Sizing up metatranscriptomics

Co-expression analysis reveals distinct alliances around two carbon fixation pathways in hydrothermal vent symbionts

Most autotrophic organisms possess a single carbon fixation pathway. The chemoautotrophic symbionts of the hydrothermal vent tubeworm Riftia pachyptila, however, possess two functional pathways: the Calvin-Benson-Bassham (CBB) and the reductive tricarboxylic acid (rTCA) cycles. How these two pathways are coordinated is unknown. Here we measured net carbon fixation rates, transcriptional/metabolic responses and transcriptional co-expression patterns of Riftia pachyptila endosymbionts by incubating tubeworms collected from the East Pacific Rise at environmental pressures, temperature and geochemistry. Results showed that rTCA and CBB transcriptional patterns varied in response to different geochemical regimes and that each pathway is allied to specific metabolic processes; the rTCA is allied to hydrogenases and dissimilatory nitrate reduction, whereas the CBB is allied to sulfide oxidation and assimilatory nitrate reduction, suggesting distinctive yet complementary roles in metabolic function. Furthermore, our network analysis implicates the rTCA and a group 1e hydrogenase as key players in the physiological response to limitation of sulfide and oxygen. Net carbon fixation rates were also exemplary, and accordingly, we propose that co-activity of CBB and rTCA may be an adaptation for maintaining high carbon fixation rates, conferring a fitness advantage in dynamic vent environments.

Contribution of different macromolecules to the diffusion of a 40 nm particle in Escherichia coli

Due to the high concentration of proteins, nucleic acids, and other macromolecules, the bacterial cytoplasm is typically described as a crowded environment. However, the extent to which each of these macromolecules individually affects the mobility of macromolecular complexes, and how this depends on growth conditions, is presently unclear. In this study, we sought to quantify the crowding experienced by an exogenous 40 nm fluorescent particle in the cytoplasm of E. coli under different growth conditions. By performing single-particle tracking measurements in cells selectively depleted of DNA and/or mRNA, we determined the contribution to crowding of mRNA, DNA, and remaining cellular components, i.e., mostly proteins and ribosomes. To estimate this contribution to crowding, we quantified the difference of the particle's diffusion coefficient in conditions with and without those macromolecules. We found that the contributions of the three classes of components were of comparable magnitude, being largest in the case of proteins and ribosomes. We further found that the contributions of mRNA and DNA to crowding were significantly larger than expected based on their volumetric fractions alone. Finally, we found that the crowding contributions change only slightly with the growth conditions. These results reveal how various cellular components partake in crowding of the cytoplasm and the consequences this has for the mobility of large macromolecular complexes.

Species-resolved, single-cell respiration rates reveal dominance of sulfate reduction in a deep continental subsurface ecosystem

Rates of microbial processes are fundamental to understanding the significance of microbial impacts on environmental chemical cycling. However, it is often difficult to quantify rates or to link processes to specific taxa or individual cells, especially in environments where there are few cultured representatives with known physiology. Here, we describe the use of the redox-enzyme-sensitive molecular probe RedoxSensor™ Green to measure rates of anaerobic electron transfer physiology (i.e., sulfate reduction and methanogenesis) in individual cells and link those measurements to genomic sequencing of the same single cells. We used this method to investigate microbial activity in hot, anoxic, low-biomass (~103 cells mL-1) groundwater of the Death Valley Regional Flow System, California. Combining this method with electron donor amendment experiments and metatranscriptomics confirmed that the abundant spore formers including Candidatus Desulforudis audaxviator were actively reducing sulfate in this environment, most likely with acetate and hydrogen as electron donors. Using this approach, we measured environmental sulfate reduction rates at 0.14 to 26.9 fmol cell-1 h-1. Scaled to volume, this equates to a bulk environmental rate of ~103 pmol sulfate L-1 d-1, similar to potential rates determined with radiotracer methods. Despite methane in the system, there was no evidence for active microbial methanogenesis at the time of sampling. Overall, this method is a powerful tool for estimating species-resolved, single-cell rates of anaerobic metabolism in low-biomass environments while simultaneously linking genomes to phenomes at the single-cell level. We reveal active elemental cycling conducted by several species, with a large portion attributable to Ca. Desulforudis audaxviator.

Dynamical model of antibiotic responses linking expression of resistance genes to metabolism explains emergence of heterogeneity during drug exposures

Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug's action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistancetetoperon inE. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.

Temporal dynamics of microbial transcription in wetted hyperarid desert soils

Rainfall is rare in hyperarid deserts but, when it occurs, it triggers large biological responses essential for the long-term maintenance of the ecosystem. In drylands, microbes play major roles in nutrient cycling, but their responses to short-lived opportunity windows are poorly understood. Due to its ephemeral nature, mRNA is ideally suited to study microbiome dynamics upon abrupt changes in the environment. We analyzed microbial community transcriptomes after simulated rainfall in a Namib Desert soil over 7 days. Using total mRNA from dry and watered plots we infer short-term functional responses in the microbiome. A rapid two-phase cycle of activation and return to basal state was completed in a short period. Motility systems activated immediately, whereas competition-toxicity increased in parallel to predator taxa and the drying of soils. Carbon fixation systems were downregulated, and reactivated upon return to a near-dry state. The chaperone HSP20 was markedly regulated by watering across all major bacteria, suggesting a particularly important role in adaptation to desiccated ecosystems. We show that transcriptomes provide consistent and high resolution information on microbiome processes in a low-biomass environment, revealing shared patterns across taxa. We propose a structured dispersal-predation dynamic as a central driver of desert microbial responses to rainfall.

Environmental transcriptomics under heat stress: Can environmental RNA reveal changes in gene expression of aquatic organisms?

To safeguard biodiversity in a changing climate, taxonomic information about species turnover and insights into the health of organisms are required. Environmental DNA approaches are increasingly used for species identification, but cannot provide functional insights. Transcriptomic methods reveal the physiological states of macroorganisms, but are currently species-specific and require tissue sampling or animal sacrifice, making community-wide assessments challenging. Here, we test whether broad functional information (expression level of the transcribed genes) can be harnessed from environmental RNA (eRNA), which includes extra-organismal RNA from macroorganisms along with whole microorganisms. We exposed Daphnia pulex as well as phytoplankton prey and microorganism colonizers to control (20°C) and heat stress (28°C) conditions for 7 days. We sequenced eRNA from tank water (after complete removal of Daphnia) as well as RNA from Daphnia tissue, enabling comparisons of extra-organismal and organismal RNA-based gene expression profiles. Both RNA types detected similar heat stress responses of Daphnia. Using eRNA, we identified 32 Daphnia genes to be differentially expressed following heat stress. Of these, 17 were also differentially expressed and exhibited similar levels of relative expression in organismal RNA. In addition to the extra-organismal Daphnia response, eRNA detected community-wide heat stress responses consisting of distinct functional profiles and 121 differentially expressed genes across eight taxa. Our study demonstrates that environmental transcriptomics based on extra-organismal eRNA can noninvasively reveal gene expression responses of macroorganisms following environmental changes, with broad potential implications for the biomonitoring of health across the trophic chain.

Into the microbial niche

The environmental niche concept describes the distribution of a taxon in the environment and can be used to understand community dynamics, biological invasions, and the impact of environmental changes. The uses and applications are still restricted in microbial ecology, largely due to the complexity of microbial systems and associated methodological limitations. The development of shotgun metagenomics and metatranscriptomics opens new ways to investigate the microbial niche by focusing on the metabolic niche within the environmental space. Here, we propose the metabolic niche framework, which, by defining the fundamental and realised metabolic niche of microorganisms, has the potential to not only provide novel insights into habitat preferences and the metabolism associated, but also to inform on metabolic plasticity, niche shifts, and microbial invasions.

