Appendectomy and Long-term Colorectal Cancer Incidence, Overall and by Tumor Fusobacterium nucleatum Status.

OBJECTIVE: To test hypotheses that appendectomy history might lower long-term colorectal cancer risk and that the risk reduction might be strong for tumors enriched with Fusobacterium nucleatum, bacterial species implicated in colorectal carcinogenesis. BACKGROUND: The absence of the appendix, an immune system organ and a possible reservoir of certain pathogenic microbes, may affect the intestinal microbiome, thereby altering long-term colorectal cancer risk. METHODS: Utilizing databases of prospective cohort studies, namely the Nurses' Health Study and the Health Professionals Follow-up Study, we examined the association of appendectomy history with colorectal cancer incidence overall and subclassified by the amount of tumor tissue Fusobacterium nucleatum​​ (Fusobacterium animalis). We used an inverse probability weighted multivariable-adjusted duplication-method Cox proportional hazards regression model. RESULTS: During the follow-up of 139,406 participants (2,894,060 person-years), we documented 2811 incident colorectal cancer cases, of which 1065 cases provided tissue F. nucleatum analysis data. The multivariable-adjusted hazard ratio of appendectomy for overall colorectal cancer incidence was 0.92 (95% CI, 0.84-1.01). Appendectomy was associated with lower F. nucleatum-positive cancer incidence (multivariable-adjusted hazard ratio, 0.53; 95% CI, 0.33-0.85; P=0.0079), but not F. nucleatum-negative cancer incidence (multivariable-adjusted hazard ratio, 0.98; 95% CI, 0.83-1.14), suggesting a differential association by F. nucleatum status (Pheterogeneity=0.015). This differential association appeared to persist in various participant/patient strata including tumor location and microsatellite instability status. CONCLUSIONS: Appendectomy likely lowers the future long-term incidence of F. nucleatum-positive (but not F. nucleatum-negative) colorectal cancer. Our findings do not support the existing hypothesis that appendectomy may increase colorectal cancer risk.

Optimized model architectures for deep learning on genomic data.

The success of deep learning in various applications depends on task-specific architecture design choices, including the types, hyperparameters, and number of layers. In computational biology, there is no consensus on the optimal architecture design, and decisions are often made using insights from more well-established fields such as computer vision. These may not consider the domain-specific characteristics of genome sequences, potentially limiting performance. Here, we present GenomeNet-Architect, a neural architecture design framework that automatically optimizes deep learning models for genome sequence data. It optimizes the overall layout of the architecture, with a search space specifically designed for genomics. Additionally, it optimizes hyperparameters of individual layers and the model training procedure. On a viral classification task, GenomeNet-Architect reduced the read-level misclassification rate by 19%, with 67% faster inference and 83% fewer parameters, and achieved similar contig-level accuracy with ~100 times fewer parameters compared to the best-performing deep learning baselines.

Gut microbiome and metabolome profiling in Framingham heart study reveals cholesterol-metabolizing bacteria.

Accumulating evidence suggests that cardiovascular disease (CVD) is associated with an altered gut microbiome. Our understanding of the underlying mechanisms has been hindered by lack of matched multi-omic data with diagnostic biomarkers. To comprehensively profile gut microbiome contributions to CVD, we generated stool metagenomics and metabolomics from 1,429 Framingham Heart Study participants. We identified blood lipids and cardiovascular health measurements associated with microbiome and metabolome composition. Integrated analysis revealed microbial pathways implicated in CVD, including flavonoid, γ-butyrobetaine, and cholesterol metabolism. Species from the Oscillibacter genus were associated with decreased fecal and plasma cholesterol levels. Using functional prediction and in vitro characterization of multiple representative human gut Oscillibacter isolates, we uncovered conserved cholesterol-metabolizing capabilities, including glycosylation and dehydrogenation. These findings suggest that cholesterol metabolism is a broad property of phylogenetically diverse Oscillibacter spp., with potential benefits for lipid homeostasis and cardiovascular health.

