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Osman R, Dema E, David A, Hughes G, Field N, Cole M, Didelot X, Saunders J. Understanding the potential role of whole genome sequencing (WGS) in managing patients with gonorrhoea: A systematic review of WGS use on human pathogens in individual patient care. J Infect 2024; 88:106168. [PMID: 38670270 DOI: 10.1016/j.jinf.2024.106168] [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: 01/10/2024] [Revised: 04/19/2024] [Accepted: 04/20/2024] [Indexed: 04/28/2024]
Abstract
OBJECTIVES The utility of whole genome sequencing (WGS) to inform sexually transmitted infection (STI) patient management is unclear. Timely WGS data might support clinical management of STIs by characterising epidemiological links and antimicrobial resistance profiles. We conducted a systematic review of clinical application of WGS to any human pathogen that may be transposable to gonorrhoea. METHODS We searched six databases for articles published between 01/01/2010-06/02/2023 that reported on real/near real-time human pathogen WGS to inform clinical intervention. All article types from all settings were included. Findings were analysed using narrative synthesis. RESULTS We identified 12,179 articles, of which eight reported applications to inform tuberculosis (n = 7) and gonorrhoea (n = 1) clinical patient management. WGS data were successfully used as an adjunct to clinical and epidemiological data to enhance contact-tracing (n = 2), inform antimicrobial therapy (n = 5) and identify cross-contamination (n = 1). WGS identified gonorrhoea transmission chains that were not established via partner notification. Future applications could include insights into pathogen exposure detected within sexual networks for targeted patient management. CONCLUSIONS While there was some evidence of WGS use to provide individualised tuberculosis and gonorrhoea treatment, the eight identified studies contained few participants. Future research should focus on testing WGS intervention effectiveness and examining ethical considerations of STI WGS use.
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Affiliation(s)
- Roeann Osman
- Institute for Global Health, University College London (UCL), Mortimer Market Centre, London WC1E 6JB, United Kingdom; National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Blood Borne and Sexually Transmitted Infections at University College London (UCL), London, United Kingdom.
| | - Emily Dema
- Institute for Global Health, University College London (UCL), Mortimer Market Centre, London WC1E 6JB, United Kingdom
| | - Alexandra David
- Institute for Global Health, University College London (UCL), Mortimer Market Centre, London WC1E 6JB, United Kingdom
| | - Gwenda Hughes
- Department of Infectious Disease Epidemiology and Dynamics, London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT, United Kingdom
| | - Nigel Field
- Institute for Global Health, University College London (UCL), Mortimer Market Centre, London WC1E 6JB, United Kingdom
| | - Michelle Cole
- UK Health Security Agency (UK HSA), 61 Colindale Avenue, London NW9 5EQ, United Kingdom
| | - Xavier Didelot
- School of Life Sciences and Department of Statistics, University of Warwick, Coventry CV4 7AL, United Kingdom; National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Genomics and Enabling Data at Warwick University, United Kingdom
| | - John Saunders
- Institute for Global Health, University College London (UCL), Mortimer Market Centre, London WC1E 6JB, United Kingdom; National Institute for Health Research (NIHR) Health Protection Research Unit (HPRU) in Blood Borne and Sexually Transmitted Infections at University College London (UCL), London, United Kingdom; UK Health Security Agency (UK HSA), 61 Colindale Avenue, London NW9 5EQ, United Kingdom
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2
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Nascimento FF, Mehta SR, Little SJ, Volz EM. Assessing transmission attribution risk from simulated sequencing data in HIV molecular epidemiology. AIDS 2024; 38:865-873. [PMID: 38126363 PMCID: PMC10994139 DOI: 10.1097/qad.0000000000003820] [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: 03/07/2023] [Revised: 12/08/2023] [Accepted: 12/14/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND HIV molecular epidemiology (ME) is the analysis of sequence data together with individual-level clinical, demographic, and behavioral data to understand HIV epidemiology. The use of ME has raised concerns regarding identification of the putative source in direct transmission events. This could result in harm ranging from stigma to criminal prosecution in some jurisdictions. Here we assessed the risks of ME using simulated HIV genetic sequencing data. METHODS We simulated social networks of men-who-have-sex-with-men, calibrating the simulations to data from San Diego. We used these networks to simulate consensus and next-generation sequence (NGS) data to evaluate the risks of identifying direct transmissions using different HIV sequence lengths, and population sampling depths. To identify the source of transmissions, we calculated infector probability and used phyloscanner software for the analysis of consensus and NGS data, respectively. RESULTS Consensus sequence analyses showed that the risk of correctly inferring the source (direct transmission) within identified transmission pairs was very small and independent of sampling depth. Alternatively, NGS analyses showed that identification of the source of a transmission was very accurate, but only for 6.5% of inferred pairs. False positive transmissions were also observed, where one or more unobserved intermediaries were present when compared to the true network. CONCLUSION Source attribution using consensus sequences rarely infers direct transmission pairs with high confidence but is still useful for population studies. In contrast, source attribution using NGS data was much more accurate in identifying direct transmission pairs, but for only a small percentage of transmission pairs analyzed.
