|
1
|
Hufsky F, Abecasis AB, Babaian A, Beck S, Brierley L, Dellicour S, Eggeling C, Elena SF, Gieraths U, Ha AD, Harvey W, Jones TC, Lamkiewicz K, Lovate GL, Lücking D, Machyna M, Nishimura L, Nocke MK, Renard BY, Sakaguchi S, Sakellaridi L, Spangenberg J, Tarradas-Alemany M, Triebel S, Vakulenko Y, Wijesekara RY, González-Candelas F, Krautwurst S, Pérez-Cataluña A, Randazzo W, Sánchez G, Marz M. The International Virus Bioinformatics Meeting 2023. Viruses 2023; 15:2031. [PMID: 37896809 PMCID: PMC10612056 DOI: 10.3390/v15102031] [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: 07/10/2023] [Revised: 09/08/2023] [Accepted: 09/14/2023] [Indexed: 10/29/2023] Open
Abstract
The 2023 International Virus Bioinformatics Meeting was held in Valencia, Spain, from 24-26 May 2023, attracting approximately 180 participants worldwide. The primary objective of the conference was to establish a dynamic scientific environment conducive to discussion, collaboration, and the generation of novel research ideas. As the first in-person event following the SARS-CoV-2 pandemic, the meeting facilitated highly interactive exchanges among attendees. It served as a pivotal gathering for gaining insights into the current status of virus bioinformatics research and engaging with leading researchers and emerging scientists. The event comprised eight invited talks, 19 contributed talks, and 74 poster presentations across eleven sessions spanning three days. Topics covered included machine learning, bacteriophages, virus discovery, virus classification, virus visualization, viral infection, viromics, molecular epidemiology, phylodynamic analysis, RNA viruses, viral sequence analysis, viral surveillance, and metagenomics. This report provides rewritten abstracts of the presentations, a summary of the key research findings, and highlights shared during the meeting.
Collapse
Affiliation(s)
- Franziska Hufsky
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany;
| | - Ana B. Abecasis
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- 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
| | - Artem Babaian
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 3E1, Canada
- Donnelly Centre, University of Toronto, Toronto, ON M5S 1A1, Canada
| | - Sebastian Beck
- Leibniz Institute of Virology, Department Viral Zoonoses—One Health, 20251 Hamburg, Germany;
| | - Liam Brierley
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Department of Health Data Science, University of Liverpool, Liverpool L69 3GF, UK
| | - Simon Dellicour
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP160/12, 50 av. FD Roosevelt, 1050 Bruxelles, Belgium
- Laboratory for Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, University of Leuven, 3000 Leuven, Belgium
| | - Christian Eggeling
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Institute of Applied Optics and Biophysics, Friedrich Schiller University Jena, Max-Wien-Platz 1, 07743 Jena, Germany
| | - Santiago F. Elena
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Institute for Integrative Systems Biology (I2SysBio), CSIC-Universitat de Valencia, Catedratico Agustin Escardino 9, 46980 Valencia, Spain
| | - Udo Gieraths
- Institute of Virology, Charité, Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Anh D. Ha
- Department of Biological Sciences, Virginia Tech, Blacksburg, VA 24061, USA
| | - Will Harvey
- The Roslin Institute, University of Edinburgh, Edinburgh EH25 9RG, UK
| | - Terry C. Jones
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Institute of Virology, Charité, Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
- Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK
| | - Kevin Lamkiewicz
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany;
| | - Gabriel L. Lovate
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany;
| | - Dominik Lücking
- Max-Planck Institute for Marine Microbiology, Celsiusstraße 1, 28359 Bremen, Germany
| | - Martin Machyna
- Paul-Ehrlich-Institut, Host-Pathogen-Interactions, 63225 Langen, Germany
| | - Luca Nishimura
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- 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
| | - Maximilian K. Nocke
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Department for Molecular & Medical Virology, Ruhr University Bochum, 44801 Bochum, Germany
| | - Bernard Y. Renard
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Digital Engineering Faculty, Hasso Plattner Institute, University of Potsdam, 14482 Potsdam, Germany
| | - Shoichi Sakaguchi
- Department of Microbiology and Infection Control, Faculty of Medicine, Osaka Medical and Pharmaceutical University, Osaka 569-8686, Japan;
| | - Lygeri Sakellaridi
- Institute for Virology and Immunobiology, University of Würzburg, Versbacher Str. 7, 97078 Würzburg, Germany
| | - Jannes Spangenberg
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany;
| | - Maria Tarradas-Alemany
- Computational Genomics Lab., Department of Genetics, Microbiology and Statistics, Institut de Biomedicina UB (IBUB), Universitat de Barcelona (UB), 08028 Barcelona, Spain
| | - Sandra Triebel
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany;
| | - Yulia Vakulenko
- Martsinovsky Institute of Medical Parasitology, Tropical and Vector Borne Diseases, Sechenov First Moscow State Medical University, 119991 Moscow, Russia
| | - Rajitha Yasas Wijesekara
- Institute for Bioinformatics, University of Medicine Greifswald, Felix-Hausdorff-Str. 8, 17475 Greifswald, Germany
| | - Fernando González-Candelas
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- Institute for Integrative Systems Biology (I2SysBio), CSIC-Universitat de Valencia, Catedratico Agustin Escardino 9, 46980 Valencia, Spain
- Joint Research Unit “Infection and Public Health” FISABIO, University of Valencia, 46010 Valencia, Spain
| | - Sarah Krautwurst
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany;
| | - Alba Pérez-Cataluña
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- VISAFELab, Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, 46980 Valencia, Spain
| | - Walter Randazzo
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- VISAFELab, Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, 46980 Valencia, Spain
| | - Gloria Sánchez
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- VISAFELab, Department of Preservation and Food Safety Technologies, Institute of Agrochemistry and Food Technology, IATA-CSIC, 46980 Valencia, Spain
| | - Manja Marz
- European Virus Bioinformatics Center, 07743 Jena, Germany (A.B.A.); (L.B.); (S.D.); (C.E.); (S.F.E.); (T.C.J.); (K.L.); (G.L.L.); (M.K.N.); (B.Y.R.); (F.G.-C.); (A.P.-C.); (W.R.); (G.S.)
