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Faraci G, Park SY, Love TMT, Dubé MP, Lee HY. Precision detection of recent HIV infections using high-throughput genomic incidence assay. Microbiol Spectr 2023; 11:e0228523. [PMID: 37712639 PMCID: PMC10580985 DOI: 10.1128/spectrum.02285-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 07/21/2023] [Indexed: 09/16/2023] Open
Abstract
HIV incidence is a key measure for tracking disease spread and identifying populations and geographic regions where new infections are most concentrated. The HIV sequence population provides a robust signal for the stage of infection. Large-scale and high-precision HIV sequencing is crucial for effective genomic incidence surveillance. We produced 1,034 full-length envelope gene sequences from a seroconversion cohort by conducting HIV microdrop sequencing and measuring the genomic incidence assay's genome similarity index (GSI) dynamics. The measured dynamics of 9 of 12 individuals aligned with the GSI distribution estimated independently using 417 publicly available incident samples. We enhanced the capacity to identify individuals with recent infections, achieving predicted detection accuracies of 92% (89%-94%) for cases within 6 months and 81% (74%-87%) for cases within 9 months. These accuracy levels agreed with the observed detection accuracy intervals of an independent validation data set. Additionally, we produced 131 full-length envelope gene sequences from eight individuals with chronic HIV infection. This analysis confirmed a false recency rate (FRR) of 0%, which was consistent with 162 publicly available chronic samples. The mean duration of recent infection (MDRI) was 238 (209-267) days, indicating an 83% improvement in performance compared to current recent infection testing algorithms. The shifted Poisson mixture model was then used to estimate the time since infection, and the model estimates showed an 88% consistency with the days post infection derived from HIV RNA test dates and/or seroconversion dates. HIV microdrop sequencing provides unique prospects for large-scale incidence surveillance using high-throughput sequencing. IMPORTANCE Accurate identification of recently infected individuals is vital for prioritizing specific populations for interventions, reducing onward transmission risks, and optimizing public health services. However, current HIV-specific antibody-based methods have not been satisfactory in accurately identifying incident cases, hindering the use of HIV recency testing for prevention efforts and partner protection. Genomic incidence assays offer a promising alternative for identifying recent infections. In our study, we used microdroplet technologies to produce a large number of complete HIV envelope gene sequences, enabling the accurate detection of early infection signs. We assessed the dynamics of the incidence assay's metrics and compared them with statistical models. Our approach demonstrated high accuracy in identifying individuals with recent infections, achieving predicted detection rates exceeding 90% within 6 months and over 80% within 9 months of infection. This high-resolution method holds significant potential for enhancing the effectiveness of HIV incidence screening for case-based surveillance in public health initiatives.
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Affiliation(s)
- Gina Faraci
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Sung Yong Park
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Tanzy M. T. Love
- Department of Biostatistics and Computational Biology, School of Medicine and Dentistry, University of Rochester, Rochester, New York, USA
| | - Michael P. Dubé
- Division of Infectious Diseases, Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Ha Youn Lee
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
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Faraci G, Park SY, Dubé MP, Lee HY. Full-spectrum HIV drug resistance mutation detection by high-resolution complete pol gene sequencing. J Clin Virol 2023; 164:105491. [PMID: 37182384 PMCID: PMC10330399 DOI: 10.1016/j.jcv.2023.105491] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 03/15/2023] [Accepted: 05/03/2023] [Indexed: 05/16/2023]
Abstract
BACKGROUND Drug resistance mutation testing is a key element for HIV clinical management, informing effective treatment regimens. However, resistance screening in current clinical practice is limited in reporting linked cross-class resistance mutations and minority variants, both of which may increase the risk of virological failure. METHODS To address these limitations, we obtained 358 full-length pol gene sequences from 52 specimens of 20 HIV infected individuals by combining microdroplet amplification, unique molecular identifier (UMI) labeling, and long-read high-throughput sequencing. RESULTS We conducted a rigorous assessment of the accuracy of our pipeline for precision drug resistance mutation detection, verifying that a sequencing depth of 35 high-throughput reads achieved complete, error-free pol gene sequencing. We detected 26 distinct drug resistance mutations to Protease Inhibitors (PIs), Nucleoside Reverse Transcriptase Inhibitors (NRTIs), Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs), and Integrase Strand Transfer Inhibitors (INSTIs). We detected linked cross-class drug resistance mutations (PI+NRTI, PI+NNRTI, and NRTI+NNRTI) that confer cross-resistance to multiple drugs in different classes. Fourteen different types of minority mutations were also detected with frequencies ranging from 3.2% to 19%, and the presence of these mutations was verified by Sanger reference sequencing. We detected a putative transmitted drug resistance mutation (TDRM) in one individual that persisted for over seven months from the first sample collected at the acute stage of infection prior to seroconversion. CONCLUSIONS Our comprehensive drug resistance mutation profiling can advance clinical practice by reporting mutation linkage and minority variants to better guide antiretroviral therapy options.
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Affiliation(s)
- Gina Faraci
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, Unites States
| | - Sung Yong Park
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, Unites States
| | - Michael P Dubé
- Department of Medicine and Division of Infectious Diseases, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Ha Youn Lee
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, Unites States.