Gut microbiome composition and metabolic activity in women with diverticulitis.

The etiopathogenesis of diverticulitis, among the most common gastrointestinal diagnoses, remains largely unknown. By leveraging stool collected within a large prospective cohort, we performed shotgun metagenomic sequencing and untargeted metabolomics profiling among 121 women diagnosed with diverticulitis requiring antibiotics or hospitalizations (cases), matched to 121 women without diverticulitis (controls) according to age and race. Overall microbial community structure and metabolomic profiles differed in diverticulitis cases compared to controls, including enrichment of pro-inflammatory Ruminococcus gnavus, 1,7-dimethyluric acid, and histidine-related metabolites, and depletion of butyrate-producing bacteria and anti-inflammatory ceramides. Through integrated multi-omic analysis, we detected covarying microbial and metabolic features, such as Bilophila wadsworthia and bile acids, specific to diverticulitis. Additionally, we observed that microbial composition modulated the protective association between a prudent fiber-rich diet and diverticulitis. Our findings offer insights into the perturbations in inflammation-related microbial and metabolic signatures associated with diverticulitis, supporting the potential of microbial-based diagnostics and therapeutic targets.

A host-microbiota interactome reveals extensive transkingdom connectivity.

The myriad microorganisms that live in close association with humans have diverse effects on physiology, yet the molecular bases for these impacts remain mostly unknown1-3. Classical pathogens often invade host tissues and modulate immune responses through interactions with human extracellular and secreted proteins (the 'exoproteome'). Commensal microorganisms may also facilitate niche colonization and shape host biology by engaging host exoproteins; however, direct exoproteome-microbiota interactions remain largely unexplored. Here we developed and validated a novel technology, BASEHIT, that enables proteome-scale assessment of human exoproteome-microbiome interactions. Using BASEHIT, we interrogated more than 1.7 million potential interactions between 519 human-associated bacterial strains from diverse phylogenies and tissues of origin and 3,324 human exoproteins. The resulting interactome revealed an extensive network of transkingdom connectivity consisting of thousands of previously undescribed host-microorganism interactions involving 383 strains and 651 host proteins. Specific binding patterns within this network implied underlying biological logic; for example, conspecific strains exhibited shared exoprotein-binding patterns, and individual tissue isolates uniquely bound tissue-specific exoproteins. Furthermore, we observed dozens of unique and often strain-specific interactions with potential roles in niche colonization, tissue remodelling and immunomodulation, and found that strains with differing host interaction profiles had divergent interactions with host cells in vitro and effects on the host immune system in vivo. Overall, these studies expose a previously unexplored landscape of molecular-level host-microbiota interactions that may underlie causal effects of indigenous microorganisms on human health and disease.

Discovering and exploring the hidden diversity of human gut viruses using highly enriched virome samples.

Viruses are an abundant and crucial component of the human microbiome, but accurately discovering them via metagenomics is still challenging. Currently, the available viral reference genomes poorly represent the diversity in microbiome samples, and expanding such a set of viral references is difficult. As a result, many viruses are still undetectable through metagenomics even when considering the power of de novo metagenomic assembly and binning, as viruses lack universal markers. Here, we describe a novel approach to catalog new viral members of the human gut microbiome and show how the resulting resource improves metagenomic analyses. We retrieved >3,000 viral-like particles (VLP) enriched metagenomic samples (viromes), evaluated the efficiency of the enrichment in each sample to leverage the viromes of highest purity, and applied multiple analysis steps involving assembly and comparison with hundreds of thousands of metagenome-assembled genomes to discover new viral genomes. We reported over 162,000 viral sequences passing quality control from thousands of gut metagenomes and viromes. The great majority of the retrieved viral sequences (~94.4%) were of unknown origin, most had a CRISPR spacer matching host bacteria, and four of them could be detected in >50% of a set of 18,756 gut metagenomes we surveyed. We included the obtained collection of sequences in a new MetaPhlAn 4.1 release, which can quantify reads within a metagenome matching the known and newly uncovered viral diversity. Additionally, we released the viral database for further virome and metagenomic studies of the human microbiome.