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Affiliation(s)
- Fabrícia F. Nascimento
- MRC Centre for Global Infectious Disease Analysis and the Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Sanjay R. Mehta
- Division of Infectious Diseases, University of California San Diego, San Diego, CA, USA
| | - Susan J. Little
- Division of Infectious Diseases, University of California San Diego, San Diego, CA, USA
| | - Erik M. Volz
- MRC Centre for Global Infectious Disease Analysis and the Department of Infectious Disease Epidemiology, Imperial College London, London, UK
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3
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Obeng BM, Kelleher AD, Di Giallonardo F. Molecular epidemiology to aid virtual elimination of HIV transmission in Australia. Virus Res 2024; 341:199310. [PMID: 38185332 PMCID: PMC10825322 DOI: 10.1016/j.virusres.2024.199310] [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: 11/03/2023] [Revised: 01/03/2024] [Accepted: 01/04/2024] [Indexed: 01/09/2024]
Abstract
The Global UNAIDS 95/95/95 targets aim to increase the percentage of persons who know their HIV status, receive antiretroviral therapy, and have achieved viral suppression. Achieving these targets requires efforts to improve the public health response to increase access to care for those living with HIV, identify those yet undiagnosed with HIV early, and increase access to prevention for those most at risk of HIV acquisition. HIV infections in Australia are among the lowest globally having recorded significant declines in new diagnoses in the last decade. However, the HIV epidemic has changed with an increasing proportion of newly diagnosed infections among those born outside Australia observed in the last five years. Thus, the current prevention efforts are not enough to achieve the UNAIDS targets and virtual elimination across all population groups. We believe both are possible by including molecular epidemiology in the public health response. Molecular epidemiology methods have been crucial in the field of HIV prevention, particularly in demonstrating the efficacy of treatment as prevention. Cluster detection using molecular epidemiology can provide opportunities for the real-time detection of new outbreaks before they grow, and cluster detection programs are now part of the public health response in the USA and Canada. Here, we review what molecular epidemiology has taught us about HIV evolution and spread. We summarize how we can use this knowledge to improve public health measures by presenting case studies from the USA and Canada. We discuss the successes and challenges of current public health programs in Australia, and how we could use cluster detection as an add-on to identify gaps in current prevention measures easier and respond quicker to growing clusters. Lastly, we raise important ethical and legal challenges that need to be addressed when HIV genotypic data is used in combination with personal data.
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Affiliation(s)
- Billal M Obeng
- The Kirby Institute, University of New South Wales, Sydney, Australia
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4
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Hossain MI, Asha AT, Hossain MA, Mahmud S, Chowdhury K, Mohiuddin RB, Nahar N, Sarker S, Napis S, Hossain MS, Mohiuddin A. Investigating the role of hypothetical protein (AAB33144.1) in HIV-1 virus pathogenicity: A comparative study with FDA-Approved inhibitor compounds through In silico analysis and molecular docking. Heliyon 2024; 10:e23183. [PMID: 38163140 PMCID: PMC10755284 DOI: 10.1016/j.heliyon.2023.e23183] [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: 11/18/2023] [Accepted: 11/28/2023] [Indexed: 01/03/2024] Open
Abstract
Aim and objective Due to the a lot of unexplored proteins in HIV-1, this research aimed to explore the functional roles of a hypothetical protein (AAB33144.1) that might play a key role in HIV-1 pathogenicity. Methods The homologous protein was identified along with building and validating the 3D structure by searching several bioinformatics tools. Results Retroviral aspartyl protease and retropepsin like functional domains and motifs, folding pattern (cupredoxins), and subcellular localization in cytoplasmic membrane were determined as biological activity. Besides, the functional annotation revealed that the chosen hypothetical protein possessed protease-like activity. To validate our generated protein 3D structure, molecular docking was performed with five compounds where nelfinavir showed (-8.2 kcal/mol) best binding affinity against HXB2 viral protease (PDB ID: 7SJX) and main protease (PDB ID: 4EYR) protein. Conclusions This study suggests that the annotated hypothetical protein related to protease action, which may be useful in viral genetics and drug discovery.
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Affiliation(s)
- Md. Imran Hossain
- Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, 1902, Bangladesh
| | - Anika Tabassum Asha
- Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, 1902, Bangladesh
| | - Md. Arju Hossain
- Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, 1902, Bangladesh
| | - Shahin Mahmud
- Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, 1902, Bangladesh
| | - Kamal Chowdhury
- Biology Department, Claflin University, 400 Magnolia St, Orangeburg, SC 29115, USA
| | - Ramisa Binti Mohiuddin
- Department of Pharmacy, Mawlana Bhashani Science and Technology University, Tangail, 1902, Bangladesh
| | - Nazneen Nahar
- Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, 1902, Bangladesh
| | - Saborni Sarker
- Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, 1902, Bangladesh
| | - Suhaimi Napis
- Department of Cell and Molecular Biology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400 Serdang, Selangor D.E., Malaysia
| | - Md Sanower Hossain
- Centre for Sustainability of Mineral and Resource Recovery Technology (Pusat SMaRRT), Universiti Malaysia Pahang Al-Sultan Abdullah, Kuantan 26300, Malaysia
| | - A.K.M. Mohiuddin
- Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, 1902, Bangladesh
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5
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Goldberg EE, Lundgren EJ, Romero-Severson EO, Leitner T. Inferring Viral Transmission Time from Phylogenies for Known Transmission Pairs. Mol Biol Evol 2024; 41:msad282. [PMID: 38149995 PMCID: PMC10776241 DOI: 10.1093/molbev/msad282] [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: 09/12/2023] [Revised: 12/15/2023] [Accepted: 12/21/2023] [Indexed: 12/28/2023] Open
Abstract
When the time of an HIV transmission event is unknown, methods to identify it from virus genetic data can reveal the circumstances that enable transmission. We developed a single-parameter Markov model to infer transmission time from an HIV phylogeny constructed of multiple virus sequences from people in a transmission pair. Our method finds the statistical support for transmission occurring in different possible time slices. We compared our time-slice model results to previously described methods: a tree-based logical transmission interval, a simple parsimony-like rules-based method, and a more complex coalescent model. Across simulations with multiple transmitted lineages, different transmission times relative to the source's infection, and different sampling times relative to transmission, we found that overall our time-slice model provided accurate and narrower estimates of the time of transmission. We also identified situations when transmission time or direction was difficult to estimate by any method, particularly when transmission occurred long after the source was infected and when sampling occurred long after transmission. Applying our model to real HIV transmission pairs showed some agreement with facts known from the case investigations. We also found, however, that uncertainty on the inferred transmission time was driven more by uncertainty from time calibration of the phylogeny than from the model inference itself. Encouragingly, comparable performance of the Markov time-slice model and the coalescent model-which make use of different information within a tree-suggests that a new method remains to be described that will make full use of the topology and node times for improved transmission time inference.
