Optimizing a Metatranscriptomic Next-Generation Sequencing Protocol for Bronchoalveolar Lavage Diagnostics

Weihua Huang, Changhong Yin, Guiqing Wang, Jeremy Rosenblum, Sankaran Krishnan, Nevenka Dimitrova, John T. Fallon

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Compared with conventional serologic, culture-based, and molecular-based diagnostic tests, next-generation sequencing (NGS) provides sequence-evidenced detection of various microbes, without prior knowledge, and thus is becoming a novel diagnostic approach. Herein we describe an RNA-based metatranscriptomic NGS (mtNGS) protocol for culture-independent detection of potential infectious pathogens, using clinical bronchoalveolar lavage specimens as an example. We present both an optimized workflow for experimental sequence data collection and a simplified pipeline for bioinformatics sequence data processing. As shown, the whole protocol takes approximately 24 to 36 hours to detect a wide range of Gram-positive and -negative bacteria and possibly other viral and/or fungal pathogens. In particular, we introduce a spike-in RNA mix as an internal control, which plays a critical role in mitigating false-positive and false-negative results of clinical diagnostic tests. Moreover, our mtNGS method can detect antibiotic resistance genes and virulence factors; although it may not be comprehensive, such information is imperative and helpful for the clinician to make better treatment decisions. Results from our preliminary testing suggest that the mtNGS approach is a useful alterative in diagnostic detection of emerging infectious pathogens in clinical laboratories. However, further improvements are needed to achieve better sensitivity and accuracy.

Original languageEnglish
Pages (from-to)251-261
Number of pages11
JournalJournal of Molecular Diagnostics
Volume21
Issue number2
DOIs
StatePublished - Mar 2019
Externally publishedYes

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