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Triclosan (TCS), employed as an antiseptic and disinfectant, comes into direct contact with humans through a plethora of consumer products and its rising environmental release. We have demonstrated that TCS promotes liver tumorigenesis in mice, yet the biological and molecular mechanisms by which TCS exerts its toxicity, especially in early stages of liver disease, are largely unexplored. When mice were fed a high-fat diet (HFD), we found that fatty liver and dyslipidemia are prominent early signs of liver abnormality induced by TCS. The presumably protective HFD-induced hepatic expression of the metabolic regulator fibroblast growth factor 21 (FGF21) was blunted by TCS. TCS-altered Fgf21 expression aligned with aberrant expression of genes encoding metabolic enzymes manifested as profound systemic metabolic changes that disturb homeostasis of amino acids, fatty acids, and glucose. Using a type 1 diabetic animal model, TCS potentiates and accelerates the development of steatohepatitis and fibrosis, accompanied by increased levels of hepatic lipid droplets and oxidative stress. Analysis of fecal samples revealed that HFD-fed mice exhibited a reduction in fecal species richness, and that TCS further diminished microbial diversity and shifted the bacterial community toward lower Bacteriodetes and higher Firmicutes, resembling changes in microbiota composition in nonalcoholic steatohepatitis (NASH) patients. Using reverse-genetic approaches, we demonstrate that, along with HFD, TCS induces hepatic steatosis and steatohepatitis jointly regulated by the transcription factor ATF4 and the nuclear receptor PPARα, which participate in the transcriptional regulation of the Fgf21 gene. This study provides evidence linking nutritional imbalance and exposure to TCS with the progression of NASH.

Intestinal barrier leakage constitutes a potential therapeutic target for many inflammatory diseases and represents a disease progression marker during chronic viral infections. However, the causes of altered gut barrier remain mostly unknown. Using murine infection with lymphocytic choriomeningitis virus, we demonstrate that, in contrast to an acute viral strain, a persistent viral isolate leads to long-term viral replication in hematopoietic and mesenchymal cells, but not epithelial cells (IECs), in the intestine. Viral persistence drove sustained intestinal epithelial barrier leakage, which was characterized by increased paracellular flux of small molecules and was associated with enhanced colitis susceptibility. Type I IFN signaling caused tight junction dysregulation in IECs, promoted gut microbiome shifts and enhanced intestinal CD8 T cell responses. Notably, both type I IFN receptor blockade and CD8 T cell depletion prevented infection-induced barrier leakage. Our study demonstrates that infection with a virus that persistently replicates in the intestinal mucosa increases epithelial barrier permeability and reveals type I IFNs and CD8 T cells as causative factors of intestinal leakage during chronic infections.

Aging is determined by complex interactions among genetic and environmental factors. Increasing evidence suggests that the gut microbiome lies at the core of many age-associated changes, including immune system dysregulation and susceptibility to diseases. The gut microbiota undergoes extensive changes across the lifespan, and age-related processes may influence the gut microbiota and its related metabolic alterations. The aim of this systematic review was to summarize the current literature on aging-associated alterations in diversity, composition, and functional features of the gut microbiota. We identified 27 empirical human studies of normal and successful aging suitable for inclusion. Alpha diversity of microbial taxa, functional pathways, and metabolites was higher in older adults, particularly among the oldest-old adults, compared to younger individuals. Beta diversity distances significantly differed across various developmental stages and were different even between oldest-old and younger-old adults. Differences in taxonomic composition and functional potential varied across studies, but Akkermansia was most consistently reported to be relatively more abundant with aging, whereas Faecalibacterium, Bacteroidaceae, and Lachnospiraceae were relatively reduced. Older adults have reduced pathways related to carbohydrate metabolism and amino acid synthesis; however, oldest-old adults exhibited functional differences that distinguished their microbiota from that of young-old adults, such as greater potential for short-chain fatty acid production and increased butyrate derivatives. Although a definitive interpretation is limited by the cross-sectional design of published reports, we integrated findings of microbial composition and downstream functional pathways and metabolites, offering possible explanations regarding age-related processes.

BackgroundAlterations in gut microbiota (GMB) and host metabolites have been noted in individuals with HIV. However, it remains unclear whether alterations in GMB and related functional groups contribute to disrupted host metabolite profiles in these individuals.MethodsThis study included 185 women (128 with longstanding HIV infection, 88% under antiretroviral therapy; and 57 women without HIV from the same geographic location with comparable characteristics). Stool samples were analyzed by 16S rRNA V4 region sequencing, and GMB function was inferred by PICRUSt. Plasma metabolomic profiling was performed using liquid chromatography-tandem mass spectrometry, and 133 metabolites (amino acids, biogenic amines, acylcarnitines, and lipids) were analyzed.ResultsFour predominant bacterial genera were identified as associated with HIV infection, with higher abundances of Ruminococcus and Oscillospira and lower abundances of Bifidobacterium and Collinsella in women with HIV than in those without. Women with HIV showed a distinct plasma metabolite profile, which featured elevated glycerophospholipid levels compared with those without HIV. Functional analyses also indicated that GMB lipid metabolism was enriched in women with HIV. Ruminococcus and Oscillospira were among the top bacterial genera contributing to the GMB glycerophospholipid metabolism pathway and showed positive correlations with host plasma glycerophospholipid levels. One bacterial functional capacity in the acetate and propionate biosynthesis pathway was identified to be mainly contributed by Bifidobacterium; this functional capacity was lower in women with HIV than in women without HIV.ConclusionsOur integrative analyses identified altered GMB with related functional capacities that might be associated with disrupted plasma metabolite profiles in women with HIV.

Following publication of the original paper [1], an error was reported in the third paragraph in the section "Analysis of GMB composition and its correlates" (page 3 of the PDF). The first sentence of the text should refer to Table 2, but mistakenly refers to Table 1.

Vertebrate gut microbiota provide many essential services to their host. To better understand the diversity of such services provided by gut microbiota in wild rodents, we assembled metagenome shotgun sequence data from a small mammal, the bank vole Myodes glareolus (Rodentia, Cricetidae). We were able to identify 254 metagenome assembled genomes (MAGs) that were at least 50% (n = 133 MAGs), 80% (n = 77 MAGs) or 95% (n = 44 MAGs) complete. As typical for a rodent gut microbiota, these MAGs are dominated by taxa assigned to the phyla Bacteroidetes (n = 132 MAGs) and Firmicutes (n = 80), with some Spirochaetes (n = 15) and Proteobacteria (n = 11). Based on coverage over contigs, Bacteroidetes were estimated to be most abundant group, followed by Firmicutes, Spirochaetes and Proteobacteria. These draft bacterial genomes can be used freely to determine the likely functions of gut microbiota community composition in wild rodents.

BackgroundImbalances in the gut microbial community (dysbiosis) of vertebrates have been associated with several gastrointestinal and autoimmune diseases. However, it is unclear which taxa are associated with gut dysbiosis, and if particular gut regions or specific time periods during ontogeny are more susceptible. We also know very little of this process in non-model organisms, despite an increasing realization of the general importance of gut microbiota for health.MethodsHere, we examine the changes that occur in the microbiome during dysbiosis in different parts of the gastrointestinal tract in a long-lived bird with high juvenile mortality, the ostrich (Struthio camelus). We evaluated the 16S rRNA gene composition of the ileum, cecum, and colon of 68 individuals that died of suspected enterocolitis during the first 3 months of life (diseased individuals), and of 50 healthy individuals that were euthanized as age-matched controls. We combined these data with longitudinal environmental and fecal sampling to identify potential sources of pathogenic bacteria and to unravel at which stage of development dysbiosis-associated bacteria emerge.ResultsDiseased individuals had drastically lower microbial alpha diversity and differed substantially in their microbial beta diversity from control individuals in all three regions of the gastrointestinal tract. The clear relationship between low diversity and disease was consistent across all ages in the ileum, but decreased with age in the cecum and colon. Several taxa were associated with mortality (Enterobacteriaceae, Peptostreptococcaceae, Porphyromonadaceae, Clostridium), while others were associated with health (Lachnospiraceae, Ruminococcaceae, Erysipelotrichaceae, Turicibacter, Roseburia). Environmental samples showed no evidence of dysbiosis-associated bacteria being present in either the food, water, or soil substrate. Instead, the repeated fecal sampling showed that pathobionts were already present shortly after hatching and proliferated in individuals with low microbial diversity, resulting in high mortality several weeks later.ConclusionsIdentifying the origins of pathobionts in neonates and the factors that subsequently influence the establishment of diverse gut microbiota may be key to understanding dysbiosis and host development. Video Abstract.