Dynamical model of antibiotic responses linking expression of resistance to metabolism explains emergence of heterogeneity during drug exposures

Antibiotic responses in bacteria are highly dynamic and heterogeneous, with sudden exposure of bacterial colonies to high drug doses resulting in the coexistence of recovered and arrested cells. The dynamics of the response is determined by regulatory circuits controlling the expression of resistance genes, which are in turn modulated by the drug's action on cell growth and metabolism. Despite advances in understanding gene regulation at the molecular level, we still lack a framework to describe how feedback mechanisms resulting from the interdependence between expression of resistance and cell metabolism can amplify naturally occurring noise and create heterogeneity at the population level. To understand how this interplay affects cell survival upon exposure, we constructed a mathematical model of the dynamics of antibiotic responses that links metabolism and regulation of gene expression, based on the tetracycline resistance tet operon in E. coli. We use this model to interpret measurements of growth and expression of resistance in microfluidic experiments, both in single cells and in biofilms. We also implemented a stochastic model of the drug response, to show that exposure to high drug levels results in large variations of recovery times and heterogeneity at the population level. We show that stochasticity is important to determine how nutrient quality affects cell survival during exposure to high drug concentrations. A quantitative description of how microbes respond to antibiotics in dynamical environments is crucial to understand population-level behaviors such as biofilms and pathogenesis.

Seasonal patterns in microbial carbon and iron transporter expression in the Southern Ocean

BACKGROUND

Heterotrophic microbes in the Southern Ocean are challenged by the double constraint of low concentrations of organic carbon (C) and iron (Fe). These essential elements are tightly coupled in cellular processes; however, the prokaryotic requirements of C and Fe under varying environmental settings remain poorly studied. Here, we used a combination of metatranscriptomics and metaproteomics to identify prokaryotic membrane transporters for organic substrates and Fe in naturally iron-fertilized and high-nutrient, low-chlorophyll waters of the Southern Ocean during spring and late summer.

RESULTS

Pronounced differences in membrane transporter profiles between seasons were observed at both sites, both at the transcript and protein level. When specific compound classes were considered, the two approaches revealed different patterns. At the transcript level, seasonal patterns were only observed for subsets of genes belonging to each transporter category. At the protein level, membrane transporters of organic compounds were relatively more abundant in spring as compared to summer, while the opposite pattern was observed for Fe transporters. These observations suggest an enhanced requirement for organic C in early spring and for Fe in late summer. Mapping transcripts and proteins to 50 metagenomic-assembled genomes revealed distinct taxon-specific seasonal differences pointing to potentially opportunistic clades, such as Pseudomonadales and Nitrincolaceae, and groups with a more restricted repertoire of expressed transporters, such as Alphaproteobacteria and Flavobacteriaceae.

CONCLUSION

The combined investigations of C and Fe membrane transporters suggest seasonal changes in the microbial requirements of these elements under different productivity regimes. The taxon-specific acquisition strategies of different forms of C and Fe illustrate how diverse microbes could shape transcript and protein expression profiles at the community level at different seasons. Our results on the C- and Fe-related metabolic capabilities of microbial taxa provide new insights into their potential role in the cycling of C and Fe under varying nutrient regimes in the Southern Ocean. Video Abstract.

Inferring gene regulatory networks using transcriptional profiles as dynamical attractors

Genetic regulatory networks (GRNs) regulate the flow of genetic information from the genome to expressed messenger RNAs (mRNAs) and thus are critical to controlling the phenotypic characteristics of cells. Numerous methods exist for profiling mRNA transcript levels and identifying protein-DNA binding interactions at the genome-wide scale. These enable researchers to determine the structure and output of transcriptional regulatory networks, but uncovering the complete structure and regulatory logic of GRNs remains a challenge. The field of GRN inference aims to meet this challenge using computational modeling to derive the structure and logic of GRNs from experimental data and to encode this knowledge in Boolean networks, Bayesian networks, ordinary differential equation (ODE) models, or other modeling frameworks. However, most existing models do not incorporate dynamic transcriptional data since it has historically been less widely available in comparison to "static" transcriptional data. We report the development of an evolutionary algorithm-based ODE modeling approach (named EA) that integrates kinetic transcription data and the theory of attractor matching to infer GRN architecture and regulatory logic. Our method outperformed six leading GRN inference methods, none of which incorporate kinetic transcriptional data, in predicting regulatory connections among TFs when applied to a small-scale engineered synthetic GRN in Saccharomyces cerevisiae. Moreover, we demonstrate the potential of our method to predict unknown transcriptional profiles that would be produced upon genetic perturbation of the GRN governing a two-state cellular phenotypic switch in Candida albicans. We established an iterative refinement strategy to facilitate candidate selection for experimentation; the experimental results in turn provide validation or improvement for the model. In this way, our GRN inference approach can expedite the development of a sophisticated mathematical model that can accurately describe the structure and dynamics of the in vivo GRN.

Functional annotation and importance of marine bacterial transporters of plankton exometabolites

Metabolite exchange within marine microbial communities transfers carbon and other major elements through global cycles and forms the basis of microbial interactions. Yet lack of gene annotations and concern about the quality of existing ones remain major impediments to revealing currencies of carbon flux. We employed an arrayed mutant library of the marine bacterium Ruegeria pomeroyi DSS-3 to experimentally annotate substrates of organic compound transporter systems, using mutant growth and compound drawdown analyses to link transporters to their cognate substrates. Mutant experiments verified substrates for thirteen R. pomeroyi transporters. Four were previously hypothesized based on gene expression data (taurine, glucose/xylose, isethionate, and cadaverine/putrescine/spermidine); five were previously hypothesized based on homology to experimentally annotated transporters in other bacteria (citrate, glycerol, N-acetylglucosamine, fumarate/malate/succinate, and dimethylsulfoniopropionate); and four had no previous annotations (thymidine, carnitine, cysteate, and 3-hydroxybutyrate). These bring the total number of experimentally-verified organic carbon influx transporters to 18 of 126 in the R. pomeroyi genome. In a longitudinal study of a coastal phytoplankton bloom, expression patterns of the experimentally annotated transporters linked them to different stages of the bloom, and also led to the hypothesis that citrate and 3-hydroxybutyrate were among the most highly available bacterial substrates. Improved functional annotation of the gatekeepers of organic carbon uptake is critical for deciphering carbon flux and fate in microbial ecosystems.

Transcriptional Mechanisms of Thermal Acclimation in Prochlorococcus

Low temperature limits the growth and the distribution of the key oceanic primary producer Prochlorococcus, which does not proliferate above a latitude of ca. 40°. Yet, the molecular basis of thermal acclimation in this cyanobacterium remains unexplored. We analyzed the transcriptional response of the Prochlorococcus marinus strain MIT9301 in long-term acclimations and in natural Prochlorococcus populations along a temperature range enabling its growth (17 to 30°C). MIT9301 upregulated mechanisms of the global stress response at the temperature minimum (17°C) but maintained the expression levels of genes involved in essential metabolic pathways (e.g., ATP synthesis and carbon fixation) along the whole thermal niche. Notably, the declining growth of MIT9301 from the optimum to the minimum temperature was coincident with a transcriptional suppression of the photosynthetic apparatus and a dampening of its circadian expression patterns, indicating a loss in their regulatory capacity under cold conditions. Under warm conditions, the cellular transcript inventory of MIT9301 was strongly streamlined, which may also induce regulatory imbalances due to stochasticity in gene expression. The daytime transcriptional suppression of photosynthetic genes at low temperature was also observed in metatranscriptomic reads mapping to MIT9301 across the global ocean, implying that this molecular mechanism may be associated with the restricted distribution of Prochlorococcus to temperate zones. IMPORTANCE Prochlorococcus is a major marine primary producer with a global impact on atmospheric CO₂ fixation. This cyanobacterium is widely distributed across the temperate ocean, but virtually absent at latitudes above 40° for yet unknown reasons. Temperature has been suggested as a major limiting factor, but the exact mechanisms behind Prochlorococcus thermal growth restriction remain unexplored. This study brings us closer to understanding how Prochlorococcus functions under challenging temperature conditions, by focusing on its transcriptional response after long-term acclimation from its optimum to its thermal thresholds. Our results show that the drop in Prochlorococcus growth rate under cold conditions was paralleled by a transcriptional suppression of the photosynthetic machinery during daytime and a loss in the organism's regulatory capacity to maintain circadian expression patterns. Notably, warm temperature induced a marked shrinkage of the organism's cellular transcript inventory, which may also induce regulatory imbalances in the future functioning of this cyanobacterium.

