High-throughput automated microfluidic sample preparation for accurate microbial genomics

Soohong Kim, Joachim De Jonghe, Anthony B. Kulesa, David Feldman, Tommi Vatanen, Roby P. Bhattacharyya, Brittany Berdy, James Gomez, Jill Nolan, Slava Epstein and Paul C. Blainey ()
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Soohong Kim: The Broad Institute of MIT and Harvard
Joachim De Jonghe: The Broad Institute of MIT and Harvard
Anthony B. Kulesa: The Broad Institute of MIT and Harvard
David Feldman: The Broad Institute of MIT and Harvard
Tommi Vatanen: The Broad Institute of MIT and Harvard
Roby P. Bhattacharyya: The Broad Institute of MIT and Harvard
Brittany Berdy: Northeastern University
James Gomez: The Broad Institute of MIT and Harvard
Jill Nolan: The Broad Institute of MIT and Harvard
Slava Epstein: Northeastern University
Paul C. Blainey: The Broad Institute of MIT and Harvard

Nature Communications, 2017, vol. 8, issue 1, 1-10

Abstract: Abstract Low-cost shotgun DNA sequencing is transforming the microbial sciences. Sequencing instruments are so effective that sample preparation is now the key limiting factor. Here, we introduce a microfluidic sample preparation platform that integrates the key steps in cells to sequence library sample preparation for up to 96 samples and reduces DNA input requirements 100-fold while maintaining or improving data quality. The general-purpose microarchitecture we demonstrate supports workflows with arbitrary numbers of reaction and clean-up or capture steps. By reducing the sample quantity requirements, we enabled low-input (∼10,000 cells) whole-genome shotgun (WGS) sequencing of Mycobacterium tuberculosis and soil micro-colonies with superior results. We also leveraged the enhanced throughput to sequence ∼400 clinical Pseudomonas aeruginosa libraries and demonstrate excellent single-nucleotide polymorphism detection performance that explained phenotypically observed antibiotic resistance. Fully-integrated lab-on-chip sample preparation overcomes technical barriers to enable broader deployment of genomics across many basic research and translational applications.

Date: 2017
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DOI: 10.1038/ncomms13919

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