Quantitative analysis of a deeply sequenced marine microbial metatranscriptome

Modern microbiology: Embracing complexity through integration across scales

Microbes were the only form of life on Earth for most of its history, and they still account for the vast majority of life's diversity. They convert rocks to soil, produce much of the oxygen we breathe, remediate our sewage, and sustain agriculture. Microbes are vital to planetary health as they maintain biogeochemical cycles that produce and consume major greenhouse gases and support large food webs. Modern microbiologists analyze nucleic acids, proteins, and metabolites; leverage sophisticated genetic tools, software, and bioinformatic algorithms; and process and integrate complex and heterogeneous datasets so that microbial systems may be harnessed to address contemporary challenges in health, the environment, and basic science. Here, we consider an inevitably incomplete list of emergent themes in our discipline and highlight those that we recognize as the archetypes of its modern era that aim to address the most pressing problems of the 21st century.

Transcriptome analysis: a powerful tool to understand individual microbial behaviors and interactions in ecosystems

Transcriptome analysis is a powerful tool for studying microbial ecology, especially individual microbial functions in an ecosystem and their interactions. With the development of high-throughput sequencing technology, great progress has been made in analytical methods for microbial communities in natural environments. 16S rRNA gene amplicon sequencing (ie microbial community structure analysis) and shotgun metagenome analysis have been widely used to determine the composition and potential metabolic capability of microorganisms in target environments without requiring culture. However, even if the types of microorganisms present and their genes are known, it is difficult to determine what they are doing in an ecosystem. Gene expression analysis (transcriptome analysis; RNA-seq) is a powerful tool to address these issues. The history and basic information of gene expression analysis, as well as examples of studies using this method to analyze microbial ecosystems, are presented.

Microbiome modeling: a beginner's guide

Microbiomes, comprised of diverse microbial species and viruses, play pivotal roles in human health, environmental processes, and biotechnological applications and interact with each other, their environment, and hosts via ecological interactions. Our understanding of microbiomes is still limited and hampered by their complexity. A concept improving this understanding is systems biology, which focuses on the holistic description of biological systems utilizing experimental and computational methods. An important set of such experimental methods are metaomics methods which analyze microbiomes and output lists of molecular features. These lists of data are integrated, interpreted, and compiled into computational microbiome models, to predict, optimize, and control microbiome behavior. There exists a gap in understanding between microbiologists and modelers/bioinformaticians, stemming from a lack of interdisciplinary knowledge. This knowledge gap hinders the establishment of computational models in microbiome analysis. This review aims to bridge this gap and is tailored for microbiologists, researchers new to microbiome modeling, and bioinformaticians. To achieve this goal, it provides an interdisciplinary overview of microbiome modeling, starting with fundamental knowledge of microbiomes, metaomics methods, common modeling formalisms, and how models facilitate microbiome control. It concludes with guidelines and repositories for modeling. Each section provides entry-level information, example applications, and important references, serving as a valuable resource for comprehending and navigating the complex landscape of microbiome research and modeling.

Nematodes alter the taxonomic and functional profiles of benthic bacterial communities: A metatranscriptomic approach

Marine sediments cover 70% of the Earth's surface, and harbour diverse bacterial communities critical for marine biogeochemical processes, which affect climate change, biodiversity and ecosystem functioning. Nematodes, the most abundant and species-rich metazoan organisms in marine sediments, in turn, affect benthic bacterial communities and bacterial-mediated ecological processes, but the underlying mechanisms by which they affect biogeochemical cycles remain poorly understood. Here, we demonstrate using a metatranscriptomic approach that nematodes alter the taxonomic and functional profiles of benthic bacterial communities. We found particularly strong stimulation of nitrogen-fixing and methane-oxidizing bacteria in the presence of nematodes, as well as increased functional activity associated with methane metabolism and degradation of various carbon compounds. This study provides empirical evidence that the presence of nematodes results in taxonomic and functional shifts in active bacterial communities, indicating that nematodes may play an important role in benthic ecosystem processes.

A novel synthetic nucleic acid mixture for quantification of microbes by mNGS

Metagenomic next-generation sequencing (mNGS) provides considerable advantages in identifying emerging and re-emerging, difficult-to-detect and co-infected pathogens; however, the clinical application of mNGS remains limited primarily due to the lack of quantitative capabilities. This study introduces a novel approach, KingCreate-Quantification (KCQ) system, for quantitative analysis of microbes in clinical specimens by mNGS, which co-sequence the target DNA extracted from the specimens along with a set of synthetic dsDNA molecules used as Internal-Standard (IS). The assay facilitates the conversion of microbial reads into their copy numbers based on IS reads utilizing a mathematical model proposed in this study. The performance of KCQ was systemically evaluated using commercial mock microbes with varying IS input amounts, different proportions of human genomic DNA, and at varying amounts of sequence analysis data. Subsequently, KCQ was applied in microbial quantitation in 36 clinical specimens including blood, bronchoalveolar lavage fluid, cerebrospinal fluid and oropharyngeal swabs. A total of 477 microbe genetic fragments were screened using the bioinformatic system. Of these 83 fragments were quantitatively compared with digital droplet PCR (ddPCR), revealing a correlation coefficient of 0.97 between the quantitative results of KCQ and ddPCR. Our study demonstrated that KCQ presents a practical approach for the quantitative analysis of microbes by mNGS in clinical samples.

Flagella are required to coordinately activate competition and host colonization factors in response to a mechanical signal

Bacteria employ antagonistic strategies to eliminate competitors of an ecological niche. Contact-dependent mechanisms, such as the type VI secretion system (T6SS), are prevalent in host-associated bacteria, yet we know relatively little about how T6SS+ strains make contact with competitors in highly viscous environments, such as host mucus. To better understand how cells respond to and contact one another in such environments, we performed a genome-wide transposon mutant screen of the T6SS-wielding beneficial bacterial symbiont, Vibrio fischeri, and identified two sets of genes that are conditionally required for killing. LPS/capsule and flagellar-associated genes do not affect T6SS directly and are therefore not required for interbacterial killing when cell contact is forced yet are necessary for killing in high-viscosity liquid (hydrogel) where cell-cell contact must be biologically mediated. Quantitative transcriptomics revealed that V. fischeri significantly increases expression of both T6SS genes and cell surface modification factors upon transition from low- to high-viscosity media. Consistent with coincubation and fluorescence microscopy data, flagella are not required for T6SS expression in hydrogel. However, flagella play a key role in responding to the physical environment by promoting expression of the surface modification genes identified in our screen, as well as additional functional pathways important for host colonization including uptake of host-relevant iron and carbon sources, and nitric oxide detoxification enzymes. Our findings suggest that flagella may act as a mechanosensor for V. fischeri to coordinately activate competitive strategies and host colonization factors, underscoring the significance of the physical environment in directing complex bacterial behaviors.

Identifying biodegradation pathways of cetrimonium bromide (CTAB) using metagenome, metatranscriptome, and metabolome tri-omics integration

Traditional research on biodegradation of emerging organic pollutants involves slow and labor-intensive experimentation. Currently, fast-developing metagenome, metatranscriptome, and metabolome technologies promise to expedite mechanistic research on biodegradation of emerging organic pollutants. Integrating the metagenome, metatranscriptome, and metabolome (i.e., tri-omics) makes it possible to link gene abundance and expression with the biotransformation of the contaminant and the formation of metabolites from this biotransformation. In this study, we used this tri-omics approach to study the biotransformation pathways for cetyltrimethylammonium bromide (CTAB) under aerobic conditions. The tri-omics analysis showed that CTAB undergoes three parallel first-step mono-/di-oxygenations (to the α, β, and ω-carbons); intermediate metabolites and expressed enzymes were identified for all three pathways, and the β-carbon mono-/di-oxygenation is a novel pathway; and the genes related to CTAB biodegradation were associated with Pseudomonas spp. Four metabolites - palmitic acid, trimethylamine N-oxide (TMAO), myristic acid, and betaine - were the key identified biodegradation intermediates of CTAB, and they were associated with first-step mono-/di-oxygenations at the α/β-C. This tri-omics approach with CTAB demonstrates its power for identifying promising paths for future research on the biodegradation of complex organics by microbial communities.

