WAVES (Web-based tool for Analysis and Visualization of Environmental Samples) - a web application for visualization of wastewater pathogen sequencing results

Environmental monitoring of pathogens provides an accurate and timely source of information for public health authorities and policymakers. In the last two years, wastewater sequencing proved to be an effective way of detection and quantification of SARS-CoV-2 variants circulating in population. Wastewater sequencing produces substantial amounts of geographical and genomic data. Proper visualization of spatial and temporal patterns in this data is crucial for the assessment of the epidemiological situation and forecasting. Here, we present a web-based dashboard application for visualization and analysis of data obtained from sequencing of environmental samples. The dashboard provides multi-layered visualization of geographical and genomic data. It allows to display frequencies of detected pathogen variants as well as individual mutation frequencies. The features of WAVES for early tracking and detection of novel variants in the wastewater are demonstrated in an example of BA.1 variant and the signature Spike mutation S:E484A. WAVES dashboard is easily customized through the editable configuration file and can be used for different types of pathogens and environmental samples. AvailabilityWAVES source code is freely available at https://github.com/ptriska/WavesDash under MIT license.

VirPool: Model-Based Estimation of SARS-CoV-2 Variant Proportions in Wastewater Samples

BackgroundThe genomes of SARS-CoV-2 are classified into variants, some of which are monitored as variants of concern (e.g. the delta variant B.1.617.2 or omicron variant B.1.1.529). Proportions of these variants in a population are typically estimated by large-scale sequencing of individual patient samples. Sequencing a mixture of SARS-CoV-2 RNA molecules from wastewater provides a cost-effective alternative, but requires methods for estimating variant proportions in a mixed sample. ResultsWe propose a new method based on a probabilistic model of sequencing reads, capturing sequence diversity present within individual variants, as well as sequencing errors. The algorithm is implemented in an open source Python program called VirPool. We evaluated the accuracy of VirPool on several simulated and real sequencing data sets from both Illumina and nanopore sequencing platforms, including wastewater samples from Austria and France monitoring the onset of alpha and delta variants. ConclusionsVirPool is a versatile tool for wastewater and other mixed-sample analysis that can handle both short- and long-read sequencing data. Our approach does not require pre-selection of characteristic mutations for variant profiles, it is able to use the entire length of reads instead of just the most informative positions, and can also capture haplotype dependencies within a single read. AvailabilityVirPool is an open source software available at https://github.com/fmfi-compbio/virpool.

National-scale surveillance of emerging SARS-CoV-2 variants in wastewater

SARS-CoV-2 surveillance is crucial to identify variants with altered epidemiological properties. Wastewater-based epidemiology (WBE) provides an unbiased and complementary approach to sequencing individual cases. Yet, national WBE surveillance programs have not been widely implemented and data analyses remain challenging. We deep-sequenced 2,093 wastewater samples representing 95 municipal catchments, covering >57% of Austrias population, from December 2020 to September 2021. Our Variant Quantification in Sewage pipeline designed for Robustness (VaQuERo) enabled us to deduce variant abundance from complex wastewater samples and delineate the spatiotemporal dynamics of the dominant Alpha and Delta variants as well as regional clusters of other variants of concern. These results were cross validated by epidemiological records of >130,000 individual cases. Finally, we provide a framework to predict emerging variants de novo and infer variant-specific reproduction numbers from wastewater. This study demonstrates the power of national-scale WBE to support public health and promises particular value for countries without dense individual monitoring. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC="FIGDIR/small/21267633v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@1044af0org.highwire.dtl.DTLVardef@d3fe2borg.highwire.dtl.DTLVardef@1d3bfa1org.highwire.dtl.DTLVardef@c9fc95_HPS_FORMAT_FIGEXP M_FIG C_FIG