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Culture-independent analyses of microbial communities have progressed dramatically in the last decade, particularly due to advances in methods for biological profiling via shotgun metagenomics. Opportunities for improvement continue to accelerate, with greater access to multi-omics, microbial reference genomes, and strain-level diversity. To leverage these, we present bioBakery 3, a set of integrated, improved methods for taxonomic, strain-level, functional, and phylogenetic profiling of metagenomes newly developed to build on the largest set of reference sequences now available. Compared to current alternatives, MetaPhlAn 3 increases the accuracy of taxonomic profiling, and HUMAnN 3 improves that of functional potential and activity. These methods detected novel disease-microbiome links in applications to CRC (1262 metagenomes) and IBD (1635 metagenomes and 817 metatranscriptomes). Strain-level profiling of an additional 4077 metagenomes with StrainPhlAn 3 and PanPhlAn 3 unraveled the phylogenetic and functional structure of the common gut microbe Ruminococcus bromii , previously described by only 15 isolate genomes. With open-source implementations and cloud-deployable reproducible workflows, the bioBakery 3 platform can help researchers deepen the resolution, scale, and accuracy of multi-omic profiling for microbial community studies.

The relationship between gut microbial metabolism and mental health is one of the most intriguing and controversial topics in microbiome research. Bidirectional microbiota–gut–brain communication has mostly been explored in animal models, with human research lagging behind. Large-scale metagenomics studies could facilitate the translational process, but their interpretation is hampered by a lack of dedicated reference databases and tools to study the microbial neuroactive potential. Surveying a large microbiome population cohort (Flemish Gut Flora Project, n  = 1,054) with validation in independent data sets ( n total  = 1,070), we studied how microbiome features correlate with host quality of life and depression. Butyrate-producing Faecalibacterium and Coprococcus bacteria were consistently associated with higher quality of life indicators. Together with Dialister , Coprococcus spp. were also depleted in depression, even after correcting for the confounding effects of antidepressants. Using a module-based analytical framework, we assembled a catalogue of neuroactive potential of sequenced gut prokaryotes. Gut–brain module analysis of faecal metagenomes identified the microbial synthesis potential of the dopamine metabolite 3,4-dihydroxyphenylacetic acid as correlating positively with mental quality of life and indicated a potential role of microbial γ-aminobutyric acid production in depression. Our results provide population-scale evidence for microbiome links to mental health, while emphasizing confounder importance. Correlation of microbiome features with host quality of life and depression identified specific taxa and microbial pathways in two independent, large population cohorts, identifying links between microbial neuroactive potential and depression.

Although the composition and functional potential of the human gut microbiota evolve over the lifespan, kinship has been identified as a key covariate of microbial community diversification. However, to date, sharing of microbiota features within families has mostly been assessed between parents and their direct offspring. Here we investigate the potential transmission and persistence of familial microbiome patterns and microbial genotypes in a family cohort ( n  = 102) spanning 3 to 5 generations over the same female bloodline. We observe microbiome community composition associated with kinship, with seven low abundant genera displaying familial distribution patterns. While kinship and current cohabitation emerge as closely entangled variables, our explorative analyses of microbial genotype distribution and transmission estimates point at the latter as a key covariate of strain dissemination. Highest potential transmission rates are estimated between sisters and mother–daughter pairs, decreasing with increasing daughter’s age and being higher among cohabiting pairs than those living apart. Although rare, we detect potential transmission events spanning three and four generations, primarily involving species of the genera Alistipes and Bacteroides . Overall, while our analyses confirm the existence of family-bound microbiome community profiles, transmission or co-acquisition of bacterial strains appears to be strongly linked to cohabitation. Quantitative metagenomic analyses of gut microbiomes reveals kinship, together with current cohabitation, as drivers of microbial community transmission and persistence between family members over three to five generations.

