Parents' expectations, preferences, and recall of germline findings in a childhood cancer precision medicine trial.

BACKGROUND: Germline genome sequencing in childhood cancer precision medicine trials may reveal pathogenic or likely pathogenic variants in cancer predisposition genes in more than 10% of children. These findings can have implications for diagnosis, treatment, and the child's and family's future cancer risk. Understanding parents' perspectives of germline genome sequencing is critical to successful clinical implementation. METHODS: A total of 182 parents of 144 children (<18 years of age) with poor-prognosis cancers enrolled in the Precision Medicine for Children with Cancer trial completed a questionnaire at enrollment and after the return of their child's results, including clinically relevant germline findings (received by 13% of parents). Parents' expectations of germline genome sequencing, return of results preferences, and recall of results received were assessed. Forty-five parents (of 43 children) were interviewed in depth. RESULTS: At trial enrollment, most parents (63%) believed it was at least "somewhat likely" that their child would receive a clinically relevant germline finding. Almost all expressed a preference to receive a broad range of germline genomic findings, including variants of uncertain significance (88%). Some (29%) inaccurately recalled receiving a clinically relevant germline finding. Qualitatively, parents expressed confusion and uncertainty after the return of their child's genome sequencing results by their child's clinician. CONCLUSIONS: Many parents of children with poor-prognosis childhood cancer enrolled in a precision medicine trial expect their child may have an underlying cancer predisposition syndrome. They wish to receive a wide scope of information from germline genome sequencing but may feel confused by the reporting of trial results.

Methane-Oxidizing Activity Enhances Sulfamethoxazole Biotransformation in a Benthic Constructed Wetland Biomat.

Ammonia monooxygenase and analogous oxygenase enzymes contribute to pharmaceutical biotransformation in activated sludge. In this study, we hypothesized that methane monooxygenase can enhance pharmaceutical biotransformation within the benthic, diffuse periphytic sediments (i.e., "biomat") of a shallow, open-water constructed wetland. To test this hypothesis, we combined field-scale metatranscriptomics, porewater geochemistry, and methane gas fluxes to inform microcosms targeting methane monooxygenase activity and its potential role in pharmaceutical biotransformation. In the field, sulfamethoxazole concentrations decreased within surficial biomat layers where genes encoding for the particulate methane monooxygenase (pMMO) were transcribed by a novel methanotroph classified as Methylotetracoccus. Inhibition microcosms provided independent confirmation that methane oxidation was mediated by the pMMO. In these same incubations, sulfamethoxazole biotransformation was stimulated proportional to aerobic methane-oxidizing activity and exhibited negligible removal in the absence of methane, in the presence of methane and pMMO inhibitors, and under anoxia. Nitrate reduction was similarly enhanced under aerobic methane-oxidizing conditions with rates several times faster than for canonical denitrification. Collectively, our results provide convergent in situ and laboratory evidence that methane-oxidizing activity can enhance sulfamethoxazole biotransformation, with possible implications for the combined removal of nitrogen and trace organic contaminants in wetland sediments.

Variation in Root Exudate Composition Influences Soil Microbiome Membership and Function.

