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Tropical forest soils represent some of Earth's largest stores of soil carbon. Humid and warm conditions promote high primary productivity offsetting high ecosystem respiration rates, and this balance has resulted in significant carbon accumulation in plant biomass and soils. These vast carbon stocks can be destabilized under a changing climate, and model projections predict tropical and subtropical regions will experience disturbance to the hydrological cycle, with an increased likelihood of more frequent and prolonged droughts interspersed with periods of intense precipitation. Herein, we examine the functional response of belowground communities to a reduction in throughfall across a 1 m precipitation gradient (2350 to 3400 mm) spanning three sites from the Caribbean coast to the interior of Panama. At each site, 4 throughfall exclusion plots (10 x 10 m) were established to reduce precipitation, and exacerbate the natural variability in seasonal hydrological cycles. In January 2020, approximately 18 months since the inception of throughfall exclusion, each plot was sampled at six locations and two depths (0-10 and 10-20 cm). To identify the traits and mechanisms involved in responding to drought perturbation, we sequenced the microbiomes of the soil samples from the throughfall exclusion and corresponding controls at each site, and measured metabolite accumulation within the soils. Here we report on the accumulation of distinct metabolites along the precipitation gradient and under throughfall exclusion. We note that constitutive production of compatible solutes increases from the wettest to the driest site, indicative of trait selection due to climate history. However, under throughfall exclusion the gradient end members show a more muted metabolic response than the intermediate site. We discuss these responses with respect specific pathways invoked under drying stress, and soil carbon dynamics.

The incidence of esophageal adenocarcinoma (EA) has drastically increased in the United States since 1970s for unclear reasons. We hypothesized that the widespread usage of antibiotics has increased the procarcinogenic potential of the orodigestive microbiota along the sequence of gastroesophageal reflux (GR), Barrett's esophagus (BE) and EA phenotypes. This case control study included normal controls (NC) and three disease phenotypes GR, BE and EA. Microbiota in the mouth, esophagus, and stomach, and rectum were analyzed using 16S rRNA gene sequencing. Overall, we discovered 44 significant pairwise differences in abundance of microbial taxa between the four phenotypes, with 12 differences in the mouth, 21 in the esophagus, two in the stomach, and nine in the rectum. Along the GR→BE→EA sequence, oral and esophageal microbiota were more diversified, the dominant genus Streptococcus was progressively depleted while six other genera Atopobium, Actinomyces, Veillonella, Ralstonia, Burkholderia and Lautropia progressively enriched. In NC, Streptococcus appeared to control populations of other genera in the foregut via numerous negative and positive connections, while in disease states, the rich network was markedly simplified. Inferred gene functional content showed a progressive enrichment through the stages of EA development in genes encoding antibiotic resistance, ligands of Toll-like and NOD-like receptors, nitrate-nitrite-nitric oxide pathway and acetaldehyde metabolism. The orodigestive microbiota is in a progressive dysbiotic state along the GR-BE-EA sequence. The increasing dysbiosis and antibiotic and procarcinogenic genes in the disease states warrants further study to define their roles in EA pathogenesis.

Efficient biochemical transformation of belowground carbon by microorganisms plays a critical role in determining the long-term fate of soil carbon. As plants assimilate carbon from the atmosphere, up to 50% is exuded into the area surrounding growing roots, where it may be transformed into microbial biomass and subsequently stabilized through mineral associations. However, due to a hierarchy of interacting microbial traits, it remains elusive how emergent life-history strategies of microorganisms influence the processing of root exudate carbon. Here, by combining theory-based predictions of substrate uptake kinetics for soil bacteria and a new genome-informed trait-based dynamic energy budget model, we predicted life history traits and trade-offs of a broad range of soil bacteria growing on 82 root exudate metabolites. The model captured resource-dependent trade-offs between growth rate (power) and growth efficiency (yield) that are fundamental to microbial fitness in communities. During early phases of plant development, growth rates of bacteria were largely constrained by maximum growth potential, highlighting the predictive power of genomic traits during nutrient-replete soil conditions. In contrast, selection for efficiency was important later in the plant growing season, where the model successfully predicted microbial substrate preferences for aromatic organic acids and plant hormones. The predicted carbon-use efficiencies for growth on organics acids were much higher than typical values observed in soil. These predictions provide mechanistic underpinning for the apparent efficiency of the microbial route to mineral stabilization in the rhizosphere and add an additional layer of complexity to rhizosphere microbial community assembly.

