Multi-omics of the gut microbial ecosystem in inflammatory bowel diseases.

Inflammatory bowel diseases, which include Crohn's disease and ulcerative colitis, affect several million individuals worldwide. Crohn's disease and ulcerative colitis are complex diseases that are heterogeneous at the clinical, immunological, molecular, genetic, and microbial levels. Individual contributing factors have been the focus of extensive research. As part of the Integrative Human Microbiome Project (HMP2 or iHMP), we followed 132 subjects for one year each to generate integrated longitudinal molecular profiles of host and microbial activity during disease (up to 24 time points each; in total 2,965 stool, biopsy, and blood specimens). Here we present the results, which provide a comprehensive view of functional dysbiosis in the gut microbiome during inflammatory bowel disease activity. We demonstrate a characteristic increase in facultative anaerobes at the expense of obligate anaerobes, as well as molecular disruptions in microbial transcription (for example, among clostridia), metabolite pools (acylcarnitines, bile acids, and short-chain fatty acids), and levels of antibodies in host serum. Periods of disease activity were also marked by increases in temporal variability, with characteristic taxonomic, functional, and biochemical shifts. Finally, integrative analysis identified microbial, biochemical, and host factors central to this dysregulation. The study's infrastructure resources, results, and data, which are available through the Inflammatory Bowel Disease Multi'omics Database ( http://ibdmdb.org ), provide the most comprehensive description to date of host and microbial activities in inflammatory bowel diseases.

A communal catalogue reveals Earth's multiscale microbial diversity.

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.

Qiita: rapid, web-enabled microbiome meta-analysis.

Multi-omic insights into microbiome function and composition typically advance one study at a time. However, in order for relationships across studies to be fully understood, data must be aggregated into meta-analyses. This makes it possible to generate new hypotheses by finding features that are reproducible across biospecimens and data layers. Qiita dramatically accelerates such integration tasks in a web-based microbiome-comparison platform, which we demonstrate with Human Microbiome Project and Integrative Human Microbiome Project (iHMP) data.

Diverse tumour susceptibility in Collaborative Cross mice: identification of a new mouse model for human gastric tumourigenesis.

OBJECTIVE: The Collaborative Cross (CC) is a mouse population model with diverse and reproducible genetic backgrounds used to identify novel disease models and genes that contribute to human disease. Since spontaneous tumour susceptibility in CC mice remains unexplored, we assessed tumour incidence and spectrum. DESIGN: We monitored 293 mice from 18 CC strains for tumour development. Genetic association analysis and RNA sequencing were used to identify susceptibility loci and candidate genes. We analysed genomes of patients with gastric cancer to evaluate the relevance of genes identified in the CC mouse model and measured the expression levels of ISG15 by immunohistochemical staining using a gastric adenocarcinoma tissue microarray. Association of gene expression with overall survival (OS) was assessed by Kaplan-Meier analysis. RESULTS: CC mice displayed a wide range in the incidence and types of spontaneous tumours. More than 40% of CC036 mice developed gastric tumours within 1 year. Genetic association analysis identified Nfκb1 as a candidate susceptibility gene, while RNA sequencing analysis of non-tumour gastric tissues from CC036 mice showed significantly higher expression of inflammatory response genes. In human gastric cancers, the majority of human orthologues of the 166 mouse genes were preferentially altered by amplification or deletion and were significantly associated with OS. Higher expression of the CC036 inflammatory response gene signature is associated with poor OS. Finally, ISG15 protein is elevated in gastric adenocarcinomas and correlated with shortened patient OS. CONCLUSIONS: CC strains exhibit tremendous variation in tumour susceptibility, and we present CC036 as a spontaneous laboratory mouse model for studying human gastric tumourigenesis.

Alterations in the relative abundance of Faecalibacterium prausnitzii correlate with changes in fecal calprotectin in patients with ileal Crohn's disease: a longitudinal study.

