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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
Identification of HIV superinfection in seroconcordant couples in Rakai, Uganda, by use of next-generation deep sequencing
Journal of Clinical Microbiology, Volume 49, No. 8, Year 2011
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Description
HIV superinfection, which occurs when a previously infected individual acquires a new distinct HIV strain, has been described in a number of populations. Previous methods to detect superinfection have involved a combination of labor-intensive assays with various rates of success. We designed and tested a next-generation sequencing (NGS) protocol to identify HIV superinfection by targeting two regions of the HIV viral genome, p24 and gp41. The method was validated by mixing control samples infected with HIV subtype A or D at different ratios to determine the inter- and intrasubtype sensitivity by NGS. This amplicon-based NGS protocol was able to consistently identify distinct intersubtype strains at ratios of 1% and intrasubtype variants at ratios of 5%. By using stored samples from the Rakai Community Cohort Study (RCCS) in Uganda, 11 individuals who were HIV seroconcordant but virally unlinked from their spouses were then tested by this method to detect superinfection between 2002 and 2005. Two female cases of HIV intersubtype superinfection (18.2%) were identified. These results are consistent with other African studies and support the hypothesis that HIV superinfection occurs at a relatively high rate. Our results indicate that NGS can be used for detection of HIV superinfection within large cohorts, which could assist in determining the incidence and the epidemiologic, virologic, and immunological correlates of this phenomenon. Copyright © 2011, American Society for Microbiology. All Rights Reserved.
Available Materials
https://efashare.b-cdn.net/share/pmc/articles/PMC3147722/bin/supp_49_8_2859__index.html
https://efashare.b-cdn.net/share/pmc/articles/PMC3147722/bin/supp_49_8_2859__Superinfection_Appendix_figures_JCM.ppt
https://efashare.b-cdn.net/share/pmc/articles/PMC3147722/bin/supp_49_8_2859__Appendix_Methods_and_Figure_Legends_JCM_resubmission.doc
Authors & Co-Authors
Redd, Andrew D.
United States, Bethesda
National Institute of Allergy and Infectious Diseases Niaid
Collinson-Streng, Aleisha N.
United States, Bethesda
National Institute of Allergy and Infectious Diseases Niaid
Martens, Craig A.
United States, Bethesda
National Institutes of Health Nih
Ricklefs, Stacy M.
United States, Bethesda
National Institutes of Health Nih
Mullis, Caroline E.
United States, Baltimore
Johns Hopkins Medical Institutions
Manucci, Jordyn L.
United States, Baltimore
Johns Hopkins Medical Institutions
Tobian, Aaron A.R.
United States, Baltimore
Johns Hopkins Medical Institutions
Selig, Ethan J.
United States, Bethesda
National Institutes of Health Nih
Laeyendecker, Oliver B.
United States, Bethesda
National Institute of Allergy and Infectious Diseases Niaid
United States, Baltimore
Johns Hopkins Medical Institutions
Sewankambo, Nelson K.
Uganda, Kalisizo
Rakai Health Sciences Program
Uganda, Kampala
Makerere University
Gray, Ronald H.
United States, Baltimore
Johns Hopkins Bloomberg School of Public Health
Serwadda, David Musoke
Uganda, Kalisizo
Rakai Health Sciences Program
Uganda, Kampala
Makerere University
Wawer, Maria J.
United States, Baltimore
Johns Hopkins Bloomberg School of Public Health
Porcella, Stephen F.
United States, Bethesda
National Institutes of Health Nih
Quinn, Thomas Charles
United States, Bethesda
National Institute of Allergy and Infectious Diseases Niaid
United States, Baltimore
Johns Hopkins Medical Institutions
Statistics
Citations: 55
Authors: 15
Affiliations: 6
Identifiers
Doi:
10.1128/JCM.00804-11
ISSN:
00951137
e-ISSN:
1098660X
Research Areas
Infectious Diseases
Study Design
Cohort Study
Study Approach
Quantitative
Study Locations
Uganda
Participants Gender
Female