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Tan M, Xia J, Luo H, Meng G, Zhu Z. Applying the digital data and the bioinformatics tools in SARS-CoV-2 research. Comput Struct Biotechnol J 2023; 21:4697-4705. [PMID: 37841328 PMCID: PMC10568291 DOI: 10.1016/j.csbj.2023.09.044] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 09/29/2023] [Accepted: 09/29/2023] [Indexed: 10/17/2023] Open
Abstract
Bioinformatics has been playing a crucial role in the scientific progress to fight against the pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The advances in novel algorithms, mega data technology, artificial intelligence and deep learning assisted the development of novel bioinformatics tools to analyze daily increasing SARS-CoV-2 data in the past years. These tools were applied in genomic analyses, evolutionary tracking, epidemiological analyses, protein structure interpretation, studies in virus-host interaction and clinical performance. To promote the in-silico analysis in the future, we conducted a review which summarized the databases, web services and software applied in SARS-CoV-2 research. Those digital resources applied in SARS-CoV-2 research may also potentially contribute to the research in other coronavirus and non-coronavirus viruses.
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Affiliation(s)
- Meng Tan
- School of Life Sciences, Chongqing University, Chongqing, China
| | - Jiaxin Xia
- School of Life Sciences, Chongqing University, Chongqing, China
| | - Haitao Luo
- School of Life Sciences, Chongqing University, Chongqing, China
| | - Geng Meng
- College of Veterinary Medicine, China Agricultural University, Beijing, China
| | - Zhenglin Zhu
- School of Life Sciences, Chongqing University, Chongqing, China
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2
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Avetyan D, Hakobyan S, Nikoghosyan M, Ghukasyan L, Khachatryan G, Sirunyan T, Muradyan N, Zakharyan R, Chavushyan A, Hayrapetyan V, Hovhannisyan A, Mohamed Bakhash SA, Jerome KR, Roychoudhury P, Greninger AL, Niazyan L, Davidyants M, Melik-Andreasyan G, Sargsyan S, Nersisyan L, Arakelyan A. Molecular Analysis of SARS-CoV-2 Lineages in Armenia. Viruses 2022; 14:v14051074. [PMID: 35632815 PMCID: PMC9142918 DOI: 10.3390/v14051074] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 05/04/2022] [Accepted: 05/13/2022] [Indexed: 12/11/2022] Open
Abstract
The sequencing of SARS-CoV-2 provides essential information on viral evolution, transmission, and epidemiology. In this paper, we performed the whole-genome sequencing of SARS-CoV-2 using nanopore and Illumina sequencing to describe the circulation of the virus lineages in Armenia. The analysis of 145 full genomes identified six clades (19A, 20A, 20B, 20I, 21J, and 21K) and considerable intra-clade PANGO lineage diversity. Phylodynamic and transmission analysis allowed to attribute specific clades as well as infer their importation routes. Thus, the first two waves of positive case increase were caused by the 20B clade, the third peak caused by the 20I (Alpha), while the last two peaks were caused by the 21J (Delta) and 21K (Omicron) variants. The functional analyses of mutations in sequences largely affected epitopes associated with protective HLA loci and did not cause the loss of the signal in PCR tests targeting ORF1ab and N genes as confirmed by RT-PCR. We also compared the performance of nanopore and Illumina short-read sequencing and showed the utility of nanopore sequencing as an efficient and affordable alternative for large-scale molecular epidemiology research. Thus, our paper describes new data on the genomic diversity of SARS-CoV-2 variants in Armenia in the global context of the virus molecular genomic surveillance.
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Affiliation(s)
- Diana Avetyan
- Laboratory of Human Genomics, Institute of Molecular Biology NAS RA, Yerevan 0014, Armenia; (L.G.); (G.K.); (T.S.); (N.M.); (R.Z.); (A.C.); (V.H.)
