A Paratope-Enhanced Method to Determine Breadth and Depth TCR Clonal Metrics of the Private Human T-Cell Vaccine Response after SARS-CoV-2 Vaccination
Quantitative metrics for vaccine-induced T-cell responses are an important need for developing correlates of protection and their use in vaccine-based medical management and population health. Molecular TCR analysis is an appealing strategy but currently requires a targeted methodology involving com...
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Veröffentlicht in: | International journal of molecular sciences 2023-09, Vol.24 (18), p.14223 |
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creator | Li, Dalin Pavlovitch-Bedzyk, Ana Jimena Ebinger, Joseph E Khan, Abdul Hamideh, Mohamed Merchant, Akil Figueiredo, Jane C Cheng, Susan Davis, Mark M McGovern, Dermot P B Melmed, Gil Y Xu, Alexander M Braun, Jonathan |
description | Quantitative metrics for vaccine-induced T-cell responses are an important need for developing correlates of protection and their use in vaccine-based medical management and population health. Molecular TCR analysis is an appealing strategy but currently requires a targeted methodology involving complex integration of ex vivo data (antigen-specific functional T-cell cytokine responses and TCR molecular responses) that uncover only public antigen-specific metrics. Here, we describe an untargeted private TCR method that measures breadth and depth metrics of the T-cell response to vaccine challenge using a simple pre- and post-vaccine subject sampling, TCR immunoseq analysis, and a bioinformatic approach using self-organizing maps and GLIPH2. Among 515 subjects undergoing SARS-CoV-2 mRNA vaccination, we found that breadth and depth metrics were moderately correlated between the targeted public TCR response and untargeted private TCR response methods. The untargeted private TCR method was sufficiently sensitive to distinguish subgroups of potential clinical significance also observed using public TCR methods (the reduced T-cell vaccine response with age and the paradoxically elevated T-cell vaccine response of patients on anti-TNF immunotherapy). These observations suggest the promise of this untargeted private TCR method to produce T-cell vaccine-response metrics in an antigen-agnostic and individual-autonomous context. |
doi_str_mv | 10.3390/ijms241814223 |
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Molecular TCR analysis is an appealing strategy but currently requires a targeted methodology involving complex integration of ex vivo data (antigen-specific functional T-cell cytokine responses and TCR molecular responses) that uncover only public antigen-specific metrics. Here, we describe an untargeted private TCR method that measures breadth and depth metrics of the T-cell response to vaccine challenge using a simple pre- and post-vaccine subject sampling, TCR immunoseq analysis, and a bioinformatic approach using self-organizing maps and GLIPH2. Among 515 subjects undergoing SARS-CoV-2 mRNA vaccination, we found that breadth and depth metrics were moderately correlated between the targeted public TCR response and untargeted private TCR response methods. The untargeted private TCR method was sufficiently sensitive to distinguish subgroups of potential clinical significance also observed using public TCR methods (the reduced T-cell vaccine response with age and the paradoxically elevated T-cell vaccine response of patients on anti-TNF immunotherapy). These observations suggest the promise of this untargeted private TCR method to produce T-cell vaccine-response metrics in an antigen-agnostic and individual-autonomous context.</description><identifier>ISSN: 1422-0067</identifier><identifier>ISSN: 1661-6596</identifier><identifier>EISSN: 1422-0067</identifier><identifier>DOI: 10.3390/ijms241814223</identifier><identifier>PMID: 37762524</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Algorithms ; Antibodies ; Antigens ; Binding Sites, Antibody ; CD8-Positive T-Lymphocytes ; Cloning ; COVID-19 - prevention & control ; COVID-19 Vaccines ; Cytokines ; Disease transmission ; Health aspects ; Humans ; Methods ; Pandemics ; Peptides ; Pharmaceutical industry ; Receptors, Antigen, T-Cell - genetics ; RNA ; SARS-CoV-2 ; Severe acute respiratory syndrome coronavirus 2 ; T cells ; Tumor Necrosis Factor Inhibitors ; Vaccination</subject><ispartof>International journal of molecular sciences, 2023-09, Vol.24 (18), p.14223</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 by the authors. 