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Affiliation(s)
- Emma E Goldberg
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Erik J Lundgren
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, USA
| | | | - Thomas Leitner
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, USA
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6
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Goldberg EE, Lundgren EJ, Romero-Severson EO, Leitner T. Inferring viral transmission time from phylogenies for known transmission pairs. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.12.557404. [PMID: 37745490 PMCID: PMC10515827 DOI: 10.1101/2023.09.12.557404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
When the time of an HIV transmission event is unknown, methods to identify it from virus genetic data can reveal the circumstances that enable transmission. We developed a single-parameter Markov model to infer transmission time from an HIV phylogeny constructed of multiple virus sequences from people in a transmission pair. Our method finds the statistical support for transmission occurring in different possible time slices. We compared our time-slice model results to previously-described methods: a tree-based logical transmission interval, a simple parsimony-like rules-based method, and a more complex coalescent model. Across simulations with multiple transmitted lineages, different transmission times relative to the source's infection, and different sampling times relative to transmission, we found that overall our time-slice model provided accurate and narrower estimates of the time of transmission. We also identified situations when transmission time or direction was difficult to estimate by any method, particularly when transmission occurred long after the source was infected and when sampling occurred long after transmission. Applying our model to real HIV transmission pairs showed some agreement with facts known from the case investigations. We also found, however, that uncertainty on the inferred transmission time was driven more by uncertainty from time-calibration of the phylogeny than from the model inference itself. Encouragingly, comparable performance of the Markov time-slice model and the coalescent model-which make use of different information within a tree-suggests that a new method remains to be described that will make full use of the topology and node times for improved transmission time inference.
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Affiliation(s)
- Emma E. Goldberg
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos NM, USA
| | - Erik J. Lundgren
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos NM, USA
| | | | - Thomas Leitner
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos NM, USA
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7
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Milne R, Patch C. Ethical Challenges Associated with Pathogen and Host Genetics in Infectious Disease. New Bioeth 2023; 29:24-36. [PMID: 35972296 DOI: 10.1080/20502877.2022.2109697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
Abstract
The Covid-19 pandemic has demonstrated the potential of genomic technologies for the detection and surveillance of infectious diseases. Pathogen genomics is likely to play a major role in the future of research and clinical implementation of genomic technologies. However, unlike human genetics, the specific ethical and social challenges associated with the implementation of infectious disease genomics has received comparatively little attention. In this paper, we contribute to this literature, focusing on the potential consequences for individuals and communities of the use of these technologies. We concentrate on areas of challenges related to privacy, stigma, discrimination and the return of results in the cases of the surveillance of known pathogens, metagenomics and host genomics.
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Affiliation(s)
- Richard Milne
- Engagement and Society, Wellcome Connecting Science, Hinxton, UK.,Kavli Centre for Ethics, Science and the Public, University of Cambridge, Cambridge, UK
| | - Christine Patch
- Engagement and Society, Wellcome Connecting Science, Hinxton, UK
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8
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Comas I, Cancino-Muñoz I, Mariner-Llicer C, Goig GA, Ruiz-Hueso P, Francés-Cuesta C, García-González N, González-Candelas F. Use of next generation sequencing technologies for the diagnosis and epidemiology of infectious diseases. Enferm Infecc Microbiol Clin 2021; 38 Suppl 1:32-38. [PMID: 32111363 DOI: 10.1016/j.eimc.2020.02.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
For the first time, next generation sequencing technologies provide access to genomic information at a price and scale that allow their implementation in routine clinical practice and epidemiology. While there are still many obstacles to their implementation, there are also multiple examples of their major advantages compared with previous methods. Their main advantage is that a single determination allows epidemiological information on the causative microorganism to be obtained simultaneously, as well as its resistance profile, although these advantages vary according to the pathogen under study. This review discusses several examples of the clinical and epidemiological use of next generation sequencing applied to complete genomes and microbiomes and reflects on its future in clinical practice.