- Institute of Biomedicine and Pharmacy, Russian-Armenian University, Yerevan 0051, Armenia; (M.N.); (A.H.)
- Correspondence: (D.A.); (A.A.)
| | - Siras Hakobyan
- Bioinformatics Group, Institute of Molecular Biology NAS RA, Yerevan 0014, Armenia;
- Armenian Bioinformatics Institute, Yerevan 0014, Armenia;
| | - Maria Nikoghosyan
- Institute of Biomedicine and Pharmacy, Russian-Armenian University, Yerevan 0051, Armenia; (M.N.); (A.H.)
- Bioinformatics Group, Institute of Molecular Biology NAS RA, Yerevan 0014, Armenia;
| | - Lilit Ghukasyan
- Laboratory of Human Genomics, Institute of Molecular Biology NAS RA, Yerevan 0014, Armenia; (L.G.); (G.K.); (T.S.); (N.M.); (R.Z.); (A.C.); (V.H.)
| | - Gisane Khachatryan
- Laboratory of Human Genomics, Institute of Molecular Biology NAS RA, Yerevan 0014, Armenia; (L.G.); (G.K.); (T.S.); (N.M.); (R.Z.); (A.C.); (V.H.)
- Institute of Biomedicine and Pharmacy, Russian-Armenian University, Yerevan 0051, Armenia; (M.N.); (A.H.)
| | - Tamara Sirunyan
- Laboratory of Human Genomics, Institute of Molecular Biology NAS RA, Yerevan 0014, Armenia; (L.G.); (G.K.); (T.S.); (N.M.); (R.Z.); (A.C.); (V.H.)
- Institute of Biomedicine and Pharmacy, Russian-Armenian University, Yerevan 0051, Armenia; (M.N.); (A.H.)
| | - Nelli Muradyan
- Laboratory of Human Genomics, Institute of Molecular Biology NAS RA, Yerevan 0014, Armenia; (L.G.); (G.K.); (T.S.); (N.M.); (R.Z.); (A.C.); (V.H.)
| | - Roksana Zakharyan
- Laboratory of Human Genomics, Institute of Molecular Biology NAS RA, Yerevan 0014, Armenia; (L.G.); (G.K.); (T.S.); (N.M.); (R.Z.); (A.C.); (V.H.)
- Institute of Biomedicine and Pharmacy, Russian-Armenian University, Yerevan 0051, Armenia; (M.N.); (A.H.)
| | - Andranik Chavushyan
- Laboratory of Human Genomics, Institute of Molecular Biology NAS RA, Yerevan 0014, Armenia; (L.G.); (G.K.); (T.S.); (N.M.); (R.Z.); (A.C.); (V.H.)
- Davidyants Laboratories, Yerevan 0054, Armenia
| | - Varduhi Hayrapetyan
- Laboratory of Human Genomics, Institute of Molecular Biology NAS RA, Yerevan 0014, Armenia; (L.G.); (G.K.); (T.S.); (N.M.); (R.Z.); (A.C.); (V.H.)
- Institute of Biomedicine and Pharmacy, Russian-Armenian University, Yerevan 0051, Armenia; (M.N.); (A.H.)
| | - Anahit Hovhannisyan
- Institute of Biomedicine and Pharmacy, Russian-Armenian University, Yerevan 0051, Armenia; (M.N.); (A.H.)
- Laboratory of Evolutionary Genomics, Institute of Molecular Biology NAS RA, Yerevan 0014, Armenia
| | - Shah A. Mohamed Bakhash
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98102, USA; (S.A.M.B.); (K.R.J.); (P.R.); (A.L.G.)
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Keith R. Jerome
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98102, USA; (S.A.M.B.); (K.R.J.); (P.R.); (A.L.G.)
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Pavitra Roychoudhury
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98102, USA; (S.A.M.B.); (K.R.J.); (P.R.); (A.L.G.)