Integrated annotation prioritizes metabolites with bioactivity in inflammatory bowel disease.

Microbial biochemistry is central to the pathophysiology of inflammatory bowel diseases (IBD). Improved knowledge of microbial metabolites and their immunomodulatory roles is thus necessary for diagnosis and management. Here, we systematically analyzed the chemical, ecological, and epidemiological properties of ~82k metabolic features in 546 Integrative Human Microbiome Project (iHMP/HMP2) metabolomes, using a newly developed methodology for bioactive compound prioritization from microbial communities. This suggested >1000 metabolic features as potentially bioactive in IBD and associated ~43% of prevalent, unannotated features with at least one well-characterized metabolite, thereby providing initial information for further characterization of a significant portion of the fecal metabolome. Prioritized features included known IBD-linked chemical families such as bile acids and short-chain fatty acids, and less-explored bilirubin, polyamine, and vitamin derivatives, and other microbial products. One of these, nicotinamide riboside, reduced colitis scores in DSS-treated mice. The method, MACARRoN, is generalizable with the potential to improve microbial community characterization and provide therapeutic candidates.

Timing and duration of dog walking and dog owner's chronotype in relation to incident depression risk among middle to older-aged female nurses.

BACKGROUND: We examined associations between dog ownership, morning dog walking and its timing and duration, and depression risk in female nurses, exploring effect modification by chronotype. We hypothesized that dog ownership and morning walking with the dog are associated with lower odds of depression, and that the latter is particularly beneficial for evening chronotypes by helping them to synchronize their biological clock with the solar system. METHODS: 26,169 depression-free US women aged 53-72 from the Nurses' Health Study 2 (NHS2) were prospectively followed from 2017-2019. We used age- and multivariable-adjusted logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (95%CIs) for depression according to dog ownership, and morning dog walking, duration, and timing. RESULTS: Overall, there was no association between owning a dog (ORvs_no_pets = 1.12, 95%CI = 0.91-1.37), morning dog walking (ORvs_not = 0.87, 95%CI = 0.64-1.18), or the duration (OR>30min vs. ≤15mins = 0.68, 95%CI = 0.35-1.29) or timing of morning dog walks (ORafter9am vs. before7am = 1.06, 95%CI = 0.54-2.05) and depression. Chronotype of dog owners appeared to modify these associations. Compared to women of the same chronotype but without pets, dog owners with evening chronotypes had a significantly increased odds of depression (OR = 1.60, 95%CI = 1.12-2.29), whereas morning chronotypes did not (OR = 0.94, 95%CI = 0.71-1.23). Further, our data suggested that evening chronotypes benefited more from walking their dog themselves in the morning (OR = 0.75, 95%CI = 0.46-1.23, Pintx = 0.064;) than morning chronotypes. CONCLUSIONS: Overall, dog ownership was not associated with depression risk though it was increased among evening chronotypes. Walking their dog in the morning might help evening chronotypes to lower their odds of depression, though more data are needed to confirm this finding.

Gut-resident microorganisms and their genes are associated with cognition and neuroanatomy in children.

Emerging evidence implicates gut microbial metabolism in neurodevelopmental disorders, but its influence on typical neurodevelopment has not been explored in detail. We investigated the relationship between the microbiome and neuroanatomy and cognition of 381 healthy children, demonstrating that differences in microbial taxa and genes are associated with overall cognitive function and the size of brain regions. Using a combination of statistical and machine learning models, we showed that species including Alistipes obesi, Blautia wexlerae, and Ruminococcus gnavus were enriched or depleted in children with higher cognitive function scores. Microbial metabolism of short-chain fatty acids was also associated with cognitive function. In addition, machine models were able to predict the volume of brain regions from microbial profiles, and taxa that were important in predicting cognitive function were also important for predicting individual brain regions and specific subscales of cognitive function. These findings provide potential biomarkers of neurocognitive development and may enable development of targets for early detection and intervention.

