2013 ) and 70 to 95% of the microbiome in Red Sea corals Stylophora pistillata, Pocillopora damicornis and Acropora humilis ( Bayer et al. , 2013a ). Importantly, a meta-analysis also revealed that Oceanospirillales -related sequences (which include the Endozoicomonas genus) were among the most common ribotypes found in healthy corals ( Mouchka et al. , 2010 ), suggesting that the loss of this important taxon at high p CO 2 would have significant implications for coral health, and may contribute to the inability of these species to thrive at the CO 2 seep. Hypotheses about the function of the Endozoicomonas -related symbionts have ranged from parasite consumers of host tissue to beneficial mutualists that assist in the metabolism, nutrient acquisition and/or cycling of organic compounds. The Endozoicomonas are members of the order Oceanospirillales , a group widely known to be heterotrophic and capable of degrading complex organic compounds ( Garrity et al. , 2005 ), including the production of extracellular hydrolytic enzymes that can degrade various complex organic substrates such as whale bones ( Goffredi et al. , 2007 ). Previous studies have also found that Endozoicomonas aggregate and may live endosymbiotically, including within the coral endoderm ( Bayer et al. , 2013b ), and within membrane-bound vesicles inside the gill cells of the hydrothermal vent snail Alviniconcha ( Beinart et al. , 2014 ). Isolates of Endozoicomonas- related sequences from A. millepora coral tissues possessed the ability to metabolise the organosulphur compound dimethylsulphoniopropionate, which suggests a role in sulphur cycling ( Raina et al. , 2009 ). Furthermore, Endozoicomonas isolates from sponges were shown to produce the quorum-sensing metabolites N-acyl homoserine lactones ( Mohamed et al. , 2008 ), and demonstrate antimicrobial activity against Bacillus subtilis ( Rua et al. , 2014 ). In the present study, the Endozoicomonas -related OTUs associated with A. millepora that were significantly reduced at the seep site were ∼96% similar to Endozoicomonas numazuensis (NCBI strain HC50), a strain isolated from marine sponges in Japan ( Nishijima et al. , 2013 ) and similar to E. montiporae ( Pike et al. , 2013 ), a strain isolated from the coral Montipora aquetuberculata ( Yang et al. , 2010 ). The E. numazuensis strain is facultatively anaerobic and capable of fermenting carbohydrates, reducing nitrate and hydrolysing DNA ( Nishijima et al. , 2013 ). Consistent with the proposed roles in nutrient acquisition and cycling of organic compounds, KEGG pathway prediction for the A. millepora Endozoicomonas OTU using PICRUSt revealed the categories of membrane transport, amino acid and carbohydrate metabolism, replication and repair, and cell motility to be the most abundant known pathways (genes of unknown function were also abundant). Taken together, these several lines of evidence suggest that host-associated Endozoicomonas may have important ecological roles in host health by providing otherwise unavailable macromolecular nutrients, contributing to nitrogen and/or sulphur cycling, and shaping the associated microbial community via signalling molecules and antimicrobial activity. In contrast to the observed decrease in Endozoicomonas at the seep site, another related bacterial genus within the family Halomonadaceae increased in abundance within A. millepora . The Halomonadaceae are considered coral ‘residents' ( Ritchie, 2006 ), are known for their successful growth over a wide range of temperature and pH levels and may produce enzymes capable of catabolizing dimethylsulphoniopropionate and acrylate produced by Symbiodinium within the coral tissues ( Todd et al. , 2012 ). In the present study, the OTU responsible for this shift in community structure was ∼99% similar to Chromohalobacter salexigens based on 16S rRNA gene identity (NCBI strain DSM3043), a strain isolated from high saline environments and capable of H 2 S production, nitrate reduction and anaerobic growth in the presence of nitrate. Thus, although the seep environment may be suboptimal for Endozoicomonas sp., it may still be suitable for other putatively symbiotic members of the coral microbial community. These results suggest that coral-associated microbial communities are dynamic and responsive to changes in p CO 2 and/or pH. Although the microbial shifts reported here are not entirely consistent with previous mesocosm and laboratory studies, they do reflect host–microbial relationships that have stabilized given a lifetime of acclimation to an environment with high p CO 2 . Sponge species that are abundant at shallow water CO 2 seeps in Papua New Guinea host significantly different microbial communities to individuals of the same species at control sites less than 500 m away. Although many bacteria contribute to these differences, the variation is largely influenced by the dominance of Synechococcus (phylum Cyanobacteria ) within C. singaporensis and Cinachyra sp. at the CO 2 seep. Although carbon metabolism in sponges is typically based on filter feeding of bacterioplankton, some species can obtain >50% of their carbon demand from cyanobacterial photosymbionts ( Wilkinson, 1983 ; Cheshire and Wilkinson, 1991 ; Freeman and Thacker, 2011 ). Hosting a higher abundance of cyanobacteria may therefore lead to higher carbon fixation, but nutritional benefits may also extend to nitrogen fixation as the products of nitrogen metabolism can be transferred from the symbionts to the sponge host in some species ( Freeman and Thacker, 2011 ). An elevated abundance of cyanobacteria likely provides at least some sponge species with enhanced scope for growth in these seep environments. Consistent with this role as providers of photosynthates, the three primary KEGG level 2 pathways identified from PICRUSt analysis of the Synechococcus OTU were energy metabolism (in this case, primarily pathways involved in photosynthesis), carbohydrate metabolism and amino acid metabolism. Although research has not yet explored how symbiotic cyanobacteria respond to elevated p CO 2 , recent studies of planktonic cyanobacteria have revealed species-specific responses to CO 2 conditions projected for the end of this century ( Hutchins et al. , 2009 ). For instance, at elevated p CO 2 , increased rates of N 2 and CO 2 fixation occur in Trichodesmium ( Hutchins et al. , 2007 ; Lomas et al. , 2012 ), whereas carbon assimilation in Prochlorococcus and Synechococcus is relatively unaffected by increased p CO 2 except at elevated temperatures ( Fu et al. , 2007 ; Lomas et al. , 2012 ). Although pelagic Synechococcus spp. show an immediate increase in carbon fixation (productivity) at elevated p CO 2 , this effect appears short term with acclimation of cellular physiology occurring within 1–3 days ( Lomas et al. , 2012 ). However, it is important to consider that, individual strains of Cyanobacteria may respond differently to altered CO 2 concentrations, and these short-term experiments are unable to account for how microbes adapt and evolve in response to higher p CO 2 environments. Potential variation in photosynthetic performance of different cyanobacterial types is particularly relevant to this study where Cyanobacteria increased in all three sponge species and both coral species at the seep, yet only two of these sponge species were more abundant at the seep site. In addition to improved host fitness and enhanced competitive advantage, microbial symbionts have been shown to infer environmental stress tolerance to their plant and animal hosts. For example, in the aphid Buchnera aphidicola symbiosis, a single nucleotide mutation of the symbiont governs the thermal tolerance of the host ( Dunbar et al. , 2007 ), and in grass species from coastal and geothermal habitats, fungal endophytes confer salt and heat tolerance, respectively ( Rodriguez et al. , 2008 ). On the basis of these findings, it is plausible to consider whether specific members of the microbial community in C. singaporensis and Cinachyra sp. confer low pH/high p CO 2 tolerance to the populations that occupy the CO 2 seep habitat. For instance, the internal pH of the sponge tissue may be dramatically influenced by utilisation or production of CO 2 by symbionts (e.g., Cyanobacteria ) as well as other microbial processes such as nitrification. Transplantation experiments (potentially coupled with experimental addition of cultured symbionts) or targeted experimental analysis with microsensors would further elucidate whether these symbiont populations enhance or hinder the survival of organisms in such extreme pH environments. Furthermore, future studies at shallow CO 2 seep environments would benefit from a combination of isotope labelling experiments and metagenomic/metatranscriptomic sequencing to enhance our ability to tease apart the relative contribution of bacterial symbionts to the growth and nutrition of ‘sensitive' and ‘tolerant' CO 2 species. Although the vulnerability of corals to OA is well established ( Orr et al. , 2005 ), it has previously been proposed that sponges are one taxon that could benefit from projected climate change scenarios ( Bell et al. , 2013 ), potentially by acquiring microbially mediated competitive advantages that enable them to thrive under future conditions of OA. Here we have shown that distinct microbial communities have developed in two sponge species that were tolerant of the high p CO 2 conditions occurring within a natural volcanic CO 2 seep. Conversely, the third sponge species was significantly less abundant at the CO 2 seep and showed no flexibility in microbial symbiosis. Both coral species were also significantly less abundant at the CO 2 seep. The proposed coral symbiont Endozoicomonas sp. was significantly reduced in corals at the CO 2 seep, whereas the Cyanobacteria prominent in sponge microbiomes at the seep were present in only low abundance in the coral microbiomes. In addition, distinct microbial communities were observed in both coral species at the seep site including an overrepresentation of opportunistic bacteria previously linked with diseased and stressed corals (e.g., Flavobacteria ). Although these results emphasise how some non-calcifying coral reef organisms (i.e., C. singaporensis and Cinachyra sp.) can benefit under reduced pH/elevated p CO2 conditions, we also showed that these benefits do not extend to all species and symbiotic partnerships. Organisms that lack the flexibility (i.e., S. massa ) to alter the composition of their symbiotic microbial community or have particularly sensitive symbiont populations (i.e., A. millepora, P. cylindrica ) may be more vulnerable to the effects of OA."
} | 5,988 |
19565587 | null | s2 | 1,317 | {
"abstract": "No abstract available"
} | 5 |
37848881 | PMC10580613 | pmc | 1,319 | {
"abstract": "Background The increasing prevalence of plastic waste combined with the inefficiencies of mechanical recycling has inspired interest in processes that can convert these waste streams into value-added biomaterials. To date, the microbial conversion of plastic substrates into biomaterials has been predominantly limited to polyhydroxyalkanoates production. Expanding the capabilities of these microbial conversion platforms to include a greater diversity of products generated from plastic waste streams can serve to promote the adoption of these technologies at a larger scale and encourage a more sustainable materials economy. Results Herein, we report the development of a new strain of Pseudomonas bacteria capable of converting depolymerized polyethylene into high value bespoke recombinant protein products. Using hexadecane, a proxy for depolymerized polyethylene, as a sole carbon nutrient source, we optimized media compositions that facilitate robust biomass growth above 1 × 10 9 cfu/ml, with results suggesting the benefits of lower hydrocarbon concentrations and the use of NH 4 Cl as a nitrogen source. We genomically integrated recombinant genes for green fluorescent protein and spider dragline-inspired silk protein, and we showed their expression in Pseudomonas aeruginosa , reaching titers of approximately 10 mg/L when hexadecane was used as the sole carbon source. Lastly, we demonstrated that chemically depolymerized polyethylene, comprised of a mixture of branched and unbranched alkanes, could be converted into silk protein by Pseudomonas aeruginosa at titers of 11.3 ± 1.1 mg/L. Conclusion This work demonstrates a microbial platform for the conversion of a both alkanes and plastic-derived substrates to recombinant, protein-based materials. The findings in this work can serve as a basis for future endeavors seeking to upcycle recalcitrant plastic wastes into value-added recombinant proteins. Supplementary Information The online version contains supplementary material available at 10.1186/s12934-023-02220-0.",
"introduction": "Introduction The overwhelming majority of plastics used today are derived from non-renewable petrochemical feedstocks and are considered “recalcitrant”, meaning they are not readily degraded in natural environments. Commodity plastics produced in high volumes, such as polyethylene and polypropylene, can take upwards of a thousand years to biodegrade [ 1 ]. Ubiquitous macro and microplastic debris physically and chemically harm wildlife ecosystems and have been demonstrated to harm human health as well [ 2 – 7 ]. Unfortunately, plastic manufacturing continues to grow annually, with over 350 million tons produced in 2020 alone. Packaging materials dominate the consumer plastics market, and nearly 40% of plastics used for packaging are landfilled at their end-of-life, with another 32% leaking into the environment [ 8 ]. Polyethylene is particularly problematic, as it is commonly found in single-use applications. Resultingly, polyethylene is the most commonly produced plastic, representing 30% of all plastics production [ 9 ]. Likewise, polyethylene is the most predominant plastic pollutant, accounting for 34% of all plastic pollution [ 10 ]. Despite existing recycling infrastructure, only 9% of polyethylene is recycled using primary or secondary (i.e. mechanical) recycling methods [ 11 ]. Mechanical recycling is inefficient, typically yielding materials that have inferior mechanical properties compared to virgin plastics [ 10 ]. Moreover, the cost of recycled plastics cannot compete with the low cost of virgin plastics [ 12 ]. Tertiary recycling strategies, such as pyrolysis or chemical depolymerization, produce low molecular weight chemicals, fuels, and even monomers that can be re-polymerized, thus offering potential advantages over mechanical recycling in a circular economy. However, industrial-scale tertiary recycling has been limited to date due to engineering and economic challenges [ 13 ]. Ultimately, decreasing the environmental impact of the plastics industry requires adoption of non-recalcitrant plastics produced by green synthesis methods. Moreover, developing strategies for valorizing existing recalcitrant waste is an important step in reducing the carbon footprint and pollution potential of the current “take-make-waste” linear plastic economy. Thus, there is a growing interest in technologies that utilize plastic waste as a feedstock to generate value-added materials (which may or may not share chemical similarity with plastics) [ 14 , 15 ]. Often referred to as upcycling, these methods target products that are more sustainable than traditional plastics or which offer higher economic value versus recycled plastics [ 15 , 16 ]. Abiotic methods demonstrated for upcycling polyethylene include catalytic depolymerization and pyrolysis [ 17 – 19 ]. However, these methods are limited in the composition of upcycled product generated, typically yielding hydrocarbons similar to wax or diesel fuel [ 17 – 19 ]. These methods may also be energy intensive, often requiring high heat, and use heavy metal catalysts. Consequently, upcycling methods that utilize biological systems have gained research interest [ 16 ], for example, in the development of enzymes that hydrolyze poly (ethylene terephthalate) [ 20 , 21 ]. Nevertheless, there is a limited number of works demonstrating successful biological upcycling of polyolefins such as polyethylene. In this context, polyethylene has been depolymerized into a distribution of smaller hydrocarbons (often rich in alkanes) that are subsequently used by various microbial strains as a carbon source [ 16 , 22 – 24 ]. Strains grown on polyethylene-derived feedstock have been shown to produce endogenous biopolymers, polyhydroxyalkanoates (PHAs), demonstrating the potential upcycling of polyethylene directly into a useful biodegradable plastic [ 16 , 22 – 24 ]. Until now, microbial upcycling of polyethylene has been largely limited to PHAs as the target product [ 16 ]. While PHAs can be used as a biodegradable plastic in single-use applications, their commercial adoption in this space is impaired by a relatively high production cost [ 25 ]. The microbial production of PHAs is also limited by batch variability, inadequate material properties, and challenges in controlling copolymer sequence [ 25 ]. Therefore, expanding the range of products that can be produced through microbial upcycling and aiming to create well-defined bespoke biopolymer constructs are highly desirable goals. For this purpose, Pseudomonas bacteria are particularly interesting, as they can robustly utilize single alkanes and alkane mixtures as a sole carbon source during growth [ 22 , 26 – 28 ]. Moreover, synthetic biology tools exist for engineering Pseudomonas bacteria, including plasmid vectors and genomic integration methods [ 29 , 30 ]. With regards to high value recombinant biopolymer products, silk proteins are amongst the most desirable biomaterials to target due to their unmatched combination of properties, including high toughness, strength, extensibility, biocompatibility, biodegradability, self-assembly capacity, thermal stability, solvent resistance, and ability to act as an optical waveguide [ 31 – 36 ]. Silk can rival or exceed the properties of conventional fossil-based plastics and can be manufactured into a diverse range of constructs, such as coatings, fibers, and hydrogels, facilitating their use in a wide variety of healthcare, food packaging, and sustainability applications. In this work, we report the first microbial platform for converting polyethylene-derived hydrocarbons into bespoke recombinant protein products. We characterized and optimized the growth of Pseudomonas bacteria when hexadecane or chemically depolymerized polyethylene is used as the sole carbon nutrient source. We also created Pseudomonas strains with genomically integrated recombinant genes for green fluorescent protein (GFPuv) and a protein inspired by spider dragline spidroin. We show the ability of these strains to produce recombinant protein product in rich LB media as well as in minimal media supplemented with a model alkane, hexadecane, as the sole carbon source. Lastly, we perform proof-of-concept experiments demonstrating the ability of engineered Pseudomonas to effectively convert depolymerized polyethylene into GFPuv and dragline silk. Collectively, the findings reported herein establish a preliminary, yet functional, platform for the future upcycling of plastic waste to value-added recombinant proteins.",
"discussion": "Results and discussion Media design and growth of Pseudomonas strains using hexadecane as sole carbon source Two strains of Pseudomonas, P. aeruginosa RR1 and P. oleovorans, were chosen for this work based on their previously demonstrated ability to utilize pyrolyzed polyethylene as a sole carbon source during growth (all strains, primers, and plasmids used in this work can be found in Additional file 1 : Table S1) [ 22 ]. The growth of these strains was first characterized by using a model alkane, hexadecane (C16), as the sole carbon source. Hexadecane served as a proxy for hydrocarbons derived from polyethylene, as it can be a major alkane constituent resulting from the depolymerization of polyethylene via pyrolysis [ 22 ]. A minimal salt media that contained either ammonium chloride (NH 4 Cl) or ammonium nitrate (NH 4 NO 3 ) as the nitrogen source was used, and hexadecane added was the sole source of elemental carbon in the media. The amount of hexadecane and elemental nitrogen supplied was based on theoretical calculations for the minimum amount of elemental carbon and nitrogen required to reach high cell densities of at least 10 g/L of wet pellet mass [ 37 , 38 ]. Calculations were performed by assuming that dry cell mass accounted for 25% of wet pellet mass, and within that dry mass 50% was elemental carbon and 14% was elemental nitrogen [ 37 , 38 ]. Thus, the theoretical minimum amount of hexadecane needed to supply enough elemental carbon to reach a wet pellet mass of 10 g/L is 1.47 g/L (0.147% w/v). Likewise, the theoretical minimum amount of ammonium chloride or ammonium nitrate required for a desired wet pellet mass of at least 10 g/L, is 1.34 and 1.00 g/L respectively. A total of twelve different combinations of culture conditions were tested with three different amounts of hexadecane (0.46%, 4.6%, or 9.2% w/v), two different amounts of elemental nitrogen (0.65 g/L or 1.3 g/L elemental N), and two different nitrogen sources (NH 4 Cl or NH 4 NO 3 ). Table 1 depicts the combinations of culture conditions that were tested for growth. To promote cell growth and recombinant protein production, the levels of supplied carbon and nitrogen were several times above the calculated minimum requirements for achieving a wet pellet mass of 10 g/L. Flask cultures were inoculated with a single plated colony of either P. aeruginosa RR1 or P. oleovorans and kept at 37 °C with 225 rpm shaking. As others have noted, the growth of Pseudomonas on hexadecane resulted in the formation of millimeter-sized white, waxy particulates that were numerous enough to interfere with OD600 measurements [ 39 ]. Thus, cell growth was quantified by performing serial dilutions of cultures with subsequent plating on LB agar to determine the density of colony-forming-units (cfu/ml). Table 1 Design of Media for Growth on Hexadecane as Sole Carbon Source* Hexadecane Ammonium Chloride, NH 4 Cl Ammonium Nitrate, NH 4 NO 3 0.46% w/v or 4.6% w/v or 9.2% w/v 2.5 g/L (0.65 g/L elemental N) or 5 g/L (1.3 g/L elemental N) 1.9 g/L (0.65 g/L elemental N) or 3.8 g/L (1.3 g/L elemental N) * The minimal salt media background maintains a constant composition for all conditions Figure 1 depicts the average cfu/ml of P. aeruginosa RR1 and P. oleovorans cultures 96 h after inoculation when using hexadecane as the sole carbon source under different culture conditions. For comparison, data for overnight cultures (18 h) grown in rich LB media can be found on the far left, averaging 2.38 ± 0.61 × 10 9 cfu/ml for P. aeruginosa RR1 and 1.65 ± 0.45 × 10 9 cfu/ml for P. oleovorans . This corresponds to OD600 values in LB media of 2.62 ± 0.19 for P. aeruginosa RR1 and 2.2 ± 0.16 for P. oleovorans . Seven out of the twelve different culture conditions facilitated the growth of P. aeruginosa RR1 to levels above 1 × 10 9 cfu/ml, which is comparable to the dense growth observed for overnight cultures in LB media (Fig. 1 ). The five remaining conditions facilitate growth of to at least 5.9 × 10 8 cfu/ml (Fig. 1 ). P. oleovorans was more limited in the number of conditions that facilitated robust growth, as only two conditions supported growth above 1 × 10 9 cfu/ml and eight conditions showed cfu/ml below 1 × 10 8 (Fig. 1 ). The two best conditions both contained the lowest concentration of hexadecane tested (0.46% w/v) and NH 4 Cl as the nitrogen source (Fig. 1 ). P. oleovorans showed a preference for NH 4 Cl versus NH 4 NO 3 , as three conditions using NH 4 Cl supported growth above 1 × 10 8 cfu/ml but only one condition yielded such results when NH 4 NO 3 was supplied (Fig. 2 ). With substantially higher cfu/ml across all but two culture conditions, P. aeruginosa RR1 was found to grow robustly on a wider range of culture conditions versus P. oleovorans (Fig. 1 ). Fig. 1 Average cfu/ml of P. aeruginosa RR1 and P. oleovorans 96 h after inoculation when using hexadecane as the sole carbon source (*18 h for LB media). Hexadecane (C16) was supplemented in the cultures at either 0.46%, 4.6%, or 9.2% (w/v). a Cfu/ml when 2.5 or 5 g/L of NH 4 Cl was supplied as the nitrogen source (2.5 Cl and 5 Cl). b Cfu/ml when 1.9 or 3.8 g/L of NH 4 NO 3 was supplied as the nitrogen source (1.9 NO3 and 3.8 NO3). Error bars represent standard deviations from the mean values of three replicates Fig. 2 a Growth of P. aeruginosa RR1 RK2-GFPuv at 24 and 48 h post inoculation with and without kanamycin supplementation. b \n P. aeruginosa RR1 RK2-GFPuv plasmid maintenance at 24 and 48 h post inoculation in the presence of 50 µg/ml kanamycin. c Growth of P. oleovorans RK2-GFPuv at 24 and 48 h post inoculation with and without kanamycin supplementation. d \n P. oleovorans RK2-GFPuv plasmid maintenance at 24 and 48 h post inoculation in the presence of 50 µg/ml kanamycin. For both strains, culture conditions that yielded the best growth on hexadecane were used. Namely 0.46% w/v hexadecane with 1.9 g/L NH 4 NO 3 for P. aeruginosa RR1 and 0.46% w/v hexadecane with 2.5 g/L NH 4 Cl for P. oleovorans . Error bars represent standard deviations from the mean values of three replicates Growth kinetics for the two strains can be found in Additional file 1 : Figures S2 and S3. For both Pseudomonas strains, the cfu/ml in cultures directly after inoculation with a plated colony was in the 10 5 range. At 24 h post inoculation, cfu/ml of P. aeruginosa RR1 was found to be in the 10 7 range, with an increase to the lower end of the 10 8 cfu/ml range by 48 h (Additional file 1 : Fig. S2). Measurements at 72 h showed growth increases to the high end of the 10 8 cfu/ml range (Additional file 1 : Fig. S2). At 96 h the cfu/ml in P. aeruginosa RR1 cultures was either maintained in the 10 8 cfu/ml range or had increased to above 1 × 10 9 cfu/ml (Figs. 1 and Additional file 1 : Figure S2). The shape of the growth curves indicates that cells had reached either a late log phase or early stationary phase at 96 h (Additional file 1 : Fig. S2). The growth kinetics of P. oleovorans showed more variability across culture conditions and required more time to reach the 10 7 –10 8 cfu/ml range, versus P. aeruginosa RR1 (Figs. 1 and Additional file 1 : Figure S3). At 24 h, P. oleovorans cfu/ml was observed to be in the low 10 6 range, with either no substantial increase or an increase to the high 10 6 range at 48 h (Additional file 1 : Fig. S3). At 72 h, growth ranged from 6 × 10 6 to 7.4 × 10 8 cfu/ml depending on culture conditions (Additional file 1 : Fig. S3). Likewise, at 96 h cultures ranged from 2.63 × 10 7 to 3.1 × 10 9 cfu/ml (Figs. 1 and Additional file 1 : Figure S3). The shapes of the P. oleovorans growth curves indicate that the cultures may have been in a late log phase and shown additional growth over a longer time frame (Additional file 1 : Fig. S3). Notwithstanding, this data shows that P. aeruginosa RR1 has more favorable growth kinetics (higher cfu/ml at 24 and 48 h) across the tested culture conditions versus P. oleovorans . These findings, combined with 1–2 order of magnitude differences in the final cfu/ml for the two species, lead to the conclusion that culture conditions must be specifically designed for a given species when an alkane is employed as the sole carbon source and growth trends observed in one species are likely not replicable in another. Deleterious effects of antibiotic selection and plasmid loss in hexadecane media Upon identifying conditions that yielded growth of P. aeruginosa RR1 and P. oleovorans above 1 × 10 9 cfu/ml with hexadecane as the carbon source, focus was turned to recombinant protein production. Green fluorescent protein (GFPuv) was chosen as a reporter protein to screen for proof-of-concept results before transiting to a recombinant silk construct. A plasmid-based approach was first tested, using vector pBb(RK2)1 k-GFPuv (RK2-GFPuv) [ 29 ]. The RK2-GFPuv vector was developed for use in Pseudomonas and contains an IPTG-inducible genetic circuit to produce a GFP mutant (GFPuv or eGFP) that has increased fluorescence over wild-type GFP for easier detection and quantification [ 29 , 40 ]. The vector also contains a kanamycin resistance gene for selection [ 29 ]. The RK2-GFPuv plasmid was transformed into the Pseudomonas strains to create strains P. aeruginosa RR1 RK2-GFPuv and P oleovorans RK2-GFPuv. Production of GFPuv was first screened in rich LB media, with P. aeruginosa RR1 RK2-GFPuv and P. oleovorans RK2-GFPuv producing the recombinant protein at titers of 10.9 ± 2.7 and 12.4 ± 2.3 mg/L, respectively (Additional file 1 : Fig. S4). From here, culture conditions that yielded the highest average cfu/ml at 96 h for strains grown on hexadecane were chosen for the plasmid-based conversion of hexadecane to a recombinant protein, namely, 0.46% w/v hexadecane with 1.9 g/L NH 4 NO 3 for P. aeruginosa RR1 and 0.46% w/v hexadecane with 2.5 g/L NH 4 Cl for P. oleovorans . However, upon addition of the antibiotic selection agent (kanamycin) to the hexadecane-based media, a severe inhibition of the growth of strains P. aeruginosa RR1 RK2-GFPuv and P oleovorans RK2-GFPuv was observed (Fig. 2 a and c). At 24 h culture time, both P. aeruginosa RR1 RK2-GFPuv and P. oleovorans RK2-GFPuv showed approximately an order of magnitude decrease in cfu/ml when kanamycin was included in the media. By 48 h, there was a decrease in cfu/ml of approximately two orders of magnitude. Further examination showed that despite the presence of selective kanamycin, plasmid maintenance levels were found to be low in the system (Fig. 2 b and d). Plasmid maintenance 24 h post inoculation was 9.3 ± 5.7% for P. aeruginosa RR1 RK2-GFPuv and decreased to 1.3 ± 0.9% by 48 h (Fig. 2 b). Plasmid maintenance at 24 h post inoculation for P. oleovorans RK2-GFPuv was 12.0 ± 1.6% and decreased to 0.0 ± 0% by 48 h (Fig. 2 d). This contrasts with cultures grown overnight (18 h) in LB media with kanamycin, which show plasmid maintenance levels of 79.3 ± 16.4% and 97.3 ± 0.9% for P. aeruginosa RR1 RK2-GFPuv and P. oleovorans RK2-GFPuv, respectively. The culture conditions for both strains were changed to 0.46% w/v hexadecane with 5 g/L NH 4 Cl (a condition that supported robust growth for both strains) to ascertain if the inhibited growth and plasmid maintenance could be alleviated by altering media composition. However, this made no substantial difference for growth or plasmid maintenance at 24 or 48 h post inoculation (Additional file 1 : Figure S5). It was hypothesized that the low copy number (3) of the RK2-GFPuv vector may cause difficulties with passage of the plasmid to daughter cells during growth in the hexadecane media [ 41 ]. Two new vectors, pBb(B5)1 k-GFPuv (B5-GFPuv) and pBb(RSF1010)1 k-GFPuv (RSF-GFPuv), were tested in P. aeruginosa RR1 (transformation of these vectors into P. oleovorans was unsuccessful) [ 29 ]. Plasmid B5-GFPuv has a copy number of 70, and RSF-GFPuv has a copy number of 30–60 in Pseudomonas, with both vectors containing an IPTG-inducible GPFuv gene and a kanamycin resistance gene [ 29 , 42 ]. These increased copy numbers did not yield improved outcomes, as both vectors still showed only single digit percentages of plasmid maintenance 48 h post inoculation and there was no substantial improvement in culture cfu/ml at when selective kanamycin was present (Additional file 1 : Fig. S6). Thus, it appears that the use of plasmids and antibiotic selection in Pseudomonas is not a feasible option for producing recombinant proteins in cultures with an alkane as a sole carbon source, independent of the culture conditions, specific species, or plasmid backbone. Genomic integration of recombinant GFPuv gene A strategy that excluded antibiotic selection and enabled higher maintenance of recombinant genes over a 96-h period was required to achieve measurable levels of recombinant protein production when Pseudomonas was grown on hexadecane. Genomic integration was identified as a method that would meet these criteria, and an IPTG-inducible recombinant GFPuv gene with a tac promoter was genomically integrated into P. aeruginosa RR1 to create the strain P. aeruginosa RR1 g-GFPuv. Integration of the GFPuv construct was confirmed with colony PCR (Additional file 1 : Fig. S7). The integration method utilizes two suicide vectors for the integration of constructs at a single att Tn 7 site within the Pseudomonas genome [ 30 ]. Mutants are isolated from wild type cells via the co-integration of a gentamycin resistance gene and subsequent plating on LB-gentamicin plates [ 30 ]. However, gentamicin is not required to maintain the genomic integration, which is reported to be stable for at least 100 generations [ 30 ]. Despite the successful transformation of the RK2-GFPuv vector into P. oleovorans , a genomic mutant of this species was unable to be created as neither transformation nor conjugation techniques could introduce the genomic integration suicide vectors into P. oleovorans . Thus, all subsequent work was performed with genomic mutants of P. aeruginosa RR1, however, future work should investigate new genomic integration techniques to analyze the performance of a genomically altered P. oleovorans strain. Experiments were first performed with rich LB media to ensure that recombinant expression of the integrated GFPuv gene could be achieved without gentamicin selection. Single colonies of P. aeruginosa RR1 g-GFPuv taken from LB-gentamicin plates were used to inoculate flask cultures of LB media (without gentamicin) that contained either 0, 0.3, or 1 mM IPTG. After overnight incubation (18 h) at 37 °C cells were harvested and the presence of fluorescent GFPuv can be seen when the lysates are exposed to UV light (Additional file 1 : Figure S8). Titers of GFPuv expressed from the genome were found to be 9.0 ± 1.6 mg/L with 0.3 mM IPTG and 9.9 ± 1.1 mg/L with 1 mM IPTG, which is similar to the GFPuv titer of 10.9 ± 2.73 mg/L when using the low-copy number RK2-GFPuv plasmid. Conversion of hexadecane to recombinant GFPuv and spider silk protein Although certain hexadecane culture conditions yielded more growth versus others for strain P. aeruginosa RR1, all tested conditions facilitated growth beyond 5 × 10 8 cfu/ml by 96 h and it was unknown if the best growth conditions would also result in the highest yields of recombinant protein. Likewise, the optimal time at which to induce cells with IPTG was unknown. Therefore, a fluorescence assay was developed to measure GFPuv titer directly from unpurified cell lysates to enable the testing of many conditions. Using 96 h total culture times, all twelve culture conditions that were tested for growth were also tested for recombinant GFPuv production. The twelve different culture conditions were each tested using three different expression conditions. They were induced with 0.3 mM IPTG at either 24-, 48-, or 72-h culture time (corresponding to 72-, 48-, and 24- hour expression times), thus, resulting in data for 36 different conditions for the conversion of hexadecane to recombinant GFPuv. Production of GFPuv from hexadecane can be seen in Additional file 1 : Figure S9, in which lysates of induced P. aeruginosa RR1 g-GFPuv show a green fluorescence under UV light as compared to pale blue fluorescence of uninduced cultures (the pale blue color is due to production of a natural pigment, pyocyanin) [ 43 ]. Figure 3 shows the GFPuv titer across all culture and expression conditions tested. The highest titer of 8.3 ± 0.5 mg/L was identified in culture conditions of 0.46% w/v hexadecane with 5 g/L NH 4 Cl that had been exposed to expression conditions of 0.3 mM IPTG added 24 h post inoculation (72-h expression time). This is approximately 92% of the GFPuv production level observed for P. aeruginosa RR1 g-GFPuv when grown in LB media with 0.3 mM IPTG. The second highest titers achieved for the conversion of hexadecane to recombinant GFPuv were approximately 25% less than this (Fig. 3 ). Therefore, 0.46% w/v hexadecane with 5 g/L NH 4 Cl was selected as the optimal culture condition for the conversion of hexadecane to a recombinant silk protein. Figures 3 and Additional file 1 : Fig. S9 also show that the time of induction affected GFPuv titer, with substantial decreases in visible fluorescence for titers below 4 mg/L. IPTG added at 24 or 48 h post inoculation (longer expression times) yielded increased titers versus IPTG added at 72 h for ten of the twelve different media compositions (Fig. 3 ). Longer expression times may be favorable for titers due to the slow growth kinetics of this system in comparison to cultures grown in rich media (Fig. 1 ). Results also show that when comparing cultures with identical hexadecane concentration, elemental nitrogen concentration, and IPTG induction times, those containing NH 4 Cl achieved higher GFPuv titers versus those containing NH 4 NO 3 in 15 out of 18 cases (Fig. 3 ). This finding is significant when considering that there is no significant difference in growth of P. aeruginosa RR1 on hexadecane when either NH 4 Cl or NH 4 NO 3 is used (Figs. 1 and Additional file 1 : Fig. S2). Counterintuitively, the single highest GFPuv levels achieved for both nitrogen sources used the lowest concentration of C16 (0.46% w/v) (Fig. 3 ). It is known that PHA synthesis in Pseudomonas is promoted by increasing the ratio of carbon to nitrogen in media, and this may shuttle cellular resources away from non-essential recombinant protein synthesis thus lowering titers [ 44 , 45 ]. Future work using 13 C-labeled hexadecane to do a metabolic-flux analysis may resolve differences in metabolism at various hexadecane concentrations and lead to a more developed understanding of this observation [ 46 ]. Fig. 3 Titers of recombinant GFPuv when strain P. aeruginosa RR1 g-GFPuv is grown on hexadecane under a variety of culture conditions. a Cultures grown with either 2.5 or 5 g/L of NH 4 Cl (2.5 Cl and 5 Cl). b Cultures grown with either 1.9 or 3.8 g/L of NH 4 NO 3 (1.9 NO 3 and 3.8 NO 3 ). Error bars represent standard deviations from the mean value of three replicates. 0.3 mM IPTG was added at 24, 48, or 72 h post inoculation. Total culturing time was 96 h, resulting in expression times of either 72, 48, or 24 h. Hexadecane concentrations (C16) are provided as % w/v We have previously produced the de novo designed recombinant silk protein, A5 4mer, in E. coli and this construct was genomically integrated into P. aeruginosa RR1 to form P. aeruginosa RR1 g-A5 [ 47 ]. The A5 4mer primary sequence (Additional file 1 : Fig. S1) was designed to represent a truncated version of dragline silk protein produced by spiders [ 47 ]. Expressions carried out in LB media demonstrated that P. aeruginosa RR1 g-A5 was able to produce the A5 4mer protein at a titer of 14.7 ± 1.57 mg/L when overnight cultures (18 h) inoculated from a single colony were grown at 37 ℃ in the presence of 1 mM IPTG. This also represented the first production of recombinant silk in the Pseudomonas genus. Unlike GFPuv, for which small amounts could be measured with fluorescence, a larger amount of A5 4mer protein was required for accurate measurements of titer. Therefore, larger culture volumes were employed for the conversion of hexadecane to recombinant silk. A single colony of P. aeruginosa RR1 g-A5 was used to inoculate a 25 ml starter culture of 0.46% w/v hexadecane with 5 g/L NH 4 Cl. After 72 h of culture time, the entire 25 ml starter culture was used to inoculate a 200 ml expression culture containing 0.46% w/v hexadecane with 5 g/L NH 4 Cl and supplemented with either 0.3 or 1 mM IPTG. The expression culture was then incubated for 48, 60, or 72 h. Figure 4 shows A5 4mer silk protein purified from a culture of P. aeruginosa RR1 g-A5 grown using hexadecane as the sole carbon source and an expression time of 60 h. The purified protein can be seen at an identical molecular weight as standards of the protein produced in E. coli (Fig. 4 ). As previously documented, the 16 kDa A5 4mer silk protein appears at ~ 38 kDa due to its high level of structural disorder and subsequent aberrant mobility through SDS PAGE [ 47 ]. This represents the first conversion of an alkane to a recombinant silk protein or protein-based material. The highest titers of approximately 10 mg/L were achieved at 60- or 72-h expression time and 1 mM IPTG, with only a negligible difference between two expression times (Fig. 5 ). Interestingly, the similarity in titer between the 60- and 72-h mark coincided with a plateau of the wet pellet mass at harvest. The change in wet pellet mass from 48 to 60 h was + 1.9 g/L, but only + 0.3 g/L from 60 to 72 h (Fig. 5 ). Increasing the IPTG concentration from 0.3 mM to 1 mM increased the silk protein titer by approximately 41% and 36% for the 48- and 60/72-h expressions, respectively. The expression cultures were observed to be relatively clear directly after inoculation with the starter culture. However, progressive increases in turbidity were observed over time in accordance with increases in cfu/ml, with cultures becoming completely opaque at the time of harvest (Additional file 1 : Fig. S10). Expression cultures developed pale orange color that progressed to a darker, burnt orange tone over time (Fig. S10). Fig. 4 SDS PAGE after nickel chromatography showing the A5 4mer silk protein purified from lysates of P. aeruginosa RR1 g-A5 that were grown using hexadecane as the sole carbon source (culture conditions of 0.46% w/v hexadecane with 5 g/L NH 4 Cl and induced with 1 mM IPTG). Expression time was 60 h. Lanes (1) Protein ladder, with mass listed to left in kDa (2) flow through (3) wash (4) first elution fraction (5) second elution fraction (6–9) standards of A5 4mer protein, 2, 1, 0.5, and 0.25 mg/L. The band in lane 4 (first elution fraction) is shown at an identical molecular weight (~ 38 kDa) as the standards of A5 4mer protein produced in E. coli (lanes 6–9). As previously documented, the 16 kDa A5 4mer silk protein appears at ~ 38 kDa due to its high level of structural disorder and subsequent aberrant mobility through SDS PAGE [ 47 ]. A slight smiling effect was observed on the SDS PAGE, resulting in a slightly slower migration of outer lanes (Lanes 1,2 and 5–8) compared to inner lanes (Lane 4) [ 48 , 49 ]. The faint protein band to the right of Lane 4 is the remainder of histidine-tagged silk protein that was still bound to the purification resin after the Lane 4 elution Fig. 5 a Titer of the A5 4mer produced in P. aeruginosa RR1 g-A5 grown on hexadecane (culture conditions of 0.46% w/v hexadecane with 5 g/L NH 4 Cl). Expression times were either 48, 60, or 72 h and cultures were induced with either 0.3 or 1 mM IPTG. b Wet pellet mass at the end of A5 4mer expressions. Error bars represent standard deviations from the mean value of three replicates Conversion of polyethylene-derived hydrocarbons to recombinant silk protein Samples of depolymerized polyethylene were obtained to determine if our results could be extended to plastic-derived substrates. Polyethylene ( M w = 4,000 g/mol, M n = 1,700 g/mol, and Đ = 2.35) was depolymerized via catalytic hydrogenolysis using a Pt/SrTiO 3 catalyst in a batch reactor at 300 °C, in presence of 170 psi of H 2 for 72 h under solvent-free conditions [ 50 , 51 ]. This method confers control over the size and dispersity of the products and was leveraged to produce hydrocarbons within the range that P. aeruginosa can metabolize (approximately C 8 -C 27 ) [ 22 , 50 , 51 ]. This is the first report to use such a method for the generation of a microbial feedstock from a plastic substrate. Previous reports have used methods such as pyrolysis or alkaline hydrolysis [ 14 , 22 ]. It should be noted that unlike the monodisperse and linear hexadecane used previously herein, the chemically depolymerized polyethylene sample created in this study contains a distribution of alkanes ( M w = 305 g/mol, M n = 240 g/mol, and Đ = 1.26) and a non-negligible degree of branching (N branch/1000C = 111). The sample is white and has the consistency of a soft wax (Additional file 1 : Fig. S11). Several experiments were performed to establish robust growth of P. aeruginosa RR1 g-A5 when using this sample as the sole carbon source. For all growth experiments, the supplemental nitrogen was held constant at 5 g/L NH 4 Cl, as this provided the best GFPuv titers and facilitated the conversion of hexadecane to recombinant silk. Figure 6 a depicts the average cfu/ml 96 h after inoculation for P. aeruginosa RR1 g-A5 grown using the depolymerized polyethylene sample as the sole carbon source supplied at either 12.5 or 25 g/L. Preliminary experiments were performed by simply depositing centimeter-scale chunks of the depolymerized polyethylene sample into culture flasks, with cohesion of the sample resulting in a floating bolus (Fig. 6 a “bolus”, Fig S12a). Growth of P. aeruginosa RR1 g-A5 using this method was suboptimal compared to results obtained with hexadecane, reaching cfu/ml levels several times below that of optimized conditions using hexadecane (Figs. 1 and 6 a). It was hypothesized that increasing the surface area of the depolymerized polyethylene sample may allow the cells improved access to the substrate and facilitate increased growth. As such, multiple alternative morphologies of the depolymerized polyethylene sample within the culture flask were tested (Additional file 1 : Fig. S12). A hot plate was used to melt the sample and coat the bottom of the culture flasks prior to the addition of media and cells. This resulted in coatings that contained no gaps in the coverage of the flask within their area (Additional file 1 : Fig. S12b). Although the sample surface area was increased relative to a bolus, no improvements in growth over 96 h were observed (Fig. 6 a “coated”). However, growth was substantially improved if the coating was manually disrupted with a sterile metal laboratory scoop to form an imperfect coating with gaps in the coverage of the flask (Fig. 6 a “imperfect coating”, Fig. 6 b, Additional file 1 : Fig. S12d). This method yielded an average cfu/ml of 3.9 ± 0.6 and 4.2 ± 0.9 × 10 9 at 96 h post inoculation for 12.5 and 25 g/L of substrate, respectively. While functional, it should be acknowledged that the preparation of the “imperfect coating” via manual disruption with a laboratory scoop was not standardized and was thus subject to variability in terms of final morphology. Future work should seek to prepare hydrocarbon substrates into well-defined geometries with high surface area, such as micro or nano-scale particles. Notwithstanding, this imperfect coating method surpasses the highest levels of growth achieved with optimized conditions using hexadecane as the sole carbon source (Figs. 1 and 6 a). To our knowledge, this is the highest reported level of cell growth achieved for a microbial strain grown on a polyethylene-derived, or alkane-based, substrate as the sole carbon source. A final sample preparation method was also tested, in which a bolus of the sample was melted on top of heated culture media placed in a flask (prior to inoculation). Upon cooling, the sample formed a solid, thin floating disk that could be broken into smaller pieces with a pipette tip or prolonged agitation in an incubator (Fig. 6 a “floating disk”, Additional file 1 : Fig. S12c). This method also yielded robust cfu/ml at 96 h, although slightly lower than an imperfect coating (Fig. 6 a). Moreover, it was observed that pieces of the “floating disk” substrate tended to adhere to upper regions of the flask upon shaking incubation, effectively removing them from the culture media unless manually pushed down. For these reasons, the method of generating an imperfect coating of the substrate was chosen for silk protein expressions. Likewise, 12.5 g/L was chosen instead of 25 g/L due to similar growth between the two conditions and the ability to conserve the depolymerized polyethylene sample (Fig. 6 a “imperfect coating”). Fig. 6 a Average cfu/ml 96 h post inoculation for P. aeruginosa RR1 g-A5 grown using depolymerized polyethylene as the sole carbon source. Multiple concentrations (12.5 and 25 g/L) and morphologies of the depolymerized polyethylene were tested, with 5 g/L NH 4 Cl supplied as the nitrogen source. Error bars represent standard deviations from the mean values of three replicates. b Depiction of the “Imperfect Coating” preparation method. Samples of the depolymerization polyethylene were added to flasks and gently melted to form a coating on the bottom. Upon solidification, the coatings were agitated to create an imperfect coating coverage. Sections of coating that were removed were added back into the flask as small boluses to maintain consistency in the total amount of sample per liter of culture An expression strategy derived from results using hexadecane was applied for the conversion of polyethylene to recombinant silk. A 25 ml starter culture was grown for 72 h, and the entire culture was used to inoculate 200 ml of fresh media (with 1 mM IPTG) for a 72-h expression period. Both the starter cultures and expression cultures contained 12.5 g/L of depolymerized polyethylene prepared using the imperfect coating method. Akin to expressions using hexadecane, cultures utilizing depolymerized polyethylene were clear upon inoculation and increased in turbidity over time in accordance with cell growth, resulting in extremely turbid cultures at harvest (Additional file 1 : Fig. S13). At harvest, however, expression cultures utilizing depolymerized polyethylene were observed to be a pale brown color versus the burnt orange observed when hexadecane was used (Additional file 1 : Fig. S13d). Nickel chromatography on lysates of expression cultures of P. aeruginosa RR1 g-A5 grown using depolymerized polyethylene as the sole carbon source showed the A5 4mer protein in the elution fraction, (Additional file 1 : Fig. S14) thus demonstrating the conversion of polyethylene to a recombinant protein-based polymer material. Titers of the silk protein were 11.3 ± 1.1 mg/L, which is approximately 77% of the production level observed in rich LB media for strain P. aeruginosa RR1 g-A5. Samples of the A5 4mer spider silk protein produced via the microbial conversion of depolymerized polyethylene were dialyzed into water and lyophilized, resulting in white, cohesive biopolymer material (Fig. 7 ). Fig. 7 Purified A5 4mer spider silk protein produced through the microbial conversion of depolymerized polyethylene. The silk protein was dialyzed into water and lyophilized, resulting in several discrete and cohesive chunks of a white, polymeric material that ranged in length from approximately 1.5–4 cm. This image was obtained directly after the freeze-drying process, and the protein sample had not been spun into fibers or put through any additional material processing In conclusion, this work demonstrates the first reported microbial platform for the conversion of polyethylene-derived substrates to a bespoke recombinant protein. Our results also demonstrate the first recombinant silk production in the Pseudomonas genus. Additionally, culture conditions and specific polyethylene depolymerization parameters that yield levels of microbial growth using a plastic-derived substrate as the sole carbon source are identified. Although a plasmid-based expression system was inefficient, genomic integration of recombinant genes was found to be a viable strategy for facilitating the microbial conversion of depolymerized polyethylene into recombinant proteins. Taken together, these findings demonstrate the modularity this novel system, which can potentially be used to upcycled waste polyolefins into any recombinant protein that can be integrated into the genome of P. aeruginosa RR1. Future work will seek to increase production levels of recombinant constructs through optimization of the recombinant gene. In this context, multi-copy integrations of heterologous genes may increase production levels compared to the single copy integrations reported in this work. Likewise, the use of a stronger promoter on recombinant integrations (such as T7) may yield increased titers compared to the tac promoter used in this work. Additionally, future work may seek to decrease the time required for P. aeruginosa RR1 to reach > 1 × 10 9 cfu/ml when depolymerized polyethylene is the sole carbon source, thus increasing the efficiency and decreasing the cost of the process. Within this scope, fundamental work that can identify metabolic bottlenecks when Pseudomonas is grown on alkane-based substrates by way of metabolic flux analysis (using 13 C-labeled feedstocks) and quantify the amount of substrate consumed by the cells and its conversion rate to recombinant protein are also important aspects of future work [ 46 ]. Potential strategies to increase the rate of growth include the testing of additional morphologies of the depolymerized polyethylene sample or upregulation of endogenous alkane hydroxylases within Pseuodmonas [ 28 ]. Furthermore, the use of a depolymerization process that yields oxidized hydrocarbon substrates of increased solubility may be advantageous by promoting faster uptake of the carbon source into the cells. Oxidized substrates can also bypass the first, and possibly rate-limiting, step of terminal oxidation that occurs in the alkane degradation pathway used by Pseudomonas [ 52 , 53 ] . Since P. aeruginosa is an opportunistic pathogen, future work should also seek to implement non-pathogenic strains of P. aeruginosa to promote the optimization and scale-up of this process by ensuring a high degree of safety [ 54 ]. Recent work shas hown that the virulence of P. aeruginosa can be attenuated by deleting five chromosomal genes ( toxA , plcH , phzM , wapR , and aroA ) through a plasmid-based methods [ 55 ]. This resultant strain exhibits a mortality rate of 0% in mice upon injection, as compared to a 95% mortality rate of wild-type P. aeruginosa [ 55 ] . However, it is unknown if these genetic changes will impact the efficiency of cell growth and recombinant protein production when hydrocarbon-rich substrates are used as the sole carbon source."
} | 11,033 |
32877528 | PMC7783167 | pmc | 1,320 | {
"abstract": "Abstract The genus Acropora comprises the most diverse and abundant scleractinian corals (Anthozoa, Cnidaria) in coral reefs, the most diverse marine ecosystems on Earth. However, the genetic basis for the success and wide distribution of Acropora are unknown. Here, we sequenced complete genomes of 15 Acropora species and 3 other acroporid taxa belonging to the genera Montipora and Astreopora to examine genomic novelties that explain their evolutionary success. We successfully obtained reasonable draft genomes of all 18 species. Molecular dating indicates that the Acropora ancestor survived warm periods without sea ice from the mid or late Cretaceous to the Early Eocene and that diversification of Acropora may have been enhanced by subsequent cooling periods. In general, the scleractinian gene repertoire is highly conserved; however, coral- or cnidarian-specific possible stress response genes are tandemly duplicated in Acropora . Enzymes that cleave dimethlysulfonioproprionate into dimethyl sulfide, which promotes cloud formation and combats greenhouse gasses, are the most duplicated genes in the Acropora ancestor. These may have been acquired by horizontal gene transfer from algal symbionts belonging to the family Symbiodiniaceae, or from coccolithophores, suggesting that although functions of this enzyme in Acropora are unclear, Acropora may have survived warmer marine environments in the past by enhancing cloud formation. In addition, possible antimicrobial peptides and symbiosis-related genes are under positive selection in Acropora , perhaps enabling adaptation to diverse environments. Our results suggest unique Acropora adaptations to ancient, warm marine environments and provide insights into its capacity to adjust to rising seawater temperatures.",
"conclusion": "Conclusion These comparative genomic analyses reveal genomic novelties that could have allowed Acropora ancestors to survive dynamic environmental changes during geological periods much warmer than the present. Acropora -specific gene duplications in probable stress responsive genes (Caspase-X and SCRiPs), and DMSP lyases may also enable Acropora to cope with elevated ocean temperatures and to disperse and thrive around the world. Although further investigation will be needed, we identified candidate genes involved in Acropora diversification. Genetic mechanisms that enabled Acropora corals to survive past global warming periods may permit them to cope with current global warming. However, the speed of modern climate change may exceed their capacity to adapt, particularly when also confronting local anthropogenic stressors, such as coastal pollution and overexploitation. The present genomic resources, together with further molecular studies, will provide a powerful resource to understand how Acropora diversity originated and has been maintained.",
"introduction": "Introduction Coral reefs support the most diverse marine ecosystems on Earth ( Wilkinson 2008 ). Coral reef structure depends upon calcium carbonate deposition by anthozoan cnidarians known as scleractinian corals. Corals form obligate endosymbioses with photosynthetic dinoflagellates of the family Symbiodiniaceae, which supply the vast majority of their photosynthetic products to the host corals ( Yellowlees et al. 2008 ). However, corals face a range of anthropogenic challenges, including ocean acidification and increasing seawater temperatures ( Hoegh-Guldberg et al. 2007 ). Tropical storms, predation by crown-of-thorns starfish, and coral bleaching, a breakdown of the mutualism between corals and their symbiotic dinoflagellates caused by high ocean temperatures, are major causes of coral reef decline ( De'ath et al. 2012 ). Bleaching has been observed around the world with increasing frequency ( Hughes et al. 2017 ; Nakamura 2017 ). Loss of coral reefs also destroys the habitats of diverse marine species, making extensive loss of reef habitats one of the most pressing environmental issues of our time. The genus Acropora (Family Acroporidae) is a keystone reef taxon globally, distributed from the Red Sea through the Indo-Pacific Ocean to the Caribbean. It is also the most diverse and abundant taxon, with more than 100 described species ( Wallace 1999 ). The high growth rate of Acropora corals contributes significantly to reef growth, island formation, coastal protection, and support for fisheries ( Shinn 1966 ; Bruckner 2002 ). The complex, 3D structures of Acropora corals provide habitat and refuge for more than a million species of marine organisms ( Hinrichsen 1997 ; Knowlton et al. 2010 ). Acropora species are highly susceptible to coral bleaching induced by increasing seawater temperatures ( Marshall and Baird 2000 ; Loya et al. 2001 ; Hughes et al. 2018 ); hence, they are expected to decline in the near future ( Alvarez-Filip et al. 2013 ). Due to their bleaching susceptibility, more than 70% of acroporid species are listed as near threatened or threatened in the International Union for Conservation of Nature Red List ( Carpenter et al. 2008 ). The evolutionary history of Acropora is complex, with gaps in molecular data and fossil records. Although a molecular phylogenetic analysis using mitochondrial genes suggested that modern diversification of Acropora from a single Pliocene ancestor probably occurred after the Miocene, around 2 Ma ( Fukami et al. 2000 ), recent molecular phylogenetic analysis using nuclear and mitochondrial genes suggested that divergence of Acropora started around 34 Ma ( Richards et al. 2013 ). Despite its bleaching susceptibility, the first appearances of Acropora in the fossil record are from Somalia ( Carbone et al. 1993 ) and Austria ( Baron-Szabo 2006 ) during the Paleocene (66 Ma), a warmer period than the present, in which there was no sea ice. An Acropora -dominated fossil assemblage is first seen in the Oligocene of Greece ( Schuster 2000 ). It has been reported that 12 extant species were already present in the Indo-Pacific in the Early Miocene, suggesting that speciation and diversification of Acropora occurred throughout the Cenozoic, in different world regions, including the Indo-Pacific ( Santodomingo et al. 2015 ). In addition to Acropora fossil records from the Paleogene period (Paleocene, Eocene, and Oligocene), the presence of Acropora corals in seasonal warm water environments (the Southern Red Sea, Persian Gulf) as well as locations with large daily thermal fluctuations (reef pools in Ofu, Samoa) also suggest that they have the potential to cope with elevated ocean temperatures ( Barshis et al. 2013 ; Coles and Riegl 2013 ). The Intergovernmental Panel on Climate Change (IPCC) intermediate RCP 6.0 scenarios predicts that the global mean temperature will rise by average of 2.2 °C by AD 2100 ( IPCC 2013 ). How did Acropora corals survive under past warm ocean conditions and how will they cope with climate changes occurring today? Because of the ecological significance of Acropora , the complete genome of Acropora digitifera was the first coral genome sequenced ( Shinzato et al. 2011 ), and additional coral genomic data are becoming available ( Prada et al. 2016 ; Voolstra et al. 2017 ; Cunning et al. 2018 ; Ying et al. 2018 , 2019 ; Helmkampf et al. 2019 ; Shumaker et al. 2019 ). In order to identify genomic novelties that enabled Acropora to disperse widely and thrive, and to adapt to warmer environments, we sequenced genomes of 15 Acropora species ( A. acuminata , A. awi , A. cytherea , A. digitifera , A. echinata , A. florida , A. gemmifera , A. hyacinthus , A. intermedia , A. microphthalma , A. muricata , A. nasta , A. selago , A. tenuis , and A. yongei ) (fig. 1). We further sequenced genomes of confamilial taxa, Montipora cactus , M. efflorescens , and Astreopora myriophthalma . Montipora is another speciose genus ( fig. 1 ) ( Veron 2000 ), and Astreopora represents the basal clade of the Acroporidae, based on molecular data ( Fukami et al. 2000 ). Together with available coral and anthozoan cnidarian genomic data, we examine genomic novelties that could shed light on the evolutionary success of Acropora . Understanding such genetic mechanisms may facilitate predictions about whether and how can they survive current global warming.\n Fig. 1. Fifteen Acropora , two Montipora , and Astreopora species for which we sequenced complete genomes in this study. ( A ) Acropora acuminata , ( B ) A. awi , ( C ) A. cytherea , ( D ) A. digitifera , ( E ) A. echinata , ( F ) A. florida , ( G ) A. gemmifera , ( H ) A. hyacinthus , ( I ) A. intermedia , ( J ) A. microphthalma , ( K ) A. muricata , ( L ) A. nasta , ( M ) A. selago , ( N ) A. tenuis , ( O ) A. yongei , ( P ) Montipora cactus , ( Q ) M. efflorescens , ( R ) Astreopora myriophthalma .",
"discussion": "Results and Discussion Whole-Genome Assembly and Gene Predictions for Acroporid Corals For the 15 Acropora species, we obtained draft genome assemblies of 384–447 Mb with N50 sizes from 575 kb to 3 Mb ( table 1 ). These represent significant improvements over the first version of the A. digitifera genome assembly (N50, 484 kb) ( Shinzato et al. 2011 ), and are of comparable or better quality than other coral genomes reported in the NCBI Reference Sequence (RefSeq) database, in terms of N50 sizes and numbers of scaffold sequences ( table 1 ). In contrast to the ∼30,000 gene models in previous Acropora genome assemblies, without performing error correction or removing haplotype sequences ( Mao et al. 2018 ), we predicted ∼22,000 genes from each Acropora species ( table 1 ). Table 1. Genome Assembly and Gene Prediction Statistics for Acropora , Montipora , and Astreopora Species (family Acroporidae) Used in This Study and Comparisons with Publicly Available Scleractinian Coral Genomes (NCBI RefSeq). Coral Species Total Assembly Size (Mb) Gap Rate (%) No. Scaffolds Scaffold N50 (kb) No. Predicted Genes BUSCO Completeness % (upper: genome assembly, lower: gene model) Accession Numbers or Reference This study \n Acropora acuminata \n 395 5.3 3,293 1,005 21,904 \n C:91.5 [S:89.8, D:1.7], F:1.4, M:7.1 \n C:93.8 [S:92.2, D:1.6], F:2.0, M:4.2 \n BLEZ01000001-BLEZ01003293 \n Acropora awi \n 429 13.3 2,821 1,089 22,491 \n C:89.2 [S:88.2, D:1.0], F:1.8, M:9.0 \n C:92.7 [S:91.8, D:0.9], F:3.5, M:3.8 \n BLFA01000001-BLFA01002821 \n Acropora cytherea \n 426 6.1 4,046 1,084 22,584 \n C:90.4 [S:86.5, D:3.9], F:1.9, M:7.7 \n C:91.9 [S:90.2, D:1.7], F:3.4, M:4.7 \n BLFB01000001-BLFB01004046 \n Acropora digitifera \n 416 0.4 955 1,856 22,221 \n C:90.2 [S:88.7, D:1.5], F:1.6, M:8.2 \n C:92.4 [S:90.6, D:1.8], F:3.7, M:3.9 \n BLFC01000001-BLFC01000955 \n Acropora echinata \n 401 14.7 2,002 1,917 21,554 \n C:87.7 [S:86.4, D:1.3], F:2.5, M:9.8 \n C:91.4 [S:89.9, D:1.5], F:3.7, M:4.9 \n BLFD01000001-BLFD01002002 \n Acropora florida \n 442 9.1 6,979 751 23,237 \n C:88.6 [S:86.2, D:2.4], F:2.8, M:8.6 \n C:92.6 [S:90.8, D:1.8], F:3.5, M:3.9 \n BLFE01000001-BLFE01006979 \n Acropora gemmifera \n 401 9.5 2,274 1,141 21,983 \n C:88.6 [S:87.3, D:1.3], F:3.0, M:8.4 \n C:91.1 [S:90.0, D:1.1], F:4.3, M:4.6 \n BLFF01000001-BLFF01002274 \n Acropora hyacinthus \n 447 7.8 2,758 1,584 22,464 \n C:90.7 [S:87.8, D:2.9], F:1.5, M:7.8 \n C:93.4 [S:92.1, D:1.3], F:1.7, M:4.9 \n BLFG01000001-BLFG01002758 \n Acropora intermedia \n 417 5.3 6,224 577 22,835 \n C:90.6 [S:87.9, D:2.7], F:1.4, M:8.0 \n C:93.0 [S:91.6, D:1.4], F:2.9, M:4.1 \n BLFH01000001-BLFH01006224 \n Acropora microphthalma \n 384 9.3 4,878 1,061 22,016 \n C:88.6 [S:86.9, D:1.7], F:2.6, M:8.8 \n C:91.1 [S:89.9, D:1.2], F:3.6, M:5.3 \n BLFI01000001-BLFI01004878 \n Acropora muricata \n 421 6.8 6,861 575 23,103 \n C:88.3 [S:85.8, D:2.5], F:3.2, M:8.5 \n C:92.0 [S:90.3, D:1.7], F:3.4, M:4.6 \n BLFJ01000001-BLFJ01006861 \n Acropora nasta \n 416 7.2 4,717 1,051 22,545 \n C:90.5 [S:86.4, D:4.1], F:1.7, M:7.8 \n C:92.4 [S:91.4, D:1.0], F:2.7, M:4.9 \n BLFL01000001-BLFL01004717 \n Acropora selago \n 393 6.2 5,816 657 22,616 \n C:87.6 [S:85.5, D:2.1], F:3.5, M:8.9 \n C:90.1 [S:89.0, D:1.1], F:4.9, M:5.0 \n BLFM01000001-BLFM01005816 \n Acropora tenuis \n 403 7.4 1,538 1,166 22,802 \n C:90.5 [S:89.4, D:1.1], F:1.8, M:7.7 \n C:94.6 [S:93.9, D:0.7], F:2.8, M:2.6 \n BLAZ01000001-BLAZ01001538 \n Acropora yongei \n 438 6.7 1,010 3,033 23,044 \n C:88.6 [S:86.2, D:2.4], F:2.8, M:8.6 \n C:93.6 [S:92.0, D:1.6], F:3.3, M:3.1 \n BLFN01000001-BLFN01001010 \n Astreopora myriophthalma \n 373 5.4 1,149 1,634 28,712 \n C:89.3 [S:87.7, D:1.6], F:2.6, M:8.1 \n C:83.2 [S:82.0, D:1.2], F:6.4, M:10.4 \n BLFK01000001-BLFK01001149 \n Montipora cactus \n 653 7.9 4,925 899 21,983 \n C:88.5 [S:86.7, D:1.8], F:2.7, M:8.8 \n C:86.0 [S:85.4, D:0.6], F:5.2, M:8.8 \n BLFO01000001-BLFO01004925 \n Montipora efflorescens \n 643 9.0 5,162 1,132 21,370 \n C:86.4 [S:84.8, D:1.6], F:2.7, M:10.9 \n C:84.3 [S:84.0, D:0.3], F:5.2, M:10.5 \n BLFP01000001-BLFP01005162 NCBI RefSeq \n Acropora digitifera \n 419 15.2 2,420 484 26,060 \n C:75.9 [S:71.0, D:4.9], F:8.5, M:15.6 \n C:80.7 [S:74.2, D:6.5], F:9.2, M:10.1 \n \n Shinzato et al. (2011) \n \n Acropora millepora \n 387 9.7 3,869 494 23,710 \n C:91.3 [S:89.5, D:1.8], F:1.5, M:7.2 \n C:96.0 [S:94.5, D:1.5], F:1.5, M:2.5 \n \n Ying et al. (2019) \n \n Montipora capitata \n 614 6.9 27,865 185 NA \n C:82.1 [S:80.9, D:1.2], F:6.6, M:11.3 \n NA \n \n Helmkampf et al. (2019) \n \n Stylophora postillata \n 400 10.5 5,687 457 24,833 \n C:88.3 [S:86.8, D:1.5], F:3.3, M:8.4 \n C:96.7 [S:81.3, D:15.4], F:1.5, M:1.8 \n \n Voolstra et al. (2017) \n \n Orbicella faveolata \n 486 26.7 1,932 1,162 25,916 \n C:85.8 [S:83.2, D:2.6], F:4.5, M:9.7 \n C:90.0 [S:87.1, D:2.9], F:5.0, M:5.0 \n \n Prada et al. (2016) \n \n Pocillopora damicornis \n 234 3.7 4,392 326 19,935 \n C:89.2 [S:88.7, D:0.5], F:2.4, M:8.4 \n C:94.0 [S:93.5, D:0.5], F:2.5, M:3.5 \n \n Cunning et al. (2018) \n \n Note .—C, complete BUSCOs; S, complete and single-copy BUSCOs; D, complete and duplicated BUSCOs; F, fragmented BUSCOs; M, missing BUSCOs; NA, not available in NCBI RefSeq100. Benchmarking Universal Single-Copy Orthologs (BUSCO) analyses ( Simao et al. 2015 ; Waterhouse et al. 2018 ), which assess whether universal single-copy orthologous genes observed in more than 90% of metazoan species from the OrthoDB database of orthologs ( www.orthodb.org , version 9) are recovered in a genome/transcriptome assembly, yielded completeness scores of genome assemblies and gene models of around 89% and 92% (average of Complete BUSCO %), respectively, in all of these Acropora species ( table 1 ). The Montipora and Astreopora genome assemblies were of comparable quality ( table 1 ). BUSCO completeness scores of both genome assemblies and gene models of the acroporid genomes were also comparable to those of other coral genomes available in NCBI RefSeq ( table 1 ), indicating that these draft genome assemblies and gene predictions are of reasonable quality. Genome Organization of Acroporid Genomes Not surprisingly, proportions of various repetitive elements and repeat landscapes were similar among the acroporid genomes ( supplementary fig. S1 , Supplementary Material online). In Acropora , about 40–45% of the genomes consist of interspersed repeats ( supplementary fig. S1 , Supplementary Material online). In Montipora , 50% of the genomes comprise repeats, possibly reflecting larger assembled sizes than those of Acropora ( supplementary fig. S1 , Supplementary Material online, table 1 ). The most abundant repeat types were long interspersed nuclear element (LINE) and short interspersed nuclear element (SINE), among the annotated elements, but the majority of the repeats, comprising 28–30% of the genomes, seem to be novel and possibly acroporid- or anthozoan-specific ( supplementary fig. S1 , Supplementary Material online). In order to compare genome organization of Acropora and other anthozoan genomes, A. digitifera scaffolds containing at least 100 orthologous groups (OGs, see below) shared with other Acropora species, resulting in 38 scaffolds (125.7 Mb, 30% of the genome), were used to evaluate synteny. Genome alignments to individual scleractinian genomes revealed high conservation of genome organization within Acropora ( supplementary fig. S2 , Supplementary Material online). Commensurate with phylogenetic distances to Acropora , conservation of genome organization among acroporids ( Montipora and Astreopora ), another scleractinian ( Orbicella ), and a sea anemone ( Nematostella ) diminished progressively ( supplementary fig. S2 , Supplementary Material online). To determine whether large-scale (whole genome or chromosomal level) genome duplication occurred in the anthozoan lineage, we performed phylogenetic analyses of anthozoan genes (24 proteomes) using 300 randomly selected protein sequences from A. digitifera . We show 22 examples of phylogenetic analyses that were based on an alignment of ≥150 AAs in more than 80 gene sequences or ≥200 AAs in more than 40 gene sequences from 24 anthozoan proteomes ( supplementary fig. S3 , Supplementary Material online). Almost all nodes supported by high bootstrap values (>80%) contained one sequence from each anthozoan species ( supplementary fig. S3 , Supplementary Material online). In addition, there was no clear signature of large-scale duplications in genome alignment dotplots ( supplementary fig. S2 , Supplementary Material online). Consequently, in contrast to a suggested whole-genome duplication event in the common ancestor of Acropora ( Mao and Satoh 2019 ), we detected no incontrovertible evidence of whole-genome or large-scale duplication events in any anthozoan lineage, including scleractinians, the Acroporidae, or the genus Acropora , in this study. Thus, we did not take genome duplication events into account in subsequent analyses. Common Characteristics of Gene Repertoires of Scleractinians and Acroporids In addition to the acroporid genomes, we used publicly available gene models of two anemones, Nematostella vectensis ( Putnam et al. 2007 ) and Exaiptasia palida ( Baumgarten et al. 2015 ), two corallimorpharians, Amplexidiscus fenestrafer and Discosoma spp. ( Wang et al. 2017 ), and two scleractinians, Stylophora pistillata ( Voolstra et al. 2017 ) and Orbicella faveolata ( Prada et al. 2016 ) for OG clustering. Examination of OGs in anthozoan genomes allowed us to identify 21,697 OGs in all taxa, 20,765 in scleractinians, 19,737 in acroporids, and 18,692 in Acropora . Approximately 98% of Acropora genes and 93–97% of those of other acroporids ( Montipora and Astreopora ) belonged to OGs identified in other scleractinian species ( fig. 2 A , supplementary tables S1 and S2 , Supplementary Material online), indicating high conservation of gene repertoires among scleractinians. Of the 21,697 OGs, 27 were exclusive to all scleractinians, but not observed in other groups, 48 to the Acroporidae, and 90 to Acropora ( supplementary tables S3–S5 , Supplementary Material online). Among the 27 OGs exclusive to scleractinians, a known coral calcification gene, skeletal aspartic acid-rich protein 2 ( Ramos-Silva et al. 2013 ), was included (OG0002460, supplementary table S3 , Supplementary Material online), suggesting that this gene might be essential for coral skeleton formation. In addition, we also identified OGs that were not found in any corals ( supplementary tables S6–S8 , Supplementary Material online), suggesting that these OGs were either lost in the coral clade, or that they arose after its divergence. In a previous study, we reported that cystathionine ß-synthase, an essential enzyme for cysteine biosynthesis, was possibly lost from the A. digitifera genome ( Shinzato et al. 2011 ). As Acropora species are sensitive to bleaching ( Loya et al. 2001 ), it is likely that Acropora depends upon symbiotic dinoflagellates to produce cysteine. In this study, we were unable to detect this gene in any acroporid genome, but we did identify it in other coral, corallimorpharian, and sea anemone genomes (OG0014971, supplementary table S7 , Supplementary Material online), supporting the notion that this enzyme was lost in the common ancestor of the Acroporidae and that differences in dependency on symbiotic algae could partially explain the high sensitivity of Acropora to bleaching. Fig. 2. Comparisons of orthologous groups and phylogenetic relationships of anthozoan genomes. ( A ) Proportions of shared orthologous group genes among anthozoans. Scleractinians are shaded in blue. Astreopora and Montipora species are in yellow, and Acropora species are in red. ( B ) Molecular phylogeny of anthozoans using 818 single-copy orthologous genes (176,160 amino acids). Nodes with 100% bootstrap support are shown with black circles. Phylogenomic Analysis Revealed That the Common Ancestor of Acropora Survived Warm Periods without Sea Ice from the Mid or Late Cretaceous to the Early Eocene Phylogenomic analysis of these anthozoan genomes using 818 single-copy OGs yielded robust phylogenetic relationships, with the major anthozoan cnidarian clades being supported by 100% bootstrap values ( fig. 2 B ). Almost all nodes among the 15 Acropora species in four distinct clades were also supported by 100% bootstrap values ( fig. 2 B ), indicating that these molecular phylogenetic relationships are well supported and are likely to reflect evolutionary relationships of the 15 Acropora species. Acropora corals exhibit diverse morphologies (arborescent, hispidose, corymbose, table, etc.) ( Wallace 1999 ), and each clade contains species with different morphologies. For instance, hispidose branching corals, A. awi and A. echinata belong to Clades II and IV, respectively ( figs. 1 and 2 ), indicating that the diverse colony forms of Acropora are the result of convergent evolution in each clade. Molecular dating analysis using 2,126 single-copy OGs indicates that common ancestors of the Family Acroporidae emerged 199–147 Ma, whereas those of the genus Acropora appeared later, between 119 and 52 Ma ( fig. 3 ). In contrast to the suggested divergence timing of Acropora in a previous study using five genomes (<15 Ma) without using scleractinian fossil records for dating calibration ( Mao et al. 2018 ), diversification of Acropora was thought to have occurred during the Eocene and Oligocene (around 25–50 Ma), possibly accounting for the high species diversity of Acropora fossils known from the Miocene (5.3–23 Ma) and the existence of 12 extant species in the Early Miocene ( fig. 3 ) ( Santodomingo et al. 2015 ). Although these molecular dating estimates could shift as additional fossils are discovered, our data suggest that the Acropora common ancestor originated and survived in warm environments during the mid–late Cretaceous and the Paleocene–Eocene Thermal Maximum (55.8 Ma), when global temperatures rose 5–8 °C in 20,000 years ( McInerney and Wing 2011 ), until the Early Eocene Climatic Optimum (EECO, 51–53 Ma) when they reached a long-term maximum ( Zachos et al. 2001 , 2008 ). Then a 17-Ma cooling trend occurred until the beginning of the Oligocene (33.9 Ma), which may have facilitated diversification of Acropora. Fig. 3. Divergence time estimates for acroporid corals using 2,126 single-copy orthologous genes (621,659 amino acid length) and evolution of gene family size changes in scleractinians. Numbers of significantly ( P < 0.01) expanded or contracted orthologous groups with more or less than three genes are shown at each node. Expected sea level changes based on Olde et al. (2015) are shown with a blue dotted line, and tropical sea surface temperature of the Eocene ( Cramwinckel et al. 2018 ) is shown with a red line. The Paleocene–Eocene Thermal Maximum is indicated with an arrowhead, and the EECO is highlighted in light gray. An approximate geological time scale is shown at the bottom. Abbreviations of geologic periods are as follows; J, Jurassic Period; C, Cretaceous Period; P, Paleocene; E, Eocene; O, Oligocene; M, Miocene. Gene Expansions Unique to Acropora Include Possible Coral Stress Response Genes We detected 48 and 90 OGs that are restricted to the Acroporidae and Acropora , but not observed in the two other scleractinians, two corallimorpharians, or two anemones, respectively ( supplementary tables S4 and S5 , Supplementary Material online). Of the 90 OGs observed exclusively in Acropora , four genes are involved in coral calcification (galaxins, aspartic and glutamic acid-rich proteins, uncharacterized skeletal organic matrix protein 6) ( Ramos-Silva et al. 2013 ; Takeuchi et al. 2016 ), implying independent evolutionary mechanisms of calcification in Acropora , in addition to shared mechanisms in scleractinians and possible involvement of these genes in the great diversity of morphologies and high levels of calcification rates in Acropora . Gene duplication is a major driving force of genome evolution and facilitates acquisition of novel gene functions ( Ohno 1970 ). In contrast to the lack of expanded or contracted genes in the common ancestor of scleractinians ( fig. 3 ), 28 OGs were predicted to have expanded in the common ancestor of Acropora , which is the largest number of expanded OGs in the entire scleractinian lineage ( fig. 3 , supplementary table S9 , Supplementary Material online). These genes may contribute to adaptations to past warm environments, wide distributions, and ecological success of Acropora corals. These include genes possibly restricted to corals or cnidarians, small cysteine-rich peptides (SCRiPs) (OG0000795, only observed in Acropora and Montipora ) ( Sunagawa et al. 2009 ) and a novel coral caspase type, Caspase-X (OG0000692, supplementary table S3 , Supplementary Material online) ( Moya et al. 2016 ). Phylogenetic analyses of SCRiPs and Caspase-X genes demonstrated that expansions originated by tandem duplication in Acropora genomes ( supplementary fig. S4 , Supplementary Material online). Gene expression analysis showed that most of these genes were more highly expressed in adults than in embryos ( supplementary fig. S4 , Supplementary Material online), suggesting that they function in adult corals. Phylogenetic analysis showed that the tandemly duplicated SCRiPs did not cluster together with reported SCRiPs in UniProt, suggesting that these belong to a novel class ( supplementary fig. S4 A , Supplementary Material online). Some SCRiP genes were downregulated and are highly responsive to thermal stress ( Sunagawa et al. 2009 ) and are thought to be potent neurotoxins ( Jouiaei et al. 2015 ). It has been proposed that suppression of a caspase-mediated apoptotic cascade in host corals, induced by endogenous production of reactive oxygen species from symbiotic algae, is important in thermal stress responses ( Kvitt et al. 2011 ; Tchernov et al. 2011 ). Caspase-X genes possess both inactive and active caspase domains, probably interacting and controlling caspase activity ( Moya et al. 2016 ), as in cooperative and hierarchical binding of c-FLIP and caspase-8, in promoting or inhibiting apoptotic cell death ( Hughes et al. 2016 ), and may function in thermal stress responses of Acropora . Although detailed functions of Acropora -specific expanded SCRiPs and Caspase-X genes under thermal stress remain to be revealed, these genes may enable Acropora corals to cope with thermal stress and to disperse widely and thrive globally. Dimethlysulfonioproprionate Lyases, Which Promote Cloud Formation and Which May Have Been Acquired by Horizontal Gene Transfer from Algal Symbionts, Are the Most Duplicated Genes in the Acropora Ancestor Among the 28 expanded OGs in the Acropora ancestor, the most diversified (OG0000129) is similar to dimethlysulfonioproprionate (DMSP) lyase of a coccolithophore, Emiliania huxleyi ( Alcolombri et al. 2015 ) ( figs. 3 and 4 , supplementary tables S9 and S10 , Supplementary Material online). This enzyme mediates cleavage of DMSP into dimethyl sulfide (DMS) and acrylate. DMS is the principal form of sulfur that is released from oceans into the atmosphere; thus, it is a key component of the ocean sulfur cycle ( Quinn and Bates 2011 ). DMS may be crucial for cloud formation, and may serve to reduce light levels and water temperatures in marine environments ( Vallina and Simo 2007 ). Thus, DMSP lyases in marine organisms participate in atmosphere-ocean feedback and may influence local climate regulation. Interestingly, concentrations of DMSP and DMS in corals are the highest reported among marine organisms, suggesting that corals are important sources of these two sulfur compounds ( Broadbent et al. 2002 ; Broadbent and Jones 2004 ).\n Fig. 4. Expansions of DMSP lyase specific to the genus Acropora . ( A ) Examples of tandem duplication of DMSP lyase in Acropora genomes. Genomic sequences of Acropora species from four clades in which neighboring genes of DMSP lyases (both 5′ and 3′) were correctly assembled are shown. DMSP lyase genes are shown with blue arrows and other genes are shown as white boxes. Genes belonging to the same orthologous groups are connected by dot lines. Relative gene expression levels of A. digitifera tandemly located genes in embryonic and adult stages are shown in Z -scores. ( B ) Maximum likelihood analysis of DMSP lyase using homologous eukaryote genes identified with ORTHOSCOPE ( Inoue and Satoh 2019) . Asterisks indicate query sequences in ORTHOSCOPE analysis (BlastP, 1e −4 ), including Montiopra , Astreopora , Discosoma , and Emilania DMSP lyase genes. Species are colored as shown at the top right. Bootstrap support for representative nodes is shown. The eukaryote DMSP lyase clade is highlighted in gray and the cnidarian clade is in purple. Scleractinian DMSP lyase sequences identified from Goniastrea , Galaxea , and Porites were also included in the analysis. ( C ) Proposed evolutionary history of DMSP lyase in the Anthozoa. Two gene expansion events are shown in red in the phylogenetic tree, and numbers represent the number of genes expanded at each node. Phylogenetic relationships of scleractinian corals are derived from Kitahara et al. (2016) . Our analysis shows that DMSP lyase gene expansions occurred first in the common ancestor of Acropora and again after divergence of the basal clade ( supplementary tables S9 and S10 , Supplementary Material online). Synteny analysis revealed that the second expansion occurred by tandem duplication ( fig. 4 A ). Relative expression levels of tandemly located genes in A. digitifera showed higher expression levels in gastrula and/or adult stages ( fig. 4 A ), corresponding to higher expression of a DMSP biosynthesis gene in larval stages of an Acropora coral ( Raina et al. 2013 ). Extant scleractinians comprise two major clades, “complex” and “robust,” based on molecular analyses ( Romano and Palumbi 1996 ; Kitahara et al. 2010 ). Although DMSP lyase could not be detected in genomes of “robust” corals, except for Goniastrea aspera , we did detect it in genomes of “complex” corals, including Astreopora and Montipora , and the two corallimorpharians ( Amplexidiscus and Discosoma ) ( fig. 4 B and C ). We detected a single DMSP lyase locus in each scleractinian genome except for acroporids. Interestingly, ORTHOSCOPE analysis, for detecting orthologs, showed that among metazoans, DMSP lyases occur only in the Scleractinia and Corallimorpharia ( fig. 4 B ). Molecular phylogeny showed that DMSP lyases from Emiliania , Symbiodiniaceae, Scleractinia, and Corallimorpharia cluster together ( fig. 4 B ). Moreover, genes similar to Acropora DMSP lyase are only found in Acropora , Emiliania , and the Symbiodiniaceae, among eukaryotes in the NCBI NR database to date (BlastP, 1e −5 ). These results suggest that anthozoan DMSP lyases may have been acquired by the common ancestor of scleractinians and corallimorpharians via horizontal gene transfer from symbiotic Symbiodiniaceae or Emiliania ( fig. 4 C ) and were later possibly lost in variety species of the “robust” clade ( fig. 4 C ). Then, expansions occurred in the common ancestor of Acropora . It has been suggested that DMSP participates in a wide range of coral stress responses, including those to heat, sunlight, air exposure, and hyposalinity ( Sunda et al. 2002 ; Raina et al. 2010 ; Deschaseaux et al. 2014 ; Aguilar et al. 2017 ). Higher DMSP concentrations were observed in Acropora than in other corals ( Broadbent et al. 2002 ). These species-specific phenomena may be supported by Acropora -specific gene expansions. Although the functions of expanded DMSP lyases in Acropora remain to be determined, Acropora -specific expansions suggest that warmer and shallower environments from the Cretaceous to the EECO may have enhanced gene duplication in the Acropora ancestor. Diversified functions of Acropora DMSP lyase may enable adaptation to stresses, such as intense heat, light, and salinity, probably by forming clouds to minimize ocean heating due to insolation. Possible Antimicrobial Peptides and Symbiosis Genes Are under Positive Selection in Acropora In order to explore the genetic bases of Acropora diversification, we compared gene repertoires of Acropora corals. We identified 17 OGs for which amino acid sequences are identical among Acropora species ( supplementary table S11 , Supplementary Material online), indicating that these serve fundamental functions in Acropora . Conserved genes included Homeobox, Forkhead, and Ras-related genes. In contrast, fast-evolving genes (Ka/Ks > 1) may be essential for Acropora adaptation to diverse or changing environments. Despite the highly conserved protein sequences of Acropora single-copy genes ( supplementary fig. S5 , Supplementary Material online), manifesting Ka/Ks ratios below 1 ( supplementary fig. S6 , Supplementary Material online), we identified 35 rapidly evolving candidate OGs ( supplementary table S12 , Supplementary Material online). Among 14 OGs in which Ka/Ks ratios >1 were detected in more than three species combinations, seven OGs were exclusive to scleractinians ( supplementary table S3 , Supplementary Material online) or Acropora ( supplementary table S5 , Supplementary Material online). Interestingly, two candidate genes possibly involved in coral-alga symbiosis, prosaposin (OG0014095, Acropora restricted) and NHL domain-containing gene (OG0010986, scleractinian restricted), were included ( supplementary table S12 , Supplementary Material online). These genes were exclusively upregulated when planula larvae of Acropora tenuis were infected with native algal symbionts (Y. Yoshioka et al., under review) and Ka/Ks ratios >1 were detected from all species combinations between Clade I and Clade II in prosaposin ( supplementary table S12 , Supplementary Material online), suggesting possible diverse symbiotic mechanisms within the Acropora clade. Seven fast-evolving OGs with no similarity to proteins in the Swissprot/Pfam databases and shorter than 200 AA were predicted to be antimicrobial peptides (probability >0.95, iAMPpred), facilitating Acropora responses to diverse pathogens."
} | 8,820 |
35755868 | PMC9214320 | pmc | 1,321 | {
"abstract": "Summary The spiking neural network (SNN) mimics the information-processing operation in the human brain. Directly applying backpropagation to the training of the SNN still has a performance gap compared with traditional deep neural networks. To address the problem, we propose a biologically plausible spatial adjustment that rethinks the relationship between membrane potential and spikes and realizes a reasonable adjustment of gradients to different time steps. It precisely controls the backpropagation of the error along the spatial dimension. Secondly, we propose a biologically plausible temporal adjustment to make the error propagate across the spikes in the temporal dimension, which overcomes the problem of the temporal dependency within a single spike period of traditional spiking neurons. We have verified our algorithm on several datasets, and the experimental results have shown that our algorithm greatly reduces network latency and energy consumption while also improving network performance.",
"conclusion": "Conclusion In this paper, first, we analyze the existing problems in the SNNs trained with BP. We find that the current setting will cause the earlier spiking neurons repeat participating in the gradient calculation of the network, making a more significant influence on the network weight. The BPTT algorithm on the SNNs only propagates errors backward in a single-spike period. The temporal dependence between spikes will be truncated. By introducing the biologically plausible spatial adjustment, it will consider the spikes generated by the membrane potential of different strengths, which will have different effects on the parameter update during the backpropagation process. In addition, the biologically plausible temporal adjustment is introduced, and it considers the backpropagation across the spikes. We have achieved remarkable performance on MNIST, CIFAR10, CIFAR100, and Google Speech Commands datasets and achieved the current best performance on N-MNIST, DVS-Gesture, and DVS-CIFAR10 datasets. By analyzing the energy consumption and latency of the SNNs, we find that the BPSAs and BPTAs significantly reduces energy consumption and latency while improving performance.",
"introduction": "Introduction Deep neural networks (DNNs) have achieved success in various research areas, such as object detection, 1 visual tracking, 2 face recognition, 3 etc. However, they are still far away from the information-processing mechanisms of the human brain. Spiking neural networks (SNNs) are known as the third-generation artificial neural network. 4 They have been widely used in many fields, such as semantic segmentation, 5 visual explanations, 6 privacy protection, 7 , 8 and object detection. 9 The discrete spikes used to transmit information are more energy efficient and are more in line with the information-processing mechanism in the brain. Combined with neuromorphic computing, 10 it promises to realize real intelligence. However, due to the complex neural dynamics and non-differential characteristics of SNNs, it is still a challenge to train SNNs efficiently. Existing SNN training methods can be roughly divided into three categories: the biologically plausible method, the conversion method, and the backpropagation-based method. The biologically plausible method, such as Hebbian learning rules 11 and spike-timing-dependent plasticity (STDP), 12 is mainly inspired by the synaptic learning rules in the human brain. The Hebbian theory believes that the connection between pre- and post-synaptic neurons will increase due to continuous and repetitive stimulation of pre-synaptic neurons. STDP is an extended Hebbian learning rule based on the temporal difference between pre- and post-synaptic neurons. Diehl et al. 13 used the STDP learning rule and lateral inhibition in a two-layer SNN and achieved 95% accuracy on the MNIST dataset. Saeed et al. 14 introduced a weight-sharing strategy and designed a spiking convolutional neural network. The weight was learned by the STDP layer-wisely. Kherapisheh et al. 15 used the hand-crafted difference of Guassian (DoG) features as the input of the SNNs and trained the subsequently convolutional layer through STDP. These methods rely on the local activities of neighboring neurons to update network weights and lack the supervision of global signals. Although Zhao et al. designed a multi-layer SNN based on global feedback connections and local optimization learning rules (GLSNN), 16 it still performs poorly when transplanted to some deep networks for some complex tasks. The conversion method is an alternative way to get high-performance SNNs. It first trains the well-performed DNNs, then converts the DNNs into SNNs with some additional adjustments. 17 , 18 , 19 , 20 , 21 The analog values of DNNs are converted into the firing rates of SNNs. Although the conversion method makes the SNNs achieve performance close to the traditional DNNs, the simulation time is too long, which causes the network to have poor real-time performance and high energy consumption. Also, the conversion methods rely highly on the well-trained DNNs and do not take advantage of the temporal information of SNNs. The success of deep learning depends heavily on the proposal of the backpropagation algorithm. Several studies provide evidence for backpropagation in the brain. The feedback connections may make predictions of activities of low-level brain areas, 22 , 23 , 24 , 25 and the biological neurons will backpropagate the action potentials to provide crucial signals for synaptic plasticity. 26 , 27 , 28 , 29 Lillicrap et al. 30 argued that the differences with the feedforward and feedback neural activities may locally approximate the error signals in backpropagation. Researchers in SNN domains also introduced the backpropagation algorithm into the optimization of SNNs with the surrogate-gradient method. 31 , 32 , 33 , 34 Surrogate gradient helps SNNs perform backpropagation through time (BPTT) so that SNNs can be adopted to larger-scale network structures, such as VGG, ResNet, etc., and perform better on more complex datasets. However, directly applying the surrogate gradient into the training of SNNs may lead to some problems. First, the surrogate gradient obtains the gradient by smoothing the spike firing function. Neurons with membrane potential around the threshold will participate in the backpropagation. As a result, the neurons that do not emit spikes may participate in weight updating, significantly increasing the network’s energy consumption. Second, the spiking neuron will reset to the resting potential after the spike is emitted. The reset operation will cut off the error along the temporal dimension during the backpropagation so that errors cannot propagate across spikes, which significantly weakens the temporal dependence of the SNNs. To address the problems mentioned above, we introduced a biologically plausible spatiotemporal adjustment to improve the backpropagation training of SNNs, which can be summarized as follows: • We study the influence of the surrogate gradient on the spatial dimension of the SNNs, rethink the relationship between the neuron membrane potential and the spikes, and propose a more biologically plausible spatial adjustment (BPSA) to help regulate spike activities. • We study the limitations of the surrogate gradient in the temporal dimension and introduce a more biologically plausible temporal adjustment (BPTA), which enables the SNNs to propagate errors across the spikes, enhancing the temporal dependence of the SNNs. • We conduct experiments on several commonly used datasets. For the static datasets MNIST, CIFAR10, and CIFAR100, we get remarkable performance compared with other state-of-the-art SNNs. To the best of our knowledge, we have reached state-of-the-art performance for the neuromorphic datasets N-MNIST, DVS-CIFAR10, and DVS-Gesture. For the Google Speech Commands dataset, we have reached comparable performance with other artificial neural networks designed for speech recognition. Moreover, our method dramatically reduces energy consumption and latency through analysis compared with other state-of-the-art SNNs.",
"discussion": "Discussion In this section, firstly, we conduct the ablation study to the BPSA and BPTA mentioned above and analyze the contribution of each module. Secondly, we explore the energy consumption of the SNNs for these adjustments. Thirdly, we discuss the latency of the SNNs affected by these adjustments. Finally, we give the limitations of our algorithm and future work. Through the analysis, it is fully illustrated that the above two adjustments can make the behavior of the spiking neurons more stable and establish a better performance while reducing network latency and energy consumption. Ablation study We conduct the ablation study on the neuromorphic datasets DVS-Gesture and DVS-CIFAR10 due to the more complex spatial structure and stronger temporal information, which will fully illustrate our adjustments’ importance. We use Lillicrap et al. 31 as our baseline and then continue to add the BPSA and BPTA. As can be seen in Table 4 , with the introduction of the two adjustments, the performance of the network is gradually improved, among which the spatial adjustment brings more significant improvement. Table 4 The ablation study of the two adjustments on DVS-Gesture and DVS-CIFAR10 datasets Baseline BPSA BPSA + BPTA DVS-Gesture 93.92 97.56 98.96 DVS-CIFAR10 71.40 75.30 78.95 We also give the test curves of the DVS-Gesture dataset. As shown in Figure 1 , with the number of epochs increasing, the accuracy of the model with biologically plausible spatiotemporal adjustment fluctuates less. Because with the introduction of the two adjustments, the firing pattern of neurons is more stable, making the model more robust to more minor parameter changes. Meanwhile, a reasonable gradient allocation strategy in the BP improves the model’s generalization performance and avoids overfitting to a certain extent. Figure 1 The test accuracy curve on DVS-Gesture of our method and the baseline Energy-efficiency study To illustrate the energy efficiency of our algorithm, we visualize the firing frequency of different layers in the MNIST experiment. As can be seen from the Figure 2 , due to the biologically plausible spatiotemporal adjustment, our method exhibits an extremely low firing rate, especially in the initial convolutional layers. Figure 2 The firing frequency of different convolutional layers on MNIST of our method and the baseline We compare the accuracy and energy efficiency of the SNNs trained by the method used in Wu et al., 31 the model we propose, and the artificial neural networks (ANNs) using the same network structure and network parameters. Most operations in ANNs are multiply accumulate (MAC), while in SNNs, the spikes transmitted in the network are sparse, and the spikes are integrated into the membrane potential. As a result, most operations in SNNs are accumulate (AC) operations. We calculate the energy consumption of the SNN by multiplying floating-point operations (FLOPS) and the energy consumption of MAC and AC operations. We use the same energy-efficiency calculations as in Chakraborty et al., 62 and the computation details can be seen in Equation 1 . E A N N = F L O P S A N N × E F L _ M A C (Equation 1) E S N N = F L O P S S N N × E I N T _ A C × T As can be seen in Table 5 , our method has a lower firing rate and higher energy efficiency. The training method of the SNNs proposed in this paper distributes the gradient more reasonably along the spatial and temporal dimensions, avoiding the problem that the earlier spiking neurons would have a more significant influence on the network parameters. The cross-spikes propagation will also enhance the temporal dependence of the SNNs. Therefore, the method proposed in this paper achieves lower network power consumption while maintaining a higher accuracy. Table 5 The energy-efficiency study of our model with baseline on different datasets Dataset Accuracy (%) Firing rate EE = E A N N E S N N (×) MNIST 99.58/99.42 0.082/0.183 35.1/15.7 N-MNIST 99.61/99.32 0.097/0.176 29.6/16.3 CIFAR10 92.33/89.49 0.108/0.214 26.6/13.4 DVS-Gesture 98.26/93.92 0.083/0.165 34.6/17.4 DVS-CIFAR10 77.76/71.40 0.097/0.177 29.5/16.2 Represented as baseline/our method. Latency study The latency of the SNNs is one of the main problems that restricts the development of SNNs. The spiking neurons need to accumulate membrane potential, and once they reach the threshold, they fire spikes and transmit information. Therefore, SNNs often require a long simulation time to achieve higher performance. Here, we study the influence of different simulation lengths on the network performance. As shown in the Figure 3 , when our adjustments are not introduced, when the simulation time is reduced, the test curve of the network is not very smooth, that is, the network needs a long simulation time to converge. As can be seen in Table 6 , with the introduction of the two adjustments, our training method still achieves high accuracy while reducing the simulation time. The low latency of our approach further lays the foundation for the practical application of SNNs. Figure 3 The test accuracy of different simulation lengths on DVS-Gesture dataset with our method and the baseline Table 6 The test accuracy on DVS-Gesture dataset of different simulation lengths of our method and the baseline T = 32 T = 16 T = 8 T = 4 BPSA + BPTA 98.27 98.26 96.18 92.01 BPSA 96.53 97.56 94.44 89.58 Baseline 95.49 93.92 84.03 73.96 Limitations of the study In this paper, through the analysis of the training of the BP-based SNN, we find that neurons that do not generate spikes will still participate in the update of network weights. Also, the error signals along the temporal dimension cannot propagate across the spikes due to the reset operation. By introducing the BPSA and BPTA mechanisms, our network is more consistent with the brain in terms of weight update, and the energy consumption and latency of the SNN are greatly reduced. However, there is no independent module in the brain specially designed for the BP pathway. In future work, we will explore more biologically plausible learning methods to train SNNs with high performance and robustness."
} | 3,585 |
23235806 | null | s2 | 1,323 | {
"abstract": "This work demonstrates a facile fabrication method to produce superhydrophobic coatings on chemically distinct materials using the electrospraying process. Coatings are mechanically robust, three-dimensional, and formed using a single fabrication step."
