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Biba C, Fiaschi L, Varasi I, Paletti C, Bartolini N, Zazzi M, Vicenti I, Saladini F. A Comparison of Sanger Sequencing and Amplicon-Based Next Generation Sequencing Approaches for the Detection of HIV-1 Drug Resistance Mutations. Viruses 2024; 16:1465. [PMID: 39339940 PMCID: PMC11437444 DOI: 10.3390/v16091465] [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: 08/22/2024] [Revised: 09/10/2024] [Accepted: 09/13/2024] [Indexed: 09/30/2024] Open
Abstract
BACKGROUND Next-generation sequencing (NGS) kits are needed to finalise the transition from Sanger sequencing to NGS in HIV-1 genotypic drug resistance testing. MATERIALS AND METHODS We compared a homemade NGS amplicon-based protocol and the AD4SEQ HIV-1 Solution v2 (AD4SEQ) NGS kit from Arrow Diagnostics for identifying resistance-associated mutations (RAMs) above the 5% threshold in 28 plasma samples where Sanger sequencing previously detected at least one RAM. RESULTS The samples had a median 4.8 log [IQR 4.4-5.2] HIV-1 RNA copies/mL and were mostly subtype B (61%) and CRF02_AG (14%). Homemade NGS had a lower rate of samples with low-coverage regions (2/28) compared with AD4SEQ (13/28) (p < 0.001). Homemade NGS and AD4SEQ identified additional mutations with respect to Sanger sequencing in 13/28 and 9/28 samples, respectively. However, there were two and eight cases where mutations detected by Sanger sequencing were missed by homemade NGS and AD4SEQ-SmartVir, respectively. The discrepancies between NGS and Sanger sequencing resulted in a few minor differences in drug susceptibility interpretation, mostly for NNRTIs. CONCLUSIONS Both the NGS systems identified additional mutations with respect to Sanger sequencing, and the agreement between them was fair. However, AD4SEQ should benefit from technical adjustments allowing higher sequence coverage.
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Affiliation(s)
| | | | | | | | | | | | - Ilaria Vicenti
- Department of Medical Biotechnologies, University of Siena, 53100 Siena, Italy; (C.B.); (L.F.); (I.V.); (C.P.); (N.B.); (M.Z.); (F.S.)
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2
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Balakrishna S, Loosli T, Zaheri M, Frischknecht P, Huber M, Kusejko K, Yerly S, Leuzinger K, Perreau M, Ramette A, Wymant C, Fraser C, Kellam P, Gall A, Hirsch HH, Stoeckle M, Rauch A, Cavassini M, Bernasconi E, Notter J, Calmy A, Günthard HF, Metzner KJ, Kouyos RD. Frequency matters: comparison of drug resistance mutation detection by Sanger and next-generation sequencing in HIV-1. J Antimicrob Chemother 2023; 78:656-664. [PMID: 36738248 DOI: 10.1093/jac/dkac430] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 11/18/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Next-generation sequencing (NGS) is gradually replacing Sanger sequencing (SS) as the primary method for HIV genotypic resistance testing. However, there are limited systematic data on comparability of these methods in a clinical setting for the presence of low-abundance drug resistance mutations (DRMs) and their dependency on the variant-calling thresholds. METHODS To compare the HIV-DRMs detected by SS and NGS, we included participants enrolled in the Swiss HIV Cohort Study (SHCS) with SS and NGS sequences available with sample collection dates ≤7 days apart. We tested for the presence of HIV-DRMs and compared the agreement between SS and NGS at different variant-calling thresholds. RESULTS We included 594 pairs of SS and NGS from 527 SHCS participants. Males accounted for 80.5% of the participants, 76.3% were ART naive at sample collection and 78.1% of the sequences were subtype B. Overall, we observed a good agreement (Cohen's kappa >0.80) for HIV-DRMs for variant-calling thresholds ≥5%. We observed an increase in low-abundance HIV-DRMs detected at lower thresholds [28/417 (6.7%) at 10%-25% to 293/812 (36.1%) at 1%-2% threshold]. However, such low-abundance HIV-DRMs were overrepresented in ART-naive participants and were in most cases not detected in previously sampled sequences suggesting high sequencing error for thresholds <3%. CONCLUSIONS We found high concordance between SS and NGS but also a substantial number of low-abundance HIV-DRMs detected only by NGS at lower variant-calling thresholds. Our findings suggest that a substantial fraction of the low-abundance HIV-DRMs detected at thresholds <3% may represent sequencing errors and hence should not be overinterpreted in clinical practice.
