Recent analyses of human-associated bacterial diversity have categorized individuals into 'enterotypes' or clusters based on the abundances of key bacterial genera in the gut microbiota. There is a lack of consensus, however, on the analytical basis for enterotypes and on the interpretation of these results. We tested how the following factors influenced the detection of enterotypes: clustering methodology, distance metrics, OTU-picking approaches, sequencing depth, data type (whole genome shotgun (WGS) vs.16S rRNA gene sequence data), and 16S rRNA region. We included 16S rRNA gene sequences from the Human Microbiome Project (HMP) and from 16 additional studies and WGS sequences from the HMP and MetaHIT. In most body sites, we observed smooth abundance gradients of key genera without discrete clustering of samples. Some body habitats displayed bimodal (e.g., gut) or multimodal (e.g., vagina) distributions of sample abundances, but not all clustering methods and workflows accurately highlight such clusters. Because identifying enterotypes in datasets depends not only on the structure of the data but is also sensitive to the methods applied to identifying clustering strength, we recommend that multiple approaches be used and compared when testing for enterotypes.

BACKGROUND: Giardia duodenalis (Gd) causes intestinal parasitosis. The involvement of the intestinal microbiome in determining the infections clinical phenotype is unknown. OBJECTIVE: Investigate the fecal microbiome features in dogs with giardiasis. ANIMALS AND METHODS: Cross-sectional study, including fecal samples of kenneled dogs with Gd diagnosed by fecal Giardia antigen dot ELISA. The fecal microbial compositional characteristics and dysbiosis index (DI) were compared between diarrheic and nondiarrheic dogs. RESULTS: Fecal samples of 38 Gd-infected dogs (diarrheic, 21; nondiarrheic, 17) were included. No differences were found in Faiths phylogenic diversity and beta diversity (weighted UniFrac distances) and in specific taxa abundances at the phylum, genus, and species levels, as well as in alpha and beta diversities between diarrheic and nondiarrheic dogs, and also when divided by sex or age. Among diarrheic dogs, alpha diversity was higher in males than in females (pairwise Kruskal-Wallis, q = 0.01). Among males, fecal abundances of the genus Clostridium (W = 19) and Clostridium spiroforme species (W = 33) were higher in diarrheic compared to nondiarrheic dogs. In diarrheic dog fecal samples, Proteobacteria were more prevalent (W = 1), whereas Verrucomicrobia were less prevalent in dogs <1 year of age than in older dogs. The fecal sample DI of 19 diarrheic and 19 nondiarrheic dogs was similar (median, -0.2; range, -4.3 to 4.5 and median, -1.0; range, -4.3 to 5.8, respectively). CONCLUSIONS: The fecal microbial composition of symptomatic and asymptomatic dogs with giardiasis is similar. Based on fecal DI, giardiasis is not characterized by prominent dysbiosis. Other host and parasite characteristics might determine the severity of giardiasis in dogs.

Human microbiome research is an actively developing area of inquiry, with ramifications for our lifestyles, our interactions with microbes, and how we treat disease. Advances depend on carefully executed, controlled, and reproducible studies. Here, we provide a Primer for researchers from diverse disciplines interested in conducting microbiome research. We discuss factors to be considered in the design, execution, and data analysis of microbiome studies. These recommendations should help researchers to enter and contribute to this rapidly developing field.

Cyanobacteria were responsible for the oxygenation of the ancient atmosphere; however, the evolution of this phylum is enigmatic, as relatives have not been characterized. Here we use whole genome reconstruction of human fecal and subsurface aquifer metagenomic samples to obtain complete genomes for members of a new candidate phylum sibling to Cyanobacteria, for which we propose the designation 'Melainabacteria'. Metabolic analysis suggests that the ancestors to both lineages were non-photosynthetic, anaerobic, motile, and obligately fermentative. Cyanobacterial light sensing may have been facilitated by regulators present in the ancestor of these lineages. The subsurface organism has the capacity for nitrogen fixation using a nitrogenase distinct from that in Cyanobacteria, suggesting nitrogen fixation evolved separately in the two lineages. We hypothesize that Cyanobacteria split from Melainabacteria prior or due to the acquisition of oxygenic photosynthesis. Melainabacteria remained in anoxic zones and differentiated by niche adaptation, including for symbiosis in the mammalian gut. DOI:http://dx.doi.org/10.7554/eLife.01102.001.

