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Arctic permafrost is thawing due to global warming, with unknown consequences on the microbial inhabitants or associated viruses. DNA viruses have previously been shown to be abundant and active in thawing permafrost, but little is known about RNA viruses in these systems. To address this knowledge gap, we assessed the composition of RNA viruses in thawed permafrost samples that were incubated for 97 days at 4°C to simulate thaw conditions. A diverse RNA viral community was assembled from metatranscriptome data including double-stranded RNA viruses, dominated by

Soil fungi facilitate the translocation of inorganic nutrients from soil minerals to other microorganisms and plants. This ability is particularly advantageous in impoverished soils because fungal mycelial networks can bridge otherwise spatially disconnected and inaccessible nutrient hot spots. However, the molecular mechanisms underlying fungal mineral weathering and transport through soil remains poorly understood primarily due to the lack of a platform for spatially resolved analysis of biotic-driven mineral weathering. Here, we addressed this knowledge gap by demonstrating a mineral-doped soil micromodel platform where mineral weathering mechanisms can be studied. We directly visualize acquisition and transport of inorganic nutrients from minerals through fungal hyphae in the micromodel using a multimodal imaging approach. We found that Fusarium sp. strain DS 682, a representative of common saprotrophic soil fungus, exhibited a mechanosensory response (thigmotropism) around obstacles and through pore spaces (~12 μm) in the presence of minerals. The fungus incorporated and translocated potassium (K) from K-rich mineral interfaces, as evidenced by visualization of mineral-derived nutrient transport and unique K chemical moieties following fungus-induced mineral weathering. Specific membrane transport proteins were expressed in the fungus in the presence of minerals, including those involved in oxidative phosphorylation pathways and the transmembrane transport of small-molecular-weight organic acids. This study establishes the significance of a spatial visualization platform for investigating microbial induced mineral weathering at microbially relevant scales. Moreover, we demonstrate the importance of fungal biology and nutrient translocation in maintaining fungal growth under water and carbon limitations in a reduced-complexity soil-like microenvironment.

Soil microorganisms provide key ecological functions that often rely on metabolic interactions between individual populations of the soil microbiome. To better understand these interactions and community processes, we used chitin, a major carbon and nitrogen source in soil, as a test substrate to investigate microbial interactions during its decomposition. Chitin was applied to a model soil consortium that we developed, "model soil consortium-2" (MSC-2), consisting of eight members of diverse phyla and including both chitin degraders and nondegraders. A multiomics approach revealed how MSC-2 community-level processes during chitin decomposition differ from monocultures of the constituent species. Emergent properties of both species and the community were found, including changes in the chitin degradation potential of

Metabolites have essential roles in microbial communities, including as mediators of nutrient and energy exchange, cell-to-cell communication, and antibiosis. However, detecting and quantifying metabolites and other chemicals in samples having extremes in salt or mineral content using liquid chromatography-mass spectrometry (LC-MS)-based methods remains a significant challenge. Here, we report a facile method based on in situ chemical derivatization followed by extraction for analysis of metabolites and other chemicals in hypersaline samples, enabling for the first time direct LC-MS-based exometabolomics analysis in sample matrices containing up to 2 M total dissolved salts. The method, MetFish, is applicable to molecules containing amine, carboxylic acid, carbonyl, or hydroxyl functional groups, and it can be integrated into either targeted or untargeted analysis pipelines. In targeted analyses, MetFish provided limits of quantification as low as 1 nM, broad linear dynamic ranges (up to 5 to 6 orders of magnitude) with excellent linearity, and low median interday reproducibility (e.g., 2.6%). MetFish was successfully applied in targeted and untargeted exometabolomics analyses of microbial consortia, quantifying amino acid dynamics in the exometabolome during community succession; in situ in a native prairie soil, whose exometabolome was isolated using a hypersaline extraction; and in input and produced fluids from a hydraulically fractured well, identifying dramatic changes in the exometabolome over time in the well. IMPORTANCE The identification and accurate quantification of metabolites using electrospray ionization-mass spectrometry (ESI-MS) in hypersaline samples is a challenge due to matrix effects. Clean-up and desalting strategies that typically work well for samples with lower salt concentrations are often ineffective in hypersaline samples. To address this gap, we developed and demonstrated a simple yet sensitive and accurate method—MetFish—using chemical derivatization to enable mass spectrometry-based metabolomics in a variety of hypersaline samples from varied ecosystems and containing up to 2 M dissolved salts.