Root exudation is one of the primary processes that mediate interactions between plant roots, microorganisms, and the soil matrix, yet the mechanisms by which exudation alters microbial metabolism in soils have been challenging to unravel. Here, utilizing distinct sorghum genotypes, we characterized the chemical heterogeneity between root exudates and the effects of that variability on soil microbial membership and metabolism. Distinct exudate chemical profiles were quantified and used to formulate synthetic root exudate treatments: a high-organic-acid treatment (HOT) and a high-sugar treatment (HST). To parse the response of the soil microbiome to different exudate regimens, laboratory soil reactors were amended with these root exudate treatments as well as a nonexudate control. Amplicon sequencing of the 16S rRNA gene illustrated distinct microbial diversity patterns and membership in response to HST, HOT, or control amendments. Exometabolite changes reflected these microbial community changes, and we observed enrichment of organic and amino acids, as well as possible phytohormones in the HST relative to the HOT and control. Linking the metabolic capacity of metagenome-assembled genomes in the HST to the exometabolite patterns, we identified microorganisms that could produce these phytohormones. Our findings emphasize the tractability of high-resolution multiomics tools to investigate soil microbiomes, opening the possibility of manipulating native microbial communities to improve specific soil microbial functions and enhance crop production. IMPORTANCE Decrypting the chemical interactions between plant roots and the soil microbiome is a gateway for future manipulation and management of the rhizosphere, a soil compartment critical to promoting plant fitness and yields. Our experimental results demonstrate how soil microbial community and genomic diversity is influenced by root exudates of differing chemical compositions and how changes in this microbiome result in altered production of plant-relevant metabolites. Together, these findings demonstrate the tractability of high-resolution multiomics tools to investigate soil microbiomes and provide new information on plant-soil environments useful for the development of efficient and precise microbiota management strategies in agricultural systems.

Pharmaceutical Biotransformation is Influenced by Photosynthesis and Microbial Nitrogen Cycling in a Benthic Wetland Biomat.

In shallow, open-water engineered wetlands, design parameters select for a photosynthetic microbial biomat capable of robust pharmaceutical biotransformation, yet the contributions of specific microbial processes remain unclear. Here, we combined genome-resolved metatranscriptomics and oxygen profiling of a field-scale biomat to inform laboratory inhibition microcosms amended with a suite of pharmaceuticals. Our analyses revealed a dynamic surficial layer harboring oxic-anoxic cycling and simultaneous photosynthetic, nitrifying, and denitrifying microbial transcription spanning nine bacterial phyla, with unbinned eukaryotic scaffolds suggesting a dominance of diatoms. In the laboratory, photosynthesis, nitrification, and denitrification were broadly decoupled by incubating oxic and anoxic microcosms in the presence and absence of light and nitrogen cycling enzyme inhibitors. Through combining microcosm inhibition data with field-scale metagenomics, we inferred microbial clades responsible for biotransformation associated with membrane-bound nitrate reductase activity (emtricitabine, trimethoprim, and atenolol), nitrous oxide reduction (trimethoprim), ammonium oxidation (trimethoprim and emtricitabine), and photosynthesis (metoprolol). Monitoring of transformation products of atenolol and emtricitabine confirmed that inhibition was specific to biotransformation and highlighted the value of oscillating redox environments for the further transformation of atenolol acid. Our findings shed light on microbial processes contributing to pharmaceutical biotransformation in open-water wetlands with implications for similar nature-based treatment systems.

Optimization of proteomics sample preparation for identification of host and bacterial proteins in mouse feces.

Bottom-up proteomics is a powerful method for the functional characterization of mouse gut microbiota. To date, most of the bottom-up proteomics studies of the mouse gut rely on limited amounts of fecal samples. With mass-limited samples, the performance of such analyses is highly dependent on the protein extraction protocols and contaminant removal strategies. Here, protein extraction protocols (using different lysis buffers) and contaminant removal strategies (using different types of filters and beads) were systematically evaluated to maximize quantitative reproducibility and the number of identified proteins. Overall, our results recommend a protein extraction method using a combination of sodium dodecyl sulfate (SDS) and urea in Tris-HCl to yield the greatest number of protein identifications. These conditions led to an increase in the number of proteins identified from gram-positive bacteria, such as Firmicutes and Actinobacteria, which is a challenging task. Our analysis further confirmed these conditions led to the extraction of non-abundant bacterial phyla such as Proteobacteria. In addition, we found that, when coupled to our optimized extraction method, suspension trap (S-Trap) outperforms other contaminant removal methods by providing the most reproducible method while producing the greatest number of protein identifications. Overall, our optimized sample preparation workflow is straightforward and fast, and requires minimal sample handling. Furthermore, our approach does not require high amounts of fecal samples, a vital consideration in proteomics studies where mice produce smaller amounts of feces due to a particular physiological condition. Our final method provides efficient digestion of mouse fecal material, is reproducible, and leads to high proteomic coverage for both host and microbiome proteins.