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Affiliation(s)
- Iñaki Comas
- Instituto de Biomedicina de Valencia, IBV-CSIC, Valencia, España; CIBER en Epidemiología y Salud Pública, Valencia, España.
| | | | | | - Galo A Goig
- Instituto de Biomedicina de Valencia, IBV-CSIC, Valencia, España
| | - Paula Ruiz-Hueso
- Unidad Mixta "Infección y Salud Pública" FISABIO-Universitat de València, Instituto de Biología Integrativa de Sistemas, I2SysBio (CSIC-UV), Valencia, España
| | - Carlos Francés-Cuesta
- Unidad Mixta "Infección y Salud Pública" FISABIO-Universitat de València, Instituto de Biología Integrativa de Sistemas, I2SysBio (CSIC-UV), Valencia, España
| | - Neris García-González
- Unidad Mixta "Infección y Salud Pública" FISABIO-Universitat de València, Instituto de Biología Integrativa de Sistemas, I2SysBio (CSIC-UV), Valencia, España
| | - Fernando González-Candelas
- CIBER en Epidemiología y Salud Pública, Valencia, España; Unidad Mixta "Infección y Salud Pública" FISABIO-Universitat de València, Instituto de Biología Integrativa de Sistemas, I2SysBio (CSIC-UV), Valencia, España
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9
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Zhang J, Fan Q, Luo M, Yao J, Pan X, Li X. Phylogenetic evidence of HIV-1 transmission linkage between two men who have sex with men. Virol J 2021; 18:106. [PMID: 34059082 PMCID: PMC8166102 DOI: 10.1186/s12985-021-01573-5] [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: 02/17/2021] [Accepted: 05/11/2021] [Indexed: 11/10/2022] Open
Abstract
Background In China, an HIV-infected man (complainant; P2) alleged that another man (defendant; P1) had unlawfully infected him with HIV through unprotected homosexual contact in 2018. Methods We employed epidemiological, serological and phylogenetic analyses to investigate the transmission linkage between two men who have sex with men (MSM). Partial segments of three HIV-1 gene regions (gag, pol, and env) were amplified and sequenced by cloning. Maximum-likelihood (ML) and Bayesian methods were used to determine the direction and estimate the timing of transmission. Local control sequences and database control sequences were also used in the phylogenetic analysis. Results It indicated that P2 underwent HIV seroconversion after P1 was diagnosed as HIV positive. The time to the most recent common ancestor (tMRCA) estimates consistently showed that P1 most likely became HIV-1 infected at an earlier date than P2. P1 and P2 were infected with the same HIV-1 CRF01_AE subtype according to segments of all three gene regions (gag, pol, and env). All three genetic regions of P1 have been subject to more potential selective forces than those of P2, indicating a longer evolutionary history. Bayesian and ML trees showed similar paraphyletic-monophyletic topologies of gag and env, with the virus from P1 located at the root, which supported a P1-to-P2 transmission direction. Conclusions Phylogenetic investigations can elucidate HIV transmission linkage and might empower its use in the opposition of the intentional transmission of HIV-1 as a forensic tool.
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Affiliation(s)
- Jiafeng Zhang
- Department of HIV/AIDS & STD Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, No. 3399, Binsheng Road, Hangzhou, 310051, Zhejiang, China
| | - Qin Fan
- Department of HIV/AIDS & STD Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, No. 3399, Binsheng Road, Hangzhou, 310051, Zhejiang, China
| | - Mingyu Luo
- Department of HIV/AIDS & STD Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, No. 3399, Binsheng Road, Hangzhou, 310051, Zhejiang, China
| | - Jiaming Yao
- Department of HIV/AIDS & STD Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, No. 3399, Binsheng Road, Hangzhou, 310051, Zhejiang, China
| | - Xiaohong Pan
- Department of HIV/AIDS & STD Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, No. 3399, Binsheng Road, Hangzhou, 310051, Zhejiang, China.
| | - Xingguang Li
- Department of Technology R&D, Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, 315000, Zhejiang, China.
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10
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Hulaniuk ML, Corach D, Trinks J, Caputo M. A simple and rapid approach for human herpesvirus type 8 subtype characterization using single base extension. Lett Appl Microbiol 2021; 73:308-317. [PMID: 34048079 DOI: 10.1111/lam.13515] [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: 02/12/2021] [Revised: 05/20/2021] [Accepted: 05/21/2021] [Indexed: 11/28/2022]
Abstract
Sequence analysis of the ORFK1 of human herpesvirus type 8 (HHV-8) allows the identification of six major subtypes (A-F), which are related to human migrations and the clinical progression of Kaposi's sarcoma. Sequencing and subsequent phylogenetic analysis of ORFK1 is considered to be the most reliable method for HHV-8 genotyping. However, it exhibits challenges and limitations. Herein, we designed and validated a single base extension (SBE) protocol for characterization of HHV-8 ORFK1 subtypes. A nested polymerase chain reaction (PCR) protocol was carried out to amplify a small 294-bp PCR product encompassing four single nucleotide polymorphisms at positions 360, 406, 465 and 527 of the HHV-8 genome. Finally, a multiplex SBE technique was developed and validated in 20 samples previously genotyped by phylogenetic analysis. The patterns obtained in this reaction could successfully discriminate between ORFK1 subtypes. The typing results obtained completely matched with those of the 'gold standard' method in all analysed samples. This method can reliably identify HHV-8 subtypes A, B and C, which are the most prevalent ones worldwide, and the remaining subtypes (D, E and F). SBE can be useful as an efficient, rapid and low-cost screening method for viral genotyping in a single tube, particularly samples with low-quality DNA, and with easy data interpretation.
