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Blenkinsop A, Pantazis N, Kostaki EG, Sofocleous L, van Sighem A, Bezemer D, van de Laar T, van der Valk M, Reiss P, de Bree G, Ratmann O. Sources of Human Immunodeficiency Virus Infections Among Men Who Have Sex With Men With a Migration Background: A Viral Phylogenetic Case Study in Amsterdam, The Netherlands. J Infect Dis 2024; 230:e881-e894. [PMID: 38976562 PMCID: PMC11481325 DOI: 10.1093/infdis/jiae267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 05/17/2024] [Indexed: 07/10/2024] Open
Abstract
BACKGROUND Men and women with a migration background comprise an increasing proportion of incident human immunodeficiency virus (HIV) cases across Western Europe. METHODS To characterize sources of transmission in local transmission chains, we used partial HIV consensus sequences with linked demographic and clinical data from the opt-out AIDS Therapy Evaluation in the Netherlands (ATHENA) cohort of people with HIV in the Netherlands and identified phylogenetically and epidemiologically possible HIV transmission pairs in Amsterdam. We interpreted these in the context of estimated infection dates, and quantified population-level sources of transmission to foreign-born and Dutch-born Amsterdam men who have sex with men (MSM) within Amsterdam transmission chains. RESULTS We estimate that Dutch-born MSM were the predominant sources of infections among all Amsterdam MSM who acquired their infection locally in 2010-2021, and among almost all foreign-born Amsterdam MSM subpopulations. Stratifying by 2-year intervals indicated time trends in transmission dynamics, with a majority of infections originating from foreign-born MSM since 2016, although uncertainty ranges remained wide. CONCLUSIONS Native-born MSM have predominantly driven HIV transmissions in Amsterdam in 2010-2021. However, in the context of rapidly declining incidence in Amsterdam, the contribution from foreign-born MSM living in Amsterdam is increasing, with some evidence that most local transmissions have been from foreign-born Amsterdam MSM since 2016.
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Affiliation(s)
| | - Nikos Pantazis
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Greece
| | - Evangelia Georgia Kostaki
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Greece
| | | | | | | | | | - Marc van der Valk
- Stichting HIV Monitoring, The Netherlands
- Amsterdam Institute for Infection and Immunity, Amsterdam University Medical Center, The Netherlands
| | - Peter Reiss
- Amsterdam Institute for Global Health and Development, The Netherlands
- Department of Global Health, Amsterdam University Medical Center, University of Amsterdam, The Netherlands
| | - Godelieve de Bree
- Amsterdam Institute for Infection and Immunity, Amsterdam University Medical Center, The Netherlands
- Amsterdam Institute for Global Health and Development, The Netherlands
| | - Oliver Ratmann
- Department of Mathematics, Imperial College London, United Kingdom
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2
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Coldbeck-Shackley RC, Adamson PJ, Whybrow D, Selway CA, Papanicolas LE, Turra M, Leong LEX. Direct whole-genome sequencing of HIV-1 for clinical drug-resistance analysis and public health surveillance. J Clin Virol 2024; 174:105709. [PMID: 38924832 DOI: 10.1016/j.jcv.2024.105709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 06/14/2024] [Accepted: 06/20/2024] [Indexed: 06/28/2024]
Abstract
BACKGROUND Human Immunodeficiency virus type 1 (HIV-1) remains a significant global health threat partly due to its ability to develop resistance to anti-retroviral therapies. HIV-1 genotype and drug resistance analysis of the polymerase (pol) sequence is a mainstay of its clinical and public health management. However, as new treatments and resistances evolve, analysis methods must change accordingly. In this study, we outline the development and implementation of a direct whole-genome sequencing approach (dWGS) using probe-capture target-enrichment for HIV-1 genotype and drug resistance analysis. METHODS We implemented dWGS and performed parallel pol Sanger sequencing for clinical samples, followed by comparative genotype and drug-resistance analysis. These HIV-1 WGS sequences were also utilised for a novel partitioned phylogenetic analysis. RESULTS Optimised nucleic acid extraction and DNAse I treatment significantly increased HIV-1 whole-genome coverage and depth, and improved recovery of high-quality genomes from low viral load clinical samples, enabling routine sequencing of viral loads as low as 1000 copies/mL. Overall, dWGS was robust, accurate and more sensitive for detecting low-frequency variants at drug-resistance sites compared to Sanger sequencing. Analysis of multiple sequence regions improved phylogenetic reconstruction for recombinant HIV-1 sequences compared to analysis of pol sequence alone. CONCLUSIONS These findings demonstrate dWGS enhances HIV-1 drug-resistance analysis by quantitative variant detection and improves reconstruction of HIV-1 phylogenies compared to traditional pol sequencing. This work supports that HIV-1 dWGS is a viable option to replace Sanger sequencing for clinical and public health applications.
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Affiliation(s)
| | - Penelope J Adamson
- Microbiology and Infectious Diseases, SA Pathology, Adelaide 5000 Australia
| | - Daryn Whybrow
- Microbiology and Infectious Diseases, SA Pathology, Adelaide 5000 Australia
| | - Caitlin A Selway
- Microbiology and Infectious Diseases, SA Pathology, Adelaide 5000 Australia
| | - Lito E Papanicolas
- Microbiology and Infectious Diseases, SA Pathology, Adelaide 5000 Australia
| | - Mark Turra
- Microbiology and Infectious Diseases, SA Pathology, Adelaide 5000 Australia
| | - Lex E X Leong
- Microbiology and Infectious Diseases, SA Pathology, Adelaide 5000 Australia; UniSA Clinical and Health Sciences, University of South Australia, Adelaide 5000 Australia
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3
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Sebastião CS, Pingarilho M, Bathy J, Bonfim E, Toancha K, Miranda MNS, Martins MRO, Gomes P, Lázaro L, Pina-Araujo I, Nhampossa T, Leal S, Abecasis AB, Pimentel V. MARVEL-minimising the emergence and dissemination of HIV-1 drug resistance in Portuguese-speaking African Countries (PALOP): low-cost portable NGS platform for HIV-1 surveillance in Africa. BMC Infect Dis 2024; 24:884. [PMID: 39210296 PMCID: PMC11360575 DOI: 10.1186/s12879-024-09803-1] [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: 08/12/2024] [Accepted: 08/22/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND HIV-1 infections remain a global public health concern. Scaled-up antiretroviral treatment (ART) is crucial for reducing morbidity and mortality related to HIV/AIDS. The emergence of drug-resistance mutations (DRMs) compromises viral suppression and contributes to the continued HIV-1 transmission. Several reports indicate a recent increase in acquired (ADR) and transmitted (TDR) drug resistance in Africa, probably linked to the lack of implementation of HIV drug resistance (HIVDR) testing and suboptimal treatment adherence. Herein, we will develop a low-cost protocol using third-generation sequencing (Oxford Nanopore Technology) for HIV-1 surveillance in Portuguese-speaking African Countries - PALOP [Angola (AO), Cape Verde (CV), Mozambique (MZ), and Sao Tome & Principe (STP)]. METHODS This is a multicentric cross-sectional study that includes around 600 adult patients newly diagnosed with HIV-1 in the PALOP. An epidemiological questionnaire previously validated by our research team will be used to collect sociodemographic and clinical data. Also, whole blood samples will be collected and the plasma samples will be subjected to drug resistance testing using an in-house low-cost NGS protocol. Data analysis will involve bioinformatics, biostatistics and machine learning techniques to generate accurate and up-to-date information about HIV-1 genetic diversity, ADR and TDR. DISCUSSION The implementation of this low-cost NGS platform for HIV-1 surveillance in the PALOP will allow: (i) to increase DRM surveillance capacity in resource-limited settings; (ii) to understand the pattern and determinants of dissemination of resistant HIV-1 strains; and (iii) to promote the development of technical and scientific skills of African researchers for genomic surveillance of viral pathogens and bioinformatics analysis. These objectives will contribute to reinforcing the capacity to combat HIV infection in Africa by optimizing the selection of ART regimens, improving viral suppression, and reducing ADR or TDR prevalence in PALOPs, with relevant implications for public health.
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Affiliation(s)
- Cruz S Sebastião
- Global Health and Tropical Medicine, Associate Laboratory in Translation and Innovation Towards Global Health, GHTM, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Rua da Junqueira 100, Lisboa, 1349-008, Portugal
- Centro de Investigação em Saúde de Angola (CISA), Caxito, Angola
- Instituto Nacional de Investigação em Saúde (INIS), Luanda, Angola
| | - Marta Pingarilho
- Global Health and Tropical Medicine, Associate Laboratory in Translation and Innovation Towards Global Health, GHTM, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Rua da Junqueira 100, Lisboa, 1349-008, Portugal
| | - Jamila Bathy
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique
| | - Elizângela Bonfim
- Centro de Endemias de São Tome & Principe, Sao Tome, Sao Tome and Principe
| | - Katia Toancha
- Laboratório Central de Tuberculose e HIV de São Tome & Principe, Sao Tome, Sao Tome and Principe
| | - Mafalda N S Miranda
- Global Health and Tropical Medicine, Associate Laboratory in Translation and Innovation Towards Global Health, GHTM, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Rua da Junqueira 100, Lisboa, 1349-008, Portugal
| | - M Rosário O Martins
- Global Health and Tropical Medicine, Associate Laboratory in Translation and Innovation Towards Global Health, GHTM, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Rua da Junqueira 100, Lisboa, 1349-008, Portugal
| | - Perpetua Gomes
- Laboratório de Biologia Molecular (LMCBM, SPC, ULSLO), Lisbon, 1349-019, Portugal
- Egas Moniz School of Health & Sicence, Egas Moniz Center for Interdisciplinary Research (CiiEM), Caparica, Almada, 2829-511, Portugal
| | - Lazismino Lázaro
- Laboratório Central de Tuberculose e HIV de São Tome & Principe, Sao Tome, Sao Tome and Principe
| | | | - Tacilta Nhampossa
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique
| | - Silvania Leal
- Instituto de Saúde Pública, Praia, Cape Verde, Cabo Verde
| | - Ana B Abecasis
- Global Health and Tropical Medicine, Associate Laboratory in Translation and Innovation Towards Global Health, GHTM, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Rua da Junqueira 100, Lisboa, 1349-008, Portugal
| | - Victor Pimentel
- Global Health and Tropical Medicine, Associate Laboratory in Translation and Innovation Towards Global Health, GHTM, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Rua da Junqueira 100, Lisboa, 1349-008, Portugal.
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4
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Sebastião CS, Abecasis AB, Jandondo D, Sebastião JMK, Vigário J, Comandante F, Pingarilho M, Pocongo B, Cassinela E, Gonçalves F, Gomes P, Giovanetti M, Francisco NM, Sacomboio E, Brito M, Neto de Vasconcelos J, Morais J, Pimentel V. HIV-1 diversity and pre-treatment drug resistance in the era of integrase inhibitor among newly diagnosed ART-naïve adult patients in Luanda, Angola. Sci Rep 2024; 14:15893. [PMID: 38987263 PMCID: PMC11237101 DOI: 10.1038/s41598-024-66905-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 07/05/2024] [Indexed: 07/12/2024] Open
Abstract
The surveillance of drug resistance in the HIV-1 naïve population remains critical to optimizing the effectiveness of antiretroviral therapy (ART), mainly in the era of integrase strand transfer inhibitor (INSTI) regimens. Currently, there is no data regarding resistance to INSTI in Angola since Dolutegravir-DTG was included in the first-line ART regimen. Herein, we investigated the HIV-1 genetic diversity and pretreatment drug resistance (PDR) profile against nucleoside/tide reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs), protease inhibitors (PIs), and INSTIs, using a next-generation sequencing (NGS) approach with MinION, established to track and survey DRMs in Angola. This was a cross-sectional study comprising 48 newly HIV-diagnosed patients from Luanda, Angola, screened between March 2022 and May 2023. PR, RT, and IN fragments were sequenced for drug resistance and molecular transmission cluster analysis. A total of 45 out of the 48 plasma samples were successfully sequenced. Of these, 10/45 (22.2%) presented PDR to PIs/NRTIs/NNRTIs. Major mutations for NRTIs (2.2%), NNRTIs (20%), PIs (2.2%), and accessory mutations against INSTIs (13.3%) were detected. No major mutations against INSTIs were detected. M41L (2%) and I85V (2%) mutations were detected for NRTI and PI, respectively. K103N (7%), Y181C (7%), and K101E (7%) mutations were frequently observed in NNRTI. The L74M (9%) accessory mutation was frequently observed in the INSTI class. HIV-1 pure subtypes C (33%), F1 (17%), G (15%), A1 (10%), H (6%), and D (4%), CRF01_AG (4%) were observed, while about 10% were recombinant strains. About 31% of detected HIV-1C sequences were in clusters, suggesting small-scale local transmission chains. No major mutations against integrase inhibitors were detected, supporting the continued use of INSTI in the country. Further studies assessing the HIV-1 epidemiology in the era of INSTI-based ART regimens are needed in Angola.
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Affiliation(s)
- Cruz S Sebastião
- Centro de Investigação em Saúde de Angola (CISA), Caxito, Angola.
- Instituto Nacional de Investigação em Saúde (INIS), Luanda, Angola.
- Instituto de Ciências da Saúde (ICISA), Universidade Agostinho Neto (UAN), Luanda, Angola.
- Global Health and Tropical Medicine, GHTM, Associate Laboratory in Translation and Innovation Towards Global Health, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Rua da Junqueira 100, 1349-008, Lisboa, Portugal.
| | - Ana B Abecasis
- Global Health and Tropical Medicine, GHTM, Associate Laboratory in Translation and Innovation Towards Global Health, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Rua da Junqueira 100, 1349-008, Lisboa, Portugal
| | | | | | - João Vigário
- Instituto Nacional de Sangue (INS), Ministério da Saúde, Luanda, Angola
| | | | - Marta Pingarilho
- Global Health and Tropical Medicine, GHTM, Associate Laboratory in Translation and Innovation Towards Global Health, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Rua da Junqueira 100, 1349-008, Lisboa, Portugal
| | - Bárbara Pocongo
- Instituto Nacional de Luta contra SIDA (INLS), Ministério da Saúde, Luanda, Angola
| | - Edson Cassinela
- Centro Nacional de Investigação Científica (CNIC), Luanda, Angola
| | - Fátima Gonçalves
- Laboratório de Biologia Molecular (LMCBM, SPC, CHLO-HEM), 1349-019, Lisbon, Portugal
| | - Perpétua Gomes
- Laboratório de Biologia Molecular (LMCBM, SPC, CHLO-HEM), 1349-019, Lisbon, Portugal
- Egas Moniz Center for Interdisciplinary Research (CiiEM), Egas Moniz School of Health & Sicence, Caparica, Almada, Portugal
| | - Marta Giovanetti
- Department of Science and Technology for Humans and the Environment, University of Campus Bio-Medico di Roma, Rome, Italy
| | | | - Euclides Sacomboio
- Instituto de Ciências da Saúde (ICISA), Universidade Agostinho Neto (UAN), Luanda, Angola
| | - Miguel Brito
- Centro de Investigação em Saúde de Angola (CISA), Caxito, Angola
- H&TRC-Health & Technology Research Center, ESTeSL-Escola Superior de Tecnologia da Saúde, Instituto Politécnico de Lisboa, Lisbon, Portugal
| | | | - Joana Morais
- Instituto Nacional de Investigação em Saúde (INIS), Luanda, Angola
| | - Victor Pimentel
- Global Health and Tropical Medicine, GHTM, Associate Laboratory in Translation and Innovation Towards Global Health, LA-REAL, Instituto de Higiene e Medicina Tropical, IHMT, Universidade NOVA de Lisboa, UNL, Rua da Junqueira 100, 1349-008, Lisboa, Portugal.
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5
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Thomas A, Battenfeld T, Kraiselburd I, Anastasiou O, Dittmer U, Dörr AK, Dörr A, Elsner C, Gosch J, Le-Trilling VTK, Magin S, Scholtysik R, Yilmaz P, Trilling M, Schöler L, Köster J, Meyer F. UnCoVar: a reproducible and scalable workflow for transparent and robust virus variant calling and lineage assignment using SARS-CoV-2 as an example. BMC Genomics 2024; 25:647. [PMID: 38943066 PMCID: PMC11214259 DOI: 10.1186/s12864-024-10539-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Accepted: 06/18/2024] [Indexed: 07/01/2024] Open
Abstract
BACKGROUND At a global scale, the SARS-CoV-2 virus did not remain in its initial genotype for a long period of time, with the first global reports of variants of concern (VOCs) in late 2020. Subsequently, genome sequencing has become an indispensable tool for characterizing the ongoing pandemic, particularly for typing SARS-CoV-2 samples obtained from patients or environmental surveillance. For such SARS-CoV-2 typing, various in vitro and in silico workflows exist, yet to date, no systematic cross-platform validation has been reported. RESULTS In this work, we present the first comprehensive cross-platform evaluation and validation of in silico SARS-CoV-2 typing workflows. The evaluation relies on a dataset of 54 patient-derived samples sequenced with several different in vitro approaches on all relevant state-of-the-art sequencing platforms. Moreover, we present UnCoVar, a robust, production-grade reproducible SARS-CoV-2 typing workflow that outperforms all other tested approaches in terms of precision and recall. CONCLUSIONS In many ways, the SARS-CoV-2 pandemic has accelerated the development of techniques and analytical approaches. We believe that this can serve as a blueprint for dealing with future pandemics. Accordingly, UnCoVar is easily generalizable towards other viral pathogens and future pandemics. The fully automated workflow assembles virus genomes from patient samples, identifies existing lineages, and provides high-resolution insights into individual mutations. UnCoVar includes extensive quality control and automatically generates interactive visual reports. UnCoVar is implemented as a Snakemake workflow. The open-source code is available under a BSD 2-clause license at github.com/IKIM-Essen/uncovar.