Objectives: Crohn's disease is characterized by a gut dysbiosis with decreased abundance of butyrate producers such as Faecalibacterium prausnitzii. Although F. prausnitzii secretes anti-inflammatory molecules, few studies have addressed the importance of F. prausnitzii in a longitudinal setting. We aimed to examine the relationship between temporal profiles of F. prausnitzii, the C. leptum group, overall butyrate production, and inflammatory activity. Material and methods: Fecal samples (n = 59) were collected every third month from nine patients with ileal Crohn's disease. The abundance of F. prausnitzii and C. leptum was quantified relative to the total amount of bacteria using quantitative-PCR. To assess butyrate production of gut microbiota, gene copy numbers of the butyryl-CoA:acetate-CoA transferase (BCoAT) gene were quantified by qPCR. The inflammatory activity was defined by fecal (f)-calprotectin. Results: No correlation between the relative abundance of F. prausnitzii, the C. leptum group, or copy numbers of the BCoAT gene, and f-calprotectin was observed in the total sample set. By analyzing alterations between consecutive samples, a negative correlation between changes in the relative abundance of F. prausnitzii and f-calprotectin was observed (R = -0.39; p = .009). Changes in C. leptum (R = -0.18, p = .23) and number of copies of the BCoAT gene (R = -0.12; p = .42) did not correlate with f-calprotectin. Conclusions: There was an inverse correlation between temporal changes in the relative abundance of F. prausnitzii, but not overall butyrate producing capacity, and changes in inflammatory activity in ileal Crohn's disease. These findings indicate that F. prausnitzii may play a role in gut homeostasis, even though causality is still to be demonstrated.

Metagenomic Analysis of Subtidal Sediments from Polar and Subpolar Coastal Environments Highlights the Relevance of Anaerobic Hydrocarbon Degradation Processes.

In this work, we analyzed the community structure and metabolic potential of sediment microbial communities in high-latitude coastal environments subjected to low to moderate levels of chronic pollution. Subtidal sediments from four low-energy inlets located in polar and subpolar regions from both Hemispheres were analyzed using large-scale 16S rRNA gene and metagenomic sequencing. Communities showed high diversity (Shannon's index 6.8 to 10.2), with distinct phylogenetic structures (<40% shared taxa at the Phylum level among regions) but similar metabolic potential in terms of sequences assigned to KOs. Environmental factors (mainly salinity, temperature, and in less extent organic pollution) were drivers of both phylogenetic and functional traits. Bacterial taxa correlating with hydrocarbon pollution included families of anaerobic or facultative anaerobic lifestyle, such as Desulfuromonadaceae, Geobacteraceae, and Rhodocyclaceae. In accordance, biomarker genes for anaerobic hydrocarbon degradation (bamA, ebdA, bcrA, and bssA) were prevalent, only outnumbered by alkB, and their sequences were taxonomically binned to the same bacterial groups. BssA-assigned metagenomic sequences showed an extremely wide diversity distributed all along the phylogeny known for this gene, including bssA sensu stricto, nmsA, assA, and other clusters from poorly or not yet described variants. This work increases our understanding of microbial community patterns in cold coastal sediments, and highlights the relevance of anaerobic hydrocarbon degradation processes in subtidal environments.

Restructuring of the Aquatic Bacterial Community by Hydric Dynamics Associated with Superstorm Sandy.

UNLABELLED: Bacterial community composition and longitudinal fluctuations were monitored in a riverine system during and after Superstorm Sandy to better characterize inter- and intracommunity responses associated with the disturbance associated with a 100-year storm event. High-throughput sequencing of the 16S rRNA gene was used to assess microbial community structure within water samples from Muddy Creek Run, a second-order stream in Huntingdon, PA, at 12 different time points during the storm event (29 October to 3 November 2012) and under seasonally matched baseline conditions. High-throughput sequencing of the 16S rRNA gene was used to track changes in bacterial community structure and divergence during and after Superstorm Sandy. Bacterial community dynamics were correlated to measured physicochemical parameters and fecal indicator bacteria (FIB) concentrations. Bioinformatics analyses of 2.1 million 16S rRNA gene sequences revealed a significant increase in bacterial diversity in samples taken during peak discharge of the storm. Beta-diversity analyses revealed longitudinal shifts in the bacterial community structure. Successional changes were observed, in which Betaproteobacteria and Gammaproteobacteria decreased in 16S rRNA gene relative abundance, while the relative abundance of members of the Firmicutes increased. Furthermore, 16S rRNA gene sequences matching pathogenic bacteria, including strains of Legionella, Campylobacter, Arcobacter, and Helicobacter, as well as bacteria of fecal origin (e.g., Bacteroides), exhibited an increase in abundance after peak discharge of the storm. This study revealed a significant restructuring of in-stream bacterial community structure associated with hydric dynamics of a storm event. IMPORTANCE: In order to better understand the microbial risks associated with freshwater environments during a storm event, a more comprehensive understanding of the variations in aquatic bacterial diversity is warranted. This study investigated the bacterial communities during and after Superstorm Sandy to provide fine time point resolution of dynamic changes in bacterial composition. This study adds to the current literature by revealing the variation in bacterial community structure during the course of a storm. This study employed high-throughput DNA sequencing, which generated a deep analysis of inter- and intracommunity responses during a significant storm event. This study has highlighted the utility of applying high-throughput sequencing for water quality monitoring purposes, as this approach enabled a more comprehensive investigation of the bacterial community structure. Altogether, these data suggest a drastic restructuring of the stream bacterial community during a storm event and highlight the potential of high-throughput sequencing approaches for assessing the microbiological quality of our environment.

