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"abstract": "Macroscopic growths at geographically separated acid mine drainages (AMDs) exhibit distinct populations. Yet, local heterogeneities are poorly understood. To gain novel mechanistic insights into this, we used OMICs tools to profile microbial populations coexisting in a single pyrite gallery AMD (pH ∼2) in three distinct compartments: two from a stratified streamer (uppermost oxic and lowermost anoxic sediment-attached strata) and one from a submerged anoxic non-stratified mat biofilm. The communities colonising pyrite and those in the mature formations appear to be populated by the greatest diversity of bacteria and archaea (including ‘ARMAN' (archaeal Richmond Mine acidophilic nano-organisms)-related), as compared with the known AMD, with ∼44.9% unclassified sequences. We propose that the thick polymeric matrix may provide a safety shield against the prevailing extreme condition and also a massive carbon source, enabling non-typical acidophiles to develop more easily. Only 1 of 39 species were shared, suggesting a high metabolic heterogeneity in local microenvironments, defined by the O 2 concentration, spatial location and biofilm architecture. The suboxic mats, compositionally most similar to each other, are more diverse and active for S, CO 2 , CH 4 , fatty acid and lipopolysaccharide metabolism. The oxic stratum of the streamer, displaying a higher diversity of the so-called ‘ARMAN'-related Euryarchaeota , shows a higher expression level of proteins involved in signal transduction, cell growth and N, H 2 , Fe, aromatic amino acids, sphingolipid and peptidoglycan metabolism. Our study is the first to highlight profound taxonomic and functional shifts in single AMD formations, as well as new microbial species and the importance of H 2 in acidic suboxic macroscopic growths.",
"conclusion": "Conclusions AMD environments generally host a finely tuned restricted set of acidophiles, with a phylotype richness that depends highly on the pH condition ( Sánchez-Andrea et al. , 2011 ; Kuang et al. , 2013 ). The results of this study draw attention to the huge undiscovered and non-described pool of microorganisms populating acidic environments and having important roles in iron/carbon/hydrogen cycles, particularly in low pH suboxic macroscopic growths. In particular, by integrating biodiversity and community genomic and proteomic profiling, we determined that the Los Rueldos AMD solution was characterised by unusually low temperature and redox potential ( Supplementary Table S1 ), which may contribute to sustaining a wide microbial population compared with similar niche boundaries. It included a high proportion of uncommon Bacteria known to inhabit anoxic subsurfaces, uncultured Euryarchaeota , including methanogens, and ‘ARMAN'-related archaea. Our study further revealed that Los Rueldos is characterised by a stratified metabolically active ecosystem. In addition, clear shifts in the carbohydrate turnover have been observed in the stratified streamer (for details, see Supplementary Results and discussion and Supplementary Figure S11 ). Because a homogeneous pH of ∼2 characterised all samples, the provided evidence suggests that O 2 concentrations, spatial localisation and biofilm architecture are the main shaping factors, providing a much higher level of microbial and functional shifts within single AMD sites than previously thought. The body of the results presented here has enabled us to pinpoint the major active metabolic functions and has provided us with invaluable insights into the global differences of macroscopic growths at the local scale. One of the most crucial issues in the environment studied is the origin and further development of the streamer-mat structures. Figure 8 summarises a metabolic scheme that may provide a plausible explanation. Briefly, we hypothesise that the streamer starts as a chemolithotrophy-based community (most likely relying on Fe(II) oxidation, as suggested by the SSU tag pyrosequencing taxonomic analysis conducted over early developmental stages). This community would mainly consist of members capable of exopolysaccharide (EPS) production, allowing them access to the mineral resources on the bank side. The presence of small discrete slime growths in contact with mineral rocks at the bank was observed (data not shown). Later, a heterotrophic system would evolve, in which chemolithotrophy based on both Fe(II) and reduced inorganic sulphur compounds oxidation exists but not as the main energy metabolism. Mature communities would be able to fix both inorganic nitrogen and carbon dioxide and maintain a self-contained microbial subsystem in the overall Los Rueldos metabolism. Nitrogen and carbon would enter the community through the B1A layer, where metaproteogenomic signatures have been found for both nitrogenases and RuBisCO enzymes. The chemolithotrophic growth would thus be supported by non-described Nitrospirae (e.g., ‘ L. ferrodiazotrophum ') , Acidithiobacillales ( At. ferrivorans , ‘RCP1-48') and β -Proteobacteria (e.g., ‘ Ferrovum myxofaciens '-like) members with EPS production capabilities. The products of degradation would serve as a mainstay for the heterotrophic metabolism in B1A and would diffuse to the submerged B1B, where they could serve as the principal contributors for heterotrophic-based cell growth. Reduced inorganic sulphur compound oxidation has been demonstrated to occur through the detection of metaproteogenomic signatures in B1B, but would not represent the main metabolism within the community. The anoxic conditions favour the presence of fermentation-by products (H 2 gas), which would diffuse to the overlaying stratum B1A and could be used as an additional electron donor. The implication of H 2 in the B1A metabolism has been demonstrated by the presence of expressed hydrogenases. The origin of B1B remains unexplained; the stratification could appear as a consequence of the heterotrophy by-products originating in B1A, or such a stratum could possess an independent origin (its thickness suggests this assumption as being possible as well as the possibility of the origin of a EPS-based structure in an anoxic environment). A relevant observation in the present study is the existence of a B2 macroscropic, EPS-based submerged growth, which is uncommon in nature. It is plausible that the submerged B2 originated via a reduced inorganic sulphur compound oxidation-based metabolism and/or a heterotrophic metabolism fuelled by products originating in the B1-like formation that extends at the end of the gallery and from the point where the AMD begins to flow ( Figure 8 ). The flow could bear ammonium, DOC (dissolved organic carbon) and Fe(III) to the B2 emplacement, where the slow AMD outflow could favour the maintenance of those components in the area. Various taxonomic groups present in B2 have been reported to be capable of EPS production (‘ F. myxofaciens '-related β -Proteobacteria and Acidithiobacillales such as A. ferrooxidans ) and also of supporting heterotrophic metabolism. Nevertheless, bacteria with nitrogen and carbon fixation potential ( L. ferrooxidans and A. ferrooxidans ) have been demonstrated to exist in B2, although the ability of such gases to access the submerged mat and reach the cell membranes remains unclear. In addition, the transformation of nitrate to nitrite has been detected but is not driven by typical nitrifiers. Finally, the existence of such diverse communities as those existing in Los Rueldos supports the existence of a heterotrophy-dominated system. In accordance with this finding, the observation that the various identified taxa (e.g., Xanthomonadaceae ) have not been reported to exist in an autotrophy-dependent manner should be highlighted. The results presented here should be seen as those of an explorative study, as there are several limitations that prevented us from drawing definitive conclusions. First, we are aware that these results have been established with a limited coverage of gene sequences (from 10.8 to 14.9 Mbp) and proteins with detected expression level (1589). Consequently, it is unknown to what degree a larger set of data might influence the metabolic distributions within the communities examined; however, we should stress the fact that the community structure was extensively characterised by full-length 16S and SSU rRNA hypervariable tag sequencing and that good agreement between the gene content, protein expression profile and community composition was found in many of the most representative metabolisms. Second, we are aware that the results presented here have been established from a single AMD formation geochemically distinct to reported ones, and therefore this might influence the comparability within Los Rueldos communities to those found in other AMD sites around the World. Whatever the case, the results presented here suggested that the key environmental factor that appears to be shaping the communities inside the gallery is the DO concentration, very low at certain depth levels due to the absence of drainage flowing. This, together with the low temperature and low redox potential in the pool, may be decisive for the observed microbial species richness within Los Rueldos macroscopic growths, as less extremely pH and temperature values are commonly associated with increased richness and diversity in AMD systems. Low temperature AMD systems ( Cae Coch, Mynydd Parys, Los Rueldos ) appear to be favourable to the establishment of ‘ F. myxofaciens '-related bacteria that develop predominantly in the air–solution interface and may contribute importantly to biofilm formation. In contrast to what has been described for the Cae Coch ( Johnson, 2012 ) or Mynydd Parys ( Hallberg et al. , 2006 ), the stagnant pool from Los Rueldos would presumptively allow the establishment of a stratified and more complex microbial system. The more extreme conditions inside the Iron Mountain ( Tyson et al. , 2004 ) would restrict the genomic diversity in the existing stagnant pools or slow down the development of a stratified and mainly heterotrophic microbial growth. The stagnancy favours the creation of a system based on carbon mobilisation, where Archaea gain importance in the recycling, and also in the production of carbon compounds. The polymeric matrix where microbes appear embedded, allowing Los Rueldos streamer to be ∼15 cm thick, may acts as a safety shield against the prevailing extreme condition, the pH ∼2, and also as a massive carbon source, enabling other taxonomic groups, non-typical acidophiles, to develop more easily.",
"introduction": "Introduction Acid mine drainage (AMD) formations are common on our planet. They result from the microbially catalysed oxidation of pyrite (FeS 2 ) and other sulphide minerals, giving rise to the production of sulphuric acid and metal-rich solutions with a low pH (e.g., Rawlings, 2002 ). AMD formations extend across acidic niche boundaries, in which three distinct microenvironments may coexist: water, bed sediments and macroscopic structures, including streamers, slimes, mats, snottites and drapes. Among the AMD systems that have been characterised to date at the community level, approximately 30% have been reported to contain macroscopic microbial growths or biofilms (e.g., López-Archilla et al. , 2004 ; Tyson et al. , 2004 ; García-Moyano et al. , 2007 ; Macalady et al. , 2007 ; Ziegler et al. , 2009 ; Johnson, 2012 ; Jones et al. , 2012 ). There is increasing evidence that these acidic niche boundaries harbour a restricted set of acidophilic Bacteria and Archaea ( Bond et al. , 2000 ; Baker and Banfield, 2003 ; Hallberg et al. , 2006 ; He et al. , 2008 ; Yin et al. , 2008 ; Baker et al. , 2009 ) and Eukarya ( Aguilera et al. , 2006 ; Baker et al. , 2009 ). Bacteria that are widely distributed in these acidic ecosystems include, albeit in different proportions, those belonging to the Proteobacteria , Nitrospirae , Actinobacteria , Firmicutes , Bacteroidetes and Acidobacteria phyla. The members of these taxa are extreme acidophiles displaying pH optima below 3 and optimal mesophilic growth temperatures ranging from 17 to 45 °C ( Sánchez-Andrea et al. , 2011 ). In terms of their metabolic attributes, the bacterial members of these assemblages include chemolithoautotrophs that obtain energy mainly from iron, sulphur and hydrogen metabolism as well as mixotrophs and heterotrophs. The Archaea observed in AMDs generally belong to the order Thermoplasmatales . The metabolism of the described representatives of this order is exclusively organotrophic, with the exception of members of Ferroplasmaceae , which are able to metabolise iron ( Golyshina, 2011 ). Baker and Banfield (2003) detected many archaeal signatures, divided by the authors into numerous groups affiliated with the order Thermoplasmatales , representing a high proportion of uncultured Archaea that occur in metal-rich and low-pH habitats. Although these Archaea populate iron-rich environments, their metabolism has been speculated to most likely rely on the bacterial production of a steady supply of organic substrates, for example, sugar- and lipid-related compounds and polymers involved in biofilm formation ( Ram et al. , 2005 ; Belnap et al. , 2010 ; Denef et al. , 2010 ; Moreno-Paz et al. , 2010 ; Mueller et al. , 2010 ; Belnap et al. , 2011 ; Mueller et al. , 2011 ) or released by other free-living autotrophic acidophiles ( Nancucheo and Johnson, 2010 ). Various lineages of filterable ultramicroarchaea, referred to as the archaeal Richmond Mine acidophilic nano-organisms (‘ARMAN'), have recently been detected in AMD biofilms ( Sunna and Bergquist, 2003 ; Baker et al. , 2006 ; Juottonen et al. , 2008 ; Comolli et al. , 2009 ; Ziegler et al. , 2009 ; Baker et al. , 2010 ; Amaral-Zettler et al. , 2011 ; Bohorquez et al. , 2012 ; Ziegler et al. , 2013 ). ‘ARMAN'-related populations are believed to have a minor active role in AMD systems (yet to be defined because of the absence of cultivable members), as demonstrated by a very low contribution to the total metaproteome (0.7–1.8% of peptides), although they comprise ∼17% of the total metagenome ( Baker et al. , 2010 ). Research directed at exploring the metabolic capacities of community members has revealed that the chemical species present in oligotrophic AMD systems favour the establishment of a microbial chemolithotropic community ( Tyson et al. , 2004 ; Ram et al. , 2005 ; Rowe et al. , 2007 ; Belnap et al. , 2010 ; Amils et al. , 2011 ; Bertin et al. , 2011 ; González-Toril et al. , 2011 ; Johnson, 2012 ). However, when macroscopic microbial growths develop, the predominant metabolism shifts from chemolithotrophy to heterotrophy ( López-Archilla et al. , 2004 ; García-Moyano et al. , 2007 ; Macalady et al. , 2007 ; Ziegler et al. , 2009 ; Johnson, 2012 ; Jones et al. , 2012 ). Furthermore, a number of recent studies have indicated that there is a clear correlation between the phylotype richness and the pH conditions in situ ( Sánchez-Andrea et al. , 2011 ; Kuang et al. , 2013 ). This study presents a comparative OMIC analysis of three streamer/mat-shaped macroscopic growths along two distinct microenvironments in a mercury AMD formation ( Los Rueldos ) that displays a homogeneous pH of ∼2. This study has four aims: (1) to attain a comprehensive geochemical characterisation of the environment where these growths develop, (2) to profile the total microbial community and the streamer evolution dynamics, (3) to investigate whether shifts in the microbial populations are associated with geochemical and spatial gradients and (4) to provide a detailed characterisation of the metabolic shifts responding to microbial stratification through community genomics and proteomics analyses in each of the sampled populations. To the best of our knowledge, this study represents the first comparative integrative OMIC study investigating distinct macroscopic growths, including uncommon low pH suboxic macroscopic growths, along a single AMD formation.",
"discussion": "Results and discussion Geochemical and physical parameters in streamer/mat macroscopic growths Our aim was to provide a detailed characterisation of the geochemical characteristics of the uppermost oxic B1A and lowermost suboxic B1B strata and the non-stratified suboxic mat biofilm (B2) and to compare how the sampled populations differ at the levels of microbial phylotype, functional gene content and metabolic status. Both the microenvironments and corresponding streamer/mat-shaped macroscopic growths were characterised by a pH of ∼2 and an average annual temperature of ∼13 °C. They displayed a redox potential (Eh) of ∼256 mV and conductivities of 5.14 to 6.72 mS cm −1 throughout the year ( Supplementary Figure S2 ), which are among the lowest values reported for AMD formations. They displayed metal/metalloid contents of 422 mg l −1 Fe, 129 mg l −1 Al, 5 mg l −1 As, 0.013 mg l −1 Sb, 83 ng l −1 Hg and 7.6 μg l −1 Pb ( Supplementary Table S1 ). The multivariate statistical analysis indicated no significant geochemical differences among the three sampling sites, except that the submerged B1B (0.5±0.02 mg l −1 ) and B2 (0.25±0.01 mg l −1 ) mats at the sampling point exhibited a lower dissolved oxygen (DO) concentration compared with B1A (2.50±0.02 mg l −1 ), located in the air–solution interface. The DO profiles for the B1 and B2 microenvironments are displayed in Figure 1 . Microbial life in the Los Rueldos AMD is strongly stratified Full-length 16S rRNA and SSU rRNA hypervariable tag sequencing allowed the depth variations in the most abundant microbial populations to be compared with the geochemical and spatial variations in the selected contextual data. A total of 957 full-length 16S (B1A: 418; B1B: 275 and B2: 264) and 44 469 SSU (>150 nucleotides long; B1A: 9842, B1B: 23 727 and B2: 10 900) rRNA sequences were obtained and analysed. Bacterial stratification The bacterial sequences were grouped into 1005 operational taxonomic units according to the SSU rRNA hypervariable tag sequencing data (97% sequence identity level), with the majority belonging to the Proteobacteria phyla (>50% of the total sequences in all samples, with a variable proportion (1.5–2.4%) of unclassified SSU rRNA sequences). The γ- (B1A: 17.8–45% B1B: ∼87% and B2: 31–58%), β- (B1A: 28–75% B1B: 0.2% and B2: 13–23%) and α-Proteobacteria (B1A: 0.6–1.3% B1B: 0.03% and B2: 0.75%) classes were found, in that order. A number of sequences were also assigned to Acidobacteria (0.03–6% in all communities), Nitrospirae (B1A: 4.5–8% B1B: 1.7–2.3% and B2: 6–11%) and Actinobacteria (B1A: 2–7% B1B: 0.2–8% and B2: 4–18%), whereas other sequences were assigned to the candidate divisions WS6/TM7 (<0.5% in all samples) and AD3 (0.02–0.06%), Cyanobacteria (0.02% in B1A), Elusimicrobia (0.02% in B1A) and Lentisphaerae (0.01% in B1B) ( Supplementary Figure S3 ). In addition, according to a cutoff at 90% sequence identity level, 0–8.56% (for B1A), 0–8.98% (for B1B) and 9.0–14.11% (for B2) corresponded to unclassified bacterial full-length 16S and SSU rRNA sequences (average lowest and highest proportions shown). The sequences were further classified according to operational phylogenetic units (OPUs, equivalent to distinct taxonomic species; López-López et al. , 2010 ) ( Supplementary Table S2 ). The 18 identified bacterial OPUs were distributed among 13 major clusters based on clear phylogenetic positioning ( Figure 2 ; for details see Supplementary Results and discussion ). None of the OPUs were shared among the three macroscopic growths ( Figure 3a ), suggesting that bacterial life in the Los Rueldos AMD is strongly stratified. Notably, the OPUs belonging to B2 are widespread among all phyla ( Figure 2 ). The Shannon–Wiener and Chao-1 indices indicated that B2 displayed higher complexity when the data were obtained from full-length 16S rRNA, and an evenness value close to 1 indicated that dominance was shared among the various taxa in this sample. Nevertheless, the diversity indices obtained through SSU rRNA hypervariable tag sequencing revealed B1B as the more diverse sample ( Supplementary Table S3 ). Archaeal stratification The results from SSU rRNA hypervariable tag sequencing revealed the existence of 383 archaeal operational taxonomic units (97% sequence identity level). The Shannon–Wiener and Chao-1 indices derived from the full-length 16S rRNA sequence data indicated that B2 displayed the highest archaeal complexity and that B1B exhibited higher archaeal diversity when the data were obtained through SSU rRNA hypervariable tag sequencing ( Supplementary Table S3 ). We observed that none of the archaeal sequences were shared among the three macroscopic growths ( Figure 3a ) and that the B1A and B2 sequences appeared to be phylogenetically more related, even though they differ significantly in the O 2 concentration ( Figure 1 ). Most of the detected archaeal sequences belonged to the phylum Euryarchaeota , order Thermoplasmatales , although an important fraction of the full-length 16S and SSU rRNA sequences in B1A and B1B were affiliated with unclassified sequences ( Figure 4 ). In fact, 6.15–55.7% (for B1A), 2.46–44.12% (for B1B) and 0.32–4.76% (for B2) corresponded to unclassified archaeal full-length 16S and hypervariable rRNA sequences (average lowest and highest proportions shown). Among the 14 identified OPUs, 5 units per groups of clones were related to uncultured Thermoplasmatales lacking clear, up-to-date, taxonomic information ( Figure 4 and Supplementary Table S2 ). Cluster 1 was composed of a set of B1A and B1B sequences that the SILVA database ( Yarza et al. , 2008 ; Pruesse et al. , 2012 ) associates with Terrestrial Miscellaneous Gp (TMEG), placing it within the order Thermoplasmatales , where OPUs 10–14 were distant from the nearest described relative, Methanomassiliicoccus luminyensis (from the recently proposed order with still unclear name, candidate order ‘ Methanoplasmatales ' or ‘ Methanomassiliicoccales ' ord. nov) ( Paul et al. , 2012 ; Iino et al. , 2013 ). The rest of the sequences were associated with the genus Thermoplasma in accordance with the SILVA reference database or were identified as distantly related to Thermogymnomonas acidicola as per the Ribosomal Database Project (RDP) database. Between the two clusters containing these more diverse groups of these sequences, one was absent in B1B. As shown in Supplementary Figure S3 , other groups of sequences of clones detected in the B1B and B2 samples were represented by the previously designated group E1/E2 of uncultured euryarchaea, which is now referred to as a family-level clade within the order Methanomicrobiales and family Methanoregulaceae ( Sakai et al. , 2012 ). Putative methanogens accounted for a high proportion of the microorganisms in all three communities and were the second-most numerous archaeal group (OPUs 10–14) ( Figure 4 ). Filterable ultramicroarchaeal (‘ARMAN'-like) stratification Sequencing of the SSU rRNA hypervariable regions revealed the presence of 254 ‘ARMAN'-like operational taxonomic units (97% sequence identity level), and phylogenetic analysis of the retrieved ‘ARMAN'-like sequences revealed the existence of seven putative OPUs (one shared among communities; Figure 3a ). There were no clear differences in the composition among the samples as all of the obtained sequences appeared to be widespread in B1A, B1B and B2. However, B1A appeared to be the community displaying the majority of ‘ARMAN'-related diversity, whereas only one type of ‘ARMAN'-related clone was detected in B2 ( Figure 4 and Supplementary Figure S4 and Supplementary Table S3 ). The major homology of the Los Rueldos sequences was shared with sequences obtained from an acidic biofilm collected in the Harz Mountains (Germany) ( Ziegler et al. , 2009 , 2013 ). Approximately 18.38–100% (for B1A), 18.46–100% (for B1B) and 19.79–100% (for B2) sequences corresponded to unclassified ‘ARMAN'-like full-length 16S and SSU rRNA sequences (average lowest and highest proportions shown). The seven OPUs could be compartmentalised into three clusters defined by homology with known ‘ARMAN'-related archaeal sequences ( Figure 4 and Supplementary Figure S4 and Supplementary Table S2 ; for details see Supplementary Results and discussion ). Altogether, these results indicate that Los Rueldos appears to contain communities comprising greater major Bacteria and Archaea richness and diversity compared with other biofilm-containing AMD formations ( Figure 5 ). Fluorescent in situ hybridisation ( Supplementary Figure S5 ) and taxonomic profiling through SSU rRNA tag pyrosequencing ( Supplementary Table S4 and Supplementary Figure S6 ) analyses indicated that the Los Rueldos clusters also displayed greater diversity at early developmental stages (for details see Supplementary Results and discussion ). Los Rueldos exhibits a high proportion of uncommon Bacteria known to inhabit anoxic subsurfaces, uncultured Thermoplasmatales (including ‘ARMAN'-group Archaea ) and, to a lesser extent, putative methanogenic Archaea , but not the typical genera found in described AMD formations ( Bond et al. , 2000 ; Baker and Banfield, 2003 ; Hallberg et al. , 2006 ; He et al. , 2008 ; Yin et al. , 2008 ; Baker et al. , 2009 ; Wilmes et al. , 2009 ). Notably, Los Rueldos contains ∼44.95% and 11.84% of unclassified full-length 16S and hypervariable rRNA region sequences, respectively. We suggest that the distinct environmental features that characterise Los Rueldos ( Supplementary Table S1 ) may account for these differences and for the presence of new microbial species. The Los Rueldos microenvironments were observed to share a rather small core set of microorganisms that are not highly prevalent as only 1 (or 2.6%) out of 39 OPUs, representing a fraction of the ‘ARMAN'-related sequences that remain unrelated to any known database sequences, were shared among the three communities ( Figure 3a ). This result indicates that the Los Rueldos AMD contains a wide set of distinct microorganisms that form not only an extensive but also a stratified ecosystem. The lowermost/submerged (suboxic) mats were most similar to each other and exhibited the highest diversity, being particularly enriched in sequences representing presumptive low-O 2 -adapted organisms related to the Acidithiobacillales ‘RCP1-48' cluster, Acidobacteria , Leptospirillum ferrooxidans -like (all described Leptospirillum are known to be obligate aerobes), Acidimicrobiaceae -related Actinobacteria , Firmicutes and Lentisphaerae , associated with anoxic environments ( Hedlund et al. , 2011 ), candidate divisions WS6 and TM7, and candidate order ‘ Methanoplasmatales '/or ‘ Methanomassiliicoccales '. The sequences related to Rhizobium ( α-Proteobacteria ), ‘L. ferrodiazotrophum ', candidate division AD3, detected for first time in sandy surface soils ( Zhou et al. , 2003 ), Cyanobacteria and Elusimicrobiales , found in both oxic and anoxic environments, were mostly associated with the uppermost (oxic) mat, which also displayed a higher diversity of Archaea related to the ‘ARMAN' group. Marked taxonomic stratification was observed at the genus level within the Los Rueldos communities. L. ferrooxidans- related bacteria, able to thrive at depths below 60 cm ( Kimura et al. , 2005 ), and the non-motile Acidithiobacillus ferrooxidans ( Valdés et al. , 2008 ) appeared within the suboxic strata of the macroscopic growths (B1B and B2), whereas Acidithiobacillus ferrivorans , motile rods ( Hallberg 2010 ), and ‘L. ferrodiazotrophum '-related bacteria, able to perform atmospheric N 2 fixation ( Tyson et al. , 2005 ), thrived in the oxic B1A layer. Other organisms, such as those belonging to Acidobacteria , common in (acidic) terrestrial locations, Firmicutes , which have been detected in AMD anaerobic sediments (e.g. Sulfobacillus spp., Sánchez-Andrea et al. , 2011 ), most Actinobacteria (autotrophic or heterotrophic aerobes or anaerobes) and the candidate divisions WS6, abundant community members in organic-rich anaerobic environments ( Dojka et al. , 2000 ) and TM7, were absent in the oxic layer of the streamer. In addition, as no significant changes were identified in the solution parameters of pH, temperature, conductivity and redox potential within the microenvironments, the obtained results confirmed the importance of combining O 2 bioavailability and spatial distance in fine-tuning the acidophilic microbial structure. Genomic shifts responding to microbial stratification The total extracted DNA was directly pyrosequenced using a Roche GS FLX DNA sequencer, which produced a total of ∼14.4 (for B1A), ∼14.9 (for B1B) and ∼10.9 (for B2) Mbp of assembled DNA sequences. Approximately 57 815 (B1A: 22 162; B1B: 19 692 and B2: 15 961) potential protein-coding genes (cutoff of ⩾20 amino acids) were identified ( Supplementary Table S5 ). The obtained hits were filtered based on a minimum e-value (1e −05 ) and an alignment length of 75% minimum, and 19% were found to be shared among the three communities ( Figure 3b ). General predictive metabolic features of Los Rueldos KEGG subsystem-based JCoast annotations were used to gain a better understanding of how these population shifts could influence their metabolic potential ( Figure 6 ). To extend this analysis, we compared the results with the Richmond AMD (AMD.R) metagenome ( Tyson et al. , 2004 ). Common features included an over-representation of ‘Carbohydrate Metabolism', ‘Amino Acid Metabolism', ‘Replication and Repair' and ‘Membrane Transport' and an under-representation of ‘Cellular Processes' ( Figure 6 ). In contrast, the distribution of the subsystems ‘Glycan Biosynthesis and Metabolism' (B1A: 2.67% rel. abundance level; B1B: 2.21% B2: 2.19% and AMD.R: 1.23%), ‘Signal Transduction' (B1A: 4.23% B1B: 2.83% B2: 3.38% and AMD.R: 1.52%), ‘Cell Growth and Death' (B1A: 0.77% B1B: 0.76% B2: 0.74% and AMD.R: 0.34%) and ‘Translation' (B1A: 6.51% B1B: 5.45% B2: 6.56% and AMD.R: 10.35%) appeared to be significantly different for the B1A, B1B and B2 populations compared with the AMD.R. In addition, the abundance levels of the corresponding pooled proteins assigned to the ‘Cell Motility' subsystem were also particularly high in B1A (B1A: 3.16% B1B: 1.37% B2: 1.82% AMD.R: 1.52%). The significant enrichment in ‘Cell motility' and, to a lower extent, in ‘Signal transduction' in B1A appears to agree with the higher protein expression levels of chemotaxis, flagellar, efflux and cell division proteins (for details, see Supplementary Results and discussion and Supplementary Table S6 ) and with the observed microbial stratification and presence of the highly motile At. ferrivorans ( Hallberg, 2010 ) in the uppermost B1A layer, which is more exposed to the flow influence than the B1B and B2 strata, where flagella-absent At. ferrooxidans ( Valdés et al. , 2008 ) thrives ( Figure 2 ). The heatmap analysis ( Figure 6 ) also revealed that all three samples clustered separately from AMD.R, suggesting that functional differences may exist between both AMD formations, regardless of the microenvironment considered in Los Rueldos , as it was observed at the population structure level ( Figure 5 ). Notably, the B1B sample was functionally closer to B2 than to B1A ( Figure 6 ), even though they belong to different microenvironments. This finding may agree with the observations that both B1B and B2 hold a higher similarity in terms of microbial diversity ( Figures 2 and 4 ) and that both conformed the suboxic parts of the microbial mats. Selection and evolution of key metabolic traits We attempted to obtain insights into whether each population has selected and evolved different capabilities for the turnover of major chemical species (S, N, CO 2 , H 2 and Fe). Although members of all three communities have the potential to contribute to the cycling of these species, a few notable observations should be mentioned ( Figure 7 ). First, the presence of genes encoding rhodaneses, known to be activated at elevated concentrations of toxic sulphides as a defence mechanism, was 2.4-fold higher in B1B than in B1A or B2, suggesting that B1B is most likely a permanent euxinic formation compared with the other macroscopic growths. Second, nitrification/denitrification processes have minor importance in all three communities compared with the S or Fe oxidation processes. Indeed, the B1A ecosystem was the sample with a high abundance of genes for rusticyanins, sulphocyanins and cbb 3 -type cytochrome c oxidases (∼2- and 1.3-fold more abundant than in B1B and B2) and enzymes (e.g., TusD and DsrE) for the oxidation of sulphide (HS − ), which were ∼3-fold less abundant in B1B and absent in B2. Enzymes indicative of the putative presence of sulphur or reduced inorganic sulphur compounds metabolism such as sulphide:quinone reductases, often associated with acidophilic bacteria ( Quatrini et al. , 2009 ; Liljeqvist et al. , 2011 ; Liljeqvist et al. , 2013 ), were also encountered in all three metagenomes, although at very similarly low abundance level. Interestingly, whereas genes encoding nitrogenase MoFe proteins for nitrogen fixation were present at similar levels in B1A and B1B but absent in B2, those for nitrate reduction were most abundant in B2 and B1B (∼2-fold more abundant than in B1A). This agrees with the presence of ‘ L. ferrodiazotrophum' in B1A and B1B biofilms; in addition, BLAST searches of the NCBI non-redundant database with the nitrogenase MoFe protein sequences showed that at least 44% of them do have as best hit a homologous protein from this bacterium (identity ranging from 37% to 94%). According to thermodynamic requirements, the respiration of both reduced S and Fe is a highly exergonic process, and in the presence of high amounts of electron donors, these respiration types could support elevated growth, yielding significant amounts of organic matter in a form of such as polysaccharides ( Moreno-Paz et al. , 2010 ). The latter compounds are well-known substrates of anaerobic fermenters and organotrophic hydrolytic microorganisms. Notably, the main end products of fermentation activity under acidic, low saline conditions are mainly short-chained fatty acids, CO 2 and H 2 . Accordingly, the diffusion of gases into the overlaying strata of the biofilm can support the autotrophy because of a hydrogenoclastic mode of carbon fixation, generally assumed to be common in the majority of chemolithoautotrophic acidophiles. Thus, hydrogen has to be included as an electron donor, in addition to the S and Fe described above. This assumption is consistent with the elevated presence of [Ni-Fe] hydrogenases (6- and 1.4-fold more abundant than in B1B and B2) and ribulose-1,5-bisphosphate carboxylases (∼3-fold more abundant than in B1B and B2) in the B1A uppermost layer, the main activities of which involve gaining reducing equivalents from molecular hydrogen and supporting the Calvin–Benson–Bassham cycle of carbon fixation, respectively. Interestingly, a comparison between the suboxic B1B and B2 mats revealed that whereas CO 2 fixation gene signatures were observed at a similar level in both microbial formations, the genes encoding hydrogenases were particularly abundant in B2 (4-fold more abundant than in B1B). Taken together, these results suggest higher cell densities in the uppermost oxic B1A mat, as it was particularly enriched and active in multiple exergonic processes. This observation was further supported by 4′,6-diamidino-2-phenylindole-staining-based cell counting: ∼5 × 10 12 ± 1.36 × 10 12 , ∼2 × 10 12 ±1.14 × 10 12 and ∼1.5 × 10 12 ±2.75 × 10 12 cells per cm 3 in the B1A, B1B and B2 structures, respectively. A global analysis of the appearance and frequencies of the recovered phylogenetic groups led us to conclude that all three studied ecosystems have many metabolic parameters in common. Notably, however, the presence of oxygen appeared to prevail as a main shaping factor in the B1A ecosystem, which differentiates it from the other two systems. On the basis of the gathered data, B1B and B2, the suboxic parts of the mats, are highly reduced ecosystems inhabited by Proteobacteria , different groups of unclassified Euryarchaeota related to the ‘ARMAN' group and members of the newly proposed candidate order ‘ Methanoplasmatales '/‘ Methanomassiliicoccales ' ord. nov ( Paul et al. , 2012 ). Interestingly, the methylotrophic modification of methanogenesis, obligately relying on hydrogen uptake, has been proposed as a metabolic priority for the members of ‘ Methanoplasmatales '/‘ Methanomassiliicoccales ', which were observed to be particularly enriched in B2 compared with B1B. As it has also been recently demonstrated in mature ‘ F. acidarmanus ' Fer1 biofilms ( Baker-Austin et al. , 2010 ), a second contributing factor to the metabolic differences observed may be related to the biofilm architecture and development, which can produce a shift in anaerobic lifestyles by affecting the diffusion of gases from the lowermost to the overlaying strata (e.g., reduced S), the access to substrates from the atmosphere (e.g., nitrogen) or the accumulation of toxic compounds (e.g., toxic sulphides). The differences observed between B1B and B2 at the level of hydrogen and sulphide metabolism underscore this hypothesis. Shotgun metaproteome measurements and metabolic shifts We selected a shotgun metaproteomic approach to query the active populations and to ascertain their metabolic status within the mats. A total of 3407 proteins (B1A: 1472; B1B: 970 and B2: 965) were unambiguously identified and quantified ( Supplementary Table S6 ; for details, see Supplementary Materials and methods ). Among them, 1589 were unique proteins (i.e., proteins exclusive to any/each of the three locations), more than 99% of which could be taxonomically assigned. As shown in Supplementary Figure S8 , the protein expression levels revealed exponential distributions, with B1B displaying the highest range of protein expression levels (138.32–0.0046 mmol mol −1 ), followed by B2 (124.35–0.0044 mmol mol −1 ) and, to a much lower extent, B1A (33.45–0.0054 mmol mol −1 ). Only 206 out of 1589 (or ∼13%) uniquely expressed proteins were shared by all three communities, suggesting high divergence in the active member composition ( Figure 3c ). B1A and B1B, albeit in the same microenvironment, shared the least number of active proteins (286 out of 1589), whereas B1B and B2 (415) and B1A and B2 (517) were more similar in terms of the active protein content ( Figure 3c ). The observation that a higher number of OPUs were shared between B1B and B2 (7 OPUs) and between B1A and B2 (5) compared with B1A and B1B (only 3) ( Figure 3a ) may account for the observed differences. The contribution of sequences belonging to Bacteria (B1A: 89% B1B: 81% and B2: 85% total proteins) was significantly higher than that associated with Archaea (B1A: 10% B1B: 18% and B2: 14%), although the suboxic mats contain a slightly higher contribution of archaeal proteins ( Supplementary Figure S8 ). Eight (B1A: 3; B1B: 3 and B2: 2) were proteins assigned to Eukaryota . Proteobacteria was the major contributor (from 64% to 69%) to the total community proteomes, followed to a much lower extent by Actinobacteria (from 8.4% to 11.7%) and Nitrospirae (from 3.4% to 5.6%) in all sampled populations. The only major differences were observed in B1B at the level of Firmicutes proteins (∼6.7%), which accounted for ∼0.3% in B2 and ∼0.1% in B1A. By using a previously published method ( Hernández et al. , 2013 ; for details see Supplementary Materials and methods ), a total of 489 predicted metabolic reactions (B1A: 201; B1B: 141 and B2: 147) associated with expressed proteins were identified. Only 65 (or ∼13%) reactions appeared to be shared by the three communities ( Figure 3d ). The maps displaying changes in the various reactions are shown in Supplementary Figure S9 . The classification of the pathways obtained in the samples (heat map: Supplementary Figure S10 ) showed the same functional similarity between samples B1B and B2 as was identified by KEGG profiling ( Figure 6 ). Supplementary Figure S10 shows several notable findings. First, the high expression level of proteins involved in propanoate and pyruvate metabolism was common to all three communities. The fact that the main end products of fermentation activity under acidic conditions are mainly short-chained fatty acids agrees with the relevant preponderance of propanoate metabolism in the Los Rueldos microenvironments. Nitrogen (3- and 6-fold), tyrosine (17.3- and 5.8-fold), sphingolipid (4.0-fold each), purine (2.0-fold each) and histidine (2.0-fold each) metabolism and peptidoglycan biosynthesis (57- and 2.5-fold) were clear indicators of the differences between the samples and allowed B1A active metabolism to be distinguished from that in B1B and B2 (pooled expression level fold changes within parentheses). The anoxic B1B and B2 mats were characterised by higher abundances and expression levels of proteins for the butanoate (2.8- and 4.2-fold), CO 2 (3-fold each), CH 4 (3-fold each), fructose and mannose (2-fold each) and fatty acid (2.2- and 3.9-fold) metabolism as well as lipopolysaccharide biosynthesis (11-fold each) compared with the oxic B1A mat. In addition, the metabolism of a number of compounds was most active in both B1A and B1B compared with B2 (4.0-fold), for example, amino and nucleotide sugars (4.8- and 4.4-fold), alanine, aspartate and glutamate (4-fold each) as well as nicotinate and nicotinamide (4.1- and 2.6-fold). Finally, valine, leucine and isoleucine metabolism and folate biosynthesis were presumably the most active in B1B compared with B1A (2.4-fold) and B2 (7.0-fold). The differences at the levels of sphingolipid metabolism and peptidoglycan biosynthesis (most active in the oxic B1A mat) as well as those of fatty acid metabolism and lipopolysaccharide biosynthesis (most active in suboxic mats) may be related to differences in the population structure and metabolism of different cell membrane components. Interestingly, the results indicate that B1A and B1B populations potentially metabolise amino acids in a preferential way compared with the B2 population. A similar scenario has been suggested for communities characterised by low (but not high) pH ( Belnap et al. , 2011 ). However, the data generated herein indicate that the aromatic amino acids, histidine and tyrosine, are the best sources of carbon and energy in the uppermost population, whereas linear aromatic amino acids, such as valine, leucine and isoleucine, are barely utilised, in contrast to the lowermost populations. In addition, the metabolic analysis confirmed that none of the amino-acid pathways were particularly enriched in B2. As folate derivatives are known to provide the majority of one-carbon units to the cells and their biosynthesis was improved in B1B, we suggest that the relative contribution of the carbon pool for synthetic purposes is also stratified; a similar observation accounts for the synthesis of cofactors such as nicotinate and nicotinamide precursors, which are more produced in B1A and B1B than in B2. Furthermore, three hydrogenases, one rusticyanin and three cbb 3 -type cytochrome c oxidase subunits relevant for H 2 and Fe metabolism were found among the expressed proteins ( Supplementary Table S6 ). Within the three hydrogenases (one common, one in B1A and one in B1B, with ambiguous taxonomic affiliations), the expression levels were 32- and 8.4-fold higher in B1A than in B1B and B2, respectively, which is in agreement with the genomic evidence indicating that this community was most efficient for hydrogenoclastic activity. Secondly, among the one rusticyanin (binned to phylum Proteobacteria , most likely of the Acidithiobacillales ) and three cbb 3 -type cytochrome c oxidases (two binned to phylum Proteobacteria , most likely being members of Gallionellales , and one to Actinobacteria ), three were observed at high concentrations in B1A (up to 1.1 mmol mol −1 protein), and only one (binned to Actinobacteria ) was observed in B1B (1.4 mol mol −1 ) and B2 (0.41 mmol mol −1 ). These results again confirm that the oxic mat population is more active for Fe metabolism."
} | 11,188 |
23865623 | PMC3750248 | pmc | 3,103 | {
"abstract": "Background Metal sulfide mineral dissolution during bioleaching and acid mine drainage (AMD) formation creates an environment that is inhospitable to most life. Despite dominance by a small number of bacteria, AMD microbial biofilm communities contain a notable variety of coexisting and closely related Euryarchaea , most of which have defied cultivation efforts. For this reason, we used metagenomics to analyze variation in gene content that may contribute to niche differentiation among co-occurring AMD archaea. Our analyses targeted members of the Thermoplasmatales and related archaea. These results greatly expand genomic information available for this archaeal order. Results We reconstructed near-complete genomes for uncultivated, relatively low abundance organisms A-, E-, and Gplasma, members of Thermoplasmatales order, and for a novel organism, Iplasma. Genomic analyses of these organisms, as well as Ferroplasma type I and II, reveal that all are facultative aerobic heterotrophs with the ability to use many of the same carbon substrates, including methanol. Most of the genomes share genes for toxic metal resistance and surface-layer production. Only Aplasma and Eplasma have a full suite of flagellar genes whereas all but the Ferroplasma spp. have genes for pili production. Cryogenic-electron microscopy (cryo-EM) and tomography (cryo-ET) strengthen these metagenomics-based ultrastructural predictions. Notably, only Aplasma, Gplasma and the Ferroplasma spp. have predicted iron oxidation genes and Eplasma and Iplasma lack most genes for cobalamin, valine, (iso)leucine and histidine synthesis. Conclusion The Thermoplasmatales AMD archaea share a large number of metabolic capabilities. All of the uncultivated organisms studied here (A-, E-, G-, and Iplasma) are metabolically very similar to characterized Ferroplasma spp., differentiating themselves mainly in their genetic capabilities for biosynthesis, motility, and possibly iron oxidation. These results indicate that subtle, but important genomic differences, coupled with unknown differences in gene expression, distinguish these organisms enough to allow for co-existence. Overall this study reveals shared features of organisms from the Thermoplasmatales lineage and provides new insights into the functioning of AMD communities.",
"conclusion": "Conclusions The metagenomic and phylogenetic analyses presented here reveal evolutionary, metabolic and cell structural differences among uncultivated archaea that occur in AMD biofilm communities. We recognize Iplasma as a representative of a phylogenetically distinct class and provide both ribosomal RNA gene-based and genomic evidence supporting this conclusion. We present evidence for two new genera of the Thermoplasmatales order (one comprising E- and Gplasma and another including A-, B-, C-, and Dplasma). Based on genome content, it appears that all of the AMD plasmas have the capacity to grow both aerobically and anaerobically. However, their differing genetic potentials for biosynthesis of cofactors and amino acid precursors may allow the coexisting AMD plasmas to take advantage of microniches that occur in structurally differentiated biofilms [ 87 ]. Similarly, differences in motility may allow some AMD plasmas to colonize new sites or move along physicochemical gradients. We report new types of blue-copper proteins that future work may show are involved in iron oxidation and may further differentiate the AMD plasmas. Comparative genomic analyses also provide new information about organisms in the Thermoplasmatales clade, indicating the importance of methylotrophy, carbon monoxide oxidation, and other heterotrophic metabolisms to the AMD plasmas and demonstrating the existence of S-layer proteins outside of the Picrophilus genus.",
"discussion": "Results and discussion Phylogeny We previously published a phylogenetic tree of the 16S rRNA gene of the AMD plasmas [ 16 , 17 ]. Here we improve upon that tree with the addition of a number of new taxa. This tree illustrates that the Richmond Mine AMD plasmas form the following clades: A-, B-, and Cplasma, E- with G-plasma, Dplasma with a number of environmental clones, I-plasma with a number of environmental clones, and the Ferroplasma spp. with Acidiplasma aeolicum . All of the 16S rRNA gene sequences, other than those of Fer1 and Fer2 (which have identical sequences), share less than 97% nucleotide identity. The Iplasma gene is the most divergent, and it is almost certainly not a member of the order Thermoplasmatales or the class Thermoplasmata (Figure 1 , Additional file 1 , Additional file 2 ). We found evidence for this classification in the phylogenetic analysis for both 16S rRNA and ribosomal protein S15 genes, where Iplasma groups outside of the Thermoplasmata clade (Figure 1 and Additional file 3 ) as observed previously [ 16 , 17 , 19 , 20 ]. In the case of the 16S tree, Iplasma forms a monophyletic group with a number of environmental clones from acidic solfataric mud and acidic springs (Genbank) [ 21 ]. Because archaeal phylogeny is still unresolved, it is impossible to exactly determine the phylogeny of new taxa [ 22 ]. However, the branch length separating Iplasma and the Thermoplasmata organisms is greater than 0.25, supporting the separation of Iplasma into a new class of Euryarchaea . We previously suggested this in Justice et al. , 2012 [ 20 ], but the current study provides much more extensive evidence for this classification. The monophyletic clustering of Eplasma and Gplasma and that of A-, B-, and C-, and Dplasma on the 16S rRNA tree suggests that they belong to new genera of Thermoplasmatales (Figure 1 , Additional files 1 , 2 ). This finding is further supported by similar amino acid identities of shared orthologs from A-, E-, and Gplasma to the other Thermoplasmatales archaea (Additional file 4 ). Figure 1 16S rRNA tree indicating the possibility of a candidate class that includes Iplasma. Ferroplasma acidarmanus is Fer1 and Fer2. Bootstrap values are shown at branch splits. Gene start and stop positions and Genbank accession numbers are listed after organism names. We examined a number of whole-genome measures of relatedness to further investigate evolutionary relationships. First, we identified the fraction of predicted orthologs in pairwise comparisons, and then determined their average amino acid identity. The normalization step involved dividing the number of orthologs by the average number of genes in the pair of genomes considered. Iplasma shares a lower percentage of orthologs, and a lower average amino acid identity with each of the other AMD plasma genomes than the other AMD plasma genomes share with each other (Additional files 4 and 5 ), consistent with a divergent phylogenetic placement. Fer1 vs. Fer2 has the highest amino acid identity (82%), as expected for closely related species. It was previously suggested that the genomes of Fer1 and Fer2 are different enough to merit classification as separate species based on analysis of recombination rates [ 23 ]. This result provides additional evidence supporting this claim, as Konstantinidis and Tiedje, 2005 found that approximately 95-96% amino acid identity corresponded to the 70% DNA-DNA hybridization species cut-off [ 24 ]. Eplasma and Gplasma are relatively closely related, as are Aplasma and Gplasma. In addition to amino acid identity, we also looked at conserved gene order as a measure of evolutionary distance [ 16 ]. For each genome pair, we determined the number of syntenous orthologs and divided this by the number of shared orthologs. The Iplasma genome has the lowest synteny with the other AMD plasma genomes, Fer1 vs. Fer2 displays the highest synteny, followed by Eplasma vs. Gplasma (Additional file 6 ). The same trend holds true for another measure of synteny, the average length of syntenous blocks of genes in pairwise comparisons (Additional file 7 ). These whole-genome data support the tree topology and evolutionary distances assigned to the 16S rRNA genes in our phylogenetic analysis. General genome features Genome features of the AMD plasma organisms, including the number of tRNA synthetases and ribosomal genes, are summarized in Yelton et al. , 2011 [ 16 ]. All of the genomes contain the full suite of tRNAs and most or all orthologous marker genes [ 16 , 25 ], consistent with a high degree of genome completeness (Additional file 8 ). Important metabolic and structural features of each genome are listed and illustrated in Table 1 and Additional file 9 . Table 1 General overview of metabolic differences within the AMD plasmas Function APL EPL GPL FER1 FER2 IPL Aerobic metabolisms Aerobic respiration Y Y Y Y Y Y Fe oxidation (blue-copper protein) Y N Y Y Y N Aerobic CODH N N N Y Y Y Anaerobic CODH N N N N Y N Anaerobic metabolisms Formate dehydrogenase Y Y N Y Y Y Putative hydrogenase complex Y Y Y Y Y N Fermentation to acetate Y Y Y Y Y Y Carbon catabolism Glycolysis Y Y Y Y Y Y Entner-Doudoroff pathway Y Y Y Y Y Y Beta oxidation Y Y Y Y Y Y Methylotrophy Y Y Y Y Y Y Biosynthesis Cobalamin biosynthesis N N N Y Y N Molybdopterin biosynthesis Y N N Y Y Y Histidine synthesis Y N Y Y Y N Leucine/Isoleucine synthesis Y N Y Y Y N Glyoxylate shunt N Y N N N N Motility Flagella Y Y N N N N Chemotaxis N N N N N N Toxic metal resistance Arsenic resistance Y Y Y Y Y Y Copper resistance Y Y Y Y Y Y Mercury resistance Y Y Y Y N Y Structure/Motility S-layer Y Y Y N Y Y Ether-linked lipids Y Y Y Y Y Y Cellulose/cell wall polysaccharides N N N N N N Pili N Y Y N N Y APL is Aplasma. EPL is Eplasma. GPL is Gplasma. FER1 and FER2 are Ferroplasma acidarmanus type I and type II. IPL is Iplasma. Y indicates that the pathway is found in the genome, whereas N indicates that it is not. Unique genomic island in G-plasma A genomic island of potential importance was identified in the Gplasma genome. It consists of a block of nine genes that have virtually no orthologs in any of the other Thermoplasmatales genomes and is made up primarily of proteins of unknown function (Figure 2 , Additional file 10 ). All nine of the proteins are represented in a whole community proteomic dataset reported previously [ 26 ], and three are among the most highly detected proteins of this organism in that dataset. The motifs and domains identified suggest that a number of these proteins are membrane associated, including a protein containing an AAA + FtsH ATPase domain (gene number 13327_0053) (found in a membrane-integrated metalloprotease [ 27 ]), a protein containing six transmembrane motifs and a signal peptide (13327_0056), and another with fourteen transmembrane motifs and a signal peptide (13327_0059). Additionally, three of these proteins include a rhodanese-like domain possibly involved in phosphatase or sulfurtransferase activity and another contains an armadillo repeat region, often used to bind large substrates such as peptides or nucleic acids (13327_0058). Figure 2 Cluster of unique genes in Gplasma. Arrows are proportional to the length of each gene and indicate its direction of transcription. The gene numbers are shown inside the arrows. All genes are from contig number 13327. Motif and domain-based annotations are shown above the arrows. Genes with no annotations are hypothetical proteins. Rhod indicates a rhodanese-like domain. The absence of any orthologs to this block of hypothetical proteins in other Thermoplasmatales genomes is a strong indication that it may have been acquired by horizontal gene transfer. Many flanking genes have syntenous orthologs in other closely-related genomes. However, the lack of GC skew in the nucleotide signature of these genes suggests that the transfer event was not recent or that the donor had a similar GC content to Gplasma. Cell wall biosynthesis and imaging Thermoplasmatales cells are generally bounded by a single membrane, except for two Picrophilus species that have a single membrane surrounded by a surface-layer (S-layer) [ 13 ]. We characterized archaeal-rich biofilm communities via cryo-electron microscopy and identified surface layers on many single membrane bound cells (Figure 3 , Additional file 11 ). Thus, we looked for the genes needed for surface layer structural proteins and their post-translational modifications (i.e., N-glycosylation). We found putative S-layer genes in all of the AMD plasma genomes (except Fer1) that are homologous with the predicted P. torridus S-layer genes (Additional file 12 ) [ 28 ], but found no homology to the predicted S-layer genes in their next closest relative, Acidiloprofundum boonei [ 29 ]. We also found genes potentially involved in archaeal S-layer protein N-glycosylation. Of particular interest were homologs to the AglD and AglB genes of Haloferax volcanii , which have been shown to be essential to S-layer protein N-glycosylation in that organism [ 30 ]. Many of the Iplasma S-layer-related genes occur in a cluster, and several have conserved gene order in distant relatives, including several enzymes that attach sugars to a dolichol that might serve as a membrane anchor for the formation of an oligosaccharide during N-glycosylation. The Iplasma genome contains a gene cluster syntenous with distant relatives that encodes all of the proteins in the ADP-L-glycero-β-D-manno-heptose (AGMH) biosynthesis pathway (Additional file 12 ). AGMH is attached to S-layer proteins in gram-positive bacteria [ 31 - 33 ], suggesting that this may be involved in S-layer glycosylation in Iplasma as well. Finally, in the same genomic region genes are found for the biosynthesis of GDP-L-fucose, a glycoprotein component, and dTDP-L-rhamnose, a lipopolysaccharide component, indicating that these may make up part of the AMD plasma S-layer polysaccharides. Figure 3 Cryo-EM of surface-layer on an AMD plasma cell from the Richmond Mine. Insets show a higher magnification. Arrows point to putative surface-layer proteins. Panel A and panel B show evidence of proteinaceous surface layers in two different cells collected from the Richmond Mine AMD. Energy metabolism (a) iron oxidation Ferric iron produced by biotic iron oxidation drives metal sulfide mineral dissolution, and thus iron oxidation is one of the most important biochemical processes that occurs in acid mine drainage systems [ 34 - 36 ]. In order to assess which of the AMD plasmas were involved in this process, we looked for potential iron oxidation genes via BLASTP. Based on this analysis, Aplasma and Gplasma contain homologs to rusticyanin, a blue-copper protein implicated in iron oxidation in Acidithiobacillus ferrooxidans (Additional file 12 ) [ 37 ]. The Acidithiobacillus ferroxidans rusticyanin can complex with and reduce cytochrome c in that organism [ 38 - 41 ], is upregulated during growth on ferrous iron [ 40 - 47 ], and is believed to be essential to iron oxidation [ 48 ]. Allen et al. [ 49 ] inferred that a related blue-copper protein, sulfocyanin, is involved in iron oxidation in Ferroplasma spp. (e.g. Fer1), and Dopson et al. provided proteomic and spectrophotometric evidence that support this inference [ 50 ]. The Fer2 genome contains a sulfocyanin homolog, whereas E- and Iplasma do not appear to have a rusticyanin or a sulfocyanin gene, suggesting that they are not iron oxidizers. Additional evidence for the function of these genes was found in their inferred protein structure. All of the AMD plasma blue-copper proteins (BCPs) contain the characteristic type I copper-binding site, consisting of two histidines, one cysteine, one methionine and a cupredoxin fold, identified by a 7 or 8-stranded β-barrel fold [ 51 - 53 ] (Additional file 13 ). However, the AMD plasma BCPs differ in their conservation of motifs identified by Vivekanandan Giri et al. in sulfocyanin and rusticyanin [ 54 ]. The Fer1 and Fer2 BCPs include one recognized sulfocyanin motif, FNFNGTS, as well as imperfect conservation of the motifs identified in both sulfocyanin and rusticyanin (Additional file 14 ). Conversely, the Aplasma and Gplasma blue-copper proteins do not contain any of the conserved sulfocyanin-specific motifs. Instead, they contain imperfect matches to the rusticyanin-specific motif. These results are consistent with the inferences made based on homology alone in that they suggest that Fer1 and Fer2 BCPs are sulfocyanins and that A- and Gplasma BCPs are rusticyanins. Phylogenetic analysis was carried to confirm the original homology-based annotations of the AMD plasma BCPs and to look for evidence of horizontal gene transfer. The phylogenetic tree groups the Aplasma BCP gene with the rusticyanins, whereas the Fer1 and Fer2 genes group with the sulfocyanins (Additional file 15 ). Interestingly, the Gplasma gene is so divergent that it does not consistently group with the other iron-oxidation blue-copper proteins. Its divergence seems to stem from two more β-strands than most of the other rusticyanin-like proteins (Additional file 13 ). The tree also provides evidence for the horizontal transfer of both sulfocyanin and rusticyanin genes. Related rusticyanin-like genes are found in the Gammaproteobacteria and in a variety of Euryarchaea . Similarly, closely related sulfocyanin-like genes are found in Euryarchaea and Crenarchaea . Tyson et al. hypothesized that the sulfocyanin found in the Fer1 genome forms part of an iron-oxidizing SoxM-like supercomplex, similar to the one involved in sulfur oxidation in Sulfolobus acidocaldarius [ 55 - 57 ]. The S. acidocaldarius SoxM supercomplex contains a BCP, a cytochrome b and a Rieske iron sulfur protein. In S. acidocaldarius the sulfocyanin functions much like the cytochrome c in the complex III/cytochrome bc complex used during iron oxidation (and aerobic respiration) in A. ferrooxidans [ 58 ]. The results presented here further support Tyson’s hypothesis in that both the cytochrome b and rieske Fe-S protein subunits of the hypothetical SoxM-like complex were identified in all AMD plasma genomes. None of the genomes contain homologs to any of the other genes in the A. ferrooxidans rus operon [ 42 , 59 , 60 ]. In general, the absence of blue-copper proteins suggests that E- and Iplasma lack the Fe-oxidation capability entirely, whereas the other AMD plasmas utilize two different pathways to carry out this metabolism. It is possible that E- and Iplasma do have blue-copper proteins in their genomes because gaps remain in their assemblies, but we took steps to rule out this possibility (see Methods section). Because Fe(II) is an abundant electron donor in the AMD environment, this observed genetic variation in Fe oxidation potential may be important in niche differentiation. Energy metabolism (b) carbon monoxide dehydrogenase The Iplasma, Fer1 and Fer2 genomes encode genes for a possible carbon monoxide dehydrogenase, (CODH) (Additional file 12 ), including genes for all three subunits of the CoxMLS complex. Recent research suggests that aerobic CO oxidation may be a widespread metabolism among bacteria [ 61 ]. Thus, it is a conceivable metabolism for organisms in AMD systems. In fact, it may be a good source of carbon or energy in the Richmond Mine, where up to 50 ppm of CO has been measured in the air (M. Jones, personal communication 2011). A phylogenetic tree of the catalytic subunits of CODH indicates that all but one of the AMD plasma complexes is more closely related to the aerobic type than the anaerobic type (Additional file 16 ). The active site encoded by these genes also suggests that they are aerobic CODH proteins closely related to the form II CODH, which has the motif: AYRGAGR (Additional file 17 ) [ 61 , 62 ]. This enzyme can be used to make CO 2 either for C fixation or to make reducing equivalents. The AMD plasma genomes do not contain any of the genes for the known archaeal C fixation pathways. Based on these observations, we hypothesize that these CODH proteins are used solely to make electrons available for aerobic respiration. However, it is possible that they use a novel C fixation pathway that incorporates this CODH [ 63 ]. Interestingly, our CODH phylogenetic tree suggests that there is another AMD plasma gene that encodes a Ni-CODH, Fer2 scaffold 31 gene 47. Ni-CODHs are anaerobic and reduce CO 2 to CO. This enzyme is generally involved in C fixation via the Wood-Ljungdahl pathway, the genes for which are not found in the AMD plasma genomes. Thus, this gene may be involved in a novel carbon fixation pathway in Fer2. Additional evidence for the annotation of this gene as a Ni-CODH is provided in its structural alignment with known Ni-CODH proteins (Additional file 18 ), and by the annotation of a neighbor gene as a Ni-CODH maturation factor (Additional file 12 ). As a whole, the genomic evidence suggests CO oxidation capacity among Fer1, Fer2, and Iplasma and a potential for CO reduction in Fer2. Energy metabolism (c) aerobic respiration Fer1 and T. acidophilum are known to be facultative anaerobes [ 11 , 64 - 66 ], whereas T. volcanium and P. torridus are aerobes. Therefore, it is not surprising that all of the Richmond Mine AMD plasmas have the capacity for aerobic respiration and catabolism of organic compounds via two glucose catabolism pathways, pyruvate dehydrogenase, the TCA cycle and an aerobic electron transport chain (Additional file 12 ). Some AMD plasma genes in the aerobic electron transport chain have been observed in proteomic analyses as previously reported by Justice et al. , 2012 [ 20 ]. The AMD plasmas’ electron transport chains are similar to that of other archaea in that they do not contain all of the subunits of the NADH ubiquinone-oxidoreductase complex [ 67 ]. All of the AMD plasmas except Aplasma are missing the NuoEFG subunits found in the bacterial type complex I and instead have the subunits found in the archaeal-type complex I, NuoABCDHIJKLMN. Fer2 is missing NuoIJKLM most likely because the genes for this complex are found at the end of an incomplete contig. Eplasma, Gplasma and Fer1 maintain the Nuo gene order found in a number of other archaea including, Halobacterium sp. , Sulfolobus solfataricus , and T. acidophilum [ 68 ]. All contain succinate dehydrogenase complex genes (Additional file 12 ). In the case of A-, E-, and Gplasma, the complex is missing SdhD, and many of the SdhC genes have annotations with low confidence. This finding is congruent with previous research that shows that the genes for the membrane anchor subunits of the complex are poorly conserved in both bacteria and archaea, possibly due to low selective pressure [ 69 ]. As mentioned previously in section (v)(a), the AMD plasmas have genes homologous to several predicted archaeal complex III/cytochrome bc complex genes (Additional file 12 ). Archaeal-type aerobic terminal oxidases include cytochrome c oxidases (CCOs) and cytochrome bd oxidases. Genes for the cytochrome bd complex are found in P. torridus , T. acidophilum and T. volcanium [ 70 ]. All of the AMD plasma genomes contain the two genes for this complex. They also all contain the two essential genes for the archaeal heme-copper oxidase/CCO complex (subunit I and II) [ 70 ], and we confirm that subunit II contains the Cu-binding motif generally found in CCOs [ 71 ] (Additional file 19 ). Like the other CCO genes in B. subtilis and E. coli, the two cytochrome c genes in the AMD plasmas occur in a gene cluster with a protoheme IX farnesyltransferase, required for synthesis of the heme type used in aa(3) type CCOs [ 72 ]. The subunit II gene shares a high amino acid identity with several oxidases of this type, further indicating an aa(3) type CCO (Additional file 20 ). Archaea use A-type ATP synthases to generate ATP from an electrochemical gradient. All of the AMD archaeal genomes contain the AhaABCDEFIK genes that comprise this complex in Methanosarcina mazei , although they are missing an ortholog to AhaG. All but Eplasma and Iplasma contain a putative AhaH gene. AhaG is also absent in T. acidophilum , indicating that it may not be necessary for ATP synthesis in these organisms. Energy metabolism (d) alternative electron acceptors In addition to aerobic respiratory capabilities, some Thermoplasmatales organisms are able to respire anaerobically [ 66 ]. Anaerobic reduction of S 0 or sulfur ions could allow archaea in AMD systems to survive under anoxic conditions deep inside floating biofilms or in sunken biofilms and sediment, where many sulfur compounds are present [ 73 ]. The Iplasma genome contains several genes that are homologous to asrA and asrB , known sulfite reduction protein genes (13606_0515 and 13606_0514). These proteins comprise two of the three subunits of the AsrABC dissimilatory sulfite reductase complex found in Salmonella typhimurium [ 74 ]. However, the Iplasma genome does not contain the AsrC subunit, which contains the siroheme-binding motif and thus is thought to contain the active site for sulfite reduction. As the Asr proteins are not well characterized in many organisms, it is possible that these genes are misannotated. Synteny-based annotation ties these two genes to an adjacent FdhF formate dehydrogenase alpha subunit gene, indicating a possible involvement of these genes in formate dehydrogenase activity. In fact, one of these genes is structurally related to the HycB hydrogenase 3 Fe-S protein formate dehydrogenase subunit based on CBLAST against the NCBI protein structure database. Additional protein modeling suggests that one of the proteins in Iplasma could be a subunit of the formate dehydrogenase complex (Yelton, Zemla, and Thelen; unpublished observation). Thus, we suggest that these two proteins are functionally related to formate dehydrogenase in Iplasma. Interestingly, the Iplasma genome contains homologs to all of the genes overexpressed under anaerobic conditions for T. volcanium as well as all of the genes overexpressed or over-transcribed under anaerobic conditions for T. acidophilum (except for their predicted sulfur respiration gene Ta1129) in two previous studies [ 75 , 76 ] (Additional file 21 ). The other AMD archaea also share most, but not all, of these genes. Although there is no direct genomic evidence for anaerobic respiration, novel anaerobic respiratory pathways are possible. In fact, there is evidence that Fer1 can grow via anaerobic Fe(III) reduction [ 64 ], and enrichment cultures of Fer1 and Aplasma reduce iron [ 20 ]. Energy metabolism (e) heterotrophy Chemolithoautotrophy is a common lifestyle in AMD communities (e.g., of Leptospirillum spp.) [ 77 ]. However, the Thermoplasmatales archaea are mostly heterotrophs (only F. acidiphilum has been shown to have any autotrophic capability [ 10 ]). The AMD plasma genomes encode genes for a wide variety of heterotrophic metabolisms, both aerobic and anaerobic. The AMD plasmas have the genes necessary for energy generation via catabolism of organic compounds, including fatty acids, sugars, starch, and glycogen, but not refractory organic matter such as cellulose (Additional file 12 ). All of the AMD plasmas have genes for sugar and polysaccharide catabolism, including glucoamylase genes required to break down starch and alpha-amylase genes for glycogen catabolism into glucose and dextrin. They have the conventional Embden-Meyerhoff (EM) glycolytic pathway (Additional file 12 ). Moreover, they also have the genes for the non-phosphorylative Entner-Doudoroff (NPED) pathway for glucose degradation also found in a number of (hyper)thermophilic archaea, including T. acidophilum , P. torridus , S. solfataricus , Sulfolobus acidocaldarius , Sulfolobus tokodai and Thermoproteus tenax [ 78 - 81 ]. The AMD plasma genomes contain homologs to all of the genes in this pathway, including a homolog to the proven P. torridus KDG aldolase [ 82 ]. Thus, the AMD plasmas are similar to their Thermoplasmatales relatives, all of which have genes homologous to those of both the EM and NPED pathways. Previously published proteomic data indicates that all of the AMD plasma organisms express some of the genes in these two pathways [ 20 ]. Another potential carbon source for the AMD plasmas is lipids from lysed cells. All of the AMD plasma genomes contain a full set of homologs to the genes for the aerobic fatty acid oxidation pathway from E. coli (Additional file 12 ). Because many of the proteins in this pathway are acyl-CoA dehydrogenases, which are known to have undergone frequent gene duplication and horizontal transfer events [ 83 ], it is difficult to discern which role each gene plays in fatty acid degradation. However the number of β-oxidation-related annotations suggests that the AMD plasmas are capable of fatty acid breakdown, and many of the proteins from this pathway have been identified by proteomics [ 20 ]. Interestingly, the AMD plasmas have the genetic capacity to catabolize one-carbon compounds such as methanol. All except for Gplasma have several genes for subunits of a formate dehydrogenase. These genes were previously discussed by Yelton et al. [ 16 ], and a number are found in gene clusters with biosynthesis genes for their specific molybdopterin cofactor. We find that a formate hydrogen lyase complex gene cluster is evident in the Fer1 genome, as previously noted by Cárdenas et al. [ 63 ], but we also find a cluster of orthologous genes in Eplasma and Gplasma. It is possible that Fer1 is capable of the chimeric pathway of carbon fixation involving the formate hydrogen lyase described by Cárdenas et al. [ 84 ] (See section (vi) for further discussion of the putative group 4 hydrogenase hycE gene in this cluster). Eplasma also has the genes necessary for this pathway, but all of the other AMD plasma genomes are missing either the formate hydrogen lyase genes or the formate dehydrogenase subunit genes. Thus, we surmise that the AMD plasma formate dehydrogenases are primarily involved in an oxidative pathway for methanol methylotrophy (i.e., methanol degradation to formaldehyde, formaldehyde to formate, and formate oxidation to CO 2 ). The AMD plasmas have homologs to all of the enzymes in this pathway, including the enzyme used by all thermotolerant methanol-oxidizing bacteria, a NAD-linked methanol dehydrogenase [ 85 ] (Additional file 12 ). Among the AMD plasmas, only Iplasma appears to have the genes necessary for the ribulose monophosphate cycle, which is commonly used for carbon assimilation from formaldehyde [ 85 ]. None of the genomes contain the genes necessary for the other known formaldehyde assimilation pathway, the serine cycle. As Fer1 has been shown to produce methanethiol during cysteine degradation [ 86 ], any methanol in the AMD biofilm may be a product of methanethiol catabolism. Energy metabolism (f) fermentation and the use of fermentation products AMD archaea are typically more abundant in thick, mature AMD biofilms [ 87 ] where they may encounter anoxic microenvironments [ 73 ]. Thus, we looked for potential fermentation genes in their genomes. They all have the genes for fermentation of pyruvate to acetate found in Pyrococcus furiosus and a number of other anaerobic fermentative and aerobic archaea [ 88 - 91 ] (Additional file 12 ). This pathway is unique in that it converts acetyl-CoA to acetate in only one step, with an ADP-forming acetyl-CoA synthetase. It is the only phosphorylating step of pyruvate fermentation via the NPED pathway. Previously this enzyme had been detected in hyperthermophilic and mesophilic archaea as well as some eukaryotes [ 91 ]. In anaerobic archaea this enzyme is involved in fermentation, whereas in aerobic archaea it makes acetate that is then catabolized via aerobic respiration [ 92 ]. The AMD plasmas have the genes necessary for fermentation to acetate under anaerobic conditions and for acetate respiration under aerobic conditions via an acetate-CoA ligase or the reversal of the direction of the acetate-CoA synthetase. Putative hydrogenase 4 genes Several AMD plasma genomes contain a number of genes that group with the putative group 4 hydrogenases according to phylogenetic analysis (Additional file 22 ). A group 4 hydrogenase complex and formate dehydrogenase comprise the formate hydrogen lyase that catalyzes non-syntrophic growth on formate and production of H 2 in hyperthermophilic archaea ( Thermococcus onnurineus ) [ 93 , 94 ]. The putative group 4 hydrogenases, though closely related to the group 4 hydrogenases, lack the two conserved hydrogen and Ni-binding motifs that are thought to be necessary for H 2 formation [ 94 , 95 ], possibly indicating some other function. Toxic metal resistance The Richmond Mine solutions contain extremely high (mM) concentrations of arsenic, cadmium, copper, and zinc [ 96 ]. Genomic evidence indicates that the AMD plasmas utilize multiple strategies to protect themselves from these elements, such as oxidation/reduction to less toxic forms and efflux (Additional file 12 ) [ 8 , 97 ]. All of the AMD plasmas have at least two genes from the arsenic resistance ( arsRABC ) operon. Only Gplasma has all of the genes in the operon, but Fer1 has previously been shown to have resistance to both arsenate and arsenite, despite lacking the arsenate reductase [ 97 ]. All of the AMD plasmas except for Fer2 have two of the genes in the mercury resistance operon ( merTPCAD ), merA and merP (mercuric reductase and the mercuric ion-binding protein, respectively). All of the genomes also contain some putative copper resistance genes in the copABCD operon or the copYBZ loci, identified previously in Fer1 [ 98 ]. Specifically they all have homologs to copB . This gene has been shown to be involved in copper sequestration as a copper resistance strategy in Pseudomonas syringae [ 99 ]. The heavy metal transporter genes found in the AMD plasma genomes group into two different clades in a phylogenetic tree of metal resistance P-type ATPases. All of the genomes except for that of Iplasma contain two types of metal resistance transporters according to this phylogenetic analysis, a Cu/Ag transporter related to copA or copBZ and a Zn/Cd transporter related to cadA . Biosynthesis Because the AMD plasmas live in dense biofilms, they could potentially benefit from biomolecules (cofactors, amino acids, etc.) provided by other organisms .We previously demonstrated a lack of genes for de novo cobalamin biosynthesis in A-, E-, G-, and Iplasma [ 16 ]. Here we examined the AMD plasma genomes for other biosynthetic pathways. Biosynthesis (a) glyoxylate shunt Only Eplasma has the genes for the glyoxylate shunt, a pathway closely related to the TCA cycle that allows the use of organic compounds that are degraded to acetyl-CoA (i.e. fatty acids) for biosynthesis (Additional file 12 ). One of the proteins encoded in this pathway, the malate synthase, has been detected in proteomic analyses [ 20 ]. Biosynthesis (b) amino acid synthesis The Thermoplasmatales archaea exhibit differential abilities to synthesize amino acids, suggesting that some of them rely more heavily on organic compound uptake than others. The genomes of E-, G- and Iplasma do not contain most of the histidine synthesis pathway genes. Eplasma and Iplasma also lack many of the genes necessary for the valine and (iso)leucine synthesis pathway (Additional file 12 ). They are also among the subset of organisms that do not make their own cobalamin [ 16 ]. This group of organisms may rely on amino acid and cobalamin scavenging to avoid the energetic costs of de novo synthesis. Biosynthesis (c) trehalose biosynthesis Compatible solutes allow organisms to maintain osmotic balance under high salt conditions or to protect against heat shock and cold shock [ 100 ]. A number of archaea make organic solutes for this purpose. T. acidophilum and a number of Sulfolobales archaea have been shown to produce trehalose as a compatible solute. In these organisms it has also been suggested that it is used to thermostabilize macromolecules and as a carbon storage molecule [ 100 ]. All of the AMD plasmas except for Iplasma have the genes necessary for trehalose biosynthesis from maltose (Additional file 12 ). The monophyletic group of A-, E-, and Gplasma also has the genetic potential for trehalose synthesis from glycogen. Motility Motility can provide a competitive advantage for archaea in aquatic environments by allowing them to colonize new sites and move across environmental gradients. To determine potential for motility, we looked for flagellar, chemotaxis and pili genes in the AMD plasma genomes. Both the A- and Gplasma genomes contain the full flagella flaBCDEFGHIJ operon found in Methanococcus voltae [ 101 - 103 ] and Halobacterium salinarum [ 104 ] (Additional file 12 ). Thus, these organisms are predicted to be motile, yet they lack identifiable chemotaxis genes. No flagellar genes are found in the other AMD plasma genomes, suggesting differences in motility. We used cryo-EM to confirm the existence of flagella on cells inferred to be archaea based on the presence of a single cell membrane (Figure 4 ). We found flagella-like structures with diameters of about 10–14 nm, similar in width to the flagella of T. volcanium [ 105 ]. The structures are also thicker than the pili observed in similar AMD plasmas or in bacteria [ 106 ]. A high-electron density area can be seen inside the cytoplasm immediately adjacent to the flagella that may be part of the associated protein motor complex. Figure 4 Cryo-electron microscopy of AMD plasma cells. Panel A and panel B show evidence of flagella on two different cells collected from the Richmond Mine AMD. Arrows point to flagella. The box surrounds a potential motor protein complex. In addition to flagellar assembly genes, a number of the AMD plasma genomes contain genes for Type II secretion or Type IV pili that are used in twitching motility or possibly conjugation or attachment to the biofilm or other surfaces. All of the genomes except for Fer1 and Fer2 contain some of these genes, and in Eplasma, Gplasma, and Iplasma they are in a cluster with conserved gene order among the AMD plasmas (Additional file 23 ). Cryo-EM confirms the existence of pili, and shows attachment of the pili from the original cell to other cells (Figure 5 , Additional file 24 ). Figure 5 Cryo-electron microscopy of AMD plasma cells with putative pili. Panel A and panel B show evidence of pili on two different cells collected from the Richmond Mine AMD. Arrows point to pili. Vesicle-like structures are delineated by a single membrane layer around an ovoid shape in each cell’s cytoplasm. Vesicle-like cavities Cryo-EM imaging demonstrates that a number of the AMD plasma cells harbor low electron-density inclusions within what appears to be a lipid membrane (Figure 5 ). These are similar in appearance to the gas vesicles that some extreme halophiles use for buoyancy [ 107 ], although those vesicles are enclosed in a proteinaceous membrane. We did not find genomic evidence of gas vesicle formation in the AMD plasmas by performing BLASTP searches of their genomes against the gas vesicle protein (gvp) genes of Haloarchaea [ 108 ]. Novel vesicle formation genes are expected and we speculate that these are liquid vesicles because their apparent lipid membrane would be gas-permeable."
} | 9,894 |
34716322 | PMC8556258 | pmc | 3,105 | {
"abstract": "Biological degradation of Polyethylene terephthalate (PET) plastic and assimilation of the corresponding monomers ethylene glycol and terephthalate (TPA) into central metabolism offers an attractive route for bio-based molecular recycling and bioremediation applications. A key step is the cellular uptake of the non-permeable TPA into bacterial cells which has been shown to be dependent upon the presence of the key tphC gene. However, little is known from a biochemical and structural perspective about the encoded solute binding protein, TphC. Here, we report the biochemical and structural characterisation of TphC in both open and TPA-bound closed conformations. This analysis demonstrates the narrow ligand specificity of TphC towards aromatic para-substituted dicarboxylates, such as TPA and closely related analogues. Further phylogenetic and genomic context analysis of the tph genes reveals homologous operons as a genetic resource for future biotechnological and metabolic engineering efforts towards circular plastic bio-economy solutions.",
"introduction": "Introduction The global appetite for plastic products has transitioned our planet into an era of the “Plastic Age” 1 . Polyethylene terephthalate (PET) plastic is the most commonly used plastic in the packaging of beverages, food and pharmaceuticals. Since its first synthesis back in 1941, PET has gradually emerged as the world’s favorite food-safe plastic due to its robustness, chemical inertness and durability. Although regarded as non-toxic and 100% recyclable, single-use convenience-sized PET bottles have made PET plastic the third most collected debris in beach clean-ups in more than 100 countries 2 and is overwhelmingly omnipresent in the terrestrial ecosystem 3 , 4 . The post-consumer recyclability of plastics is still questionable owing to a number of factors 5 , 6 that have turned PET from a miraculous material into the scourge of the land and sea. For instance, the PET-recycling rate was estimated to be only ~30% in 2015 in the US, and in Europe 25% of post-consumer plastic waste still went into landfill in 2018 (ref. 7 ). This evidently ubiquitous plastic footprint, however, has not impacted upon the demand and production given the essentiality of plastics in our daily lives. The global PET market in 2017 was valued at ~USD 24 billion and is expected to hit USD 39 billion by 2027 (ref. 8 ). In 2016, around 485 billion PET bottles were manufactured, and around 583.3 billion are forecast to be produced in 2021 (ref. 9 ). The global demand for PET in 2030 is forecast to amount to 42 metric tons 10 . Both mechanical and chemical PET-recycling methods are available; however, widespread use is limited 11 . Indeed, some concerns remain over the product quality and environment impact of the mechanical and chemical PET recycling, respectively 6 . Microbial and enzyme-based plastic waste biodegradation and recycling offer promising alternative strategies due to the use of benign conditions and potential as a cost-effective environment-friendly approach 12 – 16 . Therefore, there is great interest in finding better strategies for PET bioconversion and recycling through engineering robust enzymes and microbial strains for its degradation, uptake and assimilation. Terephthalic acid (TPA) and ethylene glycol (EG), which together form a polymer chain, are the basic building blocks of PET and can be released by enzymatic hydrolysis via the action of different types of bacterial and fungal origin hydrolases, such as esterases, lipases, cutinases and carboxylesterases 17 – 24 . A bacterial strain Ideonella sakaiensis was discovered that secreted two enzymes PETase and MHETase which enable the microbe to grow on low crystalline PET film as its major carbon source under optimised non-native lab conditions 25 . PET is initially hydrolysed to monohydroxyethyl terephthalate (MHET) by PETase which is subsequently hydrolysed into TPA and EG by MHETase. Following their discovery, these two enzymes have been extensively studied biochemically and structurally, and further subjected to directed evolution to enhance their catalytic activities and substrate specificities 26 – 32 . The constituent monomers, EG and TPA, can then be taken up and degraded by microorganisms competent to utilise these compounds for their metabolism. For instance, Pseudomonas putida is capable of directly funnelling EG to the Krebs cycle via isocitrate 33 . Similarly, TPA can be converted to protocatechuic acid (PCA) via an initial dioxygenolytic step in which the aromatic ring is cleaved before entering the central metabolism 34 , 35 . TPA is converted to PCA via a pathway encoded by the tph operon (Fig. 1A ), these genes have been characterised in the β-proteobacteria Comamonas testosteroni YZW-D 36 , Comamonas sp. strain E6 (refs. 37 , 38 ) and in the actinomycete Rhodococcus sp. strain DK17 (refs. 39 ). Fig. 1 Terephthalate cellular uptake and assimilation operons. A Schematic representation of tph and tpi operons in the chromosome of Comamonas sp. strain E6. The catabolic genes of the tph operon, encoding a three-component TPA 1,2-dioxygenase (TPADO), are represented in gold ( tphA2 ), orange ( tphA3 ) and pink ( tphA 1). The tph operon regulator ( tphR ), a gene encoding a diol dehydrogenase ( tphB ) and a gene encoding a periplasmic solute-binding protein ( tphC ), are represented in green, teal and mauve, respectively. The transport genes ( tpiBA ) in tpi operon, encoding a set of transmembrane transport proteins, are shown in peach and light blue, respectively. B Schematic of TPA transport and catabolism. The tphR encoded activator (TphR) responds to the presence of inducer TPA and leads to the expression of a set of capture, transport and catabolic proteins to metabolise TPA in a successive binding, transport and catabolic steps: TphC in the periplasm first binds to TPA and relays it to a pair of transmembrane proteins, TpiB and TpiA, which in turn transport it to the cytoplasm, where it is converted by a three-component TPADO to 1,6-dihydroxycyclohexa-2,4-diene-dicarboxylate (DCD). The DCD is acted upon by TphB (1,2-dihydroxy-3,5-cyclohexadiene-1,4-dicarboxylate dehydrogenase) and converted to protocatechuate (PCA), which is then funnelled into the central metabolic pathways. To date, unlike the enzymes involved in the degradation of PET and assimilation of the breakdown products, the cellular uptake of these monomers, EG and TPA, has received limited attention. Adaptive laboratory evolution was used to engineer Pseudomonas putida KT2440 to enhance EG cellular uptake and metabolism 40 , 41 , and heterologous expression of the tph pathway has been reported in a number of different hosts 13 , 37 , 42 – 44 . Cellular uptake of TPA into Comamonas sp. strain E6 has been shown to be dependent upon the presence of the tphC gene and its product TphC 37 , 45 , which is predicted to be a solute-binding protein (SBP) belonging to the tripartite tricarboxylate transporters (TTT) class of transporters 46 . The initial ligand recognition in a TTT system is performed by the periplasmic SBP (Fig. 1B ). TTT-SBPs have also been identified in uptake mechanisms for other biotechnologically important ligands, such as C 6 dicarboxylic acids 47 , C 4 dicarboxylic acids 48 , sulfolactate 49 and the synthetic precursors for polythioesters 50 . Apart from Bug27 (ref. 51 ), the Bordetella pertussis SBP for nicotinic acid and related compounds, TTT-SBPs have been shown to bind exclusively to dicarboxylic acids. This prokaryotic secondary solute transporter family is scarcely characterised, the ligand specificity of only a few TTT-SBP systems is known and consequently the SBP–ligand interactions are poorly understood. So far, the structure of only six TTT-SBPs have been determined, two from Rhodopseudomonas palustris 47 , 48 , three from Bordetella pertussis 51 – 53 and one from Polaromonas sp. These protein structures show a common “Venus flytrap” fold comprising of two globular domains separated by a cleft that folds around the ligand. Despite cellular uptake of TPA being a key step, the confirmation of tphC- dependent uptake of TPA at the genetic-level 45 , and the potential for TphC to be used in engineered strains for the cellular uptake of TPA and bioconversion of plastic waste 14 , there have been no reports to date on the biochemical or structural characterisation of TphC. Due to the relatively recent xenobiotic introduction of PET and TPA into the environment, we were inspired to explore whether TPA is indeed the cognate ligand for TphC, or whether other closely related chemicals naturally found in the environment are also recognised by TphC. Here, we employed differential scanning fluorescence (DSF) assay, mutational analysis, isothermal titration calorimetry (ITC) and X-ray crystallography to biochemically and structurally characterise TphC from Comamonas sp. strain E6. Further phylogenetic and taxonomic analysis was used to reveal homologous operons to explore the diversity and origin of these xenobiotic catabolism genes and to provide a genetic resource for future biotechnological and metabolic engineering efforts towards circular plastic bio-economy solutions.",
"discussion": "Discussion In this study, we characterised the TphC SBP that is a key component in the cellular uptake of TPA, the breakdown product of PET plastic 45 . TphC belongs to the TTT family in Commamonas sp. strain E6 and through biochemical and structural analysis, the ligand-binding properties and 3D structure were determined in both open and ligand-bound closed forms. TTT-dependent SBPs, such as TphC belong to the Cluster E-II according to the classification of Scheepers et al. 57 . As with the tripartite ATP-independent periplasmic (TRAP) class of SBP-dependent transporters, they are symporter proteins driven by an electrochemical ion-gradient, rather than ATP as per the SBP-dependent class of ABC transporters 46 . Screening with DSF showed TphC binds to para-substituted aromatic dicarboxylates. Substitution of the aromatic ring with hydroxyl and amino groups, and the presence of hetero-atoms within the ring, is tolerated, but with a significantly lowered ligand-induced stabilisation. This seems to indicate that the binding pocket of TphC is structurally quite constrained. Furthermore, the efficient binding of the terephthalate 1 ligand but not the C 6 aliphatic or unsaturated aliphatic ligands, adipate 59 and trans,trans ‐muconate 57 , revealed the need for an aromatic structure for the binding ligand. The TTT-SBPs characterised so far are specific for aliphatic ligands 47 , 49 , 50 with the sole exception of the B. pertussis Bug27 protein which is reported to bind an aromatic mono-carboxylated nicotinate 51 . Our model proposes that TphC has a narrower more selective binding site, whereas AdpC is more relaxed, which is consistent with biochemical data in the literature that shows that AdpC binds to C 6 –C 8 aliphatic dicarboxylates plus trans, trans muconate 47 . The ITC determined TphC affinities for the ligand-hits were in µM range with terephthalate 1 and its derivatives: 2-hydroxyterephthalate 4 and 2,5-dihidroxyterephthalate 10 showing the greatest affinities (0.36−1.9 µM). The sub-micromolar TphC affinity observed for 1 (0.36 µM) is comparable to other high-affinity SBPs reported for Bug27-Nicotinate/Nicotinamide (0.36 µM) 51 , AdpC-Adipate (0.55 µM) 47 and MatC-Malate (~0.02 µM) 48 . In comparison with other open/apo structures, even though TphC has low similarity and identity to other apo SBP structures TctC (26%) and Bug27 (29%), the two domains of TphC have RMSD of 0.837 and 0.446 for the corresponding domains within TctC (PDB 4X9T), and 0.47 and 0.891 within the Bug27 (PDB 2QPQ) domains (Supplementary Table 5 ). All three SBPs have the same architecture; however, there is significant differences between the orientation of domains between TphC and TctC, specifically in the upper domains around α5-6 and β5-8, and the ligand-binding loop between β6 and α5 (Supplementary Fig. 6 ). TphC shows a 36.3° closure angle, whereas previously resolved apo- and ligand-bound structures of Bug27 reported a closure angle of 24.7° 51 and other periplasmic binding proteins show closure angles ranging from 15° to 60° 58 . Similar to MatC and AdpC, the absence of positively charged residues (to counteract the negative charges of the ligand carboxylate groups) in the ligand-binding pocket of TphC is observed. The TphC–TPA ligand-binding site appears similar to the aliphatic-SBP complex (oxoadipate-AdpC), with comparable distances between the corresponding residues responsible for H-bonding with the dicarboxylate groups. Within SBPs that recognise the smaller aspartate and malate ligands (BugD and MatC), the C 4 ligands are positioned 90° rotated along the dicarboxylate axis relative to TPA (and the other C 6 ligands), with the carboxylate H-bonding to a neighbouring serine residue (S151). While this serine is conserved in TphC (S156), a bulky glutamine residue in TphC (Q150) occludes the alternative H-bonding site and thus provides the rationale for why the smaller dicarboxylate ligands are not recognised by TphC. The bulky residues P86 and Q150 present within TphC create a narrow pocket, 6.4Å across, which appears to exclude aliphatic C 6 ligands. Along with the majority of TTT-SBPs reported to date 46 , TphC and its homologues identified here are not located in the same operon as the TTT-dependent membrane transporter subunit genes ( tpiA and tpiB ), but are located within the tph operon along with the genes encoding transcriptional regulator (TphR) and the TPA dioxygenase subunits (TphA 1–3 B) (Fig. 7 ). Due to the genomic co-localisation of the tphC and the catabolic pathway for TPA ( tph ), we sought to use TphC as genomic fish-bait to locate other homlogous gene clusters of biotechnological interest. This approach has previously been employed to identify arylmalonate decarboxylase 59 . PET was first synthesised in the 1940s from TPA and EG, and TPA in turn is prepared by the chemical oxidation of p -xylene 60 . In addition, TPA is used in the chemical synthesis of small-molecule plasticiser additives 61 , which may be more accessible sources of TPA within the environment rather than from highly crystalline PET 62 , 63 . As far as we know, TPA is not found naturally in the environment, so the question exists as to from where did the TPA recognition potential originate. At the outset of this study we had expected to identify closely related chemical compounds of natural origin that bound to TphC. However, all TphC-binding ligands identified in our screen appear to be of xenobiotic origin—why binding to non-xenobiotic compounds was not observed is unclear. One possibility is that TphC evolved from an ancestral or pre-industrial SBP that displayed side-activity or promiscuity, and TphC has since lost affinity to its original ligand, as has been proposed for the evolution of enzymes 64 . Considering the evolutionary time span of ~80 years since the first production of TPA, and the low conservation observed between the SBP’s associated with the putative tph operons (Fig. 7 ), it would seem likely that TphC homologues might have evolved from a pool of multiple ancestral SBPs rather than from a common ancestor. This notion is also consistent with the low degree of sequence conservation and global distribution of xenobiotic degradation pathways, e.g., those involved in plastic 21 , 65 and organohalide 66 degradation. In this study, we provide evidence for the structural basis of TPA recognition by TphC through DSF, ITC and X-ray crystallography. Together with TPA, we report the binding potential of TphC towards some other TPA derivatives and analogues which have varied applications. For instance, 2,5-dihydroxyterephthalic acid is a useful monomer for the synthesis of high strength fibres 67 , 2-aminoterephthalic acid and 2,5-pyridinedicarboxylic acid have application in the synthesis of lanthanide coordination polymers 68 , 69 and 2,6 naphthalene dicarboxylic acid is used as a monomer for the production of polyethylene naphthalate (PEN) esters which are considered superior to PET for certain applications 70 . In summary this biochemical, structural and phylogenetic analysis provides useful insights into the ligand-recognition potential of TphC and opens up a new array of opportunities to engineer heterologous hosts for the uptake and assimilation of the breakdown products from PET and other polymers."
} | 4,162 |
27668126 | null | s2 | 3,106 | {
"abstract": "Mechanical concepts and designs in inorganic circuits for different levels of stretchability are reviewed in this paper, through discussions of the underlying mechanics and material theories, fabrication procedures for the constituent microscale/nanoscale devices, and experimental characterization. All of the designs reported here adopt heterogeneous structures of "
} | 91 |
27183459 | null | s2 | 3,107 | {
"abstract": "Standard practice in reclamation of mine tailings is the emplacement of a 15 to 90cm soil/gravel/rock cap which is then hydro-seeded. In this study we investigate compost-assisted direct planting phytostabilization technology as an alternative to standard cap and plant practices. In phytostabilization the goal is to establish a vegetative cap using native plants that stabilize metals in the root zone with little to no shoot accumulation. The study site is a barren 62-hectare tailings pile characterized by extremely acidic pH as well as lead, arsenic, and zinc each exceeding 2000mgkg(-1). The study objective is to evaluate whether successful greenhouse phytostabilization results are scalable to the field. In May 2010, a 0.27ha study area was established on the Iron King Mine and Humboldt Smelter Superfund (IKMHSS) site with six irrigated treatments; tailings amended with 10, 15, or 20% (w/w) compost seeded with a mix of native plants (buffalo grass, arizona fescue, quailbush, mountain mahogany, mesquite, and catclaw acacia) and controls including composted (15 and 20%) unseeded treatments and an uncomposted unseeded treatment. Canopy cover ranging from 21 to 61% developed after 41 months in the compost-amended planted treatments, a canopy cover similar to that found in the surrounding region. No plants grew on unamended tailings. Neutrophilic heterotrophic bacterial counts were 1.5 to 4 orders of magnitude higher after 41months in planted versus unamended control plots. Shoot tissue accumulation of various metal(loids) was at or below Domestic Animal Toxicity Limits, with some plant specific exceptions in treatments receiving less compost. Parameters including % canopy cover, neutrophilic heterotrophic bacteria counts, and shoot uptake of metal(loids) are promising criteria to use in evaluating reclamation success. In summary, compost amendment and seeding, guided by preliminary greenhouse studies, allowed plant establishment and sustained growth over 4years demonstrating feasibility for this phytostabilization technology."
} | 514 |
27183459 | null | s2 | 3,108 | {
"abstract": "Standard practice in reclamation of mine tailings is the emplacement of a 15 to 90cm soil/gravel/rock cap which is then hydro-seeded. In this study we investigate compost-assisted direct planting phytostabilization technology as an alternative to standard cap and plant practices. In phytostabilization the goal is to establish a vegetative cap using native plants that stabilize metals in the root zone with little to no shoot accumulation. The study site is a barren 62-hectare tailings pile characterized by extremely acidic pH as well as lead, arsenic, and zinc each exceeding 2000mgkg(-1). The study objective is to evaluate whether successful greenhouse phytostabilization results are scalable to the field. In May 2010, a 0.27ha study area was established on the Iron King Mine and Humboldt Smelter Superfund (IKMHSS) site with six irrigated treatments; tailings amended with 10, 15, or 20% (w/w) compost seeded with a mix of native plants (buffalo grass, arizona fescue, quailbush, mountain mahogany, mesquite, and catclaw acacia) and controls including composted (15 and 20%) unseeded treatments and an uncomposted unseeded treatment. Canopy cover ranging from 21 to 61% developed after 41 months in the compost-amended planted treatments, a canopy cover similar to that found in the surrounding region. No plants grew on unamended tailings. Neutrophilic heterotrophic bacterial counts were 1.5 to 4 orders of magnitude higher after 41months in planted versus unamended control plots. Shoot tissue accumulation of various metal(loids) was at or below Domestic Animal Toxicity Limits, with some plant specific exceptions in treatments receiving less compost. Parameters including % canopy cover, neutrophilic heterotrophic bacteria counts, and shoot uptake of metal(loids) are promising criteria to use in evaluating reclamation success. In summary, compost amendment and seeding, guided by preliminary greenhouse studies, allowed plant establishment and sustained growth over 4years demonstrating feasibility for this phytostabilization technology."
} | 514 |
28094795 | PMC5363838 | pmc | 3,111 | {
"abstract": "Succession of redox processes is sometimes assumed to define a basic microbial community structure for ecosystems with oxygen gradients. In this paradigm, aerobic respiration, denitrification, fermentation and sulfate reduction proceed in a thermodynamically determined order, known as the ‘redox tower'. Here, we investigated whether redox sorting of microbial processes explains microbial community structure at low-oxygen concentrations. We subjected a diverse microbial community sampled from a coastal marine sediment to 100 days of tidal cycling in a laboratory chemostat. Oxygen gradients (both in space and time) led to the assembly of a microbial community dominated by populations that each performed aerobic and anaerobic metabolism in parallel. This was shown by metagenomics, transcriptomics, proteomics and stable isotope incubations. Effective oxygen consumption combined with the formation of microaggregates sustained the activity of oxygen-sensitive anaerobic enzymes, leading to braiding of unsorted redox processes, within and between populations. Analyses of available metagenomic data sets indicated that the same ecological strategies might also be successful in some natural ecosystems.",
"introduction": "Introduction In biogeochemistry, observation of chemical gradients in poorly mixed environments led to the development of a theorem known as the microbial redox ‘tower', ‘ladder' or ‘cascade'. This theorem holds that a succession (in space or time) of ecological guilds of prokaryotes consumes electron acceptors in a thermodynamically determined order (‘thermodynamic sorting' Richards, 1965 ; Orcutt et al. , 2011 ). Aerobic bacteria (E 0 ′+0.82 V) first consume oxygen until it is depleted. Subsequently, denitrifying bacteria convert nitrate to nitrogen gas (average E 0 ′+0.75 V). Reduction of manganese and iron oxides is next in line, followed by sulfate reduction (E 0 ′−0.22 V) and finally respiration of carbon dioxide to methane (E 0 ′−0.24 V). Fermentation is usually placed between denitrification and sulfate reduction ( Fenchel and Jørgensen, 1977 ). In theory, the redox tower is also an attractive model to explain community structure in microbial ecology. Natural microbial communities are complex and their study is challenging, even with modern metagenomics approaches ( Newman and Banfield, 2002 ; Oremland et al. , 2005 ; Woodcock et al. , 2007 ; Little et al. , 2008 ). We are in need of organizing principles explaining microbial community structure and the redox tower might constitute such a principle. If nature would select for microbial communities that convert the available resources with the production of the highest possible amount of biomass, redox tower behavior would be the outcome ( Rodriguez et al. , 2008 ; Temudo et al. , 2008 ). If nature would select for microbial communities that convert the available resources as quickly as possible, loss of thermodynamic sorting may result. From a thermodynamic perspective, the first scenario is consistent with Prigogine's theorem of the non-equilibrium steady state and the second is consistent with Ziegler's principle ( Bordel, 2010 ). Because metabolism is by definition outside thermodynamic equilibrium, thermodynamic sorting of redox processes cannot be deduced from first principles and it does not need to be true in general. Thus, thermodynamic sorting may be a possible outcome of community assembly that applies when certain conditions are met. In microbiology, it has long been known that at least microbial strains isolated in pure culture commonly abide to the redox tower, which is easily explained by inhibition of low redox potential processes by high potential electron acceptors. However, non-redox tower behavior has also been observed. For example, denitrification was observed in the presence of oxygen ( Takaya et al. , 2003 ; Jensen et al. , 2009 ; Gao et al. , 2010 ), sulfate reduction in the presence of nitrate ( Dalsgaard and Bak, 1994 ; Canfield et al. , 2010 ), methanogenesis in the presence of sulfate ( Kuivila et al. , 1990 ) and fermentation in the presence of oxygen ( Thomson et al. , 2005 ). The latter observation is known as the ‘Crabtree effect' in industrial yeast production and the ‘Warburg effect' in cancer biology ( Crabtree 1928 ; Warburg 1956 ; Diaz-Ruiz et al. , 2011 ). Unfortunately, many studies do not report the degree of aggregation of cells, for example, while reporting so-called ‘aerobic denitrification' ( Robertson et al. , 1989 ; Chen et al. , 2003 ; Takaya et al. , 2003 ; Khardenavis et al. , 2007 ; Su et al. , 2015 ). Diffusion of oxygen towards single bacterial cells is so effective that with the reported cellular respiration rates, a single aerobic cell can never deplete all the oxygen in its immediate surroundings, unless the bulk oxygen concentration is in the low nanomolar range ( Schulz and Jørgensen 2001 ; Stolper et al. , 2010 ). However, a microaggregate (diameter >5 μm) of tens to hundreds aerobic bacterial cells can effectively respire all oxygen in its immediate surroundings at bulk oxygen concentrations of ~20 μ m (~10% air saturation) and this could in theory explain apparently non-redox tower behavior. The present study addresses how spatio-temporal chemical gradients shape microbial community structure at low (<20 μ m ) oxygen and nitrate concentrations. If the redox tower would apply, aerobic and anaerobic processes would occur in separate (in space or time) microcompartments. If not, these processes would occur in parallel in the same compartment. The concept would also apply to gradients of nitrate, sulfate and so on. The research question was addressed experimentally by sampling a microbial community from a tidal flat sediment naturally exposed to oxygen gradients in space and time. The sampled community was incubated in a laboratory chemostat with well-defined spatio-temporal oxygen gradients. During 100 days, a simple, more or less stable microbial community had assembled from the much more complex source community. See also Yan et al. (2012) , describing a similar approach. A combination of independent methods showed that this simplified community did not abide to the microbial redox tower. Instead, the metabolism was ‘braided', with each population performing a combination of aerobic and anaerobic metabolism and exchange of partially converted substrates between populations. Future study will show to what extent this observation can be generalized (see for example, Hawley et al. , 2014 ). However, active transcription of key genes characteristic of the observed braided metabolism in two natural ecosystems with oxygen gradients, confirms ( Canfield et al. , 2010 ) and expands previous results. Our study indicated that microbial communities may convert available resources as quickly as possible, increasing resilience at the price of reduced productivity.",
"discussion": "Discussion The present study investigated how spatio-temporal chemical gradients shape microbial community structure at low (<20 μ m ) oxygen and nitrate concentrations. Two scenarios were considered. In the first scenario, the microbial redox tower was applied strictly. In the second scenario, all redox processes were allowed to proceed simultaneously. Direct evidence for the parallel occurrence of unsorted redox processes consisted of the turnover of formate, succinate and reduced sulfur compounds, and the occurrence of denitrification in the presence of oxygen. This evidence was supported by the transcription and expression of functional genes associated with each of these processes by specific populations and by the presence of one abundant respiring (aerobic/denitrification) population ( Arcobacter ) that was unambiguously dependent on fermentation products and sulfide. For each abundant population, its metabolism, inferred de novo from genomics data, was completely consistent with literature data and available whole-genome sequences of cultivated relatives. The observation that, in the absence of microaggregates, denitrification only occurred at high oxygen concentrations, was totally unexpected. The simultaneous transcription and expression of the cbb 3 terminal oxidase and the nitrate, nitrite, nitric oxide and nitrous oxide reductases indicated that all complexes might compete for electrons in a branched respiratory chain (see also discussion below). The cbb 3 terminal oxidase usually sustains microaerophilic metabolism ( Pitcher and Watmough, 2004 ). Indeed, we showed inhibition at high oxygen concentrations and this might explain why, at oxygen concentrations above 0.15 m m , the denitrification enzymes became the prevalent electron sink. Because nitrous oxide reductase is the only intrinsically oxygen-sensitive enzyme of the denitrification pathway ( Honisch and Zumft, 2003 ), nitrous oxide was the end product of denitrification at high oxygen concentration. The direct evidence was supported by a stoichiometric model of microbial metabolism consisting of 21 reactions inferred from the measured gene activities and common bioenergetic constraints. With this model, we showed that both the experimentally observed low overall biomass yield and the relative abundances of the five populations were consistent with the observed gene expression patterns and our current understanding of bioenergetics. Several factors contributed to the low growth yield. First, the best carbon substrates were used for fermentation, instead of being assimilated by respiring populations. This lowered biomass yields, because fermentative metabolism conserves relatively little energy and because the bioenergetically more efficient respiring populations now needed to perform more work during the assimilation of fermentation products, compared with what would have been required to assimilate the best substrates directly. Second, the abundant Vibrio population consumed part of the oxygen using a cytochrome bd terminal oxidase. This oxidase has a high affinity for oxygen (low micromolar range), accepts electrons from quinols (bypassing respiratory complex III) and does not translocate protons ( Jünemann, 1997 ). At a proton motive force of 180 mV, the bioenergetic efficiency of a respiratory chain terminated by a bd oxidase is only ~32%, compared to ~80% for a canonical respiratory chain with a complex III and terminated by a heme-copper-oxidase-based complex IV. Thus, use of cytochrome bd oxidases by Vibrio and Desulfovibrio populations compromised their biomass yield, and reduced the productivity of the microbial community as a whole. It is unknown whether the cytochrome bd terminal oxidase has a higher affinity for oxygen than the heme-copper cbb 3 type terminal oxidases ( Pitcher and Watmough, 2004 ) used by Rhodobacterales and Arcobacter. If this were the case, it would explain the accumulation of formate during the oxic part of the tidal cycle. At this point, one might argue that the observed aggregation of cells in the chemostat created a second spatial compartment and that the localization of denitrification (during oxic conditions), fermentation and sulfate reduction to these aggregates could rescue the redox tower scenario. All populations were represented both by suspended and aggregated cells, so if this would be the case, it would mean that each population consisted of a mixture of phenotypically differentiated cells (for example, Schreiber et al. , 2016 ), with suspended cells performing a different redox process than aggregated cells. For denitrification, this interpretation was falsified experimentally by showing that suspended cells were still capable of denitrification and that aerobic respiration was inhibited in the presence of nitrate. The latter observation was most parsimoniously explained by competition for electrons between the terminal oxidase and the denitrification enzymes (see also discussion above), which meant that these enzymes must have been present together in the same (suspended) cells. Furthermore, stoichiometric modeling of the thermodynamically sorted scenario (reactions a – c ) showed that this scenario would lead to a much higher biomass yield. A smaller portion of the carbon substrates would be respired and nitrite would never become a limiting substrate. Thus, the aggregates would be fully exposed to nitrite and the redox tower would predict that fermentation should not occur. The combined activity of multiple redox processes within the same cells provided synergistic fitness benefits. For example, Rhodobacterales, Vibrio and Arcobacter combined denitrification with aerobic respiration. These populations bypassed the need for the bioenergetically costly turnover of enzyme systems. They could swiftly respond to the temporal fluctuation of the oxygen concentration without synthesizing new proteins. Furthermore, their hybrid respiratory chains even optimally prepared them for higher oxygen concentrations. Vibrio and Arcobacter protected oxygen-sensitive molecular machinery (nitrous oxide reductase, pyruvate formate lyase) by active respiration of oxygen. And even though Vibrio 's respiratory chain had low bioenergetic efficiency, respiration was still a much more efficient sink for excess electrons than resorting to mixed acid fermentation. In oxygen-limited natural habitats, microbes experience continuous change and have three options: (i) differentiation of cells within each population (‘bet hedging', Schreiber et al. , 2016 ), (ii) continuously adapt by modulating gene expression via regulation or (iii) avoid regulation by stable expression of a set of genes that is adequate (but not optimal) for all conditions encountered. Here we mainly observed the latter ecological strategy. This increased resilience (more effective response to fluctuating conditions) at the expense of reduced productivity (biomass yield). The ecological success of fermentative populations, which outcompeted respiring populations for carbon substrates, showed that Zieglers principle better explained microbial community structure than Prigogine's theorem of the non-equilibrium steady state. Finally, our study provided strong evidence for the ecological importance of division of labor, both in carbon metabolism and in denitrification. Future study will show to what extent these conclusions can be generalized. The presence and activity of a number of key functional genes of ‘braided' metabolism in two oxygen-limited habitats confirms and expands previous work ( Canfield et al. , 2010 ; Ganesh et al. , 2015 ) and the model might thus at least be a useful template for the interpretation or experimental design of future studies of oxygen-limited natural ecosystems."
} | 3,688 |
29927925 | PMC6013025 | pmc | 3,113 | {
"abstract": "Polymicrobial interactions play an important role in shaping the outcome of antibiotic treatment, yet how multispecies communities respond to antibiotic assault is still little understood. Here we use an individual-based simulation model of microbial biofilms to investigate how competitive and mutualistic interactions between an antibiotic-resistant and a susceptible strain (or species) influence the two-lineage community response to antibiotic exposure. Our model predicts that while increasing competition and antibiotics leads to increasing competitive release of the antibiotic-resistant strain, hitting a mutualistic community of cross-feeding species with antibiotics leads to a mutualistic suppression effect where both susceptible and resistant species are harmed. We next show that the impact of antibiotics is further governed by emergent spatial feedbacks within communities. Mutualistic cross-feeding communities can rescue susceptible members by subsidizing their growth inside the biofilm despite lack of access to the nutrient-rich and high-antibiotic growing front. Moreover, we show that antibiotic detoxification by resistant cells can protect nearby susceptible cells, but such cross-protection is more effective in mutualistic communities because mutualism drives mixing of resistant and susceptible cells. In contrast, competition leads to segregation, which ultimately prevents susceptible cells to profit from detoxification. Understanding how the interplay between microbial metabolic interactions and community spatial structuring shapes the outcome of antibiotic treatment can be key to effectively leverage the power of antibiotics and promote microbiome health.",
"introduction": "Introduction The human body is home to extraordinarily diverse microbial communities, or microbiomes [ 1 ]. Metabolic interactions among microbial members are now known to play a critical role in host health, including beneficial effects such as protection against pathogens [ 2 ], but also detrimental effects such as obesity, diabetes, and enhanced virulence in polymicrobial infection sites [ 3 – 10 ]. When a pathogen arises within such diverse and dynamic ecosystems, recent evidence suggests that the efficacy of drug treatment not only depends on the target species and the drug treatment regimen used, but also on the other species present and on the nature of their interaction [ 11 – 16 ]. Key to controlling antibiotic resistance and managing microbiome health is therefore to understand which treatment strategy is most effective and under what conditions [ 17 – 19 ]. A major concern when using antibiotics is the potential emergence of de novo antibiotic resistant mutants and/or the competitive release of new or existing antibiotic resistant strains [ 19 ]. Competitive release–when one species or strain increases in density due to the decline in density of its competitors–is for instance one of the main causes of C . difficile infection, especially following treatment with broad-spectrum antibiotics. Such antibiotic therapy disrupts the normal gut microbiome composition, killing protective resident species, thus leading to the overgrowth of C . difficile [ 2 ]. Competitive release after drug treatment has also been demonstrated in rodent mixed strain malaria infections consisting of genetically distinct drug-resistant and drug-sensitive Plasmodium chabaudi clones [ 20 – 22 ], with the resistant strain rising in frequency due to the inhibition of its drug-sensitive competitor [ 20 ]. A key factor mediating the strength of competition between susceptible and resistant P . chabaudi strains is resource availability [ 23 , 24 ]. For instance, recent work has shown that resource abundance can lead to the competitive release of the resistant strain and increased virulence [ 23 ]. While there has been a strong focus on competition as a driver of antibiotic resistance and virulence, mutualistic and exploitative interactions among co-infecting bacteria have also been associated with enhanced virulence [ 4 , 25 , 26 ] and, in some cases, antibiotic resistance [ 11 – 14 , 27 ]. For example, Vega et al. (2013) showed that the pathogenic S . typhimurium was able to enhance its antibiotic tolerance by sensing indole produced by the commensal E . coli [ 12 ]. Another example of cross-species protection against antibiotics involves the beta-lactam susceptible S . aureus , which was protected from beta-lactam antibiotics when enclosed within a layer of resistant beta-lactamase producing P . aeruginosa [ 13 ]. In addition to cross-protection that arises when detoxifying enzymes are released into their local extracellular environment [ 13 , 28 – 30 ], recent studies have shown that cross-protection can also occur via intracellular detoxification [ 14 , 31 , 32 ]. For instance, Sorg et al. (2017) recently showed that chloramphenicol-resistant S . pneumoniae can protect chloramphenicol- susceptible S . pneumoniae by degrading chloramphenicol intracellularly, which then lowers the extracellular concentration of antibiotic in their neighbouring environment. Together, these examples highlight the importance of the interplay between species and strain metabolic interactions, their spatial arrangement, and the mode of resistance in shaping the outcome of antibiotic resistance. Although we use the terms strain and species interchangeably, we anticipate that competitive interactions will dominate among strains of the same species, whereas more diverse ecological interactions will be more common among species with more distinct metabolic profiles. Top-down sequencing approaches have revealed important correlations between microbiome composition and host health (e.g., [ 1 ]), yet bottom-up approaches are indispensable for identifying the causal mechanisms underlying microbiome-mediated effects on their host. A major challenge of using a bottom-up approach, however, is that microbiomes are highly diverse resulting in large networks of microbial interactions that become substantially more complex as diversity increases. In order to make sense of such complexity, many studies—as the ones described above- have focused on more tractable, well-defined microbiomes with a reduced diversity and therefore smaller interaction networks. These studies have provided valuable insights into the causal links between microbiome structure and function and host health. For instance, previous work using two-species co-infection models have revealed the role of co-infection for increased virulence [ 4 , 9 , 33 ] and antibiotic tolerance [ 8 , 12 , 34 ]. Here we use a similar qualitative, two species model approach to develop an understanding of the basic principles of antibiotic perturbations on population structure. Since microbes typically grow in multispecies, surface attached micro-colonies and biofilms [ 35 , 36 ], it is therefore key to understand the impact of species interactions and spatial arrangement on the dynamics of resistance [ 37 , 38 ]. Here we examine this idea by extending an established individual-based computer simulation model of bacterial biofilm growth on an inert surface [ 39 ]. Specifically, we investigate how the nature of the ecological relationship between antibiotic-resistant and sensitive strains or species across the conflict-mutualism continuum affects the community response to antibiotic treatment, and what is the role of spatial structure for such outcome.",
"discussion": "Discussion Microbes live in metabolically-connected and spatially extended multispecies communities [ 35 ]. Understanding how microbial communities respond to antibiotic assault is therefore central to improving human health. Our model suggests that antibiotic perturbation can lead to the competitive release of resistant competitors, or to the mutualistic suppression of resistant partner species–with the outcome tuned by costs of resistance, spatial patterning, and potential for detoxification. How can these findings inform the development of strategies that aim at promoting microbiome health? Crucially, whether one wants to enhance or attenuate competitive release and/or mutualistic suppression depends on the species that are present and the impact they have on their host, that is, whether they help or harm their host [ 37 ]. Target infections are commonly polymicrobial [ 8 , 33 , 50 ], particularly for chronic infections such as in cystic fibrosis lung infections [ 51 ] or chronic wounds [ 52 ]. Even for acute and clonal infections, the antibiotic administration still has a strong community context due to impacts on commensal microbiomes, often accompanied by unintentional collateral harm to the host [ 53 , 54 ]. Competitive release occurs when two species compete for shared limiting resources and the removal of one species liberates resources that can be used by the other species, which then increases in density. Because of higher density, the probability of getting mutations that further improve the fitness of the resistant strain increases, potentially leading to higher rates of resistance [ 17 ]. The role of spatial competition for competitive release and the spread of drug resistance has recently been studied experimentally in microbial colonies [ 55 ]. In the absence of antibiotics, de novo resistant clones may remain trapped and starved within the inner region of the colony, layered with growing sensitive cells. When high antibiotic concentrations are applied, however, the sensitive cells are killed and eventually removed from the growing front, thus freeing space and resources that can then be taken up by the resistant cells. A similar finding has been observed in the context of chemotherapy using a computer simulation of tumor growth [ 56 ]. We can therefore see how competitive release is a major concern for health if the resistant strain is a pathogen, as such release may facilitate the rise of antimicrobial-resistant parasites and virulence [ 17 , 20 , 57 ]. Under such conditions, the medical priority is therefore to reduce the rise of resistant strains via competitive release. Two candidate mechanisms for preventing the emergence of antibiotic resistance under such competitive scenario include maintaining competitive suppression, that is ensuring that cells competing with resistant cells are not inhibited or killed by the antibiotic, and/or targeting resistant cells only, for instance by combining antibiotics with phage therapy [ 58 , 59 ]. Although ubiquitous, microbial competition is not universal [ 36 ]. The oral and gut microbiome, for instance, are replete with species that benefit from the presence of other microbial species [ 3 , 4 , 60 – 63 ]. Within a polymicrobial infection context, examples are growing where co-infecting bacteria enhance each others’ growth [ 8 , 26 , 33 ]. Such dense, mutualistic communities are of particular concern for controlling infections as their higher densities may hinder clearance of targeted infections, and also, increase the likelihood of emergence of antibiotic-resistant mutants. So what are the consequences of disrupting communities of antibiotic-resistant and susceptible mutualists? As antibiotic concentration increases, we find that the density of the susceptible species decreases, causing the decline of the resistant species (mutualist suppression), but despite such decline in density, the susceptible species grows better in coculture than in monoculture, illustrating a continued impact of the mutualistic exchange (cross-species phenotypic resistance). From a medical intervention perspective, this means that one can knock down resistant bacteria by hitting mutualistic susceptible species, but also, that one can protect susceptible bacteria by not hitting resistant species that support their growth. If the susceptible species is a pathogen, such cross-species protection is therefore likely to reduce the efficacy of the antibiotic treatment. The potential for susceptible cells to be protected against antibiotics is in principle enhanced when resistant bacteria can detoxify their environment. Empirical evidence of cross-protection of susceptible cells by antibiotic-resistant detoxifying cells is accumulating in the literature, and has been documented both within the same species [ 14 , 28 , 64 – 67 ] and between different species [ 30 , 68 ], and also in different contexts, including cases in which the antibiotics were produced by other community members [ 69 ] or exogenously added to the growth medium [ 14 , 28 , 31 , 64 – 66 , 68 ]. Our work shows that, in spatially extended environments, the emergent spatial arrangement of resistant and susceptible cells influences greatly whether susceptible cells can benefit from detoxification. Importantly, our results suggest that this protective effect is much more effective in mutualistic communities. The reason for this effect is that mutualistic partners tend to spatially mix, thus allowing susceptible cells to fully benefit from the detoxification by their spatially proximate mutualistic partner. In contrast, competition leads to segregation, which ultimately prevents susceptible cells to profit from detoxification. This finding is in line with previous work on the evolution of cooperation in microbial biofilms showing that competition leads to the formation of clonal groups (high segregation) that insulates enzyme-secreting strains from non-secreting strains, thus precluding non-secretors from receiving the benefits of the secreted products [ 70 , 71 ]. Our model assumes that the antibiotic slows down the growth of susceptible cells (bacteriostatic). Generally, we expect the effect of protective detoxification to be stronger in the presence of bacteriostatic than bactericidal (killing) antibiotics. This is because, with bacteriostatic antibiotics, most cells will eventually be able to resume growth once the concentration of antibiotic drops to levels low enough to permit growth. In contrast, with bactericidal antibiotics, only the cells that survive the antibiotic assault will be able to grow. But this killing effect will be reduced in communities where susceptible and resistant lineages intermix, and so less relevant in mutualistic communities. Although our simulations do not look at the effect of bacteriocidal antibiotics, it would be interesting to test these ideas both theoretically and experimentally. Our results are based on the assumption that the antibiotic is applied at time 0, thus before any interaction between resistant and susceptible cells has taken place. In a clinical context, however, antibiotics will likely be applied to an already established microbial community with a given ecological and spatial structure that reflects the no antibiotic case. How does the timing of antibiotic administration impact our results? We ran a new set of simulations where the antibiotic is now added after 4h, 12h, or 24h of biofilm growth, and found that adding antibiotics at later stages of biofilm development generally favours the susceptible strain, and can even prevent the competitive release of the resistant strain ( S8 Fig ). This positive effect of delayed antibiotic administration on the susceptible lineage was stronger at low levels of antibiotics and with detoxification by resistant cells, as expected. Our model assumes that all the interactions are symmetric. Any deviations from the baseline dynamics are therefore due to the effect of the antibiotic and/or the cost or resistance. Interactions between resistant and susceptible strains may, however, be asymmetric, potentially changing the benefits and costs of interactions. How can asymmetries impact the outcome of antibiotic treatment? When resistant and susceptible species are mutualists, their interests are largely aligned. As such, the cross-feeding and cross-protection benefits received by susceptible cells depend on the growth of its mutualist resistant partner. If susceptibles start outgrowing the resistant type, the reciprocal benefits of mutualism are diminished, and this will ultimately harm susceptibles due to the lower provision of food and lower detoxification by resistant cells. This negative feedback can help stabilize the mutualistic interaction, and consequently, the response to antibiotic treatment. Clearly, hosts play a crucial role in shaping the composition and structure of their microbiomes, not only by providing shelter and food to their resident microbes, but also by producing antimicrobial cells and molecules that inhibit or kill potential enemies [ 72 ]. In turn, microbes affect their host’s fitness and behaviour in various ways, including aid with digestion and supplementation of essential nutrients [ 73 ], as well as protection from pathogens, either directly through competition, or indirectly by eliciting the host’s immune response [ 74 , 75 ]. While a considerable amount of work has been done to understand how within-host community dynamics shape host health, including virulence evolution and drug resistance, the majority of these studies have focused on interactions between parasites and in competition. Our work suggests that broadening our view of microbe-microbe and host-microbe interactions to include the full conflict-mutualism spectrum is important to elucidate the causes and consequences of intra- and interspecific interactions in host health. Our work focuses on a two-strain or two-species microbial community living in a simple environment (one/two resources and a single antibiotic), which is undeniably an oversimplified view of natural microbial ecosystems. Although our results are likely not generalizable to the large diversity of microbiomes, such minimal microbiome approach allows us to identify testable principles of community-mediated antibiotic resistance which can lay the foundations for further research on more complex communities. For instance, it would be interesting to extend our model to investigate the outcome of antibiotic treatment in a community consisting of isogenic resistant and susceptible strains plus a third resistant or susceptible strain that acts as a mutualist or competitor. Testing these ideas in more diverse communities and complex environments will help elucidate both general and system-specific principles that determine the outcome of antibiotic therapy. In sum, our results suggest that the interplay between the metabolic and spatial relationships of resistant and susceptible strains within a community plays an important role in shaping the outcome of antibiotic treatment. Understanding this relationship can therefore be key to develop effective control strategies. We expect that the spatial segregation and lower density of competitive communities should facilitate the clearing of an infection because the target sensitive species is isolated from the resistant species, and as such, more vulnerable to antibiotic clearance. In such competitive scenario, a priority is to maintain competitive suppression, and therefore using narrow-spectrum antibiotics may be more effective than broad-spectrum antibiotics. In contrast, the spatial mixing and higher densities of mutualistic communities will make it harder to clear the target species. Under such mutualistic conditions, narrow-spectrum and bacteriostatic antibiotics may therefore be less effective as cross-protection and cross-feeding increase the likelihood that sensitive cells will be able to resume growth once the concentration of the bacteriostatic antibiotic falls below levels permissive for growth. One potential treatment strategy for the control of mutualistic communities would be to first disrupt the mutualism, e.g. through a diet change that induces a shift in metabolic interaction [ 76 ], to lower mixing of resistant and susceptible cells, thus facilitating clearance. Testing these ideas experimentally would be an important step towards effectively leveraging the power of antibiotics to promote microbiome health."
} | 5,000 |
35211539 | PMC8861277 | pmc | 3,114 | {
"abstract": "For bacteria to thrive in an environment with competitors, phages and environmental cues, they use different strategies, including Type VI Secretion Systems (T6SSs) and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) to compete for space. Bacteria often use quorum sensing (QS), to coordinate their behavior as the cell density increases. Like other aliivibrios, Aliivibrio wodanis 06/09/139 harbors two QS systems, the main LuxS/LuxPQ system and an N-acyl homoserine lactone (AHL)-mediated AinS/AinR system and a master QS regulator, LitR. To explore the QS and survival strategies, we performed genome analysis and gene expression profiling on A. wodanis and two QS mutants (Δ ainS and Δ litR ) at two cell densities (OD600 2.0 and 6.0) and temperatures (6 and 12°C). Genome analysis of A. wodanis revealed two CRISPR systems, one without a cas loci (CRISPR system 1) and a type I-F CRISPR system (CRISPR system 2). Our analysis also identified three main T6SS clusters (T6SS1, T6SS2, and T6SS3) and four auxiliary clusters, as well about 80 potential Type VI secretion effectors (T6SEs). When comparing the wildtype transcriptome data at different cell densities and temperatures, 13–18% of the genes were differentially expressed. The CRISPR system 2 was cell density and temperature-independent, whereas the CRISPR system 1 was temperature-dependent and cell density-independent. The primary and auxiliary clusters of T6SSs were both cell density and temperature-dependent. In the Δ litR and Δ ainS mutants, several CRISPR and T6SS related genes were differentially expressed. Deletion of litR resulted in decreased expression of CRISPR system 1 and increased expression of CRISPR system 2. The T6SS1 and T6SS2 gene clusters were less expressed while the T6SS3 cluster was highly expressed in Δ litR . Moreover, in Δ litR , the hcp1 gene was strongly activated at 6°C compared to 12°C. AinS positively affected the csy genes in the CRISPR system 2 but did not affect the CRISPR arrays. Although AinS did not significantly affect the expression of T6SSs, the hallmark genes of T6SS ( hcp and vgrG ) were AinS-dependent. The work demonstrates that T6SSs and CRISPR systems in A. wodanis are QS dependent and may play an essential role in survival in its natural environment.",
"conclusion": "Conclusion In this present study we show that cell densities and temperatures influenced the expression of many genes in A. wodanis . Moreover, the QS related genes in A. wodanis are cell density- and temperature-dependent, where 6°C plays an essential role in activating the AHL-mediated QS system. A. wodanis harbors two CRISPR systems, three T6SSs and four auxiliary T6SSs in its genome. We show that the CRISPR system 2 and T6SS3 of A. wodanis are similar to those in M. viscosa , the bacteria with which A. wodanis co-exists during winter ulcer disease. The low-temperature 6°C at which winter ulcer occurs exerts a significant effect on the expression pattern of A. wodanis than at high-temperature 12°C. We demonstrate here that LitR regulates CRISPR-Cas and T6SSs in a cell density- and temperature manner. Moreover, QS is found to regulate several potential T6SEs in A. wodanis . Thus, the QS regulation of T6SSs and CRISPR-Cas system of A. wodanis could be essential to understand the possible mechanisms used by A. wodanis during its co-existence with other bacteria like M. viscosa or the host.",
"introduction": "Introduction Quorum sensing (QS) is a cell density-dependent cell-to-cell communication system in which bacteria produce and respond to signaling molecules called autoinducers (AIs), which subsequently activates the QS transcriptional regulator to control specific functions such as bioluminescence, motility, biofilm, secretion and virulence ( 1 – 5 ). Multiple QS systems have been described in several Vibrio species ( 6 ). Two QS systems, AinS/AinR and LuxS/LuxPQ that are believed to work through phosphorelay mechanism have been identified in the genome of Aliivibrio wodanis ( 7 ). The AinS/AinR QS system produces AI-1 known as N-acyl homoserine lactones (AHLs) and is present in many Gram-negative bacteria ( 2 , 8 ). These AHL-mediated QS systems are used for intra-species communication ( 8 , 9 ). The LuxS/LuxPQ QS system is present in a wide variety of Gram-negative and Gram-positive bacteria, and produces the AI-2 called furanosyl borate diester and is involved in inter-species communication ( 10 , 11 ). These two QS systems are known to work in parallel in Vibrio harveyi, Aliivibrio fischeri and Vibrio cholerae ( 12 – 14 ). At low cell density, when the AI concentrations are low, the AI receptors act as kinases and relay phosphate to the RpoN (σ54)-dependent activator LuxO via phosphotransferase LuxU. This, in turn, activates the expression of qrr sRNAs, which together with RNA chaperone Hfq represses translation of the mRNA encoding the master regulator LitR ( 9 , 14 , 15 ). At high cell density, the signaling molecules reach a threshold concentration and bind to the receptors to dephosphorylate LuxO, which terminates the qrr sRNA transcription. In the absence of Qrr sRNA, litR is activated to regulate hundreds of genes ( 1 , 14 , 16 ). In the environment, bacteria co-exist in communities with multiple competitors, including other bacterial species and phages, and have to respond to various cues such as changes in temperature, nutrient and iron availability, pH, osmolarity and salinity ( 17 – 22 ). Hence, bacteria have developed various strategies such as protein secretion, contact-dependent growth inhibition, bacteriocin production and antibiotic production to survive and thrive ( 23 – 27 ). Some strategies are not necessarily harmful to competitors, such as adhesion, exopolysaccharide production, siderophore production, motility, biofilm formation, heat shock response and quorum quenching ( 28 – 34 ). Other strategies developed, such as defense mechanisms against phages or mobile genetic elements (MGEs), including restriction-modification, receptor modification and clustered regularly interspaced short palindromic repeats-CRISPR associated (CRISPR-Cas) are for protection ( 35 – 37 ). The CRISPR-Cas system is an adaptive immune system against invading nucleic acids from phages and other MGEs and is composed of cas genes, a leader sequence and a CRISPR array with repeats separated by several spacer sequences ( 35 , 38 ). Two CRISPR classes have been identified with six main types and several subtypes, which are categorized based on the types of cas genes, direct repeats and gene arrangement where class 1 includes the type I, III and IV whereas type II, V and VI belong to class 2 ( 39 – 41 ). Several Vibrio species harbor the type I CRISPR system classified into subtypes such as type I-A, I-B, I-C, I-D, I-E and I-F ( 40 , 42 , 43 ). QS regulation of CRISPR system has been described in bacteria like Pseudomonas aeruginosa, Serratia sp. and Chromobacterium violaceum ( 44 – 47 ). QS regulates type VI secretion systems (T6SSs) in several vibrios such as V. cholerae, Vibrio parahaemolyticus, Vibrio anguillarum, Vibrio fluvialis and Vibrio alginolyticus ( 48 – 52 ). T6SS is one of the largest contact-dependent secretion system bacteria use to transport T6SS effectors (T6SEs) into eukaryotic hosts, bacterial competitors or the environment ( 53 – 56 ). In some bacteria, T6SSs are also known to be involved in the uptake of metal ion ( 57 , 58 ). The T6SS was first identified in V. cholerae as a virulence-associated secretion ( vas ) gene cluster and later in many other bacteria ( 59 – 61 ). The T6SEs are toxin molecules with anti-bacterial or anti-eukaryotic activity ( 62 – 64 ). Several anti-bacterial effector molecules such as amidases, glycoside hydrolases, lipases, phospholipases and nucleases and anti-eukaryotic effectors such as VasX, the Multifunctional-autoprocessing repeats-in-toxin and EvpP have been identified ( 65 – 69 ). T6SS gene clusters often encode immunity proteins close to the effector genes in order to neutralize their effector molecules to prevent self or sibling-killing ( 70 ). For instance, immunity proteins such as antitoxin TsaB in V. cholerae have been reported to protect self-killing against effectors VgrG-3 and Tse2, respectively ( 71 ). In addition, immunity protein-independent mechanisms like envelope stress response and two-component systems can facilitate self-protection ( 72 ). A. wodanis is a Gram-negative, rod-shaped, non-luminescent and motile bacterium with multiple polar flagella ( 73 ). A. wodanis strains grow in the range of temperatures and salt concentrations between 4–25°C and 1–4% respectively ( 73 ). The genome of A. wodanis 06/09/139 contains two chromosomes and 4 plasmids ( 7 ). A. wodanis has been repeatedly isolated together with Moritella viscosa (M. viscosa) from Atlantic salmon ( Salmo salar ) during outbreaks of winter ulcer that mainly occurs at a temperature below 8°C ( 74 , 75 ). Infected fish can survive when the temperature rises above 8°C ( 74 , 76 ). Winter ulcer causes mortality and significant losses in farming industry and is characterized by large ulcers, hemorrhages and internal tissue necrosis in the infected fish ( 74 , 77 ). Although M. viscosa is the primary agent for the disease, the role of A. wodanis and the mechanism behind the co-existence with A. wodanis in the winter ulcers are still unclear ( 74 , 77 ). Experimental study reproducing field observation reveal that A. wodanis affects the progression of M. viscosa infection and is responsible for the chronic pathogenesis in fish ( 78 ). A. wodanis adheres to Atlantic salmon head kidney cells and in a bath challenge, A. wodanis separately produces clinical symptoms such as fin rot and other internal pathological symptoms in Atlantic salmon and it can co-infect Atlantic salmon together with M. viscosa ( 78 ). In a co-cultivation experiment, A. wodanis impedes the growth of M. viscosa and when both the bacteria were implanted together in fish abdomen, A. wodanis alters the gene expression of M. viscosa ( 7 ). It has been further hypothesized that A. wodanis perhaps uses bacteriocin to impede the growth and virulence of M. viscosa ( 7 ). In our previous studies we have reported that A. wodanis produces one AHL and encodes two QS systems ( 7 , 79 ). In the cell culture studies, A. wodanis is known to be cytotoxic to different salmon cell lines when treated with supernatants harvested at cell densities higher than OD 600 (optical density measured at 600 nm) of 6.0 ( 78 , 80 ). Moreover, in a HPLC-MS/MS analysis, the AHL production in A. wodanis begins at the early log phase and increases with increase in cell density along the growth curve ( 80 ). Hence in this transcriptomics study, we chose two cell densities one at the early log phase (OD 600 2.0) and the other at the cell density close to the end log phase (OD 600 6.0) to study the role of cell densities in gene expression. Furthermore, in our recent study, we found that the temperature 6°C which is lower than the winter ulcer disease threshold temperature 8°C, has more impact on AHL production and cytotoxicity in CHSE cell line than 12°C ( 80 ). Therefore, in this study, we wanted to analyze the effects of 6°C and 12°C in gene expression. We have also shown that A. wodanis uses the QS to regulate growth, motility, siderophore- and protease production, hemolysis as well as cytotoxicity in the Chinook salmon embryo (CHSE) cell line ( 80 ). Considering the importance of understanding the QS and survival strategies in A. wodanis , we performed genome analysis and RNA sequencing (RNA-Seq) to reveal the global gene expression in the wild type and its QS mutant strains Δ ainS and Δ litR .",
"discussion": "Discussion A. wodanis is frequently isolated together with M. viscosa during the winter ulcer outbreaks and believed to be involved in the progression of winter ulcer disease ( 7 , 73 , 74 , 78 ). Although M. viscosa is the main agent causing the disease, the reason for its co-existence with A. wodanis is not yet clear. Bacteria use several strategies to compete for niche adaptions, which are known to be regulated by various mechanisms, including QS ( 49 , 100 – 102 ). In our previous study we have shown that QS in A. wodanis regulates various phenotypic traits and cytotoxicity on CHSE cell line ( 80 ). In this study, we performed genome analysis and gene expression profiling of A. wodanis to explore the QS system and its role in regulating the survival strategies. Total DEGs When comparing the transcriptome profile of the A. wodanis wild type between cell densities (tpHCD/LCD) and temperatures (tp12°C/6°C), the strongest effect in terms of number of DEGs were at LCD (164 more genes than at HCD) and at 6°C (140 more genes than at 12°C). Furthermore, the functional mapping of DEGs revealed that families such as secretion system, prokaryotic defense system and transporters were highly expressed at HCD compared to LCD. As expected, the gene families related to protein synthesis such as ribosomes, ribosome biogenesis and transfer RNA biogenesis were less expressed at HCD compared to LCD (tpHCD/LCD). Similar cell density-dependent gene expression has been reported in Aliivibrio salmonicida , where about 1,000 genes were differentially expressed in response to increase in cell density ( 103 ). In the Δ litR mutant, 1.8 times more DEGs were observed at tpHCD/LCD at 6°C than for the wild type grown at the same condition, suggesting LitR is an important regulator in A. wodanis at low temperature. Furthermore, in A. wodanis , the lowly expressed genes in comparison tp12°C/6°C were related to protein synthesis such as non-coding RNAs, ribosomes, transfer RNA biogenesis and ribosome biogenesis . This suggests that genes related to protein synthesis are less expressed at 12°C compared to 6°C. Temperature is one of the major environmental stress factors that bacteria encounter in nature and many genes respond to temperature changes. In addition, the functional families such as the secretion system and prokaryotic defense system were also regulated by temperature in A. wodanis . For example, in V . parahaemolyticus 13% of DEGs were observed when the bacteria were grown at 15°C and 42°C compared to its optimal temperature 37°C, where genes related to energy metabolism were highly affected due to temperature change ( 104 ). In A. wodanis , more DEGs were identified in tpΔ litR /WT (LCD) and tpΔ litR /WT (6°C) compared to at HCD and 12°C, suggesting LitR is a global regulator when the temperature is low and the cells are in the early log phase. This is in contrast to A. salmonicida , where the numbers of DEGs in Δ litR mutant were higher at HCD compared to LCD at 12°C ( 103 ). The comparison between the transcriptome profiles of mutants and wildtype (tpΔ litR /WT and tpΔ ainS /WT) showed about 5 to 24 times more DEGs in tpΔ litR /WT compared to tpΔ ainS /WT at both cell densities and temperatures. This indicates that only a few genes seem to be regulated through the AinS-dependent QS system. This is similar to A. salmonicida , where only about 20 genes were differentially expressed in Δ ainS mutant when compared to wild type, whereas in litR mutant compared to wild type, 3 to 10 times more DEGs were found ( 103 , 105 ). Moreover, in this study, the transcriptomics was performed at OD 600 of 6.0, which is a late log phase in A. wodanis while it can reach an OD 600 of ~8.0. Therefore, the AHL-mediated gene regulation in A. wodanis may differ at OD 600 higher than 6.0. The functional mapping of DEGs from comparisons tpΔ litR /WT and tpΔ ainS /WT showed that the genes affected by LitR and AinS in A. wodanis mainly belongs to the families such as secretion system and prokaryotic defense mechanism , which contained the T6SS and CRISPR genes, respectively. Nevertheless, other families such as enzymes, bacterial motility proteins and transporters were also found to be affected by LitR and AinS in this study. LitR and AinS in A. wodanis also influenced various pathways such as metabolic pathways, Quorum sensing , and two-component systems, suggesting their role in signaling mechanisms and metabolic activities. QS regulation of metabolic functions such as glucose uptake, phosphoenolpyruvate-dependent sugar and nucleotide biosynthesis are known to enhance the co-operative behavior of bacteria to survive under limited nutrient conditions ( 101 ). Similarly, the LitR and AinS regulation of metabolic pathways in A. wodanis may play a role in co-operative behavior under limited nutrient conditions. QS System in A. wodanis In wild type, we found that an increase in cell density resulted in a higher expression of the AHL autoinducer synthase ainS and the master QS regulator litR when grown at 6°C and not at 12°C. This demonstrates that cell density only affects the expression of litR and ainS genes at low temperature. Similar increased expression of ainS was also observed in the Δ litR mutant strain when comparing HCD to LCD (tpHCD/LCD), indicating that the ainS expression is not entirely LitR-dependent. These results confirm our previous work, where we showed that the 3OHC10-HSL production is cell density- and temperature-dependent ( 80 ). Similar to AinS in A. salmonicida ( 105 ), the AinS in A. wodanis negatively affected the luxU expression. This suggests that the decreased expression of luxU could repress qrr and activate litR in A. wodanis . Similarly, in this study, luxU was affected by AinS only at 6°C, which could suggest that low temperature affects the phosphorelay function of luxU . On the other hand, the qrr gene was more expressed at 12°C compared to 6°C. Qrr sRNAs in vibrios are known to regulate several target mRNAs, including the master QS regulator LuxR ( 106 ). In A. fischeri , Qrr sRNAs negatively regulates the production of LitR ( 16 ). Therefore, the increased expression of qrr in A. wodanis at 12°C may negatively affect the production of LitR and, subsequently, the QS dependent gene expression. Our results illustrate that litR, ainS, luxU, qrr sRNA in the A. wodanis QS system were differentially expressed in a cell density and temperature-dependent manner. The proposed QS model in A. wodanis and its regulation of target genes are presented in Figure 4 . Figure 4 Proposed model for regulation of CRISPR and T6SS in A. wodanis 06/09/139 at 6°C. The model includes the two QS systems LuxS/PQ and AinS/R in A. wodanis . At low cell density (LCD), when the AIs concentration is low, the receptors (AinR and LuxPQ) may act as kinases and relay phosphate to LuxO via LuxU, which activates the expression of qrr sRNA. The Qrr sRNA inhibits the expression of litR . When the AI concentration is high at high cell density (HCD), they bind to the receptors to dephosphorylate LuxO and inactivate qrr sRNA. Inactivation of qrr sRNA, in turn, activates litR , which regulates many genes. Arrowheads at both ends indicate phosphorylation relay, and the symbol “P” indicates the phosphorylated state. AinS seems to affect luxU negatively and the litR expression positively. LitR seems to positively affect the genes involved in T6SS1, T6SS2, Aux-1, Aux-2, T6SS effectors and CRISPR system 2 and, conversely, affect T6SS3, Aux-3 and T6SS effectors negatively. Thin line and dashed line with arrowhead indicate regulation at LCD and HCD, respectively, where arrowheads indicate increased expression (+) and bars indicate decreased expression (-). A double arrowhead red line indicates the increased expression of qrr sRNA at 12°C compared to 6°C. Genes with significantly higher and lower expression are presented in purple and blue boxes, respectively. In this study, LitR in A. wodanis did not affect the ainS expression, except at LCD and 12°C (FC = −1.93) in the Δ litR mutant. This confirms our previous work where we showed that the 3OHC10-HSL production is not completely controlled through LitR ( 80 ). However, LitR in A. fischeri and A. salmonicida has been shown to significantly upregulate AinS ( 11 , 107 ). In A. fischeri , several LitR-independent regulatory mechanisms have been reported to regulate ainS , such as ainS auto-regulation or cyclic AMP receptor protein- and glucose-mediated mechanisms ( 11 , 108 ). Similarly, in A. wodanis , other regulatory mechanisms may regulate the expression of ainS . The deletion of ainS in A. wodanis negatively affected the litR expression. In the Δ ainS mutants, the FC values of litR were slightly higher at HCD compared to LCD at both temperatures, which suggests that 3OHC10-HSL partly activates litR independently of the temperature. Similarly, the autoinducer synthase C8-HSL in A. fischeri positively affected litR in a cell density-dependent manner ( 14 ). Regulation of CRISPRs and Spacers A. wodanis harbors a type I-F CRISPR system and a CRISPR system without cas loci, the CRISPR system 1 and CRISPR system 2, respectively. CRISPR systems without cas loci are known as orphan arrays, where most of these are known to be non-functional ( 39 ). However, some of the orphan CRISPR arrays may function together with invading cas genes or the cas genes present in a different location within the same genome ( 109 ). In A. wodanis , the CRISPR system 1 consists of 25 spacers, whereas CRISPR system 2 consists of 40 spacers. The difference in the number of spacers in A. wodanis suggests that the CRISPR system 1 is less active than the CRISPR system 2 or is a remnant of a previously active CRISPR system. In addition, the spacers were not identical between CRISPR systems 1 and 2, indicating both are working independently of each other or that CRISPR system 2 has been introduced later than CRISPR system 1. The cas genes in A. wodanis shows ~90% amino acid similarity to the cas genes in M. viscosa , suggesting that the CRISPR system 2 has been horizontally transferred from M. viscosa . We speculate here that both bacteria can defend themselves against the same agents, which may favor their co-existence during the development of the winter ulcer disease. Similarity search of the spacers in A. wodanis against the phage databases revealed Vibrio phage CTX plasmid pCTX-2 and Staphylococcus phage phiSP38-1. The expressions of cas genes ( cas1, cas3 , and csy3 ) in wild type seems to be cell density-dependent at 6°C, where the cas genes showed increased expression at HCD compared to LCD. However, cell density had no significant effect on the expression of CRISPR arrays of CRISPR systems 1 and 2 regardless of temperatures. Therefore, the CRISPR systems are partially dependent on cell density. Previous studies suggest that bacteria are at higher phage risk at higher cell density densities, and thus protection against phage is important at HCD ( 45 ). This suggests that A. wodanis positively influences cas genes as the cell density increases, and this might provide protection upon phage infection at HCD. The CRISPR arrays of CRISPR system 1 in A. wodanis , was more highly expressed at 6°C when compared to 12°C, suggesting that the temperature 6°C plays a significant role in CRISPR array 1 expression. Temperature is known to regulate CRISPR-Cas genes in P. aeruginosa ( 45 , 102 ). However, temperature difference did not regulate the expression of neither the cas operon nor the CRISPR array of the CRISPR system 2. The complete cas operon of CRISPR system 2 in A. wodanis showed decreased expression in the Δ litR mutant irrespective of cell densities and temperatures, which demonstrates that the CRISPR system 2 is regulated through LitR. In the Δ litR mutant, the expression of the cas genes was higher at 6°C compared to 12°C at HCD. At LCD, only the expression values of the cas1 and cas3 were higher at 6°C compared to 12°C, while other genes such as csy1234 were higher at 12°C. Although LitR in A. wodanis activates the CRISPR system 2, the QS regulation is not completely cell density and temperature-dependent. Furthermore, the data shows that the CRISPR system 1 was more highly expressed in Δ litR mutant compared to wild type, implying that LitR negatively affects CRISPR system 1. In the Δ ainS mutant, although a lower expression was observed on genes csy2, csy3 , and csy4 , the expression of CRISPR arrays of CRISPR system 2 and CRISPR system 1 were not changed by inactivation of ainS . Hence, the activation of the CRISPR system 2 in A. wodanis seems to be partly dependent on the AHL-mediated QS system. The QS activation of the CRISPR system has been reported as an efficient mechanism to enhance the benefit-to-cost ratio in P. aeruginosa ( 44 , 45 ). Although several vibrios and aliivibrios comprise both QS and CRISPR systems, the QS regulation of the CRISPR system has not been described yet. Expression of the CRISPR system can be costly to the bacteria, and in some bacteria like Streptococcus thermophilus , the CRISPR system is constitutively expressed and confers a fitness cost ( 110 ). Therefore, the CRISPR system may only be expressed during phage infection or due to environmental cues ( 111 – 113 ). Similarly, the cell density, temperature and QS dependent regulation of CRISPR may enforce a benefit for A. wodanis during the development of winter ulcer. Despite exhibiting CRISPR systems, one intact prophage was identified in A. wodanis chromosome 1 and several incomplete prophages in both chromosomes and the plasmids. Phages that infect P. aeruginosa are known to escape the type I-F and I-E CRISPR systems using anti-CRISPR proteins ( 114 , 115 ). Therefore, we searched for anti-CRISPR proteins in A. wodanis using ArcFinder ( 116 ). No anti-CRISPR proteins were predicted, suggesting no self-targeted protospacers that prevent CRISPR-Cas response in A. wodanis . Although defective in their function, these incomplete phages are known to have adaptive functions in their hosts ( 117 ). Several of these incomplete phages are a putative source for phage-derived molecular products such as gene transfer agents, bacteriocins, phage killer particles, and they can also interfere with assembly of other phages ( 117 , 118 ). The hypothetical proteins of intact and incomplete prophages from PHASTER output were searched against non-redundant protein database using BLASTP with default parameters. The hypothetical proteins present in the intact prophage were annotated as structural phage-related proteins. However, the incomplete prophages encoded several conserved proteins (with ≥ 90% amino acid identity and query coverage) such as type I restriction endonuclease subunit M, ClbS/DfsB family four-helix bundle protein, DUF559 domain-containing protein, type II toxin-antitoxin system RelE/ParE family toxin and other conserved hypothetical proteins ( Supplementary Table 8 ). These proteins encoded by the incomplete prophage may play a role in adaptive functions of A. wodanis . However, further research is required to verify this. Regulation of T6SSs, Aux, and T6SE Molecules Bacteria secrete many virulence factors during the host-pathogen interface, not only to overcome the host's immune system but also for inter-bacterial competition ( 119 ). T6SS is an important virulence and survival factor present in about a quarter of known Gram-negative bacteria ( 120 ). A. wodanis genome revealed three T6SSs and four auxiliary clusters. Many bacteria possess more than one T6SS, which likely have different functions. For example, Burkholderia thailandensis possesses five T6SSs copies with different functions, where T6SS1 enhances the growth in the presence of other competing bacteria and T6SS4 is involved in the manganese transport to survive under oxidative stress, and the T6SS5 is involved in virulence in the murine model of pneumonic melioidosis ( 121 , 122 ). Similarly, the multiple T6SSs in A. wodanis may have different cellular functions. The T6SS1 in A. wodanis is highly similar (71–88%) to the T6SS system 1 in A. fischeri MJ11, while the T6SS2 shows high similarity (54–92%) to V. cholerae O1E1 T6SS and V. fluvialis T6SS2 ( 90 , 123 , 124 ). The T6SS3 in A. wodanis shows similarity (33–84%) to M. viscosa, V. anguillarum, A. salmonicida and Vibrio tapetis ( 48 , 125 , 126 ). Hcp and VgrG are essential components for the proper functioning of T6SS ( 127 ). A. wodanis encodes vgrG1 in Aux-1, however, it contains hcp in neither T6SS1 nor Aux-1 clusters. In A. fischeri MJ11, the T6SS1, which is similar to the T6SS1 of A. wodanis , is believed to interact with eukaryotic cells and is not involved in inter-strain killing ( 124 ). Moreover, in A. wodanis Aux-1 is located close to the heme uptake and utilization related genes. Metals such as iron are important for many cellular processes, and the genes located close to T6SS genes are known to be involved in iron uptake, for example, in P. aeuroginosa ( 58 ). Thus, the T6SS1 along with the Aux-1 may possibly be involved in iron uptake from the host or environment. Except for Hcp, the other structural T6SS proteins share low-level homology between each T6SSs. This indicates that the multiple T6SSs in A. wodanis is not a result of a recent duplication. Four copies of hcp were identified in the main and auxiliary T6SS clusters of chromosome 2. The proteins Hcp1 and Hcp4 showed 60% homology to each other, whereas Hcp3 and Hcp4 showed 100% homology to each other. Besides the structural role of Hcp, it is involved in the inter-bacterial competition, bacterial invasion, adherence, and cytotoxicity against host cells, also known to have other functions in different bacteria ( 127 , 128 ). Therefore, the multiple copies of hcp in A. wodanis may have different functions. V. cholerae utilizes T6SS to compete against diverse eukaryotic and prokaryotic organisms ( 66 , 129 ). In V. fluvialis , the T6SS2 is anti-bacterial and provides a better competitive fitness in the marine environment ( 123 ). The T6SS2 in A. wodanis , which shows higher homology to V. fluvialis and V. cholerae , may enhance A. wodanis through inter-bacterial competition and virulence. The T6SS3, unlike T6SS1 and T6SS2 in addition to structural components, contains additional genes vtsABCD encoding transporter proteins and does not contain vasH . VtsA-D plays a role in stress responses, transport function and hcp expression in V. anguillarum , and VasH is essential to drive the expression of the T6SS operon by inducing hcp and vgrG expression ( 48 , 130 ). The mutation in vasH repressed hcp expression and impaired its anti-bacterial activity in other vibrios ( 123 , 131 ). In V. anguillarum , VtsA-D proteins are involved in stress responses, however, plays no role in virulence ( 48 ). Similarly, T6SS3 in A. wodanis is probably involved in stress responses. After V. anguillarum , the T6SS similar to T6SS3 in A. wodanis is in M. viscosa (mts1). The genes encoding Hcp (AWOD_II_1028 and AWOD_II_1032), which are located close to each other, shows 71% similarity to M. viscosa hcp , MVIS_3030 ( 7 ). This implies that the T6SS3 in A. wodanis might have a similar function as mts1 of M. viscosa during the winter ulcer disease development. In this study, expression of the T6SS1 and T6SS2 genes and their auxiliary clusters in A. wodanis are dependent on cell density. Such cell density-dependent T6SS expression has been reported in V. parahaemolyticus ( 50 ). Some of the genes in the T6SS2 and auxiliary clusters (Aux-2 and Aux-3) were found to be altered by temperature. The expression was found to be higher at 6°C than at 12°C. In V. fluvialis , the T6SS2 is regulated by temperature ( 123 ). Temperature-dependent regulation of virulent factor genes may be an essential feature for many bacteria to survive in harsh environments ( 132 ). LitR in A. wodanis seemed to positively affect two T6SSs (T6SS1 and T6SS2) and negatively affect the expression of T6SS3 gene cluster. This demonstrates that QS regulation of the T6SSs in A. wodanis is very complex. The regulation of T6SS3 by LitR in A. wodanis indicates T6SS3 may play different roles than T6SS1 and T6SS2. Such reciprocal regulation has also been shown in V. parahaemolyticus , where the QS regulator OpaR downregulates T6SS1 and upregulates T6SS2 where T6SS1 functions as anti-bacterial and T6SS2 as anti-eukaryotic ( 133 ). LitR in A. wodanis seemed to positively affect only the genes encoding the outer sheath and base-plate proteins of T6SS1, suggesting these genes are QS dependent. Interestingly, LitR was involved in activating the expression of the whole apparatus of the T6SS2 system. Moreover, LitR also repressed the entire T6SS3 gene clusters but only at LCD at 6°C. Therefore, T6SS2 is ultimately QS dependent, whereas T6SS1 and T6SS3 are not completely QS dependent. Regulation of T6SS by LuxR homologs have been described in V. cholerae (HapR), V. alginolyticus (LuxR) and V. anguillarum (VanT) ( 48 , 49 , 51 , 134 ). Furthermore, we observed that LitR in A. wodanis is a strong activator of hcp1 expression at 6°C than at 12°C. Hence, this possibly implies that hcp1 of T6SS2 is may be involved in the cytotoxicity in CHSE cell line ( 80 ). Temperature has been shown to influence hcp expression in other bacteria such as Yersinia pestis and V. parahaemolyticus ( 133 , 135 ). Similarly, in A. wodanis , the high expression of hcp at 6°C indicates that the T6SS2 could be more active at low temperature (6°C). We identified that the genes in Aux-2 encoding ankyrin repeat-containing proteins and RHS proteins were differentially expressed in tpΔ litR /WT at 6°C. Ankyrin repeat proteins are known to be involved in pathogenesis by imitating and impeding host function ( 136 ). RHS proteins are toxins that are exported to the cell surface through T6SS, and it mediates anti-bacterial activity ( 137 – 139 ). AinS had no significant effect on the main and auxiliary clusters of T6SSs like LitR. However, AinS positively influenced the expression of the hcp1 and vgrG1 genes and may indicate that only these T6SS genes are dependent on AHL-mediated QS. We predicted several T6SS effectors in A. wodanis , including lipoprotein, nucleases, membrane proteins, amidases and succinylglutamate desuccinylase. However, most of them are putative and hypothetical proteins, which require further research to confirm. From the transcriptomics data, we found that cell density regulated several predicted T6SEs in wild type. Choline dehydrogenase, an osmoprotectant enzyme that protects bacteria from adverse temperatures and other stresses, was more highly expressed at 6°C ( 140 , 141 ). The temperature has affected expression of several T6SEs indicating a temperature-dependent production of effector proteins. Similar to the LitR regulation of T6SS main and auxiliary clusters, it also controlled several T6SEs. Few T6SEs were also found to be affected by AinS. This may indicate that several effectors are dependent on QS, where LitR influenced the expression higher at LCD and 6°C. Some of the known effectors included porin-like protein H (AWOD_I_1000), a molecular filter for hydrophilic compounds and bacteriocin (AWOD_p920_0063), which is a virulent factor in A. wodanis that modulates the growth and virulence of M. viscosa ( 7 , 17 ). Genes encoding T6SS immunity proteins are usually located close to the genes encoding effector proteins ( 63 ). The potential immunity protein of Aux-1 (AWOD_I_1437) in A. wodanis shows 30% amino acid similarity to the immunity protein in V. cholerae strain O1E1 ( 90 ), while in Aux-2, the immunity protein (AWOD_II_0134) shows 29% amino acid similarity to Mucilaginibacter gotjawali ( 142 ). The immunity protein (AWOD_II_1056) in Aux-4 shows 77% amino acid similarity to a hypothetical protein in A. fischeri MJ11 ( 124 )."
} | 9,042 |
38612138 | PMC11012825 | pmc | 3,115 | {
"abstract": "Superhydrophobic coatings can be a suitable solution for protecting vulnerable electrical infrastructures in regions with severe meteorological conditions. Regenerative superhydrophobicity, the ability to regain superhydrophobicity after being compromised or degraded, could address the issue of the low durability of these coatings. In this study, we fabricated a superhydrophobic coating comprising hydrophobic aerogel microparticles and polydimethylsiloxane (PDMS)-modified silica nanoparticles within a PDMS matrix containing trifluoropropyl POSS (F-POSS) and XIAMETER PMX-series silicone oil as superhydrophobicity-regenerating agents. The fabricated coating exhibited a static contact angle of 169.5° and a contact angle hysteresis of 6°. This coating was capable of regaining its superhydrophobicity after various pH immersion and plasma deterioration tests. The developed coating demonstrated ice adhesion as low as 71.2 kPa, which remained relatively unchanged even after several icing/de-icing cycles. Furthermore, the coating exhibited a higher flashover voltage than the reference samples and maintained a minimal drop in flashover voltage after consecutive testing cycles. Given this performance, this developed coating can be an ideal choice for enhancing the lifespan of electrical insulators.",
"conclusion": "4. Conclusions The presence of ice or pollution on electrical infrastructure, such as electrical insulators, can disrupt their functionality. Superhydrophobic coatings could be an appropriate solution to this issue; however, their low durability is a significant drawback. This research addresses a gap in existing literature within the domain. The development of a regenerative superhydrophobic coating, designed for application on electrical insulators and infused with select superhydrophobicity agents, capitalizes on their combined presence. The fabrication of regenerative superhydrophobic coatings capable of regaining superhydrophobicity after damage to the superhydrophobic layer would be an effective response to this challenge. We therefore developed a PDMS-based superhydrophobic coating containing hydrophobic aerogel microparticles and fumed silica and post-treated with polydimethylsiloxane nanoparticles. It is essential to incorporate self-healing superhydrophobic agents into the coating to achieve superhydrophobicity regeneration. Because of the significant potential of F-POSS in enhancing the coating’s hydrophobicity and silicone oil in reducing surface energy, FL0578 trifluoropropyl POSS (F-POSS) and XIAMETER PMX-series silicone oil were added to the coating mixture. The coating was applied to substrates using spin coating. The final coating, coded as SHP–REG, demonstrated a contact angle as high as 169.5 ± 0.6° and exhibited excellent water repellency and self-cleaning properties after water immersion and dry contamination tests. The superhydrophobicity regeneration of the SHP–REG sample was verified through repeated immersion in acidic and basic buffer solutions and repeated air plasma treatments. In contrast to the SHP coating, the developed coating was able to regain superhydrophobicity after both tests, indicating a favorable performance for its overall application. After each plasma treatment, the SHP–REG coating recovered its superhydrophobicity autonomously. The superhydrophobicity regeneration capability, determined by water contact angle measurements, profilometry, and FT-IR analysis, confirmed the regeneration of the coating’s superhydrophobicity. To better evaluate the performance of the developed coating for real-life application on electrical insulators, we ran a series of experiments. The flashover test demonstrated the beneficial impact of regenerative superhydrophobicity in increasing or maintaining flashover voltage, especially under wet conditions. The ice adhesion strength of the developed coatings was investigated through two approaches using the ice push-off test. Over multiple icing/de-icing cycles, the SHP–REG coating maintained a relatively low ice adhesion.",
"introduction": "1. Introduction In recent years, there has been considerable attention given to the development of superhydrophobic materials. These materials, characterized by a static water contact angle greater than 150° and both a contact angle hysteresis and a sliding angle less than 10°, achieve their unique properties through the combined use of low surface energy materials and micro-nano surface roughness. Superhydrophobic materials offer significant advantages, such as water repellency and self-cleaning properties, which make them suitable for various applications, including water–oil separation, anti-corrosion, and anti-icing purposes [ 1 , 2 ]. A particularly interesting application of superhydrophobic coatings is the protection of electrical infrastructure, including electrical insulators. By leveraging the self-cleaning and icephobic properties of these coatings, the durability of electrical insulators can be significantly enhanced. These properties improve the insulators’ surface resistance to flashover and increase flashover voltage [ 3 ]. Applying superhydrophobic coatings to electrical insulators offers effective protection against pollution or ice accumulation. Pollution, which may include mineral matter, electronically conductive metal oxides, soluble salts, and water, can form a conductive layer on the insulators. Similarly, ice formation on the insulators, facilitated by the freezing process, corona discharge products, and the presence of other contaminating substances, can lead to increased conductivity [ 4 ]. This increase in conductivity may result in leakage currents, potentially leading to flashover formation [ 5 ]. Flashovers can lead to the loss of electrical insulation, resulting in surface damage, material degradation, and ultimately, the failure of electrical insulators. Consequently, incorporating anti-icing and self-cleaning properties in the surfaces of high-voltage insulators may become essential [ 6 ]. Therefore, researchers have concentrated on developing electrical insulators using materials with superhydrophobic properties. For example, Vazirinasab et al. [ 7 ] fabricated superhydrophobic high-temperature vulcanized (HTV) silicone rubber surfaces using atmospheric pressure plasma systems. Their goal was to enhance standard silicone-based insulators by introducing self-cleaning capabilities through the incorporation of superhydrophobicity. Similarly, Maghsoudi et al. [ 8 ] created superhydrophobic HTV silicone rubber through compression molding using a replication method. This process involved creating micro-nanostructures on the surface of HTV silicone rubber through the use of an etched aluminum surface, resulting in a superhydrophobic rubber with self-cleaning properties. These innovations represent substantial advances in producing the next generation of silicone rubber insulators. Existing porcelain, glass, and silicone rubber insulators could be improved by applying a superhydrophobic coating. For instance, Ribeiro et al. [ 9 ] developed superhydrophobic coatings for electrical insulators using three different types of polysiloxane. They assessed the effect of these polysiloxanes on the coatings’ final properties through contact angle goniometry, adhesion tests, and resistance to tracking and erosion. Among the tested coatings, the one containing PDMS-treated nano-silica within a matrix of methyl methoxy siloxane and methyl-silsesquioxane demonstrated superior performance. Although research has yielded important findings regarding the application of superhydrophobic coatings on electrical insulators, the durability of these coatings requires further investigation. The durability of superhydrophobic coatings is a critical factor that affects their service life and applicability. de Santos et al. [ 10 ] performed leakage current analyses and visual inspections of the surface to test the durability of their developed superhydrophobic coating. At an outdoor testing station, they determined the degradation rate of electrical insulators coated with their superhydrophobic nano-coatings through comparative leakage current analysis, surface condition monitoring, and observations of dry band arcing. They found that, under real-life conditions, the superhydrophobic coating initially performed well but began to lose its superhydrophobic properties after a short period. The nano-coated insulators initially showed a significant reduction in leakage current for the first two test quarters. However, by the end of the testing period, the coating failed to suppress leakage current, indicating a transition from hydrophobicity to hydrophilicity. The longevity of superhydrophobic coatings poses a challenge, as surface structures featuring micro- or nano-roughness are more prone to mechanical stress than conventional surfaces. Superhydrophobicity can be compromised in two primary ways: (i) physical damage to the structure from impact or abrasion, which increases the contact area between the solid substrate and water, or (ii) an increase in surface energy because of contamination, irradiation, or damage to the hydrophobic low-surface-energy layer. In situations where use of these coatings would be ideal, they would also be expected to be relatively durable under various environmental conditions. Given the inherent fragility of existing superhydrophobic coatings, some researchers have focused on identifying design strategies to develop more robust formulations. The strategies for increasing durability are divided into passive resistance and active regeneration. Passive resistance strategies aim to preserve a surface’s superhydrophobicity after wear, possibly by reinforcing the superhydrophobic properties with techniques such as incorporating elastic compositions to absorb shock, increasing crosslinking sites, enhancing interactions between components, and improving the adhesion between the coating and substrate [ 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. Active regeneration methods focus on restoring superhydrophobicity after deterioration, primarily relying on self-healing or easy repair techniques, with the former being the primary focus of this research [ 11 ]. Regenerative superhydrophobicity offers a potential solution to the durability issues associated with superhydrophobic coatings. These coatings can be defined as those capable of regaining their superhydrophobic properties through self-healing mechanisms after deterioration. The concept of self-healing is inspired by biology; for instance, lotus and clover leaves [ 16 ] exhibit self-healing superhydrophobicity by restoring their regenerable epicuticular wax layer. Regenerative superhydrophobic coatings can be classified on the basis of their healing principles and the type of damage they repair. The healing principles of damaged superhydrophobic coatings can be categorized as (i) transportation of low-surface-energy material to the surface following damage to the low-surface-energy layer because of chemical degradation; (ii) regeneration of hierarchical topography following surface damage from abrasion, scratches, etc.; and (iii) simultaneous use of both principles to repair both physical and chemical damage [ 18 , 19 ]. Depending on the final application or desired properties, researchers have used various low-surface-energy materials in their superhydrophobic coatings [ 20 ] ( Table 1 ). Among the components for regenerating superhydrophobicity, polyhedral oligomeric silsesquioxane (POSS) emerges as a suitable candidate enhancing multiple properties of a coating. POSS, a class of hybrid materials, can reduce a coating’s surface energy, increase its surface roughness, and enhance its hydrophobicity [ 34 ]. Its polyhedral structure and tunable peripheral organic groups make POSS an ideal choice for boosting a coating’s hydrophobicity, thus providing an intriguing option for self-healing superhydrophobic coatings [ 23 , 24 , 35 ]. Silicone oil, though less common in this field, serves as another agent for reducing surface energy, primarily consisting of low-molecular-weight chains with Si-O-Si bonds and surface tensions similar to PDMS [ 36 ]. Research on silicon-based coatings, such as the study by Zhu et al. [ 37 ], has demonstrated the efficacy of silicone-oil-infused polydimethylsiloxane coatings with icephobic properties. Their findings suggest that silicone oil, because of its exceptionally low surface energy, enhances the water repellency of the coating. A comprehensive study of the fabrication of a self-healing superhydrophobic coating for electrical insulators capable of enduring real-life conditions remains a critical gap in the current research. Thus, this study aims to develop a regenerative superhydrophobic coating for electrical insulators using POSS and silicone oil as regeneration agents. The durability and regenerative nature of the coating were tested by immersing it in different pH buffer solutions and subjecting it to air plasma treatments. Its characteristics were analyzed using water contact angle, surface profilometry, X-ray photoelectron spectrometry, and FT-IR. Additional tests of flashover voltage and ice adhesion revealed promising results, indicating that the regenerative superhydrophobic coating could significantly prolong the lifespan of electrical insulators.",
"discussion": "3. Results & Discussion 3.1. Wettability The thickness of the SHP–REG coating was approximately 100–150 µm. This semi-transparent coating exhibited a water contact angle of 169.5° and a contact angle hysteresis of 6°. A wettability comparison is presented in the Supplementary Material to illustrate the superhydrophobic properties of the SHP–REG coating ( Figure S1 ). The SHP–REG coating was applied to one side of a fabric ( Figure S1a ), whereas the other side remained untreated ( Figure S1b ). Colored water droplets were placed on both sides of the fabric. Water droplets easily penetrated the untreated fabric, unlike the SHP–REG side, where the water-repellent layer prevented the fabric from getting wet. The developed coating was spin coated onto filter paper, which then exhibited superhydrophobic characteristics. When the paper was submerged in colored water, it quickly floated to the surface ( Figure S2 ). To further highlight the self-cleaning behavior of the SHP–REG coating, we applied it to filter paper ( Figure 3 ) and glass slides ( Figure S3 ). The samples were dirtied with carbon black particles to simulate pollution. Using a 10 mL syringe filled with water, we demonstrated the coatings’ self-cleaning ability by adding droplets to the coated surfaces. When the droplets contacted the coating surface, they effortlessly removed the contaminants because of the water’s greater affinity for the pollutants relative to their adhesion to the superhydrophobic surface; this resulted in a clean surface ( Video S1 ). 3.2. Superhydrophobicity Regeneration 3.2.1. Immersion in pH Solutions The durability of the SHP–REG coating, as well as the SHP and SYL samples, was tested by immersing them in highly acidic and basic buffer solutions ( Table 3 ). After 2 h of immersion in the buffer solutions, the SHP–REG coating maintained its superhydrophobicity, whereas the SHP sample did not. Nonetheless, after 12 h of immersion, the SHP–REG sample also lost its superhydrophobicity, displaying a water contact angle of less than 150°. Remarkably, the SHP–REG coating regained its superhydrophobicity after 24 h at ambient temperatures, a recovery not observed for the SHP sample. This loss and subsequent regain of superhydrophobicity is attributed primarily to an increase in the surface energy of the sample, which, after being kept at ambient temperature, allowed the superhydrophobic regeneration agents to migrate to the surface, thus reducing the surface energy and restoring superhydrophobicity. A slight increase in the water contact angle observed in the SHP and SYL samples may reflect the hydrophobic recovery property of PDMS-based coatings [ 40 ]. 3.2.2. Plasma Treatment To confirm the superhydrophobicity regeneration capabilities of the SHP–REG samples, they were subjected to air plasma treatment for 8 min [ 41 ]. Figure 4 illustrates the significant reduction in water contact angle on the deteriorated coating following plasma exposure. This exposure introduces hydrophilic oxygen-containing groups to the surface [ 22 , 42 ], transforming it from superhydrophobic to hydrophilic and indicating a chemical modification because of interactions with oxygen and nitrogen radicals and ions as well as the introduction of polar groups [ 43 ]. However, after heating to 140 °C for 5 min or being left at an ambient temperature for 12 h, the SHP–REG samples regained their superhydrophobicity. The durability of the SHP–REG coatings’ self-healing properties was further tested by subjecting them to several cycles of plasma deterioration and healing ( Figure 5 ). Both the SHP–REG and SHP coatings underwent at least six plasma treatment cycles. After each cycle, the contact angle for both samples decreased. Following the initial plasma exposure, the SHP samples failed to recover their superhydrophobicity, with a contact angle recovery to only 120°. Conversely, the SHP–REG samples successfully regained a contact angle above 150° after each plasma exposure, maintaining superhydrophobicity even after nearly six cycles, with a contact angle of 154° documented ( Videos S2 and S3 ). This regenerative ability of the SHP–REG coatings occurs because of the migration of silicone oil and F-POSS to the surface, leading to a reduced surface energy [ 24 , 37 ]. 3.3. Surface Characteristics Surface morphology significantly influences the development of superhydrophobic coatings [ 38 , 44 ]. Thus, to evaluate the impact of plasma exposure on the SHP–REG surface, profilometry analyses were conducted (a) before any damage, (b) after plasma exposure resulting in superhydrophobicity loss, and c) following superhydrophobicity regeneration after 12 h at room temperature ( Figure 6 and Table 4 ). The root mean square (RMS) of roughness represents the standard deviation of the surface roughness height distribution. Before plasma exposure, the SHP–REG coating exhibited an excellent micro-nanostructure with significant RMS and arithmetic average (Sa) roughness values of 306.8 nm and 175 nm, respectively. This hierarchical structure was largely preserved post-plasma exposure, with RMS and Sa values reduced slightly to 225 nm and 150.3 nm, respectively. The hierarchical micro-nanostructures facilitated the trapping of air beneath the water droplets, leading to the creation of superhydrophobic surfaces. A comparison of the 3D profiles before and after plasma treatment reveals that the loss of hierarchical roughness was minimal. As hierarchical roughness is essential for maintaining superhydrophobicity, this minimal deterioration allowed for the regeneration of superhydrophobicity for the SHP–REG samples ( Figure S4 ). FT-IR spectra of the SHP–REG coating were produced before any damage, after plasma deterioration leading to a loss of superhydrophobicity, and after superhydrophobicity regeneration ( Figure 7 ). Peaks at 1259 cm −1 and 795 cm −1 represent Si-CH 3 and Si-C bonds in the coating, respectively, and the peak around 2950 cm −1 was because of asymmetric CH 3 stretching in Si-CH 3 [ 45 , 46 ]. The CH 3 peak was evident in the developed sample before any plasma-related deterioration. However, the plasma-degraded sample showed a significant reduction in the intensity of this function ( Figure 7 ). Peak intensity increased in the samples with regenerated superhydrophobicity, suggesting that the surface chemistry of the samples is susceptible to changes during plasma-induced deterioration. Comparing the spectra of the pristine superhydrophobic sample and the regenerated superhydrophobic sample reveals no significant difference. The negligible difference between the sample before plasma treatment and after superhydrophobicity regeneration indicates that the sample regained its original surface chemistry. Nevertheless, a more precise investigation is required to understand the changes that the developed coating underwent. Therefore, the samples were also analyzed by XPS. To understand the self-healing mechanism governing the superhydrophobicity of the SHP–REG sample, we performed XPS analysis. All binding energy values were calibrated using the reference peak of C1s at 284.8 eV. The XPS spectra of the samples ( Figure 8 ) demonstrate that the SHP–REG sample withstood an increase in the O 1s signal after plasma-related deterioration. The plasma treatment likely generated hydroxyl groups on the coating surface, causing changes in O 1s signals [ 47 ]. The signal decreased in the SHP–REG coating after superhydrophobicity regeneration, showing that the rearrangement of the coating components covered the hydroxyl groups and that other carbon–oxygen polar groups could have formed [ 48 ]. The curve fittings of C1s for SHP–REG before plasma ( Figure 9 ), after plasma deterioration, and after superhydrophobicity regeneration consisted of four peaks: the peak at 274 eV corresponding to C-Si, the peak at 284.8 eV corresponding to C–C and C–H moieties, and the peak at 286.4 eV corresponding to C–OH and C–O–C functional groups [ 43 , 49 , 50 ]. The ratio of C–OH and C–O–C in the SHP–REG sample before plasma deterioration was approximately 6.1%, which increased to 10.8% after plasma deterioration. However, this ratio dropped to around 7.8% for the sample after superhydrophobicity regeneration. Therefore, the increase in hydrophilic polar oxygen-containing groups on the surface after air plasma justifies the decrease in the water contact angle of these samples. 3.4. Flashover Voltage To assess the efficiency of the developed SHP–REG coating intended for electrical insulators, we tested the dielectric strength of the samples. A flashover voltage test was performed to assess the performance of the SHP–REG, SHP, and SYL samples. In the dry test, the SHP–REG coating maintained its flashover voltage over 10 cycles ( Figure 10 a). The flashover voltage under wet conditions was highest for the SHP–REG sample ( Figure 10 b). The water repellency of the surface prevented the formation of a thin water film on the superhydrophobic coatings, allowing separate water droplets to be clearly visible on the surface. Therefore, the SHP–REG coating exhibited nearly identical electrical properties to those observed in the dry test. When the flashover test was repeated, the superhydrophobicity of the SHP–REG and SHP coatings was compromised, resulting in less dispersed water droplets on the surface, thereby forming a water film. Hence, we observed an increased flashover voltage, and by the end of the 10th test, the flashover voltage of both SHP–REG and SHP samples resembled that of the SYL sample. Both superhydrophobic coatings, SHP–REG and SHP, demonstrated good performance in the flashover test under wet conditions. Thus, the water repellency of the superhydrophobic coatings helped reduce or delay flashover-related issues. The flashover voltage of the SHP sample significantly decreased after three tests, whereas the regenerative superhydrophobic coating (SHP–REG) experienced a notable drop in flashover voltage only after the fifth test. The presence of superhydrophobic regenerative agents in this coating effectively delays the effect of flashover on the coating’s nonwettability. If the low-surface-energy layer of the coating is affected during the test, the superhydrophobicity regeneration agents can migrate to the surface and delay the formation of a water film on the coating. 3.5. Ice Adhesion The ice adhesion strength of the SHP–REG, SHP, and SYL samples was determined using a push-off test ( Table 5 ). Compared to the SHP coating, the SHP–REG coating demonstrated a significantly lower ice adhesion strength, which can be attributed to the presence of silicone oil, which increases the surface’s slipperiness [ 51 ]. Ice adhesion was then evaluated over multiple icing/de-icing cycles ( Figure 11 ). For the SHP–REG coating, an increase in ice adhesion after each icing/de-icing cycle was expected given the depletion of silicone oil on the surface [ 51 ]. However, contrary to expectations, the SHP–REG coating exhibited a lower ice adhesion after each cycle. This phenomenon can be explained by the depletion of silicone oil on the surface in each cycle, which leads to an increase in the surface energy of the coating. This triggers the migration of F-POSS and silicone oil to the surface to reduce the surface energy, resulting in a further decrease in the ice adhesion strength of the coating."