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Affiliation(s)
- Suraj Balakrishna
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Tom Loosli
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Maryam Zaheri
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland.,Swiss National Center for Retroviruses, University of Zurich, Zurich, Switzerland
| | - Paul Frischknecht
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Michael Huber
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland.,Swiss National Center for Retroviruses, University of Zurich, Zurich, Switzerland
| | - Katharina Kusejko
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Sabine Yerly
- Laboratory of Virology, University Hospital Geneva, University of Geneva, Geneva, Switzerland
| | - Karoline Leuzinger
- Clinical Virology Division, Laboratory Medicine, University Hospital Basel, Basel, Switzerland
| | - Matthieu Perreau
- Division of Immunology and Allergy, University Hospital Lausanne, University of Lausanne, Lausanne, Switzerland
| | - Alban Ramette
- Institute for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Chris Wymant
- Nuffield Department of Medicine, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Christophe Fraser
- Nuffield Department of Medicine, Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.,Nuffield Department of Medicine, Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Paul Kellam
- Department of Infectious Diseases, Faculty of Medicine, Imperial College London, London, UK
| | - Astrid Gall
- Excellence in Life Sciences (EMBO), Heidelberg, Germany
| | - Hans H Hirsch
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Marcel Stoeckle
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Andri Rauch
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Matthias Cavassini
- Division of Infectious Diseases, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland
| | - Enos Bernasconi
- Division of Infectious Diseases, Regional Hospital Lugano, Lugano, Switzerland
| | - Julia Notter
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St Gallen, St Gallen, Switzerland
| | - Alexandra Calmy
- Division of Infectious Diseases, University Hospital Geneva, University of Geneva, Geneva, Switzerland
| | - Huldrych F Günthard
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Karin J Metzner
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Roger D Kouyos
- Department of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
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3
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Sertoz R, Tekin D, Erensoy S, Biceroglu S, Kaptan F, Köse S, Ozkan H, Cetin B, Türken M, Gokengin D. Prevalence of Transmitted Drug Resistance among HIV-1 Patients in the Aegean Region: Results from the Western Part of Turkey. Curr HIV Res 2023; 21:109-116. [PMID: 37231747 DOI: 10.2174/1570162x21666230525145529] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 03/23/2023] [Accepted: 03/27/2023] [Indexed: 05/27/2023]
Abstract
OBJECTIVES This study aimed to analyze the antiretroviral drug resistance in antiretroviral treatment-naïve HIV-positive patients in the Aegean Region of Turkey from 2012 to 2019. METHODS The study included 814 plasma samples from treatment-naïve HIV-positive patients. Drug resistance analysis was performed by Sanger sequencing (SS) between 2012-2017 and by next-generation sequencing sequencing (NGS) between 2018-2019. SS was used to analyze resistance mutations in the protease (PR) and reverse transcriptase (RT) gene regions using a ViroSeq HIV-1 Genotyping System. PCR products were analyzed with an ABI3500 GeneticAnalyzer (Applied Biosystems). The sequencing of the HIV genome in the PR, RT, and integrase gene regions was carried out using MiSeq NGS technology. Drug resistance mutations and subtypes were interpreted using the Stanford University HIV-1 drug resistance database. RESULTS Transmitted drug resistance (TDR) mutation was detected in 34/814 (4.1 %) samples. Nonnucleoside reverse transcriptase inhibitor (NNRTI), nucleoside reverse transcriptase inhibitor (NRTI), and protease inhibitor (PI) mutations were identified in 1.4 % (n =12), 2.4 % (n =20), and 0.3 % (n = 3) of samples, respectively. The most common subtypes were B (53.1 %), A (10.9%), CRF29_BF (10.6%), and B + CRF02_AG (8,2%). The most common TDR mutations were E138A (3.4%), T215 revertants (1.7%), M41L (1.5%), and K103N (1.1%). CONCLUSION Transmitted drug resistance rate in the Aegean Region is compatible with national and regional data. Routine surveillance of resistance mutations may guide the safe and correct selection of initial drug combinations for antiretroviral therapy. The identification of HIV-1 subtypes and recombinant forms in Turkey may contribute to international molecular epidemiological data.
