Mapping Polyclonal HIV-1 Antibody Responses via Next-Generation Neutralization Fingerprinting
Computational neutralization fingerprinting, NFP, is an efficient and accurate method for predicting the epitope specificities of polyclonal antibody responses to HIV-1 infection. Here, we present next-generation NFP algorithms that substantially improve prediction accuracy for individual donors and...
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| Published in | PLoS pathogens Vol. 13; no. 1; p. e1006148 |
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| Main Authors | , , , , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
01.01.2017
Public Library of Science (PLoS) |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Computational neutralization fingerprinting, NFP, is an efficient and accurate method for predicting the epitope specificities of polyclonal antibody responses to HIV-1 infection. Here, we present next-generation NFP algorithms that substantially improve prediction accuracy for individual donors and enable serologic analysis for entire cohorts. Specifically, we developed algorithms for: (a) selection of optimized virus neutralization panels for NFP analysis, (b) estimation of NFP prediction confidence for each serum sample, and (c) identification of sera with potentially novel epitope specificities. At the individual donor level, the next-generation NFP algorithms particularly improved the ability to detect multiple epitope specificities in a sample, as confirmed both for computationally simulated polyclonal sera and for samples from HIV-infected donors. Specifically, the next-generation NFP algorithms detected multiple specificities in twice as many samples of simulated sera. Further, unlike the first-generation NFP, the new algorithms were able to detect both of the previously confirmed antibody specificities, VRC01-like and PG9-like, in donor CHAVI 0219. At the cohort level, analysis of ~150 broadly neutralizing HIV-infected donor samples suggested a potential connection between clade of infection and types of elicited epitope specificities. Most notably, while 10E8-like antibodies were observed in infections from different clades, an enrichment of such antibodies was predicted for clade B samples. Ultimately, such large-scale analyses of antibody responses to HIV-1 infection can help guide the design of epitope-specific vaccines that are tailored to take into account the prevalence of infecting clades within a specific geographic region. Overall, the next-generation NFP technology will be an important tool for the analysis of broadly neutralizing polyclonal antibody responses against HIV-1. |
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| AbstractList |
Computational neutralization fingerprinting, NFP, is an efficient and accurate method for predicting the epitope specificities of polyclonal antibody responses to HIV-1 infection. Here, we present next-generation NFP algorithms that substantially improve prediction accuracy for individual donors and enable serologic analysis for entire cohorts. Specifically, we developed algorithms for: (a) selection of optimized virus neutralization panels for NFP analysis, (b) estimation of NFP prediction confidence for each serum sample, and (c) identification of sera with potentially novel epitope specificities. At the individual donor level, the next-generation NFP algorithms particularly improved the ability to detect multiple epitope specificities in a sample, as confirmed both for computationally simulated polyclonal sera and for samples from HIV-infected donors. Specifically, the next-generation NFP algorithms detected multiple specificities in twice as many samples of simulated sera. Further, unlike the first-generation NFP, the new algorithms were able to detect both of the previously confirmed antibody specificities, VRC01-like and PG9-like, in donor CHAVI 0219. At the cohort level, analysis of ~150 broadly neutralizing HIV-infected donor samples suggested a potential connection between clade of infection and types of elicited epitope specificities. Most notably, while 10E8-like antibodies were observed in infections from different clades, an enrichment of such antibodies was predicted for clade B samples. Ultimately, such large-scale analyses of antibody responses to HIV-1 infection can help guide the design of epitope-specific vaccines that are tailored to take into account the prevalence of infecting clades