Transcriptomic Insights into Archaeal Nitrification in the Amundsen Sea Polynya, Antarctica

Antarctic polynyas have the highest Southern Ocean summer primary productivity, and due to anthropogenic climate change, these areas have formed faster recently. Ammonia-oxidizing archaea (AOA) are among the most ubiquitous and abundant microorganisms in the ocean and play a primary role in the global nitrogen cycle. We utilized metagenomics and metatranscriptomics to gain insights into the physiology and metabolism of AOA in polar oceans, which are associated with ecosystem functioning. A polar-specific ecotype of AOA, from the "Candidatus Nitrosomarinus"-like group, was observed to be dominant in the Amundsen Sea Polynya (ASP), West Antarctica, during a succession of summer phytoplankton blooms. AOA had the highest transcriptional activity among prokaryotes during the bloom decline phase (DC). Metatranscriptomic analysis of key genes involved in ammonia oxidation, carbon fixation, transport, and cell division indicated that this polar AOA ecotype was actively involved in nitrification in the bloom DC in the ASP. This study revealed the physiological and metabolic traits of this key polar-type AOA in response to phytoplankton blooms in the ASP and provided insights into AOA functions in polar oceans.

Synechococcus nitrogen gene loss in iron-limited ocean regions

Synechococcus are the most abundant cyanobacteria in high latitude regions and are responsible for an estimated 17% of annual marine net primary productivity. Despite their biogeochemical importance, Synechococcus populations have been unevenly sampled across the ocean, with most studies focused on low-latitude strains. In particular, the near absence of Synechococcus genomes from high-latitude, High Nutrient Low Chlorophyll (HNLC) regions leaves a gap in our knowledge of picocyanobacterial adaptations to iron limitation and their influence on carbon, nitrogen, and iron cycles. We examined Synechococcus populations from the subarctic North Pacific, a well-characterized HNLC region, with quantitative metagenomics. Assembly with short and long reads produced two near complete Synechococcus metagenome-assembled genomes (MAGs). Quantitative metagenome-derived abundances of these populations matched well with flow cytometry counts, and the Synechococcus MAGs were estimated to comprise >99% of the Synechococcus at Station P. Whereas the Station P Synechococcus MAGs contained multiple genes for adaptation to iron limitation, both genomes lacked genes for uptake and assimilation of nitrate and nitrite, suggesting a dependence on ammonium, urea, and other forms of recycled nitrogen leading to reduced iron requirements. A global analysis of Synechococcus nitrate reductase abundance in the TARA Oceans dataset found nitrate assimilation genes are also lower in other HNLC regions. We propose that nitrate and nitrite assimilation gene loss in Synechococcus may represent an adaptation to severe iron limitation in high-latitude regions where ammonium availability is higher. Our findings have implications for models that quantify the contribution of cyanobacteria to primary production and subsequent carbon export.

A standardized quantitative analysis strategy for stable isotope probing metagenomics

Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many DNA-SIP studies rely on 16S rRNA gene sequences to identify active taxa, but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA gene sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes and their level of isotopic enrichment were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytical models for identifying active taxa and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg, an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. IMPORTANCE Answering the questions, "who is eating what?" and "who is active?" within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. These questions can be pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganism's taxonomic identity and genome composition while providing quantitative estimates of the microorganism's isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes.

Metagenomic next generation sequencing for studying antibiotic resistance genes in the environment

Bacterial antimicrobial resistance (AMR) is a persisting and growing threat to human health. Characterization of antibiotic resistance genes (ARGs) in the environment is important to understand and control ARG-associated microbial risks. Numerous challenges exist in monitoring ARGs in the environment, due to the extraordinary diversity of ARGs, low abundance of ARGs with respect to the complex environmental microbiomes, difficulties in linking ARGs with bacterial hosts by molecular methods, difficulties in achieving quantification and high throughput simultaneously, difficulties in assessing mobility potential of ARGs, and difficulties in determining the specific AMR determinant genes. Advances in the next generation sequencing (NGS) technologies and related computational and bioinformatic tools are facilitating rapid identification and characterization ARGs in genomes and metagenomes from environmental samples. This chapter discusses NGS-based strategies, including amplicon-based sequencing, whole genome sequencing, bacterial population-targeted metagenome sequencing, metagenomic NGS, quantitative metagenomic sequencing, and functional/phenotypic metagenomic sequencing. Current bioinformatic tools for analyzing sequencing data for studying environmental ARGs are also discussed.

Aerobic bacteria produce nitric oxide via denitrification and promote algal population collapse

Microbial interactions govern marine biogeochemistry. These interactions are generally considered to rely on exchange of organic molecules. Here we report on a novel inorganic route of microbial communication, showing that algal-bacterial interactions between Phaeobacter inhibens bacteria and Gephyrocapsa huxleyi algae are mediated through inorganic nitrogen exchange. Under oxygen-rich conditions, aerobic bacteria reduce algal-secreted nitrite to nitric oxide (NO) through denitrification, a well-studied anaerobic respiratory mechanism. The bacterial NO is involved in triggering a cascade in algae akin to programmed cell death. During death, algae further generate NO, thereby propagating the signal in the algal population. Eventually, the algal population collapses, similar to the sudden demise of oceanic algal blooms. Our study suggests that the exchange of inorganic nitrogen species in oxygenated environments is a potentially significant route of microbial communication within and across kingdoms.

Reverse engineering environmental metatranscriptomes clarifies best practices for eukaryotic assembly

BACKGROUND

Diverse communities of microbial eukaryotes in the global ocean provide a variety of essential ecosystem services, from primary production and carbon flow through trophic transfer to cooperation via symbioses. Increasingly, these communities are being understood through the lens of omics tools, which enable high-throughput processing of diverse communities. Metatranscriptomics offers an understanding of near real-time gene expression in microbial eukaryotic communities, providing a window into community metabolic activity.

RESULTS

Here we present a workflow for eukaryotic metatranscriptome assembly, and validate the ability of the pipeline to recapitulate real and manufactured eukaryotic community-level expression data. We also include an open-source tool for simulating environmental metatranscriptomes for testing and validation purposes. We reanalyze previously published metatranscriptomic datasets using our metatranscriptome analysis approach.

CONCLUSION

We determined that a multi-assembler approach improves eukaryotic metatranscriptome assembly based on recapitulated taxonomic and functional annotations from an in-silico mock community. The systematic validation of metatranscriptome assembly and annotation methods provided here is a necessary step to assess the fidelity of our community composition measurements and functional content assignments from eukaryotic metatranscriptomes.

Diversity, distribution, and expression of opsin genes in freshwater lakes

Microbial rhodopsins are widely distributed in aquatic environments and may significantly contribute to phototrophy and energy budgets in global oceans. However, the study of freshwater rhodopsins has been largely limited. Here, we explored the diversity, ecological distribution, and expression of opsin genes that encode the apoproteins of type I rhodopsins in humic and clearwater lakes with contrasting physicochemical and optical characteristics. Using metagenomes and metagenome-assembled genomes, we recovered opsin genes from a wide range of taxa, mostly predicted to encode green light-absorbing proton pumps. Viral opsin and novel bacterial opsin clades were recovered. Opsin genes occurred more frequently in taxa from clearwater than from humic water, and opsins in some taxa have nontypical ion-pumping motifs that might be associated with physicochemical conditions of these two freshwater types. Analyses of the surface layer of 33 freshwater systems revealed an inverse correlation between opsin gene abundance and lake dissolved organic carbon (DOC). In humic water with high terrestrial DOC and light-absorbing humic substances, opsin gene abundance was low and dramatically declined within the first few meters, whereas the abundance remained relatively high along the bulk water column in clearwater lakes with low DOC, suggesting opsin gene distribution is influenced by lake optical properties and DOC. Gene expression analysis confirmed the significance of rhodopsin-based phototrophy in clearwater lakes and revealed different diel expressional patterns among major phyla. Overall, our analyses revealed freshwater opsin diversity, distribution and expression patterns, and suggested the significance of rhodopsin-based phototrophy in freshwater energy budgets, especially in clearwater lakes.