Challenges and opportunities in sharing microbiome data and analyses.

Microbiome data, metadata and analytical workflows have become 'big' in terms of volume and complexity. Although the infrastructure and technologies to share data have been established, the interdisciplinary and multi-omic nature of the field can make resources difficult to identify and use. Following best practices for data deposition requires substantial effort, with sometimes little obvious reward. Gaps remain where microbiome-specific resources for data sharing or reproducibility do not yet exist. We outline available best practices, challenges to their adoption and opportunities in data sharing in microbiome research. We showcase examples of best practices and advocate for their enforcement and incentivization for data sharing. This includes recognition of data curation and sharing endeavours by individuals, institutions, journals and funders. Opportunities for progress include enabling microbiome-specific databases to incorporate future methods for data analysis, integration and reuse.

Identification and targeting of microbial putrescine acetylation in bloodstream infections.

The growth of antimicrobial resistance (AMR) has highlighted an urgent need to identify bacterial pathogenic functions that may be targets for clinical intervention. Although severe bacterial infections profoundly alter host metabolism, prior studies have largely ignored alterations in microbial metabolism in this context. Performing metabolomics on patient and mouse plasma samples, we identify elevated levels of bacterially-derived N-acetylputrescine during gram-negative bloodstream infections (BSI), with higher levels associated with worse clinical outcomes. We discover that SpeG is the bacterial enzyme responsible for acetylating putrescine and show that blocking its activity reduces bacterial proliferation and slows pathogenesis. Reduction of SpeG activity enhances bacterial membrane permeability and results in increased intracellular accumulation of antibiotics, allowing us to overcome AMR of clinical isolates both in culture and in vivo. This study highlights how studying pathogen metabolism in the natural context of infection can reveal new therapeutic strategies for addressing challenging infections.

Diet and gut microbial associations in irritable bowel syndrome according to disease subtype.

The role of diet and the gut microbiome in the etiopathogenesis of irritable bowel syndrome (IBS) is not fully understood. Therefore, we investigated the interplay between dietary risk factors and gut microbiota in IBS subtypes using a food frequency questionnaire and stool metagenome data from 969 participants aged 18-65 years in the ZOE PREDICT 1 study, an intervention study designed to predict postprandial metabolic responses. We identified individuals with IBS subtype according to the Rome III criteria based on predominant bowel habits during symptom onset: diarrhea (i.e. looser), constipation (i.e. harder), and mixed. Participants with IBS-D (n = 59) consumed more healthy plant-based foods (e.g. whole grains, leafy vegetables) and fiber, while those with IBS-C (n = 49) tended to consume more unhealthy plant-based foods (e.g. refined grains, fruit juice) than participants without IBS (n = 797). Microbial diversity was nominally lower in patients with IBS-D than in participants without IBS or with IBS-C. Using multivariable-adjusted linear regression, we identified specific microbiota variations in IBS subtypes, including slight increases in pro-inflammatory taxa in IBS-C (e.g. Escherichia coli) and loss of strict anaerobes in IBS-D (e.g. Faecalibacterium prausnitzii). Our analysis also revealed intriguing evidence of interactions between diet and Faecalibacterium prausnitzii. The positive associations between fiber and iron intake and IBS-diarrhea were stronger among individuals with a higher relative abundance of Faecalibacterium prausnitzii, potentially driven by carbohydrate metabolic pathways, including the superpathway of ß-D-glucuronide and D-glucuronate degradation. In conclusion, our findings suggest subtype-specific variations in dietary habits, gut microbial composition and function, and diet-microbiota interactions in IBS, providing insights into potential microbiome-informed dietary interventions.