Using metatranscriptomics to better understand the role of microbial nitrogen cycling in coastal sediment benthic flux denitrification efficiency

Spatial and temporal variability in benthic flux denitrification efficiency occurs across Port Phillip Bay, Australia. Here, we assess the capacity for untargeted metatranscriptomics to resolve spatiotemporal differences in the microbial contribution to benthic nitrogen cycling. The most abundant sediment transcripts assembled were associated with the archaeal nitrifier Nitrosopumilus. In sediments close to external inputs of organic nitrogen, the dominant transcripts were associated with Nitrosopumilus nitric oxide nitrite reduction (nirK). The environmental conditions close to organic nitrogen inputs that select for increased transcription in Nitrosopumilus (amoCAB, nirK, nirS, nmo, hcp) additionally selected for increased transcription of bacterial nitrite reduction (nxrB) and transcripts associated with anammox (hzo) but not denitrification (bacterial nirS/nirk). In sediments that are more isolated from external inputs of organic nitrogen dominant transcripts were associated with nitrous oxide reduction (nosZ) and changes in nosZ transcript abundance were uncoupled from transcriptional profiles associated with archaeal nitrification. Coordinated transcription of coupled community-level nitrification-denitrification was not well supported by metatranscriptomics. In comparison, the abundance of archaeal nirK transcripts were site- and season-specific. This study indicates that the transcription of archaeal nirK in response to changing environmental conditions may be an important and overlooked feature of coastal sediment nitrogen cycling.

Ecological divergence of syntopic marine bacterial species is shaped by gene content and expression

Identifying mechanisms by which bacterial species evolve and maintain genomic diversity is particularly challenging for the uncultured lineages that dominate the surface ocean. A longitudinal analysis of bacterial genes, genomes, and transcripts during a coastal phytoplankton bloom revealed two co-occurring, highly related Rhodobacteraceae species from the deeply branching and uncultured NAC11-7 lineage. These have identical 16S rRNA gene amplicon sequences, yet their genome contents assembled from metagenomes and single cells indicate species-level divergence. Moreover, shifts in relative dominance of the species during dynamic bloom conditions over 7 weeks confirmed the syntopic species' divergent responses to the same microenvironment at the same time. Genes unique to each species and genes shared but divergent in per-cell inventories of mRNAs accounted for 5% of the species' pangenome content. These analyses uncover physiological and ecological features that differentiate the species, including capacities for organic carbon utilization, attributes of the cell surface, metal requirements, and vitamin biosynthesis. Such insights into the coexistence of highly related and ecologically similar bacterial species in their shared natural habitat are rare.

Differential roles of transcriptional and translational negative autoregulations in protein dynamics

Cells continuously respond to stimuli to function properly by employing a wide variety of regulatory mechanisms that often involve protein up or down regulations. This study focuses on dynamics of a protein with negative autoregulations in E. coli, and assumes that the input signal up-regulates the protein, and then the protein down-regulates its own production via 2 distinct types of mechanisms. The mathematical models describe the dynamics of mRNA and protein for 3 scenarios: (i) a simplistic model with no regulation, (ii) a model with transcriptional negative autoregulation, and (iii) a model with translational negative autoregulation. Our analysis shows that the negative autoregulation models produce faster responses and quicker return times to the input signals compared to the model with no regulation, while the transcriptional autoregulation model is the only model capable of producing oscillatory dynamics. The stochastic simulations predict that the transcriptional autoregulation model is the noisiest followed by the simplistic model, and the translational autoregulation model has the least noise. The noise level depends on the strength of inhibition. Furthermore, the transcriptional autoregulation model filters out the noise in the input signal for longer periods of time, and this time increases as the strength of the feedback gets stronger.

Temporal profiling resolves the drivers of microbial nitrogen cycling variability in coastal sediments

Here we describe the potential for sediment microbial nitrogen-cycling gene (DNA) and activity (RNA) abundances to spatially resolve coastal areas impacted by seasonal variability in external nutrient inputs. Three sites were chosen within a nitrogen-limited embayment, Port Phillip Bay (PPB), Australia that reflect variability in both proximity to external nutrient inputs and the dominant form of available nitrogen. At three sediment depths (0-1; 1-5; 5-10 cm) across a 2 year study key genes involved in nitrification (archaeal amoA and bacterial β-amoA), nitrite reduction (clade I nirS and cluster I nirK, archaeal nirK-a), anaerobic oxidation of ammonium (anammox 16S rRNA phylogenetic marker) and nitrogen fixation (nifH) were quantified. Sediments impacted by a dominance of organic nitrogen inputs were characterised at all time-points and to sediment depths of 10 cm by the highest transcript abundances of archaeal amoA and archaeal nirk-a. Proximity to a dominance of external nitrate inputs was associated with the highest transcript abundances of nirS which temporally co-varied with seasonal changes in sediment nitrate. Sediments isolated from external inputs displayed the greatest depth-specific decrease in quantifiable transcript abundances. In these isolated sediments bacterial β-amoA transcripts were temporally associated with increased sediment ammonium levels. Across this nitrogen limited system variability in the abundance of bacterial β-amoA, archaeal amoA, archaeal nirk-a or nirS transcripts from the sediment surface (0-1 and 5 cm) demonstrated a capacity to improve our ability to monitor coastal zones impacted by anthropogenic nitrogen inputs. Specifically, the spatial detection sensitivity of bacterial β-amoA transcripts could be developed as a metric to determine spatiotemporal impacts of large external loading events. This temporal study demonstrates a capacity for microbial activity metrics to facilitate coastal management strategies through greater spatial resolution of areas impacted by external nutrient inputs.

The double life of CRISPR-Cas13

Since the discovery of RNA-programmable nucleases from the prokaryotic adaptive immune system CRISPR-Cas, these proteins have seen rapid and widespread adoption for biotechnological and clinical research. A recently discovered system, CRISPR-Cas13, uses CRISPR RNA guides to target RNA. Interestingly, RNA targeting by Cas13 results in cleavage of both target RNA and bystander RNA. This feature has been used to develop innovative diagnostic tools for the detection of specific RNAs. Unlike in vitro detection of RNA using collateral RNA cleavage, however, initial studies of mammalian cells only revealed highly specific target RNA-knockdown activity. Although these findings have been confirmed subsequently, several recent publications do report Cas13-mediated toxicity and collateral RNA cleavage when using Cas13 in eukaryotes. Here, we review these conflicting observations and discuss its potential molecular basis.