} | 63 |
36895759 | PMC9988671 | pmc | 1,325 | {
"abstract": "Developing versatile and robust surfaces that mimic the skins of living beings to regulate air/liquid/solid matter is critical for many bioinspired applications. Despite notable achievements, such as in the case of developing robust superhydrophobic surfaces, it remains elusive to realize simultaneously topology-specific superwettability and multipronged durability owing to their inherent tradeoff and the lack of a scalable fabrication method. Here, we present a largely unexplored strategy of preparing an all-perfluoropolymer (Teflon), nonlinear stability-assisted monolithic surface for efficient regulating matters. The key to achieving topology-specific superwettability and multilevel durability is the geometric-material mechanics design coupling superwettability stability and mechanical strength. The versatility of the surface is evidenced by its manufacturing feasibility, multiple-use modes (coating, membrane, and adhesive tape), long-term air trapping in 9-m-deep water, low-fouling droplet transportation, and self-cleaning of nanodirt. We also demonstrate its multilevel durability, including strong substrate adhesion, mechanical robustness, and chemical stability, all of which are needed for real-world applications.",
"introduction": "Introduction In nature, biological superhydrophobic skins often possess unique 3D microscale topologies that enable different specific interfacial functions for controlling surface matters. 1 A few examples include the nanopillar arrays on Cicada wings that promote transparency, self-cleaning, and mechanically rupturing cells 2 ; the double reentrants on a springtail skin minimizing organic liquid wetting 3 ; and the micro-papillae on a rose petal stabilizing water droplets at Wenzel wetting state. 4 For more examples, see Table S1 . The exploration of these biological surfaces has inspired diverse topological functionalities, e.g., liquid detachment/adhesion, 5 , 6 , 7 , 8 , 9 gas entrapment, 10 , 11 , 12 anti-icing, 13 , 14 , 15 chemical shielding, 16 drag reduction, 17 , 18 oil/water separation, 19 , 20 heat transfer improvement, 21 and anti-bacteria activity. 22 , 23 While notable progress has been achieved in developing some biomimetic surfaces, such as in the case of superhydrophobic surfaces, there remains a major challenge to simultaneously control precise specific topology and realize the robustness of those biomimetic surfaces. In general, biomimetic surface functions require two essential components, 19 , 21 , 24 , 25 , 26 , 27 , 28 the specific 3D surface topologies and the surface chemistry of materials. However, both components are highly susceptible to material failure caused by stress concentration, short penetration distance for invasive matters, and the easy change of surface nature from hydrophobic to hydrophilic. Also, the need to construct the specific 3D architecture 29 , 30 , 31 , 32 , 33 , 34 recalls sophisticated manufacturing and limits material and structural options for enhancing robustness. Recent years saw extensive efforts in translating bioinspired surfaces into real-world applications. For example, the surface robustness can be enhanced by introducing high-modulus materials 24 , 25 , 28 , 35 , 36 and perfluorinated chemistry 26 , 27 , 37 as manifested by those synthetic surface coatings. Yet, such coatings are commonly composed of disordered particles without microtopological controllability. Alternatively, “armor” structures (e.g., interconnected frames 29 , 38 and pillars 30 , 39 ) can be micromachined to protect weak nanostructures. But this strategy is specific to structural geometry and rigidity. To date, it remains an unresolved problem to develop versatile and scalable surfaces that simultaneously enable topology-specific functionality and ultradurability. 40 Here, we present a nonlinear stability-assisted, monolithic perfluoropolymer surface (MPS) strategy to address the above challenge. In particular, MPS uses soft perfluoropolymers (sometimes referred to as Teflon, a commercial brand name) to make the entire coating, with all surface structures being part of this inert continuum. Using theoretical modeling and experimental validation, we found the MPS strategy combines geometric-material mechanics with superwetting stability well and suggests (1) an optimal structural design and preferential materials to simultaneously realize wetting and mechanical stability, and (2) the extension of the stability of the biomimetic surfaces into a nonlinear range. This principle is contrary to conventional wisdom—using highly rigid structures to bear the concentrated stress yet failing once slight inelastic deformation occurs. MPS was prepared in multiple-use models (coating, tape, and self-supporting film) through a modified high-temperature imprinting approach that is low-cost and scalable. We also demonstrated the versatility of MPS for efficiently regulating surface matter, as well as multilevel durability.",
"discussion": "Discussion The advantages of MPS over superhydrophobic surfaces produced by conventional strategies (see Table S2 for the details) are summarized using some qualitative evaluation indices in a radar map ( Figure 5 ). The details of the rubrics are presented in Table S3 . The MPS achieved performances comparable to best records in multiple aspects, eg, peeling, abrasion, crushing, and chemical/aging resistance. Also, MPS favors eco-friendliness by minimizing the release of microplastics and nanomaterials, which is impossible for those nanoparticle-based coatings. Moreover, the fabrication cost of the MPS strategy (estimated at within 10 $/m 2 ) is competitive, especially considering its capability to create large-scale arrays of precisely defined true-3D microstructures and outstanding durability. Altogether, the MPS strategy has demonstrated the capability to simultaneously realize topology-specific functionality and multilevel robustness for the control of gas/liquid/solid matters, which may fulfill the challenging requirements for real-world applications in air trapping, liquid transport, and self-cleaning, as well as many other possible applications, such as anti-icing, anti-corrosion, heat transfer, and drag reduction. Figure 5 MPS combines topological controllability and multilevel durability (A) Illustration of two major groups of existing strategies (lower schematics), i.e., synthetic coatings and micromachined/3D printed surface, as well as MPS strategy (upper schematic) for preparing biomimetic surfaces. (B) A radar map showing the qualitative indexes of the characters of biomimetic coatings produced using different strategies (see references and rubrics in Tables S2 and S3 ). The potential applications, e.g., anti-icing and drag reduction, require multipronged merits of biomimetic coatings (light green area). MPS biomimetic surfaces (light blue line) can fulfill the multipronged requirements, addressing the limitations of synthetic coatings (gray line) and micromachined/3D printed coatings (dark yellow line)."
} | 1,754 |
35223068 | PMC8864349 | pmc | 1,327 | {
"abstract": "Complex patterns of collective behaviour may emerge through self-organization, from local interactions among individuals in a group. To understand what behavioural rules underlie these patterns, computational models are often necessary. These rules have not yet been systematically studied for bird flocks under predation. Here, we study airborne flocks of homing pigeons attacked by a robotic falcon, combining empirical data with a species-specific computational model of collective escape. By analysing GPS trajectories of flocking individuals, we identify two new patterns of collective escape: early splits and collective turns, occurring even at large distances from the predator. To examine their formation, we extend an agent-based model of pigeons with a ‘discrete’ escape manoeuvre by a single initiator, namely a sudden turn interrupting the continuous coordinated motion of the group. Both splits and collective turns emerge from this rule. Their relative frequency depends on the angular velocity and position of the initiator in the flock: sharp turns by individuals at the periphery lead to more splits than collective turns. We confirm this association in the empirical data. Our study highlights the importance of discrete and uncoordinated manoeuvres in the collective escape of bird flocks and advocates the systematic study of their patterns across species.",
"introduction": "1 . Introduction Patterns of collective escape of animals are some of the most complex and mesmerizing displays in nature: when a moving group is under attack by a predator, the group changes its shape and internal structure rapidly [ 1 – 4 ]. These patterns often confuse the predator and increase the prey's survival [ 5 – 8 ]. To counteract this, predators may attempt to split up their target groups [ 9 , 10 ]; for instance, an avian predator may attack an airborne flock several times [ 11 , 12 ], while gaining altitude in order to dive and intersect it at high speed (a hunting strategy called ‘stoop’) [ 13 ]. The anti-predator effect of aggregating is important in the evolution of group-living, particularly for species which are regularly preyed upon [ 7 , 14 ]. Because of the complexity of patterns of collective escape, however, the specifics concerning individual behaviour and coordination among group members when under attack are not so well understood. Computational models are valuable for understanding the processes that underlie such complex patterns [ 15 – 17 ]. These underlying processes comprise specific behavioural rules that control the motion of individuals. To identify these rules, collective behaviour is often studied in models that are based on self-organization [ 18 – 20 ]. In these models, collective patterns emerge from local interactions of individuals, specifically from coordination among group members by attraction to, alignment with and repulsion from, their closest neighbours [ 21 – 25 ]. These rules of coordination have been similarly modelled across different taxonomic groups, for instance insect swarms, fish schools and bird flocks [ 23 , 26 – 29 ]. However, empirical data show that species may differ in their specifics of coordination [ 30 – 35 ]. In bird flocks, European starlings ( Sturnus vulgaris ) coordinate with their seven closest neighbours (referred to as ‘topological neighbours' [ 30 ]), jackdaws ( Corvus monedula ) with their mating partner and three other topological neighbours [ 33 , 36 ] and chimney swifts ( Chaetura pelagica ) with all individuals within a specific distance (referred to as ‘metric neighbours’, [ 32 ]). The number of interaction partners may even depend on the ecological context, as found in jackdaws during roosting and mobbing flights [ 32 , 37 ]. Moreover, the collective pattern may also be affected by the specifics of locomotion, for instance flight versus swimming or species-specific differences in flight modes [ 25 , 38 ]. Because of this variation, the rules of motion and coordination at the individual level of computational models can be adjusted to empirical data in order to study what patterns of collective motion emerge [ 24 , 39 – 43 ]. Species-specific models have, however, rarely been applied to bird flocks under predation [ 44 ]. Whether patterns of collective escape differ among species is not yet known; given the unpredictability and rarity of predator attacks, as well as the difficulty of simultaneously tracking both predator and prey, studying collective escape in the field is challenging. Complete trajectories of airborne birds in flocks under predation have only recently been collected with a newly developed, remotely controlled robotic-falcon (referred to as ‘RobotFalcon’ [ 45 ]) attacking flocks of homing pigeons ( Columba livia ) [ 46 ]. In the present study, we combine these quantitative data [ 46 ] with a species-specific computational model (HoPE—Homing Pigeons Escape, [ 47 ]) to investigate what behavioural rules underlie the patterns of collective escape in pigeons. Patterns of collective escape in bird flocks have been extensively described only for large flocks of European starlings [ 2 ] (see also [ 48 – 50 ]). Their patterns include, among others: the agitation wave (dark bands moving over the flock away from the predator), flash expansion (where prey flees radially away from the predator), vacuole (where prey surrounds the predator) and splitting of sub-flocks [ 2 , 51 ]. Here, we identify two new patterns of collective escape in pigeons: namely collective turns (during which the whole flock changes its heading) and early splitting of sub-flocks (splits that occur also at large distance from the predator, see also [ 46 ]). Surprisingly, collective turns have so far been neglected in prior studies of collective escape in bird flocks [ 2 ]. To understand how these patterns arise, we need a new computational model since neither early splits nor collective turns have been reported in previous models of collective escape. In most models, individuals have only a single rule of escape, usually a continuous tendency to turn away from the predator while coordinating with their neighbours [ 26 , 47 , 52 ]. Remarkably, this single rule has led to many patterns in a model of fish schools [ 26 ] ( figure 1 ), for instance the vacuole, the hourglass [ 9 ] and the split (in close vicinity to the predator). Some collective patterns were, however, not generated, for instance the agitation wave [ 53 – 55 ].\n Figure 1 . Patterns of collective escape generated by the computational model of fish schools by Inada et al . [ 26 ], adjusted to small flocks of 10 individuals. The black bird figures represent the prey and the larger red figure the predator. Agitation waves emerged in a computational model of starlings only through a fixed escape manoeuvre, which was copied by close-by neighbours and thus propagated through the group [ 44 ]. The manoeuvre was a zigzag-like turn, which involved banking while turning, resulting in a larger area of each individual's wings being exposed to the observer. This creates the visual effect of dark bands travelling over the flock [ 44 , 51 ]. The zigzag motion is an example of a ‘discrete’ escape manoeuvre, discrete meaning that a sharp change in heading or speed interrupts the continuous, coordinated motion of the group members [ 44 , 54 , 55 ]. Such manoeuvres are found in escaping dunlins ( Calidris alpina ) and are known to underlie escape waves in other species (e.g. U-turns in fish) [ 49 , 56 – 58 ]. Empirical data further suggest that the manoeuvres may not be fixed but varying and unpredictable in terms of turning angle and speed (referred to as ‘protean’ movement) to increase the complexity of the escape path of a prey [ 58 – 60 ]. To generate the early splits and collective turns (at large distance from the predator) that we see in pigeon flocks, we extend an agent-based model of pigeons' collective escape [ 31 , 47 , 61 ] with a new escape manoeuvre that is discrete, variable and uncoordinated. We give each individual a probability to turn away from the predator without coordinating with its neighbours. In order to adjust the escape rule to pigeons, we analyse their turning when they are under attack by the RobotFalcon. We uniquely sample each escape manoeuvre in our model from distributions of turning angle and duration parametrized to our empirical data. The probability to manoeuvre depends on each individual's distance to the predator and on a unique tendency to escape (according to empirical data of escape initiation [ 62 , 63 ]). We investigate whether both patterns of collective escape may arise from the same rule of escape at the individual level. We show that both splitting and collective turning emerge in our model from a single escape manoeuvre. Based on theories of turning propagation [ 36 , 64 , 65 ] and information transfer [ 36 , 66 ], we expect collective turns to emerge more frequently when initiators: (i) are positioned more centrally in the group (directional information can reach the edges of the group faster), (ii) are turning slower and (iii) turn towards the group's centroid (making it easier for flock-mates to follow). We test these hypotheses in both our model and empirical data .",
"discussion": "4 . Discussion To gain insight in what underlies patterns of collective escape in homing pigeons, we combined GPS data of flocks under attack by the RobotFalcon [ 46 ] with a species-specific model based on self-organization [ 47 ]. We analysed the tracks of flocking pigeons and identified two patterns of collective escape: collective turns and splits (of sub-flocks or singletons), even at large distances from the predator. So far, collective turns of the whole flock have been overlooked as a pattern of collective escape in previous studies [ 2 , 26 ]. In our computational model of collective motion (adjusted to pigeon flocks, [ 47 ]) both patterns of collective escape arise when a single group member (the initiator) performs a discrete, uncoordinated and stochastic manoeuvre by turning away from the predator (electronic supplementary material, videos S2 and S3). Whether splitting or collective turning emerges depends mainly on the angular velocity of the initiator and its position relative to the flock's centre, not only in the model but also in the empirical data. Several factors may increase the angular velocity of a bird's turn in nature; first, past and present predatory risk [ 82 ], closer distances to the predator [ 46 , 58 , 83 ] and increased level of alertness of the group [ 55 , 82 ]. Secondly, the predator's behaviour [ 74 , 84 – 86 ]. A faster predator may cause prey to turn more sharply [ 13 , 86 ]. This, however, may be unnecessary if a wider turn is less ‘ costly’ (energetically cheaper or easier) to perform and has been proven successful in the past [ 82 ]. Prey may also react differently to the direction of a predator's attack (whether it approaches the flock from the side or from behind) [ 84 , 85 , 87 ]. Thirdly, the intensity of an escape (as indicated by the speed, frequency or amplitude of motion) may be prone to social enhancement by surrounding flocks [ 10 ] or dependent on the dominance of the turning individual (as shown for crayfish, where dominant individuals are more likely than subordinates to execute reflexive and sharp escape responses [ 88 ]). In our model, we showed that manoeuvres of high angular velocity lead to more splits than collective turns . The occurrence of a split or a collective turn may also depend on how quickly a turn propagates through the group. The speed of this propagation (information transfer concerning the turning direction) may be heavily affected by the specifics of coordination. These specifics differ across species, for instance whether interactions are topological (with fixed number of closest neighbours) or metric (with all individuals within a specific range), and the relative importance of alignment, attraction and repulsion [ 30 – 33 , 36 , 37 , 46 ]. For species in which interactions among flock members are biased (e.g. homing pigeons and jackdaws), how information propagates through the group may also depend on leadership dynamics [ 89 ], mating bonds [ 90 ] and individual differences in experience [ 73 ] and fitness [ 91 ]. The direction from which the turn starts may also play an important role in the speed of information transfer. The position of initiators of collective turns in airborne flocks varies across bird species and ecological contexts. During roosting, mobbing and transit flights [ 36 , 37 , 65 ], starlings that initiate turns are located at the periphery [ 65 ], whereas in jackdaws these initiators are mostly at the front of the flock [ 36 ]. The initiation of collective turns has not yet been studied during collective escape from an avian predator. In our model, group members positioned more centrally in a flock initiate collective turns more frequently than individuals at the edge. This variation may be due to across-species differences in the size and shape of their flocks; individuals in the centre of small and flat flocks [ 92 ] can probably turn more freely than in flocks that are three-dimensional, large and dense [ 93 , 94 ]. There may be several reasons that pigeon flocks turn away from a predator at large distances to it. Pigeons often form small flocks with low density. Therefore, their flocks may not confuse the predator enough to decrease its hunting success (no confusion effect [ 95 ]), and individuals may have higher probability of getting caught than when they are in large flocks (no selfish herd [ 46 ]). According to our model, early collective escape of a flock may be the result of protean movement of its members. Thus, given the variability of the emerging collective turns and splits, the escape path of the group may become less predictable [ 59 , 60 , 76 ], counteracting anticipation-based hunting strategies of the predator [ 58 , 67 , 96 ]. The role of uncoordinated escape by group members during collective motion has not yet been studied. Uncoordinated turning by an initiator, as implemented in our model, causes a collective turn to be larger, given that it is not a compromise between the headings of the initiator and its neighbours [ 52 , 97 ]. This may be more effective for avoiding the predator. Thus, an uncoordinated escape may be adaptive for the whole group and actually reflect a ‘cooperative’ [ 98 ], instead of a ‘selfish’ [ 52 , 99 ], act. Along the same lines, referring to an individual's split from the group as a ‘decision’ to leave should be done with caution [ 46 ] since our findings show that a splitting event is not decided at the individual level, but instead results from the behaviour of the followers. The consequences of a split for the survival of the prey and the success of the predator may depend on the strategy of both. The success of hunting by predators is higher when the flock is smaller and when attacking singletons, rather than flocks [ 11 , 100 ]. From the perspective of the prey, the danger of splitting from the group when performing a sharp, evasive turn may be balanced by the prey's probability of getting rid of the predator by outperforming it [ 96 ]. A predator may, however, catch a sharply manoeuvrable singleton through stooping at high speed, because stooping optimizes the predators aerodynamic forces and roll agility [ 86 ]. Whether the number of initiators of an escape manoeuvre influences the type of collective escape pattern or the prey's survival remains to be studied. In pigeon flocks, we identified fewer patterns of collective escape (splits and collective turns) than have been described for other species [ 2 , 49 ]. This may have several reasons. First, more complex patterns, such as vacuoles and agitation waves may require larger flock sizes [ 2 , 26 ]. Secondly, the large body size of pigeons and their low manoeuvrability [ 86 , 101 , 102 ] may prevent them from executing the sharp turns involved in a flash expansion [ 26 , 103 ]. Thirdly, the slower attack of the artificial predator (RobotFalcon) in comparison to a real falcon [ 2 ] may prevent some patterns that depend on the quick increase in the proximity to the predator to emerge [ 84 , 87 , 97 ]. Fourthly, the strong alignment of heading of homing pigeons [ 31 , 46 ] may support collective turns and counteract patterns with large divergence in the heading of group members, such as the fountain [ 53 ]. The rules of individual escape that were used in previous models did not suffice to produce splits at large distances to the predator and collective turns [ 26 , 52 ]. Most previous models assume that group members share a single escape behaviour: a tendency to turn away from the position or heading of the approaching predator [ 26 , 47 , 52 ]. From this rule, splits emerge mostly when the predator gets close to the group and often passes through it (causing sub-flocks to turn away from the predator in opposite directions), while collective turns do not arise. In models with only a discrete escape reaction, individuals need an additional rule of ‘copying’ any manoeuvre performed by their neighbours in order for an escape wave to emerge [ 44 , 55 , 104 , 105 ]. This additional rule of coordination counteracts splitting. In our model, we combine the continuous tendency to avoid the predator and discrete escape manoeuvres. From only these two rules, collective turns emerge instead of splits, if group members follow an initiator through the basic rules of coordination (alignment and attraction) and their own tendency to turn away from the predator. Guided by empirical data, we give each group member a varying, unique probability to perform an escape manoeuvre. With our new probabilistic approach, collective patterns arise as precautious reactions to the predator, rather than ‘panic-like’ attempts to survive when the predator is near. Future work on empirical data of airborne flocks under attack should focus on individual escape reactions, the number and relative position of initiators of turns and information transfer in relation to flock shape and size [ 55 , 90 , 106 ]. Moreover, quantitative comparisons of patterns of collective escape across species, combined with biologically relevant computational models, can significantly deepen our understanding of what rules underlie these complex patterns."
} | 4,603 |
36064549 | PMC9445036 | pmc | 1,330 | {
"abstract": "The reversibly stable formation and rupture processes of electrical percolative pathways in organic and inorganic insulating materials are essential prerequisites for operating non-volatile resistive memory devices. However, such resistive switching has not yet been reported for dynamically cross-linked polymers capable of intrinsic stretchability and self-healing. This is attributable to the uncontrollable interplay between the conducting filler and the polymer. Herein, we present the development of the self-healing, stretchable, and reconfigurable resistive random-access memory. The device was fabricated via the self-assembly of a silver-gradient nanocomposite bilayer which is capable of easily forming the metal-insulator-metal structure. To realize stable resistive switching in dynamic molecular networks, our device features the following properties: i) self-reconstruction of nanoscale conducting fillers in dynamic hydrogen bonding for self-healing and reconfiguration and ii) stronger interaction among the conducting fillers than with polymers for the formation of robust percolation paths. Based on these unique features, we successfully demonstrated stable data storage of cardiac signals, damage-reliable memory triggering system using a triboelectric energy-harvesting device, and touch sensing via pressure-induced resistive switching.",
"introduction": "Introduction Closed-loop electronic healthcare systems have been explosively spotlighted owing to their interactive functions that enable them to record physiological signals from the human body, analyze these signals using big data processing, and even deliver feedback therapy to abnormal tissues 1 – 3 . More recently, neuromorphic engineering, with respect to the way in which personal data can be stably stored or precisely processed, has been suggested to be of key importance for the realization of such smart bioelectronic systems 4 , 5 . In this regard, a soft resistive switching random-access memory (RRAM) device with low power consumption, high switching speed, and long retention time is a promising candidate that can either store massive amounts of information or acts as a neuromorphic module with embedded artificial intelligence 3 , 6 , 7 . Furthermore, its 2-terminal structure is more efficient for achieving high-density storage cells than floating-gate/charge-trap memory devices. However, the development of soft, biocompatible, high-performance RRAM with a mechanical modulus comparable to that of various living tissues is an essential prerequisite for realizing tissue-like bioelectronic systems. To meet this requirement, many research groups have adopted either strain-dissipative structural designs or intrinsically stretchable materials 8 – 15 . Although these efforts have shown the feasibility of the strain-insensitive stable electrical operation of RRAM, the mechanical reliability of the conventional stretchable materials (ultrathin wavy polyimide or non-healable viscoelastic materials) acting as stretchable substrates would be vulnerable to long-term mechanical stresses originating from repetitive movement of various organs (e.g. skin, heart, tendon, and peripheral nerve). This challenge can be overcome by applying soft stretchable polymeric materials with high toughness and self-healing properties to the electrodes and resistive switching materials of RRAM devices 16 – 18 . Although self-healing materials have various mechanisms to recover autonomously, self-healing polymers based on dynamic hydrogen bonding would be more beneficial for forming the underlying polymeric resistive switching materials of the RRAM than those using capsule-type or metal coordination methods 19 , 20 . This is because these self-healing polymers offer the skin-like modulus, the efficient dissipation of strain energy, low chemical reactivity, and even high biocompatibility 21 , 22 . Specifically, chemical stability at resistive switching interfaces is more important to precisely control the long-term electrical performance of the RRAM 23 , 24 . However, the dynamic behavior induced by the low glass transition temperature (at room temperature) may potentially intervene in reversibly forming conducting filamentary paths in the RRAM. Furthermore, the stable formation and breakdown of the electrical percolation pathways in RRAM should be maintained in various stretching modes. These critical challenges associated with upholding both the intrinsic stretchability and self-healability of RRAM remain to be resolved. Herein, we report the development of the self-healing stretchable resistive random-access memory (SS-RRAM) fabricated by allowing two Ag-gradient nanocomposites (Ag-GN) films to be a bilayer through the self-healing (Fig. 1 and Supplementary Fig. S1 ). These films are composed of a tough self-healing stretchable polymer (SHP; polydimethylsiloxane (PDMS)−4,4’-methylenebis(phenylurea) (MPU) 0.4 -isophorone bisurea units (IU) 0.6 ) and silver micro-/nanoflakes (AgFs) (Fig. 1 and Supplementary Fig. S2 ). The unique structure of the Ag-GN was the spontaneous outcome of the drying process after drop casting the AgF composite solution with low viscosity onto the handling substrate. This asymmetric Ag distribution shows that the average resistance value (~10 Ω) at the bottom is much lower than that at the top. Ag flakes are prone to be concentrated and aggregated in the lower section of the Ag-GN film because of their higher density/interaction than SHP in the solvent and the gravitational effect of the drying process. Compared to the in-plane conducting path in the upper section, the resistance value (~1 TΩ) at the vertical path between the upper and lower sections is also high, indicating that resistive switching occurs in the insulating region of the SS-RRAM. The SS-RRAM shows typical unipolar resistive switching (URS) behavior where the high- and low-resistance states (HRS and LRS) are dominantly governed by Schottky emission/hopping and Ohmic conduction mechanisms, respectively. In addition, the SS-RRAM has a high on/off ratio of ~10 5 (maximum and minimum ratio values of ~10 5 and ~10 9 ), stable electrical durability (cyclic electrical endurance of 500 cycles and data retention of ~50 h), and can be stretched up to 100% strain even after both cutting/reconnecting processes and heat-accelerated recovery (30 min at 60 °C). Based on its healing properties, the SS-RRAM can be used in reconfigurable modular electronics, potentially resulting in the realization of user-customizable electronic products. As a proof of concept, we demonstrated a reconfigurable device where a 1 × 4 array of SS-RRAM can be reconstructed to a 2 × 2 array without electrical malfunction. To highlight the self-healing ability of the SS-RRAM, we demonstrated stable data storage of cardiac signals 25 , damage-reliable memory triggering system using a triboelectric nanogenerator 26 – 29 (TENG), and touch sensing via pressure-induced resistive switching. Fig. 1 Schematic illustration of a Ag-GN film and fabrication of SS-RRAM and photographic/electron microscopy images of SS-RRAM. a Schematic diagrams of a Ag-GN film and its fabrication process by self-healing lamination. Ag-deficient region of the upper Ag-GN film laminated to the Ag-rich region of the bottom film, resulting in a metal–insulator–metal structure. b Schematic illustration of the self-healing process of the SS-RRAM. c Schematic illustration of a SS-RRAM presenting intrinsic stretchability. d Photographic image of a 3 × 3 SS-RRAM array (left) and SEM image showing a cross-sectional view of the MIM structure (inset left). SEM image of the self-bonding interface region (upper middle) and magnified SEM image of Ag-deficient/Ag-rich region (lower middle). TEM images of Ag flakes (upper right) with AgNPs (lower right).",
"discussion": "Discussion We report the first self-healable and stretchable RRAM, fabricated through the formation of the Ag-GN bilayer that has both conducting and insulating interfaces. The SS-RRAM comprised a self-healable/stretchable polymer matrix and conducting Ag-GN films. The region across which the gradient existed was employed as a switching layer for the SS-RRAM. The SS-RRAM based on the Ag-GN exhibited typical URS with a resistive window larger than 10 5 . The electrical properties of the SS-RRAM, including the endurance, switching type, and on-off ratio, were largely unaffected by mechanical stretching, moderate thermal energy, or cell-cut/healing processes. The self-healing ability of the interconnecting region revealed that the RRAM array was instantly reconfigurable. As a proof of concept, a 1 × 4 array was successfully converted to a 2 × 2 array. All cells were operated similarly, and newly connected bit- and word-lines were confirmed to function well before and after the conversion. Furthermore, the reconfigured SS-RRAM array enabled the stable data storage of electrophysiological signals generated from the human body. This self-healing property of the SS-RRAM is foreseen to become a key feature of future reconfigurable modular electronics or user-customizable electronic products. A real-time demonstration of this unique property of the SS-RRAM was conducted to visualize the operation of the self-triggering resistive switching system. Our findings are expected to provide a stepping-stone for the realization of user-customizable electronics and smart in vivo systems."
} | 2,354 |
39358940 | PMC11707565 | pmc | 1,332 | {
"abstract": "Abstract Water‐repellent superhydrophobic surfaces are ubiquitous in nature. The fundamental understanding of bio/bio‐inspired structures facilitates practical applications surmounting metastable superhydrophobicity. Typically, the hierarchical structure and/or reentrant morphology have been employed hitherto to suppress the Cassie‐Baxter to Wenzel transition (CWT). Herein, a new design concept is reported, an effect of concave structure, which is vital for the stable superhydrophobic surface. The thermodynamic and kinetic stabilities of the concave pillars are evaluated by continuous exposure to various hydrostatic pressures and sudden impacts of water droplets with various Weber numbers ( We ), comparing them to the standard superhydrophobic normal pillars. Specifically, the concave pillar exhibits reinforced impact resistance preventing CWT below a critical We of ≈27.6, which is ≈1.6 times higher than that of the normal pillar (≈17.0). Subsequently, the stability of underwater air film (plastron) is investigated at various hydrostatic pressures. The results show that convex air caps formed at the concave cavities generate downward Laplace pressure opposing the exerted hydrostatic pressure between the pillars, thus impeding the hydrostatic pressure‐dependent underwater air diffusion. Hence, the effects of trapped air caps contributing to the stable Cassie‐Baxter state can offer a pioneering strategy for the exploration and utilization of superhydrophobic surfaces.",
"conclusion": "3 Conclusion In summary, we unveil the biomimetic concave effect for a stable superhydrophobicity under impact and hydrostatic pressure. The dynamic behavior of falling water droplets on the fabricated concave pillar (CP) surfaces ( D / L = 0.125–0.5) was investigated by comparing them to the same D / L of standard superhydrophobic normal pillar (NP) surfaces. Within the critical v \n t at which the NP surfaces encountered the partial or complete CWT, the CP surfaces appeared the enhanced impact pressure resistance together with bouncing droplets or only a partial CWT. Furthermore, the wetting phase diagram showed that the CP surface was much more stable under the impact pressure, maintaining the Cassie‐Baxter state up to a larger We (≈27.6 at D / L = 0.5) compared to that of the NP surface (≈17.0 at D / L = 0.5). Next, the underwater plastron stability of the NP and CP surfaces with D / L ≈ 0.5 was studied at varying hydrostatic pressures ( p ( h )). As we expected, the CP surface withstood higher hydrostatic pressure reaching a complete CWT at p ( h ) ≈ 2.94 kPa, whereas the NP surface easily released its trapped air film and became Wenzel state even at p ( h ) ≈ 1.96 kPa. The results from fluorescence confocal microscopy supported that the convex air caps are constructed on the concave structures applying higher Δ P \n L than certain p ( h ). Given that the Δ P \n L would favor the air diffusion through the air cap on the concavity, opposing the p ( h ) on the air/water interfaces between pillars. As a result, the CP surface seems to prevent the underwater CWT resulting from the favorable air diffusion on the concavity. Therefore, we identified the competing pressure owing to the concave effect could be attributed to the stable underwater wetting stability and superhydrophobicity. Our demonstrations of the concave effect countering the impact and hydrostatic pressure can offer a design concept for other superhydrophobic surfaces with a stable Cassie‐Baxter state, further advancing in‐depth explorations and state‐of‐the‐art applications.",
"introduction": "1 Introduction The wetting of liquids on solid surfaces illustrates contacting droplets on the surfaces with a specific contact angle and that can be expressed as a balance between surface tensions at interfaces. [ \n \n 1 \n \n ] The rough topology of the surface further suggested the Wenzel model and the Cassie‐Baxter model, [ \n \n 2 \n \n ] which elucidates the correlation between surface topology and wettability. Specifically, the water‐repellent superhydrophobic surface has been accomplished by the combination of a rough surface and low surface energy, hanging vapor/liquid interfaces between their protrusions, [ \n \n 3 \n \n ] which is known as the Cassie‐Baxter state. Utilizing the peculiar properties of water repellency from superhydrophobic surfaces, recently, applications for self‐cleaning, [ \n \n 4 \n \n ] anti‐icing, [ \n \n 5 \n \n ] droplet manipulation, [ \n \n 6 \n \n ] anti‐fouling, [ \n \n 7 \n \n ] catalysis, [ \n \n 8 \n \n ] and energy harvesting [ \n \n 9 \n \n ] have attracted attention. However, the utilization of superhydrophobic surfaces for practical engineering applications is restricted due to their metastable performances. [ \n \n 10 \n \n ] Thus, unveiling and enhancing the stability and durability of superhydrophobicity under harsh conditions are of great concern. [ \n \n 11 \n \n ] \n In nature, several species live in terrestrial and marine environments, thereby evolving themselves to possess peculiar surface features and structures concerning their diverse ecosystems. [ \n \n 12 \n \n ] Their exclusive surface morphologies have guided an extreme water repellency such as stable air entrapment underwater [ \n \n 13 \n \n ] and bouncing high‐impact pressure of raindrops, [ \n \n 14 \n \n ] preventing the Cassie‐Baxter to the Wenzel transition (CWT). Therefore, they have signposted a biomimetic approach as a blueprint for fabricating artificial superhydrophobic surfaces. [ \n \n 15 \n \n ] Representatively, the multiscale nano‐microhierarchical structure, [ \n \n 16 \n \n ] closed pore structure, [ \n \n 17 \n \n ] and mushroom‐like reentrant structure [ \n \n 17 \n , \n 18 \n \n ] have been employed to implement wetting stability. Those unique structures have offered design concepts for artificial superhydrophobic surfaces and contributed to revealing the fundamental mechanism for a stable Cassie‐Baxter state. Arising from that, factors like energy barrier, [ \n \n 19 \n \n ] capillary pressure, [ \n \n 20 \n \n ] line energy on the nanostructure, [ \n \n 14 \n , \n 21 \n \n ] and air compressibility [ \n \n 17 \n , \n 22 \n \n ] are considered crucial for designing stable superhydrophobic surfaces. Likewise, the research on bio/bioinspired surfaces has addressed both the in‐depth exploration and practical applications for state‐of‐the‐art superhydrophobic surfaces. In this work, we report the effect of trapped air on the stable superhydrophobicity induced by a concave pillar (CP) structure which is found in the pulvilli of some leaf beetle species and the soil‐dwelling springtail (collembola) species. [ \n \n 23 \n \n ] It is important to note that the CP is an open pore structure without reentrancy and hierarchy, solely accounting for the concave effect (air‐trapping on the concave structure) on the wetting stability. To investigate the contribution of solid or line fraction at the air/water interfaces, CP surfaces with fixed pillar diameter ( D ) and various pillar‐to‐pillar lengths ( L ) are fabricated. Initially, the dynamic wettability of CP surfaces during the impact is evaluated by comparing them to conventional superhydrophobic surfaces with cylindrical normal pillar (NP) structures with the same D / L . Unlike the NP surfaces, notably the CP surface with the highest line fraction, D / L = 0.5, shows a significant increase in both the impact and hydrostatic pressure stability. Our findings of transition‐resistant CP structure provide the pioneering design concept as to feasible superhydrophobic surfaces with the stable Cassie‐Baxter state for exploration and state‐of‐the‐art applications.",
"discussion": "2 Result and Discussion 2.1 Fabrication of Superhydrophobic Concave Pillar Microstructures The design of CP surfaces was inspired by a concave morphology in nature such as pulvilli on the feet of leaf beetles ( Figure \n 1 a–c ) and the cuticles from various springtail species. [ \n \n 23b,c \n \n ] In the requirements of self‐cleaning to prevent contamination on their adhesive parts, insects normally possess rough structures with superhydrophobic properties on their feet. [ \n \n 24 \n \n ] Likewise, the pulvilli of the leaf beetles, especially for the male, possess an adhesive pad with a concave structure on their feet; and are considered to facilitate adhesion to the leaves and the roughly structured elytra of the female during the copulation (Figure 1a ). [ \n \n 23c \n \n ] On the other hand, the soil‐dwelling springtail species are believed to have the nano/microstructure on their cuticles for respiration even in their harsh habitat environment. Keeping a stable air film is vital for respiration, thus the complex structures (including reentrancy and concavity) are considered to be critical for maintaining a stable air film on their cuticle in temporary rain flooding and humid soil habitats. [ \n \n 23b \n \n ] Therefore, we mimicked the concavity of such structures to investigate the contribution of the concavity to the wetting stability of superhydrophobic surfaces. Figure 1 Inceptive design for concave pillar microstructure fabrication. a) Digital image of a leaf beetle, Gastrophysa atrocyanea , b) microscopic view of the leaf beetle feet, and c) pulvilli on the feet possessing a discoidal concave structure from the edge utilizing scanning electron microscopy. d) Brief schematics as to the overall fabrication process for the concave pillar. e,f) Representative scanning electron microscopy images of concave pillar structures with D and L of 20 and 40 µm, respectively. g) Static ( θ \n apa ) and dynamic ( θ \n adv and θ \n rec ) water contact angle of the fabricated concave pillar surfaces. The scale bars denote 100 µm for b, e, and f; and 5 µm for c. Figure 1d shows summarized schematics for the CP microstructure fabrication. The following top‐down processes were conducted to fabricate the concave‐shaped pillars on the surface. The photoresist (PR) was spin‐coated on the SiO 2 surface and patterned into hexagonal circle arrays via photolithography. The SiO 2 layer was then vertically etched along the same hexagonal patterns of the PR film. The SiO 2 etching revealed the silicon surface underneath the patterned SiO 2 layer. We then employed potassium hydroxide (KOH) and isopropyl alcohol (IPA) for the wet etching process to acquire an inverted pyramidal shape on the silicon surfaces. Within the KOH etching process, the (111) plane of silicon is etched more slowly than other planes, thus the inverted pyramidal shapes could be obtained (Figure S1 , Supporting Information). Moreover, the addition of IPA improves the smoothness of the etched surface and decreases the etching rate, making a shallow bottom surface. [ \n \n 25 \n \n ] Afterward, a 0.3 µm thickness of chromium (Cr) layer was deposited on the whole surface and the Cr layer on SiO 2 was lifted off simultaneously, etching the SiO 2 layer in buffered oxide etchant (BOE). The revealed silicon surface was vertically etched to get pillar‐shaped microstructures (Table S1 , Supporting Information), [ \n \n 26 \n \n ] and then the wafer was immersed in Cr etchant to remove the Cr layer on concave parts. To get rid of nanograsses among the pillars, the surface was immersed in pure ethanol followed by gentle sonication. Removing the nanograsses rules out the effect from a hierarchical (multi‐scale) structure. [ \n \n 7 \n , \n 16 \n , \n 22 \n \n ] Lastly, fluorosilanization was conducted after air plasma treatment for the superhydrophobic CP microstructures (Figure S2 , Supporting Information). It is also important to note that the fabricated CP is neither a closed pore structure nor a reentrant structure which were previously considered as critical factors in enhancing wetting stability. [ \n \n 17 \n , \n 18 \n \n ] Therefore, by utilizing CP, we can focus solely on the effect of concave structures on wetting stability. Figure 1e,f shows the manufactured CP surfaces identified with scanning electron microscopy (SEM) imaging before fluorosilanization. The fabricated concave pillar structures show a pillar diameter ( D ) of 20 µm, base diameter for concavity ( b ) of 10 µm, 20 µm of pillar height ( H \n p ), and ≈54.5° of etched angle exposing (111) plane of silicon (Figure S1b , Supporting Information). To verify the concave effect regarding line fraction at the air/water interfaces, 6 types of CP surface were fabricated with a fixed diameter of 20 µm and D / L of 0.083, 0.125, 0.17, 0.25, 0.33, and 0.5, respectively (Figure S3 , Supporting Information). Except for the CP surface with D / L = 0.083, all the surfaces exhibited the Cassie‐Baxter state with over 150° of water contact angle (apparent contact angle, θ \n apa ) and contact line shifting when measuring the dynamic contact angle (advancing contact angle, θ \n adv , and receding contact angle, θ \n rec ) (Figure 1g ). We also demonstrated the self‐cleaning property of pillars with concavity using the CP surface of D / L = 0.5 (Figure S4 , Supporting Information). Therefore, we carried out an in‐depth evaluation with 5 different surfaces ( D / L = 0.125, 0.17, 0.25, 0.33, and 0.5). 2.2 Droplet Dynamic Behaviors on the CP Surfaces Several studies have demonstrated that the pressure‐resistant properties of superhydrophobic surfaces resulted from several factors, for instance, capillary force of structure, line energy, and air compression. [ \n \n 14 \n , \n 17 \n , \n 20 \n \n ] As a result, the droplets falling on the superhydrophobic surface exhibit a series of dynamic behaviors: impacting, pancake‐like spreading, retracting, and finally detaching. Here, the dynamic wettability on the CP surfaces was characterized using a high‐speed camera, recording at the frame rate of 2500 fps. For the comparison, we also fabricated the typical superhydrophobic surfaces with cylindrical normal pillars (NP) which possess similar D and L of CP (Note S1 and Figures S5–S7 , Supporting Information). \n Figure \n 2 \n illustrates the dynamic behavior of water droplets on i) NP surfaces and ii) CP surfaces according to each D / L , utilizing the ultrapure deionized (DI) water (18.2 MΩ resistance). Water droplets of ≈2 µL (diameter of ≈1.56 mm, less than the capillary length of 2.7 mm) were dropped at various heights. We then focused on the dynamic behavior at the terminal impact velocity, v \n t , when the NP surfaces allowed the CWT (the determination of v \n t is in the Experimental section). Figure 2 Dynamic behavior of water droplets on the NP and CP surfaces with varying D / L . Plots showing dimensionless contact diameter (contacting length ( l \n c )/initial droplet diameter ( d \n o )) and snapshots of bouncing droplets as a function of time after collision ( t \n c ) on i) NP surface and ii) CP surface with a) D / L = 0.125, b) D / L = 0.17, c) D / L = 0.25, d) D / L = 0.33, and e) D / L = 0.5. The dimensionless contact diameter was traced in terms of contacting length/initial droplet diameter, l \n c / d \n 0 (see inset of Figure 2a ), as a function of time after collision ( t \n c ). Concurrently, the determination of (partial) CWT or stable Cassie‐Baxter state (manifested by the bouncing of droplets without droplet residues) was screened (bouncing on the NP surfaces is depicted in Figure S8 and Movie S1 , Supporting Information). Specifically, the partial CWT was largely determined by two points, a necking of the droplet (cohesion failure) and the smaller contact angle (than the θ \n rec in Figure 1g ; and Figure S7 , Supporting Information) during retraction. [ \n \n 14 \n , \n 27 \n \n ] The CP surfaces ( D / L = 0.125, 0.17) completely rebounded the droplets ( v \n t ≈0.31, ≈0.44 m s −1 , respectively); however, the NP surfaces ( D / L = 0.125, 0.17) exhibited the complete CWT without retraction (Figure 2a,b ; and Movie S2 , Supporting Information). Additionally, the NP surface of D / L = 0.25 also resulted in the complete CWT at the velocity of ≈0.54 m s −1 but, only the partial CWT was observed for the CP surface leaving behind the Wenzel residue (Figure 2c ; and Movie S2 , Supporting Information). CP surfaces with the higher D / L of 0.33 and 0.5 performed complete bouncing at v \n t ≈ 0.63 and ≈0.89 m s −1 while the NP surfaces exhibited partial CWT (Figure 2d,e ; and Movie S2 , Supporting Information). The concave effect enhanced the impact resistance along the various surfaces regardless of line fractions. 2.3 Impact Pressure Stability of CP Surfaces While we have provided the enhanced impact pressure resistance of CP surfaces originating from the concave effects, the question was when the CP surfaces would allow the invasion of water droplets through the air/water interfaces. As for the identification, we further evaluated the pressure stability of CP surfaces in detail at higher falling heights, comparing them to the NP surfaces (Figure S9 and Movie S3 , Supporting Information). Weber number We , where W e = ρ v t 2 d 0 γ , ρ is the density and γ is the surface tension of water (≈1000 kg m −3 and ≈72 mN m −1 , respectively), is a key parameter for the investigation of droplet dynamic behavior, involving the energy state of a droplet. Thus, we explored the CWT regime for both NP and CP surfaces based on We . The detailed impact dynamics on the surfaces were investigated under the aforementioned method using ≈2 µL of water droplets with increasing the heights by the step of 0.5 cm. In this experiment, 0.5 cm higher height corresponds to an increased We by ≈2.1. \n Figure \n 3 a shows the wetting phase map of the NP and CP surfaces depending on the D / L and We . Generally, surfaces with lower D / L , and/or droplets with higher We tend to induce partial CWT and complete CWT. Surprisingly, the CP surface with the highest D / L ≈0.5 completely rebounded the droplet with We ≈25.5 and showed a partial CWT at a critical We ≈27.6. This critical We is ≈1.6 times higher compared to that of NP surface (≈17.0). Even though the effect from the concavity was relatively less than the D / L ≈0.5 surfaces, other CP surfaces ( D / L = 0.125–0.33) also exhibited better impact pressure‐resistant properties than the NP surfaces (Figure 3a ). Figure 3 Impact pressure‐resistant regime of the NP and CP microstructures followed by deducing mechanisms. a) Phase maps of pressure‐resistant properties along with NP and CP surfaces as a function of Weber number ( We ). b) Possible CWT mechanism on the NP surface by the critical v \n t , We , of a water droplet. c) Deducing water droplet bouncing behavior on the CP surface with equal v \n t and We for the NP surface. The scale of schematics does not concern the real‐world scale. Mainly, the transition to the Wenzel state during droplet impact has been considered as a depinning of the air/water interfaces and a sagging of the interfaces due to inertia (Figure 3b ). [ \n \n 20b \n \n ] The CWT of the CP surfaces with D / L = 0.5 and different aspect ratios ( D / H \n p ) also supports the depinning/sagging of the interfaces during the droplet impact. The CP surface of D / H \n p ≈ 1.8 showed the partial CWT at a slightly smaller critical We ≈ 23.4 (Figure S10 , Supporting Information), but still higher than the NP (critical We ≈ 17.0). Whereas the CP surfaces with D / H \n p ≤ 1 experienced a partial CWT at an equal critical We of ≈27.6 (Figure S11 , Supporting Information). These results indicate that the D / H \n p = 1 ( H \n p = 20 µm) seems to be enough to protect the air/water interface touch the bottom of the microstructures during instantaneous sagging of the interfaces due to the inertia. When the droplets contact the solid surfaces instantaneously, henceforth, there could be a water hammer pressure ( P \n H ) and a dynamic pressure ( P \n D ) striking the surfaces and facilitating CWT on the surfaces. [ \n \n 14 \n , \n 20 \n , \n 22 \n , \n 28 \n \n ] To prevent penetration of water droplets into the structures, the capillary pressure ( P \n C ) should be higher than the impacting pressure. As P \n C is enhanced by an increase in D / L , commonly the higher line fraction of the surface results in more stable pressure resistance against impacting pressure (detailed calculations of P \n C are depicted in Note S2 and Figure S12 , Supporting Information). The impact pressure P \n H and P \n D are described as P \n H = k \n wh \n ρCv \n t , P \n D = 0.5 ρv \n t \n 2 , respectively, where k \n wh is a water hammer coefficient and C is sound speed in water (1497 m s −1 ). [ \n \n 20c \n \n ] As for previous studies, the impact pressure could be balanced with the P \n C then, the k \n wh is expressed as: [ \n \n 20c \n \n ] \n \n (1) \n k wh = P C − P D ρ C v t \n \n In particular, the k \n wh had been considered as the value of 0.2, [ \n \n 27 \n \n ] but several studies have experimentally revealed that the coefficient should be decreased by at least two orders of magnitude for the superhydrophobic microstructures, [ \n \n 28 \n \n ] presenting a linear relationship with P \n C . [ \n \n 20 \n , \n 22 \n \n ] The v \n t in Equation 1 refers to the critical impact velocity at which the surface confronts partial CWT (further discussion is in Note S3 , Supporting Information). We then analyzed the relationship between the experimental parameter k \n wh and P \n C for both NP and CP surfaces. The NP surfaces show a linear correlation between k \n wh and P \n C in line with previous studies (Figure S13 and Table S2 , Supporting Information). [ \n \n 20 \n , \n 22 \n \n ] To support the linear relationship between P \n C and k \n wh , we additionally fabricated a truncated cone pillar (TCP) surface with D / L = 0.5 (Note S4 , Figure S14 , and Table S3 , Supporting Information), which could exhibit multiple capillary pressures. The fabricated TCP surface also shows a stable Cassie‐Baxter state (Note S5 and Figure S15 , Supporting Information). TCP surface is expected to contain no air caps, which resulted in a significantly smaller critical We ≈ 22.3 compared to that of CP (≈27.6). Interestingly, TCP still exhibited higher CWT resistance compared to the NP (critical We ≈ 17.0), which may be due to the presence of multiple capillary pressures (further discussions in Note S5 , Figure S16 , and Movie S4 , Supporting Information). The k \n wh values of the CP surfaces with D / L < 0.5 are similar to NP, also showing a linear relationship. However, the CP surface with D / L = 0.5 shows a k \n wh value of ≈0.00109, smaller than what is expected from the linear relationship. As for the discussion in previous studies, the closed cavity surfaces, which exhibit air spring effect, accomplished high impact pressure resistance compared to the open pillar structures. [ \n \n 17b \n \n ] Judging from that, the kinetic energy of the impacting droplet to our CP surface ( D / L = 0.5) could be compensated by the compressed air on the concave parts resulting in the prevention of the water penetration through air/water interfaces between pillars. These comprehensive results allowed us to speculate that the outstanding pressure stability of the CP surface ( D / L = 0.5) strongly depends on the air compression‐induced air spring effect rather than P \n C . In other words, a higher line fraction of 0.5 or more is essential for a potent concave effect on enhancing the impact pressure resistance. We also fabricated the CP surface with D / L = 0.56 through the further 5 min of KOH + IPA wet etching process to verify whether the line fraction of 0.5 or more is effective for the impact pressure resistance or not (Figure S17a,b , Supporting Information). Indeed, the CP surface ( D / L = 0.56) underwent the partial CWT at a critical We of ≈38.2 (critical velocity of ≈1.33 m s −1 ) (Figure S17c,d , and Movie S5 , Supporting Information), where ≈1.4 times higher critical We than the CP surface of D / L = 0.5 (≈27.6). Meanwhile, CP surfaces with D / L higher than 0.56 cannot be fabricated without defects due to the saturation of the etching rate during the KOH + IPA etching process. Owing to the air spring effect from trapped air seems to strongly contribute to the impact pressure resistance of the CP surface, we demonstrate the relation between effective air volume (unit air volume of the concavity/unit area) and critical We of each surface (Note S6 and Figure S18a , Supporting Information). Notably, the critical We of each surface is directly proportional to the effective air volume of the surface (Figure S18b , Supporting Information). Thus, the higher effective air volume of the CP surface would be a key parameter for designing a stable superhydrophobic surface. Nonetheless, the CP surface may exhibit limited droplet‐repellent function in specific cases. For example, if the CP surface is exposed to a water‐condensing environment, due to the higher number of nucleation sites, it is expected to possess lower CWT resistance compared to NP and TCP. To point out the limitations and guide the future research direction, we examined the impact pressure resistance of the NP, CP, and TCP surfaces ( D / L = 0.5) with the droplet We of ≈4.2 and ≈12.7, maintaining a surface temperature of ‐10 °C (a supercooled surface which can enhance droplet condensation). As expected, the CP surface did not repel the We ≈ 4.2 of water droplets possibly due to the higher number of water nucleation sites, while the other surfaces (partially) repelled the water droplets (Note S7 and Movie S6 , Supporting Information). Meanwhile, with the water droplets of We ≈ 12.7, all the surfaces performed similar wetting behavior (further discussion in Note S7 and Movie S6 , Supporting Information). Therefore, when designing water‐repelling surfaces for water condensing environments, additional factors such as the number of nucleation sites should be thoroughly considered. 2.4 Exceptional Plastron Stability of CP Surface We further scrutinized the underwater plastron stability of NP and CP surfaces. When the superhydrophobic surface is immersed in water, the surface can hold air between the protrusions on it and the air‐trapping state called a plastron. [ \n \n 11b \n \n ] The plastron reflects a silvery sheen due to the mirror‐like reflectance of thin air film ( Figure \n 4 a ). The underwater plastron on superhydrophobic surfaces is often metastable. This indicates that slow or fast CWT may occur underwater depending on various factors. [ \n \n 17a \n \n ] More specifically, the rate of CWT primarily depends on the rate of air escaping the pores, [ \n \n 17a \n \n ] and the mass flux of air from pores to bulk water has been evaluated to increase exponentially in response to the hydrostatic pressure. [ \n \n 29 \n \n ] Therefore, the plastron stability of both NP and CP surfaces was investigated under the hydrostatic pressure p ( h ) of 0.15–2.94 kPa (water depth of 1.5–10 cm), where p ( h ) = ρgh , g is the gravitational acceleration, and h is water depth. Specifically, the NP and CP surfaces with the highest line fraction ( D / L = 0.5) were employed for these investigations since the CP surface has performed effective concave effects against droplet impact. Figure 4 Superior plastron retention property of CP surface. a) Mirror‐like reflectance of CP surface underwater due to the entrapped air film, plastron. Schemes as to b) experimental set‐up for the investigation of underwater CWT and c) acquired snapshots regarding immersion time with a bright field for entrapped air and a dark field for the wetted area by water. The fraction of Wenzel state ( φ \n t ) for the d) NP surface and the e) CP surface as a function of time after immersion ( t \n i ) at varying hydrostatic pressure of 0.15–2.94 kPa (water depths of 1.5–30 cm). The solid lines denote fitted lines with exponential functions. f) Saturated plastron (trapped air) after 1440 min, 1 − φ \n 1440 , for the NP and CP surfaces as a function of p ( h ). Dashed curve lines indicate fitted lines for the NP and the CP surfaces, respectively, based on the exponential function. A dashed linear line (at lower p ( h )) denotes a fitted line for the CP surface based on the linear function. DI water was filled in a glass tank thereafter the tank was placed in a room with a constant temperature and humidity of 18.5 ± 0.2 °C and 50 ± 5%, respectively. The NP and CP surfaces were submerged in the water followed by imaging with a horizontally mounted optical camera (for h ≈ 1.5–10 cm) (Figure 4b ) or smartphone (for h ≈ 15–30 cm, due to the limited focal length of the optical camera). The wetted area and non‐wetted area can be distinguished by the difference in contrast since the trapped air film effectively reflects the light (Figure 4c ; Figures S19 and S20 , Supporting Information). We then defined a fraction of Wenzel state ( φ \n t ) by dividing the wetted area with the initial plastron area on the NP/CP surfaces as a function of time‐after‐immersion ( t \n i ). Figure 4d,e represents φ \n t of the NP and CP surfaces with immersion time, respectively, at varying p ( h ). The higher p ( h ) resulted in a faster CWT (Figures S19 and S20 , Supporting Information) and a higher saturated φ \n t . The φ \n t exponentially increased with increasing immersion time following the modified simple first‐order kinetic model (Note S8 and Figure S21 , Supporting Information). [ \n \n 17a \n \n ] It is important to note that, at low p ( h ), only a small fraction of the CP surface has gone through the CWT (≈7.5% at p ( h ) = 0.98 kPa; ≈3.5% at p ( h ) = 0.49 kPa; and ≈0.5% at p ( h ) = 0.15 kPa). Moreover, a p ( h ) of 2.94 kPa was required for CP to achieve a complete CWT. Contrary to the CP surface, the NP surface experienced a higher fraction (≈15%) of CWT even at small p ( h ) ≈0.15 kPa, achieving complete CWT at p ( h ) ≈ 1.96 kPa which is ≈33% lower than the value for CP. Consequently, we found the enhanced underwater plastron (trapped air film) stability of the CP surface compared to the NP surface below the p ( h ) of 2.94 kPa. All the surfaces at each p ( h ) show saturated φ \n t after t \n i = 1440 min. Therefore, the retained final plastron volume fraction can be described as 1 − φ \n 1440 . Assuming an ideal gas, a higher p ( h ) results in a higher fugacity (diffusion) of air in the water. The fugacity can be substituted by an equilibrium partial pressure, p ′. As a result, the correlation between the p ′ and the p ( h ) can be termed as: [ \n \n 29b \n \n ] \n \n (2) \n \n \n v \n m is a partial molar volume of gas (assumed as constant), [ \n \n 29a \n \n ] \n R is the gas constant, T is temperature, and p 0 ′ ≈ 1 is an initial equilibrium partial pressure. In our system, the plastron volume is considered constant so, the variation in pressure from the initial state is inversely proportional to the volume change. Therefore, the final plastron volume fraction, 1 − φ \n 1440 , can be approximated as: \n (3) \n ( 1 − φ 1440 ) ∼ e − v m R T p h \n where v m R T is believed constant, describing an exponential decrease in 1 − φ \n 1440 with increasing p ( h ) ( p ( h ) is constant for here because the change of h from evaporation is negligible with < 0.1 mm for 1.5 cm and < 1 mm for other heights). Indeed, the exponential decay of 1 − φ \n 1440 (plastron) for the NP regarding p ( h ) was observed, which means the metastable underwater stability of the NP surface even at a low p ( h ) ≈ 0.15 kPa (Figure 4f ). In contrast, a high fraction of retained plastron (≈92.5%) was observed on the CP surface up to the p ( h ) ≈ 0.98 kPa with a linear relationship between 1 − φ \n 1440 and p ( h ). Above that pressure, the CP surface seemed to go through an exponential decay of the plastron volume fraction (1 − φ \n 1440 ) at a higher p ( h ), inferring there's an initial hydrostatic pressure, p \n init , for activating the CWT of the CP surface (Figure 4f ). Therefore, the retaining plastron volume fraction (1 − φ \n 1440 ) in the CP surface can be approximated as: \n (4) \n ( 1 − φ 1440 ) ∼ e − v m RT p h − p init \n \n Since the v m R T is equal to that of the NP surface, the p \n init for the CP surface is acquired as ≈1.07 kPa based on the plots in Figure 4f . Concerning the concave structure of the CP surface, a convex air cap could be formed on the concave part underwater, pressing with downward Laplace pressure, Δ P \n L (Figure S22 , Supporting Information). The p \n init ≈1.07 kPa is quite similar to the possible Δ P \n L ≈1.17 kPa (minimum value in Note S9 , Supporting Information), implying the Δ P \n L on the concave cavities could be determined as a p \n init for the CP surface. Moreover, the CP surface experienced an NP‐like complete CWT at p ( h ) ≈ 2.94 kPa, where p ( h ) ≈ 2.94 kPa can be considered as a critical hydrostatic pressure, p \n crit , for the NP‐like wetting behavior of the CP surface. In detail, we can distinguish the underwater wetting state of the CP surface into 3 regimes as a function of the p ( h ): i) non‐wetting state ( p ( h ) < p \n init ), ii) intermediate state ( p \n init < p ( h ) < p \n crit ), and iii) NP‐like wetting state ( p ( h ) ≥ p \n crit ). i) Below the p ( h ) of p \n init , there exists a rapid drop of plastron volume fraction (within ≈120 min), followed by a stable partial Cassie‐Baxter state with a very low CWT fraction. The fraction of CWT increases gradually with increasing p ( h ), which may be due to some heterogeneity in CPs. ii) The case between p \n init ≈ 1.07 kPa and p \n crit ≈ 2.94 kPa can be defined as an intermediate (transitional) state due to the similar magnitude of Δ P \n L and p ( h ). As the air diffusion occurs from the convex air cap, the volume of the air cap will be reduced followed by the decrease in curvature radii of the air cap. The smaller radii lead to a higher Δ P \n L than the initial Δ P \n L ≈ 1.17 kPa (Note S9 , Supporting Information). Therefore, the competition of p ( h ) and increasing Δ P \n L leads to an intermediate wetting state of the CP surface under the p ( h ) from p \n init ≈ 1.07 kPa to p \n init ≈ 2.94 kPa. iii) Above the p \n crit ≈ 2.94 kPa, the CP loses its concave characteristic and acts similarly to the NP surface in terms of the CWT. This indicates that high p ( h ) has triggered the instantaneous filling of concave regions of the pillars. In this regard, adjusting the p \n init induced by the concave cavities would be critical for outstanding plastron stability underwater. 2.5 Concave Effect for Underwater Plastron Stability We introduced fluorescence confocal microscopy to certify the formation of convex air caps on the concave structures. The CP and NP surfaces were immersed in a 1.5 cm depth of fluorescent dye solution (surface tension of 74.1 ± 0.4 mN m −1 ) (Note S10 and Figure S23 , Supporting Information) for 720 min followed by washing and blowing. The adhered dyes on the CP and NP surfaces were then imaged using an inverted confocal microscope stacking in a z‐direction from the top to the bottom surface ( Figure \n 5 \n ; and Figure S24 , Supporting Information). We imaged particularly the wetted area of the NP surface (fraction of Wenzel state) to investigate whether the dark area in Figure S19 (Supporting Information) is genuinely in the Wenzel state or not. Conversely, we could not find any portion of the Wenzel state when imaging the CP surface. We found a trace of dyes only at the bottom edge of the concave cavities, not their center (Figure 5b ; and Figure S24a , Supporting Information). Besides, there were no dyes on the bottom of the CP structures implying a stable Cassie‐Baxter state during immersion (Figure S24a , Supporting Information). This illustrates the air/water interfaces above the concave parts didn't bulge into the structure, not touching the inner center of concave cavities. For that reason, the Δ P \n L from the convex air caps would compete with p ( h ) on the air/water interfaces between pillars. Existing higher pressure (Δ P \n L ) than p ( h ) might lead to an inhibition of air diffusion through the air/water interfaces between pillars owing to the favorable mass flux of air under higher pressure (Figure S22 , Supporting Information). On the contrary, some portion of the NP surface, both the top and bottom of the structure, was imaged with adhered dyes indicating the CWT on the NP surface (Figure 5c ; and Figure S24b , Supporting Information). To advocate our demonstration, a bubble rupture time for both NP and CP surfaces was measured (Note S11 and Figures S25 and S26 , and Movie S7 , Supporting Information). Collectively, these comprehensive results offer evidence that the concave effect forming convex air caps on the cavities is key to the stable Cassie‐Baxter state of the CP surface. Figure 5 Fluorescence confocal microscopy images of the NP and CP surfaces after immersion. a) Schematics for experimental method. Imaging was conducted after immersion of the surfaces in the fluorescent dye solution. Z‐stacked images for b) NP surface and c) CP surface, detecting adhered dyes after immersion. Images of a whole range from the top to the bottom surfaces were stacked."
} | 9,318 |
18761088 | null | s2 | 1,334 | {
"abstract": "Global energy and environmental problems have stimulated increasing efforts toward synthesizing liquid biofuels as transportation energy. Compared to the traditional biofuel, ethanol, advanced biofuels should offer advantages such as higher energy density, lower hygroscopicity, lower vapor pressure, and compatibility with existing transportation infrastructure. However, these fuels are not synthesized economically using native organisms. Metabolic engineering offers an alternative approach in which synthetic pathways are engineered into user-friendly hosts for the production of these fuel molecules. These hosts could be readily manipulated to improve the production efficiency. This review summarizes recent progress in the engineering of Escherichia coli to produce advanced biofuels."
} | 198 |
28748930 | null | s2 | 1,335 | {
"abstract": "Neurons in the brain behave as nonlinear oscillators, which develop rhythmic activity and interact to process information. Taking inspiration from this behaviour to realize high-density, low-power neuromorphic computing will require very large numbers of nanoscale nonlinear oscillators. A simple estimation indicates that to fit 10"
} | 83 |
33494537 | PMC7865638 | pmc | 1,337 | {
"abstract": "Among smart materials, self-healing is one of the most studied properties. A self-healing polymer can repair the cracks that occurred in the structure of the material. Polyketones, which are high-performance thermoplastic polymers, are a suitable material for a self-healing mechanism: a furanic pendant moiety can be introduced into the backbone and used as a diene for a temperature reversible Diels-Alder reaction with bismaleimide. The Diels-Alder adduct is formed at around 50 °C and broken at about 120 °C, giving an intrinsic, stimuli-responsive self-healing material triggered by temperature variations. Also, reduced graphene oxide (rGO) is added to the polymer matrix (1.6–7 wt%), giving a reversible OFF-ON electrically conductive polymer network. Remarkably, the electrical conductivity is activated when reaching temperatures higher than 100 °C, thus suggesting applications as electronic switches based on self-healing soft devices.",
"conclusion": "4. Conclusions In this work, we have prepared a new polymer composite characterized by electrical conductivity and self-healing characteristics triggered by temperature variations. The starting material used for this purpose is a polyketone, obtained by the polymerization of CO, ethylene and propylene. The polyketone was chemically modified by Paal-Knorr reaction using furfurylamine to introduce a furan pendant group onto the backbone of the polymer. The modification of the polyketone with furfurylamine successfully proceeded with a very high yield of about 85%, as confirmed by elemental analysis, FT-IR and 1 H-NMR. Nanocomposites were then prepared by solution mixing using reduced graphene oxide as a nanofiller and BISM as crosslinker to confer self-healing properties. After cross-linking via the formation of a Diels-Alder adduct between the furan moieties linked to PK and the BISM a cross-linked network was obtained, characterized by a reversible character being destroyed at 120 °C and reformed at 50 °C as confirmed by ATR-FTIR and DSC. The increased softening temperature of the cross-linked polymer was confirmed by DMTA which showed a maximum in the tan δ values of ~120 °C for the polymer containing 1.6, 2.7, 4.3 wt% of nanofiller and 170 °C for the polymer containing 5.5 wt%. All the nanocomposites showed a storage modulus higher than 10 6 Pa for all the investigated temperature, confirming the robustness of the polymer also at high temperature. The electrically conductive behavior of the crosslinked nanocomposite occurred only at temperatures higher than 100 °C with an OFF-ON behavior possibly addressed to the semiconducting features of rGO distributed in the polymer network in the form apparently isolated clusters as evidenced by SEM microscopy. The self-healing ability of the nanocomposite was confirmed by testing the recovery of the mechanical properties after the breaking and reprocessing processes of the polymer network. Overall, the conductive self-healing nanocomposite reported in this work can be useful for several applications where conductivity is required only at temperature higher than a certain threshold thus suggesting the development of electronic switches triggered by temperature. Notably, this smart material is also cost-effective thanks to the favorable selection of low-cost materials and the small amount of required rGO.",
"introduction": "1. Introduction Smart polymers are a category of materials able to change their features in response to the changing characteristics of the external environment [ 1 ]. A stimulus, such as a mechanical stress, a change in temperature or pH, is sufficient to easily modify the structure of the material [ 2 ], thus suggesting useful applications in various fields. A change in the structure of the material triggered by external stimuli is for example used to produce carriers for drug delivery [ 3 ]. On this account, Convertine et al. developed a diblock copolymer with a temperature-responsive micellization [ 4 ], whereas Mahmoodzadeh et al. reported a pH-sensitive triblock copolymer as a drug delivery system for cancer therapy [ 5 ]. Hajebi et al. proposed a temperature and pH-responsive nanogel for the controlled release of doxorubicin [ 6 ]. Furthermore, smart polymers are used to fabricate high-performance sensors [ 7 ], in chromatography [ 8 ] and in the oil industry [ 9 ]. Nowadays, smart materials are also endowed with certain self-healing characteristics [ 10 ], that are fully inspired by the typical mechanisms of the biological world [ 11 ]. Notably, local and temporary mobility must be achieved to get an effective self-healing material but without hindering the structural application of the whole material. Only the damaged part should be involved in the self-healing process. For this reason, local healing is provided by heating or irradiating a small portion of the broken material, while the bulk structure can retain the overall toughness [ 12 ]. The stimulus can be also provided by electrical current, that is able to repair the material’s damage thanks to the Joule effect [ 13 ]. The healing stimulus can be switched ON and OFF quickly depending on the kinetics of the healing mechanism and the chemical groups involved in the process [ 14 ]. From the above motivations, our group has extensively worked on self-healing thermosets based on the reversible Diels-Alder reaction [ 15 , 16 , 17 , 18 ]. From the perspective to produce scalable thermoset systems, our research has been focusing on the chemical modification of polyketone with primary amines via the Paal-Knorr reaction since it is a feasible route to produce these materials at an industrial level [ 19 ]. This synthetic approach provides several advantages; it can be carried out in bulk, without catalysts, with high yields at relatively mild conditions, and with water being the only by-product [ 19 ]. In addition, it can be also carried out without any solvent or in various organic solvents depending on the physical and chemical properties of the amine compound [ 20 ]. A variety of primary amines can be used, making this synthesis a fast, cheap, and appealing approach to create polymers with almost any desired pendant functional group [ 21 , 22 ]. Self-healing thermosets have been efficiently prepared by modifying polyketone with furan groups which can undergo thermally reversible Diels-Alder reactions with maleimides compounds [ 16 , 17 , 23 , 24 ]. Diels-Alder adducts can be easily formed at 50 °C and broken via retro Diels-Alder reaction at around 120 °C, thus appearing very useful to repair surface scratches or bulk cracks of polymeric materials [ 16 , 17 , 25 ]. The mechanical properties of these materials can also be tuned by adding fillers within the matrix as demonstrated in earlier works [ 13 , 15 ]. Polyketones functionalized with furan groups and crosslinked with bismaleimide experienced the enhancement of their elastic and loss moduli and softening points thanks to the reinforcement provided by multi-walled carbon nanotubes (MWCNTs). In addition, the percolative networks created by the MWCNTs dispersions within the thermosets allowed for electrically-triggered self-healing phenomena [ 15 ]. In recent literature, graphene is reported to outperform carbon nanotubes in polymeric nanocomposites in terms of enhanced mechanical [ 26 , 27 ], thermal, and electrical properties [ 28 ]. Graphene is one of the most popular nanofiller due to its carbon-like nature, nanometric dimensions and high conjugation of the π electrons. These characteristics render graphene as the most appealing filler in nanocomposites since it exerts its beneficial functions even at very low loading (<2–5 wt%) [ 29 , 30 ]. However, its poor dispersibility in solvents and irreversible aggregation in several media may limit its use [ 31 ]. An alternative to graphene is reduced graphene oxide (rGO) which is produced by the chemical or thermal reduction of graphene oxide. The residual functional groups remaining in the rGO structure make its dispersion easier and stable in water and polar organic solvents [ 32 , 33 , 34 , 35 ]. Furthermore, they increase the number of effective interactions with polymer matrices improving its homogeneous distribution in the solid host [ 36 , 37 ], leading to the preparation of polymeric nanocomposites [ 38 , 39 , 40 ], where rGO provides substantial electrical and mechanical properties [ 41 , 42 , 43 , 44 , 45 ]. Gudkov et al. demonstrate that with only 0.6 wt% of rGO dispersed in a polymeric matrix an electrical conductivity of 0.5 S/m is achieved for the nanocomposite [ 46 ]. Cheng et al. added rGO as nanofiller into a PVA polymer matrix providing an improvement of the Young’s modulus of about 80%. Despite a good increase in the Young’s modulus, a consequent drop of the elongation at break should be however taken into account [ 47 , 48 ]. In the present work, we report the synthesis of a self-healing and electrically conductive nanocomposite that displays re-workability and tunable electrical and thermomechanical properties as a function of the rGO content added to the matrix. As starting material, we used polyketone obtained from the copolymerization of 30% ethylene, 70% propylene and CO (PK) and functionalized with furan moieties (PKFU) that act as diene in the reversible Diels-Alder crosslinking process and compatibilizer for the rGO filler [ 13 , 15 , 16 ]. Moreover, a new type of bismaleimide (BISM) was used as dienophile [ 13 , 14 , 15 , 16 , 17 ] due to its increased miscibility in polyketone that might allow for a faster reaction with PKFU in the bulk ( Figure 1 ). Spectroscopic evidence confirmed the modification of polyketone via the Paal-Knorr reaction and the crosslinking of the final composites. The mechanical properties, recyclability, and reworkability of the final materials were evaluated by thermomechanical analyses. The final morphology of the materials and the dispersion of rGO in the polymeric matrix were characterized by SEM and the modulable OFF-ON electrical conductivity eventually determined as a function of the temperature.",
"discussion": "3. Results and Discussion 3.1. Furfurylamine Functionalization of Alternating Polyketone We prepared PKFU by a chemical modification of PK with furfurylamine via the Paal-Knorr reaction ( Figure 2 a). The reaction was carried out in a 0.8 molar ratio between the 1,4-dicarbonyl groups of the PK and the amino groups according to the calculated carbonyl conversion. The functionalization of PK yielded a di-carbonyl conversion (CO %) of 68.3% as determined from elemental analysis. We confirmed the successful functionalization of PK by 1 H-NMR ( Figure 3 ), where the signal at 5.8 and 2.0 ppm were respectively attributed to the hydrogen and to the methyl group of the pyrrole ring formed during the Paal-Knorr process. The peak at 4.9 ppm, attributed to the CH 2 units connecting the pyrrole ring to the furan one, evidenced the presence of furan as a pendant group. The peaks at 7.3, 6.2 and 5.9 ppm belong to the protons of the furan moieties, as reported earlier [ 15 , 18 ]. Notably, all peaks are attributed to PKFU, thus confirming that no residual amine was present after purification [ 14 , 17 ]. Figure 4 shows the ATR-FTIR spectra of PK and PKFU. After the Paal-Knorr reaction occurred, the C=O band centered at 1707 cm −1 decreased due to the disappearance of the 1,4-dicarbonyl moieties. The typical peak of the heterocyclic moieties appeared at 1507 cm −1 due to the C=C stretching, confirming the presence of both furan and pyrrole groups. The peaks associated to the pyrrole units were found at 3115 cm −1 (C=C-H) and at 1345 cm −1 (C-N). In addition, we assigned the peaks at 3150 cm −1 (C=C-H), at 1073 cm −1 (C-O-C), and at 737 cm −1 (C-H bonds out-of-plane bending) to the furan pendant group. Finally, the stretching bands of aliphatic C-H of PK backbone and functional groups appeared between 2969 and 2873 cm −1 [ 13 ]. 3.2. Preparation and Characterization of PKFU/BISM rGO Nanocomposites The bismaleimide (BISM, Figure 2 b) was chosen as a cross-linker for various reasons. Notably, the Diels-Alder adduct is reversible, a fundamental feature for imparting thermoplasticity and self-healing characteristics to the material. Moreover, the creation of the network increases the softening point of the PK, which has been calculated to be around 21 °C. The achieved softening temperature depends on the ratio between BISM and the furan pendant groups [ 16 ]. Figure 5 shows the ATR-FTIR spectrum of the polymer network before and after crosslinking. The peaks at 1182 and 1378 cm −1 were attributed to the C-O-C ether peak of reacted furan and to the stretching of the C-N bond of the maleimide ring, respectively, and confirmed the successful crosslinking between the furan and the bismaleimide moieties. It is worth noting that the intensity of the peaks at 737 cm −1 and 1073 cm −1 attributed out-of-plane bending C-H and to the C-O-C ether bonds of furan, respectively, decreased due to the formation of the Diels-Alder adduct [ 17 ]. We characterized all the crosslinked samples by differential scanning calorimetry (DSC) to determine the thermal behavior of the material and the reversibility of the crosslinking process upon three subsequent cycles of heating and cooling. For brevity, we show only the thermogram obtained from the polymer containing 5.5 wt% of nanofiller, while reporting all other results in the supporting information section ( Figures S1 and S2 ). Figure 6 shows the three heating and cooling cycles, all displaying the occurrence of the retro Diels-Alder reaction (endothermic peaks) and the re-formation of the network during cooling. Both broad endothermic and exothermic processes can be found in the range between 120–180 °C. In the heating experiments, the peak maximum corresponds to the temperature at which the majority of the Diels-Alder adducts are broken and the area associated to the peak indicates the energy absorbed during the cleavage of the adducts. We calculated the temperature and the energy needed to cleavage the adducts related to the maximum of the peak for each sample ( Figure 6 and Figure S1 ). Notably, as seen in Figure 7 as the temperature increased by more than 10 °C with the filler content, the energy substantially diminished by about 1.25 J/g, thus indicating that rGO affected the thermal stability of the crosslinked system. This effect was already observed in PKFU networks doped with MWCNTs although apparently smaller than that reported here for rGO [ 15 ]. The mechanical behavior of the composites as a function of temperature was investigated by dynamic mechanical thermal analysis (DMTA) in the range from 40 °C to 180 °C ( Figure 8 ). The bar samples for the DMTA analysis were obtained by compression molding of grinded crosslinked composites at 150 °C and 40 bar for 30 min. This method promotes the rDA mechanism and consequently the de-crosslinking of the thermoset nanocomposite. This behavior evidences the reversible and recyclable nature of these composite materials. The variation in storage modulus (E′), loss modulus (E″) and tan δ (softening point) were measured as a function of the rGO content. All samples show an initial slow decrease of the storage modulus and a corresponding increase of the loss modulus until a maximum value is reached which corresponds to the softening point of the material. After this point, a faster decrease of both moduli occurs due to the higher softening rate of the material. Notably, both loss and elastic moduli and softening point rise substantially for rGO contents higher than 5 wt%, thus confirming the reinforcement characteristics of the graphitic fillers in polymers [ 15 ]. Remarkably, the softening point increased from ~120 °C for the composite with a 1.6–4.3 wt% of rGO to values higher than 140 °C at loadings larger than 5.5 wt%. This effect could be possibly attributed to the interfacial interactions between graphitic filler and the polymer. rGO concentrations higher than 7 wt% seem to show minor reinforcements effects possibly due to less effective phase dispersion of the filler in the polymer matrix at the highest content. In order to understand the nature of the interactions between rGO and the network components, rGO was mixed with PKFU or BISM under the same conditions carried out for the formation of the rGO/PKFUBISM composite. After mixing, the recovered rGO was washed with chloroform several times to remove the non-interacting PKFU or BISM. We then evaluated the amount of PKFU or BISM interacting with rGO by thermogravimetric analysis. The experiments were performed from 25 °C to 800 °C under nitrogen atmosphere ( Figure 9 A). PKFU experiences a thermal degradation starting about 350 °C and showed a weight loss of 70%. rGO begin to degrade at about 200 °C with a gradual rate and it did not display a plateau even at 800 °C. On the other hand, BISM showed two degradation stages at 250 °C and around 500 °C with a total weight loss of 60%. rGO-PKFU also shows two degradation stages one at 200 °C due to the thermal degradation of the oxygen-functional groups of rGO [ 48 ] and a second one around 350 °C due to the degradation of PKFU grafted onto rGO. This sample showed an overall weight loss of 5.3% with respect to the pristine rGO at 800 °C. Conversely, rGO-BISM showed an identical thermal degradation than pristine rGO and an overall weigh loss of only 0.7 with respect to pristine rGO at 800 °C. Therefore, PKFU seems to interact better with the surface of rGO with respect to the neat BISM. The same samples were also characterized in terms of Raman spectroscopy, since it gives useful insights for the structure determination of graphitic materials ( Figure 9 B). The D band (1340 cm −1 ) and G band (1580 cm −1 ) are typical peaks of the rGO Raman spectrum [ 50 , 51 ]. The G-band indicates the planar vibration of sp 2 carbon atoms forming the graphitic structure whereas the D-band is associated to the scattering from defects that break the fundamental symmetry of the graphene sheet [ 52 , 53 ]. The peak centered at 2900 cm −1 is the combination of the first overtone of the D band (2D band) and the D+G band. The ratio of D and G bands peak intensities (I D /I G ) are widely used as standard index to identify defects on rGO after its functionalization. In this respect, the functionalization of rGO with PKFU inverts the intensities of the D and G-band and the I D /I G ratio of rGO and rGO-PKFU changed from 1.15 to 0.73, respectively. This result has already been published for functionalized carbon nanotubes with polyketones bearing furan groups through the Diels-Alder reaction [ 13 ]. In addition, rGO-PKFU shows a red-shift and sharpening of the G-Band in comparison to the pristine rGO. Kudin et al., addressed the sharpening and shifting back to graphitic position (shift to lower energies) of the G-Band in rGO after the heating treatment of graphene oxide [ 54 ] to the restoration of the rGO aromaticity in the defect regions of the graphene layer [ 55 ]. Overall, it seems that the effective interaction between PKFU and rGO could be attributed by a covalent bonding between the two materials and possibly caused by the Diels-Alder between the diene PKFU and the rGO dienophile. Future work will be addressed to investigate the reliability of the proposed mechanism further. Conversely, the functionalization of rGO with BISM slightly modified the intensities of the D and G-band, thus confirming the poor interaction between the crosslinker and the graphitic filler. We also evaluated the morphology of the composite material and the dispersion degree of rGO by SEM microscopy. Figure 10 shows the SEM images of the cross-sectional area of all the investigated nanocomposites and at different magnifications. In general, all samples appear as a smooth polymer matrix that contains assemblies of rGO randomly distributed in the form of interacting flakes with the polymer matrix but apparently distributed as isolated clusters. This effect appeared well evident in samples containing the highest amount of rGO ( Figure 10 D,E for 5.5 wt% and 7 wt% of rGO loading). While on one side the interfacial interactions between the polymer matrix and the rGO appeared confirmed, on the other these were not totally effective in providing a homogeneously distributed filler content within the crosslinked PKFU/BISM network. 3.3. Electrical Conductivity Properties of PKFU/BISM rGO Nanocomposites We then investigated the electric behavior of the nanocomposites in terms of surface resistivity and as a function of the rGO content. Contrary to our expectations, no samples were able to conduct electricity at room temperature ( Figure 11 ) even at the highest rGO content and also after the annealing process carried out at temperature higher than the corresponding softening points. These results could be possibly attributed to the generation of ineffective percolation pathways of conductive rGO assemblies within the polymer network and potentially attributed to the phase dispersion behavior evidenced by the SEM analysis ( Figure 10 ). Conversely, all the investigated nanocomposites started to conduct electricity at temperatures higher than 100 °C and with absolute surface resistivity values depending on the rGO concentration. The nanocomposite with rGO content of 1.6 wt%, 2.6 wt%, 4.3 wt% showed surface resistivity around 500 MΩ/sq at temperatures higher than 150 °C ( Figure 11 A–C) and after each cycle the temperature fluctuated considerably, suggesting that the nanocomposite is still close to the percolation threshold. Increasing the rGO content, the temperature threshold decreased to 135 °C and below 100 °C for the 5.5 wt% and 7.0 wt% of filler, respectively. Notably, a substantial decrease in the surface resistivity to below 100 MΩ/sq occurred at the highest 7 wt% doping amount of the rGO filler. Such OFF-ON reversible and temperature depending conductive behavior can be due to a combination of effects: (a) during annealing, the polymer becomes softer and the rGO particles are keen to generate effective percolation pathways thanks to their higher mobility within the polymer network; (b) rGO is a typical semiconductor, whose resistance decreases with temperature increase [ 56 , 57 , 58 ], thus allowing the polymer network to conduct electricity. 3.4. Self-Healing and Mechanical Properties of the Nanocomposite When testing the recyclability or the self-healing of a new material, mechanical properties are the biggest and most important issue. The recovery of the mechanical properties of the thermoset after the self-healing is essential because otherwise the material cannot be used to any further extent, even if all the other properties are recovered. To test the self-healing effect on the mechanical properties of our material, a bar of the polymer was prepared by compression molding, and DMTA analysis was performed. Then, the bar was broken as reported in Figure 12 and remolded using the same condition used before. Once healed, a second DMTA was collected on the cured sample ( Figure 12 d). In Figure 12 the pristine bar is shown (a) as well as the broken one (b,c). We noticed that after remolding (d) the bar recovered its original shape without any cracks, thus confirming the self-healing characteristic of the material for this first attempt. The previous result was confirmed by the DMTA characterization. Storage and loss moduli of the thermoset before and after the self-healing show the same values until 100 °C, while exhibiting an opposite behavior at higher temperature ( Figure 13 ). This behavior was reflected on the softening point of the material, the Tan (δ), which increased from ~120 °C to ~140 °C in the healed sample. The enhanced rigidity of the composite material after healing might be addressed to the presence of rGO, whose interfacial interactions with the PKFU macromolecules become more effective as also recently observed in similar samples containing MWCNTs [ 15 , 42 , 44 , 47 , 59 ]."
} | 6,020 |
28622518 | null | s2 | 1,340 | {
"abstract": "How do neighboring bacterial biofilms sense and communicate with each other? In a recent paper, Liu et al. (2017) demonstrate how electrical signaling allows communication of metabolic states between adjacent B. subtilis biofilms, providing a possible generalizable mechanism for communication in multispecies biofilms with interdependent metabolism."