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Affiliation(s)
- Alexander Thomas
- Data Science Research Group, Institute for Artificial Intelligence in Medicine (IKIM), University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Thomas Battenfeld
- Data Science Research Group, Institute for Artificial Intelligence in Medicine (IKIM), University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Ivana Kraiselburd
- Data Science Research Group, Institute for Artificial Intelligence in Medicine (IKIM), University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Olympia Anastasiou
- Institute for Virology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Ulf Dittmer
- Institute for Virology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Ann-Kathrin Dörr
- Data Science Research Group, Institute for Artificial Intelligence in Medicine (IKIM), University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Adrian Dörr
- Data Science Research Group, Institute for Artificial Intelligence in Medicine (IKIM), University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Carina Elsner
- Institute for Virology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Jule Gosch
- Data Science Research Group, Institute for Artificial Intelligence in Medicine (IKIM), University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Vu Thuy Khanh Le-Trilling
- Institute for Virology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
- Institute for the Research on HIV & AIDS-associated Diseases, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Simon Magin
- Data Science Research Group, Institute for Artificial Intelligence in Medicine (IKIM), University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - René Scholtysik
- Institute for the Research on HIV & AIDS-associated Diseases, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Pelin Yilmaz
- Data Science Research Group, Institute for Artificial Intelligence in Medicine (IKIM), University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Mirko Trilling
- Institute for Virology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
- Institute for the Research on HIV & AIDS-associated Diseases, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Lara Schöler
- Institute for Virology, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
- Institute for the Research on HIV & AIDS-associated Diseases, University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
- Institute of Cell Biology (Cancer Research), University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
| | - Johannes Köster
- Bioinformatics and Computational Oncology, Institute for Artificial Intelligence in Medicine (IKIM), University Hospital of Essen, University of Duisburg-Essen, Essen, Germany
- Division of Molecular and Cellular Oncology, Department of Medical Oncology, Harvard Medical School, Boston, MA, USA
| | - Folker Meyer
- Data Science Research Group, Institute for Artificial Intelligence in Medicine (IKIM), University Hospital of Essen, University of Duisburg-Essen, Essen, Germany.
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6
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Pimentel V, Pingarilho M, Sebastião CS, Miranda M, Gonçalves F, Cabanas J, Costa I, Diogo I, Fernandes S, Costa O, Corte-Real R, Martins MRO, Seabra SG, Abecasis AB, Gomes P. Applying Next-Generation Sequencing to Track HIV-1 Drug Resistance Mutations Circulating in Portugal. Viruses 2024; 16:622. [PMID: 38675962 PMCID: PMC11054263 DOI: 10.3390/v16040622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 04/02/2024] [Accepted: 04/06/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND The global scale-up of antiretroviral treatment (ART) offers significant health benefits by suppressing HIV-1 replication and increasing CD4 cell counts. However, incomplete viral suppression poses a potential threat for the emergence of drug resistance mutations (DRMs), limiting ART options, and increasing HIV transmission. OBJECTIVE We investigated the patterns of transmitted drug resistance (TDR) and acquired drug resistance (ADR) among HIV-1 patients in Portugal. METHODS Data were obtained from 1050 HIV-1 patient samples submitted for HIV drug resistance (HIVDR) testing from January 2022 to June 2023. Evaluation of DRM affecting viral susceptibility to nucleoside/tide reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs), protease inhibitors (PIs), and integrase strand transfer inhibitors (INSTIs) was performed using an NGS technology, the Vela Diagnostics Sentosa SQ HIV-1 Genotyping Assay. RESULTS About 71% of patients were ART naïve and 29% were experienced. Overall, 20% presented with any DRM. The prevalence of TDR and ADR was 12.6% and 41.1%, respectively. M184V, T215S, and M41L mutations for NRTI, K103N for NNRTI, and M46I/L for PIs were frequent in naïve and treated patients. E138K and R263K mutations against INSTIs were more frequent in naïve than treated patients. TDR and ADR to INSTIs were 0.3% and 7%, respectively. Patients aged 50 or over (OR: 1.81, p = 0.015), originating from Portuguese-speaking African countries (PALOPs) (OR: 1.55, p = 0.050), HIV-1 subtype G (OR: 1.78, p = 0.010), and with CD4 < 200 cells/mm3 (OR: 1.70, p = 0.043) were more likely to present with DRMs, while the males (OR: 0.63, p = 0.003) with a viral load between 4.1 to 5.0 Log10 (OR: 0.55, p = 0.003) or greater than 5.0 Log10 (OR: 0.52, p < 0.001), had lower chances of presenting with DRMs. CONCLUSIONS We present the first evidence on TDR and ADR to INSTI regimens in followed up patients presenting for healthcare in Portugal. We observed low levels of TDR to INSTIs among ART-naïve and moderate levels in ART-exposed patients. Regimens containing PIs could be an alternative second line in patients with intermediate or high-level drug resistance, especially against second-generation INSTIs (dolutegravir, bictegravir, and cabotegravir).
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Affiliation(s)
- Victor Pimentel
- Global Health and Tropical Medicine (GHTM), Associate Laboratory in Translation and Innovation Towards Global Health (LA-REAL), Instituto de Higiene e Medicina Tropical (IHMT), Universidade NOVA de Lisboa (UNL), Rua da Junqueira 100, 1349-008 Lisbon, Portugal; (M.P.); (C.S.S.); (M.M.); (M.R.O.M.); (S.G.S.); (A.B.A.)
| | - Marta Pingarilho
- Global Health and Tropical Medicine (GHTM), Associate Laboratory in Translation and Innovation Towards Global Health (LA-REAL), Instituto de Higiene e Medicina Tropical (IHMT), Universidade NOVA de Lisboa (UNL), Rua da Junqueira 100, 1349-008 Lisbon, Portugal; (M.P.); (C.S.S.); (M.M.); (M.R.O.M.); (S.G.S.); (A.B.A.)
| | - Cruz S. Sebastião
- Global Health and Tropical Medicine (GHTM), Associate Laboratory in Translation and Innovation Towards Global Health (LA-REAL), Instituto de Higiene e Medicina Tropical (IHMT), Universidade NOVA de Lisboa (UNL), Rua da Junqueira 100, 1349-008 Lisbon, Portugal; (M.P.); (C.S.S.); (M.M.); (M.R.O.M.); (S.G.S.); (A.B.A.)
- Centro de Investigação em Saúde de Angola (CISA), Caxito, Angola
- Instituto Nacional de Investigação em Saúde (INIS), Luanda, Angola
| | - Mafalda Miranda
- Global Health and Tropical Medicine (GHTM), Associate Laboratory in Translation and Innovation Towards Global Health (LA-REAL), Instituto de Higiene e Medicina Tropical (IHMT), Universidade NOVA de Lisboa (UNL), Rua da Junqueira 100, 1349-008 Lisbon, Portugal; (M.P.); (C.S.S.); (M.M.); (M.R.O.M.); (S.G.S.); (A.B.A.)
| | - Fátima Gonçalves
- Laboratório de Biologia Molecular, Serviço de Patologia Clínica, Unidade Local de Saúde Lisboa Ocidental, Hospital Egas Moniz, 1349-019 Lisbon, Portugal; (F.G.); (J.C.); (I.C.); (I.D.); (S.F.); (P.G.)
| | - Joaquim Cabanas
- Laboratório de Biologia Molecular, Serviço de Patologia Clínica, Unidade Local de Saúde Lisboa Ocidental, Hospital Egas Moniz, 1349-019 Lisbon, Portugal; (F.G.); (J.C.); (I.C.); (I.D.); (S.F.); (P.G.)
| | - Inês Costa
- Laboratório de Biologia Molecular, Serviço de Patologia Clínica, Unidade Local de Saúde Lisboa Ocidental, Hospital Egas Moniz, 1349-019 Lisbon, Portugal; (F.G.); (J.C.); (I.C.); (I.D.); (S.F.); (P.G.)
| | - Isabel Diogo
- Laboratório de Biologia Molecular, Serviço de Patologia Clínica, Unidade Local de Saúde Lisboa Ocidental, Hospital Egas Moniz, 1349-019 Lisbon, Portugal; (F.G.); (J.C.); (I.C.); (I.D.); (S.F.); (P.G.)
| | - Sandra Fernandes
- Laboratório de Biologia Molecular, Serviço de Patologia Clínica, Unidade Local de Saúde Lisboa Ocidental, Hospital Egas Moniz, 1349-019 Lisbon, Portugal; (F.G.); (J.C.); (I.C.); (I.D.); (S.F.); (P.G.)
| | - Olga Costa
- Biologia Molecular, Serviço de Patologia Clínica, Centro Hospitalar de Lisboa Central, 1150-199 Lisbon, Portugal; (O.C.); (R.C.-R.)
| | - Rita Corte-Real
- Biologia Molecular, Serviço de Patologia Clínica, Centro Hospitalar de Lisboa Central, 1150-199 Lisbon, Portugal; (O.C.); (R.C.-R.)
| | - M. Rosário O. Martins
- Global Health and Tropical Medicine (GHTM), Associate Laboratory in Translation and Innovation Towards Global Health (LA-REAL), Instituto de Higiene e Medicina Tropical (IHMT), Universidade NOVA de Lisboa (UNL), Rua da Junqueira 100, 1349-008 Lisbon, Portugal; (M.P.); (C.S.S.); (M.M.); (M.R.O.M.); (S.G.S.); (A.B.A.)
| | - Sofia G. Seabra
- Global Health and Tropical Medicine (GHTM), Associate Laboratory in Translation and Innovation Towards Global Health (LA-REAL), Instituto de Higiene e Medicina Tropical (IHMT), Universidade NOVA de Lisboa (UNL), Rua da Junqueira 100, 1349-008 Lisbon, Portugal; (M.P.); (C.S.S.); (M.M.); (M.R.O.M.); (S.G.S.); (A.B.A.)
| | - Ana B. Abecasis
- Global Health and Tropical Medicine (GHTM), Associate Laboratory in Translation and Innovation Towards Global Health (LA-REAL), Instituto de Higiene e Medicina Tropical (IHMT), Universidade NOVA de Lisboa (UNL), Rua da Junqueira 100, 1349-008 Lisbon, Portugal; (M.P.); (C.S.S.); (M.M.); (M.R.O.M.); (S.G.S.); (A.B.A.)
| | - Perpétua Gomes
- Laboratório de Biologia Molecular, Serviço de Patologia Clínica, Unidade Local de Saúde Lisboa Ocidental, Hospital Egas Moniz, 1349-019 Lisbon, Portugal; (F.G.); (J.C.); (I.C.); (I.D.); (S.F.); (P.G.)
- Egas Moniz Center for Interdisciplinary Research (CiiEM), Egas Moniz School of Health & Science, Caparica, 2829-511 Almada, Portugal
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7
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Lorenzi JN, Graner F, Courtier-Orgogozo V, Achaz G. CNCA aligns small annotated genomes. BMC Bioinformatics 2024; 25:89. [PMID: 38424511 PMCID: PMC10905818 DOI: 10.1186/s12859-024-05700-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Accepted: 02/12/2024] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND To explore the evolutionary history of sequences, a sequence alignment is a first and necessary step, and its quality is crucial. In the context of the study of the proximal origins of SARS-CoV-2 coronavirus, we wanted to construct an alignment of genomes closely related to SARS-CoV-2 using both coding and non-coding sequences. To our knowledge, there is no tool that can be used to construct this type of alignment, which motivated the creation of CNCA. RESULTS CNCA is a web tool that aligns annotated genomes from GenBank files. It generates a nucleotide alignment that is then updated based on the protein sequence alignment. The output final nucleotide alignment matches the protein alignment and guarantees no frameshift. CNCA was designed to align closely related small genome sequences up to 50 kb (typically viruses) for which the gene order is conserved. CONCLUSIONS CNCA constructs multiple alignments of small genomes by integrating both coding and non-coding sequences. This preserves regions traditionally ignored in conventional back-translation methods, such as non-coding regions.
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Affiliation(s)
- Jean-Noël Lorenzi
- Université Paris Cité, Paris, France.
- CNRS, Institut Jacques Monod, 75013, Paris, France.
- SMILE Group, Center for Interdisciplinary Research in Biology (CIRB), Collège de France, 75006, Paris, France.
| | - François Graner
- Université Paris Cité, Paris, France
- CNRS, Matière Et Systèmes Complexes, 75013, Paris, France
| | | | - Guillaume Achaz
- SMILE Group, Center for Interdisciplinary Research in Biology (CIRB), Collège de France, 75006, Paris, France
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8
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Miranda MNS, Pimentel V, Gomes P, Martins MDRO, Seabra SG, Kaiser R, Böhm M, Seguin-Devaux C, Paredes R, Bobkova M, Zazzi M, Incardona F, Pingarilho M, Abecasis AB. The Role of Late Presenters in HIV-1 Transmission Clusters in Europe. Viruses 2023; 15:2418. [PMID: 38140659 PMCID: PMC10746990 DOI: 10.3390/v15122418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 11/30/2023] [Accepted: 12/08/2023] [Indexed: 12/24/2023] Open
Abstract
BACKGROUND Investigating the role of late presenters (LPs) in HIV-1 transmission is important, as they can contribute to the onward spread of HIV-1 virus before diagnosis, when they are not aware of their HIV status. OBJECTIVE To characterize individuals living with HIV-1 followed up in Europe infected with subtypes A, B, and G and to compare transmission clusters (TC) in LP vs. non-late presenter (NLP) populations. METHODS Information from a convenience sample of 2679 individuals living with HIV-1 was collected from the EuResist Integrated Database between 2008 and 2019. Maximum likelihood (ML) phylogenies were constructed using FastTree. Transmission clusters were identified using Cluster Picker. Statistical analyses were performed using R. RESULTS 2437 (91.0%) sequences were from subtype B, 168 (6.3%) from subtype A, and 74 (2.8%) from subtype G. The median age was 39 y/o (IQR: 31.0-47.0) and 85.2% of individuals were males. The main transmission route was via homosexual (MSM) contact (60.1%) and 85.0% originated from Western Europe. In total, 54.7% of individuals were classified as LPs and 41.7% of individuals were inside TCs. In subtype A, individuals in TCs were more frequently males and natives with a recent infection. For subtype B, individuals in TCs were more frequently individuals with MSM transmission route and with a recent infection. For subtype G, individuals in TCs were those with a recent infection. When analyzing cluster size, we found that LPs more frequently belonged to small clusters (<8 individuals), particularly dual clusters (2 individuals). CONCLUSION LP individuals are more present either outside or in small clusters, indicating a limited role of late presentation to HIV-1 transmission.
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Affiliation(s)
- Mafalda N. S. Miranda
- Global Health and Tropical Medicine (GHTM), Associate Laboratory in Translation and Innovation towards Global Health (LA-REAL), Institute of Hygiene and Tropical Medicine, New University of Lisbon (IHMT/UNL), 1349-008 Lisbon, Portugal; (V.P.); (M.d.R.O.M.); (S.G.S.); (M.P.); (A.B.A.)
| | - Victor Pimentel
- Global Health and Tropical Medicine (GHTM), Associate Laboratory in Translation and Innovation towards Global Health (LA-REAL), Institute of Hygiene and Tropical Medicine, New University of Lisbon (IHMT/UNL), 1349-008 Lisbon, Portugal; (V.P.); (M.d.R.O.M.); (S.G.S.); (M.P.); (A.B.A.)
| | - Perpétua Gomes
- Laboratório de Biologia Molecular (LMCBM, SPC, CHLO-HEM), 1349-019 Lisbon, Portugal;
- Centro de Investigação Interdisciplinar Egas Moniz (CiiEM), Instituto Universitário Egas Moniz, 2829-511 Costa da Caparica, Portugal
| | - Maria do Rosário O. Martins
- Global Health and Tropical Medicine (GHTM), Associate Laboratory in Translation and Innovation towards Global Health (LA-REAL), Institute of Hygiene and Tropical Medicine, New University of Lisbon (IHMT/UNL), 1349-008 Lisbon, Portugal; (V.P.); (M.d.R.O.M.); (S.G.S.); (M.P.); (A.B.A.)
| | - Sofia G. Seabra
- Global Health and Tropical Medicine (GHTM), Associate Laboratory in Translation and Innovation towards Global Health (LA-REAL), Institute of Hygiene and Tropical Medicine, New University of Lisbon (IHMT/UNL), 1349-008 Lisbon, Portugal; (V.P.); (M.d.R.O.M.); (S.G.S.); (M.P.); (A.B.A.)
| | - Rolf Kaiser
- Institute of Virology, University Hospital of Cologne, University of Cologne, 50923 Cologne, Germany; (R.K.); (M.B.)
- DZIF, Deutsches Zentrum für Infektionsforschung, German Center for Infection Research, Partner Site Bonn-Cologne, 50923 Cologne, Germany
| | - Michael Böhm
- Institute of Virology, University Hospital of Cologne, University of Cologne, 50923 Cologne, Germany; (R.K.); (M.B.)
- DZIF, Deutsches Zentrum für Infektionsforschung, German Center for Infection Research, Partner Site Bonn-Cologne, 50923 Cologne, Germany
| | - Carole Seguin-Devaux
- Laboratory of Retrovirology, Department of Infection and Immunity, Luxembourg Institute of Health, L-4354 Esch-sur-Alzette, Luxembourg;
| | - Roger Paredes
- Infectious Diseases Department, IrsiCaixa AIDS Research Institute, Hospital University Hospital Germans Trias i Pujol, 08916 Badalona, Spain;
| | - Marina Bobkova
- Gamaleya National Research Center of Epidemiology and Microbiology, 123098 Moscow, Russia;
| | - Maurizio Zazzi
- Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy;
| | - Francesca Incardona
- IPRO—InformaPRO S.r.l., 00152 Rome, Italy;
- EuResist Network, 00152 Rome, Italy
| | - Marta Pingarilho
- Global Health and Tropical Medicine (GHTM), Associate Laboratory in Translation and Innovation towards Global Health (LA-REAL), Institute of Hygiene and Tropical Medicine, New University of Lisbon (IHMT/UNL), 1349-008 Lisbon, Portugal; (V.P.); (M.d.R.O.M.); (S.G.S.); (M.P.); (A.B.A.)
| | - Ana B. Abecasis
- Global Health and Tropical Medicine (GHTM), Associate Laboratory in Translation and Innovation towards Global Health (LA-REAL), Institute of Hygiene and Tropical Medicine, New University of Lisbon (IHMT/UNL), 1349-008 Lisbon, Portugal; (V.P.); (M.d.R.O.M.); (S.G.S.); (M.P.); (A.B.A.)
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Liu Y, Yuan H, Zhang Q, Wang Z, Xiong S, Wen N, Zhang Y. Multiple sequence alignment based on deep reinforcement learning with self-attention and positional encoding. Bioinformatics 2023; 39:btad636. [PMID: 37856335 PMCID: PMC10628385 DOI: 10.1093/bioinformatics/btad636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 07/24/2023] [Accepted: 10/17/2023] [Indexed: 10/21/2023] Open
Abstract
MOTIVATION Multiple sequence alignment (MSA) is one of the hotspots of current research and is commonly used in sequence analysis scenarios. However, there is no lasting solution for MSA because it is a Nondeterministic Polynomially complete problem, and the existing methods still have room to improve the accuracy. RESULTS We propose Deep reinforcement learning with Positional encoding and self-Attention for MSA, based on deep reinforcement learning, to enhance the accuracy of the alignment Specifically, inspired by the translation technique in natural language processing, we introduce self-attention and positional encoding to improve accuracy and reliability. Firstly, positional encoding encodes the position of the sequence to prevent the loss of nucleotide position information. Secondly, the self-attention model is used to extract the key features of the sequence. Then input the features into a multi-layer perceptron, which can calculate the insertion position of the gap according to the features. In addition, a novel reinforcement learning environment is designed to convert the classic progressive alignment into progressive column alignment, gradually generating each column's sub-alignment. Finally, merge the sub-alignment into the complete alignment. Extensive experiments based on several datasets validate our method's effectiveness for MSA, outperforming some state-of-the-art methods in terms of the Sum-of-pairs and Column scores. AVAILABILITY AND IMPLEMENTATION The process is implemented in Python and available as open-source software from https://github.com/ZhangLab312/DPAMSA.