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c439t-274fe6050d2b011c2bb837bf7113d00984c075ea48a319d9d4069764b624a713</cites><orcidid>0000-0002-4977-036X ; 0000-0002-0587-1572 ; 0000-0003-4877-4358 ; 0000-0001-7472-822X ; 0000-0002-2591-5165 ; 0000-0003-1646-2974</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10531868/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10531868/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,725,778,782,883,27911,27912,53778,53780</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37762524$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Dalin</creatorcontrib><creatorcontrib>Pavlovitch-Bedzyk, Ana Jimena</creatorcontrib><creatorcontrib>Ebinger, Joseph E</creatorcontrib><creatorcontrib>Khan, Abdul</creatorcontrib><creatorcontrib>Hamideh, Mohamed</creatorcontrib><creatorcontrib>Merchant, Akil</creatorcontrib><creatorcontrib>Figueiredo, Jane C</creatorcontrib><creatorcontrib>Cheng, Susan</creatorcontrib><creatorcontrib>Davis, Mark M</creatorcontrib><creatorcontrib>McGovern, Dermot P B</creatorcontrib><creatorcontrib>Melmed, Gil Y</creatorcontrib><creatorcontrib>Xu, Alexander M</creatorcontrib><creatorcontrib>Braun, Jonathan</creatorcontrib><title>A Paratope-Enhanced Method to Determine Breadth and Depth TCR Clonal Metrics of the Private Human T-Cell Vaccine Response after SARS-CoV-2 Vaccination</title><title>International journal of molecular sciences</title><addtitle>Int J Mol Sci</addtitle><description>Quantitative metrics for vaccine-induced T-cell responses are an important need for developing correlates of protection and their use in vaccine-based medical management and population health. Molecular TCR analysis is an appealing strategy but currently requires a targeted methodology involving complex integration of ex vivo data (antigen-specific functional T-cell cytokine responses and TCR molecular responses) that uncover only public antigen-specific metrics. Here, we describe an untargeted private TCR method that measures breadth and depth metrics of the T-cell response to vaccine challenge using a simple pre- and post-vaccine subject sampling, TCR immunoseq analysis, and a bioinformatic approach using self-organizing maps and GLIPH2. Among 515 subjects undergoing SARS-CoV-2 mRNA vaccination, we found that breadth and depth metrics were moderately correlated between the targeted public TCR response and untargeted private TCR response methods. The untargeted private TCR method was sufficiently sensitive to distinguish subgroups of potential clinical significance also observed using public TCR methods (the reduced T-cell vaccine response with age and the paradoxically elevated T-cell vaccine response of patients on anti-TNF immunotherapy). These observations suggest the promise of this untargeted private TCR method to produce T-cell vaccine-response metrics in an antigen-agnostic and individual-autonomous context.</description><subject>Algorithms</subject><subject>Antibodies</subject><subject>Antigens</subject><subject>Binding Sites, Antibody</subject><subject>CD8-Positive T-Lymphocytes</subject><subject>Cloning</subject><subject>COVID-19 - prevention & control</subject><subject>COVID-19 Vaccines</subject><subject>Cytokines</subject><subject>Disease transmission</subject><subject>Health aspects</subject><subject>Humans</subject><subject>Methods</subject><subject>Pandemics</subject><subject>Peptides</subject><subject>Pharmaceutical industry</subject><subject>Receptors, Antigen, T-Cell - genetics</subject><subject>RNA</subject><subject>SARS-CoV-2</subject><subject>Severe acute respiratory syndrome coronavirus 2</subject><subject>T cells</subject><subject>Tumor Necrosis Factor Inhibitors</subject><subject>Vaccination</subject><issn>1422-0067</issn><issn>1661-6596</issn><issn>1422-0067</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNptkk1v1DAQhiMEoh9w5IosceGS4q_EyQktoVCkIqrtqlfLcSaNV4m92E4l_gi_t466lC5CPsxo_MxrzfjNsjcEnzFW4w9mOwXKSUU4pexZdrzEHONSPH-SH2UnIWwxpowW9cvsiAlR0oLy4-z3Cl0pr6LbQX5uB2U1dOg7xMF1KDr0GSL4yVhAnzyoLg5I2S5VdynbNGvUjM6qcWnwRgfkehQHQFfe3KkI6GKelEWbvIFxRDdK60VoDWHnbACk-qSNrlfr67xxNzndEyoaZ19lL3o1Bni9j6fZ5sv5prnIL398_dasLnPNWR1zKngPJS5wR1tMiKZtWzHR9oIQ1mFcV1xjUYDilWKk7uqO47IWJW9LypUg7DT7-CC7m9sJOg02ejXKnTeT8r-kU0Ye3lgzyFt3JwkuGKnKKim83yt493OGEOVkgk7zKgtuDpJWAhNW1RVN6Lt_0K2bfVrfQpU1qwoq2F_qVo0gje1delgvonIlRPpnIphI1Nl_qHQ6mIx2FnqT6gcN-UOD9i4ED_3jkATLxUjywEiJf_t0M4_0H-ewe484wTA</recordid><startdate>20230918</startdate><enddate>20230918</enddate><creator>Li, Dalin</creator><creator>Pavlovitch-Bedzyk, Ana