} | 6,196 |
35328559 | PMC8954581 | pmc | 3,116 | {
"abstract": "The production of biochemicals requires the use of microbial strains with efficient substrate conversion and excellent environmental robustness, such as Weizmannia coagulans species. So far, the genomes of 47 strains have been sequenced. Herein, we report a comparative genomic analysis of nine strains on the full repertoire of Carbohydrate-Active enZymes (CAZymes), secretion systems, and resistance mechanisms to environmental challenges. Moreover, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) immune system along with CRISPR-associated (Cas) genes, was also analyzed. Overall, this study expands our understanding of the strain’s genomic diversity of W. coagulans to fully exploit its potential in biotechnological applications.",
"conclusion": "4. Conclusions Thermophilic microorganisms are a reservoir for biodiversity, molecular phylogeny, and the production of unique industrially valuable enzymes and other compounds [ 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 ]. The purpose of this work is to expand our understanding of the intra-strain genomic diversity of W. coagulans and to provide new insights into its genetic potential in biotechnological applications. Moreover, our analysis also contributes to the exploration of genomic diversity and sheds light on genetic traits that are essential to the basic lifestyle of W. coagulans . Furthermore, we have expanded the knowledge of the selective advantages that shape the organization and dynamics of W. coagulans genomes, including niche adaptation, antibiotic resistance, and genetic tractability. It is noteworthy to underline that this work provides a comparative analysis among the nine strains based on annotation on NCBI and/or the specific bioinformatics tools used. The heterogeneity of how data are analyzed, annotated, and displayed and sometimes the lack of connectivity among the available data represent the most frequent issues related to bioinformatics studies that need wet-lab experiments to be validated. The analysis of CAZymes did not highlight significant strain-specific differences. Moreover, the amount of CAZymes represents about 1–1.5% of coding sequences for all the strains tested. GH13 genes, that are related to starch degradation, are particularly abundant. However, the lack of information regarding the isolation source of these strains, leaves this matter murky. The comparative study of secretion systems sheds light on the presence of Tat and Sec genes in all the genomes and some sporadic components belonging to type I and VII systems have been identified in some of the strains. Although experimental data on protein secretion are currently available only for MA-13, the presence of diverse pathways to export proteins makes W. coagulans an excellent strain for biotransformation and homologous/heterologous protein expression. The nine strains analyzed have the potential to face environmental challenges through diverse resistance mechanisms. Differences among these strategies are likely related to the environment in which microorganisms thrive or have developed. Analysis of immune systems involved in the defense against mobile genetic elements revealed the ubiquitous presence of the antiplasmid Wadjet system in the genomes analyzed, which could explain the refractory response of W. coagulans to genetic manipulation. Regarding adaptive immunity, although type I-B and type I-C CRISPR-Cas systems are widespread in the analyzed genomes, their patchy distribution and the presence of incomplete Cas protein cassettes and stand-alone CRISPR arrays imply that the gain and loss of CRISPR-Cas systems is a frequent trait in W. coagulans . This underlines the existence of a constant arms race with viruses supported by the CRISPR spacer matches and prophage prediction analyses. This aspect reveals a common pool of viruses of the Caudoviricetes infecting the different strains of W. coagulans . So far, MA-13 is the strain which has received the most extensive physiological and biochemical characterization and therefore can be considered a model system for some interesting biotechnological applications. Indeed, the high operating temperature used during fermentation and its innate and adaptive immunity could protect the MA-13 strain from phage infection and contamination. The next step will be setting up a genetic toolbox for genome editing and metabolic engineering.",
"introduction": "1. Introduction Wide substrate efficiency and excellent environmental robustness are indispensable features for the microbial-based production of biochemicals [ 1 , 2 ]. For instance, bacterial fermentation is currently used as an eco-sustainable alternative to obtain lactic acid (LA) from raw materials [ 3 ]. So far, several lactic-acid producer strains of W. coagulans have been used for the production of LA from lignocellulosic biomasses [ 4 , 5 , 6 ]. Interestingly, W. coagulans grows at temperatures ranging from 50 to 55 °C and pH 5–6 that are chemico-physical conditions comparable to those used for the biomass saccharification [ 7 , 8 , 9 ]. Therefore, W. coagulans represents an attractive biocatalyst for LA production because of its thermophilic nature that not only reduces the risk of microbial contamination but also makes it possible to develop efficient fermentation processes, i.e., simultaneous saccharification and fermentation (SSF) [ 8 , 10 ]. Recently, a novel W. coagulans strain, designed as MA-13 and isolated from canned beans manufacturing, has been tested in an SSF configuration for efficient production of LA from wheat straw [ 7 ]. Moreover, it turned out to be exceptionally resistant to extreme conditions, such as the presence of toxic compounds derived from the thermo-acidic treatment of lignocellulose pointing to this microbe as a suitable biological tool for the eco-friendly production of LA [ 8 ]. W. coagulans is a homofermentative microorganism, which produces LA from glucose via the Embden–Meyerhof–Parnas (EMP) pathway and from xylose via the pentose phosphate pathway (PPP) or the phosphoketolase pathway (PKP). Specifically, the yield of LA varies from 60 to 98% of the total fermentation products depending on whether xylose is metabolized through one or the other pathway [ 4 ]. Interestingly, genomic comparison among different W. coagulans strains have revealed that some of them lack at least some of the genetic determinants of the pentose phosphate pathway, hinting at a significant metabolic and genomic diversity among the isolates [ 4 , 9 , 11 ]. On the other hand, knowledge of the genomic features of the different W. coagulans strains is essential to fully exploit their potential in the white biotechnology applications [ 12 ]. Indeed, W. coagulans is also emerging as a promising GRAS (Generally Regarded As Safe) probiotic candidate, by sharing characteristics with both Bacillaceae and Lactobacillaceae [ 13 ]. Currently, W. coagulans strains are widely used as probiotics in marketed worldwide formulations namely, Sustenex, Lactospore, Neolactoflorene, etc. [ 14 ]. In a recent study, it has been demonstrated that MA-13 over-produces under standard growth conditions α- and β-galactosidases that are key enzymes for improving the nutritional value of lactose-containing food as well as for the production of galactooligosaccharides (GOS) that improve the digestibility and nutritional value of food. Moreover, the identification and comparative analysis of the full repertoire of W. coagulans CAZymes might help to shed light on the probiotic and prebiotic properties of the available strains [ 15 ]. Furthermore, W. coagulans has been also exploited in other diverse biotechnological applications such as in medicine, food, and chemical industry including the production of thermostable enzymes and antimicrobial peptides, such as coagulin [ 16 ]. Likewise microorganisms isolated from food fermentation or spoilage, Firmicutes display a significant variation within a given species, especially for gene clusters involved in the fitness or adaptation to specific conditions [ 17 ]. So far, many W. coagulans strains have been isolated and the genome sequences of 47 and 24 are available on National Center for Biotechnology Information (NCBI) and Integrated microbial Genomes (IMG), respectively (1 February 2022) [ 9 , 18 , 19 , 20 ]. To fully explore the biotechnological potential of MA-13, a comparative analysis among the 9 selected strains has been carried out. Genome decoding is functional to unravel molecular mechanisms driving diversification, genetic variability, and host–pathogen interactions [ 21 ]. Previously, a comparative genomic analyses on a few W. coagulans strains with a special focus on carbohydrates catabolism and genetic determinants responsible for general defense systems from foreign DNA has been reported [ 4 ]. In our analysis, we picked up the closest evolutionary related strains to MA-13 and pinpointed the core, the dispensable genes that are present in some but not all the strains studied (non-core) as well as the strain-specific genes (singletons) related to CAZymes, protein secretion systems, antimicrobial peptides/proteins, secondary metabolites, and the defense systems protecting cells from foreign DNA. Moreover, we show that the genomic content varied among close individual strains, and such variations are traced back to the gain or loss of singleton, genomic islands, selfish DNA (plasmids, bacteriophages, integrative conjugative elements), and/or widespread horizontal gene transfer (HGT) [ 22 ].",
"discussion": "2. Results and Discussion 2.1. Genomic Features of W. coagulans Strains A draft of the MA-13 genome was recently published [ 23 ] supplying a general overview of its genetic content. In the current work, we provide a comparative analysis among phylogenetically related strains, with the purpose to highlight the genomic features that indicate potential in different biotechnological fields. To this aim, the genome sequence of MA-13 was re-assembled using different tools (data not shown) and according to the quality check (QUAST), the best result was obtained using MEGAHIT. The updated genome assembly was deposited in NCBI under the same accession number (WGS: SMSP02000001-SMSP02000116, ACCESSION SMSP00000000) and consists of 116 contigs, with a total length of 2,942,169 bp and an average GC% content of 47.2%. Compared to the previous work [ 23 ], the number of contigs was drastically reduced (from 1653 to 116 contigs) and the total length adjusted from 3,237,270 to 2,942,169 bp. To date, 47 W. coagulans assemblies have been deposited in the NCBI database and their genomic features are summarized in Table S1 . Only 13 assemblies were reported to be sequenced as complete genome, while the others are deposited as draft. In general, W. coagulans genome size varies from 2.86 to 3.69 Mbp with an average size set around 3.33 Mbp as described for MA-13 as well as for H1, XZL4, AF24-21, AF24-19, MGYG-HGUT-00191, B4098, DSM1 strains ( Table S1 ). The number of coding sequences ranges from 2555 to 3237 and the GC% content is around 46–47% ( Table S1 ). 2.2. Phylogenetic and Comparative Genomic Analysis In microbial genomics, phylogenetic analysis is crucial not only to establish the genetic novelty and the genotype–phenotype relationships of the isolates but also to identify the closest relatives within assembled genomes. With this aim, a species tree was generated using the genomes of nine W. coagulans strains available in the KBase system. In our previous work, a phylogenetic tree was built based on 16S rRNA genes and two main groups were identified [ 7 ]. In this study, the comparative whole-genome sequence analysis highlighted the presence of two clades (named Group A and B) that underline the coexistence of two distinct evolutionary lineages. This hypothesis is supported by the similar genome size within each clade (~2.9 Mbp for Group A and ~3.4 Mbp for Group B, respectively) ( Figure 1 , Table S1 ). Moreover, the closest strain to MA-13 is DSM1 (accession number NZ_CP009709) which was also isolated from agri-food wastes [ 20 ]. Then, we resolved to calculate the average nucleotide identity (ANI) value of orthologous genes shared by the two genomes. The FastANI analysis of the reciprocal mappings shows the close evolutionary relationship between the two strains (MA-13 and DSM1) with an ANI value of 98.43% ( Table 1 ). Moreover, as further evidence of the evolutionary connection, we have calculated the digital DNA–DNA hybridization (dDDH) value using the recommended Formula 2 of the Genome-To-Genome Distance Calculator (GGDC) [ 24 ]. The estimated DDH yield was 87.70%, with a probability that these strains belong to the same species and subspecies of 94.96% and 60.49% (via logistic regression), respectively. To get a deeper insight into the genomic variation among the nine strains a comparison of all the genes grouped by sequence homology was carried out [ 25 ]. This analysis was performed using the phylogenetic tree ( Figure 1 ) as input to build up a framework for exploring the genomic diversity and the common features through the analysis of non-core and core genes, and singletons ( Figure 2 , Table S2 ). The non-core set is represented by all genes not universally conserved within a species, whilst the core is constituted by genes conserved across all the genomes [ 26 ]. The genomic diversity and variability among the isolates are highlighted by the analysis of singletons and non-core genes that may be lost or acquired from distal lineages through horizontal gene transfer and represent the genetic source for the emergence of novel variants ( Figure 2 , Table S2 ). To assess the functional features of singletons, TIGRFAM was used to cluster proteins in categories and sub-categories ( Figure 3 ). Genes involved in central metabolism as well as several hypothetical coding sequences and some with unknown functions are distributed over all the genomes. Moreover, a distinctive feature is the presence of prophage elements that are found only in MA-13, DSM1, and P38 ( Figure 3 ). These strains are also characterized by singletons related to the functions of mobile genetic elements. This feature points to the availability of genes attainable by the evolving microbial population and to the capability of microbial genomes to acquire new functions. The distribution of singletons in the MA-13 strain revealed a significant proportion (~40%) of them falling within the hypothetical proteins category with unknown function thus indicating that a significant portion of them is still “terra incognita” and therefore the full understanding of its genomic potential needs to be still unveiled ( Table S3 ). Moreover, transposable elements provide microorganisms with the ability to be responsive and susceptible to environmental changes by acquiring new genetic material and disseminating regulatory elements. The presence of singletons related to transposon activity, which is a distinctive feature of MA-13, points to significant genome plasticity, possibly to meet the requirements of environmental adaptation. 2.3. CAZome of W. coagulans CAZymes repertoire covers diverse enzymatic functions related to the synthesis, modification, and breakdown of saccharides, thus exploiting a great potential in biotechnological applications. W. coagulans CAZome was explored through two different tools, i.e., dbCAN 2 metaserver and the app developed for KBase “Search with dbCAN2 HMMs of CAZy families” ( Table 2 ). The dbCAN tool has been extensively used over the last ten years to annotate CAZymes in genomes/metagenomes and compared to the CAZy website is suitable for comparative analysis [ 27 , 28 ]. Indeed, for instance only three out of the nine genomes were present in the CAZy database. Moreover, the searching parameters in this online database are not specified, thus accounting for differences in the total number of enzymes active on carbohydrates that can be found with other tools. For these reasons, we resolved to investigate on W. coagulans CAZome with the tool “Search with dbCAN2 HMMs of CAZy families” and the results were compared with those obtained with dbCAN 2 metaserver. The former allows a comparative search through the genes of the nine selected W. coagulans genomes by HMMER models according to the dbCAN CAZyme domain HMM database. Instead, the output of the latter are lists of CAZymes identified with three different tools databases (HMMER, DIAMOND, eCAMI), thus resulting in incongruencies among the analyses. Interestingly, by comparing the HMMER data obtained with the two methods, we observed differences in the total number of GTs, CEs, AAs, and CBMs (i.e., Glycosyl Transferases, Carboxyl Esterases, Auxiliary Activities and Carbohydrate Binding Modules, respectively) but not for GHs (Glycoside Hydrolases) ( Figure S1 ). This bias can be traced back to the highest number of available structures/models for GH enzymes than for the other classes of CAZymes. Moreover, the number of GTs, CEs, AAs, and CBMs searched through dbCAN 2 metaserver over exceeds that identified by “Search with dbCAN2 HMMs of CAZy families” since the software parameters are not tunable in the metaserver. The total amount of CAZymes in each of the nine genomes (393 genes in total) represents more than ~1% of all predicted coding sequences ( Table 2 ). A deeper inspection of the CAZome is reported in Figure 4 . The annotated genes were clustered in glycoside hydrolases (50.6%), glycosyltransferases (30.8%), carbohydrate esterases (11.7%), and auxiliary activity (4.6%) families. Glycoside Hydrolases (GHs) catalyze the hydrolytic cleavage of the glycosidic bond and are involved in the degradation of agri-food and lignocellulose biomasses [ 29 , 30 , 31 , 32 , 33 , 34 ]. A total of 199 genes encoding for GHs are clustered in 22 families, among which some are spread over all the genomes, i.e., GH13, GH18, GH23, GH25, GH36, GH65, and GH170. The highest number of sequences (51 and 21, respectively) were found within GH13 and GH65 families whose members are mainly active on substrates containing α-glucoside linkages, such as starch [ 35 ]. GH42 representatives are found in almost all the strains except for H-1 and XZL4. Sequence analysis and experimental data indicate that the GH42 enzymes are mostly beta-galactosidases which are key providers of energy and carbons source through the breakdown of lactose to galactose and glucose [ 36 ]. GHs members belonging to families 18 might be involved in the spore germination and this observation is in line with the lifestyle of W. coagulans members. In particular, the GH10 member was retrieved in the singletons list of W. coagulans 36D1, suggesting that this enzyme was acquired through horizontal gene transfer among bacterial genomes. Glycosyl Transferases (GTs) are enzymes that catalyze the transfer of sugar moieties from activated donors to specific acceptor molecules, forming glycosidic bonds, and are involved in the synthesis of oligosaccharides, polysaccharides, and glycoconjugates [ 37 ]. Typically, the bacterial glycosyltransferases are poly-specific enzymes that mainly belong to families GT2 and GT4 and exploit the inverting and retaining catalytic mechanism, respectively. Except for GT2, GT35, GT83, and GT113, at least one member of the remaining identified GTs is found in all the genomes. Moreover, GT4/GT 51 and GT83/GT113 are the largest and the smallest groups, respectively. Noteworthy, the GT83 family which includes enzymes involved in lipopolysaccharide biosynthesis [ 38 ], typifies the GT repertoire of only two strains, i.e., MA-13 and CSIL1. Finally, family GT28 related to peptidoglycan biosynthesis, maintenance of the rod cell shape, and elongation of the lateral cell, is generally represented by two members for each genome. Carboxyl Esterases (CEs) release acyl or alkyl groups attached by an ester linkage to carbohydrates [ 39 ]. Among the 18 CEs families, only four of them were annotated in this analysis. CE1, CE4, CE9, and CE14 are found in almost all the strains. The remaining enzymes are categorized as Auxiliary Activities (AAs) in the CAZy database and comprise carbohydrate oxidases, redox enzymes involved in diverse functions such as lignin degradation and metabolism of lignin-derived compounds [ 40 ]. AA members (in total 18) were assigned to AA1 and AA4 families; the former are multicopper oxidases that use diphenols and related substances as donors and oxygen as acceptors [ 41 ], while the latter are potential vanillyl-alcohol oxidases [ 42 ]. Finally, a single representative of CBM 34 family has been identified in all the genomes. Little is known about the function of CBM 34 members; indeed granular starch-binding function has been demonstrated only in the case of Thermoactinomyces vulgaris R-47 α-amylase 1 [ 43 ]. The CAZome analysis along with the available biochemical and physiological data in the literature points to W. coagulans as a model microorganism not only for carbohydrate degradation processes but also as a valuable source of novel enzymes for potential applications especially in nutraceutical, food, and medical industries. Specifically, MA-13 is currently tested for its ability to use agri-food wastes as carbon and energy sources (manuscript in preparation), showing excellent degradative capability on diverse biomasses. Since enzymatic activities related to cellulose degradation are missing, W. coagulans has the potential to be used in the isolation of cellulose from agri-food wastes. 2.4. Protein Secretion Systems Bacterial cells rely on a plethora of secretion systems to dynamically interact with their environment. Two main types of protein secretion systems, the Sec and Tat pathways are the most common ones and have been identified in all domains of life [ 44 ]. Both Tat and Sec systems are present in W. coagulans as shown by the core set that includes tatC/tatA and secYEG genes [ 4 ]. Moreover, the comparative analysis of non-core genes revealed that W. coagulans exploits other less widespread secretion systems ( Table 2 ). Indeed, 36D1 and CSL1 bear the hylD gene that is a component of the Escherichia coli α-hemolysin secretion system (type I secretion system) which is otherwise made up also of hlyA, hlyB, and tolC [ 45 ]. Most, but not all, W. coagulans strains are featured by genes of the type VII secretion system (cT7SS) which exports proteins lacking a canonical cleavable signal peptide but bearing a WXG motif at the N-terminus [ 46 ]. EsxA and EsxB are molecular markers of the T7SS system and the corresponding genes (esxA and esxB) are usually part of clusters each harboring coding sequences for a membrane-associated ATPase of the FtsK–SpoIIIE protein family and for other putative components of the secretion system. Only P38 bears a complete set of the main components, whereas all the others show only some of them ( Table 3 ). It can be hypothesized that either some of the T7SS genes are dispensable for leader-less secretion systems or that single components might cross-function with Tat or Sec systems [ 44 , 47 ]. For instance, MA-13 bears essA , essB, and essC which encode for transmembrane proteins, the latter with a demonstrated ATP-ase activity. It is worth noting the absence of esxA whose product usually work in association with EssA, EssB, and EssC. Moreover, we have demonstrated in a previous work that WXG-proteins not even related to virulence factors are secreted in MA-13 through a leader-less mechanism, suggesting that esxA is dispensable for this secretion system in this strain [ 15 ]. Interestingly, a homologue (38% identity) of B. subtilis EsxA has been found in some W. coagulans strains (36D1, 2–6 and P38) but there are no reports about its functional characterization in W. coagulans . In biotechnological applications, it would be useful to facilitate protein production or protein downstream processing using different secretion mechanisms for biotransformations and/or for screening libraries of enzyme variants. The study of the multiple secretion systems functioning in MA-13 along with its fermentation performance [ 7 , 8 ] makes this host a suitable starting point for the development of a consolidated bioprocess for the production of recombinant proteins/enzymes of biotechnological interest. 2.5. Resistance Mechanisms to Environmental Challenges 2.5.1. Toxin–Antitoxin Systems Toxin–antitoxin (TA) systems are ubiquitous among bacteria and play a crucial role in the dissemination and evolution of antibiotic resistance, for instance through stabilization of multi-resistant mobile genetic elements and phages [ 48 , 49 ]. Generally, toxins are proteins that affect metabolism and antitoxins are either RNA or proteins that counteract the effect of the toxin. Currently, TA systems are based on the coordinated action of a toxin which is always a stable protein, while the labile antitoxins can be either RNAs or proteins [ 50 ]. All W. coagulans strains are endowed with a common TA system which relies on ydcD mazF and ydcE/mazF genes, encoding for both an endoribonuclease that inactivates cellular mRNAs and its inhibitor, respectively. Moreover, we spotlighted in the MA-13 singletons set, the presence of a gene encoding for sequence-specific endoribonuclease belonging to PemK/MazF family (MBF8417901.1) [ 51 ] and lying upstream of an ORF encoding for a putative antitoxin of the AbrB/MazE/SpoVT family (MBF8417900.1). The TA systems of W. coagulans are a platform to discover novel antimicrobial targets, as well as to set up genetic reporter systems for plasmid maintenance and protein production [ 52 ]. 2.5.2. Genetic Determinants of Resistance to Bacitracin Another strategy to withstand exposure to toxic compounds is antimicrobial resistance (AMR) which refers to the ability of microorganisms to cope with the effects of antibiotic treatments or antimicrobial peptides [ 53 ]. To identify genomic regions possibly related to AMR, an in silico analysis of W. coagulans “resistome” was performed using PATRIC software. The output of this analysis is a list of gene products that are mostly related to functions of the central metabolism and are potential targets of environmental stressors upon genetic mutations. Then, PATRIC results need careful interpretation since the presence or the absence of some genes cannot be traced back to susceptibility or resistance to certain compounds unless biochemical and/or physiological characterization are carried out. Examples are gyrA , gyrB , and murA present in all the strains that might be antimicrobial target of fluoroquinolone ( Table S4 ). However, no inference can be drawn in regard of fluroquinolone resistance/susceptibility since a physiological characterization has not been carried out for any of the strains. Interestingly, PATRIC analysis revealed the presence of a gene cluster encoding for resistance to a cyclic peptide (bacitracin) in MA-13. In antibiotic-producing bacteria, it is known that biosynthetic operons of peptide antibiotics are frequently associated with membrane drug efflux transporters of the ABC family, which pump out the antibiotics for self-protection [ 54 , 55 ]. Accordingly, all W. coagulans strains analyzed bear three genes encoding for efflux pumps ( bceA , bceB , bcrC ). Furthermore, MA-13 is the only strain with a complete genetic array responsible for resistance to bacitracin including the two-component signal transduction system ( bceRS ) which is adjacent to the efflux transporter genes ( bceA/B ) ( Figure 5 ). This genetic proximity is common to other Bacillus species [ 55 ] and the relative genes are located on contig k141_1005 in MA-13. In this system, BceR is a sensory transduction protein that responds to extracellular bacitracin stimulus and transmits the signal to the regulator BceS. This latter binds the promoter region upstream to bceA/B genes affecting their expression. Whilst the presence of a complete bceRS/AB gene cluster is quite widespread among other Bacillus species [ 55 ], MA-13 exhibits another genetic determinant of bacitracin resistance, i.e., bcrC encoding for a broad-specificity multidrug efflux pump which is located on a genomic region (contig k141_1) distant from the bceRS/AB genetic array. MA-13 BcrC protein is homologous (31.3% a.a. sequence identity) to BcrC of Bacillus licheniformis , a hydrophobic protein functioning as a membrane component of the permease [ 56 ]. Although some Bacillus species bear a complete three-components operon bcrABC , it has been demonstrated that the presence of the bcrC gene is sufficient to confer bacitracin resistance [ 57 ] ( Figure 5 ). To sum up, the current analysis demonstrates the presence of putative gene target(s) that may account for tolerance to bacitracin. Bacteria exposed to continuously changing chemico-physical conditions are expected to be endowed with features of better adaptability and competitive fitness to overcome environmental challenges. The horizontal gene transfer (conjugation, transformation, and transduction) and the role played by mobile genetic elements (plasmids, transposons, insertion sequences, integrons, and integrative-conjugative elements) and the bacterial toxin–antitoxin system as well as the occurrence of genetic mutations, lead to a speedy bloom of antibiotic resistance amongst bacteria [ 22 ]. 2.5.3. Secondary Metabolites: Bacteriocins The discovery of new natural compounds produced by microorganisms, the so-called secondary metabolites, is a hot topic for diverse biotechnological applications [ 58 ]. These bioactive molecules, such as pigments, alkaloids, toxins, and antimicrobials, are not involved in the basal metabolism, rather they often perform ancillary functions [ 59 ]. The ability of W. coagulans to hinder bacterial growth and balance co-habitant microbiota populations by producing antimicrobial compounds, was already demonstrated [ 16 ]. To understand the potential of MA-13 in the production of secondary metabolites, the genome was analyzed using antiSMASH, a bioinformatic tool suitable to search for clusters involved in secondary metabolites synthesis ( Figure 6 ). From this analysis, a gene encoding for a non-lanthionine-containing peptide (class II bacteriocins), the circularin A, was identified. Circularin A is usually produced as a pre-peptide that undergoes a proteolytic cleavage of the leader sequence followed by head-to-tail ligation between the N- and C-termini to produce a smaller circular antimicrobial peptide [ 60 ]. This bacteriocin is usually encoded by a set of 4–10 genes usually organized in cluster. A genetic arrangement formed by ORFs encoding for circularin A, CircC, ABC transporter, and two hypothetical proteins were found in MA-13 on contig k141_585. A similar structure is shared with almost all the strains analyzed ( Figure 6 ), but in the case of MA-13, the region is delimited by two repeats. Moreover, given the presence of several surrounding mobile elements, among which a transposase IS4, it is likely that the acquisition of this genetic cassette occurred upon HGT in MA-13. The strain XZL4 is the only one missing the circC gene, whose product is known to have a central role in the maturation of circularin A. Bacteriocin production could be considered advantageous to the producer since these peptides can kill or inhibit bacteria by competing for the same ecological niche or the same nutrient pool. Noteworthy, probiotics that synthetize bacteriocins are of particular importance because these bacteria are widely used in dairy industries. 2.6. Innate and Adaptive Immunity 2.6.1. Innate Immunity Prokaryotic immunity is constituted by multiple systems to defend from mobile genetic elements (i.e., viruses and plasmids). Innate defense mechanisms do not require previous exposure to a pathogen. The examination of the different W. coagulans genomes revealed the ubiquitous presence of the Wadjet defence immune system in all the strains analyzed ( Figure 7 and Table S5 ) [ 61 ]. Wadjet cassettes are composed of the four genes jetABCD , where JetABC are homologs of the bacterial condensins MukF, MukE, and MukB, respectively. Bacterial condensins are involved in DNA condensation and segregation during bacterial replication. The fourth component of the operon, JetD, has a putative topoisomerase VI domain. Three types of Wadjet systems have been described, reflecting the domain organization of its components within the cassette [ 62 ]. W. coagulans strains predominantly contain type II Wadjet systems, although 36D1, CSIL1, and XZL9 harbor type III Wadjet operons ( Figure 7 ). Wadjet system has been related to antiplasmid defense in the Gram-positives Bacillus cereus Q1 and Mycobacterium smegmatis [ 63 ] where it impairs plasmid transformation and plasmid segregation to daughter cells, respectively. It can be hypothesized that the presence of Wadjet systems in W. coagulans is involved in preventing the acquisition of DNA from the environment. This would hamper the development of genetic systems for these strains, similarly to what occurs in M. smegmatis, where disruption of this system allowed the transformation and maintenance of plasmid pAL5000 [ 63 ]. Other isolated defense systems are present in W. coagulans . Strains 2–6 harbor a single CBASS (cyclic-oligonucleotide-based anti-phage signaling systems) cassette in addition to a type II Wadjet system ( Figure 7 ) [ 64 ]. CBASS systems are constituted by an oligonucleotide cyclase that produces cyclic nucleotide secondary messengers upon the encounter of a pathogen, and an effector protein. They are classified into four types according to their operon organization, type of effector, and cyclic nucleotide messenger. In particular, effectors of type II CBASS systems contain ubiquitin-associated domains and their mechanism of action are still unknown given that ubiquitin has not been found in bacteria. However, this system confers protection against phages in E. coli and V. cholerae. Strain XZL9 harbors two Wadjet cassettes of types II and III, plus two Gabija loci ( Figure 7 ). The Gabija system is composed of proteins GajA and GajB where GajA is a sequence-specific DNA nicking endonuclease and GajB is predicted to be a UvrD-like helicase. It is that GajA nuclease activity is activated by the change in the intracellular nucleotide levels resulting from virus replication and transcription, thus eliciting bacteriophage resistance [ 65 ]. Similar to many environmental strains, W. coagulans is not amenable to transformation with exogenous DNA and so far only two strains (DSM1 and P4-102B) are genetically tractable. However, setting up a reproducible genetic system is indispensable to apply metabolic engineering techniques to meet the requirements of commercial applications. The ubiquitous presence of the putative antiplasmid Wadjet immune system in W. coagulans may explain the recalcitrance of these strains to genetic tractability and the deletion of this anti-plasmid cassette constitutes a promising strategy for the development of strains amenable to genetic engineering. 2.6.2. Adaptive Immunity: CRISPR-Cas System and Mobile Elements CRISPR-Cas systems constitute an adaptive immune apparatus in a wide range of bacteria (~40%), and the majority of archaea (~90%); small guide RNAs (crRNAs) interfere with sequence-specific nucleic acids neutralizing invading genetic elements [ 66 ]. A CRISPR locus consists of repeats (23–47 bp) separated by unique sequences (spacers) with similar length (21–72 bp), originating from mobile genetic elements such as bacteriophages, transposons, or plasmids. Moreover, the cas genes are generally closely linked to CRISPR arrays and are diversified. Indeed, CRISPR-Cas systems are classified into two classes which are further subclassified into six types and several sub-types: in class I, the effector module consists of several Cas proteins whereas class II is defined by the presence of a single multidomain protein (e.g., Cas9). The CRISPR-Cas defense mechanism acts in a sequence-specific manner by recognizing and cleaving foreign DNA or RNA. The defense response can be divided into three stages: (i) adaptation or spacer acquisition, (ii) crRNA biogenesis, and (iii) target interference [ 67 ]. MA-13 genome harbors 48 spacers, 51 repeats organized in at least 2CRISPR arrays with the same direct repeat sequence. The exact number of arrays cannot be determined due to the fragmented nature of the MA-13 genomic assembly that includes small contigs containing partial, truncated CRISPR arrays. Additionally, these arrays are linked to several unidirectionally arranged cas genes organized in two loci ( cas1 , cas2 , cas3 , cas4 , cas5 , cas7 , and cas8 ) ( Figure 8 and Table S6 ). Such genomic association is typical of Class I-C, characterized by the lack of cas6 , encoding for an endoribonuclease employed by most type I systems for pre-crRNA processing and by the presence of a single protein encoded by the cas8c gene. The absence of cas6 can be replaced by cas5 whose product performs a similar catalytic reaction. In type I-C system, genes are typically encoded by a single (predicted) operon. Genes cas 3 , 5 , 8c , and 7 of locus 1 share sequence identity below the 30% threshold with the corresponding genes located on the other locus. This indicates that these cas genes do not derive from gene duplication rather they have been acquired through independent events (see below). The comparative genomic analysis revealed that eight strains of W. coagulans possess cas operons of type I-B (2–6, 36D1, H-1, P-38, and XZL9), type I-C (CSIL1, DSM1, H-1, MA-13), or type IV (DSM1), mostly located in the vicinity of CRISPR arrays ( Figure 8 and Figure 9 and Table 4 ). Both type IV cas operons are located within prophages in the DSM1 genome, suggesting that they are of viral origin. Only strain XZL4 lacks a complete cas operon or CRISPR array. The W. coagulans strains contain 1 to 5 CRISPR arrays each, for a total of 30 arrays of which 13 are annotated as orphan CRISPRs (i. e. not located in the vicinity of a cas operon). Additionally, while strains MA-13, P38, and XZL9 have one consensus direct repeat sequence, strains 36D1, DSM1, CSIL1, and H1 have two to three direct repeat sequences despite all strains harboring one single adaptation cassette ( Table 4 ). At present, it is not clear whether orphan CRISPR arrays are indeed functional, although several lines of evidence indicate that at least some isolated CRISPR arrays are active [ 68 , 69 ]. Strains 2–6, 36D1, and CSIL1 have orphan arrays with a repeat different to the one of the CRISPR array associated with their cas operon and adaptation cassette. Moreover, in strains 36D1 and CSIL1 this repeat is predicted to belong to another CRISPR subtype. A similar picture is seen for strain DSM1, which has an adaptation cassette associated with an I-C CRISPR system, but an orphan array with a different direct repeat. These arrays could represent a remnant of a cas operon previously present in the genome that was subsequently lost. Additionally, strain H-1 bears interference cassettes for both I-B and I-C subtypes, but an adaptation cassette only for the I-B operon ( Table 4 ). The repeat of the associated CRISPR arrays is different for each subtype, suggesting that both cas operons are capable of interference, but only the I-B cassette may be able to acquire new spacers. The low number of spacers in the I-C CRISPR arrays (3 to 5) could reflect its inability to acquire new spacers. Taken together, the distribution of CRISPR-Cas modules in W. coagulans strains suggests that loss and gain of CRISPR-Cas cassettes is a common trait in these microorganisms. From an applicative point of view, the endogenous CRISPR-Cas adaptive immune systems can be repurposed for genome editing of W. coagulans, potentially constituting a valuable tool in the genetic toolbox for these strains. Analysis of CRISPR spacer matches allowed the identification of viruses infecting the W. coagulans . From a pool of 651 spacers extracted from the strains, 113 spacers (17.3%) matched to 77 Firmicutes- infecting viruses in the IMG-VR database [ 70 ]. These viruses are classified as members of the class Caudoviricetes, with the majority of them (66%) belonging to the Siphoviridae family. Several viruses match to CRISPR spacers of strains from both clades of W. coagulans (group A and group B), suggesting that these strains share a common pool of viruses. Additionally, most viruses in the network originate from an engineered environment (e.g., lab enrichment), including all spacers from strain MA-13 ( Figure 10 B), while only four viruses derived from environmental ecosystems. Interestingly, one single spacer from strain H-1 matched 38 viruses, of which 36 originate from host-associated environments, particularly the human digestive system ( Figure 10 ). The source of the W. coagulans viruses is in agreement with the prevalent agri-food origin of the isolated W. coagulans strains. The analysis of the adaptive immunity in MA-13 was extended also to the identification of genomic islands (GIs, regions of probable horizontal origin) and prophage regions [ 71 , 72 ]. GIs are non-self-mobilizing integrative regions encoding factors that support the adaptability and competitiveness of the microbes within a niche, including virulence factors and other medically or environmentally important adaptations. Using IslandViewer, the prediction of GIs is carried out with a precise definition of boundaries since integration splits off a gene fragment that marks the distal ends of the island. In total, 297 genes were assigned as belonging to GIs ( Table S8 and Figure 10 ), among which the following cas genes have been identified: cas3 (MBF8417476.1), cas5 (MBF8417475.1), cas8c (MBF8417474.1), cas7 (MBF8417473.1, MBF8417526.1), cas4 (MBF8417527.1), cas1 (MBF8417528.1), and cas2 (MBF8417529.1). A similar analysis conducted on strains 2–6 and 36D1 indicates that the CRISPRs-Cas systems are located in genomic islands that are flanked by transposases [ 4 ]. Several CRISPR-Cas systems have been discovered within GIs and for V. cholerae all CRISPR-Cas arrays are located in mobile genetic elements (MGEs) [ 71 ]. Among the other genetic traits found in GIs that enhance the fitness of MA-13, worth noting is the presence of (i) two genes encoding for putative thiazole-containing heterocyclic bacteriocins (MBF8418016.1 bacteriocin biosynthesis cyclodehydratase) and uberolysin/carnocyclin family circular bacteriocin (MBF8417079.1); (ii) a full set of genes belonging to type I restriction systems that are large pentameric proteins with separate restriction (R, MBF8419113.1), methylation (M, MBF8419111.1), and DNA sequence-recognition (S, MBF8419112.1) subunits; and (iii) a complete cluster of genes encoding for arsenic resistance made up of arsABCD (MBF8417195.1, MBF8417192.1, MBF8417193.1, MBF8417194.1). ArsB and ArsD are arsenite efflux transporters, ArsC is an arsenate reductase and ArsA is an arsenical pump-driving ATPase that overall contributes to confer resistance to arsenic ( Figure 11 , Table S8 ) [ 73 ]. Furthermore, the prophage finding software PHASTER was used to identify intact prophages and their integrase genes in MA-13, utilizing a BLASTP comparison of the query genome with a frequently updated prophage sequence database [ 74 ]. Only one prophage is present in the MA-13 genome whose integrity is indicated by the presence of the attachment junctions attL and attR (also named hybrid attachment sites) at the extremities of the prophage ( Figure 11 ). A total of 58 genes were identified in this genomic region that overall represent a blend of bacterial and bacteriophage features. Specifically, 20 hypothetical proteins were annotated using Bacterial Database and the remaining 38 belong to diverse phages ( Figure 12 and Table S9 ). Among these genes, 13 are linked to Bacillus cereus prophage phBC6A52 (Genbank NC_004821.1) assigned to the Podoviridae family [ 75 ]. Besides MA-13, P38 also bears a complete sequence related to a B. cereus prophage. PHASTER analysis revealed that it shares 100% identity with Bacillus Phage vB_BtS_B83 that belongs to the Bembunaquatrovirus bacteriophages genus. Although bacteriophages typically exhibit a narrow host range, yet the presence of the same phage in two different Bacillus species suggests that the horizontal gene transfer events can overcome the interspecies boundaries to allow the bacteria–phage coevolution in a given ecotype. Indeed, the exchange of phage attachment molecules could even occur in an interspecies context, enabling phage adsorption to non-host species, providing an alternative route for HGT. In in vitro models, species of Bacillus , including W. coagulans, B. subtilis, and B. cereus showed a similar life cycle in artificial gastrointestinal tract models [ 76 ]. Since W. coagulans and B. cereus strains have both been isolated mainly from food sources, it is reasonable that they share the same lifestyle and/or ecological environment, making it possible for genetic material exchanges [ 77 , 78 ]."
} | 11,361 |
40065049 | PMC11894049 | pmc | 3,118 | {
"abstract": "Microbial fuel cell (MFC) can convert the chemical energy of organic matter in wastewater into electrical energy with high degradation efficiency. In this study, a type of specialized microorganism, Pseudomonas aeruginosa, was screened and added to an MFC to promote the degradation of wastewater generated during the production of cytidine acid while improving the performance of the MFC. The MFC achieved a maximum voltage of 57.7 ± 4.4 mV and a maximum power density of 1.9 ± 0.1 mW/m 2 ; moreover, the degradation efficiencies of chemical oxygen demand (COD), total phosphorus (TP), and phosphate reached 76.3 ± 2.8%, 80.3 ± 3.3%, and 85.3 ± 3.5%, respectively. Gas chromatography-mass spectrometry (GC–MS) and metabolomics analysis revealed that Pseudomonas aeruginosa could effectively degrade organic matter in wastewater. Additionally, the metabolic pathways involved may have been pyrimidine metabolism, arginine and proline metabolism, and taurine and hypotaurine metabolism.",
"conclusion": "Conclusions In this study, Pseudomonas aeruginosa -supplemented MFC achieved maximum degradation efficiencies of COD, TP, and phosphate at 76.3 ± 2.8%, 80.3 ± 3.3%, and 85.3 ± 3.5%, respectively. The biofilm formed on the electrode enriched electroactive bacteria ( Pseudomonas aeruginosa ), enhancing the electroproduction function of the MFC and increasing microbial activity, thereby improving the wastewater degradation efficiency. Additionally, a Venn network analysis based on OTU interactions revealed that the microbial community on the electrode biofilm in the MFC exhibited high complexity and stability. The metabolic pathways contributing to wastewater degradation by Pseudomonas aeruginosa included pyrimidine metabolism and arginine and proline metabolism, which effectively degrade organic pollutants in the wastewater. A limitation of this study is the relatively low power density of the MFC. Despite its ability to treat wastewater and generate electricity, the power density achieved in this system is below the levels required for practical applications. Therefore, future research should focus on enhancing the power density of MFCs, which could be achieved by exploring strategies such as optimizing electrode materials, increasing the surface area of electrodes, improving microbial electrochemical activity, and refining operational conditions.",
"introduction": "Introduction Cytidylic acid is extensively used in various applications within the food and pharmaceutical industries 1 . The production of cytidylic acid involves a biological fermentation or chemical synthesis step 2 . This generates a large amount of organic substances, including incompletely reacted raw materials, intermediates, by-products, and microbial cytoplasm, which increase the chemical oxygen demand (COD) of the wastewater. In the process of producing cytidine acid, the use of phosphorus containing compounds as raw materials or catalysts will produce organic phosphorus intermediates and other substances, resulting in a much higher phosphorus concentration in the wastewater than normal wastewater 3 . Thus, the weakly acidic (pH 6.0–6.5) wastewater generated also contains a large amount of phosphorus, especially in the form of organic phosphorus. High content of COD and phosphorus complicate the wastewater treatment process 5 . Furthermore, these substances cause the eutrophication of water bodies and damage the ecological environment when directly discharged without treatment 6 . Currently, the commonly used treatment methods for this type of wastewater with high phosphorus content and COD are physical, chemical, and biological methods. Acelas et al. 8 utilized porous anion exchange resins in a study to selectively absorb and remove phosphate ions from phosphorus-containing wastewater with a degradation efficiency of 86% for phosphate. The selective removal ability of this method is, however, limited under the environment of multiple ion coexistence and may increase the salinity of wastewater, producing secondary pollution and consequently affecting the safety of discharge and the environment. In a study by Nayeem et al. 9 , roasted shellac was used as an adsorbent to degrade phosphorus-containing wastewater, achieving a phosphate degradation efficiency of 62.37%. However, this method has several limitations, including a restricted adsorption capacity, a high dependence on pH for treatment efficiency, and the potential release of pollutants during the roasting process 10 degraded triethyl phosphate (TEP) using a UV/O 3 digestion system with a degradation efficiency of 98.3%. However, the UV/O 3 design process is complicated and requires large monetary investment and high energy consumption, which are not suitable for engineering applications. Pan et al. 11 employed the O₃/CaO₂ advanced oxidation process to degrade sulfate in wastewater, achieving a degradation rate of 90.5%. However, the direct oxidation of phosphate by O₃/CaO₂ is limited, the reaction conditions are harsh, and the process is costly. The biological treatment of phosphorus and COD in wastewater is commonly used in anaerobic–anoxic–oxic (AAO) processes. There are many species of denitrifying bacteria in the denitrification stage of the AAO process, with the largest number of species capable of denitrification found within the genus Pseudomonas , such as Pseudomonas aeruginosa , Pseudomonas fluorescens , Pseudomonas stutzeri , and Pseudomonas mendocina 12 . The AAO process can efficiently remove COD and phosphorus from water and is more energy-efficient and environmentally friendly compared to physical or chemical treatment methods as it reduces the use of chemicals. The technology of the process is mature, and the operation method of the equipment is reliable as it is simple and easy to manage and maintain 13 . However, the activity of microorganisms decreases over time, which reduces the efficiency of treating wastewater. The addition of an applied electric field stimulates the action of microorganisms, which thus increases their activity. In a study by Hu et al., the relative abundance of bacteria increased by 4.63% at 1.5 V compared with that without applied voltage 14 . However, additional applied voltage will increase costs. Microbial fuel cells (MFCs) can produce electricity spontaneously by degrading organic matter 15 , forming an electric field. Some researches have suggested that the electric field generated by MFC can increase the activity and abundance of microbial communities by stimulating cell dehydrogenase activity, increasing the relative permeability of cell membranes, promoting the production of highly conductive and rigid cytochrome OmcZ nanowires in biofilms, enhancing electron transfer, and other methods 16 , 17 , thereby improving the treatment efficiency of wastewater and reducing the cost of treating wastewater. Zhang et al. 18 used MFC to degrade the backflow water generated during shale gas extraction, the closed-circuit MFC had a COD degradation efficiency of 72%, while the open-circuit MFC had a COD degradation efficiency of only 64%. Al-Ansari et al. 19 utilized an MFC to degrade antibiotics in wastewater; the total phosphorus (TP) removal was 89.9 ± 2.8% and the highest COD removal was 91.9 ± 2.3% after treatment with the MFC system. However, MFCs use conventional activated sludge, resulting in a slow degradation efficiency. In this study, the specialized microorganism was first screened to assess its effectiveness in degrading phosphorus and COD in wastewater generated during cytidine acid production. The selected microorganism was then injected into the MFC to evaluate the treatment performance of the bacteria-supplemented MFC on the wastewater. Subsequently, metabolomics analysis was performed to identify the degradation pathway of phosphorus in the wastewater. The Venn network was used to visualize differences in microbial community composition, which manifested in the form of operational taxonomic unit (OTU). This study expands the application potential of MFC technology and provides scientific and technical support for addressing current challenges in industrial wastewater treatment.",
"discussion": "Results and discussion Degradation of wastewater by Pseudomonas aeruginosa The degradation effect of Pseudomonas aeruginosa on COD, TP, and phosphate in wastewater is shown in Fig. 2 . Fig. 2 Degradation efficiency of ( a ) COD, ( b ) TP and ( c ) phosphate in wastewater with different dosages of Pseudomonas aeruginosa. It can be observed in Fig. 2 that the degradation efficiencies of COD, TP, and phosphate all increase with reaction time. In Fig. 2 a, there is a significant increase in COD degradation efficiency over time. During the initial phase, microorganisms are exposed to a higher concentration of organic matter, which promotes COD breakdown. As the reaction time extends to 48–72 h, the COD degradation efficiency levels off, likely due to the depletion of organic matter, which limits substrate availability for microbial metabolism 24 . As the dosage of Pseudomonas aeruginosa increases from 20 to 60 mL, COD degradation efficiency increases significantly, reaching 50.88 ± 1.82%. This improvement is likely due to the larger microbial population, which can more effectively utilize available carbon sources, thereby accelerating COD degradation. This may be attributed to the fact that when the strain dosage was low, an appropriate increase in the strain dosage could more fully utilize the carbon source in the MFC, thus accelerating the growth and reproduction of the microorganisms 25 . However, when the dosage is further increased to 100 mL, COD degradation efficiency decreases. This could be due to an excess of microorganisms, which leads to rapid consumption of available carbon, ultimately limiting microbial growth and metabolism 26 . In Fig. 2 b, the TP degradation efficiency follows a trend similar to that of COD, increasing over time and stabilizing between 48 and 72 h. TP degradation efficiency also rises with increasing Pseudomonas aeruginosa dosage, peaking at 45.12 ± 3.0% at a 60 mL dosage. However, similar to COD, when the dosage exceeds 60 mL, TP degradation efficiency begins to decline, likely due to the rapid consumption of carbon sources, which limits microbial metabolic activity. The metabolic efficiency of the microorganisms slowed down, leading to a decrease in degradation efficiency 27 . This result suggests that TP degradation follows a pattern closely resembling that of COD, both showing similar dependencies on microbial dosage. In Fig. 2 c, phosphate degradation efficiency shows a similar trend to that of TP, gradually increasing over time and stabilizing between 48 and 72 h, reaching 60.52 ± 1.6%. As with the other pollutants, phosphate degradation efficiency increases with the dosage of Pseudomonas aeruginosa . At a 60 mL dosage, phosphate degradation efficiency peaks at 60.52 ± 1.6%. Differently from COD and TP, phosphate degradation efficiency remains stable even at higher dosages. This may be due to the sufficient reaction time, along with the high COD concentration, which provides continuous carbon sources for microbial activity, thus maintaining high phosphate removal efficiency 28 . As shown in Table 1 , compared to the study of Li et al. 29 , the removal efficiencies of COD and TP in this study are relatively low. Comparing with the study of 7 , the phosphate degradation efficiency in this study is relatively high. Yang et al. 4 found that as the concentration of phosphate increased, the degradation efficiency decreased, probably because of the shortage of reaction time and carbon source during the incubation. However, the degradation efficiency of this study remained stable at 60.52 ± 1.6% under high phosphate concentration, which may be attributed to the longer reaction time and higher COD content of this study. Table 1 Efficiency of phosphorus-containing wastewater degradation by different Pseudomonas spp . Bacteria Initial wastewater Degradation time (h) rpm Temperature (°C) Degradation efficiency References Pseudomonas mendocina A4 Salinity of 10% and 15%, PO 4 3− –P concentration of 18.84 mg/L 48 160 30 PO 4 3− –P removal efficiency of approximately 40% 30 Pseudomonas aeruginosa COD concentration of 138.5 ± 15.25 mg/L, TP concentration of 2.07 ± 0.18 mg/L 26 150 28 COD and TP removal efficiencies of 68.23% and 51.21% 29 Pseudomonas stutzeri ADP-19 PO 4 3− –P concentration of 20 mg/L 36 150 30 PO 4 3− –P removal efficiency of 52.2% 7 Pseudomonas putida strain NP5 PO 4 3− –P concentration of 20, 50 and 100 mg/L, respectively 48 160 30 PO 4 3− –P removal efficiencies of 89.61%, 46.09% and 25.67%, respectively 4 Pseudomonas aeruginosa COD, TP and PO 4 3− –P concentration of 55,600 ± 320 mg/L, 5,530 ± 122 mg/L and 1,173 ± 88 mg/L, respectively 72 140 40 COD, TP and PO 4 3− –P removal efficiencies of 50.88 ± 1.82%, 45.12 ± 3.0%, and 60.52 ± 1.6%, respectively This study Notably, Pseudomonas was responsible for degrading wastewater generated during the production of cytidine acid, but it is difficult to have a comparative assessment since the initial pollutant concentration and degradation conditions varied across the studies. In order to further analyze the degradation changes of the substances in the wastewater, we measured the wastewater before and after the degradation process via GC–MS (Tables S1 – S2 ). Table S1 presents the original wastewater, and Table S2 presents the wastewater after treatment with 60 mL of bacterial solution dosage. As can be seen from Table S1 , the raw wastewater contained 96 substances, of which the highest levels of several substances were 3,4-dimethylbenzaldehyde, tricyclopentadeca-3,7-dien[8.4.0.1(11,14)], α-patchoulene, triethyl phosphate, ethyl hexadecanoate, and 2,4-di-tert-butylphenol, among others. The degraded wastewater contained 90 substances, of which the most abundant were (sec-butylsulfanyl)cyclohexane2,4-di-tert-butylphenol, triethyl phosphate, tetradecamethylcycloheptasiloxane, and 1-undecanol, among others. By comparing Table S1 and Table S2 , it is evident that 3,4-dimethylbenzaldehyde, α-patchoulene, 4-hydroxyneoisomenthol, tricyclopentadeca-3,7-dien[8.4.0.1(11,14)], 3,5,5- trimethylhexyl methylphosphonofluoridate, dichloroacetic acid, 2-(1-adamantyl)ethyl ester, and triethyl ethyl ester were present in the raw wastewater, but these substances disappeared after the degradation process. The contents of 3,5,5-Trimethylhexyl methylphosphonofluoridate, dichloroacetic acid, 2-(1-adamantyl)ethyl ester, and triethyl phosphate decreased. This indicates that Pseudomonas aeruginosa can effectively degrade organic matter in wastewater, including phosphorus-containing compounds. It was evident through metabolomics that, after the degradation of wastewater by Pseudomonas aeruginosa , uracil, pantothenic acid, thymine, nicotinic acid, acetylcholine chloride, creatinine, and other metabolites were up-regulated, while cytidine monophosphate (CMP), citric acid, cytosine, taurine, pelargonic acid, and other metabolites were down-regulated (Fig. 3 ). Nicotinic acid increased during metabolism, which is produced by the metabolism of nicotinic acid salts and nicotinamide. Nicotinic acid promoted cellular metabolism, enhanced microbial activity, thus improving the degradation of wastewater 31 . The down-regulation of CMP indicates that phosphorus-containing substances in the wastewater were degraded by the microorganisms, which led to a decrease in the TP content of the wastewater. Fig. 3 Degradation of wastewater by Pseudomonas aeruginosa alone ( a ) volcano diagram, ( b ) heatmap. DS: wastewater degraded by Pseudomonas aeruginosa alone, YS: raw wastewater). In the Kyoto Encyclopedia of Genes and Genomes (KEGG) repository, all the differential metabolites of the different control groups were matched with the KEGG repository to obtain information on the pathways in which the metabolites were involved 32 . As shown in Fig. 4 , during the degradation of wastewater by Pseudomonas aeruginosa , nicotinate and nicotinamide metabolism, citric acid cycle, and taurine metabolism are the main metabolism processes of organic matter. sample (Fig. 3 ) is consistent with the metabolism of nicotinic acid and nicotinamide to generate products, which suggests that nicotinic acid is produced during the degradation process. Nicotinic acid was obtained from upstream nicotinamide under the metabolism of nicotinic acid salt and nicotinamide, and nicotinic acid can promote cell metabolism, increase microbial activity 33 . Under the metabolism of nicotinate and nicotinamide, nicotinic acid is obtained from upstream nicotinamide, which promotes cellular metabolism and increases microbial activity, thereby accelerating COD and phosphate degradation. The tricarboxylic acid (TCA) cycle is the central metabolic network of organisms, closely associated with the metabolic process of sugar, lipids, and proteins and it provided precursors for energy metabolism 34 . The energy produced by the TCA cycle supports the growth and metabolic activities of Pseudomonas aeruginosa , especially involved in the conversion of phosphate into components of the organisms or the precipitation of phosphate minerals, and the TCA cycle is directly involved in the mineralization of organic matter in the wastewater, which breaks down the complex organisms into carbon dioxide and water, resulting in a significant reduction of COD. During taurine metabolism, Pseudomonas aeruginosa is able to utilize taurine as a carbon source and energy source to reduce the total organic carbon concentration in wastewater 35 , thereby reducing COD. Fig. 4 Metabolic pathway of nicotinate and nicotinamide metabolism, citric acid cycle, taurine metabolic during degradation. Degradation of wastewater by MFC containing Pseudomonas aeruginosa Figure 5 shows the effect of the MFC enhancing the degradation of high-phosphorus-containing wastewater after one full cycle of an operation of a single-chamber MFC. Fig. 5 Degradation efficiency of COD (a), TP (b), phosphate (c). As can be seen in Fig. 5 , compared to the degradation of wastewater by Pseudomonas aeruginosa alone (Fig. 2 ), the addition of the bacterial solution to the MFC resulted in higher degradation efficiency. This may be attributed to the abundant microbial community in the activated sludge of MFC, which promotes the degradation of wastewater 36 . Additionally, higher voltage contributes to increased microbial activity, which further supports degradation. Elevated voltage enhances the surface hydrophobicity of microorganisms, promotes the migration of negatively charged sludge, facilitates contact between sludge and substrates, improves the ability of bacteria to extract nutrients from wastewater, and provides more energy for bacterial growth and reproduction. This in turn promotes metabolic activity and degradation efficiency ( 37 ). It was obvious that MFC with added Pseudomonas aeruginosa had higher removal efficiencies for COD, TP, and phosphate than MFC without added Pseudomonas aeruginosa , regardless of whether it operates in open or closed circuit. Moreover, closed-circuit operation MFC had higher removal efficiencies than open-circuit operation, regardless of whether Pseudomonas aeruginosa was added or not. The high removal efficiency in the closed-circuit operation was due to the higher species abundance, which had a positive effect on degradation 38 . A total of 1,153,287 high-quality sequences were acquired from the sludge, anode and cathode of the four MFCs. In the sludge of MFC-1 and MFC-2, 356 (Cluster 1) and 327 (Cluster 3) OTUs were unique (Fig. 6 a), while 258 (Cluster 1) and 235 (Cluster 3) OTUs were unique to the anode (Fig. 6 b), and 26 (Cluster 1) and 221 (Cluster 3) OTUs were unique to the cathode (Fig. 6 c). In MFC-3 and MFC-4, 408 (Cluster 13) and 283 (Cluster 15) OTUs were unique to the sludge (Fig. 6 a), 224 (Cluster 11) and 226 (Cluster 15) OTUs were unique to the anode (Fig. 6 b), and 651 (Cluster 13) and 531 (Cluster 15) OTUs were unique to the cathode (Fig. 6 c). These findings indicate that the sludge, anode, and cathode in both open- and closed-circuit MFCs exhibit distinct microbiota compositions. Community diversity showed a high degree of consistency across samples for each tested condition. The species abundance (Chao 1 and ACE, as shown in Table S3 ) in the sludge, anode and cathode of the closed-circuit MFC was higher than that of the open-circuit MFC. A PCoA (Fig. S2 ) also exhibited distinctions between the in the sludge, anode and cathode of open-circuit MFC and closed-circuit MFC. And it can be seen that there is a marked separation between the MFCs with added Pseudomonas aeruginosa and the MFC without Pseudomonas aeruginosa . Fig. 6 Venn network of microbiomes. ( a ) Venn network of microbiomes in sludge of MFCs, Nodes A, B, C and D represent the sludge of MFC-1, MFC-2, MFC-3 and MFC-4, respectively. ( b ) Venn network of microbiomes in anode of MFCs, Nodes A, B, C and D represent the anode of MFC-1, MFC-2, MFC-3 and MFC-4, respectively. ( c ) Venn network of microbiomes in cathode of MFCs, Nodes A, B, C and D represent the cathode of MFC-1, MFC-2, MFC-3 and MFC-4, respectively. Cai et al. 39 also pointed out that electrical current in MFCs shaped microbiomes, especially biofilms, and thus improved pollutant removal efficiency. MFCs were dominated by the phyla Proteobacteria , Firmicutes , Actinobacteriota and Bacteroidetes (Fig. 7 ). The majority of phyla in anode belonged to Proteobacteria (41.47–93.81% relative abundance) in closed-circuit MFCs and Firmicutes (11.54–54.47%) in open-circuit MFCs. Moreover, as can be seen in Fig. 7 , in the classification level of the genus bacteria, there are differences in the dominant populations between the closed-circuit MFCs and open-circuit MFCs. In the cathode of closed-circuit MFCs, Pseudomonas showed a higher relative abundance than in open-circuit MFCs, with relative abundances ranging from 3.37% to 9.54%. Additionally, in the anode of closed-circuit MFCs, Enterobacter showed a higher relative abundance than in open-circuit MFCs. Fig. 7 The composition and relative abundance of microbiomes. ( a ) Composition and abundance of microbiomes at phyla level (a, b and c represent the sludge, anode, cathode, respectively). ( b ) Composition and abundance of microbiomes at classification level (a, b and c represent the sludge, anode, cathode, respectively). In MFC-4, the removal efficiencies of COD, TP and phosphate are the highest, reaching 76.3 ± 2.8%, 80.3 ± 3.3%, and 85.3 ± 3.5%, respectively. It is clear that the addition of Pseudomonas aeruginosa and the device state of a closed-circuit are the best conditions for the degradation of wastewater. MFC-4 was injected with Pseudomonas aeruginosa , which, on the one hand, can promote the degradation of wastewater to produce electrons, and, on the other hand, can cause a stable cycle of power production as the bacterium has been shown to transfer electrons by contacting the electrodes directly or by secreting electronic intermediates 40 , 41 . As shown in Figs. S3 and S4 , the maximum output voltage (57.7 ± 4.4 mV) and power density (1.9 ± 0.1 mW/m 2 ) of MFC-4 are 15.3% and 90.2% higher than those of MFC-3, respectively. The internal resistance of MFC-4 (360 Ω) has decreased by 86.32% compared to MFC-3 (Fig. S5 ). This may be due to the addition of Pseudomonas aeruginosa improving the power generation performance of MFC. As is known, Pseudomonas aeruginosa is a type of electrogenic bacterium 42 – 44 that is present on the activated sludge, anode, and cathode of MFC-4 (Fig. 7 ). The relative abundance (9.54%) of Pseudomonas aeruginosa in MFC-4 was higher than that of the other MFCs. Arkatkar et al. 45 demonstrated the ability of Pseudomonas aeruginosa to increase the voltage of an MFC by inoculating anaerobic sludge with Pseudomonas aeruginosa to enhance the power production of the MFC. It is thus proven that the addition of specific enriched and domesticated bacterial strains is able to increase the power generation of MFCs. These added strains exhibit an ecological advantage within the microbial cell 46 , enabling them to adhere more densely to the surfaces of the cathode and anode electrodes (as shown in Fig. S6 ) as well as facilitating metabolic activity, thus enhancing the MFC’s ability to produce electricity. Therefore, with the addition of bacterial strains, which can effectively promote the growth of microbial communities. It is worth noting that the species abundance (Chao 1 and ACE) of MFC-3 is greater than that of MFC-4, which may be due to the fact that the natural microbial community has higher functional redundancy and ecological niche differentiation, as well as greater resilience and adaptability. The introduction of specific strains may disrupt the original ecological balance and lead to competitive disadvantages for certain microorganisms, thus reducing species abundance 47 . However, the microbial diversity (Shannon) and evenness (Shannoneven) of the sludge and anode in MFC-4 were higher than those in MFC-3, indicating that the addition of Pseudomonas aeruginosa increased the stability of the microbial community in MFC-4. Therefore, MFC-4 has higher electricity generation and wastewater degradation efficiency. As shown in Table 2 , although the output voltage and power density of MFC-4 were lower than those reported by Taşkan et al. 48 and Hu et al. 49 , the degradation efficiencies of COD, TP and PO₄ 3 ⁻-P in this study were relatively high. These results highlight the potential of using MFCs injected with specific bacteria for wastewater treatment, even under suboptimal conditions for power generation. These findings underscore the effectiveness of Pseudomonas aeruginosa in enhancing the degradation efficiency of the MFC. Table 2 The performance of different MFCs. Wastewater Voltage (mV) Power density (mW/m 2 ) C E Degradation efficiency References Cottonseed effluent 193 187 12.8% COD removal efficiency of 66.6% 48 Aquaculture wastewater 32.94 102.38 – COD, and TP removal efficiencies were 80.30 ± 3.4%, and 54.44 ± 4.5%, respectively 49 Municipal sludge and wastewater – 160 13% The percentage of total chemical oxygen demand (TCOD), TN and TP were reduced by 67% (4100 mg/L), 45% (30,280 mg/kg) and 52% (7620 mg/kg), respectively 50 Wastewater generated during the production of cytidine acid 57.7 ± 4.4 1.9 4.40 ± 0.16% COD, TP and PO 4 3− -P removal efficiencies of 76.3 ± 2.8%, 80.3 ± 3.3% and 85.3 ± 3.5%, respectively MFC-4 in this study To further contextualize these results, we compared them with previous studies. As shown in Table 2 , a notable limitation of this study is the relatively low C E of the MFC-4, which was only 4.40 ± 0.16%. This value is significantly lower than the C E of 12.8% and 13% achieved for cottonseed effluent and municipal sludge, respectively, as reported by Taşkan et al. 48 , 50 ). The low C E of the MFC constructed in this study can be attributed to several factors. Firstly, the air cathode may allow oxygen to infiltrate, disrupting the anaerobic environment and reducing the activity of electroproducing microorganisms, thereby lowering electroproduction efficiency. Secondly, electrons generated by anaerobic microorganisms during organic matter degradation are directly consumed by oxygen, decreasing the number of electrons transferred to the cathode 51 . Thirdly, oxygen oxidizes part of the organic matter that should have been oxidized by microorganisms, resulting in material loss and reduced efficiency 52 . Finally, the presence of non-electroproducing microorganisms (e.g., methanogens) in the MFC, which do not generate electrical energy during COD degradation, further contributing to the low C E and power density 53 . Despite this limitation, the MFC-4 demonstrated high removal efficiencies for COD, TP and PO₄ 3 ⁻-P, which are comparable to or exceed those reported in previous studies. Analysis of degradation mechanisms To further investigate the mechanism of wastewater degradation by closed-circuit MFC with Pseudomonas aeruginosa , the main differential metabolites before and after degradation were selected for analysis. As shown in Fig. 8 , the percentage of nicotinic acid increased in the sample, which is consistent with the metabolism of nicotinic acid and nicotinamide to generate products, indicating that nicotinic acid was produced in the course of the experiment. Nicotinic acid was obtained from upstream nicotinamide under the metabolism of nicotinic acid salt and nicotinamide; it promotes cellular metabolism, increases microbial activity, and allows microorganisms to attach more tightly to the carbon plate of the single-chamber MFC electrode, which promotes the degradation of cytidylic acid. Fig. 8 Degradation of wastewater by MFC-4 ( a ) volcano diagram, ( b ) heatmap. BJ: wastewater degraded by MFC-4, YS: raw wastewater. The analysis of the metabolic pathways (Fig. 9 ) allowed us to derive a mechanism of action for the addition of Pseudomonas aeruginosa to the single-chamber MFC for the treatment of wastewater generated during the production of cytidylic acid, particularly their capacity in the decomposition and transformation of organic matter, including the effect on hydroxyl-containing, carbonyl-containing, and phosphorus-containing compounds. These changes may reflect the ability of Pseudomonas aeruginosa to degrade, transform, or synthesize new compounds of specific organics in wastewater. For phosphorus in wastewater, the following metabolic actions occur primarily in the degradation of CMP, one of the phosphorus-containing pollutants. For example, in the pyrimidine metabolic pathway, CMP is converted to uridylic acid (UMP) by the action of cytidylic acid deaminase, and UMP is hydrolyzed to uridine (Urd) and inorganic phosphoric acid (Pi) by uridine diphosphatase and uridine monophosphatase; additionally, uridine’s phosphoric acid moiety is removed by uridine phosphorylase, producing uracil. The reaction during the microbial degradation of wastewater is thus demonstrated. Fig. 9 Metabolic pathway of pyrimidine metabolism, arginine and proline metabolism, Taurine and hypotaurine metabolism during degradation. The major metabolic pathways (Fig. 4 ) relevant in the treatment of wastewater generated during the production of cytidylic acid with Pseudomonas aeruginosa alone are not the same as the major metabolic pathways involved in the degradation of wastewater when Pseudomonas aeruginosa is added to a single-chamber MFC. When Pseudomonas aeruginosa was added to the complex microbial community of the MFC, the population structure of the original sludge colony in the MFC was optimized to a certain extent, thus indicating that the MFC degraded wastewater more efficiently than Pseudomonas aeruginosa alone. This study demonstrates a prospective strategy to combine specific microbial strains with MFC technology to promote the practical application of MFCs in the efficient degradation of wastewater generated during the production of cytidine acid. Through careful screening and cultivation of special strains of microorganisms, not only can they efficiently decompose complex organic pollutants, but they can also significantly enhance the electron transfer process within the MFC, effectively converting chemical energy into electrical energy, thus increasing the activity of the strains and improving the efficiency of wastewater degradation. This innovative approach not only optimizes the resource recovery process and reduces environmental pollution, but also provides a new sustainable and energy self-sufficient pathway for industrial wastewater treatment. In terms of environmental benefits, MFC technology effectively removes phosphorus from wastewater, mitigates eutrophication, and supports ecological restoration 54 . Additionally, it reduces energy consumption and greenhouse gas emissions associated with traditional wastewater treatment, contributing to green and sustainable development. Economically, MFC technology lowers treatment costs through energy recovery, reduces reliance on external resources, and fosters the growth of green technology industries. As a result, it offers lower long-term operating costs and potential economic returns 55 . The introduction of specific microorganisms can significantly improve the efficiency of MFC in wastewater treatment. Microorganisms are able to degrade organic pollutants while generating electrical energy for the dual purpose of treating wastewater and pollutants. In this way, the MFC not only reduces the energy consumption of the wastewater treatment process, but also has the ability to degrade the wastewater more efficiently. The operation of the MFC contributes fundamentally to the energization of wastewater, which is in line with the concept of a closed-loop economy 56 . The selective addition of microorganisms (such as Pseudomonas aeruginosa ) with high degradation capacity enables rapid and effective degradation of specific pollutants 57 . The addition of microorganisms that may have a wider range of metabolic pathways and be able to process a wider variety of organics increases the adaptability and capacity of the MFC for complex pollutants. The addition of microorganisms may optimize the microbial community structure in the sludge of the MFC and accelerate the degradation of wastewater by the MFC. However, a notable limitation of this study is the relatively low power density achieved by the MFC. While the system demonstrated effective wastewater treatment and electricity generation, the power density remains below the threshold required for practical applications. This limitation highlights the need for further advancements in MFC technology. Strategies such as optimizing electrode materials, increasing the surface area of electrodes, enhancing microbial electrochemical activity, and refining operational conditions could potentially address this issue. Future studies should prioritize these improvements to enhance the feasibility and scalability of MFC for real-world applications."
} | 8,590 |
38419664 | PMC10899405 | pmc | 3,119 | {
"abstract": "Time-To-First-Spike (TTFS) coding in Spiking Neural Networks (SNNs) offers significant advantages in terms of energy efficiency, closely mimicking the behavior of biological neurons. In this work, we delve into the role of skip connections, a widely used concept in Artificial Neural Networks (ANNs), within the domain of SNNs with TTFS coding. Our focus is on two distinct types of skip connection architectures: (1) addition-based skip connections, and (2) concatenation-based skip connections. We find that addition-based skip connections introduce an additional delay in terms of spike timing. On the other hand, concatenation-based skip connections circumvent this delay but produce time gaps between after-convolution and skip connection paths, thereby restricting the effective mixing of information from these two paths. To mitigate these issues, we propose a novel approach involving a learnable delay for skip connections in the concatenation-based skip connection architecture. This approach successfully bridges the time gap between the convolutional and skip branches, facilitating improved information mixing. We conduct experiments on public datasets including MNIST and Fashion-MNIST, illustrating the advantage of the skip connection in TTFS coding architectures. Additionally, we demonstrate the applicability of TTFS coding on beyond image recognition tasks and extend it to scientific machine-learning tasks, broadening the potential uses of SNNs.",
"conclusion": "5 Conclusion In conclusion, this study has made significant strides in the exploration of TTFS coding and the optimization of skip connection architectures for improving the efficiency and accuracy of SNNs. We discovered that while addition-based skip connections introduce temporal delays, concatenation-based skip connections tend to miss crucial information from the non-linear operation branch. To address these challenges, we proposed a novel approach that introduces a learnable delay for skip connections, bridging the gap between the spike timing discrepancies of the convolution and skip branches. We demonstrated that this method not only accelerates the first spike's timing but also maintains accuracy, offering an effective solution for faster prediction in TTFS coding. We also extended our exploration to SciML tasks, unveiling the potential of TTFS coding beyond image recognition applications. Our findings suggest that there is room for further research in optimizing the network architecture of temporal SNNs, and we hope that our work will inspire new approaches and applications in this exciting field. In the future, we aim to further improve the effectiveness of our proposed method and explore its applicability to even larger and more complex tasks. We believe that the continuing evolution of SNN architectures will significantly contribute to the advancement of low-power, efficient, and highly accurate artificial intelligence systems.",
"introduction": "1 Introduction The communication between spiking neurons in the brain, characterized by its binary, event-driven, and sparse nature, offers significant potential for creating flexible and energy-efficient artificial intelligence (AI) systems (Roy et al., 2019 ; Christensen et al., 2022 ). Spiking Neural Networks (SNNs), unlike traditional Artificial Neural Networks (ANNs), leverage binary spikes, thereby offering a unique dimension of time in their operation. Recent studies have shown promising results with SNNs, making them suitable for competitive and energy-efficient applications in neuromorphic hardware (Cao et al., 2015 ; Diehl and Cook, 2015 ; Roy et al., 2019 ; Comsa et al., 2020 ; Panda et al., 2020 ). A primary application of SNNs lies in image recognition (Roy et al., 2019 ; Christensen et al., 2022 ). In order to transform a static image into binary spike trains, a range of coding schemes have been introduced (Park et al., 2019 ; Comsa et al., 2020 ; Guo et al., 2021 ). Rate coding conveys information through the firing rate of spikes (Wu et al., 2019 ; Fang et al., 2020 ; Lee et al., 2020 ; Zhang and Li, 2020 ; Zheng et al., 2020 ). Phase coding, meanwhile, embeds temporal information in spike patterns utilizing a global oscillator (Montemurro et al., 2008 ). In contrast, burst coding transmits spike bursts within brief time periods, which boosts the reliability of synaptic communication between neurons (Park et al., 2019 ). While these coding schemes have proven successful in training SNNs, they generate a large number of spikes, which presents challenges when applied to ultra-low power devices. To leverage temporal spike information in ultra-low power environments, researchers have increasingly focused on Time-To-First-Spike (TTFS) coding (Rueckauer and Liu, 2018 ; Zhang et al., 2019 ). The core concept involves representing information through spike timing, with each neuron generating a single spike during the forward process. A line of work focuses on training temporal-coded SNNs with backpropagation (Bohte et al., 2000 ; Xu et al., 2013 ; Mostafa, 2017 ; Shrestha and Song, 2017 ; Comsa et al., 2020 ; Zhang et al., 2021 ), which highlights biological plausibility and efficiency of temporal coding. Much of the previous work has centered on developing improved synaptic models capable of effectively processing temporal information. For instance, Mostafa ( 2017 ) employed non-leaky integrate-and-fire neurons to compute locally exact gradients for backpropagation, while Comsa et al. ( 2020 ) introduced the alpha-synaptic function to enhance SNNs' accuracy. Recently, Zhang et al. ( 2021 ) proposed a ReLU-like spike dynamics that effectively mitigates the dead neuron issue caused by the leaky nature of spike functions. While advances in synaptic modeling have illuminated the understanding of neuronal dynamics, the exploration of network architecture in temporal SNNs has been relatively limited. In this paper, we explore architectural improvements of TTFS coding, focusing on the role of skip connections in neural networks. Skip connections are a widely employed technique in ANNs, facilitating training and enhancing performance by allowing information to bypass certain layers. We examine two types of skip connection architectures: (1) addition-based skip connections, as proposed in ResNet (He et al., 2016 ), and (2) concatenation-based skip connections utilized in the ShuffleNetV2 architecture (Ma et al., 2018 ). We find that, when implemented in temporal SNN architectures, addition-based skip connections can introduce extra delays in the time dimension. Conversely, concatenation-based skip connections substantially reduce inference latency, but yield limited performance improvements due to discrepancies between the distributions from the convolution and skip branches. To augment the performance of concatenation-based skip connections, we propose a learnable delay for skip connections, which diminishes the distribution gap between the skip and convolutional branches, allowing for more effective information mixing between the two distributions. In addition to our exploration of a new architecture for TTFS SNNs, we also investigate applications outside of image recognition, specifically in the realm of scientific machine-learning tasks. We venture into the domain of time-reversal wave localization problems, a significant challenge in physics and engineering. This problem aims to trace back a wave's source given the wave shape at a later time (Bardos and Fink, 2002 ; Givoli and Turkel, 2012 ; Kahana et al., 2022 ). Through these experiments, we aim to demonstrate the versatility and potential of SNNs in various complex tasks, significantly expanding their applicability beyond traditional domains. In summary, our contributions in this paper are three-fold. (1) First, we explore the network architecture of temporal SNNs, with a particular emphasis on skip connections, examining both addition-based residual connections and concatenation-based skip connections in the context of temporal SNNs. (2) Second, we propose a learnable delay for skip connections to improve the performance of concatenation-based skip connections by reducing the distribution gap between skip and convolutional branches, enabling more effective information mixing. (3) Lastly, we extend the application of Time-To-First-Spike (TTFS) coding beyond image recognition to the time-reversal problem for source localization using wave signal. These contributions not only advance our understanding of network architecture in temporal SNNs but also broaden the potential applications of TTFS coding in various domains."
} | 2,159 |
40060589 | PMC11888383 | pmc | 3,120 | {
"abstract": "Abstract \nTo understand the ecophysiology and the role of iron-oxidizing bacteria (FeOB) in various ecosystems, we need to identify marker genes of the iron oxidation pathway to track activity\n in situ \n. The Gallionellaceae\n Sideroxydans \nsp. CL21, an autotrophic iron-oxidizing bacteria isolated from a peatland, is unusual amongst FeOB isolates in its genomic potential to utilize organic compounds as energy sources. Therefore, it offers the unique opportunity to determine genes expressed under litho- versus organotrophic conditions. We demonstrated the growth of\n Sideroxydans \nsp. CL21 on organic substrates (lactate and pyruvate) and inorganic substrates (Fe(II), magnetite, thiosulfate, and S(0)). Thus, cells were capable of lithoautotrophic, organotrophic, and potentially organoheterotrophic growth. Surprisingly, when lactate-grown cells were given Fe(II), mid-log phase cells were unable to oxidize iron, while late-log phase cells oxidized iron. To elucidate iron oxidation pathways, we compared gene expression between mid-log (non-iron-oxidizing) and late-log (iron-oxidizing) lactate-grown cells. Genes for iron oxidases (\n cyc2, mtoA \n) were highly expressed at both time points, so did not correspond to iron oxidation capability, making them unsuitable marker genes of iron oxidation activity by themselves. However, genes encoding periplasmic and inner membrane cytochromes were significantly upregulated in cells capable of iron oxidation. These genes include\n mtoD \n,\n cymA/imoA \n, and a cluster of Fe(II)-responsive genes (\n ircABCD \n). These findings suggest Gallionellaceae regulate their iron oxidation pathways in multiple stages, with iron oxidase-encoding genes proactively expressed. Other genes encoding electron carriers are upregulated only when iron oxidation is needed, which makes these genes (i.e.\n ircABCD \n) good prospective indicators of iron oxidation ability.\n Importance FeOB are widespread in the environment and we suspect that they play key roles in nutrient and other elemental cycles. However, with no isotopic marker, we lack the ability to monitor FeOB activity, prompting us to search for genetic markers. Previous work suggests that expression of iron oxidase genes does not directly correspond to iron oxidation activity in Gallionellaceae and little was known about the other genes in the pathway. Here we study a unique FeOB isolate that possesses organotrophic capabilities and demonstrate its potential for mixotrophic growth on lactate and Fe(II). Its ability to oxidize iron is regulated, allowing us to discover potential iron oxidation pathway genes with expression that corresponds to iron oxidation activity. If these genes can be further validated as iron oxidation marker genes, they will enable us to delineate autotrophic and organoheterotrophic FeOB impacts on carbon cycling in wetlands and other natural and engineered environments."
} | 726 |
30154474 | PMC6113270 | pmc | 3,122 | {
"abstract": "Marine foundation species such as corals, seagrasses, salt marsh plants, and mangrove trees are increasingly found to engage in mutualistic interactions. Because mutualisms by their very nature generate a positive feedback between the species, subtle environmental impacts on one of the species involved may trigger mutualism breakdown, potentially leading to ecosystem regime shifts. Using an empirically parameterized model, we investigate a facultative mutualism between seagrass and lucinid bivalves with endosymbiotic sulfide-oxidizing gill bacteria in a tropical intertidal ecosystem. Model predictions for our system show that, by alleviating the build-up of toxic sulfide, this mutualism maintains an otherwise intrinsically unstable seagrass ecosystem. However, an increase in seagrass mortality above natural levels, due to e.g. desiccation stress, triggers mutualism breakdown. This pushes the system in collapse-and-recovery dynamics (‘slow-fast cycles’) characterized by long-term persistent states of bare and seagrass-dominated, with rapid transitions in between. Model results were consistent with remote sensing analyses that suggest feedback-mediated state shifts induced by desiccation. Overall, our combined theoretical and empirical results illustrate the potential of mutualistic feedbacks to stabilize ecosystems, but also reveal an important drawback as small environmental changes may trigger shifts. We therefore suggest that mutualisms should be considered for marine conservation and restoration of seagrass beds.",
"introduction": "Introduction Mutualisms form vital ecological interactions in a wide range of ecosystems including coral reefs, seagrass beds, peatlands and forests 1 – 5 . Indeed, more than 90% of all tropical forest plants depend on mutualistic pollinator and/or seed dispersal interactions for reproduction 6 , 7 , and about 80% of all land plants are involved in mutualistic mycorrhiza-root partnerships 8 . Mutualisms can be particularly pervasive in coral reefs, salt marshes, mangroves, seagrass beds and deep-sea hydrothermal vents where they may strongly depend on mutualistic interactions 2 , 9 – 15 . In these marine ecosystems habitat-structuring foundation species alter the environmental conditions thereby facilitating many other species. However, these foundation species are increasingly found to engage in mutualistic interactions which may enable them to persist an even on a broader range of conditions 14 , 16 – 19 . As a large part of the associated marine community typically depends on these foundation species, mutualisms involving foundation species do not only affect the species directly involved but may also have a major impact on ecosystem functioning and stability. Although mutualism can increase the environmental range limits of the species involved, e.g. by improving stress tolerance of species 1 , 20 , 21 , recent studies also suggest an important potentially unavoidable downside. Because mutualistic interactions by their very nature generate a positive feedback mechanism between the species involved 4 , 22 , 23 , disruption of this feedback may lead to loss of the foundation species in conditions where in depends on mutualism for survival, potentially triggering a sudden shift in the state of the whole ecosystem 24 – 26 . Minor environmental changes (e.g. increase in temperature or nutrients) may potentially cause mutualism breakdown 4 , 17 , 27 . For example, small climate change-related phenological shifts between plants and their pollinators can cause a mismatch between mutualistic partners 28 , and in coral reef mutualisms, subtle temperature increases have been suggested to cause ‘coral bleaching events’ 9 , 29 . Even though mutualism breakdown is likely to become more common in ecosystems in the face of global change, the role of mutualisms involving foundation species for ecosystem stability and the mechanistic understanding of their disruption remains unclear. Here, we explore how a previously documented facultative mutualism between seagrasses and lucinid bivalves with endosymbiotic sulfide-oxidizing gill bacteria affects the stability and dynamics of a tropical seagrass ecosystem. By trapping suspended particles from the water layer and stabilizing sediments, seagrasses facilitate their own growth as this improves water clarity 30 – 32 . As a consequence, however, seagrass beds can also create a negative feedback, because the accumulated organic matter in the sediment is decomposed anaerobically by sulfate-reducing bacteria that produce toxic sulfide as a metabolic end-product 2 , 33 . However, previous work revealed that seagrasses can create a positive feedback by engaging in a mutualistic interaction with lucinid bivalves and their sulfide-oxidizing, gill-inhabiting bacteria to reduce sulfide stress. In return, the bivalves and their endosymbionts not only profit from sulfide that is indirectly provided by seagrasses due to organic matter trapping, but also from oxygen released by seagrass roots 2 , 17 , 33 . Lucinid bivalves are found in high densities in the rhizosphere of seagrasses meadows, especially in the tropics where sulfide production is generally high 2 , 3 . In our study system, the tropical marine intertidal flats of Banc d’Arguin in Mauritania (West Africa), a sudden seagrass die-off event occurred in 2011 when low-tide drought stress triggered the failure of the facultative seagrass-lucinid mutualism 17 . Although our earlier work suggests that environmental stress trigger the breakdown of the mutualistic seagrass-lucinid feedback, it has not yet been investigated how the mutualism affects ecosystem stability and whether its breakdown can indeed generate the observed ecosystem dynamics. We constructed a differential equation model with empirically informed parameters to (1) investigate the importance of the mutualistic interaction for seagrass ecosystem stability, and (2) gain insight how environmental stress – low-tide desiccation stress in our case – affects ecosystem resilience. We started by analysing how our model system behaves with and without the facultative mutualistic feedback. Second, we investigated whether increases in environmental stress (e.g. drought) could lead to unstable dynamics and ecosystem collapse. Specifically, we analysed the stability of the model over a range of seagrass mortality settings, which we used as a proxy for low-tide desiccation stress. Finally, we used a potential analysis – a method for detecting feedback-mediated shifts – on both model simulation results and remote sensing satellite data seagrass (NDVI) to link our theoretical results to empirical observations.",
"discussion": "Discussion Mutualisms, due to their very nature, create a positive feedback between the species involved, and these feedbacks have been hypothesized to stabilize communities and ecosystems, especially if the mutualistic interaction involves a foundation species structuring the ecosystem 13 , 14 . In this study, we demonstrate how a mutualism-driven positive feedback buffers a negative feedback imposed by the foundation species upon itself, thereby stabilizing the ecosystem in a seagrass-dominated state. More specifically, simulations from our empirically calibrated model predict that in absence of the mutualism, anaerobic decomposition of organic matter accumulated by seagrass itself leads to damped oscillations due to excessive production of toxic sulfide. By contrast, in the presence of the seagrass-bivalve-bacteria mutualism, sulfide toxicity is alleviated because sulfide is consumed by the lucinid bivalve-bacteria consortium, thereby stabilizing the ecosystem under default conditions. Our model analyses, however, also reveals an important inherent risk of mutualism-dependency: if the mutualism is weakened or overwhelmed due to enhanced environmental stress – as simulated by enhanced natural seagrass mortality here – the sulfide-buffering capacity of the mutualistic feedback can be exceeded, resulting in ecosystem collapse. Potential analyses on simulation results from the model with mutualism identified a single stable attractor at high shoot densities at default parameter settings. Here, any produced sulfide is immediately removed by the seagrass-lucinid mutualism. However, when mortality was enhanced beyond a certain threshold, a second attractor at low shoot densities was identified. In addition, the analysis predicts that seagrass shoot density for the highest attractor (i.e. seagrass-dominated state) gradually decreases with increasing mortality. These findings were similar to results we obtained from the potential analyses on the field data. In periods with low desiccation stress i.e. 2007 and 2009 17 , only a single attractor a high NDVI was stable and gradually decreased within increasing elevation. During the 2011-drought, however, a second low-NDVI attractor was identified, suggesting a feedback-mediated shift towards the degraded state observed in 2013 17 . Such ecosystem dynamics following gradual environmental change or perturbations of strong positive feedbacks have been described for a wide range of ecosystems 24 , 25 . For example, shallow lakes under excessive nutrient loading switch from clear to a turbid state 35 and climate change-related shifts in plant-pollinator disruptions 28 , 36 ; the expelling of zooxanthelae by corals leading to ‘coral bleaching events’ 9 , 29 . In many ecosystems, strong positive feedbacks can cause alternative states (i.e. bistability), implying that through gradually changing environmental conditions or a perturbation, a critical threshold can be crossed, causing a shift to an alternative state. If conditions subsequently improve, they have to progress beyond the point of collapse, before recovery to the initial state can take place, a phenomenon called hysteresis. In seagrass meadows, such hysteresis can for instance occur at high water column ammonia loading, as ammonia toxicity can only be alleviated through joint uptake and detoxification of ammonia by ample seagrass meadows of high density 37 , 38 . In our study system, however, the mutualistic feedback does not appear to lead to alternative stable states dynamics, but instead causes the occurrence of so-called “slow-fast” cycles under drought conditions. The dynamics of our model are similar to what was advanced as a potential explanation for cyclic shifts in shallow lakes where accumulation of phosphorus creates a “time bomb-effect” due to slow internal eutrophication 26 . In our system, the mutualism initially buffers sulfide production, but excessive organic matter accumulation (the “time bomb”) by seagrass at higher background mortality ( m n ) causes sulfide production to gradually increase and eventually outpace and overwhelm sulfide consumption by the mutualism, causing an abrupt shift to a bare state. Following the shift, however, organic matter is slowly exported from the system again, by erosion (the seagrass does not retain it anymore), followed by a period where seagrass can re-establish once organic matter and sulfide production drop below a certain threshold. This effectively causes slow-fast dynamics characterized by states that are persistent for long times, either seagrass or bare, with fast shifts (collapse and recovery) in between 26 , 34 , 39 . Interestingly, our model predictions reveal that such slow-fast dynamics can create patterns (i.e. bimodality) that are similar or equal to the signature of alternative stable states in a potential analysis. So far, bimodality (multiple peaks in the frequency distribution) in potential analyses has mainly been attributed to the potential existence of multiple stable states 40 – 42 . Our results, however, suggest that caution is warranted when interpreting multimodality in potential analysis or bimodal frequency distributions, as multiple types of ecosystem dynamics, albeit all typically feedback-driven, may cause similar patterns in these analyses. As there are multiple examples of ecosystems with a potential for slow-fast dynamics 39 , 43 – 47 our finding stresses the need for sufficient mechanistic insights when interpreting proxies or indicators for feedback-driven dynamics e.g. van der Heide et al ., Weerman et al . 48 – 50 . Our previous work suggests that the ecosystem collapse in our system was not a simple result of external environmental forcing but that (1) it was mediated by internal feedbacks, and (2) breakdown of the mutualistic feedback was as an important contributor 17 . Yet, thus far it was unknown to what extent the mutualism controls ecosystem stability, and whether its disruption may indeed cause the observed collapse. Here, we show that the seagrass-lucinid mutualism can indeed be vital in mediating both seagrass productivity and ecosystem stability 2 , 17 . Yet, even though a meta-analysis indicates that lucinids are present in 87% of all seagrass meadows worldwide 2 , it is currently unknown how the strength and the relative importance of the mutualism depend on abiotic conditions. As anaerobic degradation and related sulfide production are strongly temperature dependent, it is possible that mutualism strength will also depend on temperature. This appears to be supported by the lower proportion of studies that found seagrass-lucinid associations in subtropical (90%) and temperate seagrass beds (56%) compared to tropical meadows (97%) 2 . In addition, species-specific sulphide tolerance and sediment conditions such as organic matter and iron content that affect sulfide production, likely also affect mutualism dependency and thus potentially overall ecosystem dynamics 33 . As current global climatic changes lead to increased average temperatures as well as an increase in the number of extreme events, it seems likely that stress events will become a more common phenomenon 51 . This is especially the case in the tropics where high temperatures in combination with strong winds can cause desiccation events, particularly during neap tides with prolonged low tide exposure 17 , 52 – 54 . Apart from temperature increase, however, there are also many other human impacts (e.g. eutrophication, siltation events) that threaten seagrass meadows and the mutualistic interactions that support it 55 . Many other coastal ecosystems with mutualism-dependent foundation species, such as coral reefs, sea- grass meadows, kelp forest, salt marshes, and mangroves, have also declined dramatically due to global change (e.g., global warming, eutrophication, and overfishing) over recent decades. Therefore, we suggest that a more mechanistic insight into these interactions and the resulting ecosystem dynamics is required and recommend that mutualisms involving foundation species should be considered as potential conservation and restoration targets."
} | 3,707 |
35073057 | null | s2 | 3,123 | {
"abstract": "The strategic redesign of microbial biosynthetic pathways is a compelling route to access molecules of diverse structure and function in a potentially environmentally sustainable fashion. The promise of this approach hinges on an improved understanding of acyl carrier proteins (ACPs), which serve as central hubs in biosynthetic pathways. These small, flexible proteins mediate the transport of molecular building blocks and intermediates to enzymatic partners that extend and tailor the growing natural products. Past combinatorial biosynthesis efforts have failed due to incompatible ACP-enzyme pairings. Herein, we report the design of chimeric ACPs with features of the actinorhodin polyketide synthase ACP (ACT) and of the "
} | 182 |
31527694 | PMC6746700 | pmc | 3,124 | {
"abstract": "Often wetting is considered from the perspective of a single surface of a rigid substrate and its topographical properties such as roughness or texture. However, many substrates, such as membranes and meshes, have two useful surfaces. Such flexible substrates also offer the potential to be formed into structures with either a double-sided surface (e.g. by joining the ends of a mesh as a tape) or a single-sided surface (e.g. by ends with a half-twist). When a substrate possesses holes, it is also possible to consider how the spaces in the substrate may be connected or disconnected. This combination of flexibility, holes and connectedness can therefore be used to introduce topological concepts, which are distinct from simple topography. Here, we present a method to create a Slippery Liquid-Infused Porous Surface (SLIPS) coating on flexible conformable doubled-sided meshes and for coating complex geometries. By considering the flexibility and connectedness of a mesh with the surface properties of SLIPS, we show it is possible to create double-sided SLIPS materials with high droplet mobility and droplet control on both faces. We also exemplify the importance of flexibility using a mesh-based SLIPS pipe capable of withstanding laminar and turbulent flows for 180 and 90 minutes, respectively. Finally, we discuss how ideas of topology introduced by the SLIPS mesh might be extended to create completely new types of SLIPS systems, such as Mobius strips and auxetic metamaterials.",
"conclusion": "Conclusion In this paper, we have presented mesh SLIPS as an exemplar of the concepts of flexible slippery double-sided membranes and to explore topological concepts for SLIPS. These meshes were fabricated through the application of a simple SLIPS coating method, onto the complex geometry of a mesh, which does not involve complex fabrication techniques and costly materials. This method uses a hydrophobic nanoparticle spray coating that can be applied to various surfaces and forms a hydrophobic/oleophilic porous structure, which can then be impregnated with a lubricating oil. On smooth surfaces this method can achieve sliding angles as low as 0.44 ± 0.10°. By applying the coating method to highly complex metallic meshes, which are flexible, conformable, and double-sided, mesh SLIPS were created, with low sliding angles of 1.2 ± 0.2°. When applied to a #250 stainless steel mesh, with a 1000 cSt silicone oil, the material was able to maintain a low sliding angle below 2° for up to 75 mins in turbulent flows and up to 180 mins in laminar flows. This work validates that a double-sided conformable SLIP surface has been achieved with evidenced robustness as shown through mesh-based pipes withstanding both laminar and turbulent flows for a significant amount of time. The ability to create flexible slippery double-sided surfaces, such as meshes, to create slippery coatings on complex surfaces, and to conceptualize topological ideas will open-up the field of research in the use of slippery surfaces. To illustrate future possibilities, we have discussed how SLIPS Mobius strips, SLIPS auxetic, and Origami and Kirigami approaches may be possible to create new types of materials with slippery surfaces. These methods and ideas will help research to move beyond the standard characterization of the properties of slippery surfaces and allow much greater access into the applications of slippery materials.",
"introduction": "Introduction Recent advances in liquid shedding materials have seen the development of Lubricant Impregnated Surfaces (LIS) 1 or equivalently Slippery Liquid-Infused Porous Surfaces (SLIPS) 2 inspired by the Nepenthes pitcher plant. These are, by definition, porous or textured surfaces into which a layer of lubricating liquid is imbibed and stabilized by capillary forces. Conceptually, these surfaces have many similarities to their conventional superhydrophobic counterparts. They both rely on a lubricating layer, whether that be air or a liquid, to reduce or remove the contact between the droplets and the underlying solid surface. The fundamental distinction of these surfaces is the possibility of using a highly wetting liquid lubricant, which remains completely wetting when immersed in, or contacted by, another immiscible liquid (typically water). On a superhydrophobic surface a lubricating air layer would be displaced, which is not the case with SLIPS 3 . The liquid lubricant layer thus eliminates the contact line pinning normally associated with sessile droplets on solid surfaces, leading to high drop mobility and remarkably low contact angle hysteresis 4 . In addition to superhydrophobicity and SLIPS, the only other materials method, of which we are aware, to eliminate contact line pinning is to use a Slippery, Omniphobic, Covalently Attached Liquid (SOCAL) surface 5 , 6 . The first demonstrated SLIPS came from Wong et al . in 2011. The surfaces comprised of electrospun Teflon mats, which were chemically modified and impregnated with fluorinated oil 2 . They also demonstrated SLIPS using a perfluorinated oil infused Teflon membrane, although they did not report on its flexibility or discuss the possibility of utilizing the two surfaces of the membrane. Others have also shown it is possible to create SLIPS using nanofiber mats 7 – 9 , lithographically made structures 1 , 4 , 10 – 13 , electrodeposition 14 , 15 , porous films 16 , 17 , roughened surfaces 18 – 20 , nanoparticles 21 – 23 , and colloid templating 24 . The focus has tended to be on creating the surface area with suitable wetting properties to stabilize the infusing liquid in the presence of the droplet and to obtain low droplet sliding angles. Moreover, these methods are often limited to simple geometries and flat planar surfaces. Current methods to create flexible SLIPS surfaces are not able to achieve water sliding angles less than 5.5° 17 . Furthermore, they are limited to single-sided substrates. Double-sided, flexible and conformable meshes would allow SLIPS technologies to access complex surface geometries whilst sustaining flow and water repellency. There are many materials, such as membranes and foils, which inherently have two surfaces of relevance. Interestingly, these surfaces can be topologically complex, such as with meshes that have disconnected holes laterally whilst providing connection for an infusing oil between the two surfaces. The concept of topology is quite different to that of topography, which is the dominant concept when using lithographic or etching techniques to create the texture needed for SLIP surfaces. The porosity of membranes can be thought of as an alternative method to create the increased surface area needed for an infusing oil to coat and be retained by a surface due to the surface energetics. However, when there are two surfaces and materials with holes and spaces, the concept of topology can become important and this is a global rather than local geometrical concept. For example, a doughnut and a sphere both have one surface, which appears on a local scale to be the same, but globally the doughnut has a hole which a sphere does not. The topological properties, such as holes and connectedness, are relevant to a SLIP surface because for it to self-heal an infusing liquid must flow between different spaces in the structure. In this work, we focus on a flexible double-sided mesh and these concepts are important as they relate to how the two surfaces are connected. In our meshes, the flexibility of the material can be used to create macroscopic shapes by rolling them into tubes for flow or folding them to conform to irregular shaped containers. Furthermore, a double-sided mesh can easily be twisted and folded to create highly complex macro structures. This gives the potential for combing the idea of SLIPS with the ideas of auxetic 25 , and Origami and Kirigama-based materials 26 – 29 . In the auxetic case, a material can have the counter-intuitive property of becoming wider when stretched (i.e. it possesses a negative Poisson’s ratio,ν) enabled by the structure of its lattice which means all expansion occurs via its holes. Another intriguing possibility is a double-sided membrane in the form of a tape into which a single twist of 180° of one end could be introduced prior to joining its ends to create a SLIPS Mobius strip 30 . The ability to create complex macro structures from double-sided SLIP meshes also allows for the study of fluids in larger scale scenarios such as internal and external fluid flows through or around objects and to investigate the potential applications of flexible porous materials with tailored surface properties 31 – 33 . In this paper, we illustrate one potential application of highly flexible and durable mesh SLIPS, by demonstrating SLIP mesh pipes, which are capable of withstanding turbulent flows for a significant duration of time. We introduce a method to create a SLIP surface for this purpose using a combination of surface texturing and chemical functionalization by spray coating a fractal-like porous network on the solid surface, which, when impregnated with silicone oil, forms mesh SLIPS. We first show that this method can minimize contact angle hysteresis on both flat and curved surfaces. We then show that the same method can be used to create double-sided mesh SLIPS which can be bent, twisted and folded, without loss of their lubricating properties. Moreover, this original method for the creation of double-sided SLIPS materials can be generally applied to any substrate, including meshes, foils and membranes, and then allows it to be infused with a lubricating oil, without the need for the substrate material to be hydrophobic. As a mesh is composed of interwoven wires, the holes between the wires allows the lubricating fluid to transfer between the faces of the material allowing the SLIPS materials to self-repair both faces. A SLIPS-based mesh is also an exemplification of a flexible substrate which can be formed into an unusual surface, such as a Mobius strip. Finally, we discuss the potential for combining SLIPS with the principles of auxetic, Origami and Kirigami-based meta-materials. These concepts have never previously been introduced in the literature in the context of SLIP surfaces.",
"discussion": "Results and Discussion An ideal SLIPS surface must satisfy three criteria. First, the lubricating liquid must fully imbibe into and wet the surface structure. Secondly, the chosen working fluid must not displace the lubricating liquid when introduced to the surface and, thirdly, the two liquids must be immiscible 1 . One way to produce a surface into which the lubricating fluid will fully imbibe is to produce an oleophilic rough coating. Many superhydrophobic coatings are also oleophilic due to the interaction of the rough surface with high and low surface tension liquids. Water has a relatively high surface tension, whereas oils tend to have a low surface tension. This often means that when a surface is rendered superhydrophobic, the tailored roughness enhances the oleophilicity of the surface 34 , 35 . The presented coating comprises of a superhydrophobic/superoleophilic micro-scale porous network of functionalized nanoparticles, which fulfils the first criteria for creating a SLIPS when impregnated with silicone oil. This is confirmed by the complete spreading and wetting of the surface by the lubricating silicone oil when applied to the coated surface. The use of silicone oil also satisfies the second condition, as silicone oil and water are immiscible. The first stage when creating the lubricant impregnated surface is to create the rough hydrophobic surface coating. Figure 1(a) shows the advancing and receding contact angles for glass substrates as a function of the coating thickness. After one application of the nanoparticulate coating, resulting in a coating thickness of 612 ± 112 nm (Figs 2 , 1(b,c) ), the surface becomes hydrophobic, as exemplified by the increase in advancing and receding contact angles, from 36.0 ± 2.5° to 147.5 ± 3.9° and from ~0° to 102.4 ± 7.4°, respectively. Despite the increase in contact angle, the surface coverage is heterogeneous, resulting in localised pinning sites, as seen in Fig. 1(b) . Figure 1 ( a ) The advancing and receding contact angles for substrates with increasing number of coatings. SEM top down images were also taken of 1 to 5 spray coatings, ( b , d , f , h , j ) respectively. SEM cross-section images were also taken for 1 to 5 spray coatings, ( c , e , g , I , k ), respectively. Figure 2 Sliding angles (X) for 2 µl deionized water droplets as a function of nanoparticle coating thickness on glass. By applying up to five layers of the nanoparticulate coating, complete coverage of the substrate, with a continuous microscopic porous network, is achieved. This layer forms a superhydrophobic surface with low hysteresis of ~6°, displaying advancing and receding contact angles of 166.7 ± 0.2° and 160.7 ± 1.0°, respectively. The average thickness of the layer is increased to 1703 ± 116 nm (Fig. 1(d–k) ). After dip coating in silicone oil the sliding angles were measured, with the results displayed in Fig. 2 . The sliding angles for all samples are below 1.5°. This satisfies the requirement for SLIP surfaces to have sliding angles less than 5°. Figure 3(a) illustrates how a droplet of water slides on the glass SLIP surface, inclined at 5° from horizontal. With increasing number of coatings from one to five, the sliding angle of the glass SLIP surfaces falls from 1.04 ± 0.20° to 0.44 ± 0.10°. Figure 3 Time sequence of ~2 µl distilled water droplets on ( a ) a flat glass SLIP surface with a tilt angle of 5° from horizontal, ( b ) a glass tube SLIP surface, and ( c ) on both sides of a stainless steel mesh SLIPS, whilst the tilting angle of the mesh was increased to 5° from horizontal. Due to the simplicity and versatility of this method to render surfaces SLIPS, it can be extended to treat other systems that rely on a low hysteresis surface, e.g. for systems that rely on capillary forces in the investigation and manipulation of droplet motion 4 , 36 , 37 . The application of the nanoparticle coating provides both a superhydrophobic and superoleophilic substrate. The superhydrophobicity repels water from the surface, whilst the porous superoleophilic surface layer stabilizes the lubricating silicone oil. The combination of the hydrophobic/oleophilic porous coating and the stabilized lubricating silicone oil means that the three criteria for producing a SLIPS are fulfilled, as the silicone oil fully imbibes into and wets the surface, water does not displace the stabilized silicone oil, and the silicone oil and water are immiscible. To demonstrate the simplicity and versatility of this SLIPS production method, SLIPS were fabricated on increasingly complex structures. Figure 3(b) shows a time sequence of a ~2 µl distilled water droplet on a SLIPS coated 10 mm diameter glass tube, displaying very low sliding angles. By applying the SLIPS coating to stainless steel meshes, it is possible to create slippery liquid infused materials, where both sides of the flexible material display low frictions properties (Fig. 3(c) and Supplementary Videos 1 and 2 ). The ability to coat flexible conformable meshes demonstrates the ability of the coating method to coat structures of increased complexity. A range of stainless steel meshes were coated and infused with silicone oil, from #120 to #500, to determine the droplet sliding properties for different sized meshes (Fig. 4 ). This mesh structure has square open voids between the wires, meaning the material is porous, so fluids and gas can easily pass through the unmodified material. When the SLIPS coating is applied to the meshes, the silicone oil both coats the wires and fills the voids between the wires. This was confirmed using low-vacuum SEM (Fig. 4(a,b) ). With both sides of the material rendered SLIPS, the voids in the material allow the silicone oil to flow between the two sides, thus providing a double-sided self-healing mechanism. Figure 4 SEM images of an ( a ) #250 uncoated stainless steel mesh and ( b ) #250 stainless steel mesh SLIPS. ( c ) Advancing (filled) and receding (unfilled) contact angles for uncoated (■,□) and nanoparticle-coated (▲,Δ) stainless steel meshes, including sliding angles (X) for mesh SLIPS. ( d ) Sliding angles for 2 µl water droplets over time for #250 mesh SLIPS in laminar (~1500 Re)(○) and turbulent (~4000 Re) (□) water flows. The contact angles for the nanoparticle-coated meshes are shown in Fig. 4(c) . All the meshes displayed uncoated advancing contact angles of between 125° to 137° and uncoated receding contact angles of 0°. After the application of the nanoparticle coating the advancing and receding angles are increased. All advancing angles for the nanoparticle coated meshes are above 159°, with all receding angles above 150°, apart from the #120 mesh which only has a receding angle of 135° ± 2°. The large wire diameter of 90 μm with a wire separation of 122 μm of the #120 mesh is likely to be the origin of its smaller receding angle. We therefore conclude, the nanoparticle-coating transforms the #150 to #500 meshes into superhydrophobic materials. After infusion with lubricating oil, the sliding angle for the 5 sized meshes was determined (Fig. 4(c) ). The sliding angle for the #250, #400 and #500 mesh SLIPS are less than 5°, for 2 µl water droplets, so fall within the requirements for SLIPS surfaces. The lowest sliding angle was 1.2 ± 0.2° and was recorded for the #500 mesh SLIPS, which was the smallest available to us which could also be obtained at sufficient scale for the flow experiments. The robustness of the slippery liquid infused materials was tested in a flow situation, where the #250 mesh SLIPS was subjected to a constant flow of water at Re = 8200 ± 500. Different samples were fabricated with 20 cSt and 1000 cSt silicone oil as the lubricating liquid. It was determined the 20 cSt mesh SLIPS could maintain a sliding angle of <5° for a maximum of 33 minutes before sufficient degradation was caused to the surface coating, rendering the material non-SLIPS. The 1000 cSt mesh SLIPS samples were comparably more robust, being able to maintain sliding angles less than 5° for up to 90 minutes. After subjecting the 1000 cSt mesh SLIPS to a laminar flow of Re = 1550 ± 50, the sliding angle of water droplets on the surface did not deviate from 0.5 ± 0.2°, for 10 µl water droplets, over the course of 180 minutes, as shown in Fig. 1(d) . However, in a turbulent flow of Re = 4000 ± 300, the sliding angle of water droplets remained low at 0.5 ± 0.2° for 45 mins before rising to 6.0 ± 0.5° at 90 minutes. This indicates that, when combined with the #250 mesh the SLIPS coating is able to withstand the shear stress generated by the laminar flow of water over the surface to a far greater extent than those generated by the turbulent flow of water. Finally, we return to the general concept of topology and the potential for creating novel surfaces and materials. Figure 3(c) with droplets in view on both the upper and lower surfaces illustrates the ability of a SLIPS mesh to provide a double-sided SLIP surface. Such a double-sided material in a tape form could have a single 180° twist inserted, using the flexibility of the material, and the ends joined to create a single-sided SLIPS mobius strip 30 . In such a case, a drop translated once around a circuit of the strip would move from the equivalent of the “top” in such a figure to the “bottom” but would in fact remain on the same single side of the Mobius strip. To further illustrate new materials possibilities, one can consider the design of the holes in a mesh. Axially stretching a connected set of holes each defined by a six-sided hexagonal honeycomb network causes the transverse dimension to shrink. Often there may be an implicit assumption that stretching a material causes it to thin. However, if the connected holes are in the shape of, e.g., a re-entrant honeycomb network based on bow-tie elements, an auxetic material 25 , 38 , with a negative Possion’s ratio, which increases its thickness when it is stretched, can be created. Since it is possible to create auxetic materials using three-dimensional structures these ideas are not limited to surfaces arising from meshes and membranes. Thus, extending the concept of flexibility, which has potential for SLIPS-based Origami materials, to stretchability of meshes or other materials with specifically designed holes, one can now imagine creating SLIPS-based auxetic metamaterials."
} | 5,166 |
27828965 | PMC5102394 | pmc | 3,127 | {
"abstract": "Coral reefs in the central Red Sea are sparsely studied and in situ data on physico-chemical and key biotic variables that provide an important comparative baseline are missing. To address this gap, we simultaneously monitored three reefs along a cross-shelf gradient for an entire year over four seasons, collecting data on currents, temperature, salinity, dissolved oxygen (DO), chlorophyll-a, turbidity, inorganic nutrients, sedimentation, bacterial communities of reef water, and bacterial and algal composition of epilithic biofilms. Summer temperature (29–33°C) and salinity (39 PSU) exceeded average global maxima for coral reefs, whereas DO concentration was low (2–4 mg L -1 ). While temperature and salinity differences were most pronounced between seasons, DO, chlorophyll-a, turbidity, and sedimentation varied most between reefs. Similarly, biotic communities were highly dynamic between reefs and seasons. Differences in bacterial biofilms were driven by four abundant families: Rhodobacteraceae, Flavobacteriaceae, Flammeovirgaceae, and Pseudanabaenaceae. In algal biofilms, green crusts, brown crusts, and crustose coralline algae were most abundant and accounted for most of the variability of the communities. Higher bacterial diversity of biofilms coincided with increased algal cover during spring and summer. By employing multivariate matching, we identified temperature, salinity, DO, and chlorophyll-a as the main contributing physico-chemical drivers of biotic community structures. These parameters are forecast to change most with the progression of ocean warming and increased nutrient input, which suggests an effect on the recruitment of Red Sea benthic communities as a result of climate change and anthropogenic influence. In conclusion, our study provides insight into coral reef functioning in the Red Sea and a comparative baseline to support coral reef studies in the region.",
"conclusion": "Conclusions The Red Sea is known as an oligotrophic, but sparsely studied region that maintains reefs of high coral cover at high temperature and salinity. Our analyses highlight spatio-temporal dynamics of physico-chemical and biotic variables in the central Red Sea. As such, our data provide a comparative foundation for future coral reef studies. In situ data show that temperature and dissolved oxygen concentrations on reefs in this region are similar to projected ‘future ocean’ conditions on reefs elsewhere. Therefore, reefs in the central Red Sea provide an opportunity to study coral reef functioning under environmental change.",
"introduction": "Introduction Shallow-water coral reefs are marine ecosystems of high biodiversity and high economic value [ 1 ]. They depend on symbiotic reef-building corals that critically rely on sunlight, and are limited to the warm and oligotrophic conditions of equatorial oceans. Coral reefs exist in regions where seasonality, upwelling, or internal waves drive the variability of critical physico-chemical variables such as temperature, salinity, dissolved oxygen, and nutrient supply [ 2 – 4 ]. Distances of reefs to the shore are often associated with differences in certain physico-chemical properties; e.g., gradients of nutrient concentrations, sedimentation, and turbidity are common across spatial scales [ 5 – 7 ]. Physical forces such as hydrodynamics can alter physico-chemical variables by driving fluxes, the residence time of sea water in reef systems, and the exchange of coastal reef water with the open sea [ 8 , 9 ]. As a consequence, physico-chemical variables of coral reef ecosystems can fluctuate from favorable to less favorable conditions on spatial scales of kilometers and on temporal scales of months with seasonality [ 10 , 11 ]. Coral reefs are considered to be among the most sensitive ecosystems in regard to changing environmental conditions [ 12 ]. Many studies have focused on how anomalies and changes of physico-chemical variables (such as above-average summer temperatures or increased coastal nutrient input) can drive shifts in the ecology and composition of coral reef benthic invertebrate assemblages and associated reef fish communities [ 13 – 17 ]. The fundamental role of bacterial communities in coral reefs is well recognized [ 18 – 20 ]. Many studies focus on the role of bacterial consortia associated with coral or sponge host organisms in symbiosis or disease [ 21 – 26 ]. However, less is known about the drivers and dynamics in microscopic assemblages of epilithic biofilms, such as epilithic bacterial communities (hereafter ‘bacterial biofilms’). These bacterial biofilms are ubiquitous on surfaces in coral reefs, contribute to productivity, biogeochemical cycles [ 27 ], and facilitate larval recruitment of key reef-organisms, such as reef-building corals [ 28 – 30 ]. Consequently, intact bacterial biofilms are important for maintaining coral reef functioning, but local anthropogenic stressors, such as terrestrial runoff [ 31 ] and eutrophication [ 32 ], and factors related to global climate change (e.g., rising temperature and declining pH) can induce changes in coral reef biofilm communities [ 33 – 35 ]. The algal component of biofilms (hereafter ‘algal biofilms’) is another crucial part of the coral reef benthos. Epilithic algal turfs and crusts comprise a great part of reef primary production and constitute an essential food source for grazing reef fish [ 36 , 37 ]. Epilithic algae provide substrate for bacterial growth with different algal exudates selecting for specific bacterial communities [ 38 , 39 ], which also impact coral recruitment. While algal turfs reduce the settlement of marine invertebrates and inhibit the survival of coral recruits [ 40 – 42 ], crusts of coralline algae promote and induce the settlement of coral larvae [ 43 ]. At a later succession stage certain algal taxa typically compete with corals for space [ 44 ]. Under unfavorable conditions (e.g., high nutrient concentrations or overfishing) this can result in a phase shift from a coral-dominated towards an algal-dominated reef community, entailing the degradation of reef habitat [ 45 ]. Similar to bacterial biofilms, algal biofilm communities are highly responsive to changes in the environment, e.g. to temperature variation or pollution [ 46 – 48 ]. Due to the geographic location of Red Sea, locked in between two arid landmasses, precipitation and riverine input are rare and temperature and salinity are high [ 49 , 50 ]. This creates a unique environmental setting for tropical coral reefs, but despite these challenging conditions coral reefs are abundant along the Red Sea coastlines. Reefs in the central Red Sea are exposed to physico-chemical changes driven by a seasonal cycle [ 49 ], as exemplified by the prominent variability of sea water temperatures [ 51 ]. These coral reefs commonly stretch over coastal platforms and form offshore reef structures and lagoonal inshore areas that give rise to spatial environmental gradients [ 52 – 54 ]. This setting offers the opportunity to explore spatio-temporal coral reef dynamics under unique conditions. As in other regions, coral reef studies in the Red Sea have typically targeted benthic assemblages, such as reef-building coral and fish communities [ 15 , 55 – 58 ]. Conversely, little is known about the composition and dynamics of microscopic biota such as bacterial and algal biofilms. However, first data on coral associated bacteria show variable microbiomes in response to natural environmental gradients [ 59 ] and anthropogenic stressors [ 60 – 63 ], indicating variability on the level of microscopic biota in Red Sea reefs. In recent years, consequences of global climate change have been reported to affect coral reefs in the Red Sea. For instance, the Red Sea is already experiencing measurable ocean warming [ 64 ], is susceptible to coral bleaching [ 15 ], and there are indications for a temperature-related decrease in coral growth [ 54 , 65 ]. However, most data on physico-chemical conditions are still based on remote sensing or occasional sampling events [ 65 – 68 ], rather than on continuous and more accurate in situ measurements. With increasing local and global anthropogenic stressors, comprehensive studies are needed that simultaneously record multiple physical, chemical, and biotic variables in situ to disentangle spatio-temporal dynamics and to provide a baseline against which impacts can be measured [ 69 – 71 ]. The lack of in situ baseline data was an important motivation for monitoring and collecting continuous physico-chemical and biotic data in this study. We use these data to characterize the natural baselines of central Red Sea reef environments. We then link physico-chemical and biotic parameters to extract putative physico-chemical drivers that contribute insights into coral reef functioning. As such we address the natural environmental variability of coral reefs in the central Red Sea to provide a foundation for coral reef studies, which will aim at better understanding coral reef functioning in unique environments and estimating the impact of global and local environmental pressures in this region.",
"discussion": "Discussion In this study we present a first account of physical, chemical, and biotic in situ data acquired simultaneously in coral reefs of the central Red Sea over the course of a full year. Our data revealed that the reefs in this region are exposed to a high degree of spatial (cross-shelf) and temporal (seasonal) variability. We uncovered connections between physico-chemical conditions and community structure of bacterial and algal biofilms, contributing valuable information on the potential major drivers of biotic coral reef processes in this naturally variable environment. Physico-chemical baseline data of coral reefs in the central Red Sea Our in situ physico-chemical data show that coral reefs in the central Red Sea are subjected to summer temperature and salinity that exceed coral reef global average maxima [ 50 ] and to relatively low DO [ 89 , 90 ]. Turbidity and sedimentation rates were far below values reported from coral reefs elsewhere, especially from those that are frequently studied (e.g. Great Barrier Reef (GBR)), whereas chlorophyll-a and nutrients were similar to measurements from other coral reef regions [ 10 , 91 ]. Further, our data reveal a high degree of spatio-temporal variability: seasonality was primarily reflected in temperature and salinity, whereas DO, chlorophyll-a, and sedimentation varied over the spatial scale. Currents Derived from ocean model simulations, currents on the eastern coast of the central Red Sea are influenced by strong seasonal or permanent gyres and by the eastern boundary current that carries water masses from the south [ 92 ]. However, around reef platforms bathymetry and atmospheric forcing may be the strongest determinants for current properties [ 9 , 72 ]. Accordingly, the main current direction (NW to SE) at our offshore site was likely driven by north-west winds [ 72 ], while the reversed direction (SE to NW) in the nearshore reef may be related to the eastern boundary current (travelling northward) [ 92 ]. The currents around our study site are likely to transport nutrients and influence heat budgets, as indicated by the significant correlations of currents with chlorophyll-a and temperature. The offshore site receives water masses from the Red Sea basin, whereas water exchange between the nearshore reef and the basin may be limited. Elevated salinity in the nearshore reef supports this assumption, as it is likely caused by the longer residency time of water, resulting in higher relative evaporation rates. Water exchange between coral reefs and the open sea can play an important role in mediating stress events, such as rising salinity or excessive summer warming [ 93 ]. Hence, nearshore reefs in the central Red Sea may be at higher risk of experiencing episodes of environmental stress compared to the more distant reefs. Higher prevalence of bleached corals in nearshore than in offshore reefs during a coral bleaching event in 2010 and 2015 is consistent with this assumption [ 15 , 94 ]. Temperature and salinity During summer we measured a highest seasonal mean temperature of 31.9°C and maxima of up to 33°C. The highest seasonal mean temperature exceeds the typical average maximum for coral reefs (29.5°C) [ 50 ] by 2.4°C and is already similar to conditions that are predicted for most other reefs worldwide by the end of this century [ 95 ]. Salinity at our study sites (38–39 PSU), while typical for the Red Sea [ 49 ], also exceeds global coral reef averages (34–35 PSU) [ 50 , 96 ]. Among all measured physico-chemical variables, temperature and salinity fluctuate most between seasons. For instance, the annual temperature range (9°C) is 2- to 4-fold higher than in most equatorial reefs (2–4°C in coral reefs in the Caribbean, Indo Pacific, and Pacific Ocean), and in a range with temperatures from more extreme regions that support coral habitats, such as the Sea of Oman (7°C) and the Persian/Arabian Gulf (12–20°C) [ 97 ]. Although salinity is high, its fluctuation is relatively low (range: 1.43 PSU) compared to tropical reefs that are influenced by riverine and precipitation input (e.g. salinity can vary by 5 to 10 PSU in a nearshore reef in the GBR [ 98 ]). In our study salinity might be driven by evaporation processes related to temperature, which could be concluded from the correlation of both variables, but also the possible influence of currents should be considered and deserves further investigation. The Red Sea is a semi-enclosed basin located between arid landmasses [ 49 ] that may be particularly affected by ocean warming, leading to even higher temperatures and salinity. Coral bleaching events are an indication that thermal limits of many coral species have already been reached [ 15 ]. The environmental data presented here will be an important contribution to quantify long-term effects of ocean warming in the central Red Sea. Dissolved oxygen (DO) DO concentrations in coral reefs are primarily driven by biological processes such as respiration and photosynthesis [ 89 ]. Lower DO in the nearshore reef suggests a predominance of heterotrophic organisms, such as sponges and other filter feeders, or heterotrophic bacteria, but also reduced water mixing close to shore. This study presents a DO range of ~1–6 mg L -1 which is derived from continuous data, including diurnal (elevated DO due to photosynthesis) and nocturnal values (lowered DO due to respiration). This is large in relation to the ranges from a majority of studies that only report on daytime measurements (6–9 mg L -1 , e.g. [ 99 , 100 ]), but similar to day and night values measured in a high-latitude coral reef of Japan that span a similarly remarkable range from 1.3–11.1 mg L -1 [ 89 ]. Within the Red Sea averaged DO concentrations decrease from the north (6–7 mg L -1 , offshore shallow waters [ 90 ]) to the central Red Sea (2.2–4.1 mg L -1 , this study). This reduction in DO is likely driven by higher temperatures in the central Red Sea that decrease oxygen solubility. Globally, DO concentrations are predicted to decrease and hypoxic environments to spread as a consequence of climate change [ 101 ]. Values of 2 mg L -1 DO and below have been characterized as hypoxic in the majority of studies, mostly for temperate regions [ 102 ]. As DO in the central Red Sea occasionally reaches such low concentrations, hypoxia may represent another challenge for Red Sea organisms in this region. However, given the lack of data and studies, it is not clear whether these low DO values are common in the central Red Sea or not. Chlorophyll-a and dissolved inorganic nutrients Chlorophyll-a concentration is frequently used as a proxy for primary production and nutrient availability in the water column [ 103 ]. Chlorophyll-a derived from remote sensing data shows that surface water concentrations in the Red Sea range from extreme oligotrophy (< 0.01 to 0.4 mg m -3 ) in the northern and northern-central Red Sea to chlorophyll-a concentrations exceeding typical coral reef conditions by an order of magnitude in the southern Red Sea (0.5–5.0 mg m -3 ) [ 104 ]. Accordingly, in the central Red Sea we found in situ chlorophyll-a and dissolved inorganic nutrients to be mostly in the range of values from other oligotrophic coral reef regions. Conditions at the nearshore and midshore reefs in our study area were similar to inshore reefs of the GBR (up to 0.7 μg L -1 over the full year; [ 10 ]), while concentrations in the offshore reef were lower (0.16 to 0.28 μg L -1 ) and in a range with more oligotrophic reef sites such as reef systems in Hawaii (up to 0.31 μg L -1 ) [ 105 ]. Low chlorophyll-a concentrations in our study area also reflect the limited availability of inorganic nutrients. Nitrogen species concentrations (nitrate & nitrite 0.16 μM; ammonia 0.17 μM) were comparably low (Hawaii, Phoenix islands, GBR, and Western Australia; 0.04–2.5 μM and 0.05–5.52 μM for nitrate & nitrite and ammonia, respectively [ 106 ]). Phosphate (0.07 μM) was among the lowest values reported for coral reefs (0.08–0.6 μM) [ 106 ]. Sedimentation and Turbidity Sedimentation rates and turbidity were very low in the study area and decreased from nearshore to offshore following a common pattern of land-based sedimentation [ 6 , 7 , 107 , 108 ]. Turbidity is a proxy for suspended particulates in the water column that, depending on their organic content, are filtered or ingested by heterotrophic biota serving as a source of nutrition [ 109 ]. Because suspended particles inhibit light penetration, which impacts photosynthesis or smothers benthic organisms, high sedimentation loads are commonly regarded as stressors to coral reefs [ 110 ]. Sedimentation rates in Caribbean and Pacific coral reef habitats are considered ‘natural’ at 1–10 mg cm -2 day -1 [ 91 ], while stressful conditions start at around 70 mg cm -2 day -1 [ 111 ]. Sedimentation rates in the central Red Sea reefs are far below these values. Seasonal rates ranged between 0.0057–0.0193 mg cm -2 day -1 , which is only ~ 2% of the lowest natural sedimentation rate recorded elsewhere [ 91 ]. Accordingly, seasonal averages of turbidity from the central Red Sea (0.20–0.63 NTU) are well below those from some sites in the GBR (0.6–7.0 NTU) [ 10 ]. Similar to chlorophyll-a, OC of sediments and turbidity showed no significant seasonal pattern that would indicate a period of higher productivity in the water column. However, the typical decrease of sedimentation rates from nearshore to offshore was reversed in spring. This may be related to the Indian Ocean monsoon, which causes dust storms and/or increases mixing in the water column during spring and fall [ 112 ]. Further monitoring is required to confirm if this pattern is reoccurring every year. All C:N ratios of sediments were above the Redfield ratio (6.6) [ 113 ], which confirms that primary production in the central Red Sea is nitrogen limited [ 114 ]. This is also evident from low concentrations of nitrogen species in the study area. C:N ratios of particulates were even higher during summer compared to other seasons, indicating aggravated nitrogen limitation in this period [ 115 ]. Biotic baseline data of coral reefs in the central Red Sea: reef water bacteria and bacterial and algal biofilms We present a first account of basic biotic variables of coral reefs in the central Red Sea, including reef water bacteria, bacterial biofilms, and algal biofilms. The catalogue of bacterial taxa ( S2 Table ) and algal groups represents a first assessment of microscopic communities in naturally variable reef environments of the central Red Sea. Coral reef bacterial biofilms had a far higher species richness and diversity compared to Red Sea coral reef water or coral microbiomes [ 21 , 59 , 60 , 62 ]. Bacterial and algal biofilms were variable (29% of bacterial and 99% of algal communities significantly varied in abundance between reefs and seasons), and an increase in bacterial diversity during spring and summer coincided with significantly increased algal growth, supporting the notion of interaction between algal and bacterial communities via exudates [ 38 , 39 ]. Furthermore, significant variability between the warm and cool season provides insight into potential community changes associated with ocean warming. In the following the findings are discussed in detail. Composition and dynamics of reef water bacteria Reef water bacterial communities at our study sites were similar to those reported from other oceans [ 116 , 117 ]. Communities were dominated by the cyanobacterial family Synechococcaceae, which is characteristic for open sea surface water across the Red Sea [ 67 , 118 ]. Synechococcaceae are particularly adapted to oligotrophic environments and are a major primary producer in oligotrophic waters [ 119 ]. Similarly, Pelagibacteracaea, another abundant group in our samples, are associated with oligotrophic conditions [ 120 ]. Reef water bacterial community structure differed between seasons, but remained stable across reefs. This lack of spatial differences but strong seasonality may indicate minor land-based influences in our study area, given that reef water bacterial communities in areas of pollution are shown to change along spatial gradients and lack seasonal differences [ 121 ]. Composition and dynamics of bacterial biofilms Epilithic bacterial biofilms in coral reefs have been characterized using molecular tools on spatial and temporal scales in Sulawesi, Indonesia [ 32 ] and in the GBR [ 28 , 31 , 35 , 122 ]. These studies focused on CCA associated bacteria or epilithic biofilm communities along a gradient of eutrophication or terrestrial runoff. To date, little is known about bacterial biofilm and reef water community structure and their responses to natural environmental fluctuations in little impacted environments. We show that in the central Red Sea five bacterial phyla dominate biofilms over all reef sites and seasons. Of these, Proteobacteria, Bacteroidetes, and Cyanobacteria were previously described from coral reef biofilms in the GBR, and Verrucomicrobia were previously found in coral reef sediments [ 31 , 123 ] and in marine biofilms from temperate and polar regions [ 124 , 125 ]. The last bacterial phylum, Planctomycetes, was identified in estuarine biofilms [ 126 ] and on the surface of red algae [ 127 ]. On the family level, Rhodobacteraceae (Proteobacteria) and Flavobacteriaceae (Bacteroidetes) were most prevalent in Red Sea biofilms. Both families were found in coral reef biofilms before [ 28 , 35 , 128 ] and were associated with community shifts along a water quality gradient [ 31 ]. Rhodobacteraceae are known as rapid surface colonizers and are considered to be involved in the formation of marine biofilms [ 129 ]. They play diverse roles in benthic community structuring, with a few species enhancing coral recruitment [ 128 ], but other species being reported as pathogenic opportunists in coral disease [ 130 – 132 ]. Bacterial biofilm diversity in this study was at least 10-fold higher than bacterial diversity in reef water, and also in relation to reef water and coral microbiomes reported in other Red Sea studies [ 21 , 60 , 62 ]. Implications of this high bacterial diversity are still unknown and warrant further study of bacterial biofilms. Similar to findings for reef water bacterial communities, studies showed that seasonality of biofilm communities was minor or not detectable along nutrient or pollution gradients in coral reef systems, while the spatial gradient was strong [ 31 , 32 ]. This is in contrast to bacterial biofilms in our study area that displayed high seasonality and low spatial dynamics. The prominent seasonal response may be interpreted as a natural pattern in a putatively less impacted reef area. This is corroborated by the observation that all differentially abundant OTUs were previously encountered in marine environments (see S4 Table ) without any apparent link to anthropogenic sources [ 61 ]. Lastly, this study identified several bacterial OTUs that were significantly increased or decreased in the warmer seasons. These OTUs may be temperature sensitive and can presumably indicate community shifts caused by temperature changes. Composition and dynamics of algal biofilms Our biofilm data includes algal assemblages following a three months succession from a cross-shelf gradient over four seasons. Composition of algal biofilms plays an essential role in coral and other invertebrates settlement and the survival of recruits [ 40 , 43 ]. Brown or green algal crusts or turfs, which contributed up to 70% to algal communities in this study, are typically negatively associated with coral larval recruitment [ 133 ]. Some CCA have a beneficial effect on coral recruitment and survival [ 133 ], but these algae were less abundant in this study. CCA commonly dominate offshore environments, but in our data offshore and midshore environments showed similar amounts of CCA [ 134 , 135 ]. Our data represent algal settlement patterns on smooth and light exposed surfaces, where brown and green algae may have an advantage over CCA, which proliferate in low light environments [ 86 , 136 ]. Other algal groups such as red algae and red crusts were almost absent from the exposed settlement tiles, presumably because they also favor sheltered environments [ 86 ]. In our study, algal community composition significantly differed between reefs and seasons, confirming that algal communities and their biomass are highly dynamic [ 48 , 134 , 137 ]. Algal cover and bacterial diversity were highest during spring and summer coinciding with the timing of coral reproduction. This overlap with the coral spawning season in the central Red Sea (April to June) [ 138 ] indicates that algal community patterns may potentially influence the settlement behavior and success of coral larvae. Physico-chemical drivers of biotic communities in the central Red Sea Increasing the understanding of environmental variability in coral reefs is essential to predicting ecosystem response to environmental change [ 12 , 139 ]. While addressing single physico-chemical variables in isolation may provide some insight, the analysis of cumulative effects from multiple variables is of relevance to gain a more complete understanding of complex ecological systems [ 140 ]. Our study provided an opportunity to match the simultaneously collected physico-chemical and biotic data and to explore interactions between physico-chemical conditions and the biotic realm in situ . Although nutrient enrichment or pollution related factors were shown to be the only drivers of bacterial communities in coral reefs elsewhere [ 31 , 32 , 121 , 141 ], our results suggest that in less disturbed environmental settings, bacterial biofilms are influenced by a combination of temperature, salinity, DO, but also chlorophyll-a. Ex situ experiments confirmed a temperature induced regulation of bacterial biofilm composition and physiology [ 33 , 35 , 142 ]. Also, changes in salinity and DO were shown to influence biofilm and water column bacteria in estuaries [ 143 – 145 ]. The spatio-temporal structuring of algal biofilm communities at our sites were best explained by salinity, chlorophyll-a, and current speed. We expected chlorophyll-a to be associated with differences in algal composition, given that irradiance together with nutrient availability (both variables that are related to chlorophyll-a) are considered the most important requirements for algal growth [ 137 , 146 ]. Salinity has been shown to affect physiology, growth, and community shifts in marine algae, especially in estuaries, where salinity differences are high [ 147 – 149 ] However, salinity has been rarely considered as a variable controlling algal settlement and growth in coral reefs [ 48 , 134 , 146 ]. Our data indicate that in the high salinity of the central Red Sea already small differences can influence algal biofilm assemblages. It is important to note though, that our results represent the best match of the variables investigated. For algal biofilm settlement and succession, grazing is usually another highly influential driver [ 48 , 150 ], and herbivory may therefore have had a contribution in our study area as well. Conclusions The Red Sea is known as an oligotrophic, but sparsely studied region that maintains reefs of high coral cover at high temperature and salinity. Our analyses highlight spatio-temporal dynamics of physico-chemical and biotic variables in the central Red Sea. As such, our data provide a comparative foundation for future coral reef studies. In situ data show that temperature and dissolved oxygen concentrations on reefs in this region are similar to projected ‘future ocean’ conditions on reefs elsewhere. Therefore, reefs in the central Red Sea provide an opportunity to study coral reef functioning under environmental change."
} | 7,269 |
27540372 | PMC4972832 | pmc | 3,128 | {
"abstract": "Quorum sensing (QS) is a cell density-dependent mechanism which enables a population of bacteria to coordinate cooperative behaviors in response to the accumulation of self-produced autoinducer signals in their local environment. An emerging framework is that the adaptive significance of QS in the regulation of production of costly extracellular metabolites (“public goods”) is to maintain the homeostasis of cooperation. We investigated this model using the phytopathogenic bacterium Burkholderia glumae , which we have previously demonstrated uses QS to regulate the production of rhamnolipids, extracellular surface-active glycolipids promoting the social behavior called “swarming motility.” Using mass spectrometric quantification and chromosomal lux -based gene expression, we made the unexpected finding that when unrestricted nutrient resources are provided, production of rhamnolipids is carried out completely independently of QS regulation. This is a unique observation among known QS-controlled factors in bacteria. On the other hand, under nutrient-limited conditions, QS then becomes the main regulating mechanism, significantly enhancing the specific rhamnolipids yield. Accordingly, decreasing nutrient concentrations amplifies rhamnolipid biosynthesis gene expression, revealing a system where QS-dependent regulation is specifically triggered by the growth rate of the population, rather than by its cell density. Furthermore, a gradual increase in QS signal specific concentration upon decrease of specific growth rate suggests a reduction in quorum threshold, which reflects an increase in cellular demand for production of QS-dependent target gene product at low density populations. Integration of growth rate with QS as a decision-making mechanism for biosynthesis of costly metabolites, such as rhamnolipids, could serve to assess the demand and timing for expanding the carrying capacity of a population through spatial expansion mechanisms, such as swarming motility, thus promoting the chances of survival, even if the cell density might not be high enough for an otherwise efficient production of rhamnolipids. In conclusion, we propose that the adaptive significance of growth rate-dependent functionality of QS in biosynthesis of costly public goods lies within providing a regulatory mechanism for selecting the optimal trade-off between survival and efficiency.",
"conclusion": "Conclusion We propose that the adaptive significance of growth rate-dependent functionality of QS in rhamnolipids biosynthesis lies within providing a regulatory mechanism for selecting the optimal trade-off between survival and efficiency.",
"introduction": "Introduction Quorum sensing (QS) is a cell density-dependent mechanism which enables a population of bacteria to synchronize the expression of behaviors in response to the accumulation of self-produced autoinducer signals in their local environment ( Fuqua et al., 1994 ). Such auto-induction regulatory systems are implicated in regulation of various cooperative phenotypes ranging from bioluminescence, virulence and nutrient acquisition to multicellular swarming motility and biofilm development ( Bainton et al., 1992 ; Passador et al., 1993 ; Stevens and Greenberg, 1997 ; Davies et al., 1998 ; Daniels et al., 2004 ; An et al., 2014 ). These behaviors are considered cooperative because they mostly involve the production of costly extracellular metabolites (“public goods”) which, once produced, are available to all members of the community to share their benefits ( Platt and Bever, 2009 ). Examples among bacteria are widespread and include production of siderophores, exoenzymes, or surfactants ( West et al., 2006 ). While cooperative production of public goods enhances the fitness of the whole population, at the individual level it is prone to exploitation by non-cooperative individual cells (“cheaters”) that, by not producing the metabolite or QS signal, gain a competitive edge over cooperative cells and hence threaten the homeostasis of the cooperation ( Diggle et al., 2007 ; Sandoz et al., 2007 ); this brings up questions about the evolutionary stability of cooperation. In recent years, the adaptive functionality of QS in regulation of public goods has constituted the main subject of several studies, and has been reviewed extensively ( Schuster et al., 2013 ; Hense and Schuster, 2015 ). The central question relates to the benefits provided by QS in the production of public goods, and thus its role in the evolution and stability of cooperative behaviors ( Schuster et al., 2013 ). In this regard, few studies addressing the social function of QS in regulation of public goods have demonstrated that QS can offer density-dependent fitness benefits ( Darch et al., 2012 ; Goo et al., 2012 ; Pai et al., 2012 ). QS is used to coordinate the triggering of social behaviors at high cell densities when the benefits of the extracellular secretions are relatively higher and will provide the greatest advantage to the community ( Darch et al., 2012 ). Moreover, the social function of QS in regulation of public goods is not only limited to providing fitness benefits at higher cell densities, as it can also serve as a means to anticipate stationary phase or foresee the optimum cell density of a population ( Goo et al., 2012 ). Furthermore, QS can impose metabolic constraints on social cheating and protect the population from a ‘tragedy of the commons’ by simultaneously controlling the expression of private goods ( Dandekar et al., 2012 ). Another possible solution to stabilizing cooperation is ‘policing,’ where cooperators actively penalize social cheats to hinder their success ( Wang et al., 2015 ). While these studies offer insights on the role of QS in the evolution and stability of cooperative behaviors, the adaptive significance of QS has remained debatable. In fact, it was suggested that it is only through studying each specific auto-induction system in its evolutionary and ecological context that we can figure out its adaptive significance ( Platt and Fuqua, 2010 ). The general framework is that, while conditions specific to each ecological context, such as population cell density and spatial diffusion properties, determine whether triggering of the costly QS-regulated cooperative behaviors is beneficial to the population, the integration of QS circuitry with other global regulatory pathways such as stress responses, specific environmental and physiological cues ensures an optimized demand-driven supply of target cooperative behaviors ( Hense and Schuster, 2015 ). Indeed, integration of metabolic information into decision-making processes governing production of public goods, called ‘metabolic prudence,’ can stabilize cooperative behaviors and reduce the cost of cooperation for the individual cell ( Xavier et al., 2011 ; Boyle et al., 2015 ). Thus, the emerging model is that, in order for QS to properly regulate costly bacterial cooperative behaviors (when benefits outweigh costs of production), it must be integrated with additional physiological cues ( Hense and Schuster, 2015 ). Here, we demonstrate that QS-dependent regulation of a public good in the Gram-negative bacterium Burkholderia glumae , a pathogen of rice, is dependent on growth rate, a direct measure of the carrying capacity of a population through prevailing environmental conditions. B. glumae uses the LuxI/LuxR-type QS system TofR/TofI to regulate protein secretion, oxalate production and expression of various virulence determinants such as toxoflavin, lipase, KatG and flagella ( Kim et al., 2007 ; Chun et al., 2009 ; Goo et al., 2010 , 2012 ). The TofR QS transcriptional regulator is activated by its cognate N -octanoyl homoserine lactone (C 8 -HSL) autoinducer, the product of the TofI N -acyl-HSL synthase, to control the expression of target genes ( Kim et al., 2004 ). Similarly, to what is seen in Pseudomonas aeruginosa ( Ochsner and Reiser, 1995 ; Köhler et al., 2000 ), we have previously demonstrated that in B. glumae as well, QS positively regulates the expression of the rhlA gene, encoding the enzyme catalyzing the first step in biosynthesis of rhamnolipids. These extracellular surface-active glycolipids promote the social surface behavior called swarming motility ( Nickzad et al., 2015 ). Now, we show that, in contrast to P. aeruginosa , this QS regulation is dispensable in B. glumae , as rhamnolipid production is unaffected in a QS-negative mutant under unrestricted, rich nutritional conditions. This unexpected observation led us to investigate the interplay between QS and nutrition-based regulation of rhamnolipids in B. glumae . We found that growth rate, and not cell density itself, is the key factor triggering the QS-dependent regulation of rhamnolipid biosynthesis. Since rhamnolipids act as public goods promoting social swarming motility, integration of growth rate with QS-dependent regulation of rhamnolipids in B. glumae supports the concept that the adaptive significance of QS lies in providing a regulatory mechanism for trade-off between survival and efficiency.",
"discussion": "Discussion We present conclusive evidence for a functional role of QS in providing an optimized demand-driven supply of target cooperative behavior, wherein QS-dependent regulation of rhamnolipids is tightly coupled to specific growth rate. Our results support the proposed model that the adaptive functionality of QS in regulation of public goods is to maintain the homeostasis of cooperation where the production of costly public goods is conditioned by assessment of demand and efficiency ( Hense and Schuster, 2015 ). We have previously demonstrated that in the rice pathogen B. glumae , QS positively regulates the biosynthesis of rhamnolipids, extracellular surface-active glycolipids which are necessary for promoting the social surface behavior called swarming motility ( Nickzad et al., 2015 ). Here, we found that a signal-negative mutant that does not produce C 8 -HSL maintains the ability to produce rhamnolipids in a rich NB medium, in contrast with growth in a minimal medium where rhamnolipid production is absent ( Figure 1 ). This led us to hypothesize that QS-dependent regulation of rhamnolipids in B. glumae is nutritionally conditional. Comparison of the yield of rhamnolipids per biomass in the wild-type and tofI – mutant strains in a decreasing gradient of nutrients revealed that the more we dilute the growth medium the more QS regulation contributes to the production of rhamnolipids ( Figure 2 ). We increasingly realize that the QS circuitry in various bacteria is highly integrated with other global regulatory pathways, stress responses and specific environmental and physiological cues ( Williams and Camara, 2009 ; Mellbye and Schuster, 2011 ). Although, up-regulation or down-regulation of QS-controlled factors such as rhamnolipids biosynthesis genes rhlAB in P. aeruginosa by elements other than cell-to-cell communications such as nutritional status is well-known ( Guerra-Santos et al., 1986 ; Déziel et al., 2003 ), this modulation always necessitates the presence of a functional QS system. The identification of a QS-dispensable regulation of rhamnolipids in B. glumae adds these metabolites to the list of B. glumae factors whose dependence on QS is conditional ( Kim et al., 2007 ; Chen et al., 2012 ; Jang et al., 2014 ; Kato et al., 2014 ). The dispensability of QS-regulated virulence factors and other costly metabolites, such as rhamnolipids, upon prevailing conditions and environmental cues provides insights into how these regulatory pathways have evolved to optimize the functionality of target genes they regulate. For instance, in the case of rhamnolipids biosynthesis in B. glumae , we found that once unrestricted nutrient resources are available, production of rhamnolipids is carried out independently of QS regulation, obviously through still-unidentified regulatory mechanisms. However, under nutrient-limited conditions with excess carbon source, QS becomes the main regulating mechanism significantly enhancing the specific rhamnolipids yield. Under nutrient-limited conditions, which B. glumae presumably meets in its natural habitat such as plant tissue environment, it might be more cost-effective for rhamnolipids biosynthesis to be carried out via a decision-making mechanism such as QS which places more restrictive controls over nutrient utilization. Notably, QS in B. glumae directly controls nutrient acquisition of individual cells in crowded populations ( An et al., 2014 ). Since growth rate is a direct function of nutrient availability, we hypothesized that growth rate is the key triggering factor that induces QS-dependent regulation of rhamnolipids. Our results indicate there is a growth rate threshold below which QS engages in the regulation of rhamnolipids ( Figure 3 ). In P. aeruginosa , slow growth is one key condition inducing regulation of QS-controlled public good genes in a metabolic prudent manner ( Mellbye and Schuster, 2014 ). For instance, prudent regulation of rhamnolipid production ensures that cells only invest carbon into rhamnolipids biosynthesis when growth is limited by another growth-limiting nutrient, such as nitrogen ( Xavier et al., 2011 ). In fact, presence of excess carbon in different dilutions of NB medium in our experiments, also suggest that in B. glumae , QS-dependent regulation of rhamnolipids is coupled to growth rate in a metabolic prudent manner. Furthermore, a gradual increase in QS signal specific concentration upon decrease of specific growth rate suggests a reduction in activation signal threshold, which reflects an increase in cellular demand for production of QS-dependent target gene product at such low density populations. Importantly, our gene expression analyses demonstrate the direct influence of the specific growth rate on QS-dependent induction of rhlA expression in the wild-type background, in agreement with a previous report showing that rhlAB expression in P. aeruginosa in the presence of excess carbon is tightly coupled to the growth rate, and not just cell density ( Xavier et al., 2011 ). Therefore, the role of QS in regulation of public goods is not limited to stationary phase situations at higher cell densities where production is more efficient, but also upon encountering restrictive environmental conditions, an early induction of QS by slowed growth rate could provide some inclusive fitness benefits for the survival of an individual cell and could act as a trade-off mechanism between survival and efficiency. Our results are also in accordance with the regulation of QS gene expression by starvation in P. aeruginosa in which stringent response can lower the quorum threshold via triggering an increased signal synthesis ( van Delden et al., 2001 ; Schuster et al., 2013 ). From an ecological significance perspective, induction of QS-dependent regulation of rhamnolipids at low specific growth rates could reflect two distinct scenarios for which such integrated regulation has evolved: (i) restricted nutritional conditions with low cell density (free living bacteria exposed to nutritional stress during establishment of host infection), and (ii) exhausted nutritional environment with a high cell density (bacteria living in biofilms). In both instances, since population growth is limited by the carrying capacity of the direct environment, it is conceivable that slow growth can serve as a predictive factor of the population carrying capacity ( de Vargas Roditi et al., 2013 ). Accordingly, in B. glumae , QS is used for anticipation of a population reaching the carrying capacity of an habitat to avoid lethal ammonia-induced alkalization by activating oxalate production, and thus promoting survival in the stationary phase ( Goo et al., 2012 ). An effective colonization of surface niches necessitates a balance between biofilm and motility ( van Ditmarsch et al., 2013 ). In this regard, there is an inverse regulation of biofilm formation and swarming motility ( Caiazza et al., 2007 ). Since production of surfactants is as crucial for biofilm development as for swarming motility ( Nickzad and Déziel, 2014 ), it seems that the induction of QS-dependent rhamnolipids biosynthesis upon reduced growth rate is a key evolved strategy to modulate swarming motility and promote dissemination of bacterial cells to find new surface niches to colonize ( Déziel et al., 2003 ; Tremblay and Déziel, 2010 ). Thus, integration of slowed growth rate with QS as a decision-making mechanism for biosynthesis of costly rhamnolipids could serve to assess the demand and timing for expanding the carrying capacity of a population through spatial expansion mechanisms such as swarming motility, thus promoting the chances of survival."
} | 4,214 |
38543610 | PMC10975764 | pmc | 3,129 | {
"abstract": "Plant health is necessary for food security, which is a key determinant of secure and sustainable food production systems. Deficiency of soil nutrients and invasion of plant pathogens or insects are the main destroyers of the world’s food production. Synthetic fertilizers and chemical-based pesticides are frequently employed to combat the problems. However, these have negative impacts on microbial ecosystems and ecosystem functioning. Rhizosphere microorganisms have demonstrated their potency to improve or manage plant nutrients to encourage plant growth, resulting in increased yield and quality by converting organic and inorganic substances around the rhizosphere zone into available plant nutrients. Besides regulating nutrient availability and plant growth enhancement, rhizobacteria or fungi can restrict plant pathogens that cause disease by secreting inhibitory chemicals and boosting plant immunity to combat pests or pathogens. Thus, rhizosphere microorganisms are viewed as viable, alluring economic approaches for sustainable agriculture as biofertilizers and biopesticides. This review provides an overview of the role of rhizosphere microorganisms in soil nutrients and inducing of plant defenses. Moreover, a discussion is presented surrounding the recent consequences of employing these microorganisms and a sustainable strategy towards improving fertilization effectiveness, and encouraging stronger, more pest-resistant plants.",
"conclusion": "6. Conclusions and Future Perspectives Rhizosphere microorganisms have the potential to offer more environmentally friendly ways to increase crop production. The study of the structural and functional traits of the beneficial microbes in diverse farm systems represents a discipline that is constantly developing on a global scale. All types of ecosystems benefit from having healthy soil microbial communities since they support a wide range of soil processes, including respiration, nutrient cycling, and soil properties. These benefits are achieved by managing their configuration, utility characteristics, biochemical-substrate, or enzymatic activity. Additionally, several stressors above and below ground impacted by the warmer environment have effects on soil organic matter, root exudation, and microbial community structure resulting in an increased incidence of pests and pathogens. In many cases, plant microbiomes (community of microorganisms) exert a positive function in the community by defending against pathogens, promoting growth and health, and providing plants with an advantage in terms of adaptation. Consequently, complex and dynamic interactions exist between plants and their microbiome, describing a plant–soil feedback mechanism that may be used to describe this connection and dependency between abiotic and biotic elements of the soil circumstance. However, microbiome research still has a number of system-level knowledge gaps. Deciphering the intricate and dynamic microbial crosstalk in the soil system and the multitrophic interactions will undoubtedly be useful to farming systems, providing a fresh impetus to realize the full potential of the rhizosphere microorganisms. Therefore, in-depth understanding of their functions in the microbial–plant relationship, their community, their processes, or any requirements are needed. This knowledge will provide sustainable solutions by increasing soil fertility, disease tolerance, plant yield, and nutrition, as well as the potential for restoring degraded lands. This vast microbial world significantly contributes to the conservation of plant and human life on planet Earth to offer answers that aid in the creation of innovative biocontrol technologies and their applications.",
"introduction": "1. Introduction The world population is estimated to extend to around 10 billion in 2050 and global food demand will increase by 60% [ 1 ]. This suggestion will contribute to significant challenges regarding adequate farm-based food production to feed and supply a growing population, and the limited availability of additional agricultural land resulting from urbanization [ 2 ]. Improvements in crop yields and reducing negative impacts, abiotic stress, plant pest, and diseases of food production, at the same time have been essential to solve the problems. In many situations, enhanced agricultural productivity or pest-disease control depend on the application of synthetic fertilizers and pesticides that are often unaffordable to many farmers and can have negative effects on humans, wildlife, the environment, ecological diversity, and others. Thus, it is imperative to investigate and implement sustainable methods that enhance agricultural food production in a manner that is more harmonious with the environment. Advancements in sustainable crop improvement, coupled with the adoption of eco-friendly agricultural practices, represent a transformative approach for modern farming systems which integrates several environmentally friendly techniques using natural resources [ 3 ]. These innovations not only aim to increase yield and efficiency but also emphasize the reduction of environmental impact, ensuring a balance between agricultural productivity and ecological preservation. Plants are closely related to microorganisms in rhizosphere soil, such as those that provide nutrients–fertilizer, modify the physical and chemical properties of soil, and the manipulation of hormone signaling [ 4 , 5 ]. These are essential in determining plant health and can prevent plant diseases from biotic or abiotic stresses through rhizodeposition [ 6 ]. The rhizosphere zone represents a slot of microbial interaction that is established upon the recognition of the plant root system. This region generates carbon fixed through photosynthesis and an array of compounds including microbial secondary metabolites, carbohydrates, amino acids, and vitamins, all of which play a role in enhancing soil fertility [ 7 , 8 ]. It is a critical source of energy input in plant–soil ecosystems that improves the diversity of plant–microbe interaction. The primary result of which is the development of unique plant root microbial communities. Thus, understanding microbial diversity and their functions are a part of sustainable agriculture practice. Rhizosphere microorganisms refer to the diverse array of microscopic lifeforms that inhabit the rhizosphere, the narrow region of soil that is directly influenced by root secretions and associated soil microorganisms. This region is characterized by a high level of biological activity due to the presence of substances secreted by roots, such as sugars, amino acids, organic acids, and various secondary metabolites. These substances serve as nutrients for microorganisms, fostering a rich and dynamic microbial community around plant roots. The composition of rhizosphere microorganisms is varied and includes several key groups including bacteria, fungi, protozoa, archaea, viruses (phages), and nematodes [ 9 , 10 ]. These microorganisms engage in a wide range of interactions with plant roots and each other, including symbiosis, competition, predation, and parasitism. Beneficial interactions, such as those between mycorrhizal fungi or nitrogen-fixing bacteria and plant roots, enhance plant nutrient acquisition and stress tolerance. In the rhizosphere, bacteria stand out as one of the most abundant and varied groups of microorganisms. They are pivotal in nutrient cycling processes such as nitrogen fixation and phosphorus and potassium solubilizations, in addition to playing key roles in suppressing diseases and fostering plant growth through the synthesis of various hormones and enzymes [ 11 , 12 ]. Fungi are integral to this ecosystem, with symbiotic mycorrhizal fungi forming advantageous connections with plant roots to enhance water and nutrient absorption, while free-living fungi aid in the decomposition of organic matter and further nutrient cycling [ 13 ]. Protozoa, the single-celled eukaryotes that prey on bacteria and other microorganisms, are crucial for the regulation of microbial populations and the cycling of nutrients in the rhizosphere [ 14 ]. Archaea, although similar to bacteria, are a genetically distinct group of microorganisms involved in critical processes such as ammonia oxidation, a vital component of the nitrogen cycle [ 15 ]. Viruses, particularly phages that infect bacteria, are present in the rhizosphere as well, where they impact the dynamics of microbial communities through predation and the transfer of genes [ 16 ]. Additionally, nematodes and other microfauna, though not strictly microorganisms, play significant roles in the rhizosphere by contributing to nutrient cycling and the dynamics of the soil food web, highlighting the complexity and interconnectedness of life in this unique soil environment [ 17 ]. The unique soil environment facilitates a myriad of ecological interactions among microorganisms, influencing community taxonomy [ 18 ]. The taxonomy of microbial communities involves categorizing and understanding the diverse array of microorganisms present in a given environment based on their evolutionary relationships and characteristics [ 19 ]. This classification extends from broad groups to more specific categories, following a hierarchical structure typically including domain, kingdom, phylum, class, order, family, genus, and species. In the scope of microbial communities, taxonomy provides a framework for organizing this diversity and understanding the roles and interactions of different microorganisms within the community. For example, bacterial phyla such as Bacteroidetes and Proteobacteria are enriched in the rhizosphere, whereas phyla like Chloroflexi and Acidobacteria are more abundant in bulk soil. This variation is influenced by factors such as plant type, soil conditions, and agricultural practices [ 20 , 21 ]. A recent study showed that protists in the rhizosphere might protect plants by feeding on other microorganisms and shifting the taxonomic and functional composition of microorganisms of the rhizosphere [ 22 ]. Likewise, the study of Zhang et al. [ 23 ] showed that rhizospheric protists have the potential to influence bacterial and fungal communities to influence the rhizospheric co-occurrence relationships of soybean plants. Furthermore, identifying a microorganism’s taxonomic position can provide clues about its physiological properties [ 24 ]. The physiological features of microorganisms encompass a wide range of functional attributes that enable their growth, survival, and behavior in diverse environments. These features include a variety of metabolic pathways, allowing them to utilize different sources of carbon and energy through processes such as aerobic and anaerobic respiration, fermentation, photosynthesis, chemolithotrophy, and methanogenesis [ 25 , 26 ]. Microorganisms also have specific mechanisms for nutrient uptake and assimilation, crucial for processing carbon, nitrogen, phosphorus, sulfur, and various trace elements and vitamins [ 27 ]. Their growth is influenced by optimal conditions related to temperature, pH, and salinity, with adaptations that allow some to thrive in extreme conditions, resisting desiccation, high salinity, and extreme temperatures [ 28 ]. Communication is another key physiological feature, with many microorganisms using chemical signals for quorum sensing to regulate collective behaviors like biofilm formation [ 29 ]. Mobility is facilitated by structures like flagella, cilia, or pili, enabling movement in response to environmental cues [ 30 ]. Whereas fungi have developed unique strategies for spreading and colonizing new environments by spore dispersal and hyphy growth [ 31 ]. Energy storage mechanisms allow for the accumulation of resources in forms such as glycogen, polyphosphate, or sulfur globules. To defend against threats, microorganisms can produce antibiotics, toxins, and form biofilms, and have developed various resistance mechanisms. Lastly, the cellular structure, including cell wall composition and the presence of specific organelles or appendages, plays a crucial role in their physiological capabilities. Beneficial rhizosphere fungal and bacterial communities are well-known as plant growth promoting microorganisms (PGPM). These microorganisms can colonize plant roots and support their hosts by producing phytohormones, improving soil nutrients, combatting pathogens infection, and tolerance to biotic and abiotic stress, leading to a reduction in the use of pesticides and synthetic fertilizers in crop [ 32 , 33 ]. Host plants provide rhizo-deposit nutrients, boundary cells, mucilage, lignin, and cellulose as sources of food for microorganisms through their roots. Which are a complex mixture of organic compounds secreted by plant roots, including sugars, amino acids, organic acids, fatty acids, vitamins, nucleotides, and various secondary metabolites [ 34 ]. PGPM can consume boundary cells including those composed of cellulose in plant roots through a combination of enzymatic degradation, invasion strategies, and symbiotic or pathogenic interactions [ 35 , 36 ]. They help in the decomposition of plant biomass, releasing nutrients that can be reused by plants and other organisms. PGPM responds to plants by accumulating nutrients through solubilization, phosphorus and potassium solubilizations, and nitrogen fixation and the production of plant hormones in the rhizosphere, which support plant health to promote plant growth [ 37 , 38 ] ( Figure 1 ). In this review, we focused on the role of rhizosphere microorganisms in enhancing plant health by promoting nutrient availability and bolstering plant immune responses against pathogen attacks. This overview summarizes the latest research on how host plants interact with rhizosphere microorganisms, highlighting their distinct regulatory mechanisms in response to stimulation, and was primarily conducted via searches on multiple platforms to gather relevant scientific publications."
} | 3,504 |
32180698 | PMC7059595 | pmc | 3,130 | {
"abstract": "Spiking neural networks are well-suited for spatiotemporal feature detection and learning, and naturally involve dynamic delay mechanisms in the synapses, dendrites, and axons. Dedicated delay neurons and axonal delay circuits have been considered when implementing such pattern recognition networks in dynamic neuromorphic processors. Inspired by an auditory feature detection circuit in crickets, featuring a delayed excitation by post-inhibitory rebound, we investigate disynaptic delay elements formed by inhibitory–excitatory pairs of dynamic synapses. We configured such disynaptic delay elements in the DYNAP-SE neuromorphic processor and characterized the distribution of delayed excitations resulting from device mismatch. Interestingly, we found that the disynaptic delay elements can be configured such that the timing and magnitude of the delayed excitation depend mainly on the efficacy of the inhibitory and excitatory synapses, respectively, and that a neuron with multiple delay elements can be tuned to respond selectively to a specific pattern. Furthermore, we present a network with one disynaptic delay element that mimics the auditory feature detection circuit of crickets, and we demonstrate how varying synaptic weights, input noise and processor temperature affect the circuit. Dynamic delay elements of this kind open up for synapse level temporal feature tuning with configurable delays of up to 100 ms.",
"introduction": "1. Introduction Processing of temporal patterns in signals is a central task in perception, learning, and control of behavior in both biological and technological systems (Indiveri and Sandamirskaya, 2019 ). Unlike digital circuits, which are designed to perform precise logic and arithmetic operations, neurons are unreliable, stochastic and slow information processing entities which form networks that function reliably through distributed information processing and adaptation. Neural circuits are therefore interesting models for development of mixed signal analog–digital processing and perception systems implemented in resource efficient nano-electronic substrates that are subject to device mismatch and failure (Strukov et al., 2019 ). In particular, energy-efficient neuromorphic processors and sensor systems have been developed by matching the device dynamics to neural dynamics, for example in the form of CMOS analog circuits operating in the subthreshold regime where semiconductor electron diffusion mimics ion diffusion in biological ion channels (Mead, 1990 ; Indiveri et al., 2011 ; Schuman et al., 2017 ). The dynamic nature and spatial structure of biological neurons (synapses, dendrites, axons, etc.) implies that neurons are inherently capable of temporal pattern recognition (Mauk and Buonomano, 2004 ) and pattern generation, also without recurrent connections. Furthermore, the event-driven neurons in Spiking Neural Networks (SNNs) are typically sparsely activated and offer an efficient way of doing inference (Rueckauer et al., 2017 ). SNNs with biologically plausible dynamics thus offer an interesting alternative model for temporal and spatial (spatiotemporal) pattern recognition (Pfeiffer and Pfeil, 2018 ), which can be further developed with guidance from biology. However, it is an open problem how such neuromorphic pattern recognition solutions can be engineered in practical applications such that the dynamic nature of the hardware is efficiently exploited. Delays are essential for neuromorphic processing of temporal patterns in spike trains (Sheik et al., 2013 ) and have been studied since the early 90s, see for example the work by Van der Spiegel et al. ( 1994 ). Temporal delays have for example been implemented in neuromorphic processors in the form of multicompartment models (Hussain et al., 2015 ; Schemmel et al., 2017 ) and dedicated, specifically tuned delay neurons in the network architecture (Sheik et al., 2012a , b ; Coath et al., 2014 ). In the latter case the resulting SNN is similar to a model of the auditory thalamocortical system described by Coath et al. ( 2011 ). Nielsen et al. ( 2017 ) present a low-power pulse delay and extension circuit for neuromorphic processors, which implements programmable axonal delays ranging from fractions of microseconds up to tens of milliseconds. In polychronous (Izhikevich, 2006 ) architectures, asynchronously firing neurons project to a common target along delay lines so that spikes arrive at the target neuron simultaneously, thus causing it to fire. A polychronous SNN with delay adaptation for spatiotemporal pattern recognition has been implemented in a Field-Programmable Gate Array (FPGA) and in a custom mixed-signal neuromorphic processor (Wang et al., 2013 , 2014 ). The typical signal propagation delays in axons (Swadlow, 1985 ) and dendrites (Agmon-Snir and Segev, 1993 ) of cortical neurons range up to tens of milliseconds. Furthermore, the dynamics of synapses also play an important role for the processing of temporal and spatiotemporal patterns (Mauk and Buonomano, 2004 ) and offer efficient dynamic mechanisms for sequence detection and learning (Buonomano, 2000 ). Synaptic dynamics enable pattern recognition architectures with high fan-in, which is beneficial in neuromorphic systems where multicompartment modeling, axon/neuron reservation and spike transmission is costly. Rost et al. ( 2013 ) present an SNN architecture with spike frequency adaptation and synaptic short-term plasticity that models auditory pattern recognition in cricket phonotaxis. There, synaptic short-term depression and potentiation is implemented to make neurons act as high-pass and low-pass filters, respectively. The resulting signals are combined in a neuron that acts as a band-pass filter and thereby responds to a frequency band that is matched to the particular sound pulse period of the crickets. Insects offer interesting opportunities to develop neuromorphic systems by modeling and finding guidance from their neural circuits, where the relatively low complexity allows neuromorphic engineers to transfer the principles of neural computation to applications (Dalgaty et al., 2018 ). Our present investigation is inspired by a more recent description of the cricket auditory system (Schöneich et al., 2015 ) and preliminary work (Nilsson, 2018 ) indicating that dynamic synapses in a neuromorphic processor can be used to imitate the post-inhibitory rebound of the non-spiking delay neuron in the auditory circuit of the cricket. We configured disynaptic delay elements composed of inhibitory and excitatory dynamic synapses in the low-power Dynamic Neuromorphic Asynchronous Processor (DYNAP) model SE from aiCTX (Moradi et al., 2018 ). DYNAP-SE features reconfigurable mixed-mode analog/digital neuron and synapse circuits with biologically faithful dynamics. We investigated the properties and parameter dependence of the disynaptic delay elements in a population of neuromorphic neurons and found that delayed excitations of up to 100 ms can be achieved, and that the parameters can be selected so that the delay and delayed excitation amplitude depends mainly on the synaptic efficacies. Furthermore, we imitated the post-inhibitory rebound of the non-spiking neuron in the auditory circuit of the cricket (Schöneich et al., 2015 ) with one disynaptic element and investigated a circuit with three spiking neurons that reliably detects the species-specific sound-pulse interval of 20 ms. Since delays of tens of milliseconds are useful for implementing different kinds of neural circuits, cortical circuits in particular, the easily configurable properties of the disynaptic delay elements described and characterized in the following open up for further implementations and studies of SNN architectures in neuromorphic processors.",
"discussion": "4. Discussion SNN architectures for temporal pattern recognition require delays, and the dynamics of synapses, dendrites and axons of cortical neurons correspond to a spectrum of signal propagation delays ranging up to about 100 ms. In this work, we investigate delays produced by inhibitory–excitatory pairs of conventional conductance-based dynamic synapses implemented in the DYNAP-SE neuromorphic processor. Our main results presented in Figures 3 , 9 , 10 demonstrates that configurable delayed excitations of up to about 100 ms can be implemented in this way, and that a single neuron with multiple disynaptic delay elements can respond selectively to spatiotemporal input patterns. Figure 3 illustrates that for one particular configuration of the disynaptic elements, which is selected to mimic the PIR of a particular non-spiking delay neuron in crickets, a distribution of delays are realized in one neuromorphic core thanks to device mismatch. Furthermore, Figure 9B illustrates a subset of the possible disynaptic configurations resulting in different delays (τ inh = 30, 50, 70, 90 ms) and delayed excitation amplitudes. Thus, by configuring the two synaptic parameters of the disynaptic elements, variable excitation strengths and delays of up to about τ delay ≃ 100 ms are achieved, which is similar to the range of dendritic and axonal signal propagation delays in cortical circuits (Dayan and Abbott, 2005 ). At the quantitative level, we observe some differences between the feature detection results presented in section 3.2 and the behavior of the cricket circuit described by Schöneich et al. ( 2015 ). In the crickets, the response of the coincidence detector neuron LN3 for different IPIs varies so that the distribution of the number of spikes of LN3 increases as the interval gets closer to the species-specific IPI of 20 ms. This is not the case in the results presented here, and further optimization of the neuron and synapse parameters are required if this behavior is to be imitated. As illustrated in Figure 7B , our LN3 reliably produces the same number (but different timings) of spikes for all of the different IPIs, with the exception of the 0 ms IPI. A more plausible trend is observed in the case of 50% input noise, but in that case the classification results are weaker. Hence, the classification mechanism relies on the timing of spikes and the balance of inhibition and excitation. Temporal feature detection and pattern recognition are central tasks in advanced sensor and perception systems. Thus, low-power SNN processors enabling learning and recognition of complex spatiotemporal patterns (Indiveri and Sandamirskaya, 2019 ; Strukov et al., 2019 ) have many potential applications, for example for always-on machine monitoring (Martin del Campo et al., 2013 ; Martin del Campo and Sandin, 2017 ), where the system needs to operate autonomously and wirelessly with limited resources over the expected lifetime of the monitored machine component (Martin del Campo, 2017 ; Häggström, 2018 ). Although we sidestep Dale's principle, the dynamic disynaptic delay elements investigated here have the desirable property that each neuron can be configured with multiple disynaptic elements, as illustrated in Figure 10 . By combining multiple disynaptic delay elements, for example in line with the idea of polychronous networks (Izhikevich, 2006 ), more complex spatiotemporal patterns can be detected in principle. Since the disynaptic delay elements are realized with ordinary dynamic synapses, the approach is not limited to this particular neuromorphic processor, although the distribution of delays obtained is processor and device-mismatch dependent. Further work is required to investigate how the repertoire of synaptic delays can be exploited and configured/learned to solve practical pattern recognition tasks, and to further develop the understanding of how device mismatch, noise and temperature variations affect different network architectures. With dynamic synapses featuring short- and long-term plasticity, additional mechanisms for sequence detection and learning can also be realized (Buonomano, 2000 ) and investigated. Furthermore, SNNs can faithfully reproduce dynamics of brain networks, which appear to self-organize near a critical point where no privileged spatial or temporal scale exist, which has interesting consequences for information processes (Cocchi et al., 2017 ). Thus, Neuromorphic Engineering (Indiveri and Horiuchi, 2011 ; Strukov et al., 2019 ) and dynamic neuromorphic processors opens the way to new interesting architectures for pattern recognition and generation in machine perception and control."
} | 3,129 |
37528060 | PMC10427965 | pmc | 3,131 | {
"abstract": "Abstract \n Pityrogramma calomelanos and Pteris vittata are cosmopolitan fern species that are the strongest known arsenic (As) hyperaccumulators, with potential to be used in the remediation of arsenic-contaminated mine tailings. However, it is currently unknown what chemical processes lead to uptake of As in the roots. This information is critical to identify As-contaminated soils that can be phytoremediated, or to improve the phytoremediation process. Therefore, this study identified the in situ distribution of As in the root interface leading to uptake in P. calomelanos and P. vittata, using a combination of synchrotron micro-X-ray fluorescence spectroscopy and X-ray absorption near-edge structure imaging to reveal chemical transformations of arsenic in the rhizosphere–root interface of these ferns. The dominant form of As in soils was As(V), even in As(III)-dosed soils, and the major form in P. calomelanos roots was As(III), while it was As(V) in P. vittata roots. Arsenic was cycled from roots growing in As-rich soil to roots growing in control soil. This study combined novel analytical approaches to elucidate the As cycling in the rhizosphere and roots enabling insights for further application in phytotechnologies to remediated As-polluted soils.",
"conclusion": "Conclusions This study has shown that P. calomelanos and P. vittata grow vigorously in nutrient-poor and As-rich soils, cycling the As along the roots, and the As chemical species accumulated in their roots is differentiated. Further research is required to explore the full potential of both ferns for As phytoextraction, since P. vittata is highly effective, but P. calomelanos develops more biomass, an important characteristic for successful phytoextraction. 8 , 16 During the last 10 yr, above ground tissues of hyperaccumulator plants have been extensively studied by novel methods to reveal their mechanisms to store metals. However, roots are still the hidden puzzle of the hyperaccumulation phenomena, and even less is known about the rhizosphere interface and the processes that lead to metal(loid) uptake by hyperaccumulator plants. In this study, we have compared root preferences, and active As-uptake in the strongest As hyperaccumulator ferns. The dominant form of As in soils was As(V), even in As(III)-dosed soils, and the major form in P. calomelanos roots was As(III), while it was As(V) in P. vittata roots. Arsenic was cycled from roots growing in As-rich soil to roots growing in control soil.",
"introduction": "Introduction Arsenic (As) is the most toxic element on Earth, 1 although As toxicity and bioavailability depends on the chemical form, which is highly variable. 2 Arsenite [As(III)] is 60-fold more toxic to humans and biota compared to arsenate [As(V)]. 3–6 Arsenic is released to the environment naturally as well as through human activities. These releases pose risks for the affected ecosystems and human health, and are likely to represent a serious threat. 7 An eco-friendly method to remove toxic metal(loid)s from local environments is phytoextraction , where hyperaccumulator plants are used to clean soils and water. 8–11 In this method the aerial tissues of hyperaccumulator plants are harvested and either safely disposed, or processed for economic purposes, i.e. phytomining. 12 Hyperaccumulating plants can accumulate metal(loid)s in their aerial tissues at concentrations up to 1000s-fold higher than normal plants. 13–15 Typically, As concentrations in most plants are <1 µg g −1 ; however, As hyperaccumulators can reach >1000 µg g −1 dry wt. The arsenic hyperaccumulators are mainly fern species from the order Pteridales, genus Pteris, and accumulate extraordinarily high levels of As in their fronds. 16 The cosmopolitan fern Pteris vittata can attain up to 22 600 µg As g −1 dry wt. in its fronds, 17 while Pityrogramma calomelanos accumulates up to 8350 µg g −1 As dry wt. 18 Both ferns are the strongest As hyperaccumulators; however, limited research has been devoted to P. calomelanos in comparison to P. vittata . 19 The chemical speciation of As in fronds of P. vittata has been widely addressed, but studies on roots and rhizosphere are scarce. 20 The translocation of As from roots to fronds is highly effective in P. vittata , and the As enrichment follows this order root < stipe < pinnae, in the latter the As concentration is higher (78–96%). 19 Inorganic As predominates in P. vittata . 21 Arsenite is dominant in the xylem sap and accounts for 93–98% of the total As, and in fronds As(III) accounts for around 80%. 22 In the rachis and pinnules of the frond, As(III) is located in the endodermis and pericycle on the periphery of the vascular bundle system, while As(V) predominates in the vascular bundles. 19 The main inorganic forms of As are As(III) and As(V) which are released from As-mineral weathering and represent the phytoavailable forms of As in soil solution. 23 However, microbes contribute extensively to As inorganic and organic transformations through reduction, oxidation, methylation and demethylation reactions. 24 The uptake of As for plants in oxidizing conditions is via As(V) through phosphate transporters, and in reducing conditions is via As(III) through silicon transporters. 25 Another group of As analogues to As(V) are the thioarsenates (HAs 5+ S −2 n O 4- n 2− ; n = 1–4), although the uptake, and accumulation role in plants of these As species is still unclear. 26 The oxoanion and oxoacid forms of As [As(III) and As(V)] have been well studied in the strongest As hyperaccumulator plant, P. vittata. In Pteris vittata , arsenic is cycled in the roots, As(V) enters root cells via phosphate transporters, is reduced to As(III) and some of it complexed to glutathione, and then stored in vacuoles or transported to the fronds. 27 , 28 However, it is unclear how much of As(III) is complexed by glutathione in the root, and how much in the fronds. 19 An excess of As(III) is expelled from the roots to the rhizosphere as a detoxification mechanism, where oxidation of As(III) to As(V) occurs. 29–31 During As translocation from roots to fronds, the rhizome of P. vittata was found to accumulate As and regulate the preferred organ location depending on As exposure; when As is low in the substrate, the accumulation is higher in young fronds, conversely in high As environments the As accumulation is shifted to mature fronds in order to protect young tissues. 32 In previous studies, it has been identified that the As influx in the roots of As hyperaccumulators is higher compared to non-hyperaccumulators. 32 , 33 However, within As hyperaccumulators the As influx is also differentiated; e.g. a study reported that Pteris quadriaurita differs from Pteris vittata in that it does not excrete As(III) in the root efflux to control the levels of As to avoid As toxicity in the roots. 29 A hydroponic dosing experiment showed that P. calomelanos in a high dose As treatment (30 mM As in the form of sodium arsenate) accumulated relatively less As in the aerial tissues (from 90% to 74%) and increased As in the roots (from 10% to 26%), compared to the lower As treatments. 34 Arsenic probably enters P. calomelanos roots via the phosphate root system similar to other plants, 35 the processes of translocation and speciation in the rhizosphere, roots, and fronds are not yet fully understood. 16 In the fronds, the As concentration is higher in the vascular bundle, followed by the cortex, and lower in the epidermis. 36 It is not clear how vacuoles play a role in the sequestration, internal detoxification, and chemical speciation of As in P. calomelanos . A hypothesis for the reason for As(V) reduction to As(III) in P. calomelanos is to preserve energy for metabolic function. 37 Arsenite is toxic to plants because it interferes with sulfhydryl groups of enzymes and proteins, inhibiting cellular function 38 ; while As(V), as an analogue to phosphate, interferes in ATP processes, leading to disruption of energy, and if reduced to As(III), it can trigger a similar toxicity. Once As(III) is produced, it may be complexed with sulfur (S) into less toxic forms and sequestered in vacuoles. 39 It is still largely unclear whether As hyperaccumulator roots contribute actively to the geochemical processes in the interface of the rhizosphere, leading to As removal and uptake. 20 Moreover, the role of root exudates in As uptake or avoidance still remains largely unknown. 40 This study aimed to compare the in situ distribution of As in the root interface leading to uptake of this element in P. calomelanos and P. vittata growing in As(III) and As(V) enriched soils. Previous research has reported the speciation and translocation of As in P. calomelanos in spiked soil with As(V) using small freeze-dried sections of the different parts of the fern. 39 The current study used X-ray absorption near-edge structure (XANES) imaging to map the distribution of chemical forms of As in roots of living plants growing in rhizoboxes. This approach allowed visualization of the spatial variation of As coordination environment at root level including the substrate. Synchrotron-based micro-X-ray fluorescence spectroscopy (µXRF) and laboratory µXRF were harnessed to reveal As distribution in roots and shoots of both As-hyperaccumulating ferns.",
"discussion": "Discussion In this study, the use of rhizoboxes revealed the main similarities and differences in P. calomelanos and P. vittata roots growing in As(III) and As(V)-spiked soils. In both species As cycles throughout the root systems taking up As from the enriched side and transporting it to the roots growing in the control side soil (Figs. 5 and 6 ). This suggests that As is remobilized along with other macro- and micronutrients throughout their roots. 60 , 61 Morphologically, both ferns grew healthy roots in control and As-rich soils, although P. calomelanos roots developed more root hairs than P. vittata (see Figs. 3 and 6 ). The significant difference was in the biomass and As accumulation in roots and fronds, while P. calomelanos outgrew, P. vittata was more efficient taking up As, by up to three-fold (Fig. 1 , Table 3 ). This efficient translocation in P. vittata has been reported at up to four-fold compared to Pteris quadriaurita , an As hyperaccumulator. 29 In P. vittata , the As translocation efficiency is regulated by the rhizome, which can switch the transport of As from young fronds to mature ones under high As exposure. 31 , 32 , 62 The As speciation in this species is also regulated with aging processes, As(III) predominates in younger fronds, while As(V) in older ones. 63 Furthermore, P. vittata rhizodermis and root hairs were reported to be rich in pectin, and a lignified cortex, both associated with high accumulation capacity of ions. 64 The As mobility and uptake by plants is determined by the soil biogeochemical processes. 65 Although total concentration in the soil was set to 100 µg As g −1 in our study, the [Sr(NO 3 ) 2 -extractable] analysis showed that only ∼4 µg As g −1 was phytoavailable in both As(III) and As(V) enriched soil, which means that As is adsorbed by iron and aluminum oxides/hydroxides, limiting the bioavailability. 25 , 66 Arsenite mobility and solubility is higher than As(V), up to 25–60 times, 67 in this study, the phytoavailable fraction in the As(III)-spiked soil was slightly higher (3.55–4.21 µg As g −1 ) than As(V)-spiked soil (2.61–4.06 µg As g −1 ). However, both ferns translocated slightly more As from the C | As(V) treatment compared to the C | As(III) treatment, and the highest accumulation for both ferns was recorded in the mixed treatment As(V) | As(III) (Fig. 1 a), with 6670 µg As g −1 as average in old fronds of P. vittata and 4020 µg As g −1 in young fronds of P. calomelanos . Similar to our results, P. vittata did not show significant difference in As uptake when subjected to As(V) and As(III) treatments in a concentration of 10 mg As L −1 . 68 Even though As(V) predominates under aerobic conditions, As(III) can also be present due to microorganism activity and root exudates, 69 , 70 coexisting both As species in the substrate. 71 We found a predominance of As(V) in soils, even in As(III)-dosed soil. In agreement with our findings, arsenite in soil can be oxidized to As(V), especially in presence of Fe-hydroxides, Al and Mn 72 ; e.g. the As(III) recovery after the spike of 4 µg As(III) g −1 was 1.1 µg As(III) g −1 in soils with higher content of Fe, Al and Mn, in comparison to a similar treatment but with lower Fe, Al, and Mn in soils, where the As(III) recovery was 2.55 µg As(III) g −1 . 73 Moreover, the rate of As(III) oxidation in spiked soils depends on the biogeochemical characteristics of the soil, e.g. if Fe-oxyhydroxides are present in the soil, they can adsorb As(III) on the surface, stabilizing As(III) and coexisting with As(V). 66 , 74 , 75 Likewise, microbial activity added to the influence of oxides lead to partial or total As(III) oxidation in spiked soils, limiting the measurement of this species by XANES method. 75 Also, chemical reactions during the extraction method to identify the proportion of As(III) and As(V) in soils can yield misleading data. The high intensity of X-rays used in XANES analysis can lead to As(V) reduction to As(III) in As(V)-spiked soils. 38 The stability of As(III) over time, especially in spiked soils, has not been concluded yet, and may be susceptible to slow oxidation. 75 Furthermore, photodamage might occur, during the XANES analysis, but our previous work showed that this was very limited in XANES imaging mode compared to confocal spot mode. The oxidation reduction potential in the soil for this experiment was 224 ± 2.52 mV. 47 The exchangeable sulfur (S) range was 32.1–117, mean: 58.8 µg S g −1 , 76 and the pH was 5.28 in the As(III)-spiked soil (Table 1 ), providing a moderately reducing environment, where the formation of thioarsenates can be possible, 26 given high S available, 77 as it was identified in this study by XANES (Table 4 ). In strongly reducing environments, the high affinity between As(III) and S permits the oxidation of As(III) to As(V) in the form of thioarsenates. 78 In laboratory studies, the dissolution of orpiment (As 2 S 3 ) in neutral to alkaline pH produces thioarsenates of 43–55% of total As. 79 Microbial production of sulfur can enhance the production of thioarsenates, 80 and conversely sulfur-oxidizing bacteria can transform it into As(V). 81 Thioarsenates have a closer edge position to As(III) than As(V), and may be mistakenly identified as As(III) with XANES in mixed As-S compounds. 58 Furthermore, thioarsenates are not stable and are sensitive to oxidation and pH and are converted to As(V) and As(III). 78 , 82 , 83 Thioarsenate adsorption capacity is weaker than As(III) and As(V), making As more mobile 84 , 85 ; thioarsenates are more toxic to plants than As(V). 26 In our study we found that P. vittata roots are mainly enriched with As(V), similar to previous reports, 28 although this result differs substantially from a previous investigation which reported preferential As(III) storage in P. vittata roots. 29 In a previous study, As(III)-oxidizing bacteria in the rhizosphere of P. vittata were suggested to contribute to the As cycling, oxidizing the As(III) efflux from the roots to As(V). 86 Pityrogramma calomelanos roots differ from those of P. vittata , storing mainly As(III) followed by As(V) and As-glutathione [As(GSH) 3 ]. The complexation of As with glutathione is a mechanism that plants develop to cope with the As toxicity. 87 P. calomelanos accumulates As less efficiently than P. vittata , which depletes more As even from the control soil (1.83 µg g −1 for P. vittata and 2.79 µg g −1 for P. calomelanos ) and As(V)-spiked soil (85.1 µg g −1 and 92.8 µg g −1 , respectively) (Table 2 ). P. vittata roots accumulate approximately three-fold As in roots in comparison to P. calomelanos across the different treatments, e.g. in the As(V) | As(III) treatment P. vittata has 762 µg As g −1 in roots growing in the As(III) section, and P. calomelanos 131 µg As g −1 in roots in the same section. Higher As concentration was reported in P. vittata compared to P. calomelanos , albeit the translocation to the aerial tissues essentially correlated to the type of soil. In kurosol and vertosol soils translocation by P. vittata was stronger, and in ferrosol soils translocation by P. calomelanos was stronger, showing that As translocation in both ferns depends on soil properties, i.e. free Fe, clay and organic matter content. 88 Contradicting Xu et al .’s results, P. calomelanos was reported to attain higher As accumulation in fronds (887 µg As g −1 ) compared to P. vittata ( 674 µg As g −1 ) after growing for 10 mo in a former cattle dip area, polluted with As (830 µg g −1 on average) in New South Wales, Australia. 89 , 90 The As distribution in the roots of P. calomelanos and P. vittata in the As-enriched soil displays a higher As concentration, compared to the control soil, where As cycles in lower quantity, although with some cumulus of high As in the joint of primary and lateral roots (Figs. 5 – 7 ). It has been reported that P. calomelanos darkened and shortened lateral roots as a response to As enriched nutrient solution (30 mM As ∼ 2250 µg As g −1 ). 34 In our study, conversely, lateral roots, root hairs and root tips grew healthy across all the treatments, and only primary roots were darkened. However, in some plant species lateral roots and root hairs are developed when P bioavailability is low in the substrate, as a response to nutrient deficiency, triggered by hormonal signals, i.e. auxin hormone. 91–93 The emergence of lateral roots from inner tissues (pericycle or endodermis) implies a series of challenging molecular and cellular regulatory processes. 94–96 We postulate that As accumulation in nodes of the joints of lateral and primary roots is a mechanism to regulate the amount of As in younger lateral roots. It is clearly visible in P. vittata , that the As is transported through the vascular bundle and enriched in the base of lateral roots (Fig. 7 ). Most plants develop different strategies to avoid toxic elements in the substrate, i.e. secreting organic acids to restrict the influx of metals by chelation 97 or changing the root structure to inhibit root growth in areas where toxic elements are present. 98 , 99 In the case of As, as it is not essential for plants, As(V) is taken up inadvertently through phosphate transporters in aerobic environments, and As(III) by silicon transporters in anaerobic media; then sulfur through complexation of arsenite by thiol-rich peptides retains As in the roots. 25 , 28 , 100 In our study, both ferns translocate As from roots to fronds efficiently, in fronds the As enrichment is in the rachis (mid-rib of the blade), costa (midrib of the pinna), and higher in the terminal veins in old specimens, which is consistent with previous studies. 27 , 39 In P. vittata , As is stored in the endodermis and pericycle of the rachis and pinnules. 19 Arsenic hyperaccumulators predominantly store As(III), despite As(III) being more toxic than As(V). 101 Both As species are detrimental for plants and both affect plant metabolism; however, As(V) can compete with phosphate and interfere in cellular energy production disrupting ATP processes, while arsenite is a dithiol reactive compound and can inactivate enzymes and proteins inhibiting cellular function. 102 In this study, we focused on the speciation of arsenic in soil and roots of the two best arsenic hyperaccumulators P. vittata and P. calomelanos . However, the rhizosphere is a complex environment in which microbes (rhizobiome) play an essential role in As speciation, mobility, and plant growth. 103–105 More scientific reports on the microbiome were published for P. vittata in comparison to P. calomelanos . For example, P. vittata produces more exudates than normal plants, allowing the development of a microbiome responsible for the mobilization of As in the soil through As reduction, oxidation, methylation, and demethylation, and As sorption and desorption. 106 , 107 Bacteria isolated from P. vittata roots can solubilize As from insoluble ferric arsenate (FeAsO 4 ) and aluminum arsenate (AlAsO 4 ) minerals and enhance As uptake. 108 A study collected 864 bacterial cultures from the rhizosphere of P. vittata , and the majority tolerated As(V) more than As(III), 95% promoted As (V) reduction, 73% As(III) oxidation, and 71% reduced and oxidized As. 109 Another study reported a diverse As(III)-resistant bacteria in P. vittata roots growing in soils with up to 24.5 µg As g −1 . 110 We suggest further studies (i.e. metagenomics, transcriptomics) to better understand the interactions of the root exudates and microbiome in the soil and As hyperaccumulator ferns, especially for P. calomelanos ."