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Affiliation(s)
- Yuhang Liu
- School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China
| | - Hao Yuan
- School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China
| | - Qiang Zhang
- School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China
| | - Zixuan Wang
- College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China
| | - Shuwen Xiong
- School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China
| | - Naifeng Wen
- School of Mechanical and Electrical Engineering, Dalian Minzu University, Dalian 116600, China
| | - Yongqing Zhang
- School of Computer Science, Chengdu University of Information Technology, Chengdu 610225, China
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10
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Jin B, Oyama R, Tabe Y, Tsuchiya K, Hando T, Wakita M, Yan Y, Saita M, Takei S, Horiuchi Y, Miida T, Naito T, Takahashi K, Ogawa H. Investigation of the individual genetic evolution of SARS-CoV-2 in a small cluster during the rapid spread of the BF.5 lineage in Tokyo, Japan. Front Microbiol 2023; 14:1229234. [PMID: 37744926 PMCID: PMC10516552 DOI: 10.3389/fmicb.2023.1229234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 08/17/2023] [Indexed: 09/26/2023] Open
Abstract
There has been a decreasing trend in new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases and fatalities worldwide. The virus has been evolving, indicating the potential emergence of new variants and uncertainties. These challenges necessitate continued efforts in disease control and mitigation strategies. We investigated a small cluster of SARS-CoV-2 Omicron variant infections containing a common set of genomic mutations, which provided a valuable model for investigating the transmission mechanism of genetic alterations. We conducted a study at a medical center in Japan during the Omicron surge (sub-lineage BA.5), sequencing the entire SARS-CoV-2 genomes from infected individuals and evaluating the phylogenetic tree and haplotype network among the variants. We compared the mutations present in each strain within the BA.5 strain, TKYnat2317, which was first identified in Tokyo, Japan. From June 29th to July 4th 2022, nine healthcare workers (HCWs) tested positive for SARS-CoV-2 by real-time PCR. During the same period, five patients also tested positive by real-time PCR. Whole genome sequencing revealed that the infected patients belonged to either the isolated BA.2 or BA.5 sub-lineage, while the healthcare worker infections were classified as BF.5. The phylogenetic tree and haplotype network clearly showed the specificity and similarity of the HCW cluster. We identified 12 common mutations in the cluster, including I110V in nonstructural protein 4 (nsp4), A1020S in the Spike protein, and H47Y in ORF7a, compared to the BA.5 reference. Additionally, one case had the extra nucleotide-deletion mutation I27* in ORF10, and low frequencies of genetic alterations were also found in certain instances. The results of genome sequencing showed that the nine HCWs shared a set of genetic mutations, indicating transmission within the cluster. Minor mutations observed in five HCW individuals suggested the emergence of new virus variants. Five amino acid substitutions occurred in nsp3, which could potentially affect virus replication or immune escape. Intra-host evolution also generated additional mutations. The cluster exhibited a mild disease course, with individuals in this case, recovering without requiring any medical treatments. Further investigation is needed to understand the relationship between the genetic evolution of the virus and the symptoms.
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Affiliation(s)
- Bo Jin
- Department of Clinical Laboratory, Peking University First Hospital, Beijing, China
| | - Rieko Oyama
- Department of Research Support Utilizing Bioresource Bank, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yoko Tabe
- Department of Research Support Utilizing Bioresource Bank, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Clinical Laboratory Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Koji Tsuchiya
- Department of Clinical Laboratory, Juntendo University Hospital, Tokyo, Japan
| | - Tetsuya Hando
- Department of Clinical Laboratory, Juntendo University Hospital, Tokyo, Japan
| | - Mitsuru Wakita
- Department of Clinical Laboratory, Juntendo University Hospital, Tokyo, Japan
| | - Yan Yan
- Department of General Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Mizue Saita
- Department of General Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Satomi Takei
- Department of Clinical Laboratory Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yuki Horiuchi
- Department of Clinical Laboratory Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Takashi Miida
- Department of Clinical Laboratory Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Toshio Naito
- Department of Research Support Utilizing Bioresource Bank, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of General Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Kazuhisa Takahashi
- Department of Research Support Utilizing Bioresource Bank, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Respiratory Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Hideoki Ogawa
- Department of Dermatology, Juntendo University Graduate School of Medicine, Tokyo, Japan
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11
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Nirmalarajah K, Yim W, Aftanas P, Li AX, Shigayeva A, Yip L, Zhong Z, McGeer AJ, Maguire F, Mubareka S, Kozak R. Use of whole genome sequencing to identify low-frequency mutations in SARS-CoV-2 patients treated with remdesivir. Influenza Other Respir Viruses 2023; 17:e13179. [PMID: 37752062 PMCID: PMC10522481 DOI: 10.1111/irv.13179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 06/28/2023] [Accepted: 07/15/2023] [Indexed: 09/28/2023] Open
Abstract
BACKGROUND Remdesivir (RDV) has been shown to reduce hospitalization and mortality in COVID-19 patients. Resistance mutations caused by RDV are rare and have been predominantly reported in patients who are on prolonged therapy and immunocompromised. We investigate the effects of RDV treatment on intra-host SARS-CoV-2 diversity and low-frequency mutations in moderately ill hospitalized COVID-19 patients and compare them to patients without RDV treatment. METHODS From March 2020 to April 2022, sequential collections of nasopharyngeal and mid-turbinate swabs were obtained from 14 patients with and 30 patients without RDV treatment. Demographic and clinical data on all patients were reviewed. A total of 109 samples were sequenced and mutation analyses were performed. RESULTS Previously reported drug resistant mutations in nsp12 were not identified during short courses of RDV therapy. In genes encoding and surrounding the replication complex (nsp6-nsp14), low-frequency minority variants were detected in 7/14 (50%) and 18/30 (60%) patients with and without RDV treatment, respectively. We did not detect significant differences in within-host diversity and positive selection between the RDV-treated and untreated groups. CONCLUSIONS Minimal intra-host variability and stochastic low-frequency variants detected in moderately ill patients suggests little selective pressure in patients receiving short courses of RDV. The barrier to RDV resistance is high in patients with moderate disease. Patients undergoing short regimens of RDV therapy should continue to be monitored.
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Affiliation(s)
- Kuganya Nirmalarajah
- Sunnybrook Research InstituteTorontoOntarioCanada
- Department of Laboratory Medicine and PathobiologyUniversity of TorontoTorontoOntarioCanada
| | - Winfield Yim
- Sunnybrook Research InstituteTorontoOntarioCanada
| | | | | | | | - Lily Yip
- Sunnybrook Research InstituteTorontoOntarioCanada
| | - Zoe Zhong
- Sinai Health SystemTorontoOntarioCanada
| | - Allison J. McGeer
- Department of Laboratory Medicine and PathobiologyUniversity of TorontoTorontoOntarioCanada
- Sinai Health SystemTorontoOntarioCanada
| | - Finlay Maguire
- Faculty of Computer ScienceDalhousie UniversityHalifaxNova ScotiaCanada
- Department of Community Health & EpidemiologyDalhousie UniversityHalifaxNova ScotiaCanada
| | - Samira Mubareka
- Sunnybrook Research InstituteTorontoOntarioCanada
- Department of Laboratory Medicine and PathobiologyUniversity of TorontoTorontoOntarioCanada
| | - Robert Kozak
- Sunnybrook Research InstituteTorontoOntarioCanada
- Department of Laboratory Medicine and PathobiologyUniversity of TorontoTorontoOntarioCanada
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12
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Kremer C, Torneri A, Libin PJK, Meex C, Hayette MP, Bontems S, Durkin K, Artesi M, Bours V, Lemey P, Darcis G, Hens N, Meuris C. Reconstruction of SARS-CoV-2 outbreaks in a primary school using epidemiological and genomic data. Epidemics 2023; 44:100701. [PMID: 37379776 PMCID: PMC10273772 DOI: 10.1016/j.epidem.2023.100701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 06/02/2023] [Accepted: 06/12/2023] [Indexed: 06/30/2023] Open
Abstract
Mathematical modelling studies have shown that repetitive screening can be used to mitigate SARS-CoV-2 transmission in primary schools while keeping schools open. However, not much is known about how transmission progresses within schools and whether there is a risk of importation to households. During the academic year 2020-2021, a prospective surveillance study using repetitive screening was conducted in a primary school and associated households in Liège (Belgium). SARS-CoV-2 screening was performed via throat washing either once or twice a week. We used genomic and epidemiological data to reconstruct the observed school outbreaks using two different models. The outbreaker2 model combines information on the generation time and contact patterns with a model of sequence evolution. For comparison we also used SCOTTI, a phylogenetic model based on the structured coalescent. In addition, we performed a simulation study to investigate how the accuracy of estimated positivity rates in a school depends on the proportion of a school that is sampled in a repetitive screening strategy. We found no difference in SARS-CoV-2 positivity between children and adults and children were not more often asymptomatic compared to adults. Both models for outbreak reconstruction revealed that transmission occurred mainly within the school environment. Uncertainty in outbreak reconstruction was lowest when including genomic as well as epidemiological data. We found that observed weekly positivity rates are a good approximation to the true weekly positivity rate, especially in children, even when only 25% of the school population is sampled. These results indicate that, in addition to reducing infections as shown in modelling studies, repetitive screening in school settings can lead to a better understanding of the extent of transmission in schools during a pandemic and importation risk at the community level.
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Affiliation(s)
- Cécile Kremer
- Interuniversity Institute for Biostatistics and statistical Bioinformatics, Data Science Institute, Hasselt University, Hasselt, Belgium.
| | - Andrea Torneri
- Interuniversity Institute for Biostatistics and statistical Bioinformatics, Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Pieter J K Libin
- Interuniversity Institute for Biostatistics and statistical Bioinformatics, Data Science Institute, Hasselt University, Hasselt, Belgium; Artificial Intelligence Lab, Department of Computer Science, Vrije Universiteit Brussel, Brussels, Belgium; Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, University of Leuven, Leuven, Belgium
| | - Cécile Meex
- Department of Clinical Microbiology, University of Liège, Liège, Belgium
| | | | - Sébastien Bontems
- Department of Clinical Microbiology, University of Liège, Liège, Belgium
| | - Keith Durkin
- Laboratory of Human Genetics, GIGA-Institute, University of Liège, Liège, Belgium
| | - Maria Artesi
- Laboratory of Human Genetics, GIGA-Institute, University of Liège, Liège, Belgium
| | - Vincent Bours
- Laboratory of Human Genetics, GIGA-Institute, University of Liège, Liège, Belgium
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, University of Leuven, Leuven, Belgium
| | - Gilles Darcis
- Department of Infectious Diseases, Liège University Hospital, Liège, Belgium
| | - Niel Hens
- Interuniversity Institute for Biostatistics and statistical Bioinformatics, Data Science Institute, Hasselt University, Hasselt, Belgium; Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Christelle Meuris
- Department of Infectious Diseases, Liège University Hospital, Liège, Belgium
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13
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Shukla N, Srivastava N, Gupta R, Srivastava P, Narayan J. COVID Variants, Villain and Victory: A Bioinformatics Perspective. Microorganisms 2023; 11:2039. [PMID: 37630599 PMCID: PMC10459809 DOI: 10.3390/microorganisms11082039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 07/11/2023] [Accepted: 07/11/2023] [Indexed: 08/27/2023] Open
Abstract
The SARS-CoV-2 virus, a novel member of the Coronaviridae family, is responsible for the viral infection known as Coronavirus Disease 2019 (COVID-19). In response to the urgent and critical need for rapid detection, diagnosis, analysis, interpretation, and treatment of COVID-19, a wide variety of bioinformatics tools have been developed. Given the virulence of SARS-CoV-2, it is crucial to explore the pathophysiology of the virus. We intend to examine how bioinformatics, in conjunction with next-generation sequencing techniques, can be leveraged to improve current diagnostic tools and streamline vaccine development for emerging SARS-CoV-2 variants. We also emphasize how bioinformatics, in general, can contribute to critical areas of biomedicine, including clinical diagnostics, SARS-CoV-2 genomic surveillance and its evolution, identification of potential drug targets, and development of therapeutic strategies. Currently, state-of-the-art bioinformatics tools have helped overcome technical obstacles with respect to genomic surveillance and have assisted in rapid detection, diagnosis, and delivering precise treatment to individuals on time.
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Affiliation(s)
- Nityendra Shukla
- CSIR Institute of Genomics and Integrative Biology, Mall Road, Delhi 110007, India; (N.S.); (R.G.)
| | - Neha Srivastava
- Amity Institute of Biotechnology, Amity University, Uttar Pradesh, Lucknow Campus, Lucknow 226010, India; (N.S.); (P.S.)
| | - Rohit Gupta
- CSIR Institute of Genomics and Integrative Biology, Mall Road, Delhi 110007, India; (N.S.); (R.G.)
| | - Prachi Srivastava
- Amity Institute of Biotechnology, Amity University, Uttar Pradesh, Lucknow Campus, Lucknow 226010, India; (N.S.); (P.S.)
| | - Jitendra Narayan
- CSIR Institute of Genomics and Integrative Biology, Mall Road, Delhi 110007, India; (N.S.); (R.G.)
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14
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Pamornchainavakul N, Paploski IAD, Makau DN, Kikuti M, Rovira A, Lycett S, Corzo CA, VanderWaal K. Mapping the Dynamics of Contemporary PRRSV-2 Evolution and Its Emergence and Spreading Hotspots in the U.S. Using Phylogeography. Pathogens 2023; 12:740. [PMID: 37242410 PMCID: PMC10222675 DOI: 10.3390/pathogens12050740] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 05/16/2023] [Accepted: 05/19/2023] [Indexed: 05/28/2023] Open
Abstract
The repeated emergence of new genetic variants of PRRSV-2, the virus that causes porcine reproductive and respiratory syndrome (PRRS), reflects its rapid evolution and the failure of previous control efforts. Understanding spatiotemporal heterogeneity in variant emergence and spread is critical for future outbreak prevention. Here, we investigate how the pace of evolution varies across time and space, identify the origins of sub-lineage emergence, and map the patterns of the inter-regional spread of PRRSV-2 Lineage 1 (L1)-the current dominant lineage in the U.S. We performed comparative phylogeographic analyses on subsets of 19,395 viral ORF5 sequences collected across the U.S. and Canada between 1991 and 2021. The discrete trait analysis of multiple spatiotemporally stratified sampled sets (n = 500 each) was used to infer the ancestral geographic region and dispersion of each sub-lineage. The robustness of the results was compared to that of other modeling methods and subsampling strategies. Generally, the spatial spread and population dynamics varied across sub-lineages, time, and space. The Upper Midwest was a main spreading hotspot for multiple sub-lineages, e.g., L1C and L1F, though one of the most recent emergence events (L1A(2)) spread outwards from the east. An understanding of historical patterns of emergence and spread can be used to strategize disease control and the containment of emerging variants.
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Affiliation(s)
- Nakarin Pamornchainavakul
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN 55108, USA; (N.P.); (I.A.D.P.); (D.N.M.); (M.K.); (A.R.); (C.A.C.)
| | - Igor A. D. Paploski
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN 55108, USA; (N.P.); (I.A.D.P.); (D.N.M.); (M.K.); (A.R.); (C.A.C.)
| | - Dennis N. Makau
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN 55108, USA; (N.P.); (I.A.D.P.); (D.N.M.); (M.K.); (A.R.); (C.A.C.)
| | - Mariana Kikuti
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN 55108, USA; (N.P.); (I.A.D.P.); (D.N.M.); (M.K.); (A.R.); (C.A.C.)
| | - Albert Rovira
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN 55108, USA; (N.P.); (I.A.D.P.); (D.N.M.); (M.K.); (A.R.); (C.A.C.)
- Veterinary Diagnostic Laboratory, University of Minnesota, St. Paul, MN 55108, USA
| | - Samantha Lycett
- Roslin Institute, University of Edinburgh, Edinburgh EH25 9RG, UK;
| | - Cesar A. Corzo
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN 55108, USA; (N.P.); (I.A.D.P.); (D.N.M.); (M.K.); (A.R.); (C.A.C.)
| | - Kimberly VanderWaal
- Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN 55108, USA; (N.P.); (I.A.D.P.); (D.N.M.); (M.K.); (A.R.); (C.A.C.)
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15
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Genetic Characterization of a Novel Equus caballus Papillomavirus Isolated from a Thoroughbred Mare. Viruses 2023; 15:v15030650. [PMID: 36992359 PMCID: PMC10059215 DOI: 10.3390/v15030650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 02/27/2023] [Accepted: 02/27/2023] [Indexed: 03/05/2023] Open
Abstract
Papillomaviruses (PVs) are small, non-enveloped viruses, ubiquitous across the animal kingdom. PVs induce diverse forms of infection, such as cutaneous papillomas, genital papillomatosis, and carcinomas. During a survey on the fertility status of a mare, a novel Equus caballus PV (EcPV) has been identified using Next Generation Sequencing, and it was further confirmed with genome-walking PCR and Sanger sequencing. The complete circular genome 7607 bp long shares 67% average percentage of identity with EcPV9, EcPV2, EcPV1, and EcPV6, justifying a new classification as Equus caballus PV 10 (EcPV10). All EcPV genes are conserved in EcPV10, and phylogenetic analysis indicates that EcPV10 is closely related to EcPV9 and EcPV2, genus Dyoiota 1. A preliminary EcPV10 genoprevalence study, carried out on 216 horses using Real Time PCRs, suggested a low incidence of this isolate (3.7%) compared to EcPVs of the same genus such as EcPV2 and EcPV9 in the same horse population. We hypothesize a transmission mechanism different from the one observed in the closely related EcPV9 and EcPV2 that particularly infect Thoroughbreds. This horse breed is usually submitted to natural mating, thus indicating a possible sexual diffusion. No differences were detected for breeds in terms of susceptibility to EcPV10. Further studies are needed to investigate the molecular mechanisms behind the host and EcPV10 infection to explain the reduced viral spread.