within a specific geographic region. Overall, the next-generation NFP technology will be an important tool for the analysis of broadly neutralizing polyclonal antibody responses against HIV-1. Computational neutralization fingerprinting, NFP, is an efficient and accurate method for predicting the epitope specificities of polyclonal antibody responses to HIV-1 infection. Here, we present next-generation NFP algorithms that substantially improve prediction accuracy for individual donors and enable serologic analysis for entire cohorts. Specifically, we developed algorithms for: (a) selection of optimized virus neutralization panels for NFP analysis, (b) estimation of NFP prediction confidence for each serum sample, and (c) identification of sera with potentially novel epitope specificities. At the individual donor level, the next-generation NFP algorithms particularly improved the ability to detect multiple epitope specificities in a sample, as confirmed both for computationally simulated polyclonal sera and for samples from HIV-infected donors. Specifically, the next-generation NFP algorithms detected multiple specificities in twice as many samples of simulated sera. Further, unlike the first-generation NFP, the new algorithms were able to detect both of the previously confirmed antibody specificities, VRC01-like and PG9-like, in donor CHAVI 0219. At the cohort level, analysis of ~150 broadly neutralizing HIV-infected donor samples suggested a potential connection between clade of infection and types of elicited epitope specificities. Most notably, while 10E8-like antibodies were observed in infections from different clades, an enrichment of such antibodies was predicted for clade B samples. Ultimately, such large-scale analyses of antibody responses to HIV-1 infection can help guide the design of epitope-specific vaccines that are tailored to take into account the prevalence of infecting clades within a specific geographic region. Overall, the next-generation NFP technology will be an important tool for the analysis of broadly neutralizing polyclonal antibody responses against HIV-1. Computational neutralization fingerprinting, NFP, is an efficient and accurate method for predicting the epitope specificities of polyclonal antibody responses to HIV-1 infection. Here, we present next-generation NFP algorithms that substantially improve prediction accuracy for individual donors and enable serologic analysis for entire cohorts. Specifically, we developed algorithms for: (a) selection of optimized virus neutralization panels for NFP analysis, (b) estimation of NFP prediction confidence for each serum sample, and (c) identification of sera with potentially novel epitope specificities. At the individual donor level, the next-generation NFP algorithms particularly improved the ability to detect multiple epitope specificities in a sample, as confirmed both for computationally simulated polyclonal sera and for samples from HIV-infected donors. Specifically, the next-generation NFP algorithms detected multiple specificities in twice as many samples of simulated sera. Further, unlike the first-generation NFP, the new algorithms were able to detect both of the previously confirmed antibody specificities, VRC01-like and PG9-like, in donor CHAVI 0219. At the cohort level, analysis of ~150 broadly neutralizing HIV-infected donor samples suggested a potential connection between clade of infection and types of elicited epitope specificities. Most notably, while 10E8-like antibodies were observed in infections from different clades, an enrichment of such antibodies was predicted for clade B samples. Ultimately, such large-scale analyses of antibody responses to HIV-1 infection can help guide the design of epitope-specific vaccines that are tailored to take into account the prevalence of infecting clades within a specific geographic region. Overall, the next-generation NFP technology will be an important tool for the analysis of broadly neutralizing polyclonal antibody responses against HIV-1. HIV-1 remains a significant global health threat, with no effective vaccine against the virus currently available. Since traditional vaccine design efforts have had limited success, much effort in recent years has focused on gaining a better understanding of the ways select individuals are able to effectively neutralize the virus upon natural infection, and to utilize that knowledge for the design of optimized vaccine