Ivan Topolsky

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Topolsky

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Ivan

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0000-0002-7561-0810

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Publications 1 - 10 of 21

How much should we sequence? An analysis of the Swiss SARS-CoV-2 surveillance effort
Wegner, Fanny; Cabrera-Gil, Blanca; Araud, Tanguy; et al. (2023)
medRxiv
Background During the SARS-CoV-2 pandemic, many countries directed substantial resources towards genomic surveillance to detect and track viral variants. There is a debate over how much sequencing effort is necessary in national surveillance programs for SARS-CoV-2 and future pandemic threats. Aim We aimed to investigate the effect of reduced sequencing on surveillance outcomes in a large genomic dataset from Switzerland, comprising more than 143k sequences. Methods We employed a uniform downsampling strategy using 100 iterations each to investigate the effects of fewer available sequences on the surveillance outcomes: (i) first detection of variants of concern (VOCs), (ii) speed of introduction of VOCs, (iii) diversity of lineages, (iv) first cluster detection of VOCs, (v) density of active clusters, and (vi) geographic spread of clusters. Results The impact of downsampling on VOC detection is disparate for the three VOC lineages, but many outcomes including introduction and cluster detection could be recapitulated even with only 35% of the original sequencing effort. The effect on the observed speed of introduction and first detection of clusters was more sensitive to reduced sequencing effort for some VOCs, in particular Omicron and Delta, respectively. Conclusion A genomic surveillance program needs a balance between societal benefits and costs. While the overall national dynamics of the pandemic could be recapitulated by a reduced sequencing effort, the effect is strongly lineage dependent – something that is unknown at the time of sequencing – and comes at the cost of accuracy, in particular for tracking the emergence of potential VOCs.
Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data
Nadeau, Sarah Ann; Vaughan, Timothy G.; Beckmann, Christiane; et al. (2023)
Science Translational Medicine
Genome sequences from evolving infectious pathogens allow quantification of case introductions and local transmission dynamics. We sequenced 11,357 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Switzerland in 2020 - the sixth largest effort globally. Using a representative subset of these data, we estimated viral introductions to Switzerland and their persistence over the course of 2020. We contrasted these estimates with simple null models representing the absence of certain public health measures. We show that Switzerland’s border closures de-coupled case introductions from incidence in neighboring countries. Under a simple model, we estimate an 86–98% reduction in introductions during Switzerland’s strictest border closures. Furthermore, the Swiss 2020 partial lockdown roughly halved the time for sampled introductions to die out. Last, we quantified local transmission dynamics once introductions into Switzerland occurred, using a phylodynamic model. We found that transmission slowed 35–63% upon outbreak detection in summer 2020, but not in fall. This finding may indicate successful contact tracing over summer before overburdening in fall. The study highlights the added value of genome sequencing data for understanding transmission dynamics.
V-pipe 3.0: a sustainable pipeline for within-sample viral genetic diversity estimation
Fuhrmann, Lara; Jablonski, Kim Philipp; Topolsky, Ivan; et al. (2024)
GigaScience
The large amount and diversity of viral genomic datasets generated by next-generation sequencing technologies poses a set of challenges for computational data analysis workflows, including rigorous quality control, scaling to large sample sizes, and tailored steps for specific applications. Here, we present V-pipe 3.0, a computational pipeline designed for analyzing next-generation sequencing data of short viral genomes. It is developed to enable reproducible, scalable, adaptable, and transparent inference of genetic diversity of viral samples. By presenting 2 large-scale data analysis projects, we demonstrate the effectiveness of V-pipe 3.0 in supporting sustainable viral genomic data science.
How much should we sequence? An analysis of the Swiss SARS-CoV-2 surveillance effort
Wegner, Fanny; Cabrera-Gil, Blanca; Tanguy, Araud; et al. (2024)
Microbiology Spectrum
During the SARS-CoV-2 pandemic, many countries directed substantial resources toward genomic surveillance to detect and track viral variants. There is a debate over how much sequencing effort is necessary in national surveillance programs for SARS-CoV-2 and future pandemic threats. We aimed to investigate the effect of reduced sequencing on surveillance outcomes in a large genomic data set from Switzerland, comprising more than 143k sequences. We employed a uniform downsampling strategy using 100 iterations each to investigate the effects of fewer available sequences on the surveillance outcomes: (i) first detection of variants of concern (VOCs), (ii) speed of introduction of VOCs, (iii) diversity of lineages, (iv) first cluster detection of VOCs, (v) density of active clusters, and (vi) geographic spread of clusters. The impact of downsampling on