Metatranscriptomes reveal the diverse responses of Thaumarchaeota ecotypes to environmental variations in the northern slope of the South China Sea

Thaumarchaeota are among the most abundant prokaryotes in the ocean, playing important roles in carbon and nitrogen cycling. Marine Thaumarchaeota ecotypes exhibit depth-related diversification and seasonal changes. However, transcriptomic activities concerning niche partitioning among thaumarchaeal ecotypes remain unclear. Here, we examined the variations in the distribution and transcriptomic activity of marine Thaumarchaeota ecotypes. Three primary ecotypes were identified: a Nitrosopumilus-like clade; a Nitrosopelagicus-like water column A (WCA) clade, thriving in epipelagic water; and a water column B (WCB) clade, dominant in deep water. Depth-related partitioning of the three ecotypes and the seasonal variability of the WCA and WCB ecotypes were observed. Nutrient concentrations, chlorophyll α and salinity were the primary environmental factors. The relative abundance of the WCA ecotype and its transcript abundance of amoA gene were positively correlated with chlorophyll α and salinity, while the WCB ecotype was positively correlated with nitrate and phosphate. Based on high-quality metagenome-assembled genomes, transcriptomic analysis revealed that the three ecotypes exhibited various co-occurring expression patterns of the elemental cycling genes in the nitrogen, carbon, phosphorus, and sulfur cycles. Our results provide transcriptomic evidence of the niche differentiation of marine Thaumarchaeota ecotypes, highlighting the diverse roles of ecotypes and WCA subclades in biogeochemical cycles.

Engineering an incubation environment that mimics in situ conditions for in vitro coastal microbiome studies

Coastal environments are dynamic and can vary widely on short- or long-term scales depending on location and weather. Incubation equipment that reflects these changes through programmable gradient light and temperature cycles would permit more precise in vitro coastal microbiome studies. Here we present an open-source incubation environment that mimics in situ conditions for in vitro coastal microbiome studies using a modified shaking water bath that has fully customizable temperature and light gradients that can also mimic real-time field conditions. We compared coastal microbial community profiles incubated in situ and in our build mimicking field conditions over 48 h. Analyses of congruence indicated significant overlap (p > 0.2) between microbial communities incubated in situ and in vitro at each time point.

Integrated Multi-Omics Analysis Reveals Differential Effects of Fructo-Oligosaccharides (FOS) Supplementation on the Human Gut Ecosystem

Changes in the gut ecosystem, including the microbiome and the metabolome, and the host immune system after fructo-oligosaccharide (FOS) supplementation were evaluated. The supplementation of FOS showed large inter-individual variability in the absolute numbers of fecal bacteria and an increase in Bifidobacterium. The fecal metabolome analysis revealed individual variability in fructose utilization in response to FOS supplementation. In addition, immunoglobulin A(IgA) tended to increase upon FOS intake, and peripheral blood monocytes significantly decreased upon FOS intake and kept decreasing in the post-FOS phase. Further analysis using a metagenomic approach showed that the differences could be at least in part due to the differences in gene expressions of enzymes that are involved in the fructose metabolism pathway. While the study showed individual differences in the expected health benefits of FOS supplementation, the accumulation of “personalized” knowledge of the gut ecosystem with its genetic expression may enable effective instructions on prebiotic consumption to optimize health benefits for individuals in the future.

Investigating microscale patchiness of motile microbes under turbulence in a simulated convective mixed layer

Microbes play a primary role in aquatic ecosystems and biogeochemical cycles. Spatial patchiness is a critical factor underlying these activities, influencing biological productivity, nutrient cycling and dynamics across trophic levels. Incorporating spatial dynamics into microbial models is a long-standing challenge, particularly where small-scale turbulence is involved. Here, we combine a fully 3D direct numerical simulation of convective mixed layer turbulence, with an individual-based microbial model to test the key hypothesis that the coupling of gyrotactic motility and turbulence drives intense microscale patchiness. The fluid model simulates turbulent convection caused by heat loss through the fluid surface, for example during the night, during autumnal or winter cooling or during a cold-air outbreak. We find that under such conditions, turbulence-driven patchiness is depth-structured and requires high motility: Near the fluid surface, intense convective turbulence overpowers motility, homogenising motile and non-motile microbes approximately equally. At greater depth, in conditions analogous to a thermocline, highly motile microbes can be over twice as patch-concentrated as non-motile microbes, and can substantially amplify their swimming velocity by efficiently exploiting fast-moving packets of fluid. Our results substantiate the predictions of earlier studies, and demonstrate that turbulence-driven patchiness is not a ubiquitous consequence of motility but rather a delicate balance of motility and turbulent intensity.

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.

Parallel meta-transcriptome analysis reveals degradation of plant secondary metabolites by beetles and their gut symbionts

Switching to a new host plant is a driving force for divergence and speciation in herbivorous insects. This process of incorporating a novel host plant into the diet may require a number of adaptations in the insect herbivores that allow them to consume host plant tissue that may contain toxic secondary chemicals. As a result, herbivorous insects are predicted to have evolved efficient ways to detoxify major plant defenses and increase fitness by either relying on their own genomes or by recruiting other organisms such as microbial gut symbionts. In the present study we used parallel meta-transcriptomic analyses of Altica flea beetles and their gut symbionts to explore the contributions of beetle detoxification mechanisms versus detoxification by their gut consortium. We compared the gut meta-transcriptomes of two sympatric Altica species that feed exclusively on different host plant species as well as their F₁ hybrids that were fed one of the two host plant species. These comparisons revealed that gene expression patterns of Altica are dependent on both beetle species identity and diet. The community structure of gut symbionts was also dependent on the identity of the beetle species, and the gene expression patterns of the gut symbionts were significantly correlated with beetle species and plant diet. Some of the enriched genes identified in the beetles and gut symbionts are involved in the degradation of secondary metabolites produced by plants, suggesting that Altica flea beetles may use their gut microbiota to help them feed on and adapt to their host plants.

Oceanic Crustal Fluid Single Cell Genomics Complements Metagenomic and Metatranscriptomic Surveys With Orders of Magnitude Less Sample Volume

Fluids circulating through oceanic crust play important roles in global biogeochemical cycling mediated by their microbial inhabitants, but studying these sites is challenged by sampling logistics and low biomass. Borehole observatories installed at the North Pond study site on the western flank of the Mid-Atlantic Ridge have enabled investigation of the microbial biosphere in cold, oxygenated basaltic oceanic crust. Here we test a methodology that applies redox-sensitive fluorescent molecules for flow cytometric sorting of cells for single cell genomic sequencing from small volumes of low biomass (approximately 103 cells ml-1) crustal fluid. We compare the resulting genomic data to a recently published paired metagenomic and metatranscriptomic analysis from the same site. Even with low coverage genome sequencing, sorting cells from less than one milliliter of crustal fluid results in similar interpretation of dominant taxa and functional profiles as compared to 'omics analysis that typically filter orders of magnitude more fluid volume. The diverse community dominated by Gammaproteobacteria, Bacteroidetes, Desulfobacterota, Alphaproteobacteria, and Zetaproteobacteria, had evidence of autotrophy and heterotrophy, a variety of nitrogen and sulfur cycling metabolisms, and motility. Together, results indicate fluorescence activated cell sorting methodology is a powerful addition to the toolbox for the study of low biomass systems or at sites where only small sample volumes are available for analysis.