} | 87 |
29205917 | PMC6011919 | pmc | 1,341 | {
"abstract": "Summary Biogas production is performed anaerobically by complex microbial communities with key species driving the process. Hence, analyses of their in situ activities are crucial to understand the process. In a previous study, metagenome sequencing and subsequent genome binning for different production‐scale biogas plants ( BGP s) resulted in four genome bins of special interest, assigned to the phyla Thermotogae , Fusobacteria , Spirochaetes and Cloacimonetes , respectively, that were genetically analysed. In this study, metatranscriptome sequencing of the same BGP samples was conducted, enabling in situ transcriptional activity determination of these genome bins. For this, mapping of metatranscriptome reads on genome bin sequences was performed providing transcripts per million ( TPM ) values for each gene. This approach revealed an active sugar‐based metabolism of the Thermotogae and Spirochaetes bins and an active amino acid‐based metabolism of the Fusobacteria and Cloacimonetes bins. The data also hint at syntrophic associations of the four corresponding species with methanogenic Archaea .",
"introduction": "Introduction The availability of fossil fuels is limited while the demand for energy increases steadily in the private and industrial sector, due to factors like affluence and population growth (Malik et al ., 2016 ). Additionally, the consumption of natural gas and especially petroleum and coal leads to large amounts of greenhouse gas (GHG) emissions, mainly CO 2 and CH 4 , implicating climate change and global warming (Liao et al ., 2016 ; Malik et al ., 2016 ). Fuels produced from renewable sources are increasingly important alternatives to provide environmental‐friendly energy (Weiland, 2010 ; Zhang et al ., 2016 ). Biogas is one of these important alternatives, which is produced by anaerobic digestion (AD) and mostly consists of CH 4 with smaller proportions of CO 2 and other impurities (Ge et al ., 2016 ). In industrial‐sized biogas plants (BGPs), biogas production and usage take place under controlled conditions as they are connected to combined heat and power (CHP) systems where biogas is combusted to provide electricity and heat. For biogas production, a wide variety of substrates, e.g. energy crops like maize and organic household, industrial, slaughterhouse and agricultural wastes, can be used mostly in mixtures (Weiland, 2010 ; Mao et al ., 2015 ; Ge et al ., 2016 ; Zhang et al ., 2016 ). Aside from substrate input, main differences in the setup of biogas plants concern the process temperature, as they can be run at mesophilic (35–42°C) and thermophilic (45–60°C) conditions. While mesophilic biogas processes are more stable and feature lower energy demand, biomass turnover is faster and methane yield is higher in thermophilic BGPs (Weiss et al ., 2008 ; Weiland, 2010 ; Mao et al ., 2015 ; Ruile et al ., 2015 ). The anaerobic digestion of biomass into methane can formally be subdivided into four phases, namely hydrolysis, acidogenesis, acetogenesis and methanogenesis. Within these phases, specialized groups of Bacteria and Archaea are responsible for the degradation of their respective substrates and are sometimes closely linked by syntrophic interactions. Hydrolysis is the first step in which bacteria break down complex polymers, like carbohydrates, lipids and proteins, into mono‐ and oligomers that are subsequently fermented by acidogenic and acetogenic bacteria to volatile fatty acids, alcohols, acetate, H 2 and CO 2 . The last step, in which acetate (acetoclastic) or CO 2 and H 2 (hydrogenotrophic) are converted into methane, is solely performed by methanogenic Archaea (Weiland, 2010 ; Mao et al ., 2015 ; Campanaro et al ., 2016 ). Within the last years, the complex biogas‐producing microbial communities have been studied with regard to their members and their respective functions, but are still not fully understood. Culture‐dependent approaches include isolation, culturing, phenotypic analyses and sequencing of single community members (e.g. Maus et al ., 2016 ). However, the culturing approach is limited as not all Bacteria and Archaea can be cultured and do not necessarily represent dominant and therefore functionally important members of the community. Thus, culture‐independent approaches, like metagenome and metatranscriptome sequencing, are frequently used to access the communities’ functional potential and determine transcriptional activity (e.g. Zakrzewski et al ., 2012 ; Eikmeyer et al ., 2013 ; Kovács et al ., 2013 ; Bremges et al ., 2015 ; Stolze et al ., 2015 , 2016 ). However, it is important to determine in situ functions of single microorganisms within the fermenters to better understand the process and, in the long run, enable optimization of the biogas production process. Therefore, metagenome assembly and subsequent binning of assembled contigs into genome bins are used as an approach to access single genomes within the microbial community, circumventing the need of cultivation (Kunath et al ., 2017 ; Sczyrba et al ., 2017 ). In this approach, species genomes are reconstructed from metagenome data sets representing a microbial community, enabling the reconstruction of their metabolic potential and abundance determination by mapping back metagenome reads on the respective genome bins (Mande et al ., 2012 ; Sharpton, 2014 ; Sangwan et al ., 2016 ). Binning has previously been used on biogas communities from laboratory‐ and production‐scale biogas production reactors, resulting in reconstruction of unknown species (Campanaro et al ., 2016 ; Stolze et al ., 2016 ; Treu et al ., 2016 ; Xia et al ., 2016 ; Kougias et al ., 2017 ). Still, a study on the actual role within the community and these species’ in situ metabolic transcriptional activity within their respective habitats is missing. In this study, we determined the in situ transcriptional activity of four genome bins originating from deeply sequenced metagenomes obtained from mesophilic and thermophilic agricultural biogas systems using corresponding metatranscriptome data. The four genome bins, of which three are novel and uncharacterized, represent species of the bacterial phyla Thermotogae , Fusobacteria , Spirochaetes and Cloacimonetes (WWE1) respectively. They have been previously selected due to their taxonomic affiliation and genomically characterized (Stolze et al ., 2016 ). Analyses on the four species represented by the genome bins gave insights into their actual transcriptional activities and showed their respective metabolism and role within their habitats.",
"discussion": "Results and Discussion Metatranscriptome sequencing and read mapping In this study, the actual in situ transcriptional activity of the species represented by four distinct genome bins was analysed to determine their transcriptional profiles and with this their roles within the biogas production process. For this purpose, RNA was extracted simultaneously from the same samples as the metagenomic DNA was derived from and metatranscriptome sequencing was performed in duplicates. In total, 900 million reads (137 Gbp; Table 1 ) were generated for one mesophilic and one thermophilic BGP. For the evaluation of transcriptional activities, the metatranscriptome reads from the BGPs were mapped on selected genome bins, counted and normalized on gene length and data set size resulting in transcripts per million (TPM) values. Table 1 Metatranscriptome sequencing results Biogas plant sample Technical replicate No. of reads No. of bases Mesophilic 1 261 433 302 39 214 995 300 2 258 702 414 38 805 362 100 Thermophilic 1 161 677 326 24 251 598 900 2 233 914 040 35 087 106 000 Total – 915 727,082 137 359 062 300 John Wiley & Sons, Ltd To determine whether the postulated metabolic potentials of the four bins correlate with their transcriptomic activities and whether relevant genes show high transcriptional rates under in situ conditions, their TPM values were further analysed. Next to the general evaluation of the 25 most highly transcribed genes of the genome bins (see Table S1 , S2 , S3 and S4 ), analyses of the bins’ activity in carbohydrate degradation, fermentation pathways and syntrophic associations were performed in depth by determining TPMs for respective meaningful genes. To enable a direct examination of high, moderate or low transcriptional activity of these genes, their TPM values were assigned to categories, ranging from 1 (within the lowest 10%) up to 10 (within the top 10% transcripts). Table 2 lists TPM values and respective categories for genes encoding carbohydrate‐active enzymes, chosen by their relevance in anaerobic digestion according to Vanwonterghem et al . ( 2016 ). Table 3 shows those for enzymes involved in fermentation pathways. It was recently suggested that all four genome bins may be syntrophically associated with methanogenic Archaea (Stolze et al ., 2016 ). Therefore, transcriptional activities of genes encoding enzymes potentially involved in syntrophy, according to Worm et al . ( 2014 ), were analysed regarding presence and transcriptional activity for each genome bin. The results are shown in Table 4 . For better clarity, in all three Tables, only those genes are shown that were found in at least one of the genome bins (the complete tables are represented in the Tables S1 , S2 , S3 , S4 , S5 , S6 and S7 ). In the following chapters, each genome bin is discussed regarding these analyses. Table 2 Glycosyl hydrolase (GH) families relevant for anaerobic digestion according to Vanwonterghem et al . ( 2016 ) and their respective transcript per million (TPM) values and transcriptional categories for each of the four analysed genome bins. The categories range from 0 (no transcription) and 1 (lowest 10% of transcripts) to 10 (top 10% transcripts). n.d.: not detected Enzymes Glycoside \n Thermotogae bin \n Fusobacteria bin \n Spirochaetes bin \n Cloacimonetes bin Enzyme type Hydrolase family TPM Category TPM Category TPM Category TPM Category Endo – and exo‐1,4‐β‐D‐glucanase (cellulase) GH5 3.639 3 n.d. – n.d. – n.d. – Hemicellulose GH16 4.340 3 n.d. – n.d. – 0 0 GH28 2.167 2 n.d. – 0.023 2 n.d. – GH53 41.236 8 n.d. – n.d. – n.d. – GH115 n.d. – n.d. – 0.132 6 n.d. – GH76 n.d – n.d – 0.018 1 n.d – Starch and glycogen Hydrolase GH13 3.958 3 1.574 6 0.129 6 0.007 2 GH77 n.d. – 9.716 10 0.102 6 0 0 GH57 35.201 8 3.788 8 0.165 7 0.021 5 Lysozyme, chitinase (cell wall degradation) GH18 6.172 3 n.d. – n.d. – 0.021 5 GH23 20.029 6 0.655 3 n.d. – 0.063 8 GH73 n.d. – n.d – n.d – n.d – Glycosidase (hydrolysis of single sugar residues from non–reducing ends) GH1 0.822 1 n.d. – 0.074 4 n.d. – GH2 38.604 8 n.d. – 0.107 6 n.d. – GH3 3.022 2 n.d. – 0.142 6 n.d. – 0.069 4 GH4 22.249 6 n.d. – 0.019 2 n.d. – 144.144 10 GH38 n.d. – n.d. – n.d. – 0.004 1 GH51 3.355 3 n.d – 0.113 6 n.d – Oligosaccharide phosphorylase GH130 n.d. – n.d. – n.d. – 0.002 1 John Wiley & Sons, Ltd Table 3 Fermentation pathway proteins and their respective transcript per million (TPM) values and transcriptional categories for each of the four analysed genome bins. The categories range from 0 (no transcription) and 1 (lowest 10% of transcripts) to 10 (top 10% transcripts) n.d.: not detected Fermentation type Fermentation pathway Enzyme Interpro number \n Thermotogae bin \n Fusobacteria bin \n Spirochaetes bin \n Cloacimonetes bin TPM Category TPM Category TPM Category TPM Category Propionic acid fermentation Acrylyl‐CoA pathway CoA‐transferase (EC 2.8.3.1) IPR003702 n.d. – n.d. – n.d. – n.d. – Lactoyl‐CoA dehydratase dehydratase IPR010327 n.d – n.d. – 0.065 3 0.009 2 Acyl‐CoA dehydrogenase (E.C. 1.3.99.3) IPR034179 n.d. – 0.052 1 n.d. – n.d. – IPR034180 Methylmalonyl‐ CoA pathway Pyruvate carboxylase (EC 6.4.1.1) IPR005930 n.d. – n.d. – n.d. – n.d. – Malate dehydrogenase (EC 1.1.1.37) IPR001252 25.110 7 1.308 5 n.d. – 0.035 7 IPR023958 IPR011275 Fumarate hydratase (EC 4.2.1.2) IPR018951 18.872 6 0.982 4 0.13 6 0.0104 3 IPR011167 Fumarate reductase (EC 1.3.5.4) IPR005884 n.d. – n.d. – n.d. – n.d. – Succinyl‐CoA synthetase (EC 6.2.1.4; EC 6.2.1.5) IPR034722 n.d. – n.d. – n.d. – n.d. – IPR005809 IPR005810 Methylmalonyl‐CoA mutase (5.4.99.2) IPR004608 n.d. – 0.021 1 n.d. – n.d. – IPR024067 Methylmalonyl‐CoA epimerase (EC 5.1.99.1) IPR017515 38.108 8 n.d. – n.d. – n.d. – Methylmalonyl‐CoA decarboxylase (EC 4.1.1.41) – 24.441 7 n.d. – n.d. – n.d. – CoA‐transferase (EC 2.8.3.1) IPR003702 n.d. – n.d. – n.d. – n.d. – Ethanol fermentation Pyruvate dehydrogenase (EC 1.2.4.1) IPR017597 n.d. – n.d. – n.d. – n.d. – IPR027110 Pyruvate decarboxylase (EC 4.1.1.1) – n.d. – n.d. – n.d. – n.d. – Alcohol dehydrogenase (EC 1.1.1.1) IPR023921 26.691 7 1.563 6 0.337 9 0 0 0.3203 8 0.028 2 Formic acid fermentation 2,3‐Butanediol fermentation Pyruvate formate‐lyase (EC 2.3.1.54) IPR005949 n.d. – n.d. – n.d. – n.d. – Formate Hydrogen Lyase (EC 1.2.1.2) IPR006478 n.d. – n.d. – n.d. – n.d. – IPR033689 Acetolactate synthase (EC 2.2.6.1) IPR004789 57.686 9 2.784 8 n.d. – n.d. – IPR012782 18.144 6 1.922 7 IPR012846 IPR019455 Acetolactate decarboxylase (EC 4.1.1.5) IPR005128 n.d. – n.d. – n.d. – n.d. – Butanediol dehydrogenase (EC 1.1.1.4) – n.d. – n.d. – n.d. – n.d. – Mixed‐acid fermentation Pyruvate carboxylase (EC 6.4.1.1) IPR005930 n.d. – n.d. – n.d. – n.d. – Malate dehydrogenase (EC 1.1.1.37) IPR001252 25.110 7 1.309 5 n.d. – 0.035 7 IPR023958 IPR011275 Fumarase (EC 4.2.1.2) IPR018951 18.873 6 n.d. – 0.130 6 n.d. – IPR011167 Fumarate reductase (EC 1.3.1.6) IPR027477 n.d. – n.d. – n.d. – 0.007 2 Lactate dehydrogenase (EC 1.1.1.28) – 19.016 6 n.d. – 0.169 7 n.d. – 18.631 6 0.189 7 Phosphotransacetylase (EC 2.3.1.8) IPR016475 1.765 2 3.875 8 n.d. – 0.021 5 IPR004614 IPR002505 IPR012147 Acetate kinase (EC 2.7.2.1) IPR000890 79.588 9 4.573 8 0.136 6 0.029 6 IPR004372 IPR023865 Butyric acid fermentation Thiolase (EC 2.3.1.9) – n.d. – n.d. – n.d. – n.d. – 3‐hydroxybutyryl‐ CoA dehydrogenase(EC 1.1.1.157) – n.d. – n.d. – n.d. – n.d. – Crotonase (EC 4.2.1.150) – n.d. – n.d. – n.d. – n.d. – Butyryl‐CoA dehydrogenase (EC 1.3.8.1) – n.d. – n.d. – n.d. – n.d. – Phosphate butyryl transferase (EC 2.3.1.19) IPR014079 1.765 2 n.d. – n.d. – n.d. – Homoacetogenesis \nButyrate kinase (2.7.2.7) \nPyruvate: ferredoxin oxidoreductase (EC 1.2.7.1)\n IPR011245 3.494 3 n.d. – n.d. – 0.029 6 – 50.748 8 14.265 10 0.053 3 0.060 8 49.909 8 0.050 8 11.622 5 61.543 9 Phosphotransacetylase(EC 2.3.1.8) IPR016475 1.765 2 3.874 8 n.d. – 0.021 IPR004614 IPR002505 IPR012147 Acetate kinase (EC 2.7.2.1) IPR000890 79.588 9 4.573 8 0.136 6 0.029 6 IPR004372 IPR023865 Lactic acid Fermentation Homolactic acid fermentation Glucose‐6‐phosphate isomerase (EC 5.3.1.9) IPR001672 22.717 6 5.772 9 0.520 9 0.011 3 IPR010551 IPR016758 IPR018189 IPR023096 6‐phospho‐fructokinase (EC 2.7.1.11) IPR000023 74.683 9 7.921 9 n.d. – 0.057 8 IPR012003 IPR012004 IPR012828 IPR015912 IPR022953 Fructose‐bisphosphate aldolase (EC 4.1.2.13) IPR023014 152.525 10 15.580 10 1.015 10 n.d. – IPR000741 0.111 5 IPR011289 IPR029768 Triosephosphate isomerase (5.3.1.1) IPR000652 81.170 9 n.d. – n.d. – n.d. – IPR020861 IPR022891 IPR022896 Lactate dehydrogenase (EC 1.1.1.28) – 19.016 6 n.d. – 0.169 7 n.d. – 18.631 6 0.189 7 Heterolactic acid fermentation Hexokinase (EC 2.7.1.1) IPR001312 81.171 9 n.d. – 0.115 5 n.d. – IPR019807 IPR022672 IPR022673 Glucose‐6 phosphate dehydrogenase (EC 1.1.1.49) IPR001282 18.460 6 n.d. – 0.128 6 n.d. – IPR019796 IPR022674 IPR022675 6‐phosphogluconolactonase (EC 3.1.1.31) IPR022528 n.d. – n.d. – 0.346 9 n.d. – Phospho‐gluconate dehydrogenase (EC 1.1.1.44) IPR006184 6.055 3 n.d. – 0.095 5 n.d. – IPR006114 IPR006113 IPR006183 Ribulose‐phosphate 3‐epimerase (EC 5.1.3.1) IPR000056 28.915 7 2.740 8 0.578 9 0.012 3 IPR026019 Xylulose‐5‐phosphate phosphoketolase (EC 4.1.2.9) – n.d. – n.d. – n.d. – n.d. – Acyl‐phosphatase (EC 3.6.1.7) IPR001792 15.719 5 n.d. – n.d. – 0.021 5 IPR017968 IPR020456 IPR028627 Acetate kinase (EC 2.7.2.1) IPR000890 79.588 9 4.573 8 0.136 6 0.029 6 IPR004372 IPR023865 Phosphotransacetylase (EC 2.3.1.8) IPR016475 1.765 2 3.875 8 n.d. – 0.028 6 IPR004614 IPR002505 IPR012147 Acetaldehyde dehydrogenase (EC 1.2.1.10) IPR003361 n.d. – n.d. – n.d. – n.d. – IPR015426 Alcohol dehydrogenase (EC 1.1.1.1) IPR023921 26.691 7 1.563 6 0.337 9 0 0 0.303 8 0.028 2 John Wiley & Sons, Ltd Table 4 Proteins possibly associated with syntrophy according to Worm et al . ( 2014 ) and their respective transcript per million (TPM) values and transcriptional categories for each of the four analysed genome bins. The categories range from 0 (no transcription) and 1 (lowest 10% of transcripts) to 10 (top 10% transcripts). n.d.: not detected Protein Subunit Interpro number \n Thermotogae bin \n Fusobacteria bin \n Spirochaetes bin \n Cloacimonetes bin TPM Category TPM Category TPM Category TPM Category Capsule synthesis protein, CapA – IPR019079 n.d. – n.d. – n.d. – 0.04 7 Cell cycle, FtsW, RodA SpoVE – IPR018365 n.d. – 0.42 2 n.d. – n.d. – 0.64 3 0.42 2 Ribonuclease P, conserved site – IPR020539 n.d. – n.d. – n.d. – 0.12 9 Cytoplasmic FDH NUO 51 kDa IPR019575 n.d. – n.d. – 0.054 3 n.d. – IPR001949 79.06 9 0.36 8 0.054 3 0.02 5 0.02 5 Extracytopl. FDH Alpha IPR006443 79.06 9 0.36 8 n.d. – 0.02 5 FeFe‐hydrogenase Alpha IPR004108 n.d. – n.d. – 0.075 4 n.d. – IPR009016 110.75 9 2.07 7 0.075 4 0.05 8 9.26 10 IPR003149 110.75 9 2.07 7 0.075 4 0.05 8 9.27 10 IPR013352 110.75 9 9.27 10 0.075 4 0.05 8 NiFe‐hydrogenase – IPR001501 110.75 9 9.27 10 n.d. – 0.05 8 IPR018194 n.d. – n.d. – n.d. – n.d. – Rnf complex RnfB IPR007202 n.d. – n.d. – n.d. – n.d. – IPR010207 798.79 10 2.07 7 0.25 8 0.02 5 2.68 8 RnfC IPR026902 798.79 10 2.68 8 0.34 9 0.02 5 IPR010208 14.37 5 4.01 8 0.34 9 0.01 2 RnfD IPR004338 14.37 5 4.01 8 3.24 10 0.01 2 IPR011303 7.63 4 0.93 4 0.39 9 0.01 2 RnfG IPR007329 7.63 4 0.93 4 n.d. – 0.01 2 Ech complex EchA IPR001750 1100.12 10 12.01 10 n.d. – 0.01 2 162.44 10 0.01 2 IPR001516 n.d. – n.d. – n.d. – n.d. – EchB IPR001694 n.d. – n.d. – n.d. – n.d. – EchC IPR006137 n.d. – n.d. – n.d. – n.d. – EchD IPR001268 n.d. – n.d. – n.d. – n.d. – IPR012179 n.d. – n.d. – n.d. – n.d. – EchE IPR001135 n.d. – n.d. – n.d. – n.d. – Etf Alpha – IPR014731 n.d. – n.d. – 0.41 9 n.d. – Etf Beta – IPR012255 n.d. – n.d. – 1.19 10 0.03 6 Bcd – IPR006089 n.d. – n.d. – n.d. – 0.02 5 – IPR009075 n.d. – n.d. – n.d. – 0.05 8 – IPR006092 n.d. – n.d. – n.d. – 0.05 8 – IPR006091 n.d. – n.d. – n.d. – n.d. – – IPR013786 n.d. – n.d. – n.d. – 0.05 8 – IPR009100 n.d. – n.d. – n.d. – 0.05 8 DUF224 – IPR003816 n.d. – n.d. – n.d. – 0.05 8 – IPR004017 n.d. – n.d. – n.d. – n.d. – – IPR023234 n.d. – n.d. – n.d. – n.d. – John Wiley & Sons, Ltd The transcriptional profile of the Thermotogae bin indicates a metabolism based on sugar fermentation The previous taxonomic and genetic analyses of the Thermotogae genome bin showed that it represents a species closely related to the thermophilic bacterium Defluviitoga tunisiensis L3 (Maus et al ., 2015 , 2016 ), or may even indicate another strain of this species. It is presumably able to utilize a wide variety of mono‐, di‐ and polysaccharides and was predicted to produce acetate, hydrogen and carbon dioxide as end‐products (Stolze et al ., 2016 ). Analysis of the 25 most highly transcribed genes within the Thermotogae bin showed that 22 of them are functionally classified and 17 encode proteins involved in mandatory processes like transcription, translation, fatty acid metabolism, iron storage, electron transport, protein and RNA folding. Three highly transcribed genes encode proteins associated with ATP‐binding cassette (ABC) transporters (see Table S1 ), known as importers for sugars and other solutes (Davidson et al ., 2008 ), with two of them specifically annotated as maltose import system. In total, 223 transcripts encoding proteins involved in sugar utilization were found for the bin. Most of these are involved in either binding and import (ABC sugar transporters) or sugar utilization within the cell, e.g. via the glycolysis pathway. Table 2 shows that the Thermotogae bin encodes eleven glycoside hydrolase (GH) family proteins, all of them being transcribed featuring TPM values above the average (TPM categories ≥ 6). Selected sugar utilization genes of the genome bin and their transcriptional activity are indicated in Fig. 1 . It appeared that especially the sugar transporter genes and those for glycolysis enzymes are highly transcribed. In general, these findings strongly suggest that this species actively degrades and utilizes a variety of carbohydrates, whose end‐products are further channelled into the glycolysis pathway. Figure 1 Metabolic reconstruction of sugar utilization pathways in the Thermotogae genome bin and transcript per million ( TPM ) values for genes encoding involved proteins. Figure modified according to Maus et al . ( 2016 ). Carbohydrates are labelled in light orange ovals, transporters in blue and corresponding genes in yellow rectangles. White rectangles represent genes lacking in the genome bin in comparison with its reference strain Defluviitoga tunisiensis L3. Frames indicate the category of TPM values for the respective gene, the five categories explained on the bottom right. The glycolysis and the pentose phosphate pathways are highlighted in green and blue, respectively. Abbreviations: CO \n 2 , carbon dioxide; GAP , glyceraldehyde‐3‐phosphate; KDG ‐6P, 2‐keto‐3‐deoxy‐d‐gluconase‐6‐phosphate. Regarding the production of end‐products, Fig. 1 and Table 3 reflect the bin's activity in hydrogen, CO 2 , acetate and possibly lactate and ethanol production. Alternatively, lactate could be used for pyruvate production. Hydrogen and acetate production is known for D. tunisiensis L3 and was previously discussed as hint for a syntrophic lifestyle with aceticlastic or hydrogenotrophic Archaea (Maus et al ., 2016 ; Stolze et al ., 2016 ). This assumption is further supported by the presence and partially high transcriptional activities of genes encoding enzymes associated with syntrophy (Worm et al ., 2014 ). The same applies for genes that are important for hydrogen production (see Table 4 and Fig. 1 ). For example, transcripts encoding the bifurcating FeFe‐hydrogenase ( hydABG ), pyruvate oxidoreductase ( porABCD ) and subunits of the Rnf complex were identified for the genome bin. The Rnf complex represents a membrane bound transporter that was shown to be able to conserve energy by coupling the oxidation of NADH to the simultaneous reduction of ferredoxin with ion transport (Biegel and Muller, 2010 ; Hess et al ., 2013 ; Worm et al ., 2014 ). The reduced ferredoxin may then be used as electron donor by a (bifurcating) hydrogenase to form H 2 from protons (H + ). The consumption of hydrogen from the producer would enable its formation despite the thermodynamically unfavourable nature of this process (Verhaart et al ., 2010 ; Worm et al ., 2014 ). Despite the lack of other putative syntrophy‐associated genes, the high TPM values for hydrogen production‐associated genes strongly indicate that the species represented by the Thermotogae bin is syntrophically associated with a partner consuming hydrogen, as it was previously described for other Thermotogae species (Balk et al ., 2002 ; Johnson et al ., 2006 ). In summary, the in situ transcriptional profile of the Thermotogae genome bin shows partially high transcriptional activities regarding genes encoding proteins involved in (complex) sugar utilization, acetate, ethanol, CO 2 and H 2 production and those having predicted functions in a syntrophic association. The profile therefore reflects a possibly syntrophic and sugar‐based lifestyle of the corresponding species that in its thermophilic habitat occupies the role of a hydrolytic/acetogenic bacterium. The transcriptional profile of the Fusobacteria bin indicates a motile species with a metabolism based on amino acid fermentation Previous genetic analyses of the Fusobacteria genome bin suggested that the corresponding bacterium is an amino acid‐fermenting, acetogenic bacterium, possibly also syntrophically associated with methanogenic Archaea (Stolze et al ., 2016 ). The species’ transcriptome analysis, based on metatranscriptome sequencing data from its mesophilic habitat, was supposed to uncover its in situ response to prevailing environmental conditions. Analyses of the genes with the 25 highest TPM values showed functional annotations for 15 genes, with six being involved in mandatory processes of translation, chromosome and RNA protection, reactive oxygen species (ROS) scavenging, fatty acid metabolism and cell division (see Table S2 ). Interestingly, eight transcripts encode flagellum‐associated proteins. In total, the bin encodes 46 proteins of this functional context and additional 73 proteins involved in chemotaxis (e.g. histidine kinases, Che proteins) (Bi and Lai, 2015 ; Micali and Endres, 2016 ), most of them being highly transcribed (category 8). Regarding the bin's metabolism, the top 25 list of the most highly transcribed genes did not provide any information, but Table 2 shows that the Fusobacteria bin features only three encoded GH families, however with transcriptional categories of 3, 6 and 10. Still, the low number of transcribed GH family genes and their predicted functional context rather suggest that the species represented by the bin does not utilize (complex) sugars. Previous analyses on the genetic content suggested that its metabolism is based on glutamate and lysine fermentation (Stolze et al ., 2016 ). Transcriptional analyses showed that for glutamate utilization, some of the key enzymes of the hydroxyglutarate pathway have high (category 8), some others lower TPM values (categories 2 and 3). For lysine utilization, the pathway of d ‐ and l ‐lysine degradation to acetate is complete, with medium TPM values (category 6); both findings strongly indicate an active amino acid utilization. The transcriptional data also clearly indicate ethanol, acetate, H 2 , CO 2 and possibly lactate as end‐products of the species’ metabolism, as shown in Table 3 . The key genes encoding alcohol dehydrogenase, lactate dehydrogenase and acetate kinase feature transcription categories of 6, 8 and 8 respectively. Table 3 also shows that hydrogen production is likely to occur as the pyruvate:ferredoxin oxidoreductase, converting pyruvate to acetyl‐CoA and CO 2 and simultaneously reducing ferredoxin, is highly transcribed (categories 5, 8 and 9). Ferredoxin is, i.a., used for hydrogen production (Biegel and Muller, 2010 ; Hess et al ., 2013 ) and features transcriptional categories of 10 (see Table S2 ). It can be used by a bifurcating FeFe‐hydrogenase to produce hydrogen. The genes encoding this enzyme are highly transcribed (categories 7 and 10) as shown in Table 4 , which summarizes transcriptional activities of genes encoding proteins involved in syntrophy according to Worm et al . ( 2014 ). As the described reaction is thermodynamically unfavourable, it depends on a hydrogen‐consuming methanogenic archaeon (Sieber et al ., 2012 ). The hypothesis of a possible syntrophic association is supported by other transcripts encoding putative syntrophy‐associated genes being highly transcribed by the species, and among them, subunits of the Rnf complex with transcriptional categories between 4 and 8 (Table 4 ). However, these findings are not in line with the findings indicating a motile lifestyle, as it is known that the formation of mats or biofilms eventually results in motility loss (Alexandre, 2015 ). Flagella play important roles in the maintenance of the close physical contact between the syntrophic partners (McInerney et al ., 2009 ; Krumholz et al ., 2015 ), but this does not explain the high transcription rates of chemotaxis‐associated genes. However, the metatranscriptome‐based profile comprises the whole Fusobacteria bin ‐ represented population in situ . A subpopulation may be syntrophically associated, while other cells still were motile. In summary, the transcriptional profile of the Fusobacteria genome bin, as deduced from metatranscriptome sequencing data, depicts a motile, acidogenic, mostly amino acid‐based metabolism with acetate, ethanol, CO 2 , H 2 and probably lactate as fermentation end‐products. The transcriptional profile of the Spirochaetes bin indicates a sugar fermentation‐based species Previously, the Spirochaetes genome bin was analysed genetically and as deduced from its metabolic potential, the bin may constitute a syntrophic sugar‐fermenting bacterium producing acetate, CO 2 and H 2 (Stolze et al ., 2016 ). Based on metatranscriptome sequencing data from the mesophilic BGP, the bin's activity and role within its habitat were analysed at the transcriptional level. Regarding the top 25 list of the most highly transcribed genes, 19 encoded gene products received functional annotations, with 15 of them being involved in mandatory processes of translation, transcription, fatty acid metabolism, protein folding and export and electron transfer (Table S3 ). Two of the annotated genes among the 25 most highly transcribed ones encode an ABC transporter substrate‐binding protein and a LacI family transcriptional regulator, both featuring transcriptional categories 10. ATP‐binding cassette (ABC) transporters are known as importers for sugars and also other solutes, while LacI family proteins function as transcription inhibitors for genes encoding proteins for lactose utilization (Davidson et al ., 2008 ; Santillan and Mackey, 2008 ; Camas et al ., 2010 ). In total, 290 genes (14% of all genes) encoding proteins involved in sugar import and utilization are present, all but six of them being transcribed. 48 genes encode (ABC) transporters directly associated with sugar import, mostly unspecific, some specific for lactose and the monosaccharides arabinose, rhamnose, ribose, fructose and xylose (categories 2 – 9). Additionally, Table 2 shows that the bin actively transcribed genes representing seven glycoside hydrolase families with transcriptional categories between 2 and 6. Regarding the species’ fermentation end‐products, the transcriptional data strongly indicate the release of CO 2 , H 2 , acetate, ethanol and probably lactate. As shown in Table 3 , the key genes for the production of the latter three compounds show high transcriptional categories. Additionally, high transcriptional categories of the encoded ferredoxin‐reducing and CO 2 ‐producing pyruvate: ferredoxin oxidoreductase (see Table 3 ), ferredoxin (categories 4 and 9) and a bifurcating FeFe‐hydrogenase (category 10, Table 4 ) indicate hydrogen production from NADH and ferredoxin. According to Worm et al . ( 2014 ), the bifurcating FeFe‐hydrogenase belongs to those enzymes possibly involved in syntrophy, as summarized in Table 4 . Some other genes within this Table are actively transcribed by the analysed species, and among them, the majority of the Rnf complex subunit genes. They feature transcriptional categories between 8 and 10 and therefore belong to the most highly transcribed genes of this organism. It was proposed that the Rnf complex may play a crucial role in syntrophy (Worm et al ., 2014 ), and its high transcription rate indicates a possible syntrophic interaction of the studied species at the time of RNA extraction. However, as only a small number of putative syntrophy‐associated genes are transcribed, this conclusion cannot be drawn with certainty, but in the context of hydrogen production and the seemingly acetogenic lifestyle, it is a likely assumption. Summarizing, the metatranscriptome data mapping onto the Spirochaetes bin enabled in situ transcriptomic profiling of this so far unknown and uncharacterized species. Its metabolism seems to be mainly based on monosaccharides, but may also involve the degradation of some complex di‐ and polysaccharides. Transcriptional activities for associated genes also indicated acetate, ethanol, possibly lactate, CO 2 and H 2 as fermentation end‐products. A syntrophic association with methanogenic Archaea is presumed, due to the transcription of genes encoding proteins associated with syntrophy and hydrogen production, especially a bifurcating hydrogenase. The transcriptional profile of the Cloacimonetes bin indicates an amino acid fermentation‐based species In a previous study, the genome bin assigned to the phylum Cloacimonetes was analysed on the genetic level, concluding that it probably represents an amino acid‐fermenting, CO 2 and H 2 ‐producing bacterium, possibly syntrophically associated with methanogenic Archaea (Stolze et al ., 2016 ). Mapping of metatranscriptome sequencing data from the mesophilic BGP on the Cloacimonetes genome bin was supposed to give insights into the in situ transcriptomic activity of the corresponding species and enable the uncovering of its response to prevailing environmental conditions. Analyses of the 25 most highly transcribed genes, according to their TPM values, showed that 16 genes could be identified to encode proteins involved in mandatory bacterial functions like translation, chromosome structure maintenance, fatty acid metabolism and protein transport and protection (see Table S4 ). Interestingly, there are no other transcripts among them that encode proteins showing a certain response to the species’ environment or being involved in the genome bins’ postulated metabolism based on amino acids. However, Table 2 shows that five encoded glycoside hydrolases feature only low transcription categories except for those two predicted to be involved in cell wall degradation. Generally, the bin lacks genes encoding proteins for the utilization of sugars; the only exception is glucose degradation via the glycolysis pathway whose enzymes are completely encoded and feature transcriptional categories between 2 and 9. However, the transcriptional data clearly show that fermentation of the amino acids glutamate, lysine, alanine, asparagine, aspartate, cysteine and proline is preferred by the bacterium. Genes encoding proteins involved in their conversion into pyruvate were identified featuring transcriptional activity categories between 5 and 9. The end‐product of these pathways is most likely acetate, as all enzymes for its production are encoded and transcribed with categories between 5 and 8, while the other fermentation pathways are largely incomplete (Table 3 ). Interestingly, the studied species may have the potential to produce ethanol; however, no transcripts for the key enzyme, the alcohol dehydrogenase, were identified. This indicates that the Cloacimonetes species represents an acetogenic bacterium. However, other end‐products seem to be CO 2 and H 2 . Carbon dioxide is produced mainly via the conversion of pyruvate to acetyl‐CoA by the pyruvate:ferredoxin oxidoreductase (see Table 3 ), simultaneously reducing ferredoxin in the process. In addition to this, genes encoding the bifurcating FeFe‐hydrogenase using NADH and ferredoxin to produce hydrogen (Sieber et al ., 2012 ) are actively transcribed and show high TPM values (see Table 4 ). Also, a second Fe‐only hydrogenase (transcriptional categories 8 to 10) and its assembly protein (categories 3–6) are transcribed by the Cloacimonetes genome bin. Transcripts encoding ferredoxins were also found, with categories 5 and 10 (not shown). These findings strongly indicate the production of hydrogen via this thermodynamically unfavourable reaction. Additionally, it indicates that this species is likely to be syntrophically associated with hydrogenotrophic (or aceticlastic) Archaea . This is also supported by partially high transcriptional activities of genes encoding proteins presumably associated with syntrophy (Table 4 ). In summary, the metatranscriptome‐based profile of the Cloacimonetes bin showed that it actively ferments amino acids, producing acetate, H 2 and CO 2 in the process and is very likely associated with hydrogenotrophic and aceticlastic Archaea . The used methods of metatranscriptome sequencing and genome bin‐enabled transcriptional profiling therefore proved to be valuable tools for in situ characterization of unknown species and to deduce their role and importance within biogas‐producing communities."
} | 9,152 |
35210576 | PMC7612595 | pmc | 1,342 | {
"abstract": "Most trees on Earth forms a symbiosis with either arbuscular mycorrhizal or ectomycorrhizal fungi. By forming common mycorrhizal networks, actively modifying the soil environment, and other ecological mechanisms - these contrasting symbioses may generate positive feedbacks that favor their own mycorrhizal strategy (i.e. the con-mycorrhizal strategy) at the expense of the alternative strategy. Positive con-mycorrhizal feedbacks set the stage for alternative stable states of forests and their fungi, where the presence of different forest mycorrhizal strategies is determined not only by external environmental conditions but also mycorrhiza-mediated feedbacks embedded within the forest ecosystem. Here we test this hypothesis using thousands of U.S. forest inventory sites to show arbuscular and ectomycorrhizal tree recruitment and survival exhibit positive con-mycorrhizal density dependence. Data-driven simulations show these positive feedbacks are sufficient in magnitude to generate and maintain alternative stable states of the forest mycobiome. Given the links between forest mycorrhizal strategy and carbon sequestration potential, the presence of mycorrhizal-mediated alternative stable states affects how we forecast forest composition, carbon sequestration and terrestrial climate feedbacks.",
"introduction": "Introduction Most trees on Earth form belowground networks with symbiotic mycorrhizal fungi, which in turn can connect different tree stems and species within a forest \n 1 \n . Yet, the vast majority of tree species can only form one of two predominant functional types of mycorrhizal symbiosis, arbuscular mycorrhizal or ectomycorrhizal (AM or EM), each of which may set in motion processes that favor the establishment and persistence of one mycorrhizal network over the other. For example, common mycorrhizal networks may facilitate resource transfers which favor the recruitment and survival of their own mycorrhizal strategy (the con-mycorrhizal strategy) at the expense of the alternative strategy \n 2 – 5 \n . Furthermore, once established, AM and EM forests may engineer soil nutrient cycling conditions, further reinforcing positive con-mycorrhizal feedbacks to favor their own mycorrhizal strategy \n 6 – 9 \n . Additionally, establishment of either strategy can lead to an accumulation of con-mycorrhizal spores and mycelium, which may further strengthen positive feedbacks, as could potentially other yet to be discovered ecological phenomena. If such positive feedbacks exist across a wide range of forests they may, in time, generate alternative stable states of forested biomes, mediated by interactions between trees and the forest fungal microbiome \n 10 \n . As a result, forest mycorrhizal type may act as a filter on forest biodiversity, restricting community membership as a function of mycorrhizal compatibility, which may be further reinforced by soil nutrient cycle feedbacks, compatible symbiont density, and more. Given the links between forest mycorrhizal status and carbon sequestration potential \n 11 – 13 \n , the presence of mycorrhiza-mediated alternate stable states would affect how we forecast forest composition and emergent ecosystem carbon balance. The potential for positive feedbacks to drive alternative stable states in AM and EM symbioses at continental scale was originally hypothesized three decades ago, yet empirically testing this hypothesis at large spatial scale remains a challenge \n 14 \n . Recent work lends support to this idea, showing mixed mycorrhizal forests are far rarer than expected by chance \n 15 \n . While this co-occurrence pattern is consistent with the presence of alternative mycorrhizal stable states, there remain numerous other possible explanations for this pattern \n 16 \n , including environmental filtering and dispersal limitation \n 17 , 18 \n , which can also lead to the clumping of similar species \n 18 , 19 \n . Demonstrating that patterns in AM vs. EM forests reflect mycorrhizal-induced alternative stable states requires evidence that (i) bimodality exists in the frequency distribution of forest mycorrhizal types, (ii) positive community feedbacks in time could give rise to alternative stable states, and (iii) observed feedbacks are strong enough to generate and maintain alternative stable states in the face of environmental heterogeneity and demographic stochasticity \n 20 \n . Importantly, each of these criteria must consider and account for many potential non-linear controls of the environment on tree species’ demographic rates and spatial distributions, as well as signatures of dispersal limitation in recruitment dynamics \n 11 , 18 \n . These challenges have prevented previous work from disentangling the effects of mycorrhizal community feedbacks from environmental filtering and dispersal limitation. As a result, the generality of potential mycorrhizal feedbacks in shaping forest distributions at large spatial scales remains unknown.",
"discussion": "Discussion Researchers have long suspected that contrasting forest mycorrhizal strategies may generate feedbacks that reinforce the establishment and persistence of con-mycorrhizal strategies among trees \n 14 \n . However, only recently has sufficient data accrued to understand forest mycorrhizal composition and turnover at massive spatial scale, allowing us to empirically test this hypothesis. Here we show the distribution of AM vs. EM trees is bimodal across the Eastern US, likely maintained by strong positive recruitment and survival feedbacks within AM and EM forests, consistent with the presence of alternative mycorrhizal stable states. Our findings are consistent with foundational work on alternative ecosystem stable states of eastern hemlock (EM associated) and sugar maple (AM associated) forests in northern Michigan, U.S.A. \n 22 , 23 \n . Findings from this previous work are likely to be a specific example of a more general and widespread phenomenon. Given the prominent role of mycorrhizal fungi in shaping the biogeochemistry of their ecosystems \n 12 , 13 \n , it is unsurprising that mycorrhizal feedbacks extend across multiple tree species and larger spatial scales. Indeed, previous work on common mycorrhizal networks has shown positive associations between con-mycorrhizal, but not hetero-mycorrhizal tree species \n 2 , 4 , 5 \n . We hypothesize that both N-cycle feedbacks and common mycorrhizal networks within mycorrhizal types may act in concert to mediate positive feedbacks that generate and maintain alternative mycorrhizal stable states. We focus on the potential roles of common mycorrhizal networks and soil nutrient cycle feedbacks, as there is substantial empirical evidence from many different studies to support these positive feedback mechanisms \n 1 , 3 , 7 \n , yet other mechanisms remain plausible. For example, forests dominated by a particular mycorrhizal strategy may harbor a greater abundance of compatible mycorrhizal mutualists, or may be more likely to harbor exceptionally beneficial mutualists, both of which could also explain observed positive feedbacks, as could other yet-to-be discovered ecological phenomena. Regardless of the particular mechanism, the importance of positive con-mycorrhizal feedbacks demonstrated here calls for more intensive empirical study to decompose the relative importance of different positive feedback mechanisms that give rise to alternative mycorrhizal stable states. Identifying the dominant drivers will likely affect how we understand and manage these fundamentally different symbiont strategies. It is important to recognize that the presence of con-mycorrhizal feedbacks does not negate the role of environmental filtering in structuring the distribution of AM vs. EM forest symbioses at broad spatial scales \n 11 , 21 \n . In particular, climate is a strong predictor of AM vs. EM dominance within our study region \n 24 \n . However, within a continental-scale envelope of environmental conditions, prediction of AM vs. EM forests can only be made probabilistically, due to the presence of strong positive con-mycorrhizal feedbacks, which give rise to priority effects and alternative stable states \n 10 \n . This is analogous to how high vs. low rainfall is linked to the presence of savannah vs. forest, but, at intermediate rainfall, alternative stable states of forest vs. savannah emerge due to positive feedbacks linked to fire \n 25 \n . It is also likely that different environmental drivers modulate the strength of con-mycorrhizal feedbacks, which may further explain environmental dependencies, and should be a focus of future work. Nevertheless, our findings help provide mechanism behind sharp transitions in the spatial distribution of AM vs. EM ecosystem types observed at global scale \n 11 \n . Past analysis of the global distribution of mycorrhizal strategies reveals clear bimodality at the plot scale \n 15 \n , suggesting the feedbacks observed here may extend beyond North America, consistent with positive mycorrhizal feedbacks observed in this study and within forest plots outside of North America \n 2 , 26 \n . Our analysis has also lumped incredible taxonomic and functional diversity of both plants and fungi into AM vs. EM functional groups. We recognize different tree species and different mycorrhizal fungi have diverse and complex ecological strategies \n 14 \n and that these strategies may modify the strength of con-mycorrhizal density dependence and its environmental sensitivity ( Fig 2 ). We see exploring this diversity as the next frontier in understanding how the predominant form of tree mycorrhizal symbiosis shapes the biogeography and function of the forest macrosystem. Alternative stable states of terrestrial ecosystems have long been hypothesized but rarely demonstrated, in part because the empirical evidence needed is notoriously difficult to obtain at sufficient spatial and temporal scales \n 20 , 25 \n . This is particularly true for belowground microbial systems where it is exceptionally difficult to isolate the drivers of community change. Here we present multiple lines of evidence, each relying on independent analytical approaches, to provide strong inference for the presence of alternative mycorrhizal stable states within the temperate forests of eastern North America. These alternative stable states likely arise from a combination of divergent plant traits \n 27 \n , interactions between mycorrhizal fungi and free-living soil microbial communities at the molecular scale \n 28 , 29 \n , common mycorrhizal networks \n 2 , 4 , 5 \n , and potentially additional plant and microbial mechanisms. This combination of plant and microbial feedbacks then ripples through the ecosystem to affect the patterning of forest mycorrhizal symbioses across the continent. By highlighting how the soil microbiome shapes the functioning and responsiveness of entire forests, this work demonstrates the emerging importance of the forest microbiome for understanding the biogeography and function of the forest macrosystem. Given the striking differences in carbon cycling and storage between AM and EM-dominated systems \n 12 , 13 \n , the presence of alternative mycorrhizal stable states requires a rethinking of how forest composition and function vary across time and space, as well as the implications of these predictions for the global carbon cycle and in turn potential future states of the Earth."
} | 2,841 |
20520808 | PMC2877076 | pmc | 1,343 | {
"abstract": "Background With the recognition that environmental change resulting from anthropogenic activities is causing a global decline in biodiversity, much attention has been devoted to understanding how changes in biodiversity may alter levels of ecosystem functioning. Although environmental complexity has long been recognised as a major driving force in evolutionary processes, it has only recently been incorporated into biodiversity-ecosystem functioning investigations. Environmental complexity is expected to strengthen the positive effect of species richness on ecosystem functioning, mainly because it leads to stronger complementarity effects, such as resource partitioning and facilitative interactions among species when the number of available resource increases. Methodology/Principal Findings Here we implemented an experiment to test the combined effect of species richness and environmental complexity, more specifically, resource richness on ecosystem functioning over time. We show, using all possible combinations of species within a bacterial community consisting of six species, and all possible combinations of three substrates, that diversity-functioning (metabolic activity) relationships change over time from linear to saturated. This was probably caused by a combination of limited complementarity effects and negative interactions among competing species as the experiment progressed. Even though species richness and resource richness both enhanced ecosystem functioning, they did so independently from each other. Instead there were complex interactions between particular species and substrate combinations. Conclusions/Significance Our study shows clearly that both species richness and environmental complexity increase ecosystem functioning. The finding that there was no direct interaction between these two factors, but that instead rather complex interactions between combinations of certain species and resources underlie positive biodiversity ecosystem functioning relationships, suggests that detailed knowledge of how individual species interact with complex natural environments will be required in order to make reliable predictions about how altered levels of biodiversity will most likely affect ecosystem functioning.",
"introduction": "Introduction The ability of ecological systems to continue to deliver the ecosystem services on which human well-being ultimately depends is being increasingly compromised by anthropogenic endeavour, including pressures resulting from environmental change and invasion of exotic species [1] – [2] . Such pressures have also led to a rapid decline in biodiversity on a global scale, and gaining an understanding of the relationships between biodiversity and ecosystem functioning has been the primary objective of a substantial amount of literature over the last 10–15 years. Early experiments on plant communities showed declines in biomass production resulting from declines in species richness [3] – [4] , and triggered a large number of equivalent studies in other systems. When these data are integrated [5] – [7] , the relationships between biodiversity and ecosystem functioning (BEF) are mostly positive, but the most species-rich mixture tends to generate a level of functioning that is no different from that of the single most productive species used in an experiment [6] , suggesting that a limited number of species rather than diversity per se determine the shape of the curve [8] . However, studies investigating BEF relationships in the presence of abiotic and biotic external drivers [9] – [13] and their variation over time [14] are scarce. Determination of the quantitative relationships between species richness and levels of ecosystem functioning is severely inhibited by an inability to study communities in sufficient numbers and with the control, replication and realism required [15] . BEF experiments involving microbial communities offer great potential for addressing these issues, because they are relatively easily manipulated and conditions can be readily replicated in the laboratory. Moreover, given the overwhelming importance of bacterial assemblages and processes for ecosystem sustainability and overall functioning, and the desire to test the universality of BEF relationships observed in plant and animal communities, knowledge of BEF relationships for bacterial assemblages is urgently required. Recent studies investigating BEF relationships in bacteria [16] – [17] generally confirm the trend of a positive effect of species richness on ecosystem processes, but there is also evidence of saturation at low species richness levels when redundant, i.e. functionally equivalent species are present [18] , and negative sampling effects, where species with low contributions to ecosystem functioning dominate in species-rich communities [19] . Resource limitation can affect the behaviour and competitive ability of species, and environmental complexity in the form of multiple resources can sustain greater biodiversity by reducing interspecific competition through greater differentiation of resource use between species [20] . However, the interactive effects of environmental complexity and species diversity on ecosystem functioning have only recently been examined [12] , [21] – [23] . It can be hypothesised that ecosystem functioning increases with both higher species and resource richness due to stronger complementarity effects. Firstly, higher species and resource richness may reduce competition among species due to resource differentiation and, secondly, they may enhance facilitative interactions, such as cross-feeding on metabolic by-products among species. Previous studies have found evidence for [e.g. 22] and against [e.g. 24] stronger effects of increasing species richness on ecosystem functioning with increasing resource heterogeneity. Moreover, environmental heterogeneity may influence sampling effects that underpin positive BEF relationships. Resource heterogeneity may, for example, lower sampling effects by reducing the impact of a dominant species on ecosystem functioning when the presence of several resources leads to a reduction in competition. One can hypothesise that this in itself, if not counteracted or compensated by increasing complementary effects, may lead to a negative effect of resource richness on BEF relationships, unless the same species dominates irrespective of the degree of resource heterogeneity [24] . In our study we make use of the significant benefits that microorganisms offer as model systems to test and inform ecological theory [25] – [26] to examine whether interaction effects between bacterial species richness and environmental complexity (resource richness) determine levels of ecosystem functioning over time. We included all possible species combinations per species richness level (n = 6), six sampling times and all combinations within each resource richness level (n = 3, using glucose, xylose and galactose as substrates). The major emphasis of this study is to test how ecosystem functioning changes over time, depending on species richness and substrate richness, utilising a full experimental design incorporating all possible species and substrate combinations, whilst ensuring the validity of our findings by avoiding any undersampling biases related to missing species or substrate combinations. We hypothesise that substrate richness will enhance the positive effects of species richness on ecosystem functioning.",
"discussion": "Discussion Mechanisms underpinning bacterial diversity-ecosystem functioning relations A positive relationship was observed between species richness and metabolic activity. However, the form of this relationship changed with time, initially tending towards a linear relationship and, at later times, exhibiting saturation. Previous experiments linking bacterial diversity to decomposition have also found saturating relationships between diversity and functioning [18] – [19] . The underlying mechanisms were presumed to be complementarity in the first study [18] and negative sampling effects in the second [19] , where communities were dominated by a species that did not contribute strongly to decomposition. Generally, both complementarity and sampling effects have been proposed to explain positive diversity-functioning relationships [27] – [29] and the available data suggest that, in most cases, a combination of the two is likely to be operating [14] , [30] . Complementarity refers to increased resource utilisation through partitioning or positive interaction, whereas the sampling effect describes the influence of dominance by species with particular traits on ecosystem processes. In the latter case, the variation in dominance could result from changes in the densities of species (i.e. population dynamics) and/or differences in the rates at which species contribute to ecosystem functioning. The experimental design adopted here minimised changes in relative abundance of each species with time, but did not remove the potential for sampling effects through differences in metabolic rates among species, as substrates were utilised and end-products accumulated. Thus, in this experiment, we cannot rule out that these sampling effects could have masked complementarity effects. Non-transgressive overyielding was observed with all substrates at times later than 8 hours, but this extended to transgressive overyielding in far fewer cases. Hence, species mixtures tended to have higher yields than the average monoculture yield, but exceeded the maximum monoculture yield to a much lower extent. Similarly, Cardinale et al. [14] observed that plant communities tend to show non-transgressive but not transgressive overyielding and that both expressions of overyielding increase with time. The rare occurrence of transgressive overyielding suggests that true complementarity effects were not common in our experiment. Consequently, the saturation of functioning could have been caused by the lack of complementarity effects at higher species richness levels. Alternatively, negative interactions among competing species might explain the saturation. The system had a high level of functional redundancy, with all species able to utilise all supplied substrates and there was, therefore, presumably limited scope for positive complementarity effects, such as niche differentiation and facilitation. Thus, it seems more likely that negative interactions, due to increased competition between species for a limited amount and number of substrates in more diverse communities, could have led to saturation in levels of ecosystem functioning. This is supported by the hypothesis that strong niche differences between co-existing species are required for transgressive overyielding [31] . Interactive effects of resource heterogeneity and species diversity Environmental heterogeneity includes the richness of the available substrate pool. In bacterial populations, it has been shown that substrate diversity fosters diversification via adaptive radiation [32] – [33] , increases in specific growth rates of single bacterial strains [e.g. 34] and changes in composition and functioning of natural microbial communities [e.g. 35] . However, the interactive effects of substrate richness and species richness on EF are much less explored [but see 22] . Here, a positive relationship was observed with increasing substrate richness for both non-transgressive and transgressive overyielding as well as metabolic activity. A positive relationship may reflect a change in species behaviour between substrate richness levels, with species altering their pattern of resource uptake in relation to the number of resources available and other species that are present. Such mechanisms should lead to stronger complementarity effects with increasing resource richness and result in higher metabolic activity. It was therefore surprising that a significant interaction between species richness and substrate richness was not observed in any of the models. Hence, our hypothesis that substrate richness would enhance positive effects of species richness on ecosystem functioning must be rejected. Even though species richness and resource richness both enhanced metabolic activity, non-transgressive and transgressive overyielding, they did so independently from each other. One possible cause for the lack of an interaction between species and substrate richness might be, as already mentioned earlier, the presumably limited scope for complementarity due to the high levels of functional redundancy in our model system. Moreover, facilitative interactions due to, for example, cross-feeding, might have been of minor importance due to the nature of the supplied substrates, which were probably completely degraded and therefore unlikely to have produced metabolic by-products that could be utilised by other species. Instead of a direct interaction between species richness and substrate richness there were interactions between particular species and substrate combinations. This became apparent in the higher resolution model of transgressive overyielding that incorporated substrate composition as an independent variable, as it contained the significant 2-way interaction, species richness × substrate composition. Also the model of metabolic activity incorporating species composition contained the significant 3-way interaction term, species composition × substrate richness × time. Our results therefore suggest that the pattern of resource availability will be an important component in determining BEF relationships, but that the particular characteristics of the species and resources available are more important than the mere number of both. This further suggests that the effect of habitat changes in conjunction with species extinction on functioning will be difficult to predict, and general patterns within this interaction elusive. Other studies with a focus on microbial communities have also investigated the effect of resource heterogeneity on BEF relationships. Replansky and Bell [22] , in a long-term experiment, showed that both environmental complexity (i.e. the number of carbon substrates) and species richness tended to increase productivity of yeast communities, and that overyielding was mostly caused by resource partitioning. Tiunov and Scheu [36] investigated the effect of fungal species richness on decomposition and found stronger complementarity effects in less complex environments, where facilitative interactions between species, such as cross-feeding, were more prominent. Weis et al. [24] , on the contrary, found that environmental heterogeneity did not have positive effects on BEF relationship in algal communities. However, a single species dominated in both homogeneous and heterogeneous environments in their experiment, hence, limiting the scope for complementarity effects. Thus, even though the overall effect and underlying mechanisms differ between different studies, probably depending on the overall heterogeneity in the studied system as well as whether specialists or generalists are competing for the available resources [37] – [38] , the results of experiments carried out with microbial communities confirm the importance of habitat complexity reported elsewhere with larger organisms [e.g. 21] , [39] – [41] . In summary, the experimental system here demonstrates that habitat complexity in the form of resource richness can be a significant modifying force of the BEF relationship. Predicting and managing changes in ecosystem functioning resulting from declining biodiversity is likely to require an extensive knowledge of these complex interactions, and as such, resource complexity must form a major component of future research into the relationship between biodiversity and ecosystem functioning."
} | 3,975 |
36037344 | PMC9457591 | pmc | 1,345 | {
"abstract": "Significance Interactions between species in nature can vary in strength and direction and may be driven by environmental variation. We use kelp forests as an example to show how varying species-interaction strengths, estimated directly from time-series data on species abundances, can be related to low-frequency variation in environmental drivers. Our approach has relevance to the study of species interactions in other ecological systems where environmental and monitoring data exist, but experimental studies of species interactions are infeasible.",
"discussion": "Discussion Ecosystem dynamics are composed of nonlinear species relationships, played out within shifting environmental contexts. A significant challenge in the study of ecosystem dynamics has been the difficulty in appropriately extrapolating experimental results to real ecosystems, where multiple species–species and species–environment interactions are operating simultaneously. We have used this study to illustrate how EDM, in combination with rich time-series ecosystem data, can help to tackle this challenge. Long-term time-series data are not uncommon for many ecosystems and locations. As illustrated here, such monitoring data therefore provide platforms for identifying inferred causal interaction networks and investigating the influence of large-scale environmental drivers on interaction strengths using existing datasets, rather than requiring long-term experiments in the future. In this particular ecosystem, our analyses of time-series data confirmed many results from previous experimental work regarding the foundation species M. pyrifera . Perhaps more importantly, they also revealed patterns of substantial variability in multiple species-interaction strengths related to variation in underlying environmental conditions that were previously unobserved. The accumulated evidence suggests that in the San Nicolas kelp forest, environmental context drives positive-feedback loops in species interactions that maintain ecosystem states. Consider the effects of the NPGO on the interactions between Macrocystis , Pterygophora , and Laminaria ( Figs. 4 and 5 ). Lower values of the NPGO index in the study area are associated with lower nutrient availability and reduced upwelling ( 36 ). In this nutrient-stressed context, apparent facilitation between the algae species is common, and the ability of Macrocystis to compete with the understory species declines. Furthermore, there can be strong negative intraspecies and interspecies effects on Macrocystis recruitment during low NPGO phases. This creates a self-reinforcing loop that suppresses Macrocystis abundance and promotes Pterygophora and Laminaria . Even under low herbivory pressure on Macrocystis , this positive feedback remains. The implication is that under nutrient-stressed conditions, Laminaria and Pterygophora should be favored over Macrocystis in competition, a result consistent with previous findings in other kelp forests ( 49 ). Importantly, because of the positive feedback, this ecosystem state—an understory forest instead of a Macrocystis forest—should be stable as long as the environmental context does not substantially change ( 46 ). Alternatively, under elevated NPGO values, the nature of competition shifts among the kelp species. Pterygophora ’s effect on Laminaria and adult Macrocystis becomes more competitive, but Pterygophora ’s ability to suppress Macrocystis recruitment is reduced. These conditions create an opportunity for successful Macrocystis recruitment and the potential establishment of a kelp forest replete with both canopy-forming and understory kelp species. Considered in a dynamic framework, then, the ultimate outcome of elevated nutrient availability for kelp-forest relative species abundances will depend on priority effects. Negative interactions between some algal species means that whichever species is able to establish first in such a situation should be able to continue to dominate. We have shown how environmental context underpins the strength of species interactions that, in turn, drive ecosystem dynamics. The effects of large-scale environmental signals like the NPGO and PDO are clearly related to the strength of species interactions in the San Nicolas kelp forest. Moreover, the relationship of algal species interactions to increased herbivory pressure ( SI Appendix , Fig. S8 ) suggests that herbivory may reinforce or stabilize existing ecosystem states, rather than driving ecosystem change. This finding echoes other early ( 46 ) and recent ( 47 ) work done at San Nicolas Island, showing that nutrient regimes and available drift algae drive sea urchin feeding behavior, rather than herbivory driving kelp dynamics directly. Overall, we found that environmental context determines the balance of facilitation and competition and conclude that changes in environmental forcing can alter the likelihood of ecosystem state change. Therefore, we argue [in agreement with others ( 34 – 37 , 69 )] that bottom-up control is particularly important in driving kelp-forest ecosystem dynamics in southern California. One important implication of our study is that if a research goal is to understand the dynamics of entire ecosystems, studying solely the mean outcome of single-species interactions may be highly misleading. We showed how varying species interactions in the San Nicolas kelp forest are key to a deep understanding of ecosystem dynamics. In kelp forests and other ecosystems, indirect associations between multiple species and shifting environmental contexts may give rise to rare, critical moments when fleetingly strong interactions determine ecosystem shifts. Rather than being viewed as purely stochastic events, our results suggest that we may be able to understand and perhaps predict the likelihood of these events through monitoring of large-scale environmental fluctuations and current ecosystem states. This idea needs further investigation in multiple systems, but if widely applicable, it means that context dependency—and its role in mediating varying species-interaction strengths—deserves more attention than the identification of mean species-interaction strengths ( 9 ). Furthermore, it is the confluence of multiple species interactions that determines overall ecosystem dynamics, and no one interaction can necessarily be considered in isolation. It is clear from our results that when environmental context changes, the entire balance of species interactions changes as well, potentially precipitating ecosystem shifts or triggering the types of positive-feedback loops described above. This is likely the case in every ecosystem. A lesson from those findings, then, is that when investigating ecosystem shifts, it may be misleading to focus too intently on single interactions that are determined to be important a priori, without a careful analysis of how and why other interaction links may be changing concurrently. We began in this study with a complex set of dynamics observed directly in long-term monitoring data. From those data, we established causation, built interaction networks, and investigated the influence of large-scale environmental drivers on species-interaction strengths. As a result, we were able to better understand why ecosystem shifts occurred, in relation to the environmental context at the time of those shifts. There is rich dynamic information contained in seemingly simple records of species densities over time, information that can and should be uncovered in ecosystems with existing long-term monitoring data to advance our understanding of key species, interactions, and environmental drivers. Our study and others using EDM state-space reconstruction do not take the place of experimentation. Appropriate application of EDM requires relatively lengthy time series, which may not be available in many ecosystems. The San Nicolas Island dataset includes more than 30 y of data, a time-series length that could be considered a luxury in many systems. Moreover, there are detailed biological and ecological mechanisms and fine spatial- and temporal-scale dynamics that we cannot capture solely from such data analytics. That being said, the reverse is also true—even the most rigorous field experiments of ecosystem dynamics can be compromised by context dependencies, like we observed in this system. Multivariate EDM can help to both contextualize and guide insights from short-term experiments. Our analyses are a proof of concept: We started with time-series data from a monitoring dataset in a well-studied, but complex, ecosystem and showed how previous experimental results play out over a longer time period in a variable environment. The consistency of our findings with other kelp-forest studies and ecological theories, such as the Stress Gradient Hypothesis, argues for the potential of this approach to provide credible insights into other ecosystems, where time-series data exist, but where important interactions may not be nearly as well-established. Where important interactions are known, EDM can help to explore whether environmental context matters in interaction variance. Where ecosystem interactions are not as well-known, EDM may be a helpful first step in identification of ecosystem links, whose mechanisms can then be further established through other experimental and observational methods."
} | 2,356 |
35149841 | null | s2 | 1,346 | {
"abstract": "Historically, appreciation for the roles of resource gradients in biology has fluctuated inversely to the popularity of genetic mechanisms. Nevertheless, in microbiology specifically, widespread recognition of the multicellular lifestyle has recently brought new emphasis to the importance of resource gradients. Most microorganisms grow in assemblages such as biofilms or spatially constrained communities with gradients that influence, and are influenced by, metabolism. In this Review, we discuss examples of gradient formation and physiological differentiation in microbial assemblages growing in diverse settings. We highlight consequences of physiological heterogeneity in microbial assemblages, including division of labour and increased resistance to stress. Our impressions of microbial behaviour in various ecosystems are not complete without complementary maps of the chemical and physical geographies that influence cellular activities. A holistic view, incorporating these geographies and the genetically encoded functions that operate within them, will be essential for understanding microbial assemblages in their many roles and potential applications."
} | 291 |
35149841 | null | s2 | 1,347 | {
"abstract": "Historically, appreciation for the roles of resource gradients in biology has fluctuated inversely to the popularity of genetic mechanisms. Nevertheless, in microbiology specifically, widespread recognition of the multicellular lifestyle has recently brought new emphasis to the importance of resource gradients. Most microorganisms grow in assemblages such as biofilms or spatially constrained communities with gradients that influence, and are influenced by, metabolism. In this Review, we discuss examples of gradient formation and physiological differentiation in microbial assemblages growing in diverse settings. We highlight consequences of physiological heterogeneity in microbial assemblages, including division of labour and increased resistance to stress. Our impressions of microbial behaviour in various ecosystems are not complete without complementary maps of the chemical and physical geographies that influence cellular activities. A holistic view, incorporating these geographies and the genetically encoded functions that operate within them, will be essential for understanding microbial assemblages in their many roles and potential applications."
} | 291 |
38063708 | PMC10708255 | pmc | 1,348 | {
"abstract": "As artificial synapse devices, memristors have attracted widespread attention in the field of neuromorphic computing. In this paper, Al/polymethyl methacrylate (PMMA)/egg albumen (EA)–graphene quantum dots (GQDs)/PMMA/indium tin oxide (ITO) electrically/optically tunable biomemristors were fabricated using the egg protein as a dielectric layer. The electrons in the GQDs were injected from the quantum dots into the dielectric layer or into the adjacent quantum dots under the excitation of light, and the EA–GQDs dielectric layer formed a pathway composed of GQDs for electronic transmission. The device successfully performed nine brain synaptic functions: excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), short-term potentiation (STP), short-term depression (STD), the transition from short-term plasticity to long-term plasticity, spike-timing-dependent plasticity (STDP), spike-rate-dependent plasticity (SRDP), the process of learning, forgetting, and relearning, and Pavlov associative memory under UV light stimulation. The successful simulation of the synaptic behavior of this device provides the possibility for biomaterials to realize neuromorphic computing.",
"conclusion": "4. Conclusions In this paper, Al/PMMA/EA–GQDs/PMMA/ITO biomemristors were fabricated using egg protein as a dielectric layer. The PMMA was added to the upper and lower sides of the EA dielectric layer as an insulating layer, and the GQDs were doped in the EA resistive layer to increase the light-sensitive properties of the device. The electrons in the GQDs were injected from the quantum dots into the dielectric layer or into the adjacent quantum dots under the excitation of light. The EA–GQDs dielectric layer formed a pathway composed of GQDs, and electrons were transported on this pathway. After testing, it could be seen that the device has good electrical characteristics. The device successfully simulates the following synaptic functions: EPSC, PPF, STP, STD, the transformation of short-term plasticity to long-term plasticity, STDP, SRDP, the process of learning, forgetting, and relearning, and Pavlov associative memory under UV light stimulation. The results show that the Al/PMMA/EA–GQDs/PMMA/ITO memristor has a strong potential for simulating biological synapses, which is of great significance to the development of neuromorphic computing systems.",
"introduction": "1. Introduction Different from the traditional von Neumann computer architecture, neuromorphic computing, as a new type of computer system, has the advantages of a low power consumption, a high efficiency, and a high fault tolerance. Because it solves the problem of expensive data transfer between the processor and the memory, it has become a hot area worthy of in-depth study [ 1 , 2 , 3 , 4 , 5 ]. As an emerging nonvolatile device, the memristor changes its own resistance through the stimulation of the external voltage, similarly to a biological synapse, simulating the change in synaptic weight in a biological synapse. It is considered an ideal device for studying neuromorphic computing [ 6 , 7 , 8 ]. The low power consumption, scalability, high density, and nonvolatility of memristors facilitate the realization of synaptic behaviors in biological neurons [ 9 , 10 , 11 ], which are capable of performing, learning, memory, and other complex neural behaviors [ 12 , 13 , 14 , 15 ], making them a key element in neuromorphic computing research. Previous memristor research achieved a variety of synaptic behaviors, such as short-term plasticity, excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), long-term plasticity (STP), spike-rate-dependent plasticity (SRDP), and pulse-time-dependent plasticity (STDP) [ 16 , 17 , 18 , 19 , 20 ]. In an effort to find suitable materials for fabricating artificial synapses, a wide variety of materials have come into the field of researchers, such as metal oxide materials [ 21 ], inorganic materials [ 22 , 23 ], chalcogenides [ 24 ], perovskites [ 25 , 26 , 27 , 28 , 29 ], and 2D materials [ 30 , 31 ]. Most of the materials reported in the literature are complex to prepare and incompatible with organisms [ 32 , 33 , 34 ], making them difficult to use due to a lack of environmentally friendly disposal methods and for posing potential threats to the environment. Therefore, to produce biocompatible devices at a low cost, new materials must meet these requirements, using readily available natural compounds. Organic materials are widely used in the preparation and research of resistive switching layers due to their low cost and nonpolluting environment [ 35 , 36 , 37 ]. Memristors made of natural biomaterials are widely used in wearable, compatible, and environmentally friendly smart electronic devices; among these materials are lignin [ 38 ], pectin [ 39 ], chitosan [ 40 ], and anthocyanins [ 41 ], which have been used as the memristors’ active layer of a device. In addition, protein materials are also widely used in artificial synapse devices because of their good biocompatibility, degradability, specificity, and ease of processing. By regulating the synthesis process of protein materials or modifying them after synthesis, their structure and properties can be adjusted. As a protein material, egg albumen has good degradability and biocompatibility and can be absorbed by the human body. Moreover, egg albumen is a protein material with variable electrical conductivity, which is similar to the neuroplasticity of biological synapses and can simulate the synaptic connections between biological neurons. Therefore, egg albumen has been used as an active or dielectric layer in fabricating high-performance resistive switching devices [ 36 ] and thin-film transistors [ 34 ]. However, in-depth research on biomaterial-related synaptic bionics and neuromorphic computing remains incomplete. Biomemristors have been extensively studied recently. Yan et al. used EA as an active layer to prepare a flexible W/EA/ITO/PET device, which can shift from paired pulse facilitation to paired pulse depression by changing the amplitude of the pulse voltage [ 42 ]. Zhou et al. prepared a superflexible protein paper substrate with good physical flexibility and excellent electrical properties, and, through a simple thermochemical reaction, they prepared an Au/EA/Au memristor, which still showed bipolar I-V characteristics in the bending state and type-switching behavior [ 43 ]. Sung et al. prepared Al/EA–GQD/ITO biomimetic synapse devices based on a hybrid nanocomposite of egg albumin (EA) and graphene quantum dots (GQDs). The I-V characteristics of the device exhibited clockwise hysteresis behavior under continuous positive and negative voltage scans [ 44 ]. Ghosh et al. used aloe vera flower extract as the active layer to create a biomemristor. Their device can achieve a high current-switching ratio and stable cyclability and exhibits two different extraction solutions in the preparation state and in the chemical reduction state [ 45 ]. Sun et al. embedded graphene into anthocyanins to make memristors and manipulated the I-V properties through the protonation of graphene to produce a self-selected memristor effect [ 41 ]. Saha et al. synthesized water-soluble sodium caseinate (NaCas), using the natural casein extracted from edible animal milk, and used it to prepare an Al/NaCas/ITO biomemristor. The device showed a large switching-current ratio, a long retention time, and a stable cycle durability [ 46 ]. It is worth studying the use of biological memristors to further realize artificial synapses and artificial neurons [ 47 , 48 , 49 , 50 ]. Polymethyl methacrylate (PMMA) easily forms a film due to its high transmittance and is often used as an insulating layer in organic thin-film transistors. Graphene quantum dots (GQDs), as a new type of quantum dot, have a good biocompatibility, a low cytotoxicity, and photoluminescence properties, making them very suitable as dopants for biological materials. In this paper, Al/PMMA/egg albumen (EA)–GQDs/PMMA/indium tin oxide (ITO) biomemristors were fabricated using the egg protein as a dielectric layer. The PMMA was added as an insulating layer on both sides of the EA dielectric layer, and the GQDs were doped to increase the light-sensitive properties of the device. The electrons in the GQDs were injected from the quantum dots into the dielectric layer or into the adjacent quantum dots under optical excitation; a pathway composed of GQDs was formed in the EA–GQDs dielectric layer, and electrons were transmitted on this pathway. The device successfully performed nine brain synaptic functions: excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), short-term potentiation (STP), short-term depression (STD), the transition from short-term plasticity to long-term plasticity, spike-timing-dependent plasticity (STDP), spike-rate-dependent plasticity (SRDP), the process of learning, forgetting, and relearning, and Pavlov associative memory under UV light stimulation. The successful simulation of the synaptic behavior of this device provides the possibility for biomaterials to realize neuromorphic computing."
} | 2,291 |
36181435 | PMC9585477 | pmc | 1,349 | {
"abstract": "Abstract Thermoprofundales, formerly Marine Benthic Group D (MBG-D), is a ubiquitous archaeal lineage found in sedimentary environments worldwide. However, its taxonomic classification, metabolic pathways, and evolutionary history are largely unexplored because of its uncultivability and limited number of sequenced genomes. In this study, phylogenomic analysis and average amino acid identity values of a collection of 146 Thermoprofundales genomes revealed five Thermoprofundales subgroups (A–E) with distinct habitat preferences. Most of the microorganisms from Subgroups B and D were thermophiles inhabiting hydrothermal vents and hot spring sediments, whereas those from Subgroup E were adapted to surface environments where sunlight is available. H 2 production may be featured in Thermoprofundales as evidenced by a gene cluster encoding the ancient membrane-bound hydrogenase (MBH) complex. Interestingly, a unique structure separating the MBH gene cluster into two modular units was observed exclusively in the genomes of Subgroup E, which included a peripheral arm encoding the [NiFe] hydrogenase domain and a membrane arm encoding the Na + /H + antiporter domain. These two modular structures were confirmed to function independently by detecting the H 2 -evolving activity in vitro and salt tolerance to 0.2 M NaCl in vivo, respectively. The peripheral arm of Subgroup E resembles the proposed common ancestral respiratory complex of modern respiratory systems, which plays a key role in the early evolution of life. In addition, molecular dating analysis revealed that Thermoprofundales is an early emerging archaeal lineage among the extant MBH-containing microorganisms, indicating new insights into the evolution of this ubiquitous archaea lineage.",
"conclusion": "Conclusion Our study provides a comprehensive insight into the abundant and widespread sedimentary archaeal group Thermoprofundales, and it expands the knowledge of Thermoprofundales’ diversity, evolution, and ecological roles in global biogeochemical cycles. The genomic evolution of Thermoprofundales is driven by HGT events, of which ∼70.5% are derived from other distantly related archaeal lineages. Thermoprofundales possesses a separated two modular gene structure of MBH with high similarity to the ARC system, and the two modules were confirmed to be functionally independent and active. Our findings uncover an unprecedented role of Thermoprofundales as an H 2 producer in global sedimentary environments, and Thermoprofundales may fuel other H 2 consumers and facilitate extensive microbe-microbe interactions in the community.",
"introduction": "Introduction Archaeal cells are abundant and widespread in diverse habitats on Earth (∼1.1 × 10 29 cells), where they are estimated to constitute 37% and 87% of all prokaryotes in the global ocean and deep subsurface marine sediments, respectively ( Lipp et al. 2008 ; Hoshino and Inagaki 2019 ). However, our understanding of the mechanisms underlying archaeal life is still limited when compared with that of other microorganisms ( Baker et al. 2020 ). With the rapid expansion of high-quality archaeal genomes from pure isolates, metagenome-assembled genomes (MAGs) and single-cell amplified genomes (SAGs), the archaeal tree of life has expanded dramatically to at least 30 archaeal phyla ( Tahon et al. 2021 ). Thermoprofundales is an archaeal order within the class Thermoplasmata, which is formerly known as MBG-D (Marine Benthic Group D) ( Vetriani et al. 1999 ), DHVEG-1 (Deep-sea Hydrothermal Vent Euryarchaeota Group 1) ( Takai and Horikoshi 1999 ), or Izemarchaea ( Adam et al. 2017 ). Multiple studies based on 16S rRNA gene sequencing indicate that Thermoprofundales is an abundant and cosmopolitan lineage widely distributed in sedimentary habitats. Approximately 70% of the available Thermoprofundales sequences were identified in samples collected from mangrove surface sediments, open ocean, and hydrothermal vents ( Zhou et al. 2018 ), and Thermoprofundales often contributes more than 10% to total archaeal sequences in the community ( Lloyd et al. 2013 ). This lineage is also able to adapt to distinct environmental conditions, including the tolerance of extreme ranges in salinity (freshwater vs. hypersaline) and temperature (polar vs. hydrothermal) ( Swan et al. 2010 ; Zhou et al. 2018 ). Lokiarchaeota, Hadesarchaea, and anaerobic methanotrophic archaea (ANME) commonly co-occur with Thermoprofundales, suggesting the existence of syntrophic interactions or similar selective pressures in a yet unknown manner ( Inagaki et al. 2006 ; Zhou et al. 2018 ). Recently, the sequencing of some Thermoprofundales MAGs and SAGs provided preliminary insights into the metabolic features of these microorganisms. They encode a large number of genes for extracellular peptidases, such as gingipain, clostripain, and collagenase, which are common and active in the sediments from Aarhus Bay (Denmark) ( Lloyd et al. 2013 ), White Oak River estuary (USA) ( Lazar et al. 2017 ), and Shenzhen Futian mangrove (China) ( Zhou et al. 2018 ). Moreover, acetate and ethanol might be produced by Thermoprofundales through anaerobic fermentation processes ( Lazar et al. 2017 ; Zhou et al. 2018 ). Given the ubiquity and predominance of Thermoprofundales in sedimentary environments, it has been proposed that this archaeal lineage contributes significantly to global carbon cycles ( Lloyd et al. 2013 ; Zhou et al. 2018 ). However, Thermoprofundales remains one of the least studied archaeal groups, because of the limited number of sequenced genomes and the lack of pure/enriched cultures. Here, we aim to reveal the phylogenetic diversity, metabolic features, and evolutionary history of Thermoprofundales through the metagenomic mining of 146 genomes obtained in this study or retrieved from public databases. Our analyses included the identification of five monophyletic Thermoprofundales lineages, which inhabit distinct environments and possess versatile metabolic pathways. The evolutionary history of Thermoprofundales was brought to light by mapping events of horizontal gene transfer (HGT) and gene gain and loss at its ancestral node. A unique gene cluster encoding the membrane-bound hydrogenase (MBH) complex stood out as an ancient trait, because the MBH is among the 62 core proteins in the anaerobic prokaryote common ancestor and it represents the simplest form of respiration in extant organisms ( Sousa et al. 2016 ; Yu et al. 2018 ). The hydrogenase activity of the large subunit protein of the MBH gene cluster was confirmed by measuring H 2 production in vitro. Our findings substantially expand understanding of the metabolism and evolution of the cosmopolitan sedimentary archaea Thermoprofundales.",
"discussion": "Results and Discussion An Abundant Archaeal Lineage in Sedimentary Environments Worldwide A total of 146 Thermoprofundales genomes (>50% completeness and <5% contamination) were retrieved from metagenomes and single cells sequenced in this study (55 MAGs), and downloaded from the NCBI Assembly database (53 MAGs and 2 SAGs) ( Coordinators 2018 ) and the genomic catalog of Earth’s microbiomes (36 MAGs) ( Nayfach et al. 2020 ). A total of 63 genomes are more than 80% complete ( supplementary table S1, Supplementary Material online). The phylogenomic tree based on 55 conserved single-copy ubiquitous archaeal genes ( Dombrowski et al. 2020 ) showed that Thermoprofundales forms a monophyletic lineage in the Candidatus phylum Thermoplasmatota and its ancestral node is adjacent to the orders Methanomassiliicoccales, Thermoplasmatales, Acidiprofundales, Poseidoniales, and MGIII ( fig. 1 ) ( Rinke et al. 2021 ). The average amino acid identity (AAI) value between each genome in Thermoprofundales and that from its adjacent orders was <50% ( supplementary fig. S1 and table S2, Supplementary Material online), confirming that Thermoprofundales is an order-level lineage ( Zhou et al. 2018 ) according to the proposed standards for high-quality taxa descriptions of uncultivated microorganisms ( Konstantinidis et al. 2017 ; Rinke et al. 2021 ). Fig. 1. Phylogenomic tree of 146 Thermoprofundales genomes. Different colors covering the tree branches indicate the five Thermoprofundales subgroups. The filled or hollow star at each genome ID indicates the full or partial MBH subunit genes, respectively. The colors of the inner ring indicate the availability of light. The colors of the middle ring indicate the temperature range. The colors of the outer ring indicate the environmental source of each genome. Ultrafast bootstrapping was used to estimate the reliability of each branch with 1,000 times resampling, and the nodes with a bootstrap value >80 are marked with black dots. Global distribution analysis as revealed by the 16S rRNA genes and MAGs both showed that Thermoprofundales is distributed in various sedimentary environments with wide temperature and salinity ranges ( supplementary fig. S2, Supplementary Material online), presumably contributing to global carbon biogeochemical cycles as reported previously ( Lloyd et al. 2013 ; Zhou et al. 2018 ). Based on the 16S rRNA gene, the relative abundances of Thermoprofundales were 0.1–6.3% in freshwater sediment, 0.3–8.6% in saline lake sediment, 0.1–17.1% in intertidal sediment, and 0.1–4.3% in marine sediment, which was consistent with those based on the MAGs abundance ( supplementary table S3, Supplementary Material online). The highest relative abundances of Thermoprofundales as revealed by 16S rRNA genes and MAGs were found in sedimentary environments, such as an intertidal sediment from the southern coast of the United States (17.1%) and a hydrothermal sediment from the Guaymas Basin in the Gulf of California (24.5%), respectively. When compared with the upper water column which is dominated by free-living microorganisms, sedimentary habitats generally have low dissolved oxygen levels and high organic matter content, where abundant anaerobic heterotrophs adopt nonmotile or particle-attached lifestyles ( Orcutt et al. 2011 ; Zhou et al. 2018 ). Five Subgroups with Distinct Habitat Preferences and Metabolic Features The Thermoprofundales MAGs were classified into five subgroups according to their phylogenetic positions ( fig. 1 ) and AAI values ( supplementary fig. S1, Supplementary Material online), whose average values between each pair of genomes in the same subgroup were higher than 63.0% ( supplementary table S2, Supplementary Material online). Genomes from Subgroups B, D, and E showed distinct habitat preferences ( fig. 1 ). For example, 76.0% and 100% of the genomes from Subgroup B and Subgroup D were identified in sediments from deep-sea hydrothermal vents, which are characterized by extremely high temperatures for microorganisms (e.g., >60 °C) ( Dombrowski et al. 2018 ). This is further supported by the identification of a reverse gyrase gene (the hallmark gene of some hyperthermophiles and/or moderate thermophiles ( Campbell et al. 2009 ; Lipscomb et al. 2017 ; Feng et al. 2019 )) exclusively in genomes of the Subgroups B and D ( supplementary fig. S3 and table S4, Supplementary Material online). Therefore, these two subgroups seem to comprise thermophiles, and the result is consistent with a recent report in which Subgroups B and D were assigned as JdFR-43 and HyVt, respectively ( Liu et al. 2022 ). However, the preferred habitats for Subgroups A and C were not revealed because of the underrepresentation of genomes in these two subgroups (two for Subgroup A and one for Subgroup C) ( fig. 1 ). A survey combining the 16S rRNA gene sequences identified in the MAGs of this study with those from a previous report ( Zhou et al. 2018 ) showed that the sequences of Subgroup E clustered in a monophyletic lineage, which included clades from 1 to 11 as classified previously ( Zhou et al. 2018 ) ( supplementary fig. S4, Supplementary Material online). The lineage of Subgroup E had the highest diversity among the five subgroups based on the MAGs. A high percentage (84.2%) of the MAGs were obtained from terrestrial or marine surface environments (e.g., freshwater river, intertidal zone, shrimp pond, saline lake, and seawater), which are characterized by high sunlight incidence and mild temperatures (15–40 °C) ( fig. 1 ; supplementary table S1, Supplementary Material online). Interestingly, a gene encoding the light-sensing heliorhodopsin was identified exclusively in Subgroup E ( supplementary fig. S5, Supplementary Material online). However, phototrophy might not be supported in Thermoprofundales because heliorhodopsin has not yet to be confirmed to display proton-pumping activity ( Pushkarev et al. 2018 ), and the genomes of Thermoprofundales lack the key genes for photosynthesis ( PsaAB and PsbAD ). Nevertheless, the heliorhodopsin gene in Thermoprofundales was always accompanied by several protein-encoding genes involved in carotenoid biosynthesis ( CrtZ , CrtB , CrtD , CruA , and CrtU ) and repair of DNA damage caused by light-induced oxidative stress ( PhrB and UvsE ) ( Meulenbroek et al. 2013 ; Zhang et al. 2017 ) in the same gene cluster ( supplementary fig. S6, Supplementary Material online). Carotenoid production occurs often in phototrophic microorganisms, such as photosynthetic bacteria (e.g., Arthrospira , Rhodobacter , and Rhodosporidium ), extremely halophilic archaea (Halobacteria), microalgae, and some yeast ( Mussagy et al. 2019 ). In Subgroup E, some genomes possess complete gene sets for the de novo biosynthesis of bacterioruberin and zeaxanthin ( fig. 2 ), and key genes such as bisanhydrobacterioruberin hydratase ( CruF ) and beta-carotene 3-hydroxylase ( CrtZ ) were first detected in the Candidatus phylum Thermoplasmatota ( Rinke et al. 2021 ) ( supplementary figs. S7 and S8, Supplementary Material online). Carotenoids produced by these pathways might act as antioxidants and protect cells against oxidative damage, such as that resulting from exposure to sunlight, UV radiation, and/or H 2 O 2 ( Giani et al. 2019 ). Due to the adjacent gene arrangement among heliorhodopsin, carotenoid biosynthesis, and DNA damage repair, we speculate that the heliorhodopsin in Subgroup E functions as a light sensor to mitigate light-induced oxidative stress, probably by regulating the expression of genes for carotenoid biosynthesis and light-induced DNA damage repair ( Pushkarev et al. 2018 ; Bulzu et al. 2021 ). Fig. 2. Reconstructed metabolic pathways of Thermoprofundales. A full list of genes labeled with different letters is provided in supplementary table S4, Supplementary Material online. Evolutionary History of Thermoprofundales To shed light on the evolutionary history of Thermoprofundales, gene gain and loss events were predicted by mapping all the orthologous genes found in high-quality genomes (>80% completeness and <5% contamination) to a phylogenomic tree. In general, 132 and 29 genes were gained and lost at the ancestral node of Thermoprofundales, respectively (Node 1 in fig. 3 ). For example, multiple genes involved in protein degradation were gained at this node ( supplementary table S5, Supplementary Material online), making Thermoprofundales an important protein degrader in global sedimentary environments ( Lloyd et al. 2013 ; Lazar et al. 2017 ; Zhou et al. 2018 ). Two genes related to survival in fluctuating environmental conditions were gained: a gene for cold shock protein CspA and a gene for glucosylglycerate synthase (GGS). These two genes might help Thermoprofundales to cope with multiple stressful conditions, such as harsh temperatures, osmotic pressure, oxidative stress, starvation, and pH extremes ( Keto-Timonen et al. 2016 ; Nunes-Costa et al. 2017 ). Of note, the evolution of Subgroup E genomes had unique features when compared with other subgroups (104 gains and 43 losses; Node 2 in fig. 3 ). Among the 104 gained genes at the ancestral node of Subgroup E, a heliorhodopsin gene and two genes involved in chlorophyll synthesis ( BchE and BchG ) possibly facilitate the utilization of sunlight ( supplementary table S6, Supplementary Material online). Meanwhile, four DNA repair genes ( UvrABC and XthA ), which might participate in the removal of damaged bases caused by strong sunlight ( Verhoeven et al. 2002 ), were also gained at Node 2. This suggests that microorganisms in Subgroup E evolved strategies to both use light energy and prevent its damage, which may be driving forces to separate this subgroup from others during the evolution of Thermoprofundales. Fig. 3. Ancestral genome content reconstruction and HGT donor predictions of Thermoprofundales. The solid or open circles outside the tree represent the presence or absence of the genes, respectively. Node 1 and Node 2 indicate the ancestral node of all Thermoprofundales genomes and Subgroup E, respectively. The values in parentheses indicate the number of gained (+) and lost (−) genes, and full lists of the genes are provided in supplementary table S5 and S6, Supplementary Material online. The pie charts show the ratios of HGT donors. The phylogenomic tree based on 55 conserved single-copy ubiquitous archaeal genes was constructed using IQ-TREE with ModelFinder. Ultrafast bootstrapping was used to estimate the reliability of each branch with 1,000 times resampling, and the nodes with a bootstrap value >80 are marked with black dots. HGT is the process of acquiring foreign DNA from other organisms through transformation, transduction, and conjugation (e.g., conjugative plasmids) ( Douglas and Langille 2019 ). It is a major driving force for microbial evolution and plays important roles in archaeal speciation, metabolism, and adaptation ( Wagner et al. 2017 ; Brito 2021 ). On average, 3.5% of the genes in a Thermoprofundales genome were identified as HGT genes, and 70.4% of these HGTs were derived from other distantly related archaeal genomes rather than bacterial ones ( fig. 3 ; supplementary table S7, Supplementary Material online). Halobacteriota and Thermoproteota (GTDB taxonomy ( Rinke et al. 2021 ), formerly a group of archaea including Thaumarchaeota, Aigarchaeota, Crenarchaeota, and Korarchaeota) were the major HGT donors. This result is in contrast with the hypothesis that most of the HGTs in some mesophilic archaea originated from bacteria ( López-García et al. 2015 ), and previous reports showed that gene transfer from bacteria to archaea occurred five times more frequently than from archaea to bacteria ( Nelson-Sathi et al. 2015 ). The functional patterns between archaeal and bacterial-derived HGTs were further compared using the Thermoprofundales genomes at Nodes 1 and 2 in figure 3 , respectively. The result revealed that archaeal donors contributed more HGTs in the processes of transcription, and carbohydrate transport and metabolism. However, bacterial donors contributed more HGTs related to energy production and conversion, cell wall/membrane/envelope biogenesis, and translation, ribosomal structure, and biogenesis ( supplementary fig. S9, Supplementary Material online). In addition, we examined the HGT donors in genomes from other orders in the Candidatus phylum Thermoplasmatota as proposed elsewhere ( Rinke et al. 2021 ), including Acidiprofundales, Thermoplasmatales, Methanomassiliicoccales, Poseidoniales, and MGIII ( supplementary fig. S10, Supplementary Material online). More than 53% of the HGTs identified in Acidiprofundales, Thermoplasmatales, and Methanomassiliicoccales were derived from other archaeal genomes. However, more than 92% of the HGTs in Poseidoniales and MGIII were from bacterial genomes ( supplementary fig. S10, Supplementary Material online). This result minimizes the potential biases caused by the overall dominance of bacterial genomes in the reference database (191,527 bacterial vs. 3,073 archaeal genomes in GTDB Release 95; Rinke et al. 2021 ), and it further confirms that Thermoprofundales acquired most of its HGTs from other distantly related archaeal species. In addition, 437 sequences from the Thermoprofundales genomes were predicted as plasmids using PlasFlow ( Krawczyk et al. 2018 ) and PlasClass ( Pellow et al. 2020 ) ( supplementary table S8, Supplementary Material online). Plasmids are mobile genetic elements (MGEs), and they contain nonchromosomal fragments of DNA and facilitate the fast evolution and adaptation of microorganisms to diverse environments ( Heuer and Smalla 2012 ). They typically lack essential genes for microbial growth, but possess genes involved in response to changes in environmental conditions or exposure to pollutants (e.g., heavy metals and antibiotics) ( Carattoli 2013 ). Interestingly, the gene encoding an extracellular protein-degrading enzyme for gingipain (Merops family C25) was located in the plasmids of 27 genomes. This enzyme, which participates in the protein remineralization process, is abundant and active in samples from Aarhus Bay sediments of Denmark ( Lloyd et al. 2013 ). Some structural genes encoding the archaellum were located in plasmids from 19 Thermoprofundales genomes, including some key genes for archaellum rotation and assembly ( FlaI , FlaJ , and FlaB ). As a motility structure peculiar to the Archaea domain ( Albers and Jarrell 2018 ), the archaellum may enable Thermoprofundales to move toward favorable micro-niches ( Herzog and Wirth 2012 ), and/or mediate its surface attachment, cell–cell communication, and extracellular electron exchange ( Näther et al. 2006 ; Walker et al. 2019 ). Six Thermoprofundales plasmids also encoded the complete gene sets for riboflavin biosynthesis ( RibBHE ), a precursor of the coenzymes flavin mononucleotide (FMN) and flavin adenine dinucleotide (FAD). These two coenzymes are major electron carriers in multiple and ubiquitous redox reactions involved in energy conservation pathways and cellular processes ( Thakur et al. 2017 ). H 2 Production by an Ancient MBH Complex Phylogenetic reconstruction revealed that 71.2% of the genomes from the five Thermoprofundales subgroups encoded a gene of the Group 4d [NiFe] hydrogenase, which is an MBH-type H 2 -producing hydrogenase ( Vignais and Billoud 2007 ) ( fig. 4 a ; supplementary table S4, Supplementary Material online). The MBH complex is composed of 14 subunits, including a membrane arm and a peripheral arm ( Schut et al. 2013 ). The membrane arm is formed by ten subunits (MbhABCDEFGHIM) located in the cell membrane, where it functions as an Na + /H + antiporter domain ( fig. 2 ). The peripheral arm is formed by four subunits (MbhJKLN) exposed to the cytoplasm, where it functions as a [NiFe] hydrogenase domain ( Yu et al. 2018 ). The cryo-EM structure of this enzyme from a hyperthermophilic archaeon, Pyrococcus furiosus , was recently obtained. It is reported that the H 2 -evolving catalytic site is located at the E21 and the [NiFe] center (C68, C71, C374, and C377) of the large subunit MbhL ( Yu et al. 2018 ). Sequence alignment and 3D structure reconstruction of the MbhL coding genes revealed that all the H 2 -evolving catalytic sites are conserved in Thermoprofundales, when compared with P. furiosus ( supplementary fig. S11, Supplementary Material online). Furthermore, the MbhL gene from Thermoprofundales FT_bin5.232 was expressed in Escherichia coli BL21 strain to test its activity. Consistent with previous reports ( Sapra et al. 2000 ; McTernan et al. 2015 ), the purified enzyme showed catalytic activity for H 2 production as assayed by gas chromatography ( fig. 4 b ). Fig. 4. ( a ) Phylogenetic tree of Thermoprofundales based on the MbhL gene. The shaded area indicates the position of the MbhL gene, and the red branches indicate the MbhL genes of Thermoprofundales. The label at each clade indicates a hydrogenase group. ( b ) H 2 production by the recombinant MbhL protein from Thermoprofundales FT_bin5.232. Hydrogenase activity was measured in a reaction medium containing the recombinant MbhL protein or inactivated MbhL protein. A blank assay was run without any protein. The dashed line marks the H 2 peak by gas chromatography. Hydrogen metabolism (including H 2 oxidation and production) is one of the most ancient and widespread metabolic traits, whose metabolite (i.e., H 2 ) is widely used to generate energy to support microbial growth ( Lane et al. 2010 ; Greening et al. 2016 ). Microorganisms produce H 2 by using the [NiFe]-hydrogenase (Groups 3b and 4d) or [FeFe]-hydrogenase ( Greening et al. 2016 ; Søndergaard et al. 2016 ). These H 2 producers contribute to the major biogenic pool of H 2 on Earth (e.g., anoxic sediments and gastrointestinal tracts) ( Greening and Boyd 2020 ). In Thermoprofundales, the production of H 2 is catalyzed by the MBH-type [NiFe] hydrogenase, and reduced ferredoxin is the natural electron donor of this enzyme ( Yu et al. 2018 ). Various genes coding for the production of reduced ferredoxin were detected in the Thermoprofundales genomes, showing that other components needed for hydrogen production are not a limitation in this microorganism ( fig. 2 ). For example, identified pathways that lead to the generation of reduced ferredoxin include pyruvate and 2-oxoglutarate oxidation (pyruvate ferredoxin oxidoreductase, 2-oxoglutarate/2-oxoacid ferredoxin oxidoreductase) in the tricarboxylic acid cycle, and glyceraldehyde oxidation (aldehyde ferredoxin oxidoreductase) in the glycolysis pathway. New Insights into the Evolution of Modern Respiratory Systems In Subgroup E, gene arrangement of the 14 subunits of MBH differed from those in subgroups A, B, C, D, and P. furiosus ( Yu et al. 2018 ) ( fig. 5 a ). In the genomes of Subgroup E, the peripheral arm genes of the [NiFe] hydrogenase domain were separated from the membrane arm genes of the Na + /H + antiporter domain. A detailed survey of all the genomes in the NCBI GenBank database (January 25, 2021) further revealed that the discontinuous gene arrangement of MBH was unique to Thermoprofundales Subgroup E in Bacteria and Archaea ( fig. 6 ). Phylogenetic analysis of the concatenated 4 peripheral arm genes ( MbhJKLN ), the 10 membrane arm genes ( MbhABCDEFGHIM ), and the complete 14 genes ( MbhA–N ) showed a consistent placement of Thermoprofundales as a monophyletic lineage adjacent to some Aciduliprofundum genomes ( fig. 6 , supplementary fig. S12, Supplementary Material online). These results are also coherent with the genome tree of all the MBH-containing genomes, revealing that the genes for the peripheral and membrane arms in Thermoprofundales are evolutionary conserved. Fig. 5. ( a ) Gene arrangement of the MBH complex in Thermoprofundales. ARC, the proposed common ARC. ( b ) Illustration of the MBH complex. ( c – e ) Growth performances of Escherichia coli KNabc strains cultured in 0, 0.1, and 0.2 M NaCl, respectively. KNabc/pET-22 b -MbhA-M, a KNabc strain containing a gene cluster MbhABCDEFGHIM inserted into a pET-22 b (+) plasmid. KNabc/pET-22 b , a KNabc strain containing an empty pET-22 b (+) plasmid. Three replicates are performed for each treatment. ( f ) Relative transcriptional abundances of the peripheral and membrane arms in four MAGs from the FT mangrove sediments. The numbers at the right of each row indicate sediment depth intervals of the FT metatranscriptomes. Fig. 6. ( a ) Phylogenomic tree of the MBH-containing archaeal genomes in the NCBI GenBank database. The tree based on 55 archaeal marker genes is constructed using IQ-TREE with ModelFinder. ( b ) Phylogenetic tree of the concatenated 14-subunits MBH gene in the NCBI GenBank database. The colors covering the tree branches indicate different archaeal lineages. The nodes with a bootstrap value >80 are marked with black dots. Metatranscriptomic analysis of the FT mangrove sediments revealed distinct transcriptional patterns between the genes of the peripheral arm and the membrane arm in some MAGs from Subgroup E ( fig. 5 f ), suggesting that these two arms could function independently. To further confirm this, a recombinant plasmid containing the membrane arm gene cluster MbhABCDEFGHIM from FT_bin5.232 was introduced into an antiporter-deficient strain E. coli KNabc, which is commonly used to test the function of Na + /H + antiporters ( Shao et al. 2021 ). In general, when cultured in LBK medium containing either 0.1 or 0.2 M NaCl, a much better growth performance was observed for KNabc transformed with the membrane arm plasmid than that for the same strain with an empty plasmid ( fig. 5 c – e ). This showed that the membrane arm protein of Subgroup E partially compensated the deficiency of KNabc for growing at high salt concentrations, confirming its function as an Na + transporter. Molecular dating analysis revealed that Subgroup E was an early diverged lineage among all the MBH-containing microorganisms in Thermoplasmatota ( fig. 7 ). The ancestor of Subgroup E might have emerged from a habitat that resembles the sediments of terrestrial surface ( fig. 1 ), which are characterized by mild temperature (<40 °C), low salinity (<2%), low oxygen availability, and intense sunlight incidence, when compared with the deep sea. The ancestor of Subgroup E possibly experienced extensive gene duplication, rearrangement, and HGT events throughout its evolutionary history, including changes in the region of the MBH gene cluster. The separation of MBH into two modules, as observed in Subgroup E, might facilitate the adaption to the aquatic environments on the terrestrial surface. This would be achieved through a more efficient but less energy-consuming processes for hydrogen production and proton pumping, respectively. For example, 1) the synthesis of a 4-subunits (MbhJKLN) instead of a 14-subunits (MbhA–N) hydrogenase complex is functional for hydrogen production; 2) Subgroup E microorganisms may have a reduced need to pump out excess sodium when compared with other subgroups, since most of the genomes in Subgroup E were retrieved from terrestrial habitats with low salinity. These speculations are supported by the much higher transcriptional abundances of the peripheral arm than those of the membrane arm in four MAGs from the FT mangrove sediments ( fig. 5 f ), showing that hydrogen production is more transcriptionally active than proton pumping in Subgroup E. Fig. 7. Evolutionary timeline of the MBH-containing archaeal lineages. The values in parentheses are the posterior 95% confidence intervals. Interestingly, the gene structure of the peripheral arm in Subgroup E resembles that of the proposed common ancestral respiratory complex (ARC) of modern respiratory systems such as MBH and complex I ( fig. 5 a ). The ARC, encoded by 5-subunits genes ( MbhJKLMN ), is a core protein module that can be traced back to the Last Universal Common Ancestor (LUCA) of Bacteria and Archaea; it is thought to function independently as a hydrogen-producing enzyme, which plays a key role in the early evolution of life ( Schut et al. 2016 ). It is hypothesized that MBH shares a common ancestor with Complex I, and both of them possibly evolve from the Mrp (multiple resistance and pH adaptation) antiporter by acquiring a membrane-anchored hydrogenase module ( Yu et al. 2018 ). The Mrp antiporter is an Na + (or K + )/H + exchanger representing an ancestor of many essential redox-driven proton pumps including MBH and Complex I ( Steiner and Sazanov 2020 ). The conserved structural features in the two complexes indicate a similar energy conservation mechanism between the peripheral and membrane arms. However, a major difference between the two complexes is the absence of a proposed sodium ion translocation unit in the membrane arm of Complex I, but it is shared between MBH and Mrp antiporter ( Yu et al. 2018 ). This indicates that the membrane arm of MBH evolves earlier than that of Complex I. Meanwhile, the phylogenetic tree of representative [NiFe]-hydrogenase groups also showed that the MbhL gene in the peripheral arm of MBH emerged earlier than the NuoD gene of complex I ( fig. 4 a ). A primary driving force in the evolution of ARC to modern respiratory complexes may be the availability of oxygen and associated high redox potential compounds ( Schut et al. 2016 ). However, when compared with ARC, the lack of an MbhM subunit in the peripheral arm of Subgroup E does not appear to impact its function as a hydrogenase, because the MbhM is reported to be a membrane anchor for the peripheral arm and it did not show any ion translocation activity in P. furiosus ( Yu et al. 2018 )."
} | 8,158 |
39636428 | PMC11656839 | pmc | 1,350 | {
"abstract": "Structures such as 3D buckling have been widely used\nto impart\nstretchability to devices. However, these structures have limitations\nwhen applied to piezoelectric devices due to the uneven distribution\nof internal strain during deformation. When strains with opposite\ndirections simultaneously affect piezoelectric materials, the electric\noutput can decrease due to cancellation. Here, we report an electrode\ndesign tailored to the direction of strain and a circuit configuration\nthat prevents electric output cancellation. These designs not only\nprovide stretchability to piezoelectric nanogenerators (PENGs) but\nalso effectively minimize electric output loss, achieving stretchable\nPENGs with minimal energy loss. These improvements were demonstrated\nusing an inorganic piezoelectric material (PZT thin film) with a high\npiezoelectric coefficient, achieving a substantial maximum output\npower of 8.34 mW/cm 3 . Theoretical modeling of the coupling\nbetween mechanical and electrical properties demonstrates the dynamics\nof energy harvesting, emphasizing the electrode design. In vitro and\nin vivo experiments validate the device’s effectiveness in\nbiomechanical energy harvesting. These results represent a significant\nadvancement in stretchable PENGs, offering robust and efficient solutions\nfor wearable electronics and biomedical devices.",
"conclusion": "Conclusions In this study, we introduced an approach\nto stretchable energy\nharvesting by developing a 3D buckling structure in PZT materials\ncomplemented by a curvature-specific coupling electrode design and\nan optimized circuit configuration. This approach has validated the\nfeasibility of realizing an S-PENG with buckling structures, setting\nit apart from conventional PENG designs. Our proposed S-PENG design\nenables efficient electrical energy harvesting even when the buckling\nstructure exhibits a geometrically distributed curvature with zero\naverage. This design circumvents the typical cancellation of electrical\noutput observed in conventional systems, ensuring that each segment\nof the nanogenerator effectively contributes to overall energy production.\nWe confirmed the reliability of our design through theoretical and\nsimulation analyses. Additionally, by demonstrating that the characteristics\nof the S-PENG predicted by simulations and theory align with experimental\ndata, we have experimentally proven the feasibility of our design.\nThis S-PENG achieves a maximum output of 8.34 mW/cm 3 at\nan optimal load resistance of 50 MΩ. The practical applications\nof our technology were underscored through wearable applications and\nimplantable in vivo experiments using a porcine heart. Our device\nhas proven its capability to harvest energy from body movements when\nattached to various body parts (knee, hand, and finger). Moreover,\nwe verified that it can successfully harvest energy from the surface\nof a porcine heart during repeated expansion and contraction. These\nexperiments not only confirmed the mechanical and functional viability\nof our device but also showcased its potential as a PZT-based stretchable\nPENG, a task that was extremely challenging with conventional designs.\nAdditionally, this strategy is versatile, as it is not limited by\nthe type of piezoelectric material or strain-insensitive structure.\nWhile we used PZT as the piezoelectric material in this study, our\nstrategy remains theoretically valid for other materials, such as\nPVDF or composite-based piezoelectric materials. Furthermore, as long\nas the distribution of local strain can be accurately predicted, efficient\nelectrode and circuit designs can be achieved by using our method\nwith various strain-insensitive structures, such as woven, serpentine,\nhelical, and kirigami structures. Although our strategy theoretically\noffers broad applicability, further experimental validation and further\nfuture studies are required to fully explore and confirm its effectiveness.\nIn conclusion, our study represents a significant breakthrough in\npiezoelectric energy harvesting technology. By overcoming the limitations\nof conventional S-PENGs systems, we have opened possibilities for\nthe development of stretchable, efficient, and robust S-PENGs.",
"discussion": "Results and Discussion Principle and Design of the S-PENG The S-PENG is realized\nthrough the compressive buckling of planar devices, addressing the\ninherent challenges posed by the material’s limited elastic\nmodulus and maximum tensile strain. This approach incorporates 3D\nstructures featuring wavy piezoelectric ribbons that partially detach\nfrom elastomeric substrates. The structure is induced by locally bonding\nflat PZT thin films to prestrained substrates. As the prestrain is\nreleased, the unrestrained regions (buckling regions) of the PZT thin\nfilm buckle upward ( Figure 1 a). By exploiting the buckled PZT layers, the global strain\nof the device is converted into flattening of the curvature, thereby\nmitigating strain within the thin PZT film. The precise control over\nthe 3D buckling shape, including wavelength and amplitude, is achieved\nthrough the extent of prestrain of the substrate and other design\nparameters such as the location of bonding sites between the device\nand prestrained substrates. 44 − 47 Figure 1 Principle and design of the S-PENG with curvature-specific\nelectrodes.\n(a) Structure of the S-PENG. Compressive buckling induces regions\nwith positive (red) and negative (blue) curvatures, generating opposite\nlocal polarity across the PZT layer in response to strain. (b) Representation\nof the conventional electrode design that electrically coupled regions\nwith different curvatures. (c) Finite element analysis (FEA) for the\n3D PZT nanogenerator with conventional electrodes, showing output\nvoltage and strain after compressive buckling. Scale bars, 100 μm.\n(d) Output voltage and (e) electrical energy fraction generated during\nelongation with a strain rate of 90% per second. (f) Illustration\nof the curvature-specific electrode design. (g–i) Output voltage\nand strain (g), output voltage (h), and electrical energy fraction\n(i) of the device with curvature-specific electrodes, respectively. The electrical polarity induced by the deformation\nof the PZT surface\nduring stretching motion is governed by the strain exerted on the\nlocal region. When the neutral plane of the S-PENG is positioned beneath\nthe PZT layer, the areas with negative curvature (convex regions)\nnear the apex of the curved configuration (blue region in Figure 1 a) experience tensile\nstrain, whereas the areas with positive curvature (concave regions)\nnear the trough anchored to the substrate endure compressive strain\n(red region in Figure 1 a). The difference in the local strain causes the output voltage\nin the opposite direction when the device is subject to mechanical\ndeformation. Conventional PENGs operating in the d31 mode induce\nan electric\nfield perpendicular to the direction of the mechanical stress. 27 , 33 , 48 , 49 These devices typically utilize a sandwich structure with two electrodes\ncovering either the top or the bottom sides of the PZT layer ( Figure 1 b). However, the\nconventional design’s electrical connection between regions\nwith opposite curvatures significantly undermines the energy efficiency.\nThe equivalent circuit model shown in the bottom diagram of Figure 1 b elucidates the\ndiminished output voltage of these nanogenerators. The piezoelectric\nlayer with varying curvatures within one buckling period was modeled\nas four capacitors connected in parallel. These capacitors are directly\ninterconnected through the Au and Pt, which induces immediate internal\ncurrent flow between the capacitors with opposite curvature during\nstretching motion. This internal current lasts until it invalidates\nthe vertical voltage difference of the PZT layer and dissipates the\ncapacitive energy in each region ( E CCC and E CVC ) into Joule heating energy\n( E in ) through the internal resistance. Figure 1 c depicts\nthe finite element analysis (FEA) simulation results of the strain\nin the xx direction (ε 11 ) in the\nbuckling structure after the release of prestrain of the substrate\nto estimate the output voltage. Despite the locally nonzero deformation\nin the xx direction, the average value is zero, and\nthe temporal output voltage essentially approaches zero. Figure 1 d illustrates the\noutput voltage during the more realistic scenario of elongation of\nthe device with a strain rate of 90% per second. The analytical solution\n(Supporting Note 1) for the output voltage demonstrates the decay\nof output voltage of convex (blue) and concave (red) regions within\napproximately 10 ns due to the internal current. The electrical energy\nfraction over time, summarized in Figure 1 e, shows that conventional electrodes dissipate\nthe generated total electrical energy ( E tot ) as Joule heating ( E in ) due to internal\ncurrent, rather than harvesting it through external load ( E ext ) elements. In contrast, Figure 1 f introduces a segmented electrode\nstructure based on their corresponding\ncurvature. Unlike conventional electrode designs, our approach involves\nprecisely patterning electrodes segmented within regions that share\nthe same curvature. Subsequently, these curvature-specific coupling\nelectrodes are connected at their terminals in a series configuration,\neffectively consolidating regions with the same curvature (polarity)\nand interconnecting regions with opposite polarities in series. The\nequivalent circuit model in the bottom of Figure 1 f demonstrates electrical insulation between\nelectrodes with different curvatures in principle due to the large\nresistance across polyimide gap, resulting in the dominant current\nflow through the external load. By connecting the capacitors with\nopposite curvature in series, the averaging out of the total output\nvoltages is prevented. Figure 1 g shows the simulation results for the strain and output voltage.\nWhile the strain level shows little difference, depending on the electrode\ndesign, the output voltage is clearly distinguishable. The analytical\nsolution results for the transient dynamics of the voltage generated\nin the S-PENG with the curvature-specific coupling electrodes design\nare demonstrated in Figure 1 h. Unlike the conventional S-PENG, where the local output\nvoltage decays rapidly, the proposed S-PENG design inhibits the decay\nof the output voltage in the convex (blue) and concave (red) regions.\nThis is achieved by preventing internal current through the separated\nelectrode design. Additionally, the serial connection between regions\nwith opposite curvature results in the total output voltage being\ntwice the magnitude of the local output voltage. This increase in\nthe output voltage leads to improved energy efficiency. Unlike the\nconventional design, where energy waste due to internal current was\ndominant, the curvature-specific coupling electrode design allows\nall the electrical energy generated in the S-PENG to be utilized by\nthe external load ( Figure 1 i). Fabrication Process The implementation of the curvature-specific\ncoupling electrode design requires a fabrication technique capable\nof controlling local curvature in a predetermined manner while remaining\ncompatible with planar photolithography for electrode segmentation\nand global interconnection. Compressive buckling based on residual-stress-induced\nbending addresses these requirements effectively. Figure 2 a illustrates the fabrication\nprocess for an S-PENG with curvature-specific electrodes. A two-step\ntransferring process was developed, first from the wafer to a polyimide\n(PI) layer and then from the PI layer to a prestrained elastomeric\nsubstrate. This process accommodates the high-temperature annealing\nprocess of PZT, protects it from process chemicals, and forms bonding\nsites to the substrate for a controlled buckling structure. Figure 2 Fabrication\nprocess of the S-PENG. (a) Schematic illustration of\nthe fabrication process for the S-PENG. Scale bars, 1 cm. (b–d)\nOptical images of the device on PI after the first transfer printing\n(b) and on the strained (c) or sequentially released (d) Ecoflex after\nthe second transfer printing. (e) Optical images of the uni- and biaxially\nstretchable 3D PZT nanogenerators with curvature-specific coupling\nelectrodes. Scale bars: 500 μm. The process begins with a bare silicon wafer serving\nas a temporary\nsubstrate. Before the bottom electrode is deposited, a double-layer\nstack of Cr and SiO 2 is deposited. The Cr layer maintains\nmechanical stability during the high-temperature annealing process\nof the PZT and serves as a sacrificial layer subsequently. The SiO 2 upper layer acts as a protective barrier for the PZT during\nexposure to the Cr etchant used for separating the device from the\nsilicon wafer. Next, Pt is deposited to create the bottom electrodes,\nchosen for their stability during the PZT annealing process and their\nability to enhance the crystallinity of the PZT material. The PZT\nthin film has a nominal thickness of approximately 500 nm to ensure\nmechanical flexibility of the curved structure. The sputtered PZT\nlayer is lifted off using prepatterned photoresist to minimize chemical\ndamage, offering advantages over wet etching methods involving nitric\nacid (HNO 3 ) and hydrogen fluoride. Following annealing\nof the PZT thin film layer at 650 °C ( Figure S1 ), the top and interconnect metals are\npatterned, and the top side of the device is encapsulated with polyimide\n(PI). In the first transfer-printing step, a poly(dimethylsiloxane)\n(PDMS) stamp is utilized to transfer the device to the PI film by\ndissolving the sacrificial Cr layer. Anchoring sites are incorporated\nto hold the device before the pick-up process. Bonding sites to the\nelastomeric substrate are defined using patterned SiO 2 after\nthe first transfer to PI. Figure 2 b illustrates the top and bottom sides of the device\nafter the first transfer-printing ( Figure S2 ). The adhesive region is covered with SiO 2 to ensure\nlocal fixation of the device to the elastomeric substrate via siloxane\nbonding. The second transfer to the prestrained elastomeric substrate\nand the release of the prestrain complete the fabrication process.\nPoling was performed prior to compressive buckling in silicone oil\nat 150 °C with an applied voltage of 80 kV/mm. A temporary parallel\nconnection circuit was constructed to match the direction of poling\nin vertical direction ( Figure S3a,b ). This\ntemporary circuit configuration is replaced by serial interconnection\nafter poling to maximize the efficiency of energy harvesting ( Figure S3c,d ). Figure 2 c,d depicts\nthe images of the device attached to prestrained and sequentially\nreleased elastomeric substrates, respectively ( Figure S4 ). The bottom images show the FEA results visualizing\nthe local strain in the xx direction after the formation\nof compressive buckling, indicating opposite strain depending on the\ncurvature. These local strains in opposite directions enhance the\ndielectric polarization in the concave regions and weaken it in the\nconvex regions, creating a voltage difference between these regions\n( Figure S3e –g). Figure 2 e presents the images of uni-\nand biaxially stretchable PENGs with curvature-dependent coupling\nelectrodes. The biaxially stretchable PENG can maximize energy harvesting\nfrom the 2D motion exhibited by the surface of human organs. Various\ndesign configurations can be explored to tailor the performance to\nthe varying stretching scenarios. Experimental Demonstration and On-Body Applications To experimentally demonstrate the feasibility of utilizing stretchable\nPZT ribbons with curvature-specific coupling electrodes, the output\nof a single strap of the S-PENG was tested under various circumstances.\nThe stretching/bending stage and the ribbons under test are depicted\nin Figure S5 . Figure 3 a,b illustrates the opposite signs of the\nchange in the open-circuit voltages depending on the curvature (convex\nor concave). In the initial state without global strain, the PZT ribbons\nare in a 3D buckling shape, and there is no voltage difference between\nthe top and bottom electrodes. As the PZT ribbons flatten with global\nstrain, the regions return to their original polarization levels (poling),\nresulting in decreased polarization in concave regions and increased\npolarization in convex regions. During this process, the capacitive\ncharges in the top and bottom electrodes remain mostly stationary\nin open circuit, leading to the concave region (blue) exhibiting a\nnegative output voltage, while the convex region (red) shows a positive\noutput voltage ( Figures S6 and S7 ). Figure 3 c shows the output\nvoltage of the S-PENG depending on the circuit configuration (serial\nor parallel interconnection) ( Figure S8 ). When the convex and concave regions are electrically interconnected\nin parallel, the equivalent circuit of the S-PENG is shown in Figure S8a and is equivalent to the circuit configuration\nof the S-PENG with conventional electrodes described in Figure 1 b. Therefore, the voltage generated\nin each region cancels out, significantly reducing the energy harvesting\nefficiency. Conversely, when they are connected in series, the voltages\ngenerated in each region undergo constructive interference, resulting\nin an enhanced overall output voltage. The trends observed in the\nexperimental data align with those predicted by theoretical analysis,\nlending credibility to the mechanisms of the curvature-specific coupling\ndesign. Figure 3 Validation of the S-PENG. (a, b) Open-circuit voltages of the convex\n(blue) and concave (red) regions. (c) Voltage measured between electrodes\nwith conventional (yellow) and curvature-specific design (red). (d)\nExperimental and analytical output voltages of the S-PENG, measured\nwith external loads of 50 Mohm. (e) Measured (dots) and theoretically\ncalculated (solid line) voltage and current under different external\nresistances varying from 0.1 MΩ to 1 GΩ at 2 Hz. (f) Comparison\nof current density of the S-PENG from this work and other references\nas a function of deformability. Detailed information can be found\nin Table S1 . (g–i) On-body evaluation\nof the S-PENG. Output voltage and current recordings from the S-PENG,\nattached to the knee (g), hand (h), and finger (i) in wearable applications,\nwith an external load of 100 Mohm. Scale bars: 5 cm. Figure 3 d and Figure S9 show the output\nvoltages of the S-PENG,\nboth experimentally measured and theoretically predicted ( Supporting Note 1 ), with external loads of 10,\n50, and 100 Mohm. The theoretically predicted voltage–time\ncurve ( eq S16 ) accurately conforms to the\nobserved experimental data. where e̅ represents\nthe effective piezoelectric constant and t pzt , b pzt , and A pzt denote the thickness, width, and area of the PZT layer, respectively. d pzt and z n are the z -positions of the center of the PZT layer and the neutral\nplane, respectively. k̅ is the effective dielectric\nconstant, W in is the length of the buckling\nregion, n represents the number of the periodic buckling\nstructures, and R int and R ext are the internal resistance and external load, respectively.\nFurther demonstrating a characteristic of the S-PENG, the switching\npolarity test showed polarity inversion when electrical lead-out connections\nare reversed ( Figure S10 ), thus validating\nthe piezoelectric effect of the S-PENG. Figure 3 e and Figure S11 illustrate the output characteristics\nof the S-PENG under varying external load resistances ranging from\n0.1 MΩ to 1 GΩ. The measured voltage and current outputs\n(red and blue dots) align closely with the theoretical predictions\n(solid lines), showing an increase in the voltage and a corresponding\ndecrease in the current as the resistance increases. The power density,\nderived from these measurements, peaked at approximately 8.34 mW/cm 3 at 50 MΩ, demonstrating optimal performance under this\ncondition. Peaks in the current signal (external load; 100 Mohm) were\nobserved during moments of stretching and releasing. Based on these\npeaks, the current density of the S-PENG, calculated as 15.64 μA/mm 3 , is comparatively higher than those of other reported PENGs\n( Figure 3 f and Table S1 ). 8 , 20 − 22 , 30 , 40 , 50 − 58 The volume used to calculate the current density is based on the\neffective area and the thickness of active materials. Additional measurements\nwith the device wrapped around the curved surface of the body, such\nas knees, hands, and fingers, are shown in Figure 3 g–i. The stretching and releasing\nmotion of the body parts deform the attached device, generating peaks\nin output voltage. Energy Harvesting in an Animal Model In vivo evaluations\nwere conducted to leverage biomechanical energy from cardiac motions.\nThe S-PENG was implanted near the left ventricle (LV) of a porcine\nheart, as shown in Figure 4 a and Figure S12 . Following anesthesia,\na median sternotomy was performed and the S-PENG was sutured onto\nthe epicardium. The device, encapsulated in a polyimide film, effectively\nisolates the PZT from biofluids and tissues, similar to previous studies\non implantable PENGs. 8 , 52 , 53 , 59 − 62 This encapsulation mitigates\nthe inherent cytotoxicity of PZT, ensuring biocompatibility of the\ndevice. The elastomeric substrate (Ecoflex-0030; thickness of 1 mm)\nadhered naturally to the epicardium and was secured at its four corners\nwith sutures. To investigate the electrical output in relation to\nthe implantation site, the device was attached to the LV area (0°)\nand across the direction between the LV and RV (90°) of the porcine\nheart, as illustrated in Figure 4 a. Figure 4 In vivo evaluation of the S-PENG. (a) Schematic illustration\nof\na 30 kg porcine model and the attachment position of the S-PENG for\nbiomedical applications. (b) Open-circuit voltage at an orientation\nof 0°. (c, d) Open-circuit voltage (c) and magnified views (d)\nat an orientation of 90°. (e) Maximum peak values of the open-circuit\nvoltage measured at each orientation (0 and 90°). The error bar\nis the calculated standard error (95% confidence interval). (f) Mechanical\nstability of output voltage generated from the S-PENG. The output\nvoltage increases in correlation with the bending strain induced by\nthe porcine heart movement and maintains high stability over 1700\ncycles. (g) Open-circuit voltages as a function of time, measured\nbefore and after epinephrine injection, and (h) corresponding heart\nrates, increasing from 148 to 170 bpm. Figure 4 b–d\nshows the open-circuit output voltages from the device mounted at\nthe 0 and 90° mounting sites, with the averaged half the absolute\nvalue of the difference between the positive and negative peaks reaching\n6.94 V at 0° and 7.61 V at 90° ( Figure 4 e). These results indicate that the device\nmounted at the 90° site generates an output voltage higher than\nthat at the 0° site of the porcine heart. This enhanced output\nvoltage at the 90° site not only underscores the significance\nof attachment location in optimizing energy harvest but also aligns\nwith findings from previous studies. The device also consistently\ngenerates stable output voltages over 1700 cycles, as shown in Figure 4 f. The buckling structure’s\nadaptability to the heart’s contraction and relaxation phases\nenhances the durability, contributing significantly to its effective\nenergy harvesting. To assess the S-PENG’s performance\nunder variable cardiac\nconditions, an experiment involving the administration of epinephrine\nwas conducted to increase the heart rate. Before administration of\nepinephrine, the heart rate was 148 bpm, which increased to 170 bpm\nfollowing the injection. Figure 4 g illustrates the open-circuit output voltages, captured\nboth before and after epinephrine administration. Corresponding to\nthe rise in the heart rate, the voltage generation frequency increased.\nWhile the heart rate rise led to an increase in the voltage generation\nfrequency, the magnitude of the output voltage showed no significant\nchange due to the modest increase in the heart rate from epinephrine\ninjection and the minimal impact of frequency on the open-circuit\nvoltage measurement method ( Figure S13 ).\nAdditionally, converting the output voltage data into the frequency\ndomain revealed that the peak intensity aligned with the heart rates\nmeasured pre- and postepinephrine injection ( Figure 4 h)."
