Targeted amplicon sequencing of wastewater samples for detecting SARS-CoV-2 variants with high sensitivity and resolution

Kuroiwa, Miho; Gahara, Yoshinari; Kato, Harubumi; Morikawa, Yuji; Matsui, Yoshihiko; Adachi, Takumi; Kurosawa, Shin; Kuroita, Tomohiro; Ando, Yoshinori; Rokushima, Masatomo

doi:10.1016/j.scitotenv.2023.164766

Cited by 13 publications

(9 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To identify the variant specific mutations, we utilized the CoV-Spectrum platform which contains the percentage proportion of amino acid and nucleotide mutations of the clinical sample sequences submitted to database 18 . The CoV-Spectrum has been used as a source to identify variant specific mutations in order to compare clinical and wastewater data and the identification of variants from wastewater studies 26 – 28 . This way, we could systematically identify variant specific mutations and use them to recognize SARS-CoV-2 variants from wastewater sequencing data in the time frame of interest and update list of specific mutations to recognize other variants.…”

Section: Discussionmentioning

confidence: 99%

Detection of SARS-COV-2 variants and their proportions in wastewater samples using next-generation sequencing in Finland

Lipponen,

Kolehmainen,

Oikarinen

et al. 2024

Sci Rep

View full text Add to dashboard Cite

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants may have different characteristics, e.g., in transmission, mortality, and the effectiveness of vaccines, indicating the importance of variant detection at the population level. Wastewater-based surveillance of SARS-CoV-2 RNA fragments has been shown to be an effective way to monitor the COVID-19 pandemic at the population level. Wastewater is a complex sample matrix affected by environmental factors and PCR inhibitors, causing insufficient coverage in sequencing, for example. Subsequently, results where part of the genome does not have sufficient coverage are not uncommon. To identify variants and their proportions in wastewater over time, we utilized next-generation sequencing with the ARTIC Network's primer set and bioinformatics pipeline to evaluate the presence of variants in partial genome data. Based on the wastewater data from November 2021 to February 2022, the Delta variant was dominant until mid-December in Helsinki, Finland’s capital, and thereafter in late December 2022 Omicron became the most common variant. At the same time, the Omicron variant of SARS-CoV-2 outcompeted the previous Delta variant in Finland in new COVID-19 cases. The SARS-CoV-2 variant findings from wastewater are in agreement with the variant information obtained from the patient samples when visually comparing trends in the sewerage network area. This indicates that the sequencing of wastewater is an effective way to monitor temporal and spatial trends of SARS-CoV-2 variants at the population level.

show abstract

Section: Discussionmentioning

confidence: 99%

Detection of SARS-COV-2 variants and their proportions in wastewater samples using next-generation sequencing in Finland

Lipponen,

Kolehmainen,

Oikarinen

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…As we write, SARS-CoV-2 genome sequencing has been deployed in wastewater from across the globe (e.g. USA, Canada, Uruguay, Japan, Italy, India, Spain) to augment surveillance efforts during Gamma, Delta, and Omicron (BA.1 to XBB/BQ) waves [ 12 13 27 28 51 ]. The uptake of wastewater sequencing data to bring lineage-level information to WBS highlights the importance of benchmarking and developing standards.…”

Section: Discussionmentioning

confidence: 99%

“…Designing primers to distinguish among VOCs by qPCR [9] can be laborious and is hindered by novel viral mutations [10]. A complementary approach to qPCR is to measure viral diversity by sequencing parts, or the entirety, of the viral genomes found in wastewater [11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data