} | 5,285 |
36125335 | PMC9536016 | pmc | 3,132 | {
"abstract": "A comprehensive understanding\nof the slip phenomenon\non liquid/solid\ninterfaces is essential for multiple real-world applications of superhydrophobic\nmaterials, especially those involving drag reduction. In the current\ncontribution, the so-called “slip-length” on an irregularly\nstructured superhydrophobic surface was systematically evaluated,\nwith respect to varying liquid surface tension and viscosity. The\nsuperhydrophobic polymer–nanoparticle composite (SPNC) material\nused exhibits a dual-scale surface roughness and was fabricated via\ncoating a surface with a mixture of polydimethylsiloxane solution\nand functionalized silica particles. A cone-and-plate rheometric device\nwas employed to quantify the slip length. To independently study the\nimpact of surface tension and viscosity, three types of aqueous solutions\nwere used: sodium dodecyl sulfate, ethanol, and polyethylene glycol.\nOur experimental results demonstrate that a decreasing surface tension\nresults in a decreasing slip length when the fluid viscosity is held\nconstant. Meanwhile, the slip length is shown to increase with increasing\nviscosity when the surface tension of the various liquids is matched\nto isolate effects. The study reveals a linear relationship between\nslip length and both capillary length and viscosity providing a reference\nto potentially predict the degree of achievable drag reduction for\ndiffering fluids on SPNC surfaces.",
"conclusion": "4 Conclusions Since\nmost of the previous\nstudies in the literature have focused\non the effect of material and microgeometrical impacts on the slip\nlength of SHO surfaces, the present research provides an insight into\nthe influence of liquid properties. The surface tension and shear\nviscosity dependence of slip length were systematically investigated\nby using various liquids (SDS, EtOH, and PEG) and a SHO surface (SPNCs),\nwhich provides significant apparent slip. Because of the decreasing\nsurface tension via the addition of a\nsurfactant (SDS), the SHO property of the SPNCs is significantly reduced\nwith a decreasing contact angle. However, SPNC surfaces are able to\nremain in the hydrophobic region and exhibit drag reduction characteristics\nwith an SDS concentration larger than the CMC. With the constant viscosity\nof SDS solutions, slip lengths are shown to be linearly proportional\nto the capillary length. Based on this, we hypothesize that the surface\ntension mainly affects the air layer thickness via the capillary length,\nand, therefore, decreasing the surface tension causes a decrease in\nair layer thickness and slip length, as the theoretical prediction, b ∝ l air . The relationship\nbetween slip length and shear viscosity when surface tension is held\nfixed is shown to be linearly proportional as well. Results are consistent\nbetween different liquids/fluid pairs. Moreover, we should note that,\nin the current study, the slip-length increase ratio does not follow\nthe viscosity increase ratio which indicates the idealized view of\napparent slip (e.g., eq 2 and 3 ) may not fully hold for irregularly\nstructured SHO surfaces.",
"introduction": "1 Introduction The concept of slip length\nwas first proposed two centuries ago, 1 at\nwhich time the no-slip boundary condition\nwas universally accepted for a solid/liquid interface in fluid dynamics.\nDuring the last two decades, nanoscale and microscale fluidic technologies\nhave been developed, 2 such that the inherent\nassumption of a no-slip boundary condition was revisited throughout\nthe literature, 3 , 4 especially in the scenario where\nsolid surfaces have been coated or treated to become so-called “superhydrophobic”\n(hereafter referred to as “SHO” surfaces). 5 The large slip obtained from liquid/solid interfaces\nenables the SHO surfaces to potentially reduce drag in a flow, and\nthe slip length, in return, is an ideal parameter to quantify the\ndegree of drag reduction. 6 As an\narea-average quantity, 7 the apparent\nslip originates from the various “air pockets” (often\ntermed “plastron”) trapped on the nanogeometrical and\nmicrogeometrical roughness features of a SHO surface (i.e., nonwetted\nstate) since the shear stress is much lower at an air/liquid interface\nthan at a solid/liquid interface. 8 , 9 Therefore,\nthe air pockets that are generally associated with the structural\npattern of SHO surfaces are of fundamental importance for a slip boundary\ncondition to occur. 10 Numerous studies 11 − 15 have focused on the topography of SHO surfaces, which aim to predict\nthe slip length with a given structure 14 or optimize the surface features for a higher slip length. 15 However, the test liquids for most of these\nstudies are restricted to either water 16 , 17 or water–glycerol\n(to enhance the viscosity) 18 , 19 and the systematic\nimpacts of isolated liquid property variation on\nslip length have been largely overlooked. 20 Recently, unexpectedly low slip lengths were found to be the result\nof a nonuniform surface tension over the formed air pockets on SHO\nsurfaces made from hydrophobic polydimethylsiloxane (PDMS) and comprised\nof regular rectangular gratings, 21 which\ncan be caused by the accumulation of matter (such as microparticles,\nsurfactants, or other “contaminants” such as velocimetry\ntracking particles 22 ). Previous theoretical\nworks 23 , 24 also hypothesized that the adsorption of\nsurfactants on the air/liquid interface would immobilize the interface\nand, hence, modify the slip length. Moreover, any local slip has been\nobserved to vanish because of the decreasing surface tension of the\ngiven fluid and the induced Marangoni forces along the microfeatures. 25 Thus, there is evidence that surface tension\nmodification may eliminate any potential slip/drag reduction for some\nSHO surfaces comprised of certain topologies. In addition to surface\ntension, shear viscosity also has a direct influence on slip length.\nOn a given SHO surface, the slip length was shown to increase at the\nsame ratio as shear viscosity increment by using water and 30 wt %\nglycerine. 18 , 19 Once again, there is little systematic\nwork investigating isolated effects of viscosity (while holding surface\ntension constant) for other fluids and SHO surfaces. In this\nwork, the surface tension and shear viscosity dependences\nof slip length on an irregularly structured SHO surface (so-called\n“SPNC” surfaces) were experimentally studied. A SPNC\nsurface is a recently developed superhydrophobic polymer–nanoparticle\ncomposite coating, which features extreme superhydrophobicity and\nexcellent resilience. 26 , 27 A Couette flow based on a rheometric\ncone-and-plate system was employed to measure the slip length ( Figure 1 a). This technique\nand geometry has been previously used by Choi and Kim 18 and Xu et al., 28 and similar\nexperiments for slip-length measurement have also been conducted based\non a parallel-plate geometry 29 and Taylor–Couette\nflow. 30 A schematic of the irregular microstructures\nof a SPNC surface and the Couette flow over it can be found in Figure 1 b. The volumes of\nindividual air pockets are assumed to vary dependent on the size of\nthe local microfeatures. Cross-sectionally viewing the B–B\nlocation in Figure 1 b, an idealized flow above a pure air layer can be postulated ( Figure 1 c). The shear stress\n(τ i ) between such an idealized air–liquid\ninterface can be expressed as 1 where u 0 is the slip velocity, b is the slip length, l air is\nthe thickness of the air layer (which\nis assumed to be flowing uniformly), and μ air and\nμ 1 are the viscosities of air and liquid, respectively. Figure 1 Slip-length\nmeasurement setup and concept of apparent slip on SHO\nsurfaces. (a) Schematic diagram of slip-length measurement on the\nSPNC surface with a cone-and-plate rheometer system, where ω\nis the angular velocity and α is the angle of the cone. The\nSPNC surface was coated on a stainless-steel substrate with the same\nradius ( R ) as the cone. (b) An illustration of cross-sectional\nview at line A-A in panel (a), where u is the velocity\nof the moving plate and u 0 is the slip\nvelocity. Air pockets of different volumes are formed on the SPNC\nsurfaces as shown in the schematic. (c) A conceptual illustration\nof the slip-length concept based on an idealized air layer (can also\nbe seen as the cross-sectional view of B–B in panel (b)), where l air is the thickness of the air layer and b is the slip length. Therefore, the slip length ( b )\ncan be obtained\ntheoretically via eq 2 : 31 2 An alternative\nmodel uses an assumption\nthat there is a net-zero\nmass flow rate within the surface layer flow, 24 , 32 , 33 such that there is a recirculating flow\nin the air layer. In this situation, eq 2 is found to be modified by a factor of 1 / 4 in the viscosity ratio: 3 Equations 2 and 3 show that the slip length\nis determined by the air layer thickness ( l air ) and shear viscosity ratio (μ l /μ air ) in both idealized viewpoints (note that it has been recognized\nthat eqs 2 and 3 may, in fact, be more complex for heterogeneous\nsurfaces, such as that studied here, and theoretical studies have\nattempted to relate viscosity contrast to the topography of the underlying\ntexture 34 ). To investigate the validity\nof these equations, in this study, several liquids (sodium dodecyl\nsulfate, ethanol, and polyethylene glycol solutions) are utilized\nto monitor the slip length on SPNC surfaces. The surface tension and\nshear viscosity dependence of slip length were individually analyzed.\nThe results should help to broaden the application of SHO surfaces\nto liquids other than water and aid in a better understanding of the\neffects of varying liquid properties on achievable slip lengths (and,\nconsequently, drag reduction).",
"discussion": "3 Results and Discussion 3.1 Surface Morphology and Superhydrophobicity The SEM\nimages, shown in Figure 2 , demonstrate a dual-scale surface roughness of the\nSPNC surfaces. The partial cure of PDMS polymer during the precoating\nprocess generated the first-scale surface roughness. Protrusions of\n20–30 μm in size and some cracks with different lengths\nand widths were observed at a lower magnification ( Figure 2 a). Although the appearance/severity\nof cracks was observed to be dependent on precise coating operation,\nexperimental conditions were kept as constant as possible in order\nto reduce variation in the microcrack formation. The second-scale\nroughness is on the order of several hundreds of nanometers and can\nbe observed in Figure 2 b, which results from the arrangement of silica particles. Multiple\nSEM tests show that microscale feature size remains consistent among\nthe SPNC samples (additional SEM images are available in Figure S1 in the Supporting Information). Further\ndetails regarding these SPNC materials have been previously reported. 26 , 27 Figure 2 SEM\nimages of SPNC surfaces with different magnifications. Scale\nbars are shown for each image. The superhydrophobicity of the current surfaces\nwas confirmed by\nthe large contact angle (158° ± 0.9°) and small contact\nangle hysteresis (5° ± 0.8°) results with distilled\nwater. Meanwhile, slip length as a novel indicator has also proved\nan excellent superhydrophobic surface property of SPNC coatings. The\nslip length ranged from 100 to 160 μm (equivalent to laminar\ndrag reduction ranging from 14%–18%) for 15 different coated\nsamples and ∼30 repeat measurements. An example of the slip-length\ncharacterization is shown in Figure S2 in\nthe Supporting Information. Such very high slip-length results are\nrarely observed in the literature except for a few studies, which\nwere dedicated to its maximization. 12 , 37 Following\nthe protocol of previous tests on the resilience of SHO surfaces, 28 the longevity of this drag reduction over one\nsuch SPNC surface was characterized by a long-term slip-length measurement.\nResults shown in Figure S3 in the Supporting\nInformation demonstrate that the drag-reduction performance of SPNC\nsurfaces remains constant over a period of 10 h (with water flow at\na shear rate of 75 1/s). 3.2 Liquid Properties The surface tension\nof SDS solutions are presented in Figure 3 a, as well as the data for distilled water\nalone (i.e., 0 wt % SDS concentration). The distilled water\nvalue (72.6 ± 0.59 mN/m) is consistent with other studies, 38 confirming the absence of trace contaminants.\nThe surface tension of SDS solutions decreases as the concentration\nincreases until it reaches the CMC (where a minimum surface tension\nis obtained). CMC is found to be 7 mM in this study which is slightly\nlower than the results from Hernainz and Caro 39 where CMC was reported as 8 mM. Note that a very small quantity\nof surfactant addition also results in a measurable surface tension\ndecrease. As shown in the expanded view in Figure 3 a, the “trace” level SDS solutions\n(0.01 and 0.1 mM) still have measurable surface tension variations,\ncompared to distilled water. Finally, the surface tension results\nof 0.5 and 0.75 mM SDS solutions, which were prepared to match the\nsurface tension of EtOH and PEG solutions respectively, are also presented\nin the expanded view in Figure 3 a. Four EtOH solutions were selected to match the surface\ntensions of the various SDS solutions ( Figure 3 b), together with three PEG solutions (with\nrelatively constant surface tension, as shown in Table 1 ), were adopted to study the\nimpact of viscosity on slip length (discussed in Section 3.5 ) Figure 3 Surface tension results\nfor (a) various SDS solutions and (b) four\nEtOH solutions selected to match the surface tension of specific SDS\nsolutions. The surface tension of distilled water is shown as a blue\nfilled circle and a dashed line in panel (a), and an expanded view\nprovided in panel (a) shows the surface tension of the “trace”\nlevel of SDS solutions. Error bars represent 3δ (3 times the\nstandard deviation) of typically three repeat measurements. Table 1 Surface Tension and Shear Viscosity\nfor PEG and Ethanol Solutions along with the Estimated Uncertainties sample concentration (wt.%) surface tension (mN/m) shear viscosity (mPa s) Distilled water - 72.6 ± 0.59 0.97 ± 0.02 PEG-1 1 63.1 ± 0.08 1.23 ± 0.02 PEG-2 2 62.7 ± 0.11 1.51 ± 0.02 PEG-3 3 61.0 ± 0.11 1.82 ± 0.02 EtOH-2 2 64.3 ± 0.15 1.05 ± 0.02 EtOH-7.5 7.5 52.9 ± 0.19 1.30 ± 0.04 EtOH-16.5 16.5 42.1 ± 0.30 1.83 ± 0.04 EtOH-25 25 35.9 ± 0.27 2.29 ± 0.04 The average viscosity\nof distilled water was measured\nto be 0.97\n± 0.02 mPa s at 20 °C, which represents a 3% difference,\ncompared with the result of Kestin et al. 40 The viscosity of the SDS solutions is taken to be the same as distilled\nwater (the aim of these fluids is to study the impacts of surface\ntension changes alone on slip length, as discussed in Section 3.4 ), since there is no measured\ndifference between distilled water and the SDS concentrations up to\nthe CMC. (The viscosity of distilled water and three representative\nSDS solutions are shown in Figure S4 in\nthe Supporting Information to confirm this). For PEG and EtOH solutions,\nthe viscosity results along with uncertainties are displayed in Table 1 (some data are also\nshown in Figure 3 for\nthe sake of clearer interpretation). 3.3 Changing\nthe Wettability of SHO Surfaces The wetting behaviors on\na SHO surface are of crucial importance\nregarding achieving apparent slip since a nonwetting condition is\na prerequisite for the air-pocket/plastron formation on the topography\n(i.e., a “Cassie” state). Contact angle (θ) is\ngenerally used to characterize the wettability of a surface and is\ncommonly described by Young’s equation, 41 7 where γ s-air , γ l-s , and γ 1-air represent the\ninterfacial tension of solid–air, liquid–solid, and\nliquid–air, respectively. Figure 4 a shows that the contact angle between the\nSPNC surface and SDS solutions continuously decreases as the SDS concentration\nincreases and then becomes constant when the SDS concentration reaches\nthe CMC. This is a consistent trend with Figure 3 a, which indicates the surface tension determines\nthe contact angle for SDS (as can be interpreted via eq 6 ). According to a previous study, 42 SDS as a typical ionic surfactant that contains\na linear hydrophobic tail, is defined as a surface tension ( γ 1-air ) -controlled surfactant,\nrather than a liquid–solid interfacial tension-controlled (γ 1–s ) surfactant, for which contact angle continuously\ndecay with increasing concentration and SHO surfaces transform to\nbe hydrophilic due to particle adsorption at higher concentrations.\nThe wettability of SPNC surfaces has a tendency to be altered by the\nSDS solutions as the increasing concentration (i.e., decreasing surface\ntension). However, SDS does not change the SPNC surfaces to become\nhydrophilic as the contact angles remain high at a minimum value of\n135° above the CMC. Figure 4 Contact angle measurement on SPNC surfaces.\n(a) Contact angle values\nagainst SDS concentration; the value for distilled water is shown\nas a blue filled circle and a dashed line (gray region represents\nthe variation of repeats). Representative photographs for contact\nangle tests with droplets of distilled water, SDS 5 mM and SDS 10\nmM solutions are shown. (b) Contact angle values against the surface\ntensions of various liquid samples in which the contact angle results\nwith EtOH and PEG solutions are plotted along with SDS solutions.\nThe contact angle test was conducted on the same SPNC surface with\nthree fixed locations to apply the droplet and average values are\ntaken. Error bars show 3δ of results from different locations. The contact angles are plotted against the surface\ntension of various\nliquids in Figure 4 b, in which EtOH and PEG solutions are both included. Figure 4 b reveals that the surface\ntension decrease causes an increase in wettability (i.e., decrease\nin contact angle) for a given surface. This has been shown previously\nin the literature not only for surfaces focusing on superhydrophocity 42 but also surfaces with contact angles of <90°. 43 It is also found that contact angle on SPNC\nsurfaces is shown to be more sensitive to surface tension in the hydrophobic\n(90° < θ < 150°) region than in the superhydrophobic\nregion (150° < θ < 180°). Furthermore, the surface\ntension determination on contact angle is consistent with varying\naqueous solutions (EtOH and PEG). As discussed in Section 3.2 , the surface tensions of\nthe PEG solutions are generally constant (±1.2 mN/m). Therefore,\ncontact angles are also constant with different PEG concentrations,\nwhich indicates that the wettability does not change. However, contact\nangles between SPNC surfaces and EtOH solutions decrease significantly\nwith increasing EtOH concentrations ( Figure 4 b). This is due to the fact that the addition\nof ethanol to water decreases the surface tension and, thus, gives\nrise to an increase wettability of the current surfaces. Other studies 44 − 46 have previously reported that the wettability of SHO surfaces are\nincreased and the surfaces more easily wet by ethanol–water\nsolutions than by water alone. SPNC surfaces behave as either superhydrophobic\nor hydrophobic for all the prepared liquids. Therefore, we would expect\nthe surfaces to reduce drag in aqueous liquid flow and exhibit a nonzero\nslip length. 3.4 Surface Tension Dependence\nof Slip Length SDS solutions were applied on the same SPNC\nsurface for slip-length\nmeasurement, and the results are plotted in Figure 5 . Consistent with surface tension and contact\nangle results, the slip length showed a distinctive decreasing trend\nwhen SDS concentrations were smaller than the CMC (1–7 mM),\nbecoming approximately constant between 7 and 10 mM, which is above\nthe CMC ( Figure 5 a).\nAlthough a few studies 6 , 47 already stated that high contact\nangle does not necessarily mean a large apparent slip, the slip length\n(as an indicator of drag reduction) and contact angle (as an indicator\nof wettability) results have a strong relationship on the present\nSPNC surfaces. Figure 5 a also implies that a Cassie wetting state can be achieved even though\ncontact angles are no longer strictly in the SHO region (i.e., <150°),\nsince the surfaces are still drag-reducing (exhibiting certain slip-lengths)\nwith SDS concentrations larger than 4 mM (above which contact angles\nare lower than 150°, as shown in Figure 4 a). An expanded view in Figure 5 a shows that the “trace”\namount of surfactant does not reduce significantly the slip length\nas the difference is within the measurement uncertainty. However,\nthe surface tension of these two liquid samples showed a measurable\ndecrease from water ( Figure 3 a). This demonstrates for these surfaces that slip-length\nis not significantly affected by “trace” amounts of\nsurfactants, even though surface tension is measurably lower. It was\nshown in a recent study that the slip length could be decreased by\nthe surface tension gradient-induced Marangoni force in the circumstances\nwhere water has been slightly contaminated by surfactant. 21 Our current results are not in accord with this.\nOne of the major reasons for this difference could be that an irregularly\nstructured SHO surface was used here, whereas in ref ( 21 ), a regular topology of\nrectangular gratings was used. Therefore, in this case, the surfactant\nparticles are not able to accumulate such that preferential surface\ntension gradients are formed over the topography and Marangoni stresses\nare, therefore, not significant. Figure 5 Slip-length measurement on SPNC surfaces\nwith varying SDS solutions.\n(a) Slip-length results against SDS concentration. The expanded graph\nshown in panel (a) provides the slip-length values for distilled water\n(blue filled circle and dashed line, the gray region represents the\nerror of repeats) and “trace” amount of SDS solutions.\n(b) Slip-length results against the capillary length and surface tension\n(as an inset) of various SDS solutions. The fitting lines show a clear\nlinear relationship between slip-length and capillary length/surface\ntension. The plot with capillary length shows a slightly better linear\nfit than the inset one with surface tension. Error bars represent\nthe variations of repeats (3δ). According to eqs 2 and 3 , slip length is predicted\nto be linearly\nproportional to the thickness of the air layer ( l air ) at a given viscosity ratio (μ l /μ air ). Since liquids with relatively lower surface tension can\nenter the microstructure of SHO surfaces more easily 20 and the meniscus/stability of the air pockets is dependent\nprimarily on the surface tension 48 (or,\nin nondimensional terms, the capillary number 49 ) of the liquid, we make the assumption that the surface tension\nof a liquid has a positive relationship with l air . Therefore, the slip length is assumed to be linearly proportional\nto the so-called capillary length (λ c ) which is determined\nby mass density and surface tension as 8 where\nγ is the surface tension of the\nliquid, ρ the mass density of the liquids, and g the gravitational acceleration. 50 λ c is an approximate length scale in a fluid/fluid interface,\nbelow which surface tension is able to play a role. 51 As shown in Figure 5 b, a linear fit with R 2 = 0.96\n( R 2 is a statistic used to quantify the\n“goodness-of-fit” and ranges from 0 to 1 52 ) was obtained between the measured slip-length\nand capillary length. For comparison, slip lengths are also plotted\nas a function of surface tension and are shown in the inset of Figure 5 b (linear fit with R 2 = 0.95). Obviously, a larger capillary length\n(or a higher surface tension) results in a larger slip length. This\nresult is in contradiction with a previous study 20 in which a lower surface tension (i.e.,\nsmaller capillary length) was claimed to give a higher slip length. However, in their study, 20 the viscosities of the liquids, which should also play a key role\non the slip length, were not kept constant when the effect of surface\ntension was studied as has been ensured here. It is this lack of isolation\nof the effect of surface tension from that of viscosity which gives\nrise to this contradictory result. From a fundamental perspective,\nthe formation of the trapped air (“plastron”) requires\na rough surface and a liquid with certain surface tension. A higher\nsurface tension has a tendency to increase the volume of trapped air\n(i.e., decrease the contact area between solid and liquid 53 ) and, therefore, results in a larger apparent\nslip length. We note that the actual slip length measured is only\non the order of a few percent of the magnitude of the capillary length.\nAdditionally, the minimum slip length in this study was found to be\n40 μm at a capillary length of 2 mm. This value of slip length\nis still comparably high, compared with our estimate for its uncertainty\n(±17 μm, see the uncertainty analysis of slip length in Section S6 in the Supporting Information). Thus,\nthe surface tension of liquids are confirmed to have a direct impact\non the slip length of SPNC surface and the surfaces are capable of\nreducing drag even with surfactant-contaminated water. 3.5 Shear Viscosity Dependence of Slip Length To solely\nstudy the shear viscosity dependence of slip length,\nsurface tension impacts were eliminated by matching with different\nliquids of equivalent surface tension but differing viscosity. Two\nsets of slip-length tests were conducted with the surface tension\nmatched EtOH/SDS and PEG/SDS (i.e., the slip-length results from the\nindividual liquids were paired with fluids with identical surface\ntension), fluid pairs respectively (see Figure 6 ). The raw slip-length results shown in Figures 6 b and 6 c were processed into a nondimensional quantity R b – 1, which represent the slip-length ratio of\ntwo liquids (with the matched surface tension) minus one. Meanwhile,\nthe viscosity ratio minus one ( R μ – 1) was calculated for the same paired liquids. Shown in Figure 6 a is the relationship\nbetween R b – 1 and R μ – 1, and a linear fitting line ( R b – 1 = k ( R μ – 1), k = 0.34) is presented\nas well. All the data points overlap with the fitting line within\nthe experimental uncertainty. Therefore, the slip length is also revealed\nto be linearly proportional to the shear viscosity over SPNC surfaces\nwhen surface tension differences are properly taken into account. Figure 6 a also implies that\nthe slip lengths increase with the increasing viscosity of the liquid\nbecause a higher liquid viscosity results in a higher μ l /μ air , as described in eqs 2 and 3 . Furthermore,\nincreasing the viscosity has less impact on slip length than in the\nlimited results of Choi and Kim 18 and Ahmmed\net al., 19 as doubling the viscosity only\nresults in a 34% increase in slip length (the slope of the fit shown\nin Figure 6 a is 0.34).\nBoth studies 18 , 19 reported that an ∼2.5-fold\nincrease in viscosity will lead to the slip length increasing by a\nfactor of ∼2.5 with the same measurement technique but different\nSHO materials and microgeometries. Their results are consistent with\nthe simplistic theoretical prediction ( eqs 2 and 3 ), as the slip-length\nratio should be equal to the viscosity ratio. 33 (However, more involved theoretical predictions that allow spatially\ndependent partial slip, 34 indicate a potential\nsaturation of the local slip lengths or, including meniscus curvature,\nexhibit more complex variations with viscosity contrast: 54 a lack of detailed surface topology information\nprecludes a more detailed comparison to these interesting theoretical\nstudies here). However, in their studies, only slip lengths of 10–30\nμm with water were obtained, which is close to the sensitivity\nof the rheometer system used 55 (we estimate\nour uncertainty to be ±17 μm). We note that the surface\ntension of the liquids used in Choi and Kim 18 and Ahmmed et al. 19 could have also influenced\nthe slip length, but this effect was not considered in both papers\n(the increased viscosity fluids in these studies have lower surface\ntensions than water and so the “true” influence of viscosity\nalone would be greater than linear). In the current study, the minimum\nslip length of the PEG experiments was measured to be 86 μm\n( Figure 6 c) and the\nsurface tension of liquids was controlled to be constant for a fair\ncomparison. This is significantly bigger than our uncertainty in slip-length\nestimation (which is ∼20 μm). Meanwhile, a very consistent\ntrend was obtained from the results of both EtOH/SDS and PEG/SDS.\nTherefore, it is concluded that the dependence of slip length on shear\nviscosity does exist with this irregularly structured SPNC surface,\nbut it is lower than the prediction of the idealized view encapsulated\nin eqs 2 and 3 . Figure 6 Slip-length measurement on SPNC surfaces with matched\nfluid samples\nto keep the surface tension constant. (a) Slip-length ratio minus\none ( R b – 1) versus viscosity ratio\nminus one ( R μ – 1) when the\nsurface tensions are matched. A linear fit ( R 2 = 0.95) with slope k = 0.34 is shown in\npanel (a), by forcing the intercept to be 0. The slip-length ratio\nand viscosity ratio for EtOH/SDS are calculated by the results of\nfour concentrations of EtOH solutions divided by the results of four\ncorresponding concentrations of SDS solutions ( Figure 3 b), whereas for PEG/SDS, the slip length\nand viscosity ratio are calculated by the results of three concentrations\nof PEG solutions divided by SDS 0.75 mM ( Table 1 ). The original slip-length data of (b) EtOH/SDS\nand (c) PEG/SDS are presented as well. The error bar in panel (a)\nshows the maximum range for viscosity ratio and slip-length ratio\n(a detailed calculation method can be found in Section S7 in the Supporting Information). Error bars in panels\n(b) and (c) represent the variations of repeats (3δ)."
} | 7,442 |
28644472 | null | s2 | 3,135 | {
"abstract": "The diverse structure and regulated deformation of lipid bilayer membranes are among a cell's most fascinating features. Artificial membrane-bound vesicles, known as liposomes, are versatile tools for modelling biological membranes and delivering foreign objects to cells. To fully mimic the complexity of cell membranes and optimize the efficiency of delivery vesicles, controlling liposome shape (both statically and dynamically) is of utmost importance. Here we report the assembly, arrangement and remodelling of liposomes with designer geometry: all of which are exquisitely controlled by a set of modular, reconfigurable DNA nanocages. Tubular and toroid shapes, among others, are transcribed from DNA cages to liposomes with high fidelity, giving rise to membrane curvatures present in cells yet previously difficult to construct in vitro. Moreover, the conformational changes of DNA cages drive membrane fusion and bending with predictable outcomes, opening up opportunities for the systematic study of membrane mechanics."
} | 257 |
38132766 | PMC10744690 | pmc | 3,136 | {
"abstract": "Microorganisms are an important component of global biodiversity and play an important role in plant growth and development and the protection of host plants from various biotic and abiotic stresses. However, little is known about the identities and communities of endophytic fungi inhabiting cultivated medicinal plants in the farmland ecosystem. The diversity and community composition of the endophytic fungi of cultivated medicinal plants in different hosts, tissue niches, and seasonal effects in the farmland of Northern China were examined using the next-generation sequencing technique. In addition, the ecological functions of the endophytic fungal communities were investigated by combining the sequence classification information and fungal taxonomic function annotation. A total of 1025 operational taxonomic units (OTUs) of endophytic fungi were obtained at a 97% sequence similarity level; they were dominated by Dothideomycetes and Pleosporales. Host factors (species identities and tissue niches) and season had significant effects on the community composition of endophytic fungi, and endophytic fungi assembly was shaped more strongly by host than by season. In summer, endophytic fungal diversity was higher in the root than in the leaf, whereas opposite trends were observed in winter. Network analysis showed that network connectivity was more complex in the leaf than in the root, and the interspecific relationship between endophytic fungal OTUs in the network structure was mainly positive rather than negative. The functional predications of fungi revealed that the pathotrophic types of endophytic fungi decreased and the saprotrophic types increased from summer to winter in the root, while both pathotrophic and saprotrophic types of endophytic fungi increased in the leaf. This study improves our understanding of the community composition and ecological distribution of endophytic fungi inhabiting scattered niches in the farmland ecosystem. In addition, the study provides insight into the biodiversity assessment and management of cultivated medicinal plants.",
"conclusion": "5. Conclusions This study found that the endophytic fungal taxa and communities have host (species identities and tissue niches) and season preference patterns, and endophytic fungi assembly was shaped more strongly by host than by season, which indicated high heterogeneity for endophytic fungi associated with cultivated medicinal plants in farmland environment. The results showed that endophytic fungal communities were mainly composed of Dothideomycetes and Pleosporales. Network analysis showed that the fungal network connectivity was more complex in the leaf than in the root, and the interspecific relationship between endophytic fungal OTUs in the network structure was mainly positive rather than negative. The functional prediction of fungal communities associated with medicinal plants showed that there were three trophic groups, pathotroph, symbiotroph, and saprotroph. In addition, from summer to winter, pathotroph in the root decreased, and saprotroph increased, while both pathotroph and saprotroph in the leaf increased. This study adds to our understanding of endophytic fungal communities and distribution in cultivated medicinal plants and provides insight into the biodiversity assessment and management in the farmland.",
"introduction": "1. Introduction Endophytic fungi, which are distributed in plants within a wide range of habitats, are a group of microorganisms that exist inside healthy plant tissues without causing obvious disease symptoms to the host plants [ 1 , 2 , 3 ]. Endophytic fungi are capable of promoting plant growth, modulating plant development, and protecting host plants from a wide variety of biotic and abiotic stresses [ 4 , 5 ]. Some studies reported that the composition and distribution of endophytic fungal communities vary with plant species and ecological environment [ 6 , 7 , 8 , 9 ]. For example, the operational taxonomic unit (OTU) richness and community structure of leaf endophytic fungi were found to be related to plant identity [ 10 ]. Previous studies have documented that certain fungal genera, including Balansia , Balansiopsis , Atkinsonella , and Echinadothis , predominantly inhabit warm-season grasses, whereas Acremonium primarily colonizes cool-season grasses [ 11 ]. Different orchid plants within a shared habitat exhibit distinct preferences and prioritize specific symbiotic fungi [ 12 ]. Furthermore, the distribution of endophytic fungi in desert plants showed obvious differentiation in root, stem, and leaf tissues [ 13 ]. Sun et al. [ 14 ] confirmed that the host and tissue effects were remarkable in endophyte community assembly, but the host effect was stronger than the tissue effect. Photita et al. [ 15 ] found that the diversity of endophytic fungi was mainly affected by the season, precipitation, and average temperature. Kumar and Prasher [ 16 ] found that the endophytic fungal species diversity of Dillenia indica was the lowest in the winter and highest in the rainy season. According to Martins et al. [ 17 ], the fungal diversity of olive trees was higher in the roots than aboveground, and it was higher in spring than in autumn. However, most recent research has focused on the changes in endophytic fungal communities during seasonal turnover in only one plant niche. In addition to host and environmental factors, plant microbiome construction and balance were found to be positively influenced by microbial interactions [ 18 , 19 ]. The co-occurrence network could be applied to characterize potential microbe–microbe interactions across different habitats [ 20 , 21 ] and to probe the characteristics of keystone OTUs and determine their importance in the community [ 22 ]. Zuo et al. [ 13 ] analyzed the microbial co-occurrence network in the roots, stems, and leaves of desert plants, where it was found that the interspecific connectivity of the root fungal network was the highest, whereas Hypocreales, as a critical taxon, participated in connecting above ground and underground fungal networks. Xiong et al. [ 23 ] demonstrated that rare taxa were prominently in the fungal networks and ecosystem functions (such as soil enzyme activities and crop yield). These results enhance our comprehension regarding the process of plant mycobiome assembly as well as highlight the critical role of certain species in maintaining the stability of plant microbial communities. However, our understanding of the co-occurrence network of endophytic fungi in different tissues of cultivated medicinal plants in farmland with frequent agricultural activities is limited, and research is needed to provide new insights into the interaction of fungi in the aboveground and belowground environments. The endophytic fungi possess a high degree of genetic and functional diversity and endow various types of resistance and rich evolutionary pathways on plants. They influence plant growth, development, reproduction, host structure, as well as biodiversity [ 24 ]. Zhang et al. [ 25 ] found that the rhizomes of Ligusticum chuanxiong contain a high proportion of plant pathogens and that these fungal groups may also possess other physiological functions that are still to be discovered. Most of the endophytes of the three varieties of tobacco seeds were defined as pathogens. When the seeds leave the plant, they are sometimes rotten or mildewed under certain conditions. This finding also confirmed that many plant pathogens can grow in the nutritional manner of endophytes but never cause disease symptoms in the host, and the functions change across the different growth periods of plants [ 26 ]. Referring to the potential functions of endophytic fungi, especially whether host and external factors affect the nutritional functions of fungi, it is helpful to comprehensively explore the diversity of endophytic fungi and to tap into their resources. The Anguo Medicine Planting Site is a typical farmland ecosystem. Some medicinal plants developed a symbiotic relationship with a variety of microorganisms [ 27 ]. However, little is known about how host species, tissue niches, and environmental factors interactively drive the assembly of endophytic fungi. In the present study, the endophytic fungi of five cultivated medicinal plants ( Bupleurum chinense , Astragalus membranaceus , Salvia miltiorrhiza , Lonicera japonica , and Atractylodes lancea ) in the Anguo Medicine Planting Site were selected. Furthermore, the dynamics of endophytic fungal communities in a total of 240 samples under different plant species, tissue niches (root and leaf), and seasonal alternations (summer and winter) were investigated using next-generation sequencing. We aimed to reveal the following: (1) if and how diverse endophytic fungal communities exist in cultivated medicinal plants in farmland environments; (2) their composition and distribution among different host plants, tissue niches, and seasons if present; and (3) whether endophytic fungi interact and what their functional importance is in ecological processes and the local environment. We aimed to understand the host–microbe relationship in cultivated plants and provide a basis for biodiversity evaluation and management of the farmland. These objectives were achieved by determining the endophytic fungal community composition, interactive relationships, and ecological functions in medicinal plant cultivation.",
"discussion": "4. Discussion 4.1. Taxonomic Characteristics of Endophytic Fungi In the present study, 1256 OTUs of endophytic fungi belonging to 10 phyla were recovered from all the samples. In detail, Ascomycota were the most abundant, and a few were Basidiomycotina. The dominant classes and orders were Dothideomycetes (28.65–52.15%) and Pleosporales (12.68–31.01%). Ascomycota members are saprophytic, promoting nutrient recycling in farmland. Studies of endophytic fungi, based on culture-dependent molecular approaches, showed that Alternaria sp. and Chaetomium sp. were dominant fungi in L. japonica [ 39 ], Alternaria alternata and Chaetomium sp. were dominant fungi in B. chinense [ 40 ], and Alternaria sp. and Aspergillus sp. were dominant fungi in S. miltiorrhiza [ 41 ]. This finding suggests that notable variations exist in the dominant fungal species across various plant species. This finding aligns with Whitaker’s study, which indicated notable variations in endophytic fungi among host species and host populations within 18 species of Asteraceae at a specific site. However, no distinctions were observed between host subfamilies [ 42 ]. Here, Hypocreales were distributed mainly in summer and dominated the endophytic fungal network in summer. Studies on the endophytic fungal communities of mulberry ( Morus spp.) in different seasons (spring/autumn) showed that the spring samples harbored higher Hypocreales taxa [ 43 ], which could preliminarily predict that the abundance of Hypocreales taxa was lower in the colder autumn and winter. The members of Dothideomycetes were mainly distributed above ground; similarly, previous studies have also shown that Dothideomycetes were the most dominant fungal group above ground [ 44 ]. In addition, Dothideomycetes were identified as saprophytic fungi that play a role in xylem and deciduous layer decomposition and material cycling [ 45 ]. Capnodiales were distributed and also dominated the endophytic fungal network in the leaf. Capnodiales belong to leaf surface saprophytes, which affect host photosynthesis because of shading. However, Capnodiales, as plant endophytes, generally do not cause disease in their hosts and even have positive effects, such as growth promotion and pest resistance [ 46 ]. OTU885 ( Cercospora sp.), which had a higher proportion of fungi common to the five plants, was also a key species in the fungal network. Ascochyta blight has long been a cercospora leaf spot and has become more common in recent years [ 47 ]. The possible benefits of Cercospora sp. for the host plant remain to be analyzed. 4.2. Host and Seasonal Variation Influence Diversity of Endophytic Fungal Communities The alpha diversity, niche breadth, and unique fungal OTUs of endophytic fungi in the roots were greater than those in the leaves. This may be due to microbial communities colonizing the roots and being transported to above ground. Previous studies have confirmed that microbial communities of plants are gradually filtered from non-rhizosphere soils, rhizoplane roots, the endosphere, the phylloplane, and the leaf endosphere [ 10 ]. Some studies have also shown that different microbial communities in aboveground and belowground plant tissues may originate from vertical transmission from seeds to seedlings [ 48 ]. However, in winter, the endophytic fungal richness and diversity of leaf tissue were higher than those of root tissue. As endophytic fungal species may reproduce in harsh environments (such as the leaf layer), fungal communities in aboveground tissues have a greater degree of coexistence due to stress tolerance [ 49 ]. Leaves can be colonized by airborne spores, whereas roots mainly colonize through inoculum in nearby soil. In winter, the rhizosphere environment conditions were more uniform and stable than those above ground, which may be one of the reasons for the lower species richness and diversity in the root. Researchers reported that various bacterial and fungal genera show significant preferences for different host types [ 50 ]. For example, Ferrimicrobium tends to colonize non-mycorrhizal plant tissues [ 51 ], while Nigrospora is more likely to appear on ectomycorrhizal plant leaves [ 52 , 53 ]. These confirm that host selection (i.e., plant species and tissue niche) dominates in shaping the plant microbiome assembly. Compared with plants in summer, plants in winter have a richer endophytic fungal OTU. Previous studies of rice ( Oryza sativa ) have also yielded the same results [ 54 ]. Numerous studies have shown that seasonal variations in climate (e.g., temperature, precipitation) have a remarkable impact on the diversity of aboveground fungal communities. Furthermore, seasonal changes affect the change in the ecosystem environment, leading to differences in the photosynthetic rates of host plants and their nutrient acquisition in the soil, thereby affecting the composition of the fungal community structure. As such, broad-scale environmental controls (e.g., temperature and precipitation) are the driving forces of the fungal communities [ 55 , 56 ]. Meteorological data show that, compared with May and June, October and November have lower temperatures (0 to 6 °C), lower rainfall (6.1 to 12.2 mm), and higher humidity (67% to 79%). Plant residues are the main source of primary inocula for plant fungal infections. When the air is moist and precipitation is low, fungi preferentially germinate spores on plant residues [ 57 ]. 4.3. Host and Seasonal Variations Drive the Distribution of Endophytic Fungal Communities Studies have shown that the construction of the plant microbiome is primarily determined by tissue niches and host species. The endophytic microbiome assembly is shaped more strongly by the host than by seasonal factors, according to our results. Similarly, studies on desert plants have shown that the distribution of endophytic fungi in different host plants is characterized by high heterogeneity and dispersion [ 13 ]. Some previous studies on the root and aboveground zonal microbiomes of poplar and sugarcane revealed that different tissue niches (i.e., roots or leaves) contain different microbial communities [ 7 , 8 ]. The endophytic fungal communities of the root or leaf also differ significantly between summer and winter. For example, the abundance of the rhizosphere microorganisms is climate-dependent; it is also worth noting that Pseudomonadaceae has a negative-feedback effect on long-term precipitation [ 58 ]. Hernández-Tasco conducted an evaluation of the microbial diversity, behavior, and frequency of endophytic fungi in the leaves of S. magnifica , S. schiffneri , and S. speciosa over a span of three years. The study revealed that both the year and season exerted a substantial influence on the abundance of fungal genera in plant leaves. Furthermore, in comparison to species-related factors, the α and β diversity indices were found to be more strongly affected by the year [ 59 ]. The microbial community in this coniferous forest was also shown to vary seasonally, and plant photosynthesis appeared to be a major driver of seasonality [ 60 ]. Thus, we can conclude that plant microbial communities also demonstrate the capability to vary across seasons, possibly owing to the seasonality of precipitation and temperature. LEfSe analysis and differential species analysis verified the occurrence patterns of the endophytic microbiome structure. Furthermore, it was also determined that they were different in different plants, tissue niches, and seasons, thereby indicating that endophytic fungi have certain host preferences and organ/tissue specificity [ 61 ]. This result was consistent with the assumptions that this may be a result of different species pools in different habitat regions, as well as their niche assignment, because of differences in microbial life histories. With the turnover of seasons, the endophytic fungal flora changed in the root and leaf. A total of 15 species were evidently different between summer and winter in both the root and leaf, but these fungi were not the different species that were among the five plant species. Similar studies confirmed this conclusion, whereby endophytic fungi, in great measure, exhibit an “only” tissue preference [ 62 ]. 4.4. Host and Seasonal Selection Affect the Co-Occurrence Network Complexity of Endophytic Fungi There are various ecological relationships between microorganisms, ranging from mutualism to competition, that, in addition to niche preferences, shape differences in microbial abundances. Recently, the network technique has been frequently used in microbial studies as an important means by which to identify keystone species that maintain network stability and complexity [ 63 ]. Species in the community interact with each other through relationships (such as predation, competition, and mutualism) and are interconnected to form a network. Co-occurrence networks can be used to study the reasons for the presence of certain microorganisms in the same tissue, as well as to statistically identify the highly connected taxa in the community and screen out key microbial groups in the community [ 64 , 65 ]. Research studies have employed this methodology to identify the co-occurrence patterns among microbial communities. For instance, Sun et al. [ 66 ] conducted a study examining the carbon and nitrogen cycling genes within soil microbial networks in Tibet and a control group. The researchers discovered notable disparities in the key genes (module hubs and connectors) between the grazing conditions and the control group. Hu et al. [ 67 ] discovered that the implementation of long-term mulching fosters synergistic relationships among species within bacterial and fungal symbiotic networks, thereby mitigating interspecies competition. The results of the co-occurrence network analysis demonstrated that the composition of the networks differed between the plant species and tissue niches. In one study, the phylloplane and rhizoplane were found to act as a bridge for the interaction between the host and the environment [ 68 , 69 ]. The study showed that the aboveground endophytic fungal networks are more powerful and stable than the belowground farmland ecosystems. Different from desert habitats, the close fungal interactions in the root may be associated with strategies for desert plants to adapt to arid environments [ 13 ]. We speculated that the complexity of the belowground microbial network was relatively low despite the rich diversity of the root microbial community because of the high yield and volatility of the farmland ecosystem. We found that the endophytic fungal flora of medicinal plants was mainly positively correlated, which proved that the endophytic fungi in the farmland were more mutualistic with each other. However, we also found that the negative edges of the co-occurrence networks gradually increased from the aboveground to belowground niches, which meant that the endophytic fungi increased competition in the aboveground niche. When leaves are exposed to sunlight, photosynthesis may promote endophytic fungal interactions. It has also been proposed that competitive microbial interactions can have a positive impact on microbiome stability [ 70 , 71 ]. Different plants have their own unique microbial communities. Studies have found that there is a “core microbiota” under the functional redundancy of plant-related microbiota, which, as a subset of the plant microbiota, carries genes essential for host health [ 72 ]. The dominant taxa and biomarkers, as potentially keystone taxa, are important in terms of in-microbiome assembly and ecosystem functions [ 73 ]. In this study, the potential keystone taxa were preliminarily identified according to the node connectivity coefficient (degree) of the network. The network structure of the endophytic fungal community changed little between the seasons, but the keystone taxa in the network changed significantly. The Capnodiales, Helotiales, Pleosporales, Venturiales, Hypocreales, Chaetothyriales, and unclassified Glomeromycota formed the core fungal group in the endophytic fungal network of the medicinal plants. It is worth noting that Capnodiales are the dominant taxa in the leaves, but Glomerales do not have a high relative abundance in the roots. Similarly, Helotiales, Venturiales, Chaetothyriales, and unclassified Glomeromycota were very low in abundance in the plants. Studies have shown that this does not contradict the concept that dominant taxa affect the function of microbial communities because of their high abundance, while keystone taxa may be able to selectively alter other members. Therefore, regardless of its abundance, it can exert its impact [ 45 ]. Taken together, these results suggested that plant compartments may provide different niches for specific microbiota. They can recognize signaling molecules and adapt the immune system in each niche [ 74 ]. The LEfSe analysis showed that Cercospora , unidentified Didymerllaceae , unidentified Ascomycota , Verticillium , and unidentified Mycophaeosphaeria were the indicator taxa of S. miltiorrhiza , L. japonica , B. chinense , A. membranaceus , and A. lancea , respectively. Combined with the previous results, these taxa have a high abundance in individual plants, and they may play a key role in regulating the host adaptation, inhibition of pathogens, and plant tolerance to stress, such that the indicator biota of each plant is regarded as one of their “core microbiota”. As such, these endophytic fungi are regarded as potential keynote taxa of the Anguo Medicine Planting Site. 4.5. Host and Seasonal Variation Affect the Ecological Functions of Endophytic Fungi The endophytic fungal community was mainly composed of pathotrophs and symbiotrophs. This indicates that endophytic fungi might first reduce the impact of plant immunity on themselves through pathological characteristics and then co-exist with host plants and exchange resources with hosts in order to obtain nutrients. However, the endophytic fungal community of A. lancea was mainly composed of pathotrophs and saprotrophs, which might obtain essential nutrient resources for the purposes of survival by degrading plant root and leaf epidermal cells with the help of saprophytic characteristics, as well as then promoting the growth of A. lancea through mutual symbiosis and interactions between microorganisms. The abundance of 23 ecological guilds varied among the endophytic fungi in the different plants, among which the ectomycorrhizal and undefined saprotroph differed the most among the five species, thereby indicating that the fungal communities performed different ecological functions in the different plants. In the ecological guilds, we found orchid mycorrhizal, endomycorrhizal, arbuscular mycorrhizal, root-associated biotroph, ectomycorrhizal, etc. This has potential application value in promoting the growth of medicinal plants and improving secondary metabolites [ 75 , 76 ]. In farmland ecosystems, seasonal change is one of the factors that contribute to the functional transformation of the endophytic microbiome of medicinal plant tissues. From summer to winter, the saprotroph of endophytic fungi increased in the root and leaf. A similar phenomenon was also found in the deciduous temperate forests; that is, the rot taxa of the saprotrophic reached their seasonal maximum on the freshly fallen litter in autumn [ 60 ]. In addition to the saprotrophs, the pathotrophs of the endophytic fungi in the leaf also increased, which is consistent with previous studies—that is, when the balance between the host and endophytic fungi is destroyed, endophytic fungi may become saprophytic or pathogenic [ 77 ]. This may be due to leaves becoming senescent in winter, whereby the plant defense system is broken down and the fungus is able to acquire nutrients more easily and thus colonize plant tissues more widely. In this way, endophytic fungi may manifest as saprophytes [ 78 ]. Alternatively, necrotrophic fungi become pathotrophs by killing the host and later obtaining nutrients from inside cells [ 79 ]. In conclusion, the host and season drive the functional transformation of endophytic fungal communities in medicinal plants, and through the selection of a microbial community structure and function, medicinal plants can become tenacious."
} | 6,469 |
27270788 | PMC4895234 | pmc | 3,137 | {
"abstract": "A continuous stirred microbial electrochemical reactor (CSMER), comprising of a complete mixing zone (CMZ) and microbial electrochemical zone (MEZ), was used for brewery wastewater treatment. The system realized 75.4 ± 5.7% of TCOD and 64.9 ± 4.9% of TSS when fed with brewery wastewater concomitantly achieving an average maximum power density of 304 ± 31 m W m −2 . Cascade utilization of organic matters made the CSMER remove a wider range of substrates compared with a continuous stirred tank reactor (CSTR), in which process 79.1 ± 5.6% of soluble protein and 86.6 ± 2.2% of soluble carbohydrates were degraded by anaerobic digestion in the CMZ and short-chain volatile fatty acids were further decomposed and generated current in the MEZ. Co-existence of fermentative bacteria ( Clostridium and Bacteroides , 19.7% and 5.0%), acetogenic bacteria ( Syntrophobacter , 20.8%), methanogenic archaea ( Methanosaeta and Methanobacterium , 40.3% and 38.4%) and exoelectrogens ( Geobacter , 12.4%) as well as a clear spatial distribution and syntrophic interaction among them contributed to the cascade degradation process in CSMER. The CSMER shows great promise for practical wastewater treatment application due to high pre-hydrolysis and acidification rate, high energy recovery and low capital cost.",
"discussion": "Results and Discussion Electricity generation from brewery wastewater The CSMER operated at a hydraulic retention time (HRT) of 12 h with external resistance fixed at 10 Ω during the three experiment phases. Since the system had already run for 120 days with synthetic wastewater, current output of each cell reached to 17.8 ± 1.5, 17.6 ± 1.4, 16.4 ± 1.9 and 18.1 ± 1.6 mA immediately after it was fed with the influent containing 30% (V/V, in volume) brewery wastewater in Phase I. As the brewery wastewater concentration gradually increased from 30% to 100%, a reduction of 31.2% in mean current output was observed, with each cell stabilized at 12.8 ± 2.0, 11.4 ± 1.5, 10.6 ± 1.4 and 13.2 ± 1.2 m A in Phase III ( Table S1 ). The reduction in current might be caused by more total suspended solid (TSS) contained in the influent, which increased from 451 ± 78 mg L −1 in Phase I to 1546 ± 136 mg L −1 in Phase III. Various colloidal particulates in the real wastewater would have negative effects on electricity generation as they are the main rate-limiting and resistance-increasing factors 18 . Based on polarization data, the maximum power densities for each cell of the CSMER were 536 ± 9, 519 ± 18, 512 ± 23 and 541 ± 22 mW m −2 in Phase I ( Fig. 1a ). They also exhibited a decline trend as the brewery wastewater concentration increased, which were 313 ± 32, 289 ± 34, 273 ± 14, 344 ± 31 mW m −2 in Phase III ( Fig. 1c ). The slight differences in power generation of the four cells in the same phase were mainly caused by cathode according to the polarization curves, while insignificant change of anode potential was expressed ( Figure S1 ). Nonuniform biofilm formation or salt precipitation on the cathode might lead to different cathode performance 19 . The mean maximum power density achieved by CSMER was 1.5 times higher of a single-chambered, air-cathode MES (205 m W m −2 ) fed with brewery wastewater 11 . This could be due to the syntrophic processes that occurred in the CSMER, in which better-utilizable substrates for electricity generation were provided through pre-hydrolyzing and acidifying complex organic substrates in brewery wastewater. Coulombic efficiency (CE) was 1.5 ± 0.5% based on TCOD consumed in the whole CSMER, which calculated to be 4.3 ± 0.9% based on TCOD consumed in the microbial electrochemical zone (MEZ). This value was generally in agreement with other MESs tests using real wastewater 20 . The low CE could be related to interference of fermentation, methanogenesis and other biological processes in microbial electrochemical zone (MEZ), which were non-electricity production processes and eventually decreased the CE 21 . Suppression of methanogens without affecting exoelectrogens is of great importance for improving CE. Operating the CSMER under a lower external resistance or in open-closed circuit regimes could be a way to avoid CE losses to methanogenesis 22 . In addition, reduction of oxygen diffusion by employing a separator cathode assembly configuration could prevent aerobic oxidation of COD to some extent 23 . Furthermore, shortening the HRT of MEZ by enlarging the volume ratio of CMZ (complete mixing zone) and MEZ was another way for higher CE 18 . Cyclic voltammetry (CV) was performed on anode biofilm to evaluate its bioelectrocatalytic activity in the three phases. Since anode performance of the four cells was basically the same ( Figure S1 ), CV analysis was only applied to one cell (Cell 1) of the system. In Phase I, significantly high oxidation and reduction peaks were observed in the forward scan of −0.28 V (18.7 mA) and reverse scan of −0.32 V (−2.9 mA) indicating the highest electrochemical activities of anode biofilm in this phase ( Fig. 2a ). The peak current slightly declined to 16.1 mA and 0.9 mA as the brewery wastewater concentration increased from 30% to 60%, which might be caused by a reduction of electrochemically active bacteria cell density on the anode surface due to more refractory organics present in the feed 24 . As the brewery wastewater concentration further increased to 100%, the peak current was similar as that in Phase II, indicating a functionally stable biofilm capable of adapting to complex substrates in brewery wastewater had developed on the anode surface. Pre-hydrolyzing and fermenting complex organic matter to short-chain fatty acids through the CMZ might reduce the inhibition effects of refractory organics on anode biofilm. Electrochemical impedance spectroscopy (EIS) was conducted to determine the resistance of cathode reaction. The Nyquist plots of Cell 1 obtained in each phase indicated that total internal resistance started to increase in Phase II (Variations of the other three cathodes also followed the same trend). The ohmic resistance ( R ohm ) was not significantly changed due to the same system configuration, which was about 5.7 ± 0.3 Ω ( Fig. 2b ). However, the charge transfer resistance ( R c ) and the diffusion resistance ( R d ) increased from 2.7 ± 0.9 to 7.8 ± 1.2 Ω and 3.2 ± 0.6 to 17.6 ± 2.1 Ω as the brewery wastewater concentration increased from 30% to 100%. The increase in R c and R d might be a result of cathode biofouling, which was caused by biofilm formation or salt precipitation on the catalyst layer of cathode and consequently increased proton transport resistance or decreased oxygen diffusion rate 19 . Employing a separator electrode assembly configuration might be an efficient way to slow down the deterioration process of cathode performance 23 . Organic matter degradation and cascade utilization Removal of COD and SS Effluent total COD (TCOD) and soluble COD (SCOD) of the CSMER were monitored during the three - phase operation period. TCOD removal slightly decreased from 83.2 ± 1.3% to 79.1 ± 3.4% and SCOD removal decreased from 80.0 ± 3.1% to 76.8 ± 3.5% while the percentage of raw brewery wastewater in the feed was increased from 30% to 60%. The system removed 75.4 ± 5.7% of TCOD and 73.1 ± 4.8% of SCOD in Phase III when raw brewery wastewater was used, with a reduction of the TCOD concentration from 3707 ± 220 to 909 ± 296 mg L −1 and the SCOD concentration from 2466 ± 189 to 663 ± 117 mg L −1 ( Table S1 ). Both TCOD and SCOD removal decreased as concentration of raw brewery wastewater kept increasing in the feed, indicating that the performance of CSMER got suppressed due to the induced substrate inhibition 25 . However, treatment efficiency of CSMER was still significantly higher than that of the control CSTR, which removed 47.2 ± 6.9% of TCOD and 38.4 ± 5.1% of SCOD in Phase III, resulting in final concentration of 1946 ± 186 and 1503 ± 230 mg L −1 in the effluent. Suspended solid is an important indicator in biological wastewater treatment. The CSMER reduced 64.9 ± 4.9% of TSS and 72.8 ± 5.2% of VSS in Phase III, resulting in the effluent concentration of 538 ± 64 and 156 ± 50 mg L −1 . Comparatively, the SS concentration in CSTR effluent was 862 ± 79 mg L −1 of TSS and 347 ± 61 mg L −1 of VSS ( Fig. 3 ). In addition, higher methane production rate was obtained in the CSMER (0.41 ± 0.05 L L −1 d −1 ) than that in CSTR (0.25 ± 0.07 L L −1 d −1 ). Though there might be a competition between methanogens and exoelectrogens for the same substrates, interactions between methane production in the CMZ and electricity generation in the MEZ had a positive effect on substrate removal. Continuous methane production could accelerate the acetogenic process, which produced more hydrogen or VFAs. A portion of the VFAs could transfer to MEZ along the hydraulic path, where they were further utilized by exoelectrogens for electricity production. VFAs removal from the CMZ released their inhibition on methanogens, consequently, promoting the organic matter eventual decomposition to CO 2 and H 2 O. Removal of proteins, carbohydrates and VFAs Brewery wastewater is usually comprised of various soluble organic compounds in the form of soluble proteins (s-proteins), soluble carbohydrates (s-carbohydrates) and volatile fatty acids (VFAs). In order to determine the process by which substrates were degraded in CSMER, the composition and concentration of soluble organic matter were detected in brewery wastewater. The CSMER removed 96.3 ± 3.2% of s-protein and 99.1 ± 1.8% of s-carbohydrates. Also, CMZ degraded 79.1 ± 5.6% of s-protein and 86.6 ± 2.2% of s-carbohydrates by anaerobic digestion process with short-chain VFAs as main products, which were regarded easier for exoelectrogens to generate electricity in the MEZ ( Fig. 4a ). The total VFAs concentration first increased to 694 ± 82 mg L −1 in the CMZ effluent then decreased to 257 ± 35 mg L −1 in the final effluent. Ethanol, acetic acid, propionic acid, butyric acid and valeric acid were the main VFAs in raw brewery wastewater. Ethanol was exhausted after the anaerobic digestion in CMZ. The acetic acid kept declining while other VFAs first accumulated in the CMZ and then decreased in the MEZ. Valeric acid accumulated in the largest scope, with an increase in the concentration from 10 ± 1 mg L −1 to 278 ± 31 mg L −1 . Accumulation of propionic and butyric acid were also observed, whose concentrations increased from 53 ± 13 mg L −1 to 166 ± 11 mg L −1 and 34 ± 12 mg L −1 to 87 ± 21 mg L −1 , respectively ( Fig. 4b ). These accumulated VFAs and remaining complex organics (s-protein and s-carbohydrates, 105 ± 36 and 88 ± 9 mg L −1 , respectively) were then utilized in the MEZ for electricity generation, thereby, not only recovering energy but also polishing effluent quality. During the parallel operation of CSTR, though nearly the same s-protein and s-carbohydrates removal efficiencies (98.7 ± 3.8% and 99.6 ± 1.2%, respectively) were achieved, total VFAs concentration in the CSTR effluent was 2.5 times higher than that of CSMER. Concentration of propionic acid, butyric acid and valeric acid significantly increased in the CSTR effluent and few VFAs were removed neither in the bottom nor upper part of CSTR, revealing that degradation in the CSTR was not complete. Detection of hydrogen (0.18 ± 0.04 L L −1 d −1 ) in the CSTR showed that its fermentation pathway was favorable for hydrogen production, consequently, leaving the remainder of organic matter present as VFAs. Spatial distribution of microbial community Bacterial community Pyrosequencing was used to characterize microbial communities in CSMER and CSTR. The five samples taken from CSMER (CSMER CMZ , CSMER Anode and CSMER cathode ) and CSTR (CSTR Bottom and CSTR Up ) yielded qualified sequencing reads in the range of 15453 to 33094, with each sample clustered to more than one thousand operational taxonomic units (OTUs) based on a threshold of 97% ( Table S2 ). CSMER Cathode had the highest diversity (Shannon = 5.95), and was slightly larger than that of CSTR Bottom and CSTR Up (Shannon = 5.89, 5.69), while CSMER Anode had the lowest diversity (Shannon = 4.88). Rarefaction curves showed that new phylotypes would continue to merge even after 20,000 reads, as none of the curves tended to reach a plateau ( Figure S2 ). Coverage value of each sample was more than 0.95, suggesting adequate sampling for the assessment of community composition 26 . Qualified reads retrieved from CSMER CMZ , CSMER Anode , CSMER cathode , CSTR Bottom and CSTR Up were assigned to known phyla, classes and genera ( Fig. 5 ). The five samples mainly belonged to ten phyla, and the majority of phyla were Firmicutes (9.9–46.4%) , Proteobacteria (10.3–42.3%) and Bacteroidetes (8.8–31.3%) ( Fig. 5a ). At the class level, the CSMER CMZ bacterial community was dominated by classes Clostridia (23.3%), Anaerolineae (13.1%), Actinobacteria (12.5%) , Deltaproteobacteria (8.1%) and Bacteroidia (6.4%). The CSMER Anode community composition was different from that of CSMER CMZ , which was dominated by Deltaproteobacteria (35.5%), followed by Anaerolineae (15.9%), Bacteroidia (9.8%) and Clostridia (6.2%). Since most exoelectrogens such as Geobacter belong to Deltaproteobacteria , bacteria attached to anode might be mainly for electricity generation 27 . The cathode of the CSMER mostly reflected Bacteroidia (21.3%), with less amounts of Alphaproteobacteria (14.5%), Betaproteobacteria (10.2%) and Deltaproteobacteria (8.5%). The CSTR Bottom and CSTR Up were possessed of an approximately same structure at the class level with the predominance of Clostridia (30.1%, 28.7%), Bacilli (11.4%, 11.8%), Bacteroidia (11.5%, 10.3%) and Actinobacteria (9.1%, 9.9%) ( Fig. 5b ). Genus level identification allowed us to further examine the reactors performance based on bacterial function ( Fig. 5c ). The most frequently identified sequences in CSMER CMZ were assigned to Clostridium (19.7%), Anaerolinea (12.5%), Brevibacterium (9.9%) and Bacteroides (5.0%). Similarly, Clostridium (19.1%) and Bacteroides (10.3%) were also the two major genera in CSTR Bottom . Certain species of the genus Clostridium , such as Clostridium cellobioparum and Clostridium sufflavum are highly involved in polysaccharides degradation both in laboratory and full-scale anaerobic reactors treating various wastewaters 28 29 . Moreover, Clostridium spp. is a predominant hydrolytic bacterium on the surface layer of brewery-degrading granule 30 . The Bacteroides genus is an important mesophilic fermentative bacterium that play a role in sugar catabolism, with major products of hydrogen, carbon dioxide and lower fatty acids 16 . Apart from Clostridium and Bacteroides , diverse fermentative bacteria including Bacillus , Acetobacterium and Enterococcus also existed in CSMER CMZ and CSTR Bottom 31 32 . These observations suggested that bacterial communities in CSMER CMZ and CSTR Bottom played a key role in the primary hydrolysis and acidification of macromolecular organic compounds, revealing by the fact that most s-protein and s-carbohydrates in brewery wastewater were degraded in the CMZ of CSMER and the bottom zone of CSTR. The CSMER Anode community was most similar to Syntrophobacter (20.8%), Anaerolinea (15.6%) and Geobacter (12.4%), which was much different from that of CSTR Up . Geobacter , which was the most predominant known exoelectrogen, was found present only in CSMER, suggesting that exoelectrogens have a competitive advantage over other bacteria when current was generated 33 . The Syntrophobacter genus is a syntrophic bacteria capable of oxidizing VFAs to formate, acetate and hydrogen, which is always in coculture with hydrogen or formate-utilizing methanogens 34 . The existence of Geobacter would be one reason for more Syntrophobacter presenting in CSMER Anode , since certain species of Geobacter was hydrogen consuming organism 35 36 . The relatively more abundant Syntrophobacter present in CSMER Anode (20.8%) compared with CSTR Up (6.6%) meant that more VFAs could be removed by CSMER, consequently, polishing the effluent quality. Some well-known ammonia-oxidizing bacteria, such as Nitrosomonas and Nitrospira 37 were not detected in CSMER Cathode , consequently, nitrification was rarely detected in the CSMER. This finding was not in accordance with results from previous studies that found the microorganisms on the cathode of a sediment MES participated in ammonia oxidation 38 . Alterations of oxygen level near the cathode surface caused by cathodic oxygen reduction might have impact on microbial community structure. Archaeal community Archaeal community analysis based on alpha diversity resulted in 1388 (CSMER CMZ ), 895 (CSMER Anode ) OTUs for the CSMER, and 1491 (CSTR Bottom ), 1342 (CSTR Up ) OTUs for the CSTR ( Table S3 ). Rarefaction curves based on a 97% similarity also did not reach a plateau ( Figure S3 ). The order level identification of the archaeal community showed that both hydrogenotrophic ( Methanobacteriales , 41.8%) and acetoclastic methanogens ( Methanosarcinales , 41.1%) were abundant in CMZ of CSMER ( Fig. 6a ). However, the CSTR Bottom and CSTR Up were dominated by hydrogenotrophic methanogens ( Methanobacteriales and Methanomicrobiales ). The anode of CSMER mostly reflected Thermoplasmatales (41.9%), with less amounts of Methanobacteriales (36.2%). At the genus level, the predominant genera in CSMER CMZ were affiliated with Methanosaeta (40.3%), Methanobacterium (38.4%) and Thermogymnomonas (13.2%) ( Fig. 6b ). In the CSTR, Methanosaeta was much less abundant in CSTR Bottom and CSTR Up (8.2% and 7.8%), with the main archaeal genera belonging to Methanobacterium (37.9% and 37.1%) and Methanospirillum (22.3% and 23.7%). Since Methanosaeta have been found to dominate under stable reactor with high biogas production rate and methane yield, the high relative abundance of Methanosaeta in CSMER CMZ indicated a favorable operation condition for methane production 39 . These findings were consistent with the higher methane production rate in CSMER compared with CSTR, which might be caused by synergistic effects between microbial communities between CMZ and MEZ. Methanobacterium (30.8%) and Methanosaeta (18.2%) were also observed on anode of CSMER. The co-existence of methanogens and exoelectrogens on anode of MEZ adversely affected electricity production, since methanogenesis diverted energy away from electrogenesis, consequently, reducing CE of the CSMER 22 . The microorganisms in CSMER could be functionally categorized into four groups, including fermentative bacteria ( Clostridium, Bacteroides ), acetogenic bacteria ( Syntrophobacter ), methanogenic archaea ( Methanosaeta and Methanobacterium ) and exoelectrogens ( Geobacter ), which distributed spatially in CMZ and MEZ of the system. The clear spatial distribution and complex syntrophic interactions of these four groups drove the CSMER to cascade degrade a wider range of substrates and exhibit better wastewater treatment efficiency compared with a control CSTR. Firstly, pre-hydrolyzing and fermenting of macromolecular organic compounds by fermentative bacteria in the CMZ were responsible for high power generation obtained in CSMER using brewery wastewater. Effective conversion of the s-proteins and s-carbohydrates contained in brewery wastewater to hydrogen, carbon dioxide and short-chain fatty acids by Clostridium , Bacteroides and other diverse fermentative bacteria in the CMZ was the first step for cascade degradation process. Products of the fermentation stage, such as short-chain fatty acids and amino acids were oxidized to acetate, formate, hydrogen and carbon dioxide by Syntrophobacter , which were better-utilizable substrates that could be further utilized by Methanosaeta and Methanobacterium for methane production, or transferred to MEZ for electricity generation by Geobacter . Secondly, electricity generation by Geobacter in MEZ made the CMZ a more suitable niche for methane production. A large portion of the VFAs produced in the CMZ were transferred to MEZ along the hydraulic path and utilized by Syntrophobacter and Geobacter on the anode of CSMER, consequently, releasing their inhibition on methanogens. Since the removal of VFAs from anaerobic digestion of organic matter could accelerate their eventual decomposition to CO 2 and H 2 O 40 41 , the relatively higher Syntrophobacter and Geobacter in MEZ could contribute to higher methane production rate in CSMER. Actually, real wastewater such as brewery and winery wastewater cannot be efficiently used by exoelectrogens because of a high fraction of particulate and fermentative substrate 14 . Therefore, the co-existence of various functional microbial communities as well as a clear spatial distribution and syntrophic interaction among them were crucial for MES-centered systems towards practical application. Significance of the CSMER for wastewater treatment There have been growing interests in combining AD and MESs for wastewater treatment, due to the complementary synergy between these two processes. However, some studies just connected two individual reactors in sequence without truly integrating them while the CSMER was a truly integrated system by integrating continuous stirred tank reactor (CSTR) and microbial electrochemical system into a single design. TCOD loading rate in the CSMER was 7.4 kg COD m −3 d −1 , which was 2.5 times higher than that of an upflow anaerobic sludge blanket (one of the most effective anaerobic processes for brewery wastewater treatment) 4 . Moreover, TCOD degradation rate in CSMER was 10 times higher than that in a 90-liter stackable baffled MES (0.5 kg COD m −3 d −1 ) 12 . Though the mean electricity output obtained in the 90-liter stackable baffled MES (60 mA) was much higher than that of CSMER (12 mA), energy recovery in the CSMER (0.682 kWh m −3 ) was seven times higher of the 90-liter stackable baffled MES (0.097 kWh m −3 ) because of additional gaseous methane energy recovered by CSMER (detailed calculations in the supporting information ). This fact is important for the application of MES-centered hybrid system in wastewater treatment, because technologies characterized by energy efficient and energy recovery are beneficial for environmental sustainability. Though several MES-centered hybrid systems have been previously reported, the CSMER held distinct advantages on the basis of capital costs, wastewater treatment and electricity generation ( Table 1 ). Firstly, poor economic viability was preliminarily resolved in CSMER due to its membrane-less design compared with SMFC, UMFC and AFB-MFC 42 43 44 . Capital cost was further reduced by using rolling-pressed activated carbon cathode, which was much cheaper than platinum-coated carbon cloth cathode 45 46 . Furthermore, attributed to the addition of anaerobic activated sludge, the CSMER was more suitable for treating suspended organic matters compared with some AD-MESs systems using felts, granules and meshes of carbon as anodic electrode materials 47 . Thirdly, high rate of pre-hydrolysis and acidification can be achieved in the CSMER due to continuous stirring effects and solid-liquid-gas separation, which were considered to be the rate limiting step for bioelectricity generation. Though remarkable advantages of the CSMER were shown here, additional work will be needed towards its practical implementation of wastewater treatment. Effluent TCOD (909 ± 296 mg L −1 ) was unfavorable for aerobic post-treatment step because of high concentration, therefore, performance in terms of substrate removal need to be optimized by adjusting HRT, reducing external resistance, regulating functional microbial communities or adding pre-treatment step. In addition, assessment of nitrogen and phosphorus removals was supposed to be conducted to evaluate its nutrient removal efficiency. Moreover, future research focusing on enhancing energy recovery efficiency (such as electrode modification) would benefit MES technology for practical implementation of wastewater treatment. In the present study, a CSMER showed great potential for practical implementation when treating brewery wastewater, which achieved 75.4 ± 5.7% of TCOD removal and 64.9 ± 4.9% of TSS removal. Cascade utilization of organic matter by CMZ and MEZ in CSMER contributed to its higher substrate removal efficiency compared with a control CSTR. Pyrosequencing analysis demonstrated that four groups of microorganisms, including fermentative bacteria, syntrophic acetogenic bacteria, methanogenic archaea and electrochemically active bacteria participated in this cascade degradation process. This hybrid system shows a high economical attractiveness and practical applicability due to its membrane-less design and use of cost-effective materials."
} | 6,279 |
28475180 | PMC5607358 | pmc | 3,138 | {
"abstract": "The study of host-associated microbial community composition has suggested the presence of alternative community types. We discuss three mechanisms that could explain these observations. The most commonly invoked mechanism links community types to a response to environmental change; alternatively, community types were shown to emerge from interactions between members of local communities sampled from a metacommunity. Here, we emphasize multi-stability as a third mechanism, giving rise to different community types in the same environmental conditions. We illustrate with a toy model how multi-stability can generate community types and discuss the consequences of multi-stability for data interpretation.",
"introduction": "Introduction In the past decade, the microbial composition of a large number of samples from different environments was determined. For host-associated microbiota in particular, samples can be grouped into clusters based on their microbial composition. For instance, samples of the vaginal microbiome were found to form five distinct clusters, four of them dominated by different Lactobacillus species and the fifth of mixed character ( Ravel et al. , 2011 ). Clusters were also reported for the gut microbiome, where they are known as enterotypes ( Arumugam et al. , 2011 ). A recent clustering analysis suggests that oral microbiota can be likewise divided into clusters ( Ding and Schloss, 2014 ). Figure 1a illustrates clusters present in the Flemish Gut Flora Project data ( Falony et al. , 2016 ), one of the biggest gut data sets available to date (1106 samples). The clusters are visualized as mountains in a landscape plot, where peaks are the higher the more samples share the same community composition. We refer to both distinct and overlapping clusters as community types. In the following, we will discuss different mechanisms that could explain alternative community types.",
"discussion": "Discussion In recent years, the interpretation of alternative community types in the gut (enterotypes) has been hotly debated. While some authors interpret them as gradients or as artifacts resulting from gradients of dominant gut organisms ( Knights et al. , 2014 ; Gorvitovskaia et al. , 2016 ), others describe them as peaks in the landscape of all possible community configurations ( Falony et al. , 2016 ; Figure 1a ). In the context of this debate, it is worthwhile to point out that each of the three mechanisms can generate gradients or clusters, depending on model parameters. Although it is important to discuss how to interpret community types, we think that the current gradient-versus-cluster debate obscures the more interesting question about which mechanism explains these patterns. Here, we treated each mechanism separately, but it is likely that a combination of them determines community dynamics in microbial ecosystems. For instance, enterotypes may represent alternative stable states of a multi-stable system in healthy persons, but dysbiotic communities in Crohn's disease or ulcerative colitis may be driven by a strong change in environmental conditions (for example, inflammation). In addition, enterotypes may differ in their resistance to environmentally induced community shifts ( Vieira-Silva et al. , 2016 ). In the metacommunity model as well as in our proof-of-concept model, states emerge through a few strong interactions. Thus, according to both models, the SIS, but not necessarily the most abundant species, determine the community type. Gibson and colleagues point out the special interest of SIS as targets of community engineering efforts. These species can be considered as levers with which to switch the community from one type to another. In simulations with the proof-of-concept model, we observed that the SIS are the ones that differ most across community types, whereas weakly interacting species do not differ much ( Figure 3d ). Thus, if our model applies to real-world microbial communities, SIS could play the role of the bi-stable tipping elements described by Lahti and colleagues ( Lahti et al. , 2014 ). The further investigation of mechanisms behind community types and the identification of strongly interacting microbial species constitutes a promising topic for future research."
} | 1,062 |
33970538 | PMC8087987 | pmc | 3,139 | {
"abstract": "Abstract Polyhydroxyalkanoates (PHAs) are biodegradable bioplastics that can be manufactured sustainably and represent a promising green alternative to petrochemical‐based plastics. Here, we describe the complete genome of a new marine PHA‐producing bacterium— Photobacterium ganghwense (strain C2.2), which we have isolated from the Black Sea seashore. This new isolate is psychrotolerant and accumulates PHA when glycerol is provided as the main carbon source. Transmission electron microscopy, specific staining with Nile Red visualized via epifluorescence microscopy and gas chromatography analysis confirmed the accumulation of PHA. This is the only PHA‐producing Photobacterium for which we now have a complete genome sequence, allowing us to investigate the pathways for PHA production and other secondary metabolite synthesis pathways. The de novo assembly genome, obtained using open‐source tools, comprises two chromosomes (3.5, 2 Mbp) and a megaplasmid (202 kbp). We identify the entire PHA synthesis gene cluster that encodes a class I PHA synthase, a phasin, a 3‐ketothiolase, and an acetoacetyl‐CoA reductase. No conventional PHA depolymerase was identified in strain C2.2, but a putative lipase with extracellular amorphous PHA depolymerase activity was annotated, suggesting that C2.2 is unable to degrade intracellular PHA. A complete pathway for the conversion of glycerol to acetyl‐CoA was annotated, in accordance with its ability to convert glycerol to PHA. Several secondary metabolite biosynthetic gene clusters and a low number of genes involved in antibiotic resistance and virulence were also identified, indicating the strain's suitability for biotechnological applications.",
"conclusion": "4 CONCLUSIONS We obtained the first complete genomic sequence for a Photobacterium ganghwense strain. Moreso, strain C2.2 is capable of using glycerol, as a sole carbon source, to produce PHA granules. Genome analysis revealed the presence of all the genes required to synthesize PHA from glycerol, supporting the PHA‐producing phenotype. Observation of PHA accumulation dynamics showed a sustained increase in PHA content, with peak CDW and PHB content on day 14th. Gene annotation indicated the lack of a PHA depolymerase in the strain C2.2 genome. Although a putative lipase with the presumed ability to degrade extracellular amorphous PHA was annotated, our findings suggest that strain C2.2 is naturally prone to accumulate PHA for extended periods, a feature of great biotechnological importance. Also, the multitude of secondary metabolic pathways combined with the low number of genes involved in antibiotic resistance and virulence can be a plus from an applied science perspective. Our findings highlight the biotechnological potential of P. ganghwense strain C2.2, increasing the existing knowledge regarding PHA‐producing bacteria. The complete genome of a Photobacterium ganghwense contributes to the understanding of the Photobacterium genus.",
"introduction": "1 INTRODUCTION The adverse effects plastic waste has on our biosphere (Chae & An, 2018 ; Eriksen et al., 2014 ; Sebille et al., 2015 ) demand a global need to implement plastic clean‐up strategies and replace petrochemical‐based plastics with biodegradable, bio‐based polymers (Haward, 2018 ). Polyhydroxyalkanoates (PHAs) are a group of thermoplastic biopolyesters (Harding et al., 2007 ; Raza et al., 2018 ; Zhang et al., 2018 ) which are biodegradable and immunologically inert (Wang et al., 2014 ). The most common PHA is polyhydroxybutyrate (PHB), which can be produced by diverse bacteria (Inoue et al., 2016 ; Koller et al., 2011 ; Muhammadi et al., 2015 ; Sathiyanarayanan et al., 2017 ), which synthesize and store it as intracellular reserves of carbon and energy (Cavaillé et al., 2016 ; Keshavarz & Roy, 2010 ; Sedlacek et al., 2019 ; Slaninova et al., 2018 ). The most prevalent bacteria used in industrial bioplastic production are (1) Cupriavidus necator H16 (Yield10 Bioscience; CJ CheilJedang; Tianjin GreenBio Materials Co.; TianAn Biologic Materials Co.; Bio‐On Srl.), (2) Alcaligenes sp. (Biomer; HB Industrial S.A.); and (3) genetically engineered Escherichia coli that received PHA synthesis genes from naturally PHA producing bacteria such as C. necator H16 (Patent no. US5480794A, former Metabolix), Rhodospirillum rubrum (Patent no. US5849894A, CJ CheilJedang Corp), or Ralstonia eutropha modified to express the synthase gene from Pseudomonas fluorescens GK‐13 (Danimer Scientific; Noda et al., 2005 ). However, commercialization and production of bacterial PHA are constrained by its expensive substrates such as refined sugars, starch, or valuable plant oil (Koller & Marsalek, 2015 ), making its price twofold that of conventional, petroleum‐based plastics (average cost of PHB was reported to be approx. 4.88 USD/kg; Raza et al., 2018 ). To decrease the production costs, a PHA producing strain should be able to grow to high cell densities and accumulate large amounts of PHA at the account of inexpensive carbon resources such as glycerol (Gahlawat & Soni, 2017 ; Poblete‐Castro et al., 2014 ), waste cooking oil (Sangkharak et al., 2020 ; Vastano et al., 2019 ), or other low‐cost biomass (whey, starch, spent coffee grounds, wastewaters, wheat, and rice straw, lignin, etc.; Alcântara et al., 2020 ). As biodiesel production is increasing, the glycerol market has expanded rapidly, and using this by‐product as a cheap substrate could be integrated into a circular economy approach (El‐malek et al., 2020 ). In this context, we isolated a new strain of Photobacterium ganghwense that can convert glycerol to biodegradable polymers (PHA) in the form of poly‐3‐hydroxybutyrate (PHB). The Photobacterium genus encompasses Gram‐negative, facultative‐anaerobic, and motile bacteria, which are widespread throughout marine environments where some species live symbiotically with marine animals (Urbanczyk et al., 2011 ). This genus is relatively new, with 22 of the 28 existing species described within the last 15 years (Labella et al., 2017 ; Machado & Gram, 2017 ). Although several draft genomes are available, complete genomes exist for only three species ( P. damselae , P. profundum , and P. gaetbulicola ). Neither one of them is documented as a PHA producer. The biotechnological potential of this genus is yet to be explored and most studies have focused on individual members’ pathogenicity toward animals and humans (Abushattal et al., 2020 ; Fumanal et al., 2020 ; Rivas et al., 2013 ; Romalde, 2002 ). Information regarding PHA production within the Photobacterium genus is scarce and, to our knowledge, only two species ( P. leiognathi and P. phosphoreum ) have been described to accumulate intracellular PHAs when provided with glycerol and peptone as carbon and nitrogen substrates (Boyandin et al., 2008 ). None of these PHA‐producing Photobacterium has a complete genomic sequence publicly available. In this study, we report the isolation of a new PHA‐producing Photobacterium ganghwense (Park et al., 2006 ) strain (C2.2) and its complete genomic sequence, the first complete sequence available for this species. Furthermore, we present strain C2.2’s PHA production phenotype, its genetic basis, and provide valuable insights into other predicted metabolic capacities, gene transfer, structural modifications, virulence, and antibiotic resistance.",
"discussion": "3 RESULTS AND DISCUSSION 3.1 Isolation and characterization of P. ganghwense strain C2.2 A total number of 82 bacterial isolates were obtained from the sediment samples. From all the isolates, PHA‐production screening done by Nile Red staining highlighted strain C2.2, as its cell fluorescence was observed after 24 h (Figure 1 ) and maintained throughout the entire incubation period (14‐days). Intracellular PHA granule accumulation was demonstrated by TEM imaging after growing the C2.2 in liquid media supplemented with glycerol as a sole carbon source (Figure 1 ). Cells with numerous small inclusions were already present after 24 h of incubation. After 72 h of incubation, the PHA granules and the cells had shown an apparent growth in size. Enlargement of the cell size may be a mechanism to maximize the capacity for granule storage. FIGURE 1 Epifluorescence microscopy of Nile Red stained cells (a, b) and TEM (c, d). P. ganghwense C2.2 cells after 24 (a, c) and 72 h (b, d) cultivation on 2% pure glycerol, as sole carbon source, at 20°C. The bars represent 1 μm 3.2 16S rRNA gene sequence and phylogenetic analysis 16S rRNA gene comparison against the EzTaxon database showed the close taxonomical relation of strain C2.2 to members of the Photobacterium genera, especially with P. ganghwense DSM22954 T . Strain C2.2 shared a 16S rRNA gene sequence similarity of 99.86% and a 99.68% genome identity (see below) with the P. ganghwense DSM22954 T type strain. Based on the 16S rRNA gene sequence analysis, the isolated strain was grouped into a distinct cluster, together with two P. ganghwense strains, distant from the other three Photobacterium species with complete genomic sequences (Figure 2 ). FIGURE 2 16S rRNA gene‐based phylogenetic relationships of the “C.2.2” strain. The numbers shown at the tree nodes indicate bootstrap values (in %) based on 1000 replications. The scale bar indicates 0.02 substitutions per nucleotide position. Photobacterium strains with a complete genomic sequence available in public databases are underlined 3.3 Polymer accumulation on pure glycerol Pure glycerol (PG) was used to assess the PHB‐production phenotype of strain C2.2. Intracellular polymer accumulation (% CDW) and final PHB production (g/L) were obtained from 2% PG. Culture optical density, CDW, and PHB content increased steadily throughout the cultivation. They stabilized after 7 days (OD 600 of 33.3 (±0.3)) and remained in close range until the 14th day. Peak values were recorded on the 14th day and reached 65.4% PHB content, with 4 (±0.3) g/L PHB (Figure 3 ). Strain C2.2 showed the highest overall PHB production (g/L) among those reported for PHA‐producing Gammaproteobacteria in similar conditions (use of PG as a sole carbon source and shake flask cultivations; see comparative Table 1 ). This and the moderate halotolerance of the C2.2 strain indicate its suitability for larger‐scale PHA‐production testing. FIGURE 3 Time‐dependent cell dry weight (CDW) and PHA accumulation. Changes in P. ganghwense C2.2 cell dry weight (dark gray) and PHA accumulation (light gray; in g/L) when cultivated in shake flasks, on 2% pure glycerol, at 20°C. Bar graphs represent mean values (± SD) of three independent experiments TABLE 1 Production of PHA from pure glycerol by Gammaproteobacteria strains and Cupriavidus necator \n Strain Time (h) Culture volume (ml) a \n Pure glycerol (%; v:v) CDW (g/L) PHA content (% of CDW) References Photobacterium ganghwense C2.2 \n 96 \n 14 days \n 100 2 \n 3.1 \n 6.3 \n \n 53 \n 65.4 \n Current study Vibrio harveyi MCCB 284 72 200 2 3 68 Mohandas et al. ( 2017 ) Vibrio spp. M11/M14/M20/M31 24 h after stationary phase 200 1 0.31/0.31/0.44/0.45 30.2/31.5/42.8/24 Chien et al. ( 2007 ) \n Vibrio proteolyticus \n 48 NM 1 ~ 1.6 <10 Hong et al. ( 2019 ) Salinivibrio sp. M318 48 50 3 7.2 39 Van Thuoc et al. ( 2019 ) \n Zobellella denitrificans MW1 \n 100 300 2 3.7 73.5 Ibrahim and Steinbüchel ( 2010 ) Aeromonas spp. AC_01/AC_02/AC_03 48 NM 1 1.69/1.48/1.2 7.8/5/3.6 Możejko‐Ciesielska and Pokoj ( 2018 ) Halomonas sp. KM‐1 60 20 2 NM 40.5 Kawata and Aiba ( 2010 ) Cupriavidus necator DSM 545 b \n 88 100 \n 2 \n 3 \n \n ~6.35 \n ~7.18 \n \n ~77 \n ~79 \n Sun et al. ( 2020 ) Cupriavidus necator DSM 545 b \n 33.5 \n Fed‐batch \n 1500 \n 24.9 82.5 62 Cavalheiro et al. ( 2009 ) A PHB content (wt%) was expressed as a percentage of PHA mass in dry cell mass. Abbreviation: NM, not mentioned. \n a \n The culture volume in shake flask, if not mentioned otherwise. \n b \n Cupriavidus necator DSM 545 is used in the industrial production of PHA. John Wiley & Sons, Ltd 3.4 Genome of P. ganghwense strain C2.2 The genome assembly of P. ganghwense stain C2.2 was covered 113x, with a total size of 5,744,420 bp, GC content of 50.34%, and is comprised of two chromosomes and one plasmid (Table 2 ). Genome comparison of strain C2.2 to the type strain of P. ganghwense DSM22954 T (ASM102945v1) showed an average nucleotide identity of 99.68% further supporting the classification of the C2.2 strain as a member of the P. ganghwense species. In terms of genome size, typically, Photobacterium species have genomes ranging from 4.2 to 6.4 Mbp, and a GC content between 38.7% and 50.9% (Machado & Gram, 2017 ). Thus, the 5.74 Mbp size genome and 50.34% GC content of strain C2.2 is similar to that of other metabolically versatile Photobacterium species (e.g., P. profundum and P. halotolerans ) and to that of the P. ganghwense type strain (ASM102945v1). The C2.2 genome arrangement (Figure 4 ) into two circular chromosomes is observed for the other two Photobacterium species with a complete genomic sequence available and appears specific for the Vibrionaceae family (Machado & Gram, 2017 ). As shown for other species of the genus (Machado & Gram, 2017 ; Vesth et al., 2010 ), the second chromosome and the plasmid (202 kbp) can be a source of genomic plasticity and strain‐specific differences. In most cases, the studied Photobacterium strains have plasmids that range in size from 35 to 80 Kbp (Machado & Gram, 2017 ). The C2.2 megaplasmid is the second‐largest plasmid (202.454 bp) of the genus (the largest—319.190 bp—belonging to P. damselae strain Phdp Wu‐1; GenBank assembly accession no. GCA_003130755.1). TABLE 2 The metrics for the in‐house Flye assembly generated with QUAST Assembly metrics Assembly metrics # contigs 3 GC (%) 50.34 Contig 1 length (bp) 3,515,384 N50 3,515,384 Contig 2 length (bp) 2,026,582 N75 2,026,582 Contig 3 length (bp) 202,454 Avg. coverage depth 113 Total length 5,744,420 # N's per 100 kbp 0 John Wiley & Sons, Ltd FIGURE 4 The two chromosomes and plasmid of P. ganghwense strain C2.2. The genome maps consist of genome information displayed circularly (from the outside in): CDS, tRNA, rRNA, G + C content, and GC skew Genome annotation, by PGAP, yielded 4,983 coding sequences (CDS), 188 tRNAs, 55 rRNAs (Table 3 ). Assembly completeness evaluation (BUSCO, Appendix Table A2 ) indicated that single‐copy orthologs were 100% and, respectively, 99.6% complete for Bacteria and Vibrionales lineages. According to the PathoLogic results, the CDS encode for enzymes involved in 304 metabolic pathways. After annotation, a DIAMOND blast against the UniProt TrEMBL database showed that 92.35% of CDS have over 90% similarity to protein sequences from TrEMBL, indicating the sequencing method did not have a negative impact on assembly quality and protein prediction. No CRISPR arrays were annotated. TABLE 3 Genome features for strain C2.2 Features Features Genome size (bp) 5,744,420 CDS (coding) 4.875 Chromosome 2 tRNAs 188 Plasmid 1 rRNAs 55 Genes 5.198 ncRNAs 4 CDS (total) 4.951 Pseudogenes 76 John Wiley & Sons, Ltd Genomic basis for PHA accumulation in P. ganghwense strain C2.2. The PHA‐positive phenotype of strain C2.2. was confirmed by the presence of a complete phaCAB operon (Figure 5 ) via functional annotations of clusters of orthologous groups (COGs). The phaCAB is located on chromosome 2, and also includes a phaP gene encoding a phasin family protein (FH974_19300), a surface protein with a role in PHA granule stabilization and production (Figure 3 ). The only annotated phaC (FH974_19305) encodes for a class I poly‐hydroxyalkanoic acid synthase, which polymerizes CoA thioesters of short carbon chain length hydroxyalkanoic acids (C 3 ‐C 5 ). phaA (FH974_19295) and phaB (FH974_19290) encode for: acetyl‐CoA acetyltransferase—the first enzyme in the PHA synthesis pathway, and an acetoacetyl‐CoA reductase. phaCAB cluster organization and its similarity of protein sequences with the functional ones of Cupriavidus necator H16 (DSM 428; Kutralam‐Muniasamy et al., 2018 ; Figure 5 ), suggest an operational PHA‐synthesis pathway in strain C2.2. FIGURE 5 Simplified comparative analysis of PHA gene clusters from the PHA model organism C. necator H16 and P. ganghwense C2.2. The coding regions are indicated as follows: PHA synthase gene phaC (black); precursor‐generating enzymes genes phaA (dark gray) and phaB (light gray); surface protein gene phaP (oblique lines); PHA dependent transcriptional regulator phaR (white). The numbers above the coding regions indicate the sequence similarities with the protein counterparts of C. necator H16 Additionally, three putative phaP , four phaA , nine phaB , and one phaD , encoding hypothetical PHA synthesis transcriptional regulators (De Eugenio et al., 2010 ), were annotated for strain C2.2. Unlike other PHA‐producing bacteria, genes encoding the PHA‐dependent transcriptional regulatory proteins ( phaR / Q / F ) and PHA depolymerase ( phaZ ) were not identified in the genome of P. ganghwense strain C2.2. The absence of PHA depolymerase was validated via a BLASTp search against the PHA Depolymerase Engineering Database ( http://www.ded.uni‐stuttgart.de/ ; DED). This finding may explain the prolonged stability of accumulated PHB in the shake flask experiments (Figure 3 ). In a recent paper, de Vogel et al. ( 2021 ) highlighted similar features for two Vibrio strains ( V. proteolyticus ATCC 15338 and V. alginolyticus ATCC 33787) that lack sequences similar to PhaZ depolymerases. For those strains, the authors re‐assigned two initially annotated lipases as putative extracellular PHA depolymerases. The putative depolymerases were found to be most similar to the PhaZ7 depolymerase present in Paucimonas lemoignei , with demonstrated depolymerase activity for extracellular amorphous PHA (native PHA granules; Handrick et al., 2001 ). A BLASTp hit similar to this supposed extracellular depolymerases (92% coverage, 82%–84% identity) was found in the genome of Photobacterium sp. C2.2 (FH974_07335). Its presence may indicate the ability of strain C2.2 to degrade PHB only after PHB’s extracellular release succeeding the cell death. The confirmation of depolymerase activity for this putative lipase needs to be addressed in future experiments. In contrast, C. necator H16, the model strain for PHA production studies, has five well‐characterized intracellular and two extracellular depolymerases, as well as two oligomer hydrolases (Brigham et al., 2012 ). The absence of a depolymerase may prove advantageous for biotechnological applications, as PHA‐producing strains are usually genetically engineered to inactivate the depolymerization step for a higher yield in PHA production and increase the PHA molecular mass (Adaya et al., 2018 ; Kadouri et al., 2003 ; Kobayashi & Kondo, 2019 ). Likewise, except for the extracellular PHA oligomer hydrolase PhaY, all the genes for enzymes involved in the catabolism of hydroxyacyl monomers were annotated in strain C2.2 genome: FabG (FH974_05790, FH974_24585), acetoacetate CoA synthetase AacS (FH974_21375), 3‐oxoacid‐CoA‐transferase subunits A and B (ScoA ‐ FH974_04750; ScoB ‐ FH974_04745, FH974_24545), and 3‐hydroxyisobutyrate dehydrogenase MmsB (FH974_21025). As expected, strain C2.2. harbored all four genes ( glpK , glpD , glpC , glpB ) of the glycerol conversion pathway: glpK (FH974_00925) encodes for a glycerol kinase that converts glycerol to glycerol 3‐phosphate; glpD (FH974_00520) encodes for a glycerol‐3‐phosphate dehydrogenase that converts glycerol 3‐phosphate to dihydroxyacetone phosphate, which feeds into the glycolysis pathway, where it ultimately becomes acetyl‐CoA, a substrate for PHB synthesis (Kok et al., 1998 ); glpC (FH974_06490), and glpB (FH974_06495) encode subunits for an anaerobic glycerol‐3‐phosphate dehydrogenase (Cole et al., 1988 ). Previous studies have shown the efficient use of glycerol for PHA production (Phithakrotchanakoon et al., 2015 ; Rodríguez‐Contreras et al., 2015 ; Tanadchangsaeng & Yu, 2012 ). In the case of C. necator H16, when glycerol was used instead of expensive sugars (e.g., glucose), the molecular weight of the resulting polymer was reduced, but its thermal and mechanical properties remained unchanged (Tanadchangsaeng & Yu, 2012 ). Other pathways. Several metabolic pathways of biotechnological interest were annotated: a complete pathway for the degradation of phenylacetate (Teufel et al., 2010 ) to acetyl CoA, with a total of 51 genes involved in the degradation and metabolism of xenobiotics; complete pathways for the synthesis of various isoprenoids; genes involved in the metabolism of various terpenoids and polyketides; pathways for the degradation of various carbohydrates, such as starch, glycogen, chitin, etc. Such metabolic versatility could prove useful in expanding the range of raw substrates for the production of PHAs. Prediction of smBGCs. Secondary metabolites have great potential for biotechnological applications (e.g., antibiotics, pigments, growth hormones, antitumor agents, and others). Since the production of bioactive molecules is poorly studied in Photobacterium (Čihák et al., 2017 ), we screened the genome of strain C2.2 for putative smBGCs. Based on their homology to known smBGCs, we predicted seven such gene clusters: four smBGCs on the large chromosome and three on the small chromosome. Strain C2.2 megaplasmid CDSs included no smBGCs nor genes involved in horizontal gene transfer. The smBGCs identified on the larger chromosome encode for antimicrobial functions: bacteriocin (FH974_15530), thiopeptide (FH974_04020 ‐ FH974_04040), and betalactone (FH974_13860 ‐ FH974_13885). These compounds provide a competitive advantage and protection from other microbial community members but could also mediate interspecies interactions (Čihák et al., 2017 ). The smBGCs identified on the smaller chromosome encode for: ectoine ( ectABC operon), aryl polyene (T2PKS; FH974_24595), and polyketide (T1PKS; FH974_21825) synthesis. Polyketides like aryl polyene pigments are broadly distributed within Bacteria (Grammbitter et al., 2019 ). Polyketides, together with ectoine, serve as protection against reactive oxygen species and may have a protective role for strain C2.2 in marine environments (Das et al., 2015 ; Schöner et al., 2016 ). Further research is needed to investigate whether there is a link between the production of these compounds and certain environmental conditions. Antimicrobial susceptibilities and resistance genes. Since many strains of the Photobacterium genus are well known for their virulence and antimicrobial resistance (Chiu et al., 2013 ; Fuertes‐Perez et al., 2019 ; Labella et al., 2017 ; Nonaka et al., 2012 ), we screened the P. ganghwense C2.2 genome for the acquired resistance mechanisms using Abricate. Surprisingly, strain C2.2 had only one antibiotic resistance gene ( qnrS5 ) associated with resistance to fluoroquinolone (Han et al., 2012 ). Abricate revealed several putative virulence‐associated genes: cheW ‐2 chemotaxis protein, fli G—flagellar motor protein, fli M, and fli N, both polar flagellar switch proteins, involved in cell signaling and motility in liquid environments. These genes represent only a small fraction of the 15 core virulence genes of Gammaproteobacteria (Vázquez‐Rosas‐Landa et al., 2017 ). Acquisition of additional virulence genes by horizontal gene transfer could be possibly mediated by one of the five phage regions predicted by PHASTER (Srividhya et al., 2007 ; Vázquez‐Rosas‐Landa et al., 2017 ). However, all five prophage regions are incomplete, with the largest being 103 kb in length and located on the small chromosome. Auspiciously, a low number of antibiotic resistance and virulence genes along with the incomplete prophage regions are an indicator of genome stability, which may be beneficial in the potential biotechnological applications of P. ganghwense strain C2.2."
} | 6,040 |
25729339 | null | s2 | 3,141 | {
"abstract": "Although no species lives in isolation in nature, efforts to grow organisms for use in biotechnology have generally focused on a single-species approach, particularly where a product is required at high purity. In such scenarios, preventing the establishment of contaminants requires considerable effort that is economically justified. However, for some applications in biotechnology where the focus is on lower-margin biofuel production, axenic culture is not necessary, provided yields of the desired strain are unaffected by contaminants. In this article, we review what is known about interspecific interactions of natural algal communities, the dynamics of which are likely to parallel contamination in industrial systems. Furthermore, we discuss the opportunities to improve both yields and the stability of cultures by growing algae in multi-species consortia."
} | 216 |
39757383 | PMC11895418 | pmc | 3,142 | {
"abstract": "ABSTRACT Microbial communities have shown promising potential in degrading complex biopolymers, producing value‐added products through collaborative metabolic functionality. Hence, developing synthetic microbial consortia has become a predominant technique for various biotechnological applications. However, diverse microbial entities in a consortium can engage in distinct biochemical interactions that pose challenges in developing mutualistic communities. Therefore, a systems‐level understanding of the inter‐microbial metabolic interactions, growth compatibility, and metabolic synergisms is essential for developing effective synthetic consortia. This study demonstrated a genome‐scale community modeling approach to assess the inter‐microbial interaction pattern and screen metabolically compatible bacterial pairs for designing the lignocellulolytic coculture system. Here, we have investigated the pairwise growth and biochemical synergisms among six termite gut bacterial isolates by implementing flux‐based parameters, i.e., pairwise growth support index (PGSI) and metabolic assistance (PMA). Assessment of the PGSI and PMA helps screen nine beneficial bacterial pairs that were validated by designing a coculture experiment with lignocellulosic substrates. For the cocultured bacterial pairs, the experimentally measured enzymatic synergisms (DES) showed good coherence with model‐derived biochemical compatibility (PMA), which explains the fidelity of the in silico predictions. The highest degree of enzymatic synergisms has been observed in C. denverensis P3 and Brevibacterium sp P5 coculture, where the total cellulase activity has been increased by 53%. Hence, the flux‐based assessment of inter‐microbial interactions and metabolic compatibility helps select the best bacterial coculture system with enhanced lignocellulolytic functionality. The flux‐based parameters (PGSI and PMA) in the proposed community modeling strategy will help optimize the composition of microbial consortia for developing synthetic microcosms for bioremediation, bioengineering, and biomedical applications.",
"introduction": "1 Introduction The specialized microbial guild residing in the wood‐feeding termite gut environment has been considered the most effective lignocellulose degraders (Brune 2014 ). The broad spectrum of enzymatic cocktails produced by these specialized microbial communities helps execute the complex biological processes of lignocellulose bioconversion. (Auer et al. 2017 ; Bredon et al. 2018 ; Brenner, You, and Arnold 2008 ). Several genomics and metagenomics studies have revealed the structural and functional diversity of the termite gut microbiota essential to lignocellulose bioconversion (Rossmassler et al. 2015 ; Warnecke et al. 2007 ). The enriched gene pools of the termite gut microbial symbionts for efficient lignocellulose bioconversion (Arora et al. 2022 ) have also been revealed through metagenomics and metatranscriptomics. A diverse set of bacterial genes involved in the cellulose and xylan hydrolysis has also been detected through the metagenomics analysis of the hindgut paunch of wood‐feeding higher termite species (Hu et al. 2019 ; Warnecke et al. 2007 ). Moreover, the combination of shotgun sequencing, fosmid libraries, and biochemical assays enables the identification of around 219 functional genes encoding crucial carbohydrate‐active enzymes (CAZymes) (Liu et al. 2019 ). The complementary CAZymes cocktails were essential for the effective digestion of cellulose, hemicellulose, and pectin by the termite gut microbial populations (Marynowska et al. 2023 ). Despite the characterization of numerous microbial genera and their gene pools, the basis of metabolic interdependency in microbial communities has remained indispensable. Inside a microbial consortium, the exchange of metabolic compounds in the community environment defines the ultimate phenotypic properties of an individual microbe. These interactions lead to collective biochemical properties of the microbial guild through metabolic interdependencies, cross‐feeding, and division of labor (Faust and Raes 2012 ; Seth and Taga 2014 ). Although the basis of the bacterial synergisms is not entirely decoded, several recent studies have shown the phenomenon of metabolic cooperation and division of labor in the co‐existing microbial community utilizing lignocellulosic material (Ali et al. 2023 ; Detain et al. 2022 ). The collaborative metabolic activities of a five‐member microbial community have been developed earlier for the effective degradation of the lignocellulosic material (Kato et al. 2005 ). Further, based on the division of metabolic labor, a co‐existing microbial consortium of Trichoderma reesei and Escherichia coli has been developed (Minty et al. 2013 ). In this coculture system, the enzymatic activity of T. reesei transformed the lignocellulosic biomass into soluble sugars, and E. coli fermented these into isobutanol. However, the microbial metabolic activities in a co‐existing community do not always lead to cooperative interaction. In a complex microbial consortium like termite gut microbiota, diverse metabolic activities of the microbial species can lead to positive, negative, or neutral outcomes (Faust and Raes 2012 ; Kundu et al. 2019 ). Moreover, the combinatorial assessment of different inter‐species interaction states can escalate the degree of interaction types, even with a small set of microbial entities. Therefore, pinpointing the fundamental interactions is crucial to identify the beneficial or compatible microbial pairs for improved functionality. Assessing the complex microbial interaction pattern with experimental coculture strategies may be challenging and tedious. Hence, implementing in silico modeling strategies can provide essential knowledge to screen the synergistic microbial entities and develop mutualistic communities for complex metabolic tasks. Systems biology tools like genome‐scale community metabolic modeling help investigate the biochemical pathways of individual microbes and microbial consortia for optimizing their metabolic activities (Fondi and Liò 2015 ; Ibrahim, Raajaraam, and Raman 2021 ). The genome‐scale community models (GCMs) essentially provide the biochemical flux distribution patterns of individual and community‐level metabolic networks optimized in different environments (Beura et al. 2022 ; Perez‐Garcia, Lear, and Singhal 2016 ). Hence, community modeling has been widely used to study the intricate metabolic activities and interactions among diverse microbial members and provide essential biochemical knowledge for establishing effective coculture systems. Recently, a model‐assisted coculture setup followed by constrained‐based flux simulations of the human gut microbial species Phocaeicola dorei and Lachnoclostridium symbiosum predicted high lactate and succinate cross‐feeding fluxes when growing in inulin or xylan (Hirmas et al. 2022 ). Further, a GEM‐guided cocultivation of Pichia stipitis and Saccharomyces cerevisiae showed the cross‐feeding of ethanol to derive maximum advantage in the community environment (Ravikrishnan et al. 2020 ). Moreover, in the case of more extensive and complex microbial consortia, the community models help to track the combinatorial effect of the metabolic cross‐talk to find the metabolic and growth compatibility between the community members (Kumar et al. 2022 ; Kundu and Ghosh 2023 ). Hence, assessing the inter‐microbial metabolic assistance in the community environments helps to find the growth and metabolically compatible microbial pairs. The enzymatic and biochemical synergies of these compatible microbial communities can then be tested with experimental setups. In this study, we have demonstrated a genome‐scale community modeling approach with newly introduced parameters, like pairwise growth support index (PGSI) and pairwise metabolic assistance (PMA), to screen the mutualistic bacterial communities for effective coculture development. The individual GEMs of six lignocellulolytic bacterial strains, i.e., Micrococcus luteus P1, Kluyvera sp. P2, Cellulomonas denverensis P3, Oceanobacillus sojae P4, Brevibacterium sp. P5 and Niallia circulans P6 were initially created to evaluate the flux distribution in metabolic pathways. Further, the individual GEMs were integrated to reconstruct community models for all the possible bacterial pairs. We have defined the PGSI and PMA to predict growth compatibility and metabolic assistance through the GCM analysis. The synergistic bacterial communities predicted through PGSI and PMA were tested by setting up the coculture experiments with the lignocellulosic substrates. Here, the experimentally derived degree of enzymatic synergism (DES) in filter paper (FP) (total cellulase), carboxymethyl cellulose (CMC) (endoglucanase), and xylan (xylanase) have been compared with the GCMs‐derived PMA values. The maximum DES has been achieved by cocultured bacterial communities C. denverensis P3 and Brevibacterium sp. P5, while growing in FP. The experimentally obtained DES of bacterial coculture correlated well with the model‐driven PMA values. Hence, the community model analysis helps design the optimal bacterial combination to overcome the substrate‐specific limitation of individual strains for efficient lignocellulose bioconversion. Overall, this in silico methodology highlighted implementing systems biology tools to predict the compatible microbial coculture systems, leading to the development of efficient lignocellulolytic bacterial consortia.",
"discussion": "3 Results and Discussion 3.1 Screening Lignocellulolytic Bacterial Isolates From Termite Gut Microbiota for GEM Reconstruction This study intends to design an optimized lignocellulose degrading bacterial community with termite gut isolates through genome‐scale community metabolic modeling. The enrichment of the bacterial species was initiated by inoculating the termite gut extract in the liquid culture with CMC as the metabolic substrate. Initially, 35 enriched colonies were subjected to detailed morphological characterization. Based on similar morphological traits (colony shape, color, elevation, and margin types), 16 bacterial isolates were excluded (Bhaduri et al. 2016 ; Singh et al. 2019 ). The remaining 19 bacterial isolates were used to screen the hydrolytic capacities (HC) with CMC and xylan. The positive bacteria isolated produce a zone of clearance (‘Halos’) around their colony in the agar plates containing PCS media while incubated at 37°C for 48–72 h (Figure 1A ) (Table S1 ). The HC of the bacterial isolates has been determined by measuring the ratio of the diameter (cm) of the zone of clearance to the diameter (cm) of the colony (Dar et al. 2015 ; Hendricks, Doyle, and Hugley 1995 ). The bacterial strains showed varied hydrolytic potential for the different substrates, and a maximum HC of 3.64 and 3.11 was achieved in CMC and xylan, respectively. Based on the hydrolyzing potential of bacterial isolates, six best‐performing isolates have been selected for molecular phylogeny analysis. Amplification of the 16S rRNA genes (Figure S1 ) and the sequence similarity search with NCBI BLAST helped identify the six bacterial strains as Micrococcus luteus P1 and Kluyvera sp. P2, Cellulomonas denverensis P3, Oceanobacillus sojae P4, Brevibacterium sp. P5, and Niallia circulans P6. The 16S rRNA gene amplicon sequences (FASTA) of the bacterial isolates have been submitted to the NCBI GenBank repository under the accession number OR825811 ‐ OR825819 (Table S2 ). Figure 1 Screening the lignocellulolytic abilities of the bacterial isolates: (A) The hydrolytic capacities (HC) of the bacterial isolates in CMC and xylan. The positive bacteria isolated showed a zone of clearness (‘halos’) around their colony. The HC of the positive bacterial isolates was semi‐quantitatively measured by calculating the diameter ratio of the ‘halos’ and the colony measurements. The enzyme activity profile of the individual bacterial isolates. The enzyme activity of the six best‐performing bacterial strains in filter paper (B), CMC (C), and xylan (D) are represented in the vertical axis against different time points (24, 48, 72, and 96 h). All the data points represent the average value from triplicate experimental measurements of enzyme activities. The lignocellulose degrading potential of six termite gut bacterial isolates, i.e., Micrococcus luteus P1 and Kluyvera sp. P2, Cellulomonas denverensis P3, Oceanobacillus sojae P4, Brevibacterium sp. P5 and Niallia circulans P6 have been assessed using the dinitro salicylic acid (DNS) method (Dar et al. 2015 ; Miller 1959 ). The total cellulase (FPase), endoglucanase (CMCase), and xylanase enzyme activity have been measured for the bacterial isolates at different time points using FP, CMC, and xylan, respectively. The bacterial strains M. luteus P1, C. denverensis P3, and N. circulans P6 showed a constant increase in the total cellulase potential up to 72 h, achieving the maximum activity of 0.1503 U mL −1 (±0.012), 0.1163 U mL −1 (±0.006), and 0.1604 U mL −1 (±0.012), respectively (Figure 1B ) (Table S3 ). On the other hand, the FPase activity of Bervibacterium sp. P5 reached maximum [0.1636 U mL −1 (±0.02)] at 48 h, and a slight decrease in activity was observed afterward. Overall, M. luteus P1, N. circulans P6, and Bervibacterium sp. P5 were the best‐performing individual strains in the FP substrate with the highest enzymatic activities. However, despite the high FPAse activity, M. luteus P1 and Bervibacterium sp. P5 exhibits relatively lower degradation potential in the CMC with an average activity of ~0.1 U mL −1 (±0.009) between 24 and 48 h. As the CMC degradation potential majorly depends on the presence of only endoglucanase enzyme (Singh et al. 2019 ), the low production of endoglucanase may lead to decreased CMCase activity in strains P1 and P5. In contrast, the total cellulase (FPase) activity is the combined potential of β‐glucosidase, endo‐1,4‐β‐ d ‐glucanase (endoglucanase), and exo‐1,4‐β‐ d ‐glucanase (exoglucanase) enzymes of a microbial species. Hence, the strains P1 and P5 may produce higher amounts of β‐glucosidase and exoglucanases (not estimated in this study), which leads to higher FPase activity in P1 and P2. Using CMC as the metabolic substrate, O. sojae P4, C. denverensis P3, and N. circulans P6 were found to be the best‐performing strains that achieved an enzyme activity up to 0.184 U mL −1 (± 0.006) (Figure 1C ). However, despite the high CMCase activity, P4 showed a lower FP degradation (FPase) potential (Table S3 ). This could be due to the higher secretion of endoglucanase enzymes and the lower production of β‐glucosidase and exoglucanase (not quantified in this study) by O. sojae P4. Therefore, the enzymatic potential of the isolated bacterial strains varied significantly depending on the substrates. This trend has also been observed for the xylan‐supplemented media where Kluyvera sp. P2 showed good enzymatic potential 0.25 U mL −1 (± 0.011) in the xylan‐supplemented media, but a lower activity was obtained in CMC and FP substrates (Figure 1D ). Hence, the selected bacterial isolates showed significant enzyme activity in one of the given substrates, but their hydrolytic potential greatly varied with the substrate‐specific condition (Figure 2 ). Strains exhibiting good degradation potential in one substrate may not necessarily perform similarly in an alternative substrate. A Kruskal–Wallis test (Kruskal and Wallis 1952 ) and Tukey's HSD analysis showed significant differences [ H \n \n stat \n = 10.04, p = 0.0066] between the FP, CMC, and xylan hydrolysis activity by the individual strains. The low hydrolytic potential of individual strains on specific types of lignocellulosic substrates signifies their substrate‐specific limitation that hinders the complete bio‐conversion of lignocellulosic material. This substrate‐dependent limitation of the individual bacterial activity can be overcome by developing synergistic bacterial coculture. The division of labor and cooperative metabolic activities in the microbial community help overcome the metabolic burden of fellow community members for a more efficient lignocellulolytic activity, as observed in previous studies (Kato et al. 2004 ; Lü et al. 2013 ; Singh et al. 2019 ). However, designing pairwise coculture systems by combining a large set of bacterial strains may pose several challenges. Moreover, because of the complex metabolic interactions between microbial species, implementing the model‐guided predictive method may help assess the growth and metabolic compatibility between microbial pairs. In this context, genome‐scale metabolic modeling is considered an effective tool that provides systems‐level insight into the biochemical flux distribution patterns of microbial entities. Thus, the implementation of genome‐scale modeling can predict the beneficial metabolic interaction patterns in microbial communities through in silico flux analysis to find synergistic bacterial pairs. Figure 2 The Maximum enzymatic activity of bacterial isolates in different lignocellulosic substrates: The horizontal axis represents the average maximum FPase (black), CMCase (red), and xylanase (blue) activities of the selected bacterial strains (vertical axis) derived from the triplicate experimental measurements. The error bar represents the standard deviation. 3.2 Reconstruction of Pairwise GCMs for Identifying Growth‐Compatible Bacterial Pairs Assessment of the lignocellulolytic enzyme activities of the termite gut bacterial isolates helped identify the six best‐performing strains in terms of FP, CMC, and xylan degradation. The genome‐scale community modeling strategy has been implemented to understand the systems‐level biochemical activities of the individual species and screen the synergistic bacterial pairs for developing an effective coculture system. The genome‐scale metabolic models were initially reconstructed for six best‐performing bacterial isolates, i.e., M. luteus P1, Kluyvera sp. P2, C. denverensis P3, O. sojae P4, Brevibacterium sp. P5 and Niallia circulans P6. The individual GEMs were first developed using the GPR association information from the annotated genomes of each species in the ModelSeed platform (Faria et al. 2018 ). The chemical imbalance, reaction reversibility, and other metabolic anomalies of the reconstructed GEMs were corrected manually using PubChem (NIH), ModelSeed reaction databases (Henry et al. 2010 ), and BiGG Database (Schellenberger et al. 2010 ). The individual models were further refined by gap‐filling several microbe‐specific biochemical pathways based on the KEGG database (Kanehisa et al. 2017 ). The refined models contain an average of 1460, 1726, and 1314 reactions, genes, and metabolites, respectively (Table 1 ). The individual GEMs were optimized using FBA with biomass as the objective function. To validate the in silico models, the glucose uptake rate of the individual microbes was measured experimentally. This glucose uptake rate was used to constrain each model, followed by the estimation of the in silico biomass formation rate (Table S5 ). Since the biomass formation rate of the in silico models correlates well (average Pearson r = 0.92, p = 0.008) with the experimentally measured growth values (Figure S2 ), these individual GEMs have been used for the community model (GCM) reconstruction. Table 1 Information on the structural properties of the genome‐scale metabolic models (GEMs) of the bacterial species identified from the termite gut microenvironment. Microbe Id Strain information Reactions Gene Metabolites In silico growth rate Experimental growth rate Mean SD P1 \n Micrococcus luteus P1 1120 1172 1087 0.188 0.179 0.0137 P2 \n Kluyvera sp. P2 1757 1996 1545 0.147 0.166 0.0089 P3 \n Cellulomonas denverensis P3 1260 1242 1235 0.085 0.0840 0.007 P4 \n Oceanobacillus sojae P4 1559 2446 1348 0.069 0.075 0.0098 P5 \n Brevibacterium sp. P5 1489 1562 1314 0.198 0.208 0.124 P6 \n Niallia circulans P6 1577 1942 1355 0.113 0.126 0.0068 John Wiley & Sons, Ltd. To examine the metabolic activities and flux distribution of each bacterial pair, the individual GEMs of these six bacterial species have been integrated into 15 ( 6 C 2 ) possible pairwise GCMs. The individual GEMs were represented as specific compartments in the GCM, where the community biomass was defined by summing the stoichiometric coefficients of the individual model's biomass reactions. The FBA has been performed with each community model, subjected to the maximization of the community biomass formation rate. In each pairwise GCM, an individual microbe can enhance, decrease, or have no effect on the growth of fellow community members when growing together. Therefore, a PGSI calculation has been introduced to assess how the individual microbial growth is altered in the presence of another microbe, ultimately affecting the community growth rate. Thus, considering two bacterial species (P and Q) growing together, if the community biomass is greater than the sum of the individual growth ( V bioPQ ≥ V bioP|P + V bioQ|Q ), the bacterial pair can be called growth‐compatible. Hence, PGSI analysis will help track the positive, negative, and neutral interactions between individual entities, leading to enhanced, decreased, and unchanged community growth ( V bioP|P + V bioQ|Q ), respectively. The growth compatibility assessment of 15 pairwise GCMs showed 8, 3, and 4 positive, negative, and neutral PGSI, respectively (Figure 3A ). For the 8 positively interacting bacterial pairs, an average PGSI of 0.189 has been observed. These growth‐compatible bacterial pairs show mutualistic (+/+) and commensalic (+/0) interactions, leading to a higher (> 1%) community growth ( V \n \n bioPQ \n ) than the sum of individual GEMs' growth ( V \n \n bioP|P \n + V \n \n bioQ|Q \n ). For instance, the C. denverensis P3 and O. sojae P4 showed an average PGSI of 0.65 in the community model GCM P3‐P4 (Figure 3B ) (Table S6 ). Because of this high average PGSI and mutualistic interactions between these bacterial strains, the community model growth has increased by 69.5%. On the other hand, bacterial pairs in GCM P2‐P3 (PGSI = −0.249), GCM P2‐P4 (PGSI = −0.173), and GCM P2‐P6 (PGSI = −0.049) showed negative growth support on each other (Figure 3C ). This negative PGSI leads to competitive (−/−) and amensalism (−/0) interactions in the community, where the growth has decreased up to 24.36% compared with the individual GEMs’ growth rate. Apart from the positive and negative growth impact, a neutral effect has also been noted for GCM P1‐P3 , GCM P1‐P6 , GCM P5‐P6, and GCM P4‐P6 , where no significant difference (<1%) has been observed in the community environment. Hence, the PGSI analysis helps assess positive, negative, and neutral effects on the inter‐microbial growth rate in the community to track the growth‐compatible bacterial pairs. Overall, the nine positive and four neutral inter‐microbial interactions have been revealed through the pairwise growth compatibility assessment of the GCMs. These growth‐compatible microbial pairs can have metabolic synergisms that help support the growth of fellow community members and enhance their metabolic potential. Figure 3 Assessment of in silico community growth profile and PGSI. (A) Comparison between the pairwise community model growth (blue) and the sum of the individual (grey) model growth as obtained from the FBA analysis. A higher (> 1%) community growth rate compared to the sum of individual growth signifies the in silico growth compatibility between nine bacterial pairs. (B) The positive growth support (PGSI) between strains P3 and P4 leads to mutualistic interactions. Meanwhile, the negative PGSI between P3 and P2 (C) is responsible for inter‐microbial competition. 3.3 Assessment of the Lignocellulolytic Potential of the Model‐Assisted Bacterial Coculture System Alongside the pairwise growth pattern, the metabolic benefits a bacterial species receives from its fellow community members are essential for developing synergistic relations. The metabolic compatibility between microbial entities has been measured through PMA. PMA ( P | P ∪ Q ) captures the number of flux‐range‐expanded reactions and activated reactions in an individual microbe P while growing in a duplet with Q (see Section 2 ). Thus, PMA ( P | P ∪ Q ) = 1 represents 100% beneficiary effect of microbe Q on P while growing together. Conversely, PMA ( P | P ∪ Q ) = 0 indicates that microbe Q does not provide any metabolic benefits to microbe P. The PMA has been calculated from all 15 GCMs and represented as an interactive network in Cytoscape (Figure 4 ). The average of the calculated PMA (~ 0.075) has been set as the cut‐off to identify the significant metabolic assistance between microbial pairs. The O. sojae P4 and C. denverensis P3 strains provided the maximum metabolic assistance (up to 0.16) toward different community members (Figure 4 ) (Table S7 ). In the community model GCM P1‐P3 , C. denverensis P3 provided a PMA of 0.15 towards M. luteus P1, whereas M. luteus P1 showed a PMA of 0.10 towards C. denverensis P3. The flux range of the lignocellulose degradation reactions was also increased in the GCM P1‐P3 (Figure S3 ). Hence, with a high average PMA of 0.126, GCM P1‐P3 can be considered a beneficial pairwise community where bacterial members provide positive metabolic assistance to each other. The pairwise community models GCM P3‐P5 , GCM P3‐P6 , and GCM P1‐P4 also showed a significant PMA, which is higher than the average PMA values (>0.075), considering all 15 pairwise community models (Table S7 ). Interestingly, for the nine pairwise community model with higher PMA, we observed an expansion in the flux range associated with cellulose conversion reactions and positive PGSI (Figure S3 ). Therefore, growth compatibility and metabolic assistance are essential for establishing the synergistic relationship between bacterial pairs. This may also indicate that the collaborative degradation of the cellulose can be one major factor in establishing the synergistic relations between bacterial pairs. Based on in silico analysis, seven pairwise bacterial communities (GCM P1‐P3, GCM P1‐P4 , GCM P1‐P5 , GCM P3‐P4 , GCM P3‐P5 , GCM P3‐P6 , GCM P4‐P5 ) showed positive PGSI, and two communities (GCM P1‐P3 and GCM P5‐P6 ) exhibited neutral growth assistance with a high PMA value (Table 2 ). Figure 4 Pairwise metabolic assistance between individual microbes. The network represents the inter‐microbial metabolic assistance in the pairwise bacterial community as mapped using Cytoscape. Each node denotes the specific bacterial strains, and the colored edges represent the fraction of PMA value directed toward the metabolically dependent species from fellow community members. Table 2 Pairwise growth support index (PGSI) and metabolic assistance (PMA) of nine compatible bacterial pairs that have been tested with experimental coculture systems. The growth compatibility and enzymatic synergism (DES) derived for the experimental setup have also been presented. Community model Strain 1 Strain 2 Avg. PGSI Avg. PMA Coculture systems Sum of individual growth rate (h −1 ) SD Community growth (h −1 ) SD DES GCM P1‐P3 \n \n Micrococcus luteus P1 \n Cellulomonas denverensis P3 0.006 0.126 COM P1‐P3 \n 0.263 0.010 0.291 0.023 1.106 GCM P1‐P4 \n \n Micrococcus luteus P1 \n Oceanobacillus sojae P4 0.307 0.097 COM P1‐P4 \n 0.254 0.004 0.197 0.014 0.776 GCM P1‐P5 \n \n Micrococcus luteus P1 \n Brevibacterium sp. P5 0.031 0.069 COM P1‐P5 \n 0.387 0.022 0.384 0.018 0.992 GCM P2‐P5 \n \n Kluyvera sp. P2 \n Brevibacterium sp. P5 0.011 0.054 COM P2‐P5 \n 0.292 0.011 0.301 0.026 1.031 GCM P3‐P4 \n \n Cellulomonas denverensis P3 \n Oceanobacillus sojae P4 0.647 0.108 COM P3‐P4 \n 0.159 0.016 0.157 0.014 0.987 GCM P3‐P5 \n \n Cellulomonas denverensis P3 \n Brevibacterium sp. P5 0.207 0.124 COM P3‐P5 \n 0.292 0.017 0.371 0.04 1.271 GCM P3‐P6 \n \n Cellulomonas denverensis P3 \n Niallia circulans P6 0.289 0.125 COM P3‐P6 \n 0.21 0.010 0.296 0.007 1.410 GCM P4‐P5 \n \n Oceanobacillus sojae P4 \n Brevibacterium sp. P5 0.015 0.089 COM P4‐P5 \n 0.283 0.013 0.321 0.031 1.134 GCM P5‐P6 \n \n Brevibacterium sp. P5 \n Niallia circulans P6 0.006 0.065 COM P5‐P6 \n 0.334 0.019 0.39 0.009 1.168 John Wiley & Sons, Ltd. To validate the growth and metabolic compatibility predicted by the pairwise GCM, nine bacterial coculture systems, i.e., COM P1‐P3 , COM P1‐P4 , COM P1‐P5 , COM P2‐P5 , COM P3‐P4 , COM P3‐P5 , COM P3‐P6 , COM P4‐P5 , and COM P5‐P6 have been tested experimentally. The endoglucanase, total cellulase, and xylanase activity of the model‐driven bacterial pairs have been assessed by conducting coculture with CMC, FP, and xylan, respectively. Among the nine bacterial pairs selected through the GCM analysis, seven pairs showed growth compatibility in the experimental coculture system. Hence, the GCM analysis showed a 78% accuracy in predicting synergistic growth patterns in pairwise bacterial communities. For the growth‐compatible bacterial pairs, the community growth rate either increased or remained unchanged compared to the sum of individual growth (Table 2 ). For example, a higher PGSI ranging from ~0.01 to 0.65 has been observed in the community models GCM P1‐P3 , GCM P3‐P4 , and GCM P3‐P5 . When the coculture systems (COM P1‐P3 , COM P3‐P4 , and COM P3‐P5 ) of these bacterial pairs were developed, they showed a 9.03%–26.75% increase in experimental community growth rate compared to individual growth. Therefore, for the growth‐compatible bacterial pairs, the model‐driven PGSI showed a positive correlation ( Pearson r = 0.86, p = 0.01) with the experimentally measured growth rate increment in the coculture (Figure 5A ). Figure 5 Correlation between in silico analysis and experimental data: (A) the pairwise growth support index of the pairwise GCMs showed a good correlation with the experimental community growth. (B) Similarly, the model‐derived PMA showed a good agreement with the experimentally measured degree of enzymatic synergisms. This community‐level growth compatibility can affect the metabolic synergisms (PMA) of microbial pairs, ultimately affecting the coculture systems' enzyme activities. Therefore, how inter‐microbial growth compatibility (PGSI) and metabolic assistance (PMA) act as critical factors in facilitating the DES have been investigated through coculture systems. The DES represents the ratio of the enzyme activity in coculture to the cumulative sum of the monoculture enzyme activities. The bacterial coculture showed diverse activity at different time points (Figure S4 ) towards different lignocellulosic substrates, i.e., FP, CMC, and xylan. For instance, COM P3‐P5 ( C. denverensis P3/ Brevibacterium sp. P5) and COM P5‐P6 ( Brevibacterium sp.P5/ Niallia circulans P6) are the best‐performing communities in FP, which showed the maximum enzymatic activity (FPase) of 0.429 U mL −1 (±0.06) and 0.411 U mL −1 (±0.055), respectively (Figure 6A , Table S8 ). The community enzyme activity has been increased by 53%, with the highest DES of 1.53 between C. denverensis P3 and Brevibacterium sp. P5 in the community environment while growing in FP (Figure 6D , Table S9 ). On the other hand, when CMC was used as a substrate, COM P1‐P3 ( M. luteus P1/ C. denverensis P3) and COM P3‐P6 ( C. denverensis P3/ N. circulans P6) showed the maximum enzyme activity of 0.388 U mL −1 (±0.041) and 0.45 U mL −1 (±0.03), respectively (Figure 6B ). The COM P1‐P3 also showed good degradation ability in xylan [0.32 U mL −1 (±0.014)], where the community enzyme activity was increased by 42% (DES 1.42) compared to the respective monocultures (Figure 6C,D ). Consequently, M. luteus P1 and C. denverensis P3 also possess a high PMA of 0.126, as predicted through the community model (GCM P1‐P3 ) analysis. Therefore, the experimental enzymatic synergies agree with the model‐predicted metabolic assistance between M. luteus P1 and C. denverensis P3. Overall, the model‐predicted PMA of the pairwise communities showed a good correlation ( Pearson r = 0.86, p = 0.034) with the DESs in the seven growth‐compatible bacterial cocultures (Figure 5B ). Hence, the in silico parameters showed good prediction capabilities in identifying the beneficial bacterial pairs. Overall, six pairwise communities, i.e., COM P1‐P3 , COM P3‐P4 , COM P3‐P5 , COM P3‐P6 , COM P4‐P5 , and COM P5‐P6 , have shown significant enzymatic synergies and increased community activity in one of the given substrates. Therefore, assessing the newly defined parameters of PGSI and PMA helps screen the synergistic consortia by reducing the number of testable bacterial combinations. Figure 6 Comparative analysis of the community enzyme activity and DES. The alterations in the FPase (A), CMCase (B), and xylanase (C) activities in the 9 pairwise coculture (horizontal axis) have been compared to the sum of the individual activity in the vertical axis. The higher activity in the coculture signifies the enzymatic synergism between microbial pairs. (D) The horizontal axis represents the degree of enzymatic synergism (DES) value of the 9 bacterial pairs (vertical axis) in different lignocellulosic substrates. All the data points represent the mean value from the triplicate experimental measurements, and the error bar represents the standard deviation of each measured data. However, it has been observed that the best‐performing community on one substrate sometimes showed lower degrading potential on other substrates. For example, although COM P1‐P3 showed efficient enzyme activity in CMC and xylan, it has shown very low degradation potential [0.28 U mL −1 (± 0.01)] and DES (1.05) in FP (Figure 6D ). Conversely, in FP (FPase), COM P3‐P5 and COM P5‐P6 were the best‐performing communities, with maximum DES activity of 1.53 and 1.27, respectively. However, despite demonstrating high FPase activity, COM P5‐P6 underperforms in CMC, leading to a 17.67% decrease in activity (Figure 6D ). Hence, further optimization of community composition and design in larger communities is required to achieve consistent degradation capabilities across all of the provided lignocellulosic substrates (FP, CMC, and xylan). The knowledge of growth and enzymatic compatibility derived from genome‐scale models and coculture experiments is essential for designing larger communities with the best‐performing candidates. Here, fellow community members can compensate for a particular strain's enzymatic limitation for efficient substrate utilization. Therefore, we have extended the proposed community modeling pipeline and flux‐based parameters to measure the biochemical and growth compatibilities in larger communities, thereby identifying compatible microbial combinations. 3.4 Designing GCM‐Guided Synergistic Consortia for Lignocellulose Degradation The growth compatibility (PGSI) and metabolic assistance (PMA) derived from the community models and the development of bacterial coculture help to screen six synergistic bacterial pairs with lignocellulose degradation potential. Assessing the enzymatic activities of these model‐driven bacterial cocultures helps identify different best‐performing bacterial pairs in FP, CMC, and xylan. Overall, the pairwise consortia, COM P3‐P5 , COM P4‐P5 , and COM P5‐P6, performed best in FP. On the other hand, COM P1‐P3 , COM P3‐P4 , COM P3‐P5, and COM P3‐P6 showed maximum degradation potential in CMC and xylan. Hence, to develop a more robust community that can degrade all the types of lignocellulosic substrates, three‐membered bacterial consortia have been developed by combining six best‐performing individual strains (P1‐P6) identified earlier. Combining these six individual strains can generate 20 distinct combinations ( 6 C 3 ) of three‐membered community compositions. Therefore, a total of 20 three‐membered GCMs have been reconstructed to test the growth compatibility of microbial consortia with the PGSI parameter. Out of these 20 three‐membered GCMs, 7 models exhibited positive growth support, with an average PGSI ranging from 0.01 to 0.327. On the other hand, neutral and negative growth support have been observed for 5 and 8 community models, respectively (Table S10 ). The assessments of metabolic compatibility also showed good community metabolic assistance (CMA > 0.1) in the growth‐compatible GCMs. Among the 7 growth‐compatible communities predicted through the PGSI, 4 three‐membered bacterial consortia, i.e., COM P1‐P3‐P4 , COM P1‐P3‐P5 , COM P3‐P4‐P5 , and COM P3‐P5‐P6 were tested experimentally to determine their synergistic lignocellulolytic ability. The lignocellulosic bio‐conversion potential of these model‐driven three‐membered bacterial consortia has been tested experimentally with CMC, FP, and xylan as metabolic substrates. Overall, among the four compatible bacterial communities tested experimentally, two bacterial consortia, i.e., COM P1‐P3‐P5 and COM P3‐P5‐P6 , have shown robust enzymatic degradation potential in all the provided lignocellulosic substrates. For instance, the three‐membered community model GCM P1‐P3‐P5 showed an average PGSI of 0.116 between M. luteus P1, C. denverensis P3, and Brevibacterium sp. P5 (Table S11 ). Moreover, the good community metabolic assistance (CMA = 0.095) between these microbial species may also help to increase the collaborative metabolic and enzymatic potential of COM P1‐P3‐P5 . When this synergistic bacterial consortium (COM P1‐P3‐P5 ) was developed experimentally, it showed a maximum enzymatic activity of 0.305 U mL −1 (±0.041), 0.52 U mL −1 (±0.068), and 0.459 U mL −1 (±0.046) for FP, CMC, and xylan, respectively (Figure 7A ). Hence, the GCM‐predicted growth and metabolic synergisms help to increase the enzymatic degradation potential of these bacterial consortia by lowering the substrate‐dependent limitation of the individual bacterial strains. During the monoculture experiment, the individual strains P1 and P5 showed moderate enzymatic activities [(0.1 U mL −1 ) (±0.012)] in CMC. However, when they had grown in the three‐membered consortia COM P1‐P3‐P5 with C. denverensis P3, the community showed a more proactive (~30% higher) enzymatic degradation potential against CMC. Therefore, the substrate‐specific limitation of the individual bacterial strains P1 and P5 has been covered by fellow community members (P3) in the consortia and provides a higher metabolic potential for efficient lignocellulose bio‐conversion. Compared to the pairwise coculture systems, the three‐membered consortium COM P1‐P3‐P5 performed 15.6%, 30%, and 9.5% higher FPase, CMCase, and xylanase activities, respectively. Figure 7 The FP, CMC, and xylan degradation potential of three‐membered bacterial consortia: The FPase (black), CMCase (red), and xylanase (blue) activity of the bacterial consortia (A) COM P1‐P3‐P5 (B) COM P3‐P5‐P6 at different time point. Moreover, the model‐driven information about the bacterial synergisms also helps to elevate the combined enzymatic activity of the individual strains in the experimentally developed consortium COM P3‐P5‐P6 . For instance, the individual strains, i.e., P3, P4, and P6 in COM P3‐P5‐P6 exhibited good xylanolytic potential [(~0.2 U mL −1 ) (±0.032)] in monoculture and pairwise coculture. When these three well‐performing strains were combined in COM P3‐P5‐P6 , the bacterial consortia showed the highest xylanase activity of 0.617 U mL −1 (±0.088) (Figure 7B ). Overall, in the defined microbial consortium COM P3‐P5‐P6 , the FP, CMC, and xylan bioconversion potential were increased by 44.1%, 8.4%, and 3.5%, respectively. Consequently, the model‐predicted (GCM P3‐P5‐P6) growth support index (PGSI = 0.22) and metabolic assistance (CMA = 0.13) were also found to be high in this defined consortium. Therefore, assessing the newly defined flux‐based parameters helps screen the synergistic consortia by reducing the number of testable bacterial combinations. The increase in the number of microbial species can exponentially elevate testable microbial combinations for the development of synthetic microcosms. Handling these large sets of microbial combinations and assessing their metabolic interlinks is challenging as well as highly time‐consuming. Hence, the model‐guided coculture system design approach aids in formulating the optimal bacterial composition with high enzymatic synergisms and growth compatibility while reaching higher activity on the provided lignocellulosic substrates. The community modeling method developed here can help manipulate the microbial community composition and metabolic activities to aid novel experimental strategies for bioengineering applications.\n\n4 Discussion and Conclusion Implementation of the genome‐scale modeling integrated with the conventional microbial coculture helped us develop a complete strategy for designing synergistic microbial consortia for lignocellulose bioconversion. Initially, the individual bacterial isolates (P1–P6) from the termite gut showed varied enzyme activities with substrate‐specific limitation in the provided lignocellulosic materials, i.e., CMC, FP, and xylan. The flux distribution via active biochemical pathways was assessed by constructing individual GEMs for the six best‐performing lignocellulolytic microbial strains. Further, the individual GEMs were integrated to reconstruct genome‐scale community metabolic models (GCMs) for 15 possible bacterial pairs. The maximization of biomass formation has been set as the objective function of the individual GEMs and pairwise community model. Cellulose (CMC and FP) and xylan have been used as metabolic substrates while optimizing the metabolic model. Therefore, the optimization of biomass formations will ultimately lead to the enhancement of substrate uptake or the breakdown of cellulose or hemicellulose. We have incorporated the extracellular degradation reactions of cellulose into the GEMs based on gene and biochemical information, as the cell cannot transport cellulose directly. For instance, we have incorporated reactions associated with endoglucanase, which converts cellulose to cellodextrin, exoglucanase, which converts cellodextrin to cellobiose, and beta‐glucosidase, which converts cellobiose to glucose, into the GEMs. Hence, the optimization of the biomass function provides essential information about the flux distribution patterns in the individual GEMs and pairwise community model while degrading the lignocellulosic substrate. Implementing the flux‐based parameters, namely PGSI and PMA, helps evaluate pairwise growth compatibility and metabolic assistance through GCM analysis. The PGSI and PMA‐driven growth and metabolic compatibility of the bacterial pairs were found to be essential for a mutualistic bacterial consortium. A total of 9 metabolically compatible bacterial pairs predicted from the in silico GCM analysis have been validated by designing experimental coculture systems. The pairwise community model with novel flux‐based parameters accurately predicted growth and metabolic synergisms in seven bacterial cocultures for lignocellulosic bio‐conversion, demonstrating 78% accuracy. Moreover, the PGSI derived through the GCMs analysis correlated well ( Pearson r = 0.86, p = 0.012) with the experimentally measured growth rate enhancement in bacterial coculture. The enzymatic activities of these bacterial cocultures have been tested with the FP, CMC, and xylan. Compared to the bacterial monoculture, the pairwise communities showed up to 53% higher activities in one of the given substrates (FP, CMC, and xylan). Interestingly, the model‐derived PMA of the bacterial communities showed good agreement ( Pearson r = 0.79, p = 0.034) with the DESs in the coculture systems, which signifies the reliability of the in silico assessment of the metabolic synergisms. Furthermore, we combined the six individual strains to form three‐membered communities, which enhanced the bacterial lignocellulolytic ability. To evaluate the growth compatibility among all the possible bacterial combinations, 20 ( 6 C 3 ) three‐membered GCMs have been reconstructed. The assessment of the PGSI and CMA parameters facilitated the screening of seven compatible three‐membered bacterial communities among 20 possible combinations. The model‐predicted bacterial synergisms were further tested by developing compatible bacterial consortia with experimental setups. Here, the microbial consortia comprising C. denverensis P3, Brevibacterium sp. P5, and N. circulans P6 (COM P3‐P5‐P6 ); and M. luteus P1, C. denverensis P3, and Brevibacterium sp. P5 (COM P1‐P3‐P5 ) exhibited robust degradation potential and higher enzyme activities in FP, CMC, and Xylan. Therefore, the model‐driven evaluation of bacterial metabolic assistance and growth compatibility facilitates the design of synergistic bacterial consortia with enhanced lignocellulolytic enzyme activities. Overall, the proposed community modeling strategy and flux‐based assessment of the microbial synergisms can be extended to measure biochemical and growth compatibilities in larger communities, thereby identifying compatible microbial combinations. The model‐predicted synergistic microbial combination can be tested further with a lesser experimental hurdle. We can further enhance the model‐assisted microbial consortia by optimizing the microbial ratio in the seed culture or by incorporating new microbial members into the established consortia. This could pave the way for the large‐scale implantation of synthetic microbial consortiums in bioproduction."
} | 11,503 |
33005496 | PMC7513772 | pmc | 3,144 | {
"abstract": "The benthic environments of coral reefs are heavily shaped by physiochemical factors, but also the ecological interactions of the animals and plants in the reef ecosystem. Microbial populations may be shared within the ecosystem of sediments, seagrasses and reef fish. In this study, we hypothesize that coral reef and seagrass environments share members of the microbial community that are rare in some habitats and enriched in others, and that animals may integrate this connectivity. We investigated the potential connectivity between the microbiomes of sediments, seagrass blades and roots ( Syringodium isoetifolium ), and a seagrass-specialist parrotfish ( C. spinidens ) guts in reef areas of Fiji. We contrasted these with sediment samples from the Florida Keys, gut samples from surgeonfish ( A. nigricauda , Acanthurinae sp. unknown, C. striatus ), and ocean water microbiomes from the Atlantic, Pacific and Indian Oceans to test the robustness of our characterizations of microbiome environments. In general, water, sediment and fish gut samples were all distinct microbiomes. Sediment microbiomes were mostly similar between Fiji and Florida, but also showed some regional similarities. In Fiji, we show connectivity of a shared microbiome between seagrass, fish and sediments. Additionally, we identified an environmental reservoir of a surgeonfish symbiont, Epulopiscium . The connection of these ecosystem components suggests that the total microbiome of these environments may vary as their animal inhabitants shift in a changing ocean.",
"conclusion": "Conclusions We investigated the microbiomes of oceanic waters near coral reefs, coral reef sediments in Fiji and Florida, and coral reef fish in Fiji. We see that these are distinct microbiomes, however, there is connectivity between physically circulating material, mediated by fish. These highly diverse benthic environments are created by unknown factors, particularly in Fiji. It is likely that chemical factors are likely a large determinant of total populations. However, the benthic environments in these areas are intimately linked with the animal populations of the reefs. With the high potential for change in the animal ecosystem of the fish, these communities should continue to be cataloged. Understanding connectivity among reefs, across multiple geographic and trophic scales remains one of the major challenges in tropical coastal ecology. This work suggests that microbial diversity may mirror larger macroecological processes and that connectivity exists between seagrass, sediments and fish in an intimately connected ecosystem. This small, initial study provides interesting hypotheses to pursue in future studies.",
"introduction": "Introduction Marine microbes play an important role in the ecology of coral reef systems, including mediating algal:coral interactions ( Smith et al., 2006 ) and providing settlement cues ( Ainsworth, Vega Thurber & Gates, 2010 ). In coral reef-associated systems, such as seagrass beds, there is a complex relationship between the seagrass plants and the microbial community, since seagrasses can release oxygen through their roots and impact local biogeochemistry ( Duarte, Holmer & Marbà, 2005 ). Coral reef fish interact with the surrounding water and feed on seagrass or benthic material, which influences their gut microbiome ( Smirga, Sandin & Azam, 2010 ; Clements et al., 2014 ). Our understanding of the relationships among the microbial community, the living structural elements (corals, seagrasses etc.) and the associated fish community are limited, yet we know that microbial linkages should permeate classical trophic interactions in reef systems. Some ecological interactions are known for microbial connectivity in these systems, for example, the algae, Symbiodiniaceae spp. that forms the basis of photosynthetic activity for scleractinian corals, is dispersed via the guts of coral-eating fish through their defecation ( Castro-Sanguino & Sánchez, 2012 ). It has also been shown that fish gut microbiomes shift upon fish settlement into a reef system ( Parris et al., 2016 ). Yet little is known about the microbiomes of reef sediments, which are important for nutrition in both fish ( Wilson et al., 2003 ) and invertebrates ( Uthicke, 1999 ). In seagrass and coral reef communities, microbial composition plays a leading role in disease defense and carbon sequestration ( Asmus & Asmus, 2000 ; Küsel et al., 2006 ; Gantar et al., 2011 ; Gil-Agudelo et al., 2007 ), and herbivorous fish grazing is critical to ecosystem health ( Heenan & Williams, 2013 ). Little is known about how divergent fish gut microbiomes are across species and genera ( Clements et al., 2014 ). Fish, including parrotfish (Scarine members of Labridae; herbivores in this study) and surgeonfish (Acanthuridae; detritovores in this study), are species highly characteristic of coral reef ecosystems ( Frydl & Stearn, 1978 ; Polunin, Harmelin-Vivien & Galzin, 1995 ). Similar microbial communities have been seen in parrotfish and surgeonfish guts, with major differences being seen based on diet types, across algavores and zooplankton feeders compared to detritivores and omnivores ( Clements et al., 2014 ). Initial studies investigating fish gut microbial diversity examined a variety of feeding strategies, and saw differentiation across diet types, but did not take into account different portions of the gut, which may have distinct microbiomes ( Miyake, Ngugi & Stingl, 2015 ). Notably, surgeonfish also have symbiotic gut microbes, Epulopiscium , that have no known environmental reservoir ( Flint et al., 2005 ; Grim, Nemeth & Montgomery, 2013 ). Examination of the microbiomes of waters, food sources, fish guts and the sedimentary environment will allow us to understand what role fish may play on dispersal and connectivity among microbial communities, including the potential for symbiont dispersal ( Grim, Nemeth & Montgomery, 2013 ). Here we investigate this ecological interaction over multiple spatial, ecological, and phylogenetic scales. We hypothesize that coral reef and seagrass environments, and the animal hosts that interact in them, have a connected microbiome, where shared members of the microbiome are rare in some habitats within the reef and enriched in others. We predict that interactions within the reef ecosystem will dictate the degree of microbial connectivity. We first examine regional trends, comparing the systems within our study to multiple waters sampled near other coral systems, to show the distinction of these habitats as individual microbiomes. Next, we look at microbial communities at a local biogeographic scale and compare the microbial diversity of inshore reefs in both Fiji and Florida. Lastly, we track the connectivity in microbial similarities among a three-group system in Fiji (seagrass blades and roots, the sediment that seagrass was growing in, and the digestive microbial community of a seagrass eating parrotfish) as well as the digestive microbial community of three species of detritivore surgeonfish collected from the reefs and seagrasses in coastal Fiji. In this system, we see there is an environmental reservoir of the surgeonfish gut symbiont, Epulopiscium , which has previously been undetected. In total, we show that these distinct microbiome environments have shared microbial components, which suggests a connected ecosystem and dispersal pathway for the microbes in coral reef environments.",
"discussion": "Discussion Our study examined the microbiome of multiple environments that should interact on a coral reef: the sediments, fish, seagrass and oceanic waters. While our study is limited by a lack of replication, uneven sampling efforts and water samples that were not taken in-situ, we are able to see broad trends in microbiomes and explore details of microbial connectivity across samples. We investigated sediments from both Fiji and Florida reef systems. In general, these sediments are quite similar although local similarity is expected ( Ruff et al., 2015 ; Hanson et al., 2012 ). The sediment samples consistently grouped together, separate from oceanic waters. Surprisingly, we noted a trend of high diversity within benthic Fiji samples, which mirrors large-scale patterns in macroecology, as the Indo-Pacific harbors a higher diversity of fish, corals, and mangroves ( Roberts et al., 2002 ). Whether microbial trends are driven by the same factors as macroorganisms is unknown, as microorganisms are classically expected to diversify based on local chemical factors ( Hanson et al., 2012 ). We, unfortunately, were unable to collect chemical data on these environments to compare during our study, as time and resources were limited. The driving forces behind the consistently high diversity in Fiji, compared to the reef environment in Florida, are intriguing and should be investigated and compared with other reef systems in future studies. We observe a general trend of decreased microbial diversity in association with seagrasses (blades and roots) and fish. This agrees with trends seen in more comprehensive studies, that host-associated habitats have the least microbial diversity ( Schloss et al., 2016 ). The strictly herbivorous parrotfish, C. spinidens , shows the lowest diversity. The sediment communities are generally similar between Fiji and Florida, despite different biogeographic provinces and depths, whereas the fish showed distinct populations, both within the fish and across fish species. Within the parrotfish, populations shift along the gut, sometimes showing drastic shifts from the pharyngeal mill through hindgut (samples P1–P4; Fig. 3 ). There are high numbers of Planctomycetes, Verrucomicrobia and differing abundances of Proteobacteria and other less dominant groups. Overall, the Firmicutes are the most distinct group within the fish cluster, and are present in varying amounts in all samples, except for being distinctly low in the hindgut of C. striatus . The contributions of microbial populations to fermentation in herbivorous fish has been contested ( Clements et al., 2014 ), yet the drastically different communities in these regions suggest microbes are actively responding to gut position. However, when we consider the overall relatedness of the samples, we see that in general, despite differences in species and gut location, the fish samples are considered similar to each other, compared to ocean waters, seagrasses, sediments and deep sediments. While the fish communities are distinct from the environmental samples, they do share common organisms. We examined the shared microbiome across the Fijian samples and see that specific organisms can be tracked between the external environment and the fish. OTUs from the Rhodobacteraceae and Pirellulaceae are abundant in the fish guts and in low abundance in the environment. An OTU from Herbaspirillum was most abundant in seagrass and parrotfish guts, linking the consumer and food source. The drop in abundance in mid and hindguts shows that the fish are likely digesting these organisms, but some signatures make it through. This confirms our hypothesis that a coral reef and seagrass environment contains microbes that are shared across habitats, including their animal hosts, and increase in number in only some habitats. Whether or not these signatures are from live organisms is unknown since this analysis was only performed on DNA and could potentially detect extracellular DNA or dead cells. Alongside these shared populations, we also noted that the genus Epulopiscium was seen across the samples in varying abundances. While it was most abundant in only the surgeonfish guts, where it is widely known as a symbiont ( Clements, Sutton & Choat, 1989 ), it was also seen in many environmental samples, particularly the Florida Keys sediments. Notably, the detection of Epulopiscium is in low abundance in the parrotfish sample, and different lineages of Epulopiscium dominate each of the surgeonfish species sampled, suggesting these lineages are, as expected, symbiotic in the sampled surgeonfish as the observed pattern suggests species–specific host adaptation. The same exact lineage is seen across multiple environmental samples, and is most abundant in the Florida Keys samples that are most likely to be exposed to fish, near sponges or at the head of spur and groove sediment, which are most likely to be exposed to fish. The lineages of Epulopiscium we found also branch away from known sequences of Epulopiscium , suggesting more diversity of this group is present in the environment. The mechanism of transmission of this symbiont has been debated, particularly since it unknown to survive outside of the host system ( Flint et al., 2005 ). An environmental repository of Epulopiscium has not yet been defined, although survival outside of the fish could take place via a sporulated form, which would be detectable in our analysis ( Flint et al., 2005 ; Grim, Nemeth & Montgomery, 2013 ). This study shows that cells of Epulopiscium reside in sedimentary environments. This, however, should be taken with the caveat that no activity is defined by this measurement, and the ability for the symbionts to be taken up from the sedimentary environment cannot yet be established. However, it has been shown previously that these symbionts are cleared when fish are starved ( Fishelson, Montgomery & Myrberg, 1985 ; Montgomery & Pollak, 1988 ), suggesting that active recharging of their symbiont population could be occurring through this sedimentary reservoir. surgeonfish have previously been shown to harbor gut communities that reflect their host dietary preferences and taxonomy ( Miyake, Ngugi & Stingl, 2015 ). However, past studies did not section gut samples or explore the benthic environment for relatedness. Some of the materials from gut communities, such as the symbionts that proliferate in surgeonfish guts, are seen in the benthic community."
} | 3,491 |
29593768 | PMC5854654 | pmc | 3,145 | {
"abstract": "Legumes are able to form a symbiotic relationship with nitrogen-fixing soil bacteria called rhizobia. The result of this symbiosis is to form nodules on the plant root, within which the bacteria can convert atmospheric nitrogen into ammonia that can be used by the plant. Establishment of a successful symbiosis requires the two symbiotic partners to be compatible with each other throughout the process of symbiotic development. However, incompatibility frequently occurs, such that a bacterial strain is unable to nodulate a particular host plant or forms nodules that are incapable of fixing nitrogen. Genetic and molecular mechanisms that regulate symbiotic specificity are diverse, involving a wide range of host and bacterial genes/signals with various modes of action. In this review, we will provide an update on our current knowledge of how the recognition specificity has evolved in the context of symbiosis signaling and plant immunity.",
"conclusion": "Conclusion and Future Perspectives Specificity in the legume-rhizobial symbiosis results from a suite of signal exchanges between the two symbiotic partners (summarized in Figure 1 ). Recent studies have just begun to reveal the underlying molecular mechanisms that regulate this specificity, and there are many challenging questions waiting to be answered. Effector-triggered immunity has been shown to be an important factor in determining host range of rhizobia in soybeans but the cognate effectors have not been clearly defined. In addition, what are the genes that control nodulation specificity in the Medicago-Sinorhizobium interaction where the bacterial partner lacks the type III secretion system? Cloning and characterization of the NS1 locus in M. truncatula ( Liu et al., 2014 ) will provide novel insights into this question. We now know that NCR peptides regulate nitrogen fixation specificity in Medicago and possibly in other closely related legumes, but we lack mechanistic understanding of how these peptides work. Do the pro- and anti-symbiotic peptides interact with the same bacterial targets? How do the amino-acid substitutions affect the peptide structure and function? How is nitrogen fixation specificity regulated in the NCR-lacking legumes such as soybeans where bacteria undergo reversible differentiation? These are just a handful of outstanding questions that need to be addressed. Answering these questions will certainly enrich our knowledge of how specificity is controlled and allow us to use such knowledge to develop tools for genetic improvement of symbiotic nitrogen fixation in legumes. FIGURE 1 Symbiosis signaling and plant immunity involved in recognition specificity in the legume-rhizobial interactions (indicated by the red stars). (A) The process of infection and nodule development. A mature indeterminate nodule contains a meristem zone (I), an infection zone (II), an interzone (IZ), a nitrogen fixing zone (III), and a senescent zone (IV). (B) The host secretes flavonoids to induce the expression of bacterial nodulation ( nod ) gene through the activation of NodD proteins. The enzymes encoded by the nod genes lead to the synthesis of Nod factors (NF) that are recognized by host Nod factor receptors (NFRs). Recognition specificity occurs both between Flavonoids and NodDs and between NF and NFRs. (C) In addition to NF signaling, bacteria also produce extracellular polysaccharides (EPS) and type III effectors to facilitate their infection in compatible interactions, but these molecules may also induce immune responses causing resistance to infection in incompatible interactions. (D) Certain legumes such as Medicago encode antimicrobial nodule-specific cysteine-rich (NCR) peptides to drive their bacterial partners to terminal differentiation that is required for nitrogen fixation. However, some rhizobial strains cannot survive the antibacterial activity of certain peptide isoforms, leading to formation of nodules defective in nitrogen fixation.",
"introduction": "Introduction The legume-rhizobial symbiosis starts with a signal exchange between the host plant and its microsymbiont ( Oldroyd, 2013 ). Recognition of compatible bacteria by the host induces cortical cell divisions to form root nodule primordia, and simultaneously initiates an infection process to deliver the bacteria into the nodule cells. Infection of most legumes involves the development of plant-made infection threads that initiate in the root hair. The infection threads harboring dividing bacteria grow through the epidermal cell layer into the nodule cells, where the bacteria are released and internalized in an endocytosis-like process. In nodule cells, individual bacteria are enclosed by a membrane of plant origin, forming an organelle-like structure called the symbiosome, within which the bacteria further differentiate into nitrogen-fixing bacteroids ( Jones et al., 2007 ; Oldroyd et al., 2011 ). Symbiotic nodule development involves synchronous differentiation of both nodule and bacterial cells. Legume nodules can be grouped into two major types: indeterminate (e.g., pea, clovers, and Medicago ) and determinate (e.g., soybeans, common bean, and Lotus ) ( Nap and Bisseling, 1990 ; Hirsch, 1992 ). Indeterminate nodules originate from cell divisions in the inner cortex and possess a persistent apical meristem. Consequently, indeterminate nodules are cylindrical in shape, with a developmental gradient from the apex to the base of the nodule, which can be divided into different nodule zones ( Nap and Bisseling, 1990 ). In contrast, determinate nodules result from cell divisions in the middle/outer cortex of the root, lack a persistent meristem, and are spherical in shape. Cell divisions of a determinate nodule cease at early developmental stages and the mature nodule develops through cell enlargement; as such, the infected cells develop more or less synchronously to the nitrogen-fixing stage. In both nodule types, the symbiotic nodule cells undergo genome endoreduplication, leading to polyploidization and cell enlargement. Parallel to the nodule cell development is the differentiation of the nitrogen-fixing bacteroids. Depending on the host, but independent of the nodule type, such bacterial differentiation can be terminal or reversible. Terminal differentiation is featured by genome endoreduplication, cell elongation, increased membrane permeability, and loss of reproductive ability, while in reversible differentiation the bacteroids retain cell size and DNA content similar to free-living bacteria ( Kereszt et al., 2011 ; Oldroyd et al., 2011 ; Haag et al., 2013 ). Compared to free-living bacteria, the bacteroids display dramatic changes in transcriptome, cell surface structure and metabolic activities so that they become better adapted to the intracellular environment and dedicated to nitrogen fixation ( Mergaert et al., 2006 ; Prell and Poole, 2006 ; Haag et al., 2013 ). Both legumes and rhizobial bacteria are phylogenetically diverse. No single rhizobial strains can form symbiosis with all legumes, and vice versa. Specificity occurs at both species and genotypic levels ( Broughton et al., 2000 ; Perret et al., 2000 ; Wang et al., 2012 ). This can take place at early stages of the interaction so that the same bacterial strains can infect and nodulate one host plant but not another ( Yang et al., 2010 ; Wang et al., 2012 ; Tang et al., 2016 ; Fan et al., 2017 ). Incompatibility also frequently happens at later stages of nodule development such that nitrogen-fixing efficiency differs significantly between different plant-bacteria combinations ( Wang et al., 2012 , 2017 , 2018 ; Yang et al., 2017 ). Symbiotic specificity results from the changing of signals from both host and bacterial sides; as such, various recognition mechanisms have evolved during the process of co-adaptation. Knowledge of the genetic and molecular basis of symbiotic specificity is important for developing tools for genetic manipulation of the host or bacteria in order to enhance nitrogen fixation efficiency. In this review, we will discuss our current understanding of the evolution of specificity in the root nodule symbiosis."
} | 2,042 |
26300765 | PMC4523791 | pmc | 3,146 | {
"abstract": "The mesoscopic activity of the brain is strongly dynamical, while at the same time exhibits remarkable computational capabilities. In order to examine how these two features coexist, here we show that the patterns of synchronized oscillations displayed by networks of neural mass models, representing cortical columns, can be used as substrates for Boolean-like computations. Our results reveal that the same neural mass network may process different combinations of dynamical inputs as different logical operations or combinations of them. This dynamical feature of the network allows it to process complex inputs in a very sophisticated manner. The results are reproduced experimentally with electronic circuits of coupled Chua oscillators, showing the robustness of this kind of computation to the intrinsic noise and parameter mismatch of the coupled oscillators. We also show that the information-processing capabilities of coupled oscillations go beyond the simple juxtaposition of logic gates.",
"introduction": "1. Introduction It has been established that the healthy brain operates in a highly coordinated way that involves different neural oscillations spanning through multiple spatiotemporal scales (Freeman, 1975 ; Singer, 1993 , 1999 ; Başar et al., 2000 ; Varela et al., 2001 ; Ward, 2003 ; Buzsáki and Draguhn, 2004 ). Even though these oscillatory rhythms may have different synchronization properties (Kopell et al., 2000 ), they have been explained as a result of the balance between excitatory and inhibitory neurons in a network (Börgers and Kopell, 2003 ; Börgers et al., 2005 ). In turn, this synchronous firing may subserve complex coordinated patterns of spiking activity which may be transmitted in large neural networks with high temporal accuracy over long distances (Abeles, 1991 ; Rodriguez et al., 1999 ; Abeles et al., 2004 ; Asai et al., 2008 ; Asai and Villa, 2012 ; Barardi et al., 2014b ). It has also been accepted that the oscillatory activity exhibited by brain signals such as local field potentials (LFP), electroencephalograms (EEG) and magnetoencephalograms (MEG), arises from the synchronized activity of large neuronal assemblies. Such collective dynamics throughout the different scales in the brain is likely to determine the functional role of normal and aberrant synchronization mechanisms during adaptive and cognitive processes as well as brain diseases (Del Prete et al., 2004 ; Iglesias and Villa, 2010 ; Pons et al., 2010 ; Villa and Tetko, 2010 ). Synchronization's role in coordinating and processing information at different spatiotemporal scales has been also stressed (Lachaux et al., 1999 ; Stam and de Bruin, 2004 ; Busáki, 2006 ; Malagarriga et al., 2015 ). For instance, synchronization-based selectivity of visual response has been studied in the context of monkeys and cats (Castelo-Branco et al., 2000 ; Womelsdorf et al., 2006 ) or even in humans (Rodriguez et al., 1999 ). Besides, synchronization participates in the odor perception (Stopfer et al., 1997 ; Laurent et al., 2001 ; Blumhagen et al., 2011 ) and coherence of stimuli also affects the selective capability of oscillatory networks (Börgers and Kopell, 2008 ; Börgers et al., 2008 ). The processing and computation mechanisms based in all this diversity of synchronized elements has also been studied in detail (Engel et al., 2001 ; Fries, 2009 ; Maris et al., 2013 ; Nikolić et al., 2013 ; Womelsdorf et al., 2014 ). Thus, the interaction of different synchronized ensembles of neurons (Womelsdorf et al., 2007 ; Wulff et al., 2009 ) plays a role in tasks like learning item-context associations (Tort et al., 2009 ), selective attention (Fries et al., 2001 , 2008 ; Womelsdorf and Fries, 2007 ; Bosman et al., 2012 ), or even conscious perception (Melloni et al., 2007 ; Levy et al., 2013 ). At the larger spatial scale in the brain, synchronization participates in the control of task-switching (Phillips et al., 2013 ) and is studied routinely in normal and abnormal EEG and MEG recordings (Stam, 2005 ). Even though much progress in the understanding of these synchronization mechanisms has been gained during many years, it is not fully understood yet how these synchronization relations are established with the participation of different scales simultaneously, or how they operate at the same time without interfering with each other (Barardi et al., 2014a ). So, for instance, the information processing capacity of the brain operating under multiple scales has been described very often in terms of logic calculus. At the most microscopic level, the idea of logic calculus based on neuronal activities was embedded in the seminal work of McCulloch and Pitts ( 1990 ). Neuronal circuitry performing logic operations was physically implemented in cell cultures of in vitro models of selected brain areas (Feinerman et al., 2008 ; Wolf and Geisel, 2008 ). This approach is mainly based on action potentials and on the connectivity within the network, rather than on a dynamical analysis of the ongoing activity. At the cellular level neurons have revealed that, in addition to behaving as a bistable system, they can be driven into a continuous oscillation by means of selected voltage-dependent inward currents controlled by intracellular calcium concentrations (Contreras and Steriade, 1995 ; Hughes et al., 2002 ; Crunelli et al., 2005 ). Besides, from the microscopic point of view, neurons may coordinate their firing in response to incoming stimuli, opening the way to a neurocomputing paradigm characterized by different synchronized states where the neurons oscillate with equal frequencies and specific phase relationships (Hoppensteadt and Izhikevich, 2000 ; Zanin et al., 2011 ). By associating logical states to the dynamics of coupled oscillators, all usual Boolean operations can be implemented and a full computational model can be obtained (Xu et al., 2004 ). Beyond the cellular level of neuronal oscillators, it was recently demonstrated that circuits of neurons embedded within a large-scale network of cortical cells were able to express logic functions that are dependent on complex spatiotemporal patterns (Vardi et al., 2013 ; Menon and Sinha, 2014 ). This type of analysis can also be made at the mesoscale. Large brain circuits are frequently described as networks of nodes associated with neuronal assemblies, evolving at the mesoscopic scale, in such a way that their dynamics can be considered as that of limit-cycle oscillators subjected to weak forcing and coupling. Phase-reduction theory has revealed synchronization to be among the most relevant features that determine the dynamical states of these systems (Pikovsky et al., 2003 ; Brown et al., 2004 ). Furthermore, coupled oscillator theory has established the conditions that allow all the nodes, or a subgroup of them, to operate in one of several synchronization regimes, including complete, lag, generalized, and phase synchronization (Boccaletti et al., 2002 ; Li and Chen, 2004 ). In fact, recent work shows that in networks of mesoscopic brain oscillators different forms of synchronization might coexist (Malagarriga et al., 2015 ). This phenomenon enlarges the processing capacity of neural oscillators, and endows the corresponding networks with stability, flexibility and robustness against perturbations (Zanette, 2004 ). In this paper we present a combination of a theoretical approach and its experimental implementation that may shed light on possible mechanisms of brain computation based on synchronized oscillations. Specifically, we show that networks of neural mass oscillators may process inputs in a complex Boolean-like manner. So, the combination of all the fluctuating inputs received by each oscillator in the network determines the global network dynamical response. Every combination of inputs received by the nodes produces a synchronization pattern that relates the dynamics of all the nodes of the network. We interpret the different synchronization states (i.e., phase, generalized, lag, or complete synchronization) of two oscillators in the network as Boolean variables that allow to classify the response of inputs onto pairwise logic gates of different nature. By tuning the characteristics of the oscillatory input acting upon the neural masses, the pairwise coordinated activity changes accordingly. Each form of synchronization brings different information in terms of the synchronized motion in phase space, thus providing additional characterization of such incoming stimuli in the form of coordination evolution. We show that several distinct logical operations can be implemented, in this way, by the same type of neural mass network. However, far from suggesting that the processing capacity of the brain is the result of a more or less complex boolean circuitry, we postulate that it results from its very complex collective dynamics in which synchronization may play a very relevant role (Buzsáki and Draguhn, 2004 ). The capacity of synchronized oscillations to perform Boolean-like operations is demonstrated by a physical implementation in the form of an electronic system consisting of coupled Chua oscillators driven by oscillatory input signals. Finally, we show that the processing possibilities of larger networks composed by this type of systems go beyond the simple juxtaposition of logic gates.",
"discussion": "4. Discussion In order to address how information can be processed, from the perspective of synchrony, at the mesoscopic scale we have analyzed theoretically a network of coupled neural mass oscillators. This network uses synchronization as the essential ingredient to process the information arriving to/from each of its nodes. We have seen that by interpreting the inputs arriving to the oscillators of the network as “0” or “1” and defining the output of the binary operation in terms of the synchronized state of the two oscillators also as “0” or “1”, several binary logic gates can be constructed. This dependence of the synchronization level of two columns on their stimulation has been observed experimentally, for instance, in the cat visual cortex (Gray et al., 1989 ). Interestingly, different binary logic gates constructed using the same physiological circuitry result only from changes in the input signals received by the oscillators (e.g., AND, OR, and XOR gates in Figure 2 ). This rich behavior shown by only two coupled cortical columns may be very fruitful when many other columns are considered. In this sense, the ability to analyze input signals with very different characteristics (average density of spikes, amplitude and frequency of oscillations or noise level) is multiplied by the simple addition of this type of binary logic gates in a network. Nevertheless, this simplistic view may be even more sophisticated when putting the binary motifs together in a larger network. As shown in Figure 3 , simply by connecting two different logic gates through a hub may result in a system where the two gates operate in parallel independently of each other (Figure 3A ) or operate in a different way (Figure 3B ). In this case, outputs may depend on the input of both gates at the same time or on the history of the input states driving the nodes (see examples of both behaviors in Figure 3B ). This type of dynamics, in larger networks, makes selectivity of the state in terms of the input protocol even richer than just the repetition of simple binary logic gates in a network. In order to show the generality of this type of networks (and also its robustness in terms of the dynamical oscillators used to build the network) we have constructed several binary logic gates with electronic circuits operating in a chaotic regime. We have shown experimentally that a network built by coupling two of these gates through a hub (using the same simple motif as before) is able to process information as expected (see Figure 4 ). Finally, we have shown theoretically that by using a network of oscillators we can implement a Set-Reset Flip Flop circuit (Hahnloser et al., 2000 ), which is an example of another stimulus selector, in this case, that is able to store information. To conclude, it is worth mentioning that, in this work, we have considered only the simplest interpretation of input and output states (leading to Boolean logic). However, our results may be analyzed in a wider view, for instance, if we explicitly consider the degree of synchronization of the different elements (resulting in fuzzy logic) or if we consider as possible output states all types of synchronization (phase, generalized, lag, complete, …) between the different elements which form the network of oscillators. The fact that we consider only one of the different dynamical characteristics of the system, in our case its degree of synchronization, is a coarse simplification. The dynamical response of the network is not determined only by its degree of synchronization. For instance, the frequencies involved in the dynamics, or the degree of excitation/inhibition segregation, may also inform about the input stimulus characteristics, enlarging in this way the computational capabilities of the system. 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."
