Evaluation of a commercial exogenous internal process control for diagnostic RNA virus metagenomics from different...

Metagenomic next generation sequencing (mNGS) is increasingly recognized as an important complementary tool to targeted human and animal infectious disease diagnostics. It is, however, sensitive to biases and errors that are currently not systematically evaluated by the implementation of quality controls (QC) for the diagnostic use of mNGS. We evaluated a commercial reagent (Mengovirus extraction control kit, CeraamTools, bioMérieux) as an exogenous internal control for mNGS. It validates the integrity of reagents and workflow, the efficient isolation of viral nucleic acids and the absence of inhibitors in individual samples (verified using a specific qRT-PCR). Moreover, it validates the efficient generation of viral sequence data in individual samples (verified by normalized mengoviral read counts in the metagenomic analysis). We show that when using a completely random metagenomics workflow: (1) Mengovirus RNA can be reproducibly detected in different animal sample types (swine feces and sera, wild bird cloacal swabs), except for tissue samples (swine lung); (2) the Mengovirus control kit does not contain other contaminating viruses that may affect metagenomic experiments (using a cutoff of minimum 1 Kraken classified read per million (RPM)); (3) the addition of 2.17 × 10⁶Mengovirus copies/mL of sample does not affect the virome composition of pig fecal samples or wild bird cloacal swab samples; (4) Mengovirus Cq values (using as cutoff the upper limit of the 99 % confidence interval of Cq values for a given sample matrix) allow the identification of samples with poor viral RNA extraction or high inhibitor load; (5) Mengovirus normalized read counts (cutoff RPM > 1) allow the identification of samples where the viral sequences are outcompeted by host or bacterial target sequences in the random metagenomic workflow. The implementation of two QC testing points, a first one after RNA extraction (Mengoviral qRT-PCR) and a second one after metagenomic data analysis provide valuable information for the validation of individual samples and results. Their implementation in addition to external controls validating runs or experiments should be carefully considered for a given sample type and workflow.