DRAM for distilling microbial metabolism to automate the curation of microbiome function.

Microbial and viral communities transform the chemistry of Earth's ecosystems, yet the specific reactions catalyzed by these biological engines are hard to decode due to the absence of a scalable, metabolically resolved, annotation software. Here, we present DRAM (Distilled and Refined Annotation of Metabolism), a framework to translate the deluge of microbiome-based genomic information into a catalog of microbial traits. To demonstrate the applicability of DRAM across metabolically diverse genomes, we evaluated DRAM performance on a defined, in silico soil community and previously published human gut metagenomes. We show that DRAM accurately assigned microbial contributions to geochemical cycles and automated the partitioning of gut microbial carbohydrate metabolism at substrate levels. DRAM-v, the viral mode of DRAM, established rules to identify virally-encoded auxiliary metabolic genes (AMGs), resulting in the metabolic categorization of thousands of putative AMGs from soils and guts. Together DRAM and DRAM-v provide critical metabolic profiling capabilities that decipher mechanisms underpinning microbiome function.

Coupled laboratory and field investigations resolve microbial interactions that underpin persistence in hydraulically fractured shales.

Hydraulic fracturing is one of the industrial processes behind the surging natural gas output in the United States. This technology inadvertently creates an engineered microbial ecosystem thousands of meters below Earth's surface. Here, we used laboratory reactors to perform manipulations of persisting shale microbial communities that are currently not feasible in field scenarios. Metaproteomic and metabolite findings from the laboratory were then corroborated using regression-based modeling performed on metagenomic and metabolite data from more than 40 produced fluids from five hydraulically fractured shale wells. Collectively, our findings show that Halanaerobium, Geotoga, and Methanohalophilus strain abundances predict a significant fraction of nitrogen and carbon metabolites in the field. Our laboratory findings also exposed cryptic predatory, cooperative, and competitive interactions that impact microorganisms across fractured shales. Scaling these results from the laboratory to the field identified mechanisms underpinning biogeochemical reactions, yielding knowledge that can be harnessed to potentially increase energy yields and inform management practices in hydraulically fractured shales.

Deep-Subsurface Pressure Stimulates Metabolic Plasticity in Shale-Colonizing Halanaerobium spp.

Bacterial Halanaerobium strains become the dominant persisting microbial community member in produced fluids across geographically distinct hydraulically fractured shales. Halanaerobium is believed to be inadvertently introduced into this environment during the drilling and fracturing process and must therefore tolerate large changes in pressure, temperature, and salinity. Here, we used a Halanaerobium strain isolated from a natural gas well in the Utica Point Pleasant formation to investigate metabolic and physiological responses to growth under high-pressure subsurface conditions. Laboratory incubations confirmed the ability of Halanaerobium congolense strain WG8 to grow under pressures representative of deep shale formations (21 to 48 MPa). Under these conditions, broad metabolic and physiological shifts were identified, including higher abundances of proteins associated with the production of extracellular polymeric substances. Confocal laser scanning microscopy indicated that extracellular polymeric substance (EPS) production was associated with greater cell aggregation when biomass was cultured at high pressure. Changes in Halanaerobium central carbon metabolism under the same conditions were inferred from nuclear magnetic resonance (NMR) and gas chromatography measurements, revealing large per-cell increases in production of ethanol, acetate, and propanol and cessation of hydrogen production. These metabolic shifts were associated with carbon flux through 1,2-propanediol in response to slower fluxes of carbon through stage 3 of glycolysis. Together, these results reveal the potential for bioclogging and corrosion (via organic acid fermentation products) associated with persistent Halanaerobium growth in deep, hydraulically fractured shale ecosystems, and offer new insights into cellular mechanisms that enable these strains to dominate deep-shale microbiomes.IMPORTANCE The hydraulic fracturing of deep-shale formations for hydrocarbon recovery accounts for approximately 60% of U.S. natural gas production. Microbial activity associated with this process is generally considered deleterious due to issues associated with sulfide production, microbially induced corrosion, and bioclogging in the subsurface. Here we demonstrate that a representative Halanaerobium species, frequently the dominant microbial taxon in hydraulically fractured shales, responds to pressures characteristic of the deep subsurface by shifting its metabolism to generate more corrosive organic acids and produce more polymeric substances that cause "clumping" of biomass. While the potential for increased corrosion of steel infrastructure and clogging of pores and fractures in the subsurface may significantly impact hydrocarbon recovery, these data also offer new insights for microbial control in these ecosystems.