- RNA Bioinformatics and High-Throughput Analysis, Friedrich Schiller University Jena, 07743 Jena, Germany;
- German Center for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig, Germany
- Michael Stifel Center Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany
- Cluster of Excellence Balance of the Microverse, Friedrich Schiller University Jena, 07745 Jena, Germany
- Leibniz Institute for Age Research—Fritz Lippman Institute, 07745 Jena, Germany
| |
Collapse
|
|
2
|
Rose R, Hall M, Redd AD, Lamers S, Barbier AE, Porcella SF, Hudelson SE, Piwowar-Manning E, McCauley M, Gamble T, Wilson EA, Kumwenda J, Hosseinipour MC, Hakim JG, Kumarasamy N, Chariyalertsak S, Pilotto JH, Grinsztejn B, Mills LA, Makhema J, Santos BR, Chen YQ, Quinn TC, Fraser C, Cohen MS, Eshleman SH, Laeyendecker O. Phylogenetic Methods Inconsistently Predict the Direction of HIV Transmission Among Heterosexual Pairs in the HPTN 052 Cohort. J Infect Dis 2019; 220:1406-1413. [PMID: 30590741 PMCID: PMC6761953 DOI: 10.1093/infdis/jiy734] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Accepted: 12/21/2018] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND We evaluated use of phylogenetic methods to predict the direction of human immunodeficiency virus (HIV) transmission. METHODS For 33 pairs of HIV-infected patients (hereafter, "index patients") and their partners who acquired genetically linked HIV infection during the study, samples were collected from partners and index patients close to the time when the partner seroconverted (hereafter, "SC samples"); for 31 pairs, samples collected from the index patient at an earlier time point (hereafter, "early index samples") were also available. Phylogenies were inferred using env next-generation sequences (1 tree per pair/subtype). The direction of transmission (DoT) predicted from each tree was classified as correct or incorrect on the basis of which sequences (those from the index patient or the partner) were closest to the root. DoT was also assessed using maximum parsimony to infer ancestral node states for 100 bootstrap trees. RESULTS DoT was predicted correctly for both single-pair and subtype-specific trees in 22 pairs (67%) by using SC samples and in 23 pairs (74%) by using early index samples. DoT was predicted incorrectly for 4 pairs (15%) by using SC or early index samples. In the bootstrap analysis, DoT was predicted correctly for 18 pairs (55%) by using SC samples and for 24 pairs (73%) by using early index samples. DoT was predicted incorrectly for 7 pairs (21%) by using SC samples and for 4 pairs (13%) by using early index samples. CONCLUSIONS Phylogenetic methods based solely on the tree topology of HIV env sequences, particularly without consideration of phylogenetic uncertainty, may be insufficient for determining DoT.
Collapse
Affiliation(s)
| | - Matthew Hall
- Big Data Institute, University of Oxford, United Kingdom
| | - Andrew D Redd
- Laboratory of Immunoregulation, Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Baltimore, Maryland
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | | | | | - Stephen F Porcella
- Genomics Unit, Research Technologies Section, Rocky Mountain Laboratories, Division of Intramural Research, NIAID, NIH, Hamilton, Montana
| | - Sarah E Hudelson
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | | | - Marybeth McCauley
- Science Facilitation Department, Durham, Chapel Hill, North Carolina
| | - Theresa Gamble
- Science Facilitation Department, Durham, Chapel Hill, North Carolina
| | - Ethan A Wilson
- Vaccine and Infectious Disease Science Division, Fred Hutchinson Cancer Research Institute, Seattle, Washington
| | | | - Mina C Hosseinipour
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | | | | | | | - Jose H Pilotto
- Hospital Geral de Nova Iguaçu, Rio de Janeiro, Brazil
- Laboratorio de AIDS e Imunologia Molecular (IOC/Fiocruz), Rio de Janeiro, Brazil
| | - Beatriz Grinsztejn
- Instituto Nacional de Infectologia Evandro Chagas-INI-Fiocruz, Rio de Janeiro, Brazil
| | - Lisa A Mills
- Centers for Disease Control and Prevention (CDC) Division of HIV/AIDS Prevention/KEMRI–CDC Research and Public Health Collaboration HIV Research Branch, Kisumu, Kenya
| | | | - Breno R Santos
- Servico de Infectologia, Hospital Nossa Senhora da Conceicao/GHC, Porto Alegre, Brazil
| | - Ying Q Chen
- Vaccine and Infectious Disease Science Division, Fred Hutchinson Cancer Research Institute, Seattle, Washington
| | - Thomas C Quinn
- Laboratory of Immunoregulation, Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Baltimore, Maryland
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | | | - Myron S Cohen
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Susan H Eshleman
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Oliver Laeyendecker
- Laboratory of Immunoregulation, Division of Intramural Research, National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health (NIH), Baltimore, Maryland
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| |
Collapse
|
|
3
|
Mutenherwa F, Wassenaar DR, de Oliveira T. Experts' Perspectives on Key Ethical Issues Associated With HIV Phylogenetics as Applied in HIV Transmission Dynamics Research. J Empir Res Hum Res Ethics 2018; 14:61-77. [PMID: 30486713 DOI: 10.1177/1556264618809608] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The use of phylogenetics in HIV molecular epidemiology has considerably increased our ability to understand the origin, spread, and characteristics of HIV epidemics. Despite its potential to advance knowledge on HIV transmission dynamics, the ethical issues associated with HIV molecular epidemiology have received minimal attention. In-depth interviews were conducted with scientists from diverse backgrounds to explore their perspectives on ethical issues associated with phylogenetic analysis of HIV genetic data as applied to HIV transmission dynamics studies. The Emanuel framework was used as the analytical framework. Favorable risk-benefit ratio and informed consent were the most invoked ethical principles and fair participant selection the least. Fear of loss of privacy and disclosure of HIV transmission were invariably cited as key ethical concerns. As HIV sequence data become increasingly available, comprehensive guidelines should be developed to guide its access, sharing and use, cognizant of the potential harms that may result.