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Park SY, Faraci G, Murphy G, Pilcher C, Busch MP, Lee HY. Microdrop Human Immunodeficiency Virus Sequencing for Incidence and Drug Resistance Surveillance. J Infect Dis 2021; 224:1048-1059. [PMID: 33517458 DOI: 10.1093/infdis/jiab060] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 01/26/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Precise and cost-efficient human immunodeficiency virus (HIV) incidence and drug resistance surveillances are in high demand for the advancement of the 90-90-90 "treatment for all" target. METHODS We developed microdrop HIV sequencing for the HIV incidence and drug resistance assay (HIDA), a single-blood-draw surveillance tool for incidence and drug resistance mutation (DRM) detection. We amplified full-length HIV envelope and pol gene sequences within microdroplets, and this compartmental amplification with long-read high-throughput sequencing enabled us to recover multiple unique sequences. RESULTS We achieved greater precision in determining the stage of infection than current incidence assays, with a 1.2% false recency rate (proportion of misclassified chronic infections) and a 262-day mean duration of recent infection (average time span of recent infection classification) from 83 recently infected and 81 chronically infected individuals. Microdrop HIV sequencing demonstrated an increased capacity to detect minority variants and linked DRMs. By screening all 93 World Health Organization surveillance DRMs, we detected 6 pretreatment drug resistance mutations with 2.6%-13.2% prevalence and cross-linked mutations. CONCLUSIONS HIDA with microdrop HIV sequencing may promote global HIV real-time surveillance by serving as a precise and high-throughput cross-sectional survey tool that can be generalized for surveillance of other pathogens.
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Affiliation(s)
- Sung Yong Park
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Gina Faraci
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Gary Murphy
- Public Health England, London, United Kingdom
| | - Christopher Pilcher
- Department of Medicine, University of California, San Francisco, California, USA
| | - Michael P Busch
- Research and Scientific Programs, Vitalant Research Institute, San Francisco, California, USA.,Deparment of Laboratory Medicine, University of California, California, San Francisco, USA
| | - Ha Youn Lee
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
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Park SY, Love TMT, Kapoor S, Lee HY. HIITE: HIV-1 incidence and infection time estimator. Bioinformatics 2019; 34:2046-2052. [PMID: 29438560 DOI: 10.1093/bioinformatics/bty073] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Accepted: 02/08/2018] [Indexed: 01/23/2023] Open
Abstract
Motivation Around 2.1 million new HIV-1 infections were reported in 2015, alerting that the HIV-1 epidemic remains a significant global health challenge. Precise incidence assessment strengthens epidemic monitoring efforts and guides strategy optimization for prevention programs. Estimating the onset time of HIV-1 infection can facilitate optimal clinical management and identify key populations largely responsible for epidemic spread and thereby infer HIV-1 transmission chains. Our goal is to develop a genomic assay estimating the incidence and infection time in a single cross-sectional survey setting. Results We created a web-based platform, HIV-1 incidence and infection time estimator (HIITE), which processes envelope gene sequences using hierarchical clustering algorithms and informs the stage of infection, along with time since infection for incident cases. HIITE's performance was evaluated using 585 incident and 305 chronic specimens' envelope gene sequences collected from global cohorts including HIV-1 vaccine trial participants. HIITE precisely identified chronically infected individuals as being chronic with an error less than 1% and correctly classified 94% of recently infected individuals as being incident. Using a mixed-effect model, an incident specimen's time since infection was estimated from its single lineage diversity, showing 14% prediction error for time since infection. HIITE is the first algorithm to inform two key metrics from a single time point sequence sample. HIITE has the capacity for assessing not only population-level epidemic spread but also individual-level transmission events from a single survey, advancing HIV prevention and intervention programs. Availability and implementation Web-based HIITE and source code of HIITE are available at http://www.hayounlee.org/software.html. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Sung Yong Park
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, CA, USA
| | - Tanzy M T Love
- Department of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA
| | - Shivankur Kapoor
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, CA, USA
| | - Ha Youn Lee
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, CA, USA
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Detection of IgG3 antibodies specific to the human immunodeficiency virus type 1 (HIV-1) p24 protein as marker for recently acquired infection. Epidemiol Infect 2018; 146:1293-1300. [PMID: 29925445 DOI: 10.1017/s0950268818001218] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Reducing the risk of human immunodeficiency virus type 1 (HIV-1) transmission is still a public health priority. The development of effective control strategies relies on the quantification of the effects of prophylactic and therapeutic measures in disease incidence. Although several assays can be used to estimate HIV incidence, these estimates are limited by the poor performance of these assays in distinguishing recent from long-standing infections. To address such limitation, we have developed an assay to titrate p24-specific IgG3 antibodies as a marker of recent infection. The assay is based on a recombinant p24 protein capable to detect total IgG antibodies in sera using a liquid micro array and enzyme-linked immunosorbent assay. Subsequently, the assay was optimised to detect and titrate anti-p24 IgG3 responses in a panel of sequential specimens from seroconverters over 24 months. The kinetics of p24-specific IgG3 titres revealed a transient peak in the 4 to 5-month period after seroconversion. It was followed by a sharp decline, allowing infections with less than 6 months to be distinguished from older ones. The developed assay exhibited a mean duration of recent infection of 144 days and a false-recent rate of ca. 14%. Our findings show that HIV-1 p24-specific IgG3 titres can be used as a tool to evaluate HIV incidence in serosurveys and to monitor the efficacy of vaccines and other transmission control strategies.
