Unsupervised detection of SARS-CoV-2 mutations and lineages in Norwegian wastewater samples using long-read sequencing DOI Creative Commons
Ignacio García,

Rasmus Kopperud Riis,

Line Victoria Moen

и другие.

medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Авг. 28, 2024

The COVID-19 pandemic has underscored the importance of virus surveillance in public health and wastewater-based epidemiology (WBE) emerged as a non-invasive, cost-effective method for monitoring SARS-CoV-2 its variants at community level. Unfortunately, current variant methods depend heavily on genomic databases with data derived from clinical samples, which can become less sensitive representative testing sequencing efforts decline. In this paper, we introduce HERCULES (High-throughput Epidemiological Reconstruction Clustering Uncovering Lineages Environmental SARS-CoV-2), an unsupervised, database-independent that uses long-read single 1 Kb fragment Spike gene. identifies quantifies mutations lineages without requiring database-guided deconvolution, enhancing detection novel variants. We evaluated Norwegian wastewater samples collected July 2022 to October 2023 part national pilot WBE SARS-CoV-2. Strong correlations were observed between sample terms prevalence lineages. Furthermore, found trends identified one week earlier than data. Our results demonstrate HERCULES' capability identify new before their providing early warnings potential outbreaks. methodology described paper is easily adaptable other pathogens, offering versatile tool environmental emerging pathogens.

Язык: Английский

Unsupervised detection of novel SARS-CoV-2 mutations and lineages in wastewater samples using long-read sequencing DOI Creative Commons
Ignacio García,

Rasmus K. Riis,

Line Victoria Moen

и другие.

BMC Genomics, Год журнала: 2025, Номер 26(1)

Опубликована: Янв. 29, 2025

Abstract The COVID-19 pandemic has underscored the importance of virus surveillance in public health and wastewater-based epidemiology (WBE) emerged as a non-invasive, cost-effective method for monitoring SARS-CoV-2 its variants at community level. Unfortunately, current variant methods depend heavily on updated genomic databases with data derived from clinical samples, which can become less sensitive representative testing sequencing efforts decline. In this paper, we introduce HERCULES ( H igh-throughput E pidemiological R econstruction C lustering U ncovering L ineages nvironmental S ARS-CoV-2), an unsupervised that uses long-read single 1 Kb fragment Spike gene. identifies quantifies mutations lineages without requiring database-guided deconvolution, enhancing detection novel variants. We evaluated Norwegian wastewater samples collected July 2022 to October 2023 part national pilot WBE SARS-CoV-2. Strong correlations were observed between sample terms prevalence lineages. Furthermore, found trends identified one week earlier than data. Our results demonstrate HERCULES’ capability identify new before their providing early warnings potential outbreaks. methodology described paper is easily adaptable other pathogens, offering versatile tool environmental emerging pathogens.

Язык: Английский

Процитировано

0
Unsupervised detection of SARS-CoV-2 mutations and lineages in Norwegian wastewater samples using long-read sequencing DOI Creative Commons
Ignacio García,

Rasmus Kopperud Riis,

Line Victoria Moen

и другие.

medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Авг. 28, 2024

The COVID-19 pandemic has underscored the importance of virus surveillance in public health and wastewater-based epidemiology (WBE) emerged as a non-invasive, cost-effective method for monitoring SARS-CoV-2 its variants at community level. Unfortunately, current variant methods depend heavily on genomic databases with data derived from clinical samples, which can become less sensitive representative testing sequencing efforts decline. In this paper, we introduce HERCULES (High-throughput Epidemiological Reconstruction Clustering Uncovering Lineages Environmental SARS-CoV-2), an unsupervised, database-independent that uses long-read single 1 Kb fragment Spike gene. identifies quantifies mutations lineages without requiring database-guided deconvolution, enhancing detection novel variants. We evaluated Norwegian wastewater samples collected July 2022 to October 2023 part national pilot WBE SARS-CoV-2. Strong correlations were observed between sample terms prevalence lineages. Furthermore, found trends identified one week earlier than data. Our results demonstrate HERCULES' capability identify new before their providing early warnings potential outbreaks. methodology described paper is easily adaptable other pathogens, offering versatile tool environmental emerging pathogens.

Язык: Английский

Процитировано

0