Quality control implementation for universal characterization of DNA and RNA viruses in clinical respiratory samples using single metagenomic next-generation sequencing workflow

Abstract

Background: In recent years, metagenomic Next-Generation Sequencing (mNGS) has increasingly been used for an accurate assumption-free virological diagnosis. However, the systematic workflow evaluation on clinical respiratory samples and implementation of quality controls (QCs) is still lacking.

Methods: A total of 3 QCs were implemented and processed through the whole mNGS workflow: a no-template-control to evaluate contamination issues during the process; an internal and an external QC to check the integrity of the reagents, equipment, the presence of inhibitors, and to allow the validation of results for each sample. The workflow was then evaluated on 37 clinical respiratory samples from patients with acute respiratory infections previously tested for a broad panel of viruses using semi-quantitative real-time PCR assays (28 positive samples including 6 multiple viral infections; 9 negative samples). Selected specimens included nasopharyngeal swabs (n = 20), aspirates (n = 10), or sputums (n = 7).

Results: The optimal spiking level of the internal QC was first determined in order to be sufficiently detected without overconsumption of sequencing reads. According to QC validation criteria, mNGS results were validated for 34/37 selected samples. For valid samples, viral genotypes were accurately determined for 36/36 viruses detected with PCR (viral genome coverage ranged from 0.6 to 100%, median = 67.7%). This mNGS workflow allowed the detection of DNA and RNA viruses up to a semi-quantitative PCR Ct value of 36. The six multiple viral infections involving 2 to 4 viruses were also fully characterized. A strong correlation between results of mNGS and real-time PCR was obtained for each type of viral genome (R² ranged from 0.72 for linear single-stranded (ss) RNA viruses to 0.98 for linear ssDNA viruses).

Conclusions: Although the potential of mNGS technology is very promising, further evaluation studies are urgently needed for its routine clinical use within a reasonable timeframe. The approach described herein is crucial to bring standardization and to ensure the quality of the generated sequences in clinical setting. We provide an easy-to-use single protocol successfully evaluated for the characterization of a broad and representative panel of DNA and RNA respiratory viruses in various types of clinical samples.

Keywords: Clinical virology; Next-generation sequencing; Quality control; Respiratory viruses; Viral metagenomics.

Fig. 1

Schematic representation of the metagenomic workflow and quality control steps. The whole process is summarized in the middle. On the left side, internal control (MS2 bacteriophage) is represented in blue, and external controls are represented in red, including positive control (MS2 bacteriophage spiked in viral transport medium) and No-Template Control (NTC: viral transport medium). Quality control testing 1 corresponds to MS2 bacteriophage molecular detection with commercial PCR assay. Quality control testing 2 corresponds to control by sequencing metrics (number of MS2 reads normalized with RPKM ratio and MS2 genome coverage). On the right, each technique used by phases is indicated black. In addition, on the far right the duration of each step is indicated

Fig. 2

Determination of optimal spiking level for internal quality control. The sensitivity of the metagenomic analysis workflow for MS2 bacteriophage (Internal Quality Control, IQC) detection was evaluated with a MS2 ten-fold serial dilutions in a nasopharyngeal swab tested negative with multiplex viral PCR. Relative abundance of MS2 bacteriophage and viral families are represented depending on the MS2 spiked-in concentration. IQCT1 corresponds to MS2 molecular detection with commercial real-time PCR assay after amplification step. IQCT2 corresponds to control by sequencing metrics (number of MS2 reads normalized with RPKM ratio and MS2 genome coverage)

Fig. 3

Internal quality control detection after metagenomic analysis of the respiratory samples selected. Distribution of normalized read counts (RPKM) for MS2 bacteriophage (internal quality control, IQC) depending on the proportion of viral reads for the 37 respiratory samples selected. MS2 RPKM was determined after subtracting of NTC MS2 RPKM. IQC was not detected for 4/37 samples (represented in red); among them 3 samples were tested positive with viral real-time PCR

Fig. 4

Evaluation of the metagenomic NGS workflow according to the viral genome type. a Correlation between the results of metagenomic NGS and viral real-time PCR for validated respiratory samples tested positive with viral PCR. Normalized number of reads (RPKM) obtained for targeted virus are displayed against the real-time PCR Ct values for fragmented ssRNA virus (influenza virus) linear dsDNA virus (adenovirus, Epstein-Baar virus, cytomegalovirus, human herpes virus-6) linear ssDNA (human bocavirus) and linear ssRNA (human rhinovirus, respiratory syncytial virus, parainfluenza virus, human coronavirus, human metapneumovirus and measles virus). The correlation coefficients are shown for each viral genome type. b RPKM normalized by Ct for each viral genome type of validated respiratory samples tested positive with viral PCR. Bars show median and interquartile ranges, p-values calculated with the Mann-Whitney U test are shown