Soil microorganisms have adapted to compete and exploit different metabolic niches in their physically and chemically diverse environment via evolution and acquisition of distinct physiological and biochemical traits. As the interface for most carbon and nutrient exchange between plants and microorganisms, the rhizosphere has received substantial attention. By comparison, what is commonly termed bulk-soil (soil free of living roots) represents a far greater volume and surface area throughout the season, and substantially higher taxonomic and phylogenetic diversity; the traits and activity of its inhabitants may also have a significant impact on overall soil function. We used a combination of comparative genomics and exoproteomics to identify metabolic traits of bacteria adapted to life in bulk soil and compared these with traits of bacteria living in the rhizosphere of wild oat, Avena barbata. In bulk soil bacteria, we observed: (i) greater investment in extracellular polymer-degrading enzyme production; (ii) greater potential for secretion (presence of signal peptides) of polymer-degrading enzymes; (iii) production of accessory proteins (carbohydrate binding modules) fused with glycoside hydrolases that enhance substrate affinity, stabilize, and increase reaction rates of polymer degrading enzymes; and (iv) organization of polymer degradation machinery within gene clusters that facilitate co-transcription of enzymes, transcription factors and transporters for polymer depolymerization products. Together, these findings suggest that unlike rhizosphere-adapted bacteria—which specialize on small molecules released primarily as root exudates—bulk soil-adapted bacteria have evolved to exploit plant polymers. This biochemically costly strategy may be mitigated by protein-level adaptations that enhance the efficiency of extracellular enzyme-mediated substrate acquisition.IMPORTANCEPlant-soil-microbe interactions are dynamic and complex, with significant implications for ecosystem functioning. Microbial traits, such as nutrient acquisition and growth yield, combined with soil and climate parameters, impact major biogeochemical processes and can define the future fate of soil carbon. Diverse soil microorganisms occupy different physical habitats within soil and exploit distinct niches by expressing different metabolic traits. Identifying and quantifying traits that underlie their fitness and function is key for understanding and predicting how soil carbon transformation and stabilization will change in the future or can be managed through intervention.

The frequency and intensity of environmental fluctuations play an important role in shaping microbial community composition, trait-distribution, and adaptive capacity. We hypothesize here that a communities’ climate history dictates it’s metabolic response to future perturbation under a changing climate. Such a response is significant as changes in microbial metabolism can, in turn, feedback onto metabolite exudation, the chemical structure of necromass, and the formation and stability of soil organic matter. Here we use laboratory and field experiments to examine the metabolic pathways invoked under osmotic and matric stress within semi-arid and tropical soils. For example, using non-destructive, synchrotron-based Fourier-transform infrared spectromicroscopy we profiled the stress response of phylogenetically similar bacteria isolated from soils with contrasting climate histories subjected to both matric and osmotic stress. We note a strong carbohydrate-based, metabolic response of tropical microbes that is entirely absent in semi-arid organisms. At the field scale, we use metagenomic sequencing and metabolite analysis to demonstrate how four different sites established across a 1 m precipitation gradient from the Caribbean coast to the interior of Panama respond to a 50 % reduction in throughfall. The precipitation gradient permits the development of distinct communities at each site that show clearly divergent response to imposed hydrological perturbation. Our contribution here will discuss how communities adapted to different precipitation regimes respond metabolically to drought conditions, and how these change feedback onto the structure and stability of soil organic matter.

Small genes (40,000 small-gene families in ~2.3 million phage genome contigs. We find that small genes in phage genomes are approximately 3-fold more prevalent than in host prokaryotic genomes. Our approach enriches for small genes that are translated in microbiomes, suggesting the small genes identified are coding. More than 9,000 families encode potentially secreted or transmembrane proteins, more than 5,000 families encode predicted anti-CRISPR proteins, and more than 500 families encode predicted antimicrobial proteins. By combining homology and genomic-neighborhood analyses, we reveal substantial novelty and diversity within phage biology, including small phage genes found in multiple host phyla, small genes encoding proteins that play essential roles in host infection, and small genes that share genomic neighborhoods and whose encoded proteins may share related functions.

Maize-forage grasses intercropping systems have been increasingly adopted by farmers because of their capacity to recycle nutrients, provide mulch, and add C to soil. However, grasses have been shown to increase nitrous oxide (N2O) emissions. Some tropical grasses cause biological nitrification inhibition (BNI) which could mitigate N2O emissions in the maize cycle but the reactions of the N cycle and the microbial changes that explain the N2O emissions are little known in such intercropping systems. With this in mind, we explored intercropping of forage grasses (Brachiaria brizantha and Brachiaria humidicola) with distinct BNI and yield potential to increase N cycling in no-till maize production systems compared to monocrop with two N rates (0 and 150 kg ha−1) applied during the maize season. These grasses did not strongly compete with maize during the period of maize cycle and did not have a negative effect on grain yield. We observed a legacy of these grasses on N mineralization and nitrification through the soil microbiome during maize growth. We observed that B. humidicola, genotype with higher BNI potential, increased net N mineralization by 0.4 mg N kg−1 day−1 and potential nitrification rates by 1.86 mg NO3-N kg−1 day−1, while B. brizantha increased the soil moisture, fungi diversity, mycorrhizal fungi, and bacterial nitrifiers, and reduced saprotrophs prior to maize growth. Their legacy on soil moisture and cumulative organic inputs (i.e., grass biomass) was strongly associated with enhanced mineralization and nitrification rates at early maize season. These effects contributed to increase cumulative N2O emission by 12.8 and 4.8 mg N2O-N m−2 for maize growing after B. brizantha and B. humidicola, respectively, regardless of the N fertilization rate. Thus, the nitrification inhibition potential of tropical grasses can be outweighed by their impacts on soil moisture, N recycling, and the soil microbiome that together dictate soil N2O fluxes.