Over two decades of research on the marine RNA virosphere

RNA viruses (realm: Riboviria), including RNA phages and eukaryote-infecting RNA viruses, are essential components of marine ecosystems. A large number of marine RNA viruses have been discovered in the last two decades because of the rapid development of next-generation sequencing (NGS) technology. Indeed, the combination of NGS and state-of-the-art meta-omics methods (viromics, the study of all viruses in a specific environment) has led to a fundamental understanding of the taxonomy and genetic diversity of RNA viruses in the sea, suggesting the complex ecological roles played by RNA viruses in this complex ecosystem. Furthermore, comparisons of viromes in the context of highly variable marine niches reveal the biogeographic patterns and ecological impact of marine RNA viruses, whose role in global ecology is becoming increasingly clearer. In this review, we summarize the characteristics of the global marine RNA virosphere and outline the taxonomic hierarchy of RNA viruses with a specific focus on their ancient evolutionary history. We also review the development of methodology and the major progress resulting from its applications in RNA viromics. The aim of this review is not only to provide an in-depth understanding of multifaceted aspects of marine RNA viruses, but to offer future perspectives on developing a better methodology for discovery, and exploring the evolutionary origin and major ecological significance of marine RNA virosphere.

Decoupling of respiration rates and abundance in marine prokaryoplankton

The ocean-atmosphere exchange of CO2 largely depends on the balance between marine microbial photosynthesis and respiration. Despite vast taxonomic and metabolic diversity among marine planktonic bacteria and archaea (prokaryoplankton)1-3, their respiration usually is measured in bulk and treated as a 'black box' in global biogeochemical models4; this limits the mechanistic understanding of the global carbon cycle. Here, using a technology for integrated phenotype analyses and genomic sequencing of individual microbial cells, we show that cell-specific respiration rates differ by more than 1,000× among prokaryoplankton genera. The majority of respiration was found to be performed by minority members of prokaryoplankton (including the Roseobacter cluster), whereas cells of the most prevalent lineages (including Pelagibacter and SAR86) had extremely low respiration rates. The decoupling of respiration rates from abundance among lineages, elevated counts of proteorhodopsin transcripts in Pelagibacter and SAR86 cells and elevated respiration of SAR86 at night indicate that proteorhodopsin-based phototrophy3,5-7 probably constitutes an important source of energy to prokaryoplankton and may increase growth efficiency. These findings suggest that the dependence of prokaryoplankton on respiration and remineralization of phytoplankton-derived organic carbon into CO2 for its energy demands and growth may be lower than commonly assumed and variable among lineages.

The landscape of transcriptional and translational changes over 22 years of bacterial adaptation

Organisms can adapt to an environment by taking multiple mutational paths. This redundancy at the genetic level, where many mutations have similar phenotypic and fitness effects, can make untangling the molecular mechanisms of complex adaptations difficult. Here, we use the Escherichia coli long-term evolution experiment (LTEE) as a model to address this challenge. To understand how different genomic changes could lead to parallel fitness gains, we characterize the landscape of transcriptional and translational changes across 12 replicate populations evolving in parallel for 50,000 generations. By quantifying absolute changes in mRNA abundances, we show that not only do all evolved lines have more mRNAs but that this increase in mRNA abundance scales with cell size. We also find that despite few shared mutations at the genetic level, clones from replicate populations in the LTEE are remarkably similar in their gene expression patterns at both the transcriptional and translational levels. Furthermore, we show that the majority of the expression changes are due to changes at the transcriptional level with very few translational changes. Finally, we show how mutations in transcriptional regulators lead to consistent and parallel changes in the expression levels of downstream genes. These results deepen our understanding of the molecular mechanisms underlying complex adaptations and provide insights into the repeatability of evolution.

The impact of summer drought on peat soil microbiome structure and function-A multi-proxy-comparison

Different proxies for changes in structure and/or function of microbiomes have been developed, allowing assessing microbiome dynamics at multiple levels. However, the lack and differences in understanding the microbiome dynamics are due to the differences in the choice of proxies in different studies and the limitations of proxies themselves. Here, using both amplicon and metatranscriptomic sequencings, we compared four different proxies (16/18S rRNA genes, 16/18S rRNA transcripts, mRNA taxonomy and mRNA function) to reveal the impact of a severe summer drought in 2018 on prokaryotic and eukaryotic microbiome structures and functions in two rewetted fen peatlands in northern Germany. We found that both prokaryotic and eukaryotic microbiome compositions were significantly different between dry and wet months. Interestingly, mRNA proxies showed stronger and more significant impacts of drought for prokaryotes, while 18S rRNA transcript and mRNA taxonomy showed stronger drought impacts for eukaryotes. Accordingly, by comparing the accuracy of microbiome changes in predicting dry and wet months under different proxies, we found that mRNA proxies performed better for prokaryotes, while 18S rRNA transcript and mRNA taxonomy performed better for eukaryotes. In both cases, rRNA gene proxies showed much lower to the lowest accuracy, suggesting the drawback of DNA based approaches. To our knowledge, this is the first study comparing all these proxies to reveal the dynamics of both prokaryotic and eukaryotic microbiomes in soils. This study shows that microbiomes are sensitive to (extreme) weather changes in rewetted fens, and the associated microbial changes might contribute to ecological consequences.

Proteomining-Based Elucidation of Natural Product Biosynthetic Pathways in Streptomyces

The genus Streptomyces is known to harbor numerous biosynthetic gene clusters (BGCs) of potential utility in synthetic biology applications. However, it is often difficult to link uncharacterized BGCs with the secondary metabolites they produce. Proteomining refers to the strategy of identifying active BGCs by correlating changes in protein expression with the production of secondary metabolites of interest. In this study, we devised a shotgun proteomics-based workflow to identify active BGCs during fermentation when a variety of compounds are being produced. Mycelia harvested during the non-producing growth phase served as the background. Proteins that were differentially expressed were clustered based on the proximity of the genes in the genome to highlight active BGCs systematically from label-free quantitative proteomics data. Our software tool is easy-to-use and requires only 1 point of comparison where natural product biosynthesis was significantly different. We tested our proteomining clustering method on three Streptomyces species producing different compounds. In Streptomyces coelicolor A3(2), we detected the BGCs of calcium-dependent antibiotic, actinorhodin, undecylprodigiosin, and coelimycin P1. In Streptomyces chrestomyceticus BCC24770, 7 BGCs were identified. Among them, we independently re-discovered the type II PKS for albofungin production previously identified by genome mining and tedious heterologous expression experiments. In Streptomyces tenebrarius, 5 BGCs were detected, including the known apramycin and tobramycin BGC as well as a newly discovered caerulomycin A BGC in this species. The production of caerulomycin A was confirmed by LC-MS and the inactivation of the caerulomycin A BGC surprisingly had a significant impact on the secondary metabolite regulation of S. tenebrarius. In conclusion, we developed an unbiased, high throughput proteomics-based method to complement genome mining methods for the identification of biosynthetic pathways in Streptomyces sp.

Proteomic response of Turicibacter bilis MMM721 to chicken bile and its bile acids

Objective

Bile and its individual components, mainly bile acids, are important for digestion and drive bacterial community dynamics in the upper gastrointestinal tract of chickens. However, specific responses to bile acids have been characterized in only a few commensal bacteria, and it is unclear how other members of the microbiota respond to biliary stress. Here, we used label-free LC–MS/MS to assess the proteomic response of a common inhabitant of the chicken small intestine, Turicibacter bilis MMM721, to 24 h of growth in anaerobic growth media supplemented with 0.1% whole chicken bile, 0.1% taurochenodeoxycholic acid (TCDCA), or 0.1% taurocholic acid (TCA).

Results

Seventy, 46, and 10 differentially expressed proteins were identified in Turicibacter bilis MMM721 cultured with supplements of chicken bile, TCDCA, and TCA, respectively, when compared to unsupplemented controls. Many differentially expressed proteins were predicted to be involved in ribosomal processes, post-translational modifications and chaperones, and modifications to the cell surface. Ultimately, the T. bilis MMM721 response to whole bile and bile acids is complex and may relate to adaptations for small intestine colonization, with numerous proteins from a variety of functional categories being impacted.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-022-06127-8.