} | 3,360 |
36853710 | PMC9871347 | pmc | 3,148 | {
"abstract": "Summary Self-healing materials exhibit irreplaceable advantages in artificial electronics given their ability to repair from accidental damage, but the self-healing ability is temperature sensitive, limiting their applications in cryogenic environments. Here, we describe steps to fabricate a versatile ionic hydrogel with fast self-healing ability, ultra-stretchability, and stable conductivity, under the temperature ranging from −80°C to 30°C. We also detail steps for characterizing the polymer structure and interactions of the ionic hydrogel, as well as the mechanical, electrical, and self-healing properties. For complete details on the use and execution of this protocol, please refer to Wang et al. (2022). 1"
} | 179 |
35491828 | PMC9239096 | pmc | 3,149 | {
"abstract": "ABSTRACT The rhizobium-legume symbiosis is essential for sustainable agriculture by reducing nitrogen fertilizer input, but its efficiency varies under fluctuating soil conditions and resources. The nitrogen-related phosphotransferase system (PTS Ntr ) consisting of PtsP, PtsO, and PtsN is required for optimal nodulation and nitrogen fixation efficiency of the broad-host-range Sinorhizobium fredii CCBAU45436 associated with diverse legumes, though the underlying mechanisms remain elusive. This work characterizes the PtsN-KdpDE-KdpFABC pathway that contributes to low potassium adaptation and competitive nodulation of CCBAU45436. Among three PtsN, PtsN 1 is the major functional homolog. The unphosphorylated PtsN 1 binds the sensory kinase KdpD through a non-canonical interaction with the GAF domain of KdpD, while the region covering HisKA-HATPase domains mediates the interaction of KdpD with the response regulator KdpE. KdpE directly activates the kdpFABC operon encoding the conserved high-affinity potassium uptake system. Disruption of this signaling pathway leads to reduced nodule number, nodule occupancy, and low potassium adaptation ability, but without notable effects on rhizoplane colonization. The induction of key nodulation genes NIN and ENOD40 in host roots during early symbiotic interactions is impaired when inoculating the kdpBC mutant that shows delayed nodulation. The nodulation defect of the kdpBC mutant can be rescued by supplying replete potassium. Potassium is actively consumed by both prokaryotes and eukaryotes, and components of the PTS Ntr -KdpDE-KdpFABC pathway are widely conserved in bacteria, highlighting the global importance of this pathway in bacteria-host interactions.",
"conclusion": "Conclusion. Despite the expansion of PtsN homologs in S. fredii , PtsN 1 is the major EIIA Ntr functioning in low K + adaptation and optimal nodulation, which are mediated by the two-component system KdpDE and the high-affinity K + uptake system KdpFABC. The sensor kinase KdpD interacts with the unphosphorylated form of EIIA Ntr in a novel mechanism via its GAF domain, and with the response regulator KdpE via the HisKA-HATPase fragment. KdpE directly activates the transcription of the kdpFABC operon. Disruption of this pathway leads to defects in low K + adaptation and competitive nodulation. The kdpBC mutant has a reduced nodulation ability compared with WT while showing no severe impairment in rhizoplane colonization. This can be at least partially explained by the impaired induction of host nodulation genes by the kdpBC mutant and its delayed nodulation. Collectively, these findings suggest that K + uptake regulated by the PTS Ntr -KdpDE-KdpFABC pathway is involved in optimizing early symbiotic interactions, highlighting a largely unexplored regulation of symbiosis by fluctuating nutrients in soils ( 31 ). K + is needed by all cellular organisms ( 43 ) and its role as an environmental cue in bacteria-host interactions is just emerging ( 26 ).",
"introduction": "INTRODUCTION Protein phosphorylation is one of the major mechanisms underlying organisms’ adaptation to fluctuating conditions and resources in various ecological niches. Bacterial kinases can be classified into four major families ( 1 ). The eukaryote-like protein kinases (also referred to Hanks-type kinases) phosphorylate a large spectrum of substrates at their serine and threonine residues ( 2 ). The BY kinases catalyze phosphorylation of targets at tyrosine residues ( 3 ). The two-component systems include a sensory histidine kinase that autophosphorylates at a conserved histidine by using the γ-phosphoryl group of ATP, and a response regulator that receives the phosphoryl from the histidine-phosphorylated kinase at a conserved aspartate residue ( 4 ). The fourth family is the phosphotransferase system harboring a group of enzymes that sequentially transfer the phosphoryl group derived from phosphoenolpyruvate to a histidine residue of downstream members of the system ( 5 ). The canonical phosphotransferase system (PTS) directly involved in carbohydrate uptake ( 6 , 7 ) and the nitrogen-related phosphotransferase system (PTS Ntr ) have been found in various bacteria. Both canonical PTS and PTS Ntr have enzyme I (EI or EI Ntr ), histidine protein (HPr or NPr), and enzyme II (EIIA or EIIA Ntr ), while the PTS Ntr lacks substrate specific EIIB and EIIC required for carbohydrate uptake ( 5 ). The PTS Ntr is characterized by its regulatory roles in diverse processes such as the metabolism of nitrogen and carbon, phosphate starvation, and K + homeostasis ( 5 , 8 , 9 ). K + selective cation channels are essential for both prokaryotes and eukaryotes to maintain the asymmetric K + /Na + distribution, with K + as the major cation in the cytoplasm while Na + being dominant in the media ( 10 ). Bacteria usually harbor a variable number of K + uptake systems including Trk, Ktr, Kup, and Kdp reflecting adaptations to different niches ( 11 , 12 ). The H + -dependent Trk and Na + -dependent Ktr show low cation selectivity with moderate binding affinity, while the K + uptake permease Kup and the P-type ATPase mediating system Kdp are considered specific K + transporters with Kdp being the high-affinity K + transporter ( 11 , 12 ). Moreover, kdp genes are inducible under low K + conditions where the sensor kinase KdpD phosphorylates the response regulator KdpE that promotes transcription of the kdpFABC operon ( 13 , 14 ). Although the precise signal recognized by the membrane-bound KdpD is still under discussion ( 14 ), it has been demonstrated that unphosphorylated EIIA Ntr can interact with KdpD in Escherichia coli , Rhizobium leguminosarum , and Pseudomonas putida and activates the transcription of kdpFABC genes ( 15 – 17 ). With evidences from mutants of K + uptake systems of Salmonella ( 18 ), Staphylococcus aureus ( 19 ), Helicobacter pylori ( 20 ), Mycobacterium tuberculosis ( 21 ), Pectobacterium wasabiae ( 22 ), Streptococcus mutans ( 23 ), and Sinorhizobium meliloti ( 24 ), it is only just emerging that K + is an environmental cue and a key player in host-bacteria interactions ( 25 , 26 ). These studies imply that a PTS Ntr -KdpDE-KdpFABC pathway might be involved in host-bacteria interactions, though not fully established in any individual system yet. To test this hypothesis, we focused on the mutualistic interactions between rhizobia and legumes which innovate root nodules where rhizobia reduce atmospheric nitrogen into ammonia to support plant growth ( 27 , 28 ). Our previous work reveals that PTS Ntr is essential for effective symbiosis of Sinorhizobium fredii CCBAU45436 with soybean and pigeon pea plants ( 29 ). The symbiotic defects of mutants lacking EI Ntr ( ptsP ) or Npr ( ptsO ) can be partially rescued by further deletion of an EIIA Ntr ( ptsN 1 ) while the single ptsN 1 mutant is indistinguishable from the wild-type strain except impaired nodulation and nodule occupancy abilities ( 29 ). In this work, we aimed to characterize the EIIA Ntr -KdpDE-KdpFABC pathway in CCBAU45436, and investigate the potential role of Kdp in symbiotic interactions. Three PtsN homologs were characterized for their effect on symbiosis and low potassium adaptation, and ability to interact with KdpD. Distinct domains of KdpD involved in interactions with the major EIIA Ntr (PtsN 1 ) and KdpE were identified, and direct activation of the kdpFABC operon by KdpE was demonstrated. The effects of phosphorylated or unphosphorylated PtsN 1 and the downstream KdpDE-KdpFABC pathway in low potassium adaptation and symbiotic interactions were further characterized. Together with the transcriptional analysis of key nodulation genes of soybean plants during early interaction stages and nodulation kinetics assay, the important role of K + uptake in optimal nodulation mediated by the PTS Ntr -KdpDE-KdpFABC pathway is proposed and discussed.",
"discussion": "RESULTS AND DISCUSSION Expansion of PtsN homologs in Rhizobiaceae . The regulatory roles of PTS Ntr have been intensively studied in various pathogens, with PtsN being the major output regulator ( 5 ). The broad-host-range rhizobium S. fredii CCBAU45436 (SF4 hereafter) ( 30 – 32 ) has three PtsN homologs ( Fig. 1A ). Phylogenetic analysis indicated their distinct phyletic distribution ( Fig. 1B ), with PtsN 1 conserved in the Rhizobiales order (including genera Rhizobium , Sinorhizobium , Agrobacterium , Mesorhizobium , and Bradyrhizobium ) and clustered with PtsN from other bacteria in a highly supported orthologous group, with PtsN 2 present in some species of the Rhizobiaceae family, and with PtsN 3 identified in S. fredii strains SF4 and HH103. Although PtsN 1 , PtsN 2 , and PtsN 3 of SF4 belong to three separate clusters ( Fig. 1B ), sequence alignment analysis ( Fig. 1C ) showed that they have the conserved histidine residue (H66) which is the only phosphorylated site of EIIA Ntr homologs as demonstrated previously ( 33 ). To investigate the potential role of the three ptsN homologs of SF4 in symbiosis, all single, double and triple in-frame deletion mutants were constructed and tested for their symbiotic performance on soybean plants ( Table S1 ). All test mutants were able to form functional nodules which supported the growth of soybean plants at a similar level as the wild-type SF4 regarding shoot dry weight and leaf chlorophyll content ( Table S1 ; ANOVA followed by Duncan's test, alpha = 0.05). The ptsN 1 , ptsN 12 , ptsN 13 , ptsN 123 , and ptsN 2 mutants formed similar numbers of nodules which were significantly less than those induced by SF4, ptsN 3 , and ptsN 23 mutants (ANOVA followed by Duncan's test, alpha = 0.05). This suggests that PtsN homologs are important for optimal nodulation of S. fredii on soybean plants, with the more conserved PtsN 1 being the major functional homolog and the positive effect of PtsN 2 depending on the presence of PtsN 3 . This is in line with the finding in R. leguminosarum which harbors two PtsN homologs with PtsN 1 as the major EIIA Ntr ( 9 ). FIG 1 PtsN homologs in Sinorhizobium fredii CCBAU45436. (A) Components of PTS Ntr in S. fredii CCBAU45436 (SF4) including ptsP encoding EI Ntr , ptsO encoding Npr, and three copies of ptsN encoding EIIA Ntr . (B) The unrooted maximum likelihood phylogenetic tree of EIIA Ntr homologs from representative bacterial species. Bootstrap values above 60 are shown. n = 1 indicates that only one EIIA Ntr can be identified in the corresponding strain. R , Rhizobium ; S , Sinorhizobium ; A , Agrobacterium ; M , Mesorhizobium ; B , Bradyrhizobium ; E , Escherichia ; V , Vibrio ; P , Pseudomonas ; C , Cupriavidus . (C) Alignment of PtsN homologs showing the conserved histidine (*, H66 in SF4 EIIA Ntr ) involved in phosphorylation (~P). PtsN homologs of Ralstonia eutropha H16 and E. coli MG1655 are included for comparison. 10.1128/mbio.03721-21.1 TABLE S1 Symbiotic performance of ptsN mutants on soybean plants. Download Table S1, PDF file, 0.1 MB . Copyright © 2022 Feng et al. 2022 Feng et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . Notably, a R. leguminosarum mutant lacking functional EIIA Ntr formed a similar number of nodules as the wild-type strain but fixed less nitrogen on pea plants while S. fredii lacking EIIA Ntr formed fewer effective nodules on soybean plants ( Table S1 ) ( 9 , 29 ). This contrasting phenotype may be at least partially due to different stimuli encountered by rhizobia during the establishment and maintenance of the determinate (with transient meristems, such as soybean and cowpea) and indeterminate nodules (with persistent meristems, such as pea and alfalfa) ( 34 , 35 ). Rhizobia terminally differentiate (enlarged cell size and reduced reproductive ability) in pea and alfalfa nodules but not in soybean and cowpea nodule cells ( 27 , 36 – 38 ). Nitrogen-fixing rhizobial cells accumulate more carbon storage polymer poly-β-hydroxybutyrate (PHB) in soybean and cowpea nodules than in pea and alfalfa nodules ( 27 , 36 – 38 ). We have revealed that PHB biosynthesis and nitrogen fixation is blocked in the ptsP and ptsO mutants but restored in the ptsPN 1 and ptsON 1 double mutants of S. fredii in soybean nodules ( 29 ). Although the regulation of nitrogen and carbon metabolism by PTS Ntr is supported by evidences from both S. fredii- soybean and R. leguminosarum - pea symbioses ( 9 , 29 ), the underlying signaling pathway mediated by PTS Ntr in PHB biosynthesis and other adaptive processes in these contrasting rhizobium-legume pairs remains elusive. PtsN 1 and PtsN 2 interact with KdpD and contribute to low potassium adaptation and optimal nodulation. As the interaction between EIIA Ntr and KdpD has been recurrently found in E. coli , R. leguminosarum , and Pseudomonas putida ( 15 – 17 ), the yeast two-hybrid experiment was used herein to identify which PtsN homolog(s) may keep this conserved function. It turned out that PtsN 1 and PtsN 2 rather than PtsN 3 interact with KdpD under test conditions ( Fig. 2 ). After an exploring test of different levels of K + ( Fig. S1 ), 1 μM and 10 mM was considered as low and replete K + conditions, respectively. Under the low K + condition (1 μM K + ), the ptsN 12 mutant exhibited a more severe growth defect than the ptsN 1 or ptsN 2 mutants ( Fig. 3A ), implying cumulative effects associated with PtsN 1 and PtsN 2 . Similarly, the ptsN 123 mutant grew worse than the ptsN 13 mutant that in turn grew worse than the ptsN 3 mutant. Noteworthy, growth delay was observed for the ptsN 1 mutant but not for the ptsN 2 , ptsN 3 , and ptsN 23 mutants, suggesting PtsN 1 as the major EIIA Ntr . Although the ptsN 3 mutant was indistinguishable from SF4, the ptsN 123 and ptsN 13 mutants grew slightly better than the ptsN 12 and ptsN 1 mutants, respectively, indicating a potential negative regulatory role of PtsN 3 in low K + adaptation. On the other hand, the growth rate of all test strains was higher under K + replete condition (10 mM K + ) than low K + condition ( Fig. 3A ). PtsN 1 was required for the maximum growth rate of SF4 under this K + replete condition likely due to its regulatory roles in carbon metabolism ( 16 , 29 ), with cumulative contribution by PtsN 2 and antagonistic effect from PtsN 3 . The strong synthetic negative phenotype of the ptsN 12 mutant under low K + condition was however not observed under this K + replete condition. Moreover, the ptsP and ptsO mutants grew faster than the ptsN 12 and ptsN 123 mutants under low K + condition while the reverse was observed under K + replete condition ( Fig. 3A ), suggesting a regulatory duality mediated by switching EIIA Ntr phosphorylation status ( Fig. 1A ) ( 5 ). These results, particularly the contrasting growth phenotypes of the ptsN 12 mutant under K + replete and deplete conditions, implied that EIIA Ntr is critical for S. fredii adaptation to fluctuating levels of K + that is also consumed by other organisms in the same habitat including the interacting eukaryote hosts ( 25 , 26 , 39 ). FIG 2 PtsN 1 and PtsN 2 directly interact with KdpD. Three dilutions are shown from the yeast two-hybrid experiment with pGADT7/pGBKT7 and pGADT7-T/pGBKT7-53 as negative and positive controls, respectively. Yeast cells were co-transformed with AD and BD vectors. The growth on the medium lacking Trp/Leu/His, and blue color indicate protein interaction. FIG 3 Cumulative role of ptsN 1 and ptsN 2 in low K + adaptation and nodulation. (A) Growth curves in rich medium and minimum medium supplied with 1 μM and 10 mM K + . Results are based on average ± SEM of three biological replicates. (B) Symbiotic performance on soybean plants. Different letters indicate significant difference between treatments (Average ± SEM; ANOVA followed by Duncan’s test, alpha = 0.05). More than eight plants were scored. 10.1128/mbio.03721-21.7 FIG S1 Influence of K + levels on the growth of the kdpBC , kdpDE and ptsN 123 mutants in the minimum medium. Download FIG S1, PDF file, 0.2 MB . Copyright © 2022 Feng et al. 2022 Feng et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . The ptsP mutant has pleiotropic defects including symbiotic inefficiency which can be partially rescued by further deletion of ptsN 1 (29). To investigate whether the second KdpD-interacting EIIA Ntr PtsN 2 has cumulative contribution to symbiotic efficiency, the triple mutant ptsPN 12 was constructed. This mutant was as efficient as the ptsPN 1 mutant and performed better than the ptsP mutant regarding chlorophyll content of inoculated soybean plants (ANOVA followed by Duncan's test, alpha = 0.05), though shoot dry weight was partially recovered in the ptsPN 1 and ptsPN 12 treatments at an insignificant level under test conditions ( Fig. 3B ; Table S2 ). Inefficient nodules induced by the ptsP mutant were significantly smaller than those efficient nodules formed by SF4, ptsN 1 , ptsPN 1 and ptsPN 12 mutants ( Fig. 3B ; Table S2 ). The ptsN 1 and ptsPN 12 mutants formed significantly less nodules than the ptsP and ptsPN 1 mutants, respectively. It seems that the contrasting number and weight of nodules between the ptsP and ptsN 1 treatments are in line with the canonical model of autoregulation of nodulation ( 28 ). However, nodule weight was similar between the ptsPN 1 and ptsPN 12 treatments ( Fig. 3B ; Table S2 ), indicating that the reduced nodule number in the ptsPN 12 treatment compared with the ptsPN 1 treatment may also be regulated by processes other than autoregulation of nodulation. Therefore, a cumulative role of PtsN 2 in optimal nodulation was revealed by comparing the ptsP , ptsPN 1 , and ptsPN 12 mutants. Taken together with the nodulation phenotypes and growth curves of various ptsN mutants ( Table S1 ; Fig. 3 ), despite an expansion of PtsN copies in the Rhizobiaceae family ( Fig. 1B ), these findings suggest PtsN 1 as the major EIIA Ntr in symbiotic interaction and low K + adaptation with a cumulative contribution by PtsN 2 . 10.1128/mbio.03721-21.2 TABLE S2 Symbiotic performance of ptsPN 1 and ptsPN 12 mutants on soybean plants. Download Table S2, PDF file, 0.1 MB . Copyright © 2022 Feng et al. 2022 Feng et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . Optimal nodulation and low potassium adaptation mediated by the EIIA Ntr -Kdp pathway. All known regulatory roles of EIIA Ntr are mediated by its phosphorylation status of H66 ( Fig. 1C ) ( 8 , 33 , 40 – 42 ). Here we constructed the ptsN 1 (H66A) and ptsN 1 (H66E) strains harboring non-phosphorylated PtsN 1 and phosphorylated PtsN 1 , respectively. Similar to the ptsN 1 mutant, the ptsN 1 (H66E) strain formed less nodules than the wild-type SF4, the ptsP mutant, and the ptsN 1 (H66A) strain while showing no significant difference in symbiotic performance regarding leaf chlorophyl content and shoot dry weight compared with these strains except the inefficient ptsP mutant ( Fig. 4A ; Table S3 ). Moreover, the ptsN1(H66A) strain and the ptsP mutant induced smaller nodules than the ptsN 1 (H66E) strain, the ptsN 1 mutant, and SF4 ( Fig. 4A ; Table S3 ). Therefore, the involvement of PtsN 1 in optimal nodulation is mediated by the phosphorylation status of its H66 residue. FIG 4 PTS Ntr and KdpBC are required for optimal nodulation. (A) Nodulation characteristics of strains carrying ptsN 1 (H66A) or ptsN 1 (H66E). The number of scored plants from multiple independent experiments is shown in brackets. (B) PtsN 1 (H66A) directly interacts with KdpD. Two dilutions are shown from the yeast two-hybrid experiment with the negative (pGADT7 and pGBKT7) and positive (pGADT7-T and pGBKT7-53) controls as shown in Fig. 2 (C) Cotranscription of the kdpFABC operon of SF4 grown in minimum medium (M9). The fragments covering corresponding intergenic regions targeted by three pairs of primers are indicated and amplified in RT-PCR. Reverse transcriptase was added to the reaction in RT+, but omitted from reactions in RT-. Genomic DNA was amplified as a positive control. M, 100 bp marker. (D) Deletion of kdpBC rather than kdpDE in the wild-type SF4 (WT), the ptsP or ptsO mutants leads to less nodules formed on soybean plants. The number of scored plants is indicated in brackets. (E) Nodulation defects of the kdpBC mutant and the ptsN 1 (H66E) strain can be rescued by supplying replete K + (10 mM) in the rhizosphere (more than 10 plants were scored). (A) and (D to E), different letters indicate significant difference between treatments (Average ± SEM; ANOVA followed by Duncan’s test, alpha = 0.05). 10.1128/mbio.03721-21.3 TABLE S3 Symbiotic performance of the ptsN 1 (H66A) and ptsN 1 (H66E) mutants on soybean plants. Download Table S3, PDF file, 0.1 MB . Copyright © 2022 Feng et al. 2022 Feng et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . Because the major EIIA Ntr PtsN 1 directly interacts with KdpD ( Fig. 2 ), we wonder if the KdpDE-KdpFABC pathway is involved in optimal nodulation mediated by phosphorylation status of PtsN 1 . Yeast two-hybrid experiment showed that PtsN 1 (H66E) failed to interact with KdpD while PtsN 1 (H66A) can interact with KdpD though at a relatively lower efficiency compared with the wild-type PtsN 1 ( Fig. 4B ). The interaction between unphosphorylated EIIA Ntr and KdpD is consistent with the findings in other bacteria including E. coli and R. leguminosarum ( 15 , 16 ). The kdpDE and kdpFABC operons have a widely conserved synteny in various bacteria ( 43 ). In SF4 genome, the kdpD gene has four overlapping nucleotides with the downstream coding region of the response regulator KdpE ( Fig. 4C ), and reverse transcription-PCR analysis revealed that kdpF , kdpA , kdpB , and kdpC , encoding the high-affinity K + uptake system, constitute an operon ( Fig. 4C ). To test the potential role of KdpDE and KdpFABC in nodulation, kdpDE and kdpBC were deleted in backgrounds of WT, ptsP , or ptsO mutants. All mutants lacking kdpBC formed less nodules compared with their parent strains whereas the decrease of nodule number for mutants lacking kdpDE was not statistically significant ( Fig. 4D ; Table S4 ), suggesting the requirement of high-affinity K + uptake in optimal nodulation and potential complementary effects by other K + uptake systems in the kdpDE mutant (see below for transcriptional profiles of different K + uptake systems). The kdp mutants had similar symbiotic performance as their parent strains regarding leaf chlorophyll content and shoot dry weight ( Table S4 ). When replete K + (10 mM) was supplied in the rhizosphere, nodulation defects of the kdpBC and ptsN 1 (H66E) strains can be largely rescued ( Fig. 4E ). These results suggest that EIIA Ntr and its downstream high-affinity K + uptake system are involved in optimal nodulation on soybean plants. The involvement of K + uptake system in modulating nodulation is also observed for S. meliloti associated with alfalfa ( 24 ) where the double mutant of low affinity K + uptake systems Trk and Kup ( 14 ) exhibited delayed nodulation that was further enhanced in the trk-kup-kdp triple mutant. In line with the findings in this work on S. fredii -soybean system, these S. meliloti mutants of K + uptake systems formed nitrogen fixing nodules on alfalfa ( 24 ), supporting the role of K + uptake during early symbiotic interactions. 10.1128/mbio.03721-21.4 TABLE S4 Symbiotic performance of the kdp mutants on soybean plants. Download Table S4, PDF file, 0.1 MB . Copyright © 2022 Feng et al. 2022 Feng et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . In the S. meliloti -alfalfa system, it has been shown that the low affinity Trk and Kup systems are required for competitive nodulation ( 24 ). In this work, nodule occupancy assay on soybean plants ( Fig. 5A ) revealed that S. fredii mutants lacking kdpBC or kdpDE were outcompeted by their corresponding parent strains (WT, the ptsP , or ptsO mutants) while the ptsN 1 (H66A) strain rather than ptsN 1 (H66E) was as competitive as the wild-type SF4. Further analysis of survival rate (CFU) on rhizoplane showed that the observed contrasting competitive nodulation abilities among test strains ( Fig. 4A ; Fig. 4D ; Fig. 5A ) cannot be fully explained by their rhizoplane colonization rates ( Fig. 5A ). For example, rhizoplane CFU of the kdpDE , ptsO-kdpDE , and ptsO-kdpBC mutants were comparable with those of the corresponding parent strains. These findings imply a more active role of EIIA Ntr -Kdp pathway during symbiotic interactions than in root colonization. FIG 5 PTS Ntr and Kdp system are required for nodule occupancy and low potassium adaptation. (A) Rhizoplane colonization and nodule occupancy by pairs of mixed inoculants (1:1 ratio within each pair). Significant difference is indicated based on one sample t test (theoretical mean = 0.5; *, P < 0.05; **, P < 0.01; ***, P < 0.001). Error bars represent SD of three biological replicates. (B) The growth curves of various derivatives of S. fredii CCBAU45436 (SF4) in the TY rich medium, M9 minimum medium with 1 μM or 10 mM K + . To verify if the test mutants with nodulation defects are also impaired in low K + adaptation, their growth curves were compared ( Fig. 5B ). Consistent with the predicted role of KdpDE and KdpFABC in low K + adaptation (< 100 μM) ( 14 , 44 ), the kdpDE and kdpBC mutants were unable to grow in the minimum medium containing 1 μM K + while indistinguishable from the wild-type SF4 when replete K + (10 mM) was supplied ( Fig. 5B ). Similarly, the ptsP or ptsO derivatives lacking either kdpBC or kdpDE showed significant growth defects under the low K + condition ( Fig. 5B ), which can be rescued to the level of the ptsP and ptsO mutants ( Fig. 3A ) by supplying replete K + ( Fig. 5B ). Under the low K + condition, the ptsN 1 (H66A) strain grew at a similar rate as SF4 before reaching stationary phase while the ptsN 1 (H66E) strain showed a significant growth delay ( Fig. 5B ) that can be rescued to the level of the ptsN 1 mutant ( Fig. 3A ) by adding 10 mM K + ( Fig. 5B ). It is also noteworthy that the unphosphorylated PtsN 1 allowed better growth than the ptsP and ptsO mutants under the low K + condition ( Fig. 4B and Fig. 3A ). This can be partially explained by EIIA Ntr -independent output signals derived from EI Ntr and Npr as indicated in the carbon source utilization characteristics of related mutants of SF4 ( 29 ) and potential cross talk between the canonical PTS and PTS Ntr in modulating the KdpDE-KdpFABC pathway as shown in E. coli ( 15 , 45 ). Despite the complexity in the upstream signaling components, the unphosphorylated form of PtsN 1 is notably essential for low K + adaptation through interacting with KdpD ( Fig. 5B and Fig. 4B ). KdpD interacts with KdpE and PtsN 1 in a non-canonical way. The interaction between KdpD and PtsN 1 has been demonstrated as mentioned above ( Fig. 2 and Fig. 4B ), though notable sequence variation was observed between PtsN homologs of rhizobia and E. coli ( Fig. 1B and C ). Further protein interaction analysis revealed the GAF domain as the minimum KdpD fragment interacting with PtsN 1 while the minimum region covering HisKA and HATPase domains interacting with KdpE ( Fig. 6A and B ). In E. coli , the region covering HisKA and HATPase domains interacts with KdpE, but PtsN interacts with HisKA ( 44 , 46 ), i.e., apparently competing for binding ( 43 ). This paradox is largely resolved in E. coli by forming the PtsN/KdpD 2 /KdpE ternary complex ( 46 ). Sequence analysis revealed that GAF of KdpD from SF4 and other rhizobia has additional N-terminal (from N496 to G529) and C-terminal (V650 to L672) fragments and more scattered polar residues (Q541, D570, T571, R588, R592, K601, T629, D641, and Q642) compared with GAF from E. coli ( Fig. S2 ). Various GAF variants carrying substitutions at individual polar residues were constructed and tested for their interaction activity with PtsN 1 ( Fig. 6C ). It turned out that D517 located in the N-terminal fragment and D570, not present in GAF of E. coli KdpD, were the key residues involved in the interaction between GAF of KdpD and PtsN 1 in SF4. This novel interaction mechanism between KdpD and EIIA Ntr was further confirmed in the GST pulldown assay where intact GAF of KdpD rather than GAF(D517F) can effectively interact with PtsN 1 or PtsN 2 ( Fig. 6D and E ). Because the D517 carrying N-terminal fragment is also present in KdpD of many other rhizobia ( Fig. S2 ), this signal transduction mechanism represents a novel model alternative to the well-known PtsN/KdpD 2 /KdpE ternary binding model based on findings in E. coli ( 43 , 46 ). FIG 6 KdpD interacts with KdpE and PtsN 1 by HisKA-HATPase and GAF, respectively. (A) Schematic view of KdpD domains. Four transmembrane domains are indicated in light blue. (B) Identification of KdpD fragments (AD) interacting with KdpE (BD) and PtsN 1 (BD), respectively by using the yeast two-hybrid experiment. (C) Exploring screen of polar residues in the GAF domain involved in interacting with PtsN 1 . Amino acid substitutions are indicated and residues located in either N-terminal or C-terminal fragments which are present in various rhizobia but absent in E. coli are underlined. In the yeast two-hybrid experiment (B to C), pGADT7/pGBKT7 and pGADT7-T/pGBKT7-53 were used as negative and positive controls, respectively, as shown in Fig. 2 . The relative position of domains and residues within KdpD are shown when necessary. (D) Interaction between PtsN 1 or PtsN 2 with the GAF domain of KdpD by using GST pulldown assay. (E) GAF(D517F) unable to interact with PtsN 1 or PtsN 2 in the GST pulldown assay. 10.1128/mbio.03721-21.8 FIG S2 Alignment of GAF domain of KdpD from representative rhizobia and E. coli . Polar residues subject to point mutation in Fig. 6D are indicated. The green box shows regions absent in GAF of KdpD from E. coli . Identity levels are indicated in navy blue (100%), pink (75%), and azure (50%~75%). Download FIG S2, PDF file, 0.5 MB . Copyright © 2022 Feng et al. 2022 Feng et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . KdpE directly binds the promoter of kdpFABC but not those of trkA and kup . In addition to the high-affinity K + uptake system KdpFABC, the genome of SF4 harbors homologs of low-affinity TrkA and Kup systems ( Fig. 7A ) ( 24 , 47 , 48 ). qRT-PCR analysis of SF4 revealed that kup was downregulated while kdp was strongly upregulated under the low K + condition compared to the replete K + condition ( Fig. 7B ). By contrast, the trkA gene was transcribed at a relatively lower level compared with the other two systems when replete K + was supplied in the minimum medium, and it was slightly upregulated in the low K + medium ( Fig. 7B ). Further electrophoretic mobility shift assay (EMSA) showed that KdpE can directly binds the promoter region of kdpFABC operon but not those of trkA and kup ( Fig. 7C ). Therefore, the direct activation of kdpFABC operon by KdpE ( 43 ) also function in S. fredii . FIG 7 KdpE binds promoter of kdpFABC but not those of trkA and kup . (A) Promoters of kdpFABC , trkA and kup . The positions of probes used in electrophoretic mobility shift assay (EMSA) are indicated. corA encodes a putative transport protein for magnesium and cobalt. (B) qRT-PCR analysis of kdpB , trkA , and kup genes in SF4 under 1 μM and 10 mM K + conditions in the M9 minimum medium. 16S rRNA gene is used as the reference gene. (C) EMSA of KdpE with kdpFABC / trkA / kup promoter regions. The purified KdpE-MBP and MBP (5/20/50 μM) were incubated with Cy5-labeled DNA probes (12.3 nM). KdpE-MBP did not bind the Probe1_kdpF and the result is not shown herein. The role of EIIA Ntr -KdpDE-KdpFABC pathway during early symbiotic interactions. The above-mentioned direct evidences support a EIIA Ntr -KdpDE-KdpFABC pathway in S. fredii , mediated by a non-canonical EIIA Ntr -KdpD-KdpE binding model. It is noteworthy that SF4 derivatives carrying the phosphorylated form of PtsN 1 (H66E) or lacking kdpBC formed less nodules on soybean plants while the number of nodules induced by the kdpDE mutant was not significantly different from that of the wild-type SF4 ( Fig. 4A and D ). Transcriptional profiles of kdp , trkA , and kup genes were determined under both low and replete K + conditions ( Fig. S3 ). The deletion of kdpDE led to low transcription of the high-affinity KdpFABC system compared with SF4 as expected ( Fig. S3 ), whereas the kup gene was strongly upregulated under the low K + condition ( Fig. S3A ; around 50-fold increase compared with SF4) though downregulated when 10 mM K + was supplied ( Fig. S3B ). For those strains forming less nodules such as the ptsN 1 (H66E) and kdpBC strains, the kup and/or trkA were downregulated under the low K + condition ( Fig. S3 ). By contrast, the ptsN 1 (H66A) strain forming more nodules had a significant higher transcriptional level of kdp under both low and replete K + conditions, though trkA and kup were downregulated under the low K + condition ( Fig. S3 ). The cumulative contribution of different K + uptake systems to nodulation was also observed in the S. meliloti -alfalfa symbiosis ( 24 ). In this work, we further revealed that the optimal nodulation in the S. fredii -soybean system is modulated by the EIIA Ntr -KdpDE-KdpFABC pathway. Further exploring host responses to the kdpBC mutant during early symbiotic interaction stages (2-h, 4-h, 6-h, 8-h, 24-h, 2-days, and 4-days postinoculation) revealed an impaired transcription of the indispensable nodule inception regulator gene NIN and nodule primordium initiation marker gene ENOD40 ( 28 , 49 – 51 ) in soybean roots ( Fig. 8A ). This is consistent with the significantly delayed nodulation of the kdpBC mutant compared with the wild-type SF4 ( Fig. 8B ). Taken together with the findings on rhizoplane colonization and nodule occupancy, it seems that rhizobial K + uptake modulated by the PTS Ntr -KdpDE-KdpFABC is crucial during early symbiotic interactions ( Fig. 8C ). FIG 8 Regulation of K + uptake by the PTS Ntr -KdpDE-KdpFABC pathway in nodulation. (A) Down regulation of NIN and ENOD40 in roots inoculated with the kdpBC mutant compared with those in roots treated with the wild-type SF4. Hours (h) or days (d) postinoculation are shown corresponding to the early symbiotic interaction stages. The red bars represent a significant upregulation in the WT treatment compared with the uninoculated roots. Significant differences in gene transcriptional levels between the kdpBC treatment and the WT treatment are indicated (Student’s t test; *, P < 0.05; **, P < 0.01; ***, P < 0.001). Error bars represent SE of the mean of three biological replicates. (B) Delayed nodulation of the kdpBC mutant compared with SF4 (dpi, days postinoculation). Significant differences in nodule number between two treatments are indicated (Student’s t test; **, P < 0.01; ****, P < 0.0001). Error bars represent SE (based on data from two independent experiments; 6 to 11 plants were scored at each time point in each independent experiment). White triangles indicate position of nodules. Scale bars, 1 cm. (C) During nodulation, unphosphorylated form of EIIA Ntr interacts with the GAF domain of KdpD, which activates KdpE through the direct interaction between KdpE and the HisKA-HATPase region of KdpD. The active KdpE in turn binds the promoter of the kdpFABC operon to upregulate the transcription of this high-affinity K + uptake system. 10.1128/mbio.03721-21.9 FIG S3 Transcription profiles of potassium uptake systems in related mutants of the EIIA Ntr -KdpDE-KdpFABC pathway. (A, B) qRT-PCR analysis of kdpB , trkA , and kup genes in the ptsN1(H66A) , ptsN1(H66E), kdpDE , and kdpBC mutants under 1 μM (A) and 10 mM (B) K + conditions in the M9 minimum medium. The reference gene is 16S rRNA gene. Significant difference is indicated based on one sample t test, theoretical mean = 1; red and blue represent significant up- and down-regulation, respectively, at P < 0.05 or at the marginal P values as indicated (three biological replicates with three technical replicates). Download FIG S3, PDF file, 0.2 MB . Copyright © 2022 Feng et al. 2022 Feng et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . Conclusion. Despite the expansion of PtsN homologs in S. fredii , PtsN 1 is the major EIIA Ntr functioning in low K + adaptation and optimal nodulation, which are mediated by the two-component system KdpDE and the high-affinity K + uptake system KdpFABC. The sensor kinase KdpD interacts with the unphosphorylated form of EIIA Ntr in a novel mechanism via its GAF domain, and with the response regulator KdpE via the HisKA-HATPase fragment. KdpE directly activates the transcription of the kdpFABC operon. Disruption of this pathway leads to defects in low K + adaptation and competitive nodulation. The kdpBC mutant has a reduced nodulation ability compared with WT while showing no severe impairment in rhizoplane colonization. This can be at least partially explained by the impaired induction of host nodulation genes by the kdpBC mutant and its delayed nodulation. Collectively, these findings suggest that K + uptake regulated by the PTS Ntr -KdpDE-KdpFABC pathway is involved in optimizing early symbiotic interactions, highlighting a largely unexplored regulation of symbiosis by fluctuating nutrients in soils ( 31 ). K + is needed by all cellular organisms ( 43 ) and its role as an environmental cue in bacteria-host interactions is just emerging ( 26 )."
} | 9,730 |
26788124 | PMC4717640 | pmc | 3,150 | {
"abstract": "Extracellular electron transfer in microorganisms has been applied for bioelectrochemical synthesis utilizing microbes to catalyze anodic and/or cathodic biochemical reactions. Anodic reactions (electron transfer from microbe to anode) are used for current production and cathodic reactions (electron transfer from cathode to microbe) have recently been applied for current consumption for valuable biochemical production. The extensively studied exoelectrogenic bacteria Shewanella and Geobacter showed that both directions for electron transfer would be possible. It was proposed that gram-positive bacteria, in the absence of cytochrome C, would accept electrons using a cascade of membrane-bound complexes such as membrane-bound Fe-S proteins, oxidoreductase, and periplasmic enzymes. Modification of the cathode with the addition of positive charged species such as chitosan or with an increase of the interfacial area using a porous three-dimensional scaffold electrode led to increased current consumption. The extracellular electron transfer from the cathode to the microbe could catalyze various bioelectrochemical reductions. Electrofermentation used electrons from the cathode as reducing power to produce more reduced compounds such as alcohols than acids, shifting the metabolic pathway. Electrofuel could be generated through artificial photosynthesis using electrical energy instead of solar energy in the process of carbon fixation.",
"conclusion": "Conclusions The cathodic reaction in BES is of increasing concern in the context of producing alternative fuels. Beginning with metal-utilizing bacteria, several electroactive bacteria were found and applied for the conversion of electrical to chemical energy as biofuels or biotransformation (Fig. 6 ). Nonetheless, many technical challenges must still be addressed and the titer of final product is also low. However, research is still in an early stage and efforts such as cell membrane modification and cathode surface modification would enhance the efficiency of BES, as shown in previous studies on MFC. Fig. 6 The application of bioelectrochemical reduction for cathodic electron transfer from a cathode to a microbe"
} | 544 |
37316482 | PMC10267205 | pmc | 3,151 | {
"abstract": "Plasmids are the main vector by which antibiotic resistance is transferred between bacterial cells within surface-associated communities. In this study, we ask whether there is an optimal time to administer antibiotics to minimize plasmid spread in new bacterial genotypes during community expansion across surfaces. We address this question using consortia of Pseudomonas stutzeri strains, where one is an antibiotic resistance-encoding plasmid donor and the other a potential recipient. We allowed the strains to co-expand across a surface and administered antibiotics at different times. We find that plasmid transfer and transconjugant proliferation have unimodal relationships with the timing of antibiotic administration, where they reach maxima at intermediate times. These unimodal relationships result from the interplay between the probabilities of plasmid transfer and loss. Our study provides mechanistic insights into the transfer and proliferation of antibiotic resistance-encoding plasmids within microbial communities and identifies the timing of antibiotic administration as an important determinant.",
"introduction": "Introduction The spread of antibiotic resistance (AR) is a global health problem whose causes and potential mitigation measures remain unclear 1 , 2 . The conjugation-mediated transfer of AR-encoding plasmids is a mechanism by which AR genes can spread between bacterial cells located within close spatial proximity to each other 3 – 6 . The frequencies of plasmid-free and plasmid-carrying cells within a microbial community will change over time depending on the probability of plasmid transfer from a plasmid donor to a potential recipient cell and the probability of plasmid loss upon cell division 7 – 13 . The frequencies will also depend on the relative fitness of plasmid-free and -carrying cells, where AR-encoding plasmids typically incur a fitness cost in the absence of antibiotic pressure 14 – 18 . The time during which the community is not exposed to antibiotic pressure is therefore expected to select against plasmid-carrying cells 16 , 19 . This leads to the expectation that a negative relationship exists between the timing of antibiotic administration and the transfer and proliferation of AR-encoding plasmids in new genotypes, as longer times should result in smaller frequencies of plasmid-carrying cells due to out-competition by fitter plasmid-free cells. In host-associated microbiomes, microbial communities often proliferate on surfaces (e.g. the gut lumen, skin, mucosae, etc.) where AR is typically conferred by conjugative plasmids 20 , 21 . AR in these systems can be maintained by plasmid transfer even in the absence of antibiotic pressure 22 , 23 . In patients receiving antibiotic treatment, these communities undergo frequent spatial reduction–expansion dynamics as a consequence of growth and death during which plasmid-free and plasmid-carrying individuals frequently (re)mix and expand together 24 – 26 . Work in the mouse gut has shown that the spread of AR-encoding plasmids is maximized in situations where pools of persistent AR genotypes in the gut lumen mix with invading plasmid-free enteric pathogens 27 , 28 . It can be expected that the successional stage of these communities when antibiotics are applied can determine whether AR genotypes are likely to proliferate or not. The pervasiveness of mixed proliferation of plasmid-free and plasmid-carrying cells indicates that efforts to eradicate recalcitrant infections could benefit from a better temporal understanding of the spread of AR-encoding plasmids in relation to its main mechanisms of plasmid transfer and loss. Surface-associated microbial communities, such as those associated with hosts, are considered hotspots for the conjugation-mediated transfer of AR-encoding plasmids 4 , 29 , 30 , notably because surface association promotes the close physical cell–cell contacts that are required for the conjugation process 5 , 31 . A universal feature of surface-associated communities is that as cells within a community grow and divide, the community as a whole expands across space in a process referred to as range expansion 32 – 34 . During this process, growth is confined to only a thin layer of cells located at the expansion frontier where nutrients that diffuse from the periphery are readily available 35 . One consequence of this process is that different populations become increasingly spatially segregated over time 32 , 36 – 38 . This reduces the number of interspecific cell–cell contacts (e.g., between plasmid donors and potential recipients), thus also reducing the number of potential plasmid transfer events (Fig. 1a ). Because spatial intermixing decays during range expansion and reduces the number of interspecific cell–cell contacts 32 , 36 – 39 , this again leads to the expectation that a negative relationship exists between the time of antibiotic administration and the transfer and proliferation of AR-encoding plasmids in new genotypes. Fig. 1 Schematic of range expansion and experimental system used in this study. a Different populations (in this case plasmid donors and potential recipients) become increasingly spatially segregated over time as a consequence of stochastic drift at the expansion frontier. This reduces the number of interspecific cell–cell contacts and the potential for plasmid transfer, as plasmid transfer can only occur along the interfaces of plasmid donors and potential recipients. b Our experimental system consists of pairs of strains of the bacterium Pseudomonas stutzeri . One strain is the plasmid donor that expresses red fluorescent protein from its chromosome and carries conjugative plasmid pAR145 that encodes for blue fluorescent protein and chloramphenicol resistance (Cell type 1; magenta cell). The other strain is the potential recipient that expresses green fluorescent protein from its chromosome and is plasmid-free (Cell type 2; green cell). If the potential recipient receives the plasmid, it will express both green and blue fluorescent proteins and appear in the composite color cyan. Plasmid carriers can also be cured of the plasmid during cell division and return to their plasmid-free states (magenta to red and cyan to green). Solid curved arrows indicate successful plasmid transfer while dashed curved arrows indicate plasmid loss. Inter-plasmid gain refers to plasmid transfer between different cell types, while intra-plasmid gain refers to plasmid transfer within the same cell type. In this study, we test the hypothesis that a negative relationship does indeed exist between the time of antibiotic administration and the transfer and proliferation of AR-encoding plasmids, where the negative relationship is driven by selection against plasmid-carrying cells in the absence of antibiotics and the decay in spatial intermixing during the range expansion process (Fig. 1a ). Testing this hypothesis is especially paramount because, in clinical settings, infections generally need to be treated promptly, while our hypothesis would suggest that early treatment times might have negative consequences on the spread of AR-encoding plasmids in new genotypes (Fig. 1a ). To test our hypothesis, we performed range expansion experiments with pairs of strains of the bacterium Pseudomonas stutzeri , where one strain carries the chloramphenicol resistance-encoding conjugative plasmid pAR145 (referred to as the plasmid donor strain) while the other is plasmid-free (referred to as the potential recipient strain) (Fig. 1b ). After the initiation of range expansion, we applied chloramphenicol at different times and quantified the transfer and proliferation of pAR145. We then used an individual-based computational model to quantify how the probabilities of plasmid transfer and loss interact with each other to determine the spread of AR-encoding plasmids during range expansion. This enabled us to test the generality of our experimental results and establish a causal relationship between the timing of antibiotic administration and the spread of AR-encoding plasmids in new genotypes.",
"discussion": "Discussion Combining experiments with individual-based computational modeling, we demonstrated how the timing of antibiotic administration drives the spread of AR-encoding plasmids as surface-associated microbial communities expand across space. We showed that plasmid spread into AR-sensitive cells peaks at intermediate antibiotic administration times. These intermediate times are nested in a narrow window when the spatial intermixing of plasmid donors and potential recipients is maximal. The counterbalancing effects of plasmid transfer and loss predict the impact of the timing of antibiotic administration on the spread of AR. In surface-associated microbial communities experiencing antibiotic pressure, the spread of plasmid-encoded AR is maximized for patterns of spatial organization displaying large numbers of contacts between plasmid donors and recipients (Fig. 3 ). The emergence of such patterns is dependent on the successional stage of the community; at early stages of community development the expansion frontier becomes rapidly dominated by AR types due to a fitness advantage over sensitive individuals (Fig. 3a ). At late stages of community development, the long period of antibiotic-free conditions allows sensitive cells to dominate the expansion frontier due to the fitness cost derived from plasmid maintenance in their AR counterparts 49 (Fig. 3a ). Antibiotic administration at a late stage of community development, therefore, occurs after the purging of plasmid-encoded AR and is expected to be the point when the community is most vulnerable to antibiotic stress. This vulnerability does not imply that late antibiotic administration times can completely eradicate the microbial community of interest 50 , 51 , but it marks a point when the active AR fraction is at a minimum. Intermediate stages of community succession have allowed the preferential proliferation of plasmid-free individuals without completely outcompeting the AR fraction. This maximizes the contacts between plasmid-carrying and plasmid-free cells that promote plasmid transfer and results in the maximal spread of plasmid-encoded AR (Fig. 3a ). The frequent mixing and proliferation of plasmid-carrying and plasmid-free populations of enterobacterial pathogens is considered an important factor of AR persistence and spread in the gut lumen 25 . A temporal perspective on plasmid-encoded AR spread in the gut could thus improve the understanding of the processes leading to recalcitrant AR populations on surfaces. The proliferation of new transconjugants was highly predictable at intermediate stages of community succession, but stochastic at early and late stages. Small population sizes are susceptible to stochastic drift 52 , which during range expansion can drive deleterious genetic variants to fixation 53 . We observed small and unpredictable numbers of transconjugant lineages at the expansion frontier at both early and late antibiotic administration times. At early administration times, a few “lucky” sensitive lineages were able to obtain the AR-encoding plasmid and benefit from antibiotic administration to colonize the expansion frontier. Likewise, at later stages of community succession, a few AR lineages had drifted to the expansion frontier and proliferated upon antibiotic administration (Supplementary Fig. 4 ). This is an example of how the persistence of a deleterious mutation drifting at the frontier of a range expansion can proliferate when environmental conditions change 54 . The lineage diversity of an expanding population sets the basis for its subsequent adaptation to novel conditions 55 , a factor that can determine the probability of AR spread into different environments. Our results suggest that the timing of antibiotic administrations can be important for controlling the heterogeneity (i.e. lineage diversity) of AR, which should be a key determinant for predicting the potential threat of a community carrying AR genes 56 – 59 . The number of unique transconjugant cell lineages followed the same unimodal trend as population sizes, where lineage diversity peaked at intermediate successional stages. However, the size and genetic diversity of the transconjugant population decoupled over time after antibiotic administration (Supplementary Fig. 3 ), where some lineages drifted to extinction while others kept growing. These observations are conceptually similar to those by Stevenson et al. 60 , who showed that mercury resistance encoded by conjugative plasmids spreads predominantly horizontally in the absence of mercury stress (here time before antibiotic administration), while resistance spreads predominantly vertically via clonal expansion in the presence of mercury stress (plasmid spread after antibiotic administration). Consistent with dynamics in range expansions under the strong effects of genetic drift 32 , our findings indicate that the diversity of newly formed AR populations is determined by the time lapsed before antibiotic administration, but that this diversity of the AR lineages surviving the treatment decreases rapidly over time. The counterbalancing effects of plasmid transfer and loss determine the time when antibiotic administration most effectively promotes the proliferation of plasmid-encoded AR. The transfer and loss rates of plasmids can offset the influence of plasmid fitness costs in the maintenance of AR 46 , 48 , 60 . For example, Lopatkin et al. 10 showed experimentally that nine common plasmids across six incompatibility groups can persist in microbial consortia in the absence of positive selection provided transfer rates are sufficiently high. Similarly, Porse et al. 61 found that plasmid loss rates offset the fitness cost of 14 plasmids found in E. coli strains commonly involved in urinary tract infections, driving AR persistence in those strains. We show that the interplay between these factors determines the spread of AR-encoding plasmids differently depending on the successional stage of the community. Very high plasmid transfer or very low loss rates can both lead to the preservation of plasmids at the expansion frontier over time, leading to maximal AR spread at later times of antibiotic administration (Fig. 5d, e ). This finding confirms previous work showing that it only takes the presence of a highly proficient donor (one with high plasmid transfer and low plasmid loss rates) to maintain plasmids in adjacent poor recipient populations (those with low plasmid transfer and high plasmid loss rates) 8 . On the other end, very low plasmid transfer or very high plasmid loss rates rapidly purge the plasmid from the expansion frontier and prevent AR spread (Fig. 5d, e ), and it is only when plasmid transfer and loss rates balance each other that maximal AR spread occurs at intermediate stages of community succession. Plasmid loss rates are highly variable even among strains of the same species 46 , and in complex communities, plasmid persistence in the absence of positive selection is associated with the proportion of highly proficient versus poor strains at maintaining and transferring the plasmid 62 . Intuitively, the presence of poor plasmid recipients is higher in complex communities, which could hamper the maintenance of AR. However, Kottara et al. 62 found that plasmid transfer and loss rates can offset the influence of the selective environment and of specific plasmid features to determine plasmid spread in soil microbial communities. Similar experiments to those shown here that track plasmid dynamics in more complex communities containing taxa with different plasmid transfer and loss rates would help understand how varying levels of plasmid transfer and loss rates influence the spread of plasmid-encoded AR in natural systems. We are yet aware that estimating the plasmid transfer probability is not trivial as numerous abiotic and biotic factors need to be considered such as nutrient level, pH, and temperature 63 – 65 . Especially in spatially structured environments, individual cells likely encounter different environmental conditions and thus have different transfer and loss rates at different locations. Our results can aid the mechanistic understanding of the spread of plasmid-encoded AR on surfaces colonized by microbial communities while acknowledging that plasmid dynamics are likely far more complex in natural systems. The growing body of studies that identify high plasmid transfer or low plasmid loss rates as the primary mechanism for AR maintenance in the absence of antibiotic pressure (e.g., Lopatkin et al. 10 ) suggests cessation of antibiotic use will not be sufficient to eradicate plasmid-encoded AR over prolonged periods of time. Because the timing of antibiotic administration can be a factor that varies under different circumstances 66 – 68 , we believe it is important to understand the relationships between antibiotic administration times and the spread of AR. We thus believe that a better temporal understanding of the interplay between plasmid transfer and loss in more complex microbial communities is essential to better understand the problem of AR persistence in efforts to tackle the global AR crisis."
} | 4,331 |
26696820 | PMC4678234 | pmc | 3,153 | {
"abstract": "Evaluating the effectiveness and performance of neuromorphic hardware is difficult. It is even more difficult when the task of interest is a closed-loop task; that is, a task where the output from the neuromorphic hardware affects some environment, which then in turn affects the hardware's future input. However, closed-loop situations are one of the primary potential uses of neuromorphic hardware. To address this, we present a methodology for generating closed-loop benchmarks that makes use of a hybrid of real physical embodiment and a type of “minimal” simulation. Minimal simulation has been shown to lead to robust real-world performance, while still maintaining the practical advantages of simulation, such as making it easy for the same benchmark to be used by many researchers. This method is flexible enough to allow researchers to explicitly modify the benchmarks to identify specific task domains where particular hardware excels. To demonstrate the method, we present a set of novel benchmarks that focus on motor control for an arbitrary system with unknown external forces. Using these benchmarks, we show that an error-driven learning rule can consistently improve motor control performance across a randomly generated family of closed-loop simulations, even when there are up to 15 interacting joints to be controlled.",
"conclusion": "6. Conclusions We have described a new method for benchmarking neuromorphic hardware that addresses the problem of reliably benchmarking complex tasks that involve interaction with an environment. This method involves building a minimal simulation; a simulation that is extremely simple in terms of required computation, but that has a high degree of adjustable variability. By benchmarking across a space of possibilities, we can identify hardware that performs well across that space, and is thus likely to be useful in real-world situations. In order to identify which real-world situations are covered by a minimal simulation, we can tune the variability in the simulation to particular physical systems. We demonstrated this approach by defining a minimal simulation and a task appropriate for adaptive motor control. We presented an algorithm that can use neuromorphic hardware to improve performance on this task over that of a standard non-adaptive controller. Importantly, by measuring performance while adjusting the distributions of parameters in the benchmark, it is possible to characterize different aspects of the hardware, identifying how different aspects of the task affect performance for different hardware. This was demonstrated by providing five different benchmarks, each based on the same minimal simulation, but setting parameters in different ways. We believe this sort of flexibility is important in a benchmark method, as it lets researchers be explicit about what their hardware is good at, while still using the same basic and shareable benchmark framework. Finally, we note that the benchmarking results show that this learning rule can consistently improve control performance across a wide variety of randomly generated situations, and is suitable for implementation on a wide variety of neuromorphic hardware. Given this promising result, we will be further evaluating it on specific physical embodiments, and comparing it to more complex variants of PID control.",
"introduction": "1. Introduction Neuromorphic hardware holds great promise for a wide variety of applications. The combination of massively parallel computation and low power consumption means that there is the potential to have complex algorithms running in embedded processing situations, without being a significant drain on available energy. A crucial challenge is to identify what sort of always-on or interactive functionality can best exploit these devices. To evaluate applications of neuromorphic hardware, we need benchmark tasks. These tasks must allow us to compare across different instances of neuromorphic hardware (and potentially across different algorithms implemented in that hardware). Good benchmarks will allow us to quantitatively compare systems, letting researchers both measure the progress in the field, and also directly compare competing approaches. In this paper, we focus on the development of closed-loop benchmarks. These are dynamic tasks where the output of the neuromorphic hardware influences its own future input through some environment. This is in contrast to standard categorization or pattern identification tasks, where the input is some fixed sequence and the hardware must produce the correct output for each input (or input pattern). We believe closed-loop benchmarks should be of particular interest to neuromorphic research, given that the most compelling applications of neuromorphic hardware are likely to be in this domain of embedded and interactive control of robotic or other physical systems. However, the closed loop itself raises a number of issues that complicate the development of such benchmarks. Rather than simply providing a data file of inputs and desired outputs, the benchmark must either specify a full physical system to be controlled, or it must provide software for a simulation of that system. As we discuss below, both approaches are problematic. Describing a method for overcoming these shortcomings is the primary goal of this paper.",
"discussion": "5. Discussion While the primary purpose of this paper is in describing the benchmarking methodology, it is also worth noting that these benchmarks indicate that the neuromorphic learning rule under investigation here is quite robust. As shown in Figure 9 , even just 500 neurons can consistently adapt to control a randomly generated 15-joint body simulation, and deal with larger delays and noise than were seen in the example 1-joint physical embodiment. Since this learning system is robust across such a wide range of conditions, and since it is efficiently implementable in a wide variety of neuromorphic hardware, we feel it is worth further study. This must include both a wider variety of minimal simulation benchmarks and also a few more traditional benchmarks. These traditional benchmarks would be particular real physical systems (specific robot arms, for example), but testing on those would only reveal performance on those particular arms. As we argued here, benchmarking against a wide variety of randomly generated minimal simulation systems is needed to demonstrate the space of potential situations in which neuromorphic adaptive control performs well. The benchmarks described above all use the same underlying minimal simulation as a way to characterize the overall performance of particular hardware across a range of situations. By adjusting the random distributions that define that range of situations, we generate different benchmarks that explore the capabilities of the systems in different ways. This allows for an explicit depiction of the sorts of conditions in which particular neuromorphic hardware performs well. After all, it is unlikely that one piece of neuromorphic hardware will be the best choice in all situations; rather, these benchmarks allow us to demonstrate the advantages and disadvantages of the hardware by looking at the same underlying system, but with multiple different distributions of parameters. Python software for the minimal simulation and the full benchmarks are available at http://github.com/ctn-waterloo/ctn_benchmarks . 5.1. Benchmark improvements The benchmarks presented here can be improved and further developed in several ways. Most obviously, we need to benchmark more hardware, and in particular we note that none of the systems tested here are analog neuromorphic hardware. While getting access to such hardware can be difficult, we believe the fact that our benchmark is easily shared with others as source code and interacts with existing hardware using a Python interface will help this process. Interestingly, it is worth noting that these benchmarks can also be run on software simulations of hardware (analog or digital), and could even be used to help form design decisions about hardware that has not yet been produced. However, it is also clear that performance on these benchmarks is a result of a combination of the hardware itself, the algorithm being run, and the system that interfaces the hardware to the environment. Thus, for any given hardware, we can explore improvements to the algorithm (better choices for e , different learning rules, adaptive learning rates, adapting K p and K d , etc.). For example, in the SpiNNaker hardware implementation not only can the neuron model be adjusted, but the distribution of the task across the multiple cores is also under programmer control. Furthermore, SpiNNaker provides a custom I/O interface for high-speed communication that could be used to reduce communication delay. In addition, other classes of benchmarks could rely on expanded or completely different minimal simulations. For example, other physical systems could be used to calibrate the minimal simulation. This would lead to other classes of randomly generated external forces that may be more (or less) difficult for the neuromorphic system to learn. If we identify classes of tasks that we are likely to want to control, we can create modify those randomly generated forces to ones that are more appropriate for different tasks. For example, it may be of interest to randomly generate N -joint arms with random arm lengths and random masses, and derive (an approximation of) the actual forces that would be seen in those situations. In particular, we feel benchmarks based on the biologically-inspired “soft-robotics” systems (e.g., Pfeifer et al., 2013 ) would be particularly appropriate for neural control, given the complexity involved in generating traditional controllers for them. 5.2. Other benchmarks While the particular minimal simulation shown here suggests that this adaptive control algorithm is worth further investigation, the overall goal of this paper is to present the general idea of using minimal simulation as a way to benchmark neuromorphic hardware. That is, we believe this same approach could be scaled up to other, more complex, closed-loop tasks. Importantly, benchmarking these other tasks would require both the creation of new minimal simulations and the specification of new algorithms suitable for performing those tasks. These algorithms would then be implemented with the neuromorphic hardware and connected to the minimal simulations to construct new benchmarks. As a first step toward scaling up, consider the more complex task of controlling a system where the values to be controlled are not the joints themselves. For example, suppose we want to control the position of a hand x , but our output u only directly controls the joints q of an arm. The position of the hand x is some function of q , but this function may be unknown or highly complex. This is often expressed as ẋ = J ( q ) q ˙ , where J ( q ) is the Jacobian. In order to successfully control x (the hand), the system needs to learn the relationship J that indicates how adjusting various joints q will affect the position of the hand. Crucially, there is a learning rule similar to the one discussed above that can learn this mapping (Cheah et al., 2006 ), and we have had some success in using it for particular arm control tasks (DeWolf, 2014 ). So far we have only tested this algorithm in the context of one particular arm, but it was successful in learning this relationship, and thus learning to correctly move its hand given an unknown arm geometry. To establish that this is a generally useful task for neuromorphic hardware, we need to benchmark this rule against a large family of different arms (and other systems to be controlled). This can be done by generating minimal simulations very similar to the one presented here; the main difference is that there would also be a randomly generated Jacobian function J ( q ). It should also be noted that in this context, the dimensionality of x and the dimensionality of q are separate variables. It may be that some algorithms work well when q is much larger than x , while others work best when they are similar. Exploring this relationship is fairly straightforward with minimal simulation, and would be an important result to know when choosing neuromorphic hardware for a particular new situation. Given this, we believe that the combination of minimal simulation and neuromorphic hardware is useful for adaptive control problems in general, whether the adaptation is in terms of an additive bias term to compensate for external forces such as gravity (as seen in the benchmarks presented in this paper) or if it is in terms of learning the Jacobian term relating the controlled variables q to the desired target space x (as in the adaptive Jacobian model discussed in the previous paragraph). This should allow systems to adapt to both unknown external forces and to unknown bodily geometries. However, it is less clear whether this approach will scale to more complex robotics tasks. One more complex robotic task where this approach might be applicable is navigation and obstacle avoidance. Here, we would need both a more complex minimal simulation for the environment, and an explicit neuromorphic algorithm capable of performing this avoidance. The minimal simulation itself would need to include some sort of sensory modality (vision, range sensing, or both), and movement in a two-dimensional environment (probably wheeled movement, for simplicity). To run such a simulation in real-time, we would use many of the same optimizations and simplifications used in Jakobi's original work (Jakobi, 1997 ). These included making separate simulations for corridors and intersections (rather than generic simulations for any possible geometries), using noisy lookup tables (rather than detailed physics simulations), treating collisions as failures (rather than modeling them), and using shifting random dot patterns for visual stimuli (rather than high-fidelity image rendering). Given Jakobi's success at building high-speed simulations over 20 years ago, we believe real-time simulations of this type are feasible now. However, having such a simulation is only half of what is required. We would also need a control algorithm suitable for such a situation. This is, itself, a topic of much research, and there is no clear best approach. We have been exploring the use of reinforcement learning in neural models (Stewart et al., 2012 ; Rasmussen and Eliasmith, 2014 ), and note that these make use of the same learning algorithm as described here, with additional neural components needed to implement action selection. In this case, the learning rule would adjust the system's estimate of which action is most appropriate given the current sensory state. We are currently investigating this approach further. As a more speculative possibility, we also intend to apply this approach to tasks involving classical and operant conditioning. Conditioning effects are extremely common in living creatures, and are clearly evident when animals are exposed to novel environments. As such, it is natural to define benchmark tasks involving learning the associations between sensory events in the environment (akin to classical conditioning) and the associations between actions and desired sensory states (akin to operant conditioning). In this case, the minimal simulations would consist of a set of small, controlled rooms with controllable buttons and stimuli, matching the sort of “Skinner Box” environments used in experimental psychology. The minimal simulation will also require a basic simulated body, capable of movement, pushing buttons, and observing stimuli. The tasks would consist of pairing stimuli together and determining if the learning algorithm is able to respond correctly. For example, a model might have a built-in response where it will salivate when presented with food. If the sound of a bell is paired with the presentation of food, it should learn to salivate with presented with just the sound of a bell. Importantly, there are extensive results showing the rate at which such associations are learned and un-learned in various animals. Furthermore, we would test the ability to learn associations that are separated in time (delayed conditioning), and to recover associations that had been previously learned (spontaneous recovery). Interestingly, there already exist neuron-based classical conditioning learning rules that may be suitable for such implementation, given their similarity to the learning rule used in the adaptive control benchmark (Verschure et al., 2003 )."
} | 4,184 |
36798498 | PMC9926886 | pmc | 3,157 | {
"abstract": "Due to the increased industrial oily wastewater, developing a successful oil/water separation mechanism is a ubiquitous challenge. As oil/water separation is an interfacial phenomenon, a straightforward way is to utilize the special wettability of novel materials towards oil and water. In this work, we intend to construct a durable membrane/mesh that can have a selective response towards oil and water based on the difference in surface tension. Graphene oxide (GO) is one such material that exhibits in-air hydrophilicity and underwater superoleophobicity. GO-coated wire meshes can act as membranes with excellent efficiency for oil/water separation, but they lack long-term durability for repeated use under different environments. We created GO*-coated wire meshes by dip coating multiple layers of GO with intermediate air plasma treatment. While the multiple steps of coating ensured complete coverage of the mesh with GO, plasma treatment improved the binding of the GO coating to the wire mesh. After coating five GO layers, the mesh is subjected to mild plasma treatment to improve the porosity. The GO*-coated mesh is extremely hydrophilic in air, and the underwater oil contact angles (CA) are ≥125° for different oils. To test the long-term durability, the GO*-coated mesh is continuously immersed underwater in acidic and basic media, and the underwater oil CA is measured at different immersion times. The initial durability results are very promising and show that the GO*-coated mesh retains a significant level of underwater oleophobicity even after 60 days of continuous immersion in water.",
"conclusion": "4. Conclusion In this work, we show that intermediate steps of air plasma treatment during the coating of GO on a wire mesh significantly improve its hydrophilic and underwater oleophobic properties towards different types of low surface tension liquids (edible oil, toluene, kerosene). We used a wire mesh with a large pore size (300 μm) and multiple GO dip coating steps followed by plasma treatment to open up the fully obturate pores and control pore size to obtain a GO*-coated mesh. The underwater oil CA significantly increased by at least 30% for different liquids as compared to bare mesh. In addition to this, we tested the long-term durability of the GO*-coated mesh in acidic, basic and neutral media. The GO*-coated mesh performs much better than the GO-coated mesh (without plasma treatment) when immersed continuously underwater for 60 days. While the GO-coated mesh lost underwater oleophobicity in 10 days and leaching of GO flakes was observed, the GO*-coated mesh maintained high oil CA even after 60 days of continuous immersion. We can infer that plasma treatment not only helps unclog obturate pores, but also improves the binding of the GO coating to the mesh. In acidic and basic media, the protonation or ionization of GO leads to gradual degradation of the coating. The maximum degradation was observed in the basic medium as the underwater oil CA reduced by 61.7%. This work highlights that while methods such as air plasma treatment can improve the underwater oleophobicity of the GO-coated mesh, it is also extremely important to study the long-term durability of these coatings upon continuous immersion in water and other media before proposing them as good oil/water separation membranes.",
"introduction": "1. Introduction Nanotechnology and its unique implications have evolved in nature in various forms. Many enchanting effects seen in nature, such as the water-repelling and self-cleaning properties of the lotus leaf, a water strider walking on water, the brilliant colors of a butterfly, or the super adhesion exhibited by spiders and geckos climbing on vertical surfaces, are essentially due to the presence of micro to nanoscale hierarchical structured surfaces with complex morphologies and chemical composition. 1 Several of these properties, if replicated into artificial materials, can lead to enormous benefits and multiple applications. 2–4 One such application garnering much attention and is the need of the hour is oil/water separation. 4,5 Oil/water separation techniques will have an immediate pragmatic contribution to fixing the obstacle of industrial oily wastewater and other pollution caused by oil. 6 With the fast development of our industries, oily wastewater discharge and oil spills have seriously polluted our environment. A swift environmental demand emphasizes the need for materials that can separate oil and water. The traditional separation processes used for separating oil and water require special equipment, consume high energy, and are expensive. 7 For example, mechanical devices such as oil skimmers, 8 agitated floatation cells, 9 and microwave heaters that use temperature change 10 all require high power and high pressures to aid in the separation. Other material absorption-based separation techniques include foams, sponges, or textiles, 11–13 but these materials have limitations such as poor selectivity towards oil and low efficiency, as well as their recycling being difficult and time-consuming. 7 To overcome these shortcomings, it is essential to design simple and economic approaches which are durable and can be implemented for large-scale oil/water separations. For achieving oil/water separation, we need to target properties that are very different between oil and water. The surface tension of water is ∼72.8 mJ m −2 , whereas, for most oils, surface tension is below 30 mJ m −2 . Thus, by creating porous membranes/meshes that have selective responses based on the surface tension of the liquid, one can achieve effective oil/water separation. Much research has been reported in this regard with the emergence of biomimetic water-repelling (superhydrophobic) and oil repelling (superoleophobic) surfaces inspired by the surface features of lotus leaves and springtails. 1,2 Novel materials with unique micro and nanoscale surface structures have been ingeniously designed to achieve both superhydrophobic and superoleophobic properties. 14–16 But for the required oil/water separation, we need to fabricate materials that are either superhydrophobic/superoleophilic (high affinity towards oil) or superoleophobic/superhydrophilic (high affinity towards water). 4–7 In the first approach, the oil phase will spread quickly on the surface and penetrate it (in the case of a porous membrane), while the water phase will be repelled, resulting in oil/water separation. 17 However, as oil has a lower density than water, it is challenging to design an efficient separation technique for large-scale applications. Moreover, oil-removing membranes easily become fouled and clogged by the oil due to the oleophilic properties, reducing the separation efficiency. 4 The second approach of superoleophobic/superhydrophilic surfaces/membranes also has several limitations. Oil has a much lower surface tension than water, due to which a superhydrophilic surface exhibits superoleophilicity. In addition, making any surface oleophobic is not easy as there are no chemicals available that can directly achieve this property. Superoleophobicity has only been achieved by making specific micro and nanoscale structures with fluorinated polymers, which can be a complicated multi-step process. 4 However, the study of fish scales a decade ago showed that they are highly hydrophilic and, therefore, can exhibit superoleophobicity underwater and protect the fish from contagion by oil pollution in the sea. 18 This inspired the most effective and straightforward oil/water separation techniques reported till now based on membranes/meshes showing superhydrophilicity at the air/solid interface and superoleophobicity at the water/solid interface. One of the first works on oil/water separation using a superhydrophilic and underwater superoleophobic mesh was reported by Xue et al. using PAM hydrogel-coated stainless steel meshes to separate water from oil/water mixtures with >99% efficiency. 19 However, hydrogels can swell quickly in water and have weak stability. Several other techniques and materials have been used since then for better functionalization of meshes. Coatings of organic materials such as polymers, block copolymers, polyelectrolytes, polymer blends, and polymer brushes have been extensively used to create hydrophilic water-selective meshes. 7,20–23 Copper (Cu), copper oxide, or copper hydroxide-based nanostructure-coated meshes have been the most widely reported inorganic functionalization techniques to obtain water-selective meshes. 3,24,25 Zhang et al. reported Cu(OH) 2 nanowire-haired copper mesh that can effectively separate oil/water mixtures and oil-in-water emulsions and provide long-term anti-fouling properties. 24 Apart from Cu, silica particles, carbon nanotubes, titanium dioxide nanoparticles, zeolites, and several other materials have also been used to functionalize metal meshes better. All the reported meshes with organic or inorganic materials have reasonable oil/water separation efficiency, but they either fail to give high filtrate flux or have poor chemical stability. 5,6 For better stability, direct etching of the metallic meshes using the laser ablation technique has been used for making more reusable meshes. But the method can be costly for large-scale oil/water separation. Recently, Lian et al. reported a nanosecond laser ablation technique to modify brass mesh, which they claim is low cost and more economical compared to previous methods. 26 Of all the reported materials, graphene oxide (GO) coated membranes can be considered unique because of the layered nanostructure resembling that of fish scales or clamshells, abundant oxygen-containing functional groups, and excellent hydrophilicity, making them promising 2D meshes for oil/water separation. 27–31 Recently, simple GO coatings on brass or steel wire meshes have been reported with high separation efficiency. Dong et al. reported for the first time in 2014 that GO-coated stainless steel meshes have extraordinary hydrophilic and underwater superoleophobic properties and can be used for gravity-driven oil/water separation. 27 The GO-coated meshes showed very low oil-adhesion characteristics and separation efficiency above 90% with all types of oils. Liu et al. used O 2 plasma treatment after coating GO on the stainless-steel mesh to open clogged pores and change the pore diameter. 28 They achieved high separation efficiency even after 50 cycles of oil/water separation. Both works mention that finer meshes (300 or 400 mesh) with pore diameter of ∼40 μm were best suited for oil/water separation. While GO coated meshes have been proven to be highly effective and promising for large-scale oil/water separation applications, to achieve a reasonable flux rate at low cost, we need to depend on a coarser mesh with larger pore size, and for long-term usage of these meshes, we need to have the excellent chemical stability of the GO coating. 31 Notably, for marine applications, the long-term effect of continuous immersion underwater on superoleophobicity must be checked. 32 In this work, we report the preparation of a stable underwater superoleophobic mesh by dip-coating GO on a brass mesh. Air plasma treatment of the mesh was done before and after the GO coating steps. The initial plasma treatment of the bare mesh helped improve the adhesion between the GO and the metallic mesh. The dip-coating of GO was done multiple times to achieve complete coverage and a layered texture. After dip coating, the second plasma treatment resulted in the etching and opening of the fully obturate mesh pores. We also checked for the long-term durability of the GO coating on the wire mesh for the first time upon continuous immersion of the mesh in acidic, basic, and neutral media, mimicking the usual properties of industrial oily wastewater. We observed that the plasma-treated meshes remained superoleophobic underwater even after 60 days of immersion, while the untreated samples showed leaching of the GO coating within a couple of hours. We show that the plasma treatment steps significantly enhance the long-term stability and chemical durability of the GO coating on the wire mesh.",
"discussion": "3. Results and discussion GO monolayers possess sp 2 hybridized carbon atoms and partly sp 3 hybridized carbon atoms having oxygen-containing functional groups. Fig. 2A reveals the FTIR transmittance spectra of the as-prepared GO powder. The broad peak at 3442.31 cm −1 can be assigned to the stretching of the O–H bond, which is in the high-frequency area. This reveals the presence of hydroxyl groups bonded onto carbon at several places in the GO molecular structure. The bands at 1722.121 cm −1 and 1628.5 cm −1 depict C \n \n\n<svg xmlns=\"http://www.w3.org/2000/svg\" version=\"1.0\" width=\"13.200000pt\" height=\"16.000000pt\" viewBox=\"0 0 13.200000 16.000000\" preserveAspectRatio=\"xMidYMid meet\"><metadata>\nCreated by potrace 1.16, written by Peter Selinger 2001-2019\n</metadata><g transform=\"translate(1.000000,15.000000) scale(0.017500,-0.017500)\" fill=\"currentColor\" stroke=\"none\"><path d=\"M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z\"/></g></svg>\n\n O and C C bonds, respectively, which confirms the presence of the carboxylic acid group and aromatic groups. The band at 1395.24 cm −1 can be due to the stretching of the C–OH group in water molecules soaked onto GO sheets. Similarly, the bands at 1219.75 cm −1 and 1044.56 cm −1 can be due to the stretching of C–O (epoxy) groups. Fig. 2B shows the XPS C 1s spectra of the as-prepared GO powder. After deconvolution, it is distinctly apparent that the C 1s spectrum contains four peaks at 284.78 eV, 286.88 eV, 288.68 eV, and 289.78 eV, which are attributed to the C C bond (in the aromatic ring), C–O bond (in hydroxyl and epoxy groups), C O bond (carbonyl group) and O–C O (carboxyl group) respectively. We can clearly infer from the intensities of the peaks that GO has been oxidized satisfactorily. 33 Fig. 2C and D show the AFM and FESEM images, respectively of the GO sheets on the silicon wafer substrate. Both AFM and FESEM images show the presence of thin sheets along with wrinkle-like structures on the GO surface. This wrinkle formation may have been observed due to the coating and the drying process on the substrate. 36 To check the level of oxidation and hydrophilicity, the GO powder was dispersed in water and mixed with an equal amount of different non-polar solvents with vigorous shaking by hand. The nonpolar solvents used were kerosene, toluene, petroleum ether, hexane, chloroform, and edible sunflower oil, as shown in Fig. 2E . As the dispersion settled, we observed that most of the GO was present in the water phase proving the hydrophilic properties of GO. Some amount of GO was also seen in the interface between water and the non-polar solvents, as GO can also act as an amphiphilic material due to the sp 2 conjugated system. 27 Fig. 2 (A) FTIR spectrum of GO. (B) XPS C 1s spectrum of GO. (C) AFM image of GO sheets coated on a silicon wafer. (D) FESEM image of GO sheets. (E) GO dispersion in water and various nonpolar solvents for testing its hydrophilicity. \n Fig. 3A shows the OM images of the brass mesh (∼300 μm pore size) after cleaning and plasma treatment. The initial plasma treatment was done to remove any impurities, increase the surface energy and oxidize the surface for better binding of GO to the mesh. To achieve uniform coverage of GO on the mesh, we dip-coated the mesh with the GO dispersion five times with intermediate drying after each coating. Fig. 3B shows the mesh after applying three coats of GO. After coating five times, we observed that most of the pores in the mesh were covered with a continuous GO film, as seen in Fig. 3C . To open the fully obturate pores, the mesh was subjected to air plasma treatment from one side for 1 min. 28 Plasma treatment leads to strong oxidation and etching of GO from the pores of the mesh while the GO coating on the opposite side of the mesh remains intact. After treatment, we obtained a GO*-coated mesh with all open pores with an average pore size of 202 ± 15 μm, as seen in Fig. 3D . While applying multiple layers of coating helps in ensuring uniform coverage of the mesh with GO, the final plasma treatment can be used to open pores with control of pore size. Fig. 3 Optical microscope images of the brass mesh (A) after cleaning and plasma treatment, (B) after dip coating three times with GO, and (C) after dip coating five times with GO, as well as (D) open pores after final plasma treatment. The scale bar represents 200 μm. The in-air wettability and underwater oleophobicity of the mesh were quantified using contact angle (CA) measurements. The bare mesh showed slight hydrophobicity in the air with a CA of ∼92.7° ± 1.6°. The image of a water drop on the brass mesh is shown in Fig. 4A . The GO-coated mesh was hydrophilic with an initial CA of 81.3° ± 2.2° which reduced to 29.0° slowly over 15 min as water permeated through the mesh ( Fig. 4B ). Upon coating GO following our protocol which includes plasma treatment steps, we observed an initial CA of 74.3° ± 2°. The water drops quickly permeated through the GO*-coated mesh, and the CA reduced to 5.5° within 30 s, and the drop fully disappeared ( Fig. 4C ). The improved hydrophilic nature of the GO*-coated mesh and open pores obtained after plasma treatment makes water permeate through the membrane very quickly, which is an essential property for high flux underwater oil/water separation application. The underwater oil CA was measured by placing the mesh samples upside down and immersing in water near the top of a water bath. Drops of oil or organic solvent like toluene were created in the water bath and were allowed to deposit on the mesh as the drops moved upwards due to density difference. The CA data and images of oil drops on bare mesh, GO-coated mesh, and GO*-coated mesh are shown in Fig. 4D for edible oil, toluene, and kerosene. The GO*-coated mesh showed a CA of 130° or above for the three oils, whereas the GO-coated mesh showed a CA of above 110° for the three oils. The bare mesh showed CA between 85° and 105°. This is a considerable improvement in oleophobic properties for a coarse mesh with ∼300 μm pore size. The reason behind the underwater oleophobicity of the GO*-coated mesh is its super hydrophilicity which is a combined effect of GO coating and plasma treatment. Typically, the liquid CA and wettability on a solid surface in the air are determined using Young's equation. 1 Young's equation can be modified for different settings, including the determination of CA of a liquid on a solid surface immersed in a second liquid. 18 The modified equation can be written as: 1 where γ o–a is the oil–air interface tension, θ 1 is the CA of oil in the air, γ w–a is the water–air interface tension, θ 2 is the CA of water in the air, γ o–w is the oil/water interface tension, and θ 3 is the CA of oil in water. We have calculated the values of θ 3 for edible oil and non-polar liquids using in-air CA values (Table S1, ESI † ). If we take edible oil as an example, γ o–a = 31.5 mN m −1 , γ w–a = 72.8 mN m −1 and γ o–w = 37.04 mN m −1 . The CA of edible oil ( θ 1 ) on a GO-coated glass slide in the air was ∼10.5° ± 0.6°. The initial CA of water on a glass slide coated once with GO ( θ 2 ) was measured to be 59.8° ± 3°. Therefore, using eqn (1) , the CA of edible oil on the glass slide when placed underwater ( θ 3 ) was calculated to be 105.5°. This shows that GO-coated surfaces show oleophobic nature underwater. Eqn (1) also shows that a decrease in the value of θ 2 will lead to an increase in the value of θ 3 . Thus, a more hydrophilic surface in air will show better oleophobicity underwater. With our coating process using multiple rounds of dip coating and plasma treatment, we were able to make meshes with significantly lower values of θ 2 (as shown in Fig. 4B ) and achieve superoleophobicity underwater. Fig. 4 (A) In-air water CA on an uncoated bare mesh. (B) CA of water on the GO-coated mesh reduced over 15 min from 81.3° to 29.0°. (C) CA of water on the GO*-coated mesh was measured to be 74.3° which reduced as the water permeated immediately through the open pores. (D) Underwater CA of edible oil, toluene, and kerosene on bare mesh, GO-coated mesh, and GO*-coated mesh. Insets show the images of the oil drops. The durability of the coating on the mesh is a significant factor in determining the long-term usage of the mesh in applications such as oil/water separation. While a myriad of fabrication techniques have been proposed to date, the foremost challenge with all the techniques is the poor durability against external influences. 4 Many works have reported the stable separation efficiency of the membranes after repeated cycles of oil/water separation tests. Some of the works went one step ahead and tested chemical and thermal stability by using water/oil mixtures containing hot water, acidic water, basic water, or salt. 28,31,37 But only a few groups have studied the long-term durability and chemical stability of the meshes when immersed in a medium for durations up to 24 h. 37 To better understand the long-term durability of the GO*-coated mesh and the stability of the superoleophobic properties of the mesh, we immersed the GO*-coated mesh samples in water, acidic medium, and basic medium continuously for up to 60 days. We took out different samples at intermediate durations, dried them naturally, and imaged and measured the underwater oil CA. \n Fig. 5A and B show the GO-coated mesh and GO*-coated mesh immersed in water, respectively. Upon continuous immersion for 10 days, we observed that the GO-coated mesh started leaching out, and the GO flakes dispersed into the water slowly, as seen in Fig. 5A . Under an OM, we can see that the coating is missing from several parts of the mesh, as shown in Fig. 5E . For the GO*-coated mesh samples, we did not see any GO flakes leaching out even after 60 days of continuous immersion ( Fig. 5B ). This experiment gives preliminary proof that the initial step of plasma treatment has helped in improving the adhesion between GO flakes and the brass mesh. Fig. 5F shows the OM image of the mesh after 60 days of continuous immersion in water. We can see that the mesh is still coated with the GO and looks similar to the GO*-coated mesh shown in Fig. 3D . Fig. 5 (A and E) GO-coated mesh immersed in water for 10 days and the corresponding OM image of the mesh after drying. GO*-coated mesh samples immersed continuously for 60 days in (B and F) water, (C and G) acidic medium, and (D and H) basic medium. The scale bar for OM images represents 200 μm. (I) Variation in the underwater edible oil CA when the GO*-coated mesh was immersed in water, acidic medium and basic medium for time durations up to 60 days. In a low pH medium, it has been reported that the carboxyl groups of the GO sheets become protonated, lose their hydrophilic properties, and form aggregates. 38 When GO*-coated meshes were immersed in an acidic medium, we observed a similar process of gradual formation of aggregates in the medium, which was clearly visible after 60 days of continuous immersion, as seen in Fig. 5C . The formed aggregates may detach from the mesh and remain suspended in the medium. Fig. 5G shows the OM image of the same mesh in which the GO coating around the wire mesh appears to be swollen with pore size ∼ 63 ± 2 μm. The swelling can be due to the protonated carboxyl groups of GO in an acidic medium, which can form stable layered aggregates of GO and water. 38,39 In a basic medium, the ionization of the carboxylic groups may cause the dissolution of GO sheets into the medium. 39 While we did not observe any change in the color of the basic medium even after 60 days of continuous immersion, the brass mesh became very brittle and corroded due to dezincification in the high pH medium ( Fig. 5D ). The dissolution of the GO coating exposed the brass mesh which caused faster corrosion. Fig. 5H shows that the pore size of the mesh in the basic medium has been reduced to ∼50 ± 8 μm, and a few pores have closed up. For the GO-coated mesh, after ten days of continuous immersion in water, the underwater edible oil CA reduced from 138.2° to 90.0° (35% reduction). The leaching of GO flakes reduces the oleophobicity, and the edible oil CA was similar to that of the bare mesh. In contrast, for the GO*-coated mesh, the edible oil CA reduced from 141.0° ± 3.0° to 135.0° ± 0.6° (4% reduction) after ten days of continuous immersion in water. Fig. 5I shows the variation in the underwater edible oil CA when the GO*-coated mesh is immersed continuously in water, acidic medium and basic medium for different durations of time up to 60 days. In the neutral medium, the GO*-coated mesh remains significantly oleophobic with an underwater edible oil CA of 112.0° ± 3.0° after 60 days of immersion (20.6% reduction). This shows that the GO*-coated mesh is much more durable than the GO-coated mesh. In an acidic medium, the formation of aggregates and leaching of GO flakes affected the oleophobicity as the edible oil CA dropped to 99° ± 1.0° after 60 days (30% reduction). The basic medium caused maximum degradation of the GO coating as the edible oil CA dropped to 54° ± 8.0° (61.7% reduction). Still, Fig. 5I confirms that all the GO*-coated meshes maintain significant oleophobicity (underwater oil CA > 120°) after 20 days of continuous immersion. Apart from oil CA, another important physical property for oil/water separation application is the breakthrough pressure, the maximum pressure required to make the liquid permeate through the mesh. 6 For an underwater superoleophobic mesh, the breakthrough pressure, Δ P w C , depends on r P (radius of the mesh pores) and is given as: 2 For the GO*-coated mesh, the theoretical value of Δ P w C was calculated to be 621.7 Pa, for r P = 101 μm. Upon continuous immersion in water, acidic medium and basic medium for 60 days, the theoretical Δ P w C reduced to 272.4 Pa, 198.6 Pa and −940.5 Pa respectively. This shows that along with degradation of superoleophobicity, the maximum pressure that the mesh can withstand also reduces. A negative value of Δ P w C in the basic medium indicates that the oil will spontaneously penetrate through the mesh without any external force and the mesh cannot be used for oil/water separation. Using Δ P w C = h max ρg ( ρ is the density of edible oil, g is the acceleration due to gravity, and h max is the maximum height of the edible oil column that the mesh can support), the theoretical value of h max over a fresh GO*-coated mesh was ∼6.9 cm. We also measured the stability of a 10 cm oil column over the GO*-coated mesh and found that the oil column remains stable over the mesh even after 30 min of observation. This shows that the experimental value of the breakthrough pressure for the mesh was ∼900.4 Pa."
} | 6,787 |
32728495 | PMC7357558 | pmc | 3,158 | {
"abstract": "Background Plants are commonly colonized by a wide diversity of microbial species and the relationships created can range from mutualistic through to parasitic. Microorganisms that typically form symptomless associations with internal plant tissues are termed endophytes. Endophytes associate with most plant species found in natural and managed ecosystems. They are extremely important plant partners that provide improved stress tolerance to the host compared with plants that lack this symbiosis. Plant domestication has reduced endophyte diversity and therefore the wild relatives of many crop species remain untapped reservoirs of beneficial microbes. Brassica species display immense diversity and consequently provide the greatest assortment of products used by humans from a single plant genus important for agriculture, horticulture, bioremediation, medicine, soil conditioners, composting crops, and in the production of edible and industrial oils. Many endophytes are horizontally transmitted, but some can colonize the plant’s reproductive tissues, and this gives these symbionts an efficient mechanism of propagation via plant seed (termed vertical transmission). Methods This study surveyed 83 wild and landrace Brassica accessions composed of 14 different species with a worldwide distribution for seed-originating bacterial endophytes. Seed was stringently disinfected, sown within sterile tissue culture pots within a sterile environment and incubated. After approximately 1-month, direct isolation techniques were used to recover bacterial endophytes from roots and shoots of symptomless plants. Bacteria were identified based on the PCR amplification of partial 16S rDNA gene sequences and annotated using the BLASTn program against the NCBI rRNA database. A diversity index was used as a quantitative measure to reflect how many different bacterial species there were in the seed-originating microbial community of the Brassica accessions sampled. Results Bacterial endophytes were recovered from the majority of the Brassica accessions screened. 16S rDNA gene sequencing identified 19 different bacterial species belonging to three phyla, namely Actinobacteria, Firmicutes and Proteobacteria with the most frequently isolated species being Methylobacterium fujisawaense , Stenotrophomonas rhizophila and Pseudomonas lactis . Methylobacterium was the dominant genus composing 56% of the culturable isolated bacterial community and was common in 77% of accessions possessing culturable bacterial endophytes. Two selected isolates of Methylobacterium significantly promoted plant growth when inoculated into a cultivar of oilseed rape and inhibited the growth of the pathogen Leptosphaeria maculans in dual culture. This is the first report that investigates the seed-originating endophytic microorganisms of wild Brassica species and highlights the Brassica microbiome as a resource for plant growth promoting bacteria and biological control agents.",
"conclusion": "Conclusions Although three species of Methylobacterium , namely Methylobacterium extorquens , Methylobacterium mesophilicum and Methylobacterium goesingense , were previously identified in Thlaspi goesingense belonging to the wider Brassicaceae family ( Idris et al., 2006 ), to our knowledge this is the first report to describe the isolation and identification of endophytic bacteria of seeds of wild and landrace Brassica species. We present a straight-forward strategy to screen and cultivate seed-originating endophytes with possible beneficial traits. The microbiome of many vegetables, including Brassica spp., can serve as sources of biological control agents ( Wassermann et al., 2017 ) while focusing our efforts on seed-originating organisms may facilitate novel endophyte technologies that could be incorporated into future crop seed ( Berg et al., 2017 ). This approach would then also be advantageous to companies that wish to invest in the commercialization of such products as they can lower their financial risk in terms of delivering a suitable efficacious product to farmers whilst protecting their IP. The latter is possible because an elite plant cultivar and the biological control agent can be protected together in one commercial seed product entity. This means of propagation relies on the plant’s reproductive strategy and may aid the marketing of any potential plant-endophyte product ( Card et al., 2016 ).",
"introduction": "Introduction Endophytes are a diverse sub-group of microorganisms that reside inside the tissues of nearly every vascular plant and, for at least part of their life cycle, do not cause any immediate symptoms ( Card et al., 2016 ; Hardoim et al., 2015 ; Porras-Alfaro & Bayman, 2011 ; Wilson, 1995 ). However, not all endophytes remain within their plant host throughout their entire life cycle. Additionally, some may change their behavior, from mutualistic to commensalism or even pathogenic, due to a change in the environment, during host senescence or when the host is stressed ( Aly, Debbab & Proksch, 2011 ; Fisher & Petrini, 1992 ). Endophytes can be found in nearly every type of plant organ, in both vegetative (e.g., leaves, roots and shoots) and reproductive (e.g., flower and seed) tissues ( Rodriguez et al., 2009 ). The presence of bacterial endophytes within the reproductive tissues has been reported for many plant species ( Mundt & Hinkle, 1976 ), including coffee ( Vega et al., 2005 ), cotton ( Adams & Kloepper, 1996 ), cucumber ( Khalaf & Raizada, 2016 ), eucalyptus ( Ferreira et al., 2008 ), oilseed rape ( Granér et al., 2003 ), maize ( Rijavec et al., 2007 ), Norway spruce ( Cankar et al., 2005 ), tobacco ( Mastretta et al., 2009 ) and rice ( Elbeltagy et al., 2000 ; Okunishi et al., 2005 ). These seed-originating bacterial endophytes may be disseminated from one generation to the next, persisting in the next population of plants ( López-López et al., 2010 ) and is indicative of their ability to vertically transmit. Plant hosts harboring endophytes can gain additional advantageous traits, granting them an ecological advantage over individuals lacking these microorganisms and/or other plant species that occupy a similar ecological niche. These benefits include greater resistance to abiotic and biotic stresses ( Hallmann et al., 1997 ; Mastretta et al., 2006 ) as well as plant growth promotion ( Azevedo et al., 2000 ). Modern Brassica cultivars were originally domesticated from species mostly originating from Europe ( Rakow, 2004 ), although now many Brassica crops, particularly Brassica napus (oilseed rape), Brassica rapa (turnip) and Brassica oleracea (cabbage), are extensively cultivated throughout the world. These species are a major source of vegetables for human consumption and for forage, ornamental plants, condiments, medicinal crops, green manure, bioremediation, and as very important sources of edible and industrial oils ( Dixon, 2007 ; Gómez-Campo, 1980 ). A wide range of insect pests, such as aphids ( Brevicoryne brassica ), diamond back moth ( Plutella xylostella ) and flea beetles ( Phyllotreta and Psylliodes spp.), in addition to several diseases, such as clubroot (caused by Plasmodiophora brassicae ), phoma stem canker (caused by Leptosphaeria maculans ) and sclerotinia stem rot (caused by Sclerotinia sclerotiorum ) cause extensive damage to Brassica crops worldwide ( Kimber & McGregor, 1995 ) with few or no control options available ( Granér et al., 2003 ). Most studies investigating endophytes of Brassica have focused on isolating microorganisms from the vegetative tissues of modern-day cultivars ( Germida et al., 1998 ; Narisawa, Tokumasu & Hashiba, 1998 ; Sheng et al., 2008 ; Sunkar & Nachiyar, 2013 ; Zhang et al., 2014 ). However, this strategy may be restrictive as the diversity and frequency of endophytic species found in domesticated crops is assumed to be much lower than in their respective wild relatives ( Mousa et al., 2015 ; Putra, Rahayu & Hidayat, 2015 ). Additionally, targeting endophytic species that are associated with the reproductive plant tissues (those microorganisms that are seed-borne or seed-transmitted) would greatly aid the marketing of potential commercial products ( Card et al., 2015 , 2016 ). This study focused on developing a strategy for screening wild and landrace Brassica species for mutualistic, seed-originating endophytes that may offer beneficial traits to elite Brassica cultivars.",
"discussion": "Discussion This study investigated the cultivable bacterial community persisting in wild and landrace Brassica seed. Nineteen bacterial species were isolated from 83 accessions, belonging to eight Brassica species, covering five continents, with some of the accessions more than 20 years old. The bacterial genera to which these species belong have been previously reported in the literature as seed endophytes of a diverse number of plant species. For example, Methylobacterium and Paenibacillus spp. have both been described as seed endophytes from Eucalyptus ( Ferreira et al., 2008 ), Oryza sativa ( Mano et al., 2006 ) and Phaseolus vulgaris ( López-López et al., 2010 ), while Bacillus and Micrococcus spp. are common seed endophytes of Coffea arabica ( Vega et al., 2005 ) and O. sativa ( Mano et al., 2006 ). Our results indicate that the diversity of bacterial endophytes in seed of wild Brassica is relatively high with most of the bacterial species identified belonging to the Proteobacteria, the major phylum of gram-negative bacteria. This is consistent with earlier work that showed the seed microbiome of oilseed rape were colonized mostly by Proteobacteria and that individual cultivars each had their own unique microbiome profile ( Rybakova et al., 2017 ). Development of an effective surface disinfection protocol was paramount to this study. A protocol that was too harsh could sterilize the seed and kill any potentially beneficial microorganisms residing in the seed tissues, as well as potentially damaging the seed itself, while a protocol that was too moderate could yield unwanted saprophytic microorganisms residing on the surface of the seed coat. These non-target saprophytes have the potential to outgrow any slower growing endophytic organisms that may be beneficial. Many of these non-target species can colonize the interior tissues of the germinating plant during the emergence of the radicle ( Bent & Chanway, 2002 ). The surface disinfection protocol used in this study was not designed to eliminate all organisms living on the seed surface, just to reduce their frequency. For example, Alternaria sp., commonly associated with seed coats or pericarps of seed ( Harman, 1983 ; Neergaard, 2011 ) was frequently isolated. Many studies have reported that strains belonging to the same genera identified in our study confer several beneficial traits to their host plants, including enhanced resistance against certain plant pathogens and/or growth promotion ( Araújo et al., 2002 ; Berg & Hallmann, 2006 ; Khan et al., 2014 ; Rashid, Charles & Glick, 2012 ; Rout & Chrzanowski, 2009 ; Sessitsch, Reiter & Berg, 2004 ; Ying et al., 2016 ). We assessed the antagonistic activity of selected isolates of bacterial species against L. maculans (the causal agent of phoma stem canker in oilseed rape) through dual culture bioassays and observed that Methylobacterium fujisawaense and Methylobacterium phyllosphaerae possessed antagonistic potential against the pathogen. The genus Methylobacterium is composed of pink-pigmented facultative methylotrophs (PPFMs) ( Dourado et al., 2015 ) that are able to form endophytic associations with a range of plant species including citrus ( Araújo et al., 2002 ), cotton ( Madhaiyan et al., 2012 ), eucalyptus ( Andreote et al., 2009 ), mangrove ( Dourado et al., 2012 ), peanut ( Madhaiyan et al., 2006b ), pine ( Pohjanen et al., 2014 ), tobacco ( Andreote et al., 2006 ) and white cabbage ( Wassermann et al., 2017 ). PPFMs are not pathogenic to their plant hosts ( Idris et al., 2006 ) making them ideal candidates for endophytic biological control strategies ( Omer, Tombolini & Gerhardson, 2004 ). Additionally, Methylobacterium spp. are able to enhance plant growth through several mechanisms, including, nitrogen fixation ( Lee et al., 2006 ; Menna et al., 2006 ; Sy et al., 2001 ), phytohormone production such as cytokinins and auxins ( Madhaiyan et al., 2006a ; Meena et al., 2012 ; Trotsenko, Ivanova & Doronina, 2001 ), interact with and inhibit plant pathogens ( Araújo et al., 2002 ; Lacava et al., 2004 ; Poorniammal, Sundaram & Kumutha, 2009 ), promote plant growth ( Madhaiyan et al., 2006a , 2006b ; Tani et al., 2012 ), induce higher photosynthetic activity ( Cervantesmartinez, Lopezdiaz & Rodriguezgaray, 2004 ), induce systemic resistance ( Madhaiyan et al., 2006b ), decrease environmental stress ( Muller et al., 2011 ) and immobilize heavy metals ( Dourado et al., 2012 ). We analyzed the fresh weight of seedlings of an oilseed rape cultivar under growth chamber conditions when the roots were inoculated with two isolates of Methylobacterium fujisawaense and Methylobacterium phyllosphaerae and found that inoculated plants had a higher growth rate than non-inoculated plants. Cultivated Brassica crops, such as oilseed rape, have a high nitrogen demand ( Rathke, Behrens & Diepenbrock, 2006 ) and their cultivation is reliant on fertilization with nitrogen rich products. These crops usually have low nitrogen use efficiency and this is a specific target for the breeding of new cultivars ( Bouchet et al., 2014 , 2016 ). The frequent presence of Methylobacterium in wild Brassica species, that are usually found within infertile soils, such as those where some of the wild species used in our study were collected suggests that this symbiosis improves the development of the host plant. These bacteria may therefore possess traits for use as plant growth promoters in artificial Brassica hosts such as domesticated cultivars. This study isolated species of Methylobacterium , and the closely related Methylorubrum extorquens ( Green & Ardley, 2018 ), from above and below ground plant organs (shoot and root, respectively). As morphologically similar isolates were identified from multiple root and shoot tissue pieces belonging to the same individual plant, we speculate that these bacterial isolates are capable of systemic plant colonization. Additionally, these tissues were dissected from symptomless seedlings grown from surface disinfected seed under sterile conditions and therefore this strongly suggests that these bacteria are vertically transmitted. The Methylobacterium species isolated in this study were present in a range of plant accessions originating from a geographically diverse set of countries with varied altitude. This is consistent with other reports of endophytic microbes, for example, among Zea spp. which were found across species grown in wide range of geographical locations ( Johnston-Monje & Raizada, 2011 ). It has been reported the age of seed may considerably influence the seed microbiome ( Cankar et al., 2005 ). Indeed, no bacteria were isolated from six accessions that had been stored for more than 15 years. However, one accession that was over 26 years old gave rise to Methylobacterium indicating that this bacterium can adapt and survive in seed tissues for a long period of storage time. Mano et al. (2006) reported that only certain bacteria such as Methylobacterium are able to reside inside rice seed. These endophytic bacteria enter the seeds during the seed maturation stages and are tolerant to high osmotic pressure. The isolates possess a high degree of amylase activity, which may aid survival in the seed ( Mano et al., 2006 )."
} | 3,960 |
36179017 | PMC9524840 | pmc | 3,160 | {
"abstract": "Infectious diseases are an increasing threat to coral reefs, resulting in altered community structure and hindering the functional contributions of disease-susceptible species. We exposed seven reef-building coral species from the Caribbean to white plague disease and determined processes involved in (i) lesion progression, (ii) within-species gene expression plasticity, and (iii) expression-level adaptation among species that lead to differences in disease risk. Gene expression networks enriched in immune genes and cytoskeletal arrangement processes were correlated to lesion progression rates. Whether or not a coral developed a lesion was mediated by plasticity in genes involved in extracellular matrix maintenance, autophagy, and apoptosis, while resistant coral species had constitutively higher expression of intracellular protein trafficking. This study offers insight into the process involved in lesion progression and within- and between-species dynamics that lead to differences in disease risk that is evident on current Caribbean reefs.",
"introduction": "INTRODUCTION At low prevalence, disease acts as a natural selective pressure on species and has the capacity to shape species’ evolution and positively affects ecology of an environment over time ( 1 , 2 ). However, infectious disease outbreaks have also been observed to reduce biodiversity at a global scale ( 3 , 4 ), resulting in the sudden extirpation of species ( 5 ), and fundamentally change ecological services and productivity ( 6 – 8 ). Marine ecosystems are experiencing an increase in these disease outbreaks as a result of climate change and globalization ( 9 , 10 ). Marine infectious diseases are unlike terrestrial diseases, as the ocean environment is suitable for diverse microbial growth and promotes transmission through the water, and the pathogens cannot be practically removed or isolated. Therefore, disease outbreaks have become a primary threat to marine ecosystems. By understanding host susceptibility, disease scale, and pathogen virulence, we can learn from these events and work toward understanding the ecology of future marine ecosystems in a changing environment. Coral reefs are ecologically and economically invaluable resources that have experienced gradual community biodiversity loss alongside increasingly frequent and severe disease outbreaks ( 11 – 14 ). Coral diseases are a global threat with increased prevalence and disease outbreaks reported in nearly all major ocean basins including the Caribbean, Red Sea, Indian Ocean, Indo-Pacific, and Great Barrier Reef ( 15 ). Coral reefs provide a unique opportunity to understand the ecology of disease dynamics, including the spatial and temporal scale of disease ( 14 ). An example is the historical tissue loss disease, white plague, which has gripped the Caribbean since the 1970s and is still pervasive, perhaps because of its ability to infect multiple coral hosts ( 16 ). Newly emerging diseases such as stony coral tissue loss disease (SCTLD) are devastating what remains of Caribbean reefs by affecting multiple species, including several species previously considered disease tolerant ( 17 ). Collectively, disease outbreaks are shifting the seascape toward more disease-tolerant coral species, which changes the functionality and ecological services of coral reefs. The rise in infectious diseases emphasizes coral immunity and other disease tolerance and resistance mechanisms as an increasingly selective force in ecology. Although our understanding of immunity has increased, especially in naturally infected corals and those exposed to immune stimulators and bacteria within laboratory studies, we currently lack a sufficient understanding of how immune defenses and other cellular mechanisms vary among species. There is an urgent need to understand the difference between inducible immune responses to an active infection and the constitutive, species-specific resistance mechanisms that prevent some species from developing disease lesions. As in the example of white plague, Montastraea cavernosa , Porites porites , and Porites astreoides are typically more disease resistant, as demonstrated in the field and our previous study, which showed that these same species had significantly reduced relative risk of white plague disease when exposed to diseased corals ( 16 ). These species’ resistance, however, may differ after exposure to other marine diseases, such as SCTLD, indicating that different diseases stimulate different host responses, including the host immune system ( 17 ). Previous studies on coral disease and immunity have successfully identified genes induced by disease that contribute to biological processes such as apoptosis, autophagy, extracellular matrix maintenance, lipid metabolism, and protein trafficking ( 18 – 22 ). However, comparing immune responses between coral species that differ in disease resistance or susceptibility, linking specific disease phenotypes to gene expression, and determining adaptive or plastic disease resistance–associated expression patterns are understudied. By leveraging the outcome of the experimental exposure of seven coral species to white plague disease, we can identify lineage-specific expression adaptation and highly plastic genes that are linked to tangible disease phenotypes associated with coral species that are disease resistant or susceptible.",
"discussion": "DISCUSSION Marine diseases are increasing in scale and severity and have the capacity to reshape ecosystems ( 6 , 14 , 16 , 17 ). By examining how disease affects coral species, we can understand the gene expression patterns that contribute to disease resistance or susceptibility and predict how disease will affect the survival and subsequent ecological contributions of a population in a changing environment. By exposing seven coral species of diverse disease susceptibility to white plague disease, the present study links lineage-specific expression-level adaptation and plasticity patterns to tangible disease phenotypes: lesion progression rate, relative risk of disease incidence, and treatment outcome. Through a combination of identifying genes with differential expression in response to disease exposure (DEGs), association with lesion progression (WGCNA), and distinction between phylogenetically and white plague exposure–mediated gene expression (EVE), we can begin to weigh the gene expression patterns that consistently lead to either survival or lesion development during disease exposure. Our study illustrates three consistent patterns. First, in corals that developed disease lesions, immunity and cytoskeletal arrangement processes were enriched and correlated to lesion progression rate. Second, whether a coral developed lesions was mediated by plasticity in genes involved in extracellular matrix maintenance, autophagy, and apoptosis. Third, resistant species had higher levels of intracellular protein trafficking, and these processes have a lineage-specific adaptive basis to disease resistance. Together, these patterns demonstrate that the plasticity of genes that are associated with disease resistance may be evolutionarily constrained by expression-level adaptation processes. Lesion progression is mediated by immune signaling, cytoskeletal, and protein modification Genes involved in the coral innate immune system were highly correlated with lesion progression rate. Coral fragments across the five species that developed lesions and had measurable lesion progression rates had higher positively correlated enrichment of immunity-associated biological processes, driven by classical immune signaling proteins, including B cell lymphoma 3 protein, tumor necrosis factor receptor–associated factor 2 (TRAF2), NACHT, LRR, and PYD domain–containing protein 3 (NLRP3), and TLR6. These proteins form core components of the coral innate immune system, which functions to detect pathogens and initiates immune responses ( 42 ). The correlation of these immune proteins with lesion progression rate indicates that as the disease progresses through coral tissue, there is activation of the immune system when the coral tissue is trying to fight infection. Genes that were negatively correlated with lesion progression rate demonstrate a pattern of damage mitigation and slow the spread of the disease lesion. Slower lesion progression rates were mediated by genes that function in cytoskeletal organization and protein modification including cytoplasmic dynein 1 heavy chain 1 (DYNC1H1), proteasome subunit α type-7, B cell receptor–associated protein 31, serine/threonine-protein kinase mTOR (MTOR), and cathepsin B. While not considered a classical component of innate immunity, the regulation of cell structures including the cytoskeleton is an important process that promotes the cell’s ability to respond and slow the progression of disease by mediating vesicle-organelle transport, extracellular matrix interactions, and cell adhesion and motility ( 43 – 45 ). These genes that comprise the glandular and secretory type cells, which we are now showing in this experimental work, are critical at preventing lesions from killing the organism ( 22 ). It also expands the scope of what is important and contributes to slowing the lesion progression. Some elements of NF-κB–inducing kinase activity, namely, TRAF2 and MALT1, were both positively and negatively correlated to lesion progression rates, indicating the importance of these pathways in the response to active lesions. Apoptosis has been identified as a key process used by coral to mitigate infection, but because apoptosis is irreversible, it must be controlled and mediated by the cell. Control of apoptosis has been shown to differentiate disease susceptible and resistant corals ( 18 ). TRAF2 itself may set a threshold for apoptosis and act to ubiquinate caspases ( 46 , 47 ). The multiple roles for TRAF2 specifically may contribute to the sensitivity of a coral species to regulate apoptosis and fight lesions in a way that slows lesion progression or contributes to lesion advancement. Processes associated with lesion progression rate were overwhelmingly associated with signaling the immune system, rather than downstream classical immune effectors such as antimicrobial peptides, reactive oxygen molecules, and antioxidant activities ( 48 ). These immune effectors are often posttranslationally regulated proteins that would not appear in transcriptomic datasets, or alternatively, the sampling location near the lesion or timing was not resolved enough to observe them ( 49 ). Despite this, our study shows that canonical immune signaling is involved when a disease lesion is spreading on a coral primarily in susceptible species. These same pathways were not significantly associated with lesion progression in species that had slower lesion progression rates and were more disease resistant, such as S. siderea . Plasticity of autophagy, apoptosis, and extracellular matrix genes are associated with disease outcome Gene expression plasticity in cell fate processes including the recovery pathway of autophagy or the terminal pathway of apoptosis are relevant to disease outcomes at the individual level. Namely, genes that contribute to autophagy are more highly expressed in corals fragments that were exposed to white plague but remained healthy, while the expression of genes that contribute to apoptosis is increased in fragments that developed lesions. Previous work has supported that this axis of cell fate is regulated differently in disease-resistant versus disease-susceptible corals ( 18 , 50 ). Our current work shows that this is significant within species that show variability based on disease outcome. Specifically, up-regulation of lysosomal genes that promote autophagy was consistent within corals across all species that were exposed to white plague but did not develop disease lesions. Guanosine 3′,5′-monophosphate–adenosine 5′-monophosphate synthase, which activates autophagy, was also up-regulated in these disease-resistant individuals. Further autophagic activity is presented by reactive oxygen species metabolism (protein FAM72A), protein unfolding (γ-interferon–inducible lysosomal thiol reductase), and protein degradation genes [cathepsin L, low-density lipoprotein receptor-related protein 2 (LRP2)–binding proteins, and glycosyl hydrolase ecdE]. The expression of these genes was lower in the coral fragments among all species that developed disease lesions. Conversely, genes associated with apoptosis including caspase recruitment domain 15 [nucleotide-binding oligomerization domain-containing protein 2 (NOD2)], interferon development regulator 1, allene oxide synthase-lipoxygenase, and the proteasome subunit α 4 demonstrate higher expression in fragments that developed lesions than those that remained healthy. Interferons (IFIH1) may also play a role in cytoplasmic detection of viruses and signal downstream type I interferons and proinflammatory cytokines and act as an immune regulator. Allene oxide converts arachidonic acid into oxygenated eicosanoids that act as mediators in cell stress and inflammation and results from lipid metabolic shifts ( 51 , 52 ). These metabolic shifts to digest lipids have been observed during disease and bleaching, while apparently healthy coral tend to reduce lipid digestion in exchange for lipid storage ( 23 , 53 – 56 ). Excessive levels of immune activation and inflammation can lead to apoptosis, which is further supported through the increased expression of caspase recruitment domains in disease-infected coral ( 18 ). Caspases are the effector proteins of apoptosis that are initiated through interactions with the caspase recruitment domain–containing proteins ( 57 , 58 ). All of these genes that contribute to apoptosis represent patterns of highly plastic expression that indicate that immune activation and inflammation could culminate in apoptosis for coral infected with white plague disease as seen in Acropora white syndrome ( 59 ). Overall, we demonstrate that the genes involved in the autophagy-apoptosis axis ( 18 , 50 ) show an inducible and plastic response that consistently defines resistance or lesion development across these seven diverse coral species. This advances our knowledge of cell fate decisions as a key modulator of how corals fight disease. Disease resistance was also characterized by the induced expression of genes associated with extracellular matrix stability. Corals exposed to disease but did not develop lesions consistently down-regulated degradation of the extracellular matrix through a metalloproteinase (ADAMTS), while those coral that developed lesions down-regulated extracellular matrix–stabilizing genes (α l -fucosidase and FAM92A). Degradation proteins of the extracellular matrix are frequently up-regulated in disease-infected coral, such as astacin and gelatinase ( 19 ). Pathogens such as Vibrio corralliilyticus have been shown to significantly up-regulate zinc metalloproteinases to better infect coral hosts within minutes of detecting stressed coral mucus ( 60 ). The coral mucus layer is a first-line barrier defense held together by the extracellular matrix that is integral for preventing pathogen penetration and directing immune responses such as cytokine activity and wound healing ( 61 , 62 ). The coral mucus layer also serves the maintenance of beneficial coral-associated microbial communities ( 63 ) and as a means to discriminate beneficial microorganisms from pathogens ( 64 ). In our previous study, we demonstrate that white plague–resistant species such as M. cavernosa and Porites spp. show a tolerance for microbial change ( 16 ), and now, we show that these species also induced plastic expression of extracellular matrix–stabilizing genes. This furthers our understanding of how host-microbiome associations can contribute to host resistance. Extracellular matrix stability through possible mechanisms of collagen α chain, protocadherin, and hemicentin has been associated with disease-resistant individuals ( 20 , 43 ). Deleted in malignant brain tumors 1 (DMBT)-1 is a putative mucosal immunity gene involved in coral microbial pattern recognition and signaling processes suspected to maintain mucosal immunity and microbial homeostasis ( 65 – 67 ). DMBT-1 was significantly up-regulated in disease-resistant M. cavernosa but significantly down-regulated in disease-susceptible O. annularis , further demonstrating the relevance in extracellular matrix maintenance as a plastic expression associated with disease susceptibility across species. Processes like extracellular matrix stability are proving to be very important in not only the disease response but also resistance to disease, demonstrating the valuable contributions of other aspects of coral physiology that complement or bolster the classic immune response. Protein trafficking delineates disease resistance among species Constitutive lineage-specific expression patterns were dominated by genes that contribute to intracellular protein trafficking, suggesting these genes are candidates for disease adaptation. Genes responsible for protein and vesicular transport had, on average, higher constitutive expression in resistant species such as M. cavernosa , P. astreoides , and P. porites than in species with intermediate ( C. natans and S. siderea ) or high risk ( O. faveolata and O. annularis ) of contracting white plague. Protein trafficking is critical for mediating immune processes ( 68 ) such as the transport of immune vesicles, antimicrobials, or sequestration of damaged organelles ( 69 , 70 ) and expressed higher in resistant species in this study. Namely, genes that contribute to cytoplasmic scaffolding [Iron-sulfur cluster assembly enzyme (ISCU)], cytoplasm to mitochondria transporters [phosphate carrier protein solute carrier family 25 member 3 (SLC25A3)], cytoskeletal motility (DYNC1H1), exocytosis (Ras-related protein Rab-3), and protein folding stability (AN1 zinc finger) were more highly constitutively expressed in the resistant species. Protein trafficking has demonstrated significant differential expression in response to several cellular dysfunctions such as coral disease and bleaching ( 45 , 71 , 72 ). Recent single-cell gene expression work in Stylophora pistillata shows that coral immune cells have up-regulated expression of vesicular trafficking, protein stability, and lysosomal genes, supporting that these processes go hand in hand ( 22 ). Our study shows that protein turnover and trafficking are expressed in a lineage-specific pattern that prevents corals from getting white plague disease. Our data show consistent patterns that up-regulated protein trafficking pathways are associated with survival. This increased vesicular transport and protein trafficking in disease-resistant species such as Porites spp., and M. cavernosa may indicate better preparation to respond and fight off potential infections before lesion development occurs through inflammatory or apoptotic events. The lower expression of genes that contribute to protein trafficking in susceptible species suggests that there is an adaptive constraint that limits the susceptible species’ ability to mitigate a changing environment while demonstrating a process that allows resistant corals to tolerate change. These lineage-specific expression-level disease adaptation candidates also relate to the apoptosis-autophagy axis as autophagy requires the sequestration and transport of damaged cellular components to lysosomes for turnover. A key regulator of intracellular transport that initiates autophagy and exocytosis is Ras-related protein Rab 3 ( 73 , 74 ). This protein facilitates autophagy-related vesicle transport and is also a regulator of intracellular protein transport, which is more highly constitutively expressed in resistant coral that demonstrates why autophagy, rather than apoptosis, is successfully used in resistant coral. These resistant species have higher lineage-specific adaptive expression of the protein transport mechanisms that support this autophagic protein recycling pathway. In conclusion, this study provides a novel framework to identify broad coral disease resistance traits. By leveraging a disease transmission experiment with seven coral species, we weigh the variable immune strategies that consistently lead to either a susceptible or resistant disease-exposure outcome that is both considerate and independent of phylogeny. The integration of disease phenotypes (disease outcome, lesion progression rate, and relative risk) into our analyses also identified processes directly involved in lesion development and progression. Considering these phenotypes, phylogeny, and gene expression broadens our understanding of processes that are relevant in mediating the holobiont’s innate immune system across coral species ( 16 ). Faster lesion progression is widely dominated by immune signaling, while lesion arrest is promoted by the coral’s modification of cytoskeletal arrangement and ability to traffic vesicles and organelles. Maintaining coral health when exposed to disease is also associated with intracellular protein trafficking mechanisms to fulfill prosurvival autophagic processes over apoptotic ones. These analyses offer insight into the evolutionary constraints of species to mitigate disease and present predictive gene-level markers and broader biological processes consistent across coral species that will shape coral reef populations in this changing environment."
} | 5,403 |
30073049 | PMC6065350 | pmc | 3,161 | {
"abstract": "Abstract A major quest in network and community ecology has been centered on understanding the importance of structural patterns in species interaction networks—the synthesis of who interacts with whom in a given location and time. In the past decades, much effort has been devoted to infer the importance of a particular structure by its capacity to tolerate an external perturbation on its structure or dynamics. Here, we demonstrate that such a perspective leads to inconsistent conclusions. That is, the importance of a network structure changes as a function of the external perturbations acting on a community at any given point in time. Thus, we discuss a research agenda to investigate the relative importance of the structure of ecological networks under an environment‐dependent framework. We hypothesize that only by studying systematically the link between network structure and community dynamics under an environment‐dependent framework, we can uncover the limits at which communities can tolerate environmental changes.",
"conclusion": "3 INCONSISTENT CONCLUSIONS ABOUT THE IMPORTANCE OF NETWORK STRUCTURE To illustrate how naive simulations of external perturbations can lead to inconsistent conclusions about links between network structure and community persistence, we follow a structural stability approach (Rohr et al., 2014 ; Thom, 1972 ). This approach is particularly useful for our purposes as it allows us to focus on how the qualitative behavior of a dynamical system changes as a function of the parameters of the system itself. For example, the dynamics of the system can be approximated by a population dynamics model (Case, 2000 ). Then, the qualitative behavior of this dynamical system can be translated into a given measure of community persistence. Thus, one can investigate the extent to which different interaction networks can tolerate external perturbations (changes in parameter values) without pushing species toward extinction. This approach can also be graphically represented (see Figure 1 ). For example, for a two‐species community, the axes of Figure 1 represent the 2‐dimensional parameter space of species vital rates. The colored regions correspond to the set of those vital rates compatible with positive species abundances (the necessary condition for community persistence). The size and shape of this region depend upon network structure (Cenci, Montero‐Castaño & Saavedra, 2018 ). This region is typically called the feasibility domain of a community (Logofet, 1993 ; Rohr et al., 2014 ). The open and colored symbols represent some initial and final parameter values (after a hypothetical external perturbation), respectively. Rows correspond to the same external perturbation under two different network structures (the reader can think of any type of structures). Columns correspond to the same network structure under two different external perturbations. Note that positive species abundances will be satisfied as long as the parameter values fall inside the feasibility domain. If we were to focus on the first row only, we would conclude that Structure 1 is more robust that Structure 2. However, if we were to focus on the second row, then we would conclude the opposite. Similarly, if we were to focus on each column separately, we would arrive to contrasting conclusions. Moreover, these inconsistent conclusions can be repeated by moving the perturbation (parameter values) to almost any other direction. That is, there is no conceptual support to think of either a positive or negative association exclusively, especially not by focusing on a single type of perturbation. Figure 1 Linking external perturbations, network structures, and community persistence. The blue region represents the feasibility domain (parameter space compatible with community persistence) of a population dynamics model. The orange and red circles represent a vector of species intrinsic growth rates r → = [ r 1 , r 2 ] before and after a hypothetical perturbation, respectively. The necessary condition for community persistence is to have a vector of intrinsic growth rates within the feasibility domain (as we show on the top‐left and bottom‐right panels). The cartoon shows that not only the structure of an interaction network is important for community persistence, but also the direction of the perturbation. In fact, just by changing the direction of the perturbation, one may not observe community persistence under the same network structures (as we show on the top‐right and bottom‐left panels). That is, structure per se says little about community persistence if not seen in the light of its local environment More systematically, let us take the classic Lotka‐Volterra (LV) dynamics N → ˙ = N → ( r → − A N → ) as a toy model. These dynamics are useful as one can directly associate the structure of the feasibility domain with the network structure (Saavedra, Rohr, Gilarranz, & Bascompte, 2014 ). However, note that results of our discussion extend to a larger class of population dynamics models with nonlinear functional responses (Cenci & Saavedra, 2018 ). In the LV model, the abundances of species are represented by the n ‐dimensional vector N → , where n corresponds to the community size. The temporal evolution of species abundances N → ˙ is a function of the abundances at any given point in time N → , the vector of intrinsic growth rates (vital rates) of species r → , and the interaction matrix A (Case, 2000 ). Note that the interaction matrix is a quantitative description of the interaction network, while the values of intrinsic growth rates are inherently linked to environmental conditions (Cadotte & Tucker, 2017 ; Coulson et al., 2017 ; Levins, 1968 ). If we take our measure of community persistence as that in which there are no extinctions at equilibrium (i.e., N → ∗ = A − 1 r → > 0 ), then we can see that this condition will be satisfied as long as the vector of intrinsic growth rates r → falls inside a feasibility domain constrained by the interaction matrix A (Rohr et al., 2014 ; Saavedra et al., 2017 ). Formally, this domain is defined by D F ( A ) = r → = N 1 ∗ v → 1 + ⋯ + N S ∗ v → S , with N 1 ∗ > 0 , ⋯ , N n ∗ > 0 , where v → i are the i th columns of the interaction matrix A . To quantitatively illustrate the inconsistent conclusions about the importance of the structure of interaction networks through their tolerance to external perturbations, we test the association of community persistence with modular and nested structures under LV dynamics. Yet, we need to stress that our approach can be applied to any combination of structures, perturbations, and models. We measure community persistence as the capacity of a particular structure to avoid extinctions. We build interaction networks on communities of 21 species (this number allows us to easily divide the network into modules, but different dimensions generate the same qualitative results). Interactions are distributed among the species so that there is a clear distinction between the two types of structures analyzed (see Figure 2 for a graphical representation). For comparison purposes, the elements of the interaction matrix A are taken from a normal distribution with parameters chosen such that the resulting interaction matrices for each structure have same mean and standard deviation. In the absence of an interaction between two species, the corresponding entry in the interaction matrix is zero. Communities (each with a different type of structure) are initialized inside the feasibility region by fixing a lognormal distribution of species abundances N ∗ → (Begon, Townsend & Harper, 2009 ), and then finding the corresponding vectors of intrinsic growth rates, that is, r → = A N → ∗ (Rohr et al., 2016 ). Once the communities (with the different structures) are initialized with all species present ( N → ∗ > 0 ), we introduce random and directional perturbations on either the interaction matrix or the vector of intrinsic growth rates. While random perturbations act on all the elements of the interaction matrix or the vector of intrinsic growth rates, directional perturbations act on one single column or element. These changes are equivalent to random and targeted perturbations either on the interactions or nodes of a network (Saavedra et al., 2013 , 2014 ). After the perturbations, we compute the new equilibrium solution with the changed parameters. Then, we record which community (network structure) avoids extinctions. We repeat this process 5,000 times. Figure 2 Inconsistent conclusions about the importance of network structures. As an example, we show the response of two different network structures (a modular and a nested structure) to different external perturbations (see text for details on the simulations performed using a Lotka‐Volterra competition model). All communities are initialized inside the feasibility domain having the same species abundance distribution (see text for details). The y ‐axis corresponds to the number of times (out of 5,000) that the community tolerated a perturbation (i.e., no species goes extinct). That is, the large the bar, the more tolerant the network structure. Panel (a) corresponds to random perturbations on species interactions. Panel (b) corresponds to random perturbations on species intrinsic growth rates. Panels (c) and (d) correspond to directional perturbations on species interactions. That is, only the values of one column of the interaction matrix are changed in each case. Finally, Panels (e) and (f) correspond to directional perturbations on species intrinsic growth rates. That is, only one growth rate of one species is changed in each case Figure 2 shows the estimated community persistence (number of times a given structure avoids extinctions) derived for each combination of structure and perturbation. The first row corresponds to the community persistence under random perturbations acting on either the interaction matrix (Panel a) or the vector of intrinsic growth rates (Panel b). The second row corresponds to the community persistence under directional perturbations acting on either the interaction matrix or on the vector of intrinsic growth rates of the most and least connected species. In the same line as in Figure 1 , if we were to focus on the first row only, we would conclude that modular and nested structures are more robust under perturbations acting on the interaction matrix and intrinsic growth rates, respectively. However, if we were to focus on the second row, then we would conclude the opposite (Panels c and f), or simply that there is no difference between the structures (Panels d and e). Similarly, if we were to focus on each network structure separately, we would arrive to contrasting conclusions as a function of the perturbations. Note that these inconsistencies are not exclusive to the perturbations here analyzed. Overall, these simple conceptual and quantitative analyses demonstrate that the association of a given network structure with community persistence completely depends on the type, direction, and magnitude of perturbations.",
"introduction": "1 INTRODUCTION Since the beginnings of modern network theory (Newman, 2003 , 2010 ), studies have assessed the importance of particular network structures (e.g., exponential or scale‐free networks) by their capacity to tolerate an external perturbation acting on their structure or dynamics (e.g., a random or targeted sequential removal of nodes, Albert, Jeong, & Barabási, 2000 ). This has paved the way for a similar research agenda in network and community ecology (Bascompte & Jordano, 2013 ; Pascual & Dunne, 2005 ). In particular, theoretical studies have been investigating this importance by quantifying the effects of network structure on community persistence (Montoya, Pimm, & Solé, 2006 ). To capture these effects, a typical approach has been centered on randomly removing species (removing interactions or sampling randomly model parameters) and comparing the extent to which different network structures avoid additional species extinctions. This tolerance has then been taken as evidence for a structure's advantage, disadvantage, or lack of any importance over other structural patterns (James, Pitchford, & Plank, 2013 ; Sales‐Pardo, 2017 ). However, the large number of degrees of freedom involved in these analyses (e.g., parameter values and choice of perturbation) has been a central limitation. In fact, it is unclear the extent to which such conclusions can be generalized (Grilli, Rogers, & Allesina, 2016 ; Saavedra, Rohr, Dakos, & Bascompte, 2013 ). Therefore, the question has become whether it is possible at all to infer the importance of a network structure through its capacity to tolerate external perturbations (Rohr, Saavedra, & Bascompte, 2014 ). In this manuscript, we use a simple example to demonstrate that the tolerance to external perturbations of different network structures under the same dynamics can quickly change as a function of the type, direction, and magnitude of the perturbations. That is, the importance of a network structure depends on the external perturbations faced by a community at any given point in time (Cadotte & Tucker, 2017 ; Coulson et al., 2017 ; Song, Rohr, & Saavedra, 2017 ). Thus, if studies focus on a specific set of external perturbations in order to infer the general importance of a network structure, it would lead to inconsistent conclusions. This implies that the importance of a given network structure in a community should always be understood in relation to local environmental settings. In this line, we propose and discuss a research agenda to investigate the relative importance of the structure of ecological networks under an environment‐dependent framework. We strongly believe that this new synthesis can move the field of ecology toward a more systematic and predictive science (Petchey et al., 2015 )."
} | 3,499 |
28833661 | null | s2 | 3,162 | {
"abstract": "Marine mussels use catechol-rich interfacial mussel foot proteins (mfps) as primers that attach to mineral surfaces via hydrogen, metal coordination, electrostatic, ionic, or hydrophobic bonds, creating a secondary surface that promotes bonding to the bulk mfps. Inspired by this biological adhesive primer, it is shown that a ≈1 nm thick catecholic single-molecule priming layer increases the adhesion strength of crosslinked polymethacrylate resin on mineral surfaces by up to an order of magnitude when compared with conventional primers such as noncatecholic silane- and phosphate-based grafts. Molecular dynamics simulations confirm that catechol groups anchor to a variety of mineral surfaces and shed light on the binding mode of each molecule. Here, a ≈50% toughness enhancement is achieved in a stiff load-bearing polymer network, demonstrating the utility of mussel-inspired bonding for processing a wide range of polymeric interfaces, including structural, load-bearing materials."
} | 247 |
33219310 | PMC7679399 | pmc | 3,163 | {
"abstract": "In a globalized world, plant invasions are common challenges for native ecosystems. Although a considerable number of invasive plants form arbuscular mycorrhizae, interactions between arbuscular mycorrhizal (AM) fungi and invasive and native plants are not well understood. In this study, we conducted a greenhouse experiment examining how AM fungi affect interactions of co-occurring plant species in the family Asteracea, invasive Echinops sphaerocephalus and native forb of central Europe Inula conyzae . The effects of initial soil disturbance, including the effect of intact or disturbed arbuscular mycorrhizal networks (CMNs), were examined. AM fungi supported the success of invasive E. sphaerocephalus in competition with native I. conyzae , regardless of the initial disturbance of CMNs. The presence of invasive E. sphaerocephalus decreased mycorrhizal colonization in I. conyzae , with a concomitant loss in mycorrhizal benefits. Our results confirm AM fungi represent one important mechanism of plant invasion for E. sphaerocephalus in semi-natural European grasslands.",
"conclusion": "Conclusions In our current study, we focused on competition of important invasive species from the family Asteraceae in central Europe with a co-occurring native forb, both are abundant in invaded semi-natural plant communities. Among the economically and ecologically important mycotrophic invasive plants in Central Europe, the Asteraceae family is the most abundant. Additionally, we selected species from one family (Asteraceae), as domestic plants of the same family typically bring the least bias. The effects of AM fungi on invasive plant growth and P status recorded in our study indicate that AM fungi can play an important role in invasive plant competitive success. However, decreases in abundance of AM fungi followed by decreases in mycorrhizal benefits in I. conyzae growing in competition with invasive E. sphaerocephalus do not support the ‘ enhanced mutualist hypothesis ’ but instead point to the ‘degraded mutualism hypothesis’. Ecosystems containing nonnative invasive plant species are common, but mechanisms promoting their co-occurrence are not well understood. It may become increasingly important to study the widespread effects of AM fungi on nonnative plant invasibility and establishment as these fungi affect plant species coexistence and community composition 64 – 66 . Understanding the mechanisms leading to successful invasion may be especially important in light of global alterations such as increases in invasive plant species, but also climate change, alterations in nutrient availability, and land use changes. This is the first study to directly assess the role of AM fungi in the competition of E. sphaerocephalus with a native plant. Our experiment was limited to pair-wise interactions among plant species, and this is a critical first step in resolving complex interactions that occur among native and nonnative plant species in a community. The next step will include assessments of additional invasive-native plant pairs to allow generalization of the results to a broader range of plant taxa, with an ultimate goal of assessing AM fungi in field studies.",
"introduction": "Introduction Arbuscular mycorrhizal (AM) fungi (subphylum Glomeromycotina; 1 are a key functional group of soil biota. AM fungi are obligate symbionts of a large majority of land plant species 2 , 3 , including some of the most harmful invasive species. AM fungi supply host plants with nutrients (especially phosphorus [P]) 4 and water 5 from the soil, aid in plant pathogen protection 6 , 7 and increase tolerance to drought and osmotic stresses 8 – 10 in exchange for carbon [C] from the host plant 11 , 12 .\n AM mycelium often interconnects two or more plant individuals of the same or different species, establishing arbuscular (common) mycorrhizal networks (CMNs; 13 . These CMNs play an important role in the long-distance transport of nutrients through soil ecosystems and redistributing symbiotic benefits and costs within a plant community 14 . Therefore, CMNs affect the survival, fitness, and competitiveness of their hosts, regulate plant coexistence 15 – 20 , and maintain plant community diversity 21 and, therefore, ecosystem stability. Importantly, host plants have been shown to disproportionately distribute C among fungal partners according to fungal benefits (e.g., nutrient supply rates) 14 , 22 , 23 . Similarly, CMNs may distribute nutrients among plant partners according to their C supply 4 , 24 . The partitioning of mineral nutrients acquired via CMNs among neighboring plants and the associated C costs are likely to influence both plant competition and facilitation 19 , 20 . AM fungi are, however, sensitive to perturbations that act at the ecosystem level, such as agricultural management practices, pollution (e.g., heavy metals), or plant invasion 25 . Tillage, or local distrbances, significantly impact symbiotic functioning of mycorrhiza by disrupting CMNs 26 . The subsequent reestablishment of CMNs comes at a cost for both fungi and host plants. Plant invasions are a global phenomenon 27 and invasive plants are a major threat to local biodiversity, community composition, and ecosystem processes worldwide 28 – 30 . To understand the mechanisms of invasion success of exotic plants is essential to alleviate damage caused by plant invasions. Different mechanisms of plant invasion have been postulated and most involve altered biotic interactions 31 – 33 , with release from natural enemies being a prominent explanation for invasive success 34 . However, as invasions are context-dependent processes, other factors such as propagule pressure, climate, time of introduction 35 , or disturbance 36 also play a role. The majority of studies describing underlying mechanisms for successful invasion have focused on above- rather than belowground processes, however accumulating evidence suggests soil organisms may be important regulators of plant invasions 37 – 40 . Although many invasive plants are mycotrophic (~ 82% 41 , and fungal associations have been shown to both facilitate and hinder invasion success 42 – 50 , the role of AM mycelial networks in the invasion process has not been determined. Further, information on the role of mycorrhizae on invasive plant success is available for only a small number of plant species at this time. Two main hypotheses have been proposed to explain the role of mycorrhizal fungi in plant invasions, both of which are based on the invasive plants interacting differently with AM fungi relative to native plants: (i) the ‘ degraded mutualism hypothesis ’ 51 and (ii) the ‘ enhanced mutualist hypothesis ’ 52 . The degraded mutualism hypothesis indicates invasive plants either do not form AM (e.g., Brassicaceae or Proteaceae), or are poorly colonized with low dependency on AM fungi in its new range, thereby suppressing AM fungal abundance. By doing so, invasive plants strongly affect mycorrhizal symbiosis of native mycorrhizal plants, often reducing native plant competitiveness 46 , 53 . (ii) The ‘ enhanced mutualist hypothesis ’ 52 indicates invasive plants receive greater benefit from the symbiosis than native plants, altering native AM fungal communities and increasing invasive species competitiveness 50 , 52 , 54 , 55 . Therefore, invasive plants in their new range may parasitize local CMNs, deriving disproportionally large benefits compared to their symbiotic costs at the expense of competing native plants. CMNs have been shown to preferentially transfer mineral nutrients ( 15 N and P) to an invasive plant, with less transferred to the native species 56 . CMNs mediation of invasive and native plants may be crucial to the understanding of invasion success or naturalization of an invasive plant and concomitant ‘spread ’ : these aspects of invasion have not currently been widely studied. Because it has been shown that the majority of invasive plants are mycotrophic 41 , 57 , 58 and able to establish mycorrhizal associations in the secondary range 49 , our current study will focus on the ‘ enhanced mutualism hypothesis’ . We selected mycorrhizal plant species Echinops sphaerocephalus commonly invasive to central Europe and conducted a coexistence (intercropping) experiment to determine if feedbacks between AM fungi, invasive plant species, and native plant species ( Inula conyzae ) play a role in successful invasions by the non-native (Fig. 1 ). We hypothesized that (i) presence of AM fungi enhances success of a mycotrophic invader in competition with a domestic plant—AM fungi preferentially support plant growth and nutrition of the invasive plant, with a concomitant reduction in native plant growth and nutrition, (ii) competitive advantage of the mycotrophic invader provided by AM fungi is in initial growth phases more pronounced in non-disturbed than in disturbed environments, where (compared to non-disturbed environment) it increases with time. Figure 1 Experimental design. This design was used for both harvests. Both mycorrhizal (M+) and nonmycorrhizal (M−) pots were pre-planted with a nurse plant Festuca pratensis . Soil was disturbed or left intact before target plants were planted, resulting in disturbed or non-disturbed arbuscular mycorrhizal (AM) networks in M+ treatment. Each figured pot contained 5 replicates.",
"discussion": "Discussion In agreement with our hypothesis which predicted AM fungi help facilitate the success of a mycotrophic invasive plant in competition with a domestic plant, our study shows that there were negative effects of AM fungi on proportional total biomass and P content of native I. conyzae . Our results indicate that the presence of AM fungi enhanced the competitive ability of invasive E. sphaerocephalus against native I. conyzae . This is in agreement with Callaway et al. 59 , and Workman and Cruzan 60 who reported positive effects of AM fungi on biomass production of invasive Centaurea melitensis and Brachypodium sylvaticum , respectively, growing in competition with native plants. Contrary to our second hypothesis, the difference between the M+ and M− treatments was more pronounced in plants grown in experimentally disturbed soil. In fact, the positive effect of AM fungi abolished negative effects of disturbance on the invasive E. sphaerocephalus . This hypothesis was based on our assumption that competitive advantages of invasive plant would originate from linking with existing CMNs and disproportionally profit, at the expense of competing native plants, with the strongest advantage observed in invasive plants grown in pots with non-disturbed CMNs. However, this was not supported by our data, as the invader was competitively more proficient with mycorrhizal inoculation in both initially disturbed and non-disturbed treatments. Although we cannot confirm or reject existence of CMNs directly, molecular analyses indicated that both the invasive and native plants generally shared the same AM fungal taxa, with F. mosseae being dominant, regardless of native or invasive plant species. The absence of effects of disturbance on abundance of AM fungi supports a rapid recovery of CMNs following disturbance. Therefore, the invasive plant with intact mycelium was not at an advantage over invasive plants with initially disturbed mycelium. The disproportionate distribution of mycorrhizal benefits by CMNs between these invasive and native plants may have played a role in the competitive success of invasive E. sphaerocephalus grown with domestic I. conyzae . However, the competitive advantage of E. sphaerocephalus over I. conyzae is more likely due to lower abundances of AM fungal taxa in roots of I. conyzae , when grown in the presence of invader ( E. sphaerocephalus ), compared to growth without the invasive. Our results are similar to Zhang et al. 61 , where invasive Solidago canadensis inhibited AM fungal root colonization of native species. Callaway et al. 62 found the invasive plant Alliaria petiolata suppressed native AM fungi, resulting in an indirect inhibition of native mycorrhizal plants. The mechanisms of mutualist degradation may be mediated by allelochemical production by invasive plants. Allelopathy likely played a role in the invasion success of non-native Echinops echinatus when grown with native Argemone mexicana 63 . While beyond the scope of our current study, it is possible that allelopathic biochemicals produced by invasive E. sphaerocephalus decreased mycorrhizal colonization in native I. conyzae , thereby reducing mycorrhizal benefits. However, AM fungi continued to be beneficial to E. sphaerocephalus . Therefore, it is likely that the decrease in abundance of AM fungi in the roots of domestic I. conyzae when grown with the invasive plant is a reflection of root turnover, as colonized roots died and were replaced by new root growth not able to form associations with the fungal symbiosis. This was also reflected by reduced biomass production of the native plant when grown with the invasive plant."
} | 3,268 |
26757703 | PMC4710996 | pmc | 3,164 | {
"abstract": "Background Metatranscriptomics is emerging as a powerful technology for the functional characterization of complex microbial communities (microbiomes). Use of unbiased RNA-sequencing can reveal both the taxonomic composition and active biochemical functions of a complex microbial community. However, the lack of established reference genomes, computational tools and pipelines make analysis and interpretation of these datasets challenging. Systematic studies that compare data across microbiomes are needed to demonstrate the ability of such pipelines to deliver biologically meaningful insights on microbiome function. Results Here, we apply a standardized analytical pipeline to perform a comparative analysis of metatranscriptomic data from diverse microbial communities derived from mouse large intestine, cow rumen, kimchi culture, deep-sea thermal vent and permafrost. Sequence similarity searches allowed annotation of 19 to 76 % of putative messenger RNA (mRNA) reads, with the highest frequency in the kimchi dataset due to its relatively low complexity and availability of closely related reference genomes. Metatranscriptomic datasets exhibited distinct taxonomic and functional signatures. From a metabolic perspective, we identified a common core of enzymes involved in amino acid, energy and nucleotide metabolism and also identified microbiome-specific pathways such as phosphonate metabolism (deep sea) and glycan degradation pathways (cow rumen). Integrating taxonomic and functional annotations within a novel visualization framework revealed the contribution of different taxa to metabolic pathways, allowing the identification of taxa that contribute unique functions. Conclusions The application of a single, standard pipeline confirms that the rich taxonomic and functional diversity observed across microbiomes is not simply an artefact of different analysis pipelines but instead reflects distinct environmental influences. At the same time, our findings show how microbiome complexity and availability of reference genomes can impact comprehensive annotation of metatranscriptomes. Consequently, beyond the application of standardized pipelines, additional caution must be taken when interpreting their output and performing downstream, microbiome-specific, analyses. The pipeline used in these analyses along with a tutorial has been made freely available for download from our project website: http://www.compsysbio.org/microbiome . Electronic supplementary material The online version of this article (doi:10.1186/s40168-015-0146-x) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusions In this study, we present a standard bioinformatics pipeline to process, annotate and analyse metatranscriptomic datasets. Applied to five disparate metatranscriptomic datasets (mouse cecum, cow rumen, kimchi, deep sea and permafrost), this pipeline captures both common and microbiome-specific taxonomic and functional signatures. In general, each microbiome is dominated by members of four bacterial phyla ( Firmicutes , Proteobacteria , Bacteroidetes , Actinobacteria ) and one archaeal phylum; however, each microbiome features distinct differences in the relative representation at higher phylogenetic levels (i.e. families and genera). Diversity analyses reveals that mRNA taxonomic representation is broadly congruent with 16S taxonomic representation, with the proviso that a lack of suitable reference genomes can result in mRNA datasets overestimating diversity. Comparisons of microbiome metabolic capacities revealed a core of 592 enzymes common to the four well-sampled microbiomes (i.e. ignoring permafrost), largely associated with housekeeping functions such as carbohydrate, amino acid and nucleotide metabolism. While the concept of ‘core’ bacterial functions have previously been described for individual taxa (e.g. [ 54 ]), this concept has yet to be explored from a metatranscriptomic viewpoint. Such conserved pathways provide a valuable benchmark to assess the quality and coverage of metatranscriptomic datasets. Furthermore, we identified microbiome-specific enzymes reflecting distinct differences in habitat. We choose to compare mouse cecal flush and cecal wall samples to determine whether gene expression is substantially different in the wall-adherent compared to luminal microbiome. Analyses with three established tools identified only a limited set of differentially expressed genes between the cecal wall and cecal flush samples. However, a gene set enrichment approach applying a fold-change metric identified several pathways of differentially expressed genes at these two locations suggesting that biogeographical differences require additional study in mammalian gut microbiomes. Finally, integration of phylogenetic and functional annotations within a systems context provides a powerful route to identify the relationship between taxonomic representation within a microbiome and their contribution to biochemical activities; while dominant taxa appear broadly represented across biochemical pathways, key contributions may be performed by a more limited set of less abundant taxa.",
"discussion": "Results and discussion Annotation of metatranscriptomic datasets reflect depth of available reference genomes We applied a systematic pipeline to process sequence data from five metatranscriptomic studies: (1) 30 million 76 bp paired end reads from 12 mouse large intestine samples [ 7 ]; (2) 35 million 101 bp single end reads from a sample of kimchi, obtained on the 29th day of fermentation [ 9 ]; (3) 14 million 100 bp paired end reads from a sample obtained from a bovine rumen [ 8 ]; (4) 103 million 100 bp paired end reads from a deep-sea sample [ 10 ]; and (5) 131 million 150 bp paired end reads from a sample obtained from permafrost (Fig. 1a ). All datasets were generated with Illumina sequencing platforms. After the removal of rRNA/tRNA, low quality, adaptor contaminants and host sequences, from 0.01 % (permafrost) to 19.1 % (kimchi) messenger RNA (mRNA) reads were predicted (Fig. 1b and Additional file 1 ). The permafrost sample was composed of 99.9 % low quality and adaptor reads, likely reflecting the low biomass of this sample. In addition, mouse intestinal content samples (prepared with Invitrogen mirVana kit) displayed higher proportions of reads of host origin (23 and 47 %) relative to other samples (0.3–21 %), reflecting the abundance of epithelial cell shedding in this compartment. In the absence of a complete set of reference genomes to which reads could be effectively mapped, read assembly can help improve annotation. For each dataset, putative mRNA reads were assembled using the Trinity RNA-Seq assembly algorithm [ 20 ] which we previously identified as an optimal short read assembler for metatranscriptomic data, in terms of improving annotation as well as minimizing the incidence of misassemblies [ 11 ]. The deep-sea and kimchi datasets possessed the highest proportion of reads assembled (‘contigs’; 62 and 72 %, respectively). The kimchi dataset featured a contig N50 length of 368 bp, likely reflecting the limited diversity of this microbiome. Fig. 1 Workflow and Read Processing. a Workflow of the pipeline for processing, annotation and analyses of metatranscriptome (RNA-seq). b Composition of sequence reads for twelve mouse metatranscriptome datasets and four additional microbiomes (see Methods ). c Distribution of reads annotated through three complementary sequence similarity search tools: (1) BWA and (2) BLAT searches against a database of 2271 microbial genomes and (3) BLASTX searches against the protein non-redundant database. The mouse dataset represents a summary of all 12 datasets analysed in this study Assembled contigs and unassembled reads, representing putative mRNA sequences, were then parsed through a hierarchical annotation pipeline, with unannotated reads passing to the next annotation step. This analysis included (1) mapping of sequences to a reference set of 4443 prokaryotic genomes using the BWA algorithm that relies on near perfect sequence matches (defined here as no more than two base pair mismatches—see Methods ) [ 13 ]; (2) sequence similarity searches against the same set of reference genomes using a less stringent BLAT algorithm [ 21 ]; and (3) sequence similarity searches against the protein non-redundant database [ 22 ] using BLASTX [ 23 ]. Of the five datasets, the cow rumen samples produced the lowest frequency (19 %) and the kimchi dataset featured the highest frequency (72 %) of mapped reads (Fig. 1c ). This latter result is a consequence of 51 % of putative mRNA reads that were mapped to two reference genomes, Lactobacillus sakei and Weissella koreensis . The high proportion of BLAT mappings compared to BWA results suggests genetic variation from the reference strains. BLAT-based mapping identified 24 % of the deep sea, and 12 % of the permafrost datasets, but mapping of the mouse gut and cow rumen samples reads performed better with the least stringent BLASTX algorithm (Fig. 1c ). These findings highlight the lack of representative reference genomes for these microbiomes, such that many sequence reads map to homologs from distant relatives of the actual species present in the samples. These results are broadly consistent with the original reports of these datasets but also highlight important differences produced by the selected analytical pipelines. For example, the cow rumen study [ 8 ], which relied on BLASTX sequence similarity searches with a score cut-off less than e -5 , reported ~400,000 reads of putative mRNA origin compared to 452,708 reported here. However, we do note some significant discrepancies. The original study of the kimchi microbiome [ 9 ] applied the BWA algorithm to map 3.9 million reads to six reference strains; here, using the BWA/BLAT/BLASTX pipeline, we mapped 4.8 million reads to bacterial mRNA transcripts. For the deep-sea microbiome, the original analysis applied a combination of the Velvet and Oases assembly algorithms to construct 78,000 contigs with an average contig size of 243 bp [ 10 ]. Subsequent sequence similarity searches using the BWA algorithm identified ~81,000 predicted genes, of which only 18,500 were protein coding. In the current study, we identified 643,000 contigs with an N50 of 110 bp with the Trinity assembly. Further, we identified 243,000 unique transcripts by inclusion of 3.0 million reads not assigned to a contig. These differences reflect the often arbitrary choice of parameters and algorithms, usually in the absence of rigorous benchmarking, that can impact coverage and accuracy, and highlight the need for standardized pipelines. Pathway enrichment analysis identifies tissue specific gene expression in the mouse gut microbiome In previous studies of the cow rumen, deep-sea and kimchi microbiomes, gene expression was assessed by direct comparisons of raw or normalized read counts [ 8 – 10 ]. In the absence of standardized statistical models to identify significant changes in gene expression from metatranscriptomic datasets, we evaluated three methods previously employed to detect changes in gene expression: DEseq2 [ 24 ], EdgeR [ 25 ] and ANOVA-like differential expression analysis (ALDEx2—[ 26 ]). We compared microbial expression patterns between three cecal wall-associated (cecal wall) and four cecal lumen flush derived (cecal flush) microbiomes from four NOD strain mice of identical age and sex which had been prepared with the same RNA extraction protocol. Of the 20,160 non-mouse transcripts identified in these samples (11,231 and 11,015 for cecal wall and cecal flush, respectively), 2087 were shared between sample types. Only five transcripts displayed significant differences in expression between the two types of microbiome samples (Additional file 2 ). This reflects the large variation observed across animals and tissue samples as defined by a biological coefficient of variation (BCV) of 1.11, where the BCV is a measure of how the (unknown) true abundance of the gene varies between replicate RNA samples (see Methods ). While the above approaches are useful for identifying individual genes displaying differential expression across samples, additional insights can be gained by considering collections of functionally related genes (e.g. complexes and pathways). We therefore applied a pathway enrichment approach that, due to the limited number of genes identified above, relied on fold change in expression [ 27 , 28 ], to examine expression of metabolic pathways. In this analysis, 551 genes displayed ≥fivefold difference in expression between the two types of samples, with a greater frequency of genes up-regulated in the cecal wall compared to the cecal flush datasets (Additional file 3 ). We identified 199 genes that could be mapped to 72 unique Enzyme Commission (EC) identifiers. Pathway enrichment analysis revealed 17 metabolic pathways to be significantly associated with these genes (hypergeometric test, p value <0.05; Table 1 ). Pathways demonstrating significant differential expression include six involved in carbohydrate metabolism (e.g. the citrate cycle, pyruvate metabolism and glycolysis/gluconeogenesis), four involved in amino acid metabolism and three involved in energy metabolism. Previous studies have shown that changes in the expression of carbohydrate-associated enzymes in the mouse intestinal microbiome were linked to microbial community composition [ 29 , 30 ]. Table 1 Pathways enriched in transcripts displaying large (>fivefold) differences in relative expression between mouse cecal wall and cecal flush samples Fold change in expression Differentially expressed genes Matched ECs/total ECs in pathway Genes up-regulated in cecal wall Genes up-regulated in cecal flush Pathway \n p value 5–10 10–20 >20 5–10 10–20 >20 Glycolysis/gluconeogenesis 9.35E-07 14 5 3 5 4 1 32 11/45 Methane metabolism 6.44E-05 10 5 3 4 5 2 29 11/68 Carbon fixation in photosynthetic organisms 1.00E-04 8 1 2 4 0 0 15 5/25 One carbon pool by folate 2.88E-04 4 3 0 1 2 0 10 6/24 Starch and sucrose metabolism 4.59E-04 5 4 2 3 3 0 17 10/71 Alanine, aspartate and glutamate metabolism 1.43E-03 9 1 0 0 1 0 11 7/43 Citrate cycle (TCA cycle) 1.52E-03 4 0 2 2 1 0 9 5/22 Pyruvate metabolism 3.08E-03 7 0 2 1 1 1 12 8/62 Amino sugar and nucleotide sugar metabolism 6.63E-03 5 3 1 1 3 2 15 9/85 Oxidative phosphorylation 1.10E-02 2 3 1 0 3 0 9 3/12 Purine metabolism 3.08E-03 10 0 0 2 0 2 14 9/100 Propanoate metabolism 3.37E-02 3 0 0 0 1 1 5 5/45 Valine, leucine and isoleucine biosynthesis 3.40E-02 1 1 0 0 1 2 5 3/18 Aminoacyl-tRNA biosynthesis 3.85E-02 2 0 0 1 0 3 6 4/32 Histidine metabolism 4.25E-02 1 3 0 1 0 0 5 4/33 Drug metabolism—other enzymes 4.49E-02 3 0 0 0 0 0 3 3/20 Other glycan degradation 4.88E-02 1 1 0 0 0 0 2 2/9 Short read data reveals microbiome-specific taxonomic signatures In addition to deriving functional insights (see following sections), we were interested in the ability of metatranscriptomic datasets, associated with relatively short reads, to inform on the taxonomic composition of a habitat. Based on mappings of reads of putative mRNA origin to known genes, we explored the taxonomic assignments of reads at three different taxonomic levels (Fig. 2 ). Previous comparisons across the mouse datasets revealed relatively minor taxonomic variations between samples at least at the class/phylum level [ 7 , 11 ]. Here, we identified distinct taxonomic profiles for each microbiome. At the level of phylum, reads from all five samples could be largely defined into four major groups: Firmicutes , Proteobacteria, Bacteroidetes and Actinobacteria (Fig. 2a ). However, while the cow rumen and mouse intestinal samples had significant representation from all four taxa, the kimchi sample was largely restricted to the Firmicute families Leuconostocaceae and Lactobacillaceae, while the deep-sea and permafrost samples lacked significant representation of Bacteriodetes, the former also lacking significant representation of Actinobacteria. Indeed, consistent with a previous study based on 16S rRNA reads [ 10 , 31 ], we found that the majority (51 %) of reads of putative mRNA origin from the deep-sea sample could be classified as Gammaproteobacteria. Interestingly, we also found reads mapping to non-bacterial genes. For example, for the deep-sea dataset, we identified reads mapping to Archaea (0.8 % of reads of putative mRNA origin), fungi (0.6 %) and protozoa (1.5 %). Fig. 2 Taxonomic composition of five metatranscriptomic datasets. a Abundance of 10 major bacterial phyla and sub-phyla across the five samples. Also shown are the observed frequency of assignments in the 2271 microbial genomes used in the BWA and BLAT searches as well as the protein non-redundant database. b Phylogenetic representation of major genera (represented by at least 100 reads) associated with the five datasets. Node size represents the relative abundance of reads mapped to the corresponding genus in each sample. For each dataset, reads were normalized by the average read count associated with each sample (see Methods ). c Top ten most abundant species associated with each dataset (by number of reads; minimum 100 transcripts) Next, we examined the contribution of distinct genera to each microbiome (Fig. 2b ). Within these ‘abundant’ genera, the deep-sea dataset displayed the largest number of unique taxa (13) while the kimchi dataset displayed the fewest (2; Leuconostoc and Weissellla ). Indeed, the kimchi dataset appears dominated by three main taxa. On the other hand, Lactobacillus was well represented across four of the five datasets; although present in the deep-sea dataset, it does not comprise one of the defined, abundant genera in this dataset. We note that Lactobacillus is one of the twelve most abundant genera in our reference datasets (45 genomes) and assignment of a large proportion of reads to this genus may simply reflect that bias, potentially acting as a surrogate taxon for species not represented within our reference datasets. In any event, despite such biases, our pipeline reveals each habitat to possess a unique taxonomic signature with the presence of specific abundant taxa adapted to individual environmental conditions. For example, Weissella is a genus of lactic acid bacteria, first identified in kimchi at 2002, that are regarded as one of the three main genera that are strongly associated with fermentation of kimchi based on both transcriptome or 16S rRNA study [ 9 , 32 , 33 ]. This analysis also shows the value in using a higher level of taxonomic resolution. For example, from Fig. 2a , both the cow rumen and mouse samples reveal the presence of reads from Bacteroidetes; however, deeper analysis reveals such reads to be dominated by Prevotella in the cow rumen sample compared to Bacteroides and Parabacteroides in the mouse samples. Finally, we examined the performance of the hierarchical annotation pipeline to assign reads to discrete species for each sample (Fig. 2c ). To reduce the influence of species with matches involving only a limited number of genes, only species represented by 100 or more transcripts were included in these analyses with the exception of the permafrost sample, the latter due to the low number of putative mRNA reads. The kimchi sample was associated with the simplest community, with 10 species accounting for ~93 % of total reads of putative mRNA origin. These assignments were remarkably consistent with a previous report [ 9 ], with similar abundances for five of the top six most represented taxa. Emphasizing the findings at the genus level, there was no overlap in the ten most abundant species in the mouse and cow datasets despite the phylum/sub-phylum similarities (Fig. 1a ). The mouse microbiome samples were obtained from germ-free animals colonized with altered Schaedler flora (ASF) which were defined, before the advent of high through-put sequence analysis, to contain eight known species [ 34 , 35 ]: Lactobacillus acidophilus, Lactobacillus murinis, Parabacteroides distasonis, Mucispirillum schaedleri , three members of Clostridium cluster XIV and a poorly characterized Firmicute species. Of these previously defined species, only P. diastonis appears significantly represented in our samples. However, previous studies have suggested that Lactobacillus animalis , identified within the samples, is identical to L. murinis [ 34 ], while reads assigned to the poorly classified ‘ Clostridium sp.’ may represent the species associated with Clostridium cluster XIV. The additional species presented in Fig. 2c likely represent close relatives to the remaining unaccounted ASF taxa. Conversely and again consistent with a previous study, amongst the top ten most abundant species represented in the cow dataset were those that have previously been associated with the rumen [ 36 ] including bacteria that degrade cellulose and other carbohydrates ( Prevotella spp . and Fibrobacter spp.) and those that utilize fatty acids ( Succinivibrionaceae spp . and Treponema spp . ) as well as the protozoan Oxytricha trifallax , a relative of Oxytricha granulifera , previously reported to occupy the rumen [ 37 ]. Similarly, the deep-sea dataset was represented by species previously associated with the marine environment [ 10 , 31 ] including Alteromonas macleodi , the ammonia oxidizing archaeon— Candidatus nitrospumilis , methanotrophs ( Methylomonas methanica and Methylomicrobium alcaliphilum ) and the sulphur oxidizing SUP05 [ 38 ]. Across samples, we note a varying proportion (from 7 to 87 % for kimchi and cow rumen datasets, respectively) of reads mapping to ‘Others’. These include reads from species with few transcripts and likely false positives, as well as reads associated with a more diverse community. For example, we note that in the deep-sea dataset, 504 species were represented by 100 or more transcripts, with species represented by 10 or fewer transcripts contributing only 3.9 % of the reads, suggesting a highly diverse microbiome. On the other hand, only 67 species were represented by 100 or more transcripts in the cow rumen dataset, with 45 % of the reads contributed by species with 10 or fewer transcripts, suggesting a higher number of false positive assignments. Beyond resorting to more complex phylogenetic mapping solutions such as the naïve Bayes classifier [ 39 ], more sophisticated approaches to resolving such issues of false positive assignments could include examining BLAST-based sequence similarity matches to taxa beyond the first match reported. For example, one source of false positives is reads that map to highly conserved regions of sequences. Such reads are likely to possess many sequence similarity matches with the same BLAST score cut-offs. Through considering abundant taxa identified through mappings to other reads, it is possible to devise an algorithm that selects the most likely match, from a list of matches sharing the same score. In the next section, we explore these issues further through comparing the performance of 16S- and mRNA-derived reads to assess diversity within and between samples. Consistency of diversity analyses between 16S rRNA and mRNA datasets We assessed species diversity for each sample based on putative mRNA reads and compared them to species representations derived from filtered 16S rRNA reads obtained in our pipeline (see ‘ Methods ’). Four ecological biodiversity indices were employed: three based on diversity measures (Shannon diversity index, Simpson index and Fisher’s alpha) and the Chao1 richness index (Table 2 ). Amongst the diversity indices, the Shannon and Fisher’s alpha are broadly consistent with the exception of the two individual cecal-derived samples, which Fisher’s alpha suggest are less diverse than the Kimchi dataset. Conversely, the Simpson index rates the mouse cecal-flush sample as the most diverse. However, in general, across samples and consistent with the large number of species with broad transcript representation, the deep-sea dataset was found to be the most diverse and rich with the results based on mRNA reads (5.01 and 4408 for Shannon and Chao1 indices, respectively). Conversely, the kimchi dataset was the least diverse and rich, likely due to the dominance of a few taxa (1.69 and 634). Noteworthy, the permafrost dataset appeared the least diverse microbiome based on the Chao1 index but not for any diversity based index. This is likely due to the small number of annotatable reads associated with this dataset. Table 2 Diversity analysis within mice samples and between five samples Sample name Shannon index (mRNA) Simpson index (mRNA) Fisher’s alpha (mRNA) Shannon index (16S rRNA) Chao1 index (mRNA) Chao1 index (16S rRNA) Mouse cecal wall 3.83 16.51 23.26 2.00 1162 283 Mouse cecal flush 4.43 43.34 30.52 2.57 1055 411 Mouse combined 4.51 17.14 167.33 2.48 1709 523 Cow rumen 4.14 21.79 140.67 4.15 1461 1042 Kimchi 1.69 3.27 56.07 2.91 634 615 Deep sea 5.01 35.75 481.29 5.02 4408 4565 Permafrost 3.82 10.98 24.31 4.5 295 348 Comparing between sequence types, we find broad consistency between the results for the 16S rRNA and mRNA based analyses, with the exception of the mouse samples. For the latter datasets, while the 16S rRNA gene analyses yielded lower diversity metrics for the mouse datasets (reflecting the limited number of taxa associated with the altered Schaedler flora (ASF) used to inoculate germ free mice), the mRNA-based analyses yielded comparatively higher diversity metrics. This is likely due to the challenge of mapping the putative mRNA reads in these datasets to their correct taxa in the absence of ASF reference genomes used for mapping. Instead, reads appear to have been assigned to multiple closely related taxa. We note for example that this does not arise for the kimchi dataset for which there is good representation of reference genomes. Although the 16S rRNA- and mRNA-based diversity and richness analyses are largely consistent, excluding the permafrost dataset, we find that from 56 % (kimchi) to 81 % (mouse) of genera identified from 16S rRNA reads overlap with reads of mRNA origin (Additional File 4 ). At the same time, we also note many genera predicted by the mRNA reads compared to the 16S rRNA reads, with the former predicting from 83 % (kimchi) to 478 % (deep sea) additional genera. Such additional predictions likely arises from a combination of the lack of a complete set of reference datasets for both mRNA or 16S rRNA reads, as well as mispredictions from the taxonomic annotation pipeline as noted above. Nevertheless, given the consistency in diversity and richness metrics between sequence types for the cow rumen, kimchi and deep-sea datasets, these results suggest that even short-read data derived from mRNA can reveal significant taxonomic differences that reflect genuine differences in habitat. In the following sections, we show how this information may be leveraged to identify distinct taxonomic contributions towards biochemical activities within a microbiome. Functional interrogation of metatranscriptome datasets reveals a conserved core of essential metabolic functions supplemented with habitat-specific pathways A major challenge in metatranscriptomic studies is determining the depth of sequencing required to adequately capture the functional capacity of a microbiome (i.e. ‘how much sequencing is enough?’). Focusing on metabolism, we performed a rarefaction analysis of enzyme annotations captured by increasing numbers of reads within the five datasets. As expected, all five datasets revealed an asymptotic relationship between number of reads generated and enzymes (as defined by distinct Enzyme Classification (EC) numbers—Fig. 3a ). For the two largest datasets, kimchi and deep sea, we find that for ~4 million putative mRNA reads, the rate of new enzyme discovery is 30 and 45 per million reads, respectively. Given a current expected yield of 20 % reads of putative mRNA origin, our analysis suggests that the generation of ~20 million reads for a microbiome provides a reasonable compromise between sequencing costs and enzyme discovery. However, such decisions should also assess additional factors such as mirobiome complexity; we note that the deep-sea dataset contained the greatest metabolic capacity. Due to the relatively low number of putative mRNA reads (~14,300) suggesting only a limited sampling of its metabolic capacity, the permafrost dataset was excluded from subsequent analyses. Fig. 3 Metabolic composition of five metatranscriptomic datasets. a Rarefaction analysis indicating the number of unique enzymes (as defined by enzyme classification numbers) captured by increasing numbers of putative mRNA reads generated. b Overlap of enzyme complements across four datasets reveals a common core of 592 enzymes. c Global metabolic network indicating taxonomic representation of metabolic activities within the combined mouse dataset. Pie charts indicate the relative proportion of each taxon, size of pie chart indicates relative expression (see key). Indicated are specific metabolic pathways Comparisons across the four datasets revealed a common core of 592 enzymes (Fig. 3b ). These core enzymes were significantly associated (hypergeometric test, p value <0.01) with 22 pathways, as defined by the Kyoto Encylcopedia of Genes and Genomes (KEGG—Table 3 ) [ 40 ]. These pathways represent core metabolic functions including carbohydrate and energy metabolism (7 pathways), amino acid metabolism (5 pathways) and nucleotide metabolism (2 pathways). It is suggested that future studies consider using enzymes involved in these pathways as a benchmark to assess the quality and coverage of their datasets. For example, within the permafrost dataset, of 152 defined enzymes, only 93 (15.8 % of our defined core) are present. These include 5 of 40 (12.5 %) core enzymes associated with nucleotide metabolism, 13 of 84 (15.5 %) core enzymes associated with amino acid metabolism, 10 of 66 (15.2 %) core enzymes associated with carbohydrate metabolism, 22 of 119 (18.5 %) core enzymes associated with multiple pathways and 25 of 146 (17.1 %) core enzymes that were not assigned into a KEGG defined pathway. Hence, it appears that enzymes in core pathways missing in the permafrost dataset are relatively evenly distributed across functional categories, reflective of lower coverage rather than microbiome bias. Table 3 Pathways significantly enriched in ‘core’ microbiome enzymes Pathway name Pathway class a \n \n p value b \n Core enzymes in pathway Total enzymes in pathway Aminoacyl-tRNA biosynthesis O 3.57E-08 22 32 Purine metabolism NT 1.49E-06 44 100 Peptidoglycan biosynthesis G 4.30E-06 12 15 Glycolysis/gluconeogenesis C 2.89E-05 23 45 Alanine, aspartate and glutamate metabolism AA 4.24E-05 22 43 Valine, leucine and isoleucine biosynthesis AA 8.75E-05 12 18 Pyrimidine metabolism NT 2.89E-04 27 63 Phenylalanine, tyrosine and tryptophan biosynthesis AA 6.27E-04 15 29 Pentose phosphate pathway C 7.05E-04 17 35 Carbon fixation pathways in prokaryotes E 2.22E-03 17 38 One carbon pool by folate CO 3.21E-03 12 24 Lysine biosynthesis AA 3.32E-03 13 27 Pyruvate metabolism C 3.37E-03 24 62 Fatty acid biosynthesis L 3.88E-03 9 16 Citrate cycle (TCA cycle) C 4.76E-03 11 22 Amino sugar and nucleotide sugar metabolism C 5.66E-03 30 85 Oxidative phosphorylation E 8.48E-03 7 12 Drug metabolism—other enzymes X 2.34E-02 9 20 Cysteine and methionine metabolism AA 2.55E-02 21 61 Polyketide sugar unit biosynthesis T 2.74E-02 4 6 Streptomycin biosynthesis S 3.48E-02 8 18 Folate biosynthesis CO 3.61E-02 7 15 \n a Defined according to KEGG. AA amino acid, C carbohydrate, CO co-factor, E energy, G glycan, L lipid, NT nucleotode, O other, S secondary metabolites, T terpenoids, X xenobiotics \n b Here, we used the hypergeometric test to examine enrichment of pathways compared to all KEGG defined pathways In addition to the core enzymes, we also identified the unique expression of enzymes providing habitat-specific biochemical functions (Additional files 5 and 6 ). For example, the deep-sea dataset includes enzymes involved in phosphonate metabolism, a significant component of organic phosphorous in the marine environment [ 41 ]. Similarly, the glucosyltransferase, levansucrase (EC: 2.4.1.10), was uniquely associated with the kimchi dataset. Levansucrase is involved in the synthesis of glucose polymers and was previously isolated and characterized from a key member of the kimchi community, Leuconostoc mesenteroides [ 42 ]. Unique to the cow rumen dataset were pectate di- and tri-saccharide lyases, reflecting the presence of pectin in animal feed and thought to be responsible for supporting the growth of Trepnonema sp . [ 43 ]. In the next section, we combine the taxonomic and metabolic annotation data to examine the contributions of specific taxa to biochemical activities in the sampled microbiomes. Integration of taxonomic and functional annotations: I. Metabolic networks While previous microbiome studies have associated shifts in taxonomic distributions and/or biochemical functions with disease states or other evolving habitats, such as the process of fermentation [ 9 , 44 , 45 ], our understanding of the contribution of specific taxa to these functions is limited. In the previous sections, we demonstrated the capacity of short sequence reads associated with metatranscriptomic datasets to provide both taxonomic and functional insights. In the following sections, we show how the integration of such information can be used to derive a more complete understanding of how different taxa contribute towards the biochemical activities of a microbiome. Given the limits of taxonomic resolution identified above, we chose to divide reads into twelve taxonomic categories including archaea and protozoa. From these assignments, we constructed a global metabolic network graph in which nodes, representing enzymes, are linked through shared substrates. Each node is depicted as a pie chart in which the relative contribution of each taxon is represented as a slice (Fig. 3c and Additional files 7 , 8 and 9 ). These global views of metabolism enable the identification of biochemically related enzymes sharing similar taxonomic profiles. For example, for the mouse dataset, reads originating from Clostridiales dominate several amino acid pathways as well as parts of the glycolytic pathway (Additional file 10 ). Pathways such as pyruvate metabolism, the tricarboxylic acid (TCA) cycle and alanine, aspartate and glutamate metabolism feature larger contributions from other taxa such as Gammaproteobacteria and Bacteroides (Fig. 4 and Additional file 11 ). Fig. 4 Detailed views of taxonomic contributions to specific components of the tricarboxylic acid (TCA) cycle for four metatranscriptomic datasets. Each schematic indicates the taxonomic representation of enzymatic activities involved in the TCA cycle for four metatranscriptome datasets: mouse, kimchi, cow and deep sea. Pie charts indicate enzymes, with coloured sectors indicating the relative proportion of each taxon, size of pie chart indicates relative expression (see key). Small triangles indicate substrates with links indicating enzyme-substrate relationships Comparisons across samples further reveal that as noted above, many pathways are conserved but the taxa responsible for these pathways as well as their relative expression are not conserved (Fig. 3c , Fig. 4 and Additional files 7 , 8 , 9 , 10 and 11 ). For example within the TCA cycle, relative to the cow rumen dataset, the other three samples feature high expression of enzymes that together comprise the pyruvate dehydrogenase complex involved in anaerobic fermentation, e.g. dihydrolipoyl acetyltransferase (EC: 2.3.1.12), dihydrolipoyl dehydrogenase (EC: 1.8.1.4) and pyruvate decarboxylase (EC: 1.2.4.1). However, whereas Actinobacteria, Bacteroides and Gammaproteobacteria contribute significant reads to these enzymes in the mouse dataset, these enzymes are represented largely by Gammaproteobacteria in the deep-sea dataset and by Leuconostocaceae and Lactobacillaceae in the kimchi dataset. Furthermore, within a sample, we identify pathway sections that feature distinct taxonomic profiles. For example in the mouse intestinal dataset, Clostridiales contribute significantly to pyruvate carboxylase (EC: 6.4.1.1) as well as members of the TCA cycle. Also, noteworthy is the relatively high expression of phosphoenolpyruvate carboxykinase (EC: 4.1.1.49) in the mouse intestinal and cow rumen datasets. Previously associated with Ruminococcus flavefaciens , a Clostridiales bacterium found in the rumen [ 46 ] and Bacteroides fragilis found in the human gut [ 47 ], this enzyme is believed to be involved in the fermentation of cellulose to succinate in the rumen and catalyses phosphoenolpyruvate to oxaloacetate with the concomitant formation of ATP in human gut, may act as a ‘feeder’ reaction for carbon from the TCA cycle to drive various biosynthetic and oxidative processes such as gluconeogenesis and serine synthesis [ 48 ]. Focusing on glycolysis/gluconeogenesis (Additional file 10 ), as for the TCA cycle, we found that taxonomic groups that dominate the entire datasets also dominate specific enzyme activities. However again, sections of the pathway can be dominated by specific taxa. For example, aldose 1-epimerase (EC: 5.1.3.3) in the cow rumen and l -lactate dehydrogenase (EC: 1.1.1.27) in kimchi are predominantly expressed by Bacterioidetes and Lactobacillaceae, respectively. Further, even apparently minor taxa appear to provide specific functionality, suggestive of keystone roles within the community. For example, in the mouse intestinal dataset, both alcohol dehydrogenase (EC: 1.1.1.2) and aldose 1-epimerase (EC: 5.1.3.3) are predominantly expressed by Lactobacillaceae despite representing only 1.9 % of putative mRNA reads. As a final example of taxonomic contributions to metabolic functionality, we find that for the mouse intestinal dataset, Bacterioidetes and Gammaproteobacteria tend to dominate aspartate metabolism, while Closteridiales dominate glutamate metabolism (Additional File 11 ). As for the TCA cycle, while the majority of enzymes are well expressed in the mouse intestinal dataset, for the Kimchi dataset, expressions of genes within these pathways are more heterogeneous. This raises an important caveat, notably that the ability to map reads to the enzymes is dependent on the availability of suitable sequences in the reference databases. Hence, an inability to assign reads to asparagine synthase (EC 6.3.5.4) in the kimchi dataset may be due to the inability of sequence searches to map reads from the orthologous genes in the kimchi microbiome to known examples of this enzyme in the reference database. Integration of taxonomic and functional annotations provides molecular level insights into the biochemical contributions of individual taxa: II. Protein-protein interaction networks Beyond metabolic pathways, the provision of protein-protein interaction (PPI) networks offers additional opportunities to explore taxa-specific contributions to biochemical processes. Here, we integrate taxonomic information with a PPI network previously constructed for Escherichia coli [ 49 ]. The ABC transporter superfamily is a collection of transporters typically comprised of an extracellular substrate binding subunit, an intracellular ATP-binding subunit and a membrane incorporated permease. Across the different datasets, we see distinct signatures of subunit expression and taxonomic contributions (Fig. 5a ). For example, while many members of this family are well expressed in the mouse intestine, expression within the kimchi dataset is largely limited to putrescine-ornithine transport (potA-D), oligopeptide transport (oppA-D and F), ribose transport (rbsB-DK and R) and members or glutamine, histidine and arginine transport (e.g. glnH, glnP, hisP and argT). Similarly, in cow rumen, only a subset of transporters were well represented; these included xylF-H (xylose), malE-GK (maltose) and ugpA-CE (glycerol-3-phosphate). Fig. 5 Taxonomic contributions to functional modules defined through protein-interaction networks. a ABC transporters and ( b ) cell wall biogenesis and cell division. Protein interactions were obtained from a previously generated network of functional interactions for E. coli [ 49 ]. Pie charts indicate the relative proportion of each taxon, size of pie chart indicates relative expression (see key). c Relative representation of specific functional groups across the four well sampled datasets In the deep-sea microbiome dataset, many transporter components were associated with alphaproteobacteria, although leucine, isoleucine and valine transport components (livF-HJK and M) were broadly represented across phyla. In the mouse dataset, alphaproteobacteria were also the main contributors of transporters including dipeptide ABC transporter (dppBD), glutathione ABC transporter (yliABC), leucine ABC transporter (LivMF), glycerol-3-phosphate ABC transporter (ugpC) and xlycose ABC transporter (xylFH). xylF was largely represented by clostridiales and ‘other bacteria’ in the cow rumen dataset, suggesting that the contribution of alphaproteobacteria in the mouse data does not reflect annotation bias. The mouse intestine samples also display Gammaproteobacteria and Actinobacteria contributions to transporter components. Finally, the lack of Bacteroidetes representation in transporter components may reflect the reduced complement of these genes previously noted for members of this phylum [ 50 , 51 ]. Many genes involved in cell wall biogenesis and cell division were expressed within all datasets (Fig. 5b ). Of these, secA, prlA(secY) and ftsZ were the most highly expressed in each dataset. SecA mediate critical roles in protein translocation, and ftsZ is involved in organizing the initial stages of cell division. Within the mouse datasets, few reads from Bacteroidetes were assigned to ftsZ, suggesting that the ortholog(s) within this taxon display significant divergence from their E. coli counterpart. For example, the conserved C-terminus of E. coli ftsZ is absent in Bacteroidetes [ 52 ]. Genes encoding proteins involved in later steps of cell division (e.g. ftsN, ftsB, ftsQ and zipA) were largely restricted to representation by Gammaproteobacteria, suggesting these sequences are highly specialized within this taxon. Genes involved in the synthesis of cell wall components (e.g. mur and mrd) were well represented across the datasets, with the mouse and kimchi datasets featuring clear patterns of taxonomic contributions. For example, within the mouse dataset, murCEG were well represented by Bacteroidetes, while for the kimchi dataset, mrdA and mrdB were largely represented by the Lacteobacillaceae, potentially representing altered cell wall composition in these taxa. Unlike cell wall biogenesis and cell division, genes involved in flagella assembly, chemotaxis and hydogenases were poorly represented in the four datasets (Additional files 12 and 13 ). For example, both cow and kimchi datasets lacked significant expression of many flagella and chemotaxis genes reflecting an absence of flagella in many of the major taxa in these microbiomes (e.g. Lactobacillus spp . and Leuconostoc spp . in kimchi). Indeed, for kimchi, expression was largely limited to flgJ, a peptidoglycan hydrolase required for flagella formation and likely reflects significant local sequence similarity with other proteins such as N -acetylmuramoyl- l -alanine amidase from L. sakei which shares a conserved, ~200 residue lysine motif with flgJ. In the mouse, we noted little representation from Bacteriodetes, with most expression dominated by Closteridiales. As noted above, the restriction of certain components to Gammaproteobacteria may reflect their relative sequence diversity and/or specialized functions. Finally, we note that four genes were dominated by representation from the Alphaproteobacteria: motA, mbhA, cheY and flip. Such abundance may at least in part be due to variable copy numbers of these genes in this taxon, for example, cheY is present in six copies in the Rhodobacter sphaeroides genome [ 53 ]. Finally, we also explored the expression and taxonomic representation of genes involved in NADH dehydrogenase and hydrogenase complexes (Additional file 13 ). As for flagella assembly and chemotaxis, many components were not represented within the four samples. For example, 16 of the 50 genes that comprise these complexes lack expression in the kimchi, cow rumen and deep-sea datasets. Indeed, within the kimchi dataset, only tpiA, dps and iscS are well represented. This is likely related to local sequence conservation between the Fe-binding motif of dps and the cysteine desulfurization and conservative C-terminal of iscS, resulting in misannotations. Curiously, while both the cow and deep-sea datasets feature relatively homogenous patterns of taxonomic representation in their respective NADH dehydrogenase subunits, those in the mouse dataset appear largely incongruent."
} | 11,365 |
38602433 | PMC11187886 | pmc | 3,165 | {
"abstract": "Abstract The appearance of triboelectric nanogenerators (TENG) provides a promising energy technology for harvesting abundant water wave energy. Here, the design and fabrication of a swinging origami‐structured TENG (SO‐TENG) tailored specifically for water wave energy harvesting are presented. The design incorporates an oscillating structure weighted at the bottom, inducing reciprocating motion propelled by the inertia of passing water waves. This reciprocating motion efficiently converts mechanical into electrical energy through the origami structure. By employing origami as the monomer structure, the surface contact area between friction layers is enhanced, thereby optimizing output performance. the swinging structure, combined with the placement of heavy objects, enhances the folding and contact of the origami, allowing it to operate effectively in low‐frequency water wave environments. This configuration exhibits robust power generation capabilities, making it suitable for powering small electronic devices in water wave environments. Furthermore, when applied to metal corrosion protection, the SO‐TENG demonstrates notable efficacy. Compared to exposed Q235 carbon steel, Q235 carbon steel protected by SO‐TENG exhibits a significant reduction in open‐circuit potential drop, approximately 155 mV, indicative of superior anti‐corrosion properties. It lays a solid foundation for water wave energy collection and self‐powered metal corrosion protection in marine environments.",
"conclusion": "3 Conclusion In summary, we have designed and manufactured a TENG with a swinging origami structure for the collection of wave energy. Utilizing origami as the monomer structure of the device, the device can effectively improve the surface contact area of the TENG in a limited space and greatly improve the output performance of the TENG device. The lead block is placed on the bottom fan blade of the swing body of the swing device so that the swing body can make the reciprocating swing motion due to the influence of inertia under the trigger of the water wave so that the contact separation motion between the friction layers of the origami structure can occur. It can greatly improve the folding degree and contact degree of origami, with an output of up to 138 µA and a peak power density of 2.62 W m −2 under a weight of 500 g, with good output performance. When operating under low‐frequency water waves, the device exhibits reliable power generation capabilities and can power small electronic devices in underwater environments. When applied to corrosion protection of metals, the open‐circuit potential of Q235 carbon steel, protected by TENG, is reduced by approximately 155 mV, showing effective corrosion protection. This indicates a broad application prospect for TENG in large‐scale wave energy harvesting and the realization of self‐powered ocean sensors in marine environments.",
"introduction": "1 Introduction With the continuous development and utilization of fossil energy, the degree of energy crisis has gradually intensified, and the ecological environment has been deteriorating. [ \n \n 1 \n , \n 2 \n \n ] Consequently, the development and utilization of renewable clean energy have become paramount. marine energy, abundant on earth, holds immense potential for obtaining marine environmental information and monitoring the marine environment. [ \n \n 3 \n \n ] To this end, researchers have invested in the research and development of energy harvesting in marine environments. Presently, energy harvesting devices in marine environments primarily rely on traditional electromagnetic generators (EMGs). [ \n \n 4 \n \n ] However, their low energy conversion efficiency, high cost, and large footprint hinder their application in the marine environment. [ \n \n 5 \n , \n 6 \n \n ] Therefore, it is necessary to develop cost‐effective marine energy harvesting devices with high energy conversion efficiency. Recently, the research of triboelectric nanogenerators (TENG) has provided a new strategy for various kinds of energy harvesting. [ \n \n 7 \n , \n 8 \n , \n 9 \n , \n 10 \n , \n 11 \n , \n 12 \n , \n 13 \n \n ] Compared with traditional EMG, TENGs have obvious advantages, such as the simplicity of their design and their small footprint. [ \n \n 14 \n , \n 15 \n , \n 16 \n , \n 17 \n , \n 18 \n \n ] Various energy harvesting types of TENG have been proposed to capture energy from human activity, [ \n \n 19 \n , \n 20 \n \n ] wind, [ \n \n 21 \n , \n 22 \n , \n 23 \n , \n 24 \n , \n 25 \n \n ] water waves, [ \n \n 26 \n , \n 27 \n , \n 28 \n , \n 29 \n , \n 30 \n , \n 31 \n \n ] and raindrops. [ \n \n 32 \n , \n 33 \n \n ] At present, various TENG structures have been designed specifically for water wave energy harvesting. In the marine environment, water wave movement is random and unpredictable. Driven by this motion, TENGs with different configurations exhibit various movements, including swinging, [ \n \n 34 \n \n ] slapping movement, [ \n \n 35 \n , \n 36 \n \n ] sliding movement, [ \n \n 37 \n \n ] and rolling ball‐type independent layer movement. [ \n \n 38 \n , \n 39 \n \n ] In addition, the surface charge density and surface contact area between friction layers can affect the output performance of TENG. [ \n \n 40 \n \n ] To increase the surface charge density, many researchers have explored extensively and modified the friction layer material to increase the electronegativity difference between the two friction layers and change the surface topography of the friction layer material. [ \n \n 41 \n \n ] However, these approaches often incur higher manufacturing and time costs. Another common method involves enlarging the size of TENG devices to increase surface contact area; however, this leads to larger footprints and higher production expenses. Transforming 2D planar devices into 3D structures has proven effective in addressing this issue. By designing the friction layer for double‐sided contact, TENG devices can optimize space utilization and enhance surface contact area. [ \n \n 42 \n , \n 43 \n \n ] While traditional origami technology is designed for double‐sided contact. [ \n \n 44 \n , \n 45 \n , \n 46 \n , \n 47 \n \n ] Existing structures exhibit relatively low space utilization rates and lack suitable driving mechanisms, resulting in insufficient friction layer contact and limited device output. [ \n \n 48 \n , \n 49 \n , \n 50 \n \n ] Hence, it is necessary to design a suitable device to integrate a large number of units in a limited space and drive them to work under the action of water waves to achieve higher output performance. In this work, a swinging origami structure of the TENG (SO‐TENG) was designed and fabricated to collect water wave energy. By using origami as the monomer structure of SO‐TENG, the surface contact area of TENG can be effectively improved in a limited space. At the bottom of the oscillating body, a swing structure for placing heavy objects is designed as a driving device, which can effectively collect water wave energy. Firstly, the thickness of the friction layer material and the matrix material was optimized. Next, the effects of different origami quantities, lead block weights, and various movements on the output performance were systematically measured. Finally, SO‐TENG was applied to power small electronic devices in a water‐wave environment and provided effective corrosion protection for Q235 carbon steel, demonstrating the wide range of applications of TENG in marine environments.",
"discussion": "2 Results and Discussion 2.1 Structure and Working Principle of the SO‐TENG The origami structure has good elasticity and a compact design, with a large contact area between friction layers. Figure \n 1 a shows a 3D view of a single origami TENG (O‐TENG). The detailed manufacturing process is shown in Figure S1 (Supporting Information), in which two polymer strips are folded repeatedly to make O‐TENG. Both polymer strips are composed of copper /PET/ copper sandwich structures, as shown in the inset. One polymer strip serves as the friction layer, while the other acts as the electrode. A layer of friction material is applied to the copper electrode, as depicted in the inset. The optical photos of the folded origami are shown in Figure 1b . Figure 1c,d displays optical photos of the O‐TENG during stretching and compression, which exhibits excellent elastic performance. The stretching or compression process only requires a small driving force, making it easy to harvest energy from different environmental forms. Figure 1 The 3D drawing, production process, and shape of origami monomer. a) A 3D diagram of an origami monomer illustrated with an enlarged cross‐section of a sandwich structure. b) Optical photo of origami monomer in its natural state. c) Optical photo of an origami unit in a stretched state. d) Optical photo of an origami unit under compression. Working process, structure, and working principle of SO‐TENG. e) Schematic diagram of SO‐TENG driven by a servo motor. f) Schematic diagram of the structure of SO‐TENG. g) Diagram of the working principle of the No. 1 origami TENG. h) The COMSOL software was used to simulate and evaluate the different working processes of the No. 1 origami TENG. Figure 1e illustrates a schematic diagram of the measurement system for the designed swinging origami TENG device used to test its electrical output performance. The enlarged view of the SO‐TENG in the system is shown in Figure 1f . The SO‐TENG consists of a stator housing with three baffles and a three‐blade oscillating body, which is placed between each baffle and the oscillating body blades. The design incorporates a sphenoid feature to ensure full contact inside each origami, thereby enhancing the surface contact area between the friction layers. Additionally, a lead block is positioned within the hollow section of the bottom fan blade, enabling the swinging body to oscillate under external excitation, utilizing the inertia of the lead block to make the TENG work. Upon external triggering, the prepared SO‐TENG oscillating body undergoes swinging motion due to inertia. This reciprocating oscillation causes the origami paper to experience stretching and compression movements. Illustrated in Figure 1g‐i–iv , the working mechanism of the No. 1 origami TENG begins with an initial equilibrium of charges (stage i). Upon stretching (stage ii), electrons flow from the copper electrode to the copper friction layer via the outer circuit. Subsequently, during the rebound motion, equilibrium is reached (stage iii). Driven by inertia, the oscillating body continues its motion, compressing the No. 1 origami TENG (stage iv), facilitating electron flow from the copper friction layer back to the copper electrode. This completes a cycle of work as the device returns to its initial position. For a more in‐depth analysis of its working mechanism, the COMSOL finite element analysis software was used to simulate the operation of the No. 1 origami TENG in one cycle, as shown in Figure 1h . In the initial state, the two friction layers are separated, establishing an electrostatic equilibrium. As the origami is stretched, an induced electromotive force is generated, disrupting the initial electrostatic equilibrium. When the origami is stretched to its maximum, it reaches a new electrostatic equilibrium state. Subsequently, a rebound motion occurs as the origami is compressed. During the compression process, an induced electromotive force is generated, and when fully compressed, it reaches a new electrostatic equilibrium state. 2.2 Material Optimization of the SO‐TENG and Its Performance In the process of stretching and compression, the thickness of the friction layer material and the substrate material of the origami paper have a significant impact on its output. Different friction layer materials exhibit substantial differences in electronegativity, leading to notable variations in output performance. The thickness of the PET substrate, which serves as the origami paper base, can affect the flexibility and elasticity of the origami paper. the swinging motion of the device influences the stretching and compression of the origami paper, and it also affects the folding degree and contact level of the paper. Consequently, this influences the surface contact area between the friction layers, thereby affecting the electrical output performance of the device. In the subsequent experiments, 12 origami papers with alternating contact and separation were placed on the No.1 and No.2 TENGs, as shown in Figure S2 (Supporting Information). Several common friction layer materials were selected: polyimide (PI), polytetrafluoroethylene (PTFE), and fluorinated ethylene propylene (FEP), and the short‐circuit current, transferred charge and open‐circuit voltage of the No.1 TENG were tested. The results are shown in Figure \n 2 a–c . It can be seen that FEP and copper (Cu) are used as friction layer materials to produce a maximum output of 65 µA, 1.5 µC, and 220 V. This is attributed to the larger electronegativity difference between these two friction layer materials. In the subsequent experiments, FEP and Cu were chosen as friction layer materials for further study. Figure 2 Optimization of friction materials for SO‐TENG. Output performance of the No.1 TENG under different friction layer materials in SO‐TENG: a) Short‐circuit current, b) Transferred charge. c) Open‐circuit voltage. Output performance of the No.1 TENG under different thicknesses of PET in SO‐TENG: d) Short‐circuit current, e) Transferred charge. f) Open‐circuit voltage. Several thicknesses of PET substrate were selected, and the number of folded sides of origami was the same for different thicknesses, and the output performance of the SO‐TENG was tested. The results are shown in Figure 2d–f . It can be observed that the output is highest when the PET substrate material has a thickness of 0.05 mm. During the folding process of the origami paper, the 0.05 mm thick PET substrate exhibits better folding and contact effects, resulting in a larger surface contact area between the friction layer materials. Consequently, 0.05 mm thick PET was chosen as the base material for origami paper in subsequent experiments. Based on the results of the above experiments, we optimized the friction layer material and PET matrix thickness of origami paper to enhance the device's electrical output performance. FEP and Cu were selected as the friction layer materials, and 0.05‐mm‐thick PET was selected as the base material of origami paper. 2.3 Structure Optimization of the SO‐TENG and Its Performance To fully utilize the space and enhance the output performance of the SO‐TENG, the number of contact‐separations of origami paper is optimized. As shown in Figure \n 3 a , the 3D diagram of different contact‐separation numbers of origami paper and the corresponding optical photos are shown in Figure S3a (Supporting Information). The number of origami contact‐separations is 6, 8, 10, 12, 14, 16, 18. Due to the different contact separation quantities, the thickness of the origami is inconsistent in the compressed state. Therefore, different sphenoid is designed for origami with different amounts of contact‐separation. To ensure that the working process of the SO‐TENG device can be fully compressed, the specific working process, such as the Video S1 , is in the Supporting Information. Different sphenoid sizes are shown in the photos in Figure S3b (Supporting Information). Subsequently, six origami papers were created for each contact‐separation number and positioned accordingly (1‐6). The results, depicted in Figure 3b–d , illustrate a trend where the output performance of the No. 1 origami paper initially increases with the contact‐separation number and then decreases. Specifically, among the 12 contact‐separation quantities tested, the maximum output reaches 33 µA, 0.75 µC, and 185 V. This phenomenon arises due to the intricate interplay between the contact area, number of contacts, and contact stress within the TENG system operating in contact separation mode. The origami paper with different amounts of contact separation is placed in the same space, and the contact stress decreases with the increase of the origami contact area. This relationship diagram between contact area and contact stress of the No. 1 origami TENG in different contact separation quantities was tested, as shown in Figure S4 (Supporting Information). Notably, when the number of contact separations of origami increases from 6 to 12, the impact of origami contact area on the device's electrical output performance surpasses that of contact stress. Conversely, when the number of contact separations of origami increases from 12 to 18, the influence of origami contact stress is greater than the effect of contact area on the electrical output performance of the device. Therefore, it is concluded that with the increase in the number of origami monomer contact separation, the electrical output performance of the device first increases and then decreases. When the number of origami contact separations is 12, the electrical output performance of the device is the highest. Therefore, in the experiments aimed at enhancing the device's electrical output performance, origami paper with 12 contact‐separation number was selected for further investigation. Figure 3 Optimization of SO‐TENG. a) 3D diagram of origami paper for SO‐TENG with different contact‐separation quantities. Output performance of No.1 TENG under different contact–separation quantity of SO‐TENG origami paper: b) short‐circuit current, c) transfer charge, d) open‐circuit voltage. Output performance of SO‐TENG after rectification under three different origami quantities: e) output current, f) the output power under different external loads. g) Charging a 47 µF capacitor. Subsequently, the effect of origami quantity on the output performance of TENG devices was studied. Figure S5a (Supporting Information) shows the 3D representation of three different quantities of origami, represented as ZZ‐2, ZZ‐4, and ZZ‐6. Due to the elasticity of origami paper, with the increase of the number of origami papers, the strength between origami papers weakens and the corresponding force decreases, so the output performance of a single origami TENG weakens. This is because the electrical output performance of the contact separation mode TENG is greatly affected by the force. The electrical output performance of different amounts of origami paper after rectification is tested. Figures 3e and S5b (Supporting Information) respectively show the output current and output voltage of the TENG device after rectification. It can be seen that with the increase of the amount of origami, the output current of the TENG device increases after rectification, while the output voltage remains relatively constant. This is because the circuit after rectification is in a parallel state, the current is superimposed, and the voltage is not superimposed. In addition, on the other hand, according to TENG's theoretical basis, charge transfer mainly depends on the surface contact area and surface charge density between the friction layers. Under the same excitation conditions, increasing the amount of origami will increase the surface contact area between the friction layers. Current is defined as the amount of charge transferred per unit time. The following formula is shown:\n \n (1) \n I = d Q d t \n \n Therefore, as the number of origami papers increases, the surface contact area also increases, leading to an increase in friction charge generation during the contact process. Consequently, the output current increases. However, the current output does not increase proportionally because the slight increase in resistance due to the higher number of origami papers has a relatively small impact. The output voltage remains essentially unchanged, and the voltage has no relationship with the charge transfer density. Therefore, with an increase in the number of origami papers, the output voltage remains relatively constant. The resistive load behavior of origami papers in different quantities was studied, and Figure 3f illustrates the variation in the rectified output power of the TENG with different numbers of origami papers as the external load changes. The power calculation for the TENG is given by the following formula,\n \n (2) \n P = U I \n \n When the number of origami papers increases from 2 to 6, the output power increases from 1.16 to 2.76 mW. Furthermore, the increased number of origami papers also enhances the charging speed of the capacitor, as depicted in Figure 3g . ZZ‐6 exhibits the fastest charging speed, being able to charge a 47 µF capacitor to 16.8 V within 60 s, nearly 2.5 times faster than ZZ‐2. It has been proved that the application of an origami structure in the oscillating device can effectively collect energy, and multiple origami structures can be arrayed in the oscillating device to improve its electrical output performance. To enhance the application of the TENG device for blue energy collection in marine environment and optimize the electrical output performance of the SO‐TENG, further optimizations were pursued. Lead weight plays a very important role in the energy harvesting process of TENG devices with swinging origami structure. It is used to collect energy and then drive the origami structure to complete the contact separation movement to achieve electrical energy output. In theory, the greater the weight, the greater the inertia during motion. Figure S6 (Supporting Information) shows a 3D view of SO‐TENG with optical images of lead blocks of different weights. The seven lead blocks with different weights have the same cross‐sectional area, and as the weight increases, the length of the lead block increases proportionally. In order to improve the electrical output performance of the device, under a reciprocating frequency of 1.75 Hz and a stroke of 150 mm, we tested the electrical output performance of several different weight lead blocks. Figures \n 4 a and S7 (Supporting Information) show the rectified output current and output voltage, respectively; it can be observed that the output current of SO‐TENG increases with the weight of the lead block. When the weight of the lead block is 500 g, the current can reach 102 µA. This phenomenon can be attributed to the heightened inertia with increased weight, resulting in a more compact surface contact area between the friction layers. Consequently, the friction charge generated during the contact process amplifies, leading to a corresponding increase in output current. The output voltage also increases with the weight of the lead block, but the increase is relatively slow. Additionally, the resistive load behavior under different weights of the lead block is studied, as shown in Figure 4b . Its performance is positively correlated with the weight of the lead block. When the weight of the lead block is 500 g, with a matching resistance of 2 MΩ, the maximum peak power is 4.085 mW. The impact of lead block weight on the charging performance of SO‐TENG after rectification was then compared, as shown in Figure 4c . As the weight of the lead block increases, the charging speed increases. A 500‐g lead block has the fastest charging speed, being able to charge a 47 µF capacitor to 24 V within 60 s, which is twice as fast as the 200‐g lead block. Consequently, for further experimentation aimed at optimizing the device structure and enhancing its electrical output performance, a 500 g lead block was chosen. Figure 4 Optimization of SO‐TENG and testing of electrical output performance. a) Rectified output current of SO‐TENG under different weights of lead blocks. b) Output power under different external loads after rectification under different weights of lead blocks driving SO‐TENG. c) Charging a 47 µF capacitor after rectification under the drive of weights of different lead blocks. Simulate the output performance of SO‐TENG water wave energy harvesting in an ocean environment. d) 3D schematic of the testing principle for energy harvesting by SO‐TENG. The output performance of SO‐TENG under different reciprocating stroke and frequency: e) output current, f) output voltage. The output performance of the SO‐TENG under different reciprocating strokes after rectification at a reciprocating frequency of 1.75 Hz: g) output current, h) external load output power, i) charging a 33 µF capacitor, j) charging capacitors of different capacitances. k) durability and stability testing of SO‐TENG device over ten continuous days. In order to evaluate the output performance of SO‐TENG, the influence of different reciprocating strokes and frequencies on the output performance of SO‐TENG was tested. Figure 4d shows a schematic diagram of its working process, and SO‐TENG is driven by a servo motor. As shown in Figure 4e,f , we tested the dependence of the output current and output voltage of SO‐TENG on different reciprocating strokes and frequencies. It can be observed that with the increase of reciprocating stroke and frequency, the output performance of SO‐TENG improves. This indicates that with the increase of reciprocating stroke and frequency, the folding degree of the paper becomes more complete, increasing the surface contact area between the friction layers, resulting in better output performance. Subsequently, the output performance of SO‐TENG after rectification was specifically tested under different reciprocating strokes at a frequency of 1.75 Hz, as shown in Figures 4g and S8 (Supporting Information). With the increase of reciprocating stroke, the output current and output voltage increase. At a stroke of 175 mm, the output can reach 138 µA and 188 V. This is because with the increase of reciprocating stroke, the relative motion speed increases, resulting in better folding degree and contact effect of the paper. At a matching internal resistance of 15 MΩ, the maximum peak power can reach 6.035 mW, and the peak power density can reach 2.62 W m −2 , demonstrating extremely high output performance (Figure 4h ). Subsequently, the charging performance of the rectified SO‐TENG under different reciprocating strokes is compared, as shown in Figure 4i . As the reciprocating stroke increases, the faster the capacitor is charged. A 33 µF capacitor can be charged to 20 V in 27 s at a 175‐mm stroke. In addition, different capacitors are charged, as shown in Figure 4j . As the capacitance increases, the capacitor charging speed decreases, demonstrating good charging performance for different capacitors. The stability of TENG devices is crucial. To evaluate the durability and stability of the SO‐TENG device, the current output after 1 h of rectification was continuously tested for 10 d. As shown in Figure 4k , the continuous output current for 10 d remained around 138 µA, which has good output stability. The unique advantages of applying origami structures to oscillating devices are demonstrated. 2.4 Application of SO‐TENG in a Water Wave Environment To simulate and test the performance of the SO‐TENG device in collecting wave energy in a real ocean environment, we placed a plastic box containing the SO‐TENG device into a water tank environment in the laboratory to simulate wave motion. The water waves were generated by a motor driving a wave‐making board back and forth. Figure \n 5 a shows the output current after rectification of the SO‐TENG device is shown for four different water wave frequencies. It can be observed that the current increases with the increase in water wave frequency. This is because as the water wave frequency increases, the contact between the friction layers of individual TENGs in the motion process of the SO‐TENG becomes more sufficient, leading to higher current output. Figure 5b illustrates the charging of a 47 µF capacitor after rectification of the SO‐TENG device under four different water wave frequencies. At a water wave frequency of 1.25 Hz, the SO‐TENG device can charge a 47 µF capacitor to 7 V within 60 s. It is further demonstrated that in a certain frequency range of water wave, the output performance of SO‐TENG is better with the increase of water wave frequency. By charging the capacitor, the stored energy can drive small electronic devices. Figure 5c shows the test diagram of SO‐TENG under a real water wave environment. Figure 5d shows the voltage variation diagram of charging a 150 µF capacitor driven by a water wave frequency of 1 Hz. It can be seen that SO‐TENG charged the 150 µF capacitor to 1.4 V within 50 s, making the calculator work normally. The voltage remains stable with continuous operation of the SO‐TENG, enabling the calculator to function normally as illustrated in Video S2 (Supporting Information). In addition, under the same water wave conditions, the SO‐TENG can be driven to power small watch, hygrothermograph, and LEDs, as shown in the illustration in Figure 5c . The circuit diagram for charging electronic devices with the SO‐TENG device is illustrated in Figure S9 (Supporting Information). Figure 5 Application of SO‐TENG wave energy harvesting in the simulated real ocean environment. a) Output current after rectification of SO‐TENG at different water wave frequencies. b) Charging of a 47 µF capacitor after rectification of SO‐TENG at different water wave frequencies. c) Real testing environment for SO‐TENG wave energy harvesting. d) Charging diagram for powering the calculator. e) Schematic diagram of the cathodic protection system for SO‐TENG. f) Curve showing the variation of open‐circuit potential. g) Metallographic images of Q235 carbon steel after 6 h with and without DR‐TENG protection. As an economical and environmentally friendly energy source, TENG can harvest wave energy in marine environments and convert it into electrical energy. The application of the generated electrical energy in the corrosion protection of metals shows promising prospects, and many researchers have been actively involved in this field. [ \n \n 51 \n , \n 52 \n , \n 53 \n , \n 54 \n , \n 55 \n , \n 56 \n \n ] The schematic diagram of the cathodic protection system for SO‐TENG is shown in Figure 5e . The alternating current output during the operation of SO‐TENG is converted into direct current output through the rectification bridge. During the operation of SO‐TENG, electrons transfer to the surface of Q235 carbon steel to effectively protect it. In electrochemical experiments, open circuit potential (OCP) is an important parameter used to evaluate the effect of metal cathodic protection. [ \n \n 57 \n , \n 58 \n , \n 59 \n , \n 60 \n , \n 61 \n \n ] Subsequently, the TENG equipment was driven to protect the Q235 carbon steel in a real water wave environment, and its OCP changes were tested, as shown in Figure 5f . Initially, when the TENG is not connected, the OCP value of the Q235 carbon steel is ‐565 mV. Upon connecting the TENG at 100 s, the OCP value of the Q235 carbon steel rapidly drops to ‐720 mV, indicating that the Q235 carbon steel provides effective protection when connected to the TENG. Here, the OCP drops by 155 mV, and after disconnecting the circuit at 200 s, the OCP value recovers. In general, achieving a lower OCP value is imperative for optimal cathodic protection. Hence, the application of SO‐TENG demonstrates a commendable protective effect on Q235 carbon steel in a real water wave environment. To further illustrate the corrosion protection provided by the SO‐TENG on Q235 carbon steel, metallographic microscope images provide a more intuitive view of the corrosion situation of Q235, as shown in Figure 5g . It is evident that the extent of corrosion for Q235 carbon steel without SO‐TENG protection intensifies over time, while the Q235 carbon steel protected by the SO‐TENG shows only slight corrosion traces after 6 h of immersion. These findings demonstrate the promising applicability of SO‐TENG for wave energy harvesting in marine environments."