BackgroundThe discovery of membrane-enclosed, metabolically functional organelles in Bacteria has transformed our understanding of the subcellular complexity of prokaryotic cells. Biomineralization of magnetic nanoparticles within magnetosomes by magnetotactic bacteria (MTB) is a fascinating example of prokaryotic organelles. Magnetosomes, as nano-sized magnetic sensors in MTB, facilitate cell navigation along the local geomagnetic field, a behaviour referred to as magnetotaxis or microbial magnetoreception. Recent discovery of novel MTB outside the traditionally recognized taxonomic lineages suggests that MTB diversity across the domain Bacteria are considerably underestimated, which limits understanding of the taxonomic distribution and evolutionary origin of magnetosome organelle biogenesis.ResultsHere, we perform the most comprehensive metagenomic analysis available of MTB communities and reconstruct metagenome-assembled MTB genomes from diverse ecosystems. Discovery of MTB in acidic peatland soils suggests widespread MTB occurrence in waterlogged soils in addition to subaqueous sediments and water bodies. A total of 168 MTB draft genomes have been reconstructed, which represent nearly a 3-fold increase over the number currently available and more than double the known MTB species at the genome level. Phylogenomic analysis reveals that these genomes belong to 13 Bacterial phyla, six of which were previously not known to include MTB. These findings indicate a much wider taxonomic distribution of magnetosome organelle biogenesis across the domain Bacteria than previously thought. Comparative genome analysis reveals a vast diversity of magnetosome gene clusters involved in magnetosomal biogenesis in terms of gene content and synteny residing in distinct taxonomic lineages. Phylogenetic analyses of core magnetosome proteins in this largest available and taxonomically diverse dataset support an unexpectedly early evolutionary origin of magnetosome biomineralization, likely ancestral to the origin of the domain Bacteria.ConclusionsThese findings expand the taxonomic and phylogenetic diversity of MTB across the domain Bacteria and shed new light on the origin and evolution of microbial magnetoreception. Potential biogenesis of the magnetosome organelle in the close descendants of the last bacterial common ancestor has important implications for our understanding of the evolutionary history of bacterial cellular complexity and emphasizes the biological significance of the magnetosome organelle. Video Abstract.

BackgroundWhile the physical and chemical properties of airborne particulate matter (PM) have been extensively studied, their associated microbiome remains largely unexplored. Here, we performed a longitudinal metagenomic survey of 106 samples of airborne PM2.5 and PM10 in Beijing over a period of 6 months in 2012 and 2013, including those from several historically severe smog events.ResultsWe observed that the microbiome composition and functional potential were conserved between PM2.5 and PM10, although considerable temporal variations existed. Among the airborne microorganisms, Propionibacterium acnes, Escherichia coli, Acinetobacter lwoffii, Lactobacillus amylovorus, and Lactobacillus reuteri dominated, along with several viral species. We further identified an extensive repertoire of genes involved in antibiotic resistance and detoxification, including transporters, transpeptidases, and thioredoxins. Sample stratification based on Air Quality Index (AQI) demonstrated that many microbial species, including those associated with human, dog, and mouse feces, exhibit AQI-dependent incidence dynamics. The phylogenetic and functional diversity of air microbiome is comparable to those of soil and water environments, as its composition likely derives from a wide variety of sources.ConclusionsAirborne particulate matter accommodates rich and dynamic microbial communities, including a range of microbial elements that are associated with potential health consequences.

BackgroundMicrobial interactions shape the structure and function of microbial communities; microbial co-occurrence networks in specific environments have been widely developed to explore these complex systems, but their interconnection pattern across microbiomes in various environments at the global scale remains unexplored. Here, we have inferred an Earth microbial co-occurrence network from a communal catalog with 23,595 samples and 12,646 exact sequence variants from 14 environments in the Earth Microbiome Project dataset.ResultsThis non-random scale-free Earth microbial co-occurrence network consisted of 8 taxonomy distinct modules linked with different environments, which featured environment specific microbial co-occurrence relationships. Different topological features of subnetworks inferred from datasets trimmed into uniform size indicate distinct co-occurrence patterns in the microbiomes of various environments. The high number of specialist edges highlights that environmental specific co-occurrence relationships are essential features across microbiomes. The microbiomes of various environments were clustered into two groups, which were mainly bridged by the microbiomes of plant and animal surface. Acidobacteria Gp2 and Nisaea were identified as hubs in most of subnetworks. Negative edges proportions ranged from 1.9% in the soil subnetwork to 48.9% the non-saline surface subnetwork, suggesting various environments experience distinct intensities of competition or niche differentiation. Video abstract CONCLUSION: This investigation highlights the interconnection patterns across microbiomes in various environments and emphasizes the importance of understanding co-occurrence feature of microbiomes from a network perspective.

BACKGROUND: Transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is possible among symptom-free individuals and some patients are avoiding medically necessary healthcare visits for fear of becoming infected in the healthcare setting. Limited data are available on the point prevalence of SARS-CoV-2 infection in symptom-free U.S. healthcare workers (HCW). METHODS: A cross-sectional convenience sample of symptom-free HCWs from the metropolitan area surrounding Minneapolis and St. Paul, Minnesota was enrolled between April 20 th and June 24 th , 2020. A participant self-collected nasopharyngeal swab (NPS) was obtained. SARS-CoV-2 infection was assessed via polymerase chain reaction. Participants were queried about their willingness to repeat a self-collection NPS for diagnostic purposes. We had >95% power to detect at least one positive test if the true underlying prevalence of SARS-CoV2 was ≥1%. RESULTS: Among n=489 participants 80% were female and mean age±SD was 41±11. Participants reported being physicians (14%), nurse practitioners (8%), physician's assistants (4%), nurses (51%), medics (3%), or other which predominantly included laboratory technicians and administrative roles (22%). Exposure to a known/suspected COVID-19 case in the 14 days prior to enrollment was reported in 40% of participants. SARS-CoV-2 was not detected in any participant. Over 95% of participants reported a willingness to repeat a self-collected NP swab in the future. CONCLUSIONS: The point prevalence of SARS-CoV-2 infection was likely

Low concordance between studies that examine the role of microbiota in human diseases is a pervasive challenge that limits the capacity to identify causal relationships between host-associated microorganisms and pathology. The risk of obtaining false positives is exacerbated by wide interindividual heterogeneity in microbiota composition1, probably due to population-wide differences in human lifestyle and physiological variables2 that exert differential effects on the microbiota. Here we infer the greatest, generalized sources of heterogeneity in human gut microbiota profiles and also identify human lifestyle and physiological characteristics that, if not evenly matched between cases and controls, confound microbiota analyses to produce spurious microbial associations with human diseases. We identify alcohol consumption frequency and bowel movement quality as unexpectedly strong sources of gut microbiota variance that differ in distribution between healthy participants and participants with a disease and that can confound study designs. We demonstrate that for numerous prevalent, high-burden human diseases, matching cases and controls for confounding variables reduces observed differences in the microbiota and the incidence of spurious associations. On this basis, we present a list of host variables that we recommend should be captured in human microbiota studies for the purpose of matching comparison groups, which we anticipate will increase robustness and reproducibility in resolving the members of the gut microbiota that are truly associated with human disease.