} | 6,096 |
38347913 | PMC10859422 | pmc | 1,352 | {
"abstract": "Our reliance on agriculture for sustenance, healthcare, and resources has been essential since the dawn of civilization. However, traditional agricultural practices are no longer adequate to meet the demands of a burgeoning population amidst climate-driven agricultural challenges. Microalgae emerge as a beacon of hope, offering a sustainable and renewable source of food, animal feed, and energy. Their rapid growth rates, adaptability to non-arable land and non-potable water, and diverse bioproduct range, encompassing biofuels and nutraceuticals, position them as a cornerstone of future resource management. Furthermore, microalgae’s ability to capture carbon aligns with environmental conservation goals. While microalgae offers significant benefits, obstacles in cost-effective biomass production persist, which curtails broader application. This review examines microalgae compared to other host platforms, highlighting current innovative approaches aimed at overcoming existing barriers. These approaches include a range of techniques, from gene editing, synthetic promoters, and mutagenesis to selective breeding and metabolic engineering through transcription factors.",
"conclusion": "5 Conclusion Microalgae stand at the forefront of sustainable agriculture, heralding a new era where the constraints of traditional farming are circumvented through innovation. As the global population marches towards the 10 billion mark, the urgency for alternative resources intensifies. Microalgae’s rapid growth rates and versatility in non-traditional farming settings offer a sustainable and renewable lifeline for food, feed, and energy. They also play a critical role in carbon sequestration, aligning with environmental preservation efforts. However, economic factors present a paradox: large-scale, cost-effective production is needed for widespread application, yet such production depends on economic viability. This review has illuminated contemporary methods that enhance microalgae biomass quality, including gene editing and metabolic engineering. It also acknowledges the challenges ahead and underscores the importance of focusing on commercially viable strains. As research progresses, harnessing the full potential of microalgae requires not only scientific ingenuity but also a strategic approach to surmounting economic barriers, ensuring that microalgae can fulfill its promise as a scalable, low-cost solution for future generations.",
"introduction": "1 Introduction Humans have cultivated plants as a sustainable source of food, medicine, and materials for millennia. Since the first Agricultural Revolution (10,000 BC), we have optimized our agricultural practices to meet the increasing demands of our civilization ( Harlander, 2002 ). Today, with growing populations and food production shortcomings brought about by climate change, we can no longer count on the traditional crop optimization cycles to keep the world fed. According to the United Nations, the world population is expected to increase to about 10 billion by 2059 ( World Population Prospects, 2022 ). Over-exploitation of arable land, rising global temperatures, changing climate, and extreme weather make land crops an increasingly strained source of food, feed, and energy ( Kurukulasuriya and Rosenthal, 2013 ). Hence, new technology and resources are essential to meet the needs of future generations. Microalgae hold significant promise as a sustainable and renewable source of food, feed, and energy ( Barbosa et al., 2023 ). Microalgae are microscopic photosynthetic organisms that have high growth rates, can be cultivated using non-arable land and non-potable water, and have the ability to produce a variety of bioproducts, such as food supplements, biofuels, biopolymers, nutraceuticals, animal feeds, and medical therapeutics ( Khan et al., 2018 ; Dolganyuk et al., 2020 ; Torres-Tiji et al., 2020 ; Diaz et al., 2023 ). Additionally, microalgae capture and utilize carbon dioxide (CO 2 ) from the atmosphere to make these products, helping to mitigate greenhouse gas Emissions ( Onyeaka et al., 2021 ). With their versatile bioproducts production capabilities, ability for carbon sequestration, and capacity to do this using non-arable land and non-potable water, microalgae offer a promising avenue for meeting society’s future demands, while reducing environmental impacts associated with this increased production. However, despite their immense potential, the lack of concerted domestication efforts has resulted in relatively expensive biomass production. This chicken or egg problem, where large-scale cultivation is needed to achieve low-cost production, and low-cost production is needed for large-scale utilization, has slowed the rate at which algae will attain widespread utilization ( Chen and Wang, 2022 ). Overcoming the initial cost barriers will be crucial to fully exploit the advantages microalgae offer and establish them as low-cost, sustainable, and scalable solutions for the future ( Lane, 2022 ). Past research endeavors have demonstrated continuous improvements in a number of the properties of algae cultivation, aiming to either boost biomass production or optimize the downstream process ( Chu, 2017 ; Maity, 2019 ; Kang et al., 2022 ; Chettri et al., 2023 ). Several methods have been utilized to enhance biomass production, including improved pond design, improved crop protection, better growth media, and water chemistry, improving photosynthetic efficiency, working with extremophile strains, and optimizing strain development through molecular engineering, breeding, selection, and in-vitro evolution. For enhanced metabolic engineering, multiple techniques are available, one of which involves either overexpressing or repressing functional genes ( Mochdia and Tamaki, 2021 ; Chettri et al., 2023 ). Earlier literature has surveyed these landscape of engineering tools for algae ( Mochdia and Tamaki, 2021 ; Sproles et al., 2021 ; Dhokane et al., 2023 ; Khoo et al., 2023 ; Patel et al., 2023 ). In our current review, we update and expand upon these evaluations, providing fresh insights into the field. Our discussion starts with a comparison of microalgae against alternative production platforms, emphasizing new methods intended to improve the quality of microalgae-derived biomass. We delve into various methodologies such as gene editing, the introduction of synthetic promoters, mutagenesis, selective breeding, adaptive laboratory evolution, and metabolic engineering driven by transcription factors. We also present a thorough survey of studies focused on transcription factor-mediated metabolic engineering in microalgae. Additionally, we confront the existing hurdles and forecast potential developments, stressing the crucial integration of these innovative tools into commercially valuable algae strains."
} | 1,708 |
40032838 | PMC11876297 | pmc | 1,354 | {
"abstract": "The practicality of memristor-based computation-in-memory (CIM) systems is limited by the specific hardware design and the manual parameters tuning process. Here, we introduce a software-hardware co-development approach to improve the flexibility and efficiency of the CIM system. The hardware component supports flexible dataflow, and facilitates various weight and input mappings. The software aspect enables automatic model placement and multiple efficient optimizations. The proposed optimization methods can enhance the robustness of model weights against hardware nonidealities during the training phase and automatically identify the optimal hardware parameters to suppress the impacts of analogue computing noise during the inference phase. Utilizing the full-stack system, we experimentally demonstrate six neural network models across four distinct tasks on the hardware automatically. With the help of optimization methods, we observe a 4.76% accuracy improvement for ResNet-32 during the training phase, and a 3.32% to 9.45% improvement across the six models during the on-chip inference phase.",
"introduction": "Introduction With the rapid development of artificial intelligence (AI) technology, AI algorithm model parameters have exhibited explosive growth, creating very large hardware computing performance demands 1 , 2 . Conventional computing hardware based on the von Neumann architecture encounters a computing performance and energy efficiency ceiling due to the memory wall issue 3 . The computation-in-memory (CIM) architecture 4 – 8 , which stores the weight data locally and directly accomplishes the matrix-vector multiplication (MVM) with the memristor crossbar arrays, can enhance the computing performance and energy efficiency by orders. This attractive feature makes the memristor-based CIM architecture a revolutionary technology for future computing hardware systems 9 – 12 . Recently, CIM functional demonstrations with memristor arrays have made remarkable progress, including pattern classification with a perceptron 13 and convolution neural network 14 , 15 , voice recognition with long short-term memory (LSTM), image recovery with restricted Boltzmann machine 16 , and sparse coding 17 . These prototype demonstrations have experimentally verified the feasibility and advantage of CIM technology. However, to truly support practical and useful AI tasks, a CIM system should decouple with AI models, and can run various complex AI models with high accuracy. To date, there is a lack of a general methodology for such a practical system, leading to a deficiency in the practical application of CIM systems. The challenges towards this goal lie in two aspects: (1) The contradiction between the rigid memristor arrays and application flexibility requirement. Currently, AI models are increasingly complex and diverse, as shown in Fig. 1a . The size of each network layer varies and the connections between adjacent layers are complex. However, the size and arrangement of memristor arrays are fixed, which makes it difficult to adapt to the complex and rapidly changing AI models. (2) The accuracy loss caused by the nonideal effects of the hardware. Analogue computing with memristor arrays has many nonideal effects, including device variations, array voltage drops, analogue-digital conversion precision and so on. Existing studies have utilized specific hardware designs and manual parameter tuning methods to address these nonideal effects, but these optimizations are difficult to extend to a flexible CIM system due to its poor efficiency and transferability. These challenges lead to a very large gap (Fig. 1a ) between the AI models and the CIM hardware, which severely blocks the transition of CIM technology from basic functional demonstrations to practical computing systems. Fig. 1 The CIM system with software-hardware codesign. a Four AI tasks with different model topology structures. The best hardware parameters vary from model to model. Inappropriate parameters will lead to significant error which can severely reduce the on-chip inference accuracy. It is challenging to deploy various complex AI models on the CIM hardware and find the appropriate parameters, leading to a gap between the AI models and the CIM hardware. b The proposed CIM-oriented software framework with a loop compiler-hardware-optimizer for generating the hardware runnable codes and automatically finding the optimized tunable parameters. The compiler is used to generate runnable codes that can be directly executed on the hardware or simulator. The optimizer is used to optimize the weight and hardware parameters to be more robust against hardware nonidealities according to the built-in optimization method. c The flexible CIM hardware system with eight memristor chips, one FPGA module and one power supply PCB module on board. To address these challenges, we propose a full-stack memristor-based CIM system employing a software-hardware co-development approach. Firstly, a CIM-oriented software framework (Fig. 1b ) and a flexible hardware (Fig. 1c ) are developed to tackle flexibility issues. The designed software, including a CIM compiler, an optimizer, and a chip simulator, can handle variable and complex AI models, effectively mapping them to memristor arrays with optimized spatial-temporal utilization rates. The flexible hardware, which incorporates multiple memristor chips, supports diverse AI model dataflows and offers flexible weight and input mapping. Secondly, to address the accuracy issues, we incorporate a variety of software-hardware co-optimization methods into the optimizer, applicable to both the training and deployment phases. During the offline training phase, we propose a post-deployment training method that autonomously refines model weights to enhance robustness against hardware nonidealities. During the model deployment phase, two optimization methods, namely single-stage automatic tuning and progressive two-stage search, are introduced to facilitate the automatic identification of optimal hardware parameters. These methods suppress the impacts of analogue computing noise, thereby enhancing the accuracy across various models. Finally, six representative AI models with typical topology structures applied to four AI tasks, including image classification, text classification, image segmentation, and object detection, are automatically demonstrated using the developed CIM hardware and software, achieving fully multiply-accumulate (MAC) operations on chips. Experimental results show that, for small-scale networks, including 2-layer multilayer perceptron 18 (MLP), 3-layer convolution neural network 19 (CNN), LSTM network 20 , U-Net 21 , and reduced RetinaFace-Net 22 , the proposed CIM software framework achieves notable improvements in on-chip inference accuracy by 5.40%, 9.12%, 4.99%, 9.45%, and 7.87% respectively. Furthermore, for medium-scale networks such as ResNet-32 23 , the CIM software framework enhances accuracy by 4.76% during the training phase and 3.32% during the on-chip inference phase. Even more significantly, for a large-scale network such as ResNet-50 23 , we also observe improvements of 38.76% and 3.39% in accuracy during the training and inference phase respectively, when using a chip simulator to evaluate our approach.",
"discussion": "Discussion In this study, we have demonstrated the feasibility of our memristor-based CIM system through the automatic execution of six typical AI models. This system encompasses both an end-to-end software framework and hardware design, effectively catering to the inference requirements of diverse AI tasks. Remarkably, the full-stack system exhibits state-of-the-art flexibility in dealing with diverse AI models and maintaining the on-chip inference accuracy, when compared to the latest reported works in the field. Our software framework enables the seamless execution of the entire processing pipeline, encompassing model parsing, model deployment, on-chip inferencing, and automatic optimization of CIM hardware performance, all without the need for manual intervention. What’s more, we have showcased six typical AI models that encompass the most prevalent deep learning operations and model topology structures. The experimental results underscore the strong generality of our CIM-oriented software framework for a wide range of existing AI tasks, delivering significant enhancements in accuracy. Furthermore, the on-chip experiments demonstrate that our proposed software-hardware co-optimization method can effectively alleviate the impact of system discrepancies on model accuracy. Compared to the prior studies, our work demonstrates a significant advancement, particularly in the realms of automatic transformation during algorithm training, the optimization of parameters within the software automation framework, and the enhancement of model diversity in hardware validation (see Supplementary Tables S8 and S9 ). Importantly, this framework does not impose strict constraints on device type and can be deployed not only on memristor-based systems but also on other CIM systems. This full-stack system introduces an innovative approach to promote the wider adoption of CIM systems, facilitating research and demonstrations in this field for a broader audience."
} | 2,326 |
36506134 | PMC9730453 | pmc | 1,355 | {
"abstract": "The separation of\noceanic spilled oils and industrial oily wastewaters\nbecomes a great challenge, and it is highly desirable to develop efficient\nmaterials for oil/water separation. As abundant sustainable resources,\nsuperhydrophobic papers (SPs) have drawn much attention because of\nlow-cost and efficient oil/water separation. Herein, this mini-review\nsummarizes recent advances of SPs in terms of design, preparation,\nand properties. On the basis of the many excellent properties of SPs\n(i.e., self-cleaning, durability, chemical corrosion resistance, and\nreusability), the oil/water separation performances (i.e., separation\nefficiency, permeation flux, and recyclability) of SPs as well as\nthe corresponding mechanisms are discussed. The efficient oil/water\nseparation property and recyclability of SPs make them promising candidates\nin the field of oily wastewater treatment.",
"conclusion": "Conclusions and Outlook In summary, this mini-review introduces the design, preparation,\nand properties of SPs for their application in the field of oil/water\nseparation. The SPs are cellulosic fiber-based materials, consisting\nof porous structures, microtextures, and rich hydrophilic functional\ngroups. The excellent properties of SPs (i.e., self-cleaning, durability,\nchemical corrosion resistance, and reusability) enable the efficient\noil/water mixtures (or emulsions). Thus, as abundant sustainable resources,\nSPs are promising candidates in the field of oily wastewater treatment. In the future, the rational design of SPs needs to be realized\nto meet the requirements (i.e., thermal stability, chemical resistance,\ndurability, antiaging (or anti-UV), and reusability) of practical\napplications (i.e., oil/water separation). When utilized in oil/water\nseparation, two main challenges (i.e., the separation of emulsions\nand the separation of viscous oil/water mixtures) exist. By adjusting\nthe pore size of the SPs and the working pressure, oil/water emulsions\ncan be efficiently separated. However, nanoemulsions (with droplet\nsize <20 nm) are still difficult to separate. The separation efficiency\nof nanoemulsions probably can be improved by the combination of the\nfollowing two methods: (1) the introduction of an external stimulus\n(i.e., electrothermal or photothermal heating and magnetic field)\nin the separation of oil/water emulsions is beneficial to the demulsification\nprocesses; (2) a multistep process can be employed by utilizing SPs\nwith different pore sizes to realize the separation of nanoemulsions.\nAs for viscous oil/water mixtures, electrothermal or photothermal\nheating has been demonstrated to enhance the separation of oil/water\nmixtures, while the recyclability of SPs should be improved after\nseveral cycles of viscous oil/water separation. Of course, SPs also\nhave disadvantages for oil/water separation. For example, the adsorption\ncapacity of SPs for oil/water mixtures (or emulsions) is much lower\nthan that of sponges and porous materials. Thus, in the practical\napplication of oil/water separation, suitable separation materials\ncan be selected to meet different conditions and environments (i.e.,\nviscous oils, nanoemulsions, light oils, and heavy oils). All in all,\nlow-cost and renewable SPs are promising candidates in the field of\noily wastewater treatment, providing a great potential use in different\nharsh environments.",
"introduction": "Introduction Oceanic oil spill incidents and the discharge\nof oily wastewaters\nhave caused long-term significant threats to the environment and human\nhealth. 1 To address this issue, traditional\nmethods have been reported to remove oils from oily wastewaters, including\nin situ burning, bioremediation, centrifugation, coagulation, flotation,\nand chemical dispersion. 1a − 1d Unfortunately, these methods suffer from complex\noperations, high cost, low separation efficiency, and secondary pollution. 1b − 1d Therefore, efficient and energy-saving methods are highly desired\nfor the separation of oily wastewaters. Due to excellent liquid\nrepellency, superhydrophobic materials\nhave been utilized in the applications of oil/water separation, 1c anti-icing, 2 self-cleaning, 3 anticorrosion, 4 and\nantibacterial activity. 5 Various substrate\nmaterials have been developed to obtain surface superhydrophobicity,\nsuch as papers, metals, polymers, ceramics, wood, and glass. Among\nthem, papers have drawn much attention because of abundant sustainable\nresources, 6 light weight, 1c low cost, 1a , 5 flexibility, 5 and environmental friendliness. 6 , 7 For\nexample, SPs show much better resistance to highly acidic or alkaline\nsolutions when compared with metals (i.e., stainless steel and copper\ngrid) and polymer (i.e., polyester) fabrics. 1e Also, SPs with proper pore sizes have good performances for the\nseparation of oil/water emulsions rather than other materials (i.e.,\nmetal meshes and glass fiber membranes). 1e , 7b Generally, the paper material is a type of cellulosic material,\nconsisting of porous structures, microtextures, and rich hydrophilic\nfunctional groups. Thus, superhydrophobic papers (SPs) can be easily\nachieved via the decoration of nanomaterials and chemical modification.\nThe rational design endows SPs with many excellent properties, including\nself-cleaning, 1c mechanical and thermal\ndurability, 5 chemical resistance (i.e.,\nacid, base, and saline solutions), 1c − 1e and reusability. 1a , 4 Recently, SPs have been used in the field of oil/water separation\nbecause oil can easily wet and penetrate SPs with low surface tension. 8 For example, He et al. prepared durable TiO 2 /polydopamine (PDA)-based SPs and found that the TiO 2 /PDA-based SPs can maintain the separation efficiency of an oil/water\nmixture (or water-in-oil emulsions) above 94.3% (or 93.7%) after 15\ncyclic separation processes. 1c Yang et\nal. designed recyclable, magnetic, and fire-retardant SPs, and the\nSPs showed a separation selectivity above 99.0% and a good recycling\nability for >10 times. 4 Li et al. reported\nthat a durable and sustainable superhydrophobic/superoleophilic paper\ncan be prepared by layer-by-layer assembly and polydimethylsiloxane\n(PDMS) modification, and the SPs exhibited good separation efficiencies\nof >99% for oil/water mixtures even after 30 cycles. 9 Herein, we summarize recent advances of SPs in\nterms of\ndesign, preparation, and properties. Then, the oil/water separation\napplication of SPs as well as corresponding mechanisms is discussed.\nDue to the excellent separation properties of oil/water mixtures (or\nemulsions), the low-cost, sustainable, and recyclable SPs become promising\ncandidates for the treatment of oily wastewaters."
} | 1,658 |
36844545 | PMC9948220 | pmc | 1,360 | {
"abstract": "The development of triboelectric nanogenerators (TENGs)\ntechnology\nhas advanced in recent years. However, TENG performance is affected\nby the screened-out surface charge density owing to the abundant free\nelectrons and physical adhesion at the electrode-tribomaterial interface.\nFurthermore, the demand for flexible and soft electrodes is higher\nthan that for stiff electrodes for patchable nanogenerators. This\nstudy introduces a chemically cross-linked (XL) graphene-based electrode\nwith a silicone elastomer using hydrolyzed 3-aminopropylenetriethoxysilanes.\nThe conductive graphene-based multilayered electrode was successfully\nassembled on a modified silicone elastomer using a cheap and eco-friendly\nlayer-by-layer assembly method. As a proof-of-concept, the droplet-driven\nTENG with the chemically XL electrode of silicone elastomer exhibited\nan output power of approximately 2-fold improvement owing to its higher\nsurface charge density than without XL. This chemically XL electrode\nof silicone elastomer film demonstrated remarkable stability and resistance\nto repeated mechanical deformations like bending and stretching. Moreover,\ndue to the chemical XL effects, it was used as a strain sensor to\ndetect subtle motions and exhibited high sensitivity. Thus, this cheap,\nconvenient, and sustainable design approach can provide a platform\nfor future multifunctional wearable electronic devices.",
"conclusion": "Conclusions In summary, the graphene-based electrode\nwith silicone elastomer\nfilms was successfully XL by a hydrolyzed APTES solution. The graphene-based\nmultilayer electrode was coated on modified silicone elastomer films\nusing a layer-by-layer assembly method. The ATR/FT-IR spectral analysis\nand fluorescence labeling confirmed the modified silicone elastomer\nsurface. The W-TENG with a chemically XL electrode of silicone elastomer\nexhibited an output power of approximately twice that without XL.\nFurthermore, this chemically XL conductive silicone elastomer film\nexhibited remarkable stability under repeated mechanical deformation\nand obtained 12, 18, and 102 V for twisting, bending, and tapping\nwith fingertips and charged capacitors in seconds. In addition, we\ndemonstrated these chemically XL films as a strain sensor to detect\nsubtle movement and exhibited high sensitivity. Therefore, this improved\nperformance and sensitivity of conductive XL silicone elastomer film\nassembly approach can be an excellent choice for wearable electronics\nin the future.",
"introduction": "Introduction Technology is considerably improving the\nquality of our lives through\nportable and wearable technological gadgets. 1 In this regard, triboelectric nanogenerators (TENGs) have sparked\nmuch attention as new mechanical energy scavenger that generates electricity. 2 , 3 TENGs have been successfully shown in various applications with\nadvantages such as high electrical output power, high material selection,\nlightweight, and great adaptability to varied applications. 4 − 7 Despite the success of using a variety of coating processes\nto\ncreate TENG devices, 8 − 11 challenges still need to be solved before these approaches can be\ncommercialized, including the cost of tribomaterial (TM) fabrications\nand sustainable power sources. 12 − 15 Furthermore, as stated in previous reports, 16 , 17 several approaches have been tried to improve the performance of\nTENGs. However, the surface charge density screened out still needs\nto be solved, caused by factors such as an abundance of free interfacial\nelectrons 16 , 18 , 19 and physical\nadhesion at the electrode–TM interface. Particularly, the latter\nstill needs to be taken into account. As a result, the electrical\nstability and conductivity of electrodes adhering to TMs was impaired,\naffecting TENG performances. In addition, attachable wearable electronic\ndevices require the substitution of stiff electrodes with soft and\nstretchable elastomeric electrodes because elastomeric films can withstand\nrepeated mechanical deformations such as bending, twisting, and stretching. 20 − 23 This study introduces chemically cross-linked (XL) electrodes\nwith\nsilicone elastomer films (polydimethylsiloxane (PDMS) and dragon skin\n(DS)) to preserve the surface charge density and improve the TENG\nand sensitivity performances. We considered silicone elastomeric films\nbecause of their high flexibility, softness, optical transparency,\nbiocompatibility, and ease of fabrication. 23 , 24 However, the hydrophobicity and the low surface energy of silicone\nelastomers made it difficult to interact with other species. Various\nmethods, such as chemical and energy manipulation, have been developed\nto manipulate the surface energy of silicone elastomers. 24 − 28 Here, we presented a quick and easy method for surface modification\nby one-time dipping in a hydrolyzed 3-aminopropylenetriethoxysilanes\n(APTES) solution at room temperature. The chemical interaction between\nsilicone elastomer substrates and hydrolyzed APTES solution containing\namine-functional groups was confirmed using attenuated total reflectance\nFourier-transform infrared spectroscopy (ATR/FT-IR) and fluorescent\nlabeling. The conductive graphene-based multilayer electrode\nwas assembled\non a modified silicone elastomer surface using electrostatic interactions.\nSelf-assembled electrodes were fabricated based on poly(vinyl alcohol)\n(PVA), graphene nanoplatelets (GNP), and polystyrene sulfonic acid\n(PSS; denoted as GL = [PVA/GNP-PSS] n ).\nTo clarify, the newly protonated amine groups in the APTES-modified\nsilicone elastomeric film chemically interacted with the first monolayer\nof the negatively charged PVA moieties. Then, it was followed by LbL\nself-assembly to form the GNP-PSS coating via H-bonding. 29 − 32 The three BL GL electrode was selected and coated owing to its thickness\nof ∼30 nm and TENG output of ∼4 μA and ∼100\nV. 31 Water droplet-based TENG (W-TENG)\nwas used to assess the performance\nof silicone elastomer films with and without chemical XL electrodes.\nDue to higher surface charge density, the chemically XL silicone elastomer\nfilms exhibited higher W-TENG performances than the uncross-linked\nsilicone elastomer films. This result confirmed the screened-out surface\ncharge density for physically attached TM, but chemically XL TMs with\nelectrodes maintained the surface charge density. Furthermore, a strain\nsensor of the silicone elastomer films with and without chemical XL\nelectrodes was employed by measuring their resistance change (Δ R / R o ) under cyclic stretching\nand releasing. As a result, the chemical XL electrode silicone elastomers\ndisplayed less change in relative resistance to the applied strain\nthan the uncross-linked films. Moreover, the conductive XL-PDMS film\ndemonstrated a significant output performance against repeated mechanical\ndeformations such as twisting, bending, and tapping. Therefore, we\npresented straightforward, reproducible, and high-performance chemically\nXL TMs with electrodes as a platform for future wearable electronics.",
"discussion": "Results and Discussion Preparation and Characterization of Silicone Elastomer Films Due to its excellent flexibility, softness, optical transparency,\nand biocompatibility, silicone elastomer film is a promising material\nfor wearable electronics. 23 , 24 PDMS and DS films were\nprepared using a straightforward casting procedure, as illustrated\nin Figure 1 . After\nsuccessfully modifying a silicone elastomer substrate with hydrolyzed\nAPTES solution containing amine-functional groups, it chemically interacted\nwith the first monolayer of the negatively charged PVA moieties. Then,\nan ultrathin 3 BL [PVA/GNP-PSS] 3 electrode film was fabricated\nvia LbL self-assembly ( Figure 1 ). 29 − 32 Figure 1 Schematic\nillustration of chemically cross-linked conductive silicone\nelastomer film fabrication. The peeling tape test was performed to assess the\nmechanical robustness\nof the conductive XL-silicone elastomer surface. According to the\nscheme illustrated in Figure S1a , the conductive\nXL-PDMS surface was considered for the tape peeling test with cyclic\nadhesion and detachment operations by the tape. A weight of 450 g\nwas applied to the tape to provide tight adhesion between the coated\nsurface and the strong tape (see the photograph of the tape peeling\ntest in Figure S1b ). First, the tape was\nattached to the conductive XL-PDMS surface, and 450 g of weight was\nrolled on the sturdy tape while it oscillated. Next, the strong tape\nwas removed from the conductive XL-PDMS surface. This adhesion and\npeeling process was conducted for 100 cycles. After 100 cycles, a\ntiny quantity of coated constituents peeled off. So, we performed\na single-electrode TENG test to ensure the film withstands its performance\nby tapping with fingertips. A total of 38 green LEDs were successfully\nlit up ( Figure S1c and Supporting Information Video S1 ) and exhibited a slight decrease\nin output voltage (<5%) compared with before the peeling test ( Figure 1Sd ). This result demonstrated good mechanical\nstability of the chemically XL electrode silicone elastomer layer. The surface morphologies of silicone elastomers, PDMS, and DS families\nwere observed using optical microscopy, as shown in Figure 2 a. The PDMS film shows a rougher\nsurface than the DS film, whereas the surface of the DS film was smoother\nand denser. Similarly, the 2D atomic force microscope (AFM) images\nshow the same surface features ( Figure 2 b). In addition, the average surface roughness values\nof DS and PDMS films were 0.097 and 0.295 μm, respectively,\nsupporting that the DS coating was relatively smooth, as observed\nfrom surface imaging. Figure 2 (a) Optical microscopic images of PDMS and DS films, (b)\n2D AFM\nsurface morphologies of PDMS and DS films, (c) water contact angles\nof PDMS and DS films at room temperature, (d) UV–vis light\nabsorbance spectra of PDMS and DS films (the inset is the UV–vis\nlight transmittance spectra of PDMS and DS films), and (e) stress–strain\ncurves of PDMS and DS films determined through the tensile test (inset:\ntensile DS sample with a strain value of 300%). The hydrophobicity of each silicone elastomer film\nwas observed\nby measuring the contact angle under 30% humidity and using a 5 μL\ndroplet of DI water at 27.5 °C for each sample. As shown in Figure 2 c, the water contact\nangles of PDMS and DS were 113.1° and 109.7°, respectively.\nThe PDMS film demonstrated a more hydrophobic surface than the DS\nfilm due to its roughness. 17 , 33 Furthermore, UV–vis\nlight spectral analysis of silicone elastomer films exhibited that\nthe PDMS film was more transparent than the DS film ( Figure 2 d). Additionally, to demonstrate\nthe silicone elastomer film’s stretching and deforming ability,\nthe tensile stress–strain relationship of the film was conducted\nusing the ASTM D412 Type C standard test, as shown in Figure 2 e. As the inset demonstrates\nduring elongation, DS film exhibited a higher elongation at break\nthan PDMS film, but the PDMS film exhibited greater strength than\nthe DS film. However, both qualities are important for TENG performance\nand various applications. 25 , 26 ATR/FT-IR spectra\nof PDMS and DS were performed with and without\nAPTES in order to verify the APTES modifications. All characteristic\npeaks associated with silicone elastomeric films were observed ( Figure 3 a and b). The common\nsignals appeared at 785 cm –1 (Si-CH 3 ),\n1079–1007 cm –1 (Si–O–Si), 1259–785\ncm –1 (Si–CH 3 ), and 2962 cm –1 (CH 3 ). However, the modified silicone\nelastomer film exhibited two characteristic peaks attributed to APTES\nobserved at 1629 cm –1 (N–H bending) and 3375\ncm –1 (N–H stretching). Accordingly, it is\nassumed that the hydrolyzed APTES molecules chemically interacted\nwith the silicone elastomer surface before undergoing a condensation\nreaction to generate the grafted elastomer surface. 27 , 34 − 38 Figure 3 (a)\nATR/FT-IR spectra of pristine PDMS and DS, (b) ATR/FT-IR spectra\nof PDMS and DS films functionalized with APTES, (c) top view of fluorescence\nlabeling of pristine PDMS and DS films, and (d) top view of fluorescence\nlabeling of PDMS and DS films functionalized with APTES (inset: cross\nsections of functionalized PDMS and DS films). The modified silicone elastomer surface was subjected\nto an APTES\ninteraction to fluorescence labeling using rhodamine B. The fluorescence\nof functionalized surfaces is highly effective and helpful for detecting\nsurface APTES. 24 , 39 As shown in Figure 3 c and d, the modified silicone\nelastomer strips surpassed the intensity of the pristine silicone\nstrips more than twice, showing a significant concentration of APTES\non the modified silicone elastomer surface, evidence of a well-functionalized\nsurface. Additionally, the cross-sectional views show the presence\nof APTES-treated silicone elastomer surfaces ( Figure 3 d). Moreover, the UV–vis absorbance\nspectra of functionalized PDMS and DS films also show an increase\nin absorbance spectra owing to the presence of APTES ( Figure S2a ). As a result, these surface alterations\nfacilitated a simple fabrication method by lowering surface degradation\nand reversion, impeding charge coupling, and enabling simple attachment\nof ultrathin films to the modified surface. Performance Analysis of Silicone Elastomer Films The\nsurface charge density produced on the TM surface dominates the output\npower of TENGs. However, the surface charge density was screened out\nby factors such as the abundance of free interfacial electrons and\nphysical adhesion at the electrode–TM contact. 16 , 18 , 19 Thus, as shown in Figure 4 a,i, these screening issues\ncan be avoided by employing chemical XL electrodes with TMs. Thus,\nwe propose that the surface charge density of TENGs with chemically\nXL electrodes with silicone elastomer films can be preserved and increase\nthe output power ( Figure 4 a,ii), which can also completely replace stiff electrodes. 20 − 23 , 40 Figure 4 (a) Schematic illustration of charge preserving\nmechanism of silicone\nelastomer films with and without chemically cross-linking electrode,\n(b) TENG power generation mechanism of the water droplet mode (i–iv),\nand (c,d) output voltage and current of W-TENGs with and without chemical\ncross-linking of conductive PDMS and DS films. To demonstrate our concept, a W-TENG device was\nemployed to assess\nthe performance of physical and chemical XL electrode silicone elastomer\nfilms. 41 As shown in Figure 4 b, water droplets continuously fall on the\nsilicone elastomer surfaces. The contact electrification between the\nwater droplet and the silicone elastomer surface created negative\ncharges and opposite charges on the bottom electrode ( Figure 4 b,i). First, the induced charges\nwere distributed to the bottom electrode as the water droplet settled\non the surface before spreading over it. The droplet then came into\ncontact with the top electrode ( Figure 4 b,ii). Then, electrons flowed from the top electrode\nto the bottom electrode until the potential difference was balanced\n( Figure 4 ,iii). Once\nthe droplet reached the maximum limit, it contracted and got away\nfrom the film. As the water droplet contracted, its spreading area\nshrank, so opposite charges were induced on the bottom electrode to\nbalance the negative charges on the silicone elastomer surface, resulting\nin opposite peak signals ( Figure 4 ,iv). Steps i–iv were repeated to generate the\nAC output power of the W-TENG device. Based on this mechanism, the\nelectrical output performance of silicone elastomer films with and\nwithout a chemical XL electrode was conducted under fixed working\nconditions (i.e., a flow rate of 26 mL/min with tubing cross-section\nof L/S 16 and contact area of 2 × 3 cm 2 ). As\nshown in Figure 4 c\nand d, the chemically XL electrode silicone elastomer films exhibited\nhigher W-TENG performances in terms of voltage and current than the\nuncross-linked silicone elastomer films. This increase in output power\noccurred due to the enhanced surface charge density of chemically\nXL electrode silicone elastomers. In contrast, the physical adhesion\ncondition created the gap between the TM and electrode interface,\nyielding surface charge density screened out and lowered results.\nIn addition, the PDMS films showed higher TENG output power than DS\nfilms, owing to their surface morphology features such as a higher\nroughness and contact angle ( Figure 2 ). 17 Subsequently,\nthe strain sensor performance, Δ R / R o , with and without chemical XL conductive\nsilicone elastomer films was measured during cyclic stretching and\nreleasing of the index finger. Figure 5 a and b show that films without XL display larger Δ R / R o values than those with\nchemical XL. The PDMS and DS films coated without chemical XL demonstrated\nan exponential increase in Δ R / R o due to the gap length created by physical adhesion.\nFurthermore, because of the lower sheet resistance and higher conductivity\n( Figure S2b ), the conductive XL-PDMS film\nexhibited a smaller change in Δ R / R o than the XL-DS film. Nevertheless, owing to its more\nsignificant elongation at break, the conductive XL-DS film was selected\nfor further analysis and attached to various body parts ( Figure 2 d), exhibiting the\nimproved capacity to withstand the high strain. 42 As a result, significant signal changes were observed under\ncyclic stimuli of stretching and releasing, except a considerable\nstrain was applied in the film attached to the knee and obtained a\nrelatively higher Δ R / R o value ( Figure S3 and Supporting Information Video S2 ). 43 Figure 5 (a,b) The strain sensor shows relative resistance changes\nduring\ncyclic stretching and releasing with and without cross-linking of\nPDMS and DS films with the electrode, respectively, and (c,d) relative\nresistance change and gage factor calculated from the equation of k ε = Δ R / R o for conductive cross-linked DS films under different strains\nof 15%, 20%, and 25%, respectively. Furthermore, the effect of varying strains of 15%,\n20%, and 25%\nwas evaluated for conductive DS films ( Figure 5 c). As a result of the strain applied, cracks\nappeared on the graphene layer, as illustrated in Figure S4 . The electrical resistance increased due to the\nfracture, indicating a partial breakdown of the electrical channels\non the graphene layer. 42 , 44 Figure S4 showed that the size of the crack grew with the increasing strain,\nleading to a larger Δ R / R o at higher strain ( Figure 4 c). Likewise, the sensitivity of the sensors was compared\nusing the gauge factor, k , calculated from the equation\nof k ε = Δ R / R o , where ε, Δ R , and R 0 represent the applied strain, resistance change\nwith strain, and initial resistance without strain, respectively. 42 At a lower strain of 15%, the DS film showed\nlower sensitivity ( k = 20), but at a strain of 25%,\nit showed higher sensitivity ( k = 39; Figure 5 d). Inspired by this result,\nwe demonstrated this ultrathin conductive XL-DS film as a mechanically\nresponsive strain sensor of a topographic scanner. As a topographic\nscanner, the XL-DS film was used to detect the cylinders, as shown\nin a photographic image ( Figure S5 ). As\na cylinder passed through the model scanner, the film was bent and\nwarped, resulting in a band of Δ R / R o signals ( Figure S5a ). As\nmore cylinders passed, the Δ R / R o signal band and bending angle also widened ( Figure S5b and S5c , and Supporting Information Video S3 ). Therefore, the chemically XL conductive\nsilicone elastomer films can be used as a flexible wearable strain\nsensor to detect delicate motions. To further provide the performance\nvariation between conductive\nsilicone elastomer films with and without chemical XL, we charged\na 10 μF capacitor using a single-electrode mode TENG after rectification.\nThe test results exhibited that the charging amount steadily increased\ninitially, then the increasing rate gradually decreased and finally\nstabilized. As shown in Figure 6 a, the chemically XL electrode silicone elastomer film exhibited\na higher charging capacity than without chemically XL films. This\nresult demonstrated that the chemically XL TM with the GL electrode\nhelps to maintain the charge density, thereby increasing the efficiency\nof the nanogenerator. Figure 6 (a) Charging capacitors with and without chemical cross-linking\nof PDMS and DS films with the electrode and (b) photographs and output\nvoltages of the conductive cross-linked PDMS-based TENG under twisting,\nbending, and tapping. Finally, we used chemically XL electrode PDMS film\nto assess TENG\nperformances under various forms of deformation, and Al film (80-μm-thick)\nwas used as a counter TM. Energy harvesting occurred under repeated\ncontact and separation, as shown in Figure 6 b, which exhibited 12, 18, and 102 V for\ntwisting, bending, and tapping, respectively. Thus, the chemically\nXL electrode silicone elastomer film could withstand high strain under\nrepeated contact and separation, which allowed for stable power generation\neven when the device was highly deformed."
} | 5,252 |
22215088 | PMC3272573 | pmc | 1,361 | {
"abstract": "To utilize biofilms for chemical transformations in biorefineries they need to be controlled and replaced. Previously, we engineered the global regulator Hha and cyclic diguanylate-binding BdcA to create proteins that enable biofilm dispersal. Here we report a biofilm circuit that utilizes these two dispersal proteins along with a population-driven quorum-sensing switch. With this synthetic circuit, in a novel microfluidic device, we form an initial colonizer biofilm, introduce a second cell type (dispersers) into this existing biofilm, form a robust dual-species biofilm and displace the initial colonizer cells in the biofilm with an extracellular signal from the disperser cells. We also remove the disperser biofilm with a chemically induced switch, and the consortial population could tune. Therefore, for the first time, cells have been engineered that are able to displace an existing biofilm and then be removed on command allowing one to control consortial biofilm formation for various applications.",
"discussion": "Discussion We developed a synthetic μBE system by combining a QS signalling module with two of our engineered biofilm dispersal proteins. With this synthetic circuit, in a microfluidic channel, we formed an initial colonizer biofilm with cells tagged red, introduced a second cell type (dispersers, tagged green) into this existing biofilm, created a means of communication between the two cell types and formed a robust biofilm with the disperser cells in an existing initial colonizer biofilm. We then displaced the initial colonizer cells in the biofilm with a QS signal from the disperser cells, and removed the disperser cells with a chemically induced switch. Our work demonstrates that biofilms can be formed, that new cells may be engineered to integrate and then replace the initial colonizer biofilm, and that both cell types may be removed, which is a promising strategy for applications requiring different kinds of engineered cells such as creating a biorefinery. Although some of the biofilms may be dispersed naturally upon changes in environmental conditions (for example, nutrition level and oxygen depletion) 39 , it is a significant challenge to remove biofilms 40 41 as cells in biofilms are cemented in place by the secreted polymer matrix consisting of polysaccharide, protein, DNA and lipids 1 . The matrix holds bacterial cells together and forms a protective barrier that confers resistance to killing by nonspecific and specific host defenses during infection and that confers tolerance to various antimicrobial agents such as disinfectants and antibiotics 1 . Thus, the defensive nature of the biofilm colony makes most biofilms difficult or impossible to eradicate 39 ; hence, our demonstration that both the initial colonizer and disperser biofilms may be nearly completely removed is significant. To preferentially remove one type of cell in a biofilm, our system requires that the second cell type elicits robust growth such that it can attach to the existing biofilm and propagate, that it flourishes, that it communicates to the other cell type via a QS signal, and that it displaces the existing biofilm without itself being displaced so that it instead forms a strong biofilm. Here, we produced the QS signal in the biofilm itself to remove the initial colonizer cells. As the signal accumulated, the engineered BdcA in the initial colonizer cells reduces c-di-GMP levels, which results in a cascade of events, such as an increase in motility and reduction in adhesion production, that allows the initial colonizer cells to disperse 16 . As the initial colonizer cells disperse, the disperser cells must form a robust biofilm. After the disperser biofilm is formed, the engineered Hha protein, once induced, causes dispersal by inducing cell lysis 15 . Therefore, our synthetic μBE system provides a useful platform for the removal of existing deleterious biofilms via generating signalling molecules in situ . In addition, as the disperser cells grow more slowly than the initial colonizer ones, the disperser cells cannot displace the initial colonizer biofilm based on a difference in growth rates. This clearly demonstrates that a QS circuit was required to complete this feat of progressive biofilm development/dispersal. As several biofilm dispersal signals have been identified including the auto-inducing peptide of the agr QS system of Staphylococcus aureus 42 , changes in carbon sources 43 , reduction in the concentration of c-di-GMP 16 (as utilized here with BdcA), surfactant 44 , cis -2-decenoic acid 45 , as well as D -amino acids 46 , we envision that other biofilm dispersal mechanisms may also be utilized to control biofilms. The μBE device described here offers several advantages over the commercially available BioFlux device developed by Benoit et al . 47 and other microfluidic devices used for biofilm study 48 . With our device, we can precisely control the development of biofilm by intermittent flow of nutrients, completely isolate the biofilm from the media inlet and gradient-generating channels using the pneumatic valves, and sequentially introduce different cell types into the biofilm chamber. Of course, the ability to study a range of concentrations simultaneously with the eight channels (for example, Fig. 3c,d ) was instrumental in analysing the effect of various concentrations of 3 o C12HSL and IPTG. Bacterial QS systems have the attractive design features that they utilize diffusible signals 20 . Here we show, for the first time, that a QS system may be utilized with biofilm dispersal proteins to control consortial biofilm formation; that is, that an existing biofilm may be formed and then replaced by another biofilm, which then may be removed. These types of synthetic QS circuits may be used to pattern biofilms by facilitating the reuse of platforms and to create sophisticated reactor systems that will be used to form biorefineries. Although it may not be needed in practice to remove one biofilm with another, we chose to show this may be accomplished in order to show in principle that biofilms may be controlled; that is, that biofilms may be dispersed and that consortia populations may be controlled such that complex synthetic biocatalysis may be performed. Furthermore, these systems may be adopted in industrial and clinical processing as an alternative strategy to overcome the current limitations of biofilm control."
} | 1,610 |
20573513 | null | s2 | 1,362 | {
"abstract": "The expression of many bacterial phenotypes is regulated according to the concentration of chemical cues that they or other bacteria produce, a process often termed quorum sensing (QS). Many aspects of the environment can affect cue concentration. Thus these molecules might be indirect proxies for any one or combination of environmental factors. Recent research suggests that the adaptive significance of QS varies depending on its evolutionary and ecological context. Consequently, some researchers have proposed new terms, each emphasizing different adaptive functions, for the QS process. However, these new terms generate potential for a semantic quagmire and perpetuate the questionable notion that we can identify a single, dominant environmental feature to which the microbes respond. In fact, the ecological context of QS regulation, like the process itself, is complex and impacted by multiple aspects of natural environments."
} | 234 |
25096883 | PMC4128364 | pmc | 1,363 | {
"abstract": "ABSTRACT Biofilms are densely populated communities of microbial cells protected and held together by a matrix of extracellular polymeric substances. The structure and rheological properties of the matrix at the microscale influence the retention and transport of molecules and cells in the biofilm, thereby dictating population and community behavior. Despite its importance, quantitative descriptions of the matrix microstructure and microrheology are limited. Here, particle-tracking microrheology in combination with genetic approaches was used to spatially and temporally study the rheological contributions of the major exopolysaccharides Pel and Psl in Pseudomonas aeruginosa biofilms. Psl increased the elasticity and effective cross-linking within the matrix, which strengthened its scaffold and appeared to facilitate the formation of microcolonies. Conversely, Pel reduced effective cross-linking within the matrix. Without Psl, the matrix becomes more viscous, which facilitates biofilm spreading. The wild-type biofilm decreased in effective cross-linking over time, which would be advantageous for the spreading and colonization of new surfaces. This suggests that there are regulatory mechanisms to control production of the exopolysaccharides that serve to remodel the matrix of developing biofilms. The exopolysaccharides were also found to have profound effects on the spatial organization and integration of P. aeruginosa in a mixed-species biofilm model of P. aeruginosa-Staphylococcus aureus . Pel was required for close association of the two species in mixed-species microcolonies. In contrast, Psl was important for P. aeruginosa to form single-species biofilms on top of S. aureus biofilms. Our results demonstrate that Pel and Psl have distinct physical properties and functional roles during biofilm formation.",
"introduction": "INTRODUCTION Bacteria form surface-attached biofilm communities in nature and are significant in the context of environmental sustainability and health care ( 1 , 2 ). Integral to the biofilm is a matrix of extracellular polymeric substances (EPS). The EPS form a heterogeneous viscoelastic material that holds the microbial cells together and account for 50 to 90% of the total organic matter in the biofilm ( 3 ). Division of labor in metabolism, gene transfer, and quorum sensing are facilitated in the biofilm because the matrix is responsible for maintaining the spatial organization of cells in the biofilm ( 4 , 5 ). The EPS are largely composed of polysaccharides, proteins, nucleic acids, humic acids, and lipids and determine the architecture of the biofilm ( 6 ). For example, biofilms assume many, often highly differentiated forms during development, including mushroom-like microcolonies and filamentous streamers, as well as a homogenous, undifferentiated layer of cells. The physical properties of the matrix determine the shape and mechanical stability of biofilms ( 7 , 8 ) and affect processes such as mass transfer and detachment kinetics of the various differentiated forms. For example, EPS shearing can form sieve-like networks that result in rapid accumulation of cells and other dispersed biomass that results in the formation of biofilm streamers ( 9 ). Sloughing and dispersal via the detachment of streamer tails from biofilms depend on the mechanical failure of the EPS ( 8 ). The EPS matrix also responds to the chemical composition of the environment, where osmotic pressure gradients have been shown to be responsible for the surface spreading of biofilms ( 10 ). Finally, the physical response of biofilms to flow has been shown to have an impact on community composition and succession ( 11 ). Despite many such observations of its importance, quantitative descriptions of the physical properties of the matrix and its impact on biofilm architecture and composition are limited. Pseudomonas aeruginosa is an opportunistic pathogen that causes a wide range of hospital-acquired infections ( 12 ). P. aeruginosa has also been found to coexist with Staphylococcus aureus in the lungs of cystic fibrosis patients and in chronic wounds ( 13 , 14 ). P. aeruginosa is known to produce three different exopolysaccharides that can potentially be components of the biofilm matrix. Alginate, which consists mainly of mannuronic and guluronic acid residues, is often overexpressed in P. aeruginosa strains isolated from chronically infected cystic fibrosis patients ( 15 ). Alginate overexpression protects P. aeruginosa from host immune responses and antibiotics ( 16 ) and gives the biofilm a mucoid phenotype. However, alginate was shown not to be essential for biofilm structure maintenance ( 17 ). Psl and Pel have been found to play important roles in biofilm formation ( 18 , 19 ). Psl and Pel have overlapping structural roles, and deletions of both genes in the laboratory strain PAO1 significantly impair biofilm formation ( 20 , 21 ). The structures of Psl and Pel have yet to be fully elucidated, but carbohydrate analyses indicate that Psl is mannose and galactose rich and Pel is glucose rich ( 18 , 19 ). Studies have indicated that Psl can wrap itself around P. aeruginosa cells to thus contribute to cell surface attachment and microcolony formation ( 22 , 23 ). However, the contribution of Pel to the biofilm life cycle in P. aeruginosa strains that contain both the pel and psl operons remains unclear. Particle-tracking microrheology is an optical technique that measures the rheological properties by tracking the Brownian motion of spherical probes or particles within the sample ( 24 , 25 ). The mean squared displacement (MSD), 〈Δ r 2 ( t )〉, of the particles undergoing Brownian motion over time, t , is related to the mechanical properties of the substance in which the particles are suspended according to 〈Δ r 2 ( t )〉 α t α where α = 1 for viscous fluids, 0 < α < 1 for viscoelastic substances, and α = 0 for elastic substances. Viscous fluids show irreversible deformation to stress, whereas elastic materials return to their original shape after the removal of stress. The MSD is directly proportional to and can be used to calculate the creep compliance of the material, which is the tendency of the material to deform permanently over time. Low MSD values and high elasticity are a consequence of high degrees of polymeric cross-linking (i.e., effective cross-linking) ( 26 , 27 ). Such cross-linking can be chemical through covalent bonds, or physical from noncovalent interactions, such as ionic and hydrogen bonds ( 28 , 29 ) and topological constraints from entanglements of polymer chains ( 30 ). Previous microrheological experiments have mapped the mechanical properties of biofilms according to the height and location within the flow cell ( 31 , 32 ). However, the difference in rheological properties of specific biofilm structures, such as the microcolonies or undifferentiated regions, was not investigated. Furthermore, a direct link between the molecular components of the matrix and local biofilm rheology and function has not yet been established. In this study, particle-tracking microrheology, in combination with confocal laser scanning microscopy, was used to characterize the local viscoelasticities of P. aeruginosa biofilms at different stages of development. The contributions of Pel and Psl exopolysaccharides to biofilm rheology during development were investigated in P. aeruginosa strains with the clinically relevant mucoid phenotype that expresses the combination of the three exopolysaccharides (Alg + Pel + Psl + ) and mutant derivatives (Alg + Pel + Psl − , Alg + Pel − Psl + , and Alg + Pel − Psl − ) ( 33 ). To assess the rheological roles of Pel and Psl in the absence of alginate, nonmucoid P. aeruginosa strains expressing a combination of Pel and Psl exopolysaccarides (Alg − Pel + Psl + , Alg − Pel − Psl + , and Alg − Pel + Psl − ) ( 20 ) were also investigated ( Table 1 ). This allowed the rheological impact of exopolysaccharides to the biofilm in the context of population and community behavior to be explored using single-species P. aeruginosa streamer as well as P. aeruginosa-S. aureus mixed-species biofilm assays. TABLE 1 Characteristics of the strains used in this study Phenotype Genotype Description Alg + Pel + Psl + ΔmucA Overexpresses alginate, wild type Alg + Pel − Psl + ΔmucA ΔpelA Overexpresses alginate, no Pel Alg + Pel + Psl − ΔmucA ΔpslBCD Overexpresses alginate, no Psl Alg + Pel − Psl − ΔmucA ΔpelA ΔpslBCD Overexpresses alginate, no Pel and Psl Alg − Pel + Psl + PAO1 Minimal or no alginate, wild type Alg − Pel − Psl + ΔpelA Minimal or no alginate, no Pel Alg − Pel + Psl − ΔpslBCD Minimal or no alginate, no Psl",
"discussion": "DISCUSSION Microrheological techniques can provide a more quantitative description of how different matrix components contribute to the rheology and function of biofilms. Specifically, particle-tracking microrheology was employed to study the contributions of Pel and Psl exopolysaccharides to the rheological properties of the biofilm matrix. We show here that that Psl favors the development of elastic biofilms with highly effective cross-linking, whereas Pel favors viscoelastic and loose biofilms. Biofilms expressing exclusively either Psl or Pel do not appear to change significantly in rheological properties over time. However, when both exopolysaccharides are produced, the biofilm becomes less effectively cross-linked within the mature parts of the biofilm, consistent with a shift in production of the dominant polysaccharides from Psl to Pel. The reduction in effective cross-linking could be due to a reduction in the expression, release, or degradation of surface-bound Psl at the microcolony center prior to dispersal ( 22 ). While the generation of a Psl matrix-free cavity also probably occurs in Pel − Psl + strains, the absence of Psl could have resulted in a complete loss of biofilm and fast dispersal and expulsion of particles without Pel supporting the matrix. Thus, Psl contributes to a stiffer matrix during the initial stages of biofilm development, and Pel increases in contribution to and remodels the matrix into a more malleable structure at the later stages. P. aeruginosa is known to use multiple regulatory systems to control the synthesis of different EPS components during growth ( 4 , 38 ), and the variation between Psl expression and Pel expression may represent an important adaptation strategy of P. aeruginosa in dynamic and fluctuating environments. We postulate that because young biofilms are thinner and less robust, a more cross-linked and elastic matrix that is relatively more resistant to external mechanical shear forces, such as brushing and rapid flows, is expressed. This would prevent cells from dispersing and thus centralize growth to the newly attached site when the biofilm has just been established and is less populated. After the biofilm has matured and is fully populated, Pel could be used to remodel the matrix to yield a more viscous biofilm. Unlike elastic materials that return to their original shape after stress is removed, viscous materials deform irreversibly when exposed to stress and hence can flow. Thus, a viscous biofilm can more effectively spread laterally to colonize new areas. We have functionally validated the above hypothesis by growing the biofilm on a steel mesh to promote an alternative, bioprocess-relevant, biofilm morphology (i.e., that of streamers). Streamer formation is dependent on the malleability of the EPS of surface-attached biofilms and can cause rapid disruption of flow in industrial and medical systems ( 9 ). Biofilms expressing the Psl polysaccharide initially form a strongly surface-attached rough biofilm. When the Pel polysaccharide was also expressed, surface spreading of the biofilm was enhanced during maturation. Without the Pel polysaccharide, the biofilm spreads minimally and resists streamer formation. As the biofilm matures, it develops tall, rigid colonies. Expression of Pel in the absence of Psl polysaccharide results in extensive streamer formation that eventually fills the spaces between the mesh. The rheological roles of Pel and Psl in regulating species integration within a dual-species biofilm model were also explored. In cocultures with S. aureus , Pel was required to form mixed-species biofilms with S. aureus at the substratum. Increased loosening and malleability of the P. aeruginosa matrix imparted by Pel may have allowed for S. aureus to infiltrate and associate with P. aeruginosa to produce an integrated, mixed-species biofilm. Alternatively, the loosening of the matrix by Pel may have allowed for P. aeruginosa to interact and become incorporated with the S. aureus matrix ( 39 ). Psl expression favored species segregation and formed monospecies microcolonies of P. aeruginosa and S. aureus . The high effective cross-linking in the P. aeruginosa matrix conferred by Psl may have presented a physical barrier that did not allow for interaction with S. aureus strain. Without both polysaccharides, P. aeruginosa outcompeted the S. aureus in the form of tiny cell clusters spread across the substratum. Thus, the entrapment of P. aeruginosa into microcolonies by Psl appeared to provide more substratum space for S. aureus to colonize and establish a biofilm. Psl was also found to be important for dominance of monospecies P. aeruginosa biofilms at the upper layer of the biofilm and could result from Psl facilitating upward growth and microcolony expansion in P. aeruginosa biofilms. We therefore suggest a new model for P. aeruginosa biofilm remodeling in which Psl is more elastic and acts as stiff wire-like structures to build the initial biofilm architecture and support on-site growth—e.g., the enlargement of existing microcolonies. Pel is more viscous and acts to allow spreading of cells in the matrix, which would be important for expansion during the later stages ( Fig. 8 ). This complements previous studies that have shown that Psl is important for cell attachment ( 22 ), biofilm initiation, and microcolony development ( 20 , 40 ), and Pel is important for pellicle formation (non-surface-attached or floating biofilm morphology) ( 19 ). The model presented here is based upon the early creep experiments conducted on P. aeruginosa streamers ( 8 ) and suggests that Psl is responsible for constructing the firmly surface-attached streamer head, while Pel designs the loose streamer tail. Recently, a combined optical and atomic force microscopy study has revealed that Psl expression results in cells tilting upwards off the surface, while Pel expression results in P. aeruginosa cells lying flat on surfaces ( 41 ). If cell orientation impacts the growth pattern, Psl would direct cells and growth upwards, increasing microcolony height, and Pel would direct cells to grow laterally for the spreading onto new surfaces, consistent with our model. FIG 8 Schematic of P. aeruginosa streamer formation, in which Psl forms the surface-attached streamer head and Pel forms the streamer tail. Psl acts as stiff wires that build up the biofilm architecture and support on-site growth, such as the enlargement of microcolonies, whereas Pel acts as a spreader and filler important for expansion during the later stages of biofilm development. Regardless of the strain used, the microsized particles used do not penetrate the biofilm easily once formed. Instead, the particles are incorporated during the growth of the biofilm. Both particle-counting and passive microrheological experiments indicate that the biofilm exhibits a range of mesh sizes smaller than 1.0 µm. The 0.5-µm particles were apparently able to slip through the matrix in the microcolonies, indicating that the matrix mesh size is between 0.5 and 1.0 µm within the microcolonies. Drug delivery using particles to combat biofilms should also consider using particles larger than biofilm mesh size as these results indicate that they would assimilate more readily into the microcolonies than the smaller particles during biofilm growth. In conclusion, particle-tracking microrheology can be used to spatially and temporally resolve the local mechanical properties of biofilms in real time at the microscale and are effective tools for studying biofilms. Our study shows how different parts of the biofilm can be remodeled using different components of the matrix and suggests that the production of Pel and that of Psl are differentially regulated during biofilm development. The flexibility of the matrix would be an important emergent property of the biofilm resulting from microbial adaption to growth conditions. This could have consequences for P. aeruginosa to compete or cooperate with coexisting species in the biofilm. The concept of modifying the physical properties of the biofilm by using natural components of the matrix has important implications for the guided engineering and control of biofilms for health care and industrial applications—for example, by expressing an elastic and highly cross-linked matrix to limit biofilm propagation by surface spreading and streamer formation or to resist invasion or incorporation of other microbial species."
} | 4,324 |
35541105 | PMC9080522 | pmc | 1,364 | {
"abstract": "Electrospun hybrid nanofibers prepared using combinations of natural and synthetic polymers have been widely investigated in tissue engineering. In this study, silk fibroin (SF) and poly( l -lactic acid- co -ε-caprolactone) (PLCL) hybrid scaffolds were successfully prepared by electrospinning. Scanning electron micrographs (SEM) showed that SF/PLCL scaffolds were composed of defect-free nanofibers with a smooth and homogeneous fiber morphology. Water contact angle measurements demonstrated that the scaffolds were hydrophilic. To assess the cell affinity of SF/PLCL scaffolds, rabbit conjunctival epithelial cells (rCjECs) were cultured on the electrospun scaffolds. Scanning electron micrographs and in vitro proliferation assays showed that the cells adhered and proliferated well on the scaffolds. The quantitative polymerase chain reaction (qPCR) results showed excellent expression of CjEC genes, with reduced expression of inflammatory mediators. Hematoxylin and eosin (H&E) staining showed that the engineered conjunctiva constructed with SF/PLCL scaffolds consisted of 2–4 layers of epithelium. Furthermore, SF/PLCL scaffolds transplanted subcutaneously exhibited excellent biocompatibility. Therefore, SF/PLCL scaffolds may find biomedical applications in conjunctival reconstruction in the near future.",
"conclusion": "Conclusions SF/PLCL scaffolds, with high porosity and high surface area resembling the topographic features of the ECM, were successfully prepared using electrospinning techniques. Our data demonstrated that SF/PLCL scaffolds not only promoted CjEC growth and proliferation without any inflammatory reaction, but also maintained the phenotypic development of CjECs. Moreover, CjECs cultured on the scaffolds could form a stratified conjunctival epithelium including goblet cells, suggesting that SF/PLCL scaffolds may be preferable for conjunctival regeneration.",
"introduction": "Introduction The conjunctival epithelium and corneal epithelium form the outer surface of the eye, and injury to one part may result in system-wide secondary dysfunction. 1 The conjunctival epithelium, covering the ocular surface from the limbus to the posterior surface of the eyelids, is composed of a stratified non-keratinized epithelium with goblet cells, which are specialized epithelial cells. 2,3 Normal function of the conjunctiva is crucial for the integrity of the ocular surface as it can provide the mucin component of the tear film, and serve as a barrier against external stimuli. 4,5 Therefore, ocular surface reconstruction almost inevitably fails unless the conjunctival surface is first repaired and a deep fornix is restored. Although the conjunctiva has the capacity to spontaneously re-epithelialize upon injury, this is usually accompanied by a certain amount of fibrosis and wound contracture, especially in extensive disorders such as chemical/thermal burns, Stevens–Johnson syndrome, microbial infection, and ocular cicatricial pemphigoid. 6–8 In these cases, tissue engineering needs to be applied for conjunctival reconstruction. The general principle of tissue engineering is to repair or generate the damaged tissue using three-dimensional scaffolds, in combination with cells and/or growth factors to rapidly heal damaged tissue. 9 The scaffolds should be biocompatible and have similar properties to the native extracellular matrix (ECM). 10 Moreover, for each specific tissue, a scaffold should have suitable mechanical properties, a well-interconnected pore network, and an optimum pore size. 11 Among the currently known fabrication techniques, electrospinning has been shown to be an effective approach for producing nanofibrous scaffolds that facilitate cell adhesion and proliferation, and allow for an efficient exchange of nutrients and metabolites. 12,13 SF, a kind of natural protein, has been widely used in a number of biomedical applications due to its unique properties including good biocompatibility, low toxicity, and lower pro-inflammatory effects compared to collagen. 14–16 However, scaffolds made of SF alone failed to fulfil the desired mechanical characteristics, as in previous reports which showed that the pure SF nanofibrous scaffolds typically underwent brittle fracture. 12 PLCL, a copolymer of l -lactic acid and PCL, is one of the most common polymers for tissue engineering due to its good mechanical properties and tunable biodegradability, but having no natural cell recognition sites greatly limits its application in the biomedical field. 17–19 Therefore, the blending of bioactive SF with the beneficial mechanical properties of PLCL will produce a new biohybrid material which may be suitable for conjunctival reconstruction. In previous studies, we have applied SF/PLCL scaffolds for corneal endothelial reconstruction, retinal reconstruction and bone regeneration. 20–22 In this study, we attempted to employ SF/PLCL scaffolds to engineer a conjunctival equivalent. Systematic experiments were conducted to evaluate the physiochemical properties of the SF/PLCL scaffolds, and we explored the effects of SF/PLCL scaffolds on cell adhesion, viability, proliferation, inflammatory reaction and cell stratification. Based on these evaluations, we present a promising scaffold with favorable mechanical and biological properties for conjunctival regeneration.",
"discussion": "Discussion The conjunctiva is an important functional and structural component of the ocular surface, and the conjunctival epithelium secrets the mucin component of the tear film and protects the ocular surface. 28 Conjunctiva-related diseases and injuries will compromise the homeostasis and functionality of the ocular surface. In severe cases, tissue-engineering strategies could be applied for optimal reconstruction to prevent fibrosis and wound contracture, especially symblepharon. 8 A ideal scaffold used in conjunctiva engineering should exhibit the following properties: biocompatibility and biodegradability for cell attachment and proliferation, with a well-interconnected pore network to allow the transport of nutrients and metabolic waste, and ability to be well tolerated without causing inflammation or stimulating rejection. Importantly, the scaffolds should also preserve the physiological CjEC features in vivo , such as the phenotypic development containing distinctive goblet cells. 29,30 Our previous results on the wettability of the scaffold showed that the pure PLCL scaffold was hydrophobic, whereas the incorporation of SF dramatically lowered the contact angle of the SF/PLCL scaffolds. The water contact angle of the SF/PLCL (75/25) scaffold was 66.8° ± 3.2°, which is in the range of favorable water contact angles (water contact angle 50–70°) for cell attachment and proliferation. Last but not least, our previous study demonstrated that SF/PLCL scaffolds were porous nanofibrous scaffolds with high porosity and a high surface area resembling the topographic features of the ECM, to which the structure contributed nutrients and gas exchange, cell attachment and proliferation. In this study, SEM showed that the average fiber diameter of the SF/PLCL (75/25) scaffold was 215 nm ± 69 nm, which demonstrated that the average fiber diameter of around 200 nm could better promote cell attachment, proliferation, and migration. 20,31 One of the most important hallmarks of the conjunctival epithelium is the goblet cells that synthesize, store and release MUC5AC. 25,32,33 Many ocular surface defects are accompanied by goblet cell loss and/or mucin component alteration. 34 Therefore, the functional restoration of goblet cells may be a critical procedure for the reconstruction of the ocular surface. Previously, it was commonly accepted that a conjunctival epithelium cultivated in vitro can hardly develop the goblet cell phenotype. 35 However, our results showed that SF/PLCL scaffolds supported the growth and phenotypic development of goblet cells. We speculate that the advantageous effect of SF/PLCL scaffolds in supporting differentiation of goblet cells could be attributed to its electrospun fibrillar structure, which closely mimics the structure and function of the ECM, because the highly porous structure of interconnected pores provides proteins, genes, nutrients and gas exchange. Few previous studies examined whether the biomaterials could affect the secretion of pro-inflammatory factors by CjECs. IL-6, one of the most important molecules in conjunctival inflammation, was analyzed by qPCR. 2,36 The results showed that at different culture times of CjECs, there was no significant difference in IL-6 expression, indicating that SF/PLCL scaffolds might not elicit obvious inflammatory responses for conjunctival reconstruction. We also evaluated the formation in vitro and in vivo of conjunctiva tissue by seeding CjECs on the scaffolds. In vitro CjECs cultured on the scaffolds generated an epithelium 2–4 layers thick. With the extension of implantation time in vivo , the CjECs formed more and more stratification structures as observed using H&E staining. It has been reported that degradation properties play a pivotal role in the selection and design of the biomaterials. The ideal degradation speed of the scaffold should match the rate of conjunctival regeneration. 37 H&E staining showed that with the extension of the implantation time in vivo , the fibers of the scaffolds gradually degrade, and the degradation products of SF/PLCL scaffolds are amino acids from SF, and lactic acid and caproic acid from PLCL, and these are metabolizable and nontoxic. 38 Thus, these findings indicate that SF/PLCL scaffolds could promote conjunctiva formation."
} | 2,410 |
37007672 | PMC10054230 | pmc | 1,366 | {
"abstract": "ABSTRACT The traditional von Neumann architecture is gradually failing to meet the urgent need for highly parallel computing, high-efficiency, and ultra-low power consumption for the current explosion of data. Brain-inspired neuromorphic computing can break the inherent limitations of traditional computers. Neuromorphic devices are the key hardware units of neuromorphic chips to implement the intelligent computing. In recent years, the development of optogenetics and photosensitive materials has provided new avenues for the research of neuromorphic devices. The emerging optoelectronic neuromorphic devices have received a lot of attentions because they have shown great potential in the field of visual bionics. In this paper, we summarize the latest visual bionic applications of optoelectronic synaptic memristors and transistors based on different photosensitive materials. The basic principle of bio-vision formation is first introduced. Then the device structures and operating mechanisms of optoelectronic memristors and transistors are discussed. Most importantly, the recent progresses of optoelectronic synaptic devices based on various photosensitive materials in the fields of visual perception are described. Finally, the problems and challenges of optoelectronic neuromorphic devices are summarized, and the future development of visual bionics is also proposed.",
"introduction": "1. Introduction The traditional von Neumann architecture, which is the basis of modern computers, physically separates storage and computation. The data to be computed needs to be extracted from memory and transferred to a processing unit, and then the result of the processing is transferred back to the memory. This operation increases energy consumption, processing time, and the data transfer efficiency is limited [ 1 ]. Nowadays, the society is demanding how to process complex data efficiently and rapidly [ 2 ]. The von Loymann architecture is increasingly unable to support the high speed of information development. Therefore, a high-performance artificial brain-like computing system is needed to meet the increasing data volume and intelligence requirements. It is known that the human brain consists of about 10 11 neurons and about 10 15 synapses [ 3 ]. It has the advantages of high efficiency, low power consumption and autonomous cognition. Based on this, brain-inspired neuromorphic computing systems with advantages such as high parallelism and ultra-low power consumption are considered to be the ideal way to achieve efficient artificial intelligence [ 4 ]. Synapses, which exist in the biological nervous system to connect and transmit signals, have both computing and storage capabilities [ 5 ]. They can help realize various biological functions with ultra-low power consumption and high efficiency [ 3 , 6 ]. For example, in the formation of biological vision, the retina converts the perceived light signals into electrical signals, and then the synapses rapidly transmit visual information layer by layer in the neural network. The transmission from the optic nerve to the visual cortex of the brain for storage and processing consumes very little energy to form biological visual perception [ 7–11 ]. Interestingly, it has been reported that approximately 80% of the external environment information obtained by humans is collected by the eyes [ 12–15 ]. Thus the visual perceptual system becomes an important way to acquire and learn information from the external environment [ 7 ]. Therefore, constructing artificial vision systems with efficient signal processing by retina-like optoelectronic synaptic devices [ 16 ] is a promising avenue [ 17–21 ]. In recent years, the retina-inspired devices have flourished in enabling many neuromorphic functions such as learning, memory, and pattern recognition in artificial intelligence [ 22–25 ]. Such neuromorphic devices can also be beneficial in meeting the increasing demand for edge computing in the era of big data [ 17–21 ]. Optoelectronic synaptic devices mainly rely on the optical signals or combined photoelectric signals to mimic synaptic functions [ 26 ]. Compared to electrical signals, optical signals have the advantages of low computational requirements, ultra-fast signal transmission speed, and high bandwidth [ 27 , 28 ]. Therefore, optoelectronic synaptic devices are not limited by the trade-off of bandwidth connection density of neuromorphic devices using pure electrical signals [ 29–33 ]. They help broaden the bandwidth, reduce the crosstalk, and realize the ultra-fast signal processing [ 32 , 34 , 35 ]. In addition, conventional neuromorphic visual imaging systems usually consist of photodetectors that convert optical signals into electrical signals, memory units that record visual information, and processing units that process information [ 36–40 ]. The physical separation of light perception, information storage, and processing functions leads to severe consumption of energy, space, and time. In contrast, the photoelectric synapse integrates light sensing and synaptic functions. It can not only respond to light stimuli but also realize real-time processing and temporary storage of optical information in parallel [ 41 , 42 ]. This working mode effectively eliminates unnecessary consumption and is very similar to the human visual system [ 13 , 43 , 44 ]. Currently, there is a growing interest to explore these optoelectronic synaptic devices [ 45 , 46 ]. Among them, the optoelectronic two-terminal memristors [ 47–49 ] and three-terminal transistors [ 50–53 ] are promising candidates for constructing the future artificial vision systems [ 54–57 ]. In this way, artificial visual intelligence with ultra-low power consumption and ultra-high computing speed can be realized. Photoelectric synaptic memristors and transistors can tune synaptic weights by changing conductance through optical spike stimulation. It enables the realization of various synaptic visual functions, such as long-term plasticity (LTP), short-term plasticity (STP) [ 30 ], paired pulse facilitation/depression (PPF/PPD), and peak rate-dependent plasticity, etc. More importantly, the in-depth research on optoelectronic neuromorphic devices has promoted the development of electronic devices in the field of visual bionics [ 7 ]. Material science is indispensable for solving various problems faced by modern society. It has contributed greatly to the development of functional systems. Research on various functionalized materials is beneficial to promote the development of synaptic bionics, neuromorphic engineering and related artificial intelligence applications [ 58 , 59 ]. To date, a variety of different photoactive materials including MoS 2 , graphene (Gr), carbon nanotubes, metal oxides, organics, halide perovskites, and ferroelectric materials have been investigated for optoelectronic synaptic memristors and transistors [ 23 , 28 , 30 , 32 , 56 , 57 , 60–67 ]. In this review, recent progress on optoelectronic memristors and transistors using various photosensitive materials for visual bionic applications is mainly summarized. The principles of biovision generation are introduced at first. Then, the device structures and working mechanisms of optoelectronic memristors and transistors are discussed. The recent advances of these two optoelectronic synapses using different photosensitive materials for realizing the visual perception functions are presented in Figure 1 . In the end, the current issues, challenges, and future directions in this area are proposed.\n Figure 1. Schematic diagram for the visual devices from three perspectives in this review. Reproduced by permission from [ 68 ], copyright [2020, WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim]. Reproduced by permission from [ 69 ], copyright [2019, WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim]. Reproduced by permission from [ 70 ], copyright [2022, IEEE]. Reproduced by permission from [ 71 ], copyright [2022, Tsinghua University Press]. Reproduced by permission from [ 72 ], copyright [2021, Wiley‐VCH GmbH]."
} | 2,017 |
37598370 | PMC10444008 | pmc | 1,367 | {
"abstract": "ABSTRACT Fermentation effluents from organic wastes contain simple organic acids and ethanol, which are good electron sources for exoelectrogenic bacteria, and hence are considered a promising substrate for hydrogen production in microbial electrolysis cells (MECs). These fermentation products have different mechanisms and thermodynamics for their anaerobic oxidation, and therefore the composition of fermentation effluent significantly influences MEC performance. This study examined the microbial electrolysis of a synthetic fermentation effluent (containing acetate, propionate, butyrate, lactate, and ethanol) in two-chamber MECs fitted with either a proton exchange membrane (PEM) or an anion exchange membrane (AEM), with a focus on the utilization preference between the electron sources present in the effluent. Throughout the eight cycles of repeated batch operation with an applied voltage of 0.8 V, the AEM-MECs consistently outperformed the PEM-MECs in terms of organic removal, current generation, and hydrogen production. The highest hydrogen yield achieved for AEM-MECs was 1.26 L/g chemical oxygen demand (COD) fed (approximately 90% of the theoretical maximum), which was nearly double the yield for PEM-MECs (0.68 L/g COD fed). The superior performance of AEM-MECs was attributed to the greater pH imbalance and more acidic anodic pH in PEM-MECs (5.5–6.0), disrupting anodic respiration. Although butyrate is more thermodynamically favorable than propionate for anaerobic oxidation, butyrate was the least favored electron source, followed by propionate, in both AEM- and PEM-MECs, while ethanol and lactate were completely consumed. Further research is needed to better comprehend the preferences for different electron sources in fermentation effluents and enhance their microbial electrolysis.",
"conclusion": "4. Conclusions Exoelectrogenic degradation of SFE and its conversion to hydrogen was significantly more efficient in AEM-MECs than PEM-MECs. This performance difference was attributed to the larger pH imbalance and more acidic anodic pH in PEM-MECs, which inhibit electron transfer and growth of exoelectrogenic bacteria. Butyrate was the least favored electron source in both MECs, followed by propionate. The preference for utilizing propionate over butyrate implies that factors beyond thermodynamics, such as energy investment and microbial community are involved in determining the utilization preference for different electron sources. Therefore, a deeper understanding of the varying preferences for different electron sources is required.",
"introduction": "1. Introduction Microbial electrolysis cells (MECs) provide an attractive bioelectrochemical platform for converting organic matter to green hydrogen. In an MEC, organic matter is oxidized to CO 2 by exoelectrogenic bacteria on the anode, and released protons and electrons to form hydrogen gas at the cathode with a small external energy input (typical applied voltage ≤1 V) [ 1–4 ]. If this input energy is provided from carbon-neutral energy source such as wind, solar, and tidal powers, the MEC technology can establish a feasible hydrogen economy. The transfer of protons (or hydroxide ions) between electrodes occurs through the ion exchange membrane physically separating the anode and cathode sides in a two-chamber MEC or by simple diffusion in the electrolyte in a single-chamber MEC. The single-chamber design is attractive since it does not need expensive ion exchange membranes. However, single-chamber MECs are not suitable to achieve high hydrogen purity and productivity mainly due to the consumption of hydrogen by hydrogenotrophic methanogens. In contrast, the two-chamber design allows the production high-purity hydrogen by separating the bioanode (exoelectrogenic oxidation of organic matter) from the abiotic cathode (hydrogen evolution) [ 5 , 6 ]. An important element to ensure the practical applicability of MECs is to find low-cost sustainable substrates suitable for exoelectrogenic respiration. Waste streams rich in organic matter, such as sugar-processing wastewater, food waste fermentation effluent, landfill leachate, and distillery wastewater, are good candidates for alternative MEC substrates [ 7–11 ]. However, real wastewaters generally contain relatively complex organic materials and considerable amounts of suspended particles, which causes performance and stability degradation related to membrane fouling and pH imbalance, especially in two-chamber MECs [ 12 , 13 ], and wastewater-fed MECs are still far away from practical application. Dark fermentation of organic wastes, such as food waste, produces mainly simple organic acids and alcohols, which are readily utilized by exoelectrogenic bacteria for anodic respiration in MECs [ 14 ], and therefore the fermentation effluent can be a promising substrate for MECs. Fermentation effluents typically contain acetate, propionate, butyrate, and lactate as the major organic acids along with ethanol, and their composition varies greatly depending on the feedstocks and operating conditions such as hydraulic retention time, organic loading rate, pH, and temperature [ 11 , 15 , 16 ]. The compositional variation can affect the utilizability of fermentation effluents and hence the performance of MECs since the fermentation products are used and converted to hydrogen with different efficiencies in MECs [ 17 ]. Accordingly, many previous studies have examined major organic acids, especially acetate, propionate, and butyrate, as MEC substrates and reported different results on their utilization and conversion efficiencies. For example, Escapa et al. [ 18 ] and Yang et al. [ 19 ] reported that butyrate is more readily consumed than propionate, while Torres et al. [ 20 ] reported a higher reaction rate with propionate than with butyrate. Lactate and ethanol have been relatively less studied as substrates for hydrogen production in MECs [ 17 , 21 ], although they are also major fermentation products and often occur in high concentrations in industrial effluents, for example, from food and beverage processing [ 22 , 23 ]. Different fermentation products coexist in fermentation effluents, and thus understanding the differences in their utilization rates and hydrogen-producing efficiencies can help to improve the performance and application of fermentation effluent-fed MECs. However, not much has been reported on the utilization preference of MECs for different fermentation products in a single mixture. Rivera et al. [ 24 ] examined two synthetic fermentation effluents (SFE) in two-chamber MECs; however, the effluents did not contain lactate and/or ethanol, and the focus was given to optimizing the operating conditions rather than assessing the preference for electron sources. Paz-Mireles et al. [ 25 ] examined the effects of adding lactate-ethanol mixtures on the performance of two-chamber MECs fed with an acetate-propionate-butyrate mixture as the base substrate; however, they focused on the effects on the reaction rate, with little attention to the utilization preference between electron sources. This study focuses on comparing the utilization and conversion properties of the major fermentation products in MECs fed with their mixture. For a more comprehensive comparison, two-chamber MECs equipped with two different types of ion exchange membranes, i.e. anion exchange membrane (AEM) or proton exchange membrane (PEM), were operated in parallel with an equal chemical oxygen demand (COD) concentration mixture of acetate, propionate, butyrate, lactate, and ethanol. The MECs were closely monitored during the operation for the consumption of organic acids and ethanol as well as bioelectrochemical performance.",
"discussion": "3. Results and discussion 3.1. Hydrogen and current productions This study examined the MEC performance with a synthetic fermentation effluent containing acetate, propionate, butyrate, lactate, and ethanol with a focus on the conversion preference between the organic substrates using MECs equipped with either AEM or PEM. The cumulative hydrogen production per subculture cycle of 7 days (H C ) increased steadily with the number of cycles and reached a plateau of approximately 288 mL in the last two cycles (no significant difference between the seventh and eighth cycles; t -test, p > 0.05) in AEM-MECs ( Figure 2a ). Meanwhile, the H C in PEM-MECs did not increase significantly after the third cycle and rather decreased in the last two cycles, with its maximum of 122 mL being recorded in the sixth cycle. AEM-MECs showed significantly higher H C values than PEM-MECs throughout the subcultures, and accordingly the hydrogen yield and recovery also remained significantly higher in AEM-MECs (>2-fold in the last two cycles; Figure 3 ). In AEM-MECs, the hydrogen yield reached up to 1.26 L/g COD, which is approximately 90% of the theoretical maximum of 1.40 L/g COD [ 37 ], in the last cycle. In contrast, the highest hydrogen yield in PEM-MECs was only 0.68 L/g COD, which was recorded in the sixth cycle. The maximum hydrogen production rate estimated by the Gompertz model was also much higher in AEM-MECs (>1.6-fold in the last two cycles), and correspondingly the maximum current density, which indicates the peak rate of electrochemical reaction, was significantly greater in AEM-MECs (>1.3-fold in the last two cycles). The hydrogen content in the gas recovered from the cathode remained consistently above 94% throughout the experimental cycles in both AEM- and PEM-MECs. These results clearly demonstrate that using AEM is significantly better than using PEM in two-chamber MECs for producing hydrogen from fermentation effluents, in terms of hydrogen productivity.\n Figure 2. Hydrogen (a) and current (b) production profiles during repeated batch operation of experimental MECs. Asterisk denotes that the measurement of cathodic hydrogen production in AEM-MECs during the sixth cycle was compromised by mechanical issues with respirometer. \n Figure 3. Performance comparison between experimental AEM- and PEM-MECs during repeated batch operation: (a) maximum hydrogen production rate, (b) maximum current density, (c) coulombic efficiency, (d) cathodic hydrogen recovery, (e) COD removal efficiency, and (F) hydrogen yield and recovery. Asterisks denote that the measurement of cathodic hydrogen production in AEM-MECs during the sixth cycle was compromised by mechanical issues with respirometer. Data from the first two cycles run for microbial inoculation and acclimation were excluded from comparison. In both AEM- and PEM-MECs, significant current generation and hydrogen evolution were observed from the first cycle after a two-day lag time, and relatively high and stable coulombic efficiency and coulomb production were maintained after the third cycle ( Figures 2 and 3 ). In addition, the MECs produced hydrogen immediately without a lag time from the second cycle. These results indicate that the inoculation and acclimation of exoelectrogenic bacteria on the anodes (i.e. the development of bioanodes) over the first three cycles (see Subsection 2.2 for details) were successful [ 38 ]. The average value of the maximum current density for the fourth to eighth cycles was approximately 1.3-fold higher in AEM-MECs (5.1 ± 0.4 A/m 2 ) than in PEM-MECs (3.9 ± 0.3 A/m 2 ). These values are comparable to those reported in previous studies using two-chamber MECs. Cario et al. [ 39 ] reported a maximum current density of approximately 5 A/m 2 in acetate-fed AEM-MECs equipped with carbon felt anodes and Pt/C-treated stainless steel mesh cathodes at an applied voltage of 0.8 V. Apostolopoulos et al. [ 40 ] observed a peak current density of approximately 3.8 A/m 2 in PEM-MECs installed with carbon paper anodes and Pt-coated carbon cloth cathodes, using a mixture of volatile fatty acids (C 2 –C 6 ) as the substrate at an applied voltage of 0.9 V. It is worth noting that the hydrogen production rate and yield were significantly greater in AEM-MECs than in PEM-MECs although both maintained comparably high levels of coulombic efficiency (≥96% in the last two cycles; Figs. 2 and 3 ). The superior performance of AEM-MECs were attributed to their significantly higher COD removal efficiency (i.e. more electrons to be transferred to the anodes) and cathodic hydrogen recovery (i.e. higher proportion of cathodic electrons toward hydrogen evolution) compared to PEM-MECs. Correspondingly, AEM-MECs showed markedly higher coulomb production than PEM-MECs (>1.4-fold in the last two cycles). The differences in cathodic hydrogen recovery between AEM-MECs (approximately 85%) and PEM-MECs (approximately 51%) were particularly pronounced in the last two cycles (>1.7-fold greater in AEM-MECs). These results can be related to the pH imbalance between the anode and cathode sides, which was greater in PEM-MECs compared to AEM-MECs especially in the later cycles ( Figure 4 ). An imbalance in pH levels across the membrane is a significant factor that reduces the performance of two-chamber MECs [ 41 ]. Furthermore, the more acidic anodic pH in PEM-MECs (≤6.0) likely contributed to their poorer performance compared to AEM-MECs, given that the optimal pH for most exoelectrogenic bacteria is between 6 and 7 [ 42 ]. The effect of pH imbalance on the MEC performance will be discussed in detail in subsection 3.2 . Another factor that could lower the cathodic hydrogen recovery is the loss of hydrogen through membrane permeation from the cathode to anode sides [ 43 ].\n Figure 4. Final anodic and cathodic pH values in each cycle (a) and their difference (b). 3.2. pH imbalance The anodic pH measured at the end of each cycle was consistently higher in AEM-MECs (6.2–6.7) compared to PEM-MECs (5.5–6.0) throughout the experiment ( Figure 4 ). The cathodic pH also remained higher in AEM-MECs (11.1–12.1) than in PEM-MECs (10.8–11.6) during the first five cycles, but it was the same (11.9–12.1) in both in the following cycles. Consequently, the pH imbalance between anolyte and catholyte across the ion exchange membrane was significantly greater in PEM-MECs (5.9–6.6) compared to AEM-MECs (5.4–5.6) during the last three cycles. A large pH difference between acidified anolyte and alkalized catholyte results in significant reductions in current generation and hydrogen production by inducing a high concentration overpotential, which increases the energy needed for hydrogen evolution [ 44 , 45 ]. Therefore, the higher pH imbalance in PEM-MECs compared to AEM-MECs appears to have contributed significantly to the poorer cathodic hydrogen recovery in the former, which was more pronounced in the last three cycles ( Figures 3 and 4 ). Although it is difficult to quantitatively determine all electron sinks other than hydrogen evolution at the cathode, pH imbalance must have had a significant impact on the flow of cathodic electrons. Another point to consider is that the anodic pH level in PEM-MECs was as low as 5.5–6.0, which is not favorable for the growth of exoelectrogenic bacteria. The acidic anodic pH likely inhibited exoelectrogenic electron transfer to the anode, thereby reducing MEC performance [ 46 ]. The increase in cathodic pH and decrease in anodic pH have been extensively reported in two-chamber MECs [ 41 , 47–49 ]. In PEM-MECs, pH imbalance can occur due to slower proton transport across the membrane than the rates of proton generation (at the anode) or consumption (at the cathode), and the undesired transport of other cations commonly present in electrolytes (e.g. Na + , K + , and NH 4 + ) exacerbates the problem by interfering with proton transport [ 50 ]. Typically, the electrolyte containing 10 5 times higher concentration of other cations than that of protons could provoke slower proton transport rate by transferring other cations more easily instead of protons to balance the charge [ 51 ]. The less acidic anodic pH in AEM-MECs compared to PEM-MECs can be attributed to the more efficient transport of hydroxide ions from the cathode to anode sides to balance electroneutrality in AEM-MECs, as compared to the transport of protons from the anode to cathode sides in PEM-MECs [ 52 ]. This difference appears to have contributed to the larger pH imbalance and poorer performance of PEM-MECs compared to AEM-MECs ( Figures 3 and 4 ). Moreover, in AEM-MECs, the transmembrane transport of protons can be facilitated with the assistance of pH buffers such as phosphate or carbonate [ 46 ]. For example, in PBS systems, as used in this study, HPO 4 2− can be converted to H 2 PO 4 − by combining with protons produced at the anode, and then transported through AEM to the cathode side. The transported H 2 PO 4 − ions can release protons at the cathode by reverting back to HPO 4 2− ions, which can then move back to the anode side [ 46 , 53 ]. This proton shuttling across AEM also likely helped, in part, to reduce the pH imbalance and thus minimize the performance loss in AEM-MECs [ 54 ]. According to a recent study on MECs, it was found that an imbalance in pH levels between the anolyte and catholyte in two-chamber MECs can be addressed by utilizing a new cathode design. This innovative design does not require a liquid catholyte and instead incorporates closely spaced electrodes and an AEM [ 51 ]. The study reported achieving a record-high current density and hydrogen production rate at a cell voltage of 0.79 V, suggesting that this vapor-fed design should be tested in MECs used for treating fermentation effluent to enhance MEC efficiency. 3.3. Electron source utilization After the first three cycles of inoculating and acclimating the anodic microbial community, the AEM-MECs maintained significantly higher COD removal (≥95%) compared to the PEM-MECs (≤68%) throughout the entire experimental cycles ( Figure 3e ). This difference corresponds to the superior performance of the AEM-MECs to the PEM-MECs discussed above. Butyrate was the organic compound that remained the most in the anode chamber after the batch reaction, followed by propionate and then acetate, throughout the experimental cycles in both AEM- and PEM-MECs ( Figure 5 ). Meanwhile, lactate and ethanol were entirely removed and not detected in any of the cycles, indicating that they could be readily utilized as electron sources in the MECs, either directly or indirectly. Acetate is commonly known to be the most rapidly consumed electron source, followed by butyrate and then propionate, in MECs [ 20 , 55 ]. The detection of a small amount of residual acetate is likely due to its production during the degradation of other electron sources in the SFE ( Table 1 ).\n Figure 5. Residual concentrations of organic electron sources in each cycle in (a) AEM-MECs and (b) PEM-MECs. Table 1. Biochemical reactions involved in exoelectrogenic utilization of fermentation products under anaerobic conditions. Substrate Reaction ∆G°’ (kJ/mol) a Reference Hydrogen H 2 → 2H + + 2e – −34.9 [ 56 ] Formate HCO 2 – + H 2 O → HCO 3 – + 2H + + 2e – −49.6 [ 56 ] HCO 2 – + H 2 O → HCO 3 – + H 2 +1.3 [ 57 ] 4HCO 2 – + H + → CH 3 COO – + 2HCO 3 −99.1 [ 56 ] Acetate CH 3 COO – + 4H 2 O → 2HCO 3 – + 9H + + 8e – −35.5 [ 56 ] CH 3 COO – + H + + 2H 2 O → 2CO 2 + 4H 2 +104.6 [ 58 ] Propionate C₂H₅COO – + 2HCO 3 – → CH 3 COO – + 3HCO 2 – + H + +72.2 [ 56 ] C₂H₅COO – + 3H 2 O → CH 3 COO – + H + + HCO 3 – + 3H 2 +76.1 [ 56 ] C₂H₅COO – + 5H 2 O → 2CO 2 + HCO 3 – + 14H + + 14e – −73.0 [ 56 ] Butyrate C 3 H 7 COO – + 2HCO 3 – → 2CH 3 COO – + 2HCO 2 – + H + +45.5 [ 59 ] C 3 H 7 COO – + 2H 2 O → 2CH 3 COO – + H + + 2H 2 +48.1 [ 59 ] Lactate 3CH 3 CH(OH)COO – → 2C₂H₅COO – + CH 3 COO – + HCO 3 – + H + −164.8 [ 60 ] CH 3 CH(OH)COO – + H 2 O → CH 3 COO – + CO 2 + 2H 2 −8.8 [ 60 ] Ethanol CH 3 CH 2 OH + H 2 O → CH 3 COO – + 2H 2 + H + +9.6 [ 60 ] a Gibbs free energy under standard conditions (pH 7 and 25°C). Note that the utilization of butyrate as an electron source was significantly less efficient than other sources, even propionate, although the anaerobic degradation of propionate is less thermodynamically favorable than that of butyrate. The preferred utilization of butyrate over propionate in MECs has been reported in numerous studies [ 18 , 19 , 61 , 62 ], but there are also many studies that report the opposite result [ 20 , 35 , 55 , 63 ]. These conflicting observations suggest that there are other factors beyond thermodynamics, such as energy investment [ 35 ], that influence the utilization preference between different electron sources. The preferred utilization of propionate over butyrate observed in this study may also be attributed to the potential existence of specialized exoelectrogenic bacteria, such as Geobacter anodireducens , capable of directly utilizing propionate for current generation [ 56 , 64 ]. Lactate, which has a similar molecular structure to propionate, can also be directly converted to electrical current by some Geobacter species [ 53 ]. Lactate can be consumed directly by exoelectrogenic bacteria (e.g. Geobacter sulfurreducens PCA) without electron shuttle through intracellular conversion of lactate to acetate and hydrogen, followed by their oxidation to electrons, and this overall oxidation reaction is known to be highly spontaneous process [ 65 ]. Although the anodic microbial community was not analyzed in this study, it is possible that exoelectrogenic bacteria, which can directly utilize propionate (and lactate), were active and helped to facilitate the utilization of propionate (and lactate) in the experimental MECs. The facilitated propionate utilization would have benefited the syntrophic exoelectrogenic utilization of lactate via propionate ( Table 1 ). These results suggest that MECs can have different preferences for various electron sources, which warrants further research on the microbial interactions and their effects on the conversion of electron sources to current and then hydrogen in MECs. Another point to consider regarding the exoelectrogenic propionate utilization is the effect of pH. Syntrophic degradation of propionate can occur through two pathways: the acetate/H 2 pathway, which is more favorable at a pH below 6.37, or the acetate/formate pathway, which is more favorable at a pH above that [ 64 ]. Given that the latter pathway is more energetically favorable than the former ( Table 1 ), the less acidic anodic pH of AEM-MECs (6.2–6.7) compared to PEM-MECs (5.5–6.0) likely contributed to the more efficient degradation of propionate in the AEM-MECs ( Figure 5 ). The difference in the utilizability of propionate, which is a relatively challenging electron source, can be linked to the performance difference in current and hydrogen production observed between the AEM- and PEM-MECs. Unlike propionate and lactate, there is currently no evidence that exoelectrogenic bacteria can directly utilize butyrate and ethanol to generate electrical current. It is believed that these compounds can only be converted to current indirectly via acetate in MECs [ 66 , 67 ]. Since the anaerobic oxidation of butyrate or ethanol to acetate is thermodynamically unfavorable ( Table 1 ), their exoelectrogenic utilization requires syntrophic relationship with hydrogen scavengers [ 66 ]. However, the significantly lower Gibbs free energy of ethanol oxidation compared to butyrate oxidation makes ethanol a more favorable electron source than butyrate. This thermodynamic advantage of ethanol is well reflected in the absence of residual ethanol in every cycle in both AEM- and PEM-MECs ( Figure 5 ). While this study presents intriguing findings regarding the choice of organic compounds in SFE depending on the type of membrane employed, there are a few limitations associated with the current experiments. First, a fermentation effluent which was artificially synthesized was used here. There were some previous studies which utilized the actual fermentation effluent in MECs or MFCs generated from food wastewater, landfill leachate, and corn stalk as substrate for fermentation processes [ 11 , 55 , 68 ]. Incorporating the actual fermentation effluent in future studies would be beneficial in reducing the operating costs and improving the practicality and commercial feasibility of MECs. Additionally, it is important to note that the current experiments were conducted using small lab-scale reactors with a working volume of 200 mL. This limited scale makes it challenging to accurately predict and scale up the process to larger industrial-scale bioreactors. Once process optimization and a comprehensive understanding of the dynamics of MECs with mixed fermentation effluent have been achieved through lab-scale research, the technology can be scaled up to pilot-scale reactors for the treatment of actual fermentation effluent, as demonstrated in previous works involving other actual organic wastewater [ 69–71 ]. It is worth noting that for scaling up the two-chamber MEC technology, the choice of ion exchange membrane (e.g. PEM and AEM) becomes a critical factor that influences the cost. Although the ion exchange membrane accounts for up to 40% of the overall cost of MECs, it is inevitable to use a membrane to get a high-purity hydrogen from MECs [ 36 ]. The AEM (e.g. AMI-7001, ~80 USD/m 2 ) is approximately 18-folds cheaper than PEM (e.g. Nafion 117, ~1,400 USD/m 2 ) [ 72 ]. Given that nearly double higher hydrogen yield in AEM than PEM in our study, using AEM can enhance the cost-effectivity of MECs."