How soil is managed, particularly for agriculture, exerts stresses upon soil microbiomes, resulting in altered community structures and functional states. Understanding how soil microbiomes respond to combined stresses is important for predicting system performance under different land use scenarios, aids in identification of the most environmentally benign managements, and provides insight into how system function can be recovered in degraded soils. We use a long-established field experiment to study the effects of combined chronic (press) disturbance of the magnitude of organic carbon inputs with acute (pulse) effects of physical disturbance by tillage and chemical disturbance due to inorganic fertilization and pesticide application. We show that because of the variety of ways it can be assessed, biodiversity—here based on microbial small subunit rRNA gene phylotypes—does not provide a consistent view of community change. In contrast, aggregated traits associated with soil microbiomes indicate general loss of function, measured as a reduction of average genome lengths, associated with chronic reduction of organic inputs in arable or bare fallow soils and altered growth strategies associated with rRNA operon copy number in prokaryotes, as well as a switch to pathogenicity in fungal communities. In addition, pulse disturbance by soil tillage is associated with an increased influence of stochastic processes upon prokaryote community assembly, but fungicide used in arable soils results in niche assembly of fungal communities compared to untilled grassland. Overall, bacteria, archaea, and fungi do not share a common response to land management change, and estimates of biodiversity do not capture important facets of community adaptation to stresses adequately. IMPORTANCE Changes in soil microbiome diversity and function brought about by land management are predicted to influence a range of environmental services provided by soil, including provision of food and clean water. However, opportunities to compare the long-term effects of combinations of stresses imposed by different management approaches are limited. We exploit a globally unique 50-year field experiment, demonstrating that soil management practices alter microbiome diversity, community traits, and assembly. Grassland soil microbiomes are dominated by fewer—but phylogenetically more diverse—prokaryote phylotypes which sustain larger genomes than microbiomes in arable or bare fallow soil maintained free of plants. Dominant fungi in grassland soils are less phylogenetically diverse than those in arable or fallow soils. Soil tillage increases stochastic processes in microbiome assembly: this, combined with reduced plant biomass, presents opportunities for organisms with a capacity for pathogenesis to become established in stressed soils.

