Karlsson OE, Belák S, Granberg F.
Compared to routine diagnostics, screening for pathogens in outbreak situations, with or without intentional release, poses demands on the detection technology to not only indicate the presence of already known causative agents but also novel and unexpected pathogens. The metagenomic approach to detecting viral pathogens, using unbiased high-throughput sequencing (HTS), is a well-established methodology with a broad detection range and wide applicability on different sample matrices. To prepare a sample for HTS, the common presequencing steps include homogenization, enrichment, separation (eg, magnetic separation), and amplification. In this initial study, we explored the benefits and drawbacks of preprocessing by sequence-independent, single-primer amplification (SISPA) of nucleic acids by applying the methodology to artificial samples. More specifically, a synthetic metagenome was divided into 2 samples, 1 unamplified and 1 diluted, and amplified by SISPA. Subsequently, both samples were sequenced using the Ion Torrent Personal Genome Machine (PGM), and the resulting datasets were analyzed by using bioinformatics, short read mapping, de novo assembly, BLAST-based taxonomic classification, and visualization. The results indicate that even though SISPA introduces a strong amplification bias, which makes it unsuitable for whole-genome sequencing, it is still useful for detecting and identifying viruses.