BackgroundObesity is an established risk factor for multiple cancer types. Lower microbial richness has been linked to obesity, but human studies are inconsistent, and associations of early-life body mass index (BMI) with the fecal microbiome and metabolome are unknown.MethodsWe characterized the fecal microbiome (n = 563) and metabolome (n = 340) in the Northern Finland Birth Cohort 1966 using 16S rRNA gene sequencing and untargeted metabolomics. We estimated associations of adult BMI and BMI history with microbial features and metabolites using linear regression and Spearman correlations (rs ) and computed correlations between bacterial sequence variants and metabolites overall and by BMI category.ResultsMicrobial richness, including the number of sequence variants (rs = -0.21, P < 0.0001), decreased with increasing adult BMI but was not independently associated with BMI history. Adult BMI was associated with 56 metabolites but no bacterial genera. Significant correlations were observed between microbes in 5 bacterial phyla, including 18 bacterial genera, and metabolites in 49 of the 62 metabolic pathways evaluated. The genera with the strongest correlations with relative metabolite levels (positively and negatively) were Blautia, Oscillospira, and Ruminococcus in the Firmicutes phylum, but associations varied by adult BMI category.ConclusionsBMI is strongly related to fecal metabolite levels, and numerous associations between fecal microbial features and metabolite levels underscore the dynamic role of the gut microbiota in metabolism.ImpactCharacterizing the associations between the fecal microbiome, the fecal metabolome, and BMI, both recent and early-life exposures, provides critical background information for future research on cancer prevention and etiology.

Lyme disease is the most common vector-borne disease in the United States, with an estimated incidence of 300,000 infections annually. Antibiotic intervention cures Lyme disease in the majority of cases; however, 10 to 20% of patients develop posttreatment Lyme disease syndrome (PTLDS), a debilitating condition characterized by chronic fatigue, pain, and cognitive difficulties. The underlying mechanism responsible for PTLDS symptoms, as well as a reliable diagnostic tool, has remained elusive. We reasoned that the gut microbiome may play an important role in PTLDS given that the symptoms overlap considerably with conditions in which a dysbiotic microbiome has been observed, including mood, cognition, and autoimmune disorders. Analysis of sequencing data from a rigorously curated cohort of patients with PTLDS revealed a gut microbiome signature distinct from that of healthy control subjects, as well as from that of intensive care unit (ICU) patients. Notably, microbiome sequencing data alone were indicative of PTLDS, which presents a potential, novel diagnostic tool for PTLDS.IMPORTANCE Most patients with acute Lyme disease are cured with antibiotic intervention, but 10 to 20% endure debilitating symptoms such as fatigue, neurological complications, and myalgias after treatment, a condition known as posttreatment Lyme disease syndrome (PTLDS). The etiology of PTLDS is not understood, and objective diagnostic tools are lacking. PTLDS symptoms overlap several diseases in which patients exhibit alterations in their microbiome. We found that patients with PTLDS have a distinct microbiome signature, allowing for an accurate classification of over 80% of analyzed cases. The signature is characterized by an increase in Blautia, a decrease in Bacteroides, and other changes. Importantly, this signature supports the validity of PTLDS and is the first potential biological diagnostic tool for the disease.

Antibiotics are a mainstay of modern medicine, but as they kill their target pathogen(s), they often affect the commensal microbiota. Antibiotic-induced microbiome dysbiosis is a growing research focus and health concern, often assessed via analysis of fecal samples. However, such analysis does not inform how antibiotics influence the microbiome across the whole host or how such changes subsequently alter host chemistry. In this study, we investigated the acute (1 day postadministration) and delayed (6 days postadministration) effects of a single parenteral dose of two common antibiotics, ampicillin or vancomycin, on the global metabolome and microbiome of mice across 77 different body sites from 25 different organs. The broader-spectrum agent ampicillin had the greatest impact on the microbiota in the lower gastrointestinal tract (cecum and colon), where microbial diversity is highest. In the metabolome, the greatest effects were seen 1 day posttreatment, and changes in metabolite abundances were not confined to the gut. The local abundance of ampicillin and its metabolites correlated with increased metabolome effect size and a loss of alpha diversity versus control mice. Additionally, small peptides were elevated in the lower gastrointestinal tract of mice 1 day after antibiotic treatment. While a single parenteral dose of antibiotic did not drastically alter the microbiome, nevertheless, changes in the metabolome were observed both within and outside the gut. This study provides a framework for how whole-organism -omics approaches can be employed to understand the impact of antibiotics on the entire host.IMPORTANCE We are just beginning to understand the unintended effects of antibiotics on our microbiomes and health. In this study, we aimed to define an approach by which one could obtain a comprehensive picture of (i) how antibiotics spatiotemporally impact commensal microbes throughout the gut and (ii) how these changes influence host chemistry throughout the body. We found that just a single dose of antibiotic altered host chemistry in a variety of organs and that microbiome alterations were not uniform throughout the gut. As technological advances increase the feasibility of whole-organism studies, we argue that using these approaches can provide further insight on both the wide-ranging effects of antibiotics on health and how to restore microbial communities to mitigate these effects.

Depression is influenced by the structure, diversity, and composition of the gut microbiome. Although depression has been described previously in human immunodeficiency virus (HIV) and hepatitis C virus (HCV) monoinfections, and to a lesser extent in HIV-HCV coinfection, research on the interplay between depression and the gut microbiome in these disease states is limited. Here, we characterized the gut microbiome using 16S rRNA amplicon sequencing of fecal samples from 373 participants who underwent a comprehensive neuropsychiatric assessment and the gut metabolome on a subset of these participants using untargeted metabolomics with liquid chromatography-mass spectrometry. We observed that the gut microbiome and metabolome were distinct between HIV-positive and -negative individuals. HCV infection had a large association with the microbiome that was not confounded by drug use. Therefore, we classified the participants by HIV and HCV infection status (HIV-monoinfected, HIV-HCV coinfected, or uninfected). The three groups significantly differed in their gut microbiome (unweighted UniFrac distances) and metabolome (Bray-Curtis distances). Coinfected individuals also had lower alpha diversity. Within each of the three groups, we evaluated lifetime major depressive disorder (MDD) and current Beck Depression Inventory-II. We found that the gut microbiome differed between depression states only in coinfected individuals. Coinfected individuals with a lifetime history of MDD were enriched in primary and secondary bile acids, as well as taxa previously identified in people with MDD. Collectively, we observe persistent signatures associated with depression only in coinfected individuals, suggesting that HCV itself, or interactions between HCV and HIV, may drive HIV-related neuropsychiatric differences.IMPORTANCE The human gut microbiome influences depression. Differences between the microbiomes of HIV-infected and uninfected individuals have been described, but it is not known whether these are due to HIV itself, or to common HIV comorbidities such as HCV coinfection. Limited research has explored the influence of the microbiome on depression within these groups. Here, we characterized the microbial community and metabolome in the stools from 373 people, noting the presence of current or lifetime depression as well as their HIV and HCV infection status. Our findings provide additional evidence that individuals with HIV have different microbiomes which are further altered by HCV coinfection. In individuals coinfected with both HIV and HCV, we identified microbes and molecules that were associated with depression. These results suggest that the interplay of HIV and HCV and the gut microbiome may contribute to the HIV-associated neuropsychiatric problems.

Alterations in the gut microbiome are associated with neurocognition and related disorders, including in the context of human immunodeficiency virus (HIV) and hepatitis C virus (HCV) infection. However, the connection between the gut microbiome and cognitive decline, gauged by increased dependence in instrumental activities of daily living (IADL), remains largely unexplored in the context of these diseases. Here we characterized the gut microbiome using 16S rRNA amplicon sequencing and untargeted metabolomics with liquid chromatography-mass spectrometry from 347 people with HIV, HIV and HCV, or neither, all of whom underwent a comprehensive neuropsychiatric assessment. We observed that IADL-dependent and -independent HIV-monoinfected (HIV-positive [HIV+]/HCV-negative [HCV-]) and coinfected (HIV+/HCV+) individuals have distinct gut microbiomes. Moreover, we found that dependent individuals with HIV or HIV and HCV were enriched in Bacteroides These results may have implications for the characterization of cognitive decline, as well as the development of potential prevention and treatment strategies for individuals infected with HIV and/or HCV. Of particular interest is the possibility that dietary interventions that are known to modify the microbiome could be used to shift the microbiome toward more favorable states for preserving independence.IMPORTANCE The microbes in the gut and the chemicals they produce by metabolism have been linked to brain function. In earlier work, we showed that infection with two viruses, HIV and HCV, changed the gut microbes and metabolism in ways that were associated with a lifetime history of major depressive disorder. Here, we extend this analysis looking at a measurement of independence in daily living. We find that in individuals with HIV, whether or not they also have HCV, those who reported reduced independence were enriched in a genus of bacteria called Bacteroides This result is interesting because Bacteroides is strongly associated with diets low in carbohydrates and high in animal protein, suggesting that diet changes may help preserve independent living in people living long-term with HIV (although clinical intervention trials would be needed in order to confirm this).