This study is the first to determine the safety and tolerance in humans of a butyrate-producing Clostridium cluster IV next-generation probiotic. Advances in gut microbiota research have triggered interest in developing colon butyrate producers as next-generation probiotics. Butyricicoccus pullicaecorum 25-3 T is one such potential probiotic, with demonstrated safety in vitro as well as in animal models. Here, we produced an encapsulated B. pullicaecorum formulation that largely preserved its viability over an 8-month storage period at 4°C. Administration of this formulation to healthy volunteers allowed us to establish the intervention as safe and well tolerated. The probiotic intervention did not cause disruptive alterations in the composition or metabolic activity of health-associated microbiota. The results presented pave the way for the exploration of the impact of the strain on microbiota alterations in a clinical setting. Advances in gut microbiota research have triggered interest in developing colon butyrate producers as niche-specific next-generation probiotics, targeted at increasing colon butyrate production and countering disease-associated microbiota alterations. Crucial steps in the development of next-generation probiotics are the design of formulations with a reasonable shelf life as well as the safety demonstration of an intervention in healthy volunteers. One such potential next-generation butyrate-producing probiotic is Butyricicoccus pullicaecorum 25-3 T , with demonstrated safety in in vitro as well as animal models. Here, we examined the strain’s safety, tolerability, and impact on microbiota composition and metabolic activity in healthy volunteers in a randomized, double-blind, placebo-controlled crossover study in 30 healthy volunteers. The study design consisted of two 4-week intervention periods (10 8 CFU B. pullicaecorum [treatment] or maltodextrin [placebo] per day) with a 3-week washout in between. We assessed adverse events, blood parameters (primary endpoints), and fecal microbiota composition and metabolite profiles (secondary endpoints). The number of reported adverse events during the B. pullicaecorum treatment was similar to that of placebo intervention, as were observed changes in blood chemistry parameters, bowel habits, and fecal calprotectin concentrations. Administration of the strain did not induce any disruptive effect in microbiota composition or metabolic activity. In this first human intervention trial with a butyrate-producing Clostridium cluster IV isolate, we demonstrated B. pullicaecorum 25-3 T administration to be both safe and well tolerated by healthy participants. This safety study paves the way for the further development of the strain as a next-generation probiotic. IMPORTANCE This study is the first to determine the safety and tolerance in humans of a butyrate-producing Clostridium cluster IV next-generation probiotic. Advances in gut microbiota research have triggered interest in developing colon butyrate producers as next-generation probiotics. Butyricicoccus pullicaecorum 25-3 T is one such potential probiotic, with demonstrated safety in vitro as well as in animal models. Here, we produced an encapsulated B. pullicaecorum formulation that largely preserved its viability over an 8-month storage period at 4°C. Administration of this formulation to healthy volunteers allowed us to establish the intervention as safe and well tolerated. The probiotic intervention did not cause disruptive alterations in the composition or metabolic activity of health-associated microbiota. The results presented pave the way for the exploration of the impact of the strain on microbiota alterations in a clinical setting.

Objective Multiple sclerosis (MS) is a heterogenous, inflammatory disease of the central nervous system. Microbiota alterations in MS versus healthy controls (HC) are observed, but results are inconsistent. We studied diversity, enterotypes, and specific gut microbial taxa variation between MS and HC, and between MS subgroups. Methods Amplicon sequencing of the 16S ribosomal RNA V4 region (Illumina MiSeq) was used to evaluate alpha and beta diversity, enterotypes, and relative taxa abundances on stool samples. MS subgroups were based on phenotype, disease course modifiers, and treatment status. Results were controlled for recently identified confounders of microbiota composition. Results Ninety‐eight MS patients and 120 HC were included. Microbial richness was lower in interferon‐treated (RRMS_I, N = 24) and untreated relapsing–remitting MS during relapse (RRMS_R, N = 4) when compared to benign (BMS, N = 20; Z = −3.07, Pcorr = 0.032 and Z = −2.68, Pcorr = 0.055) and primary progressive MS (PPMS, N = 26; Z = −2.39, Pcorr = 0.062 and Z = −2.26, Pcorr = 0.071). HC (N = 120) and active untreated MS (RRMS_U, N = 24) showed intermediate microbial richness. Enterotypes were associated with clinical subgroups (N = 218, χ2 = 36.10, P = 0.002), with Bacteroides 2 enterotype being more prevalent in RRMS_I. Butyricicoccus abundance was lower in PPMS than in RRMS_U (Z = −3.00, Pcorr = 0.014) and BMS (Z = −2.56, Pcorr = 0.031), lower in RRMS_I than in BMS (Z = −2.50, Pcorr = 0.034) and RRMS_U (Z = −2.91, Pcorr = 0.013), and inversely correlated with self‐reported physical symptoms (rho = −0.400, Pcorr = 0.001) and disease severity (rho = −0.223, P = 0.027). Interpretation These results emphasize the importance of phenotypic subcategorization in MS‐microbiome research, possibly explaining previous result heterogeneity, while showing the potential for specific microbiome‐based biomarkers for disease activity and severity.

