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Clinical Next Generation Sequencing Outperforms Standard Microbiological Culture for Characterizing Polymicrobial Samples
Author(s) -
Lisa A. Cummings,
Kyoko Kurosawa,
Daniel R. Hoogestraat,
Dhruba J. SenGupta,
Febrian Candra,
Michael P. Doyle,
Stephanie Thielges,
Tyler A. Land,
Christopher Rosenthal,
Noah G. Hoffman,
Stephen J. Salipante,
Brad T. Cookson
Publication year - 2016
Publication title -
clinical chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.705
H-Index - 218
eISSN - 1530-8561
pISSN - 0009-9147
DOI - 10.1373/clinchem.2016.258806
Subject(s) - dna sequencing , computational biology , biology , medicine , genetics , dna
BACKGROUND Humans suffer from infections caused by single species or more complex polymicrobial communities. Identification of infectious bacteria commonly employs microbiological culture, which depends upon the in vitro propagation and isolation of viable organisms. In contrast, detection of bacterial DNA using next generation sequencing (NGS) allows culture-independent microbial profiling, potentially providing important new insights into the microbiota in clinical specimens. METHODS NGS 16S rRNA gene sequencing (NGS16S) was compared with culture using (a) synthetic polymicrobial samples for which the identity and abundance of organisms present were precisely defined and (b) primary clinical specimens. RESULTS Complex mixtures of at least 20 organisms were well resolved by NGS16S with excellent reproducibility. In mixed bacterial suspensions (107 total genomes), we observed linear detection of a target organism over a 4-log concentration range (500–3 × 106 genomes). NGS16S analysis more accurately recapitulated the known composition of synthetic samples than standard microbiological culture using nonselective media, which distorted the relative abundance of organisms and frequently failed to identify low-abundance pathogens. However, extended quantitative culture using selective media for each of the component species recovered the expected organisms at the proper abundance, validating NGS16S results. In an analysis of sputa from cystic fibrosis patients, NGS16S identified more clinically relevant pathogens than standard culture. CONCLUSIONS Biases in standard, nonselective microbiological culture lead to a distorted characterization of polymicrobial mixtures. NGS16S demonstrates enhanced reproducibility, quantification, and classification accuracy compared with standard culture, providing a more comprehensive, accurate, and culture-free analysis of clinical specimens.

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