Collapse
Affiliation(s)
- Farirai Mutenherwa
- 1 University of KwaZulu-Natal, South Africa.,2 KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
| | | | - Tulio de Oliveira
- 1 University of KwaZulu-Natal, South Africa.,2 KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa.,3 Centre for the AIDS Programme of Research in South Africa, Durban, South Africa
| |
Collapse
|
|
4
|
Coltart CEM, Hoppe A, Parker M, Dawson L, Amon JJ, Simwinga M, Geller G, Henderson G, Laeyendecker O, Tucker JD, Eba P, Novitsky V, Vandamme AM, Seeley J, Dallabetta G, Harling G, Grabowski MK, Godfrey-Faussett P, Fraser C, Cohen MS, Pillay D. Ethical considerations in global HIV phylogenetic research. Lancet HIV 2018; 5:e656-e666. [PMID: 30174214 PMCID: PMC7327184 DOI: 10.1016/s2352-3018(18)30134-6] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2018] [Revised: 05/28/2018] [Accepted: 06/06/2018] [Indexed: 01/01/2023]
Abstract
Phylogenetic analysis of pathogens is an increasingly powerful way to reduce the spread of epidemics, including HIV. As a result, phylogenetic approaches are becoming embedded in public health and research programmes, as well as outbreak responses, presenting unique ethical, legal, and social issues that are not adequately addressed by existing bioethics literature. We formed a multidisciplinary working group to explore the ethical issues arising from the design of, conduct in, and use of results from HIV phylogenetic studies, and to propose recommendations to minimise the associated risks to both individuals and groups. We identified eight key ethical domains, within which we highlighted factors that make HIV phylogenetic research unique. In this Review, we endeavoured to provide a framework to assist researchers, public health practitioners, and funding institutions to ensure that HIV phylogenetic studies are designed, done, and disseminated in an ethical manner. Our conclusions also have broader relevance for pathogen phylogenetics.
Collapse
Affiliation(s)
| | - Anne Hoppe
- Division of Infection and Immunity, University College London, London, UK.
| | - Michael Parker
- The Wellcome Centre for Ethics and Humanities (Ethox), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Liza Dawson
- Division of AIDS, National Institutes of Health, Bethesda, MD, USA
| | - Joseph J Amon
- Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ, USA
| | | | - Gail Geller
- Berman Institute of Bioethics and School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Gail Henderson
- Center for Genomics and Society, Department of Social Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Oliver Laeyendecker
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Joseph D Tucker
- Institute for Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, NC, USA
| | - Patrick Eba
- Community Support, Social Justice and Inclusion Department, Geneva, Switzerland; School of Law, University of KwaZulu-Natal, Pietermaritzburg, South Africa
| | - Vladimir Novitsky
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Anne-Mieke Vandamme
- Clinical and Epidemiological Virology, Rega Institute for Medical Research, Department of Microbiology and Immunology, KU Leuven-University of Leuven, Leuven, Belgium; Center for Global Health and Tropical Medicine, Unidade de Microbiologia, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisbon, Portugal
| | - Janet Seeley
- Africa Health Research Institute, KwaZulu-Natal, South Africa; Department of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK
| | | | - Guy Harling
- Institute for Global Health, University College London, London, UK; Africa Health Research Institute, KwaZulu-Natal, South Africa
| | - M Kate Grabowski
- Department of Pathology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Rakai Community Cohort Study, Rakai Health Sciences Program, Kalisizo, Uganda
| | - Peter Godfrey-Faussett
- Joint United Nations Programme on HIV/AIDS, Geneva, Switzerland; Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK
| | - Christophe Fraser
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Myron S Cohen
- Institute for Global Health and Infectious Diseases, University of North Carolina, Chapel Hill, NC, USA; Department of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Deenan Pillay
- Division of Infection and Immunity, University College London, London, UK; Africa Health Research Institute, KwaZulu-Natal, South Africa
| |
Collapse
|
|
5
|
Vrancken B, Alavian SM, Aminy A, Amini-Bavil-Olyaee S, Pourkarim MR. Why comprehensive datasets matter when inferring epidemic links or subgenotyping. INFECTION GENETICS AND EVOLUTION 2018; 65:350-351. [PMID: 30118874 DOI: 10.1016/j.meegid.2018.08.012] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 07/20/2018] [Accepted: 08/13/2018] [Indexed: 02/07/2023]
Affiliation(s)
- Bram Vrancken
- KU Leuven, Department of Microbiology and Immunology, Rega Institute, Laboratory of Evolutionary and Computational Virology, 3000, Leuven, Belgium
| | - Seyed Moayed Alavian
- Baqiyatallah Research Center for Gastroenterology and Liver Disease, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Ali Aminy
- Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98, 4032 Debrecen, Hungary
| | - Samad Amini-Bavil-Olyaee
- Biosafety Development Group, Cellular Sciences Department, Amgen Inc., One Amgen Center Drive, Thousand Oaks, CA 91320, USA
| | - Mahmoud Reza Pourkarim
- KU Leuven, Department of Microbiology and Immunology, Rega Institute, Laboratory of Clinical and Epidemiological Virology, 3000, Leuven, Belgium; Blood Transfusion Research Centre, High Institute for Research and Education in Transfusion Medicine, Hemmat Exp. Way, 14665-1157, Tehran, Iran.
| |
Collapse
|
|
6
|
Leitner T, Romero-Severson E. Phylogenetic patterns recover known HIV epidemiological relationships and reveal common transmission of multiple variants. Nat Microbiol 2018; 3:983-988. [PMID: 30061758 PMCID: PMC6442454 DOI: 10.1038/s41564-018-0204-9] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Accepted: 06/22/2018] [Indexed: 11/09/2022]
Abstract
The growth of human immunodeficiency virus (HIV) sequence databases resulting from drug resistance testing has motivated efforts using phylogenetic methods to assess how HIV spreads1-4. Such inference is potentially both powerful and useful for tracking the epidemiology of HIV and the allocation of resources to prevention campaigns. We recently used simulation and a small number of illustrative cases to show that certain phylogenetic patterns are associated with different types of epidemiological linkage5. Our original approach was later generalized for large next-generation sequencing datasets and implemented as a free computational pipeline6. Previous work has claimed that direction and directness of transmission could not be established from phylogeny because one could not be sure that there were no intervening or missing links involved7-9. Here, we address this issue by investigating phylogenetic patterns from 272 previously identified HIV transmission chains with 955 transmission pairs representing diverse geography, risk groups, subtypes, and genomic regions. These HIV transmissions had known linkage based on epidemiological information such as partner studies, mother-to-child transmission, pairs identified by contact tracing, and criminal cases. We show that the resulting phylogeny inferred from real HIV genetic sequences indeed reveals distinct patterns associated with direct transmission contra transmissions from a common source. Thus, our results establish how to interpret phylogenetic trees based on HIV sequences when tracking who-infected-whom, when and how genetic information can be used for improved tracking of HIV spread. We also investigate limitations that stem from limited sampling and genetic time-trends in the donor and recipient HIV populations.
