1
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Kim J, Steinegger M. Metabuli: sensitive and specific metagenomic classification via joint analysis of amino acid and DNA. Nat Methods 2024; 21:971-973. [PMID: 38769467 DOI: 10.1038/s41592-024-02273-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 04/11/2024] [Indexed: 05/22/2024]
Abstract
Metagenomic taxonomic classifiers analyze either DNA or amino acid (AA) sequences. Metabuli ( https://metabuli.steineggerlab.com ), however, jointly analyzes both DNA and AA to leverage AA conservation for sensitive homology detection and DNA mutations for specific differentiation of closely related taxa. In the Critical Assessment of Metagenome Interpretation 2 plant-associated dataset, Metabuli covered 99% and 98% of classifications of state-of-the-art DNA- and AA-based classifiers, respectively.
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Affiliation(s)
- Jaebeom Kim
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea
| | - Martin Steinegger
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
- School of Biological Sciences, Seoul National University, Seoul, Republic of Korea.
- Institute of Molecular Biology and Genetics, Seoul National University, Seoul, Republic of Korea.
- Artificial Intelligence Institute, Seoul National University, Seoul, Republic of Korea.
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2
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He KY, Lei XY, Zhang L, Wu DH, Li JQ, Lu LY, Laila UE, Cui CY, Xu ZX, Jian YP. Development and management of gastrointestinal symptoms in long-term COVID-19. Front Microbiol 2023; 14:1278479. [PMID: 38156008 PMCID: PMC10752947 DOI: 10.3389/fmicb.2023.1278479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 11/20/2023] [Indexed: 12/30/2023] Open
Abstract
Background Emerging evidence reveals that SARS-CoV-2 possesses the capability to disrupt the gastrointestinal (GI) homeostasis, resulting in the long-term symptoms such as loss of appetite, diarrhea, gastroesophageal reflux, and nausea. In the current review, we summarized recent reports regarding the long-term effects of COVID-19 (long COVID) on the gastrointestine. Objective To provide a narrative review of abundant clinical evidence regarding the development and management of long-term GI symptoms in COVID-19 patients. Results Long-term persistent digestive symptoms are exhibited in a majority of long-COVID patients. SARS-CoV-2 infection of intestinal epithelial cells, cytokine storm, gut dysbiosis, therapeutic drugs, psychological factors and exacerbation of primary underlying diseases lead to long-term GI symptoms in COVID-19 patients. Interventions like probiotics, prebiotics, fecal microbiota transplantation, and antibiotics are proved to be beneficial in preserving intestinal microecological homeostasis and alleviating GI symptoms. Conclusion Timely diagnosis and treatment of GI symptoms in long-COVID patients hold great significance as they may contribute to the mitigation of severe conditions and ultimately lead to the improvement of outcomes of the patients.
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Affiliation(s)
- Kai-Yue He
- School of Life Sciences, Henan University, Kaifeng, China
| | - Xin-Yuan Lei
- School of Life Sciences, Henan University, Kaifeng, China
| | - Lei Zhang
- School of Life Sciences, Henan University, Kaifeng, China
| | - Dan-Hui Wu
- School of Life Sciences, Henan University, Kaifeng, China
| | - Jun-Qi Li
- School of Life Sciences, Henan University, Kaifeng, China
| | - Li-Yuan Lu
- School of Life Sciences, Henan University, Kaifeng, China
| | - Umm E. Laila
- School of Life Sciences, Henan University, Kaifeng, China
| | - Cui-Yun Cui
- Department of Blood Transfusion, Henan Provincial People’s Hospital, Zhengzhou, Henan, China
| | - Zhi-Xiang Xu
- School of Life Sciences, Henan University, Kaifeng, China
| | - Yong-Ping Jian
- School of Life Sciences, Henan University, Kaifeng, China
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3
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Tegally H, Wilkinson E, Tsui JLH, Moir M, Martin D, Brito AF, Giovanetti M, Khan K, Huber C, Bogoch II, San JE, Poongavanan J, Xavier JS, Candido DDS, Romero F, Baxter C, Pybus OG, Lessells RJ, Faria NR, Kraemer MUG, de Oliveira T. Dispersal patterns and influence of air travel during the global expansion of SARS-CoV-2 variants of concern. Cell 2023; 186:3277-3290.e16. [PMID: 37413988 PMCID: PMC10247138 DOI: 10.1016/j.cell.2023.06.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 05/31/2023] [Accepted: 06/02/2023] [Indexed: 07/08/2023]
Abstract
The Alpha, Beta, and Gamma SARS-CoV-2 variants of concern (VOCs) co-circulated globally during 2020 and 2021, fueling waves of infections. They were displaced by Delta during a third wave worldwide in 2021, which, in turn, was displaced by Omicron in late 2021. In this study, we use phylogenetic and phylogeographic methods to reconstruct the dispersal patterns of VOCs worldwide. We find that source-sink dynamics varied substantially by VOC and identify countries that acted as global and regional hubs of dissemination. We demonstrate the declining role of presumed origin countries of VOCs in their global dispersal, estimating that India contributed <15% of Delta exports and South Africa <1%-2% of Omicron dispersal. We estimate that >80 countries had received introductions of Omicron within 100 days of its emergence, associated with accelerated passenger air travel and higher transmissibility. Our study highlights the rapid dispersal of highly transmissible variants, with implications for genomic surveillance along the hierarchical airline network.