Comparative genomics and physiology of the genus Methanohalophilus, a prevalent methanogen in hydraulically fractured shale.

About 60% of natural gas production in the United States comes from hydraulic fracturing of unconventional reservoirs, such as shales or organic-rich micrites. This process inoculates and enriches for halotolerant microorganisms in these reservoirs over time, resulting in a saline ecosystem that includes methane producing archaea. Here, we survey the biogeography of methanogens across unconventional reservoirs, and report that members of genus Methanohalophilus are recovered from every hydraulically fractured unconventional reservoir sampled by metagenomics. We provide the first genomic sequencing of three isolate genomes, as well as two metagenome assembled genomes (MAGs). Utilizing six other previously sequenced isolate genomes and MAGs, we perform comparative analysis of the 11 genomes representing this genus. This genomic investigation revealed distinctions between surface and subsurface derived genomes that are consistent with constraints encountered in each environment. Genotypic differences were also uncovered between isolate genomes recovered from the same well, suggesting niche partitioning among closely related strains. These genomic substrate utilization predictions were then confirmed by physiological investigation. Fine-scale microdiversity was observed in CRISPR-Cas systems of Methanohalophilus, with genomes from geographically distinct unconventional reservoirs sharing spacers targeting the same viral population. These findings have implications for augmentation strategies resulting in enhanced biogenic methane production in hydraulically fractured unconventional reservoirs.

High-resolution sequencing reveals unexplored archaeal diversity in freshwater wetland soils.

Despite being key contributors to biogeochemical processes, archaea are frequently outnumbered by bacteria, and consequently are underrepresented in combined molecular surveys. Here, we demonstrate an approach to concurrently survey the archaea alongside the bacteria with high-resolution 16S rRNA gene sequencing, linking these community data to geochemical parameters. We applied this integrated analysis to hydric soils sampled across a model methane-emitting freshwater wetland. Geochemical profiles, archaeal communities, and bacterial communities were independently correlated with soil depth and water cover. Centimeters of soil depth and corresponding geochemical shifts consistently affected microbial community structure more than hundreds of meters of lateral distance. Methanogens with diverse metabolisms were detected across the wetland, but displayed surprising OTU-level partitioning by depth. Candidatus Methanoperedens spp. archaea thought to perform anaerobic oxidation of methane linked to iron reduction were abundant. Domain-specific sequencing also revealed unexpectedly diverse non-methane-cycling archaeal members. OTUs within the underexplored Woesearchaeota and Bathyarchaeota were prevalent across the wetland, with subgroups and individual OTUs exhibiting distinct occupancy and abundance distributions aligned with environmental gradients. This study adds to our understanding of ecological range for key archaeal taxa in a model freshwater wetland, and links these taxa and individual OTUs to hypotheses about processes governing biogeochemical cycling.

Polyphenol rewiring of the microbiome reduces methane emissions.