A two-cohort study on the association between the gut microbiota and bone density, microarchitecture, and strength.

The gut microbiome affects the inflammatory environment through effects on T-cells, which influence the production of immune mediators and inflammatory cytokines that stimulate osteoclastogenesis and bone loss in mice. However, there are few large human studies of the gut microbiome and skeletal health. We investigated the association between the human gut microbiome and high resolution peripheral quantitative computed tomography (HR-pQCT) scans of the radius and tibia in two large cohorts; Framingham Heart Study (FHS [n=1227, age range: 32 - 89]), and the Osteoporosis in Men Study (MrOS [n=836, age range: 78 - 98]). Stool samples from study participants underwent amplification and sequencing of the V4 hypervariable region of the 16S rRNA gene. The resulting 16S rRNA sequencing data were processed separately for each cohort, with the DADA2 pipeline incorporated in the16S bioBakery workflow. Resulting amplicon sequence variants were assigned taxonomies using the SILVA reference database. Controlling for multiple covariates, we tested for associations between microbial taxa abundances and HR-pQCT measures using general linear models as implemented in microbiome multivariable association with linear model (MaAslin2). Abundance of 37 microbial genera in FHS, and 4 genera in MrOS, were associated with various skeletal measures (false discovery rate [FDR] ≤ 0.1) including the association of DTU089 with bone measures, which was independently replicated in the two cohorts. A meta-analysis of the taxa-bone associations further revealed (FDR ≤ 0.25) that greater abundances of the genera; Akkermansia and DTU089, were associated with lower radius total vBMD, and tibia cortical vBMD respectively. Conversely, higher abundances of the genera; Lachnospiraceae NK4A136 group, and Faecalibacterium were associated with greater tibia cortical vBMD. We also investigated functional capabilities of microbial taxa by testing for associations between predicted (based on 16S rRNA amplicon sequence data) metabolic pathways abundance and bone phenotypes in each cohort. While there were no concordant functional associations observed in both cohorts, a meta-analysis revealed 8 pathways including the super-pathway of histidine, purine, and pyrimidine biosynthesis, associated with bone measures of the tibia cortical compartment. In conclusion, our findings suggest that there is a link between the gut microbiome and skeletal metabolism.

Interplay between diet, circulating indolepropionate concentrations and cardiometabolic health in US populations.

OBJECTIVES: To identify indolepropionate (IPA)-predicting gut microbiota species, investigate potential diet-microbiota interactions, and examine the prospective associations of circulating IPA concentrations with type 2 diabetes (T2D) and coronary heart disease (CHD) risk in free-living individuals. DESIGN: We included 287 men from the Men's Lifestyle Validation Study, a substudy of the Health Professionals Follow-Up Study (HPFS), who provided up to two pairs of faecal samples and two blood samples. Diet was assessed using 7-day diet records. Associations between plasma concentrations of tryptophan metabolites and T2D CHD risk were examined in 13 032 participants from Nurses' Health Study (NHS), NHSII and HPFS. RESULTS: We identified 17 microbial species whose abundance was significantly associated with plasma IPA concentrations. A significant association between higher tryptophan intake and higher IPA concentrations was only observed among men who had higher fibre intake and a higher microbial species score consisting of the 17 species (p-interaction<0.01). Dietary and plasma concentrations of tryptophan and most kynurenine pathway metabolites were positively associated with T2D risk (HRQ5 vs Q1 ranged from 1.17 to 1.46) while a significant inverse association was found for IPA (HRQ5 vs Q1 (95% CI) 0.70 (0.56 to 0.88)). No associations were found in CHD for any plasma tryptophan metabolites. CONCLUSIONS: Specific microbial species and dietary fibre jointly predicted significantly higher circulating IPA concentrations at higher tryptophan intake. Dietary and plasma tryptophan, as well as its kynurenine pathway metabolites, demonstrated divergent associations from those for IPA, which was significantly predictive of lower risk of T2D.