Background Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent; however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and microbial contributions to biogeochemical cycling. Results We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry studies using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the microbiome, potential microbial metabolic handoffs and metabolite exchange, reconstruction of functional networks, and determination of microbial contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, community-scale microbial functional networks using a newly defined metric “MW-score” (metabolic weight score), and metabolic Sankey diagrams. METABOLIC takes ~ 3 h with 40 CPU threads to process ~ 100 genomes and corresponding metagenomic reads within which the most compute-demanding part of hmmsearch takes ~ 45 min, while it takes ~ 5 h to complete hmmsearch for ~ 3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut. Conclusion METABOLIC enables the consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available under GPLv3 at https://github.com/AnantharamanLab/METABOLIC.

Determining the carbon sources for active microbial populations in the subsurface is a challenging but highly informative component of subsurface microbial ecology. This work developed a method to provide ecological insights into groundwater microbial communities by characterizing community RNA through its radiocarbon and ribosomal RNA (rRNA) signatures. RNA was chosen as the biomolecule of interest because rRNA constitutes the majority of RNA in prokaryotes, represents recently active organisms, and yields detailed taxonomic information. The method was applied to a groundwater filter collected from a shallow alluvial aquifer in Colorado. RNA was extracted, radiometrically dated, and the 16S rRNA was analyzed by RNA-Seq. The RNA had a radiocarbon signature (Δ14C) of −193.4 ± 5.6‰. Comparison of the RNA radiocarbon signature to those of potential carbon pools in the aquifer indicated that at least 51% of the RNA was derived from autotrophy, in close agreement with the RNA-Seq data, which documented the prevalence of autotrophic taxa, such as Thiobacillus and Gallionellaceae. Overall, this hybrid method for RNA analysis provided cultivation-independent information on the in-situ carbon sources of active subsurface microbes and reinforced the importance of autotrophy and the preferential utilization of dissolved over sedimentary organic matter in alluvial aquifers.

Beneficial microbial associations enhance the fitness of most living organisms, and wood-feeding insects offer some of the most striking examples of this. Odontotaenius disjunctus is a wood-feeding beetle that possesses a digestive tract with four main compartments, each of which contains well-differentiated microbial populations, suggesting that anatomical properties and separation of these compartments may enhance energy extraction from woody biomass. Here, using integrated chemical analyses, we demonstrate that lignocellulose deconstruction and fermentation occur sequentially across compartments, and that selection for microbial groups and their metabolic pathways is facilitated by gut anatomical features. Metaproteogenomics showed that higher oxygen concentration in the midgut drives lignocellulose depolymerization, while a thicker gut wall in the anterior hindgut reduces oxygen diffusion and favours hydrogen accumulation, facilitating fermentation, homoacetogenesis and nitrogen fixation. We demonstrate that depolymerization continues in the posterior hindgut, and that the beetle excretes an energy- and nutrient-rich product on which its offspring subsist and develop. Our results show that the establishment of beneficial microbial partners within a host requires both the acquisition of the microorganisms and the formation of specific habitats within the host to promote key microbial metabolic functions. Together, gut anatomical properties and microbial functional assembly enable lignocellulose deconstruction and colony subsistence on an extremely nutrient-poor diet.

Motivation Microbiome datasets provide rich information about microbial communities. However, vast library size variations across samples present great challenges for proper statistical comparisons. To deal with these challenges, rarefaction is often used in practice as a normalization technique, although there has been debate whether rarefaction should ever be used. Conventional wisdom and previous work suggested that rarefaction should never be used in practice, arguing that rarefying microbiome data is statistically inadmissible. These discussions, however, have been confined to particular parametric models and simulation studies. Results We develop a semiparametric graphical model framework for grouped microbiome data and analyze in the context of differential abundance testing the statistical trade-offs of the rarefaction procedure, accounting for latent variations and measurement errors. Under the framework, it can be shown rarefaction guarantees that subsequent permutation tests properly control the Type I error. In addition, the loss in sensitivity from rarefaction is solely due to increased measurement error; if the underlying variation in microbial composition is large among samples, rarefaction might not hurt subsequent statistical inference much. We develop the rarefaction efficiency index (REI) as an indicator for efficiency loss and illustrate it with a dataset on the effect of storage conditions for microbiome data. Simulation studies based on real data demonstrate that the impact of rarefaction on sensitivity is negligible when overdispersion is prominent, while low REI corresponds to scenarios in which rarefying might substantially lower the statistical power. Whether to rarefy or not ultimately depends on assumptions of the data generating process and characteristics of the data. Availability and implementation Source codes are publicly available at https://github.com/jcyhong/rarefaction. Supplementary information Supplementary data are available at Bioinformatics online.