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Alexander L. Greninger
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98102, USA; (S.A.M.B.); (K.R.J.); (P.R.); (A.L.G.)
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Lyudmila Niazyan
- NORK Infection Clinical Hospital, MoH RA, Yerevan 0047, Armenia; (L.N.); (M.D.)
| | - Mher Davidyants
- NORK Infection Clinical Hospital, MoH RA, Yerevan 0047, Armenia; (L.N.); (M.D.)
| | - Gayane Melik-Andreasyan
- National Center of Disease Control and Prevention, Ministry of Health RA, Yerevan 0025, Armenia; (G.M.-A.); (S.S.)
| | - Shushan Sargsyan
- National Center of Disease Control and Prevention, Ministry of Health RA, Yerevan 0025, Armenia; (G.M.-A.); (S.S.)
| | - Lilit Nersisyan
- Armenian Bioinformatics Institute, Yerevan 0014, Armenia;
- SciLifeLab, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 17177 Solna, Sweden
| | - Arsen Arakelyan
- Laboratory of Human Genomics, Institute of Molecular Biology NAS RA, Yerevan 0014, Armenia; (L.G.); (G.K.); (T.S.); (N.M.); (R.Z.); (A.C.); (V.H.)
- Institute of Biomedicine and Pharmacy, Russian-Armenian University, Yerevan 0051, Armenia; (M.N.); (A.H.)
- Bioinformatics Group, Institute of Molecular Biology NAS RA, Yerevan 0014, Armenia;
- Armenian Bioinformatics Institute, Yerevan 0014, Armenia;
- Correspondence: (D.A.); (A.A.)
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Tragni V, Preziusi F, Laera L, Onofrio A, Mercurio I, Todisco S, Volpicella M, De Grassi A, Pierri CL. Modeling SARS-CoV-2 spike/ACE2 protein-protein interactions for predicting the binding affinity of new spike variants for ACE2, and novel ACE2 structurally related human protein targets, for COVID-19 handling in the 3PM context. EPMA J 2022; 13:149-175. [PMID: 35013687 PMCID: PMC8732965 DOI: 10.1007/s13167-021-00267-w] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 12/04/2021] [Indexed: 12/12/2022]
Abstract
Aims The rapid spread of new SARS-CoV-2 variants has highlighted the crucial role played in the infection by mutations occurring at the SARS-CoV-2 spike receptor binding domain (RBD) in the interactions with the human ACE2 receptor. In this context, it urgently needs to develop new rapid tools for quickly predicting the affinity of ACE2 for the SARS-CoV-2 spike RBD protein variants to be used with the ongoing SARS-CoV-2 genomic sequencing activities in the clinics, aiming to gain clues about the transmissibility and virulence of new variants, to prevent new outbreaks and to quickly estimate the severity of the disease in the context of the 3PM. Methods In our study, we used a computational pipeline for calculating the interaction energies at the SARS-CoV-2 spike RBD/ACE2 protein-protein interface for a selected group of characterized infectious variants of concern/interest (VoC/VoI). By using our pipeline, we built 3D comparative models of the SARS-CoV-2 spike RBD/ACE2 protein complexes for the VoC B.1.1.7-United Kingdom (carrying the mutations of concern/interest N501Y, S494P, E484K at the RBD), P.1-Japan/Brazil (RBD mutations: K417T, E484K, N501Y), B.1.351-South Africa (RBD mutations: K417N, E484K, N501Y), B.1.427/B.1.429-California (RBD mutations: L452R), the B.1.141 (RBD mutations: N439K), and the recent B.1.617.1-India (RBD mutations: L452R; E484Q) and the B.1.620 (RBD mutations: S477N; E484K). Then, we used the obtained 3D comparative models of the SARS-CoV-2 spike RBD/ACE2 protein complexes for predicting the interaction energies at the protein-protein interface. Results Along SARS-CoV-2 mutation database screening and mutation localization analysis, it was ascertained that the most dangerous mutations at VoC/VoI spike proteins are located mainly at three regions of the SARS-CoV-2 spike "boat-shaped" receptor binding motif, on the RBD domain. Notably, the P.1 Japan/Brazil variant present three mutations, K417T, E484K, N501Y, located along the entire receptor binding motif, which apparently determines the highest interaction energy at the SARS-CoV-2 spike RBD/ACE2 