} | 6,385 |
29696650 | null | s2 | 1,368 | {
"abstract": "Large-scale environmental disturbances may impact both partners in coral host-Symbiodinium systems. Elucidation of the assembly patterns in such complex and interdependent communities may enable better prediction of environmental impacts across coral reef ecosystems. In this study, we investigated how the community composition and diversity of dinoflagellate symbionts in the genus Symbiodinium were distributed among 12 host species from six taxonomic orders (Actinaria, Alcyonacea, Miliolida, Porifera, Rhizostoma, Scleractinia) and in the reef water and sediments at Lizard Island, Great Barrier Reef before the 3rd Global Coral Bleaching Event. 454 pyrosequencing of the ITS2 region of Symbiodinium yielded 83 operational taxonomic units (OTUs) at a 97% similarity cut-off. Approximately half of the Symbiodinium OTUs from reef water or sediments were also present in symbio. OTUs belonged to six clades (A-D, F-G), but community structure was uneven. The two most abundant OTUs (100% matches to types C1 and A3) comprised 91% of reads and OTU C1 was shared by all species. However, sequence-based analysis of these dominant OTUs revealed host species specificity, suggesting that genetic similarity cut-offs of Symbiodinium ITS2 data sets need careful evaluation. Of the less abundant OTUs, roughly half occurred at only one site or in one species and the background Symbiodinium communities were distinct between individual samples. We conclude that sampling multiple host taxa with differing life history traits will be critical to fully understand the symbiont diversity of a given system and to predict coral ecosystem responses to environmental change and disturbance considering the differential stress response of the taxa within."
} | 436 |
39664056 | PMC11631926 | pmc | 1,369 | {
"abstract": "Underlying the thick sediment layer in ocean basins, the flow of seawater through the cracked and porous upper igneous crust supports a previously hidden and largely unexplored active subsurface microbial biome. Subseafloor crustal systems offer an enlarged surface area for microbial habitats and prolonged cell residence times, promoting the evolution of novel microbial lineages in the presence of steep physical and thermochemical gradients. The substantial metabolic potential and dispersal capabilities of microbial communities within these systems underscore their crucial role in biogeochemical cycling. However, the intricate interplay between fluid chemistry, temperature variations, and microbial activity remains poorly understood. These complexities introduce significant challenges in unraveling the factors that regulate microbial distribution and function within these dynamic ecosystems. Using synthesized data from previous studies, this work describes how the ocean crustal biosphere functions as a continuous-flow biogechemical reactor. It simultaneously promotes the breakdown of surface-derived organic carbon and the creation of new, chemosynthetic material, thereby enhancing element recycling and ocean carbon productivity. Insights gained from the qualitative analysis of the extent of biogeochemical microbial activity and diversity across the temperature and chemical gradients that characterize these habitats, as reviewed herein, challenge traditional models of global ocean carbon productivity and provide the development of a new conceptual framework for understanding the quantitative metabolic potential and broad dispersal of the crustal microbial biome.",
"conclusion": "Conclusion The subseafloor crustal system plays a crucial role in the biogeochemical cycling within mid-ocean ridge flanks by redistributing mass and energy between deep sediments and basement aquifers and back into the ocean. Although quantitative estimates of microbial contributions to global biogeochemical cycles are limited by difficult access and sparse sampling, the widespread metabolic potential of this biosphere suggests that incorporating the crustal system into current global biogeochemical models will be crucial for accurately representing the full ocean carbon cycle. The ocean crustal biosphere plays a dual role, capturing the intricate processes of carbon degradation and synthesis occurring beneath the ocean floor. Recognizing its impact on global biogeochemical cycles will allow for a more comprehensive understanding of carbon mineralization and recycling, enhancing the accuracy of predictions related to ocean productivity and ecological dynamics. Moreover, studying the ocean crustal biosphere has significant implications for astrobiology, as it serves as an analog for potential life on other planetary bodies ( Jones et al., 2018 ). Understanding how microbial life thrives in these extreme conditions on Earth offers valuable insights into the potential for life in similar environments elsewhere in the solar system and beyond. This connection highlights the broader importance of studying these systems, not only to improve our biogeochemical models but also to advance our search for life beyond Earth.",
"introduction": "Introduction The biogeochemical role of microbes deeply buried beneath the seafloor is far more important than presumed possible 80 years ago ( Zobell and Anderson, 1936 ; Zobell, 1938 ). Over the past decades, comprehensive studies of subseafloor sedimentary microbes have revealed not only cell abundances that match previous estimates in seawater and in surface sediments ( Kallmeyer et al., 2012 ) but most importantly, have demonstrated the viability of these microbes ( Morono et al., 2011 ; Trembath-Reichert et al., 2017 ; Imachi et al., 2019 ) and their essential role in operating and maintaining global biogeochemical cycles ( Parkes et al., 2014 ). We now understand that beneath the sediment layer, fluids moving through the basaltic ocean crust hold a similar amount of organic carbon, stored within living prokaryotic biomass (~1.6 Gt C, Bar-On et al., 2018 ). The volume of the ocean crust biosphere represents nearly 2% of the volume of the oceans ( Johnson and Pruis, 2003 ). Conditions along the active fluid flow paths that characterize this habitat indicate that the crustal biosphere is the most favorable of deep-subsurface habitats and is likely a very active site of element cycling ( Johnson et al., 2006 ). Furthermore, this aquifer is hydrothermally active and interactions with the overlaying sediments and ocean seawater facilitate the free exchange of fluid, chemicals, biological material, and heat, which likely have a large impact on the variability of seawater chemical composition and global biogeochemical cycling ( Edwards et al., 2011 )."
} | 1,201 |
29970091 | PMC6029019 | pmc | 1,370 | {
"abstract": "Background High production cost of bioplastics polyhydroxyalkanoates (PHA) is a major obstacle to replace traditional petro-based plastics. To address the challenges, strategies towards upstream metabolic engineering and downstream fermentation optimizations have been continuously pursued. Given that the feedstocks especially carbon sources account up to a large portion of the production cost, it is of great importance to explore low cost substrates to manufacture PHA economically. Results Escherichia coli was metabolically engineered to synthesize poly-3-hydroxybutyrate (P3HB), poly(3-hydroxybutyrate- co -4-hydroxybutyrate) (P3HB4HB), and poly(3-hydroxybutyrate- co -3-hydroxyvalerate) (PHBV) using acetate as a main carbon source. Overexpression of phosphotransacetylase/acetate kinase pathway was shown to be an effective strategy for improving acetate assimilation and biopolymer production. The recombinant strain overexpressing phosphotransacetylase/acetate kinase and P3HB synthesis operon produced 1.27 g/L P3HB when grown on minimal medium supplemented with 10 g/L yeast extract and 5 g/L acetate in shake flask cultures. Further introduction succinate semialdehyde dehydrogenase, 4-hydroxybutyrate dehydrogenase, and CoA transferase lead to the accumulation of P3HB4HB, reaching a titer of 1.71 g/L with a 4-hydroxybutyrate monomer content of 5.79 mol%. When 1 g/L of α-ketoglutarate or citrate was added to the medium, P3HB4HB titer increased to 1.99 and 2.15 g/L, respectively. To achieve PHBV synthesis, acetate and propionate were simultaneously supplied and propionyl-CoA transferase was overexpressed to provide 3-hydroxyvalerate precursor. The resulting strain produced 0.33 g/L PHBV with a 3-hydroxyvalerate monomer content of 6.58 mol%. Further overexpression of propionate permease improved PHBV titer and 3-hydroxyvalerate monomer content to 1.09 g/L and 10.37 mol%, respectively. Conclusions The application of acetate as carbon source for microbial fermentation could reduce the consumption of food and agro-based renewable bioresources for biorefineries. Our proposed metabolic engineering strategies illustrate the feasibility for producing polyhydroxyalkanoates using acetate as a main carbon source. Overall, as an abundant and renewable resource, acetate would be developed into a cost-effective feedstock to achieve low cost production of chemicals, materials, and biofuels. Electronic supplementary material The online version of this article (10.1186/s12934-018-0949-0) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusions In this study, E. coli was engineered to synthesize P3HB, P3HB4HB, and PHBV using acetate as a main carbon source. The production of biopolymers was significantly improved by the overexpression of phosphotransacetylase and acetate kinase. In shake flask cultures, the engineered E. coli produced 1.27 g/L of P3HB and 1.71 g/L P(3HB- co -5.79 mol% 4HB), respectively, with minimal medium supplemented 10 g/L yeast extract and 5 g/L acetate. When 1 g/L citrate was added as assistant carbon source, P3HB4HB production titer was increased to 2.15 g/L. The overexpression of propionyl-CoA transferase and propionate permease lead to a production titer of 1.09 g/L P(3HB- co -10.37 mol% 3HV) when 5 g/L acetate and 1.5 g/L propionate were simultaneously supplied. To our knowledge, this is the first study reporting the efficient production of P3HB, P3HB4HB, and PHBV using acetate as a main carbon source by engineered E. coli .",
"discussion": "Results and discussion Pathway construction for P3HB synthesis from acetate Over the past few decades, researchers have mainly been studying the “acetate switch” with the aim to enable microorganisms to efficiently consume acetate that is produced by their own metabolism to eliminate the toxicity of acetate to cell growth [ 28 , 29 ]. Nonetheless, acetate could be a potential cost-effective feedstock for synthesis of value-added chemicals. Recently, the feasibility of converting acetate to poly-3-hydroxybutyrate (P3HB) and succinate was demonstrated in Y. lipolytica [ 30 ] and E. coli [ 23 ], respectively. Moreover, co-production of hydrogen and P3HB with engineered E. coli on glucose and acetate under anaerobic condition was reported. The addition of acetate to the culture as part of carbon source significantly increased P3HB production, yet the P3HB titer was still below 0.04 g/L [ 31 ]. To investigate the possibility of P3HB production using acetate as a main carbon source in E. coli , P3HB synthesis operon phaCAB carrying plasmid pBHR68 was transformed into E. coli JM109, and the recombinant strain was inoculated into MM medium supplemented with 2 g/L yeast extract and 5 g/L acetate (Fig. 2 ). After 48 h shake flask cultivation, E. coli JM109 (pBHR68) consumed all the acetate and yielded 1.49 g/L CDW with 0.22 g/L P3HB accumulation, which indicated that P3HB could be produced from acetate, yet the P3HB titer was much lower than that obtained from glucose [ 32 ]. Therefore, further metabolic engineering strategies were applied to improve P3HB accumulation from acetate. Fig. 2 Effects of the overexpression of pta - ackA and acs on cell growth and P3HB production. E. coli recombinants harboring different plasmids were cultivated in MM medium supplemented with 5 g/L acetate and 2 g/L yeast extract at 37 °C for 48 h. CDW ( a ), P3HB content ( b ), P3HB titer ( c ), and rCDW ( d ) were measured. The columns represent the averages of triplicate experiments, and the error bars represent standard deviation \n Pathway engineering for improved P3HB accumulation In E. coli , there are two potential routes for the generation of acetyl-CoA from acetate: phosphotransacetylase/acetate kinase ( pta - ackA pathway) and AMP-forming acetyl-CoA synthetase ( acs pathway) (Fig. 1 ). These two pathways were augmented through the overexpression of pta - ackA and acs genes, respectively. Shake flask cultivations in acetate containing MM medium showed that JM109 (pBHR68 + pMCS-pta-ackA) consumed 5 g/L acetate and produced 0.66 g/L P3HB. The P3HB production titer of was roughly four times of that produced by control strain JM109 (pBHR68 + pBBR1MCS-2). By contrast, the overexpression of acs gene has little effect on improving P3HB accumulation (Fig. 2 ). The activation of each molecule of acetate for acetyl-CoA synthesis in acs pathway requires two molecule of ATP, while pta - ackA pathway consumes only one molecule of ATP for acetyl-CoA synthesis [ 22 , 33 ]. It was reported also that the growth of E. coli stains on low concentrations of acetate depends on acs pathway, while growth on high concentrations requires pta - ackA pathway [ 28 , 29 ]. Therefore, the engineering of the pta - ackA pathway to strengthen acetate assimilation was considered to be an effective strategy for improving P3HB production in recombinant E. coli . Optimizing culture conditions to increase P3HB production The engineered E. coli JM109 (pBHR68 + pMCS-pta-ackA) and control strain JM109 (pBHR68 + pBBR1MCS-2) were cultivated in shake flasks with LB, TB, and MM medium to evaluate the effects of medium composition on cell growth and P3HB accumulation (Fig. 3 ). Initial acetate concentration was 5 g/L and MM medium was supplemented with 2 g/L yeast extract. After 48 h cultivation, no acetate was left in the medium for all groups. The recombinant strain harboring extra pta - ackA genes produced more CDW and P3HB in the three different kinds of culture media, further demonstrated that pta - ackA overexpression was effective for improving P3HB production from acetate (Fig. 3 ). With MM medium, JM109 (pBHR68 + pMCS-pta-ackA) produced 1.67 g/L CDW, containing 0.66 g/L P3HB, while the use of LB and TB medium resulted in 1.55 g/L CDW with 0.52 g/L P3HB, and 1.93 g/L CDW with 0.74 g/L P3HB, respectively. TB medium helped to obtain higher CDW and P3HB titer than those achieved in MM and LB medium. Among three culture conditions, MM medium possesses lowest cost and resulted in acceptable P3HB titer. Therefore, it was considered to be a favorable medium for the production of P3HB from acetate. Fig. 3 Effects of medium composition on cell growth and P3HB production. E. coli recombinants harboring different plasmids were cultivated in MM, LB, or TB medium supplemented with 5 g/L acetate at 37 °C for 48 h. MM medium contained 2 g/L yeast extract. CDW ( a ), P3HB content ( b ), P3HB titer ( c ), and rCDW ( d ) were measured. The columns represent the averages of triplicate experiments, and the error bars represent standard deviation \n Next, different concentration (0, 2, 4, 6, 8, 10 g/L) of yeast extract were added to MM medium to study its potential for enhancing cell growth and P3HB accumulation (Fig. 4 ). When yeast extract was not provided, CDW of E. coli JM109 (pBHR68 + pMCS-pta-ackA) reached 1.03 g/L, and P3HB concentration was only 0.02 g/L. The CDW and P3HB accumulation increased gradually with the increase of yeast extract concentration, although the intracellular P3HB content did not change obviously. The addition of 10 g/L yeast extract yielded 3.02 g/L CDW, containing 1.27 g/L P3HB, which was the highest P3HB production titer obtained in this study. The production yield was 0.25 g P3HB/g acetate, which was 35% of the maximal theoretical yield. It has been shown that yeast extract contributes a large amount of amino acids for biomass growth, thus the addition of complex nitrogen sources such as yeast extract to defined medium saved NADPH for amino acids synthesis and increased intracellular NADPH level as well as NADPH/NADP ratio [ 34 ]. P3HB biosynthesis is a NADPH-dependent pathway and high NADPH level and availability were considered to be of great importance for the efficient synthesis of PHB in recombinant E. coli [ 32 ]. Therefore, we speculate that the addition of yeast extract favored cell growth and intracellular NADPH availability which in turn led to high biomass and P3HB production. Fig. 4 Effect of yeast extract concentration on cell growth and P3HB production. E. coli JM109 (pBHR68 + pMCS-pta-ackA) was cultivated in MM medium supplemented with 5 g/L acetate at 37 °C for 48 h. Different concentration (0, 2, 4, 6, 8, 10 g/L) of yeast extract (YE) was added to the culture. CDW ( a ), P3HB content ( b ), P3HB titer ( c ), and rCDW ( d ) were measured. The columns represent the averages of triplicate experiments, and the error bars represent standard deviation \n We next cultivated E. coli JM109 (pBHR68 + pMCS-pta-ackA) using MM medium supplemented with 10 g/L yeast extract and different concentration (0, 1, 2, 3, 4, 5 g/L) of acetate to evaluate the effect of acetate concentration on P3HB accumulation. As shown in Additional file 1 : Figure S1, when acetate was not provided, the CDW reached 1.15 g/L and the intracellular P3HB content was only 3.23 wt%. With the increase of acetate concentration, the CDW, P3HB content, and P3HB titer all increased gradually. The addition of 5 g/L acetate led to the highest P3HB content of 42.02 wt%. Although yeast extract was provided at a relatively high level, P3HB synthesis was still limited by acetate addition. In contrast, the results of shake flask cultures using 5 g/L acetate and different amounts of yeast extract showed that the P3HB content did not change obviously when yeast extract concentration increased from 2 to 10 g/L (Fig. 4 ). These results demonstrated that the carbon source existed in yeast extract was not able to support effective P3HB synthesis, and acetate was the main carbon source to synthesize P3HB. Production of P3HB4HB from acetate Poly(3-hydroxybutyrate- co -4-hydroxybutyrate) (P3HB4HB) exhibits favorable biodegradability and a wide range of physical properties ranging from highly crystalline plastic to elastic rubber, thus it is considered to be one of the most promising PHA materials. The synthesis of P3HB4HB copolymer from structural unrelated carbon sources such as glucose in E. coli has been reported [ 24 , 35 , 36 ]. Nevertheless, in terms of substrate cost, acetate is a promising carbon source for microbial fermentations. Therefore, we aimed to developed an engineered E. coli that can produce P3HB4HB from acetate as carbon source. The genes involved in succinate degradation pathway of Clostridium kluyveri , including sucD , 4hbD , and orfZ [ 37 ], was combined with P3HB synthesis operon phaCAB to construct P3HB4HB producing pathway. E. coli native succinate semialdehyde dehydrogenase genes sad and gabD were both deleted for eliminating succinate formation from succinate semialdehyde (Fig. 1 ). The resulting strain JM109SG (p68orfZ + pMCSH5) was able to achieve 2.37 g/L CDW containing 35.79 wt% P(3HB- co -9.48 mol% 4HB) when grown in mineral medium supplemented with 10 g/L yeast extract and 5 g/L acetate (Fig. 5 ). In addition, the pta - ackA genes were overexpressed to strengthen acetate assimilation, and the recombinant JM109SG (p68orfZ + pMCSH5-pta-ackA) yielded 2.96 g/L CDW, containing 58.01 wt% P(3HB- co -5.79 mol% 4HB) (Fig. 5 ). In terms of P3HB4HB production titer, pta - ackA overexpression resulted in 1.71 g/L, significantly higher than 0.85 g/L of the control strain without pta - ackA overexpression. These results were consistent with previous P3HB producing studies, and it appears that the pta - ackA plasmid carrying recombinants were more productive than the strains without pta - ackA overexpression. Fig. 5 P3HB4HB production by E. coli strains grown in shake flasks. E. coli recombinants harboring different plasmids were cultivated in MM medium supplemented with 10 g/L yeast extract and different carbon sources at 37 °C for 48 h. Initial acetate (A) concentration was 5 g/L. α-ketoglutarate (KG) or citrate (C) was added as assistant carbon source at a concentration of 1 g/L. CDW ( a ), P3HB4HB content ( b ), P3HB4HB titer ( c ), and rCDW ( d ) were measured. The columns represent the averages of triplicate experiments, and the error bars represent standard deviation \n Influence of TCA cycle intermediates on P3HB4HB synthesis Previously, the addition of TCA cycle intermediates including α-ketoglutarate and citrate were found to be effective for increasing metabolic flux into 4HB precursor when glucose was employed as carbon source [ 24 ]. Therefore, shake flask cultures were performed to evaluate the effects of α-ketoglutarate and citrate addition on cell growth and P3HB4HB accumulation profiles in case of acetate as a main carbon source. As shown in Fig. 5 , when 1 g/L of α-ketoglutarate was added, the recombinant E. coli reached 3.63 g/L CDW, containing 54.97 wt% P(3HB- co -5.80 mol% 4HB). Similarly, the addition of 1 g/L citrate as joint carbon source resulted in 3.62 g/L CDW, containing 59.48 wt% P(3HB- co -3.43 mol% 4HB). The addition of α-ketoglutarate and citrate as additional carbon sources increased the cell growth and P3HB4HB production, but had no obvious effect on improving 4HB monomer content. When E. coli metabolizes acetate as a sole carbon and energy source, the genes involved in acetate uptake, glyoxylate cycle, TCA cycle, and gluconeogenesis were all up-regulated [ 12 ]. The addition of α-ketoglutarate or citrate could improve the supply of TCA cycle intermediates, thus may benefit cell growth and acetate assimilation. However, on this occasion, 4HB monomer content was not increased, indicating the metabolic flux towards 4HB precursor synthesis was still limited in spite of improved TCA cycle intermediate supply. Production of PHBV from acetate and propionate Poly(3-hydroxybutyrate- co -3-hydroxyvalerate) (PHBV) is more flexible and tougher than P3HB homopolymer and has been commercially produced for many years [ 7 ]. The normal PHBV synthesis process requires the addition of propionate as assistant carbon source to generate propionyl-CoA, which was the precursor of 3-hydroxyvalerate (3HV) monomer (Fig. 1 ) [ 38 ]. The conversion of propionate to propionyl-CoA could be catalyzed by the ATP-dependent propionyl-CoA synthetase or propionyl-CoA transferase (Pct). When acetate was employed as carbon source, the intracellular pool size of acetyl-CoA should be favorable for transferring a CoA group from acetyl-CoA to propionate. To study the possibility of PHBV synthesis from acetate and propionate, plasmid p68-pct-CAB, harboring Megasphaera elsdenii propionyl-CoA transferase and P3HB synthesis operon phaCAB , was co-transformed with pMCS-pta-ackA into E. coli JM109. The resulting recombinant reached 2.64 g/L CDW, containing 12.52 wt% P(3HB- co -6.58 mol% 3HV) (Fig. 6 ). In contrast, the control strain JM109 (p68-pct-CAB +pBBR1MCS-2) only reached 2.36 g/L CDW containing 6.48 wt% P(3HB- co -15.80 mol% 3HV) under the same culture condition. PHBV production titer was increased from 0.15 to 0.33 g/L with pta - ackA overexpression, further demonstrating that pta - ackA overexpression was an effective strategy for improving acetate-dependent biopolymer synthesis. Fig. 6 PHBV production by E. coli strains grown in shake flasks. E. coli recombinants harboring different plasmids were cultivated in MM medium supplemented with 10 g/L yeast extract, 5 g/L acetate, and 1.5 g/L propionate at 37 °C for 48 h. CDW ( a ), PHBV content ( b ), PHBV titer ( c ), and rCDW ( d ) were measured. The columns represent the averages of triplicate experiments, and the error bars represent standard deviation \n Previously, recombinant E. coli harboring phaCAB operon and propionate permease (or propionyl-CoA synthase) failed to incorporate 3HV into the biopolymer in M9 medium containing 2 g/L yeast extract, 1 g/L sodium propionate, and 20 g/L sodium acetate [ 39 ]. However, a high concentration of yeast extract (10 g/L) was used in this study. It was speculated that a high concentration of yeast extract favors cell growth. In addition, propionyl-CoA transferase used acetyl-CoA and propionate to produce propionyl-CoA, yielding the precursor for 3HV incorporation. Therefore, our engineering strategy suggest that PHBV could be produced from acetate and propionate, yet the biopolymer content was lower than that achieved for P3HB or P3HB4HB. Next, prpP gene encoding propionate permease of R. eutropha H16 was overexpressed to study its effect on PHBV synthesis. E. coli JM109 (p68-pct-CAB + pMCS-pta-ackA-prpP) resulted in 3.15 g/L CDW, containing 34.77 wt% P(3HB- co -10.37 mol% 3HV) (Fig. 6 ). The overexpression of propionate permease improved PHBV production titer from 0.33 to 1.09 g/L. Meanwhile, 3HV monomer content was increased from 6.58 to 10.37 mol%. Similar phenomenon were also observed in previous studies, in which overexpression of PrpP not only increased the 3HV monomer content but also promoted the biopolymer accumulation [ 40 ]. Propionate permease is responsible for the uptake of propionate and PrpP overexpression may improve the pool of intracellular propionate for propionyl-CoA formation. Thus, it was reasonable to find that 3HV fraction in PHBV was increased with PrpP overexpression. However, the reason for improved biopolymer production caused by PrpP overexpression was not clear and need to be discussed further. Use of corn steep liquor as an economical nitrogen source Yeast extract was proved to be a critical nutritional supplement for improved PHA production (Fig. 4 ). To reduce the feedstock cost, many studies tried to develop cheaper supplements which can be used as an alternative or in combination with yeast extract. Corn steep liquor, a low-cost byproduct of the corn wet-milling process, contains a large amount of amino acids, peptides and vitamins [ 41 ]. Therefore, there have been increasing studies on the utilization of corn steep liquor as a nitrogen source for microbial fermentations [ 42 , 43 ]. Shake flask cultivations using various concentration (2, 4, 6, 8, 10 g/L) of corn steep liquor instead of yeast extract were performed (Fig. 7 ). The CDW of E. coli JM109 (pBHR68 + pMCS-pta-ackA) increased gradually with the increase of corn steep liquor concentration, yet the P3HB production exhibit a trend of first increasing then decreasing. The addition of 4 g/L and 6 g/L of corn steep liquor to MM medium containing 5 g/L acetate yielded 0.91 and 0.96 g/L P3HB, respectively. Although 10 g/L corn steep liquor addition led to highest CDW among the different corn steep liquor concentration condition, the P3HB concentration was only 0.56 g/L. Therefore, the favorable corn steep liquor concentration for P3HB production was 4–6 g/L under our culture condition. These results indicated that P3HB can be synthesized when corn steep liquor is employed as a nitrogen source, albeit with somewhat lower efficiency in comparison with yeast extract. The use of corn steep liquor for PHA production from acetate therefore merits further research. Fig. 7 Comparative cell growth and P3HB production of engineered E. coli cultivated with yeast extract or corn steep liquor as nitrogen source. E. coli JM109 (pBHR68 + pMCS-pta-ackA) was cultivated in MM medium supplemented with 5 g/L acetate at 37 °C for 48 h. Different concentration (0, 2, 4, 6, 8, 10 g/L) of yeast extract (YE) or corn steep liquor (CSL) was added to the culture as nitrogen source. CDW ( a ), P3HB content ( b ), P3HB titer ( c ), and rCDW ( d ) were measured. The columns represent the averages of triplicate experiments, and the error bars represent standard deviation \n In addition, we performed shake flask studies without acetate addition to evaluate the contribution of CSL to P3HB production. As shown in Additional file 1 : Table S2, E. coli JM109 (pBHR68 + pMCS-pta-ackA) showed the highest P3HB accumulation of 0.04 g/L among all strains studied when cultivated in MM medium supplemented with 6 g/L CSL. The P3HB titer obtained without acetate was much lower than that achieved by acetate supplementation. These results further demonstrated that acetate was served as the main carbon source to support effective P3HB synthesis."
} | 5,527 |
28254477 | null | s2 | 1,372 | {
"abstract": "Fifty years ago, Lynn Margulis, inspiring in early twentieth-century ideas that put forward a symbiotic origin for some eukaryotic organelles, proposed a unified theory for the origin of the eukaryotic cell based on symbiosis as evolutionary mechanism. Margulis was profoundly aware of the importance of symbiosis in the natural microbial world and anticipated the evolutionary significance that integrated cooperative interactions might have as mechanism to increase cellular complexity. Today, we have started fully appreciating the vast extent of microbial diversity and the importance of syntrophic metabolic cooperation in natural ecosystems, especially in sediments and microbial mats. Also, not only the symbiogenetic origin of mitochondria and chloroplasts has been clearly demonstrated, but improvement in phylogenomic methods combined with recent discoveries of archaeal lineages more closely related to eukaryotes further support the symbiogenetic origin of the eukaryotic cell. Margulis left us in legacy the idea of 'eukaryogenesis by symbiogenesis'. Although this has been largely verified, when, where, and specifically how eukaryotic cells evolved are yet unclear. Here, we shortly review current knowledge about symbiotic interactions in the microbial world and their evolutionary impact, the status of eukaryogenetic models and the current challenges and perspectives ahead to reconstruct the evolutionary path to eukaryotes."
} | 360 |
34204975 | PMC8199887 | pmc | 1,373 | {
"abstract": "Discovering novel bacterial strains might be the link to unlocking the value in lignocellulosic bio-refinery as we strive to find alternative and cleaner sources of energy. Bacteria display promise in lignocellulolytic breakdown because of their innate ability to adapt and grow under both optimum and extreme conditions. This versatility of bacterial strains is being harnessed, with qualities like adapting to various temperature, aero tolerance, and nutrient availability driving the use of bacteria in bio-refinery studies. Their flexible nature holds exciting promise in biotechnology, but despite recent pointers to a greener edge in the pretreatment of lignocellulose biomass and lignocellulose-driven bioconversion to value-added products, the cost of adoption and subsequent scaling up industrially still pose challenges to their adoption. However, recent studies have seen the use of co-culture, co-digestion, and bioengineering to overcome identified setbacks to using bacterial strains to breakdown lignocellulose into its major polymers and then to useful products ranging from ethanol, enzymes, biodiesel, bioflocculants, and many others. In this review, research on bacteria involved in lignocellulose breakdown is reviewed and summarized to provide background for further research. Future perspectives are explored as bacteria have a role to play in the adoption of greener energy alternatives using lignocellulosic biomass.",
"conclusion": "9. Conclusions Bacterial bioconversion of lignocellulosic biomass has great potential, but still requires research to reveal the untapped opportunities and how they can be harnessed. Whilst genetic engineering and the advent of omics technologies offers great promise to discovering new bacterial communities yet to be studied for their lignocellulolytic ability, these processes are still largely time consuming and not cheap. Molecular studies have not eliminated the need for culture-dependent techniques, which is when an organism’s optimum functionality can be studied to enable adoption in industrial processes. More research is required to circumvent these current challenges and discover versatile, novel bacteria species which can be studied and modified for a greener outcome. Bacteria with multi-enzyme functions and extremophilic abilities will play huge roles, as they will be more versatile and able to play several roles in the production cycle. Collaborations and research-enabled environments will be vital to see a rise in bacteria adoption in lignocellulose-driven bio-refinery to derive the inherent benefits.",
"introduction": "1. Introduction Lignocellulosic biomass refers to affordable [ 1 ], superabundant, and green materials, that are vital in the goal of clean and alternative energy production and ensuring our reliance on fossils is minimized/eliminated [ 2 ]. They can be used in the sustainable production of useful chemicals, fuels [ 3 ], and renewable energy [ 4 ]. Studies have shown that lignocellulosic biomass can be broken down by contributions from several microorganisms [ 5 ] with manifold fungal and bacterial genera giving rise to cellulolytic and hemicellulolytic enzymes [ 6 ] under aerobic and anaerobic surroundings to achieve this [ 7 ]. The use of enzymes from microbial sources is being preferred to others because they are not difficult to nurture and manipulate for desired yields when compared to other sources [ 8 ]. Bacterial and fungal organisms are considered the most available biological organisms present in nature, with the ability to breakdown both manmade and natural polymers [ 9 ]. In lignin breakdown, fungi, especially white rot, have been extensively studied [ 10 ]. Despite the large amount of research that has established fungi as primary decomposers, their genetic manipulation capabilities for genetic engineering still remain very low as opposed to other organisms of interest. Fungal enzymes also do not show significant specificity and are costly to manufacture industrially. They also do not do well in extreme conditions as they cannot tolerate or adapt to altered environmental conditions [ 11 ]. Bacteria and the enzymes they produce have shown that they can adapt better to pH and temperature changes, as opposed to fungi [ 12 ]. Recent analysis of a synthetic microbial community showed that bacteria in the overall structure are more significant to lignocellulolytic enzyme activity than fungi [ 13 ]. Bacterial Glucuronoyl esterases (GEs) which arise from carbohydrate esterase family 15 were biochemically characterized and structurally determined on model substrates deepen the knowledge on their biological roles and functions and the results revealed few enzymes with higher catalytic efficiencies than previously characterized fungal GEs [ 14 ]. A halotolerant lignocellulose degrading microbial consortia was produced from salt marsh soil microbiome using wheat straw as carbon and energy source. The consortium showed bacteria possess a unique role in the breakdown of recalcitrant lignocellulose under saline conditions, as opposed to fungi. The final consortia showed greater lignocellulolytic haloenzymes than the initial one, with the results affirming bacteria’s more central role in lignocellulose degradation in saline environment compared to fungi [ 15 ]. In recent times, research focus has been turning to bacteria for lignocellulose conversion to useful products as a result of their ability and versatility [ 16 ]. To achieve success in degradation of lignocellulose biomass in the production of biofuels, it is necessary to have novel and efficient enzyme mixtures, consortia of microorganisms, and appropriate use of bioengineering to improve promising strains and create microbial communities that can use synergistic relationship with each other to breakdown the biomass. It is interesting that, in nature, bacterial abundance increases when simple carbon sources are diminished leaving their complex counterparts and higher lignin levels. These reasons, as well as a functional diversity, a wide range of terminal electron acceptors and the lignin degrading abilities are responsible for the increased bacterial interest in future biotechnological strategies [ 17 ]. A lot of research on lignin degrading bacteria has come from guts of insects and Alphaproteobacteria, Gammaproteobacteria, and Actinomycetia are some of the bacteria recognized for breaking down lignin. Discovering novel bacterial lignin degrading enzymes is vital to industrial production of next-generation biofuels. This is largely due to bacteria’s potential for use as engineered organisms involved in biofuel generation, their flexible oxygen demands and ability and range in extreme environmental conditions [ 18 ]. Time’s effect on the synergism that exists among lignocellulolytic enzymes involved in hydrolysis showed aerobic bacteria are one of the groups with the prevalent mechanism for the breakdown of lignocellulosic biomass via the free enzyme system. Anaerobic bacteria instead use an alternative lignocellulolytic system that makes use of complex protein structures like cellulosomes and xylanosomes which are supporting enzymes when biomass is hydrolyzed [ 19 ]. Bacteria also possess a handful of characteristics that make them more advantageous in the production of hydrolytic enzymes, which are vital to the degradation of lignocellulosic biomass [ 20 ]. Research findings from several researchers shows bacteria-driven breakdown of lignocellulosic biomass with some identified bacteria including Acetovibrio , Bacillus , Bacteroides , Cellulomanas , Clostridium , Erwinia , Microbispora , Ruminococcus , Streptomyces , and Thermomonospora [ 21 ]. This paper covers a review of bacterial involvement in lignocellulose breakdown into useful products. A Scopus search on 6 March 2021 using the keywords “lignocellulolytic bacteria” yielded 233 papers and covers papers from 1986 till the search date. Our results showed that papers between 2015–2021 represent triple the number of papers from 2011–2014 which was 46. Another search using the key words “lignocellulose degradation by bacteria” yielded 781 papers from 1984 till the search date. As with the first search, publications increased from the early 2000s with over 600 of the papers being published since 2010. The relevance of this study can be seen in the significant rise in publications about lignocellulolytic bacteria in recent years, as depicted in Figure 1 . From the literature, many articles on lignocellulose breakdown and mechanisms exist, but a focus on bacteria has only begun in recent years. Bacteria has not received as much reporting in bio-refinery applications as fungi. Due to its enormous potential, a review on available research is necessary to stimulate further research and discussion. This review captures the mechanism of delignification and cellulose in bacteria; distribution of lignocellulose degrading bacteria, bacterial enzymes involved in lignocellulose breakdown, and bio-refinery products. Molecular advancements have provided more insight to microbial communities than was previously possible. Thus, studies of bacteria for lignocellulolytic capabilities were also reviewed. Lignocellulose driven bio-refineries will thrive from bacterial adoption in their processes, and this is the basis for this review which covers the recent trends driven by molecular technologies, challenges, and perspectives for future research."
} | 2,361 |
38535654 | PMC10974313 | pmc | 1,375 | {
"abstract": "In pursuit of realizing neuromorphic computing devices, we demonstrated the high-performance synaptic functions on the top-to-bottom Au/ZnVO/Pt two-terminal ferroelectric Schottky junction (FSJ) device architecture. The active layer of ZnVO exhibited the ferroelectric characteristics because of the broken lattice-translational symmetry, arising from the incorporation of smaller V 5+ ions into smaller Zn 2+ host lattice sites. The fabricated FSJ devices displayed an asymmetric hysteresis behavior attributed to the ferroelectric polarization-dependent Schottky field-emission rate difference in between positive and negative bias voltage regions. Additionally, it was observed that the magnitude of the on-state current could be systematically controlled by changing either the amplitude or the width of the applied voltage pulses. Owing to these voltage pulse-tunable multi-state memory characteristics, the device revealed diverse synaptic functions such as short-term memory, dynamic range-tunable long-term memory, and versatile rules in spike time-dependent synaptic plasticity. For the pattern-recognition simulation, furthermore, more than 95% accuracy was recorded when using the optimized experimental device parameters. These findings suggest the ZnVO-based FSJ device holds significant promise for application in next-generation brain-inspired neuromorphic computing systems.",
"conclusion": "4. Conclusions The high-performance synaptic functions were magnificently demonstrated on the ZnVO-based memristive FSJ device scheme. The ZnVO active layer displayed clear ferroelectric hysteresis characteristics attributed to the polar crystalline symmetry due to the incorporation of smaller V 5+ ions in bigger Zn 2+ sites. Because of the non-volatile E p nature in ZnVO, the FSJ device exhibited voltage polarity-rectifiable asymmetric hysteresis behavior in its I–V characteristics. Additionally, the E p -adjustable Schottky field-emission rate allowed us to effectively represent both voltage pulse amplitude- and width-tunable multiple memory states. Using these astonishing characteristics, diverse synaptic functions such as EPSC, PPF, LTM, and STDP were efficaciously demonstrated. Through MNIST pattern recognition simulations, the device was shown to achieve a high accuracy up to 95.3%. Furthermore, it was also observed that the device could accomplish the versatile STDP Hebbian learning rules within a timescale of a few tens of ms. These findings suggest that the ZnVO-based FSJ device holds significant promise for next-generation brain-inspired neuromorphic computing systems.",
"introduction": "1. Introduction Neuromorphic computing, which is conceived to replicate the highly efficient parallel data computation of the human brain, has emerged as one of the most prospective techniques for realizing future artificial intelligence technology [ 1 , 2 ]. In the field of semiconductor electronics, the core challenge is to emulate the biological synapses, which are the fundamental units of the human brain responsible for information processing (e.g., logic, memory, learning, cognition, etc.). To accomplish this goal, many researchers have devoted themselves to investigating various materials and device architectures that can exhibit versatile synaptic functions with high computational efficiency and low energy consumption. At this point, we need to consider how one can mimic biological synapses to adapt and learn by using electronic devices. When considering the device operation schemes, diverse memory cells can be potential candidates that may implement neuro-inspired arithmetic computation. This is because the pivotal role of the memory cell is the dynamic nature of the biological synapse for storing, modulating, and computing the synaptic weights [ 3 ]. Additionally, the controllability of synaptic plasticity is of importance for learning and memory in both biological brains and artificial neural networks. Therefore, memory-based neuromorphic computing systems may offer great potential to achieve efficient brain-mimicked information processes as well as sophisticated cognitive functions. For instance, two-terminal memory devices, such as resistive switching memory [ 4 , 5 ], phase-change memory [ 6 , 7 ], and ferroelectric memory [ 8 , 9 ], and three-terminal devices, such as ferroelectric gate-oxide memory [ 10 , 11 ], charge-trap memory [ 12 , 13 ], and floating-gate memory [ 14 , 15 ], are feasible examples that can demonstrate the analog synaptic memory functions. Among the various memory device structures, two-terminal ferroelectric memristors may offer exceptional advantages such as simplified device structures, being devoid of extra control terminals, streamlining integration, and having rapid computational speeds [ 16 , 17 ]. These are beneficial for the demonstration of compact and energy-efficient artificial neural networks. For materializing ferroelectric memristor-based synapses, typical ferroelectric materials are often used, such as perovskite ABO 3 ferroelectric oxides (e.g., BiTiO 3 [ 18 , 19 ], BiFeO 3 [ 20 , 21 ], and Pb(Zr,Ti)O 3 [ 22 , 23 ]), non-perovskite ferroelectric oxides (e.g., HfZrO 2 [ 24 , 25 , 26 , 27 ]), and organic ferroelectric materials (e.g., P(VDF-TeFE) [ 28 , 29 ]). Except for high-quality HfZrO 2 that can be grown by atomic layer deposition [ 26 , 27 ], however, it is still difficult to grow high-quality thin films of other perovskite materials. Additionally, conventional ferroelectric materials may suffer from sneak current issues because of the strong ferroelectric domain wall motion [ 30 , 31 ]. Therefore, finding an alternative ferroelectric material is essential. Fortunately, there is an exceptional opportunity to use a ferroelectric semiconductor layer because it allows for the growth of high-quality thin films as well as the formation of the ferroelectric Schottky junction (FSJ) structure. In recent years, it has been reported that transition metal-doped ZnO semiconductors could show a ferroelectric nature at elevated temperatures [ 32 , 33 , 34 , 35 ]. In particular, vanadium-doped ZnO (ZnVO) represented an innovative approach to replace conventional ferroelectric materials. One of its most striking features is high ferroelectric stability at higher Curie temperatures above 300 K [ 36 , 37 , 38 ], providing robust solutions to perform the enhanced memory performances such as superior data retention, memory reliability, and explicit switching characteristics. These advantages specify an ample potential of ZnVO as a superior choice for demonstrating robust and reliable synaptic devices. Despite these substantial benefits, ZnVO-based FSJs and their synapse applications have not been investigated. Motivated by all these backgrounds, we therefore investigated the fabrication and the characterization of high-performance ZnVO-based two-terminal FSJ synaptic devices. The devices were fabricated in the form of top-to-bottom Au/ZnVO/Pt two-terminal FSJ memristors, and exhibited high-performance synaptic functions. Herein, we initially examine the material properties of the ZnVO active layers, such as structural phases, chemical valence states, ferroelectric hysteresis, and electrical switching characteristics, and then we thoroughly assess and discuss the synaptic functions of the Au/ZnVO/Pt FSJ synaptic devices.",
"discussion": "3. Results and Discussion In vertically stacked FSJ devices such as our Au/ZnVO/Pt scheme, the morphological surface texture is of importance because the microstructural faults, such as such grain boundaries, hillocks, and pinholes, may create a leakage path inside the vertical FSJ device. This will, in turn, eventually degrade the ferroelectric switching and electrical transport characteristics of the FSJ device. Thus, firstly, we devoted ourselves to obtaining smooth and well-merged ZnVO layers by controlling both the growth temperature and the oxygen partial pressure. When changing the substrate temperature from 200 to 500 °C (100 °C step), the 300 °C-grown ZnVO layer exhibited a smooth surface texture with no grain agglomeration ( Figure S1a–d ). Additionally, when varying the oxygen flow rate from 0 to 20 sccm (5 sccm step), it was found that the formation of hillocks and pinholes was drastically diminished at the gas flow condition of ‘Ar:O 2 = 10 sccm:20 sccm’ ( Figure S2a–d ). Based on these results, we could grow the 70 nm thick high-quality ZnVO layer at 300 °C in gas ambiance with Ar (10 sccm) and O 2 (20 sccm) ( Figure 1 b,c, see also Figure S3 ). From the XRD analysis, the sample revealed the clear diffraction pattern of the wurtzite (002) ZnVO phase ( Figure 1 d), and exhibited only a small broadening of the (002) phase ( Figure 1 e). Furthermore, no secondary phases from V-related precipitates were observed, except for two negligible peaks from the Ti adhesion layer. These depict that the high-quality (002) ZnVO layer was homogeneously grown onto the Pt metal layer. Next, we examined the elemental compositions and the chemical bonding states of the ZnVO layer. As can be seen from Figure 2 a, the XPS survey spectrum clearly displayed that the ZnVO layer involves only its intrinsic species of Zn, V, and O. From the XPS quantitative analysis, we confirmed that 2.5 at.% of V contents were incorporated in the ZnVO layer. We here note that 2.5 at.% of V was chosen on the basis of the following reasons. According to a previous report [ 39 ], the crystal phase segregation might occur when V contents exceeded 4 at.%. Additionally, it was reported that the lattice displacement in ZnVO could be optimized when 2–3 at.% of V was incorporated into the host material–ZnO [ 40 ]. The small C 1s peak in the survey spectrum is known to arise from adventitious hydrocarbon that is inevitably detected in the XPS chamber [ 41 ]. Thus, the peak position of C 1s (284.6 eV) is typically utilized as a reference binding-energy value for calibrating the core level positions of other species [ 42 ]. In the high-resolution Zn 2p spectrum ( Figure 2 b), two predominant Zn 2p 1/2 and Zn 2p 3/2 peaks appeared at 1021.4 and 1044.5 eV, respectively. The binding energy gap between the two peaks was 23.1 eV, corresponding to that of the +2 valence state for the Zn species [ 43 , 44 ]. In the case of O 1s ( Figure 2 c), the asymmetric feature was observed, and the spectrum could be deconvoluted into the three different components. Namely, the surface-residing loosely bound oxygen ions (~533.0 eV), oxygen vacancies (~531.9 eV), and covalently bonded O 2- ions (~530.5 eV) were included in the ZnVO layer [ 45 , 46 ]. Figure 2 d shows the bonding states of V, which are of the most significance in ZnVO because the valence states of V ions are directly related to the ferroelectric nature of ZnVO. As depicted in Figure 2 d, the V 2p spectrum could be deconvoluted into the three different ionic constituents. Namely, the spin–orbit doublet of both V 2p 1/2 and V 2p 3/2 could be primarily fitted to the three valence states: (i) V 5+ (i.e., 524.63 eV for V 2p 1/2 and 517.38 eV for V 2p 3/2 ), (ii) V 4+ (523.09 eV for V 2p 1/2 and 516.20 eV for V 2p 3/2 ), and (iii) V 3+ (521.67 eV for V 2p 1/2 and 515.19 eV for V 2p 3/2 ) [ 47 ]. The gray curve centered at 518.7 eV corresponds to the satellite of the O 1s core level [ 48 ]. As can be confirmed from the deconvoluted spectra, the portion of V 5+ is predominant in the present ZnVO layer. Hence, it can be inferred that the penta-valent V ions were effectively incorporated into ZnVO. In other words, the positively ionized V 5+ (ionic radius: 0.54 Å [ 47 ]) dopants were well substituted to the Zn 2+ (ionic radius: 0.74 Å [ 32 ]) cation sites in the ZnO host lattices. In transition metal-doped ZnO, the smaller dopant ions residing at the bigger Zn 2+ sites significantly give rise to the increase in the local lattice vibrations [ 49 ]. In addition, both theoretical [ 50 , 51 ] and experimental studies [ 52 , 53 , 54 , 55 , 56 ] suggested and substantiated that the lattice displacement led to the ferroelectric nature in transition metal-doped ZnO. Therefore, we evaluated the ferroelectric properties of the prepared ZnVO layer. As shown in the polarization vs. electric field (P–E) characteristic curves ( Figure 3 a), the Au/ZnVO/Pt sample clearly exhibited ferroelectric hysteresis loops, in which both the coercive field ( E c ) and the remnant polarization ( P r ) were increased with increasing magnitude of the electric-field sweeping range ( E sweep ). When E sweep = |±430 kV/cm|, P r and E c were 1.51 μC/cm 2 and 168 kV/cm, respectively. From multiple samples that were devised by identical process conditions, a similar feature was observed ( Figure S4 ). For more clarity on the ferroelectric nature of ZnVO, we assessed the ferroelectric-switching response characteristics by utilizing the positive-up–negative-down (PUND) method, which can eliminate the impact of movable defects or non-ferroelectric components. Namely, when using the P, U, N, and D pulses with the appropriate pulse-to-pulse interval ( Figure 3 b), the polarization charge with only switching components could be extracted by subtracting the U- and D-stimulated response signals from the P- and N-induced response signals, respectively (i.e., polarization charge = [(P − U) + (N − D)]/2) [ 57 , 58 ]. Here, the pulse-to-pulse interval plays a key role in distinguishing both switching and non-switching components before applying the P–U–N–D pulses. As shown in Figure 3 c, the PUND curve clearly revealed the typical shape of the ferroelectric hysteresis loop. From the PUND curve, P r and E c of ZnVO were confirmed to be 1.06 μC/cm 2 and 230 kV/cm, respectively. As aforementioned, such a clear ferroelectric characteristic could be attributed to the polar crystalline symmetry, arising from the ionic radii difference between V 5+ (0.54 Å) and Zn 2+ (0.74 Å). Namely, the smaller V 5+ ions would occupy the off-centered positions when they are substituted into the tetrahedrally coordinated host lattice sites of the bigger Zn 2+ ions [ 49 , 54 ]. This could eventually create localized dipoles within the ZnVO lattices; hence, the ferroelectric nature would exist in the whole ZnVO solid-state system. We therefore ascribe the ferroelectric behavior in our ZnVO to its broken lattice-translational symmetry, originating from the incorporation of smaller V 5+ ions into bigger Zn 2+ sites. After confirming the ferroelectric properties of ZnVO, we evaluated its ferroelectric polarization-dependent resistive switching characteristics. As can be seen from the current vs. voltage (I–V) characteristic curves ( Figure 3 d), the Au/ZnVO/Pt FSJ device exhibited asymmetric hysteresis loops in negative and positive voltage regions. Namely, the clear hysteresis loops and the reasonable on-state current values appeared in the positive voltage region, while only negligible loops with minimal current values appeared in the negative voltage region (see also the inset of Figure 3 d). Additionally, the hysteresis loops in the positive bias voltage region became larger with increasing magnitude of the sweep voltage range ( V sweep ). We here note that more than 90% of the devices, fabricated under the same experimental conditions, exhibited a similar asymmetric hysteresis feature ( Figure S5 ). Such a voltage polarity-dependent asymmetric hysteresis behavior can offer several advantages over the typical symmetric hysteresis characteristics (e.g., butterfly shape of symmetric hysteresis loops in negative and positive voltage regions [ 59 , 60 , 61 ]). For example, different from the symmetric hysteresis case, the asymmetric hysteresis characteristics with a rectifying behavior might allow explicit program/erase operations by switching only the applied voltage polarity because there is only a minimal current flow during the erase operation [ 62 ]. Furthermore, the explicit on/off switching characteristics could effectively release the sneak current issue in the cross-bar array of two-terminal synapses’ networks [ 63 ]. To help understand the charge conduction and the switching mechanisms, we fitted the I–V curves to the well-known space charge-limited conduction model [ 64 ] and the Schottky emission model [ 64 ] (see Figure S6a–d ). The I–V curve in the lower voltage region below ~1 V was well fitted to the space charge-limited conduction model, while the I–V curve in the higher voltage region above ~1 V was well fitted to the Schottky emission model. Namely, in the lower voltage region, the memristive switching behavior could initially start with the space charge-limited conduction via charge trapping and detrapping at the defect sites. After fully filling the trap sites in the higher voltage region, the charge transport mechanism would, in turn, be changed into the Schottky emission. Thus, it can be conjectured that memristive switching in the on-state current regime is mostly governed by ferroelectric polarization switching. Here, it should be noticeable that the hysteresis characteristics could be modulated by applying consecutive V sweep . As shown in Figure 3 e, when applying consecutive V sweep 10 times, interestingly, the current level gradually increased with increasing number of sweeping cycles (see also the inset of Figure 3 e). To quantitatively understand the sweeping-cycle-dependent on-state current variation, we determined the effective Schottky barrier height ( ϕ B ) by using the well-known Schottky equation [ 32 ]: (1) J = J 0 exp ( q V / η k T ) \n (2) J 0 = A A * T 2 e x p ( − q ϕ B / k T ) , \nwhere J 0 is the reverse saturation current, q is the electron charge, η is the ideality factor, k is the Boltzmann constant, T is the absolute temperature, A is the contact area, and A* is the Richardson constant (32 A·cm −2 K −2 for ZnO [ 65 ]). As plotted in Figure 3 f, the initial ϕ B values were determined to be ~0.65 and ~0.57 eV at the first stage of onward and backward sweeping, respectively, and these are in agreement with the literature values [ 65 ]. As the sweep number increased, the ϕ B values in the onward and backward sweeping cycles were decreased to ~0.59 and ~0.53 eV, respectively. This can be interpreted by the accumulated ferroelectric dipole moments ( E p ) that are continuously created and retained by consecutive V sweep . Namely, the effective ϕ B would gradually decrease with increasing sweep number ( Figure 3 f, inset), as discussed in detail later. Prior to discussing the synaptic characteristics of the Au/ZnVO/Pt FSJ device, we here explain the plausible mechanism of the rectified asymmetric hysteresis behavior. Figure 4 illustrates the energy band diagrams of the Au/ZnVO/Pt FSJ device in various bias conditions. At thermal equilibrium ( Figure 4 a), the Schottky barriers would be created at both Au/ZnVO and ZnVO/Pt interfacial regions because the work function energy values of both Au (Φ Au ≈ 5.1 eV [ 66 ]) and Pt (Φ Pt ≈ 5.7 eV [ 66 ]) are much greater than the electron affinity of the host material ZnO (χ ZnO ≈ 4.1 eV [ 65 , 67 , 68 ]). In addition, since Φ Pt > Φ Au , the Schottky barrier height on the ZnVO/Pt side should be larger than that on the Au/ZnVO side. Under the Pt-grounded condition, therefore, the Schottky field emission could easily occur on the ZnVO/Pt side when applying the positive upward bias voltage stress (e.g., V A = + V 1↑ ) to the Au electrode terminal ( Figure 4 b). Namely, because of both the image force barrier lowering effect and the greater electric field on the ZnVO/Pt side (which is greater than that on the Au/ZnVO side), the effective Schottky barrier would easily become low and thin enough to ensure the electron emission from Pt to Au through ZnVO. At the same time, the external electric field ( E ex ) from + V 1↑ would lead to the dipole alignment inside the ferroelectric ZnVO layer. Thus, the additional field from the ferroelectric dipole moment ( E p ) would be created along with the E ex direction. As one increased the applied upward voltage (e.g., V A = + V 2↑ ), the electron emission probability would become larger than that at + V 1↑ ( Figure 4 c). When assuming that the magnitude of + V 2↑ exceeds the coercive voltage (+ V c ) of ZnVO, the ZnVO layer should be laid on the full polarization state with the non-volatile E p . When decreasing the applied downward voltage back to + V 1↓ ( Figure 4 d), therefore, the electron emission probability would remain high because the ferroelectrically retained E p still holds the potential gradient inside the ferroelectric ZnVO layer. In other words, the potential difference (Δ μ ) could occur in the two bias conditions between upward + V 1↑ and downward + V 1↓ even though the voltage magnitudes are same in both + V 1↑ and + V 1↓ . This could eventually lead to a larger electron emission rate at + V 1↓ than at + V 1↑ , and it could result in the hysteresis behavior in the I–V characteristic curve. Such a retainable E p component would not be smeared out unless the ferroelectric dipoles are unpolarized at − V c . When returning back to zero bias (e.g., V A = 0 ↓ V), thus, the E p should retain inside the ZnVO layer, while the electron emission should be drastically reduced because of the increased effective Schottky barrier width ( Figure 4 e). Under this circumstance, the applied negative voltage (e.g., V A = − V 3 ) would be primarily spent on depoling the ferroelectric dipoles. Namely, the effective Schottky barrier would remain high and thick on the Au/ZnVO side because the large portion of − V 3 should compensate the E p that was created by + V 2↑ . This behavior will be maintained unless the magnitude of |− V A | largely exceeds |− V c |. At a moderate |− V A | below |− V c |, therefore, the Schottky emission rate would be kept low so that no hysteretic behavior occurs in the − V A↑↓ region ( Figure 4 f). When repeating these switching cycles, the effective ϕ B value would gradually decrease because of the retained E p and its corresponding increase in Δμ. This could eventually lead to a gradual increase in the Schottky emission rate so that the on-state current would gradually increase upon increasing switching cycles (e.g., increasing sweep numbers or pulse numbers). The ferroelectric E p -dependent ϕ B variation and its corresponding memristive characteristics could offer a significant advantage for demonstrating synaptic functions. Based upon this feature, we emulated the biological synaptic functions by using the present Au/ZnVO/Pt FSJ device. Figure 5 a,b show the transient characteristics of excitatory postsynaptic current (EPSC) after applying a single presynaptic stimulus with pulse amplitudes ( V pulse ) of 4 and 4.5 V, respectively. Here, the read-out voltage ( V read ) was fixed constant at 1.3 V, while the pulse width ( t pulse ) was varied from 1 μs to 1 ms. In both cases ( Figure 5 a,b), the device showed the typical EPSC transient curves after applying the single pulse stimulus. Namely, the electric pulse-stimulated postsynaptic current (ΔPSC) was rapidly stabilized after its initial decay (see also Figure S7a ). In addition, the magnitude of residual ΔPSC increased with increasing t pulse . Notably, the device revealed a t pulse -dependent gradual ΔPSC augmentation, particularly when applying the 4.5 V pulse stimulus. Furthermore, the residual ΔPSC value for each t pulse was greater when V pulse was 4.5 V compared to that when V pulse was 4.0 V. These behaviors are quite similar to those of the biological synapse. In other words, the synaptic plasticity in biological systems depends on both the strength and the duration of incident stimuli. Thus, it can be conjectured that the infusion of the relatively modest stimuli may strengthen the synaptic plasticity so that our Au/ZnVO/Pt FSJ device can mimic the biological synapse. To verify the above hypothesis, we examined the short-term memory (STM) and the long-term memory (LTM) characteristics of the Au/ZnVO/Pt FSJ device. Firstly, the paired pulse facilitation (PPF) characteristics were assessed to evaluate how effectively the device can perform short-term synaptic strength. PPF quantifies the amplification ratio of ΔPSC in between the first and the second peaks, corresponding to the first and the second pulse stimuli, respectively. At this point, the pulse-to-pulse interval ( t interval ) between the two pulses is of importance because the second stimulus could primarily contribute to updating the short-term synaptic strength. Thus, we measured the variation in ΔPSC with respect to t interval . Similar to EPSC, the PPF curves also showed typical transient responses to the applied pulses (see Figure S7b ). In the PPF case, however, the second ΔPSC value increased after applying the second pulse from the paired pulses ( Figure 5 c). Here, it should be noticed that the magnitude of ΔPSC decreased with increasing t interval . This is because, during long t interval , the ferroelectrically polarized dipoles were somewhat depoled so that their memory retention weakened. Additionally, the discrepancy between the two peaks (i.e., A 2 − A 1 , see the inset of Figure 5 d) tended to decrease with increasing t interval ( Figure 5 d). Accordingly, the PPF index (i.e., ( A 2 − A 1 )/ A 1 × 100%) exponentially decayed with increasing t interval . Such a PPF decay can be attributable to two distinct relaxation phases (i.e., rapid and slow) [ 69 , 70 ]: (3) P P F i n d e x = C 1 e x p − t i n t e r v a l / τ 1 + C 2 e x p − t i n t e r v a l / τ 2 , \nwhere τ 1 and τ 2 are the time constants for the rapid and slow relaxation phases, respectively, and C 1 and C 2 denote the initially facilitated values for the rapid and slow relaxation phases, respectively. From the fitting curve (see the red line in Figure 5 d), τ 1 and τ 2 were determined to be 8.34 and 352.09 ms, respectively, and these values belong to the reasonable range of the biological synapse [ 71 ]. This specifies that the present Au/ZnVO/Pt FSJ device could splendidly replicate the biological synapse. In the biological synapse, the transfer of selected information from STM to LTM represents a fundamental synaptic learning rule. LTM signifies the permanent change in synaptic weights, updating from the high-frequency consecutive stimuli, while STM rapidly reverts to the initial state from the temporarily updated memory state. Thus, similar to the rehearsal process in the human brain [ 69 , 72 ], repetitive practice may enhance the transition probability from STM to LTM (see the left-hand-side panel in Figure 6 a). In our device scheme, such a rehearsal process can be demonstrated by gradual thinning of the Schottky barrier width. As discussed above, the non-volatile E p , created by the applied electrical pulse, yields a change in Δ μ ( Figure 4 d). Additionally, it was also observed that the magnitude of ΔPSC depends on the pulse parameters of V pulse , t pulse , and t interval ( Figure 5 a–d). These infer that, when choosing the appropriate pulse parameters, the magnitude of Δ μ can be gradually increased by applying the consecutive pulses because the degree of polarization can also be gradually increased by applying the consecutive pulses (see the right-hand-side panel in Figure 6 a). Hence, the effective Schottky barrier width would become thinner and thinner upon increasing the number of pulse stimuli, resulting in enhanced retention with increased conductivity. Based on this idea, we examined the LTM characteristics of the Au/ZnVO/Pt FSJ device. As shown in Figure 6 b, the device clearly exhibited long-term potentiation (LTP) and long-term depression (LTD) characteristics when the device was subjected to 100 consecutive LTP pulses ( V pulse = 4 V, t pulse = 1 ms, and t interval = 5 ms) and 100 consecutive LTD pulses ( V pulse = −1 V, t pulse = 100 μs, and t interval = 10 ms). The sequentially updated synaptic weights can also be traced from the inset of Figure 6 b. After observing the clear LTP/LTD functions, we evaluated the dependence of the ΔPSC dynamic range on the V pulse magnitude because the ΔPSC value relies on the variation of Δ μ , which is predominantly dependent on E p (∝ V pulse ). For this assessment, we only varied the pulse magnitudes for both LTP and LTD (i.e., V LTP and V LTP ), while t pulse , t interval , and V read were fixed at 1 ms, 1 ms, and 1.3 V, respectively. As a result, the dynamic range of ΔPSC increased with increasing V LTP and V LTP ( Figure 6 c). From the application point of view, the electronic synapse should possess not only a wide dynamic range but also a good linearity because both of the two factors are essential to improve the learning accuracy as well as the training efficiency of the synapse. The linearity of the synapse can be quantitatively analyzed by following equation [ 73 ]: (4) G P = G m i n + G 0 1 − e − A p \n (5) G D = G m a x − G 0 1 − e A p − 1 \n (6) G 0 = G m a x − G m i n 1 − e − A p , \nwhere G P and G D denote the conductance values for LTP and LTD, respectively; G min and G max are the minimum and the maximum conductance values, respectively; and p is the number of applied pulses. A is the fitting parameter that presents the nonlinearity of the synaptic weights with respect to the applied pulses. For instance, | A | becomes large when the LTP/LTD curves are convex, whereas | A | converges to zero when the LTP/LTD curves are linear. By fitting the experimental LTP and LTM data to the above equations, the | A | values were calculated to be 0.91–1.03 for LTP and 7.05–9.25 for LTD. The high degree of nonlinearity in the LTD mode is thought to result from the early depression (i.e., abrupt change in ΔPSC at the initial LTD pulse stage), presumably because of the small reverse saturation current in the negative bias voltage region (see Figure 3 b). To improve the linearity in the LTD mode, improving the rectification characteristics can be the next step for realizing future high-performance neuromorphic synapse networks (e.g., reducing the oxygen vacancies inside the ferroelectric layer and/or decreasing the interfacial states at the metal/ferroelectric junction). Although the above issue (i.e., improving the LTD linearity) is still challenging in two-terminal synaptic devices [ 74 , 75 ], utilizing the pulse modulation methods (e.g., using the incremental pulse scheme [ 76 , 77 ] and/or changing the pulse frequency [ 78 , 79 ]) can be an effective solution to improve both the linearity and the symmetricity for reliable LTP/LTD functions. We therefore tried to find the proper pulse schemes by modulating the magnitude of V pulse . As represented in the inset of Figure 7 , we chose incremental pulse schemes for both V LTP and V LTP , while t pulse , t interval , and V read were fixed at 500 μs, 500 μs, and 1.3 V, respectively. Compared to the case of the identical pulse scheme ( Figure 6 c), the linearity was significantly improved when using the incremental pulse scheme ( Figure 7 ). Through fitting the experimental date to Equations (2)–(4), we confirmed that the | A | values were improved to 0.34–0.72 for LTP and 2.13–2.17 for LTD when the incremental pulse schemes were subjected to the device. As aforementioned, the improved linearity is closely related to the deep learning accuracy of the synapse. We therefore tested the pattern recognition accuracy within an artificial neural network system, which is based upon the backpropagation learning rule in a neuromorphic system. For this test, we employed a synthetic multilayer neural network, comprising one input layer, three hidden layers, and one output layer ( Figure 8 a). Here, we note that the pattern recognition accuracy was assessed by theoretical simulation using the Modified National Institute of Standard and Technology (MNIST) handwritten digit dataset, in which 60,000 handwritten training images and 10,000 testing images are included. Each handwritten training image involves 28 × 28 pixels, and they are converted into the 784 input vector neurons at the input layer. Those vectors are delivered to the 10 output neurons via propagating through the 128 → 64 → 32 nodes of the hidden layers. Then, the output layer calculates the recognition accuracy by comparing the updated synaptic weights and the database values. Through multiple simulation runs using the experimental parameters from Figure 6 c and Figure 7 , we found that the recognition accuracy was improved when using the incremental pulse scheme. For example, after 10 epochs, the pattern recognition accuracy reached 95.1–95.3% for the incremental pulse scheme ( Figure 8 b), whereas this was 93.4–93.9% for the identical pulse scheme ( Figure 8 c). Finally, we examined the spike-timing-dependent plasticity (STDP) characteristics, which are of importance for emulating the perceptron role of the synapse in the neural network [ 80 , 81 , 82 ]. In electronic synapses, STDP is typically characterized by measuring the chance in synaptic weights (Δ w ), depending on the time difference between the simultaneously applied pulse pair of the presynaptic and the postsynaptic stimuli (i.e., Δ t = t post − t pre ). Thus, STDP can allow us to assess the synaptic perceptron role that discriminates the temporal difference in synaptic states between the presynapse and the postsynapse. As shown in Figure 9 , by changing the polarities of the applied pair pulses (see each inset of the figure), we efficaciously demonstrate the four different Hebbian STDP learning rules on our Au/ZnVO/Pt FSJ device, i.e., (i) the asymmetric Hebbian rule ( Figure 9 a), (ii) the asymmetric anti-Hebbian rule ( Figure 9 b), (iii) the symmetric Hebbian rule ( Figure 9 c), and (iv) the symmetric anti-Hebbian rule ( Figure 9 d). In all cases, Δ w tended to decay as Δ t was increased. Such a Δ t -dependent Δ w decay characteristic can be further analyzed by parametrizing the STDP time constant ( τ s ) by using the following equations [ 83 ]: (7) ∆ w = A e x p − Δ t τ s + ∆ w 0 ( for asymmetric Hebbian rules ) \n (8) ∆ w = A e x p − Δ t 2 τ s 2 + ∆ w 0 ( for symmetric Hebbian rules ) , \nwhere A is the scaling factor and Δ w 0 is the constant value that is non-associative to the synaptic weight change. By fitting the experimental parameters to the above equations, the τ s values were extracted to be (i) 22.58, (ii) 18.84, (iii) 21.99, and (iv) 7.63 ms from Figure 9 a–d, respectively. The obtained τ s values, i.e., timescales of a few tens of milliseconds, are analogous to those of the biological synapses in the human brain [ 84 ]. Furthermore, the rapid change in Δ w can be a substantial benefit for the neural network circuit design because the temporal Δ w change within a peripheral Δ t range (i.e., short τ s ) is of excellent use for parallel computing in future neuromorphic computing systems."
} | 8,771 |
30815030 | PMC6376720 | pmc | 1,376 | {
"abstract": "Lignin is the most abundant aromatic substrate on Earth and its valorization technologies are still under developed. Depolymerization and fragmentation are the predominant preparatory strategies for valorization of lignin to chemicals and fuels. However, due to the structural heterogeneity of lignin, depolymerization and fragmentation typically result in diverse product species, which require extensive separation and purification procedures to obtain target products. For lignin valorization, bacterial-based systems have attracted increasing attention because of their diverse metabolisms, which can be used to funnel multiple lignin-based compounds into specific target products. Here, recent advances in lignin valorization using bacteria are critically reviewed, including lignin-degrading bacteria that are able to degrade lignin and use lignin-associated aromatics, various associated metabolic pathways, and application of bacterial cultures for lignin valorization. This review will provide insight into the recent breakthroughs and future trends of lignin valorization based on bacterial systems.",
"conclusion": "Conclusion and perspectives Even though various lignin-degrading bacteria were found widely and some lignin-based aromatics metabolic pathways have been elucidated and applied to produce bio-products. Based on the current knowledge, it has been suggested that the conversion of high-molecular weight lignin into bacteria available compounds (such as aromatic monomers or dimers) is the major bottleneck in the synthesis of bio-products from lignin. There is still a long way to go before lignin valorization at an industrial scale with bacteria can be realized technically and economically. The following perspectives should be considered for future studies: Most lignin-degrading bacteria can only assimilate a fraction of lignin-based compounds. More efficient bacteria and metabolic pathways are in need for the comprehensive utilization of lignin or lignocellulosic biomass. As we further our understanding of lignin degradation process in bacteria, it is expected that pathway engineering can be applied in suitable bacterial hosts to assimilate more lignin components, as well as achieving high yields of the targeted products. One drawback of lignin valorization by bacterial system is the low product titers. The product titers from lignin-based solutions are much lower than from glucose or other common substrates. Except the limited lignin utilization capability of target bacteria, the inhibition from lignin-based compounds is another key factor that causes the low microbial productivity. Fed-batch fermentation is a good solution for releasing the inhibition from high content lignin. Moreover, some microbes with high tolerance to lignin-based compounds can be obtained by screening, genetic engineering, or adapted evolution. One major disadvantage of using microbes in lignin valorization processes is their low capability in utilizing water-insoluble and/or high-molecular weight lignin. Thus, appropriate depolymerization processes are required to disrupt lignin-enriched substrates into low-molecular weight and water-soluble species that can be assimilated by bacteria efficiently (Fig. 3 ). In particular, gasify the solid lignin and run a syngas bacterial culture may be a promising strategy for lignin valorization by bacteria cultures. In this case, the gasified components will be utilized more efficiently by related bacteria compared with the solid lignin or other lignin streams. Fig. 3 The scheme of hybrid lignin valorization route with depolymerization process and biochemical assimilation system \n In previous lignocellulosic biorefinery designs, biomass pretreatment was generally designed for high content fermentable sugars. As different pretreatments can contribute to different lignin characteristics [ 137 ], lignin valorization is expected to be considered in addition to fermentable sugars when pretreatment and process are designed. In addition to biological methods, other alternative methods have also applied wildly in lignin valorization, e.g., reduction, supercritical fluids, ionic liquids treatment, and fractionation by ultrafiltration and selective precipitation [ 11 , 13 ]. These methods are not standalone and different alternatives pathways must be integrated for better lignin valorization. For example, the present results suggest that the productivities of lignin valorization by biological methods are relatively low and many bacteria can only utilize small lignin fragments. Thus, it is promising to integrate the chemical or physical lignin depolymerization processes and biological assimilation processes."
} | 1,169 |
38333584 | PMC10850570 | pmc | 1,377 | {
"abstract": "Introduction Ligninolytic bacteria can secrete extracellular enzymes to depolymerize lignin into small-molecular aromatics that are subsequently metabolized and funneled into the TCA cycle. Carbohydrates, which are the preferred carbon sources of bacteria, influence the metabolism of lignin-derived aromatics through bacteria. Methods In this study, untargeted metabolomics and transcriptomics analyses were performed to investigate the effect of carbohydrates on lignin degradation mediated by Bacillus amyloliquefaciens MN-13, a strain with lignin-degrading activity that was isolated in our previous work. Results The results demonstrated that the cell growth of the MN-13 strain and lignin removal were promoted when carbohydrates such as glucose and sodium carboxymethyl cellulose were added to an alkaline lignin-minimal salt medium (AL-MSM) culture. Metabolomics analysis showed that lignin depolymerization took place outside the cells, and the addition of glucose regulated the uptake and metabolism of lignin-derived monomers and activated the downstream metabolism process in cells. In the transcriptomics analysis, 299 DEGs were screened after 24 h of inoculation in AL-MSM with free glucose and 2 g/L glucose, respectively, accounting for 8.3% of the total amount of annotated genes. These DEGs were primarily assigned to 30 subcategories, including flagellar assembly, the PTS system, RNA degradation, glycolysis/gluconeogenesis, the TCA cycle, pyruvate metabolism, and tryptophan metabolism. These subcategories were closely associated with the cell structure, generation of cellular energy, and precursors for biosynthetic pathways, based on a − log 10 (P adjust) value in the KEGG pathway analysis. Conclusion In summary, the addition of glucose increased lignin degradation mediated by the MN-13 strain through regulating glycolysis, TCA cycle, and central carbon metabolism.",
"conclusion": "4 Conclusion This study revealed that the addition of carbohydrates, such as glucose and sodium carboxymethyl cellulose, accelerates lignin degradation mediated by B. amyloliquefaciens MN-13 inoculated in AL-MSM, with alkaline lignin as the only carbon source. This study also provides metabolomics and transcriptomics details for exploring the synergistic effects of glucose on lignin degradation, which is mediated by bacteria. The acceleration of lignin degradation can be attributed to the upregulation of glycolysis, the TCA cycle, and central carbon metabolism with the addition of glucose. These findings offer new insights into the regulation and influence of carbon sources on lignin degradation mediated by B. amyloliquefaciens and a synergistic mode for sugar and aromatic metabolism. Based on these findings, a synergistic combination of cellulase-producing strains and strain MN-13 will be performed in our future research in order to verify the feasibility of microbial-mediated full component utilization of lignocellulose.",
"introduction": "1 Introduction Lignocellulose is generally considered to be the most abundant and sustainable feedstock for bioenergy and bio-product manufacturing ( Kumari and Singh, 2018 ). Lignocellulose is primarily comprised of three complex compounds, namely, cellulose, hemicellulose, and lignin, which are highly resistant to degradation; thus, efficient deconstruction of lignocellulose is difficult. As a result, there has been increasing research interest in the pretreatment of lignocellulosic biomass for further processing into high-value chemicals ( Bugg et al., 2011 ). Among these chemical, physical, and biological treatments, microbial degradation is considered a promising solution for the conversion of lignocellulosic biomass ( Gupta and Verma, 2015 ; Achinivu, 2018 ; Kumari and Singh, 2018 ). To date, the available studies have demonstrated that biological processing platforms can convert cellulose and hemicellulose into biofuels; however, none of these platforms can convert both sugar and lignin into biofuels or high-value chemicals, resulting in a tremendous waste of lignin biomass and a huge environmental challenge ( Liu C.-G. et al., 2019 ). Lignin is a highly complex branched polymer derived mainly from three monolignans: the 4-hydroxyphenyl (H), guaiacol (G), and syringyl (S) units ( Mnich et al., 2017 ). Due to the complex bond linkages between the three aromatic units of lignin, efficient delignification and lignin conversation remain major challenges for lignocellulosic biomass utilization and environmental sustainability ( Liu et al., 2022 ). Many microorganisms and their enzymes involved in lignin degradation have been thoroughly studied over the last few decades ( Atiwesh et al., 2022 ), e.g., white rot fungus and its extracellular ligninolytic enzymes, such as lignin peroxidases (LiPs), manganese-dependent peroxidases (MnPs), versatile peroxidases (VPs), dye-decolorizing peroxidases (DyPs), and laccases (Lac) ( Hunt et al., 2013 ; Rodriguez-Couto, 2017 ). Recently, there has been growing interest in ligninolytic bacteria due to their versatile nutrient and environmental adaptation, despite their lower lignin degradation efficiency than fungi ( Huang et al., 2013 ). Among these bacteria, members of Rhodococcus , Pseudomonas putida , Sphingomonas paucimobilis , and Streptomyces viridosporus have shown great potential in lignin degradation ( Reshmy et al., 2022 ). Recently, some Bacillus sp. strains have also been reported to be highly efficient in lignin degradation ( Zhu et al., 2017 ; Mei et al., 2020 ). In our previous study, a strain of B. amyloliquefaciens named MN-13 (accession number of the 16S rRNA gene sequence in NCBI GenBank: KP292553) with lignin-degrading ability was isolated and stored in our laboratory. The multi-copper oxidase CotA and dye-decolorizing peroxidases from B. amyloliquefaciens MN-13 were expressed in Escherichia coli, and the roles of the corresponding recombinant proteins in the cleavage of guaiacylglycerol-beta-guaiacyl ether and the oxidization of Cα and Cβ of the aromatic intermediates to generate benzaldehydes and phenyl acetones were also demonstrated ( Yang et al., 2018 , 2019 ). These findings indicate that some strains of B. amyloliqueficiens exhibit strong lignin degradation performance. However, compared with fungi, lignin-degrading bacteria and their ligninolytic enzymes are much less well characterized ( Wan and Li, 2012 ; Iram et al., 2021 ). With the development in omics technology, the metabolic pathways of lignin degradation mediated by bacteria have been progressively identified. Lignin degradation mediated by bacteria involves three main steps: lignin depolymerization, degradation of lignin-derived aromatics, and target product biosynthesis ( Abdelaziz et al., 2016 ; Wada et al., 2021 ; Yaguchi et al., 2021 ). Depolymerization of lignin into aromatics depends on the oxidation catalyzed by multiple enzymes, such as laccases, peroxidases, and additional oxidative enzymes from bacteria ( Masai et al., 2007 ; Ragauskas et al., 2014 ; Rahmanpour and Bugg, 2015 ; Kamimura et al., 2019 ). As a result, aromatic intermediates derived from lignin depolymerization accumulate ( Zhang and Wang, 2020 ), initiating further degradation of aromatic compounds through various pathways, e.g., β-ketoadipate, phenylacetic acid, and meta pathways ( Ragauskas et al., 2014 ; Salvachúa et al., 2015 ; Janusz et al., 2017 ; Li et al., 2019 ; Liu et al., 2019a ). The degradation products of aromatics enter the central carbon metabolism process through the tricarboxylic acid (TCA) cycle ( Fuchs et al., 2011 ; Wells and Ragauskas, 2012 ; Johnson et al., 2019 ). These pathways contribute to the microbial conversion of various lignin-derived aromatic molecules into structure carbon and energy sources. On the other hand, carbohydrates, as common, easy-to-use carbon sources for microorganisms, and the major source of energy for living cells via glycolysis and the TCA cycle, will compete with lignin to act as the preferential carbon source because both carbohydrates and lignin are finally funneled into central carbon metabolism to provide energy for cells. This competition undoubtedly interferes with lignin degradation by bacteria. On the other hand, as reported previously, the process of lignin degradation mediated by bacteria requires extensive reducing power and energy, which is mainly generated by the glycolysis of glucose (hexose), to deal with the decomposition of polymeric structures and corresponding oxidative stress during aromatic compound catabolism ( Li et al., 2019 ). Therefore, several studies have evaluated the co-fermentation of lignin with glucose, with the findings indicating that the addition of glucose can promote the process of lignin degradation ( Linger et al., 2014 ; Salvachúa et al., 2015 , 2020 ; Liu et al., 2019b ). However, to the best of our knowledge, no published studies have investigated the detailed mechanism, underlying the effect of carbohydrates on lignin degradation by bacteria. Therefore, this study investigated the effect of carbohydrates on lignin degradation mediated by B. amyloliquefaciens MN-13 metabolomics and transcriptomics approaches. The synergistic effect of different carbon sources on lignin degradation mediated by B. amyloliquefaciens MN-13 was explored.",
"discussion": "3 Results and discussion 3.1 Effects of carbohydrates on cell growth and lignin removal The cell growth of the MN-13 strain and lignin removal in AL-MSM with different carbohydrates are shown in Figures 1A , B , respectively. The results revealed that the addition of different carbohydrates to AL-MSM affected the cell growth of the MN-13 strain and lignin degradation. Cell growth and lignin degradation were promoted within 24 h of the addition of carbohydrates to AL-MSM. Among the tested carbohydrates, glucose and sodium carboxymethyl cellulose had significantly greater promotion effects than other carbohydrates. When the carbohydrates were consumed, the majority of bacterial cells became dormant or formed spores, and some bacteria died. Therefore, the cell growth of the MN-13 strain decreased, and lignin removal remained unchanged over time. Figure 1 Effects of different carbohydrates on cell growth and lignin degradation. (A) Cell weight; (B) lignin removal. Glu, AL-MSM with 2.0 g/L glucose; FP, AL-MSM with 2.0 g/L filter paper; DC, AL-MSM with 2.0 g/L degreasing cotton; SCC, AL-MSM with 2.0 g/L sodium carboxymethyl cellulose; CB, AL-MSM with 2.0 g/L cellobiose; CK, AL-MSM with no extra carbohydrates. 3.2 Effects of different concentrations of glucose on cell growth and lignin degradation Due to the ability of glucose to promote cell growth and lignin degradation, we further investigated the effects of different concentrations of glucose on cell growth of the MN-13 strain and lignin degradation ( Figures 2A , B ). Figure 2 Effects of different concentrations of glucose on the cell growth of the MN-13 strain and lignin degradation. (A) Cell growth; (B) lignin removal. 1 g/L Glu, 2 g/L Glu and 4 g/L Glu: AL-MSM with 1 g/L, 2 g/L, and 4 g/L glucose respectively; CK: AL-MSM with no extra carbohydrates. There was a smaller increase in the cell weight of the MN-13 strain inoculated in AL-MSM with 1 g/L glucose as compared with the cell weight of those inoculated in AL-MSM with 2 g/L and 4 g/L glucose; however, there was no significant difference between AL-MSM with 2 g/L and 4 g/L glucose after 24 h of incubation, which suggests that 1 g/L glucose is not adequate to support cell growth, and 4 g/L might be excessive. Additionally, the maximum lignin removal mediated by the MN-13 strain within 24 h was observed with inoculation in AL-MSM with 2 g/L glucose. Therefore, 2 g/L of glucose in AL-MSM was used as the condition for the metabolomics and transcriptomics analyses. 3.3 Metabolomics and transcriptomics analyses 3.3.1 Cell growth curves of the MN-13 strain in AL-MSM and AL-MSM with 2 g/L glucose To comprehensively investigate the influence of glucose on lignin degradation, the growth of B. amyloliquefaciens MN-13 in AL-MSM and AL-MSM with 2 g/L glucose was monitored, and the results are shown in Figure 3 . The biomass of B. amyloliquefaciens MN-13 in AL-MSM with 2 g/L glucose reached a maximum after 22 h of inoculation while that in AL-MSM exhibited a low growth rate. Therefore, fermentation cultures were ceased at 22 h, and the cells were collected and treated for metabolomics and transcriptomics analyses. Figure 3 Growth curve of B. amyloliquefaciens MN-13 in AL-MSM and 2 g/L glucose+ AL-MSM. 3.3.2 Metabolomics analysis The intracellular and extracellular metabolite profiles of the MN-13 strain incubated in AL-MSM (A group) and AL-MSM with 2 g/L glucose (C group), respectively, were compared. To ensure the stability and reliability of the experimental data and results, three repetitions for each group were performed. A total of 258 metabolites were identified from the fermentation broth (extracellular), and 306 metabolites were identified from the cells (intracellular) in the A and C groups. PCA demonstrated clear grouping between the samples ( Supplementary Figure S1 ). Based on a variable importance in the projection (VIP) > 1 and p < 0.05, there were 57 differentially accumulated intracellular metabolites (DAIMs) and 54 differentially accumulated extracellular metabolites (DAEMs) between groups A and C ( Supplementary Tables S2, S3 ). These differentially accumulated metabolites (DAMs) showed different regulation patterns, with 25 DAIMs and 34 DAEMs upregulated and 32 DAIMs and 20 DAEMs downregulated between groups A and C, respectively ( Figure 4 ). Since there were more lignin-derived aromatic compounds in DAEMs than in DAIMs ( Supplementary Tables S2, S3 ), it could be concluded that lignin was depolymerized into low-molecular-weight aromatic compounds outside the cell, and some lignin-derived intermediates were taken up into the cells for further degradation. The latter conclusion was confirmed by the presence of the lignin-derived monomer 4-hydroxycinnamic acid ( p -coumaric acid) and protocatechuic acid in DAIMs. Protocatechuic acid is generally considered a gradation product from lignin-derived monomer hydroxyl-cinnamic acid ( Gurujeyalakshmi and Mahadevan, 1987 ; Andreoni et al., 1995 ; Parke and Ornston, 2003 ; Plaggenborg et al., 2003 ). In this study, the higher accumulation of 4-hydroxycinnamic acid and lower abundance of protocatechuic acid in group C indicates that the addition of glucose promoted the uptake of 4-hydroxycinnamic acid into the cells and the subsequent degradation of protocatechuic acid. Additionally, with the addition of glucose, oxoglutaric acid and succinic acid, involved in the TCA cycle, exhibited high accumulation, indicating greater NADH generation of energy. As reported previously, the process of lignin degradation mediated by bacteria requires extensive reducing power and energy to deal with the cleavage of the polymeric structure and corresponding oxidative stress caused by the metabolism of lignin-derived aromatics ( Li et al., 2019 ). Therefore, it can be concluded that the addition of glucose promoted lignin depolymerization and lignin-derived aromatics uptake and catabolism, which is consistent with the findings of many previous studies ( Linger et al., 2014 ; Salvachúa et al., 2015 , 2020 ; Liu et al., 2019b ). Meanwhile, the presence of lignin-derived monomers, such as 3-hydroxybenzoic acid, vanillic acid, alpha-oxo-benzeneacetic acid, 4-hydroxyphenylacetaldehyde, and 3-methylbenzyl alcohol in DAEMs, indicates that the addition of glucose affected the depolymerization of lignin and the uptake of these lignin-derived aromatics. Figure 4 Heat map of differentially accumulated metabolites between groups A and C. (A) DAIMs between group A (A1) and group C (C1); (B) DAEMs between group A (A2) and group C (C2). To further understand the effect of glucose on lignin degradation mediated by the MN-13 strain, the KEGG enrichment analysis was performed on the DAIMs. A total of 20 KEGG pathways were found in A vs. C, according to the criterion of p -value <0.05 ( Figure 5 ). Among them, the DAIMs were mainly involved in the biosynthesis of amino acids; alanine, aspartate, and glutamate metabolism; central carbon metabolism; biosynthesis of phenyl-propanoids; 2-oxocarboxylic acid metabolism; phenylalanine, tyrosine, and tryptophan biosynthesis; and ABC transporters. These enriched pathways suggest that the addition of glucose promoted the degradation of lignin, which uses phenyl propanoids as building blocks and funneled lignin-derived intermediates into central carbon metabolism and the biosynthesis of amino acids. Figure 5 KEGG enrichment analysis of DAIMs between groups A and C. The vertical coordinates represent the metabolic pathways and the horizontal coordinates represent the effect values of enrichment in different metabolic pathways. 3.4 Transcriptomics analysis 3.4.1 Changes in the expression of genes related to lignin degradation To characterize the gene expression profiles of the MN-13 strain cultured in AL-MSM (A group) and AL-MSM with 2 g/L glucose (C group), transcriptomics analysis was performed to identify the differentially expressed genes (DEGs) between the groups (A/C). PCA indicated that six samples could be unambiguously assigned to the two groups ( Figure 6 ). In total, 3,598 genes were identified, among which genes encoding peroxidases and key oxidases involved in lignin depolymerization, such as gene-LUX28_RS15125 (thiol peroxidase), gene-LUX28_RS19610 (heme peroxidase), gene-LUX28_RS19895 (Dyp-type peroxidase YwbN), and gene-LUX28_RS03655 (spore coat protein A, cotA laccase), were slightly upregulated in group C. This indicates that lignin degradation mediated by the MN-13 strain incubated in AL-MSM with 2 g/L glucose was more active than the MN-13 strain that was incubated in AL-MSM. Figure 6 Principal component analysis (PCA) plot of the transcriptome data from the MN-13 strain incubated in AL-MSM (A3 group, red spots) and in AL-MSM with 2 g/L glucose (C3 group, blue spots). Aromatic O -demethylation, hydroxylation, and decarboxylation are generally considered to be rate-limiting steps in the process of conversion of lignin-derived aromatics by microorganisms ( Perez et al., 2021 ). To date, two typical oxidative enzymes related to aromatic O -demethylation, that is, cytochrome P450s (P450s) and Rieske non-heme iron oxygenases (ROs), have been found to catalyze the conversion of guaiacol and 3- O -methyl-catechol to catechol, which is the key step in the lignin degradation process mediated by microorganisms ( Bleem et al., 2022 ; Wolf et al., 2022 ). In this study, gene-LUX28_RS05610 (Rieske 2Fe-2S iron–sulfur protein YhfW) and gene-LUX28_RS04020 (CYPD_BACSU Probable bifunctional P-450/NADPH-P450 reductase 1) were downregulated in group C, while gene-LUX28_RS01310 (4-hydroxyphenylacetate 3-monooxygenase) and gene-LUX28_RS05685 (aromatic compound monooxygenase YhjG), which are considered to be catalysts for lignin-derived phenol hydroxylation ( Sucharitakul et al., 2005 ), were upregulated ( Figure 7 ). The pattern of downregulation of O -demethylation and upregulation of hydroxylation might be the result of the high accumulation of 4-hydroxycinnamic acid ( p -coumaric acid) in cells. This finding confirms that glucose can promote the hydroxylation of p-coumaric acid, which is necessary for the ring cleavage of lignin-derived aromatics into the TCA cycle. Additionally, to date, several P450s involved in hydroxylation have been identified in natural lignin-relevant catabolic reaction pathways; however, to the best of our knowledge, they are only identified in fungal hosts ( Lah et al., 2011 ). In this study, it remains to be confirmed whether the presence of gene-LUX28_RS05870 (cytochrome P450), gene-LUX28_RS12490 (cytochrome P450 YjiB), and gene-LUX28_RS13720 (cytochrome P450 CYP102A3) in upregulated DEGs in group C means that these bacterial P450s can mediate hydroxylation. In the lower pathway, these aromatic O -demethylation and hydroxylation intermediates are subjected to ring opening, catalyzed by dioxygenases via the meta and ortho pathways. Gene-LUX28_RS04485 (catechol-2, 3-dioxygenase) was downregulated, while gene-LUX28_RS06840 , gene-LUX28_RS01435, and gene-LUX28_RS10145 (putative ring-cleaving dioxygenase MhqA, MhqO and MhqE) were upregulated in group C, indicating that the addition of glucose promoted aromatic ring opening of lignin-derived intermediates. Figure 7 Proposed promoting effect of glucose on lignin degradation by B. amyloliquefaciens MN-13. In the 4-hydroxyphenylacetate pathway, HPA is metabolized via the meta-cleavage pathway with 3, 4-dihydroxyphenylacetate (3,4-DHPA) as the dihydroxylated intermediate and succinate and pyruvate as the final products ( Ali et al., 1998 ). The HPA pathway has been found to play a role in the aerobic catabolism of aromatic xenobiotic compounds in several bacteria. Granja-Travez et al. found that five bacteria possess the 4-hydroxyphenylacetate (or homoprotocatechuate) pathway among 12 bacteria whose genomes were surveyed for the presence of lignin-derived aromatic degradation gene clusters ( Granja-Travez et al., 2020 ). In the current study, the key enzymes involved in the HPA pathway, including 4-hydroxyphenylacetate-3-hydroxylase ( gene-LUX28_RS01310 ), catechol-2, 3-dioxygenase ( gene-LUX28_RS04485 ), and 5-carboxymethyl-2-hydroxymuconate isomerase ( gene-LUX28_RS05780 ), were identified in the annotation of sequences in the transcriptomics analysis ( Supplementary Table S4 ). Among genes encoding the three enzymes, gene-LUX28_RS01310 was significantly upregulated in group C. Meanwhile, the comparative analysis of the metabolome revealed that DAIMs contained intermediates related to the HPA pathway, such as 4-hydroxyphenylacetaldehyde ( p > 0.05) 3, 4-Dihydroxyphenylacetaldehyde ( p > 0.05), pyruvate ( p > 0.05), and succinic acid ( p < 0.05) ( Supplementary Table S5 ). Therefore, we speculate that the HPA pathway might be an important pathway for lignin degradation mediated by the MN-13 strain, and the HPA pathway appears to be regulated by the addition of glucose. Additionally, lignin biodegradation mediated by bacteria involves oxidative conditions induced by hydrogen peroxide-producing enzymes, resulting in the activation of the antioxidant mechanism in bacteria ( Li et al., 2019 ). With the addition of glucose, the expression patterns of many genes involved in oxidative stress response systems, such as catalase ( gene-LUX28_RS03095 , gene-LUX28_RS02370 ) and cytochrome bd complex ( gene-LUX28_RS17830 , gene-LUX28_RS15730 and gene-LUX28_RS20135 ), were upregulated. Meanwhile, several studies of bacteria have shown that the SufBCD protein complex is the scaffold for iron–sulfur cluster assembly, and the Suf pathway functions as an emergency pathway under the conditions of oxidative stress ( Tian et al., 2014 ). In the current study, upregulation of the SufBCD genes ( gene-LUX28_RS16970 , gene-LUX28_RS16975, and gene-LUX28_RS16985 ) suggests that the addition of glucose is beneficial to the protection of cells from lignin depolymerization-induced oxidative stress. 3.4.2 KEGG pathway enrichment of differentially expressed genes Using p < 0.05 and |log 2 FC| values >1 as the threshold, 299 differentially expressed genes (DEGs) were identified from pairwise comparison (A vs. C), 191 of which were upregulated and 108 were downregulated ( Figure 8 ). To provide an overview of the effect of glucose addition on the cell transcriptome in the process of lignin degradation, KEGG pathway enrichment analysis was performed. In total, 299 DEGs with significant matches were mapped to 55 KEGG pathways ( Supplementary Table S6 ). The addition of glucose caused the most significant changes in four subcategories, i.e., flagellar assembly, PTS system, RNA degradation, and glycolysis/ gluconeogenesis, which were assigned to four categories: cellular process, environmental information processing, genetic information processing, and metabolism, respectively ( Figure 9 ; Supplementary Table S7 ). Furthermore, the DEGs were functionally enriched in the following subcategories: glycolysis/gluconeogenesis, TCA cycle, pyruvate metabolism, tryptophan metabolism, glyoxylate and dicarboxylate metabolism, propanoate metabolism, and glycerolphospholipid metabolism. These categories are closely associated with energy generation and downstream metabolism processes, meaning that the addition of glucose provided adequate energy and activated the metabolism of the MN-13 strain. Figure 8 Volcano plots of DEGs in the pairwise comparisons. Volcano plot of DEGs with and without the addition of glucose. Figure 9 KEGG analysis of DEGs between groups A and C. Flagellar motility enables bacteria to navigate their environment, e.g., to acquire nutrition and evade noxious substances. Increased flagellar motility in bacteria promotes biofilm initialization and loss of motility promotes increased growth rates of cells, extracellular protein excretion, and biofilm development in oligotrophic aquatic environments ( Du et al., 2020 ). In the current study, the genes involved in the flagellar assembly and biofilm formation pathways were downregulated in group C, indicating that the addition of glucose provided a more favorable environment for cells to grow and excrete extracellular ligninolytic enzymes. This is consistent with the metabolic analysis and the increased cell growth and lignin degradation with the addition of 2 g/L glucose. Based on the KEGG analysis where the addition of glucose promoted the excretion of ligninolytic enzymes, depolymerization and modification of lignin should be more active in group C than in group A. In the process of lignin degradation, Cα-oxidative lignin-derived aromatics were generally considered to be resulted from ligninolytic peroxidases and laccase. Now a greater accumulation of these aromatic intermediates in DAEMs in A group than that of C group, indicated that there is greater extracellular activity of ligninolytic peroxidases and laccase in A group. Why were these paradoxical phenomena observed in the transcriptomic and metabolic analyses? It is well known that outer membrane vesicles (OMVs) are released by all bacteria and are loaded with a diverse array of small molecules, proteins, and genetic cargo ( Cao and Lin, 2021 ). According to Salvachúa et al. (2020) , in the study of lignin-degrading bacteria, many enzymes that were not predicted to be secreted were trafficked to the extracellular compartment via OMVs, and some ligninolytic enzymes were packaged in OMVs. Therefore, we can conclude that OMVs are the reason for the paradoxical results. That is, genes encoding heme peroxidases and CotA were upregulated with the addition of glucose in the transcriptome, but the corresponding enzymes exhibited less extracellular activities, resulting in decreased accumulation of Cα-oxidative compounds in group C. Future research will need to determine what role OMVs play in lignin degradation mediated by Bacillus amyloliquefaciens MN-13. 3.5 Validation of the DEG results by qRT-PCR analysis To verify the reliability of the transcriptome analysis, six DEGs were selected for qRT-PCR ( Figure 10 ). The expression trends in the DEGs were largely consistent in the transcriptome analysis, although the fold changes were different. Additionally, the correlation coefficient was 0.8422, indicating a positive correlation between the RNA-seq and qRT-PCR data. Figure 10 qRT-PCR validation of the expression patterns of DEGs. The left y-axis represents the expression levels of selected genes calculated by the FPKM reads method, and the right y-axis represents the relative gene expression assessed by qRT-PCR."