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16
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Jeon H, Bae J, Kim H, Kim MS. VPrimer: A Method of Designing and Updating Primer and Probe With High Variant Coverage for RNA Virus Detection. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2023; 20:775-784. [PMID: 34951850 DOI: 10.1109/tcbb.2021.3138145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Fatal infectious diseases caused by RNA viruses, such as COVID-19, have emerged around the world. RT-PCR is widely employed for virus detection, and its accuracy depends on the primers and probes since RT-PCR can detect a virus only when the primers and probes bind to the target gene of the virus. Most of primer design methods are for a single host and so require a great deal of effort to design for RNA virus detection, including homology tests among the host and all the viruses for the host using BLAST-like tools. Furthermore, they do not consider variant sequences, which are very common in viruses. In this study, we describe VPrimer, a method of designing high-quality primer-probe sets for RNA viruses. VPrimer can find primer-probe sets that cover more than 95% of the variants of a target virus but do not cover any sequences of other viruses or the host. With VPrimer, we found 381,698,582 primer-probe sets for 3,104 RNA viruses. Multiplex PCR assays using the top 2 primer-probe sets suggested by VPrimer usually cover 100% of variants. To address the rapid changes in viral genomes, VPrimer finds the best and up-to-date primer-probe sets incrementally against the most recently reported variants.
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17
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Pickering B, Lung O, Maguire F, Kruczkiewicz P, Kotwa JD, Buchanan T, Gagnier M, Guthrie JL, Jardine CM, Marchand-Austin A, Massé A, McClinchey H, Nirmalarajah K, Aftanas P, Blais-Savoie J, Chee HY, Chien E, Yim W, Banete A, Griffin BD, Yip L, Goolia M, Suderman M, Pinette M, Smith G, Sullivan D, Rudar J, Vernygora O, Adey E, Nebroski M, Goyette G, Finzi A, Laroche G, Ariana A, Vahkal B, Côté M, McGeer AJ, Nituch L, Mubareka S, Bowman J. Divergent SARS-CoV-2 variant emerges in white-tailed deer with deer-to-human transmission. Nat Microbiol 2022; 7:2011-2024. [PMID: 36357713 PMCID: PMC9712111 DOI: 10.1038/s41564-022-01268-9] [Citation(s) in RCA: 92] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 10/13/2022] [Indexed: 11/12/2022]
Abstract
Wildlife reservoirs of broad-host-range viruses have the potential to enable evolution of viral variants that can emerge to infect humans. In North America, there is phylogenomic evidence of continual transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from humans to white-tailed deer (Odocoileus virginianus) through unknown means, but no evidence of transmission from deer to humans. We carried out an observational surveillance study in Ontario, Canada during November and December 2021 (n = 300 deer) and identified a highly divergent lineage of SARS-CoV-2 in white-tailed deer (B.1.641). This lineage is one of the most divergent SARS-CoV-2 lineages identified so far, with 76 mutations (including 37 previously associated with non-human mammalian hosts). From a set of five complete and two partial deer-derived viral genomes we applied phylogenomic, recombination, selection and mutation spectrum analyses, which provided evidence for evolution and transmission in deer and a shared ancestry with mink-derived virus. Our analysis also revealed an epidemiologically linked human infection. Taken together, our findings provide evidence for sustained evolution of SARS-CoV-2 in white-tailed deer and of deer-to-human transmission.
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Affiliation(s)
- Bradley Pickering
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada.
- Department of Veterinary Microbiology and Preventative Medicine, College of Veterinary Medicine, Iowa State University, Ames, IA, USA.
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Manitoba, Canada.
| | - Oliver Lung
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Finlay Maguire
- Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada
- Department of Community Health & Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada
- Shared Hospital Laboratory, Toronto, Ontario, Canada
- Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Peter Kruczkiewicz
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | | | - Tore Buchanan
- Wildlife Research and Monitoring Section, Ontario Ministry of Natural Resources and Forestry, Peterborough, Ontario, Canada
| | - Marianne Gagnier
- Ministère des Forêts, de la Faune et des Parcs, Quebec City, Quebec, Canada
| | - Jennifer L Guthrie
- Public Health Ontario, Toronto, Ontario, Canada
- Department of Microbiology & Immunology, Western University, London, Toronto, Ontario, Canada
| | - Claire M Jardine
- Canadian Wildlife Health Cooperative, Ontario-Nunavut, Department of Pathobiology, University of Guelph, Guelph, Ontario, Canada
| | | | - Ariane Massé
- Ministère des Forêts, de la Faune et des Parcs, Quebec City, Quebec, Canada
| | - Heather McClinchey
- Public Health, Health Protection and Surveillance Policy and Programs Branch, Ontario Ministry of Health, Toronto, Ontario, Canada
| | | | | | | | | | - Emily Chien
- Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Winfield Yim
- Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Andra Banete
- Sunnybrook Research Institute, Toronto, Ontario, Canada
| | | | - Lily Yip
- Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Melissa Goolia
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | - Matthew Suderman
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | - Mathieu Pinette
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | - Greg Smith
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | - Daniel Sullivan
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Josip Rudar
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | - Oksana Vernygora
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | - Elizabeth Adey
- Wildlife Research and Monitoring Section, Ontario Ministry of Natural Resources and Forestry, Peterborough, Ontario, Canada
| | - Michelle Nebroski
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | | | - Andrés Finzi
- Centre de Recherche du CHUM, Montréal, Quebec, Canada
- Département de Microbiologie, Infectiologie et Immunologie, Université de Montréal, Montréal, Quebec, Canada
| | - Geneviève Laroche
- Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario, Canada
- Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, Ontario, Canada
- Centre for Infection, Immunity, and Inflammation, University of Ottawa, Ottawa, Ontario, Canada
| | - Ardeshir Ariana
- Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario, Canada
- Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, Ontario, Canada
- Centre for Infection, Immunity, and Inflammation, University of Ottawa, Ottawa, Ontario, Canada
| | - Brett Vahkal
- Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario, Canada
- Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, Ontario, Canada
- Centre for Infection, Immunity, and Inflammation, University of Ottawa, Ottawa, Ontario, Canada
| | - Marceline Côté
- Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario, Canada
- Ottawa Institute of Systems Biology, University of Ottawa, Ottawa, Ontario, Canada
- Centre for Infection, Immunity, and Inflammation, University of Ottawa, Ottawa, Ontario, Canada
| | - Allison J McGeer
- Sinai Health System, Toronto, Ontario, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Larissa Nituch
- Wildlife Research and Monitoring Section, Ontario Ministry of Natural Resources and Forestry, Peterborough, Ontario, Canada
| | - Samira Mubareka
- Sunnybrook Research Institute, Toronto, Ontario, Canada.
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.
| | - Jeff Bowman
- Wildlife Research and Monitoring Section, Ontario Ministry of Natural Resources and Forestry, Peterborough, Ontario, Canada.
- Environmental and Life Sciences Graduate Program, Trent University, Peterborough, Ontario, Canada.
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18
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Blenkinsop A, Monod M, van Sighem A, Pantazis N, Bezemer D, Op de Coul E, van de Laar T, Fraser C, Prins M, Reiss P, de Bree GJ, Ratmann O. Estimating the potential to prevent locally acquired HIV infections in a UNAIDS Fast-Track City, Amsterdam. eLife 2022; 11:e76487. [PMID: 35920649 PMCID: PMC9545569 DOI: 10.7554/elife.76487] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 08/01/2022] [Indexed: 11/13/2022] Open
Abstract
Background More than 300 cities including the city of Amsterdam in the Netherlands have joined the UNAIDS Fast-Track Cities initiative, committing to accelerate their HIV response and end the AIDS epidemic in cities by 2030. To support this commitment, we aimed to estimate the number and proportion of Amsterdam HIV infections that originated within the city, from Amsterdam residents. We also aimed to estimate the proportion of recent HIV infections during the 5-year period 2014-2018 in Amsterdam that remained undiagnosed. Methods We located diagnosed HIV infections in Amsterdam using postcode data (PC4) at time of registration in the ATHENA observational HIV cohort, and used HIV sequence data to reconstruct phylogeographically distinct, partially observed Amsterdam transmission chains. Individual-level infection times were estimated from biomarker data, and used to date the phylogenetically observed transmission chains as well as to estimate undiagnosed proportions among recent infections. A Bayesian Negative Binomial branching process model was used to estimate the number, size, and growth of the unobserved Amsterdam transmission chains from the partially observed phylogenetic data. Results Between 1 January 2014 and 1 May 2019, there were 846 HIV diagnoses in Amsterdam residents, of whom 516 (61%) were estimated to have been infected in 2014-2018. The rate of new Amsterdam diagnoses since 2014 (104 per 100,000) remained higher than the national rates excluding Amsterdam (24 per 100,000), and in this sense Amsterdam remained a HIV hotspot in the Netherlands. An estimated 14% [12-16%] of infections in Amsterdan MSM in 2014-2018 remained undiagnosed by 1 May 2019, and 41% [35-48%] in Amsterdam heterosexuals, with variation by region of birth. An estimated 67% [60-74%] of Amsterdam MSM infections in 2014-2018 had an Amsterdam resident as source, and 56% [41-70%] in Amsterdam heterosexuals, with heterogeneity by region of birth. Of the locally acquired infections, an estimated 43% [37-49%] were in foreign-born MSM, 41% [35-47%] in Dutch-born MSM, 10% [6-18%] in foreign-born heterosexuals, and 5% [2-9%] in Dutch-born heterosexuals. We estimate the majority of Amsterdam MSM infections in 2014-2018 originated in transmission chains that pre-existed by 2014. Conclusions This combined phylogenetic, epidemiologic, and modelling analysis in the UNAIDS Fast-Track City Amsterdam indicates that there remains considerable potential to prevent HIV infections among Amsterdam residents through city-level interventions. The burden of locally acquired infection remains concentrated in MSM, and both Dutch-born and foreign-born MSM would likely benefit most from intensified city-level interventions. Funding This study received funding as part of the H-TEAM initiative from Aidsfonds (project number P29701). The H-TEAM initiative is being supported by Aidsfonds (grant number: 2013169, P29701, P60803), Stichting Amsterdam Dinner Foundation, Bristol-Myers Squibb International Corp. (study number: AI424-541), Gilead Sciences Europe Ltd (grant number: PA-HIV-PREP-16-0024), Gilead Sciences (protocol numbers: CO-NL-276-4222, CO-US-276-1712, CO-NL-985-6195), and M.A.C AIDS Fund.
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Affiliation(s)
- Alexandra Blenkinsop
- Department of Mathematics, Imperial College LondonLondonUnited Kingdom
- Amsterdam Institute for Global Health and DevelopmentAmsterdamNetherlands
| | - Mélodie Monod
- Department of Mathematics, Imperial College LondonLondonUnited Kingdom
| | | | - Nikos Pantazis
- Department of Hygiene, Epidemiology and Medical Statistics, University of AthensAthensGreece
| | | | - Eline Op de Coul
- Center for Infectious Diseases Prevention and Control, National Institute for Public Health and the Environment (RIVM)BilthovenNetherlands
| | - Thijs van de Laar
- Department of Donor Medicine Research, SanquinAmsterdamNetherlands
- Department of Medical Microbiology, Onze Lieve Vrouwe GasthuisAmsterdamNetherlands
| | - Christophe Fraser
- Big Data Institute, Nuffield Department of Medicine, University of OxfordOxfordUnited Kingdom
| | | | - Peter Reiss
- Amsterdam Institute for Global Health and DevelopmentAmsterdamNetherlands
- Department of Global Health, Amsterdam University Medical CentersAmsterdamNetherlands
| | - Godelieve J de Bree
- Amsterdam Institute for Global Health and DevelopmentAmsterdamNetherlands
- Division of Infectious Diseases, Department of Internal Medicine, Amsterdam Infection and Immunity InstituteAmsterdamNetherlands
| | - Oliver Ratmann
- Department of Mathematics, Imperial College LondonLondonUnited Kingdom
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19
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Juma J, Fonseca V, Konongoi SL, van Heusden P, Roesel K, Sang R, Bett B, Christoffels A, de Oliveira T, Oyola SO. Genomic surveillance of Rift Valley fever virus: from sequencing to lineage assignment. BMC Genomics 2022; 23:520. [PMID: 35850574 PMCID: PMC9295512 DOI: 10.1186/s12864-022-08764-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 07/13/2022] [Indexed: 01/01/2023] Open
Abstract
Genetic evolution of Rift Valley fever virus (RVFV) in Africa has been shaped mainly by environmental changes such as abnormal rainfall patterns and climate change that has occurred over the last few decades. These gradual environmental changes are believed to have effected gene migration from macro (geographical) to micro (reassortment) levels. Presently, 15 lineages of RVFV have been identified to be circulating within the Sub-Saharan Africa. International trade in livestock and movement of mosquitoes are thought to be responsible for the outbreaks occurring outside endemic or enzootic regions. Virus spillover events contribute to outbreaks as was demonstrated by the largest epidemic of 1977 in Egypt. Genomic surveillance of the virus evolution is crucial in developing intervention strategies. Therefore, we have developed a computational tool for rapidly classifying and assigning lineages of the RVFV isolates. The computational method is presented both as a command line tool and a web application hosted at https://www.genomedetective.com/app/typingtool/rvfv/. Validation of the tool has been performed on a large dataset using glycoprotein gene (Gn) and whole genome sequences of the Large (L), Medium (M) and Small (S) segments of the RVFV retrieved from the National Center for Biotechnology Information (NCBI) GenBank database. Using the Gn nucleotide sequences, the RVFV typing tool was able to correctly classify all 234 RVFV sequences at species level with 100% specificity, sensitivity and accuracy. All the sequences in lineages A (n = 10), B (n = 1), C (n = 88), D (n = 1), E (n = 3), F (n = 2), G (n = 2), H (n = 105), I (n = 2), J (n = 1), K (n = 4), L (n = 8), M (n = 1), N (n = 5) and O (n = 1) were also correctly classified at phylogenetic level. Lineage assignment using whole RVFV genome sequences (L, M and S-segments) did not achieve 100% specificity, sensitivity and accuracy for all the sequences analyzed. We further tested our tool using genomic data that we generated by sequencing 5 samples collected following a recent RVF outbreak in Kenya. All the 5 samples were assigned lineage C by both the partial (Gn) and whole genome sequence classifiers. The tool is useful in tracing the origin of outbreaks and supporting surveillance efforts. Availability: https://github.com/ajodeh-juma/rvfvtyping
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Affiliation(s)
- John Juma
- International Livestock Research Institute (ILRI), Nairobi, Kenya.,South African MRC Bioinformatics Unit, South African National Bioinformatics Institute, Cape Town, South Africa
| | - Vagner Fonseca
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.,Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University Stellenbosch, Stellenbosch, South Africa.,Laboratorio de Genética Celular e Molecular, Instituto de Ciências Biologicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.,Organização Pan-Americana da Saúde/Organização Mundial da Saúde, Brasília, Distrito Federal, Brazil
| | - Samson L Konongoi
- International Livestock Research Institute (ILRI), Nairobi, Kenya.,Kenya Medical Research Institute (KEMRI), Nairobi, Kenya
| | - Peter van Heusden
- South African MRC Bioinformatics Unit, South African National Bioinformatics Institute, Cape Town, South Africa
| | - Kristina Roesel
- International Livestock Research Institute (ILRI), Nairobi, Kenya
| | - Rosemary Sang
- Kenya Medical Research Institute (KEMRI), Nairobi, Kenya
| | - Bernard Bett
- International Livestock Research Institute (ILRI), Nairobi, Kenya
| | - Alan Christoffels
- South African MRC Bioinformatics Unit, South African National Bioinformatics Institute, Cape Town, South Africa
| | - Tulio de Oliveira
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.,Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University Stellenbosch, Stellenbosch, South Africa.,Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa.,Department of Global Health, University of Washington, Seattle, WA, USA
| | - Samuel O Oyola
- International Livestock Research Institute (ILRI), Nairobi, Kenya.
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20
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Hufsky F, Abecasis A, Agudelo-Romero P, Bletsa M, Brown K, Claus C, Deinhardt-Emmer S, Deng L, Friedel CC, Gismondi MI, Kostaki EG, Kühnert D, Kulkarni-Kale U, Metzner KJ, Meyer IM, Miozzi L, Nishimura L, Paraskevopoulou S, Pérez-Cataluña A, Rahlff J, Thomson E, Tumescheit C, van der Hoek L, Van Espen L, Vandamme AM, Zaheri M, Zuckerman N, Marz M. Women in the European Virus Bioinformatics Center. Viruses 2022; 14:1522. [PMID: 35891501 PMCID: PMC9319252 DOI: 10.3390/v14071522] [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: 06/16/2022] [Revised: 07/05/2022] [Accepted: 07/07/2022] [Indexed: 02/01/2023] Open
Abstract
Viruses are the cause of a considerable burden to human, animal and plant health, while on the other hand playing an important role in regulating entire ecosystems. The power of new sequencing technologies combined with new tools for processing "Big Data" offers unprecedented opportunities to answer fundamental questions in virology. Virologists have an urgent need for virus-specific bioinformatics tools. These developments have led to the formation of the European Virus Bioinformatics Center, a network of experts in virology and bioinformatics who are joining forces to enable extensive exchange and collaboration between these research areas. The EVBC strives to provide talented researchers with a supportive environment free of gender bias, but the gender gap in science, especially in math-intensive fields such as computer science, persists. To bring more talented women into research and keep them there, we need to highlight role models to spark their interest, and we need to ensure that female scientists are not kept at lower levels but are given the opportunity to lead the field. Here we showcase the work of the EVBC and highlight the achievements of some outstanding women experts in virology and viral bioinformatics.