Methane mitigation is regarded as a critical strategy to combat the scale of global warming. Currently, about 40% of methane emissions originate from microbial sources, which is causing strategies to suppress methanogens, either through direct toxic effects or by diverting their substrates and energy, to gain traction. Problematically, current microbial methane mitigation knowledge derives from rumen studies and lacks detailed microbiome-centered insights, limiting translation across ecosystems. Here we utilize genome-resolved metatranscriptomes and metabolomes to assess the impact of a proposed methane inhibitor, catechin, on greenhouse gas emissions for high-methane-emitting peatlands. In microcosms, catechin drastically reduced methane emissions by 72-84% compared to controls. Longitudinal sampling allowed for reconstruction of a novel catechin degradation pathway involving Actinomycetota and Clostridium, which break down catechin into smaller phenolic compounds within the first 21 days, followed by degradation of phenolic compounds by Pseudomonas_E from days 21 to 35. These genomes also co-expressed hydrogen-uptake genes, suggesting that hydrogenases may act as a hydrogen sink during catechin degradation, depriving methanogens of substrates. This was supported by decreased gene expression in hydrogenotrophic and hydrogen-dependent methylotrophic methanogens under catechin treatment. We also saw reduced gene expression from genomes inferred to be functioning syntrophically with hydrogen-utilizing methanogens. We propose that catechin metabolic redirection effectively starves hydrogen-utilizing methanogens, offering a potent avenue for curbing methane emissions across diverse environments including ruminants, landfills, and constructed or managed wetlands.

Gut microbiota carbon and sulfur metabolisms support Salmonella infections.

Salmonella enterica serovar Typhimurium is a pervasive enteric pathogen and ongoing global threat to public health. Ecological studies in the Salmonella impacted gut remain underrepresented in the literature, discounting microbiome mediated interactions that may inform Salmonella physiology during colonization and infection. To understand the microbial ecology of Salmonella remodeling of the gut microbiome, we performed multi-omics on fecal microbial communities from untreated and Salmonella-infected mice. Reconstructed genomes recruited metatranscriptomic and metabolomic data providing a strain-resolved view of the expressed metabolisms of the microbiome during Salmonella infection. These data informed possible Salmonella interactions with members of the gut microbiome that were previously uncharacterized. Salmonella-induced inflammation significantly reduced the diversity of genomes that recruited transcripts in the gut microbiome, yet increased transcript mapping was observed for seven members, among which Luxibacter and Ligilactobacillus transcript read recruitment was most prevalent. Metatranscriptomic insights from Salmonella and other persistent taxa in the inflamed microbiome further expounded the necessity for oxidative tolerance mechanisms to endure the host inflammatory responses to infection. In the inflamed gut lactate was a key metabolite, with microbiota production and consumption reported amongst members with detected transcript recruitment. We also showed that organic sulfur sources could be converted by gut microbiota to yield inorganic sulfur pools that become oxidized in the inflamed gut, resulting in thiosulfate and tetrathionate that support Salmonella respiration. This research advances physiological microbiome insights beyond prior amplicon-based approaches, with the transcriptionally active organismal and metabolic pathways outlined here offering intriguing intervention targets in the Salmonella-infected intestine.

Time resolved multi-omics reveals diverse metabolic strategies of Salmonella during diet-induced inflammation.

With a rise in antibiotic resistance and chronic infection, the metabolic response of Salmonella enterica serovar Typhimurium to various dietary conditions over time remains an understudied avenue for novel, targeted therapeutics. Elucidating how enteric pathogens respond to dietary variation not only helps us decipher the metabolic strategies leveraged for expansion but also assists in proposing targets for therapeutic interventions. Here, we use a multi-omics approach to identify the metabolic response of Salmonella enterica serovar Typhimurium in mice on both a fibrous diet and high-fat diet over time. When comparing Salmonella gene expression between diets, we found a preferential use of respiratory electron acceptors consistent with increased inflammation of the high-fat diet mice. Looking at the high-fat diet over the course of infection, we noticed heterogeneity of samples based on Salmonella ribosomal activity, which separated into three infection phases: early, peak, and late. We identified key respiratory, carbon, and pathogenesis gene expression descriptive of each phase. Surprisingly, we identified genes associated with host-cell entry expressed throughout infection, suggesting sub-populations of Salmonella or stress-induced dysregulation. Collectively, these results highlight not only the sensitivity of Salmonella to its environment but also identify phase-specific genes that may be used as therapeutic targets to reduce infection. Importance: Identifying novel therapeutic strategies for Salmonella infection that occur in relevant diets and over time is needed with the rise of antibiotic resistance and global shifts towards Western diets that are high in fat and low in fiber. Mice on a high-fat diet are more inflamed compared to those on a fibrous diet, creating an environment that results in more favorable energy generation for Salmonella . Over time on a high-fat diet, we observed differential gene expression across infection phases. Together, these findings reveal the metabolic tuning of Salmonella to dietary and temporal perturbations. Research like this, exploring the dimensions of pathogen metabolic plasticity, can pave the way for rationally designed strategies to control disease.