Oral mucositis (OM) is a common debilitating dose-limiting toxicity of cancer treatment, including hematopoietic stem cell transplantation (HSCT). We hypothesized that the oral microbiome is disturbed during allogeneic HSCT, partially accounting for the variability in OM severity. Using 16S ribosomal RNA gene sequence analysis, metabolomic profiling, and computational methods, we characterized the behavior of the salivary microbiome and metabolome of 184 patients pre- and post-HSCT. Transplantation was associated with a decrease in oral α diversity in all patients. In contrast to the gut microbiome, an association with overall survival was not detected. Among 135 patients given methotrexate for graft-versus-host disease prophylaxis pre-HSCT, Kingella and Atopobium abundance correlated with future development of severe OM. Posttransplant, Methylobacterium species were significantly enriched in patients with severe OM. Moreover, the oral microbiome and metabolome of severe OM patients underwent distinct changes post-HSCT, compared with patients with no or mild OM. Changes in specific metabolites were well explained by microbial composition, and the common metabolic pathway was the polyamines pathway, which is essential for epithelial homeostasis. Together, our findings suggest that salivary microbial composition and metabolites are associated with the development of OM, offering new insights on pathophysiology and potential avenues of intervention.

Host genetics and the gut microbiome can both influence metabolic phenotypes. However, whether host genetic variation shapes the gut microbiome and interacts with it to affect host phenotype is unclear. Here, we compared microbiotas across >1,000 fecal samples obtained from the TwinsUK population, including 416 twin pairs. We identified many microbial taxa whose abundances were influenced by host genetics. The most heritable taxon, the family Christensenellaceae, formed a co-occurrence network with other heritable Bacteria and with methanogenic Archaea. Furthermore, Christensenellaceae and its partners were enriched in individuals with low body mass index (BMI). An obese-associated microbiome was amended with Christensenella minuta, a cultured member of the Christensenellaceae, and transplanted to germ-free mice. C. minuta amendment reduced weight gain and altered the microbiome of recipient mice. Our findings indicate that host genetics influence the composition of the human gut microbiome and can do so in ways that impact host metabolism.

Culture-independent studies of human microbiota by direct genomic sequencing reveal quite distinct differences among communities, indicating that improved sequencing capacity can be most wisely utilized to study more samples, rather than more sequences per sample.

Soil microbes that colonize plant roots and are responsive to differences in plant genotype remain to be ascertained for agronomically important crops. From a very large-scale longitudinal field study of 27 maize inbred lines planted in three fields, with partial replication 5 y later, we identify root-associated microbiota exhibiting reproducible associations with plant genotype. Analysis of 4,866 samples identified 143 operational taxonomic units (OTUs) whose variation in relative abundances across the samples was significantly regulated by plant genotype, and included five of seven core OTUs present in all samples. Plant genetic effects were significant amid the large effects of plant age on the rhizosphere microbiome, regardless of the specific community of each field, and despite microbiome responses to climate events. Seasonal patterns showed that the plant root microbiome is locally seeded, changes with plant growth, and responds to weather events. However, against this background of variation, specific taxa responded to differences in host genotype. If shown to have beneficial functions, microbes may be considered candidate traits for selective breeding.

Acute gastrointestinal infection with intracellular pathogens like Salmonella Typhimurium triggers the release of the proinflammatory cytokine interleukin 1β (IL-1β). However, the role of IL-1β in intestinal defense against Salmonella remains unclear. Here, we show that IL-1β production is detrimental during Salmonella infection. Mice lacking IL-1β (IL-1β -/-) failed to recruit neutrophils to the gut during infection, which reduced tissue damage and prevented depletion of short-chain fatty acid (SCFA)-producing commensals. Changes in epithelial cell metabolism that typically support pathogen expansion, such as switching energy production from fatty acid oxidation to fermentation, were absent in infected IL-1β -/- mice which inhibited Salmonella expansion. Additionally, we found that IL-1β induces expression of complement anaphylatoxins and suppresses the complement-inactivator carboxypeptidase N (CPN1). Disrupting this process via IL-1β loss prevented mortality in Salmonella-infected IL-1β -/- mice. Finally, we found that IL-1β expression correlates with expression of the complement receptor in patients suffering from sepsis, but not uninfected patients and healthy individuals. Thus, Salmonella exploits IL-1β signaling to outcompete commensal microbes and establish gut colonization. Moreover, our findings identify the intersection of IL-1β signaling and the complement system as key host factors involved in controlling mortality during invasive Salmonellosis.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by heterogeneous cognitive, behavioral and communication impairments. Disruption of the gut-brain axis (GBA) has been implicated in ASD although with limited reproducibility across studies. In this study, we developed a Bayesian differential ranking algorithm to identify ASD-associated molecular and taxa profiles across 10 cross-sectional microbiome datasets and 15 other datasets, including dietary patterns, metabolomics, cytokine profiles and human brain gene expression profiles. We found a functional architecture along the GBA that correlates with heterogeneity of ASD phenotypes, and it is characterized by ASD-associated amino acid, carbohydrate and lipid profiles predominantly encoded by microbial species in the genera Prevotella, Bifidobacterium, Desulfovibrio and Bacteroides and correlates with brain gene expression changes, restrictive dietary patterns and pro-inflammatory cytokine profiles. The functional architecture revealed in age-matched and sex-matched cohorts is not present in sibling-matched cohorts. We also show a strong association between temporal changes in microbiome composition and ASD phenotypes. In summary, we propose a framework to leverage multi-omic datasets from well-defined cohorts and investigate how the GBA influences ASD.