Multi-Omics Study of Keystone Species in a Cystic Fibrosis Microbiome

Ecological networking and in vitro studies predict that anaerobic, mucus-degrading bacteria are keystone species in cystic fibrosis (CF) microbiomes. The metabolic byproducts from these bacteria facilitate the colonization and growth of CF pathogens like Pseudomonas aeruginosa. Here, a multi-omics study informed the control of putative anaerobic keystone species during a transition in antibiotic therapy of a CF patient. A quantitative metagenomics approach combining sequence data with epifluorescence microscopy showed that during periods of rapid lung function loss, the patient's lung microbiome was dominated by the anaerobic, mucus-degrading bacteria belonging to Streptococcus, Veillonella, and Prevotella genera. Untargeted metabolomics and community cultures identified high rates of fermentation in these sputa, with the accumulation of lactic acid, citric acid, and acetic acid. P. aeruginosa utilized these fermentation products for growth, as indicated by quantitative transcriptomics data. Transcription levels of P. aeruginosa genes for the utilization of fermentation products were proportional to the abundance of anaerobic bacteria. Clindamycin therapy targeting Gram-positive anaerobes rapidly suppressed anaerobic bacteria and the accumulation of fermentation products. Clindamycin also lowered the abundance and transcription of P. aeruginosa, even though this patient's strain was resistant to this antibiotic. The treatment stabilized the patient's lung function and improved respiratory health for two months, lengthening by a factor of four the between-hospitalization time for this patient. Killing anaerobes indirectly limited the growth of P. aeruginosa by disrupting the cross-feeding of fermentation products. This case study supports the hypothesis that facultative anaerobes operated as keystone species in this CF microbiome. Personalized multi-omics may become a viable approach for routine clinical diagnostics in the future, providing critical information to inform treatment decisions.

The Transcriptional Response of Soil Bacteria to Long-Term Warming and Short-Term Seasonal Fluctuations in a Terrestrial Forest

Terrestrial ecosystems are an important carbon store, and this carbon is vulnerable to microbial degradation with climate warming. After 30 years of experimental warming, carbon stocks in a temperate mixed deciduous forest were observed to be reduced by 30% in the heated plots relative to the controls. In addition, soil respiration was seasonal, as was the warming treatment effect. We therefore hypothesized that long-term warming will have higher expressions of genes related to carbohydrate and lipid metabolism due to increased utilization of recalcitrant carbon pools compared to controls. Because of the seasonal effect of soil respiration and the warming treatment, we further hypothesized that these patterns will be seasonal. We used RNA sequencing to show how the microbial community responds to long-term warming (~30 years) in Harvard Forest, MA. Total RNA was extracted from mineral and organic soil types from two treatment plots (+5°C heated and ambient control), at two time points (June and October) and sequenced using Illumina NextSeq technology. Treatment had a larger effect size on KEGG annotated transcripts than on CAZymes, while soil types more strongly affected CAZymes than KEGG annotated transcripts, though effect sizes overall were small. Although, warming showed a small effect on overall CAZymes expression, several carbohydrate-associated enzymes showed increased expression in heated soils (~68% of all differentially expressed transcripts). Further, exploratory analysis using an unconstrained method showed increased abundances of enzymes related to polysaccharide and lipid metabolism and decomposition in heated soils. Compared to long-term warming, we detected a relatively small effect of seasonal variation on community gene expression. Together, these results indicate that the higher carbohydrate degrading potential of bacteria in heated plots can possibly accelerate a self-reinforcing carbon cycle-temperature feedback in a warming climate.

A Quantitative Metagenomic Sequencing Approach for High-Throughput Gene Quantification and Demonstration with Antibiotic Resistance Genes

Comprehensive microbial risk assessment requires high-throughput quantification of diverse microbial risks in the environment. Current metagenomic next-generation sequencing approaches can achieve high-throughput detection of genes indicative of microbial risks but lack quantitative capabilities. This study developed and tested a quantitative metagenomic next-generation sequencing (qmNGS) approach. Numerous xenobiotic synthetic internal DNA standards were used to determine the sequencing yield (Y_seq) of the qmNGS approach, which can then be used to calculate absolute concentration of target genes in environmental samples based on metagenomic sequencing results. The qmNGS approach exhibited excellent linearity as indicated by a strong linear correlation (r² = 0.98) between spiked and detected concentrations of internal standards. High-throughput capability of the qmNGS approach was demonstrated with artificial Escherichia coli mixtures and cattle manure samples, for which 95 ± 3 and 208 ± 4 types of antibiotic resistance genes (ARGs) were detected and quantified simultaneously. The qmNGS approach was further compared with quantitative real-time PCR (qPCR) and demonstrated comparable levels of accuracy and less variation for the quantification of six target genes (16S, tetO, sulI, tetM, ermB, and qnrS). IMPORTANCE Monitoring and comprehensive assessment of microbial risks in the environment require high-throughput gene quantification. The quantitative metagenomic NGS (qmNGS) approach developed in this study incorporated numerous xenobiotic and synthetic DNA internal standard fragments into metagenomic NGS workflow, which are used to determine a new parameter called sequencing yield that relates sequence base reads to absolute concentration of target genes in the environmental samples. The qmNGS approach demonstrated excellent method linearity and comparable performance as the qPCR approach with high-throughput capability. This new qmNGS approach can achieve high-throughput and accurate gene quantification in environmental samples and has the potential to become a useful tool in monitoring and comprehensively assessing microbial risks in the environment.

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.

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.

Taxonomic and Functional Shifts in the Sprout Spent Irrigation Water Microbiome in Response to Salmonella Contamination of Alfalfa Seeds

Despite recent advances in Salmonella-sprout research, little is known about the relationship between Salmonella and the sprout microbiome during sprouting. Sprout spent irrigation water (SSIW) provides an informative representation of the total microbiome of this primarily aquaponic crop. This study was designed to characterize the function and taxonomy of the most actively transcribed genes in SSIW from Salmonella enterica serovar Cubana-contaminated alfalfa seeds throughout the sprouting process. Genomic DNA and total RNA from SSIW was collected at regular intervals and sequenced using Illumina MiSeq and NextSeq platforms. Nucleic acid data were annotated using four different pipelines. Both metagenomic and metatranscriptomic analyses revealed a diverse and highly dynamic SSIW microbiome. A "core" SSIW microbiome comprised Klebsiella, Enterobacter, Pantoea, and Cronobacter The impact, however, of Salmonella contamination on alfalfa seeds influenced SSIW microbial community dynamics not only structurally but also functionally. Changes in genes associated with metabolism, genetic information processing, environmental information processing, and cellular processes were abundant and time dependent. At time points of 24 h, 48 h, and 96 h, totals of 541, 723, and 424 S Cubana genes, respectively, were transcribed at either higher or lower levels than at 0 h in SSIW during sprouting. An array of S Cubana genes (107) were induced at all three time points, including genes involved in biofilm formation and modulation, stress responses, and virulence and tolerance to antimicrobials. Taken together, these findings expand our understanding of the effect of Salmonella seed contamination on the sprout crop microbiome and metabolome.IMPORTANCE Interactions of human enteric pathogens like Salmonella with plants and plant microbiomes remain to be elucidated. The rapid development of next-generation sequencing technologies provides powerful tools enabling investigation of such interactions from broader and deeper perspectives. Using metagenomic and metatranscriptomic approaches, this study identified not only changes in microbiome structure of SSIW associated with sprouting but also changes in the gene expression patterns related to the sprouting process in response to Salmonella contamination of alfalfa seeds. This study advances our knowledge on Salmonella-plant (i.e., sprout) interaction.