Time-resolved multi-omics reveals diverse metabolic strategies of Salmonella during diet-induced inflammation.

With a rise in antibiotic resistance and chronic infection, the metabolic response of Salmonella enterica serovar Typhimurium to various dietary conditions over time remains an understudied avenue for novel, targeted therapeutics. Elucidating how enteric pathogens respond to dietary variation not only helps us decipher the metabolic strategies leveraged for expansion but also assists in proposing targets for therapeutic interventions. In this study, we use a multi-omics approach to identify the metabolic response of Salmonella enterica serovar Typhimurium in mice on both a fibrous diet and high-fat diet over time. When comparing Salmonella gene expression between diets, we found a preferential use of respiratory electron acceptors consistent with increased inflammation in high-fat diet mice. Looking at the high-fat diet over the course of infection, we noticed heterogeneity in samples based on Salmonella ribosomal activity, which is separated into three infection phases: early, peak, and late. We identified key respiratory, carbon, and pathogenesis gene expressions descriptive of each phase. Surprisingly, we identified genes associated with host cell entry expressed throughout infection, suggesting subpopulations of Salmonella or stress-induced dysregulation. Collectively, these results highlight not only the sensitivity of Salmonella to its environment but also identify phase-specific genes that may be used as therapeutic targets to reduce infection.IMPORTANCEIdentifying novel therapeutic strategies for Salmonella infection that occur in relevant diets and over time is needed with the rise of antibiotic resistance and global shifts toward Western diets that are high in fat and low in fiber. Mice on a high-fat diet are more inflamed compared to those on a fibrous diet, creating an environment that results in more favorable energy generation for Salmonella. We observed differential gene expression across infection phases in mice over time on a high-fat diet. Together, these findings reveal the metabolic tuning of Salmonella to dietary and temporal perturbations. Research like this, which explores the dimensions of pathogen metabolic plasticity, can pave the way for rationally designed strategies to control disease.

Gut microbiome carbon and sulfur metabolisms support Salmonella during pathogen infection.

Salmonella enterica serovar Typhimurium is a pervasive enteric pathogen and an ongoing global threat to public health. Ecological studies in the Salmonella impacted gut remain underrepresented in the literature, discounting the microbiome mediated interactions that may inform Salmonella physiology during colonization and infection. To understand the microbial ecology of Salmonella remodeling of the gut microbiome, here we performed multi-omics approaches on fecal microbial communities from untreated and Salmonella -infected mice. Reconstructed genomes recruited metatranscriptomic and metabolomic data providing a strain-resolved view of the expressed metabolisms of the microbiome during Salmonella infection. This data informed possible Salmonella interactions with members of the gut microbiome that were previously uncharacterized. Salmonella- induced inflammation significantly reduced the diversity of transcriptionally active members in the gut microbiome, yet increased gene expression was detected for 7 members, with Luxibacter and Ligilactobacillus being the most active. Metatranscriptomic insights from Salmonella and other persistent taxa in the inflamed microbiome further expounded the necessity for oxidative tolerance mechanisms to endure the host inflammatory responses to infection. In the inflamed gut lactate was a key metabolite, with microbiota production and consumption reported amongst transcriptionally active members. We also showed that organic sulfur sources could be converted by gut microbiota to yield inorganic sulfur pools that become oxidized in the inflamed gut, resulting in thiosulfate and tetrathionate that supports Salmonella respiration. Advancement of pathobiome understanding beyond inferences from prior amplicon-based approaches can hold promise for infection mitigation, with the active community outlined here offering intriguing organismal and metabolic therapeutic targets.