VOC detection is disparate for the three VOC lineages, but many outcomes including introduction and cluster detection could be recapitulated even with only 35% of the original sequencing effort. The effect on the observed speed of introduction and first detection of clusters was more sensitive to reduced sequencing effort for some VOCs, in particular Omicron and Delta, respectively. A genomic surveillance program needs a balance between societal benefits and costs. While the overall national dynamics of the pandemic could be recapitulated by a reduced sequencing effort, the effect is strongly lineage-dependent-something that is unknown at the time of sequencing-and comes at the cost of accuracy, in particular for tracking the emergence of potential VOCs.IMPORTANCESwitzerland had one of the most comprehensive genomic surveillance systems during the COVID-19 pandemic. Such programs need to strike a balance between societal benefits and program costs. Our study aims to answer the question: How would surveillance outcomes have changed had we sequenced less? We find that some outcomes but also certain viral lineages are more affected than others by sequencing less. However, sequencing to around a third of the original effort still captured many important outcomes for the variants of concern such as their first detection but affected more strongly other measures like the detection of first transmission clusters for some lineages. Our work highlights the importance of setting predefined targets for a national genomic surveillance program based on which sequencing effort should be determined. Additionally, the use of a centralized surveillance platform facilitates aggregating data on a national level for rapid public health responses as well as post-analyses.
Quantifying SARS-CoV-2 spread in Switzerland based on genomic sequencing data
Nadeau, Sarah Ann; Beckmann, Christiane; Topolsky, Ivan; et al. (2020)
medRxiv
Pathogen genomes provide insights into their evolution and epidemic spread. We sequenced 1,439 SARS-CoV-2 genomes from Switzerland, representing 3-7% of all confirmed cases per week. Using these data, we demonstrate that no one lineage became dominant, pointing against evolution towards general lower virulence. On an epidemiological level, we report no evidence of cryptic transmission before the first confirmed case. We find many early viral introductions from Germany, France, and Italy and many recent introductions from Germany and France. Over the summer, we quantify the number of non-traceable infections stemming from introductions, quantify the effective reproductive number, and estimate the degree of undersampling. Our framework can be applied to quantify evolution and epidemiology in other locations or for other pathogens based on genomic data.
Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data
Sutcliffe, Steven G.; Kraemer, Susanne A.; Ellmen, Isaac; et al. (2024)
Microbial Genomics
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.
Tracking SARS-CoV-2 genomic variants in wastewater sequencing data with LolliPop
Dreifuss, David; Topolsky, Ivan; Icer Baykal, Pelin; et al. (2022)
medRxiv
During the COVID-19 pandemic, wastewater-based epidemiology has progressively taken a central role as a pathogen surveillance tool. Tracking viral loads and variant outbreaks in sewage offers advantages over clinical surveillance methods by providing unbiased estimates and enabling early detection. However, wastewater-based epidemiology poses new computational research questions that need to be solved in order for this approach to be implemented broadly and successfully. Here, we address the variant deconvolution problem, where we aim to estimate the relative abundances of genomic variants from next-generation sequencing data of a mixed wastewater sample. We introduce LolliPop, a computational method to solve the variant deconvolution problem by simultaneously solving least squares problems and kernel-based smoothing of relative variant abundances from wastewater time series sequencing data. We derive multiple approaches to compute confidence bands, and demonstrate the application of our method to data from the Swiss wastewater surveillance efforts
Wastewater monitoring of SARS-CoV-2 shows high correlation with COVID-19 case numbers and allowed early detection of the first confirmed B.1.1.529 infection in Switzerland: results of an observational surveillance study
Bagutti, Claudia; Alt Hug, Monica; Heim, Philippe; et al. (2022)
Swiss Medical Weekly
AIMS OF THE STUDY: Wastewater-based epidemiology has contributed significantly to the comprehension of the dynamics of the current COVID-19 pandemic. Its additional value in monitoring SARS-CoV-2 circulation in the population and identifying newly arising variants independently of diagnostic testing is now undisputed. As a proof of concept, we report here correlations between SARS-CoV-2 detection in wastewater and the officially recorded COVID-19 case numbers, as well as the validity of such surveillance to detect emerging variants, exemplified by the detection of the B.1.1.529 variant Omicron in Basel, Switzerland. METHODS: From July 1 to December 31, 2021, wastewater samples were collected six times a week from the inflow of the local wastewater treatment plant that receives wastewater from the catchment area of the city of Basel, Switzerland, comprising 273,075 inhabitants. The number of SARS-CoV-2 RNA copies