Unraveling bacteria-mediated degradation of lignin-derived aromatic compounds in a freshwater environment

Terrestrial organic carbon-lignin plays a crucial role in the global carbon balance. However, limited studies presented the functional and ecological traits of lignin decomposers population in natural aquatic ecosystem. In this study, we performed a multi-omics analysis by deploying amplicon, metagenomic, and metatranscriptomic approaches to identify the key potential degraders and pathways involved lignin-derived aromatic compounds in the later stage of lignin degradation. By establishing microcosms with model lignin-derived aromatic compound (vanillic acid, VAN), based on the estimated absolute abundance (EAA) and the metagenome-assembled genomes (MAGs), novel potential lignin-derived aromatic compounds degraders were identified in the aquatic ecosystem. Furthermore, members of the phyla Proteobacteria and Actinobacteria were the potential major lignin-derived aromatic compounds degraders in the studied ecosystem. Our study demonstrated that genomes of the class Betaproteobacteria (Proteobacteria) possess a complete enzymatic system for the degradation of diarylpropanes, vanillate and protocatechuate, besides having the capacity to degrade other lignin-derived aromatic compounds. This study provides strong evidence for the ability of aquatic bacteria to degrade lignin-derived aromatic compounds and suggest that different microbes might occupy different niches in the later stage of lignin degradation.

Microbial Niche Diversification in the Galápagos Archipelago and Its Response to El Niño

The Galápagos Archipelago is located at the intersection of several major oceanographic features that produce diverse environmental conditions around the islands, and thus has the potential to serve as a natural laboratory for discerning the underlying environmental factors that structure marine microbial communities. Here we used quantitative metagenomics to characterize microbial communities in relation to archipelago marine habitats, and how those populations shift due to substantial environmental changes brought on by El Niño. Environmental conditions such as temperature, salinity, inorganic dissolved nutrients, and dissolved organic carbon (DOC) concentrations varied throughout the archipelago, revealing a diversity of potential microbial niches arising from upwelling, oligotrophic to eutrophic gradients, physical isolation, and potential island mass effects. The volumetric abundances of microbial community members shifted with these environmental changes and revealed several taxonomic indicators of different water masses. This included a transition from a Synechococcus dominated system in the west to an even mix of Synechococcus and Prochlorococcus in the east, mirroring the archipelago’s mesotrophic to oligotrophic and productivity gradients. Several flavobacteria groups displayed characteristic habitat distributions, including enrichment of Polaribacter and Tenacibaculum clades in the relatively nutrient rich western waters, Leeuwenhoekiella spp. that were enriched in the more nutrient-deplete central and eastern sites, and the streamlined MS024-2A group found to be abundant across all sites. During the 2015/16 El Niño event, both environmental conditions and microbial community composition were substantially altered, primarily on the western side of the archipelago due to the reduction of upwelling from the Equatorial Undercurrent. When the upwelling resumed, concentrations of inorganic nutrients and DOC at the western surface sites were more typical of mesopelagic depths. Correspondingly, Synechococcus abundances decreased by an order of magnitude, while groups associated with deeper water masses were enriched, including streamlined roseobacters HTCC2255 and HIMB11, Thioglobacaceae, methylotrophs (Methylophilaceae), archaea (Nitrosopumilaceae), and distinct subpopulations of Pelagibaceriales (SAR11 clade). These results provide a quantitative framework to connect community-wide microbial volumetric abundances to their environmental drivers, and thus incorporation into biogeochemical and ecological models.

Integration of absolute multi-omics reveals dynamic protein-to-RNA ratios and metabolic interplay within mixed-domain microbiomes

While the field of microbiology has adapted to the study of complex microbiomes via modern meta-omics techniques, we have not updated our basic knowledge regarding the quantitative levels of DNA, RNA and protein molecules within a microbial cell, which ultimately control cellular function. Here we report the temporal measurements of absolute RNA and protein levels per gene within a mixed bacterial-archaeal consortium. Our analysis of this data reveals an absolute protein-to-RNA ratio of 10²–10⁴ for bacterial populations and 10³–10⁵ for an archaeon, which is more comparable to Eukaryotic representatives’ humans and yeast. Furthermore, we use the linearity between the metaproteome and metatranscriptome over time to identify core functional guilds, hence using a fundamental biological feature (i.e., RNA/protein levels) to highlight phenotypical complementarity. Our findings show that upgrading multi-omic toolkits with traditional absolute measurements unlocks the scaling of core biological questions to dynamic and complex microbiomes, creating a deeper insight into inter-organismal relationships that drive the greater community function.

Here, the authors perform a temporal multi-omic analysis of a minimalistic cellulose-degrading and methane-producing consortium at the strain level and estimate protein-to-RNA ratios and RNA-protein dynamics of the community simultaneously over time.

Diversity and structure of prokaryotic communities within organic and conventional farming systems in central highlands of Kenya

Management practices such as tillage, crop rotation, irrigation, organic and inorganic inputs application are known to influence diversity and function of soil microbial populations. In this study, we investigated the effect of conventional versus organic farming systems at low and high input levels on structure and diversity of prokaryotic microbial communities. Soil samples were collected from the ongoing long-term farming system comparison trials established in 2007 at Chuka and Thika in Kenya. Physicochemical parameters for each sample were analyzed. Total DNA and RNA amplicons of variable region (V4-V7) of the 16S rRNA gene were generated on an Illumina platform using the manufacturer's instructions. Diversity indices and statistical analysis were done using QIIME2 and R packages, respectively. A total of 29,778,886 high quality reads were obtained and assigned to 16,176 OTUs at 97% genetic distance across both 16S rDNA and 16S rRNA cDNA datasets. The results pointed out a histrionic difference in OTUs based on 16S rDNA and 16S rRNA cDNA. Precisely, while 16S rDNA clustered by site, 16S rRNA cDNA clustered by farming systems. In both sites and systems, dominant phylotypes were affiliated to phylum Actinobacteria, Proteobacteria and Acidobacteria. Conventional farming systems showed a higher species richness and diversity compared to organic farming systems, whilst 16S rRNA cDNA datasets were similar. Physiochemical factors were associated differently depending on rRNA and rDNA. Soil pH, electrical conductivity, organic carbon, nitrogen, potassium, aluminium, zinc, iron, boron and micro-aggregates showed a significant influence on the observed microbial diversity. The observed higher species diversity in the conventional farming systems can be attributed to the integration of synthetic and organic agricultural inputs. These results show that the type of inputs used in a farming system not only affect the soil chemistry but also the microbial population dynamics and eventually the functional roles of these microbes.

A brief guide for the measurement and interpretation of microbial functional diversity

The importance of functional diversity for the functioning and behaviour of microbial communities is clear, yet the widespread incorporation of functional diversity measurements into environmental microbiology study designs remains surprisingly limited. This may, at least to some extent, be a consequence of the unique conceptual and methodological challenges to measuring functional diversity in microbial communities. To facilitate the increased incorporation of functional diversity measurements into environmental microbiology study designs, we review here the process and some key caveats for measuring functional diversity and provide specific examples. We highlight three main decision points and provide guidance to making these decisions based on the underlying mechanisms for how functional diversity relates to an ecosystem process or property of interest. We discuss the selection of an appropriate type of functional trait, selection of the specificity at which functional diversity will be measured, and selection of an appropriate metric for estimating functional diversity from quantitative measures of those traits. We further discuss decisions regarding the use of one- or multi-dimensional measures of functional diversity and how advances in the field of trait-based community ecology could be applied or adapted to address questions in environmental microbiology.