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Park SY, Love TMT, Reynell L, Yu C, Kang TM, Anastos K, DeHovitz J, Liu C, Kober KM, Cohen M, Mack WJ, Lee HY. The HIV Genomic Incidence Assay Meets False Recency Rate and Mean Duration of Recency Infection Performance Standards. Sci Rep 2017; 7:7480. [PMID: 28785052 PMCID: PMC5547093 DOI: 10.1038/s41598-017-07490-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2017] [Accepted: 06/29/2017] [Indexed: 11/09/2022] Open
Abstract
HIV incidence is a primary metric for epidemic surveillance and prevention efficacy assessment. HIV incidence assay performance is evaluated via false recency rate (FRR) and mean duration of recent infection (MDRI). We conducted a meta-analysis of 438 incident and 305 chronic specimens' HIV envelope genes from a diverse global cohort. The genome similarity index (GSI) accurately characterized infection stage across diverse host and viral factors. All except one chronic specimen had GSIs below 0.67, yielding a FRR of 0.33 [0-0.98] %. We modeled the incidence assay biomarker dynamics with a logistic link function assuming individual variabilities in a Beta distribution. The GSI probability density function peaked close to 1 in early infection and 0 around two years post infection, yielding MDRI of 420 [361, 467] days. We tested the assay by newly sequencing 744 envelope genes from 59 specimens of 21 subjects who followed from HIV negative status. Both standardized residuals and Anderson-Darling tests showed that the test dataset was statistically consistent with the model biomarker dynamics. This is the first reported incidence assay meeting the optimal FRR and MDRI performance standards. Signatures of HIV gene diversification can allow precise cross-sectional surveillance with a desirable temporal range of incidence detection.
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Affiliation(s)
- Sung Yong Park
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Tanzy M T Love
- Department of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY, United States
| | - Lucy Reynell
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Carl Yu
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Tina Manzhu Kang
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Kathryn Anastos
- Department of Medicine, and Epidemiology & Population Health, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY, United States
| | - Jack DeHovitz
- Department of Medicine, SUNY Downstate Medical Center, Brooklyn, NY, United States
| | - Chenglong Liu
- Department of Medicine, Georgetown University, Washington, DC, United States
| | - Kord M Kober
- Department of Physiological Nursing, University of California San Francisco, San Francisco, CA, United States
| | - Mardge Cohen
- Department of Medicine, Stroger Hospital, Chicago, IL, United States
| | - Wendy J Mack
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Ha Youn Lee
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.
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Moyo S, Wilkinson E, Vandormael A, Wang R, Weng J, Kotokwe KP, Gaseitsiwe S, Musonda R, Makhema J, Essex M, Engelbrecht S, de Oliveira T, Novitsky V. Pairwise diversity and tMRCA as potential markers for HIV infection recency. Medicine (Baltimore) 2017; 96:e6041. [PMID: 28178146 PMCID: PMC5313003 DOI: 10.1097/md.0000000000006041] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Intrahost human immunodeficiency virus (HIV)-1 diversity increases linearly over time. We assessed the extent to which mean pairwise distances and the time to the most recent common ancestor (tMRCA) inferred from intrahost HIV-1C env sequences were associated with the estimated time of HIV infection. Data from a primary HIV-1C infection study in Botswana were used for this analysis (N = 42). A total of 2540 HIV-1C env gp120 variable loop region 1 to conserved region 5 (V1C5) of the HIV-1 envelope gp120 viral sequences were generated by single genome amplification and sequencing, with an average of 61 viral sequences per participant and 11 sequences per time point per participant. Raw pairwise distances were calculated for each time point and participant using the ape package in R software. The tMRCA was estimated using phylogenetic inference implemented in Bayesian Evolutionary Analysis by Sampling Trees v1.8.2. Pairwise distances and tMRCA were significantly associated with the estimated time since HIV infection (both P < 0.001). Taking into account multiplicity of HIV infection strengthened these associations. HIV-1C env-based pairwise distances and tMRCA can be used as potential markers for HIV recency. However, the tMRCA estimates demonstrated no advantage over the pairwise distances estimates.
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Affiliation(s)
- Sikhulile Moyo
- Division of Medical Virology, Stellenbosch University, Tygerberg, South Africa
- Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana
| | - Eduan Wilkinson
- College of Health Sciences, University of KwaZulu-Natal, Durban, Republic of South Africa
| | - Alain Vandormael
- Africa Health Research Institute, School of Nursing and Public Health, University of KwaZulu-Natal, Durban, Republic of South Africa
| | - Rui Wang
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jia Weng
- Division of Sleep Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | | | - Simani Gaseitsiwe
- Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Rosemary Musonda
- Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Joseph Makhema
- Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Max Essex
- Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Susan Engelbrecht
- Division of Medical Virology, Stellenbosch University, Tygerberg, South Africa
- National Health Laboratory Services (NHLS), Tygerberg Coastal, South Africa
| | - Tulio de Oliveira
- Africa Health Research Institute, School of Nursing and Public Health, University of KwaZulu-Natal, Durban, Republic of South Africa
- Research Department of Infection, University College London, London, United Kingdom
- College of Health Sciences, University of KwaZulu-Natal, Durban, Republic of South Africa
| | - Vladimir Novitsky
- Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
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Moving towards a reliable HIV incidence test - current status, resources available, future directions and challenges ahead. Epidemiol Infect 2016; 145:925-941. [PMID: 28004622 DOI: 10.1017/s0950268816002910] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
In 2011 the Incidence Assay Critical Path Working Group reviewed the current state of HIV incidence assays and helped to determine a critical path to the introduction of an HIV incidence assay. At that time the Consortium for Evaluation and Performance of HIV Incidence Assays (CEPHIA) was formed to spur progress and raise standards among assay developers, scientists and laboratories involved in HIV incidence measurement and to structure and conduct a direct independent comparative evaluation of the performance of 10 existing HIV incidence assays, to be considered singly and in combinations as recent infection test algorithms. In this paper we report on a new framework for HIV incidence assay evaluation that has emerged from this effort over the past 5 years, which includes a preliminary target product profile for an incidence assay, a consensus around key performance metrics along with analytical tools and deployment of a standardized approach for incidence assay evaluation. The specimen panels for this evaluation have been collected in large volumes, characterized using a novel approach for infection dating rules and assembled into panels designed to assess the impact of important sources of measurement error with incidence assays such as viral subtype, elite host control of viraemia and antiretroviral treatment. We present the specific rationale for several of these innovations, and discuss important resources for assay developers and researchers that have recently become available. Finally, we summarize the key remaining steps on the path to development and implementation of reliable assays for monitoring HIV incidence at a population level.