Utilizing novel diversity estimators to quantify multiple dimensions of microbial biodiversity across domains.

BACKGROUND: Microbial ecologists often employ methods from classical community ecology to analyze microbial community diversity. However, these methods have limitations because microbial communities differ from macro-organismal communities in key ways. This study sought to quantify microbial diversity using methods that are better suited for data spanning multiple domains of life and dimensions of diversity. Diversity profiles are one novel, promising way to analyze microbial datasets. Diversity profiles encompass many other indices, provide effective numbers of diversity (mathematical generalizations of previous indices that better convey the magnitude of differences in diversity), and can incorporate taxa similarity information. To explore whether these profiles change interpretations of microbial datasets, diversity profiles were calculated for four microbial datasets from different environments spanning all domains of life as well as viruses. Both similarity-based profiles that incorporated phylogenetic relatedness and naïve (not similarity-based) profiles were calculated. Simulated datasets were used to examine the robustness of diversity profiles to varying phylogenetic topology and community composition. RESULTS: Diversity profiles provided insights into microbial datasets that were not detectable with classical univariate diversity metrics. For all datasets analyzed, there were key distinctions between calculations that incorporated phylogenetic diversity as a measure of taxa similarity and naïve calculations. The profiles also provided information about the effects of rare species on diversity calculations. Additionally, diversity profiles were used to examine thousands of simulated microbial communities, showing that similarity-based and naïve diversity profiles only agreed approximately 50% of the time in their classification of which sample was most diverse. This is a strong argument for incorporating similarity information and calculating diversity with a range of emphases on rare and abundant species when quantifying microbial community diversity. CONCLUSIONS: For many datasets, diversity profiles provided a different view of microbial community diversity compared to analyses that did not take into account taxa similarity information, effective diversity, or multiple diversity metrics. These findings are a valuable contribution to data analysis methodology in microbial ecology.

Draft Metagenome-Assembled Genome Sequence of a Novel Citricoccus Species from Agricultural Soil in Western Colorado.

Members of the genus Citricoccus are recognized as salt-tolerant soil microorganisms. Here, we report the metagenome-assembled genome sequence of a novel Citricoccus species recovered from untilled, surface agricultural soils in western Colorado.

Human-Gut Phages Harbor Sporulation Genes.

Spore-forming bacteria are prevalent in mammalian guts and have implications for host health and nutrition. The production of dormant spores is thought to play an important role in the colonization, persistence, and transmission of these bacteria. Spore formation also modifies interactions among microorganisms such as infection by phages. Recent studies suggest that phages may counter dormancy-mediated defense through the expression of phage-carried sporulation genes during infection, which can alter the transitions between active and inactive states. By mining genomes and gut-derived metagenomes, we identified sporulation genes that are preferentially carried by phages that infect spore-forming bacteria. These included genes involved in chromosome partitioning, DNA damage repair, and cell wall-associated functions. In addition, phages contained homologs of sporulation-specific transcription factors, notably spo0A, the master regulator of sporulation, which could allow phages to control the complex genetic network responsible for spore development. Our findings suggest that phages could influence the formation of bacterial spores with implications for the health of the human gut microbiome, as well as bacterial communities in other environments. IMPORTANCE Phages acquire bacterial genes and use them to alter host metabolism in ways that enhance phage fitness. To date, most auxiliary genes replace or modulate enzymes that are used by the host for nutrition or energy production. However, phage fitness is affected by all aspects of host physiology, including decisions that reduce the metabolic activity of the cell. Here, we focus on endosporulation, a complex and ancient form of dormancy found among the Bacillota that involves hundreds of genes. By coupling homology searches with host classification, we identified 31 phage-carried homologs of sporulation genes that are mostly limited to phages infecting spore-forming bacteria. Nearly one-third of the homologs recovered were regulatory genes, suggesting that phages may manipulate host genetic networks by tapping into their control elements. Our findings also suggest a mechanism by which phages can overcome the defensive strategy of dormancy, which may be involved in coevolutionary dynamics of spore-forming bacteria.

