Dataset Information

Capturing sequence diversity in metagenomes with comprehensive and scalable probe design.

ABSTRACT: Metagenomic sequencing has the potential to transform microbial detection and characterization, but new tools are needed to improve its sensitivity. Here we present CATCH, a computational method to enhance nucleic acid capture for enrichment of diverse microbial taxa. CATCH designs optimal probe sets, with a specified number of oligonucleotides, that achieve full coverage of, and scale well with, known sequence diversity. We focus on applying CATCH to capture viral genomes in complex metagenomic samples. We design, synthesize, and validate multiple probe sets, including one that targets the whole genomes of the 356 viral species known to infect humans. Capture with these probe sets enriches unique viral content on average 18-fold, allowing us to assemble genomes that could not be recovered without enrichment, and accurately preserves within-sample diversity. We also use these probe sets to recover genomes from the 2018 Lassa fever outbreak in Nigeria and to improve detection of uncharacterized viral infections in human and mosquito samples. The results demonstrate that CATCH enables more sensitive and cost-effective metagenomic sequencing.

SUBMITTER: Metsky HC

PROVIDER: S-EPMC6587591 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Capturing sequence diversity in metagenomes with comprehensive and scalable probe design.

Metsky Hayden C HC Siddle Katherine J KJ Gladden-Young Adrianne A Qu James J Yang David K DK Brehio Patrick P Goldfarb Andrew A Piantadosi Anne A Wohl Shirlee S Carter Amber A Lin Aaron E AE Barnes Kayla G KG Tully Damien C DC Corleis Bjӧrn B Hennigan Scott S Barbosa-Lima Giselle G Vieira Yasmine R YR Paul Lauren M LM Tan Amanda L AL Garcia Kimberly F KF Parham Leda A LA Odia Ikponmwosa I Eromon Philomena P Folarin Onikepe A OA Goba Augustine A Simon-Lorière Etienne E Hensley Lisa L Balmaseda Angel A Harris Eva E Kwon Douglas S DS Allen Todd M TM Runstadler Jonathan A JA Smole Sandra S Bozza Fernando A FA Souza Thiago M L TML Isern Sharon S Michael Scott F SF Lorenzana Ivette I Gehrke Lee L Bosch Irene I Ebel Gregory G Grant Donald S DS Happi Christian T CT Park Daniel J DJ Gnirke Andreas A Sabeti Pardis C PC Matranga Christian B CB

Nature biotechnology 20190204 2

Metagenomic sequencing has the potential to transform microbial detection and characterization, but new tools are needed to improve its sensitivity. Here we present CATCH, a computational method to enhance nucleic acid capture for enrichment of diverse microbial taxa. CATCH designs optimal probe sets, with a specified number of oligonucleotides, that achieve full coverage of, and scale well with, known sequence diversity. We focus on applying CATCH to capture viral genomes in complex metagenomic ...[more]

PMID: 30718881

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Dataset Information

Capturing sequence diversity in metagenomes with comprehensive and scalable probe design.

Publications

Capturing sequence diversity in metagenomes with comprehensive and scalable probe design.

Similar Datasets

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