Exploring neighborhoods in large metagenome assembly graphs reveals hidden sequence diversity

Brown, C. Titus; Moritz, Dominik; O’Brien, Michael P.; Reidl, Felix; Reiter, Taylor; Sullivan, Blair D.

doi:10.1101/462788

Cited by 8 publications

(9 citation statements)

References 51 publications

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“…We have modified the analysis protocol by replacing the complete metagenomic assembly with a local assembly using MetaCherchant algorithm. Also, there are new additional methods to restore the hidden gene diversity of MAGs (Brown et al, 2019).…”

Section: Resultsmentioning

confidence: 99%

Shifts in the Human Gut Microbiota Structure Caused by Quadruple Helicobacter pylori Eradication Therapy

et al. 2019

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The human gut microbiome plays an important role both in health and disease. Use of antibiotics can alter gut microbiota composition, which can lead to various deleterious events. Here we report a whole genome sequencing metagenomic/genomic study of the intestinal microbiota changes caused by Helicobacter pylori (HP) eradication therapy. Using approaches for metagenomic data analysis we revealed a statistically significant decrease in alpha-diversity and relative abundance of Bifidobacterium adolescentis due to HP eradication therapy, while the relative abundance of Enterococcus faecium increased. We have detected changes in general metagenome resistome profiles as well: after HP eradication therapy, the ermB, CFX group, and tetQ genes were overrepresented, while tetO and tetW genes were underrepresented. We have confirmed these results with genome-resolved metagenomic approaches. MAG (metagenome-assembled genomes) abundance profiles have changed dramatically after HP eradication therapy. Focusing on ermB gene conferring resistance to macrolides, which were included in the HP eradication therapy scheme, we have shown a connection between antibiotic resistance genes (ARGs) and some overrepresented MAGs. Moreover, some E. faecium strains isolated from stool samples obtained after HP eradication have manifested greater antibiotic resistance in vitro in comparison to other isolates, as well as the higher number of ARGs conferring resistance to macrolides and tetracyclines.

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Section: Resultsmentioning

confidence: 99%

Shifts in the Human Gut Microbiota Structure Caused by Quadruple Helicobacter pylori Eradication Therapy

et al. 2019

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“…While sequence assembly has been an active area of research 61 , this has not been the case for gene prediction methods 61 , which are becoming outdated 62 and cannot cope with the current amount of data. Alternatives like protein-level assembly 63 combined with exploring the assembly graphs’ neighborhoods 64 become very attractive for our purposes. In any case, we still face the challenge of discriminating between real and artifactual singletons 65 .…”

Section: Discussionmentioning

confidence: 99%

Unifying the known and unknown microbial coding sequence space

Vanni

Schechter

Acinas

et al. 2020

Preprint

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AbstractBridging the gap between the known and the unknown coding sequence space is one of the biggest challenges in molecular biology today. This challenge is especially extreme in microbiome analyses where between 40% to 60% of the coding sequences detected are of unknown function, and ignoring this fraction limits our understanding of microbial systems. Discarding the uncharacterized fraction is not an option anymore. Here, we present an in-depth exploration of the microbial unknown fraction through the lenses of a conceptual framework and a computational workflow we developed to unify the microbial known and unknown coding sequence space. Our approach partitions the coding sequence space in gene clusters and contextualizes them with genomic and environmental information. We analyzed 415,971,742 genes predicted from 1,749 metagenomes and 28,941 bacterial and archaeal genomes putting into perspective the extent of the unknown fraction, its diversity, and its relevance in a genomic and environmental context. With the identification of a target gene of unknown function for antibiotic resistance, we demonstrate how a contextualized unknown coding sequence space provides a robust framework for the generation of hypotheses that can be used to augment experimental data.

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“…This likely indicates that a P. ruminis strain that has not been sequenced before is in our sample, and that it shares more k-mers of size 31 in common with one strain than the other. (See Brown CT et al 23 for further analysis of this strain. )…”

Section: Use Casesmentioning

confidence: 99%

Large-scale sequence comparisons with sourmash

et al. 2019

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The sourmash software package uses MinHash-based sketching to create “signatures”, compressed representations of DNA, RNA, and protein sequences, that can be stored, searched, explored, and taxonomically annotated. sourmash signatures can be used to estimate sequence similarity between very large data sets quickly and in low memory, and can be used to search large databases of genomes for matches to query genomes and metagenomes. sourmash is implemented in C++, Rust, and Python, and is freely available under the BSD license at http://github.com/dib-lab/sourmash.

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Exploring neighborhoods in large metagenome assembly graphs reveals hidden sequence diversity

Cited by 8 publications

References 51 publications

Shifts in the Human Gut Microbiota Structure Caused by Quadruple Helicobacter pylori Eradication Therapy

Shifts in the Human Gut Microbiota Structure Caused by Quadruple Helicobacter pylori Eradication Therapy

Unifying the known and unknown microbial coding sequence space

Large-scale sequence comparisons with sourmash

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