Sutcliffe,

Kraemer,

Ellmen

et al. 2024

Microbial Genomics

View full text Add to dashboard Cite

Wastewater-based surveillance (WBS) is an important epidemiological and public health tool for tracking pathogens across the scale of a building, neighbourhood, city, or region. WBS gained widespread adoption globally during the SARS-CoV-2 pandemic for estimating community infection levels by qPCR. Sequencing pathogen genes or genomes from wastewater adds information about pathogen genetic diversity, which can be used to identify viral lineages (including variants of concern) that are circulating in a local population. Capturing the genetic diversity by WBS sequencing is not trivial, as wastewater samples often contain a diverse mixture of viral lineages with real mutations and sequencing errors, which must be deconvoluted computationally from short sequencing reads. In this study we assess nine different computational tools that have recently been developed to address this challenge. We simulated 100 wastewater sequence samples consisting of SARS-CoV-2 BA.1, BA.2, and Delta lineages, in various mixtures, as well as a Delta–Omicron recombinant and a synthetic ‘novel’ lineage. Most tools performed well in identifying the true lineages present and estimating their relative abundances and were generally robust to variation in sequencing depth and read length. While many tools identified lineages present down to 1 % frequency, results were more reliable above a 5 % threshold. The presence of an unknown synthetic lineage, which represents an unclassified SARS-CoV-2 lineage, increases the error in relative abundance estimates of other lineages, but the magnitude of this effect was small for most tools. The tools also varied in how they labelled novel synthetic lineages and recombinants. While our simulated dataset represents just one of many possible use cases for these methods, we hope it helps users understand potential sources of error or bias in wastewater sequencing analysis and to appreciate the commonalities and differences across methods.

show abstract

“…Since then, the recombinant XBB (Nextstrain clade 22F) has risen to global abundance, and convergent mutations have made it increasingly challenging to disentangle lineages. As we write, SARS-CoV-2 genome sequencing has been deployed in wastewater from across the globe (e.g., USA, Canada, Uruguay, Japan, Italy, India, Spain) to augment surveillance efforts during Gamma, Delta, and Omicron (BA.1 to XBB/BQ) waves 12,13,25,26,48 . The uptake of wastewater sequencing data to bring lineage-level information to WBS highlights the importance of benchmarking and developing standards.…”

Section: Discussionmentioning

confidence: 99%

“…Designing primers to distinguish among VOCs by qPCR 9 can be laborious and is hindered by novel viral mutations 10 . A complementary approach to qPCR is to measure viral diversity by sequencing parts, or the entirety, of the viral genomes found in wastewater [11][12][13][14][15] .…”

Section: Introductionmentioning

confidence: 99%

Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data

Sutcliffe,

Kraemer,

Ellmen

et al. 2023

Preprint

View full text Add to dashboard Cite

Wastewater-based surveillance (WBS) is an important epidemiological and public health tool for tracking pathogens across the scale of a building, neighbourhood, city, or region. WBS gained widespread adoption globally during the SARS-CoV-2 pandemic for estimating community infection levels by qPCR. Sequencing pathogen genes or genomes from wastewater adds information about pathogen genetic diversity which can be used to identify viral lineages (including variants of concern) that are circulating in a local population. Capturing the genetic diversity by WBS sequencing is not trivial, as wastewater samples often contain a diverse mixture of viral lineages with real mutations and sequencing errors, which must be deconvoluted computationally from short sequencing reads. In this study we assess nine different computational tools that have recently been developed to address this challenge. We simulated 100 wastewater sequence samples consisting of SARS-CoV-2 BA.1, BA.2, and Delta lineages, in various mixtures, as well as a Delta-Omicron recombinant and a synthetic “novel” lineage. Most tools performed well in identifying the true lineages present and estimating their relative abundances, and were generally robust to variation in sequencing depth and read length. While many tools identified lineages present down to 1% frequency, results were more reliable above a 5% threshold. The presence of an unknown synthetic lineage, which represents an unclassified SARS-CoV-2 lineage, increases the error in relative abundance estimates of other lineages, but the magnitude of this effect was small for most tools. The tools also varied in how they labelled novel synthetic lineages and recombinants. While our simulated dataset represents just one of many possible use cases for these methods, we hope it helps users understand potential sources of noise or bias in wastewater sequencing data and to appreciate the commonalities and differences across methods.

show abstract

Targeted amplicon sequencing of wastewater samples for detecting SARS-CoV-2 variants with high sensitivity and resolution

Cited by 13 publications

References 45 publications

Detection of SARS-COV-2 variants and their proportions in wastewater samples using next-generation sequencing in Finland

Detection of SARS-COV-2 variants and their proportions in wastewater samples using next-generation sequencing in Finland

Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data

Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data

Contact Info

Product

Resources

About