2021bioRxiv (Cold Spring Harbor Laboratory)Open access

Genome binning of viral entities from bulk metagenomics data

Joachim Johansen, Damian R. Plichta, Jakob Nybo Nissen, Marie Louise Jespersen, Shiraz A. Shah, Ling Deng, Jakob Stokholm, Hans Bisgaard, Dennis Sandris Nielsen, Søren J. Sørensen, Simon Rasmussen

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Abstract

Abstract Despite the accelerating number of uncultivated virus sequences discovered in metagenomics and their apparent importance for health and disease, the human gut virome and its interactions with bacteria in the gastrointestinal are not well understood. In addition, a paucity of whole-virome datasets from subjects with gastrointestinal diseases is preventing a deeper understanding of the virome’s role in disease and in gastrointestinal ecology as a whole. By combining a deep-learning based metagenomics binning algorithm with paired metagenome and metavirome datasets we developed the Phages from Metagenomics Binning (PHAMB) approach for binning thousands of viral genomes directly from bulk metagenomics data. Simultaneously our methodology enables clustering of viral genomes into accurate taxonomic viral populations. We applied this methodology on the Human Microbiome Project 2 (HMP2) cohort and recovered 6,077 HQ genomes from 1,024 viral populations and explored viral-host interactions. We show that binning can be advantageously applied to existing and future metagenomes to illuminate viral ecological dynamics with other microbiome constituents.

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Abstract Despite the accelerating number of uncultivated virus sequences discovered in metagenomics and their apparent importance for health and disease, the human gut virome and its interactions with bacteria in the gastrointestinal are not well understood. In addition, a paucity of whole-virome datasets from subjects with gastrointestinal diseases is preventing a deeper understanding of the virome’s role in disease and in gastrointestinal ecology as a whole. By combining a deep-learning based metagenomics binning algorithm with paired metagenome and metavirome datasets we developed the Phages from Metagenomics Binning (PHAMB) approach for binning thousands of viral genomes directly from bulk metagenomics data. Simultaneously our methodology enables clustering of viral genomes into accurate taxonomic viral populations. We applied this methodology on the Human Microbiome Project 2 (HMP2) cohort and recovered 6,077 HQ genomes from 1,024 viral populations and explored viral-host interactions. We show that binning can be advantageously applied to existing and future metagenomes to illuminate viral ecological dynamics with other microbiome constituents.

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Available abstract

Abstract Despite the accelerating number of uncultivated virus sequences discovered in metagenomics and their apparent importance for health and disease, the human gut virome and its interactions with bacteria in the gastrointestinal are not well understood. In addition, a paucity of whole-virome datasets from subjects with gastrointestinal diseases is preventing a deeper understanding of the virome’s role in disease and in gastrointestinal ecology as a whole. By combining a deep-learning based metagenomics binning algorithm with paired metagenome and metavirome datasets we developed the Phages from Metagenomics Binning (PHAMB) approach for binning thousands of viral genomes directly from bulk metagenomics data. Simultaneously our methodology enables clustering of viral genomes into accurate taxonomic viral populations. We applied this methodology on the Human Microbiome Project 2 (HMP2) cohort and recovered 6,077 HQ genomes from 1,024 viral populations and explored viral-host interactions. We show that binning can be advantageously applied to existing and future metagenomes to illuminate viral ecological dynamics with other microbiome constituents.

Key concepts: Human virome, Metagenomics, Microbiome, Genome, Biology, Computational biology, Human Microbiome Project, Evolutionary biology

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