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Affiliation(s)
- Ruchan Sertoz
- Department of Medical Microbiology, Ege University Medical School, Izmir, Turkey
| | - Duygu Tekin
- Department of Medical Microbiology, Tepecik Training and Research Hospital, Izmir, Turkey
| | - Selda Erensoy
- Department of Medical Microbiology, Ege University Medical School, Izmir, Turkey
| | - Servet Biceroglu
- Department of Medical Microbiology, Ege University Medical School, Izmir, Turkey
| | - Figen Kaptan
- Department of Clinical Microbiology and Infectious Diseases, Atatürk Training and Research Hospital, Izmir, Turkey
| | - Sukran Köse
- Department of Clinical Microbiology and Infectious Diseases, Tepecik Training and Research Hospital, Izmir, Turkey
| | - Hulya Ozkan
- Department of Clinical Microbiology and Infectious Diseases, Bozyaka Training and Research Hospital, Izmir, Turkey
| | - Banu Cetin
- Department of Clinical Microbiology and Infectious Diseases, Celal Bayar University Medical School, Izmir, Turkey
| | - Melda Türken
- Department of Clinical Microbiology and Infectious Diseases, Tepecik Training and Research Hospital, Izmir, Turkey
| | - Deniz Gokengin
- Department of Clinical Microbiology and Infectious Diseases, Ege University Medical School, Izmir, Turkey
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Li Y, Han L, Wang Y, Wang X, Jia L, Li J, Han J, Zhao J, Li H, Li L. Establishment and application of a method of tagged-amplicon deep sequencing for low-abundance drug resistance in HIV-1. Front Microbiol 2022; 13:895227. [PMID: 36071961 PMCID: PMC9444182 DOI: 10.3389/fmicb.2022.895227] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Accepted: 07/29/2022] [Indexed: 11/16/2022] Open
Abstract
In the latest HIV-1 global drug resistance report released by WHO, countries are advised to strengthen pre-treatment monitoring of drug resistance in AIDS patients. In this study, we established an NGS-based segmented amplification HIV-1 drug resistance mutation detection method. The pol region of HIV-1 was divided into three short fragments for NGS. The entire amplification and sequencing panel were more cost-effective and batched by using the barcode sequence corresponding to the sample. Each parameter was evaluated using samples with known resistance variants frequencies. The nucleotide sequence error rate, amino acid error rate, and noise value of the NGS-based segmented amplification method were both less than 1%. When the threshold was 2%, the consensus sequences of the HIV-1 NL4-3 strain were completely consistent with the Sanger sequences. This method can detect the minimum viral load of the sample at 102 copies/ml, and the input frequency and detection frequency of HIV-1 resistance mutations within the range of 1%–100% had good conformity (R2 = 0.9963; R2 = 0.9955). This method had no non-specific amplification for Hepatitis B and C. Under the 2% threshold, the incidence of surveillance drug resistance mutations in ART-naive HIV-infected patients was 20.69%, among which NRTIs class resistance mutations were mainly.
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Affiliation(s)
- Yang Li
- School of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, China
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Leilei Han
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
- School of Public Health, North China University of Science and Technology, Tangshan, Hebei, China
| | - Yanglan Wang
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
- College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, China
| | - Xiaolin Wang
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Lei Jia
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Jingyun Li
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Jingwan Han
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Jin Zhao
- Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China
| | - Hanping Li
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
- *Correspondence: Hanping Li,
| | - Lin Li
- School of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, China
- Department of Virology, State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
- Lin Li,
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Sarinoglu RC, Sili U, Hasdemir U, Aksu B, Soyletir G, Korten V. Diversity of HIV-1 subtypes and transmitted drug-resistance mutations among minority HIV-1 variants in a Turkish cohort. Curr HIV Res 2021; 20:54-62. [PMID: 34802406 DOI: 10.2174/1570162x19666211119111740] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 08/02/2021] [Accepted: 08/13/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND The World Health Organization (WHO) recommends the surveillance of transmitted drug resistance mutations (TDRMs) to ensure the effectiveness and sustainability of HIV treatment programs. OBJECTIVE Our aim was to determine the TDRMs and evaluate the distribution of HIV-1 subtypes using and compared next-generation sequencing (NGS) and Sanger-based sequencing (SBS) in a cohort of 44 antiretroviral treatment-naïve patients. METHODS All samples that were referred to the microbiology laboratory for HIV drug resistance analysis between December 2016 and February 2018 were included in the study. After exclusions, 44 treatment-naive adult patients with a viral load of >1000 copies/mL were analyzed. DNA sequencing for reverse transcriptase and protease regions was performed using both DeepChek ABL single round kit and Sanger-based ViroSeq HIV-1 Genotyping System. The mutations and HIV-1 subtypes were analyzed using the Stanford HIVdb version 8.6.1 Genotypic Resistance software, and TDRMs were assessed using the WHO surveillance drug-resistance mutation database. HIV-1 subtypes were confirmed by constructing a maximum-likelihood phylogenetic tree using Los Alamos IQ-Tree software. RESULTS NGS identified nucleos(t)ide reverse transcriptase inhibitor (NRTI)-TDRMs in 9.1% of the patients, non-nucleos(t)ide reverse transcriptase inhibitor (NNRTI)-TDRMs in 6.8% of the patients, and protease inhibitor (PI)-TDRMs in 18.2% of the patients at a detection threshold of ≥1%. Using SBS, 2.3% and 6.8% of the patients were found to have NRTI- and NNRTI-TDRMs, respectively, but no major PI mutations were detected. M41L, L74I, K65R, M184V, and M184I related to NRTI, K103N to NNRTI, and N83D, M46I, I84V, V82A, L24I, L90M, I54V to the PI sites were identified using NGS. Most mutations were found in low-abundance (frequency range: 1.0% - 4.7%) HIV-1 variants, except M41L and K103N. The subtypes of the isolates were found as follows; 61.4% subtype B, 18.2% subtype B/CRF02_AG recombinant, 13.6% subtype A, 4.5% CRF43_02G, and 2.3% CRF02_AG. All TDRMs, except K65R, were detected in HIV-1 subtype B isolates. CONCLUSION The high diversity of protease site TDRMs in the minority HIV-1 variants and prevalence of CRFs were remarkable in this study. All minority HIV-1 variants were missed by conventional sequencing. TDRM prevalence among minority variants appears to be decreasing over time at our center.