Collapse
Affiliation(s)
- Thomas Leitner
- Theoretical Biology and Biophysics Group, MS K710, Los Alamos National Laboratory, Los Alamos, NM, USA.
| | - Ethan Romero-Severson
- Theoretical Biology and Biophysics Group, MS K710, Los Alamos National Laboratory, Los Alamos, NM, USA
| |
Collapse
|
|
7
|
Barré‐Sinoussi F, Abdool Karim SS, Albert J, Bekker L, Beyrer C, Cahn P, Calmy A, Grinsztejn B, Grulich A, Kamarulzaman A, Kumarasamy N, Loutfy MR, El Filali KM, Mboup S, Montaner JSG, Munderi P, Pokrovsky V, Vandamme A, Young B, Godfrey‐Faussett P. Expert consensus statement on the science of HIV in the context of criminal law. J Int AIDS Soc 2018; 21:e25161. [PMID: 30044059 PMCID: PMC6058263 DOI: 10.1002/jia2.25161] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Accepted: 06/21/2018] [Indexed: 02/06/2023] Open
Abstract
INTRODUCTION Globally, prosecutions for non-disclosure, exposure or transmission of HIV frequently relate to sexual activity, biting, or spitting. This includes instances in which no harm was intended, HIV transmission did not occur, and HIV transmission was extremely unlikely or not possible. This suggests prosecutions are not always guided by the best available scientific and medical evidence. DISCUSSION Twenty scientists from regions across the world developed this Expert Consensus Statement to address the use of HIV science by the criminal justice system. A detailed analysis of the best available scientific and medical research data on HIV transmission, treatment effectiveness and forensic phylogenetic evidence was performed and described so it may be better understood in criminal law contexts. Description of the possibility of HIV transmission was limited to acts most often at issue in criminal cases. The possibility of HIV transmission during a single, specific act was positioned along a continuum of risk, noting that the possibility of HIV transmission varies according to a range of intersecting factors including viral load, condom use, and other risk reduction practices. Current evidence suggests the possibility of HIV transmission during a single episode of sex, biting or spitting ranges from no possibility to low possibility. Further research considered the positive health impact of modern antiretroviral therapies that have improved the life expectancy of most people living with HIV to a point similar to their HIV-negative counterparts, transforming HIV infection into a chronic, manageable health condition. Lastly, consideration of the use of scientific evidence in court found that phylogenetic analysis alone cannot prove beyond reasonable doubt that one person infected another although it can be used to exonerate a defendant. CONCLUSIONS The application of up-to-date scientific evidence in criminal cases has the potential to limit unjust prosecutions and convictions. The authors recommend that caution be exercised when considering prosecution, and encourage governments and those working in legal and judicial systems to pay close attention to the significant advances in HIV science that have occurred over the last three decades to ensure current scientific knowledge informs application of the law in cases related to HIV.
Collapse
Affiliation(s)
| | - Salim S Abdool Karim
- Mailman School of Public HealthColumbia UniversityNew YorkNYUSA
- Centre for the AIDS Program of Research in South AfricaUniversity of KwaZulu‐NatalDurbanSouth Africa
- Weill Medical CollegeCornell UniversityNew YorkNYUSA
| | - Jan Albert
- Department of Microbiology, Tumor and Cell BiologyKarolinska InstitutetStockholmSweden
| | - Linda‐Gail Bekker
- Institute of Infectious Disease and Molecular MedicineUniversity of Cape TownCape TownSouth Africa
| | - Chris Beyrer
- Department of EpidemiologyCenter for AIDS Research and Center for Public Health and Human RightsJohn Hopkins Bloomberg School of Public HealthBaltimoreMDUSA
| | - Pedro Cahn
- Infectious Diseases UnitJuan A. Fernandez Hospital Buenos AiresCABAArgentina
- Buenos Aires University Medical SchoolBuenos AiresArgentina
- Fundación HuéspedBuenos AiresArgentina
| | - Alexandra Calmy
- Infectious DiseasesGeneva University HospitalGenevaSwitzerland
| | - Beatriz Grinsztejn
- Instituto Nacional de Infectologia Evandro Chagas‐FiocruzFiocruz, Rio de JaneiroBrazil
| | - Andrew Grulich
- Kirby InstituteUniversity of New South WalesSydneyNSWAustralia
| | | | | | - Mona R Loutfy
- Women's College Research InstituteTorontoCanada
- Women's College HospitalTorontoCanada
- Department of MedicineUniversity of TorontoTorontoCanada
| | - Kamal M El Filali
- Infectious Diseases UnitIbn Rochd Universtiy HospitalCasablancaMorocco
| | - Souleymane Mboup
- Institut de Recherche en Santéde Surveillance Epidemiologique et de FormationsDakarSenegal
| | - Julio SG Montaner
- Faculty of MedicineUniversity of British ColumbiaVancouverCanada
- BC Centre for Excellence in HIV/AIDSVancouverCanada
| | - Paula Munderi
- International Association of Providers of AIDS CareKampalaUganda
| | - Vadim Pokrovsky
- Russian Peoples’ Friendship University (RUDN‐ University)MoscowRussian Federation
- Central Research Institute of EpidemiologyFederal Service on Customers’ Rights Protection and Human Well‐being SurveillanceMoscowRussian Federation
| | - Anne‐Mieke Vandamme
- KU LeuvenDepartment of Microbiology and ImmunologyRega Institute for Medical Research, Clinical and Epidemiological VirologyLeuvenBelgium
- Center for Global Health and Tropical MedicineUnidade de MicrobiologiaInstituto de Higiene e Medicina TropicalUniversidade Nova de LisboaLisbonPortugal
| | - Benjamin Young
- International Association of Providers of AIDS CareWashingtonDCUSA
| | - Peter Godfrey‐Faussett
- UNAIDSGenevaSwitzerland
- Department of Infectious and Tropical DiseasesLondon School of Hygiene and Tropical MedicineLondonEngland
| |
Collapse
|
|
8
|
Abstract
: Because HIV is a fast-evolving virus, HIV genomic sequences of several individuals can be used to investigate whether they belong to a transmission network. Since the infamous 'Florida dentist case' in the beginning of the 1990s, phylogenetic analyses has been recurrently used in court settings as a forensic tool in HIV transmission investigations, for example cases where one or more complainants allege that a defendant has unlawfully infected them with HIV. Such cases can arise both in the context of HIV-specific criminal laws - in countries where transmission of HIV infection is specifically criminalized - or in the context of general laws, for example, by applying physical or sexual assault laws to HIV-related cases. Although phylogenetic analysis as a forensic technique for HIV transmission investigations has become common in several countries, the methodologies have not yet been standardized, sometimes giving rise to unwarranted conclusions. In this literature review, we revisit HIV court case investigations published in the scientific literature, as well as the methodological aspects important for the application and standardization of phylogenetic analyses methods as a forensic tool. Phylogenetic methodologies are improving quickly, such that more recently, phylogenetic relatedness, directionality of transmission and timing of nodes in the tree are used to assess whether the phylogenetic transmission analysis is consistent with or contradicting the charges. We find that there has been a lack of consistency between methods used in court case investigations and that it is essential to define guidelines to be used by phylogenetic forensic experts in HIV transmission cases in court.