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Affiliation(s)
- Franziska Hufsky
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany
| | - Ana Abecasis
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Global Health and Tropical Medicine, Institute of Hygiene and Tropical Medicine, New University of Lisbon, 1349-008 Lisbon, Portugal
| | - Patricia Agudelo-Romero
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Wal-Yan Respiratory Research Centre, Telethon Kids Institute, University of Western Australia, Nedlands, WA 6009, Australia
| | - Magda Bletsa
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 115 27 Athens, Greece
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Katholieke Universiteit Leuven, B-3000 Leuven, Belgium
| | - Katherine Brown
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Division of Virology, Department of Pathology, University of Cambridge, Cambridge CB2 1TN, UK
| | - Claudia Claus
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Institute of Medical Microbiology and Virology, Medical Faculty, Leipzig University, 04103 Leipzig, Germany
| | - Stefanie Deinhardt-Emmer
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Institute of Medical Microbiology, Jena University Hospital, 07747 Jena, Germany
| | - Li Deng
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Institute of Virology, Helmholtz Centre Munich-German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Microbial Disease Prevention, School of Life Sciences, Technical University of Munich, 85354 Freising, Germany
| | - Caroline C. Friedel
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Institute of Informatics, Ludwig-Maximilians-Universität München, 80333 Munich, Germany
| | - María Inés Gismondi
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Institute of Agrobiotechnology and Molecular Biology (IABIMO), National Institute for Agriculture Technology (INTA), National Research Council (CONICET), Hurlingham B1686IGC, Argentina
- Department of Basic Sciences, National University of Luján, Luján B6702MZP, Argentina
| | - Evangelia Georgia Kostaki
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, 115 27 Athens, Greece
| | - Denise Kühnert
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Transmission, Infection, Diversification and Evolution Group, Max Planck Institute for the Science of Human History, 07745 Jena, Germany
| | - Urmila Kulkarni-Kale
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Bioinformatics Centre, Savitribai Phule Pune University, Pune 411007, India
| | - Karin J. Metzner
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, 8091 Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Irmtraud M. Meyer
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 10115 Berlin, Germany
- Institute of Chemistry and Biochemistry, Department of Biology, Chemistry and Pharmacy, Freie Universität Berlin, 14195 Berlin, Germany
- Faculty of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany
| | - Laura Miozzi
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Institute for Sustainable Plant Protection, National Research Council of Italy, 10135 Torino, Italy
| | - Luca Nishimura
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Department of Genetics, School of Life Science, The Graduate University for Advanced Studies (SOKENDAI), Mishima 411-8540, Japan
- Human Genetics Laboratory, National Institute of Genetics, Mishima 411-8540, Japan
| | - Sofia Paraskevopoulou
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Methods Development and Research Infrastructure, Bioinformatics and Systems Biology, Robert Koch Institute, 13353 Berlin, Germany
| | - Alba Pérez-Cataluña
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- VISAFELab, Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, 46980 Valencia, Spain
| | - Janina Rahlff
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Centre for Ecology and Evolution in Microbial Model Systems (EEMiS), Department of Biology and Environmental Science, Linneaus University, 391 82 Kalmar, Sweden
| | - Emma Thomson
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Queen Elizabeth University Hospital, NHS Greater Glasgow and Clyde, Glasgow G51 4TF, UK
- MRC-University of Glasgow Centre for Virus Research, Glasgow G61 1QH, UK
| | - Charlotte Tumescheit
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- School of Biological Sciences, Seoul National University, Seoul 08826, Korea
| | - Lia van der Hoek
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, Amsterdam UMC, University of Amsterdam, 1012 WX Amsterdam, The Netherlands
- Amsterdam Institute for Infection and Immunity, 1100 DD Amsterdam, The Netherlands
| | - Lore Van Espen
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Katholieke Universiteit Leuven, B-3000 Leuven, Belgium
| | - Anne-Mieke Vandamme
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Katholieke Universiteit Leuven, B-3000 Leuven, Belgium
- Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, 1349-008 Lisbon, Portugal
- Institute for the Future, Katholieke Universiteit Leuven, B-3000 Leuven, Belgium
| | - Maryam Zaheri
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Institute of Medical Virology, University of Zurich, 8057 Zurich, Switzerland
| | - Neta Zuckerman
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- Central Virology Laboratory, Public Health Services, Ministry of Health and Sheba Medical Center, Ramat Gan 52621, Israel
| | - Manja Marz
- European Virus Bioinformatics Center, 07743 Jena, Germany; (A.A.); (P.A.-R.); (M.B.); (K.B.); (C.C.); (S.D.-E.); (L.D.); (C.C.F.); (M.I.G.); (E.G.K.); (D.K.); (U.K.-K.); (K.J.M.); (I.M.M.); (L.M.); (L.N.); (S.P.); (A.P.-C.); (J.R.); (E.T.); (C.T.); (L.v.d.H.); (L.V.E.); (A.-M.V.); (M.Z.); (N.Z.)
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany
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Jeong H, Lee S, Ko J, Ko M, Seo HW. Identification of conserved regions from 230,163 SARS-CoV-2 genomes and their use in diagnostic PCR primer design. Genes Genomics 2022; 44:899-912. [PMID: 35653026 PMCID: PMC9160177 DOI: 10.1007/s13258-022-01264-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 05/03/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND As the rapidly evolving characteristic of SARS-CoV-2 could result in false negative diagnosis, the use of as much sequence data as possible is key to the identification of conserved viral sequences. However, multiple alignment of massive genome sequences is computationally intensive. OBJECTIVE To extract conserved sequences from SARS-CoV-2 genomes for the design of diagnostic PCR primers using a bioinformatics approach that can handle massive genomic sequences efficiently. METHODS A total of 230,163 full-length viral genomes were retrieved from the NCBI SARS-CoV-2 Resources and GISAID EpiCoV database. This number was reduced to 14.11% following removal of 5'-/3'-untranslated regions and sequence dereplication. Fast, reference-based, multiple sequence alignments identified conserved sequences and specific primer sets were designed against these regions using a conventional tool. Primer sets chosen among the candidates were evaluated by in silico PCR and RT-qPCR. RESULTS Out of 17 conserved sequences (totaling 4.3 kb), two primer sets targeting the nsp2 and ORF3a genes were picked that exhibited > 99.9% in silico amplification coverage against the original dataset (230,163 genomes) when a 5% mismatch between the primers and target was allowed. In addition, the primer sets successfully detected nine SARS-CoV-2 variant RNA samples (Alpha, Beta, Gamma, Delta, Epsilon, Zeta, Eta, Iota, and Kappa) in experimental RT-qPCR validations. CONCLUSION In addition to the RdRp, E, N, and S genes that are targeted commonly, our approach can be used to identify novel primer targets in SARS-CoV-2 and should be a priority strategy in the event of novel SARS-CoV-2 variants or other pandemic outbreaks.
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Affiliation(s)
- Haeyoung Jeong
- Infectious Disease Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, 34141, Republic of Korea.
| | - Siseok Lee
- NanoHelix Co., Ltd. 43-15, Daejeon, 34014, Republic of Korea
| | - Junsang Ko
- NanoHelix Co., Ltd. 43-15, Daejeon, 34014, Republic of Korea
| | - Minsu Ko
- NanoHelix Co., Ltd. 43-15, Daejeon, 34014, Republic of Korea
| | - Hwi Won Seo
- Infectious Disease Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, 34141, Republic of Korea.
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Differential patterns of postmigration HIV-1 infection acquisition among Portuguese immigrants of different geographical origins. AIDS 2022; 36:997-1005. [PMID: 35220350 DOI: 10.1097/qad.0000000000003203] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To investigate the dynamics of phylogenetic transmission clusters involving immigrants of Portuguese Speaking Countries living in Portugal. DESIGN/METHODS We included genomic sequences, sociodemographic and clinical data from 772 HIV migrants followed in Portugal between 2001 and 2017. To reconstruct HIV-1 transmission clusters, we applied phylogenetic inference from 16 454 patients: 772 migrants, 2973 Portuguese and 12 709 global controls linked to demographic and clinical data. Transmission clusters were defined using: clusters with SH greater than 90% (phylogenetic support), genetic distance less than 3.5% and clusters that included greater than 66% of patients from one specific geographic origin compared with the total of sequences within the cluster. Logistic regression was performed to assess factors associated with clustering. RESULTS Three hundred and six (39.6%) of migrants were included in transmission clusters. This proportion differed substantially by region of origin [Brazil 54% vs. Portuguese Speaking African Countries (PALOPs) 36%, P < 0.0001] and HIV-1 infecting subtype (B 52%, 43% subtype G and 32% CRF02_AG, P < 0.001). Belonging to a transmission cluster was independently associated with treatment-naive patients, CD4+ greater than 500, with recent calendar years of sampling, origin from PALOPs and with seroconversion. Among Brazilian migrants - mainly infected with subtype B - 40.6% were infected by Portuguese. Among migrants from PALOPs - mainly infected with subtypes G and CFR02_AG - the transmission occurred predominantly within the migrants' community (53 and 80%, respectively). CONCLUSION The acquisition of infection among immigrants living in Portugal differs according to the country of origin. These results can contribute to monitor the HIV epidemic and prevent new HIV infections among migrants.
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Pingarilho M, Pimentel V, Miranda MNS, Silva AR, Diniz A, Ascenção BB, Piñeiro C, Koch C, Rodrigues C, Caldas C, Morais C, Faria D, da Silva EG, Teófilo E, Monteiro F, Roxo F, Maltez F, Rodrigues F, Gaião G, Ramos H, Costa I, Germano I, Simões J, Oliveira J, Ferreira J, Poças J, da Cunha JS, Soares J, Henriques J, Mansinho K, Pedro L, Aleixo MJ, Gonçalves MJ, Manata MJ, Mouro M, Serrado M, Caixeiro M, Marques N, Costa O, Pacheco P, Proença P, Rodrigues P, Pinho R, Tavares R, de Abreu RC, Côrte-Real R, Serrão R, Castro RSE, Nunes S, Faria T, Baptista T, Martins MRO, Gomes P, Mendão L, Simões D, Abecasis A. HIV-1-Transmitted Drug Resistance and Transmission Clusters in Newly Diagnosed Patients in Portugal Between 2014 and 2019. Front Microbiol 2022; 13:823208. [PMID: 35558119 PMCID: PMC9090520 DOI: 10.3389/fmicb.2022.823208] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 03/21/2022] [Indexed: 11/13/2022] Open
Abstract
Objective To describe and analyze transmitted drug resistance (TDR) between 2014 and 2019 in newly infected patients with HIV-1 in Portugal and to characterize its transmission networks. Methods Clinical, socioepidemiological, and risk behavior data were collected from 820 newly diagnosed patients in Portugal between September 2014 and December 2019. The sequences obtained from drug resistance testing were used for subtyping, TDR determination, and transmission cluster (TC) analyses. Results In Portugal, the overall prevalence of TDR between 2014 and 2019 was 11.0%. TDR presented a decreasing trend from 16.7% in 2014 to 9.2% in 2016 (p for-trend = 0.114). Multivariate analysis indicated that TDR was significantly associated with transmission route (MSM presented a lower probability of presenting TDR when compared to heterosexual contact) and with subtype (subtype C presented significantly more TDR when compared to subtype B). TC analysis corroborated that the heterosexual risk group presented a higher proportion of TDR in TCs when compared to MSMs. Among subtype A1, TDR reached 16.6% in heterosexuals, followed by 14.2% in patients infected with subtype B and 9.4% in patients infected with subtype G. Conclusion Our molecular epidemiology approach indicates that the HIV-1 epidemic in Portugal is changing among risk group populations, with heterosexuals showing increasing levels of HIV-1 transmission and TDR. Prevention measures for this subpopulation should be reinforced.
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Affiliation(s)
- Marta Pingarilho
- Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical (IHMT), Universidade Nova de Lisboa (UNL), Lisbon, Portugal
| | - Victor Pimentel
- Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical (IHMT), Universidade Nova de Lisboa (UNL), Lisbon, Portugal
| | - Mafalda N S Miranda
- Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical (IHMT), Universidade Nova de Lisboa (UNL), Lisbon, Portugal
| | - Ana Rita Silva
- Serviço de Infeciologia, Hospital Beatriz Ângelo, Loures, Portugal
| | - António Diniz
- Unidade de Imunodeficiência, Centro Hospitalar Universitário Lisboa Norte - HPV, Lisbon, Portugal
| | | | - Carmela Piñeiro
- Serviço de Doenças Infeciosas, Centro Hospitalar Universitário de São João, Porto, Portugal
| | - Carmo Koch
- Centro de Biologia Molecular, Serviço de Imunohemoterapia do Centro Hospitalar Universitário de São João, Porto, Portugal
| | - Catarina Rodrigues
- Serviço de Medicina, Hospital de São José, Centro Hospitalar Universitário de Lisboa Central, Lisbon, Portugal
| | - Cátia Caldas
- Serviço de Doenças Infeciosas, Centro Hospitalar Universitário de São João, Porto, Portugal
| | - Célia Morais
- Serviço de Patologia Clínica, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Domitília Faria
- Serviço de Medicina, Hospital de Portimão, Centro Hospitalar Universitário do Algarve, Portimão, Portugal
| | | | - Eugénio Teófilo
- Serviço de Medicina, Hospital de Santo António dos Capuchos, Centro Hospitalar Universitário de Lisboa Central, Lisbon, Portugal
| | - Fátima Monteiro
- Centro de Biologia Molecular, Serviço de Imunohemoterapia do Centro Hospitalar Universitário de São João, Porto, Portugal
| | - Fausto Roxo
- Hospital de Dia de Doenças Infeciosas, Hospital Distrital de Santarém, Santarém, Portugal
| | - Fernando Maltez
- Serviço de Doenças Infeciosas, Hospital de Curry Cabral, Centro Hospitalar Universitário de Lisboa Central, Lisbon, Portugal
| | - Fernando Rodrigues
- Serviço de Patologia Clínica, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Guilhermina Gaião
- Serviço de Patologia Clínica, Hospital de Santa Maria, Centro Hospitalar Universitário de Lisboa Norte, Lisbon, Portugal
| | - Helena Ramos
- Serviço de Patologia Clínica, Centro Hospitalar do Porto, Porto, Portugal
| | - Inês Costa
- Laboratório de Biologia Molecular (LMCBM, SPC, CHLO-HEM), Lisbon, Portugal
| | - Isabel Germano
- Serviço de Medicina, Hospital de São José, Centro Hospitalar Universitário de Lisboa Central, Lisbon, Portugal
| | - Joana Simões
- Serviço de Medicina, Hospital de São José, Centro Hospitalar Universitário de Lisboa Central, Lisbon, Portugal
| | - Joaquim Oliveira
- Serviço de Doenças, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - José Ferreira
- Serviço de Medicina, Hospital de Faro, Centro Hospitalar Universitário do Algarve, Faro, Portugal
| | - José Poças
- Serviço de Infeciologia, Centro Hospitalar de Setúbal, Setúbal, Portugal
| | | | - Jorge Soares
- Serviço de Doenças Infeciosas, Centro Hospitalar Universitário de São João, Porto, Portugal
| | - Júlia Henriques
- Laboratório de Biologia Molecular (LMCBM, SPC, CHLO-HEM), Lisbon, Portugal
| | - Kamal Mansinho
- Serviço de Doenças Infeciosas, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Lisbon, Portugal
| | - Liliana Pedro
- Serviço de Medicina, Hospital de Portimão, Centro Hospitalar Universitário do Algarve, Portimão, Portugal
| | | | | | - Maria José Manata
- Serviço de Doenças Infeciosas, Hospital de Curry Cabral, Centro Hospitalar Universitário de Lisboa Central, Lisbon, Portugal
| | - Margarida Mouro
- Serviço de Infeciologia, Hospital de Aveiro, Centro Hospitalar Baixo Vouga, Aveiro, Portugal
| | - Margarida Serrado
- Unidade de Imunodeficiência, Centro Hospitalar Universitário Lisboa Norte - HPV, Lisbon, Portugal
| | - Micaela Caixeiro
- Serviço de Infeciologia, Hospital Professor Doutor Fernando da Fonseca, Amadora, Portugal
| | - Nuno Marques
- Serviço de Infeciologia, Hospital Garcia da Orta, Almada, Portugal
| | - Olga Costa
- Serviço de Patologia Clínica, Biologia Molecular, Centro Hospitalar Universitário de Lisboa Central, Lisbon, Portugal
| | - Patrícia Pacheco
- Serviço de Infeciologia, Hospital Professor Doutor Fernando da Fonseca, Amadora, Portugal
| | - Paula Proença
- Serviço de Infeciologia, Hospital de Faro, Centro Hospitalar Universitário do Algarve, Faro, Portugal
| | - Paulo Rodrigues
- Serviço de Infeciologia, Hospital Beatriz Ângelo, Loures, Portugal
| | - Raquel Pinho
- Serviço de Medicina, Hospital de Portimão, Centro Hospitalar Universitário do Algarve, Portimão, Portugal
| | - Raquel Tavares
- Serviço de Infeciologia, Hospital Beatriz Ângelo, Loures, Portugal
| | - Ricardo Correia de Abreu
- Serviço de Infeciologia, Unidade de Local de Saúde de Matosinhos, Hospital Pedro Hispano, Matosinhos, Portugal
| | - Rita Côrte-Real
- Serviço de Patologia Clínica, Biologia Molecular, Centro Hospitalar Universitário de Lisboa Central, Lisbon, Portugal
| | - Rosário Serrão
- Serviço de Doenças Infeciosas, Centro Hospitalar Universitário de São João, Porto, Portugal
| | | | - Sofia Nunes
- Serviço de Infeciologia, Hospital de Aveiro, Centro Hospitalar Baixo Vouga, Aveiro, Portugal
| | - Telo Faria
- Unidade Local de Saúde do Baixo Alentejo, Hospital José Joaquim Fernandes, Beja, Portugal
| | - Teresa Baptista
- Serviço de Doenças Infeciosas, Hospital de Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Lisbon, Portugal
| | - Maria Rosário O Martins
- Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical (IHMT), Universidade Nova de Lisboa (UNL), Lisbon, Portugal
| | - Perpétua Gomes
- Laboratório de Biologia Molecular (LMCBM, SPC, CHLO-HEM), Lisbon, Portugal.,Centro de Investigação Interdisciplinar Egas Moniz (CiiEM), Instituto Universitário Egas Moniz, Costa da Caparica, Portugal
| | - Luís Mendão
- Grupo de Ativistas em Tratamentos (GAT), Lisbon, Portugal
| | - Daniel Simões
- Grupo de Ativistas em Tratamentos (GAT), Lisbon, Portugal
| | - Ana Abecasis
- Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical (IHMT), Universidade Nova de Lisboa (UNL), Lisbon, Portugal
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Zhang Y, Zhang Q, Zhou J, Zou Q. A survey on the algorithm and development of multiple sequence alignment. Brief Bioinform 2022; 23:6546258. [PMID: 35272347 DOI: 10.1093/bib/bbac069] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 01/30/2022] [Accepted: 02/09/2022] [Indexed: 12/21/2022] Open
Abstract
Multiple sequence alignment (MSA) is an essential cornerstone in bioinformatics, which can reveal the potential information in biological sequences, such as function, evolution and structure. MSA is widely used in many bioinformatics scenarios, such as phylogenetic analysis, protein analysis and genomic analysis. However, MSA faces new challenges with the gradual increase in sequence scale and the increasing demand for alignment accuracy. Therefore, developing an efficient and accurate strategy for MSA has become one of the research hotspots in bioinformatics. In this work, we mainly summarize the algorithms for MSA and its applications in bioinformatics. To provide a structured and clear perspective, we systematically introduce MSA's knowledge, including background, database, metric and benchmark. Besides, we list the most common applications of MSA in the field of bioinformatics, including database searching, phylogenetic analysis, genomic analysis, metagenomic analysis and protein analysis. Furthermore, we categorize and analyze classical and state-of-the-art algorithms, divided into progressive alignment, iterative algorithm, heuristics, machine learning and divide-and-conquer. Moreover, we also discuss the challenges and opportunities of MSA in bioinformatics. Our work provides a comprehensive survey of MSA applications and their relevant algorithms. It could bring valuable insights for researchers to contribute their knowledge to MSA and relevant studies.