Model projections predict that climate change impacts on the tropics will include an increased frequency of drought and precipitation cycles. Such environmental fluctuations at the soil pore-scale play an important role in shaping microbial adaptive capacity, and trait composition of a community, which feeds back on to the breakdown and formation of soil organic matter (SOM). Understanding the factors controlling the carbon balance of humid tropical forest soils remains a social imperative. Microbial feedback to SOM pools is critical. Herein, we examine the microbial response to drought perturbations across 3 different, but complementary scales. At the largest scale, we explored the impacts of drought across a 1 m precipitation gradient spanning four sites from the Caribbean coast to the interior of Panama. At each site 4, throughfall exclusion plots (10 x 10 m) were established to reduce precipitation by 50 %. In addition, 4 corresponding control plots were also constructed. At the meso-scale, we incubated intact soil cores from one of these sites (P12) under 3 different hydrological treatments (control, drought, rewetting-drying cycles) for over a 5-month period. For the field and meso-scale experiments, we evaluated changes imparted by hydrological perturbations using multi-omic approaches, and physico-chemical measurements. In order to identify the traits involved in response to drought at the field and meso-scale, we isolated a range of bacteria to subject to stress at the scale of the single-cell and simple communities. Cell extracts were subjected to osmotic or matric stress and the short-term physiological responses determined using non-destructive synchrotron radiation-based Fourier Transform-Infrared spectromicroscopy. Through this approach, we identified changes in metabolic allocation within different cells, in particular to the secondary metabolome of the different bacteria. Our contribution will discuss the outcomes of these multi-scale experiments. Specifically focusing on how shifts in the microbial community and physiological changes may influence tropical soil carbon stability under future scenarios of altered drought and precipitation cycles.

Summary Remote sensing capabilities have revolutionized several fields including geology and vegetation ecology. With these new capabilities to observe important interactions between subsurface hydrobiogeochemical properties and surface biological response, there is vast potential to rigorously test theories of ecosystem function and evolution. For example, the functional trait distributions of plants can be quantified at increasingly broader scales allowing ecological theories to be tested across plots to watersheds and beyond. Geophysical methods now allow us to interrogate how regolith properties vary across the same scales and provide an insight into the factors regulating plant species composition and functional trait distributions. Given the fundamental constraints of water, energy and nutrients are shared across biology, and that plants and microorganisms share a long history of coevolution, it is likely that microbial functional traits distributions follow similarly interpretable and predictable patterns at ecosystem scales. In this presentation I will cover our work combining theory, observation and modeling to advance how microbial traits are deciphered from genomic information, as well as approaches to ground truth these hypotheses. I will also discuss how we combine various sensing approaches, including vegetation, geophysical, and microbial to evaluate patterns of co-evolution across a watershed with consequences for ecosystem hydrobiogeochemistry.

Objectives Thousands of cases of multidrug-resistant tuberculosis (TB) have been observed in the Philippines, but studies on the Mycobacterium tuberculosis (MTB) genotypes that underlie the observed drug resistance profiles are lacking. This study aimed to analyse the whole genomes of clinical MTB isolates representing various resistance profiles to identify single nucleotide polymorphisms (SNPs) in resistance-associated genes. Methods The genomes of ten MTB isolates cultured from banked sputum sources were sequenced. Bioinformatics analysis consisted of assembly, annotation and SNP identification in genes reported to be associated with resistance to isoniazid (INH), rifampicin (RIF), ethambutol (ETH), streptomycin, pyrazinamide (PZA) and fluoroquinolones (FQs). Results The draft assemblies covered an average of 97.08% of the expected genome size. Seven of the ten isolates belonged to the Indo-Oceanic lineage/EA12-Manila clade. Two isolates were classified into the Euro-American lineage, whilst the pre-XDR (pre-extensively drug-resistant) isolate was classified under the East Asian/Beijing clade. The SNPs katG Ser315Thr, rpoB Ser450Leu and embB Met306Val were found in INH- (4/7), RIF- (3/6) and ETH-resistant (2/6) isolates, respectively, but not in susceptible isolates. Mutations in the inhA promoter and in the pncA and gyrA genes known to be involved in resistance to INH, PZA and FQs, respectively, were also identified. Conclusions This study represents the first effort to investigate the whole genomes of Philippine clinical strains of MTB exhibiting various multidrug resistance profiles. Whole-genome data can provide valuable insights to the mechanistic and epidemiological qualities of TB in a high-burden setting such as the Philippines.

Due to the promiscuous exchange of genetic material and asexual reproduction, delineating microbial species (and, by extension, populations) remains challenging. Because of this, the vast majority of microbial studies assessing population structure often compare divergent strains from disparate environments under varied selective pressures. Here, we investigated the population structure within a single bacterial ecotype, a unit equivalent to a eukaryotic species, defined as highly clustered genotypic and phenotypic strains with the same ecological niche. Using a combination of genomic and computational analyses, we assessed the phylogenetic structure, extent of recombination, and flexible gene content of this genomic diversity to infer patterns of gene flow. To our knowledge, this study is the first to do so for a dominant soil bacterium. Our results indicate that bacterial soil populations, similarly to those in other environments, are structured by gene flow discontinuities and exhibit distributional patterns consistent with both isolation by distance and isolation by environment. Thus, both dispersal limitation and local environments contribute to the divergence among closely related soil bacteria as observed in macroorganisms., For free-living bacteria and archaea, the equivalent of the biological species concept does not exist, creating several obstacles to the study of the processes contributing to microbial diversification. These obstacles are particularly high in soil, where high bacterial diversity inhibits the study of closely related genotypes and therefore the factors structuring microbial populations. Here, we isolated strains within a single Curtobacterium ecotype from surface soil (leaf litter) across a regional climate gradient and investigated the phylogenetic structure, recombination, and flexible gene content of this genomic diversity to infer patterns of gene flow. Our results indicate that microbial populations are delineated by gene flow discontinuities, with distinct populations cooccurring at multiple sites. Bacterial population structure was further delineated by genomic features allowing for the identification of candidate genes possibly contributing to local adaptation. These results suggest that the genetic structure within this bacterium is maintained both by ecological specialization in localized microenvironments (isolation by environment) and by dispersal limitation between geographic locations (isolation by distance).