Infections elicit immune adaptations to enable pathogen resistance and/or tolerance and are associated with compositional shifts of the intestinal microbiome. However, a comprehensive understanding of how infections with pathogens that exhibit distinct capability to spread and/or persist differentially change the microbiome, the underlying mechanisms, and the relative contribution of individual commensal species to immune cell adaptations is still lacking. Here, we discovered that mouse infection with a fast-spreading and persistent (but not a slow-spreading acute) isolate of lymphocytic choriomeningitis virus induced large-scale microbiome shifts characterized by increased Verrucomicrobia and reduced Firmicute/Bacteroidetes ratio. Remarkably, the most profound microbiome changes occurred transiently after infection with the fast-spreading persistent isolate, were uncoupled from sustained viral loads, and were instead largely caused by CD8 T cell responses and/or CD8 T cell-induced anorexia. Among the taxa enriched by infection with the fast-spreading virus, Akkermansia muciniphila, broadly regarded as a beneficial commensal, bloomed upon starvation and in a CD8 T cell-dependent manner. Strikingly, oral administration of A. muciniphila suppressed selected effector features of CD8 T cells in the context of both infections. Our findings define unique microbiome differences after chronic versus acute viral infections and identify CD8 T cell responses and downstream anorexia as driver mechanisms of microbial dysbiosis after infection with a fast-spreading virus. Our data also highlight potential context-dependent effects of probiotics and suggest a model in which changes in host behavior and downstream microbiome dysbiosis may constitute a previously unrecognized negative feedback loop that contributes to CD8 T cell adaptations after infections with fast-spreading and/or persistent pathogens.

Benign hepatosteatosis, affected by lipid uptake, de novo lipogenesis and fatty acid (FA) oxidation, progresses to non-alcoholic steatohepatitis (NASH) on stress and inflammation. A key macronutrient proposed to increase hepatosteatosis and NASH risk is fructose. Excessive intake of fructose causes intestinal-barrier deterioration and endotoxaemia. However, how fructose triggers these alterations and their roles in hepatosteatosis and NASH pathogenesis remain unknown. Here we show, using mice, that microbiota-derived Toll-like receptor (TLR) agonists promote hepatosteatosis without affecting fructose-1-phosphate (F1P) and cytosolic acetyl-CoA. Activation of mucosal-regenerative gp130 signalling, administration of the YAP-induced matricellular protein CCN1 or expression of the antimicrobial peptide Reg3b (beta) peptide counteract fructose-induced barrier deterioration, which depends on endoplasmic-reticulum stress and subsequent endotoxaemia. Endotoxin engages TLR4 to trigger TNF production by liver macrophages, thereby inducing lipogenic enzymes that convert F1P and acetyl-CoA to FA in both mouse and human hepatocytes.

A mysterious feature of Crohn's disease (CD) is the extra-intestinal manifestation of "creeping fat" (CrF), defined as expansion of mesenteric adipose tissue around the inflamed and fibrotic intestine. In the current study, we explore whether microbial translocation in CD serves as a central cue for CrF development. We discovered a subset of mucosal-associated gut bacteria that consistently translocated and remained viable in CrF in CD ileal surgical resections, and identified Clostridium innocuum as a signature of this consortium with strain variation between mucosal and adipose isolates, suggesting preference for lipid-rich environments. Single-cell RNA sequencing characterized CrF as both pro-fibrotic and pro-adipogenic with a rich milieu of activated immune cells responding to microbial stimuli, which we confirm in gnotobiotic mice colonized with C. innocuum. Ex vivo validation of expression patterns suggests C. innocuum stimulates tissue remodeling via M2 macrophages, leading to an adipose tissue barrier that serves to prevent systemic dissemination of bacteria.

In this cross-sectional study, we describe the composition and diversity of the gut microbiota among undernourished children living in urban slums of Mumbai, India, and determine how nutritional status, including anthropometric measurements, dietary intakes from complementary foods, feeding practices, and micronutrient concentrations, is associated with their gut microbiota. We collected rectal swabs from children aged 10 to 18 months living in urban slums of Mumbai participating in a randomized controlled feeding trial and conducted 16S rRNA sequencing to determine the composition of the gut microbiota. Across the study cohort, Proteobacteria dominated the gut microbiota at over 80% relative abundance, with Actinobacteria representation at

We present ReDU ( https://redu.ucsd.edu/ ), a system for metadata capture of public mass spectrometry-based metabolomics data, with validated controlled vocabularies. Systematic capture of knowledge enables the reanalysis of public data and/or co-analysis of one's own data. ReDU enables multiple types of analyses, including finding chemicals and associated metadata, comparing the shared and different chemicals between groups of samples, and metadata-filtered, repository-scale molecular networking.

Staphylococcus aureus bacteremia (SaB) causes significant disease in humans, carrying mortality rates of ∼25%. The ability to rapidly predict SaB patient responses and guide personalized treatment regimens could reduce mortality. Here, we present a resource of SaB prognostic biomarkers. Integrating proteomic and metabolomic techniques enabled the identification of >10,000 features from >200 serum samples collected upon clinical presentation. We interrogated the complexity of serum using multiple computational strategies, which provided a comprehensive view of the early host response to infection. Our biomarkers exceed the predictive capabilities of those previously reported, particularly when used in combination. Last, we validated the biological contribution of mortality-associated pathways using a murine model of SaB. Our findings represent a starting point for the development of a prognostic test for identifying high-risk patients at a time early enough to trigger intensive monitoring and interventions.

Determining factors that contribute to interindividual and intra-individual variability in pharmacokinetics (PKs) and drug metabolism is essential for the optimal use of drugs in humans. Intestinal microbes are important contributors to variability; however, such gut microbe-drug interactions and the clinical significance of these interactions are still being elucidated. Traditional PKs can be complemented by untargeted mass spectrometry coupled with molecular networking to study the intricacies of drug metabolism. To show the utility of molecular networking on metabolism we investigated the impact of a 7-day course of cefprozil on cytochrome P450 (CYP) activity using a modified Cooperstown cocktail and assessed plasma, urine, and fecal data by targeted and untargeted metabolomics and molecular networking in healthy volunteers. This prospective study revealed that cefprozil decreased the activities of CYP1A2, CYP2C19, and CYP3A, decreased alpha diversity and increased interindividual microbiome variability. We further demonstrate a relationship between the loss of microbiome alpha diversity caused by cefprozil and increased drug and metabolite formation in fecal samples. Untargeted metabolomics/molecular networking revealed several omeprazole metabolites that we hypothesize may be metabolized by both CYP2C19 and bacteria from the gut microbiome. Our observations are consistent with the hypothesis that factors that perturb the gut microbiome, such as antibiotics, alter drug metabolism and ultimately drug efficacy and toxicity but that these effects are most strongly revealed on a per individual basis.