} | 6,988 |
27112228 | PMC5082532 | pmc | 1,378 | {
"abstract": "Abstract Formation of magnetite nanocrystals by magnetotactic bacteria is controlled by specific proteins which regulate the particles’ nucleation and growth. One such protein is Mms6. This small, amphiphilic protein can self‐assemble and bind ferric ions to aid in magnetite formation. To understand the role of Mms6 during in vitro iron oxide precipitation we have performed in situ pH titrations. We find Mms6 has little effect during ferric salt precipitation, but exerts greatest influence during the incorporation of ferrous ions and conversion of this salt to mixed‐valence iron minerals, suggesting Mms6 has a hitherto unrecorded ferrous iron interacting property which promotes the formation of magnetite in ferrous‐rich solutions. We show ferrous binding to the DEEVE motif within the C‐terminal region of Mms6 by NMR spectroscopy, and model these binding events using molecular simulations. We conclude that Mms6 functions as a magnetite nucleating protein under conditions where ferrous ions predominate.",
"introduction": "Introduction Essential to many organisms, iron is an important component of many biological processes. 1 Due to the inherent redox activity and pH sensitivity of this transition metal its presence in cells must be carefully controlled to prevent potentially harmful effects from reactive oxygen species 1c or iron precipitation. 2 Many proteins have therefore evolved to utilise, control and harness the useful capabilities of iron whilst minimizing any potentially damaging side effects. 1a , 1b In the case of magnetotactic bacteria (MTB), they have evolved to take advantage of the magnetic characteristics of certain iron oxides by producing biogenic magnetic nanoparticles 3 within internal lipid vesicles termed magnetosomes. 4 These vesicles are in effect a nanoreactor for the precise synthesis of, most commonly, the iron oxide magnetite (Fe 3 O 4 ). 3c , 5 The formation of nanocrystalline magnetite is tightly controlled by a suite of biomineralisation proteins which are present within the lipid membrane of the magnetosome. 6 The nucleation, crystal growth and regulation of the final size and shape of the particle are strictly regulated by these proteins. A single strain of MTB harbours a highly uniform population of nanoparticles; homogeneous in terms of size, shape, and chemical composition. Research is currently focusing on identifying and characterising these biomineralisation Mms (magnetosome membrane specific) proteins in order to elucidate a detailed understanding of iron oxide biomineralisation. One key protein found tightly bound to the magnetite particles of Magnetospirillum magneticum AMB‐1 7 is a 6 kDa protein, Mms6. Mms6 comprises a hydrophobic N‐terminal region and a hydrophilic C‐terminal region (KSRDIESAQSDEEVELRDALA) which contains a high number of residues with acidic sidechains that have been implicated in the ferric iron binding capability of the protein (Figure 1 ). 7 , 8 If the mms6 gene is removed from MTB (so Mms6 protein is not produced) the resulting nanoparticles which form are both small and poorly formed compared to the wild‐type. 9 Mms6 has therefore been classified as an important member of the magnetite biomineralisation mechanism. Due to its amphiphilic sequence, purified Mms6 self‐assembles into micellar structures. 8a These large aggregates are able to both bind and accumulate ferric ions from solution, 7 , 8 , 10 and purified assemblies of Mms6 on a biomimetic magnetosome interior surface demonstrate magnetite formation properties, indicating that Mms6 can act as a potential iron oxide nucleation site for subsequent crystal formation. 11 In addition, the acid rich C‐terminal part of Mms6 has been studied and was found to exhibit some similar characteristics to the full‐length protein such as iron binding and a limited ability to affect magnetite crystal growth. 8a , 10 , 12 \n Figure 1 Mms6 in magnetotactic bacterial magnetosome. In blue is the hydrophilic acid‐rich region and in pink is the hydrophobic membrane region with the sequence below. Experimental schematic showing pH recording during addition of base to ferric/ferrous solution with or without Mms6 micelles is also illustrated. Magnetic nanoparticles have received much attention due to their potential use in a wide range of different applications spanning various scientific disciplines and technologies. 13 These range from the magnetic components of ferrofluids 14 and data‐storage devices, to precision applications in medical diagnostics and therapies. 15 For this latter use, magnetite is one of the most desirable materials due to its magnetic properties and general low toxicity. 15a There are a number of synthetic routes for magnetite nanoparticles including thermal decomposition, and high temperature methods in the presence of organic surfactants. 16 An alternative and simple method of producing magnetite nanoparticles is by room temperature co‐precipitation (RTCP). This results in particles with a high size polydispersity making them unsuitable for critical biomedical applications. Taking inspiration from nature where MTB synthesize magnetite nanoparticles with a high degree of control over size and shape, purified Mms6 has been introduced into RTCP and other reactions. 7 , 17 The resulting products demonstrate improved homogeneity in both size and mineral type, suggesting that Mms6 is able to control the formation of magnetite nanoparticles in vitro. 7 , 17 , 18 However, the exact mechanism by which Mms6 achieves this type of control both in vivo and in vitro remains poorly understood. In this study we analyse the effect of Mms6 during a simple RTCP of magnetite by monitoring differences in the pH profile during the reaction process. This was performed under a range of different reaction conditions to build up a rigorous and detailed picture of Mms6 activity at different ratios of ferric and ferrous iron. A previous study of iron oxide formation using this approach 19 has provided a methodology by which to investigate the effect of these additives on the crystallisation process. We find that Mms6 exerts its greatest influence over the process in the pH range where ferrous ions are precipitated out of solution (>pH 7). Previous studies have shown that Mms6 interacts with ferric iron but there is, to the best of our knowledge, currently no analysis of any potential interaction with ferrous iron. Therefore, to complement our study we have used 2D NMR spectroscopy to investigate the ferrous‐binding activity of the C‐terminal peptide region of Mms6, which reveals that the peptide has specific interactions with ferrous iron centred around the DEEVE acidic residue cluster. Further insight is gained through molecular dynamics simulations of this cluster and its interactions with both ferric and ferrous iron. This study therefore provides a new perspective on the activity of the Mms6 protein by suggesting it is interacting with both ferric and ferrous iron during the magnetite crystallisation process, and that it is the predominant and specific interaction with ferrous iron that is the key to driving the reaction towards magnetite. This finding has implications for our understanding of magnetite biomineralisation and how we can control magnetite formation in biomimetic magnetic nanoparticle synthesis for wider nanotechnology applications.",
"discussion": "Discussion and Conclusions Analysing the effect of Mms6 in situ through pH measurements throughout the magnetite‐formation process has enabled us to obtain an insight into the protein's function and in particular, at what stage in the reaction it exerts its effect. We see no influence of the protein in the early stages of the reaction at low pH at the point where ferric oxyhydroxide minerals are formed, consistent with the theoretical isoelectric point of 4.2 of the acidic iron binding region of the protein. It is from pH 5 and upwards that we see Mms6 affecting the formation of the minerals, at the point that ferrous ions begin to precipitate out of solution and mixed valence iron minerals are formed. From our data it appears that Mms6 promotes the formation of magnetite under ferrous‐rich conditions, even in conditions in which magnetite does not readily form. All previous studies on the iron binding activity of Mms6 have focused on ferric‐ion binding of the acidic C‐terminal region 7 , 8 and often at low pH. From our study it seems Mms6 is more likely to interact predominantly with ferrous ions at pH>5. In this context we performed an NMR metal‐binding experiment under these conditions and we saw that Mms6 does indeed show specific and significant interactions with ferrous ions compared to both positive and negative control metals, including ferric ions. The residues responsible for binding metals vary for ferrous and ferric ions, but the DEEVE cluster was found to have the biggest shift for both iron ions, with the double EE site having the prominent shift for ferric ions and all the acidic residues of the whole DEE V E region significantly shifted (up to 5×>Fe 3+ ) in the presence of ferrous ions. The interaction of this smaller peptide of interest with ferrous and ferric ions was thus modelled by atomistic simulation in order to further understand the binding event. This indicated that the acidic residues may bind the ferrous iron not only through their carboxylate sidechain but also through the peptide carbonyls. The MD calculations also show that multidentate binding is preferred, especially for ferrous ions, and that bidentate binding of Fe 2+ to E12 carbonyl and E13 carboxylate is particularly frequent. Ferric ions show binding, but unspecifically across the acidic amino acids. As the pH is raised, and particularly at high ratios of ferrous to ferric ions, the initially formed ferric oxyhydroxide precipitate must re‐dissolve and reform into a different crystalline structure in order to incorporate ferrous ions and form magnetite. Our data suggest that Mms6 is facilitating this process. We therefore propose an in vitro mechanism in which Mms6 displays little activity below pH 4–5. Above this, Mms6 specifically sequesters and binds ferrous ions. We also propose that the Mms6’s known affinity for ferric ions promotes the dissolution of the unstable ferric precursors to sequester ferric ions as well. We have shown here that the role of Mms6 is to promote the formation of magnetite at high ferrous ratios, which are conditions where magnetite is formed poorly if at all in the absence of Mms6. We therefore propose that Mms6 not only helps to dissolve undesired precipitates, such as ferric oxyhydroxide, but helps the formation of magnetite by acting as a nucleation protein. Mms6 is known to self‐aggregate 10 and it is already proposed that Mms6 assembles to form an acidic, charged, C‐terminal surface to bind multiple iron ions. 8 , 25 The self‐assembly of Mms6 could space these acidic residues to bind both ferrous and ferric ions in a magnetite crystallographic geometry to template and promote the initial formation of magnetite over other iron minerals by lowering the free energy for formation of magnetite. Relating the reactions occurring in solution in this experiment to those found in vivo is challenging. Mms6 is associated with the magnetosome membrane, so the C‐terminal acidic surface of an Mms6 assembly will differ in its in vitro micelle structure compared to the arrangement in the internal lumen of the magnetosome. In the magnetosome there are transporters that transport iron ions into the magnetosome. 26 All current knowledge points to the transport of ferrous ions only, with partial oxidation of some of the ferrous ions to generate the ratio required for magnetite formation. 26 Furthermore, ferrous transporters are antiporters meaning they bring ferrous iron in as they take protons out. This will help to regulate the internal pH, but the precise pH of this environment is also not currently known. Additionally, due to the iron transport system it is highly unlikely that there will be SO 4 \n 2− counter‐ions, ruling out the formation of schwertmannite and green‐rust phases. However, similarities between the two systems can be drawn to predict the action of Mms6 in the magnetosome. While the pH of the interior of the magnetosome has not yet been determined, it must at some point be high enough to enable magnetite to crystallise (≥pH 7), and we have established in this study that Mms6 is active in these conditions. In the natural system we assume some of the ferrous ions are converted to ferric (through the action of oxidase enzymes), and thus a ferric mineral will precipitate (due to its chemical insolubility at pH≥2.5). There have been several reports of such ferric precursors, 27 and while our suggested mechanism relies on dissolution of this precursor, its exact form is immaterial, be it schwertmannite (in vitro) or ferrihydrite (in vivo). Interestingly, Mms6 activity is greatest in ferrous‐rich conditions, which is likely to be the predominant state in magnetosomes if it is confirmed that iron transport is of ferrous iron. It is therefore likely that in vivo conditions in the magnetosome are similar to our in vitro conditions with respect to possible pH, ferric precursors in a ferrous‐ion‐rich solution, and the protein's ability to form a self‐assembled charged surface capable of sequestering ferrous and ferric iron in the exact proportions to promote the crystallization of magnetite. Therefore we propose, both in vitro and in vivo, that Mms6 is a magnetite nucleation protein, able to bind both ferric and specifically ferrous iron to initiate the process of templating the magnetite crystal."
} | 3,432 |
32974292 | PMC7471869 | pmc | 1,380 | {
"abstract": "Oxygenic photosynthesis conducted by cyanobacteria has dramatically transformed the geochemistry of our planet. These organisms have colonized most habitats, including extreme environments such as the driest warm desert on Earth: the Atacama Desert. In particular, cyanobacteria highly tolerant to desiccation are of particular interest for clean energy production. These microorganisms are promising candidates for designing bioelectrodes for photocurrent generation owing to their ability to perform oxygenic photosynthesis and to withstand long periods of desiccation. Here, we present bioelectrochemical assays in which graphite electrodes were modified with the extremophile cyanobacterium Gloeocapsopsis sp. UTEXB3054 for photocurrent generation. Optimum working conditions for photocurrent generation were determined by modifying directly graphite electrode with the cyanobacterial culture (direct electron transfer), as well as using an Os polymer redox mediator (mediated electron transfer). Besides showing outstanding photocurrent production for Gloeocapsopsis sp. UTEXB3054, both in direct and mediated electron transfer, our results provide new insights into the metabolic basis of photocurrent generation and the potential applications of such an assisted bioelectrochemical system in a worldwide scenario in which clean energies are imperative for sustainable development.",
"conclusion": "Conclusion A new bio-photoelectrochemical system was studied, consisting on the modification of GEs with extremophile cyanobacteria Gloeocapsopsis sp. culture. During both the preparation steps of bio-photovoltaic cells and operations, the organisms responsible for the bio-photoelectrocatalytic currents might undergo osmotic stress and desiccation, hence our interest in extremophile cyanobacteria. Although Gloeocapsopsis entered into a metabolic arrest during desiccation, its biological membranes remained unaltered as mean of FA composition and viability tests, therefore becoming a good candidate for bioelectrode construction. Through cyclic voltammetry and chronoamperometric experiments, we determined that 0.40 V was the optimum potential for photocurrent density generation. The best-performing bioelectrode achieved 2.26 ± 0.28 μA cm –2 of current density when OsP was present as an electron mediator at the electrode surface.",
"introduction": "Introduction The environmental consequences of the current dependency of worldwide economy on fossil fuels have brought attention to alternative energy sources, among which solar energy-based photovoltaics represent the most appealing one. The solar radiation might also be used as energy source when assisted with photosynthetic organisms, forming photo-bioelectrochemical cells ( Deng and Coleman, 1999 ; McCormick et al., 2011 ; Kaiser et al., 2013 ). These bioelectrochemical cells are based on the wiring of whole photosynthetic organisms or parts of their photosynthetic machinery to electrodes ( Zhang et al., 2018 ), attempting to efficiently convert sunlight energy into electrical energy ( Rosenbaum et al., 2005 ; Pankratova et al., 2017 , 2019a ; Pankratova and Gorton, 2017 ). The main principle of such technology is the interception of the electrons that flow from the water photolysis through the photosystem I and II (PSI and PSII). Cyanobacteria are exceptionally good candidates for assisting generation of photocurrent for three main reasons: (1) they generate electricity from their photosynthetic electron transport chain; (2) cultivation at industrial scale is possible and inexpensive; (3) feasibility of engineering the cyanobacterial genome for desired metabolic improvements. In cyanobacteria, photons are absorbed from the photosystems’ antennas and the energy is transferred to the PSII and PSI and used to drive electrons which are transferred from water to reduce NADP + . In the absence of light, cyanobacteria oxidize carbon sources via the respiratory system to consume oxygen and produce CO 2 and ATP. Nevertheless, the exchange of electrons from the cyanobacterial electron transport chain to external electrodes is not a simple task. Aiming to optimize this process, cyanobacteria have been grown or dried on the top electrodie surfaces ( McCormick et al., 2011 ; Cereda et al., 2014 ; Sekar et al., 2016 ; Wei et al., 2016 ). In other cases, they have been exposed to small pressures with a microfluidizer to obtain modification of the internal structure that allowed for endogenous mediators to shuttle electron between the respiratory chain and the PSI and to electrodes ( Saper et al., 2018 ). The electron transfer from the inner side of cyanobacteria to electrode surface might be direct (where some proteins or endogenous mediator does provide for the electron transfer) or mediated by added biological or chemical redox mediators ( Schemes 1A,B ) ( Torimura et al., 2001 ; Tsujimura et al., 2001 ; Yehezkeli et al., 2012 ; Longatte et al., 2017 ; Pankratova et al., 2019a , b ). In particular, osmium complex-based redox polymers have been extensively studied in combination with various microorganisms showing an enhanced electron transfer between the electron cascades in microbial cells and the electrodes ( Timur et al., 2007b ; Rawson et al., 2011 ; Hasan et al., 2012 , 2014 , 2015 ; Hamidi et al., 2015 ; Pankratova et al., 2019b ). Therefore, the preparation steps of an electrochemical system constituted by photosynthetic bacteria might imply that the bacteria have gone through an osmotic stress because of a desiccation step for the preparation of the modified electrodes and because of the need of redox mediators. Moreover, if bio-photovoltaic cells should be considered for major electricity production (e.g., home bio-photovoltaic systems), desiccation might also occur because of uncontrolled environment conditions and evaporation. A photosynthetic organism able to withstand extreme stress and long periods of dryness will therefore be a suitable candidate for testing photocurrent generation. Gloeocapsopsis sp. UTEXB3054 is a unicellular cyanobacterium originally isolated from Atacama, the driest warm desert on Earth, with an impressive ability to tolerate desiccation periods based on unique genetic features associated to desiccation tolerance ( Urrejola et al., 2019 ). Because of these properties, its genome and sugar biosynthesis pathways have been studied ( Urrejola et al., 2019 , 2020 ). In this work, for the first time, we explored the use of Gloeocapsopsis sp. UTEXB3054 as part of a photo-bioelectrochemical system for testing photocurrent generation. Both direct and mediated electron transfer using a high-potential redox mediator were evaluated, as represented in Schemes 1A,B . Moreover, a biochemical characterization of Gloeocapsopsis behavior under desiccation was also conducted. Our results are discussed with relation to cellular strategies to deal with the lack of water and the implications that might affect green and sustainable technologies for energy generation. SCHEME 1 (A) Schematic modification of graphite electrode with Cyanobacteria. Under light conditions, e – and O 2 are produced and water is oxidized. Electrons can reach directly the electrode. During cyclic voltammetry experiments with Gloeocapsopsis sp. UTEXB3054, a positive current can be noticed in correspondence of an anodic redox peak (0.5 V). (B) Schematic modification of graphite electrode with cyanobacteria and Os polymer. Under light conditions, e – and O 2 are produced and water is oxidized. Electrons can reach the electrode surface through Os polymer redox centers which are in high concentration and can penetrate cyanobacteria membranes. During cyclic voltammetry experiments with electrode modified with Gloeocapsopsis sp. UTEXB3054 and Os polymer, a positive current with onset at 0.5 V can be noticed in correspondence of an anodic redox peak (0.6 V). Os redox peak at 0.24 V.",
"discussion": "Results and Discussion Culture Characterization and Survival on Desiccation Experiments To generate photocurrent by using Gloeocapsopsis sp. UTEXB3054 as photo-electrocatalyst, cell cultures must survive desiccation conditions when placed over the electrodes. As a first approach, different staining techniques that could prove cell survival after desiccation were tested. The membrane-impermeable fluorescent dye from the SYTOX series, SYTOX Blue, has been extensively employed to determine the portion of dead cells in a wide spectrum of organisms ( Wobus et al., 2003 ; Krause et al., 2007 ; Adav and Lee, 2008 ; Tashyreva et al., 2013 ; Roldán et al., 2014 ; Giannattasio et al., 2015 ; Mason-Osann et al., 2015 ). This stain is an organo-arsenical compound with high affinity to nucleic acids that easily penetrates cells with compromised membranes ( Park et al., 2011 ). In agreement with results previously reported ( Azua-Bustos et al., 2014 ), after desiccating the cyanobacterial cultures for 4 weeks, 94% of the population appeared to be alive (total cells = 970) using membrane integrity as criterion of viability. These results were further complemented with FDA staining, a molecule with different chemical properties than those of SYTOX Blue. FDA is a non-fluorescent compound that is able to passively enter cells owing to its hydrophobicity. However, once inside the cell, non-specific esterases break down the molecule into fluorescein, a highly fluorescent and polar molecule that remains in the cytoplasm ( Dorsey et al., 1989 ). The dye has been associated to metabolic vigor, allowing the discernment between cells that are still metabolically active from the inactive ones. Before desiccation, 86% of cells tested positive for the FDA (FDA+) method. After 4 weeks of desiccation, the percentage of FDA + cells fall to only 15%, a situation that became reverted once rehydration of the culture occurred, increasing FDA + cells to 50% of the whole population within 1 h (a proportion that was maintained during the following hours). After rehydration, desiccated cells were able to colonize both liquid and solid BG11 media, a clear demonstration of metabolism reactivation. Bioelectrochemical systems for current generation are based on electron movement in biological membranes. All the biological elements associated with current generation in cyanobacteria (photosynthetic elements) are located in biological membranes. Although several ultrastructural changes became evident throughout the desiccation process that could be linked to the high tolerance to water deprivation of Gl , the physical integrity of membranes was maintained as evident from Figure 1 . Because of the crucial role FAs play in the maintenance of membrane fluidity (and therefore, functionality), the FA profiles during desiccation were also explored ( Table 1 ). GC-MS results indicated that most FAs detected are C16 and C18 in almost equal amounts, both accounting for 97% of all FAs. FAs of the C14, C15, and C17 series were detected in trace or minor levels (each below 1% of the total FA content). Therefore, we focused exclusively on FAs with 16 and 18 carbons, considering them all together as a whole ( Table 1 ). Interestingly, the ratio of unsaturated to saturated FAs remained unaltered under desiccation conditions. No significant differences were detected between the control samples (culture at active growth in liquid medium) and the desiccated samples for up to 4 weeks ( p > 0.05; non-parametric data were tested by Kruskal–Wallis ANOVA test). Desiccation appears not to affect the FA composition of Gl . Considering the ability of Gl to thrive under desiccation periods preserving membranes integrity and composition of FA, we hypothesized that Gloeocapsopsis sp. UTEXB3054 might be a good candidate for biolectrode constructions. TABLE 1 Percentage content of fatty acid of Gloeocapsopsis sp. UTEXB3054 during desiccation. Fatty acids Liquid culture before desiccation After 4 weeks of desiccation Monoenoic 65.6 ± 0.4 59.5 ± 6.5 Dienoic 11.6 ± 1.6 9.36 ± 3.9 C16 49.6 ± 0.8 50.3 ± 1.9 C18 50.4 ± 0.8 49.7 ± 1.9 Unsaturated/total 0.8 ± 0.02 0.7 ± 0.10 The values represent average percentages of three FA extractions ± SDs. TABLE 2 Effect of electrode modification on photocurrent density outputs during chronoamperometric tests with electrodes polarized at 0.4 V vs Ag| AgCl| KCl 3.5 M. Electrode architecture J min J max Δ J (μA cm –2 ) GE| Gl 19.3 ± 0.6 20.2 ± 0.70 0.96 ± 0.08 GE| OsP| Gl 3.50 ± 0.10 5.70 ± 0.30 2.26 ± 0.28 GE| OsP| Ec 0.88 ± 0.07 0.95 ± 0.07 0.07 ± 0.02 Values presented ± SDs. Averages and SDs were calculated from four different experiments. Bioelectrochemical Experiments Electrochemical activity of modified and unmodified GEs with photoautotrophic bacteria can be estimated along with the contribution from illumination ( Figure 2 ). Bare GE does not demonstrate photoelectrochemical activity; similar results were obtained for electrodes modified with E. coli (GE| Ec ) which were used as non-photosynthetic control. The latter profiles under illumination can be considered as the biotic blank. Under dark conditions, GE with Gloeocapsopsis (GE| Gl ) reached ca. 38.3 ± 2.02 μA cm –2 at the positive working potentials, whereas GE| Ec gave only around 0.9 ± 0.02 μA cm –2 . Under light conditions, the GE| Gl increased its current density to 47.1 ± 1.7 μA cm –2 at the positive potentials, whereas for GE| Ec the current density reached 1.1 ± 0.1 μA cm –2 . To optimize GE| Gl photocurrent density production, the effect of working electrode potential was studied during potentiostatic (chronoamperometry) tests, as shown in Figure 3 . As expected, when electrodes are poised at higher electrode potential values, ranging from 0.30 to 0.45 V versus Ag| AgCl| KCl 3.5 M, higher current density outputs and baselines are produced. To select for optimal photocurrent density production, a single 200-s illumination step was applied, calculating photocurrent density difference (Δ J ) between the beginning (see the arrows in Figure 3 ) and the maximum current density developed during the length of the step. When the system was polarized at 0.30, 0.35, 0.40, and 0.45 V, the Δ J values were 2.5 ± 0.2, 3.3 ± 0.0, 3.5 ± 0.3, and 3.3 ± 0.1 μA cm –2 , respectively. These results indicate that GE| Gl at 0.40 V produces higher photocurrent density. Possibly, at values higher than 0.40 V, electrode components may become over-oxidized, losing its photoelectrochemical activity. For determining photocurrent density production, multiple illumination steps were applied monitoring current density ( Figure 4A ). Multiple illumination steps have no effect on GE; light does not alter current density output over time nor does it change the curve inflection ( Figure 4A ). In contrast, GE| Gl current density output undergoes an evident increase after each illumination step: an average 1.3 ± 0.1 μA cm –2 of Δ J increment owing to photocurrent density production can be calculated. Although we show only the first 2,000 s of the experiment, no decrease in current density could be noticed after 1 day of continuous cycles. To corroborate that the measured current density was generated by the photosynthetic cyanobacteria, two different photosystem inhibitors (i.e., diuron and paraquat) were included in working solution under continuous lighting for 1,200 s, after 1,800 s of continuous cycles ( Figure 4B ). Both inhibitors do not show strong light absorbance or interaction with the electrodes at this potential, or have the possibility to shuttle electrons ( Hasan et al., 2014 , 2017 ; Hamidi et al., 2015 ). Diuron is known to irreversibly block quinone A and B from photosystem II, hindering electron flow into plastoquinone ( Rodea-Palomares et al., 2015 ; Rowen et al., 2017 ), whereas paraquat inhibition is known to take place at photosystem I, generating radical oxygen species (hydroxyl, superoxide, etc.) and finally damaging chloroplast structure and disrupting photocurrent density ( Hupp and Meyer, 1989 ). Our results indicate that the generated current density is associated to electron flux of cyanobacterial photosynthesis ( Figure 4B ). Immediately after diuron addition (final concentration 0.2 mM), a current density peak was observed, but after ≈500 s, the inhibition of photosystem II took place. On the other hand, when paraquat is added (final concentration 0.2 mM) into the working solution, photocurrent density is inhibited after 900 s. Therefore, the measured current density is directly linked to the presence of photosynthetic organisms on the electrodes. In an attempt to improve electrical wiring of electroactive bacteria, GE were modified with an OsP, an electrode wiring mediator previously used for wiring both enzymes and microorganisms to electrodes ( Ohara et al., 1993 ; Vostiar et al., 2004 ; Timur et al., 2007a , b ; Coman et al., 2009 ). Increased photocurrent outputs are usually obtained when in the presence of OsP because a higher number of molecules or living cells can be wired to the electrode because the OsP is usually present in excess and can penetrate the protein and membrane structures ( Scheme 1B ) ( Kurbanoglu et al., 2018 ; Antiochia et al., 2019 ). In Figure 5 , a typical CV obtained with electrodes modified with both OsP and Gl is presented. At 0.26 V, it is possible to observe the reversible peak for the OsP, corresponding to the Os(III)/Os(II) redox couple. Similar results were obtained in previous works ( Hasan et al., 2014 ; Hamidi et al., 2015 ; Antiochia et al., 2013 , 2019 ). Interestingly, at higher potential (0.65 V), a second oxidation peak is obtained. When in the presence of light, an anodic photo-electrocatalytic current appears with an onset at 0.45 V which can be assigned as related to the oxidation peak observed in dark conditions. Definitely the peak at 0.65 V belongs to one or more proteins wired to the photo-electrolysis system of Gl . In the presence of light, the Os(III) redox centers in the polymer matrix are reduced by available electrons occurring from the photo-electrolysis of the electrolyte. The formed Os(II) centers are acting as a relay of electrons and are then re-oxidized at the electrode surface (if the electrode is polarized at potentials positive enough for the oxidation to be consistent). When in the presence of light, at lower potential (−0.1 V), a cathodic current might be noticed which probably corresponds to the reduction of the oxygen produced by Gl during the photoelectrocatalysis. A summary of photocurrent density production obtained with by GE| OsP| Gl during chronoamperometric measurements is presented on Table 2 . OsP made a significant effect in the generation of photocurrent density (ANOVA test; p = 7.6 × 10 –7 ). To compare the photocurrent generated by the two different electrode modifications used in this work, the background current has to be subtracted ( Torimura et al., 2001 ; Tsujimura et al., 2001 ; Timur et al., 2007b ; McCormick et al., 2011 ; Rawson et al., 2011 ; Hasan et al., 2012 , 2014 , 2015 ; Yehezkeli et al., 2012 ; Cereda et al., 2014 ; Hamidi et al., 2015 ; Sekar et al., 2016 ; Wei et al., 2016 ; Longatte et al., 2017 ; Pankratova et al., 2017 ; Pankratova and Gorton, 2017 ; Saper et al., 2018 ). In this case, the background current is consisting of the anodic current which is measured during dark chronoamperometric experiments in conditions ( J min ) and which is caused by the anodic polarizing potential. Therefore, the difference (Δ J ) between the photocurrent measured during chronoamperometric experiments in light conditions ( J max ) and J min must be analyzed ( Table 2 ). The comparison of the J min and J max values for each type of electrode modification reveals that the OsP layer diminishes the background current density of the Gl bioelectrode. This type of behavior has been observed for other bioelectrode systems ( Hasan et al., 2014 ; Hamidi et al., 2015 ). Once comparing photocurrent density productions, Δ J , a significant increase in photocurrent density production was observed: GE| OsP| Gl produces ca. 2.4 times more photocurrent density than GE| Gl , which was confirmed with statistical ANOVA with p < 0.05 ( Table 2 ). The best-performing system obtained in this work corresponds to GEs modified with OsP and Gl , which yield a photocurrent density of 2.26 ± 0.28 μA cm –2 at 400 mV versus Ag| AgCl, KCl 3.5 M. OsP appears to be a good mediator to be used for light-energy to electrical-energy conversion because of its ability to accept electrons produced during the photosynthesis and shuttle them to the electrode. The photocurrent density production obtained in this work is within the range of photocurrent density production previously reported ( Table 3 ). TABLE 3 Comparison of photocurrent density output for various reports using whole living cells. Organism Electrode material Redox mediator Loaded biomass Light intensity Potential Δ J References (mg cm –2 ) (mW cm –2 ) (mV*) (μA cm –2 ) Paulschulzia pseudovolvox Graphite OsP electrode phase 0.055 44 344 0.1 Hasan et al. (2015) Nostoc sp. (cyanobacteria) Carbon paper with carbon nanotubes None 2.2 76 239 3.0 Sekar et al. (2014) Leptolyngbya sp. (cyanobacteria) Graphite OsP electrode phase 0.13 44 244 4.5 Hasan et al. (2014) Gloeocapsopsis sp. (cyanobacteria) Graphite OsP electrode-phase 0.1 44 400 2.3 Present work None 44 400 1.0 *Versus Ag| AgCl, KCl 3.5 M."
} | 5,377 |
40287420 | PMC12033221 | pmc | 1,381 | {
"abstract": "Recent advances in our understanding of cyanobacterial photoacclimation have the potential to improve photosynthetic efficiency in crops. Whereas oxygenic photosynthesis typically relies on visible light, some cyanobacteria acclimate to absorb far-red light, thus expanding the absorbance cross-section of their photosystems. This expanded absorbance range, via the implementation of red-shifted chromophores, could be bioengineered into crops to enhance yields by capturing more light energy and boosting photosynthetic efficiency in light-limited environments. Recent insight into natural cyanobacterial photoacclimation mechanisms offer promising avenues for engineered photosynthetic improvements in agriculture."
} | 179 |
38981048 | PMC11425989 | pmc | 1,384 | {
"abstract": "Abstract Triboelectric nanogenerators (TENGs) have become reliable green energy harvesters by converting biomechanical motions into electricity. However, the inevitable charge leakage and poor electric field (EF) of conventional TENG result in inferior tribo‐charge density on the active layer. In this paper, TiO 2 ‐MXene incorporated polystyrene (PS) nanofiber membrane (PTMx NFM) charge trapping interlayer is introduced into single electrode mode TENG (S‐TENG) to prevent electron loss at the electrode interface. Surprisingly, this charge‐trapping mechanism augments the surface charge density and electric output performance of TENGs. Polyvinylidene difluoride (PVDF) mixed polyurethane (PU) NFM is used as tribo‐active layer, which improves the crystallinity and mechanical property of PVDF to prevent delamination during long cycle tests. Herein, the effect of this double‐layer capacitive model is explained experimentally and theoretically. With optimization of the PTMx interlayer thickness, S‐TENG exhibits a maximum open‐circuit voltage of (280 V), short‐circuit current of (20 µA) transfer charge of (120 nC), and power density of (25.2 µW cm −2 ). Then, this energy is utilized to charge electrical appliances. In addition, the influence of AC/DC EF simulation in wound healing management (vitro L929 cell migration, vivo tissue regeneration) is also investigated by changing the polarity of trans‐epithelial potential (TEP) distribution in the wounded area.",
"conclusion": "3 Conclusion In summary, we improved the S‐TENG device surface charge density and output performance through a new regulated charge‐trapping mechanism of interfacial polarization. Through the intercepting of PTMx NFM, we were able to increase the charge‐storing capacity as well as the resistance to charge recombination. Further, all fiber‐based fabrication offers many advantages for wearable biomechanical energy harvesting. The tribo‐friction layer PPU shows good mechanical properties and stretchability which extend the duration of S‐TENG lifespan. With excellent flexibility, hydrophobicity, breathability, and lightweight, this TENG is highly comfortable to wear. The electrical output performance of S‐TENG was evaluated in glowing 60 LED lights, and commercial capacitors. Intriguingly, owing to its high sensitivity the S‐TENG was designed as smart keys for “Snakebite” video game. In addition, the resulting output was utilized to treat chronic wounds, where the EF was induced through connecting. Ag /SBS NFM. Prior to this wound healing experiment, the efficiency of S‐TENG was verified by in vitro and in vivo tests. The device tested in both AC and DC modes of operation showed better results. Thus, the multiple features of S‐TENG with wearable advantage are expected to have a significant impact in sensors as well as therapeutic medicinal areas of research.",
"introduction": "1 Introduction The power of electricity contributes to every aspect of human innovation in an incredible way. In the recent era, portable miniaturized electronic gadgets provide easy access to global information and enable people to stay connected from almost anywhere. However, such portable electronic devices demand reliable and sustainable power sources. Plenty of green energy sources (wind, solar, mechanical vibration, and ocean waves) were utilized to fulfill this energy shortage. Among them, triboelectric energy nanogenerators (TENG) are prospective candidates for the future self‐powered energy source, which efficiently convert mechanical energy into electricity and provoke intensive research in various fields. [ \n \n 1 \n , \n 2 \n , \n 3 \n \n ] TENG enable electricity by a coupled effect of tribo‐electrification and electrostatic induction effects. However, most of the high‐performance wearable TENG devices are constructed using rigid metal electrodes or conductive silicon‐based rubbers. Besides, such electrode films do not demonstrate air permeability, which may cause skin irritation due to sweating. Wearable on‐skin TENGs are highly desirable along with good stretchability, air permeability, and waterproof capability. [ \n \n 4 \n , \n 5 \n \n ] Electrospun nanofibers and textiles‐based electrodes are ideal substrates to meet these requirements. It is also important to pay attention to their wearing comfort, environmental friendliness, and antibacterial ability. [ \n \n 6 \n \n ] Despite the fact that electrospun NFs are lightweight and flexible, ultrathin nanofiber has a high surface area to volume ratio, [ \n \n 7 \n \n ] and its irregular bumpy surface can generate more static charges than other normal films, making them still a competitive option in TENG fabrication. TENG devices are categorized into four modes namely, contact‐separation, single‐electrode, contact‐sliding, and freestanding. [ \n \n 8 \n \n ] Among them, single electrode mode (S‐TENG) poses a thin device architecture with super agility and flexibility. [ \n \n 9 \n , \n 10 \n \n ] Moreover, fast response time with high voltage pulse replaces the traditional ceramic piezo sensors in motion detectors. [ \n \n 11 \n \n ] \n Notably, the density of electrostatic induced charges in the friction layer has been focused on enhancing the electric output of TENG. Particularly choosing dielectric material with defects (porous, rough contact surface), incorporating the charge trapping materials, optimizing the gap between the friction layer and primary‐electrode and separating them with the charge trapping layer can enhance the surface charge density. [ \n \n 12 \n , \n 13 \n , \n 14 \n \n ] For example, Kim et al. investigated the S‐TENG electrical output performance by varying the thickness of the PDMS deep charge trapping layer. [ \n \n 15 \n \n ] Similarly, by applying a polyimide insulating thin layer as a separator the potential loss from the recombination can be prevented. [ \n \n 16 \n \n ] These literature studies proved that reducing the charge recombination could directly enhance the surface charge and reach the saturation point rapidly. On the other hand, placing the high electron affinity materials as interlayer like reduced Graphene oxide, [ \n \n 17 \n \n ] MXene, [ \n \n 18 \n \n ] MnO nanosheets [ \n \n 19 \n \n ] etc., act as a charge storage layer. However, direct contact with the electrode often leads to fast charge drifting due to the metal‐semiconductor Schottky contact. In light of these findings, the charge‐trapping mechanism could still be improved. S‐TENG are suitable candidates for human‐machine interface energy harvesting and sensing applications, hence the animal skin and hair naturally generate electrostatic charge when approaching the opposite charged surface. [ \n \n 20 \n , \n 21 \n \n ] This phenomenal behavior can be utilized in many ways to produce free electric energy, and biophysical medical appliances with the help of electrical circuits. Recently, tissue‐engineering research achieved new milestones by improvising the trans‐epithelial potential (TEP) charges with exogenous EFs to treat chronic wounds. [ \n \n 22 \n , \n 23 \n , \n 24 \n , \n 25 \n \n ] TEP is the key component in wound repairing where the charged ions flux and cell transport effectively take place. [ \n \n 26 \n , \n 27 \n \n ] Although numerous conductive hydrogel energy transfer mediums have been used to transfer external electric current to treat chronic wounds, these patches rely on stable DC power battery resources. [ \n \n 28 \n , \n 29 \n \n ] The development of nanofiber‐based TENG is widely adapted by wearable smart garment fabrications and has become a true energy source for portable electronic gadgets. [ \n \n 30 \n , \n 31 \n \n ] Current developing research extensively investigates the optimization of EF strength and the unidirectional effect on wound remolding. [ \n \n 32 \n , \n 33 \n \n ] However, to further improve the visibility of TENG in wound management; it is paramount to specify the effect of tribo‐positive and negative potential charges with the TEP mechanism. Herein, we propose a surface charge improved S‐TENG for biomechanical sensing and EF assisted wound healing applications. The TiO 2 ‐MXene (TMx) incorporated PS NFM as a charge trapping layer benefited the electrical performance enhancement. Furthermore, the tribo‐negative layer PVDF/PU (PPU) NFM with improved mechanical properties promises a long‐lasting conversion of biomechanical energy into electricity. The fabricated S‐TENG was tested in powering LEDs, and charging a hygrothermograph. Moreover, the high sensitivity of S‐TENG facilitated the engineering of the Snakebite game with four S‐TENG as smart keys. Owing to the excellent flexibility, hydrophobicity, breathability, and lightweight, the wearable feature was established. This, flexible and wearable S‐TENG with no biological toxicity has promising wound healing applications. The EF simulation by S‐TENG was further verified by in vitro and in vivo studies. Thus, the multiple features and multi modal operation of this S‐TENG pave way in the field of energy harvesting as well as therapeutic research.",
"discussion": "2 Result and Discussion \n Figure \n 1 a conceptually illustrates the electrospun nanofiber drawing and tribo‐electrostatic interaction of NFM onto the epidermis tissue for wound repair. As NFMs possess breathable, flexible and water permeability nature, they can efficiently convert human bio‐motion into electric energy without causing skin irritation. In prior, we have described the synthesis and structure morphology of TMx doping material using scanning electron microscopy (FE‐SEM) in Figure S1 (Supporting Information), the morphology images prove that oxidation was taking place on the MXene terminals. In particular, Figure 1b shows the partly oxidized MXene containing an optimal amount of TiO 2 on the surface without destroying the entire carbon chain. X‐ray diffraction (XRD) in Figure 1c shows the peak positions corresponding to the MXene and TMx. More prominent peak appears at 6.9° indicating the successful etching of Al layers. It is evident that 6 h of oxidation does not show any of peak corresponding to TiO 2 but in the case of 12 and 24 h oxidation, a new peak appears at 25° corresponding to anatase TiO 2 (JCPDS 21‐1272) presenting partial conversion of MXene. [ \n \n 34 \n \n ] From this, we conclude that 12 h oxidation renders a large surface area with an optimal amount of TiO 2 . Electrospinning process were carried out to prepare PS NF with different weight ratios of TMx. As shown in Figure S2 (Supporting Information) the pure PS polymer produces NFs with beads due to the lower viscosity, whereas TMx with optimal weight ratio (%) produces the beadles NFs. It is obvious that TMx doping has improved the localized electrical conductivity, which diminishes the beads efficiently. Despite this, at high concentration (10 wt%) of TMx exhibit needle block due to the particle agglomeration resulting in the less dense NFs formation. Figure 1d , FE‐SEM image with bar chart profile indicates the average diameter of 7.5 wt% of TMx doping (PTMx‐7.5) NFs to be approximately 800 nm and the uniform coverage of NFs. The magnified image confirms the MXene incorporation into PS NF, which was further confirmed by energy dispersive X‐ray analysis (EDS) mapping (Figure 1e ). Also, the SEM surface morphology of PPU NFM given in Figure 1f and control sample PVDF in Figure S3 (Supporting Information) indicates that the diameter of the NFs was increased after blending PU because of viscosity change. The electroactive β phase of PVDF was improved via hydrogen bond formation with PU. As shown Fourier transform infrared spectroscopy (FTIR) (Figure S4 , Supporting Information) spectrum at 762 and 840 cm −1 are attributed to the relative polymorphs of α and β phase of PVDF respectively. [ \n \n 35 \n , \n 36 \n \n ] XRD data (Figure 1g ) result confirms the β crystalline phase appeared in PPU by suppressing the α‐phase. Figure 1 a) Schematically illustration of nanofiber synthesis and its EF induced wound healing application. b) FE‐SEM shows the surface morphology 12 h oxidized MXene. c) FT‐IR of TiO 2 grown on MXene at 6, 12, 24 h. d) Surface morphology of PTMx nanofiber membrane. e) Magnified SEM image of PTMx with EDS elemental analysis. f) SEM image of PPU NFM friction layer (inset fiber diameter bar chart). g)) XRD spectra h) tensile strength of PVDF and PVDF/ PU. i) Air permittivity of NFM. j) Dielectric constant of the PPU, and PS with various doping amount of TMx. Furthermore, a test sample with an area of 1.5×1.5 cm 2 was subjected to stress‐strain measurements, as demonstrated in Video S1 (Supporting Information). The mechanical properties of NFMs are shown in Table S1 (Supporting Information); it is observed that the PU mixing increases the Young modules and elongation breaking point enormously (Figure 1h ). Such enhanced properties can protect the NFM from delamination and mechanical damage during the pressure press‐release cycle, thereby expanding their potential lifespan. In addition, to meet the wearing comfort, the NFM scaffolds were subjected to air‐breathing tests, water‐vapor permeability tests, and water contact angle tests (WCA) individually. In Figure 1i , the air permeability of PPU NFM was shown without and with PTMx NFM interlayer; the obtained results indicated that both samples membrane has a linear relationship with air pressure (20–100 Pa). Similarly, water‐vapor permeability was evaluated by comparing the water vapor evaporation rate of NFMs with paper and cotton as shown in Figure S5a (Supporting Information). These results confirm the produced NFMs possess good air and water‐vapor permeation. Moreover, the WCA of PVDF NF increased due to the formation of hydrogen bonds by PU, which is in agreement with FTIR results. While WCA of PS NF was reduced owing to the hydrophilic nature of MXene, further the electrode styrene butadiene (SBS) NF WCA was measured, it is admired that all the WCA results show hydrophobic (≤90°) properties that sustain the NFM in sweat conditions. In general, the electrostatic charge polarity of the TENG is defined by the high dielectric permittivity and low dielectric loss of the material. The generated EF would be strongly established at a high dielectric constant; for example, Dayananda et al. [ \n \n 37 \n \n ] discovered that incorporating MXene into polymer builds the interfacial polarization and improves the dielectric constant of polymers. Taking this into account, the TMx was incorporated into PS polymer, and as expected the dielectric value of PS improved upon TMx concentration. Figure 1j , shows the dielectric of PS NFM substantially improved up to 7.5 wt% doping, which is near the percolation limit. However, the charge loss occurred when the TMx reached 10 wt% due to ohmic contact between the conductive fillers. It is obvious that the PPU NFM dielectric value is higher than the PS due to the PVDF naturally exhibiting strong charge polarity in β semi‐crystalline phase. [ \n \n 38 \n \n ] \n 2.1 Electrical Output Performance of S‐TENG In Figure \n 2 \n , we have demonstrated the electric output performance of the TENG by optimizing the thickness of the charge trapping layer and doping amount of TMx. Previously, in the S‐TENG device fabrication and charge trapping mechanism illustrated in Figure S6 (Supporting Information), the addition of PU improved the tribo‐electronegativity of PVDF, resulting in an increment in the output performance (Figure 2a ). Although, increasing the PVDF electroactive phase does not effectively improve the electric output of TENG, rather close contact with the primary‐electrode causes charge recombination and a weak EF. To prevent such energy loss and improve the static potential charge distribution, PS charge trapping polymer was placed between the contact material and the primary‐electrode. By fixing the 20 µm thickness of PPU NFM, we optimized the PS NFM thickness of 20, 40, and 60 µm (1:1, 2:1, 3:1 represented). As shown in Figure 2a–c ), PS interlayer thickness has an influence on the results of open‐circuit voltage ( V \n OC ), short‐circuit current ( I \n SC ), and transfer charge ( Q ). According to Coulomb's law expression, the EF is inversely proportional to the square of separation distance ( r ) of the dielectric layer with an electrode. Therefore, at 20 µm separation distance, the induced charges are transferred and stored in the PS layer, which gives approximately V \n OC = 80 V, I \n SC = 5.5 µA, Q = 35 nC. However, at a high EF, the accumulated electrons rushed towards the electrode with high velocity. Subsequently, at 60 µm dielectric thickness provides a large surface to store the electrons, still the electrostatic potential is inversely proportional to distance; therefore it induces the weak surface potential charges on the electrode which gives V \n OC = 60 V, I \n SC = 2 µA, Q = 20 nC. While, 40 µm PS thickness exhibits the electrostatic charge with threshold limit giving V \n OC = 120 V, I \n SC = 8 µA, Q = 40 nC approximately. Enhancing the EF strength of the dielectric without losing charges would trigger the researchers to focus more on energy storing semiconductors addition. MXene has already proved its potential in energy storage and optoelectrical applications, due to its large surface area and high electrical conductivity. In contrast, in situ oxidation provides the MXene with improved dielectric properties, which helps to store charge without loss. However, at high EF the stored charges flow to the nearby electrode, whereas adding this charge carrier into the PS dielectric polymer can accumulate the charges at the interface owing to the Maxwell‐Wagner Sillars interfacial polarization phenomena. As proof of concept, Figure 2d–f shows the electric output performance of S‐TENG, when the TMx doping ratio of 2.5, 5, and 7.5 wt% to PS, the output performance increased gradually. The maximum output [ V \n OC = 280 V, I \n SC = 20 µA, Q = 120 nC] was achieved with a doping amount of 7.5 wt%. At this level considered the percolation limit, where the induced charges transfer to TMx and are trapped. This result confirms that TMx doping retains the electron clouds even at the high EF, which forms the maximum static charges on the primary electrode. On the contrary, further addition of TMx (10 wt%) was not helpful because high doping of conductive material forms an interconnecting network that leads to electron flow through them. Moreover, the particle agglomeration causes poor fiber morphology with less dense NFM per unit area, it exhibits a decreasing trend in electrical outputs. A frequency range of 1 to 5 Hz was applied to study the change in V OC with changing frequency as shown in Figure 2g . Notably, the maximum voltage output was obtained at 3 Hz frequency. The reason is that at higher frequencies, the contact‐separation operation time becomes shorter, which results in a faster surface charge saturation. In spite of this, further increasing the frequency does not help to deform the S‐TENG efficiently and induces charges, so the V \n OC starts to decrease. The contact electrification ability of PPU NFM with various positive friction layers such as Al, PVA, glove and skin was also investigated (Figure 2h ). The variation in the V OC is related to their electron donating nature, a high number of electrons causes strong polarization, which gives high amplitude output. Moreover, a prototype of S‐TENG device with 1 × 3 cm 2 was mounted on finger to study the sensitivity at various bending angles (30°, 45°, 60°, and 90°) as shown in Figure 2i . It was observed that the results were in linear agreement with strain based upon the bending angle. Figure 2 a) Optimization of voltage, b) short‐circuit current and c) charge transfer of S‐TENGs, pure PVDF and PPU friction layer; PS charge trapping layer with three different thickness (1:1, 2:1, 3:1). d–f) Influence of PS interlayer with various doping amount of TMx in electric output performances. g) Voltage of S‐TENG upon various applied frequency. h) S‐TENG working ability under various tribo‐positive friction materials. i) Finger mounted S‐TENG show voltage at different bending angles. 2.2 Surface Charge Enhancement in S‐TENG The surface charge enhancement in TENG can be directly related to the built‐in EF of the dielectric. In detail, the contact separation or sliding mechanism of TENG generated the electrostatic potential difference between the electrode and contact layer where the strong EF is built. However, the induced EF could vanish rapidly, which affects the surface charges on the contact layer. This phenomenon can be explained by mainly two factors, i) neutralization of surface charges by ionized air, ii) at high EF the charges drive faster to the electrode. Owing to the above reasons, the maximum charge transfer efficiency of S‐TENG is less than the normal TENG. Many physical and chemical surface treatments were performed to improve the tribo‐electrified charges on the electrified area. [ \n \n 39 \n \n ] However, to achieve high performance S‐TENG the induced electrons must be trapped and stored within the dielectric medium. As we discussed previously, the PTMx interlayer increases the capacitance of the transfer charge accumulation by metal‐polymer interfacial polarization and prevents the charge drifting by the electrode, which enhances the surface potential ( Q ) and surface charge density ( σ ) on the electrode. According to the equivalent circuit diagram, the voltage output ( V ) is a linear relationship with Q and reciprocal to the capacitance ( C ), [ \n \n 40 \n , \n 41 \n \n ] \n \n (1) \n V = − 1 C × Q + V oc \n where V is the sum of the E = E \n PPU + E \n PTMx of the dielectric layers, in short circuit condition V equals 0 and Q equals to short circuit transfer charge ( Q sc), therefore,\n \n (2) \n Q sc = C V oc \n \n Due to the fixed electrodes in S‐TENG, the C value becomes constant even with the increase of gap distance x ( t ), resulting in the increase of surface charge density (σ) on the electrode leading to a faster saturation of V \n OC .\n \n (3) \n V oc = σ x t ε 0 \n \n To understand the proposed theoretical model, evaluating changing Q on the dielectric surface as a function of time is a more promising approach. In Figure \n 3 \n , we have demonstrated the comparison of overall surface charge distribution on PPU NFM with and without PTMx trapping interlayer over time by utilizing a powerful Kelvin probe force microscope (KPFM) analytical tool and COMSOL multiphysics simulation study. As systematically described in Figure 3a , a KPFM superior lateral resolution technique was employed to capture the surface image and quantify the Q variations at the nanometer scale. As following our previous study, [ \n \n 41 \n \n ] the potential charges were induced by gently rubbing the surface of contact material with the finger, resulting in the generation of high surface charge density on the NFM. Figure 3b–d shows the PPU NFM surface topographical image with respective charge potential distribution before and after contact separation with skin. The obtained spatial potential value of (−1.5 V) was decreased to (−5.5 V) after the surface contact experiment. A negative sign in the obtained value confirms the polarized charges generated on the PPU NFM resulting in the enhancement in tribo‐negativity, thus generating the opposite charges on the electrode surface. As a result, a strong EF forms between the electrode and the dielectric. However, inevitable charge recombination at the electrode surface neutralized the total charge transfer efficiency, which could reduce the S‐TENG performance. To address the potential loss, screening the generated electrons inside the dielectric can significantly change the electrical output. By considering this, we trapped the charges into the PTMx NFM and avoided the charge recombination with the electrode. Figure 3 a) Schematic representation of KPFM measurement on PPU surface with and without charge trapping PTMx‐7.5 NFM layer. b) Topographical image of PPU frictional layer. c,d) Surface charge density on PPU layer before and after contact separation process. e‐i) shows the observed surface charge loss on the friction layer without PTMx‐7.5 NFM. (ii) The surface potential derived from the image (i). (iii‐iv) COMSOL derived theoretical assumption on electric potential. f‐i,ii) surface energy loss, (iii,iv) COMSOL derived theoretical electric potential with PTMx‐7.5 NFM. Usually KPFM measurements, the surface potential is derived from the contact potential difference between the AFM measuring tip and the sample surface, which defines the work function of the sample.\n \n (4) \n V CPD = φ sample − φ Tip / e \n where φ sample , φ Tip are the work function of the sample and the tip, e is the elementary charge. The above equation confirms that the obtained result during the operation (after contact with skin) also corresponds to the PPU sample work function. By taking this into account, we measured the retained charges on the surface before and after contact. As well the surface charge dissipation was tracked at various time intervals of 10, 20, and 30 min in a closed environment to avoid the influence of moisture ionization (Figure S7 , Supporting Information). Therefore, the potential loss in contact surface area can only be caused by charge neutralization with the electrode. In Figure 3e without PTMx interlayer, the surface electrons disappear faster due to the above‐mentioned factor. Figure 3e‐i–iii , experimental results show that after 30 min interval the surface potential value has increased from −5.1 to −1.5 eV. This confirms that the surface electron loss is because of charge drifting resulting in poor polarity. Whereas, after placing the trapping layer the induced electrons are trapped within the PTMx layer, which prevents and slower the rate of charge recombination. Meanwhile, the stored electrons create a strong EF to form high charge polarization (Figure 3f ). A simulation study was performed using COMSOL (6.1) to conclude the experimental results supported with theoretical proof. Herein, the S‐TENG model is defined with and without PTMx trapping layer, the PPU contact layer with human skin. The derived surface potential values of Figure 3e‐iv,f‐iv proved that inserting the trapping layer would increase the S‐TENG performance. In summary, we conclude that insertion of the PTMx charge trapping layer not only prevents energy loss but also increases the EF strength, which induces high polarized charges on the primary electrode. This new approach can give the solution for fabricating high‐performance TENGs without energy loss. 2.3 Evaluating the Electrical Performance of S‐TENG in Commercial Electric Appliances \n Figure \n 4 \n illustrates the utilization of electrical output performance in electrical appliances and real‐time demonstration of S‐TENG in touch sensors. In general, the contact separation process of TENG device produces the electrostatic potential charges in terms of alternating current (AC). The AC produces a high amplitude voltage, due to the fact that the parallel plate capacitors are charged and discharged simultaneously. In order to rectify this, a four‐wave bridge rectifier was connected in the series, as described in Figure 4a inset circuit sketch. The results confirm the full conversion of AC sine‐wave signal into direct current (DC). To demonstrate the working of S‐TENG in portable electronics, our device is connected to charge various capacitors (4.7, 10, 22, 47 µF) by applying the pressure at a constant (3 Hz) frequency. Figure 4b,c render the comparison of capacitor charging efficiency of S‐TENG without and with PTMx NFM interlayer, respectively. It is obvious that after inserting PTMx NFM the charging time becomes shorter. From the above results, we concluded that with the trapping layer, the surface charges attain their maximum shortly and facilitate sustainable output for rectification with applied frequency. Before employing the S‐TENG directly to charge electrical appliances, we evaluated the sustainable power density (PD) across the various load resistance ( R ) (1–100 MΩ). As Ohm's law states, with an increasing R ‐value the prompt voltage increases, when R is significantly high the V \n OC becomes saturated. In such manner, the maximum PD reached to be 25.2 µW cm −2 at 7 MΩ resistance, and further increase of R leads to the PD decline as shown in Figure 4d . To demonstrate the S‐TENG performance towards electronic gadgets, we have shown the instantons powering of 60 LED (red‐green‐blue) in Video S2 (Supporting Information) this proves that the device produces enough power with regular periodic pressure. Similarly, an experiment with a capacitor was conducted by connecting the S‐TENG to a circuit containing a digital hygrothermograph device (Figure 4e ), this graph reveals a typical charge‐discharge can occur in repeated cycles. Furthermore, the device durability was tested by continuously beating with a homemade tapping instrument at a fixed 1.5 Hz frequency. As displayed in Figure 4f , the voltage profile appeared regularly, confirming that S‐TENG can generate stable output for a long‐term. As shown in the photographic image in Figure S8 (Supporting Information), after long‐time tapping the PVDF NFM displays a poor surface with delaminated fibers, whereas the PPU NFM surface remains intact. This outcome proved that the PPU NFM can protect the PTMx interlayer and is extensively operative when employed for human use. Figure 4 a) Rectified voltages. Inset circuit shows the bridge rectifier with S‐TENG device. Capacitor charging ability of S‐TENG b) without and c) with PTMx‐7.5 NFM interlayer. d) Power density of the optimized sample under various resistance. e) Powering the time piece using 22 µF capacitor charging. f) S‐TENG duration test under 1.5 Hz for long time, inset (before and after voltage output). g) Engineering of electronic circuit for self‐powered flexible smart key. h) Photographical images of powered electronic gadgets, smart keys and “Snakebite” video game. Featuring a high electronegative surface, our S‐TENG exhibits excellent energy harvesting properties on human skin and epoxy gloves. In order to make S‐TENG devices in biocompatible wearable applications, the device performance with various area dimensions was evaluated. According to Figure S9a (Supporting Information) with increasing the friction area the energy output increases, which is obvious that high surface area can accumulate a large charge density. Additionally, S‐TENG device shows excellent sensitivity under various load impact pressure (Figure S9b,c , Supporting Information). Herein, we applied force of 0.5 to 15 N m −1 with load mass, the observed voltage amplitude shows an increasing trend. From the obtained result, the derived sensitivity value of S‐TENG is 11.2 V N −1 . Furthermore, the device responds to the other regular environmental forces of finger‐taping, metal friction and water droplet impact pressure (Figure S9e–g , Supporting Information). Owing to S‐TENG high sensitivity, we designed self‐powered physical sensors using circuit‐engineering technology. As shown in Figure 4g , four S‐TENG devices were constructed as flexible keys to the programmed Snakebite video game (Video S3 , Supporting Information). The devices with high sensitivity perform well as self‐powered navigation keys. This proto‐type self‐powered invention can reduce battery usage in regular switches and gaming gadgets (Figure 4h ). Moreover, AgNP‐coated SBS NFM (Ag/SBS NFM) electrodes with stretchable, breathable and antibacterial properties afford S‐TENG to be utilized for skin wearable devices. 2.4 Influence of S‐TENG Electric Field Simulation on L929 Cells Vitro Experiment Prior to EF stimulated wound healing experiment, it is important to understand the basic healing mechanism of wounds. Normally wound healing process is promoted by difference in TEP between the wounded area and normal skin. [ \n \n 42 \n \n ] Comprehensively, when a wound occurs, the endogenous TEP generates an electric current to drive the charged ions Na + Cl − toward the center of the wounded area to promote the healing process. [ \n \n 22 \n , \n 27 \n \n ] However, in treating chronic wounds, a weak TEP prolongs the wound healing duration. This creates the demand for the use of an exogenous EF. As shown in Figure \n 5 a , the S‐TENG was designed with a PET substrate for free tapping on the rat skin when it moves (Figure S10 , Supporting Information), and the induced energy was transferred to the wounded area with the help of Ag/SBS NFM. A breathable Ag/SBS NFM was fixed on the wound using transparent 3M Tegaderm. Our previous work on Ag/SBS NFM electrode synthesis with optimized electrical performance and antibacterial properties was followed up in this work. [ \n \n 41 \n , \n 43 \n \n ] In addition, we directly investigated the cytotoxicity of the electrode membrane with L929 cells by adjusting the AgNP coating percentage of 3, 6, 9, 12, and 15 wt% (Figure 5b ). The obtained results show that up to 12 wt% of AgNP, the electrode shows good agreement with 90% cell viability. However, further increasing the AgNP concentration is not advisable since it shows electroporation in the nucleus. Using the L929 cell assay, an vitro scratch experiment was conducted to examine the influence of the EF on cell migration and assembly. As we discussed in the experimental section a linear scratch was made on the cell monolayer with a spacing of approximately 5 µm. Afterwards, a pair of copper taps were fixed on both sides of the scratch with a distance of 1.5 cm, and a continuous AC EF was given by the TENG device. The sewing machine was used to tap the device with 4 Hz frequency and continue for 30 min, this procedure was continued for three consecutive days. A similar procedure was followed for the DC EF; the experimental procedure was captured in Video S4 (Supporting Information). A control sample was kept aside without any special treatment. As depicted in Figure 5c , the microscopic result ascertained that EF stimulation has improved cell migration enormously. After 30 min of EF simulation, the AC potential accelerate the cell mobility randomly which was clearly observed, whereas the DC drove the cells uniformly to the scratch. Meanwhile, the control cell group remained unchanged. Typically, the EF strength in the units of V m −1 may cause electroporation in vitro experiments, but in the living body, it is safe and harmless to the cells. However, this time‐limited operation accelerated the cell regeneration faster without causing the electroporation in the nucleus. Figure 5d , given the quantitative assessment of the cell migration ratio of the three test samples, in which DC EF results show 100% cell rearrangement; AC EF shows more than 90% regeneration. Before employing the device in vivo experiment, we evaluated the AC and DC electric output performance of the skin‐mounted S‐TENG. In Figure 5e , the obtained result elicits that frequent voltage pulse was obtained when the rat was physically active (running, bending, shaking), and the obtained V \n OC is 1‐10 V and rectified negative bias voltage is 1–2.5 V. To support this, we have monitored the rat movement by using Arduino Uno wireless circuit, Video S5 (Supporting Information) indicates the “Wound Healing Progress” keyword to represent the S‐TENG activation. It is assumed that our S‐TENG's EF stimulation cues could assist wound re‐epithelialization rapidly. Figure 5 a) Illustration of S‐TENG electric simulation during wound healing process. b) Cell viability of Ag/SBS NF with different doping amount. c) In vitro starch assay of L929 cells without treatment (control) and with AC/DC EF. d) Cell migration ratio before and after 30, 60, 90 min. e) S‐TENG electric outputs with open circuit and rectified voltage. 2.5 Electric Field Accelerated Wounded Repairing Our S‐TENG device is believed to induce triboelectric charges continuously when in contact with the rat skin, as formed electrostatic potential progressively provokes cells to proliferate towards re‐epithelialization. To prove this, an vivo experiment was conducted by directly mounting the S‐TENG on the wounded rats as described in the schematic Figure \n 6 a . According to the animal experiment protocol (LAC‐2022‐0203), six SD rats' dorsum skin was cut into 1.8 cm in circles. A pair of rats were used for the concordant results. The wound status was monitored by taking photos on 3, 7, 10, and 14 d of surgery (Figure 6b ). The control sample represented rats without being subjected to any treatment. Figure 6 a) Schematic demonstration of AC and DC ES process on wounded area. b) Photograph of wounded skin at various time intervals. c) Wound area recovery after 3, 7, 10, 14 d of treatment. d) H&E and e) M–T histogram examination of newly formed skin tissue. f) Collagen density measurement of M–T image. Generally, the wounded skin naturally produces TEP to pump the Na + ions inwards and Cl − ions apically outwards, where the short‐circuited positive current flows towards the wound center. Lately, it has been proven that increasing ion flux in endogenous EF by applying exogenous current works well. The purpose of the present study is to investigate how changing exogenous electric potentials affect the flow of endogenous ions movement. During AC EF simulation, the induced electrostatic potential generates dense positive surface charges on the electrode whereby high Cl − ions were generated at the apical side of the wounded area as shown in Figure 6a . As generated exogenous potential, induce the large endogenous EF as favoring the Na + ion at the basal side (unwounded). It is evident that when coupling an exogenous EF to TEP accelerates wound healing rapidly, besides forming laterally orientated cell proliferation. We patch the electrode mainly to contact the edges of the wound this allows the wound to recover symmetrically. The obtained wound closure ratio already reached 95% on day 14 (Figure 6c ). This result ascertains that tissue granulation occurred from all directions (Figure 6b ). Whereas in DC EF simulation, the transformed DC negative bias via bridge rectifier was transferred to the electrode patch (Figure 6a ). As we expected the negative potential significantly affects the TEP. This may be the case that Cl − ions do not attract the negative charges, thus generating a poor potential barrier at the skin surface. However, when compared with an untreated wound, DC EF simulation significantly improved wound healing by 70%. After the completion of 14 d of the experiment, the regenerated skin was collected from the rats for histological analysis in order to quantify the phase of proliferation, tissue granulation, and collagen formation. Hematoxylin and eosin (H&E) staining experiment results in Figure 6d reveal the EF simulated the samples have progressively improved cell proliferation including the formation of thick keratinocytes (dark purple) at the epidermis layer and blood vessels (BV‐black circle) at the dermis (D) region. Especially with some new hair follicles found in the EF treated wounded area, this confirms the complete rehabilitation of the epidemic skin. On the contrary, the control sample shows many gaps, and a large number of inflammatory cells in the dermis, this indicates that granulation was not taking place in the control sample. Masson trichrome (M‐T) staining test results as seen in Figure 6e further affirmed the dense collagen formation upon EF simulation, whereas the control sample shows defects, which affect the elasticity of the skin. Using imageJ software RGB color deconvolution to measure the collagen deposition of M‐T samples. As shown in Figure 6f , collagen deposition of approximately 28%, 41%, and 48% in control, DC, and AC test samples respectively. These results confirm that electrostatic potential significantly promoted fibroblast cells for collagen formation to accelerate wound healing."
} | 10,042 |
34145392 | PMC8630106 | pmc | 1,387 | {
"abstract": "Methane-generating archaea drive the final step in anaerobic organic compound mineralization and dictate the carbon flow of Earth’s diverse anoxic ecosystems in the absence of inorganic electron acceptors. Although such Archaea were presumed to be restricted to life on simple compounds like hydrogen (H 2 ), acetate or methanol, an archaeon, Methermicoccus shengliensis , was recently found to convert methoxylated aromatic compounds to methane. Methoxylated aromatic compounds are important components of lignin and coal, and are present in most subsurface sediments. Despite the novelty of such a methoxydotrophic archaeon its metabolism has not yet been explored. In this study, transcriptomics and proteomics reveal that under methoxydotrophic growth M. shengliensis expresses an O -demethylation/methyltransferase system related to the one used by acetogenic bacteria. Enzymatic assays provide evidence for a two step-mechanisms in which the methyl-group from the methoxy compound is (1) transferred on cobalamin and (2) further transferred on the C 1 -carrier tetrahydromethanopterin, a mechanism distinct from conventional methanogenic methyl-transfer systems which use coenzyme M as final acceptor. We further hypothesize that this likely leads to an atypical use of the methanogenesis pathway that derives cellular energy from methyl transfer (Mtr) rather than electron transfer (F 420 H 2 re-oxidation) as found for methylotrophic methanogenesis.",
"conclusion": "Conclusion In this study, we analysed the growth of the demethoxylating methanogen M . shengliensis on methoxylated aromatic compounds and showed that this archaeon uses a demethoxylation system (Mto) similar to those found in acetogenic bacteria. In contrast to the methylotrophic pathway of methanogenic archaea, the methyl group derived from the methoxylated compound is most likely transferred to H 4 MPT instead of CoM. In theory, such activation would thermodynamically require that methoxydotrophic methanogenesis takes an energy acquisition strategy distinct from that of methylotrophic methanogenesis. This hypothesis can be supported by the finding that, during methoxydotrophy, M. shengliensis downregulates genes involved in energy-generating electron transfer metabolism that is essential for methylotrophy. Clearly, methoxydotrophic methanogenesis exhibits several interesting features that differ from methylotrophic methanogenesis and requires further investigation to verify the biochemistry of methoxylated aromatic compound activation and downstream energy metabolism.",
"introduction": "Introduction Methanogenesis evolved more than 3.46 Gyr ago and has profoundly contributed to Earth’s climate [ 1 , 2 ]. About 70% of the emitted methane (CH 4 ) is produced by methane-generating archaea (methanogens; [ 3 ]) underlining the importance of methanogenesis for the global carbon cycle. Methanogens are known to produce methane from one- to two-carbon substrates (i.e., carbon dioxide [CO 2 ], acetate, and methylated compounds), often using (in)organic compounds as electron donors (e.g., hydrogen [H 2 ] and formate). Three major pathways of methanogenesis are known. In the hydrogenotrophic pathway, H 2 (or formate) are used as electron donors with carbon dioxide as electron acceptor. In the methylotrophic pathway, small methylated carbon compounds are converted to methane and carbon dioxide. In the aceticlastic pathway, acetate is cleaved to methane and carbon dioxide [ 4 ]. Beyond this, a thermophilic methanogen isolated from a deep subsurface environment [ 5 ], Methermicoccus shengliensis , was recently discovered to directly generate methane from a variety of methoxylated aromatic compounds (ArOCH 3 ) [ 6 ]. Methoxylated aromatic compounds are derived from lignin and occur in large quantities on Earth [ 7 ]. The environmental abundance of methoxylated aromatics indicates that methoxydotrophic archaea might play a so far unrecognized and underestimated role in methane formation and carbon cycling of coal, lignin, and other humic substances, especially in the subsurface [ 8 ]. Aromatic compounds are a major component of crude oil with about 20–43% [ 9 , 10 ], and it is quite likely that methoxylated aromatic compounds in oil might be degraded by methoxydotrophic organisms. As M. shengliensis has been isolated from oil production water [ 5 ], the organism might play a role in the degradation of methoxy compounds in oil reservoirs. Next to oil, methoxylated aromatic compounds are components of coal. Although conversion of coal compounds to methane has been thought to require metabolic interactions [ 11 ], Methermicoccus ’ ability to accomplish this alone might have significant implications for coalbed methane formation (7% of global annual methane formation [ 12 ]), including enhanced methane recovery [ 13 ]. Therefore, it is important to understand the unique methoxy compound-degrading methane-forming metabolism of M. shengliensis . The discovery of the methoxydotrophic ability of M. shengliensis revealed that the capacity to degrade methoxylated aromatic compounds is not confined to bacteria as previously thought, yet how M. shengliensis (and thus archaea) accomplish methoxydotrophic methanogenesis remains unknown. The organism is also capable of and possesses the necessary genes for methylotrophic methanogenesis [ 6 ], in which a methylated substrate (e.g., methanol) is disproportionated to ¾ CH 4 and ¼ CO 2 . In principle, degradation of methoxy groups could follow a similar pathway, given that methyl and methoxy groups have the same oxidation state. However, isotope-based investigation showed that methoxydotrophic methanogenesis unprecedentedly entails both methyl disproportionation and CO 2 reduction to CH 4 [ 6 ], suggesting the involvement of a novel methanogenic pathway. In this study, integration of genomics, transcriptomics, and proteomics reveals that M. shengliensis methoxydotrophy employs a novel methyltransferase system for ArOCH 3 \n O -demethylation. While known methanogens transfer methyl compounds using coenzyme M (CoM) as a C 1 carrier [ 14 ], we suggest that the M. shengliensis ArOCH 3 methyltransferase rather uses tetrahydromethanopterin (H 4 MPT) as final C 1 carrier. The different entry point into methanogenesis (i.e., as CH 3 -H 4 MPT rather than CH 3 -CoM) putatively prompts changes in energetics, thermodynamics, and kinetics that might involve an idiosyncratic C 1 catabolism cycling between oxidation and reduction.",
"discussion": "Results and discussion Genomic analysis Anaerobic degradation of methyl compounds in both Archaea and Bacteria begins with the transfer of the methyl group to a physiological C 1 carrier. In both systems, a substrate-specific methyltransferase (MT1; Eq. 1 ) transfers the methyl group to a corrinoid protein (CP) and another methyltransferase (MT2 Eq. 2 ) performs a subsequent transfer to a physiological C 1 carrier—coenzyme M (CoM) for Archaea and tetrahydrofolate (H 4 F) for Bacteria [ 14 , 43 ]. Both require two methyltransferases, one CP, and an activating enzyme to recycle adventitiously oxidized CPs [ 44 , 45 ]. 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}$${\\mathrm{CH}}_3--{\\mathrm{X}} + {\\mathrm{Co}}( {\\mathrm{I}})--{\\mathrm{CP}} + {\\mathrm{H}}^ + \\to {\\mathrm{CH}}_3--{\\mathrm{Co}}({{\\mathrm{III}}})--{\\mathrm{CP}} + {\\mathrm{H}}--{\\mathrm{X}}$$\\end{document} CH 3 X + Co ( I ) CP + H + → CH 3 Co ( III ) CP + H X 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}$${\\mathrm{CH}}_3--{\\mathrm{Co}}({{\\mathrm{III}}})--{\\mathrm{CP}} + {\\mathrm{Y}}--{\\mathrm{H}} \\to {\\mathrm{CH}}_3--{\\mathrm{Y}} + {\\mathrm{Co}}( {\\mathrm{I}})--{\\mathrm{CP}} + {\\mathrm{H}}^ +$$\\end{document} CH 3 Co ( III ) CP + Y H → CH 3 Y + Co ( I ) CP + H + Y = CoM or H 4 F M. shengliensis can metabolize MeOH and mono-, di-, and tri-methylamines and encodes the necessary substrate-specific CPs, MT1s, and MT2s (Fig. 1a, b ; Supplementary Table S1 ). However, with help of an extensive genome analysis we identified an operon in the M. shengliensis AmaM and ZC-1 genomes encoding a putative methyltransferase complex of unknown specificity that has previously been overlooked. This operon includes a CP (Amam_00017; BP07_RS03260), three methyltransferases (Amam_00018, Amam_00019, and Amam_00021; BP07_03250, BP07_03255, and BP07_RS03240), and a corrinoid activator protein (Amam_00022; BP07_RS03235) distantly related to known methanogen methyltransferase components (Fig. 1a–c , and Supplementary Fig. S1 ). Fig. 1 M. shengliensis AmaM and ZC-1 corrinoid protein and methyltransferase phylogeny. a A phylogenetic tree of AmaM methyltransferase corrinoid proteins (red and bolded) and homologs were generated through sequenced alignment via MAFFT v7.394 and tree calculation via RAxML-NG v0.5.1b. The homologs include those specific to vanillate (MtvC; purple), MeOH (e.g., MtaC; green), methylated thiols (e.g., MtsB; yellow), and methylamines (e.g., MtmC; blue). For methyltransferase corrinoid proteins fused with their partner methyltransferase, only the cobalamin-binding region was extracted for this alignment. In addition, a novel cluster of bacterial methyltransferases is shown, including those from ArOCH 3 -metabolizing anaerobes (indicated with purple circles). Bootstrap values are shown for 200 iterations (>90% black, >70% gray, >50% white). b Phylogenetic tree of MtaA/CmuA family (TIGR01463, cd03307, and IPR006360) and MtvB-related methyltransferases, including those from M. shengliensis (red and bolded) and M. thermoacetica (purple and bolded). MT2 for MeOH (e.g., MtaA; green), methylamine (e.g., MtbA; blue), and MeOH/methylamine bifunctionally; bifunctional MT1/MT2 for methylated thiols (e.g., MtsA; yellow); and MT1 for chloromethane (gray) are shown. Methyltransferases affiliated with ArOCH 3 -metabolizing anaerobes (purple circles) form a novel cluster. c The operon encoding the novel corrinoid protein (MtoC) with methyltransferases (MtoB1, MtoB2, and MtoA) and corrinoid protein activase (MtoD) along with potential aromatic compound transporters (MfsT MFS transporter, EffT Efflux transporter) and a transcriptional regulator (TR). Operons identified in bacterial ArOCH 3 metabolizers are also shown with amino acid sequence percent identity with MtoC and MtoB2. Although an archaeal O -demethylase/methyltransferase system for methoxylated aromatic compounds has not been described previously, some genes identified in this study and mentioned above show homology with counterparts in the bacterial Mtv O -demethylation system present in the homoacetogenic bacterium Moorella thermoacetica (Pierce et al. [ 60 ]; Fig. 1a, b ; Supplementary Table S1 ). Amam_00017 (BP07_RS03260) and Amam_00018/19 (BP07_RS03255/50) are closely related to the CP (MtvC) and vanillate-specific MT1 (MtvB) of the three-component Moorella thermoacetica vanillate O -demethylase system MtvABC [ 46 ], indicating involvement of the operon in ArOCH 3 demethylation. We also found Amam_00017, 18, and 19 homologs in the genomes of other ArOCH 3 -catabolizing bacterial anaerobes whose methyltransferases have yet to be identified (Fig. 1c ) [ 47 – 51 ]. Based on phylogenetic comparison of the archaeal and bacterial systems, Archaea likely acquired the O -demethylase (MtvB) and corresponding CP (MtvC) for methoxylated aromatic compound metabolism through horizontal gene transfer from Bacteria (Fig. 1a, b ). The genes putatively involved in methoxydotrophic growth are also present in other archaea like Archaeoglobus fulgidus and the hydrogenotrophic methanogens Methanolacinia petrolearia and Methanothermobacter tenebrarum (Fig. 1a, b ), indicating that the trait for methoxydotrophic growth might be more prevalent among archaea than previously thought. As the above methyltransferases and CP are cytosolic, M. shengliensis requires transporters for the uptake of methoxylated aromatic compounds. Although specific transporters for aromatic compounds have not been found for methanogens, previous studies have characterized several bacterial aromatic acid:H + symporters belonging to the major facilitator superfamily (MFS) [ 52 ]. This includes PcaK from Pseudomonas putida [ 53 ], TfdK from Ralstonia eutropha [ 54 ], BenK, VanK, PcaK, and MucK from Acinetobacter sp. ADP1 [ 55 – 57 ] and MhpT from Escherichia coli [ 58 ]. We also identified genes encoding MFS transporters adjacent to the aforementioned methyltransferases (Fig. 1c and Supplementary Table S1 ) and suspect that they drive aromatic compound transport for M. shengliensis . Novel demethoxylation pathway involves methyl transfer to tetrahydromethanopterin To verify involvement of the aforementioned gene cluster in ArOCH 3 metabolism, we compared AmaM transcriptomes during methanogenesis from ArOCH 3 (i.e., p -methoxy-benzoate [MB] and 3,4,5-trimethoxybenzoate [TMB]) and methyl compounds (i.e., MeOH and trimethylamine) as well as the ZC-1 transcriptomes and proteomes of ArOCH 3 (i.e., TMB)—and cells grown on methyl compounds (i.e., MeOH). For AmaM, the MtvB-related methyltransferase MtoB2, another methyltransferase designated MtoA, reductive activase MtoD, and an MFS transporter MfsT1 were consistently strongly upregulated during growth on methoxylated aromatic compounds ( p value < 0.05; Fig. 2 and Supplementary Tables S1 and S2 ). Similarly, ZC-1 upregulated MtoB1, MtoB2, CP MtoC, reductive activase MtoD, and MfsT1 in the transcriptomes and or proteomes ( p value < 0.05; Fig. 2 and Supplementary Table S1 ). The novel M. shengliensis methyltransferase genes displayed one of the highest increases in expression among all genes (Fig. 2 and Supplementary Table S1 ), up to 90-fold. We propose that Amam_00017~22/BP07_RS03235~60 collectively function as a novel ArOCH 3 -specific O -demethylase/methyltransferase system, tentatively termed the Mto system based on the nomenclature used by Sauer and Thauer for methanogenic methyltransferases [ 59 ], and the adjacent transporters as ArOCH 3 uptake or byproduct aromatic compound efflux proteins. We further propose that Amam_00018/BP07_RS03255 and Amam_00019/BP07_RS03250 function as ArOCH 3 -specific MT1 (MtoB1 and MtoB2 respectively) and Amam_00017/BP07_RS03260 as the corresponding methyl-carrying CP (MtoC), based on the aforementioned similarity with Moorella thermoacetica MtvB and MtvC (Fig. 1 ). Together, MtoB(1/2) and MtoC likely accomplish the first step in ArOCH 3 \n O -demethylation (Eq. 3 ). 3 \\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}$${\\mathrm{ArOCH}}_3 + {\\mathrm{Co}}({{\\mathrm{I}}}) + {\\mathrm{H}}^ + \\to {\\mathrm{CH}}_3-- {\\mathrm{Co}}( {{\\mathrm{III}}})--{\\mathrm{MtoC}} + {\\mathrm{ArOH}}$$\\end{document} ArOCH 3 + Co ( I ) + H + → CH 3 Co ( III ) MtoC + ArOH Fig. 2 Comparison of gene expression during growth on methylated and methoxylated substrates. (left) Gene expression of the novel AmaM/ZC-1 corrinoid protein and methyltransferase operon, methanogenesis pathways, and electron transduction (see Supplementary Table S1 for abbreviations). RPKM (reads per kilobase transcript per million mapped reads) values are normalized to the average ribosomal protein RPKM under methanogenesis from MeOH, trimethylamine (TMA), 2-methoxybenzoate (MB), and trimethyoxybenzoate (TMB). (right) The ratios of gene expression between ArOCH 3 - and methylated compound-fed conditions are shown ( p value < 0.05 marked with dot). For ZC-1, dots are shown if at least two TMB-grown cultures show significantly different RNA expression levels ( p value < 0.05) from the MeOH-grown cultures (see Supplementary Table S1 ). Similarly, triangles are shown if significant differences in protein expression levels were observed ( p value < 0.05). For entries spanning multiple genes, expression levels of specific subunits are shown as indicated on the right-hand side. As described before, M. shengliensis can use a broad range of different methoxylated aromatics for growth [ 6 ]. The O -demethylase proteins MtoB1 (Amam_00018/BP07_RS03255; 48 kDa) and MtoB2 (Amam_00019/BP07_RS03250; 47 kDa) have a sequence similarity of 57% to each other (NCBI BLASTp). This dissimilarity might hint towards different substrate affinities of the two proteins. In the first step of methoxydotrophic methanogenesis, through O -demethylation via the MtoB proteins, the methyl group is most likely transferred to the cobalt containing CP MtoC (22 kDa; N-terminal Coenzyme B 12 binding site [Prosite: https://prosite.expasy.org ]). MtoD (Amam_00019/BP07_RS03235; 68 kDa) is predicted to perform activation of the CP, a process necessary for catalytic activity of the CP in both acetogens and methanogens. This corrinoid activation protein MtoD harbors an N-terminal 2Fe-2S binding site (Prosite: https://prosite.expasy.org ), a feature more similar to those of acetogens than methanogens (two C-terminal 4Fe-4S clusters) [ 28 ]. The next step is methyl transfer from CH 3 -MtoC to a physiological C 1 carrier by a methyl transferase (MT2). In methylotrophic methanogens, the methyl group is transferred from the CP to CoM via the methyl transferase MtaA when grown on methanol (Fig. 3 ). In the acetogen Moorella thermoacetica the methyl transferase MtvA transports the methyl group from the CP to H 4 F [ 46 ]. M. shengliensis does not encode an mtvA -like gene and mtaA is neither upregulated under growth on methoxylated compounds nor part of the identified methoxydotrophy gene cluster. Instead, an mtrH -like gene (Amam_00021/BP07_RS03240) is part of the aforementioned operon and is highly upregulated under methoxydotrophic growth in M. shengliensis . This gene is not homologous to any known MT2 and rather relates to methyltransferase family PF02007: methyl-tetrahydromethanopterin (H 4 MPT):CoM methyltransferase (Mtr) subunit H (MtrH; 41% peptide similarity to that of Methanosarcina barkeri ) (Supplementary Fig. S1 ). Although MtrH (subgroup I) is part of the membrane-bound Mtr complex found in methanogens, the identified M. shengliensis MtrH homolog Amam_00021/BP07_RS03240 relates more to MtrH-related proteins (e.g., subgroup III) that do not form such a complex and are found in non-methanogenic archaea (e.g., Archaeoglobus fulgidus ) and methylotrophic bacteria Desulfitobacterium hafniense or Acetobacterium woodii [ 61 ] (i.e., organisms that neither synthesize nor utilize CoM). MtrH in Desulfitobacterium hafniense has been described as a methylcorrinoid:tetrahydrofolate methyltransferase [ 62 ]. As Amam_00021/BP07_RS03240 is upregulated together with the neighboring MtoC, MtoB1, and MtoB2 during ArOCH 3 metabolism, we hypothesize that the gene product serves as an CH 3 -(CoIII)-MtoC:H 4 MPT methyltransferase (Eq. 4 ), tentatively named MtoA. Together MtoAB(1/2)C might catalyze complete methyl transfer from ArOCH 3 to H 4 MPT (Eq. 5 ) and MtoD is a corresponding corrinoid activation protein required for sustained methyltransferase activity (Eq. 6 ): 4 \\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}$${\\mathrm{CH}}_3--{\\mathrm{Co}}({{\\mathrm{III}}})--{\\mathrm{MtoC}} \\, +\\, \t {\\mathrm{H}}_4{\\mathrm{MPT}}\\to {\\mathrm{CH}}_3--{\\mathrm{H}}_4{\\mathrm{MPT}} \\\\ +\\, \t {\\mathrm{Co}}( {\\mathrm{I}})--{\\mathrm{MtoC}}$$\\end{document} CH 3 Co ( III ) MtoC + H 4 MPT → CH 3 H 4 MPT + Co ( I ) MtoC 5 \\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}$${\\mathrm{ArOCH}}_3 + {\\mathrm{H}}_4{\\mathrm{MPT}} \\to {\\mathrm{ArOH}} + {\\mathrm{CH}}_3--{\\mathrm{H}}_4{\\mathrm{MPT}}$$\\end{document} ArOCH 3 + H 4 MPT → ArOH + CH 3 H 4 MPT 6 \\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}$${\\mathrm{Co}}( {{\\mathrm{II}}})--{\\mathrm{MtoC}} \\, +\\, \t {\\mathrm{ATP}} + {\\mathrm{H}}_2{\\mathrm{O}} + {\\mathrm{e}}^ - \\to {\\mathrm{Co}}( {\\mathrm{I}})--{\\mathrm{MtoC}} \\\\ +\\, \t {\\mathrm{ADP}} + {\\mathrm{P}}_{\\mathrm{i}}$$\\end{document} Co ( II ) MtoC + ATP + H 2 O + e − → Co ( I ) MtoC + ADP + P i Fig. 3 Demethylation and demethoxylation pathways in acetogenic bacteria and methanogenic archaea. a Demethylation and demethoxylation pathways as described for the acetogenic bacterium Moorella thermoacetica , modified from Pierce et al. [ 60 ]. b Demethylation and tentative demethoxylation pathways in methanogenic archaea. Co(I/III): oxidation state of the cobalamin carried by the cobalamin binding protein MtoC, H 4 MPT: tetrahydromethanopterin. To verify the function of the Mto proteins from M. shengliensis in O -demethylation and methyl transfer, we purified the Mto proteins and analyzed them by UV–vis spectroscopy and enzyme activity assays (Fig. 4 and Supplementary Fig. S2 ). Fig. 4 O -demethylation and methyl transfer conducted by Mto proteins. Reaction A: MtoD, ATP and titanium (III) citrate are required for activation of MtoC from the Co(II) state (blue) to the active Co(I) state (dark green). Reaction B: MtoB transfers the methyl group of the methoxy compound (Ar-O-CH 3 ) to Co(I)-MtoC resulting in methylated Co(III)-MtoC (red). The MtoB activities with 2-methoxybenzoate (MB) and TMB are shown in Fig. S2A . With methanol or trimethylamine as substrate no activity could be observed. Conversion of TMB to 3-OH-4,5-dimethoxybenzoate was confirmed by HPLC (Fig. S3 ). Reaction C: For measuring MtoA activity, the H 4 MPT structural analog H 4 F was used. We got strong evidence that MtoA transfers the methyl group from methylated Co(III)-MtoC (red) to H 4 F thereby producing Co(I)-MtoC (light green). The activity is shown in Fig. S2B . In M. shengliensis H 4 MPT and not H 4 F is most likely the methyl group acceptor as M. shengliensis does not have the genomic capacity to synthesize H 4 F. Also, the methyl-transfer reaction is not occurring if CoM is used instead of H 4 F (Fig. S2B ). All bottom panels correspond to UV/visible spectra measured after each reaction reflecting the different states of the cobalamin carried by MtoC. MtoC exhibits different UV–vis spectroscopic features depending on the oxidation state of its cobalamin cofactor. In the inactive Co(II) state, the UV–vis spectrum shows a peak at around 480 nm (Fig. 4 , before reaction A). The corrinoid activator MtoD can reactivate the Co(II) state of MtoC by reducing the cobalamin to the active Co(I) state with the use of ATP and titanium (III) citrate (Fig. 4 , reaction A). The active Co(I) state exhibits a peak at around 390 nm (gamma band). When MtoB and the methoxylated aromatic compound are added to the enzyme assay mixture the methyl group is transferred to the cobalamin (Fig. 4 , reaction B), as also shown by HPLC (Supplementary Fig. S3 ). The formation of methyl-Co(III) provokes the disappearance of the peak at 390 nm and the appearance of a new peak at 520 nm. The demethylation of MtoC by MtoA was observed when tetrahydrofolate (H 4 F), a C1-carrier analogous to H 4 MPT, was added (Fig. 4 , reaction C). This reaction can be followed by the decrease of absorbance at 520 nm and the increase of absorbance at 390 nm, which is explained by a switch back to the Co(I) state. As H 4 F instead of the native methyl acceptor H 4 MPT is used in the assay no specific activity value for MtoA could be accurately determined. By HPLC analysis of the methoxy compounds and their hydroxylated derivatives we observed that roughly 2.2% of the methoxy compound is converted (i.e., about 51 µM of the initial 2.3 mM TMB; Supplementary Fig. S3 ), which agrees with the concentration of the methyl-acceptor MtoC in the assay mixture (~55 µM). The MtoB activity with 2-methoxybenzoate (MB) was found to be 0.87 ± 0.04 µmol Co(III) formed per min and per mg of MtoB and with TMB 0.76 ± 0.04 µmol of Co(III) formed per min and per mg of MtoB (see also Supplementary Fig. S2A ). The specific activity values of the O -demethylase of Acetobacterium dehalogenans measured with vanillate and isovanillate are 0.43 and 0.65 µmol Co(III) formed per min and per mg MT1 respectively, for example [ 28 ]. With those experiments we showed that the O -demethylation and methyl transfer reaction are indeed catalyzed by the Mto proteins and that this system works in a similar way as shown for methoxydotrophic bacteria such as Moorella thermoacetica [ 46 ] or A. dehalogenans [ 28 ]. We could identify MtoB (WP_042685515.1) as the O -demethylase catalysing the methyl transfer from the methoxy compound to Co(I)-MtoC. After accepting the methyl group from MtoB, MtoC could not be demethylated by MtoA in the presence of HS-CoM, the conventional methyl-acceptor for methylotrophic methanogenenesis. On the other hand, MtoC demethylation by MtoA could be observed when the H 4 MPT structural analog H 4 F was present. Given that M. shengliensis can only synthesize H 4 MPT and not H 4 F (e.g., absence of bacterial dihydrofolate reductase), this gives us strong evidence that H 4 MPT, rather than HS-CoM, should accept the methyl group from CH 3 -Co(III)-MtoC in M. shengliensis . Such a H 4 MPT-dependent methyl transfer would be the first of its kind though, in some aspects, comparable to other pterin-dependent methyl activation pathways—H 4 MPT/H 4 F-dependent acetyl-CoA decarbonylation and H 4 F-dependent acetogenic methyl transfer pathway [ 63 ]. If the Methermicoccus methyltransferase system is indeed dependent on the archaeal equivalent of H 4 F, this may be because the archaeal ability to degrade methoxylated aromatic compounds likely originated in C1-metabolizing Firmicutes , based on the topology of the MtoB and MtoC phylogenetic trees (Fig. 1a, b ). The proposed transfer of the ArOCH 3 -derived methyl group to H 4 MPT rather than CoM would significantly influence the energetics of methanogenesis. Based on thermodynamic calculations we suggest the following hypotheses regarding the energy metabolism of methoxydotrophic methanogens: typical methylotrophic methanogenesis disproportionates CH 3 -S-CoM to ¼ CO 2 and ¾ CH 4 . In this pathway (4CH 3 X + 2H 2 O → CO 2 + 3CH 4 + 4HX), CH 3 -S-CoM oxidation to CO 2 requires an energy input (~2Na + transported in for transferring the methyl group from CoM to H 4 MPT; Fig. 5 ) but electron transfer from this oxidation to reduction of CH 3 -S-CoM to CH 4 allows energy recovery (~8H + transported out, assuming all F 420 H 2 is re-oxidized via Fpo-related Fd:methanophenazine (Mp) oxidoreductase (Fpl); Fig. 5 ). Assuming each H + /Na + transported across the membrane stores 20 kJ per mol, this yields a net energy gain of 120 kJ per four mol methyl substrate. If methoxydotrophic methanogenesis follows an analogous pathway with an entry point at CH 3 -H 4 MPT (CH 3 -H 4 MPT disproportionation to ¼ CO 2 and ¾ CH 4 ), oxidation of CH 3 -H 4 MPT to CO 2 would not incur any energetic cost, while reduction of CH 3 -H 4 MPT to CH 4 would generate energy (~6Na + transported out; Fig. 5 ). Combined with the energy gain from electron transfer (~8H + transported out), such metabolism would yield a net energy gain of 280 kJ per four mol methoxylated substrate. Based on such energetics, M. shengliensis methylotrophic and methoxydotrophic methanogenesis would, in theory, respectively reach roughly 40% and 94% thermodynamic efficiency (e.g., 40.0, 41.2, and 93.7% for MeOH [−299.7 kJ], monomethylamine [−291.0 kJ], and 2-methoxybenzoate [−298.9 kJ] correspondingly at 60 °C, pH 7, 0.2 atm CO 2 , 0.2 atm CH 4 , 1 mM NH 4 + , and 10 mM for all other compounds; see also Supplementary Table S3 ). However, most anaerobes work at efficiencies around 25–50% and efficiencies above 80% are highly improbable [ 64 ], suggesting that methoxydotrophic methanogenesis through such a pathway would be impossible. To operate at an energetic efficiency that organisms can physicochemically achieve, methoxydotrophic methanogenesis most likely takes an alternative route that recovers a lesser amount of energy. As an analogous phenomenon of trading off energy yield for thermodynamic driving force, one can look at glycolysis—compared to the Embden-Meyerhof-Parnas pathway, the Entner-Douduroff pathway sacrifices half of the ATP yield partly to minimize thermodynamic bottlenecks and prioritize thermodynamic feasibility [ 65 , 66 ] Fig. 5 Comparison of CH 3 -CoM- and hypothetical CH 3 -H 4 MPT-disproportionating methanogenesis based on (a) energetics and (b) expression. a Reactions and reaction directions unique to MeOH (green) or 2-methoxybenzoate (pink) decomposition are shown. Below are the estimated Gibbs free energy (∆G) and the predicted energy yield (in terms of H + /Na + extruded across the membrane, assuming the typical scheme of methylotrophic methanogenesis is followed) and thermodynamic efficiency of the shown methanogenesis pathways. ∆G was calculated assuming 60 °C, pH 7, 0.2 atm CO 2 , 0.2 atm CH 4 , 1 mM NH 4 + , and 10 mM for all other compounds. b Comparison of gene/protein expression of M. shengliensis grown on methoxylated aromatic compounds and methylated compounds. Yellow: genes/proteins for which both strains showed significantly increased expression during methoxydotrophic methanogenesis. Green: genes/proteins for which either (i) expression levels were not significantly different for both strains or (ii) consistent trends were not observed in both strains. Blue: genes/proteins for which both strains showed significantly decreased expression during methoxydotrophic methanogenesis. Arrows involving Fpl and HdrDE are dotted as Fpl was downregulated during methoxydotrophic methanogenesis and, with decreased Fpl activity, HdrDE’s activity would consequently decrease as well. H 4 MPT tetrahydromethanopterin, MF methanofuran. Supporting the possibility of an alternative route (i.e., not simple disproportionation to CO 2 and CH 4 ), we obtained evidence that methylotrophic and methoxydotrophic methanogenesis behave differently metabolically—while nearly all CH 4 (96.4%) produced from strain AmaM methylotrophic methanogenesis originated from the methylated substrate (as was also observed for Methanosarcina barkeri [98-99% CH 4 from methanol; [ 67 ]), CH 4 from strain AmaM methoxydotrophic methanogenesis originated from both the methoxylated substrate (2/3) and CO 2 (1/3) [ 6 ]. We also compared the growth of strain ZC-1 on TMB and MeOH and, in agreement, found that the former consumes more CO 2 for methanogenesis: in a qualitative experiment with [ 13 C] bicarbonate we found that ZC-1 cells grown on TMB produced roughly 10 times more [ 13 C]-CH 4 from [ 13 C]-bicarbonate-derived CO 2 than those grown on MeOH. Thus, both strains seem to display the same atypical behavior when degrading methoxylated compounds. Given that both strains lack genes for any alternative C 1 metabolism (e.g., aerobe-like aldehyde-based or anaerobic bacterial H 4 F-based metabolism), H 4 MPT-dependent C 1 metabolism is presumably responsible for running both CO 2 and CH 4 generation from ArOCH 3 as well as CH 4 generation from CO 2 . In search of a metabolic route that provides a rationale for this anomalous behavior and thermodynamic efficiency, we further compare the gene expression of M. shengliensis when degrading methylated compounds and ArOCH 3 to gain insight into how the pathways may differ regarding electron transport and energy recovery. During methylotrophic growth, AmaM and ZC-1 express the corresponding methyltransferase system and the complete methanogenesis pathway (i.e., CH 3 -S-CoM disproportionation to CO 2 and CH 4 ). To transfer electrons from the oxidative to reductive pathway, the two strains express two putative ferredoxin (Fd)-dependent F 420 :CoB-S-S-CoM oxidoreductases (HdrA1B1C1 or FrhBG-HdrA2B2C2; Eq. 7 ) [ 40 ], a putative Fpo-related Fd:methanophenazine (Mp) oxidoreductase (FplABCDHIJKLMNO; Eq. 8 ; see Supplementary Table S1 ) [ 68 , 69 ], and a Mp-oxidizing membrane-bound heterodisulfide reductase (HdrDE; Eq. 9 ). 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}$$2{\\mathrm{F}}_{420}{\\mathrm{H}}_2 \\, +\\, \t {\\mathrm{Fd}}_{{\\mathrm{ox}}} + {\\mathrm{CoM}}--{\\mathrm{S}}--{\\mathrm{S}}-- {\\mathrm{CoB}}\\\\ \t \\to 2{\\mathrm{F}}_{420} + {\\mathrm{Fd}}_{{\\mathrm{red}}}+ {\\mathrm{HS}}--{\\mathrm{CoM}} + {\\mathrm{HS}}--{\\mathrm{CoB}}$$\\end{document} 2 F 420 H 2 + Fd ox + CoM S S CoB → 2 F 420 + Fd red + HS CoM + HS CoB 8 \\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}$${\\mathrm{Fd}}_{{\\mathrm{red}}} + {\\mathrm{Mp}} + 4{\\mathrm{H}}_{{\\mathrm{in}}}^ + \\to {\\mathrm{Fd}}_{{\\mathrm{ox}}} + {\\mathrm{MpH}}_2 + 2{\\mathrm{H}}_{{\\mathrm{out}}}^ +$$\\end{document} Fd red + Mp + 4 H in + → Fd ox + MpH 2 + 2 H out + 9 \\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}$${\\mathrm{MpH}}_2 \t+ {\\mathrm{CoM}}--{\\mathrm{S}}--{\\mathrm{S}}--{\\mathrm{CoB}}+2{\\mathrm{H}}^+\\\\ \t\\to {\\mathrm{Mp}} + {\\mathrm{HS}}--{\\mathrm{CoM}} + {\\mathrm{HS}}--{\\mathrm{CoB}}+2{\\mathrm{H}}_{{\\mathrm{out}}}^ +$$\\end{document} MpH 2 + CoM S S CoB + 2 H + → Mp + HS CoM + HS CoB + 2 H out + Combined together, these complexes can facilitate complete electron transfer for CH 3 -S-CoM disproportionation (Eq. 7 + 2x Eq. 8 + 2x Eq. 9 ; Fig. 5 ). However, during methoxydotrophic growth, we observe significant decreases in the expression of Fpl compared to methylotrophy (Supplementary Table S1 ): 3.8–10.1 fold decrease for FplBIMN in AmaM transcriptomes ( p < 0.043) and 3.2 fold decrease for FplD in ZC-1 proteomes ( p = 0.0027). Although decreases in all Fpl subunits were not observed, the downregulated subunits play critical roles in the activity of the Fpl complex – FplBI and FplD are predicted to mediate Fd red oxidation [ 68 ] and interaction with the transmembrane subunits, respectively. Thus, both AmaM and ZC-1 might decrease electron transfer via Fpl and then would have to redirect intracellular electron flow through an alternative pathway. Interestingly, Fpl is central to energy generation from electron transfer (Eqs. 7 and 8 ), suggesting that M. shengliensis switches to an energy acquisition scheme distinct from that of methylotrophic methanogenesis. In other words, while methylotrophic methanogenesis gains energy purely from electron transfer (F 420 H 2 re-oxidation), methoxydotrophic methanogenesis may forgo such energy metabolism and rather gain energy from methyl transfer (CH 3 -H 4 MPT to CH 3 -S-CoM). Based on the annotatable genes for methanogenesis and energy metabolism expressed by M. shengliensis , the above electron transfer/energy acquisition scheme cannot accomplish complete electron transfer from CH 3 -H 4 MPT oxidation to CH 3 -H 4 MPT reduction (Fig. S4 ; see Supplementary Material “Electron transfer metabolism” including Figs. S5 and S6 ). There is a possibility that M. shengliensis possesses genes that encode a novel electron transfer metabolism, but, assuming that this is not the case, ArOCH 3 disproportionation would result in accumulation of reducing power distributed among multiple electron carriers (e.g., through activity of a ferredoxin:F 420 oxidoreductase and HdrABC). Given that methoxydotrophic methanogenesis was observed to reduce CO 2 to CH 4 , switching to CO 2 -reducing methanogenesis may allow cells to re-oxidize excess reducing power. Based on a thermokinetic model (see Supplementary Material; Fig. S7 ), cells could potentially passively alternate between oxidative (ArOCH 3 disproportionation) and reductive (CO 2 -reducing methanogenesis) metabolism as the cells respectively approach thermodynamic and kinetic limits through accumulation or consumption of cellular reducing power. Although not found in methanogens yet, such repeated intracellularly triggered reversals in metabolism (“metabolic oscillation” or “intracellular feedback loops”) involving fluctuation of reducing power (i.e., NADH) have been observed in various organisms, including Klebsiella sp . (succinate or glycerol metabolism) [ 70 , 71 ] and Saccharomyces cerevisiae (glucose) [ 72 ]. These oscillations occur on the scale of seconds to hours and concomitantly perform repeated cycles of production and consumption of metabolic end-products (e.g., CO 2 , H 2 , ethanol, or acetate) [ 71 , 73 ] and intermediates (e.g., ATP) [ 74 ]. The proposed theoretical oscillation between oxidative CO 2 -/CH 4 -liberating CH 3 -H 4 MPT disproportionation and CO 2 -reducing methanogenesis is in line with the predicted need for an alternative electron transfer route (i.e., forgoing energy gain via Fpl and Hdr) and concomitant CO 2 generation/consumption during methoxydotrophic methanogenesis, but certainly requires verification."