Young women in sub-Saharan Africa are disproportionally affected by HIV infection and unintended pregnancies. However, hormonal contraceptive (HC) use may influence HIV risk through changes in genital tract microbiota and inflammatory cytokines. To investigate this, 130 HIV negative adolescent females aged 15–19 years were enrolled into a substudy of UChoose, an open-label randomized crossover study (NCT02404038), comparing acceptability and contraceptive product preference as a proxy for HIV prevention delivery methods. Participants were randomized to injectable norethisterone enanthate (Net-En), combined oral contraceptives (COC) or etonorgesterol/ethinyl estradiol combined contraceptive vaginal ring (CCVR) for 16 weeks, then crossed over to another HC for 16 weeks. Cervicovaginal samples were collected at baseline, crossover and exit for characterization of the microbiota and measurement of cytokine levels; primary endpoints were cervical T cell activation, vaginal microbial diversity and cytokine concentrations. Adolescents randomized to COCs had lower vaginal microbial diversity and relative abundance of HIV risk-associated taxa compared to Net-En or CCVR. Cervicovaginal inflammatory cytokine concentrations were significantly higher in adolescents randomized to CCVR compared to COC and Net-En. This suggests that COC use may induce an optimal vaginal ecosystem by decreasing bacterial diversity and inflammatory taxa, while CCVR use is associated with genital inflammation., Hormonal contraception may alter women’s susceptibility to HIV. Here, the authors report the results of a randomized clinical trial substudy assessing the effects of injectable Net-En, oral contraceptives (COC) and Nuvaring on vaginal microbiota and cytokines, associating COC with lower microbial diversity and Nuvaring with increased inflammation.

BackgroundAdvances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent, however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and contributions to biogeochemical cycling.ResultsWe present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, identification of metabolism markers, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the community, potential microbial metabolic handoffs and metabolite exchange, and calculation of microbial community contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or from single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, and community-scale metabolic networks using a newly defined metric ‘MN-score’ (metabolic network score). METABOLIC takes ∼3 hours with 40 CPU threads to process ∼100 genomes and metagenomic reads within which the most compute-demanding part of hmmsearch takes ∼45 mins, while it takes ∼5 hours to complete hmmsearch for ∼3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut.ConclusionMETABOLIC enables consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available at https://github.com/AnantharamanLab/METABOLIC under GPLv3.

Background Young women in sub-Saharan Africa are at high risk for sexually transmitted infections (STIs) and often rely on hormonal contraception (HC) to prevent unwanted pregnancies. Some observational data suggest that HC might affect STI risk. We examined the impact of three HC methods on the adolescent STI incidence and BV prevalence in a randomized trial. Methods 130 adolescent females aged 15 to 19 from Cape Town were enrolled and randomized into three study arms: 1. injectable norethisterone enanthate (NET-EN), 2. combined oral contraceptives (COCs) or 3. combined contraceptive vaginal ring (CCVR) for 16 weeks. Participants then switched to a second HC for a final four months. Vaginal samples were collected at baseline, crossover and exit for STI (chlamydia, gonorrhoea, mycoplasma and trichomoniasis) and bacterial vaginosis (BV) testing by Nugent scoring. Results At baseline, the BV and STI prevalence was 44% and 42%, respectively. There were no significant differences in STI incidence between study arms at crossover, however in an according to protocol analyses, participants using COCs were significantly less likely to present with any STI than participants using either NET-EN (OR 0.22, 95% CI 0.06–0.71, p=0.017) or CCVR (OR 0.21, 95% CI 0.05–0.69, p=0.015). Specifically, participants on CCVR were more likely to be infected with N. gonorrhoea (OR 11.7, 95% CI 2.0–224, p=0.025). These associations stayed significant after adjusting for sexual risk behaviour, including condom use. There was a decreased prevalence of BV in the COC arm and an increased BV prevalence in the NET-EN and CCVR arms at crossover, but these differences were not statistically significant. Conclusion Use of COCs was associated with lower BV prevalence and STI incidence compared to NET-EN and CCVR use. Disclosure No significant relationships.