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Affiliation(s)
- M L Hulaniuk
- Instituto de Medicina Traslacional e Ingeniería Biomédica (IMTIB), CONICET, Instituto Universitario del Hospital Italiano (IUHI), Hospital Italiano (HIBA), Buenos Aires, Argentina
| | - D Corach
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina.,Universidad de Buenos Aires, Facultad de Farmacia y Bioquímica, Departamento de Microbiología, Inmunología, Biotecnología y Genética, Cátedra de Genética Forense y Servicio de Huellas Digitales Genéticas, Buenos Aires, Argentina
| | - J Trinks
- Instituto de Medicina Traslacional e Ingeniería Biomédica (IMTIB), CONICET, Instituto Universitario del Hospital Italiano (IUHI), Hospital Italiano (HIBA), Buenos Aires, Argentina.,Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina
| | - M Caputo
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina.,Universidad de Buenos Aires, Facultad de Farmacia y Bioquímica, Departamento de Microbiología, Inmunología, Biotecnología y Genética, Cátedra de Genética Forense y Servicio de Huellas Digitales Genéticas, Buenos Aires, Argentina
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11
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Chen Y, Shen Z, Feng Y, Ruan Y, Li J, Tang S, Tang K, Liang S, Pang X, McNeil EB, Xing H, Chongsuvivatwong V, Lin M, Lan G. HIV-1 subtype diversity and transmission strain source among men who have sex with men in Guangxi, China. Sci Rep 2021; 11:8319. [PMID: 33859273 PMCID: PMC8050077 DOI: 10.1038/s41598-021-87745-3] [Citation(s) in RCA: 10] [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: 09/23/2020] [Accepted: 03/30/2021] [Indexed: 11/08/2022] Open
Abstract
With the rapid increase in HIV prevalence of men who have sex with men (MSM) in recent years and common human migration and travelling across different provinces in China, MSM are now finding it easier to meet each other, which might contribute to local HIV epidemics as well as fueling cross-province transmission. We performed a cross-sectional survey in 2018-2019 to investigate the current HIV subtype diversity and inferred HIV strain transmission origin among MSM in Guangxi province, China based on a phylogenetic analysis. Based on 238 samples, we found that the HIV-1 subtype diversity was more complicated than before, except for three major HIV subtypes/circulating recombinant forms (CRFs): CRF07_BC, CRF01_AE, CRF55_01B, five other subtypes/CRFs (CRF59_01B, B, CRF08_BC, CRF67_01B, CRF68_01B) and five unique recombinant forms (URFs) were detected. In total, 76.8% (169/220) of samples were infected with HIV from local circulating strains, while others originated from other provinces, predominantly Guangdong and Shanghai. The high diversity of HIV recombinants and complicated HIV transmission sources in Guangxi MSM indicates that there has been an active sexual network between HIV positive MSM both within and outside Guangxi without any effective prevention. Inter-province collaboration must be enforced to provide tailored HIV prevention and control services to MSM in China.
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Affiliation(s)
- Yi Chen
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
| | - Zhiyong Shen
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
| | - Yi Feng
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, 102206, China
| | - Yuhua Ruan
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, 102206, China
| | - Jianjun Li
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
| | - Shuai Tang
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
| | - Kailing Tang
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
| | - Shujia Liang
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
| | - Xianwu Pang
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
| | - Edward B McNeil
- Epidemiology Unit, Faculty of Medicine, Prince of Songkla University, Hat Yai, 90110, Thailand
| | - Hui Xing
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China
- State Key Laboratory of Infectious Disease Prevention and Control (SKLID), Chinese Center for Disease Control and Prevention (China CDC), Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Beijing, 102206, China
| | | | - Mei Lin
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China.
| | - Guanghua Lan
- Institute of HIV/AIDS Prevention and Control, Guangxi Center of Disease Control and Prevention, Nanning, 530028, China.
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12
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Zhang Y, Wymant C, Laeyendecker O, Grabowski MK, Hall M, Hudelson S, Piwowar-Manning E, McCauley M, Gamble T, Hosseinipour MC, Kumarasamy N, Hakim JG, Kumwenda J, Mills LA, Santos BR, Grinsztejn B, Pilotto JH, Chariyalertsak S, Makhema J, Chen YQ, Cohen MS, Fraser C, Eshleman SH. Evaluation of Phylogenetic Methods for Inferring the Direction of Human Immunodeficiency Virus (HIV) Transmission: HIV Prevention Trials Network (HPTN) 052. Clin Infect Dis 2021; 72:30-37. [PMID: 31922537 PMCID: PMC7823077 DOI: 10.1093/cid/ciz1247] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 01/07/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Phylogenetic analysis can be used to assess human immunodeficiency virus (HIV) transmission in populations. We inferred the direction of HIV transmission using whole-genome HIV sequences from couples with known linked infection and known transmission direction. METHODS Complete next-generation sequencing (NGS) data were obtained for 105 unique index-partner sample pairs from 32 couples enrolled in the HIV Prevention Trials Network (HPTN) 052 study (up to 2 samples/person). Index samples were obtained up to 5.5 years before partner infection; partner samples were obtained near the time of seroconversion. The bioinformatics method, phyloscanner, was used to infer transmission direction. Analyses were performed using samples from individual sample pairs, samples from all couples (1 sample/person; group analysis), and all available samples (multisample group analysis). Analysis was also performed using NGS data from defined regions of the HIV genome (gag, pol, env). RESULTS Using whole-genome NGS data, transmission direction was inferred correctly (index to partner) for 98 of 105 (93.3%) of the individual sample pairs, 99 of 105 (94.3%) sample pairs using group analysis, and 31 of the 32 couples (96.9%) using multisample group analysis. There were no cases where the incorrect transmission direction (partner to index) was inferred. The accuracy of the method was higher with greater time between index and partner sample collection. Pol region sequences performed better than env or gag sequences for inferring transmission direction. CONCLUSIONS We demonstrate the potential of a phylogenetic method to infer the direction of HIV transmission between 2 individuals using whole-genome and pol NGS data.