Iron (Fe) availability has well-known effects on plant and microbial metabolism, but its effects on interspecies interactions are poorly understood. The purpose of this study was to investigate metabolite exchange between the grass Brachypodium distachyon strain Bd21 and the soil bacterium Pseudomonas fluorescens SBW25::gfp/lux (SBW25) during Fe limitation under axenic conditions. We compared the transcriptional profiles and root exudate metabolites of B. distachyon plants grown semihydroponically with and without SBW25 inoculation and Fe amendment. Liquid chromatography-mass spectrometry analysis of the hydroponic solution revealed an increase in the abundance of the phytosiderophores mugineic acid and deoxymugineic acid under Fe-limited conditions compared to Fe-replete conditions, indicating greater secretion by roots presumably to facilitate Fe uptake. In SBW25-inoculated roots, expression of genes encoding phytosiderophore biosynthesis and uptake proteins increased compared to that in sterile roots, but external phytosiderophore abundances decreased. P. fluorescens siderophores were not detected in treatments without Fe. Rather, expression of SBW25 genes encoding a porin, a transporter, and a monooxygenase was significantly upregulated in response to Fe deprivation. Collectively, these results suggest that SBW25 consumed root-exuded phytosiderophores in response to Fe deficiency, and we propose target genes that may be involved. SBW25 also altered the expression of root genes encoding defense-related enzymes and regulators, including thionin and cyanogenic glycoside production, chitinase, and peroxidase activity, and transcription factors. Our findings provide insights into the molecular bases for the stress response and metabolite exchange of interacting plants and bacteria under Fe-deficient conditions. IMPORTANCE Rhizosphere bacteria influence the growth of their host plant by consuming and producing metabolites, nutrients, and antibiotic compounds within the root system that affect plant metabolism. Under Fe-limited growth conditions, different plant and microbial species have distinct Fe acquisition strategies, often involving the secretion of strong Fe-binding chelators that scavenge Fe and facilitate uptake. Here, we studied interactions between P. fluorescens SBW25, a plant-colonizing bacterium that produces siderophores with antifungal properties, and B. distachyon, a genetic model for cereal grain and biofuel grasses. Under controlled growth conditions, bacterial siderophore production was inhibited in the root system of Fe-deficient plants, bacterial inoculation altered transcription of genes involved in defense and stress response in the roots of B. distachyon, and SBW25 degraded phytosiderophores secreted by the host plant. These findings provide mechanistic insight into interactions that may play a role in rhizosphere dynamics and plant health in soils with low Fe solubility.

Rhizosphere bacteria influence the growth of their host plant by consuming and producing metabolites, nutrients, and antibiotic compounds within the root system that affect plant metabolism. Under Fe-limited growth conditions, different plant and microbial species have distinct Fe acquisition strategies, often involving the secretion of strong Fe-binding chelators that scavenge Fe and facilitate uptake., Iron (Fe) availability has well-known effects on plant and microbial metabolism, but its effects on interspecies interactions are poorly understood. The purpose of this study was to investigate metabolite exchange between the grass Brachypodium distachyon strain Bd21 and the soil bacterium Pseudomonas fluorescens SBW25::gfp/lux (SBW25) during Fe limitation under axenic conditions. We compared the transcriptional profiles and root exudate metabolites of B. distachyon plants grown semihydroponically with and without SBW25 inoculation and Fe amendment. Liquid chromatography-mass spectrometry analysis of the hydroponic solution revealed an increase in the abundance of the phytosiderophores mugineic acid and deoxymugineic acid under Fe-limited conditions compared to Fe-replete conditions, indicating greater secretion by roots presumably to facilitate Fe uptake. In SBW25-inoculated roots, expression of genes encoding phytosiderophore biosynthesis and uptake proteins increased compared to that in sterile roots, but external phytosiderophore abundances decreased. P. fluorescens siderophores were not detected in treatments without Fe. Rather, expression of SBW25 genes encoding a porin, a transporter, and a monooxygenase was significantly upregulated in response to Fe deprivation. Collectively, these results suggest that SBW25 consumed root-exuded phytosiderophores in response to Fe deficiency, and we propose target genes that may be involved. SBW25 also altered the expression of root genes encoding defense-related enzymes and regulators, including thionin and cyanogenic glycoside production, chitinase, and peroxidase activity, and transcription factors. Our findings provide insights into the molecular bases for the stress response and metabolite exchange of interacting plants and bacteria under Fe-deficient conditions. IMPORTANCE Rhizosphere bacteria influence the growth of their host plant by consuming and producing metabolites, nutrients, and antibiotic compounds within the root system that affect plant metabolism. Under Fe-limited growth conditions, different plant and microbial species have distinct Fe acquisition strategies, often involving the secretion of strong Fe-binding chelators that scavenge Fe and facilitate uptake. Here, we studied interactions between P. fluorescens SBW25, a plant-colonizing bacterium that produces siderophores with antifungal properties, and B. distachyon, a genetic model for cereal grain and biofuel grasses. Under controlled growth conditions, bacterial siderophore production was inhibited in the root system of Fe-deficient plants, bacterial inoculation altered transcription of genes involved in defense and stress response in the roots of B. distachyon, and SBW25 degraded phytosiderophores secreted by the host plant. These findings provide mechanistic insight into interactions that may play a role in rhizosphere dynamics and plant health in soils with low Fe solubility.