Assessment of a novel continuous cleaning device using metatranscriptomics in diverse hospital environments.

Introduction: Despite routine implementation of cleaning and disinfection practices in clinical healthcare settings, high-touch environmental surfaces and contaminated equipment often serve as reservoirs for the transmission of pathogens associated with healthcare-associated infections (HAIs). Methods: The current study involved the analysis of high-touch surface swabs using a metatranscriptomic sequencing workflow (CSI-Dx™) to assess the efficacy of cleanSURFACES® technology in decreasing microbial burden by limiting re-contamination. This is a non-human single center study conducted in the Emergency Department (ED) and on an inpatient Oncology Ward of Walter Reed National Military Medical Center that have followed hygienic practices during the COVID-19 pandemic environment. Results: Although there was no difference in observed microbial richness (two-tailed Wilcoxon test with Holm correction, P > 0.05), beta diversity findings identified shifts in microbial community structure between surfaces from baseline and post-intervention timepoints (Day 1, Day 7, Day 14, and Day 28). Biomarker and regression analyses identified significant reductions in annotated transcripts for various clinically relevant microorganisms' post-intervention, coagulase-negative staphylococci and Malassezia restricta, at ED and Oncology ward, respectively. Additionally, post-intervention samples predominantly consisted of Proteobacteria and to a lesser extent skin commensals and endogenous environmental microorganisms in both departments. Discussion: Findings support the value of cleanSURFACES®, when coupled with routine disinfection practices, to effectively impact on the composition of active microbial communities found on high-touch surfaces in two different patient care areas of the hospital (one outpatient and one inpatient) with unique demands and patient-centered practices.

cleanSURFACES® intervention reduces microbial activity on surfaces in a senior care facility.

As one of the top public health challenges outlined by the Centers for Disease Control (CDC), estimates report that hospital acquired infections (HAIs) claim the lives of 99,000 Americans and cost healthcare providers over $28 billion each year. In addition to underlying conditions related to age, elderly patients in long-term care facilities are at an elevated risk of acquiring HAIs. A large percentage of HAIs is attributable to contaminated surfaces and medical devices. To that end, this study utilized a metatranscriptomic sequencing workflow (CSI-Dx™) to profile active microbial communities from surfaces in the HJ Heinz Community Living Center, a long-term care facility in the Veterans Affairs Pittsburgh Health Care System. Swabs were collected from high-touch surfaces (Keyboard, Ledge, Workstation on Wheels, Worksurfaces) before (Baseline) and after cleanSURFACES® were installed at 4 timepoints (Day 1, Day 7, Day 14, and Day 30). Microbial richness was significantly reduced after cleanSURFACES® intervention (Wilcoxon test with Holm correction, p=0.000179). Beta diversity results revealed distinct clustering between Baseline and Post-intervention samples (Adonis, p<0.001). Reduction in bacterial (Staphylococcus aureus, Staphylococcus epidermidis, Staphylococcus hominis) and fungal (Malassezia restricta, Candida albicans, Candida glabrata, and Candida orthopsilosis) expression of opportunistic pathogens was observed. Additionally, a subset of taxa (Corynebacterium, Cutibacterium acnes, and Ralstonia pickettii) was present in specific Post-intervention timepoints and surface types. This study revealed decreased microbial activity, highlighting the potential for the combinatorial application of cleanSURFACES® and regular decontamination practices to reduce the prevalence of microbes causing HAIs.

