Wastewater-based surveillance of respiratory syncytial virus (RSV) genome sequence variations in the Windsor-Essex border region

Isidora Sekaric, Department of Chemistry and Biochemistry, University of Windsor
Ana Podadera, Department of Chemistry and Biochemistry, University of Windsor
Mackenzie Beach, Great Lakes Institute for Environmental Research, University of Windsor
Ryland Corchis-Scott, Great Lakes Institute for Environmental Research, University of Windsor
Ethan Harrop, Great Lakes Institute for Environmental Research, University of Windsor
Qiudi Geng, Great Lakes Institute for Environmental Research, University of Windsor
R. Michael McKay, Great Lakes Institute for Environmental Research, University of Windsor
Kenneth K.S. Ng, Department of Chemistry and Biochemistry, University of Windsor

Description

Respiratory syncytial virus (RSV) is a leading cause of respiratory tract infections in both pediatric and elderly populations. RSV is an enveloped, negative-sense, single-stranded RNA virus that belongs to the Pneumoviridae family. In addition to the variation seen in the two antigenically distinct subtypes of RSV, A and B, previous genomic sequencing studies on clinical samples show particular variability in the sequences of the attachment protein G and fusion protein F. To more thoroughly evaluate the amount of variation in RSV genomic sequences in the Windsor-Essex border region, we are in the process of developing a robust tiled amplicon sequencing method that targets the G and F genes for RSV subtypes A and B. Our method uses primer sequences from the ARTIC network, R10.4.1 flow cells on the Oxford Nanopore MinION platform, and data processing and bioinformatics analysis from the Galaxy Suite. Preliminary results indicate that high levels of sequence coverage and redundancy can be obtained for the complete G gene and part of the F gene of RSV A and B from many of wastewater samples collected from hospitals, student residence halls, and wastewater plants. Improvements in sample preparation, primer design and the conditions for multiplex amplification are currently being explored to further improve the reliability and sensitivity of our novel genomic surveillance method for monitoring the evolution of sequence variations over time, including the emergence of novel variants of concern.

 
Mar 22nd, 11:00 AM Mar 22nd, 5:30 PM

Wastewater-based surveillance of respiratory syncytial virus (RSV) genome sequence variations in the Windsor-Essex border region

Respiratory syncytial virus (RSV) is a leading cause of respiratory tract infections in both pediatric and elderly populations. RSV is an enveloped, negative-sense, single-stranded RNA virus that belongs to the Pneumoviridae family. In addition to the variation seen in the two antigenically distinct subtypes of RSV, A and B, previous genomic sequencing studies on clinical samples show particular variability in the sequences of the attachment protein G and fusion protein F. To more thoroughly evaluate the amount of variation in RSV genomic sequences in the Windsor-Essex border region, we are in the process of developing a robust tiled amplicon sequencing method that targets the G and F genes for RSV subtypes A and B. Our method uses primer sequences from the ARTIC network, R10.4.1 flow cells on the Oxford Nanopore MinION platform, and data processing and bioinformatics analysis from the Galaxy Suite. Preliminary results indicate that high levels of sequence coverage and redundancy can be obtained for the complete G gene and part of the F gene of RSV A and B from many of wastewater samples collected from hospitals, student residence halls, and wastewater plants. Improvements in sample preparation, primer design and the conditions for multiplex amplification are currently being explored to further improve the reliability and sensitivity of our novel genomic surveillance method for monitoring the evolution of sequence variations over time, including the emergence of novel variants of concern.

https://scholar.uwindsor.ca/we-spark-conference/2025/postersessions/69