Microbial communities are key components of the soil ecosystem. Recent advances in metagenomics and other omics capabilities have expanded our ability to characterize the composition and function of the soil microbiome. However, characterizing the spatial metabolic and morphological diversity of microbial communities remains a challenge due to the dynamic and complex nature of soil microenvironments. The SoilBox system, demonstrated in this work, simulates an ∼12-cm soil depth, similar to a typical soil core, and provides a platform that facilitates imaging the molecular and topographical landscape of soil microbial communities as a function of environmental gradients. Moreover, the nondestructive harvesting of soil microbial communities for the imaging experiments can enable simultaneous multiomics analysis throughout the depth of the SoilBox. Our results show that by correlating molecular and optical imaging data obtained using the SoilBox platform, deeper insights into the nature of specific soil microbial interactions can be achieved., Understanding the basic biology that underpins soil microbiome interactions is required to predict the metaphenomic response to environmental shifts. A significant knowledge gap remains in how such changes affect microbial community dynamics and their metabolic landscape at microbially relevant spatial scales. Using a custom-built SoilBox system, here we demonstrated changes in microbial community growth and composition in different soil environments (14%, 24%, and 34% soil moisture), contingent upon access to reservoirs of nutrient sources. The SoilBox emulates the probing depth of a common soil core and enables determination of both the spatial organization of the microbial communities and their metabolites, as shown by confocal microscopy in combination with mass spectrometry imaging (MSI). Using chitin as a nutrient source, we used the SoilBox system to observe increased adhesion of microbial biomass on chitin islands resulting in degradation of chitin into N-acetylglucosamine (NAG) and chitobiose. With matrix-assisted laser desorption/ionization (MALDI)-MSI, we also observed several phospholipid families that are functional biomarkers for microbial growth on the chitin islands. Fungal hyphal networks bridging different chitin islands over distances of 27 mm were observed only in the 14% soil moisture regime, indicating that such bridges may act as nutrient highways under drought conditions. In total, these results illustrate a system that can provide unprecedented spatial information about interactions within soil microbial communities as a function of changing environments. We anticipate that this platform will be invaluable in spatially probing specific intra- and interkingdom functional relationships of microbiomes within soil. IMPORTANCE Microbial communities are key components of the soil ecosystem. Recent advances in metagenomics and other omics capabilities have expanded our ability to characterize the composition and function of the soil microbiome. However, characterizing the spatial metabolic and morphological diversity of microbial communities remains a challenge due to the dynamic and complex nature of soil microenvironments. The SoilBox system, demonstrated in this work, simulates an ∼12-cm soil depth, similar to a typical soil core, and provides a platform that facilitates imaging the molecular and topographical landscape of soil microbial communities as a function of environmental gradients. Moreover, the nondestructive harvesting of soil microbial communities for the imaging experiments can enable simultaneous multiomics analysis throughout the depth of the SoilBox. Our results show that by correlating molecular and optical imaging data obtained using the SoilBox platform, deeper insights into the nature of specific soil microbial interactions can be achieved.