In free-living bacteria and archaea, the equivalent of the biological species concept does not exist, creating several barriers to the study of the processes contributing to microbial diversification. As such, microorganisms are often operationally defined using conserved marker genes (i.e., 16S rRNA gene) or whole-genome measurements (i.e., ANI) to interpret intra-specific processes. However, as in eukaryotes, investigations into microbial populations must consider the potential for interacting genotypes among individuals that are subjected to similar environmental selective pressures. Therefore, we isolated 26 strains within a single bacterial ecotype (equivalent to a eukaryotic species definition) from a common habitat (leaf litter) across a regional climate gradient and asked whether the genetic diversity in a free-living soil bacterium (Curtobacterium) was consistent with patterns of allopatric or sympatric differentiation. By examining patterns of gene flow, our results indicate that microbial populations are delineated by gene flow discontinuities and exhibit evidence for population-specific adaptation. We conclude that the genetic structure within this bacterium is due to both adaptation within localized microenvironments (isolation-by-environment) as well as dispersal limitation between geographic locations (isolation-by-distance).

The rhizosphere is a hotspot for microbial carbon transformations, and is the entry point for root polysaccharides and polymeric carbohydrates that are important precursors to soil organic matter (SOM). However, the ecological mechanisms that underpin rhizosphere carbohydrate depolymerization are poorly understood. Using Avena fatua, a common annual grass, we analyzed time-resolved metatranscriptomes to compare microbial functions in rhizosphere, detritusphere, and combined rhizosphere-detritusphere habitats. Transcripts were binned using a unique reference database generated from soil isolate genomes, single-cell amplified genomes, metagenomes, and stable isotope probing metagenomes. While soil habitat significantly affected both community composition and overall gene expression, the succession of microbial functions occurred at a faster time scale than compositional changes. Using hierarchical clustering of upregulated decomposition genes, we identified four distinct microbial guilds populated by taxa whose functional succession patterns suggest specialization for substrates provided by fresh growing roots, decaying root detritus, the combination of live and decaying root biomass, or aging root material. Carbohydrate depolymerization genes were consistently upregulated in the rhizosphere, and both taxonomic and functional diversity were highest in the combined rhizosphere-detritusphere, suggesting coexistence of rhizosphere guilds is facilitated by niche differentiation. Metatranscriptome-defined guilds provide a framework to model rhizosphere succession and its consequences for soil carbon cycling.

The rhizosphere is a hotspot for microbial C transformations, and the origin of root polysaccharides and polymeric carbohydrates that are important precursors to soil organic matter. However, the ecological mechanisms that underpin rhizosphere carbohydrate depolymerization are poorly understood. UsingAvena fatua, a common annual grass, we analyzed time-resolved metatranscriptomes to compare microbial function in rhizosphere, detritusphere, and combined rhizosphere-detritusphere habitats. Population transcripts were binned with a unique reference database generated from soil isolate and single amplified genomes, metagenomes, and stable isotope probing metagenomes. While soil habitat significantly affected both community composition and overall gene expression, succession of microbial functions occurred at a faster time scale than compositional changes. Using hierarchical clustering of upregulated decomposition gene expression, we identified four distinct microbial guilds populated by taxa whose functional succession patterns suggest specialization for substrates provided by fresh growing roots, decaying root detritus, the combination of live and decaying root biomass, or aging root material. Carbohydrate depolymerization genes were consistently upregulated in the rhizosphere, and both taxonomic and functional diversity were high in the combined rhizosphere-detritusphere—suggesting coexistence of rhizosphere guilds is facilitated by niche differentiation. Metatranscriptome-defined guilds provide a framework to model rhizosphere succession and its consequences for soil carbon cycling.

Metagenomic sequencing provides a window into microbial community structure and metabolic potential; however, linking these data to exogenous metabolites that microorganisms process and produce (the exometabolome) remains challenging. Previously, we observed strong exometabolite niche partitioning among bacterial isolates from biological soil crust (biocrust). Here we examine native biocrust to determine if these patterns are reproduced in the environment. Overall, most soil metabolites display the expected relationship (positive or negative correlation) with four dominant bacteria following a wetting event and across biocrust developmental stages. For metabolites that were previously found to be consumed by an isolate, 70% are negatively correlated with the abundance of the isolate’s closest matching environmental relative in situ, whereas for released metabolites, 67% were positively correlated. Our results demonstrate that metabolite profiling, shotgun sequencing and exometabolomics may be successfully integrated to functionally link microbial community structure with environmental chemistry in biocrust., Metagenomic sequencing provides a window into microbial community structure and metabolic potential. Here, Swenson et al. integrate metabolomics and shotgun sequencing to functionally link microbial community structure with environmental chemistry in biological soil crust (biocrust).

Beneficial microbial associations enhance the fitness of most living organisms, and wood-feeding insects offer some of the most striking examples of this. Odontotaenius disjunctus is a wood-feeding beetle that possesses a digestive tract with four main compartments, each of which contains well-differentiated microbial populations, suggesting that anatomical properties and separation of these compartments may enhance energy extraction from woody biomass. Here, using integrated chemical analyses, we demonstrate that lignocellulose deconstruction and fermentation occur sequentially across compartments, and that selection for microbial groups and their metabolic pathways is facilitated by gut anatomical features. Metaproteogenomics showed that higher oxygen concentration in the midgut drives lignocellulose depolymerization, while a thicker gut wall in the anterior hindgut reduces oxygen diffusion and favours hydrogen accumulation, facilitating fermentation, homoacetogenesis and nitrogen fixation. We demonstrate that depolymerization continues in the posterior hindgut, and that the beetle excretes an energy- and nutrient-rich product on which its offspring subsist and develop. Our results show that the establishment of beneficial microbial partners within a host requires both the acquisition of the microorganisms and the formation of specific habitats within the host to promote key microbial metabolic functions. Together, gut anatomical properties and microbial functional assembly enable lignocellulose deconstruction and colony subsistence on an extremely nutrient-poor diet.