A Metatranscriptomics Survey of Microbial Diversity on Surfaces Post-Intervention of cleanSURFACES® Technology in an Intensive Care Unit.

Hospital-acquired infections (HAIs) pose a serious threat to patients, and hospitals spend billions of dollars each year to reduce and treat these infections. Many HAIs are due to contamination from workers' hands and contact with high-touch surfaces. Therefore, we set out to test the efficacy of a new preventative technology, AIONX® Antimicrobial Technologies, Inc's cleanSURFACES®, which is designed to complement daily chemical cleaning events by continuously preventing re-colonization of surfaces. To that end, we swabbed surfaces before (Baseline) and after (Post) application of the cleanSURFACES® at various time points (Day 1, Day 7, Day 14, and Day 28). To circumvent limitations associated with culture-based and 16S rRNA gene amplicon sequencing methodologies, these surface swabs were processed using metatranscriptomic (RNA) analysis to allow for comprehensive taxonomic resolution and the detection of active microorganisms. Overall, there was a significant (P < 0.05) global reduction of microbial diversity in Post-intervention samples. Additionally, Post sample microbial communities clustered together much more closely than Baseline samples based on pairwise distances calculated with the weighted Jaccard distance metric, suggesting a defined shift after product application. This shift was characterized by a general depletion of several microbes among Post samples, with multiple phyla also being reduced over the duration of the study. Notably, specific clinically relevant microbes, including Staphylococcus aureus, Clostridioides difficile and Streptococcus spp., were depleted Post-intervention. Taken together, these findings suggest that chemical cleaning events used jointly with cleanSURFACES® have the potential to reduce colonization of surfaces by a wide variety of microbes, including many clinically relevant pathogens.

Temporal Transcriptomics of Gut Escherichia coli in Caenorhabditis elegans Models of Aging.

Host-bacterial interactions over the course of aging are understudied due to complexities of the human microbiome and challenges of collecting samples that span a lifetime. To investigate the role of host-microbial interactions in aging, we performed transcriptomics using wild-type Caenorhabditis elegans (N2) and three long-lived mutants (daf-2, eat-2, and asm-3) fed Escherichia coli OP50 and sampled at days 5, 7.5, and 10 of adulthood. We found host age is a better predictor of the E. coli expression profiles than host genotype. Specifically, host age was associated with clustering (permutational multivariate analysis of variance [PERMANOVA], P = 0.001) and variation (Adonis, P = 0.001, R2 = 11.5%) among E. coli expression profiles, whereas host genotype was not (PERMANOVA, P > 0.05; Adonis, P > 0.05, R2 = 5.9%). Differential analysis of the E. coli transcriptome yielded 22 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and 100 KEGG genes enriched when samples were grouped by time point [LDA, linear discriminant analysis; log(LDA), ≥2; P ≤ 0.05], including several involved in biofilm formation. Coexpression analysis of host and bacterial genes yielded six modules of C. elegans genes that were coexpressed with one bacterial regulator gene over time. The three most significant bacterial regulators included genes relating to biofilm formation, lipopolysaccharide production, and thiamine biosynthesis. Age was significantly associated with clustering and variation among transcriptomic samples, supporting the idea that microbes are active and plastic within C. elegans throughout life. Coexpression analysis further revealed interactions between E. coli and C. elegans that occurred over time, building on a growing literature of host-microbial interactions. IMPORTANCE Previous research has reported effects of the microbiome on health span and life span of Caenorhabditis elegans, including interactions with evolutionarily conserved pathways in humans. We build on this literature by reporting the gene expression of Escherichia coli OP50 in wild-type (N2) and three long-lived mutants of C. elegans. The manuscript represents the first study, to our knowledge, to perform temporal host-microbial transcriptomics in the model organism C. elegans. Understanding changes to the microbial transcriptome over time is an important step toward elucidating host-microbial interactions and their potential relationship to aging. We found that age was significantly associated with clustering and variation among transcriptomic samples, supporting the idea that microbes are active and plastic within C. elegans throughout life. Coexpression analysis further revealed interactions between E. coli and C. elegans that occurred over time, which contributes to our growing knowledge about host-microbial interactions.

Deconstructing the Soil Microbiome into Reduced-Complexity Functional Modules.