Microbial contamination during long-term confinements of space exploration presents potential risks for both crew members and spacecraft life support systems. A novel swab kit was used to sample various surfaces from a submerged, closed, analog habitat to characterize the microbial populations. Samples were collected from various locations across the habitat which were constructed from various surface materials (linoleum, dry wall, particle board, glass, and metal), and microbial populations were examined by culture, quantitative PCR (qPCR), microbiome 16S rRNA gene sequencing, and shotgun metagenomics. Propidium monoazide (PMA)-treated samples identified the viable/intact microbial population of the habitat. The cultivable microbial population ranged from below the detection limit to 106 CFU/sample, and their identity was characterized using Sanger sequencing. Both 16S rRNA amplicon and shotgun sequencing were used to characterize the microbial dynamics, community profiles, and functional attributes (metabolism, virulence, and antimicrobial resistance). The 16S rRNA amplicon sequencing revealed abundance of viable (after PMA treatment) Actinobacteria (Brevibacterium, Nesternkonia, Mycobacterium, Pseudonocardia, and Corynebacterium), Firmicutes (Virgibacillus, Staphylococcus, and Oceanobacillus), and Proteobacteria (especially Acinetobacter) on linoleum, dry wall, and particle board (LDP) surfaces, while members of Firmicutes (Leuconostocaceae) and Proteobacteria (Enterobacteriaceae) were high on the glass/metal surfaces. Nonmetric multidimensional scaling determined from both 16S rRNA and metagenomic analyses revealed differential microbial species on LDP surfaces and glass/metal surfaces. The shotgun metagenomic sequencing of samples after PMA treatment showed bacterial predominance of viable Brevibacterium (53.6%), Brachybacterium (7.8%), Pseudonocardia (9.9%), Mycobacterium (3.7%), and Staphylococcus (2.1%), while fungal analyses revealed Aspergillus and Penicillium dominance.IMPORTANCE This study provides the first assessment of monitoring cultivable and viable microorganisms on surfaces within a submerged, closed, analog habitat. The results of the analyses presented herein suggest that the surface material plays a role in microbial community structure, as the microbial populations differed between LDP and metal/glass surfaces. The metal/glass surfaces had less-complex community, lower bioburden, and more closely resembled the controls. These results indicated that material choice is crucial when building closed habitats, even if they are simply analogs. Finally, while a few species were associated with previously cultivated isolates from the International Space Station and MIR spacecraft, the majority of the microbial ecology of the submerged analog habitat differs greatly from that of previously studied analog habitats.

Vancomycin-resistant Enterococcus faecium (VREfm) is an emerging antibiotic-resistant pathogen. Strain-level investigations are beginning to reveal the molecular mechanisms used by VREfm to colonize regions of the human bowel. However, the role of commensal bacteria during VREfm colonization, in particular following antibiotic treatment, remains largely unknown. We employed amplicon 16S rRNA gene sequencing and metabolomics in a murine model system to try and investigate functional roles of the gut microbiome during VREfm colonization. First-order taxonomic shifts between Bacteroidetes and Tenericutes within the gut microbial community composition were detected both in response to pretreatment using ceftriaxone and to subsequent VREfm challenge. Using neural networking approaches to find cooccurrence profiles of bacteria and metabolites, we detected key metabolome features associated with butyric acid during and after VREfm colonization. These metabolite features were associated with Bacteroides, indicative of a transition toward a preantibiotic naive microbiome. This study shows the impacts of antibiotics on the gut ecosystem and the progression of the microbiome in response to colonization with VREfm. Our results offer insights toward identifying potential nonantibiotic alternatives to eliminate VREfm through metabolic reengineering to preferentially select for BacteroidesIMPORTANCE This study demonstrates the importance and power of linking bacterial composition profiling with metabolomics to find the interactions between commensal gut bacteria and a specific pathogen. Knowledge from this research will inform gut microbiome engineering strategies, with the aim of translating observations from animal models to human-relevant therapeutic applications.

BackgroundSome studies have suggested that in people with type 2 diabetes, Roux-en-Y gastric bypass has therapeutic effects on metabolic function that are independent of weight loss.MethodsWe evaluated metabolic regulators of glucose homeostasis before and after matched (approximately 18%) weight loss induced by gastric bypass (surgery group) or diet alone (diet group) in 22 patients with obesity and diabetes. The primary outcome was the change in hepatic insulin sensitivity, assessed by infusion of insulin at low rates (stages 1 and 2 of a 3-stage hyperinsulinemic euglycemic pancreatic clamp). Secondary outcomes were changes in muscle insulin sensitivity, beta-cell function, and 24-hour plasma glucose and insulin profiles.ResultsWeight loss was associated with increases in mean suppression of glucose production from baseline, by 7.04 μmol per kilogram of fat-free mass per minute (95% confidence interval [CI], 4.74 to 9.33) in the diet group and by 7.02 μmol per kilogram of fat-free mass per minute (95% CI, 3.21 to 10.84) in the surgery group during clamp stage 1, and by 5.39 (95% CI, 2.44 to 8.34) and 5.37 (95% CI, 2.41 to 8.33) μmol per kilogram of fat-free mass per minute in the two groups, respectively, during clamp stage 2; there were no significant differences between the groups. Weight loss was associated with increased insulin-stimulated glucose disposal, from 30.5±15.9 to 61.6±13.0 μmol per kilogram of fat-free mass per minute in the diet group and from 29.4±12.6 to 54.5±10.4 μmol per kilogram of fat-free mass per minute in the surgery group; there was no significant difference between the groups. Weight loss increased beta-cell function (insulin secretion relative to insulin sensitivity) by 1.83 units (95% CI, 1.22 to 2.44) in the diet group and by 1.11 units (95% CI, 0.08 to 2.15) in the surgery group, with no significant difference between the groups, and it decreased the areas under the curve for 24-hour plasma glucose and insulin levels in both groups, with no significant difference between the groups. No major complications occurred in either group.ConclusionsIn this study involving patients with obesity and type 2 diabetes, the metabolic benefits of gastric bypass surgery and diet were similar and were apparently related to weight loss itself, with no evident clinically important effects independent of weight loss. (Funded by the National Institutes of Health and others; ClinicalTrials.gov number, NCT02207777.).

Background Several small-scale animal studies have suggested that gut microbiota and blood pressure (BP) are linked. However, results from human studies remain scarce and conflicting. We wanted to elucidate the multivariable-adjusted association between gut metagenome and BP in a large, representative, well-phenotyped population sample. We performed a focused analysis to examine the previously reported inverse associations between sodium intake and Lactobacillus abundance and between Lactobacillus abundance and BP. Methods and Results We studied a population sample of 6953 Finns aged 25 to 74 years (mean age, 49.2±12.9 years; 54.9% women). The participants underwent a health examination, which included BP measurement, stool collection, and 24-hour urine sampling (N=829). Gut microbiota was analyzed using shallow shotgun metagenome sequencing. In age- and sex-adjusted models, the α (within-sample) and β (between-sample) diversities of taxonomic composition were strongly related to BP indexes (P

Microbial contamination during long-term confinements of space exploration presents potential risks for both crew members and spacecraft life support systems. A novel swab kit was used to sample various surfaces from a submerged, closed, analog habitat to characterize the microbial populations. Samples were collected from various locations across the habitat which were constructed from various surface materials (linoleum, dry wall, particle board, glass, and metal), and microbial populations were examined by culture, quantitative PCR (qPCR), microbiome 16S rRNA gene sequencing, and shotgun metagenomics. Propidium monoazide (PMA)-treated samples identified the viable/intact microbial population of the habitat. The cultivable microbial population ranged from below the detection limit to 106 CFU/sample, and their identity was characterized using Sanger sequencing. Both 16S rRNA amplicon and shotgun sequencing were used to characterize the microbial dynamics, community profiles, and functional attributes (metabolism, virulence, and antimicrobial resistance). The 16S rRNA amplicon sequencing revealed abundance of viable (after PMA treatment) Actinobacteria (Brevibacterium, Nesternkonia, Mycobacterium, Pseudonocardia, and Corynebacterium), Firmicutes (Virgibacillus, Staphylococcus, and Oceanobacillus), and Proteobacteria (especially Acinetobacter) on linoleum, dry wall, and particle board (LDP) surfaces, while members of Firmicutes (Leuconostocaceae) and Proteobacteria (Enterobacteriaceae) were high on the glass/metal surfaces. Nonmetric multidimensional scaling determined from both 16S rRNA and metagenomic analyses revealed differential microbial species on LDP surfaces and glass/metal surfaces. The shotgun metagenomic sequencing of samples after PMA treatment showed bacterial predominance of viable Brevibacterium (53.6%), Brachybacterium (7.8%), Pseudonocardia (9.9%), Mycobacterium (3.7%), and Staphylococcus (2.1%), while fungal analyses revealed Aspergillus and Penicillium dominance.IMPORTANCE This study provides the first assessment of monitoring cultivable and viable microorganisms on surfaces within a submerged, closed, analog habitat. The results of the analyses presented herein suggest that the surface material plays a role in microbial community structure, as the microbial populations differed between LDP and metal/glass surfaces. The metal/glass surfaces had less-complex community, lower bioburden, and more closely resembled the controls. These results indicated that material choice is crucial when building closed habitats, even if they are simply analogs. Finally, while a few species were associated with previously cultivated isolates from the International Space Station and MIR spacecraft, the majority of the microbial ecology of the submerged analog habitat differs greatly from that of previously studied analog habitats.

