Growth dynamics of gut microbiota in health and disease inferred from single metagenomic samples

Abstract

Metagenomic sequencing increased our understanding of the role of the microbiome in health and disease, yet it only provides a snapshot of a highly dynamic ecosystem. Here, we show that the pattern of metagenomic sequencing read coverage for different microbial genomes contains a single trough and a single peak, the latter coinciding with the bacterial origin of replication. Furthermore, the ratio of sequencing coverage between the peak and trough provides a quantitative measure of a species' growth rate. We demonstrate this in vitro and in vivo, under different growth conditions, and in complex bacterial communities. For several bacterial species, peak to trough coverage ratios, but not relative abundances, correlated with the manifestation of inflammatory bowel disease and type II diabetes.

Numerous uncharacterized and highly divergent microbes which colonize humans are revealed by circulating cell-free DNA

“…The lower coverage of novel contigs may have kept them hidden from previous analyses, and only by pooling many samples together were these sequences found (22). Biases in read coverage across the bacterial contigs may also be used to estimate their growth dynamics (23).…”

Survey of (Meta)genomic Approaches for Understanding Microbial Community Dynamics

“…Recently Korem et al [16] devised a way to obtain information on growth dynamics of particular bacteria/genome enriched in a metagenome. This methodology focuses on examining pattern of sequencing coverage specifically at origin of replication of bacterial genomes (Fig.…”

“…2 Diagram showing four major aspects connecting metagenomics (M) and genomics (G) as discussed in the review; a average genome size estimation of metagenome data to understand genome selection pressure, b understanding the growth dynamics of specific bacterium from metagenome data, c SNP analysis using temporal metagenomics, and d G?C driven codon usage and protein selection analysis across metagenomic-derived genomes (The figure was originally produced for this review. The concepts for a-d were taken from Nayfach and Pollard [56], Korem et al [16], Bendall et al [15], and Ran et al [74], respectively) habitat specific genomic alterations over indigenous populations [21].…”

“…While there are numerous studies based on using genomics and metagenomics independently, it has not been until recently that the potential of mining genome and metagenome datasets together was exploited to unveil complex environmenthost interactions. Using (meta)genomics in sync, can provide a better understanding of habitat independent gene acquisitions and functional contributions of taxa enriched in an environment [15,16]. (Meta)genomics can also predict in situ growth dynamics, environment specific lifestyles, seasonal dynamics, and gene-specific genomewide sweeps across resident populations [17,18] (Figs.…”

A contemporary view of glyphosate

“…· effects on the cytochromes P450 [23]; · effects on the gastrointestinal tract (one of the few papers on this topic is that of Shehata et al [24]; the study of the gut microbiota is however advancing far and fast now [25] and it is to be hoped that studies of the effect of glyphosate on the human gut microbiota will be carried out in the nearest future; · effects on soil ecosystem diversity-hitherto not studied but their occurrence seems obvious; · trace element chelation in the soil [2], leading to depletion of essential elements. It may hardly be necessary to mention that the increase of glyphosate use is strongly correlated with the spread of crop varieties genetically modified to resist glyphosate.…”