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Abstract
OBJECTIVE Properly priming cytotoxic T-lymphocyte (CTL) responses is an important task in HIV-1 vaccination. However, the STEP trial showed no efficacy even though the vaccine elicited HIV-specific CTL responses. Our study is to investigate whether or not the STEP vaccine enhanced viral escape in infected volunteers. METHODS The signature of viral escape, the presence of multiple escape variants, could be falsely represented by the existence of multiple founder viruses. Therefore, we use a mathematical model to designate STEP study patients with infections from a single founder virus. We then conduct permutation tests on each of 9988 Gag, Pol, and Nef overlapping peptides to identify epitopes with significant differences in diversity between the vaccine and placebo groups using previously published STEP trial sequence data. RESULTS We identify signatures of vaccine-enhanced viral escape within HIV-1 Nef from the STEP trial. Vaccine-treated patients showed a greater level of epitope diversity in one of the immunodomiant epitopes, EVGFPVRPQVPL (Nef65-76), compared with placebo-treated patients (P = 0.0038). In the other three Nef epitopes, there is a marginally significant difference in the epitope diversity between the vaccine and placebo group (P < 0.1). This greater epitope diversity was neither due to any difference in infection duration nor overall nef gene diversity between the two groups, suggesting that the increase in viral escape was likely mediated by vaccine-induced T-cell responses. CONCLUSION Viral escape in Nef is elevated preferentially in STEP vaccine-treated individuals, suggesting that vaccination primarily modulated initial CTL responses. Our observations provide important insights into improving vaccine-primed first immune control.
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Moyo S, Vandormael A, Wilkinson E, Engelbrecht S, Gaseitsiwe S, Kotokwe KP, Musonda R, Tanser F, Essex M, Novitsky V, de Oliveira T. Analysis of Viral Diversity in Relation to the Recency of HIV-1C Infection in Botswana. PLoS One 2016; 11:e0160649. [PMID: 27552218 PMCID: PMC4994946 DOI: 10.1371/journal.pone.0160649] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2016] [Accepted: 07/23/2016] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Cross-sectional, biomarker methods to determine HIV infection recency present a promising and cost-effective alternative to the repeated testing of uninfected individuals. We evaluate a viral-based assay that uses a measure of pairwise distances (PwD) to identify HIV infection recency, and compare its performance with two serologic incidence assays, BED and LAg. In addition, we assess whether combination BED plus PwD or LAg plus PwD screening can improve predictive accuracy by reducing the likelihood of a false-recent result. METHODS The data comes from 854 time-points and 42 participants enrolled in a primary HIV-1C infection study in Botswana. Time points after treatment initiation or with evidence of multiplicity of infection were excluded from the final analysis. PwD was calculated from quasispecies generated using single genome amplification and sequencing. We evaluated the ability of PwD to correctly classify HIV infection recency within <130, <180 and <360 days post-seroconversion using Receiver Operator Characteristics (ROC) methods. Following a secondary PwD screening, we quantified the reduction in the relative false-recency rate (rFRR) of the BED and LAg assays while maintaining a sensitivity of either 75, 80, 85 or 90%. RESULTS The final analytic sample consisted of 758 time-points from 40 participants. The PwD assay was more accurate in classifying infection recency for the 130 and 180-day cut-offs when compared with the recommended LAg and BED thresholds. A higher AUC statistic confirmed the superior predictive performance of the PwD assay for the three cut-offs. When used for combination screening, the PwD assay reduced the rFRR of the LAg assay by 52% and the BED assay by 57.8% while maintaining a 90% sensitivity for the 130 and 180-day cut-offs respectively. CONCLUSION PwD can accurately determine HIV infection recency. A secondary PwD screening reduces misclassification and increases the accuracy of serologic-based assays.
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Affiliation(s)
- Sikhulile Moyo
- Division of Medical Virology, Stellenbosch University, Tygerberg, South Africa
- Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana
- * E-mail:
| | - Alain Vandormael
- Wellcome Trust Africa Centre for Health and Population Studies, Dorris Duke Medical Research Centre, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Eduan Wilkinson
- Wellcome Trust Africa Centre for Health and Population Studies, Dorris Duke Medical Research Centre, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Susan Engelbrecht
- Division of Medical Virology, Stellenbosch University, Tygerberg, South Africa
- National Health Laboratory Services (NHLS), Tygerberg Coastal, South Africa
| | - Simani Gaseitsiwe
- Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | | | - Rosemary Musonda
- Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Frank Tanser
- Wellcome Trust Africa Centre for Health and Population Studies, Dorris Duke Medical Research Centre, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Max Essex
- Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Vladimir Novitsky
- Botswana-Harvard AIDS Institute Partnership, Gaborone, Botswana
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Tulio de Oliveira
- Wellcome Trust Africa Centre for Health and Population Studies, Dorris Duke Medical Research Centre, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
- Research Department of Infection, University College London, London, United Kingdom
- College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa
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Park SY, Love TMT, Perelson AS, Mack WJ, Lee HY. Molecular clock of HIV-1 envelope genes under early immune selection. Retrovirology 2016; 13:38. [PMID: 27246201 PMCID: PMC4888660 DOI: 10.1186/s12977-016-0269-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Accepted: 05/11/2016] [Indexed: 11/10/2022] Open
Abstract
Background The molecular clock hypothesis that genes or proteins evolve at a constant rate is a key tool to reveal phylogenetic relationships among species. Using the molecular clock, we can trace an infection back to transmission using HIV-1 sequences from a single time point. Whether or not a strict molecular clock applies to HIV-1’s early evolution in the presence of immune selection has not yet been fully examined. Results We identified molecular clock signatures from 1587 previously published HIV-1 full envelope gene sequences obtained since acute infection in 15 subjects. Each subject’s sequence diversity linearly increased during the first 150 days post infection, with rates ranging from \documentclass[12pt]{minimal}
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\begin{document}$$2.69 \times 10^{ - 5}$$\end{document}2.69×10-5 per base per day. The rate of diversification for 12 out of the 15 subjects was comparable to the neutral evolution rate. While temporal diversification was consistent with evolution patterns in the absence of selection, mutations from the founder virus were highly clustered on statistically identified selection sites, which diversified more than 65 times faster than non-selection sites. By mathematically quantifying deviations from the molecular clock under various selection scenarios, we demonstrate that the deviation from a constant clock becomes negligible as multiple escape lineages emerge. The most recent common ancestor of a virus pair from distinct escape lineages is most likely the transmitted founder virus, indicating that HIV-1 molecular dating is feasible even after the founder viruses are no longer detectable. Conclusions The ability of HIV-1 to escape from immune surveillance in many different directions is the driving force of molecular clock persistence. This finding advances our understanding of the robustness of HIV-1’s molecular clock under immune selection, implying the potential for molecular dating. Electronic supplementary material The online version of this article (doi:10.1186/s12977-016-0269-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sung Yong Park
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, 1450 Biggy Street, Los Angeles, CA, 90089, USA
| | - Tanzy M T Love
- Department of Biostatistics and Computational Biology, University of Rochester, Rochester, NY, 14642, USA
| | - Alan S Perelson
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA
| | - Wendy J Mack
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90089, USA
| | - Ha Youn Lee
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, 1450 Biggy Street, Los Angeles, CA, 90089, USA.
