Capturing sequence diversity in metagenomes with comprehensive and scalable probe design

Hayden C. Metsky, Katherine J. Siddle, Adrianne Gladden-Young, James Qu, David K. Yang, Patrick Brehio, Andrew Goldfarb, Anne Piantadosi, Shirlee Wohl, Amber Carter, Aaron E. Lin, Kayla Barnes, Damien C. Tully, Bjӧrn Corleis, Scott Hennigan, Giselle Barbosa-Lima, Yasmine R. Vieira, Lauren M. Paul, Amanda L. Tan, Kimberly F. GarciaLeda A. Parham, Ikponmwosa Odia, Philomena Eromon, Onikepe A. Folarin, Augustine Goba, Etienne Simon-Lorière, Lisa Hensley, Angel Balmaseda, Eva Harris, Douglas S. Kwon, Todd M. Allen, Jonathan A. Runstadler, Sandra Smole, Fernando A. Bozza, Thiago M.L. Souza, Sharon Isern, Scott F. Michael, Ivette Lorenzana, Lee Gehrke, Irene Bosch, Gregory Ebel, Donald S. Grant, Christian T. Happi, Daniel J. Park, Andreas Gnirke, Pardis C. Sabeti, Christian B. Matranga

Research output: Contribution to journalArticlepeer-review

103 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)160-168
Number of pages9
JournalNature Biotechnology
Volume37
Issue number2
DOIs
Publication statusPublished - 1 Feb 2019
Externally publishedYes

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