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Affiliation(s)
- Houriiyah Tegally
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa; KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa.
| | - Eduan Wilkinson
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | | | - Monika Moir
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Darren Martin
- Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa), Cape Town, South Africa; Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | | | - Marta Giovanetti
- Laboratorio de Flavivirus, Fundacao Oswaldo Cruz, Rio de Janeiro, Brazil; Laboratório de Genética Celular e Molecular, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil; Department of Science and Technology for Humans and the Environment, University of Campus Bio-Medico di Roma, Rome, Italy
| | - Kamran Khan
- BlueDot, Toronto, ON, Canada; Department of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, ON, Canada
| | | | - Isaac I Bogoch
- Department of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, ON, Canada
| | - James Emmanuel San
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Jenicca Poongavanan
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Joicymara S Xavier
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa; Universidade Federal de Minas Gerais, Belo Horizonte, Brazil; Institute of Agricultural Sciences, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Unaí, Brazil
| | - Darlan da S Candido
- MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Filipe Romero
- MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Cheryl Baxter
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Oliver G Pybus
- Department of Biology, University of Oxford, Oxford, UK; Pandemic Sciences Institute, University of Oxford, Oxford, UK; Department of Pathobiology and Population Sciences, Royal Veterinary College London, London, UK
| | - Richard J Lessells
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Nuno R Faria
- Department of Biology, University of Oxford, Oxford, UK; MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College London, London, UK; Departamento de Moléstias Infecciosas e Parasitárias e Instituto de Medicina Tropical da Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
| | - Moritz U G Kraemer
- Department of Biology, University of Oxford, Oxford, UK; Pandemic Sciences Institute, University of Oxford, Oxford, UK.
| | - Tulio de Oliveira
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa; KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa; Department of Global Health, University of Washington, Seattle, WA, USA.
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4
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Tegally H, Wilkinson E, Martin D, Moir M, Brito A, Giovanetti M, Khan K, Huber C, Bogoch II, San JE, Tsui JLH, Poongavanan J, Xavier JS, Candido DDS, Romero F, Baxter C, Pybus OG, Lessells R, Faria NR, Kraemer MUG, de Oliveira T. Global Expansion of SARS-CoV-2 Variants of Concern: Dispersal Patterns and Influence of Air Travel. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.11.22.22282629. [PMID: 36451885 PMCID: PMC9709793 DOI: 10.1101/2022.11.22.22282629] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
In many regions of the world, the Alpha, Beta and Gamma SARS-CoV-2 Variants of Concern (VOCs) co-circulated during 2020-21 and fueled waves of infections. During 2021, these variants were almost completely displaced by the Delta variant, causing a third wave of infections worldwide. This phenomenon of global viral lineage displacement was observed again in late 2021, when the Omicron variant disseminated globally. In this study, we use phylogenetic and phylogeographic methods to reconstruct the dispersal patterns of SARS-CoV-2 VOCs worldwide. We find that the source-sink dynamics of SARS-CoV-2 varied substantially by VOC, and identify countries that acted as global hubs of variant dissemination, while other countries became regional contributors to the export of specific variants. We demonstrate a declining role of presumed origin countries of VOCs to their global dispersal: we estimate that India contributed <15% of all global exports of Delta to other countries and South Africa <1-2% of all global Omicron exports globally. We further estimate that >80 countries had received introductions of Omicron BA.1 100 days after its inferred date of emergence, compared to just over 25 countries for the Alpha variant. This increased speed of global dissemination was associated with a rebound in air travel volume prior to Omicron emergence in addition to the higher transmissibility of Omicron relative to Alpha. Our study highlights the importance of global and regional hubs in VOC dispersal, and the speed at which highly transmissible variants disseminate through these hubs, even before their detection and characterization through genomic surveillance. Highlights Global phylogenetic analysis reveals relationship between air travel and speed of dispersal of SARS-CoV-2 variants of concern (VOCs)Omicron VOC spread to 5x more countries within 100 days of its emergence compared to all other VOCsOnward transmission and dissemination of VOCs Delta and Omicron was primarily from secondary hubs rather than initial country of detection during a time of increased global air travelAnalysis highlights highly connected countries identified as major global and regional exporters of VOCs.