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12
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Fecal bacterial microbiome diversity in chronic HIV-infected patients in China. Emerg Microbes Infect 2016; 5:e31. [PMID: 27048741 PMCID: PMC4855070 DOI: 10.1038/emi.2016.25] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2015] [Revised: 10/06/2015] [Accepted: 12/23/2015] [Indexed: 02/06/2023]
Abstract
The purpose of this study was to identify fecal bacterial microbiome changes in patients with chronic human immunodeficiency virus (HIV) infection in China. Bacterial 16S rRNA genes were amplified, sequenced (454 pyrosequencing), and clustered into operational taxonomic units using the QIIME software. Relative abundance at the phylum and genus levels were calculated. Alpha diversity was determined by Chao 1 and observed-species indices, and beta diversity was determined by double principal component analysis using the estimated phylogeny-based unweighted Unifrac distance matrices. Fecal samples of the patients with chronic HIV-infection tended to be enriched with bacteria of the phyla Firmicutes (47.20%±0.43 relative abundance) and Proteobacteria (37.21%±0.36) compared with those of the non-HIV infected controls (17.95%±0.06 and 3.81%±0.02, respectively). Members of the genus Bilophila were exclusively detected in samples of the non-HIV infected controls. Bacteroides and arabacteroides were more abundant in the chronic HIV-infected patients. Our study indicated that chronic HIV-infected patients in China have a fecal bacterial microbiome composition that is largely different from that found in non-HIV infected controls, and further study is needed to evaluate whether microbiome changes play a role in disease complications in the distal gut, including opportunistic infections.
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13
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Love TMT, Park SY, Giorgi EE, Mack WJ, Perelson AS, Lee HY. SPMM: estimating infection duration of multivariant HIV-1 infections. Bioinformatics 2015; 32:1308-15. [PMID: 26722117 DOI: 10.1093/bioinformatics/btv749] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2015] [Accepted: 12/17/2015] [Indexed: 12/20/2022] Open
Abstract
MOTIVATION Illustrating how HIV-1 is transmitted and how it evolves in the following weeks is an important step for developing effective vaccination and prevention strategies. It is currently possible through DNA sequencing to account for the diverse array of viral strains within an infected individual. This provides an unprecedented opportunity to pinpoint when each patient was infected and which viruses were transmitted. RESULTS Here we develop a mathematical tool for early HIV-1 evolution within a subject whose infection originates either from a single or multiple viral variants. The shifted Poisson mixture model (SPMM) provides a quantitative guideline for segregating viral lineages, which in turn enables us to assess when a subject was infected. The infection duration estimated by SPMM showed a statistically significant linear relationship with that by Fiebig laboratory staging (P = 0.00059) among 37 acutely infected subjects. Our tool provides a functional approach to understanding early genetic diversity, one of the most important parameters for deciphering HIV-1 transmission and predicting the rate of disease progression. AVAILABILITY AND IMPLEMENTATION SPMM, webserver, is available at http://www.hayounlee.org/web-tools.html. CONTACT hayoun@usc.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Tanzy M T Love
- Department of Biostatistics and Computational Biology, University of Rochester, Rochester, New York, 14642, USA
| | - Sung Yong Park
- Department of Molecular Microbiology and Immunology, Keck School of Medicine, University of Southern California, Los Angeles, 90089, USA
| | - Elena E Giorgi
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM 87545, USA and
| | - Wendy J Mack
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, 90089, USA
| | - Alan S Perelson
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM 87545, USA and
| | - Ha Youn Lee
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM 87545, USA and
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14
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Ode H, Matsuda M, Matsuoka K, Hachiya A, Hattori J, Kito Y, Yokomaku Y, Iwatani Y, Sugiura W. Quasispecies Analyses of the HIV-1 Near-full-length Genome With Illumina MiSeq. Front Microbiol 2015; 6:1258. [PMID: 26617593 PMCID: PMC4641896 DOI: 10.3389/fmicb.2015.01258] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2015] [Accepted: 10/29/2015] [Indexed: 12/29/2022] Open
Abstract
Human immunodeficiency virus type-1 (HIV-1) exhibits high between-host genetic diversity and within-host heterogeneity, recognized as quasispecies. Because HIV-1 quasispecies fluctuate in terms of multiple factors, such as antiretroviral exposure and host immunity, analyzing the HIV-1 genome is critical for selecting effective antiretroviral therapy and understanding within-host viral coevolution mechanisms. Here, to obtain HIV-1 genome sequence information that includes minority variants, we sought to develop a method for evaluating quasispecies throughout the HIV-1 near-full-length genome using the Illumina MiSeq benchtop deep sequencer. To ensure the reliability of minority mutation detection, we applied an analysis method of sequence read mapping onto a consensus sequence derived from de novo assembly followed by iterative mapping and subsequent unique error correction. Deep sequencing analyses of aHIV-1 clone showed that the analysis method reduced erroneous base prevalence below 1% in each sequence position and discarded only < 1% of all collected nucleotides, maximizing the usage of the collected genome sequences. Further, we designed primer sets to amplify the HIV-1 near-full-length genome from clinical plasma samples. Deep sequencing of 92 samples in combination with the primer sets and our analysis method provided sufficient coverage to identify >1%-frequency sequences throughout the genome. When we evaluated sequences of pol genes from 18 treatment-naïve patients' samples, the deep sequencing results were in agreement with Sanger sequencing and identified numerous additional minority mutations. The results suggest that our deep sequencing method would be suitable for identifying within-host viral population dynamics throughout the genome.
