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

We describe here a 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 demonstrated, the whole protocol takes about 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 in clinical diagnostic tests. Moreover, our mtNGS method is capable of detecting antibiotic resistance genes and virulence factors; though it may not be comprehensive, such information is imperative and helpful for the clinician to make better treatment decisions. Our preliminary testing suggests the mtNGS approach is a useful alterative in diagnostic detection of emerging infectious pathogens in clinical laboratory. However, further improvements are needed to achieve better sensitivity and accuracy.
Source: The Journal of Molecular Diagnostics - Category: Pathology Source Type: research