Background Bacteria within family S24-7 (phylum Bacteroidetes ) are dominant in the mouse gut microbiota and detected in the intestine of other animals. Because they had not been cultured until recently and the family classification is still ambiguous, interaction with their host was difficult to study and confusion still exists regarding sequence data annotation. Methods We investigated family S24-7 by combining data from large-scale 16S rRNA gene analysis and from functional and taxonomic studies of metagenomic and cultured species. Results A total of 685 species was inferred by full-length 16S rRNA gene sequence clustering. While many species could not be assigned ecological habitats (93,045 samples analyzed), the mouse was the most commonly identified host (average of 20% relative abundance and nine co-occurring species). Shotgun metagenomics allowed reconstruction of 59 molecular species, of which 34 were representative of the 16S rRNA gene-derived species clusters. In addition, cultivation efforts allowed isolating five strains representing three species, including two novel taxa. Genome analysis revealed that S24-7 spp. are functionally distinct from neighboring families and versatile with respect to complex carbohydrate degradation. Conclusions We provide novel data on the diversity, ecology, and description of bacterial family S24-7, for which the name Muribaculaceae is proposed. Electronic supplementary material The online version of this article (10.1186/s40168-019-0637-2) contains supplementary material, which is available to authorized users.

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic and complex datasets with long- and short-read sequences, created computationally from around 1,700 new and known genomes, as well as 600 new plasmids and viruses. Here we analyze 5,002 results by 76 program versions. Substantial improvements were seen in assembly, some due to long-read data. Related strains still were challenging for assembly and genome recovery through binning, as was assembly quality for the latter. Profilers markedly matured, with taxon profilers and binners excelling at higher bacterial ranks, but underperforming for viruses and Archaea. Clinical pathogen detection results revealed a need to improve reproducibility. Runtime and memory usage analyses identified efficient programs, including top performers with other metrics. The results identify challenges and guide researchers in selecting methods for analyses.

The microbiota contributes to colonization resistance against invading pathogens by competing for metabolites, producing inhibitory substances, and priming protective immune responses. However, the specific commensal bacteria that promote host resistance and immune-mediated protection remain largely elusive. Using isogenic mouse lines with distinct microbiota profiles, we demonstrate that severity of disease induced by enteric Salmonella Typhimurium infection is strongly modulated by microbiota composition in individual lines. Transferring a restricted community of cultivable intestinal commensals from protected into susceptible mice decreases S. Typhimurium tissue colonization and consequently disease severity. This reduced tissue colonization, along with ameliorated weight loss and prolonged survival, depends on microbiota-enhanced IFNγ production, as IFNγ-deficient mice do not exhibit protective effects. Innate cells and CD4 T cells increase in number and show high levels of IFNγ after transfer of the commensal community. Thus, distinct microbiota members prevent intestinal Salmonella infection by enhancing antibacterial IFNγ responses.

The composition of the intestinal microbiota influences the outcome of enteric infections in human and mice. However, the role of specific members and their metabolites contributing to disease severity is largely unknown. Using isogenic mouse lines harboring distinct microbiota communities, we observed highly variable disease kinetics of enteric Citrobacter rodentium colonization after infection. Transfer of communities from susceptible and resistant mice into germ-free mice verified that the varying susceptibilities are determined by microbiota composition. The strongest differences in colonization were observed in the cecum and could be maintained in vitro by coculturing cecal bacteria with C. rodentium. Cohousing of animals as well as the transfer of cultivable bacteria from resistant to susceptible mice led to variable outcomes in the recipient mice. Microbiome analysis revealed that a higher abundance of butyrate-producing bacteria was associated with the resistant phenotype. Quantification of short-chain fatty acid (SCFA) levels before and after infection revealed increased concentrations of acetate, butyrate and propionate in mice with delayed colonization. Addition of physiological concentrations of butyrate, but not of acetate and/or propionate strongly impaired growth of C. rodentium in vitro. In vivo supplementation of susceptible, antibiotic-treated and germ-free mice with butyrate led to the same level of protection, notably only when cecal butyrate concentration reached a concentration higher than 50 nmol/mg indicating a critical threshold for protection. In the recent years, commensalderived primary and secondary bacterial metabolites emerged as potent modulators of

Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the community-driven initiative for the Critical Assessment of Metagenome Interpretation (CAMI). In its second challenge, CAMI engaged the community to assess their methods on realistic and complex metagenomic datasets with long and short reads, created from ∼1,700 novel and known microbial genomes, as well as ∼600 novel plasmids and viruses. Altogether 5,002 results by 76 program versions were analyzed, representing a 22x increase in results.Substantial improvements were seen in metagenome assembly, some due to using long-read data. The presence of related strains still was challenging for assembly and genome binning, as was assembly quality for the latter. Taxon profilers demonstrated a marked maturation, with taxon profilers and binners excelling at higher bacterial taxonomic ranks, but underperforming for viruses and archaea. Assessment of clinical pathogen detection techniques revealed a need to improve reproducibility. Analysis of program runtimes and memory usage identified highly efficient programs, including some top performers with other metrics. The CAMI II results identify current challenges, but also guide researchers in selecting methods for specific analyses.