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Affiliation(s)
- Hirotaka Ode
- Department of Infectious Diseases and Immunology, Clinical Research Center, National Hospital Organization Nagoya Medical Center Nagoya, Japan
| | - Masakazu Matsuda
- Department of Infectious Diseases and Immunology, Clinical Research Center, National Hospital Organization Nagoya Medical Center Nagoya, Japan
| | - Kazuhiro Matsuoka
- Department of Infectious Diseases and Immunology, Clinical Research Center, National Hospital Organization Nagoya Medical Center Nagoya, Japan
| | - Atsuko Hachiya
- Department of Infectious Diseases and Immunology, Clinical Research Center, National Hospital Organization Nagoya Medical Center Nagoya, Japan
| | - Junko Hattori
- Department of Infectious Diseases and Immunology, Clinical Research Center, National Hospital Organization Nagoya Medical Center Nagoya, Japan
| | - Yumiko Kito
- Department of Infectious Diseases and Immunology, Clinical Research Center, National Hospital Organization Nagoya Medical Center Nagoya, Japan
| | - Yoshiyuki Yokomaku
- Department of Infectious Diseases and Immunology, Clinical Research Center, National Hospital Organization Nagoya Medical Center Nagoya, Japan
| | - Yasumasa Iwatani
- Department of Infectious Diseases and Immunology, Clinical Research Center, National Hospital Organization Nagoya Medical Center Nagoya, Japan ; Department of AIDS Research, Graduate School of Medicine, Nagoya University Nagoya, Japan
| | - Wataru Sugiura
- Department of Infectious Diseases and Immunology, Clinical Research Center, National Hospital Organization Nagoya Medical Center Nagoya, Japan ; Department of AIDS Research, Graduate School of Medicine, Nagoya University Nagoya, Japan
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15
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Identifying Recent HIV Infections: From Serological Assays to Genomics. Viruses 2015; 7:5508-24. [PMID: 26512688 PMCID: PMC4632395 DOI: 10.3390/v7102887] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2015] [Revised: 10/12/2015] [Accepted: 10/13/2015] [Indexed: 01/07/2023] Open
Abstract
In this paper, we review serological and molecular based methods to identify HIV infection recency. The accurate identification of recent HIV infection continues to be an important research area and has implications for HIV prevention and treatment interventions. Longitudinal cohorts that follow HIV negative individuals over time are the current gold standard approach, but they are logistically challenging, time consuming and an expensive enterprise. Methods that utilize cross-sectional testing and biomarker information have become an affordable alternative to the longitudinal approach. These methods use well-characterized biological makers to differentiate between recent and established HIV infections. However, recent results have identified a number of limitations in serological based assays that are sensitive to the variability in immune responses modulated by HIV subtypes, viral load and antiretroviral therapy. Molecular methods that explore the dynamics between the timing of infection and viral evolution are now emerging as a promising approach. The combination of serological and molecular methods may provide a good solution to identify recent HIV infection in cross-sectional data. As part of this review, we present the advantages and limitations of serological and molecular based methods and their potential complementary role for the identification of HIV infection recency.
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16
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Assessing Biases in the Evaluation of Classification Assays for HIV Infection Recency. PLoS One 2015; 10:e0139735. [PMID: 26436915 PMCID: PMC4593552 DOI: 10.1371/journal.pone.0139735] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2015] [Accepted: 09/15/2015] [Indexed: 12/03/2022] Open
Abstract
Identifying recent HIV infection cases has important public health and clinical implications. It is essential for estimating incidence rates to monitor epidemic trends and evaluate the effectiveness of interventions. Detecting recent cases is also important for HIV prevention given the crucial role that recently infected individuals play in disease transmission, and because early treatment onset can improve the clinical outlook of patients while reducing transmission risk. Critical to this enterprise is the development and proper assessment of accurate classification assays that, based on cross-sectional samples of viral sequences, help determine infection recency status. In this work we assess some of the biases present in the evaluation of HIV recency classification algorithms that rely on measures of within-host viral diversity. Particularly, we examine how the time since infection (TSI) distribution of the infected subjects from which viral samples are drawn affect performance metrics (e.g., area under the ROC curve, sensitivity, specificity, accuracy and precision), potentially leading to misguided conclusions about the efficacy of classification assays. By comparing the performance of a given HIV recency assay using six different TSI distributions (four simulated TSI distributions representing different epidemic scenarios, and two empirical TSI distributions), we show that conclusions about the overall efficacy of the assay depend critically on properties of the TSI distribution. Moreover, we demonstrate that an assay with high overall classification accuracy, mainly due to properly sorting members of the well-represented groups in the validation dataset, can still perform notoriously poorly when sorting members of the less represented groups. This is an inherent issue of classification and diagnostics procedures that is often underappreciated. Thus, this work underscores the importance of acknowledging and properly addressing evaluation biases when proposing new HIV recency assays.