Metatranscriptomics From a Small Aquatic System: Microeukaryotic Community Functions Through the Diurnal Cycle

Light is an important factor for the growth of planktonic organisms, and many of them depend on the diurnal light/dark cycle to regulate key metabolic processes. So far, most of the diel responses were only studied in single species or marine and large lake communities. Yet, we lack information on whether these processes are regulated similarly in small aquatic systems such as ponds. Here, we investigated the activity of a microeukaryotic community from a temperate, small freshwater pond in response to the diurnal cycle. For this, we took samples at midday and night during the Central European summer. We extracted pigments and RNA from samples and the sequencing of eukaryotic transcripts allowed us to obtain day and night metatranscriptomes. Differentially expressed transcripts primarily corresponded to photosynthesis-related and translational processes, and were found to be upregulated at midday with high light conditions compared to darkness. Unique gene ontology classes were found at each respective condition. During the day, ontology classes including photoreception for photosynthesis, defense, and stress mechanisms dominated, while motility, ribosomal assembly and other large, energy-consuming processes were restricted to the night. Euglenophyta and Chlorophyta dominated the active phototrophic community, as shown by the pigment composition analysis. Regarding the gene expression patterns, we could confirm that the pond community appears to follow similar diurnal dynamics as those described for larger aquatic ecosystems. Overall, combining pigment analyses, metatranscriptomics, and data on physicochemical factors yielded considerably more insight into the metabolic processes performed by the microeukaryotic community of a small freshwater ecosystem.

Transcriptional Patterns of Biogeochemically Relevant Marker Genes by Temperate Marine Bacteria

Environmental microbial gene expression patterns remain largely unexplored, particularly at interannual time scales. We analyzed the variability in the expression of marker genes involved in ecologically relevant biogeochemical processes at a temperate Atlantic site over two consecutive years. Most of nifH transcripts, involved in nitrogen (N) fixation, were affiliated with the symbiotic cyanobacterium Candidatus Atelocyanobacterium thalassa, suggesting a key role as N providers in this system. The expression of nifH and amoA (i.e., marker for ammonia oxidation) showed consistent maxima in summer and autumn, respectively, suggesting a temporal succession of these important N cycling processes. The patterns of expression of genes related to the oxidation of carbon monoxide (coxL) and reduced sulfur (soxB) were different from that of amoA, indicating alternate timings for these energy conservation strategies. We detected expression of alkaline phosphatases, induced under phosphorus limitation, in agreement with the reported co-limitation by this nutrient at the study site. In contrast, low-affinity phosphate membrane transporters (pit) typically expressed under phosphorus luxury conditions, were mainly detected in post-bloom conditions. Rhodobacteraceae dominated the expression of soxB, coxL and ureases, while Pelagibacteraceae dominated the expression of proteorhodopsins. Bacteroidetes and Gammaproteobacteria were major contributors to the uptake of inorganic nutrients (pit and amt transporters). Yet, in autumn, Thauma- and Euryarchaeota unexpectedly contributed importantly to the uptake of ammonia and phosphate, respectively. We provide new hints on the active players and potential dynamics of ecologically relevant functions in situ, highlighting the potential of metatranscriptomics to provide significant input to future omics-driven marine ecosystem assessment.

Microbial responses to perfluoroalkyl substances and perfluorooctanesulfonate (PFOS) desulfurization in the Antarctic marine environment

Perfluorooctanesulfonate (PFOS) and perfluorooctanoate (PFOA) acids are ubiquitous in the oceans, including remote regions, and are toxic to fish and mammals. The impact to the lowest trophic levels of the food web, however, remains unknown. We challenged natural bacterial communities inhabiting Antarctic coastal waters (Deception Island) with PFOS and PFOA concentrations ranging from 2 ng/L to 600 ng/L that selected for tolerant taxa. After 48 h, concentrations of PFOS decreased by more than 50% and sulfur metabolism-related transcripts were significantly enriched in the treatments suggesting desulfurization of PFOS. Conversely, no significant differences were found between initial and final PFOA concentrations. Gammaproteobacteria and Roseobacter, two abundant groups of marine bacteria, increased their relative activity after 24 h of incubation, whereas Flavobacteriia became the main contributor in the treatments after 6 days. Community activities (extracellular enzyme activity and absolute number of transcripts) were higher in the treatments than in the controls, while bacterial abundances were lower in the treatments, suggesting a selection of PFOS and PFOA tolerant community in the exposed treatments. Our results show a direct effect of PFOS and PFOA exposure on the composition and functionality of natural Antarctic marine microbial communities. While no evidence of defluorination of PFOS or PFOA was detected, probable desulfurization of PFOS depicts a direct link with the sulfur biogeochemistry of the ocean.

Taxonomy and functional interactions in upper and bottom waters of an oligotrophic high-mountain deep lake (Redon, Pyrenees) unveiled by microbial metagenomics

High mountain lakes are, in general, highly sensitive systems to external forcing and good sentinels of global environmental changes. For a better understanding of internal lake processes, we examined microbial biodiversity and potential biogeochemical interactions in the oligotrophic deep high-mountain Lake Redon (Pyrenees, 2240 m altitude) using shotgun metagenomics. We analyzed the two ends of the range of environmental conditions found in Lake Redon, at 2 and 60 m depths. Bacteria were the most abundant component of the metagenomic reads (>90%) and the diversity indices of both taxonomic (16S and 18S rRNA) and functional (carbon-, nitrogen-, sulfur-, and phosphorous-cycling) related genes were higher in the bottom dark layer than in the upper compartment. A marked segregation was observed both in biodiversity and in the dominant energy and biomass generating pathways between the extremes. The aerobic respiration was mainly dominated by heterotrophic Burkholderiales at the top and Actinobacteria and Burkholderiales at the lake bottom. The potential for an active nitrogen cycle (nitrogen fixation, nitrification, nitrite oxidation, and nitrate reduction) was mainly found at 60 m, and potential for methanogenesis, anaerobic ammonia oxidation and dissimilatory sulfur pathways were only observed there. Some unexpected and mostly unseen energy and biomass pathways were found relevant for the biogeochemical cycling in lake Redon, i.e., those related to carbon monoxide oxidation and phosphonates processing. We provide a general scheme of the main biogeochemical processes that may operate in the sentinel deep Lake Redon. This framework may help for a better understanding of the whole lake metabolism.

Comparative metatranscriptome analysis revealed broad response of microbial communities in two soil types, agriculture versus organic soil

BACKGROUND

Studying expression of genes by direct sequencing and analysis of metatranscriptomes at a particular time and space can disclose structural and functional insights about microbial communities. The present study reports comparative analysis of metatranscriptome from two distinct soil ecosystems referred as M1 (agriculture soil) and O1 (organic soil).

RESULTS

Analysis of sequencing reads revealed Proteobacteria as major dominant phyla in both soil types. The order of the top 3 abundant phyla in M1 sample was Proteobacteria > Ascomycota > Firmicutes, whereas in sample O1, the order was Proteobacteria > Cyanobacteria > Actinobacteria. Analysis of differentially expressed genes demonstrated high expression of transcripts related to copper-binding proteins, proteins involved in electron carrier activity, DNA integration, endonuclease activity, MFS transportation, and other uncharacterized proteins in M1 compared to O1. Of the particular interests, several transcripts related to nitrification, ammonification, stress response, and alternate carbon fixation pathways were highly expressed in M1. In-depth analysis of the sequencing data revealed that transcripts of archaeal origin had high expression in M1 compared to O1 indicating the active role of Archaea in metal- and pesticide-contaminated environment. In addition, transcripts encoding 4-hydroxyphenylpyruvate dioxygenase, glyoxalase/bleomycin resistance protein/dioxygenase, metapyrocatechase, and ring hydroxylating dioxygenases of aromatic hydrocarbon degradation pathways had high expression in M1. Altogether, this study provided important insights about the transcripts and pathways upregulating in the presence of pesticides and herbicides.

CONCLUSION

Altogether, this study claims a high expression of microbial transcripts in two ecosystems with a wide range of functions. It further provided clue about several molecular markers which could be a strong indicator of metal and pesticide contamination in soils. Interestingly, our study revealed that Archaea are playing a significant role in nitrification process as compared to bacteria in metal- and pesticide-contaminated soil. In particular, high expression of transcripts related to aromatic hydrocarbon degradation in M1 soil indicates their important role in biodegradation of pollutants, and therefore, further investigation is needed.