SummaryThe software pipeline SHOGUN profiles known taxonomic and gene abundances of short-read shotgun metagenomics sequencing data. The pipeline is scalable, modular and flexible. Data analysis and transformation steps can be run individually or together in an automated workflow. Users can easily create new reference databases and can select one of three DNA alignment tools, ranging from ultra-fast low-RAM k-mer-based database search to fully exhaustive gapped DNA alignment, to best fit their analysis needs and computational resources. The pipeline includes an implementation of a published method for taxonomy assignment disambiguation with empirical Bayesian redistribution. The software is installable via the conda resource management framework, has plugins for the QIIME2 and QIITA packages and produces both taxonomy and gene abundance profile tables with a single command, thus promoting convenient and reproducible metagenomics research.Availability and implementationhttps://github.com/knights-lab/SHOGUN.

Microbial diversity in the cystic fibrosis (CF) lung decreases over decades as pathogenic bacteria such as Pseudomonas aeruginosa take over. The dynamics of the CF microbiome and metabolome over shorter time frames, however, remain poorly studied. Here, we analyze paired microbiome and metabolome data from 594 sputum samples collected over 401 days from six adult CF subjects (subject mean = 179 days) through periods of clinical stability and 11 CF pulmonary exacerbations (CFPE). While microbiome profiles were personalized (permutational multivariate analysis of variance [PERMANOVA] r 2 = 0.79, P

Successful rearing of fish in hatcheries is critical for conservation, recreational fishing, commercial fishing through wild stock enhancements, and aquaculture production. Flowthrough (FT) hatcheries require more water than recirculating aquaculture systems (RAS), which enable up to 99% of their water to be recycled, thus significantly reducing environmental impacts. Here, we evaluated the biological and physical microbiome interactions of three Atlantic salmon hatcheries (RAS n = 2, FT n = 1). Gill, skin, and digesta from six juvenile fish along with tank biofilms and water were sampled from tanks in each of the hatcheries (60 fish across 10 tanks) to assess the built environment and mucosal microbiota using 16S rRNA gene sequencing. The water and tank biofilm had more microbial richness than fish mucus, while skin and digesta from RAS fish had 2 times the richness of FT fish. Body sites each had unique microbiomes (P

Long-range sequencing information is required for haplotype phasing, de novo assembly, and structural variation detection. Current long-read sequencing technologies can provide valuable long-range information but at a high cost with low accuracy and high DNA input requirements. We have developed a single-tube Transposase Enzyme Linked Long-read Sequencing (TELL-seq) technology, which enables a low-cost, high-accuracy, and high-throughput short-read second-generation sequencer to generate over 100 kb of long-range sequencing information with as little as 0.1 ng input material. In a PCR tube, millions of clonally barcoded beads are used to uniquely barcode long DNA molecules in an open bulk reaction without dilution and compartmentation. The barcoded linked-reads are used to successfully assemble genomes ranging from microbes to human. These linked-reads also generate megabase-long phased blocks and provide a cost-effective tool for detecting structural variants in a genome, which are important to identify compound heterozygosity in recessive Mendelian diseases and discover genetic drivers and diagnostic biomarkers in cancers.

Many tools for dealing with compositional ' 'omics' data produce feature-wise values that can be ranked in order to describe features' associations with some sort of variation. These values include differentials (which describe features' associations with specified covariates) and feature loadings (which describe features' associations with variation along a given axis in a biplot). Although prior work has discussed the use of these 'rankings' as a starting point for exploring the log-ratios of particularly high- or low-ranked features, such exploratory analyses have previously been done using custom code to visualize feature rankings and the log-ratios of interest. This approach is laborious, prone to errors and raises questions about reproducibility. To address these problems we introduce Qurro, a tool that interactively visualizes a plot of feature rankings (a 'rank plot') alongside a plot of selected features' log-ratios within samples (a 'sample plot'). Qurro's interface includes various controls that allow users to select features from along the rank plot to compute a log-ratio; this action updates both the rank plot (through highlighting selected features) and the sample plot (through displaying the current log-ratios of samples). Here, we demonstrate how this unique interface helps users explore feature rankings and log-ratios simply and effectively.

QIIME 2 is a completely re-engineered microbiome bioinformatics platform based on the popular QIIME platform, which it has replaced. QIIME 2 facilitates comprehensive and fully reproducible microbiome data science, improving accessibility to diverse users by adding multiple user interfaces. QIIME 2 can be combined with Qiita, an open-source web-based platform, to re-use available data for meta-analysis. The following basic protocol describes how to install QIIME 2 on a single computer and analyze microbiome sequence data, from processing of raw DNA sequence reads through generating publishable interactive figures. These interactive figures allow readers of a study to interact with data with the same ease as its authors, advancing microbiome science transparency and reproducibility. We also show how plug-ins developed by the community to add analysis capabilities can be installed and used with QIIME 2, enhancing various aspects of microbiome analyses-e.g., improving taxonomic classification accuracy. Finally, we illustrate how users can perform meta-analyses combining different datasets using readily available public data through Qiita. In this tutorial, we analyze a subset of the Early Childhood Antibiotics and the Microbiome (ECAM) study, which tracked the microbiome composition and development of 43 infants in the United States from birth to 2 years of age, identifying microbiome associations with antibiotic exposure, delivery mode, and diet. For more information about QIIME 2, see https://qiime2.org. To troubleshoot or ask questions about QIIME 2 and microbiome analysis, join the active community at https://forum.qiime2.org. © 2020 The Authors. Basic Protocol: Using QIIME 2 with microbiome data Support Protocol: Further microbiome analyses.

Changing ocean conditions driven by anthropogenic activities may have a negative impact on fisheries by increasing stress and disease. To understand how environment and host biology drives mucosal microbiomes in a marine fish, we surveyed five body sites (gill, skin, digesta, gastrointestinal tract [GI], and pyloric ceca) from 229 Pacific chub mackerel, Scomber japonicus, collected across 38 time points spanning 1 year from the Scripps Institution of Oceanography Pier (La Jolla, CA). Mucosal sites had unique microbial communities significantly different from the surrounding seawater and sediment communities with over 10 times more total diversity than seawater. The external surfaces of skin and gill were more similar to seawater, while digesta was more similar to sediment. Alpha and beta diversity of the skin and gill was explained by environmental and biological factors, specifically, sea surface temperature, chlorophyll a, and fish age, consistent with an exposure gradient relationship. We verified that seasonal microbial changes were not confounded by regional migration of chub mackerel subpopulations by nanopore sequencing a 14,769-bp region of the 16,568-bp mitochondria across all temporal fish specimens. A cosmopolitan pathogen, Photobacterium damselae, was prevalent across multiple body sites all year but highest in the skin, GI, and digesta between June and September, when the ocean is warmest. The longitudinal fish microbiome study evaluates the extent to which the environment and host biology drives mucosal microbial ecology and establishes a baseline for long-term surveys linking environment stressors to mucosal health of wild marine fish.IMPORTANCE Pacific chub mackerel, Scomber japonicus, are one of the largest and most economically important fisheries in the world. The fish is harvested for both human consumption and fish meal. Changing ocean conditions driven by anthropogenic stressors like climate change may negatively impact fisheries. One mechanism for this is through disease. As waters warm and chemistry changes, the microbial communities associated with fish may change. In this study, we performed a holistic analysis of all mucosal sites on the fish over a 1-year time series to explore seasonal variation and to understand the environmental drivers of the microbiome. Understanding seasonality in the fish microbiome is also applicable to aquaculture production for producers to better understand and predict when disease outbreaks may occur based on changing environmental conditions in the ocean.