The soil microbiome represents one of the most complex microbial communities on the planet, encompassing thousands of taxa and metabolic pathways, rendering holistic analyses computationally intensive and difficult. Here, we developed an alternative approach in which the complex soil microbiome was broken into components ("functional modules"), based on metabolic capacities, for individual characterization. We hypothesized that reproducible, low-complexity communities that represent functional modules could be obtained through targeted enrichments and that, in combination, they would encompass a large extent of the soil microbiome diversity. Enrichments were performed on a starting soil inoculum with defined media based on specific carbon substrates, antibiotics, alternative electron acceptors under anaerobic conditions, or alternative growing conditions reflective of common field stresses. The resultant communities were evaluated through 16S rRNA amplicon sequencing. Less permissive modules (anaerobic conditions, complex polysaccharides, and certain stresses) resulted in more distinct community profiles with higher richness and more variability between replicates, whereas modules with simple substrates were dominated by fewer species and were more reproducible. Collectively, approximately 27% of unique taxa present in the liquid soil extract control were found across functional modules. Taxa that were underrepresented or undetected in the source soil were also enriched across the modules. Metatranscriptomic analyses were carried out on a subset of the modules to investigate differences in functional gene expression. These results demonstrate that by dissecting the soil microbiome into discrete components it is possible to obtain a more comprehensive view of the soil microbiome and its biochemical potential than would be possible using more holistic analyses.IMPORTANCE The taxonomic and functional diversity inherent to the soil microbiome complicate assessments of the metabolic potential carried out by the community members. An alternative approach is to break down the soil microbiome into reduced-complexity subsets based on metabolic capacities (functional modules) prior to sequencing and analysis. Here, we demonstrate that this approach successfully identified specific phylogenetic and biochemical traits of the soil microbiome that otherwise remained hidden from a more top-down analysis.

Corrigendum: Light-Stress Influences the Composition of the Murine Gut Microbiome, Memory Function, and Plasma Metabolome.

[This corrects the article DOI: 10.3389/fmolb.2019.00108.].

Genetic and metabolic links between the murine microbiome and memory.

BACKGROUND: Recent evidence has linked the gut microbiome to host behavior via the gut-brain axis [1-3]; however, the underlying mechanisms remain unexplored. Here, we determined the links between host genetics, the gut microbiome and memory using the genetically defined Collaborative Cross (CC) mouse cohort, complemented with microbiome and metabolomic analyses in conventional and germ-free (GF) mice. RESULTS: A genome-wide association analysis (GWAS) identified 715 of 76,080 single-nucleotide polymorphisms (SNPs) that were significantly associated with short-term memory using the passive avoidance model. The identified SNPs were enriched in genes known to be involved in learning and memory functions. By 16S rRNA gene sequencing of the gut microbial community in the same CC cohort, we identified specific microorganisms that were significantly correlated with longer latencies in our retention test, including a positive correlation with Lactobacillus. Inoculation of GF mice with individual species of Lactobacillus (L. reuteri F275, L. plantarum BDGP2 or L. brevis BDGP6) resulted in significantly improved memory compared to uninoculated or E. coli DH10B inoculated controls. Untargeted metabolomics analysis revealed significantly higher levels of several metabolites, including lactate, in the stools of Lactobacillus-colonized mice, when compared to GF control mice. Moreover, we demonstrate that dietary lactate treatment alone boosted memory in conventional mice. Mechanistically, we show that both inoculation with Lactobacillus or lactate treatment significantly increased the levels of the neurotransmitter, gamma-aminobutyric acid (GABA), in the hippocampus of the mice. CONCLUSION: Together, this study provides new evidence for a link between Lactobacillus and memory and our results open possible new avenues for treating memory impairment disorders using specific gut microbial inoculants and/or metabolites. Video Abstract.

Correction to: Genetic and metabolic links between the murine microbiome and memory.

An amendment to this paper has been published and can be accessed via the original article.

Light-Stress Influences the Composition of the Murine Gut Microbiome, Memory Function, and Plasma Metabolome.