Collapse
|
|
9
|
HIV-1 Infection in Cyprus, the Eastern Mediterranean European Frontier: A Densely Sampled Transmission Dynamics Analysis from 1986 to 2012. Sci Rep 2018; 8:1702. [PMID: 29374182 PMCID: PMC5786036 DOI: 10.1038/s41598-017-19080-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Accepted: 12/21/2017] [Indexed: 11/09/2022] Open
Abstract
Since HIV-1 treatment is increasingly considered an effective preventionstrategy, it is important to study local HIV-1 epidemics to formulate tailored preventionpolicies. The prevalence of HIV-1 in Cyprus was historically low until 2005. To investigatethe shift in epidemiological trends, we studied the transmission dynamics of HIV-1 in Cyprususing a densely sampled Cypriot HIV-1 transmission cohort that included 85 percent ofHIV-1-infected individuals linked to clinical care between 1986 and 2012 based on detailedclinical, epidemiological, behavioral and HIV-1 genetic information. Subtyping andtransmission cluster reconstruction were performed using maximum likelihood and Bayesianmethods, and the transmission chain network was linked to the clinical, epidemiological andbehavioral data. The results reveal that for the main HIV-1 subtype A1 and B sub-epidemics,young and drug-naïve HIV-1-infected individuals in Cyprus are driving the dynamics of thelocal HIV-1 epidemic. The results of this study provide a better understanding of thedynamics of the HIV-1 infection in Cyprus, which may impact the development of preventionstrategies. Furthermore, this methodology for analyzing densely sampled transmissiondynamics is applicable to other geographic regions to implement effective HIV-1 preventionstrategies in local settings.
Collapse
|
|
10
|
Guthrie JL, Gardy JL. A brief primer on genomic epidemiology: lessons learned from Mycobacterium tuberculosis. Ann N Y Acad Sci 2016; 1388:59-77. [PMID: 28009051 DOI: 10.1111/nyas.13273] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2016] [Revised: 09/02/2016] [Accepted: 09/13/2016] [Indexed: 12/13/2022]
Abstract
Genomics is now firmly established as a technique for the investigation and reconstruction of communicable disease outbreaks, with many genomic epidemiology studies focusing on revealing transmission routes of Mycobacterium tuberculosis. In this primer, we introduce the basic techniques underlying transmission inference from genomic data, using illustrative examples from M. tuberculosis and other pathogens routinely sequenced by public health agencies. We describe the laboratory and epidemiological scenarios under which genomics may or may not be used, provide an introduction to sequencing technologies and bioinformatics approaches to identifying transmission-informative variation and resistance-associated mutations, and discuss how variation must be considered in the light of available clinical and epidemiological information to infer transmission.
Collapse
Affiliation(s)
- Jennifer L Guthrie
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - Jennifer L Gardy
- School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada.,Communicable Disease Prevention and Control Services, British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
| |
Collapse
|
|
11
|
Siljic M, Salemovic D, Cirkovic V, Pesic-Pavlovic I, Ranin J, Todorovic M, Nikolic S, Jevtovic D, Stanojevic M. Forensic application of phylogenetic analyses - Exploration of suspected HIV-1 transmission case. Forensic Sci Int Genet 2016; 27:100-105. [PMID: 28024238 DOI: 10.1016/j.fsigen.2016.12.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2016] [Revised: 12/05/2016] [Accepted: 12/18/2016] [Indexed: 11/28/2022]
Abstract
Transmission of human immunodeficiency virus (HIV) between individuals may have important legal implications and therefore may come to require forensic investigation based upon phylogenetic analysis. In criminal trials results of phylogenetic analyses have been used as evidence of responsibility for HIV transmission. In Serbia, as in many countries worldwide, exposure and deliberate transmission of HIV are criminalized. We present the results of applying state of the art phylogenetic analyses, based on pol and env genetic sequences, in exploration of suspected HIV transmission among three subjects: a man and two women, with presumed assumption of transmission direction from one woman to a man. Phylogenetic methods included relevant neighbor-joining (NJ), maximum likelihood (ML) and Bayesian methods of phylogenetic trees reconstruction and hypothesis testing, that has been shown to be the most sensitive for the reconstruction of epidemiological links mostly from sexually infected individuals. End-point limiting-dilution PCR (EPLD-PCR) assay, generating the minimum of 10 sequences per genetic region per subject, was performed to assess HIV quasispecies distribution and to explore the direction of HIV transmission between three subjects. Phylogenetic analysis revealed that the viral sequences from the three subjects were more genetically related to each other than to other strains circulating in the same area with the similar epidemiological profile, forming strongly supported transmission chain, which could be in favour of a priori hypothesis of one of the women infecting the man. However, in the EPLD based phylogenetic trees for both pol and env genetic region, viral sequences of one subject (man) were paraphyletic to those of two other subjects (women), implying the direction of transmission opposite to the a priori assumption. The dated tree in our analysis confirmed the clustering pattern of query sequences. Still, in the context of unsampled sequences and inherent limitations of the applied methods, we cannot unambiguously prove that HIV-1 transmission occurred directly between two individuals. Further exploration of the known and suspected transmission cases is needed in order to define methodologies and establish their reliability.