Coastal Ocean Metagenomes and Curated Metagenome-Assembled Genomes from Marsh Landing, Sapelo Island (Georgia, USA)

Microbes play a dominant role in the biogeochemistry of coastal waters, which receive organic matter from diverse sources. We present metagenomes and 45 metagenome-assembled genomes (MAGs) from Sapelo Island, Georgia, to further understand coastal microbial populations. Notably, four MAGs are archaea, with two Thaumarchaeota and two marine group II Euryarchaeota.

Silicon limitation facilitates virus infection and mortality of marine diatoms

Diatoms are among the most globally distributed and ecologically successful organisms in the modern ocean, contributing upwards of 40% of total marine primary productivity^1,2. By converting dissolved silicon into biogenic silica, and photosynthetically fixing carbon dioxide into particulate organic carbon, diatoms effectively couple the silicon (Si) and carbon cycles and ballast substantial vertical flux of carbon out of the euphotic zone into the mesopelagic and deep ocean^3-5. Viruses are key players in ocean biogeochemical cycles^6,7, yet little is known about how viral infection specifically impacts diatom populations. Here, we show that Si limitation facilitates virus infection and mortality in diatoms in the highly productive coastal waters of the California Current Ecosystem. Using metatranscriptomic analysis of cell-associated diatom viruses and targeted quantification of extracellular viruses, we found a link between Si stress and the early, active and lytic stages of viral infection. This relationship was also observed in cultures of the bloom-forming diatom Chaetoceros tenuissimus, where Si stress accelerated virus-induced mortality. Together, these findings contextualize viruses within the ecophysiological framework of Si availability and diatom-mediated biogeochemical cycling.

Microbial Networks in SPRING - Semi-parametric Rank-Based Correlation and Partial Correlation Estimation for Quantitative Microbiome Data

High-throughput microbial sequencing techniques, such as targeted amplicon-based and metagenomic profiling, provide low-cost genomic survey data of microbial communities in their natural environment, ranging from marine ecosystems to host-associated habitats. While standard microbiome profiling data can provide sparse relative abundances of operational taxonomic units or genes, recent advances in experimental protocols give a more quantitative picture of microbial communities by pairing sequencing-based techniques with orthogonal measurements of microbial cell counts from the same sample. These tandem measurements provide absolute microbial count data albeit with a large excess of zeros due to limited sequencing depth. In this contribution we consider the fundamental statistical problem of estimating correlations and partial correlations from such quantitative microbiome data. To this end, we propose a semi-parametric rank-based approach to correlation estimation that can naturally deal with the excess zeros in the data. Combining this estimator with sparse graphical modeling techniques leads to the Semi-Parametric Rank-based approach for INference in Graphical model (SPRING). SPRING enables inference of statistical microbial association networks from quantitative microbiome data which can serve as high-level statistical summary of the underlying microbial ecosystem and can provide testable hypotheses for functional species-species interactions. Due to the absence of verified microbial associations we also introduce a novel quantitative microbiome data generation mechanism which mimics empirical marginal distributions of measured count data while simultaneously allowing user-specified dependencies among the variables. SPRING shows superior network recovery performance on a wide range of realistic benchmark problems with varying network topologies and is robust to misspecifications of the total cell count estimate. To highlight SPRING's broad applicability we infer taxon-taxon associations from the American Gut Project data and genus-genus associations from a recent quantitative gut microbiome dataset. We believe that, as quantitative microbiome profiling data will become increasingly available, the semi-parametric estimators for correlation and partial correlation estimation introduced here provide an important tool for reliable statistical analysis of quantitative microbiome data.

Microbial responses to anthropogenic dissolved organic carbon in the Arctic and Antarctic coastal seawaters

Thousands of semi-volatile hydrophobic organic pollutants (OPs) reach open oceans through atmospheric deposition, causing a chronic and ubiquitous pollution by anthropogenic dissolved organic carbon (ADOC). Hydrophobic ADOC accumulates in cellular lipids, inducing harmful effects on marine biota, and can be partially prone to microbial degradation. Unfortunately, their possible effects on microorganisms, key drivers of global biogeochemical cycles, remain unknown. We challenged coastal microbial communities from Ny-Ålesund (Arctic) and Livingston Island (Antarctica) with ADOC concentrations within the range of oceanic concentrations in 24 h. ADOC addition elicited clear transcriptional responses in multiple microbial heterotrophic metabolisms in ubiquitous groups such as Flavobacteriia, Gammaproteobacteria and SAR11. Importantly, a suite of cellular adaptations and detoxifying mechanisms, including remodelling of membrane lipids and transporters, was detected. ADOC exposure also changed the composition of microbial communities, through stimulation of rare biosphere taxa. Many of these taxa belong to recognized OPs degraders. This work shows that ADOC at environmentally relevant concentrations substantially influences marine microbial communities. Given that emissions of organic pollutants are growing during the Anthropocene, the results shown here suggest an increasing influence of ADOC on the structure of microbial communities and the biogeochemical cycles regulated by marine microbes.

Metatranscriptomic exploration of microbial functioning in clouds

Clouds constitute the uppermost layer of the biosphere. They host diverse communities whose functioning remains obscure, although biological activity potentially participates to atmospheric chemical and physical processes. In order to gain information on the metabolic functioning of microbial communities in clouds, we conducted coordinated metagenomics/metatranscriptomics profiling of cloud water microbial communities. Samples were collected from a high altitude atmospheric station in France and examined for biological content after untargeted amplification of nucleic acids. Living microorganisms, essentially bacteria, maintained transcriptional and translational activities and expressed many known complementary physiological responses intended to fight oxidants, osmotic variations and cold. These included activities of oxidant detoxification and regulation, synthesis of osmoprotectants/cryoprotectants, modifications of membranes, iron uptake. Consistently these energy-demanding processes were fueled by central metabolic routes involved in oxidative stress response and redox homeostasis management, such as pentose phosphate and glyoxylate pathways. Elevated binding and transmembrane ion transports demonstrated important interactions between cells and their cloud droplet chemical environments. In addition, polysaccharides, potentially beneficial for survival like exopolysaccharides, biosurfactants and adhesins, were synthesized. Our results support a biological influence on cloud physical and chemical processes, acting notably on the oxidant capacity, iron speciation and availability, amino-acids distribution and carbon and nitrogen fates.

From proteins to polysaccharides: lifestyle and genetic evolution of Coprothermobacter proteolyticus

Microbial communities that degrade lignocellulosic biomass are typified by high levels of species- and strain-level complexity, as well as synergistic interactions between both cellulolytic and non-cellulolytic microorganisms. Coprothermobacter proteolyticus frequently dominates thermophilic, lignocellulose-degrading communities with wide geographical distribution, which is in contrast to reports that it ferments proteinaceous substrates and is incapable of polysaccharide hydrolysis. Here we deconvolute a highly efficient cellulose-degrading consortium (SEM1b) that is co-dominated by Clostridium (Ruminiclostridium) thermocellum and multiple heterogenic strains affiliated to C. proteolyticus. Metagenomic analysis of SEM1b recovered metagenome-assembled genomes (MAGs) for each constituent population, whereas in parallel two novel strains of C. proteolyticus were successfully isolated and sequenced. Annotation of all C. proteolyticus genotypes (two strains and one MAG) revealed their genetic acquisition of carbohydrate-active enzymes (CAZymes), presumably derived from horizontal gene transfer (HGT) events involving polysaccharide-degrading Firmicutes or Thermotogae-affiliated populations that are historically co-located. HGT material included a saccharolytic operon, from which a CAZyme was biochemically characterized and demonstrated hydrolysis of multiple hemicellulose polysaccharides. Finally, temporal genome-resolved metatranscriptomic analysis of SEM1b revealed expression of C. proteolyticus CAZymes at different SEM1b life stages as well as co-expression of CAZymes from multiple SEM1b populations, inferring deeper microbial interactions that are dedicated toward community degradation of cellulose and hemicellulose. We show that C. proteolyticus, a ubiquitous population, consists of closely related strains that have adapted via HGT to presumably degrade both oligo- and longer polysaccharides present in decaying plants and microbial cell walls, thus explaining its dominance in thermophilic anaerobic digesters on a global scale.