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Affiliation(s)
- Houriiyah Tegally
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Eduan Wilkinson
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Darren Martin
- Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa), Cape Town, South Africa
- Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Monika Moir
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Anderson Brito
- Instituto Todos pela Saúde, São Paulo, São Paulo, Brazil
| | - Marta Giovanetti
- Laboratorio de Flavivirus, Fundacao Oswaldo Cruz, Rio de Janeiro, Brazil
- Laboratório de Genética Celular e Molecular, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- Department of Science and Technology for Humans and the Environment, University of Campus Bio-Medico di Roma, Rome, Italy
| | - Kamran Khan
- BlueDot, Toronto, Canada
- Department of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, Canada
| | | | - Isaac I Bogoch
- Department of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, Canada
| | - James Emmanuel San
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | | | - Jenicca Poongavanan
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Joicymara S Xavier
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
- Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
- Institute of Agricultural Sciences, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Unaí, Brazil
| | - Darlan da S Candido
- MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Filipe Romero
- MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College London, London, UK
| | - Cheryl Baxter
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
| | - Oliver G Pybus
- Department of Biology, University of Oxford, Oxford, UK
- Pandemic Sciences Institute, University of Oxford, Oxford, UK
- Department of Pathobiology and Population Sciences, Royal Veterinary College London, London, UK
| | - Richard Lessells
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Nuno R Faria
- MRC Centre for Global Infectious Disease Analysis and Department of Infectious Disease Epidemiology, Jameel Institute, School of Public Health, Imperial College London, London, UK
- Departamento de Moléstias Infecciosas e Parasitárias e Instituto de Medicina Tropical da Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil
- Department of Biology, University of Oxford, Oxford, UK
| | - Moritz U G Kraemer
- Department of Biology, University of Oxford, Oxford, UK
- Pandemic Sciences Institute, University of Oxford, Oxford, UK
| | - Tulio de Oliveira
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), Nelson R. Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
- Department of Global Health, University of Washington, Seattle, WA, USA
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5
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Akter S, Shahab M, Sarkar MMH, Hayat C, Banu TA, Goswami B, Jahan I, Osman E, Uzzaman MS, Habib MA, Shaikh AA, Khan MS. Immunoinformatics approach to epitope-based vaccine design against the SARS-CoV-2 in Bangladeshi patients. J Genet Eng Biotechnol 2022; 20:136. [PMID: 36125645 PMCID: PMC9487853 DOI: 10.1186/s43141-022-00410-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 08/25/2022] [Indexed: 12/02/2022]
Abstract
BACKGROUND Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic which has brought a great challenge to public health. After the first emergence of novel coronavirus SARS-CoV-2 in the city of Wuhan, China, in December 2019. As of March 2020, SARS-CoV-2 was first reported in Bangladesh and since then the country has experienced a steady rise in infections, resulting in 13,355,191 cases and 29,024 deaths as of 27 February 2022. Bioinformatics techniques are used to predict B cell and T cell epitopes from the new SARS-CoV-2 spike glycoprotein in order to build a unique multiple epitope vaccine. The immunogenicity, antigenicity scores, and toxicity of these epitopes were evaluated and chosen based on their capacity to elicit an immune response. RESULT The best multi-epitope of the possible immunogenic property was created by combining epitopes. EAAAK, AAY, and GPGPG linkers were used to connect the epitopes. In several computer-based immune response analyses, this vaccine design was found to be efficient, as well as having high population coverage. CONCLUSION This research is entirely reliant on the development of epitope-based vaccines, and these in silico findings would represent a major step forward in the development of a vaccine that might eradicate SARS-CoV-2 in Bangladeshi patients.
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Affiliation(s)
- Shahina Akter
- Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh
| | - Muhammad Shahab
- State Key Laboratories of Chemical Resources Engineering, Beijing University of Chemical Technology, Beijing, 100029, China
| | | | - Chandni Hayat
- Department of Biochemistry, Computational Medicinal Chemistry Laboratory, UCSS, Abdul Wali Khan University, Mardan, Pakistan
| | - Tanjina Akhtar Banu
- Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh
| | - Barna Goswami
- Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh
| | - Iffat Jahan
- Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh
| | - Eshrar Osman
- SciTech Consulting and Solutions, Dhaka, Bangladesh
| | | | - Md Ahashan Habib
- Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh
| | - Aftab Ali Shaikh
- Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh
| | - Md Salim Khan
- Bangladesh Council of Scientific & Industrial Research (BCSIR), Dhaka, Bangladesh.
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