Spatial and temporal metagenomics of river compartments reveals viral community dynamics in an urban impacted stream.

Although river ecosystems comprise less than 1% of Earth's total non-glaciated area, they are critical modulators of microbially and virally orchestrated global biogeochemical cycles. However, most studies either use data that is not spatially resolved or is collected at timepoints that do not reflect the short life cycles of microorganisms. As a result, the relevance of microbiome interactions and the impacts they have over time on biogeochemical cycles are poorly understood. To assess how viral and microbial communities change over time, we sampled surface water and pore water compartments of the wastewater-impacted River Erpe in Germany every 3 hours over a 48-hour period resulting in 32 metagenomes paired to geochemical and metabolite measurements. We reconstructed 6,500 viral and 1,033 microbial genomes and found distinct communities associated with each river compartment. We show that 17% of our vMAGs clustered to viruses from other ecosystems like wastewater treatment plants and rivers. Our results also indicated that 70% of the viral community was persistent in surface waters, whereas only 13% were persistent in the pore waters taken from the hyporheic zone. Finally, we predicted linkages between 73 viral genomes and 38 microbial genomes. These putatively linked hosts included members of the Competibacteraceae, which we suggest are potential contributors to carbon and nitrogen cycling. Together, these findings demonstrate that microbial and viral communities in surface waters of this urban river can exist as stable communities along a flowing river; and raise important considerations for ecosystem models attempting to constrain dynamics of river biogeochemical cycles.

Exposing new taxonomic variation with inflammation - a murine model-specific genome database for gut microbiome researchers.

BACKGROUND: The murine CBA/J mouse model widely supports immunology and enteric pathogen research. This model has illuminated Salmonella interactions with the gut microbiome since pathogen proliferation does not require disruptive pretreatment of the native microbiota, nor does it become systemic, thereby representing an analog to gastroenteritis disease progression in humans. Despite the value to broad research communities, microbiota in CBA/J mice are not represented in current murine microbiome genome catalogs. RESULTS: Here we present the first microbial and viral genomic catalog of the CBA/J murine gut microbiome. Using fecal microbial communities from untreated and Salmonella-infected, highly inflamed mice, we performed genomic reconstruction to determine the impacts on gut microbiome membership and functional potential. From high depth whole community sequencing (~ 42.4 Gbps/sample), we reconstructed 2281 bacterial and 4516 viral draft genomes. Salmonella challenge significantly altered gut membership in CBA/J mice, revealing 30 genera and 98 species that were conditionally rare and unsampled in non-inflamed mice. Additionally, inflamed communities were depleted in microbial genes that modulate host anti-inflammatory pathways and enriched in genes for respiratory energy generation. Our findings suggest decreases in butyrate concentrations during Salmonella infection corresponded to reductions in the relative abundance in members of the Alistipes. Strain-level comparison of CBA/J microbial genomes to prominent murine gut microbiome databases identified newly sampled lineages in this resource, while comparisons to human gut microbiomes extended the host relevance of dominant CBA/J inflammation-resistant strains. CONCLUSIONS: This CBA/J microbiome database provides the first genomic sampling of relevant, uncultivated microorganisms within the gut from this widely used laboratory model. Using this resource, we curated a functional, strain-resolved view on how Salmonella remodels intact murine gut communities, advancing pathobiome understanding beyond inferences from prior amplicon-based approaches. Salmonella-induced inflammation suppressed Alistipes and other dominant members, while rarer commensals like Lactobacillus and Enterococcus endure. The rare and novel species sampled across this inflammation gradient advance the utility of this microbiome resource to benefit the broad research needs of the CBA/J scientific community, and those using murine models for understanding the impact of inflammation on the gut microbiome more generally. Video Abstract.