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Author

Ivan Topolsky

Other affiliations: ETH Zurich, University of Basel
Bio: Ivan Topolsky is an academic researcher from Swiss Institute of Bioinformatics. The author has contributed to research in topics: Medicine & Genomics. The author has an hindex of 7, co-authored 9 publications receiving 162 citations. Previous affiliations of Ivan Topolsky include ETH Zurich & University of Basel.

Papers
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Posted ContentDOI
09 Jan 2021-medRxiv
TL;DR: In this paper, the authors report a genomic analysis of SARS-CoV-2 in 48 raw wastewater samples collected from three wastewater treatment plants in Switzerland between July 9 and December 21, 2020.
Abstract: The SARS-CoV-2 lineages B.1.1.7 and 501.V2, which were first detected in the United Kingdom and South Africa, respectively, are spreading rapidly in the human population. Thus, there is an increased need for genomic and epidemiological surveillance in order to detect the strains and estimate their abundances. Here, we report a genomic analysis of SARS-CoV-2 in 48 raw wastewater samples collected from three wastewater treatment plants in Switzerland between July 9 and December 21, 2020. We find evidence for the presence of several mutations that define the B.1.1.7 and 501.V2 lineages in some of the samples, including co-occurrences of up to three B.1.1.7 signature mutations on the same amplicon in four samples from Lausanne and one sample from a Swiss ski resort dated December 9 - 21. These findings suggest that the B.1.1.7 strain could be detected by mid December, two weeks before its first verification in a patient sample from Switzerland. We conclude that sequencing SARS-CoV-2 in community wastewater samples may help detect and monitor the circulation of diverse lineages.

102 citations

Journal ArticleDOI
TL;DR: An overview of S IB's resources and competence areas is provided, with a strong focus on curated databases and SIB's most popular and widely used resources.
Abstract: The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article.

52 citations

Journal ArticleDOI
TL;DR: In this paper , the authors used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.7 (Alpha), B.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level.
Abstract: The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK.

49 citations

Journal ArticleDOI
TL;DR: V-pipe as mentioned in this paper is a bioinformatics pipeline combining various state-of-the-art statistical models and computational tools for automated end-to-end analyses of raw sequencing reads.
Abstract: Motivation High-throughput sequencing technologies are used increasingly, not only in viral genomics research but also in clinical surveillance and diagnostics. These technologies facilitate the assessment of the genetic diversity in intra-host virus populations, which affects transmission, virulence, and pathogenesis of viral infections. However, there are two major challenges in analysing viral diversity. First, amplification and sequencing errors confound the identification of true biological variants, and second, the large data volumes represent computational limitations. Results To support viral high-throughput sequencing studies, we developed V-pipe, a bioinformatics pipeline combining various state-of-the-art statistical models and computational tools for automated end-to-end analyses of raw sequencing reads. V-pipe supports quality control, read mapping and alignment, low-frequency mutation calling, and inference of viral haplotypes. For generating high-quality read alignments, we developed a novel method, called ngshmmalign, based on profile hidden Markov models and tailored to small and highly diverse viral genomes. V-pipe also includes benchmarking functionality providing a standardized environment for comparative evaluations of different pipeline configurations. We demonstrate this capability by assessing the impact of three different read aligners (Bowtie 2, BWA MEM, ngshmmalign) and two different variant callers (LoFreq, ShoRAH) on the performance of calling single-nucleotide variants in intra-host virus populations. V-pipe supports various pipeline configurations and is implemented in a modular fashion to facilitate adaptations to the continuously changing technology landscape. Availability V-pipe is freely available at https://github.com/cbg-ethz/V-pipe. Supplementary information Supplementary data are available at Bioinformatics online.

49 citations

Journal ArticleDOI
TL;DR: This study estimates the transmission fitness advantage and the effective reproductive number of B.1.1-CoV-2 variant of Concern in Switzerland and quantifies the variant’s transmission Fitness advantage on a national and a regional scale.

24 citations


Cited by
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Journal ArticleDOI
TL;DR: Detailed information is provided on utilizing the three most widely accessed tools within the MPI Bioinformatics Toolkit: HHpred for the detection of homologs, HHpred in conjunction with MODELLER for structure prediction and homology modeling, and CLANS for the visualization of relationships in large sequence datasets.
Abstract: The MPI Bioinformatics Toolkit (https://toolkit.tuebingen.mpg.de) provides interactive access to a wide range of the best-performing bioinformatics tools and databases, including the state-of-the-art protein sequence comparison methods HHblits and HHpred. The Toolkit currently includes 35 external and in-house tools, covering functionalities such as sequence similarity searching, prediction of sequence features, and sequence classification. Due to this breadth of functionality, the tight interconnection of its constituent tools, and its ease of use, the Toolkit has become an important resource for biomedical research and for teaching protein sequence analysis to students in the life sciences. In this article, we provide detailed information on utilizing the three most widely accessed tools within the Toolkit: HHpred for the detection of homologs, HHpred in conjunction with MODELLER for structure prediction and homology modeling, and CLANS for the visualization of relationships in large sequence datasets. © 2020 The Authors. Basic Protocol 1: Sequence similarity searching using HHpred Alternate Protocol: Pairwise sequence comparison using HHpred Support Protocol: Building a custom multiple sequence alignment using PSI-BLAST and forwarding it as input to HHpred Basic Protocol 2: Calculation of homology models using HHpred and MODELLER Basic Protocol 3: Cluster analysis using CLANS.