} | 8,014 |
32295125 | PMC7215868 | pmc | 3,168 | {
"abstract": "Microorganisms thriving in hot springs and hydrothermally active volcanic areas are dynamically involved in heavy-metal biogeochemical cycles; they have developed peculiar resistance systems to cope with such metals which nowadays can be considered among the most permanent and toxic pollutants for humans and the environment. For this reason, their exploitation is functional to unravel mechanisms of toxic-metal detoxification and to address bioremediation of heavy-metal pollution with eco-sustainable approaches. In this work, we isolated a novel strain of the thermophilic bacterium Geobacillus stearothermophilus from the solfataric mud pool in Pisciarelli, a well-known hydrothermally active zone of the Campi Flegrei volcano located near Naples in Italy, and characterized it by ribotyping, 16S rRNA sequencing and mass spectrometry analyses. The minimal inhibitory concentration (MIC) toward several heavy-metal ions indicated that the novel G. stearothermophilus isolate is particularly resistant to some of them. Functional and morphological analyses suggest that it is endowed with metal resistance systems for arsenic and cadmium detoxification.",
"conclusion": "4. Conclusions With the aim of characterizing new thermophilic heavy-metal-resistant microorganisms, soil sampling was performed in a hydrothermal volcanic area near Naples in Italy, known as Pisciarelli. This is an acidic sulfate area located close to the Solfatara crater famous for an intense endogenous diffuse and fumarolic water-dominant outgassing activity; the chemical composition of mud and water samples revealed that the main metal is iron, but arsenate is an additional significant component. Since geothermal sites are very interesting sources of thermophilic organisms and Pisciarelli is an arsenic-rich area, we hypothesized that novel thermophiles could be found able to detoxify this metal or use it for energy-yielding reactions. We succeeded in isolating a microorganism with an optimal growth temperature of 60 °C and an optimal pH 7, from a water-poor mud. Subsequent molecular identification revealed homology to the species G. stearothermophilus . Our laboratory culturing experiments demonstrated the ability of G. stearothermophilus GF16 to grow in the presence of arsenate in a range of concentrations comparable to those of bacteria classified as arsenic resistant and in agreement with the natural environmental setting composition as well. This study highlights the adaptation capabilities of the new isolate of G. stearothermophilus and its tolerance to extreme environmental conditions and points out to further molecular and physiological investigations to clarify its role in the biogeochemical cycle of arsenic as well as its potential for the management of heavy-metal environmental contaminations.",
"introduction": "1. Introduction Heavy metals are among the most persistent and toxic pollutants. Differently from organic xenobiotics, which can be converted into non-harmful substances, they cannot be completely removed from the environment [ 1 ]. Anthropogenic sources including mining and various industrial (vehicle emissions, lead–acid batteries, paints) and agricultural activities (fertilizers, aging water supply) lead to their increasing accumulation [ 2 , 3 , 4 ]. The prolonged exposure to heavy metals is responsible for several human diseases, as documented by the World Health Organization [ 5 ]. For example, arsenic and cadmium have been classified as carcinogenic compounds by the International Agency for Research on Cancer (IARC) in both humans and animals [ 6 , 7 ], while the exposure to lead is responsible for 3% of cerebrovascular disease worldwide [ 8 ]. Therefore, reduction of heavy-metal pollution is actually among the greatest challenges of the new century [ 9 , 10 , 11 ]. As a consequence of the massive accumulation of toxic metals into the environment, majority of microorganisms have developed genetic resistance mechanisms [ 12 , 13 , 14 ] and even specific metabolic pathways to deal with toxic metals [ 15 , 16 , 17 ]. For instance, gram-positive and gram-negative bacteria possess arsenic resistance systems encoded by operons carried either on plasmids or on the chromosome. Genetic determinants are usually the three genes arsR, arsB , and arsC [ 18 , 19 ], among which arsR encodes a trans-acting repressor of the ArsR/SmtB family involved in transcriptional regulation [ 20 , 21 , 22 ], arsB encodes an As(III) efflux transporter (ArsB/Acr3) [ 23 ], and arsC encodes a cytoplasmic arsenate reductase that converts As(V) to As(III), the latter extruded outside the cell [ 24 , 25 , 26 ]. Other organisms benefit of additional proteins that improve the arsenic resistance, such as the arsenite methyltransferases [ 27 ]. The arsenic resistance system of some microorganisms also provides Cd(II) tolerance [ 28 , 29 , 30 ]. Gram-positive and gram-negative bacteria also possess cadmium resistance systems, which are generally composed by two genes, cadC coding for a helix-turn-helix transcriptional regulator that controls the second gene cadA , coding for a cadmium-translocating P-type ATPase. The loci of genes involved in cadmium resistance are either on plasmids or on chromosomes [ 31 ]. Since many metals, such as arsenic, are naturally present in volcanic and geothermal springs, these niches are commonly colonized by heavy-metal-resistant microorganisms [ 32 , 33 ]; they actively participate in geochemical cycles, solubilizing and precipitating metals thus contributing to transforming the bedrock and remodeling their ecosystems [ 34 ]. The interest in the comprehension of the molecular mechanisms underlying heavy-metal resistance in microorganisms thriving in extreme environments is growing fast because of the urgent need to develop effective and eco-sustainable approaches toward heavy-metal pollution [ 35 , 36 , 37 , 38 ]. In this work, we describe the isolation and characterization of a new thermophilic heavy-metal-resistant microorganism from the solfataric mud pool of Pisciarelli in the Campi Flegrei volcano located near Naples in Italy. The site has extreme environmental conditions in terms of temperature, acidity, and As-rich geochemistry due to an intense hydrothermal activity [ 39 , 40 ].",
"discussion": "3. Results and Discussion 3.1. Geochemical Characterization of the Sampling Site Like similar volcanic systems worldwide, the Solfatara volcano hosts an acidic sulfate environment determined by the hot circulation of aggressive sulfurous fluids deriving from mixing between deeply infiltrating meteoric waters and ascending magmatic gases [ 39 , 40 , 41 ]. This phenomenon causes intense rock alteration and concentration of certain elements, such as As [ 39 , 49 , 50 , 51 , 52 , 53 , 54 ]. However, differently from the diffuse and fumarolic outgassing characterizing the Solfatara crater, the Pisciarelli site is a water-dominant environment, showing the formation of boiling pools and water springs and the opening of low-energetic geyser-type vents. The site represents the shallowest portion of a widespread geothermal system that develops in the subsurface and converts into brines downward to its deeper roots that are directly supplied by the magmatic outgas. Due to the increased hydrothermal activity since 2006, the site shows maximum temperatures of ca. 110 °C and up to 260 tons/day of CO 2 [ 55 ] with an abundance of H 2 S and the presence of minor gaseous species such as CH 4 , N 2 , H 2 , and CO. At the time of sampling, the bubbling mud pool was at pH 4.8 and 94.3 °C and the marginal mud at pH 6.0 and 55.3 °C, while surrounding soils were at temperature up to 98–99 °C and very acidic pH. These values are in the range known for the area, although lower temperatures were also measured in the mud pool (approximately 70 °C). Furthermore, the mineralogical and chemical features of the sampled materials [ 39 ] are those usually determined. Indeed, the mud was typically gray in color and essentially enclosed sulfates (i.e., K- and Al- bearing alunite), sulfides (i.e., Fe- plus S-bearing pyrite), and silica-phases; dried water samples crystallized NH 4 -bearing sulfates. The mud is enriched in As (10–20 ppm) and Hg (around 40 ppm) compared to the protolith volcanic deposits; contains few wt.% of Fe 2 O 3 ; approximately 60 ppm of V; 10–20 ppm of Pb; <10 ppm of Co, Ni, and Cr; 10–20 ppm of Cu; 1–2 ppm of Tl; and practically lacks Cd being at <0.1 ppm [ 39 ]. Based on Valentino and Stanzione [ 56 ], Pisciarelli waters are rich in SO 4 -2 (1400–7000 mg/L) and NH 4 500–1000 mg/L); contain F (0.5–30 mg/L), Al (65–20 mg/L), and B (0.1–0.8 mg/L); lack carbonate species and chlorine; the content of As, Hg, Tl, Pb is approximately 40–2000, 40–250, 2–8, and 5–30 µg/L, respectively. The general enrichment in S, NH 4 , As, and Hg is consistent with the volcanic setting and the magmatic/geothermal outgas support. According to Aiuppa et al. [ 54 ], arsenate is the As-compost under equilibrium in the water solutions. 3.2. Isolation and Identification of Geobacillus stearothermophilus GF16 Upon incubation of mud samples taken from the marginal water-poorer portion, cell growth was observed in LB medium at pH 7 and 50 °C. Single colonies were isolated by serial dilutions in the same medium, and the isolated strain showed an optimal growth temperature of 60 °C. In order to identify the microorganism, ribotyping and fatty acid analyses were performed at DSMZ; the results led to the identification of a member of Geobacillus genus but did not allow to differentiate unambiguously at species level. Geobacilli were first described by Nazina et al. in 2001 [ 57 ]; they are gram-positive, endospore-forming, aerobic or facultative anaerobic thermophiles, growing optimally at temperatures between 50 and 72 °C and exploitable for various biotechnological applications such as for bioremediation and production of thermostable enzymes and biofuels [ 58 , 59 ]. The interest toward microorganisms of the Geobacillus genus prompted us to combine two different experimental approaches such as MALDI-TOF MS analysis and 16S rRNA sequencing to try to unambiguously identify the species. Indeed, the classification of the different species within the Geobacillus genus is challenging since the sequence similarity of the 16S rRNA can be higher than 97% even among species [ 60 ]. On the other hand, MALDI-TOF MS analysis has been proposed as a powerful bioanalytical method to detect profiles of proteins derived from whole bacterial cells to be used for bacteria identification [ 61 ]. The combined molecular approaches allowed the identification of a new isolate of Geobacillus stearothermophilus that we named G. stearothermophilus GF16. Multiple alignment of 16S rRNA sequence of the novel G. stearothermophilus isolate (GF16) with those of other Geobacilli and Bacilli with identities from 99% to 97% was performed to build the phylogenetic tree shown in Figure 2 . The results confirmed the difficulty in determining a threshold for defining species within the Geobacillus genus and supported the concept that a combination of genotypic and phenotypic characteristics could be not sufficient for describing a new species [ 60 ]. 3.3. Metal Ion Resistance and Antibiotic Susceptibility in G. stearothermophilus GF16 To evaluate the sensitivity and the tolerance of G. stearothermophilus GF16, MICs toward different antibiotics and heavy metals were determined. For this purpose, the microorganism was grown in the presence of different heavy metals (see Table 1 ) and antibiotics (ampicillin, kanamycin, chloramphenicol, tetracycline, hygromycin, bleomycin). G. stearothermophilus GF16 was found to be sensitive to all the tested antibiotics, even at the lowest concentration used; to the best of our knowledge, no antibiotic resistance has been previously reported for other G. stearothermophilus isolates, although the genome of G. stearothermophilus 10 contains a sequence coding for a putative tetracycline MFS (Major Facilitator Superfamily) efflux protein (locus tag: GT50_RS17520). Interestingly, G. stearothermophilus showed high tolerance to As(V) and V(V), as reported in Table 1 . Similar MIC values were also found in other Geobacilli such as G. stearothermophilus AGH-02 [ 62 ], G. stearothermophilus ASR4 [ 63 ], or Geobacillus kaustophilus [ 64 ]. The high resistance to both vanadate and arsenate ions was not surprising considering the similarity in their structures; in addition, the structural similarity of both ions with the phosphate ions suggested that V(V) and As(V) could be taken up by cells through phosphate transport systems [ 65 ]. As for other aerobic microorganisms [ 66 ], arsenic resistance within the Geobacillus genus relies on the ability to oxidize arsenite, or to reduce arsenate and extrude the arsenite. In particular, As(III) resistance depend on membrane or periplasmatic oxidase activities [ 67 ], while resistance to As(V) mainly involves intracellular reductase activities [ 68 ] and membrane transporters for As(III) efflux [ 69 ]. Since we measured very low tolerance to As(III) ( Table 1 ) in comparison to the values reported in the literature (1.9 mM versus 10–30 mM) [ 62 , 63 , 64 ], it can be hypothesized either that our isolate lacks arsenite oxidase activity or that the high sensitivity to As(III) is due to the absence of active transport systems for As(III) efflux. For example, the legume symbiont Sinorhizobium meliloti was very tolerant to As(V) but very sensitive to As(III) since it was deficient of As(III) transporter systems [ 65 , 70 ]. The new isolate was also found to be Cd(II) tolerant, and in this case the MIC value determined was similar to that measured in other Geobacilli (ranging from 0.4 to 3.2 mM) [ 71 ]. For the majority of these microorganisms Cd(II) resistance was ascribed to biosorption, i.e., a phenomenon of metal binding to the microbial cell wall, which does not involve energy consumption [ 72 , 73 ]. Interestingly, the Pisciarelli site is enriched in arsenic and vanadium but lacks cadmium (see Section 3.1 ). Therefore, the presence of genetic determinants for Cd(II) tolerance cannot be traced back to the selective pressure exerted by the environment. Figure 3 shows the effect of As(V) on G. stearothermophilus GF16 growth: the generation time shifted from 30 min for cells grown in the absence of As(V) to 60 and 125 min for those grown in the presence of As(V) 25 and 50 mM, respectively. As we only observed a high As(V) resistance, we sought to evaluate whether G. stearothermophilus GF16 had any As(V) reductase activity; for this purpose, an AgNO 3 colorimetric method [ 47 , 74 , 75 , 76 ] was employed on cells grown on LB-agar supplemented with As(V), using as controls plates of: (1) LB-agar with As(V) and no cells; (2) LB-agar without As(V) and with grown cells; (3) LB-agar without cells and As(V) ( Figure 4 ). The method is based on the formation of colored precipitates upon reaction of AgNO 3 with arsenic; in particular, the addition of AgNO 3 to the grown cells produces a brown precipitate (Ag 3 AsO 4 ) if AgNO 3 reacts with As(V) and a bright yellow precipitate (Ag 3 AsO 3 ) if AgNO 3 reacts with As(III) [ 47 , 74 , 75 , 76 ]. Therefore, the addition of As(V) to the growth medium implies that As(III) can be revealed only if it is produced inside the cell and extruded afterward. Moreover, as can be seen from the reference color scale in Figure 4 E, the solution is clearly yellow only when As(III) is more than 50% of the total arsenic. Figure 4 A shows a brown precipitate, indicating that As(V) was the predominant chemical species outside the cells. The negligible amount of extracellular As(III) detected within this experiment, suggested either that G. stearothermophilus GF16 had low As(V) reductase activity or could not efficiently extrude As(III). This latter hypothesis might be consistent with the lack or low activity of As(III) efflux systems. However, to confirm these hypotheses, more sensitive experimental approaches such as Inductively Coupled Plasma Mass Spectrometry (ICP-MS), able to detect lower amounts of As(III), are required. 3.4. Bionformatic Analyses To the best of our knowledge, the genomes of only three strains of G. stearothermophilus GF16 have been fully sequenced ( Table 2 ): (1) strain “10” isolated from the Yellowstone hot spring (USA); (2) strain “DSM458” isolated from a sugar beet factory in Austria [ 77 ]; and (3) strain “B5” isolated from a rice stack in China. As shown in the phylogenetic tree, these strains are evolutionarily very closely related to the GF16 isolate ( Figure 2 ). In order to verify whether different strains of G. stearothermophilus had arsenic and cadmium resistance systems and to understand whether such systems were conserved among the species, a comparative genomic analysis was carried out on the sequences of three G. stearothermophilus genomes available at NCBI ( Table 2 ). The study revealed differences in the abundance and type of putative arsenic and cadmium resistance genes in the genomes analyzed ( Table 3 ). In particular, all of them contained one conserved copy of cadC and cadA : the alignment of the corresponding proteins from the three different strains showed a high degree of identity (92%). This result could explain the tolerance of the new isolate toward Cd(II) despite the absence of this metal within its specific environment (see Section 3.1 ). Regarding arsenic resistance systems, a copy of ArsB/Acr3 arsenite efflux transporters was found in each genome, whereas at least a simple ars system encoding the arsenate reductase ( arsC ) in tandem with an ArsR/SmtB transcriptional regulator was found only in the genomes of G. stearothermophilus 10 and B5 strains (86% of identity of both proteins). On the other hand, the strain DSM458 encoded a unique arsenate reductase; moreover, sequences coding for putative arsenite oxidases were not observed in any of the genomes analyzed [ 78 , 79 ]. To the best of our knowledge there are no reports of functional studies on metal resistance systems in these three strains, therefore we conclude that additional investigation is required to shed light on the occurrence of common metal resistance mechanisms in G. stearothermophilus isolates. However, the in silico analysis of the genomes showed that the number and type of genes coding for elements involved in arsenic resistance is variable within the same species and depends on the specific evolutionary adaptation of that particular strain [ 80 ]. 3.5. Analysis of Cellular Morphology In order to better define G. stearothermophilus GF16 morphology, we resolved to analyze cells through TEM. As shown in Figure 5 , cells have a typical bacillar rod shape when they are actively growing. Moreover, with the aim of verifying whether As(V) and Cd(II) had any effect on cell morphology, TEM images were also acquired on samples of G. stearothermophilus GF16 grown for 16 h in the presence of As(V) and Cd(II) at concentrations corresponding to the MIC values, and they were compared to images of control cells not subjected to any treatment with heavy metal ( Figure 6 ). The sections obtained revealed the structure of the cell more clearly in the control cells ( Figure 6 A) than in those treated with heavy metals. However, the presence of several cells in division suggested that both As(V) and Cd(II) did not cause significant changes in the cellular structure and cell viability (of Figure 6 B vs. Figure 6 C). Nevertheless, it appeared that the cell wall of G. stearothermophilus GF16 was influenced by handling both As and Cd. In particular, the cell wall of G. stearothermophilus GF16 treated with As(V) ( Figure 6 B) exhibited abundance of ridges and grooves that can be related to a reduction in cell permeability. Interestingly, Cd(II)-treated cells ( Figure 6 C) appeared darker; this phenomenon could be ascribed to the ability of G. stearothermophilus to adsorb Cd(II), as also reported by Hetzer et al. [ 71 ]. In conclusion, electron microscopy analyses highlighted that the cell shape/structure of G. stearothermophilus GF16 changes in presence of As(V) and Cd(II), thus suppling a morphological explanation for the tolerance of the new isolate toward these metal ions."
} | 5,095 |
32338757 | PMC7319469 | pmc | 3,169 | {
"abstract": "Abstract Microbial association networks are frequently used for understanding and comparing community dynamics from microbiome datasets. Inferring microbial correlations for such networks and obtaining meaningful biological insights, however, requires a lengthy data management workflow, choice of appropriate methods, statistical computations, followed by a different pipeline for suitably visualizing, reporting and comparing the associations. The complexity is further increased with the added dimension of multi-group ‘meta-data’ and ‘inter-omic’ functional profiles that are often associated with microbiome studies. This not only necessitates the need for categorical networks, but also integrated and bi-partite networks. Multiple options of network inference algorithms further add to the efforts required for performing correlation-based microbiome interaction studies. We present MetagenoNets, a web-based application, which accepts multi-environment microbial abundance as well as functional profiles, intelligently segregates ‘continuous and categorical’ meta-data and allows inference as well as visualization of categorical, integrated (inter-omic) and bi-partite networks. Modular structure of MetagenoNets ensures logical flow of analysis (inference, integration, exploration and comparison) in an intuitive and interactive personalized dashboard driven framework. Dynamic choice of filtration, normalization, data transformation and correlation algorithms ensures, that end-users get a one-stop solution for microbial network analysis. MetagenoNets is freely available at https://web.rniapps.net/metagenonets .",
"introduction": "INTRODUCTION Microbial ecosystem is inherently complex owing to the plurality of the microbes residing under the inter-play of various confounding factors or environmental conditions ( 1 ). Metagenomics, the study of genomic material acquired from environmental samples, which targets microbial DNA to decipher taxonomic and functional attributes of collected samples, has obtained a significant boost with the advent of next- generation sequencing technologies ( 2 ). Obtaining structural or compositional insights into various microbial assemblages has always remained one of the primary objectives of most metagenomic studies ( 2 ). However, another question that interests the microbiome researchers pertains to microbial community dynamics, i.e. how various microbes correlate or associate with each other in a metagenomic environment under study ( 3 , 4 ). Even though multiple strategies are available for mining microbe-microbe associations, e.g. evidence based relationship mining and function driven associations ( 4–6 ), a commonly used microbial interaction mining approach aims at probing correlations between the occurrence (abundance) profile of microbes detected in an environment ( 6 ). Such networks are therefore also termed as co-occurrence networks and are frequently employed in metagenomic research studies ( 7 ). However. given the complexity of microbial ecosystems and technical aspects associated with network/graph theory approaches, researchers often face multiple challenges in performing a meaningful network analysis ( 8 ). These challenges may be classified into three groups: Lengthy workflow for microbial network analysis A typical workflow for network inference generally involves (a) abundance data filtration to remove spurious or irrelevant features ( 4 , 9 ), (b) choosing from multiple data normalization and transformation strategies to account for inter-sample biases, confounding factors, compositionality etc. ( 10 , 11 ), (c) choosing among multitude of correlation inference methods to derive network files (correlation matrix, adjacency matrix, edge-lists etc.) ( 4 ), (d) employing graph theory algorithms to compute network characteristics (like global network properties, local centrality measures etc.) using the said network files ( 12 , 13 ) and (e) use a visualization tool to view the the networks ( 14 ). Meta-data introduces additional complexity Availability of comprehensive meta-data associated with metagenomic studies puts an additional layer of complexity to the problem of inferring and probing microbial association networks ( 15 ). For a given environment, there can be multiple levels of meta-data groups or categories (like geography as an environment can have countries as groups). This gives rise to a need for individually processing networks for each of such groups. In addition, quite often continuous meta-data (like BMI, age) are also collected, and researchers are therefore interested in probing correlations of microbial abundances with such continuous data points (or covariates) as well ( 15 , 16 ). Inter-omic data further increases complexity It is not uncommon for metagenomic studies to have one or more ‘associated’ inter-omic abundance profile ( 16 , 17 ). For example, a shotgun metagenomics study can not only provide the researchers with microbial abundance profile, but also the abundances of various functional units (like enzymes, GO, COG, genes etc.). Related inter-omic studies on same set of samples (like transcriptome profile) can also become a closely associated inter-omic data. The inferred functions for 16S studies are another example of inter-omic profile associated with microbial abundance datasets. Availability of such secondary datasets often lead to the requirement of mining correlation of microbes with such inter-omic units (like functions, genes etc.). The outcomes of such correlations are often visualized in the form of ‘inter-omic integrated networks’ and 'bi-partite networks’ ( 17 , 18 ). The process of achieving the same for each meta-data category (and corresponding group) is therefore expected to be complex and tedious. For example, for a population of samples collected from various body sites of healthy individuals as well as those affected by a disorder, following questions pertaining to a typical microbial community dynamics study may stand relevant: What are the microbial co-occurrence patterns specific to healthy and affected individuals? What are the association patterns specific to individual body sites in healthy as well as affected individuals? How do these networks compare in terms of the interactions and various network properties? Is there any correlation between the occurrence of certain microbes with age or BMI or weight or any other 'continuous' trait of the individuals in all/any category of network? Given a metabolic profile of the given samples, is there any association between the occurrence of a microbe or a group of microbes with the profile of a metabolite or a group of metabolites of interest? Many of these questions enthuse researchers and finding answers to them requires concerted efforts. In the current state of the art, a typical study on microbial correlation networks requires dependency on stand-alone generic softwares, plugins, locally installed programs as well as knowledge of advance programming ( 19–21 ). Limited number of available web-applications are either too specialized for other research areas or offer minimal functionalities ( 22–24 ). Furthermore, currently there is a lack of webservers which allow inter-omic correlation network analysis and meaningful visualization to address such questions. Table 1 provides a comprehensive comparison of the scope and features of various tools in the network biology space (including those specifically used for microbiome research) in the current state of the art. Table 1. Comparison of the scope and key features of various tools in the network biology space (including those specifically used for microbiome research) in the current state of the art. Links to access the tools have been provided in the last column of the table \n \n We present MetagenoNets, a web-based modular framework, developed with the aim of easing the process of inferring and analyzing correlation driven microbial association networks. Following features of MetagenoNets are expected to be of significant value addition in the space of microbiome network analysis: Accepts small to large microbial feature tables (occurrence or abundance profile) along with multi-level meta-data. Provision for secondary feature tables (like functional profile) allows deeper insights for an integrated analysis. Offers frequently used data normalization strategies and transformation methods. Provision for feature reduction through prevalence and occurrence-based filters. Availability of correlation driven network inference methods frequently used by researchers. Intelligent categorization of meta-data into categorical and continuous data types. Provision for categorical, integrated and bi-partite network generation and visualization. Interactive visualizations for all networks, network properties and correlation scores. Compositional comparison of categorical networks through interactive Venn diagrams. Registration independent personalized dashboard system for privacy, traceability, collaboration.\n\nMeta-data introduces additional complexity Availability of comprehensive meta-data associated with metagenomic studies puts an additional layer of complexity to the problem of inferring and probing microbial association networks ( 15 ). For a given environment, there can be multiple levels of meta-data groups or categories (like geography as an environment can have countries as groups). This gives rise to a need for individually processing networks for each of such groups. In addition, quite often continuous meta-data (like BMI, age) are also collected, and researchers are therefore interested in probing correlations of microbial abundances with such continuous data points (or covariates) as well ( 15 , 16 ).",
"discussion": "DISCUSSION Network analysis is commonly used in microbiome research. However, researchers need to follow a lengthy workflow to perform even a simple correlation analysis and visualization. Need for inter-omic association mining using the secondary datasets or co-variates in the meta-data, further complicates the process of inferring the correlations and generating meaningful visualizations. We have developed MetagenoNets, a web-based application, to reduce the time and effort needed to conduct such analyses. The inclusion of multiple algorithms and data management methods in this tool enables the researchers to explore and employ appropriate strategy suitable to the nature of their data (and associated meta-data). In addition, the provision for multiple interactive visualization techniques and real time choice of algorithms in the framework of a modular workspace, ensures that the end-users can approach the problem of microbial correlation analysis in a logical progression. Although inter-omic correlation analysis is rather a much needed approach for microbial network analyses, it has rarely been represented in this field. MetagenoNets has made initial attempts in automating the inference and suitable visualization of integrated and bi-partite networks. Future versions of MetagenoNets will focus on expanding the scope of inter-omic correlation mining, apart from expanding the general scope of microbial association mining using microbiome datasets."
} | 2,806 |
29459692 | PMC5818653 | pmc | 3,170 | {
"abstract": "Coral reef ecosystems rely on stable symbiotic relationship between the dinoflagellate Symbiodinium spp. and host cnidarian animals. The collapse of such symbiosis could cause coral ‘bleaching’ and subsequent host death. Despite huge interest on Symbiodinium , lack of mutant strains and readily available genetic tools have hampered molecular research. A major issue was the tolerance to marker antibiotics. Here, we isolated Symbiodinium mutants requiring uracil for growth, and hence, useful in transformation screening. We cultured Symbiodinium spp. cells in the presence of 5-fluoroorotic acid (5FOA), which inhibits the growth of cells expressing URA3 encoding orotidine-5′-monophosphate decarboxylase, and isolated cells that require uracil for growth. Sequence analyses and genetic complementation tests using yeast demonstrated that one of the mutant cell lines had a point mutation in URA3 , resulting in a splicing error at an unusual exon–intron junction, and consequently, loss of enzyme activity. This mutant could maintain a symbiotic relationship with the model sea anemone Exaiptasia pallida only in sea water containing uracil. Results show that the URA3 mutant will be a useful tool for screening Symbiodinium transformants, both ex and in hospite , as survival in the absence of uracil is possible only upon successful introduction of URA3 .",
"introduction": "Introduction The dinoflagellate Symbiodinium spp. are known to sustain a stable symbiotic relationship with cnidarian animals (e.g. coral, sea anemone, jellyfish) by endosymbiosis in the gastroderm (endoderm) cells of host cnidarian animals 1 . Ecologically, Symbiodinium is a key primary producer for sustaining the coral reef ecosystems in the oligotrophic tropical and subtropical ocean, and much of the photosynthetically fixed carbon by symbionts is provided to the host coral 2 . Collapse of the coral-algal symbiosis, which is known as ‘bleaching,’ often leads to death of the host corals, causing destructive damage on the coral reef ecology 2 , 3 . From a taxonomical perspective, although Symbiodinium spp. can be classified into a number of ‘clades’ by means of molecular phylogeny 4 , all these clades lack conspicuous morphological traits applicable for species-level classification. Recently, advances in sequencing technology have revealed the diversity of Symbiodinium across a range of coral reefs and other marine environments. Previous studies suggested that the specificity of the Symbiodinium- cnidarian symbioses was dependent on the size of the algal symbiont 5 , and that the symbiont specificity of corals increased (i.e. fewer Symbiodinium types can be associated with corals) as the host coral grew 6 . On the other hand, no substantial change on the symbiont specificity was observed in the model sea anemone Exaiptasia pallida (formerly Aiptasia sp.) 7 . In spite of the accumulation of genomic and multi-omics information on cnidarian-algal symbiosis 8 , genetic tools for characterizing functions of genes that are involved in such symbiosis are still very limited and not readily available. Two independent studies on gene delivery into the Symbiodinium cells have been published. The first report by ten Lohuis and Miller discusses successful delivery of external DNA molecules using silicon carbide whiskers 9 . Seventeen years later, Ortiz-Matamoros and colleagues reported transient expression of exogenous genes delivered into S. microadriaticum subsp . microadriaticum strain S. KB8, Symbiodinium sp. strain Mf11.5b.1, and the genome-sequenced strain Symbiodinium kawagutii 10 , using polyethylene-glycol with glass beads 11 or the terrestrial bacterium Agrobacterium tumefaciens , which has been widely used for transformation of land plants 12 . However, further elaboration of methods for gene delivery into Symbiodinium cells is clearly needed: No follow-up studies have been published using the methods developed by ten Lohuis and Miller 9 and, although it was shown that transient gene introduction methods used for land plants could also be applicable to Symbiodinium , no stable transformant lines have been reported 12 . Towards developing a genetic tool for the coral symbiotic dinoflagellate Symbiodinium sp., we conducted antibiotic screening experiments and isolated a nutrient (uracil)-requiring Symbiodinium mutant. We show that the cell growth could be switched on and off by replacing the media, and that the growth switching was inducible in and ex hospite .",
"discussion": "Discussion Cnidarian-dinoflagellate symbiosis is one of the well-studied and unique model systems that can be used for examining cellular mechanisms of animal-plant symbiosis 18 , but has not been understood fully at the molecular level. The availability of Symbiodinium strains possessing conspicuous physiological and/or cellular properties enable easy tracking in symbiosis experiments, and could be an ideal genetic tool. As such no such strain has been available until now. In this study we identified a nutrient-requiring mutant strain of Symbiodinium harbouring spontaneous mutations in a gene encoding the uracil synthesis enzyme. We also demonstrated that this mutant can be employed for analysing cellular properties in symbiosis experiments. It is worth noting that the nutrient-requiring mutants, similar to those screened in this study, serve as potentially useful tools for researchers to develop systems for genetic transformation of Symbiodinium . Although gene introduction methods for Symbiodinium have been reported 9 , 11 , 12 , several challenges including low reproducibility, difficulty in isolation, and recovery of actively-growing transformed cells prevent them from being routinely used. The T01 mutant line developed in this study will be a useful tool to examine whether a gene of interest affects the stability of symbiosis by transformation with a construct containing the target gene and wild type URA3 either by fusion or as tandemly arranged genes to complement the uracil-requiring phenotype and not by mere transfection of exogenous DNA. The mutant strains obtained in this study were viable on the medium containing both 5FOA and uracil, which strongly suggests their inability to synthesize uracil due to URA3 gene mutation and/or suppressed gene expression (Fig. 1 ). Sequencing the cDNA confirmed the 9-bp deletion corresponding to 3-amino acids in the T01 mutant (Fig. 2A ). By referencing the Bacillus subtilis URA3 protein structure 17 , the deletion region was predicted to be in the vicinity of a helix containing a lysine residue shown to be important for enzymatic activity (Supplementary Fig. S2B ). This is consistent with the results of the yeast complementation tests (Fig. 4 ), indicating that the mutant URA3 gene sufficiently explains the T01 phenotype and that the spontaneous Symbiodinium URA3 mutant was successfully isolated through the 5-FOA resistance screens. The decreased cell growth rate of T01 compared to wild type strain even in the uracil-replete condition suggested that T01 might have other uncharacterized mutation(s) in the genes associated with growth rate regulation or that a slow growth individual was randomly selected (Fig. 3 ). Once the sexual reproduction cycle of Symbiodinium is fully characterized, further sophistication of algal genetic techniques, e.g. mating, backcrossing, as routinely done in the model green alga Chlamydomonas reinhardtii , will be useful to segregate mutations associated and not associated with the uracil-requiring phenotype and ‘purify’ the mutant strain 19 . Sequence comparison of the genomic DNA of the URA3 gene in T01 and wild type (SSB01) based on the genome database of the reference strain S. minutum Mf1.05b 14 revealed a single nucleotide substitution in an intron (Supplementary Fig. S3 ). A previous genome study 14 suggested that many S. minutum genes, including URA3 , possess divergent atypical exon-intron boundary structures, and that the canonical splicing donor site (GU) and acceptor site (AG) sequences were not necessarily conserved. The intron junction sequence where we identified the nucleotide substitution did not follow the ‘GU-AG’ rule, but was found to be ‘GA-AG’ in the wild type strain. Interestingly, the mutation in T01 had substituted the acceptor ‘AG’ with ‘GG,’ resulting in defective mRNA splicing. The new acceptor was not the first ‘AG’ that was positioned downstream to the original acceptor but the second ‘AG’ (Fig. 2B ). The original and second downstream ‘AG’ were followed by a ‘G,’ in contrast to the first downstream ‘AG’ followed by an ‘A,’ indicating that the splicing junction was probably recognized as ‘GA-AG-G’ including the first nucleotide of the downstream exon. To our knowledge, this is the first study using a splicing variant mutant of Symbiodinium , illustrating the unusual exon-intron boundary recognition functioning in vivo , as had been predicted in the genome analysis 14 . Our results invoke further questions on the evolution and regulation of such uncanonical splicing mechanisms. First, the mechanisms of junction site recognition and determination remain unknown; e.g. the potentially recognizable accepter ‘AGG’ sequence was also located upstream to the original site but was not recognized for splicing 14 . Second, it is still unclear whether the nucleotide sequences are sufficient for determining the junctions or if other factors such as spliceosomal RNA and proteins are involved 20 . Recent advances in high throughput sequencing technology may be helpful in tackling these issues. Accumulating large amounts of transcriptomic and proteomic data from Symbiodinium culture strains and environmental samples can be useful in identifying natural variations in splicing junctions in conserved proteins. This will enable us to estimate how frequently acceptable protein sequence alterations resulting from splicing variations occur 21 , 22 . Biochemical analysis of dinoflagellate spliceosomes as well as genetic transformation system using the Symbiodinium mutant strains developed in this study will also be of great assistance in understanding the evolution of such complex and unusual splicing mechanisms in dinoflagellates. Our co-culture experiments showed that T01 was able to maintain a stable symbiotic relationship with the model sea anemone E. pallida in uracil-containing ASW, as well as the wild type strain (Fig. 5 ), indicating that in T01 the cellular machinery involved in the symbiosis was not impaired. However, the symbiotic status between E. pallida and T01 became unstable when it was cultured in uracil-free medium (Fig. 5A and B ), suggesting that the availability of uracil in the medium was a requisite for sustaining the stable symbiosis. Ten days after depletion of uracil, the symbiosed T01 cells were only sparsely distributed in the anemone body (Fig. 5A ), which appeared to mimic the ‘bleaching’ status 22 , 23 . The unsuccessful symbiosis in the uracil-depleted condition suggested that the supply of uracil from the host to the symbiont was not enough, if any, to sustain the proliferation of the symbiont. Further, with the use of the mutant T01, it is now possible to experimentally ‘switch on and off’ the sea anemone-algal symbiosis by using media containing or lacking uracil, respectively. This has important implications on the relationship between symbiosis stability and the growth ability of the symbiont cell. In the free-living condition, T01 cell cultures showed the significantly increased cell growth depending on the availability of uracil 28 days after the onset of the medium change (Fig. 5C ). Although it is difficult to directly compare the symbiotic and free-living conditions, the uracil-dependent cell proliferation in the free-living condition can explain to some extent how the symbiosis was established in the uracil-dependent manner. A plausible interpretation is that a certain level of cell proliferation is necessary for sustaining symbiosis. Considering that dividing Symbiodinium cells were preferentially expelled from cnidarian hosts 24 , even though a certain number of cells are expelled, their daughter cells can be re-symbiosed with the host after cell division resulting in the expansion of symbiosis if they outnumber the originally expelled cells. In the case of uracil-depleted T01 unable to proliferate without uracil, the number of cells re-entering the host endodermal cells decrease, thereby, leading to loss of algae inside the animal host (Fig. 5 ). It should be noted that, although uracil was not supplied, or if any very limited, from the host to the symbiont in the model sea anemone E. pallida , other cnidarian hosts including corals may have different metabolic properties and are to be examined in future studies. This suggests that, although cautions are needed in interpreting results under less controlled experimental conditions, e.g. in the field or aquarium tank, the mutant strains developed in this study would be useful for studying metabolic interactions between hosts and symbionts, and also for screening host cnidarian species which supply uracil and possibly other basic metabolites to symbionts. Cnidarian-algal endosymbiosis has been an important study model in ecology, genomics and cell biology due to its huge impact on marine ecosystems, especially in tropical and subtropical areas 1 . Previous studies have shown that elevated sea water temperature could lead to the collapse of symbiosis and coral ‘bleaching’ 25 – 27 . Thus, understanding the mechanisms of maintaining stability of symbiosis is key to predicting possible effects of environmental changes on marine ecosystems. To our knowledge, the first mutant strain of Symbiodinium established in this study emphasizes the importance of cell proliferation in sustaining the symbiosis in vivo , and can be used to investigate the molecular mechanisms of the symbiosis in future studies. This will be a powerful tool for Symbiodinium genetics research, and for advancing ‘symbiotic genetics’, through which it is possible to examine what kinds of genes are relevant for establishing stable symbiotic relationships with cnidarian hosts and for using genetically engineered symbiotic algae."
} | 3,582 |
33758029 | PMC8546985 | pmc | 3,171 | {
"abstract": "ABSTRACT The bacterial extracellular matrix forms autonomously, giving rise to complex material properties and multicellular behaviors. Synthetic matrix analogues can replicate these functions but require exogenously added material or have limited programmability. Here, we design a two-strain bacterial system that self-synthesizes and structures a synthetic extracellular matrix of proteins. We engineered Caulobacter crescentus to secrete an extracellular matrix protein composed of an elastin-like polypeptide (ELP) hydrogel fused to supercharged SpyCatcher [SC (−) ]. This biopolymer was secreted at levels of 60 mg/liter, an unprecedented level of biomaterial secretion by a native type I secretion apparatus. The ELP domain was swapped with either a cross-linkable variant of ELP or a resilin-like polypeptide, demonstrating this system is flexible. The SC (−) -ELP matrix protein bound specifically and covalently to the cell surface of a C. crescentus strain that displays a high-density array of SpyTag (ST) peptides via its engineered surface layer. Our work develops protein design guidelines for type I secretion in C. crescentus and demonstrates the autonomous secretion and assembly of programmable extracellular protein matrices, offering a path forward toward the formation of cohesive engineered living materials. IMPORTANCE Engineered living materials (ELM) aim to mimic characteristics of natural occurring systems, bringing the benefits of self-healing, synthesis, autonomous assembly, and responsiveness to traditional materials. Previous research has shown the potential of replicating the bacterial extracellular matrix (ECM) to mimic biofilms. However, these efforts require energy-intensive processing or have limited tunability. We propose a bacterially synthesized system that manipulates the protein content of the ECM, allowing for programmable interactions and autonomous material formation. To achieve this, we engineered a two-strain system to secrete a synthetic extracellular protein matrix (sEPM). This work is a step toward understanding the necessary parameters to engineering living cells to autonomously construct ELMs.",
"introduction": "INTRODUCTION Bacterial cells mold their environment through their extracellular matrix (ECM): a heterogeneous matrix of predominately polysaccharides with a mix of proteins, nucleic acids, and minerals ( 1 ). The autonomously produced ECM is dynamic, and bacteria vary its charge, hydrophobicity, porosity, or other properties to assist the cell with survival in various environments. Biofilm matrices function to facilitate mechanical stress tolerance ( 2 ), nutrient sorption, and both genetic and chemical communication ( 3 – 5 ). By interacting with the environment and controlling mass transfer, the matrix affects morphology, resilience, and interspecies interactions ( 3 , 6 ) of the bacterial community, increasing its overall plasticity. Engineered living materials (ELMs) attempt to mimic aspects of natural systems, including biofilms, and are poised to dramatically impact the fields of soft matter assembly and structural materials by adding abilities such as self-healing, material synthesis, autonomous assembly, and responsiveness ( 7 ). Current synthetic biology tools ( 8 ), such as pioneering work with curli fibers ( 9 – 11 ) and bacterial cellulose ( 12 , 13 ), modulate the endogenous ECM content but are limited in the sequence tunability of the biopolymer in the matrix and do not directly encapsulate individual bacteria, as an extracellular polysaccharide (EPS) layer does. Direct cell encapsulation is largely approached using exogenous addition of polymers and attaching them through adhesive motifs or entrapment ( 14 , 15 ). These approaches lack the autonomous formation of natural biofilms and thus require energy-intensive processing ( 15 , 16 ) and added expense. Thus, there is an unmet need for a self-forming yet programmable bacterial ECM. Limited effort has been made to engineer the EPS layer, mostly because the confounding multistep syntheses of nonlinear polysaccharides ( 17 ) make them difficult to program genetically. A more tractable approach to engineering the supramolecular structure of the ECM is to manipulate its protein content. We hypothesize that this simplification of the ECM to a synthetic extracellular protein matrix (sEPM) would result in more programmable interactions, allowing for tunable three-dimensional (3D) structures. Previous research shows that alterations in the composition of polypeptides with hydrogel-like behaviors, such as elastin or resilin, leads to different material properties ( 18 – 20 ). The protein structure, degree of cross-linking, and number of weak interactions are all variables impacted by the peptide sequence ( 21 , 22 ). In addition, protein-protein interactions can drive highly specific, selective, and even covalent binding, for example, through the SpyCatcher-SpyTag system ( 23 , 24 ). The freshwater bacterium Caulobacter crescentus is emerging as a platform for synthetic biology and ELMs ( 25 – 29 ). This bacterium provides multiple advantages as a chassis: it is genetically tractable, is well characterized due to its intriguing dimorphic life cycle ( 30 ), strongly adheres to surfaces via its holdfast matrix ( 31 ), and has a modifiable proteinaceous surface layer (S-layer) ( 25 , 32 ). In addition, it is oligotrophic and can flourish with minimal nutrients and in cold temperatures ( 33 ). We previously reported the construction of a set of C. crescentus variants ( 25 ), in which we engineered the S-layer protein, RsaA ( 34 , 35 ), to display SpyTag, which is one part of the split-enzyme SpyTag-SpyCatcher system ( 36 ). These strains covalently ligate SpyCatcher-displaying inorganic nanocrystals, proteins, and biopolymers to the extracellular array at high density ( 25 ). With these advantages, C. crescentus is well positioned as a chassis for developing a sEPM. To make the formation of a sEPM autonomous, high-level protein secretion is required. However, secretion of heterologous biopolymers with known material properties has proven challenging for Gram-negative bacteria due to their high aggregation tendency and repetitive sequences ( 37 ). While typically type I secretion systems (T1SSs) are considered to have low titers ( 38 ), the T1SS in C. crescentus has the potential to secrete high heterologous protein titers. The T1SS is endogenously tasked with transporting 10% to 12% of the total cell protein to form the RsaA surface layer ( 39 ), and secretion of heterologous enzymes has been demonstrated ( 40 ). The T1SS is a one-step transport system that consists of an ABC transporter, membrane fusion protein, and outer membrane protein. The hallmark of T1SS substrates is the necessary C-terminal secretion signal. In addition, they typically include RTX domains with the nine-residue consensus sequence GGxGxDxUx, wherein U is a hydrophobic residue, and these domains are usually involved in Ca 2+ binding. As calcium is strictly regulated intracellularly at a level lower than required for these proteins to fold, it is presumed that TISS substrates remain largely unfolded until fully secreted ( 41 ). In C. crescentus , the RsaD-F a,b T1SS transports the 1,026-amino-acid RsaA surface layer protein ( 40 ). This system is unique in that it contains two homologous outer membrane proteins, RsaF a and RsaF b ( 42 ). The RsaA substrate protein contains an 82-amino-acid secretion signal and six occurrences of the RTX domain. However, either the C-terminal 242 or 336 amino acids are required for maximal secretion of protein ( 39 ). In this work, we put forth a new concept that employs an engineered two-strain system to create a bacterially produced sEPM that subsequently covalently coats the bacterial cell surface. We develop C. crescentus strains that use a T1SS to export elastin-like polypeptides (ELPs) or resilin-like polypeptides (RLPs) fused to supercharged SpyCatcher [SC (−) ] at levels up to 60 mg/liter, the highest level reported for a Gram-negative T1SS. We then demonstrate the sEPM by binding purified SpyCatcher (−) -ELP fusion proteins covalently to our engineered SpyTag-displaying strain. Through our secretion efforts, we confirm design guidelines around folding and the isoelectric point required to maximize biopolymer secretion via C. crescentus ’s T1SS. Thus, this work furthers the understanding of type I secretion and the value of C. crescentus as a secretion platform by demonstrating the self-synthesis and self-organization of a rationally designed and tunable synthetic extracellular protein matrix. (This article was submitted to an online preprint archive [ 43 ].)",
"discussion": "DISCUSSION As demonstrated above, we constructed a modular extracellular protein matrix through secretion of hydrogel materials that covalently coat cells. A switch to the supercharged SpyCatcher variant [SC (−) ] enables the extracellular matrix proteins to be secreted via a T1SS at unprecedented levels. Extracellular matrix proteins with hydrogel domains of an elastin-like polypeptide (ELP 60 and ELP 60x ) or a resilin-like polypeptide (RLP 12 ) can be secreted, demonstrating the modularity of our approach. The extracellular matrix protein binds specifically to our engineered RsaA 467 -SpyTag S-layer, enveloping the outermost cell surface and creating a sEPM. In the following, we discuss how our findings impact our understanding of type I secretion in C. crescentus and new routes toward self-coating bacteria and autonomous assembly of engineered living materials. Engineered C. crescentus is a platform for high-level secretion of biopolymers. This work achieved unprecedented levels of biomaterial secretion by a Gram-negative type I secretion system and has the added benefit of being a genome-integrated system, which is more robust than plasmid-based systems ( 59 ). In our research, we discovered that through the switch of SpyCatcher to SpyCatcher (−) , we achieve secretion of heterologous polymer-protein fusions ( Fig. 3B ), accomplishing the highest reported yields (60.3 ± 2.22 mg/liter) of a secreted biopolymer [SC (−) -ELP 60 -336c] by a Gram-negative bacterium ( 38 ) ( Fig. 4B ). We hypothesize that SpyCatcher (−) fusions are required in this system because SpyCatcher (−) remains largely disordered until it partners with SpyTag and the T1SS machinery has a strong preference for unfolded proteins. This hypothesis is further supported by the fact that we are unable to secrete fusions involving the suckerin 19 protein, as it contains structured beta sheets ( 51 , 52 , 60 ). Moreover, our observations that the different polymer-protein fusions vary in secretion yields ( Fig. 4C ) uncovers design strategies for maximizing heterologous protein secretion through C. crescentus ’s T1SS. For instance, SC (−) -RLP 12 -336c is secreted at significantly lower levels than SC (−) -ELP 60 -336c. Previous studies have shown that ABC transport systems, such as the RsaD-F a,b T1SS used herein, have higher secretion yields with proteins with isoelectric points (pIs) lower than 5.5. This pI selectivity is ascribed to the conformational changes of the transport machinery when it interacts with the target protein and the electric potential of cell membranes ( 61 ). While all of the successfully secreted proteins have an overall pI lower than 5.5, the lowest pI being 3.83 for 336c and the highest pI being 5.09 for SC (−) -ELP 60x -336c, the pIs of the hydrogel domains within the full-length proteins vary greatly (see Table S3 in the supplemental material). Thus, we attribute the robust secretion yield of SC (−) -ELP 60 -336c to the ELP 60 domain’s pI of 5.5 and the low secretion yield of SC (−) -RLP 12 -336c to the high pI of 9.91 for the RLP 12 domain. The ELP 60x domain also has a high pI of 10.70, and, accordingly, secretion levels of SC (−) -ELP 60x -336c are lower than those of SC (−) -ELP 60 -336c ( Fig. 4C ). We also postulate that SpyCatcher was able to be secreted ( Fig. 2B ) despite that it is a folded protein because of its low pI of 4.14. This result confirms previous work showing that secretion of ELPs is affected by amino acid sequence, credited to the shift in surface chemistry interactions ( 62 ). Overall, our work corroborates previous efforts regarding high-yield secretion in the T1SS. Therefore, we suggest the following guidelines to achieve high-yield secretion. The target protein should have (i) minimal or, ideally, no regions with secondary or tertiary structure, (ii) an overall pI lower than 5.5, and (iii) individual domains with pIs lower than 5.5. 10.1128/mSystems.00903-20.9 TABLE S3 Isoelectric points of extracellular matrix proteins and individual protein domains. Download \n Table S3, DOCX file, 0.01 MB . Copyright © 2021 Orozco-Hidalgo et al. 2021 Orozco-Hidalgo et al. https://creativecommons.org/licenses/by/4.0/ This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . Our work indicates secreted biopolymers can easily be purified from C. crescentus cultures through anion-exchange chromatography of the extracellular media, without the need for cell lysis. Since C. crescentus secretes few extracellular proteins, there are fewer contaminants to remove from the target protein. These advantages are beneficial for applications where extremely pure hydrogel material is desired without expensive processing, establishing C. crescentus as a powerful chassis for the secretion of different biopolymers. sEPM-forming consortia have applications in biomanufacturing and engineered living materials. We found that the SC (−) -ELP 60 -336c biopolymer binds covalently to the cell surface of our C. crescentus displayer strain via an engineered S-layer array. While there are many reports of cell encapsulation in chemically produced hydrogels ( 14 , 16 , 63 – 65 ), this is the first report of entirely bacterially synthesized covalent layering of hydrogel material on a bacterial cell surface. The use of spontaneously aggregating polymers such as ELP and RLP advances our previously reported two-dimensional (2D) assembly of a biomaterial onto a cell surface ( 25 ) into a 3D material. The potential for direct control over covalent and noncovalent interactions offered by this novel sEPM opens the door for the rational engineering of ELMs capable of self-encapsulation and autonomous assembly ( 7 ), i.e., not requiring intervention, induction chemicals, or applied force. Additionally, such a material could be formed by an oligotroph that does not require complex nutrients due to its high synthetic capacity ( 33 , 66 ), making it a uniquely low-cost, low-effort living material. The functionality and physical properties of these ELMs would also be modular based on the biopolymer design and consortium dynamics. This platform could be applied to streamlined biomanufacturing of complex materials but also chemicals or fuels, as enveloping cells in a hydrogel can assist with cell protection in large-scale production. We recognize however that protein degradation/aggregation events may be a limiting factor for processing and downstream applications, as they may alter the percentage of biomaterial covalently bound or the structure of the hydrogel. Therefore, efforts spent optimizing conditions and identifying increasingly stable protein sequences would be beneficial before proceeding with large-scale material synthesis. In addition to self-encapsulation for biomanufacturing, we suggest this approach has additional benefits for ELMs. First, by localizing the matrix protein to the cell surface, a hydrogel-like biomaterial may assemble under lower solution-phase protein concentrations than is usually reported for the creation of a strong hydrogel. Second, this displayer strain has been engineered in a background strain of C. crescentus that still retains the holdfast matrix at the base of its stalk as opposed to the secretor strain, in which this holdfast is no longer present. This allows for displayer cells to adhere strongly to surfaces and could be used to integrate inorganic materials into a hybrid material, such as for the introduction of orthogonal mechanical or optoelectronic properties ( 14 , 67 ). The holdfast also opens the door to cell patterning through chemical modification of the surface ( 68 ) or layer-by-layer deposition of the ELM through bioprinting ( 69 – 71 ). This hierarchical assembly and cell patterning can lead to mechanical properties found in natural systems such as tolerance of compressive force ( 72 ) or arresting crack propagation ( 73 , 74 ). Third, since the sEPM is self-synthesized, damage to the hydrogel layer can be continually repaired, the material can expand over time, and a small sample of the ELM can nucleate the growth of more material. Fourth, C. crescentus is nonpathogenic, has lower endotoxin activity than E. coli ( 75 ), and was previously developed as a microbicide ( 27 ), making it a safe option for deployment. Fifth, while consortia have been used in only a few ELMs ( 76 , 77 ), they allow for a division of labor between cell types, leading to more complex functionality and increased robustness ( 78 , 79 ). A specific benefit of our two-strain system is that by starting with a single parent species, the cell growth rates are similar and there is no interspecies incompatibility. Upon further engineering control over the cell patterning within the consortia, we also envision usage for this advanced material in self-healing infrastructure, soft robotics, bioremediation, and biomedicine. In summary, we describe the creation of strains that secrete a synthetic extracellular protein matrix and demonstrate the cell-surface attachment of the sEPM. In doing so, we confirmed guidelines for maximal biopolymer secretion via T1SS, including encoding an isoelectric point of ≤5.5 for each domain and the entire protein and limiting folded domains. Similar to a naturally occurring biofilm matrix, our engineered matrix is both composed of hydrogel-forming biomolecules and encodes specific binding to engineered strains. However, our engineered matrix binds through covalent bonds rather than weak interactions ( 3 ), and the matrix composition can potentially be altered to provide emergent properties. This work further develops C. crescentus as a chassis for high-level secretion, demonstrates a sEPM, and takes an important step forward toward creating autonomous ordered ELMs for use in biomanufacturing and advanced materials."
} | 4,658 |
35726119 | PMC9543694 | pmc | 3,172 | {
"abstract": "Abstract Biofilms are promising candidates for sustainable bioprocessing applications. This work presents a rational design of biofilm catalysts by integrating extra‐ and intracellular catalysis systems with optimized substrate channeling to realize efficient multistep biosynthesis. An assembly of four enzymes in a “three‐in‐one” structure was achieved by rationally placing the enzymes on curli nanofibers, the cell surface, and inside cells. The catalytic efficiency of the biofilm catalysts was over 2.8 folds higher than that of the control whole‐cell catalysis when the substrate benzaldehyde was fed at 100 m m . The highest yield of d ‐phenyllactic acid catalyzed by biofilm catalysts under optimized conditions was 102.19 m m , also much higher than that of the control catalysis test (52.29 m m ). The results demonstrate that engineered biofilms are greatly promising in integrating extra‐ and intracellular catalysis, illustrating great potentials of rational design in constructing biofilm catalysts as sustainable supports for whole‐cell catalysis.",
"conclusion": "Conclusion We developed a rational design strategy based on substrate channeling to construct biofilm catalysts, which was achieved by integrating extra‐ and intracellular catalysis systems to optimize the synergistic catalysis of multiple enzymes. An assembly of four enzymes ( Pa TA, Cg TD, Gra FDH2, and d ‐HicDH) in a “three‐in‐one” structure is achieved by rationally placing the enzymes on curli nanofibers, on the cell surface, and inside the cells. The catalytic efficiency of the biofilm catalysts was 2.80 and 1.33‐fold higher than that of the whole‐cell catalysts with the addition of 100 and 140 m m benzaldehyde as substrates, respectively. Furthermore, the highest yield of d ‐PLA catalyzed by biofilm catalysts was 102.19 m m , whereas that of the whole‐cell catalysts was 52.29 m m . The improvement in the catalytic efficiency was attributed to the optimized substrate channeling, which followed the direction of mass transfer from the bulk liquid phase to the intracellular reactions, with extra‐cellular enzymes placed on surface of the cells thereby minimizing the mass transfer resistance. It appeared the prepared biofilm catalysts are far more advantageous than traditional whole‐cell catalysts, indicating the potential of rational design in constructing biofilm catalysts as sustainable supports for whole‐cell catalysis. This work promises a powerful strategy in maximizing catalytic efficiency of complicated multi‐step biotransformations.",
"introduction": "Introduction Complicated biotransformations rely on the synergy of multiple enzymes. \n [1] \n However, coordinating multiple enzymes to achieve highly efficient transformation is highly challenging. \n [1b] \n Intracellular catalysis is limited by the biological environment that is highly regulated for the living system and not necessarily optimized for the reaction efficiency of a specific reaction pathway segment. On the other hand, extracellular catalysis can be engineered to realize intensified reactions but is often challenged with a narrow product scope and harsh conditions that are not compatible with biocatalysts. \n [2] \n In line with this, hybrid biocatalytic systems that promise close interactions between extracellular enzymes and intracellular components may provide a platform that can best integrate the advantages of both systems, which further maximizes the efficiency of complicated biotransformations. \n [3] \n However, closely integrating extra‐ and intracellular catalysis to minimize the mass transfer distance is still a challenge. Especially, substrate channeling formation is a key factor to achieve high catalytic efficiency, which is very different from the traditional combination of free enzymes and whole‐cell catalysts. \n [4] \n Inspiration can be found in Nature, where biofilms stand out as key solutions. Engineered Escherichia coli biofilms, as living bioscaffolds, have attracted attention in the biocatalysis research community because of the programmability and site‐specific assembly of these biofilms. \n [5] \n \n E. coli biofilms are ideal platforms for extra‐/intracellular catalysis because the functionalized curli nanofibers enable precise control of the number and orientation of enzymes at the nanometer scale, and they allow for close interaction with intracellular environments by binding to the E. coli cell surface. \n [6] \n The cell surface provides a place for enzyme localization and acts as an interposition connecting extra‐ and intracellular environments.[ \n 5a \n , \n 7 \n ] Furthermore, the intracellular environment provides a natural place for enzyme catalysis and regeneration of co‐factors. Although E. coli biofilms have been used for extra‐/intracellular catalysis, their use as hybrid systems to maximize the catalytic efficiency of complicated biotransformation goes far beyond that, especially when the spatial arrangement of multienzymes is optimized based on substrate channeling using a rational design strategy. \n [6b] \n \n Engineered E. coli biofilms provide distinct and sequential extra‐/intracellular positions for site‐specific co‐localization of multiple enzymes, which means that enzymes can be rationally positioned at curli nanofibers, cell surfaces, or intracellular environments. Based on the reaction types and enzymatic properties, enzymes requiring high loading or improved stability can be positioned at the curli nanofibers. Enzymes involved in the intermediate reactions can also be placed on the cell surface with improved stability. Furthermore, reactions involving co‐factors must be positioned in an intracellular environment. More importantly, the precise integration of extra‐ and intracellular catalysis at the nanometer scale in E. coli biofilms should follow the direction of mass transfer to guarantee the formation of substrate channeling, thereby maximizing the total catalytic performance. To optimize the synergistic catalysis of multiple enzymes, we investigated a rational design method, which integrates extra‐ and intracellular catalysis using engineered E. coli biofilms. A “three‐in‐one” structure was constructed based on substrate channeling, where four enzymes were spatially placed on the curli nanofibers, on the cell surface, and inside the cells in a layer‐by‐layer manner. The spatial placement of the enzymes within the assembly was designed to follow the substrate channeling required by the reaction cascade and the direction of mass transfer from the bulk liquid phase to the intracellular reactions. This could minimize the mass transfer distance, which was driven by the local concentration gradients. Moreover, the prepared E. coli biofilm catalysts were far more advantageous than traditional whole‐cell biocatalysts in terms of catalytic efficiency, illustrating the potential of rational design for maximizing the synergistic catalysis of multiple enzymes, which can be chosen as sustainable supports for whole‐cell catalysis.",
"discussion": "Results and Discussion Cultivation and verification of functional biofilms formed by the EX10 strain To test the feasibility and potential of the designed E. coli biofilm catalysts as sustainable supports for whole‐cell catalysis, the route for d ‐phenyllactic acid ( d ‐PLA) synthesis reported by Song et al. was used. \n [8] \n \n d ‐PLA is an organic acid widely distributed in honey and fermented foods. d ‐PLA has also shown outstanding antimicrobial activity towards fungi and gram‐positive and gram‐negative bacteria by destroying their cell membranes. \n [9] \n Moreover, they can also be used as chiral monomers for the production of biodegradable poly‐PLA or pharmaceuticals. \n [10] \n Among the synthesis approaches of d ‐PLA, enzymatic cascade biocatalyst is considered as a “green” alternative. \n [11] \n Dehydrogenases have been successfully used for the synthesis of d ‐PLA using phenylpyruvic acid as a substrate, including d ‐lactate dehydrogenase. \n [12] \n Furthermore, researchers have also developed a cascade synthetic route using l ‐α‐amino acids as substrates, where l ‐amino acid deaminase ( l ‐AAD), d ‐hydroxyisocaproate dehydrogenase ( d ‐Hic), and formate dehydrogenase (FDH) were involved. \n [13] \n To further reduce the cost of substrates, Song et al. reported a chiral‐group‐resetting process catalyzed by using four enzymes in cells, applying benzaldehyde and glycine as substrates. \n [8] \n This route was considered as a promising alternative for d ‐PLA synthesis. In the form of catalysts used, purified enzymes, cell‐free extracts, or whole‐cell catalysts have all been examined for cascade synthetic reactions. Especially, whole‐cell catalysis has been attractive because it can provide a natural environment for enzymes and can efficiently regenerate co‐factors. \n [14] \n However, whole‐cell catalysis system cannot always guarantee synergy among the enzymes in a living cell. For example, in the work of Song et al., the catalytic efficiency and yield of whole‐cell catalysts appeared to be low, which was attributed to the existence of bottleneck enzymes and un‐optimized substrate channeling.[ \n 8 \n , \n 15 \n ] The catalytic performance can be improved by rationally engineering the bottleneck enzymes and substrate channeling based on engineered E. coli biofilms, especially by coordinating the advantages of extra‐ and intracellular catalysis. As shown in Figure 1 b, the synthesis of d ‐PLA through the chiral‐group‐resetting process is as follows: (1) C−C bond formation catalyzed by Pa TA (threonine aldolase from Pseudomonas aeruginosa ), (2) atypical deamination catalysed by Cg TD (threonine deaminase from Corynebacterium glutamicum ), and (3) d ‐PLA formation and nicotinamide adenine dinucleotide (NADH) regeneration catalyzed by d ‐hydroxyisocaproate dehydrogenase ( d ‐HicDH) and an FDH from Granulicella mallensis ( Gra FDH2), respectively.[ \n 8 \n , \n 16 \n ] In our rational design (Figure 1 ), Pa TA was assembled on curli nanofibers with high enzyme loading properties because increasing the loading of Pa TA could guarantee a high yield of d ‐PLA.[ \n 6a \n , \n 8 \n ] This process is achieved through the specific recognition of SpyTag/SpyCatcher conjugation pairs.[ \n 6b \n , \n 6c \n ] Cg TD is the main rate‐limiting enzyme, which is displayed on the E. coli cell surface to improve its catalytic stability.[ \n 8 \n , \n 15 \n ] The surface display of Cg TD was then achieved using a truncated ice‐nucleation protein, InaK. \n [17] \n Furthermore, d ‐HicDH and Gra FDH2 are co‐localized inside the cells because they reduce the incompatibility among reactions and facilitate the co‐factor regeneration. More importantly, this design follows the substrate channeling required by the reaction cascade, which follows the direction of mass transfer from the bulk liquid phase to the intracellular reactions. Thus, this design is highly promising for improving the catalytic efficiency and final yield of d ‐PLA by engineering bottleneck enzymes and substrate channeling, as well as maintaining the advantages of extra‐ and intracellular catalysis.\n Figure 1 Rational design and engineering of biofilm catalyst through layer‐by‐layer assembly for d ‐PLA production. (a) Construction of recombinant plasmids for the preparation of biofilm catalysts. The pET21a‐ PaTA‐SpyCatcher was transformed into BL21(DE3) to obtain EX02, and the pET21a‐ CsgB‐CsgA(SpyTag)‐InaK‐CgTD and pACYCDuet‐ GraFDH2‐ d ‐HicDH were transformed into BL21:ΔCsgA to obtain EX10. (b) Schematic diagram of the d ‐PLA production from benzaldehyde and glycine catalyzed by the four enzymes. (c) Illustration of the layer‐by‐layer assembly of the four enzymes on biofilms and their application in d ‐PLA production. Pa TA‐SpyCatcher was assembled on the curli nanofibers through the specific recognition between SpyCatcher and SpyTag; InaK‐ Cg TD was displayed on the cell surface; Gra FDH2/ d ‐HicDH were expressed in cells to achieve the regeneration of NADH and the synthesis of d ‐PLA, respectively. We aim to construct and cultivate functional biofilms formed by EX10 strains that contain curli nanofibers, surface‐displayed Cg TD, and intracellular d ‐HicDH and Gra FDH2 (Figure 1 ). These fractions must be verified through biochemical or microscopic analyses. Furthermore, functional biofilms formed by EX10 can catalyze the synthesis of d ‐PLA (C5) from β‐hydroxy‐α‐amino acids (C3). The formation of curli nanofibers in E. coli biofilms is regulated by the csgBAC and csgDEFG operons, where CsgA is the main structural subunit and CsgB acts as an anchoring protein. \n [18] \n In our previous work, we developed a biofilm display platform based on the csgA ‐deletion strain BL21::ΔCsgA with a chloramphenicol resistance gene. \n [6a] \n For this study, we first eliminated the chloramphenicol resistance gene from the genome, resulting in the BL21:ΔCsgA strain with no csgA and any resistance genes (Figure S1, Supporting Note 1). After the transformation of the two recombinant plasmids into BL21:ΔCsgA, the EX10 strain was obtained (Figure 1 a). Furthermore, after cultivating the recombinant strain EX10 into functional biofilms, the dyeing process [Congo red (CR) and crystal violet (CV)] and microscopic analysis were used to characterize their biochemical and morphological features. \n [19] \n CR is often used to determine the amount of amyloid nanofibers, whereas CV is used to determine the total amount of biomass. As shown in Figure 2 a–d, the binding amount of EX10 biofilms towards CR and CV was much higher than that of BL21:ΔCsgA biofilms, which was attributed to the secretion and assembly of CsgA(SpyTag). Compared to the field‐emission scanning electron microscopy (FESEM) results for BL21:ΔCsgA (Figure 2 e) and EX10 biofilms (Figure 2 f), obvious extracellular masses were observed in the EX10 biofilms. Furthermore, curli nanofibers were imaged in the EX10 biofilms using transmission electron microscopy (TEM) (Figure 2 h), where no nanofibers were bound to the cell surface in BL21:ΔCsgA biofilms (Figure 2 g). These results are consistent with our previous work, which indicated that SpyTag‐modified curli nanofibers were formed in the EX10 biofilms. \n [6a] \n The appreciable curli nanofibers formed in the functional biofilms (EX10) could contribute to the assembly of Pa TA‐SpyCatcher with high enzyme loading.\n Figure 2 Preparation, determination, morphological analysis, and function verification of the functional biofilms formed by the EX10 strain. (a) CV staining of the BL21:ΔCsgA (left) and EX10 (right) biofilms. (b) CR staining of the BL21:ΔCsgA (left) and EX10 (right) biofilms. (c) Total biomass determination by CV staining of the BL21:ΔCsgA (1) and EX10 (2) biofilms. (d) Curli nanofibers determination by CR staining of the BL21:ΔCsgA (1) and EX10 (2) biofilms. (e) FESEM results of BL21:ΔCsgA biofilms with no extracellular masses. (f) FESEM results of the EX10 biofilms with clear extracellular masses. (g) TEM results of the BL21:ΔCsgA biofilms with no curli nanofibers. (h) TEM results of EX10 biofilms with clear curli nanofibers. (i) FESEM result of the EX10 biofilms after incubation with NiSiO 3 nanoparticles. No nanoparticles were immobilized on the cell surface. (j) FESEM results of the EX11 biofilms after incubation with NiSiO 3 nanoparticles. Some nanoparticles were tightly immobilized on the cell surface. The EX11 strains were obtained by transforming pET21a‐ CsgB‐CsgA(SpyTag)‐InaK‐CgTD(His) and pACYCDuet‐ GraFDH2‐ d ‐HicDH plasmids into BL21:ΔCsgA. (k) TEM results of the EX10 biofilms after incubation with NiSiO 3 nanoparticles. No nanoparticles were immobilized on the cell surface. (l) TEM result of the EX11 biofilms after incubation with NiSiO 3 nanoparticles. Some nanoparticles were tightly immobilized on the cell surface. (m) Confocal laser scanning microscopy (CLSM) results of the EX12 biofilms after incubation with mCherry solutions. No red fluorescence was obtained. The EX12 strains were obtained by transforming pET21a‐ CsgB‐CsgA(SpyTag)‐InaK‐CgTD(EFCA) and pACYCDuet‐ GraFDH2‐ d ‐HicDH plasmids into BL21:ΔCsgA. (n) CLSM results of the EX12 biofilms after incubation with mCherry‐InaD solutions. Red fluorescence with high intensity was observed. (o) SDS‐PAGE analysis of the cell lysis of EX10 biofilms: 0, protein marker; 1, the supernatant of cell lysis; 2, the precipitation of cell lysis. FESEM, TEM, and confocal laser scanning microscopy (CLSM) were used to verify the surface display of the InaK‐CgTD. We first synthesized Ni 2+ ‐functionalized SiO 2 nanoparticles (NiSiO 3 ) that could specifically bind to His‐tagged proteins (Figures S2–S6, Supporting Note 2). \n [20] \n After co‐incubation of the functional biofilms and NiSiO 3 nanoparticles, FESEM and TEM showed that NiSiO 3 nanoparticles could bind to the cell surface of the EX11 biofilms, where InaK‐ Cg TD was modified with a His‐tag (Figure 2 j,l). However, EX10 biofilms failed to bind to NiSiO 3 nanoparticles because of the lack of a His‐tag (Figure 2 i,k). Furthermore, InaK‐ Cg TD was modified with EFCA peptide (EX12). \n [6c] \n The EX12 biofilms were separately incubated with two red fluorescent protein (mCherry and mCherry‐InaD) solutions (Figure S7) and the samples were imaged using CLSM. \n [21] \n Red fluorescence was detected in Figure 2 n, but not in Figure 2 m, illustrating the successful display of InaK‐ Cg TD onto the cell surface, which was ascribed to the specific binding between EFCA and InaD. \n [6c] \n From the FESEM, TEM, and CLSM results, we concluded that InaK‐ Cg TD was successfully displayed on the cell surfaces of the EX10 biofilms. Whole‐cell structures can also protect enzymes from inactivation and provide an environment for co‐factor regeneration. \n [14b] \n The SDS‐PAGE analysis was used to determine the expression of Gra FDH2 and d ‐HicDH in the cells, and the results are shown in Figure 2 o. Clear bands with predicted molecular weights were detected, and the expression of Gra FDH2 and d ‐HicDH was further confirmed by purification (Figure S8). The above results indicated that functional EX10 biofilms were successfully prepared, as expected, where InaK‐ Cg TD was displayed on the cell surface and Gra FDH2/ d ‐HicDH was over‐expressed in cells. Immobilization of PaTA‐SpyCatcher onto EX10 biofilms After immobilizing Pa TA‐SpyCatcher (produced by EX02 strains) onto the EX10 biofilms by means of affinity binding between SpyTag and SpyCatcher, the prepared biofilm catalysts could use benzaldehyde (C1) and glycine (C2) as substrates to synthesize C5 (Figure 1 ).[ \n 6c \n , \n 8 \n ] We first determined the function of curli nanofibers in the EX10 biofilms, which meant it was to verify whether the SpyTag‐modified curli nanofibers could specifically bind to the SpyCatcher‐modified proteins. As shown in Figure 3 b, high‐intensity emission from green fluorescence proteins (GFP) was observed under CLSM, indicating the tight binding of GFP‐SpyCatcher (Figure S9b) onto the SpyTag‐modified curli nanofibers. \n [22] \n However, GFP (Figure S9a) could not bind to the curli nanofibers because of the lack of biological conjugation pairs (Figure 3 a). The results indicated that EX10 biofilms had the function to specifically immobilized SpyCatcher‐modified proteins in cell lysis solutions. In other words, EX10 biofilms could directly immobilize and purify Pa TA‐SpyCatcher from EX02 cell lysis solutions without being significantly influenced by other unwanted proteins.\n Figure 3 Function analysis of the curli nanofibers in EX10 biofilms and immobilization of Pa TA‐SpyCatcher onto the EX03 biofilms. (a) CLSM results of the EX10 biofilms after incubation with GFP solutions. Only weak green fluorescence was observed. (b) CLSM results of the EX10 biofilms after incubation with GFP‐SpyCatcher solutions. Green fluorescence with high intensity were determined. (c) Influence of the immobilization time on the enzyme loading of EX03 biofilms. (d) Influence of the concentration of Pa TA‐SpyCatcher solutions on the enzyme loading of EX03 biofilms. Increasing the concentration of Pa TA could also improve the reaction rate. \n [8] \n Thus, the highest loading of Pa TA‐SpyCatcher (Figures S10 and S11) onto the EX10 biofilms was investigated in this section. To avoid the influence of other enzymes on Pa TA‐SpyCatcher loading and activity, EX03 biofilms without InaK‐ Cg TD, Gra FDH2 and d ‐HicDH were cultivated and used as an alternative to EX10 biofilms. As shown in Figure 3 c, from 0 to 9 h, the amount of immobilized Pa TA‐SpyCatcher increased gradually and remained unchanged after 9 h. However, the highest activity was observed at 6 h, and a significant decrease in activity was observed after 6 h. This phenomenon may be ascribed to the blockage of active sites caused by the immobilization of surplus Pa TA‐SpyCatcher. Thus, the optimal immobilization time was set to 6 h. In Figure 3 d, as the concentration of Pa TA‐SpyCatcher solutions increased from 0.5 to 10 mg mL −1 , the activity gradually increased. However, the highest protein loading was observed when the concentration of the Pa TA‐SpyCatcher solutions was 8.0 mg mL −1 , and the highest protein loading was determined as 24.42 mg g −1 EX03 biofilms. The immobilization amount of Pa TA‐SpyCatcher was appealing, which was attributed to the high content of SpyTag‐modified curli nanofibers in the E. coli biofilms (Figure 2 b,d,f,h). The high loading of Pa TA‐SpyCatcher contributed to an improvement in the reaction rate. In 8.0 mg mL −1 solutions, the immobilized activity was 96 % of the highest activity (in 10 mg mL −1 solutions), which was approximately 63.54 U g −1 EX03 biofilms. Finally, in 8.0 mg mL −1 solutions, EX10 biofilms were used to immobilize Pa TA‐SpyCatcher from the solutions for 6 h, resulting in the final biofilm catalysts used for the d ‐PLA synthesis. However, considering that EX10 biofilms contain fewer curli nanofibers than EX03 biofilms, the actual immobilization amount and activity of Pa TA‐SpyCatcher in the EX10 biofilms would be lower than that in EX03 biofilms. Optimization of reaction conditions Reaction conditions are key factors for the enzyme catalysis, especially for improving or balancing the overall activity of cascade reactions. After immobilization of the Pa TA‐SpyCatcher onto the EX10 biofilms, the prepared biofilm catalysts were used to optimize the reaction conditions, where the addition amount of benzaldehyde was maintained at 100 m m . Cg TD is a PLP‐dependent aldolase, where PLP acts as an activator by binding to the active site of Cg TD. \n [23] \n As shown in Figure 4 a, the addition of PLP had no significant effect on the production of d ‐PLA, and the highest yield of d ‐PLA was obtained when 140 μ m of PLP was added. Furthermore, HCOONH 4 acted as a hydrogen donor for the NADH regeneration, which had a significant effect on the synthesis of d ‐PLA (Figure 4 b). The highest yield of d ‐PLA at 24 h was observed when the concentration of HCOONH 4 was 60 m m , and higher concentrations of HCOONH 4 decreased the total transformation speed. However, although the yield of d ‐PLA at 100 m m HCOONH 4 was lower (88.76 %) than that at 60 m m HCOONH 4 at 24 h, we maintained the optimal concentration of HCOONH 4 at 100 m m to guarantee the complete transformation of substrates, that is, the ratio of HCOONH 4 to benzaldehyde was maintained at 1 : 1. Figure 4 c shows that the addition of NAD + facilitated the synthesis of d ‐PLA, and a higher concentration of NAD + contributed to a higher transformation speed. However, for economic considerations and further comparison, the final concentration of NAD + was set to 1 m m , as previously reported. \n [8] \n As shown in Figure 4 d, when the ratio of glycine to benzaldehyde was lower than 4 : 1, the yield of d ‐PLA increased as the ratio increased. However, when the concentration was higher than 4 : 1, d ‐PLA production was limited. Thus, the optimal ratio of glycine to benzaldehyde was determined to be 4 : 1. Moreover, reaction buffers with higher concentrations provide a more stable reaction environment, and their influence on the d ‐PLA production is shown in Figure 4 e. The highest yield of d ‐PLA (100 %) was observed when the concentration of potassium phosphate buffer (KPB) was 50 m m and increasing the concentration of KPB decreased the production of d ‐PLA. We finally set the concentration of KPB to 100 m m (99.78 %) to improve its buffering ability and make it more suitable for the transformation of substrates with higher concentrations. Tween 80 often acts as an emulsifier for substrate dissolution, and its influence on d ‐PLA production is shown in Figure 4 f. Without the addition of Tween 80, the production of d ‐PLA was the lowest, which was attributed to inadequate contact between the enzymes and substrates. The optimal addition of Tween 80 was determined to be 0.05 % for significant improvement in d ‐PLA production. It is worth pointing out that we used Tween 80 (0.05 %) to replace DMSO (10 %) in the reaction system, because organic solvents with high concentrations easily influence the catalytic activity and stability of enzymes, thus further reducing the yield of products. \n [8] \n \n Figure 4 Optimization of reaction conditions. (a) Influence of the PLP concentration. (b) Influence of the HCOONH 4 concentration. (c) Influence of the addition of NAD + . (d) Influence of the ratio of glycine to benzaldehyde. (e) Influence of the concentration of reaction buffers. (f) Influence of the addition of Tween 80. The optimal reaction conditions were as follows: 140 μ m PLP, 1 : 1 ratio of HCOONH 4 /benzaldehyde, 1 m m NAD + , 4 : 1 ratio of glycine/benzaldehyde, 0.05 % Tween 80, and KPB (pH 8.0, 100 m m ). Synthesis of d ‐PLA In this section, biofilm catalysts were compared with whole‐cell catalysts to investigate whether the rational design of biofilm catalysts could obtain higher transformation efficiency and yield while maintaining the advantages of whole‐cell catalysts. The prepared biofilm catalysts were used to synthesize d ‐PLA under optimal reaction conditions. The conversion curves of benzaldehyde with the addition of 50 mg mL −1 wet biofilm catalysts (approximately 10 mg mL −1 dried biofilm catalysts) are shown in Figure 5 a. When the benzaldehyde concentration was 10 m m , the conversion rate of benzaldehyde was as high as 99.9 % in 9 h, which was far more efficient than the 85 % in 36 h reported by Song et al. \n [8] \n Even when the concentration of benzaldehyde was increased to 100 m m , the conversion rate of benzaldehyde reached 98.84 % in 36 h. However, in the report by Song et al., 90 m m benzaldehyde was added to the reaction system in two batches, which was attributed to the inhibitory effect of the substrates. Their results differed from how our prepared biofilm catalysts had a higher tolerance towards substrates with high concentrations. When the concentration of benzaldehyde was more than 100 m m , the highest conversion rates were only 88.91 and 68.13 % at concentrations of 120 and 140 m m , respectively. We also prepared whole‐cell catalysts for d ‐PLA production, and the yield of d ‐PLA with 100 m m benzaldehyde is shown in Figure 5 b. This result showed that the highest yield of whole‐cell biocatalysts was only 29.67 m m in 60 h, while the highest yield was identified as 78.25 m m in 48 h using the biofilm catalysts. Furthermore, the transformation efficiency of the biofilm catalysts (0.0594 μmol h −1 mg −1 ) was 2.80‐fold higher than that of the whole‐cell catalysts (0.0212 μmol h −1 mg −1 ), which might be ascribed to the formation of substrate channeling through the layer‐by‐layer assembly (Figure S12a). Moreover, we increased the addition of whole‐cell biocatalysts to investigate whether d ‐PLA production could be improved, as shown in Figure 5 c. The addition of 100 mg mL −1 of whole‐cell catalysts improved the yield of d ‐PLA to 45.65 m m . However, the transformation efficiency and yield were still far lower than those of biofilm catalysts, illustrating the advantages of using biofilms to assemble multiple enzymes.\n Figure 5 \n d ‐PLA synthesis catalyzed by the biofilm and whole‐cell catalysts. (a) Conversion curve of benzaldehyde catalyzed by 50 mg mL −1 biofilm catalysts. (b) Comparison of the yield of d ‐PLA catalyzed by biofilm and whole‐cell catalysts (50 mg mL −1 ). (c) Change in the d ‐PLA yield after increasing the addition of whole‐cell catalysts. An improvement of 31.1 % was determined when the addition of whole‐cell catalysts increased from 50 to 100 mg mL −1 . (d) Conversion curve of benzaldehyde catalyzed by 150 mg mL −1 biofilm catalysts. (e) Comparison of the yield of d ‐PLA catalyzed by biofilm and whole‐cell catalysts (150 mg mL −1 ). (f) Change in the d ‐PLA yield after increasing the addition of whole‐cell catalysts. To further investigate the potential of biofilm catalysts in d ‐PLA production, 150 mg mL −1 of wet biofilm catalysts were added to the reaction system with an improved concentration of benzaldehyde (Figure 5 d). Increasing the amount of biofilm catalysts significantly increased the transformation efficiency with the addition of 100 m m benzaldehyde. Even when the concentration of benzaldehyde was increased to 140 m m , the conversion rate of benzaldehyde was still up to 97.3 %. However, when the concentration of benzaldehyde was increased above 200 m m , the conversion of benzaldehyde was highly inhibited, with a final conversion rate of no more than 5 % (Figure 5 d). As shown in Figure 5 e, with the addition of 140 m m benzaldehyde, the highest yield of d ‐PLA was 90.66 m m using the biofilm catalysts at 36 h. Compared with biofilm catalysts, the yield of d ‐PLA catalyzed by the whole‐cell catalysts was only 47.89 m m at 36 h. It was worth pointing out that improving the addition of whole‐cell catalysts would not contribute to the production of d ‐PLA (Figure 5 f). More importantly, the catalytic efficiency of the biofilm catalyst (0.0228 μmol h −1 mg −1 ) was still about 1.33‐fold higher than that of the whole‐cell catalyst (0.0172 μmol h −1 mg −1 , Figure S12b). For the determination of d ‐PLA, we only determined the content of d ‐PLA in the supernatant of the reaction system. However, some products may be adsorbed onto the biofilms or kept inside the cells without external secretion, leading to a low d ‐PLA yield. Thus, ethyl acetate was used to extract d ‐PLA in biofilm or whole‐cell catalysts with the determined d ‐PLA contents of 11.53 and 4.40 m m , respectively. The real yield of the d ‐PLA catalyzed by biofilm and whole‐cell catalysts was at least 102.19 and 52.29 m m , respectively. However, this still cannot lead to complete conversion, which is attributed to the metabolic background of E. coli. E. coli strains can convert aldehydes into carboxylic acids or their corresponding alcohols, thus causing loss of the starting substrates. \n [24] \n The produced d ‐PLA was identified by using high‐performance liquid chromatography (HPLC) mass spectrometry (MS) (Figure S13a). A strong quasi‐molecular ion can be observed at m / z 165, which was corresponded to [M−H] + of d ‐PLA. Furthermore, benzoic acid has been identified as a by‐product through this analysis, which was believed resulted from the oxidization of benzaldehyde (Figure S13b). From the results in Figure 5 e, the production of d ‐PLA catalyzed by whole‐cell catalysts did not increase further after 24 h. Combined with the results from Figure 5 e,f, this phenomenon might be ascribed to the effect of product inhibition, thus illustrating a higher product tolerance of biofilm catalysts compared with that of whole‐cell catalysts. For the biofilm catalysts, the transformation efficiency increased as the concentration of benzaldehyde increased from 100 to 140 m m (Figure S14). However, the real‐time yield of d ‐PLA decreased when the concentration of benzaldehyde was increased to more than 140 m m , which might be ascribed to the effect of substrate inhibition (Figure S14). Song et al. reported that when the concentration of benzaldehyde was greater than 50 m m , the catalytic activity of Cg TD was significantly inhibited due to substrate inhibition. \n [8] \n However, this phenomenon occurred only when the concentration of benzaldehyde was increased to 140 m m using biofilm catalysts, which might be ascribed to the substrate tolerance improvement of InaK‐ Cg TD when displayed on the cell surface. Furthermore, when Pa TA‐SpyCatcher was assembled on the curli nanofibers, its catalytic stability significantly improved, which might be another factor that resulted in the high yield of d ‐PLA (Figure S15). The above results clearly indicate that the prepared biofilm catalysts are far more advantageous than whole‐cell catalysts in terms of catalytic efficiency and yield, illustrating the success of rational design in constructing hybrid biocatalytic systems by combining bottleneck enzyme engineering and substrate channeling. The reasons for the improved transformation efficiency and yield were as follows: (1) the substrate channeling formation via layer‐by‐layer assembly to improve the catalytic efficiency; (2) the high content of Pa TA‐SpyCatcher assembled onto the curli nanofibers; (3) the improved catalytic stability of Pa TA‐SpyCatcher after assembly onto the curli nanofibers; (4) the tolerance of InaK‐ Cg TD towards substrates and improved products when displayed on the cell surface; and (5) the layer‐by‐layer assembly enabled the division of reactions to reduce the incompatibility among reactions. Furthermore, we observed that the results obtained by whole‐cell catalysts in our study were more appealing than those in the report by Song et al., which might be ascribed to the changes in reaction conditions. \n [8] \n In particular, Tween 80 (0.05 %) was used to replace DMSO (10 %) to protect the enzymes from organic solvents."
} | 8,548 |
38869023 | PMC11210287 | pmc | 3,174 | {
"abstract": "Controlling surface\nmorphology is one of the main strategies\nused\nto tune surface hydrophobic and icephobic properties. Taking advantage\nof coating growth by initiated chemical vapor deposition, random and\nordered wrinkles were induced on a thin film of polyperfluorodecyl\nacrylate (pPFDA) deposited on polydimethylsiloxane (PDMS) to simultaneously\nmodify surface chemistry and morphology. A range of wrinkles of different\nwavelengths were studied, and how the wrinkle characteristics change\nwith varying coating thickness. Ordered wrinkles enhanced hydrophobicity\nmore when compared to random wrinkles, with a noticeable effect for\ncoating thickness on the order of hundreds of nanometers. An insight\ninto the mechanism of surface wrinkling and its effect on freezing\ndelay is also provided, and promising results were found on ordered\nwrinkles, where a freezing delay was observed.",
"conclusion": "Conclusions Our study focuses on\niCVD and has been\nused for the enhancement\nof hydrophobic properties of PDMS by depositing via iCVD a fluorinated\ncoating with a wrinkled pattern. The use of ordered wrinkles resulted\nin better performance than random wrinkling, and controlling the wavelength\nand height of wrinkles allowed for higher water contact angles at\nlower thicknesses of coating. A crucial finding in our study is the\nidentification of a threshold value that enhances the hydrophobic\nproperties of samples, thereby minimizing the required chemicals for\nthe process. Moreover, iCVD proved to be a suitable instrument for\nhighly tunable and controllable synthesis. A correlation between wrinkling\nparameters and thickness of the deposited layer was found, and it\nwas also possible to calculate the energy involved in the system wrinkle-water\ndroplet adapting the Cassie–Baxter theory. Through the analysis,\nit was proven that achieving thicknesses greater than 200 nm did not\nimprove substrate properties, in terms of hydrophobicity and freezing\ndelay. A decrease in the effect of wrinkling was observed when the\ncoating thickness exceeded a certain value, as for the 600 nm coated\nsample, because the higher the film thickness, the more distant were\nthe wrinkles, resulting in a faster loss of the Cassie–Baxter\nstate. Wrinkles were stable at low temperatures, and freezing delay\nexperiments showed an increase in the freezing time, with a maximum\ndelay of 200 s observed for 300 nm thick coatings. Even though these\nare still preliminary results, they show that wrinkling holds promise\nfor improvement also of the icephobic properties of PDMS.",
"introduction": "Introduction Over\nthe last few decades, research has\nfocused on studying wrinkling\nin both naturally occurring and artificially induced scenarios. Wrinkles\ncan change the properties of the substrate on which they appear, for\ninstance affecting the mechanical properties of a material or its\nconductivity. 1 − 3 In general, wrinkles enhance the surface area, which\ncan be beneficial to enhance transport phenomena in a variety of applications:\ne.g., micropatterning was found to affect the dissolution rate in\ndrug release. 4 Within the context\nof surface wetting, wrinkles with the right\ngeometrical characteristics can be used to induce the so-called Cassie–Baxter\nstate. When the Cassie–Baxter state is induced, the hydrophobicity\nof the surface is enhanced. A surface is considered hydrophobic when\nthe water contact angle measured for a water droplet deposited on\nit is above 90°. 5 Values above 150°\nfor the water contact angle have been observed when inducing the Cassie–Baxter\nstate, along with a hysteresis value ranging from 5 to 10°, thereby\nreaching the so-called superhydrophobic state. 6 , 7 The\nCassie–Baxter state can be described as a state in which a\ndrop has low contact with the substrate, touching the top of surface\nasperities and with air pockets limiting the contact between the surface\nand droplet. 8 This is why this state is\nalso known as the fakir state . Although the Cassie–Baxter\nstate is a metastable state, susceptible to transition to the Wenzel\nstate, it can be obtained in special conditions, where the surface\nis patterned. An example of this is the induction of the Cassie–Baxter\nstate through the presence of a micropattern distributed across the\nsurface, such as in the case of micropillars. 9 , 10 Wrinkles potentially represent a suitable configuration to obtain\nthe Cassie–Baxter state 11 and so\nto enhance hydrophobicity. Until now, it has been widely accepted\nthat wrinkles can appear in substrates of varying magnitudes, depending\non the characteristics of the substrate involved, as discussed by\nRodríguez-Hernández. 10 Wrinkles\nform when the top layer expands at a rate faster than that of the\nlayer beneath it. In general, wrinkling can be understood as an out-of-plane\nsurface bending that occurs due to instability under compression,\ninduced by any parallel or perpendicular force above a certain stress\nthreshold. 12 With these ideas in mind,\nwe want to focus on the random and controlled wrinkling induced by\ndepositing a thin polymer film via initiated chemical vapor deposition\n(iCVD). iCVD is a versatile method to deposit polymer thin films because\nit has the advantage of being a completely dry process and it can\nbe tuned to a high degree. 13 Gleason et\nal. 14 managed to induce a controlled wrinkling\non a thin polymeric film of two combined monomers, ethylene glycol\ndiacrylate and 2-hydroxyethyl methacrylate, deposited on polydimethylsiloxane\n(PDMS) via iCVD. Random wrinkles were also obtained by a previous\nwork of our group exploiting iCVD to form poly- N -vinyl\nCaprolactam thin films on Eudragit surface. 15 Wrinkling has been observed on Teflon layers deposited on various\nplastic substrates, resulting in a durable superhydrophobic state. 16 This finding provides further evidence of the\ninfluence of wrinkles on the Cassie–Baxter state. Moreover,\npatterning induced under an electric field on piezopolymers proved\nthe possibility of controlling the wetting properties. 17 In the present work, we have studied how\ndifferent wrinkle sizes\ncan enhance hydrophobicity and freezing delay of a surface. For this,\nwe induced wrinkling on a thin film of polyperfluorodecyl acrylate\n(pPFDA), deposited on PDMS via iCVD. pPFDA was selected as a coating\ndue to its well-known hydrophobic properties, which arise from the\nabundance of fluorine atoms present in its molecular chains. In general,\nvery high values of water contact angles (>130°) can be measured\non such a material, depending on the degree of crystallinity of the\npolymer. 18",
"discussion": "Results and Discussion The first\ngoal of our study\nwas to understand how the coating thickness\naffects the wrinkle shape. Specifically, we studied the effect of\ncoating thickness on the wrinkle wavelength and height, as it is known\nfrom previous studies that these parameters are directly proportional\nto the coating thickness. 10 In all samples,\nwrinkles were oriented perpendicular to the direction of the applied\nstretching, indicating a consistent pattern ( Figure 2 a). Samples I and II exhibited a comparable\nshape, likely due to their relatively close wrinkle heights. For samples\nIII–V, the distance between wrinkles increased with thickness.\nThis also led to an increase of the wavelengths, as will be discussed\nlater. In Figure 2 a , the second row shows the AFM scans for each sample. Wrinkles\nin samples IV and V presented a double peak, so two wavelengths could\nbe obtained through the 2D-FFT analysis. Differently, for samples\nI–III, only a single wavelength was found. Random wrinkles\nwere observed on PDMS samples that were not prestretched. The shape\nof random wrinkles differs considerably from the ordered wrinkles\non stretched PDMS, as visible in Figure 2 b,c. The wavelength is rather small, ranging\nbetween 1.5 up to 2 μm, and their height closely corresponds\nto the thickness of the deposited coating. However, the measured roughness\nis lower than that found on samples with ordered wrinkles with the\nsame coating thickness. The overall roughness on the surface of the\n200 nm sample with random wrinkles measures 55 ± 5 nm. Figure 2 (a) Optical\nmicroscopy images (first row) and the AFM scans (second\nrow) resulting from the five different coated surfaces are here shown:\n(I) 100 nm, (II) 150 nm, (III) 200 nm, (IV) 300 nm, and (V) 600 nm.\nThe scale bar for the optical microscope images is 20 μm, while\nfor the AFM images, it is 10 μm. In the third row, the 3D scan\nis reported, showing the 3D shape of wrinkles and the different distributions\non the surface due to the change in thickness. On the right angle,\nthe highest value for the height of wrinkles is reported. (b) Optical\nmicroscopy image of random wrinkles on a 200 nm coated PDMS with pPFDA.\nThe scale bar is 20 μm. (c) AFM micrographs of the same surface,\nthe scale bar is 5 μm. (d) Wrinkle wavelength versus coating\nthickness; two different wavelengths were identified: a long wavelength,\nλ long, and a short wavelength, λ short. The long wavelength\nshows the strongest influence from the increase of thickness, while\nthe short wavelength has mostly a constant behavior. Both wavelengths\nare in the range of μm. e. This plot shows the height of wrinkles\nversus coating thickness: the increase is again linear. The plotted\nheights were obtained by averaging the wrinkle heights measured by\nAFM. As shown in the plot in Figure 2 d, the distance between\nthe double peaks\nis described\nby a short wavelength (λ short ), while the distance\nbetween two contiguous double peaks is a long wavelength (λ long ). The short wavelength appeared to be weakly affected\nby the increase in thickness, as it remained approximately constant.\nOn the contrary, the long wavelength was highly enhanced by the thickness,\nreaching a value of almost 16 μm on the 600 nm coated sample. Between the wrinkles, the surface appears uneven, thus leading\nto a difference in roughness over the surface. Nevertheless, the overall\nroughness increased with the coating thickness, as already reported\nin the literature. 20 , 21 Defects and porosity are introduced\ninto a pPFDA coating during synthesis via iCVD, 22 , 23 as the coating becomes thicker. This leads to an increase of surface\nroughness. 24 In Figure 2 e, the\nwrinkle height is shown as a function of the coating thickness. It\nappears that increasing the thickness also leads to an increase in\nthe height of wrinkles, consequently influencing the pattern shape.\nThis was also confirmed by the 3D scan of the surfaces, shown in Figure 2 a , third line. Note that wrinkle height ranges around the coating thickness. Hydrophobicity\nCharacterization To assess hydrophobicity\nand how this is affected by wrinkles, static water contact angle was\nmeasured. 25 , 26 The reference value of water contact angle\nfor uncoated PDMS is 120 ± 2°, measured at a room temperature\nof 25 °C. Therefore, PDMS can already be considered hydrophobic. 27 The water contact angle measured on pPFDA deposited\nover a silicon wafer was 133 ± 2°. The fluorinated polymer\nis highly hydrophobic and highly crystalline when deposited on bare\nsilicon. 26 , 27 Figure 3 a shows the water contact angles measured on the ordered\nand random wrinkles: both the thickness and patterning affected the\nwater contact angle. 28 − 31 The ordered wrinkles resulted in higher static contact angles compared\nto random wrinkles but also slightly higher contact angle hysteresis,\nprobably due to a pinning effect derived from the peculiar shape of\nsurfaces. For the sample with a 100 nm coating and ordered wrinkles,\nthe water contact angle was higher than that of the 300 nm coating\nwith a random pattern. As the coating thickness increased from 100\nto 300 nm, the water contact angle increased to 140°. However,\nthe impact of the ordered pattern diminished when the thickness exceeded\n300 nm. The 600 nm coated sample showed a comparable value to thinner\ncoatings, indicating that the wavelength of wrinkles was too long\nto interact effectively with the water droplet. Higher water contact\nangle values were measured on hierarchical wrinkles on Teflon by Scarratt\net al. 16 Figure 3 (a) Water contact angles were measured\non several samples with\nordered and random wrinkles. The error bars are indicated for each\ndata point in the plot, but sometimes, they are hidden by the symbols.\nAn enhancement in the WCA could be seen already in the 100 nm coated\nsample with ordered wrinkles, in comparison to the random wrinkles.\n(b) Schematic representation of how the Cassie–Baxter theory,\noriginally developed to study systems based on fibers, was adapted\nto a wrinkled system to calculate the areas of interface and the energy\nspent to originate a Cassie–Baxter state. The parameters used\nto describe the fibers (radius, r , and middle distance\nbetween fibers, d ) were related to the parameters\nof wrinkling (long wavelength, λ long , and width, b ). (c) In this plot, the total area values of solid–liquid, f 1 , and solid–air, f 2 , interfaces are represented. (d) The net energy (ED) expended\nin forming unit geometrical areas of interface is plotted with the\nlong wavelength: the shape of wrinkles determines a clustering of\nthe values. The Cassie–Baxter model\nis useful to calculate\nthe nondimensional\narea of solid–liquid and liquid–air interfaces, f 1 and f 2 , in the\nsystem and understand if the Cassie–Baxter state can be induced\nby the morphology of the wrinkles. From the total areas of the interface,\nit is possible to estimate the surface energy required to generate\nthe Cassie–Baxter state. 6 The Cassie–Baxter\ntheory was developed for fabrics, so the equations used to study the\nsystem refer to fabric parameters. In this work, the model was adapted\nto wrinkles as shown in detail in the Supporting Information , Section 2. In Figure 3 b, we show the overlap of wrinkles and fibers\nto define the corresponding approximations. The wrinkles on the samples\nwere characterized by two different wavelengths: a short one and long\none. In the model, only the long wavelength was considered, assuming\nthat only droplets of relatively small dimensions could sit in a Cassie–Baxter\nstate over the double peak of a wrinkle. In the graph shown in Figure 3 c , the total interface areas are shown with the thickness of the coating.\nThe solid–liquid interface area, f 1 , decreases with increasing coating thickness. This area represents\nthe area of interaction between the wrinkles and droplet. At higher\nthicknesses, the distance between wrinkles increases and therefore\nthe contact between the liquid and the wrinkles decreases, leading\nto the presence of air pockets (Cassie–Baxter state) between\ntwo consecutive wrinkles and the droplet. Nevertheless, this effect\ndepends also on the height of the features, a parameter not included\nin the model. However, for the sample with thickness <300 nm, the\nheight-to-wavelength ratio is high enough to ensure that the droplets\nare not sinking into the area between wrinkles. In the case of the\n600 nm sample, this is no more verified, since the droplets were observed\nmainly in the flat area between wrinkles. This scenario is not described\nby the model, which only considers the area of interaction between\nwrinkles\nand droplet. Since the wrinkles are largely apart, the area of interaction\nwith the droplet is small, which should lead to a decrease in the\nWCA. In the measurements for the 600 nm thick sample, though, the\ndroplet sinks between wrinkles, and the Cassie–Baxter theory\nis no more verified. Only a slight increase in the total liquid–air\narea of the interface, f 2 , is observed\nwith the coating thickness. Figure 3 d shows\nthe net expended energy, ED, required to generate or consume interface\nareas as a function of the long wavelength. What influences most the\nentity of ED is the wrinkle shape. Indeed, when the wrinkles showed\nhigher wavelengths (i.e., for the 600 nm thick sample), less energy\nwas needed to generate the interface area. This agrees with the plot\nof f 1 and f 2 : when the wavelength was higher, the solid–liquid area of\nthe interface, f 1 , was lower, and the\nliquid–air interface area, f 2 ,\nwas only slightly increasing. A lower area of the solid–liquid\ninterface was found when there were fewer wrinkles on a specific area\n(e.g., greater wavelengths). Therefore, the net energy expended to\nform the interface area was lower. Two forces act on the droplet\nto keep it suspended between two\nwrinkles: these are the Laplace pressure, which pushes the droplet\ndown toward the surface of the sample, and opposite pressure related\nto the energy barrier to overcome when the Cassie–Baxter state\ntransits to the Wenzel state. Figure 4 a shows the Laplace and energy barrier pressures calculated\nfrom the model as a function of the coating thickness. First, both\npressures are of the same order of magnitude, meaning that the pressure\nexerted by the surface could efficiently contrast liquid penetration.\nA decrease in the Laplace pressure is observed when the coating thickness\nis increased, because of higher wavelengths. The pressure is higher\nin shorter wavelengths. Instead in the 600 nm sample, the energy barrier\npressure equals Laplace pressure. Also, when larger droplets were\ntested, a larger depth of penetration has been calculated ( Figure S2 , Supporting Information ). Since the wavelength is strictly connected to the coating thickness, 10 , 16 the droplet penetration increases with coating thickness. Moreover,\nthe activation energy related to the transition Cassie–Baxter\nto the wet state, for both wavelengths, was calculated and found to\nbe correlated to the thickness. However, while the one related to\nshort wavelength is directly proportional to it, the activation energy\nrelated to long wavelength is indirectly proportional to the thickness,\nas shown in Section 3, Supporting Information in detail. Figure 4 (a) Values for the Laplace and energy barrier pressure\nwere calculated\nfor each sample, considering both wavelengths where possible. Here,\nthey were plotted with the thickness of the coating. (b) The depinning\nforce per unit length could be calculated for each sample; it is related\nto the hysteresis values, which are reported for each sample. Going\nfurther with the thickness of the coating results in a decrease of\nthe depinning force, and the 600 nm coated sample shows characteristics\nsimilar to those of the thinner coated samples. This is because different\nroughnesses are observed in different areas of the sample. (c) Plot\nof the pinning force over the volume of the droplet used during the\ntests, respectively, 3, 4, 5, 7, and 10 μL. An increase in the\ncalculated pinning force is observed with the thickness, finding the\n600 nm coated sample with the highest value. (d) Plot of delay in\nfreezing measured for a droplet at the enhancement of thickness. Results\nare shown for ordered (black) and random (red) wrinkles. Multiple\ndroplets on the surface of 10 μL, T = −30\n°C, 3 cycles were run and averaged. The large error bars are\ndue to inhomogeneities on the PDMS thickness derived from its preparation.\n(e) Images taken during the cooling to −80 °C and the\nheating up to RT at a cooling rate of 15 °C/min. 50× magnification,\noptical microscope, Olympus BX51. Finally, we evaluated the pinning force and force\nneeded to remove\na droplet from the surface; the description is brought on in detail\nin the Supporting Information , Section\n3. The pinning force for the samples with ordered wrinkles is shown\nin Figure 4 c, versus\nthe volume of the droplets. The volume did not affect the entity of\nthe pinning force, while when the thickness increases, the pinning\nforce tends to increase as well. The depinning force ( Figure 4 b) needed to remove the droplet\nfrom the surface depends on the hysteresis. Quantifying this force\ngave information directly on the stickiness to the surface without\nconsidering the dimensions of wrinkling. The calculated depinning\nforce was quite higher than the pinning force, as calculated. Although\nthe 200 and 300 nm coated samples were the best performing with regard\nto hydrophobicity, they showed a greater hysteresis associated with\na higher force needed to remove the droplet from the surface. The\n600 nm coated sample proved once more to behave similarly to the thinnest\nsamples. An explanation was found by measuring the roughness of these\nsurfaces. As previously mentioned, the overall roughness increased\nwith the thickness. On the 100 nm coated sample, the roughness was\nfound to be 35 ± 2 and 37 ± 2 nm on the 150 nm coated sample.\nOn the 600 nm coating, the overall roughness was 93 ± 11 nm.\nThe high standard deviation derives from the inhomogeneity of the\nroughness over the surface. The measured roughness in the region between\nwrinkles was 42 ± 9 nm, and the coating appeared smoother already\nat first glance during the microscope analysis. This value is close\nto those found for the 100 and 150 nm coated samples. Differently,\nfor the 200 and 300 nm coated samples, roughness of 63 ± 3 and\n66 ± 4 nm were respectively measured. Moreover, the lower values\nof hysteresis found on the 600 nm coated sample suggested that the\ndroplet has a favorite position, which is between two wrinkles on\nthe smoother surface. It is noteworthy to mention that the stickiness\nof these surfaces\ncould also be characterized by measuring the roll-off-angle upon tilting\nthe samples. For the case of surfaces with ordered wrinkles, it was\nnoticed that the direction of tilting, either parallel or perpendicular\nto the wrinkle direction, caused differences in the roll-off-angle\ndetermination. Preliminary results on this are shown in Figure S4 , Supporting Information . Analysis of the Behavior toward Freezing and Icephobicity The behavior of the substrates in freezing conditions was investigated\nto understand if wrinkle structures change at low temperatures and\nif water droplet freezing is affected by wrinkles. The goal was to\nassess the substrates icephobicity potential, and specifically assessing\nthe ice nucleation delay. 32 First, we checked\nthat wrinkles preserved their shape even after cooling down to −80\n°C. In Figure 4 e , the 600 nm thick coated sample is shown. No changes\nwere observed in the wrinkle pattern, as the coating appeared unaffected\nby the cooling process. However, during the cooling, it was possible\nto observe the thermal contraction of PDMS. 33 By heating up the substrates to room temperature, the original shape\nwas recovered. A simple observation of the surface through an optical\nmicroscope did not reveal any wrinkle pattern modification. Thus,\nit can also be inferred that there was no change in height as the\nwavelength remained constant. We concluded that the coating is unaffected\nby low temperatures, and changes in the shape of the substrate did\nnot alter it. With respect to water drop freezing, nucleation\nstarted at the air–liquid interface 34 (see the picture in Figure S5a , Supporting Information ). The freezing front propagated\ntoward the bottom of the droplet starting from the outer surface,\nand two phases could be distinguished. This was common among the pPFDA-coated\nsamples: indeed, it was possible to remove the droplets from the surface\nof the substrates since the bottom part had a lower adhesion to the\nsubstrate surface. The experiment was repeated on a pPFDA-coated silicon\nsample, finding that the coating was damaged by the droplet ( Figure S5 , Supporting Information ). Due to the coating stiffness ( E = 2.2–2.4\nGPa) 35 and the rigidity of silicon, the\ndroplet ripped the coating during the freezing process. Figure 4 d shows\nthe effect of wrinkles on the freezing of droplets. Random wrinkles\ncan delay freezing respectively of 36 ± 15 s for the 200 nm and\n48 ± 19 s for the 300 nm coated samples. Although just the presence\nof a pattern helped delaying the freezing, having an ordered pattern\naffects it even more. Observing the results for ordered wrinkles,\nthe delay was above the threshold reached with random wrinkles already\nwith the 100 nm coated sample. The 200 nm coated samples with ordered\nwrinkles showed the highest value of 199 ± 105 s. The damage\non the coating due to droplet removal can be observed\nin Figure S8 , Supporting Information . The experiment was done at room temperature, and\nthe substrate was previously at −18 °C. The droplets had\na volume of 10 μL. Bare PDMS and silicon wafer were tested as\nwell. The force needed to remove ice from the silicon surface with\ntweezers severely damaged the sample: this was expected since silicon\nis hydrophilic 36 and ice sticks to its\nsurface. Instead, with bare PDMS ice could be more easily removed\nwithout damaging the substrate. The pPFDA coating significantly reduced\nice adhesion: simple touching of the frozen droplets with tweezers\nwas enough to promote ice detachment. Iced droplets left round transparent\nareas on every coated sample, meaning that damage occurred. The results\nfrom profilometry proved that a few nanometers of the coating were\nremoved in those areas ( Table S4 , Supporting Information ). The sample with the\n300 nm coating was damaged the most, probably due to its higher hysteresis\nand pinning force."
} | 6,298 |
27555854 | PMC4977305 | pmc | 3,175 | {
"abstract": "Microalgae are currently emerging to be very promising organisms for the production of biofuels and high-added value compounds. Understanding the influence of environmental alterations on their metabolism is a crucial issue. Light, carbon and nitrogen availability have been reported to induce important metabolic adaptations. So far, the influence of these variables has essentially been studied while varying only one or two environmental factors at the same time. The goal of the present work was to model the cellular proteomic adaptations of the green microalga Chlamydomonas reinhardtii upon the simultaneous changes of light intensity, carbon concentrations (CO 2 and acetate), and inorganic nitrogen concentrations (nitrate and ammonium) in the culture medium. Statistical design of experiments (DOE) enabled to define 32 culture conditions to be tested experimentally. Relative protein abundance was quantified by two dimensional differential in-gel electrophoresis (2D-DIGE). Additional assays for respiration, photosynthesis, and lipid and pigment concentrations were also carried out. A hierarchical clustering survey enabled to partition biological variables (proteins + assays) into eight co-regulated clusters. In most cases, the biological variables partitioned in the same cluster had already been reported to participate to common biological functions (acetate assimilation, bioenergetic processes, light harvesting, Calvin cycle, and protein metabolism). The environmental regulation within each cluster was further characterized by a series of multivariate methods including principal component analysis and multiple linear regressions. This metadata analysis enabled to highlight the existence of a clear regulatory pattern for every cluster and to mathematically simulate the effects of light, carbon, and nitrogen. The influence of these environmental variables on cellular metabolism is described in details and thoroughly discussed. This work provides an overview of the metabolic adaptations contributing to maintain cellular homeostasis upon extensive environmental changes. Some of the results presented here could be used as starting points for more specific fundamental or applied investigations.",
"conclusion": "Conclusions Altogether, the present results support that the environmental regulation of the primary metabolism is a multifactorial issue, since nearly all biological variables were found to be influenced by complex superimpositions of linear effects, quadratic effects and/or second-order interactions of the environmental variables. That supports the usefulness of studying regulation in a context where light, carbon and nitrogen are varied simultaneously in the medium, in order to guarantee that the observations are not specific of a particular physiological state. The quadratic effects exerted by nitrate concentration on some components of the machineries for photosynthesis and CO 2 fixation appear to us as particularly interesting. In our opinion, this influence of nitrate would deserve to be further investigated with regard to its possible consequences on primary productivity and industrial biomass yields (potential existence of an optimal nitrate concentration). If combined to omics methods exhibiting higher output levels than 2D-DIGE (gel-free proteomics, microarray, etc.), we think that the present statistical methodology could enable to considerably improve current understanding of systems biology in diverse organisms. In this context, extensive sequential statistical analyses could help dealing with heterogeneous experimental and analytical procedures to unveil hidden information in increasingly large biological data sets.",
"discussion": "Discussion The present work is focused on studying the influence of simultaneous variations of light, carbon and inorganic nitrogen on the cellular proteome of C. reinhardtii . For this purpose, design of experiments (DOE) and sequential multivariate analyses were used to model protein regulation upon overall environmental changes. Proteomic results were completed by additional assays for respiration, photosynthesis, and cellular contents of some lipids and pigments, and the data of these assays were integrated into proteomic results through multivariate statistics. To date, most reported efforts have been focused on studying the effects of one or two environmental variables on photosynthetic metabolism (keeping the other variables constant). Moreover, little information was available in literature concerning the mathematical influence profile of each variable and its relative weight. Over the last decade, a very wide panel of omics-based approaches has been developed to gain deeper understanding of many aspects of cellular biology. With regard to the huge amount of data generated by these techniques, efficient bioinformatics methods of meta-analyses have been developed to reconstitute biological systems. In this context, dealing with data heterogeneity is the key problem (Fukushima et al., 2009 ; Mochida and Shinozaki, 2011 ). The use of multivariate statistical approaches could help solving this problem to some extent, by making possible to perform an overall regulation study with a single experimental design. The present set of sequential multivariate analyses is suitable for the characterization of the environmental regulation of C. reinhardtii metabolism As already described in details, the results of the regression-based initial screening are homogenous for the different spots of proteins with multi-identifications (Additional file 3 ). In the individual MLR models obtained for the selected biological variables, an important proportion of the variability can be explained by light, carbon and nitrogen (Figure 5 , Additional file 10 ). These elements indicate that the screening procedure that we used here is reliable for the present data set. Hierarchical clustering is a key element of the present work that enabled to partition biological variables according to their regulatory similarities. Such a methodology had already been employed by Höhner et al. for the analysis of C. reinhardtii proteomic data to study the response to environmental changes (iron availability and trophic status; Höhner et al., 2013 ). The authors demonstrated that the proteins participating to a common biological function tended to be grouped together. Similarly here, hierarchical clustering enabled to partition biological variables into eight co-regulated clusters corresponding to specific biological processes: Calvin cycle (cluster 1), acetate assimilation (cluster 4), protein synthesis and maturation (cluster 5), anabolic pathways (cluster 6), processes of energy transduction (cluster 7), and composition of the photosynthetic apparatus (cluster 8; Figure 3 , Table 5 ). The observation of such a weak number of clusters is outstanding with regard to the diversity of the environmental perturbations applied here. An overview of the regulation by light, carbon and nitrogen within each cluster was further characterized by PCA, PLSR, and ANCOVA (Figure 4 , Additional file 9 ). These analyses indicated the existence of slight in-cluster differences with regard to the influence of the environmental variables. These observations were particularly marked for clusters 1, 2, 4, 5, and 7, and suggested that subtle regulatory divergences could exist within each cluster despite the existence of a common pattern. These divergences among biological variables were therefore assessed by modeling the influence of light, carbon and inorganic nitrogen through MLR, independently for each protein spot and additional assay. In contrast with PCA and PLSR, these analyses enabled to simulate the mathematical influence profile of each environmental variable by taking into account quadratic effects and second-order interactions (Figures 5 , 6 ). As expected, the differences were much less marked within the clusters than among them, confirming the existence of a clear regulatory pattern unique to every cluster. The present analyses provide deeper insight into the metabolic adaptations set up in response to overall environmental changes Light, carbon, and inorganic nitrogen exert no influence on a series of biological variables associated to specific sub-cellular compartments or biological functions According to the results of the initial regression-based screening, most proteins which are not substantially influenced by light, carbon or nitrogen (Table 4 , Additional file 3 ) seem to belong to discrete sub-cellular compartments or functional groups. On the one hand, as verified by gene set enrichment analysis, this absence of environmental regulation concerns the chloroplastic and vacuolar subunits of ATP synthase. On the other hand, no incidence of light, carbon and nitrogen could be noticed for the glycolytic enzymes nor for the cytoskeleton and flagellar components analyzed here, independently of their sub-cellular localization. Previous studies indicated that light might influence glycolysis by inhibiting pyruvate kinase in C. reinhardtii (Xue et al., 1996 ). As suggested here, this possible light-mediated inhibition of glycolytic activity might not be associated to a significant decrease of the capacity of the pathway. In C. reinhardtii , some subunits of the chloroplastic and vacuolar ATP synthases are also known to be regulated by light through the thioredoxin system (Lemaire et al., 2004 ). This variation of activity does not seem to correlate with a significant modification of protein abundance. Among the functional assays for respiration and photosynthesis, only NPQ 800 did not pass the initial screening (Additional file 4 ). This may be related to the lower ability of C. reinhardtii to set up non-photochemical quenching of chlorophyll fluorescence in comparison with plants (Finazzi et al., 2006 ). Influence of light, carbon, and inorganic nitrogen on the cellular metabolism As shown in Figure 5 , the regulation of most selected biological variables occurs through linear effects of light, acetate, nitrate and ammonium. For CO 2 concentration, the number of significant coefficients ( p ≤ 0.05) is twice lower in comparison with the other variables. Moreover, no cluster-specific regulatory tendency can be distinguished regarding this factor, except in cluster 5 in which there is a positive influence of CO 2 for many biological variables. Remarkably, no influence of CO 2 concentration could be detected here for Calvin cycle enzymes, including RubisCO as already reported at the abundance level (Borkhsenious et al., 1998 ; Mitchell et al., 2014 ). We hypothesize that the weakness of CO 2 influence could arise from two particularities of the experimental design. Firstly, the cellular density in algal cultures was relatively weak at the time of harvest (biomass: 250 μg.mL −1 ). The uptake of CO 2 by algal cells was therefore probably not limited by the rate of CO 2 diffusion in the aqueous phase. In these conditions, the induction of the carbon-concentrating mechanism (CCM) under 350 ppm CO 2 might have been sufficient to buffer the variations of CO 2 levels in the local environment of RubisCO (Moroney et al., 2011 ; Wang et al., 2011 ; Kupriyanova et al., 2013 ). Accordingly, the acclimation of C. reinhardtii cells to low CO 2 has been associated with increased levels of several CCM proteins without modification of the abundance of RubisCO large and small subunits (Mitchell et al., 2014 ). Secondly, the maximal light intensity used here (200 μmol photons .m −2 .s −1 ) is not high enough to induce saturation the photosynthetic electron transport chain (Sueltemeyer et al., 1986 ; White and Critchley, 1999 ). The production rates of NADPH and ATP (rather than the availability of CO 2 ) are therefore likely to constitute limiting factors for the Calvin cycle in the present conditions. Altogether, these different elements might rationalize that huge modifications of CO 2 availability (from 350 ppm to 1.5%) are shown here to induce only slight metabolic adaptations. The features discussed below regarding the influence of light, carbon, and inorganic nitrogen on the cellular metabolism are illustrated in Figure 7 . Figure 7A is for nitrate and ammonium; Figure 7B is for light, acetate and CO 2 . These schemes represent interpretations of our results, mostly related to changes in protein abundance. Figure 7 Metabolic adaptations induced in response to variations of light, carbon, and nitrogen in the medium . These schemes represent interpretations deduced from our results, mostly related to changes in protein abundance. (A) Influence of nitrate and ammonium concentrations. (B) Influence of light intensity and carbon availability (acetate and CO 2 ). The postulated effects of the environmental factors are colored in blue and pointed out by bold arrows surrounded by specific symbols describing the type of influence: + and – are for linear profiles whereas concave and convex shapes are for quadratic profiles. CETC, chloroplastic electron transport chain; Fd, ferredoxin; G-3-P, glyceraldehyde-3-phosphate; LHC, light-harvesting complex. Influence of nitrate and ammonium As shown in Figure 5 , nitrate and ammonium exert a significant influence on biological variables related to carbon metabolism (Calvin cycle, glyoxylate cycle, gluconeogenesis) and processes of energy transduction (respiration, photosynthesis, light harvesting; see also Table 5 ). The predominant regulatory nitrogen form and its mathematical influence profile are specific for each pathway: for example, light-harvesting antennae components (cluster 8) are regulated by nitrate concentration through a quadratic influence profile, whereas processes of energy transduction (cluster 7) rather depend on the total availability of inorganic nitrogen through negative effects. To date, the influence of nitrate and ammonium concentrations had poorly been investigated, but dramatic effects of nitrogen deprivation on many aspects of biological functions had nonetheless been reported (Plumley and Schmidt, 1989 ; Turpin, 1991 ). Altogether, these data and the present results emphasize that the inorganic nitrogen source is a key factor controlling the energetic balance of the cell. Interestingly, for nearly half of the biological variables, a significant interaction could be detected between nitrate and ammonium concentrations (Figure 5 ). This suggests that the balance between these two forms also exerts a particularly important control on biological processes, probably because of the higher energetic requirements of nitrate assimilation (Fernandez et al., 2004 ). Nitrate quadratically influences the machineries for light-harvesting, photosynthesis and CO 2 fixation: A way to adjust the photo-production of reductant, ATP and carbon skeletons to the assimilation of this N source? The components of light-harvesting antennae (LHC proteins ant pigments in cluster 8) are shown here to be regulated by nitrate concentration through a convex profile with an inflecion point around 12.5 mM (Figures 5 , 6 , Additional file 10 ). Interestingly, several other biological variables related to photosynthesis are controlled by nitrate through a reciprocal concave profile: Calvin cycle enzymes (sedoheptulose-1,7-bisphosphatase, phosphoribulokinase, some spots of RubisCO large subunit), linolenic acid (the most abundant fatty acid in thylakoid membranes), P 800 (the gross photosynthetic O 2 evolution), and some spots of ferredoxin-NADP reductase (Figures 5 , 6 ). These data suggest that certain aspects of light harvesting, photosynthetic electron transport and CO 2 fixation are coordinately regulated by nitrate concentration. Remarkably, the observation of quadratic profiles indicates the existence of an optimal concentration of this factor for photosynthesis. The experimental elements are nevertheless insufficient to rationalize the occurrence of two types of reciprocal quadratic effects. Photosynthesis is an important source of reductant, ATP and carbon skeletons for nitrogen assimilation (Turpin, 1991 ). Consequently, it can be argued that the regulation of photosynthesis by nitrate concentration arises from the need to adjust the rate of reductant, ATP and carbon skeleton production to the rate of nitrate assimilation. That had already been suggested for P 800 in a previous publication (Gérin et al., 2014 ). The data reported here indicate that nitrate-induced adaptations occur at two levels: (i) at the level of the photosynthetic electron transport chain as a way to control the production of reductant and ATP, and (ii) at the level of the Calvin cycle as a way to adjust the rate of carbon skeleton production (Figure 7A ). Such adaptations are likely to contribute to the regulation of the carbon-to-nitrogen balance of the cell under changing nitrate availability in the culture medium. Nitrogen down-regulates pathways contributing to its assimilation at the protein abundance level A recent study reported the proteomic adaptations of algal cells upon changes of ammonium availability in the culture medium (testing of four different concentrations; Lee et al., 2012 ). A drastic increase of the abundance of several TCA cycle enzymes (citrate synthase, isocitrate dehydrogenase, α-ketoglutarate dehydrogenase, succinate dehydrogenase, malate dehydrogenase) and of glutamine synthetase could be detected while decreasing ammonium concentration. These results were attributed to the need to heighten the capacity for amino acid biosynthesis through the GS/GOGAT cycle and anabolic pathways (requiring organic acids as carbon skeletons) in case of low nitrogen supply (Lee et al., 2012 ). Here the observation that total nitrogen availability (nitrate + ammonium) exerts a negative influence on biological variables involved in mitochondrial catabolism (notably citrate synthase and isocitrate dehydrogenase) and amino acid biosynthesis (argininosuccinate synthase; see cluster 7 in Figure 5 ) is in agreement with this assumption. In line with that previous study, a strong negative influence of ammonium concentration on the abundance of glutamine synthetase could also be detected here (Figure 5 ). The present work further demonstrates that nitrogen influence prevails over the effects of light and carbon for the regulation of TCA cycle and amino acid biosynthetic enzymes at the protein abundance level (no clear regulatory tendency upon changes related to light, CO 2 and acetate, see Figures 5 , 7A ). Influence of light, acetate and CO 2 Light-mediated activation of the calvin cycle does not always correlate to higher protein abundance Calvin cycle enzymes are known to be activated by light through redox mechanisms mediated by the thioredoxin system. That enables to accelerate the turnover of NADPH and ATP when light intensity increases, with a concomitant improvement of CO 2 fixation (Perchorowicz et al., 1981 ; Brooks et al., 1988 ). Remarkably, the data presented here indicate that the thioredoxin activation of Calvin cycle enzymes is not always associated to higher protein abundance levels. Statistically significant coefficients were indeed detected for some enzymes (glyceraldehyde-3-phosphate dehydrogenase, phosphoribulokinase) but in other cases light was not shown to be a regulatory factor (RubisCO large subunit, sedoheptulose-1,7-bisphosphatase, transketolase; Figure 5 ). Accordingly, no major changes of the abundance of RubisCO large and small subunits could be detected during the dark-to-light transition in C. reinhardtii (Mitchell et al., 2014 ). Light had previously been reported to considerably enhance the mRNA levels for sedoheptulose-1,7-bisphosphatase in C. reinhardtii (Hahn et al., 1998 ) but our results indicate that this increase in transcript abundance does not result in higher protein amount. Adaptation to increasing irradiance heightens the capacity to assembly and protect photosystem ii reaction centers The quantum yield of photosystem II under saturating light (φPSII 800 ) was partitioned in the same cluster (n°5) as the components of the machinery for protein synthesis and maturation (Figure 3 , Table 5 ). In this group, biological variables are positively influenced by light, acetate and CO 2 (Figure 5 ). Interestingly, increasing light irradiance is known to accelerate the turnover of the D1 protein of photosystem II as a way to replace photo-damaged reaction centers (Schuster et al., 1988 ). In this context, the chloroplastic heat-shock protein 70B has been suggested to participate to both the protection and repair of the reaction centers (Schroda et al., 1999 ). Here the observation that φPSII 800 and HSP70B are found in the same light-dependent cluster is in agreement with this postulated role of HSP70B. φPSII 800 and P 800 were partitioned in the same cluster, but nonetheless differ from each other regarding the effects of acetate, nitrate and CO 2 concentrations (Figure 5 ). These features might be attributable to the fact that P 800 does not only depend on intrinsic properties of the photosynthetic apparatus, but is also modulated by interactions of photosynthesis with other metabolic pathways (Calvin cycle, photorespiration, Mehler reaction, etc.; Badger et al., 2000 ). The molecular mechanisms underlying P 800 environmental regulation are therefore likely to be more complex than φPSII 800 . Heightening the metabolic rate and decreasing the capacities for light and acetate assimilation: a double strategy to limit the harmful effects of excess energy input? In C. reinhardtii , the metabolic rate is known to be stimulated by light, acetate and CO 2 (Sager and Granick, 1953 ; Yang and Gao, 2003 ; Boyle and Morgan, 2009 ). Here data demonstrate that these environmental variables exert a positive influence on the enzymatic machinery for protein synthesis and maturation (Figure 5 ). That could indicate that the capacity for protein turnover is increased in response to light, acetate and CO 2 , possibly as a way to support the higher metabolic rates induced by heightening these variables (Figure 7B ). Conversely, light was shown here to exert a negative influence on some pathways related to carbon assimilation, i.e., acetate metabolism (acetyl-CoA synthetase, glyoxylate cycle, TCA cycle, gluconeogenesis) and light harvesting (indirectly connected to CO 2 fixation through the photo-production of reductant and ATP as substrates of the Calvin cycle; Figure 5 ). In addition, a negative influence of acetate concentration could also be detected for light-harvesting antennae components. For acetate assimilatory enzymes, the influence of this factor occurs indirectly through a negative second-order interaction with light intensity (Figure 5 ). This interaction strengthens the negative influence of light while increasing acetate availability, in such a way that the most important effect of light is observed in case of high acetate concentration (see also Figure 6 ). Accordingly, cross-talk between light and acetate signaling pathways has already been reported to play a key role in the regulation of malate synthase, a specific enzyme of the glyoxylate cycle (Nogales et al., 2004 ). However, varying acetate concentration alone (i.e., without changing light) appears to be insufficient to induce metabolic adaptations of the acetate assimilatory pathways (Figure 5 ). This observation that acetate does not exert a direct control on its own assimilation at the protein abundance level is quite remarkable. The negative influence of light on the capacity of the photosynthetic antennae has long been known to avoid over-reducing the photosynthetic apparatus while increasing irradiance. This adaptation enables to control light energy capture and to prevent the occurrence of oxidative stress within the cell (Falkowski and LaRoche, 1991 ; Teramoto et al., 2002 ). By extension, the aforementioned adaptations related to acetate assimilation and light harvesting (Figure 5 ) could be a way to limit the energy input while increasing the availability of electron sources such as light and acetate. Overall, accelerating the metabolic rate and decreasing the capacities for light and acetate assimilation might be a double strategy enabling to prevent primary metabolism blocking and to limit oxidative damages consequently to increased availabilities of light and acetate (Figure 7B )."
} | 6,134 |
21990612 | PMC3190357 | pmc | 3,176 | {
"abstract": "ABSTRACT Antivirulence drugs disarm rather than kill pathogens and are thought to alleviate the problem of resistance, although there is no evidence to support this notion. Quorum sensing (QS) often controls cooperative virulence factor production and is therefore an attractive antivirulence target, for which inhibitors (QSI) have been developed. We designed a proof-of-principle experiment to investigate the impact of bacterial social interactions on the evolution of QSI resistance. We cocultured Pseudomonas aeruginosa QS-deficient mutants with small proportions of the QS-proficient wild type, which in the absence of QSI mimic QSI-sensitive and -resistant variants, respectively. We employed two different QS-dependent nutrients that are degraded by extracellular (public) and cell-associated (private) enzymes. QS mutants (QSI-sensitive mimics) behaved as social cheaters that delayed population growth and prevented enrichment of wild-type cooperators (QSI-resistant mimics) only when nutrient acquisition was public, suggesting that QSI resistance would not spread. This highlights the potential for antivirulence strategies that target cooperative behaviors and provides a conceptual framework for future studies.",
"introduction": "Introduction Infectious diseases are the second-leading cause of death worldwide and cause significant morbidity. A factor contributing to the prevalence of infectious disease has been the development and spread of resistance to current antibiotics ( 1 ). Despite this alarming trend, research into the discovery of new antibiotics by large pharmaceutical companies has dwindled ( 2 ). Traditionally, antibiotics have been classified by their ability to either kill bacteria (bacteriocidal) or inhibit bacterial growth (bacteriostatic) by targeting functions essential to bacterial viability. While historically effective, this approach imposes selective pressure that results in the evolution of resistant strains ( 1 ). An alternative approach is to develop “antivirulence” drugs that disarm pathogens within their host ( 1 , 3 ). These new compounds would target specific factors essential for successful infection, such as toxin function, toxin delivery, virulence gene regulation, or cell adhesion. The benefits of this approach may be 2-fold: reduction in selective pressure for resistance and preservation of the host microflora. Cell-cell communication or quorum sensing (QS) is one important target for antivirulence therapy because it controls virulence gene expression in many bacterial pathogens ( 4 ). In the opportunistic pathogen Pseudomonas aeruginosa , QS is mediated by diffusible acyl-homoserine lactone (acyl-HSL) signals ( 5 ). Two interconnected pairs of signal synthases and cognate receptors (LasI-LasR and RhlI-RhlR) control the transcription of more than 300 genes, many of which encode virulence factors, including extracellular enzymes, toxins, and secondary metabolites ( 5 ). A number of QS inhibitors (QSIs) have been developed with efficacy against P. aeruginosa QS in vitro and in vivo ( 6 ). In particular, receptor-targeting acyl-HSL analogs such as halogenated furanones have been studied in great detail. However, to this date, there have been no experimental data on the evolution of resistance to antivirulence drugs. Presumably, QSI resistance mechanisms would be similar to those conferring resistance to traditional antibiotics, namely, limited access, efflux, enzymatic inactivation, and target modification. A recent review by Defoirdt et al. suggested that QS proficiency and hence QSI resistance would be selected for in vivo during infection, whenever QS promotes colonization, systemic spread, or immune evasion ( 7 ). However, this opinion does not consider social interactions that take place during QS. \n P. aeruginosa QS coordinates the production of many important extracellular factors that are cooperative “public goods” for the population ( 8 ). Mutants that do not produce these goods, but benefit from them, are considered social cheaters ( 8 , 9 ). Under culture conditions that favor QS, such cheaters emerge in the form of receptor-negative, signal-blind lasR mutants ( 10 ). They invade wild-type populations with negative frequency dependence ( 11 – 13 ). As their proportion increases in a population, their relative fitness decreases as there are fewer cooperators to exploit. In P. aeruginosa , signal-blind mutants are favored over signal-negative mutants because common goods production is much more costly than signal production ( 13 ). These social interactions have generally been investigated with low proportions of cheaters, but the situation is expected to be reversed in the emergence of QSI resistance: if strains evolved resistance and retained infectivity, they would likely become QS-proficient cells in a population of QS-deficient social cheaters. Based on a previous model ( 14 ), we predict that the exploitation of QSI-resistant clones by the QSI-sensitive majority would greatly slow the development of resistance and prevent the enrichment of a QSI-resistant subpopulation. We tested this prediction in the present study."
} | 1,286 |
30112808 | PMC6528610 | pmc | 3,180 | {
"abstract": "Abstract Three anaerobic reactors using pig manure ( PM ), maize straw ( MS ), and a mixture of the two as substrates were compared for archaeal community structure and diversity, and for methanogens response to increased organic loading rate ( OLR , expressed in the mass of volatile solid ( VS )). Methanogenic archaeal richness during codigestion of pig manure with maize straw ( ACE : 2412) was greater than that during the others ( ACE : 1225, 1467) at an OLR of 4 g L −1 day −1 , accompanied by high specific methane yield. Euryarchaeota and Crenarchaeota predominated during overall digestion of different substrates; with relative abundances of 63.5%–99.0% and 1.0%–36.3%, respectively. Methanosarcina was the predominant genus that accounted for 33.7%–79.8% of the archaeal community. The diversity in the PM digester decreased with increase in OLR , but increased in the MS digester. The diversity was stable during the codigestion with increased OLR . The relative abundances of hydrogenotrophic methanogens increased by 2.6 and 2.1 folds; the methanogenic community shifted from acetoclastic to hydrogenotrophic methanogens during digestion of MS , and of the mixture of MS and PM . Canonical correspondence analysis revealed a strong relationship between reactor parameters and methanogenic community.",
"conclusion": "4 CONCLUSIONS High‐throughput sequencing data showed differences in archaeal community; Euryarchaeota and Crenarchaeota constituted the majority community; the relative abundances were approximately 63.5%–99.0% and 1.0%–36.3%, respectively. Methanosarcina , which accounted for 33.7%–79.8%, represented the predominant genus. The richness of archaeal community during codigestion of pig manure with maize straw (ACE: 2412) was greater, the diversity during the digestion of maize straw was higher (Shannon: 3.56). With increase in OLR, methanogenic archaea showed larger shifts in all reactors. A shift from acetoclastic ( Methanosarcina ) to hydrogenotrophic methanogens was observed in the reactors of the mixture or maize straw only; VFA, but not high ammonia concentration, could probably be the reason. Further studies should focus on the unclassified genus during digestion of maize straw.",
"introduction": "1 INTRODUCTION China is a large agricultural country in which abundant biomass resources are generated during agricultural processes. In 2012, 846 million tons of crop residues and 3.21 billion tons of livestock manure were produced; had these wastes been utilized for anaerobic fermentation, their biogas potential would have been 4.23 × 10 11 m 3 (Li, Liu, & Sun, 2016 ). The production of livestock manure was around 3.49 billion tons in 2016 (National Bureau of Statistics of the People's Republic of China, 2017 ; Zhang, Bo, & Geng, 2012 ). It was reported that the total biogas production from these agricultural wastes was 2 billion m 3 , implying that less than 5% of the waste was utilized for biogas production in 2014 (Chen, Cong, Shu, & Mi, 2017 ; Zhang, Yang, & Xie, 2015 ). Worldwide, large amounts of livestock and poultry manure have become concentrated in certain areas over the last few decades, as agricultural land is not sufficient for their recycling via the soil‐plant system. This fact together with the inadequate management of these wastes, has caused serious land, water, and air pollution problems (Chen & Liu, 2017 ; Li, Liu, et al., 2016 ) that have received increased attention from environmentalists, economists, and policymakers (Li, Cheng, Yu, & Yang, 2016 ). Anaerobic digestion (AD), also called biogas fermentation, is an important microbial process for the generation of renewable energy and reduction in environmental pollution; it promotes ecofriendly agricultural land by the application of digester residues simultaneously (Wang et al., 2016 ). In addition, AD has significant advantages over other forms of waste treatment, such as less biomass sludge, minimal odor emissions, and so on (Smet, Van Langenhove, & De Bo, 1999 ; Ward, Hobbs, Holliman, & Jonesw, 2008 ). The characteristics of agricultural waste, such as imbalance in nutrition and high proportion of proteins or lignocellulosic biomass pose a challenge for process engineering. Furthermore, they affect the microbial community involved in AD, since the high concentration of ammonia likely inhibits methanogens activity, and high fiber content can cause blockage of pumps or sinking or floating layers (Munk, Guebitz, & Lebuhn, 2017 ). AD is a complicated microbial process which involves four sequential steps: hydrolysis, acidogenesis, acetogenesis, and methanogenesis. Its performance and stability is strongly related with the microbial community structure. Archaea, especially methanogens, are key players during methanogenesis, thus attracting much attention of researchers (Li, Rui, et al., 2015 ). Methane is produced through hydrogen oxidation and acetate cleavage by hydrogenotrophic and acetoclastic methanogens, respectively (Kim et al., 2014 ). Munk et al. ( 2017 ) evaluated the potential utility of grass silage, which is rich in nitrogen. The result showed that the reactors could be operated stably as sole substrate at low OLR, although the ammonia concentration was high and hydrogenotrophic methanogens were dominant in the thermophilic and mesophilic reactors. Despite some novel findings, these results were very limited. Due to the accumulation of inhibitory intermediates such as volatile fatty acids (VFAs) and ammonia, AD of agricultural waste is more prone to failure at high OLR compared to that at a low OLR. Investigation of the structure and dynamics of microbial community during the process of elevating the OLR should enable elucidation of the syntrophic interactions in AD, which may be used to optimize operational conditions. In this study, the typical agricultural wastes like MS, PM, and mixture of MS and PM were digested in laboratory‐scale completely mixed anaerobic reactors, at different OLR of 2 and 4 g L −1 day −1 for 219 days. Methanogenic community was investigated using high‐throughput sequencing technology. The objective of this study was to compare the structure of methanogenic community in AD with different substrates (PM, MS, and PM+MS), analyze the changes in methanogens due to elevated OLR, and elucidate the link between methanogenic community and reactor performance. It is expected that the results presented herein would enable the optimization of operational conditions in order to achieve high efficiency AD for agricultural applications.",
"discussion": "3 RESULTS AND DISCUSSION 3.1 Bioreactor performance The physical and chemical parameters of the three reactors at different OLRs were shown in Table 2 . These values were the average of every stage. The average specific methane yield (SMY) of R2 (PM and MS) was 218 and 254 ml g −1 day −1 at OLR of 2 and 4 g L −1 day −1 , respectively, which were 7.4%, 10.4%, and 33.7%, 192.0% higher, respectively, compared with that in R1 and R3. This difference could be explained by the optimal C / N ratio of 26 in R2. In R1 (PM), the average SMY at an OLR of 4 g L −1 day −1 reached 230 ml g −1 day −1 , which was 8.0% higher than that at OLR 2 g L −1 day −1 . This was consistent with the report by Bolzonella, Pavan, Battistoni, and Cecchi ( 2005 ) which demonstrated that a higher OLR (up to 4 g L −1 day −1 ) for shorter SRTs (15 days) generated higher methane levels under both mesophilic and thermophilic conditions. However, the value decreased by 46.6% in R3 (MS), this was supported by the research of Zhou et al. ( 2017 ), who reported that biogas yield improved when OLR increased at levels below 2 g L −1 day −1 during AD of rice straw. Table 2 Process parameters of the three reactors used in this study Reactor OLR (g L −1 day −1 ) SMY a (ml g −1 day −1 ) NH 4 \n + ‐N (mg L −1 ) Acetic acid (mg L −1 ) Propionic acid (mg L −1 ) VFAs b (mg L −1 ) VFAs/Alk c \n R1 2 203 ± 18 2,482 ± 65 85.3 15.7 141.0 0.01 4 230 ± 20 4,384 ± 53 608.2 103.0 965.5 0.06 R2 2 218 ± 22 1,572 ± 55 100.1 24.6 149.2 0.02 4 254 ± 10 1,020 ± 33 82.1 4.1 94.4 0.02 R3 2 163 ± 17 1,175 ± 98 49.2 27.2 108.9 0.02 4 87 ± 8 22 ± 3 165.5 59.3 264.2 0.18 \n Note . Values are expressed as average ± SD . a Specific methane yield. b The values of VFAs were shown as acetic acid. c Alkalinity. John Wiley & Sons, Ltd Ammonia is an important nitrogen source for the growth of methanogens as well as a key pH‐stabilizing agent for the neutralization of VFAs. However, high concentration of ammonia inhibit the activity of methanogens (Li, Liu, et al., 2015 ). Ammonia concentration in R1 increased from 2,482–4,384 mg/L, but decreased in R2 and R3 when the OLR increased from 2 to 4 g L −1 day −1 . Particularly in the case of R3, the ammonia concentration sharply decreased to 22 mg L −1 from 1,175 mg L −1 . Except R1 at OLR of 4 g L −1 day −1 , the ammonia concentration was lower than 3,860 mg L −1 , which was reported as the inhibition level for methanogens (Benabdallah El Hadj, Astals, Gali, Mace, & Mata‐Alvarez, 2009 ). It indicated that the C / N ratio of substrate, as well as the OLR, affected the concentration of ammonia. The concentration of VFAs is about 50–250 mg L −1 in a stable anaerobic digester, and the inhibitory concentration is around 1,500 mg L −1 (Khanal, 2008 ). Other studies report that AD didn't fail until up to 10,000 mg/L of acetic acid or butyric acid (Khanal, 2008 ), this large difference may be attributed to the buffer capacity, which maintains the pH at the desired level, as well as to the methanogens’ tolerance to toxic agents such as ammonia. In this study, the VFAs in three reactors changed when OLR was elevated: unlike the observed accumulation of VFAs in R1 and R3, acetate, propionate, and VFAs concentrations in R2 decreased by 18.0%, 83.3%, and 36.7%, respectively, as OLR increased from 2 to 4 g L −1 day −1 , and propionic acid concentration was below the inhibitory threshold value of 900 mg L −1 (Wang et al., 2016 ). The ratio of propionate/acetate is also an indicator of the stability of AD process. A ratio over 1.25 was reported to induce biomethanation process failure (Wang, Wang, Cai, & Sun, 2012 ). In this study, the ratio was under 1.25 over the experimental period. Although the concentration of VFAs in R1 (965.5 mg L −1 ) was more than ten times that in R2 (94.4 mg L −1 ), the system was capable of sustaining its performance since the higher alkaline capacity of manure allows higher OLR without accumulation of VFAs. Cheng and Zhong ( 2014 ) studied the effect of codigestion on biogas production from AD of cotton stalk at a feed‐to‐inoculum ratio of 4:1 and 5% TS concentration of substrates, and determined that the concentration of VFAs was 320 and 3,000 mg/L during the mono‐digestion of cotton stalk and codigestion with PM, respectively. 3.2 Richness and diversity analysis of OTUs A total of 431, 693, and 730 OTUs from R1, R2, and R3, respectively, were obtained based on 97% sequence similarity when OLR was 4 g L −1 day −1 . Venn diagram showed that R1 and R2 had maximum similarity, sharing 218 OTUs, R2 and R3 shared 101 OTUs, R1 and R3 shared 44 OTUs, and 28 OTUs were shared by the three samples (Figure 1 ). Figure 1 Venn diagram of the OTU s in the three samples at OLR of 4 g L −1 day −1 ; unique and shared OTU s among the three samples are based on 97% sequence similarity. The numbers inside the diagram indicate the number of OTU s The diversity estimators for each sample based on a species level of 97% similarity were showed in Table 3 . Rarefaction curves of OTUs profiled the change in archaeal species richness in different feedstock and OLRs (Figure 2 ). R3 showed the highest community diversity, followed successively by R2 and R1, as confirmed by the Simpson and Shannon index (Table 3 ). Although none of the rarefaction curves approached a plateau, the Shannon's diversity index rarefaction curves approached asymptotes, indicating that the sampling depths were sufficient to capture the overall microbial diversities in all six samples (Zhang, Sun, et al., 2015 ). The mixing of different substrates improves the nutrients in the feedstock, thereby increase the growth rate of microbial organisms, and additionally enhances digestion efficiency of the system (Li, Cheng, et al., 2016 ). Anaerobic codigestion of PM with MS (R2) enhances the nutritional balance and reduces the possibility of inhibition induced by lipids and ammonia. Interestingly, when the OLR was elevated, archaeal species richness decreased in R1, increased in R3, whereas that of R2 was relatively stable during the experiment. Table 3 Statistical data for the archaeal community in R1, R2, and R3 at OLR of 4 g L −1 day −1 \n OLR Reactor Shannon ACE Chao 1 Coverage Simpson OTUs Sequences 2 R1 3.06 2048 1562 0.988 0.222 812 31384 R2 3.60 1828 1600 0.989 0.123 836 34281 R3 3.82 2300 1980 0.990 0.088 1082 43986 4 R1 1.41 1225 877 0.994 0.568 431 36624 R2 2.81 2412 1762 0.989 0.168 693 33225 R3 3.56 1467 1233 0.991 0.074 730 33570 John Wiley & Sons, Ltd Figure 2 Rarefaction curves based on OTU s at 97% sequence similarity. Black and red lines represent the samples at an OLR of 2 and 4 g L −1 day −1 , respectively To compare the methanogens community in the three samples at OLR of 4 g L −1 day −1 , the principal coordinates analysis (PCoA) were performed to cluster community. Based on unweighted UniFrac PCoA, the cluster community had the maximum variation in 63.1% (PC1) and 36.9% (PC2) (Figure 3 a). It demonstrated a clear regional reparation, and samples from R1 and R2 tended to cluster together, whereas R3 was clearly different from them. These clustering results suggested that R1 and R2 shared similar methanogens community, which were clearly different from those in R3. Weighted UniFrac PCoA (Figure 3 b) represented that R1 and R3 were grouped together along PC2 which only accounted for 9.8% of the total variations; however, the three samples were separated from each other according to PC1, which accounted for 90.2% of the total variations. Figure 3 Principal Coordinate Analysis ( PC oA): (a) Based on unweighted UniFrac metrics, (b) Based on weighted UniFrac metrics 3.3 The methanogenic archaeal community for different substrates Archaeal community compositions of different substrates at OLR of 4 g L −1 day −1 were compared (Figure 4 ). The majority community detected from the three reactors was classified to the phylum Euryarchaeota and Crenarchaeota . The relative abundance of Euryarchaeota was 99.0%, 84.8%, and 63.5%, and that of Crenarchaeota was 1.0%, 15.2%, and 36.3% in R1, R2, and R3, respectively (Figure 4 a). The findings indicate that maize straw affected the Crenarchaeota levels. Figure 4 Archaeal community compositions at (a) phylum level, (b) class level (c), order level, and (d) genus level at an OLR of 4 g L −1 day −1 \n At the class level (Figure 4 b), Methanomicrobia was predominant in R1 (81.3%), R2 (52.8%), and R3 (50.8%), respectively. Thermoprotei accounted for 15.2% and 36.3%, implying that no other class was affiliated with Crenarchaeota in R2 and R3. Methanobacteria in the three reactors accounted for 17.0%, 31.3%, and 9.6% of the total effective archaeal sequences, respectively. The predominant order was Methanosarcinales , which accounted for 82.2%, 47.0%, and 34.8% in the three reactors. The other two dominant orders were Methanobacteriales and Methanomicrobiales ; Methanobacteriales accounted for 31.3% of total sequences in R2, which was higher than that for R1 (17.0%) and R3 (9.6%). The relative abundance of Methanomicrobiales was 1.1%, 5.8%, and 16.0% in R1, R2, and R3, respectively (Figure 4 c). Although Methanobacteriales and Methanomicrobiales were both hydrogenotrophic methanogens, they showed different correlation pattern with regard to AD performance; Methanobacteriales appeared to play an important role in high loading AD, in contrast to the negative correlation of the Methanomicrobiales to biogas and OLR (Vrieze et al., 2015 ). The SMY of R1 (230 ml g −1 day −1 ), R2 (254 ml g −1 day −1 ), and R3 (87 ml g −1 day −1 ) fitted the correlation pattern of Methanobacteriales and Methanomicrobiales . The relative abundance of unclassified order increased sharply with the addition of MS, from 0.1% (R1) to 15.1% (R2), and finally reached 34.4% in R3 (feeding with MS only). The composition of methanogens at the genus level was further investigated to evaluate the influence of substrate on the archaeal community and biogas production performance (Figure 4 d). Seven genera of methanogens, namely Methanosarcina , Methanospirillum , Methanosphaera , Methanoculleus , Methanobrevibacter , Methanobacterium, and Methanosaeta , were identified in this experiment. In the case of Methanosarcina , which has been often reported as the dominant methanogen in AD, the relative abundance was 79.8%, 41.5%, and 33.7% in R1, R2, and R3, respectively. This result was consistent with the finding that the most abundant sequences (41.1%) belonged to Methanosarcina during the anaerobic codigestion of pretreated wheat straw with cattle manure (Song & Zhang, 2015 ). Unlike that of Methanosarcina , the relative abundance of Methanosaeta was as low as 0.4%, 5.5%, and 1.0% in the three reactors, respectively. Methanosphaera was the second most abundant in R1 (13.1%) and R2 (21.8%). Methanospirillum and Methanobacterium, which were observed only in R3, were the other dominant genera, accounting for 12.6% and 9.4%, respectively. Among methanogens, Methanosarcina and Methanosaeta are well‐known for utilizing acetate for methanogenesis. Methanosaeta is specialized in producing methane by acetate cleavage, whereas Methanosarcina is a relative generalist whose metabolic features are diverse and include both acetoclastic and hydrogenotrophic pathways (Li et al., 2013 ; Liu & William, 2008 ). Compared with Methanosarcina , the relative abundance of Methanosaeta was very low. The great difference in the relative abundances of Methanosaeta (0.4%) and Methanosarcina (79.8%) in R1 may be attributed to their tolerance to high concentrations of toxic ionic agents (ammonia concentration of 4,384 mg L −1 ) due to their ability of growing in aggregates and forming irregular cell clumps. Furthermore, high acetate concentrations favor the growth of Methanosarcina , which requires a minimum concentration of about 60.1 mg L −1 and predominates at acetate concentrations above 234.3 mg L −1 . In contrast, Methanosaeta requires concentrations as low as 0.3 mg L −1 , and not exceeding 140.6 mg L −1 (Liu & William, 2008 ). In this study, the concentration of acetic acid in the three reactors was not in the optimal concentration range for Methanosaeta (though not so for Methanosarcina ) and induced selective proliferation of Methanosarcina (Guo, Wang, Sun, Zhu, & Wu, 2014 ). In addition, the intermittent stirring in completely mixed reactor may be responsible for conferring an advantage to Methanosarcina since Methanosarcina was reported to be frequently predominant in fixed and stirred tank digesters (Liu & William, 2008 ). Other methanogens, such as Methanosphaera , Methanospirillum , Methanoculleus , Methanobrevibacter , and Methanobacterium detected in this study are hydrogenotrophic methanogens. In R1, the relative abundance of acetoclastic methanogens was 80.2%, which was much higher than that of hydrogenotrophic methanogens (total relative abundance was 18.1%); therefore, it can be concluded that acetoclastic methanogens represent a major pathway for the digestion of PM. However, for R2 and R3, the relative abundances of acetoclastic methanogens were 46.9% and 34.8%, and that of hydrogenotrophic methanogens 37.2% and 23.5%, respectively. Therefore, acetoclastic and hydrogenotrophic pathways for methanogens occur at approximately equal extents during the digestion of the PM and MS mixture, or that of MS solely. This result was consistent with the finding that the methane‐producing microbial community is involved in the anaerobic codigestion of pretreated wheat straw with cattle manure and solid state codigestion of kitchen waste, pig manure, and excess sludge (Li et al., 2013 ; Song & Zhang, 2015 ). In addition, a large proportion of archaeal sequences belonging to class Thermoprotei , phylum Crenarchaeota were unclassified, especially in R3 (34.4%); this proportion was approximately equal to that of Methanosarcina (33.7%). Unfortunately, no further data on the predominance of this microorganism were available, owing to the lack of information regarding archaea in recent reports; however, this microorganism may be significant for methanogens, especially for digestion with MS as mono or multiple substrates (Francisci, Kougias, Treu, Campanaro, & Angelidaki, 2015 ). 3.4 The methanogenic archaeal community at different OLRs The genus Methanosarcina represented the predominant phylotype under different OLRs (Figure 5 ), accounting for 33.7%–79.8% of all sequencing reads in the three reactors. In R1, the main change was observed with regard to Methanosarcina and Methanobrevibacter ; the relative abundance of Methanosarcina increased from 65.2% to 79.8%, whereas that of Methanobrevibacter decreased from 18.0% to 3.8%. The hydrogenotrophic methanogens accounted for 31.3% to 18.1%. In R2, although the richness of methanogens showed no obvious change (Figure 2 ); the archaeal community showed a clear shift when OLR increased. The relative abundances of acetoclastic methanogens genera Methanosarcina and Methanosaeta decreased from 50.7% to 10.6% to 41.5% and 5.5%, respectively, whereas that of hydrogenotrophic Methanobrevibacter and Methanosphaera increased from 0.1% to 3.9% to 8.9% and 21.8%, respectively. The relative abundance of Methanoculleus decreased from 9.1% to 5.8%; Methanoculleus has been reported to show high identity with methanogenic archaea in stable anaerobic cellulose‐degrading reactors (Chin, Lukow, Stubner, & Conrad, 1999 ). The total abundance of hydrogenotrophic methanogens increased to 37.2% from 17.7% when OLR was elevated. In R3, the relative abundance of Methanosarcina decreased from 46.9% to 33.7%, that of Methanoculleus decreased from 7.0% to 1.3%, and that of Methanobacterium increased from 0.8% to 9.4%. Methanospirillum , which was also present, showed a relative abundance of 12.6%. The total abundance of hydrogenotrophic methanogens increased from 8.9% to 23.5%. Figure 5 Relative abundance of methanogens 16S rDNA gene sequences of R1 (a), R2 (b), and R3 (c) at OLR of 2 g L −1 day −1 (left) and 4 g L −1 day −1 (right). The sequences showing a percentage of reads below 1.0% in all samples were grouped into ‘Others’ \n Methanosarcina w as predominant in the three reactors, and its advantage in R1 was enhanced with the increase in ammonia concentration from 2,482 to 4,384 mg L −1 . In previous studies (Li, Liu, et al., 2016 ), the stable CH 4 production that accompanies an increase in ammonia level may be explained by the increasing activity of hydrogen‐utilizing methanogens. This is because hydrogenotrophic methanogens are capable of tolerating ammonia concentrations of 6,000 mg L −1 , which is two folds higher than the threshold ammonia concentration for Methanosarcina . In this study, although the ammonia concentration increased strongly, the relative abundance of hydrogenotrophic methanogens decreased from 31.3% to 18.1%, and the SMY increased from 303 to 330 ml g −1 day −1 . Since the inoculum was cultured with high ammonia during AD feeding with PM, the ammonia in R1 (2,482–4,384 mg/L) had no inhibition for Methanosarcina . In addition, acetate has a crucial impact on the presence and relative abundance of acetoclastic methanogens (Yu et al., 2014 ); the acetate concentration in the three reactors was higher than the threshold value that favors the growth of Methanosaeta . With increased in OLR, the relative abundance of Methanosarcina decreased, whereas that of hydrogenotrophic methanogens in R2 and R3 increased by 2.1 and 2.6 folds, respectively. Furthermore, the ratio of acetoclastic/hydrogenotrophic methanogens declined to 1.26 and 1.48 from 3.46 to 5.30, which indicated that the methanogenic pathway apparently shifted from mainly acetoclastic to the coexistence of acetoclastic and hydrogenotrophic methanogens pathways in the system (Goux et al., 2015 ). The coexistence of methanogenic pathways seems necessary for response to perturbation and maintenance of stable process performance (Lerm et al., 2012 ); this was evidenced by the performance of R2, in which the SMY increased by 13.3%, whereas it decreased by 46.6% in R3. 3.5 The correlation between archaeal population and reactor parameters Canonical correspondence analysis (CCA) was used to highlight the influence of altered process parameters on the archaeal community (Goux et al., 2015 ). As shown in Figure 6 , the first and second canonical axes represented 74.6% and 22.5% of variance, respectively. Compared with the OLR, substrate type and ammonia were the biggest influencing factors for the study probably because pig manure contains high amounts of protein. The archaeal community was segregated by substrate, and OLR indicated that substrate type and loading could segregate archaeal community in these anaerobic digesters. OLR2 was distinguished by the second canonical axis from OLR4 in all reactors, and R1 was separated from the other reactors by the first axis; these distinctions suggest that a significant shift in the archaeal community occurred in all reactors (Jang, Kim, Ha, & Park, 2014 ). These results agree with those for the taxonomic distribution of archaeal community (Figure 5 ). Figure 6 Canonical correspondence analysis ( CCA ) of the archaeal community and the operational parameters in the three reactors. Blue vectors represent the influence of the process parameters such as OLR , SMY , substrate type, VFA , and NH \n 4 \n + ‐N; red vectors represent methanogenic archaea identified by high‐throughput sequencing at the genus level. Black points represent the substrate type at different OLR s CCA revealed that substrate, ammonia, and VFA play key roles in determining the community structure; these factors are positively correlated with the abundance of Methanosarcina . On the contrary, the presence of Methanosaeta was negatively correlated with these factors, and with the abundance of Methanosarcina . These findings may be attributed to the greater tolerance of Methanosarcina for ammonia and VFA relative to that of Methanosaeta (Hao et al., 2016 ). The analysis also showed a clear positive relationship between OLR and hydrogenotrophic methanogens; with an increase in OLR, the relative abundance of hydrogenotrophic methanogens increased, whereas that of Methanosarcina decreased in R2 and R3, and the concentrations of ammonia and VFA decreased (Table 2 , Figure 5 )."
} | 6,790 |
37599649 | PMC10467333 | pmc | 3,181 | {
"abstract": "We numerically study the dynamics of a passive fluid droplet confined within a microchannel whose walls are covered with a thin layer of active gel. The latter represents a fluid of extensile material modelling, for example, a suspension of cytoskeletal filaments and molecular motors. Our results show that the layer is capable of producing a spontaneous flow triggering a rectilinear motion of the passive droplet. For a hybrid design (a single wall covered by the active layer), at the steady state the droplet attains an elliptical shape, resulting from an asymmetric saw-toothed structure of the velocity field. In contrast, if the active gel covers both walls, the velocity field exhibits a fully symmetric pattern considerably mitigating morphological deformations. We further show that the structure of the spontaneous flow in the microchannel can be controlled by the anchoring conditions of the active gel at the wall. These findings are also confirmed by selected 3D simulations. Our results may stimulate further research addressed to design novel microfludic devices whose functioning relies on the collective properties of active gels.",
"conclusion": "4. Conclusions To summarize, we have theoretically studied the dynamics of a passive fluid droplet confined within a microfluidic channel whose walls are covered with a layer of an extensile active gel. The physics is mostly controlled by the activity and the orientation of the liquid crystal both in the layer and at the walls. Our results show that, for sufficiently high values of activity, the passive droplet acquires a rectilinear motion lasting over long periods of time caused by the spontaneous flow produced by the active material. If the active gel covers only one wall, at the steady state the droplet attains an ellipsoidal shape, whose rate of deformation increases with the activity. This is due to the asymmetric structure of the spontaneous flow, which exhibits a saw-toothed pattern with a maximum at the interface of the layer. If, in contrast, the active material covers both walls, the flow displays a trapezoidal-like symmetric structure and shape deformations turn negligible. In addition, if the liquid crystal points along opposite directions in the layers, a shear-like profile of the flow is found. These behaviors are also affected by the orientation of the liquid crystal at the wall. Indeed, our simulations suggest that, for a fixed value of activity, the magnitude of the flow (and thus the speed of the drop) increases when the anchoring angle at the wall augments. These findings are confirmed by 3D simulations, although the liquid crystal and velocity field display a more complex structure especially within the active layer, where an undulating flow favours the formation of well-defined bend distortions. In this paper we devise a strategy to control and rectify the trajectory of passive fluid drops confined in an “active” microchannel, in which the necessary work to sustain the motion is extracted from a layer of active material. This result could be in principle extended to active droplets, where maintaining a certain direction of motion remains challenging. Indeed, although an enhanced Brownian motion has been observed in drops containing either a dispersion of bacteria 69,70 or a suspension of motorized microtubules, 16 only recently a controllable propulsion has been realized in active droplets hosted in a nematic environment 52 or activated through a Marangoni-like effect. 35 Our device could be concretely realized by dispersing an extensile fluid (such as microtubule bundles and kinesin or bacterial suspensions) into a water–oil solution, in which the aqueous medium containing the active material wets the walls. To enforce a specific anchoring, the active fluid could be pinned following the protocols adopted for passive liquid crystals, i.e. through mechanical or chemical treatment of the surface. 57,71 Although not discussed in the present study, it would be relevant to investigate how a predetermined anchoring at the fluid interface (where the active gel may either orient tangentially 72,73 or perpendicularly 74 ) would affect the motion of the droplet and the structure of the flow. Finally, it is interesting to discuss some directions of future works. Releasing, for example, the approximation of single viscosity of both fluid components could be a further route to control shape deformations as well as simulate highly viscous drops closely behaving as rigid particles. In this context, the system studied in this work would partially capture the dynamics of a spherical non-deformable particle when the activity is low (as in Fig. 1a–d ) whereas for non-spherical solid objects, such as elliptical ones, the dynamics is expected be more complex since in-plane or out-of-plane rotations could be observed. 75 Likewise, abandoning the restriction of small Capillary numbers would be useful to explore regimes in which breakup events are more likely. While this physics is well understood in passive systems (such as a droplet subject to shear flows 76,77 ), less is known when the rupture would be determined by a spontaneous flow, as well as to what extent this kind of flow would impact on critical Capillary numbers, beyond which no-steady state droplet exists. Our device would also be highly suitable for exploring more complex designs, such as those in which the activity is spatially dependent. One may envisage, for example, a microfluidic channel in which the wall is patterned with separated holes (realized using static phase fields 32 ) containing an active gel which could trigger a hop-like motion of a drop dispersed in the surrounding passive fluid. This may hold an interest for the manufacturing of active energy-saving devices whose functioning relies on reduced amounts of active material.",
"introduction": "1. Introduction The last few years have seen a rapid surge in the study of active matter, which deals with systems composed of self-driven units capable of converting stored energy into systematic movement. 1 Active matter encompasses a large variety of natural and artificial instances, ranging from flocks of birds 2 and school of fishes 3 at the macroscopic scale to suspensions of bacteria, 4 cytoskeletal proteins 5 and self-propelled colloids at the microscopic one. 6 Their inherent non-equilibrium nature results in a wealth of enthralling phenomena, such as spontaneous flows, 7,8 active turbulence, 9,10 anomalous diffusion, 11 superfluid-like behavior 12,13 and motility induced phase separation, 14,15 to name a few. Innovative examples of autonomous systems are synthetic self-propelled droplets, i.e. spatially confined fluid suspensions whose motion is guided by sophisticated modes of propulsion mechanisms which can involve, for example, the use of an active gel confined within. 16–20 Some of the best known experimental realizations of such active materials are actomyosin solutions 21,22 and suspensions of microtubules and kinesin, 7,23 which are soft fluids comprising force dipoles exhibiting a long range orientational order typical of liquid crystals. 24–26 The former is an example of contractile material since the dipolar forces (exerted by the myosin) are directed towards the center of mass, whereas the latter pertains to extensile fluids. From a technological perspective, active gel droplets are gaining significant interest as model systems for studying the dynamics of micro-organisms, such as cells, 27–31 and for designing artificial microswimmers. 32–40 Alongside these objects, an alternative design is represented by the “inverted” counterpart, i.e. passive Newtonian droplets surrounded (partially or entirely) by an active (or passive) gel. 41,42 A number of theoretical and experimental works have demonstrated that the inclusion of micron-sized objects in an active fluid bath often results in a persistent motion induced by a combination of mechanical energy extracted by the surrounding fluid and a careful manufacturing of the object, such as rigid structures with asymmetric boundaries 43–45 or soft deformable ones, like polymeric chains. 46,47 It would then be natural to ask whether similar conditions can be realized in the context of inverted liquid crystals, where a passive drop can be spontaneously set into motion using the energy provided by the external active gel. Indeed, while many efforts have been dedicated to realizing self-motile droplets containing the active material, a much less investigated system is that in which the latter is hosted in the exterior environment. In this paper we consider a microchannel comprising a mixture of an active extensile gel and a passive isotropic fluid, where the former is confined within a thin layer attached to the wall while the latter occupies the rest of the channel and is made of a Newtonian fluid droplet immersed in a second fluid (see Fig. 1a ). With respect to a typical “inverted” design where a passive drop would be fully embedded in an active medium, here the active component is distanced from the drop and occupies only a small portion of the channel. Such a system could be realized in the lab by dispersing self-attractive cytoskeletal gels in a layer of water wetting the wall (following a protocol akin to that discussed in ref. 16 ), while the passive mixture could be produced through usual microfluidic techniques. 35,48,49 Fig. 1 Motion of a passive fluid droplet within an active microchannel, in which an extensile material covers the bottom wall. In (a)–(d) ζ = 2 × 10 −3 , in (e)–(h) ζ = 3 × 10 −3 and in (i)–(l) ζ = 4 × 10 −3 . In all cases, the unidirectional motion of the droplet is caused by the spontaneous flow generated by the active layer. For increasing values of ζ , droplet speed and shape deformations augment. The green arrows indicate the direction of motion. The color bar represents the values of the phase field of both passive and active fluids. We will show below that this geometry is capable of producing a spontaneous flow triggering a unidirectional motion of the passive drop, with a speed strongly depending on the activity. We also find that, if the active layer covers a single wall, the flow propelling the drop displays an asymmetric saw-tooth profile, fostering significant morphological changes for high activities. Alternatively, if the layers cover both walls, the fluid velocity acquires a symmetric profile suppressing droplet deformations. In agreement with previous works, 50 our results also suggest that controlling the orientation of the active gel at the boundaries decisively affects the emerging flow as well as the speed and shape of the droplet. These findings could be relevant for the design of autonomous microdevices able to sort and drive non-motile drops in a predictable manner, a challenging task in active matter especially if the need for keeping a certain direction of motion is required for long periods of time. 51,52 In addition, they may be potentially useful for realizing energy-saving soft systems whose functioning would require a reduced amount of active material (and hence energy) with respect to a fully inverted geometry. 41 The paper is structured as follows. In the next section we shortly describe the theory and some numerical details while in the following ones we illustrate the results. First we discuss the physics of a passive drop plus a single active layer in terms of the structure of the flow and droplet kinematics, and then we move on to the case with two layers. Afterwards, the effect of boundary conditions is described and, before concluding, a selection of 3D results is presented."