Collapse
Affiliation(s)
- Marina Siljic
- Institute of Microbiology and Immunology, University of Belgrade School of Medicine, Belgrade, Serbia
| | - Dubravka Salemovic
- Infectious and Tropical Diseases University Hospital, Clinical Center Serbia, HIV/AIDS Unit, Belgrade, Serbia
| | - Valentina Cirkovic
- Institute of Microbiology and Immunology, University of Belgrade School of Medicine, Belgrade, Serbia
| | - Ivana Pesic-Pavlovic
- Virology Laboratory, Microbiology Department, Clinical Center Serbia, Belgrade, Serbia
| | - Jovan Ranin
- Institute of Microbiology and Immunology, University of Belgrade School of Medicine, Belgrade, Serbia; Infectious and Tropical Diseases University Hospital, Clinical Center Serbia, HIV/AIDS Unit, Belgrade, Serbia
| | - Marija Todorovic
- Institute of Microbiology and Immunology, University of Belgrade School of Medicine, Belgrade, Serbia
| | - Slobodan Nikolic
- Institute of Forensic Medicine, University of Belgrade School of Medicine, Belgrade, Serbia
| | - Djordje Jevtovic
- Institute of Microbiology and Immunology, University of Belgrade School of Medicine, Belgrade, Serbia; Infectious and Tropical Diseases University Hospital, Clinical Center Serbia, HIV/AIDS Unit, Belgrade, Serbia
| | - Maja Stanojevic
- Institute of Microbiology and Immunology, University of Belgrade School of Medicine, Belgrade, Serbia.
| |
Collapse
|
|
12
|
Paraskevis D, Nikolopoulos GK, Magiorkinis G, Hodges-Mameletzis I, Hatzakis A. The application of HIV molecular epidemiology to public health. INFECTION GENETICS AND EVOLUTION 2016; 46:159-168. [PMID: 27312102 DOI: 10.1016/j.meegid.2016.06.021] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2016] [Revised: 06/06/2016] [Accepted: 06/07/2016] [Indexed: 02/02/2023]
Abstract
HIV is responsible for one of the largest viral pandemics in human history. Despite a concerted global response for prevention and treatment, the virus persists. Thus, urgent public health action, utilizing novel interventions, is needed to prevent future transmission events, critical to eliminating HIV. For public health planning to prove effective and successful, we need to understand the dynamics of regional epidemics and to intervene appropriately. HIV molecular epidemiology tools as implemented in phylogenetic, phylodynamic and phylogeographic analyses have proven to be powerful tools in public health planning across many studies. Numerous applications with HIV suggest that molecular methods alone or in combination with mathematical modelling can provide inferences about the transmission dynamics, critical epidemiological parameters (prevalence, incidence, effective number of infections, Re, generation times, time between infection and diagnosis), or the spatiotemporal characteristics of epidemics. Molecular tools have been used to assess the impact of an intervention and outbreak investigation which are of great public health relevance. In some settings, molecular sequence data may be more readily available than HIV surveillance data, and can therefore allow for molecular analyses to be conducted more easily. Nonetheless, classic methods have an integral role in monitoring and evaluation of public health programmes, and should supplement emerging techniques from the field of molecular epidemiology. Importantly, molecular epidemiology remains a promising approach in responding to viral diseases.
Collapse
Affiliation(s)
- D Paraskevis
- Department of Hygiene Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece.
| | - G K Nikolopoulos
- Hellenic Center for Diseases Control and Prevention, Maroussi, Greece
| | - G Magiorkinis
- Department of Hygiene Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece; Department of Zoology, University of Oxford, South Parks Road, OX1 3PS, Oxford, United Kingdom
| | | | - A Hatzakis
- Hellenic Center for Diseases Control and Prevention, Maroussi, Greece
| |
Collapse
|
|
13
|
Montoya V, Olmstead A, Tang P, Cook D, Janjua N, Grebely J, Jacka B, Poon AFY, Krajden M. Deep sequencing increases hepatitis C virus phylogenetic cluster detection compared to Sanger sequencing. INFECTION GENETICS AND EVOLUTION 2016; 43:329-37. [PMID: 27282472 DOI: 10.1016/j.meegid.2016.06.015] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2016] [Revised: 06/03/2016] [Accepted: 06/04/2016] [Indexed: 01/17/2023]
Abstract
Effective surveillance and treatment strategies are required to control the hepatitis C virus (HCV) epidemic. Phylogenetic analyses are powerful tools for reconstructing the evolutionary history of viral outbreaks and identifying transmission clusters. These studies often rely on Sanger sequencing which typically generates a single consensus sequence for each infected individual. For rapidly mutating viruses such as HCV, consensus sequencing underestimates the complexity of the viral quasispecies population and could therefore generate different phylogenetic tree topologies. Although deep sequencing provides a more detailed quasispecies characterization, in-depth phylogenetic analyses are challenging due to dataset complexity and computational limitations. Here, we apply deep sequencing to a characterized population to assess its ability to identify phylogenetic clusters compared with consensus Sanger sequencing. For deep sequencing, a sample specific threshold determined by the 50th percentile of the patristic distance distribution for all variants within each individual was used to identify clusters. Among seven patristic distance thresholds tested for the Sanger sequence phylogeny ranging from 0.005-0.06, a threshold of 0.03 was found to provide the maximum balance between positive agreement (samples in a cluster) and negative agreement (samples not in a cluster) relative to the deep sequencing dataset. From 77 HCV seroconverters, 10 individuals were identified in phylogenetic clusters using both methods. Deep sequencing analysis identified an additional 4 individuals and excluded 8 other individuals relative to Sanger sequencing. The application of this deep sequencing approach could be a more effective tool to understand onward HCV transmission dynamics compared with Sanger sequencing, since the incorporation of minority sequence variants improves the discrimination of phylogenetically linked clusters.
Collapse
Affiliation(s)
- Vincent Montoya
- BC Centre for Disease Control, Vancouver, BC, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Andrea Olmstead
- BC Centre for Disease Control, Vancouver, BC, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | | | - Darrel Cook
- BC Centre for Disease Control, Vancouver, BC, Canada
| | - Naveed Janjua
- BC Centre for Disease Control, Vancouver, BC, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Jason Grebely
- The Kirby Institute, UNSW Australia, Sydney, NSW, Australia
| | - Brendan Jacka
- The Kirby Institute, UNSW Australia, Sydney, NSW, Australia
| | - Art F Y Poon
- BC Centre for Excellence in HIV/AIDS, St Paul's Hospital, Vancouver, BC, Canada
| | - Mel Krajden
- BC Centre for Disease Control, Vancouver, BC, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada.
| |
Collapse
|
|
14
|
Abstract
Although the use of phylogenetic trees in epidemiological investigations has become commonplace, their epidemiological interpretation has not been systematically evaluated. Here, we use an HIV-1 within-host coalescent model to probabilistically evaluate transmission histories of two epidemiologically linked hosts. Previous critique of phylogenetic reconstruction has claimed that direction of transmission is difficult to infer, and that the existence of unsampled intermediary links or common sources can never be excluded. The phylogenetic relationship between the HIV populations of epidemiologically linked hosts can be classified into six types of trees, based on cladistic relationships and whether the reconstruction is consistent with the true transmission history or not. We show that the direction of transmission and whether unsampled intermediary links or common sources existed make very different predictions about expected phylogenetic relationships: (i) Direction of transmission can often be established when paraphyly exists, (ii) intermediary links can be excluded when multiple lineages were transmitted, and (iii) when the sampled individuals' HIV populations both are monophyletic a common source was likely the origin. Inconsistent results, suggesting the wrong transmission direction, were generally rare. In addition, the expected tree topology also depends on the number of transmitted lineages, the sample size, the time of the sample relative to transmission, and how fast the diversity increases after infection. Typically, 20 or more sequences per subject give robust results. We confirm our theoretical evaluations with analyses of real transmission histories and discuss how our findings should aid in interpreting phylogenetic results.