Quantitive microbiome profiling reveals that total microbial load is an important determinant of enterotypes and may be a key driver of microbiota alterations in patients with Crohn’s disease. Microbial load weighs in on microbiota Changes in the microbiota are becoming increasingly recognized as markers and potential drivers of physiological and pathogenic processes. Most current methods use relative microbiome profiling to assess these changes, but this method does not account for changes in the overall microbial load. Here, the authors describe quantitative microbiome profiling that combines microbial cell count using flow cytometry with faecal microbiome sequencing data, providing more power in assessing variation within and between individuals. They apply this framework to healthy individuals and find that microbial load is an important determinant of gut community type. They also find that changes in microbial load drive microbiota alterations in a small cohort of patients with Crohn's disease. Current sequencing-based analyses of faecal microbiota quantify microbial taxa and metabolic pathways as fractions of the sample sequence library generated by each analysis 1 , 2 . Although these relative approaches permit detection of disease-associated microbiome variation, they are limited in their ability to reveal the interplay between microbiota and host health 3 , 4 . Comparative analyses of relative microbiome data cannot provide information about the extent or directionality of changes in taxa abundance or metabolic potential 5 . If microbial load varies substantially between samples, relative profiling will hamper attempts to link microbiome features to quantitative data such as physiological parameters or metabolite concentrations 5 , 6 . Saliently, relative approaches ignore the possibility that altered overall microbiota abundance itself could be a key identifier of a disease-associated ecosystem configuration 7 . To enable genuine characterization of host–microbiota interactions, microbiome research must exchange ratios for counts 4 , 8 , 9 . Here we build a workflow for the quantitative microbiome profiling of faecal material, through parallelization of amplicon sequencing and flow cytometric enumeration of microbial cells. We observe up to tenfold differences in the microbial loads of healthy individuals and relate this variation to enterotype differentiation. We show how microbial abundances underpin both microbiota variation between individuals and covariation with host phenotype. Quantitative profiling bypasses compositionality effects in the reconstruction of gut microbiota interaction networks and reveals that the taxonomic trade-off between Bacteroides and Prevotella is an artefact of relative microbiome analyses. Finally, we identify microbial load as a key driver of observed microbiota alterations in a cohort of patients with Crohn’s disease 10 , here associated with a low-cell-count Bacteroides enterotype (as defined through relative profiling) 11 , 12 .

Cardiometabolic diseases have become a leading cause of morbidity and mortality globally. They have been tightly linked to microbiome taxonomic and functional composition, with diet possibly mediating some of the associations described. Both the microbiome and diet are modifiable, which opens the way for novel therapeutic strategies. High-throughput omics techniques applied on microbiome samples (meta-omics) hold the unprecedented potential to shed light on the intricate links between diet, the microbiome, the metabolome and cardiometabolic health, with a top-down approach. However, effective integration of complementary meta-omic techniques is an open challenge and their application on large cohorts is still limited. Here we review meta-omics techniques and discuss their potential in this context, highlighting recent large-scale efforts and the novel insights they provided. Finally, we look to the next decade of meta-omics research and discuss various translational and clinical pathways to improving cardiometabolic health. Cardiometabolic health is tightly linked to diet and the gut microbiome. This Review explains how meta-omics technologies are revealing the intricate links between them and discusses the most promising paths to clinical translation.

