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Nat Biotechnol. 2019 Feb;37(2):160-168. doi: 10.1038/s41587-018-0006-x. Epub 2019 Feb 4.

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

Author information

1
Broad Institute of MIT and Harvard, Cambridge, MA, USA. hayden@mit.edu.
2
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA. hayden@mit.edu.
3
Broad Institute of MIT and Harvard, Cambridge, MA, USA. kjsiddle@broadinstitute.org.
4
Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA. kjsiddle@broadinstitute.org.
5
Broad Institute of MIT and Harvard, Cambridge, MA, USA.
6
Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
7
Faculty of Arts and Sciences, Harvard University, Cambridge, MA, USA.
8
Division of Infectious Diseases, Massachusetts General Hospital, Boston, MA, USA.
9
Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
10
The Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA.
11
Massachusetts Department of Public Health, Boston, MA, USA.
12
Fundação Oswaldo Cruz (FIOCRUZ), Rio de Janeiro, Rio de Janeiro, Brazil.
13
Department of Biological Sciences, College of Arts and Sciences, Florida Gulf Coast University, Fort Myers, FL, USA.
14
Instituto de Investigacion en Microbiologia, Universidad Nacional Autónoma de Honduras, Tegucigalpa, Honduras.
15
Institute of Lassa Fever Research and Control, Irrua Specialist Teaching Hospital, Irrua, Nigeria.
16
African Center of Excellence for Genomics of Infectious Disease (ACEGID), Redeemer's University, Ede, Nigeria.
17
Department of Biological Sciences, College of Natural Sciences, Redeemer's University, Ede, Nigeria.
18
Lassa Fever Laboratory, Kenema Government Hospital, Kenema, Sierra Leone.
19
Evolutionary Genomics of RNA Viruses, Virology Department, Institut Pasteur, Paris, France.
20
Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, US National Institutes of Health, Frederick, MD, USA.
21
Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua.
22
Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, Berkeley, CA, USA.
23
Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University, North Grafton, MA, USA.
24
Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
25
Department of Microbiology and Immunobiology, Harvard Medical School, Boston, MA, USA.
26
Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO, USA.
27
College of Medicine and Allied Health Sciences, University of Sierra Leone, Freetown, Sierra Leone.
28
Howard Hughes Medical Institute, Chevy Chase, MD, USA.

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.

PMID:
30718881
DOI:
10.1038/s41587-018-0006-x

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