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An Improved and High Throughput Respiratory Syncytial Virus RSV Micro-neutralization Assay
Published on: January 26, 2019
Whole-genome nanopore sequencing and automatic downstream analysis of respiratory syncytial virus using RSVTyper
Duyen Bao Le1, Inga Tometten1, Nadine Lübke1
1Institute of Virology , University Hospital Düsseldorf Heinrich Heine University Düsseldorf , Düsseldorf, Germany.
Insights
A new RSVTyper method enables whole-genome sequencing of respiratory syncytial virus (RSV) from patient and wastewater samples. This cost-effective tool aids in tracking RSV variants and detecting escape mutations for enhanced public health surveillance.
Area of Science:
- Virology
- Genomics
- Bioinformatics
Background:
- Respiratory syncytial virus (RSV) causes severe respiratory illness in vulnerable populations.
- Recent vaccine approvals necessitate robust surveillance of circulating RSV strains.
- Existing methods may not be sufficiently scalable or cost-effective for comprehensive RSV monitoring.
Purpose of the Study:
- To develop an integrated method for whole-genome sequencing of RSV from clinical and environmental samples.
- To establish a bioinformatics pipeline (RSVTyper) for efficient analysis of RSV genomic data.
- To assess the utility of RSVTyper for surveillance and detection of viral evolution.
Main Methods:
- Developed RSVTyper, an integrated pipeline for RSV amplification, Oxford Nanopore sequencing, and bioinformatics analysis.
- Utilized multiplex tiling PCR to generate overlapping amplicons for whole-genome sequencing.
- Analyzed patient isolates (2008-2025) and wastewater samples (2023-2024) using the RSVTyper pipeline.
Main Results:
- Achieved successful whole-genome sequencing for 213/243 RSV samples, with high coverage for samples above 10,000 copies/mL.
- RSVTyper demonstrated suitability for both patient and wastewater samples, reflecting seasonal clade shifts.
- No detected RSV variants exhibited known escape mutations from current prophylactic monoclonal antibodies.
Conclusions:
- RSVTyper provides a cost-effective, scalable solution for integrated RSV genome sequencing and analysis.
- The method is adaptable for resource-limited settings and high-throughput surveillance applications.
- Enhanced RSV surveillance using RSVTyper can facilitate genomic characterization and rapid detection of immune escape variants.
Abstract:
Respiratory syncytial virus (RSV) is a globally circulating virus, causing severe respiratory infections in infants and the elderly. Two RSV vaccines were recently approved, and passive immunization is now recommended in several countries for all newborns, therefore careful surveillance of RSV variants will be important in the future. We therefore develop an integrated whole genome RSV amplification, sequencing and bioinformatics analysis method ("RSVTyper"; https://anaconda.org/bioconda/rsv-typer ) that is suitable for patient samples as well as wastewater. 243 RSV isolates from 2008 to 2025 and wastewater samples from 2023/2024 were amplified in a multiplex tiling PCR with specific primers, generating 39 amplicons ~ 550 bp in length, and sequenced with Oxford Nanopore Technologies. Sequencing reads of patient isolates were analyzed with the RSVTyper pipeline, a tailored analysis pipeline including automatic reference selection, consensus sequence generation and clade assignment via Nextclade. Amplification and sequencing were successful for 213/243 samples. Whole genomes (> 90% coverage) were obtained from 98% of samples with > 10,000 copies/mL, from 3/14 samples with 1,000-10,000 copies/mL, and from none with < 1,000 copies/mL. Average genome-wide mean depth for successfully sequenced samples was 31,800x with an average mean depth of 41,400x in the F gene. Phylogenetic analysis showed seasonal clade and subtype shifting, with a good representation of clade frequencies from patients in wastewater sequences. No variants with known escape mutations from prophylactic monoclonal antibodies were detected. In conclusion, we developed RSVTyper, a cost-effective and scalable RSV sequencing pipeline by integrating sequencing and bioinformatic analysis. It is suitable for both resource-limited settings and high-throughput applications. It will facilitate enhanced RSV surveillance, allowing for further characterization of the RSV genome and rapid detection of potential escape mutations.

