Bifidobacteria-mediated immune system imprinting early in life

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Pan-cancer analyses reveal cancer-type-specific fungal ecologies and bacteriome interactions

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Metagenomics of the subsurface Brazos-Trinity Basin (IODP site 1320): comparison with other sediment and pyrosequenced metagenomes

The Brazos-Trinity Basin on the slope of the Gulf of Mexico passive margin was drilled during Integrated Ocean Drilling Progam Expedition 308. The buried anaerobic sediments of this basin are largely organic-poor and have few microbial inhabitants compared with the organic-rich sediments with high cell counts from the Peru Margin that were drilled during Ocean Drilling Program Leg 201. Nucleic acids were extracted from Brazos-Trinity Basin sediments and were subjected to whole-genome amplification and pyrosequencing. A comparison of the Brazos-Trinity Basin metagenome, consisting of 105 Mbp, and the existing Peru Margin metagenome revealed trends linking gene content, phylogenetic content, geological location and geochemical regime. The major microbial groups (Proteobacteria, Firmicutes, Euryarchaeota and Chloroflexi) occur consistently throughout all samples, yet their shifting abundances allow for discrimination between samples. The cluster of orthologous groups category abundances for some classes of genes are correlated with geochemical factors, such as the level of ammonia. Here we describe the sediment metagenome from the oligotrophic Brazos-Trinity Basin (Site 1320) and show similarities and differences with the dataset from the Pacific Peru Margin (Site 1229) and other pyrosequenced datasets. The microbial community found at Integrated Ocean Drilling Program Site 1320 likely represents the subsurface microbial inhabitants of turbiditic slopes that lack substantial upwelling.     

Autism-related dietary preferences mediate autism-gut microbiome associations

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Codiversification of gastrointestinal microbiota and phylogeny in passerines is not explained by ecological divergence

Vertebrate gut microbiota (GM) is comprised of a taxonomically diverse consortium of symbiotic and commensal microorganisms that have a pronounced effect on host physiology, immune system function and health status. Despite much research on interactions between hosts and their GM, the factors affecting inter‐ and intraspecific GM variation in wild populations are still poorly known. We analysed data on faecal microbiota composition in 51 passerine species (319 individuals) using Illumina MiSeq sequencing of bacterial 16S rRNA (V3–V4 variable region). Despite pronounced interindividual variation, GM composition exhibited significant differences at the interspecific level, accounting for approximately 20%–30% of total GM variation. We also observed a significant correlation between GM composition divergence and host's phylogenetic divergence, with strength of correlation higher than that of GM vs. ecological or life history traits and geographic variation. The effect of host's phylogeny on GM composition was significant, even after statistical control for these confounding factors. Hence, our data do not support codiversification of GM and passerine phylogeny solely as a by‐product of their ecological divergence. Furthermore, our findings do not support that GM vs. host's phylogeny codiversification is driven primarily through trans‐generational GM transfer as the GM vs. phylogeny correlation does not increase with higher sequence similarity used when delimiting operational taxonomic units. Instead, we hypothesize that the GM vs. phylogeny correlation may arise as a consequence of interspecific divergence of genes that directly or indirectly modulate composition of GM.     

Promises and pitfalls of using high‐throughput sequencing for diet analysis

The application of high‐throughput sequencing‐based approaches to DNA extracted from environmental samples such as gut contents and faeces has become a popular tool for studying dietary habits of animals. Due to the high resolution and prey detection capacity they provide, both metabarcoding and shotgun sequencing are increasingly used to address ecological questions grounded in dietary relationships. Despite their great promise in this context, recent research has unveiled how a wealth of biological (related to the study system) and technical (related to the methodology) factors can distort the signal of taxonomic composition and diversity. Here, we review these studies in the light of high‐throughput sequencing‐based assessment of trophic interactions. We address how the study design can account for distortion factors, and how acknowledging limitations and biases inherent to sequencing‐based diet analyses are essential for obtaining reliable results, thus drawing appropriate conclusions. Furthermore, we suggest strategies to minimize the effect of distortion factors, measures to increase reproducibility, replicability and comparability of studies, and options to scale up DNA sequencing‐based diet analyses. In doing so, we aim to aid end‐users in designing reliable diet studies by informing them about the complexity and limitations of DNA sequencing‐based diet analyses, and encourage researchers to create and improve tools that will eventually drive this field to its maturity.