A global survey of prokaryotic genomes reveals the eco-evolutionary pressures driving horizontal gene transfer.

Horizontal gene transfer, the exchange of genetic material through means other than reproduction, is a fundamental force in prokaryotic genome evolution. Genomic persistence of horizontally transferred genes has been shown to be influenced by both ecological and evolutionary factors. However, there is limited availability of ecological information about species other than the habitats from which they were isolated, which has prevented a deeper exploration of ecological contributions to horizontal gene transfer.

From microbiome composition to functional engineering, one step at a time.

SUMMARYCommunities of microorganisms (microbiota) are present in all habitats on Earth and are relevant for agriculture, health, and climate. Deciphering the mechanisms that determine microbiota dynamics and functioning within the context of their respective environments or hosts (the microbiomes) is crucially important. However, the sheer taxonomic, metabolic, functional, and spatial complexity of most microbiomes poses substantial challenges to advancing our knowledge of these mechanisms.

Reproducible Propagation of Species-Rich Soil Bacterial Communities Suggests Robust Underlying Deterministic Principles of Community Formation.

Microbiomes are typically characterized by high species diversity but it is poorly understood how such system-level complexity can be generated and propagated. Here, we used soil microcosms as a model to study development of bacterial communities as a function of their starting complexity and environmental boundary conditions. Despite inherent stochastic variation in manipulating species-rich communities, both laboratory-mixed medium complexity (21 soil bacterial isolates in equal proportions) and high-diversity natural top-soil communities followed highly reproducible succession paths, maintaining 16S rRNA gene amplicon signatures prominent for known soil communities in general.

Fermentation Ability of Gut Microbiota of Wild Japanese Macaques in the Highland and Lowland Yakushima: In Vitro Fermentation Assay and Genetic Analyses.

Wild Japanese macaques (Macaca fuscata Blyth) living in the highland and lowland areas of Yakushima are known to have different diets, with highland individuals consuming more leaves. We aim to clarify whether and how these differences in diet are also reflected by gut microbial composition and fermentation ability. Therefore, we conduct an in vitro fermentation assay using fresh feces from macaques as inoculum and dry leaf powder of Eurya japonica Thunb.

Rapid Inference of Direct Interactions in Large-Scale Ecological Networks from Heterogeneous Microbial Sequencing Data.

The availability of large-scale metagenomic sequencing data can facilitate the understanding of microbial ecosystems in unprecedented detail. However, current computational methods for predicting ecological interactions are hampered by insufficient statistical resolution and limited computational scalability. They also do not integrate metadata, which can reduce the interpretability of predicted ecological patterns.

Ecologically informed microbial biomarkers and accurate classification of mixed and unmixed samples in an extensive cross-study of human body sites.

Background: The identification of body site-specific microbial biomarkers and their use for classification tasks have promising applications in medicine, microbial ecology, and forensics. Previous studies have characterized site-specific microbiota and shown that sample origin can be accurately predicted by microbial content. However, these studies were usually restricted to single datasets with consistent experimental methods and conditions, as well as comparatively small sample numbers.

MAPseq: highly efficient k-mer search with confidence estimates, for rRNA sequence analysis.

Motivation: Ribosomal RNA profiling has become crucial to studying microbial communities, but meaningful taxonomic analysis and inter-comparison of such data are still hampered by technical limitations, between-study design variability and inconsistencies between taxonomies used.

Results: Here we present MAPseq, a framework for reference-based rRNA sequence analysis that is up to 30% more accurate (F½ score) and up to one hundred times faster than existing solutions, providing in a single run multiple taxonomy classifications and hierarchical operational taxonomic unit mappings, for rRNA sequences in both amplicon and shotgun sequencing strategies, and for datasets of virtually any size.

Availability And Implementation: Source code and binaries are freely available at https://github.