} | 2,921 |
38899885 | PMC11267869 | pmc | 3,182 | {
"abstract": "ABSTRACT Purple sulfur bacteria (PSB) are capable of anoxygenic photosynthesis via oxidizing reduced sulfur compounds and are considered key drivers of the sulfur cycle in a range of anoxic environments. In this study, we show that Allochromatium vinosum (a PSB species) is capable of autotrophic growth using pyrite as the electron and sulfur source. Comparative growth profile, substrate characterization, and transcriptomic sequencing data provided valuable insight into the molecular mechanisms underlying the bacterial utilization of pyrite and autotrophic growth. Specifically, the pyrite-supported cell cultures (“py”’) demonstrated robust but much slower growth rates and distinct patterns from their sodium sulfide-amended positive controls. Up to ~200-fold upregulation of genes encoding various c - and b -type cytochromes was observed in “py,” pointing to the high relevance of these molecules in scavenging and relaying electrons from pyrite to cytoplasmic metabolisms. Conversely, extensive downregulation of genes related to LH and RC complex components indicates that the electron source may have direct control over the bacterial cells’ photosynthetic activity. In terms of sulfur metabolism, genes encoding periplasmic or membrane-bound proteins (e.g., FccAB and SoxYZ) were largely upregulated, whereas those encoding cytoplasmic proteins (e.g., Dsr and Apr groups) are extensively suppressed. Other notable differentially expressed genes are related to flagella/fimbriae/pilin(+), metal efflux(+), ferrienterochelin(−), and [NiFe] hydrogenases(+). Characterization of the biologically reacted pyrite indicates the presence of polymeric sulfur. These results have, for the first time, put the interplay of PSB and transition metal sulfide chemistry under the spotlight, with the potential to advance multiple fields, including metal and sulfur biogeochemistry, bacterial extracellular electron transfer, and artificial photosynthesis. IMPORTANCE Microbial utilization of solid-phase substrates constitutes a critical area of focus in environmental microbiology, offering valuable insights into microbial metabolic processes and adaptability. Recent advancements in this field have profoundly deepened our knowledge of microbial physiology pertinent to these scenarios and spurred innovations in biosynthesis and energy production. Furthermore, research into interactions between microbes and solid-phase substrates has directly linked microbial activities to the surrounding mineralogical environments, thereby enhancing our understanding of the relevant biogeochemical cycles. Our study represents a significant step forward in this field by demonstrating, for the first time, the autotrophic growth of purple sulfur bacteria using insoluble pyrite (FeS2) as both the electron and sulfur source. The presented comparative growth profiles, substrate characterizations, and transcriptomic sequencing data shed light on the relationships between electron donor types, photosynthetic reaction center activities, and potential extracellular electron transfer in these organisms capable of anoxygenic photosynthesis. Furthermore, the findings of our study may provide new insights into early-Earth biogeochemical evolutions, offering valuable constraints for understanding the environmental conditions and microbial processes that shaped our planet’s history.",
"conclusion": "Conclusion In this study, we showed that A. vinosum cells are capable of autotrophic growth using pyrite as the source of sulfur and electron donors. The differential gene expression analysis along with growth profile and substrate characterization data provided valuable insight into the molecular mechanisms underlying the bacterial autotrophic growth. Up to ~200-fold upregulation of genes encoding for a range of c-type and b-type cytochromes (including multiheme ones) points to the high relevance of these proteins in scavenging and relaying electrons from pyrite to key metabolic pathways. Conversely, the exclusive downregulation of LH and RC complex components may suggest that the available electron donor source likely has dominant control over the bacterial cells’ photosynthetic activity. The possibility that A. vinosum may bypass some or all of the photosynthetic pathway and couple the electron scavenging from pyrite directly to carbon fixation is not ruled out. The results of this study have, for the first time, put the interplay of purple sulfur bacteria and transition metal sulfide chemistry under the spotlight, with the potential to advance multiple fields, including metal and sulfur biogeochemistry, bacterial extracellular electron transfer, and artificial photosynthesis.",
"introduction": "INTRODUCTION Purple bacteria are photosynthetic, Gram-negative prokaryotes that convert light energy into chemical energy through the process of anoxygenic photosynthesis ( 1 ). Anoxic conditions are required for purple bacteria to grow phototrophically, as the biosynthesis of their pigments and complexes is repressed by molecular oxygen ( 2 ). Although purple bacteria can utilize a wide range of electron donors to couple their autotrophic CO 2 fixation, a subgroup preferentially oxidizes reduced sulfur compounds (i.e., hydrogen sulfide) during their phototrophic growth and are named purple sulfur bacteria (PSB). Almost all identified PSB belong to Chromatiaceae , Ectothiorhodospiraceae, or Halorhodospiraceae families ( 3 ). A key difference between these families of PSB lies in the location of the sulfur globules formed during the bacterial growth on reduced sulfur ( 4 ), which occur intracellularly in members of Chromatiaceae but extracellularly in those of Ectothiorhodospiraceae/ Halorhodospiraceae . The specific strain studied in this reported work, Allochromatium vinosum DSM180, belongs to Chromatiaceae . Purple sulfur bacteria can thrive in various freshwater, marine, and hypersaline environments that contain hydrogen sulfide and are illuminated, usually inhabiting the stratum below oxygenic phototrophs. A consequence of this is that the wavelengths of light reaching purple sulfur (and non-sulfur) bacteria are limited, due to the absorption of the blue and red regions in the solar spectrum by the chlorophyll-containing oxygenic phototrophs ( 5 ). The most essential pigments in PSB are capable of absorbing near-infrared and green light and use it for anoxygenic photosynthesis. PSB are key participants in the anoxic cycling of carbon, mostly as primary producers fixing CO 2 and occasionally as light-stimulated consumers of reduced organic compounds ( 6 – 9 ). The most critical roles of PSB in ecosystems, however, lie in their capability of reoxidizing hydrogen sulfide produced by sulfate-reducers ( 1 ). Hydrogen sulfide is a highly poisonous substance for most biota. The reoxidation of sulfide by PSB yields nontoxic forms of sulfur, such as elemental sulfur (S 0 ) and sulfate (SO 4 2− ), thereby detoxifying the associated environments and importantly closing the essential sulfur oxidation-reduction cycle. Photosynthetic pathways in phototrophic purple bacteria (including PSB) have been studied for decades ( 10 – 17 ). Here, we will briefly describe the phototrophic pathway in PSB. In PSB, incident photons are absorbed by an array of light-harvesting (LH) complexes within the intracytoplasmic membrane. These complexes consist of proteins that contain bacteriochlorophyll (BChl) and carotenoid pigments, which can absorb light energy by transforming their bonding and electronic states and funneling it down an energy gradient to a central reaction center (RC). In RC, charge separation occurs across the membrane and drives a series of redox reactions involving other biomolecules or protein complexes such as quinone/quinol, cytochrome b/c , and cytochrome c complexes bound within the membrane. Along with electron transport, proton motive force (PMF) is formed and powers ATP synthase complexes. Weissgerber et al. ( 18 ) sequenced and annotated the full genome of A. vinosum, identifying three subunits of the RC, pufC , pufM, and pufL, which are clustered and co-transcribed with three sets of pufA and pufB genes encoding light-harvesting complex (LH1) apoproteins ( 19 ). Six potential puc gene pairs were also identified that encode α- and β-apoproteins for several LH2 complex types ( 20 ). It was reported that A. vinosum produces one type of bacteriochlorophyll, namely BChl a , and carotenoids of the spirilloxanthin series ( 18 ). A central feature of PSB is their capability to oxidize reduced sulfur compounds during photolithoautotrophic growth. The known substrates that can be used by PSB include sulfide, polysulfides, elemental sulfur, and thiosulfate ( 21 ). In terms of sulfide oxidation, A. vinosum has the genetic capacity to form several different enzymes, including the periplasmic flavocytochrome c sulfide dehydrogenase (Fcc), and membrane-bound sulfide:quinone-oxidoreductases (Sqr), which are predicted to be oriented toward the periplasm ( 22 , 23 ). A. vinosum was also shown to contain the genetic information for rhodaneses, sulfur relay proteins, and polysulfide reductase-like proteins with unknown functions ( 24 – 27 ). Some PSB including A. vinosum have been shown to oxidize externally supplied elemental sulfur ( 28 ). However, controversy exists regarding whether PSB may utilize commercially available elemental sulfur, and it remains unknown how PSB may bind, activate, and take up solid-phase sulfur. In principle, bacterial cells may interact with their insoluble substrate through direct physical contact via outer membrane proteins or through excreting extracellular substances that solubilize the substrate. For A. vinosum , evidence for the formation of soluble intermediates like sulfide or polysulfides during uptake of elemental sulfur was not obtained ( 29 ), rendering direct cell-sulfur contact as a likely option for the cells’ interaction with the solid substrate. It was also shown that A. vinosum strongly prefers the polymeric sulfur fraction (i.e., sulfur chains) of the elemental sulfur and is likely unable to utilize the S 8 rings ( 30 ). Regarding sulfur-oxidation in A. vinosum , many of the former studies have also focused on the mechanisms involved in their sulfur globule utilization and proposed that the dissimilatory sulfite reductase (Dsr) system might play essential roles as several dsr -deleted mutants of A. vinosum were found unable to degrade these globules ( 31 – 34 ). It remains unknown if A. vinosum or other PSB are capable of utilizing other solid-phase substrates besides elemental sulfur. In the various habitats of PSB through geological time, there had been, and still are, high chances of metal sulfide formation, which may divert free sulfide out of the sulfur cycle and complicate the associated metal-sulfur geochemistry ( Fig. 1 ). Interaction of PSB with metal sulfides in general, therefore, may have its evolutionary basis, especially considering the prevalence and transformations of sulfide-dominated environments on early Earth. Based on previous studies ( 35 , 36 ), the oceans during the Mesoproterozoic Era were overall constrained to support a mix of sulfidic, ferruginous, and oxic conditions. Later statistical treatment of the available iron speciation data suggests that euxinic conditions were relatively common ( 37 , 38 ), which may have provided a strong sink for Fe(II), leading to extensive FeS formation. For modern geochemical settings, partial documentation of coexistence of Fe sulfide precipitates and microbial sulfide oxidation (including phototrophic) was available for euxinic or ferruginous lakes ( 39 – 41 ), fjords ( 42 – 44 ), estuaries ( 45 – 47 ), and shallow marine basins ( 48 – 50 ). Iron monosulfide in geochemical setting is a metastable phase and will eventually transform into greigite and pyrite ( 51 – 55 ). Fig 1 Microbial sulfur oxidation-reduction patterns complicated by the presence of transition metal species (TMs). In the absence of TMs, sulfate reducers reduce sulfate to sulfide/elemental sulfur in couple with heterotrophy or mixotrophy, whereas sulfur-oxidizers oxidize sulfide/elemental sulfur back to sulfate in couple with autotrophy. In the presence of TMs, TM sulfide nanoparticles or thiometallate clusters may form within the cycle. It is unknown how the formed TM-sulfur nanoparticles or complexes may affect the metabolic activity of associated sulfur-oxidizers that depend on “free” sulfide to support CO 2 fixation. Here, we present the first evidence for A. vinosum ’s capability of utilizing solid-phase metal sulfide, that is, pyrite (FeS 2 ) and provide thorough transcriptomic profiling and substrate characterization data. We confirmed robust but much slower growth of the pyrite-supported cell cultures (“py”) compared with their positive controls (amended with sodium sulfide and containing soluble ∑H 2 S). Differential gene expression analyses (of cells harvested at their respective exponential growth phases in “py” versus positive controls) revealed up to hundreds of fold changes in the expression of genes encoding various types of cytochromes, LH complex subunits, bacteriochlorophyll a , and enzymes involved in dissimilatory sulfur metabolism. We have also proposed a model for pyrite oxidation by A. vinosum in the discussion.",
"discussion": "DISCUSSION The cell growth profiles and transcriptomic analysis results revealed significant changes in the cells’ major metabolic pathways, including electron transport, RC and LH complex biosynthesis, and sulfur oxidation. We have specifically discussed these changes in the following section. Combining these molecular biological analyses with the pyrite substrate analyses, we have also proposed mechanisms of interaction between A. vinosum and pyrite that enabled the bacterial cells’ autotrophic growth. Key roles of cytochromes in A. vinosum -pyrite electron transfer The genome of A. vinosum encodes a wide range of cytochromes that are known to play key roles as diffusible electron carriers, dissimilatory sulfur metabolism enzymes, hydrogenases, etc. In the current study, up to ~200-fold upregulation was identified for a number of genes related to c -type and, to a lesser extent, b -type cytochromes in the “py” cell cultures. Further analyses revealed that some of the upregulated genes are associated with soluble or membrane-bound c -type cytochromes or flavocytochromes (Alvin_1093, 0020, and 0023), previously classified as diffusible electron carriers. It is noted that Alvin_1093 is one of the top upregulated genes (expression increased by ~175-fold) in the “py” cells. Alvin_1093 and Alvin_1092 (upregulated by ~75-fold) encode a heterodimer consisting of a 21 kDa diheme cytochrome c subunit (FccA) and a 46 kDa flavin-binding subunit (FccB) in A. vinosum ( 4 ). Although soluble c -type cytochromes were shown to catalyze the oxidation of sulfide to sulfur or polysulfides in vitro ( 22 ), the roles of FccA and FccB in A. vinosum remain unresolved. As pointed out in Weissgerber et al . ( 18 ) mutants in which the genes fccAB are inactivated by a kanamycin cassette still oxidize sulfide with rates similar to the wild type ( 22 ). Some sulfide-utilizing green sulfur bacteria, for example, Chlorobium luteolum , and purple sulfur bacteria, for example, Thiocapsa roseopersicina , Thiococcus pfennigii , and Allochromatium warmingii , do not produce flavocytochrome c , which is an additional hint that flavocytochrome c is not essential for sulfide oxidation ( 4 ). Interestingly, Alvin_1093 along with Alvin_1092, 0020, and 0022–0023 showed distinctive regulation patterns for the pyrite-supported cells in this study than the elemental sulfur (S 0 )-supported cells (also of A. vinosum DSM180) in a previous study ( 59 ) ( Table S2 and data sets). Specifically, Alvin_0020, 0022, and 0023 were significantly suppressed in the S 0 -supported, photoautotrophically grown cells versus their positive controls using soluble sulfide, whereas Alvin_1093 was slightly enhanced ( 59 ). Such evident variations strongly indicate that Alvin_0020, 0022–0023, and 1092–1093 have played particularly important roles in the A. vinosum -pyrite interactions in the current study (further discussion of Fcc is provided in the “dissimilatory sulfur metabolism” section). Up to 41-fold upregulation of Alvin_1095, associated with a 4-heme c -type cytochrome, was also observed although the component’s function and pathway have not been resolved. We further evaluated whether cytochromes, especially those with multihemes, may play a role in the A. vinosum cell-pyrite electron transfer, linking intracellular energy reactions to the oxidation of solid pyrite external to the cells. The phenomenon of extracellular electron transfer (EET) has been demonstrated in over ~100 microbes to date, perhaps most notably in Geobacter sulfurreducens and Shewanella oneidensis , where a network of multiheme c -type cytochromes on the inner membrane, periplasm, and outer membrane couple intracellular energy reactions with the use of external solid electron donors or acceptors ( 60 – 63 ). Multiheme cytochromes (MHCs) in particular are key players in extracellular electron transfer ( 62 ), as the proximity and arrangement of hemes can allow efficient intraprotein electron transfer ( 64 ). We identified 43 putative c -type cytochromes in A. vinosum based on the presence of CXXCH heme c binding motifs, and of these, 18 were putative MHCs (containing multiple CXXCH motifs): specifically, 11 × diheme, 1 × 3 heme, 3 × 4 heme, 1 × 7 heme, and 2 × 8 heme cytochromes ( Table S3 ). Some of the larger ones (e.g., 7- or 8-heme) in particular, and various others, have no annotated functions; the expression of these larger MHCs was exclusively enhanced in the “py” cells. The remaining 25 are putative monoheme c -type cytochromes. We also probed these genes for the presence of LXXC lipid-binding motifs and/or signal peptides, as both periplasmic and membrane-associated cytochromes are required for extracellular electron transfer. LXXC is a lipoprotein consensus sequence for signal peptidase II found in key outer membrane cytochromes in S. oneidensis ( 65 ). SignalP ( 66 ) can detect 5 types of signal peptides, that is, a protein can enter the cell’s secretory pathway, where it may be localized to the inner membrane, exported to periplasm, or localized to the outer membrane. In total, 19 out of 43 putative cytochromes contained LXXC lipid motifs, 21 were detected by SignalP, and eight were detected for both. The fact that multiple cytochromes are potentially associated with the inner or outer membrane (with others not identified here possibly being soluble electron carriers) is promising for identifying a potential cytochrome network for extracellular electron transfer in A. vinosum . Experimental evidence will be required to confirm the cellular localization of cytochromes in A. vinosum , and whether they contribute to extracellular electron transfer. As a disclaimer, other cytochromes of interest may exist, for example, those without heme c motif (CXXCH) or those not detected by the LXXC lipid motif or by SignalP. In total, 10 putative c -type cytochromes (including an 8-heme, 2 diheme, and 7 monoheme) were upregulated in the “py” cells and may be of particular interest toward investigating the coupling of carbon fixation at the inner membrane to the oxidation of pyrite outside the cell. Less important roles of LH and RC complex components? Another major change identified in the “py” cells is the downregulation of photosynthetic genes related to the biosynthesis and assembly of LH and RC components ( Table 2 ; Fig. S1 ). As a recap, the expression of puc clusters encoding LH2 apoproteins was significantly suppressed, by up to ~70-fold; the puf clusters and genes related to biosynthesis of Bchl a were also downregulated, by ~8- to 10-fold for the former and by ~2-fold for the latter. The only genes not affected or enhanced in expression within the photosynthetic category are those representing carotenoids biosynthesis (Alvin_2564–2570). It is still premature to conclude what has caused the extensive downregulation of the photosynthetic LH- and RC-related genes in the “py” cells. A most likely reason might be that the growth rate of the “py” cells was limited by the electron supply and its connection to the carbon fixation pathway, and thus, the demand for higher-density LH and RC complexes was no longer existent. We have compared the availability of solid-phase pyrite versus soluble Na 2 S as an electron donor ( Fig. 6 ) assuming that the electron scavenge was restricted in the surface layer of pyrite and found ~2–3 order of magnitude difference in their effective concentrations. Fig 6 Comparison of the availability of solid-phase pyrite versus soluble Na 2 S as an electron donor. It is noted that the relationships among the RC complex, sulfur-oxidation pathway, and carbon fixation pathway are not fully understood. In other words, it is unknown whether the reactivity of RC complex is specifically affected by the electron donor source. If so, the possibility of bypassing the LH-RC complex by the bacterial cells when using an alternative electron source cannot be ruled out. We further evaluated the expression of genes related to ribulose 1,5-biphosphate carboxylase/oxygenase (RuBisCO) in the “py” and positive control cells as both types grew autotrophically with bicarbonate as the sole carbon source. A. vinosum possesses two complete sets of genes encoding for RuBisCO subunits: the large subunit RbcA/RbcB represented by Alvin_1365–1366 and the small one RbcS/RbcL represented by Alvin_2749–2750 ( 67 ). Opposite trends have been observed for the two sets of RuBisCO genes in the “py” cells, with Alvin_1365–1366 downregulated by at least 10-fold and Alvin_2749–2750 moderately upregulated by ~2-fold. According to the gene arrangement, the rbcAB gene belongs to IAq-form RuBisCO genes, typically associated with cbbQ encoding proteins affecting RuBisCO activity ( 68 ), whereas the rbcSL genes are IAc-form RuBisCO genes ( 69 ). Besides the RuBisCO genes, A. vinosum harbors a gene encoding an IV-type RuBisCO-like protein (RLP) (Alvin_2545), the expression of which decreased just slightly in the “py” cells. It remains unclear what roles such RLPs play in A. vinosum metabolism, but likely not involved in RuBis-dependent CO 2 fixation ( 70 , 71 ). An alternative explanation for the probable “shutdown” of LH and RC, other than the electron donor restriction, might be that the cells have established a less “expensive” pathway for obtaining energy to drive their carbon fixation and growth. Regarding what other pathways may be possible for A. vinosum cells to capture light energy, here, we present a new hypothesis that requires further experimental evidence. In this hypothesis, we assume that the electron transfer from the extracellular pyrite substrate can be driven by both photochemical and non-photochemical reactions to support CO 2 fixation, and these mechanisms do not involve RC complexes in A. vinosum ( Fig. 7 ). There are obvious energy and nutrient appeals for A. vinosum to enable such cell-pyrite interactions, which are further discussed in the “hypothetical model” for pyrite oxidation by A. vinosum . Fig 7 Proposed oxidation of pyrite driven by both photochemistry and diffusible and membrane-bound cytochromes in A. vinosum . ( A ) Illustration of major proteins and other components in PSB’s RC complex. ( B ) Proposed mechanisms for pyrite oxidation by A. vinosum . ( C ) Comparison of energy levels for PSB photosynthetic electron carriers vs. pyrite conduction/valence bands (potential values obtained from references 72 , 73 ). Dissimilatory sulfur-oxidation metabolism For genes encoding major enzymes (likely) involved in dissimilatory sulfur metabolism, we have observed opposite trends in their differential expressions (in “py” vs. positive control), primarily divided by associated pathways of the relevant enzymes ( Table 3 ; Fig. S2 ). We will first discuss the genes representing Fcc and Sqr, respectively, although their roles in dissimilatory sulfur oxidation have not been fully resolved. It has been pointed out in our former discussion on cytochromes that FccA and FccB, the two subunits constituting an enzyme catalyzing sulfide oxidation and a cytochrome reduction in the periplasm, are likely key in enabling the A. vinosum -pyrite electron transfer. Chen et al . ( 74 ) provided a detailed illustration of Fcc structures, which consist of a glutathione reductase-like flavin-binding subunit and a diheme cytochrome subunit. Specifically, the diheme cytochrome folds as two domains with an unusual interpropionic acid linkage joining the two heme groups in the interior of the subunit, and a tryptophan, threonine, or tyrosine side chain may provide a partial conduit for electron transfer to one of the heme groups located ~10 Å from the flavin. This structural configuration of FccA or B cannot rule out the possibility of it bridging membrane-bound pyrite oxidation to periplasmic metabolisms other than oxidizing pyrite within the periplasmic space. Meanwhile, A. vinosum contains two membrane-bound Sqr enzymes belonging to types IV (Alvin_2145) and VI (Alvin_1195) ( 59 ). Sqr belongs to a family of FAD-dependent oxidoreductases utilizing a motif of Cys-S-S-Cys as the key redox site ( 75 ). Sqr has been previously identified to reduce the quinone pool present in the photosynthetic or plasma membranes of purple bacterial cells and was proposed as a candidate protein for oxidizing sulfide ( 22 , 76 ). In the case of Rhodobacter capsulatus , polysulfides were identified as the main reaction products in vitro . In our current study, opposite trends were observed in the differential gene expressions (“py” versus positive control) for Alvin_2145, encoding type IV SqrD (upregulated by ~4.5-fold) and for Alvin_1195, encoding type IV SqrF (downregulated slightly). A correlation between the occurrence of SqrD and the production of intracellular sulfur globules has been suggested previously ( 23 ) mainly through observations that sqrD genes are present in members of Chromatiaceae but absent in species of Ectothiorhodospiraceae that exclusively produce extracellular sulfur globules. Relevant to this discussion, we identified sulfur-rich amorphous phase in the biologically reacted pyrite in the TEM analysis. However, we have not confirmed the source of this possibly polymeric sulfur phase, that is, whether it was intracellular or pyrite oxidation product. The downregulation of Alvin_1195 is consistent with the previous understanding that SqrF is involved in optimizing cell growth at high sulfide concentrations ( 23 ), which was not the case for the “py” cell cultures in this study. It is still unknown if the cells grown on pyrite in this study can form sulfur globules in the periplasm. The genes representing the envelope proteins of such sulfur globules (i.e., SgpA, SgpB, and SgpC) showed interesting patterns in differential gene expression analysis, however. Specifically, SgpA, SgpB, and SgpC are encoded by Alvin_1905, Alvin_0358, and Alvin_1325, respectively. SgpC plays an important role in globule expansion, whereas SgpA and SgpB can be replaced by each other to some extent ( 77 , 78 ). In our study, Alvin_1905 and Alvin_0358 were slightly downregulated, and Alvin_1325 remained unchanged. We note here that the expression of genes representing Sgp was not apparently suppressed in the “py” cell cultures compared with positive controls, which creates a sharp contrast with the trends previously reported for “S 0 -supported” cells ( 59 ). The general trend for the three clusters of sox genes is moderately upregulated or relatively unaffected in the “py” cells (compared with positive controls). It is noted that the Sox protein complex is localized in the periplasm, which differs from the location of Dsr proteins. Although Dsr proteins were implicated as key participants in the oxidation of sulfur globules, genes related to Dsr are downregulated in the current study [except that dsrC (Alvin_1256) remained relatively unchanged in its expression level]. In fact, a review chapter on dissimilatory sulfur metabolism in purple sulfur bacteria pointed out that purple non-sulfur bacteria, including those able to oxidize elemental sulfur lack dsr genes ( 28 ) and the A. vinosum cells grown upon external sulfur, showed significant downregulation in their dsr genes ( 59 ). Combined with the latest results in this study, it is strongly suggested that Dsr are not highly involved in the metabolism of external solid substrates of sulfur. Dsr proteins are largely localized in the cytoplasm, with a transmembrane complex (DsrMKJOP). It is likely that the specific locality and connection to photosynthetic electron transport chains ( 79 ) of Dsr proteins make it difficult for most of them to participate in pyrite utilization if pyrite oxidation occurred largely outside the cells, and the produced intermediate sulfur species differed from those produced through soluble sulfide oxidation. It is noted that although the dsr genes are transcribed as one single element, dsrC has an additional independent promoter site ( 80 ), pointing to a special function of DsrC. Furthermore, besides dsrC , there are four more genes annotated as TusE/DsrC/DsvC family sulfur relay proteins, namely Alvin_0028, Alvin_0345, Alvin_0732, and Alvin_1508. We observed upregulation by ~2-fold to 4-fold for Alvin_0028, 0345, and 0732 and downregulation by ~8-fold for Alvin_1508. The dsr gene expression data are consistent with the lack of sulfate in the “py” cell culture medium (i.e., IC data), both of which suggest that A. vinosum cells might be capable of oxidizing pyrite (or specifically pyrite surface-bound sulfur) to polysulfide or elemental sulfur, but not able to further oxidize these sulfur species to sulfate. However, we also note that pyrite is the sole sulfur source for the “py” cells, which may assimilate any sulfate produced from the bacterial oxidation of pyrite. Further comparative kinetic studies are necessary to verify if A. vinosum can oxidize pyrite to sulfate. Information from flagellum, fimbriae, and pilin genes We have singled out the genes associated with the biosynthesis of flagella, fimbria, and pili because the expression of these genes was exclusively enhanced in “py.” Many species of purple bacteria swim with the assistance of flagella toward carbon/other nutrient sources and light, using a complex set of chemosensory pathways ( 81 ). The flagellum in bacterial cells is an extremely complex structure, requiring the expression of genes encoding flagellar proteins to be tightly regulated and ordered. The upregulation of Alvin_0408, 1188, 1569, and 3021 opens a discussion on whether flagella, fimbria, and pili are involved in establishing physical contact between A. vinosum cells and pyrite. Furthermore, although a possible connection between flagellation and substrate exploration and utilization has not been shown in bacterial cells, flagellar proteins were recently speculated to be involved in direct physical contact with insoluble elemental sulfur for oxidation in Aquifex aeolicus ( 82 ). Overall, the extensive upregulation of flagellum-, fimbriae-, and pilin-related genes manifests two key messages. First, mobility may be a critical factor for A. vinosum cells grown upon pyrite. High mobility may help the cells to move around easily to either find the most “bioavailable” spots on pyrite or avoid the potential cytotoxic effects of substrate surface radical species (which are common in photochemical reactions) and oxidation products. Second, the enhanced expression of appendage genes also indicates that physical contact is likely important in cell-pyrite interactions. Hypothetical model for pyrite oxidation by A. vinosum Based on the obtained solution, substrate, and gene expression analyses, we have proposed a hypothetical model for pyrite oxidation by A. vinosum ( Fig. 7 ). In this model, physical contact of bacterial cells and pyrite particle surfaces is necessary for the pyrite-supported cell growth. The utilization of pyrite is proposed to be driven by both photochemical and non-photochemical processes. As pyrite has a band gap of 0.9 eV ( 83 ), the illumination setup for the experiments is capable of exciting the charge separation in pyrite. Certain monoheme c -type cytochromes may play a role as diffusible electron carriers, leading to the oxidation of surface-bound sulfur. Meanwhile, the periplasmic proteins SoxY and SoxZ may bind to the sulfur on pyrite surfaces and catalyze their oxidation. Both SoxYZ and diffusible electron carriers will pass the electrons to a membrane-bound c -type cytochromes, which relay the electrons through a quinone pool to cytochrome b to subsequently generate adenosine triphosphate (ATP). The various cytochromes involved in the proposed pathways are yet to be identified, but from the upregulated list (based on the gene expression analyses), several candidates with compatible reduction potentials may fit into these roles. It is noted that there is no evidence that A. vinosum is capable of oxidizing ferrous iron (separately tested in the current study). This hypothetical model well explains the cryptic behavior of dissolved iron in the solution as the initial charge separation in pyrite is more likely to oxidize structural Fe(II) to Fe(III), subsequently oxidizing the sulfur while being reduced back to Fe(II); these cyclic reactions may lead to iron mobilization and/or monosulfide reprecipitation depending on the locality of the sulfur involved in the process. Further experimental evidence is required to validate this hypothetical model. Conclusion In this study, we showed that A. vinosum cells are capable of autotrophic growth using pyrite as the source of sulfur and electron donors. The differential gene expression analysis along with growth profile and substrate characterization data provided valuable insight into the molecular mechanisms underlying the bacterial autotrophic growth. Up to ~200-fold upregulation of genes encoding for a range of c-type and b-type cytochromes (including multiheme ones) points to the high relevance of these proteins in scavenging and relaying electrons from pyrite to key metabolic pathways. Conversely, the exclusive downregulation of LH and RC complex components may suggest that the available electron donor source likely has dominant control over the bacterial cells’ photosynthetic activity. The possibility that A. vinosum may bypass some or all of the photosynthetic pathway and couple the electron scavenging from pyrite directly to carbon fixation is not ruled out. The results of this study have, for the first time, put the interplay of purple sulfur bacteria and transition metal sulfide chemistry under the spotlight, with the potential to advance multiple fields, including metal and sulfur biogeochemistry, bacterial extracellular electron transfer, and artificial photosynthesis."
} | 8,840 |
30597855 | PMC6359297 | pmc | 3,184 | {
"abstract": "The aim of this work is to investigate the properties of biofilms, spontaneously grown on cathode electrodes of single-chamber microbial fuel cells, when used as catalysts for oxygen reduction reaction (ORR). To this purpose, a comparison between two sets of different carbon-based cathode electrodes is carried out. The first one (Pt-based biocathode) is based on the proliferation of the biofilm onto a Pt/C layer, leading thus to the creation of a biohybrid catalyst. The second set of electrodes (Pt-free biocathode) is based on a bare carbon-based material, on which biofilm grows and acts as the sole catalyst for ORR. Linear sweep voltammetry (LSV) characterization confirmed better performance when the biofilm is formed on both Pt-based and Pt-free cathodes, with respect to that obtained by biofilm-free cathodes. To analyze the properties of spontaneously grown cathodic biofilms on carbon-based electrodes, electrochemical impedance spectroscopy is employed. This study demonstrates that the highest power production is reached when aerobic biofilm acts as a catalyst for ORR in synergy with Pt in the biohybrid cathode.",
"conclusion": "4. Conclusions In the present work, the synergistic catalytic properties for the ORR of aerobic biofilms spontaneously grown on the cathode electrodes and Pt/C layers are investigated. The main aim was first of all to provide direct evidence of ORR catalysis using electrochemical techniques. The properties of the cathodic biofilms obtained in different configurations, coupled or not to a Pt/C layer, were analyzed by employing electrochemical impedance spectroscopy and cyclic voltammetry. The obtained results confirmed the improved electrocatalytic behavior of the cathode electrode when aerobic biofilm is grown on it. Indeed, for both the A2 bio and B2 bio cathodes, a reduction peak at 0.3–0.4 V compared to SHE was visible, associated with ORR activity. Moreover, a decrease of 60% of cathodic charge transfer resistance was achieved when the biofilm was formed on both electrodes. On the contrary, the charge transfer resistance increased when the biofilm was absent in the A2 new and B2 new cathodes. This result demonstrated the key role played by the biofilm in helping the ORR catalysis in the biohybrid cathodes, based on the combination of the Pt/C catalyst layer and the aerobic biofilm.",
"introduction": "1. Introduction Microbial fuel cells (MFCs) are classified as bio-electrochemical devices, comprised of two different compartments: anode and cathode [ 1 , 2 , 3 , 4 , 5 ]. The main advantage of this kind of device is the capability of producing electrical energy, starting from chemical energy, contained in organic matter of different substrates, known as fuel. In the anode compartment, a specified class of microorganisms called exoelectrogenic bacteria, are able to directly convert chemical energy into electrical energy through the oxidation of organic matter, while in the cathode compartment, oxygen reduction reaction (ORR) is usually carried out, especially when the open-air cathode configuration is implemented [ 6 , 7 , 8 , 9 , 10 , 11 ]. As deeply investigated in the literature [ 6 , 7 , 8 , 9 , 10 , 11 ], one of the main limits of this configuration is the sluggish kinetics of ORR, which requires four electrons to directly reduce oxygen to water, leading to minimized hydrogen peroxide, an intermediate product that is harmful to microorganisms [ 10 ]. As reported by several works in the literature [ 6 , 11 ], Pt is the best catalyst for ORR [ 11 ]. However, Pt is not abundant, and the high cost limits its further employment as catalyst layer at the cathode. In recent years, many works focused their attention on the development of new catalyst layers, based on non-precious metal compounds [ 12 , 13 , 14 , 15 , 16 , 17 ], their alloys and metal-free materials [ 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 ]. Another class of catalysts important for ORR is comprised of aerobic bacteria, which are able to directly transfer the electrons released from the anode to molecular oxygen. In particular, several works in the literature [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ] analyze the electrochemically active microorganisms, proliferated on the cathode surface and involved in the conversion of different chemical compounds, such as carbon dioxide (CO 2 ), Fe (III), Mn (IV) and oxygen (O 2 ) when an aerobic bio-cathode is developed [ 34 , 35 , 36 ]. Aerobic bacteria, acting as bio-catalyst in air-cathode single chamber microbial fuel cells (SCMFC), results in an important alternative to inorganic catalysts, leading thus to the minimization of the overpotential for ORR [ 34 ]. These types of microorganisms are able to accept the electrons and the protons produced in the anode compartment, reducing the oxygen to water. These bacteria, arranged in the form of a biofilm grown onto the cathode electrode, play an important role as bio-catalyst. Different methods were employed to control and ensure the biofilm formation on the cathode electrode [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]. Among all of them, the most common method is based on a polarization technique where a fixed potential is applied. This method is carried out in an electrochemical cell and many researchers confirmed that an applied potential of +0.3 V compared to the standard hydrogen electrode (SHE) ensures the best performing bio-cathodes for ORR [ 30 , 36 , 37 , 38 , 39 ]. Few works in the literature [ 29 , 39 ] investigate the role of biofilm spontaneously grown on the cathode electrode, when a SCMFC is employed. Santoro and co-workers [ 29 ] studied the growth of anodic and cathodic biofilms in SCMFCs subjected to a constant resistive load. They found that, after a start-up phase, the performance of devices based on clean anodes and Pt-free cathodes were eventually similar to that of devices based on pre-colonized anodes and Pt-based cathodes, due to the formation of biofilms on both electrodes. Starting from that paper, our aim was to provide direct evidence of ORR using electrochemical techniques and investigate the reasons behind the observed behavior. To this purpose, we analyzed the properties of spontaneously grown cathodic biofilms on carbon-based electrodes employing electrochemical impedance spectroscopy (EIS). EIS is an electrochemical technique widely employed for the characterization of materials and devices [ 40 ]. In the field of MFCs, it has already been applied to investigate anode [ 41 ] and cathode [ 41 , 42 ] properties, as well as whole-device behavior [ 41 ]. In this work, the attention was especially focused on biofilm/electrode interface, and on its effect on the total cathodic resistance. Two different cathodes were compared. The first one was based on a bare carbon-based electrode on which an aerobic biofilm is set free to grow. The second one represented a biohybrid cathode based on a combination between a Pt catalyst layer and a cathodic biofilm, which spontaneously proliferated on it. For both samples, the biofilm formation was obtained by a mixed culture, which ensured better MFC performance with respect to pure cultures, as demonstrated in the literature [ 29 ]. The cathodes were studied in SCMFCs and the biofilm formation was forced by applying an external resistance of 100 Ω.",
"discussion": "3. Results and Discussion 3.1. SCMFC Performance As previously described, at the beginning of experiments, fresh anodes and cathodes made of CP were used as electrodes in all SCMFCs. During the first phase of experimentation, to evaluate the key role played by biofilms grown on both electrodes, the overall performance of SCMFCs was assessed. In particular, Figure 1 reports the average voltage values of both A1 and B1 SCMFCs monitored over time. The start-up phase, defined as the period of time required for the effective formation of biofilms on anode and cathode electrodes, was the same for the two different kinds of devices, close to 25 days. After that period, the voltage values increased according to the implemented cycles, during which fresh electrolytes were replenished inside the devices. A corresponding increment of current production (see Figure 1 ) was reached for both A1 and B1 SCMFCs, with maximum values of 382.25 ± 13.33 mA m −2 and 684.1 ± 5.8 mA m −2 . Since the anodic compartments of both kinds of devices are nominally identical, the differing performance of the SCMFCs can be directly attributed to the use of diverse cathodes. The formation of a biohybrid catalyst on the B1 cathode is thus responsible for the overall better device performance in terms of its output voltage, which was about two times larger than the one provided by A1, where only biofilm acted as the effective catalyst toward ORR. However, it is worthwhile to notice the active role played by aerobic cathodic biofilms spontaneously proliferated on Pt-free cathodes as catalysts for ORR, as previously observed in the literature [ 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ]. To deeply define the contribution of the biofilms spontaneously grown on cathode electrodes on the overall SCMFCs performance, a second phase of experimentation was performed. In particular, during this experimental phase, polarization curves obtained for A2 bio and B2 bio SCMFCs were directly compared to the ones collected when fresh cathodes were employed, namely A2 new and B2 new SCMFCs. Figure 2 shows such results. Open circuit voltage (OCV) values of both B2 new and B2 bio resulted quite similarly, close to 0.65 V. However, it should be noted that B2 bio has a higher short circuit current density (I sc ) of 768.62 ± 4.43 mA m −2 , than the one achieved by B2 new, equal to 278.42 ± 3.07 mA m −2 . The same considerations can be drawn for A2 new and A2 bio. Indeed, I sc with A2 bio (445.07 ± 5.28 mA m −2 ) is one order of magnitude higher than the one obtained by A2 new (67.31 ± 1.44 mA m −2 ). Moreover, it is mandatory to appreciate that the best performance was ensured by the combination of Pt and biofilm, acting as catalysts for ORR. These biohybrid cathodes showed a better electrocatalytic activity than the one ensured by cathode based on biofilm that is grown on bare carbon-based electrode, which represents the configuration deeply investigated in several works in the literature [ 27 , 28 , 29 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ]. Since the anodic electrode of SCMFCs resulted as equal for all the studied devices, the beneficial performance of the cathode can be directly translated as beneficial performance of the whole cell. 3.2. EIS Characterizations The development of biofilm/electrode interface and its effect on the total cathodic resistance over time was investigated through EIS. In particular, this analysis was performed at the beginning of experimentation (t = 3 days), when new cathode electrodes were present, and after 55 days, when cathodic biofilm were grown onto both A1 and B1 cathodes. It is worth noting that the electrochemical properties of A2 bio and B2 bio cathodes are comparable with A1 and B1 day 55 cathodes. For this reason, data related to those samples are not shown. Typical Nyquist plots related to A1 and B1 cathodes are represented in Figure 3 a,b, respectively. The curves obtained through the fitting procedure are also reported in Figure 3 , overlaid on the experimental data, while all resistance values are summarized in Table 1 . As clearly observed in Figure 3 , the series resistance resulted in a similarity for both kinds of devices, independently on biofilm formation. This was to be expected, since electrolyte and wires and electrical connection were identical for all of the cells. Moreover, the lower the R 2 , the larger the formation of aerobic biofilm on both A1 and B1 cathodes. A decrease of 60% of charge transfer resistance (related to the low-frequency large arc in Figure 2 ) was in fact achieved when the biofilm was formed on both electrodes. In particular, R 2 for B1 cathodes decreased from 23.1 Ω on day 3 to 15 Ω on day 55, while for the A1 cathode, it decreased from 41.4 Ω to 18.1 Ω. This proves that the biohybrid cathode is more efficient in carrying out the ORR with respect to a bare biocathode. A similar trend was observed for the transport resistance R 1 (visible in the high-frequency smaller arc in Figure 3 ), implying that the cathodic biofilm was effective in increasing the electrode transport properties, similar to what was observed in anodic biofilms [ 38 ]. These results confirm that the biofilm on cathodes can improve the electrodes’ catalytic properties for the oxygen reduction reaction. In particular, they demonstrated how the biohybrid cathode, based on the combination of Pt/C and microorganisms, resulted in being more effective as a catalyst layer. Indeed, at day 3, the presence of an inorganic catalyst ensured a proper electrochemical behavior, which was increased by aerobic biofilm colonizing the cathode electrode, combining its efficiency with the typical one of the Pt/C layer. In line with our hypothesis—according to which the presence of biocatalyst on electrodes improved the catalysis of ORR—R 2 of A1 cathode resulted in being quite close to the one obtained for the B1 cathode. To demonstrate that the improved electrochemical behavior of A1 and B1 cathodes was due to the presence of microorganisms proliferated on the cathode electrodes, EIS characterizations were performed on the SCMFCs where the latter cathodes were substituted with fresh ones, namely A2 new and B2 new (see Figure 3 ). The curves obtained through the fitting procedure are also reported in Figure 3 , superimposed on the experimental data. The calculated resistance values are summarized in Table 1 . The charge transfer resistance, R 2 , increased when the biofilm was absent on both of the B2 new and A2 new cathodes. These values were found to be equal to 38.8 Ω and 19.9 Ω for the A2 new and B2 new cathodes, respectively, compared to 18.1 Ω and 15 Ω. This result demonstrates the key role played by the biofilm in helping the ORR catalysis in the biohybrid cathodes. 3.3. Cyclic Voltammetry Characterizations To further assess the ORR activity of the A2 bio and B2 bio cathodes, cyclic voltammetry characterizations were performed. An additional electrode based on carbon paper without biofilm (A2 new) was employed as the control. In Figure 4 , the cyclic voltammograms of the analyzed electrodes are reported. For both the B2 bio and A2 bio, a reduction peak at 0.3–0.4 V compared to SHE is visible. This peak can be associated with ORR activity, as shown in [ 26 , 28 , 45 ]. On the contrary, no peaks are evidenced for the control electrode, A2 new, leading to the demonstration of the electrocatalytic activity of biofilm. In addition, larger current production is associated with the Pt-based electrode, validating the synergistic effect of biofilm and Pt on the catalytic activity of biohybrid cathodes toward the ORR. All results confirmed how the biohybrid catalysts play a key role in minimizing the activation losses at the cathode, providing a promising path for ORR. Pt is not highly abundant and is very expensive, limiting its further employment as a catalyst layer. Therefore, great focus could be put on the development of new biohybrid catalysts based on the combination of non-noble metals or metal-free materials and aerobic bacteria proliferated on them. Previously, different kinds of nanostructured catalysts, based on non-precious metals like manganese oxide nanofibers [ 46 , 47 ] and metal-free nanofibers, such as carbon nanofibers [ 46 ], were developed by our group, and their electrochemical properties were demonstrated to be similar to those of Pt. One of the main interesting developments of the present work is focused on the coupling between the aerobic bacteria to the latter nanostructured materials."
} | 3,977 |
38013676 | PMC10644234 | pmc | 3,185 | {
"abstract": "Dynamic covalent networks (DCNs) are materials that feature reversible bond formation and breaking, allowing for self-healing and recyclability. To speed up the bond exchange, significant amounts of catalyst are used, which creates safety concerns. To tackle this issue, we report the synthesis of a lipoic acid-based vitrimer-like elastomer (LAVE) by combining (i) ring-opening polymerization (ROP) of lactones, (ii) lipoic acid modification of polylactones, and (iii) UV crosslinking. The melting temperature ( T m ) of LAVE is below room temperature, which ensures the elastic properties of LAVE at service temperature. By carefully altering the network, it is possible to tune the T m , as well as the mechanical strength and stretchability of the material. An increase in polylactone chain length in LAVE was found to increase strain at break from 25% to 180% and stress at break from 0.34 to 1.41 MPa. The material showed excellent network stability under cyclic strain loading, with no apparent hysteresis. The introduction of disulfide bonds allows the material to self-heal under UV exposure, extending its shelf life. Overall, this work presents an environmentally friendly approach for producing a sustainable elastomer that has potential for use in applications such as intelligent robots, smart wearable technology, and human–machine interfaces.",
"conclusion": "Conclusions This study showed the straightforward synthesis of a novel LA-based vitrimer-like elastomer with excellent stretchability and self-healing properties. The attributes of LAVE, such as molecular weight and mechanical and thermal properties, can be simply adjusted by varying the M/I ratios, allowing for material customization. Without premixing or the inclusion of any initiator or catalyst, LAVE films can be straightforwardly prepared through UV irradiation, making it an environmentally benign elastomer. As a result of its elastic, adjustable, and sustainable properties, LAVE has the potential to revolutionize the field of self-healing materials and has tremendous potential in a wide range of applications, such as sustainable wearables, human–machine interfaces, and food-contact materials. Further research in this field will focus on synthesizing a variety of LA-based primers with the possibility of application in 3D printing electronics. Hoping to address the challenges of sustainability in material science and pave the way for the development of a new generation of materials.",
"introduction": "Introduction Self-healing materials have gained popularity as an exciting and rapidly growing area of research due to their unique ability to repair themselves after being damaged. 1 This property is achieved through the incorporation of healing agents or physical and/or chemical dynamic bonding within the material's structure. 2,3 Dynamic covalent networks (DCNs), which combine the processing advantages of thermoplastics with permanent bonds of thermosets, have rapidly gained popularity and have been the subject of numerous studies. DCNs make use of dynamic covalent bonds, which can be broken and reformed at elevated temperatures or other stimuli, allowing for their dynamic behavior. 4 In general, the bond exchange process of DCNs can proceed via two mechanisms. The first type of DCNs, also called vitrimers, simultaneously break and reform their bonds, resulting in a material that is highly stable. 5 The other type follows a dissociative exchange mechanism, which means that the breaking and rebuilding of chemical bonds take place at different locations and times, resulting in a material that is highly adaptable; these materials are often referred to as nontraditional vitrimers. From a chemistry point of view, various dynamic bonds, including transesterification, 6,7 transamination of vinylogous urethane, 8 transalkylation of triazolium salts, 9 olefin metathesis, dioxaborolane exchange, disulfide exchange, Diels–Alder reactions, and imine formation, have been featured in designing DCNs. 10–14 In recent years, there has been intensive research to push the boundaries of polymer science and broaden the application of DCNs. For example, DCNs have been investigated for use in oil-spill remediation, 15 fast healing strain sensors, 16 sustainable 3D printing, 17–19 and stimulus-responsive materials. 20,21 While DCNs have shown great promise in their ability to self-heal and be recycled, the use of a large amount of catalyst in their production is a major concern. The high level of catalyst required to boost the bond exchange reaction has negative environmental impacts, and the monomers used in their production are not sustainable, leading to questions about their long-term viability as a sustainable material choice. 22 To address these issues, researchers have developed several catalyst-free networks to create DCNs, but these systems have their own limitations. For instance, a system developed by Zhang et al. 23 utilized glycerol as an aid, which resulted in material degradation and reduced robustness, leading to a more thermoplastic material. Similarly, a transamination-type vitrimer developed by Du Prez et al. , 8 used a vinylogous urethane moiety but the free amines in the network could pose concerns in long-term practical use due to oxidative damage and environmental issues. DCNs based on oxime–ester bonds also face similar limitations. 7 These challenges underline the need for further research and development of sustainable and environmentally friendly methods of synthesizing DCNs with lower catalyst amounts and through more sustainable production processes. Lipoic acid (LA), also known as thioctic acid, is a naturally occurring small molecule with a complex structure. It consists of a terminal carboxylic acid and a terminal dithiolane ring, which is a fully saturated, five-membered, sulfur heterocycle. This structure imparts distinctive chemical properties to LA that can undergo self-polymerization and depolymerization when exposed to heat, UV, or chemical stimuli. 24–27 Due to this characteristic, LA has the potential to be used in the construction of DCNs in a sustainable manner. However, polymerized lipoic acid exhibits metastable properties because of an inverse ring-closing depolymerization process. To overcome the problem of this undesired metastability, grafting-through polymerization technology was used to incorporate lipoic acid into the network using a “phase-locked disulfide bond”. 28,29 These bonds provide both elasticity and healing capability, with the soft segment ensuring elasticity and the hard backbone imparting healing capability. 2 This approach allows for the mechanical properties and stability of the network to be tailored to meet specific requirements, making LA an attractive choice for the development of advanced materials with unique functionalities. In this study, a straightforward method was designed to develop LA-based vitrimer-like elastomers (LAVE) by transforming a small molecule of biological origin into a high-performance elastomer with self-healing properties ( Scheme 1 ). First, a diol primer was synthesized by ring-opening polymerization (ROP) of lactones, followed by esterification with LA, which ensures crosslinking and introduces DCNs. LA can undergo UV-induced ROP, allowing for crosslinking without the involvement of initiators or catalysts. Additionally, the presence of a polylactone network in the elastomer enhances its biodegradability in specific natural biological environments, thereby enhancing the overall sustainability of the materials. 30 The resulting LAVE material exhibits high elasticity and low hysteresis and is able to self-heal under UV irradiation. The design flexibility of LAVE facilitates the tunability of mechanical properties, making it a potential candidate for sustainable elastomers used in soft robotics and electronics. Scheme 1 Schematic illustration of the LAVE preparation process.",
"discussion": "Results and discussion LAVE was produced through a combination of (i) ROP of lactones, (ii) esterification of polylactones with LA, and (iii) UV crosslinking (see Scheme 1 ). As a first step, a stannous octoate (Sn(Oct) 2 )-catalyzed ROP of lactones using ethylene glycol (EG) as the initiator was performed. ε-CL and δ-VL were chosen because of their mutual interference with their crystallization profile and their ability to form copolymers with desirable properties, with a mole ratio of 1 : 1. 31 We produced a series of diol primers (EG-CV- X , X = 10, 20, or 30) by varying the monomer to initiating site ratio (M/I, Table S1 † ) and achieved conversions as high as 98% after 240 min at 110 °C. To better understand the ROP, a kinetic study of EG-CV-10 was performed using 1 H-NMR. Unlike most macroinitiators, 30 EG does not impart any induction time during polymerization. With time, a decrease in the monomer fraction and an increase in the polymer fraction were observed. 1 H-NMR analyses performed on EG-CV- X feature the characteristic signals of PCL and PVL at 4.03, 2.28, 1.61, and 1.35 ppm (see Fig. 1A and Fig. S1 † ). After ROP, the characteristic peak of EG at 3.63 ppm (f) shifted downfield to 4.27 ppm (j) due to the addition of the electron withdrawing polylactone chains. Furthermore, the peak at 3.60 ppm represents the terminal CH 2 , and was used to calculate the degree of polymerization of the polylactone chains (Fig. S1 † ). 32 Since the polymerization was conducted in bulk, a minor amount of lactones was left in the system. Both catalyst Sn(Oct) 2 (0.91 ppm) and monomer will not influence further modification since they are inactive at room temperature, 33 and therefore, EG-CV- X was used without further purification. Fig. 1 (A) 1 H-NMR spectra of EG-CV-10, EG-CV-10-LA-F (full substituted), and EG-CV-10-LA-P (partly substituted); (B) FTIR of EG, EG-CV- X , EG-CV- X -LA, and LAVE. Size exclusion chromatography (SEC, Fig. 2A ) confirmed the polymeric nature of EG-CV- X , displaying a single polymer peak for each sample. With increasing M/I ratios, a significant shift of the polymer peak toward lower retention times was observed, indicating an increase in the molecular weight of EG-CV- X , from 3100 Da to 6000 Da. However, the molecular weight distributions ( Đ , Table S2 † ) of EG-CV- X were quite broad and increased from 2.22 to 2.83 with increasing M/I ratios. This is very common for ROP, likely due to side reactions such as transesterification, racemization, and the formation of macrocycles. 34,35 The molecular weights of EG-CV- X agreed well with the calculated values from 1 H-NMR spectroscopy and theoretical values based on the chemical composition of the system and increased linearly with the M/I ratios. Differential scanning calorimetry (DSC, Fig. 3A and Table S3 † ) analyses of EG-CV- X showed that all samples possess a melting temperature ( T m ), which increased from 13 °C for EG-CV-10 to 18 °C for EG-CV-30, correlating to the increased length of the PCL- co -PVL. It is worth noting that the T m of the pure PCL- co -PVL (1 : 1) is approximately 20 °C, higher than our systems, which may originate from EG hampering/limiting crystallization. 31 With an increased M/I ratio, EG-CV- X is closer to pure PCL- co -PVL without much steric restriction; hence an increased T m was observed. The cooling cycles show two crystallization peaks, in which the first is broader and the second is sharper, owing to the wide molecular weight distribution. With decreasing polylactone chain length in LAVE, the crystallization temperature ( T c ) increases slightly from −5 to −1 °C. In addition to SEC and DSC, further characterization of EG-CV- X was conducted using Fourier transform infrared spectroscopy (FTIR) ( Fig. 1B and Fig. S3 † ). The appearance of the C \n \n\n<svg xmlns=\"http://www.w3.org/2000/svg\" version=\"1.0\" width=\"13.200000pt\" height=\"16.000000pt\" viewBox=\"0 0 13.200000 16.000000\" preserveAspectRatio=\"xMidYMid meet\"><metadata>\nCreated by potrace 1.16, written by Peter Selinger 2001-2019\n</metadata><g transform=\"translate(1.000000,15.000000) scale(0.017500,-0.017500)\" fill=\"currentColor\" stroke=\"none\"><path d=\"M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z\"/></g></svg>\n\n O stretch at 1735 cm −1 alongside a decrease in the O–H stretch at 3300 cm −1 (from EG and terminal hydroxy) confirms the formation of the ester bond during the ROP of lactones with EG. Fig. 2 (A) SEC elugrams of EG-CV- X ; (B) SEC elugrams of EG-CV- X -LA. Fig. 3 DSC analyses of the (A) EG-CV- X , (B) EG-CV- X -LA and (C) LAVE systems. (D) Comparative thermogravimetric analyses of EG-CV- X , EG-CV- X -LA, and LAVE. In the second step, the remaining hydroxy groups of EG-CV- X were used to react with the carboxylic group from LA. Since LA has a heat-sensitive five-membered cyclic disulfide ring, Steglich esterification was performed using dicyclohexylcarbodiimide (DCC) and 4-dimethylaminopyridine (DMAP) to avoid using a high reaction temperature. In this reaction, DCC acts as a dehydrating agent and hydrates to form dicyclohexylurea (DCU), a compound nearly insoluble in most organic solvents and water. It is worth noting that the hydroxy groups were both fully and partially substituted. Fig. 1A shows a comparison of the partial and full substitution of EG-CV-10 (EG-CV-10-LA-P and EG-CV-10-LA-F), with some hydroxy left in the partly substituted polymers (peaks at 3.60 ppm representing –CH 2 –OH). The signals at 3.55 and 3.15 ppm confirmed the successful esterification and enabled the determination of the degree of substitution (DS) of EG-CV-10-P (DS = 1.4). The gel fraction showed that partial substitution (70%) of the hydroxy group could result in a stable crosslinked network (Fig. S4 † ). Therefore, for all EG-CV- X -LA samples, we used 0.7 equiv. of the carboxylic group per hydroxy groups to ensure complete crosslinking, while preserving sufficient dangling polylactone chains. 30 An appropriate proportion of dangling chains can significantly reduce the material's modulus by preventing the formation of entanglements, 36 increasing the flowability of the network. The resulting EG-CV- X -LA are viscous yellowish liquids, and their structure is depicted in Scheme 1 . Since LA only represents a small portion of EG-CV- X -LA, no visible changes were observed in FTIR ( Fig. 1B and Fig. S3 † ). The post esterification marginally increases the molecular weight of the polymers, which is visible in SEC elugrams ( Fig. 2B and Table S2 † ). The molecular weight from SEC was well correlated with that derived from the theoretical ( M w (theo)) and 1 H-NMR calculation ( M w (NMR)). To our surprise, the polydispersity of EG-CV- X -LA was greatly improved compared to that of EG-CV- X , probably due to the washing steps after the Steglich esterification. A decreased T c was observed after esterification, likely due to the introduction of LA, which inhibited PCL- co -PVL crystallization. With increased M/I ratios, a decreased T c was also observed. However, the changes in T m do not follow any visible rules. In the third step, EG-CV- X -LA was crosslinked by a UV lamp at a wavelength of 365 nm, without an initiator and premixing step, resulting in the production of LAVE X ( X = 10, 20 or 30, e.g. , LAVE10 refers to the elastomer made of EG-CV-10-LA). After UV irradiation, the slightly yellow, oily mixture EG-CV- X -LA turned into a transparent film LAVE X displaying a rubbery behavior with no visual sign of flowing. Even though LA itself is able to self-polymerize above its T m , 37 EG-CV- X -LA is unable to crosslink when heated in our investigation. Gel fraction measurements (Fig. S4 † ) were performed to monitor the potential leaching of noncrosslinked material. The higher the gel fraction, the higher the crosslinking density, indicating a more stable polymer network. In this study, the uncured EG-CV- X -LA was fully soluble in acetone; therefore, the gel fraction was zero. However, the cured films of EG-CV- X -LA showed excellent crosslinking and stability, with gel fractions ranging from 85% to 95% depending on the M/I ratios. The marginal increase in gel fraction with increasing M/I ratios can be attributed to the increased flexibility of primers, which facilitates crosslinking. This is consistent with the curing efficiency of EG-CV- X -LA. In contrast to the system described by Choi et al. , 28 in which the gel fraction shows a decreasing trend as the molecular weight of the primer increases. Our system, EG-CV-30-LA was fully cured after 20 min, while EG-CV-20-LA and EG-CV-10-LA needed 1 hour to be fully cured. This was probably due to the limited flexibility of EG-CV-10-LA and EG-CV-20-LA, which leads to slow polymerization and a lower gel fraction. Nonetheless, LAVE10 still possessed a high gel fraction of 85%, indicating that most EG-CV- X -LA was linked into the network. However, LAVE remains more stable in a solvent environment than commercially available EcoFlex (gel fraction of 60%). 38 To further confirm proper network integrity, a frequency sweep in the linear viscoelastic regime ( Fig. 4A and Fig. S5 † ) was performed to monitor the viscoelasticity of the materials before and after crosslinking. All LAVE samples showed a central plateau in G ′ and a multidecade separation between G ′ and G ′′, convincingly resembling rubber. On the other hand, the modulus of uncured DE-CV- X -LA vastly increased with increasing frequency, further confirming successful curing. Next, we investigated the thermal properties of LAVE. Thermogravimetric analysis (TGA, Fig. 3D ) showed a lower degradation profile for EG than for its derivatives. After ROP and esterification, the thermal stability of the primer significantly improves. Once crosslinked, the thermal stability reaches its maximum. LAVE starts to degrade at ∼300 °C with a maximal burn rate at ∼400 °C (Table S3 † ), which is beyond the requirements for most applications, such as wearables, grips, and biomedical devices. 39 There is little difference between LAVE produced using different PCL- co -PVL chain lengths. DSC ( Fig. 3C ) analyses of the elastomers showed that all LAVEs possess a T m below room temperature. However, no T g was observed within the temperature range of −75 to 150 °C. Fig. 4 (A) Oscillatory rheology measurements on EG-CV-10-LA and LAVE10; (B) tensile stress–strain curves of native and first cycle healed LAVE10; (C) cycling test of LAVE10; (D) photograph of healed LAVE30 during tensile testing. The results of the tensile tests conducted on the various LAVEs revealed interesting insights into the mechanical properties of these elastomers. As shown in Fig. 4B and Fig. S6, † the LAVEs exhibited characteristic behavior of elastomeric materials, with a high degree of strain at break. With an increase in the number of polylactone chains in LAVE, the strain at break increased from 25% to 180%. At the same time, the stress at break increased from 0.34 to 1.41 MPa (Table S4 † ). It is worth noting that the stress–strain curve follows a strict linear increase in tensile stress with increasing strain, which is also a typical behavior of DCNs, without the involvement of physical bonding and entanglements. 24 The exceptional stretchability and mechanical strength of LAVE can be attributed to two mechanisms: (1) dangling polylactone chains and (2) the two-phase network having disulfide as the crosslinks. To verify their reparability, the elastomers were cut into two pieces, joined back together and self-healed under UV irradiation. The ability of the LAVEs to self-heal under UV irradiation was further confirmed through force loading–unloading ( Fig. 4C and Fig. S7 † ). The repaired samples showed no significant change in their mechanical properties, even after 50 cycles of repeated stretching and relaxation. This contrasts with thermoplastic elastomers, which exhibit severe hysteresis in stretching–relaxation cycles, resulting in mechanical loss under cyclic loading. 40 The excellent mechanical stability of LAVEs after self-healing makes them ideal candidates for applications in which sustained mechanical performance is critical, such as in soft robotics or wearable electronics. Additionally, the adhesive properties of the primer used in our study contribute to the potential of the final products to function as an excellent bioglue. 41 To conclude, LAVA demonstrated excellent stretchability and self-healing properties, making it an idea candidate for sustainable and durable materials. Our materials have advantages over 100% natural polymers such as gelatin and cellulose, due to their mechanical tunability. Meanwhile, the primer (EG-CV- X -LA) can be crosslinked and self-healed via disulfide exchange without the addition of initiator or catalyst."
} | 5,216 |
20119486 | PMC2810364 | pmc | 3,186 | {
"abstract": "Honeybees exhibit two patterns of organization of work. In the spring and summer, division of labor is used to maximize growth rate and resource accumulation, while during the winter, worker survivorship through the poor season is paramount, and bees become generalists. This work proposes new organismal and proximate level conceptual models for these phenomena. The first half of the paper presents a push–pull model for temporal polyethism. Members of the nursing caste are proposed to be pushed from their caste by the development of workers behind them in the temporal caste sequence, while middle-aged bees are pulled from their caste via interactions with the caste ahead of them. The model is, hence, an amalgamation of previous models, in particular, the social inhibition and foraging for work models. The second half of the paper presents a model for the proximate basis of temporal polyethism. Temporal castes exhibit specialized physiology and switch caste when it is adaptive at the colony level. The model proposes that caste-specific physiology is dependent on mutually reinforcing positive feedback mechanisms that lock a bee into a particular behavioral phase. Releasing mechanisms that relate colony level information are then hypothesized to disrupt particular components of the priming mechanisms to trigger endocrinological cascades that lead to the next temporal caste. Priming and releasing mechanisms for the nursing caste are mapped out that are consistent with current experimental results. Less information-rich, but plausible, mechanisms for the middle-aged and foraging castes are also presented.",
"introduction": "Introduction Division of labor (DOL) in the honeybee is one of the most well explored phenomena in the study of animal behavior. Although studies go back to the 1800s, dedicated experimental work began in the 1930s and has continued to the present with numerous labs approaching the problem from every biological perspective (Rösch 1930 ; Lindauer 1952 ; Ribbands 1953 ; Free 1965 ; Seeley 1982 , 1995 ; Calderone and Page 1988 ; Page and Robinson 1991 ; Page et al. 1992 , 2000 ; Moritz et al. 2001 ; Page and Erber 2002 ; Robinson 2002 ; Grozinger and Robinson 2002 ; Grozinger et al. 2003 ; Johnson 2003 , 2005 , 2008a , b ; Robinson et al. 2005 ; Elekonich and Roberts 2005 ; Slessor et al. 2005 ; Whitfield et al. 2003 , 2006 ; Rüeppell et al. 2004 ; Amdam et al. 2003 ; Oldroyd and Thompson 2007 ; Schmickl and Crailsheim 2007 , 2008 ; Beekman et al. 2007 ; Smith et al. 2008 ). Given the expansive nature of this work, it is necessary that any researcher take an integrative approach. To facilitate this, a synthesis of behavioral ecology, physiology, and neurobiology approaches to the subject is presented. The biological disciplines included in this study were chosen because they all share a focus on qualitative mechanisms, typically feedback processes, for regulating worker behavior. The important role played by genotypic variability, in contrast, is quantitative in nature, in that it causes variability within the context of general qualitative mechanisms (Calderone and Page 1988 , 1991 ; Breed et al. 1990 ; Fewell and Bertram 1999 ; Kryger et al. 2000 ; Oldroyd and Thompson 2007 ). I therefore leave the role played by these effects to future work. The paper does not attempt to exhaustively review the many papers on honeybee DOL; instead, it conceptualizes the key results into two models: one at the behavioral level, the push–pull model, that explains the form and adaptive basis of DOL and another at the proximate level that explains how colony level needs are translated into individual-level patterns of physiological development."
} | 930 |
31844298 | null | s2 | 3,188 | {
"abstract": "Legumes obtain nitrogen from air through rhizobia residing in root nodules. Some species of rhizobia can colonize cereals but do not fix nitrogen on them. Disabling native regulation can turn on nitrogenase expression, even in the presence of nitrogenous fertilizer and low oxygen, but continuous nitrogenase production confers an energy burden. Here, we engineer inducible nitrogenase activity in two cereal endophytes (Azorhizobium caulinodans ORS571 and Rhizobium sp. IRBG74) and the well-characterized plant epiphyte Pseudomonas protegens Pf-5, a maize seed inoculant. For each organism, different strategies were taken to eliminate ammonium repression and place nitrogenase expression under the control of agriculturally relevant signals, including root exudates, biocontrol agents and phytohormones. We demonstrate that R. sp. IRBG74 can be engineered to result in nitrogenase activity under free-living conditions by transferring a nif cluster from either Rhodobacter sphaeroides or Klebsiella oxytoca. For P. protegens Pf-5, the transfer of an inducible cluster from Pseudomonas stutzeri and Azotobacter vinelandii yields ammonium tolerance and higher oxygen tolerance of nitrogenase activity than that from K. oxytoca. Collectively, the data from the transfer of 12 nif gene clusters between 15 diverse species (including Escherichia coli and 12 rhizobia) help identify the barriers that must be overcome to engineer a bacterium to deliver a high nitrogen flux to a cereal crop."
} | 371 |
39747160 | PMC11695860 | pmc | 3,190 | {
"abstract": "Nylon 12 is valued for its exceptional properties and diverse industrial applications. Traditional chemical synthesis of nylon 12 faces significant technical challenges and environmental concerns, while bioproduction from plant-extracted decanoic acid (DDA) raises issues related to deforestation and biodiversity loss. Here, we show the development of an engineered Escherichia coli cell factory capable of biosynthesizing the nylon 12 monomer, ω-aminododecanoic acid (ω-AmDDA), from glucose. We enable de novo biosynthesis of ω-AmDDA by introducing a thioesterase specific to C12 acyl-ACP and a multi-enzyme cascade converting DDA to ω-AmDDA. Through modular pathway engineering, redesign and dimerization enhancement of the rate-limiting P450, reconstruction of redox and energy homeostasis, and enhancement of oxidative stress tolerance, we achieve a production level of 471.5 mg/L ω-AmDDA from glucose in shake flasks. This work paves the way for sustainable nylon 12 production and offers insights for bioproduction of other fatty acid-derived products.",
"introduction": "Introduction As an important representative of aliphatic polyamides, nylon 12 exhibits excellent properties, including low water absorption, low relative density, high abrasion resistance, flame resistance, chemical resistance, and good weather resistance. Due to these advantages, nylon 12 is widely used in various fields such as 3D printing, automotive manufacturing, oil and gas exploitation, medical instruments, electronics, and other fields such as offshore pipelines and automotive parts 1 . However, the chemical synthesis of nylon 12 involves multiple steps and the use of toxic and corrosive raw materials, leading to high technical barriers and environmental concerns. Consequently, the bio-based synthesis of nylon 12 has garnered increasing attention in recent years. Currently, the bioproduction of nylon 12 monomers is mainly achieved through multi-enzyme cascade reactions converting dodecanoic acid (DDA) or its esters to ω-aminododecanoic acid (ω-AmDDA) or its esters 2 – 5 . In our previous work, we successfully constructed a cofactor self-sufficient multi-enzyme cascade pathway in E. coli for the biotransformation of DDA to ω-AmDDA 6 . This approach, combined with P450 directed evolution and enhanced heme supply, resulted in the production of 9.4 mM ω-AmDDA 7 . In all these studies, the substrate DDA and its derivatives were typically sourced from coconut oil and palm kernel oil. While the vegetable oil pathway offers high efficiency, it raises significant environmental concerns related to deforestation and biodiversity loss 8 . In addition, using edible vegetable oils for industrial oleochemical production intensifies the debate over whether land should be allocated for fuel or food 9 . These challenges could be mitigated if the nylon 12 monomer ω-AmDDA could be produced from glucose using microbial cell factories. The glucose pathway presents a more sustainable alternative with superior land use efficiency (please refer to Supplementary Note 1 for the calculation details), especially when utilizing non-food biomass. Although the theoretical maximum yield of the glucose pathway is lower due to its longer process, the substantially lower feedstock price and markedly higher land use efficiency of glucose production provide a strong foundation for its competitiveness. Moreover, ongoing advancements in metabolic engineering would steadily improve the actual yields of the glucose pathway. As research progresses, this pathway has the potential to not only match but also to surpass the overall efficiency of the vegetable oil pathway, when considering both economic and environmental factors. Using E. coli as the chassis, genome-scale genetic perturbation has successfully produced up to 30 g/L of free fatty acids 10 . For de novo biosynthesis of nylon 12 monomer, the selective synthesis of fatty acid with a chain length of 12 carbons is essential. Voelker et al. have demonstrated the production of a high proportion of free DDA in E. coli by introducing the medium-chain acyl-ACP thioesterase BTE from Umbellularia californica 11 . If this enzyme could be heterologously expressed in E. coli together with the multi-enzyme cascade pathway that converts DDA to ω-AmDDA 6 , the selective accumulation of DDA as an intermediate may enable the de novo biosynthesis of ω-AmDDA from glucose. A sufficient supply of DDA as the key precursor and its efficient conversion to ω-AmDDA is essential for high production of the nylon 12 monomer, which makes the regulation of the cell factory challenging. Dozens of genes are involved in the endogenous metabolic network and the heterologous synthetic pathway, along with the requirement for various metals and multiple cofactors such as NADPH, NADH, and pyridoxal 5’-phosphate (PLP) to support enzyme activities 12 . Additionally, the heterologous product and intermediates may exert adverse effects on the chassis cells 13 . Therefore, the performance of an ω-AmDDA cell factory is combinatorically determined by the balanced expression and activity of both endogenous and heterologous enzymes, availability of multiple cofactors, and tolerance to the toxic metabolites. In this work, we develop a multi-level regulation strategy to enable efficient de novo biosynthesis of nylon 12 monomer ω-AmDDA from glucose, a cost-effective and renewable feedstock. We integrate modular pathway engineering, cofactor engineering, tolerance engineering, and protein engineering to optimize the complex synthetic pathway. By bridging endogenous fatty acid metabolism with a heterologous multi-enzyme cascade that converts DDA to ω-AmDDA, we construct an engineered E. coli strain capable of biosynthesizing ω-AmDDA from glucose. Additionally, we reconstruct the metabolic balance in this cell factory by strengthening and balancing the four pathway modules (glycolysis, acetyl-CoA activation, acyl-ACP synthesis, and heterologous DDA transformation), regulating NAD(P)H and ATP supply, enhancing oxidative stress tolerance, and engineering the rate-limiting P450 (Fig. 1 ). This comprehensive approach results in the construction of an efficient ω-AmDDA cell factory, paving the way for sustainable glucose-derived nylon 12 production. Fig. 1 De novo biosynthesis of nylon 12 monomer from glucose. D-Gdl D-glucono-δ-lactone, ETC electron transport chain, ROS reactive oxygen species, DDA dodecanoic acid, ω-OHDDA ω-hydroxydodecanoic acid, ω-AmDDA ω-aminododecanoic acid.",
"discussion": "Discussion To establish a green and sustainable production route of nylon 12 monomer, de novo biosynthesis of ω-AmDDA using glucose as feedstock was achieved by introducing a thioesterase for selective DDA production, along with a multi-enzyme cassette for converting DDA to ω-AmDDA into E. coli . However, the significantly lower ω-AmDDA titer (27.5 mg/L) in the engineered cell factory, even after optimizing culture conditions, compared to that of resting cells harboring the same multi-enzyme cassette (1.04 g/L) 6 , suggests a higher complexity in the de novo biosynthesis system. This discrepancy may be attributed to an unbalanced supply and conversion of DDA as the key intermediate in the cell factory, disturbed metabolic homeostasis, and intermediate/product toxicity associated with ω-AmDDA biosynthesis in growing cells. Fatty acids, including DDA, may be secreted after biosynthesis, leading to substrate inaccessibility for the DDA-converting enzymes. Secretion of palmitic acid was observed during the biosynthesis of ω-hydroxypalmitic acid, and the overexpression of the endogenous outer membrane protein FadL enhanced ω-hydroxypalmitic acid production by improving the re-uptake of secreted palmitic acid 53 . Additionally, overexpressing the outer membrane protein AlkL from P. putida GPo1 in recombinant E. coli containing the alkane monooxygenase AlkBGT for dodecanoic acid methyl ester oxygenation addressed the substrate mass transfer issue and increased oxygenation activity by 28-fold 54 . When DDA was used as the substrate for biotransformation using recombinant E. coli strains, AlkL overexpression improved the ω-AmDDA yield by 20.3% 6 . Changes in the intracellular/extracellular distribution of DDA before and after AlkL overexpression in the ω-AmDDA cell factory confirmed the secretion of DDA during ω-AmDDA de novo biosynthesis and suggested that the re-uptake of secreted precursors contributed to the improved production of ω-AmDDA (Supplementary Fig. 8 ). Besides DDA loss by secretion, its synthesis and conversion efficiencies determined the flux towards ω-AmDDA biosynthesis. DDA biosynthesis from glucose involves enzymes for glycolysis, acetyl-CoA activation, acyl-ACP synthesis, and thioesterification of C12 acyl-ACP, while its conversion is mediated by the heterologous pathway composed of a chimeric P450, an alcohol dehydrogenase, an ω-TA, and the cofactor-regenerating GDH1, AlaDH2, and yaaDE. The involvement of dozens of genes in ω-AmDDA de novo biosynthesis renders its regulation challenging. The modular pathway engineering strategy, which divides the complex pathway into several modules, largely simplified the manipulation. By designing and overexpressing the glycolysis, acetyl-CoA activation, acyl-ACP synthesis modules individually and in combination together with the heterologous ω-AmDDA formation module, the rate-limiting steps of ω-AmDDA de novo synthesis were identified as glycolysis, acyl-ACP synthesis and the P450-mediated DDA hydroxylation. Meanwhile, the key genes from difference sources with better performance in acetyl-CoA activation and acyl-ACP synthesis were selected out, leading to 3-fold higher ω-AmDDA production. However, excessive accumulation of DDA, resulted from simultaneous overexpressing the glycolysis, acetyl-CoA activation, and acyl-ACP synthesis modules, or multi-copy expression of the acyl-ACP synthesis module, or elevating BTE expression, decreased both the biomass and ω-AmDDA production, indicating cytotoxicity. Exogenous addition of DDA has shown substantial toxicity against bacteria 55 , and the synthesis of fatty acids in the cells exacerbates the adverse effects on cell viability and productivity 56 . These results suggested sufficient but not excessive DDA supply as a key to efficient de novo biosynthesis of ω-AmDDA, and demonstrated the effectiveness of modular pathway engineering in regulating such complex pathways. To reconstruct the balance between DDA formation and conversion, DDA hydroxylation was reinforced by engineering CYP153A-NCP. Tertiary-structure-based multiple sequence alignment was found to be more efficient in identifying positive engineering targets compared primary-structure-based multiple sequence alignment, provided that tertiary structures are accessible. These structures can be obtained using protein structure prediction tools such as Alphafold3 57 . Besides the rational engineering of residues in or on top of the substrate-binding tunnels, saturation mutagenesis of the residues at the tunnel entrance also generated positive variants. Finally, a combinatorial mutant CYP153Am4-NCP with 89% activity improvement was obtained. In this process, a colorimetric high-throughput screening method for in situ DDA hydroxylation detection was developed based on the coupled transamination reaction using 4-nitrophenylamine as the amine donor, which provides the possibility for in vivo directed evolution or co-evolution of single or multiple enzymes involved in ω-AmDDA biosynthesis. In addition, the hydroxylation activity was further elevated by N-terminal fusion of intermolecular affinity-enhancing structures to enhance protein dimerization of CYP153Am4-NCP. Studies have shown that increasing the affinity between homodimer or oligomer protein molecules can promote the formation of the correct quaternary structure and improve their function 58 . Interestingly, C-terminal fusion constructs all failed to enhance the activity. Since the C-terminus of NCP is part of the FAD-binding pocket and is less exposed to solvents 45 , domain dimerization may limit its accessibility for FAD and thus hinder catalysis. In addition to the metabolic flux of the target synthetic pathway, maintaining metabolic homeostasis is also crucial for the fermentative production of microbial cell factories 59 . However, the burden of ω-AmDDA de novo synthesis may disrupt this homeostasis. A redox imbalance can arise from the substantial consumption of NAD(H) and NADP(H) during fatty acid biosynthesis and the conversion of DDA to ω-AmDDA, which can significantly hinder cellular metabolism and impair the growth and biosynthesis performance of the engineered strains 60 . Moreover, the production and accumulation of DDA and its derivatives can lead to ROS accumulation, which may be exacerbated by redox imbalance and insufficient electron transfer efficiency during heterologous pathway oxidoreductase reactions, such as P450 17 , 35 , 61 – 63 . Therefore, the redox homeostasis and ROS tolerance of the cells were modulated to further improve the performance of the cell factory. Due to the lower abundance of NADP(H) than NAD(H) in cells 64 , enhancing the supply of NADP(H) is often beneficial for restoring redox balance. Overexpression of the NADH kinase Pos5p has proven to be an efficient strategy in the metabolic engineering of S. cerevisiae , resulting in increased production of retinoids 65 and tocotrienols 66 by bolstering NADPH supply. Similarly, PntAB and NadK in E. coli catalyze the conversion of NAD(H) to NADP(H). As anticipated, overexpression of these enzymes contributed to enhanced production of ω-AmDDA. However, excessive PntAB overexpression significantly impaired cell growth and ω-AmDDA production. This may be attributed to the excessive consumption of NADH and ATP by PntAB 28 . Besides the NADP(H)/NAD(H) ratio, the ratio of the reduced form to the oxidized form also affects the redox homeostasis. In the multi-enzyme cassette for converting DDA to ω-AmDDA, the glucose dehydrogenase GDH1 had been introduced to regenerate NAD(P)H from NAD(P) + 6 , but its efficiency may be limited by the availability of unphosphorylated glucose as its substrate, since most glucose is transported via the PTS system in the form of 6-phospho-glucose. By introducing the Z. mobilis Glf to strengthen transportation of unphosphorylated glucose, both glucose consumption and NADPH regeneration were enhanced (Supplementary Table 1 ), leading to further improvement in ω-AmDDA production. These results suggest moderately expanding the NADP(H) pool and accelerating NADPH regeneration rather than excessively enhancing the NADP(H)/NAD(H) ratio as an efficient approach to regulate the redox cofactors. In addition, ATP is required in the bioconversion of NAD(H) to NADP(H), and also in fatty acid biosynthesis 32 , 33 . Therefore, there may be a shortage of ATP supply in the cell factory, which can be addressed by blocking reactions that competitively consume ATP or by enhancing substrate-level phosphorylation. However, because PEP plays a crucial role in the native metabolism of E. coli , its consumption during substrate-level phosphorylation may have adverse effects. Accordingly, deleting the gene encoding the ATPase in the citrate-dependent iron transport system, rather than overexpressing the heterologous PEP carboxykinase, improved ω-AmDDA production. Studies have shown that strengthening the ROS defense enzyme system in E. coli can significantly increase its survival rate under ROS stress 67 – 69 and improve the production of chemicals that induce oxidative stress 69 . Overexpression of the ROS defense regulator OxyR significantly reduced the ROS level in the engineered cells (Supplementary Table 1 ), and improved both the ω-AmDDA titer and biomass (Fig. 5 and Supplementary Table 1 ). However, its excessive overexpression negatively affected the cell factory. This might be universal for transcription factors with broad regulation targets, as observed in a previous study where moderate rather than excessive overexpression of the transcriptional factor Gal4p improved isoprene production in S. cerevisiae 70 . It is worth noting that the effect of engineering oxidative stress tolerance was more pronounced in the strain where the NADP(H) supply was not strengthened (Fig. 5D ). This suggests that the imbalance in intracellular redox homeostasis may be a possible source of oxidative stress. In conclusion, efficient de novo biosynthesis of the nylon 12 monomer ω-AmDDA using glucose as feedstock has been achieved in an E. coli cell factory. Although the current yield of ω-AmDDA from glucose is modest at 0.01 g per gram, this milestone underscores both the challenges ahead and the significant potential for further research and optimization. This work establishes a foundational framework for the fermentative production of nylon 12, marking a crucial advancement toward sustainable bioproduction. To regulate such a complex pathway composed of glycolysis, acetyl-CoA activation, fatty acid selective synthesis, and DDA transformation processes involving multiple genes and different cofactor requirements, and meanwhile to mitigate the adverse effects caused by cytotoxic intermediates and product, a combinatorial engineering strategy was proposed, which integrates modular pathway engineering, cofactor engineering, tolerance engineering, and protein engineering (Fig. 9 ). This multi-level metabolic regulation strategy covering the rate-limiting enzyme, pathway flux, cofactor, energy supply, and oxidative stress tolerance would provide a valuable reference for optimizing the biosynthesis of ω-AmDDA and other fatty acid-derived compounds. Fig. 9 Construction and optimization of the ω-AmDDA cell factory. DDA dodecanoic acid, ω-AmDDA ω-aminododecanoic acid."
} | 4,474 |
38538313 | PMC10982111 | pmc | 3,191 | {
"abstract": "A more detailed understanding of the mechanisms underlying the formation of microbial communities is essential for the efficient management of microbial ecosystems. The stable states of microbial communities are commonly perceived as static and, thus, have not been extensively examined. The present study investigated stabilizing mechanisms, minority functions, and the reliability of quantitative analyses, emphasizing a metabolic network perspective. A bacterial community, formed by batch transferred cultures supplied with phenol as the sole carbon and energy source and paddy soil as the inoculum, was analyzed using a principal coordinate analysis (PCoA), mathematical models, and quantitative parameters defined as growth activity, community-changing activity, community-forming activity, vulnerable force, and resilience force depending on changes in the abundance of operational taxonomic units (OTUs) using 16S rRNA gene amplicon sequences. PCoA showed succession states until the 3 rd transferred cultures and stable states from the 5 th to 10 th transferred cultures. Quantitative parameters indicated that the bacterial community was dynamic irrespective of the succession and stable states. Three activities fluctuated under stable states. Vulnerable and resilience forces were detected under the succession and stable states, respectively. Mathematical models indicated the construction of metabolic networks, suggesting the stabilizing mechanism of the community structure. Thirteen OTUs coexisted during stable states, and were recognized as core OTUs consisting of majorities, middle-class, and minorities. The abundance of the middle-class changed, whereas that of the others did not, which indicated that core OTUs maintained metabolic networks. Some extremely low abundance OTUs were consistently exchanged, suggesting a role for scavengers. These results indicate that stable states were formed by dynamic metabolic networks with members functioning to achieve robustness and plasticity.",
"discussion": "Discussion A more detailed understanding of microbial community dynamics consisting of community succession and stable states is important for managing microbial ecosystems. The present study focused on stable states that have been recognized as static states without deep attention because they are valuable for productivity and functionality in natural and engineered microbial systems. In the present study, the dynamics of bacterial communities were evaluated using PCoA, mathematical models, and quantitative analyses. The results obtained indicated that the stable states of bacterial communities were formed via dynamic metabolic networks with members functioning to achieve robustness and plasticity. This challenges our conventional understanding of microbial ecosystems. Average growth activity, community-changing activity, and community-forming activity showed that bacterial communities are always in a dynamic state irrespective of succession or stable states recognized by PCoA. Vulnerable and resilience forces were useful parameters for quantitatively distinguishing which bacterial community was in a succession or stable state: bacterial communities were under stable states when resilience force was detected and vice versa . Quantitative analyses showed that community-changing activity gradually decreased from approximately 180 to 27 during succession states, whereas community-forming activity was stable at approximately 180 with constant and low average growth activity at around 0.35. These results suggest that the majority of bacteria did not adapt well to new conditions (the carbon source was phenol), whereas specific bacterial groups adapted, grew constantly, and remained stable. In the succession state, γ-proteobacteria was dominant in the diverse soil bacterial community ( Fig. 1 B), providing quantitative insights into selection processes in new environments. The three activities were not stable, but fluctuated under the stable states, which would be an important cue to understand them. Fluctuations in these activities suggest that the microbial community was formed via metabolic networks. Metabolic networks play roles in the functional stability of a whole system by supporting common goods ( Morris et al. , 2013 ; Niehaus et al. , 2019 ; Smith and Schuster, 2019 ) and removing toxic metabolic byproducts that inhibit the growth of other bacteria ( Luli and Strohl, 1990 ; Lilja and Johnson, 2016 ; Aziz et al. , 2021 ; Mohd Din et al. , 2021 ). Pure and synthetic microbial cultures collapse with feedback inhibition caused by the accumulation of metabolites ( Aziz et al. , 2015 ; Mohd Din et al. , 2021 ), suggesting that a fixed metabolic network is incapable of maintaining a stable state, even in complex systems. Among the 13 core OTUs, the abundance of OTUs_9947, 2765, and 2727 was mostly maintained and they kept their dominant states ( Fig. 4 A). They belonged to Acinetobacter and Comamonas (Supplementary Fig. S3 ), and specific strains belonging to these genera are known as phenol-utilizing bacteria with higher growth activity ( Futamata et al. , 2001a , 2005 ; Aziz et al. , 2015 ). Therefore, these bacteria appear to predominantly utilize phenol, whereas the simulation of the rank-abundance distribution showed that all bacteria corresponding to high ranks did not necessarily exhibit a strong preference for phenol ( Fig. 3 ). These results are consistent with our previous culture-dependent findings ( Aziz et al. , 2021 ); a bacterium becomes dominant by microbial cheating of public goods ( Smith and Schuster, 2019 ) supplied from minor populations, indicating that all dominant OTUs did not necessarily utilize phenol. OTU_4642 and 7749 belonged to Acinetobacter and Pseudomonas , and specific strains belonging to these genera are known as phenol utilizers ( Watanabe et al. , 1996 ; Futamata et al. , 2001a , 2005 ; Aziz et al. , 2015 , Suzuki et al. , 2016 ); however, they remained a minority ( Fig. 4 B). The rank-abundance distribution suggested that minorities exhibited a weaker preference for phenol and coexisted with majorities, challenging the common assumption that this preference is overcome under competitive conditions. Previous culture-dependent research demonstrated that a minor phenol-utilizing bacterium suppressed phenol hydroxylase, but expressed catechol dioxygenase under coexisting conditions, resulting in the obviation of competitive conditions for phenol, while minor populations incurred the cost for catechol degradation to maintain the functional stability of the whole system ( Aziz et al. , 2021 ). A previous study reported that minorities (abundance as low as 0.1%) played roles in the central hub and communication, maintaining the stability and functionality of the microbial community ( Guo et al. , 2022 ). These findings suggest that OTU_4642 and 7749 incurred the cost for catechol degradation and supplied common goods, contributing to the maintenance of stable states. The dynamics of middle-class OTUs differed from each other ( Fig. 4 A and B), which may change not only the metabolism of some bacteria in communities, but also interspecies interactions. The dynamics of middle-class OTUs may release the fixed metabolism of the whole system and contribute to the maintenance of stable states because all core OTUs exhibited specific resilience force ( Fig. 4 F). These results indicate that core OTUs, which had coexisted and occupied more than 98% of total abundance, functioned for the robustness of the bacterial community under the stable state. In contrast, extreme minorities consistently underwent exchanges in every transferred culture ( Fig. 5 A, B, and C, and Supplementary Fig. S5 ). Growth activity was not necessarily a factor for the exchange of extreme minorities because disappeared OTUs exhibited similar levels to remaining OTUs ( Fig. 5 D). Therefore, their survival may be restricted by the metabolites produced from highly abundant OTUs in dynamic metabolic networks. These results suggest that extreme minorities play a role as final scavengers for changeable metabolites, contributing to the plasticity of the bacterial community in the stable state. Fluctuations in the three quantitative parameters appeared to accurately reflect community physiological conditions. In observations of the changing symptoms of stable states, we focused on community vulnerability and resilience forces. A weak force was evident during the 7 th to 9 th transferred cultures, coinciding with changes in the abundance of middle-class OTUs ( Fig. 4 B) and the strong exchange of extreme minorities (Supplementary Fig. S4 C). The average growth activity of total OTUs was <1.0 in the 10 th transferred culture, similar to the level observed during the succession state ( Table 1 ). The community structure underwent tentative changes from the 10 th to 12 th cultures ( Fig. 1 A). Community-changing and -forming activities in the 10 th transferred culture were not as high as those in the succession state, and resilience force was re-exhibited, suggesting dynamic metabolic network functions. A more detailed understanding of the permissible range of fluctuations for stabilizing microbial ecosystems is crucial, and the driving force behind bacterial community succession, which changes from one stable state to another, remains unknown. Quantitative analyses are expected to provide valuable information for solving this problem using diverse complex microbial samples. These aspects are currently under investigation in our laboratory."
} | 2,407 |
35857760 | null | s2 | 3,192 | {
"abstract": "Bacteria are keenly sensitive to properties of the surfaces they contact, regulating their ability to form biofilms and initiate infections. This study examines how the presence of flagella, interactions between the cell body and the surface, or motility itself guides the dynamic contact between bacterial cells and a surface in flow, potentially enabling cells to sense physicochemical and mechanical properties of surfaces. This work focuses on a poly(ethylene glycol) biomaterial coating, which does not retain cells. In a comparison of four "
} | 136 |
27757415 | PMC5065250 | pmc | 3,193 | {
"abstract": "Plants have convergently evolved to use monolignol ferulate conjugates to produce lignins containing chemically labile backbone esters.",
"introduction": "INTRODUCTION One of the major adaptations of terrestrial plants to life on land is their ability to produce lignin for structural strength and defense ( 1 ). Stochastically synthesized through stepwise radical coupling of 4-hydroxycinnamyl alcohols (called monolignols, primarily coniferyl and sinapyl alcohols), lignin is a polymer with aryl ether and various other C–O–C and C–C interunit connections ( 2 , 3 ). Fragmentation of lignin allows polysaccharidase enzymes to access and convert cell wall polysaccharides to monomeric sugars or facilitates cell wall deconstruction to cellulose, hemicelluloses, and lignin fragments. These components are used in economically important processes, including production of paper and other fiber products, second-generation biofuels, and other bioproducts ( 4 , 5 ). Lignin fragmentation often requires high temperatures and/or harsh chemical treatments to cleave even its weakest interunit bonds ( 6 , 7 ). However, if chemically labile ester bonds are introduced into the lignin polymer, as can be accomplished by augmenting the prototypical monomers with monolignol ferulate (ML-FA) conjugates ( Fig. 1A ), then lignin fragmentation can occur under mild pretreatment conditions ( Fig. 1B ) ( 8 – 10 ). The findings here provide evidence that “zip-lignins,” lignins derived, in part, from ML-FAs, have developed naturally via convergent evolution in diverse angiosperm lineages ( Fig. 2 ). Fig. 1 Incorporation of ML-FAs into lignin introduces chemically labile esters into the polymer backbone. ( A ) FMT enzyme couples feruloyl-CoA and monolignols together to form ML-FA conjugates. The compounds are then transported to the cell wall and undergo radical coupling–based polymerization to form lignin; all the bonds that can be formed when ML-FAs are incorporated into β-ether structures in zip-lignin are shown with dashed lines. ( B ) Mild base (for example, 0.05 M NaOH at 30°C) cleaves the ML-FA–derived (green) ester bonds dividing the polymer into ≤( n + 1) fragments, where n is the number of ML-FA units. ( C ) DFRC breaks down the lignin by cleaving β-aryl ethers but leaving the esters intact. ( D ) Electron impact MS fragmentation pattern for coniferyl and sinapyl DHFA (G-DHFA and S-DHFA). FW, formula weight; m / z , mass/charge ratio. ( E ) GC-MRM-MS chromatograms of the DFRC product mix reveal the presence of the diagnostic products for ML-FA incorporation into lignin from a number of WT plants. The symbol ♦ indicates the signals corresponding to S-DH p CA, which shares an MRM transition with G-DHFA. Initial work on the incorporation of ML-FAs into plant lignin was carried out by engineering poplar trees ( Populus alba × Populus grandidentata ) to express a gene from Chinese angelica [ Angelica sinensis ( As ), a dicotyledonous Chinese medicinal plant] encoding a feruloyl–coenzyme A (CoA) monolignol transferase ( As FMT) ( 8 ). The As FMT enzyme couples monolignols with feruloyl-CoA, an intermediate in the monolignol biosynthetic pathway (fig. S1), to produce ML-FAs. As FMT is a member of a family of proteins found in plants and fungi termed BAHD acyltransferases (AT; Fig. 3 ) ( 11 ). AsFMT -expressing poplar trees produce ML-FAs and use them in lignification, resulting in improved cell wall saccharification following mild base pretreatment ( 8 ). Fig. 2 Comparison of the DFRC-releasable ML-DHFA conjugates among plant species. ( A ) A phylogenetic tree of the spermatophytes (“seed plants”), with the orders and families in which plant species were studied. ( B ) DFRC-released ML-DHFA conjugates; red bars indicate no evidence of ML-DHFAs. Bars indicate SEM for the summation of detected conjugates on duplicate analyses run on a single sample prepared from each plant species. The lignin assay, derivatization followed by reductive cleavage (DFRC) ( 12 ), was used to confirm that ML-FAs were integrally incorporated into the lignin of AsFMT -expressing poplar trees ( 8 ). DFRC cleaves β-ether bonds to release lignin fragments ( 12 ), while leaving the ester linkages of incorporated ML-FAs intact. Hence, DFRC-releasable coniferyl and sinapyl dihydroferulate diacetates (ML-DHFAs; Fig. 1C ) are diagnostic for the ML-FAs incorporated into lignin and their release level is proportional to the amount of ML-FAs in the lignin ( 8 ). However, because DFRC releases just a fraction of the incorporated ML-FAs as ML-DHFAs, only the relative level of conjugates in the lignin can be determined ( 8 ). The threshold to detect DFRC-released ML-DHFAs by gas chromatography–multiple reaction monitoring–mass spectrometry (GC-MRM-MS; table S1) is ~0.01 mg/g of acetyl bromide soluble lignin (ABSL) (see Materials and Methods). These experimental conditions revealed that wild-type (WT) poplar trees already release low levels (0.3 mg/g of ABSL) of the ML-DHFAs from their lignins ( 8 ), indicating that poplar plants naturally synthesize ML-FA conjugates and use them in lignification.",
"discussion": "DISCUSSION Upon examination of the phylogeny of the assessed plant species ( Fig. 2 ), some patterns emerged. For example, plants known to produce significant levels of other monolignol conjugates also incorporate ML-FAs into their lignins. These include the commelinids, which incorporate monolignol p -coumarates into their lignins and also have ferulates acylating the arabinoxylan hemicelluloses ( 18 ), and plants that use monolignol p -hydroxybenzoates in lignification, such as palms (Arecaceae), willows ( Salix ), and poplars/aspen ( Populus ). A weaker link exists between plants incorporating ML-FAs and those known to use monolignol acetates, which include kenaf and sisal ( 19 ), several other monocots ( 20 – 22 ), and various hardwoods ( 23 , 24 ). However, the introduction of ML-FAs into Arabidopsis via transgenesis, which appears to natively lack them, indicates that the ability to use monolignol conjugates does not appear to be isolated to those species that have evolved to do so, highlighting the plasticity of cell wall lignification. The evidence for BAHD proteins with FMT activity (fig. S2) suggests that the activity has arisen at least twice; that is, it has convergently evolved. For example, the two nonhomologous FMT protein sequences, Os FMT from a commelinid monocot and As FMT from a eudicot, have little sequence similarity (20%). Furthermore, the model that shows that FMT activity is an ancestral trait of angiosperms is inconsistent with the apparent absence of DFRC-releasable ML-DHFAs in most of the noncommelinid monocots and many of the eudicots, although it cannot be ruled out. Whether an As FMT ortholog is responsible for the incorporation of ML-FAs into eudicot lignins is unclear from the phylogenetic reconstructions. Analysis of the genomes of the ML-FA–producing eudicot tree species Eucalyptus globulus and Populus trichocarpa reveals a large number of clade III BAHD ATs that are absent from the commelinids, none of which have great similarity to As FMT, as the closest poplar homologs are POPTR_0001s31750 and POPTR_0004s01720, with 36% identity (fig. S2A). The convergent evolution and subsequent proliferation of plants that incorporate ML-FA conjugates into their lignins indicate that, potentially, there is a biological advantage for the production of this lignin structure. Regardless of the actual driving forces selecting for them, the diversity and environmental success of plants with native zip-lignins show that they have no apparent general disadvantages in terms of plant defense or structural stability. Finally, our findings further refute the contention by some researchers that lignins are derived only from three monolignols. It has been increasingly evident over the past 20 years that many other compounds biosynthesized by plants are used as monomers in lignification ( 2 , 3 , 25 , 26 ). As demonstrated here, ML-FA conjugates must now be added to the list of authentic lignin precursors. In practical terms, our discovery unveils new approaches to increasing levels of readily cleavable ester bonds in the lignin backbone, either by breeding or by transgenic methods similar to those used to introduce AsFMT into poplar ( 8 ). Further work is also needed to explore the effects of ML-FA–containing lignins on processes such as carbon sequestration and biomass utilization."
} | 2,120 |
36828856 | PMC9957988 | pmc | 3,196 | {
"abstract": "Neuromorphic computing using nonvolatile memories is expected to tackle the memory wall and energy efficiency bottleneck in the von Neumann system and to mitigate the stagnation of Moore’s law. However, an ideal artificial neuron possessing bio-inspired behaviors as exemplified by the requisite leaky-integrate-fire and self-reset (LIFT) functionalities within a single device is still lacking. Here, we report a new type of spiking neuron with LIFT characteristics by manipulating the magnetic domain wall motion in a synthetic antiferromagnetic (SAF) heterostructure. We validate the mechanism of Joule heating modulated competition between the Ruderman–Kittel–Kasuya–Yosida interaction and the built-in field in the SAF device, enabling it with a firing rate up to 17 MHz and energy consumption of 486 fJ/spike. A spiking neuron circuit is implemented with a latency of 170 ps and power consumption of 90.99 μW. Moreover, the winner-takes-all is executed with a current ratio >10 4 between activated and inhibited neurons. We further establish a two-layer spiking neural network based on the developed spintronic LIFT neurons. The architecture achieves 88.5% accuracy on the handwritten digit database benchmark. Our studies corroborate the circuit compatibility of the spintronic neurons and their great potential in the field of intelligent devices and neuromorphic computing.",
"introduction": "Introduction Neuromorphic computing (NC) imitates the functions of the brain by utilizing a network of synthetic neurons interconnected among synaptic devices 1 , 2 . Owing to its potential for artificial intelligence (AI) and big data analysis in an energy-efficient manner beyond the traditional von Neumann computing system, NC is attracting intensive attention worldwide and promising to deliver increased intelligence for autonomous driving, embedded artificial intelligence of things (AIoT) and terminal devices 1 – 5 . Since early 2000s researchers found that it is feasible to develop neuromorphic neuron and synapse devices to realize complex and highly reliable neural networks on a chip 6 , there have been many attempts to simulate the brain’s functions using traditional silicon technology over the last two decades. But AI is asking questions about the best way to build an NC system. Researchers have been trying to mimic the various characteristics of biological neurons 7 utilizing either traditional complementary metal-oxide-semiconductor (CMOS) technology 8 or emerging nonvolatile memory (NVM) devices, such as spintronic memory 9 – 14 , resistive switching memory 15 , 16 , phase change memory 17 , and ferroelectric memory 18 . However, most of these approaches, especially traditional CMOS technology-based neuron circuits, require multiple capacitors and dozens of transistors, which involve enormous amounts of power and area for emulating complex behaviors of biological neurons 1 . In contrast, the NC based on NVMs promises to provide a more efficient solution for complex tasks such as pattern recognition, machine learning and edge computing, as they can better simulate the biological characteristics of neurons, e.g., leaking, integrating, firing and auto-reset capabilities with less or free of transistor and capacitors 1 , 2 . Among them, spintronic NVM, which allows the implementation of nonlinear magnetization dynamics on nanoscale, provides numerous opportunities in this field 3 , 19 . In the research community of spintronic neuron devices, the studies of magnetic skyrmion and domain wall (DW) are rising 20 . However, the injection and manipulation of skyrmion are still immature 21 and the skyrmion-based devices require exotic or wedge-shaped structures 12 , 13 , rendering the deteriorated stability and high process complexity. In contrast, magnetic DW nucleation and manipulation techniques are intensively developed 22 – 24 . The DW-based spintronic devices combine unique features that other technologies cannot match, including non-volatility, outstanding read/write endurance, high-speed operation, and high scalability. Nevertheless, the reported DW-neuromorphic devices warrant considerable improvements. For example, Fan et al. 14 reported a non-linear spin-transfer torque neuron (STT-Neuron) with neuron circuit application but it lacks the leaky characteristics like biological neurons, in particular, the essential reset operation inevitably involves the complex operation and increased power consumption. Hassan et al. 11 demonstrated a type of DW-Neuron with leaky-integrate-fire (LIF) characteristics by applying a large area of the hard magnetic layer and claimed a local inhibition between adjacent neurons through the stray field between devices. However, these reports are purely based on the simulation framework with no genuine global inhibition, hence it is urgent to experimentally verify the feasibility of DW based LIF devices with self-reset and complementary device-circuit implementation with superior power efficiency to conventional computers, to facilitate the integrated AI applications in CMOS compatible industrial level mass production. Moreover, it is expected to solve reliability, area cost and energy efficacy bottlenecks and provide more possibilities for learning and computing processes of large-scale NC. Typically, the magnetoresistive random-access memory (MRAM) bears competitive advantages of high read and write speed, high reliability, ultra-low power consumption, and nearly infinite endurace 25 , 26 . Therefore, developing neuromorphic hardware based on the advanced MRAM components is paramount important from the practical application perspectives, in which the synthetic antiferromagnet (SAF) 27 – 29 poises as the kernel of the commercialized MRAM cell, i.e., magnetic tunnel junction (MTJ) as described in early reports and our previous works 3 , 30 – 38 . In the present work, to tackle the aforementioned challenges and bottleneck, upon extensive investigations on the dynamic process of field- and current-driven DW motion (DWM) in the SAF heterostructure, we further explore the modulation of interlayer-exchange-coupling (IEC) by engineering the dynamic Joule heating. Importantly, for the first time, we propose a new type of highly reliable spintronic neuron device with leaky-integrate-fire and self-reset (LIFT) features based on the tailored DWM in the spin-polarized ferro-coupler layers of SAF heterostructure, intrinsically mimicking the LIFT behaviors of neurons under a synergistic effect of built-in field (H built-in ) and Ruderman–Kittel–Kasuya–Yosida (RKKY) interaction without any additional reset devices or circuitry. Aiming at the CMOS compatible and manufacturable application, the winner-takes-all (WTA) 39 with global inhibition has been realized among the developed neuron devices by differentiating current through the negative differential resistance (NDR) effect of the semiconductor 40 , and the feasibility of the neuron device in the spiking neural networks (SNN) and its good circuit compatibility with high performance were verified.\n\nSpintronic neurons with LIFT characteristics A series of Hall bar-like devices were fabricated and the corresponding Kerr images were recorded as shown in Fig. 2a, b . From Fig. 2c , an obvious shift from measured major and minor Kerr magnetic hysteresis loops validates that there is an effective field of 885 Oe existing between the ferro-coupled layers of CoFeB/Co and the bottom hard layer in the SAF heterostructure. Both enhanced coercivity and RKKY effective fields are attributed to the device shrinking 47 and the unavoidable peripheral edge damages introduced during the ion beam etching (IBE) process 48 . Due to the high IEC existence in our samples, a constant external OOP field of −860 Oe was applied to compensate for the RKKY field in the experiments. Briefly, a 3 s pulsed current of 7.5 mA was firstly injected along the ˗ x direction of the Hall bar and a nucleated down domain was observed at the left end of the strip with a favored expansion to the + x region. Subsequently, upon a RKKY equivalent field application, both DWs on the left and right sides contracted towards the nucleation point center, i.e., the DW contraction. Then, a 50% duty cycle pulsed current of 3.35 mA was injected into the strip from the x direction for six consecutive 6 s cycles, and the down-up (DU) DW gradually moved to the right driven by the current, while it moved to the left under the RKKY interaction when the current was removed. After the sixth pulse was applied, the DU DW reached the cross region of the Hall bar, and a Hall voltage signal was sensed through the anomalous Hall effect (AHE) as an output signal. Such current input-voltage output scheme is explicitly compatible with the in-memory neuromorphic computing architecture. It is noted that the DU DW fell back to the initial position with typical self-reset manners of an ideal neuron under the net effective RKKY field. The aforementioned DW motion dynamic processes biologically emulate the integration, leakage, and firing of ideal neurons. As to a brief ‘refractory’ period after firing, the neuron device will not integrate any input spike current. The complete process is revealed in Fig. 2d and Supplementary Movie 1 , and the corresponding state of DW during the process is illustrated in the insets, respectively. The appearance of DW pinning during the integration and leakage is caused by randomly distributed pinning centers 49 . Note that to alleviate the DW motion stochasticity issue in our work, we employed the synergistic co-optimization approach from material physics, device fabrication process engineering and LIFT neuron devices’ operation mechanism (Supplementary Note S1 ). Fig. 2 Prototype spintronic neuron device with LIF characteristics. a Schematic of p-MOKE setup for in-situ magneto-electrical transport probing. b Kerr image with the yellow dashed box indicating DW stripe and Kerr signal in d (i), red dashed box refers to the threshold region and corresponding Kerr signal in d (ii). The scale bar is 20 μm. c Major K-H Loop of the device. H RKKY refers to effective field from RKKY interaction and is equaled to 885 Oe. d Dynamic DW motion emulated LIF processes under an applied |H z | field that partially offsets H RKKY with an effective net field of ~25 Oe. Joule heating modulated RKKY, dynamic DW motion processes are recorded at different stage as depicted in (i), the reversal characteristics of threshold region in (ii), and anomalous Hall voltage under associated applied current pulses in (iii).\n\nOptimization and scaling of spintronic neuron devices The human nervous system contains about 10 11 neurons and 10 15 synapses 56 . As schematically illustrated in Fig. 4a , the pre-neuron signals can be transmitted to the post-neuron via synaptic weighting. Remarkably, some typical models have been developed to mimic the characteristics of neurons. Among various neuronal models, the LIF neuron model 7 , 12 is widely accepted as it can better mimic the characteristics of biological neurons with the minimum number of circuit elements, unlike other models. In addition to emulating the process by which a neuron will fire only when the input signal exceeds a threshold, it also can fully portray the leakage nature of a neuron. Fig. 4 Joule heating temperature and DWM characteristics in the proposed device. Schematic of a biological neuron a and proposed spintronic neuron b . c Schematic directions of effective fields and torques of upper ferromagnetic layer. M denotes the magnetization in DW center, the longitudinal torque τ DMI , exchange torque τ RKKY , DW energy torque τ DWE and built-in torque τ built-in is derived from the longitudinal field H DMI , antiferromagnetic exchange coupling field H RKKY , DW energy fields H DWE and H built-in , respectively. Static d and dynamic e temperature distribution of device under 14 μA DC current. f Phase diagram of temperature and the modulated RKKY effective field evolution. g Dynamic temperature upon 23.5 μA and 2 ns pulsed current. h DW LIFT characteristics. To further enhance the energy and time efficiency, a 20 nm thick semiconductor ScN with appropriate resistivity 57 is utilized as a heater, and the length and width of the device are scaled down to 220 nm and 50 nm, respectively. The proposed neuron device consists of individual key layer schematically as shown in Fig. 4b . The upper ferromagnetic layer of the SAF multilayer serves as the PSP free layer (FL), while the lower one is pinned in the opposite magnetization to the FL by the bottom antiferromagnetic pinning layer. These two layers form the antiferromagnetic coupling through the spacer layer with the RKKY interaction. An MTJ is used for detecting and releasing signals with a higher sensing margin. The magnetization orientation of the RL is preset as downward. The bottom antiferromagnetic layer is pinned towards the +z direction so that the magnetization of the bottom ferromagnetic layer in SAF can be pinned along the -z direction. Moreover, upon RKKY antiferromagnetic coupling interaction, the PSP FL is always exerted by a positive effective field. However, the leftmost region of the FL will be pinned in the -z direction by the left antiferromagnetic pinning layer with +z direction under a preset external magnetic field. Therefore, the configuration of a DU DW is generated near the boundary of the left antiferromagnetic pinning region. In addition, the right antiferromagnetic pinning layer possesses an opposite magnetization direction to the left so that the DW can move in the range between two terminal antiferromagnetic pinning regions without annihilation. DW motion dynamics is governed by the Landau–Lifshitz–Gilbert (LLG) equation 58 , 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}$$\\frac{d{\\hat{{{{{\\mathbf{m}}}}}}}}{dt}=-\\gamma \\hat{{{{{{\\mathbf{m}}}}}}}\\times {{{{{\\mathbf{H}}}}}}_{{{e}}{{f}}{{f}}}+\\alpha \\hat{{{{{{\\mathbf{m}}}}}}}\\times \\frac{d\\hat{{{{{{\\mathbf{m}}}}}}}}{dt}$$\\end{document} d m ^ d t = − γ m ^ × H e f f + α m ^ × d m ^ d t where γ is the gyromagnetic ratio, α is the Gilbert damping constant, and \\documentclass[12pt]{minimal}\n\t\t\t\t\\usepackage{amsmath}\n\t\t\t\t\\usepackage{wasysym} \n\t\t\t\t\\usepackage{amsfonts} \n\t\t\t\t\\usepackage{amssymb} \n\t\t\t\t\\usepackage{amsbsy}\n\t\t\t\t\\usepackage{mathrsfs}\n\t\t\t\t\\usepackage{upgreek}\n\t\t\t\t\\setlength{\\oddsidemargin}{-69pt}\n\t\t\t\t\\begin{document}$$\\hat{{{{{{\\mathbf{m}}}}}}}$$\\end{document} m ^ is the unit vector along the magnetization of the FM. With the Dzyaloshinskii–Moriya interaction (DMI) 59 at the HM/FM interface in SAF, the effective magnetic field \\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}$${{{{{\\mathbf{H}}}}}}_{eff}$$\\end{document} H e f f can be written as 58 , 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}$${{{{{\\mathbf{H}}}}}}_{{{e}}{{f}}{{f}}}=\t \\frac{2A_{ex}}{M_{s}}\\frac{{\\partial }^{2}\\hat{{{{{{\\mathbf{m}}}}}}}}{\\partial {x}^{2}}+\\frac{2K}{M_{s}}m_{z}\\hat{{{{{{\\mathbf{z}}}}}}}+\\frac{2K_{d}}{M_{s}}m_{y}\\hat{{{{{{\\mathbf{y}}}}}}}-\\frac{2D_{0}}{M_{s}}\\left(\\hat{{{{{{\\mathbf{y}}}}}}}\\times \\frac{\\partial \\hat{{{{{{\\mathbf{m}}}}}}}}{\\partial x}\\right)\\\\ \t+{{{{{{\\rm{H}}}}}}}_{{{{{{\\rm{R}}}}}}{{{{{\\rm{K}}}}}}{{{{{\\rm{K}}}}}}{{{{{\\rm{Y}}}}}}}+{{{{{{\\rm{H}}}}}}}_{{{{{{\\rm{b}}}}}}{{{{{\\rm{u}}}}}}{{{{{\\rm{i}}}}}}{{{{{\\rm{l}}}}}}{{{{{\\rm{t}}}}}}-{{{{{\\rm{i}}}}}}{{{{{\\rm{n}}}}}}}$$\\end{document} H e f f = 2 A e x M s ∂ 2 m ^ ∂ x 2 + 2 K M s m z z ^ + 2 K d M s m y y ^ − 2 D 0 M s y ^ × ∂ m ^ ∂ x + H R K K Y + H b u i l t − i n where A ex is the exchange stiffness constant, K d refers to the hard-axis anisotropy and D 0 denotes the DMI constant. A modified RKKY exchange field term evaluated using a 6-neighbor small-angle approximation is included in the effective field 60 , 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}$${{{{{{\\boldsymbol{H}}}}}}}_{{{{{{\\rm{RKKY}}}}}}}=2\\frac{{A}_{{{{{{\\rm{RKKY}}}}}}}}{{M}_{s}}\\mathop{\\sum}\\limits_{i}\\frac{({\\hat{{{{{{\\boldsymbol{m}}}}}}}}_{i}-\\hat{{{{{{\\boldsymbol{m}}}}}}})}{{\\varDelta }_{i}^{2}}$$\\end{document} H RKKY = 2 A RKKY M s ∑ i ( m ^ i − m ^ ) Δ i 2 where A RKKY is the RKKY exchange stiffness constant, M s is the saturation magnetization, and Δ i is the thickness of the ferromagnetic cell. The fields and torques acting on the magnetic moments at the center of DW are shown in Fig. 4c and Supplementary Fig. S2 . The temperature-dependent RKKY modulation is attributed to the weakened IEC due to the softening of the Fermi edge at higher temperatures and the complex reflection coefficients at the spacer/magnet interface 52 . In the nanoscale devices with a heater, the device can be heated up to the same level as that in the experiment by using a current of two orders lower in magnitude, as shown in Fig. 4d . And it takes only 50 ns for the temperature to saturate, as depicted in Fig. 4e . Figure 4f demonstrates a phase diagram of temperature evolution with current amplitude and time, and the corresponding variation of RKKY effective field strength is mapped in color contour based on the change rate obtained from our experiments. Therefore, the energy and time costs can be optimized by compromising current amplitude and pulse width. As shown in Fig. 4g , with a pulsed current of 23.5 μA in 2 ns, one can achieve the desired temperature at the ns time scale. Based on the temperature rising and dissipation evolution diagram, a simple mathematical model can be fitted and introduced into MuMax3 for micromagnetic simulations 60 . Briefly, when four current pulses were applied with a width of 2 ns and a period of 10 ns, the RKKY field exertion on DWM was effectively and precisely reduced through the Joule heating generated by the heater. When the net effect of competition between RKKY interaction and the built-in field presents a negative effective field, DW begins to move to the right. When the current is removed, the temperature begins to dissipate, and the RKKY interaction gradually increases. When the net effect of the RKKY interaction and the built-in field present a positive effective field, DW begins to move to the left. The process of neuron integration and auto-leakage is reliably executed in a commercialized SAF device by repeating the above operations, as demonstrated in Fig. 4h and Supplementary Movie 2 . The comparison among different neuron devices (Supplementary Table S3 ) with calculated power and energy consumption (Supplementary Note S3 ) corroborates that the developed spintronic neuron devices successfully mimicked the LIFT characteristics of biological neurons. The rising time of 10 ns and the falling time of 50 ns further warrant the application of high-speed NC. Although the energy consumption of the neuron device is about 486 fJ/spike, it is still applicable to gradually approach or even surpass the energy consumption of biological neurons through structural minimization and Joule heating optimization.\n\nSpintronic LIFT-neuron-based SNN implementation From the application perspectives, the hardware implementations of neuromorphic computing are of paramount importance because of their competitive efficiency in solving recognition and classification tasks. We further evaluated the applicability of the developed spintronic LIFT neuron devices with implementation of typical Modified National Institute of Standards and Technology (MNIST) handwritten digits recognition. A spintronic LIFT neurons-based spiking neural network was constructed using an SNN simulator known as BRIAN2 66 . As shown in Fig. 6a , the topology of a typical two-layer SNN was adopted with inputs consisting of 2D array of 28×28 pixels. The Poisson encoding data flow was executed to trigger excitatory neurons via synapses thru spike-timing-dependent plasticity (STDP) learning. The input neurons are fully connected to the excitatory neurons and each excitatory neuron connects to a matching inhibitory neuron which inhibits the spiking event of all rest excitatory neurons 67 . The DW motion in each excitatory neuron device is regulated by the interconnected synaptic conductance, which calculates the value of the current flowing into the device, thereby generating Joule heating to drive the DW motion. In our device, the mechanism of effective magnetic field drives the magnetic DW motion can be expressed as the following physical model 45 , \\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}$$v=m{H}_{eff}$$\\end{document} v = m H e f f , where \\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}$$m=\\gamma \\varDelta /(\\alpha+{\\alpha }^{-1})$$\\end{document} m = γ Δ / ( α + α − 1 ) . H eff is attributed to the competition between H built-in and H RKKY , where H RKKY is modulated by the Joule heating generated by the current, which can be written as the following model \\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}$${H}_{eff}={H}_{built-in}+{H}_{RKKY}$$\\end{document} H e f f = H b u i l t − i n + H R K K Y , \\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}$${H}_{RKKY}={H}_{RKKY0}+k{I}^{2}$$\\end{document} H R K K Y = H R K K Y 0 + k I 2 , where k is the coefficient of Joule heating modulation of the RKKY field, which is extracted from our experimental results. Fig. 6 LIFT-SNN implementation. a LIFT-SNN topology structure. b Weight matrix of the first 256 excitatory neurons after training. c MNIST digital handwritten patterns recognition accuracy with 1600 excitation neurons under different number of training samples. d LIFT-SNN performance comparison of accuracy. ME Magnetoelectric. We further implemented an SNN with 1600 excitatory neurons and ten classes of handwritten digits, “0” through “9” were sequentially trained and inferenced. Figure 6b shows the representative first 256 excitatory neurons learned synaptic weights connecting the input neurons to excitatory neurons. Figure 6c depicts the handwritten patterns recognition accuracy with 1600 excitation neurons under different number of training samples after verification of 10,000 test sets. The average classification accuracy of ~88.5% was achieved with the first 33,000 samples of the training set for the SNN which learned the digits incrementally in a dynamic environment, demonstrating the comparable performance in comparison with the state-of-the-art 67 – 69 as shown in the benchmark table in Fig. 6d . Note that the accuracy warrants to be enhanced further by optimizing model parameters, e.g., network structure, network size, and training parameters, etc.",
"discussion": "Discussion Although the dynamic DW motion and modulation have been verified experimentally with neurons LIF featured behaviors, to further enhance the performance of the spintronic neuron devices, there is still a pressing need to carefully design the thermal heat generation and the CMOS compatible process technology. On the one hand, to improve the energy efficiency and eliminate the cross interference among neurons motivate researchers to simultaneously reduce the density of the local pinning center, i.e., improving the device reliability. In the large scale and high-density neuron circuits, thermal diffusion is a major problem to be resolved. On the other hand, our design may be more suitable for sparse and habitual neuron circuits 70 , 71 by virtue of the nature of heat dissipation, which is also one of the focuses of our subsequent research, i.e., constructing neuron circuits with specific tasks. From the perspectives of material systems (e.g., FM/AFM/FM 72 , FM/FM(PM)/FM 73 ), the Joule heating modulates not only the strength but also the sign of RKKY coupling, which is applicable for the CMOS devices integration. Furthermore, the voltage and strain bear extra engineering knob to modulate RKKY interaction 27 , 74 , 75 , enabling more reconfigurable neurons diversity. Importantly, the idea of introducing semiconductor negative differential resistance devices into SNN is expected to replace the traditional sense amplifier or analog-to-digital converter reading mode and further reduce the network overhead. Furthermore, the implemented two-layer SNN architecture achieves 88.5% accuracy on the MNIST benchmark under the unoptimized conditions, paving the way for more ambitious and futuristic applications of neuromorphic computing. In conclusion, we have experimentally realized precise modulation of the RKKY effective field by Joule heating in a CMOS compatible SAF-structured neuron, and the spiking LIFT characteristics can be biologically emulated by the dynamic competition between RKKY interaction and H built-in . Such Joule heating-assisted DW-SAF spiking LIFT neuron requires neither the membrane capacitor nor the reset circuit because of its inherent RKKY-H built-in competition property. Our developed spintronic spiking neurons demonstrated the LIF and self-reset functionalities with an ultra-low energy of 486 fJ/spike and a high firing rate up to 17 MHz, enabling attractive hardware acceleration compared to the biological counterpart. By integrating the NDR devices, the WTA functionalized among spintronic LIFT spiking neurons with a synaptic array current differential ratio >10 4 . An NDR-WTA spiking neuron circuit was successfully implemented with low latency of 170 ps and low power consumption of 90.99 μW. The proposed device-circuit codesign with synergistic tailoring of interlayer-coupling-induced magnetic DWM and integrating of NDR enables LIFT spiking neurons with WTA in neuron circuits, offering a reliable platform for future neuromorphic devices and chip applications. The established two-layer SNN based on our developed spintronic LIFT neurons that can be cascaded to the MTJ synapses crossbar with evading additional interfacing circuitry. The 88.5% accuracy has been achieved on the MNIST benchmark, facilitating the spintronic LIFT neurons hardware exploration for promising neuromorphic computing. It is believed that our studies will arouse a wide range of research in neuromorphic computing and pronounced interdisciplinarity, e.g., the CMOS integrated artificial neurons circuit tape-out process."
} | 6,977 |
37603746 | PMC10466089 | pmc | 3,197 | {
"abstract": "Significance Atmospheric methane abundance has risen to a historically high value at 1.92 ppm in 2023 and continues to increase rapidly. A key natural sink for methane is attributed to aerobic methanotrophs that can actively oxidize methane and assimilate the carbon into biomass, and thus, they are candidates for methane removal technology. We demonstrate here that an extant gammaproteobacterial methanotroph, Methylotuvimicrobium buryatense 5GB1C, can grow at low methane concentrations in the range from 200 ppm to 1,000 ppm and exhibits greater methane consumption rates at both low and high methane compared to other methanotroph strains. These features make this strain a promising candidate for methane removal technology at emission sites with enriched methane in air.",
"discussion": "Results and Discussion Screening Aerobic Methanotrophs Capable of Growing at 500 ppm Methane. We first carried out a screen for methanotrophs showing strong growth at 500 ppm methane, by testing growth in stoppered serum bottles. Six phylogenetically diverse representatives from both alphaproteobacterial and gammaproteobacterial groups were tested from our culture collection, and of these, M. buryatense 5GB1C, Methylomicrobium (previously Methylosarcina ) lacus LW14, Methylosinus sp. LW4, and Methylocystis sp. LW5 were able to grow at 500 ppm methane. However, M. lacus LW14 did not show sustained growth after 10 d at 500 ppm methane. Little or no growth was observed for Methylomonas LW13 or Methylotuvimicrobium alcaliphilum 20Z incubated for 14 d ( Fig. 1 ). Additionally, Methylococcus capsulatus (Bath) and Methylosinus trichosporium OB3b, two broadly studied methanotrophs, had previously been shown to not grow or grow poorly at 1,000 ppm or lower concentrations ( 18 ), and thus, their growth analyses were not repeated here. In this screen, the four methanotrophs capable of growing at 500 ppm methane show generally linear growth curves ( Fig. 1 A , C , D , and F ), likely because the headspace in each bottle was refreshed with 500 ppm methane once a day and the daily biomass growth was capped by this restricted supply of methane. Of these four methanotrophs, M. buryatense 5GB1C exhibited the fastest growth and highest optical density values at the end of cultivation at 500 ppm; hence, we focused on this strain in the following analyses. It is worth noting that M. buryatense 5GB1C is also a fast-growing methanotroph at high methane concentrations (25% or 250,000 ppm) with a maximum growth rate of 0.22 h −1 ( 20 ). Fig. 1. Growth performance of wild-type methanotrophs at 500 ppm methane. ( A–G ) Growth curves of M. buryatense 5GB1C ( A ), M. alcaliphilum 20Z ( B ), Methylosinus sp. LW4 ( C ), Methylocystis sp. LW5 ( D ), Methylomonas sp. LW13 ( E ), and Methylomicrobium lacus LW14 ( F ) (n = 3). A , B , E , and F = gammaproteobacteria; C and D = alphaproteobacteria. ( G ) Daily OD 600 increase of the seven methanotrophs during a 14-d growth period (n = 3), which were determined based on the slopes of the linear region of growth curves. ** P < 0.01, which was determined by the unpaired t test. Error bars represent SDs. It is reported that lanthanum (La 3+ ) addition in medium, which changes the methanol oxidation system induced, can improve the growth rate of M. buryatense 5GB1C by 10% in the presence of sufficient methane ( 21 ), but the impact on growth at 500 ppm methane was unknown. We tested the addition of lanthanum, but it did not stimulate growth at 500 ppm methane under the conditions tested ( SI Appendix , Fig. S1 ). Although M. buryatense 5GB1C is not predicted to generate N 2 O, to confirm the prediction, cultures were tested for N 2 O production after growth at 500 ppm methane for 14 d. N 2 O concentration in the headspace was measured at 0.22 ± 0.10 ppm, comparable to atmospheric N 2 O (0.33 ppm), confirming no N 2 O production under these conditions. Characterization of M. buryatense 5GB1C Growth and Kinetic Parameters at Low Methane Concentrations. To more thoroughly evaluate growth performance of M. buryatense 5GB1C in response to low methane, we utilized a bioreactor-based system with continuous flow of methane:air mixtures, coupled with gas chromatography (GC) measurement of off-gases. M. buryatense 5GB1C was cultivated at seven low methane concentrations (i.e., on 2,500 ppm, 1,000 ppm, 800 ppm, 500 ppm, 300 ppm, 200 ppm, and 100 ppm levels) that were expected to be significantly below the whole-cell K M for methane [K M(app) ], and at 2.5% (v/v, or 25,000 ppm) as a sufficient methane control ( Fig. 2 A and B and SI Appendix , Fig. S2 and Table S1 ). A linear relationship between the methane uptake rate and the specific growth rate was observed for the entire range studied ( Fig. 2 B ). These results also show that M. buryatense 5GB1C is able to grow below 500 ppm methane, with growth observed as low as ~200 ppm methane ( Fig. 2 A and B and SI Appendix , Tables S1 and S2 ). No other gammaproteobacterial methanotrophs have been shown to grow at such low methane concentrations ( 11 , 18 , 19 ). At ~100 ppm methane, we observed initial growth of M. buryatense 5GB1C for 2 wk; however, biomass barely increased afterward ( SI Appendix , Fig. S2 C ). The culture was allowed to recover for 17 h at ~600 ppm methane and then switched to ~100 ppm methane, but the same behavior was observed ( SI Appendix , Fig. S2 C ). These results indicate that 100 ppm methane may not support long-term growth of M. buryatense 5GB1C. Notably, some alphaproteobacterial methanotrophs have been shown to grow at 100 ppm and lower methane, including Methylocystis species ( 18 , 19 ) and Methylocapsa gorgona MG08 ( 11 ). However, two Methylocystis strains for which data are available grew two to threefold more slowly than M. buryatense 5GB1C at 1,000 ppm methane and M. gorgona MG08 showed sixfold lower methane oxidation rates at 800 ppm methane ( SI Appendix , Tables S1 and S2 ). Assuming a similar linear relationship for the methanotrophs listed in SI Appendix , Table S2 , it may be predicted that they would also grow more slowly and consume methane at lower rates than M. buryatense 5GB1C at 200 to 500 ppm methane. Finally, our measurements reveal a strong linear correlation for M. buryatense 5GB1C between the specific growth rate and the methane concentration of the inlet gas from 200 ppm to 2,500 ppm, corresponding to specific growth rates from 0.004 to 0.07 h −1 ( Fig. 2 A ). Fig. 2. Characterization of growth and kinetic parameters of M. buryatense 5GB1C. ( A ) Relationship between specific growth rates and the methane concentrations of inlet gas. In the range between 200 ppm and 2,500 ppm methane, the yellow line represents the fitted linear regression curve (R 2 = 0.82, P = 1.2 × 10 −5 ). Growth data at 20% (v/v) or 200,000 ppm CH 4 balanced with 5% O 2 and 75% N 2 were based on a previous report ( 22 ). ( B ) A linear relationship between the specific growth rate and the methane uptake rate. The yellow line represents the fitted linear regression curve (R 2 = 0.96, P = 3.6 × 10 −15 ). ( C ) The Michaelis–Menten plot of whole-cell methane uptake rate [mmol methane (gram cell dry weight) −1 h −1 ] as a function of initial substrate concentration (R 2 = 0.96, P = 1.6 × 10 −17 ). The initial substrate concentration was calculated based on Henry’s law ( Methods and Materials ). ( D ) Linear regression of the linear region of the Michaelis–Menten curve (R 2 = 0.93, P = 6.6 × 10 −8 ). Each symbol represents an independent measurement. In methanotrophs, a part of the energy produced from methane oxidation is allocated for cell maintenance. For M. buryatense 5GB1C grown at methane sufficiency (14% methane; 140,000 ppm), the non-growth-associated ATP maintenance energy (NG-ATPM) is 10 to 15 mmol ATP per gram of dry weight per hour (mmol ATP g −1 h −1 ) ( 23 ). However, M. buryatense 5GB1C grown with 200 ppm methane exhibits a methane uptake rate of 0.2 to 0.5 mmol methane g −1 h −1 ( Fig. 2 A and B and SI Appendix , Table S1 ) and thus can only yield up to 3.0 mmol ATP g −1 h −1 assuming six mole ATP generated per mole of methane consumed ( 24 ). Since during active growth, the methane consumed must be partitioned into carbon allocated for biomass generation and carbon for ATP generation, the actual NG-ATPM must be significantly lower than 3.0 mmol ATP g −1 h −1 . Indeed, fitting our measurements with the Herbert-Pirt model ( 25 ) yielded an NG-ATPM of 0.36 mmol ATP g −1 h −1 ( SI Appendix , Fig. S3 A ), comparable to the NG-ATPM (0.6 mmol ATP g −1 h −1 ) required for retentostat-grown Saccharomyces cerevisiae at a growth rate of ~0.001 h −1 ( 26 ). However, the NG-ATPM derived from the linear regression has a high P value (0.75) and a wide 95% CI from 0 to 2.8 mmol ATP g −1 h −1 ( SI Appendix , Fig. S3 A ). We also used a genome-scale reconstruction (GEM) model ( 27 ) to predict growth rates at 1,000 ppm methane or lower. Results show that the NG-ATPM must be ~0.4 mmol ATP g −1 h −1 or lower to allow reasonable growth rate predictions at low methane concentrations ( SI Appendix , Fig. S3 B – D ). These findings suggest that M. buryatense 5GB1C is able to decrease the NG-ATPM as a function of decreased substrate availability, as reported previously for S. cerevisiae ( 26 ). It may be predicted that such a capability could contribute to the relatively strong growth of M. buryatense 5GB1C at low methane, since it would enhance the energy from methane oxidation available to support biomass production. It has been suggested that methanotrophs able to grow at 100 ppm methane and below contain a special high-affinity pMMO ( 18 , 19 ), although this is apparently not the case in M. gorgona MG08 ( 11 ). To assess whether M. buryatense 5GB1C might show methane oxidation kinetics indicative of a high-affinity pMMO, we carried out whole-cell Michaelis–Menten analysis ( Fig. 2 C ), determining that the whole-cell K m [K M(app) ] and the whole-cell V max (V max(app) ) for methane are 8.8 ± 1.7 µM (equivalent to 6,681 ± 1,291 ppm methane in the gas phase at equilibrium) and 18.9 ± 0.9 mmol g −1 h −1 , respectively. Although the V max(app) is higher than other known methanotrophs, indicating a rapid maximum methane oxidation rate, K M(app) is also high compared to other methanotrophs ( 18 ). This result does not support the idea that M. buryatense 5GB1C possesses a pMMO with higher affinity to methane than other known methanotrophs. It has been well established that K M(app) is in part dependent on the overall expression of pMMO ( 18 ). The specific affinity as o which denotes the slope of the linear part of the Michaelis–Menten curve, has been suggested to be a more suitable parameter for comparing methane oxidation rates among methanotrophs at low concentrations ( 18 , 19 ). Through a linear regression ( Fig. 2 D ), as o for M. buryatense 5GB1C is determined to be 1,101 ± 87 ×10 −12 L cell −1 h −1 (or 1,776 ± 140 L g −1 h −1 ), more than fivefold larger than the highest reported value and 30 to 100-fold higher than most tested methanotrophs ( 11 , 18 , 19 ) ( SI Appendix , Table S2 ), in keeping with the ability of this methanotroph to grow at methane significantly below the K M(app) . The underlying mechanism for high as o is unknown. pMMO phylogenetic analysis suggests that the high as o measured for M. buryatense 5GB1C is likely not due to a high-affinity pMMO, since the M. buryatense 5GB1C pMMO subunit DNA sequences are closely related to other gammaproteobacterial pMMO sequences, including those of methanotrophs unable to grow at 500 ppm methane ( 28 ). At low growth rates, bacteria may display significant morphological changes ( 25 ). We thus quantified biomass dry weight per OD 600 unit, cell sizes, and the coverage of intracytoplasmic membranes (ICMs) that house pMMO. No significant changes were found in any of these parameters between low (500 ppm methane or less) and high (2.5% or more) methane growth conditions ( SI Appendix , Fig. S4 ), which indicates robustness of cell morphology. Particularly, we found a moderate 20% reduction of ICM coverage in cells at 500 ppm methane but without statistical significance ( SI Appendix , Fig. S4 A ). Transcriptional Response of M. buryatense 5GB1C to Low Methane. In some bacteria, strong transcriptional responses accompany growth under nutrient limitation and at low growth rates: Bacteria often decrease expression of the translation and transcription apparatus, up-regulate functions involved in motility and chemotaxis, and up-regulate amino acid synthesis pathways ( 25 , 29 – 31 ). To understand how M. buryatense 5GB1C responds to low methane at the transcriptional level, we quantified holistic gene expression of cultures grown at 500 ppm and 1,000 ppm at methane-limited steady-state in the bioreactor, with growth rates of 0.009 h −1 and 0.02 h −1 , respectively. Differentially expressed genes are defined as those exhibiting an absolute log 2 -fold change over one and adjusted p value less than 0.05 in comparison to a reference condition, i.e., methane-limited steady-state growth on 2.5% (v/v) methane at a growth rate of ~0.125 h −1 ( 22 ). Transcription profiles of M. buryatense 5GB1C at 500 ppm and 1,000 ppm methane are highly consistent with each other, without any significant variations in gene expression ( SI Appendix , Fig. S5 ). When compared to transcriptional profiles under 2.5% methane conditions ( 32 ), 725 genes are differentially expressed at both 500 ppm and 1,000 ppm methane ( Fig. 3 A and Dataset S1 ). Of note, two cold-shock proteins, which are RNA chaperones and in other bacteria are involved in regulation of transcription and translation under stress ( 33 ), show strongly changed gene expression but with divergent trends: One (EQU24_RS15705) is down-regulated by two log 2 -fold, while the other (EQU24_RS16055) is up-regulated by over three log 2 -fold. Transposases are highly up-regulated in general; however, many but not all of their gene expression levels are low in transcripts per million (TPM < 10) ( Dataset S1 ). Cells under stress commonly up-regulate transposase expression ( 34 ). Fig. 3. Transcriptional changes of M. buryatense 5GB1C grown at 500 ppm (blue) and 1,000 ppm (orange) methane in comparison to 2.5% (v/v) methane growth conditions. ( A–F ) Volcano plots of gene expression changes of the entire genome ( A ), core central carbon metabolism ( B ), energy metabolism ( C ), biosynthesis of building blocks and cofactors ( D ), translation and transcription apparatus ( E ), and motility and chemotaxis ( F ). Symbol sizes are correlated with gene expression as shown in the figure. The horizontal dashed line represents P = 0.05. The two vertical dashed lines represent log 2 -fold at −1 and 1, respectively. Genes that do not change significantly are colored in gray. Gene abbreviations and gene products: csp , cold shock protein; fae , formaldehyde activating enzyme; fdh , formate dehydrogenase; mtk , malate-CoA ligase; atpC , F 1 F 0 type ATP synthase subunit epsilon; atpH , F 1 F 0 type ATP synthase subunit delta; nuoF , NADH-quinone oxidoreductase subunit NuoF; fabA , 3-hydroxyacyl-[acyl-carrier-protein] dehydratase FabA; csrA , carbon storage regulator CsrA; glyA , glycogen synthase GlgA; zapA , cell division protein ZapA; rpmA , 50S ribosomal protein L27; flgA , flagellar basal body P-ring formation chaperone FlgA; flgN , flagellar protein FlgN. An interactive version of this figure is available at https://erinhwilson.github.io/limited-ch4-tpm-analysis/ . We also analyzed expression of specific genes involved in central metabolism. In the pathway converting methane to CO 2 , genes encoding pMMO (converts methane to methanol) and the MxaF-type methanol dehydrogenase (converts methanol to formaldehyde) are highly expressed but with no significant variations ( Fig. 3 B ). Transcriptional levels of the tetrahydromethanopterin (H 4 MPT) pathway (converts formaldehyde to formate) remain unperturbed except for two genes encoding formaldehyde-activating enzyme (EQU24_RS13345 and EQU24_RS14315) displaying significant variations in expression. All six genes encoding two formate dehydrogenases (convert formate to CO 2 ) are down-regulated, with greater decreases at 500 ppm methane than at 1,000 ppm methane. These results are accordant with the observation that the excreted formate rate is roughly two times higher at 500 ppm methane (0.018 ± 0.002 mmol formate g −1 h −1 ) than at 1,000 ppm methane (0.009 ± 0.003 mmol formate g −1 h −1 ). These values are much lower than corresponding methane uptake rates (0.95 ± 0.08 mmol CH 4 g −1 h −1 at 500 ppm and 1.5 ± 0.2 mmol CH 4 g −1 h −1 at 1,000 ppm, SI Appendix , Table S1 ), suggesting that cells growing at low methane tend to reduce carbon loss as formate or CO 2 to allow more carbon assimilation. Gene expression of other central metabolic pathways remains mostly unchanged ( Fig. 3 B ), including glycolysis, the tricarboxylic acid cycle, and the ribulose monophosphate cycle (converts formaldehyde and ribulose 5-phosphate to three-carbon compounds for assimilation). One exception is the incomplete serine cycle (converts formate and CO 2 to acetyl-CoA), where the malate-CoA ligase (EQU24_RS04635) and the malyl-CoA lyase (EQU24_RS04630) are down-regulated by two log 2 -fold. Taken together, these results suggest that although the growth rate is decreased by over an order of magnitude, expression of the proteins important for central metabolism pathways is largely unchanged. Such a response is in keeping with a strategy to poise the cells to take advantage of whatever methane is available under these strongly methane-limiting growth conditions. As for energy metabolism, the NADH-ubiquinone reductase and the F 1 F 0 -type ATP synthase are strongly down-regulated, in keeping with the greatly decreased energy needs at these low growth rates ( Fig. 3 C ). Gene expression for biosynthesis pathways of fatty acids, amino acids, nucleotides, vitamins, and cofactors remain either stable or down-regulated ( Fig. 3 D ), again, in keeping with the low growth rates and expected decreased fluxes through these pathways. In contrast, genes glgA (EQU24_RS18670) and glgB (EQU24_RS18665) associated with glycogen synthesis are up-regulated by about one log 2 -fold, while other related genes including those for glycogen degradation do not show significant changes in expression. This is consistent with downregulation (1.5 to 2.0 log 2 -fold) of the carbon storage regulator csrA (EQU24_RS07950), which has been shown to negatively mediate glycogen synthesis in Escherichia coli ( 35 ). It is not clear why the cells would increase carbon storage, but it may reflect a strategy to prepare the cells to accommodate future starvation. We also observed a strong decline in gene expression of ribosomal proteins, tRNA-ligases, RNA polymerases, and sigma factors ( Fig. 3 E ), suggesting a slowdown of transcription and translation processes. Cell division genes, such as ftsL (EQU24_RS19745), ftsB (EQU24_RS13310), and zapA (EQU24_RS04165), are also significantly down-regulated ( Fig. 3 E ). These changes also reflect decreased need at the low growth rates. By contrast, many genes related to flagellar protein synthesis and chemotaxis are up-regulated ( Fig. 3 F ), as bacteria tend to be more active in searching for nutrients and more favorable environments under stress ( 29 ). All in all, the transcriptional response is in keeping with the low NG-ATPM values, in which the cells down-regulate functions that are not needed at low growth rates, while maintaining or up-regulating those functions that will poise the cells to take advantage of better growth conditions, or alternatively, the onset of complete carbon starvation. Global Removal Projections. In order to assess whether this improved performance of methane removal at 500 ppm could theoretically be feasible for a future methane removal technology, we have carried out projections based on our results compared to literature results. Many examples exist of methanotroph-based biofilter technology for removing methane from waste streams, but the majority of these are carried out at 10,000 ppm (1%) methane or higher and involve “wild” mixed methanotroph communities (consortia), enriched with high (greater than 1%) methane ( 36 ). In the few cases in which methane inlet concentrations below 1% have been reported, elimination capacities (ECs) at 500 ppm methane are estimated to be in the range of 0.5 to 3.2 g CH 4 removed m −3 h −1 ( 37 – 39 ) ( SI Appendix , Table S3 ). With the 121 m 3 treatment unit size used in a previous modeling study ( 16 ) and assuming 7,200 h (300 d) ( 16 ) operation per year, such ECs are projected to result in removal of 0.4 to 2.8 tons methane per year per treatment unit at 500 ppm methane. At the higher end, these ECs are similar to the 5 tons methane per year predicted for pure cultures of methanotrophs ( 16 ), strains that are known to not grow significantly at 500 ppm methane ( 18 ). These results suggest that the methanotroph strains enriched in published biofilter experiments may not be well-suited for removing such low methane. We have shown the M. buryatense 5GB1C specific affinity is more than fivefold higher than the highest reported values and 30 to 100-fold higher than most methanotrophs enriched at high methane. Thus, in theory, the EC for 500 ppm methane with M. buryatense 5GB1C should be at least fivefold greater than those in the literature, increasing to 2 to 14 ton per year per treatment unit, and could be significantly higher. The actual EC would depend on how well this strain performs under such conditions compared to general methanotrophs. Given known biomass yields for M. buryatense 5GB1C ( 22 ), 0.78 ton biomass dry weight is predicted to be formed per ton methane utilized ( Methods and Materials ). Methane-derived biomass (single cell protein) has been used for aquaculture feed and is predicted to have a value of ~$1,600 per ton ( 40 ), a cobenefit of methane removal by methanotrophs. If bioreactor systems could be developed that would allow automated biomass harvesting, this cobenefit could substantially add to the attractiveness of a bio-based methane removal system. Standard biofilters are not designed for use of low methane and alternative bioreactor configurations that focus on enhanced mass transfer could significantly increase ECs at these low methane inlet concentrations. If a combination of strain improvement and bioreactor/bioprocess design could increase ECs 20-fold, treatment units would be projected to remove 40 to 280 tons methane per year. In such a case, 50,000 to 300,000 units deployed worldwide for 20 y at sites with methane enrichment in air averaging 500 ppm would keep 240 million tons methane from entering the atmosphere, an outcome predicted to significantly impact global warming ( 1 , 5 ). A previous economic analysis ( 16 ) suggests that a 20-fold improvement in EC would also become economically feasible, but full environmental life cycle and technoeconomic analyses are needed to more definitively address economic and environmental impacts. The above analysis suggests the use M. buryatense 5GB1C either by itself or as part of a consortium as the basis of a methane treatment technology is potentially feasible in the 500 ppm range. More studies are necessary to determine actual feasibility under field conditions. In summary, M. buryatense 5GB1C has emerged from our screening study as a promising candidate for a methane removal technology that does not increase N 2 O emissions, and our results suggest that its ability to grow at low methane relies at least partly on a high specific affinity and a low maintenance energy. The former denotes an inherently rapid methane assimilation that provides the basis for energy production and biomass growth. The latter is in keeping with drastic downregulation of translation and transcription machineries, as both synthesis and maintenance of those components are energy-demanding. They both confer growth advantages in the face of severe substrate limitation, enhancing the energy produced from methane oxidation that can be invested into biomass synthesis. This well-studied bacterium is an excellent candidate to serve as a platform for developing methane removal technology either by itself or as part of a consortium. Strain improvements could be carried out using approaches such as adaptive laboratory evolution and targeted genetic manipulations to improve growth at low methane, and growth improvements could involve testing other medium constituents such as copper concentration. Moving forward, research should also be focused on integration of these methane consumers into deployable and scalable bioreactor systems as well as environmental life cycle and technoeconomic analyses of such a methane removal technology to ensure both economic feasibility and environmental benefit."
} | 6,317 |
30687779 | PMC6343076 | pmc | 3,198 | {
"abstract": "Variation in microbial activity levels is increasingly being recognized as both an important dimension in community function and a complicating factor in sequencing-based survey methods. This study extends previous reports that rare taxa may contribute disproportionately to community activity in some natural environments, showing that this may also hold in artificially maintained model communities with well-described inputs, outputs, and biochemical functions. These results demonstrate that assessment of activity levels using the rRNA/rDNA ratio is robust across taxonomic unit formation methods and is independently corroborated by omics methods. The results also provide insight into the comparative advantages and disadvantages of different taxonomic unit formation methods in amplicon sequencing studies, showing that UNOISE3 provides comparable microbial diversity, structure, and activity information as the 97% sequence similarity method but potentially loses some phylogenetic diversity and creates more “phantom taxa” (which are present in the RNA pool but not the corresponding DNA pool).",
"conclusion": "Conclusions. Variation in microbial activity levels is an important factor in community function. In our model AD communities, the rRNA/rDNA ratio revealed large variance in cell-level microbial activity levels across taxa, cooperated with two alternative taxonomic unit formation methods and by reconstructed metagenomic population genomes and their complementary transcriptomes. Confirming previous findings, the most metabolically active and rapidly dividing taxa tended to be the least abundant in the five AD communities, though further work is needed to establish whether this is an entirely natural or at least partially artifactual pattern. We found no obvious evidence to support the suggestion that the conventional 97% sequence similarity 16S OTUs conflates distinct ecological entities or discards biologically relevant information compared to the UNOISE3 method applied in this study, and instead found the UNOISE3-based ZOTU method generated a higher rate of phantom taxa, suggesting it may less suitable for assessing metabolic activity with the rRNA/rDNA ratio, a method already fraught with difficulties in interpretation.",
"introduction": "INTRODUCTION Bioconversion of carbon and other nutrients in wastewater via anaerobic digestion (AD) is achieved by a community of microbes ( 1 ). The composition, diversity, structure, and metabolic activity of these microbial communities all affect how well anaerobic digesters perform ( 2 ). Many previous studies have investigated the composition, diversity, and structure of AD microbial communities by evaluating the 16S rRNA gene (rDNA) ( 3 – 5 ), while others have assessed potential metabolic capabilities by examining microbial metagenomes ( 6 – 8 ). However, DNA-based microbial community surveys can provide information only on the total community and are unable to discriminate between microbes with different levels of metabolic activity. While significant differences have been demonstrated between the total and active microbial communities in full-scale anaerobic digesters based on 16S rDNA/rRNA amplicon data ( 9 ), the activity levels of participating microbes have not been examined in detail. Microbes can be growing (undergoing cell division), active (performing metabolic functions but not dividing), dormant (neither dividing nor metabolizing), or recently deceased, and thus, they participate in ecological functions to different degrees ( 10 ). As the number of 16S rRNA transcripts in a cell is positively correlated with its metabolic activity and/or growth rate ( 11 – 13 ), the metabolic state of a population of cells could be inferred by quantitative rRNA sequencing ( 14 ). The ratio between transcribed and genomic 16S rRNA sequences (rRNA/rDNA ratio) is a means of normalizing rRNA transcription against cell count, and it has been used to compare metabolic activity between populations ( 15 , 16 ). The rRNA/rDNA ratio has been used to study the active microbial communities in aquatic ( 17 – 20 ), ice sheet ( 21 ), air ( 22 , 23 ), soil ( 24 – 27 ), and activated-sludge ( 28 , 29 ) environments, but it has not yet been widely applied in anaerobic digesters ( 30 ). Furthermore, as microbial ribosomal amplification is highly variable across both taxonomy and ecological strategy, the rRNA/rDNA ratio may not always be sufficient to discriminate between microbes in different metabolic states ( 10 ), and it may be particularly prone to error in populations with a mixture of amplification levels ( 31 ). In previous studies, the rRNA/rDNA ratio has been calculated at the level of operational taxonomic units (OTUs), conventionally represented as clusters of 16S rRNA gene sequences with at least 97% sequence similarity. However, a growing number of recent studies suggest that the 97% sequence similarity threshold does not necessarily capture phylogenetically and ecologically homogeneous microbial populations ( 32 , 33 ), and it may underestimate species richness by grouping dissimilar taxa. This has led to the proposal of studying taxonomic units at a single-nucleotide resolution, and they are called “zero-radius OTUs” (ZOTUs), exact sequence variants (ESVs), amplicon sequence variants (ASVs), features, or sub-OTUs ( 34 – 36 ). Because the formation of such units is exquisitely sensitive to sequencing error, 100% sequence similarity-based methods rely on denoising and error correction algorithmic approaches to infer accurate ESVs from potentially noisy sequencing data ( 35 – 37 ). A number of packages (e.g., DADA2, Deblur, and UNOISE3), each with its own strengths as compared previously ( 38 ), are available to generate ESVs. These methods are best conceptualized as alternative methods of forming taxonomic units rather than differing from conventional OTU formation merely by the choice of the sequence similarity threshold. For example, UNOISE3 is an algorithm that depends on the frequency of occurrence of a read, but not the sequencing quality scores, and two parameters with preset values to infer correct biological sequences from the erroneous ones ( 35 ). It is not currently known how well different taxonomic unit formation methods accurately capture the composition, diversity, and structure of AD communities, nor how well rRNA/rDNA ratios based on 100% sequence similar taxonomic units reflect their true metabolic activity. We have previously established five microbial AD communities capable of digesting cellulose or xylan to CH 4 at mesophilic (35°C) or thermophilic (55°C) conditions ( 39 ) and reconstructed 107 population genomes and their transcriptional activity from combined metagenomic and metatranscriptomic sequencing of these communities ( 40 ). Because these reconstructed population genomes are not sensitive to sequence similarity thresholds or minor sequencing errors, and the transcription of structural genes is not directly dependent on variance in ribosomal amplification, these population genomes and their transcription profiles provide another means of revealing microbial metabolic activity, so can be used to validate the use of alternative taxonomic units and rRNA/rDNA ratios to assess AD communities. In this study, we sequenced 16S rDNA and rRNA amplicons from our five enriched AD microbial communities and assessed microbial community structure and activity using rRNA/rDNA ratios with both the conventional OTU (97% sequence similarity) and ZOTU (single-nucleotide resolution taxonomic unit by UNOISE3 [ 35 ]) methods. We also used metagenomic and metatranscriptomic (mRNA) sequencing data from the same samples to calculate transcription/abundance ratios for reconstructed population genomes, allowing us to cross-validate and identify relative biases in the 16S amplicon-based methods.",
"discussion": "RESULTS AND DISCUSSION Overview of total and active communities. AD of cellulose or xylan to CH 4 is achieved by a diverse microbial community performing a range of functions at different levels of metabolic activity. In this study, partial 16S rDNA and 16S rRNA regions were sequenced to query the total and active microbial communities, and taxonomic units formed with either conventional 97% sequence similarity clustering (OTUs) or denoising with UNOISE3 at 100% similarity (ZOTUs). With both methods, the rDNA (total community) and rRNA (active community) reads captured largely identical sets of taxonomic units (see Table S1 in the supplemental material). From each sample, 83 to 268 OTUs and 86 to 263 ZOTUs were identified in both the rDNA and rRNA read sets, accounting for >98% of the rDNA and >98% of the rRNA reads in all but one sample (SWH-C-D15). While all samples yielded some taxonomic units that were identified in only the rDNA or rRNA read sets, these represented <2% of the total reads for either read set, again with the exception of SWH-C-D15. These read set-specific taxonomic units ranged in number from 11 to 117 (OTUs) and 13 to 141 (ZOTUs) per sample. In SWH-C-D15, a high proportion (35 to 36%) of rRNA reads contributed to OTUs or ZOTUs that were not identified in the rDNA read set. 10.1128/mSystems.00208-18.6 TABLE S1 Summary of the proportion of overlaps between 16S rDNA and 16S rRNA reads in each sample based on OTU clustering and ZOTU denoising methods. Download Table S1, XLSX file, 0.01 MB . Copyright © 2019 Jia et al. 2019 Jia et al. This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . Taxonomic units that were detected exclusively in the rDNA read set might represent microbes that were present but not metabolically active (i.e., dormant or dead). Conversely, taxonomic units exclusively detected in the rRNA read set represent “phantom taxa,” where the rDNA template was not successfully identified due to either undersampling of rDNA or the introduction of nucleotide errors during reverse transcription (an error rate of ∼1/15,000 for reverse transcriptase) ( 41 ), PCR (an error rate of ∼1/10,000 to 1/50,000 for Taq polymerase [ 41 ]), or sequencing ( 22 ). rDNA undersampling may be more likely in the case of rare taxa which are nonetheless highly active and/or have high ribosomal amplification, which would yield abundant rRNA transcripts relative to scarce rDNA genes. Either of these explanations is consistent with the higher proportion of phantom taxa among ZOTUs (31% of ZOTUs) compared to OTUs (11%). A single-nucleotide error introduced in PCR or sequencing and not corrected by denoising will either create a phantom ZOTU or cause the sequence to be misclassified into an incorrect ZOTU, where the same error may have no effect on OTUs formed by 97% similarity clustering. Similarly, a single rRNA read from a taxon that did not yield an rDNA read due to undersampling might not create a phantom taxon if the read was included in a 97% similar OTU for which at least one complementary rDNA sequence was detected, but such concealment is not afforded by 100% similar ZOTUs. Community diversity and structure. While 80% of filtered reads were successfully clustered into OTUs, only 48% were assigned to ZOTUs. Despite this, OTU and ZOTU richness across all samples did not differ significantly among either the total (rDNA) or active (rRNA) communities ( Table 1 ). This suggests that the tendency of the 100% similarity threshold to “split” taxa that would otherwise be “lumped” at the 97% threshold mostly compensated for the decreased number of reads retained in the ZOTU set, although it does not indicate which of the two methods achieved a more accurate estimate of the ecologically meaningful taxon richness. Faith’s phylogenetic diversity (PD) index was significantly higher among OTUs compared to ZOTUs in both the total and active communities, suggesting that the OTU method was able to capture a greater degree of phylogenetic diversity than the ZOTU method, likely because of the large number of low-abundance reads discarded during ZOTU formation. The Shannon index of diversity was significantly higher among ZOTUs compared to OTUs in both the total and active communities, but as the two taxonomic unit formation methods yielded similar richness, this is likely due to greater abundance evenness among ZOTUs, which again may be attributable to the discarding of low-abundance reads. TABLE 1 Mean values across all samples of alpha-diversity indices in the 16S rDNA and 16S rRNA read sets for the OTU and ZOTU taxonomic formation methods a \n Alpha-diversity index Read set Mean (SD) value for diversity index by the following taxonomic formation method: P b \n OTU ZOTU Richness rDNA 240 (68) 240 (56) 0.67 rRNA 240 (72) 220 (47) 0.20 Faith’s PD rDNA 7.9 (1.6) 5.0 (0.82) 0.00* rRNA 8.2 (2.1) 5.3 (1.2) 0.00* Shannon index rDNA 3.4 (0.7) 4.2 (0.6) 0.00* rRNA 3.7 (0.8) 4.4 (0.64) 0.02* a Alpha-diversity was calculated after all samples were normalized to a read depth of 31,560 or 17,707 for OTUs and ZOTUs, respectively, by randomly subsampling 10 times, and values were averaged. b P values are for Mann-Whitney tests for a significant difference between methods for the given index and read set. P values of <0.05 are indicated by an asterisk. At the rank of family, the 16S rDNA (total community) and 16S rRNA (active community) sample taxonomic compositions were broadly similar for both the OTU and ZOTU taxonomic unit formation methods ( Fig. S1 ). The exception was SWH-C-D15, which was generally consistent in taxonomic composition between methods, but had a large population of Mycoplasmataceae and Rhizobiaceae taxa in the rRNA community which were not identified in the rDNA community. These represent phantom taxa, which as described above were unusually abundant in SWH-C-D15. Members of the Mycoplasmataceae and Rhizobiaceae families are not known to be prevalent in AD communities, and these sequences could be contaminants (they were present in one of the five negative controls at a relative abundance of <6.8%). The amplicon-based taxonomic compositions were also reflected in our previously reported population genomes ( 40 ), of which the bacterial families Clostridiaceae, Ruminococcaceae , and Veillonellaceae and the methanogenic archaeal family Methanobacteriaceae were among the most abundant taxa in most samples. 10.1128/mSystems.00208-18.1 FIG S1 Taxonomic composition of the total and active communities in the enrichment culture samples at the taxonomic rank of family based on OTU clustering and ZOTU denoising results. The top 12 families across all samples were plotted, with all the others grouped into the “Minor/Unclassified” category. Many sequences could not be annotated at the genus level. Download FIG S1, TIF file, 1.4 MB . Copyright © 2019 Jia et al. 2019 Jia et al. This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . We have previously reported that the 16S rDNA profiles of these enrichment cultures differ significantly by enrichment condition ( 39 ). This was found to hold true for both read clustering and denoising methods using profiles that combined rDNA and rRNA OTUs/ZOTUs ( Fig. 1 ), with significant differences between enrichment conditions based on both weighted (PERMANOVA pseudo-F = 12.19, P = 0.001 for OTU; pseudo-F = 7.504, P = 0.001 for ZOTU) and unweighted (PERMANOVA pseudo-F = 8.823, P = 0.001; pseudo-F = 15.92, P = 0.001 for ZOTU) UniFrac distances (all time points pooled for each enrichment condition). FIG 1 Principal-coordinate analysis of the pooled total (rDNA) and active (rRNA) communities as measured with the weighted (A and C) and unweighted (B and D) UniFrac distances, using either the OTU (A and B) or ZOTU (C and D) taxonomic unit formation method. The percentage in parentheses on each axis gives the estimated contribution of each principal coordinate to the total variance. Community-level correlations between taxon abundance and transcriptional activity. Previous 16S amplicon sequencing studies have demonstrated that the relative abundance (contribution to total rDNA) and relative metabolic activity (contribution to total rRNA) of microbial taxa are significantly and positively correlated in a range of environments, including coastal ocean ( 20 ), benthic glacier streams ( 17 ), and soil ( 26 ). This is also a key premise of the rRNA/rDNA method of inferring cell-level microbial activity, as it is assumed that after rRNA abundance is normalized against rDNA abundance, any remaining variation can be attributed to cell-level differences in ribosomal amplification. We found a positive and significant linear correlation between rRNA and rDNA relative abundances across both clustering and denoising methods and all samples ( Fig. 2 ; Pearson’s ρ ≥ 0.63, P < 0.0001 for all samples). There was no significant difference between the correlation coefficients obtained using the OTU clustering versus ZOTU denoising methods (Mann-Whitney P = 0.08). For the samples from which population genomes were reconstructed from metagenomes, we also tested for a linear correlation between population genomes’ metagenomic and metatranscriptomic relative abundances. In all but one sample (SWH-C-55-Mid), a significant positive linear correlation was found ( Fig. 2 ; Pearson’s ρ ≥ 0.72, P < 0.001 for all samples except SWH-C-55-Mid). On average, the 10 most abundant taxa in each sample contributed 79% (OTUs), 69% (ZOTUs), or 95% (population genomes) of RNA production ( Fig. S2 ). FIG 2 Relationship between relative abundance and relative transcription (logarithmic scales) of OTUs (brown), ZOTUs (turquoise), and population genomes (pink) across all samples. Each symbol represents one taxonomic unit. Lines represent linear models fitted for each set of taxonomic units in each sample. For OTUs and ZOTUs, abundance and transcription are the relative rDNA and rRNA abundances, respectively; for population genomes, they are derived from metagenomic and metatranscriptomic abundances. Pearson’s ρ (when P < 0.05) for each set of taxonomic units is given in the top left-hand corner of each plot. 10.1128/mSystems.00208-18.2 FIG S2 Cumulative relative production compared to the rank abundance of OTUs (brown), ZOTUs (turquoise), and population genomes (pink) for each culture. Each symbol represents one taxonomic unit. For OTUs and ZOTUs, production of a taxon is its relative contribution to total rRNA; for population genomes, it is derived from the contribution of transcripts from a population genome to total mRNA. Download FIG S2, TIF file, 2.6 MB . Copyright © 2019 Jia et al. 2019 Jia et al. This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . The positive relationship between genomic and transcriptional abundance and the rapid accumulation of cell production support previous reports that the most abundant community members are also the greatest contributors to total community metabolic activity, independent of variation in cell-level metabolic activity between taxa ( 42 ). This is unlikely to be an artifact of “lumping” dissimilar taxa during the clustering or denoising of amplicon-based reads ( 32 ), as the correlation was consistent between the OTU and ZOTU methods and was corroborated by the reconstructed population genomes, which are not susceptible to clustering artifacts. Cell-level metabolic activity. The rRNA/rDNA ratio of a taxonomic unit has been used to infer its cell-level metabolic activity or growth rate, normalized against its population abundance. We found that taxonomic units formed using the OTU method had slightly higher average rRNA/rDNA ratios (mean = 1.5, SD = 8.1) than ZOTUs (mean = 1.4, SD = 5.1), though the difference was not statistically significant (Mann-Whitney P = 0.83). The rRNA/rDNA ratio ranged from 0 to 316 for OTUs and from 0 to 206 for ZOTUs, with approximately 50% of both sets of taxonomic units having a ratio smaller than one across all samples. In contrast, the transcription/abundance ratios of reconstructed population genomes had a similar mean (1.5) but much lower variance (SD = 2.9; range, 0 to 26). As the population genome transcription levels were estimated from the transcription of ORFs in the population genome scaffolds, this difference in variance may reflect a higher variance in ribosomal amplification between taxa relative to variance in the transcription level of structural genes. To compare the inferred metabolic activities of 16S amplicon-based taxonomic units against those of the population genomes, we examined three high-abundance orders for which a number of representative population genomes had been reconstructed ( Fig. 3 ). The Clostridiales had per-sample rRNA/rDNA ratios ranging from 0 to 316 among OTUs and from 0 to 206 among ZOTUs and transcription/abundance ratios from 0 to 13.4 among population genomes but had similar mean ratios with all three methods (OTU mean = 1.4, ZOTU mean = 1.3, population genome mean = 1.6), although the ratios were found to differ significantly between methods using an analysis of variance (Kruskal-Wallis P = 0.001). FIG 3 Transcription/abundance ratios (logarithmic scale) of OTUs, ZOTUs, and population genomes of selected microbial orders. For OTUs and ZOTUs, the transcription/abundance ratio is the rRNA/rDNA ratio; for population genomes, it is derived from metagenomic and metatransciptomic abundances. The box indicates the 25th to 75th percentiles, the thick vertical line indicates the median, and whiskers represent smallest and largest values no more than 1.5× interquartile range. The Methanobacteriales had similarly low ratios across all three methods (OTU range = 0 to 64, mean = 0.93; ZOTU range = 0 to 3.9, mean = 0.58; population genome range = 0.05 to 0.96, mean = 0.34), with no statistically significant differences between methods (Kruskal-Wallis P = 0.20). While this consistently low ratio might suggest that the Methanobacteriales are mostly dormant, we note that methane production was demonstrated for all the mesophilic enrichment cultures ( 39 , 40 ), suggesting that the Methanobacteriales were in fact metabolically active. This apparent contradiction may be due to the fact that ribosomal amplification is not always linearly correlated with metabolic activity ( 10 ), and it could also reflect the tendency for mixed-growth rate communities and undersampling to falsely suggest that active taxa are dormant ( 31 ). rRNA/rDNA and transcription/abundance ratios for the order Desulfovibrionales (of which only the genus Desulfovibrio was detected using either the amplicon-based or population genome methods) tended to be higher than that for the other two orders, suggesting a higher level of metabolic activity. The ratios ranged from 0 to 232 (mean = 32) among OTUs, 4.0 to 76 (mean = 18.4) among ZOTUs, and 3.2 to 26 (mean = 14.3) among population genomes, with no statistically significant difference between the three methods (Kruskal-Wallis P = 0.68). Despite this high transcriptional activity, the order was not abundant, with an average relative abundance of <0.3% (0 to 1.1% of OTUs and 0 to 0.7% of ZOTUs) among the amplicon-based populations. While high rRNA/rDNA ratios were detected from Desulfovibrionales in all the mesophilic cellulose culture samples, no Desulfovibrionales were detected in the mesophilic xylan or thermophilic cellulose cultures. Only one Desulfovibrionales population genome was reconstructed from a metagenome, and it was found only in the SWH-C-35 culture at two time points, where it exhibited transcription/abundance ratios of 3.2 and 26. Variation in neither ribosomal amplification ( 10 ) nor the transcription of structural genes is necessarily directly related to growth or metabolic activity, and different growth strategies may entail different levels of transcriptional regulation. For example, the oligotrophic marine bacterium “ Candidatus Pelagibacter ubique” (SAR11), which has an atypically small and streamlined genome, has been reported not to vary the transcription of >99% of its genes in response to growth rate and to transcribe 30S and 50S ribosomal genes at much lower levels than taxa with a copiotrophic growth strategy ( 43 ). However, the concordance between amplicon rRNA/rDNA and population genome transcription/abundance ratios suggests that both methods capture at least some of the true variance in metabolic and growth rates between taxa. We compared the transcription/abundance ratios of 16S amplicon taxonomic units and population genomes against their relative abundances ( Fig. 4 ). For all three methods, a pattern emerged in which taxonomic units with the highest rRNA/rDNA or transcription/abundance ratios were almost always those with low relative abundances, with the majority of taxonomic units with ratios of >1 having relative abundances of <1%. Other studies have reported a similar pattern in marine environments ( 18 – 20 ), as well as in outdoor air ( 22 ) and indoor air ( 23 ), and activated-sludge systems ( 28 ), although as noted above and by others ( 42 ), despite this pattern, the vast majority of total community production is still contributed by high-abundance taxa ( Fig. S2 ). FIG 4 Relationship between relative abundance and transcription/abundance ratio (logarithmic scales) of OTUs (brown), ZOTUs (turquoise), and population genomes (pink) across all samples. Each symbol represents one taxonomic unit. For OTUs and ZOTUs, abundance and transcription are the relative rDNA and rRNA abundances, respectively; for population genomes, they are derived from metagenomic and metatranscriptomic abundances. The gray dashed lines indicate a relative abundance of 1% (vertical line) and a transcription/abundance ratio of 1 (horizontal line). There are several possible explanations for this observation. It may arise from methodological artifacts, such as PCR bias or undersampling. Steven et al. ( 31 ) reported that undersampling of simulated microbial communities can increase the apparent range of rRNA/rDNA ratios, presumably due to the scarcity of rDNA relative to rRNA. The higher number of rare compared to abundant taxonomic units could also give rise to a higher absolute number of extreme rRNA/rDNA ratios by random chance, even if variance in ratios was identical between rare and abundant taxa. Alternatively, this may be a true biological pattern arising from the microbial community dynamics and/or structure. The “kill-the-winner” hypothesis suggests that fast-growing taxa may be more prone to lysis and grazing, preventing them from being dominant, while the slow-growing taxa are more resistant and thus can flourish ( 44 ). This hypothesis has been used to explain the higher growth rate of the rare taxa and the lower growth rate of the abundant taxa in marine environments ( 20 , 42 ). To further investigate whether this pattern was biological or artifactual, we estimated the replication rates of the population genomes using the iRep metric, which is derived from variable read coverage across the length of a genome ( 45 ), and thus provides corroboration of microbial activity independent of the transcription/abundance ratios. We found a similar pattern of high-iRep genomes being almost exclusively low abundance ( Fig. 5 ), although the linear correlation between the iRep metric and the transcription/abundance ratio was only weakly positive (Pearson’s ρ = 0.22, P = 0.048). Taken together, this suggests that while methodological artifacts may influence observed rRNA/rDNA ratios, the rRNA/rDNA method can capture biologically meaningful patterns using either OTU or ZOTU taxonomic unit formation method even in the presence of undersampling. FIG 5 iRep index (estimated genome copy number/cell) compared to relative abundance (logarithmic scale) for population genomes. Each symbol represents a population genome. The vertical gray dashed lines indicate a relative abundance of 1%. Close examination of the transcriptional profiles of the top three genomes with a high transcription/abundance ratio but low relative abundance (<1%) in each sample revealed that the top 20 transcribed ORFs spanned a wide range of biological functions, although most of the proteins could not be classified based on the SEED system category ( 46 , 47 ) ( Fig. S3 ). Among the most highly transcribed ORFs, they encode a membrane transporter protein, a rubrerythrin and a zinc finger domain protein ( Fig. S3 ). These proteins are known to perform substrate uptake, stress protection, or diverse molecular recognition and binding functions. Hence, microbial populations that are rare but have a high transcription/abundance ratio could play important functional roles in AD communities. 10.1128/mSystems.00208-18.3 FIG S3 Biological functional category and transcription level of the top 20 transcribed ORFs in the top three genomes with a high transcription/abundance ratio and low relative abundance (<1%) in each sample. (A) The number of the ORFs in each SEED system category. (B) Transcription level of the ORFs represented as TPM in each SEED system category. ORFs with a TPM greater than 2,000 were indicated with an asterisk together with functions based on the SEED functional role where available. Download FIG S3, TIF file, 1.2 MB . Copyright © 2019 Jia et al. 2019 Jia et al. This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . Transcriptional activity dynamics of abundant ZOTUs. In order to understand to what extent the 97% sequence similarity threshold may cause ecologically different microbes to be “lumped” into the same taxonomic unit, we mapped each ZOTU against the representative sequence for each OTU sequence using a similarity threshold of 97%. A total of 1,318 ZOTUs (87%) were successfully mapped to 425 OTUs, with each OTU recruiting 1 to 29 ZOTUs. The mapping of the majority of ZOTU sequences to a small subset of OTUs is consistent with the lower phylogenetic diversity of the ZOTU-based communities ( Table 1 ). ZOTUs with a 16S rDNA relative abundance greater than 1% in any sample were selected for further analysis. The relative abundances of these ZOTUs ranged from 0 to 32% in each sample, while their rRNA/rDNA ratios ranged from 0 to 15.9. In the two mesophilic cellulose cultures for which time course data were available, ZOTUs mapped to the same OTU showed similar dynamic trends in rDNA relative abundance, rRNA relative abundance, and rRNA/rDNA ratio during the course of fermentation ( Fig. S4 ). Because compositional microbial abundance data are not independent and can exhibit spurious cooccurrence patterns, we used a compositionally robust method ( 48 , 49 ) to investigate whether ZOTUs mapped to the same OTU tended to have different cooccurrence patterns, which would suggest the inclusion of ecologically distinct taxa within the same OTU. The resulting networks ( Fig. 6 ) tended to closely group ZOTUs from the same OTU into positively interacting clusters in both the total (rDNA) and active (rRNA) communities. No significant negative interactions were observed in the networks between ZOTUs from the same OTU. Overall, the results suggest that, at least among abundant ZOTUs, OTUs tended to cluster together ZOTUs with similar dynamics in abundance and metabolic activity. FIG 6 Cooccurrence of abundant ZOTUs determined by the SPIEC-EASI algorithm, in the total (rDNA) (A) and active (rRNA) (B) communities. Nodes indicate ZOTUs, colored by the OTU to which they had ≥97% sequence similarity (ZOTUs not belonging to the 14 most abundant OTUs grouped in “Minor/Unclassified”), with the size of the node proportional to the ZOTU magnitude of correlations with other ZOTUs. Edges indicate significant correlations between ZOTUs, colored by a positive (blue) or negative (red) interaction. 10.1128/mSystems.00208-18.4 FIG S4 Dynamic trends in ZOTU rDNA relative abundance, rRNA relative abundance, and rRNA/rDNA ratio in the two cultures for which time series data were collected, GZ-C-35 (A) and SWH-C-35 (B). ZOTUs with abundance of ≥1% in at least one sample are shown. OTUs indicate the OTU to which each ZOTU had a ≥97% sequence similarity match. The horizontal axis indicates day of fermentation time course (D5, day 5; Mid, mid-exponential point; D10, day 10; D15, day 15). Download FIG S4, TIF file, 2.5 MB . Copyright © 2019 Jia et al. 2019 Jia et al. This content is distributed under the terms of the Creative Commons Attribution 4.0 International license . Comparison of the ZOTU and conventional OTU methods in evaluating activity. The use of ESVs, features, or ZOTUs in microbial community surveys has recently been proposed as superior to conventional OTUs formed at 97% sequence similarity, as these new methods may maximize the phylogenetic resolution of the sequencing data while minimizing the conflation of biologically distinct populations into the same taxonomic unit ( 32 , 35 , 37 ). We found that, at least for the UNOISE3 algorithm with default settings and for the types of communities studied (which were simplified following long-term enrichment), there was no clear advantage of the ZOTU method over conventional OTU formation method and that the ZOTU method may indeed discard some biologically relevant information. Both methods provided comparable pictures of the community taxonomic compositions ( Fig. S1 ), though the ZOTU method appeared to capture less phylogenetic diversity ( Table 1 ), and both methods largely agreed with the results of a separate metagenome-based survey in the assessment of relative metabolic activity ( 40 ). Both methods, and the reconstructed population metagenomes, appeared susceptible to the type of false-negative error described previously ( 31 ), in which taxa confirmed to be active by in vitro measurements appeared dormant based on low rRNA/rDNA ratios ( Fig. 3 ). However, the ZOTU method produced a much larger proportion (31%) of phantom taxa than the OTU method (11%). Because phantom taxa are necessarily the result of undersampling and/or methodological error and because these taxa must be excluded from any analysis that relies on relative rDNA and rRNA abundances, this suggests that the ZOTU method may be inferior to conventional OTUs when attempting to assess metabolic activity inferred by the rRNA/rDNA ratio, especially for studies with insufficient sequencing effort or communities with a large number of rare taxa. UNOISE3 uses the abundance of reads to denoise sequences, rather than quality scores and a model of sequencing error as in other methods ( 37 ), and it excludes sequences that do not meet an abundance threshold (by default 8) in the pooled input reads ( 35 ). Given the large proportion of reads excluded in the ZOTU pipeline compared to the OTU pipeline, it is likely that this default threshold had a significant effect on ZOTU formation and may have resulted in the ZOTU set discarding many genuine low-abundance taxa. We found little evidence to support the proposal that 97% similar OTUs frequently conflate taxa with different ecological roles in our enriched model communities, at least among higher-abundance ZOTUs. Further work is needed to explore whether this holds true for other artificial and natural systems and whether other ZOTU formation algorithms give similar results. Conclusions. Variation in microbial activity levels is an important factor in community function. In our model AD communities, the rRNA/rDNA ratio revealed large variance in cell-level microbial activity levels across taxa, cooperated with two alternative taxonomic unit formation methods and by reconstructed metagenomic population genomes and their complementary transcriptomes. Confirming previous findings, the most metabolically active and rapidly dividing taxa tended to be the least abundant in the five AD communities, though further work is needed to establish whether this is an entirely natural or at least partially artifactual pattern. We found no obvious evidence to support the suggestion that the conventional 97% sequence similarity 16S OTUs conflates distinct ecological entities or discards biologically relevant information compared to the UNOISE3 method applied in this study, and instead found the UNOISE3-based ZOTU method generated a higher rate of phantom taxa, suggesting it may less suitable for assessing metabolic activity with the rRNA/rDNA ratio, a method already fraught with difficulties in interpretation."
} | 9,148 |
22027591 | PMC3207205 | pmc | 3,199 | {
"abstract": "Expanding the useful lifespan of materials is becoming highly desirable, and self-healing and self-repairing materials may become valuable commodities. The formation of supramolecular materials through host–guest interactions is a powerful method to create non-conventional materials. Here we report the formation of supramolecular hydrogels and their redox-responsive and self-healing properties due to host–guest interactions. We employ cyclodextrin (CD) as a host molecule because it is environmentally benign and has diverse applications. A transparent supramolecular hydrogel quickly forms upon mixing poly(acrylic acid) (pAA) possessing β-CD as a host polymer with pAA possessing ferrocene as a guest polymer. Redox stimuli induce a sol−gel phase transition in the supramolecular hydrogel and can control self-healing properties such as re-adhesion between cut surfaces.",
"discussion": "Discussion We successfully realized reversible sol−gel switching and a self-healing supramolecular hydrogel system consisting of pAA-6βCD/pAA-Fc. Although microscale switching of supramolecular complexes by redox is well known, a macroscale morphological change is difficult to achieve. This work demonstrates that intelligent supramolecular hydrogels may be formed using a main chain with a sufficient length and an adequate number of guest molecules to generate reversible multipoint crosslinks between pAA-6βCD/pAA-Fc. A redox reaction alters the morphology of a supramolecular hydrogel by controlling the formation of an inclusion complex. These stimulus-responsive self-healing properties are similar to the selective cell-adhesive protein observed on a cellular surface. Stimulus-responsive self-healing properties have many general applications. Thus, we believe that these stimulus-responsive and healing properties may eventually be used in stimulus-responsive drug-delivery carriers and peripheral vascular embolization materials with healing properties that target cancer cells and myoma."
} | 493 |
39645585 | PMC11754932 | pmc | 3,200 | {
"abstract": "Summary \n Many plant species experience a prolonged subterranean phase during which they rely entirely on mycorrhizal fungi for carbon. While this mycoheterotrophic strategy spans liverworts, lycophytes, and ferns, most empirical research has centered on angiosperms. This study explores the fungal associations of Sceptridium (Ophioglossaceae), an early‐diverging fern with mycoheterotrophic gametophytes. We analyzed germination patterns and fungal associations in Sceptridium gametophytes, comparing them to the distribution and mycorrhizal partners of photosynthetic sporophytes. High‐throughput sequencing data reveal that mycoheterotrophic gametophytes consistently associate with a single Entrophospora fungus in the order Entrophosporales (Glomeromycotina), while photosynthetic sporophytes primarily partner with fungi from Glomeraceae (Glomerales, Glomeromycotina). Consequently, gametophytes exhibit spatial clustering without association with adult plants. This is the first documentation of an association between Entrophosporaceae (and the order Entrophosporales) and mycoheterotrophic plants. The drastic shifts in Sceptridium mycorrhizal communities across life stages likely reflect changing physiological needs during development. Further research is essential to determine whether the association with Entrophosporaceae is widespread among mycoheterotrophic species and to elucidate the functional and physiological mechanisms underlying these mycorrhizal shifts.",
"conclusion": "Conclusion We revealed a drastic shift in fungal partners between the mycoheterotrophic gametophytes and photosynthetic sporophytes in Sceptridium species. The interaction between Entrophosporaceae and mycoheterotrophic plants represents a novel discovery. Whether this is a unique case or a frequent but undocumented phenomenon among other mycoheterotrophs, particularly gametophytes, remains uncertain. Future studies, including ancestral character‐state reconstruction analyses with more extensive mycorrhizal data from other Ophioglossaceae species, will be crucial for understanding the coevolution between ferns and AM fungi. The dramatic change in mycorrhizal associations in Sceptridium species is potentially linked to physiological transitions. Future research should focus on the functional and physiological mechanisms driving this shift. Experimental studies under controlled conditions could provide key insights into the symbiotic interactions and resource translocation dynamics between these partners.",
"introduction": "Introduction Most land plants, from liverworts to angiosperms, engage in mutualistic arbuscular mycorrhizal (AM) symbioses with fungi belonging to Glomeromycotina and, to a lesser extent, Mucoromycotina (Bidartondo et al ., 2011 ; van der Heijden et al ., 2015 ; Hoysted et al ., 2018 ). In these associations, plants acquire essential mineral nutrients from their mycorrhizal partners in exchange for carbon produced through photosynthesis. These AM symbioses are considered pivotal for the colonization and diversification of land plants (Remy et al ., 1994 ; Selosse & Le Tacon, 1998 ; Redecker et al ., 2000 ; Wang et al ., 2010 ; Hoysted et al ., 2018 ). AM associations are the most widespread mycorrhizal interaction, found not only in vascular plants but also in liverworts and hornworts (Wang & Qiu, 2006 ; Merckx, 2013 ; Rimington et al ., 2020 ), while shifts toward novel mycorrhizal associations with basidiomycete or ascomycete fungi are key innovations that have driven the evolution of specialized life histories and nutritional modes in land plants (Brundrett, 2002 ; Wang et al ., 2021 ). Many early‐diverging vascular plants, such as lycophytes (the outgroup to all other living vascular plant lineages), exhibit a life cycle characterized by a subterranean mycoheterotrophic gametophyte generation (Winther & Friedman, 2007 , 2008 , 2009 ) that produces gametes and, after mating, supports the growth of a diploid, photosynthetic sporophyte. Gametophytes typically rely on Glomeromycotina and Mucoromycotina fungi to meet their carbon requirements (Winther & Friedman, 2007 , 2008 , 2009 ; Horn et al ., 2013 ; Hoysted et al ., 2021 ). This strategy, known as mycoheterotrophy, exploits fungal partners by reversing the usual carbon flow from plant to fungi (Merckx, 2013 ). This life‐history trait is present in ca . one thousand species of ferns and lycophytes across various biomes, from tropical to subalpine ecosystems (Merckx, 2013 ). Despite its prevalence, information on the associations between mycoheterotrophic gametophytes and AM fungi is relatively scarce, due to the hidden nature of these life stages. Further research is needed to investigate the dynamics of plant–fungal associations throughout the entire life cycle of such plants. Available evidence indicates that both fully mycoheterotrophic gametophytes and photosynthetic sporophytes of lycophytes ( Lycopodium and Huperzia ) and ophioglossoid ferns ( Botrychium and Psilotum nudum ) typically exhibit high‐intergenerational fidelity toward a specific clade of Glomeraceae or Mucoromycotina fungi (Winther & Friedman, 2007 , 2008 , 2009 ; Perez‐Lamarque et al ., 2023 ). This fidelity suggests a ‘take now, pay later’ mechanism in their mycorrhizal relationships, where carbon invested by AM fungal partners to support mycoheterotrophic stages is reciprocated later by green sporophytes (Leake et al ., 2008 ; Field et al ., 2015 ). This mechanism has also been proposed as the principle underlying fungal specificity and mutualism throughout the mycoheterotrophic‐to‐autotrophic life stages in the development of most green‐leaved orchids (Cameron et al ., 2008 ; Read et al ., 2024 ). Furthermore, intergenerational fungal specificity may indicate a carbon subsidy from green‐leaved sporophytes to achlorophyllous gametophytes via a shared fungal partner, a form of parental nurture (Leake et al ., 2008 ). Indeed, although experimental evidence of this process is still lacking in lycophytes and ferns, recent research shows that the fungal partners of the orchid Dactylorhiza fuchsii transfer photosynthates from autotrophic adult plants to mycoheterotrophic protocorms via a common mycorrhizal network, further supporting the parental nurture hypothesis (Read et al ., 2024 ). Ophioglossaceae, along with Psilotaceae, are unique among eusporangiate fern lineages for their fully mycoheterotrophic gametophytes (Zhang et al ., 2020 ; Zhang & Zhang, 2022 ). While the earliest fossils of Ophioglossaceae can only be traced back to the Paleocene (Rothwell & Stockey, 1989 ), they represent one of the earliest diverging fern clades, with estimated stem ages between 250 and 370 million years (Pryer et al ., 2004 ; Rothfels et al ., 2015 ; Testo & Sundue, 2016 ). Ophioglossaceae are distinguishable from other ferns by their bifurcated fronds, which consist of one vegetative leaf and another reproductive, spore‐bearing leaf (Hauk et al ., 2003 ). Molecular studies have confirmed the monophyly of the family and identified two species‐rich subfamilies, Botrychioideae and Ophioglossoideae, each containing ca . 100 species (Hauk et al ., 2003 ; Zhang & Zhang, 2022 ). Within Botrychioideae, the genera Botrychium and Sceptridium are species‐rich and nearly cosmopolitan (Zhang & Zhang, 2022 ). This study investigates the largely unexplored fungal associates of Sceptridium . The taxa studied exhibit typical Ophioglossaceae characteristics: the inconspicuous, subterranean, and Chl‐free gametophyte generation, persisting for several years, is eventually replaced by an erect, green, autotrophic sporophyte (Campbell, 1921 ; Nozu, 1954 ; Takahashi & Imaichi, 2007 ). Although AM associations in these plants have been microscopically observed during their subterranean stages (Daigobo, 1979 , 1983 ), the molecular and phylogenetic identities of the fungal partners throughout the plant life cycle remain unknown, highlighting the need for molecular studies to unravel the fungal partners involved. In line with previous studies on mycoheterotrophic gametophytes of Lycopodium , Huperzia , Botrychium , and Psilotum species (Winther & Friedman, 2007 , 2008 , 2009 ), we primarily expect Glomeraceae fungi to be the fungal associates in both gametophyte and sporophyte generations. However, considering dynamic shifts in mycorrhizal partnerships during plant development in certain angiosperms (Jacquemyn & Merckx, 2019 ; Ventre Lespiaucq et al ., 2021 ), we cannot exclude similar mycorrhizal shifts in response to the nutritional or ecological needs of each life stage. Our primary objectives are to address key questions about mycorrhizal symbiosis in nonseed plants with subterranean mycoheterotrophic stages, specifically focusing on Sceptridium : (1) What is the molecular identity of the AM fungi associated with Sceptridium species? (2) Do the AM fungal symbionts remain consistent throughout both autotrophic and mycoheterotrophic stages? (3) Is there a spatial association between sporophytes and gametophytes, as predicted by the hypothesis that parental plants act as carbon donors?",
"discussion": "Discussion Novel mycoheterotrophic interaction between Entrophospora and Sceptridium \n We identified a consistent mycorrhizal association between fully mycoheterotrophic Sceptridium gametophytes and a single Entrophospora species (VTX00225). While AM α‐diversity was not significantly lower during the gametophyte generation, specialization can still occur when a plant primarily relies on key mycorrhizal partners, with additional nonspecific fungi providing less critical resources (Shefferson et al ., 2019 ; Suetsugu et al ., 2021 ). Given the consistently high abundance of VTX00225 across all gametophyte samples, we consider Sceptridium gametophytes to be specialized on this fungus. Although the fine hyphae and terminal hyphal swelling observed in Sceptridium gametophytes do not entirely exclude the possibility of co‐colonization by Mucoromycotina (e.g. Rimington et al ., 2015 , 2020 ; Perez‐Lamarque et al ., 2023 ), Mucoromycotina fungi are unlikely to be major mycobionts due to the lack of amplification with Mucoromycotina‐specific primers. Therefore, the observed morphological differences in mycorrhizal structures between Sceptridium sporophytes and gametophytes likely reflect differences in fungal partners within Glomeromycotina (Glomeraceae vs Entrophosporaceae) and the degree of mycoheterotrophy (at least partial autotrophy vs full mycoheterotrophy). Our findings generally support the trend that mycoheterotrophic plant species tend to specialize in ‘narrow’ clades of fungi (Bidartondo et al ., 2002 ; Yamato et al ., 2014 ; Gomes et al ., 2017 ). Nonetheless, most mycorrhizal fungi identified in AM‐forming mycoheterotrophic plants belong to the family Glomeraceae, regardless of plant phylogenetic background (Bidartondo et al ., 2002 ; Merckx et al ., 2012 ; Suetsugu et al ., 2014 ; Yamato et al ., 2014 ; Gomes et al ., 2017 ; Perez‐Lamarque et al ., 2020 ; Zhao et al ., 2021 ). For example, Yamato et al . ( 2014 ) found that the mycorrhizal fungi associated with the fully mycoheterotrophic Petrosavia sakuraii belonged to a single clade within Glomeraceae, while its autotrophic sister species Japonolirion osense associated with a more diverse range of mycorrhizal fungi, including Glomeraceae, Acaulosporaceae, and Diversisporaceae. Similarly, Zhao et al . ( 2021 ) demonstrated a gradual shift away from non‐Glomeraceae fungi during the mycoheterotrophic evolution of Burmannia species with different trophic modes. Notably, VTX00225, which is predominantly associated with Sceptridium gametophytes, has not been identified in other mycoheterotrophic lycophytes ( Lycopodium and Huperzia ) or ferns ( Botrychium and Psilotum nudum ). Furthermore, no previous associations between Entrophosporaceae (or the order Entrophosporales) and mycoheterotrophic plants have been documented (Perez‐Lamarque et al ., 2020 ). This newly identified partnership broadens our understanding of the diversity of fungal partners in mycoheterotrophic plants. Genomic studies have positioned Entrophosporaceae as a sister group to a clade that includes Glomeraceae, Diversisporaceae, and Acaulosporaceae (Perez‐Lamarque et al ., 2022 ). Interestingly, these early‐diverging clades, including Entrophosporaceae, are often perceived as less beneficial to plants compared to more rapidly diversifying groups such as Glomeraceae and Diversisporaceae (Säle et al ., 2021 ). In a biological marketplace model of mycorrhizal interactions, these early‐diverging fungi might be less effective in maintaining beneficial symbioses with autotrophic plants, potentially making them less preferred partners (Kiers et al ., 2011 ). However, their potentially less stringent control over nutritional exchanges might render them ideal for mycoheterotrophic plants, particularly in certain environments. Since these fungi may form parasitic associations with autotrophic AM plants (Säle et al ., 2021 ), they could discriminate less in their interactions, making them more vulnerable to exploitation by mycoheterotrophic plants. Mycoheterotrophic plants tend to favor keystone fungi, which connect them to a wide variety of autotrophic plants, offering a more stable and reliable carbon source (Gomes et al ., 2022 ). Notably, the AM taxon utilized by mycoheterotrophic Sceptridium gametophytes (VTX00225) is a keystone taxon with high‐network connectivity in certain low‐disturbance forests (Wall et al ., 2020 ), where the gametophytes thrive. It also displays resilience in agricultural and urban environments, including lawns and gardens, forming mycorrhizal associations with a broad range of plant taxa, such as species in Poaceae, Rosaceae, and Lamiaceae (Öpik et al ., 2010 ). Additionally, Entrophospora fungi, including VTX00057 and VTX00193, have been identified in photosynthetic gametophytes of certain ferns, such as Osmunda banksiifolia (Osmundaceae) and Plagiogyria euphlebia (Plagiogyriaceae) (Ogura‐Tsujita et al ., 2013 ). Considering the limited studies on fungal associates in mycoheterotrophic fern gametophytes (Winther & Friedman, 2007 , 2009 ), further research will be essential to evaluate the ecological role of Entrophospora fungi in other ferns with mycoheterotrophic gametophytes. Intergenerational mycorrhizal community shifts in Sceptridium \n Our research reveals a notable shift in mycorrhizal associations in Sceptridium species during the transition from mycoheterotrophic gametophytes to autotrophic sporophytes. Gametophytes predominantly associate with a single Entrophospora VTX (VTX00225), while sporophytes primarily engage with Glomeraceae VTXs. Consequently, Sceptridium gametophytes were often clustered but did not spatially align with adult sporophytes. In many mycoheterotrophic plants, the availability of appropriate mycorrhizal fungi is crucial for seedling recruitment (McCormick & Jacquemyn, 2014 ). Previous studies often report a strong correlation between adult plants and seed germination, attributed to consistent mycorrhizal partnerships throughout the life cycle (Diez, 2007 ; Jacquemyn et al ., 2007 , 2012 ; Waud et al ., 2016 ; McCormick et al ., 2018 ). Adult autotrophic plants of initially mycoheterotrophic species host dense fungal networks, likely facilitating carbon transfer to nearby seedlings, which may explain why seedling recruitment predominantly occurs near parent plants (Waud et al ., 2016 ; McCormick et al ., 2018 ; Read et al ., 2024 ). However, all currently known examples of such correlations are from orchid mycorrhizas with basidiomycetes. Our study found no significant correlation between the abundance of gametophytes and sporophytes, likely due to the different mycorrhizal preferences between these two life stages. Adult plants primarily associate with Glomeraceae fungi, which are nearly absent in gametophytes. Therefore, proximity to sporophytes does not enhance the availability of necessary mycorrhizal fungi for gametophyte formation. Previous research indicates a high fidelity of specific arbuscular mycorrhizal fungi with sporophytes and gametophytes in Botrychium (Ophioglossaceae), Huperzia (Lycopodiaceae), and Psilotum (Psilotaceae) (Winther & Friedman, 2007 , 2008 , 2009 ). This fidelity is thought to support parental nurture, where organic carbon is transferred across generations (Winther & Friedman, 2007 , 2008 , 2009 ; Leake et al ., 2008 ; Field et al ., 2015 ). Cameron et al . ( 2008 ) proposed a ‘give now, get more later’ model in green orchids, where fungi invest resources in the early mycoheterotrophic stage, which is later reciprocated when the plant becomes autotrophic. However, given the observed mycorrhizal shift, neither of these concepts applies to Sceptridium species and VTX00225. The lack of direct intergenerational transmission of mycorrhizal fungi through the gametophyte–sporophyte interface may favor different mycorrhizal associations. However, this alone does not explain the shift, as independent recruitment of the same partners has been observed in Botrychium and Huperzia , both of which maintain similar mycorrhizal communities across stages (Leake et al ., 2008 ). An intriguing aspect is the complete absence of Entrophospora in mature Sceptridium sporophytes. Such drastic transitions are rare among mycoheterotrophic plants, with exceptions including the orchids Gastrodia elata (Chen et al ., 2019 ), G. confusoides (Li et al ., 2022 ), and the Ericaceae species Pyrola asarifolia (Hashimoto et al ., 2012 ). Drastic changes in mycorrhizal communities can create challenges in acquiring new partners and may negatively impact the population dynamics of mycoheterotrophs (Ogura‐Tsujita et al ., 2021 ; Ventre Lespiaucq et al ., 2021 ). Therefore, partner switching likely occurs only when it confers advantages in resource acquisition. For instance, in the fully mycoheterotrophic orchid G. elata , a shift from litter‐decaying Mycena fungi to Armillaria fungi allows access to a larger carbon pool (Ogura‐Tsujita et al ., 2021 ). The shifts in Sceptridium species during the generational transition may reflect changes in resource acquisition strategies similar to mycorrhizal transitions observed in some orchids that become autotrophic upon reaching adulthood (Bayman et al ., 2016 ; Zahn et al ., 2022 ). If Sceptridium sporophytes are fully autotrophic, transitioning to conventional mutualistic mycorrhizal associations, fungi such as Entrophospora sp., which are less beneficial for autotrophic plants (Säle et al ., 2021 ), would not effectively provide minerals. Consequently, sporophytes may have evolved associations with fungi that better meet their nutrient demands. Alternatively, if Sceptridium sporophytes retain some level of mycoheterotrophy, as shown in some Ophioglossaceae species (e.g. Suetsugu et al ., 2020 ), their larger biomass might require greater carbon input from fungal partners, despite their partial autotrophy. This hypothesis may be indirectly supported by the fact that most VTXs found in Sceptridium sporophytes (e.g. VTX00080 and VTX00084) largely overlap with those in fully mycoheterotrophic species across multiple families, including Burmanniaceae, Gentianaceae, Petrosaviaceae, Polygalaceae, Thismiaceae, and Triuridaceae (Perez‐Lamarque et al ., 2020 ; Suetsugu & Okada, 2021 ; Suetsugu et al ., 2022 ). Overall, regardless of the specific nature of these associations, shifts in plant physiological requirements likely drive the observed changes in mycorrhizal partners. Conclusion We revealed a drastic shift in fungal partners between the mycoheterotrophic gametophytes and photosynthetic sporophytes in Sceptridium species. The interaction between Entrophosporaceae and mycoheterotrophic plants represents a novel discovery. Whether this is a unique case or a frequent but undocumented phenomenon among other mycoheterotrophs, particularly gametophytes, remains uncertain. Future studies, including ancestral character‐state reconstruction analyses with more extensive mycorrhizal data from other Ophioglossaceae species, will be crucial for understanding the coevolution between ferns and AM fungi. The dramatic change in mycorrhizal associations in Sceptridium species is potentially linked to physiological transitions. Future research should focus on the functional and physiological mechanisms driving this shift. Experimental studies under controlled conditions could provide key insights into the symbiotic interactions and resource translocation dynamics between these partners."