protein-protein interface, among those calculated. Conversely, it was also observed that the replacement of a single acidic/hydrophilic residue with a basic residue (E484K or N439K) at the "stern" or "bow" regions, of the boat-shaped receptor binding motif on the RBD, appears to determine an interaction energy with ACE2 receptor higher than that observed with single mutations occurring at the "hull" region or with other multiple mutants. In addition, our pipeline allowed searching for ACE2 structurally related proteins, i.e., THOP1 and NLN, which deserve to be investigated for their possible involvement in interactions with the SARS-CoV-2 spike protein, in those tissues showing a low expression of ACE2, or as a novel receptor for future spike variants. A freely available web-tool for the in silico calculation of the interaction energy at the SARS-CoV-2 spike RBD/ACE2 protein-protein interface, starting from the sequences of the investigated spike and/or ACE2 variants, was made available for the scientific community at: https://www.mitoairm.it/covid19affinities. Conclusion In the context of the PPPM/3PM, the employment of the described pipeline through the provided webservice, together with the ongoing SARS-CoV-2 genomic sequencing, would help to predict the transmissibility of new variants sequenced from future patients, depending on SARS-CoV-2 genomic sequencing activities and on the specific amino acid replacement and/or on its location on the SARS-CoV-2 spike RBD, to put in play all the possible counteractions for preventing the most deleterious scenarios of new outbreaks, taking into consideration that a greater transmissibility has not to be necessarily related to a more severe manifestation of the disease. Supplementary Information The online version contains supplementary material available at 10.1007/s13167-021-00267-w.
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Affiliation(s)
- Vincenzo Tragni
- Department of Biosciences, Biotechnologies, Biopharmaceutics, University of Bari, Via E. Orabona, 4, 70125 Bari, Italy
| | - Francesca Preziusi
- Department of Biosciences, Biotechnologies, Biopharmaceutics, University of Bari, Via E. Orabona, 4, 70125 Bari, Italy
| | - Luna Laera
- Department of Biosciences, Biotechnologies, Biopharmaceutics, University of Bari, Via E. Orabona, 4, 70125 Bari, Italy
| | - Angelo Onofrio
- Department of Biosciences, Biotechnologies, Biopharmaceutics, University of Bari, Via E. Orabona, 4, 70125 Bari, Italy
| | - Ivan Mercurio
- Department of Biosciences, Biotechnologies, Biopharmaceutics, University of Bari, Via E. Orabona, 4, 70125 Bari, Italy
| | - Simona Todisco
- Department of Sciences, University of Basilicata, Viale dell’Ateneo Lucano, 10-85100 Potenza, Italy
| | - Mariateresa Volpicella
- Department of Biosciences, Biotechnologies, Biopharmaceutics, University of Bari, Via E. Orabona, 4, 70125 Bari, Italy
| | - Anna De Grassi
- Department of Biosciences, Biotechnologies, Biopharmaceutics, University of Bari, Via E. Orabona, 4, 70125 Bari, Italy
- BROWSer S.r.l. at Department of Biosciences, Biotechnologies, Biopharmaceutics, University “Aldo Moro” of Bari, Via E. Orabona, 4, 70126 Bari, Italy
| | - Ciro Leonardo Pierri
- Department of Biosciences, Biotechnologies, Biopharmaceutics, University of Bari, Via E. Orabona, 4, 70125 Bari, Italy
- BROWSer S.r.l. at Department of Biosciences, Biotechnologies, Biopharmaceutics, University “Aldo Moro” of Bari, Via E. Orabona, 4, 70126 Bari, Italy