Linking transcriptional dynamics of CH4-cycling grassland soil microbiomes to seasonal gas fluxes

Soil CH₄ fluxes are driven by CH₄-producing and -consuming microorganisms that determine whether soils are sources or sinks of this potent greenhouse gas. To date, a comprehensive understanding of underlying microbiome dynamics has rarely been obtained in situ. Using quantitative metatranscriptomics, we aimed to link CH₄-cycling microbiomes to net surface CH₄ fluxes throughout a year in two grassland soils. CH₄ fluxes were highly dynamic: both soils were net CH₄ sources in autumn and winter and sinks in spring and summer, respectively. Correspondingly, methanogen mRNA abundances per gram soil correlated well with CH₄ fluxes. Methanotroph to methanogen mRNA ratios were higher in spring and summer, when the soils acted as net CH₄ sinks. CH₄ uptake was associated with an increased proportion of USCα and γ pmoA and pmoA2 transcripts. We assume that methanogen transcript abundance may be useful to approximate changes in net surface CH₄ emissions from grassland soils. High methanotroph to methanogen ratios would indicate CH₄ sink properties. Our study links for the first time the seasonal transcriptional dynamics of CH₄-cycling soil microbiomes to gas fluxes in situ. It suggests mRNA transcript abundances as promising indicators of dynamic ecosystem-level processes.

One Cell at a Time: Advances in Single-Cell Methods and Instrumentation for Discovery in Aquatic Microbiology

Studying microbes from a single-cell perspective has become a major theme and interest within the field of aquatic microbiology. One emerging trend is the unfailing observation of heterogeneity in activity levels within microbial populations. Wherever researchers have looked, intra-population variability in biochemical composition, growth rates, and responses to varying environmental conditions has been evident and probably reflect coexisting genetically distinct strains of the same species. Such observations of heterogeneity require a shift away from bulk analytical approaches and development of new methods or adaptation of existing techniques, many of which were first pioneered in other, unrelated fields, e.g., material, physical, and biomedical sciences. Many co-opted approaches were initially optimized using model organisms. In a field with so few cultivable models, method development has been challenging but has also contributed tremendous insights, breakthroughs, and stimulated curiosity. In this perspective, we present a subset of methods that have been effectively applied to study aquatic microbes at the single-cell level. Opportunities and challenges for innovation are also discussed. We suggest future directions for aquatic microbiological research that will benefit from open access to sophisticated instruments and highly interdisciplinary collaborations.

Diel investments in metabolite production and consumption in a model microbial system

Organic carbon transfer between surface ocean photosynthetic and heterotrophic microbes is a central but poorly understood process in the global carbon cycle. In a model community in which diatom extracellular release of organic molecules sustained growth of a co-cultured bacterium, we determined quantitative changes in the diatom endometabolome and the bacterial uptake transcriptome over two diel cycles. Of the nuclear magnetic resonance (NMR) peaks in the diatom endometabolites, 38% had diel patterns with noon or mid-afternoon maxima; the remaining either increased (36%) or decreased (26%) through time. Of the genes in the bacterial uptake transcriptome, 94% had a diel pattern with a noon maximum; the remaining decreased over time (6%). Eight diatom endometabolites identified with high confidence were matched to the bacterial genes mediating their utilization. Modeling of these coupled inventories with only diffusion-based phytoplankton extracellular release could not reproduce all the patterns. Addition of active release mechanisms for physiological balance and bacterial recognition significantly improved model performance. Estimates of phytoplankton extracellular release range from only a few percent to nearly half of annual net primary production. Improved understanding of the factors that influence metabolite release and consumption by surface ocean microbes will better constrain this globally significant carbon flux.

Insights into microbial diversity on plastisphere by multi-omics

Plastic pollution is a major concern in marine environment as it takes many years to degrade and is one of the greatest threats to marine life. Plastic surface, referred to as plastisphere, provides habitat for growth and proliferation of various microorganisms. The discovery of these microbes is necessary to identify significant genes, enzymes and bioactive compounds that could help in bioremediation and other commercial applications. Conventional culture techniques have been successful in identifying few microbes from these habitats, leaving majority of them yet to be explored. As such, to recognize the vivid genetic diversity of microbes residing in plastisphere, their structure and corresponding ecological roles within the ecosystem, an emerging technique, called metagenomics has been explored. The technique is expected to provide hitherto unknown information on microbes from the plastisphere. Metagenomics along with next generation sequencing provides comprehensive knowledge on microbes residing in plastisphere that identifies novel microbes for plastic bioremediation, bioactive compounds and other potential benefits. The following review summarizes the efficiency of metagenomics and next generation sequencing technology over conventionally used methods for culturing microbes. It attempts to illustrate the workflow mechanism of metagenomics to elucidate diverse microbial profiles. Further, importance of integrated multi-omics techniques has been highlighted in discovering microbial ecology residing on plastisphere for wider applications.

Communality in microbial stress response and differential metabolic interactions revealed by time-series analysis of sponge symbionts

The diversity and function of sponge-associated symbionts is now increasingly understood, however, we lack an understanding on how they dynamically behave to ensure holobiont stability in the face of environmental variation. Here we performed a metatransciptomics analysis of three microbial symbionts of the sponge Cymbastela concentrica in situ over 14 months and through differential gene expression and correlation analysis to environmental variables uncovered differences that speak to their metabolic activities and level of symbiotic and environmental interactions. The nitrite-oxidising Ca. Porinitrospira cymbastela maintained a seemingly stable metabolism, with the few differentially expressed genes related only to stress responses. The heterotrophic Ca. Porivivens multivorans displayed differential use of holobiont-derived compounds and respiration modes, while the ammonium-oxidising archaeon Ca. Nitrosopumilus cymbastelus differentially expressed genes related to phosphate metabolism and symbiosis effectors. One striking similarity between the symbionts was their similar variation in expression of stress-related genes. Our timeseries study showed that the microbial community of C. concentrica undertakes dynamic gene expression adjustments in response to the surroundings, tuned to deal with general stress and metabolic interactions between holobiont members. The success of these dynamic adjustments likely underpins the stability of the sponge holobiont and may provide resilience against environmental change. This article is protected by copyright. All rights reserved.

Diversity and Evolution of Mamiellophyceae: Early-Diverging Phytoplanktonic Green Algae Containing Many Cosmopolitan Species

The genomic revolution has bridged a gap in our knowledge about the diversity, biology and evolution of unicellular photosynthetic eukaryotes, which bear very few discriminating morphological features among species from the same genus. The high-quality genome resources available in the class Mamiellophyceae (Chlorophyta) have been paramount to estimate species diversity and screen available metagenomic data to assess the biogeography and ecological niches of different species on a global scale. Here we review the current knowledge about the diversity, ecology and evolution of the Mamiellophyceae and the large double-stranded DNA prasinoviruses infecting them, brought by the combination of genomic and metagenomic analyses, including 26 metabarcoding environmental studies, as well as the pan-oceanic GOS and the Tara Oceans expeditions.