Jimena</creator><creator>Ebinger, Joseph E</creator><creator>Khan, Abdul</creator><creator>Hamideh, Mohamed</creator><creator>Merchant, Akil</creator><creator>Figueiredo, Jane C</creator><creator>Cheng, Susan</creator><creator>Davis, Mark M</creator><creator>McGovern, Dermot P B</creator><creator>Melmed, Gil Y</creator><creator>Xu, Alexander M</creator><creator>Braun, Jonathan</creator><general>MDPI AG</general><general>MDPI</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>COVID</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-4977-036X</orcidid><orcidid>https://orcid.org/0000-0002-0587-1572</orcidid><orcidid>https://orcid.org/0000-0003-4877-4358</orcidid><orcidid>https://orcid.org/0000-0001-7472-822X</orcidid><orcidid>https://orcid.org/0000-0002-2591-5165</orcidid><orcidid>https://orcid.org/0000-0003-1646-2974</orcidid></search><sort><creationdate>20230918</creationdate><title>A Paratope-Enhanced Method to Determine Breadth and Depth TCR Clonal Metrics of the Private Human T-Cell Vaccine Response after SARS-CoV-2 Vaccination</title><author>Li, Dalin ; Pavlovitch-Bedzyk, Ana Jimena ; Ebinger, Joseph E ; Khan, Abdul ; Hamideh, Mohamed ; Merchant, Akil ; Figueiredo, Jane C ; Cheng, Susan ; Davis, Mark M ; McGovern, Dermot P B ; Melmed, Gil Y ; Xu, Alexander M ; Braun, Jonathan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c439t-274fe6050d2b011c2bb837bf7113d00984c075ea48a319d9d4069764b624a713</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Antibodies</topic><topic>Antigens</topic><topic>Binding Sites, Antibody</topic><topic>CD8-Positive T-Lymphocytes</topic><topic>Cloning</topic><topic>COVID-19 - 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Molecular TCR analysis is an appealing strategy but currently requires a targeted methodology involving complex integration of ex vivo data (antigen-specific functional T-cell cytokine responses and TCR molecular responses) that uncover only public antigen-specific metrics. Here, we describe an untargeted private TCR method that measures breadth and depth metrics of the T-cell response to vaccine challenge using a simple pre- and post-vaccine subject sampling, TCR immunoseq analysis, and a bioinformatic approach using self-organizing maps and GLIPH2. Among 515 subjects undergoing SARS-CoV-2 mRNA vaccination, we found that breadth and depth metrics were moderately correlated between the targeted public TCR response and untargeted private TCR response methods. The untargeted private TCR method was sufficiently sensitive to distinguish subgroups of potential clinical significance also observed using public TCR methods (the reduced T-cell vaccine response with age and the paradoxically elevated T-cell vaccine response of patients on anti-TNF immunotherapy). These observations suggest the promise of this untargeted private TCR method to produce T-cell vaccine-response metrics in an antigen-agnostic and individual-autonomous context.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>37762524</pmid><doi>10.3390/ijms241814223</doi><orcidid>https://orcid.org/0000-0002-4977-036X</orcidid><orcidid>https://orcid.org/0000-0002-0587-1572</orcidid><orcidid>https://orcid.org/0000-0003-4877-4358</orcidid><orcidid>https://orcid.org/0000-0001-7472-822X</orcidid><orcidid>https://orcid.org/0000-0002-2591-5165</orcidid><orcidid>https://orcid.org/0000-0003-1646-2974</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Antibodies Antigens Binding Sites, Antibody CD8-Positive T-Lymphocytes Cloning COVID-19 - prevention & control COVID-19 Vaccines Cytokines Disease transmission Health aspects Humans Methods Pandemics Peptides Pharmaceutical industry Receptors, Antigen, T-Cell - genetics RNA SARS-CoV-2 Severe acute respiratory syndrome coronavirus 2 T cells Tumor Necrosis Factor Inhibitors Vaccination |
title | A Paratope-Enhanced Method to Determine Breadth and Depth TCR Clonal Metrics of the Private Human T-Cell Vaccine Response after SARS-CoV-2 Vaccination |
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