} | 5,217 |
36997991 | PMC10064694 | pmc | 3,203 | {
"abstract": "The difficulty of degrading lignin is the main factor limiting the high-value conversion process of lignocellulosic biomass. The biodegradation of lignin has attracted much attention because of its strong environmental friendliness, but it still faces some dilemmas such as slow degradation rate and poor adaptability. The microbial consortia with high lignin degradation efficiency and strong environmental adaptability were obtained in our previous research. To further increase the lignin degradation efficiency, this paper proposes a composite treatment technology of steam explosion combined with microbial consortium degradation to treat three kinds of biomass. We measured the lignin degradation efficiency, selectivity value (SV) and enzymatic saccharification efficiency. The structural changes of the biomass materials and microbial consortium structure were also investigated. The experimental results showed that after 1.6 MPa steam explosion treatment, the lignin degradation efficiency of the eucalyptus root reached 35.35% on the 7th days by microbial consortium. At the same time, the lignin degradation efficiency of the bagasse and corn straw treated by steam explosion followed by microbial biotreatment was 37.61–44.24%, respectively, after only 7 days of biotreatment. The microbial consortium also showed strong selectivity degradation to lignin. The composite treatment technology can significantly improve the enzymatic saccharification efficiency. Saccharomycetales, Ralstonia and Pseudomonadaceae were the dominant microorganisms in the biomass degradation systems. It was proved that the combined treatment technology of steam explosion and microbial consortium degradation could overcome the drawbacks of traditional microbial pretreatment technology, and can facilitate the subsequent high-value conversion of lignocellulose.",
"conclusion": "Conclusion Converting lignocellulose waste biomass into high-value products such as biofuel ethanol can not only effectively alleviate the energy shortage, but also be of great significance to achieve the goal of “double carbon”. Lignin structure is stable and difficult to be degraded, which is the main barrier for lignocellulose to achieve high-value transformation. Biological degradation of lignin has low energy consumption, strong safety and good prospects, but the degradation time is long, which affects the industrial application. In this study, the treatment method of biomass steam explosion combined with microbial biodegradation was proposed, which can not only effectively improves the degradation efficiency of lignin, shorten the microbial treatment time, but also greatly improves the enzymatic hydrolysis efficiency of subsequent treatment. The obtained microbial consortia J-6 and J-1 with high lignin degradation rate and strong environment adaptability were selected to degrade lignin in three kinds of biomass (Eucalyptus root, bagasse and corn straw). The results showed that the lignin degradation efficiency of bagasse and eucalyptus root can reach more than 30% in 7 days, and that of corn straw can reach more than 40% with the steam explosion combined with microbial consortium biodegradation. The selective degradation ability of J-6 and J-1 was also studied. The experimental results showed that in the presence of cellulose and hemicellulose, J-6 and J-1 could selectively degrade lignin. After steam explosion combined with microbial treatment, the enzymatic sugar conversion efficiency of biomass materials also increased significantly. The above research results were also verified by SEM, fiber crystallinity of biomass materials and microbial consortium structure analysis. It could be inferred that the destruction degree of the biomass materials may show a certain correlation with the lignin degradation efficiency. The increase of sample porosity and the destruction of structure could increase the accessibility of enzymatic hydrolysis. And the crystallinity of cellulose decreased after steam explosion, however, the crystallinity of cellulose was not changed significantly after the pretreatment by the lignin degradation microorganisms. In addition, according to genomic sequencing analyses, the fungal community composition of the microbial consortia in different systems was not significantly different, and was nearly the same as that of the original microbial consortia. But the bacterial composition of J-6/J-1 microbial consortium was changed in different systems. Ralstonia and Pseudomonadaceae can play an important role in the biomass system for lignin degradation. The microbial consortium had strong adaptability in different degradation systems. The steam explosion combined with microbial consortium degradation of lignin pretreatment technology in this study can help waste biomass create higher value-added products. It was also proved that the collaborative degradation of lignin by microbial consortium could overcame the problem of degradation by the single strain. This research also provided a reference for exploring the mechanism of lignin degradation and microorganisms. In the future, the change of lignin degradation products and the mechanism of microbial interaction during degradation will also be studied.",
"introduction": "Introduction Due to the large consumption of fossil energy in the world, excessive greenhouse gases are emitted into the air every year. The environmental harm and climate impact caused by the increase of greenhouse gas content have been widely concerned all over the world. In 2020, China’s total carbon emission reached 10.251 billion tons, with the energy consumption and carbon dioxide emissions second only to the United States [ 1 ]. The carbon dioxide emission of China would rise to the first around 2025 [ 2 ]. Therefore, it is urgently needed to control carbon dioxide emissions and reduce the use of fossil energy at present. Many countries in the world are implementing carbon emission reduction plans. For example, China has proposed the Dual Carbon strategic goal of achieving carbon peak by 2030 and carbon neutrality by 2060. On the other hand, with the tension and changes in the international situation, there is a great risk of countries relying too much on fossil energy. Therefore, the efficient use of biomass energy has received extensive attention. The efficient utilization of biomass energy can replace the consumption of some fossil energy and reduce carbon emissions [ 3 ]. Biomass will absorb carbon dioxide in the atmosphere during its growth, and biomass energy is a carbon Zero emission energy in the sense of life cycle analysis. Lignocellulose biomass is the most abundant renewable biomass resource on earth, with wide sources and low cost. According to the data from the Ministry of Agriculture and Rural Affairs of China, the production of straw lignocellulose in China reached 797 million tons in 2020 [ 4 ]. If effective treatment technology can be developed to convert the waste lignocellulose biomass into high-value products such as biofuel ethanol, the shortage of fossil energy can be effectively alleviated, and the carbon emission caused by lignocellulose incineration should be reduced [ 5 ]. Therefore, it is vital to develop and utilize lignocellulose biomass resources. The raw materials of lignocellulose are mainly composed of cellulose, hemicellulose and lignin. Lignin is closely connected with hemicellulose molecules through covalent and hydrogen bonds, making lignocellulose a strong structure and highly resistant to enzymatic and microbial hydrolysis [ 6 ]. Lignin is considered as a natural barrier against the degradation of lignocellulose biomass, which brings difficulties to the industrial biorefinery of lignocellulose biomass. The degradation of lignin can improve the pretreatment efficiency of lignocellulosic biomass, realize the effective separation of cellulose, hemicellulose and lignin, and mildly convert lignocellulosic biomass into bioenergy and other valuable products [ 7 ]. Exploring and developing efficient lignin degradation technology has become a research hotspot in recent years [ 8 ]. The existing research on the efficient degradation of lignin indicates that lignin can be degraded by physical and chemical methods. However, most of these methods require harsh operating conditions or high energy-consumption equipment, and there are some problems such as inhibitors in the degradation process, affecting the subsequent enzymatic hydrolysis and fermentation process. Biological pretreatment is considered as a potential method because of its advantages of low energy consumption, little chemical addition and environmental friendliness [ 9 ]. Traditional lignin-biodegradation microorganisms are represented by fungi such as white rot fungi, but fungal degradation faces some problems, such as slow reaction process and high requirements for strain culture environment and conditions [ 10 ]. Compared with fungi, bacteria can degrade lignin in a faster way, but its degradation efficiency is lower [ 11 ]. The direct use of lignin-degrading enzymes has the disadvantages of high cost and easy inactivation. How to achieve rapid, efficient and low-cost degradation is the key problem to be solved in the industrial application of lignin microbial degradation. The decomposition of lignin in nature is the result of the cooperation of fungi and bacteria in the natural microbial community [ 12 ]. In view of the potential strengths of microbial consortium, our previous research successfully screened four microbial consortia of J-1, J-6, J-8 and J-15 with high lignin degradation efficiency from the decayed wooden relics [ 13 ]. Among them, the lignin degradation efficiency of J-6 was highest and reached 54% after 48 h treatment with an initial lignin concentration of 0.5 g/L. Our work also demonstrated the potential utilization of microbial consortia via the synergy of fungi and bacteria, which can overcome the shortcomings of traditional lignin biodegradation when using a single strain. This indicates the potential application of the microbial consortium to lignin degradation and removal. In addition, microorganisms in the microbial consortium can form metabolic complementarity or nutrition dependence through interaction in the metabolic system, thereby driving the metabolic division of labor. As a result, the microbial consortium always has a high tolerance to nutritional shocks and shows adaptability to different environments [ 14 ]. The microbial consortia screened in our previous research presented high degradation efficiency in the process of degrading alkali lignin (a kind of purified lignin commodity). So, it is of great necessity to explore the application of these lignin degrading microbial consortia in the biomass treatment. Of course, other researchers report some similar studies. For example, Fang et al. screened the microbial consortium from the decaying plant for the treatment of tree trimmings biomass, which can realize the selective degradation of lignin, and this microbial consortium was also composed of fungi and bacteria [ 15 ]. Ali et al. investigated the effective bio-pretreatment of sawdust waste utilizing a novel microbial consortium and reported that the capability of a single strain to degrade lignin was much weaker than using a microbial consortium [ 16 ]. On the other hand, according to the analysis of the existing research results, compared with other physical and chemical methods, biological pretreatment still has dilemmas in low lignin degradation efficiency and long degradation time, which is not conducive to industrial application. Previous research has shown that it is a promising method to combine biological pretreatment with other pretreatment methods to achieve better treatment effect. Consequently, this research selected microbial consortia with high lignin degradation rate and strong environment adaptability to degrade lignin in three kinds of biomass (eucalyptus root, bagasse and corn straw) and biodegradation process was combined with other physical–chemical method to make up for the shortcomings. The degradation mechanism of lignin can be better explained by analyzing and comparing the degradation of different biomass. The research objects mainly include the degradation efficiency of lignin by the microbial consortium in different biomass under different physical–chemical pretreatment conditions such as steam explosion treatment, the selective degradation ability of the microbial consortium and the cellulase hydrolysis efficiency after the microbial consortium treatment. Meanwhile, the degradation mechanism was discussed and analyzed by examining the changes of morphology and community structure in the process of biomass degradation. The research results aim to provide reference for the efficient utilization of microbial consortium to degrade lignocellulose.",
"discussion": "Results and discussion Lignin degradation in biomass In our previous research, it has been confirmed that the microbial degradation process of lignin was mainly related to carbon source composition, degradation pH, and degradation time. Therefore, this research mainly investigates the effects of these factors on the degradation of lignin in biomass. At the same time, our previous experiments also showed that the microorganisms of the microbial consortium had a certain demand for oxygen during the growth and the lignin utilization, because shaking incubation can achieve higher degradation efficiency. Accordingly, shaking incubation was performed in this research and the results showed that temperature had a negligible effect on lignin degradation efficiency within the range of 160–200 rpm. In addition, degradation experiments at different temperatures were also carried out. The results demonstrated that temperature also had a negligible effect on lignin degradation within the temperature range of 25–35 °C. Because the rotation speed and temperature both had little effect on the lignin degradation, in the subsequent experiments, the degradation temperature was 30 °C, and the rotation speed was 180 r/min. And lignin was not degraded in the control group without adding microorganisms. Effect of pH on microbial consortium degradation When lignin is degraded by microorganisms, the pH value of the culture medium is an important factor affecting the degradation efficiency. However, the most suitable pH value for lignin degradation by each microorganism is usually very different. For example, it was reported that the optimal pH value for Aneuribacillus aneurilyticus to degrade lignin was 7.6 [ 21 ]. Our previous research showed that J-6 and J-1 reached the highest efficiency of degrading purified lignin under acidic condition [ 13 ]. The efficiency of J-6 and J-1 in degrading lignin in biomass under different pH conditions is pictured in Fig. 1 . The raw materials used in the experiment were three kinds of biomass without steam explosion treatment, and the biodegradation time was 14 days. The results showed that when the pH was 4.0–8.0, the microbial consortia could grow and degrade lignin. When the pH was 4.0–5.0, the lignin degradation efficiency was the highest. In the subsequent experiments, pH was 4. Through one-way ANOVA, pH was not a significant factor affecting lignin degradation in biomass, which was consistent with our previous research. Under acidic conditions, the lignin degradation efficiency was higher, which may be related to the microbial community composition and enzyme activity of lignin-degrading microorganisms. According to our previous study [ 13 ], under the condition that the fungi were mainly composed of Saccharomycetales, acidic condition was more suitable for the degradation of lignin. The Saccharomycetales adapted to the lignin substrate media and may have promoted lignin degradation. To determine the effect of yeast on the activity of lignin-degrading enzymes, J-6 was treated with nystatin to inhibit yeast activity. The results indicated that yeast in the microbial consortium improved the enzyme activity of lignin-degrading enzymes and thus increased the lignin degradation efficiency. At the same time, the lignin-degrading enzyme activity has been reported to be higher under acidic conditions [ 22 ]. In addition, lignin in biomass materials might be demethylated under acidic conditions and the increase of phenolic hydroxyl content might improve the degradation efficiency of lignin [ 23 ], which also verified the experimental results of this research. Fig. 1 Effect of initial pH on lignin degradation in biomass by microbial consortia Effect of steam explosion treatment on microbial consortium degradation Steam explosion is the most commonly used biomass pretreatment technology at present. It utilizes high-temperature and high-pressure steam to handle materials and instantly release pressure, so as to realize component separation and internal structure change of materials [ 24 , 25 ]. Through researching the relationship between the internal structure of biomass and effective utilization, Asada et al. found that the pore distribution of softwood biomass could be changed by steam explosion pretreatment [ 26 ]. Silva et al. used bagasse as raw material and pretreated it with water and the experimental results showed that 12.86% of lignin and 14.89% of hemicellulose were dissolved by steam explosion treatment, while the cellulose retention efficiency was as high as 97.5% [ 27 ]. The structural changes caused by steam explosion treatment may have a beneficial effect on the lignin degradation by the microbial consortium. This research proposes a method combining steam explosion pretreatment with lignin bio-degrading treatment. The steam explosion treatment could provide better attachment and living place for microorganisms, and improve the lignin degradation efficiency by microbial consortium. This combined treatment method can also reduce the by-products produced in the pretreatment process, thereby improving the enzymatic hydrolysis efficiency in the subsequent treatment process. In this experiment, three different pressure values (1.2 MPa, 1.6 MPa and 2.0 MPa) were selected for steam explosion pretreatment of biomass. The degradation efficiency of lignin was investigated under the above three pressure conditions and the condition without steam explosion treatment. The experimental results are shown in Fig. 2 . It should be noted that 2.0 MPa treatment has high energy consumption and poor pretreatment results, which was not chosen in the subsequent experiments. Fig. 2 Lignin degradation in biomass under different treatment conditions by microbial consortia (Degradation temperature: 30 °C; Rotation speed: 180 r/min; pH: 4) The experimental results revealed that the lignin degradation efficiency of the three kinds of biomass treated by steam explosion was improved compared with that of the untreated biomass, especially under the pressure of 1.6 MPa. After 1.6 MPa treatment, the lignin degradation efficiency of eucalyptus root reached 34.36% on the 7th days by J-6 and 35.35% on the 7th days by J-1 microbial consortium treatment, which was significantly higher than that of the biomass without explosion treatment. The lignin degradation efficiency of bagasse was 37.61% after the combined treatment of steam explosion and J-1 microbial biotreatment for 7 days. The lignin degradation efficiency of corn straw processed by steam explosion and then treated by J-6 microbial community for only 7 days reached 44.24%. However, Zhang used mixed strains to degrade corn straw (without steam explosion), with the maximum lignin degradation efficiency reaching 29.1% [ 28 ]. Zhen et al. also reported that steam explosion pretreatment can improve the microbial degradation efficiency of lignocellulose biomass [ 29 ]. The results of our experiment were also consistent with their conclusion. Therefore, steam explosion can provide better conditions for subsequent microbial degradation by changing the material structure, and its mechanism will be discussed in the follow-up part. In addition, after the steam explosion treatment in this study, small amount of degradation of the hemicellulose and lignin occurred and cellulose remains essentially the same as before treatment which was consistent with the results of the reference [ 30 ]. Taking 1.6 MPa treatment as an example, the degradation efficiency of lignin in biomass after explosion was only 7.72% for eucalyptus roots, 5.31% for bagasse, and 8.83% for corn straw. However, after the combined treatment, the lignin degradation efficiency of the corn straw could reach more than 40%. According to other literature, the lignin degradation efficiency of corn straw optimized by steam explosion treatment can reach about 24% [ 31 ], which was much lower than that of our biological method. It was further confirmed that the steam explosion combined with microbial consortium degradation could greatly improve the lignin degradation efficiency. Effect of degradation time on microbial consortium degradation The effect of degradation time on microbial consortium degradation is also illustrated in Fig. 2 . The biomass after steam explosion reached higher degradation efficiency within 7 days after adding two microbial consortia. The degradation efficiency of bagasse and eucalyptus root reached more than 30% in 7 days, and that of corn straw reached more than 40%. This demonstrated the advantages of biological method in the treatment of straw biomass. After 14 days, the degradation efficiency increased slightly with the extension of degradation time. Among them, the highest lignin degradation efficiency of corn straw biomass reached 44.24%. The optimal degradation efficiency was reached in the biomass under 1.6 MPa treatment. According to other literatures, Zhang et al. used the mixture of Trichoderma koningiopsis and Phanerochaete chrysosporium to degrade corn straw and after 11 days of treatment, the lignin degradation efficiency was 28.87% [ 32 ]. Zhu et al. chose Trametes versicolor as the experimental strain for lignin degradation. After 21 days of culture, the lignin degradation efficiency of straw reached 34.8% [ 33 ]. In contrast, the microbial consortium used in this experiment showed strong degradation ability to lignin, and the degradation time was greatly shortened, providing a novel microbial resource and research direction for the degradation of lignin. The lignin-degrading ability of the microbial consortium was related to the activity of lignin-degrading enzymes. Our previous studies showed that both J-1 and J-6 can produce three different lignin-degrading enzymes: laccase, LiP (Linin Peroxidase) and MnP (Manganese Peroxidase) [ 13 ]. In summary, the main defects of the current microbial pretreatment methods for lignocellulose materials are slow reaction speed and difficulty in industrial application. The combination of biological method and physical–chemical method in this research may provide a better idea. Steam explosion and microbial consortium degradation can produce a coupling effect. The combined treatment method achieved high lignin degradation efficiency for three different types of biomass raw materials of eucalyptus root, bagasse and corn straw. In the following content, the results of morphological analysis, enzymatic hydrolysis performance and microbial consortium composition and structure will be discussed in detail to explain the corresponding conclusions. Selective degradation of lignin by microbial consortia The microbial consortia used in this research was obtained from decayed wooden antiques. Cellulose, hemicellulose and other compounds in wooden relics that are easy to be used by microorganisms are largely decomposed during long-term burial, thus forming a lignin rich environment (lignin content > 60%), which can create good living conditions for lignin degrading microorganisms [ 34 ]. The microbial consortia were mainly screened according to the ability to produce lignin-degrading enzymes. Therefore, they have high lignin degradation capacity. For better application in biomass degradation, the ability to selectively degrade lignin is required to avoid the degradation of other effective components in lignocellulose. The selective degradation ability of the microbial consortia was investigated, and the SVs were calculated. The results are presented in Table 1 . Table 1 Lignin degradation SV values of different biomass by microbial consortia SV Bagasse Corn straw Eucalyptus root Without steam explosion treatment (J-6) 2.12 3.02 2.07 1.2 MPa steam explosion treatment(J-6) 2.75 3.23 2.39 1.6 MPa steam explosion treatment(J-6) 2.68 3.59 2.35 Without steam explosion treatment ((J-1) 2.33 1.89 2.46 1.2 MPa steam explosion treatment(J-1) 2.56 2.11 2.77 1.6 MPa steam explosion treatment(J-1) 2.85 2.33 2.84 The SV can be calculated by the ratio of lignin degradation efficiency to degradation efficiency of cellulose. The higher the value, the better the selective degradation ability of microorganisms to lignin is. The SV of screened DM-1 microbial consortium was 2.78 [ 15 ]. In this research, the biomass materials with high lignin degradation efficiency were tested. It was found that the SV of various biomass after 1.6 MPa steam explosion treatment was significantly higher than this value. The SV of J-6 was up to 3.59. And the SV of J-1 was up to 2.85. The selective degradation ability of J-6 was relatively strong. Meanwhile, the composition and structure of the biomass materials were also different, which also might lead to differences in the selective degradation ability of the microorganisms. The stable structure of eucalyptus root may be the reason for its weaker selective degradation ability compared with other kinds of biomass materials. The experimental results showed that the microbial consortia could selectively degrade lignin in the presence of cellulose. Simultaneously, the composition of microbial consortium might be closely related to the selective degradation ability, which needs to be further explored. Effect of microbial consortium treatment on enzymatic hydrolysis The literature reported that the pretreatment of lignocellulose materials by lignin-degrading microorganisms can significantly improve the saccharification efficiency of cellulase hydrolysis [ 35 ]. By the treatment of lignin-degrading microorganisms, the original structure of lignocellulose can be broken and the content of lignin can be reduced, thereby increasing the cellulase action area [ 36 ]. The saccharification process can be promoted due to the weakened inhibition of cellulose activity. In this research, the biomass treated by microbial consortium was enzymatically hydrolyzed, and the result was compared with the untreated biomass. The change of saccharification efficiency is shown in Fig. 3 . The results illustrated that the saccharification efficiency after biological treatment was significantly improved and positively correlated with the degradation efficiency of lignin. Lignin is considered a major obstacle to the enzymatic hydrolysis of cellulose, as it is closely associated with cellulose microfibrils [ 37 ] and microbial consortium can enhance the enzymatic digestion of lignocellulosic biomass by changing the chemical composition through degradation of lignin. Although some previous studies have shown that the phenols produced by pretreatment before lignin degradation usually inhibit enzymatic hydrolysis [ 24 , 36 ], no significant inhibition was found in the treatment by microbial consortium. Compared with wood, corn straw has lower lignin content and looser structure, which is more suitable for biological pretreatment. Without steam explosion treatment, only biological treatment can achieve better results, and the total saccharification efficiency of direct biological pretreatment can also reach 40.76%. Fig. 3 Saccharification efficiency of biomass under different treatment conditions Furthermore, the results showed that the cellulase hydrolysis efficiency after steam explosion treatment was also significantly improved. The structure of lignocellulose was destroyed due to its own expansion during the steam explosion process [ 38 ]. Thus, the pretreatment of eucalyptus biomass by the combined treatment can gain better pretreatment effect. Moreover, the treatment time of the microbial consortium in this research was only 7 days, which was less than the biological pretreatment time reported in many literatures. For example, Keller et al. reported the treatment time of the corn straw pretreated by C. stercoreus was 29 days and the saccharification efficiency reached 36% when corn straw was hydrolyzed under the condition of enzyme dosage of 60 FPU/g [ 39 ]. At the same time, the treatment time of the wood biomass with biological pretreatment reported in the literature was always very long, even up to 120 days [ 40 ]. In this research, the enzymatic hydrolysis efficiency of eucalyptus root after 7 days of microbial consortium pretreatment was significantly improved, which can reflect the advantages of microbial consortium treatment in this research. Morphological analysis The experimental results of lignin degradation efficiency and the effect of microbial degradation pretreatment on biomass saccharification efficiency can confirm that both steam explosion treatment and microbial treatment may affect the structure of biomass, and the structures and morphologies of different biomass are different. In this experiment, SEM was used to obtain the morphology of three kinds of biomass (Fig. 4 ) and to observe the surface structure of different materials. Then the effects of various pretreatment methods on the morphology were evaluated. Further, we analyzed the mechanism of steam explosion combined with microbial treatment to achieve efficient lignin degradation and to improve the enzymatic hydrolysis efficiency. The three kinds of original biomass all presented a relatively smooth surface structure, but the density of the material surface was different. The density of eucalyptus root was higher, and the structure was more stable. The density of corn straw material was relatively lower. The surface of the biomass after steam explosion treatment was loose, and the fiber structure was destroyed, resulting in some pores especially that the eucalyptus root displayed significant structural damage. According to literature [ 41 ], lignin-degrading microorganisms easily adhere and grow in the cracks and pores of biomass materials, and further secrete enzymes to destroy biomass structure and produce macrospores. Therefore, steam explosion pretreatment was conducive to the microbial consortium growth in the biomass materials and contributed to the degradation of lignin in biomass. SEM results also demonstrated that the structure of eucalyptus root was partially damaged and perforated after microbial consortium treatment. The bagasse had large cracks after microbial consortium treatment. Moreover, fragmentation appeared on the surface of corn straw after microbial consortium treatment. From the morphological analysis, it could be inferred that the destruction degree of the biomass materials may show a certain correlation with the lignin degradation efficiency. Morphological changes are also related to subsequent enzymatic hydrolysis efficiency and the increase of sample porosity and the destruction of structure could increase the accessibility of enzymatic hydrolysis [ 26 , 37 ], which verified our previous research results. Fig. 4 SEM morphology of biomass under different treatment conditions. ( A : Eucalyptus root; B : Eucalyptus root after steam explosion treatment; C : Eucalyptus root after steam explosion- J-6 combined treatment; D : Eucalyptus root after steam explosion- J-1 combined treatment; E : bagasse; F : bagasse after steam explosion treatment; G : bagasse after steam explosion-J-6 combined treatment; H : bagasse after steam explosion-J-1 combined treatment; I : corn straw; J : corn straw after steam explosion treatment; K : corn straw after steam explosion- J-6 combined treatment; L : corn straw after steam explosion- J-1 combined treatment) In addition, researchers have found that the crystallinity of cellulose has a certain impact on the efficiency of enzymatic hydrolysis [ 42 , 43 ]. In this research, the crystallinity of cellulose decreased after steam explosion, and the average reduction of the three kinds of biomass was 10.3%. However, the crystallinity of cellulose was not changed significantly after the pretreatment by the lignin degradation microorganisms. Therefore, the microbial consortium showed strong selective degradation ability. The biodegradation process by the microbial consortium was mainly aimed at the degradation of lignin in biomass materials, and had no obvious effect on the cellulose crystallization zone. Therefore, if the pretreatment method of steam explosion combined with microbial consortium biodegradation was adopted, the crystallinity of cellulose can be reduced and the lignin can be removed. Meanwhile, the porosity of raw biomass materials can be improved to increase the effective contact area between cellulase and cellulose, and the amount of inhibitor in the enzymatic hydrolysis system can be reduced. Microbial consortium structure analysis The above experiments confirmed that the J-6 microbial consortium had strong adaptability to different environments and high degradation efficiency of lignin in biomass. Other research showed that the main performance of the strong adaptability would be that the community structure of the microbial consortium can change with environmental conditions [ 44 ]. Through the analysis of microbial genomic sequencing, we studied the variation of community structure and dominant bacteria in the process of biomass degradation and discussed the mechanism of lignin degradation by microbial consortium to provide data reference for the future efficient utilization of microbial synergistic degradation of lignin. Microbial community composition Genomic sequencing analyses indicated that there was no significant difference in the fungal community composition of the microbial consortia of different systems, which was nearly the same as that of the original microbial consortia. Fungi of the microbial consortium were mainly composed of Saccharomycetales. This also confirmed the conclusion of 3.1.2. In addition, according to our previous research [ 13 ], the lignin degradation enzyme activities of J-1 and J-6 were closer, which may be related to the similar fungal composition of J-1 and J-6. Fungi play an important role in lignin degradation system. For example, Saccharomycetales in the microbial consortium improved the enzyme activity of lignin-degrading enzymes and thus increased the lignin degradation efficiency [ 13 , 45 ]. The stability of fungal community may have an important relationship with the maintenance of the lignin degradation ability of different systems. However, the bacterial composition of J-6 and J-1 microbial consortium was changed significantly in different systems (Fig. 5 ), and was different from the original J-6 microbial consortium. The proportion of dominant bacteria shinella sp. in original J-6 and Serratia sp. in original J-1 decreased significantly. In addition, in different biomass systems, the bacterial composition was also obviously different. J-6 in eucalyptus root system was mainly composed of Staphylococcaceae (26.32%), Ralstonia (22.12%) and Pseudomonadaceae (18.55%). In the bagasse system, J-6 was mainly composed of Geobacter (48.25%) and Ralstonia (7.81%). In the corn straw system, J-6 was mainly composed of Pseudomonadaceae (30.04%) and Ralstonia (20.53%). J-1 in Eucalyptus root system was mainly composed of 24.65% Ralstonia and 36.33% Pseudomonadaceae. In bagasse system, J-1 was mainly composed of 32.05% Ralstonia and 21.24% Pseudomonadaceae. In the corn straw system, J-1 was mainly composed of 90.15% Alcaligenaceae. Fig. 5 Bacterial community composition of different biomass degradation systems Additionally, there are certain similarities in bacterial composition among different biomass degradation systems. For example, Ralstonia and Pseudomonadaceae are abundant in eucalyptus root system. The bagasse biomass also contains a large number of these two kinds of bacteria, indicating that Ralstonia and Pseudomonadaceae can play an important role in the biomass system for lignin degradation. These two kinds of bacteria are also present in the biomass degradation microbial consortia in other literatures, such as the corn straw degradation microbial consortium GF-20 [ 46 ] and the wheat straw degradation microbial consortium [ 47 ]. According to other literature [ 48 ], Pseudomonadaceae is very common in the degradation process of lignocellulose in nature, and has strong adaptability to biomass degradation systems. The composition of community structure should be closely related to degradation behavior of microbial consortium. There were great differences in bacterial composition between the original J-6 and J-1 microbial consortium, and there were also obvious differences in community structure between J-6 and J-1 in biomass degradation system. Although both of them showed high lignin degradation effect in the biomass degradation system, there were some differences in the efficiency of selective degradation of lignin. The selective degradation ability of J-6 was stronger than that of J-1, and the main difference in the composition of the community structure between J-6 and J-1 was that the proportion of Alcaligenaceae in J-1 was much higher. According to other literature [ 5 , 45 ], Alcaligenaceae is very common in the degradation process of lignocellulose in nature, and has strong adaptability to biomass degradation systems. At the same time, it could cooperate with other microorganisms such as cellulose degrading bacterium Clostridium sp. to promote the decomposition of biomass [ 5 ]. This again showed that the composition of community structure should be closely related to degradation behavior of microbial consortium. In addition, the composition of bacteria in the microbial consortium was also related to the types of the lignin degradation products. Our previous study showed that the lignin degradation process of J-6 was more complete and the product structure was simpler than that of J-1 [ 13 ]. Diversity analysis of community structure Bray Curtis, weighted UniFrac and unweighted UniFrac distances was calculated by the OTU abundance information of samples to evaluate the differences in microbial community structure. Bray Curtis distance is the most commonly used indicator to reflect the differences between communities, and only the abundance information of species is considered. The unweighted UniFrac distance is the distance between samples calculated based on the phylogenetic relationship of species. The weighted UniFrac distance is the distance between samples obtained by combining the abundance information of OTU and the phylogenetic relationship. Unweighted UniFrac distance is more sensitive to rare species, while Bray Curtis and weighted UniFrac distance are more sensitive to species with higher abundance. As beta diversity distance, weighted UniFrac distance, unweighted UniFrac distance and Bray Curtis distance are indicators to measure the dissimilarity coefficient between the two samples. The smaller the value, the smaller the difference between the two samples in species diversity [ 49 , 50 ]. Figure 6 a shows the heat maps of the above three distances between different samples. The results showed that in the J-6 degradation system, there were great differences between different biomass, especially the Bray Curtis distance and the weighted UniFrac distance, which considered the species abundance information were far away, indicating that there were great differences in species abundance in different biomass. But the unweighted UniFrac distance of bagasse and Eucalyptus root was closer than that of bagasse and corn straw indicating that in the phylogenetic relationship of species, the genetic distance between the microbial consortia of sugarcane system and eucalyptus root system was closer. The lignin degradation of eucalyptus root degradation system and bagasse degradation system were also relatively similar according to previous studies. Also, the J-1 degradation system was similar with the J-6 degradation system, which verified that the bagasse degradation system was close to the eucalyptus root degradation system. Fig. 6 Bacterial community diversity of different biomass degradation systems Alpha diversity index is an analysis of species diversity in a sample, including two factors: richness and evenness of species composition in the sample. It usually uses ObservedOTU, Shannon and Faith’s Phylogenetic Diversity to evaluate the species diversity of a sample. The higher the index, the more complex the diversity of the sample is [ 51 ]. In this study, Shannon index was used to evaluate species diversity. The result is shown in Fig. 6 b. The bacterial community diversity of J-6 was still higher than J-1, showing no difference with the original microbial consortium [ 13 ]."
} | 10,349 |
29021534 | PMC5636887 | pmc | 3,204 | {
"abstract": "Streptococcus pneumoniae becomes competent for genetic transformation when exposed to an autoinducer peptide known as competence-stimulating peptide (CSP). This peptide was originally described as a quorum-sensing signal, enabling individual cells to regulate competence in response to population density. However, recent studies suggest that CSP may instead serve as a probe for sensing environmental cues, such as antibiotic stress or environmental diffusion. Here, we show that competence induction can be simultaneously influenced by cell density, external pH, antibiotic-induced stress, and cell history. Our experimental data is explained by a mathematical model where the environment and cell history modify the rate at which cells produce or sense CSP. Taken together, model and experiments indicate that autoinducer concentration can function as an indicator of cell density across environmental conditions, while also incorporating information on environmental factors or cell history, allowing cells to integrate cues such as antibiotic stress into their quorum-sensing response. This unifying perspective may apply to other debated quorum-sensing systems.",
"introduction": "Introduction Bacteria release small diffusible molecules in the extracellular medium known as autoinducers. These molecules induce the expression of particular functions including biofilm formation, luminescence and genetic competence as well as their own production 1 , 2 . The most prevalent functional interpretation of the production and response to autoinducers is known as quorum sensing (QS). According to this view, the concentration of autoinducer molecules is a proxy for cell density, allowing bacteria to regulate the expression of those phenotypes that are only beneficial when expressed by many cells 1 , 2 . However, it is likely that the concentration of autoinducer molecules does not only reflect cell density, but also environmental factors, such as the diffusivity of the medium. In fact, alternative hypotheses state that bacteria release autoinducers to sense these environmental factors rather than to monitor cell density. A well-known hypothesis proposed by Redfield is that the function of autoinducers is diffusion sensing, allowing cells to avoid the secretion of costly molecules under conditions where they would quickly diffuse away 3 . Other potential roles suggested for autoinducer production are sensing local cell density together with diffusion 4 , the positioning of other cells during biofilm formation 5 , and temporal variations in pH 6 . We study pneumococcal competence, a system classically used as an example of QS. However, whether competence is actually controlled by QS has been recently debated. Competence is a transient physiological state that is developed by Streptococcus pneumoniae , as well as other bacteria. Upon entry into competence, pneumococci upregulate the expression of genes required for uptake of exogenous DNA as well as bacteriocins and various genes involved in stress response 7 . In S . pneumoniae , competence is regulated by an autoinducer molecule known as the competence-stimulating peptide (CSP) in a two-component regulatory system formed by the histidine kinase ComD and the response regulator ComE 8 , 9 (Fig. 1 ). Despite the detailed understanding of the regulatory network of competence induction, little is known about why competence is controlled by an autoinducer peptide like CSP. CSP has been classically thought to be a QS signal 10 , whose function could be to monitor the density of potential DNA donors 11 . However, competence can be induced in response to environmental factors like pH, oxygen, phosphate, and antibiotic stress 12 – 15 . Based on this evidence and the finding that competence initiates at the same time in pneumococcal cultures inoculated at different initial densities, it was suggested that CSP acts as a timing device that allows cells to mount a timed response to environmental stress independently of cell density 16 . Since then, this hypothesis has established in the field as an alternative to the QS view of competence 15 , 17 – 19 . Recently, Prudhomme et al. renamed the timing device mechanism as a growth-time dependent mechanism and proposed that a subpopulation of competent cells that originates stochastically spreads the competent state to the rest of the population by cell–cell contact 20 . Another alternative to QS is that pneumococcal competence is an instance of diffusion sensing. This was suggested by Yang et al. based on the observation that the quorum for competence induction is not fixed but decreases with more restrictive diffusion 21 . Fig. 1 Network of competence regulation in S. pneumoniae . ComC (C) binds the membrane protein complex ComAB, and it is processed and exported as CSP to the extracellular space. CSP binds to the histidine kinase ComD, which is located in the membrane as a dimer. Upon CSP binding, ComD autophosphorylates and transfers the phosphate group to the response regulator ComE 9 , 24 . The phosphorylated form of ComE (ComE~P) dimerizes and activates transcription of comAB, comCDE , and comX by binding to their promoters 8 , 9 . Unphosphorylated ComE can also bind these promoters, repressing their transcription 24 , 68 . Synthesis of the alternative sigma factor ComX directs transcription of genes required for genetic transformation as well as other functions 7 , 25 . Two key features of this network are the presence of a positive feedback loop (since increasing CSP detection leads to increasing CSP production) and of non-linearity (since ComE~P interacts with the gene promoters as a dimer) \n Here, we study the regulation of pneumococcal competence by cell density and two environmental factors, antibiotic stress and pH. Using batch-culture experiments, single-cell analyses, and mathematical modeling we show that these factors simultaneously regulate competence development because they all affect the CSP concentration: cell density sets the amount of cells producing CSP, whereas the environment and cell history modify the rate at which individual cells produce or sense CSP. Since there is density regulation and we show that CSP is exported extracellularly, we advocate to keep using the term “quorum sensing” in the context of pneumococcal competence but with a broader meaning to acknowledge that in addition to cell density, multiple factors are integrated into this QS response.",
"discussion": "Discussion Recently, the view that bacteria use autoinducers as QS signals has been debated since autoinducer concentration can change in response to the environment. Here, we show experimentally that cell density, pH and antibiotic stress simultaneously regulate competence development in S . pneumoniae (Figs. 2 – 5 ), a system classically framed in the paradigm of QS. Using a mathematical model, we show that this occurs because pH and antibiotics modify the rates at which single cells produce and sense CSP and therefore the strength of the positive feedback loop coupling CSP detection to CSP production (Figs. 4 and 5 ). This environmental dependency does not override regulation by cell density but rather modulates the relationship between the number of cells and the CSP concentration. A fundamental aspect to the dependency on cell density is that cells share CSP with others. Importantly, here we provide evidence both in liquid culture (Supplementary Fig. 1 ) and through single-cell observations (Fig. 3 ) that CSP is exported to the extracellular space. Finally, we show that competence development is history-dependent since past environmental conditions can modify the status of the machinery to produce and respond to CSP determining whether competence switches on or not (Fig. 6 ). Hysteresis in the competence response might be especially important in the natural niche of the pneumococcus, the human nasopharynx. In particular it is consistent with the observation that there is constitutive upregulation of competence in pneumococcal biofilms during nasopharyngeal colonization 36 . In this context, once competence is triggered for the first time, cells would be primed to rapidly initiate another round of competence. Why is competence controlled by CSP? CSP does not act as a timing device in our encapsulated strain since competence develops in a cell-density-dependent manner without the necessity of cell–cell contact 16 , 17 , 20 (Figs. 2 and 3 ). Regarding the hypothesis that CSP is a probe to test diffusion 21 , our results suggest that focusing on diffusion alone oversimplifies the information and functionality that cells can gather through CSP production. We hypothesize that by using an autoinducer peptide, bacteria can coordinate the development of competence and in particular the expression of fratricins and bacteriocins, which are under the control of the competent state. These proteins can lyse or inhibit the growth of surrounding cells that are not competent, increasing the efficiency of genetic transformation and mediating competition with other bacteria 37 – 40 . By coordinating competence expression via CSP, an isogenic bacterial population can increase the total concentration of secreted fratricins and bacteriocins in times where population density is high, which likely translates into a higher amount of lysed cells and therefore potential DNA donors. Importantly, coordinating competence expression can also prevent the killing of clonal siblings since immunity to these proteins comes with the competent state. Note however that the extent to which cells synchronize competence development may vary depending on the strain, genotype and growth conditions. In particular, our results suggest that unencapsulated strains may synchronize less, which would explain the difference between the findings reported by Prudhomme et al. 20 and our study. Decreased synchronization may result from cells exporting less CSP to the extracellular space and keeping more to themselves. In fact, in other species like Streptococcus thermophilus where competence is controlled by ComS, a peptide that rapidly gets imported back into the cell, the rate of competence development decreases with the inoculation density 41 as observed for the unencapsulated pneumococcal strains. Finally, note that S . pneumoniae grows primarily in biofilms where there is heterogeneity in the physiological status and microenvironment that different cells experience. This can certainly influence the degree of synchronization in competence initiation across a population especially in the light of our findings that both current and past environmental conditions affect the competence regulatory network. Indeed, recent work in Streptococcus mutans showed heterogeneous competence activation of cells within biofilms and upon different environmental pH ranges 42 , 43 . While studies of well-mixed cultures give insight into the response mechanism shared by all cells in a population, additional work is needed in the future to study how CSP production and detection by individual cells is shaped by their spatial context and history and to unravel how individual responses translate into patterns of population synchronization across different genotypes and strains. What is the relevance of the information carried by CSP? Alkaline pH and antibiotic stress can induce competence by increasing the rate at which single cells produce and sense CSP. We expect this to be a general mechanism by which sources of stress that are alleviated through competence induce this state (e.g., mobile genetic elements as hypothesized by Croucher et al. 44 ). Upregulating competence in the presence of antibiotics can increase survival by activating the expression of stress response genes 7 , 19 , facilitating repair of damaged DNA and mediating acquisition of resistance 19 , 45 . Our findings suggest that strategies to prevent competence development in response to antibiotics can focus on counteracting the effect of antibiotics on the rate at which cells produce or sense CSP. Regarding the benefits of upregulating competence with alkaline pH, these are less clear and could be an example of a non-adaptive response resulting from the inherent biochemical properties of ComAB and possibly ComD. Importantly, CSP can integrate additional environmental cues like oxygen availability through the CiaRH two-component system, which represses comC post-transcriptionally and is required for virulence expression and host colonization 12 , 46 . In fact, CiaRH is key for the regulation of competence by multiple environmental signals in other streptococci like S . mutans \n 47 . Our findings support the view that functional hypotheses stressing individual factors like diffusion or population density underplay the complexity of information integrated by QS systems 4 , 48 – 52 . Although the term “quorum sensing” overemphasizes the role of population density, we advocate for keeping it due to its widespread use and the fact that density will modify autoinducer concentration in any autoinducer production system. Crucially, QS should be used in a broad sense acknowledging that bacteria integrate past and current environmental factors in addition to population density into their QS responses. This view might be very useful for other autoinducer production systems like competence in Vibrio cholerae , where the synthesis of the autoinducer, CAI-1, depends on the intracellular levels of cAMP–CRP and therefore might incorporate information on the metabolic status of the cell 53 , 54 . Also in other systems, clear links between signal production, quorum threshold and environmental conditions have been shown to affect QS 55 – 59 . Given that many biotic and abiotic factors can modify autoinducer concentrations 60 , future work should aim to study the relevance of such factors in the natural context where bacteria secrete autoinducers. Such work is crucial to assess whether upregulating QS in response to a particular factor provides a benefit for bacteria or is merely a result of the biochemical properties of the QS regulatory network. An interesting possibility is that, as in other biological systems 61 , bacteria could perform collective sensing of the environment through social interactions. In this context, by secreting autoinducers cells could share individual estimates of environmental conditions (e.g., antibiotic stress) for which upregulating QS is beneficial. Then, autoinducer secretion would provide a way to get a more reliable estimate of the environmental conditions by allowing a population to pool estimates made by individual cells. Importantly, such a role for autoinducer secretion would explain the dependency of QS on both cell density and the environment."
} | 3,703 |
37681105 | PMC10480136 | pmc | 3,205 | {
"abstract": "Explaining the foundation of cognitive abilities in the processing of information by neural systems has been in the beginnings of biophysics since McCulloch and Pitts pioneered work within the biophysics school of Chicago in the 1940s and the interdisciplinary cybernetists meetings in the 1950s, inseparable from the birth of computing and artificial intelligence. Since then, neural network models have traveled a long path, both in the biophysical and the computational disciplines. The biological, neurocomputational aspect reached its representational maturity with the Distributed Associative Memory models developed in the early 70 s. In this framework, the inclusion of signal-signal multiplication within neural network models was presented as a necessity to provide matrix associative memories with adaptive, context-sensitive associations, while greatly enhancing their computational capabilities. In this review, we show that several of the most successful neural network models use a form of multiplication of signals. We present several classical models that included such kind of multiplication and the computational reasons for the inclusion. We then turn to the different proposals about the possible biophysical implementation that underlies these computational capacities. We pinpoint the important ideas put forth by different theoretical models using a tensor product representation and show that these models endow memories with the context-dependent adaptive capabilities necessary to allow for evolutionary adaptation to changing and unpredictable environments. Finally, we show how the powerful abilities of contemporary computationally deep-learning models, inspired in neural networks, also depend on multiplications, and discuss some perspectives in view of the wide panorama unfolded. The computational relevance of multiplications calls for the development of new avenues of research that uncover the mechanisms our nervous system uses to achieve multiplication.",
"conclusion": "Conclusions and perspectives Multiplication greatly enhances the capabilities of neural models, and it is included in several classical models of cognitive processing like tensor matrix memories (Mizraji 1989 ), tensor models of symbolic processing (Smolensky 1990 ), or pattern recognition machines (like functional-link nets, Pao 1989 ). It is also used in state-of-the-art Artificial Intelligence tools, like Long Short-Term Memories (LSTM, Hochreiter and Schmidhuber 1997 ) and Transformers (Vaswani et al 2017 ). Newer models based on Structured Space Models (Dao et al. 2022 ) also include forms of multiplication. The growing importance of this basic operation opens two questions. On one side, multiplications allow for the flexible modulation of input–output mappings, which in turn permits neural networks to implement gratuitous mappings, i.e., computations that are not dependent on the details of the input (much in the way an allosteric modulator allows for the regulation of a metabolic pathway by chemical compounds unrelated to the pathway, as proposed by Monod 1967 ). Is the presence of gratuitous interactions an inescapable design feature of intelligent systems? If the answer is positive, in this sense classical multiplicative neural networks, but also state-of-the art intelligent machines realize the postulate that Ross Ashby proposed as necessary for a system to present adaptive behaviors (Ashby 1956 , 1960 ; Mizraji and Lin 2011 ). There is an opportunity then, to understand theoretically what is required for this type of intelligent computation. Multiplication will likely be part of the necessary ingredients of this understanding. This leads to the other question. What are the concrete material bases for multiplying signals in the nervous system? Most simple expositions of synaptic integration start with an additive, linear summation model, not different from the usual connectionist information processing unit (Kandel 2001 ; Rumelhart, Hinton and McClelland 1986). It is clear that dendritic trees, shunting inhibition, des-inhibition, and nonlinear receptor dynamics drastically modify this simplistic picture. What precise combination of these and other ingredients are actually used by different parts of the nervous system? An interdisciplinary effort starting with computational models and ending at the molecular level to explain these aspects is needed to unravel the secrets that synapses and circuitry hide and what it takes to be intelligent.",
"introduction": "Introduction Neural network models with the ability to process signals multiplicatively are a stage of neurocomputational network theory that began to develop in the 1970s. These multiplicative models were a sequel to the remarkable associative memory matrix models developed primarily in the early 1970s. These memory matrix models sought to explain the reliability of data storage in the face of partial deterioration of neural support, a fact long established by clinical neurology and by experimentation in animal models. Matrix memory models were stimulated in the late 1960s by various suggestions, notably Gabor ( 1968 ), regarding the possibility that neural systems could support distributed data recording and storage, mathematically (not physically) analogous to the holograms of optics. Several authors independently contributed to the development of these matrix models, especially Anderson ( 1972 ) and Kohonen ( 1972 ). But it was soon realized that along with their remarkable properties and their explanatory power, these matrix models had severe problems. In particular, they were not apt to branch their associations when the same key pattern was contextualized by different patterns. For example, when faced with the image of a dog, these memories had theoretical limits for associating that image with the different names that this animal has in different languages (e.g., the image of the dog associated with the contexts “English language” or “Spanish language” should be able to generate two divergent responses: “dog” and “perro” respectively). As a way of solving this problem and not losing the mathematical potential of matrix representations, since the mid-1970s, in particular due to the contributions of Poggio ( 1975 ) and Kohonen ( 1977 ), multiplicative models have been introduced. Varieties of these multiplicative models were developed and had an important expansion in the following years. In this review, we cover more than fifty years of approaches that call for the inclusion of multiplicative processes in neural networks. In particular, we show how multiplication is used in these computational models. We also present the available evidence for how multiplication is carried on in biological networks. We review this domain of research including contributions that use networks with multiplicative processing from various angles. This is not intended to be an exhaustive review. We will focus on topics that we consider relevant for modeling cognitive functions and neuromimetic systems. In the followign section, we will outline the nature of distributed memory models and their limitations. After that, we will analyze the theoretical and experimental arguments that have been developed to explain the appearance of multiplicative events in neural interactions. Then, we will show the various tensor representation formats proposed during the 1980s and their current developments. In the following section, we will show how these multiplicative processes are influencing powerful computational algorithms that are at the roots of modern artificial intelligence. Finally, we will present a perspective on the role of multiplicative models in neural computation."
} | 1,925 |
37744813 | PMC10515406 | pmc | 3,206 | {
"abstract": "Cyanobacteria have been studied in recent decades to\ninvestigate\nthe principle mechanisms of plant-type oxygenic photosynthesis, as\nthey are the inventors of this process, and their cultivation and\nresearch is much easier compared to land plants. Nevertheless, many\ncyanobacterial strains possess the capacity for at least some forms\nof heterotrophic growth. This review demonstrates that cyanobacteria\nare much more than simple photoautotrophs, and their flexibility toward\ndifferent environmental conditions has been underestimated in the\npast. It summarizes the strains capable of heterotrophy known by date\nstructured by their phylogeny and lists the possible substrates for\nheterotrophy for each of them in a table in the Supporting Information.\nThe conditions are discussed in detail that cause heterotrophic growth\nfor each strain in order to allow for reproduction of the results.\nThe review explains the importance of this knowledge for the use of\nnew methods of cyanobacterial cultivation, which may be advantageous\nunder certain conditions. It seeks to stimulate other researchers\nto identify new strains capable of heterotrophy that have not been\nknown so far.",
"conclusion": "3 Conclusion and Future Research From\nthe very beginning, cyanobacteria have mainly been presented\nas the inventors of plant oxygenic photosynthesis, which, however,\naccounts for only part of their complex metabolism. While even facultatively\nheterotrophic cyanobacteria show the highest growth rates under photoautotrophic\nconditions, the various forms of heterotrophy in this kingdom are\nmore widespread than previously thought. In recent years, more and\nmore strains have been either intentionally identified 23 , 64 , 74 , 93 , 120 , 122 or identified\nby chance 96 as potential heterotrophs. The vast majority of cyanobacteria strains is still considered\nto be strictly photoautotrophic 23 with\nthe caveat that most of these strains have not been tested on all\npossible substrates. Therefore, we need to examine other potential\nsubstrates (fatty acids and amino acids) that have been rather neglected\nin the past. For example, Rippka et al. 23 tested only glucose, fructose, ribose, sucrose, and in some cases\nalso glycerol for the ability to undergo heterotrophy. Although it\nis unlikely that strains that cannot grow photoheterotrophically have\nthe potential for dark chemoheterotrophic growth, it is possible that\nsome of these strains may use the substrates tested by Rippka et al. 23 or other compounds as growth-promoting substrates\nfor photomixotrophy. There may also be strains classified as strictly\nphotolithoautotrophic as no suitable conditions for heterotrophy have\nbeen identified so far. In some cases, classic substrates such as\nfructose can stimulate growth; however, exceptionally high concentrations\nnot existing in nature must be offered as shown in Anabaena sp. PCC 7120 96 and Synechocystis sp. PCC 6803 gtr – , 74 because the substrate would not enter the cell\nat naturally occurring external concentrations. Since no specific\ntransporter has been identified so far, we have to assume that a transporter\nfor a related substance (another sugar?) will import that molecule\nif its external concentration is high enough. Regarding the fact that\nphotosynthesis and respiration are intimately linked in cyanobacteria, 137 , 138 the question arises whether the facultative heterotrophy of some\ncyanobacteria strains is a relic of heterotrophic predators before\nthe invention of oxygenic photosynthesis and was lost in other strains\nor whether the facultative heterotrophy was formed de novo as a secondary acquisition in some strains. To answer this question,\nknowledge about facultative (particularly photo) heterotrophy in anoxygenic\nphototrophs such as purple and green bacteria needs to be increased.\nRecently, Matheus Carnevali et al. 139 analyzed\nthe genome sequences of melainabacteria and sericytochromatia, which\nare considered to be the organisms most closely related to cyanobacteria,\nalthough they themselves do not carry out photosynthesis. 140 According to Matheus Carnevali et al. 139 the ancestors of cyanobacteria, melainabacteria,\nand seritochromatia are probably anaerobes living on fermentation\nand possessing various hydrogenases. Cyanobacteria therefore became\naerobic after splitting off from melainabacteria and seritochromatia.\nAlthough the capacity for growth on external organic substances may\nhave originated independently in various strains, we think that increasing\nthe knowledge of heterotrophy among cyanobacteria will give new insights\ninto evolutionary processes. Cultivation under heterotrophic\nconditions without oxygenic photosynthesis\ncan also promote research on critical cell parts (e.g., parts of photosystems),\nwhere otherwise erasing the gene information would be lethal. Heterotrophic\ncultivation can also allow growth when light must be avoided or is\nunavailable for long periods (e.g., transportation in space). Our\npicture of cyanobacteria needs to change from pure photoautotrophs\nto multitrophs capable of adapting to appropriate metabolic modes,\ndepending on the current environmental conditions.",
"introduction": "1 Introduction Cyanobacteria have evolved\nto a photolithoautotrophic growth mode 1 , 2 because they\nuse light as an energy source (phototrophic), the inorganic\nwater molecule as an electron source (lithotrophic) for NADPH production,\nand carbon dioxide, that has only one carbon atom, as the sole carbon\nsource (autotrophic) (the different types of trophies and their possible\ncombinations are explained in Table 1 ). This implies that autotrophic organisms must metabolically\nform all covalent bonds between carbon atoms. Unlike other phototrophic\nprokaryotes such as purple bacteria and green sulfur bacteria, which\nperform an anoxygenic mode of photosynthesis and have only one photosystem,\ncyanobacteria are defined as prokaryotes capable of oxygenic photosynthesis\nand possess two photosystems (I, for a review about photosystem I,\nplease see ref ( 3 ),\nand II, for a review about photosystem II, please see ref ( 4 )). Oxygenic photosynthesis\nrequires two distinct photosystems to ensure sufficient reduction\npotential for water splitting (removal of electrons from the very\nelectronegative oxygen and the release of protons and molecular dioxygen)\non one hand and the production of enough ATP needed for carbon fixation\nin the Calvin cycle on the other. In eukaryotes such as algae and\nland plants, only oxygenic photosynthesis takes place, which consists\nof two photosystems. This fact is consistent with the endosymbiotic\ntheory 5 that the chloroplasts of algae\nand plants descended from cyanobacteria that invaded eukaryotic cells,\nthe progenitor of modern algae and plants. Table 1 Various Combinations of Trophies of\nNaturally Occurring Organisms Growth mode Energy source Electron\nsource Carbon source photolithoautotrophic light inorganic compounds (e.g.,\nH 2 , Fe 2+ , NH 3 , H 2 S, H 2 O) molecules\nconsisting of\nonly one carbon atom (e.g., CO 2 , HCOOH, CH 3 OH,\nCH 4 ) photolithoheterotrophic light inorganic compounds (e.g.,\nH 2 , Fe 2+ , NH 3 , H 2 S, H 2 O) organic\nmolecules consisting\nof at least two carbon atoms (e.g., glucose, fructose, sucrose, glycerol,\n...) chemolithoautotrophic inorganic compounds (e.g.,\nH 2 , Fe 2+ , NH 3 , H 2 S) inorganic compounds (e.g.,\nH 2 , Fe 2+ , NH 3 , H 2 S) molecules consisting of\nonly one carbon atom (e.g., CO 2 , HCOOH, CH 3 OH,\nCH 4 ) chemolithoheterotrophic inorganic compounds (e.g.,\nH 2 , Fe 2+ , NH 3 , H 2 S) inorganic compounds (e.g.,\nH 2 , Fe 2+ , NH 3 , H 2 S) organic molecules consisting\nof at least two carbon atoms (e.g., glucose, fructose, sucrose, glycerol,\n...) photoorganoheterotrophic light organic molecules consisting\nof at least two carbon atoms (e.g., glucose, fructose, sucrose, glycerol,\n...) organic molecules\nconsisting\nof at least two carbon atoms (e.g., glucose, fructose, sucrose, glycerol,\n...) chemoorganoheterotrophic organic molecules consisting\nof at least two carbon atoms (e.g., glucose, fructose, sucrose, glycerol,\n...) organic molecules\nconsisting\nof at least two carbon atoms (e.g., glucose, fructose, sucrose, glycerol,\n...) organic molecules\nconsisting\nof at least two carbon atoms (e.g., glucose, fructose, sucrose, glycerol,\n...) photomixotrophic light inorganic and organic molecules molecules consisting of\none carbon atom and molecules consisting of at least two carbon atoms Due to their production of free molecular oxygen,\ncyanobacteria\nwere among the first evolutionary organisms to protect themselves\nagainst radical oxygen species (ROS). As a result, cyanobacteria evolved\naerobic respiration in addition to their oxygenic photosynthesis.\nThe oxygen and organic molecules that have been formed in the light\ncan be utilized for respiration in the dark. In contrast to eukaryotic\nalgae and embryophytes, where these two processes are spatially separated\nin chloroplasts and mitochondria, they take place in the same compartment\nin cyanobacteria. 6 While all cyanobacteria,\neukaryotic algae, and land plants can\nsurvive in periods of darkness by aerobic respiration, few strains\nof cyanobacteria 7 − 9 and eukaryotic algae 10 − 12 but no plants are able\nto grow in prolonged darkness, where carbon dioxide can no longer\nbe fixed since NADPH and ATP production only occurs during the light\nreaction. In the dark, organic molecules are used as a source of carbon,\nenergy, and electrons, and this growth mode is called chemoorganoheterotrophic\ngrowth (chemotrophic because energy is obtained through chemical reactions,\norganotrophic because the electrons are derived from organic molecules,\nand heterotrophic because organic substrates normally used for growth\nconsist of at least two carbon atoms, as illustrated in Table 1 ). In the following sections,\nthe terms photolithoautotrophic and chemorganoheterotrophic are abbreviated\nto photoautotrophic and chemoheterotrophic. Normally, cyanobacteria\ncapable of chemoheterotrophic growth can use only one or two distinct\norganic molecules as a carbon source, and the substrates vary between\ncyanobacterial strains. The most prevalent substrates are sugars such\nas glucose, fructose, and sucrose and the alcohol glycerol. 7 − 9 , 13 − 23 This is consistent with the fact that the genomes of many strains\nof cyanobacteria contain genes that are either responsible for the\nuptake of sugars or for their metabolism. 24 Import through the outer membrane is more likely to occur through\nnonspecific porins, 25 while for transport\nthrough the cytoplasmic membrane, homologues of the glucose transporter\nGlc in Synechocystis sp. PCC 6803 26 and the fructose transporter FrtRABC in Anabaena\nvariabilis ATCC 29413 27 are widely\ndistributed. 28 Figure 1 summarizes various substrates that are imported\nand metabolized by cyanobacteria. Figure 1 Overview of uptake and metabolization\nof diverse organic molecules\nby a cyanobacterial cell. GlpK, glycerol kinase; XylA, xylose isomerase;\nXylB, xylulokinase; Glk, glucokinase; CscA/InvA, invertase; CscK,\nfructokinase (from E . coli ). The\n“?” at the glycerol transporter implies that this transporter\nand the corresponding gene in Cyanothece sp. ATCC\n51142 have not been identified yet. The “?” after the\n(native cyanobacterial) fructokinase indicates that no gene within\nthe genome of either Anabaena sp. ATCC 29413 or Nostoc sp. ATCC 29133 has been annotated as fructokinase\nso far. 24 Synechocystis sp. PCC 6803 is\ncapable of a particular\nform of chemoheterotrophy, as it requires 5 min of daily illumination\nfor glucose-dependent dark growth. Nevertheless, this growth mode\ncan be considered as a kind of chemoheterotrophic growth since it\nis strictly dependent on the presence of glucose. This modified growth\nmode is termed light-activated heterotrophic growth (LAHG). 29 A similar case is observed for Synechococcus sp. PCC 7002. This strain can grow in dim light (40 μW cm –2 ) in the presence of 55 mM glucose but not in total\ndarkness at the same glucose concentration. 30 Since a light intensity of 40 μW cm –2 itself\ndoes not induce (photoautotrophic) growth, it may be true (light-activated)\nheterotrophic growth. Some strains of cyanobacteria are strictly\nlight dependent but\ncan also grow in the absence of photosystem II. If no water is split\ndue to the lack of photosystem II, organic molecules serve as the\nelectron source. Since photosystem I is still active, light can be\nconsidered as the energy source; however, the ATP originating from\nphotosystem I is not sufficient for carbon dioxide fixation, and an\norganic electron source is additionally used for carbon assimilation.\nTherefore, this growth mode is termed photoorganoheterotrophic growth\nor, more briefly, photoheterotrophic growth. 8 , 9 , 23 In cyanobacteria, photoheterotrophic conditions\narise naturally through spontaneous mutations in genes encoding photosystem\nII subunits, but these mutations can also be engineered. 31 − 33 Alternatively, photoheterotrophy can be induced by the herbicide\n3-(3,4-dichlorophenyl)-1,1-dimethylurea (DCMU), which blocks electron\ntransfer from photosystem II to the quinone pool. 34 − 37 Some strains of cyanobacteria\nare unable to grow heterotrophically,\nso they cannot grow in the absence of light or either of their two\nphotosystems; however, their photoautotrophic growth rate is further\nincreased by the addition of organic molecules to their growth medium.\nThis mode is called photomixotrophic growth. Although photomixotrophic\ngrowth is not a true form of heterotrophy, we will discuss it in this\nreview because this growth mode is based on at least a partial growth\ndependence on organic molecules. In all of the above cases,\nthe appropriate substrate must be imported\ninto the cell (for a review of the transport of organic substances\nacross the cytoplamic membrane, please see ref ( 38 )); however, strict photoautotrophy\nis not always caused by a lack of transport alone, as the entering\nmolecule has to be metabolized in some way for the synthesis of ATP\nand NAD(P)H without accumulation of any toxic (by-)products. 39 In this review, we summarize and analyze\nall available data on\nthe different forms of heterotrophic (photomixotrophic, photoheterotrophic,\nor chemoheterotrophic) growth in cyanobacteria. In the past decades,\nthere has been a strong focus on autotrophy, while little is known\nabout facultative heterotrophy, as this topic has been rather neglected.\nThe aim of this review is to expand knowledge about the possibility\nof heterotrophic cultivation of cyanobacterial strains that were previously\nconsidered strictly photoautotrophic in order to stimulate new research\ntopics with cultivation forms that were previously not thought possible.\nOverall, the picture of cyanobacteria will change from purely photosynthetic\norganisms to highly flexible organisms that can adapt their metabolism\nto new circumstances when environmental conditions change."
} | 3,744 |
30784401 | null | s2 | 3,207 | {
"abstract": "Metabolic engineers seek to produce high-value products from inexpensive starting materials in a sustainable and cost-effective manner by using microbes as cellular factories. However, pathway development and optimization can be arduous tasks, complicated by pathway bottlenecks and toxicity. Pathway organization has emerged as a potential solution to these issues, and the use of protein- or DNA-based scaffolds has successfully increased the production of several industrially relevant compounds. These efforts demonstrate the usefulness of pathway colocalization and spatial organization for metabolic engineering applications. In particular, scaffolding within an enclosed, subcellular compartment shows great promise for pathway optimization, offering benefits such as increased local enzyme and substrate concentrations, sequestration of toxic or volatile intermediates, and alleviation of cofactor and resource competition with the host. Here, we describe the 1,2-propanediol utilization (Pdu) bacterial microcompartment (MCP) as an enclosed scaffold for pathway sequestration and organization. We first describe methods for controlling Pdu MCP formation, expressing and encapsulating heterologous cargo, and tuning cargo loading levels. We further describe assays for analyzing Pdu MCPs and assessing encapsulation levels. These methods will enable the repurposing of MCPs as tunable nanobioreactors for heterologous pathway encapsulation."
} | 362 |
22229696 | null | s2 | 3,210 | {
"abstract": "Novel protein chimeras constituted of \"silk\" and a silica-binding peptide (KSLSRHDHIHHH) were synthesized by genetic or chemical approaches and their influence on silica-silk based chimera composite formation evaluated. Genetic chimeras were constructed from 6 or 15 repeats of the 32 amino acid consensus sequence of Nephila clavipes spider silk ([SGRGGLGGQG AGAAAAAGGA GQGGYGGLGSQG](n)) to which one silica binding peptide was fused at the N terminus. For the chemical chimera, 28 equiv of the silica binding peptide were chemically coupled to natural Bombyx mori silk after modification of tyrosine groups by diazonium coupling and EDC/NHS activation of all acid groups. After silica formation under mild, biomaterial-compatible conditions, the effect of peptide addition on the properties of the silk and chimeric silk-silica composite materials was explored. The composite biomaterial properties could be related to the extent of silica condensation and to the higher number of silica binding sites in the chemical chimera as compared with the genetically derived variants. In all cases, the structure of the protein/chimera in solution dictated the type of composite structure that formed with the silica deposition process having little effect on the secondary structural composition of the silk-based materials. Similarly to our study of genetic silk based chimeras containing the R5 peptide (SSKKSGSYSGSKGSKRRIL), the role of the chimeras (genetic and chemical) used in the present study resided more in aggregation and scaffolding than in the catalysis of condensation. The variables of peptide identity, silk construct (number of consensus repeats or silk source), and approach to synthesis (genetic or chemical) can be used to \"tune\" the properties of the composite materials formed and is a general approach that can be used to prepare a range of materials for biomedical and sensor-based applications."
} | 478 |
22355675 | PMC3240979 | pmc | 3,212 | {
"abstract": "Apoptotic cell death has been implicated in coral bleaching but the molecules involved and\n the mechanisms by which apoptosis is regulated are only now being identified. In contrast\n the mechanisms underlying apoptosis in higher animals are relatively well understood. To\n better understand the response of corals to thermal stress, the expression of coral homologs\n of six key regulators of apoptosis was studied in Acropora aspera under conditions\n simulating those of a mass bleaching event. Significant changes in expression were detected\n between the daily minimum and maximum temperatures. Maximum daily temperatures from as low\n as 3°C below the bleaching threshold resulted in significant changes in both pro- and\n anti-apoptotic gene expression. The results suggest that the control of apoptosis is highly\n complex in this eukaryote-eukaryote endosymbiosis and that apoptotic cell death cascades\n potentially play key roles tipping the cellular life/death balance during environmental\n stress prior to the onset of coral bleaching.",
"discussion": "Discussion The apoptotic network regulates cellular responses to stress and death signals and\n maintains the balance between life and death 11 12 13 14 15 . Both biotic\n (for example starvation and pathogens) and abiotic stimuli (for example exposure to\n ultraviolet light and heat stress) initiate this network 12 13 16 and during\n thermal stress events on coral reefs, the coral animal is exposed to all of these stress\n signals over long time periods prior to the onset of the observable bleaching stress\n response. However how the coral organism regulates the cellular response to these signals\n and controls cell death prior to, and during, the bleaching response is largely unknown and\n we are yet to understand the broader significance of early stress impacts to the coral\n organism or the reef community. Tchenov et al. 41 recently proposed a model of coral cell death during\n bleaching, in which they suggest that some populations of cells within the host are\n irreversibly damaged by dinoflagellate generated ROS, while other cells suppress the cell\n death cascade, survive the stress event, and are the basis for tissue regeneration. Under\n the Tchenov model, an up-regulation of genes encoding both pro- and anti-apoptotic proteins\n would be expected during bleaching, and this was found in the current study. However we also\n find these changes occurring at temperatures lower than the bleaching threshold and prior to\n the onset of the bleaching response. Here we present substantial evidence to support the\n Tchenov model of cellular control of death and recovery from coral bleaching events and\n further suggest that early abiotic stressors, occurring prior to the onset of the bleaching\n phenomena also strongly influence the impact of thermal stress events to the coral. In fact\n the complexity of apoptotic gene expression in thermal stress responses mirrors that of\n higher organisms and is indicative of the myriad of stress signals being concurrently\n interpreted. Upstream apoptotic regulators in the Bcl-2 family have been shown in higher organisms to\n function as a cellular life/death switch and to be key sentinels of cell death 19 which are up-regulated in response to cell death signals 17 .\n This is the first study of lower organisms to characterize the presence of a Bcl-2 family\n member with BH and nuclear transporter domains consistent with the upstream apoptosis\n regulator, Bok. In mammalian cells, where the function of Bok has been determined, an\n upregulation in expression is independent of anti-apoptotic Bcl-2 family members and\n responds to nuclear damage 17 . In the present study we find a significant\n up-regulation of coral Bok-like expression coinciding with the peak thermal impacts to the\n coral host, potentially reflecting thermal damage to the nucleus occurring prior to the\n onset of coral bleaching. However this is the first study to demonstrate a significant down\n regulation in Bok gene expression, which was observed coinciding with peak light/temperature\n interactions 3°C prior to and during the bleaching threshold. Further investigation of this\n protein is warranted to determine if it is also a sentinel of nuclear damage and to\n determine the biological significance of a down regulation of this protein. Unlike upstream regulators, other Bcl-2 family members however interact with each other to\n control damage to the cell's organelles. Pro-apoptotic Bax and Bak, interact with\n anti-apoptotic Bcl-2 (and Bcl-x) to form heterodimeric proteins and an excess of Bax or Bak\n within the cytoplasm results in the pro-apoptotic targeting and permeabilisation of both the\n mitochondria and the endoplasmic reticulum membranes 20 21 . In the present\n study the largest fold gene expression changes were observed for the anti-apoptotic Bcl-2.\n Bcl-2 is widely linked to anti-oxidant function in cells and cells expressing Bcl-2 are\n considered to be resistant to oxidant stress. A 7.1 fold up-regulation in Bcl-2 expression\n was first observed from 3°C below the bleaching threshold and expression remained\n significantly up-regulated (through to a 28.5 fold up-regulation) until bleaching occurred.\n This large up-regulation indicates a strong anti-apoptotic and anti-oxidant response from\n the host prior to the onset of coral bleaching. Importantly, we also find the peak Bcl-2\n expression clearly evident during the highest daily cumulative light/temperature stress,\n lower at the 6 pm temperature stress events (low light but the longest daily thermal stress\n exposure) and lowest at the 8 am time point following the overnight recovery period. An\n interaction between light and temperature stress is a necessary determinant of coral\n bleaching, in that without the cumulative impact of light and temperature on the\n dinoflagellate photosystems the coral has a higher thermal threshold before mortality\n occurs 39 . However apoptotic cell death is clearly evident within\n gastrodermal cells (those holding the endosymbiotic dinoflagellate) 3°C prior to the onset\n of bleaching 7 . Given that the sustained upregulation of Bcl-2 prior to\n bleaching is also accompanied by significant up-regulation of both pro-apoptotic Bax and\n Bak, the anti-oxidant and anti-apoptotic function of Bcl-2 is likely to vary across the\n organism, have cell and tissue specific regulation and these factors maybe important in\n determining the capacity of the organism as a whole to control cell death, mortality and\n ultimately cellular regeneration. The fine control of cell death in multi-cellular organisms is further regulated through\n downstream inhibitors. Bax inhibitor-1 (BI-1) is highly conserved and its inhibitory\n (anti-apoptotic) role has been demonstrated in both plant and animal species 42 43 . The protein is located within the endoplasmic reticulum membrane where it\n prevents targeting of the pro-apoptotic Bcl-2 family proteins, confers protection from ER\n stress, and prevents the generation of ROS within the cell 44 . In the present\n study we find a significant and sustained up regulation of BI-1 occurring throughout the\n early thermal stress responses and during bleaching onset. While ROS generation due to ER\n stress has been proposed as one of the underlying mechanisms in coral bleaching 4 45 the prevention of ER damage in some cells maybe a key mechanism underlying\n the capacity for coral recovery and regeneration. Over expression of BI-1 is linked to\n increased cell adhesion through a direct interaction of the protein with actin 46 . Therefore further investigation of the role of BI-1 is warranted to determine\n if this is a mechanism for maintaining cell and tissue integrity of cells not damaged during\n coral stress and bleaching. However unlike the anti-apoptotic Bcl-2 and BI-1, the apoptosis\n inhibitor BIR (survivin) is significantly down regulated only during the onset of coral\n bleaching. Survivin functions by suppressing both intrinsic and extrinsic apoptotic pathways\n and blocking caspase-9 function (for review see 22 ). Previous studies in\n higher organisms have linked low expression of BIR with an increased sensitivity to\n pro–apoptotic stress signals and to cell death execution 47 48 , an\n up-regulation however is considered critical for prevention of the cell death cycle 47 . In the current study there is an up-regulation in the expression of this gene\n prior to exposure to the bleaching threshold, but a clear down-regulation at the highest\n temperature exposure and the onset of coral bleaching. If survivin function is analogous to\n that of higher organisms, a down regulation during bleaching onset provides evidence that\n stress-affected cells have in fact entered an irreversible terminal state and there is a\n tipping of the cellular balance from survival to death. Here we show that the molecular machinery governing cell death in the tightly coupled\n coral-dinoflagellate symbiosis is highly complex and responds significantly to subtle, daily\n changes in the environment, and at temperatures that are generally considered to have little\n impact on holobiont function. The kinetics of apoptotic gene expression during thermal\n stress responses highlights the need to better understand cellular processes occurring prior\n to and during bleaching events, and the need to determine the mechanisms which underlie\n coral mortality and recovery in response to environmental stress. Based on the current\n understanding of coral apoptosis we provide a basic conceptual model of cell death function\n within the coral symbiotic system during thermal stress ( Figure 4 ) and\n demonstrate that prior to bleaching there is an initiation of the cell death cascade and a\n potential tipping of the cellular balance from survival to death. However one major constraint in understanding this complex cell death system is a lack of\n information on the cell biology, cellular differentiation, tissue function and the cellular\n recovery processes in coral. It is likely that the regulation of apoptosis found in the\n current study represents a homogenization of responses across distinct cell and tissue types\n within a complex, colonial, habitat under which there is significant biotic and abiotic\n variation 49 . All of these factors likely have significant impacts on the\n capacity of the coral to regenerate tissues and recover from bleaching events."
} | 2,789 |
29048525 | PMC5737686 | pmc | 3,213 | {
"abstract": "Abstract Scleractinian corals are the foundation species of the coral-reef ecosystem. Their calcium carbonate skeletons form extensive structures that are home to millions of species, making coral reefs one of the most diverse ecosystems of our planet. However, our understanding of how reef-building corals have evolved the ability to calcify and become the ecosystem builders they are today is hampered by uncertain relationships within their subclass Hexacorallia. Corallimorpharians have been proposed to originate from a complex scleractinian ancestor that lost the ability to calcify in response to increasing ocean acidification, suggesting the possibility for corals to lose and gain the ability to calcify in response to increasing ocean acidification. Here, we employed a phylogenomic approach using whole-genome data from six hexacorallian species to resolve the evolutionary relationship between reef-building corals and their noncalcifying relatives. Phylogenetic analysis based on 1,421 single-copy orthologs, as well as gene presence/absence and synteny information, converged on the same topologies, showing strong support for scleractinian monophyly and a corallimorpharian sister clade. Our broad phylogenomic approach using sequence-based and sequence-independent analyses provides unambiguous evidence for the monophyly of scleractinian corals and the rejection of corallimorpharians as descendants of a complex coral ancestor.",
"introduction": "Introduction Scleractinian corals form the large bicarbonate structures that constitute the foundation of the coral reef ecosystem. Their evolutionary history traces back to the early Triassic around 245 Ma, a time of high diversification within this order when multiple coral clades appear in the fossil record for the first time ( Simpson etal. 2011 ; Park etal. 2012 ). However, in contrast to fossil evidence, molecular analyses of the evolutionary history of Scleractinia remain inconclusive, with some extant deep-water families suggesting the evolutionary roots of this order to potentially date as far back as approximately 425 Ma ( Stolarski etal. 2011 ). Phylogenetic analyses of extant corals using different genetic markers and methods clearly identify two distinct clades, termed the “Complex” and the “Robust” clades ( Romano and Palumbi 1996 ; Romano and Cairns 2000 ; Chen etal. 2002 ; Le Goff-Vitry etal. 2004 ; Medina etal. 2006 ; Fukami etal. 2008 ; Stolarski etal. 2011 ; Kitahara etal. 2014 ; Lin etal. 2014 ; ). However, the precise phylogenetic relationships of scleractinian corals within the Hexacorallia has further been elusive due to contradicting phylogenies derived from phylogenetic analyses using different molecular markers and evolutionary models ( Medina etal. 2006 ; Kitahara etal. 2014 ). Yet, understanding the evolutionary history of these organisms is imperative if we aim to understand their evolutionary history and resilience in light of climate change. Of special interest is the phylogenetic relationship of scleractinian corals to the order Corallimorpharia ( Kitahara etal. 2014 ). Corallimorpharia, colloquially termed “false corals”, are closely related to Scleractinia ( Dunn 1982 ), but unlike reef-building corals, they do not possess a calcareous skeleton. Based on phylogenetic analyses of complete mitochondrial genomes it was proposed that Corallimorpharia evolved from a complex coral ancestor approximately 110–132 Ma ( fig. 1 ), suggesting the loss of the calcium carbonate skeleton in response to increased oceanic CO 2 prevalent during this time period ( Medina etal. 2006 ). This finding provided strong support for the so-called “naked coral” hypothesis, which was first coined by Stanley and Fautin ( Stanley and Fautin 2001 ) and proposes that corals have lost and reevolved skeletons repeatedly during the middle Triassic. The importance of this hypothesis lays in its implications as a potential mechanism for corals to escape extinction from aragonite skeletal dissolution during periods of increased CO 2 levels such as those projected by future climate change scenarios.\n Fig . 1. —Phylogenetic relationships according to the “naked coral” hypothesis. (SL) marks the putative evolutionary origin of Corallimorpharia from a complex coral ancestor through “skeleton loss.” Despite the strong support for this hypothesis provided by mitochondrial genome-based phylogenetic analyses ( Chen etal. 1995 ; Medina etal. 2006 ), other studies using different markers and techniques reported contradicting results ( Daly etal. 2003 ; Brugler and France 2007 ; Fukami etal. 2008 ; Aranda etal. 2012 ). Recently, various studies ( Stolarski etal. 2011 ; Kayal etal. 2013 ; Kitahara etal. 2014 ; Lin etal. 2014 , 2016 ) have addressed this discrepancy in detail by analyzing mitochondrial nucleotide and amino-acid-based alignments using different evolutionary models, showing that certain models allowed the recovery of Scleractinia as monophyletic group even when using mitochondrial markers. Although these newer studies kept challenging the idea of a potential complex coral origin of Corallimorpharia, the dearth of genome sequences did not allow rigorous testing of the hypothesis using nonsequence-based phylogenomic approaches. To overcome these limitations, we used a multipronged approach including phylogenetic analyses of nuclear-encoded genes as well as genome-wide presence/absence information and synteny conservation ( supplementary fig. S1 , Supplementary Material online) of genomes from six hexacorallian species including the Actiniaria Nematostella vectensis ( Putnam etal. 2007 ) and Aiptasia pallida ( Baumgarten etal. 2015 ), the Corallimorpharia Amplexidiscus fenestrafer and Discosoma sp. ( Wang etal. 2017 ) as well as the complex scleractinian coral Acropora digitifera ( Shinzato etal. 2011 ) and the robust coral Stylophora pistillata .",
"discussion": "Results and Discussion Nuclear-Encoded Genes Support Scleractinian Monophyly Phylogenetic analyses of nuclear encoded genes were performed on a set of single-copy orthologs on both the amino acid (aa) and nucleotide (nt) level. To this end, we first identified a suitable set of single-copy orthologs using OrthoMCL ( Li etal. 2003 ) and the genome-encoded protein sets of N. vectensis , A. pallida , A. fenestrafer , Discosoma sp., A. digitifera , and S. pistillata as well as the hydrozoan Hydra magnipapillata which served as an outgroup in our analyses. Using this approach, we identified 1,421 single-copy orthologs that were used to select suitable subsets of orthologs for aa and nt-based phylogenetic analyses using Maximum Likelihood (ML) as well as Bayesian Inference (BI)-based methods in combination with different evolutionary models. For the aa based analysis, we concatenated aligned sequences from 1,021 selected single copy orthologs that passed the filtering process (see material and methods), providing a supermatrix with 179,381 aa positions for phylogenetic reconstruction. Given the ongoing discussions with regard to the most appropriate substitution model for the inference of deep evolutionary splits ( Pisani etal. 2015 ), we performed ML and BI-based phylogenetic analyses using different evolutionary substitution models (see also Materials and Methods). ML trees were constructed with RAxML using the LG + I+G + F ( supplementary fig. S2 A , Supplementary Material online) as determined by ProtTest ( Darriba etal. 2011 ). BI analyses were performed with MrBayes using the LG + I+G +F ( supplementary fig. S2 B , Supplementary Material online) as well as Phylobayes using the CAT-LG ( supplementary fig. S3 A , Supplementary Material online), CAT-GTR ( supplementary fig. S3 B , Supplementary Material online), and CAT-Poisson models ( supplementary fig. S3 C , Supplementary Material online). The topologies of both the ML as well as the BI-based trees were identical and consistently showed maximum support for all nodes, independent of the substitution model used ( fig. 2 A ). All trees recovered Scleractinia as monophyletic group with Corallimorpharia as its sister group. We also generated independent trees for each of the orthologous genes and obtained a consensus tree (majority rule) ( supplementary fig. S4 , Supplementary Material online). Interestingly, 96% of the single ortholog trees supported the monophyly of Corallimorpharia, but only 62% of the trees supported the monophyly of Scleractinia.\n Fig . 2. —( A ) Phylogenetic analyses based on amino acid sequences of single-copy genes. ( B ) Phylogenetic analysis based on nucleotide sequences of coding single-copy genes. Values on the nodes correspond to branch support from RAxML, MrBayes, and PhyloBayes. Node support values depicted here were identical across all evolutionary models used. Phylogenetic analyses of nucleotide sequence alignments followed the same general procedure. The nt super matrix was based on 1,255 selected single-copy orthologs that passed filtering, providing a total of 668,245 positions. Similar to the aa analysis, we used ML and BI-based methods and tested different evolutionary models in order to account for potential biases due to long-branch effects (see Material and Methods). Based on initial model tests using JModelTest2, we selected the GTR + I+G as the best model for further ML analyses with RAxML ( supplementary fig. S5 A , Supplementary Material online). BI-based phylogenetic reconstructions were performed with MrBayes using the GTR + I+G model ( supplementary fig. S5 B , Supplementary Material online) and Phylobayes to infer phylogenetic trees using the CAT-Poisson ( supplementary fig. S6 A , Supplementary Material online), and CAT-GTR model ( supplementary fig. S6 B , Supplementary Material online). All nucleotide-based analyses ( fig. 2 B ) recovered the same topologies as the aa-based tree with maximum bootstrap and posterior probability support for all nodes independent of the method or model used. Sequence-Independent Analyses Support Scleractinian Monophyly The use of sequence data to resolve phylogenetic relationships can produce controversial results when analyzing deep evolutionary splits due to biases such as long-branch attraction or the choice of evolutionary models to determine evolutionary relationships, even in the presence of whole-genome information ( Philippe etal. 2011 ). To address this problem, we also performed sequence-independent phylogenetic analyses using information on the presence/absence of ortholog groups as well as a synteny conservation. Based on our ortholog analysis, we identified 21,718 ortholog groups that were used to generate a distance matrix in R using the binary method ( Borg and Groenen 2005 ). Based on this matrix we reconstructed putative phylogenetic relationships through hierarchical clustering of calculated distances across the six Hexacorallia genomes and our outgroup H. magnipapillata. To provide further statistical support for the nodes, we calculated the approximately unbiased probability and bootstrap probability using pvclust and 1,000 bootstraps. The recovered topology was identical to the phylogenetic analyses using nuclear-encoded single-copy orthologs and showed very high statistical support for all branches ( fig. 3 ). Scleractinian monophyly was also recovered with strong statistical support when analyzing the presence/absence information using the binary F81-like model implemented in MrBayes, after applying an ascertainment bias correction by removing genes present in fewer than two species as suggested by Pisani ( Pisani etal. 2015 ) ( supplementary fig. S7 , Supplementary Material online). Additionally, we also recovered the same tree topology using phylogenetic reconstruction based on the number of paralogs identified for the different ortholog/paralog groups ( supplementary fig. S8 , Supplementary Material online).\n Fig . 3. —Phylogenetic analyses based on gene presence/absence. The node supports are AU (Approximately Unbiased) P values and BP (Bootstrap Probability) values. The distance was calculated using binary methods and hierarchical cluster analysis with 1,000 bootstraps using the average Hcluster method. In order to derive further sequence-independent evidence we analyzed synteny conservation across the six genomes using the phylogenetic reconstruction tool PhyChro. Due to the phylogenetic distance and the dearth of conserved synteny groups in the H. magnipapillata genome, we omitted the outgroup from this analysis. Briefly, we first identified synteny blocks using SynChro ( Drillon etal. 2014 ) with different block stringency parameters (Delta 1–6). In the following step, we analyzed the different outputs using PhyChro to identify “incompatible” block adjacencies between all genome pairs and from them deduce “pairs of incompatible groups of genomes” (PIGGs). If a block order (A, B) is shared by genome G1 and at least one other genome while block order (A, C) is shared by G2 and at least one other genome, we got a PIGG. From its set of PIGGs, PhyChro reconstructs the most parsimonious tree (where each PIGG can be “explained” by a unique rearrangement). A common tree was found for Delta 2–5 (other deltas 1, 6 show only partial reconstructions), showing strong support for Scleractinia as a monophyletic group ( fig. 4 ). The Scleractinia group ( S. pistillata and A. digitifera ) was, as expected, the weakest group in this analysis. It was also the last group identified in the recursive tree reconstruction, after the Actiniaria and Corallimorpharia. However, we identified only one PIGG that contradicted scleractinian monophyly, which is illustrated by the number of contradicting PIGGs ( fig. 4 ) and the number of PIGGs supporting the branch of the Scleractinia group. It should be noted that this specific PIGG also contradicted corallimorpharian monophyly, which casts general doubt on its validity. Consequently, we conclude that scleractinian monophyly is the most parsimonious explanation for our results.\n Fig . 4. —Phylogenetic analyses based on synteny conservation. The unrooted tree (represented rooted as in figures 1 and 2 for more clarity) represents the topology obtained by PhyChro for Delta 2–5. The values on the branches correspond to the total number of PIGGs (pairs of incompatible groups of genomes) contradicting the branch/the total number of PIGGs supporting the branch obtained for Delta 2–5. Corallimorpharia Are Not “Naked Corals” Our phylogenetic analyses were based on a subset of stringently selected, high-confidence nuclear encoded single-copy orthologs that provided the longest alignment used to date to validate the phylogenetic relationship of scleractinian corals and corallimorpharians ( Kitahara etal. 2014 ; Lin etal. 2016 ). The results obtained are consistent across all analyses independent of the sequence type, method or model used and recover Scleractinia as monophyletic group with Corallimorpharia as a close sister clade with maximum support for each node. Although the limited number of species used in our phylogenetic analyses is of potential concern, it should be noted that our results are in line with a recent study based on 15 Hexacorallia transcriptomes, including three Corallimorpharia species ( Lin etal. 2016 ). More importantly, though, we show that our sequence-based results are strongly supported by two separate sequence-independent analyses that produced identical tree topologies with very strong support. Although our synteny-based analysis recovered Scleractinia as the weakest group, we did not find a single incompatibility allowing for a different grouping of these species and no alternative tree topologies were recovered. The use of presence/absence and synteny information has previously been employed to provide additional support for sequence-based phylogenies in other organisms ( Tian etal. 2012 ; Ryan etal. 2013 ; Pisani etal. 2015 ), but represents a novelty in the field of coral research due to the dearth of genomic data, although this is expected to change ( Voolstra etal. 2015 ). Similar to sequence-based phylogenetic reconstruction methods these analyses are not entirely free of biases and potential errors ( Pisani etal. 2015 ). However, the use of two sequence-independent approaches and two genomes for each of the orders analyzed provides additional confidence and support for our results. Although all phylogenetic reconstruction methods are subject to biases and errors, we are confident that our whole-genome approach combining sequence and nonsequence-based approaches provides the most comprehensive study of the “naked coral” hypothesis to date. Although each analysis on its own might be associated with method-inherent biases, the consistent outcome in their sum provides unambiguous evidence for the monophyly of extent scleractinian corals and the rejection of Corallimorpharia as “naked corals.” Our findings therefore show that corallimorpharians did not evolve from a complex coral ancestor but rather from a common ancestor of complex and robust corals. Consequently Corallimorpharia do not qualify as proof of the “naked coral” hypothesis, and it remains to be shown if scleractinian corals can indeed lose and regain the ability to calcify over geological timescales. Experimental approaches on selected coral species have shown that reef-building corals can indeed lose the ability to calcify under extreme conditions ( Fine and Tchernov 2007 ) and recover; however, it remains to be shown if these responses observed in short-term experiments allow coral species to survive for evolutionary relevant periods. Although corallimorpharians do not appear to be the paragon of coral survival in light of increasing ocean acidification, they still represent their closest living, noncalcifying relatives to date, making them the best candidates for future studies aiming at understanding the evolution of corals and their traits, in particular calcification."
} | 4,503 |
33336520 | PMC11468029 | pmc | 3,214 | {
"abstract": "Abstract The advancement of technology has a profound and far‐reaching impact on the society, now penetrating all areas of life. From cradle to grave, one is supported by and depends on a wide range of electronic and robotic appliances, with an ever more intimate integration of the digital and biological spheres. These advances, however, often come at the price of negatively impacting our ecosystem, with growing demands on energy, contributions to greenhouse gas emissions and environmental pollution—from production to improper disposal. Mitigating these adverse effects is among the grand challenges of the society and at the forefront of materials research. The currently emerging forms of soft, biologically inspired electronics and robotics have the unique potential of becoming not only like their natural antitypes in performance and capabilities, but also in terms of their ecological footprint. This review outlines the rise of sustainable materials in soft and bioinspired robotics, targeting all robotic components from actuators to energy storage and electronics. The state‐of‐the‐art in biobased robotics spans flourishing fields and applications ranging from microbots operating in vivo to biohybrid machines and fully biodegradable yet resilient actuators. These first steps initiate the evolution of robotics and guide them into a sustainable future.",
"conclusion": "7 Conclusion With the rise of sustainable material approaches for electronic devices, nature‐inspired forms of soft and lightweight robots emerge, which almost exclusively employ renewable, ecofriendly, and biodegradable components. The diverse soft robotic creations benefit manifold from these activities, as a careful use of resources reduces weight and promotes autonomous operation, bioresorbable materials allow in vivo deployment, or biodegradation eliminates waste issues and usage in remote areas without worries. At the forefront of materials research scientists aim to unite performance and sustainability while keeping materials and production costs low, to allow ready implementation in state‐of‐the art prototypes. Highly stretchable yet biodegradable polymers, transient sensors and transistors, and easy to recycle batteries assembled in ecofriendly fabrication lines are examples of major interdisciplinary research goals covering diverse fields. Beyond the development of individual components, the tight integration into fully autonomous robots is difficult to achieve, which requires to rethink current robot designs, actuation principles, and energy supply. This must also include concepts for their repair, disassembly, reuse, and refabrication, which all benefit from designs with reduced complexity, self‐healing, or biodegradable components. Integrating sustainability as a key metric in our future creations will not only become a must but also open a multitude of possible applications across diverse ecological niches. Renewable, low‐cost and easy to access resources finally will allow for low energy production of tech‐products and simpler recycling schemes. However, achieving this will require an extensive amount of research dedicated to closing the gap to high performance solutions or provide entirely new pathways—with robotics as the major driver toward sustainable technology development—that mitigate this challenge.",
"introduction": "1 Introduction A world affected by climate change and prevalent waste production demands environmental impact as a key metric of technological innovations. Tech disposables in particular represent a rapidly growing fraction of our garbage, accumulating in over 100 000 tons per day. [ \n \n 1 \n \n ] End‐of‐lifetime appliances such as consumer electronics are typically trashed, as the various product designs and material compositions are difficult to recycle yet are cheaply produced. Additionally, the unsustainable use of rare and often toxic materials poses an environmental threat when released into nature due to improper treatment or landfilling. [ \n \n 2 \n \n ] Easy to recycle device designs, low‐cost and renewable materials, and biodegradable or transient systems are promising approaches toward technologies with a closed life cycle and establish new opportunities across different fields from medicine and environmental monitoring to security and intelligence applications. [ \n \n 3 \n \n ] \n Current developments in robotics that focus on safe human–machine interaction, swarm robotics, and untethered autonomous operation are often inspired by nature's diversity. [ \n \n 4 \n \n ] The complexity we find in nature drives scientists from various fields to establish soft and lightweight forms of robots that aim to replicate or mimic the fluent motion of animals or their efficient energy management. [ \n \n 5 \n , \n 6 \n \n ] In future, the increased integration of such soft robots in our everyday life raises, in close analogy to consumer electronics, environmental concerns at the end of their life cycle. Again, we can learn here from nature and design our creations sustainably and mitigate the problems of currently used technology. In contrast to standardized industrial robots that are already integrated in recycling loops, bioinspired robotics will find various applications in diverse ecological niches. [ \n \n 7 \n \n ] \n Possible examples range from soft healthcare machines that support elderly people in their everyday lives to robots that first harvest produce and afterwards become compost for next season's plants. Current demonstrations with transient behavior include elastic pneumatic actuators, [ \n \n 8 \n \n ] wound patching millibots operating in vivo, [ \n \n 9 \n \n ] robot swarms for drug delivery, [ \n \n 10 \n \n ] or small grippers that are controlled by engineered muscle tissues. [ \n \n 11 \n \n ] These developments benefit from major research activities toward bioresorbable electronic devices, [ \n \n 12 \n \n ] which are mainly explored for the biomedical sector, and sustainable energy storage technology, [ \n \n 13 \n \n ] seeking to resolve environmental concerns for the increasing demand of energy for mobile appliances. Bringing those fields together will be the future challenge for autonomous robots, whether their development focuses on performance, sustainability, or both. The efficient integration of actuators, sensors, computation, and energy into a single robot will require new concepts and ecofriendly solutions, and can only be successful if material scientists, chemists, engineers, biologists, computer scientists, and roboticists alike join forces. In this review, we highlight materials, fabrication approaches, and design routes for environmentally friendly bioinspired robots and their components. We focus on sustainable device concepts, nontoxic, and low‐cost fabrication processes, and benign materials that are biodegradable or from renewable resources, to address the challenging needs of our time. The review starts with a discussion of sustainability and summarizes various approaches that enable technology with reduced environmental impact. Focusing on soft and lightweight forms of robotics, we then compare biodegradable polymers—from elastomers to bioplastics—and regrowing resources for the main robotic body. For each component of typical autonomous robots, we review environmentally friendly sensors, computation, and control tools and present promising candidates for energy harvesters and storage systems, from solar‐ and biofuel cells to batteries. Finally, we present a selection of current soft robotic demonstrations that use frugal material approaches and degrade with a positive impact on the environment."
} | 1,900 |
40113245 | PMC11974394 | pmc | 3,215 | {
"abstract": "Abstract Iron cycling including phototrophic Fe(II) oxidation has been observed in multiple permanently stratified meromictic lakes, yet less focus has been on dimictic lakes, which seasonally overturn and are vastly more common. Here, we investigated iron cycling in a dimictic lake, Großes Heiliges Meer in northwest Germany, using 16S rRNA amplicon sequencing, as well as in-situ and lab-based experiments. Bacterial community composition in the lake follows geochemical gradients and differs markedly between oxic and anoxic conditions. Potential iron-metabolizing bacteria were found mostly in anoxic conditions at 7 and 8 m depth and were comprised of taxa from the genera Chlorobium, Thiodictyon, Sideroxydans, Geobacter , and Rhodoferrax . We were able to recreate active iron cycling (1) with an ex-situ microbial community from 8 m depth and (2) with a successful microbial enrichment culture from 7 m depth. Varying the light and organic carbon availability in lab-based experiments showed that Fe(III) reduction overshadows Fe(II) oxidation leading to a cryptic iron cycle. Overall, we could demonstrate that microbial iron cycling can be a key biogeochemical process in dimictic lakes despite regular disturbance, and that complex environmental factors such as organic substrates control the balance between Fe(II) oxidation and Fe(III) reduction.",
"conclusion": "Conclusions In this study, we could show that dimictic lakes like Großes Heiliges Meer are habitats for microbial iron cycling, despite the regular disruption of their geochemistry during seasonal turnover. This further expands the refugia in which photoferrotrophs in particular can survive, demonstrating they can form active communities in holomictic lakes as well as in the rarer meromictic lakes. However, we also demonstrated that the contribution of microorganisms to Fe(II) oxidation is likely masked by a cryptic iron cycle driven by fast and efficient Fe(III)-reducing bacteria. The availability and quality of DOC is thus a critical control on the balance of Fe(II) oxidation and Fe(III) reduction in dimictic lakes; controlling whether Fe(III) (oxyhydr)oxides are stable and thus able to interact with carbon, nutrients and pollutants. Alongside enhancing our fundamental understanding of such important iron cycling habitats, we were able to enrich an iron-metabolizing culture dominated by the phototrophic Fe(II)-oxidizer Thiodictyon . This is the first time that iron cycling could be simulated in a dimictic lake using the ex-situ community and an enrichment culture.",
"introduction": "Introduction Iron cycling, consisting of Fe(II) oxidation and Fe(III) reduction, is a widespread process in stratified lakes and freshwater sediments, and plays a critical role in shaping the biogeochemistry of lacustrine environments (Berg et al. 2016 , Otte et al. 2018 , Kappler et al. 2021 ). During Fe cycling and subsequent formation and dissolution of Fe minerals, nutrients (e.g. phosphorus), carbon, and pollutants can be bound and sequestered or released back into the environment (Tipping 1981 , Eickhoff et al. 2014 , Mu et al. 2016 , Kappler et al. 2021 ). Furthermore, various microbial metabolisms link iron redox transformations with those of other key element cycles including carbon, sulfur, and nitrogen (Kappler et al. 2021 ). Both oxidative and reductive parts of the iron cycle can be facilitated abiotically and biotically. However, microbial iron cycling plays a particularly important role under microoxic and anoxic conditions where rapid abiotic oxidation by O 2 is inhibited (Bryce et al. 2018 , Kappler et al. 2021 ). Fe(II) oxidation in oxic environments is either abiotically driven by reaction with atmospheric O 2 or is microbially mediated at low pH (Kappler et al. 2021 ). In the interface of oxic to anoxic environments, Fe(II) can be directly oxidized by microaerophilic Fe(II)-oxidizing bacteria (Kucera and Wolfe 1957 , Maisch et al. 2019 ). In contrast, in anoxic, (sunlit) environments, nitrate-reducing and phototrophic bacteria like Chlorobium spp., Thiodictyon spp., and Acidovorax spp. can oxidize Fe(II) (Heising et al. 1999 , Croal et al. 2004 , Kappler et al. 2005 , Laufer et al. 2017 , Bryce et al. 2018 ). Direct microbial Fe(III) reduction occurs in anoxic environments and is performed by various genera of bacteria i.e. Geobacter spp., Shewanella spp., and Geothrix spp. (Myers and Nealson 1990 , Lovley et al. 1993 , Coates et al. 1999 ), whereas indirect microbial Fe(III) reduction occurs in sulfur-rich environments where bacteria reduce oxidized sulfur-species to form sulfides which react abiotically with Fe(III) to form FeS or/and FeS 2 (Canfield 1989 ). Both Fe(III)-reducers and Fe(II)-oxidizers have been found to be abundant and active in freshwater sediments and stratified lakes (Berg et al. 2016 , Laufer et al. 2016 , Otte et al. 2018 ). However, much of the previous work on anaerobic iron cycling in freshwater environments has focused on permanently stratified meromictic lakes due to their relevance as an analogue to Archean ocean biogeochemistry (reviewed in Bryce et al. 2018 , Kappler et al. 2021 ). Meromictic lakes do not mix completely and typically develop an anoxic bottom water body (monimolimion) that is not mixed and thus creates stable geochemical gradients (Stewart et al. 2009 ). For example, an active iron cycle with potential for rapid FeS recycling has been found in meromictic Lake Cadagno (Switzerland) which has low iron content (Berg et al. 2016 ); as well as in Lake Matano (Indonesia) and Lake La Cruz (Spain) which contain hundreds of micromolar dissolved Fe(II) in the anoxic bottom waters (Crowe et al. 2008 , Walter et al. 2014 ). A number of these lakes contain active phototrophic Fe(II)-oxidizers (Crowe et al. 2008 , Walter et al. 2014 ). True meromictic lakes are relatively rare as their existence requires specific physical and geochemical conditions e.g. the basin is particularly deep and steep-sided; or there are particularly steep salinity differences between layers that inhibit full water-column overturn even when temperatures are favourable. In contrast, most lakes are holomictic (uniform from top to bottom) where the salinity is constant throughout the depth. Variations in thermal stratification drive water density fluctuations, causing holomictic lakes to mix regularly. These may be classed as polymictic, where the lake mixes multiple times a year, monomictic (mixes once) or dimictic, which mixes twice per year usually in spring and autumn. These seasonally stratified lakes have been gaining increasing attention as hot-spots for microbial iron cycling due to their relative abundance and apparent suitability for supporting a diversity of iron-based metabolisms (Schiff et al. 2017 , Tsuji et al. 2020 , Liu et al. 2022 ). Carbon also plays a key role in Fe(II) oxidation and Fe(III)-reduction. Phototrophic Fe(II)-oxidizers can use inorganic carbon (CO 2 ) and different organic carbon molecules like acetate, lactate and others as a carbon source (Ehrenreich and Widdel 1994 , Heising et al. 1999 , Jiao et al. 2005 ). Additionally, they can use organic molecules such as acetate as an electron donor (McKinlay and Harwood 2010 ). During their growth, phototrophic Fe(II)-oxidizers can use multiple electron donors like Fe(II) and organics simultaneously or in sequential order depending on the different electron donors and different Fe(II)-oxidizers (Ehrenreich and Widdel 1994 , Melton et al. 2014 , Nikeleit et al. 2024 ). The same organic molecules are also used by Fe(III)-reducers and are necessary for their growth (Lovley et al. 1993 , Pinchuk et al. 2009 ). Thus, organic carbon plays an important role in both sides of iron cycling. Recent research of the impacts of organics on iron cycling and minerals has been reviewed by Dong et al ( 2023 ), and a study by Peng et al ( 2019 ) that demonstrated influences of organic carbon on iron cycling with a phototrophic Fe(II)-oxidizer and abiotic Fe(III) reduction. Yet the impact carbon has on microbial iron cycling in complex environments such as lakes is largely unknown. In this study, we investigated iron cycling in a dynamic lake and assessed the role of carbon in dictating the relative contribution of microbial Fe(II) oxidation and Fe(III) reduction in shaping biogeochemical cycling. Specifically, we present insights on Fe cycling from Großes Heiliges Meer in northwest Germany, a dimictic lake that develops anoxic bottom layers containing iron and sulfur during the summer months (mid-April to October). It is surrounded by valley sand containing Fe-bearing minerals like garnet and epidote underlain by gypsum-containing Münder-Mergel formation (Dölling and Stritzke 2009 ). Using a suite of in-situ and ex-situ experiments we investigated the relative importance of Fe(II)-oxidizing and Fe(III)-reducing processes throughout the depth profile at summer stratification; and assessed how changes in carbon input alter microbial iron cycling.",
"discussion": "Discussion Key phototrophic Fe(II)-oxidizer in Großes Heiliges Meer In Großes Heiliges Meer, the only taxa attributed to potential phototrophic Fe(II) oxidation were Chlorobium , a green sulfur bacteria (12% at 7 m), and Thiodictyon , a purple sulfur bacteria (1% at 7 m). Few isolated Chlorobium from stratified lakes have the ability to oxidize Fe(II). From Lake la Cruz, a Chlorobium -dominated enrichment culture was obtained (Walter et al. 2014 ), from Lake Kivu the first pelagic strain C. phaeoferrooxidans KB01 isolated (Crowe et al. 2017 ) and a co-culture dominated by Ca.C. masyuteum was enriched from Brownie lake in Minnesota (Lambrecht et al. 2021 ). Although the in-situ community of potential photoferrotrophs was dominated by a Chlorobium with 12% in Großes Heiliges Meer, the phototrophic enrichment was obtained with a Thiodictyon (1% in-situ community). This is the first time that an enrichment capable of Fe(II) oxidation was successful for a dimictic lake with a dominant Fe(II)-oxidizer being a Thiodictyon (31% of enrichment) and not a Chlorobium. Thiodictyon belongs to the Chromatiaceae family of the Gammaproteobacteria class. In a phylogenic tree we tested how close the Thiodictyon in our study is to other Thiodictyon and other Fe(II)-oxidizing model strains like Acidithiobacillus ferrooxidans B20 and Rhodobacter ferrooxidans SW2. We could determine that the Thiodictyon ASV from the lake is the same Thiodictyon ASV that was enriched in the phototrophic Fe(II) oxidation enrichment (Fig. 6 ). The Thiodictyon in our study is closely related (98.43%) to another Thiodictyon Thd2 associated to phototrophic Fe(II) oxidation (Ehrenreich and Widdel 1994 ). Lamprocystis purpurea A12.3, Candidatus Thiodictyon syntrophicum Cad16 and Thiorhodococcus sp. Mog2 are other purple sulfur bacteria found in stratified lakes (Lunina et al. 2005 , Peduzzi et al. 2012 ). Lamprocystis purpurea A12.3 and Candidatus Thiodictyon syntrophicum Cad16 were found in Lake Cadagno, where Berg et al ( 2016 ) studied FeS recycling. FeS recycling was tested in a lab incubation of an in-situ community from Lake Cadagno where FeS was added as the sole electron donor and after 6 months the enrichment was dominated by bacteria morphologically similar to Thiodictyon (Berg et al. 2016 ). Thiodictyon has also been associated with acetate assimilation (Kappler and Newman 2004 ). Acetate could potentially be assimilated by Thiodictyon in the setups with organics in the in-situ experiment (Fig. 3 ). After day 23 an increase of Thiodictyon could be observed in comparison to the in-situ community in the setup where only organics were added. In the experiment with the phototrophic Fe(II)-oxidizing enrichment, we could demonstrate that phototrophic Fe(II) oxidation was performed by a phototrophic enrichment dominated by Thiodictyon (Fig. 5 ). Thiodictyon is the only bacteria in the enrichment associated to both phototrophy and Fe(II) oxidation. Thus, we suggest Thiodictyon has strong potential to conduct phototrophic Fe(II) oxidation in Großes Heiliges Meer. Nevertheless we cannot rule out the participation of Chlorobium in iron cycling or its association with other cycles like the sulfur cycle (Thompson et al. 2017 ). Figure 6. A maximum-likelihood tree based on 16S rRNA gene sequences indicating the phylogenetic position of Thiodictyon from this study among reference Thiodictyon sequences and model Fe(II)-oxidizers. Scale bar for branch length indicates the number of substitutions per site. Accession numbers are included in brackets. Potential for a cryptic iron cycle and effect of organics Despite the clear potential for microbial Fe(II) oxidation, particularly the abundance of anoxygenic phototrophs, it is surprising that no changes in Fe speciation were observed during the in-situ experiment. Furthermore, all measured iron was in the reduced Fe(II) form. This could have two plausible explanations. Either (1) there are no active bacteria present that can oxidize iron or (2) all oxidized iron is immediately reduced soon after it is oxidized resulting in no net change in Fe speciation. We favour the latter interpretation, which would also align with the calculated rates of Fe(III) reduction and Fe(II) oxidation from our enrichments where Fe(III) reduction rates were ∼3 times higher than Fe(II) oxidation rates (0.33 and 0.12 mM/d, respectively). Additionally, we found both potential Fe(II)-oxidizers and Fe(III)-reducers in Großes Heiliges Meer at 7 and 8 m depth (Fig. 2 ) demonstrating clear potential for a complete iron cycle. The sequencing data suggest that anoxygenic photoferrotrophs from the genera Chlorobium and Thiodictyon could play a crucial part in Fe(II) oxidation below the metalimnion. However, our enrichment culture only contained Thiodictyon , thus whether or not the Chlorobium contribute to Fe(II) oxidation is unclear. Microaerophilic Fe(II)-oxidizers like Sideroxydans are also present at 7 and 8 m and could contribute to Fe(II) oxidation. We did not sample the community during the night, but it is likely that microaerophilic Fe(II)-oxidizers would play a relatively more important role in Fe(II) oxidation in the dark given that photoferrotrophy would be inhibited during the night (Nikeleit et al. 2024 ). Above the metalimnion, Fe(II) is likely oxidized abiotically by O 2 produced by the cyanobacteria present ( Snowella , Fig. 2 ). On the Fe(III) reduction side four different potential Fe(III)-reducers were found. Geobacter can couple the oxidation of acetate to Fe(III) reduction (Lovley et al. 1993 , Caccavo et al. 1994 ), whereas Rhodoferax and Geothrix can couple Fe(III) reduction to the oxidation of lactate and acetate (Coates et al. 1999 , Finneran et al. 2003 , Risso et al. 2009 ). Another potential Fe(III)-reducer could be Sulfurospirillum which couples Fe(III) reduction to oxidation of sulfur and thiosulfate (Straub and Schink 2004 ). From the geochemical data alone we cannot draw conclusions as to which Fe(III)-reducer and which Fe(II)-oxidizers actively contribute to Fe turnover and to which extent. In the enrichment culture, however, we measured lactate consumption during Fe(III) reduction (Fig. 6 ) and identified Rhodoferax . The coupled consumption of lactate with the production of acetate has been observed in Fe(III)-reducer and could be an indication for microbial Fe(III) reduction (Pinchuk et al. 2009 ). Fe(III) reduction could also be indirectly taken place by sulfate-reducing bacteria and abiotic Fe(III) reduction of sulfide to FeS minerals (black minerals observed in enrichment experiment). This potential for a cryptic iron cycle was further demonstrated in our iron cycling experiments with the ex-situ community from 8 m depth. We observed that Fe(II) oxidation and Fe(III) reduction are stable in a day/night cycle with no added organics (Fig. 4 , Fe(II)-only setup). When organics were added Fe(III) reduction was stimulated and became the dominating process and thereby masking Fe(II) oxidation (Fig. 4 ). It could also be that Thiodictyon , like other phototrophic Fe(II)-oxidizer, is able to use organics and could use both organics and Fe(II) at the same time or in sequential order (Nikeleit et al. 2024 ). Once the organics are used up Fe(II) oxidation becomes the dominating process (Fig. 4 , Fe(II)+organic and Fe(II) only setup and Fig. 5 ). It is hard to distinguish and exclude processes and it could be that all are taking place at the same time. The results in our study demonstrate that photoferrotrophs are abundant and active at Großes Heiliges Meer, yet their contribution is masked by a faster Fe(III)-reducing community which can thrive on the organics present and rapidly recycle Fe(III). Limitations of studying in-situ microbial iron cycling In our experimental design, we intended to eliminate the potential contribution of cyanobacteria to Fe(II) oxidation in the light by adding the inhibitor DCMU. In all of these setups, bacteria from the genus Sulfurospirillum bloomed, reaching up to 45% of the bacterial community. It is possible that DCMU provided an additional source of carbon and nitrogen which could be accessed by these bacteria. This drastic shift was not observed when we added Fe(II), acetate and lactate, suggesting that these substrates play an active role and did not trigger a fundamental change in the microbial community composition. In future, alternative methods should be used to assess the impact of microbial iron oxidation in the absence of cyanobacteria. Dimictic lakes as potential iron cycling habitats So far, studies on phototrophic Fe(II) oxidation, iron cycling and Archean ocean analogues have focused on permanently stratified meromictic lakes such as Lake Kivu (Llirós et al. 2015 ), Brownie Lake (Lambrecht et al. 2021 ), Lake Cadagno (Berg et al. 2016 ), Lake de la Cruz (Walter et al. 2014 ), Lake Pavin (Busigny et al. 2014 ) and Lake Matano (Crowe et al. 2008 , 2017 ). Of all lakes on earth, only a few are characterized as meromictic whilst most lakes are holomictic and mix periodically. Dimictic lakes like Großes Heiliges Meer, mix once in spring and once in fall. During the summer stratification anoxic bottom water can be formed. Geochemical gradients of oxygen depletion and iron rich bottom waters have been observed in Großes Heiliges Meer, as they are observed in some other dimictic lakes such as Lake 227 and 442 (Kenora, Canada). These conditions make them suitable refugia for phototrophic Fe(II)-oxidizers which once dominated the Earth's oceans and are now resigned to more isolated anoxic yet sunlit niches (Liu et al. 2022 , Schiff et al. 2017 , Swanner et al. 2022 ). Geochemical data from Großes Heiliges Meer from 2014, 2015, and 2018 are comparable to the observations in this study with oxygen depletion at 6 to 7 m (Swanner et al. 2022 ). 16S rRNA amplicon sequencing data of Großes Heiliges Meer showed that potential Fe(II)-oxidizing and Fe(III)-reducing bacteria represented up to 25% of the microbial community in the anoxic bottom waters. This implies that despite regular turnover a diverse iron-cycling microbial community can rapidly re-form when geochemical conditions are favourable. The combination of in-situ experiments, and iron cycling experiments with the ex-situ community and the enrichment culture could confirm that iron cycling takes place in Großes Heiliges Meer; both Fe(III) reduction and phototrophic Fe(II) oxidation. This study shows that complete iron cycling can take place in dimictic lakes but is likely dominated by Fe(III)-reduction, creating a cryptic cycle in which Fe(II) oxidation can be easily overlooked."
} | 4,965 |
37885729 | PMC10598529 | pmc | 3,218 | {
"abstract": "Nowadays, the tendency to replace conventional fossil-based plastics is increasing considerably; there is a growing trend towards alternatives that involve the development of plastic materials derived from renewable sources, which are compostable and biodegradable. Indeed, only 1.5 % of whole plastic production is part of the small bioplastics market, even when these materials with a partial or full composition from biomass are rapidly expanding. A very interesting field of investigation is currently being developed in which the disposal and processing of the final products are evaluated in terms of reducing environmental harm. This review presents a compilation of polyethylene (PE) types, their uses, and current problems in the waste management of PE and recycling. Particularly, this review is based on the capabilities to synthesize bio-based PE from natural and renewable sources as a replacement for the raw material derived from petroleum. In addition to recent studies in degradation on different types of PE with weight loss ranges from 1 to 47 %, the techniques used and the main changes observed after degradation. Finally, perspectives are presented in the manuscript about renewable and non-renewable polymers, depending on the non-degradable, biodegradable, and compostable behavior, including composting recent studies in PE. In addition, it contributes to the 3R approaches to responsible waste management of PE and advancement towards an environmentally friendly PE.",
"conclusion": "8 Conclusions and perspectives New trends in the development of polymeric materials with more environmentally friendly features are the joint objective of the development of bioplastics. However, a more environmentally friendly material must meet certain characteristics that allow its use without generating more contamination or avoiding its proliferation in clean or pure environments. The idea is to create less waste that pollutes the environment since it has been shown that microplastics are generated from non-degradable polymers that could harm health. Transitioning to bioplastics is a prudent choice, given their renewable nature, degradability, eco-friendliness, and sustainable characteristics in contrast to plastics derived from petroleum sources. PE is non-biodegradable and contributes significantly to the world's plastic waste products. However, some factors could help to reduce the accumulation and contamination derived from PE and its degradation rates, such as the 3R methodology and recycling approaches, the chemical and structure modification, and the synthesis and use of bio-based PE and bio-PE; this will enable a new vision of bio-based-PE that is still being developed to reduce single-use petroleum-derived plastics. Finally, considering that PE is an inert and highly recalcitrant material, further degradation and biodegradation studies of the different types of PE are needed since the most studied is LDPE because of its properties, low density, molecular weight and crystallinity. In addition to the fact that if a PE is bio-based, this does not make it biodegradable or compostable, requiring studies for its classification. Perspectives: • Standard norms that demand the use of bio-PE, bio-based PE or the incorporation of recycled PE for the production of single-use PE materials are needed. Since chemical modification and structure of PE could enhance the degradation level. • Studies and techniques are needed to evaluate the formation of micro and nanoplastics released from degradation processes. • Further research is required to explore reaction pathways and potential degradation products of PE and plastics under conditions that simulate the real-world environment. • Additional research is necessary to explore the composting of PE under ambient conditions or in-home composting settings; this entails identifying the microorganisms and enzymes engaged in biodegradation across various compost types, decomposition time, and the byproducts formed.",
"introduction": "1 Introduction PE is one of the most widely used thermoplastics and the highest-volume polymer in production and consumption. Its high toughness, ductility, excellent chemical resistance, low permeability and electrical conductivity, semicrystalline and ease of process make PE an attractive choice for various products and applications [ [1] , [2] , [3] , [4] ]. Although PE is considered an excellent material widely used in the areas of health care and food packaging, a considerable problem is the time required to achieve its complete degradation under uncontrolled conditions. For this reason, new tools and bio-based formulations must be formulated to reduce the material's degradation time and avoid contamination in landfills where it is discarded. Since most of the resources and raw materials used in PE production originate from oil, there is a predominant emphasis within the industry and scientific community on substituting these fossil-based materials with environmentally sustainable alternatives. Additionally, there is a significant focus on creating materials that can be effectively recycled or biodegraded after their product life cycle and bio-based compounds to produce new polymers and materials [ [5] , [6] , [7] , [8] ]. Some examples found in the literature are those in which agro-industrial residues such as garlic [ 9 ] and morning glory stem fibers [ 10 ] are used to elaborate dishes and cutlery, respectively. Besides, studies based on non-degradable polymers such as PE [ 11 , 12 ] and polyethylene terephthalate (PET) [ 13 , 14 ] by using bio-based sources to enhance the green behavior of the material, increase the possibilities of the inclusion in packaging with a more environmentally purpose. This review addresses a compilation of PE types, their uses, and current problems in waste management and recycling; recent studies in degradation on different types of PE, weight loss ranges, the techniques used and the main changes observed after degradation. Particularly, the review is based on the capabilities to synthesize bio-based PE from natural and renewable sources. In addition, it contributes to the 3R approaches to responsible waste management of PE and advancement towards an environmentally friendly PE."
} | 1,562 |
37248049 | PMC10549213 | pmc | 3,219 | {
"abstract": "Abstract Plastic waste is an outstanding environmental thread. Poly(ethylene terephthalate) (PET) is one of the most abundantly produced single-use plastics worldwide, but its recycling rates are low. In parallel, additive manufacturing is a rapidly evolving technology with wide-ranging applications. Thus, there is a need for a broad spectrum of polymers to meet the demands of this growing industry and address post-use waste materials. This perspective article highlights the potential of designing microbial cell factories to upcycle PET into functionalized chemical building blocks for additive manufacturing. We present the leveraging of PET hydrolyzing enzymes and rewiring the bacterial C2 and aromatic catabolic pathways to obtain high-value chemicals and polymers. Since PET mechanical recycling back to original materials is cost-prohibitive, the biochemical technology is a viable alternative to upcycle PET into novel 3D printing materials, such as replacements for acrylonitrile butadiene styrene. The presented hybrid chemo-bio approaches potentially enable the manufacturing of environmentally friendly degradable or higher-value high-performance polymers and composites and their reuse for a circular economy. One-Sentence Summary Biotransformation of waste PET to high-value platform chemicals for additive manufacturing.",
"conclusion": "Conclusions and Future Perspectives The chemical toxicity of PET-derived TPA and EG, metabolic intermediates, and the targeted product(s) is one of the critical challenges in the in-process development to achieve the techno-economically viable product yield, titer, and rate (YTR; Lynd et al., 2022 ). Studies demonstrated that EG and its intermediates, metabolites glycolaldehyde and glyoxal, significantly inhibit microbial growth ( Franden et al., 2018 ; Jayakody et al., 2017 ). Synthetic biology approaches have been proposed to alleviate the inhibitory effect of those molecules (Jayakody et al., 2018 , 2021 ; Lynd et al., 2022 ). The specific toxicity tolerance mechanisms, based on the chemical functionality, can be introduced to the strains to enhance the tolerance. The two-tier tolerance mechanisms can be adopted, including macromolecule protection and conversion of toxic chemicals to high-value products (Jayakody et al., 2021 ; Lynd et al., 2022 ). For instance, debottlenecking the EG catabolism by overexpression of glycolate oxidase and the glc operon eliminated the accumulation of glycolaldehyde and glyoxal, enhanced the EG tolerance by 100-fold, and enabled the production of mcl-PHA from EG (Franden et al., 2018 ). Protein quality control machinery is key to overcoming macromolecule damage caused by aldehydes such as glycolaldehyde (Ahn et al., 2002 ). Hence, overexpression of the chaperone ClpB–GroESL system (protection) along with the desired catabolic pathway (i.e., two-tier protection) might further enhance the robustness of the strain (Henson et al., 2022 ; Jayakody et al., 2021 ). Note that the expression of chaperone machineries also protects host cells from the chemical toxicity of products. Often, the overexpression of the numerous native and heterologous pathways could compete with the cellular metabolites or redox cofactors and struggle to produce the desired chemicals and polymers efficiently (Henson et al., 2021 ). The synthetic metabolic circuits could be used for fine-tuning the multiple pathway(s) to minimize the metabolic burdens or feedback regulations (Mannan & Bates, 2021 ). Adaptive laboratory evolution (ALE) enables the strain to optimize further the engineered genome and fine-tuning of translational and transcriptional machineries toward the desired phenotype (Wang et al., 2021 ). The developed strain(s) with engineered metabolic pathways to upcycle PET-derived compounds can be subjected to ALE to increase the YTR of platform chemicals or polymer production. Also, tolerance adaptive laboratory evolution has been a useful tool in developing tolerance strains for toxic chemicals, for instance, P. putida for aromatic compounds (Werner et al., 2021 ). Product separations to form the fermented broth with high purity to produce polymers and biomaterials are another critical technical challenge. Werner and coworkers employed highly efficient purification (96–99% purity) of dicarboxylic acids (i.e., β-ketoadipate) from the culture broth by activated carbon treatment, pH/temperature shift crystallization, and ethanol dissolution with microfiltration to produce polymers (Werner et al., 2021 ). Notably, in situ product recovery (ISPR) is a vital process strategy that separates the target product(s) from the broth while the fermentation is ongoing. ISPR can involve the target product recovery by adsorption to a resin, liquid organic overlayer, selective chemical precipitation, or stripped from the broth with a gas. Continuous removal of the product ISPR ameliorates end-product toxicity allowing greater yield and titer. ISPR can dramatically lower costs, reduce energy footprints, alleviate end-product toxicity, lower process water footprints, and increase volumetric productivity (Lynd et al., 2022 ). There are multiple sources for AM polymer waste, including failed parts, inappropriate geometry designs or process parameter settings, removed support structures, wasted filament in case of machine malfunctions, wasted powders, abandoned parts, used parts because of insufficient property or functionality, and others, and accounted for approximately 10% of AM waste generation ( www.filamentive.com ., 2019). According to the lifecycle analysis, AM products generally end up in landfills or ecosystems (>90%) due to mismanagement and a lack of techno economically feasible recycling or upcycling process (Colorado et al., 2020 ). It has been indicated that about 5000 tons of AM waste annually contributes to plastic waste (Zhu et al., 2021 ). Promising chemical recycling or upcycle methods have been developed for PLA to make the AM material(s) to enable the circular economy (Shao et al., 2022 ; Yang et al., 2022 ). However, those technologies are still in the infancy stage. A mechanical process was developed to process waste pellets into reusable filaments for extrusion-based AM (Shanmugam et al., 2020 ). However, the state-of-the-art research on AM thermoplastic waste recycling suggests a decrease in mechanical properties after one or multiple rounds of recycling, which can be compensated by adjusting the values of process parameters. Because of the similarity of the chemical bond structures, including amino and ester groups, the biological or chemo-biological process can be deployed to recycle the new 3D-printed materials developed through the biotransformation process. Hence, the microbial system can be developed toward closed-loop material flow in AM. For instance, we can tailor microbe biocatalysts to degrade the new polymer into original monomers selectively by secreting appropriate enzymes (e.g., PETase to break the esterase link). We can knock out those monomers’ metabolic pathways to enable the accumulation of products (i.e., adipic acid catabolism). The generated monomers can be replenished through the production of new 3D-printed material with similar material properties and to complete a circular material economy. In summary, designing efficient microbial cell factories enable the upcycling of PET-derived compounds to high-value platform chemicals that can be used to manufacture advanced material for AM. The presented microbial metabolic routes (i.e., biofunneling) can be leveraged to obtain the performance of advanced monomers or polymers to manufacture the filaments for 3D printing applications (Fig. 1 and supplemental figure ). Techno-economic analysis and life cycle assessment are vital to affirm the techno-economic viability and sustainability of the proposed biotransformation routes. The proposed approaches, including C2 and aromatic catabolic routes, can be widely adopted to valorize other synthetic waste plastic [e.g., polyurethane-derived dioles and bioplastic poly(butylene-adipate-co-terephthalate)-derived compounds] to enable the circular material economy and reduce plastic pollution.",
"introduction": "Introduction Synthetic plastics, introduced after World War II, are growing in demand due to their attractive properties and low cost. High-volume applications include packaging, building materials (replacing metals and wood), and the health sector (Geyer et al., 2017 ; Lebreton & Andrady, 2019 ). Many petroleum-derived plastics are designed for single-use applications. As a result, ∼175 metric tons (Mt) of plastic waste enter landfills and the natural environment each year, with a significant burden on land and oceanic ecosystems. Plastics production will contribute 20% of global petroleum use and 15% of gas emissions in 2050 (World Economic Forum, 2016 ). Currently, only about 9% of plastic is recycled, 19% is burned, 50% goes to landfills, and 20% is not managed, ending up in oceans or other environments ( OECD.org ). Projections show that in 2025, cities globally will generate 6 Mt of solid waste daily (Hoornweg et al., 2013 ). Poly(ethylene terephthalate) (PET) is one of the most abundantly produced single-use plastics worldwide, and the annual production of PET exceeds 73.4 million Mt. Low recycling rates and the expected increases in single-use items magnify the situation. Thus, circularity of plastics is sorely needed. PET is also used for everyday commercial products including food packaging, water bottles, and textiles (Evode et al., 2021 ). For instance, PET packaging is a safe, cost-effective method for packaging food, beverages, and other agricultural products. The United States is the second-largest PET-packaging market with a 20.5% global share (22 Mt, with a 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${\\$}$\\end{document} 44 billion in 2020). Of note, novel advancements in the field have highlighted the possibility of producing PET more sustainably from biomasses or recycled PET (rPET) via biochemical approaches (Benavides et al., 2018 ). Additive manufacturing (AM), also called 3D printing, is a rapidly evolving fabrication technology. AM is defined as the ‘‘process of joining materials to make parts from 3D model data, usually layer upon layer, as opposed to subtractive manufacturing and formative manufacturing methodologies’’ ( ISO/ASTM Standard 52900 ). AM technologies are diverse but can be grouped into seven categories: material extrusion [also called fused deposition modeling (FDM) or fused filament fabrication], material jetting (inkjet printing), vat photopolymerization [stereolithography (SLG), two-photon polymerization], powder bed fusion [selective laser sintering (SLS), selective laser melting, and electron beam melting], binder jetting, directed energy deposition, and sheet lamination (SL) (laminated object manufacturing, ultrasonic AM) ( ISO/ASTM Standard 52900 ). Polymers are utilized mainly in the first four categories (Devine, 2019 ; González-Henríquez et al., 2019 ). AM has numerous advantages over traditional (subtractive) manufacturing methods. The AM offers design flexibility (geometric freedom), which allows printing complex shapes, lightweight parts, simpler-to-assemble components, and parts with varying material properties. Other advantages include production flexibility, such as fast prototyping, printing custom-made parts, and a simpler production process. In economic terms, the global AM market is expected to reach \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n${\\$}$\\end{document} 23.33 billion by 2026 and is considered as one of the most promising manufacturing technologies merging in the Fourth Industrial Revolution also named Industry 4.0 (Godina et al., 2020 ; Sanchez et al., 2020 ). A rapid compound annual growth rate (CAGR) of 22% is expected for the period of 2019–2024 (Tan et al., 2020 ). SmartTech Analysis reported that the AM polymers market grew to \\documentclass[12pt]{minimal}\n\\usepackage{amsmath}\n\\usepackage{wasysym}\n\\usepackage{amsfonts}\n\\usepackage{amssymb}\n\\usepackage{amsbsy}\n\\usepackage{upgreek}\n\\usepackage{mathrsfs}\n\\setlength{\\oddsidemargin}{-69pt}\n\\begin{document}\n${\\$}$\\end{document} 7.3 billion in 2022 with 20% CAGR (SmarTech Analysis Reports 2020 ). The AM is more sustainable due to its material efficiency resulting in less material waste and resource efficiency since printing on demand and closer to customers reduce storage and transportation costs (Kunovjanek et al., 2022 ; Sardon et al., 2022 ). The first applications of AM were in rapid prototyping and then in tooling. Currently, the AM is dominant in nearly every industry: aerospace (enabling lighter and less complex engine parts), space exploration (parts made on the Space Station), automotive (parts and customized cars), energy (harvesting and storage), architecture (prototypes of designs), construction (buildings and bridges), dentistry (custom-made orthodontics), medicine (devices, custom-made implants, prosthetics, and scaffolds), nanotechnology (microdevices), education (outreach, classroom projects, and training of workforce), food (complex food shapes or patterns, e.g., chocolate, pizza), cultural heritage (replicas of art and architecture, preservation, and restoration), consumer goods (e.g., clothing, shoes), art (new sculptural forms and designs), and jewelry (new designs), among others (Jasiuk et al., 2018 ). AM uses a wide range of materials, including metallic, ceramic, and polymeric, and their combinations in composites, hybrids, or functionally graded materials, with polymers being the most widely used materials (González-Henríquez et al., 2019 ). Polymers have been widely used for rapid prototyping. Different types of polymers, such as photosensitive resins, thermoplastics, and viscous polymer inks, have been utilized in various AM techniques. Thermoplastics, including acrylonitrile butadiene styrene (ABS), polylactic acid (PLA), nylon, and polypropylene (PP), are the main polymers used for extrusion-based AM applications (Park et al., 2022 ). Currently, the polymers for AM are predominately produced using petroleum-based feedstock. However, this process faces several issues regarding its raw material supply. For example, the higher cost of the raw materials used in AM compared to the conventional manufacturing processes, the limited availability, sustainability, and environmental and health concerns of those raw materials are some upfront issues (Shukla et al., 2018 ). One approach to overcoming the shortage of raw materials is through product recycling (Garmulewicz et al., 2018 ; Paris & Mandil., 2017 ). Of note, many 3D-printed thermoplastics are designed for single-use applications, are not recycled efficiently, and end up in landfills. Drastic changes in plastic recycling/upcycling technologies are essential to enable a more circular material flow for 3D printing plastics to eliminate adverse environmental impacts. It is vital to have scalable, reproducible, and sustainable feedstocks for the AM. For sustainability, the feedstock materials should be derived from bio-based resources and waste recycling streams by implementing green chemistry principles. Thermal and mechanical recycling of PET often results in PET polymer with inferior properties and ∼33% lower value (Ragaert et al., 2017 ). PET can be chemically recycled via full breakdown to monomers and re-polymerized back to PET (Barnard et al., 2021 ). However, this approach is not economically feasible currently. Researchers have discovered PET hydrolases from microorganisms evolved within plastic-containing ecosystems (i.e., the so-called ‘‘Plastisphere’’) and investigated these enzymes to establish bio-based PET recycling approaches. Researchers have developed promising industrially applicable enzyme-based recycling technology to remake PET bottles with similar material properties using recycled PET monomers (Zhu et al., 2022 ). Techno-economic analyses of this approach predict that recycled PET has remarkable energy and environmental impacts, including reducing greenhouse gas (GHG) emissions (∼1.5 CO 2 -eq-ton/recycle PET) and energy input (>20 MJ/ton) over virgin PET. Utilization of rPET-derived monomers can reduce environmental impacts while generating more socioeconomic benefits to the United States relative to petroleum-derived monomer production. With advances in synthetic microbiology, the development of a sustainable microbial-based ‘‘PET upcycling’’ route toward a green, circular economy becomes attractive. Upcycling is achieved by adding value to the PET waste by providing a path for utilizing PET-derived compounds to manufacture high-value fuels, chemicals, food ingredients, and pharmaceuticals (Dissanayake & Jayakody, 2021 ; Sadler & Wallace, 2021 ). As we highlighted, renewable-source biopolymers are widely applicable in AM platforms, and the production of those monomers from unconventional substrates, such as plastic waste, through a biological approach can enhance the sustainability of AM sector. This perspective review paper discusses the potential of microbial upcycling of PET to manufacture the advanced biopolymers and biochemicals that can be used to generate environmentally friendly polymers for AM."
} | 4,425 |
22851018 | PMC3536970 | pmc | 3,221 | {
"abstract": "In this study, the potential of Corynebacterium glutamicum for reductive whole-cell biotransformation is shown. The NADPH-dependent reduction of the prochiral methyl acetoacetate (MAA) to the chiral ( R )-methyl 3-hydroxybutyrate (MHB) by an alcohol dehydrogenase from Lactobacillus brevis ( Lbadh ) was used as model reaction and glucose served as substrate for the regeneration of NADPH. Since NADPH is mainly formed in the oxidative branch of the pentose phosphate pathway (PPP), C. glutamicum was engineered to redirect carbon flux towards the PPP. Mutants lacking the genes for 6-phosphofructokinase ( pfkA ) or glyceraldehyde 3-phosphate dehydrogenase ( gapA ) were constructed and analyzed with respect to growth, enzyme activities, and biotransformation performance. Both mutants showed strong growth defects in glucose minimal medium. For biotransformation of MAA to MHB using glucose as reductant, strains were transformed with an Lbadh expression plasmid. The wild type showed a specific MHB production rate of 3.1 mmol MHB h −1 g cdw −1 and a yield of 2.7 mol MHB mol glucose −1 . The ∆ pfkA mutant showed a similar MHB production rate, but reached a yield of 4.8 mol MHB mol glucose −1 , approaching the maximal value of 6 mol NADPH mol glucose −1 expected for a partially cyclized PPP. The specific biotransformation rate of the Δ gapA mutant was decreased by 62 % compared to the other strains, but the yield was increased to 7.9 mol MHB mol glucose −1 , which to our knowledge is the highest one reported so far for this mode of NADPH regeneration. As one fourth of the glucose was converted to glycerol, the experimental yield was close to the theoretically maximal yield of 9 mol NADPH mol glucose −1 .",
"introduction": "Introduction Whole-cell biotransformation has become an important method in chemoenzymatic synthesis, e.g., for the production of amino acids and chiral alcohols (Ishige et al. 2005 ). Corynebacterium glutamicum is a Gram-positive, non-pathogenic soil bacterium which is predominantly used for the large-scale industrial production of the flavor enhancer l -glutamate and the food additive l -lysine (Pfefferle et al. 2003 ; Kimura 2003 ; Hermann 2003 ). Recent metabolic engineering studies have shown that C. glutamicum is also capable of producing a variety of other commercially interesting compounds, e.g., other l -amino acids (Wendisch et al. 2006 ), d -amino acids (Stäbler et al. 2011 ), organic acids such as succinate (Okino et al. 2008 ; Litsanov et al. 2012a , b ), diamines such as cadaverine (Mimitsuka et al. 2007 ) or putrescine (Schneider and Wendisch 2010 ), biofuels such as ethanol or isobutanol (Inui et al. 2004 ; Smith et al. 2010 ; Blombach et al. 2011 ), or proteins (Meissner et al. 2007 ). An overview of the product spectrum of C. glutamicum can be found in a recent review (Becker and Wittmann 2011 ). \n C. glutamicum was also shown to be a suitable host for whole-cell biotransformation with resting cells for production of mannitol (Bäumchen and Bringer-Meyer 2007 ) and cyclohexanone derivatives (Doo et al. 2009 ; Yun et al. 2012 ). These reactions are often NAD(P)H dependent and cofactor recycling is crucial for profitable processes. For example, formate dehydrogenase or glucose dehydrogenase are used, but only 1 mol NAD(P)H can be generated from 1 mol formate or 1 mol glucose (Kaup et al. 2004 , 2005 ; Ernst et al. 2005 ; Eguchi et al. 1992 ; Tan 2006 ). Use of metabolically active cells gives the opportunity to regenerate reduced cofactors via sugar metabolism and to gain a higher reduced cofactor to glucose ratio (Chin and Cirino 2011 ). In Escherichia coli , several attempts were made for engineering cellular metabolism towards a higher NADPH per glucose yield (Fasan et al. 2011 ; Akinterinwa and Cirino 2011 ). NADPH is mainly generated in the oxidative branch of the pentose phosphate pathway (PPP), where glucose 6-phosphate dehydrogenase catalyzes the oxidation of glucose 6-phosphate to 6-phopshoglucono-δ-lactone and 6-phosphogluconate dehydrogenase, which catalyzes the oxidative decarboxylation of 6-phosphogluconate to ribulose 5-phosphate, yielding 2 mol NADPH (Fig. 1 ). Therefore, employment of the PPP is an interesting option for NADPH-dependent processes (Chin and Cirino 2011 ; Chemler et al. 2010 ). In a recent study with E. coli , we analyzed the NADPH-dependent reduction of the prochiral β-ketoester methyl acetoacetate (MAA) to the chiral hydroxy ester ( R )-methyl 3-hydroxybutyrate (MHB) using glucose as substrate for the generation of NADPH (Siedler et al. 2011 , 2012 ). The reduction was catalyzed by an R -specific alcohol dehydrogenase (ADH) from Lactobacillus brevis . MHB serves as a building block of statins (Panke and Wubbolts 2005 ). Deletion of pfkA and pfkB encoding phosphofructokinase I and II, respectively, resulted in a partial cyclization of the PPP and a yield of 5.4 mol MHB mol glucose −1 , which was near the theoretically maximal yield of 6 (Kruger and von Schaewen 2003 ). Fig. 1 Scheme of the upper part of glycolysis and pentose phosphate pathway of C. glutamicum . Gene deletions and NADPH generating reactions are indicated. PTS phosphotransferase system, IolT1/IolT2 alternative glucose import system, Glk ATP-dependent glucokinase, PpgK polyphosphate/ATP-dependent glucokinase, Pgi phosphoglucose isomerase, PfkA phosphofructokinase, GapA glyceraldehyde-3-phosphate dehydrogenase, DHAP dihydroxyacetone phosphate, PEP phosphoenolpyruvate \n To determine whether this metabolic engineering strategy can be generalized, is e.g. transferable to C. glutamicum , was one major goal of this study. It has to be kept in mind that differences exist in the repertoires of metabolic enzymes of E. coli and C. glutamicum . Of relevance for the present work is the occurrence of only one gene encoding a 6-phosphofructo1-kinase ( pfkA ) and the absence of genes encoding transhydrogenases and the key enzymes of the Entner–Doudoroff-pathway in C. glutamicum (Yokota and Lindley 2005 ) . To further improve the NADPH per glucose yield, deletion of the glyceraldehyde 3-phosphate dehydrogenase ( gapA ) gene would be beneficial, as it should result in a complete cyclization of the PPP. Deletion of gapA theoretically enables a yield of 12 mol NADPH per mole of glucose 6-phosphate by complete recycling of fructose 6-phosphate and triose 3-phosphate through the oxidative PPP (Kruger and von Schaewen 2003 ). The gapB gene encoding a second glyceraldehyde 3-phosphate dehydrogenase in C. glutamicum should not be relevant in this context, as GapB does not function in the glycolytic direction (Omumasaba et al. 2004 ). In this study, we analyzed C. glutamicum mutants lacking either pfkA or gapA for their behavior in reductive whole-cell biotransformation. The results supported the view that the PPP operates in cyclic manner, oxidizing glucose to CO 2 with concomitant reduction of NADP + to NADPH.",
"discussion": "Discussion For reductive whole-cell biotransformations requiring NADPH, attempts were made in this work to increase the NADPH yield per mole of glucose using C. glutamicum as host strain and the reduction of MAA to MHB as NADPH-requiring model reaction. Rerouting of glucose catabolism from glycolysis to the oxidative PPP was achieved by deletion of either the pfkA gene or the gapA gene. \n C. glutamicum wild type carrying pEKEx2- Lbadh showed a 31 % lower specific MHB production rate compared to E. coli carrying pBtac- Lbadh , even when compared to an E. coli biotransformation conducted at 30 °C (unpublished data). This difference might be due to a lower glucose uptake capacity or to a generally lower metabolic flux capacity of C. glutamicum . Overexpression of the genes involved in glucose uptake and catabolism via glycolysis or PPP could improve the rate of glucose catabolism, as shown recently for oxygen-deprived conditions (Yamamoto et al. 2012 ; Jojima et al. 2010 ). The MHB per glucose yield found for C. glutamicum WT/pEKEx2- Lbadh (2.7 mol/mol) was 10 % higher than the corresponding value determined for E. coli BL21(DE3)/pBtac- Lbadh (2.44 mol/mol) (Siedler et al. 2011 ), which might be due to slight differences in the partition of glucose 6-phosphate between glycolysis and the PPP. Biotransformation studies with E. coli ∆ pfkA and ∆ pfkA ∆ pfkB mutants expressing Lbadh showed yields of 4.8 and 5.4 mol MHB mol glucose −1 , respectively (Siedler et al. 2011 ). 13 C metabolic flux analysis demonstrated a negative net flux through phosphoglucose isomerase in the ∆ pfkA mutant, in compliance with the proposed partial cyclization of the PPP (Siedler et al. 2012 ). The MHB yield per glucose of the E. coli strain ∆ pfkA /pBtac- Lbadh was comparable to that of the C. glutamicum strain ∆ pfkA /pEKEx2- Lbadh (4.8 mol MHB mol glucose −1 ), indicating that a partial cyclization of the PPP occurred in the latter species, too. Furthermore, similarities were found when comparing by-product formation in E. coli and C. glutamicum . Less acetate and no succinate was produced in both ∆ pfkA mutant strains compared to the reference strains within the experimental period, presumably as a consequence of a decreased carbon flux through the lower part of glycolysis and the TCA cycle in these mutants (Siedler et al. 2012 ). \n C. glutamicum possesses two glyceraldehyde 3-phosphate dehydrogenases (GAPDH), but only GapA functions in the glycolytic direction (Omumasaba et al. 2004 ). Thus, a deletion of the corresponding gene theoretically should result in a cyclization of the PPP. The fact that the MHB per glucose yield of the strain ∆ gapA /pEKEx2- Lbadh (7.9 mol/mol) was higher compared to the strain ∆ pfkA /pEKEx2- Lbadh and corresponded to 66 % of the maximal value of 12 mol NADPH per mole of glucose indicated a more extended cyclic operation of the PPP in the ∆ gapA mutant compared to the ∆ pfkA mutant. The maximal value for a complete oxidation of glucose in the PPP was not reached because 25 % of the glucose carbon was lost by reduction of glyceraldehyde 3-phosphate to glycerol. Taking this loss into account, only 9 mol MHB mol glucose −1 could be achieved maximally. The experimental yield of 7.9 mol MHB mol glucose −1 corresponds to 88 % of this value and is 46 % above the best yields reported so far (Chin and Cirino 2011 ; Siedler et al. 2011 , 2012 ). Future yield optimization could be achieved by deletion of the gene encoding glycerol 3-phosphatase. Such a deletion was recently shown to prevent glycerol formation, which predominantly occurs in fructose-utilizing C. glutamicum strains (Lindner et al. 2012 ). The strongly reduced biotransformation rate of the strain Δ gapA /pEKEx2- Lbadh was probably a consequence of the diminished capability for glucose uptake. In a Δ gapA mutant, no PEP should be formed during glucose catabolism and consequently, glucose uptake via the PTS should be impossible. PTS-independent glucose uptake has recently been described for C. glutamicum. It involves the inositol transporters IolT1 and IolT2 which also function as low-affinity glucose permeases (Lindner et al. 2011 ). Subsequent phosphorylation of glucose to glucose 6-phosphate is catalyzed either by an ATP-dependent glucokinase encoded by glk (Park et al. 2000 ) or by the polyphosphate- or ATP-dependent glucose kinase PpgK (Lindner et al. 2010 ). It can be assumed that glucose uptake during biotransformation with the Δ gapA mutant occurs via this alternative pathway, as the observed glucose consumption rate of 2.5 nmol min −1 mg cdw −1 (Table 5 ) at glucose concentrations >10-fold above the apparent K \n s values of IolT1 and IolT2 (2.8 and 1.9 mM, respectively) is in the range determined for PTS-independent glucose uptake at 1 mM glucose (0.7 nmol min −1 mg cdw −1 ) (Lindner et al. 2011 ). Overexpression of either iolT1 or iolT2 together with ppgK was shown to allow almost wild-type growth rates in a PTS-negative mutant (Lindner et al. 2011 ) and thus would probably also allow higher biotransformation rates of a Δ gapA mutant. Alternatively, expression of the glucose facilitator gene glf from Zymomonas mobilis could help to increase glucose uptake (Weisser et al. 1995 ; Parker et al. 1995 ). Overall, we could demonstrate the potential of C. glutamicum for NADPH-dependent reductive whole-cell biotransformation and show that deletion of either pfkA or gapA is beneficial to improve the NADPH per glucose yield, presumably by cyclization of the PPP."
} | 3,161 |
34553134 | PMC8441150 | pmc | 3,223 | {
"abstract": "Summary Biohybrid photo/electrosynthetic systems synergize microbial metabolic pathways and inorganic materials to generate the fuels and chemicals to power our society. They aim to combine the strengths of product selectivity from biological cells and efficient charge generation and light absorption of inorganic materials. However crucial mechanistic questions still remain. In this review we address significant knowledge gaps that must be closed and recent efforts to do so to push biohybrid systems closer to applicability. In particular, we focus on noteworthy advances that have recently been made in applying state-of-the-art analytical spectroscopic, electrochemical, and microelectronic techniques to help pinpoint key complexities of the microbe-materials interface. We discuss the basic function of these techniques, how they have been translated over to study biohybrid systems, and which key insights and implications have been extracted. Finally, we delve into the key advances necessary for the design of next generation biohybrid energy conversion systems.",
"introduction": "Introduction The accelerating consumption of fossil fuels since the industrial revolution has resulted in the deterioration of earth’s environment. As such, mitigating climate change, decreasing the levels of environmental pollution, and developing sustainable pathways to power tomorrow’s society are amongst the most pressing challenges facing future generations ( Chu and Majumdar, 2012 ; Lewis and Nocera, 2006 ). In the context of renewable energy, there has been much progress in technology development in generating electricity efficiently from solar, wind, and hydro sources ( NREL, 2021 ). A central difficulty is converting the resultant intermittent electricity into energy dense fuels and chemical building blocks as replacements for fossil fuels because the catalytic chemistry has not yet been developed. Nature, on the other hand, has evolved elegant catalytic routes in using light, simple reducing/oxidizing equivalents and simple raw ingredients (e.g. CO 2 , H 2 O) to generate complex chemical products. Despite these strengths, natural systems powered by photosynthesis suffer from overall light to product efficiencies. Often natural systems are limited by incomplete light absorption and low throughput with overall solar to chemical/biomass efficiencies often typically situated below 1% as they are geared primarily for survival and proliferation ( Blankenship et al., 2011 ). Against this backdrop, there has been a rapid growth of research focusing on combining strengths of synthetic materials and natural catalysts into integrated biohybrid energy conversion systems ( Kornienko et al., 2018 ). Specifically, this line of work aims to synergize the efficient light absorption and charge delivery of semiconductor photocatalysts and inorganic (photo) electrodes with electroactive microbes ( Cestellos-Blanco et al., 2020 ). The chosen microbes are selected to take up the resultant charge from the inorganic material via various extracellular electron transfers (EET) pathways and perform the requisite complex catalytic chemistry through their evolved metabolic pathways, ideally generating products of high value at industrially relevant throughputs. A secondary advantage linked to microbial systems is that they contain built-in self-repair and reproductive mechanisms, alleviating the stability issues often limiting the use of isolated enzymes. With such biohybrid systems, the sustained, efficient and selective reduction of CO 2 to multi-carbon products is a longstanding goal. However, its achievement is still hampered by difficulties in seamlessly integrating the synthetic and biological components. We argue that overcoming these challenges will largely be made possible by the development of a fundamental understanding of the materials/biology interface aided through the innovation of analytical methods and thus, this is the focus of the present review. The systems that will be covered in this review are those consisting of either (photo)electrodes that donate charge to microbes who carry out the chemical catalysis ( Figure 1 A) or light-absorbing semiconductor nanoparticles directly interfaced with microbes who accept their photogenerated charges ( Figure 1 B). Although analogous systems featuring isolated enzymes in place of whole cells are of significant fundamental value ( Cracknell et al., 2008 ; Ruff et al., 2020 ), this scope of this particular work is limited to microbial systems. Thus, the target of this review is to identify knowledge gaps in the function of biohybrid systems and subsequently detail the emerging techniques being adopted in this field to address these gaps. The key insights include those that help the following: 1. Understanding charge transfer mechanisms between inorganic and biological components 2. Identifying, then approaching, theoretical limits of macroscopic electrode performance 3. Pinpointing limiting factors in macroscopic biohybrid system performance 4. Rationally increasing synergy between inorganic and biological components Figure 1 Overview of emerging techniques (A and B) Biohybrid systems composed of electroactive microbes interfaced with (photo)electrodes (A) and synthetic light-absorbing particles synergized with functional microbes (B) will be the two principal types of systems focused on in this work. (C–F) The emerging methods translated to probe biohybrid systems primarily include microelectronic measurements (C), QCM-based techniques (D), steady-state spectroelectrochemistry (E) and time-resolved spectroscopy (F), each of which can be applied to certain subsets of systems and offers unique mechanistic insights. Against this backdrop, this work first will focus on the use of microelectronic devices and conductivity measurements which are increasingly used to decipher means of inter and intracellular charge transport and EET mechanisms ( Figure 1 C). Next, quartz-crystal microbalance (QCM) based techniques will be covered which provide insights into how the mass and rigidity changes of growing biofilms correspond to observed electrochemical activity ( Figure 1 D). Methods employing the use of steady-state vibrational and UV-Vis absorbance spectroscopy will then be discussed, which offer information regarding the proliferation of various cellular components implicated in EET pathways and redox changes of electroactive proteins as a function of location or applied potential ( Figure 1 E). Finally, the recent translation of time-resolved techniques to elucidate photoexcited charge transfer pathways and rates of various photoinduced processes will be the final topic ( Figure 1 F). Not every study focuses on functional biohybrid systems but rather aims to uncover mechanistic knowledge that can later be applied to such systems. Further, as some techniques are better geared toward measuring electrode or photocatalyst based biohybrids, the different sections will thus focus more on one particular type of system. To conclude, we provide future perspectives for steps necessary to take en route to realizing biohybrid systems in practical applications. Microelectronic devices and conductivity measurements We begin the discussion with the translation of microelectronic and conductivity techniques to probe charge transfer behavior of functional biofilms and isolated microbial cells. This knowledge is especially important because as EET mechanisms are still being elucidated ( Kumar et al., 2017 ), charge transfer is often a factor limiting the throughput of biohybrid systems and rational means to maximize charge transfer rates thus underpins the development of next generation biohybrids. Ideally, the solar photon flux or charge flux from the inorganic component is limiting, rather than sluggish charge transfer between inorganic and biological components. Briefly, EET mechanisms largely consist of either 1) direct modes in which microbes and/or microbial nanowires directly transfer charge to/from electrodes. In contrast, 2) mediated EET modes often use soluble redox mediators such as flavins through other species such as cell-derived free enzymes have also been implicated ( Deutzmann Jörg et al. 2015 ). In this direction, microfabricated devices featuring (1) an open window with a conductive electrode accessible ( Figure 2 A) or (2) the conductive electrode covered by an insulator with only small open holes which were below the size of individual microbes ( Figure 2 B) were used to investigate EET pathways in Shewanella oneidensis MR-1 ( Jiang et al., 2010 ). The results showed similar current outputs for both devices and that the currents rapidly decreased upon the exchange of media. Further, the current was not heavily dependent on the quantity of microbes directly adsorbed overtop of the microfabricated electrodes. Thus, this heavily implied that mediated EET was the dominant mode for this system. Alternatively, a field-effect transistor (FET) was used to probe EET pathways of Clostridium ljungdahlii microbes ( Li et al., 2021 ), which do not possess genes coding for pili and cytochrome expression or quinone and hydrogenase secretion which are often used in the EET pathways. In an electrochemical cell under turnover conditions, the voltage across the source and drain electrodes, with the biofilm in between, dictated the availability and potential of electrons. The availability of electrons was determined to be the dominant factor that resulted in the amount of catalytic current output and provided evidence for direct charge transfer as the principal mode of EET. Figure 2 Microelectronic devices and conducitivity (A and B) The use of open electrodes (A) or those with exposed holes (B) enables the distinction between direct and mediated EET as the dominant mode ( Jiang et al., 2010 ). (C and D) Measuring conductivity between interdigitated electrodes (C) as a function of temperature can elucidate charge hopping as the dominant conductivity mode (D) ( Xu et al., 2018 ). Reproduced with permission from the American Chemical Society. Source-drain type measurements have also been conducted as a function of temperature, to discern the mode of conductivity of conductive structures employed by Geobacter sulfurreducens ( Yates et al., 2015 ). A pronounced temperature dependence in the conductivity, which could be subsequently fit to an Arrhenius model, provided evidence for a system in which charges hop via proximal cytochromes. In contrast, metallic conductivity would not have exhibited such temperature-dependent behavior. A similar line of studies was conducted with S. oneidensis MR-1 cells, also suggesting the presence of a charge hopping mechanism via a heme-based pathway ( Figures 2 C and 2D) ( Xu et al., 2018 ). In a complementary work, individual microbial nanowires of S. oneidensis MR-1 were probed with a combination of nanofabricated electrodes and conductive atomic force microscopy (AFM) ( El-Naggar et al., 2010 ). Having a microbial nanowire between two electrodes enabled the direct probing of its resistivity, found to be on the order of 1 Ω·cm while conductive AFM measurements were used to confirm the data. The deletion of cytochrome-coding genes resulted in mutants with non-conductive nanowires, demonstrating the involvement of cytochromes in the conductance mechanism. Utilizing microelectrode methods can also enable single cell measurements, which are important to both understand diversity in performance between individual cells and to quantify upper efficiency limits from the extrapolation of single microbe measurements. To this end, microelectrodes are an important tool to interface with one cell at a time. The combination of real-time current measurements and optical tracking of G. sulfurreducens DL-1 on nanofabricated electrodes revealed steps in the current density that were correlated in time with the passing of a microbe over the electrode ( Jiang et al., 2013 ). The consistency of the magnitude of these stepwise current jumps was evidence that they stem from single microbes. Finally, dividing the current by the cell volume and extrapolating to a macroscale electrode gave rise to a theoretical current density of ∼10 6 A m −3 , a value higher by 100–1000× than previously attained at the time. This signifies that there is much room to improve the performance output of microbe-grafter electrodes via improving interfacial charge transfer. The EET efficiency of single microbes was further augmented by encapsulating S. oneidensis MR-1 cells with conductive polymer shells which ideally contact the EET machinery on the entirety of the cell exterior rather than just the part directly in contact with the electrode ( Yu et al., 2020 ). Indeed, through correlating microelectrode currents with optical tracking, the polymer coated microbes exhibited currents of 292 ± 55 fA (or ∼2.5 × 10 6 electrons s −1 ) per cell, which was more than 4 times greater than unfunctionalized microbes. As such, the results pave a tangible path forward to maximize macroscopic biohybrid performance via maximizing connectivity to individual microbes. There are several important implications to the works cited above ( Table 1 ). Although discerning between various modes of mediated and direct EET can be accomplished through porous electrodes or temperature-dependent conductivity and provide a good start for determining how to maximize the rates of these processes, there is still a significant gap between macroscopic electrode’s current output and that measured for single cells. Although strategies like polymer encapsulation have been shown to help, knowledge of how to simultaneously optimize microbe ‘wiring’, local chemical environment, mass transport of reactants is not fully established. Further, the open question remains regarding the effects of discrepancies in the environment between those in microscopic single cell measurements (more open environment) and macroscopic electrodes (packed, extracellular matrix present). This is briefly summarized in Table 1 . Table 1 Summary of information conferred from microelectronic device measurements and limitations of the experiments Information Challenges, limitations Mediated vs. direct EET Device fabrication, experimental throughput Hopping vs. Metallic conductance Translating from macroscopic to nanoscale Single cell measurements, theoretical limits Chemical/biological basis behind data Table 2 Summary of unique information and challenges of QCM measurements applied to biohybrid systems Information Challenges, limitations Biofilm growth vs. time Qualitative rather than quantitative Hydration, ion/solvent movement in response to stimuli Chemical/biological basis behind data Window into electrochemically silent events Discrepancies in environment, mass transport between QCM cell, standard reactor Table 3 Steady-state spectroscopy and its strengths and limits when applied to the interrogation of biohybrid systems Information Challenges, limitations Identity of species involved in EET Spectral interpretation Chemical environment tracking Not all species give rise to strong spectral features Cellular response to electrochemical stimuli Selective probing of species besides cytochromes Table 4 Unique insights conferred from time-resolved measurements and the associated challenges that come with such experiments Information Challenges, limitations Kinetics of photoinduced processes Spectral interpretation Identity of electron/hole acceptor Translucent sample required, more difficult for photoelectrodes Efficiency of natural/synthetic charge conduits Charge flux from laser is much higher in typical experiment than photo(electro)chemical experiments Quartz-crystal microbalance QCM measurements run an oscillating voltage through a piezoelectric quartz substrate and the resultant substrate's oscillation frequency is directly proportional to the mass adsorbed overtop of it ( Sauerbrey, 1959 ). Further, the application of dissipation measurements (essentially measuring the time it takes for the quartz to stop oscillating once the voltage application stops) enables the determination of the film rigidity, which in turn provides information of biofilm composition. As such, this line of measurements is especially important in correlating the growth and physical characteristics of biofilms to the performance (e.g. current density, product formation) of the resultant biohybrid system. Further, QCM is a useful platform in measuring how surface chemistry, charge, and morphology influence initial bacterial attachment and film growth en route to functional biohybrid electrodes. It must be mentioned that the highly viscoelastic (not rigid) nature of biofilms renders the data from QCM measurements qualitative rather than quantitative. For electrochemical QCM measurements, the piezoelectric quartz chip is covered with a thin film of a conductive material to serve as the working electrode, and the solution containing microbes/electrolyte/reactant is flowed overtop. QCM measurements were initially used to correlate the growth of Pseudomonas cepacian cells with the biofilm mass, with non-linearities attributed to the formation of extracellular polymers ( Nivens et al., 1993 ). In the context of electroactive microbes, QCM measurements were used to evaluate G. sulfurreducens biofilms with a customized cell that enabled spectroscopic measurements to be performed on the same electrode ( Figure 3 A) ( Heidary et al., 2020 ). The goal of this work was to understand EET mechanisms in play during biofilm growth and operation in anodic and cathodic modes. A rapid increase of mass was noted as soon as the cells were injected into the media, whereas the current did not increase until 2 days later ( Figure 3 B). This was interpreted to signify that the delay in current was because of the necessity for the microbes to express cytochrome-based units used in their EET pathway. Further, switching from anodic mode (oxidation of acetate to CO 2 ) to cathodic mode (reduction of fumarate to succinate) did not significantly change the biofilm mass ( Figure 3 C), indicating that the decrease in reaction rates mainly stem from decreases in EET and/or metabolic rates of the microbes. Complementary QCM measurements of G. sulfurreducens biofilms also noted changes in film frequency during cyclic voltammetry cycles, suggesting a significant amount of solvent coming into/out of the biofilm during this process ( Babauta et al., 2014 ). This signifies that the morphology and resultant abundance of solvent diffusion pathways may be a critical parameter in influencing biohybrid electrode performance. Figure 3 Quartz-crystal microbalance probes of biofilms (A) Customized QCM cells enable correlating mass and viscosity changes with spectroscopic measurements (A) ( Heidary et al., 2020 ). (B and C) G. sulfurreducens biofilms increased in mass far before current increased (B) while switching to cathodic mode did not significantly alter the biofilm mass (C). Reproduced with permission from the American Chemical Society. Overall, these studies established that biofilm growth, EET machinery expression, and the onset of macroscopically measured currents are not always occurring simultaneously ( Table 2 ). Although the lag and exponential phase periods of currents typically are used as proxies for understanding what is happening in a growing biofilm, these studies call to attention the importance of understanding what is occurring prior to any significant current outputs and raise important questions of how processes during this electrochemically silent period will affect performance measured afterward. A powerful line of experiments to this end could be the simultaneous utilization of QCM, electrochemical analysis, and perhaps spectroscopic probing during these early stages to get a better handle of the evolving materials-microorganism interface."
} | 4,998 |
36557852 | PMC9785513 | pmc | 3,224 | {
"abstract": "Regarding the limited resources for fossil fuels and increasing global energy demands, greenhouse gas emissions, and climate change, there is a need to find alternative energy sources that are sustainable, environmentally friendly, renewable, and economically viable. In the last several decades, interest in second-generation bioethanol production from non-food lignocellulosic biomass in the form of organic residues rapidly increased because of its abundance, renewability, and low cost. Bioethanol production fits into the strategy of a circular economy and zero waste plans, and using ethanol as an alternative fuel gives the world economy a chance to become independent of the petrochemical industry, providing energy security and environmental safety. However, the conversion of biomass into ethanol is a challenging and multi-stage process because of the variation in the biochemical composition of biomass and the recalcitrance of lignin, the aromatic component of lignocellulose. Therefore, the commercial production of cellulosic ethanol has not yet become well-received commercially, being hampered by high research and production costs, and substantial effort is needed to make it more widespread and profitable. This review summarises the state of the art in bioethanol production from lignocellulosic biomass, highlights the most challenging steps of the process, including pretreatment stages required to fragment biomass components and further enzymatic hydrolysis and fermentation, presents the most recent technological advances to overcome the challenges and high costs, and discusses future perspectives of second-generation biorefineries.",
"conclusion": "3. Conclusions The production of second-generation bioethanol has several benefits in offsetting the general use of fossil fuels by increasing global supplies of liquid transport fuels in response to growing energy demand and improving energy security in regions devoid of fossil resource deposits. Thereby, bioethanol contributes to restricting worldwide dependence on fossil supplies and the petroleum industry, thus helping alleviate the energy crisis. Moreover, the transition from petroleum- to biomass-derived fuels reduces net carbon dioxide emissions per unit of energy produced and used, helping tackle anthropogenic climate change and its consequences for people and the environment. Lignocellulosic biomass used for bioethanol production seems to be a promising renewable energy source. To avoid conflicts of interest, biorefineries should focus on utilising agro- and industry-waste biomass rather than biomass used for animal feed. In this context, lignocellulosic feedstocks employed as an energy source are particularly beneficial. It is abundant, does not threaten food security, and is inexpensive since it can be derived from native vegetation (e.g., invasive species, forest residues and thinnings, and grass), discarded agricultural residues (corn stove and cereal straw), and even industrial urban waste rich in organic matter. Unfortunately, the production of cellulosic ethanol is highly challenging due to the complexity and recalcitrance of lignocellulose and the diversity of biomass. It requires several steps to release the energy-carrying carbohydrates from the lignocellulosic complex and convert them into ethanol, starting from biomass pretreatment through hydrolysis and fermentation. These three steps contribute their own unique bottlenecks in the entire production process, seriously affecting the final efficiency of the production process and generating high operating costs. Therefore, intensive research has been conducted to develop new technologies that are efficient, economically viable, and universal for various biomass types, while being environmentally friendly. Although significant progress has been made in this field in the past decade, including the development of advanced engineered microorganisms or attempts to combine pretreatment, hydrolysis, and fermentation, or part of them into a single, more efficient step, there are still several gaps between novel findings and practical applications. Some of the most crucial challenges include the following: the selection of a suitable pretreatment strategy that is cost-effective and does not impede the overall efficiency of enzymatic saccharification, the improvement of the anaerobic digestibility of biomass, limiting carbohydrate degradation and the generation of inhibitors during pretreatment to prevent conversion yield loss, downsizing the consumption of toxic chemicals, as well as energy and water, the improvement and application of novel biocatalysts that can enhance the efficiency of the saccharification process, increasing the efficiency of individual enzymes by designing enzymes with enhanced specific activity, thermal stability, and reduced end-product inhibition, and reducing the overall footprint of the process. Detailed knowledge about the structure and composition of different biomass types is required, as well as the effects of individual pretreatment techniques on various biomass materials at the macro and molecular scales. Additionally, a thorough study of the interactions between biomass, microorganisms, products, and by-products generated during hydrolysis and fermentation at the molecular scale is necessary to establish optimal conditions for those processes. The existing knowledge is broad, but even more comprehensive interdisciplinary research is still needed to bring bioethanol production into a profitable and pervasive light for commercial use. However, it should also be remembered that transitioning from a laboratory to a commercial scale is extremely difficult and requires additional pilot-scale studies with optimisation and high financial expenditure. As for now, it seems that just using lignocellulosic biomass as a sustainable feedstock for bioethanol production does not guarantee a successful transition from petroleum-based to renewable biomass-derived energy. It seems that the strategy to utilise all components of the lignocellulosic complex by employing cost-competitive manufacturing processes designed with green chemistry is more likely to succeed. The future of this energy sector will be integrated biorefineries that produce both energy and value-added components for the chemical industry based on green chemistry principles with respect to the environment. This is achievable through enhancing the efficiency of all used materials and energy, reducing waste production and toxicity, and reusing resources and by-products. Integrated biorefineries are gaining interest worldwide as they support the circular bioeconomy concept. However, greener processes and technologies are required, such as employing water-based reactions and environmentally friendly oxidants instead of materials and chemicals with high environmental burdens, or those using alternative energy-saving pretreatment methods, such as ultrasound or microwaves, which require time, effort, and financial investment. Since the 1970s, tremendous progress has been made to alleviate the use of fossil fuels. With the persistent passion of researchers worldwide, there is great optimism for the future of bioethanol from lignocellulosics. This review is meant to not only educate on bioethanol processes and their challenges, but also to illuminate novel and debatable research ideas that will tackle these challenges and build sustainable partnerships in an interdisciplinary fashion to combat the global energy crisis at hand.",
"introduction": "1. Introduction Concerning the continuously increasing global demand for energy, fossil fuel resources on our planet are anticipated to become depleted within the next several decades, endangering worldwide energy security. More importantly, the combustion of fossil fuels contributes to CO 2 emissions and hence global warming, a rise in sea levels, urban pollution, and loss of biodiversity, constituting a threat to the global environment. Therefore, the energy transition to low-carbon-intensity fuels becomes necessary to tackle climate change [ 1 , 2 ]. All these negative environmental, social, political, and energy security concerns of the current world has boosted interest in alternative energy sources, including biofuels. However, although alternative energy sources hold the key to solving the three critical global problems, i.e., energy demand and security and climate change ( Figure 1 ), the transition from fossil fuels to more sustainable energy resources require a high initial investment and innovative technologies. Therefore, employing an energy mix of fossil fuels, biofuels, and renewable energy sources seems to be a good starting strategy to switch to solely sustainable resources in the near future [ 1 , 2 , 3 , 4 ]. Biofuels emerged as a promising alternative to fossil fuels [ 5 , 6 , 7 ]. Among them, bioethanol is one of the most attractive as it can substitute gasoline [ 8 , 9 , 10 , 11 ]. As a result, several countries, including the USA, Brazil, China, Canada, India, Thailand, Argentina, and many EU members, have already proclaimed commitments to reducing their dependence on fossil fuels towards developing bioethanol production. However, industrial-scale bioethanol production still faces a severe challenge of suitable feedstock acquisition and economic viability while environmentally friendly production technology [ 1 , 12 , 13 ]. Bioethanol can be produced from a variety of renewable materials rich in carbohydrates, which can be hydrolysed to fermentable sugars and converted to ethanol. Three main feedstock types can be used for bioethanol production: sucrose and starch crops, such as cereals, sugarcane, corn, and others similar (the first-generation bioethanol) [ 14 , 15 , 16 ], lignocellulosic biomass (the second-generation bioethanol) [ 12 , 17 , 18 ], and microalgae (the third-generation bioethanol) [ 19 , 20 , 21 ]. The first-generation bioethanol constitutes the majority of over 27,000 million gallons (over 102,060 million litres) of bioethanol produced worldwide (status as of 2021), with the United States of America and Brazil being the indisputable leaders producing almost 85% of the global output mainly from corn and sugarcane, respectively ( Figure 2 ) [ 22 ]. On the other hand, France and Germany are the leading bioethanol producers in Europe ( Table 1 ). The primary feedstock for bioethanol production is wheat (in Belgium, Germany, France, and the UK), corn (in Central Europe, the Netherlands, and Spain), sugar beets (in France, Germany, the UK, the Czech Republic, Belgium, and Austria), as well as beet pulp or concentrated juice (in Austria and Belgium) [ 23 ]. However, the increasing bioethanol production levels, along with the growing population, raise concerns over the long-term sustainability of first-generation bioethanol, including a threat to global food and feed security, demand for land and water resources, and potential contamination of soil with distillation residues, which prompts intensive research on alternatives, such as second- and third-generation bioethanol production technologies [ 14 , 24 , 25 ]. Over the past few decades, the experience gained from first-generation bioethanol production has paved the way for new technologies enabling the utilisation of more sustainable feedstock without adverse effects on food supplies and the environment. Second-generation biorefineries are based on widely available lignocellulosic biomass generated from various sectors (see Section 2.1 ) that are not directly used as food, and new technologies to convert the biomass into ethanol and other valuable co-products have been continuously developed. Such an approach has the potential to meet energy demands sustainably in an economically viable and environmentally safe way [ 13 , 14 ]. The existing or planned second-generation biorefineries in the US with their production capacity are listed in Table 2 . Total cellulosic ethanol production for 2022 in Brazil is estimated at 55 million litres, with an increase of 15 million litres compared to 2021 [ 26 ]. In the European Union, there are only a few advanced biofuel plants producing second-generation bioethanol at a commercial scale ( Table 3 ); several others, based on sawdust, forest residues, cereal straw, and by-products from cellulose production, are planned to be opened soon in Finland, Norway, Slovakia, Romania, and Austria [ 23 ]. However, commercial production of second-generation bioethanol still represents only an insignificant share of total ethanol production worldwide. Second-generation bioethanol has gained increased interest from governments, large companies, and academic research over the past two decades since it represents an attractive renewable alternative to diminishing fossil fuels. Its production is also widely accepted by the general public as it is perceived as non-competitive with the food and feed market and can help mitigate climate change. However, the commercial production of cellulosic ethanol is still in its infancy, being hampered by the high cost of research and production, and tremendous efforts are required to make it more widespread and profitable [ 17 , 28 , 29 ]. In this paper, we present the state of the art in bioethanol production from lignocellulosic biomass, discuss the most challenging stages of the process, highlight the up-to-date solutions and technological advances that can increase the efficiency of fuel ethanol yield and reduce production costs, and debate future perspectives of second-generation biorefineries."