Microbial genomes are available at an ever-increasing pace, as cultivation and sequencing become cheaper and obtaining metagenome-assembled genomes (MAGs) becomes more effective. Phylogenetic placement methods to contextualize hundreds of thousands of genomes must thus be efficiently scalable and sensitive from closely related strains to divergent phyla. We present PhyloPhlAn 3.0, an accurate, rapid, and easy-to-use method for large-scale microbial genome characterization and phylogenetic analysis at multiple levels of resolution. PhyloPhlAn 3.0 can assign genomes from isolate sequencing or MAGs to species-level genome bins built from >230,000 publically available sequences. For individual clades of interest, it reconstructs strain-level phylogenies from among the closest species using clade-specific maximally informative markers. At the other extreme of resolution, it scales to large phylogenies comprising >17,000 microbial species. Examples including Staphylococcus aureus isolates, gut metagenomes, and meta-analyses demonstrate the ability of PhyloPhlAn 3.0 to support genomic and metagenomic analyses.

Animal work indicates exposure to air pollutants may alter the composition of the gut microbiota. This study examined relationships between air pollutants and the gut microbiome in young adults residing in Southern California. Our results demonstrate significant associations between exposure to air pollutants and the composition of the gut microbiome using whole-genome sequencing. Higher exposure to 24-hour O3 was associated with lower Shannon diversity index, higher Bacteroides caecimuris, and multiple gene pathways, including L-ornithine de novo biosynthesis as well as pantothenate and coenzyme A biosynthesis I. Among other pollutants, higher NO2 exposure was associated with fewer taxa, including higher Firmicutes. The percent variation in gut bacterial composition that was explained by air pollution exposure was up to 11.2% for O3 concentrations, which is large compared to the effect size for many other covariates reported in healthy populations. This study provides the first evidence of significant associations between exposure to air pollutants and the compositional and functional profile of the human gut microbiome. These results identify O3 as an important pollutant that may alter the human gut microbiome.

Lifestyle factors, such as diet, strongly influence the structure, diversity, and composition of the microbiome. While we have witnessed over the last several years a resurgence of interest in fermented foods, no study has specifically explored the effects of their consumption on gut microbiota in large cohorts. To assess whether the consumption of fermented foods is associated with a systematic signal in the gut microbiome and metabolome, we used a multi-omic approach (16S rRNA amplicon sequencing, metagenomic sequencing, and untargeted mass spectrometry) to analyze stool samples from 6,811 individuals from the American Gut Project, including 115 individuals specifically recruited for their frequency of fermented food consumption for a targeted 4-week longitudinal study. We observed subtle but statistically significant differences between consumers and nonconsumers in beta diversity as well as differential taxa between the two groups. We found that the metabolome of fermented food consumers was enriched with conjugated linoleic acid (CLA), a putatively health-promoting molecule. Cross-omic analyses between metagenomic sequencing and mass spectrometry suggest that CLA may be driven by taxa associated with fermented food consumers. Collectively, we found modest yet persistent signatures associated with fermented food consumption that appear present in multiple -omic types which motivate further investigation of how different types of fermented food impact the gut microbiome and overall health.IMPORTANCE Public interest in the effects of fermented food on the human gut microbiome is high, but limited studies have explored the association between fermented food consumption and the gut microbiome in large cohorts. Here, we used a combination of omics-based analyses to study the relationship between the microbiome and fermented food consumption in thousands of people using both cross-sectional and longitudinal data. We found that fermented food consumers have subtle differences in their gut microbiota structure, which is enriched in conjugated linoleic acid, thought to be beneficial. The results suggest that further studies of specific kinds of fermented food and their impacts on the microbiome and health will be useful.

Microbiome-based disease classification depends on well-validated disease-specific models or a priori organismal markers. These are lacking for many diseases. Here, we present an alternative, search-based strategy for disease detection and classification, which detects diseased samples via their outlier novelty versus a database of samples from healthy subjects and then compares these to databases of samples from patients. Our strategy's precision, sensitivity, and speed outperform model-based approaches. In addition, it is more robust to platform heterogeneity and to contamination in 16S rRNA gene amplicon data sets. This search-based strategy shows promise as an important first step in microbiome big-data-based diagnosis.IMPORTANCE Here, we present a search-based strategy for disease detection and classification, which detects diseased samples via their outlier novelty versus a database of samples from healthy subjects and then compares them to databases of samples from patients. This approach enables the identification of microbiome states associated with disease even in the presence of different cohorts, multiple sequencing platforms, or significant contamination.

Even high-quality collection and reporting of study metadata in microbiome studies can lead to various forms of inadvertently missing or mischaracterized information that can alter the interpretation or outcome of the studies, especially with nonmodel organisms. Metabolomic profiling of fecal microbiome samples can provide empirical insight into unanticipated confounding factors that are not possible to obtain even from detailed care records. We illustrate this point using data from cheetahs from the San Diego Zoo Safari Park. The metabolomic characterization indicated that one cheetah had to be moved from the non-antibiotic-exposed group to the antibiotic-exposed group. The detection of the antibiotic in this second cheetah was likely due to grooming interactions with the cheetah that was administered antibiotics. Similarly, because transit time for stool is variable, fecal samples within the first few days of antibiotic prescription do not all contain detected antibiotics, and the microbiome is not yet affected. These insights significantly altered the way the samples were grouped for analysis (antibiotic versus no antibiotic) and the subsequent understanding of the effect of the antibiotics on the cheetah microbiome. Metabolomics also revealed information about numerous other medications and provided unexpected dietary insights that in turn improved our understanding of the molecular patterns on the impact on the community microbial structure. These results suggest that untargeted metabolomic data provide empirical evidence to correct records and aid in the monitoring of the health of nonmodel organisms in captivity, although we also expect that these methods may be appropriate for other social animals, such as cats.IMPORTANCE Metabolome-informed analyses can enhance omics studies by enabling the correct partitioning of samples by identifying hidden confounders inadvertently misrepresented or omitted from carefully curated metadata. We demonstrate here the utility of metabolomics in a study characterizing the microbiome associated with liver disease in cheetahs. Metabolome-informed reinterpretation of metagenome and metabolome profiles factored in an unexpected transfer of antibiotics, preventing misinterpretation of the data. Our work suggests that untargeted metabolomics can be used to verify, augment, and correct sample metadata to support improved grouping of sample data for microbiome analyses, here for nonmodel organisms in captivity. However, the techniques also suggest a path forward for correcting clinical information in microbiome studies more broadly to enable higher-precision analyses.

BackgroundCommon bean and cowpea contain about 25% protein and 25% fiber, and are recommended as complementary foods in sub-Saharan Africa.ObjectiveThe objective of this study was to determine if a daily legume supplement given to Malawian infants aged 6 to 12 mo alters the 16S configuration of the fecal microbiota as read out by amplicon sequence variants (ASVs).MethodsThis study was conducted within the context of a randomized, double-blind, controlled clinical trial to assess whether cowpea or common bean supplementation reduced intestinal permeability or increased linear growth. There were 2 village clusters in which the study was conducted. Fresh stool collections were flash frozen from 236 infants at ≤6 time points. The stools were sequenced using Earth Microbiome project protocols and data were processed using Qiime and Qiita, open-source, validated software packages. α-diversity was measured using the Faith's test. The 16S configuration was characterized by determining the weighted UniFrac distances of the ASVs and comparing them using permutational multivariate ANOVA.ResultsAmong the 1249 samples analyzed, the α-diversity of the fecal microbiome was unchanged among subjects after initiation of legume supplementation. Neither cowpea nor common bean altered the overall 16S configuration at any age. The 16S configuration differed between children with adequate and poor linear growth aged from 6 to 9 mo, but no specific ASVs differed in relative abundance. The 16S configuration differed between children with normal and abnormal intestinal permeability at 9 mo, but no specific ASVs differed in relative abundance. Among categorical characteristics of the population associated with different 16S configurations, village cluster was most pronounced.ConclusionLegume supplementation in breastfed, rural African infants did not affect the structure of the gut microbial communities until the children were aged 9 mo. This trial was registered at clinicaltrials.gov as NCT02472262.