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Tangaro MA, Mandreoli P, Chiara M, Donvito G, Antonacci M, Parisi A, Bianco A, Romano A, Bianchi DM, Cangelosi D, Uva P, Molineris I, Nosi V, Calogero RA, Alessandri L, Pedrini E, Mordenti M, Bonetti E, Sangiorgi L, Pesole G, Zambelli F. Laniakea@ReCaS: exploring the potential of customisable Galaxy on-demand instances as a cloud-based service. BMC Bioinformatics 2021; 22:544. [PMID: 34749633 PMCID: PMC8574934 DOI: 10.1186/s12859-021-04401-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 09/24/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Improving the availability and usability of data and analytical tools is a critical precondition for further advancing modern biological and biomedical research. For instance, one of the many ramifications of the COVID-19 global pandemic has been to make even more evident the importance of having bioinformatics tools and data readily actionable by researchers through convenient access points and supported by adequate IT infrastructures. One of the most successful efforts in improving the availability and usability of bioinformatics tools and data is represented by the Galaxy workflow manager and its thriving community. In 2020 we introduced Laniakea, a software platform conceived to streamline the configuration and deployment of "on-demand" Galaxy instances over the cloud. By facilitating the set-up and configuration of Galaxy web servers, Laniakea provides researchers with a powerful and highly customisable platform for executing complex bioinformatics analyses. The system can be accessed through a dedicated and user-friendly web interface that allows the Galaxy web server's initial configuration and deployment. RESULTS "Laniakea@ReCaS", the first instance of a Laniakea-based service, is managed by ELIXIR-IT and was officially launched in February 2020, after about one year of development and testing that involved several users. Researchers can request access to Laniakea@ReCaS through an open-ended call for use-cases. Ten project proposals have been accepted since then, totalling 18 Galaxy on-demand virtual servers that employ ~ 100 CPUs, ~ 250 GB of RAM and ~ 5 TB of storage and serve several different communities and purposes. Herein, we present eight use cases demonstrating the versatility of the platform. CONCLUSIONS During this first year of activity, the Laniakea-based service emerged as a flexible platform that facilitated the rapid development of bioinformatics tools, the efficient delivery of training activities, and the provision of public bioinformatics services in different settings, including food safety and clinical research. Laniakea@ReCaS provides a proof of concept of how enabling access to appropriate, reliable IT resources and ready-to-use bioinformatics tools can considerably streamline researchers' work.
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Affiliation(s)
- Marco Antonio Tangaro
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR), Via Giovanni Amendola 122/O, 70126, Bari, Italy
- National Institute for Nuclear Physics (INFN), Section of Bari, Via Orabona 4, 70126, Bari, Italy
| | - Pietro Mandreoli
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR), Via Giovanni Amendola 122/O, 70126, Bari, Italy
- Department of Biosciences, University of Milan, Via Celoria 26, 20133, Milano, Italy
| | - Matteo Chiara
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR), Via Giovanni Amendola 122/O, 70126, Bari, Italy
- Department of Biosciences, University of Milan, Via Celoria 26, 20133, Milano, Italy
| | - Giacinto Donvito
- National Institute for Nuclear Physics (INFN), Section of Bari, Via Orabona 4, 70126, Bari, Italy
| | - Marica Antonacci
- National Institute for Nuclear Physics (INFN), Section of Bari, Via Orabona 4, 70126, Bari, Italy
| | - Antonio Parisi
- Istituto Zooprofilattico Sperimentale Della Puglia e Della Basilicata, Via Manfredonia 20, 71121, Foggia, Italy
| | - Angelica Bianco
- Istituto Zooprofilattico Sperimentale Della Puglia e Della Basilicata, Via Manfredonia 20, 71121, Foggia, Italy
| | - Angelo Romano
- National Reference Laboratory for Coagulase-Positive Staphylococci Including Staphylococcus Aureus, Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d'Aosta, Via Bologna 148, 10154, Turin, Italy
| | - Daniela Manila Bianchi
- National Reference Laboratory for Coagulase-Positive Staphylococci Including Staphylococcus Aureus, Istituto Zooprofilattico Sperimentale del Piemonte, Liguria e Valle d'Aosta, Via Bologna 148, 10154, Turin, Italy