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17
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Montoya V, Olmstead AD, Janjua NZ, Tang P, Grebely J, Cook D, Richard Harrigan P, Krajden M. Differentiation of acute from chronic hepatitis C virus infection by nonstructural 5B deep sequencing: a population-level tool for incidence estimation. Hepatology 2015; 61:1842-50. [PMID: 25645961 DOI: 10.1002/hep.27734] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2014] [Accepted: 01/28/2015] [Indexed: 01/19/2023]
Abstract
UNLABELLED The ability to classify acute versus chronic hepatitis C virus (HCV) infections at the time of diagnosis is desirable to improve the quality of surveillance information. The aim of this study was to differentiate acute from chronic HCV infections utilizing deep sequencing. HCV nonstructural 5B (NS5B) amplicons (n = 94) were generated from 77 individuals (13 acute and 64 chronic HCV infections) in British Columbia, Canada, with documented seroconversion time frames. Amplicons were deep sequenced and HCV genomic diversity was measured by Shannon entropy (SE) and a single nucleotide variant (SNV) analysis. The relationship between each diversity measure and the estimated days since infection was assessed using linear mixed models, and the ability of each diversity measure to differentiate acute from chronic infections was assessed using generalized estimating equations. Both SE and the SNV diversity measures were significantly different for acute versus chronic infections (P < 0.009). NS5B nucleotide diversity continued to increase for at least 3 years postinfection. Among individuals with the least uncertainty with regard to duration of infection (n = 39), the area under the receiver operating characteristic curve (AUROC) was high (0.96 for SE; 0.98 for SNV). Although the AUROCs were lower (0.86 for SE; 0.80 for SNV) when data for all individuals were included, they remain sufficiently high for epidemiological purposes. Synonymous mutations were the primary discriminatory variable accounting for over 78% of the measured genetic diversity. CONCLUSIONS NS5B sequence diversity assessed by deep sequencing can differentiate acute from chronic HCV infections and, with further validation, could become a powerful population-level surveillance tool for incidence estimation.
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Affiliation(s)
- Vincent Montoya
- BC Center for Disease Control, Vancouver, British Columbia, Canada.,University of British Columbia, Vancouver, British Columbia, Canada
| | - Andrea D Olmstead
- BC Center for Disease Control, Vancouver, British Columbia, Canada.,University of British Columbia, Vancouver, British Columbia, Canada
| | - Naveed Z Janjua
- BC Center for Disease Control, Vancouver, British Columbia, Canada.,University of British Columbia, Vancouver, British Columbia, Canada
| | - Patrick Tang
- BC Center for Disease Control, Vancouver, British Columbia, Canada.,University of British Columbia, Vancouver, British Columbia, Canada
| | - Jason Grebely
- The Kirby Institute, University of New South Wales, Sydney, New South Wales, Australia
| | - Darrel Cook
- BC Center for Disease Control, Vancouver, British Columbia, Canada
| | - P Richard Harrigan
- BC Center for Excellence in HIV/AIDS, St Paul's Hospital, Vancouver, British Columbia, Canada
| | - Mel Krajden
- BC Center for Disease Control, Vancouver, British Columbia, Canada.,University of British Columbia, Vancouver, British Columbia, Canada
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18
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Cousins MM, Konikoff J, Sabin D, Khaki L, Longosz AF, Laeyendecker O, Celum C, Buchbinder SP, Seage GR, Kirk GD, Moore RD, Mehta SH, Margolick JB, Brown J, Mayer KH, Kobin BA, Wheeler D, Justman JE, Hodder SL, Quinn TC, Brookmeyer R, Eshleman SH. A comparison of two measures of HIV diversity in multi-assay algorithms for HIV incidence estimation. PLoS One 2014; 9:e101043. [PMID: 24968135 PMCID: PMC4072769 DOI: 10.1371/journal.pone.0101043] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2014] [Accepted: 06/03/2014] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Multi-assay algorithms (MAAs) can be used to estimate HIV incidence in cross-sectional surveys. We compared the performance of two MAAs that use HIV diversity as one of four biomarkers for analysis of HIV incidence. METHODS Both MAAs included two serologic assays (LAg-Avidity assay and BioRad-Avidity assay), HIV viral load, and an HIV diversity assay. HIV diversity was quantified using either a high resolution melting (HRM) diversity assay that does not require HIV sequencing (HRM score for a 239 base pair env region) or sequence ambiguity (the percentage of ambiguous bases in a 1,302 base pair pol region). Samples were classified as MAA positive (likely from individuals with recent HIV infection) if they met the criteria for all of the assays in the MAA. The following performance characteristics were assessed: (1) the proportion of samples classified as MAA positive as a function of duration of infection, (2) the mean window period, (3) the shadow (the time period before sample collection that is being assessed by the MAA), and (4) the accuracy of cross-sectional incidence estimates for three cohort studies. RESULTS The proportion of samples classified as MAA positive as a function of duration of infection was nearly identical for the two MAAs. The mean window period was 141 days for the HRM-based MAA and 131 days for the sequence ambiguity-based MAA. The shadows for both MAAs were <1 year. Both MAAs provided cross-sectional HIV incidence estimates that were very similar to longitudinal incidence estimates based on HIV seroconversion. CONCLUSIONS MAAs that include the LAg-Avidity assay, the BioRad-Avidity assay, HIV viral load, and HIV diversity can provide accurate HIV incidence estimates. Sequence ambiguity measures obtained using a commercially-available HIV genotyping system can be used as an alternative to HRM scores in MAAs for cross-sectional HIV incidence estimation.