Collapse
|
|
15
|
Rossi LMG, Escobar-Gutierrez A, Rahal P. Advanced molecular surveillance of hepatitis C virus. Viruses 2015; 7:1153-88. [PMID: 25781918 PMCID: PMC4379565 DOI: 10.3390/v7031153] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2014] [Revised: 02/05/2015] [Accepted: 02/20/2015] [Indexed: 12/12/2022] Open
Abstract
Hepatitis C virus (HCV) infection is an important public health problem worldwide. HCV exploits complex molecular mechanisms, which result in a high degree of intrahost genetic heterogeneity. This high degree of variability represents a challenge for the accurate establishment of genetic relatedness between cases and complicates the identification of sources of infection. Tracking HCV infections is crucial for the elucidation of routes of transmission in a variety of settings. Therefore, implementation of HCV advanced molecular surveillance (AMS) is essential for disease control. Accounting for virulence is also important for HCV AMS and both viral and host factors contribute to the disease outcome. Therefore, HCV AMS requires the incorporation of host factors as an integral component of the algorithms used to monitor disease occurrence. Importantly, implementation of comprehensive global databases and data mining are also needed for the proper study of the mechanisms responsible for HCV transmission. Here, we review molecular aspects associated with HCV transmission, as well as the most recent technological advances used for virus and host characterization. Additionally, the cornerstone discoveries that have defined the pathway for viral characterization are presented and the importance of implementing advanced HCV molecular surveillance is highlighted.
Collapse
Affiliation(s)
- Livia Maria Gonçalves Rossi
- Department of Biology, Institute of Bioscience, Language and Exact Science, Sao Paulo State University, Sao Jose do Rio Preto, SP 15054-000, Brazil.
| | | | - Paula Rahal
- Department of Biology, Institute of Bioscience, Language and Exact Science, Sao Paulo State University, Sao Jose do Rio Preto, SP 15054-000, Brazil.
| |
Collapse
|
|
16
|
Preciado MV, Valva P, Escobar-Gutierrez A, Rahal P, Ruiz-Tovar K, Yamasaki L, Vazquez-Chacon C, Martinez-Guarneros A, Carpio-Pedroza JC, Fonseca-Coronado S, Cruz-Rivera M. Hepatitis C virus molecular evolution: Transmission, disease progression and antiviral therapy. World J Gastroenterol 2014; 20:15992-16013. [PMID: 25473152 PMCID: PMC4239486 DOI: 10.3748/wjg.v20.i43.15992] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2014] [Revised: 06/22/2014] [Accepted: 08/28/2014] [Indexed: 02/06/2023] Open
Abstract
Hepatitis C virus (HCV) infection represents an important public health problem worldwide. Reduction of HCV morbidity and mortality is a current challenge owned to several viral and host factors. Virus molecular evolution plays an important role in HCV transmission, disease progression and therapy outcome. The high degree of genetic heterogeneity characteristic of HCV is a key element for the rapid adaptation of the intrahost viral population to different selection pressures (e.g., host immune responses and antiviral therapy). HCV molecular evolution is shaped by different mechanisms including a high mutation rate, genetic bottlenecks, genetic drift, recombination, temporal variations and compartmentalization. These evolutionary processes constantly rearrange the composition of the HCV intrahost population in a staging manner. Remarkable advances in the understanding of the molecular mechanism controlling HCV replication have facilitated the development of a plethora of direct-acting antiviral agents against HCV. As a result, superior sustained viral responses have been attained. The rapidly evolving field of anti-HCV therapy is expected to broad its landscape even further with newer, more potent antivirals, bringing us one step closer to the interferon-free era.
Collapse
|
|
17
|
Vrancken B, Rambaut A, Suchard MA, Drummond A, Baele G, Derdelinckx I, Van Wijngaerden E, Vandamme AM, Van Laethem K, Lemey P. The genealogical population dynamics of HIV-1 in a large transmission chain: bridging within and among host evolutionary rates. PLoS Comput Biol 2014; 10:e1003505. [PMID: 24699231 PMCID: PMC3974631 DOI: 10.1371/journal.pcbi.1003505] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2013] [Accepted: 01/15/2014] [Indexed: 11/23/2022] Open
Abstract
Transmission lies at the interface of human immunodeficiency virus type 1 (HIV-1) evolution within and among hosts and separates distinct selective pressures that impose differences in both the mode of diversification and the tempo of evolution. In the absence of comprehensive direct comparative analyses of the evolutionary processes at different biological scales, our understanding of how fast within-host HIV-1 evolutionary rates translate to lower rates at the between host level remains incomplete. Here, we address this by analyzing pol and env data from a large HIV-1 subtype C transmission chain for which both the timing and the direction is known for most transmission events. To this purpose, we develop a new transmission model in a Bayesian genealogical inference framework and demonstrate how to constrain the viral evolutionary history to be compatible with the transmission history while simultaneously inferring the within-host evolutionary and population dynamics. We show that accommodating a transmission bottleneck affords the best fit our data, but the sparse within-host HIV-1 sampling prevents accurate quantification of the concomitant loss in genetic diversity. We draw inference under the transmission model to estimate HIV-1 evolutionary rates among epidemiologically-related patients and demonstrate that they lie in between fast intra-host rates and lower rates among epidemiologically unrelated individuals infected with HIV subtype C. Using a new molecular clock approach, we quantify and find support for a lower evolutionary rate along branches that accommodate a transmission event or branches that represent the entire backbone of transmitted lineages in our transmission history. Finally, we recover the rate differences at the different biological scales for both synonymous and non-synonymous substitution rates, which is only compatible with the ‘store and retrieve’ hypothesis positing that viruses stored early in latently infected cells preferentially transmit or establish new infections upon reactivation. Since its discovery three decades ago, the HIV epidemic has unfolded into one of the most devastating pandemics in human history. When HIV replication cannot be completely inhibited, the fast-evolving retrovirus continuously evades intra-host immune and drug selective pressure, but diversifies according to more neutral epidemiological dynamics at the interhost level. Limited evidence suggests that the virus may evolve faster in a single host than in a population of hosts, and various hypotheses have been put forward to explain this phenomenon. Here, we develop a new computational approach aimed at integrating host transmission information with pathogen genealogical reconstructions. We apply this approach to comprehensive sequence data sets sampled from a large HIV-1 subtype C transmission chain, and in addition to providing several insights into the reconstruction of HIV-1 transmissions histories and its associated population dynamics, we find that transmission decreases the HIV-1 evolutionary rate. The fact that we also identify this decline for substitutions that do not alter amino acid substitutions provides evidence against hypotheses that invoke selection forces. Instead, our findings support earlier reports that new infections start preferentially with less evolved variants, which may be stored in latently infected cells, and this may vary among different HIV-1 subtypes.