Association Between Bowel Movement Pattern and Cognitive Function: Prospective Cohort Study and a Metagenomic Analysis of the Gut Microbiome.

BACKGROUND AND OBJECTIVES: Little is known regarding the association between intestinal motility patterns and cognitive function in individuals who are baseline cognitively healthy. The gut microbiome may contribute to the association. We examined the association between bowel movement (BM) pattern and cognitive function and explored the role of the gut microbiome in explaining this association. METHODS: In this prospective study, we leveraged 3 cohort studies, Nurses' Health Study (NHS), NHSII, and Health Professionals Follow-Up Study (HPFS). Participants reported BM frequency and subjective cognitive function. In a subset of NHSII participants, we assessed cognitive function using an objective neuropsychological battery. We profiled the gut microbiome in a subset of participants using whole-genome shotgun metagenomics. General linear models, Poisson regression, and logistic regression were used to quantify the association of BM frequency with different cognitive measurements. RESULTS: We followed 112,753 men and women (women: 87.6%) with a mean age of 67.2 years at baseline (NHS: 76 years, NHSII: 59 years, HPFS: 75 years) for a median follow-up of 4 years (NHSII and HPFS: 4 years, NHS: 2 years). Compared with those with BM once daily, participants with BM frequency every 3+ days had significantly worse objective cognitive function, equivalent to 3.0 (95% confidence interval [CI],1.2-4.7) years of chronological cognitive aging. We observed similar J-shape dose-response relationships of BM frequency with the odds of subjective cognitive decline and the likelihood of having more subsequent subjective cognitive complaints (both p nonlinearity < 0.001). BM frequencies of every 3+ days and ≥twice/day, compared with once daily, were associated with the odds ratios of subjective cognitive decline of 1.73 (95% CI 1.60-1.86) and 1.37 (95% CI 1.33-1.44), respectively. BM frequency and subjective cognitive decline were significantly associated with the overall gut microbiome configuration (both p < 0.005) and specific microbial species in the 515 participants with microbiome data. Butyrate-producing microbial species were depleted in those with less frequent BM and worse cognition, whereas a higher abundance of proinflammatory species was associated with BM frequency of ≥twice/day and worse cognition. DISCUSSION: Lower BM frequency was associated with worse cognitive function. The gut microbial dysbiosis may be a mechanistic link underlying the association.

BugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signatures.

The literature of human and other host-associated microbiome studies is expanding rapidly, but systematic comparisons among published results of host-associated microbiome signatures of differential abundance remain difficult. We present BugSigDB, a community-editable database of manually curated microbial signatures from published differential abundance studies accompanied by information on study geography, health outcomes, host body site and experimental, epidemiological and statistical methods using controlled vocabulary. The initial release of the database contains >2,500 manually curated signatures from >600 published studies on three host species, enabling high-throughput analysis of signature similarity, taxon enrichment, co-occurrence and coexclusion and consensus signatures. These data allow assessment of microbiome differential abundance within and across experimental conditions, environments or body sites. Database-wide analysis reveals experimental conditions with the highest level of consistency in signatures reported by independent studies and identifies commonalities among disease-associated signatures, including frequent introgression of oral pathobionts into the gut.

Profiling novel lateral gene transfer events in the human microbiome.

Lateral gene transfer (LGT) is an important mechanism for genome diversification in microbial populations, including the human microbiome. While prior work has surveyed LGT events in human-associated microbial isolate genomes, the scope and dynamics of novel LGT events arising in personal microbiomes are not well understood, as there are no widely adopted computational methods to detect, quantify, and characterize LGT from complex microbial communities. We addressed this by developing, benchmarking, and experimentally validating a computational method (WAAFLE) to profile novel LGT events from assembled metagenomes. Applying WAAFLE to >2K human metagenomes from diverse body sites, we identified >100K putative high-confidence but previously uncharacterized LGT events (~2 per assembled microbial genome-equivalent). These events were enriched for mobile elements (as expected), as well as restriction-modification and transport functions typically associated with the destruction of foreign DNA. LGT frequency was quantifiably influenced by biogeography, the phylogenetic similarity of the involved taxa, and the ecological abundance of the donor taxon. These forces manifest as LGT networks in which hub species abundant in a community type donate unequally with their close phylogenetic neighbors. Our findings suggest that LGT may be a more ubiquitous process in the human microbiome than previously described. The open-source WAAFLE implementation, documentation, and data from this work are available at http://huttenhower.sph.harvard.edu/waafle.