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Affiliation(s)
- Matthew M. Cousins
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Jacob Konikoff
- Department of Biostatistics, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America
| | - Devin Sabin
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Leila Khaki
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Andrew F. Longosz
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Oliver Laeyendecker
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Connie Celum
- Departments of Global Health and Medicine, University of Washington, Seattle, Washington, United States of America
| | - Susan P. Buchbinder
- Bridge HIV, San Francisco Department of Health, San Francisco, California, United States of America
- Departments of Epidemiology and Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - George R. Seage
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, United States of America
| | - Gregory D. Kirk
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Richard D. Moore
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Shruti H. Mehta
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Joseph B. Margolick
- Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Joelle Brown
- Department of Epidemiology, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, United States of America
| | - Kenneth H. Mayer
- The Fenway Institute/Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, Massachusetts, United States of America
| | - Beryl A. Kobin
- Laboratory of Infectious Disease Prevention, New York Blood Center, New York, New York, United States of America
| | - Darrell Wheeler
- Graduate School of Social Work, Loyola University Chicago, Chicago, Illinois, United States of America
| | - Jessica E. Justman
- Departments of Epidemiology and Medicine, Columbia University, New York, New York, United States of America
| | - Sally L. Hodder
- Department of Medicine, Division of Infectious Diseases, New Jersey Medical School, Newark, New Jersey, United States of America
| | - Thomas C. Quinn
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Ron Brookmeyer
- Department of Biostatistics, School of Public Health, University of California Los Angeles, Los Angeles, California, United States of America
| | - Susan H. Eshleman
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- * E-mail:
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Quiñones-Mateu ME, Avila S, Reyes-Teran G, Martinez MA. Deep sequencing: becoming a critical tool in clinical virology. J Clin Virol 2014; 61:9-19. [PMID: 24998424 DOI: 10.1016/j.jcv.2014.06.013] [Citation(s) in RCA: 90] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2014] [Revised: 06/12/2014] [Accepted: 06/14/2014] [Indexed: 02/07/2023]
Abstract
Population (Sanger) sequencing has been the standard method in basic and clinical DNA sequencing for almost 40 years; however, next-generation (deep) sequencing methodologies are now revolutionizing the field of genomics, and clinical virology is no exception. Deep sequencing is highly efficient, producing an enormous amount of information at low cost in a relatively short period of time. High-throughput sequencing techniques have enabled significant contributions to multiples areas in virology, including virus discovery and metagenomics (viromes), molecular epidemiology, pathogenesis, and studies of how viruses to escape the host immune system and antiviral pressures. In addition, new and more affordable deep sequencing-based assays are now being implemented in clinical laboratories. Here, we review the use of the current deep sequencing platforms in virology, focusing on three of the most studied viruses: human immunodeficiency virus (HIV), hepatitis C virus (HCV), and influenza virus.
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Affiliation(s)
- Miguel E Quiñones-Mateu
- University Hospital Translational Laboratory, University Hospitals Case Medical Center, Cleveland, OH, USA; Department of Pathology, Case Western Reserve University, Cleveland, OH, USA
| | - Santiago Avila
- Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico; Centro de Investigaciones en Enfermedades Infecciosas, Mexico City, Mexico
| | - Gustavo Reyes-Teran
- Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico; Centro de Investigaciones en Enfermedades Infecciosas, Mexico City, Mexico
| | - Miguel A Martinez
- Fundació irsicaixa, Universitat Autònoma de Barcelona, Hospital Universitari Germans Trias i Pujol, Badalona, Spain
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Assessment of ambiguous base calls in HIV-1 pol population sequences as a biomarker for identification of recent infections in HIV-1 incidence studies. J Clin Microbiol 2014; 52:2977-83. [PMID: 24920768 DOI: 10.1128/jcm.03289-13] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
An increase in the proportion of ambiguous base calls in HIV-1 pol population sequences during the course of infection has been demonstrated in different study populations, and sequence ambiguity thresholds to classify infections as recent or nonrecent have been suggested. The aim of our study was to evaluate sequence ambiguities as a candidate biomarker for use in an HIV-1 incidence assay using samples from antiretroviral treatment-naive seroconverters with known durations of infection (German HIV-1 Seroconverter Study). We used 2,203 HIV-1 pol population sequences derived from 1,334 seroconverters to assess the sequence ambiguity method (SAM). We then compared the serological incidence BED capture enzyme immunoassay (BED-CEIA) with the SAM for a subset of 723 samples from 495 seroconverters and evaluated a multianalyte algorithm that includes BED-CEIA results, SAM results, viral loads, and CD4 cell counts for 453 samples from 325 seroconverters. We observed a significant increase in the proportion of sequence ambiguities with the duration of infection. A sequence ambiguity threshold of 0.5% best identified recent infections with 76.7% accuracy. The mean duration of recency was determined to be 208 (95% confidence interval, 196 to 221) days. In the subset analysis, BED-CEIA achieved a significantly higher accuracy than the SAM (84.6 versus 75.5%, P < 0.001) and results were concordant for 64.2% (464/723) of the samples. Also, the multianalyte algorithm did not show better accuracy than the BED-CEIA (83.4 versus 84.3%, P = 0.786). In conclusion, the SAM and the multianalyte algorithm including SAM were inferior to the BED-CEIA, and the proportion of sequence ambiguities is therefore not a preferable biomarker for HIV-1 incidence testing.
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