[en] After a decade of application in research, high throughput sequencing (HTS) technologies are raising a growing interest for virus diagnostics. Many technical challenges are progressively overcome, but the problem of cross-contamination between samples still needs to be addressed, as it can impact both research and diagnostic fields. Indeed, cross-contamination is an exchange of genetic material between the samples that can occur during the laboratory process and may cause false positive results. In the frame of validating HTS as a diagnostic test for indexing banana viruses, we have used an Alien-control (a wheat sample infected by BYDV, a virus that cannot infect banana) as external control processed together with the analyzed samples. This alien control is a new type of control, allowing to monitor cross-contamination.
The monitoring of reads from alien control in banana datasets showed that cross-contamination can be highly variable between sequencing batches and that the contamination threshold should be adapted to each sequencing. In addition, the contamination threshold determination should also consider the results obtained for each banana virus in the batch samples. Those considerations allowed us to reach high performance criteria, e.g. inclusivity, analytical sensitivity, repeatability and reproducibility, of HTS compared to traditional virus indexing on Musa (1). Further on, the automation of cross-contamination checks in bioinformatic analysis via Cont-ID (2) proved that metrics analyses could classify the origin (contamination or infection) of a detected virus with high confidence (91%) for different plants and human datasets. This classification helps raise confidence in the detection and reduce the confirmation work needed by highlighting most critical detections to be checked and also underlined the need for expert judgement.
Monitoring viral cross-contamination in metagenomic datasets, whatever its origin, using an alien control-based strategy is possible and should be recommended to raise confidence in results obtained during research projects or diagnostics.