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Affiliation(s)
- Yinfeng Zhang
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Chris Wymant
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Oliver Laeyendecker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - M Kathryn Grabowski
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Matthew Hall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Sarah Hudelson
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Estelle Piwowar-Manning
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Marybeth McCauley
- HIV Prevention Trials Network Leadership and Operations Center, FHI, Washington, District of Columbia, USA
| | - Theresa Gamble
- HIV Prevention Trials Network Leadership and Operations Center, FHI, Durham, North Carolina, USA
| | - Mina C Hosseinipour
- Division of Infectious Diseases, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- University of North Carolina Project–Malawi, Institute for Global Health and Infectious Diseases, Lilongwe, Malawi
| | - Nagalingeswaran Kumarasamy
- Chennai Antiviral Research and Treatment Clinical Research Site, Infectious Diseases Medical Centre, Voluntary Health Services, Chennai, India
| | - James G Hakim
- Department of Medicine, University of Zimbabwe, Harare, Zimbabwe
| | | | - Lisa A Mills
- US Centers for Disease Control and Prevention, HIV Research Branch, Kisumu, Kenya
| | - Breno R Santos
- Department of Infectious Diseases, Hospital Nossa Senhora da Conceição, Porto Alegre, Brazil
| | - Beatriz Grinsztejn
- Instituto Nacional de Infectologia Evandro Chagas-Fiocruz, Rio de Janeiro, Brazil
| | - Jose H Pilotto
- Hospital Geral de Nova Iguacu and Laboratorio de AIDS e Imunologia Molecular–Instituto Oswaldo Cruz/Fiocruz, Rio de Janeiro, Brazil
| | - Suwat Chariyalertsak
- Research Institute for Health Sciences, Chiang Mai University, Chiang Mai, Thailand
| | - Joseph Makhema
- Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana
| | - Ying Q Chen
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Myron S Cohen
- Department of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Christophe Fraser
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Susan H Eshleman
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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13
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Villabona-Arenas CJ, Hall M, Lythgoe KA, Gaffney SG, Regoes RR, Hué S, Atkins KE. Number of HIV-1 founder variants is determined by the recency of the source partner infection. Science 2020; 369:103-108. [PMID: 32631894 DOI: 10.1126/science.aba5443] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Accepted: 05/11/2020] [Indexed: 01/10/2023]
Abstract
During sexual transmission, the high genetic diversity of HIV-1 within an individual is frequently reduced to one founder variant that initiates infection. Understanding the drivers of this bottleneck is crucial to developing effective infection control strategies. Little is known about the importance of the source partner during this bottleneck. To test the hypothesis that the source partner affects the number of HIV founder variants, we developed a phylodynamic model calibrated using genetic and epidemiological data on all existing transmission pairs for whom the direction of transmission and the infection stage of the source partner are known. Our results suggest that acquiring infection from someone in the acute (early) stage of infection increases the risk of multiple-founder variant transmission compared with acquiring infection from someone in the chronic (later) stage of infection. This study provides the first direct test of source partner characteristics to explain the low frequency of multiple-founder strain infections.
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Affiliation(s)
- Ch Julián Villabona-Arenas
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.,Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Matthew Hall
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Katrina A Lythgoe
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Stephen G Gaffney
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Roland R Regoes
- Institute of Integrative Biology, Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland
| | - Stéphane Hué
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.,Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Katherine E Atkins
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK. .,Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.,Centre for Global Health, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
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14
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Pérez-Losada M, Arenas M, Galán JC, Bracho MA, Hillung J, García-González N, González-Candelas F. High-throughput sequencing (HTS) for the analysis of viral populations. INFECTION GENETICS AND EVOLUTION 2020; 80:104208. [PMID: 32001386 DOI: 10.1016/j.meegid.2020.104208] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 01/21/2020] [Accepted: 01/24/2020] [Indexed: 12/12/2022]
Abstract
The development of High-Throughput Sequencing (HTS) technologies is having a major impact on the genomic analysis of viral populations. Current HTS platforms can capture nucleic acid variation across millions of genes for both selected amplicons and full viral genomes. HTS has already facilitated the discovery of new viruses, hinted new taxonomic classifications and provided a deeper and broader understanding of their diversity, population and genetic structure. Hence, HTS has already replaced standard Sanger sequencing in basic and applied research fields, but the next step is its implementation as a routine technology for the analysis of viruses in clinical settings. The most likely application of this implementation will be the analysis of viral genomics, because the huge population sizes, high mutation rates and very fast replacement of viral populations have demonstrated the limited information obtained with Sanger technology. In this review, we describe new technologies and provide guidelines for the high-throughput sequencing and genetic and evolutionary analyses of viral populations and metaviromes, including software applications. With the development of new HTS technologies, new and refurbished molecular and bioinformatic tools are also constantly being developed to process and integrate HTS data. These allow assembling viral genomes and inferring viral population diversity and dynamics. Finally, we also present several applications of these approaches to the analysis of viral clinical samples including transmission clusters and outbreak characterization.