Collapse
Affiliation(s)
- Bram Vrancken
- Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium
- * E-mail:
| | - Andrew Rambaut
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Marc A. Suchard
- Department of Biomathematics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, California, United States of America
- Department of Human Genetics, David Geffen School of Medicine at UCLA, University of California, Los Angeles, Los Angeles, California, United States of America
- Department of Biostatistics, UCLA Fielding School of Public Health, University of California, Los Angeles Los Angeles, California, United States of America
| | - Alexei Drummond
- Allan Wilson Centre for Molecular Ecology and Evolution, University of Auckland, Auckland, New Zealand
| | - Guy Baele
- Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium
| | | | | | - Anne-Mieke Vandamme
- Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium
- Centro de Malária e Outras Doenças Tropicais Instituto de Higiene e Medicina Tropical and Unidade de Microbiologia, Universidade Nova de Lisboa, Lisboa, Portugal
| | - Kristel Van Laethem
- Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium
| | - Philippe Lemey
- Department of Microbiology and Immunology, Rega Institute, KU Leuven, Leuven, Belgium
| |
Collapse
|
|
18
|
Field N, Cohen T, Struelens MJ, Palm D, Cookson B, Glynn JR, Gallo V, Ramsay M, Sonnenberg P, MacCannell D, Charlett A, Egger M, Green J, Vineis P, Abubakar I. Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID): an extension of the STROBE statement. THE LANCET. INFECTIOUS DISEASES 2014; 14:341-52. [DOI: 10.1016/s1473-3099(13)70324-4] [Citation(s) in RCA: 89] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
|
|
19
|
Brooks JI, Niznick H, Ofner M, Merks H, Angel JB. Local phylogenetic analysis identifies distinct trends in transmitted HIV drug resistance: implications for public health interventions. BMC Infect Dis 2013; 13:509. [PMID: 24171696 PMCID: PMC3816547 DOI: 10.1186/1471-2334-13-509] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2013] [Accepted: 10/17/2013] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND HIV transmitted drug resistance (TDR) surveillance is usually conducted by sampling from a large population. However, overall TDR prevalence results may be inaccurate for many individual clinical setting. We analyzed HIV genotypes at a tertiary care setting in Ottawa, Ontario in order to evaluate local TDR patterns among sub-populations. METHOD Genotyping reports were digitized from ART naïve patients followed at the Immunodeficiency Clinic at the Ottawa Hospital, between 2008 and 2010. Quality controlled, digitized sequence data were assessed for TDR using the Stanford HIV Database. Patient characteristics were analyzed according to TDR patterns. Finally, a phylogenetic tree was constructed to elucidate the observed pattern of HIV TDR. RESULTS Among the 155 clinic patients there was no statistically significantly difference in demographics as compared to the Ontario provincial HIV population. The clinic prevalence of TDR was 12.3%; however, in contrast to the data from Ontario, TDR patterns were inverted with a 21% prevalence among MSM and 5.5% among IDU. Furthermore, nearly 80% of the observed TDR was a D67N/K219Q pattern with 87% of these infections arising from a distinct phylogenetic cluster. CONCLUSIONS Local patterns of TDR were distinct to what had been observed provincially. Phylogenetic analysis uncovered a cluster of related infections among MSM that appeared more likely to be recent infections. Results support a paradigm of routine local TDR surveillance to identify the sub-populations under care. Furthermore, the routine application of phylogenetic analysis in the TDR surveillance context provides insights into how best to target prevention strategies; and how to correctly measure outcomes.
Collapse
Affiliation(s)
- James I Brooks
- National HIV & Retrovirology Laboratories, Public Health Agency of Canada, Ottawa, Canada.
| | | | | | | | | |
Collapse
|
|
20
|
Vandamme AM, Pybus OG. Viral phylogeny in court: the unusual case of the Valencian anesthetist. BMC Biol 2013; 11:83. [PMID: 24059471 PMCID: PMC3717106 DOI: 10.1186/1741-7007-11-83] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2013] [Accepted: 07/11/2013] [Indexed: 12/17/2022] Open
Abstract
A large and complex outbreak of hepatitis C virus in Valencia, Spain that began 25 years ago led to the prosecution and conviction of an anesthetist who was accused of infecting hundreds of his patients. Evolutionary analyses of viral gene sequences were presented as evidence in the trial, and these are now described in detail by González-Candelas and colleagues in a paper published in BMC Biology. Their study illustrates the challenges and opportunities that arise from the use of phylogenetic inference in criminal trials concerning virus transmission. See research article: http://www.biomedcentral.com/1741-7007/11/76
Collapse
Affiliation(s)
- Anne-Mieke Vandamme
- Laboratory for Clinical and Epidemiological Virology, Rega Institute for Medical Research, Department of Microbiology and Immunology, University of Leuven, Leuven, Belgium.
| | | |
Collapse
|
|
21
|
Beloukas A, Magiorkinis E, Magiorkinis G, Zavitsanou A, Karamitros T, Hatzakis A, Paraskevis D. Assessment of phylogenetic sensitivity for reconstructing HIV-1 epidemiological relationships. Virus Res 2012; 166:54-60. [DOI: 10.1016/j.virusres.2012.03.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2011] [Revised: 03/02/2012] [Accepted: 03/04/2012] [Indexed: 12/27/2022]
|