Systematic characterization of the cancer microbiome provides the opportunity to develop techniques that exploit non-human, microorganism-derived molecules in the diagnosis of a major human disease. Following recent demonstrations that some types of cancer show substantial microbial contributions1-10, we re-examined whole-genome and whole-transcriptome sequencing studies in The Cancer Genome Atlas11 (TCGA) of 33 types of cancer from treatment-naive patients (a total of 18,116 samples) for microbial reads, and found unique microbial signatures in tissue and blood within and between most major types of cancer. These TCGA blood signatures remained predictive when applied to patients with stage Ia-IIc cancer and cancers lacking any genomic alterations currently measured on two commercial-grade cell-free tumour DNA platforms, despite the use of very stringent decontamination analyses that discarded up to 92.3% of total sequence data. In addition, we could discriminate among samples from healthy, cancer-free individuals (n = 69) and those from patients with multiple types of cancer (prostate, lung, and melanoma; 100 samples in total) solely using plasma-derived, cell-free microbial nucleic acids. This potential microbiome-based oncology diagnostic tool warrants further exploration.

A mosaic of cross-phylum chemical interactions occurs between all metazoans and their microbiomes. A number of molecular families that are known to be produced by the microbiome have a marked effect on the balance between health and disease1-9. Considering the diversity of the human microbiome (which numbers over 40,000 operational taxonomic units10), the effect of the microbiome on the chemistry of an entire animal remains underexplored. Here we use mass spectrometry informatics and data visualization approaches11-13 to provide an assessment of the effects of the microbiome on the chemistry of an entire mammal by comparing metabolomics data from germ-free and specific-pathogen-free mice. We found that the microbiota affects the chemistry of all organs. This included the amino acid conjugations of host bile acids that were used to produce phenylalanocholic acid, tyrosocholic acid and leucocholic acid, which have not previously been characterized despite extensive research on bile-acid chemistry14. These bile-acid conjugates were also found in humans, and were enriched in patients with inflammatory bowel disease or cystic fibrosis. These compounds agonized the farnesoid X receptor in vitro, and mice gavaged with the compounds showed reduced expression of bile-acid synthesis genes in vivo. Further studies are required to confirm whether these compounds have a physiological role in the host, and whether they contribute to gut diseases that are associated with microbiome dysbiosis.

Amyloids are a class of protein with unique self-aggregation properties, and their aberrant accumulation can lead to cellular dysfunctions associated with neurodegenerative diseases. While genetic and environmental factors can influence amyloid formation, molecular triggers and/or facilitators are not well defined. Growing evidence suggests that non-identical amyloid proteins may accelerate reciprocal amyloid aggregation in a prion-like fashion. While humans encode ~30 amyloidogenic proteins, the gut microbiome also produces functional amyloids. For example, curli are cell surface amyloid proteins abundantly expressed by certain gut bacteria. In mice overexpressing the human amyloid α-synuclein (αSyn), we reveal that colonization with curli-producing Escherichia coli promotes αSyn pathology in the gut and the brain. Curli expression is required for E. coli to exacerbate αSyn-induced behavioral deficits, including intestinal and motor impairments. Purified curli subunits accelerate αSyn aggregation in biochemical assays, while oral treatment of mice with a gut-restricted amyloid inhibitor prevents curli-mediated acceleration of pathology and behavioral abnormalities. We propose that exposure to microbial amyloids in the gastrointestinal tract can accelerate αSyn aggregation and disease in the gut and the brain.

Human gut microbiomes are known to change with age, yet the relative value of human microbiomes across the body as predictors of age, and prediction robustness across populations is unknown. In this study, we tested the ability of the oral, gut, and skin (hand and forehead) microbiomes to predict age in adults using random forest regression on data combined from multiple publicly available studies, evaluating the models in each cohort individually. Intriguingly, the skin microbiome provides the best prediction of age (mean ± standard deviation, 3.8 ± 0.45 years, versus 4.5 ± 0.14 years for the oral microbiome and 11.5 ± 0.12 years for the gut microbiome). This also agrees with forensic studies showing that the skin microbiome predicts postmortem interval better than microbiomes from other body sites. Age prediction models constructed from the hand microbiome generalized to the forehead and vice versa, across cohorts, and results from the gut microbiome generalized across multiple cohorts (United States, United Kingdom, and China). Interestingly, taxa enriched in young individuals (18 to 30 years) tend to be more abundant and more prevalent than taxa enriched in elderly individuals (>60 yrs), suggesting a model in which physiological aging occurs concomitantly with the loss of key taxa over a lifetime, enabling potential microbiome-targeted therapeutic strategies to prevent aging.IMPORTANCE Considerable evidence suggests that the gut microbiome changes with age or even accelerates aging in adults. Whether the age-related changes in the gut microbiome are more or less prominent than those for other body sites and whether predictions can be made about a person's age from a microbiome sample remain unknown. We therefore combined several large studies from different countries to determine which body site's microbiome could most accurately predict age. We found that the skin was the best, on average yielding predictions within 4 years of chronological age. This study sets the stage for future research on the role of the microbiome in accelerating or decelerating the aging process and in the susceptibility for age-related diseases.

Oral microbiome dysbiosis has been associated with various local and systemic human diseases such as dental caries, periodontal disease, obesity, and cardiovascular disease. Bacterial composition may be affected by age, oral health, diet, and geography, although information about the natural variation found in the general public is still lacking. In this study, citizen-scientists used a crowdsourcing model to obtain oral bacterial composition data from guests at the Denver Museum of Nature & Science to determine if previously suspected oral microbiome associations with an individual's demographics, lifestyle, and/or genetics are robust and generalizable enough to be detected within a general population. Consistent with past research, we found bacterial composition to be more diverse in youth microbiomes when compared to adults. Adult oral microbiomes were predominantly impacted by oral health habits, while youth microbiomes were impacted by biological sex and weight status. The oral pathogen Treponema was detected more commonly in adults without recent dentist visits and in obese youth. Additionally, oral microbiomes from participants of the same family were more similar to each other than to oral microbiomes from non-related individuals. These results suggest that previously reported oral microbiome associations are observable in a human population containing the natural variation commonly found in the general public. Furthermore, these results support the use of crowdsourced data as a valid methodology to obtain community-based microbiome data.

In humans, the composition of microbial communities differs among body sites and between habitats within a single site. Patterns of variation in the distribution of organisms across time and space are referred to as "biogeography." The human oral cavity is a critical observatory for exploring microbial biogeography because it is spatially structured, easily accessible, and its microbiota has been linked to the promotion of both health and disease. The biogeographic features of microbial communities residing in spatially distinct, but ecologically similar, environments on the human body, including the subgingival crevice, have not yet been adequately explored. The purpose of this paper is twofold. First, we seek to provide the dental community with a primer on biogeographic theory, highlighting its relevance to the study of the human oral cavity. We summarize what is known about the biogeographic variation of dental caries and periodontitis and postulate that disease occurrence reflects spatial patterning in the composition and structure of oral microbial communities. Second, we present a number of methods that investigators can use to test specific hypotheses using biogeographic theory. To anchor our discussion, we apply each method to a case study and examine the spatial variation of the human subgingival microbiota in 2 individuals. Our case study suggests that the composition of subgingival communities may conform to an anterior-to-posterior gradient within the oral cavity. The gradient appears to be structured by both deterministic and nondeterministic processes, although additional work is needed to confirm these findings. A better understanding of biogeographic patterns and processes will lead to improved efficacy of dental interventions targeting the oral microbiota.