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Affiliation(s)
- Marcos Pérez-Losada
- Computational Biology Institute, Milken Institute School of Public Health, George Washington University, Washington, DC, USA; CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Campus Agrário de Vairão, Vairão 4485-661, Portugal
| | - Miguel Arenas
- Department of Biochemistry, Genetics and Immunology, University of Vigo, 36310 Vigo, Spain; Biomedical Research Center (CINBIO), University of Vigo, 36310 Vigo, Spain.
| | - Juan Carlos Galán
- Microbiology Service, Hospital Ramón y Cajal, Madrid, Spain; CIBER in Epidemiology and Public Health, Spain.
| | - Mª Alma Bracho
- CIBER in Epidemiology and Public Health, Spain; Joint Research Unit "Infection and Public Health" FISABIO-University of Valencia, Valencia, Spain.
| | - Julia Hillung
- Joint Research Unit "Infection and Public Health" FISABIO-University of Valencia, Valencia, Spain; Institute for Integrative Systems Biology (I2SysBio), CSIC-University of Valencia, Valencia, Spain.
| | - Neris García-González
- Joint Research Unit "Infection and Public Health" FISABIO-University of Valencia, Valencia, Spain; Institute for Integrative Systems Biology (I2SysBio), CSIC-University of Valencia, Valencia, Spain.
| | - Fernando González-Candelas
- CIBER in Epidemiology and Public Health, Spain; Joint Research Unit "Infection and Public Health" FISABIO-University of Valencia, Valencia, Spain; Institute for Integrative Systems Biology (I2SysBio), CSIC-University of Valencia, Valencia, Spain.
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15
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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: 13] [Impact Index Per Article: 2.6] [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.
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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
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16
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Günthard HF, Kouyos R. Can Directionality of HIV Transmission be Predicted by Next-Generation Sequencing Data? J Infect Dis 2019; 220:1393-1395. [PMID: 30590738 DOI: 10.1093/infdis/jiy737] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 12/21/2018] [Indexed: 11/12/2022] Open
Affiliation(s)
- Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.,Institute of Medical Virology, University of Zurich, Switzerland
| | - Roger Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.,Institute of Medical Virology, University of Zurich, Switzerland
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17
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Ciccozzi M, Lai A, Zehender G, Borsetti A, Cella E, Ciotti M, Sagnelli E, Sagnelli C, Angeletti S. The phylogenetic approach for viral infectious disease evolution and epidemiology: An updating review. J Med Virol 2019; 91:1707-1724. [PMID: 31243773 DOI: 10.1002/jmv.25526] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2019] [Accepted: 06/24/2019] [Indexed: 12/16/2022]
Abstract
In the last decade, the phylogenetic approach is recurrent in molecular evolutionary analysis. On 12 May, 2019, about 2 296 213 papers are found, but typing "phylogeny" or "epidemiology AND phylogeny" only 199 804 and 20 133 are retrieved, respectively. Molecular epidemiology in infectious diseases is widely used to define the source of infection as so as the ancestral relationships of individuals sampled from a population. Coalescent theory and phylogeographic analysis have had scientific application in several, recent pandemic events, and nosocomial outbreaks. Hepatitis viruses and immunodeficiency virus (human immunodeficiency virus) have been largely studied. Phylogenetic analysis has been recently applied on Polyomaviruses so as in the more recent outbreaks due to different arboviruses type as Zika and chikungunya viruses discovering the source of infection and the geographic spread. Data on sequences isolated by the microorganism are essential to apply the phylogenetic tools and research in the field of infectious disease phylodinamics is growing up. There is the need to apply molecular phylogenetic and evolutionary methods in areas out of infectious diseases, as translational genomics and personalized medicine. Lastly, the application of these tools in vaccine strategy so as in antibiotic and antiviral researchers are encouraged.
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Affiliation(s)
- Massimo Ciccozzi
- Unit of Medical Statistics and Molecular Epidemiology, University Campus Bio-Medico of Rome, Rome, Italy
| | - Alessia Lai
- Department of Biomedical and Clinical Sciences 'L. Sacco', University of Milan, Milan, Italy
| | - Gianguglielmo Zehender
- Department of Biomedical and Clinical Sciences 'L. Sacco', University of Milan, Milan, Italy
| | - Alessandra Borsetti
- National HIV/AIDS Research Center, Istituto Superiore di Sanità, Roma, Italy
| | - Eleonora Cella
- Unit of Medical Statistics and Molecular Epidemiology, University Campus Bio-Medico of Rome, Rome, Italy
| | - Marco Ciotti
- Laboratory of Molecular Virology, Polyclinic Tor Vergata Foundation, Rome, Italy
| | - Evangelista Sagnelli
- Department of Mental Health and Public Medicine, Section of Infectious Diseases, University of Campania Luigi Vanvitelli, Naples, Italy
| | - Caterina Sagnelli
- Department of Mental Health and Public Medicine, Section of Infectious Diseases, University of Campania Luigi Vanvitelli, Naples, Italy
| | - Silvia Angeletti
- Unit of Clinical Laboratory Science, University Campus Bio-Medico of Rome, Rome, Italy
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18
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Wu J, Hu Z, Yao H, Wang H, Lei Y, Zhong P, Feng Y, Xing H, Shen Y, Jin L, Liu A, Qin Y, Miao L, Su B, Zhang Y, Guo H. The inference of HIV-1 transmission direction between HIV-1 positive couples based on the sequences of HIV-1 quasi-species. BMC Infect Dis 2019; 19:566. [PMID: 31253127 PMCID: PMC6599307 DOI: 10.1186/s12879-019-4163-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Accepted: 06/04/2019] [Indexed: 11/22/2022] Open
Abstract
