Empirical assessment of the enrichment-based metagenomic methods in identifying diverse respiratory pathogens

Abstract

Probe-based nucleic acid enrichment represents an effective route to enhance the detection capacity of next-generation sequencing (NGS) in a set of clinically diverse and relevant microbial species. In this study, we assessed the effect of the enrichment-based sequencing on identifying respiratory infections using tiling RNA probes targeting 76 respiratory pathogens and sequenced using both Illumina and Oxford Nanopore platforms. Forty respiratory swab samples pre-tested for a panel of respiratory pathogens by qPCR were used to benchmark the sequencing data. We observed a general improvement in sensitivity after enrichment. The overall detection rate increased from 73 to 85% after probe capture detected by Illumina. Moreover, enrichment with probe sets boosted the frequency of unique pathogen reads by 34.6 and 37.8-fold for Illumina DNA and cDNA sequencing, respectively. This also resulted in significant improvements on genome coverage especially in viruses. Despite these advantages, we found that library pooling may cause reads mis-assignment, probably due to crosstalk issues arise from post-capture PCR and from pooled sequencing, thus increasing the risk of bleed-through signal. Taken together, an overall improvement in the breadth and depth of pathogen coverage is achieved using enrichment-based sequencing method. For future applications, automated library processing and pooling-free sequencing could enhance the precision and timeliness of probe enrichment-based clinical metagenomics.

Keywords: Illumina; Nanopore; Respiratory pathogens; Virus; mNGS.

Fig. 1

Schematic of the mNGS assay workflow. Total nucleic acids (TNAs) were extracted by bead beating and guanidinium isothiocyanate-based lysis. Part of TNAs were used for qPCR panel test, the rest of TNAs were split into two aliquots for subsequent DNA and cDNA Illumina library preparation, the libraries were either analysed directly by Novaseq (sMS) or enriched by probes and further analysed by Illumina or Nanopore-based sequencing (eMS). Separate DNA and cDNA libraries were constructed and sequenced in this study.

Fig. 2

Taxonomic identification provided by sMS and eMS compared to qPCR panel. A and B, Venn diagrams of pathogen hits identified by mNGS compared to qPCR panel. Of the 30 qPCR-positive bacteria hits, 27 were positively detected by sMS-Illumina, eMS-Illumina or eMS-Nanopore. Of the 25 qPCR-positive viruses hits detected by qPCR panel, 13 were positively detected by sMS-Illumina, another 7 or 6 were further positively identified by eMS-Illumina and eMS-Nanopore.

Fig. 3

Reads plot of representative pathogens detected by sMS- or eMS-Illumina sequencing. By using the pathogen nucleic acid capture probes, the reads/million (RPM) of pathogen sequences were plotted. *p < 0.05; **p < 0.01; ***p < 0.001(paired t-test using Graphpad Prism 5 software).

Fig. 4

Performance of different sequencing workflows on selected respiratory pathogenic viruses. (A, B and C) Genomic coverage plot of Respiratory syncytial virus, Human rubulavirus 2 and Human parainfluenza virus 1, respectively.