Dataset Information

A robust, scalable, and cost-efficient approach to whole genome sequencing of RSV directly from clinical samples.

ABSTRACT: Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infections causing significant morbidity and mortality among children and the elderly; two RSV vaccines and a monoclonal antibody have recently been approved. Thus, there is an increasing need for a detailed and continuous genomic surveillance of RSV circulating in resource-rich and resource-limited settings worldwide. However, robust, cost-effective methods for whole genome sequencing of RSV from clinical samples that are amenable to high-throughput are still scarce. We developed Next-RSV-SEQ, an experimental and computational pipeline to generate whole genome sequences of historic and current RSV genotypes by in-solution hybridization capture-based next generation sequencing. We optimized this workflow by automating library preparation and pooling libraries prior to enrichment in order to reduce hands-on time and cost, thereby augmenting scalability. Next-RSV-SEQ yielded near-complete to complete genome sequences for 98% of specimens with Cp values ≤31, at median on-target reads >93%, and mean coverage depths between ~1,000 and >5,000, depending on viral load. Whole genomes were successfully recovered from samples with viral loads as low as 230 copies per microliter RNA. We demonstrate that the method can be expanded to other respiratory viruses like parainfluenza virus and human metapneumovirus. Next-RSV-SEQ produces high-quality RSV genomes directly from culture isolates and, more importantly, clinical specimens of all genotypes in circulation. It is cost-efficient, scalable, and can be extended to other respiratory viruses, thereby opening new perspectives for a future effective and broad genomic surveillance of respiratory viruses.

Importance

Respiratory syncytial virus (RSV) is a leading cause of severe acute respiratory tract infections in children and the elderly, and its prevention has become an increasing priority. Recently, vaccines and a long-acting monoclonal antibody to protect effectively against severe disease have been approved for the first time. Hence, there is an urgent need for genomic surveillance of RSV at the global scale to monitor virus evolution, especially with an eye toward immune evasion. However, robust, cost-effective methods for RSV whole genome sequencing that are suitable for high-throughput of clinical samples are currently scarce. Therefore, we have developed Next-RSV-SEQ, an experimental and computational pipeline that produces reliably high-quality RSV genomes directly from clinical specimens and isolates.

SUBMITTER: Kondgen S

PROVIDER: S-EPMC10935636 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

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A robust, scalable, and cost-efficient approach to whole genome sequencing of RSV directly from clinical samples.

Köndgen Sophie S Oh Djin-Ye D-Y Thürmer Andrea A Sedaghatjoo Somayyeh S Patrono Livia V LV Calvignac-Spencer Sébastien S Biere Barbara B Wolff Thorsten T Dürrwald Ralf R Fuchs Stephan S Reiche Janine J

Journal of clinical microbiology 20240226 3

Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infections causing significant morbidity and mortality among children and the elderly; two RSV vaccines and a monoclonal antibody have recently been approved. Thus, there is an increasing need for a detailed and continuous genomic surveillance of RSV circulating in resource-rich and resource-limited settings worldwide. However, robust, cost-effective methods for whole genome sequencing of RSV from clinical samp ...[more]

PMID: 38407068

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Project description:Whole-genome sequencing (WGS) of microbial pathogens from clinical samples is a highly sensitive tool used to gain a deeper understanding of the biology, epidemiology, and drug resistance mechanisms of many infections. However, WGS of organisms which exhibit low densities in their hosts is challenging due to high levels of host genomic DNA (gDNA), which leads to very low coverage of the microbial genome. WGS of Plasmodium vivax, the most widely distributed form of malaria, is especially difficult because of low parasite densities and the lack of an ex vivo culture system. Current techniques used to enrich P. vivax DNA from clinical samples require significant resources or are not consistently effective. Here, we demonstrate that selective whole-genome amplification (SWGA) can enrich P. vivax gDNA from unprocessed human blood samples and dried blood spots for high-quality WGS, allowing genetic characterization of isolates that would otherwise have been prohibitively expensive or impossible to sequence. We achieved an average genome coverage of 24×, with up to 95% of the P. vivax core genome covered by ≥5 reads. The single-nucleotide polymorphism (SNP) characteristics and drug resistance mutations seen were consistent with those of other P. vivax sequences from a similar region in Peru, demonstrating that SWGA produces high-quality sequences for downstream analysis. SWGA is a robust tool that will enable efficient, cost-effective WGS of P. vivax isolates from clinical samples that can be applied to other neglected microbial pathogens. Malaria is a disease caused by Plasmodium parasites that caused 214 million symptomatic cases and 438,000 deaths in 2015. Plasmodium vivax is the most widely distributed species, causing the majority of malaria infections outside sub-Saharan Africa. Whole-genome sequencing (WGS) of Plasmodium parasites from clinical samples has revealed important insights into the epidemiology and mechanisms of drug resistance of malaria. However, WGS of P. vivax is challenging due to low parasite levels in humans and the lack of a routine system to culture the parasites. Selective whole-genome amplification (SWGA) preferentially amplifies the genomes of pathogens from mixtures of target and host gDNA. Here, we demonstrate that SWGA is a simple, robust method that can be used to enrich P. vivax genomic DNA (gDNA) from unprocessed human blood samples and dried blood spots for cost-effective, high-quality WGS.

Project description:BackgroundChlamydia trachomatis is a pathogen of worldwide importance, causing more than 100 million cases of sexually transmitted infections annually. Whole-genome sequencing is a powerful high resolution tool that can be used to generate accurate data on bacterial population structure, phylogeography and mutations associated with antimicrobial resistance. The objective of this study was to perform whole-genome enrichment and sequencing of C. trachomatis directly from clinical samples.MethodsC. trachomatis positive samples comprising seven vaginal swabs and three urine samples were sequenced without prior in vitro culture in addition to nine cultured C. trachomatis samples, representing different serovars. A custom capture RNA bait set, that captures all known diversity amongst C. trachomatis genomes, was used in a whole-genome enrichment step during library preparation to enrich for C. trachomatis DNA. All samples were sequenced on the MiSeq platform.ResultsFull length C. trachomatis genomes (>95-100% coverage of a reference genome) were successfully generated for eight of ten clinical samples and for all cultured samples. The proportion of reads mapping to C. trachomatis and the mean read depth across each genome were strongly linked to the number of bacterial copies within the original sample. Phylogenetic analysis confirmed the known population structure and the data showed potential for identification of minority variants and mutations associated with antimicrobial resistance. The sensitivity of the method was >10-fold higher than other reported methodologies.ConclusionsThe combination of whole-genome enrichment and deep sequencing has proven to be a non-mutagenic approach, capturing all known variation found within C. trachomatis genomes. The method is a consistent and sensitive tool that enables rapid whole-genome sequencing of C. trachomatis directly from clinical samples and has the potential to be adapted to other pathogens with a similar clonal nature.

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Dataset Information

A robust, scalable, and cost-efficient approach to whole genome sequencing of RSV directly from clinical samples.

Importance

Publications

A robust, scalable, and cost-efficient approach to whole genome sequencing of RSV directly from clinical samples.

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