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Affiliation(s)
- Rabia Can Sarinoglu
- Marmara University School of Medicine, Pendik Training and Research Hospital, Department of Medical Microbiology, Istanbul. Turkey
| | - Uluhan Sili
- Marmara University School of Medicine, Pendik Training and Research Hospital, Department of Infectious Diseases and Clinical Microbiology, Istanbul. Turkey
| | - Ufuk Hasdemir
- Marmara University School of Medicine, Pendik Training and Research Hospital, Department of Medical Microbiology, Istanbul. Turkey
| | - Burak Aksu
- Marmara University School of Medicine, Pendik Training and Research Hospital, Department of Medical Microbiology, Istanbul. Turkey
| | - Guner Soyletir
- Marmara University School of Medicine, Pendik Training and Research Hospital, Department of Medical Microbiology, Istanbul. Turkey
| | - Volkan Korten
- Marmara University School of Medicine, Pendik Training and Research Hospital, Department of Infectious Diseases and Clinical Microbiology, Istanbul. Turkey
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Manyana S, Gounder L, Pillay M, Manasa J, Naidoo K, Chimukangara B. HIV-1 Drug Resistance Genotyping in Resource Limited Settings: Current and Future Perspectives in Sequencing Technologies. Viruses 2021; 13:1125. [PMID: 34208165 PMCID: PMC8230827 DOI: 10.3390/v13061125] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 05/27/2021] [Accepted: 05/31/2021] [Indexed: 12/14/2022] Open
Abstract
Affordable, sensitive, and scalable technologies are needed for monitoring antiretroviral treatment (ART) success with the goal of eradicating HIV-1 infection. This review discusses use of Sanger sequencing and next generation sequencing (NGS) methods for HIV-1 drug resistance (HIVDR) genotyping, focusing on their use in resource limited settings (RLS). Sanger sequencing remains the gold-standard method for detecting HIVDR mutations of clinical relevance but is mainly limited by high sequencing costs and low-throughput. NGS is becoming a more common sequencing method, with the ability to detect low-abundance drug-resistant variants and reduce per sample costs through sample pooling and massive parallel sequencing. However, use of NGS in RLS is mainly limited by infrastructure costs. Given these shortcomings, our review discusses sequencing technologies for HIVDR genotyping, focusing on common in-house and commercial assays, challenges with Sanger sequencing in keeping up with changes in HIV-1 treatment programs, as well as challenges with NGS that limit its implementation in RLS and in clinical diagnostics. We further discuss knowledge gaps and offer recommendations on how to overcome existing barriers for implementing HIVDR genotyping in RLS, to make informed clinical decisions that improve quality of life for people living with HIV.
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Affiliation(s)
- Sontaga Manyana
- National Health Laboratory Service, Department of Virology, School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban 4058, South Africa; (L.G.); (M.P.); (B.C.)
| | - Lilishia Gounder
- National Health Laboratory Service, Department of Virology, School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban 4058, South Africa; (L.G.); (M.P.); (B.C.)
| | - Melendhran Pillay
- National Health Laboratory Service, Department of Virology, School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban 4058, South Africa; (L.G.); (M.P.); (B.C.)
| | - Justen Manasa
- Department of Laboratory Medicine and Investigative Sciences, Faculty of Medicine and Health Sciences, University of Zimbabwe, Harare, Zimbabwe;
| | - Kogieleum Naidoo
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban 4013, South Africa;
- South African Medical Research Council (SAMRC), CAPRISA HIV-TB Pathogenesis and Treatment Research Unit, Durban 4013, South Africa
| | - Benjamin Chimukangara
- National Health Laboratory Service, Department of Virology, School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban 4058, South Africa; (L.G.); (M.P.); (B.C.)
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban 4013, South Africa;
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