Massively parallel sequencing combined with computational host sequence subtraction is a highly sensitive method for detecting low-abundance viral and bacterial transcripts in human tissue.
Demonstrates method sensitivity for rare transcripts in animal tissue; leaves open human diagnostic translation and clinical validation.
Massively parallel sequencing technology now provides the opportunity to sample the transcriptome of a given tissue comprehensively. Transcripts at only a few copies per cell are readily detectable, allowing the discovery of low abundance viral and bacterial transcripts in human tissue samples. Here we describe an approach for mining large sequence data sets for the presence of microbial sequences. Further, we demonstrate the sensitivity of this approach by sequencing human RNA-seq libraries spiked with decreasing amounts of an RNA-virus. At a modest depth of sequencing, viral transcripts can be detected at frequencies less than 1 in 1,000,000. With current sequencing platforms approaching outputs of one billion reads per run, this is a highly sensitive method for detecting putative infectious agents associated with human tissues.
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Moore et al. (2011) studied this question.
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