} | 3,395 |
23863124 | PMC3755335 | pmc | 3,226 | {
"abstract": "In Corynebacterium glutamicum formation of glc-1-P (α-glucose-1-phosphate) from glc-6-P (glucose-6-phosphate) by α-Pgm (phosphoglucomutase) is supposed to be crucial for synthesis of glycogen and the cell wall precursors trehalose and rhamnose. Furthermore, Pgm is probably necessary for glycogen degradation and maltose utilization as glucan phosphorylases of both pathways form glc-1-P. We here show that C. glutamicum possesses at least two Pgm isoenzymes, the cg2800 ( pgm ) encoded enzyme contributing most to total Pgm activity. By inactivation of pgm we created C. glutamicum IMpgm showing only about 12% Pgm activity when compared to the parental strain. We characterized both strains during cultivation with either glucose or maltose as substrate and observed that (i) the glc-1-P content in the WT (wild-type) and the mutant remained constant independent of the carbon source used, (ii) the glycogen levels in the pgm mutant were lower during growth on glucose and higher during growth on maltose, and (iii) the morphology of the mutant was altered with maltose as a substrate. We conclude that C. glutamicum employs glycogen as carbon capacitor to perform glc-1-P homeostasis in the exponential growth phase and is therefore able to counteract limited Pgm activity for both anabolic and catabolic metabolic pathways.",
"introduction": "INTRODUCTION The non-sporulating, Gram-positive, rod-shaped actinomycete Corynebacterium glutamicum is employed in the industrial-scale production of amino acids [ 1 ]. Moreover, this non-pathogenic bacterium is widely accepted as a useful model to depict metabolism and cell wall biogenesis of Corynebacterineae including the pathogenic Mycobacterium tuberculosis [ 2 – 4 ]. C. glutamicum utilizes various substrates, including sugars, organic acids and alcohols for growth and amino acid production [ 5 – 7 ]. In the course of cultivation in media containing sugars as carbon and energy source or when phosphate is limiting in the culture broth, C. glutamicum transiently accumulates large amounts of glycogen [ 8 , 9 ]. This transient accumulation of glycogen in C. glutamicum is different from the situation in other organisms [ 10 – 12 ] as the accumulated glycogen is already degraded in C. glutamicum in the course of the late exponential growth phase before the substrate is consumed and the stationary growth phase begins [ 8 , 13 ]. As generally described for bacteria [ 10 , 12 ], glycogen synthesis is catalysed in C. glutamicum by the consecutive action of the enzymes ADP-glucose pyrophosphorylase GlgC, glycogen synthase GlgA and the glycogen branching enzyme GlgB [ 8 , 14 , 15 ]. Besides, genes for the alternative α-glucan synthesis pathway via GlgE, recently identified in Mycobacterium and Streptomyces species [ 11 , 16 ], are also present in the C. glutamicum genome [ 17 , 18 ]. However, the contribution of the GlgE pathway to glycogen synthesis in C. glutamicum seems negligible, because inactivation of glgC as well as glgA abolished glycogen synthesis in C. glutamicum [ 8 , 15 ]. The substrate for ADP-glucose formation by GlgC, glc-1-P (α-glucose-1-phosphate) is generally formed from glc-6-P (glucose-6-phosphate) by α-Pgm (phosphoglucomutase) [ 19 – 21 ]. The Pgm reaction is reversible and in the direction of glc-6-P formation represents the last step of C. glutamicum glycogen degradation [ 13 , 22 ]. In addition, the Pgm reaction links the maltose and maltodextrin utilization pathways to the glycolysis, as in the course of these pathways also glc-1-P is formed [ 13 , 23 , 24 ]. In bacteria such as Escherichia coli , Bacillus subtilis and Streptococcus gordonii the inactivation of genes encoding Pgm enzymes brought about changes of the cell shape and size [ 25 – 28 ]. These morphological changes are probably entailed by the limited intracellular glc-1-P availability, as glucose-1-P functions as a precursor of various cell wall components in aforementioned bacteria. Analysis of the metabolic pathways deduced from the genome sequence of C. glutamicum [ 18 ] indicates that the Pgm catalysed formation of glc-1-P is also required for synthesis of the nucleotide sugars dTDP-glucose and UPD-glucose, two central intermediates in the synthesis rhamnose and trehalose, which both are essential cell wall constituents of Corynebacterineae [ 29 – 31 ]. Despite its central role in catabolism and anabolism, Pgm so far has only scarcely been studied in C. glutamicum . Pgm activity was shown to be present in cell extracts of C. glutamicum [ 13 ] and the ORF (open reading frame) cg2800 has been annotated as Pgm gene pgm based on sequence comparisons [ 18 ]. We recently found pgm to be up-regulated in response to phosphate limitation [ 9 ], however, the gene product of pgm has not been analysed and its role for both the transient accumulation of glycogen and the metabolization of maltose has not yet been studied. In addition, the levels of the central intermediate glc-1-P so far have not been analysed in C. glutamicum . We here characterize Pgm activity in C. glutamicum , identify the pgm encoded isoenzyme as main Pgm and study the consequences of pgm inactivation in C. glutamicum on growth, the intracellular glc-1-P and glycogen levels, and morphology in the course of cultivations when Pgm is supposed to be required either for anabolism or catabolism.",
"discussion": "DISCUSSION We here show that C. glutamicum possesses at least two Pgm isoenzymes, the one encoded by pgm contributing mostly to the total Pgm activity within the cells. Accordingly, Pgm activity in the C. glutamicum strain with inactivated pgm was approx. 9-fold lower when compared with C. glutamicum WT, but not completely eliminated as reported for pgm -deficient (or pcgA -deficient) mutant strains of E. coli , B. subtilis, Streptococcus iniae and Streptococcus gordonii [ 26 – 28 , 47 ]. This result corroborates the finding of a second protein with Pgm activity apart from the pgm gene product ( Figure 2 ). We used the pgm -inactivated strain to analyse the effects of limited Pgm activity on morphology, glycogen accumulation and intracellular concentrations of glc-1-P, an intermediate of glycogen metabolism and a precursor for the synthesis of nucleotide sugars and cell wall components such as trehalose and rhamnose [ 10 , 12 , 30 , 31 , 48 ]. Based on the proposed metabolic scheme for maltose and glycogen metabolism in C. glutamicum [ 13 ], and on the specific activities and kinetic properties of total Pgm in cell extracts of C. glutamicum IMpgm (this work), we selected cultivation conditions in which Pgm activity was supposed to limit either the conversion of glc-6-P to glc-1-P required for anabolism (cultivation on glucose) or vice versa the formation of glc-6-P from glc-1-P required for catabolism (cultivation on maltose). We observed drastic changes in cell morphology of C. glutamicum IMpgm cells in the course of cultivation with maltose as substrate. Changes of the cell shape and size caused by the inactivation of genes encoding Pgm enzymes have also been reported for E. coli , B. subtilis and S. gordonii [ 25 – 28 ]: whereas cells of a pgm deficient E. coli strain are approx. 70% shorter but also slightly wider than cells of the parental strain [ 26 ], cell diameters of pgm -deficient strains of both S. iniae and S. gordonii are increased [ 28 , 47 ]. For pgm -deficient B. subtilis strains different cell morphologies were observed. Lazarevic et al. [ 27 ] reported that B. subtilis pgm mutants adopt a spherical shape; however, the B. subtilis cells of the pgm -mutant described by Weart et al. [ 25 ] were shorter as cells of the parental strain but still rod-shaped. The lack of Pgm activity in these bacteria has been proposed to limit the availability of the common precursor glc-1-P and thereby to affect the synthesis of cell wall components such as the lipoteichoic acids in B. subtilis and Staphylococcus aureus [ 25 , 49 ], the LPS (lipopolysaccharides) of the outer membrane in Agrobacterium tumefaciens and Brucella abortus [ 50 , 51 ], and the capsular polysaccharides in Streptococcus pneumonia [ 52 ]. Also for C. glutamicum limited glc-1-P availability has been suggested to cause the drastically altered cell morphology and decreased viability in maltose-grown cells of C. glutamicum ΔmalP [ 13 ]. However, we exclusively observed elongated cells during cultivations of C. glutamicum IMpgm on maltose, cultivation conditions initially supposed to favour accumulation of glc-1-P. Albeit we did not observe significant alterations of the intracellular glc-1-P levels between C. glutamicum WT and C. glutamicum IMpgm in the course of cultivations with both glucose and maltose as a carbon source, the changes in the glycogen content in C. glutamicum IMpgm reflected the initially conceived changes in the availability of its precursor glc-1-P. As expected, the glycogen content in the pgm mutant strain was reduced in cells cultivated on glucose and increased in cells cultivated on maltose. Since glc-1-P is both a precursor and a degradation product of glycogen metabolism, it can be speculated that a constant level of glc-1-P in the course of cultivation is maintained by coordination of glycogen synthesis and degradation in C. glutamicum. Such a glc-1-P homoeostasis reflects the proposed role of glycogen as a carbon capacitor in Corynebacterianeae [ 22 , 53 ]. The concept of glycogen as carbon capacitor was initially proposed for Mycobacterium smegmatis as both excessive synthesis and recycling of glycogen were observed in the course of the exponential growth phase [ 53 ], an observation that does not fit to the generally accepted role of glycogen in non-sporulating bacteria as a long-term energy reserve required for the survival in substrate-limited environments [ 11 , 12 , 17 ]. For the latter function (i.e., slow degradation of glycogen in the course of the stationary growth phase), the energy necessary for maintenance in the absence of extracellular substrates is provided [ 11 ]. C. glutamicum , however, degrades the majority of the accumulated glycogen before the onset of the stationary growth phase and, moreover, survival of a glycogen synthesis-deficient strain, C. glutamicum IMglgC, was not reduced upon prolonged incubation when compared with the parental strain [ 8 ]. Since the reactions for glycogen synthesis and degradation take place simultaneously in exponentially growing C. glutamicum cultures [ 22 ], we adapted the concept of glycogen as a carbon capacitor also as a model for C. glutamicum . This function of glycogen as a carbon capacitor during growth is also supported by the recent findings of Koch-Koerfges et al. [ 54 ]. These authors found that exponentially growing cells of C. glutamicum show endogenous respiration in the absence of an external energy source, proceeding at a rate of approx. 50% of the respiration rate in the presence of glucose. In contrast, the endogenous respiration was significantly lower in cells starved for 3 h before the measurement. The first observation – high rate of endogenous respiration in the absence of external substrates – reflects the ability of C. glutamicum to degrade glycogen to level fluctuations in substrate availability whereas the second observation – low endogenous respiration in starved cells – reflects that glycogen is not a long-term storage compound in C. glutamicum . Taken further into account (i) the importance of the cell wall component and compatible solute trehalose for growth and viability of Corynebacterianeae [ 30 , 55 , 56 ], (ii) the abundance of interconnections between the pathways for glycogen metabolism and synthesis of trehalose in this group of bacteria (reviewed in [ 57 , 58 ]) and (iii) the interplay between glycogen metabolism and homoeostasis of glc-1-P (the precursor for both glycogen and trehalose synthesis) as shown here, the concept of glycogen as a carbon capacitor to metabolic (carbon) fluctuations seems quite reasonable. However, glycogen synthesis-deficient C. glutamicum strains (e.g., C. glutamicum IMglgC and C: glutamicum IMglgB) showed identical growth rates and final absorbance at 600 nm as the parental strain when cultivated in a CgC minimal medium with glucose as a sole source of carbon and energy [ 8 , 14 ]. The lack of a growth phenotype for glycogen synthesis-deficient C. glutamicum strains might be explained by the nearly constant and more or less optimal conditions in the course of the cultivations (i.e., shake flask experiments using well pH-buffered CgC minimal medium or pH-, pO 2 - and temperature-controlled batch-fermentations in small bioreactors). The importance of glycogen (metabolism) for growth and fitness of C. glutamicum might be observed in the course of large-scale industrial cultivations, when abiotic parameters repeatedly change. Our results indicate that a decreased intracellular availability of glc-1-P and thus, reduced levels of cell wall components are not responsible for the observed cell elongations in C. glutamicum strains. As morphology of both C. glutamicum ΔmalP and C. glutamicum IMpgm were changed in the course of cultivation with maltose and unaffected during cultivation with glucose, it seems reasonable that the accumulation of intermediates of the maltose metabolism, e.g., maltodextrins or the drastically increased accumulation of glycogen induce these morphological changes in C. glutamicum cells with abolished MalP or reduced Pgm activity."
} | 3,406 |
35311532 | PMC9040828 | pmc | 3,230 | {
"abstract": "ABSTRACT Pseudomonas aeruginosa is an opportunistic bacterial pathogen that exhibits pathogenicity in an unusually broad range of plants and animals, and it is of interest to study the roles of particular virulence-related factors in diverse hosts. The production of many P. aeruginosa virulence factors is under the control of a quorum sensing (QS) signaling network, which has three interconnected branches that engage in intricate cross talk: Las, Rhl, and MvfR. Because there has been no systematic comparison of the roles of the three QS systems in mediating P. aeruginosa virulence in various hosts, we compared the virulence of wild-type (WT) P. aeruginosa PA14 and a set of isogenic PA14 QS in-frame deletion mutants in four selected hosts, the reference plant Arabidopsis thaliana (Arabidopsis), the crop plant Brassica napus (canola), the nematode Caenorhabditis elegans , and the fruit fly Drosophila melanogaster . The first letters of the selected host genera, A, B, C, and D, inspired the title of this article and indicate that this work lays the groundwork for future elucidation of the specific roles of each QS branch in mediating virulence in diverse hosts."
} | 297 |
35566827 | PMC9101211 | pmc | 3,231 | {
"abstract": "Humins waste valorization is considered to be an essential pathway to improve the economic viability of many biorefinery processes and further promote their circularity by avoiding waste formation. In this research, the incorporation of humins in a Diels–Alder (DA) polymer network based on furan-maleimide thermoreversible crosslinks was studied. A considerable enhancement of the healing efficiency was observed by just healing for 1 h at 60 °C at the expense of a reduction of the material mechanical properties, while the unfilled material showed no healing under the same conditions. Nevertheless, the thermal healing step favored the irreversible humins polycondensation, thus strengthening the material while keeping the enhanced healing performance. Our hypothesis states a synergistic healing mechanism based on humins flowing throughout the damage, followed by thermal humins crosslinking during the healing trigger, together with DA thermoreversible bonds recombination. A multi-material soft robotic gripper was manufactured out of the proposed material, showing not only improved recovery of the functional performance upon healing but also stiffness-tunable features by means of humins thermal crosslinking. For the first time, both damage healing and zone reinforcement for further damage prevention are achieved in a single intrinsic self-healing system.",
"conclusion": "4. Conclusions Humins formation is a biorefinery issue of great concern; thus, new routes towards their valorization are needed to prevent waste formation and accumulation and to pave a path to improve the economic viability of their processes. In this research, it was demonstrated that humins blended into a reversible covalent polymer network facilitate the self-healing behavior under the proposed compositions and healing conditions. For classical furan-maleimide Diels–Alder systems, an energetic thermal treatment needs to be applied to unbind a sufficient amount of reversible covalent bonds to have a sufficiently high mobility for an efficient and effective healing process. It was shown that the humins enable healing of fatal damage and successful recovery of the mechanical properties at temperatures of 60 and 80 °C, where the pristine DA polymer network does not have the required reactivity and mobility for damage healing. The facilitation of the healing behavior by the humins is a result of physical processes aiding the subsequent reformation of Diels–Alder bonds as is well established for such self-healing materials. While partially phase separated, the humins provide a plasticizing effect on the polymeric network, improving the polymer chain mobility and creating an effective contact between the damage surfaces. The strong change in viscosity of the humins upon mild heating further facilitates the healing action at moderate temperatures of around 60 °C. Thus, lower temperatures are required to achieve an efficient mended state while keeping high mechanical properties compared to other reported DA networks. Moreover, the addition of a large fraction of humins improves the ecological and economic impact of the final self-healing blend by valorizing the humins waste stream. Thermal crosslinking of humins is detected during healing at more elevated temperatures. On the one hand, this poses a limit to the number of thermal healing cycles and thermal reprocessing cycles that can be performed. On the other hand, this can be exploited for the preparation of stiffness-tunable humins-based self-healable materials upon thermal treatment, which possess a higher stiffness than the raw DA material but also a better healing performance. It has been demonstrated that Humins-DA is a suitable and sustainable solution for the preparation of novel soft robotic systems that can be healed locally to recover their actuation performance while achieving a reinforced state, thus reducing any potential future damage at the healed zone. This approach mirrors for the first time the formation of protective calluses existing in biological systems on an artificial intrinsic self-healable composite. It should be noted that under mild healing conditions, e.g., at 60 °C, the stiffening effect was negligible, while the healing was also slower at these temperatures. At moderate temperatures, the contribution of the humins to the self-healing performance was purely of a physical nature and was thus an aiding mechanism to facilitate the healing by way of the reformation of Diels–Alder bonds. At more elevated temperatures, due to the crosslinking of the humins, the humins actively participated in the reformation of (additional) covalent crosslinks in a chemical manner, in addition to the physical facilitation.",
"introduction": "1. Introduction The sustainable production of organic chemicals, fuels, and materials that are able to replace the classic fossil fuel-derived analogues has been the main motivation of many biorefinery technologies. More precisely, the development of efficient bio-based plastics offers an attractive opportunity to substitute their petro-based counterparts using renewable resources [ 1 ]. An example of such materials is the so-called polyethylene furanoate (PEF), developed by Avantium Renewable Polymers BV, which satisfies the requirements to be a suitable candidate to complement, and eventually substitute, polyethylene terephthalate (PET) in both price and performance [ 2 ]. PEF synthesis involves the acid treatment of saccharides to obtain the platform molecule 2,5-furandicarboxylic acid (FDCA), followed by its polycondensation with glycols [ 3 ]. However, one of the main drawbacks of the acid-catalyzed processing of biomass-derived sugars is the unavoidable humins formation. Humins are a black, viscous, heterogeneous, highly polydisperse macromolecular side-product that arise from polycondensation reactions of sugar-derived furanic monomeric units, affecting the overall yield and economic viability of the process [ 4 ]. Researchers have worked intensively to understand the formation path and molecular structure of humins [ 5 , 6 ] and find strategies to suppress their production during the biorefinery process [ 7 ]. In addition, novel strategies towards their valorization have been explored, either via chemical treatment to obtain valuable platform molecules [ 8 , 9 , 10 ] or via the development of humins-derived materials. The latter has recently shown promising outcomes for the preparation and application of a wide variety of different materials, including thermoset resins [ 11 , 12 , 13 ], elastomers [ 14 ], bio-foams [ 15 , 16 ], and fibers [ 17 ]. Interest in the utilization of humins to obtain high added-value products is expected to grow as their valorization will encourage the circularity of biorefinery operations towards a zero-waste process. Despite the fact that the development of novel economically viable bio-based material formulations is a promising valorization route, either an appropriate degradation and/or recycling method or a way to extend these products life span is mandatory to avoid their landfilling or release to the environment after usage [ 1 ]. In this regard, self-healing (SH) polymers arise as an attractive approach to extend the service lifetime of plastics. These materials have the capability to repair their own structure after micro- or macroscopic mechanical damage is applied, avoiding material failure and recovering their initial mechanical performance [ 18 ]. One of the most extended classification criteria of SH materials is based on the healing mechanism. Hence, SH polymers can repair damage either by exhaustion of healing agents that are stored within microcapsules [ 19 ] or vascular networks [ 20 ] in a polymeric matrix, so-called extrinsic SH materials. Alternatively, healing can be done by the restoration of reversible links (supramolecular interactions or dynamic covalent bonds) inherent to the material chemical nature, known as intrinsic SH materials [ 21 ]. Extrinsic materials can heal autonomously under ambient conditions but only for a limited amount of healing cycles at the same damage location, as the healing agent is irreversibly consumed after the damage repair. On the other hand, intrinsic materials can, theoretically, be healed an infinite number of times, provided that the chemical nature remains unaltered. However, in most cases, an external trigger (heat [ 22 ], light [ 23 , 24 ], moisture [ 25 ], etc.) is required to enhance molecular diffusion enough to close the damage gap, bringing the reversible bonds back in contact and promoting the rearrangement of the matrix. SH polymers have found very promising applications in coatings [ 24 , 26 ], sensors [ 27 ], or robotics [ 28 , 29 , 30 ]. More precisely, the SH soft robotics upsurge has incited novel trends to find more eco-friendly solutions, as well as to enhance their performance and capabilities [ 31 , 32 ]. During the last decade, substantial progress has been made to divert conventional petroleum-based SH materials to more sustainable, bio-based alternatives [ 33 ]. The combination of natural polymers such as cellulose [ 34 ], alginate [ 35 ], chitosan [ 36 ], or lignin [ 37 , 38 , 39 ] with the required chemical modifications to provide healing ability have inspired an extensive variety of materials that orchestrate high properties versatility by tailoring their chemical structure design. Nevertheless, these materials (especially intrinsic SH materials) possess a relatively complex preparation process and require harsh external triggers and long healing timescales to accomplish an efficient repaired state [ 33 ]. To address these challenges, we report for the first time a polymer composite prepared by blending humins with a healable material based on thermoreversible Diels–Alder (DA) crosslinks using a furan-maleimide system. DA thermoreversible polymer networks and composites exhibit excellent healing performance by making use of temperature, often needing highly energetic thermal treatments for a complete material recovery [ 40 ]. Incorporation of viscous liquids within an elastomeric polymer matrix can provide a subsequent plasticizing effect. Plasticizers are known to increase the polymer chain mobility, thus enhancing the healing performance of intrinsic SH materials at the expense of the mechanical properties. However, humins can not only exhibit this plasticizing effect on the DA matrix, but also undergo irreversible intramolecular crosslinking via condensation reactions when exposed to moderate temperatures, hence influencing the final material stiffness and mechanical strength upon thermal postprocessing. The resulting stiffness-tunable material shows interesting properties to be further exploited as a new source for the preparation of SH soft robotics. To keep the mechanical properties of the actuator consistent when submitted to a healing thermal treatment, focalized healing using a welder is proposed to expose only the damaged zone to a thermal source, efficiently closing the cut and subsequently reinforcing the healed spot, thus preventing any potential future damage.",
"discussion": "3. Results and Discussion 3.1. Reactants Employed and Thermal Properties of the Synthesized Materials The chemical structures of the reagents employed for the synthesis are given in Figure 1 . Figure 1 d provides an accepted representation of the chemical structure of humins, bearing many furan groups with different substituents. The infrared spectrum of the humins ( Figure 1 e) is similar to those reported in literature [ 14 , 15 ]. The most important peaks are assigned and summarized in Table 1 . Both a high concentration of oxygenated functional groups, and an elevated proportion of unsaturations, were observed for humins composition. First, efforts were made to accomplish the straight DA reaction between the humins and the bismaleimide BMI689; however, the DA reactivity of the humins furan groups was too low to create a covalently crosslinked gel. It is well-known that electron-withdrawing substituents on the furan rings lower the reactivity towards the DA reaction [ 42 ]. The humins’ high chemical complexity, as well as the phase separation ensuing the bad miscibility of the two compounds, yielded a broad IR absorption which made monitoring this process via FT-IR not possible. For these reasons, another approach was taken in which the humins were blended with a furan-functionalized Jeffamine F400 and bismaleimide BMI689. The humins were mixed with the reactive compounds and the polymer network was formed in the presence of the humins. The final material can be considered as a semi-interpenetrating polymer network. An important question when developing Humins-DA materials is the choice of the optimal amount of humins. Proportions corresponding to 40:60 and 20:80 humins:DA ratios were also evaluated during the blend composition optimization process. On one hand, a 40:60 composition led to a sample overfilled of humins, being impossible to be properly handled. This occurred as a consequence of the sample high stickiness and very poor mechanical properties, even losing the morphology of the manufactured piece when manipulated. On the other hand, a 20:80 proportion exhibited a very poor dispersion quality of humins within the DA matrix, showing even by glance certain regions of the composite not filled with humins as a consequence of bad miscibility. In addition, lower humins loadings entailed a higher humins confinement within the highly crosslinked network, limiting their flow and not showing any visible difference in the healing behavior as compared to BMI689-F400. As a compromise, 30 wt% of humins were blended into the BMI689-F400 DA polymer network. Dynamic rheometry measurements were performed to assess the viscosity and viscoelastic response of the pure humins under different temperatures that could be suitable conditions as the thermal healing trigger ( Figure 1 f). The modulus of the complex viscosity (η*) changed four orders of magnitude from 10 5 to 10 1 Pa.s when heated stepwise from 20 to 100 °C. The proposed thermoreversible product requires a sufficiently high thermal stability to prevent material degradation during the healing process and during thermal (re)processing. Based on previous research, it is expected that temperatures higher than 100 °C are not needed to either achieve a fully healed state [ 43 ] or for most commonly applied thermal processing techniques on these DA-based polymer networks [ 44 ]. TGA experiments show no significant weight losses for the neat polymer matrix and the Humins-DA blend within the expected healing and (re)processing temperature range up to at least 100 °C ( Figure 2 a). Thus, temperatures up to 100 °C were chosen as potential healing temperatures to avoid any mass loss during the application and reprocessing of the material. The raw humins showed lower thermal stability, as a small weight loss was observed already at temperatures from 100 °C onward, suggesting gradual loss of small molecule fractions. While the weight loss was drastically reduced when confined in the reversible polymer network, special attention needs to be given to long exposures times at high temperatures, as the release of volatiles could lead to porosity generation and variations in the composite mechanical strength. Thus, a temperature of 60 °C (η* ≈ 10 2 Pa.s) was chosen in this research as a potential candidate to substantially lower the viscosity of humins while keeping their chemical nature as unaltered as possible and to thermodynamically favor the formation of the DA adducts. Under the proposed low healing temperature, low reaction medium mobility, low humins’ furans reactivity, and absence of a catalyst, it was not expected that any humins functionalities could side react with the proposed F400 and BMI689 monomers. To corroborate this assumption, FT-IR analysis of Humins-DA was performed, and the BMI689-F400 component was subtracted and compared to the raw BMI689-F400 polymer, showing no significant differences (See Figure S1, from Supplementary Materials ). DSC measurements ( Figure 2 b) show the influence of humins on the glass transition temperature (T g ) of the formed blend, analyzed by performing a heating/cooling cycle from −80 to 50 °C. A plasticizing effect was observed when adding humins with a low T g of around −26 °C to a polymer network with a higher T g . The incorporation of humins reduced the T g from 3.1 to −9.3 °C, enhancing polymer chain mobility. The single glass transition for Humins-DA implies that a homogeneous system was obtained by good mixing of the humins and the DA network. Compatibility and phase morphology are crucial aspects when preparing polymer blends. In contrast to the DSC measurements, phase separation was observed using SEM ( Figure 2 c), showing a droplet-matrix immiscible polymer blend morphology. Humins droplets could be observed throughout the DA matrix with a range of droplet diameters from submicron size up to several hundred μm. The humins were highly aromatic and polar, while BMI689 and F400 were aliphatic. The bismaleimide BMI689 was mostly apolar, while the furan-functionalized Jeffamine F400 was rather polar and expected to be somewhat compatible with the humins due to the polarity and presence of the furan molecules. The single T g observed in DSC ( Figure 2 b) was not in good agreement with the phase morphology observed in SEM. Since the humins droplet size confined within the DA network was big enough, it would be expected to observe to different T g , one for each component. The glass transition temperatures of both pure phases were only about 30 °C apart. Partial mixing of one phase into the other will induce a shift of the glass transitions of the two phases, possibly resulting in a single, broad transition. It was not possible to differentiate two transitions using the derivative of the heat flow signal to confirm this hypothesis. To the authors’ knowledge, this research shows for the first time the preparation of an immiscible polymer blend using humins. 3.2. Rheological Behaviour during the Gel Transition The influence of humins on the gelation behavior was derived using dynamic rheology. The gel transition temperature (T gel ), going from predominantly solid, elastic behavior to viscous, liquid-like behavior was determined according to Winter’s criteria as the point where the phase angle becomes frequency independent in a multi-frequency experiment [ 45 ]. For BMI689-F400, a T gel value of 123 °C was found ( Figure 3 a), whereas for the humins composite, no cross-point was observed. Still, a clear degelation transition of the polymer network could be observed as the phase angle increased for all the frequencies up to 80°, demonstrating clear viscous, liquid-like behavior ( Figure 3 b). Moreover, a significant decrease in the phase angle was visible at temperatures well above the T gel , which suggests an increase in the elastic behavior of the viscoelastic composite. This phenomenon could find its origin in either of three effects taking place during degelation or a combination thereof. First, humins can self-crosslink via post-condensation reactions under the studied thermal conditions, which is translated into an increase in humins M w that enhances the elastic performance of the composite. The thermal behavior of humins has been thoroughly investigated, reflecting the same curing behavior of humins on their viscoelastic properties, being able to reach T g values up to 80 °C at total reaction conversion [ 15 , 46 , 47 , 48 , 49 ]. This could bring some issues in terms of material thermal reprocessability as the internal structure of the composite can be influenced by extensive thermal treatments [ 50 ]. Second, this phase angle behavior was previously found for other composites based on thermally reversible polymer networks, for which it is hypothesized that the interactions between the solid particles forms a filler network, limiting the mobility of the unbonded furan and maleimide monomers in their liquid state [ 51 ]. The large polydispersity of humins involves not only small liquid molecules but also the presence of solid, high M w macromolecules which can also hinder the monomer mobility, holding the main role of the rheological properties above the gel transition. Finally, a minor weight loss was observed at temperatures above 100 °C for the pure humins and the composite, matching the region where the phase angles of the dynamic rheology experiment decreased. This mass loss of small molecules could entail an increasing average M w of the humins in the high temperature region of the experiment, where the material is in the liquid state. Furthermore, the incorporation of humins shifted the gel transition towards lower temperatures, due to the decreased concentration of furan and maleimide adduct bonds in the composite, shifting the Diels–Alder reaction equilibrium. 3.3. Mechanical Properties and Self-Healing Efficiency DMA experiments were performed to determine the mechanical properties of Humins-DA and compared to the pure BMI689-F400 network. The parameters studied were the fracture stress (σ), fracture strain (ε), and Young’s modulus (E) ( Table 2 ). First, it should be noted that the presence of humins reduced the fracture stress and Young’s modulus, while the fracture strain remained nearly unchanged. These results are in line with the plasticizing effect of the humins. It is hypothesized that, due to the high polydispersity of humins, the influence of big macromolecular clusters in terms of chain mobility when deformation is applied hinders the larger elasticity provided by the small molecules that act as plasticizers. Immiscibility of the phases can also induce interfacial slippage upon force application, thus diminishing sample yielding at large deformations due to the weak applied force transmission into the dispersed minor phase. To quantitatively appraise the healing efficiency of the proposed materials, sample specimens were cut in two pieces with a scalpel, and the cut parts were manually brought back into contact, commencing the healing action. Then, the samples were heated at 60 °C for 1 h, followed by a slow cooling to room temperature to restore the Diels–Alder equilibrium and, consequently, the crosslink density and mechanical properties. The healed materials were submitted to the same tensile testing conditions and the fracture properties were compared. The healing efficiency (η) is calculated as the ratio between the material property after healing and before damage. A clear healing performance enhancement was observed for Humins-DA, recovering an important part (roughly 80%) of its initial properties, while the original counterpart BMI689-F400 did not exhibit any healing under the same mild healing conditions. In addition, after applying such a healing process, an increase in the Young’s modulus of Humins-DA was observed as compared to BMI689-F400, showing a non-representative healing efficiency of 177%. This phenomenon is not realistic and can be attributed to intramolecular crosslinking of humins under such conditions within the polymeric matrix, translated into a stiffening development. Thus, humins post-condensation during the healing process, as well as during processing, could influence the material properties when exposing it to external thermal sources for successive times such as lower healing efficiencies due to humins restricted mobility upon crosslinking and mechanical properties strengthening. 3.4. Stiffening Effect upon Heating and Healing Mechanism Elucidation To gain insights into the stiffening effect observed during the thermal healing treatment, dynamic rheometry measurements were performed on the Humins-DA. An isothermal oscillatory time sweep was performed at 60 °C for several hours to monitor the changes in the viscoelastic properties. The results in Figure 4 a show no noticeable changes at short timescales, representative for the healing procedure. This is not in agreement with the DMA results obtained. Nevertheless, increasing the temperature to 90 °C demonstrated a noticeable difference in the storage modulus G’ value of Humins-DA. Subsequently, an oscillatory time sweep was performed on the raw humins at 60 °C to isolate the influence of temperature on their rheological behavior to be extrapolated to Humins-DA properties, i.e., without the influence of the elastic DA matrix on the thermo-rheological behavior. In this case, the results obtained ( Figure 4 b) displayed a steady increase of the viscoelastic response, even at short timescales where the healing experiments were occurring. The observed increase confirmed the hypothesis that humins intramolecular crosslinking influences the mechanical properties of Humins-DA upon healing, despite the fact that these changes are not visible for the composite rheology test. To elucidate the thermal stiffening influence on Humins-DA mechanical properties, fracture tests were performed on samples treated isothermally at 90 °C for increasing isothermal times ( Figure 5 a). Averaged mechanical properties parameters of the thermally annealed samples, together with the respective healing efficiencies at both 60 and 80 °C for 1 h, are summarized in Table 3 . As previously observed, there is a clear plasticizing effect upon incorporation of humins in the Humins-DA hybrid system. However, this can be partially compensated by thermally treating the sample, in this case at 90 °C. An enhancement of the Young’s modulus of Humins-DA from 2.46 to 4.38 MPa and 5.41 MPa was observed when heated at 90 °C for two and three hours, respectively. In addition, there was a partial compensation of the lost mechanical strength. The resulting material stiffness became higher than BMI689-F400 with a Young’s Modulus of 3.66 MPa. This stiffening effect emerged as a consequence of humins crosslinking within the DA network, increasing their M w . Longer thermal exposures entailed both a growth of fracture stress as well as a decrease in fracture strain. Thus, humins crosslinking exhibited a stiffening effect on the formed composite when thermally treated at the expense of the stretchability, since high M w humins fractions also acted as stress concentration points, making the binary composite system easier to be fractured. Hence, the humins served as a reinforcing filler due to the formation of bigger crosslinked macromolecular clusters, instead of a plasticizer. The stiffening effect of the humins on the composite also affected the self-healing properties. Figure 5 b exhibits the stress-strain curves of Humins-DA treated at 90 °C for 1 h. Samples healed for 1 h at 60 °C (blue) and 80 °C (red) were compared to the original stress-strain behavior (black). The healing efficiency at 60 °C of the thermally treated material drastically decreased compared to the untreated sample, as the plasticizing effect of the humins decreased. Healing at 80 °C for 1 h showed much higher mechanical properties recovery, resulting in a total strain recovery and a great development of the mechanical strength of the sample following further thermal treatment during the healing cycle at a more elevated temperature. Hence, the thermal treatment of the humins resulted not only in a stiffening effect on Humins-DA at small deformations but also entailed a great stress recovery of the sample properties. For the samples submitted to longer thermal treatments of two hours ( Figure 5 c) and three hours ( Figure 5 d), further mechanical strengthening was observed, as discussed previously. When the samples were healed, the recovery of the strain at break was limited as a consequence of the loss of plasticizing effect of the humins. Conversely, the stress at break was recovered completely after 1 h at 80 °C. Finally, no visible variations in the humins droplet morphology were observed when Humins-DA was submitted to a prolonged thermal treatment (See Figure S2, from Supplementary Materials ). The obtained results demonstrate that the humins play a crucial role, not only on the mechanical properties, but also on the Humins-DA healing performance. We hypothesize that there are synergistic mechanisms between humins and the DA crosslinked polymer that improve the healing behavior of the composite compared to the pure DA polymer network. This effect consists of the combination of two healing mechanisms in a single SH system: intermolecular diffusion carried out by humins and dynamic covalent bonds rearrangement derived from the DA network. Essentially, once a damage is applied to the material containing the humins, the viscous liquid components of humins are able to diffuse throughout the damage and enhance the wetting of the broken surfaces. This diffusive flow induces the mobility required by the DA system to bring the furan and maleimide moieties back in contact, which is normally achieved under the application of heat. Under the proposed conditions, as the DA reaction is thermodynamically favored at low temperatures, healing is efficient even under a mild thermal treatment if the surface contact is close enough. Due to humins high viscosity under ambient conditions, their incorporation is possible at high proportions (30 wt% in this research), while keeping high enough mechanical properties. Alternatively, it could be hypothesized that the healing mechanism first consists of a gluing effect of the humins followed by a post-condensation step. As humins are highly viscous at room temperature, the broken surfaces stick to each other upon contacting, due to the humins acting as a glue. Upon heating at 60 °C, humins can condense and increase the mechanical strength of the composite, both within the matrix and at the crack surface. Thus, a healing effect would be detected which is not directly related to DA bonds recombination but to humins diffusive recombination followed by thermal condensation. However, it can be argued that the viscosity of humins is not high enough to obtain the observed properties in the DMA results even after a mild thermal treatment and consequent condensation. Especially, the increase of the Young’s modulus and the high recovered stress and strain at break cannot be the result of humins post-condensation and subsequent Diels–Alder crosslinking is necessary to achieve the reported healing efficiencies. Similar approaches have been proposed for thermosets by the incorporation of thermoplastic polymers in blended [ 52 ] or semi-interpenetrated [ 53 ] polymer network systems. Upon heating above the thermal transition of the thermoplastic, the linear polymer flows into the crack, sealing the damage and recovering the mechanical properties upon solidification during cooling. To the authors’ knowledge, this is the first time that a similar principle is reported for elastomeric intrinsic self-healing polymers using an aiding mechanism based on a mobile agent under mild conditions. Thus, humins are a promising candidate to both enhance the healing performance of conventional thermoreversible SH materials and lower their cost by means of valorizing a biorefinery waste. 3.5. Humins-DA Reprocessability One of the greatest advantages that thermoreversible polymer networks offer is the combination of excellent mechanical strength as seen in traditional elastomers and their thermal reprocessability, by heating above the reversible gel transition temperature T gel or dissolving in a suitable solvent. This further promotes the sustainability of thermoreversible covalent networks besides their SH performance [ 44 ]. If the SH material is submitted to a too aggressive, unhealable damage (e.g., a robotic actuator working in a harsh environment) the material loses its functionality and needs to be replaced. A few approaches have been explored in literature to overcome large damage issues on SH materials, such as magnetically driven damage closure [ 51 ] or shape-memory assisted self-healing (SMASH) [ 53 , 54 ]. Unless SH materials have these added functionalities, reprocessing is the only valid route to revalorize the materials after unrepairable damage. In this research, it was observed that Humins-DA was extrudable at 100 °C, i.e., at a temperature well below T gel (see Figure 3 b), which highlights the possibility to (re)process the material at low enough temperatures during short processing timescales to limit the influence of humins post-condensation reactions on the properties to a minimum. The fact that the material could be extruded at temperatures below T gel was due to the well-differentiated flow behavior of the composite components and the reversible dynamics of the Diels–Alder reaction. On the one hand, the conversion of Diels–Alder-based polymer networks was above the critical gel conversion at temperatures below T gel , resulting in a crosslink density high enough to keep the gel structure at such temperatures. On the other hand, the reversible dynamics of the Diels–Alder reaction increased significantly and the viscosity of the humins decreased strongly with temperature ( Figure 1 f). Furthermore, upon high shear stress, it is not unlikely that reversible bonds are further broken during extrusion. The overall behavior is translated into a gel with low enough (visco)elastic properties and high enough dynamic reactivity, making it suitable to be manufactured under the designed conditions. Reprocessing also influences the polymer blend microstructure ( Figure 6 ). Some authors have reported DA-based polymer blends, observing nanosized droplets-in-matrix morphologies strongly influenced by the applied thermal treatments [ 55 ]. Intense mixing under high shear forces in the twin screw extruder has resulted in a much finer and homogeneous droplet morphology of the humins in the DA matrix (2–6 μm diameter). The fact that humins morphology can be controlled under shear flow in an immiscible blend allows a plethora of potential opportunities to tailor their morphology, and hence, the final blend properties. The mechanical properties of the extruded Humins-DA were assessed before and after healing under different conditions ( Table 4 ). First, it should be noted that the mechanical properties of the extruded specimens were higher than the untreated blend, undergoing a stiffening as also seen for the thermally treated samples ( Table 3 ). The Young’s modulus after extrusion at 100 °C was between the moduli of the blends that were thermally treated at 90 °C for 1 and 2 h. The fracture strain was similar to the thermally treated samples, while the stress at fracture was significantly higher than all thermally treated samples. Similar to the thermally treated samples, the healing efficiency after 1 h at 60 °C reduced compared to the untreated material, showing a considerable improvement by increasing the healing temperature to 80 °C. The healed samples showed a pronounced further stiffening with an increased Young’s modulus. The healing performance of the extruded samples after 1 h at 60 °C was lower than that of the non-extruded, thermally treated counterparts, while the healing efficiency at 80 °C for the extruded samples fell between those of the samples that were thermally treated at 90 °C for 1 and 2 h. From an application point of view, it is important to consider this aspect, as it can be assumed that the healing properties decrease after several reprocessing cycles, similarly to the annealed samples. Two potential explanations are given to elucidate these properties variations when comparing to the non-extruded Humins-DA. On the one hand, a lower healing efficiency can be explained by a reduction of the droplet size of humins. Smaller droplets, combined with a high interfacial tension, hinders humins flow out of the matrix confinement, thus limiting their influence in the healing mechanism. This confirms that the humins droplets morphology has an important influence on the healing mechanism, especially enabling healing at lower temperatures, by the hypothesized wetting of the damage surfaces and aiding the broken chain rearrangement and, hence, DA bonds reformation. On the other hand, considering the mechanical properties, two potential explanations could enlighten the observed variations. First, the short but highly energetic heating step performed during extrusion, together with the high applied shear forces, can induce a thermo-mechanochemical response on humins curing that accelerates their crosslinking reaction kinetics even at low timescales. Approaches such as on-line ATR-FTIR monitoring of polymer melts at the extruder barrel have been previously explored, showing promising potential applicability in the study of humins behavior during processing [ 56 ]. Second, smaller humins droplets confined within the DA matrix lead to a higher interfacial surface area. A faster gelation due to the DA higher conversion at the extrusion temperature (a gel is still present) followed by enhanced DA reaction kinetics at high temperatures, hinders humins droplets nucleation and growth. Thus, a finer humins droplet-matrix phase dispersion is achieved. As a consequence, a better dispersed phase can more efficiently distribute the applied load force, thus increasing the final mechanical performance. 3.6. Soft Robotic Gripper as a Multi-Material Demonstrator To explore the potential in an end-use application, the Humins-DA system was exploited in a soft robotic demonstrator. The high loading of the liquid humins strongly affects the elastic recovery of the material due to viscous losses. To overcome this issue, authors have reported the assembly of multi-material robotic structures combining two different samples with different mechanical properties, so that a more elastic phase can take care of the mechanical compliance while a less compliant but softer phase interacts with the environment, being easily healed under mild conditions [ 57 ]. The dynamic covalent bonds are also active at the interface, so the materials can be strongly fused together upon thermal treatment [ 30 ]. To manufacture the soft finger, a thermal pre-treatment was first applied on BMI689-F400 at 110 °C for 10 min to reduce the crosslinking concentration and obtain enough free furan and maleimide moieties at the sample surface for an efficient binding. Upon BMI689-F400 furan and maleimide moieties activation, the material fragments were brought in contact with a piece of Humins-DA and kept at 60 °C for 1 h to promote the (re)formation of DA interfacial bonds. A temperature of 60 °C was used to try to keep Humins-DA integrity and limit thermal stiffening to the greatest extent while an efficient fusion on the interface is obtained. As can be observed in Figure 7 a, a good interfacial contact was achieved under the proposed conditions for a multi-material assembly. Following the same procedure, a series of multi-material robotic fingers were created using the same method as Roels et al. to build a gripper ( Figure 7 b) [ 57 ]. The resulting assembled finger consisted of a BMI689-F400 base (yellow) fused to four Humins-DA phalanges (black), exhibiting an excellent interfacial connectivity and part flexibility as shown in Figure 7 c. A hole was drilled in each phalanx through which the tendon cable (nylon fishing wire) was routed. The holes were lined with Teflon tubing to avoid the tendon cutting into the soft material. The bending of the finger was characterized using the test setup as described in Section 2.4 . The flexing motion was achieved by pulling the tendon cable, and the finger returned to the initial position by recovering the elastic energy stored in the material when the tendon was released. The finger actuation performance is presented in Figure 7 d, observing a suitable bending motion for tendon-driven grasping actuation. The maximal achieved bending angle was 84°, measured as the angle between the horizontal axis and the line connecting base to tip. A common mode of failure in soft robotics is debonding of multi-material parts at the interface due to a lack of strong interfacial bonds. The use of self-healing polymers overcomes this problem. Four fingers were assembled in a square pattern to form a soft gripper that is able to pick up objects of different size and shape. As can be observed in Figure 8 a, even delicate objects can be manipulated without damaging. To corroborate the improved healing performance of Humins-DA compared to the BMI689-F400, the finger was cut in half using a scalpel blade. Subsequently, the broken parts were put back in contact and healed at 60 °C for 1 h. Figure 8 b shows how the Humins-DA component exhibited an excellent healing performance, whereas the BMI689-F400 broken parts remained separated, confirming previous observations. Global heating is undesired for real applicability since each healing cycle entails modifications on Humins-DA mechanical properties due to humins crosslinking. To overcome this issue, a hot tip welder heated up to 100 °C was used to execute a localized damage healing. Using this approach, not only was the damage successfully closed upon contacting for a few seconds, but this can also be used to reinforce the damaged zone by means of humins crosslinking, preventing future potential damage at the healed zone (see Figure 8 c). To automatize the healing process and make it more efficient, other methodologies such as optothermal healing could be considered for longer and more precise thermal exposures. Laser sources have already been proven as a suitable technique to perform localized healing thermal treatments [ 58 , 59 ]. Inspired by biology, this behavior resembles soft tissues able to grow calluses when subjected to aggressive mechanical friction or pressure, generating extra skin layers for protective functions. This research shows, for the first time, the formulation of an intrinsic self-healable system that can both heal and reinforce the heated zone, finding a promising suitability in the sustainable soft robotics field [ 31 ]."
} | 10,532 |
36406536 | PMC9670377 | pmc | 3,233 | {
"abstract": "Crevice corrosion accounts for 62% of the recorded breakdown\nof\ninsulators utilized in transmission lines, which may interfere with\nthe reliability of power utilities. To address these challenges, sustainable\nand resilient slippery lubricant-infused porous surfaces (SLIPS) are\ndeveloped on insulators to prevent electrochemically/biochemically\ninduced crevice corrosion especially occurring in tropical and coastal\nenvironments. The conventional way of developing SLIPS by chemical\nand physical etching might interfere with the mechanical stability\nof insulators composed of pin (galvanized steel), cement, and shell\n(porcelain). The current study proposes a noble concept of developing\nhierarchical patterned textured surfaces on insulators to fabricate\na resilient SLIPS coating without physical/chemical etching. The proposed\ncoating exhibits 99% antiadhesion performance against a mixed culture\nof bacterial strains, superior hydrophobicity (contact angle: 160°,\ncontact angle hysteresis: 4°), and crevice corrosion resistance\nperformance at elevated temperatures (25–75 °C) and humidity.\nThis study could facilitate a new route for the development of sustainable\nand highly reliable SLIPS coatings in the future.",
"conclusion": "4 Conclusions The study introduced a\nstrategy to develop lubricating oil-infused\nhierarchical patterned porous surfaces on insulators by utilizing\nthe EPDM lubricating oil-infused steric acid-modified cerium oxide\ncomposite (green composite) to prevent electrochemically/biochemically\ninduced crevice corrosion in the tropical and coastal environment.\nThe surface analysis results utilizing EDS, FTIR, and AFM suggested\nthe existence of EPDM lubricating oil-infused cerium stearate on the\nsurface. The superhydrophobic property (CA of 160° and CAH of\n4°) of the proposed composite (T2) before and after exposure\nto corrosion media at 25–75 °C was validated by contact\nangle measurements and macrographs. The schematic and the corresponding\nSEM micrographs revealed the superhydrophobic performance of the lubricant-infused\nhierarchical surface developed on treated substrate T2. This excellent\nwater-repelling performance and acquired stability have made the treatment\n(T2) ideal for usage in extreme conditions, including tropical and\ncoastal regions. The confocal and SEM images confirm the efficacy\nof the proposed treatment (T2) against the microbial population by\npreventing adherence (99%) and fatal effects (0.1%). The removal of\nthe dead bacterial population attached to the surface due to extremely\nlow surface energy is an added advantage. The antielectrochemical\ncorrosion property of the proposed composite was validated by image\nanalysis, potentiodynamic polarization, and electrochemical impedance\nspectroscopic studies. Thus, the proposed treatment is an encouraging\ngreen solution against electrochemical- and biochemical-inspired crevice\ncorrosion of insulators installed in tropical and coastal regions\nand leads to the safe operation of power utilities.",
"introduction": "1 Introduction The evidence so far suggests\nthat the presence of microbes inside\ncrevices frequently results in highly localized changes in electrolyte\nconstituent concentrations, pH, and oxygen levels. 1 − 3 The crevice\nbecomes oxygen-depleted, while the surrounding electrolyte gains oxygen,\nallowing this crevice system to exist. As a result, the material within\nthis crevice system serves as the anode, and the exterior serves as\nthe cathode, completing the redox system. The increase in M + ions within the material crevice causes an influx of chloride ions,\nwhich results in a net neutralization reaction. The metal chloride\nis then hydrolyzed to produce a free acid, resulting in an acidic\nreaction. 4 The hydrolysis reaction produces\nfree acid, which keeps the pH below 2, while the pH outside the crevice\nremains neutral. Because of the microenvironment and pH state, the\nelectrolyte within the crevice contains a high concentration of metal\nchloride ions, which are dissolved at near-total saturation concentrations.\nThe biofilm can accelerate oxygen depletion inside the crevice. The\nrespiring microbial colonies within the crevice become anodic, causing\nthe surrounding areas to become cathodic. Two different oxygen concentrations\nin two different locations result in a difference in electrical potential\nand, as a result, crevice corrosion. 5 , 6 Microorganism\ndevelopment has been evidenced in both ceramic and\nnonceramic insulators placed all over the world, particularly in tropical\nand subtropical conditions with high humidity, significant rainfall,\nand high temperature. It has been found that heterogeneous populations\nof bacteria, algae, moss, and fungus coexist in insulator biofilms.\nSingle-celled green algae, which is abundant in Asia, is the most\ncommonly discovered biofouling on insulators ( Figure 1 ). The intriguing part about dry algae colonies\non insulator surfaces is that they began to develop again when moist. 7 − 9 Figure 1 Global\nimplications of biofilm formation on crevice corrosion. According to published research, the formation\nof a biofilm layer\non the surface of an insulator poses a significant risk of crevice\ncorrosion within an insulator’s pin–cement crevice.\nCrevice corrosion causes crack propagation within the insulator, reduces\nflashover voltage by 30%, and induces surface leakage current. 10 Such conditions compromise the integrity of\nhigh-voltage insulators, as shown in Figure 1 . Considering the complexity of the situation,\nit is preferable to limit biofilm formation to avoid abrupt insulator\nfailure. Most of the available biofilm resistance methods deal\nwith either\nactive coating or passive coating. The first category emits biocides\nand antibiotics. 10 − 12 The other category includes antimicrobial chemicals\nthat are securely bound to surfaces, such as hydrophilic polymers\nand polycationic biocides. 13 The major\nlimitation of the first category is the uncontrolled release of biocides,\nwhich decreases over time. 13 Furthermore,\nboth types of coatings promote the formation of an extracellular polymeric\nadhering film and dead bacteria on coating surfaces, which eventually\ninhibits initial attachment and has no inhibitory effect over a longer\nstretch. On the other hand, antimicrobial resistance to the biofilm\nincreases at the same time. 14 − 16 Superhydrophobic surfaces\nhave attracted great attention as a green\nalternative to solve the existing issue. 17 The superhydrophobic surfaces consist of an air layer trapped by\nmicro/nanostructures that prevent direct contact between the corrosive\nfluid and the surface. The air layer cannot withstand high humidity,\nair pressure, and biological fluids. Thus, superhydrophobic surfaces\ncannot be a reliable alternative for the issue. 18 Over the last decade, surface modification technologies\nknown as\nslippery liquid-infused porous surfaces (SLIPS) or lubricant-impregnated\nsurfaces (LIS) have evolved. SLIPS coatings have a broad application\nin marine, biomedical, and construction industries due to their environment-friendly\nand reliable nature. 19 Until now, several\ntechniques for fabricating SLIPS have been used, including chemical,\nphysical etching, sol–gel synthesis, and so on. 20 However, chemical and physical etching interfere\nwith the mechanical stability of cement and porcelain materials. 21 Similarly, chemical and physical etching are\nnot safe for galvanized steel. 21 Keeping\nthis in mind, a few researchers have used the sol–gel technique\nto develop SLIPS. 21 , 22 However, nanopatterns are built\non surfaces rather than hierarchical patterns, which have a poorer\nlubricant retention ability than hierarchical patterns. The stability\nof SLIPS is based on the capability of surface textures to retain\nthe lubricant by capillary and van der Waals forces. 22 To the best of our knowledge, constructing hierarchical\npatterned textured surfaces on power insulators without using physical/chemical\netching has not been reported so far. In addition, coatings involving\ncerium are popular as an electrochemical corrosion-resistant material,\nbut its biochemical corrosion resistance has not been explored much. 23 The current study suggests a noble concept\nof developing hierarchical\npatterned textured surfaces on insulators to fabricate a robust SLIPS\ncoating without physical/chemical etching. The efficacy of the proposed\ntreatment has been evaluated systematically against electrochemically\nand biochemically induced crevice corrosion in a simulated tropical\nand coastal environment.",
"discussion": "3 Results and Discussion 3.1 Surface Morphology and Composition EDS was used to analyze the surface chemistry of the treated specimens.\nThe contents of unprocessed specimens (bare) were Zn (wt %): 89, O\n(wt %): 10.8, and Al (wt %): 4.1, with a roughness ( R a ) of 3.5 μm, as shown in Figure 3 a. In addition, treated specimens (T2) show\nC (wt %): 72, Ce (wt %): 20.8, and O (wt %): 9.1, with a roughness\n( R a ) of 9.5 μm, as shown in Figure 3 b. Figure 3 Surface analysis of (a)\nuntreated (bare) and (b) treated specimens\n(T2). The EDS results suggest that the EPDM lubricating\noil-infused steric\nacid-modified cerium oxide composite was adsorbed on the surface.\nIn the FTIR spectra of the deposited specimens ( Figure 3 b), peaks 2848 and 2920 cm –1 are attributed to the adsorption of C–H asymmetric and symmetric\nstretching vibrations, revealing the presence of EPDM. The carboxylate\npeaks are detected at 1448 and 1546 cm –1 , reconfirming\nthe adsorption of cerium stearate on the surface. 26 Stearic acid, CH 3 (CH 2 ) 16 COOH,\nis ionized to produce CH 3 (CH 2 ) 16 COO – ions and H + ions in the presence of a catalyst.\nThe CH 3 (CH 2 ) 16 COO – ions reside in the cathode region. However, H + ions combine\nwith electrons to produce H 2 . The Ce 3+ ions\nare oxidized to Ce 4+ ions. With the progress of the reaction,\nCe 4+ , Ce 3+ , and CH 3 (CH 2 ) 16 COO – react and adsorb on the treated\nspecimens (cathode). Cerium stearate is adsorbed on the surface to\nform microstructures; meanwhile, emitting H 2 facilitates\nthe formation of micro/nanostructures. 26 Thus, the roughness ( R a ) of the treated\nspecimen changes to 9.5 μm, as shown in Figure 3 b. The chemical processes can be explained\nusing Figure 4 . Figure 4 Chemical reaction\nbetween Ce ions and stearic acid. The particle size of Ce(III) stearate and Ce(IV)\nstearate was measured\nto be 10 μm on average by a particle analyzer. 3.2 Surface Wettability The wettability\nof the surface is influenced by factors like surface morphology and\nsurface topology. To operate effectively in harsh tropical or coastal\nenvironments, the treated insulator should be water repellent, as\nwater infiltration in insulator microcracks is primarily responsible\nfor crevice corrosion and other corrosion. The hydrophobic performances\nof untreated (bare) and treated specimens (T1 and T2) are compared\nin Figure 5 a. The untreated\nspecimens depict a contact angle (CA) of 60° and a contact angle\nhysteresis (CAH) of 150°. After treatment, specimen T1 depicts\na CA of 150° and a CAH of 10°. Figure 5 Wettability performance\nof (galvanized steel and cement) specimens.\n(a) Contact angle measurements at the planer surface. (b) Water-repelling\nperformance of water droplets on bare and treated specimens; schematic\nof the water–surface interface of the bare and treated specimens\nand the corresponding surface morphology. At the same time, specimen T2 depicts a CA of 160°\nand a CAH\nof 4°. T1 specimens comprise higher CA due to higher surface\nroughness, a lower actual contact area, and a long carbon chain of\nstearic acid adsorbed on globular cerium stearate that supports nanosheet\nformation (hierarchical structure; Figure 5 b). However, due to higher CAH, the water\ndroplets could not slide off the treated substrate, as shown in Figure 6 a. Figure 6 Sliding performance of\nwater droplets on treated specimens at the\nsliding position: (a) T1 and (b) T2. T2 specimens show higher CA and CAH due to the\npresence of the\nEPDM-based lubricant oil as a top layer in addition to the hierarchical\nstructure ( Figure 5 b). The nanosheets on the surface of microspheres and in the gaps\nbetween them can provide enough capillary force to retain the EPDM\nlubricating oil. Due to the presence of the lubricant, the water droplet\nrolls off the substrates, as shown in Figure 6 b. The CA and CAH measurements were carried\nout on both untreated and treated substrates cut from the insulator,\nsuch as pins (galvanized steel) and cement specimens, as shown in Figures 5 b and 6 a,b. In addition, contact of bare and treated specimens (T1\nand T2) with water and corresponding micrographs revealing the morphology\nof treated specimens are depicted in Figures 5 b and 6 a,b. For the evaluation of the stability of treated specimens in harsh\nconditions, the hydrophobic performance was re-examined after exposure\nto corrosion media for 90 days at a temperature range of 25–75\n°C (see Figure 7 ). The CA of specimen T1 reduces to 115° and its CAH increases\nto 16°. The reason could be the solubility of stearate-based\nnanosheets under harsh conditions. 27 However,\nT2 specimens have shown stable CA and CAH under harsh conditions.\nThe probable explanation could be that due to lower CAH, the corrosive\nsolution droplets could easily roll off the substrate. The liquid\nrepellency attitude of T2 specimens under any condition is attributed\nto the EPDM lubricating oil on the top layer. If the substrate has\ncrevices/microcracks, the lubricant will penetrate the crevice and\nprevent the entry of liquid/corrosive liquid, which is the source\nof crevice corrosion. This excellent performance has made the treatment\n(T2) ideal for usage in extreme conditions, including higher temperatures\nup to 75 °C. 28 Additionally, the aged\nsamples T2 underwent five cycles of simulating rainstorms to test\ntheir lubricant resilience against stress and gravity. Figure 8 a,a′ depicts the experimental\nsetup. The flowing water (five cycles) from the setup’s output\nwas subjected to XPS ( Figure 8 b), but no evidence of the EPDM lubricating oil was discovered.\nThe stability of the lubricating oil was further reconfirmed by the\nNoack volatility test. Only 7% of the EPDM lubricating oil was lost\nwhen heated over >75–100 °C for 15 min (see Figure 9 ). The results are\nin line\nwith silicone oil (200 cSt). Thus, it is confirmed that the proposed\napproach for SLIPS fabrication is stable. Figure 7 Wettability performance\nafter exposure to corrosive media with\nvarying temperatures from 25 to 75 °C: (a) contact angle measurements\nand (b) contact angle hysteresis measurements. Figure 8 Experimental setup to examine the stability of T2 (a,a′).\nIn flowing water/rain at horizontal and vertical positions. (b) XPS\nof liquid media coming out from the outlet of the setup (a,b). Figure 9 Volatility results for the lubricating EPDM oil. 3.3 Antibiofilm Performance The accumulation\nof bacteria, diatoms, and other microorganisms on the surface of the\ninsulator is primarily responsible for biofilm development. Since\na biofilm may change the microenvironment of crevices, it causes significant\ncrevice corrosion. Reduced biofilm development can considerably reduce\nthe massive damage caused by the future establishment of crevice corrosion,\nbiocorrosion, and macrofouling biological populations. For biofilm\nantiadhesion testing, a mixed culture of A. ferroxidans ATCC 23270 and T. organoparus Markosian\nATCC 27977 bacterial strains was chosen. The three substrates bare,\nT1, and T2 were kept in the bacterial suspension for 90 days and studied,\nas shown in Figure 10 . The bare substrate was covered with a dense layer of living cells\n(green), resulting in biofilm development, as illustrated in Figure 10 a by confocal and\ncorresponding SEM micrographs. The treated specimens (T1 and T2) showed\nantiadhesive performance against the bacterial population. Figure 10 Biofilm resistance\nperformance of treatment: (a) antiadhesion performance,\n(b) fatal effect, and (c) schematic of the biofilm resistance efficacy\nof T2. The confocal and SEM micrographs of the treated\nsubstrate (T1)\nshow minimal bacterial adherence and simultaneous fatal effect (red)\non the attached bacterial population. The corresponding SEM micrographs\ndemonstrate bacterial cell wall breakdown of the attached bacterial\npopulation. The reason might be the fewer attachment points of the\nhierarchal structure formed on specimen T1 and the bactericidal effect\nof Ce (see Figure 10 a). 29 For specimen T2, the confocal micrograph\ndepicts no bacterial adhesion. The reason might be that even if a\nsmall number of bacteria clings to the substrate and die, the dead\nbacterial population does not bind to the substrate for an extended\nperiod due to the extremely low surface energy of the top EPDM lubricating\noil, and the result is reconfirmed by the corresponding SEM micrograph\n(see Figure 10 a).\nThe fatal effect of Ce(III) stearate and the EPDM lubricating oil-infused\nCe(III) stearate composite was reconfirmed by the CFU/mL test, as\nshown in Figure 10 b. The schematic of the antibiofilm and bactericidal efficacy of\ncomposite T2 is represented in Figure 10 c. The statistical analysis reveals that\nthe adhesion ratios for bare and treated substrates (T1 and T2) were\n63.3, 3.8, and 0.1% respectively. The proposed treatment (T2) illustrates\ndual protection from the microbial population by prevention of adherence\n(99%) and fatal effect (0.1%). The removal of the dead bacterial population\nattached to the proposed treatment (T2) due to extremely low surface\nenergy is an added advantage. 3.4 Anticorrosion Performance The anticorrosion\nperformance is an essential assessment for coatings applied to insulators\ninstalled in tropical and coastal regions. To evaluate the corrosion\nperformance of the proposed treatment, the bare and treated substrates\n(T1 and T2) are studied after exposure to corrosion media for 90 days\nat 25–75 °C, as shown in Figure 11 a–c. The untreated crevice can quickly\ndevelop localized corrosion in the presence of corrosive fluids, leading\nto crevice or pitting corrosion. The topology of the crevice formed\nin metal–nonmetal joints is most susceptible to local corrosion\nunder harsh microenvironments. 30 − 32 Thus, the crevice of pin (galvanized\nsteel)–cement was studied to evaluate the progress of any local\ncorrosion in the bare and treated substrates. The crevice found in\nthe untreated and T1 treated pin–cement joint reveals symptoms\nof corrosion in pin (galvanized steel) and cement deterioration, as\nexhibited in Figure 11 a,b. The early indications of deterioration in the pin–cement\njunction found in T1 treated specimens may be caused due to solubility\nof cerium stearate under very harsh conditions. However, the excellent\ncorrosion performance of the T2 treated specimen is related to stable\nlubricating oil (EPDM oil) and the hierarchical structure that serves\nas a barrier against penetration of corrosive fluids inside the crevice.\nAdditionally, potentiodynamic polarization and electrochemical impedance\nspectroscopic studies were performed to reconfirm the corrosion resistance\nproperties of the treated specimens (see Figure 12 ). Figure 11 Anticorrosion performance of bare and treated\npin (galvanized steel)–cement\njoint specimens after exposure to corrosion media for 90 days at 25–75\n°C: (a) bare, (b) T1, and (c) T2. Figure 12 (a) Tafel polarization curves. Electrochemical impedance\nspectroscopic\nstudies: (b) Bode magnitude plots, (c) Bode phase plots, and (d) Nyquist\nplots. The corrosion current density, I corr , and the corrosion rate (CR) for the bare specimen\nare highest (4.61\n× 10 –6 A/cm 2 and 5.41 × 10 –2 mm/Y, respectively) over the treated specimens (T1\nand T2). However, T2 has I corr and CR\n1 order of magnitude lesser than T1 (see Figure 12 a). The Bode and Nyquist plots represent\nthe highest capacitance for T2, which is also in line with the previous\nfindings (see Figure 12 b–d). Therefore, the proposed composite T2 exhibit the best\ncorrosion resistance against biochemical and electrochemical corrosion."
} | 5,039 |
28206708 | null | s2 | 3,236 | {
"abstract": "The current upper thermal limit for life as we know it is approximately 120°C. Microorganisms that grow optimally at temperatures of 75°C and above are usually referred to as 'extreme thermophiles' and include both bacteria and archaea. For over a century, there has been great scientific curiosity in the basic tenets that support life in thermal biotopes on earth and potentially on other solar bodies. Extreme thermophiles can be aerobes, anaerobes, autotrophs, heterotrophs, or chemolithotrophs, and are found in diverse environments including shallow marine fissures, deep sea hydrothermal vents, terrestrial hot springs-basically, anywhere there is hot water. Initial efforts to study extreme thermophiles faced challenges with their isolation from difficult to access locales, problems with their cultivation in laboratories, and lack of molecular tools. Fortunately, because of their relatively small genomes, many extreme thermophiles were among the first organisms to be sequenced, thereby opening up the application of systems biology-based methods to probe their unique physiological, metabolic and biotechnological features. The bacterial genera Caldicellulosiruptor, Thermotoga and Thermus, and the archaea belonging to the orders Thermococcales and Sulfolobales, are among the most studied extreme thermophiles to date. The recent emergence of genetic tools for many of these organisms provides the opportunity to move beyond basic discovery and manipulation to biotechnologically relevant applications of metabolic engineering. WIREs Syst Biol Med 2017, 9:e1377. doi: 10.1002/wsbm.1377 For further resources related to this article, please visit the WIREs website."
} | 420 |
38966388 | PMC11223650 | pmc | 3,237 | {
"abstract": "While poly (3-hydroxybutyrate) (PHB) holds promise as a bioplastic, its commercial utilization has been hampered by the high cost of raw materials. However, glycerol emerges as a viable feedstock for PHB production, offering a sustainable production approach and substantial cost reduction potential. Glycerol stands out as a promising feedstock for PHB production, offering a pathway toward sustainable manufacturing and considerable cost savings. The identification and characterization of strains capable of converting glycerol into PHB represent a pivotal strategy in advancing PHB production research. In this study, we isolated a strain, Ralstonia sp. RRA (RRA). The strain exhibits remarkable proficiency in synthesizing PHB from glycerol. With glycerol as the carbon source, RRA achieved a specific growth rate of 0.19 h −1 , attaining a PHB content of approximately 50% within 30 h. Through third-generation genome and transcriptome sequencing, we elucidated the genome composition and identified a total of eight genes ( glpR , glpD , glpS , glpT , glpP , glpQ , glpV , and glpK ) involved in the glycerol metabolism pathway. Leveraging these findings, the strain RRA demonstrates significant promise in producing PHB from low-cost renewable carbon sources.",
"conclusion": "Conclusion In this study, we successfully identified and characterized a potential strain capable of efficiently utilizing glycerol to produce PHB. Through phylogenetic analyses, we provided valuable insights into Ralstonia sp. This research sheds light on the potential of this bacterial genus. The newfound strain exhibits significant promise for producing various products from low-cost renewable carbon sources.",
"introduction": "Introduction Poly (3-hydroxybutyrate) (PHB), the most extensively studied member of the polyhydroxyalkanoates (PHAs), represents a class of biodegradable and biocompatible polyesters. PHB exhibits a diverse array of chemical structures, physical properties, and thermoplastic characteristics ( Chen, 2009 ; Gao et al., 2011 ; Chen and Patel, 2012 ), rendering it highly promising for applications in biomedical, food, and environmental fields ( Chen, 2009 ; Gao et al., 2011 ). Researchers have been actively engaged in advancing the commercialization of PHB ( Chen and Patel, 2012 ; Chen and Hajnal, 2015 ). The cost of raw materials has emerged as a substantial constraint, representing over half of the total production expenses ( Tyo et al., 2010 ; Yu et al., 2019 ). Over the past three decades, progress in metabolic engineering has facilitated the synthesis of PHB from a range of feedstock, including glycerol, fatty acids, industrial waste, and sugars ( Wang et al., 2013 ; Chen and Jiang, 2018 ; Sirohi and Pandey, 2019 ; Li and Wilkins, 2020 ; Sirohi et al., 2020 ). Among these options, glycerol stands out as an exceptionally attractive substrate for PHB production, offering a high degree of reduction and cost-effectiveness ( Koller et al., 2008 ; Cavalheiro et al., 2009 ). Currently, a diverse array of potential PHB-producing strains has been documented, including Ralstonia eutropha ( Cupriavidus necator ) ( Xu et al., 2010 ), Aquabacterium sp. ( Westbrook et al., 2019 ), Halomonas campaniensis ( Russmayer et al., 2019 ), Rhodospirillum rubrum ( Zhang et al., 2022 ), Pseudodonghicola xiamenensis ( Feng et al., 2023 ), Rhodococcus sp. ( Yue et al., 2014 ), Priestia megaterium ( Sznajder and Jendrossek, 2011 ), Streptomyces sp. ( Mostafa et al., 2020 ), Erythrobacter aquimaris ( Trakunjae et al., 2021 ), Rhodospirillum rubrum ( Vázquez et al., 1996 ), Burkholderia spp. ( Krishnan et al., 2017 ; Mostafa et al., 2020 ), Pandorea sp. ( Narancic et al., 2016 ), and so on. Among these, strains capable of converting glycerol into PHB have been identified, with Bacillus sp. and Cupriavidus sp. being commonly reported. Additionally, it is worth noting that bacteria are not the only organisms demonstrating excellence in PHA production from glycerol; certain archaea, such as Haloferax mediterranei ( Coutinho de Paula et al., 2019 ), also exhibit promising capabilities in this regard. Expanding the strain library for PHB production is paramount, especially for Gram-negative bacteria with thinner cell walls. Additionally, it is essential to explore wild-type strains with industrial potential and to strategically design and construct PHB cell factories. This study aimed to isolate and characterize a potential strain capable of efficiently utilizing glycerol to produce PHB. Recently, we have isolated a strain from R. eutropha H16 cultures with an excellent ability to consume pure glycerol for growth and PHB accumulation. The characterization of this strain offers valuable insights and enhances our understanding of the PHB production potential within the Ralstonia genus. One of the significant advantages of the biodiesel boom has been the substantial decrease in the market price of glycerol ( de Paula et al., 2017 ; Oliveira-Filho et al., 2021 ), which currently ranges from approximately $566.42 to 599.33 per ton. This approach presents a novel solution by connecting the utilization of the chemical by-product glycerol with the production of a high-value, low-cost product, PHB, thereby achieving cost-effectiveness. Furthermore, the versatility of the novel bacterium suggests the potential for genetic engineering to expand its capability to produce a diverse array of products.",
"discussion": "Discussion In this study, the strain RRA was isolated and identified from Cupriavidus necator cultures with an excellent ability to utilize glycerol. The ANI analysis, whole genome alignment analysis, and evolutionary tree analysis were implemented to identify RRA as a branch of Ralstonia sp., and after analysis of its genome and transcriptome, we found that it has two potentially high-value products, PHB and NI-siderophore. Its native PHB synthesis gene could be heterologously expressed in E. coli by a constitutive or inducible promoter, allowing it to synthesize PHB. The increasing concern for energy and environmental sustainability has led to extensive research into improving green processes for converting sustainable resources into biochemicals ( Mortazavi et al., 2008 ). Identifying the strain RRA has provided insight into the Ralstonia sp. and a new potential strain to produce PHB. Ralstonia sp. has received a lot of attention in the last two decades for its excellent PHB production and has been used by many researchers as a model PHB-producing bacterium. R. eutropha was discovered and classified in Germany in the 1960s and was first designated as Hydrogenomonas eutropha due to its capability of utilizing molecular hydrogen and carbon dioxide as sole energy and carbon sources ( Blin et al., 2023 ). The name tree has six items in four decades until Cupriavidus necator and Wautersia eutropha were considered as one species ( Schlegel et al., 1961 ; Davis et al., 1969 ; Makkar and Casida, 1987 ; Kumar and Kim, 2018 ; Nurjadi et al., 2020 ) ( Supplementary Figure S4 ). In this study, we observed distinctions between RRA and strain R. insidiosa based on both 16S rRNA sequences and ANI analysis, which suggests that RRA may represent a novel genus of bacteria. Nevertheless, these differences lie on the borderline of species classification. For instance, ANI analysis revealed a similarity of 94.3%, which is slightly below the customary 95% threshold for species classification. Nevertheless, the current limitations that prevent further phenotypic analyses of RRA and R. insidiosa mean that any reclassification of RRA as a new species is, at this stage, only speculative. In recent times, the development of sustainable and environmentally friendly materials has attracted the attention of researchers as potential alternatives to petroleum-based materials ( Yabuuchi et al., 1995 ; Vandamme and Coenye, 2004 ). Biodegradable microbial polyesters have been regarded as potential candidates to replace traditional petrochemical-derived plastics in a circular economy, especially in agricultural applications ( Vaneechoutte et al., 2004 ; Sharma et al., 2023a ). For instance, straw cellulose is a renewable and biodegradable material with the potential to be developed into cellulose nanofibers in agriculture. Such nanofibers could be used as a carrier for the delivery and release of fertilizer ( Sharma et al., 2023b ; Koshy et al., 2024 ). The recognition of such biomaterials as a solution to the problems of a sustainable, circular economy is becoming increasingly prevalent. At present, research on polyhydroxyalkanoates (PHAs) attracts more attention due to potentially wide applications based on their biocompatibility, biodegradability, and structural diversity ( Kasirajan and Ngouajio, 2012 ). However, the production cost is still the greatest challenge hindering the expansion of the commercial PHB market ( Tyo et al., 2010 ). The selection of feedstock plays a critical role in determining the economic feasibility and sustainability of the process. The production of PHAs from various biomass feedstocks such as glycerol, lignin, cellulose, and agro-industrial wastes has the potential to reduce the reliance on virgin materials and minimize waste, thereby enabling the establishment of a closed-loop system within a circular economy. Lignin is a particularly abundant renewable resource that has the potential to be utilized as a biomass feedstock for the synthesis of PHB ( Sharma et al., 2023c ). R. eutropha ( C. necator ) H16 was observed to accumulate biopolymer (PHA 0.6 g/L) using lignin derivatives as the sole source of carbon ( Sharma et al., 2023d ). The strain R. eutropha is capable of converting lignocellulose biomass to PHB. It can accumulate 11.4 g/L of PHB after 48 h of fermentation using rice straw as a feedstock ( Moradali and Rehm, 2020 ). Glycerol-based waste materials are more readily processed and obtained than lignin and its derivatives. Crude glycerol is the chief by-product of biodiesel-producing industries, and the market price is low ( Tomizawa et al., 2014 ; Chauhan et al., 2022 ). Hence, utilization of glycerol could provide a sustainable production model and significantly reduce the production cost of biopolymers. Bacillus sp. are capable of efficient production of PHB using glycerol or crude glycerol. The maximum PHB accumulation was obtained as 2.80 g/L using glycerol through B. megaterium ( Saratale and Oh, 2015 ). Bacillus sp. ISTVK1 can accumulate 85.19% cell dry weight of PHA at optimized conditions using crude glycerol for the synthesis of PHA ( Anitha et al., 2016 ). In this study, the RRA strain was able to accumulate 2.25 g/L of PHB in glycerol at 48 h, which exhibited excellent ability to convert glycerol to PHB, yielding 0.45 g/g glycerol. In addition, the strain RRA showed an excellent capacity for glycerol metabolism, and the specific growth rate reached 0.19 h −1 when using glycerol as the sole carbon source, significantly faster than that of R. eutropha . The wild-type R. eutropha was completely unable to grow in a medium with glycerol as the sole carbon source. Therefore, for the construction of engineered strains using glycerol as a substrate, the isolated wild-type RRA strain has greater potential. Furthermore, Ralstonia sp. should be expected to conduct genetic manipulation for the production of a wide range of products from glycerol. The field of low-carbon resources used by microorganisms currently faces significant challenges ( Gómez Cardozo et al., 2016 ; Mota et al., 2017 ). In particular, the adaptive evolution of substrate utilization combined with selection is a promising approach ( Morya et al., 2018 ). However, isolation and identification of new strains are also efficient strategies that could reduce the time costs of strain evolution and modification ( Grim et al., 2020 ). This study showed that the strain RRA has great potential for producing PHB from low-cost renewable carbon sources and reminded researchers of the importance of isolating new strains."
} | 3,029 |
27247624 | PMC4886415 | pmc | 3,238 | {
"abstract": "Background Clostridium acetobutylicum has been a focus of research because of its ability to produce high-value compounds that can be used as biofuels. Lignocellulose is a promising feedstock, but the lignin–cellulose–hemicellulose biomass complex requires chemical pre-treatment to yield fermentable saccharides, including cellulose-derived cellobiose, prior to bioproduction of acetone–butanol–ethanol (ABE) and hydrogen. Fermentation capability is limited by lignin and thus process optimization requires knowledge of lignin inhibition. The effects of lignin on cellular metabolism were evaluated for C. acetobutylicum grown on medium containing either cellobiose only or cellobiose plus lignin. Microscopy, gas chromatography and 8-plex iTRAQ-based quantitative proteomic technologies were applied to interrogate the effect of lignin on cellular morphology, fermentation and the proteome. Results Our results demonstrate that C. acetobutylicum has reduced performance for solvent production when lignin is present in the medium. Medium supplemented with 1 g L −1 of lignin led to delay and decreased solvents production (ethanol; 0.47 g L −1 for cellobiose and 0.27 g L −1 for cellobiose plus lignin and butanol; 0.13 g L −1 for cellobiose and 0.04 g L −1 for cellobiose plus lignin) at 20 and 48 h, respectively, resulting in the accumulation of acetic acid and butyric acid. Of 583 identified proteins (FDR < 1 %), 328 proteins were quantified with at least two unique peptides. Up- or down-regulation of protein expression was determined by comparison of exponential and stationary phases of cellobiose in the presence and absence of lignin. Of relevance, glycolysis and fermentative pathways were mostly down-regulated, during exponential and stationary growth phases in presence of lignin. Moreover, proteins involved in DNA repair, transcription/translation and GTP/ATP-dependent activities were also significantly affected and these changes were associated with altered cell morphology. Conclusions This is the first comprehensive analysis of the cellular responses of C. acetobutylicum to lignin at metabolic and physiological levels. These data will enable targeted metabolic engineering strategies to optimize biofuel production from biomass by overcoming limitations imposed by the presence of lignin. Electronic supplementary material The online version of this article (doi:10.1186/s13068-016-0523-0) contains supplementary material, which is available to authorized users.",
"conclusion": "Conclusions In conclusion, our study presents the most comprehensive analysis of the effect of lignin on cellular metabolism of C. acetobutylicum . This is the first time that the inhibitory effect of lignin on growth, morphology, ABE and H 2 production and cellular functions was investigated and integrated. Glycolysis, fermentation and associated pathways were significantly repressed when lignin was present. Several proteins involved in the glycolysis and fermentation pathways were down-regulated in the presence of lignin concomitantly with lower ATP production. Lignin also suppressed the ATP-dependent Clp protease complex (which controls normal cell division) synthesis and activity resulting in a delay in sporulation and solventogenesis. Lignin imposed morphological adaptation since cellular stress associated with decreased ATP-dependent housekeeping activity and the cellular divisome were affected. Our main aim was to analyse the ‘lignin bottleneck’ by monitoring fermentation end products and associated changes in the proteome of C. acetobutylicum in response to lignin with a view on providing insights into lignocellulose as a feedstock for biofuel generation. Our results shed light on the breadth of the metabolic routes involved in the lignin response in a commercially valuable bacterium for future implementation for lignocellulosic biofuel generation.",
"discussion": "Results and discussion Carbohydrate polymers (cellulose and hemicellulose) and aromatic polymers (lignin) are the major components of lignocellulosic biomass that, upon hydrolysis (alkali/acid or enzymatic), produces fermentable sugars (that can be utilized by C. acetobutylicum ) and non-fermentable phenol compounds. Therefore, it is very important to understand how the presence of lignin affects fermentation end products (ABE) formation and core metabolic pathways. This study focused on metabolic and physiological changes in C. acetobutylicum during growth on cellobiose only (hereafter: C condition) and cellobiose plus lignin (hereafter: CL condition) supplemented conditions. The workflow shown in Fig. 1 demonstrates the integrated metabolic and proteomics analysis. Fig. 1 8-plex iTRAQ proteomic workflow. Proteins from eight individual samples (4 each for C and CL 2, exponential and 2 stationary phases) were digested into peptides that were tagged with isobaric stable isotope-labelled reagents. Relative quantification information was extracted upon collision-induced dissociation. 8-plex iTRAQ reagents tags have eight unique reporter ions of specific mass-to-charge ( m/z ) values (113, 114, 115, 116, 117, 118, 119 and 121) that produced peptide fragmentation during tandem MS and are used for relative quantitation by relative peak intensity. Fragmented peptide ions were used for peptide ID and protein identification. Samples for hydrogen, metabolites and dry cell biomass measures were taken in parallel Effect of lignin on the cell morphology, growth and fermentative end products Microscopic observations showed filamentous morphology of C. acetobutylicum with asymmetric and phenotypic cell division when lignin was present in combination with cellobiose (Fig. 2 d–f) relative to cellobiose alone (Fig. 2 a–c) in both exponential and stationary phases. The morphological changes suggest that the presence of lignin challenged the bacterial metabolism but did not affect the growth (based on dry cell biomass as shown in Fig. 3 a), since similar growth trends were observed until the late exponential phase (16 h) for both C and CL. Upon reaching stationary phase, a significant reduction in cell biomass was observed in C compared to CL at 36 h (Fig. 3 a). Alteration in cell morphology is a visible indicator of bacterial adaptation strategies to tackle different environmental stress conditions [ 17 ]. Reduction in cell biomass concentration in the C condition could reflect reduced cell size and sporulation during the stationary phase (Fig. 2 a, b versus Fig. 2 d, e) as previously proposed by Steiner et al. [ 18 ]. A comparatively faster rate of cellobiose consumption was observed in C media compared to CL media in the exponential phase (Fig. 2 a), consistent with lignin inhibition. Fig. 2 Morphology of C. acetobutylicum cells grown on C ( a – c ) and CL ( d – f ) at exponential phase (16 h) as shown in a and d and stationary phase (48 h) as shown in b and e . a – d were obtained by Olympus BX51 microscopy at ×60 magnification and c and e were obtained by transmission electron microscopy (TEM) at ×11,000 magnification Fig. 3 Growth, cellobiose consumption and metabolite formation during fermentation in C. acetobutylicum under CL ( dashed line ) and C ( solid line ) conditions; a Growth/dry cell biomass ( closed triangle ), cellobiose consumption profiles ( striked cross ), b H 2 production ( open triangle ), c acetic acid ( closed square ), d butyric acid ( open square ) and e ethanol ( closed circle ) and f butanol ( open circle ). Data were taken from four biological replicates and mean values with the error bars indicate standard error of the mean. Arrows indicate the sampling points for iTRAQ quantitative proteomic analysis (16 and 48 h). * p ≤ 0.05 and ** p ≤ 0.0099 Metabolites production was also validated: acetic acid and butyric acid and hydrogen (H 2 ); acetone, ethanol and butanol were detected and quantified by GC, to measure acidogenesis and solventogenesis, respectively. Metabolite profiles between C and CL are shown in Fig. 3 b–f (Additional file 1 : Metabolites data). Metabolite production was significantly affected by the presence of lignin. The major change was lignin inhibition of butanol production in both exponential and stationary phases (Fig. 3 f). Ethanol production was inhibited by lignin during exponential phase, but not stationary phase (Fig. 3 e). Acetone production was below the level of detection for both C and CL conditions. In terms of acidogenesis, hydrogen production was statistically significantly lower in the CL versus the C condition throughout the experiment (Fig. 3 b). The onset of acetic acid production began as soon as cells started to grow (8 h) and reached a maximum at 36 h (Fig. 3 c), which was followed by butyric acid production, starting at 12 h and reaching a maximum at 36 h (Fig. 3 d). Afterwards, a statistically significant decrease in acetic acid and butyric acid concentrations ( p values of 0.018 and 0.01, respectively) in C versus CL was observed that can be correlated with the statistically significantly higher ethanol and butanol production ( p values of 0.006 and 0.0021, respectively) in the C condition versus CL (ethanol; 0.47 g L −1 for C and 0.27 g L −1 for CL and butanol; 0.13 g L −1 for C and 0.04 g L −1 for CL) (Fig. 3 e, f). This indicates a rapid production of solvents in C versus CL and the accumulation of acids in the presence of lignin. Furthermore, there was delayed production of solvents in the presence of lignin, i.e. the onset of ethanol production started at 10 and 12 h for C and CL conditions and comparatively late butanol production started at 18 and 36 h for C and CL conditions, respectively. This is interesting that morphological changes (observed during transition of exponential to stationary) and reduced cell dry biomass concentration occur in C versus CL (Figs. 2 , 3 a). In general, it is presumed that acid production and solvent production occur at different stages, but our results suggest that simultaneous acid and solvent production is occurring (metabolic shift) [ 19 ] during growth. Our results have some agreement though, with previous studies that show simultaneous production of acids and solvents during growth and suggest that acidogenic and solventogenic cells co-exist in the culture [ 2 , 19 ]. Overall, the presence of lignin in the growth medium resulted in less H 2 and solvent production (Fig. 3 b, e, f). Usually, higher H 2 production occurs when acetic acid and butyric acid are produced during the acidogenic growth phase (exponential phase), [ 4 , 20 ] and it is believed to be due to accumulation of organic acids as a function of pH [ 21 ]. Acetic acid, butyric acid and H 2 were reasonably high and concomitantly produced in both treatment conditions, which is in agreement with previous findings that a mixture of acetic acid and butyric acid as a fermentative product yields more H 2 [ 22 ]. However, production seemed to be continued through the mid-stationary phase, indicating simultaneous acid and solvent production is possible, as previously observed [ 20 ]. Interestingly, acetone production was not observed. The results are consistent with previous observations in C. acetobutylicum when grown on cellobiose as the main carbon source, where higher H 2 , ethanol and acetic acid were produced as the main by-products and little or no acetone and butanol production was observed [ 23 – 25 ]. This study demonstrates substrate specificity and substrate-dependent fermentation flexibility of this bacterium. Despite the versatility of C. acetobutylicum in producing acids, H 2 and ABE, very little is known about the dynamic regulation of metabolic networks, stoichiometry and directionality of metabolic fluxes in this bacterium [ 26 ]. It is believed that the efficiency of substrate conversion to final product solely depends on the direction of carbon intermediates and electron flow in the fermentation pathway [ 27 , 28 ]. Therefore, since lignin had a negative effect on growth, morphology and fermentative products of C. acetobutylicum, we investigated this further by iTRAQ-based proteomics to gain insight into differential regulation of key proteins in the presence of lignin by comparing the exponential and stationary phases of cells grown under C and CL conditions. Effect of lignin on C. acetobutylicum metabolism: an iTRAQ-based quantitative proteomic approach A biological duplicate of each exponential and stationary phase from C and CL was chemically labelled using 8-plex iTRAQ reagents (following tryptic digestion to generate peptides) and analysed by HPLC–MS/MS analysis. Of 583 identified proteins (FDR < 1 %), 328 proteins were quantified with at least two unique peptides [ 29 ] (Additional file 2 : Proteomic data). To evaluate replicates, hierarchical clustering (dendrogram) and principal component analysis (PCA) were applied to the iTRAQ reporter ion intensities. Hierarchical clustering (dendrogram form) and PCA analyses revealed that there was a clear clustering and distinction between biological replicates. Moreover, the proteomes of C and CL grown cells in their respective exponential and stationary phases were clustered closely in the same size of the dendrogram and PCA (Fig. 4 ) indicating similarity between replicates and differences between biological conditions. Notably, the proteome in all four comparisons (each of exponential and stationary phase of C and CL condition) was evidently different as shown in Fig. 4 . Fig. 4 Hierarchical clustering (dendrogram) and principal component analysis (PCA) plot of proteome analysis data that characterizes the trend exhibited by the differentially expressed protein profile of ExpC (113,114), ExpCL (115,116), StaC (117,118) and StaCL (119,121) The effects of various lignin derivative compounds, metabolites and substrates stresses on Clostridia have been recently reviewed by Baral and Shah [ 7 ]. In particular, in C. acetobutylicum, several transcriptomics studies were dissected to study phase-related metabolism [ 30 ], physiological changes [ 31 ] and butanol stress or tolerance [ 32 ], but very few studies have been performed at the quantitative proteomics level. In a rare example, an adaptive stress response of C. acetobutylicum to the toxic metabolites, butyrate and butanol, was recently analysed by Vekantraman et al. [ 33 ] using iTRAQ-based quantitative proteomics. Our proteomics data provide vital information on differential expressions of proteins, thus providing a more detailed understanding of the effect of lignin on various cellular functions in C. acetobutylicum . A total 158 and 134 proteins were found to be differentially regulated in the exponential phase and stationary phases of CL, respectively, when compared to the exponential and stationary phases of cells grown in C media (ExpCL/ExpC and StaCL/StaC). Moreover, changes in protein expressions were also observed when shifting from exponential to stationary phase occurring in their respective conditions. In total, 173 and 216 proteins were differentially expressed in C (StaC/ExpC) and CL (StaCL/ExpCL) conditions, respectively. These significantly differentially expressed proteins were mapped into pathways and the results are summarized in Figs. 5 , 6 and 7 . Lignin significantly changed the cellular functions of C. acetobutylicum , namely sugar transport, glycolysis, fermentative pathways, DNA replication, transcription/translation, cell division, sporulation/stress response and cell signalling/secretion. Therefore, these pathways/enzymes are discussed and correlated individually in the following sections. Fig. 5 Alterations in relative abundance of protein expressions (iTRAQ ratio representing fold changes) in sugar transportation during growth on C and CL. [Comparing ratio; ExpCL/ExpC ( red ), StaCL/StaC ( blue ), StaC/ExpC ( yellow ) and StaCL/ExpCL ( green )]. (Fold change in protein expression: negative values indicate reduced abundance of proteins and positive values indicate increased abundance of proteins). The stars indicate the phosphoryl group of PEP, which is transferred to the imported cellobiose via series of PTS system proteins Fig. 6 Alterations in relative abundance of protein expressions (iTRAQ ratio representing fold changes) in glycolysis during growth on C and CL. [Comparing ratio; ExpCL/ExpC ( red ), StaCL/StaC ( blue ), StaC/ExpC ( yellow ) and StaCL/ExpCL ( green )] (Fold change in protein expression: negative values indicate reduced abundance of proteins and positive values indicate increased abundance of proteins) Fig. 7 Alterations in relative abundance of protein expressions (iTRAQ ratio representing fold changes) during pyruvate to end products formation during fermentation in C. acetobutylicum. The diagram represents protein profiling changes during lignin stress conditions in C. acetobutylicum (Fold change in protein expression: negative values indicate reduced abundance of proteins and positive values indicate increased abundance of proteins). Comparing ratio; ExpCL/ExpC ( red ), StaCL/StaC ( blue ), StaC/ExpC ( yellow ) and StaCL/ExpCL ( green ) Protein expression changes associated with cellobiose transport and glycolysis regulation Our iTRAQ proteomics results revealed that proteins involved in the cellobiose transport system and glycolytic pathway were altered in expression levels by the presence of lignin. The majority of enzymes in these pathways were down-regulated in both exponential and stationary phase in the presence of lignin relative to the cellobiose-only condition. Clostridium acetobutylicum can utilize a wide variety of carbohydrate sugars as carbon source and has multiple adaptable sugar transport and metabolic processes that are specifically regulated at the transcriptional level depending on environmental stress and nutrient conditions [ 34 ]. The phosphoenolpyruvate (PEP)-linked phosphotransferase system (PTS) is the major sugar transportation system exhibited in C. acetobutylicum. The PTS-dependent sugar transport systems are shown in Fig. 5 . Usually, C. acetobutylicum uses a cellobiose-specific PTS system for cellobiose phosphorylation and transportation. The system consists of four proteins: PTS IIA (CA_C0383), PTS IIB (CA_C0384) and PTS IIC (CA_C0386), and β glucosidase (CA_C0385). In this study, the cellobiose-specific PTS complex was down-regulated in the presence of lignin (ExpCL/ExpC). However, the data suggest that to maintain the sugar level, cells adaptively switched to the non-specific mannose PTS system. The components of the non-specific mannose PTS system are IIA (CA_P0066), IIC/D (CA_P0068) and 6-β-glucosidase (CA_C0743) (possibly associated with mannose PTS system). These were found to be up-regulated (ExpCL/ExpC). The data show that C. acetobutylicum possesses multiple cellobiose transport systems, as suggested by Servinesky et al. [ 34 ]. Thus, adaptive activation of different transport systems in different environmental stress conditions could be possible and reflected at the level of the proteome, which represents a novel finding. The cellobiose/mannose PTS systems allow cellobiose to enter the cell, so that it can be further cleaved into glucose and glucose 6-P by β-glucosidases and enter the glycolytic pathway. Non-phosphorylated glucose molecules are further phosphorylated by glucokinase (CA_C2613) to glucose-6-P; a protein was found to be in increased abundance in CL (ExpCL/ExpC). Glucose-6-P then enters into glycolysis (Fig. 6 ). In C. acetobutylicum , glucose to pyruvate conversion generally occurs via the Embden–Meyerhof–Parnas (EMP) pathway; the majority of measured proteins of the EMP pathway were down-regulated in the presence of lignin in the exponential phase. Since the metabolism of sugar presumably takes place during the exponential phase of C. acetobutylicum , the ratio of ExpCL/ExpC was considered to be crucial for the changes in the glycolysis process. Remarkably, the adaptive evolutionary enzyme 2-keto-3-deoxy-6-phosphogluconate aldolase (CA_C2973) was observed to be significantly up-regulated in the presence of lignin in both exponential and stationary phases; this enzyme can reversibly catalyse KDPG to pyruvate and glyceraldehyde-3-phosphate, bypassing the entire glycolytic process without any ATP production [ 35 – 37 ]. This protein is a vital protein in the modified Entner–Doudoroff (ED) pathway found in Archaea and Clostridium aceticum growing in extreme conditions [ 38 ]. Microbes using different glucose catabolic pathways is a little known fact; however, it solely depends on species and culture conditions [ 39 ]. Our results show that in presence of lignin, where EMP pathway proteins were down-regulated, cells might have attempted to maintain the cellular pyruvate/acetyl CoA level to achieve normal metabolic functions. This protein skips crucial steps in glycolysis, resulting in no net ATP generation. Although enolase (CA_C0713) was identified in this study, no differential expression was found. Our data show a reduced abundance of phosphofructokinase (CA_C0517) and this was adaptively accompanied by a reverse reaction catalysed by protein fructose 1,6-biphosphatase (CA_C1088), which had an elevated abundance in the lignin stress condition. Interestingly, tricarboxylic acid (TCA) cycle proteins aconitase (CA_C0971) and NAD-isocitrate dehydrogenase (CA_C0972) were up-regulated in the exponential phase of CL grown cells (ExpCL/ExpC). These proteins are involved in energy harvesting via NADH/NADPH generation [ 40 ]. Therefore, it can be possible that to compensate for low NADH derived from glycolysis in the presence of lignin, the bacterium adaptively increased expression of these proteins. Protein expression changes associated with fermentation pathway regulation Clostridium acetobutylicum is a model organism for ABE fermentation. The enzymes involved in acid and solvent production pathways were identified in both conditions with differential expressions. In agreement with the negative effect of lignin on glycolysis, the subsequent fermentation pathways were also found to be down-regulated in CL conditions. The network of differentially expressed proteins during acidogenesis and solventogenesis is shown in Fig. 7 . The major route for the synthesis of fermentation products starts with pyruvate, which is first converted into acetyl CoA, carbon dioxide (CO 2 ) and reduced ferredoxin (or flavodoxin; Fld) [ 41 ]. This further undergoes a biphasic branched fermentation process, where acids (formic acid, acetic acid and butyric acid) are produced during acidogenesis and solvents (ethanol and butanol) are produced during solventogenesis [ 42 , 43 ]. Reduced flavodoxin (Rd) is further used as an electron carrier for either NADH, NAD(P)H or hydrogen production depending on the cellular states [ 44 ]. In this study, we found increased acetic acid and hydrogen production, indicating carbon and electron flow towards the molecular hydrogen production and carbon flow towards acetic acid in both conditions. The hydrogenase (HydA) that receives electrons from flavodoxin (Fed) and produces hydrogen was only quantified by a single unique peptide at low abundance in CL conditions. Even though tentative, this observation is in agreement with lower hydrogen production in the CL condition (Fig. 3 b). The enzymes involved in acetic acid and butyric acid production were down-regulated in lignin condition (CL), particularly, acetate kinase (CA_C1743), phosphate acetyltransferase (CA_C1742), acetaldehyde dehydrogenase (CA_P0162), butyrate kinase (CA_C3075) and phosphate transbutyrylase (CA_C3076) (Fig. 7 ). However, no significant difference was observed in acids production in both conditions, but Fig. 3 c, d indicates decreased acid production during the stationary phase of C, this possibly explains the utilization of acids for solvent production (ethanol and butanol) was faster in C than CL conditions. This can be further justified by subsequent down-regulation of solvent-producing enzymes in CL: acetaldehyde dehydrogenase (CA_C0162) and (AdhE2) (ExpCL/ExpC and StaCL/ExpC). Down-regulation of these enzymes suggests less conversion of acids into solvents in CL. This is in agreement with our metabolite analysis (Fig. 3 e, f). Interestingly, the protein acetoacetate decarboxylase (CA_P0165) (involved in acetone production) was differentially regulated across all comparisons, but no acetone production was observed during fermentation. No expression of acetate/butyrate CoA transferase (CA_P0163, CA_P0164) was observed in both conditions, indicating that these enzymes possibly controlled acetone production in C. acetobutylicum . Providing evidence to this suggestion, it was previously found that acetone production was controlled at the transcriptional level through the expression of CoA transferase, but not through the expression of acetoacetate carboxylase [ 44 , 45 ]. In addition, our results are in agreement with previous studies that suggested that higher hydrogen production results in less or no acetone production when C. acetobutylicum was grown on cellobiose as the substrate [ 23 – 25 ]. Some studies also found that higher hydrogen partial pressure resulted in lower acetone production [ 27 , 46 ]. As seen in our data, two major ATP generation pathways, i.e. glycolysis and acid production were down-regulated in lignin conditions, likely resulting in lower ATP production. This could be the possible reason for reduced abundance of those proteins that possess ATP-dependant activity with a consequent effect on various functions related to transcription/translation and in cell division/sporulation. Protein expression changes associated with DNA metabolism/transcription/translation Since C. acetobutylicum produces acids and solvents at different stages of its life cycle and lignin affects their production due to changes in metabolism as confirmed by GC and proteomic data, we decided to investigate other metabolic functions (e.g. DNA metabolism, transcription/translation) that may contribute to this behaviour and also correlated to changes in cell morphology. Fold changes in protein expression levels of various other metabolic functions during growth on C and CL are shown in Additional file 3 : Fig. S1 and Table S1. These changes appear to manifest as an adaptive survival strategy of this bacterium at the replication, transcription and translation level [ 47 ]. The regulation of the most relevant proteins to lignin-induced changes is discussed in the following sections. The proteins involved in DNA repair, maintenance and stabilization that were only found in CL (StaCL/ExpCL), including DNA-binding protein HU (CA_C3211), nucleoid-associated protein (CA_C0126), and single-stranded DNA-binding protein (CA_C2382). These proteins were up-regulated in the presence of lignin, suggesting that DNA damage was induced by lignin, thus the repair system worked efficiently. We found that many transcriptional proteins were observed to be present in low abundance when comparing stationary phases to their respective exponential phases in C and CL conditions. However, the adaptive transcriptional regulator Lrp family protein (CA_C0977) [ 47 ] and GTP sensing transcriptional pleiotropic repressor CodY protein (CA_C1786) [ 48 ] were up-regulated in CL conditions (ExpCL/ExpC and StaCL/StaC). GTP binding CodY protein suppresses many genes of transition from exponential to the stationary/sporulation phase by binding to DNA [ 48 , 49 ]. Increased abundance of this protein in CL conditions may correlate with a delay in sporulation/defective cell division in CL conditions. In addition, the transcription regulatory septation protein SpoVG (CA_C3223) (involved in a site-specific DNA-binding activity) [ 50 ] was down-regulated in the presence of lignin and, therefore, cells may not have been able to control normal cell division and sporulation conditions, resulting in the filamentous morphology observed with CL grown cells. We also identified 33 ribosomal proteins differentially regulated between the CL and C conditions. However, it was observed that during the exponential phase of CL conditions, most of the ribosomal proteins were increased in abundance (ExpCL/ExpC). These proteins were also increased in abundance during stationary phases compared to their respective exponential phases (StaC/ExpC and StaCL/ExpCL). These proteins are normally down-regulated during stress conditions and stationary phases. The possible reason for increased abundance of these proteins could be correlated to the low expression of the ATP-dependent Lon protease (CA_C2637), which degrades ribosomal proteins when cells starve for amino acids [ 51 ]. This effect could be possible, since a major translational regulator [ 52 ] protein TYPA/BIPA ATPase (CA_C1684) was significantly down-regulated in CL conditions. This protein alters ribosomal structure/function to achieve normal translation in C. acetobutylicum. The activity of this protein has been shown to be GTP dependent and also previously correlated with adaptive response to stress [ 53 ]. The lower abundance of this protein possibly was dominated by high abundance of a suppressor CodY protein, since both require GTP for its activity. When comparing the stationary phase of C and CL to their respective exponential phases (StaCL/ExpCL and StaC/ExpC), proteins such as 5-methylthioadenosine S -adenosylhomocysteine (SAM) nucleosidase (pfs CA_C2117) (salvage pathway) and M18 family aminopeptidase (apeA CA_C1091 and apeB CA_C0607) that recycle amino acids from peptides (preferably aspartate glutamate) were up-regulated during the stationary phase of both conditions. SAM nucleosidase (that produces universal quorum sensing autoinducer-2 [ 54 ]) was up-regulated during solventogenesis and may be the vital indicator of transition of phases [ 18 ]. This strongly suggests that metabolic activities are highly regulated at the transcription and translational level, not only in lignin conditions, but also during the transition from exponential to stationary phase. Protein expression changes associated with chemotaxis/cell division/sporulation/energy metabolism Chemotaxis and motility are the vital functions in the lifestyle of many unicellular organisms and are metabolically costly processes. In this study, flagellin (flaC) and chemotaxis proteins (CheW and CheA) (CA_C2224 and CA_C2220) that trigger cellular motility in response to environmental conditions were significantly down-regulated in CL (ExpCL/ExpC and StaCL/StaC). These results are consistent with the literature which demonstrated loss of motility associated with no solvent production in C. acetobutylicum [ 55 – 57 ]. Interestingly, ESAT-6 antigen-like protein (CA_C0040), a vital early expression protein of secretion system VII was found in significantly high abundance in CL conditions. This indicates a strong and early response to lignin, which could have vital role in chemotaxis activity via flagellin in C. acetobutylicum . We speculate that there must be relation between ESAT-6, Chew/ChewA and flagellin that triggers the initial stress response with subsequent changes in transcription/translation sporulation/cell division proteins. In this study, we identified seven differentially regulated proteins from the divisome (division complex). As C. acetobutylicum is closely related to B. subtilis , it can be speculated that the structural complex could be similar to the divisome in B. subtilis . Our data show most of these proteins were up-regulated during growth on CL compared to C, indicating significant changes in divisomes (ExpCL/ExpC) induced by lignin. In particular, protein DivIVA (CA_C2118), a vital self-recruiting protein and involved in chromosome segregation during sporulation [ 58 ], SepF (CA_C2120), Z ring forming protein and cell division protein FtsX (CA_C0498) and FtsZ (CA_C1693) were found to be at increased abundance. In previous studies, high abundance of these proteins was correlated to abnormal morphology [ 59 ] and delay in sporulation [ 58 ]. This is confirmed by the controller of the sporulation protein (Spo0A) being down-regulated in CL conditions (ExpCL/ExpC and StaCL/StaC). Sporulation Spo0A (CA_C2071) induces the ftsZ protein to allow cells to divide at transcriptional level and governs sporulation/solventogenesis at the transcriptional level [ 60 , 61 ]. Evidence suggests that cell division and sporulation are concomitantly regulated by a stress response protein complex (ClpP, ClpX and ClpC and Lon protease) that works as a quality control and regulatory proteolysis pathway under stress conditions [ 62 ] to remove/stabilize defective or aggregated proteins. In this study, we found that several ATP-dependent proteins, ClpB (CA_C0959), ClpC (CA_C094, CA_C3189), DnaK (CA_C1282), Lon (CA_C2637), TerE (CA_C1412) and hsp18 (CA_C3714), were significantly down-regulated in lignin stress conditions. Therefore, we hypothesize that the quality control system of this bacterium fails to keep cells up to date, resulting in abnormal cell division/sporulation. It has been demonstrated that the relative concentrations of nucleotides (particularly ATP and GTP) play important roles in cell physiology and regulation [ 63 ]. In C. acetobutylicum , glycolysis and acids production during the exponential phase are energy generation (ATP generation) steps [ 64 ]. In this work, seven subunits from ATP synthase were identified, including alpha, beta, gamma, epsilon and delta subunits. However, the relative abundance of these proteins was not significantly regulated in both conditions. This suggests that intracellular protons are mostly used for hydrogen production, thus limiting expenditure of ATP at substrate level phosphorylation [ 65 ]. Thus, it can be hypothesized that down-regulation of glycolysis and acid production decreased ATP synthesis in CL conditions to cumulatively affect cell regulation. WrbA family protein (multimeric flavodoxin) (CA_C3314) was found at high abundance in CL treatment (StaCL/StaC and StaCL/ExpCL) which is involved in electron transfer systems and only expresses during adaptive cell response to stress conditions [ 66 ]. It has been proposed that C. acetobutylicum possesses another energy conserving module based on NADH:ferredoxin oxidoreductase (rnf) and butyryl-CoA dehydrogenase complex (Bcd/etfAB), [ 67 ] also proposed in Clostridium kluyveri [ 68 ]. Interestingly, we identified butyryl-CoA dehydrogenase (Bcd) (CA_C2711), electron transfer flavoprotein (subunit etfA (CA_C2709) and etfB (CA_C2710) and probable NADH/NADPH oxidoreductase (CA_C1958) in both conditions, suggesting the presence of extra energy conserving modules in this bacterium."
} | 8,724 |
26405376 | null | s2 | 3,240 | {
"abstract": "We present a new fabrication method to produce arrays of highly responsive polymer-metal core-shell magnetic microactuators. The core-shell fabrication method decouples the elastic and magnetic structural components such that the actuator response can be optimized by adjusting the core-shell geometry. Our microstructures are 10 μm long, 550 nm in diameter, and electrochemically fabricated in particle track-etched membranes, comprising a poly(dimethylsiloxane) core with a 100 nm Ni shell surrounding the upper 3-8 μm. The structures can achieve deflections of nearly 90° with moderate magnetic fields and are capable of driving fluid flow in a fluid 550 times more viscous than water."
} | 172 |
25931032 | null | s2 | 3,241 | {
"abstract": "Metabolic glycoengineering is a specialization of metabolic engineering that focuses on using small molecule metabolites to manipulate biosynthetic pathways responsible for oligosaccharide and glycoconjugate production. As outlined in this article, this technique has blossomed in mammalian systems over the past three decades but has made only modest progress in prokaryotes. Nevertheless, a sufficient foundation now exists to support several important applications of metabolic glycoengineering in bacteria based on methods to preferentially direct metabolic intermediates into pathways involved in lipopolysaccharide, peptidoglycan, teichoic acid, or capsule polysaccharide production. An overview of current applications and future prospects for this technology are provided in this report."
} | 198 |
38658197 | PMC11092278 | pmc | 3,245 | {
"abstract": "Abstract The dihydrogen (H 2 ) sector is undergoing development and will require massive storage solutions. To minimize costs, the conversion of underground geological storage sites, such as deep aquifers, used for natural gas storage into future underground hydrogen storage sites is the favored scenario. However, these sites contain microorganisms capable of consuming H 2 , mainly sulfate reducers and methanogens. Methanogenesis is, therefore expected but its intensity must be evaluated. Here, in a deep aquifer used for underground geological storage, 17 sites were sampled, with low sulfate concentrations ranging from 21.9 to 197.8 µM and a slow renewal of formation water. H 2 -selected communities mainly were composed of the families Methanobacteriaceae and Methanothermobacteriaceae and the genera Desulfovibrio, Thermodesulfovibrio , and Desulforamulus . Experiments were done under different conditions, and sulfate reduction, as well as methanogenesis, were demonstrated in the presence of a H 2 or H 2 /CO 2 (80/20) gas phase, with or without calcite/site rock. These metabolisms led to an increase in pH up to 10.2 under certain conditions (without CO 2 ). The results suggest competition for CO 2 between lithoautotrophs and carbonate mineral precipitation, which could limit microbial H 2 consumption.",
"conclusion": "Conclusion As the first study of its kind on this aquifer, which serves as a UGS for natural gas, these experiments are intended to assess the hydrogenotrophic potential of indigenous communities in general, and of methanogens in particular. Interestingly, it was shown that the hydrogenotrophy capacity linked to sulfate reduction was present over the entire aquifer used as UGS and hydrogenotrophic methanogenesis was only present near the current natural gas storage. It is obvious than these batch experiments at atmospheric pressure underestimate H 2 consumption because of its low dissolution and low quantity available for the microbial growth. However, this study has made it possible to identify certain sites and conditions to be tested from now on under conditions closer to reality (high pressure, monitoring over time, and so on) in order to determine H 2 consumption (or even CO 2 ) and methane and sulfide production yields, and to assess the economic relevance of a future UHS in this deep aquifer. Finally, the strong alkalization initiated by lithoautotrophic microbial metabolisms is a key parameter to take into consideration. In the context of a UHS sure, this phenomenon could considerably curb microbial consumption of H 2 by mineralizing CO 2 dissolved in carbonates and thus making this CO 2 inaccessible to autotrophic microorganisms. In the context of in situ biomethanation, alkalinization could be counterbalanced by CO 2 coinjection, enabling active in situ biomethanation to be maintained.",
"introduction": "Introduction Our societies are facing the challenges of climate change, the need to massively develop renewable energies, the energy sovereignty, and the cost of energy. The ongoing development of the dihydrogen (H 2 ) sector and the imminent arrival of green H 2 from renewable energies in the gas grid (Le Duigou et al. 2017 ) have led many industrialists and academic researchers around the world to examine the consequences for surface infrastructure (DBI GUT 2017 ) and underground geological storage (UGS) sites used to balance the grid and secure supplies. Ultimately, the aim is to transform UGS into underground H 2 storage (UHS; Dopffel et al. 2021 , Heinemann et al. 2021 , Krevor et al. 2023 ). The question of the future of UGS in general, and UHS in particular, is central to (i) developing future massive energy storage to accommodate seasonal variations; (ii) securing countries’ energy reserves; and (iii) avoiding a possible fragmentation of a global gas network that would hinder the development of the H 2 energy sector or even renewable energies (Rabiee et al. 2021 ). In the petrochemical and chemical sectors, H 2 storage in salt caverns has been in use for several decades, and specialists agree that the technology is reliable (Aftab et al. 2022 , Réveillère et al. 2022 , Bradshaw et al. 2023 ). However, the number, volume, and geographical distribution of these salt caverns are far from sufficient to store H 2 on a massive scale, given current production projections, which explains the strong interest in porous reservoirs (Barison et al. 2023 ). Most of the work focusing on H 2 storage in porous reservoirs, such as depleted reservoirs or deep aquifers, involves simulations using various models that generally do not take microbial activity into account; several examples of such simulations can be found in the review by Al-Shafi et al. ( 2023 ). However, models that take microorganisms into account have shown that microorganisms are likely to have a strong impact on the evolution of these future storage sites (Ivanova et al. 2007 , Panfilov 2010 , Ebigbo et al. 2013 , Amid et al. 2016 , Hemme and van Berk 2018 , Thaysen et al. 2021 , Tremosa et al. 2023 ). Many deep environments are home to microbial communities that use H 2 as an energy source. These communities are referred to by the acronym SLiME, standing for SubLithoautotrophic Microbial Ecosystem (Stevens and McKinley 1995 , Fry et al. 1997 , Chapelle et al. 2002 , Takai et al. 2003 , Lin et al. 2005 , Crespo-Medina et al. 2014 ). Several works have demonstrated, directly or indirectly, that UHS in porous reservoirs, particularly in deep aquifers, could lead under certain conditions to in situ biomethanation by hydrogenotrophic methanogenic archaea that naturally evolve in these ecosystems (Amigáň et al. 1990 , Buzek et al. 1994 , Panfilov 2010 , Liebscher et al. 2016 , Gregory et al. 2019 , Strobel et al. 2020 , Haddad et al. 2022a , Molíková et al. 2022 ). These initial biomethanation results obtained for UGS in deep aquifers are attractive because they allow us to envisage a disruptive innovation. UGS in deep aquifers would combine the capture and injection of CO 2 with the production of nonfossil methane, thereby reducing the consumption of fossil hydrocarbons and curbing the quantities of greenhouse gases released while enabling more virtuous carbon-neutral energy production, i.e. more homogeneous on a territorial scale (Zavarko et al. 2021 , Chai et al. 2023 ). Indeed, deep aquifers are found all over the globe in sedimentary basins, and those in the first 2 km of depth could reach a cumulative volume of 22.6 million km 3 (Gleeson et al. 2016 ). The use of these storage sites would be conditional on the presence of a decarbonated H 2 production area (renewable and nuclear), an accessible source of CO 2 , ideally captured from industry or even the atmosphere (Gutknecht et al. 2018 , Hou et al. 2022 ), and a geological storage reservoir equipped with injection and production wells, as well as a gas network enabling biomethane distribution (Bellini et al. 2022 ). By overcoming a number of scientific hurdles, these deep, secure sites would represent a biomethanation potential at a scale several times larger than that of conventional catalytic or biological methanation reactors due to the very large reservoir volumes (Molíkova et al. 2022 , Vítĕzová et al. 2023 ). The concept of biomethanation in porous reservoirs has its origins, on the one hand, in the discovery that part of the methane present in natural gas reservoirs has a biogenic origin (Davis and Updegraff 1954 ) and, on the other hand, in the realization that in situ biomethanation in a geological reservoir could be performed at time-scales compatible with industrial exploitation, as demonstrated by a study of town gas storage in Lobodice (Czech Republic), with an estimated conversion of 17% H 2 (associated with CO 2 /CO present at the site) to CH 4 in just 7 months (Šmigáň et al. 1990). In 2021, a study on the Olla Oil Field, which was operated using CO 2 injection (CO 2 -EOR) until 1986, showed a conversion of 13%–19% of CO 2 into CH 4 via methanogenesis (Tyne et al. 2021 ). At present, three projects are attempting to prove the feasibility of biomethanation in depleted hydrocarbon reservoirs and are being tested under real conditions: the Hychico-BRGM pilot project in Argentina, the Underground Sun Conversion—Flexible Storage Project, and the Bio-UGS Project “Biological conversion of carbon dioxide and hydrogen to methane in porous underground gas storage facilities: Analysis of underground biomethanation potential” (see reviews by Strobel et al. 2020 , Dopffel et al. 2021 , Bellini et al. 2022 ). This study targets a deep aquifer used for natural gas UGS and featuring formation water with low sulfate concentrations (Ranchou-Peyruse et al. 2019 ). In the context of its potential use as a UHS site, CO 2 will also be present due to its natural presence in the aquifer, as a coconstituent of the natural gas already present in the storage site or even as a result of voluntary injection (Delshad et al. 2022 , Wang et al. 2022 ). In UHS sites in porous reservoirs, hydrogenotrophic methanogenic archaea compete mainly with sulfate reducers for H 2 and CO 2 , although a smaller proportion of these substrates may also be consumed by homoacetogens (Haddad et al. 2022b , Mura et al. 2024 ). Here, cultural and molecular biological approaches were used to assess the effect of the two dominant hydrogenotrophic functional groups in this aquifer, methanogens and sulfate reducers, on gas-phase H 2 . Formation waters from various monitoring wells in the aquifer were collected to (i) assess whether the quantity of methanogens present is a good proxy for the potential for methanogenesis; (ii) evaluate competition and possible inhibition between the two functional groups; and (iii) assess the impact of the rock, specifically calcite, on the metabolic activities of interest.",
"discussion": "Results and discussion Targeting UGS sites that are already functional for upgrading to UHS sites There is an urgent need to assess the potential of the various aquifers used as UGS sites to determine their possible future uses (H 2 storage, CO 2 storage, in situ biomethanation, geothermal energy, and so on). For this study, we selected an aquifer used for natural gas storage (Fig. 1 ) that has already been the subject of several studies and could be converted into a UHS site (Ranchou-Peyruse et al. 2019 , Haddad et al. 2022a ). The aquifer is configured into two anticlines (Fig. 1A , in turquoise blue in the center of the image; Fig. 1B ), which enables two storage zones to be accommodated in the submolassic sand layer composed mainly of quartz, some calcite, and occasionally dolomite and K-feldspar (André et al. 2002 ), with a porosity varying between 25% and 35% and a low concentration of sulfate (from 21.9 to 197.8 µM; Table S1 , Supporting Information ); consequently, the site is a priori favorable for H 2 storage (Bo et al. 2021 ). Of the 17 sampling sites, 13 are located in the Eocene-Lutetian stratum dated from −40 to −46 My and coded Ab_L_1 to Ab_L_14 (except Ab_L_6) at depths ranging from −10 to −874 m above mean sea level (AMSL). Three wells provide access to water from the lower Eocene-Ypresian level (−46 to −53 My) at depths ranging from −475 to −949 m AMSL. Finally, formation water was sampled in the lower Paleocene/Danian layer (−59 to −65 My) at −595 m AMSL; stored gas does not reach this layer, and a new UHS site could be considered here. The average age of the water circulating in this zone has been estimated by the GAIA project using 14 C and some 36 Cl dating to be between 20 000 and 50 000 years old ( http://infoterre.brgm.fr/rapports/RP-69126-FR.pdf ), with pore-level circulation estimated at ∼5 m year −1 (Labat 1998 ). Quantification of sulfate-reducing and methanogenic microorganisms at all sites to assess biomethanation potential An initial sampling campaign was carried out in October 2020 to screen the 17 sites for their estimated 16S rRNA gene copy concentrations (total prokaryotes), dsrB (sulfate reducers) and mcrA (methanogens), as presented in Fig. 2 . For prokaryotes, the average concentration for all sites studied was 4.8 × 10 5 ± 3.3 × 10 4 copies of the 16S rRNA gene ml −1 , with the lowest concentrations found at sites Ab_L_10 and Ab_Y_3 with 1.1 × 10 3 ± 1.5102 and 8.3 × 10 2 ± 1.7 × 10 2 copies of the 16S rRNA gene ml −1 , respectively. Conversely, the sites with the highest concentrations were Ab_L_4, Ab_Y_2, and Ab_P_1, with 2.1 × 10 6 ± 1.9 × 10 5 , 2.4 × 10 6 ± 1.5 × 10 5 , and 2.5 × 10 6 ± 1.5 × 10 5 copies of the 16S rRNA gene ml −1 , respectively. All sites showed the presence of sulfate-reducing microorganisms, which often dominate microbial communities. On the other hand, based on mcrA gene detection and quantification, the presence of methanogens was observed at only 12 sites with variable and low concentrations ranging from 1.6 × 10 0 to 4.3 × 10 2 ± 8.3 × 10 1 mcrA gene copies ml −1 . The corresponding formation waters were also incubated in the laboratory with a mixture of H 2 /CO 2 (80/20; 1 bar), and the asterisk in Fig. 2 identifies the samples showing methanogenesis activity: Ab_L_1 (2% of CH 4 in 49 days of incubation), Ab_L_3 (6% in 40 days), Ab_L_7 (6.2% in 32 days), Ab_L_8 (0.7% in 17 days), Ab_L_9 (0.2% in 254 days), Ab_L_10 (2.8% in 193 days), Ab_Y_1 (2.7% in 48 days), Ab_Y_2 (1.9% in 138 days), and Ab_P_1 (3.9% in 97 days). As expected, the absence of detection of the mcrA gene in water was corroborated by a systematic absence of methanogenesis, and quantification of this gene is therefore a good proxy for this metabolic capacity. Of the 12 formation water samples with the mcrA gene, nine showed methane production. Over a 1-year monitoring period, samples Ab_L_2, Ab_L_4 and Ab_L_13 showed no methane production. Low concentrations of mcrA gene copies alone cannot explain these latest results, since methane production in other assays was sometimes achieved at lower concentrations. We therefore hypothesize that the methanogens encountered at these three sites, such as members of the families Methanomicrobiaceae and Methanosarcinaceae , could be nonhydrogenotrophic and use acetate, formate, alcohols and methylated compounds identified at some sites in this aquifer (Ranchou-Peyruse et al. 2019 ). This could also imply a low acetogenic activity (i.e. production of acetate and/or formate), preventing sustained activity of acetotrophic methanogens. Figure 2. Comparison of prokaryote (bacteria and archaea) quantifications in the 17 formation waters sampled from the three levels of the aquifer. Concentrations of prokaryotes, sulfate reducers, and methanogens were estimated by qPCR in copy numbers per milliliter of water of the 16S rRNA, dsrB , and mcrA genes, respectively. *: formation water that showed methane production after incubation in the presence of H 2 /CO 2 (80/20; 1 bar). It is important to note that, with the exception of sites Ab_L_2 and Ab_L_4, all the other sites that did not exhibit methanogenic archaea and/or methane production are remote from current gas storage locations (Fig. 1A ). The redox potential may partly explain some of these results, since several of these sites had redox potential unfavorable to hydrogenotrophic methanogenesis, such as Ab_L_5 (−73.9 mV), Ab_L_11 (−71.2 mV), Ab_L_12 (+130.9 mV), and Ab_L_13 (−50.1 mV), instead of the optimal −200 to −400 mV (Reeburgh 1983 , Hirano et al. 2013 ). Ab_L_12 showed great variation in redox potential over the years, ranging from −119.0 to 161 mV since June 2020. Based on the results of this first sampling campaign, a panel of sites was selected for further study: Ab_L_1, Ab_L_3, Ab_L_7, Ab_L_8, Ab_Y_2, and Ab_P_1. The choice took into account the geological layer of the formation water (L: Eocene-Lutetian, Y: Eocene-Ypresian, and P: Paleocene-Danian), methane production from the H 2 /CO 2 gas mixture, and the quantity of mcrA genes. On this last point, site Ab_L_10 was also selected as it had few copies of mcrA genes but nevertheless showed methanogenesis potential in cultivation trials. The rest of the study focused on demonstrating the effect of physico-chemical and microbiological parameters on methanogenesis. Physico-chemistry of water samples from seven selected sites Two new sampling campaigns were carried out in May and September 2021 to resample the seven selected formation waters ( Table S1 , Supporting Information ). These waters had low salinity characterized by an electrical conductivity of ∼300 µS cm −1 and negative redox potential between −40.3 and −351 mV. Average sulfate concentrations ranged from 21.9 to 197.8 µM. Nitrate and nitrite concentrations were all below the detection limits of 1.6 µM and 0.3 µM, respectively. For dissolved iron, we were unable to distinguish between Fe 2+ and Fe 3+ , but the redox potential at the sites favors its more reduced form. André et al. ( 2007 ) suggested an equilibrium between Ca-HCO 3 facies and the dissolution of carbonate minerals such as calcite (CaCO 3 ). These carbonates may represent a source of carbon accessible to autotrophic microorganisms under the pH and redox potential conditions prevailing in the aquifer. There are complex balances between carbonate minerals, CO 3 2− and HCO 3 − , CO 2 dissolved in water and CO 2 in the gas phase (gas storage). By consuming dissolved CO 2 , lithoautotrophic microorganisms significantly alter these balances. The metabolic groups likely to dominate microbial communities are sulfate reducers, methanogens, homoacetogens and fermenters. Given the nature of our study (i.e. in situ biomethanation), we decided to focus on sulfate reducers and methanogens. These two functional groups comprise H 2 -consuming lithoautotrophic organisms. We consider homoacetogens and fermenters as complementary, but nonetheless secondary, in the functioning of these communities in the context of massive H 2 injection. Indeed, it is expected that homoacetogens will consume part of the H 2 and CO 2 to form acetate and/or formate (Stoll et al. 2018 , Haddad et al. 2022b , Mura et al. 2024 ), which will be consumed by the rest of the microbial community and, in particular, by methanogenic archaea to form methane (Pan et al. 2016 ) and heterotrophic sulfate reducers (Weijma et al. 2002 , Dai et al. 2022 ). The experiment carried out by Haddad et al. ( 2022b ), which aimed to simulate H 2 injection into an aquifer similar to the one in this study in terms of sulfate concentration (around 150 µM), showed that the main consumers of H 2 were methanogens (around 80% of the H 2 ), while homoacetogens accounted for only 4%. The remaining H 2 lost (around 16%) could be considered as consumed by sulfate reducers. In these oligotrophic environments, where organic carbon concentrations are low (1.1 mg l −1 ) or below the detection limit, the impact of fermenters is expected to be strongly constrained, participating in particular in the recycling of microbial necromass into H 2 , CO 2 , and other organic acids that can be used by sulfate reducers and methanogens. Finally, the low detected concentrations of ammonium (between 3.3 and 26.6 µM) and dissolved phosphates (<2.1 µM) suggest a low capacity of these ecosystems to sustain a much higher biomass concentration than before H 2 injection. These molecules have already been cited several times as limiting nutrients in the deep biosphere (Madigan et al. 1997 , Head et al. 2003 ). Similarly, the concentrations of certain metals such as nickel, essential for the proper functioning of enzymes such as hydrogenases, could be limiting factors for hydrogenotrophic microbial populations in these environments. This information is crucial and should be taken into account in future UHS modeling incorporating the microbiological dimension (Hagemann et al. 2016 ). In our case, we believe that with a slow recharge of the aquifer (5 m year −1 ; Labat 1998 ) and in the context of a rock overwhelmingly composed of quartz and few minerals that could serve as a source of phosphorus or nitrogen, the cell concentration will remain constant to within one log. Unsurprisingly, these two parameters (i.e. ammonium and phosphate) do not appear to be the only ones driving the communities, since their concentrations were not directly correlated with those of prokaryotes in the collected formation water ( Table S1 , Supporting Information ; Fig. 2 ). Enrichment in the presence of H 2 /CO 2 gas phase (80/20; 1 bar) Following this first part of the study, incubations in the presence of calcite (CaCO 3 ) were carried out. Calcite plays a role in methanogenesis as an indirect carbon source via its dissolution, but its presence in the geological structures used for storage can lead to changes in porosity and permeability (Haddad et al. 2022b , Saeed et al. 2023 ). In these UGS sites, CO 2 is present naturally or artificially (coinjected with natural gas to ∼2%; Burgers et al. 2011 ). Added to this is a complex balance between gaseous and dissolved CO 2 , on the one hand, and between carbonates (CO 3 2− ) and bicarbonates (HCO 3 − ) in water and carbonate minerals on the other. Cultivation trials were carried out at near-atmospheric pressure (1 bar at the start of the experiment) in flasks to screen a wide range of conditions, which would not be possible with pressurized experiments. The pressures encountered on these sampling sites (between 40 and 80 bars) are relatively low, compared to abyssal pressures, e.g. and are thought to have little effect on the microorganisms that evolve there; no piezophile has ever been discovered in deep continental systems. A priori , the microorganisms revealed in this study at atmospheric pressure would be the same at pressures simulating those in situ (i.e. high pressure). On the other hand, it is certain that manipulations at high pressure have an effect on the solubility of gases in water and therefore their accessibility to microbial populations, particularly in the case of lithoautotrophs. Here, the aim was not to assess yields but rather to evaluate a potential for hydrogenotrophy. For each site, the formation water and its indigenous microbial community (without nutrient supplementation) were brought into contact with a gas phase of H 2 /CO 2 (80/20) or H 2 alone, with or without calcite. In the case of Ab_Y_2, an additional condition was added with the presence of barite (BaSO 4 ) as a potential sulfate source for sulfate reducers (Haddad et al. 2022b ). For Ab_P_1, calcite was replaced with rock from the reservoir to mimic in situ conditions as closely as possible. The most critical and quantifiable physico-chemical data measured at the start of the experiment and after 26 to 193 days of incubation are represented in the principal component analysis (PCA) shown in Fig. 3 , explaining 67.6% of the sample distribution. As expected, the “Bicarbonate,” “Calcium,” and “Calcite” vectors are associated and correlate very well with Axis 1. They aggregate the controls and the H 2 /CO 2 tests (both with calcite) at the end of the experiment. The “sulfate” vector correlates well with axis 2 and is opposite to the “CH 4 ” vector. The almost right angle formed by the “sulfate” vector and the group of the three “bicarbonate”–“calcium”–“calcite” vectors indicates that these two sets of variables are independent of each other. Finally, the “ Eh ” vector is logically opposed to the “CH 4 ” vector. A summary of the information from the seven analyzed variables shows that, regardless of the conditions tested, sulfate is the factor with the greatest influence at the start of incubation (as indicated by the empty geometric shapes in Fig. 3 ). While the sulfate concentration remained constant in all the abiotic controls, sulfate reducers consumed sulfate in all the biotic trials, although this consumption was not total over the incubation period ( Table S2 , Supporting Information ). All biotic tests showed methane production and the presence of sulfate at the end of the experiment, suggesting that methanogens were able to thrive and be active at the same time as sulfate reducers ( Table S3 , Supporting Information ). Black iron sulfide precipitates were observed in all biotic assays. In the conditions without rock and without barite, the sulfide concentrations did not exceed 5 µM at the end of incubation. With the rock from the site (Ab_P_1), these concentrations increased from 2.3 ± 1.3 µmol of sulfide to 11.3 ± 0.9 µmol of sulfide. For the Ab_Y_2 formation water, the sulfide production increased from 2.9 ± 1.6 µmol of sulfide to 7.2 ± 0.0 µmol with the barite supplementation (Ab_Y_2) without there being any more sulfate-reducing agents quantified ( Table S3 , Supporting Information ). Low sulfate concentrations allow methanogens to compete for H 2 with sulfate reducers. In their work, Lupton and Zeikus (1984) set a concentration limit of ∼5 mM, well above the concentrations found at the various sites in the present aquifer. H 2 tests, with and without calcite, are grouped together in the upper left quadrant (Fig. 3 ). These trials are strongly marked by their highest pH values, since the acidity generated by CO 2 solubilization from the gas phase is absent, and calcite dissolution was observed. Clearly, in the condition with CO 2 in the gas phase, CO 2 was the carbon source for methanogens and other chemolithoautotrophs. In the condition without CO 2 but with calcite, calcite dissolution enabled methanogenesis (CaCO 3 ↔ CO 3 2− / HCO 3 − ↔ CO 2(aq) ). Biotic tests with H 2 alone in the gas phase naturally showed higher initial pH values (average pH 8.1 ± 0.1) than those under H 2 /CO 2 conditions (average pH 6.3 ± 0.2). At the end of incubation in CO 2 -free conditions with calcite, the highest pH was 10.2, averaging 9.3 ± 0.7 across all sites. The ionic Ca 2+ concentration decreased under the action of microorganisms (0.93 ± 0.08 mM in the abiotic controls versus 0.32 ± 0.19 mM under biotic conditions). Initially, calcite-carbonate-dissolved CO 2 -gas equilibrium was achieved. The methane production indicates that the dissolved CO 2 was consumed by methanogenic archaea. This consumption led to increased calcite dissolution, the release of calcium ions and an increase in pH with the appearance of hydroxyl ions. Methanogenesis and sulfate reduction are associated with alkalinization (Berta et al. 2018 , Dopffel et al. 2023 ), and this can lead to conditions deviating from the optimal growth conditions of methanogenic archaea, which are generally at approximately pH 6.5 to 8.5, but their resistance can reach pH 10 for some (Gerardi 2003 , Liu and Whitman 2008 , Thayssen et al. 2021 ). In the assays without CO 2 , we assume that when the pH of the enrichments became very alkaline, conditions became unfavorable for microorganisms, but not necessarily because of a toxic effect on microorganisms, as has already been observed (Bassani et al. 2015 ). Calcium ions could then complex with the organic matter of the necromass (Kloster et al. 2013 , Zhang et al. 2019 ), contributing to lower concentrations of this ion in biotic tests than in abiotic tests ( Table S2, Supporting Information ). This hypothesis will require dedicated experiments to confirm or disprove it under experimental conditions simulating environmental parameters, in particular those related to pressure, salinity, temperature, rock type, and microorganisms. In the context of in situ biomethanation, this point is crucial, as it assumes that during methanogenesis, alkalinization initiates a new thermodynamic equilibrium that induces competition for CO 2 between lithoautotrophs (i.e. methanogens, sulfate reducers, and homoacetogens) and carbonate precipitation. After the depletion in sulfate, this would represent a potential brake on methanogenesis and imply a possible decrease in porosity/permeability as a function of Ca 2+ , Mg 2+ , or Fe 2+ concentration, which would induce calcite (CaCO 3 ), magnesite (MgCO 3 ), or siderite (FeCO 3 ) precipitation, respectively. For the CO 2 - and calcite-free conditions, we can only hypothesize CO 2 production by fermentative and heterotrophic functional groups (i.e. sulfate reducers) growing on the necromass of part of the microbial community. Figure 3. PCA of the main physico-chemical parameters (bicarbonate, calcium, calcite, CH 4 , pH, Eh , and sulfate) before and after incubation of the microbial communities from the six formation waters studied (Ab_L_1, Ab_L_3, Ab_L_7, Ab_L_8, Ab_L_10, and Ab_Y_2). Incubations were carried out in the presence of a gas phase consisting of either H 2 /CO 2 (80/20; 1 bar) or H 2 only and with or without calcite. The results from site Ab_P_1 are not shown in this figure ( Fig. S4 , Supporting Information ). Methane production as a function of test conditions All the test conditions for the seven formation waters, apart from the abiotic controls, showed methane production (Fig. 4 ). It should be noted that in the formation waters closest to the stored natural gas bubble (Ab_L_1 and Ab_L_7), methane may still have been dissolved when the experimental tests began, which explains some of the results. The highest methane production was observed under H 2 /CO 2 conditions (80/20) and without calcite (CaCO 3 ; Fig. 4 , Part 1). Methane production was also observed for Ab_L_10 formation water, which had a barely detectable amount of mcrA genes. Logically, in incubations with only H 2 in the gas phase (Fig. 4 Part 2), methanogenesis was generally less efficient than in the presence of H 2 /CO 2 (80/20). In all these assays, an increase in pH was measured, from around 8.0 at the start of the incubations to 10.2 (in particular, Ab_L_7 with calcite). The methanogenesis in the tests without calcite (and without CO 2 ) implies that a significant proportion of the carbon used to produce methane did not come from calcite. We hypothesize that the source carbon could be bicarbonate ions in the waters, with concentrations ranging from 2.5 to 3.2 mM ( Table S2, Supporting Information ), and by the fermentation and heterotrophy of the microbial necromass, producing H 2 , CO 2 , and organic acids that feed methanogenic archaea. Ab_Y_2 formation water in the presence of barite (BaSO 4 ), a potential source of sulfate, did not show an increase in the concentration of the sulfate reducers ( Table S3, Supporting Information ), but rather in their activity (i.e. more sulfide produced). We deduce that for such an aquifer with relatively low sulfate concentrations between 0.02 and 0.2 mM ( Table S2, Supporting Information ), methanogenesis can take place at the same time as sulfate reduction, and the latter is not limiting for the development of methanogens. Based on the hydrogenotrophic methanogenesis reaction (4H 2 + CO 2 → CH 4 + 2H 2 O) and the quantities of methane detected at the end of incubation, the theoretical H 2 consumption by this metabolism has been estimated at between 0.1% and 13.4% of the H 2 consumed under H 2 /CO 2 conditions, and between 0.3% and 3.8% under conditions with only H 2 in the gas phase. As for the other hydrogenotrophic metabolisms, their theoretical H 2 consumption was estimated at between 20% and 65% when the gas phase was composed of the H 2 /CO 2 mixture, and between 15% and 72% when only H 2 was present. The taxonomic diversity results (Fig. 5 ) suggest that hydrogenotrophic sulfate reducers are the key players in this consumption. In deep aquifers with slow water turnover, low sulfate concentrations are expected to be rapidly consumed, allowing methanogens and acetogens to become the dominant metabolisms in a second phase. In the context of natural gas storage, annual monitoring at site Ab_L_1, the interface between stored natural gas and formation water, between 1992 and 2017 showed that increased microbial activity had reduced the sulfate concentration from 18 mg l −1 to less than 7 mg l −1 (190 to 73 µM; Ranchou-Peyruse et al. 2019 ). This increase in sulfate-reducing activity was explained by the solubilization of organic molecules present in the natural gas and available to heterotrophic microorganisms present in the water of the oligotrophic aquifer. This same research article also suggested that the effect of a massive arrival of H 2 in such an ecosystem could impact microbial diversity, and by indirect effect on the physico-chemistry of water by maintaining low sulfate concentrations in particular, over several decades; and this even when the H 2 storage was finished. Figure 4. Monitoring of the gas phase evolution in microbial tests on the seven formation waters with and without calcite. Part 1: tests in the presence of a H 2 /CO 2 gas phase (80/20; 1 bar); Part 2: tests in the presence of a H 2 gas phase (1 bar). Test Ab_Y_2 also featured an additional condition with added barite (BaSO 4 ). Test Ab_P_1 was carried out with aquifer rock rather than calcite. C: abiotic controls; A/A’: trials used for molecular biology analysis; B: trials used for physicochemical analysis. X%/Y%: written on histograms; X% indicates the theoretical percentage of H 2 consumed by methanogens as a function of the number of mmol of CH 4 produced based on the hydrogenotrophic methanogenesis reaction (4H 2 + CO 2 → CH 4 + 2H 2 O); Y% indicates the theoretical percentage of H 2 consumed by other hydrogenotrophic microorganisms (total H 2 disappeared—H 2 consumed by methanogens). Figure 5. Taxonomic diversity of prokaryotes based on the 16S rRNA gene in different enrichment cultures at the end of incubation in the presence of H 2 . (A) Heatmap representing taxonomic diversity results based on the 16S rRNA gene. The 50 dominant phylotypes, representing between 86% and 99% of sequences in each culture trial, are indicated. (B) Heatmap showing the taxonomic diversity results based on 16S rRNA gene transcripts. The 50 dominant phylotypes, representing between 83% and 99% of sequences in each cultivation trial, are shown. H 2 : incubation with H 2 in the gas phase; H 2 CO 2 : incubation with H 2 /CO 2 (80/20; 1 bar) in the gas phase; C: incubation with calcite; Wt: incubation without calcite; R: incubation with rock; WtR: incubation without rock; and Ba: incubation with barite. Final microbial taxonomic diversity of cultivation trials with H 2 /CO 2 Prokaryotic taxonomic diversity was studied at the end of incubation in biotic assays with a gas phase consisting of H 2 or H 2 /CO 2 . These biomethanation conditions strongly selected for microbial communities, as previously reported (Bellini et al. 2022 ). In order to test a large number of conditions, it was decided not to use culture replicates for taxonomic diversity analyses, which can make it difficult, if not impossible, to interpret the evolution of complex microbial communities. Bearing this limitation in mind, we can only note the astonishing maintenance of a few prokaryotic genera present on all the sites tested, and that it is not possible to draw general conclusions on community behavior and changes without appropriate replication. The relative abundances of the 50 dominant ASVs obtained from high-throughput sequencing of the 16S rRNA genes of the different communities are represented in the form of a heatmap (Fig. 5A ). Although each condition tested was only in a single replicate for taxonomic diversity analyses, hydrogenotrophic methanogenesis was systematically carried out by members of the Methanobacteriaceae family, which includes the genera Methanobacterium and Methanobrevibacter , and the Methanothermobacteriaceae family (i.e. Methanothermobacter spp.), as confirmed by analysis of the mcrA genes in the same samples ( Fig. S2, Supporting Information ). The corresponding 16S rRNA gene transcripts showed activity until the end of incubation (Fig. 5 \n B ). These archaeal families are regularly highlighted in microbial communities in deep aquifers (Kotelnikova et al. 1998 , Ma et al. 2019 , Kadnikov at et al. 2020 , Ranchou-Peyruse et al. 2019 , 2021 , Moliková et al. 2022 ) and were assumed to be responsible for in situ biomethanation in the case of town gas storage at the Lobodice site (Czechia; Buzek et al. 1994 , Moliková et al. 2022 ). The growth conditions interfered with the representativeness of ASVs but ultimately had little influence on the results at the genus level. In the majority of trials, methanogenesis was carried out by members of the genus Methanobacterium (ASV16-16S, ASV4-16S, ASV13-16S, ASV25-16S, ASV46-16S, ASV48-16S, and ASV58-16S). In samples Ab_L_7, Ab_L_10, Ab_Y_2, and Ab_P_1, members of the Methanothermobacter genus were also represented. Their presence is unexpected, because of formation water temperatures at the bottom of the wells range from around 37°C to 40°C. These temperatures are deduced from temperature gradient measurements taken during logging operations (Gal et al. 2021 ). In 2019, archaea belonging to the Methanopyraceae family, a group of exclusively hyperthermophilic microorganisms, were identified at sites Ab_L_1, Ab_L_3, Ab_L_7, and Ab_L_10 (Ranchou-Peyruse et al. 2019 ). Faults allowing fluid circulation between the different superimposed aquifers could explain these results in the context of a sedimentary basin strongly impacted by the proximity of the Pyrenean mountain range and could explain the frequent detection of a priori strictly thermophilic organisms in the shallower mesothermal aquifers. However, this hypothesis does not explain why thermophilic microorganisms could be active and thrive at temperatures so far from these optima, even in this study with an incubation temperature of 37°C (Fig. 5 ). We hypothesize that these archaea are eurythermal or simply mesophile. The same was true of the order Thermotogales , which includes thermophiles. Environmental sequences of this order had been detected in mesothermal environments, such as a UGS in the Paris sedimentary basin (−830 m; Berlendis et al. 2010 ). Isolation from the aquifer’s formation water enabled to isolate a new species, Mesotoga infera , which can grow from 30°C to 50°C, with a growth optimum at 45°C (Ben Hania et al. 2013 ). Note that the Methanobrevibacter genus was also detected in formation water from well Ab_Y_2 (ASV49-mcr; Fig. S2 , Supporting Information ). Notably, the diversity study was carried out at the end of incubation when the sulfate had largely been consumed, i.e. under conditions that are a priori more favorable for methanogens than for sulfate reducers. For the results based on the 16S rRNA gene and its transcripts, while sulfate reducing conditions were constant in all cultivation trials, each enrichment culture seemed to be exclusively dominated by a phylogenetic group of sulfate reducers such as the genera Desulfovibrio (Ab_L_3, Ab_L_8, Ab_Y_2, and Ab_P_1), Thermodesulfovibrio (Ab_L_10) or Desulforamulus (Ab_L_1, Ab_L3, Ab_L_7, and Ab_L_10), suggesting competition between these different taxa (Fig. 5 ). The diversity of this group based on the dsrB gene ( Fig. S3 , Supporting Information ) is more nuanced but could be explained by the persistence of spores in the assays and the greater specificity of the primers targeting the dsrB gene than the more generalist primers targeting the 16S rRNA gene. This presumed higher specificity would also explain the detection of genera not identified by 16S rRNA -based approaches ( Desulfosporosinus, Desulfosarcina, Desulfobulbus , and LA-dsrAB), and therefore justifies the systematic use of the dsrB gene for the study of this functional group. Sporulating sulfate reducers are regularly found in deep continental environments and often described as lithoautotrophic (Aüllo et al. 2013 ). These bacteria are represented in all trials by one or two phylogenetic groups close to the genera Desulfosporosinus, Desulfotomaculum , and Desulforamulus or even the LA-dsrAB group (Müller et al. 2015 ). While these sulfate reducers have already been identified in this aquifer, some have also been identified in other UGS sites in aquifers, such as members of the Desulforamulus genus and microorganisms close to the strain formerly named Desulfotomaculum profundi Bs107 (Aüllo et al. 2016 , Berlendis et al. 2016 ). In addition to these microorganisms, others persist in these simplified communities and have already been identified in a previous study carried out on this aquifer ( Burkhoderiaceae, Pseudomonadaceae , and Rhizobiaceae ; Ranchou-Peyruse et al. 2023 ). Their survival can be explained by a fermentative metabolism, as in the case of members of the genus Pseudoclostridium (ASV44-16S) and the phylogenetic group DTU014 (ASV68-16S; Dyksma et al. 2020 ). Under the conditions studied, no ASVs could be matched to any of the homoacetogenic bacteria previously described. Microbiological assessment of dedicated H 2 storage in the lower Eocene The formation water for well Ab_P_1 comes from a reservoir located at a lower level than the aquifer currently used as a UGS site, which itself evolved in a geological layer dating from the Eocene (Fig. 1 \n B ). A rock sample from the same horizon as Ab_P_1, at the boundary of the Eocene and Dano-Paleocene, was obtained and used in the tests in place of calcite. This rock is composed of 63% quartz, 13% calcite, 16% clay, and 7% pyrite (DRX/FluoX analysis, TEREGA data). During the first sampling campaign, this formation water had one of the highest concentrations of methanogenic archaea, with 2.62 × 10 2 ± 5.7 × 10 1 mcrA gene copies ml −1 . The methane production from Ab_P_1 formation water in the presence of H 2 /CO 2 gas (80/20; 1 bar) was among the highest and did not increase in the presence of rock (Fig. 4 ; Fig. S4, Supporting Information ). After 2 months of rock-free incubation with a gas phase composed of H 2 /CO 2 , the test carried out with formation water from site Ab_P_1 showed a production of 3.3 × 10 −1 mmol of CH 4 in 2 months with a total consumption of 3.8 mmol of H 2 . With rock incubation, H 2 consumption almost doubled (6.4 mmol) and CH 4 production decreased (1.4 × 10 −1 mmol), revealing increased activity of metabolisms other than methanogenesis. Conversely, when the gas phase was composed solely of H 2 (1 bar), the yield was among the lowest. For the other sites, the highest pH values were obtained in the absence of CO 2 in the gas phase and were associated with the lowest Ca 2+ and HCO 3 − concentrations ( Fig. S4 and Table S2 , Supporting Information ). The results presented in Fig. S5 ( Supporting Information ) clearly illustrate the strong similarity between the taxonomic diversity obtained from the 16S rRNA genes and that obtained from their transcripts. For batch cultures with very limited available nutrients, this result is interesting, as it suggests a restructuring of the microbial community with strong recycling of the necromass constituted by microorganisms that are not adapted to the experimental conditions and leave no remnant DNA. From an initial state mainly dominated by sporulating sulfate-reducing Firmicutes affiliated with the Desulfurispora genus, the communities were subsequently all dominated by hydrogenotrophic methanogenic archaea belonging to the Methanobacteriaceae or Methanothermobacteriaceae families. The results suggest that the members of Methanothermobacteriaceae are not all thermophilic since the environmental factor selecting them was not temperature, but rather the acid pH induced by the addition of CO 2 associated with one or more nutrients released into the rock. We note that while the addition or nonaddition of calcite or rock did not have any effect on the structuring of microbial communities based on H 2 and CO 2 consumption and production and dominated by methanogens and sulfate reducers. Regarding calcite, rock, or even barite supplementation, the diversity may differ between communities at the ASV level, but this variation is very low, or even nonexistent, at the microbial genus level. However, these minerals represent a carbon source (calcite dissolution), sulfate source (barite dissolution), and buffer for microorganisms, they had little impact on the structure of the sulfate-reducing functional group and none on that of methanogens. These results suggest that the ecological valence of these microorganisms is stronger than expected. For example, members of the genus Methanobacterium show activity at pH values ranging from ∼6 (conditions with H 2 /CO 2 ) to around pH 10. While alkalinization is often associated with methanogenesis and sulfate reduction, a sharp increase in pH has been shown to be responsible for the cessation of methanogenesis. Here, methane production yields were lower when the gas phase was composed solely of H 2 (without CO 2 ), even in the presence of calcite as an indirect carbon source. On deep aquifers with mineralogically more complex reservoir rocks, a recent study experimentally simulating H 2 injections into a high-pressure three-phase reactor (gas–rock–water) with indigenous microorganisms suggested similar alkalinization during physicochemical modeling (Mura et al. 2024 ). Here, the rock of the aquifer studied is essentially composed of quartz (81%), while calcite was estimated at around 12% (Haddad et al. 2023 ). It is reasonable to assume that the buffering effect of the aquifer rock is greater than that of our test media, but over the lifetime of such a storage facility (i.e. several decades), it seems likely that minerals such as calcite will be almost completely dissolved, given their low concentrations. On the other hand, bearing in mind that even at the highest pH and based on the study of the 16S rRNA, dsrB , and mcrA genes transcripts, methanogenic archaea continued to be active, we hypothesize that the low methane yields may be more related to a limitation of CO 2 solubilization rather than to a deleterious effect of pH on the physiological activity of the hydrogenotrophs present."
} | 11,582 |
39468862 | PMC11733720 | pmc | 3,246 | {
"abstract": "Abstract Neural networks as a core information processing technology in machine learning and artificial intelligence demand substantial computational resources to deal with the extensive multiply‐accumulate operations. Neuromorphic computing is an emergent solution to address this problem, allowing the computation performed in memory arrays in parallel with high efficiencies conforming to the neural networks. Here, scalable synaptic transistor memories are developed from solution‐sorted carbon nanotubes. The transistors exhibit a large switching ratio of over 10 5 , a significant memory window of ≈12 V arising from charge trapping, and low response delays down to tens of nanoseconds. These device characteristics endow highly stabilized reconfigurable conductance states, successful emulation of synaptic functions, and a high data processing speed. Importantly, the devices exhibit uniform characteristic metrics, e.g., with a 1.8% variation in the memory window, suggesting an industrial‐scale manufacturing capability of the fabrication. Using the memories, a hardware convolution kernel is designed and parallel image processing is demonstrated at a speed of 1 M bit per second per input channel. Given the efficacy of the convolution kernel, a promising prospect of the memories in implementing neuromorphic computing is envisaged. To explore the potential, large‐scale convolution kernels are simulated and high‐speed video processing is realized for autonomous driving.",
"conclusion": "3 Conclusion In this work, we have successfully realized scalable fabrication of charge trapping s‐SWCNT synaptic transistor memories. The memories demonstrate highly‐stabilized reconfigurable conductance states, successful emulation of the biological synaptic functions, and a high data processing speed. Notably a high uniformity in the device performance characteristic metrics is proved, suggesting the capability of our device fabrication for industrial‐scale manufacturing. These above device characteristics allow us to design and implement hardware convolution kernel using the memories for high‐speed convolution image processing. We show the key convolution operation for edge detection using the Sobel operators. Given the efficacy of the convolution kernel, we envisage the use of the hardware convolution kernel in real‐time high throughput information processing. As demonstrations, we simulate large‐scale convolution kernels for high‐speed edge detection and noise reduction of videos (Videos S2 and S3 , Supporting Information) to explore the potential of our synaptic transistor memories in practical neuromorphic computing applications in, for instance, autonomous driving.",
"introduction": "1 Introduction Neural networks, computational frameworks with nonlinear mapping, parallel data processing, and adaptive learning capabilities are a core information processing technology in machine learning and artificial intelligence. [ \n \n 1 \n , \n 2 \n \n ] However, their implementation can demand substantial computational resources to deal with the extensive multiply‐accumulate operations for reliable results. This poses challenges for the computing hardware, particularly, the von Neumann computers where the data has to be moved constantly between the processing and memory units for computation—the slow access to the memory limits the computation speed, while the constant data movement consumes energy. [ \n \n 3 \n \n ] Neuromorphic computing emerges as a promising solution to address this issue. In this architecture, using emerging nonvolatile memory arrays, the data can be processed in high parallelism to perform the matrix multiply‐accumulate operations following the Ohm's and Kirchhoff's laws, conforming to the neural networks. [ \n \n 4 \n \n ] Recent advances show that synaptic transistor memories with reconfigurable conductance states and synaptic functions are a promising memory technology for neuromorphic computing. [ \n \n 5 \n , \n 6 \n , \n 7 \n , \n 8 \n , \n 9 \n \n ] Particularly, with a transistor configuration, the memories can allow data programming and read operations with a higher precision, greater freedom, and lesser crosstalk in the memory arrays. [ \n \n 10 \n \n ] \n Synaptic transistor memories can be typically realized with electrochemical, [ \n \n 6 \n , \n 11 \n \n ] ferroelectric, [ \n \n 7 \n , \n 9 \n \n ] and floating‐gate mechanisms. [ \n \n 5 \n \n ] Among them, the electrochemical transistor memories with low voltage operation and linear weight (i.e., conductance state) updating capabilities draw considerable interest. However, the need to introduce ions, typically liquid electrolytes, into the gate dielectric is problematic for integration with the complementary metal‐oxide‐semiconductor (CMOS) manufacturing processes. The ferroelectric and floating‐gate transistor memories, on the other hand, are CMOS‐compatible and allow fast switching and stable weight updating. However, the memory in these transistors is achieved using multilayer structures, which often require complex fabrication processes that can incur high production cost. Different from these synaptic transistor memories, devices based on nanomaterials and a charge trapping mechanism appear to be promising. [ \n \n 12 \n \n ] For instance, carbon nanotubes with high carrier concentrations, high carrier mobilities, and the largest specific surface area are reported to exhibit active surface chemistry and this can be exploited to develop charge trapping electronic devices with prominently regulatable conductance states. [ \n \n 13 \n , \n 14 \n \n ] Indeed, carbon nanotubes have been recently widely reported in charge trapping synaptic transistor memory fabrication. [ \n \n 15 \n , \n 16 \n , \n 17 \n , \n 18 \n , \n 19 \n \n ] However, the memory mechanism may require a detailed examination and, at the current development stage, the fabrication needs optimization for scalable high‐performance devices, particularly towards their implementation of neuromorphic hardware. The major obstacle from lab to fab is at the engineering level, including the sorting of carbon nanotubes, the development of large‐scale films, the scalable device fabrication, and the compatibility of the fabrication to the current semiconductor processes. [ \n \n 20 \n \n ] The implementation of neuromorphic hardware also requires careful engineering considerations for designing multiply‐accumulate computing arrays. [ \n \n 6 \n , \n 21 \n \n ] \n Herein, in this work, we develop scalable synaptic transistor memories from solution‐sorted semiconducting single‐walled carbon nanotubes (s‐SWCNTs). The memories exhibit a large switching ratio of over 10 5 , a significant memory effect with a memory window of ≈12 V, and low response delays down to tens of nanoseconds. Our analysis reveals that the memory arises from the charge trapping in the sorting polymer. These above device characteristics endow highly‐stabilized reconfigurable conductance states, successful emulation of biological synaptic functions, and a high data processing speed. Leveraging solution‐processing and photolithographic patterning, the fabrication is scalable and demonstrates uniform memory characteristic metrics, e.g., with a 1.8% variation in the memory window. Capitalizing on the device characteristics and the fabrication scalability, we design memory arrays to function as a hardware convolution kernel, and perform parallel convolution image processing at a speed of 1 M bit per second per input channel. Given the efficacy of the hardware convolution kernel, we simulate large‐scale kernels for high‐speed edge detection and noise reduction of videos to explore the potential of our memories in practical neuromorphic computing applications."
} | 1,921 |
32689917 | null | s2 | 3,247 | {
"abstract": "Biofilms are the dominant bacterial lifestyle. The regulation of the formation and dispersal of bacterial biofilms has been the subject of study in many organisms. Over the last two decades, the mechanisms of "
} | 52 |
35409042 | PMC8998331 | pmc | 3,248 | {
"abstract": "Hydrophobic fibrous slippery liquid-infused porous surfaces (SLIPS) were fabricated by electrospinning polydimethylsiloxane (PDMS) and polystyrene (PS) as a carrier polymer on plasma-treated polyethylene (PE) and polyurethane (PU) substrates. Subsequent infusion of blackseed oil (BSO) into the porous structures was applied for the preparation of the SLIPS. SLIPS with infused lubricants can act as a repellency layer and play an important role in the prevention of biofilm formation. The effect of polymer solutions used in the electrospinning process was investigated to obtain well-defined hydrophobic fibrous structures. The surface properties were analyzed through various optical, macroscopic and spectroscopic techniques. A comprehensive investigation of the surface chemistry, surface morphology/topography, and mechanical properties was carried out on selected samples at optimized conditions. The electrospun fibers prepared using a mixture of PDMS/PS in the ratio of 1:1:10 (g/g/mL) using tetrahydrofuran (THF) solvent showed the best results in terms of fiber uniformity. The subsequent infusion of BSO into the fabricated PDMS/PS fiber mats exhibited slippery behavior regarding water droplets. Moreover, prepared SLIPS exhibited antibacterial activity against Staphylococcus aureus and Escherichia coli bacterium strains.",
"conclusion": "4. Conclusions SLIPS have been fabricated on polyethylene PE and polyurethane PU substrates by electrospinning polystyrene PS/PDMS fiber mats with subsequent BSO infusion. Various surface morphologies, including beads with different sizes and shapes, bead-on-string structures, as well as well-defined fibers with various diameters, were formed during the electrospinning process. Results showed that all the prepared fibrous structures showed high resistance to wetting due to their surface hydrophobicity (contact angle > 100°). Upon using PS in PDMS as a carrier polymer, well-defined bead-free fibers were obtained by a direct electrospinning solution containing PS/PDMS/THF (1:1:10). Plasma treatment acted as an adhesion promoter between the polymeric substrate and PS/PDMS electrospun fiber mats, which was confirmed by peel resistance measurements. The subsequent infusion of natural BSO into the porous structures caused slippery behavior, as was confirmed by sliding angle measurements at 10° of titling angle. Moreover, the antibacterial properties of prepared SLIPS on PU and PE have been investigated and found to exhibit significant antibacterial activity against Gram-positive S. aureus and Gram-negative E. coli bacteria.",
"introduction": "1. Introduction Biofouling refers to the phenomena of the aggregation and growth of live organisms on wet surfaces and membranes [ 1 , 2 ]. This has a significant impact on liquid transportation, non-fouling marine devices, desalination membranes, and health care devices [ 3 , 4 , 5 , 6 , 7 , 8 ]. Coating nanoparticles (NPs) on the side in contact with the liquid is one method to prepare an anti-biofouling surface. Ag, TiO 2 , ZnO, and Cu NPs are found to exhibit antimicrobial properties, which primarily kill the microorganisms settled on the surface, acting as a biocide. The synthesis of these NPs is costly and increases the overhead in production for possible commercialization. Furthermore, the performance is reported to decline over time, mainly due to the poor addition of the coat with the substrate. Studies have been conducted on NPs on a graphene oxide (GO) matrix to mitigate some of the concerns encountered with coating pristine metal or metal oxide NPs on membranes. Ag NPs on GO [ 9 , 10 ] and Fe NPs on GO systems [ 11 , 12 ] have been extensively studied in this regard and have been found to demonstrate a synergistic effect. However, they have limited applications, and approaches to fabricate anti-biofouling materials based on different principles are in demand. In health care devices, such as catheters, biofouling control is highly regarded, as this allows pathogens to accumulate and spread diseases. One easy way to overcome this issue is by maintaining the dryness of the surface and sliding away any liquid drops incident on the surface. This approach is more environmentally friendly than biocidal coatings. SLIPS [ 13 , 14 ] are the most recent improvement, addressing weaknesses caused by superhydrophobic surfaces [ 15 , 16 ]. Superhydrophobic surfaces have micro/nanostructures on the surfaces that are capable of holding an air layer in between them, preventing the surface from becoming wet by liquid. Conversely, in SLIPS, a lubricating thin film coated on the surface makes sure the liquid droplets on the surface slide away. This concept is inspired by the natural pitcher plant [ 17 ], which has a thin lubricating layer on the rough microscopic structures on its peristome. This lubricating film reduces the friction so that any small organism incident on the petal slides to the digestive tract of the plant. Polydimethylsiloxane (PDMS) is an elastomeric polymer with low surface energy, high transparency, biocompatibility, and high hydrophobicity [ 18 ]. Therefore, PDMS has been reported to exhibit high contact angles >100° and a slippery effect [ 19 ]. This water repellency characteristic is important in fouling/contamination prevention [ 20 ]. For this reason, PDMS has been diversely used in many applications, including, but not limited to, membrane fabrication [ 21 ], biomedical devices [ 22 ], and the fabrication of superhydrophobic and/or self-cleaning surfaces [ 23 ]. However, pristine PDMS has poor fouling resistance and weak adhesion to substrates [ 24 ]. Therefore, PDMS is typically combined with a second component or a mixture to achieve an amphiphilic surface with biofouling activity [ 25 , 26 , 27 ]. The surface topographies present on the surface decrease the interfacial bonding and thereby inhibit contaminant attachment [ 28 ]. PDMS is typically used as either a dense film or fibrous structure. Fibrous PDMS possess high porosity, a large surface area, and remarkable mechanical properties; therefore, it has much wider applications than PDMS films. Fabrication of fibrous networks can be done using the electrospinning technique. Electrospinning has been employed for decades to produce various materials and has proven to be a simple, versatile, and cost-effective technique for the production of thin fibers of nanometer- to micrometer-sized diameters [ 29 ]. This method can be applied using a wide range of materials, ranging from natural and synthetic polymers to polymer composites [ 30 , 31 , 32 , 33 ]. PDMS has a low molecular weight, and its chain entanglements are typically not enough to provide sufficient crosslinking to form fibrous filaments. For this reason, PDMS is typically incorporated with another carrier polymer to form electrospun fiber mats. Correspondingly, polystyrene (PS) is a suitable candidate for this application, representing an amorphous, transparent polymer with good stiffness and high resistance to electrical forces. PS fiber mats are applied in many industrial aspects, including as ion exchangers [ 34 ], in filtration [ 35 ] for water purification and some other membrane applications, in medical uses as an enzyme immobilizer [ 36 ], in tissue engineering [ 37 , 38 ], in packaging, and as insulation [ 33 ]. Typically, two methods are employed to produce electrospun fiber mats: (1) solvent spinning and (2) melt spinning. By far, dissolving the polymer using appropriate solvents is the more widely used method since it is a more adjustable technique. Moreover, the diameter of melt-spun fibers ranges from about 5 µm to 200 µm, whereas electrospun fibers can have diameters in the nanometer range [ 39 ]. In the electrospinning process, a polymer solution is placed in a syringe/needle that is subjected to an external electric field applied at the end of the needle [ 40 ]. A polymer droplet (known as a Taylor cone) is formed, and when the charge on the surface becomes higher than the surface tension, continuous polymer jets are ejected from the tip of the syringe, which splits into bundles of smaller fibers on a collector surface. The produced thin fibers have a very high surface-to-volume ratio and a high number of fibrous pores [ 30 , 32 ]. Such a technique offers many opportunities to construct controllable surface properties, such as the fiber’s morphology, chemical composition, and functionality. The properties of the electrospun fibers will depend mainly on the polymer’s molecular weight, viscosity, and conductivity [ 41 ]. To produce uniform, bed-free fibers, several process parameters need to be adjusted during the electrospinning process, including the distance between the syringe and the collector, applied voltage, and solution concentration. An increase in the voltage beyond a critical value typically results in the formation of beads and an increase in the fiber diameter due to the increase in the jet velocity [ 42 ]. Moreover, when the polymer solution concentration is low, the entanglements of the polymeric chains will break into small fragments before reaching the collector [ 43 ]. Similarly, the distance between the needle tip and the collector plays a vital role in the properties of the electrospun fibers, specifically the morphology. The surface morphology mainly depends on the deposition time and evaporation rate; hence, a proper distance is required to produce uniform fibrous matrices [ 44 ]. The fibers can be tailored depending on the properties/specifications required for their usage. In this study, novel SLIPS have been fabricated by electrospinning polystyrene PS/PDMS fiber mats on polyethylene PE and polyurethane PU substrates with subsequent BSO infusion. BSO is commonly used in medicine because it demonstrates antimicrobial, anti-inflammatory and antioxidant effects and no cytotoxicity towards human peripheral blood mononuclear cells [ 45 ]. The process conditions were optimized to yield a homogenous fibrous mat with the desired properties. The anti-wetting/hydrophobic properties of the prepared fibers, as well as morphology, mechanical properties, and chemical composition, have been thoroughly analyzed. The expected end-use of these SLIPS is on health care products made up of PE or PU. In addition, a biocompatible lubricant like BSO with its natural character and antimicrobial properties, containing 32 compounds, including 9-eicosyne (63.04%), linoleic acid (13.48%) and palmitic acid (9.68%) as major constituents [ 46 , 47 ], in addition to its multiple medicinal properties encourages the implementation of such systems in commercial practice. Antibacterial properties of prepared SLIPS on PU and PE have been investigated and shown to exhibit significant antibacterial activity against Gram-positive S. aureus and Gram-negative E. coli bacteria.",
"discussion": "2. Results and Discussion 2.1. Fiber Mat Characterization 2.1.1. Surface Morphology/Topography Analysis Electrospun fiber mats composed of PDMS and PS were utilized to create hydrophobic porous structures for oil infusion. The use of PS in THF with a concentration of 10% w / v ( Figure 1 a) led to the creation of well-shaped thick fibers. A combination of PDMS with PS overcomes problems with the electrospinning process of pure PDMS [ 48 ]. In order to improve the fiber mats’ production processes, several concentrations of the PS/PDMS/THF solution were tested (conditions are provided in Table 1 ). Using a 1:1:8 ratio of PS/PDMS/THF resulted in the formation of fibers with different diameters and led to the formation of a glue-like fibrous matrix. Nevertheless, SEM images ( Figure 1 b) of the fibers confirmed the formation of fibrous structures, which proves the good integrity between PS and PDMS in forming a homogenous spinnable polymeric solution. The water contact angle (WCA) showed a hydrophobic behavior (WCA = 124.0 ± 3.6°) ( Table 2 ). Upon increasing the THF solvent content in the polymer mixture (1:1:10 PS/PDMS/THF), the viscosity of the mixture decreased, which resulted in the formation of well-defined fibers. This resulted in fiber mats with larger diameters (rougher surface); hence, the hydrophobicity increased (the contact angle of water for PS/PDMS/THF with a ratio of 1:1:8 was 124 ± 3.6° in comparison with 149.4 ± 3.2° for the PS/PDMS/THF mixture with a ratio of 1:1:10). Decreasing the ratio of PS to PDMS (0.5:1:10) ( Figure 1 ) led to the formation of very thin fibers surrounded by flocs. Moreover, increasing the PS content in the PS/PDMS solution (1.5:1:10) led to the formation of beaded fibers. The formation of flocs might be caused by the low net charge density of the prepared polymer solution [ 31 ]. However, the water contact angle was 141 ± 3.8°, which was relatively close to 1:1:10 PS/PDMS/THF (149 ± 3.2°) ( Table 2 ). Figure 2 shows SEM and EDX mapping of the cross-section of electrospun fiber mats containing PS/PDMS/THF—1:1:10 (g/g/mL), confirming the presence of C, O, N and Si elements. Both polymers, PDMS and PS, contribute to C and O elements due to their chemical structures. Distinguishable N and Si elements in Figure 2 b confirm the homogenous distribution of PDMS within the electrospun fiber mats. The cross-section view of the fibers in Figure 2 a demonstrates that the formed fiber is homogeneous and uniform. The optimized electrospun fibers prepared using the mixture of PS/PDMS in the ratio of 1:1:10 (g/g/mL) using THF solvent on Al foil was used for the formation of fiber mats on the plasma-pre-treated PE and PU substrates, which were used as SLIPS for oil infusion. AFM was performed to provide detailed information about surface morphology/topography of the optimized electrospun fiber mats from the 80 × 80 µm 2 surface area ( Figure 3 ). This analysis provides information on fiber diameter and the structural features of the fiber mats. It can be observed that the fiber mats produced using neat PS/THF solution (1:10 g/mL) are homogeneous and well-packed; hence, they are expected to possess a relatively small pore size. Smaller pore sizes cause an enhancement in surface hydrophobicity due to the decreased ability of water to penetrate through porous structures. Moreover, it can be remarked that the surface roughness represented by the Ra value (arithmetic mean of line profile) was 501 nm, while surface roughness is a significant factor affecting the hydrophobicity of the surface. The diameter of the fibers can be estimated by measuring the dz of particular peaks in the line profile graphs obtained from ZSensor AFM images. The diameter of PS fibers was approximately 300–700 nm. In the case of the fiber mats fabricated using the polymeric mixture PDMS/PS/THF—1:1:10 (g/g/mL), the fabricated fiber mats excelled with rougher structures, while Ra achieved 1989 nm, caused by the larger diameter of particular fibers around 2–2.5 µm. This increased roughness was responsible for the high water contact angle value (WCA = 149.4 ± 3.2°). The optimized PS/PDMS samples were subsequently used for the preparation of SLIPS on PE and PU substrates, which is discussed later. 2.1.2. Characterization of Mechanical Properties Characterization The investigation of the mechanical properties was done thoroughly using the nano-indentation measurements by AFM with an MFP-3D Nanoindenter. Hardness and reduced Young’s modulus (E c ) were measured and calculated as penetration of indenter tip into the fiber mats’ surfaces in different areas and taking an average of 10 points. As the indenter penetration depth was in the range of 2–4 µm, it is assumed that the obtained mechanical properties are attributed to the fiber mats and not only particular fibers. This allowed average values of hardness and E c with standard deviations to be obtained, as shown in Table 3 . The relation between stiffness and hardness can vary based on the properties of each material. In practice, the E c of the produced PS fibers prepared in THF solvent was 3.4 ± 0.7 MPa, and their hardness was 0.4 ± 0.2 MPa. In coexistence with PDMS, the E c and hardness of PS/PDMS even increased. The E c value was greater than in the neat PS, achieving a value of 7.2 ± 1.2 MPa, and hardness was increased around 3 times, achieving a value of 1.1 ± 0.3 MPa. Compared to the literature, the mechanical properties of the produced fibers were similar to neat PDMS [ 49 ]. 2.1.3. Chemical Composition Analyses The chemical composition of the fabricated electrospun fiber mats was analyzed using FTIR-ATR to confirm the presence of certain functional groups. The results are shown in Figure 4 . PS in its pure form contains a styrene aromatic ring, which is in agreement with the literature [ 50 ]. The main peaks of the pure form shown in Figure 4 are –CH stretching at 3081 cm –1 –3001 cm −1 of the aromatic ring resonation. The stretching of –CH at 2923 cm −1 and CH 2 at 2850 cm −1 originates from the asymmetric and symmetric stretching vibrations. The mono-substitution of the benzene ring of styrene occurs at 1943–1728 cm –1 , and the deformation between –CH 2 and C–C in the aromatic ring occurs at 1500 cm –1 . PDMS in its pure form contains three main peaks [ 51 ]: an Si–CH 3 peak at 1270 cm −1 , O–Si–O at 1160 cm −1 , and a methyl group –CH at 2980 cm −1 . When both the polymers were mixed, PS and PDMS shared only the same solution, and their peaks were merged but not reacted. This was observed from the peaks of the PS/PDMS spectrum. The peaks of O–Si–O and –Si–CH 3 were shown with high intensity at 1160 cm –1 and 1270 cm –1 . Interestingly, the whole peaks of PS were observed in the mixed fibers with lower intensity than the pure form, but no shifting in the wavenumber was observed. The stretching of the peaks of –CH (PS and methyl groups in PDMS) was observed at 3030 cm –1 and 2960 cm –1 . The aromatic C–C was found at 1500 cm –1 in the FTIR spectrum of PS/PDMS, and it confirmed the successful incorporation of PS with PDMS. 2.1.4. Adhesion Investigation The plasma treatment was used to improve the wettability and adhesion characteristics of PE and PU substrates prior to the deposition of the PS/PDMS fiber mats. Analyses of adhesion between polymeric substrates and produced electrospun fiber mats were carried out by peel test measurements using Scotch tape. Figure 5 shows peel resistance (peel force per entire width) between PS/PDMS fiber mats and the PE and PU substrates. Peel resistance of untreated PE was relatively low, achieving a value of 3.9 ± 1.5 N/m. The plasma treatment was responsible for an improvement in the adhesion of PE, while peel resistance increased to 6.2 ± 0.8 N/m. More visible differences were observed for PU. The peel resistance of untreated PU was much lower compared with untreated PE, achieving 0.1 ± 0.1 N/m because of the lower surface free energy of PU. Plasma treatment led to a remarkable increase in adhesion, while peel resistance increased to 0.4 ± 0.2 N/m. The improvement of the adhesion of the plasma-treated polymeric surface was caused by the improvement in wettability as a result of changes in the functionalization and roughness [ 52 , 53 ]. 2.2. Characterization of SLIPs 2.2.1. Surface Morphology/Topography Analysis SEM and AFM techniques were used to analyze fabricated SLIPS on the PE and PU substrates. The surface morphology/topography images of the PE and PU substrates with applied PDMS/PA/BSO are shown in Figure 6 . A relatively homogeneous infusion of BSO into the porous structures of PS/PDMS fiber mats was observed by SEM images, while only a few uncovered fibers were present. Further detailed surface morphology/topography characterization of prepared SLIPs was analyzed by AFM from the 40 × 40 µm 2 surface area. The PS/PDMS/BSO SLIPS fabricated on the PE substrate were characterized by a smoother surface (Ra = 91.6 nm) in comparison with the same fabricated on the PU substrate, while Ra achieved 288.7 nm. Moreover, the line profile revealed the irregularities of SLIPS on the PE substrate, with a maximum of about 785 nm in comparison to the 2085 nm for PS/PDMS/BSO SLIPS fabricated on the PU substrate in the entire surface area. 2.2.2. Slippery Behavior Investigation As mentioned, slippery behavior observed in SLIPS provides an environmentally way to combat the adhesion of pathogens or any particle of that sort on a surface. In this concern, PDMS/PS/THF—1:1:10 (g/g/mL) fiber mats fabricated on plasma-treated PE or PU substrates were converted into a slippery surface by modification with natural-based BSO via spin coating. Visual examination of the BSO layer revealed it to be stable and sufficiently wet within the fiber mat substrate. Pathogens are more easily transported by water than any other liquid encountered during daily activities. Hence, water was employed as the model-impinging liquid to evaluate the potential liquid-repellent performance of BSO-infused PDMS/PS fiber mats. PDMS/PS fiber mats on substrate exhibited a WCA of ~149°, which was reduced to ~78° for PDMS/PS/BSO-PU and ~67° with PDMS/PS/BSO-PE. The key requirements of the lubricating liquid (BSO) are to have a higher affinity for the fiber mat surface compared to that of the impinging liquid (water) and for the two liquids to be immiscible [ 14 ]. Immiscibility is confirmed by the satisfactory water contact angle values depicted in Figure 7 . As can be seen, BSO-infused fiber mats prepared on the PU substrate demonstrated faster sliding behavior than on the PE substrate. Additionally, water droplets of 3 µL, used to avoid the line pinning effect, had a more globular structure on the PU substrate ( Figure 7 a), and the shape was maintained throughout the sliding period. Conversely, the droplet was more spread on the PE substrate ( Figure 7 b), as observed by the CCD camera connected to the contact angle measuring device. Precise analysis shows that the translation of the water droplet was similar on both substrates after the initial 50 s. It is also noteworthy that the water droplet was dispensed on the surface at 0°, followed by tilting to 10° at a gentle base to avoid vibrational impacts on the droplet during the sliding stage. At 50 s, the stage reaches a 10° inclination, and the translation of the impinging droplet afterward is distinctly two-fold faster with the BSO-infused fiber mat on the PU substrate. However, PDMS/PS/BSO on both the PU and PE substrates demonstrate favorable sliding behavior with water as the impinging liquid. Thus, the use of a biocompatible lubricant like BSO with multiple medicinal properties encourages the implementation of such systems in commercial practice. 2.2.3. Antibacterial Activity Investigation The antibacterial properties of fabricated SLIPS on the polymeric substrates were evaluated using S. aureus (Gram-positive) and E. coli (Gram-negative) bacterium strains. Increases in the bacterial colonies of the PS/PDMS samples are summarized in Table 4 , and representative photos are shown in Figure 8 and Figure 9 for S. aureus and E. coli , respectively. The fabrication of PS/PDMS fiber mats on the PE or PU substrate demonstrated poor antibacterial activity against S. aureus and E. coli, with poor bacterial proliferation inhibition caused by their chemical nature. However, subsequent fabrication of SLIPS using the BSO infusion into the PS/PDMS porous structures led to a significant improvement in antibacterial activity, as BSO has a strong antibacterial effect. PS/PDMS/BSO-PE samples demonstrated an increase of zero bacterial colonies for both S. aureus and E. coli, and PS/PDMS/BSO-PU samples were characterized by zero colonies for S. aureus and zero or single colonies detectable for E. coli . This analysis proved the significant antibacterial effect of prepared SLIPS."
} | 5,949 |
28362724 | PMC5496671 | pmc | 3,249 | {
"abstract": "Theory predicts that horizontal gene transfer (HGT) expands the selective conditions under which genes spread in bacterial populations. Whereas vertically inherited genes can only spread by positively selected clonal expansion, mobile genetic elements can drive fixation of genes by infectious HGT. We tested this using populations of Pseudomonas fluorescens and the conjugative mercury resistance (Hg R ) plasmid pQBR57. HGT expanded the selective conditions allowing the spread of Hg R : Chromosomal Hg R only increased in frequency under positive selection, whereas plasmid-encoded Hg R reached fixation with or without positive selection. Tracking plasmid dynamics over time revealed that the mode of Hg R inheritance varied across mercury environments. Under mercury selection, the spread of Hg R was driven primarily by clonal expansion while in the absence of mercury Hg R dynamics were dominated by infectious transfer. Thus, HGT is most likely to drive the spread of resistance genes in environments where resistance is useless."
} | 261 |
34693062 | PMC8515249 | pmc | 3,250 | {
"abstract": "Soil microbial communities play a crucial role in soil fertility, sustainability, and plant health. However, intensive agriculture with increasing chemical inputs and changing environments have influenced native soil microbial communities. Approaches have been developed to study the structure, diversity, and activity of soil microbes to better understand the biology and plant-microbe interactions in soils. Unfortunately, a good understanding of soil microbial community remains a challenge due to the complexity of community composition, interactions of the soil environment, and limitations of technologies, especially related to the functionality of some taxa rarely detected using conventional techniques. Culture-based methods have been shown unable and sometimes are biased for assessing soil microbial communities. To gain further knowledge, culture-independent methods relying on direct analysis of nucleic acids, proteins, and lipids are worth exploring. In recent years, metagenomics, metaproteomics, metatranscriptomics, and proteogenomics have been increasingly used in studying microbial ecology. In this review, we examined the importance of microbial community to soil quality, the mystery of rhizosphere and plant-microbe interactions, and the biodiversity and multi-trophic interactions that influence the soil structure and functionality. The impact of the cropping system and climate change on the soil microbial community was also explored. Importantly, progresses in molecular biology, especially in the development of high-throughput biotechnological tools, were extensively assessed for potential uses to decipher the diversity and dynamics of soil microbial communities, with the highlighted advantages/limitations.",
"conclusion": "9 Conclusions and future prospects Terrestrial ecosystems represent 30% of the surface of our planet, and the soil is a biocenosis consisting of microorganisms, soil fauna, and plant roots with only about 20% of living things currently known. Microorganisms play a major role in the soil environment, especially in the rhizosphere; they are involved in the biogeochemical cycling of essential elements, and other interactions which influence the structure or function of soil. Yet, the identification and characterization of these organisms pose many challenges ( Zhou et al., 2015 ). There has been substantial progress in studying soil microbial diversity, due to the advances and increased uses of molecular technologies; they helped identify, and characterize the compositional and functional traits of a range of soil microbial communities. Most of the molecular tools today are highly automated for efficiently processing a large number of samples; they have become more efficient and less expensive tools for research. Despite the progress, much of the soil ecosystem remains little unknown due to the complexity of interactions ( Juzan et al., 2012 ). There are also technical issues related to potential bias in RNA and DNA extraction, PCR, and bioinformatics. Sometimes the true abundance and interaction of different taxa in the soil environment can be difficult to determine based solely on molecular tools ( Ahmad et al., 2011 ). Recently, HTS tools/platforms have been developed and used extensively to study the soil microbial community. Illumina, Roche, and other platforms of high throughput sequencing can focus on targeted genes, functional or shotgun-metagenome sequencing ( Zhou et al., 2015 ). Substantial progress has been made in understanding soil microbial communities using these new HTS technologies, despite some challenges that remained ( Tedersoo et al., 2021 ). Indeed, the effective application of high-throughput molecular tools in studying soil microbial communities depends on the ability to analyze and interpret massive amounts of data properly, about biodiversity, functionality, and ecosystem stability. Further progress in bioinformatics may help in face of complex soil microbial communities ( Abdelfattah et al., 2018 ; Amarasinghe et al., 2020 ; Ramirez et al., 2018 ; Xia et al., 2018 ; Zhou et al., 2015 ).",
"introduction": "1 Introduction Microbes, which have populated the Earth for over 3.5 billion years, are the most dominant living entities in nature, with the biosphere containing an estimated 4–6 × 10 30 prokaryotic cells ( Whitman et al., 1998 ). This microbial wealth is still poorly explored, and it is highly desired to better understand the biodiversity and ecology of soil microbial communities ( Ahmad et al., 2011 ). Bacterial populations have been frequently studied using various molecular biology methods. Indeed, the study through the isolation of bacterial strains using culture media, commonly known as culturomics , allows the identification of a very small proportion of bacterial species present in a given soil sample ( Sarhan et al., 2019 ). Better knowledge of the microbial community is important to improve our understanding of the ecosystem, but it is also a challenging endeavor due to the difficulties of cultivating or directly observing some of the soil microorganisms. Consequently, many of these microbial communities are not yet well characterized ( Jo et al., 2020 ). Several studies have attempted to characterize the microbiome from agricultural ecosystems for a better understanding of soil microbial biodiversity. Since the composition of soil microbial community is influenced mainly by plant species and soil types, the interactions in the soil environment are highly complex, especially between plants and soil microbes ( Wei et al., 2018 ). Microorganisms play an important role in soil structure and organic matter recycling ( Ahmad et al., 2011 ). The secretion of root exudates modulates the structure of the microbial community and its enzymatic activities, which provide important nutrients for plants through degradation and mineralization of soil organic matter ( Andrianarisoa et al., 2010 ; Jacoby et al., 2017 ). Moreover, soil microorganisms are the main mediators of these chemical transformations during nutrient recycling, playing a fundamental role in the biogeochemical process ( Dong et al., 2017 ; Falkowski et al., 2008 ). The use of molecular technologies in microbial ecology research may be linked to the development of molecular phylogeny in the late '60s ( Falkowski et al., 2008 ). Methods used for diversity analysis of microbial communities such as traditional cultural and non-cultural methods (i.e. Random Amplified Polymorphic DNA, RAPD; Real-Time Polymerase Chain Reaction, RT-PCR; Restriction Fragment Length Polymorphism, RFLP; Denaturing Gradient Gel Electrophoresis, DGGE) provided preliminary knowledge of these communities ( Feinstein et al., 2009 ) but would often be insufficient for a comprehensive taxonomic assessment ( Rastogi and Sani, 2011 ). Metagenomic approaches can explore both the functional and structural diversity of soil microbial communities ( Dubey et al., 2020 ). Next-Generation Sequencing (NGS) or High-Throughput Sequencing (HTS) has shown a great potential to reveal the hidden diversity of these communities. HTS allows investigations to a specific habitat, with relatively low cost and high accuracy, radically changing the methodology of research and generating a huge amount of data ( Wei et al., 2018 ). This review attempts to summarize the evolution of HTS tools and highlight the progress made during the last decades to study soil microbial communities. It will also look at the biodiversity and plant-microbe/microbe-microbe interactions in soils, the importance of soil microbiome, and factors that affect the soil microbial community. The strength and weaknesses of different techniques and approaches used for HTS in this field will also be discussed."
} | 1,937 |
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