Omics-Inferred Partitioning and Expression of Diverse Biogeochemical Functions in a Low-O2 Cyanobacterial Mat Community

Cyanobacterial mats profoundly influenced Earth’s biological and geochemical evolution and still play important ecological roles in the modern world. However, the biogeochemical functioning of cyanobacterial mats under persistent low-O₂ conditions, which dominated their evolutionary history, is not well understood. To investigate how different metabolic and biogeochemical functions are partitioned among community members, we conducted metagenomics and metatranscriptomics on cyanobacterial mats in the low-O₂, sulfidic Middle Island sinkhole (MIS) in Lake Huron. Metagenomic assembly and binning yielded 144 draft metagenome assembled genomes, including 61 of medium quality or better, and the dominant cyanobacteria and numerous Proteobacteria involved in sulfur cycling. Strains of a Phormidium autumnale-like cyanobacterium dominated the metagenome and metatranscriptome. Transcripts for the photosynthetic reaction core genes psaA and psbA were abundant in both day and night. Multiple types of psbA genes were expressed from each cyanobacterium, and the dominant psbA transcripts were from an atypical microaerobic type of D1 protein from Phormidium. Further, cyanobacterial transcripts for photosystem I genes were more abundant than those for photosystem II, and two types of Phormidium sulfide quinone reductase were recovered, consistent with anoxygenic photosynthesis via photosystem I in the presence of sulfide. Transcripts indicate active sulfur oxidation and reduction within the cyanobacterial mat, predominately by Gammaproteobacteria and Deltaproteobacteria, respectively. Overall, these genomic and transcriptomic results link specific microbial groups to metabolic processes that underpin primary production and biogeochemical cycling in a low-O₂ cyanobacterial mat and suggest mechanisms for tightly coupled cycling of oxygen and sulfur compounds in the mat ecosystem.

IMPORTANCE Cyanobacterial mats are dense communities of microorganisms that contain photosynthetic cyanobacteria along with a host of other bacterial species that play important yet still poorly understood roles in this ecosystem. Although such cyanobacterial mats were critical agents of Earth’s biological and chemical evolution through geological time, little is known about how they function under the low-oxygen conditions that characterized most of their natural history. Here, we performed sequencing of the DNA and RNA of modern cyanobacterial mat communities under low-oxygen and sulfur-rich conditions from the Middle Island sinkhole in Lake Huron. The results reveal the organisms and metabolic pathways that are responsible for both oxygen-producing and non-oxygen-producing photosynthesis as well as interconversions of sulfur that likely shape how much O₂ is produced in such ecosystems. These findings indicate tight metabolic reactions between community members that help to explain the limited the amount of O₂ produced in cyanobacterial mat ecosystems.

Recent advances in understanding the ecology of the filamentous bacteria responsible for activated sludge bulking

Activated sludge bulking caused by filamentous bacteria is still a problem in wastewater treatment plants around the world. Bulking is a microbiological problem, and so its solution on species-specific basis is likely to be reached only after their ecology, physiology and metabolism is better understood. Culture-independent molecular methods have provided much useful information about this group of organisms, and in this review, the methods employed and the information they provide are critically assessed. Their application to understanding bulking caused by the most frequently seen filament in Japan, 'Ca. Kouleothrix', is used here as an example of how these techniques might be used to develop control strategies. Whole genome sequences are now available for some of filamentous bacteria responsible for bulking, and so it is possible to understand why these filaments might thrive in activated sludge plants, and provide clues as to how eventually they might be controlled specifically.

Why Environmental Biomarkers Work: Transcriptome-Proteome Correlations and Modeling of Multistressor Experiments in the Marine Bacterium Trichodesmium

Ocean microbial communities are important contributors to the global biogeochemical reactions that sustain life on Earth. The factors controlling these communities are being increasingly explored using metatranscriptomic and metaproteomic environmental biomarkers. Using published proteomes and transcriptomes from the abundant colony-forming cyanobacterium Trichodesmium (strain IMS101) grown under varying Fe and/or P limitation in low and high CO₂, we observed robust correlations of stress-induced proteins and RNAs (i.e., involved in transport and homeostasis) that yield useful information on the nutrient status under low and/or high CO₂. Conversely, transcriptional and translational correlations of many other central metabolism pathways exhibit broad discordance. A cellular RNA and protein production/degradation model demonstrates how biomolecules with small initial inventories, such as environmentally responsive proteins, achieve large increases in fold-change units as opposed to those with a higher basal expression and inventory such as metabolic systems. Microbial cells, due to their immersion in the environment, tend to show large adaptive responses in both RNA and protein that result in transcript-protein correlations. These observations and model results demonstrate multi-omic coherence for environmental biomarkers and provide the underlying mechanism for those observations, supporting the promise for global application in detecting responses to environmental stimuli in a changing ocean.

Prospects for multi-omics in the microbial ecology of water engineering

Advances in high-throughput sequencing technologies and bioinformatics approaches over almost the last three decades have substantially increased our ability to explore microorganisms and their functions - including those that have yet to be cultivated in pure isolation. Genome-resolved metagenomic approaches have enabled linking powerful functional predictions to specific taxonomical groups with increasing fidelity. Additionally, related developments in both whole community gene expression surveys and metabolite profiling have permitted for direct surveys of community-scale functions in specific environmental settings. These advances have allowed for a shift in microbiome science away from descriptive studies and towards mechanistic and predictive frameworks for designing and harnessing microbial communities for desired beneficial outcomes. Water engineers, microbiologists, and microbial ecologists studying activated sludge, anaerobic digestion, and drinking water distribution systems have applied various (meta)omics techniques for connecting microbial community dynamics and physiologies to overall process parameters and system performance. However, the rapid pace at which new omics-based approaches are developed can appear daunting to those looking to apply these state-of-the-art practices for the first time. Here, we review how modern genome-resolved metagenomic approaches have been applied to a variety of water engineering applications from lab-scale bioreactors to full-scale systems. We describe integrated omics analysis across engineered water systems and the foundations for pairing these insights with modeling approaches. Lastly, we summarize emerging omics-based technologies that we believe will be powerful tools for water engineering applications. Overall, we provide a framework for microbial ecologists specializing in water engineering to apply cutting-edge omics approaches to their research questions to achieve novel functional insights. Successful adoption of predictive frameworks in engineered water systems could enable more economically and environmentally sustainable bioprocesses as demand for water and energy resources increases.

Multi 'omic data integration: A review of concepts, considerations, and approaches

The application of 'omic techniques including, but not limited to genomics/metagenomics, transcriptomics/meta-transcriptomics, proteomics/meta-proteomics, and metabolomics to generate multiple datasets from a single sample have facilitated hypothesis generation leading to the identification of biological, molecular and ecological functions and mechanisms, as well as associations and correlations. Despite their power and promise, a variety of challenges must be considered in the successful design and execution of a multi-omics study. In this review, various 'omic technologies applicable to single- and meta-organisms (i.e., host + microbiome) are described, and considerations for sample collection, storage and processing prior to data generation and analysis, as well as approaches to data storage, dissemination and analysis are discussed. Finally, case studies are included as examples of multi-omic applications providing novel insights and a more holistic understanding of biological processes.

Metatranscriptomics for the Human Microbiome and Microbial Community Functional Profiling

Shotgun metatranscriptomics (MTX) is an increasingly practical way to survey microbial community gene function and regulation at scale. This review begins by summarizing the motivations for community transcriptomics and the history of the field. We then explore the principles, best practices, and challenges of contemporary MTX workflows: beginning with laboratory methods for isolation and sequencing of community RNA, followed by informatics methods for quantifying RNA features, and finally statistical methods for detecting differential expression in a community context. In thesecond half of the review, we survey important biological findings from the MTX literature, drawing examples from the human microbiome, other (nonhuman) host-associated microbiomes, and the environment. Across these examples, MTX methods prove invaluable for probing microbe-microbe and host-microbe interactions, the dynamics of energy harvest and chemical cycling, and responses to environmental stresses. We conclude with a review of open challenges in the MTX field, including making assays and analyses more robust, accessible, and adaptable to new technologies; deciphering roles for millions of uncharacterized microbial transcripts; and solving applied problems such as biomarker discovery and development of microbial therapeutics.