Climate change is predicted to result in increased drought extent and intensity in the highly productive, former tallgrass prairie region of the continental United States. These soils store large reserves of carbon. The decrease in soil moisture due to drought has largely unknown consequences on soil carbon cycling and other key biogeochemical cycles carried out by soil microbiomes. In this study, we found that soil drying had a significant impact on the structure and function of soil microbial communities, including shifts in expression of specific metabolic pathways, such as those leading toward production of osmoprotectant compounds. This study demonstrates the application of an untargeted multi-omics approach to decipher details of the soil microbial community’s metaphenotypic response to environmental perturbations and should be applicable to studies of other complex microbial systems as well., Climate change is causing shifts in precipitation patterns in the central grasslands of the United States, with largely unknown consequences on the collective physiological responses of the soil microbial community, i.e., the metaphenome. Here, we used an untargeted omics approach to determine the soil microbial community’s metaphenomic response to soil moisture and to define specific metabolic signatures of the response. Specifically, we aimed to develop the technical approaches and metabolic mapping framework necessary for future systematic ecological studies. We collected soil from three locations at the Konza Long-Term Ecological Research (LTER) field station in Kansas, and the soils were incubated for 15 days under dry or wet conditions and compared to field-moist controls. The microbiome response to wetting or drying was determined by 16S rRNA amplicon sequencing, metatranscriptomics, and metabolomics, and the resulting shifts in taxa, gene expression, and metabolites were assessed. Soil drying resulted in significant shifts in both the composition and function of the soil microbiome. In contrast, there were few changes following wetting. The combined metabolic and metatranscriptomic data were used to generate reaction networks to determine the metaphenomic response to soil moisture transitions. Site location was a strong determinant of the response of the soil microbiome to moisture perturbations. However, some specific metabolic pathways changed consistently across sites, including an increase in pathways and metabolites for production of sugars and other osmolytes as a response to drying. Using this approach, we demonstrate that despite the high complexity of the soil habitat, it is possible to generate insight into the effect of environmental change on the soil microbiome and its physiology and functions, thus laying the groundwork for future, targeted studies. IMPORTANCE Climate change is predicted to result in increased drought extent and intensity in the highly productive, former tallgrass prairie region of the continental United States. These soils store large reserves of carbon. The decrease in soil moisture due to drought has largely unknown consequences on soil carbon cycling and other key biogeochemical cycles carried out by soil microbiomes. In this study, we found that soil drying had a significant impact on the structure and function of soil microbial communities, including shifts in expression of specific metabolic pathways, such as those leading toward production of osmoprotectant compounds. This study demonstrates the application of an untargeted multi-omics approach to decipher details of the soil microbial community’s metaphenotypic response to environmental perturbations and should be applicable to studies of other complex microbial systems as well.

Author(s): Cristea, Ileana M; Dorrestein, Pieter C; Eisen, Jonathan A; Gilbert, Jack A; Huber, Julie A; Jansson, Janet K; Knight, Rob; Pollard, Katherine S; Raes, Jeroen; Silver, Pamela A; Webster, Nicole S; Xu, Jian

The views expressed in this Editorial do not necessarily reflect the views of this journal or of ASM. Recently, we published the first large-scale analysis of data from the Earth Microbiome Project (EMP) ([1][1], [2][2]), a truly multidisciplinary research program involving more than 500

This study elucidates how a cyanobacterial primary producer acclimates to heterotrophic partnership by modulating the expression levels of key metabolic genes. Heterotrophic bacteria can indirectly regulate the physiology of the photoautotrophic primary producers, resulting in physiological changes identified here, such as increased intracellular ROS. Some of the interactions inferred from this model system represent putative principles of metabolic coupling in phototrophic-heterotrophic partnerships., The mechanisms by which microbes interact in communities remain poorly understood. Here, we interrogated specific interactions between photoautotrophic and heterotrophic members of a model consortium to infer mechanisms that mediate metabolic coupling and acclimation to partnership. This binary consortium was composed of a cyanobacterium, Thermosynechococcus elongatus BP-1, which supported growth of an obligate aerobic heterotroph, Meiothermus ruber strain A, by providing organic carbon, O2, and reduced nitrogen. Species-resolved transcriptomic analyses were used in combination with growth and photosynthesis kinetics to infer interactions and the environmental context under which they occur. We found that the efficiency of biomass production and resistance to stress induced by high levels of dissolved O2 increased, beyond axenic performance, as a result of heterotrophic partnership. Coordinated transcriptional responses transcending both species were observed and used to infer specific interactions resulting from the synthesis and exchange of resources. The cyanobacterium responded to heterotrophic partnership by altering expression of core genes involved with photosynthesis, carbon uptake/fixation, vitamin synthesis, and scavenging of reactive oxygen species (ROS). IMPORTANCE This study elucidates how a cyanobacterial primary producer acclimates to heterotrophic partnership by modulating the expression levels of key metabolic genes. Heterotrophic bacteria can indirectly regulate the physiology of the photoautotrophic primary producers, resulting in physiological changes identified here, such as increased intracellular ROS. Some of the interactions inferred from this model system represent putative principles of metabolic coupling in phototrophic-heterotrophic partnerships.