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Affiliation(s)
- Yongqing Zhang
- School of Computer Science, Chengdu University of Information Technology, 610225, Chengdu, China.,School of Computer Science and Engineering, University of Electronic Science and Technology of China, 611731, Chengdu, China
| | - Qiang Zhang
- School of Computer Science, Chengdu University of Information Technology, 610225, Chengdu, China
| | - Jiliu Zhou
- School of Computer Science, Chengdu University of Information Technology, 610225, Chengdu, China
| | - Quan Zou
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, 610054, Chengdu, China
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Abstract
Although lessons have been learned from previous severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) outbreaks, the rapid evolution of the viruses means that future outbreaks of a much larger scale are possible, as shown by the current coronavirus disease 2019 (COVID-19) outbreak. Therefore, it is necessary to better understand the evolution of coronaviruses as well as viruses in general. This study reports a comparative analysis of the amino acid usage within several key viral families and genera that are prone to triggering outbreaks, including coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2], SARS-CoV, MERS-CoV, human coronavirus-HKU1 [HCoV-HKU1], HCoV-OC43, HCoV-NL63, and HCoV-229E), influenza A (H1N1 and H3N2), flavivirus (dengue virus serotypes 1 to 4 and Zika) and ebolavirus (Zaire, Sudan, and Bundibugyo ebolavirus). Our analysis reveals that the distribution of amino acid usage in the viral genome is constrained to follow a linear order, and the distribution remains closely related to the viral species within the family or genus. This constraint can be adapted to predict viral mutations and future variants of concern. By studying previous SARS and MERS outbreaks, we have adapted this naturally occurring pattern to determine that although pangolin plays a role in the outbreak of COVID-19, it may not be the sole agent as an intermediate animal. In addition to this study, our findings contribute to the understanding of viral mutations for subsequent development of vaccines and toward developing a model to determine the source of the outbreak. IMPORTANCE This study reports a comparative analysis of amino acid usage within several key viral genera that are prone to triggering outbreaks. Interestingly, there is evidence that the amino acid usage within the viral genomes is not random but in a linear order.
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26
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Bezemer D, Blenkinsop A, Hall M, van Sighem A, Cornelissen M, Wessels E, van Kampen J, van de Laar T, Reiss P, Fraser C, Ratmann O. Many but small HIV-1 non-B transmission chains in the Netherlands. AIDS 2022; 36:83-94. [PMID: 34618753 PMCID: PMC8655833 DOI: 10.1097/qad.0000000000003074] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 08/26/2021] [Accepted: 09/13/2021] [Indexed: 11/26/2022]
Abstract
OBJECTIVE The aim of this study was to investigate introductions and spread of different HIV-1 subtypes in the Netherlands. DESIGN We identified distinct HIV-1 transmission chains in the Netherlands within the global epidemic context through viral phylogenetic analysis of partial HIV-1 polymerase sequences from individuals enrolled in the ATHENA national HIV cohort of all persons in care since 1996, and publicly available international background sequences. METHODS Viral lineages circulating in the Netherlands were identified through maximum parsimony phylogeographic analysis. The proportion of HIV-1 infections acquired in-country among heterosexuals and MSM was estimated from phylogenetically observed, national transmission chains using a branching process model that accounts for incomplete sampling. RESULTS As of 1 January 2019, 2589 (24%) of 10 971 (41%) HIV-1 sequenced individuals in ATHENA had non-B subtypes (A1, C, D, F, G) or circulating recombinant forms (CRF01AE, CRF02AG, CRF06-cpx). The 1588 heterosexuals were in 1224, and 536 MSM in 270 phylogenetically observed transmission chains. After adjustments for incomplete sampling, most heterosexual (75%) and MSM (76%) transmission chains were estimated to include only the individual introducing the virus (size = 1). Onward transmission occurred mostly in chains size 2-5 amongst heterosexuals (62%) and in chains size at least 10 amongst MSM (64%). Considering some chains originated in-country from other risk-groups, 40% (95% confidence interval: 36-44) of non-B-infected heterosexuals and 62% (95% confidence interval: 49-73) of MSM-acquired infection in-country. CONCLUSION Although most HIV-1 non-B introductions showed no or very little onward transmission, a considerable proportion of non-B infections amongst both heterosexuals and MSM in the Netherlands have been acquired in-country.
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Affiliation(s)
| | - Alexandra Blenkinsop
- Department of Mathematics, Imperial College London, London
- Department of Global Health, Amsterdam University Medical Centers, University of Amsterdam and Amsterdam Institute for Global Health and Development, Amsterdam, The Netherlands
| | - Matthew Hall
- Oxford Big Data Institute, University of Oxford, Oxford, UK
| | | | - Marion Cornelissen
- Laboratory of Clinical Virology, Department of Medical Microbiology, Academic Medical Center of the University of Amsterdam, Amsterdam
| | - Els Wessels
- Department of Medical Microbiology, Leiden University Medical Center, Leiden
| | | | - Thijs van de Laar
- Department of Donor Medicine Research, laboratory of Blood-borne Infections, Sanquin Research
- Department of Medical Microbiology, Onze Lieve Vrouwe Gasthuis, Amsterdam, The Netherlands
| | - Peter Reiss
- Stichting HIV Monitoring, Amsterdam, The Netherlands
- Department of Global Health, Amsterdam University Medical Centers, University of Amsterdam and Amsterdam Institute for Global Health and Development, Amsterdam, The Netherlands
| | | | - Oliver Ratmann
- Department of Mathematics, Imperial College London, London
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27
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Seabra SG, Libin PJK, Theys K, Zhukova A, Potter BI, Nebenzahl-Guimaraes H, Gorbalenya AE, Sidorov IA, Pimentel V, Pingarilho M, de Vasconcelos ATR, Dellicour S, Khouri R, Gascuel O, Vandamme AM, Baele G, Cuypers L, Abecasis AB. OUP accepted manuscript. Virus Evol 2022; 8:veac029. [PMID: 35478717 PMCID: PMC9035895 DOI: 10.1093/ve/veac029] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Revised: 01/24/2022] [Accepted: 03/28/2022] [Indexed: 11/13/2022] Open
Abstract
The Zika virus (ZIKV) disease caused a public health emergency of international concern that started in February 2016. The overall number of ZIKV-related cases increased until November 2016, after which it declined sharply. While the evaluation of the potential risk and impact of future arbovirus epidemics remains challenging, intensified surveillance efforts along with a scale-up of ZIKV whole-genome sequencing provide an opportunity to understand the patterns of genetic diversity, evolution, and spread of ZIKV. However, a classification system that reflects the true extent of ZIKV genetic variation is lacking. Our objective was to characterize ZIKV genetic diversity and phylodynamics, identify genomic footprints of differentiation patterns, and propose a dynamic classification system that reflects its divergence levels. We analysed a curated dataset of 762 publicly available sequences spanning the full-length coding region of ZIKV from across its geographical span and collected between 1947 and 2021. The definition of genetic groups was based on comprehensive evolutionary dynamics analyses, which included recombination and phylogenetic analyses, within- and between-group pairwise genetic distances comparison, detection of selective pressure, and clustering analyses. Evidence for potential recombination events was detected in a few sequences. However, we argue that these events are likely due to sequencing errors as proposed in previous studies. There was evidence of strong purifying selection, widespread across the genome, as also detected for other arboviruses. A total of 50 sites showed evidence of positive selection, and for a few of these sites, there was amino acid (AA) differentiation between genetic clusters. Two main genetic clusters were defined, ZA and ZB, which correspond to the already characterized ‘African’ and ‘Asian’ genotypes, respectively. Within ZB, two subgroups, ZB.1 and ZB.2, represent the Asiatic and the American (and Oceania) lineages, respectively. ZB.1 is further subdivided into ZB.1.0 (a basal Malaysia sequence sampled in the 1960s and a recent Indian sequence), ZB.1.1 (South-Eastern Asia, Southern Asia, and Micronesia sequences), and ZB.1.2 (very similar sequences from the outbreak in Singapore). ZB.2 is subdivided into ZB.2.0 (basal American sequences and the sequences from French Polynesia, the putative origin of South America introduction), ZB.2.1 (Central America), and ZB.2.2 (Caribbean and North America). This classification system does not use geographical references and is flexible to accommodate potential future lineages. It will be a helpful tool for studies that involve analyses of ZIKV genomic variation and its association with pathogenicity and serve as a starting point for the public health surveillance and response to on-going and future epidemics and to outbreaks that lead to the emergence of new variants.
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Affiliation(s)
| | | | | | - Anna Zhukova
- Institut Pasteur, Université Paris Cité, Unité Bioinformatique Evolutive, 25-28 rue du Dr Roux, Paris F-75015, France
- Institut Pasteur, Université Paris Cité, Bioinformatics and Biostatistics Hub, 25-28 rue du Dr Roux, Paris F-75015, France
| | | | - Hanna Nebenzahl-Guimaraes
- Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical (IHMT), Universidade Nova de Lisboa (UNL), Rua da Junqueira 100, Lisboa 1349-008, Portugal
| | | | | | - Victor Pimentel
- Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical (IHMT), Universidade Nova de Lisboa (UNL), Rua da Junqueira 100, Lisboa 1349-008, Portugal
| | - Marta Pingarilho
- Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical (IHMT), Universidade Nova de Lisboa (UNL), Rua da Junqueira 100, Lisboa 1349-008, Portugal
| | | | - Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, Laboratory of Clinical and Epidemiological Virology, KU Leuven, Herestraat 49 - box 1030, Leuven 3000, Belgium
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP 264/3, 50 av. F.D. Roosevelt, Bruxelles B-1050, Belgium
| | | | | | | | | | - Lize Cuypers
- Department of Laboratory Medicine, University Hospitals Leuven, Herestraat 49, Leuven 3000, Belgium
| | - Ana B Abecasis
- Global Health and Tropical Medicine (GHTM), Instituto de Higiene e Medicina Tropical (IHMT), Universidade Nova de Lisboa (UNL), Rua da Junqueira 100, Lisboa 1349-008, Portugal
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28
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Brandt D, Simunovic M, Busche T, Haak M, Belmann P, Jünemann S, Schulz T, Klages LJ, Vinke S, Beckstette M, Pohl E, Scherer C, Sczyrba A, Kalinowski J. Multiple Occurrences of a 168-Nucleotide Deletion in SARS-CoV-2 ORF8, Unnoticed by Standard Amplicon Sequencing and Variant Calling Pipelines. Viruses 2021; 13:1870. [PMID: 34578452 PMCID: PMC8518987 DOI: 10.3390/v13091870] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 09/14/2021] [Accepted: 09/15/2021] [Indexed: 12/20/2022] Open
Abstract
Genomic surveillance of the SARS-CoV-2 pandemic is crucial and mainly achieved by amplicon sequencing protocols. Overlapping tiled-amplicons are generated to establish contiguous SARS-CoV-2 genome sequences, which enable the precise resolution of infection chains and outbreaks. We investigated a SARS-CoV-2 outbreak in a local hospital and used nanopore sequencing with a modified ARTIC protocol employing 1200 bp long amplicons. We detected a long deletion of 168 nucleotides in the ORF8 gene in 76 samples from the hospital outbreak. This deletion is difficult to identify with the classical amplicon sequencing procedures since it removes two amplicon primer-binding sites. We analyzed public SARS-CoV-2 sequences and sequencing read data from ENA and identified the same deletion in over 100 genomes belonging to different lineages of SARS-CoV-2, pointing to a mutation hotspot or to positive selection. In almost all cases, the deletion was not represented in the virus genome sequence after consensus building. Additionally, further database searches point to other deletions in the ORF8 coding region that have never been reported by the standard data analysis pipelines. These findings and the fact that ORF8 is especially prone to deletions, make a clear case for the urgent necessity of public availability of the raw data for this and other large deletions that might change the physiology of the virus towards endemism.
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Affiliation(s)
- David Brandt
- Center for Biotechnology (CeBiTec), Bielefeld University, 33615 Bielefeld, Germany; (D.B.); (M.S.); (T.B.); (M.H.); (P.B.); (S.J.); (T.S.); (L.J.K.); (S.V.); (M.B.); (A.S.)
| | - Marina Simunovic
- Center for Biotechnology (CeBiTec), Bielefeld University, 33615 Bielefeld, Germany; (D.B.); (M.S.); (T.B.); (M.H.); (P.B.); (S.J.); (T.S.); (L.J.K.); (S.V.); (M.B.); (A.S.)
| | - Tobias Busche
- Center for Biotechnology (CeBiTec), Bielefeld University, 33615 Bielefeld, Germany; (D.B.); (M.S.); (T.B.); (M.H.); (P.B.); (S.J.); (T.S.); (L.J.K.); (S.V.); (M.B.); (A.S.)
| | - Markus Haak
- Center for Biotechnology (CeBiTec), Bielefeld University, 33615 Bielefeld, Germany; (D.B.); (M.S.); (T.B.); (M.H.); (P.B.); (S.J.); (T.S.); (L.J.K.); (S.V.); (M.B.); (A.S.)
| | - Peter Belmann
- Center for Biotechnology (CeBiTec), Bielefeld University, 33615 Bielefeld, Germany; (D.B.); (M.S.); (T.B.); (M.H.); (P.B.); (S.J.); (T.S.); (L.J.K.); (S.V.); (M.B.); (A.S.)
- Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany
| | - Sebastian Jünemann
- Center for Biotechnology (CeBiTec), Bielefeld University, 33615 Bielefeld, Germany; (D.B.); (M.S.); (T.B.); (M.H.); (P.B.); (S.J.); (T.S.); (L.J.K.); (S.V.); (M.B.); (A.S.)
- Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany
| | - Tizian Schulz
- Center for Biotechnology (CeBiTec), Bielefeld University, 33615 Bielefeld, Germany; (D.B.); (M.S.); (T.B.); (M.H.); (P.B.); (S.J.); (T.S.); (L.J.K.); (S.V.); (M.B.); (A.S.)
- Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany
| | - Levin Joe Klages
- Center for Biotechnology (CeBiTec), Bielefeld University, 33615 Bielefeld, Germany; (D.B.); (M.S.); (T.B.); (M.H.); (P.B.); (S.J.); (T.S.); (L.J.K.); (S.V.); (M.B.); (A.S.)
| | - Svenja Vinke
- Center for Biotechnology (CeBiTec), Bielefeld University, 33615 Bielefeld, Germany; (D.B.); (M.S.); (T.B.); (M.H.); (P.B.); (S.J.); (T.S.); (L.J.K.); (S.V.); (M.B.); (A.S.)
| | - Michael Beckstette
- Center for Biotechnology (CeBiTec), Bielefeld University, 33615 Bielefeld, Germany; (D.B.); (M.S.); (T.B.); (M.H.); (P.B.); (S.J.); (T.S.); (L.J.K.); (S.V.); (M.B.); (A.S.)
- Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany
| | - Ehmke Pohl
- Department of Biosciences, Durham University, Durham DH1 3LE, UK;
| | - Christiane Scherer
- Evangelisches Klinikum Bethel, Institut für Laboratoriumsmedizin, Mikrobiologie und Hygiene, 33617 Bielefeld, Germany;
- Universitätsklinikum OWL der Universität Bielefeld, 33615 Bielefeld, Germany
| | - Alexander Sczyrba
- Center for Biotechnology (CeBiTec), Bielefeld University, 33615 Bielefeld, Germany; (D.B.); (M.S.); (T.B.); (M.H.); (P.B.); (S.J.); (T.S.); (L.J.K.); (S.V.); (M.B.); (A.S.)
- Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany
| | - Jörn Kalinowski
- Center for Biotechnology (CeBiTec), Bielefeld University, 33615 Bielefeld, Germany; (D.B.); (M.S.); (T.B.); (M.H.); (P.B.); (S.J.); (T.S.); (L.J.K.); (S.V.); (M.B.); (A.S.)
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Seatla KK, Maruapula D, Choga WT, Morerinyane O, Lockman S, Novitsky V, Kasvosve I, Moyo S, Gaseitsiwe S. Limited HIV-1 Subtype C nef 3'PPT Variation in Combination Antiretroviral Therapy Naïve and Experienced People Living with HIV in Botswana. Pathogens 2021; 10:1027. [PMID: 34451492 PMCID: PMC8400509 DOI: 10.3390/pathogens10081027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 08/05/2021] [Accepted: 08/11/2021] [Indexed: 11/23/2022] Open
Abstract
Dolutegravir (DTG) is a potent anti-HIV drug that is used to treat HIV globally. There have been reports of mutations in the HIV-1 3'-polypurine tract (3'PPT) of the nef gene, contributing to DTG failure; however, there are limited 'real-world' data on this. In addition, there is a knowledge gap on the variability of 3'PPT residues in patients receiving combination antiretroviral therapy (cART) with and without viral load (VL) suppression. HIV-1 subtype C (HIV-1C) whole-genome sequences from cART naïve and experienced individuals were generated using next-generation sequencing. The nef gene sequences were trimmed from the generated whole-genome sequences using standard bioinformatics tools. In addition, we generated separate integrase and nef gene sequences by Sanger sequencing of plasma samples from individuals with virologic failure (VF) while on a DTG/raltegravir (RAL)-based cART. Analysis of 3'PPT residues was performed, and comparison of proportions computed using Pearson's chi-square test with p-values < 0.05 was considered statistically significant. A total of 6009 HIV-1C full genome sequences were generated and had a median log10 HIV-1 VL (Q1, Q3) copies/mL of 1.60 (1.60, 2.60). A total of 12 matching integrase and nef gene sequences from therapy-experienced participants failing DTG/ RAL-based cART were generated. HIV-1C 3'PPT nef gene sequences from therapy-experienced patients failing DTG cART (n = 12), cART naïve individuals (n = 1263), and individuals on cART with and without virological suppression (n = 4696) all had a highly conserved 3'PPT motif with no statistically significant differences identified. Our study confirms the high conservation of the HIV-1 nef gene 3'PPT motif in 'real-world' patients and showed no differences in the motif according to VL suppression or INSTI-based cART failure. Future studies should explore other HIV-1 regions outside of the pol gene for associations with DTG failure.
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Affiliation(s)
- Kaelo K. Seatla
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana; (D.M.); (W.T.C.); (O.M.); (S.L.); (S.M.); (S.G.)
- Faculty of Health Sciences, School of Allied Health Professions, University of Botswana, Gaborone, Botswana;
| | - Dorcas Maruapula
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana; (D.M.); (W.T.C.); (O.M.); (S.L.); (S.M.); (S.G.)
- Faculty of Health Sciences, School of Allied Health Professions, University of Botswana, Gaborone, Botswana;
| | - Wonderful T. Choga
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana; (D.M.); (W.T.C.); (O.M.); (S.L.); (S.M.); (S.G.)
- Division of Human Genetics, Department of Pathology, Faculty of Health Sciences, University of Cape Town, Cape Town 7925, South Africa
| | - Olorato Morerinyane
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana; (D.M.); (W.T.C.); (O.M.); (S.L.); (S.M.); (S.G.)
| | - Shahin Lockman
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana; (D.M.); (W.T.C.); (O.M.); (S.L.); (S.M.); (S.G.)