candidates. Primary emphasis has been placed on characterizing the antibody arm of the immune system, and specifically on antibodies capable of neutralizing the majority of circulating HIV-1 strains. Various experimental techniques can be applied to map the epitope targets of these antibodies, but more recently, the development of computational methods has provided an efficient and accurate alternative for understanding the complex antibody responses to HIV-1 in a given individual. Here, we present the next generation of this computational technology, and show that these new methods have significantly improved accuracy and confidence, and that they enable the interrogation of biologically important questions that can lead to new insights for the design of an effective vaccine against HIV-1. Computational neutralization fingerprinting, NFP, is an efficient and accurate method for predicting the epitope specificities of polyclonal antibody responses to HIV-1 infection. Here, we present next-generation NFP algorithms that substantially improve prediction accuracy for individual donors and enable serologic analysis for entire cohorts. Specifically, we developed algorithms for: (a) selection of optimized virus neutralization panels for NFP analysis, (b) estimation of NFP prediction confidence for each serum sample, and (c) identification of sera with potentially novel epitope specificities. At the individual donor level, the next-generation NFP algorithms particularly improved the ability to detect multiple epitope specificities in a sample, as confirmed both for computationally simulated polyclonal sera and for samples from HIV-infected donors. Specifically, the next-generation NFP algorithms detected multiple specificities in twice as many samples of simulated sera. Further, unlike the first-generation NFP, the new algorithms were able to detect both of the previously confirmed antibody specificities, VRC01-like and PG9-like, in donor CHAVI 0219. At the cohort level, analysis of ~150 broadly neutralizing HIV-infected donor samples suggested a potential connection between clade of infection and types of elicited epitope specificities. Most notably, while 10E8-like antibodies were observed in infections from different clades, an enrichment of such antibodies was predicted for clade B samples. Ultimately, such large-scale analyses of antibody responses to HIV-1 infection can help guide the design of epitope-specific vaccines that are tailored to take into account the prevalence of infecting clades within a specific geographic region. Overall, the next-generation NFP technology will be an important tool for the analysis of broadly neutralizing polyclonal antibody responses against HIV-1.Computational neutralization fingerprinting, NFP, is an efficient and accurate method for predicting the epitope specificities of polyclonal antibody responses to HIV-1 infection. Here, we present next-generation NFP algorithms that substantially improve prediction accuracy for individual donors and enable serologic analysis for entire cohorts. Specifically, we developed algorithms for: (a) selection of optimized virus neutralization panels for NFP analysis, (b) estimation of NFP prediction confidence for each serum sample, and (c) identification of sera with potentially novel epitope specificities. At the individual donor level, the next-generation NFP algorithms particularly improved the ability to detect multiple epitope specificities in a sample, as confirmed both for computationally simulated polyclonal sera and for samples from HIV-infected donors. Specifically, the next-generation NFP algorithms detected multiple specificities in twice as many samples of simulated sera. Further, unlike the first-generation NFP, the new algorithms were able to detect both of the previously confirmed antibody specificities, VRC01-like and PG9-like, in donor CHAVI 0219. At the cohort level, analysis of ~150 broadly neutralizing HIV-infected donor samples suggested a potential connection between clade of infection and types of elicited epitope specificities. Most notably, while 10E8-like antibodies were observed in infections from different clades, an enrichment of such antibodies was predicted for clade B samples. Ultimately, such large-scale analyses of antibody responses to HIV-1 infection can help guide the design of epitope-specific vaccines that are tailored to take into account the prevalence of infecting clades within a specific geographic region. Overall, the next-generation NFP technology will be an important tool for the analysis of broadly neutralizing polyclonal antibody responses against HIV-1. |