The gut microbiome plays an important role in the mammalian host and when in proper balance helps protect health and prevent disease. Host environmental stress and its influence on the gut microbiome, health, and disease is an emerging area of research. Exposures to unnatural light cycles are becoming increasingly common due to travel and shift work. However, much remains unknown about how these changes influence the microbiome and host health. This information is needed to understand and predict the relationship between the microbiome and host response to altered sleep cycles. In the present study, we exposed three cohorts of mice to different light cycle regimens for 12 consecutive weeks; including continuous light, continuous dark, and a standard light dark regimen consisting of 12 h light followed by 12 h of dark. After exposure, motor and memory behavior, and the composition of the fecal microbiome and plasma metabolome were measured. Memory potential was significantly reduced in mice exposed to continuous light, whereas rotarod performance was minimally affected. The overall composition of the microbiome was relatively constant over time. However, Bacteroidales Rikenellaceae was relatively more abundant in mice exposed to continuous dark, while Bacteroidales S24-7 was relatively more abundant in mice exposed to continuous light. The plasma metabolome after the continuous dark exposure differed from the other exposure conditions. Several plasma metabolites, including glycolic acid, tryptophan, pyruvate, and several unidentified metabolites, were correlated to continuous dark and light exposure conditions. Networking analyses showed that serotonin was positively correlated with three microbial families (Rikenellaceae, Ruminococcaceae, and Turicibacteraceae), while tryptophan was negatively correlated with abundance of Bacteroidales S24-7 based on light exposure. This study provides the foundation for future studies into the mechanisms underlying the role of the gut microbiome on the murine host during light-dark stress.

Forfeiting the priority effect: turnover defines biofilm community succession.

Microbial community succession is a fundamental process that affects underlying functions of almost all ecosystems; yet the roles and fates of the most abundant colonizers are often poorly understood. Does early abundance spur long term persistence? How do deterministic and stochastic processes influence the ecological contribution of colonizers? We performed a succession experiment within a hypersaline ecosystem to investigate how different processes contributed to the turnover of founder species. Bacterial and eukaryotic colonizers were identified during primary succession and tracked through a defined, 79-day biofilm maturation period using 16S and 18S rRNA gene sequencing in combination with high resolution imaging that utilized stable isotope tracers to evaluate successional patterns of primary producers and nitrogen fixers. The majority of the founder species did not maintain high abundance throughout succession. Species replacement (versus loss) was the dominant process shaping community succession. We also asked if different ecological processes acted on bacteria versus Eukaryotes during succession and found deterministic and stochastic forces corresponded more with microeukaryote and bacterial colonization, respectively. Our results show that taxa and functions belonging to different kingdoms, which share habitat in the tight spatial confines of a biofilm, were influenced by different ecological processes and time scales of succession.

Selection, Succession, and Stabilization of Soil Microbial Consortia.

Soil microorganisms play fundamental roles in cycling of soil carbon, nitrogen, and other nutrients, yet we have a poor understanding of how soil microbiomes are shaped by their nutritional and physical environment. In this study, we investigated the successional dynamics of a soil microbiome during 21 weeks of enrichment on chitin and its monomer, N-acetylglucosamine. We examined succession of the soil communities in a physically heterogeneous soil matrix as well as a homogeneous liquid medium. The guiding hypothesis was that the initial species richness would influence the tendency for the selected consortia to stabilize and maintain a relatively constant community structure over time. We also hypothesized that long-term, substrate-driven growth would result in consortia with reduced species richness compared to the parent microbiome and that this process would be deterministic with relatively little variation between replicates. We found that the initial species richness does influence the long-term community stability in both liquid media and soil and that lower initial richness results in a more rapid convergence to stability. Despite use of the same soil inoculum and access to the same major substrate, the resulting community composition differed greatly in soil from that in liquid medium. Hence, distinct selective pressures in soils relative to homogenous liquid media exist and can control community succession dynamics. This difference is likely related to the fact that soil microbiomes are more likely to thrive, with fewer compositional changes, in a soil matrix than in liquid environments. IMPORTANCE The soil microbiome carries out important ecosystem functions, but interactions between soil microbial communities have been difficult to study due to the high microbial diversity and complexity of the soil habitat. In this study, we successfully obtained stable consortia with reduced complexity that contained species found in the original source soil. These consortia and the methods used to obtain them can be a valuable resource for exploration of specific mechanisms underlying soil microbial community ecology. The results of this study also provide new experimental context to better inform how soil microbial communities are shaped by new environments and how a combination of initial taxonomic structure and physical environment influences stability.

Metaphenomic Responses of a Native Prairie Soil Microbiome to Moisture Perturbations.

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 Correction: Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.