- Department of Immunology & Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Vladimir Novitsky
- The Warren Alpert Medical School of Brown University, Providence, RI 12321, USA;
- Division of Infectious Diseases, The Miriam Hospital, Providence, RI 23324, USA
| | - Ishmael Kasvosve
- Faculty of Health Sciences, School of Allied Health Professions, University of Botswana, Gaborone, Botswana;
| | - Sikhulile Moyo
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana; (D.M.); (W.T.C.); (O.M.); (S.L.); (S.M.); (S.G.)
- Department of Immunology & Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Simani Gaseitsiwe
- Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana; (D.M.); (W.T.C.); (O.M.); (S.L.); (S.M.); (S.G.)
- Department of Immunology & Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
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Tasakis RN, Samaras G, Jamison A, Lee M, Paulus A, Whitehouse G, Verkoczy L, Papavasiliou FN, Diaz M. SARS-CoV-2 variant evolution in the United States: High accumulation of viral mutations over time likely through serial Founder Events and mutational bursts. PLoS One 2021; 16:e0255169. [PMID: 34297786 PMCID: PMC8301627 DOI: 10.1371/journal.pone.0255169] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 07/11/2021] [Indexed: 12/13/2022] Open
Abstract
Since the first case of COVID-19 in December 2019 in Wuhan, China, SARS-CoV-2 has spread worldwide and within a year and a half has caused 3.56 million deaths globally. With dramatically increasing infection numbers, and the arrival of new variants with increased infectivity, tracking the evolution of its genome is crucial for effectively controlling the pandemic and informing vaccine platform development. Our study explores evolution of SARS-CoV-2 in a representative cohort of sequences covering the entire genome in the United States, through all of 2020 and early 2021. Strikingly, we detected many accumulating Single Nucleotide Variations (SNVs) encoding amino acid changes in the SARS-CoV-2 genome, with a pattern indicative of RNA editing enzymes as major mutators of SARS-CoV-2 genomes. We report three major variants through October of 2020. These revealed 14 key mutations that were found in various combinations among 14 distinct predominant signatures. These signatures likely represent evolutionary lineages of SARS-CoV-2 in the U.S. and reveal clues to its evolution such as a mutational burst in the summer of 2020 likely leading to a homegrown new variant, and a trend towards higher mutational load among viral isolates, but with occasional mutation loss. The last quartile of 2020 revealed a concerning accumulation of mostly novel low frequency replacement mutations in the Spike protein, and a hypermutable glutamine residue near the putative furin cleavage site. Finally, end of the year data and 2021 revealed the gradual increase to prevalence of known variants of concern, particularly B.1.1.7, that have acquired additional Spike mutations. Overall, our results suggest that predominant viral genomes are dynamically evolving over time, with periods of mutational bursts and unabated mutation accumulation. This high level of existing variation, even at low frequencies and especially in the Spike-encoding region may become problematic when super-spreader events, akin to serial Founder Events in evolution, drive these rare mutations to prominence.
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Affiliation(s)
- Rafail Nikolaos Tasakis
- Division of Immune Diversity, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Biosciences, University of Heidelberg, Heidelberg, Germany
| | - Georgios Samaras
- Division of Immune Diversity, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Program of Translational Medical Research, Medical Faculty Mannheim, University of Heidelberg, Heidelberg, Germany
| | - Anna Jamison
- The Nightingale-Bamford School, New York, NY, United States of America
| | - Michelle Lee
- Cornell University, Ithaca, NY, United States of America
| | - Alexandra Paulus
- The Nightingale-Bamford School, New York, NY, United States of America
| | | | - Laurent Verkoczy
- San Diego Biomedical Research Institute (SDBRI), San Diego, CA, United States of America
| | - F. Nina Papavasiliou
- Division of Immune Diversity, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Marilyn Diaz
- San Diego Biomedical Research Institute (SDBRI), San Diego, CA, United States of America
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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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32
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Moshiri N. ViralMSA: massively scalable reference-guided multiple sequence alignment of viral genomes. Bioinformatics 2021; 37:714-716. [PMID: 32814953 DOI: 10.1093/bioinformatics/btaa743] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 07/21/2020] [Accepted: 08/13/2020] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION In molecular epidemiology, the identification of clusters of transmissions typically requires the alignment of viral genomic sequence data. However, existing methods of multiple sequence alignment (MSA) scale poorly with respect to the number of sequences. RESULTS ViralMSA is a user-friendly reference-guided MSA tool that leverages the algorithmic techniques of read mappers to enable the MSA of ultra-large viral genome datasets. It scales linearly with the number of sequences, and it is able to align tens of thousands of full viral genomes in seconds. However, alignments produced by ViralMSA omit insertions with respect to the reference genome. AVAILABILITY AND IMPLEMENTATION ViralMSA is freely available at https://github.com/niemasd/ViralMSA as an open-source software project. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Niema Moshiri
- Department of Computer Science and Engineering, UC San Diego, La Jolla, CA 92093, USA
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33
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Hufsky F, Lamkiewicz K, Almeida A, Aouacheria A, Arighi C, Bateman A, Baumbach J, Beerenwinkel N, Brandt C, Cacciabue M, Chuguransky S, Drechsel O, Finn RD, Fritz A, Fuchs S, Hattab G, Hauschild AC, Heider D, Hoffmann M, Hölzer M, Hoops S, Kaderali L, Kalvari I, von Kleist M, Kmiecinski R, Kühnert D, Lasso G, Libin P, List M, Löchel HF, Martin MJ, Martin R, Matschinske J, McHardy AC, Mendes P, Mistry J, Navratil V, Nawrocki EP, O’Toole ÁN, Ontiveros-Palacios N, Petrov AI, Rangel-Pineros G, Redaschi N, Reimering S, Reinert K, Reyes A, Richardson L, Robertson DL, Sadegh S, Singer JB, Theys K, Upton C, Welzel M, Williams L, Marz M. Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research. Brief Bioinform 2021; 22:642-663. [PMID: 33147627 PMCID: PMC7665365 DOI: 10.1093/bib/bbaa232] [Citation(s) in RCA: 78] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 07/28/2020] [Accepted: 08/26/2020] [Indexed: 12/16/2022] Open
Abstract
SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories. Contact:evbc@unj-jena.de.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Christian Brandt
- Institute of Infectious Disease and Infection Control at Jena University Hospital, Germany
| | - Marco Cacciabue
- Consejo Nacional de Investigaciones Científicas y Tócnicas (CONICET) working on FMDV virology at the Instituto de Agrobiotecnología y Biología Molecular (IABiMo, INTA-CONICET) and at the Departamento de Ciencias Básicas, Universidad Nacional de Luján (UNLu), Argentina
| | | | - Oliver Drechsel
- bioinformatics department at the Robert Koch-Institute, Germany
| | | | - Adrian Fritz
- Computational Biology of Infection Research group of Alice C. McHardy at the Helmholtz Centre for Infection Research, Germany
| | - Stephan Fuchs
- bioinformatics department at the Robert Koch-Institute, Germany
| | - Georges Hattab
- Bioinformatics Division at Philipps-University Marburg, Germany
| | | | - Dominik Heider
- Data Science in Biomedicine at the Philipps-University of Marburg, Germany
| | | | | | - Stefan Hoops
- Biocomplexity Institute and Initiative at the University of Virginia, USA
| | - Lars Kaderali
- Bioinformatics and head of the Institute of Bioinformatics at University Medicine Greifswald, Germany
| | | | - Max von Kleist
- bioinformatics department at the Robert Koch-Institute, Germany
| | - Renó Kmiecinski
- bioinformatics department at the Robert Koch-Institute, Germany
| | | | - Gorka Lasso
- Chandran Lab, Albert Einstein College of Medicine, USA
| | | | | | | | | | | | | | - Alice C McHardy
- Computational Biology of Infection Research Lab at the Helmholtz Centre for Infection Research in Braunschweig, Germany
| | - Pedro Mendes
- Center for Quantitative Medicine of the University of Connecticut School of Medicine, USA
| | | | - Vincent Navratil
- Bioinformatics and Systems Biology at the Rhône Alpes Bioinformatics core facility, Universitó de Lyon, France
| | | | | | | | | | | | - Nicole Redaschi
- Development of the Swiss-Prot group at the SIB for UniProt and SIB resources that cover viral biology (ViralZone)
| | - Susanne Reimering
- Computational Biology of Infection Research group of Alice C. McHardy at the Helmholtz Centre for Infection Research
| | | | | | | | | | - Sepideh Sadegh
- Chair of Experimental Bioinformatics at Technical University of Munich, Germany
| | - Joshua B Singer
- MRC-University of Glasgow Centre for Virus Research, Glasgow, Scotland, UK
| | | | - Chris Upton
- Department of Biochemistry and Microbiology, University of Victoria, Canada
| | | | | | - Manja Marz
- Friedrich Schiller University Jena, Germany
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Neches RY, Kyrpides NC, Ouzounis CA. Atypical Divergence of SARS-CoV-2 Orf8 from Orf7a within the Coronavirus Lineage Suggests Potential Stealthy Viral Strategies in Immune Evasion. mBio 2021; 12:e03014-20. [PMID: 33468697 PMCID: PMC7845636 DOI: 10.1128/mbio.03014-20] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Accepted: 12/11/2020] [Indexed: 01/19/2023] Open
Abstract
Orf8, one of the most puzzling genes in the SARS lineage of coronaviruses, marks a unique and striking difference in genome organization between SARS-CoV-2 and SARS-CoV-1. Here, using sequence comparisons, we unequivocally reveal the distant sequence similarities between SARS-CoV-2 Orf8 with its SARS-CoV-1 counterparts and the X4-like genes of coronaviruses, including its highly divergent "paralog" gene Orf7a, whose product is a potential immune antagonist of known structure. Supervised sequence space walks unravel identity levels that drop below 10% and yet exhibit subtle conservation patterns in this novel superfamily, characterized by an immunoglobulin-like beta sandwich topology. We document the high accuracy of the sequence space walk process in detail and characterize the subgroups of the superfamily in sequence space by systematic annotation of gene and taxon groups. While SARS-CoV-1 Orf7a and Orf8 genes are most similar to bat virus sequences, their SARS-CoV-2 counterparts are closer to pangolin virus homologs, reflecting the fine structure of conservation patterns within the SARS-CoV-2 genomes. The divergence between Orf7a and Orf8 is exceptionally idiosyncratic, since Orf7a is more constrained, whereas Orf8 is subject to rampant change, a peculiar feature that may be related to hitherto-unknown viral infection strategies. Despite their common origin, the Orf7a and Orf8 protein families exhibit different modes of evolutionary trajectories within the coronavirus lineage, which might be partly attributable to their complex interactions with the mammalian host cell, reflected by a multitude of functional associations of Orf8 in SARS-CoV-2 compared to a very small number of interactions discovered for Orf7a.IMPORTANCE Orf8 is one of the most puzzling genes in the SARS lineage of coronaviruses, including SARS-CoV-2. Using sophisticated sequence comparisons, we confirm its origins from Orf7a, another gene in the lineage that appears as more conserved, compared to Orf8. Orf7a is a potential immune antagonist of known structure, while a deletion of Orf8 was shown to decrease the severity of the infection in a cohort study. The subtle sequence similarities imply that Orf8 has the same immunoglobulin-like fold as Orf7a, confirmed by structure determination. We characterize the subgroups of this superfamily and demonstrate the highly idiosyncratic divergence patterns during the evolution of the virus.
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Affiliation(s)
- Russell Y Neches
- DOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley California, USA
| | - Nikos C Kyrpides
- DOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley California, USA
| | - Christos A Ouzounis
- Biological Computation and Process Laboratory, Chemical Process and Energy Resources Institute, Centre for Research and Technology Hellas, Thessalonica, Greece
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35
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Mastriani E, Rakov AV, Liu SL. Isolating SARS-CoV-2 Strains From Countries in the Same Meridian: Genome Evolutionary Analysis. JMIR BIOINFORMATICS AND BIOTECHNOLOGY 2021; 2:e25995. [PMID: 33497425 PMCID: PMC7837406 DOI: 10.2196/25995] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 12/30/2020] [Accepted: 01/13/2021] [Indexed: 01/25/2023]
Abstract
BACKGROUND COVID-19, caused by the novel SARS-CoV-2, is considered the most threatening respiratory infection in the world, with over 40 million people infected and over 0.934 million related deaths reported worldwide. It is speculated that epidemiological and clinical features of COVID-19 may differ across countries or continents. Genomic comparison of 48,635 SARS-CoV-2 genomes has shown that the average number of mutations per sample was 7.23, and most SARS-CoV-2 strains belong to one of 3 clades characterized by geographic and genomic specificity: Europe, Asia, and North America. OBJECTIVE The aim of this study was to compare the genomes of SARS-CoV-2 strains isolated from Italy, Sweden, and Congo, that is, 3 different countries in the same meridian (longitude) but with different climate conditions, and from Brazil (as an outgroup country), to analyze similarities or differences in patterns of possible evolutionary pressure signatures in their genomes. METHODS We obtained data from the Global Initiative on Sharing All Influenza Data repository by sampling all genomes available on that date. Using HyPhy, we achieved the recombination analysis by genetic algorithm recombination detection method, trimming, removal of the stop codons, and phylogenetic tree and mixed effects model of evolution analyses. We also performed secondary structure prediction analysis for both sequences (mutated and wild-type) and "disorder" and "transmembrane" analyses of the protein. We analyzed both protein structures with an ab initio approach to predict their ontologies and 3D structures. RESULTS Evolutionary analysis revealed that codon 9628 is under episodic selective pressure for all SARS-CoV-2 strains isolated from the 4 countries, suggesting it is a key site for virus evolution. Codon 9628 encodes the P0DTD3 (Y14_SARS2) uncharacterized protein 14. Further investigation showed that the codon mutation was responsible for helical modification in the secondary structure. The codon was positioned in the more ordered region of the gene (41-59) and near to the area acting as the transmembrane (54-67), suggesting its involvement in the attachment phase of the virus. The predicted protein structures of both wild-type and mutated P0DTD3 confirmed the importance of the codon to define the protein structure. Moreover, ontological analysis of the protein emphasized that the mutation enhances the binding probability. CONCLUSIONS Our results suggest that RNA secondary structure may be affected and, consequently, the protein product changes T (threonine) to G (glycine) in position 50 of the protein. This position is located close to the predicted transmembrane region. Mutation analysis revealed that the change from G (glycine) to D (aspartic acid) may confer a new function to the protein-binding activity, which in turn may be responsible for attaching the virus to human eukaryotic cells. These findings can help design in vitro experiments and possibly facilitate a vaccine design and successful antiviral strategies.
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Affiliation(s)
- Emilio Mastriani
- Systemomics Center, College of Pharmacy, Genomics Research Center, State-Province Key Laboratories of Biomedicine-Pharmaceutics of China, Harbin Medical University, Harbin, China
- HMU-UCCSM Centre for Infection and Genomics, Harbin Medical University, Harbin, China
| | - Alexey V Rakov
- Somov Institute of Epidemiology and Microbiology, Vladivostok, Russian Federation
| | - Shu-Lin Liu
- Systemomics Center, College of Pharmacy, Genomics Research Center, State-Province Key Laboratories of Biomedicine-Pharmaceutics of China, Harbin Medical University, Harbin, China
- HMU-UCCSM Centre for Infection and Genomics, Harbin Medical University, Harbin, China
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, AB, Canada
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36
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Torsson E, Kgotlele T, Misinzo G, Johansson Wensman J, Berg M, Karlsson Lindsjö O. Field-Adapted Full Genome Sequencing of Peste-Des-Petits-Ruminants Virus Using Nanopore Sequencing. Front Vet Sci 2020; 7:542724. [PMID: 33195515 PMCID: PMC7649132 DOI: 10.3389/fvets.2020.542724] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Accepted: 09/30/2020] [Indexed: 01/01/2023] Open
Abstract
Peste-des-petits-ruminants virus (PPRV) is currently the focus of a control and eradication program. Full genome sequencing has the opportunity to become a powerful tool in the eradication program by improving molecular epidemiology and the study of viral evolution. PPRV is prevalent in many resource-constrained areas, with long distances to laboratory facilities, which can lack the correct equipment for high-throughput sequencing. Here we present a protocol for near full or full genome sequencing of PPRV. The use of a portable miniPCR and MinION brings the laboratory to the field and in addition makes the production of a full genome possible within 24 h of sampling. The protocol has been successfully used on virus isolates from cell cultures and field isolates from tissue samples of naturally infected goats.
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Affiliation(s)
- Emeli Torsson
- Department of Biomedical Sciences & Veterinary Public Health, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Tebogo Kgotlele
- Department of Veterinary Microbiology and Parasitology, Sokoine University of Agriculture, Morogoro, Tanzania
| | - Gerald Misinzo
- Department of Veterinary Microbiology and Parasitology, Sokoine University of Agriculture, Morogoro, Tanzania
| | - Jonas Johansson Wensman
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Mikael Berg
- Department of Biomedical Sciences & Veterinary Public Health, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Oskar Karlsson Lindsjö
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
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37
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Rangan R, Zheludev IN, Hagey RJ, Pham EA, Wayment-Steele HK, Glenn JS, Das R. RNA genome conservation and secondary structure in SARS-CoV-2 and SARS-related viruses: a first look. RNA (NEW YORK, N.Y.) 2020; 26:937-959. [PMID: 32398273 PMCID: PMC7373990 DOI: 10.1261/rna.076141.120] [Citation(s) in RCA: 182] [Impact Index Per Article: 45.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 05/11/2020] [Indexed: 05/11/2023]
Abstract
As the COVID-19 outbreak spreads, there is a growing need for a compilation of conserved RNA genome regions in the SARS-CoV-2 virus along with their structural propensities to guide development of antivirals and diagnostics. Here we present a first look at RNA sequence conservation and structural propensities in the SARS-CoV-2 genome. Using sequence alignments spanning a range of betacoronaviruses, we rank genomic regions by RNA sequence conservation, identifying 79 regions of length at least 15 nt as exactly conserved over SARS-related complete genome sequences available near the beginning of the COVID-19 outbreak. We then confirm the conservation of the majority of these genome regions across 739 SARS-CoV-2 sequences subsequently reported from the COVID-19 outbreak, and we present a curated list of 30 "SARS-related-conserved" regions. We find that known RNA structured elements curated as Rfam families and in prior literature are enriched in these conserved genome regions, and we predict additional conserved, stable secondary structures across the viral genome. We provide 106 "SARS-CoV-2-conserved-structured" regions as potential targets for antivirals that bind to structured RNA. We further provide detailed secondary structure models for the extended 5' UTR, frameshifting stimulation element, and 3' UTR. Lastly, we predict regions of the SARS-CoV-2 viral genome that have low propensity for RNA secondary structure and are conserved within SARS-CoV-2 strains. These 59 "SARS-CoV-2-conserved-unstructured" genomic regions may be most easily accessible by hybridization in primer-based diagnostic strategies.