Sequencing-based analyses of microbiomes may lead to a breakthrough in our understanding of the microbial worlds associated with humans, animals, and the environment. Such insight could further the development of innovative ecosystem management approaches for the protection of our natural resources and the design of more effective and sustainable solutions to prevent and control infectious diseases. Genome sequence information is an organism (pathogen)-independent language that can be used across sectors, space, and time. Harmonized standards, protocols, and workflows for sample processing and analysis can facilitate the generation of such actionable information. In this study, we assessed several procedures for the isolation of DNA for next-generation sequencing. Our study highlights several important aspects to consider in the design and conduct of sequence-based analysis of microbiomes. We provide a standard operating procedure for the isolation of DNA from a range of biological specimens particularly relevant in clinical diagnostics and epidemiology., Explorations of complex microbiomes using genomics greatly enhance our understanding about their diversity, biogeography, and function. The isolation of DNA from microbiome specimens is a key prerequisite for such examinations, but challenges remain in obtaining sufficient DNA quantities required for certain sequencing approaches, achieving accurate genomic inference of microbiome composition, and facilitating comparability of findings across specimen types and sequencing projects. These aspects are particularly relevant for the genomics-based global surveillance of infectious agents and antimicrobial resistance from different reservoirs. Here, we compare in a stepwise approach a total of eight commercially available DNA extraction kits and 16 procedures based on these for three specimen types (human feces, pig feces, and hospital sewage). We assess DNA extraction using spike-in controls and different types of beads for bead beating, facilitating cell lysis. We evaluate DNA concentration, purity, and stability and microbial community composition using 16S rRNA gene sequencing and for selected samples using shotgun metagenomic sequencing. Our results suggest that inferred community composition was dependent on inherent specimen properties as well as DNA extraction method. We further show that bead beating or enzymatic treatment can increase the extraction of DNA from Gram-positive bacteria. Final DNA quantities could be increased by isolating DNA from a larger volume of cell lysate than that in standard protocols. Based on this insight, we designed an improved DNA isolation procedure optimized for microbiome genomics that can be used for the three examined specimen types and potentially also for other biological specimens. A standard operating procedure is available from https://dx.doi.org/10.6084/m9.figshare.3475406. IMPORTANCE Sequencing-based analyses of microbiomes may lead to a breakthrough in our understanding of the microbial worlds associated with humans, animals, and the environment. Such insight could further the development of innovative ecosystem management approaches for the protection of our natural resources and the design of more effective and sustainable solutions to prevent and control infectious diseases. Genome sequence information is an organism (pathogen)-independent language that can be used across sectors, space, and time. Harmonized standards, protocols, and workflows for sample processing and analysis can facilitate the generation of such actionable information. In this study, we assessed several procedures for the isolation of DNA for next-generation sequencing. Our study highlights several important aspects to consider in the design and conduct of sequence-based analysis of microbiomes. We provide a standard operating procedure for the isolation of DNA from a range of biological specimens particularly relevant in clinical diagnostics and epidemiology.

