دورية أكاديمية
Utilizing Computational Machine Learning Tools to Understand Immunogenic Breadth in the Context of a CD8 T-Cell Mediated HIV Response.
| العنوان: | Utilizing Computational Machine Learning Tools to Understand Immunogenic Breadth in the Context of a CD8 T-Cell Mediated HIV Response. |
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| المؤلفون: | McGowan E; IAVI Human Immunology Laboratory, Imperial College, London, United Kingdom., Rosenthal R; Cancer Evolution and Genome Instability Laboratory, Francis Crick Institute, London, United Kingdom., Fiore-Gartland A; Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, United States., Macharia G; IAVI Human Immunology Laboratory, Imperial College, London, United Kingdom., Balinda S; Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Health and Tropical Medicine (LSHTM), Uganda Research Unit, Entebbe, Uganda., Kapaata A; Medical Research Council/Uganda Virus Research Institute (MRC/UVRI) and London School of Health and Tropical Medicine (LSHTM), Uganda Research Unit, Entebbe, Uganda., Umviligihozo G; Project San Francisco (PSF) Center for Family Health Research (CFHR), Kigali, Rwanda., Muok E; Project San Francisco (PSF) Center for Family Health Research (CFHR), Kigali, Rwanda., Dalel J; IAVI Human Immunology Laboratory, Imperial College, London, United Kingdom., Streatfield CL; IAVI Human Immunology Laboratory, Imperial College, London, United Kingdom., Coutinho H; IAVI Human Immunology Laboratory, Imperial College, London, United Kingdom., Dilernia D; Emory Vaccine Center, Emory University, Atlanta, GA, United States., Monaco DC; Emory Vaccine Center, Emory University, Atlanta, GA, United States., Morrison D; Bitefirst, South Walsham, United Kingdom., Yue L; Emory Vaccine Center, Emory University, Atlanta, GA, United States., Hunter E; Emory Vaccine Center, Emory University, Atlanta, GA, United States., Nielsen M; Department of Health Technology, Technical University of Denmark, Lyngby, Denmark., Gilmour J; IAVI Human Immunology Laboratory, Imperial College, London, United Kingdom., Hare J; IAVI, New York, NY, United States. |
| المصدر: | Frontiers in immunology [Front Immunol] 2021 Feb 18; Vol. 12, pp. 609884. Date of Electronic Publication: 2021 Feb 18 (Print Publication: 2021). |
| نوع المنشور: | Journal Article; Research Support, U.S. Gov't, Non-P.H.S. |
| اللغة: | English |
| بيانات الدورية: | Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101560960 Publication Model: eCollection Cited Medium: Internet ISSN: 1664-3224 (Electronic) Linking ISSN: 16643224 NLM ISO Abbreviation: Front Immunol Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: [Lausanne : Frontiers Research Foundation] |
| مواضيع طبية MeSH: | Machine Learning*, CD8-Positive T-Lymphocytes/*immunology , HIV/*immunology , HIV Infections/*immunology , HIV Infections/*virology , Host-Pathogen Interactions/*immunology, Antigens, Viral/genetics ; Antigens, Viral/immunology ; Epitopes, T-Lymphocyte/immunology ; Genetic Variation ; Genome, Viral ; HLA Antigens/immunology ; Humans ; Peptides/immunology ; Proteome ; Viral Proteins |
| مستخلص: | Predictive models are becoming more and more commonplace as tools for candidate antigen discovery to meet the challenges of enabling epitope mapping of cohorts with diverse HLA properties. Here we build on the concept of using two key parameters, diversity metric of the HLA profile of individuals within a population and consideration of sequence diversity in the context of an individual's CD8 T-cell immune repertoire to assess the HIV proteome for defined regions of immunogenicity. Using this approach, analysis of HLA adaptation and functional immunogenicity data enabled the identification of regions within the proteome that offer significant conservation, HLA recognition within a population, low prevalence of HLA adaptation and demonstrated immunogenicity. We believe this unique and novel approach to vaccine design as a supplement to vitro functional assays, offers a bespoke pipeline for expedited and rational CD8 T-cell vaccine design for HIV and potentially other pathogens with the potential for both global and local coverage. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2021 McGowan, Rosenthal, Fiore-Gartland, Macharia, Balinda, Kapaata, Umviligihozo, Muok, Dalel, Streatfield, Coutinho, Dilernia, Monaco, Morrison, Yue, Hunter, Nielsen, Gilmour and Hare.) |
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| معلومات مُعتمدة: | P51 OD011132 United States OD NIH HHS |
| فهرسة مساهمة: | Keywords: CD8 T-cells; HIV; T-cell epitopes; machine learning; vaccines |
| المشرفين على المادة: | 0 (Antigens, Viral) 0 (Epitopes, T-Lymphocyte) 0 (HLA Antigens) 0 (Peptides) 0 (Proteome) 0 (Viral Proteins) |
| تواريخ الأحداث: | Date Created: 20210308 Date Completed: 20210630 Latest Revision: 20240331 |
| رمز التحديث: | 20240331 |
| مُعرف محوري في PubMed: | PMC7930081 |
| DOI: | 10.3389/fimmu.2021.609884 |
| PMID: | 33679745 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1664-3224 |
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| DOI: | 10.3389/fimmu.2021.609884 |