Biological soil crusts (biocrusts) account for a substantial portion of primary production in dryland ecosystems. They successionally mature to deliver a suite of ecosystem services, such as carbon sequestration, water retention and nutrient cycling, and climate regulation. Biocrust assemblages are extremely well adapted to survive desiccation and to rapidly take advantage of the periodic precipitation events typical of arid ecosystems. Here we focus on the wetting response of incipient cyanobacterial crusts as they mature from “light” to “dark.” We sampled a cyanobacterial biocrust chronosequence before (dry) and temporally following a controlled wetting event and used high-throughput 16S rRNA and rRNA gene sequencing to monitor the dynamics of microbial response. Overall, shorter-term changes in phylogenetic beta diversity attributable to periodic wetting were as large as those attributable to biocrust successional stage. Notably, more mature crusts showed significantly higher resistance to precipitation disturbance. A large bloom of a few taxa within the Firmicutes, primarily in the order Bacillales, emerged 18 h after wetting, while filamentous crust-forming cyanobacteria showed variable responses to wet-up across the successional gradient, with populations collapsing in less-developed light crusts but increasing in later-successional-stage dark crusts. Overall, the consistent Bacillales bloom accompanied by the variable collapse of pioneer cyanobacteria of the Oscillatoriales order across the successional gradient suggests that the strong response of few organisms to a hydration pulse with the mortality of the autotroph might have important implications for carbon (C) balance in semiarid ecosystems., IMPORTANCE Desert biological soil crusts are terrestrial topsoil microbial communities common to arid regions that comprise 40% of Earth’s terrestrial surface. They successionally develop over years to decades to deliver a suite of ecosystem services of local and global significance. Ecosystem succession toward maturity has been associated with both resistance and resilience to disturbance. Recent work has shown that the impacts of both climate change and physical disturbance on biocrusts increase the potential for successional resetting. A larger proportion of biocrusts are expected to be at an early developmental stage, hence increasing susceptibility to changes in precipitation frequencies. Therefore, it is essential to characterize how biocrusts respond to wetting across early developmental stages. In this study, we document the wetting response of microbial communities from a biocrust chronosequence. Overall, our results suggest that the cumulative effects of altered precipitation frequencies on the stability of biocrusts will depend on biocrust maturity.

Biological soil crusts (biocrusts) account for a substantial portion of primary production in dryland ecosystems. They successionally mature to deliver a suite of ecosystem services, such as carbon sequestration, water retention and nutrient cycling, and climate regulation. Biocrust assemblages are extremely well adapted to survive desiccation and to rapidly take advantage of the periodic precipitation events typical of arid ecosystems. Here we focus on the wetting response of incipient cyanobacterial crusts as they mature from “light” to “dark.” We sampled a cyanobacterial biocrust chronosequence before (dry) and temporally following a controlled wetting event and used high-throughput 16S rRNA and rRNA gene sequencing to monitor the dynamics of microbial response. Overall, shorter-term changes in phylogenetic beta diversity attributable to periodic wetting were as large as those attributable to biocrust successional stage. Notably, more mature crusts showed significantly higher resistance to precipitation disturbance. A large bloom of a few taxa within the Firmicutes , primarily in the order Bacillales , emerged 18 h after wetting, while filamentous crust-forming cyanobacteria showed variable responses to wet-up across the successional gradient, with populations collapsing in less-developed light crusts but increasing in later-successional-stage dark crusts. Overall, the consistent Bacillales bloom accompanied by the variable collapse of pioneer cyanobacteria of the Oscillatoriales order across the successional gradient suggests that the strong response of few organisms to a hydration pulse with the mortality of the autotroph might have important implications for carbon (C) balance in semiarid ecosystems. IMPORTANCE Desert biological soil crusts are terrestrial topsoil microbial communities common to arid regions that comprise 40% of Earth’s terrestrial surface. They successionally develop over years to decades to deliver a suite of ecosystem services of local and global significance. Ecosystem succession toward maturity has been associated with both resistance and resilience to disturbance. Recent work has shown that the impacts of both climate change and physical disturbance on biocrusts increase the potential for successional resetting. A larger proportion of biocrusts are expected to be at an early developmental stage, hence increasing susceptibility to changes in precipitation frequencies. Therefore, it is essential to characterize how biocrusts respond to wetting across early developmental stages. In this study, we document the wetting response of microbial communities from a biocrust chronosequence. Overall, our results suggest that the cumulative effects of altered precipitation frequencies on the stability of biocrusts will depend on biocrust maturity.