Soil microorganisms carry out key processes for life on our planet, including cycling of carbon and other nutrients and supporting growth of plants. However, there is poor molecular-level understanding of their functional roles in ecosystem stability and responses to environmental perturbations. This knowledge gap is largely due to the difficulty in culturing the majority of soil microbes. Thus, use of culture-independent approaches, such as metagenomics, promises the direct assessment of the functional potential of soil microbiomes. Soil is, however, a challenge for metagenomic assembly due to its high microbial diversity and variable evenness, resulting in low coverage and uneven sampling of microbial genomes. Despite increasingly large soil metagenome data volumes (>200 Gbp), the majority of the data do not assemble. Here, we used the cutting-edge approach of synthetic long-read sequencing technology (Moleculo) to assemble soil metagenome sequence data into long contigs and used the assemblies for binning of genomes., Soil metagenomics has been touted as the “grand challenge” for metagenomics, as the high microbial diversity and spatial heterogeneity of soils make them unamenable to current assembly platforms. Here, we aimed to improve soil metagenomic sequence assembly by applying the Moleculo synthetic long-read sequencing technology. In total, we obtained 267 Gbp of raw sequence data from a native prairie soil; these data included 109.7 Gbp of short-read data (~100 bp) from the Joint Genome Institute (JGI), an additional 87.7 Gbp of rapid-mode read data (~250 bp), plus 69.6 Gbp (>1.5 kbp) from Moleculo sequencing. The Moleculo data alone yielded over 5,600 reads of >10 kbp in length, and over 95% of the unassembled reads mapped to contigs of >1.5 kbp. Hybrid assembly of all data resulted in more than 10,000 contigs over 10 kbp in length. We mapped three replicate metatranscriptomes derived from the same parent soil to the Moleculo subassembly and found that 95% of the predicted genes, based on their assignments to Enzyme Commission (EC) numbers, were expressed. The Moleculo subassembly also enabled binning of >100 microbial genome bins. We obtained via direct binning the first complete genome, that of “Candidatus Pseudomonas sp. strain JKJ-1” from a native soil metagenome. By mapping metatranscriptome sequence reads back to the bins, we found that several bins corresponding to low-relative-abundance Acidobacteria were highly transcriptionally active, whereas bins corresponding to high-relative-abundance Verrucomicrobia were not. These results demonstrate that Moleculo sequencing provides a significant advance for resolving complex soil microbial communities. IMPORTANCE Soil microorganisms carry out key processes for life on our planet, including cycling of carbon and other nutrients and supporting growth of plants. However, there is poor molecular-level understanding of their functional roles in ecosystem stability and responses to environmental perturbations. This knowledge gap is largely due to the difficulty in culturing the majority of soil microbes. Thus, use of culture-independent approaches, such as metagenomics, promises the direct assessment of the functional potential of soil microbiomes. Soil is, however, a challenge for metagenomic assembly due to its high microbial diversity and variable evenness, resulting in low coverage and uneven sampling of microbial genomes. Despite increasingly large soil metagenome data volumes (>200 Gbp), the majority of the data do not assemble. Here, we used the cutting-edge approach of synthetic long-read sequencing technology (Moleculo) to assemble soil metagenome sequence data into long contigs and used the assemblies for binning of genomes. Author Video: An author video summary of this article is available.