| | - Davide Cangelosi
- Clinical Bioinformatics Unit, Scientific Direction, IRCCS Istituto Giannina Gaslini, Via Gerolamo Gaslini 5, 16147, Genova, Italy
| | - Paolo Uva
- Clinical Bioinformatics Unit, Scientific Direction, IRCCS Istituto Giannina Gaslini, Via Gerolamo Gaslini 5, 16147, Genova, Italy
- Italian Institute of Technology, Via Morego 30, 16163, Genova, Italy
| | - Ivan Molineris
- Department of Life Science and System Biology, University of Turin, Via Accademia Albertina, 13-1023, Turin, Italy
| | - Vladimir Nosi
- Department of Computer Science, University of Turin, Via Pessinetto 12, 10049, Turin, Italy
| | - Raffaele A Calogero
- Department of Molecular Biotechnology and Health Sciences, Via Nizza 52, 10126, Turin, Italy
| | - Luca Alessandri
- Department of Molecular Biotechnology and Health Sciences, Via Nizza 52, 10126, Turin, Italy
| | - Elena Pedrini
- Department of Rare Skeletal Disorders, IRCCS Istituto Ortopedico Rizzoli, Via di Barbiano 1/10, 40136, Bologna, Italy
| | - Marina Mordenti
- Department of Rare Skeletal Disorders, IRCCS Istituto Ortopedico Rizzoli, Via di Barbiano 1/10, 40136, Bologna, Italy
| | - Emanuele Bonetti
- Department of Rare Skeletal Disorders, IRCCS Istituto Ortopedico Rizzoli, Via di Barbiano 1/10, 40136, Bologna, Italy
- Department of Experimental Oncology, European Institute of Oncology, Via Adamello 16, 20139, Milan, Italy
| | - Luca Sangiorgi
- Department of Rare Skeletal Disorders, IRCCS Istituto Ortopedico Rizzoli, Via di Barbiano 1/10, 40136, Bologna, Italy
| | - Graziano Pesole
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR), Via Giovanni Amendola 122/O, 70126, Bari, Italy.
- Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Via Orabona 4, 70126, Bari, Italy.
| | - Federico Zambelli
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR), Via Giovanni Amendola 122/O, 70126, Bari, Italy.
- Department of Biosciences, University of Milan, Via Celoria 26, 20133, Milano, Italy.
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Pinoli P, Bernasconi A, Sandionigi A, Ceri S. VirusLab: A Tool for Customized SARS-CoV-2 Data Analysis. BIOTECH 2021; 10:biotech10040027. [PMID: 35822801 PMCID: PMC9245481 DOI: 10.3390/biotech10040027] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 10/26/2021] [Accepted: 11/02/2021] [Indexed: 12/14/2022] Open
Abstract
Since the beginning of 2020, the COVID-19 pandemic has posed unprecedented challenges to viral data analysis and connected host disease diagnostic methods. We propose VirusLab, a flexible system for analysing SARS-CoV-2 viral sequences and relating them to metadata or clinical information about the host. VirusLab capitalizes on two existing resources: ViruSurf, a database of public SARS-CoV-2 sequences supporting metadata-driven search, and VirusViz, a tool for visual analysis of search results. VirusLab is designed for taking advantage of these resources within a server-side architecture that: (i) covers pipelines based on approaches already in use (ARTIC, Galaxy) but entirely cutomizable upon user request; (ii) predigests analysis of raw sequencing data from different platforms (Oxford Nanopore and Illumina); (iii) gives access to public archives datasets; (iv) supplies user-friendly reporting – making it a tool that can also be integrated into a business environment. VirusLab can be installed and hosted within the premises of any organization where information about SARS-CoV-2 sequences can be safely integrated with information about hosts (e.g., clinical metadata). A system such as VirusLab is not currently available in the landscape of similar providers: our results show that VirusLab is a powerful tool to generate tabular/graphical and machine readable reports that can be integrated in more complex pipelines. We foresee that the proposed system can support many research-oriented and therapeutic scenarios within hospitals or the tracing of viral sequences and their mutational processes within organizations for viral surveillance.