} | 9,636 |
25717324 | PMC4324140 | pmc | 1,388 | {
"abstract": "Microbial syntrophy is a vital metabolic interaction necessary for the complete oxidation of organic biomass to methane in all-anaerobic ecosystems. However, this process is thermodynamically constrained and represents an ecosystem-level metabolic bottleneck. To gain insight into the physiology of this process, a shotgun proteomics approach was used to quantify the protein landscape of the model syntrophic metabolizer, Syntrophomonas wolfei , grown axenically and syntrophically with Methanospirillum hungatei . Remarkably, the abundance of most proteins as represented by normalized spectral abundance factor (NSAF) value changed very little between the pure and coculture growth conditions. Among the most abundant proteins detected were GroEL and GroES chaperonins, a small heat shock protein, and proteins involved in electron transfer, beta-oxidation, and ATP synthesis. Several putative energy conservation enzyme systems that utilize NADH and ferredoxin were present. The abundance of an EtfAB2 and the membrane-bound iron-sulfur oxidoreductase (Swol_0698 gene product) delineated a potential conduit for electron transfer between acyl-CoA dehydrogenases and membrane redox carriers. Proteins detected only when S. wolfei was grown with M. hungatei included a zinc-dependent dehydrogenase with a GroES domain, whose gene is present in genomes in many organisms capable of syntrophy, and transcriptional regulators responsive to environmental stimuli or the physiological status of the cell. The proteomic analysis revealed an emphasis on macromolecular stability and energy metabolism by S. wolfei and presence of regulatory mechanisms responsive to external stimuli and cellular physiological status.",
"introduction": "Introduction The metabolic cooperation called syntrophy is a thermodynamically-based interaction between two or more microorganisms, which must rely on each other to maintain pool sizes of exchanged metabolites at sufficiently low concentrations so that the overall catabolic conversion is thermodynamically favorable (Schink and Stams, 2006 ; McInerney et al., 2008 ). Syntrophy is an essential intermediary step in the anaerobic degradation of natural polymers such as polysaccharides, proteins and lipids where syntrophic associations are needed to convert the products of fermentative microorganisms, fatty acids, alcohols and aromatic compounds, to methanogenic growth substrates acetate, H 2 and formate (McInerney et al., 2008 ; Stams and Plugge, 2009 ). Thus, syntrophic fatty acid metabolism accounts for much of the carbon flux and methane production in methanogenic environments (McInerney et al., 2008 ). Despite the ubiquity of syntrophy processes in anoxic environments, little is known about mechanisms by which syntrophic consortia regulate their metabolism. S. wolfei is a metabolic specialist that syntrophically metabolizes a very limited number of fatty acids from four to eight carbons in length to acetate, H 2 and formate (McInerney et al., 1979 , 1981 ; Beaty and McInerney, 1987 ). It can grow axenically on unsaturated fatty acids such as crotonate by oxidizing part of the molecule to acetate and reducing to remainder to the respective saturated fatty acid (Beaty and McInerney, 1987 ; Amos and McInerney, 1990 ). However, to oxidize saturated fatty acids, S. wolfei requires the presence of a suitable H 2 - and/or formate-consuming partner (i.e., a methanogen) to maintain H 2 and formate at sufficiently low levels so that saturated fatty acid degradation is thermodynamically favorable (Schink, 1997 ). This allows S. wolfei to reoxidize its reduced electron carriers by forming H 2 and formate rather than by using the unsaturated fatty acid as an electron acceptor. Thus, the interaction between S. wolfei and M. hungatei during growth on crotonate is beneficial to each species but not obligatory as when S. wolfei grows syntrophically with M. hungatei on butyrate. A critical physiological feature of S. wolfei during syntrophic growth on saturated fatty acids is the requirement for reverse electron transfer to produce H 2 (E′ of −261 mV at 1 Pa H 2 ) and formate (E′ of −258 mV at 1 μM formate) from electrons generated in the oxidation of acyl-CoA intermediates to their respective enoyl-CoA intermediates (E′ of −10 mV) (Sato et al., 1999 ). This redox reaction is energetically unfavorable (ΔE′ of ~ −250 mV) and requires energy input to drive the reaction forward. The use of inhibitors showed that a chemiosmotic gradient is required for hydrogen production from butyrate (Wallrabenstein and Schink, 1994 ). A reverse quinone loop involving a membrane-bound, electron transfer flavoprotein (EtfAB):menaquinone oxidoreductase and either a membrane-bound hydrogenase or formate dehydrogenase has been hypothesized to use the proton motive force to produce H 2 or formate, respectively, from electrons derived from the oxidation of butyryl-CoA (Schink, 1997 ; Sieber et al., 2012 ; Schmidt et al., 2013 ). The reverse quinone loop model for syntrophic reverse electron transfer is supported by the more than 100-fold higher expression of a membrane-bound hydrogenase, hyd2 (Sieber et al., 2014 ), and the presence of a membrane-bound formate dehydrogenase, Fdh2 (Schmidt et al., 2013 ) when S. wolfei is grown with M. hungatei on butyrate. In addition, a membrane-bound, iron-sulfur protein that may function as an EtfAB:menaquinone oxidoreductase and EtfAB2 were detected in the S. wolfei proteome (Schmidt et al., 2013 ). However, the genome of S. wolfei contains other possibilities for reverse electron transfer including the Fix system and a bifurcating, butyryl-CoA dehydrogenase (Bcd):EtfAB1 (Sieber et al., 2010 ). Unlike organisms capable of syntrophy such as sulfate and iron reducers, S. wolfei cannot use alternative electron acceptors for growth (Sieber et al., 2010 ). The limited metabolic potential of S. wolfei makes it an ideal model organism for identifying the essential machinery of syntrophy, but makes it difficult to use genetic approaches to identify syntrophic processes. The genomes of S. wolfei (Sieber et al., 2010 ) and M. hungatei (NCBI Reference Sequence: NC_007796) have been recently sequenced and annotated, which has opened the investigation of syntrophy to high-throughput analyses. Genomic analyses of S. wolfei revealed metabolic specialization and nutritional self-sufficiency consistent with its limited metabolic potential (Sieber et al., 2010 ). Thus, S. wolfei appears to be genetically “hard-wired” for syntrophy. As a metabolic specialist that survives on reactions close to thermodynamic equilibrium, we hypothesize that S. wolfei is physiologically adapted to fatty acid metabolism and hydrogen and/or formate production and the shift from axenic to syntrophic growth involves a limited number of enzyme systems rather than the large global changes in gene expression that have been detected with sulfate reducers (Meyer et al., 2013a , b ). In this study, we used whole cell proteomic analyses of S. wolfei grown alone and in coculture with M. hungatei grown axenically to identify the major metabolic systems used for axenic and syntrophic lifestyles.",
"discussion": "Results and discussion Proteomic overview of S. wolfei The repertoire of proteins involved in syntrophic and axenic growth of S. wolfei was characterized by growing S. wolfei in pure culture on crotonate and in coculture with M. hungatei on either crotonate or butyrate (Supplemental Figure 1 ). The genome of S. wolfei contains 2574 protein encoding genes (Sieber et al., 2010 ) and the proteomic analysis detected a total of 790 proteins among the three growth conditions. Of these, 106 are proteins without a known function (Supplemental Data Set 1 ). NMDS ordination using distance metrics that include presence/absence and abundance revealed protein abundance patterns between axenic and syntrophic growth conditions were highly reproducible among the replicates of a given growth condition (Figure 1 ). Only one technical replicate of a S. wolfei-M. hungatei coculture grown on crotonate differed from the other three and this was driven primarily by low protein recovery. Nonetheless, the ordination value of this replicate was much closer to those for the other crotonate-grown coculture replicates than to those of the other growth conditions. These results allowed us to evaluate the contributions of multiple hydrogenases, electron transfer flavoproteins (Etf), formate dehydrogenases and paralogous enzymes involved in fatty acid metabolism to axenic and syntrophic lifestyles. NMDS ordination analysis showed that the protein pattern of S. wolfei as represented by the NSAF was different when M. hungatei was present. Figure 1 Non-metric multidimensional scaling of the S. wolfei protein profiles obtained from each technical replicate for each duplicate culture grown under the three conditions . Symbols: green circle, S. wolfei pure culture on crotonate; pink circles, S. wolfei-M. hungatei coculture on crotonate; blue circles, S. wolfei-M. hungatei coculture on butyrate. The number of proteins detected between the three growth conditions is compared in Supplemental Figure 2 . Three hundred and ninety-one proteins were detected under all three conditions of which 113 appear to be constitutively present (i.e., less than 0.5-fold change among all conditions; Supplementary Table 1 ). Four open reading frames previously predicted to be pseudogenes (Swol_0818, Swol_1580, Swol_2335, and Swol_2574) were found to be protein encoding. Remarkably, the protein abundance, as represented by NSAF of most proteins changed very little between the pure and coculture growth conditions (Figure 2 ). Figure 2 Abundance of peptides detected from each condition mapped by genomic location . Proteins encoded by genes on the lagging strand are represented as negative abundance. Symbols: green circle, S. wolfei pure culture on crotonate; pink circles, S. wolfei-M. hungatei coculture on crotonate; blue circles, S. wolfei-M. hungatei coculture on butyrate. Highly abundant proteins during all growth conditions Highly abundant proteins were those involved in major pathways and processes within the cell. Nine proteins had an NSAF greater than 0.01 under all three growth conditions including two chaperonins (GroEL and GroES), one small heat shock protein (Swol_0588 gene product), two paralogs of the DNA-binding proteins HU, rubrerythrin (a protein employed during oxidative stress), two transcription factors, and the Swol_0133 gene product, annotated as a putative copper amine oxidase (Table 1 ). The Swol_0133 gene product is a predicted cytoplasmic protein although a role in cell envelope function was recently proposed (Schmidt et al., 2013 ). Other abundant proteins had annotated functions involved in beta-oxidation, electron transfer and energy production (Table 1 ). GroEL and GroES were among the most abundant proteins in Escherichia coli (See datasets in Lu et al., 2007 ; Mancuso et al., 2012 ). The types of abundant proteins detected emphasize the importance of macromolecular stability and energy metabolism to S. wolfei . Table 1 The most abundant peptides detected in each condition . Locus tag Gene description NSAF of peptides detected Crotonate Crotonate with M. hungatei Butyrate with M. hungatei Swol_0047 Transcriptional regulator, AbrB family 0.010 ± 0.002 0.011 ± 0.004 0.011 ± 0.001 Swol_0083 DNA-binding protein HU 0.008 ± 0.0004 0.011 ± 0.003 0.007 ± 0.002 Swol_0133 Copper amine oxidase 0.027 ± 0.002 0.042 ± 0.010 0.026 ± 0.003 Swol_0435 3-hydroxybutyryl-CoA dehydrogenase 0.026 ± 0.002 0.002 ± 0.000 0.006 ± 0.001 Swol_0436 Coenzyme A transferase 0.011 ± 0.0004 0.008 ± 0.002 0.005 ± 0.001 Swol_0588 Small heat shock protein 0.011 ± 0.001 0.015 ± 0.004 0.011 ± 0.002 Swol_0648 DNA-binding protein HU 0.009 ± 0.0003 0.012 ± 0.002 0.008 ± 0.001 Swol_0670 Rubrerythrin 0.008 ± 0.001 0.010 ± 0.003 0.006 ± 0.001 Swol_0696 Electron transfer flavoprotein β-subunit 0.022 ± 0.003 0.022 ± 0.005 0.010 ± 0.001 Swol_0697 Electron transfer flavoprotein α-subunit 0.016 ± 0.001 0.021 ± 0.004 0.009 ± 0.001 Swol_0767 Phosphate acetyltransferase 0.009 ± 0.0003 0.010 ± 0.001 0.008 ± 0.0003 Swol_0768 Acetate kinase 0.007 ± 0.001 0.013 ± 0.002 0.008 ± 0.001 Swol_1190 Molybdenum-pterin-binding protein 0.007 ± 0.001 0.011 ± 0.003 0.007 ± 0.001 Swol_1244 Polyhydroxyalkanoate synthesis regulator 0.001 ± 0.001 0.027 ± 0.003 0.023 ± 0.002 Swol_1727 Zn-dependent dehydrogenase ND 0.019 ± 0.004 0.028 ± 0.005 Swol_1855 60 kDa chaperonin GROEL 0.042 ± 0.001 0.027 ± 0.004 0.014 ± 0.001 Swol_1856 10 kDa chaperonin GROES 0.049 ± 0.004 0.031 ± 0.007 0.022 ± 0.003 Swol_2030 3-hydroxybutyryl-CoA dehydrogenase 0.021 ± 0.002 0.003 ± 0.001 0.005 ± 0.001 Swol_2051 Acetyl-CoA acetyltransferase 0.035 ± 0.001 0.010 ± 0.001 0.010 ± 0.0005 Swol_2148 Branched-chain amino acid aminotransferase 0.004 ± 0.001 0.006 ± 0.001 0.009 ± 0.002 Swol_2296 Hypothetical protein 0.005 ± 0.001 0.012 ± 0.001 0.010 ± 0.001 Swol_2382 Sodium-transporting two-sector ATPase 0.009 ± 0.0004 0.012 ± 0.002 0.008 ± 0.001 Swol_2386 F 0 F 1 -type ATP synthase subunit B 0.012 ± 0.001 0.010 ± 0.0004 0.009 ± 0.002 Abbreviation: ND, not detected . Beta-oxidation enzymes The abundance of beta-oxidation proteins reflect the metabolic specialization of S. wolfei as a bacterium that metabolizes short-chain, saturated and unsaturated fatty acids (Figure 3 ) (McInerney et al., 1979 ). Genomic analysis showed that S. wolfei 's genome contained multiple paralogs for each step in beta-oxidation (Sieber et al., 2010 ) and our whole-cell proteome analysis showed that S. wolfei expressed and translated multiple, paralogous, beta-oxidation enzymes. Seven acyl-CoA dehydrogenases were detected in the proteome (Figure 3 ; Supplemental Data Set 2 ). The Swol_2052 gene product was the most abundant acyl-CoA dehydrogenase and was detected in all growth conditions. Swol_2052 and Swol_1933 gene products were detected in the dominant Bcd activity purified from butyrate-grown S. wolfei cells (Müller et al., 2009 ) and subsequent proteomic analysis detected these two Bcds in crotonate-grown pure cultures and butyrate-grown cocultures of S. wolfei (Schmidt et al., 2013 ). Multiple CoA transferases, enoyl-CoA dehydratases, 3-hydroxyacyl-CoA dehydrogenases and acetyl-CoA acetyltransferases, whose abundance varied with growth condition, also were detected (Figure 3 ; Supplemental Data Set 2 ). Interestingly, gene products corresponding to a set of adjacent beta-oxidation genes and an acetate kinase (Swol_1483-1486) were not detected under any growth condition. A 3-hydroxybutyryl-CoA dehydrogenase (Swol_2030 gene product) was among the more abundant proteins detected, suggesting a specific role in oxidation/reduction when crotonate is metabolized in the absence of a suitable partner. Figure 3 Abundance of key enzymes of S. wolfei 's metabolism . Abundance represented in the sum of NSAF for enzymes in each category. Symbols: green circle, S. wolfei pure culture on crotonate; pink circles, S. wolfei-M. hungatei coculture on crotonate; blue circles, S. wolfei-M. hungatei coculture on butyrate. Interspecies electron transfer proteins Interspecies electron transfer is necessary for degradation of butyrate (Schink, 1997 ), and depending on the growth condition, S. wolfei can utilize either hydrogen (Sieber et al., 2014 ) or formate (Schmidt et al., 2013 ). The S. wolfei genome contains three hydrogenases and five formate dehydrogenases (Sieber et al., 2010 ). All three hydrogenases were detected in all growth conditions (Figure 3 ; Supplemental Data Set 2 ), suggesting the reoxidation of reduced electron carriers (NADH, reduced flavoproteins, and reduced ferredoxin) may involve different enzyme systems. The detected hydrogenases include the electron confurcating hydrogenase, Hyd1, which is predicted to use NADH and ferredoxin; a ferredoxin-dependent hydrogenase (Hyd3); and a membrane-bound hydrogenase (Hyd2), which may interact with the quinone pool. In contrast, the abundance of the four detected formate dehydrogenases was much lower than that of the hydrogenases (Figure 3 ; Supplemental Data Set 2 ). Hydrogenases were abundant in this study, but formate dehydrogenases were abundant when S. wolfei was grown under different growth conditions (Schmidt et al., 2013 ; Sieber et al., 2014 ), suggesting that relative importance of interspecies hydrogen vs. formate transfer depends on growth condition. Proteins necessary for reverse electron transfer Swol_0697 and Swol_0696 gene products, which comprise the Etf complex EtfAB2, were among the most abundant proteins in the proteome in all growth conditions (Table 1 ; Figure 3 ), consistent with previous proteomic work (Schmidt et al., 2013 ). Adjacent to Swol_0696 and Swol_0697 is a gene for a membrane-bound FeS oxidoreductase (Swol_0698), which is postulated to be an EtfAB:menaquinone oxidoreductase (Sieber et al., 2012 ). The Swol_0698 gene product was highly abundant in under all growth conditions (Figure 3 , Schmidt et al., 2013 ). This protein was present in highly purified, Bcd preparations from butyrate-grown, S. wolfei cells (Müller et al., 2009 ; Schmidt et al., 2013 ). Swol_0696-Swol_0698 gene products likely form a complex that functions to reduce menaquinone with electrons derived from acyl-CoA intermediates when S. wolfei grows on butyrate. Proteomic analysis detected additional protein systems that could function in reverse electron transfer but these were less abundant than Swol_0696-Swol_0698 gene products (Figure 3 ). The Fix complex consists of FixAB, which is the EtfAB3 complex (Swol_2121 and Swol_2122 gene products), FixX, a ferredoxin (Swol_2123 gene product) and FixC, an Etf:quinone oxidoreductase (Swol_2124 gene product). The Fix proteins were ten-fold less abundant than the Swol_0696-Swol_0698 gene products under all growth conditions, suggesting that Fix may not function as a major catabolic system. However, it could function to supply reduced ferredoxin for biosynthetic processes, e.g., pyruvate synthesis from acetyl-CoA and CO 2 or hydrogen or formate production by confurcating hydrogenases and formate dehydrogenases (Figure 3 ). A heterodisulfide reductase (Hdr) was also detected in the proteome. In hydrogenotrophic methanogens, this enzyme couples the unfavorable reduction of ferredoxin with electrons from hydrogen or formate to the favorable reduction of CoM-S-S-CoB heterodisulfide with electrons derived from hydrogen or formate (Costa et al., 2010 ; Kaster et al., 2011 ). We also detected proteins (Swol_0400 and Swol_402 gene products) encoded by the genes adjacent to hdrABC . The Swol_0402 gene product annotates as a FAD and NAD + -binding oxidoreductase while the Swol_0400 gene product annotates as an iron-sulfur protein. Lastly, Swol_0266-Swol_0268 gene products could function as an electron bifurcating BcdEtfAB1 complex to produce reduced ferredoxin from crotonyl-CoA and NADH (Li et al., 2008 ). Key proteins needed for ATP synthesis were also abundant in all growth conditions (Figure 3 ; Table 1 ). Given that S. wolfei lacks respiratory systems to create a proton motive force (Sieber et al., 2012 ), we suggest that the ATP synthase (Swol_2381-Swol_2388) most likely functions to hydrolyze ATP to create the proton motive force. Identification of proteins exclusive to interspecies interactions We identified 15 S. wolfei proteins unique to interspecies interactions with M. hungatei (Supplemental Table 2 ; Supplemental Figure 2 ). The genes for these proteins are distributed throughout the chromosome and are not co-localized or within a genomic island. A putative zinc-dependent dehydrogenase (Swol_1727 gene product) was among the most abundant proteins detected (NSAF > 0.02) when S . wolfei was grown with M. hungatei on either crotonate or butyrate (Table 1 ; Figure 2 ). The high abundance of this gene product is surprising because S. wolfei is not known to degrade or produce alcohols (McInerney et al., 1979 ). Interestingly, Swol_1727 contains a GroES chaperonin domain and its deduced amino acid sequence is very similar (BLAST E-value of 5e-104) to that of SYN_01269 found in another syntrophic metabolizer, Syntrophus aciditrophicus (McInerney et al., 2007 ). Swol_1727 orthologs are also found in other sequenced syntrophic metabolizers, regardless of phylogenetic lineage, including Syntrophobacter fumaroxidans, Pelotomaculum thermopropionicum, Syntrophothermus lipocalidus , and Syntrophobotulus glycolicus . The abundance of the Swol_1727 gene product in the proteome of S. wolfei when grown with M. hungatei and the occurrence of closely related genes in genomes of organisms known to be capable of syntrophic metabolism suggests that it has an important function in syntrophy. Analysis of the other 14 proteins exclusive to interspecies interactions did not reveal any feature suggestive of unique interspecies interactions (Supplemental Table 2 ). Two proteins have annotated functions in beta-oxidation (Swol_1935 and Swol_1936 gene products) and one has an annotated function in poly-(3-hydroxyalkanoate) synthesis [poly-(3-hydroxyalkanoic acid) synthase, Swol_1241 gene product]. Two proteins with unknown function (Swol_1036 and Swol_2364 gene products) were detected. Swol_1036 has a nucleotidyltransferase domain and Swol_2364 has a nucleoside triphosphate pyrophosphohydrolase domain, suggesting housekeeping functions. Other proteins detected have predicted functions in cell biosynthesis (Swol_0643, Swol_0965, Swol_0975, Swol_1727, Swol_1958, and Swol_1851 gene products), energy production (Swol_1030 gene product) and replication (Swol_0001 and Swol_0002 gene products). Eighty-three S. wolfei proteins were unique to the syntrophic growth on butyrate where the activity of M. hungatei is obligatory (Supplemental Figure 2 ; Supplemental Table 3 ). The function of 33 of these proteins is unknown (Supplemental Table 3 ). Of the proteins detected only in butyrate-grown S. wolfei, four are encoded by genes with CRISPR-associated functions [Swol_2519 (CRISPR-associated protein, Cas5), Swol_2524 (DUF324 domain-containing protein), Swol_2525 (unknown function) and Swol_2529 (DUF1887 domain-containing protein)] and their genes are located with other CRISPR-associated genes and an adjacent intergenic CRISPR region. The detection of other CRISPR-associated proteins (Swol_2520 and Swol_2522 gene products) in pure culture S. wolfei cells grown on crotonate shows that CRISPR function is not unique to syntrophic growth. Seven putative transcriptional regulatory proteins were detected only in butyrate-grown S. wolfei cells. The function for many of these is unknown, but they likely serve important roles in modulating the physiological responses of S. wolfei required for syntrophic growth. The Swol_1040 gene product is signal transduction histidine kinase that contains domains similar to those of an Fe-only hydrogenase and a ferredoxin. The Swol_1040 may be part of a two-component regulator involved in the regulation of hydrogen production. Swol_0456 gene product is one of three paralogous proteins in S. wolfei that has PAS, sigma-54 and DNA-binding domains. PAS domains function as signal input modules in proteins that sense environmental stimuli by detecting changes in the electron transport system (Taylor and Zhulin, 1999 ). The Swol_1645 gene product is a redox sensitive transcriptional regulator, which in other organisms modulates transcription in response to shifts in the NADH/NAD + ratio (Brekasis and Paget, 2003 ; Gyan et al., 2006 ). Five receiver only domain proteins were also identified. The detection of these regulatory proteins suggests the importance of sensing environmental and physiological signals during interspecies interactions. Other proteins detected only in butyrate-grown cells included proteins involved in amino acid metabolism and transport, lipid metabolism and transport, nucleotide metabolism and transport and cofactor transport and metabolism (Supplemental Table 3 ). The number of peptides assigned to proteins involved in amino acid metabolism and transport based on COG functional classification was higher in butyrate-grown, coculture S. wolfei cells than crotonate-grown, pure culture S. wolfei cells (Supplemental Figure 3 ). The importance of biosynthetic capability in slow growing syntrophic coculture was unexpected. Interestingly the up-regulation of genes involved in amino acid synthesis has been detected in cocultures of termite gut spirochetes (Rosenthal et al., 2011 ) and in syntrophically grown P. thermopropionicum (Kato et al., 2009 ) by transcriptional analysis. Previous work has shown that PHA production and utilization is an important intracellular process in S. wolfei (Amos and McInerney, 1989 ). This conclusion is supported by protein abundance patterns reported here. PhaR (Swol_1244 gene product), poly-(3-hydroxyalkanoic acid) synthase (Swol_1241 gene product) and an acyl-CoA dehydratase (Swol_1242 gene product) were more abundant during growth with M. hungatei . PHA-associated enzymes, enoyl-CoA hydratases (Swol_0487 gene product) and acetoacetyl-CoA reductase (Swol_0651 gene product), were detected only in butyrate-grown cells (Supplemental Table 3 ). Nine proteins unique to S. wolfei-M. hungatei coculture growth on crotonate were detected (Supplemental Table 4 ). Here, the presence of M. hungatei is not obligatory for crotonate metabolism by S. wolfei . The proteins found exclusively during coculture growth on crotonate include a transcriptional regulator with a HD-GYP domain, which may function as a phosphodiesterase to control cyclic nucleotide levels (Marinez et al., 2002 ), a putative NAD(P)H-flavin oxidoreductase function (Swol_1523 gene product), and three proteins with unknown functions (Supplemental Table 3 ). This extensive proteomic analysis defines the physiological response of S. wolfei to the syntrophic lifestyle. NMDS analysis showed that S. wolfei adjusted its physiology in response to the methanogen. An uncharacterized, membrane-bound iron-sulfur oxidoreductase and EtfAB2 were abundant under all growth conditions and may provide the conduit for electron transfer between Bcd and the menaquinone pool. Reoxidation of menaquinol by a membrane-bound hydrogenase (Hyd2) provides a mechanism for the reverse electron transfer of electrons derived from butyryl-CoA oxidation to hydrogen using the proton motive force (Figure 3 ). Hydrogenases were abundant in this study, but formate dehydrogenases were abundant when S. wolfei is grown under different growth conditions (Schmidt et al., 2013 ; Sieber et al., 2014 ), suggesting that relative importance of interspecies hydrogen vs. formate transfer depends on growth condition. A GroES domain-containing, zinc-dependent dehydrogenase (Swol_1727 gene product) and several transcriptional regulators, responsive to environmental stimuli or cellular physiological status, were detected when S. wolfei was grown the M. hungatei . Overall, the proteomic analysis revealed an emphasis energy metabolism and macromolecular stability by the metabolic specialist, S. wolfei , and the involvement of regulatory proteins responsive to environmental and physiological signals during interspecies interactions. Conflict of interest statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest."
} | 6,947 |
22553907 | null | s2 | 1,390 | {
"abstract": "Microbial communities exhibit exquisitely complex structure. Many aspects of this complexity, from the number of species to the total number of interactions, are currently very difficult to examine directly. However, extraordinary efforts are being made to make these systems accessible to scientific investigation. While recent advances in high-throughput sequencing technologies have improved accessibility to the taxonomic and functional diversity of complex communities, monitoring the dynamics of these systems over time and space - using appropriate experimental design - is still expensive. Fortunately, modeling can be used as a lens to focus low-resolution observations of community dynamics to enable mathematical abstractions of functional and taxonomic dynamics across space and time. Here, we review the approaches for modeling bacterial diversity at both the very large and the very small scales at which microbial systems interact with their environments. We show that modeling can help to connect biogeochemical processes to specific microbial metabolic pathways."
} | 269 |
38356583 | PMC10864967 | pmc | 1,391 | {
"abstract": "Red calcified non-geniculate coralline algae (NGCA) provide habitat structures, stabilize reef structures, and foster coral larval settlement and metamorphosis. Moreover, the microbes associated with NGCA are dependent on the NGCA host species and are affected by environmental factors; however, little is known about the influence of reef conditions and depth gradients on the associated microbial communities and NGCA. In this study, we collected NGCA under different reef conditions and depth gradients and characterized the microbial communities using the V3–V4 hypervariable regions of the 16S rRNA gene. Metagenomic analysis revealed 2 domains, 51 phyla, 123 classes, and 210 genera. The NGCA-associated bacterial communities were dominated by Proteobacteria, Bacteroidetes, Chloroflexi, Actinobacteria, and Acidobacteriota. Gammaproteobacteria and Alphaproteobacteria were the most abundant bacterial classes. Differences in microbial diversity and richness were not apparent between reef conditions and depth gradients. However, there was a significant difference in bacterial evenness among the depth gradients. The bacterial abundance associated with NGCA was greater in deep zones than in shallow zones. The shallow zone exhibited a greater relative abundance of all gene functions than the deep zone, indicating differences in the distribution of gene functions. This study showed that the microbial communities associated with red calcified NGCA are diverse, and that the depth gradient affects their abundance and evenness, highlighting the need for further research to understand the functional roles of these microbial communities in coral reef conservation.",
"conclusion": "5 Conclusion This study provided information on the diversity and abundance of bacteria associated with NGCA in Thai waters under different coral reef conditions and depth gradients. The V3–V4 hypervariable regions of the 16S rRNA gene were used as a marker for bacterial identification and classification. The core microbiomes Gammaproteobacteria and Alphaproteobacteria, and Bacteroidetes were the most abundant at all sites. Bacterial diversity and richness were not significantly different among the reef conditions and depth gradients; however, there was a significant difference in bacterial evenness between the depth gradients. Given that the shallower reef area often encountered higher human and environmental disturbance, we found that bacterial relative abundance associated with NGCA was greater in the deep zone than in the shallow zone, and relative abundance in the degraded reef was slightly higher than in the fair reef. Important coral and fish pathogens Francisella , Halarcobacter , Malaciobacter , Tenacibaculum maritimum , and Vibrio ponticus , were identified in this study. Based on our observations, it appears that the sensitivity of NGCA-associated bacterial diversity to the environment makes them a promising ecological indicator for monitoring reef condition.",
"introduction": "1 Introduction Non-geniculate coralline red algae (NGCA) are important ecosystem engineers, reef builders, and carbon sequestrators [ 1 , 2 ]. Non-geniculate coralline red algae can create and provide habitats and settlement substrata for diverse marine organisms and host a variety of microbial assemblages [ 3 ]. They can foster the recruitment, settlement, and metamorphosis of the larval stages of numerous invertebrates, such as corals, economically important molluscs, abalone, echinoderms, and sponges, through chemical cues and bacterial biofilms that accumulate on the surface of NGCA [ [3] , [4] , [5] ]. Currently, NGCA abundance and community structure are influenced by environmental changes and stress, such as climate change, ocean acidification, bleaching, sedimentation, light, and nutrient enrichment [ [6] , [7] , [8] , [9] ]. These environmental variables can decrease algal growth, calcification, and cover [ 10 ]. Consequently, the loss of NGCA habitats can affect the settlement and metamorphosis of many larval stages of flora and fauna, as well as trigger shifts in the microbial composition and abundance [ 7 ]. Although NGCA has been reported to be an important habitat for corals, invertebrates, and bacteria, little is known about the abundance, community structure, and diversity of the microbial communities associated with NGCA. More recently, a few studies have investigated the relationship between crustose coralline algae and -microbial communities in terms of biomineralization and metamorphosis [ 11 ]. Alga-microbial communities are species-specific and dynamic in response to environmental changes and stress [ 2 , 3 , 7 ]. The relative abundances of microbial communities are affected by salinity, light intensity, water temperature, nutrient concentration, depth, habitat type, and algal health statuses [ 2 , 7 , [12] , [13] , [14] , [15] , [16] , [17] , [18] ]. Evaluating different habitats and depth gradients, depth is reported as an important factor driving changes in the bacterial composition [ 19 ] related to nutrient availability and sedimentation rates [ 20 ]. Coral reef degradation, coral bleaching, and coralline algal bleaching commonly occur under the influence of climate change and anthropogenic stresses, which can affect microbial communities [ 21 , 22 ]. Yang et al. [ 2 ] found that Alphaproteobacteria , Gammaproteobacteria , and Bacteroidetes were the most dominant phyla, and that the bacterial composition was similar between healthy and bleached crustose coralline alga, Porolithon onkodes . However, they found differences in the relative abundances among algal health conditions. Similarly, the bacterial compositions in healthy and bleached corals were not significantly different [ 23 ]. Nevertheless, few studies have been conducted on how depth and reef conditions (degraded vs . fair reefs) influence the microbial communities associated with NGCA and how these communities shift in response to environmental changes. The aim of the present study was to examine the diversity of microbial communities associated with NGCA under different coral reef conditions and depth gradients using next-generation sequencing of the V3–V4 hypervariable regions of the 16S rRNA gene. The results of this study are expected to contribute to our understanding of shifts in microbial communities between different coral reef conditions and depth gradients. Additionally, providing information on beneficial bacterial NGCA that can aid in coral settlement may help bolster the resilience of coral reefs.",
"discussion": "4 Discussion The composition of the microbial community associated with NGCA in Thai waters was assessed. Our study shows that, as markers for species-level microbial classification, the V3–V4 hypervariable regions of the 16S rRNA gene have potential, similar to that reported in previous studies [ 2 , 34 , 35 ]. In the present study, the Archaea domain was found to have a relative abundance of less than 2 % in the subtidal reef. Low abundance of the phylum Archaea is found in coral reefs, but this is usually the case in polluted marine environments [ 36 ]. A total of 51 bacterial phyla were recorded, of which Proteobacteria was the core member, as previously reported by Nimnoi and Pongsilp [ 37 ] and Saipan et al. [ 38 ] who studied bacterial communities in seawater in the upper Gulf of Thailand and Koh Tachai in the Andaman Sea. Proteobacteria is commonly suggested to be a dominant bacterial phylum associated with the coral Porites lutea Quoy & Gaimard, 1833 [ 39 ] and NGCA Neogoniolithon sp [ 40 ]. Gammaproteobacteria and Alphaproteobacteria were highly abundant in the reefs. Members of Gammaproteobacteria and Alphaproteobacteria are widely distributed in marine ecosystems and can metabolize organic compounds and nutrients [ 41 ]. These results are consistent with those of previous studies [ 19 , [37] , [38] , [39] , 42 ]. For example, the globally prominent Gammaproteobacteria genera Woeseia and KI89A play important ecological roles in biogeochemical cycling in marine sediment environments [ 43 ]. The three coral probiotic genera, Acinetobacter , Endozoicomonas (phylum Gammaproteobacteria), and Ruegeria (phylum Alphaproteobacteria), contribute to carbon fixation, sulfate reduction, and nutrient translocation within their host. Photosymbionts can produce DMSP and various breakdown products (e.g., DMS, acrylate, and methanesulfonic acid) performing a protective function against heat or oxidative stress on the host surface [ 44 ]. Therefore, these bioactive compounds may prevent bleaching and pathogenic invasion of corals [ 45 ]. The present study suggests that three beneficial bacteria, Acinetobacter , Endozoicomonas , and Ruegeria , are associated with NGCA, possibly supporting host metabolism. Gammaproteobacteria, Alphaproteobacteria, and Actinobacteria are the most dominant classes of the four crustose coralline algal species in the Caribbean Sea [ 3 ]. In the sea southwest of the United Kingdom, Brodie et al. [ 13 ] found the highest abundances of Gammaproteobacteria, Alphaproteobacteria, Flavobacteria, and Bacteroidetes on the surface of the geniculated coralline algae, Corallina officinalis Linnaeus, 1758. However, they found differences in bacterial communities at different sites and depths. In the present study, we found that diversity relative abundance of dominant NGCA-associated bacteria was not significantly different between fair and degraded coral reefs. Among these dominant bacteria, Alphaproteobacteria, Gammaproteobacteria and Bacteroidetes were the most abundant bacteria at all sites, indicating the core microbiome in our NGCA samples regardless of reef conditions. Yang et al. [ 2 ] found that Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes were the dominant phyla and their relative abundances differ among bleached, semi-bleached, and healthy coralline algae ( P . onkodes ). Thus, we hypothesized that the health status of NGCA plays more important role than surrounding reef conditions on the NGCA-associated bacterial relative abundance. Alternatively, other unexamined abiotic factors play more important role in shaping their relative abundance than reef conditions. We envisage that further expanding experiments would shed light into this aspect. In our study, we found the coral pathogenic bacteria Francisella , Malaciobacter , Halarcobacter , and Vibrio in the surveyed reefs. These genera are typically found in degraded coral reefs [ 46 , 47 ]. At our study site, the deterioration in reef areas is caused by careless tourism (use of mooring buoys by tourist boats and stepping on living corals), canal excavation, and local fisheries. These factors can result in coral mortality, bleaching, disease, decreased NGCA, and proliferation of fleshy macroalgae, leading to changes in bacterial communities and abundance [ [48] , [49] , [50] ]. The dead or diseased coral colony and other benthic macroalgae could then serve and host different compositions of the microbial community [ [51] , [52] , [53] ], which might explain why major marine pathogens occasionally appear in degraded reefs. In the present study, there was a significant difference in the microbial-NGCA communities between the depth gradients. Bacterial abundance was higher in deep zones than in shallow zones. This finding was consistent with the higher percentage cover of NGCA in the deep zones. A greater coralline algal surface area and structural complexity provide more opportunities for microbial colonization [ 54 ]. In the present study, we found a high abundance of different marine pathogens such as Francisella sp., Tenacibaculum maritimum , Malaciobacter sp., and Vibrio ponticus in the deep zone. In addition, the filamentous bacterium Aureispira sp. was abundant in the samples. This bacterium suppresses the growth of Vibrio by inhibiting calcium ion uptake [ 55 , 56 ]. A beneficial Aureispira species may support the recruitment of young corals that grow over NGCA colonies. In addition, the coral metamorphosis-inducing bacterium Pseudoalteromonas luteoviolacea possesses antimicrobial enzyme activity that destroys other coral pathogens, especially Vibrio spp [ 57 ]. The probiotics Aureispira and Pseudoalteromonas were only present in the deep zone of the fair reef, and one year later (February 2022), we found that young coral settlement occurred above the NGCA in the deep zone of this study site. Therefore, these two bacteria may be suggested as biological indicators for assessing the suitable coral-NGCA health for future coral restoration. Moreover, the importance of DMSP-degrading bacteria could positively affect the high abundance of other microorganisms associated with NGCA in the deep zone. Dimethylsulfoniopropionate-demethylating bacteria (family Rhodobacteraceae) such as Albidovulum, Labrenzia , and Photobacterium vary with depth. The breakdown of DMSP supports coral-NGCA growth by increasing the availability of carbon and sulfur. The antibacterial compound of the DMSP production pathway inhibits coral pathogens and contributes to the control of microbial communities associated with corals [ 44 ] and NGCA. Previous studies have reported that microbial abundance is affected by environmental factors such as seawater temperature, light intensity, turbidity, nutrient levels, and habitat [ 13 , 16 , [58] , [59] , [60] , [61] ]. Depth gradients are related to other local factors such as light intensity, organic matter concentration, and nutrient availability [ 20 ]. In the present study, the suspended matter content was high in the shallow zone, which could be an indirect factor driving the bacteria-NGCA community. We found that the bacterial decomposers in the phylum Bacteroidetes, such as WCHB1-81, Lewinella, Portibacter , and Rubidimonas , generally occurred when total organic matter was high in the shallow zone. The several organic matter–degrading bacteria such as SAR202, Geothermobacter, Weissella, Paenibacillus, BD2-11 terrestrial group , and Phycisphaera showed considerably high abundances in the deep zone under conditions of low sedimentation. Different organic matter concentrations can provide particular growth in various bacterial communities [ 62 ]. In a study conducted on the Great Barrier Reef in Australia, Hernandez-Agreda et al. [ 14 ] suggested that the bacteria associated with the coral community increased in diversity with depth, probably because increased exposure to water currents in deep reefs allowed for greater acquisition of nutrients by the bacterial community. Román et al. [ 17 ] also reported that the proportion and occurrence of microbial communities on the deep-sea floor were high because of the nutrient enrichment that occurs from coastal depths to deep waters and the pelagic productivity that modulates food availability in the deep microbial biosphere. According to the metagenomic functional content prediction from the 16S rRNA gene, highly abundant functions in the shallow-water environment, especially in cellular processes, environmental information processing, genetic information processing, and metabolism, are probably related to diverse autotrophic and heterotrophic microorganisms. The majority of transporter pathways enabled strong biological productivity and biogeochemical heterogeneity, consistent with the observations reported by Pop Ristova et al. [ 63 ]. Upward microbial process activity in shallow areas results in high environmental and genetic expression patterns. However, to predict the functional potential of a reef ecosystem, a long-term investigation into the impact of seasonal variability on bacterial communities and description of the different associations between the functional groups of bacteria and NGCA species is necessary. Thus, our study showed that the increased bacterial composition in the deep zone of the subtidal reef was correlated with NGCA cover, which increased when the algal cover and surface area increased and was related to changing environmental factors across the depth gradient. However, the effects of major environmental factors on the NGCA-bacterial community association require long-term monitoring and more replication in other areas with the same experimental design. Future work should investigate responses to extreme environmental stresses in the process of bacterial-NGCA association. Additionally, the functional roles of NGCA-microbial interactions should be investigated. The current investigation contributes to a better understanding of the interactive effects of environmental factors on NGCA-microbial communities, reef acclimatization, and resilience."
} | 4,177 |
31964899 | PMC6972901 | pmc | 1,392 | {
"abstract": "Smart surfaces in nature have been extensively studied to identify their hierarchical structures in micro-/nanoscale to elucidate their superhydrophobicity with varying water adhesion. However, mimicking hybrid features in multiscale requires complex, multi-step processes. Here, we proposed a one-step process for the fabrication of hierarchical structures composed in micro-/nanoscales for superhydrophobic surfaces with tunable water adhesion. Hierarchical patterns were fabricated using a plasma-based selective etching process assisted by a dual scale etching mask. As the metallic mesh is placed above the substrate, it serves the role of dual scale etching masks on the substrate: microscale masks to form the micro-wall network and nanoscale masks to form high-aspect-ratio nanostructures. The micro-walls and nanostructures can be selectively hybridized by adjusting the gap distance between the mesh and the target surface: single nanostructures on a large area for a larger gap distance and hybrid/hierarchical structures with nanostructures nested on micro-walls for a shorter gap distance. The hierarchically nanostructured surface shows superhydrophobicity with low water adhesion, while the hybrid structured surface becomes become superhydrophobic with high adhesion. These water adhesion tunable surfaces were explored for water transport and evaporation. Additionally, we demonstrated a robust superhydrophobic surface with anti-reflectance over a large area.",
"introduction": "Introduction Hierarchical structures appearing in nature with various special functions have recently been investigated, such as lotus leaf’s superhydrophobicity 1 – 3 , Fish scale’s underwater superoleophobicity 4 , 5 , moth eye’s anti-reflectivity 1 , 6 , 7 , gecko toes’ dry adhesion, and butterfly wing’s photonic crystals 8 . These functionalities are expressed by the constituents of the chemical substance as well as the multiscale structures from the molecular level to the macro-structure on the surface harnessed for their living environment 9 – 11 . In particular, the superhydrophobic surfaces with water contact angle (CA) exceeding 150° are present in nature, such as lotus leaf, rose petal, and peanut leaf 11 – 16 . They have hierarchical or hybrid structures in micro-/nanoscale to enhance the high static water CA, while the surface adhesions to water are diverse to allow for it to adjust to its surrounding environment; lotus leaf has low water adhesion and high mobility of water droplet, thus leading to a self-cleaning property, while peanut leaf and rose petal have a high adhesion and low mobility to water, which are beneficial for water harvesting or evaporation control 17 , 18 . The water adhesion of these superhydrophobic surfaces has been reported to depend on the shape and scale of the three-phase contact line (TCL), which is composed of water/solid/air. Research has revealed that, as the TCL becomes discontinuous by lowering the contact area due to micro or nanoscale features and the scale of individual TCL becomes smaller, the air-pocket between the structures becomes stable, decreasing the water adhesion 19 , 20 . Conversely, certain surfaces form the high water adhesion, even at high CAs, with water penetrating through the surface cavities to increase the contact area, ultimately resulting in the formation of the continuous TCL 18 , 21 – 23 . These findings underscore the importance of appropriately selecting the required structure and its smart combination, such as the hierarchical or hybridized structures, to control the adhesion of the superhydrophobic surfaces. To date, various methods such as spray coating 24 , femtosecond laser 25 , electrospinning 26 , and electrodeposition 27 have been used to fabricate well-defined micro/nanostructures on the desired surfaces with tunable adhesion. However, most of these methods require multiple-step procedures to mimic nature’s smart architecture in multiscale from nano to macro or its hybridization. Also, previous approaches have a limitation on realizing large-area surface patterning with high uniformity. Recently, a plasma-based selective etching method has been used to fabricate superhydrophobic surfaces with high-aspect-ratio nanostructures 28 – 30 . The nanostructures could be fabricated on carbon- or silicon-based materials via selective plasma etching with the metal co-deposition, and the morphology of the nanostructure could be tuned through plasma parameters such as the gas mixing ratio, chamber pressure, treatment duration, or co-deposited metal species 31 . In the primary mechanism of nanofabrication through selective ion etching, metal atoms sputtered from the cathode plate are co-deposited on the target substrate. These metal atoms can aggregate and form clusters on the substrate, forming a region with high etch resistance and low reactivity to the plasma. However, other regions exposed to plasma can be etched at a high etch rate. This anisotropic or preferential etching leads to the formation of nanostructure with high-aspect-ratio on the substrate during the continuous plasma etch with reactive gases such as O 2 , CF 4 , and SF 6 29 . This template-less method is a time-saving and eco-friendly process for the large-scale fabrication of nanostructures with tunable structural shapes such as dot, pillar, or hairy 32 , 33 . However, there are some limits to applying this method in large-scale fabrication, as the formation of the etching mask from the supply of the co-deposited metal atoms may not be uniform over a large surface area. In addition to that, as the etch mask size governed by the co-deposited metal atoms or its clusters is within a few tens of nanometers, the etched features are only formed in nanoscale, so the fabrication of patterns in micro/macroscale or hybridized micro/nano-scale is necessary for the additional complex processes such as wet etching or soft lithography 34 . Here, we proposed a one-step process for the fabrication of hierarchical structured superhydrophobic surfaces with tunable water adhesion through the plasma-based selective ion etching assisted by the dual-scale etching mask. By placing the metallic mesh with wire diameters and spaces in a few hundreds of micrometers directly above the polymeric substrate, the dual-scale etching masking effect was realized by controlling the gap distance between the substrate and metallic mesh. In the single-step process, under plasma exposure in a glow discharge of oxygen gas, the metallic mesh serves as two characteristic etching masks on the substrate: a microscale etching mask to form a micro-wall network by creating a plasma shadow zone on the substrate (Fig. 1a ) and a nanoscale etching mask to form nanostructures with a high aspect ratio through the selective ion etching mechanism (Fig. 1b ). By tuning the gap distance ( D ), the nanostructures and micro-walls can be easily hierarchized, as the plasma ion can reach under the shadow zone with respect to D . For the small D , simple hybrid structures were formed with the nanostructures surrounded by the micro-wall network (Fig. 1c,e ), while well-defined hierarchical structures were formed with the nanostructures nested on the entire surfaces of the micro-wall pattern for the larger gap distance (Fig. 1d,f ). Figure 1 Illustrations of hybrid patterning process assisted with metal-mesh overhung showing two characteristic etching masks; ( a ) microscale shadow zone formation, and ( b ) nanoscale metal etch masks formation. ( c – f ) Schematics and corresponding SEM images showing ( c , e ) hybrid patterned surface consisting of the flat micro-wall and high-aspect-ratio nanostructures, and ( d , f ) hierarchical patterned surface with low micro-wall and nanostructures. Scale bars in insets represent 500 nm. In this paper, the fabrication process of hierarchical structures was first discussed with varying gap distances. Then, the suggested patterning with the dual-scale etching mask effect was compared with the conventional plasma-based selective ion etching. The results showed that after the hydrophobic coating, the hybrid structured surface showed superhydrophobicity with high water adhesion, while the hierarchically structured surfaces superhydrophobicity with low adhesion. Two contrasting conditions of water adhesion were applied for water transport and evaporation. Further, it was demonstrated that optical reflectance could be reduced through the formation of well-distributed nanostructures on the large area substrate.",
"discussion": "Discussion A one-step process for the fabrication of hierarchical micro/nanoscale patterns was suggested in the form of plasma-based patterning with the dual-scale etching mask. Under O 2 plasma exposure, the metallic mesh overhung on the substrate with a varying gap distance serves as two characteristic etching masks against plasma exposure on the target surfaces by forming microscale wall structures and nanoscale high-aspect-ratio structures. As the sizes for the plasma shadow zone and exposure zone vary with the gap distance, the combination of nanoscale structures and its surrounding microscale wall network was hybridized to form hybrid or hierarchical structures on PET as large as the size of the cathode plate. After hydrophobic coating, the hybrid structured surface shows superhydrophobicity with high water adhesion, while the hierarchical surfaces showed non-stick along with very low water adhesion due to the air trapped between nanostructures beneath water droplets. Two contrasting conditions on which the adhesion force for the hierarchical surface is 10 times smaller than that for the hybrid surface were demonstrated for the water transport and evaporation tests. The uniform distribution of nanostructures formed in a large area was further demonstrated for low reflectance surfaces, along with robust superhydrophobicity. As our method can effectively and selectively fabricate hierarchical patterns in multiscale depending on various conditions regarding the overhung metallic mesh, it can be applied in mass production processes, such as the industry scale batch process and the roll-to-roll process, and therefore holds substantial potential for the fabrication of functional clothes for textiles, optical windows for smart devices, or energy harvesting with self-cleaning for solar cells."
} | 2,588 |
31226347 | null | s2 | 1,393 | {
"abstract": "Common strategies for conversion of lignocellulosic biomass to chemical products center on deconstructing biomass polymers into fermentable sugars. Here, we demonstrate an alternative strategy, a growth-coupled, high-yield bioconversion, by feeding cells a non-sugar substrate, by-passing central metabolism, and linking a key metabolic step to generation of acetyl-CoA that is required for biomass and energy generation. Specifically, we converted levulinic acid (LA), an established degradation product of lignocellulosic biomass, to butanone (a.k.a. methyl-ethyl ketone - MEK), a widely used industrial solvent. Our strategy combines a catabolic pathway from Pseudomonas putida that enables conversion of LA to 3-ketovaleryl-CoA, a CoA transferase that generates 3-ketovalerate and acetyl-CoA, and a decarboxylase that generates 2-butanone. By removing the ability of E. coli to consume LA and supplying excess acetate as a carbon source, we built a strain of E. coli that could convert LA to butanone at high yields, but at the cost of significant acetate consumption. Using flux balance analysis as a guide, we built a strain of E. coli that linked acetate assimilation to production of butanone. This strain was capable of complete bioconversion of LA to butanone with a reduced acetate requirement and increased specific productivity. To demonstrate the bioconversion on real world feedstocks, we produced LA from furfuryl alcohol, a compound readily obtained from biomass. These LA feedstocks were found to contain inhibitors that prevented cell growth and bioconversion of LA to butanone. We used a combination of column chromatography and activated carbon to remove the toxic compounds from the feedstock, resulting in LA that could be completely converted to butanone. This work motivates continued collaboration between chemical and biological catalysis researchers to explore alternative conversion pathways and the technical hurdles that prevent their rapid deployment."
} | 495 |
22948815 | null | s2 | 1,394 | {
"abstract": "Bacteria frequently manifest distinct phenotypes as a function of cell density in a phenomenon known as quorum sensing (QS). This intercellular signalling process is mediated by \"chemical languages\" comprised of low-molecular weight signals, known as autoinducers, and their cognate receptor proteins. As many of the phenotypes regulated by QS can have a significant impact on the success of pathogenic or mutualistic prokaryotic-eukaryotic interactions, there is considerable interest in methods to probe and modulate QS pathways with temporal and spatial control. Such methods would be valuable for both basic research in bacterial ecology and in practical medicinal, agricultural, and industrial applications. Toward this goal, considerable recent research has been focused on the development of chemical approaches to study bacterial QS pathways. In this Perspective, we provide an overview of the use of chemical probes and techniques in QS research. Specifically, we focus on: (1) combinatorial approaches for the discovery of small molecule QS modulators, (2) affinity chromatography for the isolation of QS receptors, (3) reactive and fluorescent probes for QS receptors, (4) antibodies as quorum \"quenchers,\" (5) abiotic polymeric \"sinks\" and \"pools\" for QS signals, and (6) the electrochemical sensing of QS signals. The application of such chemical methods can offer unique advantages for both elucidating and manipulating QS pathways in culture and under native conditions."
} | 371 |
24808467 | null | s2 | 1,397 | {
"abstract": "Echo state networks (ESNs) are a novel form of recurrent neural networks (RNNs) that provide an efficient and powerful computational model approximating nonlinear dynamical systems. A unique feature of an ESN is that a large number of neurons (the \"reservoir\") are used, whose synaptic connections are generated randomly, with only the connections from the reservoir to the output modified by learning. Why a large randomly generated fixed RNN gives such excellent performance in approximating nonlinear systems is still not well understood. In this brief, we apply random matrix theory to examine the properties of random reservoirs in ESNs under different topologies (sparse or fully connected) and connection weights (Bernoulli or Gaussian). We quantify the asymptotic gap between the scaling factor bounds for the necessary and sufficient conditions previously proposed for the echo state property. We then show that the state transition mapping is contractive with high probability when only the necessary condition is satisfied, which corroborates and thus analytically explains the observation that in practice one obtains echo states when the spectral radius of the reservoir weight matrix is smaller than 1."
} | 304 |
38622932 | PMC11072679 | pmc | 1,399 | {
"abstract": "Abstract Connecting genes to phenotypic traits in bacteria is often challenging because of a lack of environmental context in laboratory settings. Laboratory-based model ecosystems offer a means to better account for environmental conditions compared with standard planktonic cultures and can help link genotypes and phenotypes. Here, we present a simple, cost-effective, laboratory-based model ecosystem to study aerobic methane-oxidizing bacteria (methanotrophs) within the methane-oxygen counter gradient typically found in the natural environment of these organisms. Culturing the methanotroph Methylomonas sp. strain LW13 in this system resulted in the formation of a distinct horizontal band at the intersection of the counter gradient, which we discovered was not due to increased numbers of bacteria at this location but instead to an increased amount of polysaccharides. We also discovered that different methanotrophic taxa form polysaccharide bands with distinct locations and morphologies when grown in the methane-oxygen counter gradient. By comparing transcriptomic data from LW13 growing within and surrounding this band, we identified genes upregulated within the band and validated their involvement in growth and band formation within the model ecosystem using knockout strains. Notably, deletion of these genes did not negatively affect growth using standard planktonic culturing methods. This work highlights the use of a laboratory-based model ecosystem that more closely mimics the natural environment to uncover bacterial phenotypes missing from standard laboratory conditions, and to link these phenotypes with their genetic determinants.",
"introduction": "Introduction Despite the explosion in availability of bacterial genomic data, linking genes with organismal phenotypes remains difficult. One reason is that assigning gene functions can be hindered by a lack of ecological context in the lab, as bacteria are removed from the environments where they evolved. To address this, researchers have developed various strategies to reintegrate environmental factors and spatial structure into laboratory cultures [ 1–3 ]. Among these strategies, laboratory-based model ecosystems act as a powerful tool that can be used to more closely recapitulate the natural environment than simple planktonic cultures while still remaining experimentally tractable [ 4 , 5 ]. Model ecosystems are especially valuable for studying microbes found at oxic-anoxic interfaces, like those isolated from soils and sediments. In these settings, the distribution and behavior of microbes are closely aligned with physiochemical changes, particularly the transition from oxygenated to non-oxygenated environments [ 6 ]. One such example is aerobic methane-oxidizing bacteria (methanotrophs), which play important roles in biogeochemical cycling, bioremediation, and sequestration of the potent greenhouse gas methane [ 7–9 ]. These bacteria require methane as a carbon and energy source, and molecular oxygen for respiration and as an electron acceptor and atom donor in the methane monooxygenase reaction [ 10 ]. In the environment, oxygen diffuses into soils and sediments from the atmosphere or water column above, and methane diffuses up from anaerobic decomposition processes below, resulting in opposing gradients of oxygen and methane ideal for methanotrophs [ 6 , 11–13 ]. However, the oxygen-methane counter gradient is dynamic, as methane concentrations can vary depending on the availability of labile carbon in the soil, and oxygen can be depleted by increased activity by oxygen-respiring organisms [ 14 ]. To facilitate methane oxidation in micro-oxic conditions, methanotrophs employ a variety of metabolic strategies depending on their phylogeny. Many aerobic methanotrophs possess hemerythrin, a non-heme oxygen-binding transporter protein that scavenges and transports oxygen to the particulate methane monooxygenase enzyme used in the first step of methane oxidation [ 15 ]. Additionally, certain methanotrophs possess high affinity cytochromes to facilitate methane oxidation at low oxygen concentrations (e.g. Methylobacter spp.) [ 13 ], and some can couple this process with nitrate reduction as an energy conservation strategy (e.g. Methylomonas denitrificans ) [ 16 ]. Consistent with these diverse metabolic strategies, studies using methane enrichments of sediment have repeatedly observed dynamic population flux amongst methanotrophic communities in response to shifting oxygen and methane availability [ 17 , 18 ]. Replicating aspects of the chemical and physical environment in which methanotrophs exist is necessary for effectively studying their physiology and behavior. However, in the laboratory, these organisms have primarily been studied using homogenous planktonic cultures that lack spatial heterogeneity. This practice is likely impeding our ability to not only understand the molecular details of methanotroph physiology but also to optimize these details for industrial processes and climate change mitigation [ 19 , 20 ]. Additionally, culturing methanotrophs within a spatially resolved model ecosystem may help uncover phenotypes that are otherwise undetectable in planktonic cultures. Previously, researchers demonstrated that growing methanotrophs within opposing gradients of methane and oxygen in the lab is feasible using a variety of methods. In some examples, soil was suspended on a PTFE membrane that allowed gas exchange with the methane supply below [ 11 , 21 , 22 ]. In other cases, sediment was added to semi-solid agarose and exposed to opposing chambers of air and methane [ 23 , 24 ]. To our knowledge, these systems have been primarily used to isolate and classify methanotrophs from mixed methane-oxidizing consortia and have not yet been used to collect molecular-level information about the physiology of methanotrophs under opposing methane and oxygen gradients. Inspired by a previously published methane-taxis assay [ 25 ], we created a simple, inexpensive, laboratory-based model ecosystem using a disposable syringe that enables researchers to culture methanotrophs in a spatially resolved context. The system, called the gradient syringe, replicates the steep methane and oxygen counter gradients that are characteristic of the native environment of methanotrophs. We used this system to study pure cultures of methanotrophic soil isolates and examined their distribution, phenotypes, and cellular activity across the gas counter gradient. The results showed heterogenous physiological responses of methanotrophs and revealed new connections between a gradient syringe-specific phenotype and the genes involved.",
"discussion": "Discussion In this work, we demonstrate that culturing methanotrophs within a spatially resolved counter gradient of methane and oxygen can reveal genotype–phenotype associations that are largely unnoticed in conventional culturing approaches. We observed that methanotrophs form a distinct horizontal band located at the intersection of the counter gradient and that it is not due to an increased number of cells at this location, as previously hypothesized [ 23–25 ], but instead due to increased polysaccharide content. Using transcriptomics and deletion mutants, we identified three genes (likely out of many) involved in this phenotype. These genes are required for cell growth within the model ecosystem, but their absence did not negatively affect the ability of LW13 to grow in planktonic culture. The observed increase in polysaccharide content in the horizontal band in the gradient syringe model ecosystem may be due to increased extracellular polymeric substances (EPS) produced by methanotrophs at this depth. An established link exists between methane oxidation, oxygen availability, and EPS production in methylotrophic bacteria [ 27 , 47 ]. The primary component of this band appears to be polysaccharides, as there were no significant increases in extracellular DNA or total protein (two common EPS components) detected in the band segment ( Fig. S3 , see online supplementary material for a color version of this figure). However, these results do not negate the possibility that other biomolecules are present, and additional experiments are necessary to determine the exact molecular components of this band. We determined through flow cytometry that cells at the band were comparable in size to those directly adjacent ( Fig. S7 , see online supplementary material for a color version of this figure). This finding supports the conclusion that the biomolecules contributing to the horizontal band phenotype are likely extracellular and not due to intracellular polysaccharide accumulation or formation of a capsule. We observed variations in the depth and appearance of the horizontal band when we grew different methanotrophic genera in the gradient syringe ( Fig. 1B ). This difference may stem from the ability of different methanotrophic genera to adapt to varying oxygen tensions in the environment [ 14 , 17 , 18 ]. It is currently unclear whether the formation of the polysaccharide band is a cause or consequence of this location being at the intersection of the methane-oxygen counter gradient. It is possible that polysaccharide production was higher in cells at the intersection of the counter gradient as a response to low gas concentrations at this location or that polysaccharide production prevented the diffusion of gas substrates once a horizontal band formed. Although the exact triggers for extracellular polysaccharide production in methanotrophs remain to be precisely defined, excess carbon, nitrogen deficiency, and oxygen excess or limitation have all been reported to stimulate its production in methylotrophs [ 27 , 40 , 48 ]. More precisely identifying the involved factors may have practical implications for applied methanotrophy, such as methane mitigation in landfill covers and biofilters, which are negatively affected by the production of EPS [ 47 ]. Transcriptomic analysis of different segments within an LW13-inoculated gradient syringe revealed broad global gene expression differences, with the band and below segments being most similar ( Fig. S5A , see online supplementary material for a color version of this figure), suggesting that oxygen availability is a major influence on cellular heterogeneity. Methane monooxygenase gene expression varied between the examined syringe segments but remained highly expressed in LW13, illustrating methanotrophs’ adaptability to oxygen changes. Because cells throughout the gradient syringe appeared to have comparable growth rates and sufficient metabolic activity, we aimed to link genes upregulated in the band segment with the polysaccharide phenotype. Previously, the role of the exosortase protein EpsH in production of EPS in LW13 was identified [ 49 ] and confirmed [ 50 ], where disruption of epsH resulted in significantly reduced EPS in ammonium mineral salts media. However, this gene was not significantly differentially expressed by cells of any segment in our RNA-seq analysis, possibly due to nitrate, rather than ammonium, being used as the nitrogen source in our experiments. To explore additional potential gene-phenotype connections, we investigated a subset of genes that were upregulated in the band segment that had not yet been experimentally linked to polysaccharide production in methanotrophs. N -acyl amino acid synthases have been phylogenetically linked to the PEP-CTERM/exosortase system (ExoAT) [ 51 ], a putative protein sorting system in Gram-negative bacteria associated with EPS production [ 52 ]. The predicted product of the fucose 4-O-acetylase like acetyltransferase gene (OAT) likely engages in acylation processes impacting various sugar-containing cell-surface structures, including exopolysaccharides [ 53 ]. Hemerythrin is a non-heme oxygen-binding protein that serves as an oxygen scavenging transporter for particulate methane monooxygenase-containing aerobic methanotrophs such as LW13 and was predictably upregulated in the relatively lower oxygen concentrations of the band segment to the above segment in our study [ 15 ]. Although ExoAT and OAT are not considered essential to cell survival and have clear potential links to the production of extracellular polysaccharides, individual knockouts of these genes in LW13 had a negative effect on both horizontal band formation and growth ( Fig. 4 ) in the gradient syringe but did not interfere with growth in planktonic culture ( Fig. S6 , see online supplementary material for a color version of this figure). The fact that band formation and growth in the gradient syringe were both affected in each of these mutants suggests that either methanotrophic growth is dependent on horizontal band formation, or that the formation of the band is dependent on sufficient cell growth. Both reduction in band formation and growth in the gradient syringe by the hemerythrin mutant suggests that sufficient cell growth or metabolic activity may be required for band production, as hemerythrin production is closely linked with methane oxidation activity in micro-oxic environments [ 54 ]. Discovery of a gene that when deleted only affects band formation but not growth in the gradient syringe would further clarify the nature of this behavior. Our results have raised questions about methanotroph physiology within a methane-oxygen counter gradient that can now be studied at the molecular level using this model ecosystem. Extending this concept, our laboratory-based model ecosystem can be used to simultaneously cultivate multiple strains isolated from a methane-oxidizing bacteria community to study the molecular and genetic-level details of chemical and physical interactions between strains. Alternatively, the simple design of the gradient syringe could be modified to cultivate other types of bacteria that exist at the boundary between oxygen and non-oxygen gas environments. This includes examples such as the aerobic H 2 -oxidizing “Knallgas” bacteria present in termite guts [ 6 , 55 ], and the soil bacteria from the genus Bradyrhizobium that aerobically oxidize carbon monoxide generated by legume roots [ 56 , 57 ]. By studying these biogeochemically relevant microbes in a model ecosystem that mimics their respective gas counter gradients, we can gain deeper insights into their unique physiology and metabolic adaptations. Overall, our study not only sheds light on the behavior of methanotrophs but also underscores the broader applicability of simple laboratory-based model ecosystems for linking genes with organismal phenotypes."
} | 3,657 |
22347219 | PMC3271277 | pmc | 1,400 | {
"abstract": "In this study, both culture-dependent and culture-independent methods were used to determine whether the iron sulfide mineral- and nitrate-rich freshwater nature reserve Het Zwart Water accommodates anoxic microbial iron cycling. Molecular analyses (16S rRNA gene clone library and fluorescence in situ hybridization, FISH) showed that sulfur-oxidizing denitrifiers dominated the microbial population. In addition, bacteria resembling the iron-oxidizing, nitrate-reducing Acidovorax strain BrG1 accounted for a major part of the microbial community in the groundwater of this ecosystem. Despite the apparent abundance of strain BrG1-like bacteria, iron-oxidizing nitrate reducers could not be isolated, likely due to the strictly autotrophic cultivation conditions adopted in our study. In contrast an iron-reducing Geobacter sp. was isolated from this environment while FISH and 16S rRNA gene clone library analyses did not reveal any Geobacter sp.-related sequences in the groundwater. Our findings indicate that iron-oxidizing nitrate reducers may be of importance to the redox cycling of iron in the groundwater of our study site and illustrate the necessity of employing both culture-dependent and independent methods in studies on microbial processes.",
"introduction": "Introduction Redox cycling of iron has profound effects on the chemistry of soils and sediments due to the sheer abundance of iron, and the interdependence with the cycling of virtually all other biochemically relevant elements (Stumm and Sulzberger, 1992 ; Davison, 1993 ; Nealson et al., 2002 ). Iron species are subject to both chemical and microbial transformations. Iron can be abiotically reduced in various manners. Photoreduction, and interactions with sulfhydryl groups, organic acids, and reducing ligands, all result in reduction of ferric oxides (Nealson and Saffarini, 1994 ; Castillo-Gonzalez and Bruns, 2005 ). In sulfur-rich, mainly marine, environments, hydrogen sulfide reduces ferric iron oxides which results in the formation of iron sulfide (FeS), pyrite (FeS 2 ), and elemental sulfur (Thamdrup et al., 1994 ; Carey and Taillefert, 2005 ). In non-sulfidogenic anoxic soils and sediments however, microbial iron reduction, coupled to organic carbon or hydrogen oxidation, is the dominant process (Sobolev and Roden, 2002 ). The importance of microbial iron reduction has been unequivocally demonstrated: in many environments it accounts for significant turnover of organic carbon, and has inhibitory effects on sulfate reduction and methanogenesis (Nealson and Saffarini, 1994 ; Thamdrup, 2000 ; Nealson et al., 2002 ). The first described iron-reducing bacterial species were fermenting bacteria that make use of the reduction as a means to dispose of electron equivalents (Lovley and Phillips, 1988 ). Nowadays, also a large variety of microorganisms, ranging from slightly psychrophilic to thermophilic, have been described that use energy generated through iron reduction for growth. Examples of such dissimilatory iron reducers are Geobacter sp., Rhodoferax \n ferrireducens , Geothrix fermentans , Ferribacterium limneticum , Geoglobus ahangari , and Shewanella sp. These microorganisms couple iron reduction to oxidation of a large variety of organic compounds, hydrogen, or elemental sulfur (Nealson and Saffarini, 1994 ; Cummings et al., 1999 ; Thamdrup, 2000 ; Tor et al., 2001 ; Kashefi et al., 2002 ; Nevin and Lovley, 2002 ; Finneran et al., 2003 ). Especially Geobacter species have received considerable attention because of their ability to convert pollutants such as uranium, aromatic hydrocarbons, and chlorinated solvents (Anderson et al., 1998 ; Lin et al., 2005 ; Nevin et al., 2005 ; Sung et al., 2006 ). The microbial contribution to iron oxidation has long been subject of debate between microbiologists and geochemists (Ghiorse, 1984 ), especially because abiotic iron oxidation occurs rapidly in the presence of oxygen (Sobolev and Roden, 2002 ; Emerson and Weiss, 2004 ). Under anoxic conditions, nitrite is a chemical oxidant of ferrous iron (Moraghan and Buresh, 1977 ; Cooper et al., 2003 ; Coby and Picardal, 2005 ), although this may require millimolar amounts. In spite of these chemical reactions, it is presently accepted that microorganisms can contribute significantly to iron oxidation. Aerobic, acidophilic iron-oxidizing microorganisms play an important role in the generation of acid mine drainage (AMD; Baker and Banfield, 2003 ). Aerobic, neutrophilic, iron-oxidizing microorganisms, that have to compete with the rapid chemical oxidation, have been isolated from marine as well as freshwater environments, ranging from iron seeps, groundwater, and hydrothermal vents to root-plaque of wetland plants (Emerson and Revsbech, 1994 ; Emerson and Moyer, 1997 ; Emerson et al., 1999 ; Edwards et al., 2003 , 2004 ). The ability to gain energy from anaerobic oxidation of iron is widespread among bacteria. Ferrous iron serves as an electron donor for phototrophic, purple, non-sulfur bacteria, and green sulfur bacteria under anoxic conditions (Ehrenreich and Widdel, 1994 ; Heising et al., 1999 ). Several bacterial species and an archeon, Ferroglobus placidus , have been described that couple ferrous iron oxidation to nitrate reduction (Hafenbradl et al., 1996 ; Benz et al., 1998 ; Straub et al., 2004 ; Senko et al., 2005 ; Kumaraswamy et al., 2006 ; Weber et al., 2006 ). It has been suggested that on a global scale nitrate-reducing, iron-oxidizing bacteria are more important than the phototrophs, since they are not limited by the availability of light (Straub et al., 2001 ). Straub et al. ( 1998 ) used ferrihydrite produced by iron-oxidizing nitrate reducers to enrich iron-reducing bacteria. Indications for the coexistence of aerobic iron-oxidizing and anaerobic iron-reducing microorganisms in close proximity to each other were found by Weiss et al. ( 2003 ) and Roden et al. ( 2004 ). Furthermore, microbial anoxic iron cycling by a single organism (a Geobacter sp.) capable of both dissimilatory iron reduction and nitrate-dependent iron oxidation was proposed by Weber et al. ( 2005 ) and iron respiration with formate as electron donor as well as iron oxidation with nitrate as electron acceptor was demonstrated for the anaerobic ammonium-oxidizing bacterium Kuenenia stuttgartiensis (Strous et al., 2006 ). Iron sulfide mineral- and nitrate-rich soils in freshwater ecosystems provide both a source of reduced iron and an electron acceptor that could promote growth of anaerobic, non-phototrophic iron-oxidizers. Oxidized iron species resultant from iron-oxidizing, nitrate-reducing activity could in turn serve as electron acceptors for microbial iron reducers. To determine whether the iron sulfide mineral- and nitrate-rich freshwater environment of the nature reserve Het Zwart Water (Venlo, The Netherlands) provides a suitable habitat for anoxic microbial iron cycling, groundwater from an iron sulfide/and nitrate-rich soil was examined using both culture-dependent and culture-independent methods.",
"discussion": "Discussion Iron cycle bacteria in the groundwater of Het Zwart Water Although T. denitrificans possesses iron-oxidizing capacity in the presence of nitrate, specific reaction rates are much lower, weeks opposed to days, than those of the specific iron-oxidizing nitrate reducers previously described by Straub et al. ( 1996 ). Given the abundance of strain BrG1-like bacteria, it therefore seems most likely that the betaproteobacterial Thiobacilli detected in the groundwater are primarily involved in the oxidation of reduced sulfur compounds in Het Zwart Water as was demonstrated before (Haaijer et al., 2006 , 2007 ). Based on the abundance of Acidovorax strain BrG1-like bacteria, suggested by the clone library and FISH analyses data, these microorganisms are proposed as the mediators for anoxic iron oxidation in the groundwater from Het Zwart Water. In the iron sulfide- and nitrate-rich environment of Het Zwart Water these bacteria could be of particular importance. Edwards et al. ( 2004 ) demonstrated accelerated iron sulfide mineral dissolution in the presence of iron-oxidizing bacteria. This hypothesis is supported by earlier findings of the presence of this type of bacterium in an iron sulfide- and nitrate-fed enrichment culture (Haaijer et al., 2006 ). However, despite their abundance, strain BrG1-like bacteria were not detected in the final 50 ml volume enrichment culture. Instead, a Klebsiella -like bacterium was detected. Iron-oxidizing, nitrate-reducing activity by Klebsiella sp. cells has been described by Senko et al. ( 2005 ) under non-growth conditions. It therefore seems likely the K. pneumoniae -like organism detected in the iron-oxidizing nitrate-reducing culture did not possess the capacity of generating sufficient energy for growth by coupled iron oxidation and nitrate reduction. This fact together with the absence of any obvious iron-reducing bacteria in the groundwater, as demonstrated with the molecular methods, shows that complete microbial iron cycling could not be convincingly demonstrated in the groundwater of Het Zwart Water. The isolation of the iron-reducing Geobacter sp., however, indicates that bacterial iron reduction at the least could be important in other compartments (e.g., the surrounding soil) of Het Zwart Water. The iron-reducing Geobacter isolate converted 1 mM of acetate at the expense of 5 mM ferric iron and FISH analysis confirmed the pure culture status. This ratio does not agree well with the theoretical stoichiometry of 8 mM ferric iron reduced at the expense of 1 mM acetate (Lovley et al., 1987 ). The contribution of assimilation to the total amount of acetate consumed, however, can be high: 46% of total acetate metabolized was assimilated by Geobacter sulfurreducens grown in batch culture on fumarate and acetate (Galushko and Schink, 2000 ). This phenomenon may also explain the observed low amount of ferric iron reduced in the Geobacter sp. culture described presently. Differences in the detection of iron-oxidizing nitrate reducers and iron reducers Molecular analyses (16S rRNA gene clone library and FISH) showed that the Acidovorax strain BrG1-like, iron-oxidizing nitrate reducers accounted for a major portion of the microbial community of the groundwater sample from Het Zwart Water. In contrast to the abundance demonstrated by the molecular data, the cultivation procedure did not lead to the enrichment or isolation of this type of bacterium. A probable cause is the completely autotrophic culturing conditions adopted in the iron-oxidizing enrichments. Iron-oxidizing nitrate-reducing activity was first reported (Straub et al., 1996 ) for a solely lithotrophic enrichment culture. Isolated strains, however, seem dependent on the presence of organic co-substrates (Straub et al., 2004 ). In contrast to the results for iron-oxidizers, an iron-reducing Geobacter sp. culture was readily obtained. The molecular analyses, however, suggested the contribution of this bacterium was of little numerical relevance in the groundwater sample. Together, these results, conflicting as they are for the functional groups of interest in this study, illustrate the necessity to employ both culture-dependent and culture-independent methods in studies on microbial activity. To choose only one approach is to disregard the biases inherent to this approach, such as primer-induced biases in clone libraries (Forney et al., 2004 ), or selection of fast-growing microorganisms in culture media (Grosskopf et al., 1998 ). Inventory descriptive studies like ours, allow development of more direct approaches, necessary to understand ecosystem functioning."
} | 2,946 |
32904523 | PMC7455116 | pmc | 1,402 | {
"abstract": "This first-attempt study deciphered combined characteristics of species evolution and bioelectricity generation of microbial community in microbial fuel cells (MFCs) supplemented with Camellia green tea (GT) extracts for biomass energy extraction. Prior studies indicated that polyphenols-rich extracts as effective redox mediators (RMs) could exhibit significant electrochemical activities to enhance power generation in MFCs. However, the supplementation of Camellia GT extract obtained at room temperature with significant redox capabilities into MFCs unexpectedly exhibited obvious inhibitory effect towards power generation. This systematic study indicated that the presence of antimicrobial components (especially catechins) in GT extract might significantly alter the distribution of microbial community, in particular a decrease of microbial diversity and evenness. For practical applications to different microbial systems, pre-screening criteria of selecting biocompatible RMs should not only consider their promising redox capabilities (abiotic), but also possible inhibitory potency (biotic) to receptor microbes. Although Camellia tea extract was well-characterized as GRAS energy drink, some contents (e.g., catechins) may still express inhibition towards organisms and further assessment upon biotoxicity may be inevitably required for practice.",
"conclusion": "4 Conclusion \n Camellia green tea extract obtained from “inappropriate” extraction procedures (e.g., room temperature extraction) might be inhibitory to reduce the power generation of MFCs compared to bioelectricity stimulation by supplement of higher temperature-extracted green tea. Evidently, the main components of green tea extracted by pure water and MEOH showed significant difference in concentration and composition, which could directly lead to the differences in inhibitory potency and biocompatibility. Although the extracts obtained by different solvents (i.e., water and MEOH) owned significant redox capabilities, the application in MFCs unexpectedly still exhibited considerable inhibitory effect. Microbial community analysis showed that the supplementation of green tea extract significantly altered the distribution of microbial community, especially the decrease of microbial diversity and evenness. Therefore, in practical application of different microbial culture systems, selecting appropriate RMs should not only consider their excellent redox-mediating characteristics, but also the inhibitory responses for feasibility evaluation as screening criterion.",
"introduction": "1 Introduction In face of gradual exhaustion of fossil energy shortage around the globe, biomass energy is considered to be the most green and sustainable alternative with the environmental friendliness for worldwide utilization [1] , [2] , [3] , [4] . Among myriads of bioresources of biomass energy, microbial fuel cells (MFCs) were effective electrochemical systems to convert chemical energy for bioelectricity generation via simultaneous waste biotreatment and product biosynthesis [5] , [6] , [7] . However, the relatively low capacity of bioelectricity generation still greatly limited its potentials for practical applications due to the low electron transfer efficiency [8] . To overcome this disadvantage, exogenous supplementation of redox mediators (RMs) was considered to effectively improve the electron transfer capability for augmenting power generation [ 9 , 10 ]. Regarding such electroactive RMs, several pioneer works selected artificially synthesized compounds for feasibility study [11] , [12] , [13] . For example, aromatic compounds with promising electrochemically active functional groups (e.g.,-OH and -NH 2 ) at ortho or para positions could exhibit significant redox capabilities to effectively enhance power-generating capabilities in MFCs [11] . Compared with amino group, hydroxyl group sometimes owned the more reversible and stable electrochemical activity for electron-shuttling [14] . However, for green sustainability using synthetic compounds as RMs may still introduce several inevitable concerns for practice (e.g., inhibitory potency for biocompatibility towards biological systems) [ 15 , 16 ]. Therefore, natural resources or products were recently considered to replace such artificially synthesized compounds for sustainable applications. Several studies clearly revealed that appropriate supplementation of natural products abundant in electrochemically active substances could significantly promote simultaneous bioelectricity generation and wastewater treatment in MFCs [17] , [18] , [19] , [20] . Recently, Xu et al. [20] extracted natural herbal substances abundant in anthocyanins to effectively increase nearly threefold efficiency of bioelectricity generation in MFCs. From the perspective of chemical structure, in fact these bioelectricity-stimulating substances were mostly polyphenols, which are abundant in natural plants [17] , [18] , [19] , [20] . Regarding polyphenols in natural plants, over some thousand years, Camellia green tea (GT) has been used as a traditional drink in China and India and become popular all over the world. In particular, UK has become one of the world's greatest tea consumer since eighteen century [21] . Based upon the degree of tea fermentation, Camellia tea can be classified as GT (0%), yellow tea (10%−30%), Oolong tea (30%−80%) and red tea (80%−100%) [22] . Medicinal values of tea have been well known (e.g., “Cha Jing” (Tea Bible) by Lu Yu of the Tang Dynasty), but potential health properties of tea polyphenols indicated anticancer, antioxidant validated scientifically within these 3–4 decades [23] . Modern medicine used the theory of free radical and immunity to elucidate such specific effects of Camellia tea on human health. In summary, tea contained not only the essential nutrients of human body, but also the medicinal ingredients beneficial to the restoration of human health under certain pathological conditions [24] . In fact, tea polyphenols as the main antioxidant components in Camellia tea has been mentioned in medical literature. For instance, Bag et al. [25] and Henning et al. [26] pointed out that tea polyphenols could prevent cancer by regulating the expression of genetic aberrations occurring in targeted DNA, modified histones and micro RNAs. Ding et al. [27] also further indicated that Pu'er tea had a significant hypoglycemic effect on diabetic rats induced by streptozotocin. Chen et al. [28] even pointed out that theaflavin-3,3′-digallate (TF) in Puer and black tea could effectively inhibit SARS-CoV 3C-like protease. That is, tea polyphenols may be a potential source of anti-cancer and antiviral drugs with fewer side effects and lower prices. Moreover, recent studies also deciphered that abundant tea polyphenols in tea extract sufficiently provided a reliable source of electrochemically active RMs [ 29 , 30 ]. Considering stimulation of effective bioenergy extraction, the protagonist dealing with bioelectricity production in MFCs is electroactive microbes or mixed consortia, that effectively release electrons from oxidation of organic matter [20] . Of course, the bioactivities of the electricity-generating microorganisms (e.g., biofilm forming, electron-transporting characteristics) would directly influence the power-generating efficiency of MFCs [ 17 , 19 ]. Due to some inhibitory/antagonistic interactions to be taken place, it was not possible to guarantee that all of natural substances are appropriate sources to be natural RMs. This might also explain why the extracellular metabolites of Chlorella with significant redox capacities sometimes could not significantly stimulate the bioelectricity production of MFCs as previously mentioned [31] . If natural extracts exhibited significant redox-mediating capabilities, they may also possibly express toxicity potency to the receptor organisms. Therefore, significant redox capability cannot be the sole screening criterion to select electrochemically active natural RMs for bioenergy applications. For example, as literature mentioned [ 29 , 30 ], some tea polyphenols owned anti-inflammatory and bacteriostatic effects (e.g., noticeable inhibition on Typhoid bacillus, Paratyphoid bacillus, Yellow haemolytic staphylococcus, Streptococcus aureus and Dysentery bacillus ). Some studies have also shown that tea polyphenols had a strong killing effect on Streptococcus mutans in the oral cavity [32] . Therefore, tea polyphenols have also been widely used in industrial preparation of toothpaste. That is, such strong antibacterial effects of components in tea polyphenols may also have negative effects on bacteria in MFCs. As prior work indicated, different methods of extraction could result in different levels of antioxidant/ electron transfer capabilities (e.g., H 2 O extracted > EtOH extracted) [33] . Moreover, many medicinal herbs may not be appropriate to be extracted in low temperature, rather than at high temperature. In fact, high temperature by macerated and heat-dried or processing heating could attenuate contents of some toxic species and sometimes even reduce power of side effects in medication. To clearly reveal whether such phenomena may also be taken place in MFCs, Camellia GT was selected herein as study material using water and methanol as solvents of extraction. Furthermore, to reveal the novelty of this study and to compare results of high-temperature extraction in prior studies, low-temperature extraction was intentionally selected to inspect the electrochemical activity and/or antibacterial characteristics of Camellia green tea extract. After centrifugation and freeze drying, extracted powders of Camellia GT obtained from the extraction of different solvents were harvested for comparison. In addition, electrochemical properties of the extracts were characterized via electrochemical measures to evaluate whether their electrochemical potential activities could be considered as RMs. Quantitative analyses of bioelectricity generation and community ecology in MFCs with the supplementation of these electrochemical active extracts were further implemented to quantitatively present such inhibitory or stimulating responses to affect the performance of bioenergy-extracting processes in MFCs.",
"discussion": "3 Results and discussion 3.1 Chemical composition analysis For solid-liquid extraction, apparently the composition and content of the extract are directly associated to the solvent to be used. In this study, two types of solvents- pure water and 80% methanol were selected to extract Camellia GT at room temperature and the chemical composition and content of the obtained solid extract powder would also be greatly different. Therefore, chemical constituents of water extract and methanol extract of Camellia GT were quantitatively analyzed by HPLC method for comparative assessment. According to Jiang et al. [37] , Camellia green tea extracts mainly contain tea polyphenols and alkaloids, while major contents of tea polyphenols are phenolic acids and catechins. Therefore, representative substances of these three categories were selected for standard quantitative analysis (i.e., gallic acid (GA), epigallocatechin gallate (EGCG, catechin) and caffeine (CAF, alkaloid)). According to the HPLC spectra in Fig 1 \n(A, B and C), the fingerprint peaks of standard GA, EGCG and CAF was responded at the retention time peak at 8 min, 17 min and 18 min, respectively, indicating that the green tea extracts contained these above-mentioned standards. As comparison of relative contents of three standard substances in the two different green tea extracts, the peak height of HPLC could be approximately represented as the relative contents of the three standard substances since the mass concentration of the prepared tea extract was identical. As indicated in Fig 1 (D), the content of CAF in these two extracts was nearly equal, while the content of GA in the water extraction was relatively higher than that in the methanol extraction. However, as Table 1 \nindicated, the content of EGCG was higher in MEOH than that in water, since EGCG was more soluble in MEOH than in water. In fact, Ahmad Muhamud and Amran [38] indicated that EGCG contents in Camellia sinensis GT were 0.9347 (MEOH extract) and 0.6705 (water extract) mg/mL. Furthermore, Oh et al. [39] also mentioned that MEOH extract of GT could obtain 60–580 g major catechins/kg dry extract, but water extract was only 385 g major catechins/kg dry extract for 85 °C extraction. In addition, extraction through pure organic solvents was found to yield the highest content of catechins. As indicated in Fig. 1 , some unknown substances at the retention time of 3 min and 21 min were exhibited; however, their contents in the water extraction were also relatively small. This was owing to the different solubility of these substances in two solvents with different polarity, which resulting in the different content in the extracts [17] . Fig. 1 HPLC analysis of (A) GA (B) EGCG (C) CAF compared with tea extract and (D) HPLC analysis of tea extracts between water extract and MEOH extract . (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) Fig 1 Table 1 The measured concentrations of GA, EGCG and CAF in the water extraction and MEOH extraction. Table 1 Extracts GA EGCG CAF MEOH extraction 7 mg L − 1 122 mg L − 1 77 mg L − 1 water extraction 26 mg L − 1 68 mg L − 1 71 mg L − 1 To conduct a detailed quantitative analysis of the standards in the two extracts, HPLC analysis was implemented upon the pure standards with different concentrations ranged from 10 mg L − 1 to 500 mg L − 1 for calibration [40] . As shown in Fig 2 \n, the retention time peak of these three standards increased with the increase in concentration of GA, EGCG and CAF. The linear relationship between the integral area of the retention time peak and the concentration of the three standards was shown in Fig 2 (D). As indicated in the calibration line, the concentration of these three standards and the integral area of corresponding retention time peak showed a well-correlated linear relationship. The corresponding concentrations of GA, EGCG and CAF in the two extracts could be quantitatively determined by matching the integral area of corresponding retention time peak with the standard calibration line. The corresponding concentrations of these three standards in the water extraction and MEOH extraction were listed in Table 1 . According to the detailed data in the Table 1 , the contents of CAF in the two extracts were respectively 77 mg L − 1 and 71 mg L − 1 nearly at the same level. The content of GA in the water extraction was nearly 4 times of that in MEOH extraction, while the content of EGCG was only ca. 50%. These indicated that the contents of these three standards and other unknown substances in the two extracts also exhibited significantly different. This considerable difference might result in diverse outcomes of electrochemical and antioxidant activities as revealed in details afterwards. Fig. 2 Peak retention time of standard (A) GA (B) EGCG and (D) CAF by HPLC at different concentrations and (D) the summary diagram of calibration curve. Fig 2 3.2 Electrochemical capability assessment To reveal the electrochemical capability of water extract and MEOH extract from green tea (e.g., reversibility and stability of oxidation and reduction potential peaks), 100 cycles CV scanning of these candidate redox mediators with the same mass concentration was also carried out [11] . As indicated in Fig 3 \n, both the water extract and MEOH extracts of GT exhibited significant redox potential peaks, which directly reflected the bioenergy-stimulating capability. Regarding the electrochemical reversibility, the redox peaks of water extract tended to be stabilized after serial CV scanning (i.e., repeated reduction and oxidation) and both oxidation peaks and reduction peaks could be clearly revealed. However, the redox peaks of MEOH extract seemed to show significant electrochemical instability of CV profiles and gradually attenuated. This was likely due to antioxidant and/or anti-reductants compositions present in most of extracted contents. Therefore, it could be seen that the water extract owned more significant electroactive capabilities than MEOH extract for bioenergy extraction. Since both the extracts were mixtures of phenolic acids and catechins, especially GA and EGCG, the redox capability should be the overall responses present of the electrochemical components. In fact, the redox capabilities of both GA and EGCG were also evaluated by CV inspections under the same scanning conditions for comparison. As shown in Fig 4 \n, both GA and EGCG owned the chemical structure with three consecutive hydroxyl groups attached to the benzene ring. However, both redox capabilities of GA and EGCG were exhibited in significant differences. The CV profile of GA emerged significant redox potential peaks with higher stable reversibility. However, the redox capability of EGCG tended to be attenuated possibly due to electrochemical instability. This might indicate that GA owned more significant electrochemical capability than EGCG for electron-shuttling catalysis. Moreover, this seemed to explain why the redox capability of water extract was greater than that of MEOH extract. The water extract contained higher amount of electrochemically convertible GA, leading to the difference of electrochemical capability from MEOH extract. Fig. 3 Comparison CV profiles of (A) water extract and (B) MEOH extract of green tea at different scan cycle . (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) Fig 3 Fig. 4 The chemical structure and comparison CV profiles at different scan cycle of standard (A) GA and (B) EGCG. Fig 4 3.3 Bioenergy performance analysis As prior studies [11] indicated, aromatic compounds with electron-shuttling functional groups (e.g., ortho - or para -dihydroxyl (−OH) substituent(s)) could act as RMs to enhance efficiency of simultaneous wastewater treatment and bioelectricity generation in MFCs. According to Chen et al. [17] , [18] , [19] , RMs could be reversibly inter-converted between reduced and oxidized forms of intermediates to enhance electron transfer phenomena between electron donor(s) and electron acceptor(s) for augmenting electricity generation. Therefore, the application of two green tea extracts into MFCs should clearly present whether such electrochemical activities could be stably expressed by microbes. This would be reflected in the remarkable electron-shuttling phenomenon, improving the bioelectricity-augmenting performance of MFCs [17] . Thus, water extract and MEOH extract were supplemented to MFCs with the same mass concentration to evaluate power-generating capacity for comparison. Aware that nearly identical mass concentration of tea extract simply suggested that the same weight of Camellia tea (biomass) was used for comparison. In fact, two kinds of MFCs inoculated with different mixed consortia of bacteria (i.e., MFC-A and MFC-B) were carried out to verify whether the expression of electrochemical RMs in MFCs is still controlled by the electroactive-bacterial populations. However, supplementation of both water extract and MEOH extract did not enhance the power generation of MFCs as anticipated. On the contrary, significant inhibitory effects were observed in both MFC-A and MFC-B. As shown in Fig 5 \n, the twice successive supplementation of both water extract and MEOH extract obviously repressed the power production of MFC-A and MFC-B. Regarding the power generation capacity, the power density of MFC-A1 and MFC-B1 respectively decreased from 14 to 18 mW m − 2 to 10 and 9 mW m − 2 with the successive supplementation of water extract. Of course, dose concentration strongly influenced the degree of inhibitory potency expression since higher dose would trigger more severe adverse effects to be taken place to the receptor organisms. That was why power density of 2nd was even lower than 1st ( Fig. 5 ). This also suggested that different levels of inhibitory responses would be resulted owning to the difference of microbial community. Furthermore, addition of MEOH extract tended to dramatically inhibit the power generation of MFC-A2 and MFC-B2, respectively decreased from 15 to 19 mW m − 2 to 5 and 3 mW m − 2 . These result directly suggested that the inhibition of MEOH extract was even more considerable than that of water extract. Since the sources of water extract and MEOH extract were the same green tea, the apparent inhibitory differences were most likely owing to the differences in the composition and content of the extract due to the different solvents and temperatures of extraction as discussed afterwards. Fig. 5 Power density profiles of (A) MFC-A1 and (C) MFC-B1 supplemented with water extract and (B) MFC-A2 and (D) MFC-B2 supplemented with MEOH extract. Fig 5 3.4 Microbial community analysis As the two Camellia green tea extracts contained chemical components with strong antibacterial activities, applications to MFCs clearly expressed inhibitory effect on power generation, directly affecting electrochemical activities of the electrogenic microorganism to be exhibited in MFCs. To clearly decipher such inhibitory effect of green tea extract on bacterial strains in MFCs, microbial community analysis of MFCs before and after supplementation of MEOH extract was implemented [41] . The changes of microbial community in MFCs were analyzed from the levels of phylum, class, order and family ( Fig 6 \n). Regarding MFC-A, from the phylum level, the original flora could be mainly divided into Proteobacteria and Firmicutes , and the two phyla accounted for 48.21% and 51.78%, respectively, in a relatively even distribution state (i.e., community in higher biodiversity). However, after the supplementation of MEOH extract, the proportion of the Proteobacteria increased significantly (up to 85.60%), while the Firmicutes could not adapt to such environmental stress, leading to significant loss of cell viability (decreased to 14.40%). The same result could be found in the microbial community analysis of MFC-B. The Proteobacteria and Firmicutes respectively changed from 42.73% and 57.27% to 67.00% and 33.00%, respectively. In addition, such phenomenon could also be observed in the classification of class and order levels. From the more detailed classification of the family, in addition to the obvious changes of microbial community in MFC-A, Clostridiales UC and Clostridiaceae -1 strains seemed to become extinct with the supplementation of MEOH extract. In MFC-B, except for dying out of Clostridiaceae-1, Carnobacteriaceae strains were also eliminated from the population owing to the addition of MEOH extract. These results indicated that these strains were unlikely to resist such supplementation of MEOH extract. Fig. 6 Classification of the 16S rRNA gene sequences of clone library from (A) MFC-A and (B) MFC-B: Phylum, Class, Order and Family level category of total bacteria (from left to right). Fig 6 Considering community distribution diversity, Shannon's Diversity Index (H') was adopted herein as performance index to characterize species (OTUs) diversity in this bacterial community, suggesting both abundance and evenness of the species (OTUs) in the population [42] . Thus, the Shannon's Diversity Index for comparative inspection was calculated by the following formula H ′ Shannon = − ∑ i = 1 S o b s P i L n P i , where S obs is total number of species (OTUs) and P i is the fraction of the total number of individuals in a particular genotype or taxon i . Moreover, vlues for H’ ranged from 0 (low diversity) to 5 (high diversity) could directly reflect the abundance level of bacterial community. In addition, to express species evenness of bacterial community, Shannon's Evenness Index (also known as Pielou's Evenness Index (J)) was also calculated from the following formula J = H ′ H ′ m a x , where H ′ max is the maximum possible value of Shannon's Diversity Index. The values for J ranged from 0 (low evenness) to 1 (high evenness) could directly reflect the uniform distribution of bacterial community. In bacterial community, if the distribution of every species was likely equally, the H ′ max could be calculated as H m a x ′ ≅ − ∑ i = 1 S o b s 1 S L n 1 S = L n S , \n As indicated in these calculated indices ( Table 2 \n), continuous increases of Shannon's Diversity Index (H’) and decreases of Shannon's Evenness Index (J) from phylum to family in both MFC-A and MFC-B suggested that the bacterial community tended to be highly diverse with low evenness if more specific levels were considered. This might suggest that some species populations were possibly on the verge of extinction as well. Furthermore, comparing the two different bacterial communities before and after the supplementation of MEOH extract, both the Shannon's Diversity Index and Shannon's Evenness Index exhibited significant decrease. This result was consistent with significant extinction of species as microbial community analysis indicated. Table 2 List of calculation results of Shannon's Diversity Index (H’) and Shannon's Evenness Index (J) in microbial community analysis. Table 2 Level Shannon's Diversity Index (H’) Shannon's Evenness Index (J) MFC-A MFC-B MFC-A MFC-B Blank + Blank + Blank + Blank + Phylum 0.999 0.594 0.985 0.915 0.999 0.594 0.985 0.915 Class 1.406 0.723 1.542 1.139 0.887 0.456 0.973 0.718 Order 1.406 0.723 1.542 1.139 0.887 0.456 0.973 0.718 Family 1.768 0.770 1.911 1.537 0.684 0.385 0.739 0.547 3.5 Mechanism exploration To elucidate such different inhibitory outcomes of GT extracts, comparative analysis on prior studies and literature was carried out. As aforementioned, evidently contents of GA, EGCG and several unknown compositions in the water extract and MEOH extract were significantly different. As indicated in literature [ 30 , 31 , 41 ], EGCG owned apparent inhibitory effects on bacterial species (e.g., Staphylococcus aureus, Proteusbacillus vulgaris, Salmonella typhosa, Pseudomonas aeruginosa, Bacillus subtilis, Oral streptococcus, E. coli, Stenotrophomonas maltophilia ) . Moreover, EGCG could even express significant antibacterial activity toward food poisoning bacteria and plant pathogenic bacteria. Therefore, due to the higher content of EGCG in GT extract, the greater inhibitory potency towards the bacterial populations was revealed. In addition to EGCG, there were many chemical components with the similar chemical structure (e.g., ortho -dihydroxyl bearing aromatic compounds EC, EGC, ECG, GA, TF) in GT extracts. According to Zuo et al. [34] and Yao et al. [35] , catechins in tea extracts can also include epigallocatechin (EGC), epicatechin gallate (ECG), and epicatechin (EC), which are likely corresponding to the unidentified peaks in the HPLC results. Similar to EGCG, these catechins had high antioxidant capacities and also revealed very strong antibacterial activities. Furthermore, GT extracts obtained through room temperature extraction could also lead to higher contents of inhibitory chemical species than those from higher temperature (e.g., 65 °C) extracts. These findings all supported that the presence of antibacterial components in GT extract may directly alter the distribution of microbial community, further decreasing the power-generating capabilities of MFCs possibly due to reduction of electroactive populations in the community. However, such strong inhibitory effect of tea extract seemed to be different from our prior findings [ 17 , 18 ]. From the comparison upon experimental methods, the extraction temperature seems to be the main-effect reason to evolve such a difference. In fact, different degree of inhibition caused by changes in temperature of extraction were also found in natural products (e.g., medicinal herbs). As a matter of fact, many medicinal herbs may not be appropriate to be extracted at low temperature (e.g., room temperature). According to the practices in Herbal Medicine, macerated and heat-dried or processing (páozhì) under higher temperature heating (65–85 °C) could attenuate some inhibitory chemical species and sometimes even lose power of side effects in medication. For example, artemisinin (Qinghaosu) was found to be effectively against malaria. However, this finding was due to “accidental” modification of the extraction at low temperature by the Youyou Tu's group [42] . After their further separation of acid extract, the natural extract indeed contain very promising antimalarial activity that was even much stronger than well-known chloroquine for clinical mediation to patients with malaria. Moreover, this phenomenon was popularly observed in extracts of active compositions in medicinal herbs to against disease. As revealed in Oh et al. [39] , ethanol extract of GT at 20 °C owned potent antimicrobial activity against all five test pathogens, compared to water extract at 80 °C. That is, ethanol extracts contained higher concentrations of inhibitory chemicals to pathogens than water extracts. This may be due to the favorable solubility of antimicrobial compounds in organic alcohols (e.g., methanol, ethanol) much higher than that in water. In summary, it is noted that a Chinese saying “ every medicine has its side effect ” (yào jí shì dú). As this study and literature [1] , [2] , [3] , [4] , [5] , [6] , [7] , [8] , [9] indicated, evidently there were at least three crucial conditions to affect inhibition potency of GT to bacteria as follows: (1) temperature of extraction (e.g., room, higher temperature), (2) solvent of extraction (e.g., water, ethanol or methanol) and (3) concentration of extract (e.g., powder, concentrated solution). They all affected the role of GT to be either “medicine” (yào) or “poison” (dú). In addition, herbal tolerance and susceptibility of test organism also strongly influenced the responses to be in either “toxicity” or medication. These all strongly suggested that why macerated and heat-dried or processing (páozhì) is of great importance to clinical medication. The novelty of this MFC study was to depict a promising platform to evaluate possible herbal species for its bioenergy-extracting potential without sacrifice of living mice and animals in practice. The scope also pointed out some information of great importance on the threshold criteria of “toxicity” for the characteristic of Camellia tea extract (e.g., when and how it may be “drug” or “poison” to what receptor organisms?) [43] , [44] , [45] , [46] , [47] , [48] , [49] , [50] , [51] , [52] ."
