Abstract
AbstractThe use of RNA sequencing from wastewater samples is proven to be a valuable way for estimating infection dynamics and circulating lineages of SARS-CoV-2. This approach has the advantage of being independent from patient population testing and symptomatic disease courses. However, it is equally important to develop easily accessible and scalable tools which can highlight critical changes in infection rates and dynamics over time across different locations given sequencing data from wastewater. Here we provide an analysis of variant dynamics in Germany using wastewater sequencing and present PiGx SARS-CoV-2, a highly reproducible end-to-end pipeline with comprehensive reports. This complete pipeline includes all steps from raw-data to shareable reports, additional taxonomic analysis, deconvolution and geospatial time series analysis. Using our pipeline on a dataset of wastewater samples from different locations across Berlin from February 2021 to June 2021, we could reconstruct the dynamic of the Variant of Concern (VoC) B.1.1.7 (alpha). Additionally, we detected the unique signature mutation M:T26767C for the VoC delta B.1.617.2 (delta) and its rise in late May. This is around 1 week earlier than the increase of the proportion of detected delta cases with 6% in the first week of June and 18% in the second week. We also show that SARS-CoV-2 mutation load measured from wastewater sequencing is correlated with actual case numbers and it has potential to be used in a predictive manner. All in all, our study provides additional evidence that systematic wastewater analysis using sequencing and computational methods can be used for modeling the infection dynamics of SARS-CoV-2. In addition, the results show that our tool can be used to identify new mutations and to detect any emerging new lineages of concern. Our approach can support efforts for establishing continuous monitoring and early-warning projects for detecting SARS-CoV-2 or any other detectable pathogen.
Publisher
Cold Spring Harbor Laboratory
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献