was determined by reverse transcriptase-quantitative PCR. Spearman’s rank correlation coefficients were calculated to determine correlations with the median seven-day incidence of genome copies per litre of wastewater and official case data. To explore delayed correlation effects between the seven-day median number of genome copies/litre wastewater and the median seven-day incidence of SARS-CoV-2 cases, time-lagged Spearman’s rank correlation coefficients were calculated for up to 14 days. RNA extracts from daily wastewater samples were used to genotype circulating SARS-CoV-2 variants by next-generation sequencing. RESULTS: The number of daily cases and the median seven-day incidence of SARS-CoV-2 infections in the catchment area showed a high correlation with SARS-CoV-2 measurements in wastewater samples. All correlations between the seven-day median number of genome copies/litre wastewater and the time-lagged median seven-day incidence of SARS-CoV-2 cases were significant (p<0.001) for the investigated lag of up to 14 days. Correlation coefficients declined constantly from the maximum of 0.9395 on day 1 to the minimum of 0.8016 on day 14. The B.1.1.529 variant Omicron was detected in wastewater samples collected on November 21, 2021, before its official acknowledgement in a clinical sample by health authorities. CONCLUSIONS: In this proof-of-concept study, wastewater-based epidemiology proved a reliable and sensitive surveillance approach, complementing routine clinical testing for mapping COVID-19 pandemic dynamics and observing newly circulating SARS-CoV-2 variants.
Detection and Molecular Characterization of the SARS-CoV-2 Delta Variant and the Specific Immune Response in Companion Animals in Switzerland
Kuhlmeier, Evelyn; Chan, Tatjana; Valenzuela Agüí, Cecilia; et al. (2023)
Viruses
In human beings, there are five reported variants of concern of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). However, in contrast to human beings, descriptions of infections of animals with specific variants are still rare. The aim of this study is to systematically investigate SARS-CoV-2 infections in companion animals in close contact with SARS-CoV-2-positive owners (“COVID-19 households”) with a focus on the Delta variant. Samples, obtained from companion animals and their owners were analyzed using a real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) and next-generation sequencing (NGS). Animals were also tested for antibodies and neutralizing activity against SARS-CoV-2. Eleven cats and three dogs in nine COVID-19-positive households were RT-qPCR and/or serologically positive for the SARS-CoV-2 Delta variant. For seven animals, the genetic sequence could be determined. The animals were infected by one of the pangolin lineages B.1.617.2, AY.4, AY.43 and AY.129 and between zero and three single-nucleotide polymorphisms (SNPs) were detected between the viral genomes of animals and their owners, indicating within-household transmission between animal and owner and in multi-pet households also between the animals. NGS data identified SNPs that occur at a higher frequency in the viral sequences of companion animals than in viral sequences of humans, as well as SNPs, which were exclusively found in the animals investigated in the current study and not in their owners. In conclusion, our study is the first to describe the SARS-CoV-2 Delta variant transmission to animals in Switzerland and provides the first-ever description of Delta-variant pangolin lineages AY.129 and AY.4 in animals. Our results reinforce the need of a One Health approach in the monitoring of SARS-CoV-2 in animals.
VILOCA: sequencing quality-aware viral haplotype reconstruction and mutation calling for short-read and long-read data
Fuhrmann, Lara; Langer, Benjamin; Topolsky, Ivan; et al. (2024)
NAR Genomics and Bioinformatics
RNA viruses exist as large heterogeneous populations within their host. The structure and diversity of virus populations affects disease progression and treatment outcomes. Next-generation sequencing allows detailed viral population analysis, but inferring diversity from error-prone reads is challenging. Here, we present VILOCA (VIral LOcal haplotype reconstruction and mutation CAlling for short and long read data), a method for mutation calling and reconstruction of local haplotypes from short- and long-read viral sequencing data. Local haplotypes refer to genomic regions that have approximately the length of the input reads. VILOCA recovers local haplotypes by using a Dirichlet process mixture model to cluster reads around their unobserved haplotypes and leveraging quality scores of the sequencing reads. We assessed the performance of VILOCA in terms of mutation calling and haplotype reconstruction accuracy on simulated and experimental Illumina, PacBio and Oxford Nanopore data. On simulated and experimental Illumina data, VILOCA performed better or similar to existing methods. On the simulated long-read data, VILOCA is able to recover on average 82% of the ground truth mutations with perfect precision compared to only 69% recall and 68% precision of the second-best method. In summary, VILOCA provides significantly improved accuracy in mutation and haplotype calling, especially for long-read sequencing data, and therefore facilitates the comprehensive characterization of heterogeneous within-host viral populations.

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