Fecal microbiota transplantation (FMT) is highly effective against recurrent Clostridioides difficile infection and is considered a promising treatment for other microbiome-related disorders, but a comprehensive understanding of microbial engraftment dynamics is lacking, which prevents informed applications of this therapeutic approach. Here, we performed an integrated shotgun metagenomic systematic meta-analysis of new and publicly available stool microbiomes collected from 226 triads of donors, pre-FMT recipients and post-FMT recipients across eight different disease types. By leveraging improved metagenomic strain-profiling to infer strain sharing, we found that recipients with higher donor strain engraftment were more likely to experience clinical success after FMT ( P = 0.017) when evaluated across studies. Considering all cohorts, increased engraftment was noted in individuals receiving FMT from multiple routes (for example, both via capsules and colonoscopy during the same treatment) as well as in antibiotic-treated recipients with infectious diseases compared with antibiotic-naïve patients with noncommunicable diseases. Bacteroidetes and Actinobacteria species (including Bifidobacteria ) displayed higher engraftment than Firmicutes except for six under-characterized Firmicutes species. Cross-dataset machine learning predicted the presence or absence of species in the post-FMT recipient at 0.77 average AUROC in leave-one-dataset-out evaluation, and highlighted the relevance of microbial abundance, prevalence and taxonomy to infer post-FMT species presence. By exploring the dynamics of microbiome engraftment after FMT and their association with clinical variables, our study uncovered species-specific engraftment patterns and presented machine learning models able to predict donors that might optimize post-FMT specific microbiome characteristics for disease-targeted FMT protocols. Coupling microbial metagenomics with machine learning enables prediction of donor strain engraftment after fecal microbiota transplantation (FMT) for a range of diseases, and may help tailor design of FMT to optimize microbial engraftment and achieve clinical outcomes.

The gut microbiome is shaped by diet and influences host metabolism; however, these links are complex and can be unique to each individual. We performed deep metagenomic sequencing of 1,203 gut microbiomes from 1,098 individuals enrolled in the Personalised Responses to Dietary Composition Trial (PREDICT 1) study, whose detailed long-term diet information, as well as hundreds of fasting and same-meal postprandial cardiometabolic blood marker measurements were available. We found many significant associations between microbes and specific nutrients, foods, food groups and general dietary indices, which were driven especially by the presence and diversity of healthy and plant-based foods. Microbial biomarkers of obesity were reproducible across external publicly available cohorts and in agreement with circulating blood metabolites that are indicators of cardiovascular disease risk. While some microbes, such as Prevotella copri and Blastocystis spp., were indicators of favorable postprandial glucose metabolism, overall microbiome composition was predictive for a large panel of cardiometabolic blood markers including fasting and postprandial glycemic, lipemic and inflammatory indices. The panel of intestinal species associated with healthy dietary habits overlapped with those associated with favorable cardiometabolic and postprandial markers, indicating that our large-scale resource can potentially stratify the gut microbiome into generalizable health levels in individuals without clinically manifest disease. Analyses from the gut microbiome of over 1,000 individuals from the PREDICT 1 study, for which detailed long-term diet information as well as hundreds of fasting and same-meal postprandial cardiometabolic blood marker measurements are available, unveil new associations between specific gut microbes, dietary habits and cardiometabolic health.

Background Akkermansia muciniphila is a human gut microbe with a key role in the physiology of the intestinal mucus layer and reported associations with decreased body mass and increased gut barrier function and health. Despite its biomedical relevance, the genomic diversity of A. muciniphila remains understudied and that of closely related species, except for A. glycaniphila , unexplored. Results We present a large-scale population genomics analysis of the Akkermansia genus using 188 isolate genomes and 2226 genomes assembled from 18,600 metagenomes from humans and other animals. While we do not detect A. glycaniphila , the Akkermansia strains in the human gut can be grouped into five distinct candidate species, including A. muciniphila , that show remarkable whole-genome divergence despite surprisingly similar 16S rRNA gene sequences. These candidate species are likely human-specific, as they are detected in mice and non-human primates almost exclusively when kept in captivity. In humans, Akkermansia candidate species display ecological co-exclusion, diversified functional capabilities, and distinct patterns of associations with host body mass. Analysis of CRISPR-Cas loci reveals new variants and spacers targeting newly discovered putative bacteriophages. Remarkably, we observe an increased relative abundance of Akkermansia when cognate predicted bacteriophages are present, suggesting ecological interactions. A. muciniphila further exhibits subspecies-level genetic stratification with associated functional differences such as a putative exo/lipopolysaccharide operon. Conclusions We uncover a large phylogenetic and functional diversity of the Akkermansia genus in humans. This variability should be considered in the ongoing experimental and metagenomic efforts to characterize the health-associated properties of A. muciniphila and related bacteria.