Alterations in the gut microbiome implicate key taxa and metabolic pathways across inflammatory arthritis phenotypes.

Musculoskeletal diseases affect up to 20% of adults worldwide. The gut microbiome has been implicated in inflammatory conditions, but large-scale metagenomic evaluations have not yet traced the routes by which immunity in the gut affects inflammatory arthritis. To characterize the community structure and associated functional processes driving gut microbial involvement in arthritis, the Inflammatory Arthritis Microbiome Consortium investigated 440 stool shotgun metagenomes comprising 221 adults diagnosed with rheumatoid arthritis, ankylosing spondylitis, or psoriatic arthritis and 219 healthy controls and individuals with joint pain without an underlying inflammatory cause. Diagnosis explained about 2% of gut taxonomic variability, which is comparable in magnitude to inflammatory bowel disease. We identified several candidate microbes with differential carriage patterns in patients with elevated blood markers for inflammation. Our results confirm and extend previous findings of increased carriage of typically oral and inflammatory taxa and decreased abundance and prevalence of typical gut clades, indicating that distal inflammatory conditions, as well as local conditions, correspond to alterations to the gut microbial composition. We identified several differentially encoded pathways in the gut microbiome of patients with inflammatory arthritis, including changes in vitamin B salvage and biosynthesis and enrichment of iron sequestration. Although several of these changes characteristic of inflammation could have causal roles, we hypothesize that they are mainly positive feedback responses to changes in host physiology and immune homeostasis. By connecting taxonomic alternations to functional alterations, this work expands our understanding of the shifts in the gut ecosystem that occur in response to systemic inflammation during arthritis.

Metagenomic assessment of gut microbial communities and risk of severe COVID-19.

BACKGROUND: The gut microbiome is a critical modulator of host immunity and is linked to the immune response to respiratory viral infections. However, few studies have gone beyond describing broad compositional alterations in severe COVID-19, defined as acute respiratory or other organ failure. METHODS: We profiled 127 hospitalized patients with COVID-19 (n = 79 with severe COVID-19 and 48 with moderate) who collectively provided 241 stool samples from April 2020 to May 2021 to identify links between COVID-19 severity and gut microbial taxa, their biochemical pathways, and stool metabolites. RESULTS: Forty-eight species were associated with severe disease after accounting for antibiotic use, age, sex, and various comorbidities. These included significant in-hospital depletions of Fusicatenibacter saccharivorans and Roseburia hominis, each previously linked to post-acute COVID syndrome or "long COVID," suggesting these microbes may serve as early biomarkers for the eventual development of long COVID. A random forest classifier achieved excellent performance when tasked with classifying whether stool was obtained from patients with severe vs. moderate COVID-19, a finding that was externally validated in an independent cohort. Dedicated network analyses demonstrated fragile microbial ecology in severe disease, characterized by fracturing of clusters and reduced negative selection. We also observed shifts in predicted stool metabolite pools, implicating perturbed bile acid metabolism in severe disease. CONCLUSIONS: Here, we show that the gut microbiome differentiates individuals with a more severe disease course after infection with COVID-19 and offer several tractable and biologically plausible mechanisms through which gut microbial communities may influence COVID-19 disease course. Further studies are needed to expand upon these observations to better leverage the gut microbiome as a potential biomarker for disease severity and as a target for therapeutic intervention.