| Audience | Academic |
| Author | Cortez, Valerie O’Dell, Sijy Connors, Mark Morris, Lynn Roark, Ryan S. Wang, Felicia Louder, Mark K. Binley, James M. Martin, Malcolm A. Mascola, John R. Sutton, Matthew S. Kong, Rui Abdool Karim, Salim S. Kwong, Peter D. Doria-Rose, Nicole A. Altae-Tran, Han R. Chuang, Gwo-Yu Overbaugh, Julie McKee, Krisha Bailer, Robert T. Montefiori, David C. Schmidt, Stephen D. Haynes, Barton F. Georgiev, Ivelin S. |
| AuthorAffiliation | 9 Duke University Human Vaccine Institute, Durham, NC, United States of America 12 Laboratory of Molecular Microbiology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States of America University of Zurich, SWITZERLAND 11 Center for HIV/AIDS Vaccine Immunology-Immunogen Discovery at Duke University, Durham, NC, United States of America 6 Department of Epidemiology, Columbia University, New York, NY, United States of America 3 Program in Molecular and Cellular Biology, University of Washington, Seattle, WA, United States of America 13 Department of Surgery, Duke University School of Medicine, Durham, NC, United States of America 5 Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa 17 Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States of America 14 University of the Witwatersrand, Johannesburg, South Africa 8 HI |
| AuthorAffiliation_xml | – name: 14 University of the Witwatersrand, Johannesburg, South Africa – name: 13 Department of Surgery, Duke University School of Medicine, Durham, NC, United States of America – name: 17 Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States of America – name: 12 Laboratory of Molecular Microbiology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States of America – name: 5 Centre for the AIDS Programme of Research in South Africa (CAPRISA), University of KwaZulu-Natal, Durban, South Africa – name: 6 Department of Epidemiology, Columbia University, New York, NY, United States of America – name: 2 Human Biology Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America – name: 10 Departments of Medicine and Immunology, Duke University School of Medicine, Durham, NC, United States of America – name: 8 HIV-Specific Immunity Section, National Institutes of Health, Bethesda, MD, United States of America – name: 11 Center for HIV/AIDS Vaccine Immunology-Immunogen Discovery at Duke University, Durham, NC, United States of America – name: 1 Vaccine Research Center, National Institutes of Health, Bethesda, MD, United States of America – name: 16 Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, United States of America – name: 4 Vanderbilt Vaccine Center, Vanderbilt University, Nashville, TN, United States of America – name: 3 Program in Molecular and Cellular Biology, University of Washington, Seattle, WA, United States of America – name: 9 Duke University Human Vaccine Institute, Durham, NC, United States of America – name: University of Zurich, SWITZERLAND – name: 15 Center for HIV and STIs, National Institute for Communicable Diseases, Johannesburg, South Africa – name: 7 San Diego Biomedical Research Institute, San Diego, CA, United States of America |
| Author_xml | – sequence: 1 givenname: Nicole A. surname: Doria-Rose fullname: Doria-Rose, Nicole A. – sequence: 2 givenname: Han R. surname: Altae-Tran fullname: Altae-Tran, Han R. – sequence: 3 givenname: Ryan S. surname: Roark fullname: Roark, Ryan S. – sequence: 4 givenname: Stephen D. surname: Schmidt fullname: Schmidt, Stephen D. – sequence: 5 givenname: Matthew S. surname: Sutton fullname: Sutton, Matthew S. – sequence: 6 givenname: Mark K. surname: Louder fullname: Louder, Mark K. – sequence: 7 givenname: Gwo-Yu surname: Chuang fullname: Chuang, Gwo-Yu – sequence: 8 givenname: Robert T. surname: Bailer fullname: Bailer, Robert T. – sequence: 9 givenname: Valerie orcidid: 0000-0002-1267-5596 surname: Cortez fullname: Cortez, Valerie – sequence: 10 givenname: Rui orcidid: 0000-0003-1779-5885 surname: Kong fullname: Kong, Rui – sequence: 11 givenname: Krisha surname: McKee fullname: McKee, Krisha – sequence: 12 givenname: Sijy surname: O’Dell fullname: O’Dell, Sijy – sequence: 13 givenname: Felicia surname: Wang fullname: Wang, Felicia – sequence: 14 givenname: Salim S. orcidid: 0000-0002-4986-2133 surname: Abdool Karim fullname: Abdool Karim, Salim