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Affiliation(s)
- Ramya Rangan
- Biophysics Program, Stanford University, Stanford, California 94305, USA
| | - Ivan N Zheludev
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Rachel J Hagey
- Departments of Medicine (Division of Gastroenterology and Hepatology) and Microbiology & Immunology, Stanford School of Medicine, Stanford, California 94305, USA
| | - Edward A Pham
- Departments of Medicine (Division of Gastroenterology and Hepatology) and Microbiology & Immunology, Stanford School of Medicine, Stanford, California 94305, USA
| | | | - Jeffrey S Glenn
- Departments of Medicine (Division of Gastroenterology and Hepatology) and Microbiology & Immunology, Stanford School of Medicine, Stanford, California 94305, USA
- Palo Alto Veterans Administration, Palo Alto, California 94304, USA
| | - Rhiju Das
- Biophysics Program, Stanford University, Stanford, California 94305, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, California 94305, USA
- Department of Physics, Stanford University, Stanford, California 94305, USA
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38
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Larsen CN, Sun G, Li X, Zaremba S, Zhao H, He S, Zhou L, Kumar S, Desborough V, Klem EB. Mat_peptide: comprehensive annotation of mature peptides from polyproteins in five virus families. Bioinformatics 2020; 36:1627-1628. [PMID: 31609421 DOI: 10.1093/bioinformatics/btz777] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Revised: 10/04/2019] [Accepted: 10/10/2019] [Indexed: 11/13/2022] Open
Abstract
MOTIVATION Sequence repositories have few well-annotated virus mature peptide sequences. Therefore post-translational proteolytic processing of polyproteins into mature peptides (MPs) has been performed in silico, with a new computational method, for over 200 species in 5 pathogenic virus families (Caliciviridae, Coronaviridae, Flaviviridae, Picornaviridae and Togaviridae). RESULTS Using pairwise alignment with reference sequences, MPs have been annotated and their sequences made available for search, analysis and download. At publication the method had produced 156 216 sequences, a large portion of the protein sequences now available in https://www.viprbrc.org. It represents a new and comprehensive mature peptide collection. AVAILABILITY AND IMPLEMENTATION The data are available at the Virus Pathogen Resource https://www.viprbrc.org, and the software at https://github.com/VirusBRC/vipr_mat_peptide.
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Affiliation(s)
| | - Guangyu Sun
- Vecna Technologies, Inc., Greenbelt, MD 20770
| | - Xiaomei Li
- Northrop Grumman, Rockville, MD 20850, USA
| | | | | | - Sherry He
- Northrop Grumman, Rockville, MD 20850, USA
| | - Liwei Zhou
- Northrop Grumman, Rockville, MD 20850, USA
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Hong SL, Dellicour S, Vrancken B, Suchard MA, Pyne MT, Hillyard DR, Lemey P, Baele G. In Search of Covariates of HIV-1 Subtype B Spread in the United States-A Cautionary Tale of Large-Scale Bayesian Phylogeography. Viruses 2020; 12:v12020182. [PMID: 32033422 PMCID: PMC7077180 DOI: 10.3390/v12020182] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 01/24/2020] [Accepted: 01/28/2020] [Indexed: 12/21/2022] Open
Abstract
Infections with HIV-1 group M subtype B viruses account for the majority of the HIV epidemic in the Western world. Phylogeographic studies have placed the introduction of subtype B in the United States in New York around 1970, where it grew into a major source of spread. Currently, it is estimated that over one million people are living with HIV in the US and that most are infected with subtype B variants. Here, we aim to identify the drivers of HIV-1 subtype B dispersal in the United States by analyzing a collection of 23,588 pol sequences, collected for drug resistance testing from 45 states during 2004-2011. To this end, we introduce a workflow to reduce this large collection of data to more computationally-manageable sample sizes and apply the BEAST framework to test which covariates associate with the spread of HIV-1 across state borders. Our results show that we are able to consistently identify certain predictors of spread under reasonable run times across datasets of up to 10,000 sequences. However, the general lack of phylogenetic structure and the high uncertainty associated with HIV trees make it difficult to interpret the epidemiological relevance of the drivers of spread we are able to identify. While the workflow we present here could be applied to other virus datasets of a similar scale, the characteristic star-like shape of HIV-1 phylogenies poses a serious obstacle to reconstructing a detailed evolutionary and spatial history for HIV-1 subtype B in the US.
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Affiliation(s)
- Samuel L. Hong
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium; (S.D.); (B.V.); (P.L.); (G.B.)
- Correspondence:
| | - Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium; (S.D.); (B.V.); (P.L.); (G.B.)
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, 1050 Brussels, Belgium
| | - Bram Vrancken
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium; (S.D.); (B.V.); (P.L.); (G.B.)
| | - Marc A. Suchard
- Department of Biomathematics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA 90095, USA;
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA 90095, USA
- Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA 90095, USA
| | - Michael T. Pyne
- ARUP Institute for Clinical and Experimental Pathology, Salt Lake City, UT 84108, USA;
| | - David R. Hillyard
- Department of Pathology, University of Utah, Salt Lake City, UT 84112, USA;
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium; (S.D.); (B.V.); (P.L.); (G.B.)
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000 Leuven, Belgium; (S.D.); (B.V.); (P.L.); (G.B.)
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Abstract
Background Portugal has one of the most severe HIV-1 epidemics in Western Europe. Two subtypes circulate in parallel since the beginning of the epidemic. Comparing their transmission patterns and its association with transmitted drug resistance (TDR) is important to pinpoint transmission hotspots and to develop evidence-based treatment guidelines. Methods Demographic, clinical and genomic data were collected from 3599 HIV-1 naive patients between 2001 and 2014. Sequences obtained from drug resistance testing were used for subtyping, TDR determination and transmission clusters (TC) analyses. Results In Portugal, transmission of subtype B was significantly associated with young males, while transmission of subtype G was associated with older heterosexuals. In Portuguese originated people, there was a decreasing trend both for prevalence of subtype G and for number of TCs in this subtype. The active TCs that were identified (i.e. clusters originated after 2008) were associated with subtype B-infected males residing in Lisbon. TDR was significantly different when comparing subtypes B (10.8% [9.5–12.2]) and G (7.6% [6.4–9.0]) (p = 0.001). Discussion TC analyses shows that, in Portugal, the subtype B epidemic is active and fueled by young male patients residing in Lisbon, while transmission of subtype G is decreasing. Despite similar treatment rates for both subtypes in Portugal, TDR is significantly different between subtypes.
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An Evolutionary Model-Based Approach To Quantify the Genetic Barrier to Drug Resistance in Fast-Evolving Viruses and Its Application to HIV-1 Subtypes and Integrase Inhibitors. Antimicrob Agents Chemother 2019; 63:AAC.00539-19. [PMID: 31109980 DOI: 10.1128/aac.00539-19] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 05/15/2019] [Indexed: 12/19/2022] Open
Abstract
Viral pathogens causing global disease burdens are often characterized by high rates of evolutionary changes. The extensive viral diversity at baseline can shorten the time to escape from therapeutic or immune selective pressure and alter mutational pathways. The impact of genotypic background on the barrier to resistance can be difficult to capture, particularly for agents in experimental stages or that are recently approved or expanded into new patient populations. We developed an evolutionary model-based counting method to quickly quantify the population genetic potential to resistance and assess population differences. We demonstrate its applicability to HIV-1 integrase inhibitors, as their increasing use globally contrasts with limited availability of non-B subtype resistant sequence data and corresponding knowledge gap. A large sequence data set encompassing most prevailing HIV-1 subtypes and resistance-associated mutations of currently approved integrase inhibitors was investigated. A complex interplay between codon predominance, polymorphisms, and associated evolutionary costs resulted in a subtype-dependent varied genetic potential for 15 resistance mutations against integrase inhibitors. While we confirm the lower genetic barrier of subtype B for G140S, we convincingly discard a similar effect previously suggested for G140C. A supplementary analysis for HIV-1 reverse transcriptase inhibitors identified a lower genetic barrier for K65R in subtype C through differential codon usage not reported before. To aid evolutionary interpretations of genomic differences for antiviral strategies, we advanced existing counting methods with increased sensitivity to identify subtype dependencies of resistance emergence. Future applications include novel HIV-1 drug classes or vaccines, as well as other viral pathogens.
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Fonseca V, Libin PJK, Theys K, Faria NR, Nunes MRT, Restovic MI, Freire M, Giovanetti M, Cuypers L, Nowé A, Abecasis A, Deforche K, Santiago GA, de Siqueira IC, San EJ, Machado KCB, Azevedo V, Filippis AMBD, da Cunha RV, Pybus OG, Vandamme AM, Alcantara LCJ, de Oliveira T. A computational method for the identification of Dengue, Zika and Chikungunya virus species and genotypes. PLoS Negl Trop Dis 2019; 13:e0007231. [PMID: 31067235 PMCID: PMC6527240 DOI: 10.1371/journal.pntd.0007231] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 05/20/2019] [Accepted: 02/11/2019] [Indexed: 11/19/2022] Open
Abstract
In recent years, an increasing number of outbreaks of Dengue, Chikungunya and Zika viruses have been reported in Asia and the Americas. Monitoring virus genotype diversity is crucial to understand the emergence and spread of outbreaks, both aspects that are vital to develop effective prevention and treatment strategies. Hence, we developed an efficient method to classify virus sequences with respect to their species and sub-species (i.e. serotype and/or genotype). This tool provides an easy-to-use software implementation of this new method and was validated on a large dataset assessing the classification performance with respect to whole-genome sequences and partial-genome sequences. Available online: http://krisp.org.za/tools.php.
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Affiliation(s)
- Vagner Fonseca
- Laboratório de Flavivírus, IOC, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), College of Health Sciences, University of KwaZuluNatal, Durban, South Africa
- Laboratório de Genética Celular e Molecular, ICB, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Pieter J. K. Libin
- Artificial Intelligence Lab, Department of Computer Science, Vrije Universiteit Brussel, Brussels, Belgium
- KU Leuven—University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Leuven, Belgium
| | - Kristof Theys
- KU Leuven—University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Leuven, Belgium
| | - Nuno R. Faria
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | | | - Maria I. Restovic
- Laboratório de Patologia Experimental, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Murilo Freire
- Laboratório de Patologia Experimental, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Marta Giovanetti
- Laboratório de Flavivírus, IOC, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | - Lize Cuypers
- KU Leuven—University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Leuven, Belgium
| | - Ann Nowé
- Artificial Intelligence Lab, Department of Computer Science, Vrije Universiteit Brussel, Brussels, Belgium
| | - Ana Abecasis
- Center for Global Health and Tropical Medicine, Unidade de Microbiologia, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisbon, Portugal
| | | | - Gilberto A. Santiago
- Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico, United states of America
| | | | - Emmanuel J. San
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), College of Health Sciences, University of KwaZuluNatal, Durban, South Africa
| | | | - Vasco Azevedo
- Laboratório de Genética Celular e Molecular, ICB, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | | | - Rivaldo Venâncio da Cunha
- Coordenação de Vigilância em Saúde e Laboratórios de Referências, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | - Oliver G. Pybus
- Department of Zoology, University of Oxford, Oxford, United Kingdom
| | - Anne-Mieke Vandamme
- KU Leuven—University of Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, Leuven, Belgium
- Center for Global Health and Tropical Medicine, Unidade de Microbiologia, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisbon, Portugal
| | - Luiz C. J. Alcantara
- Laboratório de Flavivírus, IOC, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
- Laboratório de Genética Celular e Molecular, ICB, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil
| | - Tulio de Oliveira
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), College of Health Sciences, University of KwaZuluNatal, Durban, South Africa
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Pérez AB, Vrancken B, Chueca N, Aguilera A, Reina G, García-del Toro M, Vera F, Von Wichman MA, Arenas JI, Téllez F, Pineda JA, Omar M, Bernal E, Rivero-Juárez A, Fernández-Fuertes E, de la Iglesia A, Pascasio JM, Lemey P, Garcia F, Cuypers L. Increasing importance of European lineages in seeding the hepatitis C virus subtype 1a epidemic in Spain. Euro Surveill 2019; 24:1800227. [PMID: 30862327 PMCID: PMC6402173 DOI: 10.2807/1560-7917.es.2019.24.9.1800227] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
BackgroundReducing the burden of the hepatitis C virus (HCV) requires large-scale deployment of intervention programmes, which can be informed by the dynamic pattern of HCV spread. In Spain, ongoing transmission of HCV is mostly fuelled by people who inject drugs (PWID) infected with subtype 1a (HCV1a).AimOur aim was to map how infections spread within and between populations, which could help formulate more effective intervention programmes to halt the HCV1a epidemic in Spain.MethodsEpidemiological links between HCV1a viruses from a convenience sample of 283 patients in Spain, mostly PWID, collected between 2014 and 2016, and 1,317, 1,291 and 1,009 samples collected abroad between 1989 and 2016 were reconstructed using sequences covering the NS3, NS5A and NS5B genes. To efficiently do so, fast maximum likelihood-based tree estimation was coupled to a flexible Bayesian discrete phylogeographic inference method.ResultsThe transmission network structure of the Spanish HCV1a epidemic was shaped by continuous seeding of HCV1a into Spain, almost exclusively from North America and European countries. The latter became increasingly relevant and have dominated in recent times. Export from Spain to other countries in Europe was also strongly supported, although Spain was a net sink for European HCV1a lineages. Spatial reconstructions showed that the epidemic in Spain is diffuse, without large, dominant within-country networks.ConclusionTo boost the effectiveness of local intervention efforts, concerted supra-national strategies to control HCV1a transmission are needed, with a strong focus on the most important drivers of ongoing transmission, i.e. PWID and other high-risk populations.
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Affiliation(s)
- Ana Belen Pérez
- Department of Microbiology, Institute of Bio Sanitary Research (IBIS), AIDS Research Network, University Hospital of Granada, Granada, Spain,These authors contributed equally to the article
| | - Bram Vrancken
- These authors contributed equally to the article,KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Evolutionary and Computational Virology, Leuven, Belgium
| | - Natalia Chueca
- Department of Microbiology, Institute of Bio Sanitary Research (IBIS), AIDS Research Network, University Hospital of Granada, Granada, Spain
| | - Antonio Aguilera
- Department of Microbiology, University Hospital of Santiago, Santiago de Compostela, Spain
| | - Gabriel Reina
- Department of Microbiology, University Hospital of Navarra, Institute for Health Research (IdisNA), Pamplona, Spain
| | | | - Francisco Vera
- Unit of Infectious Diseases, Internal Medicine, General Hospital of Rosell, Cartagena, Murcia, Spain
| | | | - Juan Ignacio Arenas
- Unit of Infectious Diseases, Hospital Universitario de San Sebastian, San Sebastian, Spain
| | - Francisco Téllez
- Unit of Infectious Diseases and Microbiology, University Hospital of Puerto Real, Cádiz, Spain
| | - Juan A Pineda
- Unit of Infectious Diseases, University Hospital of Valme, Sevilla, Spain (J.A. Pineda)
| | | | - Enrique Bernal
- Unit of Infectious Diseases, General University Hospital, Murcia, Spain
| | - Antonio Rivero-Juárez
- Unit of Infectious Diseases, University Hospital Reina Sofía of Córdoba, Maimonides Institute of Biomedical Research of Córdoba, University of Córdoba, Córdoba, Spain
| | | | | | - Juan Manuel Pascasio
- Clinical Management Unit of Digestive Diseases, University Hospital of Virgen del Rocío, Sevilla, Spain
| | - Philippe Lemey
- KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Evolutionary and Computational Virology, Leuven, Belgium
| | - Féderico Garcia
- Department of Microbiology, Institute of Bio Sanitary Research (IBIS), AIDS Research Network, University Hospital of Granada, Granada, Spain,These authors contributed equally to the article
| | - Lize Cuypers
- These authors contributed equally to the article,KU Leuven, Department of Microbiology and Immunology, Rega Institute for Medical Research, Laboratory of Clinical and Epidemiological Virology, Leuven, Belgium
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44
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Cuypers L, Libin PJK, Simmonds P, Nowé A, Muñoz-Jordán J, Alcantara LCJ, Vandamme AM, Santiago GA, Theys K. Time to Harmonize Dengue Nomenclature and Classification. Viruses 2018; 10:E569. [PMID: 30340326 PMCID: PMC6213058 DOI: 10.3390/v10100569] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 10/05/2018] [Accepted: 10/15/2018] [Indexed: 12/22/2022] Open
Abstract
Dengue virus (DENV) is estimated to cause 390 million infections per year worldwide. A quarter of these infections manifest clinically and are associated with a morbidity and mortality that put a significant burden on the affected regions. Reports of increased frequency, intensity, and extended geographical range of outbreaks highlight the virus's ongoing global spread. Persistent transmission in endemic areas and the emergence in territories formerly devoid of transmission have shaped DENV's current genetic diversity and divergence. This genetic layout is hierarchically organized in serotypes, genotypes, and sub-genotypic clades. While serotypes are well defined, the genotype nomenclature and classification system lack consistency, which complicates a broader analysis of their clinical and epidemiological characteristics. We identify five key challenges: (1) Currently, there is no formal definition of a DENV genotype; (2) Two different nomenclature systems are used in parallel, which causes significant confusion; (3) A standardized classification procedure is lacking so far; (4) No formal definition of sub-genotypic clades is in place; (5) There is no consensus on how to report antigenic diversity. Therefore, we believe that the time is right to re-evaluate DENV genetic diversity in an essential effort to provide harmonization across DENV studies.
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Affiliation(s)
- Lize Cuypers
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, KU Leuven, 3000 Leuven, Belgium.
- Nuffield Department of Medicine, University of Oxford, Oxford OX1 3SY, UK.
| | - Pieter J K Libin
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, KU Leuven, 3000 Leuven, Belgium.
- Artificial Intelligence Lab, Department of Computer Science, Vrije Universiteit Brussel, 1050 Brussels, Belgium.
| | - Peter Simmonds
- Nuffield Department of Medicine, University of Oxford, Oxford OX1 3SY, UK.
| | - Ann Nowé
- Artificial Intelligence Lab, Department of Computer Science, Vrije Universiteit Brussel, 1050 Brussels, Belgium.
| | - Jorge Muñoz-Jordán
- Division of Vector-Borne Diseases, Dengue Branch, Centers for Disease Control and Prevention, San Juan, PR 00920, USA.
| | | | - Anne-Mieke Vandamme
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, KU Leuven, 3000 Leuven, Belgium.
- Global Health and Tropical Medicine, Unidade de Microbiologia, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, 1349-008 Lisbon, Portugal.
| | - Gilberto A Santiago
- Division of Vector-Borne Diseases, Dengue Branch, Centers for Disease Control and Prevention, San Juan, PR 00920, USA.
| | - Kristof Theys
- Department of Microbiology and Immunology, Rega Institute for Medical Research, Clinical and Epidemiological Virology, KU Leuven, 3000 Leuven, Belgium.
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