} | 7,758 |
39248369 | PMC11586697 | pmc | 1,403 | {
"abstract": "Abstract Interacting with living systems typically involves the ability to address lipid membranes of cellular systems. The first step of interaction of a nanorobot with a cell will thus be the detection of binding to a lipid membrane. Utilizing DNA origami, we engineered a biosensor with single‐molecule Fluorescence Resonance Energy Transfer (smFRET) as transduction mechanism for precise lipid vesicle detection and cargo delivery. The system hinges on a hydrophobic ATTO647N modified single‐stranded DNA (ssDNA) leash, protruding from a DNA origami nanostructure. In a vesicle‐free environment, the ssDNA coils, ensuring high FRET efficiency. Upon vesicle binding to cholesterol anchors on the DNA origami, hydrophobic ATTO647N induces the ssDNA to stretch towards the lipid bilayer, reducing FRET efficiency. As the next step, the sensing strand serves as molecular cargo that can be transferred to the vesicle through a triggered strand displacement reaction. Depending on the number of cholesterols on the displacer strands, we either induce a diffusive release of the fluorescent load towards neighboring vesicles or a stoichiometric release of a single cargo‐unit to the vesicle on the nanosensor. Ultimately, our multi‐functional liposome interaction and detection platform opens up pathways for innovative biosensing applications and stoichiometric loading of vesicles with single‐molecule control.",
"conclusion": "Conclusion Understanding the interactions between vesicles and probes is not just of biophysical interest—it is a pathway to improving applications in medicine, diagnostics, and molecular biology. Built on the principles of affinity interactions, in this research, we have successfully developed a biosensor predicated on the flexibility and programmability of DNA origami structures. The vesicle sensor utilizes smFRET for the precise detection of lipid vesicles. Central to the effectiveness of the sensor is the hydrophobic ATTO647N dye‐modified DNA leash, whose conformational shifts in the presence or absence of lipid vesicles facilitate distinguishable FRET signals. This observed versatility in response is further augmented by the strategic positioning of cholesterol anchors, underscoring the pivotal role of precise molecular design in dictating vesicle‐sensor interactions. Moreover, the dynamic behavior of the sensor, as evidenced by the FRET shift upon vesicle interaction and the subsequent engagement of the hydrophobic probe with the vesicle, showcases its potential for targeted cargo transfer delivering a precisely adjustable number of molecules. Our findings on the different affinities of hydrophobic and hydrophilic dyes to lipid vesicles further amplify the importance of selecting appropriate probes for specific biosensing applications. Furthermore, the combination of the vesicle sensor with a strand displacement system highlighted the potential of the DNA origami nanosensing structures for conditional molecular transfer with initial vesicle sensing and subsequent cargo transfer. Our design introduces a new dimension to conditional cargo transfer. Unlike traditional delivery systems based on molecular logic gates (e.g., an AND gate that requires the presence of two chemical receptors), our system first senses the vesicle and then triggers cargo transfer through toehold‐mediated strand displacement. \n [32] \n The final experiment with dual cholesterol‐labeled DNA strands highlights a significant improvement in the specificity of cargo transfer within DNA origami systems. Notably, this approach enabled to deliver exactly one desired cargo molecule per trapped vesicle, as opposed to the cargo spontaneously translocating to neighboring non‐trapped vesicles. This platform can therefore become the basis for loading lipid vesicles with a precisely defined number and combination of cargo molecules.",
"introduction": "Introduction In the rapidly advancing field of nanotechnology, the development of dynamic systems that respond to specific molecular signals is becoming increasingly important. These systems, capable of translating molecular behavior into practical applications, have the potential to reshape areas such as biosensing, targeted therapeutics, and precise engineering at the nanoscale. Central to these advancements is the DNA origami technique,[ \n 1 \n , \n 2 \n , \n 3 \n , \n 4 \n , \n 5 \n , \n 6 \n , \n 7 \n ] which offers a reliable and customizable framework for designing nanoscale interactions by having stoichiometric and positional control over the DNA structure and attached functional elements. DNA origami, utilizing the innate programmability of DNA sequences, enables the design and realization of intricate nanostructures with exceptional precision. This unique capability has fostered innovations across nanotechnology, particularly in biosensing.[ \n 8 \n , \n 9 \n , \n 10 \n , \n 11 \n ] With the ability to design custom sensors tailored for specific molecular targets, DNA origami emerges as a powerful tool to address the challenges posed by complex biological systems.[ \n 12 \n , \n 13 \n , \n 14 \n , \n 15 \n , \n 16 \n , \n 17 \n , \n 18 \n , \n 19 \n ] Among the challenges, membrane systems and especially, lipid vesicles stand out. These membranous sacs play pivotal roles in diverse cellular functions, from molecular transfer and signaling to compartmentalization.[ \n 20 \n , \n 21 \n ] Therefore, detecting and characterizing lipid vesicles is of great importance. Sensors based on DNA origami can offer a subtle understanding of how lipid vesicles behave, with the potential to probe, detect, and even manipulate their activities.[ \n 22 \n , \n 23 \n , \n 24 \n , \n 25 \n , \n 26 \n , \n 27 \n ] Bridging the innovative capabilities of DNA origami to the intricate world of lipid vesicles can provide deeper insights into vesicular behaviors and potentially unlock new therapeutic opportunities.[ \n 28 \n , \n 29 \n , \n 30 \n , \n 31 \n ] DNA origami has uses beyond just detection. As modern medicine and technology advance, the need for precise and controlled cargo transportation at the nanoscale becomes increasingly evident. From targeted drug delivery to the transfer of specific molecular agents, the ability to move and release cargo with specificity could reshape therapeutic strategies. In one of the pioneering works, Douglas et al. developed a DNA nanorobot that delivers payloads to cells and changes its structure to release them, showing promise for targeted cell therapy. \n [32] \n Thubagere et al. created a self‐powered DNA robot with three functional domains that can move across a DNA origami sheet and sort two types of molecular cargoes to their respective destinations using a simple algorithm. \n [33] \n In a more recent work involving lipid vesicles, Baumann et al. created a DNA mesh around lipid vesicles for drug delivery, releasing the dye calcein upon triggering. This method increased cytotoxicity in HEK293T cells and holds potential for targeted chemotherapy delivery. \n [34] \n In our research, we have developed a multifunctional system that is not only capable of sensing the presence of a vesicle, but also has the potential to deliver a desired cargo directly to the vesicle it is attached to. By leveraging the capabilities of DNA origami, integrating the precision of single‐molecule FRET (smFRET), and utilizing specific binding interactions, we have created a biosensing and single‐molecule cargo transfer system. Building on our experience with DNA origami nanosensors for lipid vesicle characterization, \n [27] \n herein we introduce a DNA origami biosensor tailored for lipid vesicle detection. This system utilizes an ATTO647N labeled single‐stranded DNA (ssDNA) protrusion, a donor dye ATTO542, and cholesterol anchors. It capitalizes on smFRET and the affinity interactions of ATTO647N, allowing for real‐time vesicle sensing and the potential for triggered cargo transport of single molecules. In our system, ATTO647N serves a dual role: not only it is the acceptor dye in the FRET process, but its hydrophobic nature also drives its interaction with lipid bilayers. It sets the stage for innovative biosensing applications and the transport of molecules, particularly by delivering desired single cargoes to lipid membranes in a localized or diffusive manner.",
"discussion": "Results and Discussion The vesicle sensor is crafted from a rectangular DNA origami nanostructure[ \n 2 \n , \n 35 \n ] with the dimensions of 70×100 nm. It features a 12 nucleotide (nt) long ssDNA leash, modified with an ATTO647N fluorophore which serves as the main probe for vesicle sensing (Figure 1a ). This probe, due to its hydrophobic and cationic properties, anchors itself in phospholipid vesicles, a behavior noted in prior studies.[ \n 36 \n , \n 37 \n , \n 38 \n ] Moreover, the sensor is equipped with an internally labeled ATTO542 fluorophore, serving as a donor for FRET (Figure 1a and Figure S1). We postulate that the relative position of the acceptor probe will change based on the presence or absence of lipid vesicles (Figure 1b ). In a vesicle‐free environment, the ssDNA probe naturally adopts a coiled conformation due to its flexible and dynamic nature. This coiling behavior is driven by the entropy of the polymer, hydrophobic interactions of the bases, and electrostatic repulsion along the phosphate backbone. Upon vesicle binding to cholesterol anchors on the DNA origami, the interaction of the hydrophobic ATTO647N dye with the membrane stretches the ssDNA out towards the lipid bilayer, reducing FRET efficiency due to the increased distance between the donor and acceptor dyes. For anchoring the sensor to modified glass coverslips, biotin attachments are located at the four corners of the DNA origami structure (Figure 1a and Figure S1). The sensor includes four cholesterol‐based anchors (Figure 1a and Figure S1) to facilitate the capture of lipid vesicles by providing multiple interaction sites. The parallel arrangement of these anchors ensures structural stability and maintains a defined distance between the sensor unit and the cholesterol line.[ \n 39 \n , \n 40 \n ]\n Figure 1 Concept and validation of the vesicle sensor. (a) A rectangular DNA origami base equipped with a sensing unit consisting of a 12 nt ssDNA leash labeled with an ATTO647N acceptor and an ATTO542 donor positioned on the DNA origami base. The extended length of the ssDNA leash is 7.56 nm. Cholesterol anchors, strategically placed at various distances for vesicle capture, and biotin moieties for surface attachment are also featured. Note: Illustrations are not to scale. Please refer to Supplementary Figure S2 for a scaled diagram. (b) These sensors have the capability to bind to BSA‐Biotin‐NeutrAvidin‐treated glass coverslips using biotin moieties. Without lipid vesicles (left), the ssDNA sensing probe adopts a coiled configuration, positioning it closer to the donor dye, resulting in higher FRET. When lipid vesicles are present (right), the sensing probe elongates to permeate the lipid bilayer, driven by the hydrophobic nature of the ATTO647N fluorophore. Due to the increased distance between the probe and the donor dye, a decreased FRET is observed. (c) The image at the top presents a superimposed TIRF image with the donor dye (D) shown in cyan, and the acceptor (A) in magenta. Gray spots denote sensors that incorporate both the donor and acceptor dyes. An exemplary single‐molecule FRET (smFRET) trace at the bottom illustrates the fluorescence intensity over a period, detailing the donor excitation–donor emission (I DD ) channel (cyan), the donor excitation–acceptor emission (I DA ) channel (gray), and the acceptor excitation–acceptor emission (I AA ) channel (magenta). Mean FRET efficiencies are calculated from the I DD and I DA channels. Scale bar is 5 μm. (d) FRET efficiency distributions for vesicle sensors with cholesterol anchors placed at 15 nm distance from the probe position, in scenarios both without (top) and with (bottom) lipid vesicles. Distributions are shown for the hydrophobic sensing probe with ATTO647N and (e) the hydrophilic control probe with Alexa Fluor 647. Accompanying illustrations in the plots suggest potential conformations of the probe. The error refers to the standard deviation (SD). Number of molecules used in the FRET calculations are as follows; for the sensor with hydrophobic ATTO647N probe 111 molecules were used without LUVs and 131 with LUVs and for the sensor with hydrophilic Alexa Fluor 647 probe 127 molecules were used without LUVs and 112 with LUVs. To visualize individual vesicle sensors, we employed smFRET using total internal reflection fluorescence microscopy (TIRF) on a commercial fluorescence microscope (Nanoimager S, ONI Ltd., UK) with green‐red alternating laser excitation (ALEX).[ \n 41 \n , \n 42 \n ] Intensity transients of single spots were extracted from TIRF videos using the iSMS software based on Matlab. \n [43] \n In Figure 1c , a false‐color image displays donor dye emission in cyan, acceptor in magenta, and their overlay in gray. We verified the fluorescence as originating from single vesicle sensors by observing single‐step photobleaching. For instance, in Figure 1c , the acceptor dye photobleaches after 11 seconds, leading to an increased, unquenched donor fluorescence (I DD ), while the FRET signal (I DA ) drops to zero. This synchronized response confirms the presence of a single DNA origami structure exhibiting FRET. We further tracked acceptor emission following its excitation (I AA ) to study associated photophysical behaviors and prioritize initial acceptor bleaching events. From the intensity data of both the I DD and I DA channels during energy transfer, the FRET efficiency of individual sensors was quantified as \n \n \n Here, I DA is corrected to account for the direct excitation of the acceptor at the donor excitation wavelength and for any donor emission leakage into the acceptor emission channel. The γ correction factor compensates for the different quantum yields of the dyes and wavelength‐dependent efficiencies of the detection (see Supporting Information for detailed materials and methods). For each sample, we analyzed around 100 molecules and represented the FRET efficiencies in histograms, complemented with Gaussian fits where relevant. To validate our design, we contrasted the FRET efficiencies of the sensor both in the absence and presence of lipid vesicles. For this experiment, considering the highest possible overlap with the leash length and 100 nm lipid vesicles, we used sensors with cholesterol anchors placed at a 15 nm distance from the probe position. The calculated optimal distance using the ideal chain model for a 12 nt ssDNA leash and 50 nm radius vesicles is approximately 14.93 nm, which closely matches our experimental setup (Please refer to the Supporting Information Appendix I for the calculation details). After immobilizing the sensors on BSA‐Biotin‐NeutrAvidin‐treated glass coverslips, smFRET measurements were performed. In the absence of vesicles, the mean FRET value was 0.83±0.03 (standard deviation of the mean, SD). Upon introducing 1 nM of 100 nm 1,2‐Dioleoyl‐sn‐glycero‐3‐phosphocholine (DOPC) vesicles (see Supporting Information for the details of lipid vesicle preparation) with a 1‐hour incubation, we observed an additional population with a mean FRET value of 0.61±0.06 (Figure 1d ). This shift confirms the effective binding of lipid vesicles to the DNA origami platform and suggests the binding of the sensing unit to the vesicle membrane. A remaining fraction of 20 % with a mean FRET of 0.81±0.03 likely represents either sensors that do not have vesicles in their vicinity or sensors where the probe is unable to successfully engage with the incorporated vesicles. To further substantiate the role of affinity interactions in the sensor mechanism, the hydrophobic ATTO647N fluorophore was substituted with Alexa Fluor 647 on the ssDNA probe. Previous research has demonstrated that Alexa Fluor 647 exhibits minimal interaction with lipid vesicles due to its hydrophilic nature.[ \n 36 \n , \n 44 \n ] When analogous experiments were conducted without and with lipid vesicles for the sensors equipped with Alexa Fluor 647, the mean FRET values remained consistent at 0.78±0.02 (Figure 1e ). The notably homogeneous and narrow distributions for the Alexa Fluor 647 probe further underscore the assertion that the distinct behavior of the sensor arises from the hydrophobic affinity interactions between the ATTO647N probe and lipid vesicles. Building on our observations, we investigated the influence of the distance of the FRET probe to the cholesterol anchors. In addition to sensors with cholesterol anchors at 15 nm distance, we assembled vesicle sensors with cholesterol moieties positioned at 5 nm and 30 nm distance from the probe. Each sensor was subjected to smFRET studies both with and without lipid vesicles. For the sensor with the cholesterol anchors at a 30 nm distance from the leash, the smFRET results (Figure 2a ) reported mean FRET values of 0.81±0.04 and 0.81±0.03 for scenarios without and with vesicles, respectively. The data suggests that, even when vesicles are present, the probe remains in its coiled state because the vesicles are too distant to be reached by the ATTO647N anchor. This design confirms that the FRET contrast arises solely when the ATTO647N probe anchors into the lipid bilayer—an event only possible when the vesicle is close enough to allow the probe to stretch toward it.\n Figure 2 Influence of the cholesterol anchoring distances on the sensor both in the absence and presence of lipid vesicles. The distributions of FRET efficiency for the vesicle sensors, both without and with lipid vesicles, is depicted for (a) 30 nm, (b) 15 nm, and (c) 5 nm cholesterol‐FRET probe distances. Illustrations accompanying the data highlight the positions of the cholesterol anchors and potential movement patterns of the sensing probe. The error refers to the standard deviation (SD). Number of molecules used in the FRET calculations are as follows; for the sensor with 30 nm cholesterol anchors 97 molecules were used without LUVs and 113 with LUVs, for the sensor with 15 nm cholesterol anchors 111 molecules were used without LUVs and 131 with LUVs, and for the sensor with 5 nm cholesterol anchors 85 molecules were used without LUVs and 112 with LUVs. In the sensor variant with cholesterols at a 15 nm distance from the sensor, as already presented in Figure 1d , a clear FRET shift occurred based on vesicle presence, underlining the effect of proximity (Figure 2b ). However, the results took a captivating turn when cholesterol anchors were only 5 nm from the probe. Independent of lipid vesicle presence, these sensors exhibited wider FRET distributions with comparable mean values (0.75±0.07 without vesicles and 0.71±0.09 with vesicles, Figure 2c ), yet distinct from the other tested distances. We attribute this observation to the strong hydrophobic interactions that allow the ATTO647N probe to already interact with closely positioned cholesterol anchors. Consequently, given the distinctive and reliable FRET shift observed with the 15 nm spacing, we chose to utilize sensors with cholesterol moieties at this distance for the remainder of our study. Additionally, a noteworthy observation was that, upon testing the 5 nm cholesterol configuration with a control system featuring Alexa Fluor 647, there was no apparent difference in FRET distributions (Figure S3). In our pursuit to understand the sensor‘s response to varying lipid vesicle sizes, we further examined its behavior with 50 nm, and 200 nm DOPC vesicles using the 15 nm cholesterol as well as a 20 nm cholesterol configuration (Figure S4‐a). Notably, while the 15 nm cholesterol‐based sensor exhibited minimal variation across vesicle sizes (Figure S4), the 20 nm variant revealed a discernible peak in its interaction with the 200 nm DOPC vesicles, as illustrated in Figure S4‐c. This new population, however, constituted less than 10 % of the overall sample. These findings indicate that the positioning of cholesterol in relation to the probe can influence the affinity of the sensor towards differently sized vesicles. Although the observed new distribution is a small fraction of the overall sample, it underscores the importance of meticulous design and adaptation in probe creation for vesicle interactions. Tailoring probes to align with specific vesicle dimensions can optimize their performance and extend their versatility in multiple disciplines.[ \n 45 \n , \n 46 \n , \n 47 \n , \n 48 \n ] Building upon the insights from our prior experiments and recognizing the transformative potential of cargo transport systems in molecular and nanoscale research, we delved deeper into an intricate investigation employing the ATTO647N FRET acceptor probe as membrane cargo within a strand displacement system. A 17 nt ssDNA was protruding from the probe position on the DNA origami and a 17 nt ATTO647N probe was attached to this protrusion, preserving a 5 nt toehold at the forefront (Figure 3a ). The cargo transfer system involved a 17 nt cholesterol‐modified displacer strand, which has a stronger affinity for the ATTO647N probe. Upon interaction, this displacer strand binds to the probe at the toehold segment, leading to its displacement from the origami structure. More precisely, as we noted higher FRET values without vesicles and a decrease upon vesicle introduction, we further anticipated witnessing a loss of the FRET signal but a persisting colocalization of green and red emission after the displacement of the ATTO647N probe. We initially expected colocalized spots after introducing the displacer strand because the ATTO647N‐labeled cargo, upon displacement, was designed to remain associated with the lipid vesicles bound to the DNA origami structure. This expectation is based on the assumption that the cholesterol‐modified displacer strand would transfer the cargo directly to the vesicles captured by the DNA origami, maintaining proximity due to the membrane interaction. Initial smFRET imaging without lipid vesicles revealed a mean FRET value of 0.39±0.04. This lower initial FRET value compared to the previous sensing system (0.83±0.03) is attributed to the structural differences between the two designs. In the initial vesicle sensing system, the probe is a flexible ssDNA leash, allowing close proximity of the donor and acceptor fluorophores. In contrast, the cargo transport system has a longer (17 nt) protrusion including a 12 nt duplex DNA region, resulting in a more extended configuration for the duplex part and greater distance between the donor and acceptor, thereby reducing the FRET efficiency. Presence of lipid vesicles reduced this value to 0.23±0.06, corroborating the consistent working principle of the sensor (Figure 3b and Figure 3c , left and middle panels). This new vesicle sensing and cargo transporting system design showed a unimodal distribution after LUV incorporation, indicating no unbound fraction (Figure 3b ). By estimating the bound fractions, we observed a notable increase from 80 % in the initial sensor system to 95 % in the cargo transfer system design (Figure S5). It is noteworthy that both ssDNA and dsDNA probes exhibit marked FRET changes upon vesicle docking. While ssDNA is flexible and can adopt various conformations, dsDNA is more rigid due to its stable double‐helix structure.[ \n 49 \n , \n 50 \n , \n 51 \n , \n 52 \n ] In our design, the cargo transfer system design includes a probe having both dsDNA and ssDNA regions. The flexibility of the ssDNA parts allows for significant conformational changes, even when combined with the more rigid dsDNA segments.\n Figure 3 Triggered cargo transfer to the lipid vesicles. (a) Schematic illustrations detailing the cargo transfer system. A 17 nt strand protrudes from the DNA origami base, binding to a complementary 17 nt strand labeled with ATTO647N, leaving a 5 nt toehold exposed. The system initially exhibits higher FRET levels in the absence of lipid vesicles. Upon interaction with lipid vesicles, the ATTO647N‐labeled strand anchors into the lipid bilayer, leading to reduced FRET. After cargo transfer by strand displacement, the system shows no FRET due to increased separation between the FRET pair. (b) FRET histograms displaying the FRET characteristics of the system under different conditions: without lipid vesicles (left), with lipid vesicles (middle), and post‐cargo transfer (right), where no FRET is observed. (c) Superimposed TIRF images after green‐only excitation. The systems without vesicles (left) and with vesicles (middle) show clear FRET, evidenced by colocalization. After cargo transfer (right), only green spots are observed, indicating the loss of FRET and absence of colocalization. (d) Superimposed TIRF images after both green and red excitation. In the absence (left) and presence (middle) of lipid vesicles, high degree of colocalization is observed. Following cargo transfer (right), the colocalization is lost, coinciding with the absence of FRET. However, numerous red spots remain at other locations. Scale bar is 5 μm. Number of molecules used in the FRET calculations are as follows; 160 molecules were used without LUVs and 136 with LUVs. The experiment took an interesting development when 1 nM of the 17 nt cholesterol‐labeled displacer strand was introduced. The FRET signal on the DNA origami nanosensors immediately vanished, yet a non‐colocalizing red emission, primarily at neighboring spots, persisted on the images (Figure 3b and Figure 3c , right panel). This red emission provided compelling evidence of the probe being successfully detached from the origami. Prior to cargo transfer, the system exhibited a high degree of colocalization, as evidenced in Figure 3d , left and middle panels. However, upon introduction of the displacer strand, instead of the anticipated colocalized spots, numerous red‐only spots appeared (Figure 3d , right panel). As single cholesterol can diffuse in and out of lipid vesicles,[ \n 53 \n , \n 54 \n ] the transferred probe can subsequently relocate to surrounding lipid vesicles. We theorize that the DNA displacer strand and cargo with a single cholesterol still exhibits mobility across vesicles and can bind to free lipid vesicles also adhering to the surface. \n [53] \n This phenomenon resulted in diminished colocalization of the red fluorescent cargo within the DNA origami sensors (and their trapped vesicles). Furthermore, the evident post‐displacement motion in these non‐colocalized red spots hints at the dynamic diffusion of the fluorescent ATTO647N cargo transfered with single‐cholesterol‐modified displacer strand in and across lipid vesicles (Supporting Information Movie 1). Supporting these observations, when lipid vesicles in the system were deliberately ruptured using a 0.05 % Tween20 buffer, \n [55] \n almost all red signals disappeared, reaffirming the specific vesicle‐probe interaction (Figure S6‐d). A separate evaluation of the impact of Tween20 on the system showed it only disrupts lipid vesicles and thereby resets the sensor to its original state without vesicles (see Figure S7). To fortify our hypothesis, a control test without vesicles was carried out. Upon introducing the cholesterol‐labeled displacer strand, a near‐complete disappearance of the red signal was evident which highlights the effectiveness of the strand in displacing the probe (Figure S8). In the absence of lipid vesicles, the displacement process was considerably slower, taking almost an hour for the red signal to fade, whereas in the presence of the vesicles, the red signal faded in just tens of seconds. Supposedly, the cholesterol displacer strand first binds to the lipid vesicles, locally upconcentrating the displacer strand. This upconcentration close to the probe results in increased transfer kinetics. After our initial observations of cargo transfer using single‐cholesterol modified displacer strands, we aimed to refine the specificity of cargo transfer to ensure that it remains within the vesicle bound to the DNA origami structure, instead of spontaneously translocating to neighboring vesicles. As indicated before, previous research has shown the mobility of cholesterol‐labeled DNA strands across vesicles.[ \n 53 \n , \n 54 \n ] To address this, we adopted a strategy involving the use of a dual cholesterol‐labeled DNA strand for the strand displacement reaction. We engineered a 39 nt long ssDNA with a cholesterol‐TEG modification to which our ATTO647N‐labeled cargo strand can bind at the 3’ end. An additional 18 nt ssDNA with a 3′ end cholesterol‐TEG modification was designed to bind to the 5′ end of the long DNA strand creating a double‐stranded configuration with enhanced vesicle binding stability. With a 4 nt Thymine (T) spacer between the hybridized regions, we aimed to provide flexibility to the construct (Figure 4a ).\n Figure 4 Targeted cargo transfer using a dual cholesterol‐labeled displacer. (a) Illustration of the dual‐cholesterol displacer consisting of a 39 nt ssDNA with a 3′ end cholesterol‐TEG modification, linked to an ATTO647N‐labeled 17 nt ssDNA at its 3′ end. Additionally, an 18 nt ssDNA with a 3′ end cholesterol modification is bound to the 5′ end of the long strand, separated by a 4 nt thymine (T) spacer. On the right is the depiction of DNA origami vesicle sensor with a bound lipid vesicle, illustrating the post‐transfer scenario with the new construct. (b) % colocalization of the cargo transfer systems with single and dual cholesterol displacers compared to the system prior cargo transfer. (c) Histogram of FRET efficiency post‐cargo transfer, displaying negligible FRET values, indicative of successful cargo displacement with minimal proximity between FRET pairs. (d) Superimposed TIRF microscopy images following cargo transfer; left image shows detection after only green excitation to highlight the loss of FRET with an encircled spot to exemplify a rare FRET event, and the right image under green and red excitation, illustrating the colocalization and confirming the presence of cargo within the system. Scale bar is 5 μm. Number of molecules used in the FRET calculations is 90. Prior to experimentation, the two cholesterol‐modified strands were pre‐incubated in a 1 : 1 molar ratio at 37 °C for 2 hours, forming the new displacer strand. This construct was introduced to the system following the standard protocol for vesicle incubation and FRET monitoring. Upon addition of 1 nM of the dual cholesterol‐labeled displacer strand, we observed an immediate loss of FRET but a remaining colocalization (Figure 4b ). The loss of FRET was supported with a histogram showing negligible FRET values (Figure 4c ). The occasional FRET events (encircled spot in the left image in Figure 4d ) are likely due to sensors either failing to capture vesicles or to cargo translocated near the FRET‐sensitive region of the sensor. Contrary to earlier findings, in this case, we observed a high level of control over the cargo transfer, as evidenced by the complete loss of FRET population (Figure 4c ). This signifies that almost every molecule could be precisely transferred, a fact further highlighted by not losing colocalization of donor and acceptor fluorophores before and after the transfer (Figure 4b ). The absence of mobility in the red spots further corroborated the effectiveness of the dual cholesterol modification in achieving targeted and stable cargo delivery (Supporting Information Movie 2). This modification signifies an advancement in the precision of cargo transport mechanisms via DNA origami structures, highlighting the potential for highly specific molecular and stoichiometric delivery systems in nanoscale applications. These findings highlight the importance of structural modifications in enhancing the specificity and efficacy of DNA origami‐based delivery systems."
} | 7,997 |
27065782 | PMC4814530 | pmc | 1,405 | {
"abstract": "The development of power-efficient neuromorphic devices presents the challenge of designing spike pattern classification algorithms which can be implemented on low-precision hardware and can also achieve state-of-the-art performance. In our pursuit of meeting this challenge, we present a pattern classification model which uses a sparse connection matrix and exploits the mechanism of nonlinear dendritic processing to achieve high classification accuracy. A rate-based structural learning rule for multiclass classification is proposed which modifies a connectivity matrix of binary synaptic connections by choosing the best “k” out of “d” inputs to make connections on every dendritic branch ( k < < d ). Because learning only modifies connectivity, the model is well suited for implementation in neuromorphic systems using address-event representation (AER). We develop an ensemble method which combines several dendritic classifiers to achieve enhanced generalization over individual classifiers. We have two major findings: (1) Our results demonstrate that an ensemble created with classifiers comprising moderate number of dendrites performs better than both ensembles of perceptrons and of complex dendritic trees. (2) In order to determine the moderate number of dendrites required for a specific classification problem, a two-step solution is proposed. First, an adaptive approach is proposed which scales the relative size of the dendritic trees of neurons for each class. It works by progressively adding dendrites with fixed number of synapses to the network, thereby allocating synaptic resources as per the complexity of the given problem. As a second step, theoretical capacity calculations are used to convert each neuronal dendritic tree to its optimal topology where dendrites of each class are assigned different number of synapses. The performance of the model is evaluated on classification of handwritten digits from the benchmark MNIST dataset and compared with other spike classifiers. We show that our system can achieve classification accuracy within 1 − 2% of other reported spike-based classifiers while using much less synaptic resources (only 7%) compared to that used by other methods. Further, an ensemble classifier created with adaptively learned sizes can attain accuracy of 96.4% which is at par with the best reported performance of spike-based classifiers. Moreover, the proposed method achieves this by using about 20% of the synapses used by other spike algorithms. We also present results of applying our algorithm to classify the MNIST-DVS dataset collected from a real spike-based image sensor and show results comparable to the best reported ones (88.1% accuracy). For VLSI implementations, we show that the reduced synaptic memory can save upto 4X area compared to conventional crossbar topologies. Finally, we also present a biologically realistic spike-based version for calculating the correlations required by the structural learning rule and demonstrate the correspondence between the rate-based and spike-based methods of learning.",
"introduction": "1. Introduction There has been significant research in the last decade aimed at designing neuromorphic systems which can emulate the architectural and computational principles of the brain. These systems exploit the spike-based operation of human brain, with minimal power consumption during long inactive periods, to implement power-efficient neuromorphic devices. Moreover, this attempt to mimic the neuronal function can enable us to design event-driven, compact hardware systems which can provide efficient, real-time, intelligent solutions for several applications like robotics and brain-machine interfaces. Conversely, the neuromorphic systems can be used to understand the working principles of brain. The development of event-driven sensors like the artificial retina (Lichtsteiner et al., 2008 ; Posch et al., 2011 ; Serrano-Gotarredona and Linares-Barranco, 2013 ) and cochlea (Liu et al., 2013 ), which produce continuous and asynchronous spikes encoding the sensory information, make it essential to interface these sensors with spike-based classifier systems to enable the classification of real-world complex stimuli. The spike classification algorithms designed to this effect can also attain large computational power of spiking neural networks (Maass and Schmitt, 1999 ). The spike-based neuromorphic systems implemented in very-large-scale integration (VLSI) technology consist of hybrid analog-digital circuits, where the neuronal and synaptic computations are usually performed in analog form on the chip (though TrueNorth Merolla et al., 2014 and Spinnaker Painkras et al., 2013 are notable exceptions) while the synaptic connectivity information is stored on or off-chip in a digital memory. An asynchronous communication protocol called the address-event representation (AER; Boahen, 2000 ; Choi et al., 2005 ; Vogelstein et al., 2007 ; Serrano-Gotarredona et al., 2009 ), is used to transmit neuronal spikes between neuromorphic chips on a shared fast digital bus. The AER-based neuromorphic systems have the added advantage of reconfigurability since the configuration details of a network are stored in a separate memory, thereby giving the user flexibility to reconfigure the network connectivity. However, the statistical variations in VLSI devices which reduce the accuracy of the synaptic weights are a major cause for concern in attaining performance comparable to software simulations. To mitigate the effect of increasing device mismatch with progressively shrinking transistor sizes, the usual solutions are to increase device sizes or employ a large number of neurons, both of which increase chip area. For example, a spiking network classifier implemented on a neuromorphic hardware system achieved performance comparable with standard machine learning linear classifier and exhibited tolerance against variability by using population coding (Schmuker et al., 2014 ). However, a limitation of this model is the large number of high resolution weights used to attain the reported performance. Similarly, spike classifiers consisting of Restricted Boltzmann Machine (RBM) constructed with integrate and fire neurons, use a large number of recurrent synaptic connections (O'Connor et al., 2013 ; Neftci et al., 2014 ) rendering these algorithms impractical for compact VLSI implementation. A simple and robust solution to the problem of device mismatch can be obtained by using binary synaptic weights. A spike-based STDP learning rule using bistable synapses was implemented in Brader et al. ( 2007 ) with the VLSI implementation in Mitra et al. ( 2009 ) to classify complex stimuli. A pool of neurons was used to improve the classification accuracy by employing a voting scheme, which again leads to the problem of increased number of synapses. Digital implementations do not suffer from mismatch issues like their analog counterparts; however, the usage of a lot of memory to implement high resolution weights for deep networks increases chip area significantly. A spike classification model proposed in Hussain et al. ( 2013 , 2015 ) offers a solution to the problem of large number of synaptic weights by using a structural plasticity based learning rule which involves formation of sparse connections with binary weights. Moreover, it was shown that a simple correlation-based learning rule provides an alternative to the traditional weight-based learning rules and is more suitable for implementation on neuromorphic chips. The problem of reduced memory capacity of a network with binary synapses as compared with that of continuous-valued synaptic weights (Senn and Fusi, 2005 ) is alleviated by the use of nonlinear dendritic processing, which emerges due to the presence of voltage gated ion channels (Magee, 2000 ; London and Hausser, 2005 ). A limitation of this method is that it uses a preassigned network size and the number of dendrites and synapses required for solving a classification problem of given complexity is not known. Hence, it is desirable to use an approach which learns to allocate the required number of synaptic resources for a specific problem. Several adaptive approaches have been used to control the network size and structure. A constructive approach involves training with a minimal architecture, for example a single hidden-layered network with one hidden neuron, and then adding further hidden units and weights to implement the desired mapping (Kwok and Yeung, 1997 ; Lahnajarvi et al., 2002 ; Islam et al., 2009 ). The second approach for automating the design of appropriate neural network is by pruning in which a network larger than necessary is trained and then redundant connections and/or neurons are removed until an acceptable solution is obtained. A group of pruning algorithms eliminate a neuron or a connection which have the least effect on the error function (Karnin, 1990 ). The other group of pruning algorithms are referred to as regularization methods which add a penalty term proportional to the sum of weights to the objective function. Hence, the unnecessary weights are driven to zero during training and are eliminated in effect (Kwok and Yeung, 1996 ). Several other pruning methods are reviewed in Islam et al. ( 2009 ) and Reed ( 1993 ). Another class of algorithms that are developed to control the network size and structure use a hybrid approach of combining the constructive and pruning methods (Fiesler, 1994 ). The growth and pruning algorithms discussed here have not considered the number of dendrites as an adaptive parameter. In this paper, we present a multiclass classifier using neurons with nonlinear dendrites (NNLD) and a structural learning rule for finding sparse, binary weight matrices. The unique contributions of this work are: (1) Showing that for ensembles of NNLD with the same number of synapses, having a single dendritic branch (perceptron) or having too many dendrites are sub-optimal; the optimal cases is a moderate size of the dendritic tree. (2) Developing an algorithm that adapts the size of the dendritic tree for each class according to the difficulty of classifying that pattern category. (3) Applying this network to the problem of handwritten digit recognition task from MNIST and MNIST-DVS datasets to show its benefit in achieving high accuracy with very small memory usage for weights. (4) Demonstrating memory size reductions possible in VLSI implementations by using this training method. The paper is organized as follows. First, the rate-based multiclass spike pattern classification model is presented in Section 2.1.1, followed by the description of an ensemble method which combines the outputs of several dendritic classifiers to obtain improved classification accuracy in Section 2.1.2. In Section 2.1.3, we propose an adaptive structural learning scheme which involves growth of the network by adding dendrites based on the progress of learning process. The performance of different learning schemes on classification of handwritten digit samples is demonstrated in Sections 3.2–3.4, while noise sensitivity analysis is in Section 3.5 and analysis of dendrite weights in Section 3.6. Next, in Section 3.7, we present an approach to optimize the performance of our method by utilizing theoretically determined optimal neuron topology. Finally, the evaluation of our algorithm on event-based MNIST-DVS dataset is presented in Section 3.8 followed by a comparison of the performance of our model with the results obtained using other spike-based classification algorithms in Section 3.9. The relevance of our work in terms of the biological plausibility, comparisons with other related studies, hardware considerations and a discussion of future work is included in Section 4.",
"discussion": "4. Discussion Here, we discuss the neurobiological relevance of our work and its potential for future hardware implementation. We also compare our method with other studies based on these neurobiological mechanisms. Finally, we discuss the future directions of our work. 4.1. Role of dendritic nonlinearity in neuronal processing Several experimental evidences support the nonlinear processing in dendrites including active backpropagation of axonal spikes into the dendritic tree and dendritic spikes (Hausser et al., 2000 ; Schiller et al., 2000 ). However, there are not many evidences regarding the role of these nonlinear mechanisms in synaptic integration in pyramidal neurons. Experimental and compartmental modeling studies of pyramidal neurons have indicated that nearby synaptic inputs on the same dendrite sum sigmoidally while inputs on different dendrites sum up linearly (Poirazi et al., 2003b ; Polsky et al., 2004 ). These findings support the notion of a two-layer model of neurons, thereby having implications for the synaptic plasticity and the computational capacity of cortical tissue. Mel and his group presented several computational studies to elucidate the role of dendrites in neuronal processing. (Mel, 1991 ; Poirazi et al., 2003b ). In more recent studies, an abstract two-layer model using sigmoidal dendritic nonlinearity was shown to predict the firing rate of a detailed compartmental model of a pyramidal neuron (Poirazi et al., 2003a ) and much larger storage capacities were computed for dendritic neurons with degree 10 polynomial nonlinearity in Poirazi and Mel ( 2001 ). In contrast to these studies, we use a more hardware-friendly quadratic nonlinearity which is easier to implement than a sigmoid or a high order polynomial. We also modify the learning rule to adapt the structure of the dendritic tree of different neurons in the network according to difficulty of the classification task. 4.2. Structural plasticity as a learning mechanism The phenomenon of structural plasticity involving formation and elimination of synapses thereby leading to alterations to the cortical wiring diagram (Chklovskii et al., 2004 ; Butz et al., 2009 ) provides for alternative form of long term information storage in addition to the traditional synaptic weight plasticity. The information storage capacity associated with structural plasticity lies in the ability to change wiring diagram in a sparsely connected network, which provides a large number of functionally distinct circuits available to encode information (Chklovskii et al., 2004 ) and hence has important implications for the computational properties of the network. The computational modeling study by Poirazi and Mel ( 2001 ) demonstrated the use of structural plasticity to modify binary synaptic connections on dendritic branches. Similar to our model, a poorly performing active synapse is eliminated and replaced by the best performing synapse in a set of silent synapses. However, our learning rule is simple and easier to implement in hardware systems as compared with the learning rule used by Poirazi and Mel ( 2001 ). 4.3. Binary synapses: computational challenges There is accumulating experimental evidence that biological synapses exist in only a small number of states which can be restricted to even two states (Petersen et al., 1998 ; O'Connor et al., 2005 ). The use of synapses with only one or two bits of long-term information has severe implications for the storage capacity of networks working as classifiers or associative memories with capacity for binary synapses reducing by more than half as compared to the capacity using continuous-valued synapses (Senn and Fusi, 2005 ). Some studies have presented learning algorithms as biological solutions to deal with the reduced storage capacity of networks with binary synapses. A stochastic spike-driven synaptic plasticity rule was used to train a network of binary synapses, where a pool of output neurons was used to calculate the classification accuracy by a voting mechanism (Brader et al., 2007 ). This results in a large number of synapses being used. In comparison to this study, our model employs a sparsely connected network of binary synapses which learns by using a correlation-based structural plasticity rule. The use of dendritic nonlinearity yields higher computational power thereby alleviating the problem of reduced capacity of binary weights. Also, the adaptive learning of number of dendrites according to problem complexity reduces the number of synapses compared to a brute force approach. Hence, our model can achieve higher accuracy by utilizing a small number of binary synapses. 4.4. Binary synapses and structural plasticity: considerations for hardware implementation Over the past decade, several low-power neuromorphic systems have been built to perform classification of spike patterns. A common feature in several of these systems is the usage of binary synapses (Indiveri et al., 2006 ; Arthur and Boahen, 2007 ; Mitra et al., 2009 ). One reason for this is the ease with which two states can be stored in current CMOS technology using a latch. This also makes the system more robust to parametric variations due to mismatch in device - it is unlikely that high resolution weights can be obtained from a massive array of analog synapses due to a combination of systematic and random mismatch (Linares-Barranco et al., 2003 ). Even a recently introduced multi-core asynchronous digital chip (Merolla et al., 2014 ) uses a limited number of weight values per axon per core. Our algorithm is consistent with this philosophy of low-resolution weights since we limit the number of synaptic connections per dendrite and each connection is a binary value. Effectively each input afferent (or axon) connects with a small integer weight to a dendrite. Another advantage of our architecture is that the learning happens by modifying connectivity patterns of the network. In most current event-based neuromorphic systems, this connection matrix is stored in a separate memory (Liu, 2014 ) either on or off chip. This implies that since our hardware architecture enforces sparsity, we require less memory and memory reads to store and access connection information respectively. Before expanding on this point, it is important to note that we are not considering advantages of hardware implementations of on-chip learning to find optimal connections (though we have presented some initial results on the same in Roy et al., 2014b ). We are only comparing the advantages of using our proposed architecture to implement the final network and using structural plasticity to reduce the memory requirement of this implementation. In this context, it should be noted that normal weight learning methods do not necessarily produce sparse weights and simple quantization of small weights to zero values increase errors. This was shown to be true for an ensemble of perceptrons trained by the p-delta algorithm in Roy et al. ( 2014a ). More recently, there have been efforts to improve rounding algorithms to reduce weight resolution for efficient implementation of deep networks (Muller and Indiveri, 2015 ). Even with these methods, a two layer fully connected neural network with 500 hidden nodes needs at least 4 bits per synaptic weight to achieve comparable performance (~96%) as our network on the MNIST dataset. This results in approximately 397, 000 4-bit weights as opposed to ~21, 000 1-bit weights in our case. To generalize this result, let us consider a two layer network for the conventional case with d inputs, H hidden layer neurons and C output neurons for “C” classes. The comparable network in our proposed case has H dendrites and C output neurons. “2m” out of the H dendrites connect to each of the C output neurons ( H = 2 m × C ) using unit weights and hence can be implicitly implemented by accumulators. Considering each weight of the conventional network having resolution of “b” bits, the total number of bits required by the conventional network ( NOB conv ) is given by:\n (22) N O B c o n v = b × H × d + b × H × C ≈ b × H × d for C < < d For the proposed case, the connection matrix is of size d × H though only k × H entries are non-zero where k < < H . To implement this sparse connectivity efficiently in an address event framework, we propose to use a two tier addressing scheme as shown in Figure 10 . Here, the incoming address will be used to index into a pointer array of “d” entries with ⌈ log 2 ( H × k )⌉ bits per entry. An incoming spike address, say “i,” is used to index into this array and read the two consecutive values a i and a i + 1 . As shown in the figure, suppose a i = p and a i + 1 = q . n i = a i + 1 − a i is the number of synapses connected to this input. If n i > 0, then a i = p is used as a pointer to the p th location in a dendrite address array. This second array has H × k entries with ⌈ log 2 ( H )⌉ bits per entry that hold the address of the dendritic branch where the synapse is located. n i consecutive values ( d p to d q − 1 ) are read as destination addresses to route the spikes. Now, the total memory required by the look up table in the proposed method ( NOB prop ) can be estimated as:\n (23) N O B p r o p = d × ⌈ l o g 2 ( H × k ) ⌉ + H × k × ⌈ l o g 2 ( H ) ⌉ Figure 10 To implement the sparse connectivity matrix, a two level addressing scheme is proposed where the first memory (indexed by the incoming address of the event) holds pointers to valid connection addresses stored in the second memory . The memory requirements for proposed and conventional methods are compared in Figure 11 by setting b = 4, H = 10 4 and varying d over a wide range for k = 16, 32, and 64. It can be seen that the proposed method requires much less memory than the conventional case for large values of d when the sparsity is higher while the overhead of having a pointer array is more for small values of d . The crossover typically happens for d < 200 for values of k as large as 64. Since for most practical cases d is much larger, we expect our method to be widely applicable. Figure 11 Memory requirement of proposed sparse connectivity scheme is compared with that of a normal fully connected weight memory with 4 bits per weight . The proposed scheme is far more memory efficient for high dimensional inputs ( d > 200). To underline the importance of this memory reduction, we consider a digital implementation of this system following principles similar to the ones in Merolla et al. ( 2014 ) and Seo et al. ( 2011 ). In particular, we assume that the dendritic nonlinearity/hidden neuron can be a shared physical circuit that can be time multiplexed across all required instances and we assume synaptic weight resolution is 4 bits following Seo et al. ( 2011 ). Here, for simplicity we ignore the overhead needed if the network is spread across multiple cores. Using the numbers quoted in Merolla et al. ( 2014 ), the area requirement of a neuron circuit is 2900 μ m 2 . Compared to that, the area required to implement a conventional crossbar of 4 bit weights for the MNIST case of d = 784 and say H = 1000 is 470, 400 μ m 2 where we estimate 0.15 μ m 2 area per bit from Merolla et al. ( 2014 ). This is clearly the dominant factor in chip area. Compared to this, our scheme with even k = 64, H = 1000 and d = 784 requires approximately 98, 000 μ m 2 area, a reduction by > 4 X . 4.5. Future work The classification performance attained by our model on the benchmark MNIST data is not state-of-the-art. The best MNIST classification result achieved so far is 99.06% accuracy using maxout networks (Goodfellow et al., 2013 ). Hence, we need to bridge this gap by enhancing our model. Our present model consists of lumped dendritic nonlinearity such that each dendrite is considered to be a single compartment where all the synaptic inputs are lumped together. The storage capacity of this network can be increased by introducing multiple compartments on each dendrite. The dendritic compartments represent time delays in signal propagation along a dendrite and therefore, the information about the location of synaptic inputs on a dendrite is important. We will utilize this additional source of spatial information to enhance our dendritic structural learning rule which will involve finding the optimal location on the optimal dendritic branch for a synaptic connection. The storage capacity of the network can further be increased by including distributed nonlinearity along a dendrite such that the nonlinear output of each compartment serves as input to the next compartment on the dendrite. This scheme is also more bio-realistic from the perspective of real neurons consisting of extended dendritic trees with complex branching patterns. We will also enhance our adaptive learning rule to prune the redundant or least “salient” synapses. This pruning method combined with the progressive addition of dendrites will yield an optimally sized network that will fit the data. The network will learn both the number of required dendrites as well as the number of synapses on each dendrite. This approach to obtain the smallest network can also improve the generalization performance. In this work, we have not used temporal information to classify input patterns and have focussed on rate and place encoding of the binary images from the MNIST dataset. In a recent work (Roy et al., 2015 ), we have used structural plasticity to learn binary classification spatiotemporal patterns as used in Gutig and Sompolinsky ( 2006 ). Hence, a natural extension of our present work is to combine the use of spike timing information with structural learning to enable classification of multiclass temporal codes."
} | 6,429 |
36713314 | PMC9802364 | pmc | 1,406 | {
"abstract": "Abstract Droplet spreading and transport phenomenon is ubiquitous and has been studied by engineered surfaces with a variety of topographic features. To obtain a directional bias in dynamic wetting, hydrophobic surfaces with a geometrical asymmetry are generally used, attributing the directionality to one-sided pinning. Although the pinning may be useful for directional wetting, it usually limits the droplet mobility, especially for small volumes and over wettable surfaces. Here, we demonstrate a pinning-less approach to rapidly transport millimeter sized droplets on a partially wetting surface. Placing droplets on an asymmetrically structured surfaces with micron-scale roughness and applying symmetric horizontal vibration, they travel rapidly in one direction without pinning. The key, here, is to generate capillary-driven rapid contact-line motion within the time-scale of period of vibration. At the right regime where a friction factor local at the contact line dominates the rapid capillary motion, the asymmetric surface geometry can induce smooth and continuous contact-line movement back and forth at different speed, realizing directional motion of droplets even with small volumes over the wettable surface. We found that the translational speed is selective and strongly dependent on the droplet volume, oscillation frequency, and surface pattern properties, and thus droplets with a specific volume can be efficiently sorted out.",
"conclusion": "Conclusion We introduced a new approach to directionally transport droplets on vibrated micron-sized asymmetric surface structures. By using a simple model based on fundamental theory of fluid dynamics and droplet motion, we show how the translational speed is determined by the contact-line friction and the detailed surface geometry. With the given structure scale of a micron or less, the substrate smoothly slides under the droplet, and the anisotropic contact-line friction can cause a directional rapid travel on the surface. We identify that the speed is considerable ( U > 20 mm s –1 ) compared to the reported works ( 7 , 8 , 13 , 14 , 24 , 40 ), and resolve limitation in movable droplet size to a certain extent. We observed that the system can transport water droplets down to 0.7 μl, which was usually difficult to move due to a strong pinning force. This gives rise to large sensitivity to the droplet properties like the size realizing an efficient sorting of droplets with a specific property. This approach can be used without limitation in travel distance and is expected to extend to other liquids with various surface tensions and viscosities ( 31 ), realizing systematically predictable and controllable droplet transport and sorting.",
"introduction": "Introduction Dynamic wetting, where liquid spreads over a dry surface, is a crucial phenomenon with underlying rich multiphase physics and technological importance in vast industrial processes. Numerous research in the past has made great progress in describing and understanding the general characteristics of dynamic wetting, for instance, in terms of scales and regimes ( 1 , 2 ). An attraction of the topic lies in the controllability of overall macroscopic flow by the chemistry and physics at the local contact line, where a nonintegrable singularity ( 3 ) of the viscous stress makes the detailed nanoscopic features of the liquid and the surface important, giving rise to passive and active controllability with high gain or efficiency involving nonlinear and complex dynamics. Such controllability is useful in various applications such as spray painting and coating, but is particularly important in microfluidics ( 4 , 5 ). A common challenge among others is to handle small volumes of liquid, and a useful way to do this is to manipulate small droplets ( 4 ), where engineering of the solid surfaces for wetting is a great means. Many different strategies to use the surfaces to control droplet motion have been reported such as using hydrophobic and hydrophilic patterns ( 6 ), textured hydrophobic supports in a superhydrophobic surface ( 7 ), dynamically controllable microstructure generating a traveling wave ( 8 ), and stretchable wrinkled surfaces ( 9 ). Another possibility to introduce directionality to the droplet motion is to design anisotropic surfaces, such as nanotextured hydrophobic surfaces patterned with tilted nanorods or nanopillars ( 10 , 11 ). Dynamic wetting driven by vibration has been of practical importance and a convenient way to study the contact-line dynamics. The dynamics of a sessile droplet on a vertically oscillating surface is sensitive to the detailed characteristics of the contact line such as magnitude of hysteresis and dissipation ( 12–14 ). Furthermore, when asymmetry is induced to the system, a steady droplet motion can be generated. For example, by oscillating an inclined smooth surface or oscillating a horizontal surface in an inclined direction, the droplet can be transported to a specific direction ( 15–19 ). Another way to introduce the asymmetry is to use an oscillation waveform that has different accelerations in the forward and the backward part of the droplet motion ( 20–23 ). Asymmetry can also be implemented in the surface microstructure, which has an advantage in device implementation being insensitive to the oscillation direction. It has been shown that applying vertical oscillations to a nanotextured hydrophobic surface with tilted nanorods can transport the droplet ( 11 ) at speeds on the order of a few millimeters per second when the input frequency is near the natural frequency of droplet oscillation ( 24 ). Here, the precise mechanism of the transport is not entirely clear, but it is likely that the one-sided pinning induced by the tilted nanorods play a key role. Pinning forces may allow directional droplet mobility. However, pinning itself acts as a strong energy barrier on contact-line mobility ( 25 ), deteriorating the transport speed and restricting the mobility of smaller droplets. Leidenfrost effect is well-known to achieve droplet transport without pinning by levitating the droplet from the solid surface using the superheated solid surface temperature at hundreds of degrees inducing self-vaporized layer in between the droplet and solid surface, but on/off switching and controllability of the droplet motion is difficult to obtain ( 26–30 ). This work aims to explore a possibility to transport water by asymmetric surface microstructure without the pinning effects, with an aim to realize faster and predictable transport. The idea is to utilize contact-line friction that has been previously found to become directional on asymmetric microstructures. In the previous paper, we have performed spontaneous spreading of a droplet on a surface with micron-sized asymmetric sawtooth corrugations and demonstrated that the spreading is faster in the direction to which the contact line moves upward (downward) on the more steeply (gently) sloping face of the ridge ( 31 ). The formulated toy model accounting for the detailed shape of the corrugations reproduced the measured spreading speeds and showed that, in our experiments, pinning is not important, but instead the effective contact-line friction plays a dominant role in the mechanism. Here, the contact-line friction means the local dissipation at the contact line caused by the dynamic contact angle being different from the static value, whose rate, as de Gennes described ( 25 ), is proportional to \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\mu _f}{U^2}$\\end{document} , where U is the contact-line speed and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\mu _f}$\\end{document} is the contact-line friction coefficient with the same dimensions as viscosity (denoted \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\mu _l}$\\end{document} in de Gennes' original paper). This local dissipation can have different hydrodynamic or molecular origins ( 32–35 ) and can be effectively modulated by microstructures ( 36 ) or electrostatics ( 37 ). On the asymmetric sawtooth corrugations, the deviation of the dynamic contact angle from the static value depends on the direction of spreading. In this paper, by combining the asymmetric contact-line friction and oscillation, we demonstrate a new ratchet mechanism that realizes fast and steady droplet transport, with a droplet placed on asymmetric sawtooth corrugated surfaces and vibrated horizontally. Here, the contact-line friction is an important factor determining the translational speed, and pinning in many cases does not occur achieving faster movement even on rather wettable surfaces. A simple theory is presented that predicts the droplet mean horizontal speed, given the droplet volume and properties, the substrate geometry, and the oscillation frequency. Then, the predicted phenomena are realized by the experiment. It is demonstrated that the fast transport by this pinning-less mechanism, together with the nature of droplet oscillation having the largest amplitude near the resonance frequency, gives rise to efficient vibration sorting of droplets with a specific volume. Droplet oscillation system We consider a system with a water droplet of a few microliters placed on a partially wetting substrate surface with micrometer-scale texture of asymmetric shape as shown in Fig. 1(A) . Then, the substrate is oscillated horizontally at an input frequency of f according to \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$a\\ ( t ) = \\ A\\ sin\\omega t$\\end{document} , where \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\omega \\ = \\ 2\\pi f$\\end{document} , and thus excites an oscillatory motion in the droplet. In order to describe the droplet response, we formulate a simple mechanical analog by introducing \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$x( t )$\\end{document} to represent the position of the droplet center of mass, and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$s( t )$\\end{document} as the midpoint between the left and right contact lines. We consider a droplet of volume V with radius r , mass m , and approximate height h with surface tension γ . The following 3 equations constitute a simple dynamic model in terms of the uncompensated Young's stress, a geometric relation, and the equation of motion of the droplet. \n (1) \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}\\begin{eqnarray*} S{\\mu _f}\\left( {\\dot{s} - \\dot{a}} \\right)sin\\ {\\theta _g} = \\frac{3}{{2\\surd 2}}\\ \\gamma \\left( {cos{\\theta _e} - cos{\\theta _g}} \\right). \\end{eqnarray*}\\end{document} (2) \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}\\begin{eqnarray*} \\cos {\\theta _e} - {\\rm{\\ }}\\cos {\\theta _g} = {\\rm{\\ }} - \\left( {s - x} \\right)/h. \\end{eqnarray*}\\end{document} (3) \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}\\begin{eqnarray*} m\\ddot{x} = - 2\\gamma r(cos{\\theta _e} - \\cos {\\theta _g}). \\end{eqnarray*}\\end{document} Fig. 1. Propulsion of an oscillating water droplet. (A) Schematic of an experimental model showing a water droplet deposited on an asymmetric sawtooth structure oscillating at frequency of f . Blowing up shows a scanning electron microscopy (SEM) image of the sawtooth structure with α = 13°, β = 115°, σ = 52°, and p = 1.67 μm. The direction (“up” or “down”) is named considering the surface geometry. (B) A water droplet of V = 2 μl on substrate oscillated at f = 90 Hz starts to move to the down direction, increasing the velocity. High-speed imaging with time interval of 100 ms between the 2 successive images and the bar indicates 2 mm. (C) Position of designated points (blue circles of R traces the right contact line of droplet and L traces that of the left, black triangles of R–L show droplet footprint length, and gray squares for the position following the substrate motion) on the oscillating substrate with sawtooth surface of α = 13°. (D) Analyzed velocity for the R and L points. Refer to Movie S1 (Supplementary Material) . Note that \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\theta _g}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\theta _e}$\\end{document} denote a global dynamic contact angle and an equilibrium contact angle, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\dot{s} - \\dot{a}$\\end{document} is the macroscopic contact-line speed relative to the moving substrate. Equation 1 is the same as that derived by Yue and Feng ( 38 ) (see their Equation 21, identifying \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\mu _f} = $\\end{document} \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\mu \\ {\\rm{\\Pi }}/Cn$\\end{document} with \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\mu $\\end{document} denoting liquid viscosity and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\rm{\\Pi }}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$Cn$\\end{document} as defined in their paper), with the exception that here the line friction is written as \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$S{\\mu _f}$\\end{document} , which should be interpreted as an effective value for an equivalent flat substrate. \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\mu _f}$\\end{document} is the contact-line friction coefficient (in units of Pascal seconds, Pa s) on a perfectly flat surface of the same material, which is numerically fitted based on experiments. S is a nondimensional geometrical factor that accounts for the increased time for the contact line to pass over the microscopic substrate structures, considering the detailed value of α, β , and σ as shown in Fig. 1(A) ( 26 , 36 ). For the sawtooth shaped asymmetric patterns used here, however, we must expect a directional dependence, this is indeed the essential feature of the problem at hand. Referring to Fig. 1(A) , we will, in the following, call a contact line moving to the right (left) as moving in the “down” (“up”) direction and the corresponding S value \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${S_d}$\\end{document} \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$( {{S_u}} )$\\end{document} . During one period, the contact lines oscillate left and right, but as the contact line moves faster in the “down”-direction, the net displacement over a cycle is to the right, in the “down” direction. Using this to calculate the distance L d and L u traveled on the substrate during the positive and negative half periods respectively, according to Eq. 1 we obtain \n (4) \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}\\begin{eqnarray*} {\\rm{\\ }}{L_d} = \\frac{\\gamma }{{{S_d}{\\mu _f}}}\\ \\frac{3}{{2\\surd 2}}\\left| \\Phi \\right|\\ \\mathop \\smallint \\limits_0^{T/2} \\sin \\omega tdt = \\frac{{2\\gamma }}{{{S_d}{\\mu _f}}}\\ \\frac{3}{{2\\surd 2}}\\left| \\Phi \\right|\\frac{1}{\\omega }, \\end{eqnarray*}\\end{document} (5) \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}\\begin{eqnarray*} {\\rm{\\ }}{L_u} = \\frac{\\gamma }{{{S_u}{\\mu _f}}}\\ \\frac{3}{{2\\surd 2}}\\left| \\Phi \\right|\\ \\mathop \\smallint \\limits_{T/2}^T \\sin \\omega tdt = \\frac{{2\\gamma }}{{{S_u}{\\mu _f}}}\\ \\frac{3}{{2\\surd 2}}\\left| \\Phi \\right|\\frac{1}{\\omega }, \\end{eqnarray*}\\end{document} where \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\Phi $\\end{document} is the complex amplitude of the oscillation of the contact angle, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\theta_{ g}-\\theta_{ e} = \\varphi \\ ( t ) = {\\rm{\\ }}re( {\\Phi {e^{i\\omega t}}} )$\\end{document} . The details of the derivation of Eqs. 4 and 5 are given in the Supplementary Material . Note that we have assumed a hemispherical droplet and will calculate droplet natural angular frequency \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\rm{\\Omega }}$\\end{document} for this ( 12 ). Finally, the net translational speed U is obtained as the difference between left and right motion, divided by the period of the oscillation, and with the above expression for \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$| \\Phi |$\\end{document} , and using the nondimensional \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\omega _r} = {\\rm{\\ \\omega }}/{\\rm{\\Omega }}$\\end{document} , \n (6) \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}\\begin{eqnarray*} U\\ &=& \\left( {{L_d} - {L_u}} \\right)\\ \\ \\frac{\\omega }{{2\\pi }}\\nonumber\\\\&& = {\\rm{\\ \\ }}\\frac{A}{h}\\ \\frac{\\gamma }{{{\\mu _f}}}{\\rm{\\ }}\\frac{{\\omega _r^2}}{{\\sqrt {{{\\left( {1 - \\omega _r^2} \\right)}^2} + \\frac{{2\\pi }}{3}{{\\left( {\\frac{{{\\omega _r}}}{{O{h_f}}}} \\right)}^2}} }}{\\rm{\\ \\ }}\\frac{3}{{{\\rm{\\ }}2\\pi \\sqrt 2 }}{\\rm{\\ }}\\left( {\\frac{1}{{{S_d}}} - \\frac{1}{{{S_u}}}} \\right). \\end{eqnarray*}\\end{document} Here, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$O{h_f} = S{\\mu _f}/\\sqrt {\\rho \\gamma r} \\ \\ $\\end{document} denotes the effective-line friction Ohnesorge number, using the average of \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${S_d}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${S_u}$\\end{document} for S ( 31 , 36 , 39 ). This means that we expect little motion at low frequencies, that the translational speed should be proportional to the oscillation amplitude, and that the maximum speed should occur near the eigenfrequency. The details of the substrate geometry enter through the difference between \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${S_d}$\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${S_u}$\\end{document} , which thus determine the speed. Droplet transport To realize the droplet oscillation system designed in Fig. 1(A) , we place a small water droplet with volume of V = 2 μl ( r ≈ 0.78 mm, γ = 0.072 N m −1 , and μ = 997 kg m − 3 ) on an asymmetric sawtooth-shaped structure, which is firmly fixed on the drive arm of a mechanical oscillator. The symmetric sine wave generated by a function generator applied to the substrate via the oscillator. The surface used is coated with a thin aluminum layer on the top with geometry of α = 13°, β = 115°, σ = 52°, and p = 1.7 μm (Fig. 1B ). The average of S d ( = 1.22) and S u ( = 1.59) for S is given as 1.40 for the geometry. The top surface was functionalized with APTS((3-aminopropyl) triethoxysilane) to achieve uniform surface wettability with \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\theta _e} = $\\end{document} 63° and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\mu _f}$\\end{document} = 0.09 Pa s, which is obtained from a water droplet on a flat aluminum surface processed with the identical silanization. The above experimental condition gives \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$O{h_f} = S{\\mu _f}/\\sqrt {\\rho \\gamma r} \\ \\ $\\end{document} = 0.533 close to unity, which means the droplet speed would be influenced by not only the capillary-driven inertia but also the details of the surface geometry. Then the substrate with the droplet was vibrated at f = 90 Hz with A = 0.5 mm. As we have expected from the theory, we found that the droplet travels to the down direction at a considerable speed of 23 mm s −1 , which is an unprecedented motion of the small volume of water droplet on the partial wetting surface (Fig. 1B ). As we used sawtooth structures of 3 different geometries with α of 13, 23, and 26° in the following experiments ( Figure S2(a) and (b), Supplementary Material ), hereafter we denote each substrate with the values of α , as in “ α 13 substrate.” To understand the detailed behavior and quantitatively analyze the droplet motion, high-speed recordings ( Movie S1 and Figure S1(a), Supplementary Material ) were digitally processed to track time histories of droplet positions (Fig. 1C ). At the interface between the droplet and the substrate, we define the right edge as “R” and the left as “L.” Using the position time histories of R and L from Fig. 1(C) , we extracted the velocity of the points as shown in Fig. 1(D) . At the start of substrate oscillation (50 ms ∼), the displacements of R and L follow the substrate, and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$x( t )$\\end{document} is almost stationary, named “still” stage. In this stage, only R accelerates towards the “down” direction, due to the deviation of dynamic contact angle from the equilibrium value, while L is temporarily still at the ridge due to contact angle hysteresis. As the vibration amplitude increases beyond a threshold value, the capillary force overcomes the contact-line hysteresis and L also starts moving toward the “down” direction. As we show in Fig. 1(D) , the transition region begins from around 95 ms with the complete motion of the contact line. During this time period of about 355 ms, the droplet cyclically expands and contracts horizontally as seen in the footprint length R–L, gradually elongating the droplet shape along the direction of the oscillation. Simultaneously, the droplet starts to completely slide over the surface as we can see from the time-varying deviation in oscillation phase and the traveled distance per each oscillation between the R or L and the substrate. We note that the peaks of R and L, are in phase with the substrate at the beginning of the transition stage. However, as the motion develops over time, R finally becomes 180° out of phase. Interestingly, the oscillation direction of \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$x( t )$\\end{document} with respect to the substrate is reversed via the transition region taking time to synchronize the motion between the droplet and the substrate. It is noticeable that the droplet can slide over the surface within 45 ms only with the transient substrate amplitude of 0.072 mm, so-called threshold amplitude, and accelerates rapidly within around 120 ms (from 450 to 570 ms) reaching the translational speed once the motion between the substrate and the droplet is synchronized. Within the synchronized region, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$x( t )$\\end{document} and the substrate oscillate in opposite directions, so that the contact line obtains the maximum possible travel distance with respect to the substrate. The droplet finally reaches a terminal translational speed of 23 mm s −1 after about 530 ms from the start of the vibration. Frequency dependence To understand the effect of input frequency, we analyzed droplet behavior as a function of f between 10 and 160 Hz, focusing on how the contact-line motion differs and report the representative cases for f = 50, 90, and 130 Hz in Fig. 2 . In the frequency range between 10 and 50 Hz with A of 0.5 mm, a water droplet of 2 μl did not move relative to the sawtooth surface. Figure 2(A) shows the case of f = 50 Hz, where L (red circle) and the substrate position corresponding to L at start (gray square) completely overlap with a stationary center of mass with respect to the substrate. As increasing f , the droplet started to translate over the sawtooth surface to the “down” direction and the translational speed gradually increased, and the highest translational speed is reached at 90 Hz as shown in Fig. 2(B) . The droplet footprint length also oscillates in a sinusoidal manner with an amplitude of 0.25 mm, which is half of A . In other words, the droplet oscillation generates an additional harmonic mode at the footprint, which is generally observed when vertical oscillation is applied ( 13 , 40 , 41 ). Interestingly, we observed that the footprint oscillation is accompanied by a pulsating motion of R manifesting the lower contact-line friction to “down” relative to the opposite, which drives \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$x( t )$\\end{document} to this direction. The contact line of R moves rapidly during about 1 ms and elongates footprint length temporarily, and the movement speed is close to maximum of the capillary spreading ( Figure S3, Supplementary Material ). At the same time, L is mirroring R with a 1-ms delay due to the pulsating, which is modest compared to the oscillation period of 11 ms, as seen in the sum of L and R with nearly no oscillation ( Figure S4, Supplementary Material ). Fig. 2. Contact-line motion at different input frequencies. Observed droplet positions at R and L and determined footprint length of R–L for respective frequencies of (A) 50 Hz, (B) 90 Hz, and (C) 130 Hz on the sawtooth surface of α = 13° during the time period of 100 ms in the synchronized regime. One cyclic spatiotemporal diagram of the oscillating droplet with oscillation frequency of (D) 90 Hz and (E) 130 Hz with respective time intervals of 2.8 and 1.9 ms. Cyan bars denote 2 mm, tracing the same location on the substrate. We show the cyclic droplet behavior in Fig. 2(D) and note how the contact line moves relative to the cyan bar of 2 mm length, tracing the same location on the substrate (refer to Movie S2 [Supplementary Material] , which is slower playback speed version of Movie S1 [Supplementary Material] ). When the substrate accelerates from the left end and pauses at the right end, moving distance of 2 A = 1 mm, L is displaced to the left by about 0.5 mm, which corresponds to sliding over 299 pitches to “up.” In the successive half period, R is displaced to the “down” by about 1.25 mm, sliding over 748 pitches to “down.” As the footprint oscillation with amplitude of ∼ 0.25 mm is added on this spontaneous behavior, the ultimate net displacement is ∼ 0.25 mm. As f increases, the droplet oscillation mode evolves and generates more complicated behavior. The droplet remarkably slows down at a higher frequency of 130 Hz as shown in Fig. 2(C) and (E ) (see also Movie S3, Supplementary Material ). As f exceeds the resonance frequency, we expect the oscillation amplitude of \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$x( t )$\\end{document} to decrease. Furthermore, when the speed of the substrate \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$A\\omega $\\end{document} exceeds the capillary line-friction velocity \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\gamma /{\\mu _f}S$\\end{document} of 0.57 m s −1 , the contact line follows the substrate motion closely. We will use the ratio of \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$A\\omega $\\end{document} and \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$\\gamma /{\\mu _f}S$\\end{document} as a dimensionless quantity to represent line-friction capillary number \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$C{a_f}$\\end{document} . In the case shown in Fig. 2(E) with A = 0.5 mm, both L and R oscillate with amplitudes of 0.4 mm, which means that the droplet is mostly following the substrate. In this case, the line-friction capillary number is \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$C{a_f}\\ ( {\\ = {\\mu _f}SA\\omega /\\gamma \\ } ) = \\ 0.72$\\end{document} , close to unity, thus the contact-line friction limits the velocity difference between the substrate and the contact line. The snapshots at the high frequencies (Fig. 2E ) show that the bottom layer of water near the contact line is constrained by the rapidly oscillating substrate, and the upper layer is rather separated from the bottom sustaining its own oscillation mode. Once this footprint has been established, the contact-line motion relative to the substrate is limited and no longer drives the translation of the droplet center of mass. As a result, the elongated footprint length noticeably converges to the value of \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${l_0} + 2A$\\end{document} at the high frequencies, where \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${l_0}$\\end{document} is the initial length of the footprint before oscillation starts ( Figure S5, Supplementary Material ). The droplet finally stopped to travel at f = 140 Hz, with \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$C{a_f} = \\ 0.77$\\end{document} almost maintaining the footprint elongation with \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${l_0} + 2A$\\end{document} (see Movie S4, Supplementary Material ). Large droplet volume and reversed transport direction To verify how the directional motion differs when the droplet becomes more inertial and surface roughness has lower asymmetry (closer to flat), we evaluated the motion of a larger droplet of V = 6 μl ( r ≈ 1.1 mm) on an asymmetric sawtooth surface with geometry of α = 23°, β = 112°, σ = 45°, and p = 0.82 μm (inset of Fig. 3A ). Oh f is given as 0.524 for this case, which is close to the previous α 13 with V = 6 μl case shown in Figs 1 and 2 . Note that the structure pitch in this case is half of the α 13 substrate, thus all the length scales of surface roughness are submicron. Figure 3(A) shows the dependence of droplet translational speed on the input frequency with A = 1 mm for the larger water droplet, where the estimated eigenfrequency is 46 Hz. In this case, the droplet starts to travel at f = 30 Hz and the translational speed grows with increasing f until it reaches the maximum speed of 15 mm s −1 at 55 Hz (Fig. 3A and C , Movie S5, Supplementary Material ). As f exceeds 55 Hz, the droplet gradually elongates (Fig. 3B ) and the translational speed drops prominently to 5.2 mm s −1 at 70 Hz with corresponding value of \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$C{a_f}$\\end{document} = 0.86 (Fig. 3B and Figure S5, Supplementary Material ). Interestingly, as f exceeds 80 Hz, the droplet alters its moving direction to “up” with apparently elongated footprint. Increasing f further, the droplet speed decreases, but remains in the “up” direction. The reversed transport has been observed in the work of Daniel et al., when the droplet size was increased at a fixed input frequency when applying asymmetric waveform on a flat hydrophobic surface ( 20 ). They reported transport motion in reversed direction with more inertial droplets in size of nearly 1 or 2 mm in radius and attributed it to the splitting of the droplet oscillation modes. While we agree with the possibility of the mode splitting, we here describe the reversed motion with respect to the emerging liquid layer near the substrate surface accompanied by its movement (see the gradual elongation in Fig. 3B and those changes in tails). Figure 3(C) shows the case of 120 Hz, with extremely complex droplet shape due to higher oscillation modes ( Movie S6, Supplementary Material ). Here, it becomes clearer how the droplet center of mass is essentially stationary, lubricated by a wetted footprint of length \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${l_0} + 2A$\\end{document} , as noted above. Figure 3(C) also shows how a thin liquid film of a thickness similar to a Stokes layer, \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}${\\rm \\delta}\\sim{( {2\\gamma /\\rho f} )^{1/2}} \\sim 0.1\\ mm$\\end{document} , is being pulled out left and right as the substrate oscillates. It is clear from this that the contact-line dynamics has a very limited influence on the net droplet motion, but the motion, rather, is controlled by other weaker effects, such as the finite Reynolds number flow in the Stokes layer over the asymmetric substrate pattern. A representative Reynolds number would be Re rough = Aωpρ / μ , where p is the pattern pitch. For the case in Fig. 3(C) at f = 120 Hz, with A = 1 mm, p = 0.82 μm, ρ = 997 kg m − 3 , and μ = 0.992 mPa s, Re rough takes a value of 0.62, which could allow the local flow around the saw tooth ridges to be different going left or right, causing a weak net force in the “up” direction. Fig. 3. Travel directions of droplet depending on the frequency. (A) Experimentally determined droplet ( V ≈ 6 μl) translational speed at maximum value vs. driving frequency f together with indication of travel direction over sawtooth surface of α = 23°. Inset, SEM image of the sawtooth surface structure with α = 23°, β = 112°, σ = 45°, and p = 0.82 μm. (B) Snapshots of droplet during travel at the terminal speed. Each image shows the one at a specific time with the highest elongation of footprint length. (C) One cyclic spatiotemporal diagram of the oscillating droplet at frequencies of 55 Hz to downward travel and 120 Hz to upward travel with time interval of 4.5 ms and 2.1 ms, respectively. Red dotted lines in vertical are indicating initial position of leading points depending on the travel directions and colored bars tracking the substrate motions are 2 mm. Droplet sorting It is natural to obtain the maximum droplet mobility at near the eigenfrequency from the droplet oscillation, however, it is not usually easy to realize in a predictable way when the droplet is resting on the solid surface as those liquid–solid interaction generally induces contact-line pinning and additional hydrodynamic effect at inside of droplet, especially when vertically vibrated. From the earlier discussion, we verified that contact-line motion can be continuous over the less than 1 micron scale roughness whose geometry is rather smooth without a sharp edge. If we tune the droplet Ohnesorge number \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$O{h_f}\\ $\\end{document} and surface fiction in a suitable range where surface geometry can be visible, the anisotropic surface will cause the droplet to move most efficiently at its eigenfrequency, which is sensitive to droplet size. This scenario can realize vibration sorting of droplets with a specific size by asymmetric contact-line friction. To verify the scenario, we traced the droplet behavior for various geometries, and plotted the droplet translational speed U as a function of f in Fig. 4(A) . When the droplet volume is relatively large ( V = 6 μl), U is more sensitive to f , showing a sharp peak near the eigenfrequency of 46 Hz. The peaks are sharper in α 13 and α 23 cases with full-width half-maximum (FWHM) of ∼ 20 Hz. The maximum obtained speed and the FWHM vary with surface geometry despite the droplet size R being the same. Considering the geometry factor as 1/ S d –1/ S u (0.19, 0.13, and 0.31 for α 13, α 23, and α 26 structures, respectively; Table S1, Supplementary Material ), the factor closer to 0 makes the sorting range sharper. We report our observation in Fig. 4(B) , focusing on the droplet-sorting property. In this diagram, all the experimental parameters of A, f , and geometric features of α, β, σ , and p are included in the presented dimensionless coordinates of Re rough and 1/ S d –1/ S u . With fixed geometry factor and increasing Re rough , the droplets can be sorted efficiently within the FWHM range (orange zone). Below the sorting region (white zone), droplets show only feeble travel motion or remain stationary. Above the sorting region (gray zone), the droplet transits to the higher mode and the travel speed is low and the direction may be reversed ( U < 0) when the surface geometry has a little asymmetry. There exists an optimal range of surface asymmetricity for efficient sorting of droplet as presented with the α 13 structure showing the narrow FWHM range reaching the highest translational speed of 23 mm s −1 . For the higher modes obtained for the 6 μl droplet, such as in Fig 3(D) at f = 120 Hz, the prediction in Eq. 6 is not applicable since the assumed geometrical relation in Eq. 2 does not describe this complex higher mode of droplet oscillation (Movie S6 and Figure S6, Supplementary Material ). Fig. 4. Sorting of oscillating droplets. (A) Translational speed of water droplet over the sawtooth surface depending on the driving frequency with 6 μl droplet. (B) Dynamical behavior of droplets subjected to substrate oscillation described using Re rough as a function of asymmetry factor of 1/ S u –1/ S d . Coordinates on x- axis define the degree of geometry asymmetry positively. Each color of marker gives the specific experimental condition as defined in the legend. The filled circle shows travel to down, the empty circle is to up, and cross is still on the substrate. The orange zone is for droplet sorting region for 6 μl droplet in the frequency region of FWHM along the velocity peaks. The gray zone is higher modes of droplet oscillation with largely elongated footprint length showing dynamic upward, still, and downward motion. (C) and (D) Translational speed of water droplet over the sawtooth surface depending on the driving frequency with 2 μl droplet, respectively for α = 13° (C) and α = 26° (D) structures. Solid lines show theoretically derived translational speed from Eq. 6 corresponding to each experimental condition. Each dashed line and dash-dotted line illustrates theoretical speed with geometric variations of α ∓ 1°, σ ± 1° with fixed β . (E) Sequence of optical images of the droplets with various volumes resting on the α = 13° structure. The substrate is subjected to oscillation at f = 90 Hz and A = 0.25 mm, repeating with pausing time in between (see Movie S7, Supplementary Material ). Scale bars, 2 mm. Figure 4C and D show the comparison with the theoretical model in Eq. 6 for the smaller droplet ( V = 2 μl). Drawn with full solid lines, Eq. 6 is found to agree with the results for α 13 and α 26 structures, respectively. Note that the contact line fails to move when the frequency is below 50 Hz ( α 13 case) and 40 Hz ( α 26 case) because the displacement of the center of mass x ( t ) and the induced dynamic angle is not enough to overcome the contact angle hysteresis. The droplet in the low-frequency range can be transported by increasing the oscillation amplitude, although the travel speed is lower. We found that geometric variations may sensitively affect the translational speed as shown with the dashed and dash-dotted line, which includes α of ∓ 1° and σ of ± 1° difference when β is fixed (for detail values of S d and S u used for the prediction, see Table S2, Supplementary Material ). This feature can be used to design the surface structure for faster transport, for example, the transport speed can be increased more than 2 times at the maximum in case of α 13 structure when the surface shape becomes conventional sawtooth shape with sigma of 90° (see Figure S7, Supplementary Material ). Compared to the breakthrough work done by Daniel et al. ( 20 ), which actuates drop motion with asymmetric vibration waveform over flat hydrophobic surface generating succession of stop and go motion, our method gives further controllability of the transport as the effective contact-line friction can be tuned by the geometry of the surface structure, which has not been achieved before. We validated possible droplet volume variations from the experiment (sum of systematic and random error of ± 0.07 μl when the droplet volume is 2 μl), but it only merely altered the prediction results and not shown on the graph. In the proposed theory, it should be noted that the model is expected to give qualitatively reasonable predictions for f up to and around the first eigenfrequency, but not beyond (see the derivation of model theory in the Supplementary Material ). Showing a broader sorting range with FWHM of ∼ 50 Hz compared to that of the larger droplet case, cutoff frequency, where the translational speed drops significantly at 120 Hz for α 13 and 100 Hz for α 26, is lower for larger \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n}{}$S\\ (\\ = \\ ({S_d} + {S_u})/2\\ = \\ 2.5)$\\end{document} with α 26 structure, whereas S = 1.4 for the α 13 structure, becoming stationary with Ca f ≈ 1.1 at 130 Hz. As the larger volume of droplets can only travel in a narrow-frequency range, droplets lying over the asymmetric sawtooth structures can be sorted in a controlled manner. Figure 4(E) and Movie S7 (Supplementary Material) illustrate what happens when several droplets of different volume resting on the α 13 structure are oscillated at 90 Hz with amplitude of 0.25 mm. We first oscillate for 1 including the rising and falling time of the vibration and pause, then we oscillate again for 1.5 s in the same way. In this situation, specific droplets (2 μl and 5 μl) move toward “down” direction at different speeds, rather faster with the 2 μl drop, while the 5 μl drop is almost stationary showing apparent elongation. The 5 μl droplet finally stops when it merges with a small droplet of 0.7 μl, while the 2 μl droplet continues to move forward. As shown, the oscillation can turn the droplet travel motion on and off in a controlled manner using the frequency and amplitude. Using the α 13 structure, we further demonstrate the rapid sorting of a 2 μl droplet at U > 20 mm s –1 with f = 90 Hz and A = 0.5 mm ( Movie S8, Supplementary Material ), sorting of 6 μl droplet at low speed at U ∼ 1 mm s –1 with f = 40 Hz and A = 0.5 mm ( Movie S9, Supplementary Material )."
} | 12,889 |
35494704 | PMC9047967 | pmc | 1,408 | {
"abstract": "The superhydrophobic properties of biological surfaces in nature have attracted extensive attention in scientific and industrial circles. Relative to the rolling superhydrophobic state of lotus leaves, the adhesive superhydrophobic state of geckos and Parthenocissus tricuspidata is also significant in many fields. In this work, polydopamine (PDA) with its excellent biological compatibility and strong adhesion was selected as a substance to simulate the secretion of the suckers of P. tricuspidata and it was precipitated at the surface of honeycomb polyurethane porous membranes (PUPM). The results demonstrated that the honeycomb PUPM, as prepared, displayed special super-adhesion properties similar to those of geckos and P. tricuspidata . PDA formed via self-polymerization in aqueous solution was equivalent to a double-sided adhesive, acquiring a micro–nano structure of PDA and PUPM and displaying increased surface hydrophobicity and improved adhesion properties. Even when the surface precipitation of PDA and modification with n -dodecyl mercaptan made the contact angle increase to more than 160°, the surface adhesion to water was rather strong and remained stable. The addition of the PDA adhesive can effectively change the microporous structure of PUPM, enhancing the viscosity, and facilitating an enhancement in the fracture strength.",
"conclusion": "4. Conclusions PDA samples at various concentrations were precipitated at the surface of honeycomb PUPM to simulate the secretion of the suckers of P. tricuspidata . The honeycomb PUPM were found to display especially strong adhesion, similar to those of geckos and P. tricuspidata . Moreover, PDA formed by self-polymerization in aqueous solution was shown to be equivalent to a double-sided adhesive, forming a micro–nano structure consisting of PDA and PUPM and dramatically increasing the surface hydrophobicity and adhesion. Including the surface precipitation of PDA and modification with n -dodecyl resulted in an increase of the CA to more than 160°, and led to the rather strong and stable adhesion of water onto the surface of PUPM. The addition of the PDA was found to change the microporous structure of PUPM, increasing the viscosity, and contributing to an enhancement in the tensile strength. These results are expected to benefit the exploration of new functional materials with especially strong adhesion at levels similar to those displayed by geckos and P. tricuspidata .",
"introduction": "1. Introduction Bionics is the product of human learning from nature, and has made great contributions to human development and progress. With the continuous development of bionics, there have been many bionic studies on animal and plant parts displaying hydrophobic properties, such as lotus leaves, duck feathers and butterfly wings, etc 1–3 . In particular, the superhydrophobic properties of biological surfaces in nature have attracted extensive attention from scientific and industrial circles. 3,4 However, more research on the wettability of animal and plant surfaces displaying strong adhesion needs to be done. Scientists have studied the surfaces of lotus leaves and rose petals and other plants by using scanning electron microscopy and contact angle meters. 5 The wettability has been shown from many experiments to be mainly determined by the surface microscopic geometric structure and surface chemical composition. 6,7 Early studies on adhesive materials mainly focused on animal and plant biology and physiology. 8,9 The representative subjects of such studies have been the gecko and Parthenocissus tricuspidata . Investigations of the surface structure of P. tricuspidata and analysis of the development of the suckers have resulted in improved understandings of tendril development, mucus secretion, morphological structure and other aspects. 10,11 Targeted scientific exploration has been carried out by combining materials science, physical chemistry, micro design and measurements, nanobionics, and other disciplines. For example, Endress et al. 12 studied the morphological and structural characteristics and adhesive properties of sucker organs of the highly adhesive P. tricuspidata . The nanoscale particles formed between the surface and the secretion of the suckers were observed using atomic force microscopy. 13 The positions of these nanoparticles and their functional effects on the adhesion of the sucker were analyzed. 14 These results indicated the presence of as many as 19 components in the viscous fluid, and that these nanoparticles play a significant and direct role in the adhesion process. Steinbrecher et al. 15 used cytochemical staining to find that the fully mature suckers have a special porous shape. Secreted mucus has been demonstrated to occupy the porous cells of the epidermis and to extend into the depressions, leading to an essentially perfect occlusive contact between the suckers and the base surface, and hence resulting in superadhesion. 16 Utilizing the strong adhesion of such adhesive materials in medical applications involving antifouling is highly promising. 17 Furthermore, these materials have good biocompatibility and can also be used in the field of biomedical materials such as artificial blood vessels. 18 Scientists have simulated the micro–nano structure of the mature surface of the P. tricuspidata . Some studies have shown a nearly complete lack of adsorption of platelets onto the surfaces of superhydrophobic polyurethane (PU) porous films, 19 while platelets have been observed to be adsorbed onto the hydrophobic surfaces of smooth PU porous films. The superhydrophobic adhesive materials exhibit better biocompatibility than do common materials, and this better biocompatibility opens up a new research direction for the development of biomedical materials. 20–23 Adhesive materials in modern medicine, food and industry also have great potential development value, and more attention should be paid to the comprehensive exploitation and utilization of such materials, and to strengthen their biological medicinal value and industrial applications. 24 In the work described in this paper, polydopamine (PDA) with its excellent biological compatibility and strong adhesion was selected as a substance to simulate the secretion of the suckers of P. tricuspidata in order to find a kind of material displaying strong adhesion. Specifically, PDA-enhanced superadhesion and fracture strength of honeycomb polyurethane porous membranes (PUPM) were focused on. The prepared honeycomb PUPM displayed special superadhesion properties, similar to those of the geckos and P. tricuspidata . The growth of PDA on PUPM was first investigated, followed by the effect of PDA on the fracture strength of PUPM, and finally the effect of PDA on the surface wettability of PUPM."
} | 1,704 |
22882172 | null | s2 | 1,409 | {
"abstract": "Many bacteria organize themselves into structurally complex communities known as biofilms in which the cells are held together by an extracellular matrix. In general, the amount of extracellular matrix is related to the robustness of the biofilm. Yet, the specific signals that regulate the synthesis of matrix remain poorly understood. Here we show that the matrix itself can be a cue that regulates the expression of the genes involved in matrix synthesis in Bacillus subtilis. The presence of the exopolysaccharide component of the matrix causes an increase in osmotic pressure that leads to an inhibition of matrix gene expression. We further show that non-specific changes in osmotic pressure also inhibit matrix gene expression and do so by activating the histidine kinase KinD. KinD, in turn, directs the phosphorylation of the master regulatory protein Spo0A, which at high levels represses matrix gene expression. Sensing a physical cue such as osmotic pressure, in addition to chemical cues, could be a strategy to non-specifically co-ordinate the behaviour of cells in communities composed of many different species."
} | 281 |
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