A low-cost genomics workflow enables isolate screening and strain-level analyses within microbiomes

• Type of Material: Article
• Authors: Jon G Sanders, Cornell University; Weiwei Yan, Cornell University; Deus Mjungu, Gombe Stream Research Center; Elizabeth Lonsdorf, Emory University; John A Hart, Lukuru Wildlife Research Foundation; Crickette M Sanz, Washington University in St. Louis; David B Morgan, Lester E. Fisher Center for the Study and Conservation of Apes; Martin e Peeters, Université de Montpellier; Beatrice H Hahn, University of Pennsylvania Perelman School of Medicine; Andrew H Moeller, Cornell University
• Language: English
• Date: 2022-12-01
• Publisher: Springer Nature
• Publication Version: Final Published Version
• Copyright Statement: © The Author(s) 2022
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1186/s13059-022-02777-w
• Title of Journal or Parent Work: Genome Biology
• Volume: 23
• Issue: 1
• Start Page: 212
• End Page: 212
• Grant/Funding Information: JGS was partially supported by grant T32 AI145821 to the Cornell Institute for Host–Microbe Interaction and Disease by the National Institutes of Health.; This work was supported by a laboratory start-up grant from Cornell University to AHM and grant R35 GM138284 from the National Institute of General Medical Sciences to AHM, and grant R01 AI 050529 to BHH.
• Keywords: Metagenome; Pan troglodytes; Genome, Bacterial; Animals; Genomics; Workflow; Bacteria; Microbiota; Phylogeny
• Research Categories: Psychology, General

Abstract

Earth’s environments harbor complex consortia of microbes that affect processes ranging from host health to biogeochemical cycles. Understanding their evolution and function is limited by an inability to isolate genomes in a high-throughput manner. Here, we present a workflow for bacterial whole-genome sequencing using open-source labware and the OpenTrons robotics platform, reducing costs to approximately $10 per genome. We assess genomic diversity within 45 gut bacterial species from wild-living chimpanzees and bonobos. We quantify intraspecific genomic diversity and reveal divergence of homologous plasmids between hosts. This enables population genetic analyses of bacterial strains not currently possible with metagenomic data alone.