Biogenesis of hydrogen sulfide (H 2 S) (microbial souring) has detrimental impacts on oil production operations and can cause health and safety problems. Understanding the processes that control the rates and patterns of sulfate reduction is crucial in developing a predictive understanding of reservoir souring and associated mitigation processes. This work demonstrates an approach to utilize genomic information to constrain the biological parameters needed for modeling souring, providing a pathway for using microbial data derived from oil reservoir studies. Minimum generation times were calculated based on codon usage bias and optimal growth temperatures based on the frequency of amino acids. We show how these derived parameters can be used in a simplified multiphase reactive transport model by simulating the injection of cold (30 °C) seawater into a 70 °C reservoir, modeling the shift in sulfate reducing microorganisms (SRM) community composition, sulfate and sulfide concentrations through time and space. Finally, we explore the question of necessary model complexity by comparing results using different numbers of SRM. Simulations showed that the kinetics of a SRM community consisting of twenty-five SRM could be adequately represented by a reduced community consisting of nine SRM with parameter values derived from the mean and standard deviations of the original SRM.

This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Hypersaline photosynthetic microbial mats are stratified microbial communities known for their taxonomic and metabolic diversity and strong light-driven day-night environmental gradients. In this study of the upper photosynthetic zone of hypersaline microbial mats of Elkhorn Slough, California (USA), we show how metagenome sequencing can be used to meaningfully assess microbial ecology and genetic partitioning in these complex microbial systems. Mapping of metagenome reads to the dominant Cyanobacteria observed in the system, Coleofasciculus (Microcoleus) chthonoplastes, was used to examine strain variants within these metagenomes. Highly conserved gene subsystems indicated a core genome for the species, and a number of variant genes and subsystems suggested strain level differentiation, especially for nutrient utilization and stress response. Metagenome sequence coverage binning was used to assess ecosystem partitioning of remaining microbes to both reconstruct the model organisms in silico and identify their ecosystem functions as well as to identify novel clades and propose their role in the biogeochemical cycling of mats. Functional gene annotation of these bins (primarily of Proteobacteria, Bacteroidetes, and Cyanobacteria) recapitulated the known biogeochemical functions in microbial mats using a genetic basis, and revealed significant diversity in the Bacteroidetes, presumably in heterotrophic cycling. This analysis also revealed evidence of putative phototrophs within the Gemmatimonadetes and Gammaproteobacteria residing in microbial mats. This study shows that metagenomic analysis can produce insights into the systems biology of microbial ecosystems from a genetic perspective and to suggest further studies of novel microbes.

Author(s): Wood, Lianna F; Brown, Bryan P; Lennard, Katie; Karaoz, Ulas; Havyarimana, Enock; Passmore, Jo-Ann S; Hesseling, Anneke C; Edlefsen, Paul T; Kuhn, Louise; Mulder, Nicola; Brodie, Eoin L; Sodora, Donald L; Jaspan, Heather B | Abstract: Background:Exclusive breastfeeding reduces the rate of postnatal human immunodeficiency virus (HIV) transmission compared to nonexclusive breastfeeding; however, the mechanisms of this protection are unknown. Our study aimed to interrogate the mechanisms underlying the protective effect of exclusive breastfeeding. Methods:We performed a prospective, longitudinal study of infants from a high-HIV-prevalence, low-income setting in South Africa. We evaluated the role of any non-breast milk feeds, excluding prescribed medicines on stool microbial communities via 16S rRNA gene sequencing, peripheral T-cell activation via flow cytometry, and buccal mucosal gene expression via quantitative polymerase chain reaction assay. Results:A total of 155 infants were recruited at birth with mean gestational age of 38.9 weeks and mean birth weight of 3.2 kg. All infants were exclusively breastfed (EBF) at birth, but only 43.5% and 20% remained EBF at 6 or 14 weeks of age, respectively. We observed lower stool microbial diversity and distinct microbial composition in exclusively breastfed infants. These microbial communities, and the relative abundance of key taxa, were correlated with peripheral CD4+ T-cell activation, which was lower in EBF infants. In the oral mucosa, gene expression of chemokine and chemokine receptors involved in recruitment of HIV target cells to tissues, as well as epithelial cytoskeletal proteins, was lower in EBF infants. Conclusions:These data suggest that nonexclusive breastfeeding alters the gut microbiota, increasing T-cell activation and, potentially, mucosal recruitment of HIV target cells. Study findings highlight a biologically plausible mechanistic explanation for the reduced postnatal HIV transmission observed in EBF infants.

© 2017 The Author(s). Cyanobacterial mats are laminated microbial ecosystems which occur in highly diverse environments and which may provide a possible model for early life on Earth. Their ability to produce hydrogen also makes them of interest from a biotechnological and bioenergy perspective. Samples of an intertidal microbial mat from the Elkhorn Slough estuary in Monterey Bay, California, were transplanted to a greenhouse at NASA Ames Research Center to study a 24-h diel cycle, in the presence or absence of molybdate (which inhibits biohydrogen consumption by sulfate reducers). Here, we present metagenomic analyses of four samples that will be used as references for future metatranscriptomic analyses of this diel time series.