Towards Quantitative Microbiome Community Profiling Using Internal Standards

An inherent issue in high-throughput rRNA gene tag sequencing microbiome surveys is that they provide compositional data in relative abundances. This often leads to spurious correlations, making the interpretation of relationships to biogeochemical rates challenging. To overcome this issue, we quantitatively estimated the abundance of microorganisms by spiking in known amounts of internal DNA standards. Using a 3-year sample set of diverse microbial communities from the Western Antarctica Peninsula, we demonstrated that the internal standard method yielded community profiles and taxon cooccurrence patterns substantially different from those derived using relative abundances. We found that the method provided results consistent with the traditional CHEMTAX analysis of pigments and total bacterial counts by flow cytometry. Using the internal standard method, we also showed that chloroplast 16S rRNA gene data in microbial surveys can be used to estimate abundances of certain eukaryotic phototrophs such as cryptophytes and diatoms. In Phaeocystis, scatter in the 16S/18S rRNA gene ratio may be explained by physiological adaptation to environmental conditions. We conclude that the internal standard method, when applied to rRNA gene microbial community profiling, is quantitative and that its application will substantially improve our understanding of microbial ecosystems.IMPORTANCE High-throughput-sequencing-based marine microbiome profiling is rapidly expanding and changing how we study the oceans. Although powerful, the technique is not fully quantitative; it provides taxon counts only in relative abundances. In order to address this issue, we present a method to quantitatively estimate microbial abundances per unit volume of seawater filtered by spiking known amounts of internal DNA standards into each sample. We validated this method by comparing the calculated abundances to other independent estimates, including chemical markers (pigments) and total bacterial cell counts by flow cytometry. The internal standard approach allows us to quantitatively estimate and compare marine microbial community profiles, with important implications for linking environmental microbiomes to quantitative processes such as metabolic and biogeochemical rates.

From hairballs to hypotheses-biological insights from microbial networks

Microbial networks are an increasingly popular tool to investigate microbial community structure, as they integrate multiple types of information and may represent systems-level behaviour. Interpreting these networks is not straightforward, and the biological implications of network properties are unclear. Analysis of microbial networks allows researchers to predict hub species and species interactions. Additionally, such analyses can help identify alternative community states and niches. Here, we review factors that can result in spurious predictions and address emergent properties that may be meaningful in the context of the microbiome. We also give an overview of studies that analyse microbial networks to identify new hypotheses. Moreover, we show in a simulation how network properties are affected by tool choice and environmental factors. For example, hub species are not consistent across tools, and environmental heterogeneity induces modularity. We highlight the need for robust microbial network inference and suggest strategies to infer networks more reliably.

Transient O2 pulses direct Fe crystallinity and Fe(III)-reducer gene expression within a soil microbiome

BACKGROUND

Many environments contain redox transition zones, where transient oxygenation events can modulate anaerobic reactions that influence the cycling of iron (Fe) and carbon (C) on a global scale. In predominantly anoxic soils, this biogeochemical cycling depends on Fe mineral composition and the activity of mixed Fe(III)-reducer populations that may be altered by periodic pulses of molecular oxygen (O₂).

METHODS

We repeatedly exposed anoxic (4% H₂:96% N₂) suspensions of soil from the Luquillo Critical Zone Observatory to 1.05 × 10², 1.05 × 10³, and 1.05 × 10⁴ mmol O₂ kg^-1 soil h^-1 during pulsed oxygenation treatments. Metatranscriptomic analysis and ⁵⁷Fe Mössbauer spectroscopy were used to investigate changes in Fe(III)-reducer gene expression and Fe(III) crystallinity, respectively.

RESULTS

Slow oxygenation resulted in soil Fe-(oxyhydr)oxides of higher crystallinity (38.1 ± 1.1% of total Fe) compared to fast oxygenation (30.6 ± 1.5%, P < 0.001). Transcripts binning to the genomes of Fe(III)-reducers Anaeromyxobacter, Geobacter, and Pelosinus indicated significant differences in extracellular electron transport (e.g., multiheme cytochrome c, multicopper oxidase, and type-IV pilin gene expression), adhesion/contact (e.g., S-layer, adhesin, and flagellin gene expression), and selective microbial competition (e.g., bacteriocin gene expression) between the slow and fast oxygenation treatments during microbial Fe(III) reduction. These data also suggest that diverse Fe(III)-reducer functions, including cytochrome-dependent extracellular electron transport, are associated with type-III fibronectin domains. Additionally, the metatranscriptomic data indicate that Methanobacterium was significantly more active in the reduction of CO₂ to CH₄ and in the expression of class(III) signal peptide/type-IV pilin genes following repeated fast oxygenation compared to slow oxygenation.

CONCLUSIONS

This study demonstrates that specific Fe(III)-reduction mechanisms in mixed Fe(III)-reducer populations are uniquely sensitive to the rate of O₂ influx, likely mediated by shifts in soil Fe(III)-(oxyhydr)oxide crystallinity. Overall, we provide evidence that transient oxygenation events play an important role in directing anaerobic pathways within soil microbiomes, which is expected to alter Fe and C cycling in redox-dynamic environments.

Wastewater treatment plant resistomes are shaped by bacterial composition, genetic exchange, and upregulated expression in the effluent microbiomes

Wastewater treatment plants (WWTPs) are implicated as hotspots for the dissemination of antibacterial resistance into the environment. However, the in situ processes governing removal, persistence, and evolution of resistance genes during wastewater treatment remain poorly understood. Here, we used quantitative metagenomic and metatranscriptomic approaches to achieve a broad-spectrum view of the flow and expression of genes related to antibacterial resistance to over 20 classes of antibiotics, 65 biocides, and 22 metals. All compartments of 12 WWTPs share persistent resistance genes with detectable transcriptional activities that were comparatively higher in the secondary effluent, where mobility genes also show higher relative abundance and expression ratios. The richness and abundance of resistance genes vary greatly across metagenomes from different treatment compartments, and their relative and absolute abundances correlate with bacterial community composition and biomass concentration. No strong drivers of resistome composition could be identified among the chemical stressors analyzed, although the sub-inhibitory concentration (hundreds of ng/L) of macrolide antibiotics in wastewater correlates with macrolide and vancomycin resistance genes. Contig-based analysis shows considerable co-localization between resistance and mobility genes and implies a history of substantial horizontal resistance transfer involving human bacterial pathogens. Based on these findings, we propose future inclusion of mobility incidence (M%) and host pathogenicity of antibiotic resistance genes in their quantitative health risk ranking models with an ultimate goal to assess the biological significance of wastewater resistomes with regard to disease control in humans or domestic livestock.

Identifying labile DOM components in a coastal ocean through depleted bacterial transcripts and chemical signals

Understanding which compounds comprising the complex and dynamic marine dissolved organic matter (DOM) pool are important in supporting heterotrophic bacterial production remains a major challenge. We eliminated sources of labile phytoplankton products, advected terrestrial material and photodegradation products to coastal microbial communities by enclosing water samples in situ for 24 h in the dark. Bacterial genes for which expression decreased between the beginning and end of the incubation and chemical formulae that were depleted over this same time frame were used as indicators of bioavailable compounds, an approach that avoids augmenting or modifying the natural DOM pool. Transport- and metabolism-related genes whose relative expression decreased implicated osmolytes, carboxylic acids, fatty acids, sugars and organic sulfur compounds as candidate bioreactive molecules. FT-ICR MS analysis of depleted molecular formulae implicated functional groups ~ 30-40 Da in size cleaved from semi-polar components of DOM as bioreactive components. Both gene expression and FT-ICR MS analyses indicated higher lability of compounds with sulfur and nitrogen heteroatoms. Untargeted methodologies able to integrate biological and chemical perspectives can be effective strategies for characterizing the labile microbial metabolites participating in carbon flux.