Background To infer transmission direction of a HIV transmission chain is helpful not only in legal jurisdiction but also in precise intervention to prevent HIV spread. Recently, the direction of transmission is inferred by whether paraphyletic-monophyletic (PM) or a combination of paraphyletic and polyphyletic (PP) topologies is observed or not between the sequences of source and recipient in the phylogenetic tree. However, paraphyly between them often declines over time and may disappear between spouses due to bidirectional transmission after primary infection. In this study, our aim is to test the reliability of inferring HIV transmission direction between epidemiologically linked HIV-1 positive couples using whether or not paraphyly is observed in phylogenetic tree. Methods HIV quasi-species were sequenced using PCR product clones, and then Bayesian analysis of molecular sequences with MCMC was employed to construct phylogenetic relationship of env, gag, pol gene fragments of HIV-1 positive couples using BEAST software. Results Our results showed that all sequences of seven couples except pol sequences of couple 12 and 13 form their own monophyletic cluster in phylogenetic tree including the closest control sequences from GenBank or other studies on local samples, which are supported by significant Bayesian posterior probabilities more than 0.9932. Of seven couples, paraphyly is only observed in phylogenetic tree constructed with env and pol gene sequences of three couples and gag gene sequences of four couples. Paraphyly is not observed in half of HIV positive couples. Pol sequences of couple 13 is separated by Blast selected controls; pol sequences of couple 12 in phylogenetic tree is supported by a lower Bayesian posterior value. Conclusion Paraphyly relationship between sequences of donator and recipient is only observed among partial HIV-1 positive couples with epidemiological link. Phylogenetic relationship is not always the same when various gene regions of HIV are used to conduct phylogenetic analysis. The combination of phylogenetic analysis based on various gene regions of HIV and enough epidemiology investigation is essential when inferring transmission direction of HIV in a transmission chain or in one couple. However, while observed paraphyly can be used to infer transmission direction in HIV-1 positive couple, no observed paraphyly cannot deny it.
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Affiliation(s)
- Jianjun Wu
- Anhui Provincial Center for Disease Control and Prevention, 12560 Fanhuadadao, Hefei, China
| | - Zhongwang Hu
- Hefei Prefecture Center for Disease Control and Prevention, 86 Liu'an Road, Hefei, China
| | - Hui Yao
- Hefei Prefecture Center for Disease Control and Prevention, 86 Liu'an Road, Hefei, China
| | - Hai Wang
- Hefei Prefecture Center for Disease Control and Prevention, 86 Liu'an Road, Hefei, China
| | - Yanhua Lei
- Hefei Prefecture Center for Disease Control and Prevention, 86 Liu'an Road, Hefei, China
| | - Ping Zhong
- Shanghai Municipal Center for Disease Control and Prevention, 1380 Zhongshan West Road, Shanghai, China
| | - Yi Feng
- Chinese Center for Disease Control and Prevention, 155 Changbei Road, Beijing, China
| | - Hui Xing
- Chinese Center for Disease Control and Prevention, 155 Changbei Road, Beijing, China
| | - Yuelan Shen
- Anhui Provincial Center for Disease Control and Prevention, 12560 Fanhuadadao, Hefei, China
| | - Lin Jin
- Anhui Provincial Center for Disease Control and Prevention, 12560 Fanhuadadao, Hefei, China
| | - Aiwen Liu
- Anhui Provincial Center for Disease Control and Prevention, 12560 Fanhuadadao, Hefei, China
| | - Yizu Qin
- Anhui Provincial Center for Disease Control and Prevention, 12560 Fanhuadadao, Hefei, China
| | - Lifeng Miao
- Anhui Provincial Center for Disease Control and Prevention, 12560 Fanhuadadao, Hefei, China
| | - Bin Su
- Anhui Provincial Center for Disease Control and Prevention, 12560 Fanhuadadao, Hefei, China.
| | - Yibo Zhang
- Department of Hospital Infection Control, Shanghai Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Hongxiong Guo
- Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, China.
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19
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Abstract
OBJECTIVES Molecular epidemiology is applied to various aspects of HIV transmission analyses. With ultradeep sequencing (UDS), in-depth characterization of transmission episodes involving minority variants is permitted. We explored HIV-1 epidemiological linkage and evaluated characteristics of transmission dynamics and transmitted drug resistance (TDR) detection through the added value of UDS. DESIGN HIV pol gene fragments were sequenced by UDS and Sanger sequencing on samples of 70 HIV-1-infected, treatment-naive recently diagnosed MSM. METHODS Pairwise genetic distances and maximum likelihood phylogenies were computed. Transmission events were identified as clades with branch support at least 70% and intraclade genetic difference less than 4.5%. TDR mutations were recognized from the TDR consensus list. Transmission directionality, directness and inoculum size were inferred from tree topologies. RESULTS Both datasets concurred in the identification of seven transmission pairs and one cluster of three patients. With UDS, direction of transmission was inferred in four out of eight chains. Evidence for multiple founder viruses was found in two out of eight chains. No transmission of minority-resistant variants was evidenced. TDR mutations prevalence in protease and reverse transcriptase fragments was 4.3% with Sanger sequencing and 18.6% with UDS. CONCLUSION Although Sanger sequencing and UDS identified the same transmission chains, UDS provided additional information on founder viruses, direction of transmission and levels of TDR. Nevertheless, topology of clusters was not always consistent across gene fragments, calling for a cautious interpretation of the data. Moreover, unobserved intermediary links cannot be excluded. Phylogenetic analysis use as a forensic technique for HIV transmission investigations is risky.
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20
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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: 4.8] [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.
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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
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21
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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: 6.8] [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.
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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
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