337 citations

Journal ArticleDOI
07 Jun 2021-Nature
TL;DR: A novel SARS-CoV-2 variant, 20E (EU1) that emerged in Spain in early summer, and subsequently spread across Europe is reported in this article.
Abstract: Following its emergence in late 2019, the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)1,2 has been tracked via phylogenetic analysis of viral genome sequences in unprecedented detail3–5. While the virus spread globally in early 2020 before borders closed, intercontinental travel has since been greatly reduced. However, within Europe travel resumed in the summer of 2020. Here we report on a novel SARS-CoV-2 variant, 20E (EU1), that emerged in Spain in early summer, and subsequently spread across Europe. We find no evidence of increased transmissibility, but instead demonstrate how rising incidence in Spain, resumption of travel, and lack of effective screening and containment may explain the variant’s success. Despite travel restrictions, we estimate 20E (EU1) was introduced hundreds of times to European countries by summertime travelers, likely undermining local efforts to keep SARS-CoV-2 cases low. Our results demonstrate how a variant can rapidly become dominant even in absence of a substantial transmission advantage in favorable epidemiological settings. Genomic surveillance is critical to understanding how travel can impact SARS-CoV-2 transmission, and thus for informing future containment strategies as travel resumes.

264 citations

Journal ArticleDOI
TL;DR: The Swiss Bioinformatics Resource Portal (expasy) as mentioned in this paper provides a portfolio of reliable and state-of-the-art resources for the storage, analysis and interpretation of biological data.
Abstract: The SIB Swiss Institute of Bioinformatics (https://www.sib.swiss) creates, maintains and disseminates a portfolio of reliable and state-of-the-art bioinformatics services and resources for the storage, analysis and interpretation of biological data. Through Expasy (https://www.expasy.org), the Swiss Bioinformatics Resource Portal, the scientific community worldwide, freely accesses more than 160 SIB resources supporting a wide range of life science and biomedical research areas. In 2020, Expasy was redesigned through a user-centric approach, known as User-Centred Design (UCD), whose aim is to create user interfaces that are easy-to-use, efficient and targeting the intended community. This approach, widely used in other fields such as marketing, e-commerce, and design of mobile applications, is still scarcely explored in bioinformatics. In total, around 50 people were actively involved, including internal stakeholders and end-users. In addition to an optimised interface that meets users' needs and expectations, the new version of Expasy provides an up-to-date and accurate description of high-quality resources based on a standardised ontology, allowing to connect functionally-related resources.

201 citations

Posted ContentDOI
28 Oct 2020-medRxiv
TL;DR: It is currently unclear whether this variant of SARS-CoV-2 is spreading because of a transmission advantage of the virus or whether high incidence in Spain followed by dissemination through tourists is sufficient to explain the rapid rise in multiple countries.
Abstract: This work was supported by the SNF through grant numbers 31CA30 196046 (to RAN, EBH) and 31CA30 196267 and core funding by the University of Basel. SeqCOVID-SPAIN is funded by the Instituto de Salud Carlos III project COV20/00140, Spanish National Research Council and ERC StG 638553 to IC.

175 citations

Journal ArticleDOI
TL;DR: In this paper, the authors analyzed more than 300,000 high-quality genome sequences of SARS-CoV-2 variants available as of January 2021, and found that the ongoing evolution of CoV2 during the COVID-19 pandemic is characterized primarily by purifying selection, but a small set of sites appear to evolve under positive selection.
Abstract: Understanding the trends in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution is paramount to control the COVID-19 pandemic. We analyzed more than 300,000 high-quality genome sequences of SARS-CoV-2 variants available as of January 2021. The results show that the ongoing evolution of SARS-CoV-2 during the pandemic is characterized primarily by purifying selection, but a small set of sites appear to evolve under positive selection. The receptor-binding domain of the spike protein and the region of the nucleocapsid protein associated with nuclear localization signals (NLS) are enriched with positively selected amino acid replacements. These replacements form a strongly connected network of apparent epistatic interactions and are signatures of major partitions in the SARS-CoV-2 phylogeny. Virus diversity within each geographic region has been steadily growing for the entirety of the pandemic, but analysis of the phylogenetic distances between pairs of regions reveals four distinct periods based on global partitioning of the tree and the emergence of key mutations. The initial period of rapid diversification into region-specific phylogenies that ended in February 2020 was followed by a major extinction event and global homogenization concomitant with the spread of D614G in the spike protein, ending in March 2020. The NLS-associated variants across multiple partitions rose to global prominence in March to July, during a period of stasis in terms of interregional diversity. Finally, beginning in July 2020, multiple mutations, some of which have since been demonstrated to enable antibody evasion, began to emerge associated with ongoing regional diversification, which might be indicative of speciation.

157 citations