Studies characterizing both the taxonomic composition and metabolic profile of various microbial communities are becoming increasingly common, yet new computational methods are needed to integrate and interpret these data in terms of known biological mechanisms. Here, we introduce an analytical framework to link species composition and metabolite measurements, using a simple model to predict the effects of community ecology on metabolite concentrations and evaluating whether these predictions agree with measured metabolomic profiles. We find that a surprisingly large proportion of metabolite variation in the vaginal microbiome can be predicted based on species composition (including dramatic shifts associated with disease), identify putative mechanisms underlying these predictions, and evaluate the roles of individual bacterial species and genes. Analysis of gut microbiome data using this framework recovers similar community metabolic trends. This framework lays the foundation for model-based multi-omic integrative studies, ultimately improving our understanding of microbial community metabolism., Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites’ abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in health and disease. IMPORTANCE Studies characterizing both the taxonomic composition and metabolic profile of various microbial communities are becoming increasingly common, yet new computational methods are needed to integrate and interpret these data in terms of known biological mechanisms. Here, we introduce an analytical framework to link species composition and metabolite measurements, using a simple model to predict the effects of community ecology on metabolite concentrations and evaluating whether these predictions agree with measured metabolomic profiles. We find that a surprisingly large proportion of metabolite variation in the vaginal microbiome can be predicted based on species composition (including dramatic shifts associated with disease), identify putative mechanisms underlying these predictions, and evaluate the roles of individual bacterial species and genes. Analysis of gut microbiome data using this framework recovers similar community metabolic trends. This framework lays the foundation for model-based multi-omic integrative studies, ultimately improving our understanding of microbial community metabolism.

Marine plastic debris is a growing concern that has captured the general public’s attention. While the negative impacts of plastic debris on oceanic macrobiota, including mammals and birds, are well documented, little is known about its influence on smaller marine residents, including microbes that have key roles in ocean biogeochemistry. Our work provides a new perspective on microbial communities inhabiting microplastics that includes its effect on microbial biogeochemical activities and a description of the cross-domain communities inhabiting plastic particles. This study is among the first molecular ecology, plastic debris biota surveys in the North Pacific Subtropical Gyre. It has identified fundamental differences in the functional potential and taxonomic composition of plastic-associated microbes versus planktonic microbes found in the surrounding open-ocean habitat., Marine plastic debris has become a significant concern in ocean ecosystems worldwide. Little is known, however, about its influence on microbial community structure and function. In 2008, we surveyed microbial communities and metabolic activities in seawater and on plastic on an oceanographic expedition through the “great Pacific garbage patch.” The concentration of plastic particles in surface seawater within different size classes (2 to 5 mm and >5 mm) ranged from 0.35 to 3.7 particles m−3 across sampling stations. These densities and the particle size distribution were consistent with previous values reported in the North Pacific Ocean. Net community oxygen production (NCP = gross primary production − community respiration) on plastic debris was positive and so net autotrophic, whereas NCP in bulk seawater was close to zero. Scanning electron microscopy and metagenomic sequencing of plastic-attached communities revealed the dominance of a few metazoan taxa and a diverse assemblage of photoautotrophic and heterotrophic protists and bacteria. Bryozoa, Cyanobacteria, Alphaproteobacteria, and Bacteroidetes dominated all plastic particles, regardless of particle size. Bacteria inhabiting plastic were taxonomically distinct from the surrounding picoplankton and appeared well adapted to a surface-associated lifestyle. Genes with significantly higher abundances among plastic-attached bacteria included che genes, secretion system genes, and nifH genes, suggesting enrichment for chemotaxis, frequent cell-to-cell interactions, and nitrogen fixation. In aggregate, our findings suggest that plastic debris forms a habitat for complex microbial assemblages that have lifestyles, metabolic pathways, and biogeochemical activities that are distinct from those of free-living planktonic microbial communities. IMPORTANCE Marine plastic debris is a growing concern that has captured the general public’s attention. While the negative impacts of plastic debris on oceanic macrobiota, including mammals and birds, are well documented, little is known about its influence on smaller marine residents, including microbes that have key roles in ocean biogeochemistry. Our work provides a new perspective on microbial communities inhabiting microplastics that includes its effect on microbial biogeochemical activities and a description of the cross-domain communities inhabiting plastic particles. This study is among the first molecular ecology, plastic debris biota surveys in the North Pacific Subtropical Gyre. It has identified fundamental differences in the functional potential and taxonomic composition of plastic-associated microbes versus planktonic microbes found in the surrounding open-ocean habitat. Author Video: An author video summary of this article is available.