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Affiliation(s)
- Pietro Pinoli
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy; (P.P.); (S.C.)
| | - Anna Bernasconi
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy; (P.P.); (S.C.)
- Correspondence: ; Tel.: +39-02-2399-3655
| | - Anna Sandionigi
- Quantia Consulting S.r.l., Mariano Comense, 22066 Como, Italy;
| | - Stefano Ceri
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy; (P.P.); (S.C.)
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Farkas C, Mella A, Turgeon M, Haigh JJ. A Novel SARS-CoV-2 Viral Sequence Bioinformatic Pipeline Has Found Genetic Evidence That the Viral 3' Untranslated Region (UTR) Is Evolving and Generating Increased Viral Diversity. Front Microbiol 2021; 12:665041. [PMID: 34234758 PMCID: PMC8256173 DOI: 10.3389/fmicb.2021.665041] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Accepted: 05/28/2021] [Indexed: 12/27/2022] Open
Abstract
An unprecedented amount of SARS-CoV-2 sequencing has been performed, however, novel bioinformatic tools to cope with and process these large datasets is needed. Here, we have devised a bioinformatic pipeline that inputs SARS-CoV-2 genome sequencing in FASTA/FASTQ format and outputs a single Variant Calling Format file that can be processed to obtain variant annotations and perform downstream population genetic testing. As proof of concept, we have analyzed over 229,000 SARS-CoV-2 viral sequences up until November 30, 2020. We have identified over 39,000 variants worldwide with increased polymorphisms, spanning the ORF3a gene as well as the 3' untranslated (UTR) regions, specifically in the conserved stem loop region of SARS-CoV-2 which is accumulating greater observed viral diversity relative to chance variation. Our analysis pipeline has also discovered the existence of SARS-CoV-2 hypermutation with low frequency (less than in 2% of genomes) likely arising through host immune responses and not due to sequencing errors. Among annotated non-sense variants with a population frequency over 1%, recurrent inactivation of the ORF8 gene was found. This was found to be present in the newly identified B.1.1.7 SARS-CoV-2 lineage that originated in the United Kingdom. Almost all VOC-containing genomes possess one stop codon in ORF8 gene (Q27∗), however, 13% of these genomes also contains another stop codon (K68∗), suggesting that ORF8 loss does not interfere with SARS-CoV-2 spread and may play a role in its increased virulence. We have developed this computational pipeline to assist researchers in the rapid analysis and characterization of SARS-CoV-2 variation.
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Affiliation(s)
- Carlos Farkas
- Research Institute in Oncology and Hematology (RIOH), CancerCare Manitoba, Winnipeg, MB, Canada
- Department of Pharmacology and Therapeutics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Andy Mella
- Departamento de Física, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Santiago, Chile
- Instituto de Ciencias Naturales, Universidad de las Américas, Santiago, Chile
| | - Maxime Turgeon
- Department of Statistics, University of Manitoba, Winnipeg, MB, Canada
- Department of Computer Science, University of Manitoba, Winnipeg, MB, Canada
| | - Jody J. Haigh
- Research Institute in Oncology and Hematology (RIOH), CancerCare Manitoba, Winnipeg, MB, Canada
- Department of Pharmacology and Therapeutics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
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