Responses of Coastal Marine Microbiomes Exposed to Anthropogenic Dissolved Organic Carbon

Coastal seawaters receive thousands of organic pollutants. However, we have little understanding of the response of microbiomes to this pool of anthropogenic dissolved organic carbon (ADOC). In this study, coastal microbial communities were challenged with ADOC at environmentally relevant concentrations. Experiments were performed at two Mediterranean sites with different impact by pollutants and nutrients: off the Barcelona harbor ("BCN"), and at the Blanes Bay ("BL"). ADOC additions stimulated prokaryotic leucine incorporation rates at both sites, indicating the use of ADOC as growth substrate. The percentage of "membrane-compromised" cells increased with increasing ADOC, indicating concurrent toxic effects of ADOC. Metagenomic analysis of the BCN community challenged with ADOC showed a significant growth of Methylophaga and other gammaproteobacterial taxa belonging to the rare biosphere. Gene expression profiles showed a taxon-dependent response, with significantly enrichments of transcripts from SAR11 and Glaciecola spp. in BCN and BL, respectively. Further, the relative abundance of transposon-related genes (in BCN) and transcripts (in BL) correlated with the number of differentially abundant genes (in BCN) and transcripts (in BLA), suggesting that microbial responses to pollution may be related to pre-exposure to pollutants, with transposons playing a role in adaptation to ADOC. Our results point to a taxon-specific response to low concentrations of ADOC that impact the functionality, structure and plasticity of the communities in coastal seawaters. This work contributes to address the influence of pollutants on microbiomes and their perturbation to ecosystem services and ocean health.

Towards omics-based predictions of planktonic functional composition from environmental data

Marine microbes play a crucial role in climate regulation, biogeochemical cycles, and trophic networks. Unprecedented amounts of data on planktonic communities were recently collected, sparking a need for innovative data-driven methodologies to quantify and predict their ecosystemic functions. We reanalyze 885 marine metagenome-assembled genomes through a network-based approach and detect 233,756 protein functional clusters, from which 15% are functionally unannotated. We investigate all clusters' distributions across the global ocean through machine learning, identifying biogeographical provinces as the best predictors of protein functional clusters' abundance. The abundances of 14,585 clusters are predictable from the environmental context, including 1347 functionally unannotated clusters. We analyze the biogeography of these 14,585 clusters, identifying the Mediterranean Sea as an outlier in terms of protein functional clusters composition. Applicable to any set of sequences, our approach constitutes a step towards quantitative predictions of functional composition from the environmental context.

Bacterial responses to background organic pollutants in the northeast subarctic Pacific Ocean

Thousands of man-made synthetic chemicals are released to oceans and compose the anthropogenic dissolved organic carbon (ADOC). Little is known about the effects of this chronic pollution on marine microbiome activities. In this study, we measured the pollution level at three sites in the Northeast Subarctic Pacific Ocean (NESAP) and investigated how mixtures of three model families of ADOC at different environmentally relevant concentrations affected naturally occurring marine bacterioplankton communities' structure and metabolic functioning. The offshore northernmost site (North) had the lowest concentrations of hydrocarbons, as well as organophosphate ester plasticizers, contrasting with the two other continental shelf sites, the southern coastal site (South) being the most contaminated. At North, ADOC stimulated bacterial growth and promoted an increase in the contribution of some Gammaproteobacteria groups (e.g. Alteromonadales) to the 16 rRNA pool. These groups are described as fast responders after oil spills. In contrast, minor changes in South microbiome activities were observed. Gene expression profiles at Central showed the coexistence of ADOC degradation and stress-response strategies to cope with ADOC toxicities. These results show that marine microbial communities at three distinct domains in NESAP are influenced by background concentrations of ADOC, expanding previous assessments for polar and temperate waters.

Translational autoregulation of RF2 protein in E. coli through programmed frameshifting

Various feedback mechanisms regulate the expression of different genes to ensure the required protein levels inside a cell. In this paper, we develop a kinetic model for one such mechanism that autoregulates RF2 protein synthesis in E. coli through programmed frameshifting. The model finds that the programmed frameshifting autoregulates RF2 protein synthesis by two independent mechanisms. First, it increases the rate of RF2 synthesis from each mRNA transcript at low RF2 concentration. Second, programmed frameshifting can dramatically increase the lifetime of RF2 transcripts when RF2 protein levels are lower than a threshold. This sharp increase in mRNA lifetime is caused by a first-order phase transition from a low to a high ribosome density on an RF2 transcript. The high ribosome density prevents the transcript's degradation by shielding it from nucleases, which increases its average lifetime and hence RF2 protein levels. Our study identifies this quality control mechanism that regulates the cellular protein levels by breaking the hierarchy of processes involved in gene expression.

Does It Pay Off to Explicitly Link Functional Gene Expression to Denitrification Rates in Reaction Models?

Environmental omics and molecular-biological data have been proposed to yield improved quantitative predictions of biogeochemical processes. The abundances of functional genes and transcripts relate to the number of cells and activity of microorganisms. However, whether molecular-biological data can be quantitatively linked to reaction rates remains an open question. We present an enzyme-based denitrification model that simulates concentrations of transcription factors, functional-gene transcripts, enzymes, and solutes. We calibrated the model using experimental data from a well-controlled batch experiment with the denitrifier Paracoccous denitrificans. The model accurately predicts denitrification rates and measured transcript dynamics. The relationship between simulated transcript concentrations and reaction rates exhibits strong non-linearity and hysteresis related to the faster dynamics of gene transcription and substrate consumption, relative to enzyme production and decay. Hence, assuming a unique relationship between transcript-to-gene ratios and reaction rates, as frequently suggested, may be an erroneous simplification. Comparing model results of our enzyme-based model to those of a classical Monod-type model reveals that both formulations perform equally well with respect to nitrogen species, indicating only a low benefit of integrating molecular-biological data for estimating denitrification rates. Nonetheless, the enzyme-based model is a valuable tool to improve our mechanistic understanding of the relationship between biomolecular quantities and reaction rates. Furthermore, our results highlight that both enzyme kinetics (i.e., substrate limitation and inhibition) and gene expression or enzyme dynamics are important controls on denitrification rates.

A distinct growth physiology enhances bacterial growth under rapid nutrient fluctuations

It has long been known that bacteria coordinate their physiology with their nutrient environment, yet our current understanding offers little intuition for how bacteria respond to the second-to-minute scale fluctuations in nutrient concentration characteristic of many microbial habitats. To investigate the effects of rapid nutrient fluctuations on bacterial growth, we couple custom microfluidics with single-cell microscopy to quantify the growth rate of E. coli experiencing 30 s to 60 min nutrient fluctuations. Compared to steady environments of equal average concentration, fluctuating environments reduce growth rate by up to 50%. However, measured reductions in growth rate are only 38% of the growth loss predicted from single nutrient shifts. This enhancement derives from the distinct growth response of cells grown in environments that fluctuate rather than shift once. We report an unexpected physiology adapted for growth in nutrient fluctuations and implicate nutrient timescale as a critical environmental parameter beyond nutrient identity and concentration.

Here the authors use microfluidics and single-cell microscopy to quantify the growth dynamics of individual E. coli cells exposed to nutrient fluctuations with periods as short as 30 seconds, finding that nutrient fluctuations reduce growth rates up to 50% compared to a steady nutrient delivery of equal average concentration, implying that temporal variability is an important parameter in bacterial growth.