S. – sequence: 15 givenname: James M. surname: Binley fullname: Binley, James M. – sequence: 16 givenname: Mark surname: Connors fullname: Connors, Mark – sequence: 17 givenname: Barton F. surname: Haynes fullname: Haynes, Barton F. – sequence: 18 givenname: Malcolm A. orcidid: 0000-0002-6845-9905 surname: Martin fullname: Martin, Malcolm A. – sequence: 19 givenname: David C. surname: Montefiori fullname: Montefiori, David C. – sequence: 20 givenname: Lynn surname: Morris fullname: Morris, Lynn – sequence: 21 givenname: Julie surname: Overbaugh fullname: Overbaugh, Julie – sequence: 22 givenname: Peter D. surname: Kwong fullname: Kwong, Peter D. – sequence: 23 givenname: John R. surname: Mascola fullname: Mascola, John R. – sequence: 24 givenname: Ivelin S. surname: Georgiev fullname: Georgiev, Ivelin S. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28052137$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | COPYRIGHT 2017 Public Library of Science 2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Doria-Rose NA, Altae-Tran HR, Roark RS, Schmidt SD, Sutton MS, Louder MK, et al. (2017) Mapping Polyclonal HIV-1 Antibody Responses via Next-Generation Neutralization Fingerprinting. PLoS Pathog 13(1): e1006148. doi:10.1371/journal.ppat.1006148 2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Doria-Rose NA, Altae-Tran HR, Roark RS, Schmidt SD, Sutton MS, Louder MK, et al. (2017) Mapping Polyclonal HIV-1 Antibody Responses via Next-Generation Neutralization Fingerprinting. PLoS Pathog 13(1): e1006148. doi:10.1371/journal.ppat.1006148 |
| Copyright_xml | – notice: COPYRIGHT 2017 Public Library of Science – notice: 2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Doria-Rose NA, Altae-Tran HR, Roark RS, Schmidt SD, Sutton MS, Louder MK, et al. (2017) Mapping Polyclonal HIV-1 Antibody Responses via Next-Generation Neutralization Fingerprinting. PLoS Pathog 13(1): e1006148. doi:10.1371/journal.ppat.1006148 – notice: 2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Doria-Rose NA, Altae-Tran HR, Roark RS, Schmidt SD, Sutton MS, Louder MK, et al. (2017) Mapping Polyclonal HIV-1 Antibody Responses via Next-Generation Neutralization Fingerprinting. PLoS Pathog 13(1): e1006148. doi:10.1371/journal.ppat.1006148 |
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| Notes | new_version ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Conceived and designed the experiments: ISG NADR HRAT.Performed the experiments: NADR HRAT RSR SDS MSS RTB GYC MKL KM SO FW ISG.Analyzed the data: NADR HRAT RSR SDS MSS RTB GYC MKL KM SO FW PDK JRM ISG.Contributed reagents/materials/analysis tools: VC RK MKL SSAK MC BFH MAM DCM LM JO.Wrote the paper: NADR HRAT JRM LM JMB ISG. The authors have declared that no competing interests exist. |
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| Snippet | Computational neutralization fingerprinting, NFP, is an efficient and accurate method for predicting the epitope specificities of polyclonal antibody responses... Computational neutralization fingerprinting, NFP, is an efficient and accurate method for predicting the epitope specificities of polyclonal antibody... |
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| SubjectTerms | Acquired immune deficiency syndrome AIDS AIDS Vaccines - immunology Algorithms Analysis Antibodies Antibody Formation Antibody Specificity Antigenic determinants Biology Biology and Life Sciences Cohort Studies Colleges & universities Computer Simulation Epitope Mapping - methods Epitopes - immunology Experiments Health aspects HIV HIV Antibodies - immunology HIV Infections - immunology HIV Infections - virology HIV-1 - immunology Human immunodeficiency virus Humans Immunology Infections Lentivirus Medical research Medicine and Health Sciences Neutralization Neutralization Tests Physical Sciences Physiological aspects Polyclonal antibodies Research and Analysis Methods Retroviridae Vaccines |
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| Title | Mapping Polyclonal HIV-1 Antibody Responses via Next-Generation Neutralization Fingerprinting |
| URI | https://www.ncbi.nlm.nih.gov/pubmed/28052137 https://www.proquest.com/docview/1869527986 https://www.proquest.com/docview/1855787697 https://www.proquest.com/docview/1872839731 https://pubmed.ncbi.nlm.nih.gov/PMC5241146 https://doaj.org/article/8a81c72949514c31829e9f7bf5c3f8b9 http://dx.doi.org/10.1371/journal.ppat.1006148 |
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