Microbial fuel cells: a comprehensive review for beginners

Microbial fuel cells (MFCs) have shown immense potential as a one-stop solution for three major sustainability issues confronting the world today-energy security, global warming and wastewater management. MFCs represent a cross-disciplinary platform for research at the confluence of the natural and engineering sciences. The diversity of variables influencing performance of MFCs has garnered research interest across varied scientific disciplines since the beginning of this century. The increasing number of research publications has made it necessary to keep track of work being carried out by research groups across the globe and consolidate significant findings on a regular basis. Review articles are often the nodal points for beginners who are required to undertake an exploratory survey of literature to identify a suitable research problem. This 'review of reviews' is a ready-reckoner that directs readers to relevant reviews and research articles reporting significant developments in MFC research in the last two decades. The article also highlights the areas needing research attention which when addressed could take this technology a few more steps closer to practical implementation.

Divergence of Phyllosphere Microbial Communities Between Females and Males of the Dioecious Populus cathayana

Females and males of dioecious plants have evolved sex-specific characteristics in terms of their morphological and physiological properties. However, the differentiation of phyllosphere microbiota in dioecious plants remains largely unexplored. Here, the diversity and composition of female and male Populus cathayana phyllosphere bacterial and fungal communities were investigated using 16S rRNA/ITS1 gene-based MiSeq sequencing. The divergences of bacterial and fungal community compositions occurred between females and males. Both females and males had their unique phyllosphere bacterial and fungal microbiota, such as bacterial Gemmata spp. (5.41%) and fungal Pringsheimia spp. (0.03%) in females and bacterial Chitinophaga spp. (0.009%) and fungal Phaeococcomyces spp. (0.02%) in males. Significant differences in the relative abundance of phyla Proteobacteria and Planctomycetes bacteria and phyla Ascomycota and Basidiomycota fungi (P < 0.05) were also found between females and males. Some bacterial species of genera Spirosoma and Amnibacterium and fungal genera Venturia, Suillus, and Elmerina spp. were significantly enriched in males (P < 0.05). In contrast, levels of fungal genera Phoma and Aureobasidium spp. were significantly higher in females than in males (P < 0.05). The mineral, inorganic, and organic nutrients content contributed differently to the divergence of female and male phyllosphere microbial communities, with 87.08 and 45.17% of the variations being explained for bacterial and fungal communities, respectively. These results highlight the sexual discrimination of phyllosphere microbes on the dioecious plants and provide hints on the potential host-associated species in phyllosphere environments.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Environmental RNA: A Revolution in Ecological Resolution?

Current advancements in environmental RNA (eRNA) exploit its relatively fast turnover rate relative to environmental DNA (eDNA) to assess 'metabolically active' or temporally/spatially recent community diversity. However, this focus significantly underutilizes the trove of potential ecological information encrypted in eRNA. Here, we argue for pushing beyond current species-level eDNA detection capabilities by using eRNA to detect any organisms with unique eRNA profiles, potentially including different life-history stages, sexes, or even specific phenotypes within a species. We also discuss the future of eRNA as a means of assessing the physiological status of organisms and the ecological health of populations and communities, reflecting ecosystem-level conditions. We posit that eRNA has the potential to significantly improve the resolution of organism detection, biological monitoring, and biomonitoring applications in ecology.

Modulating the Gut Microbiota of Humans by Dietary Intervention with Plant Glycans

The human colon contains a community of microbial species, mostly bacteria, which is often referred to as the gut microbiota. The community is considered essential to human well-being by conferring additional energy-harvesting capacity, niche exclusion of pathogens, and molecular signaling activities that are integrated into human physiological processes. Plant polysaccharides (glycans, dietary fiber) are an important source of carbon and energy that supports the maintenance and functioning of the gut microbiota. Therefore, the daily quantity and quality of plant glycans consumed by the human host have the potential to influence health. Members of the gut microbiota differ in ability to utilize different types of plant glycans. Dietary interventions with specific glycans could modulate the microbiota, counteracting ecological perturbations that disrupt the intricate relationships between microbiota and host (dysbiosis). This review considers prospects and research options for modulation of the gut microbiota by the formulation of diets that, when consumed habitually, would correct dysbiosis by building diverse consortia that boost functional resilience. Traditional "prebiotics" favor bifidobacteria and lactobacilli, whereas dietary mixtures of plant glycans that are varied in chemical complexity would promote high-diversity microbiotas. It is concluded that research should aim at improving knowledge of bacterial consortia that, through shared nourishment, degrade and ferment plant glycans. The consortia may vary in composition from person to person, but functional outputs will be consistent in a given context because of metabolic redundancy among bacteria. Thus, the individuality of gut microbiotas could be encompassed, functional resilience encouraged, and correction of dysbiosis achieved.

A metatranscriptomic analysis of changing dynamics in the plankton communities adjacent to aquaculture leases in southern Tasmania, Australia

Aquaculture releases nitrogen to the marine environment, potentially changing dynamics of local plankton populations and causing adverse impacts. Metatranscriptomics have been used to study planktonic nutrient cycles and community dynamics. We hypothesised that the metatranscriptome could be used to monitor changing phytoplankton physiology near leases. To test this hypothesis, opportunistic samples were collected from one oceanic location in winter and one estuarine location in spring and analysed via RNASeq. Transcriptomes from different locations were found to have little overlap, due to different community compositions in the oceanic and estuarine locations. Transcript function was similar at each location. Proximity to the salmon pen had little influence over the transcriptome at the estuarine location. In the oceanic environment, diatom-based activity decreased near pens and dinoflagellate-based activity increased as demonstrated through the abundance of carbon fixation and nitrogen-acquisition-related transcripts. Our initial results suggest that the use of the metatranscriptome in monitoring is promising.

High Throughput Sequencing of MicroRNA in Rainbow Trout Plasma, Mucus, and Surrounding Water Following Acute Stress

Circulating plasma microRNAs (miRNAs) are well established as biomarkers of several diseases in humans and have recently been used as indicators of environmental exposures in fish. However, the role of plasma miRNAs in regulating acute stress responses in fish is largely unknown. Tissue and plasma miRNAs have recently been associated with excreted miRNAs; however, external miRNAs have never been measured in fish. The objective of this study was to identify the altered plasma miRNAs in response to acute stress in rainbow trout (Oncorhynchus mykiss), as well as altered miRNAs in fish epidermal mucus and the surrounding ambient water. Small RNA was extracted and sequenced from plasma, mucus, and water collected from rainbow trout pre- and 1 h-post a 3-min air stressor. Following small RNA-Seq and pathway analysis, we identified differentially expressed plasma miRNAs that targeted biosynthetic, degradation, and metabolic pathways. We successfully isolated miRNA from trout mucus and the surrounding water and detected differences in miRNA expression 1-h post air stress. The expressed miRNA profiles in mucus and water were different from the altered plasma miRNA profile, which indicated that the plasma miRNA response was not associated with or immediately reflected in external samples, which was further validated through qPCR. This research expands understanding of the role of plasma miRNA in the acute stress response of fish and is the first report of successful isolation and profiling of miRNA from fish mucus or samples of ambient water. Measurements of miRNA from plasma, mucus, or water can be further studied and have potential to be applied as non-lethal indicators of acute stress in fish.

Environmental fluctuations and their effects on microbial communities, populations and individuals

From the homeostasis of human health to the cycling of Earth's elements, microbial activities underlie environmental, medical and industrial processes. These activities occur in chemical and physical landscapes that are highly dynamic and experienced by bacteria as fluctuations. In this review, we first discuss how bacteria can experience both spatial and temporal heterogeneity in their environments as temporal fluctuations of various timescales (seconds to seasons) and types (nutrient, sunlight, fluid flow, etc.). We then focus primarily on nutrient fluctuations to discuss how bacterial communities, populations and single cells respond to environmental fluctuations. Overall, we find that environmental fluctuations are ubiquitous and diverse, and strongly shape microbial behavior, ecology and evolution when compared with environments in which conditions remain constant over time. We hope this review may serve as a guide toward understanding the significance of environmental fluctuations in microbial life, such that their contributions and implications can be better assessed and exploited.